Source-specific pollution exposure and associations with pulmonary response in the Atlanta Commuters Exposure Studies

Abstract

Concentrations of traffic-related air pollutants are frequently higher within commuting vehicles than in ambient air. Pollutants found within vehicles may include those generated by tailpipe exhaust, brake wear, and road dust sources, as well as pollutants from in-cabin sources. Source-specific pollution, compared to total pollution, may represent regulation targets that can better protect human health. We estimated source-specific pollution exposures and corresponding pulmonary response in a panel study of commuters. We used constrained positive matrix factorization to estimate source-specific pollution factors and, subsequently, mixed effects models to estimate associations between source-specific pollution and pulmonary response. We identified four pollution factors that we named: crustal, primary tailpipe traffic, non-tailpipe traffic, and secondary. Among asthmatic subjects (N = 48), interquartile range increases in crustal and secondary pollution were associated with changes in lung function of −1.33% (95% confidence interval (CI): −2.45, −0.22) and −2.19% (95% CI: −3.46, −0.92) relative to baseline, respectively. Among non-asthmatic subjects (N = 51), non-tailpipe pollution was associated with pulmonary response only at 2.5 h post-commute. We found no significant associations between pulmonary response and primary tailpipe pollution. Health effects associated with traffic-related pollution may vary by source, and therefore some traffic pollution sources may require targeted interventions to protect health.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

References

  1. 1.

    Mar TF, Ito K, Koenig JQ, Larson TV, Eatough DJ, Henry RC, et al. PM source apportionment and health effects. 3. Investigation of inter-method variations in associations between estimated source contributions of PM2.5 and daily mortality in Phoenix, AZ. J Expo Sci Environ Epidemiol. 2006;16:311–20.

    Article  PubMed  CAS  Google Scholar 

  2. 2.

    Kioumourtzoglou M-A, Coull BA, Dominici F, Koutrakis P, Schwartz J, Suh H. The impact of source contribution uncertainty on the effects of source-specific PM2. 5 on hospital admissions A case study in Boston, MA. J Expo Sci Environ Epidemiol. 2014;24:365–71.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  3. 3.

    Bell ML, Ebisu K, Leaderer BP, Gent JF, Lee HJ, Koutrakis P, et al. Associations of PM2.5 Constituents and Sources with Hospital Admissions: Analysis of Four Counties in Connecticut and Massachusetts (USA) for Persons > = 65 Years of Age. Environ Health Perspect. 2013;122:138–44.

    PubMed  PubMed Central  Article  Google Scholar 

  4. 4.

    Gass K, Balachandran S, Chang HH, Russell AG, Strickland MJ. Ensemble-based source apportionment of fine particulate matter and emergency department visits for pediatric asthma. Am J Epidemiol. 2015;181:504–12.

    Article  PubMed  PubMed Central  Google Scholar 

  5. 5.

    US Department of Transportation. Summary of travel trends: 2009 National Household Survey. Federal Highway Administration: Washington, D.C., 2011.

  6. 6.

    HEI Panel on the Health Effects of Traffic-Related Air Pollution. Traffic-related air pollution: a critical review of the literature on emissions, exposure, and health effects. Health Eff Inst. 2010;17:85–89.

    Google Scholar 

  7. 7.

    Adams HS, Nieuwenhuijsen MJ, Colvile RN, McMullen MA, Khandelwal P. Fine particle (PM2.5) personal exposure levels in transport microenvironments, London. Sci Total Environ. 2001;279:29–44.

    Article  PubMed  CAS  Google Scholar 

  8. 8.

    Zhu Y, Eiguren-Fernandez A, Hinds WC, Miguel AH. In-cabin commuter exposure to ultrafine particles on Los Angeles freeways. Environ Sci Technol. 2007;41:2138–45.

    Article  PubMed  CAS  Google Scholar 

  9. 9.

    Rodes C, Sheldon L, Whitaker D, Clayton A, Fitzgerald K Measuring concentrations of selected air pollutants inside California vehicles. Final Report. Research Triangle Inst., Research Triangle Park, NC (US); Sierra Research, Inc., Sacramento, CA (US); Aerosol Dynamics, Inc., Berkeley, CA (US); Nevada Univ. System, Reno, NV (US); California State Air Resources Board, Sacramento, CA (US); Research Triangle Inst., Durham, NC (US); 1999.

