GaBi Databases & Modeling Principles 2021
GaBi Databases &Modelling Principles2020February 2021
Authors:Dr. Thilo Kupfer, Dr. Martin Baitz, Dr. Cecilia Makishi Colodel, Morten Kokborg, Steffen Schöll,Matthias Rudolf, Dr. Ulrike Bos, Fabian Bosch, Maria Gonzalez, Dr. Oliver Schuller, JasminHengstler, Alexander Stoffregen, Daniel Thylmann, Dr. Chris KofflerWith contributions of the Sphera expert teams:Energy, Transport, Metals, Chemistry, Construction, Renewables, Electronics, End-of-Life,Plastics, Coating and textiles, Water.www.sphera.comwww.gabi-software.comFor more information contact us at:https://sphera.com/contact-us 2021 Sphera. All Rights Reserved.II
List of ContentsList of Contents . IIIList of Figures . VIList of Tables . VIIIAbbreviations . IX1Introduction and Aim of Document . 12GaBi Database Framework . 32.1GaBi Database concept and management . 32.2GaBi Database development, maintenance and update . 62.3Structure of the Master Database contents . 82.4Standardisation, conformanceconformance and application of LCI databases. 152.5Databases in reference networks, standards and principles . 162.6GaBi LCI Teams . 183Methodological Framework . 203.1Definition of tasks in database work . 203.2Goal . 213.3Scope . 213.3.1Function and Functional Unit . 223.3.2Definition of terms within system boundaries . 223.3.3System boundaries for the creation of standard LCI cradle to gate datasets . 243.3.4Cut-offs . 313.3.5Gap closing . 333.3.6Infrastructure . 333.3.7Transportation . 363.3.8Water . 373.3.9Wastes and recovered material or energy . 443.3.10Radioactive waste and stockpile goods . 453.3.11Selected aspects of biomass modelling . 473.3.12Aspects of primary energy of fossil and renewable energy sources . 563.3.13Land Use using the LANCA method . 573.3.14Land Use Change (LUC) . 593.4Sources and types of data . 643.4.1Primary and secondary sources of data . 643.4.2Unit process and aggregated data . 663.4.3Units . 69III
3.4.4LCI data and supported LCIA methods . 703.4.5Production and consumption mix. 713.5Data quality approach . 733.5.1Decision context . 743.5.2Data Quality Indicators (DQIs) . 753.5.3Reproducibility, Transparency, Data aggregation . 894System Modelling Features . 924.1Data collection . 924.1.1Quality check and validation of collected data . 934.1.2Treatment of missing data . 934.1.3Transfer of data and nomenclature. 944.2Geographical aspects of modelling . 964.3Parameter . 974.4Multifunctionality and allocation principle . 974.5Generic Modules as background building block . 994.6Special modelling features for specific areas . 994.6.1Energy . 1004.6.2Transport . 1064.6.3Mining, metals and metallurgy . 1144.6.4Chemistry and plastics . 1164.6.5Construction . 1214.6.6Renewables . 1414.6.7Electronics . 1414.6.8Recycling and other End-of-Life treatments . 1455Review, documentation and validation . 1535.1Review procedures and check routines . 1535.1.1Technical information and documentation routines in GaBi . 1545.1.2Important material and energy balances . 1545.1.3Plausibility of emission profiles and avoiding errors . 1555.2Documentation . 1565.2.1Nomenclature . 1565.2.2Documentation of Flows. 1575.2.3Documentation of LCI process data . 1585.3Validation . 1606Literature . 1627Appendix A Description of result and impact categories . 169IV
7.1Primary energy consumption . 1737.2Waste categories . 1747.3Climate Change – Global Warming Potential (GWP) and Global Temperature Potential(GTP). 1747.4Acidification Potential (AP) . 1807.5Eutrophication Potential (EP) . 1837.6Photochemical Ozone Creation Potential (POCP) . 1867.7Ozone Depletion Potential (ODP) . 1887.8Human and eco-toxicity . 1917.9Resource depletion . 1957.10Land Use. 1987.11Water use. 1997.12Particulate matter formation (PM) . 2027.13Odour potential. 2027.14Normalization . 2037.15Weighting . 2038Appendix B List of active methods and impact categories . 2069Appendix C Background information on uncertainty . 214V
List of FiguresFigure 2-1:GaBi Database concept embedded in a three-pillar approach3Figure 2-2:Database Management at Sphera6Figure 2-3:Hierarchical structure of the processes and plans8Figure 2-4:Aggregated dataset in GaBi, illustrative example9Figure 2-5:Polymerisation subsystem in GaBi Master DB10Figure 2-6:Tetrafluoroethylene subsystem in GaBi Master DB10Figure 2-7:R22 subsystem in GaBi Master DB11Figure 2-8:Chlorine production mix in GaBi Master DB11Figure 2-9:Chlorine membrane technology production in GaBi Master DB12Figure 2-10:Refinery model in GaBi Master DB12Figure 2-11:Crude oil import mix and country specific oil extraction in GaBi Master DB13Figure 2-12:Example of a country-specific grid mix model in the GaBi Master DB14Figure 2-13:German natural gas consumption mix in GaBi MasterDB14Figure 2-14:German natural gas production in GaBi MasterDB15Figure 2-15:GaBi DB in the international context of databases and frameworks17Figure 2-17:Turning standards into technology solutions17Figure 2-18:GaBi LCI industry sector Expert Teams and the core GaBi Data “Content” team19Figure 2-19:Overview of relevant data sources consistently covered in GaBi Databases19Figure 3-1:Graphic representation of different (sub-) system boundaries23Figure 3-2:Generic example product system of a dataset development standard [ISO 14040:2006],24Figure 3-3:Application of water flows in open-loop and closed-loop cooling systems41Figure 3-4:Application of water flows in in electricity generation42Figure 3-5:Application water flows in hydropower generation43Figure 3-6:Ad hoc example of a simple plan system including different processes and water flows43Figure 3-7:CO2 removals48Figure 3-8:Exemplary flow properties50Figure 3-9:Basic concept of the carbon correction in GaBi50Figure 3-10:Carbon correction formula51Figure 3-12:Balance view for carbon correction I52Figure 3-13:Balance view for carbon correction II53Figure 3-14:CO2 correction process - parameters53Figure 3-15:Example of different biotic carbon flows in GaBi62Figure 3-16:Example of methane biotic emissions to air62Figure 3-17:Example of LUC emissions occurring with additional LUC flows63VI
Figure 3-18:Example of LUC emissions occurring without an additional LUC flow as fossil CO 2 64Figure 3-19:Difference between “production mix” and “consumption mix” (for power generation)72Figure 3-20:Overall data quality according to ILCD assessment scheme [ILCD 2011]. This followspartly a more robust “wealkest link in the chain” logic, that the poorest data aspectdowngrades the overall quality (as it has a higher weight assigned).87Figure 3-21:Overall data quality according to EF assessment scheme [PEF guide 2013]87Figure 3-22:Overview of the six GaBi DQIs and the criteria for the assessment of datasets88Figure 3-23:Screenshot of a dependent internal review including the DQIs89Figure 3-24:Principle graphical explanation of the relation of completeness, precision90Figure 4-1:Hierarchical structure of the processes and plans96Figure 4-2:Conventional natural gas production in Germany101Figure 4-3:Natural gas supply for Germany101Figure 4-4:US, East electricity grid mix103Figure 4-5:Parameterized US Coal gas CHP power plant104Figure 4-6:Principle known functions of tropospheric ozone creation and reduction110Figure 4-7:Excerpt of the organic network1F considered in GaBi117Figure 4-8:Consumption mix of Epoxy resin in Germany119Figure 4-9:Example of PVC resin – compound- part121Figure 4-10:Schematic life cycle of a building122Figure 4-11:Life cycle stage modules according to EN 15804 A2 (2019)124Figure 4-12:Creation of a model for an electronic product – modular structure via Generic Modules143Figure 4-13:Exemplary incineration model with in GaBi (here average European domestic wastetreatment with dry off-gas cleaning)147Figure 4-14:Details of incineration and dry off-gas cleaning in GaBi incineration model148Figure 4-15:Exemplary landfill model in GaBi (here commercial waste composition for certaingeographic example regions)Figure 4-16:Figure 5-1 :149Exemplary wastewater treatment model in GaBi (here municipal wastewater forGerman setting)151Example documentation in GaBi (excerpt) [GABI]159VII
