Last updated on 29 Aug 2019 09:29 (cf. Authors)
NFR-Code | Name of Category | Method | AD | EF | Key Category 1 | State of reporting |
---|---|---|---|---|---|---|
3.B | Manure Management | see sub-category details | ||||
consisting of / including source categories | ||||||
3.B.1.a & 3.B.1.b | Cattle | T3 (NH3), T2 (NOx, TSP, PM10, PM2.5), T1 (NMVOC) | NS, RS | CS (NH3, NOx), D (TSP, PM10, PM2.5, NMVOC) | L & T: NH3 (for 3.B.1.b), NMVOC | L: NH3 (for 3.B.1.a) | |
3.B.2, 3.B.4.d, 3.B.4.e | Sheep, Goats, Horses | T2 (NH3, NOx, TSP, PM10, PM2.5), T1 (NMVOC) | NS, RS | CS (NH3,NOx), D (TSP, PM10, PM2.5, NMVOC) | no key category | |
3.B.3 | Swine | T3 (NH3), T2 (NOx, TSP, PM10, PM2.5), T1 (NMVOC) | NS, RS | CS (NH3, NOx), D (TSP, PM10, PM2.5, NMVOC) | L & T: NH3, TSP | |
3.B.4.a | Buffalo | NO, from 1990 until 1995, since 1996 IE, considered in 3.B.1.b | ||||
3.B.4.f | Mules and asses | IE, considered in 3.B.4.e | ||||
3.B.4.g i-iv | Poultry | T2 (NH3, NOx, TSP, PM10, PM2.5), T1 (NMVOC) | NS, RS | CS (NH3, NOx), D (TSP, PM10, PM2.5, NMVOC) | L: TSP (for 3.B.4.g i) | |
3.B.4.h | Other animals | NE, see a) |

Country specifics
In 2017, NH3 emissions from sector 3.B (manure management) derived up to 42.5 % from total agricultural emissions, which is equal to ~ 272.1 kt NH3. Within those emissions 51.4 % originate from cattle manure (~ 139.9 kt), 34.6 % from pig manure (ca. 94.1 kt), and 11.2 % from poultry manure (~ 30.5 kt). Calculations take into account the impact of anaerobic digestion of manure on the emissions.
NOx emissions from sector 3 B (manure management) contribute only 1.2 % (~ 1.5 kt) to the total agricultural NOx emissions. They are calculated proportionally to N2O emissions. (see Rösemann et al., 2019, Chapter 3.3.4.3.5 [1]).
NMVOC emissions from sector 3.B (manure management) contributed 95.2 % (192.7 kt) from total agricultural NMVOC emissions (202.4 kt).
In 2017, manure management contributed, respectively, 71.9 % (44.5 kt), 43.5 % (13.4 kt) and 85.3 % (3.9 kt) to the total agricultural TSP, PM10 and PM2.5 emissions (TSP: 61.9 kt, PM10: 30.8 kt, PM2.5: 4.6 kt, respectively).
Activity data for all pollutants
The Federal Statistical Agency and the Statistical Agencies of the federal states carry out surveys in order to collect, along with other data, the head counts of animals. The results of these surveys are used for emission calculations, for details see Rösemann et al., 2019, Chapter 3.4.2 [1].
The animal population figures used in the inventory are presented in Table 1. Buffaloes are included in the cattle population figures, mules and asses are included in the horse population figures (IE), see Rösemann et al. (2019), Chapters 4.1 and 7.1 [1]. In the first years after the German reunification in 1990 animal livestock decreased markedly. The head counts for cattle continued to decrease significantly until 2006/2007 with, from then on, a slight increase of dairy cattle numbers (reaching 2017 with 66.1 % of 1990) and only a slight decrease of the numbers of other cattle (2017: 61.5 % of 1990). The swine numbers decreased further until 1995 and then increased again (2017: 86.5 % of 1990). The 2017 numbers of horses, sheep and goats are, respectively, at 87.2 %, 57.0 % and 157.4 % of 1990.
Figures for broilers and turkeys are showing a massive increase since 1990. In total, 2017 poultry population figures are at 152.4 % of 1990. A detailed description of the animal figures used can be found in the National Inventory Report (NIR 2019 [11], Chapter 5.1.3.2.3).
Table 1: Population of animals
a) Emissions of other animals were approximated with estimated population figures (see Rösemann et. al., 2017, Chapter 9) [12] and submitted to the TERT oft he NECD-Review. The TERT confirmed that emissions are below the threshold of significance. For GHG emission reporting the UNFCC has acknowledged that the emissions from Germany's other animals are negligible. As Germany does not have to report emissions of other animals in GHG-reporting it is consistent to do so in reporting of air pollutants.
Additional data
Emission calculations in accordance with a Tier 2 or Tier 3 method require data on animal performance (animal weight, weight gain, milk yield, milk protein content, milk fat content, numbers of births, numbers of eggs and weights of eggs) and on the relevant feeding details (phase feeding, feed components, protein and energy content, digestibility and feed efficiency). To subdivide officially recorded total numbers of turkeys into roosters and hens, the respective population percentages need to be known. Details on data requirements for the modelling of emissions from livestock husbandry in the German inventory can be found in Rösemann et al. (2019), Chapters 4 to 8 [1].
Most of the data mentioned above is not available from official statistics and was obtained from the open literature, from publications by agricultural association, from regulations for agricultural consulting in Germany and from expert judgements.
For 1991, 1995 and 1999, frequency distributions of feeding strategies, husbandry systems (shares of pasturing/stabling; shares of various housing methods), storage types as well as techniques of farm manure spreading were obtained with the help of the RAUMIS agricultural sector model (Regionalisiertes Agrar- und UmweltInformationsystem für Deutschland/ Regionalised agricultural and environmental information system for Germany). RAUMIS has been developed and is operated by the Institute of Rural Studies of the Thünen Institute (Federal Research Institute for Rural Areas, Forestry and Fisheries). For an introduction to RAUMIS see Weingarten (1995) [6]; a detailed description is provided in Henrichsmeyer et al. (1996) [7].
1991-RAUMIS data are used for the years 1990 to 1993, 1995-RAUMIS data for the years 1994 to 1997, and 1999-RAUMIS data for the years 1998 and 1999.
For the year 2010 respective data are used that were derived from the 2010 official agricultural census and the simultaneous survey of agricultural production methods (Landwirtschaftliche Zählung 2010, Statistisches Bundesamt/ Federal Statistical Office) as well as the 2011 survey on manure application practices (Erhebung über Wirtschaftsdüngerausbringung, Statistisches Bundesamt/ Federal Statistical Office).
For the year 2015 data on techniques of farm manure spreading from the 2016 official agricultural census (Agrarstrukturerhebung 2016, Statistisches Bundesamt / Federal Statistical Office) were used.
The gaps between the latest RAUMIS model data (1999) and the first official data (2010) were closed by linear interpolation on district level. For 2011 to 2017 the 2010 data was kept, with the exception of data on techniques of farm manure spreading. For the latter the data was linearly interpolated between 2010 and 2015, and for 2016 and 2017 the 2015 data was kept. In addition it was taken into account that, as of 2012, slurry spread on bare soil has to be incorporated within four hours. For a description of the RAUMIS data, tha data from official surveys and additional data from other sources see Rösemann et al. (2019), Chapter 3.4 [1]. Time series of frequency distributions of housing systems, storage systems and application techniques as well as the corresponding emission factors are provided in NIR 2019 [11], Chapter 19.3.2.
NH3 & NOx
Methodology
N in manure management
N excretion
In order to determine NH3 and NOx emissions from manure management of a specific animal category, the individual N excretion rate must be known as well as, for NH3, the TAN content of the N excretions. Default excretion rates are provided by IPCC Guidelines and default TAN contents can be found in the EMEP Guidebook (EMEP, 2016) [10]. However, the German agricultural emission inventory uses N mass balances to calculate the N excretions and the TAN contents of almost all animal categories to be reported. N mass balance calculations (see below) consider N intake with feed, N retention due to growth, N contained in milk and eggs, and N in offspring. Table 2 presents national means of N excretions and TAN contents. For methodological details and mass balance input data see
Rösemann et al. (2019), Chapter 3.3.4.3 as well as Chapters 4 to 8 [1].
Table 2: National means of N excretions and TAN contents
N mass flow and emission assessment
The calculation of the emissions of NH3, N2O, NOx and N2 from German animal husbandry is based on the so-called N mass flow approach (e. g. Dämmgen and Hutchings, 2008, [3]).
This approach differentiates between N excreted with faeces (organic nitrogen Norg, i. e. undigested feed N) and urine (total ammoniacal nitrogen TAN, i. e. fraction of feed N metabolized). The N flow within the manure management system is treated as depicted in the figure below. This method reconciles the requirements of both the Atmospheric Emission Inventory Guidebook for NH3 emissions (current edition: EMEP, 2016) [10], and the IPCC guidelines for greenhouse gas emissions (current edition: IPCC (2006) [4])). Reidy et al. (2008),[2])), showed for several European countries (Germany, the Netherlands, Switzerland, United Kingdom) that their N-flow based inventory models yielded, in spite of national peculiarities, comparable results as long as standardised data sets for the input variables were used. The comparison is currently being repeated for the updated inventory models (Harald Menzi, EAGER group, https://www.eager.ch/).
Not explicitly shown in the N mass flow scheme is air scrubbing in housing and anaerobic digestion of manure. These issues are separately described farther below. Note that emissions from grazing and application are reported in sector 3.D.

General scheme of N flows in animal husbandry
m: mass from which emissions may occur. Narrow broken arrows: TAN (total ammoniacal nitrogen); narrow continuous arrows: organic N. The horizontal arrows denote the process of immobilisation in systems with bedding occurring in the house, and the process of mineralisation during storage, which occurs in any case. Broad arrows denote N-emissions assigned to manure management (Eyard NH3 emissions from yards; Ehouse NH3 emissions from house; Estorage NH3, N2O, NOx and N2 emissions from storage; Eapplic NH3 emissions during and after spreading; Egraz NH3, N2O, NOx and N2 emissions during and after grazing; Esoil N2O, NOx and N2 emissions from soil resulting from manure input).
The figure allows tracing of the pathways of the two N fractions after excretion. The various locations where excretion may take place are considered. The partial mass flows down to the input to soil are depicted. During storage Norg can be transformed into TAN and vice versa. Both, the way and the amount of such transformations may be influenced by manure treatment processes like, e. g., anaerobic digestion where a considerable fraction of Norg is mineralized to TAN. For details see Rösemann et al. (2019), Chapters 3.3.4.3 and 3.3.4.4 [1]. Wherever NH3 is emitted, its formation is related to the amount of the TAN present. For poultry the excretion of uric acid nitrogen (UAN) should be used instead of TAN (see Dämmgen and Erisman, 2005, [5]). In line with EMEP (2016) [10], it is assumed that UAN excreted can be considered TAN. N2O emissions are related to the total amount of N available (Norg + TAN).NOx emissions (i. e. NO emissions) are calculated proportionally to the N2O emissions, see section 'Emission factors'. Note that the N2O, NOx and N2 emissions from the various storage systems include the respective emissions from the related housing systems.
Air scrubber systems in swine husbandry
For pig production the inventory considers the effect of air scrubbin. Data on frequencies of air scrubbing facilities and the removal efficiency were provided by KTBL (Kuratorium für Technik und Bauwesen in der Landwirtschaft / Association for Technology and Structures in Agriculture). The average removal efficiency of NH3 is 80 % while for TSP and PM10 the rates are set to 90 % and for PM2.5 to 70 %.
According to the KTBL data, in 2017 6.2 % of all pig places were equipped with air scrubbers.
The amounts of NH3-N removed by air scrubbing are completely added to the pools of total N and TAN for landspreading. For details see Rösemann et al. (2019), Chapter 3.3.4.3.3 [1]).
Anaerobic digestion of manure
According to IPCC (2006) [4], anaerobic digestion of manure is treated like a particular storage type that, however, comprises three sub-compartments (pre-storage, fermenter and storage of digestates). For details see Rösemann et al. (2019), Chapters 3.3.4.4 and 3.4.4.2 [1]). The resulting digestates are considered as liquid. Two different types of digestates storage systems are considered: gastight storage and open tank. For the open tank formation of a natural crust because of the usual co-fermentation of energy crops is taken into account. Furthermore, the modelling of anaerobic digestion and spreading of the digestates takes into account that the amount of TAN in the digestates is higher than in untreated slurry and that the frequencies of spreading techniques differ from those for untreated slurry.
