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Reducing greenhouse gas emissions is a crucial challenge in urban areas characterized by high energy consumption and reduced exposure to nature. In this context, the urban green system could play a pivotal role. In the literature, scholars have analyzed both the ability of species-specific and layout-specific green infrastructure to increase carbon sequestration and the best location sites for new green infrastructure to increase the provision of overall ecosystem services. There is a lack of studies helping green urban planners and designers choose where and which green infrastructure to implement based on vegetation species-specific performance and the local carbon emissions of city components. This paper uses tree inventory data from a medium-sized city in central Italy (Perugia) to develop a spatial analysis of urban park performance in carbon sequestration. Then, the method evaluates the carbon emission of a public city building to generate a spatialized balance between building demand and tree supply to support local decisions about the best locations for new green infrastructure and the choice between species. The paper contributes to GIS-based tools that vary the recommended location sites and species for new green infrastructure based on the demanded ecosystem service. [ABSTRACT FROM AUTHOR]

The paper discusses the energy efficiency of smart working (SW) as a solution to traditional work-approach issues, with a focus on evaluating benefits for both employers and employees. Remote working, while offering environmental advantages such as reduced commuting and office space use, poses challenges in assessing its true impact. The study presents results from a dynamic analysis on a real residential building, typical of an architectural style diffused in northern Italy, revealing a 15% average increase in energy consumption when all work tasks are performed from home. To address concerns about the environmental impact of SW, the research proposes a method and metrics for evaluation. Four novel indices (SWEET, SEE, SSEE, and 4E) are introduced, providing a structured approach to assess the energy efficiency of SW initiatives. The paper outlines a methodology for data gathering and metric application, aiming to acquire quantitative insights and mitigate disparities arising from a transfer of burdens to employees. This contribution not only signifies a ground-breaking methodology but also addresses an unresolved research question concerning the evaluation of the actual energy efficiency of smart working implementations for both employers and employees. The results underscore the importance of understanding the nuances of SW's impact on household energy usage and its broader implications for sustainability goals. [ABSTRACT FROM AUTHOR]

Before the COVID-19 pandemic, ventilation in buildings was not always given its due importance. The World Health Organization has highlighted the important role of air exchange with the outdoors in improving the air quality in buildings; buildings should, therefore, be equipped with mechanical ventilation or adequate air conditioning systems. This paper aims to investigate different retrofit solutions for air conditioning, evaluating them in terms of energy consumption and cost and the impact of increased outdoor air exchange rates on countering the propagation of COVID-19; the latter is the main novelty of the paper. As a case study, we take an existing office building located in Central Italy that was previously not equipped with a mechanical ventilation system (a system with primary air was introduced during the study). The energy analysis was conducted using dynamic simulation software after validation through energy bills; energy and economic analyses were conducted considering different external-air exchange rates. An optimal number of outdoor air changes was found to mitigate the risk of COVID-19 infection, a finding in line with the international literature. The increase in air changes with outdoor air leads to a rise in energy consumption and costs. These values were evaluated for different air conditioning systems and operational schedules. These drawbacks can be made less significant by combining interventions in the system with energy-efficiency measures applied to the building envelope. [ABSTRACT FROM AUTHOR]

In the frame of developing sustainable, reliable, and regenerative interventions on existing buildings, namely on large-scale public housing, the implementation of functional, technological, and effective strategies is devoted to thoroughly assessing the transformability of buildings using trustworthy performance indicators. With this aim, in the present paper, an assessment framework tool is presented and tested to evaluate the potential of buildings for transformation through the detection of regeneration strategies for the reduction of energy consumption, a definition of the new apartments' internal layout, and the implementation of sustainable systems to foster rainwater harvesting. The procedure is tested on a case study in Latina (Italy), showing its suitability to quantitatively assess the regenerative potentiality of public housing, thus resulting in an effective supporting tool for designers and policy makers. [ABSTRACT FROM AUTHOR]

The transition towards energy efficiency measures and green energy sources is strongly fostered by the European Union. Italy is among the EU countries that have heavily invested in renewable energy sources, more than doubling their share in gross final energy consumption. In particular, biogas has a pivotal role in the generation of electricity and can also be upgraded into biomethane, with a higher and more stable energy content. In this study, the sustainability of the supply chain of electricity from biogas in Italy has been thoroughly analyzed in the broader framework of the ARCADIA (Life Cycle Approach in Public Procurement and Italian LCA Database for Resource Efficiency) project. The environmental assessment, carried out by means of Life Cycle Assessment (LCA), provides a two-fold perspective. Firstly, it allows us to identify the main hotspots of the investigated system, such as the cultivation of dedicated crops, and to provide useful insights for improving environmental performance. Furthermore, a focus on the modeling of the dataset related to the production of electricity from biogas within the Italian electricity mix represents a step ahead in the LCA research, filling the lack of site-specific databases for reliable LCA results. [ABSTRACT FROM AUTHOR]

This study considers an application of the first-order Grey Markov Model to foresee the values of Italian power generation in relation to the available energy sources. The model is used to fit data from the Italian energy system from 2000 to 2022. The integration of Markovian error introduces a random element to the model, which is able now to capture inherent uncertainties and misalignments between the Grey Model predictions and the real data. This application provides valuable insights for strategic planning in the energy sector and future developments. The results show good accuracy of the predictions, which could provide powerful information for the effective implementation of energy policies concerning the evolution of energy demand in the country. Results show an improvement in the performance of more than 50% in terms of Root Mean Squared Error (RMSE) when the Markov chain is integrated in the analysis. Despite advancements, Italy's 2032 energy mix will still significantly rely on fossil fuels, emphasizing the need for sustained efforts beyond 2032 to enhance sustainability. [ABSTRACT FROM AUTHOR]

Neutral-temperature district heating and cooling (NT-DHC) is a recent concept in the district heating sector. The current literature does not directly address the ability to create comprehensive master plans for NT-DHC systems and reliably model their performance. This research presents a new approach for the evaluation and planning of NT-DHC systems. The methodology involves the use of a knapsack optimization algorithm to perform a comprehensive analysis of the conditions that make the NT-DHC solution competitive against individual heating and cooling technologies. The algorithm determines the optimal combination of potential extensions that maximizes overall economic value. The results of a case study, which was conducted in Italy, show that NT-DHC is more suitable in dense urban areas, while air-to-water heat pumps are better suited for low heat density zones. This methodology aims to reduce the risks associated with energy demand and provide more certainty about which areas a network can expand into to be competitive. It is targeted at energy planners, utilities experts, energy engineers, and district heating experts who require assistance and guidance in the planning and early stages of designing a NT-DHC system. This method might enable pre-feasibility studies and preliminary design to determine the opportunities and limitations of a system of this kind from an economic and technological perspective. [ABSTRACT FROM AUTHOR]

The paper deals with the energy transition, focusing on the decisions to be taken about the change in the energy conversion capacity of specified portion of the universe, such as industrial or domestic districts, regions, countries, etc. Conversion capacity is intended here as the set of all energy conversion and storage units characterized by type, size and number, and interacting with the natural gas and electricity grids. The goal is to find guidelines for new installations, obtained by simulations of a model able to describe properly the behavior of each energy conversion technology and the interaction with grids. The model is based on a traditional MILNP approach, but contains unique features in the literature, which allow to obtain results of general validity for applications to very different geographical areas, or to countries including very different regions that transmit energy with each other or export/import it from abroad. The main novelty of this work is to identify the best planning for the decarbonisation of energy demand sectors, according to the criterion of minimum cost, both at global and at regional level. The results applied to the case of Italy allow identifying clearly the energy demand sectors to which new installations should be applied first to minimize the cost for the total energy system, and the units that must be foreseen to satisfy these energy demands, i.e. a precise strategy for the energy transition towards a 100% renewable system. • A multi-regional model is built to find the most convenient energy transition path. • General guidelines for Western countries are derived from the Italian case study. • Replacement of boilers with heat pumps allows increasing RES share from 20 to 30%. • For RES share >60%, PtG is the low-carbon strategy for high temperature heat demand. • Transportation is the last energy sector that should be decarbonized. [ABSTRACT FROM AUTHOR]

