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High spatial resolution land-use regression model for urban ultrafine particle exposure assessment in Shanghai, China.
Ge, Yihui; Fu, Qingyan; Yi, Min; Chao, Yuan; Lei, Xiaoning; Xu, Xueyi; Yang, Zhenchun; Hu, Jianlin; Kan, Haidong; Cai, Jing.
Afiliación
  • Ge Y; School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China.
  • Fu Q; Shanghai Environmental Monitoring Center, Shanghai 200233, China.
  • Yi M; Shanghai Environmental Monitoring Center, Shanghai 200233, China.
  • Chao Y; Shanghai Environmental Monitoring Center, Shanghai 200233, China.
  • Lei X; School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China.
  • Xu X; School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China.
  • Yang Z; MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, London, United Kingdom.
  • Hu J; Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing 210044, China.
  • Kan H; School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China. Electronic address: kanh@fudan.edu.cn.
  • Cai J; School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China. Electronic address: jingcai@fudan.edu.cn.
Sci Total Environ ; 816: 151633, 2022 Apr 10.
Article en En | MEDLINE | ID: mdl-34785221
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Contaminantes Atmosféricos / Contaminación del Aire Tipo de estudio: Prognostic_studies País/Región como asunto: Asia Idioma: En Revista: Sci Total Environ Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Países Bajos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Contaminantes Atmosféricos / Contaminación del Aire Tipo de estudio: Prognostic_studies País/Región como asunto: Asia Idioma: En Revista: Sci Total Environ Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Países Bajos