The Value of BECCS in IAMs: a Review
Purpose of Review Integrated assessment model (IAM) scenarios consistent with Paris Agreement targets involve large negative emission technologies (NETs), mostly bioenergy with carbon capture and storage (BECCS). Such reliance on BECCS implies IAMs assign it a high value. Past analyses on the value...
Ausführliche Beschreibung
Autor*in: |
Köberle, Alexandre C. [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2019 |
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Anmerkung: |
© The Author(s) 2019 |
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Übergeordnetes Werk: |
Enthalten in: Current sustainable renewable energy reports - Cham : Springer Internat. Publ., 2014, 6(2019), 4 vom: Dez., Seite 107-115 |
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Übergeordnetes Werk: |
volume:6 ; year:2019 ; number:4 ; month:12 ; pages:107-115 |
Links: |
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DOI / URN: |
10.1007/s40518-019-00142-3 |
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Katalog-ID: |
SPR036568937 |
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245 | 1 | 4 | |a The Value of BECCS in IAMs: a Review |
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520 | |a Purpose of Review Integrated assessment model (IAM) scenarios consistent with Paris Agreement targets involve large negative emission technologies (NETs), mostly bioenergy with carbon capture and storage (BECCS). Such reliance on BECCS implies IAMs assign it a high value. Past analyses on the value of BECCS in IAMs have not explicitly addressed the role of model structure and assumptions as value drivers. This paper examines the extent to which the value of BECCS in IAMs is enhanced by model structure constraints and assumptions. Recent Findings Predominant use of high discount rates (3.5–5%) means models opt for delayed-action strategies for emissions mitigation that lead to high levels of cumulative net-negative emissions, while lower discount rates lead to reduce reliance on NETs. Until recently in the literature, most models limited NET options to only BECCS and afforestation, but introduction of other CDR options can reduce BECCS deployment. Constraints on grid penetration of variable renewable energy (VRE) is a determining factor on the level of BECCS deployment across models, and more constrained grid penetration of VREs leads to more BECCS in electricity generation. Summary This paper concludes BECCS derives significant value not only from the existing structure of IAMs but also from what is not represented in models and by predominant use of high discount rates. Omissions include NETs other than BECCS and deforestation, low-carbon innovation in end-use technologies, grid resilience to intermittent sources, and energy use in agriculture production. As IAMs increasingly endogenize such constraints, the value of BECCS in resulting scenarios is likely to be dampened. | ||
650 | 4 | |a BECCS |7 (dpeaa)DE-He213 | |
650 | 4 | |a IAMs |7 (dpeaa)DE-He213 | |
650 | 4 | |a Bioenergy |7 (dpeaa)DE-He213 | |
650 | 4 | |a Integrated assessment models |7 (dpeaa)DE-He213 | |
650 | 4 | |a Negative emissions |7 (dpeaa)DE-He213 | |
650 | 4 | |a Carbon dioxide removal |7 (dpeaa)DE-He213 | |
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10.1007/s40518-019-00142-3 doi (DE-627)SPR036568937 (SPR)s40518-019-00142-3-e DE-627 ger DE-627 rakwb eng Köberle, Alexandre C. verfasserin aut The Value of BECCS in IAMs: a Review 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2019 Purpose of Review Integrated assessment model (IAM) scenarios consistent with Paris Agreement targets involve large negative emission technologies (NETs), mostly bioenergy with carbon capture and storage (BECCS). Such reliance on BECCS implies IAMs assign it a high value. Past analyses on the value of BECCS in IAMs have not explicitly addressed the role of model structure and assumptions as value drivers. This paper examines the extent to which the value of BECCS in IAMs is enhanced by model structure constraints and assumptions. Recent Findings Predominant use of high discount rates (3.5–5%) means models opt for delayed-action strategies for emissions mitigation that lead to high levels of cumulative net-negative emissions, while lower discount rates lead to reduce reliance on NETs. Until recently in the literature, most models limited NET options to only BECCS and afforestation, but introduction of other CDR options can reduce BECCS deployment. Constraints on grid penetration of variable renewable energy (VRE) is a determining factor on the level of BECCS deployment across models, and more constrained grid penetration of VREs leads to more BECCS in electricity generation. Summary This paper concludes BECCS derives significant value not only from the existing structure of IAMs but also from what is not represented in models and by predominant use of