Testing U.S. EPA's ISCST -Version 3 Model On Dioxins: A Comparison Of Predicted And Observed Air And Soil Concentrations
The central purpose of our study was to examine the performance of the United States Environmental Protection Agency's (EPA) nonreactive Gaussian air quality dispersion model, the Industrial Source Complex Short Term Model (ISCST3) Version 98226, in predicting polychlorinated dibenzodioxins and polychlorinated dibenzofurans concentrations (subsequently referred to as dioxins and furans, or CDD/Fs) in both air and soil near the Columbus Municipal Solid Waste-to-Energy Facility (CMSWTE) in Columbus, Ohio. During its eleven year operation, the CMSWTE was estimated to be emitting nearly 1 kg of CDD/F Toxic Equivalents (TEQs) per year, making it one of the highest single emitters of dioxin in the United States during its operation. An ambient air monitoring study conducted in 1994, prior to its shutdown in December of 1994, clearly identified high dioxin air concentration in the downwind direction during two sampling events. In one of the events, the CMSWTE stack was concurrently monitored for dioxins. A soil sampling study conducted in 1995/96 was similarly able to identify an area of impacted soil extending mainly in the predominant downwind direction up to 3 km from the CMSWTE. Site-specific information, including meteorological data, stack parameters and emission rates, and terrain descriptions, were input into ISCST3 to predict ground-level 48-hr concentrations which could be compared with the 48-hr measured air concentrations. Predicted annual average dry and wet deposition of particle-bound dioxins were input into a simple soil reservoir model to predict soil concentrations that would be present after 11.5 years of emissions, which were compared to measured concentrations. Both soil and air predicted concentrations were generally within a factor of ten of observations, and judged to be reasonable given the small number of observations and the uncertainties of the exercise. Principal uncertainties identified and discussed include: source characterization (stack emission rates of dioxins), meteorological data, and atmospheric and soil fate and transformation processes of the dioxins.