Improving estimates of non-exhaust particulate matter emissions from motor vehicles

S. Xie; Davy, R.
February 2014
Air Quality & Climate Change;Feb2014, Vol. 48 Issue 1, p11
Academic Journal
Effectively reducing particulate matter (PM) emissions from motor vehicles requires accurate estimates of both exhaust (tailpipe) and non-exhaust (suspended road dust and brake/tyre/body wear) emissions. It is particularly challenging to quantify non-exhaust emissions. Source apportionment studies can be used to provide robust information about motor vehicle source chemical profiles and their contribution to ambient PM concentrations. This paper presents the results of the tracer component method (TCM), which has been used to separate exhaust and non-exhaust emissions from the entire source profile for motor vehicles in Auckland by using chemical markers. TCM was applied to ambient PM data collected in Auckland by taking the concentration of black carbon as the lower limit of the exhaust component and the concentration of crustal elements as the lower limit of the non-exhaust component. For PM2.5, the non-exhaust components and the ratios of non-exhaust to total vehicle components (NT ratio) were higher at Queen Street and Khyber Pass (busy traffic sites in the city centre) than at Takapuna and Penrose (outside the city centre). For PM10, the non-exhaust components were also higher at Queen Street and Khyber Pass but the NT ratios were similar across all sites. TCM estimated that the NT ratios were approximately 18.6% and 30.2% for PM2.5 and PM10, respectively, which was higher than those in the Auckland vehicle emissions inventory which consisted of exhaust emissions and brake/tyre wear only. In literature, studies have not been found to separate exhaust from non-exhaust components of the entire source profile of motor vehicles. TCM provides useful information about the ratio of non-exhaust to exhaust emissions, which can be used for improving the non-exhaust emission estimates in the Auckland vehicle emissions inventory.


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