Search Results (671)

Improving outdoor thermal comfort is a critical objective in urban design, particularly in densely built urban environments. Elevated semi-open spaces—outdoor areas located beneath raised building structures—have been recognized for enhancing pedestrian comfort by improving airflow and shading. However, previous studies primarily focused on warm or temperate climates, leaving a significant research gap regarding their thermal performance in cold climate zones characterized by extreme seasonal variations. Specifically, few studies have investigated how these spaces perform under conditions typical of northern Chinese cities like Xi’an, which is explicitly classified within the Cold Climate Zone according to China’s national standard GB 50176-2016 and experiences both severe summer heat and cold winter conditions. To address this gap, we conducted field measurements and numerical simulations using the ENVI-met model (v5.0) to systematically evaluate the microclimatic performance of elevated ground-floor spaces in Xi’an. Key microclimatic parameters—including air temperature, mean radiant temperature, relative humidity, and wind velocity—were assessed during representative summer and winter conditions. Our findings indicate that the height of the elevated structure significantly affects outdoor thermal comfort, identifying an optimal elevated height range of 3.6–4.3 m to effectively balance summer cooling and winter sheltering needs. These results provide valuable design guidance for architects and planners aiming to enhance outdoor thermal environments in cold climate regions facing distinct seasonal extremes. Full article

To date, few studies have been published for cities in Germany that take into account climate change and changing hydrologic patterns due to increases in building density. This study investigates the efficiency of LID for past and future climate in the polycentric agglomeration area Frankfurt, Main (Central Germany) using observed and projected climate (model) data for a standard reference period (1961–1990) and a high emission scenario (RCP 8.5) as well as a climate protection scenario (RCP 2.6), under 40 to 75 percent building density. LID elements included green roofs, permeable pavement and bioretention cells. SWMM₅ was used as model for simulation purposes. A holistic evaluation of simulation results showed that effectiveness increases incrementally with LID implementation percentage and inverse to building density if implemented onto at least 50 percent of available impervious area. Building density had a higher adverse effect on LID efficiency than climate change. The results contribute to the understanding of localized effects of climate change and the implementation of adaption strategies to that end. The results of this study can be helpful for the scientific community regarding future investigations of LID implementation efficiency in dense residential areas and used by local governments to provide suggestions for urban water balance revaluation. Full article

This study investigates ground deformations in the southeastern Po Plain (northern Italy), focusing on the Bologna area—a densely populated region affected by natural and anthropogenic subsidence. Ground deformations in the area result from geological processes (e.g., sediment compaction and tectonic activity) and human activities (e.g., ground water production and underground gas storage—UGS). We apply a multidisciplinary approach integrating subsurface geology, ground water production, advanced differential interferometry synthetic aperture radar—DInSAR, gas storage data, and land use information to characterize and analyze the spatial and temporal variations in vertical ground deformations. Seasonal and trend decomposition using loess (STL) and cluster analysis techniques are applied to historical DInSAR vertical time series, targeting three representatives areas close to the city of Bologna. The main contribution of the study is the attempt to correlate the lateral extension of ground water bodies with seasonal ground deformations and water production data; the results are validated via knowledge of the geological characteristics of the uppermost part of the Po Plain area. Distinct seasonal patterns are identified and correlated with ground water production withdrawal and UGS operations. The results highlight the influence of superficial aquifer characteristics—particularly the geometry, lateral extent, and hydraulic properties of sedimentary bodies—on the ground movements behavior. This case study outlines an effective multidisciplinary approach for subsidence characterization providing critical insights for risk assessment and mitigation strategies, relevant for the future development of CO₂ and hydrogen storage in depleted reservoirs and saline aquifers. Full article

The Latin American and Caribbean (LAC) region faces persistent challenges of inequality, climate change vulnerability, and deteriorating air quality. The Aburrá Valley, where Medellín is located, is a narrow tropical valley with complex topography, strong thermal inversions, and unstable atmospheric conditions, all of which exacerbate the accumulation of pollutants. In Medellín, ${\mathrm{NO}}_2$ concentrations have remained nearly unchanged over the past eight years, consistently approaching critical thresholds, despite the implementation of air quality control strategies. These persistent high concentrations are closely linked to the variability of the atmospheric boundary layer (ABL) and are often intensified by prolonged dry periods. This study focuses on a representative street canyon in Medellín that has undergone recent urban interventions, including the construction of new public spaces and pedestrian areas, without explicitly considering their impact on ${\mathrm{NO}}_x$ dispersion. Using Computational Fluid Dynamics (CFD) simulations, this work evaluates the influence of urban morphology on ${\mathrm{NO}}_x$ accumulation. The results reveal that areas with high Aspect Ratios (AR > 0.65) and dense vegetation exhibit reduced wind speeds at the pedestrian level—up to 40% lower compared to open zones—and higher ${\mathrm{NO}}_2$ concentrations, with maximum simulated values exceeding 50 μg/m³. This study demonstrates that the design of pedestrian corridors in complex urban environments like Medellín can unintentionally create pollutant accumulation zones, underscoring the importance of integrating air quality considerations into urban planning. The findings provide actionable insights for policymakers, emphasizing the need for comprehensive modeling and field validation to ensure healthier urban spaces in cities affected by persistent air quality issues. Full article

The growing mismatch between ecosystem service (ES) supply and demand underscores the importance of thoroughly understanding their spatiotemporal patterns and key drivers to promote ecological civilization and sustainable development at the regional level in China. This study investigates six key ES indicators across mainland China—habitat quality (HQ), carbon sequestration (CS), water yield (WY), sediment delivery ratio (SDR), food production (FP), and nutrient delivery ratio (NDR)—by integrating a suite of analytical approaches. These include a spatiotemporal analysis of trade-offs and synergies in supply, demand, and their ratios; self-organizing maps (SOM) for bundle identification; and interpretable machine learning models. While prior research studies have typically examined ES at a single spatial scale, focusing on supply-side bundles or associated drivers, they have often overlooked demand dynamics and cross-scale interactions. In contrast, this study integrates SOM and SHAP-based machine learning into a dual-scale framework (grid and city levels), enabling more precise identification of scale-dependent drivers and a deeper understanding of the complex interrelationships between ES supply, demand, and their spatial mismatches. The results reveal pronounced spatiotemporal heterogeneity in ES supply and demand at both grid and city scales. Overall, the supply services display a spatial pattern of higher values in the east and south, and lower values in the west and north. High-value areas for multiple demand services are concentrated in the densely populated eastern regions. The grid scale better captures spatial clustering, enhancing the detection of trade-offs and synergies. For instance, the correlation between HQ and NDR supply increased from 0.62 (grid scale) to 0.92 (city scale), while the correlation between HQ and SDR demand decreased from −0.03 to −0.58, indicating that upscaling may highlight broader synergistic or conflicting trends missed at finer resolutions. In the spatiotemporal interaction network of supply–demand ratios, CS, WY, FP, and NDR persistently show low values (below −0.5) in western and northern regions, indicating ongoing mismatches and uneven development. Driver analysis demonstrates scale-dependent effects: at the grid scale, HQ and FP are predominantly influenced by socioeconomic factors, SDR and WY by ecological variables, and CS and NDR by climatic conditions. At the city level, socioeconomic drivers dominate most services. Based on these findings, nine distinct supply–demand bundles were identified at both scales. The largest bundle at the grid scale (B3) occupies 29.1% of the study area, while the largest city-scale bundle (B8) covers 26.5%. This study deepens the understanding of trade-offs, synergies, and driving mechanisms of ecosystem services across multiple spatial scales; reveals scale-sensitive patterns of spatial mismatch; and provides scientific support for tiered ecological compensation, integrated regional planning, and sustainable development strategies. Full article

