Sustainability of Rearing System Using Multicriteria Analysis: Application in Commercial Poultry Production.

The aim of the present study was to develop a multicriteria model for the comparison of three commercial poultry farms: organic with Ross 308 genotype (OR), organic with Naked Neck genotype (ONN) and a conventional system (C), which represents the most common commercial farming system. A model based on multicriteria decision analysis was developed, considering for the first time the One Welfare approach in an operational manner, including three dimensions: human, environmental and animal welfare. The three alternatives demonstrated different performances, according to the different dimensions considered. In particular, the two organic systems performed better for human welfare and animal welfare, with relevant differences due to the genetic strains used. Conventional rearing performed better for the environment index due to the method chosen. The multicriteria analysis showed that the organic system performed better overall than the conventional system. In particular, the use of an adapted Slow Growing (SG) strain positively affected the final rank, mainly by reducing welfare problems and producing good economic and social performance. The stability of the results was verified by performing a sensitivity analysis, specifically a weight stability analysis, which confirmed the strength of results.

A model for measuring the environmental sustainability of events.

Like all human activities, events can generate significant pressures on environmental resources, unless they are well-managed and monitored. Therefore, it is becoming more and more important to develop models that can measure their environmental sustainability. Although increasing attention is being paid to this sector, there is currently no standard protocol or method to assess the eco-sustainability of events. This article presents an innovative assessment procedure to measure the environmental sustainability of events. It is based on several indicators, combined by means of a multi-criteria approach and aggregated into a final index, which we called METER (Measuring Events Through Environmental Research). The METER index uses nine major operational categories, divided in sub-categories and detailed items, which cover all the main aspects concerning environmental sustainability of an event and are evaluated for all its phases, i.e. planning, organisation, implementation, post event. The index is fairly analytical, and is thus able to represent the numerous aspects to be taken into consideration in the environmental assessment of an event. At the same time, it is simple to apply and user-friendly, thanks to its graphics and effective communication of the web platform within it is implemented. Moreover, METER is based on a participatory approach using the bottom-up model and on the principle of subsidiarity. All official international documents regarding sustainable development now require subsidiarity. However, it is not being currently applied as part of any certification or with any evaluation tool. Therefore, although the index is still a prototype, it represents an innovation in the field of environmental management. A simple exemplary case is presented, about a European Spring School held at University of Perugia (Italy) in 2014, in which the application of METER showed a sustainability assessment score of 638 points out of 1000, with an excellent management of waste, catering, internal travel and participation aspects.

Decision support systems for environmental management: a case study on wastewater from agriculture.

Dealing with spatial decision problems means combining and transforming geographical data (input) into a resultant decision (output), interfacing a Geographical Information System (GIS) with Multi-Criteria Decision Analysis (MCDA) methods. The conventional MCDA approach assumes the spatial homogeneity of alternatives within the case study area, although it is often unrealistic. On the other side, GIS provides excellent data acquisition, storage, manipulation and analysis capabilities, but in the case of a value structure analysis this capability is lower. For these reasons, several studies in the last twenty years have given attention to MCDA-GIS integration and to the development of Spatial Decision Support Systems (SDSS). Hitherto, most of these applications are based only on a formal integration between the two approaches. In this paper, we propose a complete MCDA-GIS integration with a plurality of MCDA methodologies, grouped in a suite. More precisely, we considered an open-source GIS (GRASS GIS 6.4) and a modular package including five MCDA modules based on five different methodologies. The methods included are: ELECTRE I, Fuzzy set, REGIME analysis, Analytic Hierarchy Process and Dominance-based Rough Set Approach. Thanks to the modular nature of the package, it is possible to add new methods without modifying the existing structure. To present the suite, we applied each module to the same case study, making comparisons. The strong points of the MCDA-GIS integration we developed are its open-source setting and the user friendly interface, both thanks to GRASS GIS, and the use of raster data. Moreover, our suite is a genuine case of perfect integration, where the spatial nature of criteria is always present.

Assessing Rural Sustainable Development potentialities using a Dominance-based Rough Set Approach.

Rural Development is a priority in Europe and it is supported by specific, financial programmes. At the same time, sustainability is the key word for the European Union to construct programmes and policies for all human activities. However, measuring sustainability of rural areas is not easy, due to their particular features. The improvement of knowledge on sustainability in rural areas is important to build long term policies and strategies for those territories. The objective of this study is the development of a decision support system based on the Dominance-based Rough Set Approach (DRSA), to assess the level of Rural Sustainable Development in specific areas. We used DRSA to analyze the level of sustainability of the 92 municipalities of the Region of Umbria, Italy. The results were synthesized in a final ranking, taking into account the equilibrium and the integration between development and sustainability of each municipality. DRSA showed a high potential in the context of management or planning, and for supporting Decision Makers. DRSA is able to give a ranking as well as an explanation of the main factors driving sustainable development in rural areas.