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. For a detailed description of the models and scenarios available, see the Introduction_. .. _Introduction: introduction.rst .. 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: .. python:: ndb = NewDatabase(...) ndb.generate_scenario_report() Supported versions of ecoinvent """"""""""""""""""""""""""""""" *premise* currently works with the following ecoinvent database versions: * **v.3.5, cut-off** * **v.3.6, cut-off** * **v.3.7 and v.3.7.1, cut-off** * **v.3.8, cut-off and consequential** * **v.3.9 and v.3.9.1, cut-off and consequential** * **v.3.10 and v.3.10.1, cut-off and consequential** * **v.3.11, cut-off and consequential** * **v.3.12, 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 .. _ecoinvent: https://ecoinvent.org .. _brightway2: https://brightway.dev/ .. 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*. .. _EULA: https://ecoinvent.org/app/uploads/2024/01/EULA_new_branding_08_11_2023.pdf 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`: .. code-block:: python 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', keep_imports_uncertainty=True, # True by default, set to False to drop uncertainty in additional inventories keep_source_db_uncertainty=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 stored 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: .. code-block:: python 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: .. code-block:: python 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`: .. code-block:: python 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. All inventories can be found in the `premise/data/additional_inventories`_ folder. .. _premise/data/additional_inventories: https://github.com/polca/premise/tree/master/premise/data/additional_inventories 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. .. _Volkart: https://doi.org/10.1016/j.ijggc.2013.03.003 .. _Briones-Hidrovo: https://doi.org/10.1016/j.jclepro.2020.125680 .. _LCI_Power_generation: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-Carma-CCS.xlsx 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_. .. _LCI_Oil_NG: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-ESU-oil-and-gas.xlsx 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. .. _report: http://www.esu-services.ch/fileadmin/download/publicLCI/meili-2021-LCI%20for%20the%20oil%20and%20gas%20extraction.pdf ========================================================== ============================================================== 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_. .. _IEA_PV: https://iea-pvps.org/wp-content/uploads/2020/12/IEA-PVPS-LCI-report-2020.pdf .. _LCI_PV: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-PV.xlsx The methodology follows the IEA-PVPS Task 12 approach to construct country-specific photovoltaic electricity mixes in life cycle assessment by starting from technology- and installation-specific capacity archetypes and translating them into per-kWh inventory coefficients. For each country, photovoltaic capacity is disaggregated by installation type (rooftop, façade, ground-mounted), module technology (e.g. mono-Si, multi-Si, thin-film variants), and mounting/integration option. These capacity shares are combined with country-specific annual electricity yields (kWh/kWp·yr), derived from irradiation-based PV productivity data and corrected according to PVPS Task 12 guidelines, and with a fixed system lifetime (30 years), to convert installed capacity into lifetime electricity output. We further split the installed capacity in each country between residential (<= 3kWp) and commercial (>3 kWp) installations. The resulting lifetime-normalized contributions are then scaled so that their sum delivers exactly 1 kWh of photovoltaic electricity, yielding electricity-weighted shares for each archetype. These shares are implemented in the LCI as exchanges to specific PV system construction activities, producing a country-specific, technology-resolved PV electricity mix that is consistent with observed productivity differences while remaining transparent and extensible to additional countries. The PV installation datasets provided by the report are listed in the table below. ============================================================================================ =========== 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 productivity (in annual kWh produced per kWp) for 33 countries, which are used to build country-specific PV electricity mixes: ======================= =========== ========= ========== 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 ======================= =========== ========= ========== To extend the set of country-specific photovoltaic electricity datasets beyond those originally covered in IEA-PVPS Task 12, we followed a structured, PVPS-consistent extrapolation approach. First, country-specific annual PV electricity yields for a reference, free-standing system were derived from the GlobalSolarAtlas_ by aggregating monthly PVOUT rasters into annual values and computing country averages. These reference yields were then disaggregated into rooftop, façade, and centralized yields using empirical yield ratios inferred from the Task 12 country dataset, thereby preserving the relative productivity differences between installation types. In parallel, national PV deployment structures were approximated by assigning residential, commercial, and centralized capacity shares using available international statistics (where possible) and transparent proxy assumptions otherwise. Within each market segment, capacity was further distributed across PV technology and installation archetypes following the same hierarchical logic as in Task 12. Finally, these capacity shares were converted into per-kWh inventory coefficients using country-specific yields and a fixed system lifetime, and embedded into duplicated LCI templates to generate fully specified, country-resolved photovoltaic electricity datasets. This procedure ensures methodological continuity with the original PVPS datasets while enabling consistent, scalable extension to additional countries. .. _GlobalSolarAtlas: https://globalsolaratlas.info/download/world Finally, we collected electricity generation volumes through photovoltaic installations from the 2025 IRENA_ Renewable Energy Statistics to provide country-specific mix shares when building regional electricity mixes. .. _IRENA: https://www.irena.org/Publications/2025/Jul/Renewable-energy-statistics-2025 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: .. code-block:: 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 ============================================================================================ =========== .. _Pallas: https://doi.org/10.1007/s11367-020-01791-z .. _Roffeis: https://doi.org/10.1039/D2SE90051C .. note:: These two technologies are not included in the current country-specific production mix datasets, as IAM scenarios do not specify sub-technology mixes. 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. .. _Maeder: https://www.psi.ch/sites/default/files/import/ta/PublicationTab/BSc_Mattia_Maeder_2016.pdf 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_. .. _LCIgeothermal: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-geothermal.xlsx 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 -------- Hydrogen production ******************* *premise* imports inventories for hydrogen production. The table below gives an overview of the different pathways and their assumed specific energy use in 2020 and 2050. +-------------------------------------------------------------------------------------------------------------------+-------------+-----+----------+----------+----------+----------+-------+-----+------------------------------------+ | Dataset | Feedstock | U | 2020 avg | 2020 rng | 2050 avg | 2050 rng |Floor |Loc | Literature reference | +===================================================================================================================+=============+=====+==========+==========+==========+==========+=======+=====+====================================+ | hydrogen production, steam methane reforming | natural gas | m^3 | N/A | N/A | N/A | N/A | 3.5 | CH | Antonini_ et al. 2021 [LCI_SMR_] | +-------------------------------------------------------------------------------------------------------------------+-------------+-----+----------+----------+----------+----------+-------+-----+------------------------------------+ | hydrogen production, steam methane reforming, with CCS | natural gas | m^3 | N/A | N/A | N/A | N/A | 3.5 | CH | Antonini_ et al. 2021 [LCI_SMR_] | +-------------------------------------------------------------------------------------------------------------------+-------------+-----+----------+----------+----------+----------+-------+-----+------------------------------------+ | hydrogen production, steam methane reforming, from biomethane | biomethane | kg | N/A | N/A | N/A | N/A | 3.2 | CH | Antonini_ et al. 2021 [LCI_SMR_] | +-------------------------------------------------------------------------------------------------------------------+-------------+-----+----------+----------+----------+----------+-------+-----+------------------------------------+ | hydrogen production, steam methane reforming, from biomethane, with CCS | biomethane | kg | N/A | N/A | N/A | N/A | 3.2 | CH | Antonini_ et al. 2021 [LCI_SMR_] | +-------------------------------------------------------------------------------------------------------------------+-------------+-----+----------+----------+----------+----------+-------+-----+------------------------------------+ | hydrogen production, auto-thermal reforming, from biomethane | biomethane | kg | N/A | N/A | N/A | N/A | 3.2 | CH | Antonini_ et al. 2021 [LCI_ATR_] | +-------------------------------------------------------------------------------------------------------------------+-------------+-----+----------+----------+----------+----------+-------+-----+------------------------------------+ | hydrogen production, auto-thermal reforming, from biomethane, with CCS | biomethane | kg | N/A | N/A | N/A | N/A | 3.2 | CH | Antonini_ et al. 2021 [LCI_ATR_] | +-------------------------------------------------------------------------------------------------------------------+-------------+-----+----------+----------+----------+----------+-------+-----+------------------------------------+ | hydrogen production, gaseous, 25 bar, from heatpipe reformer gasification of woody biomass with CCS | wood chips | kg | N/A | N/A | N/A | N/A | 7.0 | CH | Antonini2_ et al. 2021 [LCI_woody_]| +-------------------------------------------------------------------------------------------------------------------+-------------+-----+----------+----------+----------+----------+-------+-----+------------------------------------+ | hydrogen production, gaseous, 25 bar, from heatpipe reformer gasification of woody biomass | wood chips | kg | N/A | N/A | N/A | N/A | 7.0 | CH | Antonini2_ et al. 2021 [LCI_woody_]| +-------------------------------------------------------------------------------------------------------------------+-------------+-----+----------+----------+----------+----------+-------+-----+------------------------------------+ | hydrogen production, gaseous, 25 bar, from gasification of woody biomass in entrained flow gasifier, with CCS | wood chips | kg | N/A | N/A | N/A | N/A | 7.0 | CH | Antonini2_ et al. 2021 [LCI_woody_]| +-------------------------------------------------------------------------------------------------------------------+-------------+-----+----------+----------+----------+----------+-------+-----+------------------------------------+ | hydrogen production, gaseous, 25 bar, from gasification of woody biomass in entrained flow gasifier | wood chips | kg | N/A | N/A | N/A | N/A | 7.0 | CH | Antonini2_ et al. 2021 [LCI_woody_]| +-------------------------------------------------------------------------------------------------------------------+-------------+-----+----------+----------+----------+----------+-------+-----+------------------------------------+ | hydrogen production, coal gasification | hard coal | kg | N/A | N/A | N/A | N/A | 5.0 |RER | Wokaun_, Li_ [LCI_coal_] | +-------------------------------------------------------------------------------------------------------------------+-------------+-----+----------+----------+----------+----------+-------+-----+------------------------------------+ | hydrogen production, gaseous, 30 bar, from PEM electrolysis, from grid electricity | electricity | kWh | 54.0 |52.9–55.1 | 48.9 |45.3–52.5 | 45.3 |RER | Gerloff_ 2021 [LCI_electrolysis_] | +-------------------------------------------------------------------------------------------------------------------+-------------+-----+----------+----------+----------+----------+-------+-----+------------------------------------+ | hydrogen production, gaseous, 20 bar, from AEC electrolysis, from grid electricity | electricity | kWh | 51.8 |48.7–54.9 | 48.5 |47.1–49.9 | 47.1 |RER | Gerloff_ 2021 [LCI_electrolysis_] | +-------------------------------------------------------------------------------------------------------------------+-------------+-----+----------+----------+----------+----------+-------+-----+------------------------------------+ | hydrogen production, gaseous, 1 bar, from SOEC electrolysis, from grid electricity | electricity | kWh | 42.3 |41.2–43.4 | 40.6 |40.0–41.2 | 40.0 |RER | Gerloff_ 2021 [LCI_electrolysis_] | +-------------------------------------------------------------------------------------------------------------------+-------------+-----+----------+----------+----------+----------+-------+-----+------------------------------------+ | hydrogen production, gaseous, 1 bar, from SOEC electrolysis, with steam input, from grid electricity | electricity | kWh | 42.3* |41.2–43.4 | 40.6 |40.0–41.2 | 40.0 |RER | Gerloff_ 2021 [LCI_electrolysis_] | | (same performance as SOEC, no separate data) | +-------------------------------------------------------------------------------------------------------------------+-------------+-----+----------+----------+----------+----------+-------+-----+------------------------------------+ | hydrogen production, gaseous, 25 bar, from thermochemical