Search Results (296)

Retrofitting existing residential buildings is a critical strategy for achieving urban decarbonization while addressing public health disparities, particularly in communities disproportionately affected by environmental and socioeconomic stressors. This study presents a scalable urban building energy modeling framework that integrates physics-based simulations with machine learning to evaluate and prioritize health-driven retrofit strategies across residential building stocks. Synthetic datasets were generated through parametric simulations of representative building archetypes and retrofit scenarios, capturing variations in envelope performance, HVAC systems, infiltration rates, and ventilation strategies. Machine learning models were trained as surrogate predictors of building energy performance, enabling the rapid evaluation of retrofit impacts. A range of algorithms—including decision trees, random decision forests, gradient-boosting machines, support vector machines, k-nearest neighbors, and artificial neural networks—were evaluated. An artificial neural network implemented as a multilayer perceptron was selected for further analysis due to its strong predictive performance (R² = 0.94) and ability to capture complex nonlinear relationships among retrofit variables. The final model used the Port optimization algorithm for stable convergence and improved generalization. The framework is applied to Seattle’s Duwamish Valley, a community experiencing disproportionate environmental and health burdens, and is generalizable and transferable to other cities with comparable residential building stocks across a range of climatic and environmental contexts. The results highlight retrofit priorities—particularly infiltration reduction, HVAC upgrades, and improved envelope performance—that deliver co-benefits for energy efficiency, indoor environmental quality, and occupant health. The results demonstrate that machine learning-enhanced physics-based UBEM can significantly accelerate retrofit evaluation while preserving the interpretability of simulation-based approaches. The proposed framework provides a scalable approach for identifying health-informed retrofit pathways that support equitable urban decarbonization. Full article

Long-term decarbonization of urban residential buildings in southern China depends on the joint evolution of building stock, end-use efficiency, and electricity carbon intensity. This study develops a dynamic stock-energy-carbon framework for urban residential buildings in China’s hot-summer warm-winter region from 2010 to 2060, using Guangdong, Guangxi, Fujian, and Hainan as case provinces. The model links demographic and housing-space change with stock survival, retrofit of the base-year stock, cohort-specific performance levels for post-2022 new construction, and time-varying provincial grid emission factors. EnergyPlus simulations of seven high-rise residential archetypes show that nearly zero-energy performance reduces province-level EUI by 19.2–26.5% relative to the baseline, with cooling-load reductions forming the dominant part of the improvement in the warmer provinces. Across coupled demand-side scenarios, stricter new-build performance standards reduce 2026–2060 cumulative operational energy by 5.3–10.1% relative to the conservative demand-side setting, while increasing retrofit intensity provides a smaller but consistent additional reduction. Carbon outcomes are more sensitive to electricity-sector assumptions: under the main demand-side setting, moving from the conservative to the accelerated grid pathway advances the operational-carbon peak by 8–15 years across the four provinces and lowers 2060 residual emissions by about 71%. A comparison with available observed provincial household-electricity statistics is added as a plausibility check; it confirms the relevant order of magnitude but also indicates that absolute demand estimates should be interpreted cautiously because of boundary and EUI-representation differences. These results suggest that demand-side efficiency policies must be coordinated with rapid provincial power-sector decarbonization if the residential sector in Hot-Summer Warm-Winter Region is to reach earlier carbon peaks and lower residual operational emissions. Full article

