An integrated strategy by using long-term monitoring data to identify volatile organic compounds of high concern near petrochemical industrial parks

Chin Yu Hsu, Pei Yu Wu, Yu Cheng Chen, Pau Chung Chen, Yue Leon Guo, Yi Jun Lin*, Pinpin Lin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Exposure to ambient volatile organic compounds (VOCs) is associated with a risk of cancer in the residents living near petrochemical facilities. However, research on the contribution of different VOCs to the lifetime cancer risk remains inconclusive. The variability in source emissions, geographical locations, seasons, and meteorological conditions can be assessed through long-term measurement of ambient VOCs with a wide spatial distribution, thus reducing the uncertainty of health risk assessment from source emissions. This study analyzed comprehensive measurement data of 109 VOCs at 17 monitoring stations around petrochemical industrial parks, collected once every six days during 2015–2018 by the Taiwan Environmental Protection Agency. We calculated the annual mean concentration of selected VOCs and then integrated the probability risk assessment (PRA) and positive matrix factorization (PMF) models to identify the sources of VOCs of high concern. First, we prioritized 12 out of 23 carcinogenic VOCs based on the PRA results. Further, the results obtained from the PMF model revealed that petrochemical industrial parks contributed to more than 50% of the emissions of six VOCs, namely 1,3-butadiene, benzene, 1,2-dichloroethane, chloroform, vinyl chloride, and acrylonitrile, measured at a few monitoring stations. This integrated approach can help regulatory agencies to efficiently propose control strategies on the emissions of VOCs of high concern, thereby reducing the population's health risk.

Original languageEnglish
Article number153345
JournalScience of the Total Environment
Volume821
DOIs
StatePublished - 15 May 2022

Keywords

  • Petrochemical industrial parks
  • Positive matrix factorization
  • Probability risk assessment
  • Volatile organic compounds

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