Search Results (41)

The next decade will see severe environmental and technological risks, pushing our adaptive capacity to its limits. The EPBD Case Green directive, to counter this phenomenon, emphasizes accelerating building renovations, reducing GHG emissions and energy consumption, and promoting renewable energy installations. Additionally, it calls for deadlines to phase out fossil fuels and mandates solar system installations. This research provides a comprehensive perspective on the opportunities for and challenges of incorporating renewable energy into the built environment. It focuses on the 2961 residential buildings on Procida, a small island located south of Italy, to efficiently utilize energy resources and lay the groundwork for sustainability. Beginning with an analysis of the territorial, urban, historical–conservation, structural, and geological context, in addition to environmental assessments, the research develops a classification and archetypalization system using in-house software. This system aggregates data on the island’s residential buildings, analyzes their current state, and formulates various intervention scenarios. These scenarios demonstrate how integrating technological–environmental design interventions, such as upgrading the building envelope and enhancing bioclimatic behavior, with energy retrofitting measures, such as replacing mechanical systems and installing solar panels, can improve the overall performance of the existing building stock and achieve energy self-sufficiency. Full article

This study introduces an innovative methodology for designing sustainable urban energy districts using Geographic Information Systems (GIS). The scope is to identify specific parts of the urban fabric, suitable for becoming energy districts that can meet the energy needs of dwellings and activities and produce an energy surplus for the city. The method uses building archetypes to characterize the districts and perform simulations through an algorithm based on correction coefficients considering variables such as total building height, exposure, year of construction, and building typology. By leveraging GIS, this approach supports the creation of urban energy maps, which help identify and address potential energy-related issues in various urban contexts. Additionally, the research explores different scenarios for developing energy communities within the district, aiming to optimize energy use and distribution. A case study in Naples, Southern Italy, demonstrates that installing photovoltaic panels on the roofs of buildings can allow a complete electrical supply to the building stock. The final goal is to provide a robust tool that enhances confidence in urban energy planning decisions, contributing to more sustainable and efficient energy management at the district level. This approach may support the urban and territorial governance towards sustainable solutions by developing strategies for the creation of energy communities and optimizing the potential of specific sites. Full article

A conceptual study was performed on intelligent driving acceleration strategies for vehicles equipped with internal combustion engines. Two archetypal acceleration scenarios of highway driving and urban driving were prescribed. Three trajectories were considered for each scenario. They involved (a) nearly constant acceleration, (b) fast acceleration first and slow acceleration later, and (c) slow acceleration first and fast acceleration later. The selected vehicle was a generic European small–medium passenger car. Engine inlet pressure and ignition time were optimized along each trajectory to minimize fuel consumption, CO, and CO₂ emissions, and travel time. The optimization process involved a methodological approach based on the higher-order singular value decomposition of the tensor form of the engine model. The optimized trajectories were analyzed and compared among themselves. Conceptual acceleration design guidelines for intelligent driving were provided that could be of interest when integrating vehicle/engine performance into the surrounding traffic flow. Full article

Megacities boost peri-urban socioeconomic development but fulfill their high natural resource demands by overexploitation, yielding irreversible environmental damage in surroundings that turn into sacrifice zones. This study reports the effects on the Cuautitlán-Pachuca Valley, the Mexico City main expansion zone at the northeast of the metropolitan area on the Central Mexico plateau, the trend scenarios from 2020 to 2050, and the actions to mitigate the growing water demand that will worsen its aquifer overexploitation. We designed a conceptual archetype to apply the Water Evaluation and Planning System (W.E.A.P.) mathematical model calibrated with 2013–2014 data to calculate groundwater volume demand in future scenarios. The demand output for the international airport and agriculture was less than 5%. The local climate change effect up to 2050 will slightly reduce the infiltration. The most crucial water demand increase (195% in 2050) is due to the population and industrial growth of the Mexico City northern municipalities (89% of the total groundwater extraction volume), and the aquifer will have a notable −2192.3 hm³ accumulated deficit in 2050, while urban sprawl will decrease water infiltration by 2.3%. Mitigation scenarios such as rainwater harvesting may reduce the urban water supply only by 9%, and a leak cutback will do so by 24%, which is still insufficient to achieve sustainable water management in the future. These outcomes emphasize the need to consider other actions, such as importing water from near aquifers and treating wastewater reuse to meet the future water demand. Full article

