(659c) Carbon Footprint Analysis of Dairy Feed From a Mill in Michigan, USA

A carbon footprint analysis was conducted for a single dairy feed mill located in Michigan USA with the aim of developing a preliminary assessment of dairy feed mill operations. The goal was to develop life cycle assessment methodology applicable to the animal feed mill industry and also to gain understanding of the relative importance of milled dairy feed inputs on the greenhouse gas (GHG) emissions of the outputs of the mill. In the final analysis, GHGs emitted from feed mill operations on the basis of one kilogram of dairy feed output from the mill (kg CO₂ eq kg^-1 of milled dairy feed) was estimated. Scenarios were investigated to consider the prevalence of different feed ingredient inputs likely to represent different U.S. mill locations.

The functional unit used for this study was 1 kg of milled dairy feed at its exit moisture content (an average feed formulation for dairy animal nutrition). Inputs and activities identified in this cradle-to-mill-to-dairy farm analysis included; feed ingredients, onsite energy, and transportation of feed inputs to the milling site and transportation mill output to dairy farms. Sources of Life cycle inventory (LCI) input data include; peer reviewed journal articles, purchase history documents of the milling facility, internet searches (ISI, Google scholar, ProQuest, etc), and a site visit. Using Ecoinvent™ unit processes in SimaPro, an open IO model and other peer reviewed articles, the cradle-to-mill-to-dairy farm (receiving) gate analysis was estimated using  two allocation methods (economic and mass).

Feed mill GHG emissions were estimated to be 0.62 and 0.93 kg CO₂ eq (equivalent) kg^-1 of milled dairy feed for economic and mass allocation, respectively. The highest emissions were due to the feed ingredient inputs which contributed 73-82% towards the carbon footprint depending on the allocation method. Energy and transportation impacts together contributed between 8-12%. Scenario analyses were include to simulate different mill locations where dominant feed inputs change compared to the MI location, for example to a prevalence of dry distiller grains and solids for mills located in Iowa and a prevalence of oats for a mill located in North Dakota.