Global energy modelling — A biophysical approach (GEMBA) Part 2: Methodology
S. Krumdieck and
Ecological Economics, 2012, vol. 73, issue C, 158-167
Economists, investors and policy makers need to understand the changing climate of energy systems and the potential for investment in both alternative energy supply and demand side efficiency and management technologies. Biophysical economics has contributed to conventional economics by incorporating thermodynamic and ecological principles and emphasising the importance of natural resources to the economic process. This paper is presented in two parts. Part 1 gives a historic review of biophysical economics and discusses some previous models of the energy-economy system built around the principles of biophysical economics. Part 2 presents the GEMBA model — a new modelling methodology in the biophysical economics tradition. The methodology proposes a new and important contribution to the field of biophysical economics; a lifetime evolving function for the dynamics of the energy return on investment (EROI). In the development stage of a new resource, EROI increases due to technological learning, market growth and capital investment. EROI then reaches a peak as diminishing returns are experienced on further technological innovation and capital investment. In the later stage EROI declines over time as the most accessible resources are developed first, resources become depleted, or scarcity develops for materials needed to extract, process or convert the energy for the market. EROI can also diminish over time as environmental restoration or emission reduction becomes required by the society. The dynamic EROI function was incorporated into a global energy model using a biophysical approach (GEMBA) and implemented in VenSim. The GEMBA model is calibrated using historical energy production data, i.e. training to historical data, then running the trained model to 2100 under a series of varying assumptions regarding availability of energy resources and corresponding EROIs. The main finding of the model is that growth of the renewable energy sector may impact investment in other areas of the economy and thereby stymie economic growth.
Keywords: Physical resource modelling; Net energy analysis (NEA); Systems dynamics (SD); Resource quality; Embodied energy (search for similar items in EconPapers)
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