Post-disaster reconstruction programmes create an irreversible window for embedding or foreclosing residential energy efficiency at scale. This study examines the structural determinants of per capita residential electricity consumption (K_MES) across all 81 provinces of Türkiye over 2013–2022 using a balanced province-year panel. We develop two complementary panel models, both estimated by two-way fixed effects (province + year) with cluster-robust standard errors, and supported by GLS-AR(1) and random-effects GLS robustness checks. Note that K_MES measures the electricity component of residential energy use only; we, therefore, also estimate the building-stock model with a constructed total-energy dependent variable that combines residential electricity (H_MES) and natural-gas consumption (X_DG) in kWh-equivalent units. Model 1 isolates the macroeconomic transmission channel through which exchange-rate volatility shapes residential electricity demand. Because the USD/TRY rate has no cross-sectional variation, its identifying power in two-way fixed effects comes from its interaction with province-level natural-gas-heating exposure (sh_gas × EV_DA). The interaction is robustly negative across all full-sample specifications (β ≈ −0.022, p < 0.01), indicating that provinces with greater gas-heating penetration are buffered against currency-depreciation pass-through into electricity demand. Provincial GDP carries the dominant direct macro coefficient (β ≈ 0.27–0.29, p < 0.01), establishing income elasticity rather than the exchange rate as the headline aggregate driver. Model 2 decomposes the building stock by structural system, filler material, heating system, and heating fuel. The dominant predictors are the share of electric heating (β ≈ 1.16–1.27, p < 0.01) and the share of AC-only heating (β ≈ −1.0 to −1.13, p < 0.05), with a total-energy specification reaching R² = 0.92. In the comparative subsample of the eleven Kahramanmaraş-affected provinces, masonry construction emerges as the dominant pre-disaster predictor of per capita electricity consumption (β = 14.04, p < 0.05), revealing structurally distinct stock characteristics that pre-date the February 2023 earthquake. Two re-framings are required. First, since the panel covers 2013–2022, the disaster-province estimates capture pre-disaster structural heterogeneity rather than post-disaster market rupture. Second, the macroeconomic mechanism that prior work attributed to the exchange-rate level is more accurately understood as a fuel-mix-mediated exposure channel. The combined evidence implies that mandatory building-code enforcement and natural-gas grid extension are complementary policy levers in the 488,000-unit Turkish Housing Development Administration reconstruction programme: gas grid expansion reduces the macroeconomic vulnerability of residential energy demand, while masonry-replacement construction standards address the largest pre-disaster structural determinant of energy intensity in the affected region. Full article

The evaluation of intervention strategies for the existing building stock, within the context of energy transition and increasing attention being given to sustainability, requires approaches capable of systematically integrating economic and environmental dimensions over the entire building life cycle. From this perspective, the present study develops and applies an integrated Life Cycle Costing (LCC) and Life Cycle Assessment (LCA) model aimed at comparing two alternative intervention strategies for traditional residential buildings: conservative retrofit of the existing structure and demolition with reconstruction according to Nearly Zero Energy Building (NZEB) criteria. The methodological framework, compliant with ISO 15686-5 and based on a simplified LCA-oriented approach inspired by EN 15978 principles, is applied to a representative case study of Swedish vernacular wooden architecture (röd stuga) located in the municipality of Falun. The assessments are carried out over 50- and 100-year time horizons, adopting Net Present Value (NPV) as the primary economic indicator and Global Warming Potential over 100 years (GWP100) and Cumulative Energy Demand (CED) as environmental indicators. The results show that the NZEB scenario, despite higher initial investment costs, achieves a significant reduction in life-cycle environmental impacts, with a decrease of approximately 20–25% in terms of GWP100 and about 45–50% in terms of CED compared to the retrofit scenario. The analysis also highlights a differentiated behavior of environmental indicators—while operational energy use remains dominant in cumulative energy demand, embodied impacts become increasingly significant in the GWP balance, particularly in high-performance scenarios. From an economic perspective, conservative retrofit results in lower global costs over the considered time horizons, although the economic gap tends to narrow in the long term. The integrated LCC–environmental assessment approach highlights the economic–environmental trade-offs and provides a replicable decision-support framework for sustainable regeneration policies targeting the existing residential building stock. Full article

