Fine Particle Receptor Modeling in the Atmosphere of Mexico City

Abstract Source apportionment analyses were carried out by means of receptor modeling techniques to determine the contribution of major fine particulate matter (PM2.5) sources found at six sites in Mexico City. Thirty-six source profiles were determined within Mexico City to establish the fingerprints of particulate matter sources. Additionally, the profiles under the same source category were averaged using cluster analysis and the fingerprints of 10 sources were included. Before application of the chemical mass balance (CMB), several tests were carried out to determine the best combination of source profiles and species used for the fitting. CMB results showed significant spatial variations in source contributions among the six sites that are influenced by local soil types and land use. On average, 24-hr PM2.5 concentrations were dominated by mobile source emissions (45%), followed by secondary inorganic aerosols (16%) and geological material (17%). Industrial emissions representing oil combustion and incineration contributed less than 5%, and their contribution was higher at the industrial areas of Tlalnepantla (11%) and Xalostoc (8%). Other sources such as cooking, biomass burning, and oil fuel combustion were identified at lower levels. A second receptor model (principal component analysis, [PCA]) was subsequently applied to three of the monitoring sites for comparison purposes. Although differences were obtained between source contributions, results evidence the advantages of the combined use of different receptor modeling techniques for source apportionment, given the complementary nature of their results. Further research is needed in this direction to reach a better agreement between the estimated source contributions to the particulate matter mass.