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appendices:appendix5_additional_information [2025/04/08 14:30] – [5.2.1 The EDGAR AP Inventory] mielkeappendices:appendix5_additional_information [2026/04/13 12:36] (current) – [5.3.1 The EDGAR AP Inventory] mielke
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 <figure EDGARDATA> <figure EDGARDATA>
-{{ :appendices:iir_figure3.jpg?direct&1000 | The upper images show EDGAR time series data plotted versus the reported inventory data of Germany. The lowermost image illustrates the correlation between each of the reported time-series with the respective EDGAR data}}+{{ :appendices:edgar_ii2026_fig.jpg?direct&1000 | The upper images show EDGAR time series data plotted versus the reported inventory data of Germany. The lowermost image illustrates the correlation between each of the reported time-series with the respective EDGAR data}}
 <caption>The upper images show EDGAR time series data plotted versus the reported inventory data of Germany. The lowermost image illustrates the correlation between each of the reported time-series with the respective EDGAR data.  <caption>The upper images show EDGAR time series data plotted versus the reported inventory data of Germany. The lowermost image illustrates the correlation between each of the reported time-series with the respective EDGAR data. 
 </caption> </caption>
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 <figure CAMSDATA> <figure CAMSDATA>
-{{ :appendices:iir_figure_eac4.jpg?direct&1000 | The upper images show yearly aggregated CAMS time series data plotted versus the reported inventory data of Germany. The lowermost image illustrates the correlation between each of the reported time-series with the respective CAMS data. }}+{{ :appendices:cams_iir2026_fig.jpg?direct&1000 | The upper images show yearly aggregated CAMS time series data plotted versus the reported inventory data of Germany. The lowermost image illustrates the correlation between each of the reported time-series with the respective CAMS data. }}
 <caption>The upper images show yearly aggregated CAMS time series data plotted versus the reported inventory data of Germany. The lowermost image illustrates the correlation between each of the reported time-series with the respective CAMS data.  <caption>The upper images show yearly aggregated CAMS time series data plotted versus the reported inventory data of Germany. The lowermost image illustrates the correlation between each of the reported time-series with the respective CAMS data. 
 </caption> </caption>
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 <figure PRTRAPDATA> <figure PRTRAPDATA>
-{{ :appendices:figure_aps_prtr.jpg?direct&1000 | The upper images show yearly time series data for air-pollutants extracted from the PRTR database plotted versus the reported inventory data of Germany. The lowermost image illustrates the correlation between each of the reported time-series with the respective AP species from the PRTR data.  }}+{{ :appendices:prtr_2026_iir_ap.jpg ? direct&1000 | The upper images show yearly time series data for air-pollutants extracted from the PRTR database plotted versus the reported inventory data of Germany. The lowermost image illustrates the correlation between each of the reported time-series with the respective AP species from the PRTR data.  }}
 <caption>The upper images show yearly time series data for air-pollutants extracted from the PRTR database plotted versus the reported inventory data of Germany. The lowermost image illustrates the correlation between each of the reported time-series with the respective AP species from the PRTR data.  <caption>The upper images show yearly time series data for air-pollutants extracted from the PRTR database plotted versus the reported inventory data of Germany. The lowermost image illustrates the correlation between each of the reported time-series with the respective AP species from the PRTR data. 
 </caption> </caption>
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 <figure PRTRHMDATA> <figure PRTRHMDATA>
-{{ :appendices:figure_hm_prtr.jpg?direct&1000 |  }}+{{ :appendices:prtr_hm_2026.jpg ?direct&1200 |  }}
 <caption>The upper images show yearly time series data for heavy metals extracted from the PRTR database plotted versus the reported inventory data of Germany. The lowermost image illustrates the correlation between each of the reported time-series with the respective HM species from the PRTR data.  <caption>The upper images show yearly time series data for heavy metals extracted from the PRTR database plotted versus the reported inventory data of Germany. The lowermost image illustrates the correlation between each of the reported time-series with the respective HM species from the PRTR data. 
 </caption> </caption>
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 <figure CORRDATA> <figure CORRDATA>
-{{:appendices:corcoeff.png?direct&800|Alt-Text}}+{{:appendices:corrcoeff_2026_iir_corrcoeff.jpg ?direct&600|Alt-Text}}
 <caption>Here the tabulated results for the correlation analysis between the individual datasets and the respective reported emissions time series are shown as individual blocks.  <caption>Here the tabulated results for the correlation analysis between the individual datasets and the respective reported emissions time series are shown as individual blocks. 
 </caption> </caption>
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 ==== 5.4.1 The EDGAR Inventory ==== ==== 5.4.1 The EDGAR Inventory ====
  
