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Predicting latent source-specific PM2.5 pollution from regional sources at unmonitored sites by Bayesian spatial multivariate receptor modeling.
Lee, Young Su; Kim, Jae Young; Yi, Seung-Muk; Kim, Ho; Park, Eun Sug.
Afiliación
  • Lee YS; Department of Civil and Environmental Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, Republic of Korea.
  • Kim JY; Department of Civil and Environmental Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, Republic of Korea.
  • Yi SM; Department of Environmental Health Sciences, Graduate School of Public Health, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, Republic of Korea.
  • Kim H; Department of Public Health Sciences, Graduate School of Public Health, & Institute of Sustainable Development, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, Republic of Korea.
  • Park ES; Texas A&M Transportation Institute, 3135 TAMU, College Station, TX 77843-3135, USA. Electronic address: e-park@tti.tamu.edu.
Environ Pollut ; 324: 121389, 2023 May 01.
Article en En | MEDLINE | ID: mdl-36870595
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Contaminantes Atmosféricos / Contaminación del Aire Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Environ Pollut Asunto de la revista: SAUDE AMBIENTAL Año: 2023 Tipo del documento: Article
Texto completo
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Contaminantes Atmosféricos / Contaminación del Aire Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Environ Pollut Asunto de la revista: SAUDE AMBIENTAL Año: 2023 Tipo del documento: Article