Sustainability in urban development, economic growth and human well-being are critical issues faced all over the world. In the last decade urban planning and management had accomplished, or will do it, innovations in order to meet the challenges posed by sustainable development. Reduction of 20% of GHG emission, the achievement of 20% energy demand by renewable energy together with an increase of 20% of energy efficiency are targets foreseen by EU. In this scenario a strategic role is played by municipal waste integrated management system (MWIMS). The matter is becoming increasingly important as a results of the growth of urbanization rate: the raising complexity of a MWIMS relies on the high number of design and management variables and relationships pertaining to collection, treatments and disposal phases. Waste management practices can sway greenhouse gas emission by affecting energy consumption, methane generation, carbon sequestration and non-energy related manufacturing emission. In this context, a sustainable waste management system allows a reduction of negative impacts on environment. The purpose of such a study is to propose a decision-making framework aiming to minimize the carbon footprint of a MWIMS. The model goes beyond the existing technical and organizational solutions outlining the different options in a much broader view concerning both waste collection and treatments. A mixed integer linear programming model , has been applied to a full case study concerning Bari. The study is carried out within the research project RES NOVAE (Reti, Edifici, Strade ‐ Nuovi Obiettivi Virtuosi per l’Ambiente e l’Energia). The strength of the framework results in supporting public decision-making, a complex process due to the number of decision variables and their implications on economic performance. Results exhibit the effectiveness of the model also in pointing out opportunities non yet evaluated.
Minimizing Carbon-footprint of Municipal Waste Integrated Management Systems / Digiesi, S; Mossa, G; Mummolo, G; Verriello, R. - In: ...SUMMER SCHOOL FRANCESCO TURCO. PROCEEDINGS. - ISSN 2283-8996. - (2014), pp. 373-378. (Intervento presentato al convegno XIX Summer School Francesco Turco, 2014 tenutosi a Senigallia, Italy nel September 9-12, 2014).
Minimizing Carbon-footprint of Municipal Waste Integrated Management Systems
Digiesi S;Mossa G;Mummolo G;Verriello R
2014-01-01
Abstract
Sustainability in urban development, economic growth and human well-being are critical issues faced all over the world. In the last decade urban planning and management had accomplished, or will do it, innovations in order to meet the challenges posed by sustainable development. Reduction of 20% of GHG emission, the achievement of 20% energy demand by renewable energy together with an increase of 20% of energy efficiency are targets foreseen by EU. In this scenario a strategic role is played by municipal waste integrated management system (MWIMS). The matter is becoming increasingly important as a results of the growth of urbanization rate: the raising complexity of a MWIMS relies on the high number of design and management variables and relationships pertaining to collection, treatments and disposal phases. Waste management practices can sway greenhouse gas emission by affecting energy consumption, methane generation, carbon sequestration and non-energy related manufacturing emission. In this context, a sustainable waste management system allows a reduction of negative impacts on environment. The purpose of such a study is to propose a decision-making framework aiming to minimize the carbon footprint of a MWIMS. The model goes beyond the existing technical and organizational solutions outlining the different options in a much broader view concerning both waste collection and treatments. A mixed integer linear programming model , has been applied to a full case study concerning Bari. The study is carried out within the research project RES NOVAE (Reti, Edifici, Strade ‐ Nuovi Obiettivi Virtuosi per l’Ambiente e l’Energia). The strength of the framework results in supporting public decision-making, a complex process due to the number of decision variables and their implications on economic performance. Results exhibit the effectiveness of the model also in pointing out opportunities non yet evaluated.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.