Disaggregation of nation-wide dynamic population exposure estimates in The Netherlands: Applications of activity-based transport models
Disaggregation of nation-wide dynamic population exposure estimates in The Netherlands: Applications of activity-based transport models
复制标题
DOI：
10.1016/j.atmosenv.2009.07.035
复制
发表时间：
2009-11-01
影响因子：
5
通讯作者：
Wets, Geert
中科院分区：
文献类型：
--
作者：
Beckx, Carolien;Panis, Luc Int;Wets, Geert
将浓度与人口数据联系起来的传统接触研究并不总是考虑到浓度和人口密度的时间和空间变化。在本文中，我们提出了一个集成的模型链，用于确定全国范围内的暴露估计，包括时间和空间上解决的信息，人们的位置和活动（从基于活动的运输模型获得）和环境污染物浓度（从分散模型获得）。据我们所知，这是第一次以全面运作的方式成功地对所有审议中的模式进行这种综合演习。在荷兰的人口水平暴露于NO2在不同的时间段，地点，不同的亚群（性别，社会经济地位）和在不同的活动（居住，工作，交通，购物）的评价被选为一个案例研究，指出这种方法的新功能。结果表明，通过忽略人们的旅行行为，NO2的总平均暴露量将被低估4%，每小时的暴露结果可以被低估30%以上。更详细的接触分析揭示了接触估计值的日内变化，以及不同活动（交通>工作>购物>家庭）和亚人群（男性>女性，低社会经济阶层>高社会经济阶层）之间存在较大的接触差异。这种暴露分析按活动或亚群、一天中的每个时间进行分类，为科学和政策目的提供了有用的见解和信息。它表明，旨在降低人口总体（平均）接触浓度的政策措施可能会以不同的方式产生影响，这取决于一天中的时间或所考虑的亚组。从科学的角度来看，这种新方法可以用来减少暴露错误分类。(C)2009爱思唯尔有限公司保留所有权利。
Traditional exposure studies that link concentrations with population data do not always take into account the temporal and spatial variations in both concentrations and population density. In this paper we present an integrated model chain for the determination of nation-wide exposure estimates that incorporates temporally and spatially resolved information about people's location and activities (obtained from an activity-based transport model) and about ambient pollutant concentrations (obtained from a dispersion model). To the best of our knowledge, it is the first time that such an integrated exercise was successfully carried out in a fully operational modus for all models under consideration. The evaluation of population level exposure in The Netherlands to NO2 at different time-periods, locations, for different subpopulations (gender, socio-economic status) and during different activities (residential, work, transport, shopping) is chosen as a case-study to point out the new features of this methodology. Results demonstrate that, by neglecting people's travel behaviour, total average exposure to NO2 will be underestimated by 4% and hourly exposure results can be underestimated by more than 30%. A more detailed exposure analysis reveals the intra-day variations in exposure estimates and the presence of large exposure differences between different activities (traffic > work > shopping > home) and between subpopulations (men > women, low socio-economic class > high socio-economic class). This kind of exposure analysis, disaggregated by activities or by subpopulations, per time of day, provides useful insight and information for scientific and policy purposes. It demonstrates that policy measures, aimed at reducing the overall (average) exposure concentration of the population may impact in a different way depending on the time of day or the subgroup considered. From a scientific point of view, this new approach can be used to reduce exposure misclassification. (C) 2009 Elsevier Ltd. All rights reserved.