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- Mahatma Gandhi

You must be the change you wish to see in the world.


Dr. James J. Stone is a professor of Civil and Environmental Engineering at South Dakota School of Mines and Technology (SD Mines) in Rapid City, South Dakota.  His research focuses on life cycle assessment (LCA) modeling, heavy metal (U, As, Hg) fate and transport, and wastewater and stormwater treatment systems.  He has developed LCA models for stormwater best management practices, swine and beef feedlot productions, feed production, and antibiotic manufacturing.  His recent LCA efforts have been related to utilization of LCA as an assessment and management tool for decision making processes. 


 F.E.W. Nexus

Thank you to all of the collaborators and participants of our recent NSF-funded FEW workshop!


A summary of the critical FEW vunerabilities in the northern Great Plains have been published in the first issue of Ag & Environmental Letters and is available for download.

Waste Anaerobic Digestion

Bioresource Technology 2016

Batch anaerobic digestion of food waste and cardboard mixtures for energy production​​

Beef Feedlot Eco-Efficiency

Journal of Environmental Quality 2016

Eco-efficiency model to optimze beef cattle feedlot production in the Great Plains U.S.

U In-Situ Mining Model

Mine Water and the Environment 2016

​​Geochemical model of uranium sorption on oxidized aquifer material at proposed in-situ U recovery site.

Current Research

Life Cycle

LCAs quantify the full range of environmental impacts of products and services to assess their ecobalance.  This information is used to improve efficiency of processes and make informed decisions.

Accelerated biodegradation of non-recyclable household waste can be used to produce methane and topsoil within a portable, containerized unit that captures methane.  Methane can then be used as a fuel for either heating or energy production.


In-situ mining of uranium poses contamination concerns.  Research is on-going on subsurface uranium redox geochemical mobilization and post-mining reclamation modeling.

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