Development of Marginal Abatement Cost Curves for the Waste Sector

Development of Marginal Abatement 

Cost Curves for the Waste Sector 

Report for 

Committee on Climate Change 

Defra and 

Environment Agency 

Authors: 

Dr Dominic Hogg 

Adam Baddeley 

Ann Ballinger 

Tim Elliott 

December 2008

Report for: 

CCC, Defra and the Environment Agency 

Prepared by: 

Adam Baddeley (Project Manager), Ann Ballinger, Tim Elliott and Dominic Hogg 

Approved by: 

Dominic Hogg 

8 th December 2008 

(Project Director) 

Contact Details 

Eunomia Research & Consulting Ltd 

62 Queen Square 

Bristol 

BS1 4JZ 

United Kingdom 

Tel: +44 (0)117 9450100 

Fax: +44 (0)8717 142942 

Web: www.eunomia.co.uk 

Acknowledgements 

Our thanks to Jenny Byars and Michael Thompson (CCC), Gemma Mills and David 

Mottershead (Defra), and Matt Georges (Environment Agency) for their support in developing 

this report, and for comments on earlier Drafts of this Report. The report also benefited from 

helpful comments from ERM at a peer review meeting. 

Disclaimer 

Eunomia Research & Consulting has taken due care in the preparation of this report to 

ensure that all facts and analysis presented are as accurate as possible within the scope of 

the project. However no guarantee is provided in respect of the information presented, and 

Eunomia Research & Consulting is not responsible for decisions or actions taken on the basis 

of the content of this report. 

Development of MACCs for the Waste Sector


EXECUTIVE SUMMARY 

i 

The Committee on Climate Change (CCC) is tasked with advising Government on the setting of 

carbon budgets in forthcoming years. To inform this budget setting process, the CCC is 

reviewing the potential for abatement of greenhouse gases (GHGs) from the perspective of 

the cost effectiveness of different measures. 

The central aim of this work has been the development of a large number of marginal 

abatement cost curves (MACCs) as an aid to understanding the potential for cost effective 

abatement of GHGs emitted from the waste management sector. 

The basic approach for developing the MACCs was as follows: 

‣ A baseline for the management of waste in the UK was developed, the aim being to 

reflect the effects of firm and funded policies; 

‣ A range of materials within the municipal, commercial, industrial and construction 

waste streams were identified as being of interest to the study. It is important to note 

that this list was not comprehensive, but that the materials were chosen on the basis 

that they were anticipated to hold significant potential for abatement; 

‣ A range of different treatments, applicable to these materials, were considered for 

analysis. Again, it is important to recognise that this list was not comprehensive, but 

focused on relatively well characterised treatments of the materials chosen for 

analysis; 

‣ From these treatments, a range of ‘switches’ were identified, involving the movement 

of material from one management to another; 

‣ These switches were characterised in terms of their cost per tonne of waste switching 

from the one management method to another, and the level of abatement achieved 

per tonne of waste switched; 

‣ The ratio of these two effectively gave the unit cost of abatement for the different 

management switches. This measure is the basis for the construction of a MACC, the 

logic of which is that abatement options (in this case, our management switches) are 

chosen in ascending order, with the best options considered to be those with the 

lowest unit cost of abatement; 

‣ The other key element in the construction of MACCs is the overall potential for 

abatement. In this case, this is given by the product of the potential tonnage of waste 

which could be switched from the one management to the other and the level of 

abatement achieved per tonne of waste undergoing this switch. This relies upon an 

assessment of the feasible potential, over and above the firm and funded baseline, for 

waste to be switched in this way. 

It is important to note that the emissions ‘savings’ presented in this report include both 

emissions falling within and outside the EU-ETS. To the (currently limited) extent that figures 

include savings from sectors which are included under the EU-ETS, this would not generate 

additional abatement in terms of the UK’s carbon account.

ii 

Range of MACCs Developed 

A range of MACCs were developed reflecting: 

1. Varying scope of emissions considered. These are as follows: 

a. GHG emissions considered only insofar as they affect the UK’s inventory as 

reported to the IPCC, referred to as ‘IPCC’. In this case, any increase or 

reduction in GHG emissions overseas as a result of UK waste management are 

ignored; 

b. All emissions considered, irrespective of the location of their generation, 

referred to as ‘Global’; 

c. A scenario in which the MACC was generated assuming abatement potential as 

for the IPCC above but with the cost effectiveness measure calculated using 

the abatement achieved per tonne of waste under the Global scenario. This 

was referred to as the Hybrid scope; 

2. Different cost metrics. Three approaches were used: 

a. A social cost metric; 

b. A private cost metric, recognising that whilst the CCC is to advise on the level of 

carbon budgets from a societal perspective, a ‘private MACC’ provides an 

important indicator in terms of how rational agents may act to the costs they 

face in the market place. 

c. A hybrid cost metric, which recognises capital costs as a resource cost (this is a 

hybrid approach which is contrary to conventional government appraisal); and 

3. Different feasible potentials for the switches achieved. These were 

a. High feasible potential represents the amount of abatement that could be 

achieved if everyone who could adopt this measure did so. The uptake rate of 

feasible technology will be bounded by practical constraints but could reach up 

to 100% if no such practical constraints existed. If we were to think about this 

in a policy context this scenario would represent a very ambitious policy 

environment that was extremely effective at delivering the identified 

abatement measures. 

b. Central feasible potential represents the amount of abatement that could be 

achieved if there was an ambitious & effective policy environment in place to 

deliver these abatement measures. 

c. Low feasible potential represents the amount of abatement that could be 

achieved if there was a moderately ambitious and somewhat effective policy 

environment 

Whilst the modelling outcomes presented in this report are for the UK as a whole, it is 

important to recognise that the model has been set up to allow for the calculation of levels of 

abatement, relative to respective baselines, for each of England, Wales, Scotland and 

Northern Ireland. 

The modelling also focused on key target years for the CCC, 2012, 2017 and 2022. However, 

interpolation allows MACCs to be generated for any year. In addition, in the work, CCC asked 

that a cut-off be drawn at the £200 per tonne of CO 2 equivalent abated level. Switches which 

fell short of this criterion were not considered in the development of MACCs. 


Key Conclusions 

Development of MACCs for the Waste Sector 

iii 

It is not possible to discuss all the MACCs in a meaningful way in an Executive Summary. 

However, some high level points are worth making in this Summary: 

‣ As expected, abatement potential in later years is greater than in earlier years; 

‣ As expected, abatement potential under the high feasible potential is greater than 

under the central, which is greater than under the low feasible potential. This is for 

obvious reasons; 

‣ There is generally more ‘below the line’ (i.e. negative cost) abatement under the 

private cost metric. This is due to the fact that the private cost metric makes landfill 

more expensive (owing to the inclusion of landfill tax), and though the cost of capital is 

greater in the private cost metric than under the social cost metric, the increase in 

costs implied by this change is not as great as the real (2006 terms) level of the tax in 

future (which is assumed to remain constant in real terms once it reaches £48 per 

tonne); 

‣ There is generally greater abatement under the Global accounting methodology than 

under the IPCC accounting approach. This is because of the inclusion of avoided 

emissions associated with the recycling of dry recyclables, both in recycling options, 

and in treatment options where materials are recovered from residual waste (i.e. all 

the non-landfill residual waste treatments); 

‣ The total abatement under the IPCC scope runs in the following order: 

Social > Hybrid > Private. 

Under the Global scope, the ordering runs differently 

Hybrid > Social > Private 

The reasons for this are not entirely straightforward to explain, and relate to the 

sequential logic which the approach to developing MACCs implies; 

‣ The levels of abatement under the different cost metrics for the year 2022 under the 

IPCC Scope and for the high feasible potential are shown in Figure E - 1. These show 

that the levels of abatement achieved vary – as expected – depending upon the cost 

metric used. In general, changing the cost metric alters the ranking of measures in 

terms of their cost effectiveness since the assumptions concerning the cost of capital, 

and the inclusion of taxes / subsidies or not affects the costs of the different switches 

in quite different ways. The shifts in ranking, in turn, imply that measures dealing with 

a given material (e.g. residual waste, or food waste) appear earlier or later in the 

sequence of measures ‘picked up’ in order of cost-effectiveness, and since these 

perform differently in terms of the abatement achieved per tonne of waste ‘switched’, 

then the total abatement achieved will vary depending upon whether measures which 

have a high level of abatement per tonne of waste switched fall earlier or later in the 

rankings; 

‣ As Figure E - 1 also shows, the bulk of the abatement under the IPCC scope comes 

from MBT, AD and IVC/Windrow. 

With regard to the final bullet, it should be noted that the abatement being proposed is largely 

dependent upon measures which are known to be capable of being implemented. In some 

cases – for example, the use of MBT residues on land – there may be questions regarding 

how widely this material could be safely used. On the other hand, where this option is ranked 

highly, it effectively depresses the level of abatement that is achieved because the 

abatement per tonne of waste switched is relatively low compared with other MBT options. 

Other questions might relate to the potential for using solid recovered fuels in cement kilns or

iv 

power stations, not least when one considers that the abatement potential relates to the 

quantity of material which could be used in this way over and above the level of use assumed 

in a firm and funded baseline. The issues here are not so much technical, but more related to 

the nature of policy and regulation. 

Figure E - 1: Abatement of Major Treatment Switches for Each Cost Metric 

14 

12 

10 

Abatement CO2e, Mt 

8 

6 

Other 

IVC / Windrow Abatement 

AD Abatement 

MBT Abatement 

4 

2 

0 

Private Hybrid Social 

Cost Metric 

Finally, it is worth stating that a key ‘result’ of this work has been the development of ‘the 

model’. The model provides the user with the capability to change specific variables and to 

conduct analysis under different scenarios, scopes (of abatement) and cost metrics. In the 

type of analysis undertaken, however, one cannot avoid choosing point estimates, and we 

have sought to do this using publicly available sources where possible. In addition, the 

various metrics used to characterise costs can be considered a form of sensitivity analysis, 

though quite clearly, these metrics do not necessarily imply a flexing of all parameters one 

might wish to see flexed in a fully-fledged sensitivity analysis. 


Key Assumptions and Their Influence 

v 

A key question might be, ‘to what extent can one be sure that this level of abatement can be 

achieved’ There are a number of issues which one can raise in seeking to answer this 

question: 

‣ The abatement levels are measured relative to a ‘firm and funded’ baseline, which has 

been developed with a horizon out to 2022. Given the rapid (at least in comparison to 

historic rates) rate of change in the waste management sector, it almost goes without 

saying that the development of a ‘firm and funded baseline’ comes with a health 

warning. Since all abatement is measured relative to this, then one must understand 

that the abatement the modelling suggests might be achieved is heavily reliant on this 

being an accurate prediction of the future. Whilst care has been taken to develop this 

in a sensible way, one cannot guarantee the validity of the assumptions made; 

‣ The analysis of costs of waste treatment facilities – particularly looking forward - is not 

straightforward. We have derived point estimates for facilities based on published data 

sources for each of the cost metrics. However, there are a number of factors which are 

likely to affect costs, including (amongst others) the nature of the delivery mechanism 

used to procure facilities (in the public sector), the approach to financing in the private 

sector, and the rate of construction price inflation. The choice of the weighted average 

cost of capital also has a significant impact on more capital intense facilities under the 

private and hybrid cost metrics; 

‣ The carbon (or GHG) intensity of the marginal energy source – be it transport fuel, 

electricity or heat – which one assumes is being displaced through the generation of 

energy has a significant bearing upon the analysis. In the baseline MACC modelling, 

these figures were based around the firm and funded baselines for energy generation. 

However, to the extent that the work of CCC is expected to lead to ‘decarbonising’ of 

transport and energy emissions over time, so the net GHG performance of all 

technologies which generate energy in some form would be expected to decline. The 

net benefits from the switches being considered here would also decline as a result. 

‣ As regards recycling, partly to highlight the difference between the IPCC and Global 

scopes (in terms of coverage of emissions), we assumed all materials collected for 

recycling were sent abroad, and that recycling effectively displaced primary material 

that was being imported. The impact on UK inventories will depend, in practice on the 

degree to which materials being recycled a) are displacing domestic or imported 

primary materials; and b) are being recycled within the UK or overseas; 

‣ Some sensitivity analysis was carried out with regard to landfill gas captures. We were 

asked to use a figure of 75% for lifetime gas captures, but if this assumption is varied, 

then the abatement achieved changes significantly (see Figure E-2), especially at lower 

rates of capture. It should be noted that this graph exhibits discontinuities precisely 

because of the sequential logic followed in the MACC modelling; 


Figure E - 2: Total Abatement Achieved vs. Landfill Gas Capture Rate (IPCC Social, Central 

feasibility, 2022). 

vi 

25 

20 

Total Abatement CO2 equ, Mt 

15 

10 

5 

0 

20% 30% 40% 50% 60% 70% 80% 90% 100% 

Landfill Gas Capture Rate 

‣ The ‘maximum achievable levels’ under the high feasible potential scenario have an 

impact upon what can or cannot be achieved. We have been quite bullish in this 

regard, but recognising that 2022 is some way ahead in time, and that the high 

feasible scenario is intended to reflect a policy supportive of the changes being 

considered; and 

‣ Finally, the list of treatment switches considered, though large, was far from 

exhaustive. There are a range of technologies which do not feature in this work. This 

relates to a priori assumptions that increases in abatement levels would not be great 

for specific materials (materials were excluded) and a decision to choose only those 

technologies for which cost data was (notwithstanding the points made previously) 

tolerably good (technologies were excluded). It seems reasonable to assume that 

some novel technologies will prove their worth in years to come, and so might 

contribute additional abatement should that be the case. It goes without saying, 

however, that their cost will be at least as important as their abatement performance 

in this regard. 

Future Abatement Potential Relative to 1990 Levels 

Analysis was carried out to estimate the level of abatement possible, relative to 1990 levels, 

in the waste sector (including emissions from facilities other than landfills). The aim was to 

understand what the focus of attention might be if electricity generation and transport are 

substantially decarbonised. Table E-1 shows figures for the GHGs for the years 2005, 2022 

and for 2050, with the 2050 figures shown with and without replacement of plastics in the 

residual waste stream by non-fossil materials. The reported figures for 1990 are shown for 

comparison, and to enable the potential reduction, relative to 1990 levels, to be calculated. 


Table E-1: GHG Emissions in Specified Year (‘000 tonnes CO 2 equ), and Reduction Potential 

(%, relative to 1990 levels) 

vii 

Year 

Landfill 

Emissions Only 

Process 

Emissions from 

Facilities 

All Waste Sector 

Emissions 

% Reduction 

Relative to 

1990 

1990 49,754 1,576 51,330 0% 

2005 39,320 491 39,811 22% 

2022 10,021 14,727 24,748 52% 

2050 – with no 

replacement of 

fossil based 

plastics 

2050 – with a 

complete switch 

of fossil to nonfossil 

based 

plastics 

1,852 14,727 16,597 68% 

1,852 2,540 4,393 91% 

Source: 1990 and 2005 data from Defra data 

http://www.defra.gov.uk/environment/statistics/globatmos/download/xls/gatb04.xls 

This analysis shows that: 

‣ Between 1990 and 2005, the emissions from landfilling have declined by around 20% 

reflecting both the movement of waste away from landfill and the improvement in 

landfill gas captures at more modern landfill sites; 

‣ By 2022, the emissions from landfilling show a further significant drop. Even without 

changes in waste flows to different treatment facilities, these fall further between 

2022 and 2050, principally because the emissions associated with materials being 

landfilled in earlier years are dropping off exponentially with time. The significance of 

removing untreated waste from landfill is clear; 

‣ At the same time, whilst the data for 1990 and 2005 in respect of other GHGs from 

other facilities seem to be less reliable, these increase considerably between 1990 

and 2022 (even assuming zero fossil CO 2 emissions for fuel used in processes). It 

should be noted that the drop in these emissions between 1990 and 2005 is as 

recorded in Defra data, and the methodology for deriving these figures is not 

comparable with the approach used in this report, on which the data for later years are 

based; 

‣ These remain constant to 2050 reflecting constant mass flows, as long as the fossil 

carbon content of fuels remains broadly constant; 

‣ If fossil carbon in residual waste is eliminated, then 2050 process emissions decline 

significantly. Indeed, the major contribution to reducing process emissions comes from 

eliminating fossil carbon from the residual waste stream; 

‣ Reflecting the above discussion, the GHGs from processes are greater than GHG 

emissions from landfill in 2050; 


viii 

‣ Although the MBT: stabilisation – output to land recovery process is managing more 

waste than the combined thermal treatment options, the total emissions (mainly CH 4 

based) are much less, at around 1/12 overall; 

‣ Without the elimination of fossil carbon from the residual waste stream, then the 

reduction (relative to 1990 levels) in emissions from the waste sector (writ large) 

reaches 52% by 2022 and 68% by 2050; and 

‣ If fossil carbon is completely eliminated from the residual waste stream, then the 


reaches 91% by 2050. 

In the context of this analysis, it should be noted that an assumption of zero growth has been 

used. 

The Sequential Logic of MACC Modelling 

One specific issue has concerned us throughout the MACC modelling project. It relates to the 

sequential logic which MACC modelling implies. Our switches include a number of measures 

for moving specific materials – notably residual waste and food waste – to and from a range 

of different treatments. MACC curves may be used to determine which measures should be 

undertaken by drawing a limit, in terms of costs per tonne of GHG abated, at a given point on 

the y-axis. Our experience suggests that if one takes the view that one treats food waste or 

residual waste in the most cost-effective (in terms of abatement) way, this does not secure 

the highest level of abatement. 

For example, consider two switches, A and B, both relating to treating residual waste in a 

different way. 

Suppose for A, the cost per tonne of abatement is £X, and for B, the cost per tonne of 

abatement is £X+£20. Suppose A delivers Y tonnes of abatement per tonne of waste 

‘switched’, but B delivers 2Y tonnes of abatement per tonne of waste switched. If A delivers 

lower abatement per tonne of waste switched (but is more cost effective because the cost of 

the switch, per tonne of waste, is lower), then the total level of abatement will be half what 

might have been achieved if switch B had been ‘chosen’. Yet whether A or B is chosen might 

ultimately depend upon where one draws the cut-off in terms of the cost society is willing to 

bear in terms of cost per tonne of abatement. Arguably, unless one knows where this cut-off 

is drawn, one ought to follow the sequential logic in drawing the MACC curve. 

In principle, therefore, the MACC curve representation does not maximise the level of 

abatement achievable through all measures below a given cut-off point. To secure this 

maximum level of abatement – particularly in circumstances where more than one of the 

measures being considered apply to the same material – a more considered look at the 

measures would be required. 

Future Research 

As regards further research, the following suggestions are offered: 

‣ The firm and funded baseline should be updated on the basis of emerging 

understanding of the effects of the higher rate of landfill tax escalator; 

‣ There is a need to review a more comprehensive range of possible abatement 

measures. This list should seek to cover waste prevention measures given that 

legitimate policy measures could have an effect in this regard. Time led to our 

truncating this list earlier than we would have liked. Ideally, the project would have 


ix 

followed a two-step approach in which all switches were assessed for GHG 

performance before then looking at their cost; 

‣ Some closer considerations should be given as to the likely differences in cost at 

facilities procured through PPP-type arrangements by the public sector, and merchant 

plant developed by the private sector (since this itself might suggest a way towards 

improving the cost effectiveness of many switches). Costs might also consider the 

effect of construction price inflation; 

‣ Ongoing work at the Environment Agency may highlight ways of addressing emissions 

from landfills related to waste already deposited. To the extent that these measures 

prove cost-effective, they should be incorporated into the MACC modelling; 

‣ As stated above many of the switches are cost negative on a private basis. Although 

the GHG emissions do not capture all environmental impacts, the negative cost 

switches that have the potential to deliver abatement deserve closer investigation to 

seek to understand why the uptake of these switches is not already higher than it is. 

Analysis of the wider policy options for effectively unlocking the associated abatement 

ought to be given serious consideration; 

‣ Improved understanding of the link from energy prices to primary materials prices 

would be welcome. Our impression is that this link exists (recent evidence is at least 

suggestive of this), and an understanding of this would allow modelling of changes in 

energy prices to be reflected in the prices of / revenues from materials; 

‣ The landfill model used for the purpose of assessing baseline emissions is, we 

understand, undergoing an overhaul, which is to be welcomed; 

‣ The number of variables which drive the analysis is very large indeed. Sensitivity 

analysis conducted around both costs per tonne of waste switched, and the 

abatement per tonne of waste switched, could clearly have a bearing upon where a 

given switch is ranked in the overall list of treatment switches, particularly where the 

numerator and the denominator (the cost, and the level of abatement, respectively) 

are both small. Some sensitivity analysis around the cost-effectiveness of different 

measures might be useful in future work; 

‣ The non-GHG environmental effects of the switches examined have been discussed 

briefly in the main report. It is by no means certain that the switches being examined 

are unequivocally positive in this regard. Where air pollution externalities are 

concerned, GHGs account for the majority of the impacts of landfilling. The same is not 

true for other treatments. An analysis of the non-GHG externalities associated with the 

switches could further assist in identifying the most desirable switches, taking into 

account a broader environmental perspective. 


x 

Contents 

1.0 Background and Objectives ................................................................................................ 1 

2.0 Scope of the Analysis .......................................................................................................... 3 

2.1 Waste Types and Sub-sectors ............................................................................................4 

2.2 Potential for Variation in ‘Nature’ of Costs........................................................................5 

2.3 Potential for Variation in ‘Scope’ of Emissions .................................................................6 

2.4 ‘Feasible’ Potentials............................................................................................................6 

2.5 ‘Tradable’ and ‘Non-Tradable’ Emissions..........................................................................7 

2.6 Renewable Energy Generation...........................................................................................7 

2.7 Ancillary Costs .....................................................................................................................7 

2.8 Non-fossil Carbon................................................................................................................8 

2.9 Waste Growth ......................................................................................................................8 

2.10 Waste Prevention.............................................................................................................9 

3.0 Methodological Framework............................................................................................... 10 

3.1 Model Overview................................................................................................................ 10 

3.2 Switches between Waste Management Methods ......................................................... 11 

3.2.1 ‘Additionality’ and Interdependency of Switches.................................................... 12 

3.3 Switches Not Considered................................................................................................. 13 

3.3.1 Measures at Existing Landfills ................................................................................. 13 

3.4 Characterising Switches for Modelling ........................................................................... 14 

3.4.1 The Magnitude of the Switch.................................................................................... 15 

3.4.2 ‘Shapes’ for the Switches ......................................................................................... 16 

4.0 Baseline Development ...................................................................................................... 20 

4.1 ‘Firm and Funded’ Policy ................................................................................................. 20 

4.2 Waste Growth ................................................................................................................... 20 

4.3 Baseline for Municipal Solid Wastes .............................................................................. 21 

4.3.1 Waste Composition ................................................................................................... 21 

4.3.2 Recycling and Composting Rates ............................................................................ 25 

4.3.3 Firm and Funded’ Policies for MSW......................................................................... 28 

4.3.4 Material-specific Projections for Carbon Budget Years.......................................... 32 

4.3.5 Baseline for Total UK MSW....................................................................................... 34 

4.4 Commercial and Industrial Wastes................................................................................. 36 

4.4.1 C&I Waste Composition ............................................................................................ 36 

4.4.2 ‘Firm and Funded’ Policies ....................................................................................... 36 


xi 

4.4.3 Projections to Target Years........................................................................................38 

4.4.4 Baselines for UK C&I Wastes ....................................................................................41 

4.5 Construction, Demolition and Excavation (CDE).............................................................44 

4.5.1 Waste Composition ....................................................................................................44 

4.5.2 Latest Position............................................................................................................44 

4.5.3 ‘Firm and Funded’ Policies ........................................................................................45 

4.5.4 Baseline for UK CDE Wastes .....................................................................................46 

5.0 Approach to Emissions Modelling..................................................................................... 47 

5.1 Composition of Residual Waste.......................................................................................47 

5.2 Transport ...........................................................................................................................50 

5.3 Literature Sources for Modelling Treatment Methods ...................................................50 

5.4 Generic Assumptions for Treatment Technologies.........................................................51 

5.4.1 Avoided CO 2 Emissions from Energy Generation.....................................................51 

5.4.2 Emissions Avoided Through Recycling .....................................................................52 

5.5 Treatment of Residual Waste...........................................................................................53 

5.5.1 Landfill ........................................................................................................................53 

5.5.2 Incineration.................................................................................................................60 

5.5.3 MBT .............................................................................................................................65 

5.5.4 Energy Generation from Wood..................................................................................74 

5.6 Dry Recycling .....................................................................................................................75 

5.6.1 Impacts Considered under the IPCC Scope .............................................................77 

5.6.2 Impacts Considered Under the Global Scope ..........................................................77 

5.7 Treatment of Source-Separated Organic Material..........................................................87 

5.7.1 AD of Source-Separated Food Wastes......................................................................88 

5.7.2 Land Spreading ..........................................................................................................90 

5.7.3 In Vessel Composting – Mixed Green and Food Waste...........................................90 

5.7.4 Open-air Windrow Composting of Green Waste.......................................................94 

6.0 Modelling of Costs ............................................................................................................. 96 

6.1 Cost Metrics.......................................................................................................................96 

6.2 Why Not Gate Fees .........................................................................................................96 

6.3 The Nature of Switches ....................................................................................................98 

6.4 Key Variables.....................................................................................................................98 

6.4.1 Centrally Determined .................................................................................................98 

6.4.2 Waste Specific Assumptions .................................................................................. 101 

6.5 Process Modelling.......................................................................................................... 103 

6.5.1 General Approach ................................................................................................... 104 


xii 

6.5.2 Collection Systems .................................................................................................. 105 

6.5.3 Open Air Windrow Composting............................................................................... 109 

6.5.4 In-vessel Composting (IVC) ..................................................................................... 110 

6.5.5 Anaerobic Digestion ................................................................................................ 112 

6.5.6 Landfill ..................................................................................................................... 121 

6.5.7 Incineration.............................................................................................................. 122 

6.5.8 Mechanical Biological Treatment (MBT) ............................................................... 128 

6.5.9 Wood Combustion ................................................................................................... 133 

7.0 Presentation and Discussion of Key Results..................................................................134 

7.1 Emissions per Tonne of Waste Switched ..................................................................... 134 

7.2 Costs per Tonne of Waste Switched ............................................................................. 139 

7.3 Putting it All Together – Average Costs per Tonne of GHG Abatement ...................... 145 

7.3.1 An Example – the IPCC Social MAC Curve, Central Feasible Potential ............... 145 

7.3.2 MAC Curves.............................................................................................................. 153 

7.3.3 Variation in Abatement with Relation to Cost Metrics.......................................... 163 

7.4 Landfill Gas Capture Rate ............................................................................................. 167 

7.5 Levels of Abatement Achievable................................................................................... 168 

7.6 Potential Implications for Policy.................................................................................... 168 

7.7 Ancillary Costs and Benefits.......................................................................................... 169 

8.0 Concluding Remarks .......................................................................................................171 

8.1 IPCC or Global............................................................................................................... 173 

8.2 A 2050 Vision............................................................................................................... 174 

8.2.1 What Levels of Emissions Reduction (relative to 1990 levels) Might be 

Achievable........................................................................................................................... 176 

A.1.0 References ...................................................................................................................179 

A.2.0 Assumptions for Baseline Development .....................................................................184 

A.2.1 Compositions (MSW) .................................................................................................. 184 

A.2.1.1 England Composition........................................................................................... 184 

A.2.1.2 Scotland Composition.......................................................................................... 185 

A.2.1.3 Wales Composition .............................................................................................. 185 

A.2.1.4 Northern Ireland Composition............................................................................. 187 

A.2.2 Recycling Rates (MSW)............................................................................................... 188 

A.2.2.1 England Recycling Rates..................................................................................... 188 

A.2.2.2 Scotland Recycling Rates.................................................................................... 190 

A.2.2.3 Wales Recycling Rates ........................................................................................ 193 

A.2.2.4 Northern Ireland Recycling Rates....................................................................... 195 


xiii 

A.2.2.5 Time Profiles for MSW from 2008 to 2022 ....................................................... 197 

A.2.3 C&I ............................................................................................................................... 197 

A.2.3.1 Composition of C&I ‘Other Low Abatement Potential’ ...................................... 197 

A.2.3.2 Time Profiles for C&I waste from 2008 to 2022 ............................................... 198 

A.3.0 List of Switches Considered.........................................................................................199 


1 

1.0 Background and Objectives 

The Committee on Climate Change (CCC) has been tasked with advising Government on 

carbon ‘budgets’ required to meet the targets proposed in the UK Climate Change Bill. This 

advice includes guidance concerning the degree to which carbon budgets should be met by 

reductions in domestic emissions, or purchasing of credits for certified emissions reductions, 

such as EU Allowances (EUAs) achieved overseas. The first task for the CCC is to provide 

advice on the first three carbon ‘budgets’ by December 2008. 

In this context, marginal abatement cost curves (MACCs) for specific sectors can, either when 

used separately, or when used to construct an economy-wide marginal abatement cost curve, 

inform the extent of abatement of greenhouse gases (GHGs) which might be achieved at a 

given cost of abatement. Furthermore, ongoing discussions around the Shadow Price of 

Carbon might be used to inform whether particular levels of abatement, and the associated 

costs, were deemed to be excessive or not from the societal point of view. 

On behalf of Defra, CCC and the Environment Agency, Eunomia was appointed to undertake 

this study to construct MACCs to measure the potential for GHG abatement within the waste 

sector. These can be used to inform the wider work of the CCC, as well as Defra and the 

Environment Agency. This report considers the potential scope for reducing greenhouse gas 

emissions from the waste sector. The report does not focus only on carbon-based GHGs 

since CCC has been asked to consider non-CO 2 GHGs in setting so-called carbon budgets. We 

consider emissions and abatement potential of all greenhouse gases expressed as carbon 

dioxide (CO 2 ) equivalents. This information is combined with abatement cost information over 

the specified time horizons to derive a graphical representation of the cost of mitigation in the 

form of a MACC. 

An illustrative example of a MACC is shown in Figure 1-1. A MACC ranks abatement measures 

in order of decreasing cost effectiveness moving from left to right. Measures to the left of the 

curve are the most cost-effective measures, and sometimes these lie below the x-axis (as the 

unit costs of abatement are negative). Measures to the right of the curve, and above the x- 

axis, illustrate the unit costs to society from implementation of abatement measures. The 

MACC permits technologies and measures to be compared at the margin (i.e. the steps of the 

curve). The width of each provides information on the volume of abatement potential 

associated with a measure. The graph provides a tool for cost-effectiveness analysis. 

The basis for measuring the potential for abatement in this study is the potential for 

reductions over and above those which are estimated to occur in a baseline scenario, which 

is intended to represent the emissions profile resulting from the implementation of ‘firm and 

funded’ policy initiatives. Because of the nature of the waste management sector, and 

because a range of technologies may be used to deal with any given material, the approach 

undertaken has been to model ‘switches’ in management method. In other words, we have 

modelled the costs and the abatement potential of material being moved from one (baseline) 

waste management method to another. We refer to these as ‘switches’ in the report. 

It is anticipated that the model produced by Eunomia can be used by Defra, CCC and the 

Environment Agency to generate further MACCs according to future developments in the 

waste and energy markets. CCC and Defra wish to use the waste MACC model in informing 

their evidence base on carbon budgets, which will constitute legally binding caps on the level 

of emissions measured in the UK inventory. This requires a view on what level of emissions 

can be achieved after cost effective abatements are achieved, and in particular how this 

compares to current government projections of emissions from waste.

This project provides the MAC curve for that task. It does not go so far as to generate year on 

year ‘MACC-on’ emissions projections for the waste sector, although CCC and Defra are 

provided with the capacity to do that. 

Figure 1-1: Illustrative Example of a Marginal Abatement Cost Curve 

2 

£ /tCO 2e 

1,300 

650 

600 

550 

500 

450 

300 

150 

100 

50 

0 

- 50 

0 

20 

40 

60 

80 

100 

120 

140 

- 100 

MtCO2e 

- 150 

- 250 

As such this report does not present results in the form of ‘waste-related’ budgets, but rather 

aims to be a comprehensive detailed technical report covering all the assumptions used to 

ensure full transparency in the construction of the MAC curve. It is recognised that some of 

the assumptions are likely to be the subject of debate given the uncertainty that prevails in 

the assessment of how the baseline picture may evolve over time, and the assessment of 

future costs and performance of the options being assessed. It is also recognised that the list 

of switches examined is not comprehensive, and does not cover many technologies, novel 

and otherwise, which may be, or are becoming, available in the market place. 


2.0 Scope of the Analysis 

3 

The Climate Change Bill (‘the Bill’) is intended to drive change and reduce emissions in the 

whole of the UK, and therefore this study has been developed to incorporate analysis of 

England and all devolved administrations. In this context, although the scope of the modelling 

extends out to 2022 only, qualitative commentary is included out to the year 2050 to reflect 

the goals of the Bill. Particular attention is given to the emissions profile of the waste sector in 

the carbon ‘budget’ years 2012, 2017, 2022. 

The waste sector is a small, but not insignificant, contributor to UK emissions as currently 

accounted for in national inventories. The GHG methane (CH 4 ), which is far more potent as a 

GHG than carbon dioxide, is generated by biodegradable wastes degrading under anaerobic 

conditions. 1 Under the Guidelines for National Greenhouse Gas Inventories, from the 

Intergovernmental Panel on Climate Change, the majority of GHGs from the waste sector are 

associated with the emissions of the uncaptured portion of methane which is emitted from 

landfills. However, it should be noted that under the IPCC Guidelines, other emissions of 

relevance to the waste sector are reported in different parts of the inventory. For example: 

1. Where incinerators generate no useful energy, the emissions are reported under the 

Waste source category; 

2. Biological treatment processes also lead to emissions of carbon dioxide, methane and 

nitrous oxide. The IPCC asks for these to be reported under the Waste sector (though it 

is unclear whether this has been done in UK Inventories); 

3. Where incinerators generate energy, their emissions are reported under the ‘Energy’ 

sector emissions. Although all GHG emissions should be reported (including CO 2 from 

non-fossil sources in waste), the emissions of greatest relevance are taken to be the 

CO 2 emissions from fossil sources in waste, and the nitrous oxide emissions 

associated with combustion, as well as any methane resulting from incomplete 

combustion; 

4. Where stationary combustion of waste occurs in association with the generation of 

energy, these are reported under the relevant sector under the Energy sector. Similar 

considerations apply (in terms of the way GHGs are reported) as for incineration. 

Activities of relevance here are, for example, the combustion of solid recovered fuels 

or wood wastes in power stations etc.; 

5. The ‘Industrial Processes and Product Use’ (IPPU) part of IPCC Guidance covers 

industries such as the cement industry, and the production of most materials and 

products. These all are of relevance to the waste sector insofar as their emissions are 

affected by the degree to which they make use of secondary materials. There is, as the 

authors of the IPPU Guidance note, some difficulty in allocating emissions to the IPPU 

or Energy Sectors: 2 

1 The relative weight, in terms of radiative forcing, given to emissions of methane as opposed to carbon dioxide 

is a function of various factors, not least of which is the time horizon one takes into consideration. However, 

typically, methane is cited as being 21 times more potent as a GHG than carbon dioxide. This is the current 

assumption of CCC. 

2 IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 3: Industrial Processes 

and Product Use, http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol3.html 


4 

Allocating emissions from the use of fossil fuel between the Energy and IPPU 

Sectors can be complex. The feedstock and reductant uses of fuels frequently 

produce gases that may be combusted to provide energy for the process. 

Equally part of the feedstock may be combusted directly for heat. This can lead 

to uncertainty and ambiguity in reporting. 

The above shows that although the ‘Waste Sector’ is frequently seen as a relatively small 

contributor to GHG inventories, in part, this reflects the nature of the (somewhat complex) 

accounting process. It should also be noted that as the waste and energy / fuel sectors 

deepen the extent of their integration, and as the number of more novel processes dealing 

with waste and materials continues to grow, so the approach to assigning waste-related 

emissions to one or other category is likely to become more, not less, complex. 

Finally, it has to be noted that national inventories are based very much on emissions 

associated with domestic activity. They do not, for example, attempt to account for the 

embodied energy in imported and exported raw materials, goods and services. From a waste 

perspective, this raises important questions as to whether the existing approach to reporting 

inventories can really motivate the most desirable response from ‘the waste sector’. In a 

country which imports many raw materials, and increasingly exports material for recycling 

abroad, the net effect of the activities of which these imports and exports are a part are not 

adequately reported in existing inventories. This means that there may be a distinction 

between: 

1. What is best from the perspective of the reporting inventories for the IPCC reporting; 

and 

2. What is best for the global climate. 

From an economic perspective, one might be less concerned by this distinction if, in an ideal 

world, all emissions were subject to a global cap, or if all emissions were taxed at a suitable 

rate. In the absence of such a world (as at present), however, the distinction between what is 

reported under IPCC inventories, and what is the impact of different approaches to waste 

management on the climate, remains an important distinction, and is of particular relevance 

where the use of primary and secondary materials is discussed. 

2.1 Waste Types and Sub-sectors 

Whilst all forms of waste management generate an emissions profile, the extent of this is 

highly variable according to the type of wastes managed. Inert wastes, from mining and 

quarrying, for example, do not degrade in landfills, nor can they be used to generate energy. 

The sub-sector therefore has more limited abatement potential and has therefore been 

excluded from our analysis. Similarly, the sewage management sub-sector is considered to be 

outside the scope of analysis, as although such wastes are highly biodegradable, and 

although the material is covered by the IPCC Reporting Guidelines, the intention has been to 

focus on solid wastes. 

Analysis of the abatement potential offered by agricultural wastes falls within the remit of a 

related study being undertaken to develop MACCs for the whole agricultural sector, and has 

thus been omitted from this analysis. 3 

3 This was agreed with the authors of the related study, the Scottish Agricultural College, who have provided 

analysis of the abatement potential of biodegradable wastes, such as slurry. Following liaison with Defra, it was 


5 

The focus of the analysis is therefore upon sub-sectors, and types of waste within those subsectors, 

which were believed to offer, a priori, both cost effective potential for abatement, and 

for which existing data can be used to provide meaningful outcomes. The wastes included 

within the scope of the study are therefore: 

‣ Municipal solid wastes (MSW); 

‣ Commercial and industrial (C&I) wastes; and 

‣ Construction, demolition and excavation (CDE) wastes. 4 

As discussed in more detail in Section 4.0, development of new baseline data was outside the 

scope of the study, whilst the inclusion of ‘novel’ waste management technologies has been 

limited to practices for which relevant cost data can be determined in the context of current 

commercial and regulatory environments. These are important limitations to the accuracy of 

the study. 

The study is intended to be forward looking. At the same time, we have been asked for costs 

which can be expressed in different ways. This is awkward enough in cases where costs are 

relatively well established. It is far more difficult where they are not, or where, as in the case 

of many novel and patented processes, the publicly available information suggests a very 

wide range of costs. In principle, one might suggest that this could be handled through 

sensitivity analysis. No such sensitivity analysis has been conducted in this study, but we 

have attempted to draw upon published estimates of cost to ensure transparency in the 

analysis. 

2.2 Potential for Variation in ‘Nature’ of Costs 

There are differences in the analysis between the situation in which only social costs are 

concerned (excluding the effect of taxes, support mechanisms, etc.), and those where private 

costs are concerned (including the costs of taxes, and benefits from sales of ROCs). In line 

with the request from CCC, we have provided the facility to generate MACCs according to 

three different cost metrics: 

1. A social metric; 

2. A hybrid metric, which recognises capital costs as a resource cost (this is a hybrid 

approach which is contrary to conventional government appraisal); and 

3. A private metric, recognising that whilst the CCC is to advise on the level of carbon 

budgets from a societal perspective, a ‘private MACC’ provides an important indicator 

in terms of how rational agents may act to the costs they face in the market place. 

These metrics are those under consideration by CCC. Greater detail, including on the different 

discount rates used for each metric, is provided in Section 6.1. 

also determined that there is insufficient evidence relating to current management practices for nonbiodegradable 

agricultural wastes, such as plastics, which were therefore also excluded from the analysis. 

4 The inclusion of CDE wastes is limited to paper/card, plastic, metals and wood. As detailed in Section 4.5, the 

vast majority of CDE wastes are inert, which offer low abatement potential and are thus excluded from our 

analysis 


2.3 Potential for Variation in ‘Scope’ of Emissions 


6 

The CCC is advising on, and the government will be setting, carbon budgets which are based 

on UK CO 2 (or all, or a subset of, GHGs if the Bill is amended) emissions, thus creating the 

need for a MAC based upon domestic emissions / the IPCC accounting approach. However, 

from a waste perspective, if one only takes domestic emissions into account when forming 

waste policy, one may not end up with the optimal result in terms of global emissions. This is 

due to the fact that the emissions savings from recycling certain materials accrue largely from 

the avoided extraction of raw materials overseas, and these international emissions savings 

would not appear in a domestic MACC. Therefore, recycling certain materials would not 

appear as cost-effective as they would if global emissions were taken into account. So as to 

capture the differences implied by the two approaches, MACCs have been developed using 

both the accounting convention used to report budgets to the IPCC (‘domestic’ emissions), 

and using ‘global’ emissions (i.e. including changes in GHG emissions in other countries 

which result from changes in UK-based behaviour). 

In addition, a hybrid MACC has been developed. The rationale for the hybrid MACC is 

essentially to capture only the domestic emissions reduction potential, but to include global 

impacts in the cost effectiveness metric so that ‘switches’ are ordered in such a way that will 

result in the most cost-effective reductions from a global perspective being selected. 

To summarise, the three different ‘scopes’ of MACC, in terms of GHG abatement, are as 

follows: 

1. Domestic: international emissions and emissions savings are ignored; 

2. Global: international emissions and emissions savings are included; and 

3. Hybrid – this is essentially a hybrid of the two. The reported abatement for each switch 

excludes international emissions and savings. However, the cost per unit of abatement 

is calculated using the ‘global’ emissions figures. Thus, emissions savings are as for 

the Domestic MACC and costs per unit of abatement are priced at the levels 

calculated as in the Global MACC (as defined in 2 above), hence the hybrid nature of 

the MACCs. 

The MACCs presented in Section 7.0 reflect these variations in scope, along with related 

discussion of the impacts of such variations. 

2.4 ‘Feasible’ Potentials 

The Project Brief uses what is described as an ‘official IPCC definition’ of ‘maximum technical 

potential’. This is: 

"the amount by which it is possible to reduce GHG emissions by 

implementing a technology or practice that has already been 

demonstrated. There is no specific reference to costs here, only to 

'practical constraints', although implicit economic considerations are 

taken into account in some cases." 

The CCC, Defra and the Environment Agency have requested that consideration be given to 

different feasible potentials reflecting the view that the extent to which mitigation measures 

are adopted depends on the specifics of the measure and the policy framework. MAC curves 

can be constructed to reflect abatement potentials in terms of these different levels of 

adoption. This analysis distinguishes between three potential abatement scenarios, which 

vary with the diffusion rates of technology and different levels of performance, and will 

depend on the nature of the abatement measures considered. These have been defined as 

follows:

7 

High feasible potential represents the amount of abatement that could be achieved if 

everyone who could adopt this measure did so. The uptake rate of feasible technology 

will be bounded by practical constraints but could reach up to 100% if no such 

practical constraints existed. If we were to think about this in a policy context this 

scenario would represent a very ambitious policy environment that was extremely 

effective at delivering the identified abatement measures. 

Central feasible potential represents the amount of abatement that could be achieved 

if there was an ambitious & effective policy environment in place to deliver these 

abatement measures. 

Low feasible potential represents the amount of abatement that could be achieved if 

there was a moderately ambitious and somewhat effective policy environment 

These definitions partly reflect a model based around diffusion of technology. As discussed in 

further detail in Section 3.0, not all switches in the waste management context are 

characterised by such diffusion. We have, therefore, interpreted the feasible potentials in a 

slightly more open manner to reflect differing levels of performance, depending upon the 

nature of the switches being considered. 

2.5 ‘Tradable’ and ‘Non-Tradable’ Emissions 

To inform the CCC on the proportion of abatement which might be traded within the EU 

Emissions Trading Scheme, a measure has been included which quantifies all emissions 

which might originate from sectors falling under the EU-ETS. As far as domestic emissions are 

concerned, the principle measures are those involving the generation of energy from the 

biomass fraction of wastes at facilities whose prime purpose is something other than the 

treatment of waste. This might take place either at cement kilns or indirectly in the power 

industry, as obligated suppliers source generation capacity from waste facilities. 

The waste sector itself does not currently fall within the scope of the ETS. This does not mean 

that it might not do so in the future. The New Zealand Emissions Trading Scheme has been 

designed to include the waste sector, though the modalities for its inclusion are yet to be 

determined. In addition, some discussion has already taken place with regard to including 

incineration in the EU ETS, partly at the behest of the cement industry (as competing users of 

waste, or pre-treated fractions thereof, as a fuel). 

2.6 Renewable Energy Generation 

The modelling has also sought to understand, where energy is generated from waste, the 

proportion of that energy generation that is from renewable sources. This is straightforward in 

the case of biogas, but in the case of facility types, it is calculated on the basis of the 

contribution of the biomass part of waste to energy generation. 

2.7 Ancillary Costs 

The focus of this study is upon developing MACCs for GHGs only. In addition to measuring 

GHGs, however, we have provided comment on the potential implications of the changes 

proposed for the wider environment. It should be noted, however, that explicit valuation of any 

such external costs and benefits has not been undertaken. The discussion is included to 

provide some indication of whether, and to what extent, the changes being considered might 

have negative consequences in areas other than climate change, the specific area of interest 

for this study. These considerations could be brought in to extend the analysis at a later date. 


2.8 Non-fossil Carbon 

8 

In previous work of this nature, when comparing the GHG impacts of waste management 

processes, Eunomia has included emissions of non-fossil (or ‘biogenic’) carbon within our 

analysis. The logic behind this is based on the view that the atmosphere does not 

differentiate between the type of CO 2 it absorbs, and thus why should the accounting 

methodology seek to do so 

In the IPCC Guidelines, in theory, this would not be of significance if one was confident that 

the reporting of inventories under the Agriculture, Forestry and Other Land Use (AFOLU) 

Section took adequate account of all the effects of waste-related activities on changes in soil 

carbon, carbon in the existing forest stock, etc. Using, as a convention, the assumption that 

non-fossil carbon dioxide is unimportant risks, however, ignoring the matter of the potential 

significance of changing the rate of flux of carbon dioxide from non-fossil sources into the 

atmosphere. Clearly, burning biomass leads to the immediate release of carbon dioxide. 

However, composting biomass leads to the production of a compost which, on application to 

soil, increases the carbon stock, and releases the carbon over an extended period of time. 5 

Recycling paper and card may lead to additional net sequestration of carbon in the forest 

stock according to one US study, suggesting that a full accounting system for the recycling of 

biomass and of timber based products might reveal rather greater benefits than are 

suggested by many conventional life-cycle studies. 6 

Another point of relevance to this study is that conventional accounting approaches tend to 

draw boundaries around the ‘waste management sector’ such that no heed is given to the 

production of materials which ultimately become waste. When credits are assigned, as in 

most lifecycle assessment (LCA) studies, to avoided emissions of GHGs associated with 

recycling or energy generation, this can often result in net-negative emissions profiles. These 

negative profiles grow as the growth in the waste stream increases, thereby conveying the 

misleading message that producing more waste is good for climate change, which is clearly 

an unlikely scenario, whatever the fate of the material. 

We appreciate, however, that the CCC, Defra and the Environment Agency would like to follow 

the IPCC Guidelines for total emissions, and thus have included measurement of non-fossil 

carbon emissions as an information item only, which again, is not incorporated into the 

MACCs. 

2.9 Waste Growth 

We have also agreed with the Steering Group to model the forward projections on the 

assumption of a zero growth rate in the waste stream precisely so that the growth rate 

assumptions do not obscure the ‘real’ changes in abatement potential associated with 

different assumptions around growth rates. This is unlikely to be such a poor assumption 

given recent evolution in the municipal waste stream, and given the absence of high quality 

trend data for other waste streams. The model does allow for use of non-zero growth rates. 

5 See Enzo Favoino and Dominic Hogg (2008) The Potential Role of Compost in Reducing Greenhouse Gases, 

Waste Management Research, 2008; pp. 26; 61. 

6 USEPA (2002) Solid Waste Management and Greenhouse Gases: A Life-Cycle Assessment of Emissions and 

Sinks, EPA530-R-02-006, May 2002 


2.10 Waste Prevention 

9 

It is important to state clearly that waste prevention, whilst it is recognised as playing a 

potentially important role in reducing GHG emissions, does not fall within the scope of this 

study. It does not feature in the switches under consideration. It will be important, in future, to 

understand the degree to which waste prevention can contribute to constraining emissions. 

For reasons hinted at above (with regard to imports and exports), the impact (in terms of 

abatement) of waste prevention is likely to depend upon what the materials are that are being 

prevented, the degree to which these are manufactured using primary or recycled materials, 

and whether one’s perspective is purely domestic or international in nature. 

2.11 Devolved Administrations 

Whilst the modelling outcomes presented in this report are for the UK as a whole, it is 

important to recognise that the model has been set up to allow for the calculation of levels of 

abatement, relative to respective baselines, for each of England, Wales, Scotland and 

Northern Ireland. 


3.0 Methodological Framework 

10 

Much of the emissions information used in the generation of the different MACCs for this 

study has been drawn from Eunomia’s internal waste management database. The data held 

within this tool is based both on an iterative global review of publications, and ongoing direct 

communications with waste management technology and solution providers. Whilst the 

database itself has not been provided to the project sponsors, the information on costs and 

emissions derived from the tool is presented in this document. 

The scope of the task might be appreciated if one considers that, as summarised in Table 

3-1, in the analysis required by the project sponsors, 81 different Waste Sector MACCs were 

requested for the three key budget years alone. The facility to generate MACCs for intervening 

years was developed in the model, these being generated through linear interpolation. 

Results from a range of these permutations are presented and discussed in Section 7.0. 

Table 3-1: Modelled MACC permutations 

Year Nature of Costs Scope of Emissions Feasibility / Potential 

2012 Private IPCC High 

2017 Social Global Medium 

2022 Hybrid Hybrid Low 

3.1 Model Overview 

The development of a model of this nature necessitates several related strands of work. 

Figure 3-1 summarises a 5 stage process followed by Eunomia in generating the MACCs. 

Following determination of management route switches to be included within the analysis (a 

full list of which is provided in Appendix 3), the costs and emissions profiles for each of the 

switches were modelled. Depending upon the scope of the emissions under examination, and 

depending also on the cost metric being used for that model run (the ‘Scope of Emissions’ 

and ‘Nature of Costs’ shown in Section 2.0), the switches were then ranked in ascending 

order of the unit costs of GHG abatement (expressed in terms of CO 2 equivalents). 7 

7 Phases 1 to 3 occur in one spreadsheet, before this information is fed into a further spreadsheet and married 

with information on the ‘firm and funded’ baseline to provide estimations of technical or ‘feasible’ potentials. 

The MAC Curve ‘Generator’ shown in Figure 3-1 is operated through the use of the software ‘Think-Cell’, which is 

incorporated into the wider Excel model. Eunomia has provided a tutorial for members of the CCC on all 

elements of the MAC model to enable its use far beyond the timeframes of the current project. Furthermore, 

Appendix 3 provides a basic summary guide of how to use the model. 


11 

Figure 3-1: Overview of Model Development Phases 

Determination 

of management 

route switches 

(1) Costing of 

Switches 

(2) Abatement of 

Switches 

(3) Ranking of 

Switches 

Expressed in £ / tonne of waste managed 

Expressed in tonnes of CO2e / tonne of 

waste managed 

Expressed in £s / tonne CO2e abated and 

calculated according to 9 different 

methodologies 

Determination of 

baselines for all 

waste types 

(4) Estimation of 

Technical Potentials 

Based on use of ‘expert judgement’ for 

England and 3 devolved administrations. 

Expressed in both absolutes and 

percentages for low, medium and high 

potentials in 2012, 2017, 2022 

(5) MAC Curve 

Generator 

Series of rectangles, whereby: 

x axis = (2) x (4) 

y axis = (3) 

3.2 Switches between Waste Management Methods 

As indicated above, a significant amount of the focus within our analysis has been to model 

the costs and emissions profiles of a range of switches between waste management 

methods. It was not possible, under time resource constraints, to model all possible switches. 

The nature of the exercise necessitated modelling individual switches, and developing the 

capability to generate MACCs, taking place in parallel. This demanded that the switches be 

‘set’ at an early stage. With the benefit of hindsight, and with more time available, a more 

logical approach would be a two-step one in which a thorough exploration of the options for 

GHG abatement were explored before consideration was given to the MACC modelling. 

However, it was agreed at the outset that what was important was functionality in the 

modelling with refinement occurring subsequently. The absence of some ‘switches’ from the 

list considered was, therefore, considered inevitable. Several of the switches that might be 

considered relate to newer technologies and processes. These processes would, typically, be 

difficult to characterise in terms of cost (or performance) on an accurate basis. 

The nature of these switches varies in the profundity of the change in waste management 

system that they imply. For example, some merely imply the direction of waste away from one 

management route (e.g. landfill) into another (e.g. incineration). However, others imply a 

switch from one management route (e.g. landfill) to another (e.g. recycling) which may imply a 

change in collection system as well as the management of the material. These might be 

referred to as ‘treatment switches’, and ‘system switches’, respectively. The latter are far 

more difficult to model. 


12 

Where additional waste is being collected for recycling, for example, the costs of doing this 

depend on a whole host of factors, not least of which is how that additional material is being 

obtained (i.e. what combination of change in system, change in participation, change in 

capture rate, change in relative collection frequency of recycling and refuse, etc.), and the 

costs of this change relative to a given baseline. In the general case, these costs could be 

positive or negative, depending upon the assumptions one was to use concerning how the 

additional material is collected, and the nature of any counterpart changes in the collection 

system as a whole. 

This highlights a key constraint in the modelling. Waste management systems can be 

configured in a vast number of different ways. Evidently, some of these are less attractive 

than others, but even ‘good practice’ in a fairly narrowly defined area of activity can 

encompass a wide range of systems which perform well in different spatial, social and 

demographic contexts. In this context, setting ‘an average’ cost for any of the switches under 

consideration necessarily implies the exercise of judgement, as well as some considerable 

simplification. As hinted at above, it is tempting to take the view that these matters can be 

dealt with through sensitivity analysis. However, other issues worth considering in this regard 

are: 

• The already complex nature of the model and the huge number of variables which 

drive model outcomes; and 

• The fact that if there are ‘efficient’ and ‘less efficient’ ways of achieving a particular 

switch (and associated level of abatement), it makes little sense to model the ‘less 

efficient’ ways, since these would simply be inferior options in the MACC modelling 

exercise. 

