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

Urheber*innen

Xing,  Xiaofan
External Organizations;

Wang,  Rong
External Organizations;

/persons/resource/Nicolas.Bauer

Bauer,  Nicolas
Potsdam Institute for Climate Impact Research;

Ciais,  Philippe
External Organizations;

Cao,  Junji
External Organizations;

Chen,  Jianmin
External Organizations;

Tang,  Xu
External Organizations;

Wang,  Lin
External Organizations;

Yang,  Xin
External Organizations;

Boucher,  Olivier
External Organizations;

Goll,  Daniel
External Organizations;

Peñuelas,  Josep
External Organizations;

Janssens,  Ivan A.
External Organizations;

Balkanski,  Yves
External Organizations;

Clark,  James
External Organizations;

Ma,  Jianmin
External Organizations;

Pan,  Bo
External Organizations;

Zhang,  Shicheng
External Organizations;

Ye,  Xingnan
External Organizations;

Wang,  Yutao
External Organizations;

Li,  Qing
External Organizations;

Luo,  Gang
External Organizations;

Shen,  Guofeng
External Organizations;

Li,  Wei
External Organizations;

Yang,  Yechen
External Organizations;

Xu,  Siqing
External Organizations;

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Volltexte (frei zugänglich)

25646oa.pdf
(Verlagsversion), 11MB

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Zitation

Xing, X., Wang, R., Bauer, N., Ciais, P., Cao, J., Chen, J., Tang, X., Wang, L., Yang, X., Boucher, O., Goll, D., Peñuelas, J., Janssens, I. A., Balkanski, Y., Clark, J., Ma, J., Pan, B., Zhang, S., Ye, X., Wang, Y., Li, Q., Luo, G., Shen, G., Li, W., Yang, Y., Xu, S. (2021): Spatially explicit analysis identifies significant potential for bioenergy with carbon capture and storage in China. - Nature Communications, 12, 3159.
https://doi.org/10.1038/s41467-021-23282-x


Zitierlink: https://publications.pik-potsdam.de/pubman/item/item_25646
Zusammenfassung
As China ramped-up coal power capacities rapidly while CO2 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.