EXTRACT

The EXTRACT phase consists of the following steps:

• Extraction and cleaning of the ecoinvent database

• Import and cleaning of additional inventories

• Import and cleaning of user-provided inventories (optional)

• Caching, if these database and inventories are imported for the first time

• Loading of IAM data

Current IAM scenarios

premise includes several Integrated Assessment Model (IAM) scenarios, but you can also use other scenarios. In premise, scenarios are defined by their Shared Socio-economic Pathway (SSP), a climate trajectory—often represented by a Representative Concentration Pathway (RCP)—and a year (e.g., SSP1, Base, 2035).

SSP/RCP scenario	GMST increase by 2100	Society/economy trend	Climate policy	REMIND	IMAGE	TIAM-UCL
SSP1-None	2.3-2.8 °C	Optimistic trends for human develop. and economy, driven by sustainable practices.	None	SSP1-Base	SSP1-Base
SSP1-None	~2.2 °C	Optimistic trends for human develop. and economy, driven by sustainable practices.	National Policies Implemented (NPI).	SSP1-NPi
SSP1-None	~1.9 °C	Optimistic trends for human develop. and economy, driven by sustainable practices.	Nationally Determined Contributions (NDCs).	SSP1-NDC
SSP1-RCP2.6	~1.7 °C	Optimistic trends for human develop. and economy, driven by sustainable practices.	Paris Agreement objective.	SSP1-PkBudg1150
SSP1-RCP1.9	~1.3 °C	Optimistic trends for human develop. and economy, driven by sustainable practices.	Paris Agreement objective.	SSP1-PkBudg500
SSP2-None	~3.5 °C	Extrapolation from historical developments.	None (eq. to RCP6)	SSP2-Base	SSP2-Base	SSP2-Base
SSP2-None	~3.3 °C	Extrapolation from historical developments.	National Policies Implemented (NPI).	SSP2-NPi		SSP2-RCP45
SSP2-None	~2.5 °C	Extrapolation from historical developments.	Nationally Determined Contributions (NDCs).	SSP2-NDC
SSP2-RCP2.6	1.6-1.8 °C	Extrapolation from historical developments.	Paris Agreement objective.	SSP2-PkBudg1150	SSP2-RCP26	SSP2-RCP26
SSP2-RCP1.9	1.2-1.4 °C	Extrapolation from historical developments.	Paris Agreement objective.	SSP2-PkBudg500	SSP2-RCP19	SSP2-RCP19
SSP5-None	~4.5 °C	Optimistic trends for human develop. and economy, driven by fossil fuels.	None	SSP5-Base
SSP5-None	~4.0 °C	Optimistic trends for human develop. and economy, driven by fossil fuels.	National Policies Implemented (NPI).	SSP5-NPi
SSP5-None	~3.0 °C	Optimistic trends for human develop. and economy, driven by fossil fuels.	Nationally Determined Contributions (NDCs).	SSP5-NDC
SSP5-RCP2.6	~1.7 °C	Optimistic trends for human develop. and economy, driven by fossil fuels.	Paris Agreement objective.	SSP5-PkBudg1150
SSP5-RCP1.9	~1.0 °C	Optimistic trends for human develop. and economy, driven by fossil fuels.	Paris Agreement objective.	SSP5-PkBudg500

Note

A summary report of the main variables of the scenarios selected is generated automatically after each database export. There is also an online dashboard. You can also generate it manually:

Supported versions of ecoinvent

premise currently works with the following ecoinvent database versions:

• v.3.6

• v.3.7

• v.3.8, cut-off and consequential

• v.3.9, cut-off and consequential

• v.3.10, cut-off and consequential

Supported sources of ecoinvent

premise can extract the ecoinvent database from:

• a brightway2 project that contains the ecoinvent database

• ecosposld2 files, that can be downloaded from the ecoinvent website

Note

The ecoinvent database is not included in premise. You need to have a valid license to download and use it. Also, please read carefully ecoinvent’s EULA before using premise.

From a brightway2 project

To extract from an ecoinvent database located in a brightway2 project, simply indicate the database name in source_db and its version in source_version:

from premise import *
import brightway2 as bw

bw.projects.set_current("my_project)

ndb = NewDatabase(
      scenarios=[
              {"model":"remind", "pathway":"SSP2-Base", "year":2028}
          ],
      source_db="ecoinvent 3.7 cutoff", # <-- this is NEW.
      source_version="3.7.1", # <-- this is NEW
      key='xxxxxxxxxxxxxxxxxxxxxxxxx',
      use_multiprocessing=True, # True by default, set to False if multiprocessing is causing troubles
      keep_uncertainty_data=False # False by default, set to True if you want to keep ecoinvent's uncertainty data
  )

Note that a cache of the database will be created the first time and store in the library folder. Any subsequent creation of databases using the same ecoinvent version will no longer require this extraction step.

If you wish to clear that cache folder (database and premise additional inventories), do:

from premise import *

clear_cache()

Note

It is recommended to restart your notebook once the data has been cached for the first time, so that the remaining steps can be performed using the cached data (much faster).

To clear only the premise additional inventories, do:

from premise import *

clear_inventory_cache()

Note

After a version update, databases and inventories are automatically re-extracted and re-imported. This is to ensure that the data is consistent with the new version of premise.

From ecospold2 files

To extract from a set of ecospold2 files, you need to point to the location of those files in source_file_path, as well as indicate the database format in source_type:

from premise import *

ndb = NewDatabase(
    scenarios = [
        {"model":"remind", "pathway":"SSP2-Base", "year":2028}
                ],
    source_type="ecospold", # <--- this is NEW
    source_file_path=r"C:\file\path\to\ecoinvent 3.5_cutoff_ecoSpold02\datasets", # <-- this is NEW
    source_version="3.5",
)

Import of additional inventories

After the ecoinvent database is extracted and checked, a number of additional inventories are imported, regardless of the year of scenario that is being considered.

Power generation

A number of datasets relating to power generation not originally present in ecoinvent are imported. The next sub-sections lists such datasets.

Power plants with CCS

Datasets for power generation with Carbon Capture and Storage (CCS) are imported. They originate from Volkart et al. 2013, and can be consulted here: LCI_Power_generation. An exception to this are the inventories for biomass-based integrated gasification combined cycle power plants (BIGCCS), which are from Briones-Hidrovo et al, 2020.

The table below lists the names of the new activities (only production datasets are shown).

Power generation with CCS (activities list)	location
electricity production, at power plant/hard coal, IGCC, no CCS	RER
electricity production, at power plant/hard coal, PC, no CCS	RER
electricity production, at power plant/hard coal, oxy, pipeline 200km, storage 1000m	RER
electricity production, at power plant/hard coal, oxy, pipeline 400km, storage 3000m	RER
electricity production, at power plant/hard coal, post, pipeline 200km, storage 1000m	RER
electricity production, at power plant/hard coal, post, pipeline 400km, storage 1000m	RER
electricity production, at power plant/hard coal, post, pipeline 400km, storage 3000m	RER
electricity production, at power plant/hard coal, pre, pipeline 200km, storage 1000m	RER
electricity production, at power plant/hard coal, pre, pipeline 400km, storage 3000m	RER
electricity production, at power plant/lignite, IGCC, no CCS	RER
electricity production, at power plant/lignite, PC, no CCS	RER
electricity production, at power plant/lignite, oxy, pipeline 200km, storage 1000m	RER
electricity production, at power plant/lignite, oxy, pipeline 400km, storage 3000m	RER
electricity production, at power plant/lignite, post, pipeline 200km, storage 1000m	RER
electricity production, at power plant/lignite, post, pipeline 400km, storage 3000m	RER
electricity production, at power plant/lignite, pre, pipeline 200km, storage 1000m	RER
electricity production, at power plant/lignite, pre, pipeline 400km, storage 3000m	RER
electricity production, at power plant/natural gas, ATR H2-CC, no CCS	RER
electricity production, at power plant/natural gas, NGCC, no CCS/kWh	RER
electricity production, at power plant/natural gas, post, pipeline 200km, storage 1000m	RER
electricity production, at power plant/natural gas, post, pipeline 400km, storage 1000m	RER
electricity production, at power plant/natural gas, post, pipeline 400km, storage 3000m	RER
electricity production, at power plant/natural gas, pre, pipeline 200km, storage 1000m	RER
electricity production, at power plant/natural gas, pre, pipeline 400km, storage 3000m	RER
electricity production, at wood burning power plant 20 MW, truck 25km, no CCS	RER
electricity production, at wood burning power plant 20 MW, truck 25km, post, pipeline 200km, storage 1000m	RER
electricity production, at wood burning power plant 20 MW, truck 25km, post, pipeline 400km, storage 3000m	RER

