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How carbon emission prices accelerate net zero: Evidence from China's coal-fired power plants

China produced over half the world's coal-fired power capacity. Using a recent and comprehensive dataset of 1269 Chinese coal-fired power plants from 2009 to 2019, this paper provides empirical evidence of the impact of China's carbon trading pilot program on emissions regulation. Results show the significant potential for emissions intensity reduction due to increasing carbon prices, especially for low-risk, low-efficiency but high-cost plants, particularly those in China's midland and western regions. Rising marginal abatement costs and accelerated depreciation from carbon prices may encourage utilities to retire high-emission power plants sooner than originally planned, leading to lower emissions intensity. The average retirement years of China's power plants can be shortened by 1.8001 and 1.6862 years under R2CUT and R2LUMP scenarios, respectively, as Cao et al. (2016). This study offers new insights into the impact of carbon prices on power plants and has important policy implications.
- Shanghai University of Finance and Economics China (People's Republic of)
- University College London United Kingdom
- Tsinghua University China (People's Republic of)
- Chinese Academy of Social Sciences China (People's Republic of)
- Institute of Economics China (People's Republic of)
Net-zero retirement, 338, Carbon emission price, Coal-fired power plants, Carbon emission intensity, Accelerated depreciation, Marginal abatement cost
Net-zero retirement, 338, Carbon emission price, Coal-fired power plants, Carbon emission intensity, Accelerated depreciation, Marginal abatement cost
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).30 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 10% 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 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
