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地区人口密度较低是否会导致人均 CO 排放量减少?:来自中国地级市的证据。

Does lower regional density result in less CO emission per capita? : Evidence from prefecture-level administrative regions in China.

机构信息

School of Marxism, Shanghai University of International Business and Economics, Shanghai, China.

School of Economic and Management, Tongji University, Shanghai, China.

出版信息

Environ Sci Pollut Res Int. 2022 Apr;29(20):29887-29903. doi: 10.1007/s11356-021-17884-7. Epub 2022 Jan 7.

Abstract

Regional density is a useful tool for analyzing regional spatial structure as well as a good starting point for analyzing regional CO2 emissions per capita. This paper empirically analyzes the relationship between regional density and per capita CO emissions in China's prefecture-level administrative regions. We improve the CO emission measurement method for prefecture-level administrative regions and estimate the per capita CO emissions of 252 prefectural-level cities in China from 2003 to 2013. Using panel fixed effect model regression, and taking the terrain roughness index as an instrumental variable to solve endogeneity, we find that the relationship between regional density and per capita CO emissions presents in an inverted U-shape, per capita CO emissions first increase with the increase of regional density, and after reaching the turning point, it decreases with regional density. In a mechanism test, analyzing the interaction terms between regional density and industrial structure, and regional density and urbanization level respectively. We found that industrial structure and urbanization are important mechanisms for regional density to affect CO emissions. In order to reduce per capita CO emissions, we propose corresponding policy implications for the regions in different positions of the "U" curve.

摘要

区域密度是分析区域空间结构的有用工具,也是分析人均区域 CO2 排放的良好起点。本文实证分析了中国地级市行政区域的区域密度与人均 CO 排放之间的关系。我们改进了地级市的 CO 排放计量方法,并从 2003 年到 2013 年估计了中国 252 个地级市的人均 CO 排放量。使用面板固定效应模型回归,并以地形粗糙度指数作为工具变量来解决内生性问题,我们发现区域密度与人均 CO 排放之间的关系呈倒 U 型,人均 CO 排放随区域密度的增加而先增加,达到转折点后随区域密度的增加而减少。在机制检验中,我们分别分析了区域密度与产业结构和区域密度与城市化水平的交互项。我们发现产业结构和城市化是区域密度影响 CO 排放的重要机制。为了降低人均 CO 排放量,我们针对“U”型曲线不同位置的地区提出了相应的政策建议。

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