What is the purpose of conducting a "sensitivity analysis" in dispersion modeling?

Conducting a sensitivity analysis in dispersion modeling is primarily aimed at understanding how variations in input parameters affect the output of the model. This process involves systematically changing one or more input variables to observe how these changes influence the model predictions, allowing modelers to identify which parameters have the most significant impact on results.

Through sensitivity analysis, it becomes clear which assumptions are critical to the model's reliability and performance. This can help in fine-tuning the model and ensuring that it accurately reflects the real-world dispersion of substances in the atmosphere. By understanding these relationships, analysts can make informed decisions regarding data collection efforts, model calibration, and the potential need for further study when certain parameters are particularly influential. This is vital when preparing for environmental assessments or regulatory compliance, as it provides insight into where uncertainties may lie and helps in quantifying risk associated with various input scenarios.