Articles | Volume 17, issue 8
https://doi.org/10.5194/amt-17-2481-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-17-2481-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Large-scale automated emission measurement of individual vehicles with point sampling
Institute of Electrical Measurement and Sensor Systems, Graz University of Technology, Inffeldgasse 33/I, 8010 Graz, Austria
Martin Penz
Institute of Electrical Measurement and Sensor Systems, Graz University of Technology, Inffeldgasse 33/I, 8010 Graz, Austria
Hannes Juchem
Institute of Environmental Physics, Heidelberg University, INF 229, 69120 Heidelberg, Germany
Christina Schmidt
Institute of Environmental Physics, Heidelberg University, INF 229, 69120 Heidelberg, Germany
Airyx GmbH, Justus-von-Liebig-Str. 14, 69214 Eppelheim, Germany
Denis Pöhler
Institute of Environmental Physics, Heidelberg University, INF 229, 69120 Heidelberg, Germany
Airyx GmbH, Justus-von-Liebig-Str. 14, 69214 Eppelheim, Germany
Alexander Bergmann
Institute of Electrical Measurement and Sensor Systems, Graz University of Technology, Inffeldgasse 33/I, 8010 Graz, Austria
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Cited
11 citations as recorded by crossref.
- An Ambient Measurement Technique for Vehicle Emission Quantification and Concentration Source Apportionment N. Farren et al. 10.1021/acs.est.4c07907
- Identification of high emitting heavy duty vehicles using Plume Chasing: European case study for enforcement C. Schmidt et al. 10.1016/j.scitotenv.2025.179844
- Influence of Vehicle Design on Near-Road Concentrations of Traffic-Related Air Pollutants S. Wilson et al. 10.1021/acsestair.5c00059
- Nanoparticle Counting for PTI: The Dirty Tail Paradigm — A Pragmatic Proposal to Strongly Reduce Urban PN Pollution from Combustion Engine Fleets A. Mayer et al. 10.1007/s40825-024-00257-0
- Optimisation and validation of Plume Chasing for robust and automated NOx and particle vehicle emission measurements C. Schmidt et al. 10.1016/j.aeaoa.2025.100317
- Automatic Number Plate Detection and Recognition System for Small-Sized Number Plates of Category L-Vehicles for Remote Emission Sensing Applications H. Imtiaz et al. 10.3390/s25113499
- Spatiotemporal Patterns of Super-Emitting Diesel Vehicles: A Scalable Remote Sensing Framework for Urban Emission Hotspot Mitigation J. Gao et al. 10.1016/j.apr.2025.102782
- Reconstruction of Density Fields of Category L-Vehicles’ Exhaust Plumes for Optimizing Remote Emission Sensing and Engine Performance H. Imtiaz et al. 10.4271/03-18-06-0036
- Environmental science, policy, and industry nexus: Integrating Frameworks for better transport sustainability N. Bahman et al. 10.1016/j.glt.2024.12.001
- Highly Disaggregated Particulate and Gaseous Vehicle Emission Factors and Ambient Concentration Apportionment Using a Plume Regression Technique N. Farren et al. 10.1021/acs.est.5c05015
- A modern, flexible cloud-based database and computing service for real-time analysis of vehicle emissions data C. Rushton et al. 10.1007/s44212-024-00066-4
10 citations as recorded by crossref.
- An Ambient Measurement Technique for Vehicle Emission Quantification and Concentration Source Apportionment N. Farren et al. 10.1021/acs.est.4c07907
- Identification of high emitting heavy duty vehicles using Plume Chasing: European case study for enforcement C. Schmidt et al. 10.1016/j.scitotenv.2025.179844
- Influence of Vehicle Design on Near-Road Concentrations of Traffic-Related Air Pollutants S. Wilson et al. 10.1021/acsestair.5c00059
- Nanoparticle Counting for PTI: The Dirty Tail Paradigm — A Pragmatic Proposal to Strongly Reduce Urban PN Pollution from Combustion Engine Fleets A. Mayer et al. 10.1007/s40825-024-00257-0
- Optimisation and validation of Plume Chasing for robust and automated NOx and particle vehicle emission measurements C. Schmidt et al. 10.1016/j.aeaoa.2025.100317
- Automatic Number Plate Detection and Recognition System for Small-Sized Number Plates of Category L-Vehicles for Remote Emission Sensing Applications H. Imtiaz et al. 10.3390/s25113499
- Spatiotemporal Patterns of Super-Emitting Diesel Vehicles: A Scalable Remote Sensing Framework for Urban Emission Hotspot Mitigation J. Gao et al. 10.1016/j.apr.2025.102782
- Reconstruction of Density Fields of Category L-Vehicles’ Exhaust Plumes for Optimizing Remote Emission Sensing and Engine Performance H. Imtiaz et al. 10.4271/03-18-06-0036
- Environmental science, policy, and industry nexus: Integrating Frameworks for better transport sustainability N. Bahman et al. 10.1016/j.glt.2024.12.001
- Highly Disaggregated Particulate and Gaseous Vehicle Emission Factors and Ambient Concentration Apportionment Using a Plume Regression Technique N. Farren et al. 10.1021/acs.est.5c05015
Latest update: 02 Nov 2025
Short summary
Exhaust emissions from combustion-based vehicles are negatively affecting human health and our environment. In particular, a small share (< 20 %) of poorly maintained or tampered vehicles are responsible for the majority (60 %–90 %) of traffic-related emissions. The emissions from vehicles are currently not properly monitored during their lifetime. We present a roadside measurement technique, called
point sampling, which can be used to monitor vehicle emissions throughout their life cycle.
Exhaust emissions from combustion-based vehicles are negatively affecting human health and our...