Search by property

This page provides a simple browsing interface for finding entities described by a property and a named value. Other available search interfaces include the page property search, and the ask query builder.

List of results

• DART#Documentation  + (DART documentation is limited and consists of a reference card)
• DART#Objective  + (DART is a global multi-sectoral, multi-reg … DART is a global multi-sectoral, multi-regional recursive-dynamic CGE model. First developed in the 1990s, it has been widely applied to analyze environmental policies, energy policies, biofuel policies, and international climate policies. The version used here is designed to analyze climate and energy policies.ed to analyze climate and energy policies.)
• DNE21+#Documentation  + (DNE21+ documentation consists of a referencecard and [[Model Documentation - DNE21+|detailed model documentation]])
• DNE21+#Name and version  + (DNE21+ x)
• DSK#Documentation  + (DSK documentation is limited and consists of a reference card)
• DSK#Name and version  + (DSK v2 - sfc)
• Euro-Calliope#Objective  + (Default: to minimise the actualised total system cost, including both investment costs and operation costs for a full weather year of operation. Different objective functions are possible.)
• E3ME-FTT#Objective  + (E3ME is a macro-econometric model designed to assess global policy challenges. It is widely used for policy assessment, forecasting and research purposes.)
• E3ME-FTT#Documentation  + (E3ME-FTT documentation consists of a referencecard and [[Model Documentation - E3ME-FTT|detailed model documentation]])
• E3ME-FTT#Name and version  + (E3ME-FTT-GENIE 6.2)
• PRIMES#Institution  + (E3Modelling (E3M), Greece, https://e3modelling.com/.)
• PROMETHEUS#Institution  + (E3Modelling (E3M), Greece, https://e3modelling.com/modelling-tools.)
• ENV-Linkages#Name and version  + (ENV-Linkages 4)
• ENV-Linkages#Documentation  + (ENV-Linkages documentation consists of a referencecard and [[Model Documentation - ENV-Linkages|detailed model documentation]])
• ENVISAGE#Name and version  + (ENVISAGE 1.0)
• ENVISAGE#Documentation  + (ENVISAGE documentation is limited and consists of a reference card)
• EPPA#Name and version  + (EPPA 6)
• EPPA#Documentation  + (EPPA documentation consists of a referencecard and [[Model Documentation - EPPA|detailed model documentation]])
• IMACLIM-India#Objective  + (Economy-wide model)
• TIAM-UCL#Behaviour  + (Elastic demand mode available (includes exogenous elasticity of each energy demand with respect to their own price) Technology and region specific hurdle rates.)
• IPAC-AIM technology#Institution  + (Energy Research Institute (ERI), China, http://en.cctp.org.cn/m5/product/35982.html.)
• IPAC-Global#Institution  + (Energy Research Institute (ERI), China, http://en.cctp.org.cn/m5/product/35982.html.)
• CCEM#Behaviour  + (Energy consumption behaviour includes elasticity, efficiency through progress, planned sobriety and climate-crisis-related sobriety)
• ENV-Linkages#Behaviour  + (Energy demands (projected by using elastic … Energy demands (projected by using elasticities of demands to GDP), for all kind of fuels demands, is controlled by calibration of the Autonomous Energy Efficiency Improvements (AEEIs) in energy use, by sector and type of fuel. </br>Value-added is shown as being composed of a labour input, along with a composite capital-energy bundle. The energy bundle is of particular interest for analysis of climate change issues. Energy is a composite of fossil fuels and electricity. In turn, fossil fuel is a composite of coal and a bundle of the “other fossil fuels”. At the lowest nest, the composite “other fossil fuels” commodity consists of crude oil, refined oil products and natural gas. The value of the substitution elasticities are based on existing literature and calibrated to imply a higher degree of substitution among the other fuels than with electricity and coal. According to the vintage-structure of technologies, the fuel mix in energy production is more flexible when associated with new capital. For old capital vintage production technology the substitution possibilities between fuels are very limited.sibilities between fuels are very limited.)
• PROMETHEUS#Anticipation  + (Energy system simulation.Foresight is included only is some sub-modules (i.e. electricity generation))

• Euro-Calliope#Documentation  + (Euro-Calliope documentation is limited and consists of a reference card)