-The EDGAR inventory usually is in good agreement with the national inventory data as shown in figure {{:appendices:edgar_figure53.jpg?linkonly| figure 3}}. Close, almost perfect matches of the EDGAR national totals with the reported inventory data can be found in case of SO<sub>2</sub>, NMVOC, NO<sub>2</sub>, PM<sub>2.5</sub> and PM<sub>10</sub>. Slight deviations with a convergence around 2015 exist for CO and black carbon. Ammonia data from EDGAR are considerably higher than the reported national totals (~200 kt difference). This needs to be further investigated in future disaggregated, detailed analysis, which is not offered in this report, yet. The scatterplot shows similar exceptional correlations between the EDGAR data and the reported national totals of Germany as shown in the lowermost figure of  +The EDGAR inventory usually is in good agreement with the national inventory data as shown in figure {{:appendices:iir_figure3.jpg?linkonly| figure 3}}. Close, almost perfect matches of the EDGAR national totals with the reported inventory data can be found in case of SO<sub>2</sub>, NMVOC, NO<sub>2</sub>, PM<sub>2.5</sub> and PM<sub>10</sub>. Slight deviations with a convergence around 2015 exist for CO. Ammonia data from EDGAR are considerably higher than the reported national totals (~200 kt difference). This needs to be further investigated in future disaggregated, detailed analysis, which is not offered in this report, yet. The scatterplot shows similar exceptional correlations between the EDGAR data and the reported national totals of Germany as shown in the lowermost figure of  
-{{:appendices:edgar_figure53.jpg?linkonly| figure 3}}. The correlation values for the individual time series of the EDGAR data towards the inventory data can be found in {{:appendices:correlations_figure58.jpg?linkonly| figure 8}}. Here correlation values are relatively high above 0.8-0.9 with the already discussed exception of the ammonia data, as shown in {{:appendices:edgar_figure53.jpg?linkonly| figure 3}}.+{{:appendices:iir_figure3.jpg?linkonly| figure 3}}. The correlation values for the individual time series of the EDGAR data towards the inventory data can be found in {{:appendices:corcoeff.png?linkonly| figure 8}}. Here correlation values are relatively high above 0.8-0.9 with the already discussed exception of the ammonia data, as shown in {{:appendices:iir_figure3.jpg?linkonly| figure 3}}.
  
