Source identification of exhaust and non-exhaust traffic emissions through the elemental carbon fractions and Positive Matrix Factorization method

Abstract

Our study implies the importance of exhaust and non-exhaust emissions in a highway road tunnel, which is crucial to assess their impacts on air quality, human health, climate and developing functional methods for controlling. The total suspended particulates (TSP) and road dust (RD) samples were collected by PUF samplers and manually sweeping, respectively. Campaigns were performed in the summer and winter of 2014 in a highway road tunnel in Bolu, Turkey. Chemical analyses were presented to characterize the contents of organic carbon (OC) fractions (OC1,2,3,4), elemental carbon (EC) fractions (EC1,2,3,4,5,6), polycyclic aromatic hydrocarbons (PAHs) and metals (Al, Ba, Ca, Cu, Mg, Mn, Pb, Sr, Cr and Fe) in the collected TSP and RD samples. Positive matrix factorization (PMF) and orthogonal (Deming) regression analysis were applied to find out the exhaust and non-exhaust vehicle emissions of metal and carbonaceous species in the tunnel. The results showed that the identified source profiles included resuspended road dust (43%), non-exhaust emissions (37%), diesel exhaust emissions (13%), and gasoline exhaust emissions (7%). The relationship between emission markers of metal species and EC carbon fractions was supported by correlation studies. Among these EC fractions, EC4 and EC2 were the most abundant fractions in aerosol and RD samples, respectively and so they highly represented the diesel and non-exhaust emissions. Besides, the EC1 fraction was the indicator of gasoline-fueled emissions. Lower EC1 and higher soot-EC contribution obtained in tunnel aerosol (AS) samples showed the dominance of diesel-fueled vehicles in the tunnel. The data represented herein would help to identify the characteristic of vehicle emissions.