Real-world identification of high-emitting vehicles based on near-road sensor measurement

Highlights

	● Real-world high emitters were identified using roadside measurements.
	● 12.6%–16.5% of total vehicles were identified as high-emitters in field campaign.
	● A correct identification rate of 95% was achieved and proven via on-site inspection.

Abstract

A small fraction of high-emitting vehicles make disproportionally large contributions to total fleet emissions. Therefore identifying high emitters under real driving conditions is crucial. In this study, two portable sensor platforms for high-emitter identification were used for online roadside measurements of vehicle-emitted NO, particle number (PN), and CO₂ concentrations in Tangshan and Chengdu, respectively. The measured mean concentrations of vehicle-emitted NO, PN, and CO₂ in Tangshan and Chengdu were 27.7–32.9 ppb, 5.4 × 10³–8.2 × 10³ #/cm³, and 7.3–8.2 ppm, respectively. Based on more than one month of second-by-second measured pollutant concentrations and passed vehicle information, a scheme was developed to identify high emitters. Among the 217000 and 43000 vehicles that passed the roadside sensor platforms at Tangshan and Chengdu, approximately 60% and 73% of vehicle exhaust plumes were successfully detected using the sensor platform. The NO and PN emission factors (EFs) tended to have log-normal distributions with the median values of 14.3 g/kg-fuel and 1.3 × 10¹⁵ #/kg-fuel, respectively. In general, the percentages of high-emitters identified at the Tangshan and Chengdu sites were 8.7% and 12.2% of the total identified vehicles, respectively. Among these high-emitters, 122 vehicles were randomly inspected on-site with the assistance of traffic officers, and the rate of correct identification was approximately 95%, which demonstrates that our methodology performs well in identifying real-world high-emitters. Overall, its low cost, good mobility, strong adaptability, and high correct identification rate make this roadside sensor platform a promising approach for real-world high-emitter identification.

Graphical abstract

Keywords

Real world / High-emitter identification / Roadside sensor measurement / Nitrogen oxide / Particle number

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Conflict of Interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

We acknowledge support from the National Key R&D Program of China (No. 2023YFC370540203) and the China Postdoctoral Fellowship Program of CPSF (No. GZC20231271).

Electronic Supplementary Material

Supplementary material is available in the online version of this article at https://doi.org/10.1007/s11783-025-1983-x and is accessible for authorized users.

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