Plume Modeling Toolkit

Atmospheric dispersion (Plume) modeling is the mathematical simulation of how air pollutants disperse in the ambient atmosphere. It is performed with computer programs that solve the mathematical equations and algorithms which simulate the pollutant dispersion. These are used to estimate the downwind concentration of air pollutants or toxic agents emitted from sources such as industrial plants, vehicular traffic, or even terrorist attacks. In the wake of an airborne pollutant or toxic agent release, the ADSS SensorPod™ Network provides the most accurate atmospheric data, while the Plume Modeling Toolkit accurately predicts the speed, direction and dispersion of air pollutants or toxic agents to ensure proper consequence management.

Advanced Distributed Sensor Systems has created an extremely accurate atmospheric dispersion modeling technique using its Plume Modeling Toolkit and SensorPod deployment methodology. Many factors, including wind speed and direction, temperature, and precipitation affect the travel and dispersion of air pollutants or toxic agents released in the atmosphere. For this reason, the ADSS deployment methodology locates SensorPods in precise locations where they can gather the most relevant local atmospheric data. Using this data, the ADSS Plume Modeling Toolkit can accurately predict the direction, speed, and dispersion of air pollutants or toxic agents. Accurate plume modeling in a crisis situation can save countless lives, as decision makers use these models to determine which areas to evacuate.

As shown by the diagram to the right, the effect of placing adequate numbers of SensorPod nodes in the appropriate locations is critical. Using the SensorPod placement methodology and Plume Modeling Toolkit, the atmospheric dispersion model was over 97% accurate in predicting the direction of travel of air pollutants or toxic agents. Because accurate plume prediction can be a matter of life and death, ADSS performs a sensitivity analysis of the plume model to the data sources supplied to ensure that plume modeling results will be consistent and not vary based on the data source. This process verifies that: