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In the near future, cities will have to supply innovative and high value-added mobility services, that shall be sustainable in terms of environmental impact, traffic management and energy efficiency. This represents a great challenge: transportation accounts for 20% of the global energy consumption, with a large share in urban areas (around 40% of total transport consumption). One of the most promising solutions to reduce congestion, energy consumption and air pollutants in highly-populated areas is Ride Sharing. Ride Sharing systems aim to bring together travellers with similar itineraries and time schedules, thus providing significant societal and environmental benefits, such as reducing the number of cars used for personal travel and improving the utilization of available seat capacity (also defined "occupancy rate"). This paper examines the impact of Ride Sharing by developing an enhanced transport model in Visum, which takes into account the shareability of passengers mobility patterns. The model is applied to the Milan Metropolitan Area, which represents an interesting test case for two main reasons: first, its high population density and strong transport offer and second, the large amount of information and data available on passengers mobility. The paper assumes an optimal 20% participation rate to Ride Sharing and estimates its benefits in terms of congestion reduction, energy efficiency and environmental impact. The COPERT software is used to estimate Carbon Dioxide emissions and fuel consumption savings. The simulation results show that Ride Sharing brings a sort of rebound effect, since there is an increase in passengers traveling by car. However, the overall effect is a reduction in the number of vehicles used, with consequent reductions in vehicle kilometers travelled (-3.8%). This translates into 6% energy savings and 6% Carbon Dioxide emissions reduction. Some policy recommendations are provided to develop Ride Sharing in order to increase the effectiveness of this system while restraining side effects. [ABSTRACT FROM AUTHOR]

Future residential applications could benefit from nanogrids that integrate photovoltaics (PV) and battery energy storage systems (BESS), especially after the establishment of recent European Community directives on renewable energy communities (RECs) and jointly acting renewable self-consumers (JARSCs). These entities consist of aggregations of users who share locally produced energy with the aim of gaining economic, environmental, and social benefits by enhancing their independence from the electricity grid. In this regard, the sizing of the PV and BESS systems is an important aspect that results in a trade-off from technical, economic, and environmental perspectives. To this end, this paper presents an investigation on the optimal PV-BESS system sizing of a condominium acting as a JARSC community, which includes a common PV plant and EMS, operated by rule-based criteria. PV-BESS sizing results are investigated from economic and environmental perspectives, considering a case study located in Milan, Italy. In these regards, in addition to the common techno-economic criteria, carbon dioxide emissions are considered with particular attention, as their reduction is the driving ethos behind recent EU directives. [ABSTRACT FROM AUTHOR]

Cities face unprecedented challenges and opportunities. The challenges include the need to tackle phenomena from climate change to population growth, as well as how to bring the European Union (EU) closer to the goal of climate neutrality by reducing carbon emissions. The political-institutional focus to resolve these issues is urgently required. The interventions that are needed in cities to meet the Green Deal objectives are numerous and diverse (including energy, transport, nature and biodiversity, food and agriculture, green finance, as well as with respect to the circular economy [CE]). Diverse approaches are justified, to an extent, as the starting point is not the same for all cities involved in the transition (large, medium and small) and reaction capacities are different. Diversity can cause confusion, however, and this has been found in particular with so-called circular cities; the absence of a defined intervention model has caused some cities to adopt both narrow and wider visions, leading to many 'circular imaginary' cities. The origins of these visions have stemmed from the industrial rather than the urban context, with several adaptations being made. This paper starts by discussing the journey to sustainable cities — in particular the role of circular cities in the Green Deal — and then explores the existence or lack of strategies for circular cities. Amsterdam and Milan are used as case studies to explore whether and when circular cities can be considered cornerstones of the ecological transition. [ABSTRACT FROM AUTHOR]

Recent European Community directives introduce Renewable Energy Communities (REC) and Jointly Acting Renewable Self-Consumers (JARSC). Both entities are constituted by communities of residential and/or non-residential prosumers, located in proximity of renewable generators and Electrical Storage Systems (ESS) owned and managed by the REC/JARSCs. These aggregations of prosumers are aimed at providing environmental and economic benefits by maximizing their global self-consumption. In this frame, it is relevant to introduce a control strategy which considers the whole system represented by the REC/JARSCs and performs optimal management of energy production, storage and consumption. The present paper proposes a Model Predictive Control (MPC) based control design, targeted at the minimization of electricity cost and equivalent CO2 emissions, considering the whole ensemble of loads included in the REC/JARSCs over a 24-h prediction horizon. To exploit the MPC ability of including forecasts in the optimization problem, predictors including Artificial Neural Networks (ANN) are developed for solar irradiance, air temperature, electricity price and carbon intensity. The proposed control performance is evaluated considering a case study located in Milan, Italy, and its advantages with respect to traditional control algorithms are highlighted by comprehensive numerical simulations. Lastly, an economic evaluation of the considered system is presented. • RECs and JARSCs are new forms of self-consumption introduced by EU directives. • RECs/JARSCs operation approached as an optimization problem by an MPC Controller. • ANN-based predictors for PV production, electricity price and carbon intensity. • Evaluation of economic revenues and CO2 emission reduction in different Scenarios. [ABSTRACT FROM AUTHOR]

According to the United Nations (UN), although cities occupy only 3% of Earth's surface, they host more than half of the global population, are responsible for 70% of energy consumption, and 75% of carbon emissions. All this is a consequence of the massive urbanization verified since the 1950s and which is expected to continue in the coming decades. A crucial issue will therefore concern the management of existing cities and the planning of future ones, and this was also emphasized by the UN Sustainable Development Goals (SDGs), especially in Goal 11 (Sustainable Cities and communities). Smart Cities are often seen as ideal urban environments in which the different dimensions of a city (economy, education, energy, environment, etc.) are managed successfully and proactively. So, one of the most important challenges cities will have to face, is to guide citizens towards a form of "clean" energy consumption, and the dimension on which decision-makers will be able to work is the decarbonization of transport. To achieve this, electric mobility could help reduce polluting emissions on the road. Within this research, the strategies that six Smart Cities (London, Hamburg, Oslo, Milan, Florence, and Bologna) have implemented to encourage the transition to this form of mobility have been studied. Through a systematic review of the literature (Scopus, Google Scholar, and Web of Science) and through the study of the main political/energy documents of the cities, their policies on electric mobility have been evaluated. Then, for each city, SDG 11.6.2 was analyzed to assess the air quality in the last four years (2016–2019) and, therefore, the effectiveness of the policies. The analysis showed, in general, that the policies have worked, inducing reductions in the pollutants of PM2.5, PM10, NO2. In particular, the cities showed the most significant reduction in pollutant (above 20%) were Hamburg (−28% PM2.5 and −2%6 NO2), Milan (−25% PM2.5 and −52% NO2), and London (−26% NO2). [ABSTRACT FROM AUTHOR]