Low-cost methodology to estimate vehicle emission factors

Road traffic emission factors (EFs) are important parameters in managing air quality. Estimation typically requires data from advanced (and expensive) monitoring systems which remain unavailable in some regions (e.g. in developing countries). In this context, the use of simpler (lower-cost) systems may be more appropriate, but it is essential to guarantee the robustness of EF estimations. This article describes a methodology designed to estimate vehicle EFs from street canyon measurements of traffic fluxes, wind speed and direction, and pollutant concentration levels by using low-cost devices, all samples at a one-minute interval. We use different moving window filters (time periods) to average the raw measurements. Applying standard multiple linear regressions (MRL) and principal component regressions (PCR), we show that there is an optimal smoothing level that best relates traffic episodes and pollutant concentration measurements. An application for PM10's EFs on four vehicle categories of Havana's fleet shows a preference for PCR over MLR techniques since it reduced the collinearity effects that appear when traffic fluxes are naturally correlated between vehicle categories. The best regression fits (R > 0.5 and standard deviation of estimates < 15%) were obtained by averaging data between 40′ and 60’; within the boundaries of 95% confidence interval motorcycles have an EF = 111.1 ± 2.7 mg km−1 veh−1 ;modern, light vehicles have an EF = 90.6 ± 11.2 mg km−1 veh−1 ; old, light vehicles have an EF = 125.4 ± 18.5 mg km−1 veh−1 and heavy vehicles have an EF = 415.1 ± 31.2 mg km−1 veh−1 . Weshowed that upgrading old light vehicles is a promising scenario for reducing PM10 air pollution in Havana by between 10 and 17%.


Ait-Helal, W., et al., 2015. On-road measurements of NMVOCs and NO X: determination of light-duty vehicles emission factors from tunnel studies in Brussels city center. Atmos. Environ. 122, 799–807. Retrieved August 17, 2017. http://linkinghub. elsevier.com/retrieve/pii/S1352231015304088.

Alamilla-López, Jorge Luis, 2015. An approximation to the probability normal distribution and its inverse. Ing. Investig. Tecnol. 16 (4), 605–611. Retrieved September 7, 2017. http://linkinghub.elsevier.com/retrieve/pii/S1405774315000451.

Amato, F., et al., 2016. Traffic induced particle resuspension in Paris: emission factors and source contributions. Atmos. Environ. 129, 114–124. Retrieved August 17, 2017. http://linkinghub.elsevier.com/retrieve/pii/S1352231016300309.

Belalcazar, Carlos, Luis, Clappier, Alain, Blond, Nadège, Flassak, Thomas, Eichhorn, Joachim, 2010. An evaluation of the estimation of road traffic emission factors from tracer studies. Atmos. Environ. 44 (31), 3814–3822. Retrieved October 28, 2012. http://linkinghub.elsevier.com/retrieve/pii/S1352231010005170.

Belalcazar, Carlos, Luis, Fuhrer, Oliver, Dung Ho, Minh, Zarate, Erika, Clappier, Alain, 2009. Estimation of road traffic emission factors from a long term tracer study. Atmos. Environ. 43 (36), 5830–5837. Retrieved October 28, 2012. http:// linkinghub.elsevier.com/retrieve/pii/S1352231009006712.

Berkowicz, Ruwim, 2000. OSPM - a parameterised street pollution model. Environ. Monit. Assess. 65, 323–331. Retrieved. http://www.springerlink.com/index/ QL86805806122454.pdf.

Berkowicz, Ruwim, Danmark, Miljøundersøgelser, 1997. Modelling Traffic Pollution in Streets. Ministry of Environment and Energy, National Environmental Research Institute.

Berkowicz, Ruwim, Hertel, Ole, Larsen, Se, Sørensen, Nn, Nielsen, M., 1997. Modelling traffic pollution in streets. Natl. Environ. Res. Inst. Roskilde Den. 10129 (10136), 20. http://www.mst.dk/NR/rdonlyres/9D313499-E237-4C1A-ADC4-D31737E31613/0/ A11_ModellingTrafficPollutioninStreets.pdf.

Bond, Tami C., et al., 2004. A technology-based global inventory of black and organic carbon emissions from combustion. J. Geophys. Res. D Atmos. 109 (14), 1–43. Borrego, C., et al., 2016. Urban scale air quality modelling using detailed traffic emissions estimates. Atmos. Environ. 131, 341–351.

Brimblecombe, Peter, et al., 2015. Through-tunnel estimates of vehicle fleet emission factors. Atmos. Environ. 123, 180–189. Retrieved August 17, 2017. http:// linkinghub.elsevier.com/retrieve/pii/S1352231015305021.

