| Key Data Set Information | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Location | BR | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Geographical representativeness description | Recontextualization from 'transport, freight, lorry 3.5-7.5 metric ton, EURO3, RER'. 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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 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. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 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 3.5-7.5 metric ton, EURO3” in Europe, 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 3.5-7.5 metric tons gross vehicle weight (GVW) and Euro 3 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 3.5-7.5 metric ton lorry is representing the Brazilian heavy-duty lorry with gross vehicle weight (GVW) with 3.8 to 6 metric tons and 6 to 10 metric tons categories classification. The average capacity utilization factor (including empty trips) for this category is 57.5 % 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 3.7 ton (Novo, 2016), resulting in an average freight load of 2.13 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 6.13 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. CNT (2021). CNT acompanha, com atenção, a alta histórica do diesel. Available at: cnt.org.br/agencia-cnt/cnt-acompanha-alta-historica-do-diesel 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 Comment for fatty acid methyl ester: Fuel consumption data extrapolated from the original dataset covering the RER 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. Keller, M. et al. (2010) Handbook emission factors for road transport v3.1, HBEFA. INFRAS, Berne, CH. USEPA, 2002. United States Environmental Protection Agency (2002). A Comprehensive Analysis of Biodiesel Impacts on Exhaust Emissions. Draft Technical Report. Comment for maintenance, lorry 16 metric ton: Calculated value based on lifetime vkm (540 000 for all lorry sizes) and average load factors (see Activity Description). 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. Spielmann, M., et al. (2007) Transport Services. ecoinvent report No. 14., Swiss Centre for Life Cycle Inventories, Dübendorf, CH. 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 Brazilian3.5-7.5t lorries using an average load factor is 6132 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:635818.023755492kg 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 Brazilian3.5-7.5t lorries using an average load factor is 6132 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 lorry, 16 metric ton: Calculated value based on lifetime vkm (540 000 for all lorry sizes) and average load factors (see Activity Description). 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. Spielmann, M., et al. (2007) Transport Services. ecoinvent report No. 14., Swiss Centre for Life Cycle Inventories, Dübendorf, CH. Comment for road maintenance: Calculated value based demand factors and underlying assumptions for European road transport services. Values are based on total vkm of all road transport services (RER) and the relative shares of each specific form (e.g. 3.5-7.5t lorry). The value per tkm is then based on the average load factor (see Activity Description). Transport performance data is derived from TREMOVE (2009). 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. De Ceuster, G., et al. (2009) TREMOVE: Final Report. Model code v2.7b, 2009. European Commission, Brussels. 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 Brazilian3.5-7.5t lorries using an average load factor is 6132 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:547444.792901408kg 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 Brazilian3.5-7.5t lorries using an average load factor is 6132 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] 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 Brazilian3.5-7.5t lorries using an average load factor is 6132 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:6299525.43831548kg 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 Brazilian3.5-7.5t lorries using an average load factor is 6132 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 road: Calculated value based demand factors and underlying assumptions for European road transport services. Values are based on total tkm of all road transport services (RER) and the relative shares of each specific form (i.e. 3.5-7.5t lorry). The value per tkm is then based on the net vehicle weight plus averge load factor (see Activity Description). Transport performance data is derived from TREMOVE (2009). Data extrapolated from the original dataset covering the RER region. References: Spielmann, M., et al. (2007) Transport Services. ecoinvent report No. 14., Swiss Centre for Life Cycle Inventories, Dübendorf, CH. Comment for diesel: Literature value. Derived from HBEFA database (Keller, 2010). Data extrapolated from the original dataset covering the RER 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. Keller, M. et al. (2010) Handbook emission factors for road transport v3.1, HBEFA. INFRAS, Berne, CH. USEPA, 2002. United States Environmental Protection Agency (2002). A Comprehensive Analysis of Biodiesel Impacts on Exhaust Emissions. Draft Technical Report. 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 toluene: Data extrapolated from the original dataset covering the RER 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 lead: Literature value. Fuel dependant emissions - heavy metal in fuel. Literature value. EMEP/EEA (2013) Tab. 3-100. 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. 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 ethane: Data extrapolated from the original dataset covering the RER 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 m-xylene: Data extrapolated from the original dataset covering the RER 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 propane: Data extrapolated from the original dataset covering the RER 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 chromium VI: Estimated value. Fuel dependant emissions - heavy metal in fuel. Estimated using the underlying assumption that 0.2% of the emitted Cr is emitted as Cr(IV). Fuel dependant emissions - heavy metal in fuel. Literature value for Cr. EMEP/EEA (2013) Tab. 3-100. 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. 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 pentane: Data extrapolated from the original dataset covering the RER 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 benzene: Data extrapolated from the original dataset covering the RER 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. EURO3 lorries are 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 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 heptane: Data extrapolated from the original dataset covering the RER 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 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 n-butane: Data extrapolated from the original dataset covering the RER 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 formaldehyde: Data extrapolated from the original dataset covering the RER 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 non-methane volatile organic compounds: Data extrapolated from the original dataset covering the RER 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 chromium: Literature value. Fuel dependant emissions - heavy metal in fuel. Literature value. EMEP/EEA (2013) Tab. 3-100. 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. 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 mercury: Literature value. Fuel dependant emissions - heavy metal in fuel. Literature value. EMEP/EEA (2013) Tab. 3-100. 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. 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 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 styrene: Data extrapolated from the original dataset covering the RER 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 selenium: Literature value. Fuel dependant emissions - heavy metal in fuel. Literature value. EMEP/EEA (2013) Tab. 3-100. 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. 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 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 acetaldehyde: Data extrapolated from the original dataset covering the RER 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 acrolein: Data extrapolated from the original dataset covering the RER 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 polycyclic aromatic hydrocarbons: Literature value. PAH's per kg fuel use provided by the EMEP/EEA (2013) guidebook. 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. 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 o-xylene: Data extrapolated from the original dataset covering the RER 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 nitrous oxide: Literature value. Derived from HBEFA database (Keller, 2010). 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. Keller, M. et al. (2010) Handbook emission factors for road transport v3.1, HBEFA. INFRAS, Berne, CH. Comment for zinc: Literature value. Fuel dependant emissions - heavy metal in fuel. Literature value. EMEP/EEA (2013) Tab. 3-100. 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. 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 ammonia: Literature value. Derived from HBEFA database (Keller, 2010). 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. Keller, M. et al. (2010) Handbook emission factors for road transport v3.1, HBEFA. INFRAS, Berne, CH. Comment for benzaldehyde: Data extrapolated from the original dataset covering the RER 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 arsenic: Literature value. Fuel dependant emissions - heavy metal in fuel. Literature value. EMEP/EEA (2013) Tab. 3-100. 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. 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 copper: Literature value. Fuel dependant emissions - heavy metal in fuel. Literature value. EMEP/EEA (2013) Tab. 3-100. 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. 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 nickel: Literature value. Fuel dependant emissions - heavy metal in fuel. Literature value. EMEP/EEA (2013) Tab. 3-100. 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. 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 methane (fossil): Data extrapolated from the original dataset covering the RER 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 cadmium: Literature value. Fuel dependant emissions - heavy metal in fuel. Literature value. EMEP/EEA (2013) Tab. 3-100. 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. Ntziachristos, L., et al. (2013) EMEP/EEA air pollutant emissions inventory guidebook 2009: Exhaust emissions from road transport. European Environment Agency, Copenhagen, DK. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Copyright | Yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data set LCA report, background info | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Quantitative reference | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Reference flow(s) |
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| 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 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 |
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| 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 RER. Infrastructure and maintenance information are also extrapolated from the geography RER. 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 3.5-7.5 metric ton, EURO3:27167400000metric 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 | ||||||||||||||||||||||||||||
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| 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) | 2021-09-20T15:49:53 |
| Data set format(s) | |
| Converted original data set from | |
| Data entry by | |
| Publication and ownership | |
| UUID | 4e4999d1-bbc9-450f-a6f3-93a807ecffc5 |
| Date of last revision | 2021-09-20T12:17:38 |
