Literature DB >> 17878926

Modeling population exposures to outdoor sources of hazardous air pollutants.

Halûk Ozkaynak1, Ted Palma, Jawad S Touma, James Thurman.   

Abstract

Accurate assessment of human exposures is an important part of environmental health effects research. However, most air pollution epidemiology studies rely upon imperfect surrogates of personal exposures, such as information based on available central-site outdoor concentration monitoring or modeling data. In this paper, we examine the limitations of using outdoor concentration predictions instead of modeled personal exposures for over 30 gaseous and particulate hazardous air pollutants (HAPs) in the US. The analysis uses the results from an air quality dispersion model (the ASPEN or Assessment System for Population Exposure Nationwide model) and an inhalation exposure model (the HAPEM or Hazardous Air Pollutant Exposure Model, Version 5), applied by the US. Environmental protection Agency during the 1999 National Air Toxic Assessment (NATA) in the US. Our results show that the total predicted chronic exposure concentrations of outdoor HAPs from all sources are lower than the modeled ambient concentrations by about 20% on average for most gaseous HAPs and by about 60% on average for most particulate HAPs (mainly, due to the exclusion of indoor sources from our modeling analysis and lower infiltration of particles indoors). On the other hand, the HAPEM/ASPEN concentration ratio averages for onroad mobile source exposures were found to be greater than 1 (around 1.20) for most mobile-source related HAPs (e.g. 1, 3-butadiene, acetaldehyde, benzene, formaldehyde) reflecting the importance of near-roadway and commuting environments on personal exposures to HAPs. The distribution of the ratios of personal to ambient concentrations was found to be skewed for a number of the VOCs and reactive HAPs associated with major source emissions, indicating the importance of personal mobility factors. We conclude that the increase in personal exposures from the corresponding predicted ambient levels tends to occur near locations where there are either major emission sources of HAPs or when individuals are exposed to either on- or nonroad sources of HAPs during their daily activities. These findings underscore the importance of applying exposure-modeling methods, which incorporate information on time-activity, commuting, and exposure factors data, for the purposes of assigning exposures in air pollution health studies.

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Year:  2007        PMID: 17878926     DOI: 10.1038/sj.jes.7500612

Source DB:  PubMed          Journal:  J Expo Sci Environ Epidemiol        ISSN: 1559-0631            Impact factor:   5.563


  27 in total

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2.  Exposure assessment, chemical characterization and source identification of PM2.5 for school children and industrial downwind residents in Guangzhou, China.

Authors:  Jia Wang; Senchao Lai; Zhaoyue Ke; Yingyi Zhang; Shasha Yin; Junyu Zheng
Journal:  Environ Geochem Health       Date:  2013-08-11       Impact factor: 4.609

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

Authors:  Daniela Dias; Oxana Tchepel
Journal:  Environ Sci Pollut Res Int       Date:  2013-11-24       Impact factor: 4.223

4.  Effectiveness of residential wood-burning regulation on decreasing particulate matter levels and hospitalizations in the San Joaquin Valley Air Basin.

Authors:  Poh-Sin Yap; Cynthia Garcia
Journal:  Am J Public Health       Date:  2015-02-25       Impact factor: 9.308

5.  Hypospadias risk is increased with maternal residential exposure to hormonally active hazardous air pollutants.

Authors:  Kunj R Sheth; Erin Kovar; Jeffrey T White; Tiffany M Chambers; Erin C Peckham-Gregory; Marisol O'Neill; Peter H Langlois; Abhishek Seth; Michael E Scheurer; Philip J Lupo; Carolina J Jorgez
Journal:  Birth Defects Res       Date:  2019-01-29       Impact factor: 2.344

6.  The statistical evaluation and comparison of ADMS-Urban model for the prediction of nitrogen dioxide with air quality monitoring network.

Authors:  Audrius Dėdelė; Auksė Miškinytė
Journal:  Environ Monit Assess       Date:  2015-08-21       Impact factor: 2.513

7.  Evaluating children's location using a personal GPS logging instrument: limitations and lessons learned.

Authors:  Donna Dueker; Maryam Taher; John Wilson; Rob McConnell
Journal:  J Expo Sci Environ Epidemiol       Date:  2013-03-27       Impact factor: 5.563

8.  Characterizing Variability and Uncertainty in Exposure Assessments Improves Links to Environmental Decision-Making.

Authors:  Halûk Ozkaynak; H Christopher Frey; Bryan Hubbell
Journal:  EM (Pittsburgh Pa)       Date:  2008-07

9.  Modeling of personal exposures to ambient air toxics in Camden, New Jersey: an evaluation study.

Authors:  Sheng-Wei Wang; Xiaogang Tang; Zhi-Hua Fan; Xiangmei Wu; Paul J Lioy; Panos G Georgopoulos
Journal:  J Air Waste Manag Assoc       Date:  2009-06       Impact factor: 2.235

Review 10.  Benzene exposure: an overview of monitoring methods and their findings.

Authors:  Clifford P Weisel
Journal:  Chem Biol Interact       Date:  2010-01-06       Impact factor: 5.192

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