Coordinated change of PM2.5 and multiple landscapes based on spatial coupling model: Comparison of inland and waterfront cities

Abstract

Landscape heterogeneity is closely related to the spatial differentiation characteristics of PM2.5 concentration in urbanized areas. Exploring the coordinated changes between landscape evolution and PM2.5 concentration can help alleviate urban pollution from the perspective of process governance. Researchers have mainly focused on a single landscape in a specific area but have largely neglected quantitative comparisons of multiple landscape evolution and PM2.5 concentration changes in different types of cities. Taking two typical inland and waterfront cities in China as examples, this study uses exploratory spatial data analysis and spatial coupling models to analyze the PM2.5 concentration and its coordinated changes with multiple landscapes (i.e., green, blue, and gray), with townships as the basic unit. Results show clear differences in the PM2.5 concentrations in Hohhot and Tianjin. Moreover, the coordinated changes of PM2.5 concentrations with the green landscape in the two regions show opposite trends, owing to the effect of the natural background. The change from green landscapes to other types in Hohhot can increase PM2.5 concentration, with a maximum of 2.04 μg/m3. However, this landscape evolution in Tianjin may inhibit PM2.5, particularly in blue-dominant strong-coupling areas. By comparing the dominant landscape in high-pollution areas and the changes in PM2.5 concentration caused by multiple landscape evolutions, managers can take differentiated measures based on local conditions to provide insights for urban planning strategies in mitigating air pollution.