Decarbonizing China’s coal power with sustainable BECCS: a techno-spatial analysis
Abstract This work investigates the decarbonization potential of large-scale implementation of BECCS (in the form of biomass co-firing and post-combustion amine-based $ CO_{2} $ capture) in over 150 existing coal-fired power plants in China, combining GIS-based geospatial analysis of biomass availab...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Sammarchi, Sergio [verfasserIn] Li, Jia [verfasserIn] Yang, Qiang [verfasserIn] Yu, Jing [verfasserIn] Chen, Lei [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Übergeordnetes Werk: |
Enthalten in: Clean technologies and environmental policy - Springer Berlin Heidelberg, 2001, 26(2023), 5 vom: 07. Juni, Seite 1553-1570 |
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| Übergeordnetes Werk: |
volume:26 ; year:2023 ; number:5 ; day:07 ; month:06 ; pages:1553-1570 |
| Links: |
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| DOI / URN: |
10.1007/s10098-023-02551-x |
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| Katalog-ID: |
SPR055791743 |
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| 520 | |a Abstract This work investigates the decarbonization potential of large-scale implementation of BECCS (in the form of biomass co-firing and post-combustion amine-based $ CO_{2} $ capture) in over 150 existing coal-fired power plants in China, combining GIS-based geospatial analysis of biomass availability from agricultural residues and modelling of the techno-environmental performance of the retrofitted power plants. Using a 500-m resolution map of cropland in China, the availability of residual biomass at a radius of 25–100 km from each power plant is estimated. The biomass yield is then matched with the required input for a set of co-firing scenarios, identified by the optimal mix of different co-firing ratios (10%, 25%, and 40%) and increasing % of total plant’s capacity to be retrofitted with the chosen BECCS system. Power generation performance and required biomass for the retrofitted plants are modelled in the Integrated Environmental Control Model (IECM). According to the results, the total decarbonization potential of the modelled large-scale implementation of BECCS ranges from 0.3 to 1.8 Gt $ CO_{2} $/yr (15–81% of BAU emissions), depending on the biomass collection radius. The Chinese provinces of Shandong, Jiangsu, Anhui, and Henan have the most potential for BECCS implementation, while coal-rich regions (e.g. Inner Mongolia) or highly developed coastal areas (Guangdong, Zhejiang) are constrained by local biomass availability. Overall, this work demonstrates the significant potential of the sustainable large-scale implementation of BECCS in China and provides suggestions to policymakers to include this technology in the portfolio of solutions towards carbon neutrality. Graphical abstract | ||
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10.1007/s10098-023-02551-x doi (DE-627)SPR055791743 (SPR)s10098-023-02551-x-e DE-627 ger DE-627 rakwb eng 690 VZ 58.55 bkl Sammarchi, Sergio verfasserin aut Decarbonizing China’s coal power with sustainable BECCS: a techno-spatial analysis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract This work investigates the decarbonization potential of large-scale implementation of BECCS (in the form of biomass co-firing and post-combustion amine-based $ CO_{2} $ capture) in over 150 existing coal-fired power plants in China, combining GIS-based geospatial analysis of biomass availability from agricultural residues and modelling of the techno-environmental performance of the retrofitted power plants. Using a 500-m resolution map of cropland in China, the availability of residual biomass at a radius of 25–100 km from each power plant is estimated. The biomass yield is then matched with the required input for a set of co-firing scenarios, identified by the optimal mix of different co-firing ratios (10%, 25%, and 40%) and increasing % of total plant’s capacity to be retrofitted with the chosen BECCS system. Power generation performance and required biomass for the retrofitted plants are modelled in the Integrated Environmental Control Model (IECM). According to the results, the total decarbonization potential of the modelled large-scale implementation of BECCS ranges from 0.3 to 1.8 Gt $ CO_{2} $/yr (15–81% of BAU emissions), depending on the biomass collection radius. The Chinese provinces of Shandong, Jiangsu, Anhui, and Henan have the most potential for BECCS implementation, while coal-rich regions (e.g. Inner Mongolia) or highly developed coastal areas (Guangdong, Zhejiang) are constrained by local biomass availability. Overall, this work demonstrates the significant potential of the sustainable large-scale implementation of BECCS in China and provides suggestions to policymakers to include this technology in the portfolio of solutions towards carbon neutrality. Graphical abstract Biomass energy (dpeaa)DE-He213 Carbon capture (dpeaa)DE-He213 Decarbonization (dpeaa)DE-He213 Sustainable BECCS (dpeaa)DE-He213 Li, Jia verfasserin aut Yang, Qiang verfasserin aut Yu, Jing verfasserin aut Chen, Lei verfasserin aut Enthalten in Clean technologies and environmental policy Springer Berlin Heidelberg, 2001 26(2023), 5 vom: 07. Juni, Seite 1553-1570 Online-Ressource (DE-627)351183604 (DE-600)2084025-1 (DE-576)114295905 1618-9558 nnns volume:26 year:2023 number:5 day:07 month:06 pages:1553-1570 https://dx.doi.org/10.1007/s10098-023-02551-x X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER SSG-OPC-GGO GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 58.55 Luftreinhaltung VZ AR 26 2023 5 07 06 1553-1570 |
