Contribution of polycyclic aromatic hydrocarbon (PAH) sources to the urban environment: A comparison of receptor models

Sci Total Environ. 2015 Dec 15:538:212-9. doi: 10.1016/j.scitotenv.2015.07.072. Epub 2015 Aug 22.

Abstract

The aim of this study was to evaluate the contribution of the main emission sources of PAHs associated with PM2.5, in an urban area of the Rio Grande do Sul state. Source apportionment was conducted using both the US EPA Positive Matrix Factorization (PMF) model and the Chemical Mass Balance (CMB) model. The two models were compared to analyze the source contributions similarities and differences, their advantages and disadvantages. PM2.5 samples were collected continuously over 24h using a stacked filter unit at 3 sampling sites of the urban area of the Rio Grande do Sul state every 15days between 2006 and 2008. Both models identified the main emission sources of PAHs in PM2.5: vehicle fleet (diesel and gasoline), coal combustion, wood burning, and dust. Results indicated similar source contribution amongst the sampling sites, as expected because of the proximity amongst the sampling sites, which are under the influence of the same pollutants emitting sources. Moreover, differences were observed in obtained sources contributions for the same data set of each sampling site. The PMF model attributed a slightly greater amount of PAHs to the gasoline and diesel sources, while diesel contributed more in the CMB results. The results were comparable with previous works of the region and in accordance with the characteristics of the study area. Comparison between these receptor models, which contain different physical constraints, is important for understanding better PAH emissions sources in order to reduce air pollution.

Keywords: CMB model; Emission sources; PMF 3.0 model; Polycyclic aromatic hydrocarbons; Receptor model; Source apportionment.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Air Pollutants / analysis*
  • Air Pollution
  • Cities / statistics & numerical data
  • Environmental Monitoring*
  • Models, Chemical*
  • Polycyclic Aromatic Hydrocarbons / analysis*

Substances

  • Air Pollutants
  • Polycyclic Aromatic Hydrocarbons