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Discrimination of milk carbon footprints from different dairy farms when using IPCC Tier 1 methodology for calculation of GHG emissions from managed soils

Schueler, Maximilian; Hansen, Sissel and Paulsen, Hans Marten (2018) Discrimination of milk carbon footprints from different dairy farms when using IPCC Tier 1 methodology for calculation of GHG emissions from managed soils. Journal of Cleaner Production, 177, pp. 899-907.

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Online at: https://www.sciencedirect.com/science/article/pii/S0959652617332171?via%3Dihub

Summary

Quantification of the environmental performance of dairy farms should allow comparisons between farms. We assess whether IPCC Tier 1 methodology for emissions from soil management is sufficiently precise to analyse and differentiate the carbon footprint of milk production between practical dairy farms and whether we can correctly identify which farms have the lowest and the highest GHG emissions per product unit, respectively.
We used data from 20 Norwegian dairy farms which are very similar in structure, but differ in organic/non-organic management and the share of peat soil of their farmland.We assessed the uncertainty of the carbon footprint by running Monte Carlo simulations with the uncertainty ranges given in Tier 1 of the IPCC guidelines. The carbon footprint is considered different when 95% of all Monte Carlo iterations assume that one farm has higher product-related GHG emissions than the farm in comparison. The uncertainty of results in the single farms, expressed as two-times the standard deviation divided by the median result, ranges between 4.2% and 15.3%. This means that 95% of values in the resulting distribution of one farm are within a range of 4e16% of the median of that farm. Farms can be differentiated when the variation of the carbon footprint is higher than the uncertainty of farm-related emissions. From all 190 direct comparisons of two farms in the tudy, 78% are significantly different.For this uncertainty assessment, it must be established that background processes, especially the datasets for import feed, can be judged covariant in order to prohibit them from influencing the comparison between farms. Secondly, the uncertainty ranges used for the calculation must be appropriate for the assessed systems. We were able to confirm the hypothesis that a significant differentiation of the milk carbon footprint between farms is possible with an IPCC Tier 1 approach for a majority of our comparisons, and found a difference of above 8.7% sufficient to establish significance.


EPrint Type:Journal paper
Keywords:Sensitivity,Uncertainty,IDF,CF,Variability,Monte Carlo,Dairy farming,organic farming,sustainability,
Subjects: Animal husbandry > Production systems
"Organics" in general
Animal husbandry
Environmental aspects > Air and water emissions
Research affiliation: Germany > Federal Research Institute for Rural Areas, Forestry and Fisheries - VTI > Institute of Organic Farming - OEL
Norway > NORSØK - Norwegian Centre for Organic Agriculture
ISSN:0959-6526
Deposited By: Pommeresche, Reidun
ID Code:34662
Deposited On:23 Feb 2019 12:35
Last Modified:23 Feb 2019 12:35
Document Language:English
Status:Published
Refereed:Peer-reviewed and accepted

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