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

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

Highlight

	● 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.

References

[1] Anenberg S C, Miller J, Minjares R, Du L, Henze D K, Lacey F, Malley C S, Emberson L, Franco V, Klimont Z. . (2017). Impacts and mitigation of excess diesel-related NO_x emissions in 11 major vehicle markets. Nature, 545(7655): 467–471

[2] Apte J S, Messier K P, Gani S, Brauer M, Kirchstetter T W, Lunden M M, Marshall J D, Portier C J, Vermeulen R C H, Hamburg S P. (2017). High-resolution air pollution mapping with google street view cars: exploiting big data. Environmental Science & Technology, 51(12): 6999–7008

[3] Arvind T, Marc C B, Pragalath T, Saroj P, Daniel C, Hemanth K, Mridul G, Adewale O, Henry H, Matt M. (2015). Emission rates of regulated pollutants from current technology heavy-duty diesel and natural gas goods movement vehicles. Environmental Science & Technology, 49(8): 5236–5244

[4] Bancǎ G, Ivan F, Toma M, Nişulescu V, Micu D A. (2024). Experimental research on vehicles equipped with a GMP hybrid for the new Euro 7 emissions standard. IOP Conference Series. Materials Science and Engineering, 1303(1): 012026

[5] Bishop G A, Haugen M J, Mcdonald B C, Boies A M. (2022). Utah wintertime measurements of heavy-duty vehicle nitrogen oxide emission factors. Environmental Science & Technology, 56(3): 1885–1893

[6] Bishop J D K, Molden N, Boies A M. (2019). Using portable emissions measurement systems (PEMS) to derive more accurate estimates of fuel use and nitrogen oxides emissions from modern Euro 6 passenger cars under real-world driving conditions. Applied Energy, 242: 942–973

[7] Blanco M N, Bi J, Austin E, Larson T V, Marshall J D, Sheppard L. (2023). Impact of mobile monitoring network design on air pollution exposure assessment models. Environmental Science & Technology, 57(1): 440–450

[8] BousiotisD, Allison G, BeddowsD C S, HarrisonR M, PopeF D (2023). Towards comprehensive air quality management using low-cost sensors for pollution source apportionment. npj Climate and Atmospheric Science, 6(1): 1–10

[9] BoverouxF, Cassiers S, BuekenhoudtP, ChavatteL, De Meyer P, JeanmartH, VerhelstS, Contino F (2019). Feasibility Study of a New Test Procedure to Identify High Emitters of Particulate Matter During Periodic Technical Inspection. SAE Technical Paper, 2019-01-1190. Warrendale: SAE International

[10] Camilleri S F, Montgomery A, Visa M A, Schnell J L, Adelman Z E, Janssen M, Grubert E A, Anenberg S C, Horton D E. (2023). Air quality, health and equity implications of electrifying heavy-duty vehicles. Nature Sustainability, 6(12): 1643–1653

[11] Carter S A, Rahman M M, Lin J C, Shu Y H, Chow T, Yu X, Martinez M P, Eckel S P, Chen J C, Chen Z. . (2022). In utero exposure to near-roadway air pollution and autism spectrum disorder in children. Environment International, 158: 106898

[12] Chen X, Jiang L, Xia Y, Wang L, Ye J, Hou T, Zhang Y, Li M, Li Z, Song Z. . (2022). Quantifying on-road vehicle emissions during traffic congestion using updated emission factors of light-duty gasoline vehicles and real-world traffic monitoring big data. Science of the Total Environment, 847: 157581

[13] Chu M, Brimblecombe P, Wei P, Liu C H, Du X, Sun Y, Yam Y S, Ning Z. (2022). Kerbside NO_x and CO concentrations and emission factors of vehicles on a busy road. Atmospheric Environment, 271: 118878

[14] Deng F, Lv Z, Qi L, Wang X, Shi M, Liu H. (2020). A big data approach to improving the vehicle emission inventory in China. Nature Communications, 11(1): 2801

