Development and application of an innovative approach to predicting pollutant concentrations in highway runoff

Revitt, D. Mike, Ellis, John Bryan, Gilbert, Nathalie, Bryden, John and Lundy, Lian ORCID logoORCID: (2022) Development and application of an innovative approach to predicting pollutant concentrations in highway runoff. Science of the Total Environment, 825 , 153815. pp. 1-10. ISSN 0048-9697 [Article] (doi:10.1016/j.scitotenv.2022.153815)

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Recognising the challenges and limitations of current methodologies to predict highway runoff concentrations, this paper presents a novel approach based on the derivation of pollutant emission factors for twelve different types of vehicle. Published emission factor data and properties of differing vehicles types are combined with annual average daily traffic volume (AADT), highway characteristics and rainfall data to determine the pollutant distributions associated with differing highway and traffic types. In this paper, the method is applied to 126 sections of highway in the Greater London Borough of Enfield (United Kingdom; UK) and results are comparable with values reported in the literature. The approach is used to identify the level of AADT predicted to result in an exceedance of environmental quality standards (EQS), with results suggesting that runoff from highways experiencing AADT values as low as 5000 may require treatment prior to discharge to receiving waters. Future scenario analyses indicate that the impact of progressively replacing petrol and diesel vehicles with electric vehicles will have negligible impact on concentrations of zinc (Zn), copper (Cu), cadmium (Cd) and total suspended solids discharging from highway environments. The approach enables identification and ranking of urban highways in terms of their pollution runoff potential and provides an important support to users in prioritising locations for the installation of sustainable drainage options in order to protect receiving water environments. [Abstract copyright: Copyright © 2021. Published by Elsevier B.V.]

Item Type: Article
Keywords (uncontrolled): Local rainfall, Annual average daily traffic, Organic and inorganic pollutants, Scenario analysis, Vehicle emission factors
Research Areas: A. > School of Science and Technology > Natural Sciences
Item ID: 34834
Notes on copyright: Published version: © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (
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Depositing User: Jisc Publications Router
Date Deposited: 07 Mar 2022 10:28
Last Modified: 26 Oct 2022 21:37

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