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Modelling of human exposure to air pollution in the urban environment: a GPS-based approach

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Abstract

The main objective of this work was the development of a new modelling tool for quantification of human exposure to traffic-related air pollution within distinct microenvironments by using a novel approach for trajectory analysis of the individuals. For this purpose, mobile phones with Global Positioning System technology have been used to collect daily trajectories of the individuals with higher temporal resolution and a trajectory data mining, and geo-spatial analysis algorithm was developed and implemented within a Geographical Information System to obtain time–activity patterns. These data were combined with air pollutant concentrations estimated for several microenvironments. In addition to outdoor, pollutant concentrations in distinct indoor microenvironments are characterised using a probabilistic approach. An example of the application for PM2.5 is presented and discussed. The results obtained for daily average individual exposure correspond to a mean value of 10.6 and 6.0–16.4 μg m−3 in terms of 5th–95th percentiles. Analysis of the results shows that the use of point air quality measurements for exposure assessment will not explain the intra- and inter-variability of individuals’ exposure levels. The methodology developed and implemented in this work provides time-sequence of the exposure events thus making possible association of the exposure with the individual activities and delivers main statistics on individual’s air pollution exposure with high spatio-temporal resolution.

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References

  • Allen D (2011) Getting to Know ArcGIS ModelBuilder. ESRI PR. 362 pp

  • Ashbrook D, Thad S (2003) Using GPS to learn significant locations and predict movement across multiple users. Pers Ubiquit Comput 7:275–286

    Article  Google Scholar 

  • Baklanov A, Hänninen O, Slordal LH, Kukkonen J, Bjergene N, Fay B, Finardi S, Hoe SC, Jantunen M, Karppinen A, Rasmussen A, Skouloudis A, Sokhi RS, Sorensen JH, Odegaard V (2007) Integrated systems for forecasting urban meteorology, air pollution and population exposure. Atmos Chem Phys 7:855–874

    Article  CAS  Google Scholar 

  • Ballesta PP, Field RA, Fernandez-Patier R, Galan-Madruga D, Connolly R, Caracena AB, De Saegera E (2008) An approach for the evaluation of exposure patterns of urban populations to air pollution. Atmos Environ 42:5350–5364

    Article  Google Scholar 

  • Beckx C, Int Panis L, Arentze T, Janssens D, Torfs R, Broekx S, Wets G (2009) A dynamic activity-based population modelling approach to evaluate exposure to air pollution: methods and application to a Dutch urban area. Environ Impact Assess Rev 29:179–185

    Article  Google Scholar 

  • Bock HH (1996) Probabilistic models in cluster analysis. Comput Stat Data Anal 23:5–28

    Article  Google Scholar 

  • Brauer M, Hoek G, Van Vliet P, Meliefste K, Fisher P, Wijga A, Koopman LP, Neijens HJ, Gerritsen J, Kerkhof M, Heinrich J, Bellander T, Brunekreef B (2002) Air pollution from traffic and the development of respiratory infections and asthmatic and allergic symptoms in children. Am J Respir Crit Care Med 166:1092–1098

    Article  Google Scholar 

  • Brunekreef B, Holgate ST (2002) Air pollution and health. Lancet 360:1233–1242

    Article  CAS  Google Scholar 

  • Burke JM, Zufall MJ, Ozkaynak H (2001) A population exposure model for particulate matter: case study results for PM2.5 in Philadelphia, PA. J Expo Anal Environ Epidemiol 11:470–489

    Article  CAS  Google Scholar 

  • Dons E, Int Panis L, Van Poppel M, Theunis J, Willems H, Torfs R, Wets G (2011) Impact of time–activity patterns on personal exposure to black carbon. Atmos Environ 45:3594–3602

    Article  CAS  Google Scholar 

  • Freijer JI, Bloemen HJT, Loos S, Marra M, Rombout PJA, Steentjes GM, vanVeen MP (1998) Modelling exposure of the Dutch population to air pollution. J Hazard Mater 61:107–114

