地理学报 ›› 2021, Vol. 76 ›› Issue (5): 1274-1293.doi: 10.11821/dlxb202105017

• 资源利用与环境演变 • 上一篇    下一篇

长三角多维城市化对PM2.5浓度的非线性影响及驱动机制

郭向阳1,2(), 穆学青3, 丁正山1,2(), 秦东丽1,2   

  1. 1.南京师范大学地理科学学院,南京 210023
    2.江苏省地理信息资源开发与利用协同创新中心,南京 210023
    3.云南师范大学地理学部,昆明 650500
  • 收稿日期:2020-01-08 修回日期:2020-12-18 出版日期:2021-05-25 发布日期:2021-07-25
  • 通讯作者: 丁正山(1967-), 男, 江苏南京人, 博士, 教授, 博导, 主要从事区域发展研究。E-mail: dingzhengshan@263.net
  • 作者简介:郭向阳(1990-), 男, 河南开封人, 博士生, 主要从事城市可持续发展与旅游地理研究。E-mail: guoxiangyang01@163.com
  • 基金资助:
    国家自然科学基金项目(41961021);国家自然科学基金项目(41671147);国家自然科学基金项目(41901205);江苏省研究生科研创新计划项目(KYCX20_1174)

Nonlinear effects and driving mechanism of multidimensional urbanization on PM2.5 concentrations in the Yangtze River Delta

GUO Xiangyang1,2(), MU Xueqing3, DING Zhengshan1,2(), QIN Dongli1,2   

  1. 1. School of Geographical Science, Nanjing Normal University, Nanjing 210023, China
    2. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
    3. Department of Geography, Yunnan Normal University, Kunming 650500, China
  • Received:2020-01-08 Revised:2020-12-18 Published:2021-05-25 Online:2021-07-25
  • Supported by:
    National Natural Science Foundation of China(41961021);National Natural Science Foundation of China(41671147);National Natural Science Foundation of China(41901205);Graduate Student Scientific Research Innovation Projects in Jiangsu Province(KYCX20_1174)

摘要:

探索多维城市化对PM2.5浓度的非线性影响及驱动机制,是城市群高质量发展的重要课题。以2000—2017年长江三角洲地区城市面板遥感影像和统计数据为样本,采用反距离权重空间插值、空间自相关和标准差椭圆等方法探查其PM2.5浓度的时空演变规律,并运用系统动态面板回归模型研判多维城市化对PM2.5浓度的非线性影响及驱动机制。结果表明:① 2000—2017年,长三角PM2.5浓度由低污染等级向高污染等级演替;PM2.5浓度整体呈现由东南向西北方向递增的空间趋势。② PM2.5浓度呈现显著空间集聚与关联特征;PM2.5浓度重心总体由东南向西北方向偏移,在东西方向上趋向分散,在南北方向上逐渐极化。③ 长三角城市化子系统不同发展阶段对PM2.5浓度的非线性影响存在显著差异。经济城市化与PM2.5浓度呈倒“N”型曲线关系,二者存在环境库兹涅茨曲线(EKC)关系,当人均GDP大于63709元时,经济城市化对PM2.5浓度将产生抑制效应,表明城市综合质量提升和发展方式转变是PM2.5治理的关键;而人口城市化、土地城市化与PM2.5浓度的关系仅是倒“U”型曲线的左侧部分,二者与空气质量改善的拐点尚有一定距离。人口规模、外商直接投资、工业产业结构均对PM2.5浓度具有显著的正向效应,而环境规制对PM2.5浓度具有显著的抑制效应。长三角PM2.5浓度的时空异质性特征是在经济社会因素和政府调控等诸多因素交互叠加、循环累积作用下形成,其中,经济社会因素扮演着主角。本文为探索多维城市化对PM2.5浓度的非线性影响提供了新视角,以期为实现长三角环境保护与城市可持续发展的协调提供重要参考。

关键词: 多维城市化, 非线性影响, PM2.5浓度, 驱动机制, 长江三角洲地区

Abstract:

Exploring the nonlinear effects and driving mechanism of multidimensional urbanization on PM2.5 concentrations is of great significance in the high-quality development of urban agglomerations. This paper uses inverse distance weighted spatial interpolation, spatial autocorrelation and standard deviational ellipse to analyze the spatiotemporal heterogeneity of PM2.5 concentrations in the Yangtze River Delta. It also applies the systematic dynamic panel regression model to explore the nonlinear effects and driving mechanism of multidimensional urbanization on PM2.5 concentrations based on the remote sensing images and statistical data of urban panels in the study area from 2000 to 2017. The main conclusions are as follows: (1) From 2000 to 2017, the pollution level caused by PM2.5 concentrations evolved from low to high. Overall, the PM2.5 concentrations showed a spatial trend of increasing from southeast to northwest. (2) The PM2.5 concentrations exhibited significant spatial agglomeration and correlation characteristics. Meanwhile, the centroid of the PM2.5 concentrations generally shifted from southeast to northwest, and the PM2.5 concentrations tended to be dispersed in the east-west direction, while in contrast they were gradually polarized in the north-south direction. (3) There were significant differences in the impact of different development stages of the urbanization subsystem on the PM2.5 concentrations. The economic urbanization exhibits an inverted N relationship with the PM2.5 concentrations, which indicates that an Environmental Kuznets Curve (EKC) existed between the economic urbanization and PM2.5 concentrations. When the per capita GDP exceeds RMB 63,709 yuan, economic urbanization will have a restraining effect on the PM2.5 concentrations. This illustrates the fact that the improvement of urban development quality and transformation of urban development methods are the key to controlling PM2.5 pollution. However, the relationship among population urbanization, land urbanization and PM2.5 concentrations is only the left part of the inverted U curve, which indicates that population urbanization and land urbanization are still at a certain distance from the inflection point of air quality improvement. Last but not least, the population size, foreign investment and industrial structure all have a significant positive effect on PM2.5 concentrations, while environmental regulations have a significant negative effect on PM2.5 concentrations. It is worth noting that the spatiotemporal heterogeneity of PM2.5 concentrations is formed under the interactive overlay and cycle accumulation of socioeconomic factors, government regulations, and other factors in this region. Among them, socioeconomic factors play a leading role. This paper provides a new research perspective to explore the effects of multidimensional urbanization on PM2.5 concentrations, so that we can achieve coordination between environmental protection and urban sustainable development in the Yangtze River Delta.

Key words: multidimensional urbanization, nonlinear effect, PM2.5 concentrations, driving mechanism, Yangtze River Delta