The effects of spatial-temporal changes of built-up landscape patterns on PM2.5 from a multi-scale perspective: a case study of Anhui Province, China
摘要
Sustained urbanization and industrialization have exacerbated PM2.5 pollution, posing severe threats to public health and the quality of life. The imperative need for balancing urban development and environmental protection underscores the significance of understanding how built-up landscape patterns affect PM2.5 concentrations. Using 21-year time-series data (2000–2020) for Anhui Province, we applied piecewise linear regression to detect turning points in PM2.5 concentrations and quantified their multi-scale spatiotemporal dynamics during the increasing and decreasing phases. Furthermore, bivariate spatial autocorrelation and geographically weighted regression models are employed to explore how built-up landscape patterns influence PM2.5 concentrations across different spatial scales and seasons. The key findings are as follows: (1) 2013 was the turning point for PM2.5 concentration in Anhui during 2000-2020. Before 2013, changes in built-up landscape patterns were predominantly positively correlated with rising PM2.5 levels, while after 2013, this relationship generally became negative. (2) The impact of built-up landscape patterns on PM2.5 concentrations in different regions is closely related to the topography. Effects are more pronounced in mountainous regions than in the plains. Spatial scale analysis showed that correlations strengthened with larger grids in plains but weakened in mountainous areas. (3) The influence of built-up landscape patterns on PM2.5 concentration was significantly stronger in winter than in summer. This study elucidates the spatiotemporal heterogeneity of how built-up landscapes affect PM2.5, providing critical insights for optimizing urban spatial planning to improve air quality.