Yingze Tian 1, Qianqian Xue1, Zhimei Xiao2, Kui Chen2, Yinchang Feng 1


The State Environmental Protection Key Laboratory of Urban Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
Tianjin Environment Monitoring Center, Tianjin 300071, China



Received: July 25, 2018
Revised: October 20, 2018
Accepted: October 24, 2018
Download Citation: ||https://doi.org/10.4209/aaqr.2018.07.0244  


Cite this article:
Tian, Y., Xue, Q., Xiao, Z., Chen, K. and Feng, Y. (2018). PMF-GAS Methods to Estimate Contributions of Sources and Oxygen for PM2.5, Based on Highly Time-Resolved PM2.5 Species and Gas Data. Aerosol Air Qual. Res. 18: 2956-2966. https://doi.org/10.4209/aaqr.2018.07.0244


HIGHLIGHTS

  • Three methods were developed for detail insights into PM2.5 sources.
  • Method1 enhances distinction and model primary and secondary contributions.
  • Method2 uses sum of species and precursors to estimate the total influence.
  • Method3 uses relations to quantify influence of oxidant reactions.
  • Crustal dust provided cations for ammonium salts formation.

ABSTRACT


To gain detailed insight into the gaseous sources of PM2.5, three kinds of positive matrix factorization were developed and applied to hourly elemental and gaseous data (PMF-GAS). According to the results of PMF-GAS1, which relied on gaseous markers to enhance source discrimination, crustal dust, vehicular exhaust, coal combustion, sulfate and nitrate (CD1VE1CC1SUL1 and NIT1) directly contributed 20%, 17%, 15%, 34% and 14% to the PM2.5, respectively. Using PMF-GAS2, which summed species found in PM2.5, and their corresponding precursors to estimate the overall influence of primary sources, the total contribution from CD2VE2 and CC2 to PM2.5 was quantified as 30%, 29% and 41%, respectively. Finally, PMF-GAS3 quantified the contribution of oxidation (OXI3; 27%) based on the relationships between the species and their precursors. NH4+ was found mostly in CD2 and CD3 but also in SUL1 and NIT1, implying that crustal dust can provide alkaline conditions for the formation of ammonium salts. High correlations were found between corresponding source contributions, but CD1 showed relatively weak links with CD2 and CD3 due to NH4+ being present in different factors. A fully populated map of classical bootstrap (BS) runs implies the high stability of these PMF-GAS results.


Keywords: PM2.5; Chemical compositions; Gaseous pollutants; Source apportionment; PMF-GAS.

 


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