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sector:agriculture:start [2021/12/23 07:13] – [Short description] doeringsector:agriculture:start [2022/09/19 08:16] (current) – Fix link hausmann
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 ====== Chapter 5 - NFR 3 - Agriculture (OVERVIEW) ====== ====== Chapter 5 - NFR 3 - Agriculture (OVERVIEW) ======
  
-Emissions occurring in the agricultural sector in Germany derive from manure management (NFR 3.B), agricultural soils (NFR 3.D) and agriculture other (NFR 3.I).  +Emissions occurring in the agricultural sector in Germany derive from manure management (NFR 3.B), agricultural soils (NFR 3.D) and agriculture other (NFR 3.I). Germany does not report emissions in  category field burning (NFR 3.F) (key note: NO), because burning of agricultural residues is prohibited by law (see Vos et al., 2022)((Vos C, Rösemann C, Haenel H-D, Dämmgen U, Döring U, Wulf S, Eurich-Menden B, Freibauer A, Döhler H, Schreiner C, Osterburg BFuß R (2022) Calculations of gaseous and particulate emissions from German agriculture 1990 – 2020 Report on methods and data (RMD) Submission 2022. Braunschweig: Johann Heinrich von Thünen-Institut, 452 p, Thünen Rep 91, DOI:10.3220/REP1646725833000. https://www.thuenen.de/de/fachinstitute/agrarklimaschutz/arbeitsbereiche/emissionsinventare)).
- +
-Germany does not report emissions in  category field burning (NFR 3.F) (key note: NO), because burning of agricultural residues is prohibited by law (see Vos et al., 2022 ((VosC., Rösemann C., Haenel H-D., Dämmgen U., Döring U., Wulf S., Eurich-Menden B., Freibauer A., Döhler H., Schreiner C., Osterburg B. & FußR(2022)Calculations of gaseous and particulate emissions from German Agriculture 1990 –2020Report on methods and data (RMD)Submission 2022. Thünen Report (in preparation). https://www.thuenen.de/de/ak/arbeitsbereiche/emissionsinventare/)).+
  
 ^  NFR-Code    Name of Category                                                                       ^ ^  NFR-Code    Name of Category                                                                       ^
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 Emissions occurring in the agricultural sector in Germany derive from manure management (NFR 3.B), agricultural soils (NFR 3.D) and agriculture other (NFR 3.I). Emissions occurring in the agricultural sector in Germany derive from manure management (NFR 3.B), agricultural soils (NFR 3.D) and agriculture other (NFR 3.I).
-Germany did not allocate emissions to category field burning (NFR 3.F) (key note: NO), because burning of agricultural residues is prohibited by law (see Rösemann et al., 2021)).+Germany does not report emissions in category field burning (NFR 3.F) (key note: NO), because burning of agricultural residues is prohibited by law (see Vos et al., 2022).
  
 The pollutants reported are: The pollutants reported are:
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 HCB emissions of pesticide use contributed 22.1 % to the total German emissions. HCB emissions of pesticide use contributed 22.1 % to the total German emissions.
  
-===== Recalculations and reasons =====+ 
 +====Mitigation measures==== 
 + 
 +The agricultural inventory model can represent several abatement measures for emissions of NH<sub>3</sub> and particles. The measures comprise: 
 + 
 +  * changes in animal numbers and amount of applied fertilizers  
 + 
 +  * air scrubbing techniques: yearly updated data on frequencies of air scrubbing facilities and the removal efficiency are provided by KTBL (Kuratorium für Technik und Bauwesen in der Landwirtschaft / Association for Technology and Structures in Agriculture). The average removal efficiency of NH<sub>3</sub> is 80 % for swine and 70 % for poultry, while for TSP and PM<sub>10</sub> the rates are set to 90 % and for PM<sub>2.5</sub> to 70 % for both animal categories. For swine two types of air scrubbers are distinguished: certified systems that remove both NH<sub>3</sub> and particles, and non-certified systems that remove only particles reliably. 
 + 
 +  * reduced raw protein content in feeding of fattening pigs: the german animal nutrition association (DVT, Deutscher Verband Tiernahrung e.V.) provides data on the raw protein content of fattening pig feed, therefore enabling the inventory to depict the changes in N-excretions over the time series. The time series is calibrated using data from official and representative surveys conducted by the Federal Statistical Office. 
 + 
 +  * reduced raw protein content in feeding and feed conversion rates of broilers: the German animal nutrition association (DVT, Deutscher Verband Tiernahrung e.V.) provides data on the raw protein content of fattening broiler feed, and feed conversion rates of broilers. This makes it possible to model the changes in N-excretions over the time series. 
 + 
 +  * low emission spreading techniques of manure: official agricultural censuses survey the distribution of different manure spreading techniques and how fast organic fertilizers are incorporated into the soil. Germany uses distinct emission factors for different methods, techniques and incorporation durations. 
 + 
 +  * covering of slurry storage: agricultural censuses survey the distribution of different slurry covers. Germany uses distinct emission factors for the different covers.  
 + 
 +  * use of urease inhibitors: for urea fertilizer the German fertilizer ordinance prescribes the use of urease inhibitors or the direct incorporation into the soil from 2020 onwards. 
 + 
 +The NH<sub>3</sub> emission factor for urea fertilizers is therefore reduced by 70% from 2020 onwards, according to Bittman et al. (2014, Table 15)((Bittman, S., Dedina, M., Howard C.M., Oenema, O., Sutton, M.A., (eds) (2014): Options for Ammonia Mitigation. Guidance from the UNECE task Force on Reactive Nitrogen. Centre for Ecology and Hydrology, Edinburgh, UK.)). 
 + 
 +For NO<sub>x</sub> and NMVOC no mitigation measures are included. 
 + 
 + 
 +===== Reasons for recalculations =====
  
