Accounting for inter-annual variability of farm activity data for calculation of greenhouse gas emissions in dairy farming

  • Maximilian Schueler
  • Hans Marten Paulsen
  • Werner Berg
  • Annette Prochnow



This study examines the inter-annual variability of production data in an organic dairy farm and its effect on the estimation of product-related greenhouse gas emissions (GHG) using a detailed material flow model. It is believed that the examination of only one production year may not adequately reflect temporal representativeness and may therefore lead to unreliable results. The current study also provides a method to deal with variability when temporal representativeness cannot be ensured.


All material flows related to milk production from six consecutive milk years in an organic dairy farm in northern Germany were analysed. The milk yield of the 75 to 91 cows varied between 5418 and 7102 kg energy corrected milk (ECM) per cow and year. GHG emissions were estimated using calculation guidelines from the International Dairy Federation (IDF) and the Intergovernmental Panel on Climate Change (IPCC). Emissions were calculated in the Flow Analysis and Resource Management (FARM) model ensuring mass balances for nitrogen and phosphorous in every subsection of the model. Based on the variability of crop yields, the number of years for representative average data was calculated as well as an uncertainty when only a limited number of years was available.

Results and discussion

Estimated GHG emissions varied between 0.88 and 1.09 kg CO2-eq kg−1 ECM−1 (mean, standard deviation of the mean = 0.97 and 0.07 kg CO2-eq kg−1 ECM−1). Emissions from ruminant digestion had the highest contribution (50.9 ± 2.3) percent in relation to overall product-related GHG emissions. Direct emissions from soil showed the highest coefficient of variation (36%) due to simultaneous changes in fertilization amount, crop yield and milk yield which showed no significant direct relationship. The number of years needed to be assessed for representative average yields was between 27 and 215 years for clover grass and maize silage, respectively. When performing a sensitivity analysis based on the variability of crop yields, the assessed farm showed reliable results with average data of at least 4 years.


Temporal representativeness should be dealt with explicitly in GHG assessments for dairy farming. If the representativeness of crop yields cannot be ensured, an uncertainty bandwidth of the results based on variability of yields can provide a basis for comparing different farms or farming systems. This approach could also be extended to other variabilities in dairy farming for more reliability of results.


LCA Milk Milk production Organic farming 


  1. Allen MS (2000) Effects of diet on short-term regulation of feed intake by lactating dairy cattle. J Dairy Sci 83(7):1598–1624CrossRefGoogle Scholar
  2. Althaus HJ, Chudacoff M, Hischier R, Jungbluth N, Osses M, A. P (2007) Life Cycle Inventories of Chemicals. Final report ecoinvent data v2.0 No. 8. Swiss Centre for Life Cycle Inventories, DübendorfGoogle Scholar
  3. Brade VW, Dammgen U, Lebzien P, Flachowsky G (2008) Milk production and emissions of greenhouse gases. Berichte Uber Landwirtschaft 86(3):445–460Google Scholar
  4. Cederberg C, Mattson B (2000) Life cycle assessment of milk production—a comparison of conventional and organic farming. J Clean Prod 8(1):49–60CrossRefGoogle Scholar
  5. Cederberg C, Stadig M (2003) System expansion and allocation in life cycle assessment of milk and beef production. Int J Life Cycle Assess 8(6):350–356CrossRefGoogle Scholar
  6. Dämmgen U, Hutchings NJ (2008) Emissions of gaseous nitrogen species from manure management: a new approach. Environ Pollut 154(3):488–497CrossRefGoogle Scholar
  7. EC (2007) No 834/2007 of 28 June 2007 on organic production and labelling of organic products and repealing Regulation (EEC) No 2092/91Google Scholar
  8. EC (2009) No 1307/2013 of the European Parliament and of the Council. EstablishingEstablishing rules for direct payments to farmers under support schemes within the framework of the common agricultural policy and repealing Council Regulation (EC) No 637/2008 and Council Regulation (EC) No 73/2009Google Scholar
  9. Eide MH (2002) Life cycle assessment (LCA) of industrial milk production. Int J Life Cycle Assess 7(2):115–126CrossRefGoogle Scholar
  10. Ellis JL, Bannink A, France J, Kebreab E, Dijkstra J (2010) Evaluation of enteric methane prediction equations for dairy cows used in whole farm models. Global Change Biology 16(12):3246–3256Google Scholar
  11. FAOSTAT (2015) Food and Agriculture Organization of the United Nations. Statistics, Rome, Italy. Retrieved August 15, 2015, from
  12. Flysjo A, Cederberg C, Henriksson M, Ledgard S (2011) How does co-product handling affect the carbon footprint of milk? Case study of milk production in New Zealand and Sweden. Int J Life Cycle Assess 16(5):420–430CrossRefGoogle Scholar
  13. Frank H, Schmid H, Huelsbergen KJ (2013) Energie- und Treibhausgasbilanz milchviehhaltender Landwirtschaftsbetriebe in Süd- und Westdeutschland. in Huelsbergen KJ, Rahmann G (2013) (eds) Klimawirkungen und Nachhaltigkeit ökologischer und konventioneller Betriebssysteme – Untersuchungen in einem Netzwerk von Pilotbetrieben Braunschweig, 383 p, Thünen Report 8Google Scholar
  14. Frank H, Schmid H, Hülsbergen KJ (2015) Energie- und Treibhausgasbilanz der Milchviehhaltung – Untersuchungen im Netzwerk der Pilotbetriebe. Thünen Rep 29:25–48 abstract in EnglishGoogle Scholar
  15. Gardenas AI, Agren GI, Bird JA, Clarholm M, Hallin S, Ineson P, Katterer T, Knicker H, Nilsson SI, Nasholm T, Ogle S, Paustian K, Persson T, Stendahl J (2011) Knowledge gaps in soil carbon and nitrogen interactions—from molecular to global scale. Soil Biol Biochem 43(4):702–717CrossRefGoogle Scholar
  16. GfE (2001) Gesellschaft für Ernährungsphysiologie der Haustiere / Ausschuss für Bedarfsnormen: Empfehlungen zur Energie- und Nährstoffversorgung der Milchkühe und Aufzuchtrinder, vol 8. Energie- und Nährstoffbedarf landwirtschaftlicher Nutztiere. DLG-Verl., Frankfurt am MainGoogle Scholar
  17. L Gruber, M Pries, H Spiekers, FJ Schwarz, W Staudacher (2006) Schätzung der Futteraufnahme bei der Milchkuh. DLG-Informationen 1/2006. Retrieved August 15, 2015, from
  18. Guerci M et al (2013) Parameters affecting the environmental impact of a range of dairy farming systems in Denmark, Germany and Italy. J Clean Prod 54:133–141CrossRefGoogle Scholar
  19. Guerci M et al (2014) Effect of summer grazing on carbon footprint of milk in Italian Alps: a sensitivity approach. J Clean Prod 73:236–244CrossRefGoogle Scholar
  20. Haas G, Wetterich F, Geier U (2000) Life cycle assessment framework in agriculture on the farm level. Int J Life Cycle Assess 5(6):345–348CrossRefGoogle Scholar
  21. IDF (2010) A common carbon footprint approach for dairy—the IDF guide to standard lifecycle assessement methodology for the dairy sector. Bulletin 445/2010, International Dairy FederationGoogle Scholar
  22. ILCD (2010) European Commission–Joint Research Centre–Institute for Environment and Sustainability: International Reference Life Cycle Data System (ILCD) handbook—general guide for life cycle assessment—detailed guidance. First edition March 2010. EUR 24708 EN. Luxembourg. Publications Office of the European Union; 2010Google Scholar
  23. IPCC (2006) IPCC guidelines for national greenhouse gas inventories, Prepared by the National Greenhouse Gas Inventories Programme. IGES, JapanGoogle Scholar
  24. ISO 14040 (2006) International Organization for Standardization, Geneva, Switzerland, In: Environmental management—life cycle assessment—principles and framework.
  25. Jeroch H, Drochner W, Simon O (1999) Ernährung landwirtschaftlicher Nutztiere: Ernährungsphysiologie, Futtermittelkunde, Fütterung. UTB für WissenschaftGoogle Scholar
  26. Koerber GR, Edwards-Jones G, Hill PW, Canals LMI, Nyeko P, York EH, Jones DL (2009) Geographical variation in carbon dioxide fluxes from soils in agro-ecosystems and its implications for life-cycle assessment. J Appl Ecol 46(2):306–314CrossRefGoogle Scholar
  27. Koesling M, Ruge G, Fystro G, Torpe T, Hansen S (2015) Embodied and operational energy in buildings on 20 Norwegian dairy farms—introducing the building construction approach to agriculture. Energ Build 108:330–345CrossRefGoogle Scholar
  28. Köhler W et al (2012) Biostatistik. Eine Einführung für Biologen und Agrarwissenschaftler. Springer-Lehrbuch. Berlin [u.a.], Springer: Online-Ressource (XII, 334 S)Google Scholar
  29. KTBL (2004) Kuratorium für Technik und Bauwesen in der Landwirtschaft e.V.: Betriebsplanung Landwirtschaft 2004/2005. KTBL-Datensammlung. Daten für die Betriebsplanung in der Landwirtschaft. 19., Aufl. edn. Landwirtschaftsvlg Münster, Münster, WestfGoogle Scholar
  30. KTBL (2014) KTBL-Dieselbedarf. Online resource for calcuation of diesel fuel demand. http://datenktblde/dieselbedarf/mainhtml
  31. Meyer U (2005) Fütterung von Kälbern und Jungrindern. In: Brade W, Flachowsky G (eds) Rinderzucht und Milcherzeugung Empfehlungen für die Praxis Braunschweig, pp 127–136 Landbauforschung Völkenrode - FAL Agricultural Research Special Issue 289Google Scholar
  32. Müller-Lindenlauf M, Deittert C, Köpke U (2010) Assessment of environmental effects, animal welfare and milk quality among organic dairy farms. Livest Sci 128(1–3):140–148CrossRefGoogle Scholar
  33. Nemecek T, Erzinger S (2005) Modelling representative life cycle inventories for Swiss arable crops. Int J Life Cycle Assess 10(1):68–76CrossRefGoogle Scholar
  34. Nemecek T, Kägi T, Blaser S (2007) Life cycle inventories of agricultural production systems. Ecoinvent report version 2.0. Swiss Centre for LCI, ARTGoogle Scholar
  35. Nguyen TLT, Hermansen JE, Mogensen L (2010) Environmental consequences of different beef production systems in the EU. J Clean Prod 18(8):756–766CrossRefGoogle Scholar
  36. Novak SM, Fiorelli JL (2010) Greenhouse gases and ammonia emissions from organic mixed crop-dairy systems: a critical review of mitigation options. Agron Sustain Dev 30(2):215–236CrossRefGoogle Scholar
  37. Ohm M, Schüler M, Warnecke S, Paulsen H, Rahmann G (2014) Measurement methods on pastures and their use in environmental life-cycle assessment. Org Agr 4(4):325–329CrossRefGoogle Scholar
  38. Paulsen HM, Warnecke S, Schmid H, Frank H, Brinkmann J, March S, Koopmann R (2015) Haltungsbedingungen, Tiergesundheits- und Tierwohlparameter und Medikamenteneinsatz in der Milchviehhaltung auf je zwei ökologischen und konventionellen Betrieben sowie Auswirkungen von Optimierungsansätzen zur Verbesserung der Situation der Tiere auf die Klimabilanz der Milcherzeugung. Thünen Rep 29:119–148 abstract in EnglishGoogle Scholar
  39. Petersen BM, Knudsen MT, Hermansen JE, Halberg N (2013) An approach to include soil carbon changes in life cycle assessments. J Clean Prod 52:217–224CrossRefGoogle Scholar
  40. Piatkowski B, Jentsch W, Derno M (2010) New results on methane production and its estimation for cattle. Zuchtungskunde 82(5):400–407Google Scholar
  41. Rösemann C et al (2013) Calculations of gaseous and particulate emissions from German agriculture. 1990–2011; report on methods and data (RMD) submission 2013. Calculations of gaseous and particulate emissions from German agriculture; 2013=1990–2011: Online-Ressource (PDF-Datei: 386 S., 6662 KB)Google Scholar
  42. Schulz F, Warnecke S, Paulsen HM, Rahmann G (2013) Unterschiede der Fütterung ökologischer und konventioneller Betriebe und deren Einfluss auf die Methan-Emissionen aus der Verdauung von Milchkühen. In: Huelsbergen KJ, Rahmann G (eds) Klimawirkungen und Nachhaltigkeit ökologischer und konventioneller Betriebssysteme. Untersuchungen in einem Netzwerk von Pilotbetrieben, Braunschweig p 383, Thünen Report 8Google Scholar
  43. Thoma G, Popp J, Nutter D, Shonnard D, Ulrich R, Matlock M, Kim DS, Neiderman Z, Kemper N, East C, Adom F (2013) Greenhouse gas emissions from milk production and consumption in the United States: a cradle-to-grave life cycle assessment circa 2008. Int Dairy J 31:S3–S14CrossRefGoogle Scholar
  44. Thomassen MA, Dalgaard R, Heijungs R, de Boer I (2008a) Attributional and consequential LCA of milk production. Int J Life Cycle Assess 13(4):339–349CrossRefGoogle Scholar
  45. Thomassen MA, van Calker KJ, Smits MCJ, Iepema GL, de Boer IJM (2008b) Life cycle assessment of conventional and organic milk production in the Netherlands. Agric Syst 96(1–3):95–107CrossRefGoogle Scholar
  46. Warnecke S, Paulsen H, Schulz F, Rahmann G (2014) Greenhouse gas emissions from enteric fermentation and manure on organic and conventional dairy farms—an analysis based on farm network data. Org Agr 4(4):285–293CrossRefGoogle Scholar
  47. Windisch W, Kirchgessner M, Kreuzer M (1991) Manure quantity of lactating dairy-cows as affected by varying production intensity. Agribiol Res 44(2–3):170–181Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.Thünen Institute of Organic FarmingWesterauGermany
  2. 2.Leibniz Institute for Agricultural EngineeringPotsdamGermany
  3. 3.Faculty of Life Sciences, Chair Utilization Strategies for BioresourcesHumboldt-Universität zu BerlinBerlinGermany

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