Estimating the daily PM<sub>2.5</sub> concentration in the Beijing-Tianjin-Hebei region using a random forest model with a 0.01°â¯×â¯0.01° spatial resolution.

Zhao, Chen; Wang, Qing; Ban, Jie; Liu, Zhaorong; Zhang, Yayi; Ma, Runmei; Li, Shenshen; Li, Tiantian

Estimating the daily PM_2.5 concentration in the Beijing-Tianjin-Hebei region using a random forest model with a 0.01°â¯×â¯0.01° spatial resolution.

Zhao, Chen; Wang, Qing; Ban, Jie; Liu, Zhaorong; Zhang, Yayi; Ma, Runmei; Li, Shenshen; Li, Tiantian.

Afiliação

Zhao C; National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China.
Wang Q; National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China.
Ban J; National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China.
Liu Z; College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China. Electronic address: zrliu@pku.edu.cn.
Zhang Y; National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China.
Ma R; National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China.
Li S; State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China.
Li T; National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China. Electronic address: litiantian@nieh.chinacdc.cn.

Environ Int ; 134: 105297, 2020 01.

Article em En | MEDLINE | ID: mdl-31785527

Assuntos

Poluentes Atmosféricos/análise; Poluição do Ar/análise; Monitoramento Ambiental; Material Particulado/análise; Pequim; Análise Espaço-Temporal

Palavras-chave

High spatiotemporal resolution; Human exposure; Machine learning; PM(2.5) estimation

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Monitoramento Ambiental / Poluentes Atmosféricos / Poluição do Ar / Material Particulado Tipo de estudo: Clinical_trials / Prognostic_studies País/Região como assunto: Asia Idioma: En Revista: Environ Int Ano de publicação: 2020 Tipo de documento: Article País de afiliação: China

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