This paper focuses on applying multicriteria decision making tools to determine an optimal energy retrofit plan for a portfolio of buildings. We present a two-step decision making technique employing a multiobjective optimization algorithm followed by a multiattribute ranking procedure. The method aims at deciding, in an integrated way, the optimal energy retrofit plan for a whole stock of buildings, optimizing efficiency, sustainability, and comfort, while effectively allocating the available financial resources to the buildings. The proposed methodology is applied to a real stock of public buildings in Bari, Italy. The obtained results demonstrate that the approach effectively supports the city governance in making decisions for the optimal management of the buildings' energy efficiency

In this paper, a review of the recent scientific literature contributions on innovative strategies for last mile logistics, focusing on externalities cost reduction, is presented. Transport is causing problems in urban areas, in particular in freight transport: modern cities need solutions to reduce externalities costs such as congestion, pollution and others, which have increased in the last few years, especially due to the growth of goods delivery. Online sales and globalization lead to new trends in freight transport, and moreover, a larger quantity of goods is expected to be delivered in the next future. In this context, most of the delivered goods end up in the city centers. Last mile logistics is the least efficient stage of the supply chain and comprises up to 28% of the total delivery cost. Therefore, the improvement of last mile logistics and a significant externalities reduction are very important challenges for researchers. New technologies and transport means, innovative techniques and organizational strategies allow handling in a more effective way the last mile delivery in urban areas. Based on the Systematic Literature Review (SLR) method, recent papers that significantly contributed, with original proposals, to the reduction of externalities in urban logistics are identified and analyzed in this work. Furthermore, a classification of the papers dealing with the externality reduction problem is presented. It is consistent with a general formulation proposed to evaluate external costs in urban area. The innovative contributions are classified into five main categories: innovative vehicles, proximity stations or points, collaborative and cooperative urban logistics, optimization of transport management and routing, innovations in public policies and infrastructures. The new paradigm of smart logistics is based on the combination of these concepts and on the proposed innovations.

During the last years, due to the strict regulations on waste landfilling, anaerobic digestion (AD) of the organic fraction of municipal solid waste (OFMSW) is increasingly considered a sustainable alternative for waste stabilization and energy recovery. AD can reduce the volume of OFMSW going to landfill and produce, at the same time, biogas and compost, all at a profit. The uncertainty about the collected quantity of organic fraction, however, may undermine the economic-financial sustainability of such plants. While the flexibility characterizing some AD technologies may prove very valuable in uncertain contexts since it allows adapting plant capacity to changing environments, the investment required for building flexible systems is generally higher than the investment for dedicated equipment. Hence, an adequate justification of investments in these flexible systems is needed. This paper presents the results of a study aimed at investigating how different technologies may perform from technical, economic and financial standpoints, in presence of an uncertain organic fraction quantity to be treated. Focusing on two AD treatment plant configurations characterized by a technological process with different degree of flexibility, a real options-based model is developed and then applied to the case of the urban waste management system of the Metropolitan Area of Bari (Italy). Results show the importance of pricing the flexibility of treatment plants, which becomes a critical factor in presence of an uncertain organic fraction. Hence, it has to be taken into consideration in the design phase of these plants.

Healthcare (HC) is one of the largest and most complex industries. In the last years Local Healthcare Agencies (LHAs) have been experienced high increase in expenditure. New methodological approaches allowing to optimize their efficiency and effectiveness are needed. Hospital departments are the most expensive services provided by LHAs. In this paper, a framework to model LHAs and evaluate the effects of some strategic decisions on LHAs performances is proposed. The analysis focuses on hospital units treating heart failure diseases since they are one of the main hospital admissions causes. The “de- hospitalization” of heart failure care pathways is evaluated as a possible solution to the problem of reducing costs and improving quality of service such as the system capability to provide service without delays.

