Petroleum refineries emit a variety of airborne substances which may be harmful to human health. HEIDI II (Health Effects Indicators Decision Index II) is a computer-based decision analysis tool which assesses airborne emissions from Canada's oil refineries for reduction, based on ordinal ranking of estimated health impacts. The model was designed by a project team within NERAM (Network for Environmental Risk Assessment and Management) and assembled with significant stakeholder consultation. HEIDI II is publicly available as a deterministic Excel-based tool which ranks 31 air pollutants based on predicted disease incidence or estimated DALYS (disability adjusted life years). The model includes calculations to account for average annual emissions, ambient concentrations, stack height, meteorology/dispersion, photodegradation, and the population distribution around each refinery. Different formulations of continuous dose-response functions were applied to nonthreshold-acting air toxics, threshold-acting air toxics, and nonthreshold-acting CACs (criteria air contaminants). An updated probabilistic version of HEIDI II was developed using Matlab code to account for parameter uncertainty and identify key leverage variables. Sensitivity analyses indicate that parameter uncertainty in the model variables for annual emissions and for concentration-response/toxicological slopes have the greatest leverage on predicted health impacts. Scenario analyses suggest that the geographic distribution of population density around a refinery site is an important predictor of total health impact. Several ranking metrics (predicted case incidence, simple DALY, and complex DALY) and ordinal ranking approaches (deterministic model, average from Monte Carlo simulation, test of stochastic dominance) were used to identify priority substances for reduction; the results were similar in each case. The predicted impacts of primary and secondary particulate matter (PM) consistently outweighed those of the air toxics. Nickel, PAH (polycyclic aromatic hydrocarbons), BTEX (benzene, toluene, ethylbenzene and xylene), sulphuric acid, and vanadium were consistently identified as priority air toxics at refineries where they were reported emissions. For many substances, the difference in rank order is indeterminate when parametric uncertainty and variability are considered.

Benzene is an important toxic chemical in urban air and known human carcinogen released substantially by mobile sources. It's important to understand the spatial variation of benzene concentrations in order to understand exposures of susceptible sub-populations such as children and minority groups. Current monitoring networks use large and expensive air samplers that require electricity and restrict the location and number of samplers, not allowing for fine spatial resolution data. The goals of this study are to develop and evaluate protocols for passive sampling and analysis of ambient benzene concentrations, and conduct a pilot study investigating small-scale variations over an area where children are likely to be exposed. Protocols were developed for the use and analysis of the Radiello RAD130 passive sampler for field sampling over the spatial scale of a city park adjacent to an elementary school. A pilot study was conducted from 4/27/11-5/4/11, where 11 samplers were exposed for a seven day sampling period at the park. After sampler exposure, benzene concentrations were determined through solvent desorption followed by analysis using a Varian gas chromatograph with mass spectrometer. Co-location with the existing regulatory active sampler in the county and of two samplers at the same site was done to evaluate the accuracy and precision of the methods, respectively. Health risk estimates were calculated using risk assessment guidance from the U.S. and California Environmental Protection Agencies. Concentrations over the park were found to range from 0.23 0.34 µg m^-3 with a coefficient of variation of 11%. A relative percent difference of 3% was found between the co-located sampler and the active sampler, and a 14% relative percent difference was found between the two duplicate samplers. The variation in health risk from concentration variation due to sampler placement contributed less to the overall uncertainty in the estimates than the uncertainty built in to the calculation parameters of inhalation unit risk and cancer potency factor, as estimated by the U.S. EPA and California EPA, respectively. These results suggest that the exposure of an individual at the park would be characterized sufficiently for standard health risk analysis through the use of one sampler. Further research is necessary into using passive samplers over both the same spatial scale in other areas, as well as on a larger scale to determine intra-urban benzene concentration distributions. The protocols developed here will be used in a future planned study of benzene concentration measurements to characterize neighborhood-scale exposures in Hillsborough County.