Agglomeration supports the high-quality development of the manufacturing industry, and its associated resource and environmental effects play a crucial role in driving green economic development. Based on data from prefecture-level cities in China from 2005 to 2019, this study employs the inverse distance weighting method, the bivariate local indicator of spatial association model, the spatial Durbin model, and other techniques to explore the relationship between manufacturing agglomeration and PM 2.5 concentrations, and to assess the impact of its manufacturing agglomeration. Four correlation patterns are observed: high–high, low–low, high–low, and low–high. Among these, high–high and low–low patterns dominate in terms of number of cities. These correlation patterns demonstrate strong temporal stability, with a clear “Matthew effect”. The effect of manufacturing agglomeration on PM 2.5 levels is significantly negative and helps reduce concentrations regionally, indicating the need to further enhance agglomeration levels regionally. However, it can increase PM 2.5 levels in neighboring areas due to a siphon effect, and the impact of varies across regions. Compared with levels in 2005–2013, the significance of the relationship between manufacturing agglomeration and PM 2.5 weakened in the 2013–2019 period. Accordingly, this study proposes countermeasures and policy recommendations aimed at strengthening regional collaborative governance and inspiring differentiated agglomeration strategies to support sustainable economic development in China.
Wang et al. (Sun,) studied this question.