Search Results (241)

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

Air pollution in urban areas has increased significantly over the past few years due to industrialization and population increase. Therefore, accurate predictions are needed to minimize their impact. This paper presents a neural network-based examination for forecasting Air Quality Index (AQI) values, employing two different models: a variable-depth neural network (NN) called slideNN, and a Gated Recurrent Unit (GRU) model. Both models used past particulate matter measurements alongside local meteorological data as inputs. The slideNN variable-depth architecture consists of a set of independent neural network models, referred to as strands. Similarly, the GRU model comprises a set of independent GRU models with varying numbers of cells. Finally, both models were combined to provide a hybrid cloud-based model. This research examined the practical application of multi-strand neural networks and multi-cell recurrent neural networks in air quality forecasting, offering a hands-on case study and model evaluation for the city of Ioannina, Greece. Experimental results show that the GRU model consistently outperforms the slideNN model in terms of forecasting losses. In contrast, the hybrid GRU-NN model outperforms both GRU and slideNN, capturing additional localized information that can be exploited by combining particle concentration and microclimate monitoring services. Full article

Urban blue–green space (UBGS) plays a critical role in mitigating the urban heat island (UHI) effect and reducing land surface temperatures (LSTs). However, existing research has not sufficiently explored the optimization of UBGS spatial configurations or their interactions with urban morphology. This study takes New York City as a case and systematically investigates small-scale urban cooling strategies by integrating multiple factors, including adjustments to the blue–green ratio, spatial layouts, vegetation composition, building density, building height, and layout typologies. We utilize multi-source geographic data, including LiDAR derived land cover, OpenStreetMap data, and building footprint data, together with LST data retrieved from Landsat imagery, to develop a prediction model based on generative adversarial networks (GANs). This model can rapidly generate visual LST predictions under various configuration scenarios. This study employs a combination of qualitative and quantitative metrics to evaluate the performance of different model stages, selecting the most accurate model as the final experimental framework. Furthermore, the experimental design strictly controls the study area and pixel allocation, combining manual and automated methods to ensure the comparability of different ratio configurations. The main findings indicate that a blue–green ratio of 3:7 maximizes cooling efficiency; a shrub-to-tree coverage ratio of 2:8 performs best, with tree-dominated configurations outperforming shrub-dominated ones; concentrated linear layouts achieve up to a 10.01% cooling effect; and taller buildings exhibit significantly stronger UBGS cooling performance, with super-tall areas achieving cooling effects approximately 31 percentage points higher than low-rise areas. Courtyard layouts enhance airflow and synergistic cooling effects, whereas compact designs limit the cooling potential of UBGS. This study proposes an innovative application of GANs to address a key research gap in the quantitative optimization of UBGS configurations and provides a methodological reference for sustainable microclimate planning at the neighborhood scale. Full article

Urban population growth has led to increased air pollution, influenced by disrupted wind patterns and the heterogeneous distribution of pollutants. Although the relationship between urban form and air quality is well recognized, it is often examined in isolation and through simplified urban geometries. This study addresses these limitations by numerically analyzing pollutant dispersion in densely populated hillside areas using idealized but topographically representative building geometries. A three-dimensional microclimatic simulation is conducted with ENVI-met software, incorporating parametric slope angles and building height variations. The results demonstrate that both slope steepness and building height significantly affect local pollutant concentrations: steeper slopes and taller buildings are associated with higher peak pollution values in the environment. Additionally, the simulation results show that vegetation is critical in mitigating pollution, acting as a natural barrier that enhances dispersion. These findings highlight the need for slope-sensitive urban planning and strategically integrating vegetation in hillside developments to improve air quality in complex urban terrains. Full article

With the continual expansion of global urbanization and population growth, urban energy demands have intensified, and anthropogenic activities have precipitated profound shifts in the global climate. These climatic changes directly alter urban environmental conditions, which in turn exert indirect effects on human physiological function. Consequently, the comfort of outdoor community environments has emerged as a critical metric for assessing the quality of human habitation. Although existing studies have focused on improving singular environmental factors—such as wind or thermal comfort—they often lack an integrated, multi-factor coupling mechanism, and adaptive strategy systems tailored to hot-summer, cold-winter regions remain underdeveloped. This study examines the Minhe Community in Qian’an City to develop a performance evaluation framework for outdoor spaces grounded in subjective comfort and to close the loop from theoretical formulation to empirical validation via an interdisciplinary approach. We first synthesized 25 environmental factors across eight categories—including wind, thermal, and lighting parameters—and applied the Analytic Hierarchy Process (AHP) to establish factor weights, thereby constructing a comprehensive model that encompasses both physiological and psychological requirements. Field surveys, meteorological data collection, and ENVI-met (V5.1.1) microclimate simulations revealed pronounced issues in the community’s wind distribution, thermal comfort, and acoustic environment. In response, we proposed adaptive interventions—such as stratified vegetation design and permeable pavement installations—and validated their efficacy through further simulation. Post-optimization, the community’s overall comfort score increased from 4.64 to 5.62, corresponding to an efficiency improvement of 21.3%. The innovative contributions of this research are threefold: (1) transcending the limitations of single-factor analyses by establishing a multi-dimensional, coupled evaluation framework; (2) integrating AHP with ENVI-met simulation to realize a fully quantified “evaluation–simulation–optimization” workflow; and (3) proposing adaptive strategies with broad applicability for the retrofit of communities in hot-summer, cold-winter climates, thereby offering a practical technical pathway for urban microclimate enhancement. Full article