    Article  CAS  Google Scholar 

  • Gauderman WJ, Vora H, McConnell R, Berhane K, Gilliland F, Thomas D, Lurmann F, Avol E, Künzli N, Jerrett M, Peters J (2007) Effect of exposure to traffic on lung development from 10 to 18 years of age: a cohort study. Lancet 369:571–577

    Article  Google Scholar 

  • Georgopoulos PG, Wang SW, Vyas VM, Sun Q, Burke J, Vedantham R, McCurdy T, Ozkaynak H (2005) A source-to-dose assessment of population exposures to fine PM and ozone in Philadelphia, PA, during a summer 1999 episode. J Expo Anal Environ Epidemiol 15:439–457

    Article  CAS  Google Scholar 

  • Gerharz L, Pebesma E (2012) Using geostatistical simulation to disaggregate air quality model results for individual exposure estimation on GPS tracks. Stoch Environ Res Risk Assess 27:223–234

    Article  Google Scholar 

  • Gerharz LE, Krüger A, Klemm O (2009) Applying indoor and outdoor modeling techniques to estimate individual exposure to PM2.5 from personal GPS profiles and diaries: a pilot study. Sci Total Environ 407:5184–5193

    Article  CAS  Google Scholar 

  • Gerharz LE, Klemm O, Broich AV, Pebesma E (2013) Spatio-temporal modelling of individual exposure to air pollution and its uncertainty. Atmos Environ 64:56–65

    Article  CAS  Google Scholar 

  • Graff A (2002) The new German regulatory model—a Lagrangian particle dispersion model. In: 8th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes

  • Gulliver J, Briggs DJ (2005) Time-space modeling of journey-time exposure to traffic-related air pollution using GIS. Environ Res 97:10–25

    Article  CAS  Google Scholar 

  • Health Effects Institute (2010) Traffic-related air pollution: a critical review of the literature on emissions, exposure, and health effects, HEI Special Report 17. Health Effects Institute, Boston

    Google Scholar 

  • Hertel O, Jensen S, Hvidberg M, Ketzel M, Berkowicz R, Palmgren F, Wåhlin P, Glasius M, Loft S, and Vinzents P et al (2008) Assessing the Impacts of Traffic Air Pollution on Human Exposure and Health. In: Fischer M et al (eds) Road pricing, the economy and the environment, pp. 277–299

  • Hoek G, Beelen R, de Hoogh K, Vienneau D, Gulliver J, Fischer P, Briggs D (2008) A review of land-use regression models to assess spatial variation of outdoor air pollution. Atmos Environ 42:7561–7578

    Article  CAS  Google Scholar 

  • Janicke L (2002) Lagrangian dispersion modeling. Part Matter Agric 235:37–4, 3-933140-58-7

    Google Scholar 

  • Janicke I (2004) AUSTAL2000. Programbeschreibung zu Verision 2.1. Stand 2004-12-23. Ingenieurbüro Janicke

  • Janicke L, Janicke U (2002) A modelling system for licensing industrial facilities, UFOPLAN 200 43 256. German Federal Environmental Agency UBA, German

    Google Scholar 

  • Janssen NAH, Lanki T, Hoek G, Vallius M, de Hartog JJ, Van Grieken R et al (2005) Associations between ambient, personal, and indoor exposure to fine particulate matter constituents in Dutch and Finnish panels of cardiovascular patients. Occup Environ Med 62:868–877

    Article  CAS  Google Scholar 

  • Jensen SS (2006) A GIS-GPS modeling system for personal exposure to traffic air pollution. Epidemiology 17:S38–S38

    Article  Google Scholar 

  • Klepeis NE, Nelson WC, Ott WR, Robinson JP, Tsang AM, Switzer P, Behar JV, Hern SC (2001) The national human activity pattern survey (NHAPS): a resource for assessing exposure to environmental pollutants. J Expo Anal Environ Epidemiol 11:231–252

