Search Results (212)

Under the growing threat of urban heat stress, street canyons play a critical role in shaping the pedestrian thermal environment. While street greenery is an effective mitigation strategy, its performance varies substantially with physical characteristics—such as aspect ratio, street width, and sidewalk width—highlighting the need for spatially adaptive design. This study evaluates the effects of sidewalk width, street orientation, and planting structure on thermal conditions in a humid subtropical climate in Daegu Metropolitan City, Republic of Korea. The analysis focuses on open low-aspect-ratio street canyons (H/W = 0.86 for E–W and 0.43 for N–S orientations). Using a validated ENVI-met (Version 5.6.1) model based on field measurements from Daegu, Republic of Korea, 56 street-greening scenarios were simulated by systematically varying sidewalk width, street orientation, planting rows, spacing, and planting structure. Results show that multi-row planting served as the primary structural framework governing thermal performance. Optimal configurations varied with sidewalk width, with two-row planting for 6 m sidewalks and three-row planting for 10 m sidewalks providing the most effective cooling. The greatest cooling (−2.02 °C) was achieved when optimized multi-row configurations were combined with multi-layer planting. Once optimal multi-row configurations were established, the presence of understory vegetation had a greater influence on thermal improvement than its specific composition, allowing flexibility in understory design. Clear spatial asymmetries were identified, with the highest thermal stress occurring on the north-side sidewalk in E–W streets and the west-side sidewalk in N–S streets. Targeted planting in these locations produced greater cooling benefits than uniform strategies. These findings provide a spatially grounded framework for climate-responsive street greenery and offer practical design guidance, highlighting the need for context-specific, optimized multi-row planting strategies adapted to local urban and climatic conditions. Full article

In the context of global climate change and rapid urbanization, urban outdoor thermal environment issues in summer have become increasingly severe. Shading has been widely recognized as an effective strategy for improving outdoor thermal comfort, yet existing evaluation methods still suffer from limitations in adaptability and accuracy. Taking Chongqing, a typical hot-humid city in China, as a case study, this paper proposes an evaluation method that accounts for human thermal adaptation, introducing three complementary indicators, namely Universal Thermal Climate Index Load (UTCIL), cumulative UTCIL (cUTCIL), and Heat Stress Duration (HSD). Focusing on four shading-related urban canyon morphological factors—orientation, aspect ratio (H/W), building asymmetry, and leaf area index (LAI) of street trees—a series of simulation scenarios was designed to quantitatively explore their impacts on summer outdoor thermal comfort. The applicability and reliability of the ENVI-met model for block-scale outdoor thermal environment simulation were validated by comparing field-measured microclimate data with simulation results. The findings demonstrate that all four morphological factors substantially influence the outdoor thermal environment. Canyon orientation considerably affects thermal comfort, with a 30° clockwise deviation from the north–south yielding optimal conditions, whereas the east–west (90°) orientation produces the poorest thermal environment, with a maximum UTCI of approximately 48.9 °C. For aspect ratio, thermal comfort improves continuously as H/W increases, with the benefit stabilizing beyond H/W = 3.5. Building asymmetry also plays a notable role: raising building height on one side can effectively reduce outdoor thermal stress, and canyons with taller west-side buildings show better thermal performance under the same asymmetry ratio. Furthermore, street tree shading and aspect ratio exhibit a synergistic cooling effect, where high LAI (e.g., 4.77) reduces UTCI_max by approximately 1.8 °C at H/W = 1, but this benefit diminishes as H/W increases. The optimal outdoor thermal environment is achieved through the combination of a high aspect ratio and high LAI. These findings provide a quantitative basis and design references for optimizing outdoor thermal comfort in Chongqing. In addition, the quantitative evaluation proposed method can offer a methodological reference for other hot-humid regions. Full article

