Identify the contribution of vehicle non-exhaust emissions: a single particle aerosol mass spectrometer test case at typical road environment

Qijun Zhang, Jiayuan Liu, Ning Wei, Congbo Song, Jianfei Peng, Lin Wu, Hongjun Mao

PDF(5758 KB)
PDF(5758 KB)
Front. Environ. Sci. Eng. ›› 2023, Vol. 17 ›› Issue (5) : 62. DOI: 10.1007/s11783-023-1662-8
RESEARCH ARTICLE
RESEARCH ARTICLE

Identify the contribution of vehicle non-exhaust emissions: a single particle aerosol mass spectrometer test case at typical road environment

Author information +
History +

Highlights

● A single particle observation was conducted in a high traffic flow road environment.

● Major particle types were vehicle exhausts, coal burning, and biomass burning.

● Contribution of non-exhaust emissions was calculated via PMF.

● Proportion of non-exhaust emissions can reach 10.1 % at road environment.

Abstract

A single particle aerosol mass spectrometer (SPAMS) was used to accurately quantify the contribution of vehicle non-exhaust emissions to particulate matter at typical road environment. The PM2.5, black carbon, meteorological parameters and traffic flow were recorded during the test period. The daily trend for traffic flow and speed on TEDA Street showed obvious “M” and “W” characteristics. 6.3 million particles were captured via the SPAMS, including 1.3 million particles with positive and negative spectral map information. Heavy Metal, High molecular Organic Carbon, Organic Carbon, Mixed Carbon, Elemental Carbon, Rich Potassium, Levo-rotation Glucose, Rich Na, SiO3 and other categories were analyzed. The particle number concentration measured by SPAMS showed a good linear correlation with the mass concentrations of PM2.5 and BC, which indicates that the particulate matter captured by the SPAMS reflects the pollution level of fine particulate matter. EC, ECOC, OC, HM and crustal dust components were found to show high values from 7:00–9:00 AM, showing that these chemical components are directly or indirectly related to vehicle emissions. Based on the PMF model, 7 major factors are resolved. The relative contributions of each factor were determined: vehicle exhaust emission (44.8 %), coal-fired source (14.5 %), biomass combustion (12.2 %), crustal dust (9.4 %), ship emission (9.0 %), tires wear (6.6 %) and brake pads wear (3.5 %). The results show that the contribution of vehicle non-exhaust to particulate matter at roadside environment is approximately 10.1 %. Vehicle non-exhaust emissions are the focus of future research in the vehicle pollutant emission control field.

Graphical abstract

Keywords

Non-exhaust emissions / SPAMS / PMF / Roadside environment

Cite this article

Download citation ▾
Qijun Zhang, Jiayuan Liu, Ning Wei, Congbo Song, Jianfei Peng, Lin Wu, Hongjun Mao. Identify the contribution of vehicle non-exhaust emissions: a single particle aerosol mass spectrometer test case at typical road environment. Front. Environ. Sci. Eng., 2023, 17(5): 62 https://doi.org/10.1007/s11783-023-1662-8

