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中国城市化与PM2.5浓度时空动态及作用机理——基于胡焕庸线变迁的视角
引用本文:杨宇,何唯,李鹏,刘皓宇. 中国城市化与PM2.5浓度时空动态及作用机理——基于胡焕庸线变迁的视角[J]. 资源科学, 2022, 44(10): 2100-2113. DOI: 10.18402/resci.2022.10.12
作者姓名:杨宇  何唯  李鹏  刘皓宇
作者单位:1.成都理工大学商学院,成都 610059
2.中国科学院地理科学与资源研究所,北京 100101
3.南昌大学经济与管理学院,南昌 330031
基金项目:成都理工大学“双一流”建设哲学社会科学重点建设项目(ZDJS202207);成都理工大学哲学社会科学研究基金项目(YJ2022-ZD006);中国科学院青年创新促进会会员人才专项(CAS2020055)
摘    要:在快速城市化给环境带来严峻挑战的背景下,围绕中国典型城市群的城市化对环境污染影响的研究取得了显著进展。然而,聚焦胡焕庸线时空变迁而形成的“美丽中国中脊带”(简称中脊带)的城市化与雾霾污染相关深入研究较为鲜见。为此,本文利用2005—2018年全国314个地级市城市灯光复合指数(城市化)、雾霾污染(PM2.5)及其他方面的面板数据,借助ArcGIS厘定了中脊带及其东西两侧地区城市化与雾霾污染的时空变化,在STIRPAT模型和环境库兹涅茨曲线(EKC假说)的理论框架下实证分析了3个区域城市化对雾霾污染的异质性影响并及揭示了其作用机理。研究表明:①受人口密度低等影响,西侧地区城市化推进速度上升趋势要远低于东侧及中脊带地区;②城市化与雾霾污染的关系在东侧地区存在显著的倒“U”型关系,在西侧地区表现出明显的正相关关系,在中脊带地区未呈现出显著规律;③在东侧地区通过人口集聚效应和产业结构效应可缓解城市化对雾霾污染的不利影响,而在西侧地区产业结构效应会加剧不利影响,中脊带地区人口集聚效应和产业结构效应均不明显。以上结论可为建立区域联防联控的环境治理机制、推进产业结构调整和增强人口集聚规模效应等政策建议提供实证依据,并促进西侧地区高水平的现代化和高质量的城镇化。

关 键 词:城市化  雾霾污染  胡焕庸线  中脊带  作用机理  空间杜宾模型  城市灯光复合指数  PM2.5  中国  
收稿时间:2022-05-25
修稿时间:2022-09-29

Spatiotemporal dynamics and mechanisms in urbanization and PM2.5 concentration in China: A perspective based on the transition of Hu Huanyong Line
YANG Yu,HE Wei,LI Peng,LIU Haoyu. Spatiotemporal dynamics and mechanisms in urbanization and PM2.5 concentration in China: A perspective based on the transition of Hu Huanyong Line[J]. Resources Science, 2022, 44(10): 2100-2113. DOI: 10.18402/resci.2022.10.12
Authors:YANG Yu  HE Wei  LI Peng  LIU Haoyu
Affiliation:1. School of Business, Chengdu University of Technology, Chengdu 610059, China
2. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
3. School of Economics & Management, Nanchang University, Nanchang 330031, China
Abstract:In the context of severe challenges to the environment brought by rapid urbanization, significant progress of research has been made on the impacts of urbanization on environmental pollution, especially focusing on the Mid-Spine Belt of Beautiful China (referred to as the Mid-Spine Belt for short) formed by the spatiotemporal changes of Hu Huanyong Line, and its east-west differences. Therefore, with multiple datasets of the prefecture scale (covering a total of 314 cities) including the composite index of night-light (for the level of urbanization), PM2.5 concentration (for the degree of haze pollution), and other panel statistics during 2005-2018, the spatiotemporal heterogeneities of urbanization and haze in the Mid-Spine Belt and the eastern and western regions were consistently determined via the ArcGIS platform. Next, under the theoretical framework of the STochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model and the environmental Kuznets curve (EKC) hypothesis, this study empirically analyzed the heterogeneous impact of urbanization on haze pollution in the three regions and its mechanism. The main conclusions show that: (1) Affected by low population density, the rising trend of urbanization on the west side of the Mid-Spine Belt is much lower than those on the east and in the Mid-Spine Belt; (2) There is a significant inverted U-shaped relationship between haze pollution and urbanization on the east side, contrasting a significantly positive linear relationship on the west and no significant relationship in the Mid-Spine Belt; (3) In the east, the adverse impact of urbanization on haze pollution may be alleviated through the effect of population concentration and industrial structure adjustment, while in the west, the effect of industrial structure is intensified, and the two effects are not obvious in the Mid-Spine Belt. These conclusions provide an empirical basis for policy recommendations such as establishing an environmental governance mechanism of regional joint prevention and control, promoting industrial restructuring and enhancing the scale effect of population aggregation, and promoting high-level modernization and high-quality urbanization in the western region.
Keywords:urbanization  haze pollution  Hu Huanyong Line  Mid-Spine Belt  mechanism  spatial Dubin model  composite index of night-light  PM2.5  China  
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