Urban thermal comfort in winter is an important but insufficiently quantified component of sustainable, climate-adapted urban design in cold-weather cities facing energy-intensive winter environmental challenges. This study uses high-resolution simulations to evaluate discomfort across a downtown district in Sapporo, Japan, based on the standard effective temperature (SET*) index and universal thermal climate index (UTCI). A total of 2438 sampling points were assessed under 69 hourly winter scenarios. Discomfort hotspots were found in east–west streets and wind-exposed corners, driven by limited solar access or intensified wind. SET* is a more sensitive indicator under cold conditions, particularly in shaded areas. Wind speed and mean radiant temperature distributions revealed the environmental drivers of discomfort. The influence of building height was confirmed via quantitative correlation analysis, which revealed significant negative relationships between adjacent building heights and SET* across all streets analyzed, especially in east–west street canyons, where correlation coefficients ranged from −0.80 to −0.52 in the representative street. These findings contribute to urban sustainability by providing a quantitative tool for identifying winter thermal vulnerability and supporting passive, climate-adapted public-space design. The proposed framework can help improve winter walkability, outdoor activity, and the environmental quality of downtown spaces in cold-region cities. Full article

Urban street canyons exert a critical influence on local microclimates; however, the dynamics of mixed convective airflow under unsteady wind and thermal forcing remain poorly quantified. This study systematically investigates the spatiotemporal characteristics of airflow within symmetric and asymmetric street canyons through integrated long-term field measurements and complementary CFD simulations. Field data collected over 120 monitoring days at the Weishui Campus of Chang’an University were analyzed using the Levenberg–Marquardt nonlinear curve-fitting algorithm. The analysis demonstrates that sine functions accurately represent diurnal surface temperature variations during consecutive clear sky periods, whereas polynomial functions of varying orders are required to characterize meteorologically complex episodes, including cold-wave cooling and seasonal transitions. Ambient wind patterns outside the canyon were further classified into two characteristic variation modes: stepwise and gradual. Complementary unsteady RANS simulations, with wall boundary conditions derived directly from the fitted field data, reveal that canyon geometry and meteorological forcing jointly govern the evolution of airflow structures and thermal distributions across seasons. In the symmetric canyon, the flow transitions from complex multi-vortex activity in spring and summer to a more stable regime in autumn, with two well-defined counter-rotating vortices emerging during winter cold-wave events. In the asymmetric canyon, strong summer solar heating sustains a dominant leeward vortex with a strengthening secondary structure, whereas winter cold wave intrusion generates a hierarchically nested vortex system in which secondary and tertiary vortices progressively develop and detach. By coupling empirical surface temperature functions with CFD boundary conditions, this study advances the precision of predictive microclimate models and provides an evidence-based framework for optimizing street canyon geometry to enhance ventilation performance, energy efficiency, and outdoor thermal comfort. Full article

Amid growing concerns over global warming, ensuring the outdoor thermal comfort (OTC) of public urban spaces is crucial for creating liveable and resilient cities. This study focused on the intensification of the urban heat island (UHI) effect and the heat stress experienced by the vulnerable older population. Evidence was found through the case study in a highly vulnerable area of Porto, with a high ageing ratio. The primary aim was to assess the influence of design-based adaptation strategies on OTC using ENVI-met, with a specific focus on older adults. Thermal stress was evaluated using the Physiological Equivalent Temperature (PET) index. The analysis confirms that older adults consistently experience higher PET values (+2–5 °C) and larger areas of thermal discomfort than active-age adults. Simulations reveal that the effectiveness of adaptation measures depends on the characteristics of the urban space but enhanced green infrastructure achieves the most significant heat mitigation results. Artificial shading only provides localized thermal relief. Cool pavements contribute meaningfully by lowering surface heat storage and reducing longwave radiation. However, their impact on PET, beneficial or detrimental, depends significantly on the morphology of the outdoor space and the materials used. In the analysed street canyon, PET was higher in the central hours of the day for both age ranges, when the pavement material had a higher albedo. An effective heat mitigation needs a combination of vegetation-based strategies and climate-responsive materials to ensure comfortable and age-inclusive public spaces. This research presents an actionable methodological approach for evaluating and enhancing OTC, advocating the use of microclimate simulations in a carefully selected set of public spaces within an intervention urban area to define effective climate adaptation measures for each space. Full article

