Xia Xiao-Sheng, Wang Jun-Hong, Song Wei-Dong, Cheng Xian-Fu
College of Geography and Tourism, Anhui Normal University, Wuhu 241002, China.
Provincial Key Laboratory of Natural Disaster Process and Prevention, Anhui Province, Wuhu 241002, China.
Huan Jing Ke Xue. 2020 Nov 8;41(11):4832-4843. doi: 10.13227/j.hjkx.202004108.
An ensemble estimation model of PM concentration was proposed on the basis of extreme gradient boosting, gradient boosting, random forest model, and stacking model fusion technology. Measured PM data, MERRA-2 AOD and PM reanalysis data, meteorological parameters, and night light data sets were used. On this basis, the spatiotemporal evolution features of PM concentration in China during 2000-2019 were analyzed at monthly, seasonal, and annual temporal scales. The results showed that:① Monthly PM concentration in China from 2000-2019 can be estimated reliably by the ensemble model. ② PM 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 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 concentration in China, and the main trend of monthly spatial pattern change of PM concentration was determined by meteorological conditions. ④ At an annual scale, the national PM 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.
基于极端梯度提升、梯度提升、随机森林模型和堆叠模型融合技术，提出了一种PM浓度的集成估计模型。使用了实测的PM数据、MERRA-2 AOD和PM再分析数据、气象参数以及夜光数据集。在此基础上，在月、季和年时间尺度上分析了2000 - 2019年中国PM浓度的时空演变特征。结果表明：① 集成模型能够可靠地估计2000 - 2019年中国的月PM浓度。② 2000 - 2019年PM年浓度从快速上升转变为保持稳定，然后转变为显著下降，转折点分别在2007年和2014年。PM浓度的月变化呈先下降后上升的U形，7月最低，12月最高。③ 自然地理条件和人类活动为中国PM浓度年空间格局变化奠定了基础，PM浓度月空间格局变化的主要趋势由气象条件决定。④ 在年尺度上，2000 - 2014年标准差椭圆的全国PM浓度平均中心向东移动，2014 - 2018年向西移动。在月尺度上，平均中心从1月到3月向西移动，4月到9月先向北然后向南移动，9月到12月向东移动。
