Previously named rmnd-lca. rmnd-lca was designed to work with the IAM model REMIND only. As it now evolves towards a more IAM-neutral approach, a change of name was considered.
- CODE-BREAKING CHANGES --> New workflow (please check examples notebook): better suited for creating several scenarios, as the original ecoinvent database and inventories are only loaded once.
update_solar_PV(): adjusts the efficiency of photovoltaic solar panels in ecoinvent according to the year of projection.update_cars(): creates car inventories in line with the year of projection. Also creates new fleet average car transport and links it back to transport-consuming activities.update_trucks(): creates truck inventories in line with the year of projection. Also creates new fleet average truck transport and links it back to transport-consuming activities.update_steel(): creates regional steel markets instead of one "Global" one. For each regional market, the share of primary vs. secondary steel is adjusted/extrapolated based on recent statistics. These regional markets supply steel-consuming activities within their geographical scope, but also supplies the global steel market.
https://premise.readthedocs.io/en/latest/
The objective is to produce life cycle inventories under future energy policies, by modifying the inventory database ecoinvent 3 to reflect projected energy policy trajectories.
- Python 3.9
- License for ecoinvent 3
- Some IAM output files come with the library ("REMIND_xxx.csv" for REMIND, "IMAGE_xxxx.csv" for IMAGE) and are located by default in the subdirectory "/data/iam_output_files". If you wish to use those files, you need to request (by email) an encryption key from the developers. A file path can be specified to fetch IAM output files elsewhere on your computer.
- brightway2 (optional)
Two options:
A development version with the latest advancements (but with the risks of unseen bugs), is available from Anaconda Cloud:
conda install -c romainsacchi premise
For a more stable and proven version, from Pypi:
pip install premise
will install the package and the required dependencies.
premise allows to align the life cycle inventories contained in the ecoinvent 3.5, 3.6 and 3.7 cutoff databases with the output results of Integrated Assessment Models (IAM) REMIND and IMAGE, in order to produce life cycle inventories under future policy scenarios (from business-as-usual to very ambitious climate scenarios) for any year between 2005 and 2100.
Either:
- ecoinvent v.3.5, 3.6, 3.7 or 3.7.1 as a registered brightway2 database
- ecoinvent v.3.5, 3.6, 3.7 or 3.7.1 as ecospold2 files
More specifically, premise will apply a series of transformation functions to ecoinvent.
In the latest version (0.2.0), the following transformation functions are available:
- update_electricity(): alignment of regional electricity production mixes as well as efficiencies for a number of electricity production technologies, including Carbon Capture and Storage technologies.
- update_cars(): new passenger car inventories are created based on carculator, fuel markets that supply passenger cars are adjusted according to the IAM projections, including penetration of bio- and synthetic fuels. Then, given a fleet composition, markets for passenger car transport are created. Finally, these transport markets link back to transport-consuming activities.
- update_trucks(): new truck inventories are created based on carculator_truck, fuel markets that supply trucks are adjusted according to the IAM projections, including penetration of bio- and synthetic fuels. Then, given a fleet composition, markets for truck transport are created. Finally, these transport markets link back to lorry transport-consuming activities.
- update_cement(): adjustment of technologies for cement production (dry, semi-dry, wet, with pre-heater or not), fuel efficiency of kilns, fuel mix of kilns (including biomass and waste fuels) and clinker-to-cement ratio.
- update_steel(): creation of regional low-alloy steel markets and correction/projection of primary vs. secondary steel supply.
- update_solar_PV(): adjustment of solar PV modules efficiency, to reflect current (18-20%) and future (25%) efficiencies.
However, whether or not these transformation functions can be applied will depend on the existence of the necessary variables in the IAM file you use as input.
| Function | Implemented? | Description | REMIND | IMAGE | Other IAM | Comment |
|---|---|---|---|---|---|---|
| update_electricity() | Yes | Aligns electricity markets and power plants efficiencies | Yes | Yes | No | |
| update_cars() | Yes | Creates fleet average passenger cars as projected by the IAM | Yes | Yes | No | Uses default projection if the IAM does not provide a fleet projection. |
| update_trucks() | Yes | Creates fleet average lorries as projected by the IAM | Yes | Yes | No | Uses default projection if the IAM does not provide a fleet projection. |
| update_cement() | Yes | Aligns clinker and cement production and supply | Yes | Yes | Yes | Uses external data sources (WBCSD and IEA) |
| update_steel() | Yes | Aligns primary and secondary steel production and supply | Yes | No | No | Uses external data source (BIR) |
| update_metal_markets() | Not yet | Aligns share of metal extraction vs. recycling and and supply with IAM | No | No | No | |
| update_solar_PV() | Yes | Aligns solar PV modules efficiency | Yes | Yes | Yes | Uses external data source (PSI) |
The following REMIND IAM files come with the library:
- SSP2
- Base: counter-factual scenario with no climate policy implemented
- NPi (National Policies implemented): scenario describes energy, climate and economic projections for the period until 2030, and equivalent efforts thereafter. See CD-LINKS modelling protocol for details.
- NDC: All emission reductions and other mitigation commitments of the NationallyDetermined Contributions under the Paris Agreement are implemented. See CD-LINKS modelling protocol for details.
- PkBudg 1300/1100/900: Climate policies to limit cumulative 2011-2100 CO2 emissions to 1300 / 1100 / 900 over the entire time horizon (“not-to-exceed”). Correspond to 2°, well-below 2° and 1.5° targets. Other greenhouse gases are priced with the CO2e-price using 100year global warming potentials.
The following IMAGE IAM file comes with the library:
- SSP2
- Base counter-factual scenario with no climate policy implemented
- RCP 2.6: limits radiative forcing to 2.6 W/m^2 by 2100
- RCP 1.9: limits radiative forcing to 1.9 W/m^2 by 2100
If you wish to use those scenarios, you need to request (by email) an encryption key from the maintainers. You can however use any other compatible IAM files.
Additionally, a number of inventories for emerging technologies are added upon the creation of a new database.
- electricity production using various fuels (including biomass and biogas) with Carbon Capture and Storage (CCS) Volkart et al. 2013
- hydrogen production from electrolysis from different world regions,
- hydrogen production from steam methane reforming (SMR) and auto-thermal reforming (ATR) of natural gas and biogas, with and without CCS Antonini et al. 2020
- hydrogen production from coal gasification Simons, Bauer. 2011
- hydrogen production from woody biomass gasification, with and without CCS Antonini et al. 2021
- synthetic fuels from Fischer-Tropsh (diesel), Methanol-to-liquid (gasoline) and electrochemical methanation (gas) processes, using direct air capture (DAC) Zhang et al. 2019, van der Giesen et al. 2014, Hank et al. 2019, Grimmer at al. 1988, Terlouw et al.
- current and future passenger car inventories from the library carculator
- current and future medium and heavy duty trucks from the library carculator_truck
- current and future various two-wheelers and collective means of transport (buses, trams, etc.)PSI
Either:
- a database to register in a brightway2 project
- a sparse matrix representation of the database stored in csv files
- a SimaPro CSV file for SimaPro 9.x
The best way is to follow the examples from the Jupyter Notebook.
Do not hesitate to contact the development team at [email protected] or [email protected].
See contributing.
BSD-3-Clause. Copyright 2020 Potsdam Institute for Climate Impact Research, Paul Scherrer Institut.
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