4.B Manure Management

Last updated on 24 Jan 2013 17:05 by Kevin Hausmann

NFR-Code Name of Category Method AD EF Key Source for (by)
4.B Manure Management
consisting of / including source categories
4.B 1a & 1b Cattle T3 (NH3), T2 (NOx), T1 (TSP, PM) NS, RS CS (NH3, NOx), D (PM) NH3 (L/T)
4.B 3, 4, 5, 6, 7 Buffalo, Sheep, Goats, Horses, Mules and Asses T2 (NH3), T1 (NH3, NOx, PM) NS CS (NH3,NOx), D (PM) -
4.B 8 Swine T3 (NH3), T2 (NOx), T1 (TSP, PM) NS, RS CS (NH3, NOx), D (PM) NH3 (L/T), TSP (L), PM10 (L)
4.B 9a, 9b, 9c, 9d Poultry T2 (NH3, NOx), T1 (PM) NS, RS CS (NH3, NOx), D (PM) NH3 (T)
ManureManagement.PNG

Country specifics

NH3 emissions from the agricultural sector in 2010 derive up to 86.1 % from sector 4 B (manure management), which is equal to ~ 442 Gg NH3. Within those emissions 62.5 % originate from cattle manure (~ 276 Gg), 24.4 % from pig manure (ca. 108 Gg), and 10.3 % from poultry manure (~ 45 Gg).

NOx emissions from sector 4 B (manure management) contribute only 1.5 % (~ 1.5 Gg) to the total agricultural NOx emissions.
NMVOC emissions from Agriculture are not reported for this submission as the methodology used in previous submissions has been evaluated as not adequate by international experts (see Haenel et al., 2012 [1]).

Activity data for all pollutants

The emission calculations for cattle, swine, sheep, horses and poultry are based on numbers of animal places on district level. These data is derived from the reports of the Federal Statistical Office (Statistisches Bundesamt) available for every other year during 1990 – 1996 and 1999 – 2007 as well as for the year 2010. For the years inbetween, animal head counts of cattle, swine and sheep are available at the Länder (federal state) level while missing numbers of horses and poultry were interpolated. The latter means a change in the method compared to IIR 2011, where missing numbers were generated by keeping the number of the last available census.

As of 2008, cattle head counts are taken from a special database (HIT, see [http://www.hi-tier.de]) in which each animal is registered. As a result, the relevant numbers of animals are higher than in earlier years, when, due to the cut-off definitions used, official statistics failed to include all animals concerned. An investigation performed by the Federal Statistical Office for the year 2007 revealed that the number of cattle from HIT is 2.9 % higher than those obtained with the former survey-method. According to the Federal Statistical Office it is not possible to correct the time series of cattle numbers for the years from 1990 to 2007. As a result the total emissions from cattle farming are slightly underestimated for the years 1990-2007.

As part of the agricultural census in 2010 the number of equids has been collected officially for the first time, not differentiating between horses and mules and asses. This number is interpreted as the total number of horses, as it is not possible to adequately define and subtract the number of mules and asses. However, the error caused by this simplification is negligible due to the small number of mules and asses (see below).
The number of goats has not been recorded in agricultural statistics between 1977 und 2010. For the years 1990 - 2004, the Federal Ministry of Food, Agriculture and Consumer Protection (BMELV) estimated the goat population on national level. For the years 2005 – 2009 the national total of goats was estimated by the Federal Statistical Office. In 2010 goats were counted as part of the agricultural census 2010. This 2010 number is significantly smaller than the estimated numbers of the previous years. The latter, however, are not corrected but maintained in agreement with the Federal Statistical Office.
German agricultural statistics do not include herd-size figures for buffalo and asses and mules. The relevant figures for buffalo are provided by Deutscher Büffel-Verband (the German Buffalo Association) for the years as of 2000. In keeping with a recommendation in the final report for the "Initial Review under the Kyoto Protocol and Annual 2006 Review under the Convention", the time series for the buffalo population was completed for the years prior to 2000. This was accomplished via linear extrapolation. In this process, arithmetically negative animal populations resulted for the years 1990 to 1995 and were replaced with "zero".

