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Process Data set: transport, freight, lorry >32 metric ton, EURO1 (en) en

Key Data Set Information
Location BR
Geographical representativeness description Recontextualization from 'transport, freight, lorry >32 metric ton, EURO1, ZA'. Fuel type, freight load factor, regulated and fuel-dependent emissions were updated for the Brazilian situation. The environmental interventions due to vehicle transport are modelled by linking the environmental interventions due to vehicle operation with impacts due to vehicle manufacturing, vehicle maintenance, vehicle disposal, road construction, operation and maintenance of roads and road disposal.
Reference year 2020
Name
transport, freight, lorry >32 metric ton, EURO1
Technical purpose of product or process Diesel and diesel engine. Lorry transport is further differentiated with respect to vehicle weight and emission technology standard (EURO-standard). Technology classifications are based on those used widely within the works of the European Environment Agency, particularly in the Emissions Inventory Guidebook.
Classification
Class name : Hierarchy level
  • ISIC rev.4 ecoinvent: H.Transportation and storage / 49:Land transport and transport via pipelines / 492:Other land transport / 4923:Freight transport by road
General comment on data set Type of process: ordinary transforming activity; Parent relation Ecospold2: none; Tags: ; Macroeconomic Scenario: Business-as-Usual; This dataset is an adaptation of “transport, freight, lorry >32 metric ton, EURO1” in South Africa, as available in version 3.6 of the ecoinvent database to reflect the situation in Brazil. It represents the service of 1tkm freight transport in a lorry of the size class >32 metric tons gross vehicle weight (GVW) and Euro 1 emissions class. The Brazilian lorry fleet is regulated under the Vehicles Air Pollution Control Program – Proconve, which phases are equivalent to the European control program – EURO. Since 2012, the Proconve P7 (EURO 5) phase is in practice, while the P8 phase (EURO 6) will start in 2023. Before that, the Proconve P6 phase (EURO 4) was not implemented because of the unavailability of low-sulphur diesel, therefore recontextualized datasets do not consider this phase. The P5 (EURO 3), P4 (EURO 2) and P3 (EURO 1) phases started in 2005, 2000 and 1996, respectively. Prior technologies are classified as unregulated. For the dataset recontextualization to the Brazilian reality, an updated average freight load and the diesel with 500 ppm of sulfur and 12% biodiesel blend are considered. Moreover, data from emission tests of the national vehicle production and import (CETESB, 2019) is used to update regulated emissions (carbon monoxide, particulate matter and nitrogen oxides). Furthermore, correction factors are used to consider the impact of biodiesel blend on exhaust emissions (USEPA 2002), and the fuel composition is considered to account for carbon dioxide and sulphur dioxide emission. The vehicle mass category classification considered in Brazilian national statistics is approximated to the one adopted in ecoinvent datasets. The larger than 32 metric ton lorry is representing the Brazilian heavy-duty lorry with gross vehicle weight (GVW) larger than 15 metric tons and combined gross vehicle weight (CGVW) larger than 40-ton category classification. For the Brazilian classification, CGVW refers to the total weight of the combinations of vehicles, i.e. trailers. The average capacity utilization factor (including empty trips) for this category is 65.2 % according to the Road Freight Transport Model from the Brazilian Energy Research Enterprise – EPE (Stukart, 2018). Whereas, the average payload capacity for this category is 27.2 ton (Novo, 2016), resulting in an average freight load of 17.7 ton. GWV is estimated by assuming the same empty vehicle weight as for the RER region for the respective matching categories and accounting for the updated freight load. This resulted in a GWV of 35 ton. Vehicle mass dependent non-exhaust emissions (i.e. tyre, brake and road wear) are adjusted accordingly. The emissions of carbon monoxide (CO), nitrogen oxides (NOx) and Particulate Matter (PM) were updated with data from (CETESB, 2019), which uses data from emission testing of the national vehicle fleet production and imports, weighted by sales amounts. Those tests are run with a reference fuel, which is not blended with biodiesel (ANP, 2018), therefore, those emission factors are adjusted for emissions from burning biodiesel. The impact of the 12% biodiesel blend in exhaust emissions is accounted for by correction factors derived from USEPA (2002). Correction factors were calculated for the emissions of nitrogen oxides, particulate matter, hydrocarbons, carbon monoxide, acetaldehyde, ethylbenzene, formaldehyde, naphthalene and xylene. Moreover, fuel consumption was corrected with energy content values. For conventional diesel, it was considered energy content of 129.500 Btu/gal, animal-based biodiesel 115.720 Btu/gal and plant-based biodiesel 119.216 Btu/gal (USEPA 2002). Fuel dependent emissions were updated as well. In Brazil, diesel containing 10 ppm (S10) of sulphur was introduced to attend to the demand of EURO V lorries, as its post-treatment technologies require the use of ultra-low sulphur diesel. Diesel containing 500 ppm (S500) of sulphur is also commercialized for the remaining lorry emission categories. For these cases, the use of S500 is assumed as no information on the share of S500 and S10 diesel used by these categories was available and because the price of S500 is lower than for the S10 (CNT, 2021). Therefore, sulphur dioxide emissions derived from S500 combustion were corrected assuming that all sulphur is emitted as SO2 (0.001 kg SO2/kg fossil diesel) and to account for the blend of biodiesel (12 %), which does not contain sulphur. Carbon dioxide emission is dependent on the fuel carbon content, which was considered as 77.8% for plant-based biodiesel and 76.1 % for animal-based biodiesel, resulting in a Brazilian average of 77.5%, while conventional diesel has 86.7% of carbon (USEPA, 2002). This results in emissions of 3.18 kg of fossil CO2/kg diesel and 2.84 biogenic CO2/kg biodiesel. This dataset was developed under the Cornerstone project, an initiative from the Brazilian Business Network on Life cycle Assessment (Rede ACV) in collaboration with ecoinvent to increase the quantity and quality of inventories that represent Brazil, through a thorough adaptation of the datasets. More information about this project is available in redeacv.org.br/en/wg-database/. Technical background is provided in Valebona F.; Rocha T.B.; Motta F. L. Cornerstone Project. Recontextualization of Datasets: Methodology. ACV Brasil, Brazil. Main data sources for the recontextualization: ANP, 2018. Agência Nacional do Petróleo, Gás Natural e Biocombustíveis (2018). RANP 764. RESOLUÇÃO ANP Nº 764, DE 20.12.2018 - DOU 21.12.2018. EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil. Stukart, B., Lima, C., Pacheco, C., Silva, F., Antoniasse, G., Cavalcanti, M., Souza, M., Stelling, P. (2018). Transporte Rodoviário Brasileiro, Transição para Óleo Diesel S10 e Desafios para o Refino Nacional. Rio Oil&Gas. Available at: https://stt.ibp.org.br/eventos/2018/riooil2018/pdfs/Riooil2018_1654_201806222325ibp1654_1 8_transic.pdf. Acessed in: 06/06/2020. CETESB (2019). Companhia Ambiental do Estado de São Paulo (2019). Emissões Veiculares no Estado de São Paulo. Governo do Estado de São Paulo. Available at: https://cetesb.sp.gov.br/veicular/relatoriose-publicacoes/. Accessed in 15/06/2020. USEPA, 2002. United States Environmental Protection Agency (2002). A Comprehensive Analysis of Biodiesel Impacts on Exhaust Emissions. Draft Technical Report. Novo, A. L. (2016). PERSPECTIVAS PARA O CONSUMO DE COMBUSTÍVEL NO TRANSPORTE DE CARGA NO BRASIL: UMA COMPARAÇÃO ENTRE OS EFEITOS ESTRUTURA E INTENSIDADE NO USO FINAL DE ENERGIA DO SETOR. Available at: http://www.ppe.ufrj.br/images/publica%C3%A7%C3%B5es/mestrado/Ana_Luiza_Andrade_Novo.pdf CNT (2021). CNT acompanha, com atenção, a alta histórica do diesel. Available at: cnt.org.br/agencia-cnt/cnt-acompanha-alta-historica-do-diesel Comment for [variable] transport_RP_PV: Production volume retrieved from the Brazilian National Logistic Plan -2025 (EPL, 2018), which reports the amount of 1,548 billion tonne.km of freight transported by lorries in 2015. The split among lorry size categories has been calculated according to fleet sizes, annual mileages and freight loads. The average annual mileage accounts for the annual mileage decay according to the fleet age of each size class (CETESB, 2019). Furthermore, the shares of emission regulation classes are estimated according to their respective fleet size reported for the state of São Paulo in 2018 (CETESB, 2019). References: CETESB (2019). Companhia Ambiental do Estado de São Paulo (2019). Emissões Veiculares no Estado de São Paulo. Governo do Estado de São Paulo. Available at: cetesb.sp.gov.br/veicular/relatoriose-publicacoes/. [Accessed on 15/06/2020] EPL (2018). Plano Nacional de Logística. PNL - 2025. Relatório Executivo. Available at: epl.gov.br/transporte-inter-regional-de-carga-no-brasil-panorama-2015 [Accessed on 24/05/2021] Comment for fatty acid methyl ester: Fuel consumption data extrapolated from the original dataset covering the South African region. Corrected to account for 12% biodiesel blend accordind to fuels energy content. For conventional diesel, it was considered energy content of 129.500 Btu/gal, for animal-based biodiesel 115.720 Btu/gal and for plant-based biodiesel 119.216 Btu/gal (USEPA, 2002). Final value is influenced by the updated freight load factor form EPE (2020). References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil. USEPA, 2002. United States Environmental Protection Agency (2002). A Comprehensive Analysis of Biodiesel Impacts on Exhaust Emissions. Draft Technical Report. Comment for [variable] tyre_emissions: Road freight specific non-exhaust emissions. Tyre wear emissions calculation was updated with Brazilian Gross Vehicle Weight (GVW). The linear relation 8.055E-8 kg/kg GVW*km was considered as in the original dataset for the RER region. The GVW of the Brazilian >32t lorries using an average load factor is 34981.9 kg. The GVW was calculated from the original RER value according to the updated load factor from EPE (2020). The calculated emission is normalized by the average payload, according to the reference flow. References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil. Ntziachristos, L., et al. (2013) EMEP/EEA air pollutant emissions inventory guidebook 2009: Exhaust emissions from road transport. European Environment Agency, Copenhagen, DK. ; Annual prod. tyre wear emissions, lorry:6343748.91826539kg Comment for tyre wear emissions, lorry: Road freight specific non-exhaust emissions. Tyre wear emissions calculation was updated with Brazilian Gross Vehicle Weight (GVW). The linear relation 8.055E-8 kg/kg GVW*km was considered as in the original dataset for the RER region. The GVW of the Brazilian >32t lorries using an average load factor is 34981.9 kg. The GVW was calculated from the original RER value according to the updated load factor from EPE (2020). The calculated emission is normalized by the average payload, according to the reference flow. References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil. Ntziachristos, L., et al. (2013) EMEP/EEA air pollutant emissions inventory guidebook 2009: Exhaust emissions from road transport. European Environment Agency, Copenhagen, DK. Comment for [variable] road_emissions: Road freight specific non-exhaust emissions. Road wear emissions calculation was updated with Brazilian Gross Vehicle Weight (GVW). The linear relation 7.0E-9 kg/kg GVW*km was considered as in the original dataset for the RER region. The GVW of the Brazilian >32t lorries using an average load factor is 34981.9 kg. The GVW was calculated from the original RER value according to the updated load factor from EPE (2020). The calculated emission is normalized by the average payload, according to the reference flow. References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil. Ntziachristos, L., et al. (2013) EMEP/EEA air pollutant emissions inventory guidebook 2009: Exhaust emissions from road transport. European Environment Agency, Copenhagen, DK. ; Annual prod. road wear emissions, lorry:551287.925857947kg Comment for road wear emissions, lorry: Road freight specific non-exhaust emissions. Road wear emissions calculation was updated with Brazilian Gross Vehicle Weight (GVW). The linear relation 7.0E-9 kg/kg GVW*km was considered as in the original dataset for the RER region. The GVW of the Brazilian >32t lorries using an average load factor is 34981.9 kg. The GVW was calculated from the original RER value according to the updated load factor from EPE (2020). The calculated emission is normalized by the average payload, according to the reference flow. References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil. Ntziachristos, L., et al. (2013) EMEP/EEA air pollutant emissions inventory guidebook 2009: Exhaust emissions from road transport. European Environment Agency, Copenhagen, DK. Comment for [variable] brake_emissions: Road freight specific non-exhaust emissions. Brake wear emissions calculation was updated with Brazilian Gross Vehicle Weight (GVW). The linear relation 8.13E-9 kg/kg GVW*km was considered as in the original dataset for the RER region. The GVW of the Brazilian >32t lorries using an average load factor is 34981.9 kg. The GVW was calculated from the original RER value according to the updated load factor from EPE (2020). The calculated emission is normalized by the average payload, according to the reference flow. References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil. Ntziachristos, L., et al. (2013) EMEP/EEA air pollutant emissions inventory guidebook 2009: Exhaust emissions from road transport. European Environment Agency, Copenhagen, DK. ; Annual prod. brake wear emissions, lorry:640281.548175019kg Comment for brake wear emissions, lorry: Road freight specific non-exhaust emissions. Brake wear emissions calculation was updated with Brazilian Gross Vehicle Weight (GVW). The linear relation 8.13E-9 kg/kg GVW*km was considered as in the original dataset for the RER region. The GVW of the Brazilian >32t lorries using an average load factor is 34981.9 kg. The GVW was calculated from the original RER value according to the updated load factor from EPE (2020). The calculated emission is normalized by the average payload, according to the reference flow. References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil. Ntziachristos, L., et al. (2013) EMEP/EEA air pollutant emissions inventory guidebook 2009: Exhaust emissions from road transport. European Environment Agency, Copenhagen, DK. Comment for diesel: Data extrapolated from the original dataset covering the South African region. Corrected to account for 12% biodiesel blend accordind to fuels energy content. Type of diesel represents the Brazilian diesel with 500 ppm of sulphur concentration. For conventional diesel, it was considered energy content of 129.500 Btu/gal, for animal-based biodiesel 115.720 Btu/gal and for plant-based biodiesel 119.216 Btu/gal (USEPA, 2002). Final value is influenced by the updated freight load factor form EPE (2020). References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil. USEPA, 2002. United States Environmental Protection Agency (2002). A Comprehensive Analysis of Biodiesel Impacts on Exhaust Emissions. Draft Technical Report. Comment for particles (PM2.5): Measured data from emission testing of the national vehicle fleet production and imports, weighted by sales amounts (CETESB, 2019). Correction factor applied to account the impact of the biodiesel blend on exhaust emission according to USEPA (2002). Final value is influenced by the updated freight load factor form EPE (2020). References: CETESB (2019). Companhia Ambiental do Estado de São Paulo (2019). Emissões Veiculares no Estado de São Paulo. Governo do Estado de São Paulo. Available at: https://cetesb.sp.gov.br/veicular/relatoriose-publicacoes/. Accessed in 15/06/2020. EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil. USEPA, 2002. United States Environmental Protection Agency (2002). A Comprehensive Analysis of Biodiesel Impacts on Exhaust Emissions. Draft Technical Report. Comment for non-methane volatile organic compounds: Data extrapolated from the original dataset covering the South African region. Correction factor applied to account the impact of the biodiesel blend on exhaust emission according to USEPA (2002). Final value is influenced by the updated freight load factor form EPE (2020). References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil. USEPA, 2002. United States Environmental Protection Agency (2002). A Comprehensive Analysis of Biodiesel Impacts on Exhaust Emissions. Draft Technical Report. Comment for carbon monoxide, fossil: Measured data from emission testing of the national vehicle fleet production and imports, weighted by sales amounts (CETESB, 2019). Correction factor applied to account the impact of the biodiesel blend on exhaust emission according to USEPA (2002). Value representing the fossil emission share. Final value is influenced by the updated freight load factor form EPE (2020). References: CETESB (2019). Companhia Ambiental do Estado de São Paulo (2019). Emissões Veiculares no Estado de São Paulo. Governo do Estado de São Paulo. Available at: https://cetesb.sp.gov.br/veicular/relatoriose-publicacoes/. Accessed in 15/06/2020. EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil. USEPA, 2002. United States Environmental Protection Agency (2002). A Comprehensive Analysis of Biodiesel Impacts on Exhaust Emissions. Draft Technical Report. Comment for nitrogen oxides: Measured data from emission testing of the national vehicle fleet production and imports, weighted by sales amounts (CETESB, 2019). Correction factor applied to account the impact of the biodiesel blend on exhaust emission according to USEPA (2002). Final value is influenced by the updated freight load factor form EPE (2020). References: CETESB (2019). Companhia Ambiental do Estado de São Paulo (2019). Emissões Veiculares no Estado de São Paulo. Governo do Estado de São Paulo. Available at: https://cetesb.sp.gov.br/veicular/relatoriose-publicacoes/. Accessed in 15/06/2020. EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil. USEPA, 2002. United States Environmental Protection Agency (2002). A Comprehensive Analysis of Biodiesel Impacts on Exhaust Emissions. Draft Technical Report. Comment for benzene: Data extrapolated from the original dataset covering the South African region. Correction factor applied to account the impact of the biodiesel blend on exhaust emission according to USEPA (2002). Final value is influenced by the updated freight load factor form EPE (2020). References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil. USEPA, 2002. United States Environmental Protection Agency (2002). A Comprehensive Analysis of Biodiesel Impacts on Exhaust Emissions. Draft Technical Report. Comment for sulfur dioxide: Calculated value based on fuel sulphur content. EURO2 lorries are assumed to be fuelled with 500 ppm sulphur content fossil diesel blended with 12% biodiesel, which does not contribute to sulphur emissions. References: MMA, 2014. Ministry of Environment (2014). Inventário Nacional de Emissões Atmosféricas por Veículos Automotores Rodoviários. Available at: http://www.antt.gov.br/backend/galeria/arquivos/inventario_de_emissoes_por_veiculos_rodov iarios_2013.pdf. Accessed in: 10/06/2020. Comment for carbon monoxide, non-fossil: Measured data from emission testing of the national vehicle fleet production and imports, weighted by sales amounts (CETESB, 2019). Correction factor applied to account the impact of the biodiesel blend on exhaust emission according to USEPA (2002). Value representing the biogenic emission share. Final value is influenced by the updated freight load factor form EPE (2020). References: CETESB (2019). Companhia Ambiental do Estado de São Paulo (2019). Emissões Veiculares no Estado de São Paulo. Governo do Estado de São Paulo. Available at: https://cetesb.sp.gov.br/veicular/relatoriose-publicacoes/. Accessed in 15/06/2020. EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil. USEPA, 2002. United States Environmental Protection Agency (2002). A Comprehensive Analysis of Biodiesel Impacts on Exhaust Emissions. Draft Technical Report. Comment for methane (fossil): Data extrapolated from the original dataset covering the South African region. Correction factor applied to account the impact of the biodiesel blend on exhaust emission according to USEPA (2002). Final value is influenced by the updated freight load factor form EPE (2020). References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil. USEPA, 2002. United States Environmental Protection Agency (2002). A Comprehensive Analysis of Biodiesel Impacts on Exhaust Emissions. Draft Technical Report.
Copyright Yes
Data set LCA report, background info
Quantitative reference
Reference flow(s)
Time representativeness
Data set valid until 2021
Time representativeness description Data is valid for the entire period. Validity period of the 12% biodiesel blend regulation. The regulation foresees incremental increases in the biodiesel content in the Brazilian market fuel (it started with a 2% blend in 2008, reached 12% in 2020 and will increase 1% a year, until it reaches 15% in 2023).
Technological representativeness
Technology description including background system The technology level of this process is: Current; ; Diesel and diesel engine. Lorry transport is further differentiated with respect to vehicle weight and emission technology standard (EURO-standard). Technology classifications are based on those used widely within the works of the European Environment Agency, particularly in the Emissions Inventory Guidebook.; Included activities start: From combustion of fuel in the engine. The dataset takes as input the infrastructure of the lorry and road network, the materials and efforts needed for maintenance of these and the fuel consumed in the vehicle for the journey. Included activities end: The activity ends with the transport service of 1tkm and the emissions of exhaust and non-exhaust emissions into air, water and soil.
Mathematical model
Variable / parameter Formula Mean value Minimum value Maximum value Uncertainty distribution type Relative StdDev in % General comment
transport_RP_PV 1548000000000*0.645*0.04 3.99384E10 % Variable comment placed in dataset's general comment for passing the number of characters
tyre_emissions (8.055e-8*34981.9)/17.74 1.58838333990981E-4 % Variable comment placed in dataset's general comment for passing the number of characters
pvl[kg]_b17b856e_dc7a_4f18_9d7f_ca5fc8e7f08c tyre_emissions*transport_RP_PV 6343748.91826539 % Calculated from production volume of reference product using the relative outputs.
tyre_emissions_WM 1.0 %
tyre_emissions_DM 1.0 %
road_emissions (7.0e-9*34981.9)/17.74 1.38034554678692E-5 % Variable comment placed in dataset's general comment for passing the number of characters
pvl[kg]_d74f6977_9f00_4917_96fd_85819b51f729 road_emissions*transport_RP_PV 551287.925857947 % Calculated from production volume of reference product using the relative outputs.
road_emissions_DM 1.0 %
road_emissions_WM 1.0 %
brake_emissions (8.13e-9*34981.9)/17.74 1.60317275648253E-5 % Variable comment placed in dataset's general comment for passing the number of characters
pvl[kg]_3b022fef_e7fd_4736_a52f_d1a053a09cbc brake_emissions*transport_RP_PV 640281.548175019 % Calculated from production volume of reference product using the relative outputs.
brake_emissions_DM 1.0 %
brake_emissions_WM 1.0 %
LCI method and allocation
Type of data set Unit process, black box
LCI Method Principle Not applicable
Deviation from LCI method principle / explanations System model: Undefined
LCI method approaches
  • Not applicable
Data sources, treatment and representativeness
Data cut-off and completeness principles None
Data selection and combination principles None
Data treatment and extrapolations principles Apart from particulate matter, carbon monoxide, sulfur dioxide, and carbon dioxide, exhaust emissions are extrapolated from an original dataset covering the geography ZA. Infrastructure and maintenance information are also extrapolated from the geography ZA. Fuel use and emission factors were adapted considering the 12% biodiesel blend, however original emission factors references are from earlier periods. The uncertainty has been adjusted accordingly.
Percentage supply or production covered 100 %
Annual supply or production volume Annual prod. transport, freight, lorry >32 metric ton, EURO1:39938400000metric ton*km
Sampling procedure Literatura data is used to update regulated exhaust emissions and freight load factors. Furthermore, correction factors are used to consider the impact of biodiesel blend on exhaust emissions. Refer to General Comment section for detailed recontextualization methodology.
Uncertainty adjustments Uncertainties calculated using a basic uncertainty (or informed) and a Pedigree Matrix additional uncertainty (log-normal) as it is in the standard procedure on Ecospold2 datasets (ecoinvent association)
Completeness
Completeness of product model All relevant flows quantified
Validation
Review details
Date of last review: 2021-05-10; Major version: 3.0; Minor version: 0.62
Subsequent review comments
Validation warnings: - Mass and/or economic deficit in activity dataset exceeds either 0.1% of input or output sum: Property 'wet mass': - Input='0.016966835', Output='0.0535519907681138' - Input < output by 0.0365851557681138 kg (68.32% of output) Property 'carbon content, non-fossil': - Input='0.00149036664', Output='0.00158884469840976' - Input < output by 9.84780584097596E-05 kg (6.2% of output) Property 'carbon content, fossil': - Input='0.012998631795', Output='0.013089841400408' - Input < output by 9.12096054079686E-05 kg (0.7% of output) Property 'dry mass': - Input='0.016966835', Output='0.0535519907681138' - Input < output by 0.0365851557681138 kg (68.32% of output) Property 'price': - Input='0', Output='0.0197516433767217' - Input < output by 0.0197516433767217 EUR2005 (100% of output) - Amount of property 'carbon content, fossil=0.92257895036' of exchange 'Benzene' deviates from the default amount in the master file. Amount of property 'carbon content, fossil=0.748686634968' of exchange 'Methane, fossil' deviates from the default amount in the master file. Amount of property 'carbon content, fossil=0.272916486782' of exchange 'Carbon dioxide, fossil' deviates from the default amount in the master file. Amount of property 'carbon content, fossil=0.427024457774' of exchange 'NMVOC, non-methane volatile organic compounds, unspecified origin' deviates from the default amount in the master file. Amount of property 'carbon content, non-fossil=0.427024457774' of exchange 'NMVOC, non-methane volatile organic compounds, unspecified origin' deviates from the default amount in the master file. Amount of property 'carbon content, fossil=0.92257895036' of exchange 'Particulates, < 2.5 um' deviates from the default amount in the master file. Amount of property 'carbon content, fossil=0.42880501528' of exchange 'Carbon monoxide, fossil' deviates from the default amount in the master file. - Uncertainty shall always be provided for all primary data inputs (exchange amounts, properties and parameters), except for the amount and properties of reference products. -- Property(ies): carbon content, non-fossil=0, price=0, dry mass=1, wet mass=1, price=0, carbon content, non-fossil=0, dry mass=1, wet mass=1, price=0, carbon content, non-fossil=0, wet mass=1, dry mass=1, wet mass=1, water in wet mass=0, carbon content, non-fossil=0, carbon content, fossil=0, dry mass=1, water content=0, dry mass=1, carbon content, non-fossil=0, water content=0, wet mass=1, carbon content, fossil=0, water in wet mass=0, water content=0, carbon content, non-fossil=0, water in wet mass=0, dry mass=1, wet mass=1, carbon content, fossil=0, carbon content, fossil=0, carbon content, non-fossil=0, wet mass=1, water content=0, dry mass=1, water in wet mass=0, water content=0, carbon content, non-fossil=0, dry mass=1, carbon content, fossil=0, wet mass=1, water in wet mass=0, wet mass=1, dry mass=1, carbon content, non-fossil=0, carbon content, fossil=0, water content=0, water in wet mass=0, water in wet mass=0, wet mass=1, carbon content, non-fossil=0, carbon content, fossil=0, water content=0, dry mass=1, carbon content, non-fossil=0, water content=0, dry mass=1, carbon content, fossil=0.92257895036, water in wet mass=0, wet mass=1, carbon content, fossil=0, wet mass=1, water in wet mass=0, dry mass=1, water content=0, carbon content, non-fossil=0, water content=0, wet mass=1, water in wet mass=0, carbon content, non-fossil=0, carbon content, fossil=0, dry mass=1, carbon content, fossil=0.748686634968, dry mass=1, carbon content, non-fossil=0, water content=0, water in wet mass=0, wet mass=1, water content=0, wet mass=1, carbon content, fossil=0.272916486782, carbon content, non-fossil=0, water in wet mass=0, dry mass=1, water in wet mass=0, wet mass=1, water content=0, carbon content, fossil=0.427024457774, dry mass=1, carbon content, non-fossil=0.427024457774, wet mass=1, water in wet mass=0, carbon content, non-fossil=0, dry mass=1, water content=0, carbon content, fossil=0, dry mass=1, wet mass=1, water in wet mass=0, water content=0, carbon content, non-fossil=0, carbon content, fossil=0, carbon content, non-fossil=0, water in wet mass=0, dry mass=1, water content=0, wet mass=1, carbon content, fossil=0, water in wet mass=0, wet mass=1, water content=0, carbon content, fossil=0.92257895036, dry mass=1, carbon content, non-fossil=0, carbon content, fossil=0.42880501528, water in wet mass=0, dry mass=1, water content=0, carbon content, non-fossil=0, wet mass=1, dry mass=1, water in wet mass=0, wet mass=1, carbon content, non-fossil=0, carbon content, fossil=0, water content=0, water in wet mass=0, water content=0, carbon content, fossil=0, carbon content, non-fossil=0.272916486782489, wet mass=1, dry mass=1, water in wet mass=0, carbon content, fossil=0, carbon content, non-fossil=0.428805015280039, water content=0, wet mass=1, dry mass=1 - Pedigree information shall always be provided for all uncertainties of primary data inputs (exchange amounts, properties and parameters), except for the amount and properties of reference products. -- Property(ies): carbon content, non-fossil=0, price=0, dry mass=1, wet mass=1, price=0, carbon content, non-fossil=0, dry mass=1, wet mass=1, price=0, carbon content, non-fossil=0, wet mass=1, dry mass=1, wet mass=1, water in wet mass=0, carbon content, non-fossil=0, carbon content, fossil=0, dry mass=1, water content=0, dry mass=1, carbon content, non-fossil=0, water content=0, wet mass=1, carbon content, fossil=0, water in wet mass=0, water content=0, carbon content, non-fossil=0, water in wet mass=0, dry mass=1, wet mass=1, carbon content, fossil=0, carbon content, fossil=0, carbon content, non-fossil=0, wet mass=1, water content=0, dry mass=1, water in wet mass=0, water content=0, carbon content, non-fossil=0, dry mass=1, carbon content, fossil=0, wet mass=1, water in wet mass=0, wet mass=1, dry mass=1, carbon content, non-fossil=0, carbon content, fossil=0, water content=0, water in wet mass=0, water in wet mass=0, wet mass=1, carbon content, non-fossil=0, carbon content, fossil=0, water content=0, dry mass=1, carbon content, non-fossil=0, water content=0, dry mass=1, carbon content, fossil=0.92257895036, water in wet mass=0, wet mass=1, carbon content, fossil=0, wet mass=1, water in wet mass=0, dry mass=1, water content=0, carbon content, non-fossil=0, water content=0, wet mass=1, water in wet mass=0, carbon content, non-fossil=0, carbon content, fossil=0, dry mass=1, carbon content, fossil=0.748686634968, dry mass=1, carbon content, non-fossil=0, water content=0, water in wet mass=0, wet mass=1, water content=0, wet mass=1, carbon content, fossil=0.272916486782, carbon content, non-fossil=0, water in wet mass=0, dry mass=1, water in wet mass=0, wet mass=1, water content=0, carbon content, fossil=0.427024457774, dry mass=1, carbon content, non-fossil=0.427024457774, wet mass=1, water in wet mass=0, carbon content, non-fossil=0, dry mass=1, water content=0, carbon content, fossil=0, dry mass=1, wet mass=1, water in wet mass=0, water content=0, carbon content, non-fossil=0, carbon content, fossil=0, carbon content, non-fossil=0, water in wet mass=0, dry mass=1, water content=0, wet mass=1, carbon content, fossil=0, water in wet mass=0, wet mass=1, water content=0, carbon content, fossil=0.92257895036, dry mass=1, carbon content, non-fossil=0, carbon content, fossil=0.42880501528, water in wet mass=0, dry mass=1, water content=0, carbon content, non-fossil=0, wet mass=1, dry mass=1, water in wet mass=0, wet mass=1, carbon content, non-fossil=0, carbon content, fossil=0, water content=0, water in wet mass=0, water content=0, carbon content, fossil=0, carbon content, non-fossil=0.272916486782489, wet mass=1, dry mass=1, water in wet mass=0, carbon content, fossil=0, carbon content, non-fossil=0.428805015280039, water content=0, wet mass=1, dry mass=1 - Production volume of local datasets for a specific activity, time period, and macro-economic scenario must not exceed 99.5% of the production volume of the corresponding global. Warning: - Exchange 'tyre wear emissions, lorry', global (2017-2017) production volume 1007031.47407622, sum of all non-global production volumes 1009778.4554994. Local datasets used in calculation: ZA (2017-2017) PV: 1007024.58, BR (2020-2021) PV: 2753.87549940203 Warning: - Exchange 'brake wear emissions, lorry', global (2017-2017) production volume 101640.352623671, sum of all non-global production volumes 101917.608479828. Local datasets used in calculation: ZA (2017-2017) PV: 101639.6568, BR (2020-2021) PV: 277.951679827915 Warning: - Exchange 'road wear emissions, lorry', global (2017-2017) production volume 87513.5139121929, sum of all non-global production volumes 87752.2335895197. Local datasets used in calculation: ZA (2017-2017) PV: 87512.9148, BR (2020-2021) PV: 239.318789519729 Warning: - Exchange 'transport, freight, lorry >32 metric ton, EURO1', global (2017-2017) production volume 6876047073, sum of all non-global production volumes 6893337600. Local datasets used in calculation: ZA (2017-2017) PV: 6876000000, BR (2020-2021) PV: 17337600
Reviewer name and institution
Reviewer name and institution
Reviewer name and institution
Review details
Date of last review: 2021-07-08; Major version: 3.1; Minor version: 0.4
Subsequent review comments
Validation warnings: - Mass and/or economic deficit in activity dataset exceeds either 0.1% of input or output sum: Property 'dry mass': - Input='0.016966835', Output='0.0535519907681138' - Input < output by 0.0365851557681138 kg (68.32% of output) Property 'carbon content, fossil': - Input='0.012998631795', Output='0.013089841400408' - Input < output by 9.12096054079669E-05 kg (0.7% of output) Property 'wet mass': - Input='0.016966835', Output='0.0535519907681138' - Input < output by 0.0365851557681138 kg (68.32% of output) Property 'carbon content, non-fossil': - Input='0.00149036664', Output='0.00158884469840976' - Input < output by 9.84780584097596E-05 kg (6.2% of output) Property 'price': - Input='0', Output='0.0197516433767217' - Input < output by 0.0197516433767217 EUR2005 (100% of output) - Amount of property 'carbon content, fossil=0.42880501528' of exchange 'Carbon monoxide, fossil' deviates from the default amount in the master file. Amount of property 'carbon content, non-fossil=0.427024457774' of exchange 'NMVOC, non-methane volatile organic compounds, unspecified origin' deviates from the default amount in the master file. Amount of property 'carbon content, fossil=0.427024457774' of exchange 'NMVOC, non-methane volatile organic compounds, unspecified origin' deviates from the default amount in the master file. Amount of property 'carbon content, fossil=0.92257895036' of exchange 'Particulates, < 2.5 um' deviates from the default amount in the master file. Amount of property 'carbon content, fossil=0.748686634968' of exchange 'Methane, fossil' deviates from the default amount in the master file. Amount of property 'carbon content, fossil=0.92257895036' of exchange 'Benzene' deviates from the default amount in the master file. Amount of property 'carbon content, fossil=0.272916486782' of exchange 'Carbon dioxide, fossil' deviates from the default amount in the master file. - Uncertainty shall always be provided for all primary data inputs (exchange amounts, properties and parameters), except for the amount and properties of reference products. -- Property(ies): price=0, dry mass=1, carbon content, non-fossil=0, wet mass=1, wet mass=1, carbon content, non-fossil=0, price=0, dry mass=1, price=0, carbon content, non-fossil=0, wet mass=1, dry mass=1, dry mass=1, water content=0, carbon content, fossil=0, wet mass=1, carbon content, non-fossil=0, water in wet mass=0, water content=0, carbon content, fossil=0, dry mass=1, carbon content, non-fossil=0, wet mass=1, water in wet mass=0, water in wet mass=0, water content=0, dry mass=1, carbon content, fossil=0.42880501528, wet mass=1, carbon content, non-fossil=0, carbon content, non-fossil=0, water content=0, wet mass=1, dry mass=1, carbon content, fossil=0, water in wet mass=0, dry mass=1, wet mass=1, carbon content, fossil=0, water content=0, carbon content, non-fossil=0, water in wet mass=0, water in wet mass=0, water content=0, wet mass=1, dry mass=1, carbon content, fossil=0, carbon content, non-fossil=0, carbon content, non-fossil=0.427024457774, water content=0, wet mass=1, carbon content, fossil=0.427024457774, dry mass=1, water in wet mass=0, water content=0, carbon content, non-fossil=0, water in wet mass=0, carbon content, fossil=0, dry mass=1, wet mass=1, carbon content, non-fossil=0.428805015280039, wet mass=1, water content=0, carbon content, fossil=0, water in wet mass=0, dry mass=1, dry mass=1, wet mass=1, water in wet mass=0, carbon content, non-fossil=0, carbon content, fossil=0, water content=0, water content=0, carbon content, fossil=0.92257895036, water in wet mass=0, wet mass=1, dry mass=1, carbon content, non-fossil=0, carbon content, fossil=0, carbon content, non-fossil=0.272916486782489, wet mass=1, dry mass=1, water content=0, water in wet mass=0, water in wet mass=0, dry mass=1, wet mass=1, water content=0, carbon content, non-fossil=0, carbon content, fossil=0.748686634968, carbon content, non-fossil=0, wet mass=1, carbon content, fossil=0.92257895036, water in wet mass=0, water content=0, dry mass=1, wet mass=1, water in wet mass=0, carbon content, non-fossil=0, carbon content, fossil=0, water content=0, dry mass=1, carbon content, non-fossil=0, water in wet mass=0, carbon content, fossil=0, dry mass=1, wet mass=1, water content=0, dry mass=1, carbon content, non-fossil=0, water content=0, water in wet mass=0, wet mass=1, carbon content, fossil=0, water content=0, water in wet mass=0, dry mass=1, carbon content, non-fossil=0, wet mass=1, carbon content, fossil=0, carbon content, non-fossil=0, dry mass=1, wet mass=1, water content=0, carbon content, fossil=0, water in wet mass=0, water in wet mass=0, carbon content, non-fossil=0, wet mass=1, water content=0, carbon content, fossil=0, dry mass=1, water in wet mass=0, carbon content, fossil=0.272916486782, dry mass=1, wet mass=1, water content=0, carbon content, non-fossil=0 - Pedigree information shall always be provided for all uncertainties of primary data inputs (exchange amounts, properties and parameters), except for the amount and properties of reference products. -- Property(ies): price=0, dry mass=1, carbon content, non-fossil=0, wet mass=1, wet mass=1, carbon content, non-fossil=0, price=0, dry mass=1, price=0, carbon content, non-fossil=0, wet mass=1, dry mass=1, dry mass=1, water content=0, carbon content, fossil=0, wet mass=1, carbon content, non-fossil=0, water in wet mass=0, water content=0, carbon content, fossil=0, dry mass=1, carbon content, non-fossil=0, wet mass=1, water in wet mass=0, water in wet mass=0, water content=0, dry mass=1, carbon content, fossil=0.42880501528, wet mass=1, carbon content, non-fossil=0, carbon content, non-fossil=0, water content=0, wet mass=1, dry mass=1, carbon content, fossil=0, water in wet mass=0, dry mass=1, wet mass=1, carbon content, fossil=0, water content=0, carbon content, non-fossil=0, water in wet mass=0, water in wet mass=0, water content=0, wet mass=1, dry mass=1, carbon content, fossil=0, carbon content, non-fossil=0, carbon content, non-fossil=0.427024457774, water content=0, wet mass=1, carbon content, fossil=0.427024457774, dry mass=1, water in wet mass=0, water content=0, carbon content, non-fossil=0, water in wet mass=0, carbon content, fossil=0, dry mass=1, wet mass=1, carbon content, non-fossil=0.428805015280039, wet mass=1, water content=0, carbon content, fossil=0, water in wet mass=0, dry mass=1, dry mass=1, wet mass=1, water in wet mass=0, carbon content, non-fossil=0, carbon content, fossil=0, water content=0, water content=0, carbon content, fossil=0.92257895036, water in wet mass=0, wet mass=1, dry mass=1, carbon content, non-fossil=0, carbon content, fossil=0, carbon content, non-fossil=0.272916486782489, wet mass=1, dry mass=1, water content=0, water in wet mass=0, water in wet mass=0, dry mass=1, wet mass=1, water content=0, carbon content, non-fossil=0, carbon content, fossil=0.748686634968, carbon content, non-fossil=0, wet mass=1, carbon content, fossil=0.92257895036, water in wet mass=0, water content=0, dry mass=1, wet mass=1, water in wet mass=0, carbon content, non-fossil=0, carbon content, fossil=0, water content=0, dry mass=1, carbon content, non-fossil=0, water in wet mass=0, carbon content, fossil=0, dry mass=1, wet mass=1, water content=0, dry mass=1, carbon content, non-fossil=0, water content=0, water in wet mass=0, wet mass=1, carbon content, fossil=0, water content=0, water in wet mass=0, dry mass=1, carbon content, non-fossil=0, wet mass=1, carbon content, fossil=0, carbon content, non-fossil=0, dry mass=1, wet mass=1, water content=0, carbon content, fossil=0, water in wet mass=0, water in wet mass=0, carbon content, non-fossil=0, wet mass=1, water content=0, carbon content, fossil=0, dry mass=1, water in wet mass=0, carbon content, fossil=0.272916486782, dry mass=1, wet mass=1, water content=0, carbon content, non-fossil=0
Reviewer name and institution
Commissioner and goal
Intended applications Can be used for any types of LCA studies
Data generator
Data set generator / modeller
Data entry by
Time stamp (last saved) 2021-09-20T15:47:39
Data set format(s)
Converted original data set from
Data entry by
Publication and ownership
UUID 0ff48978-51f3-49a9-9261-c0f89ec1864b
Date of last revision 2021-09-20T12:11:58
Data set version 03.01.000
Permanent data set URI http://sicv.acv.ibict.br
Workflow and publication status Data set finalised; entirely published
Unchanged re-publication of
Copyright Yes
License type License fee
Access and use restrictions License type for this dataset: Licensees

Inputs

Type of flow Classification Flow Variable Mean amount Resulting amount Minimum amount Maximum amount
Product flow
0.00203602 kg0.00203602 kg 0.0017719355530807482 0.0023394628733492615
General comment [kg] Pedigree: (2,2,4,5,3). Exchange comment placed in dataset's general comment for passing the number of characters
Product flow
1.812E-4 m*year1.812E-4 m*year 1.021955925471403E-4 3.212803916651763E-4
General comment [m*year] Pedigree: (3,5,4,5,3). Data extrapolated from the original dataset covering the South African region. Final value is influenced by the updated freight load factor form EPE (2020). References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil.
Product flow
1.04244E-7 Item(s)1.04244E-7 Item(s) 5.920753890299896E-8 1.8353763283090253E-7
General comment [unit] Pedigree: (3,1,4,5,3). Data extrapolated from the original dataset covering the South African region. Final value is influenced by the updated freight load factor form EPE (2020). References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil.
Product flow
0.001715398 m*year0.001715398 m*year 9.742958234442904E-4 0.0030202226342318454
General comment [m*year] Pedigree: (3,1,4,5,3). Data extrapolated from the original dataset covering the South African region. References: Notten et al. (2018). Life Cycle Inventories of Road Freight - India and South Africa for the SRI project.
Product flow
0.014930815 kg0.014930815 kg 0.012994195506415129 0.017156062986290042
General comment [kg] Pedigree: (2,2,4,5,3). Exchange comment placed in dataset's general comment for passing the number of characters
Product flow
1.04244E-7 Item(s)1.04244E-7 Item(s) 5.879292135476872E-8 1.84831971019562E-7
General comment [unit] Pedigree: (3,5,4,5,3). Data extrapolated from the original dataset covering the South African region. Final value is influenced by the updated freight load factor form EPE (2020). References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil.

Outputs

Type of flow Classification Flow Variable Mean amount Resulting amount Minimum amount Maximum amount
Product flow
1.0 t*km1.0 t*km
General comment [metric ton*km]
Waste flow
tyre_emissions 1.0 kg1.58838333990981E-4 kg 1.3755336788962084E-4 1.83416929240699E-4
General comment [kg] Pedigree: (3,2,4,5,3). Exchange comment placed in dataset's general comment for passing the number of characters
Waste flow
road_emissions 1.0 kg1.38034554678692E-5 kg 1.195373774335622E-5 1.5939397947670884E-5
General comment [kg] Pedigree: (3,2,4,5,3). Exchange comment placed in dataset's general comment for passing the number of characters
Waste flow
brake_emissions 1.0 kg1.60317275648253E-5 kg 1.3883412550498072E-5 1.8512472187794983E-5
General comment [kg] Pedigree: (3,2,4,5,3). Exchange comment placed in dataset's general comment for passing the number of characters
Elementary flow
Elementary flows / Emissions to air / unspecified 3.56081E-10 kg3.56081E-10 kg 1.525353654992449E-10 8.312411888613967E-10
General comment [kg] Pedigree: (2,2,4,5,3). Data extrapolated from the original dataset covering the South African region. Final value is influenced by the updated freight load factor form EPE (2020). References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil.
Elementary flow
Elementary flows / Emissions to air / unspecified 6.29786E-6 kg6.29786E-6 kg 6.0748322786813815E-6 6.5290758263056705E-6
General comment [kg] Pedigree: (2,2,1,1,1). Exchange comment placed in dataset's general comment for passing the number of characters
Elementary flow
Elementary flows / Emissions to air / unspecified 2.18607E-5 kg2.18607E-5 kg 1.902523135589646E-5 2.511875916514877E-5
General comment [kg] Pedigree: (2,2,4,5,3). Exchange comment placed in dataset's general comment for passing the number of characters
Elementary flow
Elementary flows / Emissions to air / unspecified 2.91918E-8 kg2.91918E-8 kg 1.2504969045191564E-8 6.814580541226327E-8
General comment [kg] Pedigree: (2,2,4,5,3). Data extrapolated from the original dataset covering the South African region. Final value is influenced by the updated freight load factor form EPE (2020). References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil.
