能耗双控转向碳双控的政策影响评估——基于安徽省动态CGE模型

摘要
图/表
参考文献
相关文章 (1)

全文: PDF (1661 KB) HTML (1 KB)
输出: BibTeX | EndNote (RIS)

摘要通过以安徽省为案例构建混合动态可计算一般均衡模型,分析能耗双控优化以及转向碳双控的能源经济影响.研究发现,扣除新增可再生能源显著促进能耗双控政策支持可再生能源的作用并改善经济有效性,2035年可再生能源发电占比达到27.9%,而GDP损失降低0.2个百分点;转向碳双控政策会进一步促进可再生能源发展、腾挪能源消费空间并提高经济效率,GDP损失率进一步下降0.05个百分点;控制政策会产生赢家和输家行业,转向碳双控政策将会降低输家行业产出损失,2035年行业产出的变化率在-20.6%至10.3%之间.建议坚持实施能耗双控制度优化措施并在“十五五”时期向碳双控政策过渡,匹配以前瞻性的产业布局和必要的公正转型措施来降低产业调整的不利影响,在降低短期政策调整波动的同时促进中长期“双碳”目标实现.

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	安康欣
	刘米可
	范淑婷
	王灿

关键词 ：能耗双控, 碳双控, 安徽省, 可计算一般均衡模型

Abstract：Using Anhui Province as a case study, a hybrid dynamic computable general equilibrium model was developed to analyze the energy-economic impacts of optimizing the energy consumption “dual control” and transitioning to the carbon “dual control” policy. The study found that excluding newly installed renewable energy within the energy “dual control” policy can significantly bolster the support for renewable energy development and improvement of energy efficiency. By 2035, the proportion of renewable energy in electricity generation is expected to reach 27.9%, with a corresponding reduction in GDP loss of 0.2 percentage points. Transitioning to the carbon "dual control" policy is projected to further promote renewable energy development, create additional space for energy consumption, and enhance economic efficiency, with an additional reduction in GDP loss of 0.05 percentage points. The implementation of control policies will result in both winners and losers across various industries, while shifting to the carbon "dual control" policy could mitigate output losses in the losing industries. The industry output change rates range from -20.6% to 10.3% by 2035. The recommendation is to persist in implementing optimized measures for the energy consumption "dual control" system and to gradually transition to the carbon "dual control" policy during the 15th Five-Year Plan period. This should be aligned with forward-looking industrial planning and necessary just transition measures to reduce the adverse impacts to industries, while concurrently facilitating the achievement of medium- and long-term dual carbon targets amidst the minimization of short-term policy adjustment fluctuations.

Key words： energy consumption “dual control” carbon “dual control” Anhui Province computable general equilibrium model

收稿日期: 2023-09-04

PACS:

X32

基金资助:国家自然科学基金-国际(地区)合作与交流项目(T2261129475);国家自然科学基金资助项目(72348001)

通讯作者: 王灿,教授,canwang@tsinghua.edu.cn E-mail: canwang@tsinghua.edu.cn

引用本文:

安康欣, 刘米可, 范淑婷, 王灿. 能耗双控转向碳双控的政策影响评估——基于安徽省动态CGE模型[J]. 中国环境科学, 2024, 44(4): 1795-1804. AN Kang-xin, LIU Mi-ke, FAN Shu-ting, WANG Can. Impact of transition from the energy consumption “dual control” to the carbon “dual control”: a CGE-based case study of Anhui. CHINA ENVIRONMENTAL SCIENCECE, 2024, 44(4): 1795-1804.

链接本文:

http://www.zghjkx.com.cn/CN/ 或 http://www.zghjkx.com.cn/CN/Y2024/V44/I4/1795

[1] 贺晋瑜,何捷,王郁涛,等.中国水泥行业二氧化碳排放达峰路径研究[J]. 环境科学研究, 2022,35(2):347-355. He J Y, He J, Wang Y T, et al. Pathway of carbon emissions peak for cement industry in China[J]. Research of Environmental Sciences, 2022,35(2):347-355.
[2] 宣晓伟."能耗双控"到"碳双控":挑战与对策[J]. 城市与环境研究, 2022,(3):42-55. Xuan X W. From "the amount and intensity control of energy consumption" to "the amount and intensity control of carbon emissions":challenge and strategy[J]. Urban and Environmental Studies, 2022,(3):42-55.
[3] Guan Y R, Shan Y L, Huang Q, et al. Assessment to China's recent emission pattern shifts[J]. Earth's Future, 2021,9(11):e2021EF002241.
[4] He W J, Yang Y T, GU W. A comparative analysis of China's provincial carbon emission allowances allocation schemes by 2030:A resource misallocation perspective[J]. Journal of Cleaner Production, 2022,361:132192.
[5] 王文举,陈真玲.中国省级区域初始碳配额分配方案研究——基于责任与目标、公平与效率的视角[J]. 管理世界, 2019,35(3):81-98. Wang W J, Chen Z L. Research on the initial carbon quota allocation scheme of provincial regions in China:Based on the perspective of responsibility and target, equity and efficiency[J]. Journal of Management World, 2019,35(3):81-98.
[6] Li Z Y, Zhao T, Wang J, et al. Two-step allocation of CO₂ emission quotas in China based on multi-principles:Going regional to provincial[J]. Journal of Cleaner Production, 2021,305:127173.
[7] 叶泽,何姣,周鑫,等.发电行业碳排放权初始配额分配的双层规划模型[J]. 系统工程, 2018,36(11):140-146. Ye Z, He J, Zhou X, et al. Bi-level programming model for initial quota allocation of carbon emission rights in power generation industry[J]. Systems Engineering, 2018,36(11):140-146.
[8] Zhou X, Niu A, Lin C. Optimizing carbon emission forecast for modelling China's 2030 provincial carbon emission quota allocation[J]. Journal of Environmental Management, 2023,325:116523.
[9] 齐绍洲,徐珍珍,谭秀杰,等.中国碳市场产能过剩行业的碳排放配额如何分配是有效的?[J]. 中国人口·资源与环境, 2021,31(9):73-85. Qi S Z, Xu Z Z, Tan X J, et al. How to allocate carbon allowances effectively for industries with overcapacity in China's carbon market?[J]. China Population, Resources and Environment, 2021,31(9):73-85.
[10] 王勇,程瑜,杨光春,等.2020和2030年碳强度目标约束下中国碳排放权的省区分解[J]. 中国环境科学, 2018,38(8):3180-3188. Wang Y, Cheng Y, Yang G C, et al. Provincial decomposition of China's carbon emission rights under the constraint of 2020 and 2030 carbon intensity targets[J]. Chinese Environmental Science, 2018, 38(8):3180-3188.
[11] 刘红琴,丁哲,王泳璇,等.基于信息熵的省域内能源消费总量分配研究[J]. 长江流域资源与环境, 2014,23(4):482-489. Liu H Q, Ding Z, Wang Y X, et al. Study on energy consumption allocation within one province based on information entropy[J]. Resources and Environment in the Yangtze Basin, 2014,23(4):482-489.
[12] Karplus V, Rausch S, Zhang D. Energy caps:alternative climate policy instruments for China?[J]. Energy Economics, 2016,56:422-431.
[13] 吴滨,高洪玮.能耗双控政策的碳减排效应分析[J]. 中国能源, 2021,43(6):39-45. Wu B, Gao H W. Analysis of the Carbon Emission Reduction Effect of the Energy Consumption "Dual Control" Policy[J]. Energy of China, 2021,43(6):39-45.
[14] 庞军,许昀,石媛昌,等.我国能源资源税改革对城乡居民的收入分配效应——基于CGE模型的分析[J]. 中国环境科学, 2020, 40(6):2729-2740. Pang J, Xu Y, Shi Y C, et al. Income distribution effects of China's energy resource tax reform on urban and rural households-an analysis based on CGE model. Chinese Environmental Science, 2020,40(6):2729-2740.
[15] 宋鹏,陈光明,尹梦蕾,等.电力行业可再生能源补贴与全国碳市场协同减排效应[J]. 中国人口·资源与环境, 2023,33(7):81-93. Song P, Chen G M, Yin M L, et al. Synergistic emission reduction effects of China's national carbon market and renewable energy subsidies in the power industry[J]. China Population, Resources and Environment, 2023,33(7):81-93.
[16] 张宁,庞军,温婧,等.我国取消电价补贴的经济影响——基于电价管制及完全竞争市场的分析[J]. 中国环境科学, 2022,42(5):2442-2452. Zhang N, Pang J, Wen J, et al. The economic impact of abolishing electricity price subsidies in China:Analysis based on electricity price regulation market and perfect competition market[J]. Chinese Environmental Science, 2022,42(5):2442-2452.