According theKyoto Protocol,nations around theworld,including Italy,need therationalizationofenergy consumption and lower consumption of conventional energy sources to help reduce greenhouse gases emissions. Article 5 of Italian Law 10/1991, in paragraph 5, states that municipalities with more than 50 thousand inhabitants should include a specific plan about the use of renewable energy to improve its efficiency, i.e. a Municipal Energy P lan. The purpose of this paper is to present a pilot case study in the South of Italy of Municipal Energy P lan, an indispensable tool for planning the economic, social and environmental development of the territory. The Municipal Energy Planning is identified among the priority objectives of the Environmental Action Plan adopted by Local Agenda 21. The Energy P lan collects and analyzes all incoming and outgoing energy flows in the municipal area, including the energy use for various sectors (residential, agriculture, industry and handicrafts, services, transport) and for different resources (solid fuels, derived from petroleum, natural gas, electricity). The final phase of the work will be to create some future scenarios that will be implemented by the City Council to address the strategic priorities in the years.

Energy production from the anaerobic digestion of organic waste is widely recognized as a social and environmental opportunity, since it allows reducing waste disposal and making waste management economically profitable. However, profitability of these plants is strongly affected by the quantity and the quality of wastes, as well as by the availability of local subsidies. The key role of incentive policies in the economic success of investments in biomass to energy plants is highly recognised and has led European Union (EU) governments to promote the deployment of these plants. Incentive policies adopted in EU countries differ significantly. In this paper, an evaluation model based on cost-benefit analysis is developed in order to identify the production-based incentive rates making investments in anaerobic digestion plant economically feasible without reducing social and environmental positive impacts. The model has been applied to the case of energy production plants from anaerobic digestion of cattle manure. In order to investigate the influence of the plant size on the investment profitability, different waste collection areas have been considered. Environmental performances of the plants have been evaluated by adopting a life cycle assessment approach. Results obtained confirm the environmental benefits achievable through the energy production from the anaerobic digestion of cattle manure. However, the current production-based incentive rates provided in most EU Countries revealed an inadequate balance between private and public interest, since they make profitable the investments only in case of small plants.

Assessing sustainability of manufacturing processes through LCA tools is a common approach today, but it suffers some limitations, mainly due to the use of standard databases. Deepening the assessment of sustainability is, instead, a new field of interest. This paper shows how LCA can be optimized, based on the results of a thermographic analysis supplying detailed information to a traditional LCA tool. The aim is to test this this approach observing a real industrial case of an Italian company producing High Density PolyEthylene (HDPE) nets for agriculture. A thermographic analysis of the critical processes helps in assessing the in-progress eco-profile of the process under investigation. The approach is intended as an iterative procedure to make both LCA analysis much more pertinent to the specific application and decisions on process sustainability more adherent to real practice. The improved LCA allowed to balance the specific energy savings intervention (recognized by the grace of thermographic analysis) by benchmarking the potential process quality improvements with standard reference processes. These balanced design choices and improvements can avoid useless over-dimensioning of the devices. In turn this can help to reach sustainable quality of both products and processes

The paper presents a multi-objective optimization algorithm to improve in an integrated and holistic way the building stock energy efficiency, sustainability, and comfort, while efficiently allocating the available budget to the buildings. The developed algorithm determines a set of optimal energy retrofit plans for a portfolio of public buildings in a smart city. An existing stock of public buildings located in the municipality of Bari, Italy is used as case study. The application results demonstrate that the developed algorithm is an effective support tool for the smart city governance in enhancing the energy efficiency performance of a stock of public buildings.

The full development of the energy services company (ESCO) industry is still inhibited by the difficulties during the negotiation between customers and ESCOs. Contractual arrangements are traditionally based on energy performance contracting (EPC). Improvements on EPC schemes are required in order to achieve the success of the negotiation. This work focuses on a particular type of EPC, named guaranteed savings (GS) contract, where a minimum energy saving is guaranteed to the customer by the ESCO. A model based on real options theory to share risks among contractual parties is proposed in order to estimate the fair value of main contractual parameters. A Monte Carlo simulation is adopted for evaluating the most critical factors influencing the overall risk sharing. A numerical example concerning a cogeneration plant of a paper mill is presented. A two level full factorial design of experiments (DOE) analysis is carried out in order to estimate single and compound effects of model parameters.