Global Change Analysis Model (GCAM)
Abstract:
GCAM is a long-term, integrated human and earth systems model that links a global energy-economy-agriculture-land-use model with a simple climate model. GCAM (version 5.3) models global energy with a spatial resolution of 32 economic regions and global agriculture and land use in over 380 water basins. In terms of bioenergy, GCAM provides quantitative analyses of the potential role, impacts, and sustainability of bioenergy production and use that considers economic interactions across all domestic and global energy and agriculture sectors. Bioenergy production is modeled from a number of feedstocks including dedicated bioenergy crops, residues from agriculture and forestry, and waste streams.
On the demand side, bioenergy can be transformed into several types of energy carriers including liquid fuels, gas, electric power, and hydrogen, and it can be burned directly in energy end uses for heat and steam. In GCAM analysis, bioenergy competes economically in the energy system with fossil energy, nuclear energy, and other renewable resources. GCAM is typically run in 5-year time steps to the year 2100, though other intervals are possible. GCAM is a community model with a worldwide user base, can be run on desktop and laptop computers in under an hour, and is available for download.
Model/Tool Platform:
C++
General Modeling Type:
Hybrid / other: Long-term Economic Equilibrium of Agriculture, Energy, and Related Markets
Primary analytical purpose:
Cross-sector analysis:
Integrative scenario assessment of the interactions across parts of the supply chain or multiple market sectors.
Secondary analytical purpose:
Feedstock market assessment:
Assessment of potential feedstock resources using an approach that evaluates the market sector producing the feedstock (e.g., agriculture or forestry).
Metric categories:
- Environmental:
- Air Quality (non-GHG emissions)
- Environmental Productivity (feedstock-related, e.g., NPP or yield)
- GHG Emissions
- Water Impacts (quality and/or quantity)
- Socio-economic:
- Employment
- Energy Security
- Process Productivity (conversion-related, e.g., yield)
- Techno-economic Impact
- Trade
Geospatial resolution:
Regional/Watershed
Temporal resolution:
Years
Laboratory:
PNNL - Pacific Northwest National Laboratory
Principal investigator:
Marshall Wise
Model start year:
1994
Model last updated:
2021
Development status:
Fully Developed with periodic updates
Level of validation/review:
External Peer Review / Publicly Released
Links:
Model scope:
Biomass Supply
Feedstock Logistics
Conversion
Distribution
End Use
- Feedstock Types
- Starch
- Sugar Crops
- Oil Crops
- Fiber Crops
- Cover Crops and Hay
- Agricultural Residues
- Herbaceous Energy Crops
- Forest Residues
- Forest Resources
- Woody Energy Crops
- Solid Wastes (e.g., MSW, C&D, yard trimmings)
- Landfill Gas
- Conversion Technology
- Starch to Sugars
- Lignocellulosic Biomass to Sugars
- Lignocellulosic Biomass to Gaseous Intermediate
- Lignocellulosic Biomass to Biocrude Intermediate (TC)
- Biomass-Based Oil Extraction
- Syngas Catalytic Upgrading
- Sugar Catalytic Upgrading
- Oil Catalytic Upgrading
- Sugar Biological Upgrading
- Syngas Biological Upgrading
- Alcohol Catalytic (e.g., ethanol or isobutanol to jet)
- Products/Process Outputs
- Transportation Fuels - Biodiesel
- Transportation Fuels - Ethanol
- Transportation Fuels - Renewable Diesel
- Transportation Fuels - Renewable Gasoline
- Transportation Fuels - Renewable Jet
- Renewable Natural Gas
- Biopower
- Biohydrogen
- Bioproducts
- Other Process Output
- Transportation Market Segment
- Light Duty Vehicles
- Heavy Duty Vehicles
- Trains
- Aviation
- Marine
Information last updated: Sep. 17, 2019 13:45:46 EDT