Sustainability indicators for environmental management and decision making

The general objective of this research is to explore theories and methodologies of sustainability indicators, environmental management and decision making disciplines with the operational purpose of producing scientific, robust and relevant information for supporting system understanding and decision making in real case studies. Several tools have been applied in order to increase the understanding of socio-ecological systems as well as providing relevant information on the choice between alternatives. These tools have always been applied having in mind the complexity of the issues and the uncertainty tied to the partial knowledge of the systems under study. Two case studies with specific application to performances measurement (environmental performances in the case of the K8 approach and sustainable development performances in the case of the EU Sustainable Development Strategy) and a case study about the selection of sustainable development indicators amongst Municipalities in Scotland, are discussed in the first part of the work. In the second part of the work, the common denominator among subjects consists in the application of spatial indices and indicators to address operational problems in land use management within the territory of the Ravenna province (Italy). The main conclusion of the thesis is that a ‘perfect’ methodological approach which always produces the best results in assessing sustainability performances does not exist. Rather, there is a pool of correct approaches answering different evaluation questions, to be used when methodologies fit the purpose of the analysis. For this reason, methodological limits and conceptual assumptions as well as consistency and transparency of the assessment, become the key factors for assessing the quality of the analysis.

Development of advanced tools and methods for the assessment and management of risk due to atypical major accident scenarios

Proper hazard identification has become progressively more difficult to achieve, as witnessed by several major accidents that took place in Europe, such as the Ammonium Nitrate explosion at Toulouse (2001) and the vapour cloud explosion at Buncefield (2005), whose accident scenarios were not considered by their site safety case. Furthermore, the rapid renewal in the industrial technology has brought about the need to upgrade hazard identification methodologies. Accident scenarios of emerging technologies, which are not still properly identified, may remain unidentified until they take place for the first time. The consideration of atypical scenarios deviating from normal expectations of unwanted events or worst case reference scenarios is thus extremely challenging. A specific method named Dynamic Procedure for Atypical Scenarios Identification (DyPASI) was developed as a complementary tool to bow-tie identification techniques. The main aim of the methodology is to provide an easier but comprehensive hazard identification of the industrial process analysed, by systematizing information from early signals of risk related to past events, near misses and inherent studies. DyPASI was validated on the two examples of new and emerging technologies: Liquefied Natural Gas regasification and Carbon Capture and Storage. The study broadened the knowledge on the related emerging risks and, at the same time, demonstrated that DyPASI is a valuable tool to obtain a complete and updated overview of potential hazards. Moreover, in order to tackle underlying accident causes of atypical events, three methods for the development of early warning indicators were assessed: the Resilience-based Early Warning Indicator (REWI) method, the Dual Assurance method and the Emerging Risk Key Performance Indicator method. REWI was found to be the most complementary and effective of the three, demonstrating that its synergy with DyPASI would be an adequate strategy to improve hazard identification methodologies towards the capture of atypical accident scenarios.