Identifying sources of low-wind/high particulate matter episodes in the imperial valley/Mexicali region

Particulate Matter (PM) emissions directly influence air quality and cause respiratory diseases and lung damage. PM is a major issue in the U.S.-Mexico border region and is produced by many sources including fossil fuels, road dust, agricultural emissions, and wood combustion operations. The U.S.-Mexico border experiences short-term (2-6 hr), high-PM episodes, particularly during the evening in winter months. These episodes are responsible for a significant portion of the daily average PM loadings. Source identification and characterization aims to understand the properties of PM at receptor sites to elucidate the contributions and characteristics from different sources. In this work, statistical models are used to estimate the relative contributions of emissions from sources based on receptor site measurements. This study investigated low-wind/high particulate matter episodes in the Imperial Valley/Mexicali Region using three different source attribution techniques: Principal component Analysis (PCA), Positive Matrix Factorization (PMF) and Principal Component Regression (PCR).Samples were analyzed by using Thermal-Desorption Gas Chromatography/Mass Spectrometry (TD GC/MS). Results showed that cars (using gasoline and diesel fuels), biomass, waste and wood burning were significant for this region. Comparison of the techniques was also performed.