3.B - Manure Management

Last updated on 15 Mar 2018 06:33 (cf. Authors)

NFR-Code Name of Category Method AD EF Key Category 1
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, NMVOC (for 3.B.1.b | L: NMVOC (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 | L: TSP
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)
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Country specifics

In 2016, NH3 emissions from sector 3.B (manure management) derived up to 42.0 % from total agricultural emissions, which is equal to ~ 264.5 Gg NH3. Within those emissions 50.3 % originate from cattle manure (~ 133.2 Gg), 35.3 % from pig manure (ca. 93.4 Gg), and 11.4 % from poultry manure (~ 30.3 Gg). The impact of anaerobic digestion of manure on the emission calculations is taken into account.

NOx emissions from sector 3 B (manure management) contribute only 1.5 % (~ 1.9 Gg) to the total agricultural NOx emissions. They are calculated proportionally to N2O emissions. (see Haenel et al., 2018, [1]).

NMVOC emissions from sector 3.B (manure management) derived up to 95.3 % from total agricultural NMVOC emissions, which is equal to ~ 194.5 Gg NMVOC (see Haenel et al., 2018, [1]).

In 2016, manure management contributes 71.9 % (44.5 Gg), 43.5 % (13.4 Gg) and 85.4 % (3.9 Gg) to the total agricultural TSP, PM10, and PM2.5 emissions (TSP: 61.9 Gg, PM10: 30.8 Gg, PM2.5: 4.6 Gg), respectively. These results considerably differ from the results provided in Submission 2017; this is due to the changes in emission factors according to EMEP (2016) [10].

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. In general the results of these surveys are used for emission calculations, for details see Haenel et al., 2018 [1].
The animal population figures the actual inventory is based on are presented in Table 1. Buffaloes are included in the cattle population figures, mules and asses are included in the horse population figures (IE). In the first years after the German reunification (1990), animal livestock decreased markedly. The head counts for cattle, swine, horses, sheep and goats decreased further between 2005 and 2010 while since 2010 the figures of dairy cattle and pigs slightly increased. Figures for broilers and turkeys are showing a massive increase compared with 1990 figures, laying hens and pullet figures compared with 2010. A detailed description of the animal figures used can be found in the National Inventory Report (NIR 2018 [11], Chapter 5.1.3.2.3).

Table 1: Population of animals

2018_3B_Table_1.PNG

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 German other animals emissions 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.
Most of the data mentioned above 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 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) became available. For details see Haenel et al. (2018) [11].
For the year 2015 data on techniques of farm manure spreading were used from the 2016 official agricultural census (Agrarstrukturerhebung 2016, Statistisches Bundesamt / Federal Statistical Office).
The gaps between the latest RAUMIS data (1999) and the new data for 2010 were closed by linear interpolation on district level. For 2011 to 2016 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 the data for 2015 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 more details see Haenel et al. (2018) [1]. For the resulting time series and corresponding emission factors - see NIR 2018 [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. While default excretion rates are provided by IPCC Guidelines and default TAN contents can be found in the EMEP Guidebook (EMEP, 2016) [10], 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 mean N excretions and mean TAN contents. For methodological details and mass balance input data see Haenel et al. (2018) [1].

Table 2: National means of N excretions and TAN contents

2018_3B_Table_2.PNG

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 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])). 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 (organic nitrogen Norg, i. e. undigested feed N) and urine (total ammoniacal nitrogen TAN, i. e. fraction of feed N metabolized). Note that emissions from grazing and application are reported in sector 3.D.

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.

N_flow_model.jpg

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 Haenel et al. (2018) [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

The inventory considers the effect of air scrubbing facilities in pig production. Based on data provided by KTBL (Kuratorium für Technik und Bauwesen in der Landwirtschaft / Association for Technology and Structures in Agriculture), 80 % of the NH3 emissions during housing are removed if animal places are equipped with air scrubbers. For TSP and PM10 the dust removal rates are set to 90 % and for PM2.5 to 70 %, respectively.
For the present submission 2018 frequency data on air scrubbing systems were completely updated. The new data differs considerably from the partially flawed data used in submission 2017. According to the new data 5.7 % of all pig places were equipped with air scrubbers in 2016.
The amounts of NH3-N removed by air scrubbing are completely added to the pools of total N and TAN before landspreading. For details see Haenel et al., 2018, [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 Haenel et al., 2018, [1]). The resulting digestates are considered as liquid. Two different types of digestates storage systems are accounted for i. e. gastight storage and open tank. For the open tank it is taken into account that there is a natural crust because of the usual co-fermentation of energy crops. Furthermore, the modelling of anaerobic digestion and spreading of the digestates considers 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 emission factors for the various manure application techniques are now used in section 3.D.

