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general:projections:calculation_documentation [2025/03/31 13:31] – eisoldgeneral:projections:calculation_documentation [2025/04/03 13:01] (current) – eisold
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 In the scenario “with measures” (WM), for the majority of the emission sources in the sectors 1.A.1 (energy industry), 1.A.2 (manufacturing industry), 1.A.4 (other combustion systems), 1.A.5 (military), 1.B (diffuse emissions from fuels), 2 (industrial processes) and 5 (waste and wastewater treatment) projected development of the activity rates is based on the with existing measures scenario (MMS=WEM) of the ‘Treibhausgas-Projektion 2024 für Deutschland’. The MMS of the 2024 GHG emission projections for Germany includes all climate protection-relevant measures and instruments adopted by July 31, 2023. In the scenario “with measures” (WM), for the majority of the emission sources in the sectors 1.A.1 (energy industry), 1.A.2 (manufacturing industry), 1.A.4 (other combustion systems), 1.A.5 (military), 1.B (diffuse emissions from fuels), 2 (industrial processes) and 5 (waste and wastewater treatment) projected development of the activity rates is based on the with existing measures scenario (MMS=WEM) of the ‘Treibhausgas-Projektion 2024 für Deutschland’. The MMS of the 2024 GHG emission projections for Germany includes all climate protection-relevant measures and instruments adopted by July 31, 2023.
  
-In contrast to this comprehensive projection of activity data, transport emissions are calculated using the TREMOD model ("Transport Emission Model"). To estimate the future development of transport-related energy consumption and emissions, a trend scenario up to 2050 was developed, which is updated annually. Version 6.53 of TREMOD formed the basis for the current emission projections (see Allekotte et al., 2024((https://www.umweltbundesamt.de/publikationen/aktualisierung-tremodtremod-mm-ermittlung-der))). Therefore, road transport measures from the WAM scenario of the German NAPCP 2023((https://iir.umweltbundesamt.de/2023/general/projections/wam-scenario)), including the expansion of the truck toll system and a package of measures to promote electromobility, which have since been implemented, become part of the trend scenario. Beyond the trend scenario, findings from ongoing work for the upcoming HBEFA 5.1 update (Handbook of Emission Factors for Road Transport((https://www.hbefa.net/))), such as an increase in the implied emission factors for trucks and coaches with Euro V and VI due to defective or manipulated exhaust aftertreatment systems were considered((https://ermes-group.eu/sites/default/files/2024-12/1.2_Hausberger.pdf)) in the current WM scenario. In addition, the introduction of Euro 7 on the basis of Regulation (EU) 2024/1257 was considered in the WM scenario, leading to further decline of implied emission factors of the fleet, especially beyond 2030. Furthermore, assumptions about emissions from road abrasion as well as tyre and brake wear from electrically driven mileage were included according to EMEP/EEA air pollutant emission inventory guidebook 2023((https://www.eea.europa.eu/en/analysis/publications/emep-eea-guidebook-2023)). In order to reflect the Euro 7 Regulation also regarding particle emissions from tyre and brake wear the emission factors of the historical emissions were further adjusted for the emission projections.+In contrast to this comprehensive projection of activity data, transport emissions are calculated using the TREMOD model ("Transport Emission Model"). To estimate the future development of transport-related energy consumption and emissions, a trend scenario up to 2050 was developed, which is updated annually. Version 6.53 of TREMOD formed the basis for the current emission projections (see Allekotte et al., 2024((https://www.umweltbundesamt.de/publikationen/aktualisierung-tremodtremod-mm-ermittlung-der))). Therefore, road transport measures from the WAM scenario of the German NAPCP 2023((https://iir.umweltbundesamt.de/2023/general/projections/wam-scenario)), including the expansion of the truck toll system and a package of measures to promote electromobility, which have since been implemented, become part of the trend scenario. Beyond the trend scenario, findings from ongoing work for the upcoming HBEFA 5.1 update (Handbook of Emission Factors for Road Transport((https://www.hbefa.net/))), such as an increase in the implied emission factors for trucks and coaches with Euro V and VI due to defective or manipulated exhaust aftertreatment systems were considered((https://ermes-group.eu/sites/default/files/2024-12/1.2_Hausberger.pdf)) in the current WM scenario. In addition, the introduction of Euro 7 on the basis of Regulation (EU) 2024/1257 was considered in the WM scenario, leading to further decline of implied emission factors of the fleet, especially beyond 2030. Those additional assumptions are documented in Allekotte et al. (2025)((not yet published, (Link will be added as soon as the report is published.) )). Furthermore, assumptions about emissions from road abrasion as well as tyre and brake wear from electrically driven mileage were included according to EMEP/EEA air pollutant emission inventory guidebook 2023((https://www.eea.europa.eu/en/analysis/publications/emep-eea-guidebook-2023)). In order to reflect the Euro 7 Regulation also regarding particle emissions from tyre and brake wear the emission factors of the historical emissions were further adjusted for the emission projections.
  
 The projection for the agricultural sector (NFR 3) was created by the Thünen Institute (TI) using the py-GAS-EM reporting model twofold, once based on the inventory submission 2024 and the MMS (WEM, with existing measures) of the “Treibhausgas-Projektionen 2024 für Deutschland” and once based on the current inventory submission 2025 and the MMS (WEM, with existing measures) of the “Treibhausgas-Projektionen 2025 für Deutschland”((see chapter 6 for agriculture: https://www.umweltbundesamt.de/sites/default/files/medien/11850/publikationen/projektionen-2025-zentrale-annahmen.pdf)). For both projections, the most important input data for the calculation of the agricultural emissions (animal numbers, animal performance, mineral fertilizer use) were derived for the first time using the CAPRI model, based on the current Thünen-Baseline 2024-2034 (2024)((https://literatur.thuenen.de/digbib_extern/dn068888.pdf)). Further assumptions for the sector agriculture were assumed as in the WM scenario of the German NAPCP 2023 and are described below for the year 2030. The projection for the agricultural sector (NFR 3) was created by the Thünen Institute (TI) using the py-GAS-EM reporting model twofold, once based on the inventory submission 2024 and the MMS (WEM, with existing measures) of the “Treibhausgas-Projektionen 2024 für Deutschland” and once based on the current inventory submission 2025 and the MMS (WEM, with existing measures) of the “Treibhausgas-Projektionen 2025 für Deutschland”((see chapter 6 for agriculture: https://www.umweltbundesamt.de/sites/default/files/medien/11850/publikationen/projektionen-2025-zentrale-annahmen.pdf)). For both projections, the most important input data for the calculation of the agricultural emissions (animal numbers, animal performance, mineral fertilizer use) were derived for the first time using the CAPRI model, based on the current Thünen-Baseline 2024-2034 (2024)((https://literatur.thuenen.de/digbib_extern/dn068888.pdf)). Further assumptions for the sector agriculture were assumed as in the WM scenario of the German NAPCP 2023 and are described below for the year 2030.
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 ===== General assumptions ===== ===== General assumptions =====
  
-The emission inventory aims to record the true emissions of all German emission sources. For emission projections the future emission sources are often not yet existing and true emissions cannot be measured already. Emission projections for power plants, for example, are therefore estimated using regulatory limit values. Because emission limit values in the 13<sup>th</sup> BImSchV and in the accompanying BAT conclusions are usually given in mg/Nm<sup>3</sup>, a conversion into kg/TJ is necessary to multiply emission factors with activity rates (fuel use). Table 1 shows an example of the conversion factors for NO<sub>X</sub> (Rentz et al., 2002)((Rentz, O., Karl, U., Peter. H. (2002): Determination and evaluation of emission factors for combustion installations in Germany for the years 1995, 2000 and 2010, on behalf of the German Environment Agency (UBA), Project-Nr.299 43 142.)) which are used to convert mg/Nm<sup>3</sup> into kg/TJ for the regulations under consideration. For each relevant pollutant, a fuel-specific conversion factor is given, taking into account the reference oxygen content in percent.+The emission inventory aims to record the true emissions of all German emission sources. For emission projections the future emission sources are often not yet existing and true emissions cannot be measured already. Emission projections for power plants, for example, are therefore estimated using regulatory limit values. Because emission limit values in the 13<sup>th</sup> BImSchV and in the accompanying BAT conclusions are usually given in mg/Nm<sup>3</sup>, a conversion into kg/TJ is necessary to multiply emission factors with activity rates (fuel use). Table 4 shows an example of the conversion factors for NO<sub>X</sub> (Rentz et al., 2002)((Rentz, O., Karl, U., Peter. H. (2002): Determination and evaluation of emission factors for combustion installations in Germany for the years 1995, 2000 and 2010, on behalf of the German Environment Agency (UBA), Project-Nr.299 43 142.)) which are used to convert mg/Nm<sup>3</sup> into kg/TJ for the regulations under consideration. For each relevant pollutant, a fuel-specific conversion factor is given, taking into account the reference oxygen content in percent.
  
  
-__Table 1: Fuel-specific conversion factors for air pollutants according to Rentz et al. (2002)__+__Table 4: Fuel-specific conversion factors for air pollutants according to Rentz et al. (2002)__
 ^  Pollutant ^  Fuel         ^  Reference oxygen content 3 % ^  Reference oxygen content 6 % ^  Reference oxygen content 11 %  ^  Reference oxygen content 15 %  ^ ^  Pollutant ^  Fuel         ^  Reference oxygen content 3 % ^  Reference oxygen content 6 % ^  Reference oxygen content 11 %  ^  Reference oxygen content 15 %  ^
 | NO<sub>X</sub> | Hard coal |       | 2.75        |                        | | | NO<sub>X</sub> | Hard coal |       | 2.75        |                        | |