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The aim of this study is to assess the effect of contact time, contact distance and the use of personal protective equipment on the determination of SARS-CoV-2 infection in healthcare workers (HCWs). This study consists of an analysis of data gathered for safety reasons at the Sapienza Teaching Hospital Policlinico Umberto I in Rome through the surveillance system that was put into place after the worsening of the COVID-19 pandemic. The studied subjects consist of HCWs who were put under health surveillance, i.e., all employees who were in contact with subjects who were confirmed to have tested positive for SARS-CoV-2. The HCWs under surveillance were monitored for a period encompassing ten days after the date of contact, during which they undertook nasopharyngeal swab tests analysed through RT-PCR (RealStar® SARS-CoV-2 Altona Diagnostic–Germany). Descriptive and univariate analyses have been undertaken, considering the following as risk factors: (a) no personal protective equipment use (PPE), (b) Distance &lt, 1 m between the positive and contact persons, (c) contact time &gt, 15′. Finally, a Cox regression and an analysis of the level of synergism between factors, as specified by Rothman, were carried out. We analysed data from 1273 HCWs. Of these HCWs, 799 (62.8%) were females, with a sample average age of 47.8 years. Thirty-nine (3.1%) tested positive during surveillance. The overall incidence rate was 0.4 per 100 person-days. Time elapsed from the last exposure and a positive RT-PCR result ranged from 2 to 17 days (mean = 7, median = 6 days). In the univariate analysis, a distance &lt, 1 m and a contact time &gt, 15′ proved to be risk factors for the SARS-CoV-2 infection, with a hazard ratio (HR) of 2.62 (95% CI: 1.11–6.19) and 3.59 (95% IC: 1.57–8.21), respectively. The synergism analysis found the highest synergism between the “no PPE use” x “Contact time”. The synergy index S remains strongly positive also in the analysis of the factors “no PPE use” x “Distance” and “Time of contact” x “Distance”. This study confirms the absolute need to implement safety protocols during the pandemic and to use the correct PPE within health facilities in order to prevent SARS-CoV-2 infection. The analysis shows that among the factors considered (contact time and distance, no use of PPE), there is a strong synergistic effect.

Buildings account for about 36% of CO2 emissions and 40% of energy consumption at EU level. Thus, a deep renovation of the building stock is fundamental to achieve the sustainability targets established worldwide. Accordingly, the study proposes an integrated approach for energy modeling and retrofit planning of districts/neighborhoods of buildings. A Geographic Information System (GIS) tool is coupled with SketchUp® to generate accurate geometrical models, while the thermophysical definition of the building envelopes is performed under DesignBuilder®. Then, EnergyPlus is used as dynamic energy simulator, while MATLAB® is the external post-processing engine. In detail, two phases are identified: 1) development of the energy model; 2) energy retrofit optimization. The approach is relevant to different scale-levels simultaneously, from a single apartment to the whole district/neighborhood as an entity. Furthemore, the use of EnergyPlus ensures high accuracy in energy predictions, while modeling the energy systems directly under MATLAB® environment strongly reduces the computational burden without affecting the results’ reliability. As a case study, part of an existing neighborhood located in Naples (Italy) and representative of the Southern Italy building stock is modeled, and its retrofit is optimized. According to the Italian laws, three retrofit levels are investigated to compare their effects on selected energy, financial and environmental indicators. Finally, two optimal solutions are selected: the “nZEB” (nearly Zero-Energy Building) and the “cost-optimal” ones. The former is the one that minimizes the neighborhood’s primary energy consumption, which passes from 116.9 kWh/m2a to 72.3 kWh/m2a, while the latter minimizes the global cost, which passes from 184.4 €/m2 to 129.6 €/m2.

Buildings account for around one third of World energy consumption and polluting emissions, thus their energy retrofit is crucial aiming at reducing the human impact on the environment. In this context, worldwide, public grant policies and stringent requirements have been adopted to promote energy efficiency in the building sector. This study proposes a comprehensive analysis to drive the energy retrofit of building neighborhoods by examining energy efficiency measures involving envelope components, heating, ventilating and air conditioning systems, photovoltaics. The effects of the creation of a local energy community that shares the photovoltaic production are taken into account too. Finally, the Italian “Superbonus 110%” public grant policy is considered, and some insights are given. More in detail, the analysis aims at minimizing at the same time the primary energy consumption and the global cost, satisfying both the public and the private stakeholders. It makes use of different software: CADMapper® and SketchUp® for modeling the geometry of the neighborhood; DesignBuilder® for realizing the first raw energy model; EnergyPlus to refine the energy model and to perform dynamic energy simulations; MATLAB® to post-process the results of the simulations. As case study, an existing neighborhood located in Naples (Italy) is investigated and three suboptimal solutions are proposed: nZEB solution, cost-optimal solution and utopia solution. Sensible reductions in energy consumption and global cost can be achieved in presence of public grants, i.e., up to 69.2 kWh/m2a and 153.6 €/m2, respectively.

This paper aims to underline the variability of constructions in Mediterranean regions, where different climates, architectural techniques and kinds of building uses determine different optimal energy refurbishments of residential buildings placed on the coastline. More in detail, by considering two different construction technologies (i.e., a lightweight house in reinforced concrete and a massive tuff-made villa), two different climates (Greek coast, climate of Athens and Italian coast, climate of Naples), two cost-optimal energy retrofits are presented. The optimized energy retrofit, performed by coupling transient energy simulations and genetic algorithm for generating improved models, have taken into account all levers of energy efficiency, and thus optimization of building envelope (thermal insulation, reflectance, windows and solar screens), active energy systems (daylight control, HVAC systems for the regulation of indoor conditions) and renewable energy sources at the building scale (namely, solar photovoltaic).