[15] Feng R, Hu X, Li G, Sun Z, Deng B. (2022). A comparative investigation between particle oxidation catalyst (POC) and diesel particulate filter (DPF) coupling aftertreatment system on emission reduction of a non-road diesel engine. Ecotoxicology and Environmental Safety, 238: 113576

[16] Ghaffarpasand O, Ropkins K, Beddows D C S, Pope F D. (2023). Detecting high emitting vehicle subsets using emission remote sensing systems. Science of the Total Environment, 858: 159814

[17] Heerah S, Frausto-Vicencio I, Jeong S, Marklein A R, Ding Y, Meyer A G, Parker H A, Fischer M L, Franklin J E, Hopkins F M. . (2021). Dairy methane emissions in California’s san Joaquin valley inferred with ground-based remote sensing observations in the summer and winter. Journal of Geophysical Research-Atmospheres, 126(24): e2021JD034785

[18] Hilker N, Wang J M, Jeong C H, Healy R M, Sofowote U, Debosz J, Su Y, Noble M, Munoz A, Doerksen G. . (2019). Traffic-related air pollution near roadways: discerning local impacts from background. Atmospheric Measurement Techniques, 12(10): 5247–5261

[19] Hu Z, Lu Z, Song B, Quan Y. (2021). Impact of test cycle on mass, number and particle size distribution of particulates emitted from gasoline direct injection vehicles. Science of the Total Environment, 762: 143128

[20] Huang Y, Lee C K C, Yam Y S, Mok W C, Zhou J L, Zhuang Y, Surawski N C, Organ B, Chan E F C. (2022). Rapid detection of high-emitting vehicles by on-road remote sensing technology improves urban air quality. Science Advances, 8(5): eabl7575

[21] Huang Y, Organ B, Zhou J L, Surawski N C, Hong G, Chan E F C, Yam Y S. (2018). Emission measurement of diesel vehicles in Hong Kong through on-road remote sensing: performance review and identification of high-emitters. Environmental Pollution, 237: 133–142

[22] Huang Y, Yu Y, Yam Y S, Zhou J L, Lei C, Organ B, Zhuang Y, Mok W C, Chan E F C. (2020). Statistical evaluation of on-road vehicle emissions measurement using a dual remote sensing technique. Environmental Pollution, 267: 115456

[23] Huo H, Yao Z, Zhang Y, Shen X, Zhang Q, He K. (2012). On-board measurements of emissions from diesel trucks in five cities in China. Atmospheric Environment, 54: 159–167

[24] Ježek I, Katrasnik T, Westerdahl D, Mocnik G. (2015). Black carbon, particle number concentration and nitrogen oxide emission factors of random in-use vehicles measured with the on-road chasing method. Atmospheric Chemistry and Physics, 15(19): 11011–11026

[25] Kwon S, Park Y, Park J, Kim J, Choi K H, Cha J S. (2017). Characteristics of on-road NO_x emissions from Euro 6 light-duty diesel vehicles using a portable emissions measurement system. Science of the Total Environment, 576: 70–77

[26] Lei Y, Qin C, Qiu T, Yue G, Ding M. (2021). NO_x emission removal from a parallel diesel engine group by scr system based on distributed control technology. Environmental Science & Technology, 55(9): 6352–6362

[27] Lelieveld J, Evans J S, Fnais M, Giannadaki D, Pozzer A. (2015). The contribution of outdoor air pollution sources to premature mortality on a global scale. Nature, 525(7569): 367–371

[28] Li Y, Chen X, Wu J, Zhang Q, Zhang Z, Hao J, Jiang J. (2024). A convertible condensation particle counter using alcohol or water as the working fluid. Aerosol Science and Technology, 59(2): 185–194

[29] Liu B, Zimmerman N. (2021). Fleet-based vehicle emission factors using low-cost sensors: case study in parking garages. Transportation Research Part D, Transport and Environment, 91: 102635

[30] Liu H, He K, Lents J M, Wang Q, Tolvett S. (2009). Characteristics of diesel truck emission in china based on portable emissions measurement systems. Environmental Science & Technology, 43(24): 9507–9511