  
 (see [[general:recalculations:start|Chapter 8.1 - Recalculations]]) (see [[general:recalculations:start|Chapter 8.1 - Recalculations]])
  
-The following list summarizesthe most important reasons for recalculations. Recalculations result from improvements in input data and methodologies (for details see Rösemann et al. (2021), Chapter 3.5.2).+The following list summarizes the most important reasons for recalculations. Recalculations result from improvements in input data and methodologies (for details see Vos et al. (2022), Chapter 3.5.2). 
  
-1) Dairy cows and calves: Adjustment of initial weightenergy requirements and feeding according to German expert recommendations; correction of the calculation of the TAN excretion of dairy cows.+1) Incorporation of data from the 2020 official agricultural census. This changes data on housing systemsmanure storage systems, manure application systems and cattle grazing. This results in some significant changes in the calculated emissions as far back as the year 2000 compared to the previous year's submission.
  
-2) HeifersSubdivision into dairy and slaughter heifers with different final weights; adaptation of energy requirements and feeding according to German expert recommendations.+2) Dairy cowsUpdate of milk yield and slaughter weight for the year 2019
  
-3) Male beef cattleAdjustment of feeding according to German expert recommendations; correction of the calculation of the TAN flow into manure storage.+3) HeifersMinor changes in the nutrient content of some feed ingredients.
  
-4) Male cattle > 2 yearsupdate (increase) of the amount of bedding material (straw).+4) Suckler cowsmodeling of the energy requirement and feed intake has been updated and adapted based on the dairy cow model.
  
-5) Cattle grazingThe NH<sub>3</sub> emission factors were updated according to EMEP (2019).+5) Male cattle > 2 yearsUpdate of weights from 1999 onwards.
  
-6) Sows: Update of the number of piglets per sow in 2018.+6) Sows: Update of the number of piglets per sow in 2019
  
-7) Fattening pigs and weanersUpdate of animal numbersstarting weights and final weights for 2018.+7) Fattening pigs: New data on raw protein contentash content and digestibility of feed from 1990 onwards
  
-8) All pigs except boarsUpdate of activity data of air scrubbing systems in pig housings from 2005 onwards. +8) BroilersNew data on raw protein content, ash content and digestibility of feed from 2000 onwards. Update of the national gross production of broiler meat in 2019.
  
-9) Sheep, laying hens, broilers, pullets: Update of the NH<sub>3</sub> emission factors for manure storage according to EMEP (2019)+9) Turkeys: Update of input data (slaughter weight, weight gain and feed conversion coefficient) for the years 2017-2019.
  
-10) BroilersUpdate of the national gross production of broiler meat in 2018; update of activity data of air scrubbing systems in broiler housings from 2013 onwards.+10) Geeseupdate (increase) of the amount of bedding material (straw) and update (increase) of N-excretions for the whole time series.
  
-11) TurkeysRecalculation of the final weights of roosters and hens 1990 to 2001.+11) Laying hensImproved interpolation of start weights and final weights for the whole time series. 
 +  
 +12) Pullets: Improved interpolation of start weights and final weights for the whole time series.
  
-12) Anaerobic digestion of animal manures: Update of activity data in all years and of the NH<sub>3</sub> emission factors for pre-storage of cattle manure and poultry manure.+13) Anaerobic digestion of animal manures: Update of activity data in all years
 +  
 +14) Mineral fertilizers: : New weighting procedure for the latest year: 2020 weighted mean from 2019 (weight 1/3) and 2020 (weight 2/3)).
  
-13) Mineral fertilizers, liming, application of ureaAnnual averaging of activity data (moving centered three-year mean for 1990 to 2018; for 2019 mean from 2018 and 2019).+15Application of sewage sludge to soilsUpdate of activity data in 2018 and 2019. Minor corrections of activity data in one federal state for the whole time series.
  
-14) Application of sewage sludge to soils: Update of activity data in 2018.+16Anaerobic digestion of energy crops: Update of activity data in 2019. 
 +  
 +17) Soils: Minor corrections of cultivated areas and yields in several years.
  
-15) Anaerobic digestion of energy cropsUpdate of activity data in 2018.+18PesticidesRecalculations were made for the complete time series due to the changes and new information given by the BVL for the amount of domestic sales of the active substances Lindane (1990 – 1997), Chlorothalonil and Picloram (2019) and the maximum amount of HCB in the active substance Chlorothalonil of the FAO specification was used for the calculation in the period 2005 - 2017.
  
-16) Crop residues: Minor corrections of cultivated areas and yields in the years 1999 and 2010 through 2012. 
  
  
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 __Chart showing emission trends for main pollutants in //NFR 3 - Agriculture//:__ __Chart showing emission trends for main pollutants in //NFR 3 - Agriculture//:__
 [{{:sector:iir_nfr3.png?nolink&direct&600|NFR 3 emission trends per category}}] [{{:sector:iir_nfr3.png?nolink&direct&600|NFR 3 emission trends per category}}]
 +[{{:sector:iir_nfr3_from_2005.png?nolink&direct&600|NFR 3 emission trends per category, from 2005}}]
 __Contribution of NFR categories to the emissions/Anteile der NFR-Kategorien an den Emissionen__ __Contribution of NFR categories to the emissions/Anteile der NFR-Kategorien an den Emissionen__
-[{{:sector:cats_pollutants_inkl_transport.png?nolink&direct&600|Contribution of NFR categories to the emissions}}]+[{{:sector:cats_pollutants_incl_transport.png?nolink&direct&600|Contribution of NFR categories to the emissions}}]
  
 ===== Specific QA/QC procedures for the agriculture sector===== ===== Specific QA/QC procedures for the agriculture sector=====
  
 Numerous input data were checked for errors resulting from erroneous transfer between data sources and the tabular database used for emission calculations. Numerous input data were checked for errors resulting from erroneous transfer between data sources and the tabular database used for emission calculations.
-The German IEFs and other data used for the emission calculations were compared with EMEP default values and data of other countries (see Rösemann et al. (2021)). +The German IEFs and other data used for the emission calculations were compared with EMEP default values and data of other countries (see Vos et al., 2022). 
-Changes of data and methodologies are documented in detail (see  Rösemann et al. 2021, Chapter 3.5.2).+Changes of data and methodologies are documented in detail (see  Vos et al. 2022, Chapter 3.5.2).
  
-A comprehensive review of the emission calculations was carried out by comparisons with the results of Submission 2020 and by plausibility checks.+A comprehensive review of the emission calculations was carried out by comparisons with the results of Submission 2021 and by plausibility checks.
  
-Once emission calculations with the German inventory model GAS-EM are completed for a specific submission, activity data (AD) and implied emission factors (IEFs) are transferred to the CSE database (Central System of Emissions) to be used to calculate the respective emissions within the CSE. These CSE emission results are then cross-checked with the emission results obtained by GAS-EM.+Once emission calculations with the German inventory model Py-GAS-EM are completed for a specific submission, activity data (AD) and implied emission factors (IEFs) are transferred to the CSE database (Central System of Emissions) to be used to calculate the respective emissions within the CSE. These CSE emission results are then cross-checked with the emission results obtained by Py-GAS-EM.
  
 Model data have been verified in the context of a project by external experts (Zsolt Lengyel, Verico SCE). Results show that input data are consistent with other data sources (Eurostat, Statistisches Bundesamt / Federal Statistical Office) and that the performed calculations are consistently and correctly applied in line with the methodological requirements. Model data have been verified in the context of a project by external experts (Zsolt Lengyel, Verico SCE). Results show that input data are consistent with other data sources (Eurostat, Statistisches Bundesamt / Federal Statistical Office) and that the performed calculations are consistently and correctly applied in line with the methodological requirements.
  
-Furthermore, in addition to UNFCCC, UNECE and NEC reviews, the GAS-EM model is continuously validated by experts of KTBL (Kuratorium für Technik und Bauwesen in der Landwirtschaft, Association for Technology and Structures in Agriculture) and the EAGER group (European Agricultural Gaseous Emissions Inventory Researchers Network).+Furthermore, in addition to UNFCCC, UNECE and NEC reviews, the Py-GAS-EM model is continuously validated by experts of KTBL (Kuratorium für Technik und Bauwesen in der Landwirtschaft, Association for Technology and Structures in Agriculture) and the EAGER group (European Agricultural Gaseous Emissions Inventory Researchers Network).