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Measurement and modeling of short- and long-term commuter exposure to traffic-related air pollution

机译:短期和长期通勤者接触交通相关空气污染的测量和建模

摘要

Background. Many epidemiological studies have reported associations between traffic-related air pollu¬tion exposure and acute and chronic health problems. Exposure assignment in those stud¬ies has typically relied on home outdoor locations and ignored exposure during commuting and at non-residential locations. However, because of high concentrations of harmful air pollutants in proximity to traffic, time spent in transport may contribute considerably to a person’s total daily exposure to traffic-related air pollution. An understanding of how activity patterns affect exposure to traffic-related air pollution in space and time is important for im¬proved exposure assessments. ududConcentration levels and individuals’ exposures to harmful traffic-related air pollutants in the various transport microenvironments are not well understood. Recently, exposure to ultrafine particles (UFP, particles smaller than 100 nm) has attracted particular interest. UFP are considered harmful to human health in view of their small size and the probability to penetrate deeply into the respiratory tract. Little is known about the variability in UFP concentrations and most notably the average particle size in various transport environ¬ments. This is largely due to the lack of a robust portable device to measure UFP charac¬teristics.ududObjectives. The aim of this thesis was to characterize exposure to both UFP concentration and average particle size distribution diameters in commonly used transport environments in Basel. In addition, a simulation of commuter exposure to traffic-related air pollution of a general pop-ulation was carried out to estimate the contribution of commute (i.e., the time spent in traffic traveling between home and work or school) to total exposure and inhalation dose as well as its relevance in epidemiological studies on long-term health effects of traffic-related air pollution. ududMethods. Three sub-studies were performed to characterize personal exposure to UFP concentration and average particle size distribution diameters in frequently traveled commuter microenvi-ronments. The personal monitoring campaign was carried out in the city of Basel and sur-rounding area between December 2010 and September 2011 using a newly developed portable device, the miniature Diffusion Size Classifier (miniDiSC), which measures particles in the size range of 10 to 300 nm. First, the spatial variation of sidewalk UFP exposures within urban areas and transport-specific microenvironments was explored. Measurements were conducted along four predefined walks once per month. Second, exposure to UFP concentration and average particle size were quantified for five modes of transportation (walking, bicycle, bus, tram, car) during different times of the day and week, along the same route. Finally, the contribution of bicycle commuting along two different routes (along main roads, away from main roads) to total daily exposures was assessed by 24-hour personal measurements. Measurements were equally distributed over weekdays (Monday to Friday) across three seasons – winter, spring and summer. ududThe simulation of commuter exposure to traffic-related air pollution was conducted based on spatially and temporally resolved data on commuter trips of residents working (or attending a school) within the Basel area (Cantons Basel-City and Basel-Country). The information on commuter routes, transportation modes and home, work and school locations were ex¬tracted from the year 2010 Swiss Mobility and Transport Microcensus survey. An approach to simulate travel routes based on the transportation mode and origin/destination location of the legs (pieces of the trips with the same transportation mode) was developed and vali¬dated. Individuals’ exposures to NO2 during commuting and at home, work and school