Search Results (853)

The growing urban population has made densification a key focus of urban development. It is crucial to create an urban planning strategy that understands the environmental, social, and economic effects of densification at both the district and city levels. In Switzerland, densification is a legally binding aim to foster housing and jobs within urban boundaries. The challenge is to accommodate population growth while maintaining a high quality of life. Zurich exemplifies this situation, necessitating the accommodation of approximately 25% of the anticipated increase in both the resident population and associated workplaces, as of 2016. This study examined the effects of urban densification on urban forms and microclimates in the Altstetten–Albisrieden district. It developed five densification scenarios based on current urban initiatives and assessed their impacts. Results showed that the current Building and Zoning Plan provides sufficient capacity to accommodate growth. Strategies such as densifying parcels older than fifty years and adding floors to newer buildings were found to minimally impact existing urban forms. Using the SOLWEIG model in the Urban Multi-scale Environmental Predictor (UMEP), this study simulated mean radiant temperature (Tmrt) in the selected urban areas. The results demonstrated that densification reduced daytime average temperatures by 0.60 °C and diurnal averages by 0.23 °C, but increased average nighttime temperatures by 0.38 °C. This highlights the importance of addressing warm nights. The study concludes that well-planned densification can significantly contribute to urban liveability, emphasising the need for thoughtful building design to improve outdoor thermal comfort. Full article

This study aimed to investigate land-use and land-cover change and the associated change in the ecological stability of the model area Dobrá–Opatová (district of Trenčín, Slovakia), where increasing landscape transformation has raised concerns about declining ecological resilience. Despite the importance of sustainable land management, few studies in this region have addressed long-term landscape dynamics in relation to ecological stability. This research fills that gap by evaluating historical and recent LULC changes and their ecological consequences. Four time horizons were analysed: 1850, 1949, 2009, and 2024. Although the selected time periods are irregular, they reflect key milestones in the region’s land development, such as pre-industrial land use, post-war collectivisation, and recent land consolidation. These activities significantly altered the structure of the landscape. To assess future trends, we used the MOLUSCE plug-in in QGIS to simulate ecological stability for the future. The greatest structural landscape changes occurred between 1850 and 1949. Significant transformation in agricultural areas was observed between 1949 and 2009, when collectivisation reshaped small plots into large block structures and major water management projects were implemented. The 2009–2024 period was marked by land consolidation, mainly resulting in the construction of gravel roads. These structural changes have contributed to a continuous decrease in ecological stability, calculated using the coefficient of ecological stability derived from LULC categories. To explore future trends, we simulated ecological stability for the year 2030 and the simulation confirmed a continued decline in ecological stability, highlighting the need for sustainable land-use planning in the area. Full article

The city of Al Ain is a fast-developing area. With building typology varying from low-rise to mid-rise, sustainable design in buildings is needed. As the majority of the city’s population is Emirati Citizens, the percentage of expats is increasing. The expats tend to live in mid-rise buildings. One of the central midrise areas is AL Ain Square. This study aims to investigate how an optimized mashrabiya pattern can impact the energy and the Predicted Mean Vote (PMV) in a 3-bedroom apartment, fully oriented to the south, of an expat family. The methodology is as follows: case study selection, Weather analysis, Modeling/Validation of the base case scenario, Optimization of the mashrabiya pattern, Simulation of various scenarios, and Results. Analyzing the selected case study is the initial step of the methodology. This analysis begins with the district, building typology, and the chosen apartment. The weather analysis is relevant for using the mashrabiya (screen device) and the need to improve energy consumption and thermal comfort. The modeling of the base case shall be performed in Rhino Grasshopper. The validation is based on a one-year electricity bill provided by the owner. The optimization of mashrabiya patterns is an innovative process, where various designs are compared and then optimized to select the most efficient pattern. The solutions to the selected scenarios will then yield the results of the optimal scenario. This study is relevant to industry, academia, and local authorities as an innovative approach to retrofitting buildings. Additionally, the research presents a creative vision that suggests optimized mashrabiya patterns can significantly enhance energy savings, with the hexagonal grid configuration demonstrating the highest efficiency. This finding highlights the potential for geometry-driven shading optimization tailored to specific climatic and building conditions. Contrasting earlier mashrabiya studies that assess one static pattern, we couple a geometry-agnostic evolutionary solver with a utility-calibrated EnergyPlus model to test thousands of square, hexagonal, and triangular permutations. This workflow uncovers a previously undocumented non-linear depth perforation interaction. It validates a hexagonal screen that reduces annual cooling energy by 12.3%, establishing a replicable, grid-specific retrofit method for hot-arid apartments. Full article

Steam networks are widely used for industrial heat supply. High-temperature heat pumps (HTHPs) are an increasingly attractive low-emission solution to traditional steam generation, which could also improve the operational efficiency and energy demand flexibility of industrial processes. This work characterises 4-bar steam supply via HTHPs and aims to assess how variations in power input that result from flexible HTHP operation may affect steam flow and temperature, both with and without a downstream steam accumulator (SA). First, steady-state modelling is used for system design. Then, dynamic component models are developed and used to simulate the system response to HTHP power input variations. The performance of different SA integration layouts and sizes is evaluated. Results demonstrate that steam supply fluctuations closely follow changes in HTHP operation. A downstream SA is shown to mitigate these variations to an extent that depends on its capacity. Practical SA sizing recommendations are derived, which allow for the containment of steam supply fluctuations within acceptability. By providing a basis for evaluating the financial viability of flexible HTHP operation for steam provision, the results support clean technology’s development and uptake in industrial steam and district heating networks. Full article

Background/Objectives: This study aimed to evaluate a regional implementation project for rural emergency care (RuralRescue) and to examine how its components and outcomes may support personalized approaches in emergency medicine. While not originally designed as a personalized medicine intervention, the project combined digital, educational, and organizational innovations that enable patient-specific adaptation of care processes. Methods: Conducted in the rural district of Vorpommern-Greifswald (Mecklenburg–Western Pomerania, Germany), the intervention included (1) standardized cardiopulmonary resuscitation (CPR) training for laypersons, (2) a geolocation-based first responder app for medically trained volunteers, and (3) integration of a tele-emergency physician (TEP) system with prehospital emergency medical services (EMSs). A multi-perspective pre–post evaluation covered medical, economic, and organizational dimensions. Primary and secondary outcomes included bystander CPR rates, responder arrival times, telemedical triage decisions, diagnostic concordance, hospital transport avoidance, economic simulations, workload, and technology acceptance. Results: Over 12,600 citizens were trained in CPR and the responder app supported early intervention in hundreds of cases. TEPs remotely assisted 3611 emergency calls, including delegated medication in 17.8% and hospital transport avoidance in 24.3% of cases. Return of spontaneous circulation (ROSC) after out-of-hospital cardiac arrest (OHCA) was achieved in 35.6% of cases with early CPR. Diagnostic concordance reached 84.9%, and documentation completeness 92%. Centralized coordination of TEP units reduced implementation costs by over 90%. Psychological evaluation indicated variable digital acceptance by role and experience. Conclusions: RuralRescue demonstrates that digitally supported, context-aware, and regionally integrated emergency care models can contribute significantly to personalized emergency medicine and can be cost-effective. The project highlights how intervention intensity, responder deployment, and treatment decisions can be tailored to patient needs, professional capacity, and regional structures—even in resource-limited rural areas. Full article

Urban outdoor thermal comfort (OTC) has become an increasingly critical issue under the pressures of urbanization and climate change. Comparative analyses of urban blocks with distinct spatial morphologies are essential for identifying OTC issues and proposing targeted optimization strategies. However, existing studies predominantly rely on microclimate numerical simulations, while comparative assessments of OTC from the human thermal perception perspective remain limited. This study employs the thermal walk method, integrating microclimatic measurements with thermal perception questionnaires, to conduct on-site OTC investigations across three urban blocks with contrasting spatial morphologies—a business district (BD), a residential area (RA), and a historical neighborhood (HN)—in Beijing, a hot summer and cold winter climate city. The results reveal substantial OTC differences among the blocks. However, these differences demonstrated great seasonal and temporal variations. In summer, BD exhibited the best OTC (mTSV = 1.21), while HN performed the worst (mTSV = 1.72). In contrast, BD showed the poorest OTC in winter (mTSV = −1.57), significantly lower than HN (−1.11) and RA (−1.05). This discrepancy was caused by the unique morphology of different blocks. The sky view factor emerged as a more influential factor affecting OTC over building coverage ratio and building height, particularly in RA (r = 0.689, p < 0.01), but its impact varied by block, season, and sunlight conditions. North–South streets generally perform better OTC than East–West streets, being 0.26 units cooler in summer and 0.20 units warmer in winter on the TSV scale. The study highlights the importance of incorporating more applicable physical parameters to optimize OTC in complex urban contexts and offering theoretical support for designing climate adaptive urban spaces. Full article