Global urbanization is shifting from incremental expansion to stock optimization, and old residential communities have become important spatial units for low-carbon transition. However, in existing built environments, traditional process-based inventory methods face practical constraints, including missing original drawings, complex site conditions, and severe vegetation obstruction. As a result, systematic accounting of buildings, landscapes, and natural carbon sinks remains difficult. This study integrates life cycle assessment (LCA), BIM reverse modeling, 3D point clouds, DesignBuilder simulation, inventory-based accounting, and i-Tree Eco to construct a life cycle carbon emission accounting framework for old residential communities. The framework links current-condition data reconstruction, quantity take-off, operational energy simulation, landscape inventory accounting, and vegetation carbon sequestration assessment. It is applied to Nanyuan Xincun in Hefei to quantify the community-scale carbon source–sink structure. The results show that Nanyuan Xincun presents a clear operation-led emission pattern, with the operation and maintenance phase accounting for 82.52% of total positive emissions. Within architectural engineering, operation and maintenance accounts for 82.91%, while material production accounts for 13.28%. Landscape engineering shows a more mixed structure, with operation and maintenance accounting for 52.95% and material production accounting for 36.49%. Vegetation carbon sequestration analysis shows that mature trees and shrubs are the main ecological carbon assets. Annual sequestration reaches 16.95 t-CO₂e/a, and trees and shrubs contribute 92.85% of total vegetation carbon storage. Under current vegetation conditions, annual sequestration is equivalent to 32.99% of annual landscape operation emissions, indicating considerable ecological compensation potential. Based on these findings, this study proposes four optimization pathways: operational energy reduction, low-carbon material substitution, construction and demolition waste recycling, and mature tree protection. These pathways provide data support for refined carbon management and low-carbon renewal in existing communities. Full article

Programs aimed at reducing the CO₂e footprint associated with the residential building stock should be informed by several key elements, including the expected evolution of the occupied housing stock, projected population dynamics driven by socio-economic and cultural factors, available implementation budgets, and the specific costs of intervention measures. However, in regions characterized by high seismic hazard, the occurrence of a major earthquake may substantially alter the projected outcomes of emission-reduction programs, as seismically vulnerable buildings may experience severe structural damage. This paper presents the results obtained by applying an integrated methodology for assessing the CO₂e footprint associated with residential buildings. The methodology accounts for emissions related to building operation (space heating), energy-renovation interventions, and seismic retrofitting works. While the proposed approach is applicable to other seismically exposed regions, the results presented herein refer specifically to the residential building stock in Romania and its local seismic conditions. The methodology integrates information on the existing building stock, the projected evolution of population and the built environment, energy consumption associated with building operation, changes in the energy fuel mix, construction practices across different historical periods with respect to energy efficiency and seismic protection, and the CO₂e footprint associated with energy renovation and seismic retrofitting. In addition, the analysis explicitly considers the potentially negative effects of a major earthquake, particularly the disruption of greenhouse-gas emission-reduction programs. The assessment is conducted at the building stock level and is based on combining building stock evolution with average, representative CO₂e intensity values for heating, energy renovation, and seismic retrofitting. The results demonstrate that when the sole objective is to reduce the CO₂e footprint associated with space heating, renovation of the energy fuel mix represents the most effective measure. At the same time, the analysis shows that the CO₂e footprint generated by construction works for energy renovation and/or seismic retrofitting represents only a small fraction of the emissions associated with building operation. The occurrence of a major earthquake is likely to jeopardize overall environmental objectives by increasing emissions related to building operation, energy renovation, reactive seismic retrofitting, and replacement of severely damaged buildings. Conversely, systematic preventive seismic retrofitting of the building stock does not lead to an increase in cumulative CO₂e emissions over the program implementation period. Full article

The construction sector is a major consumer of raw materials and a significant source of greenhouse gas emissions, necessitating data-driven approaches to support circular economy implementation and sustainable project management. This study develops an integrated framework combining machine learning-based material stock prediction, carbon footprint assessment, and Environmental, Social, and Governance (ESG) performance evaluation for construction projects. A dataset of 128 residential buildings was compiled from official use-permit documentation. After dimensionality reduction using variance filtering and Spearman correlation analysis, 25 regression algorithms were evaluated to estimate quantities of concrete, reinforcement, and brick products. The K-Nearest Neighbor (KNN) Regressor achieved the best predictive performance, with mean absolute percentage errors of 10.64% for concrete, 10.23% for reinforcement, and 16.05% for brick products. Predicted material quantities were used to calculate CO₂ emissions across materialization, demolition, and disposal phases under linear and circular scenarios. The results indicate that circular economy implementation significantly reduces total emissions, particularly for concrete, with reductions of up to 97% under idealized full-substitution conditions, representing an upper-bound estimate. ESG assessment using the Delphi method identified environmental indicators as the most significant sustainability dimension. The proposed framework enables early-stage emission estimation and supports informed decision-making toward low-carbon and resource-efficient construction practices. Full article

This research examines the complex relationship between climate change, rapid population growth, and building stock expansion in Egypt, as well as their combined impact on energy demand and urban sustainability, to address the rapidly increasing electricity demand. This study uses a mixed-methods approach, including quantitative analysis to examine climatic data (1970–2100), demographic trends, and building energy consumption patterns, quantifying their synergistic effects; a qualitative evaluation of policy frameworks and urban planning strategies; and building energy performance simulation using Design Builder to utilize climate-responsive design techniques for energy reduction. Finally, this study proposes energy-efficient design guidance. The research findings reveal that Egypt’s unique hot–arid climate, projected to warm by 4 °C by 2100, combined with a population set to reach 160 million by 2050, has driven the near-doubling of building stock since 1986, with residential buildings accounting for 70–83% of structures and 60% of national electricity use. The research results highlight the importance of implementing climate-responsive design strategies (optimized building-envelope thermal insulation and energy-efficient HVAC systems) in Egypt’s built environment to reduce electricity consumption by up to 40%, thereby aligning urban growth with sustainability objectives. These insights are scalable to other arid, rapidly urbanizing regions globally. Full article

Urban areas in subtropical regions are increasingly exposed to heat stress as climate change intensifies extreme heat events. In high-density cities, urban renewal is widely implemented to upgrade aging building stock, yet its potential role as a passive heat adaptation strategy remains insufficiently understood, particularly for projects below environmental impact assessment thresholds. This study examines how urban renewal influences neighborhood-scale microclimates through a comparative analysis of six residential renewal cases using computational fluid dynamics (CFD) simulations. Pre- and post-renewal scenarios are evaluated to assess changes in wind environment and thermal conditions, with a particular focus on the spatial extent and distance–decay characteristics of renewal-induced effects. The results reveal a consistent distance–decay pattern of microclimate responses across all cases. The influence of urban renewal is strongest within 0–50 m, remains detectable up to approximately 100 m, and diminishes substantially beyond 100–150 m, indicating a clear neighborhood-scale impact radius. Ventilation performance improves systematically following renewal, while thermal responses are more heterogeneous. Localized cooling of up to 1.5 °C is observed in selected cases, whereas others exhibit negligible temperature change despite enhanced airflow. These findings demonstrate that improved ventilation alone does not guarantee thermal mitigation. Instead, thermal outcomes depend on the interaction between airflow, solar exposure, and surface thermal properties. Urban renewal can therefore function as a form of passive heat adaptation when morphological changes are coordinated with shading and surface design strategies. By quantifying the spatial limits of renewal-induced microclimate effects, this study provides empirical evidence for integrating microclimate considerations into neighborhood-scale planning. The identified influence radius offers a practical reference for climate-responsive urban renewal, particularly in high-density subtropical cities where incremental redevelopment plays a dominant role. Full article

