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Predicting residential air exchange rates from questionnaires and meteorology: model evaluation in central North Carolina.

ABSTRACT: A critical aspect of air pollution exposure models is the estimation of the air exchange rate (AER) of individual homes, where people spend most of their time. The AER, which is the airflow into and out of a building, is a primary mechanism for entry of outdoor air pollutants and removal of indoor source emissions. The mechanistic Lawrence Berkeley Laboratory (LBL) AER model was linked to a leakage area model to predict AER from questionnaires and meteorology. The LBL model was also extended to include natural ventilation (LBLX). Using literature-reported parameter values, AER predictions from LBL and LBLX models were compared to data from 642 daily AER measurements across 31 detached homes in central North Carolina, with corresponding questionnaires and meteorological observations. Data was collected on seven consecutive days during each of four consecutive seasons. For the individual model-predicted and measured AER, the median absolute difference was 43% (0.17 h(-1)) and 40% (0.17 h(-1)) for the LBL and LBLX models, respectively. Additionally, a literature-reported empirical scale factor (SF) AER model was evaluated, which showed a median absolute difference of 50% (0.25 h(-1)). The capability of the LBL, LBLX, and SF models could help reduce the AER uncertainty in air pollution exposure models used to develop exposure metrics for health studies.

SUBMITTER: Breen MS

PROVIDER: S-EPMC3001757 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature

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Predicting residential air exchange rates from questionnaires and meteorology: model evaluation in central North Carolina.

Breen Michael S MS Breen Miyuki M Williams Ronald W RW Schultz Bradley D BD

Environmental science & technology 20101111 24

A critical aspect of air pollution exposure models is the estimation of the air exchange rate (AER) of individual homes, where people spend most of their time. The AER, which is the airflow into and out of a building, is a primary mechanism for entry of outdoor air pollutants and removal of indoor source emissions. The mechanistic Lawrence Berkeley Laboratory (LBL) AER model was linked to a leakage area model to predict AER from questionnaires and meteorology. The LBL model was also extended to ...[more]

PMID: 21069949

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Project description:Air pollution health studies often use outdoor concentrations as exposure surrogates. Failure to account for variability of residential infiltration of outdoor pollutants can induce exposure errors and lead to bias and incorrect confidence intervals in health effect estimates. The residential air exchange rate (AER), which is the rate of exchange of indoor air with outdoor air, is an important determinant for house-to-house (spatial) and temporal variations of air pollution infiltration. Our goal was to evaluate and apply mechanistic models to predict AERs for 213 homes in the Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS), a cohort study of traffic-related air pollution exposures and respiratory effects in asthmatic children living near major roads in Detroit, Michigan. We used a previously developed model (LBL), which predicts AER from meteorology and questionnaire data on building characteristics related to air leakage, and an extended version of this model (LBLX) that includes natural ventilation from open windows. As a critical and novel aspect of our AER modeling approach, we performed a cross validation, which included both parameter estimation (i.e., model calibration) and model evaluation, based on daily AER measurements from a subset of 24 study homes on five consecutive days during two seasons. The measured AER varied between 0.09 and 3.48 h(-1) with a median of 0.64 h(-1). For the individual model-predicted and measured AER, the median absolute difference was 29% (0.19 h‑1) for both the LBL and LBLX models. The LBL and LBLX models predicted 59% and 61% of the variance in the AER, respectively. Daily AER predictions for all 213 homes during the three year study (2010-2012) showed considerable house-to-house variations from building leakage differences, and temporal variations from outdoor temperature and wind speed fluctuations. Using this novel approach, NEXUS will be one of the first epidemiology studies to apply calibrated and home-specific AER models, and to include the spatial and temporal variations of AER for over 200 individual homes across multiple years into an exposure assessment in support of improving risk estimates.

Project description:BackgroundThe built environment, a key component of environmental health, may be an important contributor to health disparities, particularly for reproductive health outcomes.ObjectiveIn this study we investigated the relationship between seven indices of residential built environment quality and adverse reproductive outcomes for the City of Durham, North Carolina (USA).MethodsWe surveyed approximately 17,000 residential tax parcels in central Durham, assessing > 50 individual variables on each. These data, collected using direct observation, were combined with tax assessor, public safety, and U.S. Census data to construct seven indices representing important domains of the residential built environment: housing damage, property disorder, security measures, tenure (owner or renter occupied), vacancy, crime count, and nuisance count. Fixed-slope random-intercept multilevel models estimated the association between the residential built environment and five adverse birth outcomes. Models were adjusted for maternal characteristics and clustered at the primary adjacency community unit, defined as the index block, plus all adjacent blocks that share any portion of a line segment (block boundary) or vertex.ResultsFive built environment indices (housing damage, property disorder, tenure, vacancy, and nuisance count) were associated with each of the five outcomes in the unadjusted context: preterm birth, small for gestational age (SGA), low birth weight (LBW), continuous birth weight, and birth weight percentile for gestational age (BWPGA; sex-specific birth weight distributions for infants delivered at each gestational age using National Center for Health Statistics referent births for 2000-2004). However, some estimates were attenuated after adjustment. In models adjusted for individual-level covariates, housing damage remained statistically significantly associated with SGA, birth weight, and BWPGA.ConclusionThis work suggests a real and meaningful relationship between the quality of the residential built environment and birth outcomes, which we argue are a good measure of general community health.

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Predicting residential air exchange rates from questionnaires and meteorology: model evaluation in central North Carolina.

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Predicting residential air exchange rates from questionnaires and meteorology: model evaluation in central North Carolina.

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