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Modeling indoor particulate exposures in inner city school classrooms
  • Published Date:
    Sep 07 2016
  • Source:
    J Expo Sci Environ Epidemiol. 27(5):451-457.
Filetype[PDF-1.37 MB]

  • Pubmed ID:
  • Pubmed Central ID:
  • Description:
    Outdoor air pollution penetrates buildings and contributes to total indoor exposures. We investigated the relationship of indoor to outdoor particulate matter in inner-city school classrooms. The School Inner City Asthma Study investigates the effect of classroom-based environmental exposures on students with asthma in the northeast United States. Mixed effects linear models were used to determine the relationships between indoor PM2.5 (particulate matter) and black carbon (BC), and their corresponding outdoor concentrations, and to develop a model for predicting exposures to these pollutants. The indoor-outdoor sulfur ratio was used as an infiltration factor of outdoor fine particles. Weeklong concentrations of PM2.5 and BC in 199 samples from 136 classrooms (30 school buildings) were compared with those measured at a central monitoring site averaged over the same timeframe. Mixed effects regression models found significant random intercept and slope effects, which indicate that: (1) there are important PM2.5 sources in classrooms; (2) the penetration of outdoor PM2.5 particles varies by school and (3) the site-specific outside PM2.5 levels (inferred by the models) differ from those observed at the central monitor site. Similar results were found for BC except for lack of indoor sources. The fitted predictions from the sulfur-adjusted models were moderately predictive of observed indoor pollutant levels (out of sample correlations: PM2.5: r2=0.68, BC; r2=0.61). Our results suggest that PM2.5 has important classroom sources, which vary by school. Furthermore, using these mixed effects models, classroom exposures can be accurately predicted for dates when central site measures are available but indoor measures are not available.

  • Document Type:
  • Collection(s):
  • Funding:
    U01 AI110397/AI/NIAID NIH HHS/United States
    R01 AI073964/AI/NIAID NIH HHS/United States
    K23 AI104780/AI/NIAID NIH HHS/United States
    U61 TS000237/TS/ATSDR CDC HHS/United States
    K23 AI106945/AI/NIAID NIH HHS/United States
    U10 HL098102/HL/NHLBI NIH HHS/United States
    U01 AI126614/AI/NIAID NIH HHS/United States
    UL1 TR001102/TR/NCATS NIH HHS/United States
    K23 ES023700/ES/NIEHS NIH HHS/United States
    K24 AI106822/AI/NIAID NIH HHS/United States
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