This is not to downplay the desirability of such analysis, merely to reflect the fact that the 

nature of the modelling is such that one has little option other than to use point estimates 

under a given set of assumptions. 

3.2.1 ‘Additionality’ and Interdependency of Switches 

It is in the nature of MACCs that they have a sequential logic to them. In principle, the logic of 

the MACC is to maximise the abatement which is possible at the lowest cost. The things one 

does first are the things with the lowest unit costs. This sequential logic is all well and good if: 

‣ The measures are discrete and exhibit no interdependencies; or 

‣ The costs of different measures potentially affecting the same material are such that 

only one of the activities falls below what one might term a ‘cut-off’ cost (i.e. the cost 

below which it is intended that specific measures will be undertaken). 

In reality, there are a range of different measures which can be undertaken with the ability to 

affect any given material. For example, food waste could be sent for anaerobic digestion, or it 

could be composted. Residual waste could, instead of being landfilled, be treated at any one 

of a range of different MBT facilities or an incinerator, etc. 

Evidently, if a range of measures are of interest for dealing with a given waste material, but 

with differing unit costs, then the question might be raised as to how one deals with the 

possibility of switching material into one or other facility. In practice, following a sequential 

logic may diminish the opportunity for far greater abatement at a marginally higher cost from 

alternative measures. 

The following approaches, therefore, seem possible, particularly if one appreciates that 

typically, switches away from landfilling imply some upfront capital investment, so that the 


13 

issue of stranded assets is quite a real one if policy shifts to favour one approach rather than 

another: 

1. Simply maximise abatement potential from each measure in order of ascending costs, 

and seek to account for the interdependencies by ensuring that later switches do not 

seek to ‘pick up material twice’; 

2. Seek to maximise overall abatement potential below a given cut off specified in terms 

of the unit costs (i.e. costs of abating each tonne of waste) of abatement. In this 

approach, one might not maximise the potential of each measure in ascending rank, 

but where a given material could be treated through more than one measure at a cost 

below the cut-off, one seeks to maximise the amount dealt with through the measure 

giving greatest abatement per tonne of material treated. 

We have followed the former logic. However, we note that the project sponsors may wish to 

follow the latter logic once it becomes clear where the ‘cut-off’ might lie. Strictly speaking, the 

latter measure constitutes a deviation form the MACC logic, but under specific conditions, it 

might become a reasonable approach to pursue. 

The modelling of switches also allows for a ‘switch by switch’ review of how the material which 

is affected by the switch is being managed. This ensures that there is not excessive switching 

of any material from one management method to another. 

The process of analysing switches in management approach, therefore, takes into account 

both interdependencies across the measures as well as the impact on the baseline, such that 

neither abatement potential nor carbon budgets can be over- or under-estimated. 

3.3 Switches Not Considered 

As discussed above, a number of switches have not been considered which might have been. 

We would recommend some additional examination of these options in an early review of the 

modelling when more is known about costs and performance of some of the options. These 

include: 

‣ Residual waste options incorporating autoclaves / mechanical heat treatments. These 

options are now making their presence felt in the UK market, though understanding of 

their performance and cost is still developing; 

‣ Various other ‘bespoke’ variants of waste treatment, including options which deploy 

fuel cells, ethanol synthesis, etc. These are relatively unproven at this stage and costs 

are difficult to estimate; 

‣ Measures where the option was felt, a priori, to offer insufficient benefit over and 

above competing options, especially where these demanded changes in practice (such 

as piping biogas into the gas network); 

‣ Measures at existing landfills (see Section 3.3.1 below). 

There may be legitimate reasons for considering the above options in due course, and we 

recommend that this be done once cost data is more reliable. Some comments on measures 

which could be taken at existing landfills are offered below. 

3.3.1 Measures at Existing Landfills 

Some of the switches of interest, but which have not been included, are those which affect 

older landfills, or landfills which are reaching the stage at which gas collection through 

conventional approaches is becoming non-viable. These include, for example, use of ‘low 

calorific flares’ and active cover layers. 


14 

Although emissions from landfill sites have fallen by 61% since 1990, the Environment 

Agency believes that there are a number of technological and regulatory options and 

incentives that could be employed over the short term, and at relatively low cost, to further 

reduce emissions from this source. In order to play its part in helping the UK to reduce its 

GHG emissions, the Environment Agency has therefore set up an internal project to 

investigate how significant reductions from landfill sites might be achieved. 

The Environment Agency’s project is designed to improve information on the number and 

location of landfill sites – both closed and operational – that are emitting methane, and on 

the amount they are emitting. It is also examining the technological and regulatory options 

available to reduce these emissions. In tandem with this analysis, the Environment Agency is 

continuing with a number of trials designed to test approaches to emissions reduction in the 

landfill sector. 

The first of these is an audit of test data from ‘low calorific flares’ designed to burn the low 

concentrations of methane in the landfill gas emitted from old, closed sites. Although 

individual sites in this group do not emit much methane (hence the reason why it is allowed to 

escape into the atmosphere rather than being captured and burned), they are numerous and 

therefore have the potential to emit, collectively, a large amount of methane. The final results 

from this project are due to be completed over the summer of 2008, but initial findings are 

positive. Further work needs to be done, however, on issues such as improving data on the 

costs per tonne of methane abated and the policy mechanisms and incentives that might be 

required to ensure widespread take-up. 

The second piece of work involves improvements in staff training specifically on landfill gas 

engineering. In the first year of this programme, better training for Environment Agency staff 

inspecting active landfill sites led to a reduction in emissions of methane from landfill sites of 

19,022 tonnes of methane per year, or 0.8% of total UK methane emissions in 2006. This 

was achieved through visits to just 12 landfill sites. Again, further work is needed to cost 

these improvements and investigate options for continued expansion of this work. 

The Environment Agency hopes to be able to produce recommendations backed by a robust 

analysis for Government and senior decision-makers within the Agency by December 2008, 

with some initial results available by September 2008 depending on progress. 

3.4 Characterising Switches for Modelling 

The modelling of MACCs is complex because of the sequential logic which a MACC follows. 

Changing one variable, or assumption can alter the costs of one or more switches, changing 

their rankings, and so requiring a reconsideration of the movement of waste materials from 

one management method to another. Because this is complex, some approaches were taken 

to simplify the modelling to allow changes in parameters or assumptions to be 

accommodated in a more straightforward manner. One of these involved developing ‘profiles’ 

for the roll-out of specific switches over time under the high, medium and low feasible 

potentials. 

To enable the model to be functional and as transparent as possible, the estimation of ‘high’, 

‘medium’ and ‘low’ feasible potentials and how each switch changes over time was predetermined, 

according to set criteria. Although this provides a clear audit trail, however, it 

should be acknowledged that setting rigid formats will lead to some switches being 

characterised differently to how they might have been characterised should each trajectory 

have been determined on an individual manual basis. 

The deviations from the ‘ideal’ which may result from using set categories were considered to 

be acceptable in order to maintain transparency in the model, and ease of inputting data, not 


15 

least because it would be difficult to justify, on an objective basis, an alternative view as to 

how switches might be rolled out. It should be considered that for each MAC model scenario, 

as many as 130 switches might need to be considered, though in practice, 60-80 or so were 

below £200/t of abatement. 8 Given that changes in variables in the input MAC could lead to 

re-ranking of switches, and that this would in turn necessitate re-consideration of the 

switches (because the sequencing of switches – reflected in their ranking (in terms of costs) - 

matters), this approach makes changing input variables less burdensome in terms of time 

spent by the model user developing a full MAC curve. 9 

3.4.1 The Magnitude of the Switch 

In terms of understanding how much of a given material could switch from the original 

management method to the final management method, this had to be determined using 

expert judgement. The approach taken (outlined in Figure 3-2 below) was to estimate the 

likely extent of a switch in 2022 under the high feasible potential scenario. This was 

estimated as a percentage of the material still being managed through the means from which 

waste was being switched. 

Figure 3-2: Switch Category 6 – Waste Treatment Change (New Technology) 

Characterise 

Switches 

(1) Determine 

‘Profile’ 

(2) Level of 

Switch 

(3) Pace of 

Switch 

Choose one of the six shapes used to 

profile switches 

Determine extent of switch in 2022 under 

high feasible potential scenario. This sets 

the ‘upper bound’ 

Determine the pace of the switch through 

specifying the proportion of the 2022 switch 

which is achieved in a) 2017 and b) 2012 

under the high feasible potential scenario 

Model moves 

materials across 

management 

methods 

(4) Model Switches 

Material 

(5) Move to Next 

Switch 

Based on the above, the model switches 

material for a given model run (e.g. IPCC 

scope, Social cost) to give the appropriate 

management methods for 2012, 2017 and 

2022 under the low, central and high 

feasible potential scenarios 

In ascending order of unit abatement cost, 

the process is repeated 

8 It should be noted that typically, once fifty or so measures had been considered, there was no room for 

additional switching away from landfill (as all material had already been switched). 

9 In theory, it might be possible to write an algorithm that would allow the link from the ranking of measures in 

the unit MAC model to the construction of a MAC curve to be made dynamic. In practice, however, such an 

algorithm would be incredibly difficult to define such that it could account for all possible sequences in the 

switches. 


16 

A separate factor was used to estimate the fraction of the 2022 switch that would occur in 

each of the years 2017 and 2012. These factors were set on the basis of judgement, 

reflecting the pace at which treatment capacity could be implemented, or at which collection 

infrastructure could be put in place. 

On the basis of these parameters, the model calculates the switches under the low, central 

and high feasible potentials for all the target years for a given model run. This is done through 

a combination of: 

‣ the ultimate level achieved in 2022 under the high feasible potential scenario; 

‣ the rate profile implied by specifying the level of the 2022 switch achieved in 2012 

and 2017; and 

‣ the switch profile (the shapes discussed below). 

3.4.2 ‘Shapes’ for the Switches 

After the maximum technical potential for 2022 has been decided, the following stages set 

out the determination of the switch profile: 

‣ First, consider whether the extent to which waste can be switched from the one 

measure to another is dependent on ‘social factors’ (such as public participation in 

collection schemes), or whether the switch is essentially a movement of material from 

one treatment option to another (for example, part of a larger scale roll-out of residual 

infrastructure). In principle, under the former measures, the high, central and low 

feasible potentials are likely to be differentiated by the extent to which society 

responds to the scheme. The ultimate level of attainment will be different. In the latter, 

the issue is more likely to be one of the rate at which a specific switch can occur; 

‣ Second, determine whether the uptake of the change in management is likely to be 

relatively fast or relatively slow. 

The switch can then be characterised according to one of six potential profiles, which largely 

depend upon whether it might be considered to require a ‘collection-based’ change, or one 

which relies solely on switching between waste treatment methods. 

Essentially, three basic possibilities have been applied to collection based switches: 

1. Relatively low ultimate uptake of a material, with the central and low potentials failing 

to reach the high levels, and where they increase relatively slowly. In this scenario the 

central feasible potential may achieve 50% of the switch achieved by the high feasible 

potential in 2022 and the low, 20% of the switch achieved in the high feasible 

potential. This type of switch reflects materials coming from waste streams where the 

logistics are more complex, and for which the capture rate tends, even in very good 

collection systems, to be low. A good example is plastics from the municipal waste 

stream. Though some categories of dense plastics may be captured well, the 

proportion of the total that is ultimately captured has tended to be below 50% on a 

national scale. It is likely, however, that the ultimately achievable level will increase 

over time; 

2. Fast uptake of a material where, again, the medium and low do not reach the high 

potential. However, in this case, the rate achieved is increased. Thus under the central 

feasible potential scenario, the extent of the switch may reach 85% of the 2022 level 

achieved under the high potential, and the low, 50% of this same level. A good 

example here is paper and card, or glass, from the household or commercial streams. 

Here, the achievable level tends to be relatively high in many countries, so the 


17 

difference between high, medium and low potentials is deemed likely to be more 

narrow; 

3. Uptake of materials where the economic drivers (along with the practicalities of source 

separated material streams) make attaining high levels of switch (though not 100% 

levels) quite likely. Here, the technical constraints in terms of the ultimate level of 

achievement are deemed to be relatively insignificant, and the difference between 

high, medium and low potentials is reflected in the trajectory towards 2022 levels. 

For waste treatment-based switches, the extent of change is less dependent upon social 

factors. At least in principle, these switches simply entail ‘re-routing’ of material from one 

facility type to another. What constrains the extent of switching in this case is the rate at 

which a given change can, or is likely to occur. In principle, the rate is likely to be slower the 

higher is the proportion of waste being dealt with under contractual situations. This is 

reflected in how the 2022 modelling of the high technical potential scenario is modelled. In 

some cases, however, where the switch implies the roll out of a technology not yet heavily 

commercialised, we have modelled a progressive switch where the switch achieved by 2022 

does not rise to 100%. 

This approach results in the following three switch profiles: 

1. Slow roll-out of residual treatment technologies. The high potential is only met in 

2022; and 

2. Fast roll-out of residual treatment technologies. In this case there is an early plateau 

for the medium potential where it reaches the high potential by 2017. 

3. New technology, where the penetration is relatively low in 2012, rising more swiftly to 

2017 before flattening-off in 2022. 

3.4.2.1 Feasible Potential Relationships 

The graphs below are example switch profiles for each of the above 6 profiles. It is important 

to recognise that these graphics represent the level of switching as a proportion of the total 

material assumed to be switched in each of the target years. 

Figure 3-3: Switch Category 1 – Collection-based, Slow Uptake 

120% 

Feasible Potential Relationship 

Percentage of 

Switch 

100% 

80% 

60% 

40% 

20% 

0% 

2010 2012 2014 2016 2018 2020 2022 2024 

Year 

Category 

1- High 

Category 

1- Med 

Category 

1- Low 


Figure 3-4: Switch Category 2 - Collection Based, Fast Uptake 

18 


Percentage of Switch 

120% 

100% 

80% 

60% 

40% 

20% 

0% 

2010 2012 2014 2016 2018 2020 2022 2024 

Year 

Category 

2- High 

Category 

2- Med 

Category 

2- Low 

Figure 3-5: Switch Category 3 - Industrial Collection-based 



120% 

100% 

80% 

60% 

40% 

20% 

0% 

2010 2012 2014 2016 2018 2020 2022 2024 

Year 

Category 

3- High 

Category 

3- Med 

Category 

3- Low 

Figure 3-6: Switch Category 4 - Waste Treatment Change (Slow roll-out) 



120% 

100% 

80% 

60% 

40% 

20% 

0% 

2010 2012 2014 2016 2018 2020 2022 2024 

Year 

Category 

4- High 

Category 

4- Med 

Category 

4- Low 


Figure 3-7: Switch Category 5 - Waste Treatment Change (Fast roll-out) 

19 



120% 

100% 

80% 

60% 

40% 

20% 

0% 

2010 2012 2014 2016 2018 2020 2022 2024 

Year 

Category 

5- High 

Category 

5- Med 

Category 

5- Low 

Figure 3-8: Switch Category 6 – Waste Treatment Change (New Technology) 



120% 

100% 

80% 

60% 

40% 

20% 

0% 

2010 2012 2014 2016 2018 2020 2022 2024 

Year 

Category 

6- High 

Category 

6- Med 

Category 

6- Low 

It was assumed that the shape of the switch would not change if the switch ranking changed. 

Although this may not be completely accurate in reality the functionality and workability of the 

model was thought to take precedent. 


20 

4.0 Baseline Development 

4.1 ‘Firm and Funded’ Policy 

As mentioned above, the baseline for this study is intended to reflect the emissions profiles 

resulting from ‘firm and funded’ policy initiatives in England and all devolved administrations 

to 2022. To set this task in context, it should first be acknowledged that whilst current waste 

management routes are relatively well known for some waste streams, for example, MSW, our 

knowledge of management routes is rather less good for other waste streams, such as C&I 

and CDE wastes. As a result, it is very difficult to estimate outcomes based on firm and 

funded policy where we do not have accurate data on current performance. The lack of 

quality quantitative data is further exacerbated by the virtual absence of any meaningful 

characterisation of the composition of specific waste streams, with the possible exception of 

municipal waste. The quality of data clearly sets boundaries around the accuracy with which 

this study can be carried out. 

It should be noted that the ‘firm and funded’ baseline is assumed to be rather different from 

targets contained within policy documents and statements, for example, non-statutory 

recycling targets. The aim to reflect ‘firm and funded’ policy starts from the viewpoint that 

these will not automatically be met. Rather, the baseline is intended to reflect an assessment 

of the impact of policy mechanisms, such as the Landfill Allowance Trading Scheme (LATS), 

the landfill tax and the Renewables Obligation (RO) on the waste sector, from which the likely 

profiles for waste management in future can be derived. 

Clearly, there is some level of subjectivity in determining these baselines, whilst in Wales, a 

new National Waste Strategy is in the process of being drawn up, and considerable changes 

are ongoing in Scotland. Hence, what is ‘firm and funded’ today may be different to what may 

be considered ‘firm and funded’ in the not so distant future. Sections 4.2 to 4.5 therefore 

provide comprehensive explanations of how we have determined the baselines used for this 

study. 

4.2 Waste Growth 

We have assumed no growth in arisings for any of the wastes streams in the baselines. This is 

partly an assumption made for convenience, and to seek to ensure that the magnitude of 

abatement achieved was not overstated simply by overstating the rate at which the waste 

stream grows. 

Factors which are likely to affect waste growth to 2022 include: 

‣ Economic factors; 

‣ Population change; 

‣ Waste prevention or on-site management (at industrial sites); 

‣ Trends in the structure of industry and commerce in the UK, etc. 

The sum of these impacts is not straightforward to predict and the datasets which would 

allow for some forward projection of growth rates are simply not available. We have assumed 

that there will be zero growth during the period of study. 

The model does allow for users to change the growth rate over the period. However, all this 

does, from the perspective of the MAC curve, is to: 

‣ Increase baseline emissions; and 


21 

‣ Increase the magnitude of the potential savings to be generated from the activities for 

which the specific unit cost of abatement lies below an assumed cut-off value. 

Given the uncertainty over growth estimates, it was felt better to assume zero growth than to 

assume unsubstantiated higher rates of growth over the long-term which would have the 

effect of overstating the contribution which switches in waste management could make to 

reducing UK inventories / global emissions of greenhouse gases. 

4.3 Baseline for Municipal Solid Wastes 

By far the greatest quantity of data in the sector relates to MSW. Whilst in some respects, 

therefore, this renders easier the derivation of a sensible ‘firm and funded’ baseline, in other 

ways it makes the task more controversial, as it is likely that a far wider audience will have 

formed their own interpretations. It should be noted here, therefore, that every effort was 

made to agree our assumptions with key members of Waste Policy teams in England and all 

devolved administrations (DAs). As mentioned above, this was complicated by the status of 

new Strategies for Scotland and Wales being drawn up, and therefore it should be 

acknowledged that, on the advice of the CCC, our baseline for MSW is structured around the 

likely outcomes of the incumbent policy frameworks, and not around any likely new initiatives. 

For England and all DAs, the approach to calculating baselines for MSW was structured 

around the following four steps: 

‣ Determination of waste composition (see Section 4.3.1); 

‣ Assimilation of the most up-to-date recycling and composting data for translation into 

percentages of each material stream managed by each method (Section 4.3.2); 

‣ Determination of ‘firm and funded’ policy outcomes in terms of management methods 

for 2008 (current), 2012, 2017 and 2022 (Section 4.3.3); and 

‣ Modelling of recycling and composting rates for each material stream and application 

of residual treatment rates to the remaining residual stream, for each of the carbon 

budget years (Section 4.3.4). 

The final total ‘firm and funded’ policy baselines for UK MSW are then presented in Section 

4.3.5. 

Current management methods of UK MSW are diverse and could be described using many 

different terms. To simplify the modelling of our baseline, we have established clear 

categories and applied certain generic terms to treatments rather than trying to model all 

possible permutations and configurations, as is summarised in Table 4-1. 

4.3.1 Waste Composition 

Recent work by ERM on behalf of Defra was initially used as a basis for determining the 

composition of the MSW stream for England and the DAs. 10 The breakdown of the material 

stream was arranged into a framework composition to be consistent with the unit 

cost/emissions model developed for the study. The material streams that were considered to 

offer potential for cost–effective abatement are shown below in Table 4-2. It should be noted 

that the paper and card fraction was disaggregated to provide a higher level of accuracy as 

the component materials will be managed in different ways. 

10 ERM (2006) Carbon Balances and Energy Impacts of the Management of UK Wastes, Defra R&D Project WRT 

237 


22 

Table 4-1: UK Waste Management Methods 

General Management Method 

Recycling 

Process 

Materials recovery and subsequent reprocessing 

Open Air Windrow 

IVC 

IVC + scrubbers and bio-filters 

AD: with on site biogas use 

AD: compressed biogas used in vehicles 

MBT: Stabilisation, output to landfill 

Treatment 

MBT: SRF to gasification (steam turbine) 

MBT: SRF to gasification (gas engine) 

MBT: SRF to cement kiln 

MBT: SRF to dedicated thermal facility 

MBT: SRF to power station 

MBT: Stabilisation, output to land recovery 

MBT: AD – gas engine 

MBT: AD - fuel cell (MCFC) 

Incineration (electricity generation only) 

Thermal 

Incineration (CHP) 

Energy generation (dedicated boiler) 

Landfill 


Landfill of untreated waste 

Transfer 

Unrecorded 

Note: 

IVC = In Vessel Composting, AD = Anaerobic Digestion, MBT = Mechanical-Biological Treatment, SRF = Solid Recovered Fuel, MCFC = Molten 

Carbonate Fuel Cell, CHP = Combined Heat and Power 


23 

Table 4-2: Materials in the MSW Stream 

Materials 

Newsprint and Magazines 

Other Paper 

Card 

Dense Plastic 

Glass 

Targeted Materials 

Ferrous Metal 

Non-Ferrous Metal 

Waste Electrical and Electronic Equipment (WEEE) 

Wood 

Food Waste 

Green Waste 

Textiles 

Absorbent Hygiene Products 

Other Combustibles 

Non-Targeted Materials 

Fine Material 

Plastic Film 

Non-Combustibles 

Hazardous Household Waste Items (inc. batteries) 

This list of material streams was then used as a framework to marry up alternative sources of 

data for England and all DAs, as described in Sections 4.3.1.1 to 4.3.1.4. This analysis, 

however, comes with a health warning because much of the composition data is somewhat 

dated, and even at the time the data was being gathered, the basis for the analysis was not 

always as solid as one would have hoped. Hence, the results are unlikely to accurately 

represent the current situation, and only happy coincidence would lead to their being 

representative of what waste streams may look like in the future. This has knock on effects 

throughout the model. For example, depending upon whether the quantity of material in the 

waste stream is assumed to be higher or lower, the existing capture rate of a given material 

becomes lower or higher, respectively, leaving greater or lesser scope for further 

improvement in captures. 


24 

As a final point, it is worth commenting on the ambition of the task being undertaken. As far 

as one can discern, there have been no periods of fifteen to twenty years’ duration where the 

composition of household waste has remained steady. There is little reason to believe it will 

do so in future. Our certainty in the knowledge that waste composition will change, however, 

is matched only by our lack of certainty as to how it will change. 

This implies that whilst the basis for understanding waste composition today is already shaky, 

one’s confidence diminishes as one moves further into the future. Arguably, concerns in 

respect of climate change – the central motivation for this study – are likely to be an 

increasingly dominant factor influencing the future composition of the waste stream. 

4.3.1.1 England MSW Composition 

The original compositional data in the ERM report was based around a study undertaken by 

WRAP in 2002. 11 Updated compositional figures were taken from a more recent, related study 

and then translated to proportions of the framework composition. 12 Assumptions regarding 

how the compositional data was apportioned can be found in Appendix 2. 

4.3.1.2 Scotland MSW Composition 

The compositional data for Scotland in the ERM report was based on SEPA’s Waste Digest 

5. 13 The latest Waste Digest (7) was found not to contain updated information of relevance so 

the composition reported in ERM’s report was used unaltered. The composition of the paper 

and card fraction was considered to be the same as in England (see Appendix 2). 

4.3.1.3 Wales MSW Composition 

The composition in the ERM report was drawn from a 2003 report into the composition of 

municipal wastes. 14 The actual data used for this study, however, was an adapted version of 

this composition from a 2008 report by ourselves. 15 This adjusted the composition from the 

2003 study to take into account the fact that, based on current performance, using the 

previous composition estimates, some materials were already being captured at levels 

greater than 100% . Further details are shown in Appendix 2. 

4.3.1.4 Northern Ireland MSW Composition 

The data in the ERM report was assimilated from a number of different sources. For this 

study, more up-to-date data was gathered from a RPS Study and apportioned using a similar 

methodology as for England and Wales. 16 See Appendix 2 for further details. 

11 J. Parfitt (2002) Analysis of household waste composition and factors driving waste increases. WRAP, 

Banbury. 

12 BeEnvironmental (2007) National Waste Composition Estimation - Methodology & Approach Report, Report 

for Defra. 

13 See http://www.sepa.org.uk/pdf/publications/wds/wdd_5.pdf 

14 AEAT (2003) The Composition of Municipal Waste in Wales, Report for the National Assembly for Wales, 

December 2003. Data as used in the ERM/Environment Agency update to the WISARD software tool. 

15 Eunomia (2008) Scoping New Municipal Waste Targets for Wales, Report to the Welsh Local Government 

Association, forthcoming. 

16 RPS Consulting (2008), Environment & Heritage Service Review of Municipal Waste Component Analysis. 

Report to the DoE. 


4.3.2 Recycling and Composting Rates 

The source data for England and the DAs varies in quality, but the most up-do-date versions 

were sought in all cases. These data and associated assumptions are reported for England 

and the DAs in Appendix 2. Section 4.3.2.1 shows a summary methodology for England to 

indicate how we structured our analysis, whilst the latest headline figures are reported in 

Section 4.3.2.2. 

25 

4.3.2.1 England MSW Recycling and Composting Rates 

The latest complete breakdown of recycling and composting in England was generated by 

Defra for 2006/07. 17 The glass and textiles fractions, however, were the only two which 

related directly to our MSW framework composition. The remaining material streams had to 

be modelled to fit the format shown in Table 4-2. The general approach for each fraction is 

described in Table 4-3. 

Assumptions regarding organic waste management were then used to determine absolute 

quantities of food and green waste managed by recycling, windrow, IVC and AD. These were 

then converted into overall percentages of material managed by each method. The remaining 

material in the total MSW stream was considered to be in the residual waste stream. 

4.3.2.2 Current MSW Recycling and Composting Rates Modelled for 2008 

The methodology described above in Section 4.3.2.1 was repeated for each of the DAs. 

Current management rates modelled for each material are show in Table 4-4 below. These 

were used as a basis to update specific material stream rates so that the overall recycling 

and composting rates matched those determined for the carbon budget years (see Section 

4.3.3). 

17 Source: Defra Municipal Statistics 2006/07. See 

http://www.defra.gov.uk/environment/statistics/wastats/bulletin07.htm 


26 

Table 4-3: Approach to Modelling of Defra Municipal Statistics 

Material 

Paper & Card 

Compost 

Scrap metals & white goods 

Cans 

Plastics 

Co-mingled 


Non-household recycling 

Approach 

This fraction was disaggregated into the 

following three material streams; Newsprint 

and Magazines; Other Paper; and Card. This 

was done because each of the three general 

categories of material are managed by 

different processes, and are of differing 

value, hence the change in management rate 

over time would not be consistent over the 

three fractions. 

The proportions of each material (i.e. food 

and green waste) managed by open air 

windrows, in vessel composting (IVC) and 

anaerobic digestion (AD) were determined 

from relevant research, and estimations by 

Eunomia based on experience. 

This fraction was disaggregated into ferrous 

and non-ferrous metals and WEEE. 

The only two materials considered were 

ferrous and non-ferrous metals. 

This fraction comprised of plastic film and 

dense plastics only 

Only the most significant materials captured 

by co-mingled kerbside collection systems 

were considered in this fraction. These were 

Paper and card, glass, cans and plastics 

This fraction was assumed to comprise of 

wood, oils and batteries only. 

This fraction was disaggregated into 

materials in a similar proportion to source 

segregated household recycling, though 

respecting the different characteristics of the 

stream. 


Table 4-4: Current MSW Recycling and Composting Rates Modelled 

27 

Percentages of Total MSW Stream 

Waste Fraction 

Recycled Windrow IVC AD 

Eng. Sco. Wal. N.I. Eng. Sco. Wal. N.I. Eng. Sco. Wal. N.I. Eng. Sco. Wal. N.I. 

Newsprint and magazines 75% 47% 75% 72% - - - - 1%

28 

4.3.3 Firm and Funded’ Policies for MSW 

‘Firm and funded’ policy outcomes for MSW essentially rest upon achievement of 

LATS targets, by whichever means is sensible with regard to the time to get 

infrastructure in place, and with reference to existing waste policy / strategy. As 

mentioned above, consultation with England and the DAs was undertaken to check 

our interpretations, although as noted previously, this is based on current, not 

potential future policies. The sections below detail any relevant sources of 

information and any assumptions made to relate the process terminology to our 

baseline framework. Note that in our analysis we have included AD in the 

‘composting’ rates. 

4.3.3.1 ‘Firm and Funded’ Policy Outcomes for England 

For England, our assessment of ‘firm and funded’ policy is based upon an 

interpretation of the Impact Assessment (IA) undertaken for the 2007 National Waste 

Strategy (Waste Strategy for England 2007). The format of the IA differed from our 

baseline framework, and hence, in agreement with Defra, some assumptions were 

needed to apportion some categories to our baseline processes, as shown in Error! 

Not a valid bookmark self-reference.. 

Table 4-5: England Impact Assessment to Baseline Processes 

Impact Assessment Facilities for MSW 

Eunomia Baseline Processes 

Civic Amenity (CA) site recovery & recycling 

Bring recycling 

Materials recovery Facility (MRF) 

Recycling 

Dirty MRF 

Green Waste composting 

Biowaste composting/digestion 

Mechanical Biological Treatment (MBT) 

producing Solid Recovered Fuel (SRF) 

MBT compost and residue landfill 

Composting 

MBT: SRF to cement kiln 

MBT: SRF to dedicated thermal facility 

MBT: SRF to power station 

MBT: Stabilisation, output to landfill 

Energy from Waste (EFW) 

Mechanical with Residue to EfW 

Incineration 

Advanced Conversion Technology 

Unprocessed MSW direct to landfill 

Landfill 


29 

The IA included all target years aside from 2022, for which the last projected year in 

the IA (2019) was used, and hence the management rates plateau after 2019. 

MBT processes which generate Refuse Derived Fuels (RDF) were considered as one 

within the IA. Previous studies undertaken by Eunomia, however, show that the GHG 

impacts of such processes vary significantly according to the type of thermal process 

to which the RDF is sent. It has therefore been necessary to disaggregate this 

category within our model, as summarised in Table 4-6. This shows that all SRF is 

currently sent to cement kilns, but that this changes over time as both more material 

is generated, and a growing number of dedicated facilities are procured (in line with 

current plans), with a limited number of coal-fired power stations also beginning to 

accept material over time. 

In agreement with Defra, the three thermal processes within the IA were aggregated 

to ‘Incineration’ to allow for more simplistic modelling. Due to the low percentages of 

‘Mechanical with Residue to EfW’ and ‘ACT’ (advanced conversion technologies, i.e. 

gasification and pyrolysis), the lower resolution here was not considered to have a 

significant impact. The overall incineration category was then split over time between 

incineration with electricity only and incineration with CHP by the proportions shown 

in Table 4-7. This split is based upon both data for the current situation, and upon the 

assumption that policy drivers such as the RO and potential revenue streams from 

heat sales will deliver increasing amounts of CHP over time. 

Table 4-6: Proportions of MBT RDF Incinerated by Different Facilities 

Process 2008 2012 2017 2022 

MBT: SRF, output to cement kiln 100% 70% 32% 15% 

MBT: SRF, output to dedicated 0% 30% 60% 70% 

MBT: SRF, output to power station 0% 0% 8% 15% 

Table 4-7: Proportions of Incineration Type in Target Years 

Process 2008 2012 2017 2022 

Incineration 

(electricity only) 

Incineration 

(CHP) 

85% 75% 70% 65% 

15% 25% 30% 35% 

The overall management rates for the target years for England are shown in Table 

4-8. It should be noted that these rates are based on the inputs to facilities, as 

required by our modelling of CO 2 e impacts, and do not include recycling from MBT 

and incineration facilities, which would show an increased overall level of recycling. 


30 

Table 4-8: MSW Management Rates for England Based on ‘Firm and Funded’ Policy 

Treatment 2008 2012 2017 2022 

Recycling 24% 1 27% 28% 29% 

Composting 9% 12% 12% 12% 

Incineration 2 14% 21% 23% 24% 

MBT residue to 

RDF 3 1% 5% 5% 6% 

MBT residue to 

landfill 1% 6% 8% 8% 

Landfill 51% 29% 24% 21% 

Notes: 

1. The projected recycling rate for 2008 in the IA was lower than the quarterly rate published by 

Defra for the period Oct-06 to Sep-07 thus the figure was inflated by 2% to estimate the 

current rate. 

2. Includes electricity only and CHP, see Table 4-7. Also includes ACT (Advanced Thermal 

Treatments). 

3. See Table 4-6. 

4.3.3.2 ‘Firm and Funded’ Policy Outcomes for Scotland 

As discussed above, matters in Scotland appear to be in a state of flux following 

announcement of the intent to implement a ‘zero waste’ approach. This may change 

the pattern of treatment relative to those treatments considered in the 2003 National 

Waste Plan. 18 As no specific policy is in place, however, it was agreed with the CCC 

that the most sensible approach would be to model the existing targets from the 

2003 Scottish Waste Plan as ‘firm and funded’. 19 

The Scottish Waste Plan details targets for 2010, 2013 and 2020. These were 

extrapolated to the carbon budget years using the latest SEPA data. 20 The results of 

this extrapolation are summarised in Table 4-9. 

18 SEPA and Scottish Executive (2003) The National Waste Plan 2003, Stirling: SEPA. 

19 See http://www.sepa.org.uk/nws/guidance/nwp.htm 

20 SEPA Local Authority Waste Arisings Survey 2005/2006 


31 

Table 4-9: MSW Management Rates for Scotland Based on ‘Firm and Funded’ Policy 

Treatment 2008 2012 2017 2022 

Recycling 21% 27% 32% 37% 

Composting 12% 17% 19% 20% 

Converted to Energy 5% 10% 13% 15% 

Landfill 62% 46% 36% 28% 

4.3.3.3 ‘Firm and Funded’ Policy Outcomes for Wales 

Like Scotland, Wales is currently undertaking a strategic overhaul. The Welsh 

Assembly Government has recently announced a recycling / composting target of 

70%, although the existing strategy upon which our analysis must be based for 

consistency, proposes only a 40% rate by 2010, preserving the option to go to a 60% 

in later years. On the basis of recent work for the Welsh Assembly Government we 

have assumed that the amount of residual waste treatment in place will be limited in 

the short term to likely facilities in Neath Port Talbot and Wrexham. In order to meet 

LAS targets, we have assumed therefore that recycling and composting rates will 

increase to a combined 50% by 2013. At this point, in the firm and funded baseline, 

the recycling rate is assumed to plateau, and the principle change to 2022 is the 

rollout of incineration capacity, this being 25% of total waste in 2022. 

Table 4-10: MSW Management Rates for Wales Based on ‘Firm and Funded’ Policy 

Treatment 2008 2012 2017 2022 

Recycling 22% 35% 35% 35% 

Composting 12% 15% 15% 15% 

Incinerated 0% 8% 17% 25% 

Landfill 66% 42% 33% 25% 

4.3.3.4 ‘Firm and Funded’ Policy Outcomes for Northern Ireland 

Our ‘firm and funded’ baseline for Northern Ireland is drawn from a document which 

proposes desirable outcomes for 2020 and also gives indicative figures for 2010 and 

2013. 21 This data was used to extrapolate figures for the carbon ‘budget’ years. In 

terms of residual waste treatment, as the fastest way to meet LAS targets, we have 

assumed that MBT facilities will come into operation first, followed by separate food 

waste collection coupled with anaerobic digestion (AD), and then finally incineration. 

21 ERM (2005) BPEO for Waste Management in Northern Ireland, 2005. 


32 

The policy document includes a separate category for AD, but to keep consistent with 

our methodology we have included it in our overall ‘composting’ rate. 

Table 4-11: MSW Management Rates for Northern Ireland Based on ‘Firm and 

Funded’ Policy 

Treatment 2008 2012 2017 2022 

Recycling 18% 20% 21% 21% 

Composting 1 13% 24% 29% 32% 

Thermal 0% 0% 6% 13% 

MBT 2 0% 12% 13% 13% 

Landfill 69% 44% 31% 21% 

Notes: 

1. Includes AD 

2. No specific MBT treatment types were mentioned, however, the potential use of RDF based processes 

was highlighted. It was indicated at least 20% of the High Calorific Value (HCV) residue from the 

process would need to be used as an RDF, rather than landfilled, for this to represent the BPEO. This is 

consistent with the projections for England where over one third of the total MBT capacity for 2022 

includes output as RDF 

4.3.4 Material-specific Projections for Carbon Budget Years 

4.3.4.1 Recycling and Composting 

The current (2008) material-specific recycling rates detailed in Section 4.3.2 were 

used as a basis to determine rates for each material for 2022 to meet the total ‘firm 

and funded’ recycling rates set out in Section 4.3.3. Based on experience, we have 

used a set of assumptions to model the profile of each material-specific recycling rate 

forward, as shown in Table 4-12. 


33 

Table 4-12: Forecast Profile of Materials Recycling of MSW to 2022 


Recycling Rate Profile 

Newsprint and magazines Increases quickly to between 80% and 90% 


Card 

Dense plastic 

Glass 

Ferrous metal 

Non-ferrous metal 

WEEE 

Wood 

Food waste 

Green waste 

Increases to around half that of newsprint and magazines 

and at a slower rate 

Increases to around half that of newsprint and magazines, 

but at a faster rate than other paper 

Increases to around 40% at a linear rate 

Increases to between 75% and 85% quickly but total is 

limited by mixed colour 

Increases rapidly to around 70% due to high market values 

Increases in a similar fashion to ferrous metal 

Increases to around 70%, driven by the WEEE directive 

Increases steadily to around 85%, possibly driven by the 

need to segregate material as a biomass fuel 

Increases slowly as IVC and AD capacity increases and then 

more quickly to around 30% recycling in total driven by LATS 

targets 

Zero overall growth, but a switch from windrow to in-vessel 

composting as more green waste is mixed with food wastes, 

the combination of which must be treated at ABPR-compliant 

facilities 

Textiles Increases at a linear rate to around to 20% 

Other combustibles Increases at a linear rate to around 10% 

Plastic film 

Due to the difficulties in collection and reprocessing of this 

the recycling rate increases by only 2% to around 5% in total 

for the UK 

Non-combustibles Slight steady increase of

34 

was adopted to provide a better understanding of how the management of each of 

the individual material streams would change over time, and to ensure that this was 

consistent with the total ‘Firm and Funded’ projections. The management of materials 

not targeted under our analysis was assumed to be linear, essentially because less is 

known about these material streams, and they offer significantly less abatement 

potential. This approach was only used for England, Scotland and Northern Ireland as 

the recycling and composting rates for Wales were assumed to reach the maximum 

2022 values by 2012 and plateau (see Section 4.3.3.3). 

4.3.4.2 Residual Waste Management 

The management rates for residual waste (the amounts of residual waste managed 

by different treatment / disposal methods) in the carbon budget years were modelled 

as part of the ‘Firm and Funded’ policy outcomes, which gave overall figures for the 

total residual stream. The percentage of each material stream allocated to the 

different residual treatment routes was then determined by: 

‣ Calculating the total quantity of material in each stream using the composition 

and total arisings data; 

‣ Subtracting the material managed by recycling or composting; 

‣ Applying the management rate to the remaining residual quantity; and 

‣ Converting to a percentage of the total managed for each material and for 

each method. 

This approach allowed for the fact that some material streams have a higher recycling 

rate than others, thus varying amounts of material will be left in the residual stream. 

The roll-out of different types of incinerator (i.e. electricity only or CHP) for the DAs 

was considered to follow a similar path to that assumed for England (see Table 4-7). 

4.3.5 Baseline for Total UK MSW 

Table 4-13 below shows the baseline for total UK MSW for 2008 and the carbon 

budget years (2012, 2017 and 2022). The absolute tonnages were calculated by, 

applying the compositions detailed in Section 4.3.1 to the total arisings figures, 

determined from the same sources of data as the latest recycling / composting 

management rates (Section 4.3.2), and then multiplying these quantities by the 

proportions managed through different methods. 


35 

Table 4-13: Assumed Management of UK MSW in Carbon Budget Years 

2008 2012 2017 2022 

Management Method % Tonnage % Tonnage % Tonnage % Tonnage 

Recycling 23.3% 8,310 27.4% 9,776 29.1% 10,348 30.4% 10,825 

Windrow 5.9% 2,091 4.6% 1,635 4.4% 1,559 4.3% 1,533 

IVC 3.6% 1,274 4.8% 1,712 5.4% 1,938 5.8% 2,059 

AD: on-site biogas use 0.2% 64 2.5% 891 3.4% 1,200 3.8% 1,350 

MBT: stabilisation, output to landfill 0.9% 304 4.8% 1,720 6.2% 2,195 6.1% 2,161 

MBT: SRF to cement kiln 0.8% 270 3.2% 1,156 1.6% 584 0.8% 270 

MBT: SRF, output to dedicated 0% 0 1.4% 495 3.1% 1,096 3.5% 1,258 

MBT: SRF, output to power station 0% 0 0% 0 0.4% 146 0.8% 270 

Incineration (electricity only) 10.2% 3,627 14.0% 4,994 14.7% 5,241 14.7% 5,251 

Incineration (CHP) 1.8% 640 4.7% 1,665 6.3% 2,246 7.9% 2,827 

Landfill 53.4% 19,035 32.5% 11,571 25.4% 9,061 21.9% 7,810 

Total 1 100% 35,615 100% 35,615 100% 35,615 100% 35,615 

Notes: 

1. UK MSW arisings have been assumed to have a zero growth rate for this study 


36 

4.4 Commercial and Industrial Wastes 

Projecting a baseline for commercial and industrial (C&I) wastes is more challenging and 

open to greater interpretation than that for MSW. This is due to the lack of accurate arisings 

data and the more limited consideration given to the area in past strategies. The following 

points specify the process for determining the C&I baselines: 

‣ Compositional data was obtained; 

‣ ‘Firm and Funded’ policy was specified so as to define management rates for 2008 

and 2022; 

‣ Management rates were assigned to individual material streams for 2008 and 2022 

and interpolated for 2012 and 2017; and 

‣ Baselines were calculated from latest arisings, compositional, and management data. 

4.4.1 C&I Waste Composition 

Once again we based our construction of the baseline on compositions from the ERM report 

on carbon balances and energy impacts in the UK. 23 The materials that we considered to 

have low abatement potential were amalgamated into one group, and the format arranged so 

that it was broadly similar to that for MSW. Table 4-14 below shows the compositions for C&I 

wastes as used in this study. The composition of ‘Other low Abatement potential’ can be 

found in Appendix 2. 

The compositions were essentially based on the 2002/03 Environment Agency survey into 

C&I wastes in England. This puts it at least six years out of date, hence the need to caveat the 

composition to indicate that this is not likely to represent current C&I waste compositions or 

those in 2022. However, this is the most up-to-date data available. Due to the lack of any 

resolute compositions for the DAs, the same composition was used throughout the analysis 

for the DAs. Current levels of recycling and captures are highly uncertain owing to the 

absence of quality data on materials recycling and on the composition of the waste stream. 

The upshot of this is that the analysis of commercial and industrial wastes is even more 

heavily caveated than that for MSW. 

4.4.2 ‘Firm and Funded’ Policies 

Apart from England and Northern Ireland the ‘Firm and Funded’ polices for C&I wastes are 

lacking in substance and are difficult to ascertain what the future plans are. Northern 

Ireland’s headline targets are similar to England’s, so to keep the baseline simplified, and 

because the actual change in management of C&I wastes is hard to predict, the rates 

projected in England’s Impact Assessment (IA) were also used for the three DAs. 

The change in management of materials to ‘Re-use’ was excluded from the scope of this 

study so the figures from Defra were normalised to take this into account. The IA included 

figures for 2009, 2014 and 2019. These were used as the basis to extrapolate data to the 

target years. Note that the figures for 2008 (current) may be exaggerated as a simple 

23 ERM, Carbon Balances and Energy Impacts of the Management of UK Wastes Defra R&D Project WRT 237 

(2006) 


37 

extrapolation was made back to this year from future targets, hence if the targets are high the 

2008 rates may be high 24 . 

Table 4-14: C&I Composition 


Commercial % of 

Sector Arisings 

Industrial % of 

Sector Arisings 

Paper & Card 28.8% 8.8% 

Plastic (dense) 2.9% 0.9% 

Glass 6.5% 1.1% 

Ferrous Metal 2.3% 4.5% 

MAC Targeted Materials 

Non-Ferrous Metal 1.5% 2.7% 

WEEE 2.4% 0.6% 

Wood 3.3% 5.0% 

Food Waste 9.8% 4.7% 

Green Waste 8.9% 2.2% 

Other Organics 1.5% 4.6% 

Textiles 1.1% 0.3% 

Fines 1.9% 0.5% 

Non-MAC Targeted 

Materials 

Miscellaneous – 

Combustible(7) 

10.4% 17.7% 

Plastic (film) 4.3% 1.0% 

Combustion Residues 0.2% 25.5% 

Other low abatement 

potential 

14.2% 20.0% 

Total 100.0% 100.0% 

24 This was not considered to be significant as only the target years are to be modelled. 


Table 4-15 below shows the overall management rates for C&I wastes used in this study. 

Table 4-15: Management of C&I Wastes 

38 

Management Method 

Commercial 

Industrial 

2008 2012 2017 2022 2008 20012 2017 2022 

Recycling 45% 48% 50% 52% 39% 39% 40% 40% 

Thermal 8% 7% 7% 6% 5% 5% 5% 5% 

Treatment 4% 4% 3% 3% 13% 13% 13% 13% 

Landfill 43% 42% 40% 39% 43% 42% 42% 42% 

Total 100% 100% 100% 100% 100% 100% 100% 100% 

The ‘Thermal’ element was considered to comprise solely of Incineration based treatments 

with ‘electricity generation only’ and ‘CHP’ as two distinct configurations. ‘Treatment’ was 

considered to include biological processes such as IVC and AD, and other treatments such as 

autoclaving, centrifuging and any chemical processes. 25 

4.4.3 Projections to Target Years 

As in the methodology for MSW, recycling rates were assigned to each material stream so that 

the total was equivalent to the projected rate for that year. This was repeated for materials in 

both the Commercial and the Industrial streams, and for 2008 and 2022. Unlike MSW, there 

were no base compositions to define what material was managed by each method, only 

overall rates. Thus, rates had to be prescribed by Eunomia based on industry experience and 

best judgement alone. The general assumptions which underpinned our determination of 

rates are indicated in the points below: 

‣ Commercial recycling is generally expected to be consistent with MSW. However, 

overall rates will increase slower due to the expected slower roll-out of commercial 

collection services; 

‣ Industrial recycling is currently expected to be high due to the ease of collection of 

large quantities of relatively homogeneous source separated waste streams, and 

economic drivers resulting from a high value end market for some of the materials (i.e. 

metals). This is expected to increase to high rates in 2022; 

‣ Commercial composting is currently low with the most significant increase to come 

from treatment of food wastes; 

‣ Industrial composting is currently higher with a greater proportion attributed to the 

treatment of food wastes; 

25 This definition of the terminology for ‘Treatment’ was based on information from the Environment Agencies 

2002/03 C&I survey. See http://www.environmentagency.gov.uk/subjects/waste/1031954/315439/302099/302112/302298/version=1&lang=_e 


39 

‣ Thermal treatment was assumed to comprise the same proportions of facilities as for 

England’s MSW treatment (see Table 4-7), reflecting the view that the majority of 

treatment infrastructure has been closely aligned with MSW infrastructure thus far; 

‣ For Thermal treatment, material streams for which recycling rates were higher were 

assumed to be less likely to be thermally treated than those with low or zero recycling. 

The exception to this was wood, which was expected to take up a higher proportion of 

the thermal capacity than the other material streams, and take up the greatest 

increase in management rate over time; 

‣ Spreading of Industrial food wastes to land was considered to be included in the 

recycling figures. 15% of industrial food wastes were assumed to be currently 

managed by this method, with the same proportion in 2022; 26 

‣ Industrial Treatment was considered to include the treatment of sludges and 

chemicals. 

It should be noted that some of the target rates were considered to be slightly inconsistent 

with what our reasoned projections might be. These discrepancies are highlighted below; 

‣ The Industrial recycling rate only increases by 0.4% from 2008 to 2022. This was 

considered to be low considering that the percentage of material managed by ‘Re-use’ 

does not increase; 27 

‣ ‘Thermal’ treatments increase minimally for Industrial wastes and actually fall for 

Commercial wastes. Considering the increase in EfW capacity for MSW, indicated in 

the IA at 10% between 2008 and 2022, and most strategies affirming the need for 

EfW to be used as a method for residual treatment, and the desirability – hinted at 

strongly in the strategy – of treating Commercial wastes at municipal facilities, a 

stronger growth in thermal treatment might be expected (especially for commercial 

waste). 

‣ ‘Treatment’ for Commercial wastes falls, which is unlikely considering the need to 

divert food and green waste from landfill. This is one area where we deviated from the 

targets set out in the policy, as decreased composting (digestion does not feature 

separately) in 2022 does not appear representative of the likely future situation. 28 

Recycling was the first area considered. As per MSW, for each targeted material time profiles 

were used to interpolate the management rates for 2012 and 2017. This approach was used 

in order to better represent the actual changes in material management over time. These 

profiles are shown in Appendix 2. The overall recycling rates for 2012 and 2017 were crosschecked 

with the target rates indicated in the IA and found to be within +/- 0.5%. 29 

26 The proportion of UK Industrial food waste managed by land spreading was considered to be similar to the 

proportion managed in the East of England region. This was determined during a biowaste management study 

conducted by Eunomia for the East of England Regional Assembly in early 2008. 

27 See Defra (2007) Waste Strategy for England 2007: Annex A: Impact Assessment, 

http://www.defra.gov.uk/environment/waste/strategy/strategy07/index.htm . 

28 One explanation for decreasing treatment is if the IA had deviated from the classification of treatments as set 

out for the 2002/03 EA C&I survey and had included composting under the recycling rates – as per MSW. At the 

same time, this would make it more difficult to explain the low rate of increase in recycling. 

29 This level of accuracy was considered adequate for this study. 


40 

Food and green waste was considered to be managed by composting processes in the 

proportions shown in Table 4-16 below. The treatment of both Commercial and Industrial 

organic wastes has been assumed to follow a similar pattern, with regards to proportions 

treated and change over time. The general trend in the management of food wastes is a shift 

from IVC to AD. Some green waste will also move to AD, and for this analysis we have 

assumed that the proportion of green waste managed by IVC will remain constant. 

Table 4-16: Management of C&I Organic Wastes (as % of that being recycled / treated) in 

2008 and 2022 

Material Stream 

% Managed by Each Process 

Commercial 2008 Windrow IVC AD 

Food 0% 90% 10% 

Green 79% 20% 1% 

Commercial 2022 Windrow IVC AD 

Food 0% 60% 40% 

Green 76% 20% 4% 

Industrial 2008 Windrow IVC AD 

Food 0% 90% 10% 

Green 79% 20% 1% 

Industrial 2022 Windrow IVC AD 

Food 0% 60% 40% 

Green 76% 20% 4% 

Food and green waste management rates were interpolated to 2012 and 2017 using time 

profiles, as per recycling. Once again these can be found in Appendix 2. 

Initially the percentage of each material being managed by EfW was assumed to be the same 

as the overall rate i.e. if the total EfW rate was 7% then 7% of paper / card, plastics, etc were 

assumed to be managed in this way. Further to this, the percentage for wood was increased, 

as it was assumed more wood was being combusted overall, and following the same logic, the 

percentages for food and green waste were reduced. 

Table 4-17 shows the total latest total arisings figures and the corresponding sources of data. 


41 

Table 4-17: Total C&I Arisings 

Administration 

Latest Commercial 

Arisings (Thousand 

Tonnes) 

Latest Industrial 

Arisings (Thousand 

Tonnes) 

Year 

England 1 30,320 37,857 2002/03 

Scotland 2 6,060 2,350 2005 

Wales 3 1,033 4,239 2002/03 

Northern Ireland 4 524 111 2002 

Sources: 

1. EA England, Commercial and Industrial Waste Survey 2002/03 

2. SEPA Commercial and Industrial Waste Study 2005 

3. EA England, Commercial and Industrial Waste Survey 2002/03 

4. MEL and EnviroCentre (2002) Industrial and Commercial Waste Production in Northern Ireland, Final Report to the Northern Ireland 

Environment and Heritage Service, 

4.4.4 Baselines for UK C&I Wastes 

The combined UK C&I baselines are shown below in Table 4-18 and Table 4-19. Management 

rates have been assumed to be the same for England and the DAs, hence the UK figures give 

an indicative view of how C&I waste is managed for all the administrations. This should 

include the caveat that the recycling rates are likely to vary across the DAs, but without better 

supporting data, and the fact that the arisings from the three DAs constitute less than one 

quarter of England’s, the potential variance was considered acceptable within the scope of 

this study. 


