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Prediction of PM2.5 hourly concentrations in Beijing based on machine learning algorithm and ground-based LiDAR

文献类型：期刊论文

作者Fang, Zhiyuan1,2,3; Yang, Hao1,2,3; Li, Cheng1,2,3; Cheng, Liangliang1,2,3; Zhao, Ming1,2; Xie, Chenbo1,2
刊名ARCHIVES OF ENVIRONMENTAL PROTECTION
出版日期2021
卷号47
关键词PM2 5 LiDAR Machine Learning Air pollution monitoring
ISSN号2083-4772
DOI10.24425/aep.2021.138468
通讯作者Zhao, Ming(zhaom@aiofm.ac.cn) ; Xie, Chenbo(cbxie@aiofm.ac.cn)
英文摘要The prediction of PM2.5 is important for environmental forecasting and air pollution control. In this study, four machine learning methods, ground-based LiDAR data and meteorological data were used to predict the ground-level PM2.5 concentrations in Beijing. Among the four methods, the random forest (RF) method was the most effective in predicting ground-level PM2.5 concentrations. Compared with BP neural network, support vector machine (SVM), and various linear fitting methods, the accuracy of the RF method was superior by 10%. The method can describe the spatial and temporal variation in PM2.5 concentrations under different meteorological conditions, with low root mean square error (RMSE) and mean square deviation (MD), and the consistency index (IA) reached 99.69%. Under different weather conditions, the hourly variation in PM2.5 concentrations has a good descriptive ability. In this paper, we analyzed the weights of input variables in the RF method, constructed a pollution case to correspond to the relationship between input variables and PM2.5, and analyzed the sources of pollutants via HYSPLIT backward trajectory. This method can study the interaction between PM2.5 and air pollution variables, and provide new ideas for preventing and forecasting air pollution.
WOS关键词AEROSOL OPTICAL-THICKNESS
WOS研究方向Environmental Sciences & Ecology
语种英语
WOS记录号WOS:000700925000009
出版者POLSKA AKAD NAUK, POLISH ACAD SCIENCES, INST ENVIRON ENG PAS
源URL[http://ir.hfcas.ac.cn:8080/handle/334002/125753]  
专题中国科学院合肥物质科学研究院
通讯作者Zhao, Ming; Xie, Chenbo
作者单位1.Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Key Lab Atmospher Opt, Hefei 230031, Peoples R China
2.Univ Sci & Technol China, Sci Isl Branch, Grad Sch, Hefei 230026, Peoples R China
3.Adv Laser Technol Lab Anhui Prov, Hefei 230037, Peoples R China
推荐引用方式
GB/T 7714		 Fang, Zhiyuan,Yang, Hao,Li, Cheng,et al. Prediction of PM2.5 hourly concentrations in Beijing based on machine learning algorithm and ground-based LiDAR[J]. ARCHIVES OF ENVIRONMENTAL PROTECTION,2021,47.
APA Fang, Zhiyuan,Yang, Hao,Li, Cheng,Cheng, Liangliang,Zhao, Ming,&Xie, Chenbo.(2021).Prediction of PM2.5 hourly concentrations in Beijing based on machine learning algorithm and ground-based LiDAR.ARCHIVES OF ENVIRONMENTAL PROTECTION,47.
MLA Fang, Zhiyuan,et al."Prediction of PM2.5 hourly concentrations in Beijing based on machine learning algorithm and ground-based LiDAR".ARCHIVES OF ENVIRONMENTAL PROTECTION 47(2021).

入库方式： OAI收割

来源：合肥物质科学研究院

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