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7.4 Estimates of Personal Exposure to NO_2 Using Ambient Concentrations and Activity Data

机译:7.4使用环境浓度和活动数据对NO_2个人接触的估计

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This paper presents results from a study to investigate the extent to which NO_2 data from ambient network monitoring, air quality modelling, or a combination of both, can improve estimates of personal exposure across a city. As it is not practical to measure the personal exposure of every individual, a common assumption in most epidemiological studies for urban areas has been that people are exposed to a spatially-homogenous pollutant, ignoring variations in concentrations across an airshed and in various micro-environments. Our conceptual model of an individual's personal exposure to NO_2 is based on time-weighted sums of exposure in the microenvironments of home, transit and work. Personal exposure in each microenvironment is linked to ambient concentration by indoor-outdoor concentration ratios. To allow us to both develop and evaluate the model, we designed a measurement program involving volunteers across Melbourne wearing personal passive samplers. Participants also wore additional samplers for sub-periods of each 48-hour exposure, at home, at work and in transit. Diaries were designed to record details of time and activities in each micro-environment, especially those associated with cooking and ventilation. Three methods of estimating indoor-outdoor ratios and three approaches to calculating ambient exposure were evaluated. For estimation of the personal exposure to NO_2 of a large number of people, it is recommended that best results would be obtained with the I/O ratio calculated from a mass balance method. This requires participants to record daily gas cooking periods and approximate house age, although a simpler but slightly less accurate method dependent only on the existence or not of a gas cooking appliance also produces satisfactory results. The recommended method for calculating the required ambient outdoor concentration is to use values from the network monitor nearest to a person's microenvironment. Evaluation statistics were considerably poorer for a commonly-used method whereby each person is assigned the same ambient concentration, taken to be the mean concentration across all network monitors.
机译:本文提出了一项研究的结果,以研究环境网络监测,空气质量建模或两者的组合,可以改善城市个人曝光的估计。由于衡量每个人的个人暴露并不实用,城市地区大多数流行病学研究中的常见假设一直是人们暴露于空间均匀的污染物,忽略了空中环境和各种微环境中浓度的变化。我们个人个人接触NO_2的概念模型是基于在家庭,运输和工作的微环境中的时间加权曝光。每种微环境中的个人暴露通过室外室外浓度比与环境浓度相关联。为了允许我们对模型进行开发和评估,我们设计了一个涉及普通墨尔本佩戴个人被动采样器的志愿者的测量计划。参与者还涉及每个48小时曝光的额外采样器,在家,在工作和运输中。日记旨在记录每种微环境中的时间和活动的细节,尤其是与烹饪和通风相关的时间。评估了三种估算室外比率和三种计算环境暴露方法的方法。为了估计大量人群的个人风险,建议使用来自质量平衡法计算的I / O比率获得最佳结果。这要求参与者记录日常气体烹饪时段和近似房屋时代,尽管仅依赖于燃气烹饪器具的存在性更简单但略低于准确的方法,但也产生了令人满意的结果。用于计算所需环境室外浓度的推荐方法是使用最接近人的微环境的网络监视器的值。对于一种普通使用的方法,评估统计数据相当较差,其中每个人被分配相同的环境浓度,被认为是所有网络监视器的平均浓度。

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