As to asses and mules, about 6,000 to 8,000 asses and about 500 mules and hinnies, were kept in Germany in 2003 (Deutsches Eselstammbuch, 2003). No time series is available for the years 1990 – 2010. Hence, the inventory assumes a constant number of 8,500 asses and mules.
The inventory calculations require the definition of animal categories as homogeneous as possible with respect to feeding and husbandry details. Some of the animal categories defined within the official statistical censuses do not meet these requirements. Hence, their animal numbers have to be regrouped in order to fit the animal categories used in the inventory. This is why the herd-size numbers used in the inventory for calves, heifers, fattening bulls, weaners, fattening pigs, laying hens and pullets differ from the respective numbers in the official statistics.
In the "turkey" category, roosters and hens have to be considered separately.
However, the total for all cattle, the sum of the figures for pullets and laying hens, and the sum of the figures for turkey roosters and turkey hens are each in accordance with the official statistics. For pigs the number of swine considered in the inventory differs from the number of pigs officially counted. This is due to the fact that in the inventory officially counted piglets up to a weight of 8 kg are included in the system “sow with suckling-pigs”.
As already mentioned in the survey chapter, after the German reunification animal livestock decreased in 1991. The animal population figures the actual inventory is based on are presented in the table 1. The head counts for cattle, swine, horses, sheep and goats decreased between 2005 and 2010 while the total poultry population increased due to higher numbers of broilers, turkeys and ducks in 2010. Data for each animal category for the whole time series from 1990 until 2010 can be found in the National Inventory Report (NIR 2012 [11]) in Table 122.

For reasons of data protection, published district-level data records are incomplete. In co-operation with the Federal Statistical Office, the calculation was prepared with inclusion of the pertinent confidential data since 2007.

Table 1: Population of animals

Population of animals
1990 1995 2000 2005 2010
dairy cattle 6,354,555 5,229,227 4,569,752 4,236,394 4,183,111
other cattle 13,133,442 10,661,219 9,968,306 8,799,218 8,626,381
buffalo NO NO 626 1,187 2,362
mules and asses 8,500 8,500 8,500 8,500 8,500
horses 490,954 625,649 491,036 499,886 461,779
sheep 3,266,100 2,990,670 2,743,276 2,643,125 2,350,418
swine 26,502,466 20,387,251 21,767,747 22,742,804 22,244,381
laying hens 53,450,546 45,317,296 44,225,649 38,203,868 35,314,157
broilers 35,393,005 42,025,817 50,359,931 56,762,637 67,428,218
turkeys 5,029,160 6,742,043 8,893,086 10,611,031 11,343,920
pullets 17,210,833 14,591,964 14,240,459 12,301,472 11,370,999
ducks 2,013,655 1,933,719 2,055,688 2,352,290 3,164,334
geese 781,487 617,032 404,752 329,677 278,122
goats 90,000 100,000 140,000 170,000 149,936

Additional data

To calculate emissions in accordance with a Tier-2 or Tier 3 method, 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) are required. To divide officially recorded total numbers of turkeys into roosters and hens, one must know the applicable sex ratio.
For the most part, such data is not available from official statistics and was obtained from the open literature, from association publications, from regulations for agricultural consulting in Germany and from expert judgments.
Up to 1999, frequency distributions of feeding strategies, husbandry systems (shares of pasturing/stabling; shares for 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 UmweltInformationsSystem 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 vTI (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]).

An update of the RAUMIS data was not possible before 2010 when the results of the 2010 official agricultural census and the simultaneous survey of agricultural production methods (Landwirtschaftliche Zählung 2010, Statistisches Bundesamt) as well as the 2011 survey on manure application practices (Erhebung über Wirtschaftsdüngerausbringung, Statistisches Bundesamt) became available. For details see Haenel et al. (2012) [1].
The gaps between the latest RAUMIS data (1999) and the new 2010/2011 data were closed by linear interpolation on district level.

Table 2 presents mean animal weights for dairy cows, other cattle, swine and poultry. Data for the entire time series 1990-2010 can be found in the National Inventory Report (NIR 2012 [11]) in Table 123. For the Tier-1 based emission calculations of sheep, goats, horses, asses and mules and buffalo no weight data are needed.

