Model scope and methods - COFFEE-TEA

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Model Documentation - COFFEE-TEA
Corresponding documentation
Model information
Institution COPPE/UFRJ (Cenergia), Brazil, http://www.cenergialab.coppe.ufrj.br/.
Solution concept General equilibrium (closed economy)
Solution method The COFFEE model is solved through Linear Programming (LP). The TEA model is formulated as a mixed complementary problem (MCP) and is solved through Mathematical Programming System for General Equilibrium -- MPSGE within GAMS using the PATH solver.
Anticipation

COFFEE (COmputable Framework For Energy and the Environment) is a multi-regional and multi-sectorial partium equilibrium (PE) model12. The model includes a rich technological representation of the energy and land-use systems in a completely integrated framework, providing the assessment of potential synergies/trade-offs in energy, environmental and climate policies. COFFEE can assess the evolution of fossil-fuel GHG emissions from combustion, from all sectors of the economy, including industrial processes, waste treatment and land-use related, including fugitive emissions.

The COFFEE model is based on the MESSAGE (Model for Energy Supply Strategy Alternatives and their General Environmental Impacts), an optimization software in linear programming applied for most physical balances (mass, energy, exergy and land)34. MESSAGE suits the development of bottom-up models and partial equilibrium models, with perfect foresight, sovled through Linear Programming (LP).

TEA (Total Economy Assessment) is a multi-regional and multi-sectorial CGE model that tracks the production and distribution of goods in a dynamic recursive setup for the global economy. The model is based on the MIT EPPA model56 and on GTAPinGAMS7.

The model is formulated as mixed complementary problem (MCP) and is solved through Mathematical Programming System for General Equilibrium -- MPSGE8 within GAMS using the PATH solver9. It assumes total market clearance (through commodity price equilibrium), zero profit condition for producers (with constant-returns-to-scale) and perfect competition to reach general equilibrium.

The models have been developed at COPPE/UFRJ, Brazil, for assessing climate, land, energy and environmental policies, providing relevant information to experts and decision-makers about the possible development strategies and repercussions of long term climate scenarios. The model can run scenarios as a stand-alone application or linked through a soft-link process.

References

  1. ^  |  Pedro Rua Rodriguez Rochedo(2016). Development of a global integrated energy model to evaluate the Brazilian role in climate change mitigation scenarios. Retrieved from http://www.ppe.ufrj.br/images/publica%C3%A7%C3%B5es/doutorado/Pedro_Rua_Rodriguez_Rochedo.pdf
  2. ^  |  Ken Oshiro, Keii Gi, Shinichiro Fujimori, Heleen L van Soest, Christoph Bertram, Jacques Despres, Toshihiko Masui, Pedro Rochedo, Mark Roelfsema, Zoi Vrontisi (2019, Jul). Mid-century emission pathways in Japan associated with the global 2 {\textdegree}C goal: national and global models' assessments based on carbon budgets. Climatic Change, ()http://dx.doi.org/10.1007/s10584-019-02490-x
  3. ^  |  International Atomic Energy Agency (2016). Modelling Nuclear Energy Systems with MESSAGE: A User's Guide. IAEA Nuclear Energy Series, STI/PUB/1718 (NG-T-5.2), 1--126.
  4. ^  |  A Gritsevskyi, N Nakicenovi (2000). Modeling uncertainty of induced technological change. Energy policy, 28 (13), 907--921.
  5. ^  |  Z Yang, R S Eckaus, A D Ellerman, H D Jacoby (1996). The MIT Emissions Prediction and Policy Analysis (EPPA) Model. MIT Joint Program on the Science and Policy of Global Change, ().
  6. ^  |  Sergey Paltsev, John M Reilly, Henry D Jacoby, Richard S Eckaus, James R McFarland, Marcus C Sarofim, Malcolm O Asadoorian, Mustafa HM Babiker (2005). The MIT emissions prediction and policy analysis (EPPA) model: version 4. MIT Joint Program on the Science and Policy of Global Change, ().
  7. ^  |  Thomas Rutherford (1997). GTAPinGAMS: The Dataset and Static Model. Global Trade Analysis Project (GTAP), ().
  8. ^  |  Thomas F Rutherford (1999). Applied general equilibrium modeling with MPSGE as a GAMS subsystem: An overview of the modeling framework and syntax. Computational economics, 14 (1-2), 1--46.
  9. ^  |  Michael C. Ferris, Todd S. Munson (2000). Complementarity problems in GAMS and the PATH solver. Journal of Economic Dynamics and Control, 24 (), 165-188. http://dx.doi.org/10.1016/s0165-1889(98)00092-x