Which model is specifically used for passive Concentration Over Time Area (COTA) predictions?

The Pasquill-Gifford model is specifically utilized for predictions related to the Concentration Over Time Area (COTA) in passive dispersion scenarios. This model categorizes atmospheric stability conditions and incorporates these variations into its calculations, enabling a comprehensive understanding of how a substance disperses over time. It is pivotal for predicting pollutant concentrations across varying atmospheric conditions, specifically aimed at passive substances that do not have a significant buoyancy effect.

This model's methodology allows for an assessment of how long a concentration of an airborne pollutant remains within a specific area over time, which is particularly useful in assessing the impact of emissions on air quality. By evaluating factors such as wind speed, atmospheric stability, and the release height of the pollutants, the Pasquill-Gifford model provides a structured and scientifically grounded approach to predict how a chemical plume will behave in the atmosphere, making it highly relevant for COTA predictions.

While other models, like the Briggs model and the Gaussian dispersion model, are also valuable for predicting dispersion, they do not specifically serve the function of COTA predictions in the same way that the Pasquill-Gifford model does. Therefore, this model is particularly recognized for its application in this specific domain of atmospheric dispersion analysis.