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Abstract Global food systems must be a part of strategies for greenhouse gas (GHG) mitigation, optimal water use, and nitrogen pollution reduction. Insights from research in these areas can inform policies to build sustainable food systems yet limited work has been done to build understanding around whether or not sustainability efforts compete with supply chain resilience. This study explores the interplay between food supply resilience and environmental impacts in US cities, within the context of global food systems’ contributions to GHG emissions, water use, and nitrogen pollution. Utilizing county-level agricultural data, we assess the water use, GHG emissions, and nitrogen losses of urban food systems across the US, and juxtapose these against food supply resilience, represented by supply chain diversity. Our results highlight that supply chain resilience and sustainability can simultaneously exist and are not necessarily in competition with each other. We also found a significant per capita footprint in the environmental domains across Southern cities, specifically those along the Gulf Coast and southern Great Plains. Food supply chain resilience scores ranged from 0.18 to 0.69, with lower scores in the southwest and Great Plains, while northeastern and Midwestern regions demonstrated higher resilience. We found several cities with high supply chain resilience and moderate or low environmental impacts as well as areas with high impacts and low resilience. This study provides insights into potential trade-offs and opportunities for creating sustainable urban food systems in the US, underscoring the need for strategies that consider both resilience and environmental implications.
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Optimization Based Modeling for the Food Supply Chain's Resilience to Outbreaks
Scant research focuses on the resiliency of food supply chain networks to outbreaks, despite the estimated 600 million global foodborne illnesses annually. Outbreaks that cross country, state and provincial lines are virulent due to the number of people they can affect and difficulty controlling them. Research is needed on food supply chain networks, which are not well-characterized in relation to foodborne illnesses or generally. This paper introduces the United States Food, Energy, and State Transportation (US-FEAST) model and demonstrates its applicability via analysis of a hypothetical demand shock resulting from multistate food contamination. US-FEAST is an optimization-based model across all fifty states with yearly timesteps to 2030. It is a framework integrating food system data from multiple individual data sources. To calibrate, we develop a bilevel optimization routine to generate synthetic, state-level data and provide estimates of otherwise unavailable data at the intersections of the food and transportation systems. The results of US-FEAST elucidate potential heterogenous state-level variations in response, regional changes in food flows, vulnerabilities in the supply chain, and implications for food system resilience. While the generated data and scenarios are not empirical evidence, they provide insights to aid in planning by projecting outcomes and intervention effects. Our results estimate a 23% beef production decrease and 4% price decrease provide a road map toward data needs for quantifying food system resilience to foodborne illness. US-FEAST and its framework may have global utility for studying food safety in national and international food supply chain networks.
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- Award ID(s):
- 2114098
- PAR ID:
- 10350070
- Date Published:
- Journal Name:
- Frontiers in Sustainable Food Systems
- Volume:
- 6
- ISSN:
- 2571-581X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3389/fsufs.2022.887819
