首页> 美国卫生研究院文献>International Journal of Environmental Research and Public Health >Integrating Modes of Transport in a Dynamic Modelling Approach to Evaluate Population Exposure to Ambient NO2 and PM2.5 Pollution in Urban Areas
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Integrating Modes of Transport in a Dynamic Modelling Approach to Evaluate Population Exposure to Ambient NO2 and PM2.5 Pollution in Urban Areas

机译:动态模型中的运输方式集成以评估城市人口中环境NO2和PM2.5污染的暴露量

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摘要

To evaluate the effectiveness of alternative policies and measures to reduce air pollution effects on urban citizen’s health, population exposure assessments are needed. Due to road traffic emissions being a major source of emissions and exposure in European cities, it is necessary to account for differentiated transport environments in population dynamics for exposure studies. In this study, we applied a modelling system to evaluate population exposure in the urban area of Hamburg in 2016. The modeling system consists of an urban-scale chemistry transport model to account for ambient air pollutant concentrations and a dynamic time-microenvironment-activity (TMA) approach, which accounts for population dynamics in different environments as well as for infiltration of outdoor to indoor air pollution. We integrated different modes of transport in the TMA approach to improve population exposure assessments in transport environments. The newly developed approach reports 12% more total exposure to NO and 19% more to PM compared with exposure estimates based on residential addresses. During the time people spend in different transport environments, the in-car environment contributes with 40% and 33% to the annual sum of exposure to NO and PM , in the walking environment with 26% and 30%, in the cycling environment with 15% and 17% and other environments (buses, subway, suburban, and regional trains) with less than 10% respectively. The relative contribution of road traffic emissions to population exposure is highest in the in-car environment (57% for NO and 15% for PM ). Results for population-weighted exposure revealed exposure to PM concentrations above the WHO AQG limit value in the cycling environment. Uncertainties for the exposure contributions arising from emissions and infiltration from outdoor to indoor pollutant concentrations range from −12% to +7% for NO and PM . The developed “dynamic transport approach” is integrated in a computationally efficient exposure model, which is generally applicable in European urban areas. The presented methodology is promoted for use in urban mobility planning, e.g., to investigate on policy-driven changes in modal split and their combined effect on emissions, population activity and population exposure.
机译:为了评估减少空气污染对城市居民健康的替代政策和措施的有效性,需要进行人口暴露评估。由于道路交通排放是欧洲城市排放和暴露的主要来源,因此有必要在人口动态中考虑差异化的运输环境以进行暴露研究。在这项研究中,我们应用了一个建模系统来评估2016年汉堡市区的人口暴露。该建模系统由一个城市规模的化学迁移模型组成,该模型考虑了周围空气污染物的浓度以及动态的时间微环境活动( TMA)方法,该方法考虑了不同环境中的人口动态以及室外到室内空气污染的渗透。我们在TMA方法中整合了不同的运输方式,以改善运输环境中的人口暴露评估。与根据居民地址估算的暴露相比,新开发的方法报告的NO暴露总量增加了12%,PM暴露总量增加了19%。在人们花费在不同交通环境中的时间段内,车内环境对NO和PM的年暴露量的贡献分别为40%和33%;在步行环境中,占26%和30%;在自行车环境中,占15% %和17%以及其他环境(公交,地铁,郊区和区域火车)的比例分别低于10%。在车内环境中,道路交通排放对人口暴露的相对贡献最高(NO为57%,PM为15%)。人群加权暴露结果表明,在自行车环境中暴露于高于WHO AQG限值的PM浓度。对于室外和室内污染物浓度,NO和PM的排放和渗透引起的暴露贡献的不确定性范围从-12%到+ 7%。发达的“动态运输方法”被集成到计算有效的暴露模型中,该模型通常适用于欧洲城市地区。提倡将所提出的方法用于城市交通规划中,例如,调查政策驱动的模式变化及其对排放,人口活动和人口暴露的综合影响。

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