Dynamic Evaluation of Atmospheric Response to Emission Trends

Scientific investigations and environmental decision-making rely on environmental models to accurately simulate not only pollutant concentrations but also their sensitivities to emissions. Simulating sensitivities is especially challenging for air pollutants such as ozone and particulate matter that exhibit nonlinear and highly variable responses to multiple precursor emissions. Whereas models are routinely evaluated against observations for pollutant concentrations, much less is known about the accuracy of pollutant sensitivities that cannot be directly observed. This research is considering recent abatement efforts in the United States as a real-world experiment in emissions perturbations and developing innovative techniques to ground-truth pollutant sensitivities to emissions trends. Modeling is being applied to evaluate ozone and PM responsiveness to emission trends and exploring the leading contributors to uncertainty in responsiveness estimates.

Funding: National Science Foundation CAREER Award
Student: Wei Zhou