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.

Spatial Disparity and Dynamic Trajectory of Convergence in China: Construction and Application of a Composite Index of Regional Development

China is a large country characterized by remarkable growth and distinct regional diversity. Spatial disparity has always been a hot issue since China has been struggling to follow a balanced growth path but still confronting with unprecedented pressures and challenges. To better understand the inequality level benchmarking spatial distributions of Chinese provinces and municipalities and estimate dynamic trajectory of sustainable development in China, I constructed the Composite Index of Regional Development (CIRD) with five sub pillars/dimensions involving Macroeconomic Index (MEI), Science and Innovation Index (SCI), Environmental Sustainability Index (ESI), Human Capital Index (HCI) and Public Facilities Index (PFI), endeavoring to cover various fields of regional socioeconomic development. Ranking reports on the five sub dimensions and aggregated CIRD were provided in order to better measure the developmental degrees of 31 or 30 Chinese provinces and municipalities over 13 years from 1998 to 2010 as the time interval of three “Five-year Plans”. Further empirical applications of this CIRD focused on clustering and convergence estimation, attempting to fill up the gap in quantifying the developmental levels of regional comprehensive socioeconomics and estimating the dynamic convergence trajectory of regional sustainable development in a long run. Four clusters were benchmarked geographically-oriented in the map on the basis of cluster analysis, and club-convergence was observed in the Chinese provinces and municipalities based on stochastic kernel density estimation.

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.

Effects of pesticides on honey bees (Apis mellifera L.): study of a specific route of exposure and evaluation of biochemical-physiological changes in the assessment of the pesticides toxicity

In this study, some important aspects of the relationship between honey bees (Apis mellifera L.) and pesticides have been investigated. In the first part of the research, the effects of the exposure of honey bees to neonicotinoids and fipronil contaminated dusts were analyzed. In fact, considerable amounts of these pesticides, employed for maize seed dressing treatments, may be dispersed during the sowing operations, thus representing a way of intoxication for honey bees. In particular, a specific way of exposure to this pesticides formulation, the indirect contact, was taken into account. To this aim, we conducted different experimentations, in laboratory, in semi-field and in open field conditions in order to assess the effects on mortality, foraging behaviour, colony development and capacity of orientation. The real dispersal of contaminated dusts was previously assessed in specific filed trials. In the second part, the impact of various pesticides (chemical and biological) on honey bee biochemical-physiological changes, was evaluated. Different ways and durations of exposure to the tested products were also employed. Three experimentations were performed, combining Bt spores and deltamethrin, Bt spores and fipronil, difenoconazole and deltamethrin. Several important enzymes (GST, ALP, SOD, CAT, G6PDH, GAPDH) were selected in order to test the pesticides induced variations in their activity. In particular, these enzymes are involved in different pathways of detoxification, oxidative stress defence and energetic metabolism. The results showed a significant effect on mortality of neonicotinoids and fipronil contaminated dusts, both in laboratory and in semi-field trials. However, no effects were evidenced in honey bees orientation capacity. The analysis of different biochemical indicators highlighted some interesting physiological variations that can be linked to the pesticide exposure. We therefore stress the attention on the possibility of using such a methodology as a novel toxicity endpoint in environmental risk assessment.