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Designing hybrid life cycle assessment models based on uncertainty and complexity

  • UNCERTAINTIES IN LCA
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Abstract

Purpose

Despite the wide use of LCA for environmental profiling, the approach for determining the system boundary within LCA models continues to be subjective and lacking in mathematical rigor. As a result, life cycle models are often developed in an ad hoc manner, and are difficult to compare. Significant environmental impacts may be inadvertently left out. Overcoming this shortcoming can help elicit greater confidence in life cycle models and their use for decision making.

Methods

This paper describes a framework for hybrid life cycle model generation by selecting activities based on their importance, parametric uncertainty, and contribution to network complexity. The importance of activities is determined by structural path analysis—which then guides the construction of life cycle models based on uncertainty and complexity indicators. Information about uncertainty is from the available life cycle inventory; complexity is quantified by cost or granularity. The life cycle model is developed in a hierarchical manner by adding the most important activities until error requirements are satisfied or network complexity exceeds user-specified constraints.

Results and Discussion

The framework is applied to an illustrative example for building a hybrid LCA model. Since this is a constructed example, the results can be compared with the actual impact, to validate the approach. This application demonstrates how the algorithm sequentially develops a life cycle model of acceptable uncertainty and network complexity. Challenges in applying this framework to practical problems are discussed.

Conclusion

The presented algorithm designs system boundaries between scales of hybrid LCA models, includes or omits activities from the system based on path analysis of environmental impact contribution at upstream network nodes, and provides model quality indicators that permit comparison between different LCA models.

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Funding

Partial financial support was provided by the National Science Foundation (CBET-1804943) and the Sustainable and Resilient Economy Program at The Ohio State University.

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Authors and Affiliations

  1. William G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, 151 W. Woodruff Avenue, Columbus, OH, 43210, USA

    Tapajyoti Ghosh & Bhavik R. Bakshi

Authors
  1. Tapajyoti Ghosh
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  2. Bhavik R. Bakshi
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Corresponding author

Correspondence to Bhavik R. Bakshi.

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Communicated by: Andreas Ciroth

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Ghosh, T., Bakshi, B.R. Designing hybrid life cycle assessment models based on uncertainty and complexity. Int J Life Cycle Assess 25, 2290–2308 (2020). https://doi.org/10.1007/s11367-020-01826-5

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