| 2000~2019年中国PM2.5时空演化特征 |
| 摘要点击 2598 全文点击 1073 投稿时间：2020-04-12 修订日期：2020-05-22 |
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| 中文关键词 PM2.5 组合估算模型 多时间尺度 时空演化特征 中国 |
| 英文关键词 PM2.5 ensemble model estimating PM2.5 concentration multiple time scales spatio-temporal evolution China |
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| 中文摘要 |
| 本研究利用PM2.5实测数据、MERRA-2 AOD与PM2.5再分析数据、气象因子和夜间灯光等数据，基于极限梯度提升、梯度提升、随机森林模型和Stacking模型融合技术提出了PM2.5浓度组合估算模型.在此基础上，从年、季、月尺度综合分析了2000~2019年中国PM2.5时空变化特征.结果表明：①组合模型实现了中国2000年以来PM2.5逐月浓度的可靠估算.②2000~2019年中国PM2.5年均浓度呈快速增加保持稳定显著下降的趋势，2007年和2014年分别为增加到稳定和稳定到下降的转折点.PM2.5月均浓度呈先降后升的"U"型趋势，最小值在7月，最大值在12月.③自然地理条件和人类活动奠定了中国PM2.5浓度年度空间格局变化的基础，气象条件的逐月变化决定了PM2.5浓度月度空间格局变化的主基调.④2000~2014年中国PM2.5浓度的标准差椭圆中心向东移动，2014~2018年椭圆中心向西移动.1~3月椭圆中心向西移动，4~9月椭圆中心先北移后南移，9~12月椭圆中心向东移动. |
| 英文摘要 |
| An ensemble estimation model of PM2.5 concentration was proposed on the basis of extreme gradient boosting, gradient boosting, random forest model, and stacking model fusion technology. Measured PM2.5 data, MERRA-2 AOD and PM2.5 reanalysis data, meteorological parameters, and night light data sets were used. On this basis, the spatiotemporal evolution features of PM2.5 concentration in China during 2000-2019 were analyzed at monthly, seasonal, and annual temporal scales. The results showed that:① Monthly PM2.5 concentration in China from 2000-2019 can be estimated reliably by the ensemble model. ② PM2.5 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 PM2.5 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 PM2.5 concentration in China, and the main trend of monthly spatial pattern change of PM2.5 concentration was determined by meteorological conditions. ④ At an annual scale, the national PM2.5 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. |
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