Industrial Ecology Freiburg

Research group at the Faculty of Environment and Natural Resources

Table contents of Classifications

idclassification_Namedimensiondescriptionreferencemeaning_attribute1meaning_attribute2meaning_attribute3meaning_attribute4meaning_attribute5
1chemical_elements2Chemical elements 1-118 element name (lowercase)atomic numbersymbolelement name (uppercase)atomic weight (rough)
2regions_iso_iedc4ISO 3166 classification of states and regions, with custom extensions. Numbers > 10000 are self-defined. NameISO2ISO3ISO codecontinent
3time1Years 1800-2200 Year    
4generic_materials_waste5List of common materials, products, and waste groups Material    
5NACEv2_(ProdCom)6List of ProdCom commodities Commodity code (NACEv2)Commodity group name   
6broad_industry_groups7List of broad industry groupts (mining, material production, ?) Broad industry group    
7general_product_categories6List of general product categories, residential and non-residential Product category    
8basic_scenario_alternatives9High-medium-low scenarios Scenario alternatives: High/medium/low, etc.    
9ca_time1Years with ca. prefix Ca. year    
10general_energy_carriers8List of general energy carriers Energy carrier    
11cities4List of cities City namealternative city name 1alternative city name 2alternative city name 3Country or region ID
12service_categories11List of services Service type    
13building_types6List of commonly used building types Building type    
14time_ranges1List of time intervals for age cohorts and years Range of years or age-cohorts    
15custom13Custom classification, dimension specified via aspect, placeholder only! None    
16steel_cycle_200R_processes7List of processes for steel cycle MFA DOI 10.1016/j.resconrec.2012.11.008 process_nameprocess_id  process_code
17US_LCI_materials5List of materials (flows) used in US LCI database materials and substances list of US LCI database, incomplete (!)    
18LCI_material_categories5List of material categories used in LCI data broad material category for LCA (product, elementary, waste)    
19US_LCI_material_groups5List of material groups used in US LCI database grouping of flows in US LCI database into categories like 'reference product' or 'air, high population density'    
20LCI_data_layers12List of data layers used in LCI data data layers for LCI data (mass, energy, monetary, ?)    
21US_LCI_processes7List of processes used in US LCI database Process (activity) names from US LCI database    
22UK_IO_17Commodities6List of 17 commodities used for 2010 aggregated UK IO table in pxp format Aggregated industrial sector names of UK IO table    
23steel_cycle_200R_materials_products6materials and products for stocks and flows in dataset for global steel cycle material name    
24global_steel_cycle_Regions4regions used in global steel cycle project region name    
25EXIOBASEv3_163industries7List of industries for EXIOBASE3, official order and labellingDOI: 10.1111/jiec.12715Code_numberCode_textName  
26EXIOBASEv3_163Products6List of products for EXIOBASE3, official order and labelling, 163 products (1:1 correspondence to industry resolution)DOI: 10.1111/jiec.12715Code_numberCode_textName  
27EXIOBASEv3_200Products6List of products for EXIOBASE3, official order and labelling, 200 products (full resolution)DOI: 10.1111/jiec.12715Code_numberCode_textName  
28Economic_indicators10List of common economic indicators Indicator name    
29SSP_Models9List of models used in SSP processDOI: 10.1016/j.gloenvcha.2016.05.009model_name    
30SSP_32Regions4List of 32 SSP regionsDOI: 10.1016/j.gloenvcha.2016.05.009region_code    
31Population_classes9List of different population classes: urban, total, … class_name    
32EXIOBASEv2_48Regions4List of regions for EXIOBASE2, official order and labellingDOI: 10.1111/jiec.12715country_namecode_2lettercode_3letter  
33NUTS_Regions_2010_Version4List of regions at NUTS levels 1, 2, and 3, 2010 version of NUTShttps://ec.europa.eu/eurostat/ramon/nomenclatures/index.cfm?TargetUrl=LST_CLS_DLD&StrNom=NUTS_33&StrLanguageCode=ENNUTS_region_code   NUTS_region_name
3434_EXIOBASEv3_49Regions4List of regions for EXIOBASE3, official order and labellingDOI: 10.1111/jiec.12715country_namecode_2lettercode_3letter  
35NUTS_Regions_2006_Version4List of regions at NUTS levels 1, 2, and 3, 2006 version of NUTShttp://database.espon.eu/db2/jsf/DicoSpatialUnits/DicoSpatialUnits_html/ch01s01.htmlNUTS_region_code   NUTS_region_name1
36Literature13List of literature sources and their descriptionNoneliterature_idliterature_key  authors
37YSTAFDB_criticality_regional_scope4regional scopes of YSTAFDB (Yale stocks and flow database) criticality indicatorsNoneregional scope    
38YSTAFDB_materials5materials list of the YSTAFDB (Yale stocks and flow database)Nonematerial_shortnamematerial_namematerial_id atomic_weight
39YSTAFDB_criticality_timeframe1time frames of YSTAFDB (Yale stocks and flow database) criticality indicatorsNonetime frame    
40YSTAFDB_criticality_indicators12YSTAFDB (Yale stocks and flow database) criticality indicatorsNonecriticality_indicator_namecriticality_indicator_symbol   
41YSTAFDB_material_groups5YSTAFDB (Yale stocks and flow database) material groups, for sector split and recycling sharesNonematerial_group_application    
42YSTAFDB_use_phase_layer12YSTAFDB (Yale stocks and flow database) sector splits and recyclability_layers, described as 'recycling_use_type' in the original YSTAFDBNoneuse_phase_and_recyclability_layer    
43YSTAFDB_UsePhase_Applications7YSTAFDB (Yale stocks and flow database) use phase applicationsNoneuse_phase_applications    
44YSTAFDB_Time1YSTAFDB (Yale stocks and flow database) time intervals and yearsNonetime    
45YSTAFDB_Region4YSTAFDB (Yale stocks and flow database) regions (countries, regions, cities)Noneregion    
46YSTAFDB_Commodities6YSTAFDB (Yale stocks and flow database) commodities/product groupsNonecommodity    
47YSTAFDB_Processes7YSTAFDB (Yale stocks and flow database) processesNoneprocess, consisting of [aggregate_subsystem_module];[subsystem_name];[process_name]    
48StockChangeLayers12stock change layers like 'net addition, 'withdrawal', 'deposition'Nonestock change layers like 'net addition, 'withdrawal', 'deposition'    
49Wood_MFA_Indonesia_Aryapratama_2019_processes7processes used in MFA study on wood in Indonesia, by Rio AryapratamaNoneprocess name    
10000origin_process__1_F_steel_SankeyFlows_2008_Global7Custom classification, generated by IEDC_tools v0.4.0 'aspect_1' aspect of dataset    
10001destination_process__1_F_steel_SankeyFlows_2008_Global7Custom classification, generated by IEDC_tools v0.4.0 'aspect_2' aspect of dataset    
10002commodity__1_F_steel_SankeyFlows_2008_Global6Custom classification, generated by IEDC_tools v0.4.0 'aspect_3' aspect of dataset    
10003commodity__3_LT_AluCycle_LIU_20126Custom classification, generated by IEDC_tools v0.4.0 'aspect_1' aspect of dataset    
10004scenario__3_LT_AluCycle_LIU_20129Custom classification, generated by IEDC_tools v0.4.0 'aspect_4' aspect of dataset    
10005commodity__3_LT_AluCycle_LIU_20136Custom classification, generated by IEDC_tools v0.4.0 'aspect_1' aspect of dataset    
10006region__3_LT_AluCycle_LIU_20134Custom classification, generated by IEDC_tools v0.4.0 'aspect_3' aspect of dataset    
10007commodity__3_LT_IAI_GARC_20116Custom classification, generated by IEDC_tools v0.4.0 'aspect_1' aspect of dataset    
10008commodity__3_LT_MetalDemand_DEETMAN_20186Custom classification, generated by IEDC_tools v0.4.0 'aspect_1' aspect of dataset    
10009age-cohort__3_MC_Buildings_Sinha_20161Custom classification, generated by IEDC_tools v0.4.0 'aspect_4' aspect of dataset    
10010commodity__3_MC_MetalDemand_DEETMAN_20186Custom classification, generated by IEDC_tools v0.4.0 'aspect_1' aspect of dataset    
10011commodity__3_SHA_EndUseShares_56Metals_Ciacci_20156Custom classification, generated by IEDC_tools v0.4.0 'aspect_2' aspect of dataset    
10012process__3_SHA_FabricationYield_CollectionRate_Alu_Liu_20127Custom classification, generated by IEDC_tools v0.4.0 'aspect_3' aspect of dataset    
10013process__4_PE_EnergyIntensity_AluminiumCycle_Liu_20127Custom classification, generated by IEDC_tools v0.4.0 'aspect_2' aspect of dataset    
10014time__4_PE_EnergyIntensity_AluminiumCycle_Liu_20121Custom classification, generated by IEDC_tools v0.4.0 'aspect_3' aspect of dataset    
10015commodity__4_PY_FabricationYield_Alu_Liu_20126Custom classification, generated by IEDC_tools v0.4.0 'aspect_3' aspect of dataset    
10016commodity__4_PY_FabricationYield_Cullen20126Custom classification, generated by IEDC_tools v0.4.0 'aspect_3' aspect of dataset    
