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Capturing the urban canyon effect on particle number concentrations across a large road network using spatial analysis tools

机译:使用空间分析工具捕获整个大型路网中城市峡谷对颗粒数量浓度的影响

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Urban canyons increase overall air pollution concentrations at the street level. Yet, due to the difficulty in characterizing such geometric features over a regional area, they are rarely included in the evaluation of population exposures. This study combines measurements of ultrafine particles (UFP) with land-use regression techniques in order to capture the determinants of near-road concentrations of UFP while specifically accounting for urban canyon effects. Using the mean UFP concentration measured within a set of urban canyons (over 1000 road segments) as the dependent variable, we investigated the effects of a number of urban canyon descriptors (width, height, contiguity, vegetation, and road class) through a multivariate linear regression. Our models are adjusted for the effects of meteorology. The signs and values of the regression coefficients are qualitatively consistent with what is already known about urban canyons: increased building height (b(height) = 0.004; 95% CI: 0.001, 0.007) along with decreased canyon width (b(width) = -0.007; 95% CI: -0.012, -0.002) serve to worsen the air quality therein, while increased tree cover (b(trees) = -1.762; 95% CI: -2.236, -1.289) improves air quality. We also observed that the difference in UFP levels on both sides of the canyon increased with increasing street width (b(width) = 0.113; 95% CI: 0.061, 0.165), and with wind direction more perpendicular to the street. We conclude that it is possible to include urban canyon effects in the development of air pollution exposure surfaces thus refining the assessment of population exposure to air pollution in urban microenvironments. (C) 2015 Elsevier Ltd. All rights reserved.
机译:城市峡谷增加了街道一级的总体空气污染浓度。但是,由于难以在区域范围内表征此类几何特征,因此很少将其包含在人口暴露评估中。这项研究将超细颗粒(UFP)的测量与土地利用回归技术相结合,以便捕获UFP的近路浓度决定因素,同时专门考虑城市峡谷效应。使用一组城市峡谷(超过1000个路段)中测得的UFP平均浓度作为因变量,我们通过多元调查了许多城市峡谷描述符(宽度,高度,邻接性,植被和道路等级)的影响线性回归。我们的模型已针对气象学影响进行了调整。回归系数的符号和值在质量上与已知的城市峡谷一致:建筑物高度增加(b(高度)= 0.004; 95%CI:0.001、0.007),同时峡谷宽度减小(b(width)= -0.007; 95%CI:-0.012,-0.002)使空气质量恶化,而增加树木覆盖率(b(trees)= -1.762; 95%CI:-2.236,-1.289)改善空气质量。我们还观察到,峡谷两边的UFP水平差异随着街道宽度的增加而增加(b(宽度)= 0.113; 95%CI:0.061,0.165),并且风向更垂直于街道。我们得出的结论是,有可能将城市峡谷效应纳入空气污染暴露面的开发中,从而完善对城市微环境中空气污染人群的暴露评估。 (C)2015 Elsevier Ltd.保留所有权利。

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