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general:projections:calculation_documentation [2025/04/03 13:01] – eisoldgeneral:projections:calculation_documentation [2025/04/24 11:12] (current) – eisold
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 The NMVOC emissions from NFR sector 2.D.3, which includes emissions resulting from the use of solvents and solvent-containing products, as well as their manufacturing, are not calculated using activity rates and emission factors within the inventory. Instead, a separate model developed and expanded steadily over the past 15 years primarily by the Institute for Environmental Strategies (Ökopol GmbH) is utilized to calculate these emissions, and the results are imported into the inventory database. This model also provides emission projections based on economic forecasts specific to certain branches of industry. These economic projections were last updated for the emissions projections reported in 2023 using the Prognos report (2019) titled “Deutschland Report 2025 | 2035 | 2045”. The methodology for updating the NMVOC inventory and projections is detailed in Zimmermann and Memelink (2023((https://www.umweltbundesamt.de/publikationen/aktualisierung-des-deutschen-inventars-fuer-nmvoc-0))). The NMVOC emissions from NFR sector 2.D.3, which includes emissions resulting from the use of solvents and solvent-containing products, as well as their manufacturing, are not calculated using activity rates and emission factors within the inventory. Instead, a separate model developed and expanded steadily over the past 15 years primarily by the Institute for Environmental Strategies (Ökopol GmbH) is utilized to calculate these emissions, and the results are imported into the inventory database. This model also provides emission projections based on economic forecasts specific to certain branches of industry. These economic projections were last updated for the emissions projections reported in 2023 using the Prognos report (2019) titled “Deutschland Report 2025 | 2035 | 2045”. The methodology for updating the NMVOC inventory and projections is detailed in Zimmermann and Memelink (2023((https://www.umweltbundesamt.de/publikationen/aktualisierung-des-deutschen-inventars-fuer-nmvoc-0))).
  
-In a more recent project, Zimmermann et al. (2025((not yet published (Link will be added as soon as the report is published.) ))) conducted a comprehensive review of the previous methods used for projecting NMVOC emissions in the sectors of printing (NFR 2.D.3.h) and coating applications (NFR 2.D.3.d). They developed new projection methods for the years 2025 to 2050. The updates made for the individual SNAP codes can be summarised as follows:+In a more recent project, Zimmermann et al. (2025((https://www.umweltbundesamt.de/publikationen/nmvoc-projektionen))) conducted a comprehensive review of the previous methods used for projecting NMVOC emissions in the sectors of printing (NFR 2.D.3.h) and coating applications (NFR 2.D.3.d). They developed new projection methods for the years 2025 to 2050. The updates made for the individual SNAP codes can be summarised as follows:
  
 SNAP 60101 demonstrated a clear correlation with automobile production. A forecast for production in Germany has been established based on EU production forecasts and used in the emission projections. For SNAP 60102, emissions showed a correlation with vehicle fleet size from 2015 onward. Forecast data on the vehicle population was taken from the study (Adolf et al., 2014((https://www.prognos.com/sites/default/files/2021-01/140900_prognos_shell_studie_pkw-szenarien2040.pdf ))) and used for the projection. SNAP 60103 showed that employee numbers and annual construction output correlated with emissions from 2018 on. Projections have been implemented using data from BMAS (2021((https://www.bmas.de/SharedDocs/Downloads/DE/Publikationen/Forschungsberichte/fb526-3-aktualisierte-bmas-prognose-digitalisierte-arbeitswelt.pdf?__blob=publicationFile&v=2))) and the Prognos report (2019). For SNAP 60104, a correction factor to the "population development" indicator has been applied to update projections. SNAP 60105 showed a significant correlation with the completion of commercial buildings. Due to the lack of specific forecasts for this indicator, automotive production data (from SNAP 60101) has been used as an alternative. SNAP 60106 faced challenges in identifying suitable indices for emissions. A weak correlation with boat and shipbuilding turnover has been noted and additional corrections to enhance projection accuracy have been applied. In the case of SNAP 60107, no meaningful correlations were established, prompting to create emission projections based on trend extrapolations. Future investigations into specific SNAP areas will yield better methodologies. SNAP 60108 required careful analysis of several sub-areas. No correlation of the emissions to economic (or other) variables could be determined for several sub-areas, which is why some of the emissions were updated using trend progression. In the future, it may be useful to take a closer look at the individual areas of the SNAP code that are particularly relevant to emissions and the developments taking place in these areas to identify suitable alternative approaches for creating projections. No correlation could be established between SNAP 60109 and the indices used to date. However, with the "Other expenditure, inflation-adjusted" index, an alternative suitable forecast index could be used for the projection. SNAP 60101 demonstrated a clear correlation with automobile production. A forecast for production in Germany has been established based on EU production forecasts and used in the emission projections. For SNAP 60102, emissions showed a correlation with vehicle fleet size from 2015 onward. Forecast data on the vehicle population was taken from the study (Adolf et al., 2014((https://www.prognos.com/sites/default/files/2021-01/140900_prognos_shell_studie_pkw-szenarien2040.pdf ))) and used for the projection. SNAP 60103 showed that employee numbers and annual construction output correlated with emissions from 2018 on. Projections have been implemented using data from BMAS (2021((https://www.bmas.de/SharedDocs/Downloads/DE/Publikationen/Forschungsberichte/fb526-3-aktualisierte-bmas-prognose-digitalisierte-arbeitswelt.pdf?__blob=publicationFile&v=2))) and the Prognos report (2019). For SNAP 60104, a correction factor to the "population development" indicator has been applied to update projections. SNAP 60105 showed a significant correlation with the completion of commercial buildings. Due to the lack of specific forecasts for this indicator, automotive production data (from SNAP 60101) has been used as an alternative. SNAP 60106 faced challenges in identifying suitable indices for emissions. A weak correlation with boat and shipbuilding turnover has been noted and additional corrections to enhance projection accuracy have been applied. In the case of SNAP 60107, no meaningful correlations were established, prompting to create emission projections based on trend extrapolations. Future investigations into specific SNAP areas will yield better methodologies. SNAP 60108 required careful analysis of several sub-areas. No correlation of the emissions to economic (or other) variables could be determined for several sub-areas, which is why some of the emissions were updated using trend progression. In the future, it may be useful to take a closer look at the individual areas of the SNAP code that are particularly relevant to emissions and the developments taking place in these areas to identify suitable alternative approaches for creating projections. No correlation could be established between SNAP 60109 and the indices used to date. However, with the "Other expenditure, inflation-adjusted" index, an alternative suitable forecast index could be used for the projection.