Source proximity and meteorological effects on residential outdoor VOCs in urban areas: Results from the Houston and Los Angeles RIOPA studies.

Concentrations of volatile organic compounds (VOCs) measured outside homes in Houston, TX and Los Angeles, CA were characterized by the effects of source proximity and meteorological factors. Benzene, toluene, ethylbenzene, m,p-xylene, o-xylene (BTEX), methyl tert butyl ether (MTBE), tetrachloroethylene (perchloroethylene, PCE), and carbon tetrachloride (CCl4 ) were examined. Multiple stepwise regression analysis converged the best-fit models with predictors from meteorological conditions and the proximity to specific point, area, and mobile sources on the residential outdoor VOC concentrations. Negative associations of wind speed with concentrations demonstrated the effect of dilution by high wind speed. Atmospheric stability increase was associated with concentration increase. Petrochemical source proximity was a significant predictor for BTEX and MTBE concentrations in Houston. Ethylbenzene and xylene source proximity was a significant predictor in Los Angeles. Close proximity to area sources such as scrap metal recycling or dry cleaning facilities increased the MTBE, PCE, and CCl4 concentrations in Houston and Los Angeles. Models for ethylbenzene, m,p-xylene, and MTBE in Houston, and benzene in Los Angeles explained that for the median values of the meteorological factors, homes closest to influential highways would have concentrations that were 1.7-2.2 fold higher than those furthest from these mobile emission sources. If the median distance to sources were used in the models, the VOC concentrations varied 1.7 to 6.6 fold as the meteorological conditions varied over the observed range. These results highlight that each urban area is unique and localized sources need to be carefully evaluated to understand potential contributions to VOC air concentrations near residences, which influence baseline indoor air concentrations and personal exposures. Results of this study could assist in the appropriate design of monitoring networks for community-level sampling. They may also improve the accuracy of exposure models linking emission sources with estimated pollutant concentrations at the residential level.