The decarbonization of existing buildings remains a major challenge, particularly in contexts characterized by high energy demand and heating systems based on fossil fuels. While electrification is widely recognized as a key pathway, its direct application is often limited by building and operating conditions. This study investigates the potential of hybrid heating systems as transitional solutions through a large-scale numerical parametric simulation analysis based on representative models of the Italian residential building stock. The analysis explores the interaction between climatic conditions, system operation, and energy performance under standardized assumptions. The results reveal that hybrid systems achieve significant reductions in non-renewable primary energy (up to 39–44%) and CO₂ emissions (approximately 50–58%), primarily through the substitution of natural gas with electricity. Conversely, total primary energy may increase (approximately 2–26%) due to the contribution of renewable energy associated with heat pump operation. Operating cost savings are observed in the 25–40% range, with slight variation depending on climatic conditions. The effectiveness is not uniform, with maximum benefits in intermediate climate zones and reduced performance under more severe conditions. Overall, hybrid systems show stable and reliable performance across heterogeneous building configurations, supporting their role as robust mid-term transition technologies toward building decarbonization. Full article

Sustainable renovation of existing residential building stocks is essential to reduce greenhouse gas emissions, improve energy performance, and support long-term climate-neutral housing strategies. However, decisions based only on operational indicators may overlook important product-stage embodied impacts, especially in highly integrated renovation solutions. This study evaluates how alternative renovation pathways for a public residential building portfolio in the Comunitat Valenciana (Spain) perform from a stock-level sustainability perspective, comparing five INFINITE industrialised retrofit kits (Kit 1–Kit 5) with five paired conventional renovation scenarios (S1–S5). A bottom-up building stock modelling workflow is applied, combining building-energy simulation to quantify operational performance and emissions (B6) with a screening life-cycle assessment of product-stage embodied carbon reported as GWP (A1–A3). To relate upfront and in-use impacts, the study computes carbon payback, cumulative emissions avoided, and a horizon-based partial life-cycle climate indicator, PLC(H), assessed for 2030, 2035, and 2050. The results show a clear sustainability trade-off: renovation packages that sharply reduce operational emissions often require higher upfront embodied carbon, shifting net climate benefits towards longer time horizons. Low-embodied options provide earlier benefits, with Kit 1 reducing PLC(H) by 15.5% by 2030, whereas deeper decarbonisation packages achieve stronger long-term outcomes, with S5 reducing PLC(H) by 70.7% by 2050. A bounded electricity-decarbonisation sensitivity further shows that these long-horizon rankings are affected by lower grid-emission factors, particularly for highly electrified pathways, although the strongest 2050 pathways remain robust across the tested cases. Overall, the findings show that sustainable stock-level renovation planning should jointly consider operational and embodied carbon, carbon payback, and milestone-based cumulative impacts in order to support balanced portfolio sequencing between broadly deployable fast-payback measures and selective deep retrofits. Full article

Improving the energy performance of existing multi-apartment residential buildings is critical for reducing energy consumption and greenhouse gas emissions in Central and Eastern Europe, where large stocks of post-war buildings with limited insulation are connected to district heating systems. This study evaluates façade insulation retrofit strategies for two representative typologies in Novi Beograd, Serbia—a high-rise tower and an elongated slab-type (‘lamella’) building—using calibrated dynamic energy models and cradle-to-use lifecycle assessment (LCA) over a 50-year service life. Models were calibrated against measured 2023–2024 heating consumption data (NMBE < 1%, CVRMSE < 15%) and normalized with Typical Meteorological Year weather for consistent scenario comparison. Retrofit scenarios applied expanded polystyrene (EPS) and cellulose insulation at 10, 12, and 15 cm thicknesses. Results show that external insulation reduces annual heating demand by approximately 19–20% compared to the uninsulated baseline (192 kWh/m²·a), with the majority of savings achieved at 10 cm and only marginal gains from additional thickness. Insulation thickness has a stronger influence on operational energy reduction than material choice, as differences between EPS and cellulose remain below 0.5%. LCA indicates 23.6–26.0% lower climate change impacts and 23.6–25.8% reduced cumulative energy demand in retrofit scenarios, with cellulose offering modest advantages due to lower embodied emissions and biogenic carbon storage. These findings support targeted envelope retrofits as an effective strategy for decarbonizing district-heated residential buildings in the region. Full article

