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Spatially explicit analysis identifies significant potential for bioenergy with carbon capture and storage in China
Xiaofan Xing, Rong Wang, Nico Bauer, Philippe Ciais, Junji Cao, Jianmin Chen, Xu Tang, Lin Wang, Xin Yang, Olivier Boucher, Daniel Goll, Josep Peñuelas, Ivan A Janssens, Yves Balkanski, James Clark, Jianmin Ma, Bo Pan, Shicheng Zhang, Xingnan Ye, Yutao Wang, Qing Li, Gang Luo, Guofeng Shen, Wei Li, Yechen Yang, Siqing Xu

Spatially explicit analysis identifies significant potential for bioenergy with carbon capture and storage in China

Science & Mathematics Published 2021 Verification Pending

Overview & Synopsis

As China ramped-up coal power capacities rapidly while CO 2 emissions need to decline, these capacities would turn into stranded assets. To deal with this risk, a promising option is to retrofit these capacities to co-fire with biomass and eventually upgrade to CCS operation (BECCS), but the feasibility is debated with respect to negative impacts on broader sustainability issues. Here we present a data-rich spatially explicit approach to estimate the marginal cost curve for decarbonizing the power sector in China with BECCS. We identify a potential of 222 GW of power capacities in 2836 counties generated by co-firing 0.9 Gt of biomass from the same county, with half being agricultural residues. Our spatially explicit method helps to reduce uncertainty in the economic costs and emissions of BECCS, identify the best opportunities for bioenergy and show the limitations by logistical challenges to achieve carbon neutrality in the power sector with large-scale BECCS in China.

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Document Information

Document Title Spatially explicit analysis identifies significant potential for bioenergy with carbon capture and storage in China
Author / Organization Xiaofan Xing, Rong Wang, Nico Bauer, Philippe Ciais, Junji Cao, Jianmin Chen, Xu Tang, Lin Wang, Xin Yang, Olivier Boucher, Daniel Goll, Josep Peñuelas, Ivan A Janssens, Yves Balkanski, James Clark, Jianmin Ma, Bo Pan, Shicheng Zhang, Xingnan Ye, Yutao Wang, Qing Li, Gang Luo, Guofeng Shen, Wei Li, Yechen Yang, Siqing Xu
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2021
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-197539
Original Source Link Visit Source Page on hal.science »