Natural gas

Updated inventories relating to natural gas extraction and distribution are imported to substitute some of the original ecoinvent dataset. These datasets originate from ESU Services and come with a report, and can be consulted here: LCI_Oil_NG.

They have been adapted to a brightway2-compatible format. These new inventories have, among other things, higher methane slip emissions along the natural gas supply chain, especially at extraction.

Original dataset	Replaced by
natural gas production (natural gas, high pressure), DE	natural gas, at production (natural gas, high pressure), DE
natural gas production (natural gas, high pressure), DZ	natural gas, at production (natural gas, high pressure), DZ
natural gas production (natural gas, high pressure), US	natural gas, at production (natural gas, high pressure), US
natural gas production (natural gas, high pressure), RU	natural gas, at production (natural gas, high pressure), RU
petroleum and gas production, GB	natural gas, at production (natural gas, high pressure), GB
petroleum and gas production, NG	natural gas, at production (natural gas, high pressure), NG
petroleum and gas production, NL	natural gas, at production (natural gas, high pressure), NL
petroleum and gas production, NO	natural gas, at production (natural gas, high pressure), NO

The original natural gas datasets are preserved, but they do not provide input to any other datasets in the database. The new datasets provide natural gas at high pressure to the original supply chains, which remain unchanged.

The table below lists the names of the new activities (only high pressure datasets are shown).

Natural gas extraction	location
natural gas, at production	AZ
natural gas, at production	RO
natural gas, at production	LY
natural gas, at production	SA
natural gas, at production	IQ
natural gas, at production	RU
natural gas, at production	NL
natural gas, at production	DZ
natural gas, at production	NG
natural gas, at production	DE
natural gas, at production	KZ
natural gas, at production	NO
natural gas, at production	QA
natural gas, at production	GB
natural gas, at production	MX
natural gas, at production	US

Note

This import does not occur when using ecoinvent v.3.9 as those dataset updates are already included.

Photovoltaic panels

Photovoltaic panel inventories originate the IEA’s Task 12 project IEA_PV. They have been adapted into a brightway2-friendly format. They can be consulted here: LCI_PV.

They consist of the following PV installation types:

PV installation	location
photovoltaic slanted-roof installation, 1.3 MWp, multi-Si, panel, mounted, on roof	CH
photovoltaic flat-roof installation, 156 kWp, multi-Si, on roof	CH
photovoltaic flat-roof installation, 156 kWp, single-Si, on roof	CH
photovoltaic flat-roof installation, 280 kWp, multi-Si, on roof	CH
photovoltaic flat-roof installation, 280 kWp, single-Si, on roof	CH
photovoltaic flat-roof installation, 324 kWp, multi-Si, on roof	DE
photovoltaic slanted-roof installation, 3 kWp, CIS, laminated, integrated, on roof	CH
photovoltaic slanted-roof installation, 3 kWp, CIS, laminated, integrated, on roof	RER
photovoltaic slanted-roof installation, 3 kWp, CdTe, panel, mounted, on roof	CH
photovoltaic slanted-roof installation, 3 kWp, CdTe, panel, mounted, on roof	RER
photovoltaic slanted-roof installation, 3 kWp, micro-Si, laminated, integrated, on roof	RER
photovoltaic slanted-roof installation, 3 kWp, micro-Si, panel, mounted, on roof	RER
photovoltaic flat-roof installation, 450 kWp, single-Si, on roof	DE
photovoltaic open ground installation, 560 kWp, single-Si, on open ground	CH
photovoltaic open ground installation, 569 kWp, multi-Si, on open ground	ES
photovoltaic open ground installation, 570 kWp, CIS, on open ground	RER
photovoltaic open ground installation, 570 kWp, CdTe, on open ground	RER
photovoltaic open ground installation, 570 kWp, micro-Si, on open ground	RER
photovoltaic open ground installation, 570 kWp, multi-Si, on open ground	ES
photovoltaic open ground installation, 570 kWp, multi-Si, on open ground	RER
photovoltaic open ground installation, 570 kWp, single-Si, on open ground	RER
photovoltaic slanted-roof installation, 93 kWp, multi-Si, laminated, integrated, on roof	CH
photovoltaic slanted-roof installation, 93 kWp, multi-Si, panel, mounted, on roof	CH
photovoltaic slanted-roof installation, 93 kWp, single-Si, laminated, integrated, on roof	CH
photovoltaic slanted-roof installation, 93 kWp, single-Si, panel, mounted, on roof	CH

Although these datasets have a limited number of locations (CH, RER, DE, ES), the IEA report provides country-specific load factors:

production [kWh/kWp]	roof-top	façade	central
PT	1427	999	1513
IL	1695	1187	1798
SE	919	643	974
FR	968	678	1026
TR	1388	971	1471
NZ	1240	868	1315
MY	1332	933	1413
CN	971	679	1029
TH	1436	1005	1522
ZA	1634	1144	1733
JP	1024	717	1086
CH	976	683	1040
DE	922	645	978
KR	1129	790	1197
AT	1044	731	1111
GR	1323	926	1402
IE	796	557	844
AU	1240	868	1314
IT	1298	908	1376
MX	1612	1128	1709
NL	937	656	994
GB	848	593	899
ES	1423	996	1509
CL	1603	1122	1699
HU	1090	763	1156
CZ	944	661	1101
CA	1173	821	1243
US	1401	981	1485
NO	832	583	882
FI	891	624	945
BE	908	635	962
DK	971	680	1030
LU	908	635	962

In the report, the generation potential per installation type is multiplied by the number of installations in each country, to produce country-specific PV power mix datasets normalized to 1 kWh. The report specifies the production-weighted PV mix for each country, but we further split it between residential (<=3kWp) and commercial (>3kWp) installations (as most IAMs make such distinction):

