A spatially explicit environmental footprint of US meat food waste

Agriculture is a major contributor to greenhouse gas emissions and water use. Its impacts are heightened when agricultural crops are embedded in animal protein and further amplified when that food is then wasted. This impact... [ view full abstract ]

Agriculture is a major contributor to greenhouse gas emissions and water use. Its impacts are heightened when agricultural crops are embedded in animal protein and further amplified when that food is then wasted. This impact aggregation is significant considering a third of global food is wasted. For the United States, this waste primarily occurs at the consumer level and has significant economic and environmental costs. The average US family of four pays one to two thousand dollars a year in food they do not eat. The greenhouse gas emissions from global food waste are greater than every individual country’s emissions in the world except those of the US and China. Furthermore, 12-15% of global water consumption is embedded in food waste. Meat (including poultry and fish) accounts for the largest percentage of food waste by value (30%) with 41 pounds of meat per capita going uneaten in households each year. These significant consequences of both food production and food waste have motivated global discussions about livestock production, food systems and feeding the world. Our work intersects these discussions by providing spatially explicit footprints of the environmental impact of meat food waste. Our Food System Supply-Chain Sustainability (FoodS3) model transports corn and soy, the two main ingredients in livestock feed, from counties of production to livestock, embedding the products in the animals, and then moves them to primary processing facilities. We model this transport with a least cost optimization model, enabling us to connect meat processing companies with specific counties of agricultural production. We have expanded on this model, creating a new step that transports animal protein from primary processing facilities to human populations across the US. The movement of meat is based on impedance factors for transport, with demand estimated by population size and demographic characteristics. In modeling the animal protein supply chain we will be able to add a level of spatial variation in environmental impacts that has previously been ignored. This spatial variation occurs at many levels in the supply chain including varying fertilizer use, different electricity mixes, different end uses, etc. This variation gets masked by the ease in which commodity agricultural products and processed meat can move across the globe. However, where something is made, and where it consumed can have a significant effect on the environmental impact of production and the environmental neutrality of disposal. In modeling protein supply from processing to consumption we are connecting our existing work on both ends of the animal protein supply chain and developing a unique spatially explicitly, company linked, picture of the environmental impacts of meat consumption in the US.