This is a repository containing a data package that implements the projections of the TIMES model for Switzerland (STEM) within the life-cycle assessment (LCA) database ecoinvent. Projections are implemented for the scenarios SPS1 and SPS4, developed within SFOE's SWEET-SURE program.
This data package is meant to be used in premise in addition to a global IAM scenario, to provide
refined projections at the country level. premise can export the result as a data package for pathways,
which is then be used to compute the system-wide impacts of the energy scenario produced by STEM.
This data package contains all the files necessary for premise to implement
this scenario and create market-specific composition for electricity (including imports from
neighboring countries), liquid and gaseous fuels (including hydrogen) and models their supply and use.
This data package is used to produce results for the following publication:
Switzerland's net zero objective: quantifying impacts beyond borders.
Alvaro Jose Hahn Menacho, Romain Sacchi, Christian Bauer, Evangelos Panos and Peter Burgherr.
In review.
ecoinvent 3.10 cut-off
This scenario is licensed under the Creative Commons Attribution 4.0 International Public License (CC BY 4.0). See the LICENSE file for more details.
This external scenario creates markets for Switzerland listed below, according to the scenarios SPS1 and SPS4 generated by the Swiss TIMES energy model STEM (yellow boundaries in map above).
Markets
- market for biogas, domestic (SPS)
- market for biomass, for power generation (SPS)
- market for diesel (SPS)
- market for district heating (SPS)
- market for electricity, high voltage (SPS)
- market for electricity, low voltage (SPS)
- market for electricity, medium voltage (SPS)
- market for energy carriers for buses (SPS)
- market for energy carriers for cars (SPS)
- market for energy carriers for coaches (SPS)
- market for energy carriers for heavy duty trucks (SPS)
- market for energy carriers for light duty trucks (SPS)
- market for energy carriers for motorcycles (SPS)
- market for energy carriers for other transport (SPS)
- market for hydrogen (SPS)
- market for methane (SPS)
- market for petrol (SPS)
- market for process heat and space heating in industry (SPS)
- market for process heat in industry (SPS)
- market for space and water heating in residential (SPS)
- market for space heating in industry (SPS)
- market for space heating in residential (SPS)
- market for space heating in services (SPS)
- market for water heating in residential (SPS)
These markets are relinked to activities that consume final energy in Switzerland.
Additionally, the Swiss markets rely to a varying extent on imports from neighboring countries, which is provided by the regional IAM market.
See the mapping file: configuration_file/config.yaml.
The following script generates four LCA databases for the years 2020, 2030, 2040 and 2050, with STEM's SPS1 scenario combined with REMIND's SSP2-NPi scenario.
Other scenarios can be implemented by changing the scenarios list.
List of available scenarios can be found in the datapackage.json file.
from premise import *
import bw2data
from datapackage import Package
bw2data.projects.set_current("some brightway project")
sps = Package("../datapackage.json")
scenarios = [
{"model": "remind", "pathway": "SSP2-NPi", "year": 2020, "external scenarios": [{"scenario": "SPS1", "data": sps}]},
{"model": "remind", "pathway": "SSP2-NPi", "year": 2030, "external scenarios": [{"scenario": "SPS1", "data": sps}]},
{"model": "remind", "pathway": "SSP2-NPi", "year": 2040, "external scenarios": [{"scenario": "SPS1", "data": sps}]},
{"model": "remind", "pathway": "SSP2-NPi", "year": 2050, "external scenarios": [{"scenario": "SPS1", "data": sps}]},
]
ndb = NewDatabase(
scenarios=scenarios,
source_db="ecoinvent-3.10-cutoff", # <-- name of the database in the BW2 project. Must be a string.
source_version="3.10", # <-- version of ecoinvent. Must be a string.
key="xxxx", # <-- ask the key to run premise from the developers
use_absolute_efficiency=True,
biosphere_name="ecoinvent-3.10-biosphere"
)
ndb.update()
ndb.write_db_to_brightway()
To produce a data package for pathways, use the following script instead:
from premise import *
import bw2data
from datapackage import Package
bw2data.projects.set_current("some brightway project")
sps = Package("../datapackage.json")
scenarios=[
{"model": "remind", "pathway": "SSP2-NPi", "external scenarios": [{"scenario": "SPS4", "data": sps}]},
{"model": "remind", "pathway": "SSP2-PkBudg1150", "external scenarios": [{"scenario": "SPS4", "data": sps}]},
{"model": "remind", "pathway": "SSP2-PkBudg500", "external scenarios": [{"scenario": "SPS4", "data": sps}]},
{"model": "remind", "pathway": "SSP2-NPi", "external scenarios": [{"scenario": "SPS1", "data": sps}]},
{"model": "remind", "pathway": "SSP2-PkBudg1150", "external scenarios": [{"scenario": "SPS1", "data": sps}]},
{"model": "remind", "pathway": "SSP2-PkBudg500", "external scenarios": [{"scenario": "SPS1", "data": sps}]},
]
for scenario in scenarios:
name=f"{scenario['model']}-{scenario['pathway']}-stem-{scenario['external scenarios'][0]['scenario']}"
print(name)
ndb = PathwaysDataPackage(
scenarios=[scenario,],
years=[2020, 2025, 2030, 2035, 2040, 2045, 2050],
source_db="ecoinvent-3.10-cutoff",
source_version="3.10",
key="xxxx",
use_absolute_efficiency=True,
biosphere_name="ecoinvent-3.10-biosphere"
)
ndb.create_datapackage(
name=name,
contributors=[
{"name": "some name",
"email": "some email adress",}
],
)
This will produce six different data packages, one for each combination of REMIND's SSP2-NPi and SSP2-PkBudg1150
and SPS1 and SPS4 scenarios. These data packages can then be read by pathways to compute the system-wide impacts of
the energy scenario produced by STEM.