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appendices:appendix5_additional_information [2025/04/08 14:43] – [5.4.2 The CAMS EAC4 Data] 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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 ==== 5.4.3 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.)]