loca¬tions were computed by overlapping the locations and travel routes with annual mean maps of NO2 in a geographic information system (GIS). Three air pollution models (a land use regression model (LUR), a high and a low resolution dispersion model) were evaluated for estimating commuter exposures to NO2 as a marker of long-term exposure to traffic-related air pollution. Finally, the bias in health effect estimates resulting from using home outdoor exposures only and ignoring other non-residential exposures including commuter exposure was quantified. ududThis thesis is part of the Europe-wide project, Transportation Air Pollution and Physical ActivitieS (TAPAS), which is an integrated health risk assessment program on climate change and urban policies. ududResults. In general, smaller average particle sizes and higher UFP concentration levels were meas-ured at places and for transportation modes in close proximity to traffic. Average trip UFP concentrations were highest in car (31,800 particles cm-3) followed by bicycle (22,700 parti-cles cm-3), walking (19,500 particles cm-3) and public transportation (14,100-18,800 particles cm-3). Concentrations were highest for all transportation modes during weekday morning rush hours, compared to other time periods. UFP concentration was lowest in bus, regard¬less of time period. Average particle diameters followed an opposite trend than UFP con¬centration, showing larger average particle sizes for transportation modes and sampling times with lower UFP number concentrations and vice versa. Bicycle travel along main streets between home and work place (24 min on average) contributed 21% and 5% to total daily UFP exposure in winter and summer, respectively. Contribution of bicycle commutes to total daily UFP exposure could be reduced by half if main roads were avoided. ududWithin Basel-City, estimated average time-weighted NO2 population exposure during com-muting was similar among all air pollution models (around 39-41 µg m–3). The spatial varia-bility in NO2 concentrations, as typically encountered in urban street environments, was best reflected by the dispersion model with the highest resolution (grid size of 25 m). By com-parison, both the LUR model (applied to a 50x50 m grid) and the dispersion model with a lower resolution (100x100 m) underestimated the NO2 concentrations on the higher end, and overestimated the values on the lower end. ududThe population working (>= 50% work load) or attending a school within the region of Basel spent on average 49 minutes for daily commutes. Work or school occupied 22% of the subjects’ time on average. Median contribution of commuting to total weekly NO2 exposure was 2.7% (range 0.1-13.5%). With regard to inhalation dose, the commute contributed slightly more when assuming moderate (3.5%, range: 0.2-16.8%) or high (4.2%, range: 0.2-33.0%) breathing rates during active transportation. The median contribution of commute to the total NO2 exposure was highest for subjects using mainly public transportation (4.7%, range: 1.3-13.5%) who also spent the longest time in traffic (more than an hour). The com¬parison between the transportation modes based on the legs of the trips, however, revealed the highest NO2 exposures for motorized transportation.ududThe failure to differentiate between outdoor NO2 exposure at work/school and at home could result in a 12% (95%-CI: 11-14%) underestimation of related health effects. This bias was stronger for the subjects commuting between Basel-City and the rural to suburban sur-rounding areas of Basel-Country (33% underestimation) than for the subjects commuting within those areas. For the same population sub-group, potentially significant underestima¬tion of health effects (5%, 95%-CI: 4-5%) attributable to including outdoor exposures at home and at work/school but omitting exposure during the commute was found. ududConclusions and Outlook. This thesis provides important insights in the spatial and temporal variability of UFP within