| 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 | 0.006207303 kg | 0.006207303 kg | 0.005402177225393065 | 0.007132422526364913 | |||||
| |||||||||
| Product flow | 8.65973E-7 Item(s) | 8.65973E-7 Item(s) | 4.918473013933341E-7 | 1.52467896968147E-6 | |||||
| |||||||||
| Product flow | 8.65973E-7 Item(s) | 8.65973E-7 Item(s) | 4.884030014615051E-7 | 1.5354312616526916E-6 | |||||
| |||||||||
| Product flow | 6.04817E-4 m*year | 6.04817E-4 m*year | 3.411127577129346E-4 | 0.0010723832375593649 | |||||
| |||||||||
| Product flow | 0.00195 m*year | 0.00195 m*year | 0.0011075428884237746 | 0.003433275622772149 | |||||
| |||||||||
| Product flow | 0.045520224 kg | 0.045520224 kg | 0.03961596806013671 | 0.05230443415808391 | |||||
| |||||||||
Outputs
| Type of flow | Classification | Flow | Variable | Mean amount | Resulting amount | Minimum amount | Maximum amount | ||
|---|---|---|---|---|---|---|---|---|---|
| Product flow | 1.0 t*km | 1.0 t*km | |||||||
| |||||||||
| Waste flow | brake_emissions | 1.0 kg | 2.34037126760563E-5 kg | 2.0267522447669014E-5 | 2.7025196021746296E-5 | ||||
| |||||||||
| Waste flow | road_emissions | 1.0 kg | 2.01507981220657E-5 kg | 1.7450511332556348E-5 | 2.3268926463988204E-5 | ||||
| |||||||||
| Waste flow | tyre_emissions | 1.0 kg | 2.31878112676056E-4 kg | 2.0080552683391625E-4 | 2.677588609534643E-4 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 3.76934E-9 kg | 3.76934E-9 kg | 3.2804331773014938E-9 | 4.331112163451393E-9 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 2.66791E-9 kg | 2.66791E-9 kg | 1.1428597059913066E-9 | 6.228011829261345E-9 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 1.1308E-8 kg | 1.1308E-8 kg | 9.841282126028772E-9 | 1.2993313509608672E-8 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 3.69395E-7 kg | 3.69395E-7 kg | 3.21482172881535E-7 | 4.244486243263084E-7 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 3.76934E-8 kg | 3.76934E-8 kg | 3.280433177301494E-8 | 4.331112163451393E-8 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 3.07245E-12 kg | 3.07245E-12 kg | 1.316153582269638E-12 | 7.172376483769699E-12 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 2.2616E-8 kg | 2.2616E-8 kg | 1.9682564252057545E-8 | 2.5986627019217344E-8 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 2.63854E-8 kg | 2.63854E-8 kg | 2.2963049646986166E-8 | 3.031780812490526E-8 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 4.55202E-5 kg | 4.55202E-5 kg | 4.3257299268230364E-5 | 4.7901478897038135E-5 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 0.001010826 kg | 0.001010826 kg | 9.750293612322894E-4 | 0.0010479368549318746 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 1.1308E-7 kg | 1.1308E-7 kg | 9.841282126028773E-8 | 1.2993313509608672E-7 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 1.77579E-5 kg | 1.77579E-5 kg | 1.7129034961335454E-5 | 1.840985280967717E-5 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 5.65399E-8 kg | 5.65399E-8 kg | 4.9206323600765315E-8 | 6.496645264431583E-8 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 3.16624E-6 kg | 3.16624E-6 kg | 2.684838397486789E-6 | 3.733958716839057E-6 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 3.06183E-5 kg | 3.06183E-5 kg | 2.6646916211477426E-5 | 3.518156800771588E-5 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 0.017609972 kg | 0.017609972 kg | 0.013767278590709336 | 0.022525229790153183 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 1.53622E-9 kg | 1.53622E-9 kg | 6.58074649271514E-10 | 3.5861765698047775E-9 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 2.714E-10 kg | 2.714E-10 kg | 1.1626034019364994E-10 | 6.335605063369937E-10 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 2.20904E-5 kg | 2.20904E-5 kg | 2.1308107034609088E-5 | 2.2901413596590397E-5 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 2.11083E-7 kg | 2.11083E-7 kg | 1.8370422311713225E-7 | 2.42542235191787E-7 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 5.12075E-12 kg | 5.12075E-12 kg | 2.1935893037827302E-12 | 1.1953960806282833E-11 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 1.61996E-4 kg | 1.61996E-4 kg | 1.5625919436400128E-4 | 1.6794342325142405E-4 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 1.72259E-6 kg | 1.72259E-6 kg | 1.499159371902715E-6 | 1.9793201201376725E-6 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 0.144454226 kg | 0.144454226 kg | 0.1129326936435383 | 0.1847739811743437 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 6.67172E-7 kg | 6.67172E-7 kg | 5.806356454356976E-7 | 7.666054970669117E-7 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 4.00442E-9 kg | 4.00442E-9 kg | 1.7153840511357984E-9 | 9.34798217680908E-9 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 1.50774E-7 kg | 1.50774E-7 kg | 1.2785001280467464E-7 | 1.778083441472194E-7 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 1.02544E-6 kg | 1.02544E-6 kg | 8.69530006038346E-7 | 1.2093052411047308E-6 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 8.89985E-8 kg | 8.89985E-8 kg | 3.8124524269434615E-8 | 2.0775952366703367E-7 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 1.40499E-6 kg | 1.40499E-6 kg | 1.2227540656392965E-6 | 1.6143858814878925E-6 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 5.164E-7 kg | 5.164E-7 kg | 4.494197108136946E-7 | 5.933628489884966E-7 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 5.12075E-12 kg | 5.12075E-12 kg | 4.456556901915621E-12 | 5.8839326277262656E-12 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 1.0856E-9 kg | 1.0856E-9 kg | 4.650413607745998E-10 | 2.534242025347975E-9 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 4.50625E-10 kg | 4.50625E-10 kg | 1.9303543036021924E-10 | 1.0519462165368748E-9 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 9.26886E-7 kg | 9.26886E-7 kg | 7.859603576775417E-7 | 1.0930801389711727E-6 | ||||
| |||||||||
| Elementary flow | Elementary flows / Emissions to air / unspecified | 4.45505E-10 kg | 4.45505E-10 kg | 1.9084216233593227E-10 | 1.0399940065426027E-9 | ||||
| |||||||||