Table 2: Mean animal weights

Mean animal weights in kg/animal
1990 1995 2000 2005 2010
Dairy cows 607.9 621.8 644.3 645.8 646.8
Other cattle 300.1 313.7 329.5 326.4 330.0
Swine 72.8 74.1 72.4 72.3 70.6
Poultry 1.76 1.66 1.82 2.00 1.89

The mean weights of swine are higher than in Submission 2011 which is due to updated animal numbers and animal weights. Changes in the mean animal weights of poultry are caused by the newly introduced practice of data gap closure by interpolation instead of keeping the numbers of the last available census; the adjustment of the ratio between female and male turkey numbers slightly influences the mean poultry weight.

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. While default exrection rates are provided by IPCC Guidelines, the German agricultural emission inventory uses N mass balances to calculate the N excretions of almost all animal categories to be reported. The calculation of N excretion with the help of a N mass balance considers N intake with feed, N retention due to growth, N seceded with milk & eggs, and N in the offspring produced. For more details see Haenel et. al. (2012) [1].

N mass flow and emission assessment for mammals

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. This method reconciles the requirements of both the Atmospheric Emission Inventory Guidebook for NH3 emissions and the IPCC guidelines for greenhouse gas emissions (Dämmgen and Hutchings (2008) [3]). According to the N mass flow approach the N flow within the manure management system is treated as depicted in the figure below. In Europe, this approach is also applied in Denmark, the United Kingdom, the Netherlands and Switzerland. In spite of national peculiarities, a comparison of the national solutions showed identical results as long as standardised data sets for the input variables were used (Reidy et al. (2008) [2]).The approach differentiates between N excreted with faeces and urine and two fractions of N

  • Norg: organic nitrogen is the fraction that is undigested N in the feed and exreted with faeces;
  • TAN (total ammoniacal nitrogen) is the fraction of N that was metabolised and is excreted with urine.
N_flow_model.jpg
N flows in an animal subcategory. Mammals

m: mass from which emissions may occur. Narrow broken arrows: TAN (total ammonical 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 hatched arrows denote emissions assigned to manure management: E emissions of N species (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. Broad open arrows mark emissions from soils: Egraz NH3, N2O, NOx and N2 emissions during and after grazing; Ereturned 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 both fractions, Norg and TAN, react to form the respective other fraction. Both the way and the amount of such transformations may be influenced by manure treatment processes.
Whenever N species are emitted, their formation is related to the amount of the reactive TAN fraction.
The calculations are performed stepwise as listed below; for a precise discription see Haenel et al. (2012) [1].

The stepwise approach considers the following:

  • definition of animal subcategories,
  • calculation of the excretions of total N and TAN (N-mass balance),
  • calculation of the fractions of excretions deposited in stables, yards and during grazing,
  • calculation of N and TAN losses by NH3 emissions from stables, yards and during grazing,
  • calculation of N input with bedding material in housing systems with bedding
  • calculation of the amounts of total N and TAN turned over from housing and yards to storage,
  • calculation of TAN immobilization and mineralization of Norg within storage,
  • calculation of NH3 N2O, NOx and N2 emissions from the various storage systems ,
  • calculation of total N and TAN to be applied to fields (landspreading),
  • calculation of NH3 emissions during and immediately after application,
  • calculation of the amount of N returned to soil, including N excretions on pasture minus N losses by NH3 emission during grazing.

Note that the N2O, NOx and N2 emissions from the various storage systems include the respective emissions from the related housing systems.

N mass flow model for birds

Birds excrete N in the form of undigested organic N and in uric acid (uric acid nitrogen, UAN). The latter is hydrolised to form ammonium carbonate (see Dämmgen and Erisman (2005) [5]). Thus, three fractions of N have to be traced, as shown in the figure below.

N_flow_model_birds.jpg

N flows in an animal subcategory. Birds.

m: mass from which emissions may occur. Narrow broken arrows: TAN; narrow broken and dotted line: UAN; 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 hatched arrows denote emissions assigned to manure management: E emissions of N species (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. Broad open arrows mark emissions from soils: Egraz NH3, N2O, NOx and N2 emissions during and after grazing; Ereturned N2O, NOx and N2 emissions from soil resulting from manure input.

At present, a similar treatment of TAN as applied for mammals is impossible for birds, as the hydrolysis of uric acid producing ammonium carbonate occurs outside the birds’ bodies. In particular, it is difficult to model the influence of humidity on this process.
Hence, emission inventories still make use of mean potential TAN contents for their calculations which means that also the UAN excreted in the housing is completely considered to be TAN.

