Integrated waste management system and new business pattern: strategies and modelling towards Circular Economy

Nowadays, one of the biggest challenges is decoupling economic growth from the environmental impacts related to resource depletion, pollutants emissions and waste management. It represents an ambitious goal for both the extent of required changes and the breadth of its scope. It is now a requirement, which can also be defined as urgency, dictated by models that for a long time have considered the environmental aspects as side-effects subordinated to the achievement of economic results. Up to now, the economic model ‘take, make, dispose’ has been pursued to ensure population needs. It has contributed to human development and prosperity, optimizing the elements independently, and not taking into account environmental impacts on the planet. Circular economy fosters a general rethinking of the traditional linear model and orientates the choice to more effective business models. As the European Commission states, “Circular Economy looks at product and waste”. It looks at product through the implementation of business model operating from the early phase of designing to the final phase of use and dismantling. As well as, it works on wastes since, with the right approach and technologies, many waste streams become an important income stream. This is a landmark change whereas for a long time wastes were conceived and treated in a ‘zero added value’ pattern. To promote the transition towards circular economy, the main aim of this thesis has been developing both strategic planning models and analytical ones to plan, predict and evaluate the effects on economic, environmental and social performance due to the implementation of new business pattern and of efficient waste management system. Efficient integrated waste management system and innovative business models have been recognized as key factors in fostering the transition towards CE. However, in both case the implementation is not fully exploited in the huge potential. Hence, the adoption of business model ‘circular-oriented’ struggle to take hold. The causes may lie in the lack of assessment of the barriers perceived by the various actors involved in such a change and of effective impacts on different sustainable performance. Being a new business model, it is probably ‘not mature enough to be born spontaneously’. Both long-term sustainability and support policies should be evaluated. To understand the effects on economic, environmental, social and technical performance due to a shift from a traditional ownership-based business model to a leasing-based business model and closed-loop schemes, a Fuzzy Cognitive Map is developed. Supported by a case study proposed by the Ellen MacArthur Foundation, the washing machines segment is explored. The FCM allowed the identification of all impacts extensive on all actors and their relationship. On waste management side, although the progress so far achieved, a considerable amount is still landfilled and too little recycled (EU, 2017). Adverse effects on climate change are considerable. The effectiveness of such a system depends not only on technical and organizational issues but also on socio-cultural factors like citizens’ participation and cooperation, education and awareness campaigns. His will to implement a conscious and correct collection represents the beginning of the circularity. Not enough efforts have been made in that direction to understand to define that contribution. The role of communication and information as means to increase involvement and awareness of public policy/technical decision makers and citizens is completely unexplored. Consistently, a mixed integer non-linear programming model to minimize the GHGs emissions of the integrated waste management system is developed. Through a scenarios analysis approach, the evaluation of how citizen’s behaviour affect the level of separated collection and GHGs emissions is carried out and evaluated throught the definition of the Marginal Environmental Benefit. An Artificial Neural Network- based decision support tool for the assessment of system arrangements as well as prediction of direct/avoided emissions and financial flows id developed too. Finally, a description of a developed web-app-‘Smart Waste-Carbon Footprint Calculator’ –as smart tool to plan and to monitor with twice interface customized for citizens and decision makers is provided.