Industrial environmental performance evaluation: A Markov-based model considering data uncertainty

Commonly, operational aspects of an industrial process are not included when evaluating the process environmental performance. These aspects are important as operational failures can intensify adverse environmental impacts or can diminish the chance of making any amelioration. This paper proposes to include these operational aspects by applying a method called Industrial Environmental Performance Evaluation. To have a reliable environmental performance measure for assisting policy-making in an organization, two types of uncertainty are considered in the proposed method. The first type is the epistemic uncertainty due to imperfect knowledge about the environmental impacts of the process. Epistemic uncertainty is considered by using the potential probability of material release during operating and non-operating periods of the process. The second type is aleatory uncertainty due to potential stochastic behaviour of the process. Aleatory uncertainty is modelled through a Markov-based model and is considered by the state probability distribution vectors. The proposed method is employed to analyze an existing formaldehyde production process as a case study. The analysis shows the relation between environmental and operational performances of the process. Process owners can use this analysis for improving the environmental and operational aspects of their process and achieve accuracy in their environmental decisions.