Quantitative Validation of Control Bands Using Bayesian Statistical Analyses.

This study presents a quantitative validation of 15 Similar Exposure Groups (SEGs) that were derived via control bands inherent to the Risk Level Based Management System currently being used at the Lawrence Livermore National Laboratory. For 93% of the SEGs that were evaluated, statistical analyses of personal exposure monitoring data, through Bayesian Decision Analysis (BDA), demonstrated that the controls implemented from the initial control bands assigned to these SEGs were at least as protective as the controls from the control band outcomes derived from the quantitative data. The BDA also demonstrated that for 40% of the SEGs, the controls from the initial control bands were overly protective, thus allowing controls to be downgraded, which resulted in a significant saving of environmental safety and health (ES&H) resources. Therefore, as a means to both confirm existing controls and to identify candidate SEGs for downgrading controls, efforts to continuously improve the accuracy of Control Banding (CB) strategies through the routine quantitative validation of SEGs are strongly encouraged. Targeted collaborative efforts across institutions and even countries for both the development of CB strategies and the validation of discreetly defined SEGs of commonly performed tasks will not only optimize limited ES&H resources but will also assist in providing a simplified process for essential risk communication at the worker level to the benefit of billions of workers around the world.

Personal exposure to fine particulate air pollution while commuting: An examination of six transport modes on an urban arterial roadway.

Traffic-related air pollution in urban areas contributes significantly to commuters' daily PM2.5 exposures, but varies widely depending on mode of commuting. To date, studies show conflicting results for PM2.5 exposures based on mode of commuting, and few studies compare multiple modes of transportation simultaneously along a common route, making inter-modal comparisons difficult. In this study, we examined breathing zone PM2.5 exposures for six different modes of commuting (bicycle, walking, driving with windows open and closed, bus, and light-rail train) simultaneously on a single 2.7 km (1.68 mile) arterial urban route in Salt Lake City, Utah (USA) during peak "rush hour" times. Using previously published minute ventilation rates, we estimated the inhaled dose and exposure rate for each mode of commuting. Mean PM2.5 concentrations ranged from 5.20 µg/m3 for driving with windows closed to 15.21 µg/m3 for driving with windows open. The estimated inhaled doses over the 2.7 km route were 6.83 µg for walking, 2.78 µg for cycling, 1.28 µg for light-rail train, 1.24 µg for driving with windows open, 1.23 µg for bus, and 0.32 µg for driving with windows closed. Similarly, the exposure rates were highest for cycling (18.0 µg/hr) and walking (16.8 µg/hr), and lowest for driving with windows closed (3.7 µg/hr). Our findings support previous studies showing that active commuters receive a greater PM2.5 dose and have higher rates of exposure than commuters using automobiles or public transportation. Our findings also support previous studies showing that driving with windows closed is protective against traffic-related PM2.5 exposure.