water splitting, at solar tower | solar | MJ | N/A | N/A | N/A | N/A | 180 |RER | Zhang2_ 2022 | +-------------------------------------------------------------------------------------------------------------------+-------------+-----+----------+----------+----------+----------+-------+-----+------------------------------------+ | hydrogen production, gaseous, 100 bar, from methane pyrolysis | natural gas | m^3 | N/A | N/A | N/A | N/A | 6.5 |RER | Al-Qahtani_, Postels_ | +-------------------------------------------------------------------------------------------------------------------+-------------+-----+----------+----------+----------+----------+-------+-----+------------------------------------+ Future efficiencies for electrolyzers are based on Studie IndWEDe_ (see p.176). .. _Antonini: https://pubs.rsc.org/en/content/articlelanding/2020/se/d0se00222d .. _Antonini2: https://pubs.rsc.org/en/Content/ArticleLanding/2021/SE/D0SE01637C .. _Wokaun: https://www.cambridge.org/core/books/transition-to-hydrogen/43144AF26ED80E7106B675A6E83B1579 .. _Li: https://doi.org/10.1016/j.jclepro.2022.132514 .. _Gerloff: https://doi.org/10.1016/j.est.2021.102759 .. _Zhang2: https://doi.org/10.1016/j.ijhydene.2022.02.150 .. _Al-Qahtani: https://doi.org/10.1016/j.apenergy.2020.115958 .. _Postels: https://doi.org/10.1016/j.ijhydene.2016.09.167 .. _LCI_SMR: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-hydrogen-smr-atr-natgas.xlsx .. _LCI_ATR: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-hydrogen-smr-atr-natgas.xlsx .. _LCI_woody: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-hydrogen-wood-gasification.xlsx .. _LCI_coal: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-hydrogen-coal-gasification.xlsx .. _LCI_electrolysis: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-hydrogen-electrolysis.xlsx .. _IndWEDe: https://www.now-gmbh.de/wp-content/uploads/2020/09/indwede-studie_v04.1.pdf 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 ================================================================== =========== .. _Wulf: https://www.sciencedirect.com/science/article/pii/S095965261832170X .. _LCI_H2_distr: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-hydrogen-distribution.xlsx .. _Cerniauskas: https://doi.org/10.1016/j.ijhydene.2020.02.121 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_. .. _Ozawa: https://doi.org/10.1016/j.ijhydene.2019.02.230 .. _LCI_H2_turbine: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-hydrogen-turbine.xlsx Steel ----- *premise* imports inventories for a wide range of steel production technologies. These include conventional blast furnace-basic oxygen furnace (BF-BOF) routes, as well as emerging processes such as direct reduction (DRI), hydrogen-based production, electrowinning, and carbon capture (CCS) variants. They are from Harpprecht_ et al. (2025). They can be found here: LCI_steel_. The table below provides an overview of the included datasets, their key input(s), and assumed regional scope. ================================================================================================================== ========== Steel production and related processes location ================================================================================================================== ========== steel production, blast furnace-basic oxygen furnace, low-alloyed GLO steel production, blast furnace-basic oxygen furnace, unalloyed GLO alloys production, for low-alloyed steel GLO pig iron production, blast furnace, with carbon capture and storage GLO carbon dioxide, captured at pig iron production plant, using monoethanolamine GLO steel production, blast furnace-basic oxygen furnace, with carbon capture and storage, low-alloyed GLO steel production, blast furnace-basic oxygen furnace, with carbon capture and storage, unalloyed GLO pig iron production, top gas recycling-blast furnace GLO steel production, blast furnace-basic oxygen furnace, with top gas recycling, low-alloyed GLO steel production, blast furnace-basic oxygen furnace, with top gas recycling, unalloyed GLO pig iron production, blast furnace, with top gas recycling, with carbon capture and storage GLO carbon dioxide, captured at steel production plant, using vacuum pressure swing adsorption GLO steel production, blast furnace-basic oxygen furnace, with top gas recycling, with CCS, low-alloyed GLO steel production, blast furnace-basic oxygen furnace, with top gas recycling, with CCS, unalloyed GLO pig iron production, with natural gas-based direct reduction GLO steel production, natural gas-based direct reduction iron-electric arc furnace, low-alloyed GLO steel production, natural gas-based direct reduction iron-electric arc furnace, unalloyed GLO pig iron production, with natural gas-based direct reduction, with