42 

Table 4-18: Management of UK Commercial Wastes 

2008 2012 2017 2022 

Management Method % Tonnes % Tonnes % Tonnes % Tonnes 

Recycling 45.2% 18,538 48.7% 19,995 50.6% 20,789 52.2% 21,408 

Windrow 3.1% 1,279 3.1% 1,258 3.1% 1,252 3.0% 1,249 

IVC 0% 0 0.6% 266 1.0% 423 1.7% 691 

AD: on-site biogas use 0% 0 0.2% 70 0.3% 144 0.7% 307 

Incineration (electricity 

generation only) 5.5% 2,241 5.1% 2,081 4.6% 1,881 4.1% 1,681 

Incineration (CHP) 1.0% 395 1.3% 541 1.8% 723 2.2% 905 

Landfill 45.3% 18,596 41.0% 16,838 38.6% 15,837 36.1% 14,808 

Total 1 100% 41,050 100% 41,050 100% 41,050 100% 41,050 


43 

Table 4-19: Management of UK Industrial Wastes (Inputs to Facilities in Thousand Tonnes) 

2008 2012 2017 2022 

Management Method % Tonnes % Tonnes % Tonnes % Tonnes 

Recycling 38.5% 15,483 39.0% 15,682 39.4% 15,836 39.7% 15,984 

Windrow 1.6% 628 1.5% 612 1.5% 607 1.5% 604 

IVC 0.8% 329 0.9% 369 1.0% 403 1.1% 442 

AD: on-site biogas use 0.0% 19 0.3% 101 0.4% 158 0.5% 221 

Incineration (electricity 

generation only) 4.0% 1,624 3.8% 1,543 3.6% 1,443 3.3% 1,342 

Incineration (CHP) 0.7% 287 1.0% 411 1.4% 567 1.8% 723 

Landfill 43.6% 17,543 42.7% 17,173 41.9% 16,848 41.1% 16,517 

Other Treatment 10.0% 4,020 10.1% 4,042 10.1% 4,071 10.2% 0 

Total 1 100% 39,933 99% 39,933 100% 39,933 100% 35,833 


4.5 Construction, Demolition and Excavation (CDE) 

44 

There is very little data about this sector, with regards to arisings, composition and ‘Firm and 

Funded’ policies. It was considered that the management of rubble and the like would not 

provide significant capacity for abatement of CO 2 equ, hence we limited the selection of 

materials to Paper and Card, Plastic, Metals and Wood. 

4.5.1 Waste Composition 

The most useful dataset found was the Wales Construction & Demolition Survey for EC Waste 

Statistics Submission 2005/06. From this study the following composition was determined. 

Table 4-20: CDE Composition 


Percentage 

Paper and Card 0.6% 

Plastic 1.0% 

Metals 1.7% 

Wood 3.8% 

Other Low abatement Potential 93% 

Note that the majority of the materials in the sector have low potential for abatement. Wood 

was considered the material stream with the most significant abatement potential. The 

composition of wood in CDE is relatively uncertain. However, the figure of 3.8% is similar to 

that in a report into wood waste by WRAP, hence was considered appropriate for this study. 30 

4.5.2 Latest Position 

Table 4-21 below shows the management of the materials considered in this study (once 

again this was taken from the Welsh CDE study). The composition and management of 

wastes from the CDE sector was considered to be the same for England and the DAs for the 

purposes of this study. 

30 M.E.L. Research (2005) Reference Document on the Status of Wood Waste Arisings and Management in the 

UK, Final Report to WRAP, June 2005. 


45 

Table 4-21: Latest Management of UK CDE Wastes (Based on Welsh Report) 

Material Stream Landfill Recycled Incinerated Transfer 

Paper and Card 63% 16% 0% 21% 

Plastic 65% 15% 0% 21% 

Metals 11% 86% 0% 3% 

Wood 22% 72% 0.10% 6% 

The arisings data was gathered from a number of different sources. Table 4-22 below shows 

the headline figures and source data to which the Welsh composition was applied. 

Table 4-22: Latest Quantities of UK CDE Wastes 


Latest Arisings 

(Thousand Tonnes) 

Year 

England 1 90,840 2001 

Scotland 2 10,600 2005 

Wales 3 12,167 2005/06 

Northern Ireland 4 3,750 2005 

Sources: 

1. ODPM (2001/2003) Survey of Arisings and use of Construction and Demolition Waste. 

2. SEPA Construction and Demolition Waste Study 2005 

3. Wales Construction & Demolition Survey for EC Waste Stats Submission 2005/06 

4. ERM (2005)Assessment of the Best Practicable Environmental Option for Waste Management in 

Northern Ireland: Development and Analysis 

4.5.3 ‘Firm and Funded’ Policies 

There are very limited policies for the sector. The principle policies are landfill tax, the 

aggregates tax, and the recently implemented requirement for site waste management plans. 

The consultation document for the future CDE strategy is still out for review. We have based 

our recycling projections on this study but have adjusted the rates for 2022 to reflect what 

actually may happen based on limitations of implementation and uptake of procedures. 

Table 4-23 below indicates the recycling rates for CDE materials in 2022. We only considered 

a change in recycling rates in the baseline. Any change in thermal treatment (i.e. incineration 

of wood) was considered only in the MACC modelling (i.e. not in the baseline). The recycling 

rates were assumed to increase linearly from the current position. 


46 

Table 4-23: Projected CDE Recycling Rates in 2022 


2022 Recycling Rate 

Paper and Card 50% 

Plastic 50% 

Metals 85% 

Wood 90% 

4.5.4 Baseline for UK CDE Wastes 

Table 4-24 below shows the resulting management baselines for UK CDE wastes. Relevant 

tonnages can be calculated using the totals in Table 4-22. 

Table 4-24: Baseline for UK CDE Wastes 

Management Method 

2008 2012 2017 2022 

Recycling 58% 62% 67% 71% 

Incineration (electricity generation only)

5.0 Approach to Emissions Modelling 

47 

Our modelling considers the difference in emissions that occurs as a result of treatment 

changes for the following types of materials: 

‣ Paper and card; 

‣ Dense plastic; 

‣ Glass; 

‣ Steel; 

‣ Aluminium; 

‣ Wood; 

‣ WEEE; 

‣ Green waste; 

‣ Food waste; 

‣ Residual waste. 

For some treatment changes – such as a shift towards increased recycling – a focus on the 

specific material is the most appropriate method to assess the change in emissions. For 

others, however, it is more appropriate to consider the impacts that occur to the residual 

waste stream. 

The residual waste stream is the material that remains in the waste stream after removal of 

materials for recycling, and will therefore include a mixture of all the materials listed above in 

varying proportions. Changes in the collection and treatment of both source separated 

organic wastes and dry recyclables are considered, as well as switches associated with 

changing the treatment of residual waste. Further discussion regarding the types of switches 

considered is provided in Section. 

As was confirmed in Section 2.8, although Eunomia’s usual approach within projects of this 

nature is to include biogenic CO 2 within the emissions totals, non-fossil carbon emissions are 

not included within the MACCs. They are, however, reported into the relevant output sheets in 

line with good practice. 

5.1 Composition of Residual Waste 

In the modelling of the emissions from different residual waste treatments, the question 

arises as to ‘what does the residual waste look like’ The emissions from different processes, 

their performance and their cost depend upon the composition of the stream. A clear difficulty 

in this modelling exercise is that when one is considering the MACC modelling, the 

composition of residual waste changes depending upon the order in which specific switches 

fall in the ranking of measures in terms of their unit cost per tonne of CO 2 equivalent abated. 

Whilst in principle, it is possible to model the effect of these changes, in practice, the it is 

extremely complex to model these effects in a dynamic way, not least since the effect would 

be to change both the unit cost per tonne of CO 2 abated, as well as the abatement per tonne 

of waste treated, thereby leading to the situation where the ranking of measures changes 

dynamically depending upon what switches have already been ‘enacted’. Some pragmatism 

was required, therefore, in modelling the residual waste treatments. 

Our analysis uses the same residual composition for both the municipal and commercial 

waste streams. It has been developed from a municipal solid waste (MSW) composition, and 


48 

includes some waste collected from commercial premises where such collections are 

provided by the local authority. Whilst there are clearly differences between the commercial 

and municipal waste streams, the quality of compositional data for either commercial or 

industrial waste is rather poor. 

The different MSW streams include refuse collected by: 

‣ Household doorstep (kerbside) collections; 

‣ HWRC (and bring) sites; 

‣ Commercial collections where these are provided by local authorities; 

‣ Litter and street cleansing services; 

‣ Bulky waste collections; and 

‣ Collections of fly tipped wastes. 

The composition of residual waste was derived by effectively removing materials from each of 

the MSW streams for recycling in variable quantities. The modelling of capture rates of 

materials from the different streams outlined here is based on both the current data from the 

best performing local authorities in UK, and also data from best practice elsewhere in Europe. 

Given that the approach to modelling has been to ‘look backwards from 2022’, having carried 

out initial model runs and seen the effect in terms of recycling, we decided to model the 

residual waste composition on the basis of an overall recycling rate of 60% across the whole 

MSW stream, taking into account variable recycling from the constituent streams to produce 

the residual waste composition. Source separated collections of food waste are required to 

reach high recycling rates. As the overall recycling rate increases, the relative proportion of 

those materials not targeted by recycling collections (such as plastic film and disposable 

nappies) increases within the residual waste composition. In earlier years, the recycling rate is 

lower than 60%, but the view was taken that since the rankings of measures in the MACC 

modelling would potentially shift over the years, it was more important to focus on 2022 as 

an orientation point for the trajectory which the UK should pursue. 

As the overall MSW recycling rate increases from 30%, the following changes in composition 

typically occur: 

‣ the proportion of paper and card within the composition decreases (more is captured 

through the intensification of recycling collections for example); 

‣ the proportion of putrescible waste decreases through the introduction of source 

separated collections of food waste; 

‣ the proportion of plastics increases as these are generally less well captured by local 

authority recycling collections. 

Use of a standard composition with a static recycling rate throughout the time period under 

investigation is acknowledged as a simplification within the modelling. Eunomia’s previous 

experience of modelling residual waste treatment technologies has demonstrated that GHG 

emissions vary as the composition changes. The national UK recycling rate for 2006/7 was 

31%. 31 It is likely there will be some variability in emissions over time as the recycling rate 

31 Defra (2007) Municipal Waste Management Statistics 2006/7, available from 

http://www.defra.gov.uk/news/2007/071106a.htm 



49 

improves, with the exact impact being dependent on the relative proportions of materials 

removed from the different streams by recycling. 

In comparison to results obtained using a 60% recycling rate, a MSW composition with a 30% 

recycling rate results in total CO 2 equivalent emissions (excluding the non-fossil carbon) per 

tonne of waste treated that are typically: 

‣ 10% higher for MBT treatments; 

‣ 20-25% higher for incineration (depending on energy utilisation assumptions); and 

‣ 10% higher for landfill. 

Variations are also seen in the amount of energy generated by thermal technologies as 

plastics become more concentrated within the residual waste composition at the higher 

recycling rates. 

The final residual waste composition that was used is detailed in Table 5-1. 

Table 5-1: Residual Waste Composition 

Compositional element % 

Newspapers 2.19% 

Paper 

Magazines 1.36% 

Other recyclable paper 1.46% 

Card 

Cardboard 3.84% 

Unclassified paper and card 7.80% 

Refuse sacks and carrier bags 3.98% 

Plastic Film 

Packaging film 4.67% 

Other plastic film 0.57% 

PET clear 0.42% 

PET coloured 0.22% 

HDPE natural 0.54% 

HDPE coloured 0.28% 

Dense Plastic 

PVC natural 0.03% 

PVC coloured 0.03% 

Food packaging 2.98% 

Non-food packaging 1.05% 

Other 3.87% 

Textiles 

Natural man-made fibres 1.10% 

Unclassified 6.42% 

Disposable nappies 7.46% 

Misc Combustibles 

Shoes 0.68% 

Wood and furniture 7.42% 

Misc Non Combustibles Unclassified 8.66% 

Clear bottles and jars 0.92% 

Glass 

Green bottles and jars 0.92% 

Brown bottles and jars 0.58% 

Other glass 1.34% 

Food cans 0.38% 

Ferrous Metals 

Beverage cans 0.73% 

Batteries 0.07% 

Other ferrous 2.74% 

Aluminium foil 0.31% 

Non-ferrous 

Aluminium beverage cans 0.62% 

Aluminium food cans 0.48% 

Garden waste 2.44% 

Putrescibles 

Kitchen waste 7.35% 

Non-home compostable kitchen waste 6.14% 

Unclassified 3.78% 

Fines Fines 4.16% 

TOTALS 100.0%

50 

5.2 Transport 

Analyses of this nature frequently consider some kind of transport impact, usually considered 

on the basis of a certain number of fixed transport routings taken to represent different 

transport routings for the different types of collection. In a recent report for Defra, ERM 

considered these impacts using the following simplifications: 32 

‣ 10 km distance from the point of collection to the sorting facility; 

‣ 10 km distance travelled by residues to landfill; 

‣ 100 km to residual waste treatment facility. 

In our view, there is little or no justification for ‘fixing’ a transport routing, still less, a transport 

impact, to a given treatment. If specific impacts – and hence, differentials – are associated 

with treatments, then though transport might not be a significant factor in determining the 

impact of a given treatment, they might become more important in determining the net effect 

of a switch (because the impact of a switch works on the basis of differentials between 

treatments). Thus, results can become biased for, or against, a treatment purely on the basis 

of what are likely to be spurious transport assumptions. 

At the margin, it really is impossible to say whether the transport emissions will change as a 

result of a change in treatment. There is no a priori reason why one or other treatment will be 

closer or further away than another, still less that the transport implications of the 

movements will be fixed in relative terms (the distance and the impacts are not the same 

thing), especially as one considers the evolution of waste management over the coming 

decades. The effects are likely to be highly location dependent. Consequently, in the switch of 

materials from one treatment to another, we have not considered GHG-related transport 

impacts (we effectively assume no change in transport impacts). 

The one exception to this general rule was in respect of recycling. Here, we have considered 

the impacts of moving materials from ‘a depot’ to a port for onward transport. This reflects 

assumptions made concerning the destinations for reprocessing used in this study. 

5.3 Literature Sources for Modelling Treatment Methods 

The methodologies for modelling the treatment methods were developed from a variety of 

sources: 

‣ A model developed for Defra and used to estimate GHG emissions from landfills for 

submission to IPCC was used to model landfill emissions. The essence of this is 

captured by in a document by LQM and Golders. 33 Some adaptations were made to 

the model; 


237) 

33 Land Quality Management (2003) Methane Emissions from Landfill sites in the UK, Final Report for Defra, 

January 2003; Golder Associates (2005) Report on UK Landfill Methane Emissions: Evaluation And Appraisal Of 

Waste Policies And Projections To 2050, Report to Defra, November 2005 


51 

‣ A recent study by ERM formed the basis for assessing the impacts of incinerating 

specific materials. 34 Again, some adaptations were made to that modelling; 

‣ Eunomia’s residual waste model Atropos was used to model MBT facilities and the 

incineration of residual waste; 35 

‣ Previous work by Eunomia was used to model impacts for source separated organic 

materials. 36 

The different methodologies used a variety of assumptions, some of which varied between 

the sources. These included the following significant parameters: 

‣ Carbon content; 

‣ Moisture content; 

‣ Calorific value. 

Much of this variation was not considered have a significant impact upon the results. Where 

values have been changed from the original source, reference is made to the change within 

the relevant section. 

5.4 Generic Assumptions for Treatment Technologies 

Generic assumptions are those underlying assumptions common to all treatment 

technologies, including the treatment of source separated organic wastes as well as that for 

residual waste. 

5.4.1 Avoided CO 2 Emissions from Energy Generation 

All waste management processes consume, and in many cases, generate energy. Where 

energy is generated, it can be considered to replace a requirement for equivalent amounts of 

heat and power from other sources. 

The carbon intensity of an energy source is the quantity of GHG emissions associated with 

generating the energy. Where emissions are avoided as a result of generating energy from 

waste, assumptions regarding which source of energy is considered to have been displaced 

are important in determining the overall GHG benefit associated with power generation. 

For the purposes of the current analysis, the project sponsors provided the data regarding the 

carbon intensity of electricity and heat generation in order to retain consistency with MACCs 

in other sectors. These factors are fixed over time. 

Whilst the modelling of abatement potential can be carried out for any given year, as 

highlighted previously, the decision was taken to model on the basis of a trajectory stretching 

back in time from 2022. The abatement potentials change depending upon the marginal 

source of electricity being displaced, which depends, in turn, upon the year chosen. These 

figures can change by 15% or so for some switches, but the view was taken that policy was 


237. 

35 The model is described in: Eunomia Research & Consulting / Enviro Centre (2008) Greenhouse Gas Balance 

of Waste Management Scenarios, report for the Greater London Authority, January 2008, and associated 

Appendices 

36 Eunomia (2006) Managing Biowastes from Households in the UK: Applying Life-cycle Thinking in the 

Framework of Cost-benefit Analysis, Final report for WRAP, May 2006 


unlikely to be developed to support switches which were attractive in one year, but not five 

years later. 


52 

5.4.1.1 Electricity 

CCC supplied emissions figures for the carbon intensity of electricity generation for marginal 

sources for the years 2008-2050. The figure used was 0.353 kg CO 2 / kWh electricity. In 

earlier model runs, a varying figure for the carbon intensity was used, and the model allows 

for varying carbon intensities to be used for each year. 

5.4.1.2 Heat 

The carbon intensity of heat generation was estimated using the BERR conversion factor for 

the use of gas, which is 0.206 kg CO 2 equivalent per kWh of heat energy generated. This was 

then divided by the efficiency assumed for heat generation, this being 90% (giving a figure of 

0.228 kg CO 2 /kWh. This figure is likely to underestimate the GHG emissions total as it does 

not include pre-combustion emissions such as those associated extracting the gas. 

Heat generation from waste management facilities is generated continuously and would not 

always be capable of being utilised. We have incorporated a heat load factor into the model, 

and this was set at 60% for the modelling runs in this report. 

5.4.1.3 Diesel 

We have used a figure of 3.26 kg CO 2 equivalent per litre of diesel, which includes emissions 

from pre-combustion. This includes just under 2.8kg CO 2 equivalent from combustion as well 

as methane, carbon dioxide and N 2 O from pre-combustion. 

5.4.2 Emissions Avoided Through Recycling 

Recovery of material from the residual waste stream occurs at incineration and MBT facilities. 

The climate change benefits of recycling material are discussed in greater detail in Section 

5.6 which confirms the wide range of possible values attributed to these benefits. Such 

impacts are only considered within the Global scope MACCs. This is because, as Section 5.6 

highlights, it is assumed that, at the margin, additional reprocessing occurs overseas, so that 

recycling materials only delivers benefits under the global MACC. 

Most studies provide estimates of GHG reductions delivered by ‘front-end’ collection and 

recovery systems, i.e. kerbside or bring recycling, followed if necessary by sorting within a 

Materials Recovery Facility (if collected in commingled form). Materials recovered from 

residual wastes, however, have higher levels of contamination as a result of contact with the 

mixed residual waste stream. Depending upon the material, this contamination may have the 

following impacts: 

‣ Rather than a ‘closed-loop’ process, materials might be recycled into lower value 

applications (for example, mixed glass to aggregates or plastics to “plaswood”, which 

deliver reduced, if any, carbon benefits); and 

‣ Prior to reprocessing, contaminated materials will require energy for cleaning 

processes - for example, hot-washing of plastics - and thus will deliver lower carbon 

benefits than clean streams. 

The current analysis attributes the same GHG benefits to recyclables removed from residual 

waste as those obtained through specific collections. For most dry recyclables, this is a 

broadly acceptable approach since the effects of contamination are probably such as to 

affect price more than the associated benefits. However, the approach probably overstates 

the benefits associated with this practice at present, though this will be true only where it is

53 

assumed that plastics are extracted for recycling. Looking forward, the potential for closed 

loop recycling of plastic bottles extracted from the waste stream seems more plausible, 

especially given that our baseline assumption assumes relatively high captures of food 

wastes. Table 5-2 provides a summary of the values used. 

Table 5-2: Emissions Avoided Through Recycling from Residual Waste Facilities (Note: Global 

MACC only) 

Avoided emissions, t CO 2 equ / t recycled 

material 

Dense plastic 1.40 

Glass 0.32 

Steel 1.34 

Aluminium 9.20 

5.5 Treatment of Residual Waste 

5.5.1 Landfill 

5.5.1.1 Baseline Model 

Emissions from landfill were modelled using a model made available by Defra and CCC for 

this project, along with relevant supporting documentation. 37 The original model developed by 

LQM was based on the Tier 2 methodology outlined in the Revised 1996 IPCC Guidelines for 

National Greenhouse Gas Inventories and is a first order decay model with UK specific 

modifications. The LQM model was subsequently updated by Golders and AEA, and provides 

the basis for calculating methane emissions from landfill for the UK’s submission to the IPCC. 

The LQM / Golders model produces a time-dependent emissions profile, with emissions being 

modelled on the basis of the cellulose and hemi-cellulose content of the different materials. 

The model further distinguishes between slow, medium and fast rates of decay for the 

cellulose and hemi-cellulose element. 

5.5.1.2 Adaptations of the Baseline Model 

The LQM / Golders model has been modified within the current analysis where it was felt that 

key assumptions were affecting the modelling in a significant manner. We understand the 

model is being subjected to a more thorough overhaul and so have not made more 

fundamental changes. 

The model was adapted to include specific degradation factors for food and green waste, as 

the original model had only one generic factor for putrescible material. Food and garden 

waste clearly are different materials, and they tend to be collected through different routes. 

37 Land Quality Management (2003) Methane Emissions from Landfill Sites in the UK, Final Report for Defra, 

January 2003; Golder Associates (2005) Report on UK Landfill Methane Emissions: Evaluation And Appraisal Of 

Waste Policies And Projections To 2050, Report for Defra, November 2005 


54 

The model did include a category for ‘composted putrescibles’. In recent years, the model 

runs had picked up, for the landfilling of putrescible waste, the parameters for ‘composted 

putrescibles’ (presumably intended to reflect the gas generation behaviour of rejects, or 

outputs from, composting processes, or stabilised outputs being sent to landfill). The effect 

was that all putrescible waste from the municipal stream was being treated as though: 

‣ None of the carbon was of the fast degrading variety, even though food wastes clearly 

include a significant proportion of carbon which is of a fast degrading nature; 

‣ 50% of the carbon was of the medium (rate) degrading variety; 

‣ 50% of the carbon was of the slow (rate) degrading variety; 

‣ In total, 57% of the carbon landfilled was degraded and led to emissions of either 

carbon dioxide or methane. This figure would be low for many organic wastes being 

landfilled; and 

‣ The moisture content was assumed to be 30%, well below what would be expected 

from, for example, food waste, for which moisture content may be 70% or so, and also 

well below what would be expected for garden wastes. 

Increasingly, garden wastes are separately collected from households (either at the doorstep 

or at civic amenity sites). Consequently, it makes little sense to bundle together ‘food and 

garden waste’ into one ‘putrescibles’ category. 

Other authors suggest that fast-degrading components constitute a far greater proportion of 

the carbon in landfilled food waste. 38 In addition, moisture is closer to 70% for food waste. 

The proportion of rapidly degrading cellulose for the food waste component was therefore 

modified within the current analysis to reflect the influence of these additional carbon 

elements, as the model otherwise substantially understates, in our view, the emissions 

resulting from the degradation of the putrescible fraction within landfill. 

It should be noted that there are a number of other parameters in the model which appear 

questionable. These affect the modelling of other materials’ behaviour in landfill. For 

example, the model assumes a high moisture content for paper and card, so that other things 

being equal, the generation of landfill gas from paper is modelled lower than might be the 

case in reality. The important point for the UK as a whole is that: 

a) if the modelling is incorrect, the existing reporting approach might reasonably 

be said to be unsound. Having said this, the level of accuracy to which this can 

be done at all is hugely limited by the lack of quality data on exactly what it is 

that is being landfilled (the composition of landfilled waste); 

b) to the extent that the existing reporting might under-report emissions, it might 

also understate the case for abatement of GHGs going forward. 

The changes made, therefore, are a compromise between the desire to retain some 

consistency with previous reporting, but to ensure that major opportunities for abatement 

were not missed. With a 75% lifetime capture rate for methane assumed (for a discussion of 

38 See, for example, Dalemo, M (1996) The Modelling of an Anaerobic Digestion Plant and a Sewage Plant in the 

ORWARE Simulation Model, Rapport 213, Swedish University of Agricultural Sciences, Uppsala 1996; Eleazer, 

W.E., Odle, W.S., Wang, Y-S, and Barlaz, M.A. 1997. Biodegradability of Municipal Solid Waste Components in 

Laboratory-Scale Landfills. Environmental Science and Technology. 31, 911-917; Trine Lund Hansen et al 

(2006) Composition of Source-sorted Municipal Organic Waste Collected in Danish Cities, Waste Management 

27 pp.510-518. 


55 

this, see Section 5.5.1.3), the fact that the existing assumptions regarding food waste implied 

that only 37kg of carbon were degraded per tonne of food waste implied that landfilling food 

waste generated little by way of methane emissions. 

Table 5-3: Decay Characteristics for Waste Fractions in Landfill 

Carbon fractions 

RDO MDO SDO 

Inert 

Water 

content 

Cellulose 

Hemicellulose 

Decomposition 

Paper & card 0% 25% 75% 0% 30% 61.2% 9.1% 61.8% 

Dense plastics 0% 0% 0% 100% 5% 0.0% 0.0% 0.0% 

Film plastics 0% 0% 0% 100% 30% 0.0% 0.0% 0.0% 

Textiles 0% 0% 100% 0% 25% 20.0% 20.0% 50.0% 

Misc. comb. 0% 100% 0% 0% 20% 25.0% 25.5% 50.0% 

Misc. non comb. 0% 0% 0% 100% 5% 0.0% 0.0% 0.0% 

Food 80% 20% 0% 0% 70% 60.0% 40.0% 90.0% 

Green 15% 55% 30% 0% 55% 60.0% 40.0% 70.0% 

Ferrous metal 0% 0% 0% 100% 5% 0.0% 0.0% 0.0% 

Non ferrous metal 0% 0% 0% 100% 10% 0.0% 0.0% 0.0% 

Non inert fines 100% 0% 0% 0% 40% 25.5% 25.0% 50.0% 

Inert fines 0% 0% 0% 100% 5% 0.0% 0.0% 0.0% 

Notes: 

Cellulose, hemi cellulose and decomposition factors are calculated here as a proportion of the dry 

weight. 

Food and green factors are developed by Eunomia. Other decay characteristics are as detailed within 

the original model. 

5.5.1.3 The Issue of Gas Capture 

The LQM / Golders model distinguishes between four types of landfills, categorised on the 

basis of the efficiency of landfill gas collection. The current analysis considers impacts 

associated with Type 3 landfills, as these are the only type used from 1986 onwards. Type 3 

landfills are considered to have a comprehensive landfill gas collection system, with the 

recovered gas being used for energy generation or flared. 

There is some debate with regard to both the efficiency landfill gas capture and the proportion 

of the gas that is used for energy generation. Of these, the gas capture rate is both the most 

sensitive and the most contested component. 


56 

A previous assessment undertaken by Eunomia used a gas capture rate of 50%, an approach 

based upon two studies conducted on behalf of Defra by LQM and Enviros. 39 A subsequent 

study conducted by ERM on behalf of Defra, however, assumed a 75% capture rate over the 

100 year timeframe assessed. 40 A subsequent ERM report acknowledged that if one moved 

the analysis beyond this (somewhat arbitrary) timeframe, lifetime capture rates might be 

around 59%. 41 Documentation supplied with the Golders model indicates that the expert 

review group formed as part of that study considered that 85% of the gas would be collected 

during the gas utilisation phases, and a lifetime 75% gas capture rate appears to have been 

suggested upon that basis. 42 

The wider literature suggests a range of estimates for the efficiency of gas collection with a 

distinction being made between instantaneous collection efficiencies and the proportion of 

gas that can be captured over the lifetime of the landfill. 43 Whilst instantaneous collection 

rates for permanently capped landfilled waste can be as high as 90%, capture rates may be 

much lower during the operating phase of the landfill (35%) or when the waste is capped with 

a temporary cover (65%). 44 In addition, gas collection is technologically impractical towards 

the end of the site’s life. The Intergovernmental Panel on Climate Change (IPCC) has recently 

stated that lifetime gas capture rates may be as low as 20%. 45 We would consider, however, 

that landfills in the UK are somewhat better engineered than in the general (global) case, 

although a recent report by the European Environment Agency uses the IPCC figure. 46 

The current analysis uses a 75% landfill gas capture rate as advised by CCC and Defra. 

Although consistent with the other recent analyses carried out for Defra, this would appear to 

be a generous estimate in relation to the lifetime gas collection efficiencies suggested in the 

wider literature as previously indicated. We consider methane emissions occurring during a 

39 Eunomia (2006) A Changing Climate for Energy from Waste Final report to Friends of the Earth, May 2006; 

LQM (2003) Methane Emissions from Landfill Sites in the UK, Report for Defra, January 2003; Enviros, 

University of Birmingham, RPA Ltd., Open University and M. Thurgood (2004) Review of Environmental and 

Health Effects of Waste Management: Municipal Solid Waste and Similar Wastes, Final Report to Defra, March 

2004 

40 ERM (2006) Impact of Energy from Waste and Recycling Policy on UK Greenhouse Gas Emissions, Final 

Report for Defra, January 2006. 

41 ERM (2006) Carbon Balances and Energy Impacts of the Management of UK Wastes, Defra R&D project WRT 

237. December 2006 

42 Golder Associates (2005) Report on UK Landfill Methane Emissions: Evaluation and Appraisal of Waste 

Policies and Projections to 2050, report for Defra, November 2005 

43 P Anderson (2005) The Landfill Gas Recovery Hoax, Abstract for 2005 National Green Power Marketing 

Conference; USEPA (2004) Direct Emissions from Municipal Solid Waste Landfilling, Climate Leaders 

Greenhouse Gas Inventory Protocol – Core Module Guidance, October 2004; K A Brown, A Smith, S J Burnley, D 

J V Campbell, K King and M J T Milton (1999) Methane Emissions from UK Landfills, Report for the UK 

Department of the Environment, Transport and the Regions 

44 K Spokas, J Bogner, J P Chanton, M Morcet, C Aran, C Graff, Y Moreau-Le Golvan and I Hebe (2006) Methane 

Mass Balance at 3 Landfill Sites: What is the Efficiency of Capture by Gas Collection Systems Waste 

Management, 5, pp515-525 

45 IPCC (2007) Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment 

Report of the Intergovernmental Panel on Climate Change (B. Metz, O.R. Davidson, P.R. Bosch, R. Dave, L.A. 

Meyer (eds)), Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA., 600 pp. 

46 M. Skovgaard, N. Hedal and A. Villanueva, F. Andersen and H. Larsen (2008) Municipal Waste Management 

and Greenhouse Gases, ETC/RWM Working Paper 2008/1, January 2008. 


100 year timeframe, although methane will continue to be emitted in the landfill after this 

cut-off point. 

57 

5.5.1.4 Energy Generated from Landfill Gas 

Energy is generated from a variable proportion of the recovered gas. At times of high flux, 

emissions can be greater than the capacity of the engines and thus a proportion of the gas 

must be flared. At times of low flux, i.e. towards the end of the site lifetime, emissions can be 

both too little for gas engines to function effectively. In such a situation, the usual practice of 

the landfill operator is to flare the gas. 

As part of the original landfill gas model, LQM carried out a survey of landfill operators to 

estimate the total flare capacity. 47 LQM noted within their analysis that: 

There are difficulties in ascertaining the actual volumes of LFG burnt as detailed 

records, if they exist at all, will be held by individual site operators. It is rare to find a 

flow stack with a flow measurement device installed, even though the capital cost of 

such a device is relatively small. 

LQM did not consider the amount of energy generated from LFG within their analysis, 

although they estimated the total flaring back-up capacity to be around 60% of generation 

capacity. It is usual for landfill operators to maximise energy generation as this represents a 

revenue stream. We assume within the current analysis that 40% of the recovered gas will be 

flared. Although it is acknowledged that there is some uncertainty here, the impact of this 

uncertainty (in terms of CO 2 equivalent offsets associated with energy generation from 

landfill) is relatively small. 

5.5.1.5 Oxidation of Landfill Gas 

Some of the uncaptured landfill gas will be oxidised as it passes through the cap to the 

surface, the proportion being dependent upon the nature of the cap. The USEPA suggests a 

range of 10% to 25%, with clay soils at the lower end of the range and top-soils being at the 

higher end. This reflects a figure proposed by Brown et al in 1999 in a study on behalf of what 

was then the DETR. 48 A similar value was proposed by the IPCC. The figure used within the 

revised Golders / LQM model (although LQM originally proposed a much higher value) was 

10%. 

Table 5-4 shows the key landfill gas parameters used in the modelling. Table 5-5 confirms the 

overall impacts per tonne of landfilled waste for the waste streams considered within this 

analysis. A simplified version of the waste composition outlined in Section 5.1 was used to 

estimate the residual waste impacts. We assume that the landfill uses 1.65 litres of diesel 

per tonne of waste treated, and that electricity usage is 1% of that generated, based on data 

by ERM. 49 

47 Land Quality Management (2003) Methane Emissions from Landfill sites in the UK, Final Report for Defra, 

January 2003 

48 K A Brown, A Smith, S J Burnley, D J V Campbell, K King and M J T Milton (1999) Methane Emissions from UK 

Landfills, A Report for the UK Department of the Environment, Transport and the Regions 


237) 


58 

Table 5-4: Landfill Gas Management 

Parameter 

Assumption 

Proportion of CH4 captured 75% 

Proportion of captured CH4 used for energy generation 60% 

Proportion of captured CH4 that is flared 40% 

Efficiency of electricity generation, landfill gas engine 35% 

Rate of oxidation of CH4 within the landfill cap 10% 

Table 5-5: Landfill Impacts per Tonne of Waste 

Material stream 

CH4 

generated, kg 

/ tonne 

CH4 

recovered, 

kg / tonne 

CH4 oxidised, 

kg / tonne 

Energy 

generated, 

kWh / tonne 

Paper / card 89.45 67.08 2.23 20.12 

Food 79.99 59.99 1.99 17.99 

Green 93.04 69.78 2.32 20.93 

Wood 59.23 44.42 1.48 13.32 

Residual waste 44.80 33.60 1.12 10.08 

Notes: 

Wood modelled based on misc comb; lifetime emissions (calculated over a 100 year period) 

Depending on method of treatment, between 12%-58% of the input waste treated using MBT 

facilities will be sent to landfill. Eunomia’s residual waste model Atropos includes a landfill 

component, which uses a slightly different methodology for calculating the impacts from 

landfilling to the Golders model. However, although our model includes differential decay 

rates for proteins, fats, sugar / starch as well as cellulose and hemi-cellulose, it categorises 

these materials into slow, medium and fast degrading carbon. Modifications made to the 

Golders model to include differential food and green waste therefore make it similar in 

approach to Eunomia model. 

In addition, the landfilled output from MBT processes is assumed to have undergone an 

aerobic stabilisation process, which will significantly reduce the subsequent biological activity 

occurring in landfill. The differences between the two models are therefore not considered to 

give rise to significant inconsistencies because the modelling of the stabilised material has 

not been carefully considered in the model given to us, and also, because the resulting 

emissions are much lower anyway as a consequence of the pre-treatment phase. 


59 

5.5.1.6 Effect of Changes on Landfill Baseline 

As a result of the additional modifications outlined previously, the emissions calculated within 

the current study are different to recent baseline projections for the impact of CH 4 from 

landfill submitted to the IPCC for the UK GHG inventory. Further revisions to the current LQM / 

Golders landfill model are to be made by AEA but these more recent updates were not 

available for incorporation within the current analysis. 50 

Our emissions estimates are different to the previous baseline emissions for the following 

reasons: 

‣ We assume a zero growth rate in waste arisings. The previous baseline model 

assumed a positive growth rate in waste arisings. However, it should be said that the 

rate of increase in tonnages being managed through means other than landfill is 

higher in the previous model so that the two effects work in opposite directions, 

reducing the magnitude of the differences between them; 

‣ We have altered the emissions parameters for the putrescible materials (see Table 5-3 

above); 

‣ Our waste categories are somewhat different to those in the previous baseline. We 

have had to ‘map’ these to the categories used in the previous baseline model, and 

whilst this has been done in a manner which seeks to respect the categories used, the 

quantitative data in the forward projections is rather different. In particular, the 

previous baseline projections were not based upon a firm and funded approach, and 

their elaboration pre-dated the increase in the landfill tax escalator. 

The previous baseline emissions projection for landfill is shown alongside our own in Table 

5-6. We show the emissions from Type 3 landfills and the emissions form all landfills. The 

Type 3 landfills are the ones which are currently being filled, with the balance of emissions 

coming from waste landfilled in past years. Our adjustments – in terms of quantities being 

landfilled and the emissions characteristics of waste being landfilled – lead to higher baseline 

emissions. These higher emissions are sustained, and the differentials increase, in 

percentage terms, from 1.7% to 5.1%. This increasing differential partly relates to the 

cumulative effect of changes in landfill emission potential on the waste landfilled over a 

period of years. 

50 Forward projections are, in any case, affected by estimates regarding the quantity of material being landfilled. 

The views as to how this might look in future have not been updated since the landfill tax increases were 

announced, so for a number of reasons, the model we were asked to use appeared to be in need of a fairly 

major overhaul. 


60 

Table 5-6: Comparison of Previous and Current Baseline Methane Emissions from Landfills 

PREVIOUS BASELINE 

Methane 

from Type 

3 Landfills 

Total Methane 

from Landfilled 

Waste (kt) 

Total CO2 

from 

Landfilled 


CURRENT BASELINE 

Methane 

from Type 

3 Landfills 

Total Methane 

from Landfilled 


Total CO2 

from 

Landfilled 


2008 425 913 19,175 441 928 19,497 

2009 449 905 19,012 471 928 19,478 

2010 469 896 18,822 495 923 19,373 

2011 487 887 18,617 516 915 19,219 

2012 503 876 18,401 537 911 19,121 

2013 517 866 18,189 556 905 19,002 

2014 530 856 17,984 572 898 18,865 

2015 542 847 17,786 586 891 18,714 

2016 553 838 17,598 598 883 18,550 

2017 563 829 17,413 609 875 18,376 

2018 572 821 17,239 617 867 18,197 

2019 579 812 17,062 625 858 18,015 

2020 587 805 16,901 631 849 17,831 

2021 593 798 16,750 636 840 17,644 

2022 600 791 16,609 640 831 17,455 

5.5.2 Incineration 

As agreed with CCC and Defra, the initial approach was largely based on that of ERM. 51 

Subsequent modifications to this approach were made with respect to the energy utilisation 

within the process. In addition, ERM only considered material specific impacts. 52 In order to 

properly consider treatment switches associated with other technologies such as MBT, it was 

also necessary within the current analysis to consider the emissions profile associated with a 

residual waste stream. 

In line with the approach taken by ERM the energy produced through combustion is based on 

the net calorific value of the material and CO 2 emissions are based on the material’s carbon 

content. Only fossil CO 2 emissions are included within the totals, the non-fossil carbon 

emissions being reported solely as an information item. Table 5-7 confirms the carbon 

content and net calorific values of the range of materials considered within the current 

analysis. 


237) 

52 A feature of life-cycle assessments is that they are not always encumbered by matters of cost. The ERM report 

considered matters on a material by material basis. However, in order to incinerate a specific material fraction, it 

does need to be segregated in the first place. If it is not segregated, it remains part of residual waste. Once 

materials are separated, it generally makes little sense to burn them from a financial perspective. Most 

segregated materials will have a market value, whereas few occasions will arise where waste can be combusted 

without a gate fee being paid. Whilst much time and effort was expended upon the pros and cons of recycling or 

burning paper in the ERM work, the discussion does need to be set in the context of the relative costs also. 


Table 5-7: Carbon Contents and Calorific Values for Materials Under Consideration 

61 

Total C 

Proportion of 

C that is non 

fossil 

Net calorific 

value, MJ per 

kg 

Typical 

moisture 

content 

Paper / card 31.9% 100% 11.0 20.0% 

Plastic (dense) 54.8% 24.9 18.0% 

Glass 0.0 2.0% 

Ferrous metal 0.0 3.0% 

Non ferrous metal 0.0 5.0% 

WEEE 0.0 3.0% 

Wood 43.8% 100% 16.8 40.0% 

Green waste 22.0% 100% 4.2 45.0% 

Food waste 13.5% 100% 3.5 71.0% 

All of the figures, with the exception of the carbon content of garden waste (which does not 

materially affect the bulk of the analysis owing to its biogenic nature), are taken from ERM’s 

analysis. We note in passing that: 

1. As regards carbon content, the figures for plastics look low. 53 Plastics generally have 

low moisture content and are composed, to a large extent, of hydrocarbons, with 

carbon constituting the bulk of the mass; 

2. The figure for garden waste was only marginally above that for food waste. We 

increased this to 22% from 17.2% to reflect the expected lower moisture content of 

garden waste; 54 and 

3. For wood, the figure for the net calorific value (NCV) seems high, whilst figures for 

garden and food waste seem quite low. Arguably, on a material specific basis, 

materials such as glass and metals might be assigned a negative value owing to the 

fact that they are essentially heated up before being captured in the bottom ash. The 

NCV of plastics also seems quite low. The NCV figures all materially affect the analysis 

owing to the fact that energy generation is associated with ‘credits’ in terms of avoided 

energy generation. 

Difficulties with the material specific approach are highlighted by considering impacts 

associated with the incineration of food waste, which has a moisture content of 71%. If only 

53 This does materially affect the analysis as the carbon is of fossil origin. 

54 The ERM study has a figure of 17% for the carbon content of manure / slurry which is greater than that for 

garden waste. This seems almost impossible given that most manures will have a moisture content between 70- 

85%. 


62 

food waste was incinerated, it might be considered that the energy required to evaporate the 

moisture is such that no net energy would be generated. Some Swedish operators consider it 

possible to recover much of the energy used to evaporate the moisture through condensation 

of the flue gas. In practice, food waste is usually incinerated only when mixed with other 

materials and so ‘the contribution of food waste’ to energy generation is considered. 55 

Residual waste impacts are based on carbon content and calorific values of the entire waste 

stream, using the composition outlined in Table 5-1. Table 5-8 outlines our assumptions for 

the residual waste stream. 

Table 5-8: Model Parameters for Incinerated Residual Waste 

Parameter 

Calorific value 

Assumption 

11,101 MJ / t 

% of C that is non-fossil 54% 

Notes: 

As was discussed in Section 5.1 both the calorific value and the proportion of fossil carbon will 

vary over time as recycling collections remove different materials in variable quantities. 

5.5.2.1 Energy Use at Incineration Facilities 

The energy usage of the plant depends upon the scale of plant, and the nature of the flue gas 

cleaning system. It also depends upon the presence or otherwise of: 

‣ Mechanical pre-treatment systems; 

‣ Incineration air preheating; 

‣ Equipment for re-heating of flue gas; 

‣ Waste water evaporation plant; 

‣ Flue gas treatment systems with high pressure drops (which demand more powerful 

fans); and 

‣ Changes in the LHV of input waste (necessitating use of fuel to maintain minimum 

combustion temperatures). 

ERM’s analysis suggests 3.9 kWh electricity is consumed per tonne of waste treated at an 

incinerator, with process diesel use indicated as 1.2 kg of per tonne of waste. 56 They arrived 

at these figures using Environment Agency data collected for the development of the waste 

model WRATE. However, they note in their report that: 

These process data were used as a substitute for all thermal treatment processes. In 

reality the ancillary requirements of each will differ, but within the context of the 

research the more important parameter relates to the energy conversion efficiency of 

the process. 

55 The reality from an operation perspective may be that food waste in residual waste helps keep the NCV of 

waste down, allowing for combustion of greater tonnages of material at a given site. 


237) 


63 

ERM’s energy consumption figures appear to be very low in comparison to values given in the 

wider literature. The Draft BREF note for Incineration gives figures of: 57 

‣ Electricity use 

62 kWh per tonne – 257 kWh per tonne, average 142 kWh per tonne 

‣ Heat demand 

72 GJ thermal energy per tonne – 3,366 GJ thermal energy per tonne, average 433 GJ 

thermal energy per tonne. 

These, in turn, are far higher than figures suggested in, for example, reports by Erichsen and 

Hauschild (46 kWh electricity per tonne) though this figure reflects only the operation of gas 

cleaning equipment. 58 VITO give the following consumption of energy for processes with and 

without SCR: 59 

‣ Natural gas: 7.2m 3 per tonne 

‣ Oil: 4kg per tonne (or 4.7 litres per tonne) 

‣ Electricity Use (per tonne): 80 kWh with SNCR, 85 kWh with SCR 

The reason for higher electricity use when using SCR is that the metal oxide bed (the catalyst) 

cannot be located at the point in the flue gas stream where the temperature is optimal, since 

this occurs prior to the removal of many contaminants that can poison the bed. Therefore, the 

SCR system must be placed just prior to the stack, and requires the 200°F flue gas to be 

reheated at additional electrical cost. 60 

CEWEP’s survey of 97 facilities during 2001-2004 suggested the average electricity used by 

incineration processes was 78 kWh per tonne of waste input. 61 We use the CEWEP figure for 

electricity consumption (which is close to VITO’s SNCR figure), and VITO’s figure for the 

natural gas and diesel usage within the current analysis. 

5.5.2.2 Efficiencies of Energy Generation 

The efficiency of generation of electricity by an incinerator may be quoted gross, or net of any 

energy used in the plant itself. The energy use in the plant depends partly upon the nature of 

the flue gas cleaning system used, but also upon a range of other factors. The relationship to 

flue gas cleaning is important since it seems likely that as standards for abatement have 

improved, so the energy used in achieving those levels of abatement has increased also. 

57 A BREF note is a note prepared by the Joint Research Centre of the European Commission to give guidance to 

Member States as to what is implied by ‘Best Available Techniques’ under the Directive on Integrated Pollution 

Prevention and Control. European Commission (2005) Integrated Pollution Prevention and Control, Draft 

Reference Document on the Best Available Techniques for Waste Incineration, Final Draft, May 2005. 

58 L. Hanne, L. Erichsen and M. Hauschild (2000) Technical Data for Waste Incineration - Background for 

Modeling of Product Specific Emissions in a Life-cycle Assessment Context, Elaborated as part of the EUREKA 

project EUROENVIRON 1296: LCAGAPS, sponsored by the Danish Agency for Industry and Trade, April 2000. 

59 VITO (2000) Vergelijking van Verwerkingsscenario’s voor Restfractie van HHA en Niet-specifiek Categorie II 

Bedrijfsafval, Final Report. 

60 Note that this is not always the case – see European Commission (2005) Integrated Pollution Prevention and 

Control, Draft Reference Document on the Best Available Techniques for Waste Incineration, Final Draft, May 

2005. 

61 I Riemann (2006) CEWEP Energy Report (Status 2001-2004): Results of Specific Data for Energy, Efficiency 

Rates and Coefficients, Plant Efficiency Factors and NCV of 97 European W-t-E Plants and Determination of the 

Main Energy Results, updated July 2006 


64 

ERM suggested gross efficiencies of 20-27% for conventional incineration with steam cycle 

electricity generation. 62 Fichtner quotes a ‘realistic range’ for net electrical efficiency of 19- 

27%. 63 The highest figures we have seen quoted are those quoted in the context of the 

Belvedere Inquiry where it was claimed that a net efficiency of 27% would be achieved. This 

was based around assumptions of a thermal efficiency of 84% and an electrical efficiency of 

35%. These are optimistic in the context of efficiencies currently achieved and are likely to be 

deliverable only at large operating scales. The Draft BREF note gave no case where the net 

export of electricity exceeded 18%. 64 

A survey of 25 incinerators across Europe generating electricity only reported a maximum 

gross energy efficiency of 27.9% with a weighted mean efficiency of 21.8% across the 25 

facilities (the mean net efficiency was given as 17.7%). 65 The current analysis uses a gross 

efficiency of 29%. Taking into account process energy use, this is in line with the upper end 

efficiencies quoted by ERM and Fichtner. This is a generous estimate of generation efficiency 

for electricity only facilities operating within the UK at present, but it is intended, in part, to 

reflect the level of performance expected in 2022. 

Whilst CEWEP supplies maximum values for heat and electricity generation for facilities 

operating in CHP mode, the survey data does not directly supply any information regarding 

the ratio of heat to electricity produced at each of the facilities concerned. Where thermal 

facilities are concerned, and where steam turbines are used to generate energy, there is a 

trade-off between the generation of electricity and the generation of heat. 

In its submission to the DTI as part of a review of the Renewables Obligation, ILEX assumed 

electrical output would be reduced at an approximate rate of 1 MW of electrical energy for 

every 4 MW of heat off-take. 66 Data from CEWEP gives the maximum heat output from 

surveyed facilities surveyed producing only heat as 92.7%, suggesting a theoretical ratio of 

3.3 MW heat for every MW of electricity. 67 However the maximum heat output for any of the 

surveyed facilities operating in CHP mode was 83.9%, whilst the maximum electricity output 

for the CHP facilities was 26.9%. This suggests a ratio of 3.1 MW heat for every MW of 

electricity. However, the German Waste Incineration Association suggests that the ratio 

should be 2.3 MW heat for each MW of electricity, based on the data from German facilities 

(the majority of which operate in CHP mode). 68 


237) 

63 Fichtner Consulting Engineers Limited (2004) The Viability Of Advanced Thermal Treatment Of MSW In The 

UK, ESTET, March 2004. 

64 European Commission (2005) Integrated Pollution Prevention and Control, Draft Reference Document on the 

Best Available Techniques for Waste Incineration, Final Draft, May 2005. 

65 I Riemann (2006) CEWEP Energy Report (Status 2001-2004): Results of Specific Data for Energy, Efficiency 

Rates and Coefficients, Plant Efficiency Factors and NCV of 97 European W-t-E Plants and Determination of the 

Main Energy Results, updated July 2006 

66 ILEX Energy Consulting (2005) Extending ROC Eligibility to Energy from Waste with CHP, Supplementary Report 

to the Department of Trade and Industry, September 2005 

67 This is simply calculated as the ratio of the maximum gross efficiency of heat generation relative to the 

maximum gross electrical generation efficiency of 29.7%. 

68 Available from www.itad.de 


65 

Our energy generation efficiencies for facilities operating in CHP mode are based on the 

average electricity production for CHP facilities surveyed by CEWEP, using a ratio of 3.1 MW 

heat per MW electricity to calculate the heat production. 

The efficiency with which metals are recovered from incineration facilities is modelled based 

on a survey of Dutch facilities. 69 These figures are lower than those given within ERM’s 

analysis (90% for ferrous, 60% for non-ferrous). However, the higher figures are unlikely to be 

achieved using typical dry separation techniques. 

N 2 O emissions are modelled based on previous research undertaken by Eunomia on behalf of 

WRAP. 70 ERM suggested a value of 0.0057 kg per tonne of waste incinerated. The 

considerable uncertainty with respect to these emissions is acknowledged within the EU BREF 

note, which provided a range of 5.5 – 66 g N 2 O per tonne of waste treated by the facility. We 

use the mid point of these values within the current analysis. 

Table 5-9 summarises the assumptions for incineration discussed previously. 

Table 5-9: Assumptions for Incineration 

Parameter 

Assumption 

Gross electrical efficiency (electricity only mode) 29% 

Gross electrical efficiency (CHP mode) 18% 

Gross heat efficiency (CHP mode) 50% 

Electricity demand for flue gas cleaning 

Diesel use by process 

Use of natural gas by process 

78 kWh / t input 

4.8 l / t input 

7.2 m 3 / t input 

Recycling of bottom ash 50% 

CH4 emissions from process 

N2O emissions from process 

0 kg CH4 / t 

0.04 kg N2O / t 

Recovery rate for ferrous metals 70% 

Recovery rate for non-ferrous metals 30% 

5.5.3 MBT 

Our analysis assumes essentially three types of biological treatment process, with similar 

equipment being used in two of these processes. The following types of facilities are 

considered: 

69 L. Muchova and .P Rem (2008) Wet or Dry Separation: Management of Bottom Ash in Europe, Waste 

Management World Magazine, 9(3) 

70 Eunomia (2007) Emissions of Nitrous Oxide from Waste Treatment Processes, Report to WRAP, July 2007 


66 

1. Aerobic stabilisation system. The stabilised output is assumed to be either: 

a. Sent to landfill or 

b. Used for land remediation / recovery projects. 

2. An aerobic biodrying system producing a Solid Recovered Fuel (SRF) with the reject 

stream sent to landfill (after undergoing an aerobic stabilisation process). The SRF is 

assumed to generate energy via: 

a. A gasification facility using steam turbine (in CHP mode); 

b. A gasification facility using a gas engine (in CHP mode); 

c. A cement kiln displacing coal as fuel; 

d. A power station producing electricity (co-firing) 

e. A dedicated thermal facility. 

‣ Systems combining aerobic and anaerobic treatments. An anaerobic process is used 

to produce biogas, followed by an aerobic process which produces a stabilised output 

that can be sent to landfill. The biogas can be used to generate energy, using either: 

a. A gas engine; or 

b. A stationary fuel cell (MCFC) considered as an option beyond 2022. 

Impacts associated with MBT facilities are calculated using Eunomia’s model Atropos. 

We used the proportion of MBT treatments occurring in 2022 as the basis for calculating MBT 

impacts in baseline, as outlined in Table 5-10. 

Table 5-10: MBT Treatments proportion in Baseline 

Parameter 

Assumption 

Stabilisation process, output to landfill 55% 

Biodrying producing SRF, SRF to cement kiln displacing coal as fuel 7% 

Biodrying producing SRF, SRF to power station 7% 

Biodrying producing SRF, SRF to dedicated facility 32% 

All MBT facilities produce some reject material, assumed within our model to go through an 

aerobic stabilisation process prior to being landfilled. 

The landfill component of our MBT model has been adjusted to reflect the assumptions 

regarding the capture of landfill gas detailed in Table 5-4. This assumes that much of the gas 

is captured and either flared or used to generate energy. In dedicated, ‘biostabilised’ landfill 

cells such as exist elsewhere in Europe, lower rates of gas production will occur. This lower 

rate of flux is likely to be such that a far greater proportion of the fugitive CH 4 can be oxidised 

through the cap. In addition, little energy generation is likely to occur at low rates of flux (as is 

discussed in Section 5.5.1). There are no data available which provides analysis of oxidation 

rates at such landfills in Germany or Austria, although anecdotal evidence suggests that this 

may be very high indeed for wastes which have been ‘biostabilised’ to meet the relevant 

threshold limits in these Member States, and where (as a result) the flux of methane at the 

surface of the landfill is very low. Our model may therefore overstate the impact of stabilised 

material within landfill, particularly as the volume of stabilised material produced increases. 


67 

The impact is unlikely to be significant in early years where the volume of stabilised material 

is relatively small. 

The biological phase of MBT requires the decay of materials to be considered using a similar 

approach to that of degradation within landfill. This is discussed in the following Sections 

5.5.3.1 to 5.5.3.7. 

5.5.3.1 Aerobic Stabilisation Systems 

The approach for modelling the impacts of stabilisation processes draws upon work by 

Eunomia on behalf of WRAP, which was based upon a raft of published research. 71 The body 

of research included work by Baky and Eriksson, Sonneson, and Komilis and Ham, all of 

whom investigated the link between the biochemical composition of the waste and the 

release of CO 2 within composting processes. This research, together with data sourced from 

technology suppliers, was used to model the degradation of carbon fractions within our 

model. 