Elementary flow
Elementary flows / Emissions to air / unspecified 5.03887E-10 kg5.03887E-10 kg 2.1585141503005778E-10 1.176281882301506E-9
General comment [kg] Pedigree: (2,2,4,5,3). Data extrapolated from the original dataset covering the South African region. Final value is influenced by the updated freight load factor form EPE (2020). References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil.
Elementary flow
Elementary flows / Emissions to air / unspecified 0.047310864 kg0.047310864 kg 0.036987102821921636 0.06051617135851696
General comment [kg] Pedigree: (3,5,5,5,3). Calculated value based on the fuel carbon content, which was considered as 77.8% for plant-based biodiesel and 76.1 % for animal-based biodiesel, resulting in a Brazilian average of 77.5%, while conventional diesel has 86.7% of carbon (USEPA, 2002). This results in emissions of 3.18 kg fossil CO2/kg diesel and 2.84 biogenic CO2/kg biodiesel.
Elementary flow
Elementary flows / Emissions to air / unspecified 7.47355E-7 kg7.47355E-7 kg 6.337256179423351E-7 8.813585567813095E-7
General comment [kg] Pedigree: (2,5,4,5,3). Data extrapolated from the original dataset covering the RER region. Final value is influenced by the updated freight load factor form EPE (2020). References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil.
Elementary flow
Elementary flows / Emissions to air / unspecified 0.005739757 kg0.005739757 kg 0.00448727764371085 0.007341825720372539
General comment [kg] Pedigree: (3,5,5,5,3). Calculated value based on the fuel carbon content, which was considered as 77.8% for plant-based biodiesel and 76.1 % for animal-based biodiesel, resulting in a Brazilian average of 77.5%, while conventional diesel has 86.7% of carbon (USEPA, 2002). This results in emissions of 3.18 kg fossil CO2/kg diesel and 2.84 biogenic CO2/kg biodiesel.
Elementary flow
Elementary flows / Emissions to air / unspecified 9.81251E-5 kg9.81251E-5 kg 9.465017082450838E-5 1.0172760562537537E-4
General comment [kg] Pedigree: (2,2,1,1,1). Exchange comment placed in dataset's general comment for passing the number of characters
Elementary flow
Elementary flows / Emissions to air / unspecified 8.90201E-11 kg8.90201E-11 kg 3.813377711891208E-11 2.0780994705294698E-10
General comment [kg] Pedigree: (2,2,4,5,3). Data extrapolated from the original dataset covering the South African region. Final value is influenced by the updated freight load factor form EPE (2020). References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil.
Elementary flow
Elementary flows / Emissions to air / unspecified 1.67187E-7 kg1.67187E-7 kg 1.4550180711039726E-7 1.921040949532141E-7
General comment [kg] Pedigree: (2,2,4,5,3). Data extrapolated from the original dataset covering the South African region. Final value is influenced by the updated freight load factor form EPE (2020). References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil.
Elementary flow
Elementary flows / Emissions to air / unspecified 1.47807E-10 kg1.47807E-10 kg 6.331647790347391E-11 3.450430278561239E-10
General comment [kg] Pedigree: (2,2,4,5,3). Data extrapolated from the original dataset covering the South African region. Final value is influenced by the updated freight load factor form EPE (2020). References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil.
Elementary flow
Elementary flows / Emissions to air / unspecified 1.39226E-4 kg1.39226E-4 kg 1.3429555417740217E-4 1.443374592311092E-4
General comment [kg] Pedigree: (2,2,1,1,1). Exchange comment placed in dataset's general comment for passing the number of characters
Elementary flow
Elementary flows / Emissions to air / unspecified 3.74051E-7 kg3.74051E-7 kg 3.2553426074665623E-7 4.297985418803178E-7
General comment [kg] Pedigree: (2,2,4,5,3). Exchange comment placed in dataset's general comment for passing the number of characters
Elementary flow
Elementary flows / Emissions to air / unspecified 1.46128E-10 kg1.46128E-10 kg 6.259724020566573E-11 3.4112354336776795E-10
General comment [kg] Pedigree: (2,2,4,5,3). Data extrapolated from the original dataset covering the RER region. Final value is influenced by the updated freight load factor form EPE (2020). References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil.
Elementary flow
Elementary flows / Emissions to air / unspecified 1.49308E-5 kg1.49308E-5 kg 1.4188559890204654E-5 1.5711868601541668E-5
General comment [kg] Pedigree: (3,1,1,1,1). Exchange comment placed in dataset's general comment for passing the number of characters
Elementary flow
Elementary flows / Emissions to air / unspecified 1.67963E-12 kg1.67963E-12 kg 7.195075725845993E-13 3.920955170445117E-12
General comment [kg] Pedigree: (2,2,4,5,3). Data extrapolated from the original dataset covering the South African region. Final value is influenced by the updated freight load factor form EPE (2020). References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil.
Elementary flow
Elementary flows / Emissions to air / unspecified 1.67963E-12 kg1.67963E-12 kg 1.4617715508791747E-12 1.9299574787888234E-12
General comment [kg] Pedigree: (2,2,4,5,3). Data extrapolated from the original dataset covering the South African region. Final value is influenced by the updated freight load factor form EPE (2020). References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil.
Elementary flow
Elementary flows / Emissions to air / unspecified 3.03992E-5 kg3.03992E-5 kg 2.9322665382541218E-5 3.151525785886497E-5
General comment [kg] Pedigree: (2,2,1,1,1). Exchange comment placed in dataset's general comment for passing the number of characters
Elementary flow
Elementary flows / Emissions to air / unspecified 5.37559E-7 kg5.37559E-7 kg 4.558274306794812E-7 6.339453464883542E-7
General comment [kg] Pedigree: (2,5,4,5,3). Exchange comment placed in dataset's general comment for passing the number of characters
Elementary flow
Elementary flows / Emissions to air / unspecified 1.00777E-12 kg1.00777E-12 kg 4.3170111656947164E-13 2.3525544269389544E-12
General comment [kg] Pedigree: (2,2,4,5,3). Data extrapolated from the original dataset covering the South African region. Final value is influenced by the updated freight load factor form EPE (2020). References: EPE, 2020. Energy Research Enterprise (2020). Integrated Transport Model. Consultation through Information to Citizen System. Federal Government of Brazil.