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10.1007/s10098-023-02551-x doi (DE-627)SPR055791743 (SPR)s10098-023-02551-x-e DE-627 ger DE-627 rakwb eng 690 VZ 58.55 bkl Sammarchi, Sergio verfasserin aut Decarbonizing China’s coal power with sustainable BECCS: a techno-spatial analysis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract This work investigates the decarbonization potential of large-scale implementation of BECCS (in the form of biomass co-firing and post-combustion amine-based $ CO_{2} $ capture) in over 150 existing coal-fired power plants in China, combining GIS-based geospatial analysis of biomass availability from agricultural residues and modelling of the techno-environmental performance of the retrofitted power plants. Using a 500-m resolution map of cropland in China, the availability of residual biomass at a radius of 25–100 km from each power plant is estimated. The biomass yield is then matched with the required input for a set of co-firing scenarios, identified by the optimal mix of different co-firing ratios (10%, 25%, and 40%) and increasing % of total plant’s capacity to be retrofitted with the chosen BECCS system. Power generation performance and required biomass for the retrofitted plants are modelled in the Integrated Environmental Control Model (IECM). According to the results, the total decarbonization potential of the modelled large-scale implementation of BECCS ranges from 0.3 to 1.8 Gt $ CO_{2} $/yr (15–81% of BAU emissions), depending on the biomass collection radius. The Chinese provinces of Shandong, Jiangsu, Anhui, and Henan have the most potential for BECCS implementation, while coal-rich regions (e.g. Inner Mongolia) or highly developed coastal areas (Guangdong, Zhejiang) are constrained by local biomass availability. Overall, this work demonstrates the significant potential of the sustainable large-scale implementation of BECCS in China and provides suggestions to policymakers to include this technology in the portfolio of solutions towards carbon neutrality. Graphical abstract Biomass energy (dpeaa)DE-He213 Carbon capture (dpeaa)DE-He213 Decarbonization (dpeaa)DE-He213 Sustainable BECCS (dpeaa)DE-He213 Li, Jia verfasserin aut Yang, Qiang verfasserin aut Yu, Jing verfasserin aut Chen, Lei verfasserin aut Enthalten in Clean technologies and environmental policy Springer Berlin Heidelberg, 2001 26(2023), 5 vom: 07. Juni, Seite 1553-1570 Online-Ressource (DE-627)351183604 (DE-600)2084025-1 (DE-576)114295905 1618-9558 nnns volume:26 year:2023 number:5 day:07 month:06 pages:1553-1570 https://dx.doi.org/10.1007/s10098-023-02551-x X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER SSG-OPC-GGO GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 58.55 Luftreinhaltung VZ AR 26 2023 5 07 06 1553-1570 |
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10.1007/s10098-023-02551-x doi (DE-627)SPR055791743 (SPR)s10098-023-02551-x-e DE-627 ger DE-627 rakwb eng 690 VZ 58.55 bkl Sammarchi, Sergio verfasserin aut Decarbonizing China’s coal power with sustainable BECCS: a techno-spatial analysis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract This work investigates the decarbonization potential of large-scale implementation of BECCS (in the form of biomass co-firing and post-combustion amine-based $ CO_{2} $ capture) in over 150 existing coal-fired power plants in China, combining GIS-based geospatial analysis of biomass availability from agricultural residues and modelling of the techno-environmental performance of the retrofitted power plants. Using a 500-m resolution map of cropland in China, the availability of residual biomass at a radius of 25–100 km from each power plant is estimated. The biomass yield is then matched with the required input for a set of co-firing scenarios, identified by the optimal mix of different co-firing ratios (10%, 25%, and 40%) and increasing % of total plant’s capacity to be retrofitted with the chosen BECCS system. Power generation performance and required biomass for the retrofitted plants are modelled in the Integrated Environmental Control Model (IECM). According to the results, the total decarbonization potential of the modelled large-scale implementation of BECCS ranges from 0.3 to 1.8 Gt $ CO_{2} $/yr (15–81% of BAU emissions), depending on the biomass collection radius. The Chinese provinces of Shandong, Jiangsu, Anhui, and Henan have the most potential for BECCS implementation, while coal-rich regions (e.g. Inner Mongolia) or highly developed coastal areas (Guangdong, Zhejiang) are constrained by local biomass availability. Overall, this work demonstrates the significant potential of the sustainable large-scale