Urban canyons, integral components of the built environment, significantly influence microclimatic conditions and thermal comfort. This review investigates their combined effects with green infrastructure on thermal comfort, offering a comprehensive framework for supporting urban design and greening strategies. The review is based on a structured literature analysis of peer-reviewed studies retrieved from major scientific databases (Scopus and Web of Science), following defined selection and screening criteria. Urban canyon orientation determines solar exposure and its interaction with prevailing wind patterns, affecting ventilation and heat dissipation. The urban canyon aspect ratio influences shading and airflow regulation, while their sky view factor moderates radiative cooling and daylight availability. Urban greening—encompassing street trees, green roofs, and vertical green walls—complements urban geometry by reducing air temperatures, enhancing evapotranspiration, and modifying local wind dynamics. Tree shading can reduce the physiological equivalent temperature in urban canyons, mitigating extreme heat stress. Key vegetative parameters, such as leaf area index and canopy density, are critical for quantifying cooling contributions. Key findings underscore the role of higher aspect ratios in enhancing shading and ventilation while they emphasize the critical influence of street orientation and sky view factor on microclimatic regulation. Vegetation emerges as a vital component, with tree shading contributing substantially to cooling effects and reducing physiological equivalent temperature. The beneficial synergistic interaction between urban geometry and vegetation optimizes thermal comfort. Tailored strategies based on urban canyon typologies balance urban development with environmental sustainability. The proposed framework provides actionable strategies for designing resilient and thermally optimized urban spaces, promoting climate-adaptive urban planning by addressing the dual challenges of the urban heat island and thermal discomfort in cities. Full article

Urbanization and climate change intensify urban heat islands and air pollution; therefore, street canyon building planning that accounts for road orientation, shading, thermal environment, and ventilation is crucial. This study uses numerical simulations to investigate how non-uniform wall and road heating affects airflow and pollutant dispersion in street canyons under varying Richardson numbers (Ri) and heating scenarios (windward wall, leeward wall, road surface). The results indicate that large wall–atmosphere temperature differences combined with low incoming wind speed (high Ri) make thermal buoyancy a dominant control on canyon flow and pollutant transport. Heating of the leeward wall and road surface enhances ventilation and pollutant removal (prominently when the Ri ≥ 0.49), whereas heating of the windward wall suppresses dispersion and increases concentrations (prominently when the Ri ≥ 0.12). For a north–south street, diurnal solar heating produces strong micro-environmental contrasts. With easterly winds, morning heating of the windward wall elevates pollutant levels, while afternoon heating of the leeward wall promotes dispersion and lowers concentrations. Specifically, compared with the isothermal condition, the turbulent exchange rate at the top of the street canyon is enhanced to 1.71~6.86 times, while the convective exchange rate is suppressed to 58%~83% in the morning and enhanced to 1.21~1.92 times. These findings suggest that urban planning should limit windward wall temperature rises via shading and greening; thus, single-sided sidewalk and greening layouts on the windward side are recommended. Full article