Bruce, R., Coquilla, Rachael, Kuspa, Bethany, Padilla, Angelina, 2005. A Wind-tunnel Study of Air Re-entrainment from an Accidental Laboratory Exhaust Stack Release on the UC Davis Watershed Science Research Center.

Cadle, Steven H., et al., 1999. Composition of light-duty motor vehicle exhaust particulate matter in the denver, Colorado area. Environ. Sci. Technol. 33 (14), 2328–2339.

Chennamaneni, Pavan Rao, Echambadi, Raj, Hess, James D., Syam, Niladri, 2016. Diagnosing harmful collinearity in moderated regressions: a roadmap. Int. J. Res. Mark. 33 (1), 172–182. Retrieved August 30, 2017. http://linkinghub.elsevier.com/ retrieve/pii/S0167811615001068.

Durbin, Thomas D., Smith, Matthew R., Norbeck, Joseph M., Truex, Timothy J., 1999. Population density, particulate emission characterization, and impact on the particulate inventory of smoking vehicles in the south coast air quality management district. J. Air Waste Manag. Assoc. 49 (1), 28–38. Retrieved. http://www. engineeringvillage.com/blog/document.url?mid=cpx_ b753f811bff4dd3b0M75c12061377553&database=cpx%5Cnhttps://www. engineeringvillage.com/blog/document.url?mid=cpx_ b753f811bff4dd3b0M75c12061377553&database=cpx.

EPA, (United States Enviromental Protection Agency/Office of Transportation and Air Quality), 2008. Average in-Use Emission for Heavy-duty Trucks. Retrieved. https:// nepis.epa.gov/Exe/ZyNET.exe/P100EVY6.txt?ZyActionD=ZyDocument&Client= EPA&Index=2006 Thru 2010&Docs=&Query=&Time=&EndTime=& SearchMethod=1&TocRestrict=n&Toc=&TocEntry=&QField=&QFieldYear=& QFieldMonth=&QFieldDay=&UseQField=&IntQFieldOp=0&ExtQFieldOp=).

Ferm, Martin, Sjöberg, Karin, 2015. Concentrations and emission factors for PM 2.5 and PM 10 from road traffic in Sweden. Atmos. Environ. 119, 211–219. Retrieved August 17, 2017. http://linkinghub.elsevier.com/retrieve/pii/S135223101530282X.

Gertler, Alan W., Pierson, William R., Watson, John G., Bradow, Ronald L., 1991. Review and Reconciliation of on-Road Emission Factors in the South Coast Air Basin. Hansen, A.D.A., Rosen, H., 1990. Individual measurements of the emission factor of aerosol black carbon in automobile plumes. J. Air Waste Manag. Assoc. 40 (12), 1654–1657.

Huang, Yuan-dong, Zengf, Ning-bin, Liu, Ze-yu, Song, Ye, Xu, Xuan, 2016. Wind tunnel simulation of pollutant dispersion inside street canyons with galleries and multi-level flat roofs. J. Hydrodyn. Ser. B 28 (5), 801–810. Retrieved September 4, 2017. http:// linkinghub.elsevier.com/retrieve/pii/S1001605816606832.

Jaikumar, Rohit, Shiva Nagendra, S.M., Sivanandan, R., 2017. Modeling of real time exhaust emissions of passenger cars under heterogeneous traffic conditions. Atmos. Pollut. Res. 8 (1), 80–88. Retrieved August 31, 2017. http://linkinghub.elsevier. com/retrieve/pii/S1309104216300691.

Jung, Sungwoon, et al., 2017. Characterization of particulate matter from diesel passenger cars tested on chassis dynamometers. J. Environ. Sci. 54, 21–32. Retrieved August 17, 2017. http://linkinghub.elsevier.com/retrieve/pii/S1001074216301954.

Kakosimos, Konstantinos E., Hertel, Ole, Ketzel, Matthias, Berkowicz, Ruwim, 2010. Operational street pollution model (OSPM) - a review of performed application and validation studies, and future prospects. Environ. Chem. 7 (6), 485–503.

Kam, Winnie, Liacos, James W., Schauer, James J., Delfino, Ralph J., Sioutas, Constantinos, 2012. On-road emission factors of PM pollutants for light-duty vehicles (LDVs) based on urban street driving conditions. Atmos. Environ. 61, 378–386. Retrieved August 17, 2017. http://linkinghub.elsevier.com/retrieve/pii/ S1352231012007583.

