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Qiu, M. & Borken-Kleefeld, J. 
ORCID: https://orcid.org/0000-0002-5465-8559
(2022).
Using snapshot measurements to identify high-emitting vehicles.
Environmental Research Letters 17 e044045. 10.1088/1748-9326/ac5c9e.
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Abstract
Policy makers have long been interested in detecting 'high-emitters', a supposedly smallfraction of vehicles that make disproportionally large contributions to total fleet emissions. However, existing identification schemes often exclusively rely on snapshot measurements (i.e. emissions within less than a second), and thus simply identify vehicles with high instantaneous emissions, instead of vehicles with high average emissions over a driving period as regulated by emission standards. We design a comprehensive scheme to address this challenge by combining fleetwide remote sensing measurements with detailed second-by-second emission measurements from individual vehicles. We first determine the trip-average NOx emission rates of individual vehicles in a Euro-5 diesel fleet measured across European locations; this allows, second, to calculate the fraction and emission contributions of high-emitters based on trip-average emission. We demonstrate that the identification of high-emitters is quite uncertain as long as it is based on single snapshots only; but 80% of the high-emitters can be identified with over 75% precision with five or more repeated measurements of the same vehicle. Compared to the conventional detection schemes, our scheme can increase the identified high-emitters and associated emission reductions by over 140%. Our method is validated and shown to be superior to the conventional interpretation of snapshot measurements.
| Item Type: | Article |
|---|---|
| Research Programs: | Energy, Climate, and Environment (ECE) Energy, Climate, and Environment (ECE) > Pollution Management (PM) Energy, Climate, and Environment (ECE) > Sustainable Service Systems (S3) Young Scientists Summer Program (YSSP) |
| Depositing User: | Luke Kirwan |
| Date Deposited: | 25 Mar 2022 09:20 |
| Last Modified: | 28 Jun 2022 12:28 |
| URI: | https://pure.iiasa.ac.at/17908 |
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