an urban area and provides an approach for modeling commuter exposures to traffic-related air pollution in epidemiological studies. Results confirmed the expectation that people are exposed to potentially high exposures during their daily travels and that ignoring time-activity patterns in epidemiological studies results in exposure misclassification and bias associated health effects. ududThe benefit of incorporating non-residential locations and daily commute patterns in expo¬sure assignments of future epidemiological studies should carefully be evaluated based on (1) spatial and temporal variability of the pollutants of interest, and (2) the spatial spread of home and work/school locations and subjects’ level of mobility. Improved exposure estima¬tion thus requires information on subjects’ travel duration, distance, transportation modes, trip timings, route choices and work load. ududFuture exposure assessments of large cohorts will need to more frequently combine mod¬eling approaches with actual personal exposure measurements of pollutants of interest to refine and validate exposure estimates spatially as well as temporally.ud
机译:背景。许多流行病学研究报告了交通相关的空气污染暴露与急性和慢性健康问题之间的联系。这些研究室中的暴露分配通常依赖于家庭室外位置,而在通勤期间和在非居住位置忽略了暴露。但是,由于交通附近有害空气污染物的浓度很高,因此在交通上花费的时间可能会大大增加一个人每天与交通相关的空气污染的总暴露量。对于活动模式如何影响空间和时间中与交通相关的空气污染的暴露的理解,对于改善暴露评估至关重要。 ud ud在各种运输微环境中的浓度水平和个人暴露于有害的与交通相关的空气污染物的接触尚不​​十分清楚。最近,暴露于超细颗粒(UFP,小于100 nm的颗粒)引起了人们的特别兴趣。考虑到UFP的体积小和深入呼吸道的可能性,因此被认为对人体健康有害。关于UFP浓度的变化,尤其是在各种运输环境中的平均粒径,人们知之甚少。这主要是由于缺少用于测量UFP特性的坚固便携式设备。 ud udObjectives。本文的目的是描述巴塞尔常用运输环境中UFP浓度和平均粒径分布直径的暴露情况。此外,对通勤者在一般人群中与交通有关的空气污染的暴露进行了模拟,以估计通勤对总暴露和吸入的贡献(即,上下班途中在交通途中花费的时间)剂量及其在交通相关空气污染的长期健康影响的流行病学研究中的相关性。 ud udMethods。进行了三个子研究,以表征个人在经常旅行的通勤微环境中暴露于UFP浓度和平均粒径分布直径的特征。个人监测运动是在2010年12月至2011年9月之间在巴塞尔市及其周边地区进行的,使用的是新开发的便携式设备,即微型扩散尺寸分类器(miniDiSC),该设备可测量10到300范围内的颗粒纳米首先,探讨了市区内人行道UFP暴露的空间变化以及特定于交通运输的微环境。每月一次按照四个预定的步行路线进行测量。其次,在一天和一周的不同时间,沿着同一路线,对五种运输方式(步行,自行车,公共汽车,电车,汽车)暴露于UFP浓度和平均粒径的情况进行了量化。最后,通过24小时个人测量评估了沿两条不同路线(沿主要道路,远离主要道路)通勤的自行车对每日总暴露量的贡献。在冬季,春季和夏季三个季节的每个工作日(星期一至星期五)中平均分配测量值。 与根据交通和空气污染的通勤者模拟,是基于在巴塞尔地区(巴塞尔市和巴塞尔州)工作(或上学)的居民的通勤出行的时空解析数据。关于通勤路线,交通方式以及家庭,工作和学校位置的信息是从2010年瑞士交通和运输微观人口普查中提取的。开发并验证了一种基于运输方式和腿的起点/终点位置(具有相同运输方式的行程片段)来模拟行驶路线的方法。通过在地理信息系统(GIS)中将位置和行进路线与NO2的年平均图重叠,来计算个人在通勤期间以及在家庭,工作和学校期间所遭受的NO2暴露。评估了三种空气污染模型(土地使用回归模型(LUR),高分辨率和低分辨率分散模型),以估计通勤者暴露于NO2中的程度,以此作为长期暴露于交通相关空气污染的标志。最后,仅使用室外户外暴露而忽略其他通勤暴露(包括通勤者暴露)所导致的健康影响估算偏差也得以量化。 ud ud本论文是欧洲项目“运输空气污染和体育活动(TAPAS)”的一部分,该项目是有关气候变化和城市政策的综合健康风险评估计划。 ud ud结果。通常,在靠近交通点的地方和交通方式中,要测量较小的平均粒径和较高的UFP浓度。汽车中UFP的平均浓度最高(31,800微粒cm-3),其次是自行车(22,700微粒cm-3),步行(19,500微粒cm-3)和公共交通(14,100-18),800粒子cm-3)。与其他时段相比,工作日早上高峰时段所有交通方式的浓度最高。无论时间长短,UFP浓度在公交车中最低。平均粒径遵循与UFP浓度相反的趋势,在较低的UFP数浓度下,运输模式和采样时间显示出较大的平均粒径,反之亦然。在家庭和工作地点之间的主要街道上骑自行车(平均24分钟)分别占冬季和夏季每日UFP总暴露量的21%和5%。如果避开主要道路,自行车通勤对每日UFP总暴露量的贡献可以减少一半。 在在巴塞尔市内,在所有空气污染模型中,上下班期间估计的平均时间加权NO2人群暴露量相似(约39-41 µg m–3)。如在城市街道环境中通常会遇到的那样,NO2浓度的空间变异性可以通过分辨率最高(25 m的网格尺寸)的弥散模型得到最好的反映。通过比较,LUR模型(适用于50x50 m的网格)和较低分辨率(100x100 m)的弥散模型都低估了较高端的NO2浓度,而高估了较低端的NO2浓度。 ud ud工作人口(> = 50%的工作量)或在巴塞尔地区上学的人每天通勤平均花费49分钟。工作或学校平均占课程时间的22%。通勤对每周总NO2暴露的中位数贡献为2.7%(范围为0.1-13.5%)。对于吸入剂量,在积极运输过程中,假设中等(3.5%,范围:0.2-16.8%)或高(4.2%,范围:0.2-33.0%)呼吸速率,通勤的贡献会更大。对于主要使用公共交通的受试者(通勤时间最长(超过一个小时)),通勤对NO2暴露总量的中位数贡献最大(4.7%,范围:1.3-13.5%)。然而,根据行程的不同,两种交通方式之间的比较显示出机动车交通中最高的NO2暴露。 ud ud如果无法区分工作/学校和家庭中的室外NO2暴露,可能会导致12 %(95%-CI:11-14%)低估了相关健康影响。对于在巴塞尔市和巴塞尔乡村从郊区到郊区的郊区通勤的人群(低估了33%),这种偏向要强于在这些地区内通勤的人群。对于同一人群,发现在家中和在工作/学校中包括户外暴露但在通勤期间忽略暴露可能导致健康影响显着低估(5%,95%-CI:4-5%) 。 ud ud结论和Outlook。本论文为城市地区UFP的时空变化提供了重要的见识,并为流行病学研究中通勤者暴露于交通相关的空气污染提供了一种方法。结果证实了人们在日常旅行中会暴露于潜在高暴露的期望,并且在流行病学研究中忽略时间活动模式会导致暴露分类错误和与健康相关的偏见。 ud ud在未来流行病学研究的暴露分配中纳入非居住区和每日通勤模式的好处应基于以下因素仔细评估:(1)所关注污染物的时空变异性,以及(2)空间扩散家庭和工作/学校的位置以及受试者的活动水平。因此,改进的曝光估计需要有关受试者的行进时间,距离,运输方式,出行时间,路线选择和工作量的信息。大型人群的未来暴露评估需要更频繁地将建模方法与关注污染物的实际个人暴露测量相结合,以改善和验证空间和时间上的暴露估计。

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    Ragettli Martina Simone;

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  • 年度 2015
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