Future Seminar Summaries

111d modeling series: Modeling Pathways to Long-Term GHG Reductions in California


Elaine Hart, Managing Consultant, E3

Jeffery Greenblatt, Staff Scientist, Lawrence Berkeley National Laboratory

Monday, June 1, 2015 | 04:15 PM - 05:15 PM | NVIDIA Auditorium, Jen-Hsun Huang Engineering Center | Free and Open to All

Governor Brown recently issued an executive order calling for a 40% reduction in greenhouse gas (GHG) emissions across the California economy relative to 1990 levels by 2030. E3 and LBNL will present recent modeling work done by each of their organizations analyzing scenarios, policies, and technologies for emission reductions and provide an overview of key findings and implications.

The California Air Resources Board, California Energy Commission, California Public Utilities Commission, and the California Independent System Operator engaged E3 to evaluate the feasibility and cost of a range of potential 2030 targets along the way to the state's goal of reducing GHG emissions to 80% below 1990 levels by 2050. E3 developed scenarios that explore the potential pace at which emission reductions can be achieved as well as the mix of technologies and practices deployed. E3 conducted the analysis using its California PATHWAYS model.  Enhanced specifically for this study, the model encompasses the entire California economy with detailed representations of the buildings, industry, transportation, and electricity sectors.  

LBNL will discuss its separate but related effort, modeling 2020 and 2030 policy and technology scenarios in California. Using CALGAPS, a new, validated model simulating GHG and criteria pollutant emissions in California from 2010 to 2050, four scenarios were developed: Committed Policies (S1), Uncommitted Policies (S2), Potential Policy and Technology Futures (S3), and Counterfactual (S0), which omits all GHG policies. Forty-nine individual policies were represented. Sensitivity analysis provided quantification of individual policy GHG emissions reduction benefits.