Climate & Energy Systems Modeling


The Climate Hub Unit focusing on Climate and Energy Systems modeling will use system dynamics, linear and mixed integer optimization and stochastic modelling techniques to develop decarbonization pathways of the energy system at the national level.

1. Detailed inventories of the:

  • energy supply will be conducted by mapping power generation plants along with their associated fuel, including coal, oil, gas, renewables, bioenergy, nuclear and new zero carbon.
  • energy demand and use of different sectors such as transport, households, buildings and industry will be recorded along with their associated greenhouse gas (GHG) emissions.
  • Various climate solutions, such as carbon pricing will be tested and their effect on GHG emissions and overall temperature will be calculated. Scenario building will include the implementation of different fuels for power generation, electrification schemes for the transport or building sector, along with different energy efficiencies and the result will be a simulation of the scenario providing detailed values for all relevant variables, along with the resulting temperature increase.


Balmorel Energy-System model from collaborating institute DTU.

En-ROADS climate simulation model from collaborating with MIT Climate Interactive.

Data sources:

 include the International Energy Agency (IEA) and IPCC.

2. Develop statistical and machine learning approaches to downscaling global models to national, regional or sectoral level. The methodology will use input from large scale models and create statistical and machine learning models that connect the large-scale results to the required quantities of interest at the local level. By required quantities we mean, either environmental or socioeconomic variables. We also use techniques from model averaging.

Potential models used (indicative list):

BayesPop: for population probabilistic projections

MaGE: key economic indicators projections

CAPRI: Common Agricultural Policy Regional Impact

REMIND: Regional Model of Investment and Development

WITCH Model: Economic planning based on emissions, dependence on exhaustible natural resources, etc.


3. Develop tailor-made models for national and/or regional -scale – focusing on specific needs or characteristics of the region under consideration. The models will focus on spatiotemporal aspects as well as model uncertainty aspects and will use a holistic approach blending techniques from system dynamics with scientific computing, statistical modelling and machine learning tools.

4. The input of natural capital as well as climate effects on it will be an important element of our analysis. We intend to co-evolve the models along with the currently under construction Ecosystems Valuation Database gradually leading to a tool that may connect past studies through elaborate meta-analysis to reliable estimates and predictions for regions under considerations and their dependence on various climate scenarios. The data base will also feed into the tailor-made models into the modules requiring quantification of natural capital.

  • Results will be calibrated and tested against the suite of large Integrated Assessment Models (IAMs) from prestigious institutes around the world, such as IIASA (GAINS,GLOBIOM-G4M) and PNNL (ESM).

5. Different Shared Socioeconomic Pathways (SSPs) will be provided against different RCPs to provide a matrix of options, mapping the different pathways that a nation might follow and evolve considering climate policy scenarios and challenges. The scenarios will not be rigid, but the user will be allowed to increase or decrease specific variables and see the effects across a range of quantities. Analysis will result in specific outcomes, fully quantified and visualized, along with corresponding effects on emissions and temperature increase.


Dogan Keles

Professor, Technical University of Denmark

Phoebe Koundouri

Professor, Athens University of Economics and Business & Technical University of Denmark

Athanasios Yannacopoulos

Professor, Athens University of Economics and Business


Konstantinos Dellis

Dr., Post-Doctoral Researcher, "Athena" Research and Innovation Center

Stathis Devves

Researcher, PhD candidate

Chrysi Laspidou

Professor, University of Thessaly

Conrad Felix Michel Landis

Dr., Senior Researcher, Adjunct Lecturer, Athens University of Economics and Business

Georgios Papayiannis

Lecturer of Computational Mathematics at Hellenic Naval Academy, Department of Naval Sciences, Section of Mathematics

Angelos Plataniotis

Insurance Supervisor, PhD candidate

Supporting Projects


MIT Climate Interactive

Climate Interactive creates and shares tools that drive effective and equitable climate action.

Their work: Critically, the Paris Agreement asks all countries to prepare by 2020 low-emission development strategies that chart out how emissions will fall through to 2050. SDSN has played an instrumental role in developing and popularizing the concept of long-term pathways through the Deep Decarbonization Pathways Project (DDPP).  The Paris Agreement also emphasizes the central role of advances in low-emission technologies and their diffusion. The annual Zero Emissions Solutions Conference (formerly the Low-Emissions Solutions Conference) spearheaded by SDSN, the World Business Council for Sustainable Development (WBCSD) and ICLEI – Local Governments for Sustainability was launched at COP22 in Morocco and aims to advance the pace of development for key technologies. As scientist and engineers have demonstrated, we have the technologies and means to decarbonize our economy, it’s up to nations, businesses, and cities to set on a course today for a carbon neutral tomorrow. Learn more here.