Table 5-11 outlines the key assumptions within the model for stabilisation processes. 

Table 5-11: Assumptions for Stabilisation Process 

Parameter 

Residence time 

Electricity requirement 




Assumption 

10 weeks 


1 l / t input 

0.01 kg / t input 



Recovery rate for non ferrous metals 90% 

Recovery rate for plastics 70% 

Whilst the stabilised output may be used in land remediation projects, it is more likely to be 

landfilled. Both options are considered within our analysis. Table 5-12 outlines key 

71 K Schleiss (1999) Grüngutbewirtschaftung im Kanton Zürich aus betriebswirtschlaftlicher und ökologischer 

Sicht: Situationsanalyse, Szenarioanalyse, ökonomische und ökologische Bewertung sowie Synthese mit MAUT, 

Dissertation ETH No 13,746, 1999; Eunomia Research & Consulting, Scuola Agraria del Parco di Monza, HDRA 

Consultants, ZREU and LDK ECO on behalf of ECOTEC Research & Consulting (2002) Economic Analysis of 

Options for Managing Biodegradable Municipal Waste, Final Report to the European Commission; D. P. Komilis 

and R. K. Ham (2004) Life-Cycle Inventory of Municipal Solid Waste and Yard Waste Windrow Composting in the 

United States, Journal of Environmental Engineering, Vol. 130, No. 11, November 1, 2004, pp.1390-1400; A. 

Baky and O. Eriksson (2003) Systems Analysis of Organic Waste Management in Denmark, Environmental 

Project No. 822, Copenhagen: Danish EPA; U. Sonesson (1996) Modelling of the Compost and Transport 

Process in the ORWARE Simulation Model, Report 214, Swedish University of Agricultural Sciences (SLU), 

Department of Agricultural Engineering, Uppsala Sweden 


68 

assumptions within our model for land remediation. Our assumptions for landfill of stabilised 

material are discussed in Section 5.5.3. 

Table 5-12: Assumptions for Land Remediation 

Parameter 

Assumption 

Starting content of organic matter (weight for weight) 2% 

Mineralisation rate of readily available organic matter 20% 

Mineralisation rate of stable humus 1% 

Organic matter from compost that becomes humus 25% 

5.5.3.2 Aerobic Biodrying Systems 

Biodrying systems involve the application of intensive heat to the waste to ensure the removal 

of moisture prior to it being used as fuel. During this process degradation of some of the 

carbon fractions will occur as a result of the increase in temperature but the amount of 

degradation is relatively limited in comparison that occurring during aerobic decomposition 

(stabilisation) processes. Biodrying processes are modelled using an analysis of data from 

technology suppliers. 

The central aim of biodrying processes is to produce a fuel. A reject stream is also produced, 

which is assumed to be stabilised before being sent to landfill. Stabilisation is discussed in 

more detail in Section 5.5.3.1. 

Table 5-13 outlines key assumptions used to model the biodrying phase. 

Table 5-13: Assumed Used for Modelling Biodrying Phase 

Parameter 

Residence time in biodrying phase 

Residence time of rejects in maturation (stabilisation) phase 

Electricity requirement 1 

Diesel use by process 1 

CH4 emissions from process 2 

N20 emissions from process 2 

Assumption 

12 days 

7 weeks 







Recovery rates for glass (sent for aggregates production) 70% 

Notes: 

1. Per tonne input to the MBT facility. 

2. Per tonne input to the biodrying process. 


Our assumptions regarding the nature of the SRF produced are detailed in Table 5-14. 

Table 5-14: Model Parameters for Residual Waste to SRF 

69 

Parameter 

Amount of SRF produced by biodrying process 

Calorific value of SRF 

Assumption 

0.48 t / t input 

7,174 MJ / tonne of 

waste input 

% of C that is non-fossil 66% 

The different uses for this fuel are discussed in the sections that follow. 

5.5.3.3 Gasification 

Gasification is a far newer technology than incineration for the treatment or disposal of 

residual solid waste. It involves the partial oxidation of waste. This means that oxygen is 

added but the amounts are not sufficient to allow the fuel to be completely oxidised and for 

full combustion to occur. The temperatures employed are typically above 750 ºC. The main 

product is a syngas, which contains carbon monoxide, hydrogen and methane. The CV of this 

syngas will depend upon the composition of the input waste to the gasifier. The other main 

product produced by gasification is a solid, non-combustible ‘char’. 

Gasification has received significant recent attention in the municipal waste market as a 

potential alternative to incineration, but thus far only two commercial-scale facilities have 

planning permission and none are currently operating only on MSW or MSW-derived 

feedstocks in the UK. There are, however, a handful of facilities operating at commercial 

scale within the EU, although these are not always treating a mixed waste stream, along with 

many high-temperature facilities in Japan. In many cases, gasification technologies are 

planned to treat refuse-derived fuels (RDF) from MBT or autoclave facilities, as is the case for 

the facility planned for East London Waste Authority. 

Performance data is therefore perhaps less reliable than that for incineration. As a result, we 

have based our central estimates of efficiencies on information provided only by technology 

providers which have commercial-scale facilities already operating in other EU Member 

States. Once more, our assumptions are based on mass flows and energy balances quoted by 

typical technology providers. It is assumed that should the input waste undergo more 

rudimentary fuel preparation, process conditions may not be unduly different (in terms of 

energy use). 


70 

Table 5-15: Assumptions for Gasification Using Steam Turbine 

Parameter 

Calorific value of syngas 1 

Assumption 

5,881 MJ / tonne 

waste input 

Net electrical efficiency using steam turbine 1 20% 

Heat efficiency 2 48% 

Electricity demand 






Carbon content of char 10% 

Biodegradable carbon content of char 0% 

Notes: 

1. It should be noted that the efficiencies quoted relate to the power generation element 

of the process only 

2. The gasifier is assumed to be operating in CHP mode. 

Energy generation performance improves if a gas engine is used. Our assumptions used to 

model the performance of a gasifier using a gas engine are outlined in Table 5-16. 

Table 5-16: Assumptions for Gasification Using Gas Engine 

Parameter 

Assumption 

Net electrical efficiency using gas engine 1 37% 

Heat efficiency 2 36% 

Electricity demand for flue gas cleaning 



100 kWh/t input 



Carbon content of char 10% 

Biodegradable carbon content of char 0% 

Notes: 

1. It should be noted that the efficiencies quoted relate to the power generation (gas 

engine) element of the process only. 

The gas engine is assumed to be operating in CHP mode. 


71 

5.5.3.4 Cement Kiln 

In the case where SRF is sent to a cement kiln, we have assumed coal is the displaced fuel. 

The SRF replaces coal but the efficiency of replacement is estimated at 90%. Key parameters 

are shown in Table 5-17. 

Table 5-17: Assumptions for Use of SRF at Cement Kiln 

Parameter 

Avoided emissions from use of coal to generate heat 

Assumption 

0.37 kg CO2 equ / kWh 

Efficiency of energy conversion at cement kiln 90% 





Notes: 

We assume that all the heat generated can be used by the facility (i.e. there is no assumption 

with regard to heat load). 

Avoided emissions based on CCC assumption for coal, but including additional pre-combustion 

emissions. 

5.5.3.5 Power Station 

The SRF can be used to offset fuel burnt at a power station to produce electrical energy where 

efficiencies of generation are higher than those obtained by steam turbines. Table 5-18 

confirms our assumptions used to model the use of SRF at a power station. 

Table 5-18: Use of SRF at a Power Station 

Parameter 

Assumption 

Efficiency of electricity generation 38% 





5.5.3.6 Dedicated On-site Facility 

A further option considers the use of the SRF at a dedicated facility generating electricity 

using a steam turbine. Whilst the efficiency of electricity generation will be similar to that of 

that generated by an incinerator generating solely electricity, the fuel being burnt is of a lower 

moisture content. We have allowed for slightly higher efficiencies reflecting the quality of the 

SRF. The assumptions regarding the parasitic load are as for the incinerator. 


72 

Table 5-19: Use of SRF at a Dedicated On-site Facility 

Parameter 

Assumption 

Gross efficiency of electricity generation 31% 





5.5.3.7 Systems Combining Anaerobic and Aerobic processes 

Anaerobic Digestion (AD) systems can be used to treat both residual and source separated 

organic material. The anaerobic digestion of source separated organic waste is discussed in 

Section 5.7.1. 

Eunomia analysed three approaches to calculating the biogas generated by AD facilities 

during the development of the Atropos model: 

‣ The approach used in the Swedish ORWARE model, assuming a hydraulic retention 

time of 18 days; 72 

‣ An approach based on the work of Chavez-Vasquez and Bagley; 73 and 

‣ An approach based on VS content and using assumptions concerning the rate of VS 

destruction and the rate of conversion of VS into methane from Cecchi et al. 74 

These results were compared with data from suppliers which we gathered in the context of 

recent work in Northern Ireland. 75 The first two approaches gave, in our view, values which 

were at the higher end of the likely range (though they are plausible). The last of the above 

methods – in some ways, the most simple - gives results which most closely resemble what is 

quoted by technology suppliers. The theoretical approach taken by Cecchi et al was therefore 

used to derive the degradation rates used when modelling the anaerobic digestion processes. 

The emissions from anaerobic digestion vary with the degree to which digesters approach a 

theoretical maximum biogas yield from the input materials. This theoretical yield depends 

upon the efficiency of the process, the retention time within the digester; and for some 

processes, the difference between the hydraulic retention time and the solid retention time 

may be important. 

72 M. Dalemo (1997). The ORWARE Simulation Model - Anaerobic Digestion and Sewage Plant Sub-models. 

Licentiate thesis. Swedish University of Agricultural Sciences, SLU, Uppsala. M. Dalemo. (1999). Environmental 

Systems Analysis of Organic Waste Management. The ORWARE Model and the Sewage Plant and Anaerobic 

Digestion Submodels. Ph D Thesis. Swedish University of Agricultural Sciences, Uppsala 

73 M. Chavez-Vasquez and D. Bagley (2002) Evaluation of the Performance of Different Anaerobic Digestion 

Technologies for Solid Waste Treatment, Paper Presented to CSCE / EWRI of ASCE Environmental Engineering 

Conference, Niagara (Canada) 2002 

74 F. Cecchi, P. Traverso, P. Pavan, D. Bolzonella and L. Innocenti (2003) Characteristics of the OFMSW and 

Behaviour of the Anaerobic Digestion Process, in J. Mata-Alvarez (ed) (2003) Biomethanization of the Organic 

Fraction of Municipal Solid Wastes, London: IWA Publishing, pp.141-179. 

75 Eunomia (2004) Feasibility Study Concerning Anaerobic Digestion in Northern Ireland, Final Report for Bryson 

House, ARENA Network and NI2000 


The reject stream from the AD process is assumed to be stabilised before being sent to 

landfill. Stabilisation is discussed in Section 5.5.3.1 

Table 5-20: AD Process Assumptions 

73 

Parameter 

Residence in digester 

Maturation time of reject stream and organic output 



Assumption 

14 days 

5 weeks 


1 l / t input 

Recovery rate for dense plastic 70% 

Recovery rate for glass 20% 



A variety of uses for the biogas are possible, including: 

a. Using it within an on-site gas engine to generate electricity and heat; 

b. Using it as a source of hydrogen, which allows for the generation of electricity 

and heat off-site through a Molten Carbonate Fuel Cell (MCFC): 

c. Upgrading the gas and using this as a vehicle fuel to displace diesel. 

The first two uses are considered within our assessment of MBT switches. We consider the 

first and the third as suitable options for the biogas that is generated from the AD of food 

waste, discussed in more detail in Section 5.7.1. 

On-site Generation Using a Gas Engine 

The biogas output from AD systems is most frequently used on-site to generate energy using a 

gas engine. Where gas engines are concerned, the generation of heat incurs little penalty in 

terms of electricity generation, and the majority of facilities operate CHP engines, partly to 

ensure the provision of free heat which is needed to keep the feedstock at the required 

(mesophilic or thermophilic) temperature, as well as providing heat for hygienisation of the 

feedstock in the wake of the EU Animal-by Products Regulations. Table 5-21 outlines our 

assumptions used to model the performance of the gas engine at AD facilities. 

Table 5-21: Biogas to Gas Engine for Energy Generation 

Parameter 

Assumption 

Efficiency of gas engine for electricity generation 1 38% 

Efficiency of gas engine for heat generation 1 40% 

CH4 loss to atmosphere 0.05% 

Notes: 

The gas engine is assumed to be operating in CHP mode. 


74 

MCFC 

An alternative use for the biogas is as a source of hydrogen for energy generation using a 

stationary fuel cell, of which the MCFC is one type. This is considered as an abatement option 

for the period beyond 2022 out to 2050. 

For stationary applications, following biogas upgrading and purification, a steam reforming 

process takes place internally, within the fuel cell. In this configuration, most of the GHG 

emissions come from the fuel cell itself. 

Figure 5-1: Hydrogen Use in Stationary Fuel Cells 

Biogas 

Biogas 

Purification 

Steam 

Reforming 

/ Gas Shift 

Fuel Cell 

Note: Many new stationary fuel cells contain the steam reforming process internally 

Table 5-22 outlines our assumptions regarding for modelling the stationery fuel cell. 

Table 5-22: Biogas to Stationery Fuel Cell for Energy Generation 

Parameter 

Assumption 

Energy demand for biogas upgrading prior to entry into MCFC 0 1 

Efficiency of conversion of upgraded biogas to useful energy in a 

stationary MCFC 2 

Emissions of CO2 from a stationary MCFC (using upgraded biogas) for 

electrical output 

Efficiency of external steam reforming process for biogas (expressed in 

terms of conversion of energy in methane to hydrogen energy) 

Total emissions from steam reforming process for biogas (including both 

energy use and process losses) 

47% electricity 

23% heat 

300 g CO2 equ / 

kWh 

78% 

74 g CO2 equ /MJ 

fuel produced 

Separation efficiency of gas filtration process 90% 

Notes: 

1. Whilst this is acknowledged here, the lack of reliable data is such that we have not been 

able to include any emissions data within our modelling. However, this requirement is 

likely to be minimal in the context of other elements of this treatment. 

2. Assumed to be operating in CHP mode. 

5.5.4 Energy Generation from Wood 

We consider energy generation from wood could occur through two different treatment 

routes: 


75 

‣ Contaminated and surface treated waste wood is assumed to be burnt in a 

conventional incinerator as described in Section 5.5.2; 

‣ Uncontaminated waste wood (such as off-cuts) is assumed to be similar to virgin wood 

and therefore burnt in a dedicated combustion facility. 76 

Data from ERM formed the basis for our assumptions regarding the incineration of waste 

wood. ERM suggest a net calorific value for wood of 18.3 MJ / kg, which seems high 

compared to data from other literature sources – particular when combined with a moisture 

content of 40%. We have therefore taken the calorific value for wood from the figure supplied 

by the CCC within their control panel dataset. 77 

The facility is assumed to generate electricity from wood, following the emphasis given in the 

UK Biomass Strategy published in 2007. Other assumptions are based on data from ExternE 

which surveyed a range of existing biomass facilities across Europe. 78 

Table 5-23: Energy Generation from Wood – Dedicated Facility 

Parameter 

Assumption 

Carbon content of ash 1% 

Gross calorific value 




Diesel used by process 

11.90 MJ / kg wood 

0.07 kg / t wood 

0.01 kg / t wood 

0.1 kWh / t wood 

0.5 l / t wood 

Efficiency of conversion to electricity 28% 

5.6 Dry Recycling 

In examining the impact of different levels of recycling, our analysis focuses on the differential 

emissions impacts occurring at the point of treating or reprocessing these materials. As was 

confirmed in Section 5.2, whilst there will also be differences in the emissions resulting from 

76 Contaminated wood is treated as waste and must therefore be burnt in a facility with appropriate pollution 

controls. If it can be demonstrated that the wood fuel is not contaminated, it can be used to fuel a dedicated 

facility, such as those modelled within the current section. 

77 Whilst the ERM figure seems high, the CCC control panel figure looks rather too low. However, as a net 

calorific value, the ERM figure exceeds all values for waste wood. The CCC figure is much closer to what would 

be expected of waste wood unless it was clear that the moisture content, as received, was in single figures (in 

percentage terms). Where waste wood has a comparable moisture content to that assumed by ERM, reported 

lower heating values, as received, are 10.7MJ/kg at 22.5% moisture or 9.1MJ/kg at 42.9% moisture (data from 

laboratories of the Energy Research Centre of the Netherlands). These are closer to the CCC figures. The reality 

is that much depends upon the purity and moisture content of the wood waste stream, but a net calorific value 

of the level assumed by ERM is not possible at the moisture content which was being associated with the 

material. 

78 ExternE (1999) Externalities of Energy, Volume 10, National Implementation, prepared by CIEMAT for the 

European Commission, Belgium 


76 

transportation as a result of these system changes, such differences are likely to be relatively 

small, and will vary considerably from location to location. 

In producing virgin products (i.e. products made from non-recycled materials) it is inevitable 

that raw materials will be required. These raw materials may be mined from the ground or 

extracted from forests (in the case of paper / wood manufacture). Additional resources, in the 

form of the energy used for the mining or paper manufacture, for example, will also be 

required, resulting in GHG emissions. 

If a product is manufactured from recycled materials, the requirement for raw materials is 

diminished, and this typically reduces the demand for energy associated with mining or 

extraction processes, and thus also the associated GHG emissions. GHG emissions are 

therefore said to have been ‘avoided’ as a result of the use of the recycled materials in 

manufacturing processes. 

A typical LCA approach will consider all impacts associated with these avoided emissions 

irrespective of their location. However, within the context of compiling national GHG 

inventories for the IPCC, only those impacts occurring within the geographical boundary of a 

specific country are assumed relevant. It therefore becomes important to consider where the 

extraction of raw materials and manufacture of virgin products occurs, and, for goods 

produced from the re-processing of materials collected by recycling, the location of the reprocessing 

facility. The geographical location of a manufacturing or re-processing facility will 

also have an impact on its emissions, particularly with regard to the carbon intensity of the 

energy used in the plant. 

The current analysis considers impacts upon the basis of one additional tonne of recycling - 

the so-called “marginal” impact. In practice, what this implies is that in order for the analysis 

to be ‘correct’ from the perspective of reporting emissions to the IPCC, we should: 

a) seek to understand the location of the source of primary material being avoided 

when material is recycled (the displaced marginal source); and 

b) seek to understand the location of the destination of the secondary material to 

which the additional material is being sent. 

The correct accounting process would then be to: 

a) subtract emissions associated with primary production from the inventory only 

if the recycling leads to reduced production of primary materials within the UK; 

and 

b) increase emissions associated with secondary production if the recycling is 

believed to increase UK production of secondary materials. 

It should be noted, therefore, that it is possible that recycling of a material leads to increases 

in UK emissions as reported to IPCC even where the net effect on climate change is to reduce 

global emissions of GHGs. This would be where increases in domestic reprocessing reduce 

the need for imports of primary raw materials. 

Recent experience in the UK appears to indicate that a growing proportion of materials 

collected for recycling are sent abroad for reprocessing. At the same time, there has been 

some growth in domestic reprocessing capacity in some materials, but this has been dwarfed, 

by and large, by the increase in materials being exported for recycling as collected quantities 

have increased. 

In the context of this study, it was felt that rather than trying to make estimates as to exactly 

how the IPCC inventory would be affected by incremental increases in recycling of different 

materials, the approach taken would be as follows: 


77 

1. Assume that increases / decreases in the capture of dry recyclables have no bearing 

on the UK inventories reported to the IPCC other than through transport emissions 

incurred in moving materials to ports. The exception is wood, for which the impacts are 

relatively minor, and where the material tends not to be exported; and 

2. Under the Global scope, assume that recycling is attributed the full benefit, in climate 

change terms, of the activity, related to the benefits realised from the reduction in 

emissions associated with producing material from secondary materials, as opposed 

to primary raw materials. 

Strictly speaking, the former assumption is not correct. However, making the assumptions in 

this way allows a fairly clear and unambiguous comparison of the case where recycling is 

credited with emissions savings in line with the global effects which flow from it (the global 

scope) and the case where no credit or debit is registered. 

The methodology used to model the impact of recycling varies under the different MACC 

scopes. The IPCC scope methodology is described in Section 5.6.1, whilst that used for the 

Global scope is described in Section 5.6.2. 

5.6.1 Impacts Considered under the IPCC Scope 

Here, as described above, we effectively assume that at the margin, dry recyclables will be reprocessed 

overseas with the exception of wood. We further assume that the manufacture of 

virgin products also occurs overseas, including the extraction of the raw materials used within 

the manufacturing process. Under the IPCC scope, with the exception of emissions associated 

with the transportation of collected recyclables, no environmental impact is therefore 

attributable within the UK with regards to either the manufacture of virgin products or the 

reprocessing of recycled material. 

Whilst an examination of the majority of transportation impacts is excluded (as was discussed 

in Section 5.2), we include an estimate of the impact of transporting recyclables to a port 

prior to their shipment overseas within our analysis. We do not include the transport 

emissions associated with shipping the material overseas, as these impacts are not 

considered within the national inventory at present. 

Table 5-24: Transportation of Recyclables Overseas (National Impact) 

Parameter 

Average distance, national transport to dock 

Emissions per t per km, road freight 

Total impact, transport to port 

Assumption 

150 km 

0.1 kg CO2 / t / km 

15 kg CO2 / t material 

Wood is assumed to be recycled within the UK and not re-processed overseas, with 

environmental impacts described as per Section 5.6.2.6. 

5.6.2 Impacts Considered Under the Global Scope 

Here the typical LCA approach is used, with all impacts considered irrespective of where they 

occur. 

As under the IPCC scope, we assume a transport related impact associated with moving 

materials to ports. It is likely that at least some of the impact associated with transporting 

the recycled materials has already been included within many of the analyses used to 

evaluate the life cycle impacts of recycling these materials (see below), but there is 


78 

insufficient detail in the majority of studies to identify, and so deduct, these amounts. The 

impact upon the results is unlikely to be significant, given the relatively small influence of 

collection and transport upon the overall emissions totals (and the fact that the potential 

range in emissions used for the benefits from recycling is greater than the emissions from 

transport). 

Figures are given in terms of avoided CO 2 equivalent emissions per tonne of material 

recycled. In many cases, impacts are assumed to be calculated with reference to an 

alternative disposal route. Whilst the alternative disposal route is explicitly stated within some 

sources, it is not so clear in others. The default disposal route is assumed to be landfill in 

each case where the analysis does not concentrate solely on the benefits of secondary 

materials reprocessing relative to primary materials extraction and processing. In using the 

figures discussed below, therefore, we have adjusted them to reduce the benefits associated 

with recycling by the equivalent emissions associated with landfill the different materials (as 

calculated in 5.5.1). 

The GHG abatement (or otherwise) associated with recycling the following materials are 

considered: 


‣ Dense plastic; 

‣ Glass; 

‣ Steel; 

‣ Aluminium; 

‣ Wood; and 

‣ WEEE. 

We use data taken from a range of recent studies - including work undertaken within the UK, 

Europe and the US - as a basis for modelling the environmental impacts associated with 

recycling. 

The principle UK-based sources considered within our analysis are: 

‣ ERM (2006a) Carbon Balances and Energy Impacts of the Management of UK Wastes, 

December 2006; 

‣ ERM (2006b) Impact of Energy from Waste and Recycling Policy on UK Greenhouse 

Gas Emissions, Final Report for Defra, January 2006; 

‣ WRAP (2006) Environmental Benefits of Recycling: An International Review of Life 

cycle Comparisons for Key Materials in the UK Recycling Sector, Banbury: Oxon, WRAP, 

May 2006. 

‣ The WRAP analysis reviewed a number of studies, incorporating results from the UK, 

Europe and the US. 

The relevant European and American sources are those by: 

‣ AEA Technology (2001) Waste Management Options and Climate Change: Final 

Report, European Commission: DG Environment, July 2001; 

‣ USEPA (2002) Solid Waste Management and Greenhouse Gases: A Life-Cycle 

Assessment of Emissions and Sinks, EPA530-R-02-006, May 2002. 

‣ Of these, the AEA report also reviewed data from a variety of European studies. 


Sections 5.6.2.1 to 5.6.2.7 discuss the range of values for each of the material provided by 

the various literature source and confirm the value chosen for the current analysis. A 

summary of the values used is provided in Section 5.6.2.8. 

79 

5.6.2.1 Paper and Card 

WRAP’s (2006) review of life cycle assessments indicated that for paper and cardboard, the 

benefits of recycling were 1.4 tonnes CO 2 equivalent per tonne of material recycled where the 

disposal route being avoided was landfill. 

The AEA (2001) report reviewed the estimates associated with a number of studies. For 

paper, these are shown below. 

Table 5-25: Life-cycle Emissions for Paper Production (AEA) 

Paper Type 

Source 

Production emissions (kg CO2 equ / t paper) 

Virgin Materials 

Recycled Materials 

Newsprint Swedish study 1,755 849 

Newsprint US study 2,222 1,535 

Newsprint BUWAL database 291 (68% recycled) 

Kraft paper 

unbleached 

BUWAL database 1,080 633 

(Swiss kraft) 

Graphic paper 

BUWAL database 

436 (uncoated) 

730 (coated) 

586 with deinking 380 

without deinking 

Corrugated board 

BUWAL database 

644 

(25% recycled) 

522-556 

Source: AEA Technology (2001) Waste Management Options and Climate Change: Final Report, European 

Commission: DG Environment, July 2001. 

The report used the Swedish study, which converted energy use into emissions using EU 

average power mix. The study assumed that 1 tonne of recycled paper could produce 700kg 

of recycled newsprint. Actually, this estimate may be quite low for newsprint, and is more 

representative of other paper grades, but since the study was looking at other forms of paper 

and card (using ‘paper’ as one category), 70% could be a reasonable figure to use. As such, 

the estimated GHG savings associated with recycling paper were 0.7 x 906 kg CO 2 equivalent 

per tonne, or 0.634 tonnes CO 2 equivalent per tonne of paper. 

These savings are much lower than are estimated by the USEPA (2002). However, the USEPA 

modelling included some quite sophisticated modelling of the US forest sector, and the 

implications of not harvesting forests: 79 

When paper and wood products are recycled or source reduced, trees that would 

otherwise be harvested are left standing. In the short term, this reduction in 

harvesting results in a larger quantity of carbon remaining sequestered, because the 


Sinks, EPA530-R-02-006, May 2002. 


80 

standing trees continue to store carbon, whereas paper and wood product 

manufacture and use tends to release carbon. In the long term, some of the shortterm 

benefits disappear as market forces result in less planting of new managed 

forests than would otherwise occur, so that there is comparatively less forest acreage 

in trees that are growing rapidly (and thus sequestering carbon rapidly). 

Considering the effect of forest carbon sequestration on U.S. net GHG emissions, it 

was clear that a thorough examination was warranted for this study. The complexity 

and long time frame of carbon sequestration in forests, coupled with the importance 

of market dynamics that determine land use, dictated the use of best available 

models. 

Close inspection shows that these are extremely important in the modelling outcomes, albeit 

(as the study itself admits) subject to considerable uncertainty. Importantly, the study claims 

that these benefits are potentially transferable to other countries: 80 

Although the goal of this analysis is to estimate the impact of paper recycling and 

source reduction on GHG emissions in the United States, the actual effects would 

occur in Canada and other countries as well. 

The caveats under which these sequestration effects might be deemed a) accurate and b) 

directly transferable are quite numerous (and the reader is directed to the study for more 

detailed discussion). Suffice to say that the effect is potentially important, being far greater 

than the total savings estimated by the AEA report. 

The enormous significance of the sequestration effect in the total outcomes can be 

appreciated by reference to Table 5-26. These figures take into account the loss rates of 

material in the recovery process and in the production process. It can be seen that for 

newspaper, the recycled input credit – which represents GHGs saved through using recovered 

fibre as opposed to virgin materials - is close to the estimate used by AEA. The enormous 

difference in the reported outcomes is entirely associated with the sequestration effects 

modelled in the US study. It is also noteworthy that the relative performance of the different 

materials recovered in respect of the credits for using recycled inputs tends to reflect what 

was suggested in the studies reviewed by AEA. For example, the credit for corrugated 

cardboard is less than the GHGs emitted in using virgin materials, whilst the AEA review 

suggests a much reduced credit relative to virgin material production. 

Other studies which have reported on GHG emissions associated with recycling include some 

ecological footprint studies. These have generally relied upon a database reportedly held by 

the Stockholm Environment Institute-York. It is possible from some such studies to estimate 

the implied CO 2 savings associated with recycling. For example, in the report Taking Stock – 

Managing Our Impact: Material Flow Analysis and Ecological Footprint of Waste in the South 

East, the analysis suggests that for paper and card, the embodied energy lost when the 

material is landfilled is equivalent to 3.426 tonnes per tonne of material. Netting off the CO 2 

emissions associated with recycling (including transport) reported in the study gives a figure 

of 1.508 tonnes CO 2 avoided through the use of recycled material. This would appear to be 

high given that the SEI database relates to ‘an embodied energy database of over 600 

products’ (i.e., it does not appear to account for sequestration effects). 


Sinks, EPA530-R-02-006, May 2002. 


81 

Table 5-26: GHG Emissions for Recycling (MTCO 2 equ / tonne of material recovered) 

Material 

(a) (b) (c) (d) (e) (f) 

Recycled 

Input 

Credit*: 

Process 

Energy 

Recycled 

Input Credit*: 

Transportation 

Energy 

Recycled 

Input 

Credit*: 

Process 

Non- 

Energy 

Forest 

Carbon 

Sequestration 

(f = b + c + d 

+ e) 

GHG 

Reductions 

From Using 

Recycled 

Inputs Instead 

of Virgin 

Inputs 

Corrugated Cardboard 0.147 -0.037 0.000 -2.677 -2.603 

Magazines/Third-class 

Mail 

0.000 0.000 0.000 -2.677 -2.713 

Newspaper -0.770 -0.037 0.000 -2.677 -3.483 

Office Paper 0.220 0.000 0.000 -2.677 -2.493 

Phonebooks -0.660 0.000 0.000 -2.677 -3.337 

Textbooks -0.037 0.000 0.000 -2.677 -2.750 

Dimensional Lumber 0.073 0.000 0.000 -2.530 -2.457 

Medium-density 

Fiberboard 

0.037 0.000 0.000 -2.530 -2.457 

Source: USEPA (2002) Solid Waste Management and Greenhouse Gases: A Life-Cycle Assessment of Emissions 

and Sinks, EPA530-R-02-006, May 2002. 

ERM give a figure of 496 kg CO 2 equivalent avoided per tonne of material recycled. 81 A more 

recent study takes figures from the Swiss Ecoinvent database, giving values maximum and 

minimum figures of 0.62 tonnes and 0.28 tonnes respectively, with the difference apparently 

attributable to de-inking processes (this is not clear, but if true, the differential seems 

extremely high). 82 The lower end benefits seem questionable given the values given in other 

studies, though the difference between maximum and minimum values does serve to deepen 

the argument around the desirability of clean feedstocks (though this is not obviously what 

the differences refer to). 

At the other extreme lies the figure in the IWM2 model. Rather than leading to GHG savings, 

the model suggests that recycling a tonne of paper leads to additional emissions of 0.16 

tonnes CO 2 per tonne of paper recycled. 

For the purposes of this study we have taken the WRAP figures as representing a reasonable 

estimate of potential benefits. Since WRAP’s study does not incorporate the sequestration 

effects identified as being potentially of huge significance in the USEPA work, we have also 



82 ERM (2006) Carbon Balances and Energy Impacts of the Management of UK Wastes, December 2006 


82 

included sequestration impacts – of 2.68 tonnes CO 2 equivalent - within the non-fossil carbon 

emissions. 

Although not included within the MACC curves, these impacts are included for information 

purposes within the summary output sheets. Sequestration is important in the context of 

medium- to long-term GHG abatement strategies and this effect needs to be investigated 

more systematically. One of the problems with most life-cycle based studies is that all 

emissions are treated equally, regardless of the pace of their release. This is always 

problematic where biodegradable materials are concerned. 

5.6.2.2 Dense Plastic 

Different studies split out plastics fractions in different ways. Some give values of plastics by 

polymer, others simply split out materials by whether or not they are rigid or films. The 

current analysis only considers recycling of dense plastic, not plastic film. 

WRAP estimated figures for benefits of recycling plastic into plastic packaging at 1 tonne CO 2 

equivalent saved per tonne of material recycled. 83 

ERM attributed low and high values to recycling of dense plastic and plastic film. 84 In both 

cases, the low values represent the impacts associated with the use of plastic as plastic 

lumber, whilst the high value represents the effect of displacing granulate, PET in the case of 

dense plastic, and LDPE in the case of plastic film. The values for dense plastic range from - 

0.85 tonnes CO 2 equivalent saved (i.e. a net contribution to climate change) to +1.82 tonnes 

CO 2 equivalent saved per tonne of material. For plastic film, the figures range from -0.85 

tonnes CO 2 equivalent saved (i.e. a net contribution to climate change) to +1.47 tonnes CO 2 

equ saved per tonne of material. 

ERM’s earlier study gave figures for dense plastic of 2.324 tonnes CO 2 equivalent saved per 

tonne of material recycled, and for plastic film, 1.586 tonnes CO 2 equivalent saved per tonne 

of material recycled. 85 

In the AEA Report, data on the emissions associated with plastics production were taken from 

the BUWAL 250 LCA data set which is based on data from APME, except for HDPE where data 

used was taken from the Chem Systems work for the UK Environment Agency. Data on 

recycling of HDPE plastic bottles into flakes which are then extruded into pellets which can 

substitute for virgin material is available for a plant in the UK, and gives a value of 341 kg CO2 

per tonne of recyclate due to a much lower energy demand. Similarly data on PET bottle 

recycling to produce PET flakes at a Swiss plant gives a value of 114 kg CO2 per tonne of 

flakes due to a low energy demand. We have compared this with data from the US EPA study. 

AEA’s life cycle CO 2 emissions associated with the production of different types of plastics are 

given in Table 5-27. 

83 WRAP (2006) Environmental Benefits of Recycling: An International Review of Life cycle Comparisons for Key 

Materials in the UK Recycling Sector, Banbury: Oxon, WRAP, May 2006. 

84 ERM (2006) Carbon Balances and Energy Impacts of the Management of UK Wastes, December 2006. 




83 

Table 5-27: Avoided Emissions Associated with Recycling Plastics (AEA) 

Plastic type 

Emissions in kg CO2 equ / tonne material 

EU virgin EU recycled US virgin US recycled 

PE Granules (general) 2,200 

HDPE granules 1,000 341 700 280 

LDPE granules 2,320 890 330 

LDPE granules 1,910 

PVC powder 1,940 

PET granules 2,200 114 1160 450 

PP granules 1,800 



The AEA study used figures for HDPE and PET of savings of 0.53 tonnes CO 2 equivalent per 

tonne material recycled, and 1.8 tonnes CO 2 equivalent per tonne material recycled. 

The USEPA study gives quite different figures for HDPE as shown in Table 5-28. 

Table 5-28: Avoided Emissions Associated with Recycling Plastics (USEPA) 

Material 

Avoided emissions, tonne CO2 equ / 

tonne of material 

HDPE 1.40 

LDPE 1.71 

PET 1.55 

Source: USEPA (2002) Solid Waste Management and Greenhouse Gases: A Life-Cycle Assessment of Emissions 

and Sinks, EPA530-R-02-006, May 2002. 

For the current study, an average value for benefits associated with recycling plastic was 

derived - 1.40 tonnes CO 2 equivalent per tonne of material. The average is based on the 

values obtained for HDPE, LDPE and PET from the AEA, ERM and USEPA studies. 

5.6.2.3 Glass 

The WRAP report effectively gives three figures for the benefits associated with glass recycling 

depending upon how the material collected is used. The implications of mixed glass 

collections are likely to be rather different from the case where glass is collected colour 

sorted. Table 5-29 confirms the improvement in respect of climate change is by far the 

greatest for the case where ‘closed loop’ recycling occurs but this is unlikely where collections 

are of mixed glass. The most likely route for utilisation, in this case, is as an alternative to 

aggregates, in which case, the study suggests, no climate change benefits are likely to be 


derived. Since glass often constitutes something of the order 25-35% by weight of dry 

recyclables collected, the loss of these benefits has to be considered of some significance. 

Table 5-29: Avoided Emissions Associated with Glass Recycling (WRAP) 

Activity 

84 

Avoided emissions, tonne CO2 equ. per 

tonne recycled 

Recycling v Landfill 

Recycling v 

Incineration 

Glass packaging 'closed loop' recycling 0.60 0.43 

Glass packaging into aggregates 0.00 n.a. 

Glass packaging into glass fibre & other 'open 

loop' recycling 

0.30 n.a. 

Source: WRAP figures based on WRAP (2006) Environmental Benefits of Recycling: An International Review of 

Life cycle Comparisons for Key Materials in the UK Recycling Sector, Banbury: Oxon, WRAP, May 2006 

One study included within the WRAP review was a report by Enviros undertaken on behalf of 

British Glass, which indicated benefits of 0.314 tonnes of CO 2 equivalent per tonne of 

material where the avoided disposal route was landfill. 86 The study also considered the 

impacts assuming glass is re-processed by overseas facilities, and attributed a value of 0.290 

tonnes CO 2 equivalent per tonne of glass in this case. 

The AEA report used the EA / Chem Systems life cycle inventory. From this data, it was 

estimated that the carbon dioxide savings through the use of an additional tonne of cullet 

were 301 kg CO 2 . 1,049 tonnes of raw cullet are needed for 1000 tonnes of processed cullet, 

giving a net GHG savings of 0.287 tonnes CO 2 equ per tonne of recycled cullet. This is almost 

identical to the figure reported by the USEPA (0.28 tonnes CO 2 equivalent / tonne). 

Table 5-30: Energy Used to Manufacture High Cullet and Low Cullet Glass 

Input Low cullet glass High cullet glass 

Cullet 25% 59% 

diesel in transport MJ 514 282 

grid electricity MJ 411 469 

energy unspecified MJ 1,226 672 

coke oven gas MJ 0 327 

Oil MJ 1,957 828 

natural gas MJ 2,872 3,265 



86 Enviros (2003) Glass Recycling – Life Cycle Carbon Dioxide Emissions, internal report for the British Glass 

Public Affairs Committee 


85 

The ecological footprint study gives a much higher value for the GHG savings at 1.015 tonnes 

CO 2 equivalent per tonne glass (even accounting for transport emissions for recyclate), whilst 

the IWM2 model again suggests far lower benefits at 0.08 tonnes per tonne recycled (this 

figure reflects process benefits only, so does not include transport of recycled glass). 

We have used the value from Enviros within the current analysis as it explicitly considers 

overseas re-processing. This value is also similar to the net savings attributed by AEA and 

USEPA, and the ‘open loop’ value from WRAP. It should be noted that this might understate 

the benefits from domestic reprocessing of glass, an important factor given that glass is less 

commonly exported for reprocessing. Equally, the benefit applies only if the material is 

reprocessed in closed loop applications. 

5.6.2.4 Steel 

The WRAP report suggests a climate change related saving of 1.34 tonnes CO 2 equivalent per 

tonne of material where the avoided disposal route is landfill. 87 

ERM give a figure of 0.43 tonnes CO 2 equivalent per tonne of material recycled, 88 while a 

later report by the same company gives minimum and maximum figures of 0.58 tonnes CO 2 

equivalent and 0.83 tonnes CO 2 equivalent, respectively, albeit reportedly using the same 

database as in the previous study. 89 

The AEA report used the datasets from BUWAL 250 for production of tin plate from raw 

materials and from non-detinned scrap. This data includes all emissions associated with 

transport of materials, energy used in processes etc. It was assumed that 0.84 tonnes of 

tinplate were manufactured from 1 tonne of scrap. This gave a figure of 1.521 tonnes CO 2 

equivalent savings per tonne of steel collected for recycling. 

Table 5-31: Greenhouse Gas Emissions for Production of Virgin and Recycled Steel (AEA) 

Material 

Emissions total, CO2 equ 

(kg) 

1,000 kg tin plate (virgin) 2,970 

1,000 kg tin plate from non-detinned scrap 1,160 



This figure is close to that reported in the USEPA report, which is slightly higher at 1.79 tonnes 

saved. The IWM2 model gives a figure of 1.75 tonnes CO 2 equivalent saved per tonne steel 

recycled. 

We have used the WRAP figure of 1.34 tonnes CO 2 per tonne of steel recycled for the current 

analysis. This value is marginally higher than the mean of the other studies previously cited. 





89 ERM (2006) Carbon Balances and Energy Impacts of the Management of UK Wastes, December 2006. 


86 

5.6.2.5 Aluminium 

The WRAP report gave rise to figures used by WRAP of 7 tonnes of CO 2 equivalent avoided for 

every tonne of aluminium recycled. 90 

Two ERM studies gave similar values - a range from 12.3 tonnes of CO 2 equivalent avoided to 

13.1 tonnes of CO 2 equivalent avoided per tonne of aluminium, and a figure of 11.6 tonnes of 

CO 2 equivalent avoided per tonne of aluminium. 91 

The AEA report used the datasets from BUWAL 250 for production of aluminium ingots from 

raw material and from recycled aluminium, and for production of tin plate from raw materials 

and from non-detinned scrap have been drawn from the BUWAL 250 data set. This data 

includes all emissions associated with transport of materials, energy used in processes etc. 

For primary aluminium production, emissions of the potent greenhouse gas carbon 

tetrafluoride (CF4), which has a global warming potential of 6,500, are included. Table 5-32 

confirms the GHG emissions for the production of virgin and recycling aluminium indicated 

within the AEA study. It is further assumed that 0.93 tonnes of aluminium are produced from 

1 tonne of recycled cans, and 0.84 tonnes of tinplate from 1 tonne of scrap. This gives a net 

savings figure per tonne of aluminium recycled of 9.108 tonnes CO 2 equivalent. 

Table 5-32: Greenhouse Gas Emissions for Production of Virgin and Recycled Aluminium (AEA) 

Material CO 2 (kg) CF 4 (kg) Total kg CO 2 equ 

1,000 kg aluminium ingot (virgin) 7,640 0.4 10,240 

1,000 kg aluminium ingot (recycled) 403 0 403 



The USEPA report gives a figure of 15.07 tonnes CO 2 equivalent per tonne of aluminium 

recycled. As with paper and glass, the IWM2 model gives a lower figure for the benefits from 

recycling of 6.626 tonnes CO 2 equivalent. 

For this study, we have used the mean of the WRAP, ERM and AEA figures - of 9.2 tonnes CO 2 

equivalent per tonne steel recycled. 

5.6.2.6 Wood 

Unlike other dry recyclables, the same benefits are assumed to occur within both IPCC and 

Global scopes with respect to wood recycling. 

There is a lack of robust data with regard to the benefits attributable to wood recycling, as 

was acknowledged in WRAP’s international review of life cycle studies associated with 

recycling materials. 

We use the value given by ERM 0.001 tonne of CO 2 equivalent per tonne of wood recycled. 

Following the same approach as for paper and card, we also include, as an information item, 



91 ERM (2006) Carbon Balances and Energy Impacts of the Management of UK Wastes, December 2006; ERM 

(2006) Impact of Energy from Waste and Recycling Policy on UK Greenhouse Gas Emissions, Final Report for 

Defra, January 2006. 


87 

the non-fossil carbon emissions associated with carbon sequestration as previously 

discussed in Section 5.6.2.1. These are attributed as 2.53 tonnes of CO 2 equivalent per wood 

recycled, as given by USEPA. 92 

5.6.2.7 WEEE 

The benefits from the recycling of WEEE are estimated from the avoided emissions values for 

steel, aluminium and plastics, applied to the assumed composition of WEEE. The composition 

data is derived from a survey of recyclable WEEE undertaken in London, as shown in Table 

5-33. 

Table 5-33: Composition of Recyclable WEEE in London, 2006 

Steel Aluminium Plastics 

53% 2% 16% 

Notes: 

The remaining proportion of the material is assumed non-recyclable. 

Source: Axion Recycling (2006) WEEE Flows in London: An Analysis of Waste Electrical and Electronic 

Equipment within the M25 from Domestic and Business Sectors, Report for the Environment Agency, 

September 2006 

5.6.2.8 Summary of Values Used 

Table 5-34 provides a summary of the assumptions used within the current study along with 

the relevant literature source. These figures do not include the non-fossil emissions 

associated with sequestration (reported for information purposes but not included within the 

MACC totals). 

5.7 Treatment of Source-Separated Organic Material 

This section considers the treatment of source separated organic material. The following 

types of treatment are considered within our analysis: 93 

‣ AD of food waste; 

‣ Land spreading (of commercial and industrial food wastes); 

‣ In-vessel composting of mixed food and green waste; and 

‣ Windrow composting of green waste. 

These are discussed in Sections 5.7.1 to 5.7.4. Our assumptions are based largely upon 

previous work undertaken by Eunomia on behalf of WRAP. 94 


Sinks, EPA530-R-02-006, May 2002. 

93 Note that because home composting is outside the scope of the study, this is not considered. 




88 

Table 5-34: Summary of Values Used and their Literature Sources 

Avoided emissions, t CO 2 equ / t recycled 

material 

Paper and card 1 1.41 

Dense plastic 2 1.40 

Glass 3 0.29 

Steel 4 1.34 

Aluminium 5 9.20 

Wood 6 0.001 

Notes: 

1. WRAP 2006 

2. Average of HDPE, LDPE and PET taken from ERM 2006a and 2006b, AEA 2001 and 

USEPA 2002 

3. Enviros 2003 (value for overseas re-processing) 

4. WRAP 2006 

5. Average of WRAP 2006, AEA 2001 and ERM 2006b 

6. ERM 2006 

5.7.1 AD of Source-Separated Food Wastes 

As was previously discussed in Section 5.5.3.7, digesters can be used to treat residual waste 

as part of an MBT system. Our model for the AD treatment of source-separated food waste 

uses a similar approach with modifications to account for the different material being treated. 

CO 2 emissions resulting from the AD of source-separated organic waste are based on the 

carbon content of the input waste, assumed to 100% food waste for the purposes of this 

study. 95 The carbon content is calculated on the basis of the total organic content of the 

waste and its volatile solids (VS) content. A proportion of the total carbon content will be 

converted to CO 2 as a result of biogas combustion for energy generation. A further (albeit 

small) amount is emitted as CH 4 through fugitive emissions occurring during the digestion 

process. Table 5-35 outlines key assumptions used within the modelling for this study. 

Biogas can be used, amongst other things, for generating energy or it can be used as a 

vehicle fuel displacing diesel. Assumptions used to model the option of generating electricity 

are outlined in Table 5-36. 

95 These emissions are non-fossil in origin and therefore excluded from the analysis under IPCC methodology 


Table 5-35: Assumptions Relating to AD Process and Generation of Biogas 

89 

Parameter 

Assumption 

Dry matter content of food waste 30% 

Organic matter content of VS 93% 

Carbon content of VS 45% 

VS content of organic matter 45% 

VS loss during digestion 70% 

Methane content of biogas 60% 



Avoided emissions through avoided fertiliser production / tonne waste 1 


1 l / t input 

0.10 t CO2 equ 

Fugitive emissions (% carbon converted to CH4) 3% 

Notes: 

1. These avoided emissions equate to the amount of energy required to produce 

fertiliser. The fertiliser requirement is assumed to be is displaced as a result of 

applying the output from AD to land. 

As noted in Section 5.5.3.7, if the biogas is cleaned of impurities it can be subsequently used 

as a vehicle fuel, displacing the use of diesel. Our assumptions for modelling this option 

assume the fuel to be used within a fleet of vehicles, re-fuelled from a central point, as is the 

practice in Scandinavia. Some modification to the vehicle will be required to allow it to run on 

gas as opposed to diesel. Assumptions used to model this option are summarised in Table 

5-37. 

Table 5-36: Assumptions for Energy Generation from Biogas using a Gas Engine 

Parameter 

Assumption 

Gross electrical efficiency of gas engine 37% 

Heat generation efficiency of gas engine, CHP mode (excl utilisation) 40% 


90 

Table 5-37: Assumptions Regarding Upgrading of Biogas for Use in Vehicles 

Parameter 

Energy used during upgrade process 

Assumption 

0.2 kWh / Nm 3 biogas 

Process losses for CH4 (during upgrade) 2% 

Energy value of CH4 36 MJ / m 3 

Fuel consumption of CBG car 

Emissions from CBG car 

Emissions avoided by diesel production 

Emissions from diesel car 

1.88 MJ / km 

105.2 g CO2 equ / km 

13.63 g CO2 equ / MJ 

129.4 g CO2 equ / km 

Source: CONCAWE, EUCAR and JRC (2006) Well-to-Wheels Analysis of Future Automotive Fuels and Powertrains 

in the European Context: Tank-to-Wheels Report, Version 2b. May 2006; W. Urban (2008) Methods and costs of 

the generation of natural gas substitutes from biomass – presentation of results of latest field research, 17 th 

Annual Convention of Fachverband Biogas e.V, 15 th -17 th January 2008, Nuremberg 

5.7.2 Land Spreading 

Recent survey work undertaken by Eunomia has confirmed this to be a significant disposal 

route for commercial food waste as a result of the low costs involved. 96 

The carbon content of food is assumed to be released into the atmosphere as CO 2 . Since the 

carbon is non-fossil in origin, these impacts are not included under IPCC methodology. Key 

assumptions for this management route are shown in Table 5-38. 

Table 5-38: Assumptions Regarding the Land Spreading of Food Waste 

Parameter 

Assumption 

Dry matter content of food waste 30% 

Organic matter content of VS 93% 

Carbon content of VS 45% 

VS content of organic matter 45% 


1 l / t input 

5.7.3 In Vessel Composting – Mixed Green and Food Waste 

This study considers two types of aerobic digestion process for source-separated organic 

wastes – In-Vessel and Windrow Composting. Whilst garden waste can be treated by either 

96 Eunomia (2008) Regional Biowastes Management Study, report for the East of England Regional Assembly, 

May 2008 


91 

process, food waste can only be treated through IVC facilities as a consequence of the UK 

Animal By-Product Regulations (ABPR). 

Emissions from IVC facilities vary depending on the composition of the organic material being 

treated by the facility. Food waste requires structural material (i.e. green waste) to be added 

to it prior to treatment within an IVC facility. Although it is possible to treat a feedstock of up 

to 70% food waste using IVC, the proportion is usually optimised at closer to 50-60%. 97 For 

the purposes of the current analysis, 50% of the material treated at IVC facilities is assumed 

to be food waste. 

Within the modelling of IVC carried out for this study, organic waste is assumed to contain 

carbon in the form of cellulose, lignin, protein, sugar / starch and fats. The proportion of these 

constituent types of carbon varies depending on the composition of the organic stream - 

green waste contains a greater proportion of cellulose and lignin whilst food waste contains 

more protein. Whilst sugar, starch and fat will degrade completely during aerobic digestion 

processes, lignin degrades much more slowly, such that only 15% is assumed to be degraded. 

Assumptions are largely taken from a previous study undertaken by Eunomia. 98 

Biological treatment processes lead to emissions of a number of gases, but the main ones 

are carbon dioxide and ammonia. In in-vessel composting systems, ammonia is usually 

treated in biofilters. In biofilters, the nitrogen in the ammonia is converted to, in varying 

proportions, N 2 , NO and N 2 O. The last of these is a potent greenhouse gas. The N 2 O 

emissions are associated with: 

‣ The process itself (release of nitrogenous gases to the atmosphere as a result of 

degradation processes); and 

The workings of the biofilter, which are likely to include conversion of nitrogen in the form of 

ammonia to nitrogen in the form of N 2 O. 

Estimates vary as to the proportion of N in NH 3 which follows the conversion pathway, but 

best estimates are that conversion efficiencies are of the order 25%. It is possible to reduce 

ammonia emissions into the raw gas through various practices: 99 

‣ reduce sources of readily available N in the initial material mix; 

‣ increase available C-sources to balance microbial N-binding; 

‣ add approximately 5% of mature compost to provide microbial and physico-chemical 

N-sorption capacities; 

‣ run the process at lower temperatures (below 50°C) as soon as thermal sanitisation 

requirements are met (NH 3 emission is enhanced at higher temperatures); and 

‣ employ ammonia scrubbing prior to the biofilter to reduce the amount of ammonia 

available for conversion to N 2 O at the biofilter stage. 

97 It should be noted, however, that this percentage will largely depend upon the level of sophistication of each 

particular IVC facility. These range from cheap, usually static clamp systems with ‘temporary’ polymer textile-type 

roofs, which have a high propensity to generate odours, to more expensive, housed or tunnel systems with 

generally lower likelihood of problematic odours 



99 See Eunomia (2008) Emissions of Nitrous Oxide from Waste Treatment Processes, Final Report by Eunomia 

for WRAP. 


This measure focuses on the last of these only. 

One study looking at MBT processes suggests a mass balance as shown in Figure 5-2. 

92 

Figure 5-2: N-balance of a One Step Biofilter at the MBP Plant in Bassum, Germany 

Source: H. Doedens, C. Cuhls, F. Mönkeberg et al. (1999) Balancing Environmentally Relevant Chemicals in the 

Biological Pre-Treatment of Residual Waste – Phase 2: Emissions, Pollutant Balances and Waste Gas Treatment 

(in German). Final Report for the German Federal Research Project on mechanical-biological treatment of waste 

before landfill. Hannover: University, 1999 

This suggests that, as regards N, for every 500g of N entering the biofilter as NH 3 , an 

additional 111g of N is emitted as N 2 O. This would imply a conversion ratio of 22%. On the 

other hand, the above figure suggests a low overall rate of destruction of NH 3 . 

Figure 5-3 shows further measurements of N 2 O from MBT sites before and after biofiltration. 

Again, this indicates how biofiltration of ammonia leads to increases in N 2 O following the 

biofiltration process. 

Trimborn et al conclude that independent from the level of NH 3 load in the raw gas ca. 29% of 

the transformed NH 3 is released as N 2 O and ca. 9% to NO. 100 

In a forthcoming paper, Amlinger et al assume that: 101 

the continuous aerobic conditions in the biofilter supports the microbial oxidation of 

NH + 4 to NO 2- . High concentrations of NH 3 and NO - 2 can inhibit further oxidation to NO - 3 

(Spector, 1998a,b). NO - 2 can be directly denitrified to NO and N 2 O. It is likely that 

caused by a high NH - 3 concentration the microbial community in the biofilter is shifted 

in a way that deoxidising, denitrifying enzymatic activities become predominant. 

