Research on spatial spillover effect of carbon trading policy on electric carbon emission reduction

WANG Xiping; LI Yingjie

doi:10.19666/j.rlfd.202207142

English Version Reader LoginJournal Login

您当前的位置：

首页 >

文章列表页 >

Research on spatial spillover effect of carbon trading policy on electric carbon emission reduction

更新时间：2025-09-28

- Research on spatial spillover effect of carbon trading policy on electric carbon emission reduction
- Thermal Power Generation Vol. 51, Issue 10, Pages: 72-81(2022)
- 作者机构：
  
  华北电力大学经济管理系
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.202207142
  CLC： F426.61;X196;F832.5
- Published：2022
- 稿件说明：
移动端阅览
WANG Xiping, LI Yingjie. Research on spatial spillover effect of carbon trading policy on electric carbon emission reduction[J]. Thermal power generation, 2022, 51(10): 72-81.
DOI：

WANG Xiping, LI Yingjie. Research on spatial spillover effect of carbon trading policy on electric carbon emission reduction[J]. Thermal power generation, 2022, 51(10): 72-81. DOI： 10.19666/j.rlfd.202207142.

摘要

电力是我国碳排放量最高的行业，也是全国碳市场的交易主体，推动电力行业低碳发展是中国实现“双碳”目标的重要抓手。基于2005—2019年我国30个省份电力行业面板数据，考虑电力碳强度的空间相关性，构建空间双重差分模型分析碳交易政策对电力行业碳强度的影响，检验碳交易政策的空间溢出效应；在此基础上，进一步构建中介效应模型分析碳交易政策的影响机制。研究发现：碳交易政策能够显著降低电力行业碳强度，并且这种抑制作用逐年增强，政策对碳强度的减排效果比碳排放总量更好；电力行业碳强度具有显著的空间正相关性，试点地区实施碳交易政策能够形成政策溢出效应，推动相邻地区碳减排；碳交易政策主要通过调整能源消费结构、降低电耗强度和促进产业结构升级来降低电力碳强度。基于上述结论，提出了相关政策建议。

Abstract

Power industry is the industry with the highest carbon emissions in China

and it is also the trading subject of the national carbon market. Promoting the low-carbon development of power industry is an important starting point for China to achieve the “double-carbon” goal. Based on the panel data of power industry in China's 30 provinces from 2005 to 2019

considering the spatial correlation of carbon intensity of electric power

a spatial difference-in-differences model is constructed to analyze the impact of carbon trading policy on the carbon intensity of the power industry

and test the spatial spillover effect of carbon trading policy. On this basis

a mediation effect model is further established to analyze the impact mechanism of carbon trading policy. The results show that

carbon trading policy can significantly reduce the carbon intensity of the power industry

and this inhibition is increasing year by year. The emission reduction effect of policy on carbon intensity is better than that of total carbon emission.The carbon intensity of the power industry has a significant spatial positive correlation. The implementation of carbon trading policy in pilot areas can form a policy spillover effect and promote carbon emission reduction in adjacent areas. Carbon trading policy mainly reduces the carbon intensity of power industry by adjusting the energy consumption structure

reducing power consumption intensity and promoting the upgrading of industrial structure.Based on the above conclusions

some relevant suggestions are put forward.

关键词

Keywords

references

Views

945

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Research on heat storage schemes for peak shaving of condensing unit considering carbon trading

Accessibility analysis of carbon emissions intensity reduction target for China's power industry under technology heterogeneity

Discussion on low-carbon transformation of China's power industry under the “double-carbon” goal

Economic analysis of cogeneration units based on carbon emission characteristics and carbon trading rules

Research on the effect of carbon pricing policy on power industry based on dynamic stochastic general equilibrium model

Related Author

CHENG Yunrui

FENG Kang

YAO Zhehao

WEI Qingyuan

BAI Tianyu

ZHENG Puyan

ZOU Siyu

ZHAO Mengzhen

Related Institution

School of Energy and Mechanical Engineering, Shanghai Electric Power University

State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology

School of Management, China University of Mining and Technology

Sustainable Development and Energy Policy Research Center, School of Energy and Mining, China University of Mining and Technology

College of Energy, Power and Mechanical Engineering, North China Electric Power University

AI问答

⁰