Uneven PM_2.5 pollution risk: Dynamic analysis of spatial drivers and differentiated policy research in typical shrinking cities in China

To advance sustainable urban transitions in shrinking cities, a potential driving indicator system applicable to PM_2.5 concentrations in shrinking cities was constructed. Based on the Optimal Parameters-based Geographical Detector model, the study explores the effective drivers of spatial elements on PM_2.5 concentration in shrinking cities and the changes in these drivers, and proposes differentiated strategies. The results show that the PM_2.5 pollution in shrinking cities exhibits substantial volatility; the duality caused by urban shrinkage still tends towards negative effects; and the dynamics and instability of the driving forces limit the usefulness of analysis approaches based on averages. Among the assessed driving forces, the scale factors are relatively stable, the structural factors are volatile, and the connectivity factors show an upward trend. Based on the change patterns of the effectiveness of the core driving factors, the forces driving PM_2.5 concentration in shrinking cities can be divided into incremental, elastic, long-term, and weakening driving forces. Considering the change characteristics of the effective driving forces of the spatial elements, various policy concepts are proposed to strengthen the differentiation and pertinence of different strategies. These findings advance spatial-level sustainable development in shrinking cities, while establishing evidence-based governance frameworks that synergize environmental remediation with socially inclusive urban transition trajectories.