Characteristics and sources of volatile organic compounds during high ozone episodes: A case study at a site in the eastern Guanzhong Plain, China

Chemosphere. 2021 Feb:265:129072. doi: 10.1016/j.chemosphere.2020.129072. Epub 2020 Nov 21.

Abstract

This study performed continuous measurements of 105 volatile organic compounds (VOCs) in Weinan in the eastern Guanzhong Plain from 1 July to September 19, 2019. Ozone (O3) episode and non-episode days were identified according to China Ambient Air Quality Standard, and the concentrations of total quantified VOCs (TVOCs) were 33.43 ± 13.64 ppbv and 29.13 ± 14.31 ppbv, respectively. During different O3 pollution episodes, alkanes comprised the highest proportion to TVOC concentrations, while alkenes contributed the most to ozone formation potential (OFP). In addition, O3 episode days were mainly caused by enhanced emissions of precursors and meteorological conditions favorable to O3 production. Based on Empirical Kinetic Modelling Approach (EKMA), the O3 formation in Weinan was found in the transitional regime, in which the synergistic reduction of VOCs and nitrogen oxide (NOx) would be more effective for O3 reduction. Eight sources were identified by positive matrix factorization (PMF) model, with natural gas (NG)/liquefied petroleum gas (LPG) usage as the most significant contributor to VOC concentration, followed by vehicle exhaust, biomass burning, solvent usage, fuel evaporation, rubber/plastic industrial emissions, biogenic source, and mixed industrial emissions. Furthermore, rubber/plastic industrial emissions, solvent usage, fuel evaporation, and vehicle exhaust were the most significant sources to O3 formation. Based on conditional bivariate probability function (CBPF), vehicle exhaust, fuel evaporation, and solvent usage were mainly local emissions, while other sources were mainly affected by regional transport. This study provides useful reference for research on the atmospheric photochemical formation of O3 and evidence for regional O3 reduction strategies.

Keywords: Conditional bivariate probability function (CBPF); EKMA; O(3)-VOC-NOx sensitivity; Ozone; Source apportionment; Volatile organic compounds (VOCs).

MeSH terms

  • Air Pollutants* / analysis
  • China
  • Environmental Monitoring
  • Ozone* / analysis
  • Photochemical Processes
  • Vehicle Emissions / analysis
  • Volatile Organic Compounds* / analysis

Substances

  • Air Pollutants
  • Vehicle Emissions
  • Volatile Organic Compounds
  • Ozone