DELIVERING THE CIRCULAR ECONOMY A TOOLKIT FOR POLICYMAKERS

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58 • DELIVERING THE CIRCULAR ECONOMY – A TOOLKIT FOR POLICYMAKERS 2.2.3 Quantify sector impact Objective: End product: Understand the economic (and resource) impact of circular economy opportunities, either as input to an economy-wide assessment (see Section 2.3.1) or as a standalone result. Quantified impact for each opportunity and circular economy scenario (where applicable). To build the case for business action and potential policy interventions, the economic impact of each prioritised circular economy opportunity needs to be assessed. This section describes a tool to conduct this impact quantification for individual opportunities. The ambition level for the quantification exercise needs consideration before the exercise is initiated – while understanding the impact is important to help mobilise business and build the case for policy intervention, the related (potentially high) resource demands needs to be balanced with that of the other steps from the toolkit. This sector-specific quantification can be a goal in itself, or serve (as was the case in the Denmark pilot) as further input for the economy-wide impact quantification described in Section 2.3.1. In the latter case, calculations should be performed with a sufficient level of detail to be able to convert to the input-output tables needed in the CGE or other type of economy-wide impact assessment model (see Section 2.3.1 for further details). While economic impact is a natural first choice of metrics to make the case for the circular economy, other metrics such as resource savings and greenhouse gas emissions can also be taken into account. In the Denmark pilot, resource savings were estimated for two key materials (steel and plastics) and the change in CO 2 footprint was modelled in the economy-wide modelling step (see Section 2.3.1). Figure 14 shows an overview of a possible quantification methodology, illustrated in the form of a driver tree. While the details typically need to be adjusted for each opportunity, the driver tree offers a useful structure for the quantification. The core of this approach is to zoom in on specific sub-sectors or even products (branch A of the driver tree), and consequently scaling up the impact found in these sub-sectors or products to the full sector and adjacent sectors (branch B of the driver tree). The advantage of this approach is that it makes the analysis tangible, and allows businesses to provide specific input. Other approaches are possible as well. Branch A. Net value created in deep dive sub-sector. The net value creation is defined as a product of the overall adoption rate of the circular economy opportunity, the number of ‘units’ addressed, and the net value created per unit. • Adoption rate. The adoption rate is a quantitative answer to the question ‘How widely will this opportunity have been adopted in a circular scenario?’ where 100% means full realisation of the potential. In the Denmark pilot, the adoption rates were always expressed as a difference between the circular scenario (2035 and 2020 horizons) and a ‘business as usual’ scenario (where some adoption rate is typically also greater than zero). This allows the model to take into account that circular economy opportunities will probably be adopted to some extent even in a non-circular scenario. • Number of units in deep dive sub-sector. The number of units is used to denote any quantity used as the basis of the quantification in the subsector. The unit could be (an estimated) number of products, or a volume of material flow (such as tonnes of organic waste). It could also be a monetary unit, such as ‘value of purchased goods’ or ‘output of new buildings’. • Net value created per unit. Circular activities bring two kinds of direct financial benefits to businesses: (i) cost savings from materials, components or labour (for example due to parts recovery or virtualisation), and (ii) increased revenues (from additional sales and/or a higher unit price). Additional costs include increased labour costs, increased material/component costs (for example to de-
DELIVERING THE CIRCULAR ECONOMY – A TOOLKIT FOR POLICYMAKERS • 59 sign more robust products), and increased energy and capital expenditure, for example to set up bio-refineries or remanufacturing plants. These elements can all be assessed separately (as was done in the Denmark pilot), or, alternatively, for a high-level estimate, in one value (e.g. 5% net cost savings per unit). They can also be assessed for consumers rather than businesses (as in, for example, the reduction of avoidable food waste). Branch B. Scale-up factor. The scale-up factor is used to bring the net impact estimated for the deep-dive sub-sector to the full sector (and adjacent sectors). The calculation is driven by the relative size of the adjacent sub-sectors compared to the deep dive sub-sector, and a ‘scalability’ factor introduced to reflect the relative applicability of the circular economy opportunity in different sub-sectors. The final scaleup factor is the sum of each individual scale-up factor for all sub-sectors present. • Relative size of sub-sector. This calculation is based on the relative economic size of the individual sub-sectors, for example calculated by comparing output or gross value added. • Scalability factor. This value, set between 0 and 1, is introduced to adjust the scaling based on how applicable an opportunity is to an adjacent sub-sector compared to the deep-dive subsector. For example, a scalability factor of 0.2 means that the impact is estimated to be 20% of the impact estimated for the deep-dive sub-sector. 62 As in any modelling exercise, the hardest part is not to define the structure of the model, but to find good data to feed into the model. Here it is crucial to engage businesses to provide input on the key quantification assumptions. Practically, in the Denmark pilot, the key quantification assumptions were tested with businesses while detailing out the circular economic opportunities (see previous section). Existing reports such as the reports listed in Part 1 and the results from the Denmark pilot in Part 3 of this report can also be a useful source of information. Industry associations, public bodies and statistical authorities can help complete the picture. Finally, no matter how diligently the data gathering and impact quantification is carried out, predicting the impact of circular economy opportunities on multi-year time frames will always at best be a well-informed estimate that relies on important assumptions. 62 Technically, it is of course possible to set scalability factors to more than 1, if it is assumed that the circular economy opportunities are in fact larger in an adjacent sector. This was not done in the Denmark pilot.
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