high discount rates. Omissions include NETs other than BECCS and deforestation, low-carbon innovation in end-use technologies, grid resilience to intermittent sources, and energy use in agriculture production. As IAMs increasingly endogenize such constraints, the value of BECCS in resulting scenarios is likely to be dampened. BECCS (dpeaa)DE-He213 IAMs (dpeaa)DE-He213 Bioenergy (dpeaa)DE-He213 Integrated assessment models (dpeaa)DE-He213 Negative emissions (dpeaa)DE-He213 Carbon dioxide removal (dpeaa)DE-He213 Enthalten in Current sustainable renewable energy reports Cham : Springer Internat. Publ., 2014 6(2019), 4 vom: Dez., Seite 107-115 (DE-627)780378741 (DE-600)2760353-2 2196-3010 nnns volume:6 year:2019 number:4 month:12 pages:107-115 https://dx.doi.org/10.1007/s40518-019-00142-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_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_2008 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 6 2019 4 12 107-115 |
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10.1007/s40518-019-00142-3 doi (DE-627)SPR036568937 (SPR)s40518-019-00142-3-e DE-627 ger DE-627 rakwb eng Köberle, Alexandre C. verfasserin aut The Value of BECCS in IAMs: a Review 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2019 Purpose of Review Integrated assessment model (IAM) scenarios consistent with Paris Agreement targets involve large negative emission technologies (NETs), mostly bioenergy with carbon capture and storage (BECCS). Such reliance on BECCS implies IAMs assign it a high value. Past analyses on the value of BECCS in IAMs have not explicitly addressed the role of model structure and assumptions as value drivers. This paper examines the extent to which the value of BECCS in IAMs is enhanced by model structure constraints and assumptions. Recent Findings Predominant use of high discount rates (3.5–5%) means models opt for delayed-action strategies for emissions mitigation that lead to high levels of cumulative net-negative emissions, while lower discount rates lead to reduce reliance on NETs. Until recently in the literature, most models limited NET options to only BECCS and afforestation, but introduction of other CDR options can reduce BECCS deployment. Constraints on grid penetration of variable renewable energy (VRE) is a determining factor on the level of BECCS deployment across models, and more constrained grid penetration of VREs leads to more BECCS in electricity generation. Summary This paper concludes BECCS derives significant value not only from the existing structure of IAMs but also from what is not represented in models and by predominant use of high discount rates. Omissions include NETs other than BECCS and deforestation, low-carbon innovation in end-use technologies, grid resilience to intermittent sources, and energy use in agriculture production. As IAMs increasingly endogenize such constraints, the value of BECCS in resulting scenarios is likely to be dampened. BECCS (dpeaa)DE-He213 IAMs (dpeaa)DE-He213 Bioenergy (dpeaa)DE-He213 Integrated assessment models (dpeaa)DE-He213 Negative emissions (dpeaa)DE-He213 Carbon dioxide removal (dpeaa)DE-He213 Enthalten in Current sustainable renewable energy reports Cham : Springer Internat. Publ., 2014 6(2019), 4 vom: Dez., Seite 107-115 (DE-627)780378741 (DE-600)2760353-2 2196-3010 nnns volume:6 year:2019 number:4 month:12 pages:107-115 https://dx.doi.org/10.1007/s40518-019-00142-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_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_2008 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 6 2019 4 12 107-115 |
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10.1007/s40518-019-00142-3 doi (DE-627)SPR036568937 (SPR)s40518-019-00142-3-e DE-627 ger DE-627 rakwb eng Köberle, Alexandre C. verfasserin aut The Value of BECCS in IAMs: a Review 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2019 Purpose of Review Integrated assessment model (IAM) scenarios consistent with Paris Agreement targets involve large negative emission technologies (NETs), mostly bioenergy with carbon capture and storage (BECCS). Such reliance on BECCS implies IAMs assign it a high value. Past analyses on the value of BECCS in IAMs have not explicitly addressed the role of model structure and assumptions as value drivers. This paper examines the extent to which the value of BECCS in IAMs is enhanced by model structure constraints and assumptions. Recent Findings Predominant use of high discount rates (3.5–5%) means models opt for delayed-action strategies for emissions mitigation that lead to high levels of cumulative net-negative emissions, while lower discount rates lead to reduce reliance on NETs. Until recently in the literature, most models limited NET options to only BECCS and afforestation, but introduction of other CDR options can reduce BECCS deployment. Constraints on grid penetration of variable renewable