Non-climate sustainability dimension - GCAM: Difference between revisions
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|DocumentationCategory=Non-climate sustainability dimension | |DocumentationCategory=Non-climate sustainability dimension | ||
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GCAM produces a range of output variables that can be used to inform non-climate sustainability. These include indicators such as the price of agricultural commodities, production of local air pollutants, ocean pH, and energy access. See | GCAM produces a range of output variables that can be used to inform non-climate sustainability. These include indicators such as the price of agricultural commodities, production of local air pollutants, ocean pH, land use and land cover, and energy access. See [https://www.nature.com/articles/s41558-017-0039-z Iyer, et al. (2018)] for a discussion of this topic. |
Latest revision as of 18:32, 17 June 2022
Corresponding documentation | |
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Model information | |
Model link | |
Institution | Pacific Northwest National Laboratory, Joint Global Change Research Institute (PNNL, JGCRI), USA, https://www.pnnl.gov/projects/jgcri. |
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 produces a range of output variables that can be used to inform non-climate sustainability. These include indicators such as the price of agricultural commodities, production of local air pollutants, ocean pH, land use and land cover, and energy access. See Iyer, et al. (2018) for a discussion of this topic.