Rising temperatures are one of the most severe consequences of climate change, and the built environment plays a significant role in exacerbating heat, particularly in urban areas. In densely populated cities with hot climates, buildings release heat generated from cooling their interiors, contributing to the urban heat island (UHI) effect. Global research actively seeks ways to reduce UHI and promote a more sustainable built environment. Leadership in Energy and Environmental Design (LEED) is among the most widely used sustainability assessment systems. Additionally, digital technologies, especially Building Information Modelling (BIM), are increasingly used to assess and improve energy performance in buildings. While there are frameworks that apply LEED and BIM separately to address UHI strategies, there are potential LEED–BIM integrations which need to be investigated. This study investigates how LEED and BIM can be integrated to support UHI mitigation efforts. A systematic literature review was conducted to examine existing integrations, analyzing trends by publication year, country, and building type. The study identified approximately thirty examples of LEED–BIM integrations supporting ten UHI mitigation strategies. However, it also highlighted underutilized BIM technologies and gaps in addressing certain strategies. The study proposes a framework to help practitioners and policymakers apply LEED–BIM integrations more efficiently, reducing the effort required to implement UHI mitigation strategies while enhancing their practicality and effectiveness. Full article

Miami, Florida, renowned for its cultural richness and coastal beauty, also faces the concerning challenges created by urban heat islands (UHIs). As one of the hottest cities of the United States, Miami is facing escalating temperatures and threatening heat-related vulnerabilities due to urbanization and climate change. Our study addresses the critical issue of mapping and investigating UHIs in complex urban settings. This study leveraged Planet satellite data and Landsat data to conceptualize and develop appropriate mitigation strategies for UHIs in Miami. Utilizing the Planet satellite imagery and Landsat data, we conducted a combined study of land cover and land surface temperature variations within the city. This approach fuses remotely sensed data to identify the UHI hotspots. This study aims for dynamic approaches for UHI mitigation. This includes studying the status of green spaces present in the city, possible expansion of urban green spaces, the propagation of cool roof initiatives, and exploring the recent climatic trend of the city. The research revealed that built-up areas consistently showed higher land surface temperatures while zones with dense vegetation have lower surface temperatures, supporting the role of urban green spaces in surface temperature reduction. This research can also set a robust model for addressing UHIs in other cities facing rapid urbanization and experiencing mounting temperatures each passing year by helping in assessing LST, land cover, and related spectral indices as well. Full article

The rapid growth of construction and demolition waste (CDW) presents significant challenges to sustainable urban development, particularly in densely populated regions, such as the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). Despite substantial disparities in CDW management (CDWM) performance across cities, the key influencing factors and effective strategies remain underexplored, limiting the development of localized and evidence-based CDWM solutions. Therefore, this study formulated three hypotheses concerning the relationships among CDWM performance, city attributes, and governance capacity to identify the key determinants of CDWM outcomes. These hypotheses were tested using clustering and correlation analysis based on data from 11 GBA cities. The study identified three distinct city clusters based on CDW recycling, reuse, and landfill rates. Institutional support and recycling capacity were key determinants shaping CDWM performance. CDW governance capacity acted as a mediator between city attributes and performance outcomes. In addition, the study examined effective strategies and institutional measures adopted by successful GBA cities. By highlighting the importance of institutional and capacity-related factors, this research offers novel empirical insights into CDW governance in rapidly urbanizing contexts. Full article

The integration of shared autonomous vehicles into historic urban areas presents both opportunities and challenges. In heritage-rich environments like very old Asian (such as Suzhou old town, which serves as a use case example) or European (especially Mediterranean coastal cities) areas—characterized by narrow alleys, dense development, and sensitive cultural landscapes—shared autonomous vehicle adoption raises critical spatial and social questions. This study employs a qualitative, user-centered approach based on the ripple model to examine residents’ perceptions across four dimensions: residential patterns, parking land use, regional accessibility, and street-level infrastructure. Semi-structured interviews with 27 participants reveal five key findings: (1) public trust depends on transparent decision-making and safety guarantees; (2) shared autonomous vehicles may reshape generational residential clustering; (3) the short-term parking demand remains stable, but the long-term reuse of space is feasible; (4) shared autonomous vehicles could enhance accessibility in historic cores; (5) transport systems may evolve toward intelligent, human-centered designs. Based on these insights, the study proposes three strategies: (1) transparent risk assessment using explainable artificial intelligence and digital twins; (2) polycentric development to diversify land use; (3) hierarchical street retrofitting to balance mobility and preservation. While this study is limited by its qualitative scope and absence of simulation, it offers a framework for culturally sensitive, small-scale interventions supporting sustainable mobility transitions in historic urban contexts. Full article

