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Development of Land Use Regression models for predicting exposure to NO2 and NOx in Metropolitan Perth, Western Australia

机译:开发土地利用回归模型以预测西澳大利亚州珀斯大都会的NO2​​和NOx暴露

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This study developed LUR models for predicting exposure to NO2 and NOx among of 12,203 elderly men in Perth. NOx and NO2 concentrations were determined for 2-week periods in summer, autumn, and winter, from January to September 2012, at 43 sites. The LUR models were developed to predict annual average concentrations of nitric oxides based upon land use, population/household density, and traffic variables within different buffer sizes, following the procedures of the European Study of Cohort for Air Pollution Effects program. The sample mean and standard deviation of the annual average concentrations of NO2 and NOx were 10.1 +/- 5.3 mu g/m(3) and 18.7 +/- 11.7 mu g/m(3) respectively, lower than those of ESCAPE study areas. The LUR models explained 69% of the variance in NO2 and 75% variance of NOx. Both the NO2 and NOx models had similar predictors, including traffic intensity on the nearest roads, household density within-1000 m industrial activities within-5000 m, and road length within-50 m. (C) 2015 Elsevier Ltd. All rights reserved.
机译:这项研究开发了LUR模型,用于预测珀斯的12203名老年男性中NO2和NOx的暴露。从2012年1月至2012年9月,在43个站点的夏季,秋季和冬季的2周时间内确定了NOx和NO2的浓度。根据欧洲空气污染影响研究队列程序的程序,开发了LUR模型以根据土地使用,人口/家庭密度和不同缓冲区大小内的交通变量来预测一氧化氮的年平均浓度。 NO2和NOx的年平均浓度的样本平均值和标准偏差分别为10.1 +/- 5.3μg / m(3)和18.7 +/- 11.7μg / m(3),低于ESCAPE研究区域的平均值。 LUR模型解释了NO2变化的69%和NOx变化的75%。 NO2和NOx模型具有相似的预测指标,包括最近道路上的交通强度,在1000 m之内1000m以内的家庭密度,在5000 m之内的工业活动以及在50 m之内的道路长度。 (C)2015 Elsevier Ltd.保留所有权利。

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