Positive matrix factorization used to identify PM2.5 and PM10 sources in southern Brazilian cities

Abstract

Particulate matter (PM) is one of the main air pollutants found suspended in the atmosphere, and is composed of a mixture of chemical elements of natural and anthropogenic origin. Therefore, the objective of this study was to use the Positive Matrix Factorization (PMF) receptor model to identify the sources of PM_2.5 and PM₁₀ concentrations, the data for which were collected and chemically quantified through secondary studies. The Enrichment Factor (EF) was calculated to analyze the degree of anthropogenic influence on the chemical enrichment of the particles. The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) was used to identify the atmospheric transport of particles based on the trajectory of air masses. Emissions were identified as having primarily vehicular, industrial, and natural origins. The results confirm the chemical enrichment in the analyzed PM concentrations and indicate a strong relationship between the fine and coarse fractions. The identification of sources indicated that the presence of the metallic variables Ba, Cd, Cu, Pb, Cr, Ni and Zi in the PM are of anthropic origin, and present strong enrichment, while that of Fe and Mn are of natural origin, with a low degree of enrichment. The relevance of this research lies in its ability to provide precise technical support for air quality management. By identifying and quantifying human influence on atmospheric chemistry, the study offers fundamental data for the formulation of public policies to control emissions and mitigate risks to the respiratory health of the population.