A substantial number of dwellings in the UK have poor building fabric, leading to higher carbon emissions, fuel expenses, and the risk of cold homes. To tackle these challenges, domestic energy efficiency policies are being implemented. One effective approach is the use of energy models, which enable sensitivity analysis to provide valuable insights for policymakers. This study employed dynamic thermal simulation models for 32 housing archetypes representative of solid-walled homes in the UK to calculate the heat loss and the sensitivity coefficient per building fabric feature, after which a metric Heat Loss Sensitivity (HLS) index was established to guide the selection of retrofit features for each archetype. The building fabric features’ inputs were then adjusted to establish both lower and upper bounds, simulating low and high performance levels, to predict the how space heating energy demand varies. The analysis was extended by replicating the process with various scenarios considering climates, window-to-wall ratios, and overshadowing. The findings highlight the external wall as the primary consideration in retrofitting due to its high HLS index, even at high window-to-wall ratios. It was also established that dwelling type is important in retrofit decision-making, with floor and loft retrofits having a high HLS index in bungalows. Furthermore, the analysis underlines the necessity for Standard Assessment Procedure assessors to evaluate loft U-value and air permeability rates prior to implementing retrofit measures, given the significance of these factors in the lower and upper bounds analysis. Researchers globally can replicate the HLS index approach, facilitating the implementation of housing retrofit policies worldwide. Full article

Thermal processes represent a significant fraction of industrial energy consumptions, and they rely mainly on fossil fuels. Thanks to technological innovation, highly efficient devices such as high-temperature heat pumps are becoming a promising solution for the electrification of industrial heat. These technologies allow for recovering waste heat sources and upgrading them at temperatures up to 200 °C. Moreover, the coupling of these devices with thermal storage units can unlock the flexibility potential deriving from the industrial sector electrification by means of Demand-Side Management strategies. The aim of this paper is to quantify the impact on the energy system due to the integration of industrial high-temperature heat pumps and thermal storage units by means of a detailed demand–supply model. To do that, the industrial heat demand is investigated through a set of thermal process archetypes. High-temperature heat pumps and thermal storage units for industrial use are included in the open-source unit commitment and optimal dispatch model Dispa-SET used for the representation of the energy system. The case study analyzed is Belgium, and the analysis is performed for different renewable penetration scenarios in 2040 and 2050. The results demonstrate the importance of a proper sizing of the heat pump and thermal storage capacity. Furthermore, it is obtained that the electrification of the thermal demand of industrial processes improves the environmental impact (84% reduction in CO₂ emissions), but the positive effect of the energy flexibility provided by the heat pumps is appreciated only in the presence of a very high penetration of renewable energy sources. Full article

Future weather scenarios significantly affect indoor thermal comfort, influencing people’s well-being and productivity at work. Thus, future weather scenarios should be considered in the design phase to improve a building’s climate change resilience for new constructions as well as renovations in building stock. As thermal comfort is highly influenced by internal and external thermal loads resulting from weather conditions and building usage, only a dynamic building performance simulation (BPS) can predict the boundary conditions for a thermal comfort analysis during the design stage. As the model setup for a BPS requires detailed information about building geometry, materials, and usage, recent research activities have tried to derive the required simulation models from the open BIM (Building Information Modeling) Standard IFC (Industry Foundation Classes). However, even if IFC data are available, they are often faulty or incomplete. We propose a template-based enrichment of the BPS models that assists with imputing missing data based on archetypal usage of thermal zones. These templates are available for standardized enrichment of BPS models but do not include the required parameters for thermal comfort analysis. This study presents an approach for IFC-based thermal comfort analysis and a set of zone-usage-based templates to enrich thermal comfort input parameters. Full article

