Development and Application of GCAM-­Canada Model for Future Energy Scenario Analysis

Stories about this project:

• Assessing energy technologies over lunch

Integrated assessment models (IAM) support sustainable resource development and infrastructure planning, which requires reliable long-term projections of both resource supply and demand variables. Such projections rest in turn on a clear understanding both of the problem and potential trade-offs, as well as the comprehensive, “big picture” effects of alternative solutions. The IAM used here, the “Global Change Assessment Model” (GCAM), represents both the behaviour of and interactions between primary and secondary energy supply and demand, the economy, water supply and demand, agricultural production, land use, and the climate – a system-wide perspective that includes both these intersectoral connections, as well as a consistent representation of international trading and policy linkages and their evolution over 100 years under various scenarios. Canada lacks a comprehensive IAM that integrates our country with global systems, and that can simulate broader effects – on energy systems, the climate, land use and water resources – of policy decisions.

In each simulation run, GCAM takes as input a set of scenario assumptions to produce outputs in terms of prices, energy production and transformations, and commodity and other flows across regions and times. Of particular interest for the Future Energy Systems initiative, GCAM represents sources of primary energy supply, modes of energy transformation, and energy service demands – including transportation, industrial energy use, and residential and commercial energy service demands. Supplies and demands for primary and secondary energy forms are simulated, as well as emissions of greenhouse and other gases, and bioenergy demands connect to agriculture and land systems, as well as to the water system. GCAM is a community model and an important international tool for scientific inquiry; hundreds of academic papers using GCAM have been published in peer-reviewed academic journals over the last 30 years (JGCRI, http://jgcri.github.io/gcam-doc/overview.html).