Reconciling discrepancies in the source characterization of VOCs between emission inventories and receptor modeling

Jiamin Ou, Junyu Zheng, Zibing Yuan, Dabo Guan, Zhijiong Huang, Fei Yu, Min Shao, Peter K. K. Louie

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)
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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.
Original languageEnglish
Pages (from-to)697-706
Number of pages10
JournalScience of the Total Environment
Volume628-629
Early online date20 Feb 2018
DOIs
Publication statusPublished - 1 Jul 2018

Keywords

  • Source characterization
  • VOCs
  • Emission inventory
  • Receptor models
  • Discrepancy

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