 ==== 5.4.2 The CAMS EAC4 Data ==== ==== 5.4.2 The CAMS EAC4 Data ====
  
-The CAMS EAC4 data shows very high correlation values to the reported national totals as shown in {{:appendices:corrcoeff..png?linkonly| figure 8}}., all correlation values are above 0.9 with the exception of formaldehyde (HCHO). The low values here for formaldehyde are compared to the much higher national total values for NMVOC. This shows that formaldehyde on its own is not a sufficient proxy for NMVOC in case of Germany. +The CAMS EAC4 data shows very high correlation values to the reported national totals as shown in {{:appendices:corcoeff.png?linkonly| figure 8}}., all correlation values are above 0.9 with the exception of formaldehyde (HCHO). The low values here for formaldehyde are compared to the much higher national total values for NMVOC. This shows that formaldehyde is anticorelated with NMVOC in case of Germany.
- +
-PM<sub>2.5</sub> and PM<sub>10</sub> values of the EAC4 data show a good agreement to the national totals of Germany as shown in figure {{:appendices:iir_figure_eac4.jpg?linkonly| figure 4}}. The higher values of the CAMS NO<sub>2</sub>  data and the reported NO<sub>2</sub> data in the inventory are due to the fact that the here shown CAMS NO<sub>2</sub> (ECMWF, 2024)[(ECMWF2024)] data has been compiled as the sum of the total columns of the CAMS EAC4 NO, NO<sub>2</sub> and HNO<sub>3</sub> data product. The NO2 data alone or even the sum of all NO<sub>x</sub> total column products would yield significantly lower values as reported in the national totals of Germany. Only the sum of all NO<sub>x</sub> related chemical species yields a value, which is close to the reported national totals of the inventory.+
  
 +PM<sub>2.5</sub> and PM<sub>10</sub> values of the EAC4 data show a good agreement to the trend of the national totals of Germany as shown in figure {{:appendices:iir_figure_eac4.jpg?linkonly| figure 4}}, however, both species show an offset. 
  
  
 ==== 5.4.3 The Pollution Release and Transfer Register ==== ==== 5.4.3 The Pollution Release and Transfer Register ====
  
-Data for PM<sub>10</sub>, NO<sub>2</sub> and SO<sub>10</sub> are well correlated with the reported emissions with correlation values above 0.9 as shown in {{:appendices:correlations_figure58.jpg?linkonly| figure 8}}. This is also shown in the scatterplots and trend diagrams of {{:appendices:prtr_ap_plots_figure55.jpg?linkonly| figure 5}}. NMVOC and CO show moderate correlation values above 0.7, whilst ammonia data shows almost no correlation. For the heavy metals As and Hg correlation values above 0.8 are shown in {{:appendices:correlations_figure58.jpg?linkonly| figure 8}}, whilst only moderate correlation values exist for Pb and Ni (around 0.5), whilst Cu, Cr, Zn and Ni show almost no correlation, which is also visible in the scatter plot of {{:appendices:prtr_hm_plots_figure56.jpg?linkonly| figure 6}}. +Data for PM<sub>10</sub>, NO<sub>2</sub> and SO<sub>2</sub> are well correlated with the reported emissions with correlation values above 0.9 as shown in {{:appendices:correlations_figure58.jpg?linkonly| figure 8}}. This is also shown in the scatterplots and trend diagrams of {{:appendices:prtr_ap_plots_figure55.jpg?linkonly| figure 5}}. NMVOC and CO show moderate correlation values above 0.5. For the heavy metals As and Hg correlation values above 0.8 are shown in {{:appendices:corcoeff.png?linkonly| figure 8}}, whilst only moderate correlation values exist for Pb and Ni (around 0.5), whilst Cu, Cr, Zn show almost no correlation, which is also visible in the scatter plot of {{:appendices:prtr_hm_plots_figure56.jpg?linkonly| figure 6}}. 
  