Local Climate Zone (LCZ) classification is essential for urban microclimate modeling and heat mitigation planning. Traditional methods relying on manual sampling face limitations in scalability, objectivity, and handling spatial heterogeneity. This study presents an automated framework for LCZ sample generation, facilitating efficient large-scale LCZ mapping and LCZ-based urban climate analysis and geospatial applications. To this aim, it proposes a dual-path automated framework integrating GIS-driven sample generation to enhance LCZ classification accuracy: a multi-parameter Synergistic Optimization approach for urban LCZs and a Distance-driven Maximum Coverage method for natural LCZs. Specifically, urban samples are selected via multi-objective optimization and Pareto front screening for quality and representativeness, while the selection of natural samples prioritizes spatial coverage and diversity. Combining urban morphological parameters with Sentinel-2 imagery and a Random Forest classifier yielded a final accuracy of 0.95 in our test site, confirming the framework’s effectiveness. Full article

Climate change amplifies heat wave effects on outdoor thermal comfort by increasing their frequency, duration, and intensity. The urban heat island effect worsens heat risks in cities and impacts resilience. Nature-based solution (NBS) with tree plantation was reported as an effective mitigation measure. This simulation study, by the well-validated ENVI-met model, aimed to investigate the impact of different tree planting strategies and building parameters on urban heat risk mitigation and microclimate during a typical hot summer day. Hypothetical skyscrapers and super high-rise buildings were assumed in the study site located in southern China. Adopting meteorological inputs from a typical year, the simulation results revealed that both mean radiant temperature (T_mrt) and physiological equivalent temperature (PET) were elevated (T_mrt > 60 °C and PET > 50 °C) in early afternoon in sunlit areas. Three mitigation approaches with different tree planting locations were investigated. While all approaches demonstrated effective cooling (PET down to <35 °C) in the proximity of trees, a superior approach for mitigating the heat risks was not evident. Within the building array, the shade of bulky structures also lowered T_mrt and PET to a thermally comfortable level in the late afternoon. Combining open-space tree planting with optimized building designs is recommended to mitigate heat risks and enhance urban resilience while promoting outdoor activities and their health benefits. Full article

While urban greenery is known to regulate microclimates and reduce air pollution, its integrated effects remain insufficiently quantified. Through field monitoring and ENVI-met 5.1 modeling of high-rise residential areas in Jinan, the results demonstrate that: (1) vegetation exhibits distinct spatial impacts in air-quality impacts, reducing roadside PM_2.5 by 26.63 μg/m³ while increasing building-adjacent levels by 17.5 μg/m³; (2) shrubs outperformed trees in PM_2.5 reduction (up to 65.34%), particularly when planted in inner rows, whereas tree crown morphology and spacing showed negligible effects; (3) densely spaced columnar trees optimize cooling, reducing T_a by 3–4.8 °C and the physiological equivalent temperature (PET*) by 8–12.8 °C, while planting trees on the outer row and shrubs on the inner row best balanced thermal and air-quality improvements; (4) each 1 m²/m³ leaf area density (LAD) increase yields thermal benefits (ΔT_a = −1.07 °C, ΔPET* = −1.93 °C) but elevates PM_2.5 by 4.32 μg/m³. These findings provide evidence-based vegetation design strategies for sustainable urban planning. Full article

During the intense heatwaves of late summer 2024, Washington, D.C.’s urban landscape revealed the powerful influence of urban morphology on microclimates and air quality. This study investigates the impact of building height-to-width (H/W) ratios on the urban heat island (UHI) effect, using a combination of field measurements and Computational Fluid Dynamics (CFD) simulations to understand the dynamics. Street-level data collected from late August to November 2024 across three sites in Washington, D.C., indicate that high H/W ratios (1.5–2.0) increased temperatures by approximately 2–3 °C and reduced wind speeds to around 0.8 m/s. These conditions led to elevated pollutant concentrations, with ozone (O₃) ranging from 1.8 to 7.3 ppb, nitrogen dioxide (NO₂) from 0.3 to 0.5 ppm, and carbon monoxide (CO) remaining relatively constant at approximately 2.1 ppm. PM_2.5 concentrations fluctuated between 2.8 and 0.4 $\mathsf{\mu }$g/m³. Meanwhile, lower H/W ratios (less than 1.5) demonstrated better air circulation and lower pollution levels. The CFD simulations are in agreement with the experimental data, yielding an RMSE of 0.75 for temperature, demonstrating its utility for forecasting UHI effects under varying urban layouts. These results demonstrate the potential of Computational Fluid Dynamics in not only modeling but also predicting UHI dynamics. Full article