NH3 and NO emissions occur from pre-storage of solid manure, from non-gastight storage of digestates and from landspreading of digestates (NH3 emissions and NO emissions from landspreading of digested manure are reported in 3.Da.2.a). There are no such emissions from pre-storage of slurry, from the fermenter and from gastight storage of digestates. Note that NH3 and NO emissions calculated with respect to the digestion of animal manures do not comprise the contributions by co-digested energy crops. The latter are dealt with separately in 3.D.a.2.c and 3.I.
Emission Factors
Application of the N mass flow approach requires detailed emission factors for NH3, N2O, NOx and N2 describing the emissions from the various housing and storage systems NH3 emissions from manure application techniques are reported in section 3.D and their emissions factors described in the corresponding section.
In general, the detailed NH3 emission factors are related to the amount of TAN available at the various stages of the N flow chain. Most NH3, emission factors are country specific but some are taken from EMEP (2016) [10]. No specific NH3 emission factors are known for the application of digested manure. However, due to co-fermentation of energy crops, the viscosity of digested manure resembles that of untreated cattle slurry. Hence, the emission factors for untreated cattle slurry are adopted for the application of digested manure. For emission factors of livestock husbandry see Rösemann et al. (2019), Chapters 4 to 8; for emission facors of digested manure see Rösemann et al. (2019), Chapter 3.4.4.2.4 [1].
The detailed emission factors for N2O, NOx and N2 relate to the amount of N available which is N excreted plus (in case of solid manure systems) N input with bedding material. The N2O emission factors are taken from IPCC (2006) [4]. This means that the emission factor for solid manure systems is lower (see Rösemann et al. (2019), Chapter 3.5.2 [1]) than that used in earlier submissions (including Submission 2017). The emission factors for NOx and N2 are approximated as being proportional to the N2O emission factors, , i. e. the NO-N and N2 emission factors are, respectively, one-tenth and three times the value of the N2O-N emission factor, (see Rösemann et al. (2019), chapter 3.3.4.3.5 [1]). This proportionality is also applied to anaerobic digestion of manure, where N2O emissions occur from pre-storage of solid manure and non-gastight storage of digestates with the emission factors being those used for normal storage of solid manure and the storage of untreated slurry with natural crust provided by IPCC (2006) [4]. Note that the inventory model calculates NO rather than NOx. The conversion of NO emissions into NOx emissions is achieved by multiplying the NO emissions with the NOx/ NO molar weight ratio of 46/30. This relationship also holds for NO and NOx emission factors.
All NOx emissions from the agricultural sector are excluded from emission accounting by adjustment as they are not considered in the NEC and Gothenburg commitments.
Table 3 shows the implied emission factors of NH3 and NOx for the various animal categories. These emission factors normalize emissions from an animal category as the ratio of the total emission to the respective number of animals.
Table 3: IEF for NH3 & NOx from manure management
Trend discussion for Key Sources
will be added next submission.
Recalculations
The recalculation page of the IIR (https://iir-de.wikidot.com/recalculations) provides a brought overview of the recalculations of all source categories. More details about the agricultural recalculations can be found on the main agricultural page (https://iir-de.wikidot.com/3-agriculture). Further details about recalculations are described in Rösemann et al. (2019), Chapter 3.5.2.
Planned improvements
No improvements are planned at present.
NMVOC
In 2017, NMVOC emissions from manure management amount to 192,7 95.2 % of total NMVOC emissions from the agricultural sector. 76.4 % originate from cattle, 7.7 % from pigs, and 14.2 % from poultry.
All NMVOC emissions from the agricultural sector are excluded from emission accounting by adjustment as they are not considered in the NEC and Gothenburg commitments (see Chapter 11 - Adjustments and Emissions Reduction Commitments).
Method
The Tier 1 methodology provided by EMEP (2016)-3B-17 [10] was used to assess the emissions of NMVOC from manure management.
Activity data
Animal numbers serve as activity data, see Table 1.
Emission factors
Tier 1 emission factors for NMVOC are provided in EMEP (2016)-3B-18, Table 3.4 [10]. For cattle, sheep, goats and horses there are different emission factors for feeding with and without silage.
