To avoid significant negative climate change consequences, the Intergovernmental Panel on Climate Change (IPCC) advises that global warming be limited to 1.5°C from pre- industrial times, a target adopted under the Paris Agreement framework. The University of Maryland Center for Global Sustainability suggests that the U.S. would remain consistent with the IPCC target by reducing emissions 51% below 2005 levels by 2030, or 44.8% below 2012 levels, my base year. This paper examines the changes necessary in primary energy sources in order for the U.S. agri-food system to reduce its emissions from electricity use by 44.8% from 2012 to 2030. First, an environmental input-output (EIO) model is used to determine electricity consumption associated with different activities, commodities, and final uses within the U.S. food system. Additionally, electricity consumption is disaggregated by primary energy source, to which emissions levels are attributed using life cycle emissions estimates. Second, the EIO model output serves as an input into two optimization problems. Subject to the same constraints on energy use and total emissions, the first problem minimizes the cost of meeting the emissions target, while the second minimizes the change from existing electricity consumption patterns. United States Energy Information Agency (EIA) projections through 2030 for the growth of fossil-fuels, renewable energies, and nuclear are key data parameters for the optimization constraints. Given the EIA projections, my principal finding is that the U.S. food system is not on track to reduce emissions from electricity use in a manner consistent with the 1.5°C target. That is, the optimization problems cannot yield a feasible solution given the projected growth of each energy source used for electricity generation. However, solutionsfor both problems become feasible by relaxing the energy type constraint—adding eight percentage points to the EIA projected growth for all energy types. The paper concludes with a discussion of policy implications, model limitations, and the potential for future research.