implementation of BECCS in China and provides suggestions to policymakers to include this technology in the portfolio of solutions towards carbon neutrality. Graphical abstract Biomass energy (dpeaa)DE-He213 Carbon capture (dpeaa)DE-He213 Decarbonization (dpeaa)DE-He213 Sustainable BECCS (dpeaa)DE-He213 Li, Jia verfasserin aut Yang, Qiang verfasserin aut Yu, Jing verfasserin aut Chen, Lei verfasserin aut Enthalten in Clean technologies and environmental policy Springer Berlin Heidelberg, 2001 26(2023), 5 vom: 07. Juni, Seite 1553-1570 Online-Ressource (DE-627)351183604 (DE-600)2084025-1 (DE-576)114295905 1618-9558 nnns volume:26 year:2023 number:5 day:07 month:06 pages:1553-1570 https://dx.doi.org/10.1007/s10098-023-02551-x X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER SSG-OPC-GGO GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 58.55 Luftreinhaltung VZ AR 26 2023 5 07 06 1553-1570 |
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10.1007/s10098-023-02551-x doi (DE-627)SPR055791743 (SPR)s10098-023-02551-x-e DE-627 ger DE-627 rakwb eng 690 VZ 58.55 bkl Sammarchi, Sergio verfasserin aut Decarbonizing China’s coal power with sustainable BECCS: a techno-spatial analysis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract This work investigates the decarbonization potential of large-scale implementation of BECCS (in the form of biomass co-firing and post-combustion amine-based $ CO_{2} $ capture) in over 150 existing coal-fired power plants in China, combining GIS-based geospatial analysis of biomass availability from agricultural residues and modelling of the techno-environmental performance of the retrofitted power plants. Using a 500-m resolution map of cropland in China, the availability of residual biomass at a radius of 25–100 km from each power plant is estimated. The biomass yield is then matched with the required input for a set of co-firing scenarios, identified by the optimal mix of different co-firing ratios (10%, 25%, and 40%) and increasing % of total plant’s capacity to be retrofitted with the chosen BECCS system. Power generation performance and required biomass for the retrofitted plants are modelled in the Integrated Environmental Control Model (IECM). According to the results, the total decarbonization potential of the modelled large-scale implementation of BECCS ranges from 0.3 to 1.8 Gt $ CO_{2} $/yr (15–81% of BAU emissions), depending on the biomass collection radius. The Chinese provinces of Shandong, Jiangsu, Anhui, and Henan have the most potential for BECCS implementation, while coal-rich regions (e.g. Inner Mongolia) or highly developed coastal areas (Guangdong, Zhejiang) are constrained by local biomass availability. Overall, this work demonstrates the significant potential of the sustainable large-scale implementation of BECCS in China and provides suggestions to policymakers to include this technology in the portfolio of solutions towards carbon neutrality. Graphical abstract Biomass energy (dpeaa)DE-He213 Carbon capture (dpeaa)DE-He213 Decarbonization (dpeaa)DE-He213 Sustainable BECCS (dpeaa)DE-He213 Li, Jia verfasserin aut Yang, Qiang verfasserin aut Yu, Jing verfasserin aut Chen, Lei verfasserin aut Enthalten in Clean technologies and environmental policy Springer Berlin Heidelberg, 2001 26(2023), 5 vom: 07. Juni, Seite 1553-1570 Online-Ressource (DE-627)351183604 (DE-600)2084025-1 (DE-576)114295905 1618-9558 nnns volume:26 year:2023 number:5 day:07 month:06 pages:1553-1570 https://dx.doi.org/10.1007/s10098-023-02551-x X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER SSG-OPC-GGO GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 58.55 Luftreinhaltung VZ AR 26 2023 5 07 06 1553-1570 |
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10.1007/s10098-023-02551-x doi (DE-627)SPR055791743 (SPR)s10098-023-02551-x-e DE-627 ger DE-627 rakwb eng 690 VZ 58.55 bkl Sammarchi, Sergio verfasserin aut Decarbonizing China’s coal power with sustainable BECCS: a techno-spatial analysis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract This work investigates the decarbonization potential of large-scale implementation of BECCS (in the form of biomass co-firing and post-combustion amine-based $ CO_{2} $ capture) in over 150 existing coal-fired power plants in China, combining GIS-based geospatial analysis of biomass availability from agricultural residues and modelling of the techno-environmental performance of the retrofitted power plants. Using a 500-m resolution map of cropland in China, the availability of residual biomass at a radius of 25–100 km from each power plant is estimated. The biomass yield is then matched with the required input for a set of co-firing scenarios, identified by the optimal mix of different co-firing ratios (10%, 25%, and 40%) and increasing % of total plant’s capacity to be retrofitted with the chosen BECCS system. Power generation performance and required biomass for the retrofitted plants are modelled in the Integrated Environmental Control Model (IECM). According to the results, the total decarbonization potential of the modelled large-scale implementation of BECCS ranges from 0.3 to 1.8 Gt $ CO_{2} $/yr (15–81% of