100 M. Trimborn, H. Goldbach, J. Clemens, C. Cuhls, A. Breeger (2003) Endbericht zum DBU- 

Forschungsvorhaben Reduktion von klimawirksamen Spurengasenin der Abluft von Biofiltern auf 

Bioabfallbehandlungsanlagen (AZ: 15052). 

101 F. Amlinger, C. Cuhls and S. Peyr (2007) Greenhouse Gas Emissions from Composting and Mechanical 

Biological Treatment, Waste Management and Research, forthcoming. 


93 

A specific recommendation, in relation to the operation of exhaust air treatment, so as to 

reduce N 2 O emissions is – logically – to deploy acid scrubbers to eliminate NH 3 prior to 

treatment at the biofilter. This reduces the amount of NH 3 arriving at the biofilter, and hence, 

its conversion to N 2 O. 

Figure 5-3: N 2 O Emissions from MBT Plants Before and After Exhaust Air Treatment in 

Biofilters 

Literature suggests range of removal efficiencies for different compounds using biofilters. 

Vogt et al assumed a removal efficiency of 96% for NH 3 , 50% for methane and 50% for total 

organic carbon. Omrani et al site removal efficiencies of 97-99% for a biofilter using peat, soil 

and sand, whilst one of sawdust, clay and sand achieved 94% abatement. 102 

‣ Where scrubbing equipment is used alongside a biofilter the potential for further clean 

up exists. For example, ORA report 100% removal through the combined use of 

biofilter and scrubbing. 103 

In this study, we assume the following conversions: 

‣ Baseline: 

In the baseline, only a biofilter is used. In this case, we have assumed that of the NH 3 

generated in the first instance (through the composting process), 25% of the N in the 

NH 3 is converted to N 2 O. This lies between the estimates derived from Doedens et al, 

and that of Trimborn et al. 

102 G. Omrani, M. Safa and L. Ghaghazy (2004) Utilization of Biofilter for Ammonia Elimination in Composting 

Plant. Pakistan Journal of Biological Sciences 7. 2009-2013. 

103 ORA (2005) Development of a Dynamic Housed Windrow Composting System: Performance Testing and 

Review of Potential Use of End Products, Report for Canford Environmental, Dorset. 


94 

‣ With Scrubber: 

In the second, we assume that a scrubber operates before the biofilter. The scrubber 

is assumed to remove 95% of the ammonia. The remaining ammonia (and other 

exhaust gases) is passed through a biofilter where, again, it is assumed that 25% of 

the N in NH 3 is converted to N 2 O. 

Table 5-39 summarises key assumptions used in this study. 104 

Table 5-39: Assumptions for In-vessel Composting 

Parameter 



Assumption 



Non-degraded carbon (retained in microbial biomass) 2 30% 







Mineralisation rate of readily available organic matter 4 20% 


% of organic matter from compost becoming humus 25% 

Notes: 

1. Assumes that a biofilter converts 95% of the available NH3 to N2O. 88% of the total 

nitrogen is assumed to be released as NH3, whilst 10% is assumed to be released as 

N2O without the action of the biofilter and scrubber. 

2. This carbon is assumed to be used for cell reproduction and growth of the 

microbiological organisms carrying out the degradation process. 



applying the output from AD to land. 

4. The mineralisation rate is the rate at which carbon contained within the organic 

matter (or humus) is assumed to become atmospheric CO2. 

5.7.4 Open-air Windrow Composting of Green Waste 

Source-separated green waste can be treated by either IVC or open-air windrow composting 

facilities. Open-air windrow composting processes are those which occur in the open, usually 

in piles of triangular cross-section, these being turned periodically to introduce air into the 

process. In the UK, food waste cannot be treated in uncovered (open-air) facilities. 




95 

Table 5-40 outlines the key assumptions used in this study, which are again largely based on 

a previous study undertaken by Eunomia. 105 

Table 5-40: Assumptions for Windrow Composting 

Parameter 



Assumption 



Non-degraded carbon (retained in biomass) 30% 






1 l / t input 

Mineralisation rate of readily available organic matter 3 20% 


% of organic matter from compost becoming humus 25% 

Notes: 

1. No action of scrubber or biofilter is assumed for Windrow facilities. 



applying the compost to land. 

3. The mineralisation rate is the rate at which carbon contained within the organic 

matter (or humus) is assumed to become atmospheric CO2. 




6.0 Modelling of Costs 

96 

The cost modelling has been undertaken with a view to: 

‣ Seeking to preserve some ‘reality’ in the modelling of the costs of switches in 

management; and 

‣ Seeking to ensure that flexibility to changes in the parameters which CCC may seek to 

vary is preserved. 

The cost modelling focuses upon those ‘switches’ which are examined in the context of this 

report. As stated previously, this list of switches is not all-encompassing. A more extensive 

treatment would focus upon all switches, seeking to understand which offered the most costeffective 

opportunities for abatement, and then working through the MAC curve modelling. 

6.1 Cost Metrics 

CCC seeks to model using three different cost metrics: 

‣ A social metric; 

‣ A hybrid metric recognising capital costs as a resource cost (this is a hybrid approach 

which is contrary to conventional government appraisal); and 

‣ A private metric, recognising that whilst the CCC is to set carbon budgets from a 

societal perspective, a private metric will allow the CCC to view a ‘private MACC’ curve 

which provides an important indicator in terms of how rational agents may act to the 

costs they face in the market place. 

These different cost metrics are described in Table 6-1 below. 

Lastly, in terms of accounting the project sponsors have requested costs to be presented in 

real 2006 sterling. Many of our estimates are essentially given as 2007 figures, and so have 

been deflated by the GDP deflator proposed in the MACC modelling. 

6.2 Why Not Gate Fees 

Where matters of cost are concerned, the waste sector is typically used to dealing with the 

issue in terms of ‘gate fees’. Gate fees are not ‘costs’, and there are various reasons why the 

gate fee at a facility may differ from average costs, or marginal costs, as they might be 

conventionally understood. Gate fees may, depending upon the nature of the treatment, be 

affected by, inter alia: 

‣ Local competition (affected by, for example, haulage costs); 

‣ Amount of unutilised capacity; 

‣ The desire to draw in, or limit the intake of, specific materials in the context of seeking 

a specific feedstock mix; 

‣ Strategic objectives of the facility operator; and 

‣ Many other factors besides. 


97 

Table 6-1: Different Cost Metrics Used by CCC 

Metric 

Pure Social metric 

(Conventional 

NPV approach) 

Pure Private 

metric (private 

agents’ 

perspective) 

Hybrid metric 

(social metric but 

which cost of 

capital included) 

Discount Rate 

NPV using Green Book 106 social time 

preference discount rate (3.5% for first 30 

years, 3% for 31-75 years etc…) of intertemporal 

comparisons. 

No cost of capital. 

Annuitisation applying private weighted 

average cost of capital (WACC) discount 

rate and allowing for short-payback 

periods by using threshold discount rates. 

Default assumption WACC 10% - though 

consultants will be asked to comment on 

an appropriate private WACC for their 

relevant sectors. 

NPV using SDR but also include costs of 

capital at relevant sectoral WACC – 

recognising private costs of capital as a 

true resource cost. 

Resource cost v. retail 

price 

Value resource cost only, 

i.e. no taxes included 

Valuing energy savings 

and technology costs at 

retail prices including 

taxes, VAT, CCAs, ROCs, 

carbon price impacts. 

Value resource cost only 

(but include capital costs 

which are by this cost 

metric defined as 

resource costs) 

Another feature of the waste treatment market at present is the use of long-term contracts in 

the municipal waste market to procure services. The nature and length of these contracts, 

and the nature and extent of the risks which the public sector may wish to transfer to the 

private sector, influences the unitary payment, or gate fee, offered under any given contract. 

The nature of risk transfer may relate, for example, to technology and its reliability, or to 

specific outputs which a contract seeks to deliver, and these may, in turn, relate to existing 

policy mechanisms such as the Landfill Allowances Schemes. The key point is that the nature 

of the risk transfer associated with a given contract affects gate fees. In the municipal waste 

sector, contract prices are typically wrapped up in the form of a Unitary Payment, which may 

be composed of a number of different elements associated with the delivery of the contract 

against the specified outputs. This ‘unitary payment’ is typically determined on a contractual 

basis, and so is somewhat different to gate fees which might be realised at facilities operating 

in a more openly competitive market. 

In the approach suggested for use by CCC, there is no obvious link between the cost metrics 

used and either ‘gate fees’ or ‘unitary payments’ (the latter being affected, in any case, by the 

availability and extent of support through PFI credits in England and other forms of financial 

support in the DAs). It should also be noted that whilst much of the major infrastructure for 

municipal waste has, in the past, been financed using project finance, it remains possible 

106 

http://greenbook.treasury.gov.uk/chapter05.htm#discounting 


98 

that corporate finance could be used to support projects in future. This would have the effect 

of changing the cost of capital used to support any given project. Finally, local authorities 

themselves may increasingly make use of Prudential Borrowing, particularly for items for 

which the quantum of capital required is relatively small. 

For all these reasons, the ‘costs’ as modelled in this study should not be expected to 

resemble ‘gate fees’ with which many in the waste sector will be more used to dealing with. In 

general, the calculated costs will be lower than gate fees / unitary payments agreed under 

local authority contracts, except in those cases where, locally, either markets are very 

competitive, or strategic actions of operators have the effect of depressing gate fees in the 

area. 

It should also be recognised that the different cost metrics affect different treatments in 

different ways. Changes in the cost of capital (see Section 6.4.1 below) affect the unit (per 

tonne) cost of more capital intense treatments in a more significant way than they do for 

those with lower unit capital costs. Similarly, under the social and hybrid metrics, the effects 

of landfill tax, ROCs and fuel duty will affect different treatments in different ways. 

6.3 The Nature of Switches 

The nature of switches we are looking at varies in the profundity of the change in waste 

management system that they imply. For example, some merely imply the direction of waste 

away from one management route (e.g. landfill) into another (e.g. incineration). However, 

others imply a switch from one management route (e.g. landfill) to another (e.g. recycling) 

which may imply a change in collection system as well as the management of the material. 

These might be referred to as ‘treatment switches’, and ‘system switches’, respectively. The 

latter are far more difficult to model. 

Where additional waste is being collected for recycling, for example, the costs of doing this 

depend on a whole host of factors, not least of which is how that additional material is being 

obtained (i.e. what combination of change in system, change in participation, change in 

capture rate, change in relative collection frequency of recycling and refuse, etc.), and the 

costs of this change relative to a given baseline. In the general case, these costs could be 

positive or negative, depending upon the assumptions one was to use concerning how the 

additional material is collected, and the nature of any counterpart changes in the collection 

system. 

Below, we outline the basics behind our approach. 

6.4 Key Variables 

It is clear from the requirement to generate the above metrics that there are a range of 

variables which are required to model the costs of the different switches. Some of these are 

determined centrally by CCC for use in all MAC models, the others are specific to the waste 

MAC model. These are described below. We spend less time considering those variables 

determined centrally since these are effectively determined by CCC or other models. 

6.4.1 Centrally Determined 

6.4.1.1 Discount Rates 

The above discussion highlights the fact that the different cost metrics make use of different 

assumptions regarding discount rates. 


99 

‣ The social metric makes use of the standard Green Book approach using a social 

discount rate to reflect social time preference which takes into account impatience, 

catastrophic risk and marginal utility of income), 

‣ The private metric applies a private Weighted Average Cost of Capital (WACC) valuing 

the opportunity cost of capital investments – either the cost of capital charges, or the 

opportunity cost of not reinvesting capital in an alternative project [in addition a 

private sector annualisation would factor in retail prices/taxes that private agents face 

(transfers which are excluded when taking a social resource cost perspective)]. 

‣ The hybrid metric uses the social discount rate (as in the Green Book) but also 

includes costs of capital at the relevant sectoral WACC, thus recognising private costs 

of capital as a true resource cost. 

From the above discussion, the significance of the WACC is clear. 

Weighted Average Cost of Capital 

There is no readily available figure for the WACC in the waste sector. CCC was originally 

proposing a default figure of 10%. 107 Subsequently, 108 a report citing a figure estimated by 

Oxera of 4.7-5.3% emerged. 109 Both of these seem rather low in our experience, especially 

insofar as the municipal waste sector is concerned. 

A possible explanation follows: 

‣ The Oxera work used a two stage approach to assessing the cost of capital to firms. 

• The first was a high-level sectoral examination, which used data from different 

sources to estimate sectoral averages. These themselves vary, with regulators’ 

estimates being at the higher end; and 

• The second was based on examining firm-specific differences to assess the 

actual cost of capital to specific types of firm. The size of firm, and potential 

constraints experienced by investors, were considered at this stage. 

The second stage essentially led to significant uplifts in the cost of capital (see Figure 

6-1); 

‣ The waste sector’s weighted average cost of capital is affected by the risk associated 

with the investment being made. As the waste sector shifts away from ‘traditional 

ways’ of doing things, and to the extent that contract structures seek to ensure risk is 

borne, where appropriate, by the private sector, so the cost of capital appears to have 

increased. Many investments in the municipal sector are financed using project 

finance, with Special Purpose Vehicles (SPVs) set up for the purpose of delivering a 

specific service, or range of services. SPVs are financed using debt and equity, with 

the equity investors expecting greater returns on their investment. The ratio of 

107 CCC (2008) The Committee On Climate Change’s Methodology And Approach To Using Marginal Abatement 

Cost Curves To Derive Domestic Carbon Budgets, Internal Draft. 

108 CCC Shadow Secretariat (2008) Capital Costs, Discount Rates, and MAC Curves, Internal paper 

109 Oxera Consulting (2007) Economic Analysis for the Water Framework Directive: Estimating the Cost of 

Capital for the Cost-Effectiveness Analysis, Financial Viability Assessment and Disproportionate Costs 

Assessment—Phase II, Report for Defra, DfT and the Collaborative Research Programme, June 20 th 2007. It 

should be re-emphasised that these are intended to represent the WACC in real terms. As such, the implied 

nominal rates would be higher owing to the effects of inflation. 


100 

debt:equity will have an influence on the effective cost of capital to the company 

concerned. It may well be that in future, more investments are financed corporately, 

with associated impacts on the weighted cost of capital. Interestingly, Ernst & Young, 

advisers on many PFI projects in the waste sector, assumed a 15% real pre tax cost of 

capital for gasification, pyrolysis and anaerobic digestion, and, reflecting Ilex’s analysis 

of CHP, 12% cost of capital for incineration with CHP (it is not clear, from the Ilex 

analysis that the 12% figure is a real, as opposed to nominal, cost of capital). 110 These 

figures seem to reflect risks experienced in the context of municipal contracts. It 

seems possible that the average cost of capital may be lower in ‘merchant’ 

transactions, though obtaining financial support for a given project may be more 

difficult owing to the issues associated with securing supply of waste into the project. 

Figure 6-1: Adjustments Made to Average Cost of Capital Estimates 

Source: Oxera 

We have taken the following approach: 

‣ We have used Ernst & Young’s figure of 15% for large capital items of infrastructure; 

‣ We have used a figure of 12% for items of infrastructure where the quantum of capital 

required is lower (IVC and AD plants). This reflects the fact that treatment facilities are 

likely to be constructed outside of contracts on a more commercial basis; and 

‣ We have used a lower figure of 10% for collection and sorting systems, as well as for 

landfill and open air windrow composting facilities. 

This reflects, we believe, a reasonable assessment of the opportunity cost of capital going 

forward. It seems reasonable to suggest, however, that there might be variations in the cost 

of capital across technology types, and between contract (and risk-sharing) structures. For 

example, local authorities might well be more inclined to have recourse to Prudential 

Borrowing where the quantum of capital associated with a given treatment project is relatively 

small. 

110 Ernst & Young (2007) Impact of Banding the Renewables Obligation – Costs of Electricity Production, Report 

to DTI, April 2007. 


101 

6.4.1.2 Revenue from Electricity Sales 

The revenue from electricity sales is taken from values given in BERR’s energy model. The 

outcomes anticipated using the Waste MACC, at least in respect of electricity generation, are, 

effectively, endogenous variables in the calculation of electricity revenues in the model. In 

practice, however, it has not been possible to link the models such that the two reach some 

form of equilibrium. As such, the MACC model outcomes do not affect electricity revenues. 

This assumption is probably fair as long as the Waste MACC is having a marginal effect on the 

electricity market. However, where non-marginal changes are anticipated, the assumption 

would become less valid. Equally, one might argue that these values are, in any case, model 

estimates, and are unlikely to predict the future perfectly. 

The nature of Power Purchase Agreements and the quality of the deal they deliver for 

generators, varies considerably. In our modelling, we have assumed that the generator 

benefits from a proportion of the electricity revenues, with the default figure set at 80%. 

6.4.1.3 Revenues from Heat Sales 

Regarding heat sales, the central MAC model provides no estimate for the value of heat sales. 

It does provide a figure for gas prices. We have assumed that heat could be sold at a slight 

discount to heat generated from gas fired boilers. We have assumed that the gas boiler 

functions at an efficiency of 90%. Although those selling heat would be expected to expect to 

add margins to this price, we have effectively assumed that the discount at which heat from 

waste-fired CHP schemes is sold is equivalent to this margin, not least since waste-fired CHP 

schemes have some incentive – especially where investment has been made in infrastructure 

to deliver heat – to maximise heat sales. 

By way of comparison, on a model price of gas of £13.57 per MWh, the approach suggests 

heat sales of 1.22p/kWh, whilst recent work by Jacobs for SEPA used a figure of 

1.5p/kWh. 111 

We assume generators receive 100% of the revenue from heat sales calculated in this 

manner. 

6.4.1.4 ROC Values 

ROC values have again been derived from modelling for BERR carried out by Redpoint. As 

with electricity generation, the quantity of renewable electricity generated in the waste sector 

ought to be endogenous to the model of ROC values. As with electricity revenues, we have 

assumed that 80% of the ROC value is realised by the generator in the default situation. 

6.4.2 Waste Specific Assumptions 

There are a number of waste specific assumptions related to the cost modelling which have 

also been used. These are described below. 

6.4.2.1 Landfill Tax, Standard Rate 

Landfill Tax is currently at a level of £32 per tonne, and will increase at the rate of £8 per 

tonne per year until it reaches £48 per tonne in 2010. What levels it may be set at beyond 

this date are not entirely clear. However, both in the 2007 Budget (when this new level of 

111 Jacobs (2008) Development of a Policy Framework for the Tertiary Treatment of Commercial and Industrial 

Wastes: Technical Appendices, Report for SNIFFER / SEPA, March 2008. 


102 

escalator was announced) and in the most recent Budget Statement, the Chancellor signalled 

that tax rates might well increase above this level. 112 

For the purpose of this analysis, we assume that the tax increases to £48 per tonne in 2010. 

In real terms, the value is lower than this because of the effects of inflation, and the fact that 

landfill tax is set in nominal terms. Although we have been asked to address ‘firm and funded’ 

policies only, given the Chancellor’s stated intent to increase the tax further (but the lack of 

any firm statement of this nature), we have assumed that the tax maintains its value, in real 

terms, in the years after 2010. 

6.4.2.2 Landfill Tax, Lower Rate 

The lower rate of landfill tax stood at £2.00 per tonne for many years before it was increased, 

in 2008, to £2.50 per tonne. There are no firm announcements to increase this in the short 

term. There has been no announcement of intent to increase this lower rate, a situation 

different to that with the standard rate. We have taken the view that, since no announcement 

to this effect has been made, the lower rate tax remains constant in nominal terms (from 

2008) over time. 

6.4.2.3 Material Values 

Recycling collection systems recover materials which have a value in the market place. These 

material values will, of course, be susceptible to considerable fluctuations, as with any 

commodity. Evidently, the scope for modelling forward commodity prices in the sector is 

beyond the scope of this study (and in any case, fraught with difficulty). 

For the purposes of this study, the material values used in the study have been drawn from 

recent analysis by WRAP. 113 These are kept constant in real terms. This is likely to be a 

controversial assumption, but likewise, any assumption around commodity prices is likely to 

be contentious (and almost certainly wrong). Recent trends are upwards in real terms, 

showing a departure from historic trends exhibiting a real terms decline in many commodity 

prices. The assumption used here is a pragmatic one. 114 

6.4.2.4 Landfill Gate Fee, Hazardous 

Some facilities generate a residue which is classified as hazardous. From the perspective of 

this study, this material is not especially interesting as landfilling the material does not 

contribute significantly to climate change emissions. 115 It is mainly of interest in the context of 

112 In the 2007 Budget, the Chancellor wrote: ‘In order to encourage greater diversion of waste from landfill and 

more sustainable waste management options, the Government today announces that, from 1 April 2008 and 

until at least 2010-11, the standard rate of landfill tax will increase by £8 per tonne each year.’ In the most 

recent Budget statement, he stated ‘The Government expects the standard rate to continue to increase beyond 

2010-11.’ 

113 WRAP (2008) Kerbside Recycling: Indicative Costs and Performance, June 2008. 

114 It is worth noting that this report was finalised some months after the bulk of the work was completed and 

following peer review. Even the peer review pre-dated the collapse in materials prices being experienced by UK 

recyclers. This does not imply the approach taken is incorrect since the view is to 2022. If one expected the 

current state of affairs to be permanent, that would be a different matter. Similar comments could be made 

regarding the cost of capital in the wake of the diminishing availability of credit in the latter part of 2008. 

115 It is, on the other hand, not clear that either APC residues, or bottom ash should be considered entirely inert 

from this perspective. Both residues may include organic carbon which has not been completely combusted, and 

which is likely, therefore, to contribute to landfill emissions. See, for example, S. Dungenest, H. Casabianca and 

M. F. Grenier-Loustalot (1999) Municipal solid waste incineration bottom ash: Physicochemical characterization 


103 

costs. For the purpose of this study, however, we have not included a model, as such, of a 

hazardous waste landfill site. We have assumed a cost per tonne of landfilling hazardous 

waste of £180 per tonne before landfill tax. This cost is invariant across the private, social 

and hybrid metrics. Not varying the pre-landfill tax costs across the cost metrics is unlikely to 

be an unreasonable assumption as long as the contribution of capital costs to the total costs 

are relatively low. 

6.4.2.5 Landfill Gate Fee, Non-hazardous 

Where a treatment sends residues to non-hazardous waste landfill, the costs used are those 

modelled for the landfill, as described in below. The model picks up the correct cost figure for 

the cost metric being used. 

6.4.2.6 Construction Price Inflation 

In principle, it would make sense to include a figure for construction price inflation, 

particularly for the larger infrastructure projects. However, our understanding is that no other 

MACCs have incorporated such an assumption within their analysis and so we have chosen to 

follow that assumption. 116 Capital costs are, therefore, effectively kept constant in real terms. 

6.5 Process Modelling 

The following Sections highlight some of the key assumptions made in the modelling of the 

costs of different options. Where relevant, we try to pick up on some of the issues of 

significance in the discussion of costs, bearing in mind that existing cost data may not always 

be a guide to past data. 

It will be recalled from Section 6.3 that what we are really modelling, in most cases, is the 

average cost of abatement of a switch in management method (i.e. a change from one 

method of management to another). As such, all management approaches relevant to 

switching have to be considered. 

of organic matter, Analusis, 1999, 27, pp.75-81; Stefano Ferrari, Hasan Belevi and Peter Baccini (2002) 

Chemical speciation of carbon in municipal solid waste incinerator residues, Waste Management 22, pp.303- 

314; H. A. van der Sloot, D. S. Kosson and O. Hjelmar (2001) Characteristics, treatment and utilization of 

residues from municipal waste incineration, Waste Management 21 (2001) pp.753-65; Bor-Yann Chen and Kae- 

Long Lin (2006) Biotoxicity assessment on reusability of municipal solid waste incinerator (MSWI) ash, Journal of 

Hazardous Materials). A recent study, noting that organo-tin compounds were released into the gaseous phase 

in greater quantities from incinerator ash than biologically pre-treated wastes, noted: ‘The study highlighted the 

chemical reactivity of the incineration ash (which may to date have been underestimated), especially when 

access to additional organo-humic material is given. Therefore, the reuse of incinerated MSW set in contact with 

the environment should be carefully reconsidered.’ (B. Michalzik, G. Ilgen, F. Hertel. S. Hantsch and B. Bilitewski 

(2007) Emissions of organo-metal compounds via the leachate and gas pathway from two differently pre-treated 

municipal waste materials – a landfill reactor study, Waste Management 27 (2007), pp.497-509)). 

116 To do otherwise would, to the extent that one feels construction price inflation is running ahead of that 

suggested by GDP deflators, be to increase the cost of waste management measures, and potentially the costs 

of switches. This would distort the overall MACC curve modelling in such a way that waste-related measures 

would appear less favourable, in relative terms, than they are. On the other hand, it may also imply that the 

economy-wide MACC modelling underprices the costs of achieving given levels of abatement, unless these imply 

switches from more to less capital intense methods (measured per unit of abatement achieved). 


104 

6.5.1 General Approach 

As far as possible, the general approach has involved basing the cost modelling around 

published data sources. However, in order to give the modelling the flexibility to generate 

outputs using the three different cost metrics, we have effectively split out the modelling of 

any system into: 

‣ Capital costs (with different assumptions being applied to 

‣ Revenues from electricity sales split into 

• Revenues before ROC revenues 

• ROC revenues 

‣ Revenues from heat sales 

‣ Revenues from vehicle fuels sales, split into: 

• Revenues before RTFO 

• Revenues after RTFO 

‣ Costs of landfilling residues, split into: 

• Non-hazardous waste taxed at standard rate of landfill tax; 

• Non hazardous waste taxed at lower rate of landfill tax; 

• Hazardous waste taxed at standard rate of landfill tax; 

‣ Costs of fuel (in collection) split into; 

• Costs before fuel duty; and 

• Fuel duty 

‣ Other operating costs. 

This general approach enables the modelling of different MAC curves as required by CCC, and 

effectively constitutes a minimum break-out to allow: 

‣ different discount rates to be applied to the capital elements (under the social and 

private / hybrid cost MACCs); 

‣ the switching off, under the social cost metric, of existing taxes and subsidies, such as 

landfill tax, ROC revenues, etc; and 

‣ the assumed ‘constant’ (in real terms) other operating costs. 117 

In the general approach, rather than working up cashflow models, we have worked on the 

basis of annualising costs and revenues to give a single ‘annualised’ net cost per tonne of 

waste treatment. 

From this annualised cost figure, it is necessary to convert to a Net Present Value per unit of 

CO 2 equivalent abated. Because we are effectively calculating an average abatement per 

year, we have calculated a Net Present Value per year of the life of the equipment used in the 

117 In practice, of course, some of these will not be expected to be constant. Within these ‘constant’ operating 

costs are, for example, labour costs, material revenues, etc. Our working assumption is that these are constant 

in real terms, other than in those cases where operating costs or revenues are endogenous to the modelling (for 

example, landfill costs, or energy revenues). 


105 

switch being analysed. We have then converted to a Net Present Value figure, a conversion 

which is possible using the following formula: 

⎛⎛ 

⎞ 

⎞ 

⎜⎜ 

n ⎟ 

⎜ 

1 

⎟ ⎛ ⎞ 

⎜ ⎛ 1 

⎜ ⎟ 

⎞ 

* 1− 

⎟⎟ 

⎜ 

⎜ ⎟ 

⎜ 1 ⎟ r 

⎟ 

⎝ ⎝ + ⎠ 

1− 

1 

⎠ 

r 

AnnualNPV x 

⎝⎝ 

1+ 

⎠ 

= * 

⎠ 

n 

Where n = lifetime of a project 

x = Annualised cost 

r= Discount rate (i.e. 3.5% - note the private discount rate is encapsulated in 

the annualised cost - x) 

This equation assumes the annualised cost is calculated on the basis of repayment of capital 

invested at the start of each period, which in our cases, it is. 

6.5.2 Collection Systems 

As discussed above, many of the switches imply changes in collection systems. For example, 

the switch from landfilling to increased recycling of paper implies a change in the way 

materials are collected, with less being collected as refuse and more being collected as 

recycling. This has cost implications quite distinct from those associated with treatment 

systems. 

There are significant problems which one faces in seeking to cost how, at the margin, moving 

tonnages into once collection system and away from another affects the collection logistics. 

Much depends upon how that material is being acquired (for example, where households are 

concerned, this could be through civic amenity sites, through bring sites, or through kerbside 

collection systems), and where kerbside collection services are concerned, whether it is being 

acquired through increases in participating households, improved recognition of materials by 

households, and so on. 

It is not true to say, as many economists tend to assume, that increasing recycling rates 

necessarily increases collection costs. If the way the material is being delivered into the 

collection system improves the efficiency of collection logistics, marginal costs are lower than 

average costs, and average costs fall. We have based our assumptions on average costs of 

reasonably well performing systems. These may decline in future if policies act to increase the 

capture of materials per participating household. 

Another important feature of collection systems is that collecting different materials 

separately for recycling has different cost implications depending upon what that material is. 

When expressed per unit weight of material, bulk density plays an important role in 

determining costs. Materials with lower bulk density in collection occupy more space in 

vehicles and lead to, other things being equal, vehicles reaching volume capacity more 

quickly than in cases where materials are more dense. This increases the requirement for 

vehicles and staff, and increases collection costs. 

In an ideal world, we would model the marginal costs of adding each material of a given type 

to a given recycling system, and equivalently, seeing it not collected as refuse. In practice, the 

range of collection systems is large, and such a modelling process is beyond the scope of this 

particular work. We have differentiated between refuse and other materials as will become 


106 

clear below. We have done this with a view to giving reasonable average estimates of costs 

for the different materials as far as possible. 

We have not included depot costs, but have included transfer costs as necessary (on the 

assumption that changes in depot requirements are marginal for changes in collection 

system). 

6.5.2.1 Household Collection Systems 

There is an increasing amount of information concerning local authority collection systems 

across the UK. The most recent report, which focuses on provision of dry recyclables services, 

was published by WRAP. 118 This reviews a number of different collection systems and costs 

the recycling element only. 

Because some of our ‘system switches’ include switches of material into recycling and away 

from other management methods (and vice versa), one needs to have information that allows 

such switches to be modelled, in terms of their costs. In principle, one could use a model 

such as KAT, or HERMES, to model marginal changes in system costs as more waste is 

recycled or composted, and less is collected as refuse. We have carried out analysis from 

which such estimates could be drawn, though only in specific contexts. 119 Furthermore, those 

studies were not carried out with the calculation of costs under different cost metrics to the 

fore. 

Consequently, for this work, we have modelled the costs of: 

‣ Collecting refuse; 

‣ Collecting dry recyclables separately, excluding plastics; 

‣ Collecting plastics separately (through calculating marginal changes in costs of typical 

systems); 

‣ Collection of food waste separately; 

‣ Collecting garden waste separately; and 

‣ Collecting wood separately. 

In each case, we have worked up a simple model to understand the costs per tonne of 

collecting the materials concerned. The costs are composed of: 

‣ Capital costs 

• Vehicle costs; 

• Costs of containment; 

‣ Variable Costs 

• Maintenance 

• Replacement of bins 

• Costs of driver and crew 

118 WRAP (2008) Kerbside Recycling: Indicative Costs and Performance, June 2008. 

119 See Eunomia (2007) Managing Biowastes from Households in the UK: Applying Life-cycle Thinking in the 

Framework of Cost-benefit Analysis, Banbury, Oxon: WRAP; Eunomia (2007) Modelling the Impact of Household 

Charging for Waste in England, Final Report to Defra. 


107 

• Fuel use 

• Insurances etc. 

• Costs of transfer (as relevant) 

• Insurances, the driver, the crew, 

These costs are annualised, and then effectively split over an estimate of the total tonnage 

collected by the vehicle in a given year. 

For recycling collections, a true marginal cost approach would assess the costs of collecting 

each individual material. In practice, we have used one cost for collecting paper and card, 

glass and cans. We have assumed that plastics will incur a higher cost per tonne of collection 

than other recyclables. We have modelled a collection system for a system in which collection 

of plastics also occurs, and then calculated the marginal cost for the collection of a tonne of 

plastics. For both plastics, and for other materials, we have broadly followed the approach of 

WRAP’s lower cost systems on the basis that the aim is to understand systems which can 

deliver abatement at lowest marginal cost. 

For food waste collections, we have modelled costs using a dual operative vehicle. This may 

not always be the cheapest way to collect such materials (there are options for using split 

vehicles, for collecting food on the same pass as the dry recyclables, and for using vehicles 

with a driver only, the latter likely to be especially effective in rural areas) but it reflects what 

is emerging as ‘current UK practice’. We have recently been remodelling costs of food waste 

collections based around WRAP trial data and are confident these figures represent a 

meaningful ‘representative’ position in respect of food waste collections. 

For garden waste collections, we have assumed that the collections take place in similar 

circumstances to refuse collections, but the tonnages collected are lower. 

For wood, where household recycling is concerned, it seems reasonable to suggest that most 

wood recycling will take place at CA sites. Consequently, one has to consider the marginal 

cost of sorting wood at CA sites as opposed to not doing so. We believe these are unlikely to 

be significant, especially since in future Baseline systems, it would be assumed that such 

infrastructure was already in place (so the costs would be incremental). 

For WEEE, the issue is rather complex. There are a range of materials in the category ‘WEEE’ 

whose collection and reprocessing incurs quite different costs. One compliance scheme 

suggested these costs could vary, when materials are collected from designated collection 

facilities (DCFs). These costs are highest for gas discharge lamps (these being reported as 

being in excess of £2,000 per tonne). For some large household items, the value of materials 

may be considerable and may more or less cover costs of treatment and reprocessing. A 

weighted average figure has been used here of £112 per tonne. Given that this is not broken 

out in terms of capital costs and operating costs, it has not been possible to vary this figure in 

line with the changes in discount rate used to calculate annualised capital costs under the 

different cost metrics. 

A clear difficulty for the modelling is that these costs will themselves vary in any given year 

depending upon the type of systems one assumes are already in place. For example, in order 

to achieve a 60% recycling rate, a fairly comprehensive system needs to be in place already. If 

capturing additional tonnes of material is through gaining additional material from each 

household, this will lower the average costs of collection, with marginal costs below average 

costs, as the efficiency of logistics improves. On the other hand, if additional material comes 

from new participants (arguably, increasingly less likely as recycling rates increase), then 

average costs may increase as marginal costs exceed average costs. 


108 

In addition, it is clear that there are many different potential configurations for collecting 

recyclables and refuse. The range of options in use appears to be expanding each year rather 

than converging to a preferred model, and there are good reasons to believe that this is as it 

should be (albeit that a more uniform offering at the household level might make sense). To 

use only one option to represent the diversity of experience is clearly a limitation of the 

modelling, but equally, it would make little sense to seek to model on the basis of what 

already exists. Suffice to say, also, that not all local authorities will be optimising systems for 

cost. In many cases, the most effective measure in the MAC curve would be to improve the 

efficiency and design of existing collection systems with a view to delivering greater 

performance at lower cost. 

The modelling of collection costs, for this reason, is probably the element least likely to 

represent the actual costs, at the margin, of given switches. We have argued elsewhere 

against modelling collection costs on the basis of ‘costs per tonne’ for different aspects of a 

service. 120 This should be born in mind in seeking to make further improvements in the 

modelling. 

6.5.2.2 Commercial Waste Collection Systems 

The approach to modelling commercial waste collections is similar to the modelling of 

household waste collections, but with some differences. 

Refuse is modelled on the same basis but with an assumption that larger tonnages are 

collected from smaller numbers of premises. The unit costs are slightly lower than for 

household refuse, a reflection of the fact that the reduced density of logistics (commercial 

waste collectors compete in an open market) is compensated for by the higher tonnage per 

pick-up. The containment is assumed to be in Eurobins rather than 240l bins for households. 

For recycling, the materials split is assumed to be different for commercial waste than for 

household waste. Costs are determined separately for: 


‣ Plastics and cans; and 

‣ Glass, 

reflecting configurations in the market place. 

For paper and card, we have assumed a similar mechanism and a similar containment 

mechanism as with refuse. The high proportion of paper to card is assumed to reduce 

collected tonnages relative to refuse vehicles (as a result of lower bulk densities). However, 

we have assumed that after a £5 per tonne transfer cost, revenue of £50 per tonne is 

received for mixed fibres. 

For plastic and cans, we assume a transfer cost of £15 per tonne, and a sorting cost of £140 

per tonne. 

For glass, we assume an £8 per tonne transfer cost and revenue on the basis that material is 

colour sorted. 

120 See Eunomia et al (2001) Costs for Municipal Waste Management in the EU, Report for DG Environment, 

European Commission. 


109 

For food waste, we assume collection from wheeled bins in non-compacting top-loaders. The 

density of food waste allows relative large quantities of the material to be collected on the 

vehicle. Costs are similar to those for refuse. 

For garden waste, we have assumed that as with the municipal waste, the collections take 

place in similar circumstances to refuse collections, but the tonnages collected are lower. 

For wood waste, we have used the same assumption as for household wastes. 

For WEEE, the situation in the commercial and industrial sector is rather different from that in 

the municipal sector. Business to business (B2B) transactions are more likely to have resale 

value, at least for the IT category, but it is difficult to obtain reliable figures on this. B2B costs 

may be the responsibility of the supplier or the purchaser – depending on the agreement at 

the time of the transaction. Much of this activity may still be taking place outside reported 

WEEE channels. 

The costs of recycling this material are estimated, for the purpose of this report, to be (on 

average) £60 per tonne (rather lower than for municipal waste reflecting the greater weight of 

higher value materials). This is simply an estimate. 

6.5.2.3 Industrial Waste Collections 

Industrial waste streams are generally – and almost by definition – generated in relatively 

large quantities in fairly homogeneous streams. The different management methods for 

industrial waste streams are therefore less dependent upon changing the logistics and their 

costs, and more dependent upon simply re-directing waste to new facilities. Consequently, in 

most cases, we have modelled switches as changes in management routes taking into 

account the fact that: 

‣ Haulage of residual waste incurs a cost; 

‣ Haulage of separately collected materials also incurs a cost, and in large quantities, 

the cost per tonne will be broadly inversely proportional to the density of material 

being collected; 

‣ In the case of recycling routes, the separate collection of the materials generates 

revenue, whereas if collected as refuse, the material incurs a cost. 

For food wastes and garden wastes, the density factor is again deployed, but with the 

treatment incurring a cost. 

For wood waste, we have used the same figure as for household waste. For WEEE, we have 

used the same figure as for commercial waste above. 

6.5.3 Open Air Windrow Composting 

Open-air windrow composting schemes are relatively low-cost processes. 

Eunomia suggested, in 2002, costs for open-air windrow facilities of £14.47 - £20 per tonne 

(net of compost sales) for low- and high-specification windrow facilities. 121 These figures are 

only marginally higher today. 

AEA Technology examined the effects of scale on gate fees for open air windrow composting. 

These figures seem high, with gate fees supposedly never dropping below around £23 per 

121 Eunomia (2002) The Legislative Driven Economic Framework Promoting MSW Recycling in the UK, Final 

Report to the National Resources and Waste Forum. 


110 

tonne, even at a scale of 200,000 tonnes (which is more or less unprecedented for such 

facilities). 122 Recent work for WRAP confirms this with gate fees ranging from £17-£33 per 

tonne with a median figure of £22.50 per tonne. 123 The AEA study gave no information on unit 

capital costs, even though the study sought to demonstrate economies of scale at different 

plant sizes. 

We have modelled on the basis of a facility of the order 20,000 tonnes and have taken 

figures from previous studies undertaken by ourselves, 124 and inflated these to give a unit 

capital cost, including land, of £85 per tonne of throughput. We have tested this with industry 

representatives who have confirmed this as a sensible figure. 

Operating costs have been estimated at £10 per tonne of throughput before disposal of 

rejects. 

For rejects, we have assumed 5% of input material has to be landfilled. 125 This is assumed to 

attract landfill tax at a standard rate. 

The revenues from sales of compost are frequently ignored in studies assessing treatment 

costs. However, revenues from compost sales have the potential to increase in significance 

as energy prices increase. In most countries with more mature compost markets, as more 

material becomes available, so there tends to be more effort spent in marketing products, 

and refining them for specific end-use markets. This does not always translate into higher 

revenues. However, the revenues are likely to be higher as the costs of gas (and other energy 

sources) increases, with gas being a feedstock for synthetic nitrogen fertilisers. On the other 

hand, in some parts of the UK, farmers’ perceptions of compost are still influenced by the 

livestock pathogen outbreaks of the recent past, which have made farmers more risk averse 

in their attitude to compost use. 

ADAS reports a figure for the value of nutrients of the order £10 per tonne of compost. 126 A 

report for the Joint Research Centre shows average values for composts obtained in different 

countries (see Table 6-2). All of these are positive with median UK figures being between 

€0.7-€20.00 per tonne of fresh matter. We have assumed a value of £1.25 per tonne of 

waste input for compost (equivalent to around £2.50 per tonne of compost, towards the lower 

end of the range suggested in Table 6-2). 

6.5.4 In-vessel Composting (IVC) 

IVC systems come in various shapes and sizes. They can be vertical or horizontal. Unit capital 

costs depend upon, for example: 

122 AEA Technology (2007) Economies of Scale – Waste Treatment Optimisation Study by AEA Technology, Final 

Report, April 2007 

123 WRAP (2008) Comparing the Cost of Alternative Waste Treatment Options, 

http://www.wrap.org.uk/downloads/W504GateFeesReport_FINAL.c948135d.5755.pdf 

124 Eunomia (2002) The Legislative Driven Economic Framework Promoting MSW Recycling in the UK, Final 

Report to the National Resources and Waste Forum; 

125 In theory, one might suggest that this type of material could be used for other purposes. In practice, rejects 

from garden waste facilities tend to consist more of grit and stones, and to a lesser degree, materials associated 

with garden implements which find their way into the facility. The potential for, for example, energy recovery is 

less obvious with such reject streams. 

126 See ‘Compost lowering costs for farmers’, accessed from letsrecycle.com, 10 July 2007, 

http://www.letsrecycle.com/do/ecco.py/view_itemlistid=37&listcatid=217&listitemid=10069 


111 

‣ Scale of facility; 

‣ Nature of process used (and the degree to which the process is managed through 

‘fixed capital’ rather than mobile equipment); 

‣ Materials treated; 

‣ Nature of exhaust air treatment; and 

‣ Time spent in the intensive and maturation phases. 

Typically, for systems in the UK, capital costs have been relatively low (of the order £150 per 

tonne of capacity). However, there might be reasons to expect these to be somewhat higher in 

cases where: 

‣ The food waste component is higher, giving rise to a need for more thorough 

management of the input materials (notably to ensure adequate structural material is 

present through mixing), requiring more expensive treatment of exhaust air; 

‣ Concerns regarding odour are expected to be significant, again affecting exhaust air 

treatment. 

Table 6-2: Average Market Prices for Compost in Different Sectors (€/t per t f.m.) 

Sector 

BE/Fl CZ DE Fi ES GR HU IE IT 

NLbio 

NL 

green SE SI UK 

EU 

Mean 

Agriculture (food) 1.1 14.0 0.0 27.0 * - 15.0 - 3.0 -4.0 2.0 0.0 - 2.9 6.1 

vineyards, 

orchards 

1.1 - - - - - - - 12.0 - - - - 2.9 5.3 

0rganic farming 1.1 - - - - 42.0 - - - - - - - 2.9 15.3 

Horticulture & 

green house 

production 

1.1 - 15.0 - - 42.0 - - - - - - - 2.9 15.3 

Landscaping 2.5 4.5 15.0 2.0 - - 18.0 - 25 4.0 - - - 6.5 9.7 

Blends 1.1 2) - - 2.0 - - - - 3.5 - - - 2.9 2.4 

Blends (bagged 1) ) - - - - - - - 90.0 200.0 - - - - - (145) 

Soil mixing 

companies 

1.1 - - 2.0 - - - - - - - - - 6.5 3.2 

Wholesalers 1.1 - - - - - - - - - - - 12.0 - 6,6 

Wholesalers 

(bagged 1) ) 

- - 160.0 - - - - - - - - - - - (160) 

Hobby gardening 7.2 4.5 - 10.0 - - 20.0 - 13.0 0.3 - - 21.0 20 12.0 

Hobby gardening 

(bagged 1) ) 

- - - - - 300.0 - - - - - - - - (300) 

Mulch - - - - - - - - - - - - - 3.6 3.6 

Land restoration, 

landfill covers 

1.1 - - 0.7 - 0.0 - - - - - - - 0.7 0.6 

1) High prices because sold in small bags (5 to 20 litres) 2) Price for compost when sold to the substrate producer! 


112 

The capital costs of the treatment facility itself ought to be capable of being maintained 

around the £150 per tonne range. Jacobs suggest a figure of £146 per tonne for a 30,000 

tonne plant. 127 We have used a figure of £160 per tonne (2007 figure). It should be noted 

that some systems are relatively more costly (in terms of capital commitment) than others. 

For operating costs, Jacobs suggest a figure of £18 per tonne at a 30,000 tonne plant. We 

have used a figure of £19 per tonne. 

We assume rejects are 5% of input material and that these are sent to landfill where they 

attract landfill tax at the standard rate. 

As with open-air facilities, we have attributed to compost a revenue of £1.25 per tonne. 

6.5.4.1 Ammonia Scrubbing 

‣ As highlighted in Section 5.7.3, there is potential for GHG abatement through the use 

of scrubbers before biofilters at in-vessel compost plants 

The costs of the scrubber relate to the volume of air-flow through the scrubber. For a 20,000 

tonne per annum plant, the airflow would be, at a maximum, around 40,000 m 3 /hr. A suitable 

scrubber with circulation pump, tank for sulphuric acid and tank for ammonium sulphate 

would cost of the order £100,000 including additional piping (somewhat less – £70,000 or 

so - for the scrubber alone). Operating costs associated with electricity use, use of 

concentrated sulphuric acid, use of water, maintenance, and management of residue 

(ammonium sulphate) have been estimated at £1.24 per tonne of waste input. 

6.5.5 Anaerobic Digestion 

Like IVC systems, AD facilities come in different shapes and sizes. Most digesters have 

vertical tanks, but some are horizontal. Mechanisms vary considerably and a number of 

patented processes exist. Processes may: 

‣ Operate at high or low solids content; 

Wet digestion processes are carried out at a Total Solids (TS) content of no more than 

15% by weight, most commonly within the range of 7-12% TS. Usually, water must be 

added to the feedstock at the slurrying stage to dilute the waste (organic materials 

range from 10-30% TS). Mixing in process tanks can be achieved by mechanical 

mixers within the tanks, or by gas mixing, using recirculated biogas, if TS in the 

digester is below 10%. Most wet digestion processes use a completely mixed reactor. 

Dry digestion processes are carried out at a Total Solids (TS) content of over 15%, with 

25-40% being the most common TS range. This material is too thick for liquid-handling 

pumps, and therefore dry digestion technologies use concrete pumps and screw 

conveyors. Mechanical and gas mixing equipment cannot usually handle the high 

solids concentrations of dry digestion, and therefore mixing is achieved by the 

configuration of the digester and recirculation of waste through the digester. The tank 

is usually a plug flow reactor, rather than a completely-mixed reactor as normally used 

in wet digestion. 

‣ Operate at mesophilic or thermophilic temperatures; 

AD can function over a large range of temperatures from so-called psychrophilic 

temperatures (around 10 o C) to extreme thermophilic temperatures (>70 o C). 




113 

Temperature influences the speed (kinetics) of anaerobic reactions. In particular, 

methanogenesis is affected by temperature, with rates and yields increasing with 

temperature. Reactor temperature affects not only the reaction velocities of physicochemical 

processes, but also, biochemical conversion rates. 

The average value of temperature over a long time period fixes the bacterial 

population thus defining the two major groups of micro organisms. These are usually 

classified in association with two temperature ranges, around 35 o C in the mesophilic 

range (25 o C-40 o C), and around 55 o C (45 o C-65 o C) in the thermophilic range. A variation 

of reactor temperature within the specified ranges can change reaction velocity. 

The vast majority of digestion, especially of OFMSW, is carried out in these two 

temperature ranges. In the year 2000, more than 60% of capacity for treating 

municipal-type waste was in the mesophilic range with thermophilic accounting for just 

less than 40%; 128 

‣ Be one- or two- stage in nature; 

As investigations concerning anaerobic digestion have proceeded, concerns regarding 

inhibitors of the reaction process, and as to what might be the rate-limiting step in the 

process have given rise to processes which, rather than occurring in one tank, are 

carried out in separate reactors in more than one stage. The rationale for this is that 

the conversion of organic wastes to biogas is mediated by a sequence of reactions 

which are not necessarily optimized under the same conditions. Typically, two stages 

are used in which the first harbours the liquefaction-acidification reactions (with a rate 

limited by the hydrolysis of cellulose) and the second harbours the acetogenesis and 

methanogenesis, the rate of which is limited by the slow microbial growth rate. If the 

stages occur in separate reactors, the rate of methanogenesis can be enhanced 

through biomass retention schemes (or other means) whilst the rate of hydrolysis can 

be speeded up through using microaerophilic conditions. 

Various reactor designs have emerged over time. However, although in theory, the 

design of multi-stage systems should improve performance, in practice, the main 

advantage appears to be reliability in treating wastes which exhibit unstable 

performance in single-stage systems. Amongst these more problematic materials are 

those with very low C/N (Carbon/Nitrogen) ratios, such as market / wet kitchen 

wastes. Hence, Bernal et al observed that, under thermophilic conditions, if the 

feedstock has high biodegradability (as with market wastes), the rate of acidogenesis 

may create more acids than can be converted by methanogenesis, affecting the 

stability of the process. 129 This problem could be overcome by using separate reactors. 

Yet the comparative disadvantage which single stage systems have in this regard can 

be overcome by co-digesting these more problematic wastes with other materials, 

biological reliability being improved by buffering and mixing. Hence, multi-step 

processes still account for only 10% or so of the market for digesters dealing with solid 

wastes; and 

‣ Be continuous or batch processes. 

Most systems are continuous systems. Batch systems are usually simply filled with 

fresh wastes (with or without seed material) and are allowed to go through all stages 

128 

L. De Baere (2000) State of the art of Anaerobic Digestion of Solid Waste in Europe, Water Science and 

Technology, Vol.41, No.3, pp.283-90. 

129 

O. Bernal, P. Llabres, F. Cecchi and J. Mata-Alvarez (1992) A Comparative Study of the Thermophilic 

Biomethanization of Putrescible Organic Wastes, Odpadny vody / Wastewaters, Vol. 1, No.1, pp.197-206. 


114 

of degradation in the dry phase. Sometimes described as being akin to ‘landfill in a 

box’, these systems generate much more biogas than landfills because of the 

continuous recirculation of leachate (effecting a partial mixing through distribution of 

inoculant, nutrients and acids) and the higher temperature of operation. 

6.5.5.1 AD with Electricity Only 

There is a dearth of experience with the anaerobic digestion of source-separated municipal 

wastes in the UK. The continental experience is far richer in this regard. There have been 

some reviews of the costs of anaerobic digestion in Europe. A recent study found 

considerable variation in costs across different technology suppliers. The reader is referred to 

the full report for details and to our earlier review. 130 

Greenfinch, whose process is currently the subject of a Demonstrator Project under Defra’s 

New Technologies Programme, stated: 

For a commercial operation where the boroughs are responsible for delivering the 

organic waste to a facility which is owned by a private operation and which derives the 

benefits from the by-products, the commercial gate fee would be between £40 and £50 

per tonne. 131 

Greenfinch gave figures for capital costs of £4 million for 20kt, and operating costs of £20 

per tonne including rejects, but before revenues. 132 These are likely to be lower costs than 

would be realizable under a contractual situation. 

There is some uncertainty about what contract prices might look like in the UK situation given 

the lack of experience here, and the fact that the UK approach to procurement appears to 

have the potential to increase prices significantly (through requests for comprehensive 

guarantees, and associated risk transfer mechanisms). 

Capital costs for AD facilities used to deal with household, or industrial food wastes (and 

other biowastes) tend to be of the order £250 - £350 per tonne depending upon scale and 

the nature of the facility. We have estimated unit capital costs at £300 per tonne. 

In a feasibility study for Northern Ireland, suppliers were asked about the capital costs for 

facilities of given sizes. 133 The results are shown in Table 6-3. It can be seen that the capital 

costs vary enormously, rather more for a given scale plant than the operating costs. This, 

combined with the different ways of treating capital costs, makes it difficult to generalize 

concerning the costs of digestion plants. Particularly when dealing with source segregated 

fractions of municipal waste, digesters tend to be more or less heavily engineered to deal with 

potential contraries. In addition, post-digestion processes vary across suppliers. It was not 

always clear, from the financial breakdowns offered, how suppliers had accounted for UKspecific 

issues in respect of planning, permitting and contracting. 

130 Leif Wannholt (1999) Biological Treatment of Domestic Waste in Closed Plants in Europe - Plant Visit 

Reports, RVF Report 98:8, Malmo: RVF. Hogg et al (2002) Costs for Municipal Waste Management in the EU, 

Final Report to DG Environment, European Commission. 

131 Greenfinch (2003) Presentation by Greenfinch Ltd Based on Anaerobic Digestion: City Solutions Day, New & 

Emerging Technologies for Waste, February 2003. 

132 Greenfinch (2003) Presentation by Greenfinch Ltd Based on Anaerobic Digestion: City Solutions Day, New & 


133 Eunomia (2004) Feasibility Study Concerning Anaerobic Digestion in Northern Ireland, Final Report for 

Bryson House, ARENA Network and NI2000. 


115 

Table 6-3: Key Financial Data for Digestion Plant 

CAPACITY 10,000 20,000 25,000 50,000 50,000 50,000 75,000 165,000 

Total 

Investment 

Cost 

(£ millions) 

Unit 

Investment 


(£/tonne) 

Unit 

Operating 


(£/tonne) 

£3.13 

(incl land 

lease) 

£3.00 

(excl 

land) 

£12.68 £6.00 £17.60 £16.00 £16.00 £20.05 

£313 £150 £507 £120 £352 £320 £213.33 £121.49 

£27.14 £20.00 £20.24 £18.00 (e) £15.72 £28.00 £22.67 £22.20 

A study for Remade Scotland suggested that plant treating municipal waste would have 

investment costs ranging from £3 million for a 5,000 tonne/year plant (£600 per tonne 

capex) to £12 million for a 100,000 tonne /year plant (£120 per tonne capex), with operating 

costs between £100,000 (£20 per tonne capex) and £900,000 per year (£9 per tonne 

capex). 134 These operating costs would include a revenue offset associated with energy 

generation and use. 

