As part of defense acquisitions, Life Cycle Assessment (LCA) is a tool to assist in designing more sustainable systems—those that use fewer resources over the life cycle, have fewer impacts on human health and the environment, and thus have a lower total ownership cost. The objective of this study was to make LCA advancements that could be integrated to make the U.S. Department of Defense’s (DoD) Defense Input Output (DIO) model and associated methods more robust.  

Technical Approach

Advancements in LCA data, impact assessment, and input-output LCA were completed as part of three tasks. In Task 1, the research team worked with the United States Navy and IPC to get bills of materials (BOM) for the F-18 landing gear and electronic printed circuit board, respectively, to develop a prototype software to construct product system models (PSM). In Task 2, an existing eutrophication life cycle impact assessment (LCIA) method was selected. The research team updated the method with increased resolution of U.S. regional specific fate and transport factors. Also, an open-source software was created to address the data disconnect between impact assessment characterization factors (CF) and data used in life cycle inventory and to create standardized sets of CF. In Task 3, DoD’s DIO and the U.S. Environmental Protection Agency’s (EPA) Environmentally-Extended Input-Output (USEEIO) models were evaluated to determine where they shared elements or differed, and to select desirable elements from each model and associated framework to develop DIO v2.0. The research team developed a strategic plan for aligning both models and developed DIO v2.0 combining elements of USEEIO and DIO. The new model will be documented in a peer-reviewed journal.


In Task 1, the research team developed three complementary software prototypes, and each took a distinct approach to creating a complete PSM through linkages to background datasets. Each prototype addresses different steps to automate the translation of the BOM into unit processes; however, manual work is still required in each case. In Task 2, the research team generated a new set of freshwater and marine eutrophication factors specific to counties and states in the contiguous U.S. The team also created the LCIA Formatter—a Python package that produces standardized datasets of CF optionally using the Federal LCA Commons (FLCAC) Elementary Flow List (FEDEFL) as a standard flow list. In Task 3, the research team aligned the DoD DIO with the EPA USEEIO model and increased the resolution of air emissions in the USEEIO. Also, a strategic plan for the USEEIO and DIO was developed that included recommendations for short-, medium-, and long-term steps to improve EEIO models for use by DoD. 


Task 1 led to a finding that greater investment of time into refining or improving the prototypes, or into further development of methods to tackle the steps delineated by the study, is likely to yield very useful tools that automate data collection processes important to conducting LCA studies. Task 2 demonstrated how to create more spatially-explicit CF for impacts of concern that are spatially-sensitive (like eutrophication) for areas in which the DoD operates around the globe. The LCIA methods generated by the LCIA Formatter for use with the FEDEFL can be hosted publicly on the FLCAC website for use by LCA practitioners and researchers and can support LCAs performed by many parties, including FLCAC member agencies such as EPA, the U.S. Department of Energy, the U.S. Department of Agriculture, and DoD. As demonstrated in this task, data from across the Strategic Environmental Research and Development Program (SERDP) and the Environmental Security Technology Certification Program (ESTCP) could improve existing environmental models and impact assessment methods. Task 3 led to the conclusion that the USEEIO and DIO model alignment will lower DoD’s operation and maintenance costs to maintain a large background dataset that includes all indirect activities in the economy and corresponding data on extractive, industrial, agricultural, transport, and disposal processes that captures their material and energy requirements and environmental emissions and wastes. As EPA updates the USEEIO, the DIO model will be updated with the corresponding data, giving DoD access to the latest authoritative background LCA modeling information that allows it to concentrate resources on the development of defense specific process datasets currently lacking to complete LCA studies. The output of this research supports DoD’s efforts to meet executive order and statutory sustainability requirements as part of defense acquisitions.