Validation study of WindTrax reverse dispersion model coupled with a sensitivity analysis of model-specific settings

Area of Science:

• Environmental Science
• Atmospheric Chemistry
• Air Quality Modeling

Background:

• Atmospheric dispersion models are crucial for environmental research.
• Estimating emission rates is challenging but vital for model reliability.
• Backward dispersion models offer a promising approach to determine emission rates from measured concentrations.

Purpose of the Study:

• To critically validate the WindTrax Backward model.
• To assess the model's accuracy under various conditions (stability class, sensor number/location).
• To investigate the sensitivity of model outputs to specific parameter settings.

Main Methods:

• Comparison of WindTrax model predictions with experimental dataset observations.
• Sensitivity analysis of model-specific parameters influencing dispersion simulation.
• Evaluation of model performance using reduced sensor configurations and varying sensor placements.

Main Results:

• Model-specific parameter settings showed minimal impact on output variations.
• WindTrax generally predicted observed values with good accuracy, particularly under neutral atmospheric stability.
• The model tended to underestimate emission rates during unstable stratification and overestimate during stable conditions.

Conclusions:

• WindTrax demonstrates good reliability for emission rate estimation.
• Optimal accuracy is achieved under neutral atmospheric conditions.
• The model performs acceptably even with a limited number of strategically placed sensors (mid-plume).