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| sector:agriculture:start [2022/12/14 12:04] – [Mitigation measures] doering | sector:agriculture:start [2026/03/18 16:56] (current) – vosen | ||
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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 does not report emissions in category field burning (NFR 3.F) (key note: NO), because burning of agricultural residues is prohibited by law (see Rösemann | + | 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., 2026)((Vos, C., Rösemann, C., Haenel, H.-D., Dämmgen, U., Döring, U., Wulf, S., Eurich-Menden, |
| The pollutants reported are: | The pollutants reported are: | ||
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| No heavy metal emissions are reported. | No heavy metal emissions are reported. | ||
| - | In 2020 the agricultural sector emitted | + | In 2024 the agricultural sector emitted |
| - | + | ||
| - | As depicted in the diagram below, in 2021 XX % of Germany’s total NH< | + | |
| - | HCB emissions of pesticide use contributed XX % to the total German emissions. | + | |
| + | As depicted in the diagram below, in 2024 91.7 % of Germany’s total NH< | ||
| ====Mitigation measures==== | ====Mitigation measures==== | ||
| - | + | The agricultural inventory model can represent several abatement measures for emissions of NH< | |
| - | The agricultural inventory model can represent several abatement measures for emissions of NH< | + | |
| * changes in animal numbers and amount of applied fertilizers | * 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) and from the agricultural census 2020. The average removal efficiency of NH< | + | * 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) and also based on the agricultural census 2020. The average removal efficiency of NH< |
| - | * reduced raw protein content in feeding of fattening pigs: the german | + | * reduced raw protein content in feeding of fattening pigs: the German |
| - | * 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. | + | * 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 timeseries. |
| - | * low emission spreading techniques of manure: official agricultural censuses survey the distribution | + | * low emission spreading techniques of manure: official agricultural censuses survey the prevalence |
| - | * covering | + | * Depicting effects |
| - | * 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< | + | |
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| + | For NO< | ||
| - | For NO< | ||
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| (see [[general: | (see [[general: | ||
| - | The following list summarizes the most important reasons for recalculations. Recalculations result from improvements in input data and methodologies (for details see Rösemann | + | 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. (2026), Chapter 1.3). |
| + | - Adding of a transport module in the inventory model PY-GAS-EM: substrate transports to biogas plants and manure transports across district borders (NUTS 3 areas) are considered. Since manure application techniques differ between the NUTS 3 areas, this leads to slightly different NH< | ||
| + | - Mineral fertilizers: | ||
| + | - Dairy cows: N and TAN excretions are now estimated from milk yield, milk urea content and protein content of milk instead of from the modeled feed. | ||
| + | - Dairy cows: The officially recorded final milk yields for 2023 are significantly higher than the preliminary official figures used in the 2025 submission. This is due to an improved calculation method that will continue to be used in the future and which was subsequently applied for 2022. For reporting purposes a method was developed to adjust the officially recorded milk yields for the years before 2022 upwards, to achieve time series consistency. | ||
| + | - Sows: The animal category sow was subdivided into gilts and old sows, with different weights and therefore different energy requirements. In comparison with Submission 2025 the mean animal weight and energy requirements are lower in aggregate. As a consequence, | ||
| + | - Horses: Due to updated feed recommendations for heavy horses, N excretions were adjusted (increased) for the year 2020. The respective values used for Submission 2025 are still used until the year 2010; between the years 2010 and 2020, they are linearly interpolated. | ||
| + | - Deer: Due to new data for 2023, the number of animals from 2009 onwards is slightly reduced by interpolation. | ||
| + | - Dairy cows: Milk yield and slaughter weights for 2023 have been slightly corrected in the official statistics. | ||
| + | - Heifers: 2023 slaughter weights have been slightly corrected in the official statistics. | ||
| + | - Male beef cattle: In some years, slaughter ages and slaughter weights have been updated in the HIT database. | ||