This paper studies the influence of temperature and of rainfall intensity and the effect of such variations on the treatment efficiencies and on the electrical consumptions in seven medium-large size Wastewater Treatment Plants (WWTPs) in Apulia in South Italy (Bari, Barletta, Brindisi, Lecce, Foggia, Andria and Taranto). It has been observed, in the considered WWTPs, a slight but clear increase of the incoming flow due to the increase in rainfall intensity, which results to an increase of the energy consumption per incoming volume. The impact of the climate change to the incoming flow, during the last five years (2016–2020), has been assessed indicating that an increase in rainfall intensity results to an increase of the WWTPs energy consumptions per wastewater treated volume. More specifically, for a specific WWTP (Lecce) it was found that the electrical consumption increases from 0.36 kw/m3 to 0.51 kw/m3 when the rainfall intensity was increased from 0.8 mm/min to 2.9 mm/min. Some adaption measures have been considered to upgrade the existing WWTP so to mitigate the energy increase and to limit the global effects of climate change. [Display omitted] • As Rain intensity rises, wastewater influx into WWTPs increases. • Rainfall intensity influences negatively electrical consumptions. • BOD removal is lower with increasing annual precipitations. • Temperature influences BOD, COD and SST removal efficiency. [ABSTRACT FROM AUTHOR]

Wastewater treatment plants are highly energy-intensive systems. This research uses Life Cycle Assessment (LCA) to determine the impacts generated during the operation of a wastewater treatment plant. Three different scenarios are analyzed: a baseline scenario that considers a conventional activated sludge treatment technology exploiting data from an existing plant located in central Italy, a second scenario that involves the implementation of MBR technology applied to the baseline scenario, and finally a third scenario that consists of the addition of an anaerobic digester that allows energy recovery from biogas production, followed by a photovoltaic plant capable of supplying the plant energy demand. Global warming potential, eutrophication, and acidification are the environmental categories considered most relevant to emissions. The results showed that the effluent had the highest impact in terms of CO2 equivalent in all three situations due to the presence of N2O. Since emissions from biological processes, transportation, and wastewater are almost similar in all three scenarios, it is preferable to focus on the environmental impacts associated with energy consumption. The third scenario involves careful resource management and the use of treatment technologies that allow for a reduction in the use of nonrenewable energy sources in favor of renewable ones. [ABSTRACT FROM AUTHOR]

The diffusion of electric vehicles is fundamental for transport sector decarbonization. However, a major concern about electric vehicles is their compatibility with power grids. Adopting a whole-power-system approach, this work presents a comprehensive analysis of the impacts and benefits of electric vehicles' diffusion on a national power system, i.e., Italy. Demand and flexibility profiles are estimated with a detailed review of the literature on the topic, allowing us to put forward reliable charging profiles and the resulting flexibility, compatible with the Italian regulatory framework. Distribution network planning and power system dispatching are handled with dedicated models, while the uncertainty associated with EV charging behavior is managed with a Monte Carlo approach. The novelty of this study is considering a nationwide context, considering both transmission and distribution systems, and proposing a set of policies suitable for enabling flexibility provision. The results show that the power and energy demand created by the spread of EVs will have localized impacts on power and voltage limits of the distribution network, while the consequences for transmission grids and dispatching will be negligible. In 2030 scenarios, smart charging reduces grid elements' violations (−23%, −100%), dispatching costs (−43%), and RES curtailment (−50%). [ABSTRACT FROM AUTHOR]