Production-weighted PV mix	location
electricity production, photovoltaic, residential	PT
electricity production, photovoltaic, residential	IL
electricity production, photovoltaic, residential	SE
electricity production, photovoltaic, residential	FR
electricity production, photovoltaic, residential	TR
electricity production, photovoltaic, residential	NZ
electricity production, photovoltaic, residential	MY
electricity production, photovoltaic, residential	CN
electricity production, photovoltaic, residential	TH
electricity production, photovoltaic, residential	ZA
electricity production, photovoltaic, residential	JP
electricity production, photovoltaic, residential	CH
electricity production, photovoltaic, residential	DE
electricity production, photovoltaic, residential	KR
electricity production, photovoltaic, residential	AT
electricity production, photovoltaic, residential	GR
electricity production, photovoltaic, residential	IE
electricity production, photovoltaic, residential	AU
electricity production, photovoltaic, residential	IT
electricity production, photovoltaic, residential	MX
electricity production, photovoltaic, residential	NL
electricity production, photovoltaic, residential	GB
electricity production, photovoltaic, residential	ES
electricity production, photovoltaic, residential	CL
electricity production, photovoltaic, residential	HU
electricity production, photovoltaic, residential	CZ
electricity production, photovoltaic, residential	CA
electricity production, photovoltaic, residential	US
electricity production, photovoltaic, residential	NO
electricity production, photovoltaic, residential	FI
electricity production, photovoltaic, residential	BE
electricity production, photovoltaic, residential	DK
electricity production, photovoltaic, residential	LU
electricity production, photovoltaic, commercial	PT
electricity production, photovoltaic, commercial	IL
electricity production, photovoltaic, commercial	SE
electricity production, photovoltaic, commercial	FR
electricity production, photovoltaic, commercial	TR
electricity production, photovoltaic, commercial	NZ
electricity production, photovoltaic, commercial	MY
electricity production, photovoltaic, commercial	CN
electricity production, photovoltaic, commercial	TH
electricity production, photovoltaic, commercial	ZA
electricity production, photovoltaic, commercial	JP
electricity production, photovoltaic, commercial	CH
electricity production, photovoltaic, commercial	DE
electricity production, photovoltaic, commercial	KR
electricity production, photovoltaic, commercial	AT
electricity production, photovoltaic, commercial	GR
electricity production, photovoltaic, commercial	IE
electricity production, photovoltaic, commercial	AU
electricity production, photovoltaic, commercial	IT
electricity production, photovoltaic, commercial	MX
electricity production, photovoltaic, commercial	NL
electricity production, photovoltaic, commercial	GB
electricity production, photovoltaic, commercial	ES
electricity production, photovoltaic, commercial	CL
electricity production, photovoltaic, commercial	HU
electricity production, photovoltaic, commercial	CZ
electricity production, photovoltaic, commercial	CA
electricity production, photovoltaic, commercial	US
electricity production, photovoltaic, commercial	NO
electricity production, photovoltaic, commercial	FI
electricity production, photovoltaic, commercial	BE
electricity production, photovoltaic, commercial	DK
electricity production, photovoltaic, commercial	LU

Hence, inside the residential PV mix of Spain (“electricity production, photovoltaic, residential”), one will find the following inputs for the production of 1kWh:

name	amount	location	unit
Energy, solar, converted	3.8503		megajoule
Heat, waste	0.25027		megajoule
photovoltaic slanted-roof installation, 3 kWp, CIS, laminated, integrated, on roof	2.48441E-08	CH	unit
photovoltaic slanted-roof installation, 3 kWp, CdTe, panel, mounted, on roof	4.99911E-07	CH	unit
photovoltaic slanted-roof installation, 3 kWp, micro-Si, laminated, integrated, on roof	3.93869E-09	RER	unit
photovoltaic slanted-roof installation, 3 kWp, micro-Si, panel, mounted, on roof	6.55186E-08	RER	unit
photovoltaic facade installation, 3kWp, multi-Si, laminated, integrated, at building	2.10481E-07	RER	unit
photovoltaic facade installation, 3kWp, multi-Si, panel, mounted, at building	2.10481E-07	RER	unit
photovoltaic facade installation, 3kWp, single-Si, laminated, integrated, at building	1.11463E-07	RER	unit
photovoltaic facade installation, 3kWp, single-Si, panel, mounted, at building	1.11463E-07	RER	unit
photovoltaic flat-roof installation, 3kWp, multi-Si, on roof	2.20794E-06	RER	unit
photovoltaic flat-roof installation, 3kWp, single-Si, on roof	1.17025E-06	RER	unit
photovoltaic slanted-roof installation, 3kWp, CIS, panel, mounted, on roof	4.12805E-07	CH	unit
photovoltaic slanted-roof installation, 3kWp, CdTe, laminated, integrated, on roof	3.00704E-08	CH	unit
photovoltaic slanted-roof installation, 3kWp, multi-Si, laminated, integrated, on roof	1.08693E-07	RER	unit
photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, mounted, on roof	1.81407E-06	RER	unit
photovoltaic slanted-roof installation, 3kWp, single-Si, laminated, integrated, on roof	5.75655E-08	RER	unit
photovoltaic slanted-roof installation, 3kWp, single-Si, panel, mounted, on roof	9.6195E-07	RER	unit

with, for example, 2.48E-8 units of “photovoltaic slanted-roof installation, 3 kWp, CIS, laminated, integrated, on roof” being calculated as:

1 / (30 [years] * 1423 [kWh/kWp] * 0.32% [share of PV capacity of such type installed in Spain])

Note that commercial PV mix datasets provide electricity at high voltage, unlike residential PV mix datasets, which supply at low voltage only.

Note

These current production mixes are not modified over time. This simplification is made because the data is not available for the future. However, the efficiency of the panels is adjusted to reflect expected improvements (see Photovoltaics panels under Transform).

Emerging technologies for photovoltaic panels are also imported, namely:

• Gallium Arsenide (GaAs) panels, with a conversion efficiency of 28%, from Pallas et al., 2020.

• Perovskite-on-silicon tandem panels, with a conversion efficiency of 25%, from Roffeis et al., 2022.

They are available in the following locations:

Emerging PV technologies	location
electricity production, photovoltaic, 0.28kWp, GaAs	GLO
electricity production, photovoltaic, 0.5kWp, perovskite-on-silicon tandem	RER

Note

These two technologies are not included in the current country-specific production mix datasets.

Geothermal

Heat production by means of a geothermal well are not represented in ecoinvent. The geothermal power plant construction inventories are from Maeder Bachelor Thesis.

The co-generation unit has been removed and replaced by heat exchanger and district heating pipes. Gross heat output of 1,483 TJ, with 80% efficiency.

The inventories can be consulted here: LCIgeothermal.

They introduce the following datasets (only heat production datasets shown):

Geothermal heat production	location
heat production, deep geothermal	RAS
heat production, deep geothermal	GLO
heat production, deep geothermal	RAF
heat production, deep geothermal	RME
heat production, deep geothermal	RLA
heat production, deep geothermal	RU
heat production, deep geothermal	CA
heat production, deep geothermal	JP
heat production, deep geothermal	US
heat production, deep geothermal	IN
heat production, deep geothermal	CN
heat production, deep geothermal	RER

Hydrogen

premise imports inventories for hydrogen production via the following pathways:

• Steam Methane Reforming, using natural gas

• Steam Methane Reforming, using natural gas, with Carbon Capture and Storage

• Steam Methane Reforming, using bio-methane

• Steam Methane Reforming, using bio-methane, with Carbon Capture and Storage

• Auto Thermal Reforming, using natural gas

• Auto Thermal Reforming, using natural gas, with Carbon Capture and Storage

• Auto Thermal Reforming, using bio-methane

• Auto Thermal Reforming, using bio-methane, with Carbon Capture and Storage

• Woody biomass gasification, using a fluidized bed

• Woody biomass gasification, using a fluidized bed, with Carbon Capture and Storage

• Woody biomass gasification, using an entrained flow gasifier

• Woody biomass gasification, using an entrained flow gasifier, with Carbon Capture and Storage

• Coal gasification

• Coal gasification, with Carbon Capture and Storage

• Electrolysis

• Thermochemical water splitting

• Pyrolysis

Inventories using Steam Methane Reforming are from Antonini et al. 2021. They can be consulted here: LCI_SMR. Inventories using Auto Thermal Reforming are from Antonini et al. 2021. They can be consulted here: LCI_ATR. Inventories using Woody biomass gasification are from Antonini2 et al. 2021. They can be consulted here: LCI_woody. Inventories using coal gasification are from Wokaun et al. 2015, but updated with Li et al. 2022, which also provide an option with CCS. They can be consulted here: LCI_coal. Inventories using electrolysis are from Niklas Gerloff. 2021. They can be consulted here: LCI_electrolysis. Inventories for thermochemical water splitting are from Zhang2 et al. 2022. Inventories for pyrolysis are from Al-Qahtani et al. 2021, completed with data from Postels et al., 2016.

