Spatial heterogeneity of river effects on PM2.5 pollutants in waterfront neighborhoods based on mobile monitoring

Abstract

Concentrations of airborne particulate matter (PM) are influenced by land cover types. Water bodies in cities can influence the spatial distribution of air pollution by altering the microclimate. However, the influence of water bodies on PM2.5 concentrations is complex and requires further exploration, especially at the microscale. In this study, a geographically weighted regression (GWR) model was constructed to explore the spatially heterogeneous effect of a river on the PM2.5 concentrations in nearby riverside neighborhoods using mobile monitoring in Wuhan. The results showed that the GWR model was applicable at the neighborhood scale and had a good explanatory performance for PM2.5 concentrations, with a higher R2 (0.71). The river had multiple effects on the PM2.5 concentrations in the riverfront neighborhoods and strongly affected the air quality in neighborhoods within an 800 m distance due to wind infiltration, with the strongest effect at a 500–700 m distance. Moreover, considering spatial nonstationarity, the effect of the large river on street-level air quality largely depended on its effect on wind, and good ventilation conditions could amplify that effect. Commercial, road intersections, second-level roads and parks were identified as sensitive environmental factors affecting the river's influence on PM2.5 concentrations. In addition, urban parks had a greater mitigating effect on PM2.5 pollution than did water bodies in this study. These results help to clarify the impact of rivers on air quality and provide a theoretical basis for urban design to mitigate PM2.5 pollution.