Kastner-Klein, Petra, Fedorovich, Evgeni, Ketzel, Matthias, Berkowicz, Ruwim, Britter, Rex, 2003. The modelling of turbulence from traffic in urban dispersion models - Part II: evaluation against laboratory and full-scale concentration measurements in street canyons. Environ. Fluid Mech. 3 (2), 145–172.

Ketzel, Matthias, Berkowicz, Ruwim, Lohmeyer, Achim, 2000. Comparison of numerical street dispersion models with. Environ. Monit. Assess. 65 (1–2), 363–370. Retrieved. http://link.springer.com/article/10.1023%2FA%3A1006460724703.

Ketzel, Matthias, Wåhlin, Peter, Berkowicz, Ruwim, Palmgren, Finn, 2003. Particle and trace gas emission factors under urban driving conditions in copenhagen based on street and roof-level observations. Atmos. Environ. 37 (20), 2735–2749. Retrieved August 17, 2017. http://linkinghub.elsevier.com/retrieve/pii/S1352231003002450.

Keuken, M.P., et al., 2016. Particle number concentration near road traffic in amsterdam (The Netherlands): Comparison of standard and real-world emission factors. Atmos. Environ. 132, 345–355. Retrieved August 17, 2017. http://linkinghub.elsevier.com/ retrieve/pii/S1352231016301807.

Klose, S., et al., 2009. Particle number emissions of motor traffic derived from street canyon measurements in a central European city. Atmos. Chem. Phys. Discuss. 9 (1), 3763–3809. Retrieved August 17, 2017. http://www.atmos-chem-phys-discuss.net/ 9/3763/2009/.

Lawson, Douglas R., 1993. ‘Passing the test:’ human behavior and California's smog check program. Air Waste December 1993 1567–1575.

Li, Tiezhu, Chen, Xudong, Yan, Zhenxing, 2013. Comparison of fine particles emissions of light-duty gasoline vehicles from chassis dynamometer tests and on-road measurements. Atmos. Environ. 68, 82–91. Retrieved August 17, 2017. http://linkinghub. elsevier.com/retrieve/pii/S135223101201093X.

McCormick, Robert L., Graboski, Michael S., Alleman, Teresa L., Alvarez, Javier R., Duleep, K.G., 2003. Quantifying the emission benefits of opacity testing and repair of heavy-duty diesel vehicles. Environ. Sci. Technol. 37 (3), 630–637.

Moradpour, Maryam, Afshin, Hossein, Farhanieh, Bijan, 2017. A numerical investigation of reactive air pollutant dispersion in urban street canyons with tree planting. Atmos. Pollut. Res. 8 (2), 253–266. Retrieved August 17, 2017. http://linkinghub.elsevier. com/retrieve/pii/S1309104216302471.

Nakashima, Yoshihiro, Kajii, Yoshizumi, 2017. Determination of nitrous acid emission factors from a gasoline vehicle using a chassis dynamometer combined with incoherent broadband cavity-enhanced absorption spectroscopy. Sci. Total Environ. 575, 287–293. Retrieved August 17, 2017. http://linkinghub.elsevier.com/retrieve/ pii/S0048969716322161.

Ntziachristos, L., 2001. An empirical method for predicting exhaust emissions of regulated pollutants from future vehicle technologies. Atmos. Environ. 35 (11), 1985–1999. Retrieved August 21, 2017. http://linkinghub.elsevier.com/retrieve/ pii/S1352231000004714.

Ntziachristos, Leonidas, et al., 2012. EMEP/EEA Emission Inventory Guidebook 2009, Updated May 2012 1. (May).

Palmgren, Finn, Berkowicz, Ruwim, Ziv, Alexander, Hertel, Ole, 1999. Actual car fleet emissions estimated from urban air quality measurements and street pollution models. Sci. Total Environ. 235 (1–3), 101–109. Retrieved August 17, 2017. http:// linkinghub.elsevier.com/retrieve/pii/S0048969799001965.

Pang, Yanbo, Fuentes, Mark, Rieger, Paul, 2014. Trends in the emissions of volatile organic compounds (VOCs) from light-duty gasoline vehicles tested on chassis dynamometers in southern California. Atmos. Environ. 83, 127–135. Retrieved August 17, 2017. http://linkinghub.elsevier.com/retrieve/pii/S1352231013008303.

Rey deCastro, B., et al., 2008. The longitudinal dependence of black carbon concentration on traffic volume in an urban environment. J. Air Waste Manag. Assoc. 58 (7), 928–939. Retrieved. http://secure.awma.org/onlinelibrary/doihandler.aspx? doicode=10.3155-1047-3289.58.7.928.