In general, the detailed NH3 emission factors are related to the amount of TAN available at the various stages of the N flow chain. These NH3, emission factors are mainly country specific but are also 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 (see Haenel et al., 2018, [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], except for the emission factor for solid manure systems which is country specific. 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 Haenel et al., 2018, 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 conversion can equivalently be applied to the emission factors as is shown in Table 3.
For a detailed description of the emission factors see Haenel et al. (2018) [1].

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

Table 3: IEF for NH3 & NOx from manure management

2018_3B_Table_3.PNG

NMVOC

In 2016, NMVOC emissions from manure management amount to 95.3 % of total NMVOC emissions from the agricultural sector. Within the emissions from manure management 76.6 % originate from cattle, 7.6 % from pigs, and 14.1 % from poultry. . However, these emissions are excluded from emission reporting by adjustment as NMVOC emissions from agriculture are not considered in the NEC and Gothenburg commitments (see adjustment).

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. Only for cattle and horses the emission factors for feeding with silage were chosen. 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 EMEP Tier 1 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. As for the latter, no default EF is given in the EMEP guidebook (EMEP, 2016) [10],, the EF of broilers has been adopted (due to 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

2018_3B_Table_4.PNG

TSP, PM10 & PM2.5

In 2016, TSP emissions from manure management amount to 71.9 % of total emissions from the agricultural sector. Within the emissions from manure management 23.0 % originate from cattle, 40.8 % from pigs, and 35.7 % from poultry.
In 2016, 43.5 % of the PM10 emissions from the agricultural sector are caused by manure management, where 35.0 % originate from cattle, 19.7 % from pigs, and 44.4 % from poultry.
In 2016, PM2.5 emissions from the agricultural sector mostly originate from manure management (85.4 %), of which are 78.4 % from cattle, 3.0 % from pigs, and 17.0 % from poultry.

All figures differ from that calculated for submission 2017. This is due to the modified emission factors provided in the new guidebook (EMEP, 2016) [10].

Method

EMEP (2013)-3B-26 [9] provided a Tier 2 methodology. In the new 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 new 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. In case swine places are 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 Haenel et al. (2018) [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 animal housing 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 still 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.

