Understanding the distribution and drivers of PM_2.5 concentrations in the Yangtze River Delta from 2015 to 2020 using Random Forest Regression.

ABSTRACT: Understanding the drivers of PM_2.5 is critical for the establishment of PM_2.5 prediction models and the prevention and control of regional air pollution. In this study, the Yangtze River Delta is taken as the research object. Spatial cluster and outlier method was used to analyze the temporal and spatial distribution and variation of surface PM_2.5 in the Yangtze River Delta from 2015 to 2020, and Random Forest was utilized to analyze the drivers of PM_2.5 in this area. The results indicated that (1) based on the spatial cluster distribution of PM_2.5, the northwest and north of Yangtze River Delta region were mostly highly concentrated and surrounded by high concentrations of PM_2.5, while lowly concentrated and surrounded by l

SUBMITTER: Su Z 

PROVIDER: S-EPMC8926105 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature