Improving PM2.5 Forecasts in China Using an Initial Error Transport Model

doi:10.1021/acs.est.0c01680

	Improving PM2.5 Forecasts in China Using an Initial Error Transport Model
	Huangjian Wu,7,8; Xiaogu Zheng 1; Jiang Zhu,1,2; Wei Lin 8,9; Haitao Zheng,3; Xueshun Chen 4,5; Wei Wang6 ; Zifa Wang 2,4,5; Song Xi Chen 7,8
	2020
发表期刊	ENVIRONMENTAL SCIENCE & TECHNOLOGY
ISSN	0013-936X
通讯作者	Wu, Huangjian(wuhuangjian@pku.edu.cn) ; Lin, Wei(weilin@math.pku.edu.cn)
摘要	Efforts of using data assimilation to improve PM2.5 forecasts have been hindered by the limited number of species and incomplete vertical coverage in the observations. The common practice of initializing a chemical transport model (CTM) with assimilated initial conditions (ICs) may lead to model imbalances, which could confine the impacts of assimilated ICs within a day. To address this challenge, we introduce an initial error transport model (IETM) approach to improving PM2.5 forecasts. The model describes the transport of initial errors by advection, diffusion, and decay processes and calculates the impacts of assimilated ICs separately from the CTM. The CTM forecasts with unassimilated ICs are then corrected by the IETM output. We implement our method to improve PM2.5 forecasts over central and eastern China. The reduced root-mean-square errors for 1-, 2-, 3-, and 4-day forecasts during January 2018 were 51.2, 27.0, 16.4, and 9.4 mu g m(-3), respectively, which are 3.2, 6.9, 8.6, and 10.4 times those by the CTM forecasts with assimilated ICs. More pronounced improvements are found for highly reactive PM2.5 components. These and similar results for July 2017 suggest that our method can enhance and extend the impacts of the assimilated data without being affected by the imbalance issue.
DOI	10.1021/acs.est.0c01680
关键词[WOS]	VARIATIONAL DATA ASSIMILATION ; INTERCONTINENTAL TRANSPORT ; CHEMISTRY ; AEROSOLS ; POLLUTION ; BALANCE ; SYSTEM ; IMPACT ; URBAN ; MASS
收录类别	SCI
语种	英语
资助项目	National Key R&D Program of China[2016YFC0207703] ; National Key R&D Program of China[2016YFC0207701] ; National Key R&D Program of China[2018YFC0213106] ; National Key R&D Program of China[2018YFC0213100] ; National Natural Science Foundation of China[11671018] ; National Natural Science Foundation of China[71532001] ; National Natural Science Foundation of China[91644216] ; National Natural Science Foundation of China[41705108] ; Beijing Natural Science Foundation[Z190001] ; Beijing Academy of Artificial Intelligence
项目资助者	National Key R&D Program of China ; National Natural Science Foundation of China ; Beijing Natural Science Foundation ; Beijing Academy of Artificial Intelligence
WOS研究方向	Engineering ; Environmental Sciences & Ecology
WOS类目	Engineering, Environmental ; Environmental Sciences
WOS记录号	WOS:000568649900010
出版者	AMER CHEMICAL SOC
引用统计	被引频次：3[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.hfcas.ac.cn:8080/handle/334002/92815
专题	中科院安徽光学精密机械研究所
作者单位	1.Chinese Acad Sci, CAS TWAS Ctr Excellence Climate & Environm Sci, Inst Atmospher Phys, Beijing 100029, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Key Lab Environm Opt & Technol, Anhui Inst Opt & Fine Mech, Hefei 230031, Anhui, Peoples R China 4.Chinese Acad Sci, State Key Lab Atmospher Boundary Layer Phys & Atm, Inst Atmospher Phys, Beijing 100029, Peoples R China 5.Chinese Acad Sci, Ctr Excellence Reg Atmospher Environm, Inst Urban Environm, Xiamen 361021, Fujian, Peoples R China 6.China Natl Environm Monitoring Ctr, Beijing 100012, Peoples R China 7.Peking Univ, Guanghua Sch Management, Beijing 100871, Peoples R China 8.Peking Univ, Ctr Stat Sci, Beijing 100871, Peoples R China 9.Peking Univ, Sch Math Sci, Beijing 100871, Peoples R China
推荐引用方式 GB/T 7714	Huangjian Wu,,Xiaogu Zheng,Jiang Zhu,,et al. Improving PM2.5 Forecasts in China Using an Initial Error Transport Model[J]. ENVIRONMENTAL SCIENCE & TECHNOLOGY,2020,54.
APA	Huangjian Wu,.,Xiaogu Zheng.,Jiang Zhu,.,Wei Lin.,Haitao Zheng,.,...&Song Xi Chen.(2020).Improving PM2.5 Forecasts in China Using an Initial Error Transport Model.ENVIRONMENTAL SCIENCE & TECHNOLOGY,54.
MLA	Huangjian Wu,,et al."Improving PM2.5 Forecasts in China Using an Initial Error Transport Model".ENVIRONMENTAL SCIENCE & TECHNOLOGY 54(2020).

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