For cattle and horses the emission factors for feeding with silage were chosen, for all other animals the emission factors is for feeding without silage. Due to missing country-specific emission factors or emission factors that do not correspond to the inventory’s animal categories, the emission factors provided in EMEP (2016)-3B-18, Table 3.4, were used to define specific emission factors for weaners, boars, lambs, ponies/light horses and pullets, see Rösemann et al. (2019), Chapter 3.3.4.2 [1]. The implied emission factors given in Table 4 relate the overall NMVOC emissions to the number of animals in each animal category. They correspond to the EMEP Tier 1 emission factors, except for horses, sheep, swine and other poultry. These categories comprise subcategories with different emission factors so that their overall IEFs in Table 4 represent national mean values.
Note that other poultry in Germany includes not only geese and ducks but also pullets. For pullets no default EF is given in the EMEP guidebook (EMEP, 2016) [10], hence the EF of broilers has been adopted (because of similar housing). This assumption significantly lowers the overall IEF of other poultry (in Table 4 the IEFs are listed separately for each poultry category). The IEF of the sheep category is significantly lower than the EMEP Tier 1 emission factor, because for lambs the EF is assumed to be 40% lower compared to an adult sheep in accordance with the difference in N excretion between lambs and adult sheep.
Table 4: IEF for NMVOC from manure management
Trend discussion for Key Sources
will be added next submission.
Recalculations
The recalculation page of the IIR (https://iir-de.wikidot.com/recalculations) provides a brought overview of the recalculations of all source categories. More details about the agricultural recalculations can be found on the main agricultural page (https://iir-de.wikidot.com/3-agriculture). Further details about recalculations are described in Rösemann et al. (2019), Chapter 3.5.2.
Planned improvements
No improvements are planned at present.
TSP, PM10 & PM2.5
In 2017, TSP emissions from manure management amount to 71.9 % of total emissions from the agricultural sector. Within the emissions from manure management 22.7 % originate from cattle, 41.0 % from pigs, and 35.7 % from poultry. 43.5 % of the PM10 emissions from the agricultural sector are caused by manure management, where 34.7 % originate from cattle, 19.9 % from pigs, and 44.6 % from poultry. PM2.5 emissions from the agricultural sector mostly originate from manure management (85.3 %), of which are 78.2 % from cattle, 3.1 % from pigs, and 17.2 % from poultry.
Method
EMEP (2013)-3B-26 [9] provided a Tier 2 methodology. In the current Guidebook (EMEP, 2016) [10], this methodology has been replaced by a Tier 1 methodology. However, EF for cattle derived with the EMEP 2013 Tier 2 methodology remained unchanged. So the EMEP 2013 [9] methodology was kept for cattle. For swine the EMEP 2013 [9] methodology was formally kept but the EMEP 2016 Tier 1 EF was used both for slurry and solid based manure management systems. The same was done with the EMEP 2016 EFs for laying hens (used for cages and perchery). In case the EMEP 2016 EFs are just the rounded EMEP 2013 EFs, the unrounded EMEP 2013 EFs were kept.
The inventory considers air scrubber systems in swine husbandry. For swine places equipped with air scrubbing the emission factors are reduced according to the removal efficiency of the air scrubber systems (90 % for TSP and PM10, 70 % for PM2.5). For details see Rösemann et al. (2019), Chapter 3.3.4.3.3 [1].
Activity data
Animal numbers serve as activity data, see Table 1.
Emission factors
Tier 1 emission factors for TSP, PM10 and PM2.5 from livestock husbandry are provided in EMEP (2016)-3B-19, Table 3.5 and 53, Table A3-4 [10]. For cattle the Tier 2 emission factors provided in EMEP (2013)-3B-29, Table 3-11 [9] were used, because they differentiate between slurry and solid manure systems and were also used to develop the EMEP 2016 Tier 1 emissions factors.
The implied emission factors given in Table 5 relate the overall TSP and PM emissions to the number of animals in each animal category. The Guidebook does not indicate whether EFs have considered the condensable component (with or without).
Table 5: IEF for TSP, PM10 & PM2.5 from manure management
Trend discussion for Key Sources
will be added next submission.
Recalculations
The recalculation page of the IIR (https://iir-de.wikidot.com/recalculations) provides a brought overview of the recalculations of all source categories. More details about the agricultural recalculations can be found on the main agricultural page (https://iir-de.wikidot.com/3-agriculture). Further details about recalculations are described in Rösemann et al. (2019), Chapter 3.5.2.
Planned improvements
No improvements are planned at present.
Uncertainty
Details will be described in chapter 1.7.