期刊
SCIENCE ADVANCES
卷 4, 期 6, 页码 -出版社
AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/sciadv.aaq0390
关键词
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资金
- National Key R&D Program of China [2016YFA0602604, 2016YFA0602500]
- Natural Science Foundation of China [71533005, 51502103, 71503156, 41629501, 41501605]
- Social Science Foundation of China [15CJY058]
- UK Economic and Social Research Council [ES/L016028/1]
- Natural Environment Research Council [NE/N00714X/1]
- British Academy Grant [AF150310]
- Philip Leverhulme Prize
- ESRC [ES/L016028/1] Funding Source: UKRI
- NERC [NE/N00714X/1] Funding Source: UKRI
As national efforts to reduce CO2 emissions intensify, policy-makers need increasingly specific, subnational information about the sources of CO2 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 CO2 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.
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