Improved positive matrix factorization for source apportionment of volatile organic compounds in vehicular emissions during the Spring Festival in Tianjin, China

Abstract

Photochemical losses of volatile organic compounds (VOCs) and uncertainties in calculated factor profiles can reduce the accuracy of source apportionment by positive matrix factorization (PMF). We developed an improved PMF method (termed ICLP-PMF) that estimated the reaction-corrected (“initial”) concentrations of VOCs. Source profiles from literature provided constraints. ICLP-PMF evaluated the vehicular emission contributions to hourly speciated VOC data from December 2020 to March 2021 and estimated gasoline and diesel vehicles contributions to Tianjin's VOC concentrations around the Chinese Spring Festival (SF). The average observed and initial total VOCs (TVOCs) concentrations were 24.2 and 42.9 ppbv, respectively. Alkanes were the highest concentration VOCs while aromatics showed the largest photochemical losses during the study period. Literature gasoline and diesel profiles from representative Chinese cities were constructed and provided constraints. Source apportionment was performed using ICLP-PMF method and three other PMF approaches. Photochemical losses of alkenes and aromatic hydrocarbons induced differences between calculated factor profiles and literature profiles. Using observed concentrations and unconstrained profiles produced underestimated SF contributions (∼121% and 72% for gasoline and diesel vehicles, respectively). According to the ICLP-PMF results, the contributions of gasoline and diesel vehicles during the SF were 25.6% and 23.2%, respectively, lower than those before and after the SF. No diel diesel vehicle contribution variations were found during the SF likely due to the decline in truck activity north of the study site during the holiday period.