References

[1]
Abu-Allaban M, Gillies J A, Gertler A W, Clayton R, Proffitt D. (2003). Tailpipe, resuspended road dust, and brake-wear emission factors from on-road vehicles. Atmospheric Environment, 37(37): 5283–5293
CrossRef Google scholar
[2]
Adachi K, Tainosho Y. (2004). Characterization of heavy metal particles embedded in tire dust. Environment International, 30(8): 1009–1017
CrossRef Pubmed Google scholar
[3]
Amato F, Cassee F R, Denier van der Gon H A, Gehrig R, Gustafsson M, Hafner W, Harrison R M, Jozwicka M, Kelly F J, Moreno T, Prevot A S, Schaap M, Sunyer J, Querol X. (2014). Urban air quality: the challenge of traffic non-exhaust emissions. Journal of Hazardous Materials, 275: 31–36
CrossRef Pubmed Google scholar
[4]
Apeagyei E, Bank M S, Spengler J D. (2011). Distribution of heavy metals in road dust along an urban-rural gradient in Massachusetts. Atmospheric Environment, 45(13): 2310–2323
CrossRef Google scholar
[5]
Baensch-Baltruschat B, Kocher B, Stock F, Reifferscheid G. (2020). Tyre and road wear particles (TRWP): a review of generation, properties, emissions, human health risk, ecotoxicity, and fate in the environment. Science of the Total Environment, 733: 137823
CrossRef Pubmed Google scholar
[6]
Beddows D C S, Dall’osto M, Olatunbosun O A, Harrison R M. (2016). Detection of brake wear aerosols by aerosol time-of-flight mass spectrometry. Atmospheric Environment, 129: 167–175
CrossRef Google scholar
[7]
Bi X, Zhang G, Li L, Wang X, Li M, Sheng G, Fu J, Zhou Z. (2011). Mixing state of biomass burning particles by single particle aerosol mass spectrometer in the urban area of PRD, China. Atmospheric Environment, 45(20): 3447–3453
CrossRef Google scholar
[8]
Councell T B, Duckenfield K U, Landa E R, Callender E. (2004). Tire-wear particles as a source of zinc to the environment. Environmental Science & Technology, 38(15): 4206–4214
CrossRef Pubmed Google scholar
[9]
Dahl A, Gharibi A, Swietlicki E, Gudmundsson A, Bohgard M, Ljungman A, Blomqvist G, Gustafsson M. (2006). Traffic-generated emissions of ultrafine particles from pavement-tire interface. Atmospheric Environment, 40(7): 1314–1323
CrossRef Google scholar
[10]
Dall’Osto M, Beddows D C S, Gietl J K, Olatunbosun O A, Yang X, Harrison R M. (2014). Characteristics of tyre dust in polluted air: studies by single particle mass spectrometry (ATOFMS). Atmospheric Environment, 94: 224–230
CrossRef Google scholar
[11]
Garg B D, Cadle S H, Mulawa P A, Groblicki P J, Laroo C, Parr G A. (2000). Brake wear particulate matter emissions. Environmental Science & Technology, 34(21): 4463–4469
CrossRef Google scholar
[12]
Gasser M, Riediker M, Mueller L, Perrenoud A, Blank F, Gehr P, Rothen-Rutishauser B. (2009). Toxic effects of brake wear particles on epithelial lung cells in vitro. Particle and Fibre Toxicology, 6(1): 30–42
CrossRef Pubmed Google scholar
[13]
Gong Z, Lan Z, Xue L, Zeng L, He L, Huang X. (2012). Characterization of submicron aerosols in the urban outflow of the central Pearl River Delta region of China. Frontiers of Environmental Science & Engineering, 6(5): 725–733
CrossRef Google scholar
[14]
Grieshop A P, Lipsky E M, Pekney N J, Takahama S, Robinson A L. (2006). Fine particle emission factors from vehicles in a highway tunnel: effects of fleet composition and season. Atmospheric Environment, 40: 287–298
CrossRef Google scholar
[15]
Kim G, Lee S. (2018). Characteristics of tire wear particles generated by a tire simulator under various driving conditions. Environmental Science & Technology, 52(21): 12153–12161
CrossRef Pubmed Google scholar
[16]
Kwak J H, Kim H, Lee J, Lee S. (2013). Characterization of non-exhaust coarse and fine particles from on-road driving and laboratory measurements. Science of the Total Environment, 458-460: 273–282
CrossRef Pubmed Google scholar
[17]
Li L, Li M, Huang Z, Gao W, Nian H, Fu Z, Gao J, Chai F, Zhou Z. (2014). Ambient particle characterization by single particle aerosol mass spectrometry in an urban area of Beijing. Atmospheric Environment, 94: 323–331
CrossRef Google scholar
[18]
