Spatial and temporal heterogeneity of urban land area and PM2.5 concentration in China

Abstract

This study analyzed the spatiotemporal evolution of urban land and airborne concentrations of fine particulate matter (PM2.5) in China through global autocorrelation, local spatial autocorrelation, and multiscale geo-weighted regression analysis, thus revealing the relationship between them. The results were as follows:1. Built-up, construction, and residential areas in China showed significant spatial clustering from 2006 to 2018. The built-up and residential areas were mainly characterized by high-high agglomeration and high-low agglomeration, with high-high agglomeration characteristics varying more over time and high-low agglomeration characteristics varying less over time. The construction area was mainly characterized by high-high agglomeration, high-low agglomeration, and low-high agglomeration, with all three agglomeration characteristics showing significant changes over time. 2. Between 2006 and 2018, PM2.5 concentrations in China exhibited significant spatial clustering, which were mainly characterized by high-high clustering and low-low clustering. High-high spatial agglomeration varied more over time, evolving gradually from two agglomerations (one in the east and one in the west) to one agglomeration in the east. Meanwhile, the low-low spatial agglomeration showed relatively little change over time, with only slight changes in the southwest and northeast. 3. Between 2006 and 2018, spatial heterogeneity was significantly correlated between the urban land area and PM2.5 concentration; the effect of change in the built-up area on PM2.5 concentration was more stable, and the two showed a significant correlation. However, the influence of two variables (construction area and residential area) on the concentration of PM2.5, was not sufficient, and the correlation between the two variables and PM2.5 concentration gradually changed from insignificant to significant.