Emission ratio determination from road vehicles using a range of remote emission sensing techniques

Abstract

The development of remote emission sensing techniques such as plume chasing and point sampling has progressed significantly and is providing new insight into vehicle emissions behaviour. However, the analysis of remote emission sensing data can be highly challenging and there is currently no standardised method available. In this study we present a single data processing approach to quantify vehicle exhaust emissions measured using a range of remote emission sensing techniques. The method uses rolling regression calculated over short time intervals to derive the characteristics of diluting plumes. We apply the method to high time-resolution plume chasing and point sampling data to quantify gaseous exhaust emission ratios from individual vehicles. Data from a series of vehicle emission characterisation experiments conducted under controlled conditions is used to demonstrate the potential of this approach. First, the method is validated through comparison with on-board emission measurements. Second, the ability of this approach to detect changes in NOx / CO2 ratios associated with aftertreatment system tampering and different engine operating conditions is shown. Third, the flexibility of the approach is demonstrated by varying the pollutants used as regression variables and quantifying the NO2 / NOx ratios for different vehicle types. A higher proportion of total NOx is emitted as NO2 when the selective catalytic reduction system of the measured heavy duty truck is tampered. In addition, the applicability of this approach to urban environments is illustrated using mobile measurements conducted in Milan, Italy in 2021. Emissions from local combustion sources are distinguished from a complex urban background and the spatiotemporal variability in emissions is shown. The mean NOx / CO2 ratio of 1.61 ppb/ppm is considered representative of the local vehicle fleet. It is envisaged that this approach can be used to quantify emissions from a range of mobile and stationary fuel combustion sources, including non-road vehicles, ships, trains, boilers and incinerators.

Metadata

Item Type:	Article
Authors/Creators:	Farren, Naomi J. https://orcid.org/0000-0002-5668-1648 Schmidt, Christina Juchem, Hannes Pöhler, Denis Wilde, Shona E. (sw1255@york.ac.uk) Wagner, Rebecca L. Wilson, Samuel Shaw, Marvin D. https://orcid.org/0000-0001-9954-243X Carslaw, David C. https://orcid.org/0000-0003-0991-950X
Copyright, Publisher and Additional Information:	Funding Information: This work has received funding from the European Union 's Horizon 2020 research and innovation programme, as part of the CARES project under Grant Agreement No. 814966 ( https://cares-project.eu/ ). Rebecca Wagner was supported by the NERC Panorama Doctoral Training Partnership (grant no. NE/S007458/1 ). We thank TNO and RDW (the Netherlands Vehicle Authority) and their involved staff for making the test track characterisation experiments happen. The authors would like to thank Quinn Vroom for the coordination of the vehicle emission measurements, and Jan Pieter Lollinga and Marcel Moerman for their pivotal role in building and running the plume chase vehicle. The point sampling expertise of Markus Knoll and Åsa Hallquist is gratefully acknowledged. We are grateful to the H2020 DIAS project ( https://dias-project.com/ ) for helping to find a suitable truck for the test track experiments. Finally we thank Innovhub and AMAT and their involved staff for enabling the mobile measurements to take place in the city of Milan, Italy. Funding Information: This work has received funding from the European Union's Horizon 2020 research and innovation programme, as part of the CARES project under Grant Agreement No. 814966 (https://cares-project.eu/). Rebecca Wagner was supported by the NERC Panorama Doctoral Training Partnership (grant no. NE/S007458/1). We thank TNO and RDW (the Netherlands Vehicle Authority) and their involved staff for making the test track characterisation experiments happen. The authors would like to thank Quinn Vroom for the coordination of the vehicle emission measurements, and Jan Pieter Lollinga and Marcel Moerman for their pivotal role in building and running the plume chase vehicle. The point sampling expertise of Markus Knoll and Åsa Hallquist is gratefully acknowledged. We are grateful to the H2020 DIAS project (https://dias-project.com/) for helping to find a suitable truck for the test track experiments. Finally we thank Innovhub and AMAT and their involved staff for enabling the mobile measurements to take place in the city of Milan, Italy. Publisher Copyright: © 2023 The Authors
Keywords:	Plume chasing,Point sampling,Regression,Remote sensing,Vehicle emissions
Dates:	Published: 1 June 2023 Published (online): 14 March 2023 Accepted: 28 February 2023 Submitted: 27 October 2022
Institution:	The University of York
Academic Units:	The University of York > Faculty of Sciences (York) > Chemistry (York)
Depositing User:	Pure (York)
Date Deposited:	05 Apr 2023 08:30
Last Modified:	16 Oct 2024 19:09
Published Version:	https://doi.org/10.1016/j.scitotenv.2023.162621
Status:	Published
Refereed:	Yes
Identification Number:	10.1016/j.scitotenv.2023.162621
Related URLs:	http://www.scopus.com/inward/record.url?...
Open Archives Initiative ID (OAI ID):	oai:eprints.whiterose.ac.uk:198028

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Description: Emission ratio determination from road vehicles using a range of remote emission sensing techniques

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Emission ratio determination from road vehicles using a range of remote emission sensing techniques

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