Masclans Abello P, Medina Iglesias V, De Los Santos Lopez M A, Alvarez-Florez J. (2021). Real drive cycles analysis by ordered power methodology applied to fuel consumption, CO2, NOx and PM emissions estimation. Frontiers of Environmental Science & Engineering, 15(1): 4
CrossRef Google scholar
[19]
Mathissen M, Scheer V, Vogt R, Benter T. (2011). Investigation on the potential generation of ultrafine particles from the tire-road interface. Atmospheric Environment, 45(34): 6172–6179
CrossRef Google scholar
[20]
Paatero P, Tapper U. (1994). Positive matrix factorization: a non‐negative factor model with optimal utilization of error estimates of data values. Environmetrics, 5(2): 111–126
CrossRef Google scholar
[21]
Pant P, Harrison R M. (2013). Estimation of the contribution of road traffic emissions to particulate matter concentrations from field measurements: a review. Atmospheric Environment, 77: 78–97
CrossRef Google scholar
[22]
Park I, Kim H, Lee S. (2018). Characteristics of tire wear particles generated in a laboratory simulation of tire/road contact conditions. Journal of Aerosol Science, 124: 30–40
CrossRef Google scholar
[23]
PraticoF G, Briante P G (2020). Particulate Matter from Non-exhaust Sources. Vilnius: Lithuania
[24]
Pratt K A, Prather K A. (2012). Mass spectrometry of atmospheric aerosols-recent developments and applications. Part II: on-line mass spectrometry techniques. Mass Spectrometry Reviews, 31(1): 17–48
CrossRef Pubmed Google scholar
[25]
Roubicek V, Raclavska H, Juchelkova D, Filip P. (2008). Wear and environmental aspects of composite materials for automotive braking industry. Wear, 265(1–2): 167–175
CrossRef Google scholar
[26]
Tao S, Wang X, Chen H, Yang X, Li M, Li L, Zhou Z. (2011). Single particle analysis of ambient aerosols in Shanghai during the World Exposition, 2010: two case studies. Frontiers of Environmental Science & Engineering, 5(3): 391–401
CrossRef Google scholar
[27]
Timmers V R J H, Achten P A J. (2016). Non-exhaust PM emissions from electric vehicles. Atmospheric Environment, 134: 10–17
CrossRef Google scholar
[28]
von Uexkull O, Skerfving S, DoyleR, BraungartM (2005). Antimony in brake pads: a carcinogenic component? Journal of Cleaner Production, 13(1): 19–31
CrossRef Google scholar
[29]
Wen W, Cheng S, Liu L, Wang G, Wang X. (2016). Source apportionment of PM2.5 in Tangshan, China: hybrid approaches for primary and secondary species apportionment. Frontiers of Environmental Science & Engineering, 10(5): 6
CrossRef Google scholar
[30]
Yue X, Wu Y, Huang X, Ma Y, Pang Y, Bao X, Hao J. (2012). Impact of gasoline engine deposits on light duty vehicle emissions: in-use case study in Beijing, China. Frontiers of Environmental Science & Engineering, 6(5): 717–724
CrossRef Google scholar
[31]
Zhang J, Zhang X, Wu L, Wang T, Zhao J, Zhang Y, Men Z, Mao H. (2018). Occurrence of benzothiazole and its derivates in tire wear, road dust, and roadside soil. Chemosphere, 201: 310–317
CrossRef Pubmed Google scholar
[32]
Zhang Y, Wang X, Chen H, Yang X, Chen J, Allen J O. (2009). Source apportionment of lead-containing aerosol particles in Shanghai using single particle mass spectrometry. Chemosphere, 74(4): 501–507
CrossRef Pubmed Google scholar
[33]
Zhu R, Hu J, He L, Zu L, Bao X, Lai Y, Su S. (2021). Effects of ambient temperature on regulated gaseous and particulate emissions from gasoline-, E10- and M15-fueled vehicles. Frontiers of Environmental Science & Engineering, 15(1): 14
CrossRef Google scholar

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Nos. 42107114 and 42177084), the Tianjin Science and Technology Plan Project (No. 20YFZCSN01000), and the Fundamental Research Funds for the Central Universities (No. 63221411).

Electronic Supplementary Material

Supplementary material is available in the online version of this article at https://doi.org/10.1007/s11783-023-1662-8 and is accessible for authorized users.

RIGHTS & PERMISSIONS

2023 Higher Education Press
AI Summary AI Mindmap
PDF(5758 KB)

Accesses

Citations

Detail

Sections
Recommended

/