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Development of a Static Model to Identify Best Management Practices for Trace Metals from Non-Exhaust Traffic Emissions

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Abstract

Risk through exposure to non-exhaust traffic emissions continues to increase as both the number of vehicles and traveling distances continue to increase with global urbanization. To better understand their impacts on the urban environment, a contaminant pathway was developed to describe important release mechanisms, transitory environmental media, and exposure media. Sources of contaminants were identified and characterized using published literature values. Concentrations of non-exhaust sources were used in conjunction with mean emission factors to estimate contaminant loads from individual vehicles (μg/km/veh). Published daily vehicle distances traveled were used to estimate total annual emissions (kg/yr) for the United States and Houston metropolitan area. This equates to approximately 5.1 million kg of Cu, 12.8 million kg of Zn, 4.9 million kg of Pb, and 2400 kg of Cd being released each year in the United States. Tires are responsible for 92% of total Zn emissions, with heavy-duty vehicles responsible for 77% of these emissions. Tires are also responsible for 86% of total Cd emissions. Brake dust contributes to 99.9% of Cu emissions. Wheel weights contribute approximately 94% of total Pb emissions. Identified best management practices include: 1. installation of grass buffer zones (e.g., rain gardens, vegetated swales) immediately adjacent to road surfaces, and 2. permeable pavements and green roofs near major highways. There are several limitations, assumptions and uncertainties associated with the study due to its static nature. However, evidence is substantial for the need to create new policies that address the pollution created by non-exhaust traffic emissions.

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References

  • Acosta JA, Faz Á, Kalbitz K, Jansen B, Martínez-Martínez S (2011) Heavy metal concentrations in particle size fractions from street dust of Murcia (Spain) as the basis for risk assessment. J Environ Monit 13(11):3087–3096

    Article  Google Scholar 

  • Adachi K, Tainosho Y (2004) Characterization of heavy metal particles embedded in tire dust. Environ Int 30(8):1009–1017

    Article  Google Scholar 

  • Alemani M, Nosko O, Metinoz I, Olofsson U (2016) A study on emission of airborne wear particles from car brake friction pairs. SAE International Journal of Materials and Manufacturing 1:147e157. https://doi.org/10.4271/2015-01-2665

  • Amato F, Pandolfi M, Alastuey A, Lozano A, González JC, Querol X (2013) Impact of traffic intensity and pavement aggregate size on road dust particles loading. Atmos Environ 77:711–717

    Article  Google Scholar 

  • ATSDR U (2007) Toxicological profile for lead. US Department of Health and Human Services, public health service, Agency for Toxic Substances and Disease Registry. In: Atlanta (GA) available from www.atsdr.cdc.gov/toxprofiles/tp.asp?id=96&tid=22

    Google Scholar 

  • Bennett CR, Greenwood ID (2001) Volume seven: modelling road user and environmental effects in HDM-4. The highway development and management series. Report to the International Study of Highway Development and Management Tools, University of Birmingham

  • Campbell PM, Corneau E, Nishimura D, Teng E, Ekoualla D (2018) Cost-benefit analysis for a lead wheel weight phase-out in Canada. Sci Total Environ 637:79–90

    Article  Google Scholar 

  • Davis AP, Shokouhian M, Ni S (2001) Loading estimates of lead, copper, cadmium, and zinc in urban runoff from specific sources. Chemosphere 44(5):997–1009

    Article  Google Scholar 

  • Davis B, Birch G (2010) Comparison of heavy metal loads in stormwater runoff from major and minor urban roads using pollutant yield rating curves. Environ Pollut 158(8):2541–2545

    Article  Google Scholar 

  • EEA (2003) Atmospheric emission inventory guidebook, 3rd edition. Group 7: road transport. European Environmental Agency. http://www.eea.europa.eu/publications/EMEPCORINAIR5/page016.html. Accessed 19 Mar 2019

  • European Commission, 2000. EC directive 2000/53/EC. The “ELV Directive” 18th September 2000. https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=CONSLEG:2000L0053:20050701:EN:PDF

  • Fiala MJ (2017) Development of a transport model for trace metals from non-exhaust traffic emissions. Doctoral dissertation, Texas Southern University

  • Filip, P., Kovarik, L., & Wright, M. A. (1997). Automotive brake lining characterization (no. 973024). SAE Technical Paper

  • FHWA. (2015). Public road length: miles by type of surface and ownership/functional system, national summary. Federal Highway Administration (FHWA). United States Department of Transportation. https://www.fhwa.dot.gov/policyinformation/statistics/2015/hm12.cfm

  • FHWA. (1998). Materials notebook. Chapter 5: Portland cement concrete. Federal Highway Administration. https://www.fhwa.dot.gov/pavement/materials/matnote.cfm

    Google Scholar 

  • Furumai H, Balmer H, Boller M (2002) Dynamic behavior of suspended pollutants and particle size distribution in highway runoff. Water Sci Technol 46(11–12):413–418

    Article  Google Scholar 

  • Garg BD, Cadle SH, Mulawa PA, Groblicki PJ (2000) Brake wear particulate matter emissions. Environmental Science & Technology 34(21):4463–4469

    Article  Google Scholar 

  • Gulson B, Taylor A (2017) A simple lead dust fall method predicts children's blood lead level: new evidence from Australia. Environ Res 159:76–81

    Article  Google Scholar 

  • Gustafsson M, Blomqvist G, Gudmundsson A, Dahl A, Jonsson P, Swietlicki E (2009) Factors influencing PM10 emissions from road pavement wear. Atmos Environ 43(31):4699–4702