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 as well as the various manure application techniques. The detailed NH3, emission factors are generally related to the amount of TAN available at the various stages of the N flow. These NH3, emission factors are mainly country specific but are also taken from EMEP (2009) [10]. The detailed emission factors for N2O, NOx and N2 relate to the amount of N excreted. The N2O, emission factors are taken from IPCC (2006) [4] while the emission factors for NOx and N2 are approximated as proportional to the N2O emission factors. Note that the inventory model calculates NO rather than NOx. The NO emissions are then converted to NOx emissions by multiplying with 46/30 which means a transformation into NO2. Equivalently, this conversion can also be applied to the emission factors as is shown in Table 3.
For a detailed description of the emission factors see Haenel et al. (2012) [1].

Another type of emission factor is the implied emission factor (IEF) which can be obtained from the N mass flow approach. The implied emission factor is defined as the ratio of the total emission from an animal category to the respective number of animals. Table 3 shows for the various animal categories the implied emission factors of NH3 and NOx.

Table 3: IEF for NH3 & NOx

Implied emission factors for NH3 & NOx
1990 1995 2000 2005 2010
animal NH3 in kg/animal place
dairy cattle 29.77 32.80 34.06 35.21 35.93
other cattle 14.83 14.62 14.75 14.76 14.60
buffalo NO NO 28.97 28.97 28.97
mules and asses 12.56 12.56 12.56 12.56 12.56
horses 18.60 18.57 18.92 18.86 18.83
sheep 1.59 1.59 1.62 1.61 1.67
swine 5.62 5.43 5.39 5.21 4.86
laying hens 0.45 0.44 0.41 0.44 0.44
broilers 0.23 0.19 0.22 0.23 0.22
turkeys 1.04 1.04 1.03 1.15 1.10
pullets 0.17 0.15 0.14 0.15 0.14
ducks 0.26 0.26 0.26 0.26 0.26
geese 0.38 0.38 0.38 0.38 0.38
goats 2.13 2.13 2.13 2.13 2.13
NOx converted in kg NO2/animal place
dairy cattle 0.11 0.12 0.13 0.13 0.13
other cattle 0.052 0.058 0.060 0.063 0.066
buffalo NO NO 0.12 0.12 0.12
mules and asses 0.059 0.059 0.059 0.059 0.059
horses 0.085 0.085 0.086 0.086 0.086
sheep 0.0068 0.0068 0.0069 0.0068 0.007
swine 0.0093 0.0113 0.0114 0.0130 0.0141
laying hens 0.00026 0.00026 0.00024 0.00027 0.00028
broilers 0.00016 0.00014 0.00017 0.00018 0.00018
turkeys 0.00059 0.00059 0.00060 0.00066 0.00065
pullets 0.00012 0.00010 0.00010 0.00010 0.00010
ducks 0.00017 0.00017 0.00017 0.00017 0.00017
geese 0.00018 0.00018 0.00018 0.00018 0.00018
goats 0.0083 0.0083 0.0083 0.0083 0.0083

NMVOCs

NMVOC emissions from agriculture are not reported for this submission as the methodology used in previous submissions has been evaluated as not adequate by international experts (see Haenel et al., (2012) [1]).

PM2,5 & PM10

PM2,5 emissions from the agricultural sector derive up to 88 % from animal manure. Within those emissions 53.6 % originate from cattle manure, 25.1 % from pig manure, and 20.1 % from poultry manure.
PM10 emissions from the agricultural sector derive up to 51.6 % from animal manure. Within those emissions 22.3 % originate from cattle manure, 41.6 % from pig manure, and 35.8 % from poultry manure.

Method

EMEP(2009)-4B-25[10]) provides a Tier 2 methodology to assess the emissions of PM10 and PM2,5 from animal housing which was adopted. However, EMEP(2009)-4B-30[10]) states that the emission factors are a first estimate only, thus the calculations in this inventory provides only a first estimate of particulate matter from animal husbandry.

Activity data

Please see table 1 top of page.

Emission factors

Tier 2 emission factors for PM10 and PM2,5 from animal housing are provided in EMEP(2009)-4B-27, Table 3-10 [10]). For cattle and swine these emission factors differentiate between slurry and solid manure systems.
The implied emission factors given in Table 5 releat the overall PM emissions to the number of animals in each animal category.

