Quantifying ambient concentrations of primary and secondary organic aerosol in central Los Angeles using an integrated approach coupling source apportionment with regression analysis. (1st January 2022)

• Record Type: Journal Article
• Authors: Tohidi, Ramin; Altuwayjiri, Abdulmalik; Pirhadi, Milad; Sioutas, Constantinos
• Is Part Of: Atmospheric environment. Volume 268(2022)
• Publication Date: 2022-01-01
• Subjects: Carbonaceous PM Species -- Primary and secondary organic aerosol (POA -- SOA) -- Criteria gaseous pollutants -- Regression analysis -- Positive matrix factorization (PMF); Air -- Pollution -- Periodicals; Air -- Pollution -- Meteorological aspects -- Periodicals; 551.51
• DOI: 10.1016/j.atmosenv.2021.118807
• Languages: English
• ISSNs: 1352-2310

Abstract

Abstract: The main objective of this study was to explore the correlations between carbonaceous PM2.5 species (i.e., primary and secondary organic aerosols (POAs and SOAs) and elemental carbon (EC)) with various criteria gaseous pollutants over the 2015–2019 period in order to devise a simple way of estimating the 24-hr concentration of these PM species in central Los Angeles. The Positive Matrix Factorization (PMF) model was used to determine the contribution of various sources to organic carbon (OC) and its volatility fractions (OC1 -OC3 ) in the atmosphere in years of 2015, 2017, and 2019. A 5-factor solution that includes vehicular exhaust emissions (traced by EC and OC1 ), non-tailpipe emissions (characterized by Ti, Cu, and Zn), SOAs (identified by sulfate and ozone), biomass burning (associated with high loadings of K+/K), and local industrial activities (traced by Cr) was identified as the most physically interpretable solution for each of the investigated years. The SOA concentrations determined using the PMF model output and the POA concentrations, calculated by subtracting the SOA concentrations from the total OC mass, were employed in our regression analysis with criteria gaseous pollutants, the concentrations of which are routinely reported by the air quality agencies. The result of the regression analysis revealed high correlation between the concentrations of SOA and ozone (R 2 > 0.74) in different years, probably because they are originated from synchronized photochemical reactions in the atmosphere. The SOA/O3 ratios were between ∼ 47-56 μg/m 3 /ppm in the time period of 2015–2019. A strong correlation between POA and CO was also observed (R 2 > 0.70); the POA/CO ratios decreased from about 6.5 to 5 μg/m 3 /ppm from 2015 to 2019, which is consistent with the trend of tailpipe emission contributions to total OC concentrations in our monitoring site. EC was also strongly correlated with NO2 (R 2 > 0.73) and CO (R 2 > 0.70) because they are emitted from the same combustion sources (e.g., vehicular emissions in central Los Angeles). Our results show persistent and significant correlations between the concentrations of criteria gaseous pollutants and carbonaceous PM2.5 species (i.e., POA, SOA, and EC) in different years, offering a straightforward approach to estimate the 24-h average concentration of these PM species in central Los Angeles. Highlights: The correlations between carbonaceous PM2.5 and criteria gaseous pollutants were explored. The tailpipe emissions decreased during the study period in central Los Angeles. SOA and O3 were highly correlated as they have the same precursors and formation pathways. The decrease in NO2 levels were faster than EC levels due to California regulations.