    Article  Google Scholar 

  • Gustafsson M (2018) Review of road wear emissions: a review of road emission measurement studies: identification of gaps and future needs. Non-Exhaust Emissions, p 161–181

  • Hagino H, Oyama M, Sasaki S (2016) Laboratory testing of airborne break wear particle emissions using a dynamometer system under urban city driving conditions. Atmos Environ 131:269–278

    Article  Google Scholar 

  • Hammond PB, Dietrich KN (1990) Lead exposure in early life: health consequences. Reviews of Environmental Contamination and Toxicology. Springer, New York, NY, p 91–124

  • Harrison RM, Hester RE (2017) Environmental impacts of road vehicles: past, present and future. Royal Society of Chemistry, London, UK, p 2017

    Book  Google Scholar 

  • Hwang HM, Fiala MJ, Park D, Wade TL (2016) Review of pollutants in urban road dust and stormwater runoff: part 1. Heavy metals released from vehicles. Int J Urban Sci 20(3):334–360

    Article  Google Scholar 

  • Hwang HM, Fiala MJ, Park D, Wade TL (2018) Review of pollutants in urban road dust and stormwater runoff: part II. Organic contaminants from vehicles and road management. Int J Urban Sci:1–19. https://doi.org/10.1080/12265934.2018.1538811

  • Kennedy P, Gadd J, Moncrieff I (2002) Emission factors for contaminants released by motor vehicles in New Zealand. Prepared for the New Zealand Ministry of Transport and Infrastructure Auckland

  • Kukutschová J, Moravec P, Tomásek V, Matejka V, Smolík J, Schwarz J et al (2011) On airborne nano/microsized wear particles released from low-metallic automotive brakes. Environ Pollut 159(4):998e1006 Elsevier

    Article  Google Scholar 

  • Kukutschová J, Filip P (2018) Review of brake wear emissions: a review of brake emission measurement studies: identification of gaps and future needs. Non-Exhaust Emissions, p 123–146

  • Kuo CY, Wang JY, Liu WT, Lin PY, Tsai CT, Cheng MT (2012) Evaluation of the vehicle contributions of metals to indoor environments. Journal of Exposure Science and Environmental Epidemiology 22(5):489–495

    Article  Google Scholar 

  • Lee PW, Filip P (2013) Friction and wear of Cu-free and Sb-free environmental friendly automotive brake materials. Wear 302(1–2):1404–1413

  • Needleman HL, Schell A, Bellinger D, Leviton A, Allred EN (1990) The long-term effects of exposure to low doses of lead in childhood: an 11-year follow-up report. N Engl J Med 322(2):83–88

    Article  Google Scholar 

  • Padoan E, Ajmone-Marsan F, Querol X, Amato F (2017) An empirical model to predict road dust emissions based on pavement and traffic characteristics. Environ Pollut 237:713–720

    Article  Google Scholar 

  • Padoan E, Amato F (2018) Vehicle non-exhaust emissions: impact on air quality. In: Non-Exhaust Emissions, pp 21–65. https://doi.org/10.1016/B978-0-12-811770-5.00002-9

    Chapter  Google Scholar 

  • Panko J, Kreider M, Unice K (2018) Review of tire wear emissions: a review of tire emission measurement studies: identification of gaps and future needs. Non-Exhaust Emissions, p 147–160

  • Penkała M, Ogrodnik P, Rogula-Kozłowska W (2018) Particulate matter from the road surface abrasion as a problem of non-exhaust emission control. Environments 5(1):9

    Article  Google Scholar 

  • Root RA (2000) Lead loading of urban streets by motor vehicle wheel weights. Environ Health Perspect 108(10):937–940

    Article  Google Scholar 

  • Sanders PG, Xu N, Dalka TM, Maricq MM (2003) Airborne brake wear debris: size distribution, composition, and a comparison of dynamometer and vehicle tests. Environmental Science Technology 37:4060–4069

    Article  Google Scholar 

  • Steiner M, Boller M, Schulz T, Pronk W (2007) Modelling heavy metal fluxes from traffic into the environment. J Environ Monit 9(8):847–854

  • Thorpe A, Harrison RM (2008) Sources and properties of non-exhaust particulate matter from road traffic: a review. Sci Total Environ 400(1):270–282

    Article  Google Scholar 

  • TxDOT. 2018. Houston District Statistics. Retrieved from https://www.txdot.gov/inside-txdot/division/finance/discos.html?dist=HOU

  • US EPA. (N.D.) IRIS. Integrated risk information system (IRIS). United States Environmental Protection Agency https://www.epa.gov/iris (accessed 2/2019)

  • US DOT. (2018). Bureau of Transportation Statistics. National Transportation Statistics, United States Department of Transportation. Retrieved from https://www.bts.gov/sites/bts.dot.gov/files/docs/browse-statistical-products-and-data/national-transportation-statistics/223001/ntsentire2018q4.pdf

  • Wang Q, Zhao HH, Chen JW, Gu KD, Zhang YZ, Zhu YX, Zhou YK, Ye LX (2009) Adverse health effects of lead exposure on children and exploration to internal lead indicator. Sci Total Environ 407(23):5986–5992

    Article  Google Scholar 

  • Washington State Department of Ecology. (N.D.) Lead wheel weights are banned. https://fortress.wa.gov/ecy/publications/SummaryPages/1207029.html. Accessed 19 Mar 2019

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Fiala, M., Hwang, HM. Development of a Static Model to Identify Best Management Practices for Trace Metals from Non-Exhaust Traffic Emissions. Environ. Process. 6, 377–389 (2019). https://doi.org/10.1007/s40710-019-00367-w

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