  10. 10.

    Krall JR, Anderson GB, Dominici F, Bell ML, Peng RD. Short-term exposure to particulate matter constituents and mortality in a national study of US urban communities. Environ Health Perspect. 2013;121:1148–53.

    PubMed  PubMed Central  Article  Google Scholar 

  11. 11.

    Ito K, Mathes R, Ross Z, Nadas A, Thurston G, Matte T. Fine particulate matter constituents associated with cardiovascular hospitalizations and mortality in New York City. Environ Health Perspect. 2011;119:467–73.

    Article  PubMed  CAS  Google Scholar 

  12. 12.

    Bell ML, Belanger K, Ebisu K, Gent JF, Lee HJ, Koutrakis P, et al. Prenatal exposure to fine particulate matter and birth weight: variations by particulate constituents and sources. Epidemiology . 2010;21:884–91.

    Article  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Baccarelli AA, Zheng Y, Zhang X, Chang D, Liu L, Wolf KR, et al. Air pollution exposure and lung function in highly exposed subjects in Beijing, China: a repeated-measure study. Part Fibre Toxicol. 2014;11:51.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  14. 14.

    Mirowsky JE, Peltier RE, Lippmann M, Thurston G, Chen L-C, Neas L, et al. Repeated measures of inflammation, blood pressure, and heart rate variability associated with traffic exposures in healthy adults. Environ Health. 2015;14:66.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. 15.

    Zhou Y-M, Zhong C-Y, Kennedy IM, Pinkerton KE. Pulmonary responses of acute exposure to ultrafine iron particles in healthy adult rats. Environ Toxicol. 2003;18:227–35.

    Article  PubMed  CAS  Google Scholar 

  16. 16.

    Sørensen M, Schins RPF, Hertel O, Loft S. Transition metals in personal samples of PM2.5 and oxidative stress in human volunteers. Cancer Epidemiol Biomarkers Prev. 2005;14:1340–3.

    Article  PubMed  Google Scholar 

  17. 17.

    Gent JF, Koutrakis P, Belanger K, Triche E, Holford TR, Bracken MB, et al. Symptoms and medication use in children with asthma and traffic-related sources of fine particle pollution. Environ Health Perspect. 2009;117:1168–74.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  18. 18.

    Thorpe A, Harrison RM. Sources and properties of non-exhaust particulate matter from road traffic: a review. Sci Total Environ. 2008;400:270–82.

    Article  PubMed  CAS  Google Scholar 

  19. 19.

    Schauer JJ, Lough GC, Shafer MM, Christensen WF, Arndt MF, DeMinter JT, et al. Characterization of metals emitted from motor vehicles. Res Rep Health Eff Inst. 2006;133:1–76.

  20. 20.

    Sarnat JA, Marmur A, Klein M, Kim E, Russell AG, Sarnat SE, et al. Fine particle sources and cardiorespiratory morbidity: an application of chemical mass balance and factor analytical source-apportionment methods. Environ Health Perspect. 2008;116:459–66.

    PubMed  PubMed Central  Article  Google Scholar 

  21. 21.

    Ostro B, Tobias A, Querol X, Alastuey A, Amato F, Pey J, et al. The effects of particulate matter sources on daily mortality: a case-crossover study of Barcelona, Spain. Environ Health Perspect. 2011;119:1781–7.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. 22.

    Ito K, Ross Z, Zhou J, Nadas A, Lippmann M, Thurston G NPACT Study 3. Time-series analysis of mortality, hospitalizations, and ambient PM2.5 and its components. In: National Particle Component Toxicity (NPACT) Initiative: integrated epidemiologic and toxicologic studies of the health effects of particulate matter components. Health Eff Inst.: Boston, MA, 2013. Research Report177.

  23. 23.

    Peng RD, Bell ML. Spatial misalignment in time series studies of air pollution and health data. Biostatistics . 2010;11:720–40.

    Article  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Greenwald R, Bergin MH, Yip F, Boehmer T, Kewada P, Shafer MM, et al. On-roadway In-cabin exposure to particulate matter: measurement results using both continuous and time-integrated sampling approaches. Aerosol Sci Technol. 2014;48:664–75.

