Estimating the Contribution of Traction Sanding to Observed PM10 Concentrations Using Mass Balance Arguments

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Authors: Bruce Rolstad Denby, Elin Ristorp Aas, Michael Norman
Cited by: 0
References: 8

Abstract

Abstract PM 10 concentrations in many countries in Europe are above or close to the limit values set out by the European commission for 2030. This includes both the daily mean and annual mean limit values of 45 µg/m 3 and 20 µg/m 3 respectively. In the European Ambient Air Quality Directives (AAQD) from 2008 and the new AAQD for 2030 the possibility exists to discount an exceedance of a daily mean PM 10 concentration if this is caused by the contribution from traction sanding or road salting. To implement this article in the AAQD, some methodology must be applied to determine the contribution of traction sanding to the PM 10 concentrations. The current recommended method is very simple and does not account for the amount of sand applied, the studded tyre share or the traffic volume. This paper outlines the use of mass balance modelling, in combination with observed PM 10 and PM 2.5 concentrations, to determine the contribution of traction sanding to PM 10 non-exhaust emissions. A two-tiered approach is provided. The first tier assumes that all wear sources are deposited onto the road surface, allowing both traction sand and wear particles to undergo the same removal processes, conserving their relative contributions to the emitted PM. The second tier improves this method by including additional information concerning direct emissions and the surface wetness. The two methods are shown to closely follow the more complex NORTRIP road dust emission model and the methods may be applied to deduce traction sanding contributions to PM 10 concentrations with simple spreadsheet calculations. This will enable the eventual negation of exceedances caused by the traction sanding contribution.

Fields of Study & Subjects

Atmospheric chemistry and aerosols Vehicle emissions and performance Air Quality and Health Impacts

Publication details

Journal / source
Environmental Modeling & Assessment
Publication date
14 August 2026
Language
EN