Table 5: IEF for PM2,5 & PM10

Implied emission factors for PM2,5 & PM10
1990 1995 2000 2005 2010
animal PM10 in kg/animal place
dairy cattle 0.48 0.55 0.56 0.57 0.57
other cattle 0.26 0.25 0.25 0.24 0.24
buffalo NE NE NE NE NE
mules and asses 0.14 0.14 0.14 0.14 0.14
horses 0.14 0.14 0.14 0.14 0.14
sheep NE NE NE NE NE
swine 0.38 0.38 0.38 0.37 0.37
laying hens 0.021 0.021 0.026 0.035 0.072
broilers 0.052 0.052 0.052 0.052 0.052
turkeys 0.032 0.032 0.032 0.032 0.032
pullets 0.052 0.052 0.052 0.052 0.052
ducks 0.032 0.032 0.032 0.032 0.032
geese 0.032 0.032 0.032 0.032 0.032
goats NE NE NE NE NE
PM2,5 in kg/animal place
dairy cattle 0.31 0.36 0.36 0.37 0.37
other cattle 0.17 0.17 0.16 0.16 0.16
buffalo NE NE NE NE NE
mules and asses 0.10 0.10 0.10 0.10 0.10
horses 0.10 0.10 0.10 0.10 0.10
sheep NE NE NE NE NE
swine 0.062 0.062 0.062 0.061 0.061
laying hens 0.0028 0.0028 0.0038 0.0058 0.0135
broilers 0.0070 0.0070 0.0070 0.0070 0.0070
turkeys 0.0040 0.0040 0.0040 0.0040 0.0040
pullets 0.0070 0.0070 0.0070 0.0070 0.0070
ducks 0.0040 0.0040 0.0040 0.0040 0.0040
geese 0.0040 0.0040 0.0040 0.0040 0.0040
goats NE NE NE NE NE
Bibliography
1. Haenel H.-D., Rösemann C., Dämmgen U., Poddey E., Freibauer A., Döhler H., Eurich-Menden B., Wulf S., Dieterle M., Osterburg B. (2012): Calculations of gaseous and particulate emissions from German agriculture 1990 - 2010. vTI Agricultural and Forestry Research (Landbauforschung), Special Issue (Sonderheft) 356.
2. Reidy B., Dämmgen U., Döhler H., Eurich-Menden B., Hutchings N.J., Luesink H.H., Menzi H., Misselbrook T.H., Monteny G.-J., Webb J. (2008): Comparison of models used for the calculation of national NH3 emission inventories from agriculture: liquid manure systems. Atmospheric Environment 42, 3452-3467.
3. Dämmgen U., Hutchings N.J. (2008): Emissions of gaseous nitrogen species from manure management - a new approach. Environmental Pollution 154, 488-497.
5. Dämmgen U., Erisman J.W. (2005): Emission, transmission, deposition and environmental effects of ammonia from agricultural sources. In: Kuczyński T., Dämmgen U., Webb J., Myczko (eds) Emissions from European Agriculture. Wageningen Academic Publishers, Wageningen. pp 97-112.
6. Weingarten, P. (1995): Das „Regionalisierte Agrar- und Umweltinformationssystem für die Bundesrepublik Deutschland“ (RAUMIS). Ber Landwirtschaft 73, 272-302.
7. Henrichsmeyer, W.; Cypris, Ch.; Löhe, W.; Meuth, M.; Isermeyer F; Heinrich, I.; Schefski, A.; Neander, E.; Fasterding, F.;, Neumann, M.; Nieberg, H.( 1996): Entwicklung des gesamtdeutschen Agrarsektormodells RAUMIS96. Endbericht zum Kooperationsprojekt. Forschungsbericht für das BMELF (94 HS 021), Bonn, Braunschweig.
8. IPCC – Intergovernmental Panel on Climate Change (1996): 1996 IPCC Guidelines for National Greenhouse Gas Inventories, Reference Manual (Volume 3).
12. Rösemann C., Haenel H.-D., Poddey E., Dämmgen U., Döhler H., Eurich-Menden B., Laubach P., Dieterle M., Osterburg B. (2011): Calculations of gaseous and particulate emissions from German agriculture 1990 - 2009. vTI Agricultural and Forestry Research (Landbauforschung), Special Issue (Sonderheft) 342.
Unless otherwise stated, the content of this page is licensed under Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License