High resolution spatiotemporal distributionand correlation analysis of PM2.5 and PM10 concentrations in the Sichuan Basin
TANG Yu-lei1, YANG Fu-mo1,2, ZHAN Yu1,2
1. College of Architecture and Environment, Sichuan University, Chengdu 610065, China;
2. National Engineering Research Center for Flus Gas Desulfurization, Chengdu 610065, China
In order to advance the understandings of the regional air pollution in the Sichuan Basin, two machine learning based models, random forests (RF), were developed to estimate the daily PM2.5 and PM10 concentrations on the 1km grid from 2013 to 2017. The datasets used for the model training included the satellite-retrieved aerosol optical depth (AOD) from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) product, the ground-based observations from the state-managed air quality monitoring network, as well as the meteorological, geographical, and socioeconomic variables. The RF models showed superior performance in predicting PM2.5 and PM10 (R2=0.86 for both). The multiyear regional average PM2.5 and PM10 concentrations were 47.8 and 75.2μg/m3, respectively. The PM2.5 and PM10 levels were predicted to be higher in the western and southern basin than the other areas, exhibiting a shape of crescent. During these five years, the PM2.5 and PM10 concentrations both decreased by 27%. The particulate matter concentrations exhibited obvious seasonality with the highest in winter and the lowest in summer. The spatial distributions of PM2.5 and PM10 showed high correlation (r=0.96), with stronger correlation in the lowland areas and slightly weaker correlation in the surrounding mountainous area. The correlations in spring (r=0.91) and summer (r=0.90) were relatively lower than those in fall (r=0.96) and winter (r=0.96). Ratio of PM2.5 to PM10 was higher in the southwestern basin and showed adescending order of winter > fall > summer > spring.
汤宇磊, 杨复沫, 詹宇. 四川盆地PM2.5与PM10高分辨率时空分布及关联分析[J]. 中国环境科学, 2019, 39(12): 4950-4958.
TANG Yu-lei, YANG Fu-mo, ZHAN Yu. High resolution spatiotemporal distributionand correlation analysis of PM2.5 and PM10 concentrations in the Sichuan Basin. CHINA ENVIRONMENTAL SCIENCECE, 2019, 39(12): 4950-4958.
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