Subnational mobility and consumption-based environmental accounting of US corn in animal protein and ethanol supply chains

Timothy M. Smith, Andrew L. Goodkind, Taegon Kim, Rylie E.O. Pelton, Kyo Suh, Jennifer Schmitt

Research output: Contribution to journalArticlepeer-review

50 Scopus citations


Corn production, and its associated inputs, is a relatively large source of greenhouse gas emissions and uses significant amounts of water and land, thus contributing to climate change, fossil fuel depletion, local air pollutants, and local water scarcity. As large consumers of this corn, corporations in the ethanol and animal protein industries are increasingly assessing and reporting sustainability impacts across their supply chains to identify, prioritize, and communicate sustainability risks and opportunities material to their operations. In doing so, many have discovered that the direct impacts of their owned operations are dwarfed by those upstream in the supply chain, requiring transparency and knowledge about environmental impacts along the supply chains. Life cycle assessments (LCAs) have been used to identify hotspots of environmental impacts at national levels, yet these provide little subnational information necessary for guiding firms’ specific supply networks. In this paper, our Food System Supply-Chain Sustainability (FoodS3) model connects spatial, firm-specific demand of corn purchasers with upstream corn production in the United States through a cost minimization transport model. This provides a means to link county-level corn production in the United States to firm-specific demand locations associated with downstream processing facilities. Our model substantially improves current LCA assessment efforts that are confined to broad national or state level impacts. In drilling down to subnational levels of environmental impacts that occur over heterogeneous areas and aggregating these landscape impacts by specific supply networks, targeted opportunities for improvements to the sustainability performance of supply chains are identified.

Original languageEnglish (US)
Pages (from-to)E7891-E7899
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number38
StatePublished - Sep 19 2017

Bibliographical note

Funding Information:
ACKNOWLEDGMENTS. We acknowledge two of our colleagues for their initial work in this space: Dr. Kim Mullins and Mo Li. This work was supported by National Institute of Food and Agriculture Grant 2011-68005-30416 and NSF Grant 163342. We also thank the Environmental Defense Fund and Institute on the Environment at the University of Minnesota for financial support for this project.

Publisher Copyright:
© 2017, National Academy of Sciences. All rights reserved.


  • Commodity flow modeling
  • Environmental accounting
  • Food systems sustainability
  • Life cycle assessment
  • Supply chains


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