An Assessment Framework for Mapping the Air Purification Service of Vegetation at the Regional Scale

Abstract

Efficiently mitigating the severe air pollution resulting from rapid progress is crucial for the sustainable development of the socio-ecological system. Recently, concerns about nature-based solutions have emerged in the research on the treatment of air pollution. Studies on the purification of PM2.5 using vegetation currently concentrate on the individual scale of tree species or urban vegetation, ignoring the regional scale, which could better assist ecological governance. Therefore, taking the Fenwei Plain of China as the study area, an assessment framework of the air purification service’s spatial distribution reflecting regional vegetation was constructed. The dry deposition model and GeoDetector were used to quantify the spatial-temporal pattern and explore natural driving factors on the removal of PM2.5. The results showed that (1) the PM2.5 purification services offered by various types of vegetation exhibit notable variations. The average removal rates of PM2.5 by vegetation were 0.186%, 0.243%, and 0.435% in 2000, 2010, and 2021, respectively. (2) Meanwhile, a wide range of spatial mismatch exists between the PM2.5 concentration and PM2.5 removal. Insufficient supply regions of PM2.5 purification services account for 50% of the Fenwei Plain. (3) PM2.5 removal was strongly influenced by the types of vegetation and the Normalized Vegetation Index (NDVI), followed by the Digital Elevation Model (DEM), and less affected by meteorological factors; a strong joint effect was shown among the factors. The findings in this research provide a new perspective on regional air pollution management at the regional scale.