An operational method for the evaluation of resource use and environmental impacts of dairy farms by life cycle assessment.
This paper describes and applies EDEN-E, an operational method for the environmental evaluation of dairy farms based on the life cycle assessment (LCA) conceptual framework. EDEN-E requires a modest amount of data readily available on-farm, and thus can be used to assess a large number of farms at a reasonable cost. EDEN-E estimates farm resource use and pollutant emissions mostly at the farm scale, based on-farm-gate balances, amongst others. Resource use and emissions are interpreted in terms of potential impacts: eutrophication, acidification, climate change, terrestrial toxicity, non-renewable energy use and land occupation. The method distinguishes for each total impact a direct component (impacts on the farm site) and an indirect component (impacts associated with production and supply of inputs used). A group of 47 dairy farms (41 conventional and six organic) was evaluated. Expressed per 1000kg of fat-and-protein-corrected milk, total land occupation was significantly larger for organic than for conventional farms, while total impacts for eutrophication, acidification, climate change, terrestrial toxicity, and non-renewable energy use were not significantly different for the two production modes. When expressed per ha of land occupied all total impacts were significantly larger for conventional than organic farms. This study largely confirms previously published findings concerning the effect of production mode on impacts of dairy farms. However, it strikingly reveals that, for the set of farms examined, the contribution of production mode to overall inter-farm variability of impacts was minor relative to inter-farm variability within each of the two production modes examined. The mapping of impact variability through EDEN-E opens promising perspectives to move towards sustainable farming systems by identifying the structural and management characteristics of the farms presenting the lowest impacts.
van der Werf
Hayo M G
HM
INRA, UMR 1069 Sol Agro et hydrosystème Spatialisation, F-35000 Rennes, France. hayo.vanderWerf@rennes.inra.fr
Kanyarushoki
Claver
C
Corson
Michael S
MS
D000818:Animals; D002417:Cattle; D003612:Dairying; D004784:Environmental Monitoring / Q000379:methods*; D004787:Environmental Pollution / Q000517:prevention & control*; D008962:Models, Theoretical