1. Introduction - Firenze University Press

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As can be seen in Fig. 5 the impact of the distance travelled becomes increasingly significant when the amount of waste (APC for AwR and BA for BABIU) transported is increased. From 0 to 125 km the BABIU process still shows the greatest CO2 savings. At around 145 km the AwR process and the BABIU process have the same CO2 savings. At distances greater than 145 km the AwR achieves a greater CO2 savings than BABIU, but at the same time they both have a lower CO2 savings than HPWS and AS. When the distance between the MSWI and a BABIU plant reaches around 1315 km the impact from transport becomes higher than any CO2 savings and the process begins to have a negative impact on the environment. For AwR, this point is reach at a much further distance of around 10475 km. As the other part of the study, it was determined that comparatively the country where the system is implemented does not have a large effect on the GWP. Overall Spain has a greater CO2 savings than Italy but one could state that the effect is negligible. This difference exists due to the fact that Spain uses more nuclear and solar energy than Italy [11]. Only in HPWS is it possible to note a difference and that is because out of all the 4 technologies the HPWS uses the most energy, therefore highlighting better the difference between the two. 3.4 Material Flow Analysis Both BABIU and AwR use waste coming from MSWI in order to remove CO2 from biogas which comes from landfills or anaerobic digesters (AD). Therefore it is of interest to determine how much BA and APC would be needed and whether enough could be generated. To obtain a general idea, the waste flow of Spain in all of 2008 was studied and the hypothetical situation was applied where all of the biogas generated was upgraded through either BABIU or AwR. This was considered as scenario <strong>1.</strong> Fig. 2, which demonstrates the waste flow in Spain, highlights the fact that most of the unsorted waste goes to either the landfill or for composting. On the other hand, Spain currently does not treat a lot of its waste through AD or MSWI. Table 2. Scenarios for implementation of BABIU and AwR based on municipal waste flow of Spain in 2008 Scenario 1 Waste received (t) Estimated biogas production (m3) Estimated electricity production potential (MWh) MSWI BABIU AwR 69 BA from MSWI needed for BABIU (t) APC from MSWI needed for AwR (t) Anaerobic digester 624,036 37,651,670 185,476 182,570 1,648,882 185,857 Landfill 9,419,352 393,917,300 1,940,447 1,910,077 17,250,844 1,944,459 Possible BA production (t) MSWI 1,890,000 984,007 378,000 Scenario 2 Anaerobic digester 9,283,654 1,067,620,203 5,259,207 5,176,815 46,754,354 5,269,998 MSWI 6,672,517 3,473,970 1,334,503 Scenario 3 Anaerobic digester 624,036 37,651,670 185,476 182,570 1,648,882 185,857 MSWI 11,309,352 5,888,085 2,261,870 From Table 2 it can be seen that under scenario 1 not enough waste is treated through MSWI to supply sufficient BA or APC to treat all of the biogas emitted from AD and landfills. It might be possible to have enough APC to treat biogas from AD using AwR, but there would not be enough to
treat the biogas from landfills and in both cases there would not be enough BA to treat the biogas using the BABIU process. In an ideal situation countries would have citizen that are engaged enough to ensure that all organic material (OM) is selectively collected. In scenario 2 all of this OM is treated in the AD and all unsorted non OM waste would be sent to the MSWI. While in this scenario the production of biogas is around 2.5x higher, this would in turn require almost 47,000,000 t of BA for the BABIU process and 5,000,000 t of APC for the AwR, which could not be satisfied as only 6,000,000 t of waste would be treated through MSWI. Scenario 3 therefore focuses on increasing the amount of BA and APC generated by sending the unsorted waste that would have gone to the landfill to the MSWI instead. In this case there would only be biogas coming from AD. Applying this scenario could generate enough APC for AwR and even enough BA for BABIU. As well, the potential electricity generated through MSWI is greater than the potential electricity from biomethane obtained through upgrading landfill biogas. While this situation seems like the best possible choice, given the current infrastructure of waste management in Spain, it would not be feasible to implement. Currently there are not enough MSWI plants to handle the additional waste. 4. Conclusion Out of the technologies that are currently on the market the HPWS and AS showed the greatest potential CO2 savings followed by Cry. In the former and later processes the impact of electricity used plays the largest role in the CO2 emissions generated, while for AS the production of heat played this role. In the lower end of the spectrum are located PSA, OPS and at last place MS. For all of these three technologies the impact due to the methane slip plays the largest role. If the technologies are improved in these areas then its potential CO2 savings could possibly be improved. The BABIU process showed the overall greatest potential CO2 savings. Though if one starts to factor in the distance between the MSWI and the location where the technology is installed, then it rapidly decreases in CO2 savings due to the high amount of BA that must be transported. Therefore in order for the BABIU technology to keep its position as best technology, it must be installed within 125 km of a MSWI. As well since BABIU requires a large amount of BA it was found that applying it as a biogas upgrading solution for all of Spain is not realistic. Therefore based on these two studies the installation of BABIU should be applied at a local