The Annex to the English Waste Strategy gives the following gate fees: 

1. 20 ktpa £7.3 million (£365 per tonne capex) 



A Juniper report invited offers for a mock facility treating 30,000 tonnes of food waste and 

10,000 tonnes of slurry. The figures obtained from respondents using extensive pretreatment 

were, adjusting for recent movements in the exchange rate, of the order £4.2-5.0 

million (or £140 – 167 per tonne capex if one considers the food only 135 ). The operating costs 

were quoted as £340,000, or around £11 per tonne. We assume these are net of revenues 

from energy sales since they are so low. 136 

Jacobs estimate capital costs for a 40,000 tonne AD facility for commercial and industrial 

waste at £266 per tonne of annual capacity, with operating costs of £28 per tonne before 

revenues. 137 Short suggests that capital and operating costs will vary as follows: 138 

134 Fabien Monnet (2003) An Introduction to Anaerobic Digestion of Organic Wastes, Remade Scotland, 2003. 

135 The slurry was deemed to have only 5% solids content so only 5% or so of the solids would be in the slurry. 

136 Juniper (2007) Commercial Assessment: Anaerobic Digestion Technology for Biomass Projects, Report for 

Renewables East, June 2007. 



138 J Short (2008) Anaerobic Digestion and Alternative Waste Treatment Technologies, Deconstructing AD, 

Presentation to MRW Conference, May 2008. 


116 

5,000 tpa: Capex £1.8 m = £360 per tonne Opex £20 per tonne 






One can see, therefore, a very wide variation in the capital cost figures being quoted, and the 

variation cannot be explained by appeal to factors such as scale alone, partly because of the 

variety of technical designs on offer. 

We have used a figure of £300 for unit capital costs. For operating costs, we have good 

reason to believe that if one is seeking a figure before revenue generation from energy sales, 

and disposal of rejects, the figures above are all too low. We have used a figure of £35 per 

tonne. We believe this to be representative of facilities of scale 20-30,000 tonnes capacity, 

with appropriate post-treatment of the digested biowaste. 

6.5.5.2 AD with CHP 

The issue of CHP is discussed in this document with regard to both thermal facilities and AD 

facilities. Where thermal facilities are concerned, and where steam turbines are used to 

generate energy, there is a trade-off between the generation of electricity and the generation 

of heat. AD systems usually generate energy using gas engines. Where gas engines are 

concerned, the generation of heat incurs little penalty in terms of electricity generation, and 

the majority of facilities operate CHP engines, partly to ensure the provision of free heat which 

is needed to keep the feedstock at the required (mesophilic or thermophilic) temperature, as 

well as providing heat for hygienisation of the feedstock in the wake of the EU Animal-by 

Products Regulations. 

The likelihood that: 

‣ AD facilities will be operated at smaller scale than incinerators; 

‣ the total heat delivered is likely to be less than in what may be larger incinerators; and 

‣ the fact that CHP units are likely to be used to generate energy anyway, 

makes it more likely that, where AD is concerned, heat use may be more possible, and may 

be possible on a more opportunistic basis. It also implies that at least as far as generation 

equipment is concerned, the incremental costs are low (close to zero). In addition, the 

associated costs of infrastructure for delivering heat may be lower in a given area (as fewer 

end users would need to be served). 

The relatively small number of publicly available studies that have looked at the issue of CHP 

generation have tended to support the view that where thermal facilities are concerned, 

effective utilization of CHP is likely to be predicated upon district or community heating 

schemes. Where AD is concerned, this is less likely to be necessary. AEA argue that where 

sewage treatment works are concerned: 139 

139 AEA Energy and Environment (2008) The Evaluation of Energy from Biowaste Arisings and Forest Residues in 

Scotland, Report to SEPA, April 2008. 


117 

‘the option of heat recovery for additional heat (over and above what is required for 

the process) is generally not implemented as the value is low, there are limited 

opportunities for use on site (occasionally there are some works offices) and the cost 

of sale to other customers is too high as they will seldom be in close proximity to the 

water treatment works.’ 

They estimate the cost of the pipes and trenching to be of the order £1 million per mile of 

trench. 

For AD, an indication of the sort of differential between CHP and non-CHP configurations was 

given by Jacobs, who suggest that for a 40,000 tonne plant, the capital costs increase from 

£10.62 million to £11.48 million, or from £266 to £287 per tonne of annual throughput. The 

operating costs were estimated to remain constant. 140 

In this study, we have estimated capital costs for the useful deployment of CHP of an 

additional £1.65 million in capital terms. This lies between the Jacobs estimate and that 

implied by Ilex 141 (see Section 6.5.7.2 below) for a heat network. We have also added £1 per 

tonne to the operating costs. Evidently, this must be treated as a guesstimate, and the 

specifics will vary with the location and local opportunities for heat use of any given plant. 

6.5.5.3 AD with Gas Upgrading for Use as Vehicle Fuel 

The costs of gas upgrading tend to be expressed relative to the flow rate of biogas into the 

cleaning process. A number of different processes exist for cleaning up biogas (mainly for CO 2 

removal, but also for scrubbing of H 2 S), including chemical absorption, pressure swing 

adsorption, water scrubbing, and membrane separation. These processes are developing in 

terms of their energy use per unit of gas cleaned, and the extent to which methane is lost in 

the process. The aim, evidently, is to improve process efficiency without adding significantly to 

cost. 

Much of the information offered is in terms of the cost per unit of gas cleaned, or per unit of 

energy in biogas delivered. However, this is not especially useful for this study as we are 

seeking information of the change in capital cost at the AD plant, as well as in the operating 

cost. It is important in this regard to note that biogas upgrading is not simply an additional 

cost. If the intention is to make use of biogas as vehicle fuel, there are savings to be made in 

terms of the avoided cost of CHP generation, and of connection to the electricity grid. 

SLR estimate costs for a packaged gas engine generator set, up to about 1MWe, installed in a 

container ready for connection to the site switchboard, at about £600/kW (with costs per kW 

falling thereafter to £450-£500/kW). 142 For a 20-30,000 tonne plant, the generation is of the 

order 1MW, so we estimate the avoided capital costs at around £600,000. 

AEA notes: 

The costs of connection local to the generation project will be borne by the developer of 

the biowaste project. These costs will include: 



141 Ilex Consulting (2005) Eligibility of Energy from Waste – Study and Analysis, Final Report to the DTI, March 

2005. 

142 SLR (2008) Cost of Incineration and Non-incineration Energy-from-waste Technologies, Report to the Mayor 

of London, January 2008. 


118 

‣ Works on the site of the generation (e.g. new transformers, switchgear etc). 

‣ Any new or upgraded cable (over or underground) from the biowaste site to the 

nearest suitable connection point on the network. 

‣ Additional or upgraded transformers and switchgear at the connection point. 

The size of the generator, the distance to the connection point and the voltage level at 

which the connection for connection will determine the scale of costs for the local 

connection. The costs of additional or upgraded transformers and switchgear at the 

connection point will depend on the level (if any) of unused capacity on the existing grid 

equipment. 

For grid connection, the costs of connection and overhead lines will be specific to a given 

project. SLR suggests the following figures for 11, 33 and 132kV connections and overhead 

lines: 

‣ 11kV Grid connection equipment: £20,000 - £60,000; 

‣ overhead line: 

£15,000 - £30,000/km; 

‣ 33 kV Grid connection equipment: £120,000 - £150,000; 

‣ overhead line: 

£20,000 - £35,000/km; 

‣ 132 kV grid connection equipment: £800,000 - £1,000,000 

They also note that in addition to these figures, the time taken to get permission to connect to 

the grid can be important. 

Small generation projects will be connected to the lower voltage distribution network. For a 

20,000 tonne plant, generating some 0.5-0.75 MW electricity, an 11kV connection should 

suffice. Taking into account cabling costs (which are variable depending upon distance from 

the grid), we estimate a total fee to be of the order £150,000. 

For gas upgrading, the unit costs fall as the flow rate into the clean-up system increases. This 

is shown in Figure 6-2. The implications for unit costs (under specific assumptions regarding 

the cost of capital and the investment life-time) are shown in Figure 6-3. 

In our estimation, a 20,000 tonne plant, operating for around 7,500-8,000 hours per annum, 

would be expected to generate around 400m 3 of biogas per operating hour. 

A report by the Institut Catala d’Energia (ICAEN) gave figures, which appear to be 2004 

figures, of €600,000 for capital costs, and operating costs of €80,000 per annum, for 

pressure swing adsorption processes. 143 More recent figures from a Fraunhofer UMSICHT 

report gives figures for gas cleaning for different processes. At the throughputs we are 

interested in, investment costs are of the order €1.32 – €1.4 million. Operating costs were 

€327,000 – €336,000. 144 

We have used, for capital costs, an average of the Fraunhofer figures converted to UK sterling 

at a long-term exchange rate of £1 = €1.25 (as advised by CCC). These give capital costs of 

£1.03 million (or around £50 per tonne), and operating costs of £249,000 (or around £12.45 

143 ICAEN (2004) Economic Framework Report, Deliverable for the Altener Project Regulation Draft of Biogas 

Commercialisation in Gas Grid – BIOCOMM, 2004. 

144 Fraunhofer UMSICHT (2008) Technologien und Kosten der Biogasaufbereitung und Einspeisung in das 

Erdgasnetz. Ergebnisse der Markterhebung 2007-2008, report for the Bundesministerium fur Bildung und 

Forschung, April 2008. 


119 

per tonne). In addition to these costs, we have added a cost for pipework of £300,000 (£15 

per tonne). This reflects figures for 5km of pipework given by Schulz 145 and for a plant in 

Uppsala reported in an earlier study by Eunomia et al (see Table 6-4). 

Figure 6-2: Investment Cost for Biogas Clean-up as a Function of Capacity (m 3 /hr) 

Source: O. Jonsson and M Persson (2003) Biogas as a Transportation Fuel, Session 1, FVS 

Fachtagung 2003 

145 W. Schulz (2004) Untersuchung zur Aufbereitung von Biogas zur Erweiterung der Nutzungsmöglichkeiten, 

Bremer Energie-Konsens GmbH 


120 

Figure 6-3: Cost per kWh of Cleaned Biogas as a Function of Plant Capacity 

Source: Margaretta Persson (2007) Biogas Upgrading and Utilization as a Vehicle Fuel, Paper 

presented to the European Biogas Workshop, The Future of Biogas in Europe III, 14 th June 

2007. 

Table 6-4: Costs of Anaerobic Digestion Facilities 

Capital cost – digestion 

plant 

Capital cost – gas cleaning 

and compression 

Uppsala 

Linköping 

30 000 tons/year 100 000 tons/year 

€ 6 000 000 (1997) €5 900 000 (1996) 

€ 850 000 (1997) €2 800 000 (1996) 

Capital costs –piping € 330 000 (1997) €550 000 (1996, 5 km 

piping) 

Variable costs/year € 220 000 € 200 000 – 400 000 

Source: Uppsala municipality and Linköping municipality, cited in Eunomia et al (2002) 

For retailing of compressed biogas at filling stations, costs are likely to be similar to those for 

compressed natural gas, we have used the mid-point of the estimate from an NSCA report of 


121 

£200,000 for a system which provides for a vehicle fleet. 146 Since it is likely that the main 

uses of biogas would be for captive vehicle fleets with refilling stations at their home depots, 

these data seem reasonable for use in the economic analysis. 

The NSCA report also considers the additional costs of switching vehicles to either spark 

ignition or dual fuel as compared to the use of ultra-low sulphur diesel (ULSD). 147 There are 

interesting questions to be considered as to what one considers in terms of costs. In our 

analysis, we are assuming that the most likely approach to making use of compressed biogas 

in fuels is in vehicle fleets, such as buses, and refuse vehicles. 

The presumption is that these would be switching away from conventional ULSD operation. In 

this case, one might ask what assumptions should one use regarding a) the costs of the 

switch in vehicles and b) the value of the biogas derived. The NSCA report is written from the 

perspective of a fuel user. The analysis indicates that compressed biogas is competitive 

relative to ULSD, more especially so where the vehicle is a duel fuel one. The suggestion is 

that from a vehicle user’s point of view, the higher cost of vehicles (the capital involved in the 

purchase of dual fuel vehicles and their maintenance) is offset by the lower cost of biogas as 

fuel. Consequently, we have taken the view that, from the perspective of the biogas 

generator, one would either assume that one needed to equip the vehicles, but impute a 

shadow value for the fuel equivalent to that of diesel, or simply assume that the implied 

revenue generated equates to that of compressed natural gas. We have followed the latter 

approach for the sake of simplicity. 

6.5.6 Landfill 

The landfill model is broken down into: 

‣ The capital costs for the site 

Evidently, these may vary in unit (i.e. per annual tonne treated) terms depending upon 

the size of the site. We have modelled on the basis, broadly, of: 

• A fill rate of 250,000 tonnes per annum and a lifetime of 15 years; 

Of course, fill rates and life times vary, as will the total available void of a given 

site. This was felt to be broadly representative of a modern site, or extension; 

• Capex, including site assessment, acquisition, site development, restoration 

and aftercare, was initially estimated at approximately £23.5 million. For the 

modelling, we have used a figure of £100 per tonne of material accepted at the 

site each year (in other words, the landfill is being treated as a facility with a 

250,000 tonne throughput, with capex of £100 per tonne of that annual 

throughput); 

‣ Operating costs are estimated at £6 per tonne, before revenues from energy 

generation, whilst restoration, post-closure and aftercare are estimated to cost a 

further £8 per tonne; 

‣ There is a question as to how one should model the eligibility for ROCs of any energy 

generated. Under the revised Renewables Obligation, the proposed banding scheme 

146 Sustainable Transport Solutions (2006) Biogas as a Road Transport Fuel: An Assessment of the Potential 

Role of Biogas as a Renewable Transport Fuel, Report for the National Society for Clean Air, June 2006. 

147 Sustainable Transport Solutions (2006) Biogas as a Road Transport Fuel: An Assessment of the Potential 

Role of Biogas as a Renewable Transport Fuel, Report for the National Society for Clean Air, June 2006. 


122 

would see landfill qualifying for 0.5 ROCs per MWh of electricity generated. However, 

currently, the scheme allows for 1 ROC per MWh of electricity generated, and in its 

response to the Consultation on the Renewables Obligation, BERR stated: 

the Government recognises the concerns over the proposal for retrospective 

time limiting of support. The Government therefore has no intention of 

curtailing before 2027 the ROC entitlement of capacity (other than co-firing) 

which is already operational. 148 

As a result, we have modelled the private costs with an ‘average’ ROC eligibility which 

declines from 1 to 0.5 from 2009 to 2027. 

‣ Evidently, landfill tax is included or excluded depending upon the cost metric being 

used. In the social cost metric, it is not included in the costs. 

It should be noted that where a specific material is being ‘switched’ from landfill to another 

process, the model picks up the relevant energy generation associated with that material. 

6.5.7 Incineration 

Defra, in the context of the waste strategy, estimated the following gate fees for incineration: 

‣ 100,000 tonnes Capex £64.7 million £78.40 per tonne 

‣ 200,000 tonnes Capex £104.7 million £58.50 per tonne 

‣ 400,000 tonnes Capex £149.1 million £37.80 per tonne. 

Quotes from other publicly quoted sources are given in Table 6-5 below. It can be seen that 

even the same source quotes different costs in public. This merely serves to highlight the 

paucity of good, publicly available information, as well as the dependence of costs on issues 

unrelated to the plant itself. The costs of such facilities are sensitive to planning risks, and 

the nature of the procurement process. 

There are several incinerators modelled in this study. These are: 

‣ An incinerator delivering electricity only; 

‣ An incinerator delivering combined heat and power (CHP); 

‣ An incinerator delivering ‘optimised’ electricity generation; and 

‣ An incinerator delivering combined heat and power (CHP) in a fully optimised manner. 

We begin by describing the basic configuration which is the first one above. We then 

comment on changes from this baseline model. 

148 BERR (2008) Renewables Obligation Consultation: Government Response, BERR, January 2008. 


123 

Table 6-5: Publicly Quoted Sources of Incinerator Cost Information 

Capacity 

(kt) 

Capex 

(£ mn) 

Capex Average 

(£ mn) 

Opex 

(£/t) 

Opex 

Average 

(£/t) 

McLanaghan (SU) 50 12.5-19 16 35-55 45 

AEAT (North 

London) 

AEAT (EA) (elec 

only) 

100 25-36 28 

150 38-45 41 

200 40-58 47 

400 73-100 87 

500 80-105 93 

Gate Fee 

(indicative) 

(£/t) 

450 83.4 25 

270 61.3 30 

100 35.3 24 

200 53 22 

400 90.7 17 

AEAT (EA) (CHP) 100 41.1 26 

Enviros (London 

Costings) 

200 62.9 24 

400 106 18 

50-60 

Note: AEAT capex figures exclude costs of land, and gate fees exclude costs of dealing with 

residues. 

Sources: S. McLanaghan (2002) Delivering the Landfill Directive: The Role of New and 

Emerging Technologies, Report for the Strategy Unit, 0008/2002; AEAT (1999) Waste Pretreatment: 

A Review, Agency R & D Report Reference No PI-344/TR; Enviros (2003) Costing 

the Mayor’s Waste Strategy for London, Report for the GLA, September 2003. 

6.5.7.1 Electricity Only 

The incineration model is broken down into: 

‣ A capital cost element: 

Unit capital costs could be quite variable in any given situation and would depend 

upon scale, the nature of risk transfer, the detailed plant design, the requirements in 

terms of architecture, the nature of the flue gas cleaning technology etc. Quoted 

figures do not always include the costs of land, especially now that local authorities 

are encouraged to acquire sites The figure we have chosen is felt to be broadly 

representative of a plant of the order 200,000 tonnes capacity. There are likely to be 

some larger facilities constructed, but some smaller ones also. Ilex used a figure, in 


124 

2004 prices, of £58.6 million for a 200kt plant. 149 This figure seems very low in the 

current context of UK municipal waste contracts, which is the context in which most 

incinerators have been built. SLR looked at plants already built and found that capital 

costs varied with scale as in Figure 6-4. Jacobs suggest a figure of £86.5 million for a 

250,000 tonne facility, though this seems low relative to the same company’s 

estimates in the context of a recent procurement in Leeds (see below). 150 Given the 

recent cost inflation in construction projects, these figures are probably rather low for 

new-build facilities. 

Figure 6-4: Variation in Capital Cost with Scale 

Note: £/tpa refers to the “capital cost per tonne of waste treated”; ktpa refers to “thousands 

of tonnes of waste treated per annum 

Source: SLR (2008) Cost of Incineration and Non-incineration Energy-from-waste 

Technologies, Report to the Mayor of London, January 2008. 

Fichtner, looking at a one-line 182kt plant, considered that capital costs would be of 

the order £77.2 million, excluding land acquisition, costs of grid connection, and legal 

and advisory services, increasing to £98.6 million where the plant had two lines. 

Design enhancements were thought to be of the order £1.5 million, with grid 

149 Ilex Consulting (2005) Eligibility of Energy from Waste – Study and Analysis, Final Report to the DTI, March 

2005. 




125 

connection and enabling works of the order £3.5 million. For all costs, including 

contingency, but excluding land acquisition, the figure was £87.25 million. However, a 

key factor for incinerators and other capital projects, is the effect of inflation. 

Particularly in recent years, the costs of construction and of material have run ahead 

of conventional indices of inflation. The indexation cost implied for this project owing 

to inflation over the construction period was £26.5 million. 151 This inflation figure 

appears to be a figure quoted in nominal, rather than real terms. For the purposes of 

the analysis, we have assumed capital costs today would be of the order £95 million, 

with the real effects of indexation likely to be of the order £15 million. We have used a 

figure of £110 million capex, or £550 per tonne in 2008 terms; 

‣ Operating costs: 

For operating costs, before revenues from electricity generation and costs of dealing 

with residues, we have used a figure of £25per tonne in 2008 terms; 

‣ Revenues from electricity generation: 

are estimated on the basis of net delivered energy (calculated from the environmental 

analysis) and the electricity revenues from the BERR model; 

‣ Revenues from ROCs: 

The ROC-able element for the ‘electricity only’ incinerator is assumed to be zero, so 

ROC revenues are always zero; 

‣ Costs of dealing with residues: 

These are estimated as follows: 

• For fly ash, the waste is assumed to be landfilled at a hazardous waste landfill. 

As discussed above (see Section 6.4.2.4), we have not modelled this explicitly 

but have used a fixed pre-tax figure for the costs of landfilling, inclusive of 

haulage. 

• For bottom ash, we assume that on average, around two-thirds of material is 

put to some form of use in the construction industry. The remaining third is 

assumed to be landfilled at non-hazardous waste sites, and attracting lower 

rate landfill tax. 152 

6.5.7.2 Incineration with CHP 

It is difficult to know estimate, with any degree of accuracy, exactly what could be the costs of 

a CHP system given that so many variables exist. Costs will depend upon the specific design 

of a given CHP scheme. Not only are there differences related to the nature of the 

infrastructure required, but also, there will be differences in the impact on the plant itself, 

depending upon whether the intention is merely to use low grade heat for district heating, or 

medium or high pressure steam extraction. The former will have little impact on power 

generation, the latter will have a more significant effect. 

151 Fichtner (2007) Jacobs Leeds Energy-from-Waste: Validation of EFW Costs, 7 September 2007. 

152 We note that recent sampling by the Environment Agency suggests that in a relatively large minority of 

samples, bottom ash fails to meet some of the limit values. Bottom ash may, in future, have to be treated as 

hazardous waste dependent upon the outcomes of tests. 


126 

Ilex estimated the costs of a CHP system on behalf of BERR. 153 The estimated costs of CHP 

were based around the development of a 400,000 tone per annum plant, partly because a 

previous report had suggested that larger plants of this size were likely to be developed. 

Costs of CHP relate to: 

‣ Costs of providing heat from the facility (relative to costs of providing electricity only) 

‣ Costs of securing a market for the heat 

‣ Loss of revenue from power sales 

The first of these includes the costs of tapping into the steam turbine where the initial design 

allowed for this (and several have done so, or are planning to do so), provision of heat 

exchangers, and (depending on the nature of the recipients) provision of back-up boilers. In 

addition, the infrastructure for heat supply to the users has to be put in place if it does not 

already exist. The nature of the heat consumer(s) is likely to be a key determinant of these 

network-related costs. It is difficult to generalise these costs, given the wide variation in the 

possible networks. In principle, co-location alongside a major industrial heat user would be 

likely to give lower costs, but in practice, the likelihood of this occurring at conventional 

incinerators may be low. There might be a higher likelihood of merchant facilities being 

developed for the off-take of SRF, especially where the heat user is involved in the project 

itself. 

Ilex estimated costs for different CHP plant as shown below in Table 6-6. These figures were 

intended to be indicative of costs. The 43 MW capacity relates to a heat generation efficiency 

of around 24%. This is the only CHP option considered by Ilex which seems likely to qualify as 

‘good quality CHP’ as the net efficiency, however measured, is relatively low for the other 

options considered. The figures in the Table show that the main costs are related to the 

provision of the network and customer connections, and that in the Ilex assumptions, these 

show some clear increase with scale, which might not be the case depending upon the nature 

of customers. 

In reviewing the Leeds scheme, Fichtner comments on Jacobs’ costs associated with a CHP 

system which, it is claimed, have been taken directly from a scheme considered for a 

250,000 t/a EfW facility. 154 The capital costs for the CHP scheme were £33.8 million and the 

annual operating cost is £320,951 per annum. Fichtner comment: ‘We understand that these 

costs are taken from a report completed by ILEX Energy Consulting and Electrowatt Ekono for 

the DTI.’ The 250 ktpa facility is, in fact, a 400ktpa facility, and one with a power efficiency of 

20% and a heat efficiency of 12%. This would imply efficiency of heat generation of the order 

20% for a 250ktpa facility, which is quite a low figure (and would, arguably, imply a very poor 

use of capital in the investment in the heat network). 

153 Ilex Energy Consulting (2005) Extending ROC Eligibility to Energy from Waste with CHP, a supplementary 

report to the DTI, September 2005. 

154 Fichtner (2007) Jacobs Leeds Energy-from-Waste: Validation of EFW Costs, 7 September 2007. 


127 

Table 6-6: Capex and Opex Assumptions for 400kt/yr Incinerator with CHP Plant 

Thermal 

Capacity 

Capex 

Annual Opex 

Heat 

Exchanger 

Heat 

Network 

Customer 

Connections 

Pumping 

Heat 

Exchanger 

Heat 

Network 

Customer 

Connections 

3 0.19 2.39 0.95 0.01 0.00 0.01 0.02 

11 0.62 6.80 3.08 0.02 0.01 0.03 0.06 

20 0.88 14.83 5.59 0.03 0.01 0.07 0.11 

23 0.90 15.81 6.43 0.04 0.01 0.08 0.13 

28 0.90 19.25 7.83 0.05 0.01 0.10 0.16 

30 0.95 20.62 8.39 0.05 0.01 0.10 0.17 

34 0.95 23.37 9.51 0.06 0.01 0.12 0.19 

43 0.98 29.56 12.03 0.07 0.01 0.15 0.24 

66 1.00 45.37 18.46 0.11 0.01 0.23 0.37 

Note: Costs for heat networks, to a lesser extent, customer connections, will be very site 

specific and these numbers are intended only to be illustrative 

Source: Ilex Energy Consulting (2005) Extending ROC Eligibility to Energy from Waste with 

CHP, a supplementary report to the DTI, September 2005. 

The CHP option which most closely reflects our technical options are those with the higher 

thermal capacity (even though we are considering a smaller plant). The heat network and the 

customer connections would, using Ilex’s figures, imply additional capital costs of the order 

£43-£65 million. Perhaps unsurprisingly, in Ilex’s analysis, these scenarios – where the heat 

generation is greatest – are those which appear least favourable from a financial perspective 

given the power penalty implied by the increase in heat demand. Interestingly, the bottom row 

of the Table implies a heat generation efficiency of only 24%, with power generation at 17%, 

implying a much higher power to heat ration than might be expected in many CHP systems 

which had what one might call a ‘serious’ focus on heat provision. 

In a report carried out at the turn of the decade for the European Commission, investment 

costs for power and CHP schemes in Finland were as set out in Table 6-7. What this shows is 

the relative costs of power only schemes to those generating heat and power. The 

differentials are not trivial. Given that these figures are expressed in Euros in 2000, then 

accounting for exchange rate movements and for inflation over the last eight years, the 

figures do not seem so different to those provided by Ilex. 


128 

Table 6-7: Investment Costs for CHP in Finland (in €, year 2000 base) 

Heating Power / 

heating 

Heating Power / 

Heating 

Capacity, tons/year 40 000 40 000 300 000 300 000 

Investment 13 336 000 24 248 000 52 490 000 95 437 000 

Source: Eunomia (2002), Costs for Municipal Waste Management in the EU: Annexes, Final 

Report to DG Environment, European Commission, 

http://europa.eu.int/comm/environment/waste/studies/pdf/eucostwaste.pdf. 

In another report, Jacobs suggest that at 25,000 tonnes capacity, unit capital cost figures 

increase by £135 per tonne (or around a 40% increase in costs relative to their power only 

estimate). 

In our analysis, we have used Ilex’s figures at the 43 MW size, implying heat generation at 

around 30% of input energy. For such a scheme, the following applies: 

‣ Additional capital costs of £43 million; 

‣ Additional operating costs of £0.47 million; 

‣ ROC-eligibility of incineration depends upon the definition of good quality CHP which is 

to be used. Plants which meet the criterion of good quality CHP are eligible for ROCs, 

but on the electricity generation only. We have assumed that the plants operate above 

the relevant threshold and that, as a result, in the private cost metric, ROCs are 

received for the electricity. 

6.5.8 Mechanical Biological Treatment (MBT) 

MBT facilities can be configured in various different ways. Generally, outputs include more 

than one of the following: 

‣ Recyclables; 

‣ A stabilised biowaste, which may find use as a ‘compost like output’, but which may 

have to be landfilled; 

‣ A fraction to be sent to landfill; 

‣ A refuse derived fuel. 

In the UK procurement and regulatory context, the gate fees for MBT facilities have been 

difficult to estimate as the regulatory environment has been so fluid. 

An Annex to Waste Strategy for England 2007 gives gate fees for MBT facilities which are 

configured to produce an RDF with the RDF, presumably, combusted in a dedicated waste 

incinerator. The gate fees quoted were as follows: 

‣ 50,000 tonnes Capex £29.4 million (£588 per tonne) 



For some facilities of this nature, particularly lower capital cost MBT processes based on 

aerobic treatment, 60,000 tonnes or so is believed to be a near-optimum scale from a 

technical (if not a project) perspective. Figure 6-5, showing the results of analysis of tenders 


129 

for German plants over one year, suggests that economies of scale may already be limited at 

a capacity of 100,000 tonnes. 

It should also be noted that this review covered a range of plant sizes with 60,000 tonne 

facilities falling in the middle of this range. Figure 6-5 shows that this type of capacity is far 

from unusual for MBT plants. Indeed, the average size for the German facilities listed is 

around 70,000 tonnes. 

Figure 6-5: Range of Unit Capital Costs Reported in German Tenders for MBT Facilities (by 

capacity) 

Our analysis assumes essentially three types of biological treatment process, and in two of 

them, the equipment used is similar: 

‣ Aerobic stabilisation system; 

‣ Aerobic biodrying system to produce an SRF; and 

‣ System combining aerobic and anaerobic treatments 

In the second of the systems, the SRF is used either in a gasifier, a cement kiln or a power 

station, or a ‘dedicated waste combustion facility, such as a fluidised bed incinerator, or 

possibly, an incinerator with a water-cooled grate. Consequently, one needs to understand the 

costs of a range of different pieces of equipment. These include: 

‣ An aerobic stabilisation system; 

‣ An aerobic biodrying facility preparing SRF; 

‣ A gasifier; 

‣ A cement kiln; 

‣ A dedicated combustion facility; or 

‣ An MBT process incorporating an anaerobic step for a biodegradable component of 

the waste. 

These are discussed in what follows. 


130 

For each system, where more than one of the above technologies are used in one system, we 

have simply multiplied the quantity of material to be treated by the unit capital cost to 

understand the total capital costs for treating one tonne of waste in the overall process. We 

have done the same with operating costs. In all cases, flows of materials to landfill are costed 

using the relevant cost and tax from the landfill modelling, depending upon the cost metric 

being used. 

6.5.8.1 Aerobic Stabilisation System 

Stabilisation technologies are low capital cost treatments for residual waste. We have used a 

figure of £160 per tonne (2007 prices), and an operating cost of £24 per tonne before 

disposal costs. These costs are similar to those for in-vessel composting, reflecting 

similarities in technology, though scale will usually be larger, and there are costs of residue 

disposal to be considered. We have assumed all residues are landfilled except in the case 

where a ‘compost like output’ is deemed capable of being used on land. 

6.5.8.2 Aerobic Biodrying Facility Preparing SRF 

In principle, the costs of this type of system will be different depending upon whether the SRF 

which is being prepared is to be of higher or lower quality. We have used figures for the 

capital cost of £150 per tonne (2007 prices), with operating costs of £13 per tonne before 

residue disposal. It should be noted that the reality is that both the capital costs and the costs 

of dealing with residues will depend upon the detailed configuration of the system and the 

specification to which SRF is being produced. 

6.5.8.3 Gasification 

It is very difficult to give any clear figures for gasification costs. There is no commercial 

experience with waste gasification in the UK other than for small amounts of clinical waste. 

There are some demonstration projects in construction, as well as some merchant facilities 

now being planned. Some of these merchant facilities claim low unit capital costs and the 

ability to operate their technology coupled to a gas engine. Such a configuration has proved 

technically difficult to deliver in a form which is reliable. 

The quoted sources publicly available suggest enormous variation in the figures used for 

various analyses. AEA quotes indicative gate fees in North London of £37 per tonne 

(excluding disposal of residues), but quoted operating costs alone of £20-55 per tonne in a 

report for the Environment Agency. The gate fees used by Enviros for costing the London 

Strategy are roughly double those used by AEA for North London. 

Fichtner make the point: 

Reasonably accurate costs are only likely to come from real quotations to detailed 

specifications. Even costs obtained from tenders must be treated with a degree of 

caution since tender prices can vary dramatically from one supplier to the next even 

for almost identical technologies. 

Though Fichtner seem to making this point regarding the capital costs of gasification and 

pyrolysis in particular, the comment has more general applicability. 

Table 6-8 shows some information from various sources, whilst Table 6-9 gives figures from 

McLanaghan. These sources are somewhat dated now, but suggest that in the early part of 

the decade, unit capital costs varied enormously. One problem with these estimates is that it 

is not always easy to determine what is included or excluded in any given figure, nor what the 

figures for operating costs include (are they before or after revenues from energy generation, 

costs of treatment / disposal of ash, etc.). 


131 

Table 6-8: Information Regarding Costs for Pyrolysis / Gasification 

Capacity 

(‘000 tonnes) 

Capex 

(£ millions) 

Capex 

(£/tonne) 

Opex 

(£ per tonne) 

McLanaghan (SU) £350-450 46-61 

AEAT (North London) 105 24.3 £231 

AEAT (EA) 32 8 £250 

360 93 £258 

20-55 

Fichtner 100 23.5-30 £268 18-22 

European Environment 

Agency 

European Environment 

Agency 

20 9.3 £465 13-25 

200 58.9 £295 13-25 

Table 6-9: Information Regarding Costs for Pyrolysis / Gasification 

Capacity 

Capex 

(£ million) 

Capex 

(£ / tonne) 

Opex 

(£/tonne) 

Novera Energy 25,000 9 £360 20-28 

60,000 12 £200 20-28 

Thermoselect 200,000 69 £345 

240,000 77 £321 

Brightstar 100,000 25 £250 

Mitsui Babcock 60,000 45-50 £792 

120,000 80-90 £708 

Waste Gen 20,000 10 £500 15-20 

300,000 80 £267 

Compact Power 30,000 11.7 £390 45 

60,000 21.95 £366 40 

Our own view is that the tendency to generalize costs across ‘landfill’ and ‘grate incineration’, 

both relatively mature technologies in which some variation exists, but for which the 

associated cost variation is tolerably well understood, has led to a situation in which 

stakeholders have tried to generalize across technologies which are quite varied. It should not 

be expected that all pyrolysis / gasification technologies, nor all MBT configurations, will cost 

the same. Different variants are patented processes which may exhibit quite significant 

variation in design, performance and cost. 

The Annex to the English Waste Strategy gives the following figures for capital costs and gate 

fees: 

‣ 30 ktpa capex £21.7 million (723 per tonne), gate fee £93.6 per tonne 



132 

‣ 100 ktpa capex £27.9 million, (279 per tonne), gate fee £69.2 per tonne 

‣ 150 ktpa capex £67.2 million, (448 per tonne), gate fee £51.56 per tonne 

These figures seem somewhat strange, implying as they do a massive drop in unit capital 

costs as plants increase in scale from 30ktpa to 100ktpa, but then a significant increase in 

unit capital cost as the scale increases to 150ktpa. Indeed, it is rather difficult to understand 

how the gate fees would exhibit the suggested trend if the capital costs really were as the 

document states. 

We have used a figure for capital costs which assumes the gasifier has a capital cost of £350 

per tonne (2007 prices) where a steam turbine is used and £400 per tonne (2007 prices) 

where a gas engine is used (our assumption being that requirements in terms of gas clean up 

will be greater). These seem higher than many of the above figures, but in our view, most of 

the above figures are rather low. 

Operating costs are no more straightforward to determine as the variation in the above tables 

indicates. We have used a figure of £25 per tonne for all configurations. 

6.5.8.4 Cement Kiln 

For the cement kiln, we have not modelled this in terms of capital and operating cost. Instead, 

we have assumed a gate fee is paid to the kiln operator for the treatment of SRF. In terms of 

the forward projections, this gate fee would clearly vary depending upon how the market for 

SRF develops and unfolds. It seems quite possible that if prices for gas and coal increase, the 

demand for alternative fuel sources will also follow suit. The range of facilities available for 

treating SRF would be expected to increase, and the gate fee payable would be driven down 

by the increase in demand for SRF. 

We have, however, no crystal ball. For the purpose of the analysis, we assume a gate fee of 

£30 per tonne (20087 terms) of SRF is paid. This is broadly in line with the current market 

situation. 

6.5.8.5 Fluidised Bed Incinerator 

An Annex to Waste Strategy for England 2007 gives gate fees for MBT facilities which are 

configured to produce an RDF. The capital costs were quoted as follows: 




The document is not clear to which facilities these costs effectively apply. However, it seems 

the intention is that the RDF is combusted, it would seem, in a dedicated waste incinerator 

The preparation of SRF ought to make the use of fluidised bed facilities more appropriate, 

and these should be less demanding in terms of the robustness of construction if the SRF is 

suitably prepared. We have assumed a capital cost of £475 per tonne (2007 figure) which is 

a lower unit capital cost than for incineration. For comparison with Defra’s figures above, this 

gives a net unit capital cost of £365 per tonne, between the figures for facilities of 100 ktpa 

and 200 ktpa scale. 

The operating cost (before energy revenues and disposal costs) is as for a grate incinerator. 

6.5.8.6 MBT Incorporating Anaerobic Step 

There are a growing number of MBT facilities around the world which are operating, or have 

tried to operate, incorporating an anaerobic step. The track record of such facilities is

133 

somewhat chequered. These facilities typically have an intermediate unit capital cost, lower 

than for thermal facilities, but higher than those using aerobic biological treatments. This is 

related to a) the need for pre-treatment of waste (more or less extensive, depending upon the 

nature of the digestion system); and b) the deployment of the digester itself (which may only 

treat a fraction of the incoming waste following pre-treatment). 

There is relatively little published data on the costs of such facilities. We have estimated unit 

capital costs of £325 per tonne and operating costs of £28 per tonne before energy revenues 

and costs of residue disposal. 

6.5.9 Wood Combustion 

We have assumed that in some switches, wood wastes (i.e., not ‘pure biomass’) will be 

burned for the generation of energy. In principle, this could happen in any number of different 

ways, either through incineration, gasification, etc. As long as the material is not pure 

biomass, it seems likely that such facilities would need to demonstrate compliance with the 

Waste Incineration Directive. Since we are dealing here with wood waste, we assume that the 

facilities need to be WID compliant. Much then depends upon what other materials the 

facilities are designed to receive. 

Stevens Croft had a capital cost of around £90 million, the facility being sized for 44MW 

electricity production. A recent report gave a figure of £2200 per kW capacity. For wood, this 

equates to a capital costs of the order £366 per tonne. In this study, we have used the figure 

of £365 per tonne, recognising that there is a very wide range of costs which might be 

estimated. We have used an operating cost of £25 per tonne. 


7.0 Presentation and Discussion of Key Results 

134 

This Section of the report looks at the outputs of the modelling – the MAC curves themselves 

– in the context of a broader understanding of the performance of the different switches in 

terms of GHG abatement, and the costs, per tonne of material treated. As will become clear, it 

is difficult, a priori, to understand the ranking and shape of the MAC curves, but it is rather 

more straightforward to understand the costs and the environmental performance for the 

switches independently. Indeed, one could not fully explain the MAC curves without 

understanding the costs of the switches, and the associated abatement, independently from 

each other. Hence, in what follows, we discuss the abatement potentials and the costs of 

switches first, before discussing the cost-effectiveness ratios. 

It is important to note that we have drawn a cut-off, at CCC’s request, at measures which 

exceed £200 per tonne of CO 2 e abated. Measures which fall above this value are deemed to 

be of no interest in terms of cost-effective abatement in this study. 

7.1 Emissions per Tonne of Waste Switched 

The key dimensions for consideration as regards emissions relate to the differences between 

the IPCC (national) and Global emissions scenarios. The change in rankings in terms of 

emissions related to the switches are shown in Table 7-1. 

The key observations as one moves from one to the other are as follows: 

‣ For switches involving moving waste from landfill to recycling, as expected, under the 

Global accounting method, the position of recycling scenarios improves. This is most 

pronounced for metals and plastics. The move is less pronounced for paper for which 

performance is good even under the IPCC scenario owing to the avoided emissions 

from landfilling; 

‣ The exception to the rule of ‘improved ranking’ for recycling previously landfilled 

material under the global accounting approach is wood. For wood, performance does 

not change in absolute terms, but the ranking worsens as other (recycling) switches 

move ahead of wood in terms of performance under the global accounting convention; 

‣ The same (as for wood) applies for switching organic waste from landfill to composting 

and digestion. Absolute performance does not change but the ranking worsens. As 

expected, performance is better for digestion than for composting; 

‣ For materials being moved from incineration to recycling, two materials show 

interesting switches. For paper and card, the IPCC accounting approach gives negative 

abatement, but under the global approach, the abatement is positive. This leads to a 

marked improvement in ranking under the latter scenario. For dense plastics, recycling 

the material instead of incinerating is the number one option under the IPCC 

accounting approach. Although absolute performance improves under the Global 

accounting approach, the ranking worsens as other recycling options move ahead in 

the ranks. For other materials, where material is being moved from incineration to 

recycling, the ranking improves under the global accounting approach; 

‣ For the switching of organic waste from incineration to composting and digestion, then 

moving from the IPCC scope to the global one leaves absolute performance the same, 

but the ranking worsens for AD, but improves – marginally – for IVC. The IVC case is 

ranked very low in both IPCC and Global scopes; 


135 

Table 7-1: Change in Rankings for Switches Moving from IPPC to Global Emissions Scenario 

Stream Type of Switch Material From To 

Rank 

IPCC 

Rank 

Global 

Change in Rank 

(improvement in 

Global w.r.t. IPPC) 

MSW Increased dry recycling Paper / card Landfill Recycled 23 8 15 

MSW Increased dry recycling Dense plastics Landfill Recycled 67 11 56 

MSW Increased dry recycling Glass Landfill Recycled 67 51 16 

MSW Increased dry recycling Ferrous metal Landfill Recycled 67 16 51 

MSW Increased dry recycling Non ferrous metal Landfill Recycled 67 1 66 

MSW Increased dry recycling WEEE Landfill Recycled 67 22 45 

MSW Increased dry recycling Wood Landfill Recycled 35 63 -28 

MSW Increased composting / AD food waste Food Landfill AD: on-site biogas use (elec) 5 31 -26 

MSW Increased composting / AD food waste Food Landfill AD: compressed biogas used in vehicles 2 28 -26 

MSW Increased composting / AD food waste Food / Green Landfill IVC 27 56 -29 

MSW Increased composting / AD food waste Green Landfill Windrow 12 40 -28 

MSW Increased dry recycling Paper / card Incineration Recycled 114 27 87 

MSW Increased dry recycling Dense plastics Incineration Recycled 1 7 -6 

MSW Increased dry recycling Glass Incineration Recycled 61 44 17 

MSW Increased dry recycling Ferrous metal Incineration Recycled 63 50 13 

MSW Increased dry recycling Non ferrous metal Incineration Recycled 60 6 54 

MSW Increased dry recycling WEEE Incineration Recycled 61 21 40 

MSW Increased dry recycling Wood Incineration Recycled 115 106 9 

MSW Increased composting / AD food waste Food Incineration AD: on-site biogas use (elec) 49 70 -21 

MSW Increased composting / AD food waste Food Incineration AD: compressed biogas used in vehicles 30 55 -25 

MSW Increased composting / AD food waste Food / Green Incineration IVC 107 99 8 

MSW Increased composting / AD food waste Green Incineration Windrow 88 97 -9 

MSW Increased dry recycling Paper / card MBT (baseline) Recycled 42 26 16 

MSW Increased dry recycling Dense plastics MBT (baseline) Recycled 42 15 27 

MSW Increased dry recycling Glass MBT (baseline) Recycled 42 54 -12 

MSW Increased dry recycling Ferrous metal MBT (baseline) Recycled 42 20 22 

MSW Increased dry recycling Non ferrous metal MBT (baseline) Recycled 42 5 37 

MSW Increased dry recycling WEEE MBT (baseline) Recycled 42 25 17 

MSW Increased dry recycling Wood MBT (baseline) Recycled 34 96 -62 


136 


Rank 

IPCC 

Rank 

Global 




MSW Increased composting / AD food waste Food MBT (baseline) AD: on-site biogas use (elec) 18 62 -44 

MSW Increased composting / AD food waste Food MBT (baseline) AD: compressed biogas used in vehicles 8 49 -41 

MSW Increased composting / AD food waste Food / Green MBT (baseline) IVC 50 98 -48 

MSW Increased composting / AD food waste Green MBT (baseline) Windrow 48 95 -47 

MSW Decreased recycling Paper / card Recycled Incineration 31 107 -76 

MSW Decreased recycling Dense plastics Recycled Incineration 116 113 3 

MSW Decreased recycling Glass Recycled Incineration 98 105 -7 

MSW Decreased recycling Ferrous metal Recycled Incineration 97 102 -5 

MSW Decreased recycling Non ferrous metal Recycled Incineration 100 118 -18 

MSW Decreased recycling WEEE Recycled Incineration 98 112 -14 

MSW W T Change Residual waste Landfill MBT: Stabilisation, output to landfill 85 80 5 

MSW W T Change Residual waste Landfill MBT: SRF to gasification (steam turbine) 108 86 22 

MSW W T Change Residual waste Landfill MBT: SRF to gasification (gas engine) 101 67 34 

MSW W T Change Residual waste Landfill MBT: SRF to cement kiln 15 37 -22 

MSW W T Change Residual waste Landfill MBT: SRF to power station 9 34 -25 

MSW W T Change Residual waste Landfill MBT: Stabilisation, output to land recovery 51 59 -8 

MSW W T Change Residual waste Landfill MBT: AD - gas engine 64 74 -10 

MSW W T Change Residual waste Landfill MBT: SRF to dedicated thermal facility 111 83 28 

MSW W T Change Residual waste Landfill Incineration (new elec) 104 77 27 

MSW W T Change Wood Landfill Energy generation (dedicated boiler) 19 45 -26 

MSW IVC pollution control Food / Green IVC IVC + scrubber / biofilter 54 89 -35 

MSW Use of CHP in incinerators Residual waste Incineration Incineration + CHP 39 71 -32 

MSW Use of CHP in AD (food waste) Food AD: on-site biogas use (elec) AD: on-site biogas use + CHP 57 92 -35 

Commercial Increased dry recycling Paper / card Landfill Recycled 23 8 15 

Commercial Increased dry recycling Dense plastics Landfill Recycled 67 11 56 

Commercial Increased dry recycling Glass Landfill Recycled 67 51 16 

Commercial Increased dry recycling Ferrous metal Landfill Recycled 67 16 51 

Commercial Increased dry recycling Non ferrous metal Landfill Recycled 67 1 66 

Commercial Increased dry recycling WEEE Landfill Recycled 67 22 45 

Commercial Increased dry recycling Wood Landfill Recycled 35 63 -28 

Commercial Increased composting / AD food waste Food Landfill AD: on-site biogas use (elec) 5 31 -26 

Commercial Increased composting / AD food waste Food Landfill AD: compressed biogas used in vehicles 2 28 -26 


137 


Rank 

IPCC 

Rank 

Global 




Commercial Increased composting / AD food waste Food / Green Landfill IVC 27 56 -29 

Commercial Increased composting / AD food waste Green Landfill Windrow 12 40 -28 

Commercial Decreased recycling Paper / card Recycled Incineration 31 107 -76 

Commercial Decreased recycling Dense plastics Recycled Incineration 117 114 3 

Commercial Decreased recycling Glass Recycled Incineration 89 103 -14 

Commercial Decreased recycling Ferrous metal Recycled Incineration 93 100 -7 

Commercial Decreased recycling Non ferrous metal Recycled Incineration 93 116 -23 

Commercial Decreased recycling WEEE Recycled Incineration 89 110 -21 

Commercial W T Change Residual waste Landfill MBT: Stabilisation, output to landfill 85 80 5 

Commercial W T Change Residual waste Landfill MBT: SRF to gasification - steam turbine 108 86 22 

Commercial W T Change Residual waste Landfill MBT: SRF to gasification - gas engine 101 67 34 

Commercial W T Change Residual waste Landfill MBT: SRF to cement kiln 15 37 -22 

Commercial W T Change Residual waste Landfill MBT: SRF to power station 9 34 -25 

Commercial W T Change Residual waste Landfill MBT: Stabilisation, output to land recovery 51 59 -8 

Commercial W T Change Residual waste Landfill MBT: AD - gas engine 64 74 -10 

Commercial W T Change Residual waste Landfill MBT: SRF to dedicated thermal facility 111 83 28 

Commercial W T Change Residual waste Landfill Incineration 104 77 27 

Commercial W T Change Wood Landfill Energy generation (dedicated boiler) 19 45 -26 

Commercial IVC pollution control Food / Green IVC IVC + scrubber / biofilter 54 89 -35 

Commercial Use of CHP in incinerators Residual waste Incineration Incineration + CHP 39 71 -32 

Commercial Use of CHP in AD (food waste) Food AD: on-site biogas use (elec) AD: on-site biogas use + CHP 57 92 -35 

Industrial Increased dry recycling Paper / card Landfill Recycled 23 8 15 

Industrial Increased dry recycling Dense plastics Landfill Recycled 67 11 56 

Industrial Increased dry recycling Glass Landfill Recycled 67 51 16 

Industrial Increased dry recycling Ferrous metal Landfill Recycled 67 16 51 

Industrial Increased dry recycling Non ferrous metal Landfill Recycled 67 1 66 

Industrial Increased dry recycling WEEE Landfill Recycled 67 22 45 

Industrial Increased dry recycling Wood Landfill Recycled 35 63 -28 

Industrial Increased composting / AD food waste Food Landfill AD: on-site biogas use (elec) 5 31 -26 

Industrial Increased composting / AD food waste Food Landfill AD: compressed biogas used in vehicles 2 28 -26 

Industrial Increased composting / AD food waste Food / Green Landfill IVC 27 56 -29 

Industrial Increased composting / AD food waste Green Landfill Windrow 12 40 -28 


138 


Rank 

IPCC 

Rank 

Global 




Industrial Decreased recycling Paper / card Recycled Incineration 31 107 -76 

Industrial Decreased recycling Dense plastics Recycled Incineration 117 114 3 

Industrial Decreased recycling Glass Recycled Incineration 89 103 -14 

Industrial Decreased recycling Ferrous metal Recycled Incineration 93 100 -7 

Industrial Decreased recycling Non ferrous metal Recycled Incineration 93 116 -23 

Industrial Decreased recycling WEEE Recycled Incineration 89 110 -21 

Industrial W T Change Residual waste Landfill MBT: Stabilisation, output to landfill 85 80 5 

Industrial W T Change Residual waste Landfill MBT: SRF to gasification - steam turbine 108 86 22 

Industrial W T Change Residual waste Landfill MBT: SRF to gasification - gas engine 101 67 34 

Industrial W T Change Residual waste Landfill MBT: SRF to cement kiln 15 37 -22 

Industrial W T Change Residual waste Landfill MBT: SRF to power station 9 34 -25 

Industrial W T Change Residual waste Landfill MBT: Stabilisation, output to land recovery 51 59 -8 

Industrial W T Change Residual waste Landfill MBT: AD - gas engine 64 74 -10 

Industrial W T Change Residual waste Landfill MBT: SRF to dedicated thermal facility 111 83 28 

Industrial W T Change Residual waste Landfill Incineration 104 77 27 

Industrial W T Change Wood Landfill Energy generation (dedicated boiler) 19 45 -26 

Industrial IVC pollution control Food / Green IVC IVC + scrubber / biofilter 54 89 -35 

Industrial Use of CHP in incinerators Residual waste Incineration Incineration + CHP 39 71 -32 

Industrial Use of CHP in incinerators Food Landspreading AD: on-site biogas use (elec) 26 43 -17 

Industrial Use of CHP in AD (food waste) Food AD: on-site biogas use (elec) AD: on-site biogas use + CHP 57 92 -35 

c&d Increased dry recycling Dense plastics Landfill Recycling 67 11 56 

c&d Increased dry recycling Ferrous metal Landfill Recycling 67 16 51 

c&d Increased dry recycling Non ferrous metal Landfill Recycling 67 1 66 

c&d Increased dry recycling Wood Landfill Recycling 35 63 -28 

c&d Treatment change Wood Landfill Energy generation (dedicated boiler) 19 45 -26 


139 

‣ Where material is being moved from MBT to recycling, for all materials other than 

glass and wood, improvements in performance can be seen when moving to the 

Global accounting approach. This relates to the assumptions concerning recovery of 

materials, as well as to the fact that the MBT switch modelling is not ‘material specific’ 

in nature; 

‣ For organic materials, similar considerations apply. Not only does the ranking worsen 

under the Global scenario due to the fact that there is no additional benefit from 

source segregating material under the Global scenario, but the model attributes 

benefit to recycling of materials from MBT (it is not material specific), so the ranking of 

the composting / AD options worsens further; 

‣ Where material switches from landfill to MBT, a move to Global accounting tends to 

improve absolute performance (because the MBT options recover material). Whether 

ranking increases or falls depends on whether it is ranked relatively high or relatively 

low under the IPCC scope. Those options performing best tend to fall in the ranks in 

the move to Global scope because recycling options ‘leapfrog’ them. Those performing 

less well see improved rankings as they were below the recycling options in the 

rankings under the IPCC scope, so they are not ‘demoted’ in ranking by the improved 

ranking of the recycling options; 

‣ In the case of switching material from landfill to incineration, the absolute 

performance improves under the IPCC approach but worsens in terms of ranking. 

These observations highlight the changes experienced under the different ‘scopes’ used in 

this study. 

7.2 Costs per Tonne of Waste Switched 

The issue of costs also affects the shape of the MAC curves. It is interesting to consider how 

the switch rankings change as the cost metric (Social, Private, Hybrid) changes. Generally, the 

costs of the switch change as one changes metric, though in terms of ranking, the moves 

tend to be less pronounced than in the switch from IPCC to Global (see Table 7-2). The 

following observations are pertinent for the cost per tonne of waste switched (this analysis is 

not affected by the scope in terms of emissions): 

1. Under the Private metric, the switches generally have a lower cost. This relates 

principally to the inclusion of landfill tax in the private cost metric. It is absent in the 

other two. It also reflects the inclusion of support for renewable energy generation 

from AD and gasification; 

2. Under the Social cost metric, landfill is cheap. However, at the same time, capital is 

also cheap. The effect of the social cost metric relative to the private cost metric is 

discernable principally through reference to the relative impact of these two issues – 

the effect of removing landfill tax, and the effect of reducing the cost of capital. 

Landfilling has a lower cost, but capital intense treatments are also placed in a 

relatively advantageous position; and 

3. The Hybrid cost metric incorporates a higher capital cost, but no landfill tax or supports 

for renewable energy. Switch costs tend to resemble the costs under the social cost 

metric but are higher or lower depending largely upon the relative capital intensity of 

the treatments before and after the switch. 


