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Enbios 2

Project description

Enbios 2

This a ground up new implementation of enbios.

Compared to the original version of enbios, this version is more flexible does not make it's own LCA calculations, but uses brightway2 for that.

The main functionality of enbios2 is currently to run experiments, which are described a set of (brightway) activities a set of methods and a set of scenarios, which contain demand for the given activities.

In addition to get the results of the scenarios in the dendrogram (....) the user can also define a hierarchy, which contains the activities at the bottom.

Enbios 2 is a python package (https://pypi.org/project/enbios/), which can be installed with pip.

Installation

(windows) python -m venv venv

(linux) python3.9 -m venv venv

Activate the environment with

(windows) venv\Scripts\activate

(linux) source venv/bin/activate

Install enbios2 with

(windows) python -m pip install enbios

(linux) python3 -m pip install enbios

Demos

The repository contains a few notebooks (require jupyter notebook) in the demos folder.

Getting started

Plotting results

Sorting the results in alternative hierarchies

Splitting the configuration

Working with trees

Experiment configuration json schema

The json schema for the experiment configuration can be found here:

https://github.com/LIVENlab/enbios/blob/main/data/schema/experiment.schema.gen.json

This schema, provides the structure of the experiment configuration, which is used to run the experiments. Note, that there will be additional validations when the experiment is constructed (e.g. existence of brightway project, databases, activities).

Environment variables

2 environmental variables are used by enbios2:

  • CONFIG_FILE: This variable can be used to specify the location of the configuration file (json). If experiment is initialized without any parameter (configuration data or file location), the configuration is read from this path.
  • RUN_SCENARIOS: This variable can be used to specify the scenarios to run when experiment_object.run() is called. Setting the environmental variable overwrites the value set in the configuration file (config.run_scenarios). This variable should be formatted as a json array, with the aliases of the scenarios that should run. e.g. '["Scenario 0"]' (indexed default aliases, when no aliases are specified in the configuration file for the scenarios).

What is ENBIOS

ENBIOS (Environmental and Bioeconomic System Analysis) is an assessment framework designed for the assessment of the * *environmental impacts and resource use of energy pathways resulting from energy system optimization models (ESOMs)**.

It integrates Life Cycle Assessment (LCA) and Social Metabolism Assessment using the Multi-Scale Integrated Assessment of Socio-Ecosystem Metabolism (MuSIASEM). It has been been co-designed with decision makers and energy modellers.

The related python package enbios takes data on energy system design and impact assessment methods to return a characterization matrix filled with bioeconomic and environmental indicators.

More information on the roots of the framework and version 1 of the software can be found in Deliverable 2.2 of the SENTINEL project. Curently, we have upgraded to version 2 of the software using Brightway2 for LCA analysis and inventory. Samples can be consulted in deliverable 2.2 of the SEEDS project

Data inputs

  • Data on electricity production and power capacity from an energy model -Inputs from EuroCalliope model are accepted as is.
    • We are currently working in the integration with the TIMES model for the project LIVEN.
  • LCA inventories in .spold format
  • Methods of analysis

Outputs

For each energy function and technology:

  • Environmental impact indicators from the most used LCIA methods (Recipe2016, CML, AWARE, etc.)
  • Environmental externalization rates
  • Raw Material Recycling rates and Supply risk

Features

  • Integration of LCA and MuSIASEM evaluation methods
  • Import of .spold LCA inventory data to a multi-level tree-like setting
  • Library of impact assessment methods based on LCIA
  • New impact assessment methods developed for raw materials and circularity
  • Consideration of externalized environmental impacts
  • Takes data from the friendly-data package (other formats under development)
  • High level methods to quickly obtain/refresh analyses

People

Contact

Acknowledgements

ENBIOS is developed by the LIVENlab, a research lab of the the SosteniPra Research group, at ICTA-UAB.

The first verion was built in collaboration with the Technical Institute of the Canary Islands (ITC) and based on the Nexus Information System developed within the Horizon 2020 project MAGIC-nexus and the LCA-MuSIASEM integration protocol developed in the Marie Curie project IANEX. This early development was funded by wthe Horizon 2020 project Sustainable Energy Transitions Laboratory (SENTINEL, GA 837089).

The second version of enbios is in development with funds from the Spanish Research Agency (AEI) and the European Comission (CINEA):

  • SEEDS project with AEI grant PCI2020-120710-2 funds the ENBIOS 2 build based on Brightway framework, adding inventory manipulation to match the mixes of the energy scenarios
  • LIVEN project with AEI grant PID2020-119565RJ-I00 funds the regionalization and conection with the TIMES energy model
  • JUSTWIND4ALL project with Horizon Europe grant 101083936 funds the development of a higher resolution module for wind energy assessment, including new wind-specific holistic assessment methods.

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