4.6 Article

Predictors of concentrations of nitrogen dioxide, ne particulate matter, and particle constituents inside of lower socioeconomic status urban homes

Journal

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/sj.jes.7500532

Keywords

exposure modeling; particulate matter; nitrogen dioxide

Funding

  1. NHLBI NIH HHS [U01 HL072494] Funding Source: Medline
  2. NIEHS NIH HHS [R03 ES013988] Funding Source: Medline
  3. PHS HHS [5-T42-CCT1229661-02] Funding Source: Medline
  4. NIOSH CDC HHS [1-T42-OH008416-01] Funding Source: Medline

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Air pollution exposure patterns may contribute to known spatial patterning of asthma morbidity within urban areas. While studies have evaluated the relationship between traffic and outdoor concentrations, few have considered indoor exposure patterns within low socioeconomic status (SES) urban communities. In this study, part of a prospective birth cohort study assessing asthma etiology in urban Boston, we collected indoor and outdoor 3-4 day samples of nitrogen dioxide (NO2) and. ne particulate matter (PM2.5) in 43 residences across multiple seasons from 2003 to 2005. Homes were chosen to represent low SES households, including both cohort and non-cohort residences in similar neighborhoods, and consisted almost entirely of multiunit residences. Reflectance analysis and X-ray fluorescence spectroscopy were performed on the particle filters to determine elemental carbon (EC) and trace element concentrations, respectively. Additionally, information on home characteristics (e. g. type, age, stove fuel) and occupant behaviors (e. g. smoking, cooking, cleaning) were collected via a standardized questionnaire. The contributions of outdoor and indoor sources to indoor concentrations were quantified with regression analyses using mass balance principles. For NO2 and most particle constituents (except outdoor-dominated constituents like sulfur and vanadium), the addition of selected indoor source terms improved the model's predictive power. Cooking time, gas stove usage, occupant density, and humidifiers were identified as important contributors to indoor levels of various pollutants. A comparison between cohort and non-cohort participants provided another means to determine the influence of occupant activity patterns on indoor-outdoor ratios. Although the groups had similar housing characteristics and were located in similar neighborhoods, cohort members had significantly higher indoor concentrations of PM2.5 and NO2, associated with indoor activities. We conclude that the effect of indoor sources may be more pronounced in high-density multiunit dwellings, and that future epidemiological studies in these populations should explicitly consider these sources in assigning exposures.

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