Literature DB >> 15819228

Use of personal-indoor-outdoor sulfur concentrations to estimate the infiltration factor and outdoor exposure factor for individual homes and persons.

Lance Wallace1, Ron Williams.   

Abstract

A study of personal, indoor, and outdoor exposure to PM2.5 and associated elements has been carried out for 37 residents of the Research Triangle Park area in North Carolina. Participants were selected from persons expected to be at elevated risk from exposure to particles, and included 29 persons with hypertension and 8 cardiac patients with implanted defibrillators. Participants were monitored for 7 consecutive days in each of four seasons. One goal of the study was to estimate the contribution of outdoor PM2.5 to indoor concentrations. This depends on the infiltration factor Finf, the fraction of outdoor PM2.5 remaining airborne after penetrating indoors. After confirming with our measurements the findings of previous studies that sulfur has few indoor sources, we estimated an average Finf for each house based on indoor/outdoor sulfur ratios. These estimates ranged from 0.26 to 0.87, with a median value of 0.55. Since these estimates apply only to particles of size similar to that of sulfur particles (0.06-0.5 microm diameter), and since larger particles (0.5-2.5 microm) have lower penetration rates and higher deposition rates, these estimates are likely to be higher than the true infiltration factors for PM2.5 as a whole. In summer when air conditioners were in use, the sulfur-based infiltration factor was at its lowest (averaging 0.50) for most homes, whereas the average Finf for the other three seasons was 0.62-0.63. Using the daily estimated infiltration factor for each house, we calculated the contribution of outdoor PM2.5 to indoor air concentrations. The indoor-generated contributions to indoor PM2.5 had a wider range (0-33 microg/m3) than the outdoor contributions (5-22 microg/m3). However, outdoor contributions exceeded the indoor-generated contributions in 27 of 36 homes. A second goal of the study was to determine the contribution of outdoor particles to personal exposure. This is determined by the "outdoor exposure factor" Fpex, the fraction of outdoor PM2.5 contributing to personal exposure. As with Finf, we estimated Fpex by the personal/outdoor sulfur ratios. The estimates ranged from 0.33 to 0.77 with a median value of 0.53. Outdoor air particles were less important for personal exposures than for indoor concentrations, with the median outdoor contribution to personal exposure just 49%. We regressed the outdoor contributions to personal exposures on measured outdoor PM2.5 at the central site. The regressions had R2 values ranging from 0.19 to 0.88 (median = 0.73). These values provide an indication of the extent of misclassification error in epidemiological estimates of the effect of outdoor particles on health.

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Year:  2005        PMID: 15819228     DOI: 10.1021/es049547u

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  27 in total

Review 1.  A review of air exchange rate models for air pollution exposure assessments.

Authors:  Michael S Breen; Bradley D Schultz; Michael D Sohn; Thomas Long; John Langstaff; Ronald Williams; Kristin Isaacs; Qing Yu Meng; Casson Stallings; Luther Smith
Journal:  J Expo Sci Environ Epidemiol       Date:  2013-05-29       Impact factor: 5.563

2.  Sources of indoor air pollution in New York City residences of asthmatic children.

Authors:  Rima Habre; Brent Coull; Erin Moshier; James Godbold; Avi Grunin; Amit Nath; William Castro; Neil Schachter; Annette Rohr; Meyer Kattan; John Spengler; Petros Koutrakis
Journal:  J Expo Sci Environ Epidemiol       Date:  2013-10-30       Impact factor: 5.563

3.  Classroom indoor PM2.5 sources and exposures in inner-city schools.

Authors:  Aleshka Carrion-Matta; Choong-Min Kang; Jonathan M Gaffin; Marissa Hauptman; Wanda Phipatanakul; Petros Koutrakis; Diane R Gold
Journal:  Environ Int       Date:  2019-07-08       Impact factor: 9.621

4.  GPS-based microenvironment tracker (MicroTrac) model to estimate time-location of individuals for air pollution exposure assessments: model evaluation in central North Carolina.

Authors:  Michael S Breen; Thomas C Long; Bradley D Schultz; James Crooks; Miyuki Breen; John E Langstaff; Kristin K Isaacs; Yu-Mei Tan; Ronald W Williams; Ye Cao; Andrew M Geller; Robert B Devlin; Stuart A Batterman; Timothy J Buckley
Journal:  J Expo Sci Environ Epidemiol       Date:  2014-03-12       Impact factor: 5.563

5.  Indoor particle dynamics in a school office: determination of particle concentrations, deposition rates and penetration factors under naturally ventilated conditions.

Authors:  X C Cong; J J Zhao; Z Jing; Q G Wang; P F Ni
Journal:  Environ Geochem Health       Date:  2018-05-09       Impact factor: 4.609

6.  Impact of personal and ambient-level exposures to nitrogen dioxide and particulate matter on cardiovascular function.

Authors:  Ron Williams; Robert Brook; Robert Bard; Teri Conner; Hwashin Shin; Richard Burnett
Journal:  Int J Environ Health Res       Date:  2011-06-28       Impact factor: 3.411

7.  The effects of PM2.5 and its components from indoor and outdoor sources on cough and wheeze symptoms in asthmatic children.

Authors:  Rima Habre; Erin Moshier; William Castro; Amit Nath; Avi Grunin; Annette Rohr; James Godbold; Neil Schachter; Meyer Kattan; Brent Coull; Petros Koutrakis
Journal:  J Expo Sci Environ Epidemiol       Date:  2014-04-09       Impact factor: 5.563

8.  Modeling individual exposures to ambient PM2.5 in the diabetes and the environment panel study (DEPS).

Authors:  Michael Breen; Yadong Xu; Alexandra Schneider; Ronald Williams; Robert Devlin
Journal:  Sci Total Environ       Date:  2018-02-19       Impact factor: 7.963

9.  Assessment of inter-individual, geographic, and seasonal variability in estimated human exposure to fine particles.

Authors:  Wan Jiao; H Christopher Frey; Ye Cao
Journal:  Environ Sci Technol       Date:  2012-11-07       Impact factor: 9.028

10.  Indoor air quality in green-renovated vs. non-green low-income homes of children living in a temperate region of US (Ohio).

Authors:  Kanistha C Coombs; Ginger L Chew; Christopher Schaffer; Patrick H Ryan; Cole Brokamp; Sergey A Grinshpun; Gary Adamkiewicz; Steve Chillrud; Curtis Hedman; Meryl Colton; Jamie Ross; Tiina Reponen
Journal:  Sci Total Environ       Date:  2016-03-05       Impact factor: 7.963

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