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The drivers of Chinese CO2 emissions from 1980 to 2030

China's energy consumption doubled within the first 25 years of economic reforms initiated at the end of the 1970s, and doubled again in the past 5 years. It has resulted of a threefold CO2 emissions increase since early of 1980s. China's heavy reliance on coal will make it the largest emitter of CO2 in the world. By combining structural decomposition and input–output analysis we seek to assess the driving forces of China's CO2 emissions from 1980 to 2030. In our reference scenario, production-related CO2 emissions will increase another three times by 2030. Household consumption, capital investment and growth in exports will largely drive the increase in CO2 emissions. Efficiency gains will be partially offset the projected increases in consumption, but our scenarios show that this will not be sufficient if China's consumption patterns converge to current US levels. Relying on efficiency improvements alone will not stabilize China's future emissions. Our scenarios show that even extremely optimistic assumptions of widespread installation of carbon dioxide capture and storage will only slow the increase in CO2 emissions.
- University of Oslo Norway
- Norwegian University of Science and Technology Norway
- University of Cambridge United Kingdom
- University of East Anglia United Kingdom
- Carnegie Mellon University United States
330, 338
330, 338
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).543 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 0.1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 0.1% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
