Air Quality Modelling on the Contribution of Brake Wear Emissions to Particulate Matter Concentrations Using a High-Resolution Brake Use Inventory

EB2020-EBS-006
Oral
DOI:

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Abstract

Issue

Exposure to Fine Particulate Matter (PM) has been closely associated with adverse health effects. There is a close, quantitative relationship between exposure to high concentrations of PM and increased mortality or morbidity.

A major source of PM in urban areas is emissions from road traffic, particularly near roadsides. Exhaust emissions of PM from road vehicles have been declining in recent years due to the successful introduction of various abatement technologies. As the importance of exhaust emissions has declined, emissions of PM from non-exhaust sources have become relatively more prominent. Emissions from these non-exhaust sources are not currently controlled.

Brake wear is a significant non-exhaust emissions source and there remain large uncertainties for the contribution of brake wear to ambient PM concentrations. Uncertainties could be reduced by better understanding where brakes are used, and consequently, better apportioning emissions spatially. This is important, as the location and potential for human exposure will vary considerably depending on where the emissions are released.

Innovative Approach

Ricardo Energy & Environment and the FAT have developed an innovative approach to estimate brake use on a highly resolved spatial and temporal basis (https://www.vda.de/de/services/Publikationen/fat-schriftenreihe-318.html). Real vehicle measurements data (over 150,000 km driven) was analysed to estimate the energy dissipated to the brakes each second. By combining this with contemporary estimates of brake wear emission rates, brake wear emissions were distributed according to these energy dissipated estimates.

The spatially resolved brake wear emissions results were applied to Ricardo’s RapidAir air quality model to see how this affects ambient PM concentrations at a high spatial resolution. Comparisons with standard modelling assumptions (constant emission rates along road links) were made to see the effect of using the new approach.

Results

The results show that the contribution of brake wear to ambient PM10 concentrations is more spatially variable using the new approach, compared to standard modelling assumptions. This has been modelled for the Leicester, England urban domain. The results also show that there are larger brake wear contributions to ambient PM using the new approach compared to standard modelling assumptions.

These results could inform the siting of PM measurement stations to further reduce uncertainties. New measurements of brake wear emissions, which are ongoing, would reduce uncertainties too.

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