Exhaust and non-exhaust contributions from road transport to PM10 at a Southern European traffic site

Abstract

It is a well - established fact that road traffic is one of the main contributors to ambient levels of airborne particulate matter (APM). This study was carried out at a traffic site in which the PM₁₀ levels are monitored all year round. A trend analysis of these levels revealed that over a decade there was no discernible trend, with the PM₁₀ concentrations normally hovering around the EU limit values. In 2018, one of these limit values was exceeded. The contribution of traffic at the site was therefore investigated through a chemical speciation of 209 PM₁₀ samples collected throughout this year. The speciation data were used in a source apportionment exercise in which the output of the PMF model was further refined using the lesser-known, constraint weighted non - negative matrix factorization (CW - NMF) model. This technique enabled the isolation of two factors clearly related to traffic, which were labelled as "exhaust contribution" (responsible for 3.4% of the PM₁₀), "tire/brake wear contribution" (contributing 17% of the PM₁₀). Additionally, a factor including both traffic resuspended dust and crustal material was also isolated and labelled "road dust/crustal" factor. The two contributors to the factor jointly contribute 18% to the PM₁₀ and the contribution of the traffic resuspended dust was estimated at 7.3%. The traffic resuspended component of this factor together with the "tire/brake wear contribution" jointly make up the non-exhaust contribution of traffic - derived dust. Consonant with what has been known for quite some time, the exhaust fraction is the minor component of traffic PM₁₀. It is therefore, clear that policies aimed at controlling traffic derived PM₁₀ pollution at the receptor will have a minimal effect unless the non - exhaust emissions are adequately controlled.

Keywords: Constraint weighted non; Exhaust contribution; Negative matrix factorization; Non-exhaust contribution; PM(10); Positive matrix factorization; Road dust; Source apportionment; Traffic aerosol.