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首页> 外文期刊>Journal of Cleaner Production >Polycentric and dispersed population distribution increases PM_(2.5) concentrations: Evidence from 286 Chinese cities, 2001-2016
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Polycentric and dispersed population distribution increases PM_(2.5) concentrations: Evidence from 286 Chinese cities, 2001-2016

机译:多中心和分散的人口分布增加了PM_(2.5)浓度:来自286中国城市的证据,2001-2016

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摘要

While many studies find that air pollution has been generally related with natural factors and anthropogenic activities, relatively little attention has been paid to exploring the impact of urban spatial structure on air pollution. This paper investigates the relationship between urban spatial structure and PM2.5 concentrations by drawing upon a panel dataset covering 286 Chinese cities during the 2001-2016 period. We measure two dimensions of urban spatial structure by using the LandScan High Resolution Global Population Dataset. The polycentricity-monocentricity dimension reflects to what extent population is distributed in a single center or across a number of subcenters. The concentration-dispersion dimension represents to what extent population is clustered in urban centers. By controlling for per capita GDP, population density, and the employment share of the secondary industry, our empirical results based on two-way fixed panel regression models find positive relationships between poly-centricity, dispersion, and PM2.5 concentrations of Chinese cities. Other things being equal, an increase in the degrees of polycentricity and dispersion by 0.1 would lead to a rise in PM2.5 concentration by 0.1996 mg/m(3) and 0.4063 mg/m(3) respectively. Moreover, we find that the impact of polycentricity on PM2.5 concentrations is heterogeneous across cities. For cities with higher per capita GDP (5200 US$) or a higher employment share of the secondary industry (55.37%), a polycentric distribution of population is also expected to reduce PM2.5 concentrations. The results suggest that the planning of polycentric urban structure pursued by many Chinese local governments should be cautiously rethought. (c) 2019 Elsevier Ltd. All rights reserved.
机译:虽然许多研究发现空气污染一般与自然因素和人为活动有关,但已经支付了相对较少的关注,以探索城市空间结构对空气污染的影响。本文通过绘制在2001 - 2016年期间覆盖286个中国城市的面板数据集时,调查城市空间结构与PM2.5浓度的关系。我们使用Landscan高分辨率全球人口数据集测量城市空间结构的两个维度。多核性 - 单级度尺寸反射到单个中心或多个子中心的群体分布在多大程度上。浓度 - 分散尺寸代表在城市中心聚集的程度。通过控制人均GDP,人口密度和二级行业的就业份额,我们基于双向固定面板回归模型的经验结果,找到了多元,分散和PM2.5浓度的中国城市之间的正关系。其他情况相等,多核状度和分散度的增加0.1将导致PM2.5浓度的增加0.1996mg / m(3)和0.4063mg / m(3)。此外,我们发现多营心对PM2.5浓度的影响在城市之间是异质的。对于人均GDP(> 5200美元)更高的城市或二级行业的较高就业份额(> 55.37%),还预计人口的多层分布将减少PM2.5浓度。结果表明,许多中国地方政府追求的多中心城市结构的规划应小心翼翼地训练。 (c)2019 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Journal of Cleaner Production》 |2020年第1期|119202.1-119202.11|共11页
  • 作者单位

    Southeast Univ Sch Architecture Nanjing 210096 Peoples R China|MIT Dept Urban Studies & Planning Cambridge MA 02139 USA;

    Zhejiang Univ Technol Coll Civil Engn & Architecture 18 Chaowang Rd Hangzhou 310014 Peoples R China;

    Sun Yat Sen Univ Guangdong Prov Key Lab Urbanizat & Geosimulat Sch Geog & Planning Guangzhou 510275 Guangdong Peoples R China|MIT Dept Urban Studies & Planning Cambridge MA 02139 USA;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Air pollution; PM2.5 source profiles; Urban spatial structure; LandScan; Heterogeneity;

    机译:空气污染;PM2.5源简介;城市空间结构;Landscan;异质性;

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