(564d) Design Decision-Making Under Uncertainty to Identify Sustainable Integrated Forest Biorefinery Strategies

Integrated biorefinery into existing pulp and paper facilities is a potential game-changing solution for the transformation of North American forestry industry, and the manufacture of an expanded product portfolio. However not all biorefinery strategies are sustainable and not have the same level of risk. Thus it is crucial that unsustainable strategies be systematically screened-out from the list of possibilities at the early design stage. The methodology presented in this study assesses candidate biorefinery alternatives from economic, competitiveness and environmental perspectives using different process systems analysis tools (e.g, techno-economics, Life Cycle Analysis, etc.) for both deterministic and uncertain conditions. The results of these assessments are used to evaluate a set of sustainability criteria, despite of the conventional analyses which generally use only short-term profitability metrics for decision-making. These conflicting criteria were aggregated into a unique sustainability score for each candidate biorefinery strategy by conducting a multi-criteria decision-making (MCDM) panel by which candidate strategies are ranked using a sustainability perspective.

However the candidate biorefinery strategies imply different levels of technology and market risk due to different sources of uncertainties which should be addressed in decision making. Thus to make a realistic strategic decision, the sustainability of biorefinery strategies should be assessed under uncertainty. In this study, different sources of uncertainty including market, technology and panel uncertainties are considered in biorefinery decision-making. In order to address this objective, a stochastic risk analysis method (Monte-Carlo Analysis) was used to develop probability distribution functions for sustainability criteria, which were then employed in a second MCDM panel. The proposed methodology in this study not only takes into account a complete set of sources of uncertainty, but also reflects the risk attitude of decision-makers in utility functions applying risk aversion theory. Comparing the results of deterministic and uncertain conditions shows that by evaluating uncertainty and quantifying risk attitude of panelists, the basis for the panel decision changes. This confirms the necessity of systematically addressing risk in biorefinery strategic decision making.