Using snapshot measurements to identify high-emitting vehicles

17908 8 97307 2 299786 document 97307 Qiu_2022_Environ._Res._Lett._17_044045.pdf application/pdf 70bf858e560779be95a1e52150da125b MD5 10119772 2022-03-25 09:18:33 https://pure.iiasa.ac.at/id/eprint/17908/1/Qiu_2022_Environ._Res._Lett._17_044045.pdf 17908 1 1 application/pdf text en public cc_by_4

Qiu_2022_Environ._Res._Lett._17_044045.pdf

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/97307 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/97307 http://eprints.org/relation/issmallThumbnailVersionOf https://pure.iiasa.ac.at/id/document/97307 archive 353 disk0/00/01/79/08 2022-03-25 09:20:27 2022-06-28 12:28:06 2022-03-25 09:20:27 article show Qiu M. Borken-Kleefeld J. 1888 0000-0002-5465-8559 Using snapshot measurements to identify high-emitting vehicles pub ECE ECEPM S3 prog_ysp 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. 2022-03-25 published Institute of Physics Publishing (IOP) 10.1088/1748-9326/ac5c9e 36 public Environmental Research Letters 17 e044045 TRUE 1748-9326 City Air Remote Emission Sensing (CARES, H2020 814966) yes info:eu-repo/grantAgreement/EC/H2020/814966/EU//CARES info:eu-repo/semantics/article info:eu-repo/semantics/openAccess