Volume 21: Sustainable Energy Solutions for a Post-COVID Recovery towards a Better Future: Part IV

Towards the Integration of Environmental and Bio-Economic Indicators in Energy Systems Modelling Nick Martin, Laura Talens-Peiró, Gara Villalba-Méndez, Cristina Madrid-López

https://doi.org/10.46855/energy-proceedings-9354

Abstract

Current energy systems models do not generally provide a detailed analysis of environmental impacts. Even integrated assessment models (IAMs) that attempt to replicate the complex interactions between the economy, technosphere and biosphere at the global scale fail to consider impacts beyond the use of simplified relationships between parameters. This is troubling as energy technologies produce a range of environmental impacts within their life cycle beyond the carbon emissions that occur during the eventual energy production phase. Ignoring the nexus between energy systems, resource use and environmental impacts can also result in misleading information and misguided policy making. Life cycle assessment (LCA) methods provide far more detailed evaluations of processes within energy systems. Furthermore, combining LCA data with bio-economic metabolism approaches could enable the complex relationships between environmental impacts, material constraints and bio-economic functions to be assessed. Knowing that LCA outputs have previously been coupled with the well-established MuSIASEM approach to social metabolism, here we propose applying this synergy to the field of energy systems modelling. We introduce the ENBIOS module, a versatile methodology developed within the SENTINEL project that combines the bottom up, high resolution capabilities of LCA with the hierarchical multi-scale upscaling abilities of MuSIASEM for the analysis of energy systems at all scales. The module brings a more systemic methodology to the assessment of environmental impacts than previous approaches while offering a first attempt at quantifying the raw materials and circularity aspects that apply to energy systems. Recommended data inputs and possible indicators are also provided.

Keywords renewable energy, energy transition, decarbonization, energy modeling, carbon emissions, critical raw materials

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