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Modeling Spatial and Temporal Variability of Residential Air Exchange Rates for the Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS)

机译:为近道路暴露和城市空气污染物影响建模住宅空气交换速率的时空变化(NEXUS)

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摘要

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.
机译:空气污染健康研究经常使用室外浓度作为暴露指标。未能考虑到居民室外污染物的渗透变化会导致暴露错误,并导致健康影响估计中的偏差和不正确的置信区间。住宅空气交换率(AER),即室内空气与室外空气的交换率,是决定房屋间污染(空间)和时间变化的重要决定因素。我们的目标是评估和应用力学模型预测近路暴露和城市空气污染物影响研究(NEXUS)中213个家庭的AER,这是一项对居住在附近的哮喘儿童中与交通有关的空气污染暴露和呼吸作用的队列研究密歇根州底特律的主要道路。我们使用了以前开发的模型(LBLX),该模型从气象学和有关与漏风有关的建筑特征的调查表数据中预测AER,并使用了该模型的扩展版本(LBLX),其中包括从敞开的窗户进行自然通风。作为我们AER建模方法的关键和新颖的方面,我们在24天的连续五天中,根据来自24个研究房屋子集的每日AER测量结果,进行了交叉验证,包括参数估计(即模型校准)和模型评估两个季节。测得的AER在0.09至3.48 h -1 之间变化,中位数为0.64 h -1 。对于单个模型预测和测量的AER,LBL和LBLX模型的中位数绝对差为29%(0.19 h -1 )。 LBL和LBLX模型分别预测了AER的59%和61%的方差。在为期三年的研究(2010-2012年)中,对所有213户房屋的每日AER预测显示,建筑物之间的房屋泄漏差异存在很大的房屋差异,而室外温度和风速波动则存在时间差异。使用这种新颖的方法,NEXUS将成为首批应用校准的和特定于家庭的AER模型的流行病学研究之一,并将多年内200多个独立房屋的AER时空变化纳入暴露评估以支持改善风险估计。

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