Energy return on investment (EROEI) is the ratio of the energy extracted or delivered by a process to the energy used directly and indirectly in that process. The unprecedented expansion of the human population, the global economy, and per capita living standards of the last 200 years was powered by high EROEI, high energy surplus fossil fuels. Standard economic analysis, focused solely on dollars/currencies that change in value due to increases/decreases in the money supply, subsidies, and other distortions, do not accurately account for physical properties and costs of our resource base. A standard framework for establishing commensurate EROEI statistics will be of great importance to policymakers in a world where energy becomes a limiting input to our economies.
The Project: The work aims to establish a tool to evaluate EROEI (energy return on energy investment) and greenhouse gas emissions of all main energy sources and their infrastructure at a physical level based on a cradle-to-grave analysis. The end goal is to create a methodology which allows for generating scenarios of how the EROEI of different energy sources will develop in the future, due to changes in the physical nature at the level of extraction and construction. It will generate for each energy source:
• A map of all energy conversion processes involved in their construction and operation to market delivery and end disposal. For example, the production of solar powered electricity from Solar-PV requires: factories that produce Solar-PV components, an assembly factory, transport, local implementation, maintenance, and end of life disposal.
• The mass and energy data of the processes involved in the cradle-to-grave energy source chain, both at the level of direct energy costs of fuels, electricity and heat, and embedded energy of required mass inputs;
• A dynamic estimation methodology to generate changes in EROEI due to variability in the physical infrastructure. For instance, effects of changes in the depth and shape of fossil fuel deposits, impacts of thermal power plant sizes, and electricity grid complexity.
The project utilizes detailed process level data currently being gathered by IIER for all key energy sources (from fossil to renewable). See our “Online Process Data Warehouse” project for more details.
Difference to past EROEI analyses: Much of the research that takes embodied energy into account uses dollar costs for processing components, and these are converted into energy expended. The basis of making this conversion is calculating energy intensity per dollar unit output from either an individual sector of the economy such as oil and gas refining, or the entire economy. It assumes that the dollar outputs and energy inputs are directly related.
Considering the objective of net energy analysis is to create objective statistics outside of the realm of dollars, this practice has diluted the accuracy/importance of common EROI statistics. The financial approach to energy input estimations introduces large inaccuracies for a number of reasons. The dollar denoted values are based on aggregates and not actual cost of individual components, thus making the estimate fairly rough. Dollar values also add relative market scarcity from demand and supply for a particular time, which is especially relevant for bulk commodities like steel and wood products. In addition, financial system costs such as credit and loan availability distort the picture. Further, many of the conversion factors are not current and date back to studies from the 1980s.. Finally, the available data is primarily from the United States which has an significantly different energy intensity structure than other countries and regions. In applying US energy intensity figures to other countries and regions, by using exchange rate values, the local economic structures and their efficiency is ignored, and further errors are introduced from exchange rate values.
Because of these issues we work with our own physical mass and energy process based EROEI methodology that leaves dollar based values out of the calculation. By using physical dimensions we obtain the most accurate approximation of energy flows in the economy as possible, which is the original intent of making net energy analysis a valid policy tool. Moreover, by introducing dynamic physical rules from engineering disciplines, it becomes possible to create scenarios of how EROI of energy sources change over time under different assumptions of process efficiency and resource extraction difficulty.
Output: We will embed the dynamic estimation methodology into a publicly available web based “EROEI and emissions calculator”. The calculator can be fed with specific information such as fossil fuel deposit geography, location of infrastructure, and technology data, to provide a tailored analysis of the net energy gains of a particular energy source, both at present and as future scenarios.
Current status: We are collaborating with Prof. Adam Brandt and Dr. Charles Barnhart of Stanford University and Assistant Prof. Michael Dale of Clemson University on further development of the methodology for net energy calculations. Under the collaboration a study has been published, why is net energy important?, in Nature Climate Change? Two follow up studies are being conducted on the temporal and stock aspects of net energy, and a meta-analysis of data quality in solar-PV energy metric studies.