Road dust load dynamics and influencing factors for six winter seasons in Stockholm, Sweden

2019 
Abstract Traffic related non-exhaust particulate sources and road dust are an increasingly important source for PM 10 air pollution as exhaust sources are decreasing due to regulations. In the Nordic countries, the road dust problem is enhanced by use of studded tyres, causing increased road wear and winter road maintenance including gritting. Efforts to reduce road dust emissions requires knowledge on temporal and spatial road dust load dynamics. The city of Stockholm, Sweden, has therefore financed seasonal (October to May) road dust sampling to be able to optimize their winter and spring time street operation measures for reduced road dust emissions. This work describes the outcome of six seasons (2011/2012–2016/2017) of road dust sampling in five central streets using the VTI wet dust sampler (WDS).The results show that road dust load, expressed as DL180 (dust load smaller than 180 μm) has a seasonal variation with the highest loads (up to 200 g/m 2 ) in late winter and early spring and a minimum (down to about 15 g/m 2 ) in early autumn and late spring. The dust load varies between streets and is depending on pavement surface properties. On a smaller scale the dust load has a high variability across streets due to differences in rates of suspension from different parts of the road surface, with low amounts in wheel tracks and higher in-between and outside the tracks. Between 2 and 30% of the DL180 is smaller than 10 μm and could directly contribute to PM 10 emissions. In general, higher road surface texture leads to higher dust loads, but the condition of the pavement (e.g. cracks, aggregate loss) might also have an effect. A new, wear resistant pavement accumulated markedly higher road dust amounts than a several years old pavement. This paper closes with a discussion on the complex relation between road dust load and PM 10 concentrations and a discussion on the challenges and comparability of road dust sampling techniques and measures.
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