The Sustainable and Integrated Management Systems for Dairy Production (SIMSDAIRY) is a whole farm system-based model that considers the interactions between climatic conditions, biophysical characteristics, and farm management practices on the carbon and nitrogen footprint of Dairy Production Systems (DPS).

In the DairyMix platform, SIMSDAIRY is used to model mitigation strategies for greenhouse gases and nitrogen losses for different DPS in Europe.

Selected mitigation options and their combinations have been modeled for each DPS, comparing “mitigated states” with the baseline. The results show how different structural and management characteristics largely condition DPS emissions. The effect of mitigation measures and their combination is context-specific.

Select the Dairy Production System:
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WCi (Western European conventional intensive system)

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WOs (Western European organic semi-extensive system)

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ECs (Central-Eastern European conventional semi-extensive system)

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MCi (Mediterranean conventional intensive system)

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NCs (North European conventional semi-extensive system)

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ACs (Atlantic European conventional semi-extensive system)

  • The key features of the DPS are shown here.
  • The mitigation measures adopted are described here.

Read more about the methodology.

The semi-mechanistic methodology followed by the SIMSDAIRY model applies empirical and dynamic approaches to simulate different environmental aspects of sustainability, making it sensitive to different climatic and biophysical conditions. SIMSDAIRY estimates the methane (CH4), carbon dioxide (CO2), nitrous oxide (N2O), ammonia (NH3), nitrogen oxide (NOX) emissions and nitrate (NO3–) losses from the different component of the dairy production system: animals, housings, manure storages, fields, silos, feed/fertilizer purchase and energy use. The different emissions are aggregated to calculate greenhouse gas/nitrogen footprints and individual emission intensities (per liter of milk).

As for CH4, the model considers both the enteric and manure emissions. Regarding enteric fermentation, SIMSDAIRY considers the relationship between dry matter intake (DMI) and the degree of unsaturated fatty acids in the diet as a proxy for estimating these emissions. For CH4 emissions from manure management, these are calculated using specific emission factors (EF) for the manure excreta and IPCC methodology for the manure storage stage.

Regarding N losses, these are simulated following the principles of a mass-balance approach. Relevant emissions for the nitrogen footprint, such as N2O, NH3 and NOx, are simulated from the pool of total ammonium nitrogen (TAN) in manure nitrogen according to different EF for different management stages. Furthermore, NO3– losses are estimated taking into account the biological processes of plant uptake, denitrification, nitrification and mineralization as well as the weather conditions, soil texture, fertilization and grazing management.

Previous works have fully described and discussed the limitations of the model. The reference study can be found here. Other references can be found below.

References

Casey JW, Holden NM (2005) Analysis of greenhouse gas emissions from the average Irish milk production system. Agric Syst 86:97–114. https://doi.org/10.1016/j.agsy.2004.09.006

Chadwick DR, Pain BF (1997) Methane fluxes following slurry applications to grassland soils: Laboratory experiments. Agric Ecosyst Environ 63:51–60. https://doi.org/10.1016/S0167-8809(96)01119-X

DEFRA (2010) Guidelines to Defra/DECC’s greenhouse gas conversion factors for company reporting

Del Prado A, Chadwick D, Cardenas L, et al (2010) Exploring systems responses to mitigation of GHG in UK dairy farms. Agric Ecosyst Environ 136:318–332. https://doi.org/10.1016/j.agee.2009.09.015

Del Prado A, Chadwick D, Scholefield D (2009) New integrated dairy production systems: Specification, practical feasibility and ways of implementation

Del Prado A, Misselbrook T, Chadwick D, et al (2011) SIMSDAIRY: A modelling framework to identify sustainable dairy farms in the UK. Framework description and test for organic systems and N fertiliser optimisation. Sci Total Environ 409:3993–4009. https://doi.org/10.1016/j.scitotenv.2011.05.050

Del Prado A, Scholefield D (2008) Use of SIMSDAIRY modelling framework system to compare the scope on the sustainability of a dairy farm of animal and plant genetic-based improvements with management-based changes. J Agric Sci 146:195–211. https://doi.org/10.1017/S0021859608007727

Díaz de Otálora X, del Prado A, Dragoni F, Balaine L, Pardo G, Winiwarter, W, … & Amon B (2024). Modelling the effect of context-specific greenhouse gas and nitrogen emission mitigation options in key European dairy farming systems. Agronomy for Sustainable Development, 44(1), 4. https://doi.org/10.1007/s13593-023-00940-6

Giger-Reverdin S, Morand-Fehr P, Tran G (2003) Literature survey of the influence of dietary fat composition on methane production in dairy cattle. Livest Prod Sci 82:73–79. https://doi.org/10.1016/S0301-6226(03)00002-2

IPCC (1997) IPCC Guidelines for National Greenhouse Gas Inventories. Paris

Webb J, Misselbrook TH (2004) A mass-flow model of ammonia emissions from UK livestock production. Atmos Environ 38:2163–2176. https://doi.org/10.1016/j.atmosenv.2004.01.023

Yamulki S, Jarvis SC, Owen P (1999) Methane Emission and Uptake from Soils as Influenced by Excreta Deposition from Grazing Animals. J Environ Qual 28:676–682. https://doi.org/10.2134/jeq1999.00472425002800020036x