Table 7-2: Rankings and Absolute Values (£/tonne waste switched) for Costs per Tonne of Waste Switched Under Different Cost Metrics 

140 

Largest Swing 

Stream Category Material Baseline Switched to Ranking 

Net cost of switch 2006 / t material 

in Ranking 

Social Private Hybrid Social Private Hybrid 

MSW Increased dry recycling Paper / card Landfill Recycled 46 58 64 18 £23.59 £4.18 £20.57 

MSW Increased dry recycling Dense plastics Landfill Recycled 11 18 16 7 £107.34 £110.43 £105.98 

MSW Increased dry recycling Glass Landfill Recycled 55 71 78 23 £15.91 -£7.96 £12.89 

MSW Increased dry recycling Ferrous metal Landfill Recycled 55 71 78 23 £15.91 -£7.96 £12.89 

MSW Increased dry recycling Non ferrous metal Landfill Recycled 55 71 78 23 £15.91 -£7.96 £12.89 

MSW Increased dry recycling WEEE Landfill Recycled 25 41 27 16 £65.20 £19.52 £59.80 

MSW Increased dry recycling Wood Landfill Recycled 109 110 106 4 -£31.10 -£74.35 -£36.50 

MSW 

Increased composting / 

AD food waste Food Landfill 

AD: on-site biogas use 

(elec) 15 23 20 8 £80.33 £58.84 £90.76 

MSW 



AD: compressed biogas 

used in vehicles 17 22 21 5 £78.07 £61.57 £90.41 

MSW 


AD food waste Food / Green Landfill IVC 22 24 24 2 £72.40 £57.81 £76.49 

MSW 


AD food waste Green Landfill Windrow 38 54 46 16 £27.73 £6.17 £28.74 

MSW Increased dry recycling Paper / card Incineration Recycled 70 86 101 31 £11.24 -£17.44 -£24.03 

MSW Increased dry recycling Dense plastics Incineration Recycled 9 12 17 8 £138.14 £135.43 £104.52 

MSW Increased dry recycling Glass Incineration Recycled 104 103 109 6 -£19.89 -£49.55 -£55.15 

MSW Increased dry recycling Ferrous metal Incineration Recycled 104 103 109 6 -£19.89 -£49.55 -£55.15 

MSW Increased dry recycling Non ferrous metal Incineration Recycled 104 103 109 6 -£19.89 -£49.55 -£55.15 

MSW Increased dry recycling WEEE Incineration Recycled 37 91 94 57 £29.40 -£22.07 -£8.25 

MSW Increased dry recycling Wood Incineration Recycled 83 98 103 20 £3.76 -£39.12 -£32.10 

MSW 


AD food waste Food Incineration 


(elec) 30 42 50 20 £48.55 £18.16 £26.73 

MSW 


AD food waste Food Incineration 



MSW 


AD food waste Food / Green Incineration IVC 94 95 102 8 -£2.18 -£30.52 -£29.42 

MSW 


AD food waste Green Incineration Windrow 98 96 105 9 -£3.06 -£34.01 -£34.29 

MSW Increased dry recycling Paper / card MBT (baseline) Recycled 76 69 93 24 £7.24 -£5.12 -£7.85 

MSW Increased dry recycling Dense plastics MBT (baseline) Recycled 12 17 23 11 £98.67 £113.26 £85.23 

MSW Increased dry recycling Glass MBT (baseline) Recycled 75 68 92 24 £7.24 -£5.12 -£7.85 

MSW Increased dry recycling Ferrous metal MBT (baseline) Recycled 74 67 91 24 £7.24 -£5.12 -£7.85 

MSW Increased dry recycling Non ferrous metal MBT (baseline) Recycled 73 66 90 24 £7.24 -£5.12 -£7.85 


141 


Largest Swing 

in Ranking 


MSW Increased dry recycling WEEE MBT (baseline) Recycled 29 37 43 14 £56.53 £22.36 £39.06 

MSW Increased dry recycling Wood MBT (baseline) Recycled 112 112 112 0 -£43.97 -£78.14 -£61.44 

MSW 


AD food waste Food MBT (baseline) 


(elec) 26 25 26 1 £64.79 £50.82 £63.14 

MSW 


AD food waste Food MBT (baseline) 



MSW 


AD food waste Food / Green MBT (baseline) IVC 28 26 34 8 £56.87 £49.80 £48.88 

MSW 


AD food waste Green MBT (baseline) Windrow 71 65 89 24 £11.07 -£3.61 £0.01 

MSW Decreased recycling Paper / card Recycled Incineration 19 14 13 6 £77.48 £119.91 £113.34 

MSW Decreased recycling Dense plastics Recycled Incineration 78 38 42 40 £5.58 £22.04 £39.79 

MSW Decreased recycling Glass Recycled Incineration 16 13 12 4 £78.61 £122.02 £114.47 

MSW Decreased recycling Ferrous metal Recycled Incineration 10 9 9 1 £132.90 £154.50 £166.38 

MSW Decreased recycling Non ferrous metal Recycled Incineration 3 3 3 0 £195.61 £239.02 £231.47 

MSW Decreased recycling WEEE Recycled Incineration 3 3 3 0 £195.61 £239.02 £231.47 

MSW W T Change Residual waste Landfill 

MBT: Stabilisation, output 

to landfill 51 50 49 2 £18.44 £11.66 £26.91 


MBT: SRF to gasification 

(steam turbine) 86 84 67 19 £2.89 -£13.56 £18.74 


MBT: SRF to gasification 

(gas engine) 97 90 74 23 -£2.25 -£20.33 £14.96 

MSW W T Change Residual waste Landfill MBT: SRF to cement kiln 66 78 62 16 £14.40 -£7.99 £20.70 

MSW W T Change Residual waste Landfill MBT: SRF to power station 66 78 62 16 £14.40 -£7.99 £20.70 



to land recovery 60 64 57 7 £15.87 -£2.20 £22.62 

MSW W T Change Residual waste Landfill MBT: AD - gas engine 45 36 41 9 £25.56 £25.58 £44.32 

MBT: SRF to dedicated 


thermal facility 41 30 33 11 £27.39 £30.99 £50.10 

MSW W T Change Residual waste Landfill Incineration (new elec) 54 33 30 24 £18.32 £25.85 £50.57 

MSW W T Change Wood Landfill 

Energy generation 

(dedicated boiler) 34 45 37 11 £34.06 £15.75 £47.32 

MSW IVC pollution control Food / Green IVC IVC + scrubber / biofilter 92 61 87 31 £1.37 £2.21 £1.67 

MSW 

Use of CHP in 

incinerators Residual waste Incineration Incineration + CHP 81 53 71 28 £4.94 £10.65 £17.71 

MSW 

Use of CHP in AD (food 

waste) 

Food 


(elec) 

AD: on-site biogas use + 

CHP 89 57 84 32 £2.19 £4.95 £5.93 

Commercial Increased dry recycling Paper / card Landfill Recycled 107 102 100 7 -£22.77 -£44.79 -£22.37 

Commercial Increased dry recycling Dense plastics Landfill Recycled 27 27 25 2 £64.48 £38.63 £64.87 

Commercial Increased dry recycling Glass Landfill Recycled 99 99 95 4 -£12.37 -£43.76 -£14.09 


142 


Largest Swing 

in Ranking 


Commercial Increased dry recycling Ferrous metal Landfill Recycled 99 99 95 4 -£12.37 -£43.76 -£14.09 

Commercial Increased dry recycling Non ferrous metal Landfill Recycled 99 99 95 4 -£12.37 -£43.76 -£14.09 

Commercial Increased dry recycling WEEE Landfill Recycled 68 97 81 29 £12.62 -£34.13 £6.48 

Commercial Increased dry recycling Wood Landfill Recycled 110 111 107 4 -£31.68 -£76.00 -£37.82 

Commercial 




(elec) 77 93 76 17 £6.60 -£28.94 £14.68 

Commercial 




used in vehicles 82 92 77 15 £4.35 -£26.21 £14.33 

Commercial 


AD food waste Food / Green Landfill IVC 93 94 88 6 -£1.33 -£29.97 £0.41 

Commercial 


AD food waste Green Landfill Windrow 36 47 44 11 £32.65 £13.38 £34.67 

Commercial Decreased recycling Paper / card Recycled Incineration 21 16 15 6 £72.48 £114.91 £108.34 

Commercial Decreased recycling Dense plastics Recycled Incineration 14 11 11 3 £97.01 £140.42 £132.87 

Commercial Decreased recycling Glass Recycled Incineration 24 20 19 5 £65.61 £109.02 £101.47 

Commercial Decreased recycling Ferrous metal Recycled Incineration 7 7 7 0 £153.61 £197.02 £189.47 

Commercial Decreased recycling Non ferrous metal Recycled Incineration 2 2 2 0 £653.61 £697.02 £689.47 

Commercial Decreased recycling WEEE Recycled Incineration 7 7 7 0 £153.61 £197.02 £189.47 

Commercial W T Change Residual waste Landfill 


to landfill 50 49 48 2 £18.44 £11.66 £26.91 


MBT: SRF to gasification - 

steam turbine 85 83 66 19 £2.89 -£13.56 £18.74 



gas engine 96 89 73 23 -£2.24 -£20.33 £14.96 

Commercial W T Change Residual waste Landfill MBT: SRF to cement kiln 64 76 60 16 £14.40 -£7.98 £20.70 

Commercial W T Change Residual waste Landfill MBT: SRF to power station 64 76 60 16 £14.40 -£7.98 £20.70 




Commercial W T Change Residual waste Landfill MBT: AD - gas engine 44 35 40 9 £25.56 £25.58 £44.32 




Commercial W T Change Residual waste Landfill Incineration 53 32 29 24 £18.32 £25.85 £50.57 


Commercial W T Change Wood Landfill 


Commercial IVC pollution control Food / Green IVC IVC + scrubber / biofilter 91 60 86 31 £1.37 £2.21 £1.67 

Commercial 


incinerators Residual waste Incineration Incineration + CHP 80 52 70 28 £4.94 £10.65 £17.71 

Commercial 


waste) 

Food 


(elec) 


CHP 88 56 83 32 £2.19 £4.95 £5.93 

Industrial Increased dry recycling Paper / card Landfill Recycled 111 108 108 3 -£36.50 -£66.61 -£40.11 


143 


Largest Swing 

in Ranking 


Industrial Increased dry recycling Dense plastics Landfill Recycled 115 115 115 0 -£104.18 -£138.74 -£107.79 

Industrial Increased dry recycling Glass Landfill Recycled 108 109 104 5 -£29.81 -£67.43 -£33.42 

Industrial Increased dry recycling Ferrous metal Landfill Recycled 113 113 113 0 -£94.18 -£128.74 -£97.79 

Industrial Increased dry recycling Non ferrous metal Landfill Recycled 117 117 117 0 -£594.18 -£628.74 -£597.79 

Industrial Increased dry recycling WEEE Landfill Recycled 42 80 54 38 £26.44 -£13.21 £22.83 

Industrial Increased dry recycling Wood Landfill Recycled 102 106 98 8 -£17.87 -£55.09 -£21.48 

Industrial 




(elec) 61 87 52 35 £14.41 -£18.65 £24.55 

Industrial 




used in vehicles 69 85 53 32 £12.16 -£15.92 £24.20 

Industrial 


AD food waste Food / Green Landfill IVC 72 81 75 9 £11.00 -£13.39 £14.80 

Industrial 


AD food waste Green Landfill Windrow 48 70 68 22 £18.84 -£7.53 £18.33 

Industrial Decreased recycling Paper / card Recycled Incineration 20 15 14 6 £72.49 £114.92 £108.35 

Industrial Decreased recycling Dense plastics Recycled Incineration 13 10 10 3 £97.02 £140.43 £132.88 

Industrial Decreased recycling Glass Recycled Incineration 23 19 18 5 £65.62 £109.03 £101.48 

Industrial Decreased recycling Ferrous metal Recycled Incineration 5 5 5 0 £153.62 £197.03 £189.48 

Industrial Decreased recycling Non ferrous metal Recycled Incineration 1 1 1 0 £653.62 £697.03 £689.48 

Industrial Decreased recycling WEEE Recycled Incineration 5 5 5 0 £153.62 £197.03 £189.48 

Industrial W T Change Residual waste Landfill 


to landfill 49 48 47 2 £18.44 £11.66 £26.91 



steam turbine 84 82 65 19 £2.89 -£13.56 £18.74 



gas engine 95 88 72 23 -£2.24 -£20.33 £14.96 

Industrial W T Change Residual waste Landfill MBT: SRF to cement kiln 62 74 58 16 £14.40 -£7.98 £20.70 

Industrial W T Change Residual waste Landfill MBT: SRF to power station 62 74 58 16 £14.40 -£7.98 £20.70 




Industrial W T Change Residual waste Landfill MBT: AD - gas engine 43 34 39 9 £25.56 £25.59 £44.32 




Industrial W T Change Residual waste Landfill Incineration 52 31 28 24 £18.32 £25.85 £50.57 


Industrial W T Change Wood Landfill 


Industrial IVC pollution control Food / Green IVC IVC + scrubber / biofilter 90 59 85 31 £1.37 £2.21 £1.67 


Industrial incinerators Residual waste Incineration Incineration + CHP 79 51 69 28 £4.94 £10.65 £17.71 


144 


Industrial 

Industrial 


incinerators Food Landspreading 



waste) 

Food 

(elec) 

Largest Swing 

in Ranking 



(elec) 47 39 45 8 £19.64 £21.52 £33.39 


CHP 87 55 82 32 £2.19 £4.95 £5.93 

c&d Increased dry recycling Dense plastics Landfill Recycling 116 116 116 0 -£104.19 -£138.75 -£107.80 

c&d Increased dry recycling Ferrous metal Landfill Recycling 114 114 114 0 -£94.19 -£128.75 -£97.80 

c&d Increased dry recycling Non ferrous metal Landfill Recycling 118 118 118 0 -£594.19 -£628.75 -£597.80 

c&d Increased dry recycling Wood Landfill Recycling 103 107 99 8 -£17.88 -£55.10 -£21.49 


c&d Treatment change Wood Landfill 



145 

Interestingly, and of significance for the shape of the MAC curves, there are far more negative 

costs switches under the private cost metric than under the other two. Under the social and 

hybrid cost metrics, there are 26 and 29 negative costs switches, respectively. Under the 

private cost metric, there are 57. Other things being equal, therefore, one might be led to 

thinking that there is greater scope for negative cost abatement under the private cost metric. 

However, this also depends upon which measures are negative cost under the different 

metrics, as well as the abatement potential of each switch under a given emissions scope, i.e. 

Global or IPCC. Evidently, if costs are negative and abatement is positive, these switches are 

of interest, especially if they show significant abatement potential. On the other hand, some 

negative cost measures may deliver ‘negative abatement’, so they are less interesting viewed 

through the lens of ‘cost-effective abatement’. These ‘negative abatement’ measures might 

not be entirely uninteresting if they indicate that the increase in emissions associated with a 

given switch would save sufficient financial resources to be spent more cost-effectively 

elsewhere. The MAC curve presentation does not usually incorporate such switches. 

Generally, only switches delivering positive abatement are considered to be of interest, and 

that is the approach we have followed in this report. 

7.3 Putting it All Together – Average Costs per Tonne of GHG 

Abatement 

It is difficult, a priori, from the above to know clearly which switches will perform well, and 

which will perform poorly, in terms of unit abatement costs. These unit costs are derived as 

ratios. Switches with low unit abatement costs can, therefore, be: 

1. Switches for which the abatement per tonne of waste switched is low, but where costs 

per tonne of waste switched are also low. In this case, the cost per tonne of abatement 

for the switch will be particularly sensitive to the assumptions made (small changes in 

either cost per tonne of waste switched, or in the abatement per tonne of waste 

switched, can lead to significant changes in the costs per tonne of GHG abated); 

2. Switches for which the abatement per tonne of waste is high (or moderately so), but 

where costs per tonne of waste switched are low. In this case, the ranking in terms of 

average cost per tonne of abatement of the switch will be most sensitive to the 

assumptions made around costs; 

3. Switches for which the abatement per tonne of waste is very high, almost irrespective 

of costs of the switch. In this case, the ranking in terms of average cost per unit of 

abatement of the switch will be relatively less sensitive to the assumptions made; 

Evidently, wherever there is positive abatement and a negative cost, the average cost per unit 

of abatement is also negative. Partly because of the fact that what one is examining is a ratio, 

it is difficult to understand the curves other than through their general shapes. 

7.3.1 An Example – the IPCC Social MAC Curve, Central Feasible Potential 

As an example of the ranking of measures under the MACCs, we have commented below 

upon the ordering of switches under the IPCC Social Scenario in 2022 (these rankings are the 

same irrespective of whether the feasible potential is high, medium or low). These are shown 

in Table 7-3. We have shown the rank in terms of unit cost of abatement, and also, the rank 

in terms of abatement per tonne of waste switched. This enables one to see which measures 

are both cost-effective, and capable of delivering large amounts of abatement per tonne of 

waste switched. 


146 

Table 7-3: Ranking in Terms of Cost per Tonne of Abatement and Abatement per Tonne of Switch, Alongside Contribution to Total 

Abatement, IPCC Scope, Social Cost Metric, Central Feasible Potential for 2022 

Stream Nature of Switch Material Before Switch After Switch Rank 

Rank in Terms of 

Abatement per 

Tonne of Switch 

MSW Increased dry recycling Ferrous metal Incineration Recycled 1 70 2.33 

MSW Increased dry recycling Glass Incineration Recycled 2 68 1.81 

MSW Increased dry recycling Non ferrous metal Incineration Recycled 3 67 0.69 

MSW Increased dry recycling Wood MBT Recycled 4 68 0.55 

Commercial Increased dry recycling Wood Landfill Recycled 5 35 4.21 

MSW Increased dry recycling Wood Landfill Recycled 6 36 2.11 

Industrial Increased dry recycling Paper / card Landfill Recycled 7 36 94.51 

CDE Increased dry recycling Wood Landfill Recycled 8 36 35.43 

Industrial Increased dry recycling Wood Landfill Recycled 9 36 15.12 

CO2 equ 

Abated (‘000 

tonnes) 

Commercial Increased dry recycling Paper / card Landfill Recycled 10 23 125.49 

Commercial Increased composting / AD food waste Food / Green Landfill IVC 11 23 139.66 

Commercial Increased composting / AD food waste Food Landfill AD: compressed biogas used in vehicles 13 27 1,181.39 

Commercial Increased composting / AD food waste Food Landfill AD: on-site biogas use (elec) 14 5 0.00 

MSW IVC pollution control Food / Green IVC IVC + scrubber / biofilter 15 27 171.91 

Commercial IVC pollution control Food / Green IVC IVC + scrubber / biofilter 16 2 100.48 

Industrial IVC pollution control Food / Green IVC IVC + scrubber / biofilter 17 5 36.92 

Industrial Increased composting / AD food waste Food Landfill AD: compressed biogas used in vehicles 18 2 723.24 

MSW Use of CHP in incinerators Residual waste Incineration Incineration + CHP 19 43 253.55 

Commercial Use of CHP in incinerators Residual waste Incineration Incineration + CHP 20 43 83.31 

Industrial Use of CHP in incinerators Residual waste Incineration Incineration + CHP 21 43 66.49 

Industrial Increased composting / AD food waste Food Landfill AD: on-site biogas use (elec) 22 43 0.00 

MSW Increased dry recycling Paper / card MBT Recycled 23 15 57.71 

MSW Increased dry recycling Glass MBT Recycled 24 15 8.04 

MSW Increased dry recycling Ferrous metal MBT Recycled 25 15 9.93 

MSW Increased dry recycling Non ferrous metal MBT Recycled 26 55 2.98 

MSW Waste Treatment Change Residual waste Landfill MBT: SRF to power station 27 55 548.07 

Commercial Waste Treatment Change Residual waste Landfill MBT: SRF to power station 28 55 846.38 

Industrial Waste Treatment Change Residual waste Landfill MBT: SRF to power station 29 9 1,078.36 


147 





Industrial Increased composting / AD food waste Food / Green Landfill IVC 30 9 0.00 

CO2 equ 


tonnes) 

MSW Waste Treatment Change Residual waste Landfill MBT: SRF to cement kiln 31 9 424.98 

Commercial Waste Treatment Change Residual waste Landfill MBT: SRF to cement kiln 32 12 656.30 

Industrial Waste Treatment Change Residual waste Landfill MBT: SRF to cement kiln 33 49 836.18 

MSW Use of CHP in AD (food waste) Food AD: on-site biogas use (elec) AD: on-site biogas use + CHP 34 75 14.56 

Commercial Use of CHP in AD (food waste) Food AD: on-site biogas use (elec) AD: on-site biogas use + CHP 35 23 3.14 

Industrial Use of CHP in AD (food waste) Food AD: on-site biogas use (elec) AD: on-site biogas use + CHP 36 12 2.46 

Industrial Increased composting / AD food waste Green Landfill Windrow 37 58 18.06 

MSW Increased composting / AD food waste Green MBT Windrow 38 58 95.25 

Industrial Increased composting / AD food waste Food Landspreading AD: on-site biogas use (elec) 39 58 92.32 

MSW Increased composting / AD food waste Green Landfill Windrow 40 12 131.13 

MSW Increased dry recycling Paper / card Landfill Recycled 41 19 108.11 

Commercial Increased composting / AD food waste Green Landfill Windrow 42 19 370.71 

MSW Waste Treatment Change Wood Landfill Energy generation (dedicated boiler) 43 19 2.45 

CDE Increased dry recycling Wood Landfill Energy generation (dedicated boiler) 43 19 37.41 

Commercial Waste Treatment Change Wood Landfill Energy generation (dedicated boiler) 45 40 3.88 

Industrial Waste Treatment Change Wood Landfill Energy generation (dedicated boiler) 46 40 10.95 

MSW Increased dry recycling Dense plastics Incineration Recycled 47 40 111.29 

MSW Increased composting / AD food waste Food Landfill AD: compressed biogas used in vehicles 48 26 238.67 

MSW Increased composting / AD food waste Food Landfill AD: on-site biogas use (elec) 49 31 0.00 

MSW Waste Treatment Change Residual waste Landfill MBT: Stabilisation, output to land recovery 50 2 417.40 

Commercial Waste Treatment Change Residual waste Landfill MBT: Stabilisation, output to land recovery 51 64 759.98 

Industrial Waste Treatment Change Residual waste Landfill MBT: Stabilisation, output to land recovery 52 64 1,111.68 

MSW Increased composting / AD food waste Food MBT AD: compressed biogas used in vehicles 53 64 408.16 

MSW Increased composting / AD food waste Food Incineration AD: compressed biogas used in vehicles 54 43 148.30 

MSW Increased composting / AD food waste Food MBT AD: on-site biogas use (elec) 55 1 0.00 

MSW Increased composting / AD food waste Food / Green Landfill IVC n/a 5 

MSW Increased dry recycling WEEE MBT Recycled n/a 8 

Commercial Decreased dry recycling Paper / card Recycled Incineration n/a 53 

Industrial Decreased dry recycling Paper / card Recycled Incineration n/a 18 

MSW Decreased dry recycling Paper / card Recycled Incineration n/a 27 

MSW Increased composting / AD food waste Food Incineration AD: on-site biogas use (elec) n/a 54 


148 





MSW Increased composting / AD food waste Food / Green MBT IVC n/a 32 

MSW Increased dry recycling Dense plastics MBT Recycled n/a 32 

MSW Increased dry recycling WEEE Incineration Recycled n/a 32 

MSW Waste Treatment Change Residual waste Landfill MBT: AD - gas engine n/a 43 

Commercial Waste Treatment Change Residual waste Landfill MBT: AD - gas engine n/a 71 

Industrial Waste Treatment Change Residual waste Landfill MBT: AD - gas engine n/a 71 

MSW Increased dry recycling Dense plastics Landfill Recycled n/a 30 

MSW Increased dry recycling Glass Landfill Recycled n/a 76 

MSW Increased dry recycling Ferrous metal Landfill Recycled n/a 76 

MSW Increased dry recycling Non ferrous metal Landfill Recycled n/a 76 

MSW Increased dry recycling WEEE Landfill Recycled n/a 76 

MSW Increased dry recycling Paper / card Incineration Recycled n/a 76 

MSW Increased dry recycling Wood Incineration Recycled n/a 123 

MSW Increased composting / AD food waste Food / Green Incineration IVC n/a 124 

MSW Increased composting / AD food waste Green Incineration Windrow n/a 116 

MSW Decreased dry recycling Dense plastics Recycled Incineration n/a 97 

MSW Decreased dry recycling Glass Recycled Incineration n/a 125 

MSW Decreased dry recycling Ferrous metal Recycled Incineration n/a 107 

MSW Decreased dry recycling Non ferrous metal Recycled Incineration n/a 106 

MSW Decreased dry recycling WEEE Recycled Incineration n/a 109 

MSW Waste Treatment Change Residual waste Landfill MBT: Stabilisation, output to landfill n/a 107 

MSW Waste Treatment Change Residual waste Landfill MBT: SRF to gasification (steam turbine) n/a 94 

MSW Waste Treatment Change Residual waste Landfill MBT: SRF to gasification (gas engine) n/a 117 

MSW Waste Treatment Change Residual waste Landfill MBT: SRF to dedicated n/a 110 

MSW Waste Treatment Change Residual waste Landfill Incineration n/a 120 

Commercial Increased dry recycling Dense plastics Landfill Recycled n/a 113 

Commercial Increased dry recycling Glass Landfill Recycled n/a 76 

Commercial Increased dry recycling Ferrous metal Landfill Recycled n/a 76 

Commercial Increased dry recycling Non ferrous metal Landfill Recycled n/a 76 

Commercial Increased dry recycling WEEE Landfill Recycled n/a 76 

Commercial Decreased dry recycling Dense plastics Recycled Incineration n/a 76 

Commercial Decreased dry recycling Glass Recycled Incineration n/a 126 

CO2 equ 


tonnes) 


149 





Commercial Decreased dry recycling Ferrous metal Recycled Incineration n/a 98 

Commercial Decreased dry recycling Non ferrous metal Recycled Incineration n/a 102 

Commercial Decreased dry recycling WEEE Recycled Incineration n/a 102 

Commercial Waste Treatment Change Residual waste Landfill MBT: Stabilisation, output to landfill n/a 98 

Commercial Waste Treatment Change Residual waste Landfill MBT: SRF to gasification - steam turbine n/a 94 

Commercial Waste Treatment Change Residual waste Landfill MBT: SRF to gasification - gas engine n/a 117 

Commercial Waste Treatment Change Residual waste Landfill MBT: SRF to dedicated n/a 110 

Commercial Waste Treatment Change Residual waste Landfill Incineration n/a 120 

Industrial Increased dry recycling Dense plastics Landfill Recycled n/a 113 

Industrial Increased dry recycling Glass Landfill Recycled n/a 76 

Industrial Increased dry recycling Ferrous metal Landfill Recycled n/a 76 

Industrial Increased dry recycling Non ferrous metal Landfill Recycled n/a 76 

MSW Increased composting / AD food waste Food / Green Landfill IVC n/a 5 

Industrial Increased dry recycling WEEE Landfill Recycled n/a 76 

Industrial Decreased dry recycling Dense plastics Recycled Incineration n/a 76 

Industrial Decreased dry recycling Glass Recycled Incineration n/a 126 

Industrial Decreased dry recycling Ferrous metal Recycled Incineration n/a 98 

Industrial Decreased dry recycling Non ferrous metal Recycled Incineration n/a 102 

Industrial Decreased dry recycling WEEE Recycled Incineration n/a 102 

Industrial Waste Treatment Change Residual waste Landfill MBT: Stabilisation, output to landfill n/a 98 

Industrial Waste Treatment Change Residual waste Landfill MBT: SRF to gasification - steam turbine n/a 94 

Industrial Waste Treatment Change Residual waste Landfill MBT: SRF to gasification - gas engine n/a 117 

Industrial Waste Treatment Change Residual waste Landfill MBT: SRF to dedicated n/a 110 

Industrial Waste Treatment Change Residual waste Landfill Incineration n/a 120 

C&D Increased dry recycling Dense plastics Landfill Recycled n/a 113 

C&D Increased dry recycling Ferrous metal Landfill Recycled n/a 76 

CDE Increased dry recycling Non ferrous metal Landfill Recycled n/a 76 

MSW 

Energy conversion efficiency, 

incineration Residual waste Incineration Incineration + optimisation (elec) n/a 76 

Commercial 



Industrial 



MSW Increased flaring of CO2 at landfill Residual waste Landfill Landfill + flaring n/a 61 

CO2 equ 


tonnes) 


150 





Commercial Increased flaring of CO2 at landfill Residual waste Landfill Landfill + flaring n/a 50 

Industrial Increased flaring of CO2 at landfill Residual waste Landfill Landfill + flaring n/a 50 

MSW Use of CHP in AD (food waste) Food AD: on-site biogas use + CHP AD: on-site biogas use + optimised CHP n/a 50 

Commercial Use of CHP in AD (food waste) Food AD: on-site biogas use + CHP AD: on-site biogas use + optimised CHP n/a 73 

Industrial Use of CHP in AD (food waste) Food AD: on-site biogas use + CHP AD: on-site biogas use + optimised CHP n/a 73 

CO2 equ 


tonnes) 

Note: n/a implies that the unit cost of abatement exceeds £200 per tonne CO 2 equ. This was the cut-off proposed by CCC for the MACC so 

the final column – abatement potential – is empty since these measures do not fall below the £200 cut-off point. 


151 

The following comments are offered (with the switches discussed in order of their ranking in 

terms of cost-effectiveness): 155 

‣ The top ranking options from the perspective of the unit cost of abatement are not 

options which give the highest abatement per tonne of waste switched. They are, 

rather, those options for which the cost per tonne of waste switched is negative, and 

for which abatement is positive. in other words, it is the negative cost which ranks 

these options high rather than their potential to deliver high levels of abatement; 

‣ The 3 most cost effective switches are those that switch non-combustible high value 

materials from incineration to recycling. The 4 th most cost-effective switch moves wood 

from MBT to recycling, again with negative cost but with high levels of abatement. 

‣ The following 6 involve wood and paper & card only. The combined abatement for 

these switches is 277 kt CO 2 equ. 

‣ The next option involves switching commercially collected food and garden waste into 

in-vessel composting, an option again with a fractionally negative cost but a positive 

abatement potential. This delivers just over 140 kt CO 2 equ of abatement; 

‣ The options discussed above – the first eleven ranked switches – all have a negative 

cost per unit of GHG abated. The best ranked switches of these fourteen from the 

perspective of abatement per tonne of waste switched involve the recycling of 

industrial and commercial paper and card instead of landfilling; 

‣ The first options that have a positive cost of abatement are some of the best 

performing in terms of the abatement per tonne of waste switched and total 

abatement potential. They include the switching of commercial food waste and 

industrial food waste from landfill to anaerobic digestion with the gas being cleaned up 

for use as transport fuel. These two switches are the most important switches in the 

set, delivering 1,900 kt CO 2 equ of abatement between them, or around one sixth of 

that is deemed feasible for the year 2022. Note that generating electricity fares worse 

than using gas as transport fuel. The suggestion is that support mechanisms might not 

be properly aligned at present; 

‣ Fitting scrubbers in front of biofilters at compost plants is a relatively low cost measure 

which leads to significant abatement potential (over 310 kt CO 2 equ across MSW, 

commercial and industrial streams). This assumes that this is not happening at 

present and is unlikely to do so in the future. Evidently, the potential for abatement 

here depends upon the expected ‘look’ of IVC facilities in future; 

‣ Because of the low cost of capital assumed under this option, the switch from 

incineration generating electricity only to one operating in CHP mode fares relatively 

well. Even though the abatement per tonne of waste switched is relatively low, the 

sheer quantity of waste being incinerated at this date leads to a contribution of 403 kt 

CO 2 equ of abatement from the MSW, commercial and industrial streams; 

‣ Switching from MBT to recycling ranks 23 rd and delivers around 79 thousand tonnes 

CO 2 equ of abatement from paper and card, glass and metals; 

‣ One of the highest ranking options for residual waste treatment in terms of abatement 

per tonne of waste switched is the use of SRF from MBT processes in power plants 

155 The measures are discussed in order of their ranking in terms of unit cost of abatement. That is the logic 

of MACCs. MACCs do not rank switches in terms of their overall abatement potential. 


152 

instead of landfilling the residual. This is estimated to deliver 2.47 million tonnes CO 2 

equ of abatement from MSW, commercial and industrial streams. It should be noted 

that the potential for abatement through this and the next measure depends very 

much on a range of factors, including: 

1. The extent to which coal-fired power stations are in place in 2022; 

2. The extent to which they are equipped, at that point, to accept SRF, related to the 

quality of flue gas cleaning and other factors; and 

3. The extent to which those coal-fired power stations which are in place will be 

generating electricity without any carbon capture technology at the time; 

It is difficult to know whether our assumptions in respect of the above will be shown to 

stand the test of time; 156 

‣ The next highest ranking option for residual waste treatment in terms of abatement 

per tonne of waste switched is the use of SRF from MBT processes in cement kilns 

instead of landfilling the residual. This is estimated to deliver 1.92 million tonnes CO 2 

equ of abatement from MSW, commercial and industrial streams. The total is lower 

than the abatement from the previous option since we have assumed that additional 

capacity for the off-take of SRF at cement kilns, over and above the baseline level, will 

be limited; 

‣ Ensuring use of heat from AD facilities operating in CHP mode delivers 20 thousand 

tonnes CO 2 equ of abatement from MSW, commercial and industrial streams; 

‣ Moving industrial green waste from landfill to windrow delivers an additional 18 

thousand tonnes CO 2 equ of abatement; 

‣ Increased windrow composting of garden waste previously landfilled or treated at MBT 

delivers 95 thousand tonnes CO 2 equ of abatement from MSW and commercial 

wastes; 

‣ Switching from landspreading of industrial food waste to anaerobic digestion delivers 

almost 92 thousand tonnes CO 2 equ of abatement; 

‣ Moving MSW green waste from landfill to windrow delivers an additional 131 thousand 

tonnes CO 2 equ of abatement; 

‣ Switching from landfill of paper and card from MSW to recycling delivers 108 thousand 

tonnes CO 2 equ of abatement; 

‣ Moving Commercial green waste from landfill to windrow delivers an additional 371 


‣ The switch from landfilling of wood to combustion in a dedicated boiler generates 55 


‣ Dense plastics from MSW being switched from incineration to recycling is the switch 

which gives highest abatement per tonne of waste switched. However, the switch is 

156 Some ‘off-line’ estimation of the potential – under the maximum technical potential scenario – for use of SRF 

in power stations was undertaken using estimates of the capacity of coal-fired power stations in the future. The 

same applies as regards cement kilns. This was used to set a ceiling on the quantity of SRF which could be dealt 

with through the relevant switches. 


153 

costly at £104 per tonne of abatement. It delivers 111 thousand tonnes CO 2 equ of 

abatement; 

‣ Switching MSW from landfill to anaerobic digestion with the gas being cleaned up for 

use as transport fuel delivers 239 thousand tonnes CO 2 equ of abatement; 

‣ The last ranked residual waste option switching residual waste away from landfill is 

that switching waste into stabilisation with the residue spread on land. This delivers 

2.29 million tonnes CO 2 equ of abatement; 

‣ Switching food from MBT to AD with biogas compressed for use in vehicles ranks in 

the top ten measures in terms of abatement per tonne of waste switched. It delivers 

408 thousand tonnes CO 2 equ of abatement; and 

‣ Switching food from incineration to AD with biogas compressed for use in vehicles 

delivers 148 thousand tonnes CO 2 equ of abatement. 

Encouragingly, the highest ranked option – in terms of abatement per tonne of waste 

switched – which falls outside the £200 per tonne of abatement cut-off is ranked 56. 

However, many of the measures which fall inside the cut-off have distinctly mediocre 

performance in terms of abatement per tonne of waste switched. In some cases, this reflects 

assumptions made in developing the baseline concerning what is already being recycled, 

what materials are effectively left in the residual waste stream, and how residual waste is 

managed in the ‘firm and funded’ scenarios. 

There are two key options which drive abatement performance as measured under the IPCC 

scope. They are: 

1. Switching food waste from landfill to AD where biogas is cleaned and compressed for 

use in vehicles. This delivers 2.70 million tonnes CO 2 equ of abatement; 

2. Switching from landfill to other residual waste treatments (MBT with SRF to power 

stations and to cement kilns, as well as MBT stabilisation with output to land). This 

delivers 6.78 million tonnes CO 2 equ of abatement; 

Switches falling into these two categories deliver 75% of all the abatement in this scenario. 

It is important to note that the emissions ‘savings’ presented in this report include both 

emissions falling within and outside the EU-ETS. To the (currently limited) extent that figures 

include savings from sectors which are included under the EU-ETS, this would not generate 

additional abatement in terms of the UK’s carbon account. 

7.3.2 MAC Curves 

Regarding the more general shape of MAC curves, the following comments are offered: 

‣ As expected, abatement potential in later years is greater than in earlier years. This is 

the result of the fact that the switches are progressively rolled out over time (see 

Figure 7-1 to Figure 7-3); 

‣ As expected, abatement potential in high feasible potential is greater than under the 

central, which is greater than under the low feasible potential. This is for obvious 

reasons (see Figure 7-3 to Figure 7-5 and Figure 7-6 to Figure 7-8); 


154 

Figure 7-1: MAC Curve for IPCC Accounting, Social Cost, High Feasible Potential, 2022 

£/ t CO2e abated 

200 

150 

100 

50 

-50 

-100 

0 

0 1 2 3 4 5 6 7 8 9 10 11 12 13 

Mt of CO2e abated 

-150 

-200 

-250 

-300 

-350 

-400 

-450 

-500 



200 

150 

100 

50 

0 

0 

-50 

1 2 

3 4 5 6 7 

8 9 

10 

11 12 13 


-100 

-150 

-200 

-250 

-300 

-350 

-400 

-450 

-500 


155 



200 

150 

100 

50 

0 

0 1 2 3 4 5 6 7 

-50 

8 9 10 11 12 13 


-100 

-150 

-200 

-250 

-300 

-350 

-400 

-450 

-500 

Figure 7-4: MAC Curve for IPCC Accounting, Social Cost, Central Feasible Potential, 2012 


200 

150 

100 

50 

0 

0 

-50 

1 2 3 4 5 6 7 

8 

9 

10 

11 12 13 


-100 

-150 

-200 

-250 

-300 

-350 

-400 

-450 

-500 


156 

Figure 7-5: MAC Curve for IPCC Accounting, Social Cost, Low Feasible Potential, 2012 


200 

150 

100 

50 

0 

0 1 2 3 4 5 6 7 

-50 

8 

9 

10 

11 12 13 


-100 

-150 

-200 

-250 

-300 

-350 

-400 

-450 

-500 



200 

150 

100 

50 

0 

0 1 2 

-50 

3 4 5 6 7 8 9 

10 

11 12 13 


-100 

-150 

-200 

-250 

-300 

-350 

-400 

-450 

-500 


157 

Figure 7-7: MAC Curve for IPCC Accounting, Social Cost, Central Feasible Potential, 2022 


200 

150 

100 

50 

0 

-50 

0 

1 2 3 4 5 6 7 8 9 10 11 12 13 


-100 

-150 

-200 

-250 

-300 

-350 

-400 

-450 

-500 

Figure 7-8: MAC Curve for IPCC Accounting, Social Cost, Low Feasible Potential, 2022 


200 

150 

100 

50 

0 

0 1 2 3 4 5 6 7 

-50 

8 

9 

10 

11 12 13 


-100 

-150 

-200 

-250 

-300 

-350 

-400 

-450 

-500 


158 



200 

150 

100 

50 

0 

0 1 2 3 4 5 6 7 

-50 

8 

9 

10 

11 12 13 


-100 

-150 

-200 

-250 

-300 

-350 

-400 

-450 

-500 

Figure 7-10: MAC Curve for IPCC Accounting, Private Cost, High Feasible Potential, 2022 


200 

150 

100 

50 

0 

0 

-50 

1 

2 

3 

4 

5 

6 

7 8 9 10 11 12 13 


-100 

-150 

-200 

-250 

-300 

-350 

-400 

-450 

-500 

-1,200 


159 

Figure 7-11: MAC Curve for IPCC Accounting, Hybrid Cost, High Feasible Potential, 2022 


200 

150 

100 

50 

0 

-50 

0 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 11 12 

13 


-100 

-150 

-200 

-1,300 



200 

150 

100 

50 

0 

0 2 4 6 8 10 12 14 16 18 20 22 24 26 

-50 


-100 

-150 

-200 

-250 

-300 

-350 

-400 

-450 

-500 


160 

Figure 7-13: MAC Curve for Global Accounting, Social Cost, High Feasible Potential, 2022 


200 

150 

100 

50 

0 

0 

2 4 6 8 10 12 14 16 18 20 22 24 26 


-50 

-100 

-1,050 

Figure 7-14: MAC Curve for Global Accounting, Private Cost, High Feasible Potential, 2022 


200 

180 

160 

140 

120 

100 

80 

60 

40 

20 

0 

-20 0 2 4 6 8 10 12 14 16 18 20 22 24 26 

-40 

-60 

-80 

-100 

-120 

-140 

-160 

-180 

-200 

-220 

-240 

-260 

-280 


-1,880 


161 

Figure 7-15: MAC Curve for Global Accounting, Hybrid Cost, High Feasible Potential, 2022 


200 

180 

160 

140 

120 

100 

80 

60 

40 

20 

0 

0 

-20 

-40 

2 4 6 8 10 12 14 16 18 20 22 24 26 


-60 

-80 

-100 

-120 

-140 

-160 

-1,480 

Figure 7-16: MAC Curve for Hybrid Accounting, Social Cost, High Feasible Potential, 2022 


200 

150 

100 

50 

0 

0 2 4 6 8 10 12 14 16 18 20 22 24 26 

-50 


-100 

-1,050 


162 

Figure 7-17: MAC Curve for Hybrid Accounting, Private Cost, High Feasible Potential, 2022 


200 

180 

160 

140 

120 

100 

80 

60 

40 

20 

0 

-20 0 2 4 6 8 

-40 

-60 

-80 

-100 

-120 

-140 

-160 

-180 

-200 

-220 

-240 

-260 

-280 

10 

12 14 16 18 20 22 24 26 


-1,880 

Figure 7-18: MAC Curve for Hybrid Accounting, Hybrid Cost, High Feasible Potential, 2022 


200 

180 

160 

140 

120 

100 

80 

60 

40 

20 

0 

0 

-20 

2 4 6 8 10 

-40 

-60 

-80 

-100 

-120 

-140 

-160 

12 

14 16 18 20 22 24 26 


-1,480 


163 

‣ There is generally more ‘below the line’ (i.e. negative cost) abatement under the 

private cost metric. This is due, as explained in Section 7.2 above, to the fact that the 

private cost metric makes landfill more expensive (owing to the inclusion of landfill 

tax), and though the cost of capital is greater in the private cost metric than under the 

social cost metric, the increase in costs implied by this change is not as great as the 

real (2006 terms) level of the tax in future (see Figure 7-9 to Figure 7-11 and Figure 

7-13 to Figure 7-15); 157 

‣ There is generally greater abatement under the Global accounting methodology than 

under the IPCC accounting approach (compare Figure 7-9 to Figure 7-11 with Figure 

7-13 to Figure 7-15). This is because of the inclusion of avoided emissions associated 

with the recycling of dry recyclables, both in recycling options, and in treatment options 

where materials are recovered from residual waste (i.e. all the non-landfill residual 

waste treatments); 

‣ The total abatement under the IPCC scope tends to run in the following order: 

Social > Hybrid > Private (see Figure 7-9 to Figure 7-11). However, as Figure 7-13 

to Figure 7-15 show, under the Global scope, the ordering runs differently 

Hybrid > Social > Private 

The reasons for this are not entirely straightforward to explain (see Section 7.3.3). 

‣ There is a high proportion of ‘below the line’ abatement in the private cost metric, but 

total abatement is lower. 158 

7.3.3 Variation in Abatement with Relation to Cost Metrics 

The previous section highlights the fact that the abatement potential for the cost metrics ran 

differently for IPCC and Global scopes. Under the IPCC scope, the order is 

Social > Hybrid > Private, 

but under Global scope, the order is 

Hybrid > Social > Private. 

The difference in the abatement potentials of the cost metrics under the Global scope will be 

described first, then the factors that cause a shift in the ordering (in terms of abatement 

achieved under different the cost metrics for the IPCC scope) will be discussed. 

To determine why the levels of abatement change with the different cost metrics, the 

switches with the most abatement potential were considered in isolation with the focus on 

the high feasible potential MACCs. The differences occur largely because of the ordering of 

MBT and AD switches. 

It is clear that the most abatement comes from switches of residual waste from landfill to 

MBT treatments. This, and the differentials in abatement from switches to AD treatments, 

157 It will be recalled that we have assumed that the landfill tax reaches its £48 per tonne nominal level in 2010 

and is assumed to stay constant in real terms thereafter. 

158 It should be recalled that the analysis of switches does not include all materials. It has looked at those which, 

a priori, are thought likely to deliver reasonable GHG benefits. It is entirely possible that switches would occur 

which deal with material NOT currently covered by the material-specific switches, thus removing them from 

residual waste. We are seriously hindered in this analysis by the more or less complete absence of meaningful 

composition data in the commercial and industrial waste streams, and the effect of this may be to accentuate 

the significance of ‘residual waste’ in the commercial and industrial waste to the overall contribution to GHG 

abatement (in other words, what is assumed to remain ‘residual’ in this analysis might not, in fact, be residual 

waste in 2022 as a result of other measures). 


164 

provides the basis for understanding the logic behind the total abatement achieved. The 

predominance of the MBT treatments comes from the combination of high quantities of 

landfilled material in the baseline and the rationale to switch large proportions of this 

material to MBT (in essence there is no reason why all the material from landfill cannot be 

diverted to MBT, the only constraints on these switches being technical or regulatory issues). 

AD also figures highly because of the significant environmental benefit of switching food 

waste from processes which perform very poorly in terms of GHG emissions to those which 

perform rather well. This performance is not affected by the scope chosen for the GHG 

assessment. 

Firstly, we consider the MBT treatment switches since they tend to deliver the highest 

proportion of abatement achieved. Under the Global scope there are six MBT processes that 

are under the £200 limit in terms of the unit cost of abatement. These are shown, along with 

unit impacts for comparison, in Table 7-4 below. 

Table 7-4: MBT Treatments and Associated Unit Impacts 

Treatment 

kgs of CO 2 equ abated / tonne waste 

treated 

MBT: SRF to power station 592.5 

MBT: SRF to cement kiln 557.1 

MBT: SRF to gasification - gas engine 97.5 

MBT: SRF to gasification – steam turbine 57.1 

MBT: Stabilisation, output to land recovery 284.8 

MBT: Stabilisation, output to landfill 152.4 

As the amount of CO 2 equ abated does not necessarily correlate to the net cost of the switch 

when looking at individual treatment switches. Both the unit impact of the switch and the cost 

of the switch play a role in determining the cost effectiveness of a switch, and this determines 

its ranking in the MACC curve. This is crucial in determining the total amount of abated 

because of the sequential logic effectively implied by the MACC. 

This is exemplified by comparing the private and the hybrid cost metrics. MBT SRF to 

Gasification (steam turbine and gas engine) are the highest ranking residual waste treatment 

switches under the private cost metric, but also have relatively low abatement potential per 

tonne of waste switched relative to other MBT processes (see Table 7-4 above). As sequential 

logic was followed for this study (see Section 3.2.1 for a discussion) a large amount of 

material was switched from landfill to this type of MBT process. The amount switched for gas 

engine was limited because the technology is still unproven at a commercial level in this 

country. 


165 

The next MBT treatment is Land Recovery whereby no technical constraints are placed on the 

potential to divert all residual waste to this process. 159 The MBT treatments with higher 

abatement per tonne of waste treated are far lower down the rankings. Because there is ‘no 

material left’ to switch away from landfill to the options that deliver higher abatement per 

tonne of waste switched, overall abatement potential is reduced. However, the average 

marginal cost will be minimised following the sequential approach. This does highlight the 

limits of the sequential logic applied in MACC modelling, but it also raises questions regarding 

the completeness of the set of switches modelled. 

Under the hybrid metric, where the gasification switches do not come below the £200 cut off 

(the revenue from ROCs is excluded whilst the capital costs are still costed at the same cost 

of capital used under the private cost metric), the amount abated by MBT is far higher. This is 

because in the hybrid costing, there is more material being treated by processes (power / 

cement kiln / output to land recovery) with much greater potential for abatement per tonne of 

material switched, and so the total abatement potential increases. It should be noted that 

uptake at these facilities is also limited in our modelling. 

This highlights some of the issues faced in MACC modelling in the case where the different 

measures are ‘non-exclusive’. The different measures being considered actually involve 

dealing with material which, in the modelling, once dealt with in one way are not capable of 

being dealt with in another way. 

We now turn our focus to the increases in total abatement when moving from Private to 

Social to Hybrid cost metrics, combining the effects and reasons for changes in rankings of 

the major treatment categories. 

Moving from the private to the social cost metric, the increase in abatement from AD 

processes can be attributed to two factors. Firstly, when moving from Private to Social metrics 

the revenue benefits of renewable energy generation are lost. As a result, the AD switch 

involving use of biogas for electricity generation now becomes less cost effective than the one 

where biogas is used in vehicles. This is important as the net benefit from the latter process is 

nearly double the benefit from the former. The second effect is that as the MBT switches drop 

in the rankings, more food waste is available for diversion from landfill into AD processes 

(whereas under the private cost metric, much of this material has already been switched into 

an alternative residual waste treatment process). 

Finally, as we move from the Social to the Hybrid metric, the key factor influencing costeffectiveness 

is the change in capital costs. This has little effect on the AD switches as the 

biogas to vehicles option remains the more cost-effective option. The only result is that all the 

MBT and AD processes move down in the rankings due to the improved (relative) 

performance of recycling in terms of cost-effectiveness. This is because the proportion of 

costs related to the deployment of capital is much lower for the recycling options than for the 

options involving AD or residual waste treatment, at least as they are modelled in this study. 

The most significant change here, which relates to only one switch, is the loss of the MBT 

gasification switches from the rankings. The switch drops out of the rankings as under the 

hybrid cost metric there is no ROC-related revenue associated with renewable energy 

generation, but the capital costs are relatively high. The change is significant because the 

159 There may be regulatory ones. However, what these may or may not be, and how they might constrain the 

use of the approach (because, for example, of a limited availability of appropriate outlets for residues) would 

require much more detailed analysis of the specific measure. Suffice to say, a supportive policy environment 

could allow widespread deployment. 


166 

shift of material away from landfill does not happen early on in the rankings, and is now taken 

up by the switches MBT: SRF to power stations and MBT with output to land recovery. Both 

have significantly higher abatement potential per tonne of waste treated. This is also the 

reason why the abatement attributed to the AD options increases, as more food waste is now 

treated by higher performing options (i.e. through AD, rather than residual treatments) than 

before. 

Now turning to the levels of abatement achieved under the IPCC scope, we can see from 

Figure 7-19 that the ordering of cost metrics in terms of total abatement achieved is as 

follows Social > Hybrid > Private. The two main differences with in the results for the Global 

scope are: 

‣ First, the abatement under both Social and Private metrics has increased relative to 

the Hybrid metric; 

‣ Second under the Hybrid metric there is a lack of residual treatment switches which 

fall below the cut-off of £200 per tonne CO 2 equ imposed upon the modelling. Thus 

there is still a significant tonnage of active waste being managed through landfilling in 

2022. 

Figure 7-19: Abatement of Major Treatment Switches for each Cost Metric – IPCC Scope – 

High Feasible Potential 2022 

14 

12 

10 

Abatement CO2e, Mt 

8 

6 


IVC / Windrow Abatement 

AD Abatement 

MBT Abatement 

4 

2 

0 

Private Hybrid Social 

Cost Metric 

Interestingly, under the Hybrid cost metric, the highest rank switch from landfill to another 

residual waste treatment option which is not significantly constrained in terms of total 

throughput (i.e. not cement kilns or power stations) is MBT output to land recovery. This 

switch falls just above the £200 per tonne CO 2 equ cut-off at £208 per tonne CO 2 equ abated. 

If this cut-off was subsequently raised just slightly higher, significant additional abatement 

could be achieved (and the same would apply if this was this case for any other non-landfill 

residual waste treatment, the point being that in the existing rankings, there is no technically 

unconstrained residual waste treatment option falling below the £200 per tonne CO 2 equ cut- 


167 

off). This is the main reason why the Hybrid abatement is lower than the Social under the 

IPCC scope, as under the Global scope more residual treatment switches fall under the £200 

cut-off and therefore limit the amount of active waste being deposited in landfill. 

Figure 7-19 also illustrates clearly that in the model runs undertaken, the majority of 

abatement under the IPCC scope is achieved through switches to AD and MBT processes. The 

level of abatement delivered by switches to AD is higher for the Hybrid and Social metrics 

than for the Private metric, in much the same way as described above for the Global scope. 

This is because the loss of ROC-related revenue from energy generation makes the use of 

compressed biogas in vehicles a more cost effective switch, which is significant because the 

abatement per tonne of waste treated is nearly double that for the case where electricity is 

being generated. In addition MBT switches have moved down the rankings allowing for more 

food waste to be processed by AD facilities. 

Abatement from MBT processes is lowest under the Hybrid metric because many MBT (and 

other residual waste treatment) switches are ranked above £200 per tonne CO 2 equ when 

using this cost metric. The abatement is lower under the Private metric than under the Social 

metric because MBT output to land recovery falls above SRF to power in the rankings, 

reducing the quantity of waste being switched to the MBT management approaches which 

deliver better abatement performance (see Table 7-4). 

7.4 Landfill Gas Capture Rate 

A short analysis was undertaken to look at the sensitivities of the model in relation to landfill 

gas capture. In addition, this may also act as a proxy to view the sensitivity of the model on a 

whole host of variables. 

As discussed previously, the landfill gas capture rate was set at 75% as requested by Defra 

and CCC. We then varied the gas capture rate between 20 and 100%. The results are shown 

below in Figure 7-20 and relate to IPCC Social, Central feasibility in 2022. 

It is clear that the modelling is quite sensitive to changes in the landfill gas capture rate. 

Interestingly, at the higher capture rates (50%-80%), there is clearly sensitivity of a number of 

switches to the landfill gas capture rate, affecting the rankings, and giving no clear ‘trend’ in 

terms of the abatement which might be achieved. Once the capture rate falls below 50%, this 

would appear to be the point below which the rankings start to include a wider range of 

measures delivering a more consistent increase in the level of abatement. 

