Relatively weak meteorological feedback effect on PM

Aerosol-induced modification Machine learning Meteorological feedback PM(2.5) reduction

Journal

The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500

Informations de publication

Date de publication:
10 May 2019
Historique:
received: 06 12 2018
revised: 17 01 2019
accepted: 17 01 2019
pubmed: 12 2 2019
medline: 12 2 2019
entrez: 12 2 2019
Statut: ppublish

Résumé

Heavy aerosol pollution episodes (HPEs) in Beijing are worsened by the two-way feedback mechanism between unfavorable meteorological conditions and cumulative aerosols. In Winter 2017/18, mean PM

Identifiants

DOI: 10.1016/j.scitotenv.2019.01.420 PMID: 30739849
pubmed: 30739849
pii: S0048-9697(19)30241-4
doi: 10.1016/j.scitotenv.2019.01.420
pii:
doi:

Types de publication

Journal Article

Langues

eng

Pagination

140-147

Informations de copyright

Copyright © 2019 Elsevier B.V. All rights reserved.

Auteurs

Junting Zhong (J)

State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China; University of Chinese Academy of Sciences, Beijing 100049, China.

Xiaoye Zhang (X)

State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China; Center for Excellence in Regional Atmospheric Environment, IUE, Chinese Academy of Sciences, Xiamen, 361021, China.. Electronic address: xiaoye@cma.gov.cn.

Yaqiang Wang (Y)

State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China.

Classifications MeSH