energy (VRE) is a determining factor on the level of BECCS deployment across models, and more constrained grid penetration of VREs leads to more BECCS in electricity generation. Summary This paper concludes BECCS derives significant value not only from the existing structure of IAMs but also from what is not represented in models and by predominant use of high discount rates. Omissions include NETs other than BECCS and deforestation, low-carbon innovation in end-use technologies, grid resilience to intermittent sources, and energy use in agriculture production. As IAMs increasingly endogenize such constraints, the value of BECCS in resulting scenarios is likely to be dampened. BECCS (dpeaa)DE-He213 IAMs (dpeaa)DE-He213 Bioenergy (dpeaa)DE-He213 Integrated assessment models (dpeaa)DE-He213 Negative emissions (dpeaa)DE-He213 Carbon dioxide removal (dpeaa)DE-He213 Enthalten in Current sustainable renewable energy reports Cham : Springer Internat. Publ., 2014 6(2019), 4 vom: Dez., Seite 107-115 (DE-627)780378741 (DE-600)2760353-2 2196-3010 nnns volume:6 year:2019 number:4 month:12 pages:107-115 https://dx.doi.org/10.1007/s40518-019-00142-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_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_2008 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 6 2019 4 12 107-115 |
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10.1007/s40518-019-00142-3 doi (DE-627)SPR036568937 (SPR)s40518-019-00142-3-e DE-627 ger DE-627 rakwb eng Köberle, Alexandre C. verfasserin aut The Value of BECCS in IAMs: a Review 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2019 Purpose of Review Integrated assessment model (IAM) scenarios consistent with Paris Agreement targets involve large negative emission technologies (NETs), mostly bioenergy with carbon capture and storage (BECCS). Such reliance on BECCS implies IAMs assign it a high value. Past analyses on the value of BECCS in IAMs have not explicitly addressed the role of model structure and assumptions as value drivers. This paper examines the extent to which the value of BECCS in IAMs is enhanced by model structure constraints and assumptions. Recent Findings Predominant use of high discount rates (3.5–5%) means models opt for delayed-action strategies for emissions mitigation that lead to high levels of cumulative net-negative emissions, while lower discount rates lead to reduce reliance on NETs. Until recently in the literature, most models limited NET options to only BECCS and afforestation, but introduction of other CDR options can reduce BECCS deployment. Constraints on grid penetration of variable renewable energy (VRE) is a determining factor on the level of BECCS deployment across models, and more constrained grid penetration of VREs leads to more BECCS in electricity generation. Summary This paper concludes BECCS derives significant value not only from the existing structure of IAMs but also from what is not represented in models and by predominant use of high discount rates. Omissions include NETs other than BECCS and deforestation, low-carbon innovation in end-use technologies, grid resilience to intermittent sources, and energy use in agriculture production. As IAMs increasingly endogenize such constraints, the value of BECCS in resulting scenarios is likely to be dampened. BECCS (dpeaa)DE-He213 IAMs (dpeaa)DE-He213 Bioenergy (dpeaa)DE-He213 Integrated assessment models (dpeaa)DE-He213 Negative emissions (dpeaa)DE-He213 Carbon dioxide removal (dpeaa)DE-He213 Enthalten in Current sustainable renewable energy reports Cham : Springer Internat. Publ., 2014 6(2019), 4 vom: Dez., Seite 107-115 (DE-627)780378741 (DE-600)2760353-2 2196-3010 nnns volume:6 year:2019 number:4 month:12 pages:107-115 https://dx.doi.org/10.1007/s40518-019-00142-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_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_2008 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 6 2019 4 12 107-115 |
allfieldsSound |
10.1007/s40518-019-00142-3 doi (DE-627)SPR036568937 (SPR)s40518-019-00142-3-e DE-627 ger DE-627 rakwb eng Köberle, Alexandre C. verfasserin aut The Value of BECCS in IAMs: a Review 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2019 Purpose of Review Integrated assessment model (IAM) scenarios consistent with Paris Agreement targets involve large negative emission technologies (NETs), mostly bioenergy with carbon capture and storage (BECCS). Such reliance on BECCS implies IAMs assign it a high value. Past analyses on the value of BECCS in IAMs have not explicitly addressed the role of model structure and assumptions as value drivers. This paper examines the extent to which the value of BECCS in IAMs is enhanced by model structure constraints and assumptions. Recent Findings Predominant use of high discount rates (3.5–5%) means models opt for delayed-action strategies for emissions mitigation that lead to high