1. Introduction REU is the abbreviation for Research Experience for Undergraduates. The project on Hazard Mitigation is funded by the National Science Foundation. Our research was conducted at the University of Texas-Arlington with the help of professors and graduate students. Background Information Wind -Affects plume rise, the concentration, and the travel time of the pollutant. -Wind is inversely proportional to concentration. Air Stability -Tells us the amount of vertical motion in the air. -Two categories: Stable and Unstable Atmosphere. Gaussian Dispersion Equation -Used to calculate concentration. -Basis for air dispersion programs. -Uses a three dimensional axis system. HotSpot -Program provides approximation of the radiation effects. -Models short term accidents. -Evaluates and models how a pollutant disperses into the atmosphere. Abstract Since 9/11, the government of the United States has been concerned about another terrorist attack and radiological threats. In this study, potential scenarios were examined using HotSpot. We created a worse case scenario of an airborne terrorist attack outside the 2012 Super Bowl using Plutonium-238. The scenario was created based on wind speed, air stability, and the amount of explosives. Methods With our scenario, we input information into HotSpot. We ran several tests with different variables to obtain our results. Steps for our Methods: 1. We chose the type of model we needed. 2. We selected type of explosive, amount of explosive, and the MAR (Material at Risk). 3. We then input the different meteorological affects. 4. We saved the TEDE Contour File and viewed the Contour plot on Google Earth. After running the tests, we were able to determine the worse case scenario. Conclusions By examining the variables, we were able to model the most devastating scenario. The variables that caused the most destruction were wind speed at 2 m/s in a stable environment and a lower amount of explosives. This evidence agrees with all of the background information we learned about air dispersion before we modeled our scenarios. National Science Foundation, The University of Texas at Arlington Works Cited Cooper, C. David., and F. C. Alley. "Chapter 20 Atmospheric Dispersion Modeling." Air Pollution Control: aADesign Approach. Third ed. Prospect Heights, IL: Waveland, 2002. 607-48. Print. Homann, Steven G. HotSpot. Computer software. National Atmospheric Release Advisory Center (NARAC). Vers. 2.07.1. 2 Mar. 2010. Web.. Air Dispersion Modeling: Planning for Airborne Terrorism Release Objective The objective of this project was to investigate a scenario portraying a nuclear terrorist attack using the software HotSpot. Worst Case Scenario: Backpack Stability Class F with a wind speed of 2 m/s Tiffany LeBlanc Baton Rouge Community College Environmental Engineering Gerald Gruber St. Mary’s University Engineering Science Dr. Melanie Sattler University of Texas Arlington Faculty, Civil Engineering Dr. Yvette Weatherton University of Texas Arlington Faculty, Civil Engineering Results Best Case Scenario: Car Stability Class F with a wind speed of 12 m/s Ketwalee Kositkanawuth University of Texas Arlington Graduate Student Joel Hernandez Crosswinds High School Teacher Assistant Outcomes and Impact Best Case Scenario: Figure 5: The area of the plume is significantly smaller due to: High amount of explosive High wind speed Figure 6: Though the stability class is F, moderately stable, the area of impact that is fatal is significantly smaller. The wind speed is higher and the amount of explosive is significantly larger Worst Case Scenario: Figure 7: Graph of plume and measurements Models how Inner Contour line affects the population due to high concentration of radiation Figure 8: Concentration was high over a large amount of area due to: Slow wind speed Stability Class: F (moderately stable) Low amount of explosive Figure 9: The plume travelled far due to the wind speed The pollutant was slowly dispersed into the atmosphere because the air was moderately stable. Figure 1: Air Stability Chart Figure 2: Gaussian Dispersion Equation Figure 3: Gaussian Model Figure 4: Modeling Results Figure 6: TEDE Contour Plot Figure 9: TEDE Contour Plot Figure 5: Table Output Figure 8: TEDE Contour Plot Figure 7: Table Output -This is a table comparing all of our results with the variables of each test run. It has the area of the isopleths with 1000 rem. This is the area of the plume concentration that is fatal. (Figure 4) 1,000 rem 200 rem 50 rem 1,000 rem 200 rem 50 rem > 1.0E+03Fatal 200 to 1,000Causes serious illness and could be fatal 50 to 200Can cause illness < 50Rarely causes illness or harmful to the human tissue * Rem is a measurement of radiation exposure