Riccio, A., et al., 2016. Real-world automotive particulate matter and PAH emission factors and profile concentrations: results from an urban tunnel experiment in naples, Italy. Atmos. Environ. 141, 379–387. Retrieved August 17, 2017. http://linkinghub. elsevier.com/retrieve/pii/S1352231016305118.

Shunxi Deng and Christer Johansson. n.d. “Traffic Emission Factors of Particle Number Measured in a Street Canyon in Stockholm, Sweden.” Retrieved (https://www.dri. edu/images/stories/editors/leapfrog/techprog/IIe_4_Deng.pdf).

Smit, R., Kingston, P., Wainwright, D.H., Tooker, R., 2017. A tunnel study to validate motor vehicle emission prediction software in Australia. Atmos. Environ. 151, 188–199. Retrieved September 6, 2017. http://linkinghub.elsevier.com/retrieve/ pii/S1352231016309736.

Sokhi, Ranjeet S., et al., 2008. An integrated multi-model approach for air quality assessment: development and evaluation of the OSCAR air quality assessment system. Environ. Model. Softw. 23 (3), 268–281. Retrieved May 14, 2015. http://linkinghub. elsevier.com/retrieve/pii/S1364815207000813.

Subramanian, R., et al., 2009. Climate-relevant properties of diesel particulate Emissions: results from a piggyback study in Bangkok, Thailand climate-relevant properties of diesel particulate Emissions: results from a piggyback study in Bangkok, Thailand. Environ. Sci. Technol. 43 (11), 4213–4218.

Ubanwa, B., Burnette, A., Kishan, S., Fritz, S.G., 2003. Exhaust particulate matter emission factors and deterioration rate for in-use. J. Eng. Gas Turbines Power 125 (April), 513–523.

Vardoulakis, Sotiris, Fisher, Bernard E., Pericleous, Koulis, Gonzalez-Flesca, Norbert, 2003. Modelling air quality in street canyons: a review. Atmos. Environ. 37 (2), 155–182. Retrieved August 17, 2017. http://linkinghub.elsevier.com/retrieve/pii/ S1352231002008579.

Wang, Yuan, Huang, Zihan, Liu, Yujie, Yu, Qi, Ma, Weichun, 2017. Back-calculation of traffic-related PM10 emission factors based on roadside concentration measurements. Atmosphere 8 (6), 99. Retrieved. http://www.mdpi.com/2073-4433/8/6/99.

Yan, Fang, Winijkul, Ekbordin, Bond, Tami C., Streets, David G., 2014. Global emission projections of particulate matter (PM): II. Uncertainty analyses of on-road vehicle exhaust emissions. Atmos. Environ. 87, 189–199. Retrieved August 17, 2017. http:// linkinghub.elsevier.com/retrieve/pii/S1352231014000703.

Yan, Fang, Winijkul, Ekbordin, Jung, Soonkyu, Bond, Tami C., Streets, David G., 2011. Global emission projections of particulate matter (PM): I. Exhaust emissions from onroad vehicles. Atmos. Environ. 45 (28), 4830–4844. Retrieved August 17, 2017. http://linkinghub.elsevier.com/retrieve/pii/S135223101100611X.

Yanowitz, Janet, Mccormick, Robert L., Graboski, Michael S., 2000. “In-Use emissions from heavy-duty diesel vehicles. Environ. Sci. Technol. 34 (5), 729–740. http://dx. doi.org/10.1021/es990903w. Retrieved.

Zarate, Erika, Carlos Belalcazar, Luis, Clappier, Alain, Manzi, V., Bergh, Hubert van den, 2007. Air quality modelling over Bogota city: combined techniques to estimate and evaluate emission inventories. Atmos. Environ. 41 (29), 6302–6318. Retrieved October 14, 2012. http://linkinghub.elsevier.com/retrieve/pii/ S1352231007002403.

Zhang, Yanli, et al., 2015. Emission factors of fine particles, carbonaceous aerosols and traces gases from road vehicles: recent tests in an urban tunnel in the pearl river delta, China. Atmos. Environ. 122, 876–884. Retrieved August 17, 2017. http:// linkinghub.elsevier.com/retrieve/pii/S1352231015302697.

Zhang, Yi, Stedman, Donald H., Bishop, Gary A., Guenther, Paul L., Beaton, Stuart P., 1995. Worldwide on-road vehicle exhaust emissions study by remote sensing. Environ. Sci. Technol. 29 (9), 2286–2294. http://dx.doi.org/10.1021/es00009a020. Retrieved.


Atmospheric Pollution Research
  • ISSN: 1309-1042
  • Yayın Aralığı: Yılda 12 Sayı
  • Başlangıç: 2010


Sayıdaki Diğer Makaleler

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