    Article  CAS  Google Scholar 

  25. 25.

    Sarnat JA, Golan R, Greenwald R, Raysoni AU, Kewada P, Winquist A, et al. Exposure to traffic pollution, acute inflammation and autonomic response in a panel of car commuters. Environ Res. 2014;133:66–76.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  26. 26.

    Berhane K, Zhang Y, Salam MT, Eckel SP, Linn WS, Rappaport EB, et al. Longitudinal effects of air pollution on exhaled nitric oxide: the Children’s Health Study. Occup Environ Med. 2014;71:507–13.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  27. 27.

    Barath S, Mills NL, Ädelroth E, Olin A-C, Blomberg A. Diesel exhaust but not ozone increases fraction of exhaled nitric oxide in a randomized controlled experimental exposure study of healthy human subjects. Environ Health. 2013;12:1–7.

  28. 28.

    Peng C, Luttmann-Gibson H, Zanobetti A, Cohen A, De Souza C, Coull BA, et al. Air pollution influences on exhaled nitric oxide among people with type II diabetes. Air Qual Atmosphere Health. 2016;9:265–73.

    Article  CAS  Google Scholar 

  29. 29.

    Hankinson JL, Odencrantz JR, Fedan KB. Spirometric reference values from a sample of the general US population. Am J Respir Crit Care Med. 1999;159:179–87.

    Article  PubMed  CAS  Google Scholar 

  30. 30.

    Raghunathan TE, Lepkowski JM, Van Hoewyk J, Solenberger P. A multivariate technique for multiply imputing missing values using a sequence of regression models. Surv Methodol. 2001;27:85–96.

    Google Scholar 

  31. 31.

    Paatero P, Tapper U. Positive matrix factorization: a non-negative factor model with optimal utilization of error estimates of data values. Environmetrics . 1994;5:111–26.

    Article  Google Scholar 

  32. 32.

    Amato F, Hopke PK. Source apportionment of the ambient PM2.5 across St. Louis using constrained positive matrix factorization. Atmos Environ. 2012;46:329–37.

    Article  CAS  Google Scholar 

  33. 33.

    Paatero P. The multilinear engine: A table-driven, least squares program for solving multilinear problems, including the n-way parallel factor analysis model. J Comput Graph Stat. 1999;8:854–88.

    Google Scholar 

  34. 34.

    Norris G, Vedantham R, Wade K, Zahn P, Brown S, Paatero P, et al. Guidance document for PMF applications with the multilinear engine. Prepared for the US Environmental Protection Agency, Resarch Triangle Park NC. Triangle Park, NC: National Exposure Resarch Laboratory; 2009.

  35. 35.

    Krall JR, Chang HH, Sarnat SE, Peng RD, Waller LA. Current methods and challenges for epidemiological studies of the associations between chemical constituents of particulate matter and health. Curr Environ Health Rep. 2015;2:388–98.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. 36.

    US Energy Information Administration. Residential energy consumption survey [Internet]. https://www.eia.gov/consumption/residential/ (2015).

  37. 37.

    Peltier RE, Hsu S-I, Lall R, Lippmann M. Residual oil combustion: a major source of airborne nickel in New York City. J Expo Sci Environ Epidemiol. 2009;19:603–12.

    Article  PubMed  CAS  Google Scholar 

  38. 38.

    Rahimi B, Semnani A, Nezamzadeh-Ejhieh A, Shakoori Langeroodi H, Hakim Davood M. Monitoring of the physical and chemical properties of a gasoline engine oil during its usage. J Anal Methods Chem. 2012;2012:1–8.

    Article  CAS  Google Scholar 

  39. 39.

    Agarwal AK, Singh AP, Lukose J, Gupta T. Characterization of exhaust particulates from diesel fueled homogenous charge compression ignition combustion engine. J Aerosol Sci. 2013;58:71–85.

    Article  CAS  Google Scholar 

  40. 40.

    Laschober C, Limbeck A, Rendl J, Puxbaum H. Particulate emissions from on-road vehicles in the Kaisermühlen-tunnel (Vienna, Austria). Atmos Environ. 2004;38:2187–95.

    Article  CAS  Google Scholar 

  41. 41.

