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How do farm models compare when estimating greenhouse gas emissions from dairy cattle production?

Published online by Cambridge University Press:  09 January 2018

N. J. Hutchings ,
Ş. Özkan Gülzari ,
M. de Haan  and
D. Sandars
N. J. Hutchings*
Affiliation:
Department of Agroecology, Aarhus University, Blichers Allé 20, P.O. Box 50, Tjele 8830, Denmark
Ş. Özkan Gülzari
Affiliation:
Department of Animal and Aquacultural Sciences, Faculty of Veterinary Medicine and Biosciences, Norwegian University of Life Sciences (NMBU), PO Box 5003, Ås 1430, Norway Norwegian Institute of Bioeconomy Research (NIBIO), PO Box 115, Ås 1431, Norway
M. de Haan
Affiliation:
Wageningen UR, Livestock Research, PO Box 338 Wageningen, 6700AH, The Netherlands
D. Sandars
Affiliation:
School of Water, Energy, and Environment, Cranfield University, Bedford MK43 0AL, UK
*
†E-mail: nick.hutchings@agro.au.dk
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Abstract

The European Union Effort Sharing Regulation (ESR) will require a 30% reduction in greenhouse gas (GHG) emissions by 2030 compared with 2005 from the sectors not included in the European Emissions Trading Scheme, including agriculture. This will require the estimation of current and future emissions from agriculture, including dairy cattle production systems. Using a farm-scale model as part of a Tier 3 method for farm to national scales provides a more holistic and informative approach than IPCC (2006) Tier 2 but requires independent quality control. Comparing the results of using models to simulate a range of scenarios that explore an appropriate range of biophysical and management situations can support this process by providing a framework for placing model results in context. To assess the variation between models and the process of understanding differences, estimates of GHG emissions from four farm-scale models (DairyWise, FarmAC, HolosNor and SFARMMOD) were calculated for eight dairy farming scenarios within a factorial design consisting of two climates (cool/dry and warm/wet)×two soil types (sandy and clayey)×two feeding systems (grass only and grass/maize). The milk yield per cow, follower:cow ratio, manure management system, nitrogen (N) fertilisation and land area were standardised for all scenarios in order to associate the differences in the results with the model structure and function. Potential yield and application of available N in fertiliser and manure were specified separately for grass and maize. Significant differences between models were found in GHG emissions at the farm-scale and for most contributory sources, although there was no difference in the ranking of source magnitudes. The farm-scale GHG emissions, averaged over the four models, was 10.6 t carbon dioxide equivalents (CO2e)/ha per year, with a range of 1.9 t CO2e/ha per year. Even though key production characteristics were specified in the scenarios, there were still significant differences between models in the annual milk production per ha and the amounts of N fertiliser and concentrate feed imported. This was because the models differed in their description of biophysical responses and feedback mechanisms, and in the extent to which management functions were internalised. We conclude that comparing the results of different farm-scale models when applied to a range of scenarios would build confidence in their use in achieving ESR targets, justifying further investment in the development of a wider range of scenarios and software tools.

Keywords

dairy cattlefarm-scalemodelgreenhouse gas
Type
Research Article
Information
animal , Volume 12 , Issue 10 , October 2018 , pp. 2171 - 2180
Copyright
© The Animal Consortium 2018 

