Eco-efficiency indicator framework implemented in the metallurgical industry: part 1 - a comprehensive view and benchmark


Eco-efficiency indicator framework implemented in the metallurgical industry: part 1 - a comprehensive view and benchmark

Rönnlund, I.; Reuter, M. A.; Horn, S.; Aho, J.; Päällysaho, M.; Ylimäki, L.; Pursula, T.

The purpose of this work was to develop an indicator framework for the environmental sustainability benchmarking of products produced by the metallurgical industry. Sustainability differentiation has become an important issue for companies throughout the value chain. Differentiation is sometimes not attainable, due to the use of average data, lack of comparative data, certain issues being overshadowed by others, and a very narrow palette of indicators dominating the current sustainability assessments. There is a need for detailed and credible analyses, which show the current status and point out where improvements can be made. The indicator framework is developed to give a comprehensive picture of eco-efficiency, to provide methods that enable relevant comparisons as well as the tools for communicating the results. In this way, the methodology presented in this study aims to make differentiation easier and thus aid companies in driving the development toward more sustainable solutions.
Methods

The framework is based on the existing indicator framework Gaia Biorefiner, which is primarily intended for bio-based products. In this work, the framework was further developed for application in the metallurgical industry. The indicator framework is built by first looking at the issues, which are critical to the environment and global challenges seen today and which the activities of the metallurgical industry may have an impact on. Based on these issues, suitable indicators are chosen if they exist and built if they do not. The idea is that all indicators in a group form a whole, showing areas of innovation while refraining from aggregating and weighting, which often compromise a comprehensive and objective view. Both qualitative and quantitative indicators are included. The indicators are constructed following the criteria set by the EU and OECD for building indicators. Each indicator further has a benchmark. The rules for building the benchmark are connected to the indicators. Suitable data sources and criteria for the benchmark and the indicators are gathered from literature, publicly available databases, and commercial LCA software. The use of simulation tools for attaining more reliable data is also studied.
Results and discussion

The result is a visual framework consisting of ten indicator groups with one to five indicators each, totaling up to 31 indicators. These are visualized in a sustainability indicator “flower.” The flower can be further opened up to study each indicator and the reasons behind the results. The sustainability benchmark follows a methodology that is based on utilization of baseline data and sustainability criteria or limits. A simulation approach was included in the methodology to address the problem with data scarcity and data reliability. The status of the environment, current production technologies, location-specific issues, and process-specific issues all affect the result, and the aim of finding relevant comparisons that will support sustainability differentiation is answered by a scalable scoping system.
Conclusions

A new framework and its concise visualization has been built for assessing the eco-efficiency of products from the metallurgical industry, in a way that aims to answer the needs of the industry. Since there is a baseline, against which each indicator can be benchmarked, a sustainability indicator “flower” can be derived, one of the key innovations of this methodology. This approach goes beyond the usual quantification, as it is also scalable and linked to technology and its fundamental parameters. In part 2, a case study “A case study from the copper industry” tests and illustrates the methodology.

Keywords: Benchmarking; Circular economy; Indicator; Metallurgy; Process and system simulation; Product environmental footprint; Resource efficiency; Sustainability

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