自然资源学报 ›› 2021, Vol. 36 ›› Issue (3): 737-751.doi: 10.31497/zrzyxb.20210315

• 其他研究论文 • 上一篇    下一篇

工业生态效率对PM2.5污染的影响及溢出效应

李在军1(), 胡美娟2, 张爱平3, 周年兴2()   

  1. 1.扬州大学苏中发展研究院,扬州 225009
    2.南京师范大学地理科学学院,南京 210023
    3.扬州大学旅游烹饪学院,扬州 225127
  • 收稿日期:2019-09-05 修回日期:2020-03-25 出版日期:2021-03-28 发布日期:2021-05-28
  • 通讯作者: 周年兴 E-mail:junzailinyi@gmail.com;09182@njnu.edu.cn
  • 作者简介:李在军(1989- ),男,山东临沂人,博士,助理研究员,研究方向为区域经济发展。E-mail: junzailinyi@gmail.com
  • 基金资助:
    教育部人文社会科学基金项目(20YJCZH080);教育部人文社会科学基金项目(17YJCZH236);国家自然科学基金项目(41801123);国家自然科学基金项目(41671140)

Influence and spillover effect of industrial eco-efficiency on PM2.5 pollution

LI Zai-jun1(), HU Mei-juan2, ZHANG Ai-ping3, ZHOU Nian-xing2()   

  1. 1. Research Institute of Central Jiangsu Development, Yangzhou University, Yangzhou 225009, Jiangsu, China
    2. School of Geography Science, Nanjing Normal University, Nanjing 210023, China
    3. School of Tourism and Culinary Science, Yangzhou University, Yangzhou 225127, Jiangsu, China
  • Received:2019-09-05 Revised:2020-03-25 Online:2021-03-28 Published:2021-05-28
  • Contact: ZHOU Nian-xing E-mail:junzailinyi@gmail.com;09182@njnu.edu.cn

摘要:

针对2004—2016年中国地级市工业生态效率与PM2.5的时空关联特征和影响作用关系的研究表明:(1)工业生态效率与PM2.5呈时空交错分布特征,PM2.5高污染区连片分布于华北平原及长江中下游城市,工业生态效率高等级区集中分布于长三角、珠三角和环渤海经济区等沿海地市及中西部城市群内部分中心地市;(2)工业生态效率对PM2.5的冲击表现出“U型”变化的负向累积效应,PM2.5对工业生态效率的冲击则表现为“倒U型”变化的正向累积效应;(3)工业生态效率与PM2.5呈稳定时空关联演化特征,高高关联类型区集中分布于京津冀城市群、山东半岛城市群和长三角城市群内大部分城市,低低关联类型区多分布于鄱阳湖城市群、关中城市群及西部地市;(4)工业生态效率对PM2.5总体上具有显著且稳健的正向影响,但表现出明显的空间异质性,工业集聚水平、科技创新及城市绿化率起到显著负向影响,而城市规模、环保监督及产业结构系数影响并不显著。

关键词: PM2.5污染, 工业生态效率, 面板向量自回归模型, 空间杜宾模型

Abstract:

By means of spatial analysis and econometric models, the spatio-temporal correlation characteristics and effects between PM2.5 pollution and industrial eco-efficiency of prefecture-level cities in China from 2004 to 2016. The results show that: (1) Industrial eco-efficiency and PM2.5 shows a pattern of spatio-temporal staggered distribution. Areas with high PM2.5 pollution are mainly concentrated in the North China Plain and the middle and lower reaches of the Yangtze River, while high industrial eco-efficiency areas are distributed in coastal cities such as the Yangtze River Delta, the Pearl River Delta and the Bohai Rim Economic Zone, and a few major cities in the urban agglomerations of central and western China. (2) There is reciprocal interaction relationship between industrial eco-efficiency and PM2.5 pollution. Industrial eco-efficiency has a negative cumulative effect on PM2.5 pollution, and shows a "U-shaped" pattern, while the influence of PM2.5 pollution on industrial eco-efficiency is manifested by the positive cumulative effect of "inverted U-shaped" change. (3) Industrial eco-efficiency and PM2.5 pollution have significant spatio-temporal association, and the evolution of different types of spatio-temporal correlation keeps higher stability. Thereinto, the high industrial eco-efficiency and the high PM2.5 pollution regions are mainly concentrated in the urban agglomerations of the Beijing-Tianjin-Hebei region, the Shandong Peninsula and the Yangtze River Delta; the low industrial eco-efficiency and the low PM2.5 pollution regions are mainly distributed in the urban agglomerations of the Poyang Lake, the Guanzhong and the western region, as well as in a few cities in the northeast region. (4) Overall, industrial eco-efficiency has a significant and robust positive effect on PM2.5 pollution, but shows significant spatial heterogeneity. Specifically, the industrial agglomeration level, technological innovation and urban greening rates have a significant negative impact on PM2.5 pollution, while the effect of other variables is not significant.

Key words: PM2.5 pollution, industrial eco-efficiency, panel vector auto regression model, spatial Durbin model