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References

Alemu, AW, Janzen, H, Little, S, Hao, X, Thompson, DJ, Baron, V, Iwaasa, A, Beauchemin, KA and Kröbel, R 2017. Assessment of grazing management on farm greenhouse gas intensity of beef production systems in the Canadian Prairies using life cycle assessment. Agricultural Systems 158, 1–13.Google Scholar
Annetts, JE and Audsley, E 2002. Multiple objective linear programming for environmental farm planning. Journal of the Operational Research Society 53, 933–943.Google Scholar
Bellarby, J, Tirado, R, Leip, A, Weiss, F, Lesschen, JP and Smith, P 2013. Livestock greenhouse gas emissions and mitigation potential in Europe. Global Change Biology 19, 3–18.Google Scholar
Beukes, PC, Gregorini, P and Romera, AJ 2011. Estimating greenhouse gas emissions from new Zealand dairy systems using a mechanistic whole farm model and inventory methodology. Animal Feed Science and Technology 166–67, 708–720.Google Scholar
Bonesmo, H, Skjelvag, AO, Janzen, HH, Klakegg, O and Tveito, OE 2012. Greenhouse gas emission intensities and economic efficiency in crop production: a systems analysis of 95 farms. Agricultural Systems 110, 142–151.Google Scholar
Brentrup, F, Kusters, J, Lammel, J and Kuhlmann, H 2000. Methods to estimate on-field nitrogen emissions from crop production as an input to LCA studies in the agricultural sector. International Journal of Life Cycle Assessment 5, 349–357.Google Scholar
Casey, JW and Holden, NM 2005. The relationship between greenhouse gas emissions and the intensity of milk production in Ireland. Journal of Environmental Quality 34, 429–436.Google Scholar
Christie, KM, Rawnsley, RP and Eckard, RJ 2011. A whole farm systems analysis of greenhouse gas emissions of 60 Tasmanian dairy farms. Animal Feed Science and Technology 166–67, 653–662.Google Scholar
Crosson, P, Shalloo, L, O’Brien, D, Lanigan, GJ, Foley, PA, Boland, TM and Kenny, DA 2011. A review of whole farm systems models of greenhouse gas emissions from beef and dairy cattle production systems. Animal Feed Science and Technology 166–67, 29–45.Google Scholar
Cullen, BR and Eckard, RJ 2011. Impacts of future climate scenarios on the balance between productivity and total greenhouse gas emissions from pasture based dairy systems in south-eastern Australia. Animal Feed Science and Technology 166–67, 721–735.Google Scholar
Del Prado, A, Crosson, P, Olesen, JE and Rotz, CA 2013. Whole-farm models to quantify greenhouse gas emissions and their potential use for linking climate change mitigation and adaptation in temperate grassland ruminant-based farming systems. Animal 7, 373–385.Google Scholar
Erbach, G 2016. Effort sharing regulation, 2021-2030. Limiting member states’ carbon emissions. European Parliamentary Research Service, Brussels. Accessed October 2017 from http://www.europarl.europa.eu/RegData/etudes/BRIE/2016/589799/EPRS_BRI(2016)589799_EN.pdf Google Scholar
European Commission 1991. Council directive of 12 December 1991 concerning the protection of waters against pollution caused by nitrates from agricultural sources. Official Journal of the European Communities L 375/1, pp 1--8.Google Scholar
European Commission 2009. Decision no 406/2009/ec of the European Parliament and of the Council of 23 April 2009 on the effort of member states to reduce their greenhouse gas emissions to meet the community’s greenhouse gas emission reduction commitments up to 2020. Official Journal of the European Union L 140, 136–148.Google Scholar
European Commission 2013. Regulation (EU) no 525/2013 of the European Parliament and of the Council of 21 May 2013 on a mechanism for monitoring and reporting greenhouse gas emissions and for reporting other information at national and Union level relevant to climate change and repealing Decision No 280/2004/EC. Official Journal of the European Union L 165/13, 28.Google Scholar
European Commission 2014. Commission implementing decision of 16 May 2014 granting a derogation requested by the Netherlands pursuant to council directive 91/676/eec concerning the protection of waters against pollution caused by nitrates from agricultural sources (notified under document c(2014) 3103). Accessed October 2017 http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32014D0291 Google Scholar
European Commission 2017. Agriculture and rural development. Milk and milk products. Accessed 21 September 2017 https://ec.europa.eu/agriculture/milk_en Google Scholar