The efficient management of urban parking systems has emerged as a pivotal issue in today’s smart cities, where increasing vehicle populations strain limited parking infrastructure and challenge sustainable urban mobility. Aligned with the United Nations 2030 Agenda for Sustainable Development and the strategic goals of smart city planning, this study presents a sustainability-driven, multiagent simulation-based framework to model, analyze, and optimize smart parking dynamics in congested urban settings. The system architecture integrates ground-level IoT sensors installed in parking spaces, enabling real-time occupancy detection and communication with a centralized system using low-power wide-area communication protocols (LPWAN). This study introduces an intelligent parking guidance mechanism that dynamically directs drivers to the nearest available slots based on location, historical traffic flow, and predicted availability. To manage real-time data flow, the framework incorporates message queuing telemetry transport (MQTT) protocols and edge processing units for low-latency updates. A predictive algorithm, combining spatial data, usage patterns, and time-series forecasting, supports decision-making for future slot allocation and dynamic pricing policies. Field simulations, calibrated with sensor data in a representative high-density urban district, assess system performance under peak and off-peak conditions. A comparative evaluation against traditional first-come-first-served and static parking systems highlights significant gains: average parking search time is reduced by 42%, vehicular congestion near parking zones declines by 35%, and emissions from circling vehicles drop by 27%. The system also improves user satisfaction by enabling mobile app-based reservation and payment options. These findings contribute to broader sustainability goals by supporting efficient land use, reducing environmental impacts, and enhancing urban livability—key dimensions emphasized in sustainable smart city strategies. The proposed framework offers a scalable, interdisciplinary solution for urban planners and policymakers striving to design inclusive, resilient, and environmentally responsible urban mobility systems. Full article

With the rapid urbanization and increasing development of underground spaces, foundation pit groups in complex geological environments encounter considerable challenges in deformation control. These challenges are especially prominent in cases of adjacent constructions, complex geology, and environmentally sensitive areas. Nevertheless, existing research is lacking in systematic analysis of construction sequencing and the interaction mechanisms between foundation pit groups. This results in gaps in comprehending stress redistribution and optimal excavation strategies for such configurations. To address these gaps, this study integrates physical model tests and PLAXIS 3D numerical simulations to explore the Nanjing Jiangbei New District Phase II pit groups. It concentrates on deformations in segmented and adjacent configurations under varying excavation sequences and spacing conditions. Key findings reveal that simultaneous excavation in segmented pit groups optimizes deformation control through symmetrical stress relief via bilateral unloading, reducing shared diaphragm wall displacement by 18–25% compared to sequential methods. Sequential excavations induce complex soil stress redistribution from asymmetric unloading, with deep-to-shallow sequencing minimizing exterior wall deformation (≤0.12%He). For adjacent foundation pit groups, simultaneous excavation achieves minimum displacement interference, while phased construction requires prioritizing large-section excavation first to mitigate cumulative deformations through optimized stress transfer. When the spacing-to-depth ratio (B/He) is below 1, horizontal displacements of retaining structures increase by 43% due to spacing effects. This study quantifies the effects of excavation sequences and spacing configurations on pit group deformation, establishing a theoretical framework for optimizing construction strategies and enhancing retaining structure stability. The findings are highly significant for underground engineering design and construction in complex urban geological settings, especially in high-density areas with spatial and geotechnical constraints. Full article