[31] Liu Q, Hallquist Å M, Fallgren H, Jerksjö M, Jutterström S, Salberg H, Hallquist M, Le Breton M, Pei X, Pathak R K. . (2019). Roadside assessment of a modern city bus fleet: gaseous and particle emissions. Atmospheric Environment: X, 3: 100044

[32] Liu X, Elgowainy A, Vijayagopal R, Wang M. (2021). Well-to-wheels analysis of zero-emission plug-in battery electric vehicle technology for medium- and heavy-duty trucks. Environmental Science & Technology, 55(1): 538–546

[33] Olin M, Oikarinen H, Marjanen P, Mikkonen S, Karjalainen P. (2023). High particle number emissions determined with robust regression plume analysis (RRPA) from hundreds of vehicle chases. Environmental Science & Technology, 57(24): 8911–8920

[34] Park S S, Vijayan A, Mara S L, Herner J D. (2016). Investigating the real-world emission characteristics of light-duty gasoline vehicles and their relationship to local socioeconomic conditions in three communities in Los Angeles, California. Journal of the Air & Waste Management Association, 66(10): 1031–1044

[35] Preble C V, Dallmann T R, Kreisberg N M, Hering S V, Harley R A, Kirchstetter T W. (2015). Effects of particle filters and selective catalytic reduction on heavy-duty diesel drayage truck emissions at the port of Oakland. Environmental Science & Technology, 49(14): 8864–8871

[36] Qiao X, Zhang Q, Wang D, Hao J, Jiang J. (2021). Improving data reliability: a quality control practice for low-cost PM_2.5 sensor network. Science of the Total Environment, 779: 146381

[37] Qiu M, Borken-Kleefeld J. (2022). Using snapshot measurements to identify high-emitting vehicles. Environmental Research Letters, 17(4): 044045

[38] Raparthi N, Barudgar A, Chu M, Ning Z, Phuleria H C. (2023). Estimating individual vehicle emission factors from near-road measurements in India. Atmospheric Environment, 308: 119869

[39] Raparthi N, Phuleria H C. (2021). Real-world vehicular emissions in the Indian megacity: carbonaceous, metal and morphological characterization, and the emission factors. Urban Climate, 39: 100955

[40] Raparthi N, Phuleria H C. (2022). On-road vehicular emission characterization from the road-tunnel measurements in India: morphology, emission factors, and sources. Environmental Research, 215: 114295

[41] Russell H S, Kappelt N, Fessa D, Frederickson L B, Bagkis E, Apostolidis P, Karatzas K, Schmidt J A, Hertel O, Johnson M S. (2022). Particulate air pollution in the Copenhagen metro Part 2: Low-cost sensors and micro-environment classification. Environment International, 170: 107645

[42] Sahlodin A M, Sotudeh-Gharebagh R, Zhu Y. (2007). Modeling of dispersion near roadways based on the vehicle-induced turbulence concept. Atmospheric Environment, 41(1): 92–102

[43] Shen Y, Zhang Q, Wang D, Tian M, Yu Q, Wang J, Yin H, Zhang S, Hao J, Jiang J. (2022). Evaluation of a cost-effective roadside sensor platform for identifying high emitters. Science of the Total Environment, 816: 151609

[44] SuCW, YuanX, ShaoXF, Moldovan N C (2023). Explore the environmental benefits of new energy vehicles: evidence from China. Annals of Operations Research,

[45] Tian M, He L, Peng D, Fu M, Ma S, Mu J, Yu Q, Wang J, Yin H, Wang J. (2024). Characterizing NO_x emissions from diesel trucks with tampered aftertreatment systems and its implications for identifying high emitters. Science of the Total Environment, 917: 170378

[46] Tong Z, Li Y, Lin Q, Wang H, Zhang S, Wu Y, Zhang K M. (2022). Uncertainty investigation of plume-chasing method for measuring on-road NO_x emission factors of heavy-duty diesel vehicles. Journal of Hazardous Materials, 424: 127372

