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Development and application of individual and population-level human exposure models for fine particles and other vehicle-related air pollutants in Southern California.

机译:在南加州,针对微粒和其他与车辆相关的空气污染物的个体和人群水平的人类暴露模型的开发和应用。

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In this study, spatial accuracy issues in roadway data and geocoding process were investigated to provide the most accurate data for exposure and epidemiological studies concerned with vehicle-related air pollution. Large discrepancies, up to hundreds of meters, were found between two widely used roadway networks. Inaccurate roadway geometry and geocoding errors can lead to serious exposure misclassifications, on the order of factors of three to ten in assigned pollutant concentrations. A GIS-based algorithm we developed was effective in transferring vehicle activity information from a less accurate USGS roadway network to a GPS-accurate road network.; An individual exposure model was developed to quantify exposures to vehicle-related pollutants for the children in the Southern California Children's Health Study by taking into account time-activity patterns, local emissions, and regional pollution effects. Local traffic significantly increased within-community variability of exposure to vehiclerelated pollutants. The overall within-community variability of personal exposures was highest for NO2, followed by EC, PM10, PM2.5, and CO. Between-community exposure differences were affected by community location, traffic density, and locations of residences and schools in each community.; Besides the individual level exposure assessment, the population exposure to naphthalene was quantified for the first time for the California South Coast Air Basin by linking the Surface Meteorology and Ozone Generation airshed model and the Regional Human Exposure model. Average hourly naphthalene exposures in the SoCAB under summer and winter conditions were 270 ng m-3 and 430 ng m-3, respectively. More than one million and one thousand individuals were estimated to experience naphthalene exposure greater than 1000 and 3000 ng m-3, respectively.; The environmental justice issue was also investigated with respect to disproportionate exposure to vehicle-generated pollutants. Minority and high-poverty neighborhoods were found to have a higher population density, lower housing value, higher density of highways and major roads, and older and more multifamily housing. These neighborhoods bear over two times the level of traffic density compared to the rest of the Southern California region, which may associate them with a higher risk of exposure to vehicle-related pollutants.
机译:在这项研究中,调查了道路数据和地理编码过程中的空间准确性问题,以为与车辆相关的空气污染有关的暴露和流行病学研究提供最准确的数据。在两个广泛使用的巷道网络之间发现了长达数百米的巨大差异。不正确的巷道几何形状和地理编码错误会导致严重的暴露分类错误,在指定的污染物浓度中大约为三到十倍。我们开发的基于GIS的算法可有效地将车辆活动信息从不太准确的USGS道路网络传输到GPS精确道路网络。在南加州儿童健康研究中,通过考虑时间活动模式,局部排放和区域污染影响,开发了一种个体暴露模型来量化儿童对车辆相关污染物的暴露。当地交通显着增加了社区内车辆相关污染物暴露的变异性。对于NO2,个人暴露的总体社区内部变异性最高,其次是EC,PM10,PM2.5和CO。社区之间的暴露差异受社区位置,交通密度以及每个社区中住宅和学校的位置的影响。 。;除了个人暴露量评估外,通过将地表气象学和臭氧生成模型与区域人类暴露模型联系起来,加利福尼亚州南海岸空气盆地首次对萘的暴露量进行了量化。夏季和冬季条件下,SoCAB中每小时平均萘暴露量分别为270 ng m-3和430 ng m-3。估计分别有超过一百万和一千个人的萘暴露量超过1000和3000 ng m-3。还对与汽车产生的污染物不成比例的暴露进行了环境正义问题的调查。发现少数民族和高贫困社区的人口密度较高,住房价值较低,公路和主要道路的密度较高,以及较老的多家庭住房。与南加州其他地区相比,这些社区的交通密度水平是其两倍以上,这可能使它们与接触车辆相关污染物的风险更高。

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