Rapid urbanization and climate change pose significant challenges to air quality in arid metropolitan areas, with critical implications for public health and sustainable development. This study projects the evolution of air pollution in Riyadh, Saudi Arabia, through 2070 using an integrated modeling approach that combines CMIP6 climate projections with localized air quality data. We analyzed daily concentrations of major pollutants (SO₂, NO₂) across 15 strategically selected monitoring stations representing diverse urban environments, including traffic corridors, residential areas, healthcare facilities, and semi-natural zones. Climate data from two Earth System Models (CNRM-ESM2-1 and MPI-ESM1.2) were bias-corrected and integrated with historical pollution measurements (2000–2015) using hierarchical Bayesian statistical modeling under SSP2-4.5 and SSP5-8.5 emission scenarios. Our results revealed substantial deterioration in air quality, with projected increases of 80–130% for SO₂ and 45–55% for NO₂ concentrations by 2070 under high-emission scenarios. Spatial analysis demonstrated pronounced pollution gradients, with traffic corridors (Eastern Ring Road, Northern Ring Road, Southern Ring Road) and densely urbanized areas (King Fahad Road, Makkah Road) experiencing the most severe increases, exceeding WHO guidelines by factors of 2–3. Even semi-natural areas showed significant increases in pollution due to regional transport effects. The hierarchical Bayesian framework effectively quantified uncertainties while revealing consistent degradation trends across both climate models, with the MPI-ESM1.2 model showing a greater sensitivity to anthropogenic forcing. Future concentrations are projected to reach up to 70 μg m⁻³ for SO₂ and exceed 100 μg m⁻³ for NO₂ in heavily trafficked areas by 2070, representing 2–3 times the Traffic corridors showed concentration increases of 21–24% compared to historical baselines, with some stations (R5, R13, and R14) recording projected levels above 4.0 ppb for SO₂ under the SSP5-8.5 scenario. These findings highlight the urgent need for comprehensive emission reduction strategies, accelerated renewable energy transition, and reformed urban planning approaches in rapidly developing arid cities. Full article

As global climate change intensifies and energy crises deepen, photovoltaic (PV) applications in cities are increasingly garnering attention worldwide. In this context, retrofitting existing high-density residential areas with PV applications is becoming a focus of urban low-carbon development. As the most densely populated city in Western China, Chengdu is characterized by rapid development and high energy consumption. The widespread application of photovoltaic (PV) systems could significantly alleviate its energy consumption issues. This research investigated the PV application potentials of 27 non-residential areas in high-density residential areas in Chengdu, Sichuan Province from a design perspective and proposed design recommendations for PV applications in these spaces. In addition, this study analyzed urban morphological factors affecting the PV generation potential in non-residential areas through a Pearson correlation. The key factors influencing the PV application potential in these areas were building density (BD), non-residential area perimeter-to-area ratio (NBPAR), and maximum building height (H_max). This research aims to provide new strategies and methods for the low-carbon transformation of future urban high-density residential areas. Full article

Extreme rainfall in urban areas can cause major economic damage, a problem expected to intensify with climate change. Despite this, high-resolution studies at the city scale remain limited. This study analyzes rainfall organization and storm dynamics over Barcelona using data from a dense rain gauge network (1994–2019). The aim is to identify dominant spatial patterns and understand how storms evolve in relation to local urban and topographic features. Principal component analysis and simple scaling analysis revealed signs of a rainfall island effect, possibly linked to the urban heat island and modulated by orographic and coastal influences. Tailored rainfall indices highlighted a division between inland areas shaped by orography and coastal zones influenced by the sea. These spatial structures evolved with rainfall duration, shifting from localized contrasts at a 10 min resolution to more homogeneous distributions at daily scales. Storm tracking showed that 90% of speeds ranged from 5 to 60 km/h and intense rainfall events typically moved east–southeast toward the sea and north–northeast. Faster storms tended to follow preferred directions reflecting mesoscale circulations and possible modulations by local terrain. These findings underscore how urban morphology, local relief, and a coastal setting may shape rainfall at the city scale, in interaction with broader Mediterranean synoptic dynamics. Full article