The new datasets introduced are listed in the table below (only production datasets are shown).

Hydrogen production	location
hydrogen production, steam methane reforming	CH
hydrogen production, steam methane reforming, with CCS	CH
hydrogen production, steam methane reforming, from biomethane	CH
hydrogen production, steam methane reforming, from biomethane, with CCS	CH
hydrogen production, auto-thermal reforming, from biomethane	CH
hydrogen production, auto-thermal reforming, from biomethane, with CCS	CH
hydrogen production, gaseous, 25 bar, from heatpipe reformer gasification of woody biomass with CCS, at gasification plant	CH
hydrogen production, gaseous, 25 bar, from heatpipe reformer gasification of woody biomass, at gasification plant	CH
hydrogen production, gaseous, 25 bar, from gasification of woody biomass in entrained flow gasifier, with CCS, at gasification plant	CH
hydrogen production, gaseous, 25 bar, from gasification of woody biomass in entrained flow gasifier, at gasification plant	CH
hydrogen production, coal gasification	RER
hydrogen production, gaseous, 30 bar, from PEM electrolysis, from grid electricity	RER
hydrogen production, gaseous, 20 bar, from AEC electrolysis, from grid electricity	RER
hydrogen production, gaseous, 1 bar, from SOEC electrolysis, from grid electricity	RER
hydrogen production, gaseous, 1 bar, from SOEC electrolysis, with steam input, from grid electricity	RER
hydrogen production, gaseous, 25 bar, from thermochemical water splitting, at solar tower	RER
hydrogen production, gaseous, 100 bar, from methane pyrolysis	RER

Hydrogen storage and distribution

A number of datasets relating to hydrogen storage and distribution are also imported.

They are necessary to model the distribution of hydrogen:

• via re-assigned transmission and distribution CNG pipelines, in a gaseous state

• via dedicated transmission and distribution hydrogen pipelines, in a gaseous state

• as a liquid organic compound, by hydrogenation

• via truck, in a liquid state

• hydrogen refuelling station

Small and large storage solutions are also provided: * high pressure hydrogen storage tank * geological storage tank

These datasets originate from the work of Wulf et al. 2018, and can be consulted here: LCI_H2_distr. For re-assigned CNG pipelines, which require the hydrogen to be mixed together with oxygen to limit metal embrittlement, some parameters are taken from the work of Cerniauskas et al. 2020.

The datasets introduced are listed in the table below.

Hydrogen distribution	location
hydrogen refuelling station	GLO
high pressure hydrogen storage tank	GLO
pipeline, hydrogen, low pressure distribution network	RER
compressor assembly for transmission hydrogen pipeline	RER
pipeline, hydrogen, high pressure transmission network	RER
zinc coating for hydrogen pipeline	RER
hydrogenation of hydrogen	RER
dehydrogenation of hydrogen	RER
dibenzyltoluene production	RER
solution mining for geological hydrogen storage	RER
geological hydrogen storage	RER
hydrogen embrittlement inhibition	RER
distribution pipeline for hydrogen, reassigned CNG pipeline	RER
transmission pipeline for hydrogen, reassigned CNG pipeline	RER

Hydrogen turbine

A dataset for a hydrogen turbine is also imported, to model the production of electricity from hydrogen, with an efficiency of 51%. The efficiency of the H2-fed gas turbine is based on the parameters of Ozawa et al. (2019), accessible here: LCI_H2_turbine.

Ammonia

premise imports inventories for ammonia production using the following routes:

• steam methane reforming (Haber-Bosch)

• steam methane reforming (Haber-Bosch) with CCS of syngas

• steam methane reforming (Haber-Bosch) with CCS of syngas and flue gas

• partial oxidation of oil

• hydrogen from coal gasification

• hydrogen from coal gasification with CCS

• hydrogen from electrolysis

• hydrogen from natural gas pyrolysis

These inventories are published in Boyce et al., 2023, and are largely based on Carlo d’ Angelo et al., 2021.

The supply of hydrogen in the ammonia production process (coal gasification, electrolysis, etc.) is represented by the inventories described in the sections above.

Biofuels

Inventories for energy crops- and residues-based production of bioethanol and biodiesel are imported, and can be accessed here: LCI_biofuels. They include the farming of the crop, the conversion of the biomass to fuel, as well as its distribution. The conversion process often leads to the production of co-products (dried distiller’s grain, electricity, CO2, bagasse.). Hence, energy, economic and system expansion partitioning approaches are available. These inventories originate from several different sources (Wu et al. 2006 (2020 update), Cozzolino 2018, Pereira et al. 2019 and Gonzalez-Garcia et al. 2012), Cavalett & Cherubini 2022, as indicated in the table below.

The following datasets are introduced:

Activity	Location	Source
Farming and supply of switchgrass	US	Wu et al. 2006 (2020 update)
Farming and supply of poplar	US	Wu et al. 2006 (2020 update)
Farming and supply of willow	US	Wu et al. 2006 (2020 update)
Supply of forest residue	US	Wu et al. 2006 (2020 update)
Farming and supply of miscanthus	US	Wu et al. 2006 (2020 update)
Farming and supply of corn stover	US	Wu et al. 2006 (2020 update)
Farming and supply of sugarcane	US	Wu et al. 2006 (2020 update)
Farming and supply of Grain Sorghum	US	Wu et al. 2006 (2020 update)
Farming and supply of Sweet Sorghum	US	Wu et al. 2006 (2020 update)
Farming and supply of Forage Sorghum	US	Wu et al. 2006 (2020 update)
Farming and supply of corn	US	Wu et al. 2006 (2020 update)
Farming and supply of sugarcane	BR	Pereira et al. 2019/RED II
Farming and supply of sugarcane straw	BR	Pereira et al. 2019
Farming and supply of eucalyptus	ES	Gonzalez-Garcia et al. 2012
Farming and supply of wheat grains	RER	Cozzolino 2018
Farming and supply of wheat straw	RER	Cozzolino 2018
Farming and supply of corn	RER	Cozzolino 2018/RED II
Farming and supply of sugarbeet	RER	Cozzolino 2018
Supply of forest residue	RER	Cozzolino 2018
Supply and refining of waste cooking oil	RER	Cozzolino 2018
Farming and supply of rapeseed	RER	Cozzolino 2018/RED II
Farming and supply of palm fresh fruit bunch	RER	Cozzolino 2018
Farming and supply of dry algae	RER	Cozzolino 2018
Ethanol production, via fermentation, from switchgrass	US	Wu et al. 2006 (2020 update)
Ethanol production, via fermentation, from poplar	US	Wu et al. 2006 (2020 update)
Ethanol production, via fermentation, from willow	US	Wu et al. 2006 (2020 update)
Ethanol production, via fermentation, from forest residue	US	Wu et al. 2006 (2020 update)
Ethanol production, via fermentation, from miscanthus	US	Wu et al. 2006 (2020 update)
Ethanol production, via fermentation, from corn stover	US	Wu et al. 2006 (2020 update)
Ethanol production, via fermentation, from sugarcane	US	Wu et al. 2006 (2020 update)
Ethanol production, via fermentation, from grain sorghum	US	Wu et al. 2006 (2020 update)
Ethanol production, via fermentation, from sweet sorghum	US	Wu et al. 2006 (2020 update)
Ethanol production, via fermentation, from forage sorghum	US	Wu et al. 2006 (2020 update)
Ethanol production, via fermentation, from corn	US	Wu et al. 2006 (2020 update)
Ethanol production, via fermentation, from corn, with carbon capture	US	Wu et al. 2006 (2020 update)
Ethanol production, via fermentation, from sugarcane	BR	Pereira et al. 2019
Ethanol production, via fermentation, from sugarcane straw	BR	Pereira et al. 2019
Ethanol production, via fermentation, from eucalyptus	ES	Gonzalez-Garcia et al. 2012
Ethanol production, via fermentation, from wheat grains	RER	Cozzolino 2018
Ethanol production, via fermentation, from wheat straw	RER	Cozzolino 2018
Ethanol production, via fermentation, from corn starch	RER	Cozzolino 2018
Ethanol production, via fermentation, from sugarbeet	RER	Cozzolino 2018
Ethanol production, via fermentation, from forest residue	RER	Cozzolino 2018
Ethanol production, via fermentation, from forest residues	RER	Cavalett & Cherubini 2022
Ethanol production, via fermentation, from forest product (non-residual)	RER	Cavalett & Cherubini 2022
Biodiesel production, via transesterification, from used cooking oil	RER	Cozzolino 2018
Biodiesel production, via transesterification, from rapeseed oil	RER	Cozzolino 2018
Biodiesel production, via transesterification, from palm oil, energy allocation	RER	Cozzolino 2018
Biodiesel production, via transesterification, from algae, energy allocation	RER	Cozzolino 2018
Biodiesel production, via Fischer-Tropsch, from forest residues	RER	Cavalett & Cherubini 2022
Biodiesel production, via Fischer-Tropsch, from forest product (non-residual)	RER	Cavalett & Cherubini 2022
Kerosene production, via Fischer-Tropsch, from forest residues	RER	Cavalett & Cherubini 2022
Kerosene production, via Fischer-Tropsch, from forest product (non-residual)	RER	Cavalett & Cherubini 2022

Synthetic fuels

premise imports inventories for the synthesis of hydrocarbon fuels following two pathways:

• Fischer-Tropsch: it uses hydrogen and CO (from CO2 via a reverse water gas shift process) to produce “syncrude”, which is distilled into diesel, kerosene, naphtha and lubricating oil and waxes. Inventories are from van der Giesen et al. 2014.

• Methanol-to-liquids: methanol is synthesized from hydrogen and CO2, and further distilled into gasoline, diesel, LGP and kerosene. Synthetic methanol inventories are from Hank et al. 2019. The methanol to fuel process specifications are from FVV 2013.

• Electro-chemical methanation: methane is produced from hydrogen and CO2 using a Sabatier methanation reactor. Inventories are from Zhang et al, 2019.

In their default configuration, these fuels use hydrogen from electrolysis and CO2 from direct air capture (DAC). However, premise builds different configurations (i.e., CO2 and hydrogen sources) for these fuels, for each IAM region:

Fuel production dataset	location	source
Diesel production, synthetic, from Fischer Tropsch process, hydrogen from coal gasification, at fuelling station	all IAM regions	van der Giesen et al. 2014
Diesel production, synthetic, from Fischer Tropsch process, hydrogen from coal gasification, with CCS, at fuelling station	all IAM regions	van der Giesen et al. 2014
Diesel production, synthetic, from Fischer Tropsch process, hydrogen from electrolysis, at fuelling station	all IAM regions	van der Giesen et al. 2014
Diesel production, synthetic, from Fischer Tropsch process, hydrogen from wood gasification, at fuelling station	all IAM regions	van der Giesen et al. 2014
Diesel production, synthetic, from Fischer Tropsch process, hydrogen from wood gasification, with CCS, at fuelling station	all IAM regions	van der Giesen et al. 2014
Diesel production, synthetic, from methanol, hydrogen from coal gasification, at fuelling station	all IAM regions	Hank et al, 2019
Diesel production, synthetic, from methanol, hydrogen from coal gasification, with CCS, at fuelling station	all IAM regions	Hank et al, 2019
Diesel production, synthetic, from methanol, hydrogen from electrolysis, CO2 from cement plant, at fuelling station	all IAM regions	Hank et al, 2019
Diesel production, synthetic, from methanol, hydrogen from electrolysis, CO2 from DAC, at fuelling station	all IAM regions	Hank et al, 2019
Gasoline production, synthetic, from methanol, hydrogen from coal gasification, at fuelling station	all IAM regions	Hank et al, 2019
Gasoline production, synthetic, from methanol, hydrogen from coal gasification, with CCS, at fuelling station	all IAM regions	Hank et al, 2019
Gasoline production, synthetic, from methanol, hydrogen from electrolysis, CO2 from cement plant, at fuelling station	all IAM regions	Hank et al, 2019
Gasoline production, synthetic, from methanol, hydrogen from electrolysis, CO2 from DAC, at fuelling station	all IAM regions	Hank et al, 2019
Kerosene production, from methanol, hydrogen from coal gasification	all IAM regions	Hank et al, 2019
Kerosene production, from methanol, hydrogen from electrolysis, CO2 from cement plant	all IAM regions	Hank et al, 2019
Kerosene production, from methanol, hydrogen from electrolysis, CO2 from DAC	all IAM regions	Hank et al, 2019
Kerosene production, synthetic, Fischer Tropsch process, hydrogen from coal gasification	all IAM regions	van der Giesen et al. 2014
Kerosene production, synthetic, Fischer Tropsch process, hydrogen from coal gasification, with CCS	all IAM regions	van der Giesen et al. 2014
Kerosene production, synthetic, Fischer Tropsch process, hydrogen from electrolysis	all IAM regions	van der Giesen et al. 2014
Kerosene production, synthetic, Fischer Tropsch process, hydrogen from wood gasification	all IAM regions	van der Giesen et al. 2014
Kerosene production, synthetic, Fischer Tropsch process, hydrogen from wood gasification, with CCS	all IAM regions	van der Giesen et al. 2014
Lubricating oil production, synthetic, Fischer Tropsch process, hydrogen from coal gasification	all IAM regions	van der Giesen et al. 2014
Lubricating oil production, synthetic, Fischer Tropsch process, hydrogen from electrolysis	all IAM regions	van der Giesen et al. 2014
Lubricating oil production, synthetic, Fischer Tropsch process, hydrogen from wood gasification	all IAM regions	van der Giesen et al. 2014
Lubricating oil production, synthetic, Fischer Tropsch process, hydrogen from wood gasification, with CCS	all IAM regions	van der Giesen et al. 2014
Methane, synthetic, gaseous, 5 bar, from coal-based hydrogen, at fuelling station	all IAM regions	Zhang et al, 2019
Methane, synthetic, gaseous, 5 bar, from electrochemical methanation (H2 from electrolysis, CO2 from DAC using heat pump heat), at fuelling station, using heat pump heat	all IAM regions	Zhang et al, 2019
Methane, synthetic, gaseous, 5 bar, from electrochemical methanation (H2 from electrolysis, CO2 from DAC using waste heat), at fuelling station, using waste heat	all IAM regions	Zhang et al, 2019
Methane, synthetic, gaseous, 5 bar, from electrochemical methanation, at fuelling station	all IAM regions	Zhang et al, 2019
Naphtha production, synthetic, Fischer Tropsch process, hydrogen from coal gasification	all IAM regions	van der Giesen et al. 2014
Naphtha production, synthetic, Fischer Tropsch process, hydrogen from electrolysis	all IAM regions	van der Giesen et al. 2014
Naphtha production, synthetic, Fischer Tropsch process, hydrogen from wood gasification	all IAM regions	van der Giesen et al. 2014
Naphtha production, synthetic, Fischer Tropsch process, hydrogen from wood gasification, with CCS	all IAM regions	van der Giesen et al. 2014
Liquefied petroleum gas production, synthetic, from methanol, hydrogen from electrolysis, CO2 from DAC, at fuelling station	all IAM regions	Hank et al, 2019

In the case of wood and coal gasification-based fuels, the CO2 needed to produce methanol or syncrude originates from the gasification process itself. This also implies that in the methanol and/or RWGS process, a carbon balance correction is applied to reflect the fact that a part of the CO2 from the gasification process is redirected into the fuel production process.

If the CO2 originates from:

• a gasification process without CCS, a negative carbon correction is added to

reflect the fact that part of the CO2 has not been emitted but has ended in the fuel instead. * the gasification process with CCS, no carbon correction is necessary, because the CO2 is stored in the fuel instead of being stored underground, which from a carbon accounting standpoint is similar.

Carbon Capture

Two sets of inventories for Direct Air Capture (DAC) are available in premise. One for a solvent-based system, and one for a sorbent-based system. The inventories were developed by Qiu and are available in the LCI_DAC spreadsheet. For each, a variant including the subsequent compression, transport and storage of the captured CO2 is also available.

They can be consulted here: LCI_DAC.

Additional, two datasets for carbon capture at point sources are available: one at cement plant from Meunier et al, 2020, and another one at municipal solid waste incineration plant (MSWI) from Bisinella et al, 2021.

They introduce the following datasets:

Activity	Location
carbon dioxide, captured from atmosphere, with a sorbent-based direct air capture system, 100ktCO2	RER
carbon dioxide, captured from atmosphere and stored, with a sorbent-based direct air capture system, 100ktCO2	RER
carbon dioxide, captured from atmosphere, with a solvent-based direct air capture system, 1MtCO2	RER
carbon dioxide, captured from atmosphere and stored, with a solvent-based direct air capture system, 1MtCO2	RER
carbon dioxide, captured at municipal solid waste incineration plant, for subsequent reuse	RER
carbon dioxide, captured at cement production plant, for subsequent reuse	RER

Using the transformation function update(“dac”), premise creates various configurations of these processes, using different sources for heat (industrial steam heat, high-temp heat pump heat and excess heat), which are found under the following names, for each IAM region:

name	location
carbon dioxide, captured from atmosphere, with a solvent-based direct air capture system, 1MtCO2, with industrial steam heat, and grid electricity	all IAM regions
carbon dioxide, captured from atmosphere, with a solvent-based direct air capture system, 1MtCO2, with heat pump heat, and grid electricity	all IAM regions
carbon dioxide, captured from atmosphere, with a sorbent-based direct air capture system, 100ktCO2, with waste heat, and grid electricity	all IAM regions
carbon dioxide, captured from atmosphere, with a sorbent-based direct air capture system, 100ktCO2, with industrial steam heat, and grid electricity	all IAM regions
carbon dioxide, captured from atmosphere, with a sorbent-based direct air capture system, 100ktCO2, with heat pump heat, and grid electricity	all IAM regions

Note that only solid sorbent DAC can use waste heat, as the heat requirement for liquid solvent DAC is too high (~900 C)

Li-ion batteries

When using ecoinvent 3.8 as a database, premise imports new inventories for lithium-ion batteries. NMC-111, NMC-622 NMC-811 and NCA Lithium-ion battery inventories are originally from Dai et al. 2019. They have been adapted to ecoinvent by Crenna et al, 2021. LFP and LTO Lithium-ion battery inventories are from Schmidt et al. 2019. Li-S (Lithium-sulfur) battery inventories are from Wickerts et al. 2023. Li-O2 (Lithium-air) battery inventories are from Wang et al. 2020. Finally, SIB (Sodium-ion) battery inventories are from Zhang22 et al. 2024. Ecoinvent provides also inventories for LMO (Lithium Maganese Oxide) batteries.

They introduce the following datasets:

Battery components	location	source
battery management system production, for Li-ion battery	GLO	Schmidt et al. 2019
market for battery, Li-ion, NMC111, rechargeable, prismatic	GLO	Dai et al. 2019, Crenna et al. 2021
market for battery, Li-ion, NMC622, rechargeable, prismatic	GLO	Dai et al. 2019, Crenna et al. 2021
market for battery, Li-ion, NMC811, rechargeable, prismatic	GLO	Dai et al. 2019, Crenna et al. 2021
market for battery, Li-ion, NCA, rechargeable, prismatic	GLO	Dai et al. 2019, Crenna et al. 2021
market for battery, Li-ion, LFP, rechargeable, prismatic	GLO	Schmidt et al. 2019
market for battery cell, Li-ion, LTO	GLO	Schmidt et al. 2019
market for battery, Li-sulfur, Li-S	GLO	Wickerts et al. (2023)
market for battery, Li-oxygen, Li-O2	GLO	Wang et al. (2020)
market for battery, Sodium-ion, SiB	GLO	Zhang et al. (2024)
market for battery, NaCl, rechargeable, prismatic	GLO	Galloway & Dustmann (2003)

These battery inventories are mostly used by battery electric vehicles, stationary energy storage systems, etc. (also imported by premise).

NMC-111, NMC-811, LFP and NCA inventories can be found here: LCI_batteries1. NMC-622 and LTO inventories can be found here: LCI_batteries2. Li-S inventories can be found here: LCI_batteries3. Li-O2 inventories can be found here: LCI_batteries4. And SIB inventories can be found here: LCI_batteries5.

When using ecoinvent 3.9 and above, the NMC-111, NMC-811, LFP and NCA battery inventories are not imported (as are already present the ecoinvent database).

Graphite

premise includes new inventories for:

• natural graphite, from Engels et al. 2022,

• synthetic graphite, from Surovtseva et al. 2022,

forming a new market for graphite, with the following datasets:

Activity	Location
market for graphite, battery grade		1.0
graphite, natural	CN	0.8
graphite, synthetic	CN	0.2

to represent a 80:20 split between natural and synthetic graphite, according to Surovtseva et al, 2022.

These inventories can be found here: LCI_graphite.

Cobalt

New inventories of cobalt are added, from the work of Dai, Kelly and Elgowainy, 2018. They are available under the following datasets:

Activity	Location
cobalt sulfate production, from copper mining, economic allocation	CN
cobalt sulfate production, from copper mining, energy allocation	CN
cobalt metal production, from copper mining, via electrolysis, economic allocation	CN
cobalt metal production, from copper mining, via electrolysis, energy allocation	CN

We recommend using those rather than the original ecoinvent inventories for cobalt, provided by the Cobalt Development Institute (CDI) since ecoinvent 3.7, which seem to lack transparency.

These inventories can be found here: LCI_cobalt.

Lithium

New inventories for lithium extraction are also added, from the work of Schenker et al., 2022. They cover lithium extraction from five different locations in Chile, Argentina and China. They are available under the following datasets for battery production:

Activity	Location
market for lithium carbonate, battery grade	GLO
market for lithium hydroxide, battery grade	GLO

These inventories can be found here: LCI_lithium.

Vanadium Redox Flow Batteries

premise imports inventories for the production of a vanadium redox flow battery, used for grid-balancing, from the work of Weber et al. 2021. It is available under the following dataset:

• vanadium-redox flow battery system assembly, 8.3 megawatt hour

The dataset providing electricity is the following:

• electricity supply, high voltage, from vanadium-redox flow battery system

The power capacity for this application is 1MW and the net storage capacity 6 MWh. The net capacity considers the internal inefficiencies of the batteries and the min Sate-of-Charge, requiring a certain oversizing of the batteries. For providing net 6 MWh, a nominal capacity of 8.3 MWh is required for the VRFB with the assumed operation parameters. The assumed lifetime of the stack is 10 years. The lifetime of the system is 20 years or 8176 cycle-life (49,000 MWh).

These inventories can be found here: LCI_vanadium_redox_flow_batteries.

This publication also provides LCIs for Vanadium mining and refining from iron ore. The end product is vanadium pentoxide, which is available under the following dataset:

• vanadium pentoxide production

These inventories can be found here: LCI_vanadium.

Road vehicles

premise imports inventories for different types of on-road vehicles.

Two-wheelers

The following datasets for two-wheelers are imported. Inventories are from Sacchi et al. 2022. The vehicles are available for different years and emission standards. premise will only import vehicles which production year is equal or inferior to the scenario year considered. The inventories can be consulted here: LCItwowheelers.

Two-wheeler datasets	location
transport, Kick Scooter, electric, <1kW	all IAM regions
transport, Bicycle, conventional, urban	all IAM regions
transport, Bicycle, electric (<25 km/h)	all IAM regions
transport, Bicycle, electric (<45 km/h)	all IAM regions
transport, Bicycle, electric, cargo bike	all IAM regions
transport, Moped, gasoline, <4kW, EURO-5	all IAM regions
transport, Scooter, gasoline, <4kW, EURO-5	all IAM regions
transport, Scooter, gasoline, 4-11kW, EURO-5	all IAM regions
transport, Scooter, electric, <4kW	all IAM regions
transport, Scooter, electric, 4-11kW	all IAM regions
transport, Motorbike, gasoline, 4-11kW, EURO-5	all IAM regions
transport, Motorbike, gasoline, 11-35kW, EURO-5	all IAM regions
transport, Motorbike, gasoline, >35kW, EURO-5	all IAM regions
transport, Motorbike, electric, <4kW	all IAM regions
transport, Motorbike, electric, 4-11kW	all IAM regions
transport, Motorbike, electric, 11-35kW	all IAM regions
transport, Motorbike, electric, >35kW	all IAM regions

These inventories do not supply inputs to other activities in the LCI database.

Passenger cars

The following datasets for passenger cars are imported.

Passenger car datasets	location
transport, passenger car, gasoline, Large	all IAM regions
transport, passenger car, diesel, Large	all IAM regions
transport, passenger car, compressed gas, Large	all IAM regions
transport, passenger car, plugin gasoline hybrid, Large	all IAM regions
transport, passenger car, plugin diesel hybrid, Large	all IAM regions
transport, passenger car, fuel cell electric, Large	all IAM regions
transport, passenger car, battery electric Large	all IAM regions
transport, passenger car, gasoline hybrid, Large	all IAM regions
transport, passenger car, diesel hybrid, Large	all IAM regions
transport, passenger car, gasoline, Large SUV	all IAM regions
transport, passenger car, diesel, Large SUV	all IAM regions
transport, passenger car, compressed gas, Large SUV	all IAM regions
transport, passenger car, plugin gasoline hybrid, Large SUV	all IAM regions
transport, passenger car, plugin diesel hybrid, Large SUV	all IAM regions
transport, passenger car, fuel cell electric, Large SUV	all IAM regions
transport, passenger car, battery electric Large SUV	all IAM regions
transport, passenger car, gasoline hybrid, Large SUV	all IAM regions
transport, passenger car, diesel hybrid, Large SUV	all IAM regions
transport, passenger car, gasoline, Lower medium	all IAM regions
transport, passenger car, diesel, Lower medium	all IAM regions
transport, passenger car, compressed gas, Lower medium	all IAM regions
transport, passenger car, plugin gasoline hybrid, Lower medium	all IAM regions
transport, passenger car, plugin diesel hybrid, Lower medium	all IAM regions
transport, passenger car, fuel cell electric, Lower medium	all IAM regions
transport, passenger car, battery electric Lower medium	all IAM regions
transport, passenger car, gasoline hybrid, Lower medium	all IAM regions
transport, passenger car, diesel hybrid, Lower medium	all IAM regions
transport, passenger car, gasoline, Medium	all IAM regions
transport, passenger car, diesel, Medium	all IAM regions
transport, passenger car, compressed gas, Medium	all IAM regions
transport, passenger car, plugin gasoline hybrid, Medium	all IAM regions
transport, passenger car, plugin diesel hybrid, Medium	all IAM regions
transport, passenger car, fuel cell electric, Medium	all IAM regions
transport, passenger car, battery electric Medium	all IAM regions
transport, passenger car, gasoline hybrid, Medium	all IAM regions
transport, passenger car, diesel hybrid, Medium	all IAM regions
transport, passenger car, gasoline, Medium SUV	all IAM regions
transport, passenger car, diesel, Medium SUV	all IAM regions
transport, passenger car, compressed gas, Medium SUV	all IAM regions
transport, passenger car, plugin gasoline hybrid, Medium SUV	all IAM regions
transport, passenger car, plugin diesel hybrid, Medium SUV	all IAM regions
transport, passenger car, fuel cell electric, Medium SUV	all IAM regions
transport, passenger car, battery electric Medium SUV	all IAM regions
transport, passenger car, gasoline hybrid, Medium SUV	all IAM regions
transport, passenger car, diesel hybrid, Medium SUV	all IAM regions
transport, passenger car, battery electric Micro	all IAM regions
transport, passenger car, gasoline, Mini	all IAM regions
transport, passenger car, diesel, Mini	all IAM regions
transport, passenger car, compressed gas, Mini	all IAM regions
transport, passenger car, plugin gasoline hybrid, Mini	all IAM regions
transport, passenger car, plugin diesel hybrid, Mini	all IAM regions
transport, passenger car, fuel cell electric, Mini	all IAM regions
transport, passenger car, battery electric Mini	all IAM regions
transport, passenger car, gasoline hybrid, Mini	all IAM regions
transport, passenger car, diesel hybrid, Mini	all IAM regions
transport, passenger car, gasoline, Small	all IAM regions
transport, passenger car, diesel, Small	all IAM regions
transport, passenger car, compressed gas, Small	all IAM regions
transport, passenger car, plugin gasoline hybrid, Small	all IAM regions
transport, passenger car, plugin diesel hybrid, Small	all IAM regions
transport, passenger car, fuel cell electric, Small	all IAM regions
transport, passenger car, battery electric Small	all IAM regions
transport, passenger car, gasoline hybrid, Small	all IAM regions
transport, passenger car, diesel hybrid, Small	all IAM regions
transport, passenger car, gasoline, Van	all IAM regions
transport, passenger car, diesel, Van	all IAM regions
transport, passenger car, compressed gas, Van	all IAM regions
transport, passenger car, plugin diesel hybrid, Van	all IAM regions
transport, passenger car, fuel cell electric, Van	all IAM regions
transport, passenger car, battery electric Van	all IAM regions
transport, passenger car, gasoline hybrid, Van	all IAM regions
transport, passenger car, diesel hybrid, Van	all IAM regions

Inventories are from Sacchi2 et al. 2022. The vehicles are available for different years and emission standards and for each IAM region.

When doing:

update("cars")

premise will create fleet average vehicles for each IAM region. The inventories can be consulted here: LCIpasscars.

At the moment, these inventories do not supply inputs to other activities in the LCI database.

Medium and heavy duty trucks

The following datasets for medium and heavy-duty trucks are imported.

