Tools for Evaluating Energy Efficiency of Steel Production Lessons from Sweden and Europe

Abstract: The European Union faces challenges related to climate change, security of energy supply, and competitiveness of European industries. Energy efficiency indicators are required for monitoring and controlling the effectiveness of policies such as the recently endorsed Energy Efficiency Directive. This thesis aims at assessing whether traditionally used energy efficiency indicators capture the development of energy efficiency in the iron and steel sector. The study is based on results from two statistical methods: a top-down, i.e. Malmquist productivity index, and a bottom-up, i.e. partial least squares regression.The specific energy consumption (the indicator representing the sector within the Odyssee energy efficiency index) was scrutinised together with associated indicators based on economic production using the aforementioned statistical methods. The results demonstrated the specific energy consumption does not capture the characteristics of the value chain of steel products. Therefore, it is not sufficient for capturing the energy efficiency of iron and steel industries. Previous studies suggest using indicators based on economic production (e.g. value added) since they represent the value chain to larger degree. However, the value creation process of companies belonging to larger international groups cannot be estimated reliably. Furthermore, the trends of both types of indicators tend to be highly influenced by structural changes, veiling the actual efficiency development.Energy use statistics published by international organisations were also compared for the Swedish case. The results demonstrated that international organisations use different methodologies for allocating energy use statistics between consumption and transformation sectors. The method has significant implications on the trends observed, if based on openly available statistics.This thesis complements previous research by reviewing implications of traditional energy efficiency indicators based on company data, national statistics or openly available statistics and contributes with insights essential for future efforts towards improving energy efficiency indicators for the steel industry.