Few papers have dealt with the process of servitization at the firm level. There has been a particular lack of research in manufacturing. Business model innovation through convergence between products and services is an indispensable aspect of a firm’s sustainable strategy. The current paper analyzes servitization as a process innovation by performing a single case study of a manufacturing firm. Extending product value, or servitization, is an archetype of business model innovation. To investigate and identify the real problem through so-called service development in a product-service system, we utilized a single case of a headrest in a car seat. Based on study findings, this paper proposes that a product-service system could be classified into three steps: (1) understanding and discovering the service; (2) discovering service conceptualization and developing a scenario phase; and (3) service prototyping and marketization using an infusion of technological utilities. We argue that the process of servitization can be regarded as one of the processes of service design, which is a process of value creation that comes from the synchronization of customer empathy. Full article

This paper summarizes a study focused on evaluating the post-fire performance of steel Intermediate Moment Frames (IMFs) following earthquakes. To this aim, archetypes comprising 3-bay IMFs with three different heights were seismically designed, and their two-dimensional finite element models were created in OpenSees software. The post-fire mechanical properties of steel were inserted into the models based on 64 different fire scenarios. The effects of different cooling methods are scrutinized at system level. To develop seismic fragility curves, Incremental Dynamic Analysis (IDA) was performed using 50 suites of far-field and near-field records, according to FEMA-P695. Then, the Collapse Margin Ratio (CMR) of each model was calculated based on the data from the fragility analysis. The results show that the seismic resistance of structures that experienced fire declines to some extent. In addition, the lowest safety level was observed when the structures were subjected to pulse-like near-field records. Full article

Electronic medical records (EMRs) help in identifying disease archetypes and progression. A very important part of EMRs is the presence of time domain data because these help with identifying trends and monitoring changes through time. Most time-series data come from wearable devices monitoring real-time health trends. This review focuses on the time-series data needed to construct complete EMRs by identifying paradigms that fall within the scope of the application of artificial intelligence (AI) based on the principles of translational medicine. (1) Background: The question addressed in this study is: What are the taxonomies present in the field of the application of machine learning on EMRs? (2) Methods: Scopus, Web of Science, and PubMed were searched for relevant records. The records were then filtered based on a PRISMA review process. The taxonomies were then identified after reviewing the selected documents; (3) Results: A total of five main topics were identified, and the subheadings are discussed in this review; (4) Conclusions: Each aspect of the medical data pipeline needs constant collaboration and update for the proposed solutions to be useful and adaptable in real-world scenarios. Full article

Nature-based solutions (NBS) are becoming popular in urban planning and policy making as cost-effective solutions capable of delivering multiple ecosystem services and addressing several societal challenges. So far, however, the cost-effectiveness of urban NBS projects has not been consistently quantified by built environment professionals, who lack user-friendly tools to account for the environmental costs and benefits of NBS. This paper presents a prototype online decision support tool (NBenefit$^®) that calculates the negative and positive environmental impacts, externalities, and financial values of planned urban forests over their entire life cycle. NBenefit$ relies on a modelling framework that combines system dynamics, urban ecology, and life cycle thinking approaches, and it is presented as a visual web-based interface. An online map and a grid of cells is used to map the site of intervention, to delineate the size of the urban forest, and to define variations in abiotic, biotic, and management attributes in each site. Outputs are provided by year, for the entire site and NBS life cycle. The potential value of NBenefit$ as a supporting tool was exemplified with the calculation of 48 urban forest archetypes, a few of which were used to set scenarios for a hypothetical urban forest in Madrid (Spain). The results showcase the impact that decisions taken during the planning, design, or management of an NBS project may have on its long-term performance. Future works will expand the scope of NBenefit$, including other types of urban NBS. Full article

Most land consolidation projects envisage reducing fragmentation and aim at increasing productivity, land use efficiency, and competitiveness of rural areas. However, recent insights suggest that social aspects are crucial as well. Hence, a critical assessment of the conditions under which land consolidation can be socially beneficial is necessary. This article aims to identify values and qualitative indicators to measure social preferences and to assess whether one can optimize decision support tools for land consolidation projects with such indicators. Based on an exploratory and concept-centric qualitative literature review, we propose game applications from experimental economics to measure empirical indicators of social capital. The games help to disclose conflicting social preferences and enable a more accurate response to public policy programs/interventions. This is achieved by assessing commonly shared norms of trust, reciprocity, and cooperation within and across social groups in a targeted area. We posit, however, the disparity among bonding, bridging, and linking dimensions of a social capital could have a differential effect on land consolidation instruments. This experimental method applied in Kakheti, Georgia reveals that 1. the farmer communities have varying combinations of bonding, bridging, and linking social capital; 2. the local farmer societies are the archetype of the collaborative model and sharing economy; 3. only a few municipalities show the highest potential for sustainably managing land consolidation projects. Hence, applying economic games that explore social scenarios helps to derive more favourable solutions for land consolidation. Full article

