Managing Uncertainties in Modelling Air Pollution (MU-MAP)
PI: Marcel van Oijen (CEH-Edinburgh)
CO-I’s & collaborators: David Cameron, Lindsay Banin and Ron Smith (CEH-Edinburgh), staff at the Scottish Environment Protection Agency (SEPA)
Project Overview: The project develops methodology for assessing uncertainties of small, process-based models that are used to estimate deposition of air pollutants to the landscape. The aim is to include this uncertainty assessment in decision-making processes. Atmospheric deposition affects the health of terrestrial and freshwater ecosystems, and SEPA, a partner in the project, have the statutory responsibility for air pollution regulation; their decisions can depend on the deposition estimated from a process-based model. The project will embed one such model, CBED, in a Bayesian Hierarchical Model and show how this facilitates parameter estimation, discrepancy estimation, and probabilistic risk analysis. Specific project goals are to: (1) quantify parametric and structural uncertainty of CBED, (2) visually communicate this uncertainty to users at SEPA and co-develop new methods for integrating this into decision-making, (3) through dialogue with SEPA, identify other sources of uncertainty in SEPA’s decision making process and develop novel research directions to put uncertainty quantification into practice.