Exploitation scenarios in industrial system LCA.

Summary Purpose: This paper considers the variabilities that exist in the exploitation of a complex industrial system. Our scenario-based LCA model ensures the reliability of results in situations where the system life cycle is very uncertain, where there is substantial lack of data and/or where time and resources available are limited. It is also an effective tool to generate exploitation recommendations for clients. Method: Existing quantitative uncertainty methods in LCA require a huge amount of accurate data. These data are rarely available in simplified and upstream LCA for complex industrial systems. A scenario-based approach is the best compromise between acceptable quality of results and resources required. However, such methods have not yet been proposed to improve the environmental knowledge of the system in the case of exploitation scenarios. The method proposed here considers a limited number of scenarios (3 or 4) that are defined using the Stanford Research Institute (SRI) matrix. Using results from past projects, relevant parts of the system are listed, and expert knowledge and parameters are associated with these parts and quantified. A classical LCA process then provides the results for the different scenarios. Results and discussion: The method was applied to an Alstom Grid AC/DC conversion substation for the primary aluminium industry. A previous study had limited scope, as the life cycle was poorly understood. Relevant parts were thus clearly identified: spare parts program, transport failures, preventive and corrective maintenance, updates and revampings, lifetime modulation and end-of-life. Four scenarios were considered: best case, worst case, baseline (expected future) and a highly different alternative. Results show the pertinence of considering several exploitation scenarios when the life cycle is not predictable, as the environmental impacts may vary widely from one case to another. A sensitivity analysis also shows that some relevant parts such as updates and revampings will need to be carefully considered in futures studies. Conclusions: The consideration of three exploitation scenarios (best case, baseline and worst case) appears to be extremely pertinent when considering simplified LCA of industrial systems with high uncertainties and limited time and resources. This model is also very useful to generate good practice and recommendations towards clients, thus initiating a dialog centred on eco-design and continuous improvement.