Which atmospheric dispersion model's performance is less reliable with low wind speeds?

The Britter-McQuaid Model is less reliable with low wind speeds primarily due to its reliance on specific meteorological conditions and assumptions about atmospheric stability. This model is designed to account for various atmospheric conditions, but it is particularly sensitive to the effects of wind. When wind speeds are low, the dispersion of pollutants becomes highly influenced by turbulence and local factors such as terrain and buildings, which can introduce significant variability and uncertainty.

In contrast, other models, like the Gaussian Plume Model, are better suited for low wind conditions because they provide a simplified approach to understanding dispersion based on concentration and distance from the source without as many dependencies on specific atmospheric dynamics. The Pasquill-Gifford Model also has established categories for stability that can somewhat mitigate the effects of low wind situations through predefined dispersion coefficients. Meanwhile, the Computational Fluid Dynamics Model is capable of simulating various flow scenarios, including low wind speeds with high levels of detail, making it more versatile under different atmospheric conditions.

Given these aspects, the Britter-McQuaid Model is less reliable in conditions of low wind speed due to its specific limitations in modeling dispersion under those circumstances.