    Park S, Cho SY, Bae M-S. Source identification of water-soluble organic aerosols at a roadway site using a positive matrix factorization analysis. Sci Total Environ. 2015;533:410–21.

    Article  PubMed  CAS  Google Scholar 

  42. 42.

    Kim E Improving source identification of fine particles in a rural northeastern U.S. area utilizing temperature-resolved carbon fractions. J Geophys Res. 2004. https://doi.org/10.1029/2003JD004199.

  43. 43.

    Kim E, Hopke PK, Edgerton ES. Source identification of Atlanta aerosol by positive matrix factorization. J Air Waste Manag Assoc. 2003;53:731–9.

    Article  PubMed  CAS  Google Scholar 

  44. 44.

    Balachandran S, Pachon JE, Hu Y, Lee D, Mulholland JA, Russell AG. Ensemble-trained source apportionment of fine particulate matter and method uncertainty analysis. Atmos Environ. 2012;61:387–94.

    Article  CAS  Google Scholar 

  45. 45.

    Balachandran S, Chang HH, Pachon JE, Holmes HA, Mulholland JA, Russell AG. Bayesian-based ensemble source apportionment of PM2. 5. Environ Sci Technol. 2013;47:13511–8.

    Article  PubMed  CAS  Google Scholar 

  46. 46.

    Andersen ZJ, Wahlin P, Raaschou-Nielsen O, Scheike T, Loft S. Ambient particle source apportionment and daily hospital admissions among children and elderly in Copenhagen. J Expo Sci Environ Epidemiol. 2007;17:625–36.

    Article  PubMed  CAS  Google Scholar 

  47. 47.

    Peng RD, Bell ML, Geyh AS, McDermott A, Zeger SL, Samet JM, et al. Emergency admissions for cardiovascular and respiratory diseases and the chemical composition of fine particle air pollution. Environ Health Perspect. 2009;117:957–63.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  48. 48.

    McCreanor J, Cullinan P, Nieuwenhuijsen MJ, Stewart-Evans J, Malliarou E, Jarup L, et al. Respiratory effects of exposure to diesel traffic in persons with asthma. N Engl J Med. 2007;357:2348–58.

    Article  PubMed  CAS  Google Scholar 

  49. 49.

    Fang T, Verma V, Bates JT, Abrams J, Klein M, Strickland MJ, et al. Oxidative potential of ambient water-soluble PM in the southeastern United States: contrasts in sources and health associations between ascorbic acid (AA) and dithiothreitol (DTT) assays. Atmospheric. Chem Phys. 2016;16:3865–79.

    CAS  Google Scholar 

  50. 50.

    Bates JT, Weber RJ, Abrams J, Verma V, Fang T, Klein M, et al. Reactive oxygen species generation linked to sources of atmospheric particulate matter and cardiorespiratory effects. Environ Sci Technol. 2015;49:13605–12.

    Article  PubMed  CAS  Google Scholar 

  51. 51.

    Delfino RJ, Staimer N, Tjoa T, Gillen DL, Schauer JJ, Shafer MM. Airway inflammation and oxidative potential of air pollutant particles in a pediatric asthma panel. J Expo Sci Environ Epidemiol. 2013;23:466–73.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. 52.

    Yang A, Janssen NAH, Brunekreef B, Cassee FR, Hoek G, Gehring U. Children’s respiratory health and oxidative potential of PM 2.5: the PIAMA birth cohort study. Occup Environ Med. 2016;73:154–60.

    Article  PubMed  Google Scholar 

  53. 53.

    Zuurbier M, Hoek G, Oldenwening M, Meliefste K, van den Hazel P, Brunekreef B. Respiratory Effects of Commutersʼ Exposure to Air Pollution in Traffic. Epidemiology . 2011;22:219–27.

    Article  PubMed  Google Scholar 

  54. 54.

    Kubesch NJ, de Nazelle A, Westerdahl D, Martinez D, Carrasco-Turigas G, Bouso L, et al. Respiratory and inflammatory responses to short-term exposure to traffic-related air pollution with and without moderate physical activity. Occup Environ Med. 2015 ;72:284–93.

    Article  PubMed  Google Scholar 

  55. 55.