The ongoing digitalization of building operation processes creates new opportunities to improve maintenance and renovation decision-making. Despite the increasing use of BIM, renovation decisions in residential buildings are still often based on fragmented data, heterogeneous documentation, and subjective expert assessments. This challenge is particularly relevant for large-panel housing in Central and Eastern Europe, where aging building stock requires systematic long-term modernization strategies. This paper presents a Renovation Decision Support System (RDSS) integrating a simplified BIM model, technical documentation, diagnostic data, and machine learning methods to support renovation planning. The system consists of five modules: the Building Information Model Module (BIMM), Geometric and Technical Documentation Module (GTDM), Building Condition Assessment Module (BCAM), Building Performance and Condition Prediction Module (BPCM), and Renovation Decision Optimization Module (RDOM). Data exchange is managed through a Common Data Environment (CDE). The system combines multi-criteria building condition assessment with fuzzy inference to determine renovation urgency and long-term optimization using Mixed-Integer Linear Programming (MILP). Budget constraints, activity sequences, time horizons, and user preferences are considered to generate alternative renovation scenarios. The proposed approach supports sustainable management of existing buildings, improves decision transparency, and enables data-driven renovation planning consistent with life-cycle management principles. Full article

For increasing the sustainability of existing building stock, energy renovation programs for existing buildings are being implemented worldwide with the aim of reducing the CO₂e footprint associated with building operation. In countries with high seismicity, the long-term effectiveness of energy renovation programs is called into question, since a strong earthquake can severely affect existing buildings and compromise the sustainability of the implemented works. As a result, the design of energy renovation programs in seismically active countries must explicitly account for seismic risk. Integrated intervention programs were developed, in which energy renovation measures are implemented simultaneously with seismic strengthening interventions. Romania represents a particular case due to the specificity of the intermediate-depth Vrancea seismic source, which strongly affects more than 60% of the national territory, covering over 120,000 km². Consequently, a large existing building stock is susceptible to seismic damage in the event of a major earthquake. This paper proposes the assessment of the specific CO₂e footprint of the Romanian residential building stock for the two types of interventions. The results show that preventive seismic strengthening has the lowest CO₂e footprint when compared to reactive seismic strengthening, the computed values for different scenarios ranging between 6 kg/m² and 45 kg/m² in case of preventive retrofitting and 23 kg/m² to 121 kg/m² in case of reactive retrofitting. Energy renovation leads to midrange values of 27 kg/m² to 58 kg/m². Nevertheless, all calculated values are significantly lower than the specific CO₂e footprint associated with new construction, proving the sustainability of existing building stock rehabilitation techniques. The research presented in this paper can be further extended through the implementation of scenario-based analyses concerning the improvement of the existing building stock through seismic strengthening and energy renovation, considering the occurrence of a major earthquake, in order to determine the optimal solution for the implementation of national programs in relation to the assumed objective of reducing CO₂e emissions at the building stock level. Full article

This study presents a probabilistic assessment of seismic loss and recovery for residential buildings in Bucharest, Romania, using the FEMA P-58 framework implemented in SP3. A typology set is developed to represent the building stock, accounting for structural system, construction period, and height. The analysis evaluates scenario-based losses, functional recovery times, and expected annual loss (EAL) across seismic hazard levels representative of Vrancea earthquakes. Results show that frame-based systems are highly sensitive to building height, with the highest losses and longest recovery times in older mid- and high-rise buildings. For pre-1990 construction, masonry-infilled reinforced concrete frames are more representative than bare frames and drive the vulnerability of the older building stock. Reinforced concrete shear wall systems perform better, with lower losses and faster recovery across all categories. Nonstructural damage, especially drift-sensitive components, is a contributor to both repair cost and downtime. The results are interpreted comparatively, highlighting the role of structural system, code era, and height. While absolute values depend on modeling assumptions, the study provides a consistent basis for identifying vulnerable typologies and supporting risk mitigation and resilience planning. Full article