Modeling environmental impacts and risk under data uncertainties

ABSTRACT

In this article, we propose a methodology to evaluate the risk of environmental and life cycle impacts under data uncertainties that can be applied to a broad range of data availability assumptions. Specifically, we first propose a data uncertainty model that can accommodate scenarios where only a few data points are known, where data histograms are available, or where multiple, inconsistent data sources are present. An impact risk valuation model is then developed, based on the certainty equivalent of an exponential dis-utility function. We show that the evaluation of the impact risk value can be achieved using a closed-form expression and demonstrate an application in a food waste recycling alternatives comparison. We further extend the methodology to construct an impact safety index model that evaluates uncertain impacts using an impact tolerance level. We show that the proposed model is computationally tractable and can be used as an optimization criterion. Computational studies in an example of sustainable building material selection are then used to demonstrate the improvement of the proposed model compared with the standard approach of optimizing average impacts across several statistical criteria.

KEYWORDS:

• Environmental impact
• life cycle assessment
• data uncertainty
• linear programming

Funding

This research is funded by the National Research Foundation, Prime Minister’s Office, Singapore, under its Campus for Research Excellence and Technological Enterprise program.

Additional information

Notes on contributors

Kena Zhao

Kena Zhao is a Ph.D. candidate in the Department of Industrial Systems Engineering and Management at National University of Singapore. She received a B.Eng. degree in industrial engineering (2010) from Shanghai Jiao Tong University. Her current research interests include environmental risk evaluation and optimization modeling under uncertainty in the environmental sustainability problems.

Tsan Sheng (Adam) Ng

Tsan Sheng (Adam) Ng is an Associate Professor in the Department of Industrial Systems Engineering and Management at National University of Singapore. He received his Ph.D. degree in industrial & systems engineering (2005) from the National University of Singapore. His research interests focus on optimization modeling and applications in energy, logistics, and sustainability problems under risk and ambiguity. His work includes robust optimization modeling approaches in energy–economic resilience problems, energy recovery facility location systems, and natural gas production planning problems.

Harn Wei Kua

Harn Wei Kua is an Associate Professor in the Department of Building at the National University of Singapore. He received his Ph.D. degree in building technology (2006) at the Massachusetts Institute of Technology. The focus of his current research is on life cycle sustainability assessment and bio-based building materials.

Muchen Tang

Muchen Tang is a Research Fellow in the Department of Industrial Systems Engineering and Management at the National University of Singapore. He received his Ph.D. degree in industrial & systems engineering (2014) from the National University of Singapore and B.Eng. in industrial engineering from Tsinghua University (2010).