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Spatial greenhouse gas emissions from US county corn production

  • Rylie PeltonEmail author
LCA FOR AGRICULTURE

Abstract

Purpose

Stakeholders from across supply chains have been prompted to explore ways to reduce the environmental burdens of corn production. To effectively manage these environmental impacts, spatially explicit information accounting for the differences in growing conditions and production practices across the production landscape is essential, allowing for high impact intensity corn to be identified and prioritized for improvement. To support these sustainability efforts, this study examines the spatially explicit life cycle greenhouse gas emissions of US county corn production, providing the most comprehensive assessment to date.

Methods

A streamlined spatial life cycle assessment is conducted, focusing on the three key hotspots of corn production for spatial differentiation at the county scale across the contiguous USA, accounting for almost 60% of total average cradle-to-farm gate impacts. Variations in nitrogen fertilization types and rates, N2O emission rates, and irrigation emission rates are specifically revealed. Spatially distinguished hotspot inputs and related emissions are combined with static national average emission estimates from all other inputs used in corn production to gain a full picture and understand the relative contributions to total cradle-to gate impacts.

Results and discussion

Results show significant variation across corn producing counties, states, and regions. High impact priority locations are highlighted and key contributors of impact for each location are illuminated, providing critical information on the spatially explicit levers to reduce impacts. Results increase the generalizability of emission estimates using expected yields to characterize emission intensity, enabling more practical integration into company supply chain sustainability assessments to align with the time horizons in which decisions are made.

Conclusions

Streamlined life cycle assessment methods are an effective way to characterize spatial heterogeneity around key contributors of impact, helping deliver the necessary information for companies, stakeholders, and policy makers to target their influence to reduce these emissions through various engagement efforts.

Keywords

Corn production Green supply chain management (GSCM) Life cycle assessment (LCA) Spatial Streamlined LCA 

Notes

Acknowledgements

The author acknowledges the intellectual support of colleagues Dr. Jennifer Schmitt, Dr. Andrew Goodkind, and Dr. Yiwen Chiu for their valuable feedback in the development of this manuscript.

Funding information

This study received the financial support of the Institute on the Environment and Smithfield Foods.

Supplementary material

11367_2018_1506_MOESM1_ESM.docx (16.7 mb)
ESM 1 (DOCX 17144 kb)
11367_2018_1506_MOESM2_ESM.xlsx (1.1 mb)
ESM 2 (XLSX 1137 kb)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institute on the Environment, NorthStar Initiative for Sustainable EnterpriseUniversity of MinnesotaMinneapolisUSA

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