A sustainable and pleasant environment is deemed to offer various positive externalities such as scenic, visual and behavioral archetypes and patterns exhibiting in various forms. Such a scenario can significantly relieve households from many psychological and personal complications such as depression. Depression has aroused great concerns in recent years due to its personal and social burdens and unforeseeable damage. Many studies have explored the effects of air pollution caused by traditional fuel consumption on depression. However, limited evidence is available on how household non-traditional fuel choices affect depression. Based on a nationally representative dataset collected from China Family Panel Studies (CFPS) in 2012, this paper employs an endogenous switching regression (ESR) model and an endogenous switching probit (ESP) model to address the endogenous issue and to estimate the treatment effects of non-traditional fuel choices on depression in rural China. The empirical results show that non-traditional fuel users have significantly lower Epidemiologic Studies Depression Scale (CES-D) scores, indicating non-traditional fuel users face a lower risk of depression. Compared to solid fuels, employing non-traditional fuels will lead to a 3.659 reduction in depression score or decrease the probability of depression by 8.2%. In addition, the results of the mechanism analysis show that household non-traditional fuel choices affect depression by reducing the probability of physical discomfort and chronic disease. This study provides new insight into understanding the impact of air pollution in the house on depression and how to avoid the risk of depression in rural China effectively. Full article

Urban building energy modeling (UBEM) is a practical approach in large-scale building energy modeling for stakeholders in the energy industry to predict energy use in the building sector under different design and retrofit scenarios. UBEM is a relatively new large-scale building energy modeling (BEM) approach which raises different challenges and requires more in-depth study to facilitate its application. This paper performs a systematic literature review on physics-based modeling techniques, focusing on assessing energy conservation measures. Different UBEM case studies are examined based on the number and type of buildings, building systems, occupancy schedule modeling, archetype development, weather data type, and model calibration methods. Outcomes show that the existing tools and techniques can successfully simulate and assess different energy conservation measures for a large number of buildings. It is also concluded that standard UBEM data acquisition and model development, high-resolution energy use data for calibration, and open-access data, especially in heating and cooling systems and occupancy schedules, are among the biggest challenges in UBEM adoption. UBEM research studies focused on developing auto-calibration routines, adding feedback loops for real-time updates, future climate data, and sensitivity analysis on the most impactful modeling inputs should be prioritized for future research. Full article

According to the 2021 Global Status Report for Buildings and Construction published by the United Nations Environment Programme, global carbon emissions from the building sector in 2019 were nearly 14 gigatons (Gt), representing 38% of total global carbon emissions, including 10% from building construction. In the United States, the largest knowledge gap regarding embodied carbon in buildings exists at the whole-building level. The first step in creating informative policy to reduce embodied carbon emissions is to map the existing building stock emissions and changes over time to understand the primary contributing building types and hot spots (states), and then to compare and analyze mitigation scenarios. To fill this knowledge gap, this study first developed a bottom-up model to assess the embodied carbon of the US residential building stock by using 64 archetypes to represent the building stock. Then, the embodied carbon characteristics of the current building stock were analyzed, revealing that the primary contributor was single-family detached (SD) houses. The results indicated that the exterior wall was a major contributor, and that small multifamily housing was the most embodied carbon-intense building type. Two scenarios, the baseline scenario and progressive scenario, were formed to evaluate the effectiveness of six mitigation strategies. The progressive scenario with all mitigation strategies (M1–M6) applied produced a total reduction of 33.13 Gt CO_2eq (42%) in the cumulative residential building stock related to carbon emissions during 2022–2050, and a total reduction of 88.34 Gt CO_2eq (80%) during 2022–2100. The results show that with an embodied carbon emissions reduction in the progressive scenario (42% by 2100), the total embodied carbon emissions comply with the carbon budget of a 2 °C pathway, but will exceed the budget for a 1.5 °C pathway. Full article