Truck datasets	location
transport, freight, lorry, battery electric 3.5t gross weight	all IAM regions
transport, freight, lorry, fuel cell electric, 3.5t gross weight	all IAM regions
transport, freight, lorry, diesel hybrid, 3.5t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, diesel, 3.5t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, compressed gas, 3.5t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, plugin diesel hybrid, 3.5t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, battery electric 7.5t gross weight	all IAM regions
transport, freight, lorry, fuel cell electric, 7.5t gross weight	all IAM regions
transport, freight, lorry, diesel hybrid, 7.5t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, diesel, 7.5t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, compressed gas, 7.5t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, plugin diesel hybrid, 7.5t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, battery electric 18t gross weight	all IAM regions
transport, freight, lorry, fuel cell electric, 18t gross weight	all IAM regions
transport, freight, lorry, diesel hybrid, 18t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, diesel, 18t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, compressed gas, 18t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, plugin diesel hybrid, 18t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, battery electric 26t gross weight	all IAM regions
transport, freight, lorry, fuel cell electric, 26t gross weight	all IAM regions
transport, freight, lorry, diesel hybrid, 26t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, diesel, 26t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, compressed gas, 26t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, plugin diesel hybrid, 26t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, battery electric 32t gross weight	all IAM regions
transport, freight, lorry, fuel cell electric, 32t gross weight	all IAM regions
transport, freight, lorry, diesel hybrid, 32t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, diesel, 32t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, compressed gas, 32t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, plugin diesel hybrid, 32t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, battery electric 40t gross weight	all IAM regions
transport, freight, lorry, fuel cell electric, 40t gross weight	all IAM regions
transport, freight, lorry, diesel hybrid, 40t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, diesel, 40t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, compressed gas, 40t gross weight, EURO-VI	all IAM regions
transport, freight, lorry, plugin diesel hybrid, 40t gross weight, EURO-VI	all IAM regions

Inventories are from Sacchi3 et al. 2021. The vehicles are available for different years and emission standards and for each IAM region.

When doing:

update("trucks")

premise will create fleet average vehicles for each IAM region. The inventories can be consulted here: LCItrucks.

Buses

The following datasets for city and coach buses are imported.

transport, passenger bus, battery electric - overnight charging 9m midibus	all IAM regions
transport, passenger bus, battery electric - opportunity charging, LTO battery, 9m midibus	all IAM regions
transport, passenger bus, fuel cell electric, 9m midibus	all IAM regions
transport, passenger bus, diesel hybrid, 9m midibus, EURO-VI	all IAM regions
transport, passenger bus, diesel, 9m midibus, EURO-VI	all IAM regions
transport, passenger bus, compressed gas, 9m midibus, EURO-VI	all IAM regions
transport, passenger bus, battery electric - overnight charging 13m single deck urban bus	all IAM regions
transport, passenger bus, battery electric - battery-equipped trolleybus, LTO battery, 13m single deck urban bus	all IAM regions
transport, passenger bus, battery electric - opportunity charging, LTO battery, 13m single deck urban bus	all IAM regions
transport, passenger bus, fuel cell electric, 13m single deck urban bus	all IAM regions
transport, passenger bus, diesel hybrid, 13m single deck urban bus, EURO-VI	all IAM regions
transport, passenger bus, diesel, 13m single deck urban bus, EURO-VI	all IAM regions
transport, passenger bus, compressed gas, 13m single deck urban bus, EURO-VI	all IAM regions
transport, passenger bus, fuel cell electric, 13m single deck coach bus	all IAM regions
transport, passenger bus, diesel hybrid, 13m single deck coach bus, EURO-VI	all IAM regions
transport, passenger bus, diesel, 13m single deck coach bus, EURO-VI	all IAM regions
transport, passenger bus, compressed gas, 13m single deck coach bus, EURO-VI	all IAM regions
transport, passenger bus, battery electric - overnight charging 13m double deck urban bus	all IAM regions
transport, passenger bus, battery electric - opportunity charging, LTO battery, 13m double deck urban bus	all IAM regions
transport, passenger bus, fuel cell electric, 13m double deck urban bus	all IAM regions
transport, passenger bus, diesel hybrid, 13m double deck urban bus, EURO-VI	all IAM regions
transport, passenger bus, diesel, 13m double deck urban bus, EURO-VI	all IAM regions
transport, passenger bus, compressed gas, 13m double deck urban bus, EURO-VI	all IAM regions
transport, passenger bus, fuel cell electric, 13m double deck coach bus	all IAM regions
transport, passenger bus, diesel hybrid, 13m double deck coach bus, EURO-VI	all IAM regions
transport, passenger bus, diesel, 13m double deck coach bus, EURO-VI	all IAM regions
transport, passenger bus, compressed gas, 13m double deck coach bus, EURO-VI	all IAM regions
transport, passenger bus, battery electric - overnight charging 18m articulated urban bus	all IAM regions
transport, passenger bus, battery electric - battery-equipped trolleybus, LTO battery, 18m articulated urban bus	all IAM regions
transport, passenger bus, battery electric - opportunity charging, LTO battery, 18m articulated urban bus	all IAM regions
transport, passenger bus, fuel cell electric, 18m articulated urban bus	all IAM regions
transport, passenger bus, diesel hybrid, 18m articulated urban bus, EURO-VI	all IAM regions
transport, passenger bus, diesel, 18m articulated urban bus, EURO-VI	all IAM regions
transport, passenger bus, compressed gas, 18m articulated urban bus, EURO-VI	all IAM regions

Inventories are from Sacchi et al. 2021. The vehicles are available for different years and emission standards and for each IAM region.

When doing:

update("buses")

premise will create fleet average vehicles for each IAM region. The inventories can be consulted here: LCIbuses.

At the moment. these inventories do not supply inputs to other activities in the LCI database. As such, they are optional.

Migration between ecoinvent versions

Because the additional inventories that are imported may be composed of exchanges meant to link with an ecoinvent version different than what the user specifies to premise upon the database creation, it is necessary to be able to “translate” the imported inventories so that they correctly link to any ecoinvent version premise is compatible with.

Therefore, premise has a migration map that is used to convert certain exchanges to be compatible with a given ecoinvent version.

This migration map is provided here: migrationmap.

IAM data collection

After extracting the ecoinvent database and additional inventories, premise instantiates the class IAMDataCollection, which collects all sorts of data from the IAM output file and store it into multi-dimensional arrays.

Production volumes and efficiencies

The mapping between IAM variables and premise variables regarding production volumes and efficiencies can be found in the mapping file.

Land use and land use change

The mapping between IAM variables and premise variables regarding land use and emissions caused by land use change can be found in the mapping file.

Carbon Capture and Storage

The mapping between IAM variables and premise variables regarding carbon capture and storage can be found in the mapping file.

Data sources external to the IAM

premise tries to adhere to the IAM scenario data as much as possible. There are however a number of cases where external data sources are used. This is notably the case for non-CO2 pollutants emissions for different sectors (electricity, steel and cement), as well as expected efficiency gains for photovoltaic panels and batteries.

Air emissions

premise relies on projections from the air emissions models GAINS-EU and GAINS-IAM to adjust the emissions of pollutants for different sectors. As with efficiencies, premise stores the change in emissions (called scaling factor) of a given technology relative to 2020. This is based on the fact that the emissions of ecoinvent datasets are believed to reflect the current (2020) situation. Hence, if a technology, in a given region, has a scaling factor of 1.2 in 2030, this means that the corresponding ecoinvent dataset is adjusted so that its emissions of a given substance is improved by 20%. In other words, premise does not use the emissions level given by GAINS, but rather its change over time relative to 2020.

For more information about this step, refer to sub-section “GAINS emission factors” in the EXTRACT section.

Photovoltaic panels

Module efficiencies in 2010 for micro-Si and single-Si are from IEA_ Task 12 report. For multi-Si, CIGS, CIS and CdTe, they are from IEA2 road map report on PV panels.

Current (2020) module efficiencies for all PV types are given by a 2021 report from the Fraunhofer Institute.

The efficiencies indicated for 2050 are what has been obtained in laboratory conditions by the Fraunhofer Institute. In other words, it is assumed that by 2050, solar PVs will reach production level efficiencies equal to those observed today in laboratories.

% module efficiency	micro-Si	single-Si	multi-Si	CIGS	CIS	CdTe
2010	10	15.1	14	11	11	10
2020	11.9	17.9	16.8	14	14	16.8
2050	12.5	26.7	24.4	23.4	23.4	21