Dispersion Models, Mass Balance Models, and Indoor Pollution Sources
Monte Carlo Mass Balance Model. Ted Johnson developed a probabilistic mass balance model that has been used extensively in air pollution exposure assessments. The model uses Monte Carlo techniques to estimate air exchange rates, enclosure volumes, pollutant emission rates, and decay rates.
Factors Affecting Indoor Pollutant Levels. Ted Johnson conducted a review for EPA-OAQPS of the literature on how building design, ventilation, materials, and occupant activities affect indoor levels of hazardous air pollutants and associated health risks. The project focused on green building techniques and other methods to reduce emissions from consumer products. In a related project, he evaluated and compared the principal mass balance models available for estimating indoor pollutant levels.
Gas Stove Simulator. Ted Johnson developed the first Monte Carlo model for simulating the operation and emission rate patterns of gas stoves.
Window Opening Simulator. Ted Johnson developed the first Monte Carlo model for simulating the opening and closing of windows, a significant factor in determining air exchange rate.
Benzene from Attached Garages. Using field data collected in residences with attached garages, Ted Johnson developed a regression-based model for estimating the relative impact of attached garages and ambient benzene levels on residential benzene concentrations. A simplified version of this model was incorporated into HAPEM.
Optimal Receptor Spacing for Dispersion Modeling. Ted Johnson directed a statistical analysis by Mark Weaver of the effect that receptor point spacing has on the precision of dispersion model estimates for hazardous pollutants. Two methods for determining optimal receptor spacing were developed and then tested by applying each to five pollutants in two urban areas.
Ozone Exposures Based on ROM Dispersion Model Estimates. Ted Johnson developed a model for predicting the population exposure distribution of each cell included in a ROM grid. In related work, he compared ozone values obtained from fixed-site monitors in the eastern U.S. with corresponding no-control ROM/RTM III estimates for grid points near each monitor.