    Article  CAS  Google Scholar 

  • Koistinen KJ, Hänninen OO, Rotko T, Edwards RD, Moschandreas D, Jantunen MJ (2001) Behavioral and environmental determinants of personal exposures to PM2.5 In EXPOLIS-Helsinki, Finland. Atmos Environ 35:2473–2481

    Article  CAS  Google Scholar 

  • Kousa A, Oglesby L, Koistinen K, Kunzli N, Jantunen M (2002) Exposure chain of urban air PM2.5—associations between ambient fixed site, residential outdoor, indoor, workplace and personal exposures in four European cities in the EXPOLIS-study. Atmos Environ 36:3031–3039

    Article  CAS  Google Scholar 

  • Kruize H, Hänninen O, Breugelmans O, Lebret E, Jantunen M (2003) Description and demonstration of the EXPOLIS simulation model: two examples of modeling population exposure to particulate matter. J Expo Anal Environ Epidemiol 13:87–99

    Article  CAS  Google Scholar 

  • Langner C, Klemm O (2011) A comparison of model performance between AERMOD and AUSTAL2000. J Air Waste Manag Assoc 61:640–646

    Article  CAS  Google Scholar 

  • Li Q, Zheng Y, Xie X, Chen Y, Liu, W, Ma W.-Y (2008) Mining user similarity based on location history. In: Proceedings of the 16th ACM SIGSPATIAL international conference on advances in geographic information systems, GIS ’08, pp. 34:1–34:10

  • Lioy PJ (2010) Exposure science: a view of the past and milestones for the future. Environ Health Perspect 118:1081–1090

    Article  Google Scholar 

  • Merbitz H, Fritz S, Schneider C (2012) Mobile measurements and regression modeling of the spatial particulate matter. Sci Total Environ 438:389–403

    Article  CAS  Google Scholar 

  • Nethery E, Leckie SE, Teschke K, Brauer M (2008) From measures to models: an evaluation of air pollution exposure assessment for epidemiological studies of pregnant women. Occup Environ Med 65:579–586

    Article  CAS  Google Scholar 

  • Oglesby L, Künzli N, Röösli M, Braun-Fahrländer C, Mathys P, Stern W, Jantunen M, Kousa A (2000) Validity of ambient levels of fine particles as surrogate for personal exposure to outdoor air pollution. J Air Waste Manag Assoc 50:1251–1261

    Article  CAS  Google Scholar 

  • Özkaynak H, Palma T, Touma J, Thurman J (2008) Modeling population exposures to outdoor sources of hazardous air pollutants. J Expo Sci Environ Epidemiol 18:45–58

    Article  Google Scholar 

  • Peng RD, Bell ML (2010) Spatial misalignment in time series studies of air pollution and health data. Biostatistics 11:720–740

    Article  Google Scholar 

  • Pinto N, Silva JP, Pereira PM (2008) Projeto Mobilidade Sustentável para o Município de Leiria, Relatório 1- Diagnóstico e Princípios Orientadores de Intervenção, Laboratório de Planeamento, Transportes e Sistemas de Informação Geográfica. Instituto Politécnico de Leiria, Portugal

    Google Scholar 

  • Rainham D, McDowell I, Krewski D, Sawada M (2010) Conceptualizing the healthscape: contributions of time geography, location technologies and spatial ecology to place and health research. Soc Sci Med 70:668–676

    Article  Google Scholar 

  • Song C, Qu Z, Blumm N, Barabási A (2010) Limits of predictability in human mobility. Science 327:1018–1021

    Article  CAS  Google Scholar 

  • Szpiro AA, Sampson PD, Sheppard L, Lumley T, Adar SD, Kaufman J (2008) Predicting intra-urban variation in air pollution concentrations with complex spatio-temporal interactions.Working paper 337, UW Biostatistics Working Paper Series

  • Tchepel O, Dias D (2011) Quantification of health benefits related with reduction of atmospheric PM10 levels: implementation of population mobility approach. Int J Environ Health Res 21:189–200