List of TablesTable A:Background system boundariesTable B:Relevance of infrastructure for a natural gas power plant in the GaBi Master DB 35Table C:Publicly available example value for a medium size gas power plant35Table D:Publicly available example values for CO2 for a gas power plant36Table E:Changes in water flows in GaBi (regionalisation of flows is not depicted in this table)39Table F:Definitions of the radioactive waste flows in GaBi45Table G:Definitions of the Stockpile goods elementary flows in GaBi46Table H:Default treatment procedures for common materials/wastes47Table I:General procedure for some hazardous waste flows47Table J:Overview of qualitative importance of “quality indicators” in GaBi DBs73Table K:Coefficients of variation, from a case study84Table L:LCIA GWP methods with primary sources169Table M:EF 2.0: set of recommended impact methods171Table N:EF 3.0: set of recommended impact methods172Table O:Net and gross calorific value174Table P:Global warming incl. and excl. biogenic carbon, land use and aviation176Table Q:Normalization references203Table R:thinkstep Weighting 2012204Table S:Weighting factors including and excluding toxicity205Table TImpact categories and methods206Table U:Chemical substance GaBi datasets that were analyzed for result variability across24various countriesTable V:215Chemical substance GaBi datasets that were analyzed for the result variation acrossvarious technology routes217VIII
AbbreviationsAPAcidification PotentialADPAbiotic Depletion tomerCHPCombined Heat and Power PlantDeNOxNOx emission reductionDeSOxSOx emission reductionDBDatabaseDQIsData Quality IndicatorsEFEnvironmental FootprintELCDEuropean Reference Life Cycle DatabaseEoLEnd-of-LifeEPEutrophication PotentialFAETPFreshwater Aquatic Ecotoxicity PotentialGWPGlobal Warming PotentialHTPHuman Toxicity PotentialIPCCInternational Panel on Climate ChangeILCDInternational Reference Life Cycle Data SystemKEACumulated Energy Approach (German: Kumulierter Energieaufwand)LCALife Cycle AssessmentLCILife Cycle InventoryLCIALife Cycle Impact AssessmentLUCLand Use ChangeMAETPMarine Aquatic Ecotoxicity PotentialMSWMunicipal Solid WasteNDANon-Disclosure AgreementODPOzone Depletion PotentialOEFOrganisation Environmental FootprintPEFProduct Environmental FootprintPOCPPhotochemical Ozone Creation PotentialSCRSelective catalytic reduction (DeNOx type)SNCRSelective non-catalytic reduction (DeNOx type)TETPTerrestric Ecotoxicity PotentialWtEWaste-to-EnergyIX
1Introduction and Aim of DocumentRelevance, quality, consistency and continuity are the main aims of the GaBi Databases. TheGaBi Databases are the result of over 500 person years of direct data collection and analysisand over 2,000 person years of accumulated project work by the Sphera domain experts. Forthe past 30 years, Sphera has constantly developed and advanced the GaBi Databases to bettermeet tomorrow’s data needs today.The goal of the GaBi Database & Modelling Principles document is to transparently documentthe boundary conditions, background, important aspects and details of the GaBi Life CycleInventory databases, as well as the basis of the models. This is intended to help data users tobetter understand the background and to better use the datasets in their own models. At theend of the document, you will find a brief description of the Life Cycle Impact Assessment (LCIA)methods included in the GaBi Databases. This document covers all GaBi Databases, whichinclude the core GaBi Professional Database, the numerous GaBi Extension Databases, andGaBi Data-on-Demand datasets.This document neither aims to answer every possible question nor to document every possibleaspect, but to describe the most important principles that have been applied.The GaBi Databases Modelling Principles aim to mirror our existing global, regional and localeconomy and industry supply chains. They reflect major international standards and relevantprofessional initiatives. While the GaBi Databases Modelling Principles are not used to test newmethods, they are open for improvement as new methods or aspects have been sufficientlytested and proven to mirror the existing supply chains in an even more realistic way.The GaBi Databases are an important source of background LCI data sources for multiplestakeholder groups: industry, academia and education, policy and regulation, research anddevelopment, and consultancy. Any of these stakeholders aiming for accurate and reliable resultneeds accurate and reliable data—without data, there is no result. Without quality data, there isa higher risk of inaccurate or misleading results. Note that scientific and educational goals areoften different from those in policy making, development and industry. Expansion of knowledgemay be the focus of one group, policy development the focus of another group, and innovationand critical decision making the focus of a third group. These different interests require differentinterpretations of the same underlying data of our common supply chains.This underpins the GaBi Databases’ overarching aim, namely, to represent the technical realityof our dynamic and innovative economies as adequately as possible at the given point in time.Achieving this goal and maintaining a high data quality requires technological, temporal, andgeographical representativeness, professional data generation, and continuous databasemaintenance and governance, which are all important aspects of the daily work of Sphera’s GaBiData and Sector Expert Teams.1
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GaBi Databases are the result of over 500 person years of direct data collection and analysis and over 2,000 person years of accumulated project work by the Sphera domain experts. For the past 30 years, Sphera has constantly developed and advanced the GaBi Databases to better meet tomorrow’s data needs today.
14 databases History 183 databases ProQuest Primary Sources available for: Introduction ProQuest Historical Primary Sources Support Research, Teaching and Learning. Faculty and students are using a variety of resources in research, teaching and learning – including primary sources,
Control Techniques, Database Recovery Techniques, Object and Object-Relational Databases; Database Security and Authorization. Enhanced Data Models: Temporal Database Concepts, Multimedia Databases, Deductive Databases, XML and Internet Databases; Mobile Databases, Geographic Information Systems, Genome Data Management, Distributed Databases .
ISO 14046, WULCA, WFN Terminology Water Scarcity Footprint Webinar 2 - Water Assessment in the GaBi LCA software (today) Inventory –Regionalized Flows Impact Assessment Example Limitations. 24.02.2017 3 Inventory. Input flows –water use 24.
EPD Software Tool . LCA Software & Version Number GaBi ts 8.5.079 LCI Database & Version Number GaBi ts 8.5.0.79 . . assessment‐based methods to track and report. Unreported environmental impacts include (but are not limited to) factors attributable to human health, land use change and habitat
Due to the interlinkages within refinery, all refinery products and all processes within the refinery a must be considered when analyzing the environmental performance of refinery products. The "GaBi LCA Refinery Model" is a generic, parameterized LCA model which describes the con-version of crude oil into finished refinery products.
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14 D Unit 5.1 Geometric Relationships - Forms and Shapes 15 C Unit 6.4 Modeling - Mathematical 16 B Unit 6.5 Modeling - Computer 17 A Unit 6.1 Modeling - Conceptual 18 D Unit 6.5 Modeling - Computer 19 C Unit 6.5 Modeling - Computer 20 B Unit 6.1 Modeling - Conceptual 21 D Unit 6.3 Modeling - Physical 22 A Unit 6.5 Modeling - Computer
and each PWM controls two output channels. The TPS92638-Q1 also offers complete system protection features such as LED open, LED short, current foldback, and thermal shutdown, which greatly improve reliability and further simplify the design. 4 Automotive, High-Side, Dimming Rear Light Reference Design TIDUB07–November 2015 Submit .