Extreme rainfall events driven by climate change are increasing flood risks. Addressing flood mitigation solely from either a hydraulic engineering or urban planning perspective may overlook both feasibility and effectiveness. This study focuses on Tainan City and the Tainan Science Park in Taiwan, applying the NbS framework to assess flood mitigation strategies. From an urban planning perspective, Agricultural Development Zone Type II (Agri-DZII), parks, green spaces, and Taiwan Sugar Corporation (TSC) land were selected as flood detention sites. Hydraulic modeling was used to evaluate their effectiveness under both current and climate-change-induced rainfall conditions. Simulation results show that under current rainfall conditions, flood mitigation measures reduced inundated areas with depths exceeding 2.0 m by up to 7.8% citywide and 20.8% within the Tainan Science Park Special District Plan Area. However, under climate change scenarios, the reduction effects declined significantly, with maximum reductions of only 1.6% and 17.8%, respectively. Results indicate that, even when utilizing all available detention areas, the overall flood reduction in Tainan City remains limited. However, TSC agri-land within the Tainan Science Park overlaps with high-flood-risk zones, demonstrating significant local flood mitigation potential. This study recommends integrating hydrological analysis into urban planning to prevent high-density residential and economic zones from being designated in flood-prone areas. Additionally, policymakers should consider reserving appropriate land for flood detention to enhance climate resilience. By combining urban planning and hydraulic engineering perspectives, this study highlights the flexibility of NbS in disaster management, advocating for the integration of Natural Water Detention Measures into flood adaptation strategies to improve urban water management and climate adaptability. Full article

The significant contribution of buildings to the global primary energy consumption necessitates the application of energy management methodologies at a building scale. Although dynamic simulation tools and decision-making algorithms are core components of energy management methodologies, they are often accompanied by excessive computational cost. As future controlling structures tend to become autonomized in building heating layouts, encouraging distributed heating services, the research scope calls for creating lightweight building energy system modeling as well monitoring and controlling methods. Following this notion, the proposed methodology turns a programmable controller into a smart thermostat that utilizes surrogate modeling formed by the ALAMO approach and is applied in a 4-m-by-4-m-by-2.85-m environmental chamber setup heated by a heat pump. The results indicate that the smart thermostat trained on the indoor environmental conditions of the chamber for a one-week period attained a predictive RMSE of 0.082–0.116 °C. Consequently, it preplans the heating hours and applies preheating controlling strategies in real time effectively, using only the computational power of a conventional controller, essentially managing to attain at least 97% thermal comfort on the test days. Finally, the methodology has the potential to meet the requirements of future building energy systems featured in urban-scale RES-based district heating networks. Full article

Urban morphology critically shapes environmental performance, yet few studies integrate multiple sustainability targets within a unified modeling framework for its design optimization. This study proposes a data-driven, multi-scale approach that combines parametric simulation, artificial neural network-based multi-task learning (MTL), SHAP interpretability, and NSGA-II optimization to assess and optimize urban form across 18 districts in Hong Kong. Four key sustainability targets—photovoltaic generation (PVG), accumulated urban heat island intensity (AUHII), indoor overheating degree (IOD), and carbon emission intensity (CEI)—were jointly predicted using an artificial neural network-based MTL model. The prediction results outperform single-task models, achieving R² values of 0.710 (PVG), 0.559 (AUHII), 0.819 (IOD), and 0.405 (CEI), respectively. SHAP analysis identifies building height, density, and orientation as the most important design factors, revealing trade-offs between solar access, thermal stress, and emissions. Urban form design strategies are informed by the multi-objective optimization, with the optimal solution featuring a building height of 72.11 m, building centroid distance of 109.92 m, and east-facing orientation (183°). The optimal configuration yields the highest PVG (55.26 kWh/m²), lowest CEI (359.76 kg/m²/y), and relatively acceptable AUHII (294.13 °C·y) and IOD (92.74 °C·h). This study offers a balanced path toward carbon reduction, thermal resilience, and renewable energy utilization in compact cities for either new town planning or existing district renovation. Full article

Given the widespread use of gas-fired boilers and combined heat and power (CHP) units in existing district heating (DH) systems, this study investigates the integration of medium-scale heat pumps (HPs) into such configurations. Fifteen DH system variants were analysed, differing in installed HP capacity, operational strategies, and the synchronisation of heat and electricity production with thermal demand. A dynamic simulation model incorporating real-world equipment performance was developed to assess energy efficiency, environmental impact, and economic viability under three distinct energy price scenarios. The results demonstrate that an HP sized to 17% of the total heating capacity of the DH system achieves a 54% decrease in primary energy consumption and a 68% decrease in emissions compared to the base system. Larger HP capacities enhance environmental performance and increase the share of renewable energy but also entail higher investment. An economic analysis reveals that electricity-to-gas price ratios strongly influence the cost-effectiveness of HP integration. Under favourable electricity pricing conditions, systems with HP operational priority achieve the lowest levelized cost of heating. The most economically viable configuration consists of 600 kW HP and achieves a payback period of 4.7 years. The findings highlight the potential for HPs to decarbonize DH systems while emphasising the importance of market conditions and system design in ensuring economic feasibility. Full article

