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

Abstract

Context Landscape heterogeneity is closely related to the spatial differentiation characteristics of PM2.5 concentration in urbanized areas. Exploring the changing coordination of landscape evolution and PM2.5 change provides robust support for mitigating urban pollution. Previous studies mainly focused on a single landscape in a specific area, lacking a quantitative comparison of multiple landscape evolution and PM2.5 concentration changes in different types of cities. Objectives This study aims to quantify how multiple landscapes evolution could affect PM2.5 and compare whether and what kind of differences exist among such effects across various regions. Methods Taking two typical inland and waterfront cities in China as examples, this study uses exploratory spatial data analysis and spatial coupling models to compare and analyze the distribution of PM2.5 and its coordinated changes with the multiple landscapes (i.e., green, blue, and gray), with townships as the basic unit. Results The PM2.5 concentrations in Hohhot and Tianjin have evident differences in spatial concentration. Moreover, the coordinated changes of green landscape and PM2.5 in the two regions show opposite trends owing to the effect of the natural background. The change of green landscape to other landscapes in Hohhot can increase PM2.5 concentration, with a maximum increase of 2.04 µg/m3. However, this landscape evolution in Tianjin may inhibit PM2.5, particularly in the blue dominant, strong coupling area. Conclusions By comparing the changes in PM2.5 concentration caused by multiple landscape evolutions, managers can take differentiated measures tailored to local conditions to provide information for urban planning strategies related to mitigating air pollution.