Abstract: Human-Earth system models emerged nearly 40 years ago with a very focused goal: predicting how society’s demands for energy would affect global carbon dioxide emissions over the coming decades. However, these models evolved as the questions being asked by policy makers evolved. Developments included the inclusion of short-lived climate pollutants; adoption of more detailed technology representations; expansion to include agriculture, land use, water, and climate systems; spatial disaggregation to represent individual regions, then countries, then sub-national detail; temporal disaggregation, which is now able to simulate annual, seasonal, and finer detail; and support for a wide range of policy measures, including pollutant taxes and caps, and technology and fuel subsidies. Developments on the horizon include simulation of economic and climate feedbacks, disaggregation of households by income level, and a much-improved representation of the sources of industrial emissions.

With these improvements, which have largely been implemented to support the climate mitigation community, human-Earth systems models are now well positioned to support a very different purpose – air quality management. Potential applications include: estimating current and future air pollutant emissions; evaluating how emission projections change for alternative scenarios; identifying cost-effective strategies for achieving emission reduction goals; anticipating the impacts of new and emerging technologies; assessing the potential impacts of proposed policies and regulations; and, exploring new endpoints such as the environmental and energy justice implications.

In this talk, Dr. Loughlin will present the Global Change Assessment Model (GCAM) (https://github.com/JGCRI/gcam-core), an open source and publicly available human-Earth systems model. Topics that will be covered include the integration of GCAM into a decision support system (http://epa.gov/glimpse) and its linkage to a chemical transport model to explore the air quality co-benefits of a decarbonization scenario.