[47] Wang F, Fang D, Ketzel M. (2012). Particulate number emission factors and charactization from road traffic. Acta Scientiarum Naturalium Universitatis Pekinensis, 48: 1023–1029

[48] Wang H, Zhang S, Wu X, Wen Y, Li Z, Wu Y. (2023). Emission measurements on a large sample of heavy-duty diesel trucks in china by using mobile plume chasing. Environmental Science & Technology, 57(40): 15153–15161

[49] Wang J M, Jeong C H, Hilker N, Shairsingh K K, Healy R M, Sofowote U, Debosz J, Su Y, Mcgaughey M, Doerksen G. . (2018). Near-road air pollutant measurements: accounting for inter-site variability using emission factors. Environmental Science & Technology, 52(16): 9495–9504

[50] Wang J M, Jeong C H, Zimmerman N, Healy R M, Hilker N, Evans G J. (2017). Real-world emission of particles from vehicles: volatility and the effects of ambient temperature. Environmental Science & Technology, 51(7): 4081–4090

[51] Wang J M, Jeong C H, Zimmerman N, Healy R M, Wang D K, Ke F, Evans G J. (2015). Plume-based analysis of vehicle fleet air pollutant emissions and the contribution from high emitters. Atmospheric Measurement Techniques, 8(8): 3263–3275

[52] Wang X, Westerdahl D, Wu Y, Pan X, Zhang K M. (2011). On-road emission factor distributions of individual diesel vehicles in and around Beijing, China. Atmospheric Environment, 45(2): 503–513

[53] Wei P, Brimblecombe P, Yang F, Anand A, Xing Y, Sun L, Sun Y, Chu M, Ning Z. (2021). Determination of local traffic emission and non-local background source contribution to on-road air pollution using fixed-route mobile air sensor network. Environmental Pollution, 290: 118055

[54] Wen Y, Wang H, Larson T, Kelp M, Zhang S, Wu Y, Marshall J D. (2019). On-highway vehicle emission factors, and spatial patterns, based on mobile monitoring and absolute principal component score. Science of the Total Environment, 676: 242–251

[55] Xiang S, Zhang S, Yu Y T, Wang H, Shen Y, Zhang Q, Wang Z, Wang D, Tian M, Wang J. . (2023). Evaluation of the relationship between meteorological variables and NO_x emission factors based on plume-chasing measurements. ACS ES&T Engineering, 3(3): 417–426

[56] Yang Z, Tate J E, Rushton C E, Morganti E, Shepherd S P. (2022). Detecting candidate high NO_x emitting light commercial vehicles using vehicle emission remote sensing. Science of the Total Environment, 823: 153699

[57] Zeng L, Wang F, Xiao S, Zheng X, Li X, Xie Q, Yu X, Huang C, Hu Q, You Y. . (2024). Characterization and prediction of tailpipe ammonia emissions from in-use China 5/6 light-duty gasoline vehicles. Frontiers of Environmental Science & Engineering, 18(1): 6

[58] Zhang S, Wu Y, Liu H, Huang R, Yang L, Li Z, Fu L, Hao J. (2014). Real-world fuel consumption and CO₂ emissions of urban public buses in Beijing. Applied Energy, 113: 1645–1655

[59] Zheng Z, Durbin T D, Xue J, Johnson K C, Li Y, Hu S, Huai T, Ayala A, Kittelson D B, Jung H S. (2014). Correction to comparison of particle mass and solid particle number (SPN) emissions from a heavy-duty diesel vehicle under on-road driving conditions and a standard testing cycle. Environmental Science & Technology, 48(3): 1779–1786

[60] Zhou L, Hallquist Å M, Hallquist M, Salvador C M, Gaita S M, Sjödin Å, Jerksjö M, Salberg H, Wängberg I, Mellqvist J. . (2020). A transition of atmospheric emissions of particles and gases from on-road heavy-duty trucks. Atmospheric Chemistry and Physics, 20(3): 1701–1722

RIGHTS & PERMISSIONS

Higher Education Press 2025