The difference between using the 75% figure, and using the IPCC default figure of 20% (also 

used in recent work by the European Environment Agency, but almost certainly too low for the 

UK situation) is, as might be expected, considerable. The level of abatement more or less 

doubles. 


168 

Figure 7-20: Total Abatement Achieved vs. Landfill Gas Capture Rate 

25 

20 

Total Abatement CO2 equ, Mt 

15 

10 

5 

0 

20% 30% 40% 50% 60% 70% 80% 90% 100% 

Landfill Gas Capture Rate 

7.5 Levels of Abatement Achievable 

The level of abatement achievable under the different approaches is significant. For Social 

costs, by 2022, under the high feasible potential scenario, the level of abatement achievable 

is as high as 12.19 million tonnes in 2022 under the IPCC accounting approach, 18.50 

million tonnes under the Global accounting methodology, or 11.65 million tonnes in the 

Hybrid approach. 

It is worth commenting upon sensitivity of the abatement achieved to the baseline 

assumptions. If the baseline ‘firm and funded’ scenario understates the degree to which 

waste is shifted away from landfill (i.e. it assumes there will still be a considerable quantity of 

waste being landfilled), then this is likely to over-state the potential for abatement in future 

(since much of this – particularly under the IPCC scope - relates to switches away from 

landfill). 

7.6 Potential Implications for Policy 

In respect of policy implications, one would tentatively suggest that consideration of the 

following issues would be useful: 

1. The internal consistency of support mechanisms for the generation of energy or fuel 

from the same feedstock, notably biogas, deserves examination. The current support 

measures favour electricity generation, which delivers less GHG abatement than the 

use of biogas as vehicle fuel. As discussed above, if one strips out the revenue which 

might be derived from ROCs, the performance of AD options where the biogas is used 

as vehicle fuel appears rather better than in the case where the biogas is used for 

electricity. The abatement performance of AD where biogas is used in vehicles is 


169 

superior (and depending upon gas upgrading methods, there may be some 

sequestration of biogenic CO 2 also); 

2. Where the use of SRF displaces high carbon content fuels, the carbon benefits can be 

significant. To the extent that coal may still have a role to play in the UK energy mix, 

then consideration of measures to incentivise, or regulate in favour of, the 

development of markets for SRF to replace fossil fuels in power stations and kilns may 

have some merit. This needs to be considered in the context of ongoing discussions 

around the desirability of new coal fired power stations with or without a clear concept 

for carbon capture and storage in place; 

3. There would be merit in seeking to provide regulatory clarity in respect of the use of 

residuals from MBT processes on land. This is somewhat obscure at present. Other 

countries have managed to elicit relatively clear policies in this respect, referring to 

standardised measures of potentially toxic elements in land-applied material, and 

setting out rules which make clear where materials which achieve specific standards 

may be applied, and where they may not be applied. 

These measures are those which affect the treatment options which contribute most to the 

abatement under the IPCC scope. 

7.7 Ancillary Costs and Benefits 

The literature regarding external costs and benefits of different waste management activities 

is generally focused upon air emissions, and the disamenity from landfills and incineration. 160 

The changes being considered are likely to lead to: 

‣ A reduction in disamenity associated with landfilling; 

‣ An increase in disamenity associated with non-landfill treatments; 

‣ An increase in emissions of some conventional air pollutants from alternative residual 

waste treatments and from AD; and 

‣ A reduction in emissions – not necessarily in the UK – of conventional air pollutants as 

a consequence of the increase in recycling. 

There will be offsetting benefits from energy generation, but these will depend upon the 

pollutant intensity of the marginal source of energy generation. 

The net effect, therefore, is complex. It is certainly not clear that the ancillary benefits are 

unequivocally positive. This might be a reflection of the fact that, notwithstanding the 

problems associated with landfilling, most studies suggest that the main externalities are 

associated with methane emissions. It is not necessarily the case, where other treatments 

are concerned, that their main impacts are related to GHGs. Consequently, the switches 

which generate the MACC curve may address GHGs, but some of these switches may lead to 

increased impacts in other areas. 

Where disamenity is concerned, it cannot be assumed that moving waste away from landfill 

improves matters. Few studies on disamenity have been carried out at facilities other than 

landfills (none of significance in this country). However, given that many non-landfill facilities 

160 For a review of work of relevance to the UK, see Eunomia (2007) Managing Biowastes from Households in 

the UK: Applying Life-cycle Thinking in the Framework of Cost-benefit Analysis, Final report to WRAP, May 2007, 

Chapter 10, http://www.wrap.org.uk/downloads/Biowaste_CBA_Final_Report_May_2007.32bff793.3824.pdf . 


170 

are likely to be developed in more densely populated areas than is the case with landfills, the 

net disamenity effect of the shift away from landfill should not be assumed to be negative. 

The dry recycling options are less likely to give rise to concerns of this nature. For all other 

treatments, the devil is, so to speak, in the detail. The matter is clouded by the fact that some 

of the non-GHG emissions from landfill, whilst they are thought to hold the potential to do 

harm, have not been characterised by tolerably good dose response functions which would 

allow for an assessment of the impact of these non-GHG emissions. Were these 

demonstrated to have the potential to harm residents nearby, then clearly, the ancillary 

benefits would be more likely to be positive. 


171 

8.0 Concluding Remarks 

There are a number of issues which this work raises from the perspective of policy 

development. The first relates to the fact that data concerning waste quantities and waste 

composition is still very poor. This means that the extent to which any given switch can lead to 

changes in the management of a given material, and the implied levels of abatement 

anticipated, are uncertain precisely because they are heavily reliant upon the quality of this 

underlying data. Defra has a Waste Data Strategy being rolled out, but it is unlikely that this 

data strategy will lead to an improvement in our understanding of matters such as 

composition of commercial and industrial waste, nor trends in arisings, in the short-term. 

These data issues are clearly compounded by the fact that we are trying to understand 

changes in management method relative to a ‘firm and funded’ baseline, which is very much 

in a state of flux. 

Other important comments relate to some of the key assumptions which we have been asked 

to use in the modelling. Most important of these, because of their effects on the analysis, are: 

1. The assumption regarding landfill gas captures. Eunomia believes that the 75% figure 

is too high as a lifetime capture rate. There are a number of consequences which 

would flow from a change in this assumption: 

a. The baseline level of emissions from landfill would be higher than is currently 

being reported as part of the UK inventory; 

b. All methods which switch material away from landfill would, other things being 

equal, deliver higher abatement per tonne of material switched; 

c. The unit costs of abatement of the switches would fall; 

d. The potential for future abatement would increase, other things being equal, as 

a result of the increase in abatement achieved by each measure as a result of 

two effects: 

i. The increase in abatement per tonne of material switched; 

ii. The increase in the number of measures which fall below a specified 

cut-off level for the unit cost of GHG abatement 

Having said this, there are clearly wider issues, in Eunomia’s view, with the landfill 

model we have been asked to use (so ‘other things’ are ‘probably not equal’). We 

understand these are being addressed through a separate Defra contract. 

2. The assumptions concerning the source of electricity which is being displaced ‘at the 

margin’. The figures we have used come from BERR’s modelling of the baseline firm 

and funded option. With additional policies in place, the expectation might be that the 

carbon intensity of the displaced source of electricity would fall as new / additional 

policies take effect. This would reduce the greenhouse gas-related benefits associated 

with generation of energy, though if energy prices increase at the same time, one 

might expect a compensating influence on cost effectiveness of abatement through 

enhanced revenues from energy sales (depending upon the cost metric and the 

policies used to drive this change). 

Other limitations to the model include that: 


172 

• For some materials, for example, wood, the degree to which material may or my not 

be recyclable is unclear. This affects both baseline and the changes under future 

options; 

• Giving average costs for some switches is not at all straightforward. What one has to 

do, at the margin, to increase the quantity of material switched from one route to 

another will affect the cost of that switch. 

• Care would need to be taken in changing the value of energy delivered in this 

modelling. There is no means to link, within the modelling, the value of raw materials 

to the value of fuel. Clearly, this link exists, and where waste management is 

concerned, if energy prices rise, so the prices of primary commodities are likely to 

increase too. It might be acceptable to tweak energy prices, but significant and 

sustained changes in energy prices are not merely ‘perturbations’ to an economy. 

They become shocks. We would recommend that CCC seeks to ensure that, where it 

varies energy prices in its modelling, it considers the potential links (inter alia) through 

to commodity prices. This is important, in the waste management sector, for 

understanding changes in revenues derived from recycling, whilst it would also be 

difficult to imagine that capital costs for any major infrastructure project would remain 

unaffected by changes in the prices of raw materials that significant increases in 

energy prices would be likely to generate. 161 

A key remark worth making about this work is that the number of variables which drive the 

analysis is very large indeed. Sensitivity analysis conducted around both costs per tonne of 

waste switched, and the abatement per tonne of waste switched, could clearly have a bearing 

upon where a given switch is ranked in the overall list of treatment switches, particularly 

where the numerator and the denominator (the cost, and the level of abatement, respectively) 

are both small. Having said that, the more important switches in terms of delivering 

abatement, are those where the abatement potential per tonne of waste switched is large. In 

these cases, unless one has good reason to believe that costs should be varied significantly 

in the sensitivity analysis, it is the sensitivity with regard to costs which is most important, but 

sensitivity will be significant (for mathematical reasons) only where the costs of the switch are 

low. Interestingly, it is exactly in these cases (where costs are low) that a switch with high 

abatement per tonne of waste switched is likely to perform especially well in the rankings. 

Unless sensitivity analysis varies costs considerably, the high ranking position is likely to be 

maintained. 

Critically, it is worth stating that a key objective of this work has been the development of ‘the 

model’. The model provides the user with the capability to change specific variables and to 

conduct analysis under different scenarios, scopes (of abatement) and cost metrics. In the 

type of analysis undertaken, however, one cannot avoid choosing point estimates, and we 

have sought to do this using publicly available sources where possible. In addition, the 

various metrics used to characterise costs can be considered a form of sensitivity analysis, 

though quite clearly, these metrics do not necessarily imply a flexing of all parameters one 

might wish to see flexed in a sensitivity analysis. 

161 For capital facilities, a separate construction price inflation index would seem to be relevant, and where 

significant changes to energy prices were being modelled, this ought to be reflected in the construction price 

inflation index. 


8.1 IPCC or Global 

173 

Defra’s waste policy rightly demonstrates the potential benefits, in terms of climate change, 

of pursuing a strategy predicated on pursuit of the waste hierarchy. At the same time, it is 

quite clear that the way in which countries report inventories to the IPCC works in such a way 

that the benefits to the global climate of recycling are not always recognized in the inventory 

of a given country. An important question which follows, therefore, is whether one should 

seek to consider the abatement potential under the IPCC accounting methodology, or under 

the Global perspective The CCC has made an explicit decision to concentrate on emissions 

as reported to the IPCC. At the same time, CCC has been keen to explore – notably through 

the differing scopes looked at in the modelling – the implications of varying this assumption. 

It becomes of some interest to understand the extent to which the decision made by the CCC 

to concentrate on IPCC inventories is consistent with the policy elaborated by Defra, one aim 

of which is to reduce greenhouse gas emissions, but measured using the global accounting 

perspective. 

It might be supposed that focusing narrowly on the IPCC reporting conventions is likely, to the 

extent that policy shifts to reflect reductions in these, to guide the management of waste 

more on the basis of the generation of energy than on the saving of energy embodied in 

materials. Defra’s existing waste strategy broadly reflects the latter approach. Other countries 

have also highlighted GHG savings associated with recycling-led policies. Suffice to say, it 

might seem perverse to support measures – justified on the basis of climate change impacts 

– which seek to switch material into some routes rather than others, even though other 

routes would improve the net impact of waste management on the global climate. 

The concept of the Hybrid scope MAC curve seems important in this context. This is the 

situation in which the abatement achieved is reported as under the IPCC scope, but where 

the unit costs of abatement are calculated as they would be when the abatement is assumed 

to be as under the Global accounting approach. This seeks to show which policies fare well in 

terms of the cost per unit of abatement when global emissions are accounted for, but it only 

reveals the GHG emission savings which would register under the IPCC accounting approach. 

It seems important to note, therefore, that under the hybrid accounting approach, the 

abatement delivered is more or less the same as under the IPCC accounting approach, but 

that clearly, since the ranking of switches in terms of the unit cost of abatement reflects the 

Global accounting approach, then it might be expected that greater benefits – in terms of 

global climate change – are likely to flow from this situation than that where policy is 

configured to reflect the IPCC accounting convention. In other words, if policy is oriented to do 

what is most cost—effective for the planet, any penalty, in terms of a worsened position in 

respect of UK inventories – might well be rather small, at least under the assumptions used in 

this analysis. 

It would seem important, therefore, for CCC, Defra and the Environment Agency to reflect on 

what should really drive waste management policy in relation to climate change in the current 

context. Is it the issue of climate change, or the UK’s emissions as reported to the IPCC The 

two may give the same outcome in terms of inventories reported to the IPCC, but focussing 

more narrowly on the IPCC inventory might diminish the contribution made by waste 

management to addressing global emissions. Policy oriented towards improving global 

outcomes, on the other hand, would probably deliver similar results where the IPCC inventory 

is concerned. 


8.2 A 2050 Vision 

174 

The work which has been undertaken for the MACC modelling has been focused on the 

current situation, and how this might change out to 2022. The question remains as to how 

the picture might change in the longer-term. 

CCC is of the view that by 2050, the energy and transportation systems will have been 

substantially ‘de-carbonised’. What might this imply for the selection of waste management 

methods within a MACC modelling framework 

As we have seen, the cost-effectiveness of different treatment switches depends upon the 

costs of the switch and the abatement achieved by the switch. Logically, therefore, as one 

looks to the future, one seeks to understand how climate change performance, and costs, of 

different options will changes as a result of the ‘de-carbonisation’ of energy and transport 

fuels. 

In essence, what this would do is render the emissions credits, for those technologies which 

generate either energy or fuel, relatively insignificant. Since the credit element would fall 

close to zero, the key determinants of the GHG performance of the different waste 

management options would be the non-CO 2 GHG emissions, and the fossil emissions of CO 2 . 

This implies that, since landfilling of material would be marginalized even by 2022, the 

emphasis would potentially fall on: 

‣ Minimizing any residual methane emissions from landfills (from waste landfilled in the 

past) through improved capture mechanisms or improved oxidation of residual 

emissions; 

‣ Minimizing the thermal treatment of waste with a fossil carbon content; 

‣ Improving understanding of the causes of, and minimizing the emissions of, CH 4 and 

N 2 O from waste treatment processes. 

Depending upon the evolution of waste management between now and 2050, a major part of 

the net emissions of greenhouse gases could well be the thermal treatment of waste with a 

fossil carbon element. Hence, policy might consider the wisdom of one or more of the 

following: 

‣ seeking to shift materials consumption towards materials containing non-fossil carbon; 

or 

‣ seeking to ensure that all fossil carbon is kept out of the residual waste stream; or 

‣ phasing out the use of thermal processes to the extent that neither of the above two 

are deemed feasible, and to the extent that they lead to the release of fossil carbon as 

CO 2 . 

This would help to ensure that the only CO 2 emitted from waste treatment processes was of 

non-fossil origin. To the extent that decarbonisation of energy and vehicle fuel would be 

reliant upon biomass energy, the first of the above options might raise questions regarding 

the potential of the available land mass to provide all material and energy needs in the year 

2050. This, of course, is a question beyond the scope of this study, but it perhaps sheds 

some light on the types of question which may have to be faced, as well as raising the more 

fundamental question as to whether consumption levels can really be sustained in a world 

where the desire to de-carbonise energy flows is predicated upon the ability of land to provide 

the necessary ‘net photosynthetic product’ to deliver such a scenario. This re-emphasises the 

need to consider ‘waste prevention’ (not within the remit of this study) through reducing the 

consumption of materials in the first place. Policy may, therefore, have to be more strongly 



175 

oriented towards reducing materials use, and increasing the longevity / re-usability of 

products. 

The above analysis does not take account of the effect of any decarbonisation of energy and 

vehicle fuels on costs. Of course, it is extraordinarily difficult to anticipate how the costs of 

treatments might change in the period to 2050, with or without changes in the nature of 

energy supply. However, one might consider that the real price of energy could increase if the 

supply of energy is to be decarbonised. Whilst decarbonisation might worsen the net 

performance of some waste treatment methods through devaluing their ‘emissions credits’, 

at the same time, revenues to be derived from energy which is generated might be enhanced 

(though this might be increasingly untrue for energy derived from material of fossil origin). 

Consequently, other things being equal, in real terms, the cost of some technologies could 

decline as the value of energy increases, whilst recycling might also become cheaper owing to 

the savings in energy associated with the process. 

In general, therefore, one might suggest that, looking to 2050, relevant options under the 

IPCC approach would be: 

• Recycle all fossil based materials as far as possible and to the extent that they are still 

used. If IPCC inventories are the focus, then export of these materials would be the 

option which minimizes emissions as reported under these inventories; 

• The balance of treatment of biowaste might shift in favour of composting and away 

from AD as a result of the need to deliver organic matter to the soil. However, for wet 

organic materials, composting and AD seem appropriate, though the emphasis would 

be on minimizing methane generation at any stage of the process (including when 

spreading on land), and reducing N 2 O emissions. More work is required to understand 

the relative merits of organic soil improvers vis a vis synthetic fertilisers in terms of 

their effects on GHG emissions; 

• For woody biomass, the GHG benefits associated with energy recovery would be 

greatly reduced, but if higher revenues are received for energy delivered, these may 

favour its continuation. Equally, the potentially rising opportunity cost of competing 

land uses might make wood itself – as a material – rather more valuable, favouring 

recycling; 

• To the extent that plastics are in residual waste, thermal treatments leading to 

combustion of fossil carbon in some form would perform rather poorly, and this would 

be the case – at least in GHG terms – irrespective of their energetic efficiency if the 

energy system was truly decarbonised. Arguably, the waste system would be the only 

‘carbonised’ part of the energy generation system. Even at low carbon intensity for 

energy generation, it would probably be the most carbon intensive source of energy. 

This re-emphasises the point made in the first bullet above. By 2050, there may be 

means of thermally treating residual waste which do not lead to the combustion of 

fossil carbon, such as approaches to chemical synthesis / feedstock recycling, or even 

carbon capture from the material being treated, though the practicality of achieving 

this in the locations where the waste was being treated would seem to be limited; 

• Where dry recyclables are concerned, one might expect the value of primary materials 

to track energy prices, albeit in differing ways for different materials. Under the IPCC 

scope, as far as the dry recyclables were concerned, GHG performance might be much 

as today (depending upon the balance of import and export of primary and secondary 

materials). However, revenues associated with recycling of materials might increase, 

improving the cost effectiveness of these measures; 

• Landfills would need to be addressed principally in respect of the legacy methane 

emissions, so capture of residual methane would become important. This highlights 

the potential significance – for the medium to long-term – of the type of work being

176 

undertaken by the Environment Agency in respect of low-calorific flares and passive 

oxidation of methane at the cap; and 

• The focus might shift to the smaller quantities of methane, N 2 O and other GHGs 

emitted by processes. Our understanding of these is less good than for CO 2 , and this 

suggests a more strategic programme of research to understanding these issues. It 

should not be considered that these measures are not ‘low-hanging fruit’. It seems 

likely – as with the equipping of IVCs with scrubbers before biofilters – that more 

superficial analysis might be deflecting us from measures which are relatively simple, 

and potentially cost effective, to introduce. 

These comments offer a perspective on how one might – at least under the IPCC reporting 

conventions – seek to minimise emissions associated with waste management in the UK. 

As a final comment, it is as well to consider the wider implications of what is being proposed. 

Addressing the emissions of GHGs might not lead to unequivocally positive outcomes from a 

wider perspective (see comments made under Section 7.7). In particular, the impacts from 

non-GHG air emissions may increase when shifting materials away from landfill and into 

alternative treatments. An attempt to ‘decarbonise’ energy generation might logically find a 

parallel theme in a push to reduce emissions of non-GHG air emissions from both waste and 

energy plants. 

8.2.1 What Levels of Emissions Reduction (relative to 1990 levels) Might be Achievable 

In order to shed light on what sorts of abatement might be feasible in the longer term, the 

existing Defra landfill model, with the adjustments made for this work, was run using the 

quantities of waste being landfilled in the different years between the baseline and 2022 

under the IPCC Social, Maximum potential modelling scenario. In years after 2022, the 

quantities of different types of material being landfilled were kept constant to the year 2050. 

This enabled a figure to be derived for the emissions from landfill likely to result in the 

specific year 2050. 

In addition, for the flows of material into non-landfill treatments, the following analysis was 

carried out: 

‣ Emissions from electricity generation (at the margin) were set to zero; 

‣ Fossil CO 2 emissions from process energy use were not included as these were now 

assumed to be decarbonised; 

‣ All process emissions (bar non-fossil CO 2 , and CO 2 from energy use) were counted; 

‣ Final tonnages from all the waste treatments (except landfilling) were drawn from the 

model, and were multiplied by the emissions per tonne to generate total emissions; 

and 

‣ The analysis was undertaken, reflecting the above discussion, with and without a 

switch away from plastics in the residual waste stream (since as discussed above, a 

decarbonised society would have to replace all unrecycled plastic with non-fossil 

materials, thus essentially reducing the fossil CO 2 element of the process emissions to 

zero). 

The results are shown in Table 8-1 for the years 2022 and for 2050, with the 2050 figures 

shown with and without replacement of plastics by non-fossil materials. The reported figures 

for 1990 are shown for comparison, and to enable the potential reduction, relative to 1990 

levels, to be calculated. 


177 

Table 8-1: GHG Emissions in Specified Year (‘000 tonnes CO 2 equ), and Reduction Potential 

(%, relative to 1990 levels) 

Year 

Landfill 

Emissions Only 

Process 

Emissions from 

Facilities 

All Waste Sector 

Emissions 

% Reduction 

Relative to 

1990 

1990 49,754 1,576 51,330 0% 

2005 39,320 491 39,811 22% 

2022 10,021 14,727 24,748 52% 

2050 – with no 

replacement of 

fossil based 

plastics 

2050 – with a 

complete switch 

of fossil to nonfossil 

based 

plastics 

1,852 14,727 16,597 68% 

1,852 2,540 4,393 91% 

Source: 1990 and 2005 data from Defra data 

http://www.defra.gov.uk/environment/statistics/globatmos/download/xls/gatb04.xls 

This analysis shows that: 

‣ Between 1990 and 2005, the emissions from landfilling have declined by around 20% 

reflecting both the movement of waste away from landfill and the improvement in 

landfill gas captures at more modern landfill sites; 

‣ By 2022, the emissions from landfilling show a further significant drop. Even without 

changes in waste flows to different treatment facilities, these fall further between 

2022 and 2050, principally because the emissions associated with materials being 

landfilled in earlier years are dropping off exponentially with time. The significance of 

removing untreated waste from landfill is clear; 

‣ At the same time, whilst the data for 1990 and 2005 in respect of other GHGs from 

other facilities seem to be less reliable, these increase considerably between 1990 

and 2022 (even assuming zero fossil CO 2 emissions for fuel used in processes). It 

should be noted that the drop in these emissions between 1990 and 2005 is as 

recorded in Defra data, and the methodology for deriving these figures is not 

comparable with the approach used in this report, on which the data for later years are 

based; 

‣ These remain constant to 2050 reflecting constant mass flows, as long as the fossil 

carbon content of fuels remains broadly constant; 

‣ If fossil carbon in residual waste is eliminated, then process emissions decline 

significantly. Indeed, the major contribution to reducing process emissions comes from 

eliminating fossil carbon from the residual waste stream; 


178 

‣ Reflecting the above discussion, the GHGs from processes are greater than GHG 

emissions from landfill in 2050; 

‣ Although the MBT: stabilisation – output to land recovery process is managing more 

waste than the combined thermal treatment options, the total emissions (mainly CH 4 

based) are much less, at around 1/12 overall; 

‣ Without the elimination of fossil carbon from the residual waste stream, then the 


reaches 52% by 2022 and 68% by 2050; and 

‣ If fossil carbon is completely eliminated from the residual waste stream, then the 


reaches 91% by 2050. 

In the context of this analysis, it should be noted that the assumption of zero growth in 

arisings has been maintained. 


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184 

A.2.0 Assumptions for Baseline Development 

A.2.1 

Compositions (MSW) 

A.2.1.1 England Composition 

The 2005/06 composition was compiled from the National Waste Composition Estimation - 

Methodology & Approach Report. 162 Assumptions were then made regarding which fractions 

of the composition related to the framework MSW composition used in this study. 

Table A- 1: England Data Apportioned to Framework Composition 

Material 2005/06 

Fraction 

Framework Final 

Apportioned Composition Percentage 

Paper and Board 21% 21% Paper and Card 21% 

Dense Plastic 6% 6% Dense Plastics 6% 

Glass 7% 7% Glass 7% 

4% Ferrous Metals 4% 

Metals 5% 

Non-Ferrous 

1% 

Metals 

1% 

Other (incl. 

WEEE) 

7% 1% WEEE 1% 


Combustible 

8% 3% Wood 3% 

Food Waste 19% 19% Food Waste 19% 

Garden Waste 12% 12% Green Waste 12% 

Textiles 3% 3% Textiles 3% 

Nappies and 

Absorbent Hygiene 

2% 2% 

Other Sanitary 

Products 

2% 


8% 5% 


Combustible 

6% 

Combustibles 

Other (incl. WEE) 7% 1% 

Other (incl. WEE) 7% 4% Fine Material 4% 

Plastic Film 3% 3% Plastic Film 3% 

Rubble and 

Other Non- 

Combustible 

7% 7% Non-Combustibles 7% 

Other (incl. WEE) 7% 1% 

Hazardous 

Household Waste 

Items (inc. 

batteries) 

Total 100% 100% 100% 

1% 

162 BeEnvironemntal (2007) National Waste Composition Estimation - Methodology & Approach Report 


185 

The paper and card fraction was disaggregated using the following composition from a report 

by Dr Julian Parfitt. 

Table A- 2: Composition of MSW Paper and Card Fraction 

Paper and Card 

Total 

Percentage 

Newsprint and Magazines 

Newspapers and Magazines 

Magazines 

35% 


Other Recyclable Paper 

Non-Recyclable Paper 

40% 

Card 

Cardboard 

Card and paper packaging 

Card non-packaging 

Liquid cartons 

25% 

Unclassified paper and card 

Source: Parfitt, J. (2002) Analysis of household waste composition and factors driving waste increases, Report 

for WRAP 

The following points list the main assumptions in apportioning material streams to the 

framework composition. All assumptions are by Eunomia and estimated based on industry 

experience. 

‣ ‘Metals’ are 80% ferrous and 20% non-ferrous; 

‣ ‘Other (incl. WEEE)’ comprises of; WEEE - 1%; Other Combustibles – 1%; Fine Material 

– 4%; and Hazardous Wastes – 1% (Total – 7%); 

‣ 3% of ‘Other Combustibles’ is Wood; and 

‣ ‘Nappies and Other Sanitary’ are Absorbent Hygiene Products. 

A.2.1.2 Scotland Composition 

The composition from the ERM report 163 (based on the SEPA waste digest 5) was used but 

with the proportions of food and green waste inflated by 5% to more accurately reflect the 

current situation. 

A.2.1.3 Wales Composition 

The composition in the ERM report was drawn from a 2003 report into the composition of 

municipal wastes. 164 The actual data used for this study, however, was an adapted version of 

this composition from a 2008 report by ourselves (see Table A- 3). 165 This adjusted the 

composition from the 2003 study to take into account the fact that, based on current 

performance, using the previous composition estimates, some materials were already being 

captured at levels greater than 100%. 

163 ERM (2006) Carbon Balances and Energy Impacts of the Management of UK Wastes, Defra R&D Project 

WRT 237 

164 AEAT (2003) The Composition of Municipal Waste in Wales, Report for the National Assembly for Wales, 

December 2003. Data as used in the ERM/Environment Agency update to the WISARD software tool. 

165 Eunomia (2008) Scoping New Municipal Waste Targets for Wales, Report to the Welsh Local Government 



186 

Table A- 3: Wales Data Apportioned to Framework Composition 

Material 

2006/07 Report 

Newspapers and magazines 7% 

Recyclable paper 2% 

Cardboard boxes/containers 5% 

Other paper and card 5% 

Dense plastic bottles 2% 

Other packaging 2% 

Other dense plastic 2% 

Packaging glass 5% 

Non-packaging glass 1% 

Ferrous food and beverage cans 2% 

Other ferrous metal 2% 

White goods 1% 

Non-ferrous food and beverage cans

187 

‣ ‘White goods’ are included as Ferrous Metals (as there are high quantities of ferrous 

metal in white goods); 

‣ ‘Furniture’ is categorised as Wood (high quantity of wood in furniture); 

‣ ‘Shoes’ are categorised as Textiles; 

‣ ‘Mixed waste’ is categorised as Other Combustibles; and 

‣ ‘Other MNC’ is Other ‘Municipal Non-Combustibles’. 

A.2.1.4 Northern Ireland Composition 

The composition for Northern Ireland was taken from a RPS report 166 and was matched up 

with the framework composition in the same manner as described above for England and 

Wales. The resulting composition used in this study is shown below in Table A- 4. 

Table A- 4: Northern Ireland MSW Composition 

Material 

Composition from 

DoE, 2008 

Paper and card 21.03% 

Newsprint and magazines 7% 

Other Paper 8% 

Card 5% 

Dense plastic 3.94% 

Glass 14.59% 

Ferrous metal 1.87% 

Non-ferrous metal 1.55% 

WEEE 1.36% 

Wood 3.00% 

Food waste 9.34% 

Green waste 25.77% 

Textiles 4.27% 

Absorbent hygiene products 2.00% 

Other combustibles(1) 4.19% 

Fine material

188 

A.2.2 

Recycling Rates (MSW) 

A.2.2.1 England Recycling Rates 

The source data, shown below in Table A- 5, is from Defra Municipal Statistics 2006/07 167 . 

Unless otherwise stated in the report the breakdown of materials for the DAs was assumed to 

be the same as for England. 

Table A- 5: England Recycling and Composting Materials Breakdown (2006/07) 

Materials Recycled / Composted (2006/07) Total (Thousand tonnes) Percentage 

Paper & card 1,535 17% 

Glass 840 9% 

Compost 2,895 32% 

Scrap metals & white goods 601 7% 

Textiles 103 1% 

Cans 80 1% 

Plastics 49 1% 

Co-mingled 1,121 13% 

Other 751 8% 

Non-Household Recycling 961 11% 

Total Recycling & Composting 8,937 100% 

Source: Defra Municipal Statistics 

The following headings all indicate how the categories presented in Table A- 5 have been 

disaggregated to correspond to the MSW framework used in this study. 

Paper and card 

The paper and card fraction was disaggregated into the following material streams and the 

same composition as in Table A- 2. The proportions of each material currently recycled were 

estimated by Eunomia based on experience. 

Table A- 6: Percentage of MSW Paper and Card Fraction Recycled (England) 

Material Stream Percentage Recycled 

Newsprint and Magazines 60% 

Other Paper 25% 

Card 15% 

Source: Eunomia 

Compost 

This fraction relates to material managed by composting type processes i.e. open air windrow, 

IVC and AD. The materials considered, that form the ‘compost’ fraction, are food waste, green 

waste, and some card. These materials are managed in varying quantities by the processes 

mentioned above. Various sources of data regarding quantities of each material managed by 

the different processes were used. These sources, along with Eunomia assumptions, are 

indicated below with the percentages of each material stream managed by Windrow, IVC and 

AD. 

167 See http://www.defra.gov.uk/environment/statistics/wastats/bulletin07.htm 


189 

Table A- 7: Management of MSW Organic Wastes ‘Composted’ (England) 

Windrow IVC AD Total 

Food Waste 0% 5% 3 2% 3 7% 1 

Green Waste 55% 4 37% 4 0% 92% 

Card 0% 1% 5 0% 1% 

Total 61% 37% 2% 100% 

Sources: 

1. The percentage of food waste was determined by calculating the percentage of food collected in the UK out of the total 

municipal organic waste collected. This data was available in the WRAP Market Situation Report – April 2008, Realising the 

value of organic waste 

http://www.wrap.org.uk/applications/publications/publication_details.rmid=698&publication=5238&programme=wrap 

2. The percentages of organic material managed by windrow, IVC and AD were considered similar to those determined during 

research by Eunomia into compost supply and demand in the South East and East of England. Eunomia (2008) Evaluation of 

Compost Supply and Demand in South East (including London) and East England – EVA058, Final Report for WRAP 

3. The percentage managed by AD was 2%. All this material was assumed to be food waste. Therefore the remaining 5% of food 

waste was considered to be managed by IVC. 

4. Green waste was split between windrow and IVC by the same proportions as determined in the compost management study 

(see note 2). No green waste was assumed to be going to AD. 

5. In the WRAP Market Situation Report (see note 1) Graph 2 indicates that the composition of organic waste for 2005/06 

includes 2% mixed green and card. It was assumed that half of this was card. All of the card was assumed to be being 

managed by IVC only. 

The following fractions were disaggregated, and percentages apportioned, following 

estimations by Eunomia based on experience. 

Scrap metals & white goods 

Table A- 8: Materials in ‘Scrap metals & white goods’ (England) 

Material 

Percentage 

Ferrous Metal 60% 

Non-ferrous Metal 15% 

Waste Electrical and Electronic Equipment (WEEE) 25% 

Total 100% 


Cans 

Table A- 9: Materials in ‘Cans’ (England) 

Material 

Percentage 



Total 100% 


Plastics 

Table A- 10: Materials in ‘Plastics’ (England) 

Material 

Percentage 

Plastic Film 5% 

Dense Plastic 95% 

Total 100% 



Co-mingled 

Table A- 11: Materials in ‘Co-mingled’ (England) 

Material 

Percentage 

Paper and Card 70% 

Glass 9% 

Cans 6% 

Plastics 15 

Total 100% 



Table A- 12: Materials in ‘Other’ (England) 

Material 

Percentage 

Wood 90% 

Oils 5% 

Batteries 5% 

Total 100% 


Non-household recycling 

The proportions of the materials assumed to be in the ‘Non-household recycling’ category 

were considered to be broadly similar to those of the source separated fractions. 

Table A- 13: Materials in ‘Non-household recycling’ (England) 

Material 

Percentage 

Paper & Card 35% 

Glass 17% 

Compost 30% 

Scrap metals & white goods 5% 

Textiles 3% 

Cans 5% 

Plastics 5% 

Total 100% 


190 

A.2.2.2 Scotland Recycling Rates 

The management data for Scotland was sourced from the 2007 Waste Data Digest and 

based on data from the SEPA Local Authority Waste Arisings Survey 2006/2006. 

The total amount of food and green waste composted in 2005/06 was 286,450 tonnes. This 

was managed by the proportions indicated in Table A- 14. 


191 

Table A- 14: Management of MSW Organic Wastes ‘Composted’ (Scotland) 

Windrow IVC AD 2 Total 

Food Waste 0% 2% 0% 2% 1 


Card 0% 1% 4 0% 1% 

Total 66% 34% 0% 100% 

Notes: 

1. The percentage of food waste managed by composting processes was estimated by Eunomia to be 2%. 

2. No AD is currently available for the management of MSW food wastes. 

3. Green waste was split between windrow and IVC based on data from Eunomia (2008) Evaluation of Compost Supply and 

Demand in South East (including London) and East England – EVA058, Final Report for WRAP. 




Table A- 15: Scottish Local Authority Recycling 2005/2006: Breakdown of Materials 

Material Stream Tonnes Percentage 

Paper and Card 191,816 35% 

Soil/rubble 98,773 18% 

Glass 74,563 13% 

Scrap metal 38,408 7% 

Wood 35,138 6% 

Bulky household items 17,622 3% 

Incinerator residue 15,975 3% 

Textiles 14,377 3% 

Other 30,479 6% 

Fridges / freezers 9,716 2% 

Plastic 7,963 1% 

Metal cans 6,263 1% 

White goods/WEEE 4,343 1% 

Co-mingled materials 4,288 1% 

Tyres 1,795

192 

Card material streams, and recycling rates were applied by the same proportions as for 

England (see Section A.2.2.1). 

Dense Plastic 

Comprised of a proportion of ‘Plastic’ using the same composition as for England (see Table 

A- 10), plus an amount from the co-mingled fraction (see Table A- 11). 

Glass 

Source segregated glass and an amount from the co-mingled fraction (see Error! Reference 

source not found.). 

Ferrous Metal 

This material stream included a proportion of ‘Scrap Metals’ (estimation of split given by 

Eunomia in Table A- 16), all of ‘Gas Cylinders’, and a proportion of ‘Cans’ from the source 

segregated and co-mingled fractions (proportion of ‘Cans’ in co-mingled fraction given in 

Table A- 11, and proportion of Ferrous metals in ‘Cans’ given in Table A- 9). 

Table A- 16: Materials in ‘Scrap Metal’ (Scotland) 

Material 

Percentage 



Total 100% 




Eunomia in Table A- 16), and a proportion of ‘Cans’ from the source segregated and comingled 

fractions (proportion of ‘Cans’ in co-mingled fraction given in Table A- 11, and 

proportion of Ferrous metals in ‘Cans’ given in Table A- 9). 


Includes all of ‘Fridges / Freezers’ and ‘White goods / WEEE’. 

Wood 

Only includes source segregated ‘Wood’. 

Textiles 

Only includes source segregated ‘Textiles’. 


Includes ‘Bulky household items’, ‘Tyres’, and 50% of the ‘Other’ fraction. 

Plastic Film 

Comprised of a proportion of ‘Plastic’ using the same composition as for England (see Table 



Includes ‘Soil / Rubble’, ‘Incinerator residue’, and 50% of the ‘Other’ fraction. 


Includes ‘Batteries’ and ‘Oils’. 


193 

A.2.2.3 Wales Recycling Rates 

Table A- 17 below shows the source data from the Welsh Environment Agency. The headings 

thereafter indicate which material streams were apportioned to the MSW framework 

composition. Additionally, Table A- 18 shows the proportion of materials managed in 

composting facilities. 

Table A- 17: Wales Recycling and Composting Materials Breakdown (2006/07) 


Percentage 

Newspapers and magazines 19% 

Recyclable paper 1% 

Cardboard boxes/containers 4% 

Other paper and card 1% 

Dense plastic bottles 3% 

Other dense plastic 1% 

Textiles 1% 

Shoes 0.1% 

Wood 8% 

Furniture 0.3% 

Packaging glass 12% 

Garden waste 23% 

Food and kitchen waste 3% 

Ferrous food and beverage cans 1% 

Other ferrous metal 5% 

Non-ferrous food and beverage cans 0.3% 

Other non ferrous metal 0.2% 

White goods 2% 

Large electronic goods 0.3% 

TVs and monitors 1% 

Other WEEE 1% 

Lead/acid batteries 0.3% 

Oil 0.1% 

Other potentially hazardous 0.02% 

Construction and demolition waste 14% 

Other Miscellaneous Non-Combustibles 1% 

Total 100% 

Source: Wales Environment Agency 


194 

Table A- 18: Management of MSW Organic Wastes ‘Composted’ (Wales) 




Card 0% 1% 4 0% 1% 

Total 58% 42% 0% 100% 

Notes: 

1. The percentage of food waste managed out of garden and food and kitchen waste fractions from Table A- 17. 







Paper & Card 

The disaggregated fractions of Newsprint and magazines, Other paper, and Card were 

assigned material streams as shown in Table A- 19. 

Table A- 19: Materials in ‘Paper and Card’ (Wales) 

Final 

Paper and Card Fraction 

Wales Material Stream 

Percentage of 

Total Recycled / 

Composted 

Newsprint and Magazines Newspapers and magazines 19% 


Recyclable paper 

50% of Other paper and card 

2% 

Card 

Cardboard boxes/containers 

50% of Other paper and card 

5% 

Dense Plastic 

Includes ‘Dense plastic bottles’ and ‘Other dense plastic’. 

Glass 

Only includes ‘Packaging glass’. 

Ferrous Metal 

Includes ‘Ferrous food and beverage cans’ and ‘Other ferrous metal’. 


Includes ‘Non-ferrous food and beverage cans’ and ‘Other non ferrous metal’. 


Includes ‘White goods’, ‘Large electronic goods’, ‘TVs and monitors’ and ‘Other WEEE’. 

Wood 


Textiles 

Includes ‘Textiles’ and ‘Shoes’. 


195 


Only includes ‘Furniture’. 

Plastic Film 

No plastic film recycling reported. 


Includes ‘Construction and demolition waste’ and ‘Other Miscellaneous Non-Combustibles’. 


Includes ‘Lead/acid batteries’, ‘Oil’ and ‘Other potentially hazardous’. 

A.2.2.4 Northern Ireland Recycling Rates 

Table A- 20 shows the source data from the Environment and Heritage Service, Municipal 

Waste Management Northern Ireland. The proportions of compostable waste managed are 

shown in Table A- 21, with the assumptions behind the disaggregation of the fractions in 

order to marry up with the framework composition detailed thereafter. 

Table A- 20: Northern Ireland Recycling and Composting Materials Breakdown (2006/07) 

Materials Recycled / Composted 

(2006/07) 

Total (Tonnes) Percentage 

All Glass 16,075 6% 

Paper & card 77,824 28% 

Electrical and white goods 7,378 3% 

Batteries 697 0.3% 

Green / compostable waste 105,752 39% 

Cans 3,664 1% 

Plastics 7,998 3% 

Mineral & vegetable oil 421 0.2% 

Other materials 5,658 2% 

Co-mingled materials 649 0.2% 

Textiles and footwear 3,021 1% 

Other scrap metals 12,941 5% 

Wood 22,930 8% 

Rubble 8,971 3% 

Paint 341 0.1% 

Books 81 0.03% 

Total 274,401 100% 

Source: Environment and Heritage Service, Municipal Waste Management Northern Ireland, For the year ended 

31 March 2007. 


196 

Table A- 21: Management of MSW Organic Wastes ‘Composted’ (Northern Ireland) 




Card 0% 1% 4 0% 1% 

Total 66% 34% 0% 100% 

Notes: 

1. The percentage of food waste managed by composting processes was estimated by Eunomia to be 2%. 







Paper & Card 

This fraction includes; source segregated Paper& Card; a proportion from co-mingled 

materials (see Table A- 11); and ‘Books’. It was disaggregated into Newsprint and magazines, 

Other paper, and Card material streams, and recycling rates were applied by the same 

proportions as for England (see Section A.2.2.1) 

Dense Plastic 

Comprised of a proportion of ‘Plastics’ using the same composition as for England (see Table 


Glass 

Source segregated ‘All Glass’ and an amount from the co-mingled fraction (see Table A- 11). 

Ferrous Metal 


Eunomia in Table A- 16), and a proportion of ‘Cans’ from the source segregated and comingled 

fractions (proportion of ‘Cans’ in co-mingled fraction given in Table A- 11, and 

proportion of Ferrous metals in ‘Cans’ given in Table A- 9). 



Eunomia in Error! Reference source not found.), and a proportion of ‘Cans’ from the source 

segregated and co-mingled fractions (proportion of ‘Cans’ in co-mingled fraction given in 

Table A- 11, and proportion of Ferrous metals in ‘Cans’ given in Table A- 9). 


Only includes ‘Electrical and white goods’. 

Wood 


Textiles 

Only includes source segregated ‘Textiles and footwear’. 


Only includes 50% of the ‘Other materials’ fraction. 


197 

Plastic Film 

Comprised of a proportion of ‘Plastics’ (see Table A- 10), plus an amount from the co-mingled 

fraction (see Table A- 11). 


Includes ‘Rubble’ and 50% of the ‘Other materials’ fraction. 


Includes ‘Batteries’, ‘Mineral and vegetable oil’ and ‘Paint’. 

A.2.2.5 Time Profiles for MSW from 2008 to 2022 

To interpolate the recycling rates between 2008 and 2022 time profiles were determined for 

each material specifically targeted in the modelling. These were then used to determine the 

recycling rates in 2012 and 2017. This approach was taken as, in the baseline, the increase 

in recycling for different materials will progress at varying rates. The time profiles were 

developed to represent a percentage of the difference in recycling rates from 2008 to 2022. 

Thus a 0% figure for 2012, for example, would indicate that the recycling rate was the same 

as for 2008, and a 100% figure the same rate as for 2022, with 50% indicating that the rate 

would be half way in between. These are shown in Table A- 22 below. 

Table A- 22: Time Profiles Indicating Changes in Recycling Rates between 2008 and 2022 

(MSW) 

Waste Fraction 2012 2017 

Paper and card 

Newsprint and magazines 80% 95% 

Other Paper 50% 80% 

Card 70% 90% 

Dense plastics 30% 60% 

Glass 70% 90% 

Ferrous metal 75% 90% 

Non-ferrous metal 75% 90% 

WEEE 45% 75% 

Wood 70% 90% 

Food waste 55% 85% 

Green waste 80% 95% 

A.2.3 

C&I 

A.2.3.1 Composition of C&I ‘Other Low Abatement Potential’ 

For reference, the materials that were considered to have low abatement potential, or little 

was known about their management, and therefore were excluded from the modelling as 

individually targeted materials, are shown below in Table A- 23. 


198 

Table A- 23: Composition of C&I ‘Other Low Abatement Potential’ 


Commercial % of Industrial % of 

Sector Arisings Sector Arisings 

Organic Sludges 0.0% 0.4% 

Unknown/Mixed Sludges 0.3% 5.0% 

End of Life Vehicles 0.1% 0.0% 

Tyres 0.5% 0.0% 

Batteries 0.3% 0.1% 

Oils/fuels 1.3% 0.2% 

Paints/Inks/Varnishes 0.1% 0.1% 

Organic Chemicals 0.3% 1.4% 

Inorganic Chemicals 0.0% 1.5% 

Unknown Chemicals 1.5% 0.5% 

Aqueous Chemical 

1.2% 

0.2% 

Effluents 

Inorganic Sludges 0.0% 0.8% 

Soils/silts 1.7% 1.9% 

Mineral/aggregate waste 1.2% 2.0% 

Other Non-Combustible 6.5% 4.9% 

Total 14.0% 20.0% 

Source: ERM (2006) Carbon Balances and Energy Impacts of the Management of UK Wastes, Defra R&D Project 

WRT 237 

A.2.3.2 Time Profiles for C&I waste from 2008 to 2022 

As for MSW (see Section A.2.2.5) time profiles were developed to indicate the predicted roll 

out of recycling infrastructure, and therefore associated increases in recycling rates, between 

2008 and 2022 for each of the targeted material streams (see Table A- 24 below). Note, the 

percentages indicate a percentage of the difference between the 2008 and 2022 recycling 

rates. 

Table A- 24: Time Profiles Indicating Changes in Recycling Rates between 2008 and 2022 

(C&I) 

Commercial 

Industrial 

Waste Fraction 2012 2017 2012 2017 

Paper and card 60% 85% 80% 95% 

Dense plastics 25% 55% 35% 65% 

Glass 65% 90% 80% 95% 

Ferrous metal 80% 90% 85% 95% 

Non-ferrous metal 65% 85% 85% 95% 

WEEE 40% 70% 50% 80% 

Wood 65% 85% 75% 95% 

Food waste 10% 35% 35% 65% 

Green waste 70% 90% 70% 90% 


199 

A.3.0 List of Switches Considered 

Switch Description 

MSW - Paper / card from Landfill to Recycled 

MSW - Dense plastics from Landfill to Recycled 

MSW - Glass from Landfill to Recycled 

MSW - Ferrous metal from Landfill to Recycled 

MSW - Non ferrous metal from Landfill to Recycled 

MSW - WEEE from Landfill to Recycled 

MSW - Wood from Landfill to Recycled 

MSW - Food from Landfill to AD: on-site biogas use (elec) 

MSW - Food from Landfill to AD: compressed biogas used in vehicles 

MSW - Food / Green from Landfill to IVC 

MSW - Green from Landfill to Windrow 

MSW - Paper / card from Incineration to Recycled 

MSW - Dense plastics from Incineration to Recycled 

MSW - Glass from Incineration to Recycled 

MSW - Ferrous metal from Incineration to Recycled 

MSW - Non ferrous metal from Incineration to Recycled 

MSW - WEEE from Incineration to Recycled 

MSW - Wood from Incineration to Recycled 

MSW - Food from Incineration to AD: on-site biogas use (elec) 

MSW - Food from Incineration to AD: compressed biogas used in vehicles 

MSW - Food / Green from Incineration to IVC 

MSW - Green from Incineration to Windrow 

MSW - Paper / card from MBT to Recycled 

MSW - Dense plastics from MBT to Recycled 

MSW - Glass from MBT to Recycled 

MSW - Ferrous metal from MBT to Recycled 

MSW - Non ferrous metal from MBT to Recycled 

MSW - WEEE from MBT to Recycled 

MSW - Wood from MBT to Recycled 

MSW - Food from MBT to AD: on-site biogas use (elec) 

MSW - Food from MBT to AD: compressed biogas used in vehicles 

MSW - Food / Green from MBT to IVC 

MSW - Green from MBT to Windrow 

MSW - Paper / card from Recycled to Incineration 

MSW - Dense plastics from Recycled to Incineration 

MSW - Glass from Recycled to Incineration 

MSW - Ferrous metal from Recycled to Incineration 

MSW - Non ferrous metal from Recycled to Incineration 

MSW - WEEE from Recycled to Incineration 

MSW - Residual waste from Landfill to MBT: Stabilisation, output to landfill 

MSW - Residual waste from Landfill to MBT: SRF to gasification - steam turbine 

MSW - Residual waste from Landfill to MBT: SRF to gasification - gas engine 

MSW - Residual waste from Landfill to MBT: SRF to cement kiln 

MSW - Residual waste from Landfill to MBT: SRF to power station 


200 


MSW - Residual waste from Landfill to MBT: Stabilisation, output to land recovery 

MSW - Residual waste from Landfill to MBT: AD - gas engine 

MSW - Residual waste from Landfill to MBT: SRF to dedicated 

MSW - Residual waste from Landfill to Incineration 

MSW - Wood from Landfill to Energy generation (dedicated boiler) 

MSW - Green from Composting to Energy generation (dedicated boiler) 

MSW - Food / Green from IVC to IVC + scrubber / biofilter 

MSW - Residual waste from Incineration to Incineration + CHP 

MSW - Food from AD: on-site biogas use (elec) to AD: on-site biogas use + CHP 

MSW - Residual waste from Landfill to Landfill + flaring 

Commercial - Paper / card from Landfill to Recycled 

Commercial - Dense plastics from Landfill to Recycled 

Commercial - Glass from Landfill to Recycled 

Commercial - Ferrous metal from Landfill to Recycled 

Commercial - Non ferrous metal from Landfill to Recycled 

Commercial - WEEE from Landfill to Recycled 

Commercial - Wood from Landfill to Recycled 

Commercial - Food from Landfill to AD: on-site biogas use (elec) 

Commercial - Food from Landfill to AD: compressed biogas used in vehicles 

Commercial - Food / Green from Landfill to IVC 

Commercial - Green from Landfill to Windrow 

Commercial - Paper / card from Recycled to Incineration 

Commercial - Dense plastics from Recycled to Incineration 

Commercial - Glass from Recycled to Incineration 

Commercial - Ferrous metal from Recycled to Incineration 

Commercial - Non ferrous metal from Recycled to Incineration 

Commercial - WEEE from Recycled to Incineration 

Commercial - Residual waste from Landfill to MBT: Stabilisation, output to landfill 

Commercial - Residual waste from Landfill to MBT: SRF to gasification - steam turbine 

Commercial - Residual waste from Landfill to MBT: SRF to gasification - gas engine 

Commercial - Residual waste from Landfill to MBT: SRF to cement kiln 

Commercial - Residual waste from Landfill to MBT: SRF to power station 

Commercial - Residual waste from Landfill to MBT: Stabilisation, output to land recovery 

Commercial - Residual waste from Landfill to MBT: AD - gas engine 

Commercial - Residual waste from Landfill to MBT: SRF to dedicated 

Commercial - Residual waste from Landfill to Incineration 

Commercial - Wood from Landfill to Energy generation (dedicated boiler) 

Commercial - Food / Green from IVC to IVC + scrubber / biofilter 

Commercial - Residual waste from Incineration to Incineration + CHP 

Commercial - Food from AD: on-site biogas use (elec) to AD: on-site biogas use + CHP 

Commercial - Residual waste from Landfill to Landfill + flaring 

Industrial - Paper / card from Landfill to Recycled 

Industrial - Dense plastics from Landfill to Recycled 

Industrial - Glass from Landfill to Recycled 

Industrial - Ferrous metal from Landfill to Recycled 

Industrial - Non ferrous metal from Landfill to Recycled 

Industrial - WEEE from Landfill to Recycled 

Industrial - Wood from Landfill to Recycled 

Industrial - Food from Landfill to AD: on-site biogas use (elec) 


201 


Industrial - Food from Landfill to AD: compressed biogas used in vehicles 

Industrial - Food / Green from Landfill to IVC 

Industrial - Green from Landfill to Windrow 

Industrial - Paper / card from Recycled to Incineration 

Industrial - Dense plastics from Recycled to Incineration 

Industrial - Glass from Recycled to Incineration 

Industrial - Ferrous metal from Recycled to Incineration 

Industrial - Non ferrous metal from Recycled to Incineration 

Industrial - WEEE from Recycled to Incineration 

Industrial - Residual waste from Landfill to MBT: Stabilisation, output to landfill 

Industrial - Residual waste from Landfill to MBT: SRF to gasification - steam turbine 

Industrial - Residual waste from Landfill to MBT: SRF to gasification - gas engine 

Industrial - Residual waste from Landfill to MBT: SRF to cement kiln 

Industrial - Residual waste from Landfill to MBT: SRF to power station 

Industrial - Residual waste from Landfill to MBT: Stabilisation, output to land recovery 

Industrial - Residual waste from Landfill to MBT: AD - gas engine 

Industrial - Residual waste from Landfill to MBT: SRF to dedicated 

Industrial - Residual waste from Landfill to Incineration 

Industrial - Wood from Landfill to Energy generation (dedicated boiler) 

Industrial - Food / Green from IVC to IVC + scrubber / biofilter 

Industrial - Residual waste from Incineration to Incineration + CHP 

Industrial - Food from AD: on-site biogas use (elec) to AD: on-site biogas use + CHP 

Industrial - Residual waste from Landfill to Landfill + flaring 

CDE - Dense plastics from Landfill to Recycled 

CDE - Ferrous metal from Landfill to Recycled 

CDE - Non ferrous metal from Landfill to Recycled 

CDE - Wood from Landfill to Recycled 

CDE - Wood from Landfill to Energy generation (dedicated boiler)

Development of Marginal Abatement Cost Curves for the Waste Sector

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