Random forest model based fine scale spatiotemporal O-3 trends in the Beijing-Tianjin-Hebei region in China, 2010 to 2017

doi:10.1016/j.envpol.2021.116635

	Random forest model based fine scale spatiotemporal O-3 trends in the Beijing-Tianjin-Hebei region in China, 2010 to 2017
	Ma, Runmei 4; Ban, Jie 4; Wang, Qing 4; Zhang, Yayi 2,4; Yang, Yang 3; He, Mike Z.5; Li, Shenshen 6; Shi, Wenjiao 1; Li, Tiantian 4
刊名	ENVIRONMENTAL POLLUTION
	2021-05-01
卷号	276 页码:9
关键词	Ambient ozone Random forest model Simulation
ISSN号	0269-7491
DOI	10.1016/j.envpol.2021.116635
通讯作者	Li, Tiantian(litiantian@nieh.chinacdc.cn)
英文摘要	Ambient ozone (O-3) concentrations have shown an upward trend in China and its health hazards have also been recognized in recent years. High-resolution exposure data based on statistical models are needed. Our study aimed to build high-performance random forest (RF) models based on training data from 2013 to 2017 in the Beijing-Tianjin-Hebei (BTH) region in China at a 0.01 degrees x 0.01 degrees resolution, and estimated daily maximum 8h average O-3 (O-3 -8hmax) concentration, daily average O-3 (O-3 -mean) concentration, and daily maximum 1 h O-3 (O-3-1hmax) concentration from 2010 to 2017. Model features included meteorological variables, chemical transport model output variables, geographic variables, and population data. The test-R-2 of sample-based O-3-8hmax, O-3-mean and O-3-1hmax models were all greater than 0.80, while the R-2 of site-based and date-based model were 0.68-0.87. From 2010 to 2017, O-3-8hmax, O-3-mean, and O-3-1hmax concentrations in the BTH region increased by 4.18 mu g/m(3), 0.11 mu g/m(3), and 4.71 mu g/m(3), especially in more developed regions. Due to the influence of weather conditions, which showed high contribution to the model, the long-term spatial distribution of O-3 concentrations indicated a similar pattern as altitude, where high concentration levels were distributed in regions with higher altitude. (C) 2021 Elsevier Ltd. All rights reserved.
资助项目	National Key Research and Development Program of China[2017YFC0211706] ; National Natural Science Foundation of China[92043301] ; National Natural Science Foundation of China[41701234]
WOS研究方向	Environmental Sciences & Ecology
语种	英语
出版者	ELSEVIER SCI LTD
WOS记录号	WOS:000630774100010
资助机构	National Key Research and Development Program of China ; National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/162106]
专题	中国科学院地理科学与资源研究所
通讯作者	Li, Tiantian
作者单位	1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China 2.Jiangsu Ocean Univ, Lianyungang 222000, Jiangsu, Peoples R China 3.China Meteorol Adm, Inst Urban Meteorol, Beijing 100089, Peoples R China 4.Chinese Ctr Dis Control & Prevent, China CDC Key Lab Environm & Populat Hlth, Natl Inst Environm Hlth, Beijing 100021, Peoples R China 5.Icahn Sch Med Mt Sinai, Dept Environm Med & Publ Hlth, New York, NY 10029 USA 6.Chinese Acad Sci, Aerosp Informat Res Inst AIR, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
推荐引用方式 GB/T 7714	Ma, Runmei,Ban, Jie,Wang, Qing,et al. Random forest model based fine scale spatiotemporal O-3 trends in the Beijing-Tianjin-Hebei region in China, 2010 to 2017[J]. ENVIRONMENTAL POLLUTION,2021,276:9.
APA	Ma, Runmei.,Ban, Jie.,Wang, Qing.,Zhang, Yayi.,Yang, Yang.,...&Li, Tiantian.(2021).Random forest model based fine scale spatiotemporal O-3 trends in the Beijing-Tianjin-Hebei region in China, 2010 to 2017.ENVIRONMENTAL POLLUTION,276,9.
MLA	Ma, Runmei,et al."Random forest model based fine scale spatiotemporal O-3 trends in the Beijing-Tianjin-Hebei region in China, 2010 to 2017".ENVIRONMENTAL POLLUTION 276(2021):9.