Airborne exposures to polycyclic aromatic hydrocarbons (PAHs) are associated with adverse health outcomes. Because personal air measurements of PAHs are labor intensive and costly, spatial PAH exposure models are useful for epidemiological studies. However, few studies provide adequate spatial coverage to reflect intra-urban variability of ambient PAHs. In this study, we collected 39–40 weekly gas-phase PAH samples in southern California twice in summer and twice in winter, 2009, in order to characterize PAH source contributions and develop spatial models that can estimate gas-phase PAH concentrations at a high resolution. A spatial mixed regression model was constructed, including such variables as roadway, traffic, land-use, vegetation index, commercial cooking facilities, meteorology, and population density. Cross validation of the model resulted in an R² of 0.66 for summer and 0.77 for winter. Results showed higher total PAH concentrations in winter. Pyrogenic sources, such as fossil fuels and diesel exhaust, were the most dominant contributors to total PAHs.

PAH sources varied by season, with a higher fossil fuel and wood burning contribution in winter. Spatial autocorrelation accounted for a substantial amount of the variance in total PAH concentrations for both winter (56%) and summer (19%). In summer, other key variables explaining the variance included meteorological factors (9%), population density (15%), and roadway length (21%). In winter, the variance was also explained by traffic density (16%). In this study, source characterization confirmed the dominance of traffic and other fossil fuel sources to total measured gas-phase PAH concentrations while a spatial exposure model identified key predictors of PAH concentrations. Gas-phase PAH source characterization and exposure estimation is of high utility to epidemiologist and policy makers interested in understanding the health impacts of gas-phase PAHs and strategies to reduce emissions.

空气中暴露于多环芳烃（PAHs）与不良健康后果相关。由于个人空气中多环芳烃的测量非常费力且昂贵，因此空间多环芳烃暴露模型可用于流行病学研究。但是，很少有研究提供足够的空间覆盖范围以反映环境PAH的城市内部变化。在本研究中，我们于2009年夏季和冬季两次在加利福尼亚南部采集了39–40个每周的气相PAH样品，以表征PAH的来源，并建立可估算高浓度气相PAH浓度的空间模型。解析度。构建了空间混合回归模型，包括道路，交通，土地利用，植被指数，商业烹饪设施，气象学和人口密度等变量。² 0.66夏季和0.77冬季。结果显示冬季总PAH浓度较高。化石燃料和柴油废气等热源是多环芳烃总量的最主要来源。

多环芳烃的来源因季节而异，冬季的化石燃料和木材燃烧贡献较高。在冬季（56％）和夏季（19％）的总PAH浓度差异中，空间自相关性占很大的比例。在夏季，解释这一差异的其他关键变量包括气象因素（9％），人口密度（15％）和巷道长度（21％）。在冬季，交通密度（16％）也可以解释这种差异。在这项研究中，来源特征确定了交通和其他化石燃料来源对总的气相PAH浓度的支配地位，而空间暴露模型确定了PAH浓度的关键预测因子。