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自然和人为因素对 PM 的影响:来自不同收入水平中国城市的经验证据。

The effect of natural and anthropogenic factors on PM: Empirical evidence from Chinese cities with different income levels.

机构信息

Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resource and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.

Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China.

出版信息

Sci Total Environ. 2019 Feb 25;653:157-167. doi: 10.1016/j.scitotenv.2018.10.367. Epub 2018 Oct 29.

Abstract

The aim of this paper is to estimate the effects of natural conditions and anthropogenic factors on PM concentrations, taking into consideration differences in the income levels, and thus the development stages, of the cities studied. To achieve this goal, a balanced dataset of 287 Chinese cities was divided into different income-based panels for the period 1998-2015. The empirical estimation results indicated that meteorological conditions exerted varied effects on PM concentrations across different income-based panels. The results show that the coefficients of temperature were positive and significant in all panels, with the exception of upper-middle-income cities. Whilst wind speed and precipitation were found to be conducive to reducing PM concentrations, no such significant correlation was found in relation to relative humidity (except in high-income cities). In terms of the anthropogenic factors addressed in the study, we found an inverted U-shaped relationship between economic development and PM concentrations, confirming the Environmental Kuznets Curve hypothesis. In addition, the industrial structure and road density were observed to exert significant positive impacts on PM concentrations. The empirical analysis of the effects of FDI on PM concentrations indicate that FDI aggravated PM pollutions in the total cities and lower-middle-income cities panels, supporting the Pollution Haven Hypothesis. The empirical results for population density suggested that it does not significantly influence PM concentrations. Moreover, we found that built-up area exerts mixed effects on PM concentrations. These results cast a new light on the issue of PM pollution for government policy makers tasked with formulating measures to mitigate the concentration of such pollutants, encouraging that consideration be given to the differences between cities with different income levels.

摘要

本文旨在考虑到研究城市的收入水平和发展阶段的差异,评估自然条件和人为因素对 PM 浓度的影响。为实现这一目标,我们将 1998 年至 2015 年期间的 287 个中国城市的平衡数据集分为不同的基于收入的面板。实证估计结果表明,气象条件对不同基于收入的面板中的 PM 浓度产生了不同的影响。结果表明,除中上收入城市外,所有面板中温度系数均为正且显著。而风速和降水被发现有利于降低 PM 浓度,但相对湿度则没有发现显著的相关性(高收入城市除外)。就研究中涉及的人为因素而言,我们发现经济发展与 PM 浓度之间呈倒 U 型关系,证实了环境库兹涅茨曲线假说。此外,产业结构和道路密度对 PM 浓度的影响显著为正。对 FDI 对 PM 浓度的影响的实证分析表明,FDI 加剧了总城市和中下收入城市面板中的 PM 污染,支持污染避难所假说。人口密度的实证结果表明,其对 PM 浓度没有显著影响。此外,我们发现建成区对 PM 浓度的影响具有混合效应。这些结果为政府决策者制定减轻此类污染物浓度的措施提供了新的视角,鼓励考虑不同收入水平的城市之间的差异。

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