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Variation in carbon footprint of milk due to management differences between Swedish dairy farms

Published online by Cambridge University Press:  31 March 2011

M. Henriksson ,
A. Flysjö ,
C. Cederberg  and
C. Swensson
M. Henriksson*
Affiliation:
Department of Rural Buildings and Animal Husbandry, Swedish University of Agricultural Sciences, PO Box 86, SE-23053 Alnarp, Sweden
A. Flysjö
Affiliation:
Arla Foods amba, Sønderhøj 14, DK-8260 Viby J, Denmark Department of Agroecology and Environment, Aarhus University, PO Box 50, DK-8830 Tjele, Denmark
C. Cederberg
Affiliation:
SIK – the Swedish Institute for Food and Biotechnology, PO Box 5401, SE-40229 Gothenburg, Sweden
C. Swensson
Affiliation:
Department of Rural Buildings and Animal Husbandry, Swedish University of Agricultural Sciences, PO Box 86, SE-23053 Alnarp, Sweden Swedish Dairy Association, Scheelevägen 18, SE-223 63 Lund, Sweden
*
†E-mail: [email protected]
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Abstract

To identify mitigation options to reduce greenhouse gas (GHG) emissions from milk production (i.e. the carbon footprint (CF) of milk), this study examined the variation in GHG emissions among dairy farms using data from previous CF studies on Swedish milk. Variations between farms in these production data, which were found to have a strong influence on milk CF, were obtained from existing databases of 1051 dairy farms in Sweden in 2005. Monte Carlo (MC) analysis was used to analyse the impact of variations in seven important parameters on milk CF concerning milk yield (energy-corrected milk (ECM) produced and delivered), feed dry matter intake (DMI), enteric CH4 emissions, N content in feed DMI, N-fertiliser rate and diesel used on farm. The largest between-farm variations among the analysed production data were N-fertiliser rate (kg/ha) and diesel used (l/ha) on farm (CV = 31% to 38%). For the parameters concerning milk yield and feed DMI, the CV was approximately 11% and 8%, respectively. The smallest variation in production data was found for N content in feed DMI. According to the MC analysis, these variations in production data led to a variation in milk CF of between 0.94 and 1.33 kg CO2 equivalents (CO2e)/kg ECM, with an average value of 1.13 kg CO2e/kg ECM. We consider that this variation of ±17%, which was found to be based on the used farm data, would be even greater if all Swedish dairy farms were included, as the sample of farms in this study was not totally unbiased. The variation identified in milk CF indicates that a potential exists to reduce GHG emissions from milk production on both the national and farm levels through changes in management. As milk yield and feed DMI are two of the most influential parameters for milk CF, feed conversion efficiency (i.e. units ECM produced/unit DMI) can be used as a rough key performance indicator for predicting CF reductions. However, it must be borne in mind that feeds have different CF due to where and how they are produced.

Keywords

Monte Carlo analysislife-cycle assessmentgreenhouse gasesfeed efficiencyproduction parameters
Type
Full Paper
Information
animal , Volume 5 , Issue 9 , 05 August 2011 , pp. 1474 - 1484
Copyright
Copyright © The Animal Consortium 2011

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