What condition makes the Britter-McQuaid model's predictions less accurate?

The Britter-McQuaid model, which is used for predicting air pollution dispersion, tends to be less accurate under conditions of very low wind speeds. This is primarily because, at low wind speeds, the dispersion of pollutants can be highly variable and influenced significantly by local terrain, atmospheric stability, and turbulence.

In stagnant air conditions, pollutants can accumulate in a localized area rather than dispersing efficiently, leading to predictions that do not align well with actual dispersion patterns. The model relies on certain assumptions regarding turbulence and atmospheric mixing that are not satisfied in low wind conditions, which can result in significant discrepancies between predicted concentrations and real-world observations.

In contrast, high atmospheric pressure and high wind speeds typically provide more stable conditions for the model, allowing it to generate more reliable predictions. Variable wind speeds can introduce complexity into modeling scenarios but do not inherently undermine the model’s applicability as much as very low wind speeds do.