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Performance of Multi-City Land Use Regression Models for Nitrogen Dioxide and Fine Particles

机译:二氧化氮和细颗粒物多城市土地利用回归模型的性能

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摘要

Background: Land use regression (LUR) models have been developed mostly to explain intraurban variations in air pollution based on often small local monitoring campaigns. Transferability of LUR models from city to city has been investigated, but little is known about the performance of models based on large numbers of monitoring sites covering a large area.Objectives: We aimed to develop European and regional LUR models and to examine their transferability to areas not used for model development.Methods: We evaluated LUR models for nitrogen dioxide (NO2) and particulate matter (PM; PM2.5, PM2.5 absorbance) by combining standardized measurement data from 17 (PM) and 23 (NO2) ESCAPE (European Study of Cohorts for Air Pollution Effects) study areas across 14 European countries for PM and NO2. Models were evaluated with cross-validation (CV) and hold-out validation (HV). We investigated the transferability of the models by successively excluding each study area from model building.Results: The European model explained 56% of the concentration variability across all sites for NO2, 86% for PM2.5, and 70% for PM2.5 absorbance. The HV R2s were only slightly lower than the model R2 (NO2, 54%; PM2.5, 80%; PM2.5 absorbance, 70%). The European NO2, PM2.5, and PM2.5 absorbance models explained a median of 59%, 48%, and 70% of within-area variability in individual areas. The transferred models predicted a modest-to-large fraction of variability in areas that were excluded from model building (median R2: NO2, 59%; PM2.5, 42%; PM2.5 absorbance, 67%).Conclusions: Using a large data set from 23 European study areas, we were able to develop LUR models for NO2 and PM metrics that predicted measurements made at independent sites and areas reasonably well. This finding is useful for assessing exposure in health studies conducted in areas where no measurements were conducted.Citation: Wang M, Beelen R, Bellander T, Birk M, Cesaroni G, Cirach M, Cyrys J, de Hoogh K, Declercq C, Dimakopoulou K, Eeftens M, Eriksen KT, Forastiere F, Galassi C, Grivas G, Heinrich J, Hoffmann B, Ineichen A, Korek M, Lanki T, Lindley S, Modig L, Mölter A, Nafstad P, Nieuwenhuijsen MJ, Nystad W, Olsson D, Raaschou-Nielsen O, Ragettli M, Ranzi A, Stempfelet M, Sugiri D, Tsai MY, Udvardy O, Varró MJ, Vienneau D, Weinmayr G, Wolf K, Yli-Tuomi T, Hoek G, Brunekreef B. 2014. Performance of multi-city land use regression models for nitrogen dioxide and fine particles. Environ Health Perspect 122:843–849; 
机译:背景:土地使用回归(LUR)模型主要是根据通常的小型地方监测活动来解释城市内部空气污染的变化而开发的。已经研究了LUR模型在城市之间的可传递性,但是对于基于覆盖大面积区域的大量监视站点的模型的性能知之甚少。目的:我们旨在开发欧洲和区域LUR模型并研究其在城市中的可传递性。方法:我们结合了17(PM)和23(NO2)ESCAPE的标准化测量数据,评估了LUR模型中的二氧化氮(NO2)和颗粒物(PM; PM2.5,PM2.5吸收度)模型(欧洲空气污染影响研究队列)研究了14个欧洲国家的PM和NO2区域。使用交叉验证(CV)和保持验证(HV)评估模型。我们通过从模型构建中逐个排除每个研究区域来研究模型的可传递性。结果:欧洲模型解释了所有站点中NO2的浓度变化为56%,PM2.5的浓度变化为86%,PM2.5的吸收度为70%。 。 HV R 2 s仅略低于模型R 2 (NO2,54%; PM2.5,80%; PM2.5吸光度,70%)。欧洲NO2,PM2.5和PM2.5吸光度模型解释了各个区域内区域内变化的中位数分别为59%,48%和70%。转移的模型预测了从模型构建中排除的区域中的变量的适度到较大比例(R 2 中位数:NO2,59%; PM2.5,42%; PM 2.5 的吸光度,为67%)。结论:使用来自23个欧洲研究区的大量数据,我们能够针对NO 2 和PM指标开发LUR模型,以预测在独立地点进行的测量和地区都还算不错。这一发现对于评估未进行测量的地区的健康研究非常有用。 K,Eeftens M,Eriksen KT,Forastiere F,Galassi C,Grivas G,Heinrich J,Hoffmann B,Ineichen A,Korek M,Lanki T,Lindley S,Modig L,MölterA,Nafstad P,Nieuwenhuijsen MJ,Nystad W,奥尔森(Olsson D),拉肖(Raaschou-Nielsen)O,拉吉特利(Ragettli M),兰兹(Ranzi)A,斯滕普莱特(Stempfelet)M,苏吉里(Sugiri D),蔡(Tsai)我,乌德瓦迪(Ovvardy)O,瓦罗(VarróMJ),维纳瑙(Vienneau D),魏纳迈尔(Weinmayr G),沃尔夫(Wolf K),伊莉-图奥米(Yli-Tuomi T),霍克(Hoek G),布鲁内克里夫(Brunekreef B)。二氧化氮和细颗粒的多城市土地利用回归模型的性能。环境健康展望122:843–849;

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