BAU emissions), depending on the biomass collection radius. The Chinese provinces of Shandong, Jiangsu, Anhui, and Henan have the most potential for BECCS implementation, while coal-rich regions (e.g. Inner Mongolia) or highly developed coastal areas (Guangdong, Zhejiang) are constrained by local biomass availability. Overall, this work demonstrates the significant potential of the sustainable large-scale implementation of BECCS in China and provides suggestions to policymakers to include this technology in the portfolio of solutions towards carbon neutrality. Graphical abstract Biomass energy (dpeaa)DE-He213 Carbon capture (dpeaa)DE-He213 Decarbonization (dpeaa)DE-He213 Sustainable BECCS (dpeaa)DE-He213 Li, Jia verfasserin aut Yang, Qiang verfasserin aut Yu, Jing verfasserin aut Chen, Lei verfasserin aut Enthalten in Clean technologies and environmental policy Springer Berlin Heidelberg, 2001 26(2023), 5 vom: 07. Juni, Seite 1553-1570 Online-Ressource (DE-627)351183604 (DE-600)2084025-1 (DE-576)114295905 1618-9558 nnns volume:26 year:2023 number:5 day:07 month:06 pages:1553-1570 https://dx.doi.org/10.1007/s10098-023-02551-x X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER SSG-OPC-GGO GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 58.55 Luftreinhaltung VZ AR 26 2023 5 07 06 1553-1570 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR055791743</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240510064653.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240510s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10098-023-02551-x</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR055791743</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s10098-023-02551-x-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">690</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">58.55</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Sammarchi, Sergio</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Decarbonizing China’s coal power with sustainable BECCS: a techno-spatial analysis</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract This work investigates the decarbonization potential of large-scale implementation of BECCS (in the form of biomass co-firing and post-combustion amine-based $ CO_{2} $ capture) in over 150 existing coal-fired power plants in China, combining GIS-based geospatial analysis of biomass availability from agricultural residues and modelling of the techno-environmental performance of the retrofitted power plants. Using a 500-m resolution map of cropland in China, the availability of residual biomass at a radius of 25–100 km from each power plant is estimated. The biomass yield is then matched with the required input for a set of co-firing scenarios, identified by the optimal mix of different co-firing ratios (10%, 25%, and 40%) and increasing % of total plant’s capacity to be retrofitted with the chosen BECCS system. Power generation performance and required biomass for the retrofitted plants are modelled in the Integrated Environmental Control Model (IECM). According to the results, the total decarbonization potential of the modelled large-scale implementation of BECCS ranges from 0.3 to 1.8 Gt $ CO_{2} $/yr (15–81% of BAU emissions), depending on the biomass collection radius. The Chinese provinces of Shandong, Jiangsu, Anhui, and Henan have the most potential for BECCS implementation, while coal-rich regions (e.g. Inner Mongolia) or highly developed coastal areas (Guangdong, Zhejiang) are constrained by local biomass availability. Overall, this work demonstrates the significant potential of the sustainable large-scale implementation of BECCS in China and provides suggestions to policymakers to include this technology in the portfolio of solutions towards carbon neutrality. 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Sammarchi, Sergio |
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690 VZ 58.55 bkl Decarbonizing China’s coal power with sustainable BECCS: a techno-spatial analysis Biomass energy (dpeaa)DE-He213 Carbon capture (dpeaa)DE-He213 Decarbonization (dpeaa)DE-He213 Sustainable BECCS (dpeaa)DE-He213 |
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decarbonizing china’s coal power with sustainable beccs: a techno-spatial analysis |
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Decarbonizing China’s coal power with sustainable BECCS: a techno-spatial analysis |
| abstract |
