Estimation of PM2.5 Concentration in Sichuan Province Based on Improved Linear Mixed Effect Model and Geo-intelligent Random Forest

被引：0

作者：

Wu Y.-H. ^{[1
]}

Du N. ^{[1
]}

Wang L. ^{[1
]}

Cai H. ^{[1
]}

Zhou B. ^{[1
]}

Wu L. ^{[1
]}

Ao X. ^{[1
]}

机构：

[1] Mining College, Guizhou University, Guiyang

来源：

Huanjing Kexue/Environmental Science | 2021年 / 42卷 / 12期

关键词：

Collinearity diagnosis; Himawari-8; AOD; ILME+Geoi-RF model; PM[!sub]2.5[!/sub; Resampling; Temporal and spatial changes;

D O I：

10.13227/j.hjkx.202102048

中图分类号：

学科分类号：

摘要：

High-resolution PM2.5 spatial distribution data is of great significance for the dynamic monitoring and control of PM2.5 pollution. Himawari-8 AOD data, ERA5 meteorological reanalysis data, DEM, land-use data, and luminous remote-sensing data were selected as estimating variables, using an improved resampling method for data matching and an improved linear mixed model (iLME) combined with a Geo-intelligent random forest model to build the combined model for estimating PM2.5 concentration. The results showed that: ① Among the estimated variables selected, AOD, SP, TEMP, RH, and BLH were important factors affecting the PM2.5 concentration of Sichuan Province in 2016, and their correlation coefficients were 0.65, 0.58, 0.55, 0.54, and 0.35, respectively. ② The prediction accuracy of the iLME+Geoi-RF model was greatly improved compared to that of other models. The model-fitted R2, RMSR, and MAE were 0.94, 5.72 μg•m-3, and 3.92 μg•m-3, and the cross-validated R2, RMSR, and MAE were 0.82, 10.20 μg•m-3, and 6.44 μg•m-3, respectively. The model can obtain more accurate spatial and temporal distribution characteristics of PM2.5 in Sichuan Province and provide a more reasonable scientific reference for regional air quality assessment, human exposure risk assessment, and environmental pollution control. ③ There was a significant seasonal difference in PM2.5 concentration in Sichuan Province, with the highest concentration of PM2.5 in winter, followed by spring and autumn, with the concentration of PM2.5 in summer being the lowest. In 2016, the monthly average PM2.5 concentration in Sichuan Province showed a V shape that first decreased and then increased, with the minimum value in June, the maximum value in December, and slight fluctuations in August and November. In terms of spatial distribution, the PM2.5 concentration in the eastern area of Sichuan Province was generally higher than that in the west, and the local pollution level was relatively high. The high-valued areas were mainly distributed in the eastern region, where the cities have been developing rapidly and the population was densely distributed, whereas the low-valued areas were mainly distributed in the western region, where it is sparsely populated with backward economic development. ④ Although the overall distribution of PM2.5 concentration estimated by the different models was essentially the same, the iLME+Geoi-RF model could more accurately and effectively estimate the spatial distribution of pollution in this study area. © 2021, Science Press. All right reserved.

引用

页码：5602 / 5615

页数：13

共 40 条

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