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基于道路移动监测和短期路边静态测量的空气污染暴露面的开发与比较。

Development and Comparison of Air Pollution Exposure Surfaces Derived from On-Road Mobile Monitoring and Short-Term Stationary Sidewalk Measurements.

机构信息

Department of Civil Engineering , University of Toronto , 35 St. George Street , Toronto , Ontario M5S 1A4 , Canada.

Division of Clinical Epidemiology, Faculty of Medicine , McGill University , Montreal , Quebec H3A 1A2 , Canada.

出版信息

Environ Sci Technol. 2018 Mar 20;52(6):3512-3519. doi: 10.1021/acs.est.7b05059. Epub 2018 Mar 6.

Abstract

Land-use regression (LUR) models of air pollutants are frequently developed on the basis of short-term stationary or mobile monitoring approaches, which raises the question of whether these two data collection protocols lead to similar exposure surfaces. In this study, we measured ultrafine particles (UFP) and black carbon (BC) concentrations in Toronto during summer 2016, using two short-term data collection approaches: mobile, involving 3023 road segments sampled on bicycles, and stationary, involving 92 sidewalk locations. We developed four LUR models and exposure surfaces, for the two pollutants and measurement protocols. Coefficients of determination ( R) varied from 0.434 to 0.525. Various small-scale traffic variables were included in the mobile LUR. Pearson correlation coefficients between the mobile and stationary surfaces were 0.23 for UFP and 0.49 for BC. We also compared the two surfaces using personal exposures from a panel study in Toronto conducted during the same period. The personal exposures differed from the outdoor exposures derived from the combination of GPS information and exposure surfaces. For UFP, the median for personal outdoor exposure was 26 344 part/cm, while the cycling and stationary surfaces predicted medians of 31 201 and 19 057 part/cm. Similar trends were observed for BC, with median exposures of 1764 (personal), 1799 (cycling), and 1469 ng/m (stationary).

摘要

基于短期的静态或移动监测方法来建立空气污染物的空气动力学粒径(LUR)模型,这引发了一个问题,即这两种数据收集方案是否会产生相似的暴露面。在这项研究中,我们在 2016 年夏季于多伦多使用两种短期数据收集方法来测量超细颗粒(UFP)和黑碳(BC)浓度:移动监测,涉及在自行车上采样的 3023 个道路段;以及静态监测,涉及 92 个人行道位置。我们针对两种污染物和测量方案开发了四个 LUR 模型和暴露面。决定系数(R)从 0.434 到 0.525 不等。移动 LUR 中包含了各种小规模的交通变量。UFP 移动和静态暴露面之间的皮尔逊相关系数为 0.23,BC 为 0.49。我们还使用同期在多伦多进行的一项面板研究中的个人暴露数据来比较这两个暴露面。个人暴露与通过 GPS 信息和暴露面得出的室外暴露不同。对于 UFP,个人室外暴露的中位数为 26344 个/立方厘米,而骑自行车和静态暴露面预测的中位数分别为 31201 个和 19057 个/立方厘米。BC 也呈现出类似的趋势,个人暴露、骑自行车和静态暴露的中位数分别为 1764(个人)、1799(骑自行车)和 1469ng/m(静态)。

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