Yang, Z, Tate, JE orcid.org/0000-0003-1646-6852, Rushton, CE et al. (2 more authors) (2022) Detecting candidate high NOx emitting light commercial vehicles using vehicle emission remote sensing. Science of the Total Environment, 823. 153699. ISSN 0048-9697
Abstract
Vehicle emission remote sensing devices have been widely used for monitoring and assessing the real-world emission performance of vehicles. They are also well-suited to identify candidate high emitting vehicles as remote sensing surveys measure the on-road, real-driving emissions (RDE) of a high proportion of the operational vehicle fleet passing through a testing site. This study uses the Gumbel distribution to characterize the fuel-specific NOx emission rates (g·kg−1) from diesel vans (formally referred to as light commercial vehicles or LCVs) and screen candidate high emitting vehicles. Van emission trends of four European countries (Belgium, Sweden, Switzerland and the UK) from Euro 3 to Euro 6a/b have been studied, and the impact of road grade on candidate Euro 6a/b high-emitters is also evaluated. The measurements of Euro 6a/b fleets from four countries are pooled together, and a consistent 4% of candidate high-emitters are found in both class II and class III Euro 6a/b vans, accounting for an estimated 24% and 21% total NOx emissions respectively. The pooled four country data is differentiated by vehicle models and manufacture groups. Engine downsizing of Euro 6a/b class II vans is suspected to worsen the emission performance when vehicles are driven under high engine load. The VW Group is found to be the manufacture with cleanest NOx emission performance in the Euro 6a/b fleets. By distinguishing high-emitters from normally behaving vehicles, a more robust description of fleet behaviour can be provided and high-emitting vehicles targeted for further testing by plume chasing or in an inspection garage. If the vehicle is found to have a faulty, deteriorated or tampered emission after-treatment system, the periodic vehicle inspection safety and environmental performance certificate could be revoked.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 Elsevier B.V. All rights reserved. This is an author produced version of an article, published in Science of the Total Environment. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Remote sensing; Vans; NOx emissions; High-emitters identification |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Spatial Modelling and Dynamics (Leeds) |
Funding Information: | Funder Grant number EU - European Union 814966 |
Depositing User: | Symplectic Publications |
Date Deposited: | 15 Jul 2022 11:26 |
Last Modified: | 07 Feb 2023 01:13 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.scitotenv.2022.153699 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:189062 |