carbon capture and storage GLO carbon dioxide, captured at steel production plant using DRI, using vacuum pressure swing adsorption GLO steel production, natural gas-based DRI-EAF, with CCS, low-alloyed GLO steel production, natural gas-based DRI-EAF, with CCS, unalloyed GLO steel production, hydrogen-based DRI-EAF, low-alloyed GLO steel production, hydrogen-based DRI-EAF, unalloyed GLO pig iron production, hydrogen-based direct reduction iron GLO preheating of iron ore pellets GLO preheating of hydrogen GLO pig iron production, by electrowinning GLO leaching of iron ore GLO market for cathode, graphite GLO nickel anode production, for electrolysis of iron ore GLO production of alkaline solution from sodium hydroxide of 50 wt-% GLO steel production, electrowinning-electric arc furnace, low-alloyed GLO steel production, electrowinning-electric arc furnace, unalloyed GLO ultrafine grinding of iron ore GLO ================================================================================================================== ========== These inventories provide a modular basis for modeling steel systems under various future-oriented scenarios and technological configurations. .. _Harpprecht: https://doi.org/10.1039/D5EE01356A .. _LCI_steel: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-steel.xlsx Cement ------ *premise* introduces inventories for capturing carbon dioxide at cement production plants using three prospective technologies: * Post-combustion capture using monoethanolamine (MEA) * Direct separation * Oxyfuel combustion These inventories represent the gate-to-gate capture of 1 kg of CO₂ and include upstream material and energy inputs as well as transport and storage of the captured CO₂. They are from Muller_ et al. (2024). They can be found here: LCI_cement_. ============================================================================== ========== Carbon capture at cement production plants location ============================================================================== ========== carbon dioxide, captured, at cement production plant, using monoethanolamine RER carbon dioxide, captured, at cement production plant, using direct separation RER carbon dioxide, captured, at cement production plant, using oxyfuel RER ============================================================================== ========== Monoethanolamine (MEA) ********************** Represents conventional post-combustion carbon capture using MEA solvents, based on the CEMCAP study (Voldsund, 2019). The dataset includes heat and electricity demand for regeneration and compression, solvent losses, chemical pretreatment (NaOH), and incineration of spent solvents. Heat is assumed to be provided by the same fuel mix as the cement kiln. Direct separation ***************** Models CO₂ capture via a separate calciner (as in the LEILAC project), allowing for nearly pure CO₂ stream separation without additional chemical solvents. Includes extra electricity consumption for calciner operation and CO₂ compression. Oxyfuel combustion ****************** Simulates complete fuel combustion in a controlled O₂/CO₂ atmosphere. The resulting flue gas has high CO₂ purity, reducing downstream separation needs. Liquid oxygen is supplied via an air separation unit (ASU), and waste heat is recovered to offset some electricity needs. Emissions of SOₓ, NOₓ, CO, and Hg are significantly reduced. All three capture routes include subsequent CO₂ compression, transport, and storage via the carbon dioxide compression, transport and storage dataset from *premise*. .. _Muller: https://doi.org/10.1016/j.jclepro.2024.141884 .. _LCI_cement: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-carbon-capture.xlsx 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. .. _Boyce: https://doi.org/10.1016/j.heliyon.2024.e27547 .. _Angelo: https://doi.org/10.1021/acssuschemeng.1c01915 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. .. _LCI_biofuels: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-biofuels.xlsx .. _Cozzolino: https://www.psi.ch/sites/default/files/2019-09/Cozzolino_377125_%20Research%20Project%20Report.pdf .. _Gonzalez-Garcia: https://doi.org/10.1016/j.scitotenv.2012.07.044 .. _Wu: http://greet.es.anl.gov/publication-2lli584z .. _Pereira: http://task39.sites.olt.ubc.ca/files/2019/04/Task-39-GHS-models-Final-Report-Phase-1.pdf .. _Cavalett: https://doi.org/10.1002/bbb.2395 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. .. _Giesen: https://pubs.acs.org/doi/abs/10.1021/es500191g .. _Hank: https://doi.org/10.1039/C9SE00658C .. _FVV: https://www.fvv-net.de/fileadmin/user_upload/medien/materialien/FVV-Kraftstoffstudie_LBST_2013-10-30.pdf .. _Zhang: https://doi.org/10.1039/C9SE00986H 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_. .. _Qiu: https://doi.org/10.1038/s41467-022-31146-1 .. _LCI_DAC: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-direct-air-capture.xlsx 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. .. _Meunier: https://doi.org/10.1016/j.renene.2019.07.010 .. _Bisinella: https://doi.org/10.1016/j.wasman.2021.04.046 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_. .. _Dai: https://www.mdpi.com/2313-0105/5/2/48 .. _Crenna: https://doi.org/10.1016/j.resconrec.2021.105619 .. _Wickerts: https://doi.org/10.1021/acssuschemeng.3c00141 .. _Wang: https://doi.org/10.1016/j.jclepro.2020.121339 .. _Zhang22: https://doi.org/10.1016/j.resconrec.2023.107362 .. _Schmidt: https://doi.org/10.1021/acs.est.8b05313 .. _Engels: https://doi.org/10.1016/j.jclepro.2022.130474 .. _Surovtseva: https://doi.org/10.1111/jiec.13234 .. _Elgowainy: https://greet.es.anl.gov/publication-update_cobalt .. _Schenker: https://doi.org/10.1016/j.resconrec.2022.106611 .. _LCI_batteries1: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-batteries-NMC111-811-NCA-LFP.xlsx.xlsx .. _LCI_batteries2: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-batteries-NMC622-LTO.xlsx.xlsx .. _LCI_batteries3: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-batteries-LiS.xlsx .. _LCI_batteries4: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-batteries-LiO2.xlsx .. _LCI_batteries5: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-batteries-SIB.xlsx .. _LCI_graphite: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-graphite.xlsx .. _LCI_cobalt: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-cobalt.xlsx .. _LCI_lithium: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-lithium.xlsx 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). .. _Weber: https://doi.org/10.1021/acs.est.8b02073 These inventories can be found here: LCI_vanadium_redox_flow_batteries_. .. _LCI_vanadium_redox_flow_batteries: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-vanadium-redox-flow-battery.xlsx 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_. .. _LCI_vanadium: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-vanadium.xlsx 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_. .. _Sacchi: https://zenodo.org/deposit/5720779 .. _LCItwowheelers: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-two_wheelers.xlsx ================================================= ================== 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: .. code-block:: python update("cars") *premise* will create fleet average vehicles for each IAM region. The inventories can be consulted here: LCIpasscars_. .. _Sacchi2: https://www.psi.ch/en/media/72391/download .. _LCIpasscars: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-pass_cars.xlsx 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: .. code-block:: python update("trucks") *premise* will create fleet average vehicles for each IAM region. The inventories can be consulted here: LCItrucks_. .. _LCItrucks: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-trucks.xlsx .. _Sacchi3: https://pubs.acs.org/doi/abs/10.1021/acs.est.0c07773 Buses ***** The following datasets for city and coach buses are imported. =================================================================================================================== ================== Bus datasets location =================================================================================================================== ================== 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: .. code-block:: python update("buses") *premise* will create fleet average vehicles for each IAM region. The inventories can be consulted here: LCIbuses_. .. _LCIbuses: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-buses.xlsx 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_. .. _migrationmap: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/migration_map.csv 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. .. _mapping: https://github.com/polca/premise/blob/master/premise/iam_variables_mapping/mapping_overview.xlsx 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 model 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. .. _GAINS-IAM: https://gains.iiasa.ac.at/gains/IAM/index.login 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. .. _IEA2: https://iea.blob.core.windows.net/assets/3a99654f-ffff-469f-b83c-bf0386ed8537/pv_roadmap.pdf 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. .. _Fraunhofer: https://www.ise.fraunhofer.de/content/dam/ise/de/documents/publications/studies/Photovoltaics-Report.pdff ====================== =========== ============ =========== ======= ====== ======= % 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 ====================== =========== ============ =========== ======= ====== =======