levels of cumulative net-negative emissions, while lower discount rates lead to reduce reliance on NETs. Until recently in the literature, most models limited NET options to only BECCS and afforestation, but introduction of other CDR options can reduce BECCS deployment. Constraints on grid penetration of variable renewable energy (VRE) is a determining factor on the level of BECCS deployment across models, and more constrained grid penetration of VREs leads to more BECCS in electricity generation. Summary This paper concludes BECCS derives significant value not only from the existing structure of IAMs but also from what is not represented in models and by predominant use of high discount rates. Omissions include NETs other than BECCS and deforestation, low-carbon innovation in end-use technologies, grid resilience to intermittent sources, and energy use in agriculture production. As IAMs increasingly endogenize such constraints, the value of BECCS in resulting scenarios is likely to be dampened. BECCS (dpeaa)DE-He213 IAMs (dpeaa)DE-He213 Bioenergy (dpeaa)DE-He213 Integrated assessment models (dpeaa)DE-He213 Negative emissions (dpeaa)DE-He213 Carbon dioxide removal (dpeaa)DE-He213 Enthalten in Current sustainable renewable energy reports Cham : Springer Internat. Publ., 2014 6(2019), 4 vom: Dez., Seite 107-115 (DE-627)780378741 (DE-600)2760353-2 2196-3010 nnns volume:6 year:2019 number:4 month:12 pages:107-115 https://dx.doi.org/10.1007/s40518-019-00142-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_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_2008 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 6 2019 4 12 107-115 |
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Such reliance on BECCS implies IAMs assign it a high value. Past analyses on the value of BECCS in IAMs have not explicitly addressed the role of model structure and assumptions as value drivers. This paper examines the extent to which the value of BECCS in IAMs is enhanced by model structure constraints and assumptions. Recent Findings Predominant use of high discount rates (3.5–5%) means models opt for delayed-action strategies for emissions mitigation that lead to high levels of cumulative net-negative emissions, while lower discount rates lead to reduce reliance on NETs. Until recently in the literature, most models limited NET options to only BECCS and afforestation, but introduction of other CDR options can reduce BECCS deployment. Constraints on grid penetration of variable renewable energy (VRE) is a determining factor on the level of BECCS deployment across models, and more constrained grid penetration of VREs leads to more BECCS in electricity generation. Summary This paper concludes BECCS derives significant value not only from the existing structure of IAMs but also from what is not represented in models and by predominant use of high discount rates. Omissions include NETs other than BECCS and deforestation, low-carbon innovation in end-use technologies, grid resilience to intermittent sources, and energy use in agriculture production. 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Köberle, Alexandre C. |
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value of beccs in iams: a review |
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The Value of BECCS in IAMs: a Review |
abstract |
Purpose of Review Integrated assessment model (IAM) scenarios consistent with Paris Agreement targets involve large negative emission technologies (NETs), mostly bioenergy with carbon capture and storage (BECCS). Such reliance on BECCS implies IAMs assign it a high value. Past analyses on the value of BECCS in IAMs have not explicitly addressed the role of model structure and assumptions as value drivers. This paper examines the extent to which the value of BECCS in IAMs is enhanced by model structure constraints and assumptions. Recent Findings Predominant use of high discount rates (3.5–5%) means models opt for delayed-action strategies for emissions mitigation that lead to high levels of cumulative net-negative emissions, while lower discount rates lead to reduce reliance on NETs. Until recently in the literature, most models limited NET options to only BECCS and afforestation, but introduction of other CDR options can reduce BECCS deployment. Constraints on grid penetration of variable renewable energy (VRE) is a determining factor on the level of BECCS deployment across models, and more constrained grid penetration of VREs leads to more BECCS in electricity generation. Summary This paper concludes BECCS derives significant value not only from the existing structure of IAMs but also from what is not represented in models and by predominant use of high discount rates. Omissions include NETs other than BECCS and deforestation, low-carbon innovation in end-use technologies, grid resilience to intermittent sources, and energy use in agriculture production. As IAMs increasingly endogenize such constraints, the value of BECCS in resulting scenarios is likely to be dampened. © The Author(s) 2019 |