As urbanization intensifies, improving street thermal comfort has become a critical issue in urban renewal. While existing studies generally assume that increasing the Green View Index (GVI) linearly improves pedestrian thermal comfort, this study identifies a significant “Decoupling Effect” in high-density commercial areas through field measurements and numerical simulations of three typical street types (commercial–service, ecological–recreational, and historical–cultural) in Shenyang. Integrating DeepLab V3 semantic segmentation with ENVI-met version 5.1.1 microclimate simulation, the results demonstrate a robust monotonic negative correlation between GVI and Physiological Equivalent Temperature (PET) in ecological streets (Spearman’s ρ = −0.692, p < 0.001), confirming the consistent cooling benefit of greenery in nature-dominated environments. However, a distinct “Threshold Effect” was identified in commercial streets using Piecewise Linear Regression (PLR). A critical breakpoint was detected at GVI = 22.08%. Below this threshold, visual greenery effectively contributes to cooling (slope = −0.454); yet, once GVI exceeds 22.08%, the cooling efficacy diminishes significantly (slope = −0.109), marking the onset of a “decoupling” phase. Specifically, despite Wenhua Road achieving a GVI of ~24.5% with a complex “three-board, four-belt” structure, its PET peak reaches 46.15 °C, approximately 5.5 °C higher than ecological streets. Mechanism analysis reveals that under peak thermal stress (Traffic Heat ≈ 75 W/m²), the high-intensity anthropogenic heat and hardscape radiation exceed the evaporative cooling threshold of vegetation. This study reveals the non-linear relationship between visual greenery and the physical thermal environment, suggesting that simply pursuing visual green quantity is ineffective in commercial canyon renewal; instead, a threshold-based synergistic optimization of canopy shading and pavement thermal performance is required. These findings provide a quantitative basis for sustainable street landscape planning and urban climate adaptation strategies in high-density cities. Full article

Rapid urbanization has intensified microclimatic deterioration in temperate monsoon cities, directly affecting human thermal comfort. This study investigates the regulatory effects of common street tree species under varying street aspect ratios (H/W) and orientations in Shenyang, China, a representative temperate monsoon city characterized by cold winters. Field surveys and questionnaire data were combined with ENVI-met simulations to quantify thermal comfort responses using the Universal Thermal Climate Index (UTCI). Results demonstrate that street geometry strongly constrains microclimate regulation: streets with H/W = 1.2 and a SE–NW orientation achieved the most favorable balance between shading and ventilation, yielding the lowest UTCI values. Significant interspecies variability was observed: Golden Elm and Chinese Willow provided the greatest cooling benefits, whereas Ginkgo exhibited limited adaptability, particularly in enclosed or highly open canyons. A comparison with subjective thermal comfort votes confirmed strong model reliability, though discrepancies emerged in dense commercial areas due to non-meteorological factors. Based on these findings, a spatially driven, species-adaptive, and human-centered framework is proposed to optimize street greening strategies in a temperate monsoon city characterized by cold winters. This research provides quantitative evidence for urban greening design, highlights the necessity of integrating spatial form with tree-species selection, and offers practical guidance for resilient thermal comfort management in rapidly urbanizing cold-region cities. Full article

Mitigating heat stress in high-density historical districts remains a critical challenge in urban renewal due to complex morphological heterogeneity. Existing research often relies on isolated intervention measures, lacking systematic, multi-strategy assessments driven by high-precision spatial data. This study addresses this gap by establishing a quantitative framework that couples thermal infrared remote sensing with Computational Fluid Dynamics (CFD) to optimize microclimate responses in Beijing’s Liulichang Historic District. Remote sensing data were utilized to retrieve high-resolution Land Surface Temperature (LST), providing accurate thermal boundary conditions for micro-scale wind-thermal simulations. A baseline scenario (S0) and seven renewal strategies (S1–S7)—integrating varying configurations of greenery, water bodies, and permeable pavements—were evaluated using pedestrian-level comfort indices. Results reveal that single-factor interventions yield marginal improvements or thermodynamic trade-offs; specifically, adding greenery (S1) in narrow street canyons increased aerodynamic roughness, thereby obstructing ventilation and inducing localized warming. Conversely, composite strategies significantly enhanced microclimatic quality. The “greenery-water-permeable pavement” strategy (S4) achieved optimal synergistic effects, characterized by substantial cooling and spatial homogenization. Regression analysis identified water bodies as the dominant cooling driver, where a 10% increase in water coverage resulted in a temperature reduction of approximately 5.17 °C. Conversely, greenery alone showed no statistically significant cooling contribution (p > 0.05) without the synergistic presence of water or pavement modifications. This research suggests that urban renewal in high-temperature zones (>36 °C) should prioritize composite cooling networks. Furthermore, vegetation layouts near wind corridors must be precisely regulated to prevent ventilation degradation. These findings provide a scientific basis for the climate-adaptive sustainable regeneration of culturally significant, high-density urban blocks. Full article