  
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 [(CrippaMetal2023>Crippa, M. et al. (2023) ‘EDGAR v8.1 Global Air Pollutant Emissions’. Available at: https://edgar.jrc.ec.europa.eu/index.php/dataset_ap81 (Accessed: 27 February 2025).)] [(CrippaMetal2023>Crippa, M. et al. (2023) ‘EDGAR v8.1 Global Air Pollutant Emissions’. Available at: https://edgar.jrc.ec.europa.eu/index.php/dataset_ap81 (Accessed: 27 February 2025).)]
-[(ECMWF2024>CAMS global reanalysis (EAC4) monthly averaged fields, Copernicus ADS. Available at: https://ads.atmosphere.copernicus.eu/cdsapp#!/dataset/cams-global-reanalysis-eac4-monthly?tab=overview)] (Accessed: 27 February 2022).)]+[(ECMWF2024>CAMS global reanalysis (EAC4) monthly averaged fields, Copernicus ADS. Available at: https://ads.atmosphere.copernicus.eu/cdsapp#!/dataset/cams-global-reanalysis-eac4-monthly?tab=overview)] (Accessed: 27 February 2026).)]
 [(HausmannKetal2021>Hausmann, K., Zagorski, A. and Mielke, C. (2021) Convert ePRTR data to CLRTAP LPS submission. Umweltbundesamt (EPA Germany), V1.6 - Emission situation. Available at: https://gitlab.opencode.de/uba-emsit/reporting/eprtr2lps (Accessed: 24 September 2024).)] [(HausmannKetal2021>Hausmann, K., Zagorski, A. and Mielke, C. (2021) Convert ePRTR data to CLRTAP LPS submission. Umweltbundesamt (EPA Germany), V1.6 - Emission situation. Available at: https://gitlab.opencode.de/uba-emsit/reporting/eprtr2lps (Accessed: 24 September 2024).)]
 [(InnessAetal2019>Inness, A. et al. (2019) ‘The CAMS reanalysis of atmospheric composition’, Atmospheric Chemistry and Physics, 19(6), pp. 3515–3556. doi:10.5194/acp-19-3515-2019.)] [(InnessAetal2019>Inness, A. et al. (2019) ‘The CAMS reanalysis of atmospheric composition’, Atmospheric Chemistry and Physics, 19(6), pp. 3515–3556. doi:10.5194/acp-19-3515-2019.)]
-[(PattersonTetal2022>Patterson, T. and Kelso, V. (2022) Natural Earth - Free vector and raster map data at 1:10m, 1:50m, and 1:110m scales. Available at: https://www.naturalearthdata.com/ (Accessed: 8 January 2022).)] +[(PattersonTetal2022>Patterson, T. and Kelso, V. (2022) Natural Earth - Free vector and raster map data at 1:10m, 1:50m, and 1:110m scales. Available at: https://www.naturalearthdata.com/ (Accessed: 8 January 2026).)] 
-[(RomanoDetal2019>Romano, D. et al. (2019) 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories — IPCC General Guidance and Reporting. General Guidance and Reporting Volume 1. IPCC. Available at: https://www.ipcc.ch/report/2019-refinement-to-the-2006-ipcc-guidelines-for-national-greenhouse-gas-inventories/ (Accessed: 8 January 2022).)]+[(RomanoDetal2019>Romano, D. et al. (2019) 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories — IPCC General Guidance and Reporting. General Guidance and Reporting Volume 1. IPCC. Available at: https://www.ipcc.ch/report/2019-refinement-to-the-2006-ipcc-guidelines-for-national-greenhouse-gas-inventories/ (Accessed: 8 January 2026).)]
 [(SavricBetal2019>Šavrič, B., Patterson, T. and Jenny, B. (2019) ‘The Equal Earth map projection’, International Journal of Geographical Information Science, 33(3), pp. 454–465. doi:10.1080/13658816.2018.1504949.)] [(SavricBetal2019>Šavrič, B., Patterson, T. and Jenny, B. (2019) ‘The Equal Earth map projection’, International Journal of Geographical Information Science, 33(3), pp. 454–465. doi:10.1080/13658816.2018.1504949.)]
 [(SchroederWetal2019>Schröder, W. et al. (2019) ‘Nutzung von Bioindikationsmethoden zur Bestimmung und Regionalisierung von Schadstoffeinträgen für eine Abschätzung des atmosphärischen Beitrags zu aktuellen Belastungen von Ökosystemen’, Abschlußbericht, (91/2019), p. 189.)] [(SchroederWetal2019>Schröder, W. et al. (2019) ‘Nutzung von Bioindikationsmethoden zur Bestimmung und Regionalisierung von Schadstoffeinträgen für eine Abschätzung des atmosphärischen Beitrags zu aktuellen Belastungen von Ökosystemen’, Abschlußbericht, (91/2019), p. 189.)]