Emissions - GCAM

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Alert-warning.png Note: The documentation of GCAM is 'in preparation' and is not yet 'published'!

Model Documentation - GCAM

Corresponding documentation
Previous versions
No previous version available
Model information
Model link
Institution Pacific Northwest National Laboratory, Joint Global Change Research Institute (PNNL, JGCRI), USA, http://www.globalchange.umd.edu.
Solution concept General equilibrium (closed economy)GCAM solves all energy, water, and land markets simultaneously
Solution method Recursive dynamic solution method
Anticipation GCAM is a dynamic recursive model, meaning that decision-makers do not know the future when making a decision today. After it solves each period, the model then uses the resulting state of the world, including the consequences of decisions made in that period - such as resource depletion, capital stock retirements and installations, and changes to the landscape - and then moves to the next time step and performs the same exercise. For long-lived investments, decision-makers may account for future profit streams, but those estimates would be based on current prices. For some parts of the model, economic agents use prior experience to form expectations based on multi-period experiences.

GCAM projects emissions of a suite of greenhouse gases (GHGs) and air pollutants:

CO2, CH4, N2O, CF4, C2F6, SF6, HFC23, HFC32, HFC43-10mee, HFC125, HFC134a, HFC143a, HFC152a, HFC227ea, HFC236fa, HFC245fa, HFC365mfc, SO2, BC, OC, CO, VOCs, NOx, NH3

Future emissions are determined by the evolution of drivers (such as energy consumption, land-use, and population) and technology mix. How this is represented in GCAM varies by emission type. More details can be found in the documentation's section on emissions.