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Introduction: The uncertainty associated with PM 2.5 pollution hinders the economic high-quality development and threatens public health. Industrial agglomeration stands as a critical factor in regional economic and environmental governance, and the current studies about its impact on PM 2.5 pollution are mostly limited to a specific industry or unidirectional influence. Methods: Our study constructed spatial econometric models to analyze the effect of three major industrial agglomerations on PM 2.5 pollution, based on evidence from 110 prefecture-level cities of the Yangtze River Economic Belt in 2005–2019. Results: The results show that: 1) The three major industrial agglomerations and PM 2.5 pollution present different spatiotemporal characteristics and show prominent positive spatial autocorrelation and agglomeration effect. 2) The primary industrial agglomeration contributes to a decrease in PM 2.5 pollution and exhibits negative spatial spillover effects. A nonlinear relationship is observed between the secondary industrial agglomeration and PM 2.5 pollution. The tertiary industrial agglomeration results in an increase in PM 2.5 pollution. 3) The effects of secondary industrial agglomeration on PM 2.5 pollution exhibit varying degrees of ‘inverted U-shape’ curves in the upstream, midstream, and downstream cities. The midstream cities are the first to reach the inflection point of agglomeration. 4) Industrial agglomeration affects PM 2.5 pollution through three mechanisms, including scale expansion effect, technological spillover effect, and population scale effect. Discussion: Based on the empirical findings, this study provides scientific support and decision-making reference to improve the positive impacts of industrial agglomerations on PM 2.5 pollution.
Li et al. (Tue,) studied this question.