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Reconciling discrepancies in the source characterization of VOCs between emission inventories and receptor modeling.
Ou, Jiamin; Zheng, Junyu; Yuan, Zibing; Guan, Dabo; Huang, Zhijiong; Yu, Fei; Shao, Min; Louie, Peter K K.
Afiliação
  • Ou J; School of International Development, University of East Anglia, Norwich, NR4 7TJ, UK.
  • Zheng J; Institute for Environment and Climate Research, Jinan University, Guangzhou 510006, P.R. China. Electronic address: zheng.junyu@gmail.com.
  • Yuan Z; School of Environment and Energy, South China University of Technology, Guangzhou 510006, China.
  • Guan D; School of International Development, University of East Anglia, Norwich, NR4 7TJ, UK.
  • Huang Z; Institute for Environment and Climate Research, Jinan University, Guangzhou 510006, P.R. China.
  • Yu F; Institute for Environment and Climate Research, Jinan University, Guangzhou 510006, P.R. China.
  • Shao M; Institute for Environment and Climate Research, Jinan University, Guangzhou 510006, P.R. China.
  • Louie PKK; Hong Kong Environmental Protection Department, Revenue Tower, 5 Gloucester Road, Wanchai, Hong Kong, P.R. China.
Sci Total Environ ; 628-629: 697-706, 2018 Jul 01.
Article em En | MEDLINE | ID: mdl-29454209
ABSTRACT
Emission inventory (EI) and receptor model (RM) are two of the three source apportionment (SA) methods recommended by Ministry of Environment of China and used widely to provide independent views on emission source identifications. How to interpret the mixed results they provide, however, were less studied. In this study, a cross-validation study was conducted in one of China's fast-developing and highly populated city cluster- the Pearl River Delta (PRD) region. By utilizing a highly resolved speciated regional EI and a region-wide gridded volatile organic compounds (VOCs) speciation measurement campaign, we elucidated underlying factors for discrepancies between EI and RM and proposed ways for their interpretations with the aim to achieve a scientifically plausible source identification. Results showed that numbers of species, temporal and spatial resolutions used for comparison, photochemical loss of reactive species, potential missing sources in EI and tracers used in RM were important factors contributed to the discrepancies. Ensuring the consensus of species used in EIs and RMs, utilizing a larger spatial coverage and longer time span, addressing the impacts of photochemical losses, and supplementing emissions from missing sources could help reconcile the discrepancies in VOC source characterizations acquired using both approaches. By leveraging the advantages and circumventing the disadvantages in both methods, the EI and RM could play synergistic roles to obtain robust SAs to improve air quality management practices.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Monitoramento Ambiental / Poluentes Atmosféricos / Poluição do Ar / Compostos Orgânicos Voláteis Tipo de estudo: Prognostic_studies País/Região como assunto: Asia Idioma: En Revista: Sci Total Environ Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Monitoramento Ambiental / Poluentes Atmosféricos / Poluição do Ar / Compostos Orgânicos Voláteis Tipo de estudo: Prognostic_studies País/Região como assunto: Asia Idioma: En Revista: Sci Total Environ Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Reino Unido