TNO, Netherlands Organization for Applied Scientific Research, Utrecht, The Netherlands.
Environ Sci Technol. 2014 Dec 16;48(24):14435-44. doi: 10.1021/es502568z. Epub 2014 Nov 6.
Land use regression (LUR) models have been used to model concentrations of mainly traffic-related air pollutants (nitrogen oxides (NOx), particulate matter (PM) mass or absorbance). Few LUR models are published of PM composition, whereas the interest in health effects related to particle composition is increasing. The aim of our study was to evaluate LUR models of polycyclic aromatic hydrocarbons (PAH), hopanes/steranes, and elemental and organic carbon (EC/OC) content of PM2.5. In 10 European study areas, PAH, hopanes/steranes, and EC/OC concentrations were measured at 16-40 sites per study area. LUR models for each study area were developed on the basis of annual average concentrations and predictor variables including traffic, population, industry, natural land obtained from geographic information systems. The highest median model explained variance (R(2)) was found for EC - 84%. The median R(2) was 51% for OC, 67% for benzo[a]pyrene, and 38% for sum of hopanes/steranes, with large variability between study areas. Traffic predictors were included in most models. Population and natural land were included frequently as additional predictors. The moderate to high explained variance of LUR models and the overall moderate correlation with PM2.5 model predictions support the application of especially the OC and PAH models in epidemiological studies.
土地利用回归 (LUR) 模型已被用于模拟主要与交通相关的空气污染物（氮氧化物 (NOx)、颗粒物 (PM) 质量或吸光度）的浓度。发表的 PM 成分 LUR 模型很少，而与颗粒成分相关的健康影响的兴趣正在增加。我们的研究目的是评估 PM2.5 中多环芳烃 (PAH)、藿烷/甾烷以及元素和有机碳 (EC/OC) 含量的 LUR 模型。在 10 个欧洲研究区域中，在每个研究区域的 16-40 个站点测量了 PAH、藿烷/甾烷和 EC/OC 浓度。基于每年的平均浓度和预测变量（包括交通、人口、工业和地理信息系统获得的自然土地），为每个研究区域开发了 LUR 模型。发现 EC 的最高中位数模型解释方差 (R(2))为 84%。OC 的中位数 R(2)为 51%，苯并[a]芘为 67%，藿烷/甾烷总和为 38%，各研究区域之间的差异很大。大多数模型都包含交通预测因子。人口和自然土地经常作为附加预测因子包含在内。LUR 模型的解释方差适中到较高，与 PM2.5 模型预测的整体中等相关性支持在流行病学研究中应用 OC 和 PAH 模型。
