Ullrich Lorenz of the German Environment Agency, who chaired the session, started on the note of the complexity of the nexus between greenhouse gases and climate change. The nexus is an endogenous/exogenous complex model and the complexity needs to be conveyed to policy makers.
Kai Neumann of Considio GmbH, Germany, presented both quantitative, which looked at sectoral, national and global models, and qualitative models which were participatory exploratory models. The qualitative model explained the Lock-In Effect that arises when each system is waiting for the other system’s support and none progresses within the system. The models say that there is enough material for transition though less amount of high grade material is available and overall economic benefit is derived despite rising energy prices in future years. Another interesting phenomenon that was explained by the models was the Rebound Effect that would come into effect when there is a shift to renewables by some countries thus, resulting in a decline in fossil fuel prices which would in turn influence other countries to expend and use the abandoned fossil fuels. He suggests starting implementation of renewables fron now on, working on own countries and supporting other countries later as some of the actionable points. He ended on the note that “Models are something to work with”, that they are not an absolute prediction of the future or that we should be deterred by assumptions we have to work with.
Dr. Stephan Lutter from Vienna University, showcased the Multi-Regional Input-Output Modelling which took into account indirect or virtual flow or footprint. This model, in turn, is an effective way of motivating consumers by educating and making them aware of issues that they are directly or indirectly influencing and progress of resource efficiency. The SCP-HAT model looks at SDG monitoring in that it has helped countries learn of the extent of their footprint contribution as well as helped policy makers of UNDP, indivual countries in various policy framings and analysis. He has mentioned three key factors for the improvement of this model- uncertainty analysis, thematic (water, energy) coverage and increase in sectoral and product coverage within the model.
Elena Rovenskaya, who is Program Director of the International Institute for Applied Systems Analysis, approached modelling through the public policy planning lens. She starts out by saying that ‘models should be agile, reliable and relevant’ to cope within our VUCA (acronym for volatility, uncertainty, complexity and ambiguity) world. The first such model is ‘agent-based modelling of people’s behaviour’ which is people-based and behaviour-determinism centric, showing the feedback mechanism. The ‘stock-flow consistent models of economic incentives’ focusses on policy evaluation and has found that the risks get smoothened in the future anticipating climate sustainability. The ‘risk-adjusted optimisation for robust solutions’ concludes that optimal solutions are input-sensitive.
There is a huge amount of data at the public level but that data is only meaningful when it is accessed and used as per need. The complexity of data must be made meaningful to the layman by presenting smaller understandable pieces of the larger data set incorporated into the model. Also, it is important that the models are used for the purpose it has been set up for. Assumptions have to be made of the larger data set to make them fit with the models as well as the models have to be upgraded with changing times to reflect the variability in the data. Finally, it has been emphasised upon by the speakers that a top-down as well as bottoms-up approach to modelling is required and an exchange of data and modelling systems between the publicly funded and privately funded scientific institutions.
Reported by: Shelly Debbarma, The Energy and Resources Institute, India.