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Spatial and Temporal Dynamics in Air Pollution Exposure Assessment

Author

Listed:
  • Daniela Dias

    (Department of Civil Engineering, CITTA, University of Coimbra, Rua Luís Reis Santos, Polo II, 3030-788 Coimbra, Portugal)

  • Oxana Tchepel

    (Department of Civil Engineering, CITTA, University of Coimbra, Rua Luís Reis Santos, Polo II, 3030-788 Coimbra, Portugal)

Abstract

Analyzing individual exposure in urban areas offers several challenges where both the individual’s activities and air pollution levels demonstrate a large degree of spatial and temporal dynamics. This review article discusses the concepts, key elements, current developments in assessing personal exposure to urban air pollution (seventy-two studies reviewed) and respective advantages and disadvantages. A new conceptual structure to organize personal exposure assessment methods is proposed according to two classification criteria: (i) spatial-temporal variations of individuals’ activities (point-fixed or trajectory based) and (ii) characterization of air quality (variable or uniform). This review suggests that the spatial and temporal variability of urban air pollution levels in combination with indoor exposures and individual’s time-activity patterns are key elements of personal exposure assessment. In the literature review, the majority of revised studies (44 studies) indicate that the trajectory based with variable air quality approach provides a promising framework for tackling the important question of inter- and intra-variability of individual exposure. However, future quantitative comparison between the different approaches should be performed, and the selection of the most appropriate approach for exposure quantification should take into account the purpose of the health study. This review provides a structured basis for the intercomparing of different methodologies and to make their advantages and limitations more transparent in addressing specific research objectives.

Suggested Citation

  • Daniela Dias & Oxana Tchepel, 2018. "Spatial and Temporal Dynamics in Air Pollution Exposure Assessment," IJERPH, MDPI, vol. 15(3), pages 1-23, March.
  • Handle: RePEc:gam:jijerp:v:15:y:2018:i:3:p:558-:d:137126
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    References listed on IDEAS

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    1. Tom Bellander & Janine Wichmann & Tomas Lind, 2012. "Individual Exposure to NO2 in Relation to Spatial and Temporal Exposure Indices in Stockholm, Sweden: The INDEX Study," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-9, June.
    2. Kwan, Mei-Po, 2009. "From place-based to people-based exposure measures," Social Science & Medicine, Elsevier, vol. 69(9), pages 1311-1313, November.
    3. Stuart Batterman & Janet Burke & Vlad Isakov & Toby Lewis & Bhramar Mukherjee & Thomas Robins, 2014. "A Comparison of Exposure Metrics for Traffic-Related Air Pollutants: Application to Epidemiology Studies in Detroit, Michigan," IJERPH, MDPI, vol. 11(9), pages 1-25, September.
    4. Marta C. González & César A. Hidalgo & Albert-László Barabási, 2009. "Understanding individual human mobility patterns," Nature, Nature, vol. 458(7235), pages 238-238, March.
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    4. Eun-hye Yoo & Qiang Pu & Youngseob Eum & Xiangyu Jiang, 2021. "The Impact of Individual Mobility on Long-Term Exposure to Ambient PM 2.5 : Assessing Effect Modification by Travel Patterns and Spatial Variability of PM 2.5," IJERPH, MDPI, vol. 18(4), pages 1-16, February.
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    6. Keith April G. Arano & Shengjing Sun & Joaquin Ordieres-Mere & and Bing Gong, 2019. "The Use of the Internet of Things for Estimating Personal Pollution Exposure," IJERPH, MDPI, vol. 16(17), pages 1-25, August.
    7. Qingbin Wei & Lianjun Zhang & Wenbiao Duan & Zhen Zhen, 2019. "Global and Geographically and Temporally Weighted Regression Models for Modeling PM 2.5 in Heilongjiang, China from 2015 to 2018," IJERPH, MDPI, vol. 16(24), pages 1-20, December.
    8. Martin Otto Paul Ramacher & Matthias Karl, 2020. "Integrating Modes of Transport in a Dynamic Modelling Approach to Evaluate Population Exposure to Ambient NO 2 and PM 2.5 Pollution in Urban Areas," IJERPH, MDPI, vol. 17(6), pages 1-35, March.
    9. Nicholas Watanabe & Grace Yan & Christopher McLeod, 2023. "The Impact of Sporting Events on Air Pollution: An Empirical Examination of National Football League Games," Sustainability, MDPI, vol. 15(6), pages 1-13, March.
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