Modeling a localized metropolitan food system in the Midwest USA: Life cycle impacts of scenarios for Des Moines, Iowa

Food systems are energy-intensive, causing ≈25 % of anthropogenic global warming potential (GWP) and contributing to challenges across the food-energy-water nexus. The state of Iowa, USA, is of particular interest as a rainfed agricultural region of the upper Midwest; despite its highly productive landscape, a large proportion of food consumed by Iowa residents is imported. This study focused on the Des Moines Metropolitan Statistical Area (DM-MSA), a six-county area in central Iowa with a 2020 population of ≈700,000. A life cycle assessment approach was used to quantify environmental impacts (GWP, fossil energy and water consumption, land use); scenarios modeled provision and consumption of 50 % of nutritional requirements for the current DM-MSA population by food group (e.g., grains, proteins, vegetables). The four DM-MSA food system scenarios were: 1) current conditions (baseline), 2) local production for 50 % of food, 3) consumption changed to follow USA dietary guidelines, and 4) combined changes to production and consumption. Localizing food production reduced all environmental impacts more than following USA dietary guidelines. Compared to the baseline, 50 % local production scenarios reduced GWP and energy consumption (18-24 %) and water use (35-41 %) annually. Decreases by food group were least for protein (-10 % GWP) and greatest for fruits and vegetables (-58-62 % GWP). Local scenario alternatives could further reduce some environmental impacts if paired with a nutritionally- and environmentally-optimized diet (EAT-Lancet) providing the greatest change (-30-38 % for GWP and energy use) compared to the local scenario. A 50 % local production scenario for the DM-MSA could decrease GWP by 102 million CO_2eq yr^-1 and water use by 44 billion L yr^-1. However, this would require dietary changes based on seasonal food availability. Further development and co-simulation with other metropolitan-scale biophysical and social models will enhance understanding of food system drivers and support effective decision-making for urban food system improvements in the Midwest.