The concept of the 15-minutes city [15 MC] focuses on providing important services within proximity and accessibility through active travel like walking or biking. While this model is becoming popular in urban planning and academic discourse, its implementation faces challenges in both densely populated developing and developed countries. This study aims to conduct a systematic review of recent literature to (1) identify the core components of the 15 MC model, (2) examine planning tools and strategies used in its implementation, (3) compare successes and challenges across global contexts, particularly in densely populated and resource-constrained areas, and (4) offer practical recommendations for adapting the model to meet local needs. The study reviewed 33 research papers published in the last five years [2019–2024]. Following PRISMA guidelines, a structured screening and selection process was conducted using databases such as Scopus, Web of Science, and Google Scholar. Thematic analysis revealed major challenges for implementing the 15 MC in the Global South, including urban informality, gaps in infrastructure, and complex governance issues. Moreover, the review points out the potential risks of exclusion and gentrification if the specific needs of different contexts are not considered. While high-income countries tend to focus on sustainability and making neighborhoods walkable, developing countries struggle with deeper structural problems that make equitable implementation harder. This study emphasizes the need for locally adaptive frameworks in planning 15 MCs and aims to develop inclusive urban policies that support Sustainable Development Goal 11, which seeks to make cities inclusive, safe, resilient, and sustainable. Full article

Nature-based solutions (NBS) have attracted increasing attention in local air quality and climate change adaptation plans as suitable measures to reduce health risks. Although several studies have reported health benefits from short-term urban cooling effects of NBS, medium- to long-term health benefits are still poorly understood. In this study, we assess the changes in long-term mortality related to temperature fluctuations induced by city-scale vegetation actuations in three Southern European cities. We performed two annual high-resolution simulations with the Weather Research and Forecasting model to anticipate the impact of future revegetation strategies on temperature in these urban areas. Further, we assessed the impact of temperature changes on health using a country-specific minimum mortality temperature (MMT) reported in scientific literature. It was found that NBS could provide non-negligible reductions of long-term mortality related to temperature regulation (central estimate of 4.1, 1.2, and 3.4 cases avoided per year in Madrid, Milano, and Bologna, respectively). The effect of vegetation is site-dependent, and the cooling effect explains most of the benefits, especially in densely built-up areas of the cities analyzed. Future research should combine short/long-term temperature effects with other indirect implications (air quality, mental health) in the context of climate change. Full article

Urban forests are very important for the environment and for people, especially in semi-arid cities where there is not much greenery. This makes heat stress worse and makes the city less livable. This paper presents a comprehensive geospatial methodology for selecting afforestation sites in the expanding semi-arid urban area of Şanlıurfa, Turkey, characterized by minimal forest cover, rapid urbanization, and extreme weather conditions. We identified nine ecological and infrastructure criteria using high-resolution Sentinel-2 images and features from the terrain. These criteria include slope, aspect, topography, land surface temperature (LST), solar radiation, flow accumulation, land cover, and proximity to roads and homes. After being normalized to make sure they were ecologically relevant and consistent, all of the datasets were put together into a GIS-based Multi-Criteria Decision Analysis (MCDA) tool. The Analytic Hierarchy Process (AHP) was then used to weight the criteria. A deep learning-based semantic segmentation model was used to create a thorough classification of land cover, primarily to exclude unsuitable areas such as dense urban fabric and water bodies. The final afforestation suitability map showed that 151.33 km² was very suitable and 192.06 km² was suitable, mostly in the northeastern and southeastern urban fringes. This was because the terrain and subclimatic conditions were good. The proposed methodology illustrates that urban green infrastructure planning can be effectively directed within climate adaptation frameworks through the integration of remote sensing and spatial decision-support tools, especially in ecologically sensitive and rapidly urbanizing areas. Full article