City-level climate change mitigation in China
Abstract
As national efforts to reduce CO_2 emissions intensify, policy-makers need increasingly specific, subnational information about the sources of CO_2 and the potential reductions and economic implications of different possible policies. This is particularly true in China, a large and economically diverse country that has rapidly industrialized and urbanized and that has pledged under the Paris Agreement that its emissions will peak by 2030. We present new, city-level estimates of CO_2 emissions for 182 Chinese cities, decomposed into 17 different fossil fuels, 46 socioeconomic sectors, and 7 industrial processes. We find that more affluent cities have systematically lower emissions per unit of gross domestic product (GDP), supported by imports from less affluent, industrial cities located nearby. In turn, clusters of industrial cities are supported by nearby centers of coal or oil extraction. Whereas policies directly targeting manufacturing and electric power infrastructure would drastically undermine the GDP of industrial cities, consumption-based policies might allow emission reductions to be subsidized by those with greater ability to pay. In particular, sector-based analysis of each city suggests that technological improvements could be a practical and effective means of reducing emissions while maintaining growth and the current economic structure and energy system. We explore city-level emission reductions under three scenarios of technological progress to show that substantial reductions (up to 31%) are possible by updating a disproportionately small fraction of existing infrastructure.
Additional Information
© 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY). This is an open-access article distributed under the terms of the Creative Commons Attribution license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Submitted 25 September 2017. Accepted 21 May 2018. Published 27 June 2018. This work was supported by the National Key R&D Program of China (2016YFA0602604 and 2016YFA0602500), the Natural Science Foundation of China (71533005, 51502103, 71503156, 41629501, and 41501605), the Social Science Foundation of China (15CJY058), the UK Economic and Social Research Council (ES/L016028/1), the Natural Environment Research Council (NE/N00714X/1), a British Academy Grant (AF150310), the Philip Leverhulme Prize, N.F. and Z.L. thank the Resnick Sustainability Institute at Caltech. Author contributions: Y.S. and D.G. designed the research. Y.S., Z.L., Z.M., J.M., Y.L., and H.S. performed the research. Y.S. and J. Liu prepared data. Y.S. and S.J.D. wrote the paper with inputs from K.H., B.Z., J. Lin, X.D., L.J., N.F., H.W., and H.J.S. Data and materials availability: All data needed to evaluate the conclusions in the paper are uploaded to CEADs (www.ceads.net) for free download. Additional data related to this paper may be requested from the authors. The authors declare that they have no competing interests.Attached Files
Published - eaaq0390.full.pdf
Supplemental Material - aaq0390_SM.pdf
Supplemental Material - aaq0390_TablesS1_to_S5.xlsx
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Additional details
- Eprint ID
- 87418
- Resolver ID
- CaltechAUTHORS:20180627-152741323
- National Key Basic Research Program of China
- 2016YFA0602604
- National Key Basic Research Program of China
- 2016YFA0602500
- National Natural Science Foundation of China
- 71533005
- National Natural Science Foundation of China
- 51502103
- National Natural Science Foundation of China
- 71503156
- National Natural Science Foundation of China
- 41629501
- National Natural Science Foundation of China
- 41501605
- Social Science Foundation of China
- 15CJY058
- Economic and Social Research Council (ESRC)
- ES/L016028/1
- Natural Environment Research Council (NERC)
- NE/N00714X/1
- British Academy
- AF150310
- Philip Leverhulme Prize
- Resnick Sustainability Institute
- Created
-
2018-06-27Created from EPrint's datestamp field
- Updated
-
2021-11-15Created from EPrint's last_modified field
- Caltech groups
- Resnick Sustainability Institute