Source apportionment of traffic emissions of particulate matter using tunnel measurements

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, respec...

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Bibliographic Details
Published in:	Atmospheric environment (1994) Vol. 77; pp. 548 - 557
Main Authors:	Lawrence, Samantha, Sokhi, Ranjeet, Ravindra, Khaiwal, Mao, Hongjun, Prain, Hunter Douglas, Bull, Ian D.
Format:	Journal Article
Language:	English
Published:	Kidlington Elsevier Ltd 01-10-2013 Elsevier
Subjects:	Applied sciences Atmospheric pollution Exact sciences and technology Metals Non-exhaust Pollution Pollution sources. Measurement results Polycyclic aromatic hydrocarbons Principal component analysis and multiple linear regression analysis Traffic emissions Transports England United Kingdom Great Britain Europe Polycyclic aromatic hydrocarbons Traffic emissions Metals Principal component analysis and multiple linear regression analysis Non-exhaust Non-exhaut Atomic emission spectrometry Identification Motor vehicle Mutagen Inductive coupling plasma spectrometry Coarse particle Persistent organic pollutant Road tunnel Emission measure Organic compounds Hydrocarbon Polycyclic aromatic compound Heavy metal Trace element Carcinogen Gas chromatography Aerosols Pollution source inventory Air pollution Road traffic Mass spectrometry
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Summary:	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. •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.
ISSN:	1352-2310 1873-2844
DOI:	10.1016/j.atmosenv.2013.03.040