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中国经济增长模式对各行业碳配额分配的影响:粗放型还是集约型

Impact of economic growth patterns on carbon quota allocation by industry in China: extensive or intensive.

作者信息

Tang Lang, Wang Peng, Liu Xiaoyu, Ren Songyan, Mo Haihua, Tao Hai, Cao Jiabao

机构信息

School of Energy Science and Engineering, University of Science and Technology of China, Hefei, 230000, China.

Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou, 510000, China.

出版信息

Sci Rep. 2025 Apr 19;15(1):13581. doi: 10.1038/s41598-025-91114-9.

Abstract

Economic growth is closely related to carbon emissions, and determining the appropriate emission reduction targets for various sectors under different economic models has always been a challenge. This paper utilizes an Energy-Economic-Environment CGE model to simulate two types of economic growth models: extensive and intensive. Four economic growth scenarios are defined, and initial carbon quota allocations for various sectors are obtained for China at two key points: the peak year (2029) and the post-peak year (2035). The ZSG-DEA model is applied, considering the principles of fairness and efficiency, to iterate carbon efficiency across 33 industries and obtain quota adjustment values. The results indicate that the innovation-driven scenario, representing intensive growth, achieves a win-win outcome compared to other scenarios by enhancing GDP and avoiding additional carbon reduction costs. The initial carbon emission efficiency in agriculture, chemicals, steel, electronics, water supply, and services all reached 1. Comparative analysis reveals that the sectors of electricity, chemicals, coal, and cement face higher emission reduction pressures, while agriculture and services experience relatively lower pressures.

摘要

经济增长与碳排放密切相关,确定不同经济模式下各部门合适的减排目标一直是一项挑战。本文利用能源 - 经济 - 环境CGE模型模拟两种经济增长模式:粗放型和集约型。定义了四种经济增长情景,并针对中国在两个关键点(峰值年(2029年)和峰值后年份(2035年))获得了各部门的初始碳配额分配。应用ZSG - DEA模型,考虑公平和效率原则,对33个行业的碳效率进行迭代,得到配额调整值。结果表明,代表集约型增长的创新驱动情景通过提高GDP和避免额外的碳减排成本,与其他情景相比实现了双赢。农业、化工、钢铁、电子、供水和服务业的初始碳排放效率均达到1。比较分析表明,电力、化工、煤炭和水泥行业面临较高的减排压力,而农业和服务业的压力相对较低。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b9e/12009394/a90a928a74e2/41598_2025_91114_Fig1_HTML.jpg

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3
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