The intensification of extreme temperature events driven by climate change has heightened the vulnerability of urban areas to heatwaves, making it a critical environmental challenge. In this study, we investigate the spatial characteristics of urban heatwave vulnerability in Jungang-dong, Gangneung—a representative mid-sized coastal city in South Korea that experiences a strong urban heat island (UHI) effect due to the prevalent land–sea breeze dynamics, high building density, and low green-space ratio. A representative heatwave day (22 August 2024) was selected using AWS data from the Korea Meteorological Administration (KMA), and hourly meteorological conditions were applied to Computational Fluid Dynamics (CFD) simulations to model the urban microclimates. The thermal stress levels were quantitatively assessed using the Universal Thermal Climate Index (UTCI). The results indicated that, at 13:00, the surface temperatures reached 40 °C and the UTCI values peaked at 43 °C, corresponding to a “Very Strong Heat Stress” level. Approximately 17.4% of the study area was identified as being under extreme thermal stress, particularly in densely built-up zones, roadside corridors with high traffic, and pedestrian commercial areas. Based on these findings, we present spatial analysis results that reflect urban morphological characteristics to guide the optimal allocation of urban cooling strategies, including green (e.g., street trees, urban parks, and vegetated roofs), smart, and engineered infrastructure. These insights are expected to provide a practical foundation for climate adaptation planning and thermal environment improvement in mid-sized urban contexts. Full article

This study investigates the environmental parameters that contribute to the Urban Heat Island (UHI) effect in historic environments, with a particular focus on the UNESCO World Heritage City of Matera. The complex urban morphology of Matera, with its narrow streets and underground buildings, generates distinctive microclimates that intensify the UHI phenomenon, posing challenges for urban planning and heritage conservation. The main objective of the research is to identify which environmental parameters interact with Matera’s architectural and urban characteristics to intensify the UHI, and to propose mitigation strategies that balance heritage conservation with environmental sustainability. The research follows a mixed methodological approach in two phases. The first phase consisted of a comprehensive literature review, identifying gaps in previous studies and developing a methodological framework combining quantitative and qualitative techniques. The second phase involved empirical analysis using advanced techniques such as 3D laser scanning to model urban morphology, satellite image analysis to map the spatial distribution of the UHI, and the integration of historical and real-time meteorological data. The results show significant correlations between urban morphology and UHI intensity, suggesting strategic interventions such as green roofs and reflective materials to mitigate the effects. These findings provide valuable information for urban planners and policy makers, and highlight the importance of integrating sustainable approaches into heritage conservation. Full article

Low-cost sensors (LCSs) emerge as a popular tool for urban micro-climate studies by offering dense observational coverage. This study evaluates the performance of PurpleAir (PA) sensors for ambient temperature monitoring—a key but underexplored aspect of their use. While widely used for particulate matter, PA sensors’ temperature data remain underutilized and lack thorough validation. For the first time, this research evaluates their accuracy by comparing PA temperature measurements with collocated high-precision temperature data loggers across a dense urban network in a humid subtropical U.S. county. Results show a moderate correlation with reference data (r = 0.86) but an average overestimation of 3.77 °C, indicating PA sensors are better suited for identifying temperature trends but not for precise applications like extreme heat events. We also developed and compared eight calibration methods to create a replicable model using readily available crowdsourced data. The best-performing model reduced RMSE and MAE by 51% and 47%, respectively, and achieved an R² of 0.89 compared to the uncalibrated scenario. Finally, the practical application of PA temperature data for identifying heat wave events was investigated, including an assessment of associated uncertainties. In sum, this work provides a crucial evaluation of PA’s temperature monitoring capabilities, offering a pathway for improved heat mapping, multi-hazard vulnerability assessments, and public health interventions in the development of climate-resilient cities. Full article