| + | - Air scrubber systems pigs: new information on replaced facilities with minor effects on the number of animal places with air scrubbers in one federal state back to the year 2005. | ||
| + | - Sows: For several federal states, the number of piglets per sow for 2023 and 2019 were corrected. | ||
| + | - Fattening pigs: for several federal states growth rates, start weights and final weights for 2023 and 2019 were corrected. | ||
| + | - Broilers: Update of the national gross production of broiler meat for 2022 and 2023. | ||
| + | - Crop residues: The number of grassland cuts were updated for all years due to the introduction of a new procedure for outlier identification.. | ||
| + | - Application of sewage sludge: Replacement of extrapolated activity data in 2023 with data from the Federal Statistical Office. | ||
| + | - Anaerobic digestion: Due to the newly introduced substrate transports, the percentage of digested manure N in the total production of manure is no longer used as the input variable, but the absolute amount of N that goes into digestion. | ||
| + | - Anaerobic digestion of energy crops: dry matter input for 2023 has been updated. | ||
| + | - Imported manure: The amounts of imported manure from the Netherlands have been updated for years after 2009 in official NL statistics. This results in higher N application rates except for 2012, 2016, 2018 and 2022. | ||
| + | - Compost and digested waste: input data for 2023 has been updated. | ||
| - | 1) The results used from the 2020 agricultural census on the proportions of husbandry, storage or application methods and grazing were assumed to be true for the year 2019 and not for the year 2020 as in Submission 2022. This changes the data obtained by interpolation for the different proportions slightly, in some cases as far back as the year 2000. | ||
| - | 2) Deep bedding systems: As of the submission at hand, it is assumed that the NH3 emissions from deep litter systems are fully covered by the housing emissions and that the emission factor for storage emissions is 0. This was done because it can be assumed that in case of deep bedding systems manure will be spread immediately after removing it from the stable. This reduces the emissions from manure management while the emissions from application of manure (3.D.a.2.a) increases as more N is available for application. | ||
| - | 3) Heifers: Minor changes in the nutrient content of some feed ingredients. | ||
| - | 4) Suckler cows: modeling of the energy requirement and feed intake has been updated and adapted based on the dairy cow model. | + | ===== Visual overview ===== |
| - | 5) Male cattle > 2 years: Update of weights from 1999 onwards. | + | __Emission trends for main pollutants in //NFR 3 - Agriculture// |
| + | {{ : | ||
| + | {{ : | ||
| - | 6) Sows: Update | + | __Contribution |
| - | + | {{ :sector:iir_mp_sharesnfr_incltrans.png? | |
| - | 7) Fattening pigs: New data on raw protein content, ash content and digestibility of feed from 1990 onwards. | + | |
| - | + | ||
| - | 8) Broilers: New 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) Turkeys: Update of input data (slaughter weight, weight gain and feed conversion coefficient) for the years 2017-2019. | + | |
| - | + | ||
| - | 10) Geese: update (increase) of the amount of bedding material (straw) and update (increase) of N-excretions for the whole time series. | + | |
| - | + | ||
| - | 11) Laying hens: Improved 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. | + | |
| - | + | ||
| - | 13) Anaerobic digestion of animal manures: Update of activity data in all years. | + | |
| - | + | ||
| - | 14) Mineral fertilizers: | + | |
| - | + | ||
| - | 15) Application of sewage sludge | + | |
| - | + | ||
| - | 16) Anaerobic digestion of energy crops: Update of activity data in 2019. | + | |
| - | + | ||
| - | 17) Soils: Minor corrections of cultivated areas and yields in several years. | + | |
| - | + | ||
| - | 18) Pesticides: Recalculations 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. | + | |
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| - | ===== Visual overview ===== | + | |
| - | __Chart showing emission trends for main pollutants in //NFR 3 - Agriculture//: | + | |
| - | [{{:sector:iir_nfr3.png?nolink&direct& | + | |
| - | [{{: | + | |
| - | __Contribution | + | |
| - | [{{: | + | |
| ===== 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 Vos et al., 2026). Changes of data and methodologies are documented in detail (see Vos et al. 2026, Chapter |
| - | 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 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 | + | A comprehensive review of the emission calculations was carried out by comparisons with the results of Submission |
| - | 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. | + | 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 | + | Furthermore, |
| - | Furthermore, | ||