Prediction and Source Contribution Analysis of PM2.5 Using a Combined FLEXPART Model and Bayesian Method over the Beijing-Tianjin-Hebei Region in China
文献类型：期刊论文
| 作者 | Guo, Lifeng1,3; Chen, Baozhang1,2,3,4; Zhang, Huifang3; Fang, Jingchun3 |
| 刊名 | ATMOSPHERE
 |
| 出版日期 | 2021-07-01 |
| 卷号 | 12期号:7页码:16 |
| 关键词 | PM2 5 forecast source contribution FLEXPART Bayesian |
| DOI | 10.3390/atmos12070860 |
| 通讯作者 | Chen, Baozhang(baozhang.chen@igsnrr.ac.cn) |
| 英文摘要 | Fine particulate matter (PM2.5) has a serious impact on human health. Forecasting PM2.5 levels and analyzing the pollution sources of PM2.5 are of great significance. In this study, the Lagrangian particle dispersion (LPD) model was developed by combining the FLEXPART model and the Bayesian inventory optimization method. The LPD model has the capacity for real-time forecasting and determination of pollution sources of PM2.5, which refers to the contribution ratio and spatial distribution of each type of pollution (industry, power, residential, and transportation). In this study, we applied the LPD model to the Beijing-Tianjin-Hebei (BTH) region to optimize the a priori PM2.5 emission inventory estimates during 15-20 March 2018. The results show that (1) the a priori estimates have a certain degree of overestimation compared with the a posteriori flux of PM2.5 for most areas of BTH; (2) after optimization, the correlation coefficient (R) between the forecasted and observed PM2.5 concentration increased by an average of approximately 10%, the root mean square error (RMSE) decreased by 30%, and the IOA (index of agreement) index increased by 16% at four observation sites (Aotizhongxin_Beijing, Beichenkejiyuanqu_Tianjin, Dahuoquan_Xintai, and Renmingongyuan_Zhangjiakou); and (3) the main sources of pollution at the four sites mainly originated from industrial and residential emissions, while power factory and transportation pollution accounted for only a small proportion. The concentration of PM2.5 forecasts and pollution sources in each type of analysis can be used as corresponding reference information for environmental governance and protection of public health. |
| WOS关键词 | AIR-POLLUTION ; SOURCE APPORTIONMENT ; NEURAL-NETWORK ; PARTICULATE MATTER ; PM10 CONCENTRATIONS ; HAZE EPISODE ; EMISSION ; CITIES ; VISIBILITY ; GUANGZHOU |
| 资助项目 | National Key R&D Program of China[2018YFA0606001] ; National Key R&D Program of China[2017YFA0604302] ; National Natural Science Foundation of China[41771114] ; National Natural Science Foundation of China[41977404] ; State Key Laboratory of Resources and Environment Information System[O88RA901YA] |
| WOS研究方向 | Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences |
| 语种 | 英语 |
| WOS记录号 | WOS:000676008900001 |
| 出版者 | MDPI |
| 资助机构 | National Key R&D Program of China ; National Natural Science Foundation of China ; State Key Laboratory of Resources and Environment Information System |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/164803]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Chen, Baozhang |
| 作者单位 | 1.Chinese Acad Meteorol Sci, Inst Atmospher Composit & Environm Meteorol, Beijing 100081, Peoples R China 2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 4.Nanjing Univ Informat Sci & Technol, Sch Remote Sensing & Geomat Engn, Nanjing 210044, Peoples R China |
| 推荐引用方式 GB/T 7714 | Guo, Lifeng,Chen, Baozhang,Zhang, Huifang,et al. Prediction and Source Contribution Analysis of PM2.5 Using a Combined FLEXPART Model and Bayesian Method over the Beijing-Tianjin-Hebei Region in China[J]. ATMOSPHERE,2021,12(7):16. |
| APA | Guo, Lifeng,Chen, Baozhang,Zhang, Huifang,&Fang, Jingchun.(2021).Prediction and Source Contribution Analysis of PM2.5 Using a Combined FLEXPART Model and Bayesian Method over the Beijing-Tianjin-Hebei Region in China.ATMOSPHERE,12(7),16. |
| MLA | Guo, Lifeng,et al."Prediction and Source Contribution Analysis of PM2.5 Using a Combined FLEXPART Model and Bayesian Method over the Beijing-Tianjin-Hebei Region in China".ATMOSPHERE 12.7(2021):16. |
入库方式： OAI收割
来源：地理科学与资源研究所
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