This research addresses the critical issue of urban heat islands (UHI), in which urban areas experience significantly higher temperatures than their surroundings, adversely affecting human comfort and well-being. Focusing on Inglewood, a city neighboring Los Angeles, California, and Phoenix, Arizona, this study uses a comprehensive methodology involving microclimate analysis-based Universal Thermal Climate Index (UTCI) calculations to assess the impact of horizontal green surfaces and different levels of tree canopies on outdoor thermal stress mitigation. Phoenix was selected due to its hyper-arid desert climate, providing a contrasting context to assess the effectiveness of green infrastructure under extreme heat conditions. The results demonstrate that these interventions effectively reduce strong and moderate heat stress levels (32 °C < UTCI < 38 °C and 26 °C < UTCI < 32 °C); the model with maximum tree canopy achieved an 18.48% reduction in strong heat stress in Inglewood, while combined interventions led to a maximum reduction of 18.92%. However, the findings also reveal that under extreme heat conditions, particularly in hyper-arid environments such as Phoenix, the interventions may have a limited effect, with localized increases in extreme heat stress attributed to microclimate dynamics, reduced vegetation cooling efficiency, and modeling limitations. Despite these challenges, the overall reduction in average UTCI values underscores the potential of integrated green infrastructure strategies for mitigating urban heat stress. This study provides urban planning strategies for integrating these interventions to create more sustainable and resilient urban environments, supporting policymakers and urban planners in their efforts to reduce the effects of UHI. Full article

Blue and green spaces (BGS) play a crucial role in mitigating the urban heat island (UHI) effect by not only lowering land surface temperature (LST) but also regulating the urban microclimate and enhancing ecosystem services. In this study, Ningbo City is selected as the research area. LST data for the years 2014, 2017, 2020, and 2023 were retrieved using Landsat 8 imagery processed via the Google Earth Engine platform, employing an atmospheric correction approach. Simultaneously, land use types were classified using the random forest algorithm. Based on these datasets, a Geographically and Temporally Weighted Regression model was employed to quantitatively assess the spatial and temporal impacts of BGS changes on the UHI effect. The results reveal that (1) from 2014 to 2023, BGS in Ningbo exhibited a consistent decline, while construction land expanded significantly, leading to a gradual increase in the annual average LST; (2) strong UHI zones were primarily concentrated in urbanized zones and closely aligned with regions of elevated LST; the minimum, maximum, and average LST values in blue and green spaces were significantly lower than those observed in cultivated land and construction land; (3) the variation in the influence coefficient of blue space on LST was greater than that of green space, suggesting stronger spatiotemporal heterogeneity in its regulatory effect on the urban thermal environment. Additionally, the green-to-blue space area ratio increased from 9.7:1 in 2014 to 12.8:1 in 2023, deviating progressively from the optimal ecological balance. To promote sustainable urban development, it is imperative for Ningbo to strengthen the conservation and restoration of BGS, optimize their spatial configuration through evidence-based planning, and ensure the long-term stability of ecological functions. Full article

China’s urbanization process has entered the stage of mid-to-late transformation and upgrading, with the urbanization and population growth rates having passed the turning point. Urban renewal has become an increasingly important issue, among which the renovation of old residential areas holds enormous potential. The improvement of the living environment is urgent, and enhancing the microclimate to improve the livability and comfort of outdoor residential spaces is a critical factor. This study presents for the first time a quantitative framework for multifactor synergistic optimization by coupling building layout closure and material albedo effects. This paper takes typical old residential areas in Fuyang as an example and uses 3D microclimate simulation software (ENVI-met Version 4.3) to establish a simulation model. It evaluates the microclimate and thermal comfort under different building layouts, green infrastructures, building envelope materials, and various surface materials. The results show that: (1) Regarding building layout, the point-cluster layout generally results in the best improvement of daily cumulative physiological equivalent temperature (PET) values, followed by row-type and enclosed layouts; (2) The optimal solutions for improving the daily average PET value are as follows: using glass as the building envelope material in the point-cluster layout; 100% tree coverage in the row-type layout; and 100% asphalt coverage as the surface material in the point-cluster layout. These three conditions reduce the daily average PET by 3.51 °C, 23.87 °C, and 2.65 °C, respectively; (3) The degree of impact on PET is ranked as: green infrastructure configuration > building layout > building envelope materials > surface materials; (4) When the building layout of the residential area is more enclosed, such as using row-type or enclosed layouts, the order of building envelope materials improving thermal comfort is: brick, concrete, and glass. When the building layout is less enclosed, such as using point-cluster layouts, the order of building envelope materials improving thermal comfort is: glass, brick, and concrete. Therefore, it is concluded that applying point-cluster layout in buildings, using glass as the building envelope material, and having 100% coverage of asphalt pavement as the surface material and 100% coverage of trees can maximize the improvement of the thermal environment of the buildings. The conclusion is applicable to old residential areas in warm temperate semi-humid monsoon climatic zones characterized by high densities (floor area ratios > 2.5) and high rates of hardening of the ground (≥80%), and is particularly instructive for medium-sized urban renewal projects with an urbanization rate between 45% and 60%. Full article