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Characterizing the spatial distribution of ambient ultrafine particles in Toronto, Canada: A land use regression model

机译:加拿大多伦多表征环境超细颗粒的空间分布:土地利用回归模型

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Exposure models are needed to evaluate the chronic health effects of ambient ultrafine particles (<0.1 mu m) (UFPs). We developed a land use regression model for ambient UFPs in Toronto, Canada using mobile monitoring data collected during summer/winter 2010-2011. In total, 405 road segments were included in the analysis. The final model explained 67% of the spatial variation in mean UFPs and included terms for the logarithm of distances to highways, major roads, the central business district, Pearson airport, and bus routes as well as variables for the number of on-street trees, parks, open space, and the length of bus routes within a 100 m buffer. There was no systematic difference between measured and predicted values when the model was evaluated in an external dataset, although the R-2 value decreased (R-2 = 50%). This model will be used to evaluate the chronic health effects of UFPs using population-based cohorts in the Toronto area. Crown Copyright (C) 2015 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
机译:需要暴露模型来评估环境超细颗粒(<0.1微米)(UFPs)对慢性健康的影响。我们使用2010-2011年夏/冬期间收集的移动监测数据,为加拿大多伦多的UFP开发了土地利用回归模型。分析中总共包括405个路段。最终模型解释了平均UFP的67%的空间变化,其中包括到高速公路,主要道路,中央商务区,皮尔逊机场和公交路线的距离的对数,以及路边树木数量的变量,停车场,开放空间以及100 m缓冲区内的公交路线长度。在外部数据集中评估模型时,尽管R-2值降低了(R-2 = 50%),但实测值与预测值之间没有系统上的差异。该模型将用于通过多伦多地区基于人群的队列评估UFP的慢性健康影响。 Crown版权所有(C)2015,由Elsevier Ltd.发行。这是CC BY-NC-ND许可(http://creativecommons.org/licenses/by-nc-nd/4.0/)上的开放访问文章。

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