abstractGer |
Purpose of Review Integrated assessment model (IAM) scenarios consistent with Paris Agreement targets involve large negative emission technologies (NETs), mostly bioenergy with carbon capture and storage (BECCS). Such reliance on BECCS implies IAMs assign it a high value. Past analyses on the value of BECCS in IAMs have not explicitly addressed the role of model structure and assumptions as value drivers. This paper examines the extent to which the value of BECCS in IAMs is enhanced by model structure constraints and assumptions. Recent Findings Predominant use of high discount rates (3.5–5%) means models opt for delayed-action strategies for emissions mitigation that lead to high levels of cumulative net-negative emissions, while lower discount rates lead to reduce reliance on NETs. Until recently in the literature, most models limited NET options to only BECCS and afforestation, but introduction of other CDR options can reduce BECCS deployment. Constraints on grid penetration of variable renewable energy (VRE) is a determining factor on the level of BECCS deployment across models, and more constrained grid penetration of VREs leads to more BECCS in electricity generation. Summary This paper concludes BECCS derives significant value not only from the existing structure of IAMs but also from what is not represented in models and by predominant use of high discount rates. Omissions include NETs other than BECCS and deforestation, low-carbon innovation in end-use technologies, grid resilience to intermittent sources, and energy use in agriculture production. As IAMs increasingly endogenize such constraints, the value of BECCS in resulting scenarios is likely to be dampened. © The Author(s) 2019 |
abstract_unstemmed |
Purpose of Review Integrated assessment model (IAM) scenarios consistent with Paris Agreement targets involve large negative emission technologies (NETs), mostly bioenergy with carbon capture and storage (BECCS). Such reliance on BECCS implies IAMs assign it a high value. Past analyses on the value of BECCS in IAMs have not explicitly addressed the role of model structure and assumptions as value drivers. This paper examines the extent to which the value of BECCS in IAMs is enhanced by model structure constraints and assumptions. Recent Findings Predominant use of high discount rates (3.5–5%) means models opt for delayed-action strategies for emissions mitigation that lead to high levels of cumulative net-negative emissions, while lower discount rates lead to reduce reliance on NETs. Until recently in the literature, most models limited NET options to only BECCS and afforestation, but introduction of other CDR options can reduce BECCS deployment. Constraints on grid penetration of variable renewable energy (VRE) is a determining factor on the level of BECCS deployment across models, and more constrained grid penetration of VREs leads to more BECCS in electricity generation. Summary This paper concludes BECCS derives significant value not only from the existing structure of IAMs but also from what is not represented in models and by predominant use of high discount rates. Omissions include NETs other than BECCS and deforestation, low-carbon innovation in end-use technologies, grid resilience to intermittent sources, and energy use in agriculture production. As IAMs increasingly endogenize such constraints, the value of BECCS in resulting scenarios is likely to be dampened. © The Author(s) 2019 |
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title_short |
The Value of BECCS in IAMs: a Review |
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https://dx.doi.org/10.1007/s40518-019-00142-3 |
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Such reliance on BECCS implies IAMs assign it a high value. Past analyses on the value of BECCS in IAMs have not explicitly addressed the role of model structure and assumptions as value drivers. This paper examines the extent to which the value of BECCS in IAMs is enhanced by model structure constraints and assumptions. Recent Findings Predominant use of high discount rates (3.5–5%) means models opt for delayed-action strategies for emissions mitigation that lead to high levels of cumulative net-negative emissions, while lower discount rates lead to reduce reliance on NETs. Until recently in the literature, most models limited NET options to only BECCS and afforestation, but introduction of other CDR options can reduce BECCS deployment. Constraints on grid penetration of variable renewable energy (VRE) is a determining factor on the level of BECCS deployment across models, and more constrained grid penetration of VREs leads to more BECCS in electricity generation. 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|
score |
7.4013433 |