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Source apportionment of traffic emissions of particulate matter using tunnel measurements
Abstract This study aims to quantify exhaust/non-exhaust emissions and the uncertainties associated with them by combining innovative motorway tunnel sampling and source apportionment modelling. Analytical techniques ICP-AES and GC–MS were used to identify the metallic and organic composition of PM10, respectively. Good correlation was observed between Fe, Cu, Mn, Ni, Pb and Sb and change in traffic volume. The concentration of polycyclic aromatic hydrocarbons and other organics varies significantly at the entrance and exit site of the tunnel, with fluoranthene, pyrene, benzo[a]pyrene, chrysene and benzothiazole having the highest incremented concentrations. The application of Principal Component Analysis and Multiple Linear Regression Analysis helped to identify the emission sources for 82% of the total PM10 mass inside the tunnel. Identified sources include resuspension (27%), diesel exhaust emissions (21%), petrol exhaust emissions (12%), brake wear emissions (11%) and road surface wear (11%). This study shows that major health related chemical species of PM10 originate from non-exhaust sources, further signifying the need for legislation to reduce these emissions.
Highlights Identifies major sources of traffic emissions by using a real world motorway tunnel. Major non-exhaust sources include resuspension, brake wear and road surface wear. Several toxic metals (e.g. Fe, Cu, Mn, Ni, Pb, Sb) and PAHs show high incremented levels. Diesel (21%) & petrol (12%) exhaust emissions also contribute as major sources of PM10. A number of toxic chemical species of PM10 originate from non-exhaust sources.
Source apportionment of traffic emissions of particulate matter using tunnel measurements
Abstract This study aims to quantify exhaust/non-exhaust emissions and the uncertainties associated with them by combining innovative motorway tunnel sampling and source apportionment modelling. Analytical techniques ICP-AES and GC–MS were used to identify the metallic and organic composition of PM10, respectively. Good correlation was observed between Fe, Cu, Mn, Ni, Pb and Sb and change in traffic volume. The concentration of polycyclic aromatic hydrocarbons and other organics varies significantly at the entrance and exit site of the tunnel, with fluoranthene, pyrene, benzo[a]pyrene, chrysene and benzothiazole having the highest incremented concentrations. The application of Principal Component Analysis and Multiple Linear Regression Analysis helped to identify the emission sources for 82% of the total PM10 mass inside the tunnel. Identified sources include resuspension (27%), diesel exhaust emissions (21%), petrol exhaust emissions (12%), brake wear emissions (11%) and road surface wear (11%). This study shows that major health related chemical species of PM10 originate from non-exhaust sources, further signifying the need for legislation to reduce these emissions.
Highlights Identifies major sources of traffic emissions by using a real world motorway tunnel. Major non-exhaust sources include resuspension, brake wear and road surface wear. Several toxic metals (e.g. Fe, Cu, Mn, Ni, Pb, Sb) and PAHs show high incremented levels. Diesel (21%) & petrol (12%) exhaust emissions also contribute as major sources of PM10. A number of toxic chemical species of PM10 originate from non-exhaust sources.
Source apportionment of traffic emissions of particulate matter using tunnel measurements
Lawrence, Samantha (Autor:in) / Sokhi, Ranjeet (Autor:in) / Ravindra, Khaiwal (Autor:in) / Mao, Hongjun (Autor:in) / Prain, Hunter Douglas (Autor:in) / Bull, Ian D. (Autor:in)
Atmospheric Environment ; 77 ; 548-557
20.03.2013
10 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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