Food and Agriculture Organisation 2010. Greenhouse gas emissions from the dairy sector. A life cycle assessment. UN Food and Agriculture Organisation, Rome, Italy.Google Scholar
Friedman, M 1940. A Comparison of Alternative Tests of Significance for the Problem of $m$ Rankings. Ann. Math. Statist 11, 86–92.Google Scholar
Gerber, P, Vellinga, T, Opio, C and Steinfeld, H 2011. Productivity gains and greenhouse gas emissions intensity in dairy systems. Livestock Science 139, 100–108.Google Scholar
Hagemann, M, Ndambi, A, Hemme, T and Latacz-Lohmann, U 2012. Contribution of milk production to global greenhouse gas emissions. Environmental Science and Pollution Research 19, 390–402.Google Scholar
Hutchings, NJ and Kristensen, IS 2015. The FarmAC model. http://www.farmac.dk. Accessed October 2017.Google Scholar
IPCC 2006. IPCC guidelines for national greenhouse gas inventories (ed. S Eggleston, L Buendia, K Miwa, T Nagara and K Tanabe), National Greenhouse Gas Inventories Programme, Japan.Google Scholar
Jarvis, SC, Hutchings, NJ, Brentrup, F, Olesen, JE and van der Hoek, K 2011. Nitrogen flows in farming systems across Europe. In European nitrogen assessment (ed. MA Sutton, CM Howard, JW Erisman, G Billen, A Bleeker, P Grennfelt, Hv Grinsven and B Grizzetti), pp. 211–218. Cambridge University Press.Google Scholar
Johnson, IR, Chapman, DF, Snow, VO, Eckard, RJ, Parsons, AJ, Lambert, MG and Cullen, BR 2008. Dairymod and ecomod: biophysical pasture-simulation models for Australia and New Zealand. Australian Journal of Experimental Agriculture 48, 621–631.Google Scholar
Kipling, RP, Bannink, A, Bellocchi, G, Dalgaard, T, Fox, NJ, Hutchings, NJ, Kjeldsen, C, Lacetera, N, Sinabell, F, Topp, CFE, van Oijen, M, Virkajarvi, P and Scollan, ND 2016. Modeling European ruminant production systems: facing the challenges of climate change. Agricultural Systems 147, 24–37.Google Scholar
McGinn, SM 2006. Measuring greenhouse gas emissions from point sources in agriculture. Canadian Journal of Soil Science 86, 355–371.Google Scholar
Myhre, GD, Shindell, FM, Bréon, W, Collins, J, Fuglestvedt, J, Huang, D, Koch, JF, Lamarque, DL, Mendoza, B, Nakajima, T, Robock, A, Stephens, GTT and Zhang, H 2013. Anthropogenic and natural radiative forcing. In Climate change 2013: the physical science basis. Contribution of working group i to the fifth assessment report of the intergovernmental panel on climate change (ed. TF Stocker, D Qin, GK Plattner, M Tignor, SK Allen, J Boschung, A Nauels, Y Xia, V Bex and PM Midgley), pp 659--740. Cambridge University Press, Cambridge, UK.Google Scholar
Nemenyi, PB 1963. Distribution-free multiple comparisons. PhD thesis, Princeton University, Princeton, NJ, USA.Google Scholar
O’Brien, D, Shalloo, L, Buckley, F, Horan, B, Grainger, C and Wallace, M 2011. The effect of methodology on estimates of greenhouse gas emissions from grass-based dairy systems. Agriculture Ecosystems & Environment 141, 39–48.Google Scholar
Özkan Gülzari, Ş., Aspeholen Åby, B, Persson, T, Höglind, M. and Mittenzwei, K 2017. Combining models to estimate the impacts of future climate scenarios on feed supply, greenhouse gas emissions and economic performance on dairy farms in Norway. Agricultural Systems 157, 157–169.Google Scholar
Pohlert, T 2014. The pairwise multiple comparison of mean ranks package (PMCMR) R package. Accessed October 2017 http://CRAN.R-project.org/package=PMCMR Google Scholar
Schils, RLM, de Haan, MHA, Hemmer, JGA, van den Pol-van Dasselaar, A, De Boer, JA, Evers, AG, Holshof, G, van Middelkoop, JC and Zom, RLG 2007. Dairywise, a whole-farm dairy model. Journal of Dairy Science 90, 5334–5346.Google Scholar
Tesco PLC 2016. Our carbon footprint. Accessed 14 February 2017. https://www.tescoplc.com/tesco-and-society/sourcing-great-products/reducing-our-impact-on-the-environment/our-carbon-footprint/ Google Scholar
Vellinga, TV, de Haan, MHA, Schils, RLM, Evers, A and van den Pol-van Dasselaar, A 2011. Implementation of GHG mitigation on intensive dairy farms: farmers’ preferences and variation in cost effectiveness. Livestock Science 137, 185–195.Google Scholar
Veltman, K, Jones, CD, Gaillard, R, Cela, S, Chase, L, Duval, BD, Izaurralde, RC, Ketterings, QM, Li, C, Matlock, M, Reddy, A, Rotz, A, William, S, Vadas, P and Jolliet, O 2017. Comparison of process-based models to quantify nutrient flows and greenhouse gas emissions associated with milk production. Agriculture, Ecosystems and Environment 237, 31–44.Google Scholar
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