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

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. Variation between farms in these production data, which were found to have a strong influence on milk CF were obtained from existing databases of e.g. 1051 dairy farms in Sweden in 2005. Monte Carlo 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 methane emissions, N content in feed DMI, N-fertiliser rate and diesel used on farm. The largest between farm variation among the analysed production data were N-fertiliser rate (kg/ha) and diesel used (l/ha) on farm (coefficient of variation (CV) 31-38%). For the parameters concerning milk yield and feed DMI the CV was approx. 11 and 8%, respectively. The smallest variation in production data was found for N content in feed DMI. According to the Monte Carlo analysis, these variations in production data led to a variation in milk CF of between 0.94 and 1.33 kg CO2 equivalents (CO2e) per kg ECM, with an average value of 1.13 kg/CO2e kg ECM. We consider that this variation of ±17% that was found 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 national and farm level 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 per 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

Greenhouse gas emissions of realistic dietary choices in Denmark: the carbon footprint and nutritional value of dairy products

Background: Dairy products are important in a healthy diet due to their high nutritional value; they are, however, associated with relatively large greenhouse gas emissions (GHGE) per kg product. When discussing the need to reduce the GHGE caused by the food system, it is crucial to consider the nutritional value of alternative food choices. Objective: The objective of this study was to elucidate the role of dairy products in overall nutrition and to clarify the effects of dietary choices on GHGE, and to combine nutritional value and GHGE data. Methods: We created eight dietary scenarios with different quantity of dairy products using data from the Danish National Dietary Survey (1995–2006). Nutrient composition and GHGE data for 71 highly consumed foods were used to estimate GHGE and nutritional status for each dietary scenario. An index was used to estimate nutrient density in relation to nutritional recommendation and climate impact for solid food items; high index values were those with the highest nutrient density scores in relation to the GHGE. Results: The high-dairy scenario resulted in 27% higher protein, 13% higher vitamin D; 55% higher calcium; 48% higher riboflavin; and 18% higher selenium than the non-dairy scenario. There was a significant correlation between changes in calcium and changes in vitamin D, selenium, and riboflavin content (P=0.0001) throughout all of the diets. The estimated GHGE for the dietary scenario with average-dairy consumption was 4,631 g CO2e/day. Conclusions: When optimizing a diet with regard to sustainability, it is crucial to account for the nutritional value and not solely focus on impact per kg product. Excluding dairy products from the diet does not necessarily mitigate climate change but in contrast may have nutritional consequences