Date of Award
Master of Science
Department of Systems Engineering and Management
Dirk P. Yamamoto, PhD.
United States military forces in Iraq and Afghanistan have often used open burning of solid waste as a means to achieve volume reduction and to minimize vector borne illnesses. Assessing exposures to burn pit emissions has proven challenging, requiring significant numbers of personnel and sampling equipment. This study examined the use of three common dispersion models to determine the feasibility of using software modeling to predict short-range exposures to burn pit emissions, in lieu of sole reliance on ground sampling. Four open burn tests of municipal solid waste were conducted at Tooele Army Depot, Utah. Aerial samples were collected above the burns to determine emission factors for CO2 and PM2.5. Three atmospheric dispersion modeling software packages, ALOHA, HPAC, and HYSPLIT, were populated with the emission factors to determine how well they predicted ground concentrations of carbon dioxide (CO2) and fine particulate matter (PM2.5) at nearby monitoring stations. Results of this study show that ALOHA and HPAC did not accurately predict ground concentrations at the microscale resolution. HYSPLIT performed better than other models with more accurate predictions of CO2 for two of the four days. This limited testing suggests that more robust ground sampling is necessary to improve assessment of model performance. Additionally, more frequent input of accurate weather data will likely improve the predictive power of these models.
DTIC Accession Number
Oppenheimer, Val, "Prototyping the use of Dispersion Models to Predict Ground Concentrations During Burning of Deployed Military Waste" (2012). Theses and Dissertations. 1282.