The energy transition of neighborhoods towards nearly zero energy buildings (nZEBs) is fundamental to promote sustainability. The study deals with this issue by proposing a methodology to optimize energy retrofit through the exploitation of solar energy by photovoltaics. Part of a neighborhood in the city of Naples (South Italy) is investigated. The coupling between EnergyPlus and MATLAB® is used for energy modelling, simulations and retrofit optimization through a smart research method, performing a comprehensive analysis of heating, cooling and electric loads. A Pareto multi-objective approach is applied to minimize both energy consumption and global cost in order to optimize the solar energy exploitation and to achieve the nZEB standard while ensuring cost-effectiveness. Different retrofit scenarios for building envelopes and energy systems are investigated. Two optimal retrofit solutions are identified. One pursues the minimization of the neighborhood's energy impact ensuring a PEC reduction from 116.8 kWh/m2a to 66.3 kWh/m2a with discounted payback (DPB) of around 10 years. The other solution maximizes the cost-effectiveness yielding a PEC around 83.7 kWh/m2a with a DPB of only 4 years. The outcomes offer deep insights into the potentials of energy transition for neighborhoods and guidelines for the implementation of multi-generation energy systems as well as to address public energy policies.

The study aims at providing comprehensive insights into the influence of the climatic stress on building heating demand. The examined case studies are two residential buildings, representative of the Italian existing and newly-built stocks, respectively. Building energy performance is simulated by comparing a standard normative approach with a tailored accurate one using EnergyPlus. The comparison is performed for several locations (i.e., 63) to consider all typical Italian climates. A global sensitivity analysis is performed to identify the most influential climatic parameters and to investigate the correlation between heating demand and HDD (heating degree days). The findings show that a base temperature of 18 °C in HDD assessment provides higher determination coefficient compared to 20 °C, and that HDD should consider also solar radiation and/or latitude to achieve a better correlation. Finally, climatic stress curves are provided to assess thermal energy demand and running cost for heating operation as a function of HDD for both the existing and the newly-built building.

An existing industrial building ubicated in South Italy is investigated by applying a tailored approach to optimize energy retrofit. The baseline provides high energy consumption, which needs to be tackled to promote the transition towards more sustainable buildings. Accordingly, after a detailed energy audit, the building is modeled and simulated under EnergyPlus environment using DesignBuilder® to characterize geometry and HVAC (heating, ventilating and air conditioning) systems. The model is calibrated against metered data as concerns the trends of indoor temperatures. Different retrofit measures are investigated, i.e., replacement of windows, implementation of solar screens, use of heat recovery, optimization of HVAC operation and installation of photovoltaics of different sizes. Thus, a large domain of solutions is explored by conducting an exhaustive research through the coupling between EnergyPlus and MATLAB®. The research provides the Pareto optimization of building retrofit minimizing primary energy consumption and global cost for two different scenarios as regards the access to public incentives. The utopia point criterion is used to pick a solution from the Pareto front. Such solution can yield energy and global cost savings up to 81% and 45%, respectively, ensuring the same comfort level compared to the baseline. The primary energy consumption of the whole facility can be reduced up to 40.1 kWhp/m2a. The outcomes can give precious guidelines to refurbish industrial and office buildings in Mediterranean areas with a view to energy-efficiency and cost-effectiveness.

A comprehensive multi-objective optimization framework is proposed to address the energy retrofit of typical villas on Mediterranean coastlines. Primary energy consumption and global cost are minimized using a Pareto approach. Two different construction technologies (i.e., a lightweight house in reinforced concrete and a massive tuff-made villa), in two different climates (i.e., Greek and Italian coasts), are investigated to provide robust optimal retrofit strategies according to two different criteria, i.e., the achievement of the nearly zero energy standard and the cost-optimality, respectively. The optimal energy retrofit strategies are achieved by coupling transient energy simulations and a genetic algorithm. They address all main factors affecting energy performance, i.e., building envelope (thermal insulation, reflectance of coatings, windows and solar shading), active energy systems (space conditioning devices) and renewable energy sources (solar photovoltaics). The investigation findings can provide useful generic guidelines for the retrofit of houses on the Mediterranean coastlines with a view to energy-efficiency and cost-effectiveness. The implementation of the suggested retrofit strategies to the case studies can yield substantial primary energy savings, up to 125 kWh/m2a, and global cost savings, up to 140 €/m2. The most energy-efficient and cost-effective retrofit solutions are the improvement of energy systems’ efficiency, the installation of full-roof photovoltaic systems, the replacement of windows and the roof thermal insulation.

Many strategies are under investigation to reduce the environmental impact of the building stock. Among them, the implementation of optimal operation strategies of the HVAC (heating, ventilating and air conditioning) systems plays a fundamental role because it can produce substantial energy-economic savings and increment of thermal comfort. In this vein, a weather-data-based control framework is here proposed to provide optimal heating operation strategies easily applicable to a huge number of buildings. It works by coupling EnergyPlus and MATLAB® to run a multi-objective genetic algorithm and proposes a novel approach for multi-criteria decision-making. This latter addresses characteristic days (i.e., average cold days, average days and average hot days) of weather data files with the aim to provide monthly heating strategies that ensure the best compromise between running cost and thermal discomfort. As case studies, the proposed framework is applied to a residential building, representative of the Italian building stock from 1961 to 1975. In order to cover most of the Italian territory, four different cities are considered: Palermo (climatic zone B), Naples (C), Florence (D) and Milan (E). The achieved cost reduction is included between 6% (Milan) and 34% (Palermo), while the thermal comfort is not penalized. Finally, the framework provides practical indications ready to be easily applied to the Italian residential stock to achieve a significant and widespread improvement of energy performance. © 2019 Elsevier Ltd