[Improved Performance of PMF Source Apportionment for Volatile Organic Compounds Based on Classification of VOCs' Aging Degree in Air Mass]

Huan Jing Ke Xue. 2022 Feb 8;43(2):707-713. doi: 10.13227/j.hjkx.202104105.
[Article in Chinese]

Abstract

VOCs are the key precursors of ozone and secondary organic aerosols. The results of source apportionment for VOCs are very important for the coordinated control of ozone and second organic particulate matter. However, VOCs do not fully meet the assumption of the receptor model because the VOCs released from each source are relatively unstable in the transmission process for their reactivity. As a result, we do not accurately obtain the actual source contribution when the receptor model is used for the source apportionment of VOCs. In order to solve the problem that the relative changes in the components caused by VOCs reactivity are not consistent with the PMF model hypothesis, the aging degree of VOCs was introduced to distinguish the state characteristics after their photochemical reactions in the ambient air. According to the ratio of ethylbenzene to m/p-xylene, VOCs monitored at Wuhai were divided into three aging states:high, medium, and low. The results showed that the model parameters, such as regression equation parameters (slope and intercept), standard error, determination coefficient, and pass rate of residual error, were improved obviously compared to the sample set after classification. Because the degree of aging is closely related to the transport time of air mass and the atmospheric oxidation in the atmosphere, it also reflects the different sources of air mass to some extent. In the high-aging VOCs samples, the coking source occupied a high proportion (up to 47.20%). In the low-aging VOCs samples, the combustion source and coking source accounted for a higher proportion, 28.67% and 24.39%, respectively. After the classification according to the aging degree, the results of VOCs source apportionment by PMF are more consistent with the actual contribution of emission sources.

Keywords: aging characteristics; positive matrix factorization(PMF); receptor model; source apportionment; volatile organic compounds(VOCs).

MeSH terms

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

Substances

  • Air Pollutants
  • Vehicle Emissions
  • Volatile Organic Compounds