ENBIOS

What problem it solves

Administrations use energy system optimization models (ESOMs) for prospective energy scenario design. ESOMs while very important for informing the energy transition are not designed to provide insights into how sustainable a pathway is in terms of resource use and environmental impact. In SENTINEL, we found that energy-related decision makers lack information on environmental impacts like biodiversity degradation, land transformation or water and mineral depletion with a cumulative perspective. To fill this gap, ENBIOS takes the configuration and activity results provided by ESOMs and calculates a battery of environmental and bioeconomic feasibility performance indicators.

Inputs

• Energy capacities and production by technology, period and region from Calliope optimization in friendly-data nomenclature.
• Energy system hierarchical structuring
• Environmental life cycle inventory (LCI) data (from Ecoinvent and GaBi for example)
• Life cycle impact assessment (LCIA) characterization factors
• Raw material factors (from European Commission)
• Fuel combustion factors (from IPCC)
• Other socio-metabolic data, if required (e.g., employment data)
• General specifications made in online Excel file
• Other input data in CSV, SPOLD and YAML formats (human and computer readable)

Outputs

• Indicators for each time, region and technology defined in the ESOM output, aggregated at each level of hierarchical structure
• Typical indicators include:
• Greenhouse gas emissions
• Water depletion / eutrophication
• Biodiversity loss
• Land transformation and occupation
• Effects over human health
• Material supply risk, circularity factor, local impact factor (from extraction)
• Bioeconomic Pressure
• Net employment
• Output data in CSV (text-only)

Language(s)

ENBIOS is written in Python.

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