[17] 张宁,庞军,王琦瑶,等.基于CGE模型的可再生能源绿证交易机制模拟及其经济影响[J]. 中国人口·资源与环境, 2023,33(2):51-62. Zhang N, Pang J, Wang Q Y, et al. Simulation and economic impact of renewable energy green certificate trading mechanism:based on the CGE model[J]. China Population, Resources and Environment, 2023, 33(2):51-62.
[18] Mu Y, Wang C, Cai W. The economic impact of China's INDC:Distinguishing the roles of the renewable energy quota and the carbon market[J]. Renewable & Sustainable Energy Reviews, 2018,81:2955-2966.
[19] 王勇,王颖.中国实现碳减排双控目标的可行性及最优路径——能源结构优化的视角[J]. 中国环境科学, 2019,39(10):4444-4455. Wang Yong, Wang Ying. Feasibility and optimal pathway of China's double targets for carbon reduction-The perspective of energy structure optimization[J]. Chinese Environmental Science, 2019, 39(10):4444-4455.
[20] 张宁,庞军,冯相昭.全国碳市场引入配额拍卖机制的经济影响——基于CGE模型的分析[J]. 中国环境科学, 2022,42(4):1901-1911. Zhang N, Pang J, Feng X Z. The economic impacts of introducing auction into carbon allowance allocation mechanism in the national carbon market:Simulation based on CGE model[J]. China Environmental Science, 2022,42(4):1901-1911.
[21] 张宁,庞军.全国碳市场引入CCER交易及抵销机制的经济影响研究[J]. 气候变化研究进展, 2022,18(5):622-636. Zhang N, Pang J. The economic impacts of introducing CCER trading and offset mechanism into the national carbon market of China[J]. Climate Change Research, 2022,18(5):622-636.
[22] Zhang Y, Qi L, Lin X, et al. Synergistic effect of carbon ETS and carbon tax under China's peak emission target:A dynamic CGE analysis[J]. Science of The Total Environment, 2022,825:154076.
[23] 王灿,陈吉宁,邹骥.基于CGE模型的CO₂减排对中国经济的影响[J]. 清华大学学报(自然科学版), 2005,(12):1621-1624. Can W, Chen J N, Zou Y. Impact assessment of CO₂ mitigation on China economy based on a CGE model[J]. Journal of Tsinghua University (Science and Technology), 2005,(12):1621-1624.
[24] 肖谦,陈晖,张宇宁,等.碳税对我国宏观经济及可再生能源发电技术的影响——基于电力部门细分的CGE模型[J]. 中国环境科学, 2020,40(8):3672-3682. Xiao Q, Chen H, Zhang Y N, et al. The impacts of carbon tax on China's macro-economy and the development of renewable energy power generation technology:Based on CGE model with disaggregation in the electric power sector[J]. China Environmental Science, 2020,40(8):3672-3682.
[25] Zou L, Xue J J, Fox A, et al. The emissions reduction effect and economic impact of an energy tax vs. A carbon tax in china:A dynamic CGE model analysis[J]. The Singapore Economic Review, 2018,63(2):339-387.
[26] Lin B Q, Jia Z J. Supply control vs. demand control:why is resource tax more effective than carbon tax in reducing emissions?[J]. Humanities & Social Sciences Communications, 2020,7(1).
[27] Zhou J F, Wu D, Chen W. Cap and Trade Versus Carbon Tax:An Analysis Based on a CGE Model[J]. Computational Economics, 2022,59(2):853-885.
[28] 秦昌波,葛察忠,刘倩倩,等.中国煤炭环境成本内部化的经济影响分析[J]. 中国环境科学, 2018,38(2):745-754. Qin C B, Ge C Z, Liu Q Q, et al. Economic impacts of environmental cost internalization of coal in China[J]. China Environmental Science, 2018,38(2):745-754.
[29] An K X, Zhang S H, Zhou J X, et al. How can computable general equilibrium models serve low-carbon policy? A systematic review[J]. Environmental Research Letters, 2023,18(3):033002.
[30] Mu Y Q, Cai W J, Evans S, et al. Employment impacts of renewable energy policies in China:A decomposition analysis based on a CGE modeling framework[J]. Applied Energy, 2018,210:256-267.
[31] An K X, Wang C, Cai W. Low-carbon technology diffusion and economic growth of China:an evolutionary general equilibrium framework[J]. Structural Change and Economic Dynamics, 2023,65:253-263.
[32] 安徽省统计局.安徽统计年鉴2018[M]. 北京:中国统计出版社, 2018:182-263. Anhui Statistical Bureau. Anhui statistical yearbook 2018[M]. Beijing:China Statistics Press, 2018:182-263.
[33] 国家统计局能源司.中国能源统计年鉴2018[M]. 北京:中国统计出版社, 2019:196-201. Department of Energy Statistics, National Bureau of Statistics. China energy statistical yearbook 2014[M]. Beijing:China Statistics Press, 2019:196-201.
[34] Shan Y L, Huang Q, Guan D B, et al. China CO₂ emission accounts 2016~2017[J]. Scientific Data, 2020,7(1):54.
[35] Huang H, Roland-Holst D, Springer C, et al. Emissions trading systems and social equity:A CGE assessment for China[J]. Applied Energy, 2019,235:1254-1265.