    Chiu Y-HM, Garshick E, Hart JE, Spiegelman D, Dockery DW, Smith TJ, et al. Occupational vehicle-related particulate exposure and inflammatory markers in trucking industry workers. Environ Res. 2016;148:310–7.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. 56.

    Riediker M, Cascio WE, Griggs TR, Herbst MC, Bromberg PA, Neas L, et al. Particulate matter exposure in cars is associated with cardiovascular effects in healthy young men. Am J Respir Crit Care Med. 2004;169:934–40.

    Article  PubMed  Google Scholar 

  57. 57.

    Wu W, Muller R, Berhane K, Fruin S, Liu F, Jaspers I, et al. Inflammatory response of monocytes to ambient particles varies by highway proximity. Am J Respir Cell Mol Biol. 2014;51:802–9.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  58. 58.

    Owoade KO, Hopke PK, Olise FS, Adewole OO, Ogundele LT, Fawole OG. Source apportionment analyses for fine (PM 2.5) and coarse (PM 2.5–10) mode particulate matter (PM) measured in an urban area in southwestern Nigeria. Atmos Pollut Res. 2016;7:843–57.

    Article  Google Scholar 

  59. 59.

    Pandolfi M, Gonzalez-Castanedo Y, Alastuey A, de la Rosa JD, Mantilla E, de la Campa AS, et al. Source apportionment of PM10 and PM2.5 at multiple sites in the strait of Gibraltar by PMF: impact of shipping emissions. Environ Sci Pollut Res. 2011;18:260–9.

    Article  CAS  Google Scholar 

  60. 60.

    Park ES, Hopke PK, Oh M-S, Symanski E, Han D, Spiegelman CH. Assessment of source-specific health effects associated with an unknown number of major sources of multiple air pollutants: a unified Bayesian approach. Biostatistics. 2014;15:484–97.

    Article  PubMed  Google Scholar 

  61. 61.

    Henry RC, Park ES, Spiegelman CH. Comparing a new algorithm with the classic methods for estimating the number of factors. Chemom Intell Lab Syst. 1999;48:91–97.

    Article  CAS  Google Scholar 

  62. 62.

    Hopke PK, Ito K, Mar T, Christensen WF, Eatough DJ, Henry RC, et al. PM source apportionment and health effects: 1. Intercomparison of source apportionment results. J Expo Sci Environ Epidemiol. 2006;16:275–86.

    Article  PubMed  CAS  Google Scholar 

  63. 63.

    Ito K, Christensen WF, Eatough DJ, Henry RC, Kim E, Laden F, et al. PM source apportionment and health effects: 2. An investigation of intermethod variability in associations between source-apportioned fine particle mass and daily mortality in Washington, DC. J Expo Sci Environ Epidemiol. 2006;16:300–10.

    Article  PubMed  CAS  Google Scholar 

  64. 64.

    Hackstadt AJ, Peng RD. A Bayesian multivariate receptor model for estimating source contributions to particulate matter pollution using national databases. Environmetrics. 2014;25:513–27.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  65. 65.

    Nikolov MC, Coull BA, Catalano PJ, Godleski JJ. An informative Bayesian structural equation model to assess source-specific health effects of air pollution. Biostatistics . 2007;8:609–24.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

Research reported in this publication was supported by a Clean Air Research Center grant to Emory University and the Georgia Institute of Technology from the US Environmental Protection Agency (USEPA, RD834799). This publication was also made possible by a grant to Emory University from the National Institute of Environmental Health Sciences (T32ES012160). R Golan gratefully acknowledges support by a post-doctoral fellowship from the Environment and Health Fund, Jerusalem, Israel. The content of this publication is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the USEPA. Further, USEPA does not endorse the purchase of any commercial products or services mentioned in the publication.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Jenna R. Krall.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Electronic supplementary material

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Krall, J.R., Ladva, C.N., Russell, A.G. et al. Source-specific pollution exposure and associations with pulmonary response in the Atlanta Commuters Exposure Studies. J Expo Sci Environ Epidemiol 28, 337–347 (2018). https://doi.org/10.1038/s41370-017-0016-7

Download citation

Keywords

  • Source apportionment
  • Pulmonary health
  • Air pollution
  • Traffic pollution
  • Commuting
  • On-road exposures

Further reading