scale where an AD plant or landfill can be found close to a MSWI. Therefore it is dependent on whether or not there is a MSWI close enough that produces sufficient BA. Meanwhile AwR, which uses less APC per functional unit, has more of a leeway in both the distance from a MSWI and the production capacity of the MSWI. The production of the KOH used in AwR plays a large role in its CO2 impact. If the KOH is changed to NaOH then its impact is reduced. AwR can currently obtain a base regeneration rate of 70%, if this is improved then the GWP is improved as well, though it cannot yet achieve the same CO2 savings as for BABIU. These novel technologies show a great potential savings mainly due to the fact that they also store the CO2 from the biogas. If the CO2 removed from the current technologies is stored then they may also show similar savings, though it would be necessary to factor in the impact of the storage technology as well. Acknowledgments The authors of this study would like to thank the Life + 2008 programme for its financial support. 70
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Proceedings e report 90
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ECOS 2012 : the 25 th International
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Advisory Committee (Track Organizer
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The 25 th ECOS Conference 1987-2012
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VOLUME VI CONTENT VI. 1 CARBON CAPT
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-----------------------------------
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» Personal transportation energy c
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» Excess enthalpies of second gene
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VOLUME IV IV . 1 - FLUID DYNAMICS A
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» Exergy analysis and genetic algo
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» Optimal lighting control strateg
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» Stability and limit cycles in an
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PROCEEDINGS OF ECOS 2012 - THE 25 T
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Fig. 2. The exergy destruction of M
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ineffectiveness of the catalyst, in
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[ P EXmth EX SNG] ESR F where EXm
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Fuel inputkW 728221 203771 237719 3
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Not only at desined Rc (the ratio o
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4. DISCUSSION The graphic exergy an
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Figure 9(a) illustrates the energy
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Engineering Technical Conferences &
Page 46 and 47: generally there are four kinds of m
Page 48 and 49: However, even under the off-design
Page 50 and 51: Fig. 3. 600MW supercritical coal-fi
Page 52 and 53: CO2 rich loading(molCO2/molMEA) 0.4
Page 54 and 55: Net efficiency (%) 40.28 30.29 26.4
Page 56 and 57: Fig. 11. Schematic diagram of heat
Page 58 and 59: 28.67%. In addition, through heat i
Page 60 and 61: Applied Thermal Engineering 2010;30
Page 62 and 63: Abstract: PROCEEDINGS OF ECOS 2012
Page 64 and 65: Fig. 1. Solution diagram of „four
Page 66 and 67: K ~ K 1 eK 1a p K 1a iK mK
Page 68 and 69: Oxygen recovery rate, % 105 95 85 7
Page 70 and 71: Calculated optimal compressor press
Page 72 and 73: PROCEEDINGS OF ECOS 2012 - THE 25 T
Page 74 and 75: The net amount of the flue gas leav
Page 76 and 77: Figure 3. Idea for lignite drying b
Page 78 and 79: Energy efficiency, % 34,00 33,00 32
Page 80 and 81: points efficiency increase related
Page 82 and 83: Figure A1b. Thermoflex flow sheet o
Page 84 and 85: Figure A3a. Thermoflex flow sheet o
Page 86 and 87: Figure A4. Thermoflex flow sheet of
Page 90 and 91: 2.1. Life Cycle Assessment 2.1.1. G
Page 92 and 93: these factors. A sensitivity analys
Page 94 and 95: methane slip contributes to 13% of
Page 98 and 99: References [1] Eurobserv’er, The
Page 100 and 101: PROCEEDINGS OF ECOS 2012 - THE 25 T
Page 102 and 103: in which CO2 is separated from H2,
Page 104 and 105: dimensions of water droplets and wa
Page 106 and 107: Temperature (°C) 8 7 6 5 4 3 2 1 0
Page 108 and 109: 4. Conclusions In the present paper
Page 112 and 113: penalty, but without separate captu
Page 114 and 115: 0.5 - 0.7 kg/kg, resulting typicall
Page 116 and 117: 3.3 - Utilising waste heat All exis
Page 118 and 119: 4.5 - Suomusjärvi olivine deposits
Page 120 and 121: material will change from a few % t
Page 122 and 123: Fig. 5 Schematic diagram of the PFB
Page 124 and 125: 8. Combined SO2 capture and CO2 min
Page 126 and 127: Fig. 10 Carbonate- (left) and sulph
Page 128 and 129: [13] Ekdahl, E., Idman, H. Statemen
Page 132 and 133: HEAT Fig. 1. Scheme and main reacti
Page 134: (raw) materials pre-heating and AS
Page 137 and 138: Fig 3- Aspen Plus® model 110
Page 139 and 140: Table 4. Elemental and XRD analysis
Page 141 and 142: the ÅA CSM route. The content of M
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2.2 CFB plant For the current momen
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The CO2 emission factor which indic
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The CO2 emission factor calculated
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Appendix A Fig A.1. Simulation mode
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(b) Fig. A.2. Simulation model of C
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Table A.1. Calculated parameters at
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References [1] Pfaff I., Oexmann J.
