[Spatio-temporal Evolution of PM_2.5 Concentration During 2000-2019 in China]

An ensemble estimation model of PM_2.5 concentration was proposed on the basis of extreme gradient boosting, gradient boosting, random forest model, and stacking model fusion technology. Measured PM_2.5 data, MERRA-2 AOD and PM_2.5 reanalysis data, meteorological parameters, and night light data sets were used. On this basis, the spatiotemporal evolution features of PM_2.5 concentration in China during 2000-2019 were analyzed at monthly, seasonal, and annual temporal scales. The results showed that:① Monthly PM_2.5 concentration in China from 2000-2019 can be estimated reliably by the ensemble model. ② PM_2.5 annual concentration changed from rapid increase to remaining stable and then changed to significant decline from 2000-2019, with turning points in 2007 and 2014. The monthly variation of PM_2.5 concentration showed a U shape that first decreased then increased, with the minimum value in July and the maximum value in December. ③ Natural geographic conditions and human activities laid the foundation for the annual spatial pattern change of PM_2.5 concentration in China, and the main trend of monthly spatial pattern change of PM_2.5 concentration was determined by meteorological conditions. ④ At an annual scale, the national PM_2.5 concentration average center of standard deviation ellipse moved eastward from 2000-2014 and westward from 2014-2018. At a monthly scale, the average center shifted to the west from January to March, moved northward then southward from April to September, and shifted to the east from September to December.