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<p>Cities are critical areas for implementing air pollution control and climate change mitigation policies. Based on panel data for 284 Chinese cities from 2014 to 2021, this paper employs a slacks-based measure-directional distance function-global Malmquist-Luenberger (SBM-DDF-GML) model and a coordinated development model to construct a city-level evaluation system for the collaborative performance of carbon mitigation and air pollution control (CPCA). It analyzes the dynamic changes and spatio-temporal evolution of CPCA, and further uses a Geographically and Temporally Weighted Regression (GTWR) model to reveal the spatio-temporal heterogeneity of the drivers of CPCA in Chinese cities. We find that the carbon emission performance of Chinese cities shows a downward trend during the study period, with the Global Malmquist-Luenberger (GML) index remaining below 1 and efficiency change and technological progress offsetting each other. By contrast, the air pollution control performance of Chinese cities shows an upward trend, with the GML index generally greater than 1 and the improvement mainly driven by technological progress. More specifically, the decline in carbon emission performance is mainly attributable to insufficient economic output and excessive carbon dioxide emissions. Notably, the inefficiencies in air pollution control performance are mainly attributable to excessive emissions of carbon monoxide (CO), nitrogen dioxide (NO<sub>2</sub>), and ozone (O<sub>3</sub>). At the spatial level, the concentration of CPCA decreased from 2014 to 2021, showing a trend toward more decentralized distribution. Moreover, the drivers of CPCA in Chinese cities show significant temporal heterogeneity, and energy efficiency, environmental regulation intensity, the level of economic development, and natural factors such as annual precipitation mainly exert positive effects on CPCA. By identifying the dynamic evolution, spatial pattern, and heterogeneous drivers of CPCA at the city level, this study provides empirical evidence for explaining urban differences in coordinated carbon mitigation and air pollution control and for designing differentiated governance strategies across Chinese cities.</p>

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Spatio-temporal evolution mechanism and driving forces of collaborative performance in carbon mitigation and air pollution control: a case study of 284 cities in China

  • 期刊论文

  • 发表日期：

    2026年6月26日

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  • Yanming Sun,
  • Binkai Xu

摘要

Cities are critical areas for implementing air pollution control and climate change mitigation policies. Based on panel data for 284 Chinese cities from 2014 to 2021, this paper employs a slacks-based measure-directional distance function-global Malmquist-Luenberger (SBM-DDF-GML) model and a coordinated development model to construct a city-level evaluation system for the collaborative performance of carbon mitigation and air pollution control (CPCA). It analyzes the dynamic changes and spatio-temporal evolution of CPCA, and further uses a Geographically and Temporally Weighted Regression (GTWR) model to reveal the spatio-temporal heterogeneity of the drivers of CPCA in Chinese cities. We find that the carbon emission performance of Chinese cities shows a downward trend during the study period, with the Global Malmquist-Luenberger (GML) index remaining below 1 and efficiency change and technological progress offsetting each other. By contrast, the air pollution control performance of Chinese cities shows an upward trend, with the GML index generally greater than 1 and the improvement mainly driven by technological progress. More specifically, the decline in carbon emission performance is mainly attributable to insufficient economic output and excessive carbon dioxide emissions. Notably, the inefficiencies in air pollution control performance are mainly attributable to excessive emissions of carbon monoxide (CO), nitrogen dioxide (NO2), and ozone (O3). At the spatial level, the concentration of CPCA decreased from 2014 to 2021, showing a trend toward more decentralized distribution. Moreover, the drivers of CPCA in Chinese cities show significant temporal heterogeneity, and energy efficiency, environmental regulation intensity, the level of economic development, and natural factors such as annual precipitation mainly exert positive effects on CPCA. By identifying the dynamic evolution, spatial pattern, and heterogeneous drivers of CPCA at the city level, this study provides empirical evidence for explaining urban differences in coordinated carbon mitigation and air pollution control and for designing differentiated governance strategies across Chinese cities.