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with a CC installation could be avo
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2.3. Basic CHP plant indices. The b
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3. Off-design calculations The main
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Fig. 6. CHP plant efficiency Fig. 7
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amount of steam delivered to the he
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[5] Lukowicz H., Mroncz M.: Analysi
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water removal is feasible by coolin
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Figure 2. Sketch of the suggested P
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a b Figure 5. a) Exergy balance of
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The basis of comparison of each met
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Figure 7a. Impact of S/CATR on PCU
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However, more energy duty is requir
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Abstract: PROCEEDINGS OF ECOS 2012
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3.1. JACOBIAN-ASPEN Interface ASPEN
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Fig. 3. Triple Pressure Bottoming S
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As seen from Table 1, the mass flow
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4. Conclusion Fig. 5. Partial Emiss
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[19] Yantovski E., Shokotov M., Sho
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investigation and the developing of
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University of L’Aquila and German
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hydrogen combustion technology at d
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eversibility of a pre-treated synth
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Fig. 1. TG curves collected for spe
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(see Fig 5). Carbon dioxide uptake
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period is reduced to the first 15 c
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CO2 capture capacity up to 150 th c
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the way for biogas utilisation is t
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projectand is described in the foll
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4. Pilot plant tests In order to de
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Concerning the absorption reaction,
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with Regeneration (AwR), consists i
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[25] Aspen Plus 2004.1. Cambridge,
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systems for fuel drying waste strea
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heated in a heat exchanger placed i
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Fig. 2. Lower heating value of fuel
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Acknowledgements The results presen
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large amount of CO2 [1,5-7]. APCr a
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N 1 i ( x x i n 1 m ) 2.3. Carbon
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DTA analysis of the untreated APCrs
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Table 4. Relative Error (%) of the
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CaO HCl CaCl H O 193kJ / mol (
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[1] M. Fernández Bertos, S.J.R. Si
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2. Process development 2.1. Backgro
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to dissolve the chloride salts prec
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The remaining 25% (5 ml/min) of the
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Table 6. Experimental conversions o
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p p 1 1. 5 p H 1 1. 5 2O p mi
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Calculating from the Aspen Plus mod
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[11] Mattila, H.-P., Experimental s
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Mg2SiO4(s) + 2CO2(g) →2MgCO3(s) +
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(Mg/Fe) of the mineral rock, Mg-sil
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Figure 2. Effect of Mg/Fe ratio of
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Figure 4 shows that an increase in
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Figure 5. Process flow diagram of M
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2. Only cold utility is needed belo
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extraction process at 400 °C (~ 62
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Table A2. Extraction equations and
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[13] Teir S, Kuusik R, Fogelholm CJ
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In the area of coal technologies al
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Tabel 1. Characteristics quantities
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N m eT 4a ~ T cp T4a 1 ( K
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Auxiliary power rate of ASU, % 40 4
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[8] Buhre B.J.P., Elliott L.K., She
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1.1 - Cement Manufacturing The ceme
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2. Numerical model The purpose of t
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-0.309x15.77x2 2.085x3 240x4 12.53x
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Table 4 - Results of the optimizati
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1. Define the studied system (in th
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cycle) or a lignin extraction plant
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limiting factor for the maximum siz
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Table 5. Key data for the four ener
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Global CO 2 emissions [ktonnes/yr]
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for biofuels and the investment cos
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The possibility to capture CO2 from
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[17] Berglin N, Andersson L. Proces
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Therefore NL Agency (an agency of t
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2.2.2. Pinch analysis Pinch analysi
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3. Case study 3.1. Plant and proces
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Te 1000 mp era 900 tur 800 e [°C 7
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Application of the approach led to
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The advantage of dynamic models is
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e equal at both time intervals and
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2.5. Selecting the number of TSs Se
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A) Time Slices for solar thermal en
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The first step of procedure is to p
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cTSs demand TS solar TSs 0 2 4 6 8
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In the presented paper a framework
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[5] Erdil E, Ilkan M, Egelioglu F.
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district energy network simulation
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were decreased by 10°C.All scenari
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Site 3 Heat sources Heat load Site
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3.2.2. Input data and assumptions A
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Fig.7 shows the operation forecast
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[13] TERMIS Operation User Guide, 7
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Polygeneration is a term used to de
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The increase in energy utilization
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are available for an entire year, 8
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6. Extensions to core methodology 6
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thermal storage and possible suppor
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laterites. Ore Geology Reviews, v.
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gasification [15], hybrid biomass g
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the second reactor. In this unit, s
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The variables effect was evaluated
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atio, as well as the shift-syngas f
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Fig. 4. Effect of operating tempera
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SDG has slight effect on the syngas
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[26.] Castle WF. Air separation and
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1. Introduction - Firenze University Press

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