• ICES#Institution  + (Euro-Mediterranean Center on Climate Change (CMCC), Italy, https://www.cmcc.it/.)
• WITCH#Institution  + (European Institute on Economics and the Environment (RFF-CMCC EIEE), Italy, http://www.eiee.org.)
• FeliX#Name and version  + (FeliX 26)
• FeliX#Documentation  + (FeliX documentation is limited and consists of a reference card)
• RICE50+#Institution  + (Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC), Italy, https://www.cmcc.it/.)
• E3ME-FTT#Behaviour  + (For specific sectors, FTT is used to estimate investor decision making regarding technology choices.)
• IPETS#Anticipation  + (Forward looking)
• REMod#Institution  + (Fraunhofer Institute for Solar Energy Systems ISE (Fraunhofer Institute for Solar Energy Systems ISE), Germany, https://www.ise.fraunhofer.de/en.html.)
• IFs#Institution  + (Frederick S. Pardee Center for International Futures, University of Denver (Pardee Center), Colorado, USA, https://pardee.du.edu/.)
• GCAM#Name and version  + (GCAM 7.0)
• GCAM#Documentation  + (GCAM documentation consists of a referencecard and [[Model Documentation - GCAM|detailed model documentation]])
• GCAM#Anticipation  + (GCAM is a dynamic recursive model, meaning … 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.tations based on multi-period experiences.)
• GCAM-India#Anticipation  + (GCAM is a dynamic recursive model, meaning … 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.tations based on multi-period experiences.)
• GCAM#Objective  + (GCAM is an integrated, multi-sector model … GCAM is an integrated, multi-sector model that explores both human and Earth system dynamics. The role of models like GCAM is to bring multiple human and physical Earth systems together in one place to shed light on system interactions and provide scientific insights that would not otherwise be available from the pursuit of traditional disciplinary scientific research alone. GCAM is constructed to explore these interactions in a single computational platform with a sufficiently low computational requirement to allow for broad explorations of scenarios and uncertainties. Components of GCAM are designed to capture the behavior of human and physical systems, but they do not necessarily include the most detailed process-scale representations of its constituent components. On the other hand, model components in principle provide a faithful representation of the best current scientific understanding of underlying behavior.ific understanding of underlying behavior.)
• GCAM-India#Objective  + (GCAM-CEEW is a global integrated assessmen … GCAM-CEEW is a global integrated assessment model that explores the interactions among economy, energy, water, land, and climate systems in a single computational platform. It is a modified version of GCAM v5.2.The GCAM CEEW version disaggregates the residential sector into rural and urban to better represent the Indian scenario. It further separates electricity for commercial and residential use.</br></br>Data on costs of technologies, fuel prices, and energy data have been taken from Indian government databases as well as India-specific relevant surveys done by various organisations. Energy-related data is taken from IEA as well as India-specific sources.rom IEA as well as India-specific sources.)
• GCAM-India#Name and version  + (GCAM-CEEW v5.2)
• GCAM-India#Documentation  + (GCAM-India documentation is limited and consists of a reference card)
• GCAM-KAIST#Name and version  + (GCAM-KAIST 1.0)
• GCAM-KAIST#Documentation  + (GCAM-KAIST documentation is limited and consists of a reference card)
• GCAM-KSA#Name and version  + (GCAM-KSA 1.0)
• GCAM-KSA#Documentation  + (GCAM-KSA documentation is limited and consists of a reference card)
• GCAM-KSA#Anticipation  + (GCAM-KSA is a dynamic recursive model, mea … GCAM-KSA 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.tations based on multi-period experiences.)
• GCAM-KSA#Objective  + (GCAM-KSA is a global integrated assessment … GCAM-KSA is a global integrated assessment model that explores the interactions among economy, energy, water, land, and climate systems in a single computational platform. It is a modified version of GCAM v6.0. We have separated the Kingdom of Saudi Arabia (KSA) as a separate energy-economy region, i.e., GCAM–KSA includes 33 energy-economy regions (32 original regions plus KSA).my regions (32 original regions plus KSA).)
• GEM-E3#Name and version  + (GEM-E3 _092019)
• GEM-E3#Documentation  + (GEM-E3 documentation consists of a referencecard and [[Model Documentation - GEM-E3|detailed model documentation]])