10017commodity__4_PY_FabricationYield_Dahlstroem20046Custom classification, generated by IEDC_tools v0.4.0 'aspect_3' aspect of dataset    
10018commodity__4_PY_FabricationYield_Hatayama20106Custom classification, generated by IEDC_tools v0.4.0 'aspect_3' aspect of dataset    
10019input_commodity__4_PY_WorldSteel_EoL_RR_SteelScrap6Custom classification, generated by IEDC_tools v0.4.0 'aspect_4' aspect of dataset    
10020time__5_CAP_PowerGenCapacity_Germany_20181Custom classification, generated by IEDC_tools v0.4.0 'aspect_2' aspect of dataset    
10021age-cohort__5_CAP_PowerGenCapacity_Germany_20181Custom classification, generated by IEDC_tools v0.4.0 'aspect_3' aspect of dataset    
10022commodity__5_CAP_PowerGenCapacity_Germany_20186Custom classification, generated by IEDC_tools v0.4.0 'aspect_4' aspect of dataset    
10023region__5_CAP_PowerGenCapacity_Germany_20184Custom classification, generated by IEDC_tools v0.4.0 'aspect_5' aspect of dataset    
10024technology__5_CAP_PowerGenCapacity_Germany_20186Custom classification, generated by IEDC_tools v0.4.0 'aspect_6' aspect of dataset    
10025product_type__6_PCS_Buildings_Indonesia_19856Custom classification, generated by IEDC_tools v0.4.0 'aspect_4' aspect of dataset    
10026input_commodity__1_F_IOT_UK_2010_pxp_v6Custom classification, generated by IEDC_tools v0.4.0 'aspect_3' aspect of dataset    
10027process__1_F_IOT_UK_2010_pxp_x7Custom classification, generated by IEDC_tools v0.4.0 'aspect_4' aspect of dataset    
10028process__1_F_IOT_UK_2010_pxp_Y7Custom classification, generated by IEDC_tools v0.4.0 'aspect_4' aspect of dataset    
10029commodity__1_F_MetalDemand_DEETMAN_20186Custom classification, generated by IEDC_tools v0.4.0 'aspect_6' aspect of dataset    
10030origin_process__1_F_Waste_EXIOBASE2_Global_aggregated7Custom classification, generated by IEDC_tools v0.4.0 'aspect_1' aspect of dataset    
10031destination_process__1_F_Waste_EXIOBASE2_Global_aggregated7Custom classification, generated by IEDC_tools v0.4.0 'aspect_2' aspect of dataset    
10032engineering_material__1_F_Waste_EXIOBASE2_Global_aggregated5Custom classification, generated by IEDC_tools v0.4.0 'aspect_3' aspect of dataset    
10033region__1_F_Waste_EXIOBASE2_Global_aggregated4Custom classification, generated by IEDC_tools v0.4.0 'aspect_4' aspect of dataset    
10034commodity__1_F_WIO_Japan_Nakamura_Kondo_20026Custom classification, generated by IEDC_tools v0.4.0 'aspect_1' aspect of dataset    
10035origin_process__1_F_WIO_Japan_Nakamura_Kondo_20027Custom classification, generated by IEDC_tools v0.4.0 'aspect_2' aspect of dataset    
10036destination_process__1_F_WIO_Japan_Nakamura_Kondo_20027Custom classification, generated by IEDC_tools v0.4.0 'aspect_6' aspect of dataset    
10037commodity__3_LT_MaTraceGlobal_Pauliuk_20176Custom classification, generated by IEDC_tools v0.4.0 'aspect_1' aspect of dataset    
10038region__3_LT_MaTraceGlobal_Pauliuk_20174Custom classification, generated by IEDC_tools v0.4.0 'aspect_3' aspect of dataset    
10039input_commodity__4_PY_IAI_EoL_RR_AluScrap6Custom classification, generated by IEDC_tools v0.4.0 'aspect_4' aspect of dataset    
10040age-cohort__3_MC_Buildings_Heeren_Fishman_ScientificData_2019_V1.11Custom classification, generated by IEDC_tools v0.4.1 'aspect_3' aspect of dataset    
10041impact_indicator__6_IMI_EU_Regional_Carbon_Footprint_Ivanova_201710Custom classification, generated by IEDC_tools v0.4.1 'aspect_1' aspect of dataset    
10042impact_indicator__6_IMI_Global_Household_EnvFootprints_Ivanova_201610Custom classification, generated by IEDC_tools v0.4.1 'aspect_1' aspect of dataset    
10043scenario__2_IUS_Wood_Carbon_MFA_Indonesia_Aryapratama_20199Custom classification, generated by IEDC_tools v0.4.2 'aspect_4' aspect of dataset    
10083city__6_URB_MetabolismOfCities_Jan2019_DOI_7326485.v14Custom classification, generated by IEDC_tools v0.4.2 'aspect_1' aspect of dataset    
10084layer__6_URB_MetabolismOfCities_Jan2019_DOI_7326485.v112Custom classification, generated by IEDC_tools v0.4.2 'aspect_2' aspect of dataset    
10085impact_indicator__6_URB_MetabolismOfCities_Jan2019_DOI_7326485.v110Custom classification, generated by IEDC_tools v0.4.2 'aspect_3' aspect of dataset    





Table contents of Selected Classification Item