Table 5: IEF for TSP, PM10 & PM2.5 from manure management

2018_3B_Table_5.PNG
Bibliography
1. Haenel et al. (2018): Haenel H-D, Rösemann C, Dämmgen U, Döring, U, Wulf S, Eurich-Menden B, Freibauer A, Döhler H, Schreiner C, and Osterburg B (2018), Calculations of gaseous and particulate emissions from German Agriculture 1990 – 2016. Report on methods and data (RMD), Submission 2018. Thünen Report 57, 424 p.
2. Reidy B. et al. (2008): 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.
4. IPCC – Intergovernmental Panel on Climate Change (2006): IPCC Guidelines for National Greenhouse Gas Inventories, Volume 4 Agriculture, Forestry and Other Land Use.
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). Berichte über die Landwirtschaft Band 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. Stehfest E., Bouwman L. (2006): N2O and NO emission from agricultural fields and soils under natural vegetation: summarizing available measurement data and modelling of global emissions. Nutr. Cycl. Agroecosyst. 74, 207 – 228.
9. EMEP (2013): EMEP/EEA air pollutant emission inventory guidebook – 2013.
[https://www.eea.europa.eu//publications/emep-eea-guidebook-2013]
10. EMEP (2016): EMEP/EEA air pollutant emission inventory guidebook – 2016. https://www.eea.europa.eu/publications/emep-eea-guidebook-2016
11. NIR (2018): National Inventory Report 2018 for the German Greenhouse Gas Inventory 1990-2016. Available in April 2018.
12. Rösemann et al. (2017): Rösemann C, Haenel H-D, Dämmgen U, Freibauer A, Döring, U, Wulf S, Eurich-Menden B, Döhler H, Schreiner C, and Osterburg B (2017), Calculations of gaseous and particulate emissions from German Agriculture 1990 – 2015. Report on methods and data (RMD), Submission 2017. Thünen Report 46, 423 p.
13. Aarhus Protocol on Persistent Organic Pollutants (2009), United Nation: Aarhus Protocol on Long-range Transboundary Air Pollution, Persistent Organic Pollutants, 1998 - Amendment - (on Annexes V and VII) Decision 2009. Status In force (since Dec 13, 2010), Annex III.
14. Stockholm Convention (2001): The Stockholm Convention on Persistent Organic Pollutants, opened for signature May 23, 2001, UN Doc. UNEP/POPS/CONF/4, App. II (2001), reprinted in 40 ILM 532 (2001) [hereinafter Stockholm Convention]. The text of the convention and additional information about POPs is available online at the United Nations Environment Programme’s (UNEP’s) POPs Web site, <http://irptc.unep.ch/pops/>.
15. PflSchG (2012): Gesetz zur Neuordnung des Pflanzenschutzgesetzes, Bundesgesetzblatt (BGBl), Jahrgang 2012, Teil I, Nr. 7, § 64.
16. Syngenta Agro (2015), Dep. „Zulassung und Produktsicherheit“, personal communication.
17. Regulation (EC) No 1107/2009: REGULATION (EC) No 1107/2009 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 21 October 2009 concerning the placing of plant protection products on the market and repealing Council Directives 79/117/EEC and 91/414/EEC
18. Directive 2005/53/EC: Commission Directive 2005/53/EC of 16 September 2005 amending Council Directive 91/414/EEC to include chlorothalonil, chlorotoluron, cypermethrin, daminozide and thiophanate-methyl as active substances 2005/53/EC C.F.R. (2005).
19. Directive 2006/76/EC: Commission Directive 2006/76/EC of 22 September 2006 amending Council Directive 91/414/EEC as regards the specification of the active substance chlorothalonil (Text with EEA relevance) 2006/76/EC C.F.R. (2006).
20. Directive 2008/69/EC: Commission Directive 2008/69/EC of 1 July 2008 amending Council Directive 91/414/EEC to include clofentezine, dicamba, difenoconazole, diflubenzuron, imazaquin, lenacil, oxadiazon, picloram and pyriproxyfen as active substances 2008/69/EC C.F.R. (2008).
21. Directive 2016/2284/EU: Directive (EU) 2016/2284 of the European Parliament and of the Council of 14 December 2016 on the reduction of national emissions of certain atmospheric pollutants, amending Directive 2003/35/EC and repealing Directive 2001/81/EC (Text with EEA relevance ).
22. Bailey, R. E., (2001): Global hexachlorobenzene emissions. Chemosphere, 43(2), 167-182.
23. BVL (2015) (Bundesamts für Verbraucherschutz und Lebensmittelsicherheit Braunschweig): persönliche Mitteilung der Wirkstoffdaten, 2015.
24. BVL (2017) (Bundesamts für Verbraucherschutz und Lebensmittelsicherheit Braunschweig): persönliche Mitteilung der Wirkstoffdaten, 2017.
25. Council Directive 91/414/EEC of 15 July 1991 concerning the placing of plant protection products on the market, http://eur-lex.europa.eu/legal-content/en/ALL/?uri=CELEX:31991L0414
26. FAO (2015): FAO (Food and Agriculture Organization of the United Nations) Specifications and Evaluations for Chlorothalonil, p 51. http://www.fao.org/agriculture/crops/thematic-sitemap/theme/pests/jmps/ps-new/en/
27. FAO (2012): FAO (Food and Agriculture Organization of the United Nations)Specifications and Evaluations for Picloram, Table 2, p. 23. http://www.fao.org/agriculture/crops/thematic-sitemap/theme/pests/jmps/ps-new/en/.
28. Ferrari, F., Klein, M., Capri, E., & Trevisan, M. (2005). Prediction of pesticide volatilization with PELMO 3.31. Chemosphere, 60 (5), 705-713.
29. Klein, M. (2017), Calculation of emission factors for impurities in organic pesticides with PELMO. Personel communication. [Description available, Umweltbundesamt, FG I 2.6,Emissionssituation].
30. IPCS (1996), Chlorothalonil. Environmental Health Criteria, 183. 145pp. WHO, Geneva, Switzerland. ISBN 92-4-157183-7. C12138614.7.
31. EMEP EB, 2012: EMEP Executive Body Decision 3/2012 in ECE/EB.AIR/111/Add.1 - Adjustments under the Gothenburg Protocol to emission reduction commitments or to inventories for the purposes of comparing total national emissions with them
URL: http://www.ceip.at/fileadmin/inhalte/emep/Adjustments/ECE_EB.AIR_111_Add.1__ENG_DECISION_3.pdf.
32. EMEP EB, 2012: EMEP Executive Body DecisionDecision 2014/1 - Improving the guidance for adjustments under the 1999 Protocol to Abate Acidification, Eutrophication and Ground-level Ozone to emission reduction commitments or to inventories for the purposes of comparing total national emissions with them
URL: http://www.ceip.at/fileadmin/inhalte/emep/Adjustments/Decision_2014_1.pdf.
33. COMMISSION IMPLEMENTING REGULATION (EU) No 540/2011 of 25 May 2011 implementing Regulation (EC) No 1107/2009 of the European Parliament and of the Council as regards the list of approved active substances. http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A32011R0541.
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