Abstract This work investigates the decarbonization potential of large-scale implementation of BECCS (in the form of biomass co-firing and post-combustion amine-based $ CO_{2} $ capture) in over 150 existing coal-fired power plants in China, combining GIS-based geospatial analysis of biomass availability from agricultural residues and modelling of the techno-environmental performance of the retrofitted power plants. Using a 500-m resolution map of cropland in China, the availability of residual biomass at a radius of 25–100 km from each power plant is estimated. The biomass yield is then matched with the required input for a set of co-firing scenarios, identified by the optimal mix of different co-firing ratios (10%, 25%, and 40%) and increasing % of total plant’s capacity to be retrofitted with the chosen BECCS system. Power generation performance and required biomass for the retrofitted plants are modelled in the Integrated Environmental Control Model (IECM). According to the results, the total decarbonization potential of the modelled large-scale implementation of BECCS ranges from 0.3 to 1.8 Gt $ CO_{2} $/yr (15–81% of BAU emissions), depending on the biomass collection radius. The Chinese provinces of Shandong, Jiangsu, Anhui, and Henan have the most potential for BECCS implementation, while coal-rich regions (e.g. Inner Mongolia) or highly developed coastal areas (Guangdong, Zhejiang) are constrained by local biomass availability. Overall, this work demonstrates the significant potential of the sustainable large-scale implementation of BECCS in China and provides suggestions to policymakers to include this technology in the portfolio of solutions towards carbon neutrality. Graphical abstract © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstractGer |
Abstract This work investigates the decarbonization potential of large-scale implementation of BECCS (in the form of biomass co-firing and post-combustion amine-based $ CO_{2} $ capture) in over 150 existing coal-fired power plants in China, combining GIS-based geospatial analysis of biomass availability from agricultural residues and modelling of the techno-environmental performance of the retrofitted power plants. Using a 500-m resolution map of cropland in China, the availability of residual biomass at a radius of 25–100 km from each power plant is estimated. The biomass yield is then matched with the required input for a set of co-firing scenarios, identified by the optimal mix of different co-firing ratios (10%, 25%, and 40%) and increasing % of total plant’s capacity to be retrofitted with the chosen BECCS system. Power generation performance and required biomass for the retrofitted plants are modelled in the Integrated Environmental Control Model (IECM). According to the results, the total decarbonization potential of the modelled large-scale implementation of BECCS ranges from 0.3 to 1.8 Gt $ CO_{2} $/yr (15–81% of BAU emissions), depending on the biomass collection radius. The Chinese provinces of Shandong, Jiangsu, Anhui, and Henan have the most potential for BECCS implementation, while coal-rich regions (e.g. Inner Mongolia) or highly developed coastal areas (Guangdong, Zhejiang) are constrained by local biomass availability. Overall, this work demonstrates the significant potential of the sustainable large-scale implementation of BECCS in China and provides suggestions to policymakers to include this technology in the portfolio of solutions towards carbon neutrality. Graphical abstract © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstract_unstemmed |
Abstract This work investigates the decarbonization potential of large-scale implementation of BECCS (in the form of biomass co-firing and post-combustion amine-based $ CO_{2} $ capture) in over 150 existing coal-fired power plants in China, combining GIS-based geospatial analysis of biomass availability from agricultural residues and modelling of the techno-environmental performance of the retrofitted power plants. Using a 500-m resolution map of cropland in China, the availability of residual biomass at a radius of 25–100 km from each power plant is estimated. The biomass yield is then matched with the required input for a set of co-firing scenarios, identified by the optimal mix of different co-firing ratios (10%, 25%, and 40%) and increasing % of total plant’s capacity to be retrofitted with the chosen BECCS system. Power generation performance and required biomass for the retrofitted plants are modelled in the Integrated Environmental Control Model (IECM). According to the results, the total decarbonization potential of the modelled large-scale implementation of BECCS ranges from 0.3 to 1.8 Gt $ CO_{2} $/yr (15–81% of BAU emissions), depending on the biomass collection radius. The Chinese provinces of Shandong, Jiangsu, Anhui, and Henan have the most potential for BECCS implementation, while coal-rich regions (e.g. Inner Mongolia) or highly developed coastal areas (Guangdong, Zhejiang) are constrained by local biomass availability. Overall, this work demonstrates the significant potential of the sustainable large-scale implementation of BECCS in China and provides suggestions to policymakers to include this technology in the portfolio of solutions towards carbon neutrality. Graphical abstract © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| container_issue |
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| title_short |
Decarbonizing China’s coal power with sustainable BECCS: a techno-spatial analysis |
| url |
https://dx.doi.org/10.1007/s10098-023-02551-x |
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Li, Jia Yang, Qiang Yu, Jing Chen, Lei |
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Li, Jia Yang, Qiang Yu, Jing Chen, Lei |
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2024-07-03T18:02:26.664Z |
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| score |
7.4030447 |