Parameter evaluation and model validation of ozone exposure assessment using Harvard Southern California Chronic Ozone Exposure Study data.
Parameter evaluation and model validation of ozone exposure assessment using Harvard Southern California Chronic Ozone Exposure Study data.
复制标题
使用哈佛南加州慢性臭氧暴露研究数据进行臭氧暴露评估的参数评估和模型验证。
DOI：
10.1080/10473289.2005.10464754
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发表时间：
2005
期刊：
影响因子：
--
通讯作者：
Spengler,JohnD
中科院分区：
文献类型：
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作者：
Xue,Jianping;Liu,ShiV;Ozkaynak,Halûk;Spengler,JohnD
为了检验影响城市社区儿童长期臭氧暴露的因素，作者分析了个人、室内和室外臭氧浓度的纵向数据，以及在为期一年的哈佛南加州慢性臭氧暴露研究中收集的相关住房和其他问卷信息。在原始数据集中包含的224名儿童中，有160名儿童被发现在研究期间的12个月中至少有6个月进行了臭氧浓度的纵向测量。这些儿童的数据被随机分成两组：一组用于模型开发，另一组用于模型验证。具有不同方差-协方差结构的混合模型被用来评估个人慢性臭氧暴露的统计上重要的预测因子。模型拟合的结果表明，对个人臭氧暴露最重要的预测因子包括室内臭氧浓度、中心环境臭氧浓度、室外臭氧浓度、季节、性别、户外时间、室内风扇使用情况以及室内燃气灶的存在。个人臭氧浓度的分层模型显示了每个预测模型的以下解释能力水平：室内和室外臭氧浓度加问卷变量、室内和室内臭氧浓度加问卷变量、室内臭氧浓度加问卷变量、中心臭氧浓度加问卷变量、以及仅关于时间活动和住房特征的问卷数据。这些结果提供了有关儿童慢性人体接触环境臭氧的关键预测因素的重要信息，并为如何可靠且经济有效地预测未来个人接触臭氧提供了见解。此外，这项研究得出的技术和结果也对为其他环境污染物选择最可靠和最具成本效益的暴露研究设计和建模方法具有重要意义，例如细颗粒物和选定的城市空气有毒物质。
To examine factors influencing long‐term ozone (O3) exposures by children living in urban communities, the authors analyzed longitudinal data on personal, indoor, and outdoor O3concentrations, as well as related housing and other questionnaire information collected in the one‐year‐long Harvard Southern California Chronic Ozone Exposure Study. Of 224 children contained in the original data set, 160 children were found to have longitudinal measurements of O3concentrations in at least six months of 12 months of the study period. Data for these children were randomly split into two equal sets: one for model development and the other for model validation. Mixed models with various variance‐covariance structures were developed to evaluate statistically important predictors for chronic personal ozone exposures. Model predictions were then validated against the field measurements using an empirical best‐linear unbiased prediction technique.The results of model fitting showed that the most important predictors for personal ozone exposure include indoor O3concentration, central ambient O3concentration, outdoor O3concentration, season, gender, outdoor time, house fan usage, and the presence of a gas range in the house. Hierarchical models of personal O3concentrations indicate the following levels of explanatory power for each of the predictive models: indoor and outdoor O3concentrations plus questionnaire variables, central and indoor O3concentrations plus questionnaire variables, indoor O3concentrations plus questionnaire variables, central O3concentrations plus questionnaire variables, and questionnaire data alone on time activity and housing characteristics. These results provide important information on key predictors of chronic human exposures to ambient O3for children and offer insights into how to reliably and cost‐effectively predict personal O3exposures in the future. Furthermore, the techniques and findings derived from this study also have strong implications for selecting the most reliable and cost‐effective exposure study design and modeling approaches for other ambient pollutants, such as fine particulate matter and selected urban air toxics.