Yang Aileen, Wang Meng, Eeftens Marloes, Beelen Rob, Dons Evi, Leseman Daan L A C, Brunekreef Bert, Cassee Flemming R, Janssen Nicole A H, Hoek Gerard
National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands.
Environ Health Perspect. 2015 Nov;123(11):1187-92. doi: 10.1289/ehp.1408916. Epub 2015 Apr 3.
Oxidative potential (OP) has been suggested to be a more health-relevant metric than particulate matter (PM) mass. Land use regression (LUR) models can estimate long-term exposure to air pollution in epidemiological studies, but few have been developed for OP.
We aimed to characterize the spatial contrasts of two OP methods and to develop and evaluate LUR models to assess long-term exposure to the OP of PM2.5.
Three 2-week PM2.5 samples were collected at 10 regional background, 12 urban background, and 18 street sites spread over the Netherlands/Belgium in 1 year and analyzed for OP using electron spin resonance (OP(ESR)) and dithiothreitol (OP(DTT)). LUR models were developed using temporally adjusted annual averages and a range of land-use and traffic-related GIS variables.
Street/urban background site ratio was 1.2 for OP(DTT) and 1.4 for OP(ESR), whereas regional/urban background ratio was 0.8 for both. OP(ESR) correlated moderately with OP(DTT) (R2 = 0.35). The LUR models included estimated regional background OP, local traffic, and large-scale urbanity with explained variance (R2) of 0.60 for OP(DTT) and 0.67 for OP(ESR). OP(DTT) and OP(ESR) model predictions were moderately correlated (R2 = 0.44). OP model predictions were moderately to highly correlated with predictions from a previously published PM2.5 model (R2 = 0.37-0.52), and highly correlated with predictions from previously published models of traffic components (R2 > 0.50).
LUR models explained a large fraction of the spatial variation of the two OP metrics. The moderate correlations among the predictions of OP(DTT), OP(ESR), and PM2.5 models offer the potential to investigate which metric is the strongest predictor of health effects.
Yang A, Wang M, Eeftens M, Beelen R, Dons E, Leseman DL, Brunekreef B, Cassee FR, Janssen NA, Hoek G. 2015. Spatial variation and land use regression modeling of the oxidative potential of fine particles. Environ Health Perspect 123:1187-1192; http://dx.doi.org/10.1289/ehp.1408916.
氧化潜力（OP）被认为是一种比颗粒物（PM）质量更与健康相关的指标。土地利用回归（LUR）模型可在流行病学研究中估算空气污染的长期暴露情况，但针对OP开发的模型较少。
我们旨在描述两种OP方法的空间差异，并开发和评估LUR模型以评估长期暴露于PM2.5的OP。
一年内，在荷兰/比利时的10个区域背景点、12个城市背景点和18个街道站点采集了三个为期2周的PM2.5样本，并使用电子自旋共振（OP(ESR)）和二硫苏糖醇（OP(DTT)）分析OP。使用经时间调整的年平均值以及一系列与土地利用和交通相关的地理信息系统变量开发LUR模型。
街道/城市背景站点的OP(DTT)比值为1.2，OP(ESR)比值为1.4，而区域/城市背景比值两者均为0.8。OP(ESR)与OP(DTT)呈中度相关（R2 = 0.35）。LUR模型包括估算的区域背景OP、局部交通和大规模城市化，OP(DTT)的解释方差（R2）为0.60，OP(ESR)为0.67。OP(DTT)和OP(ESR)模型预测呈中度相关（R2 = 0.44）。OP模型预测与先前发表的PM2.5模型预测呈中度至高度相关（R2 = 0.37 - 0.52），与先前发表的交通成分模型预测高度相关（R2 > 0.50）。
LUR模型解释了两种OP指标空间变化的很大一部分。OP(DTT)、OP(ESR)和PM2.5模型预测之间的中度相关性为研究哪种指标是健康影响的最强预测因子提供了可能性。
Yang A, Wang M, Eeftens M, Beelen R, Dons E, Leseman DL, Brunekreef B, Cassee FR, Janssen NA, Hoek G. 2015. 细颗粒物氧化潜力的空间变化及土地利用回归建模。环境健康展望123:1187 - 1192；http://dx.doi.org/10.1289/ehp.1408916 。