Green Stormwater Infrastructure (GSI), as a nature-based solution, has gained widespread recognition for its role in mitigating urban flood risks and enhancing resilience. Equitable spatial distribution of GSI remains a pressing challenge, critical to harmonizing urban hydrological systems and maintaining ecological balance. However, the complexity of matching GSI supply with urban demand has limited comprehensive spatial assessments. This study introduces a quantitative framework to identify priority zones for GSI deployment and to evaluate supply–demand dynamics in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) using a coupled coordination simulation model. Clustering and proximity matrix analysis were applied to map spatial relationships across districts and to reveal underlying mismatches. Findings demonstrate significant spatial heterogeneity: over 90% of districts show imbalanced supply–demand coupling. Four spatial clusters were identified based on levels of GSI disparity. Economically advanced urban areas such as Guangzhou and Shenzhen showed high demand, while peripheral regions like Zhaoqing and Huizhou were characterized by oversupply and misaligned allocation. These results provide a systematic understanding of GSI distribution patterns, highlight priority intervention areas, and offer practical guidance for large-scale, equitable GSI planning. Full article

With the rapid development of science and technology, the global demand for renewable energy is increasing. In the urban context, solar energy has become one of the key ways to increase urban energy self-sufficiency and reduce carbon emissions due to its flexibility in installation and ease of expansion of applications. Therefore, based on Geographic Information System (GIS) and deep learning modeling, this paper proposes a method to efficiently assess the potential of urban rooftop solar photovoltaic (PV), which is analyzed in a typical area of Lanzhou New District, which is divided into 8774 units with an area of 87.74 km². The results show that the method has a high accuracy for the identification of the roof area, with a maximum maxF_β of 0.889. The annual solar PV potential of industrial and residential buildings reached 293.602 GWh and 223.198 GWh, respectively, by using the PV panel simulation filling method for the calculation of the area of roofs where the PV panels can be installed. Furthermore, the rooftop PV potential of the industrial buildings in the research area provided can cover 75.17% of the industrial electricity consumption. This approach can provide scientific guidance and data support for regional solar PV planning, which should prioritize the development of solar potential of industrial buildings in the actual consideration of rooftop PV deployment planning. Full article

Rainfed agriculture in Mexico is characterized by the threat of crop failure due to multiple stress factors, the most significant of which are adverse climatic conditions. Maize is one of the most important staple crops, used for both consumption and livelihoods. However, climate variability and change are threatening to exacerbate yield gaps and increase variability in yields from one year to the next, particularly due to changes in temperature and rainfall. Therefore, using the CMIP6 GCM ACCESS-ESM1-5 and the AquaCrop model, the impacts of climate change on maize yields were assessed for the SSP2-4.5 and SSP5-8.5 scenarios in the study area known as the Atlacomulco Rural Development District (ARDD), considering a projection towards three horizons, 2021–2040, 2041–2060, and 2061–2080, compared to a historical period (1985–2020). Through the metrics used for the validation of the AquaCrop model, it was possible to determine that the simulated values were satisfactorily adjusted to the yields measured by the Agricultural and Livestock Information System (SIAP) from 2003 to 2020 (0.7 ton ha⁻¹ < RMSE > 1.3 ton ha⁻¹; 0.1 < d-index > 0.8; 0.2% < NRMSE > 0.7%; −0.7 < EF > 0.3 and 0.4 < r > 0.8). Future climate change estimates in the ARDD indicate that the average temperatures could increase by between 1.8 and 2.8 °C, while the effective precipitation tends to decrease by up to 7.5−11% through SSP2-4.5 and SSP5-8.5, respectively, during the agricultural cycle. The model results indicate that by the year 2080, maize production in the ARDD will increase from 3.5 ton ha⁻¹ (historical) to 4.2 ton ha⁻¹ and 4.4 ton ha⁻¹, which represents an increase of 21% and 24% for SSP2.4.5 and SSP5-8.5, respectively. Full article