    Article  CAS  Google Scholar 

  • Tchepel O, Dias D, Ferreira J, Tavares R, Miranda AI, Borrego C (2012) Emission modelling of hazardous air pollutants from road transport at urban scale. Transport 27(8):299–306

    Article  Google Scholar 

  • Transportation Research Board (1994) Special Report 209. Highway Capacity Manual, Washington

    Google Scholar 

  • TTGPSLogger (2012). http://code.google.com/p/ttgpslogger/. Accessed November 2012

  • US Environmental Protection Agency (2006) Total risk integrated methodology (TRIM) air pollutants exposure model documentation (TRIM.Expo/APEX, Version 4)–volume i: user’s guide. U.S. Environmental Protection Agency, Research Triangle Park, NC

    Google Scholar 

  • US Environmental Protection Agency (2009) Human exposure modeling air pollutants exposure model. Available from (http://www.epa.gov/ttn/fera/human_apex.html) Accessed 28th April 2013

  • VDI (2000) Guideline 3945, Part 3. Environmental meteorology-atmospheric dispersion model—particle model. Guideline

  • Wang S-W, Tang X, Fan ZH, Lioy PJ, Georgopoulos PG (2009) Modelling personal exposures from ambient air toxics in Camden, New Jersey: an evaluation study. J Air Waste Manag 59:733–746

    Article  CAS  Google Scholar 

  • WHO and EC (2002) Guidelines for concentration and exposure-response measurement of fine and ultra-fine particulate matter for use in epidemiological studies, EUR 20238 EN 2002

  • WHO (2006) Air quality guidelines for particulate matter, ozone, nitrogen dioxide and sulfur dioxide-global update 2005. Summary of Risk Assessment, Geneva

    Google Scholar 

  • WHO (2011) Air quality and health. Fact sheet No. 313. Updated September 2011. Available from (http://www.who.int/mediacentre/factsheets/fs313/en/). Accessed 1 January 2013

  • Wu J, Jiang C, Liu Z, Houston D, Jaimes G, McConnell R (2010) Performances of different global positioning system devices for time–location tracking in air pollution epidemiological studies. Environ Health Insights 4:93–108

    Google Scholar 

  • Yau KH, Macdonald RW, The JL (2010) Inter-comparison of the AUSTAL2000 and CALPUFF dispersion models against the Kincaid data set. Int J Environ Pollut 40:267–279

    Article  CAS  Google Scholar 

  • Zheng Y, Zhou X (2011) Computing with spatial trajectories. Springer, New York

    Book  Google Scholar 

  • Zhou C, Frankowski D, Ludford P, Shekhar S, Terveen L (2004) Discovering personal gazetteers: an interactive clustering approach. In: Proc ACMGIS 266–273

  • Zhou C, Bhatnagar N, Shekhar S, Terveen L (2007a) Mining personally important places from GPS tracks. In: ICDEW ’07: Proceedings of the 2007 I.E. 23rd International Conference on Data Engineering Workshop, Washington, DC, USA. IEEE Computer Society. pp. 517–526

  • Zhou C, Frankowski D, Ludford P, Shekhar S, Terveen L (2007b) Discovering personally meaningful places: an interactive clustering approach. ACM Trans Inform Syst 25:3

    Article  Google Scholar 

  • Zou B, Wilson JG, Zhan FB, Zeng Y (2009) Air pollution exposure assessment methods utilized in epidemiological studies. J Environ Monit 11:475–490

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The authors thank the Portuguese Foundation for Science and Technology for the Ph.D. grant of D. Dias (SFRH/BD/47578/2008).

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Correspondence to Daniela Dias.

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Responsible editor: Michael Matthies

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Dias, D., Tchepel, O. Modelling of human exposure to air pollution in the urban environment: a GPS-based approach. Environ Sci Pollut Res 21, 3558–3571 (2014). https://doi.org/10.1007/s11356-013-2277-6

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