SCIENTIA GEOGRAPHICA SINICA ›› 2022, Vol. 42 ›› Issue (11): 1943-1953.doi: 10.13249/j.cnki.sgs.2022.11.009

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Spatial-temporal Evolution and Convergence Trend of Air Quality in China’s Urban Agglomerations

Wan Qing1(), Luo Xiang2, Pan Fangjie1, Jin Gui3()   

  1. 1. School of Management, Wuhan Institute of Technology, Wuhan 430205, Hubei, China
    2. College of Public Administration, Central China Normal University, Wuhan 430079, Hubei, China
    3. School of Economics and Management, China University of Geosciences, Wuhan 430078, Hubei, China
  • Received:2021-08-07 Revised:2021-12-25 Online:2022-11-30 Published:2022-11-20
  • Contact: Jin Gui E-mail:wanqing1989@126.com;jingui@igsnrr.ac.cn

Abstract:

Based on the real-time monitoring data of China’s urban air quality from 2015 to 2020, the paper quantitatively analyzed the air quality differences in urban agglomerations and their sources and convergence mechanisms, using methods such as Dagum Gini coefficient, coefficient of variation and convergence model. The results show that: 1) Since 2015, the air quality of China’s 20 urban agglomerations has not shown an ideal trend of improvement year by year, but the air quality of most urban agglomerations tends to improve in the process of fluctuation, and O3 has begun to replace PM2.5 as the most important primary pollutant in part of urban agglomerations. 2) The spatial differentiation characteristics of air quality in China’s urban agglomerations are obvious, but the spatial differences have been reduced during the study period, and the differences between urban agglomerations are much larger than those within urban agglomeration. 3) The air quality of China’s urban agglomerations not only has a trend of σ convergence, but also a trend of absolute and conditional β convergence. Whether or not other heterogeneous influencing factors other than the initial air quality are considered, the urban air quality within each urban agglomeration is moving towards steady-state level.

Key words: air quality, convergence trend, spatial Durbin model, urban agglomeration

CLC Number: 

  • X51