Deep learning-based flow field prediction for microclimate pollutant dispersion represents an emerging and promising methodology, where effectively integrating meteorological, spatial, and temporal information remains a critical challenge. To address this, we propose a novel non-intrusive reduced-order model (ROM) that synergizes a Dilated Convolutional Autoencoder (DCAE) with pre-trained large language models (LLMs). The DCAE, leveraging nonlinear mapping, was employed for extracting low-dimensional spatiotemporal flow field features. These features were then combined with textual prototypes via text embedding to enable few-shot inference using the LLM-based flow field prediction method. To optimize the utilization of pre-trained LLMs, we designed a specialized textual description template tailored for pollutant dispersion data, which enhances the contextual input of meteorological conditions to guide model predictions. Experimental validation through three-dimensional urban canyon simulations conclusively demonstrated the efficacy of the convolutional autoencoder and LLM-based framework in predicting pollutant dispersion flow fields. The proposed method exhibits remarkable transfer learning capabilities across varying street canyon geometries and meteorological conditions while significantly representing a 9.85× acceleration in prediction compared to Computational Fluid Dynamics (CFD). Full article

The low-altitude atmospheric environment has been receiving increasing attention in recent years due to rising human activities and the emerging growth of the low-altitude economy. Urban wakes generate highly inhomogeneous, multiscale turbulent flows, posing challenges for momentum transport, pedestrian-level ventilation, and low-altitude aerial vehicle operations. Large eddy simulation of a neutral boundary layer over an idealized urban street canyon is conducted, and wavelet transforms combined with quadrant analysis are applied to investigate scale-dependent momentum transport across three wake zones: recirculation, entrainment, and detrainment. The results show that strong momentum transport across a broad range of scales is exhibited at the roof level of the recirculation zone. The momentum transport in the entrainment zone is governed by large-coherent-scale turbulence. On the contrary, the dynamics are governed by small-scale turbulence activities accompanied by distinct quadrant asymmetry in the detrainment zone because of the major energy contribution from Q2 and Q4 events. Furthermore, the multiscale characteristics of turbulent transport produce distinct frequency signatures across different wake zones, underscoring their dynamically heterogeneous nature and potential implications for UAV operation. Full article

Urban air pollution from road traffic remains a major public health concern, with its spatial variability at neighbourhood scales strongly influenced by urban morphology. This study investigates how urban form affects the dispersion of traffic-related PM_2.5 in four Italian cities (Lecce, Bari, Milan and Rome) representing diverse climatic and morphological contexts. Seasonal simulations were conducted using the ADMS-Roads dispersion model, integrating detailed road geometries, standardized traffic emissions, and city-level meteorological data for 2019–2021. Urban morphology was characterized at 100 m resolution using building plan area fraction (λ_p), street-canyon aspect ratio and mean building height derived from GIS analyses. Statistical analysis combined random forest regression with partial dependence plots and quantile regression to explore both average and distributional effects. Results reveal a generally negative association between λ_p and PM_2.5 in Lecce, Milan, and Rome, particularly at higher concentration quantiles, suggesting that denser urban fabrics may mitigate extreme pollution episodes. Bari exhibits a weaker and more heterogeneous response, highlighting the influence of local wind regimes and traffic distribution. Wind speed and temperature consistently reduce PM_2.5 across all cities, while street geometry effects are non-linear and season-dependent. These findings demonstrate the importance of considering urban morphology alongside traffic and meteorology when designing strategies to reduce exposure. Importantly, the methodological framework presented here, combining high-resolution dispersion modelling with interpretable machine-learning analyses, is transferable to other urban contexts, providing a robust approach to assess morphology–pollution interactions beyond the studied cities. Full article

Urban traffic noise poses escalating environmental challenges in rapidly urbanizing regions with high-density buildings, yet systematic investigations into its spatiotemporal characteristics remain relatively scarce. This study addresses this research gap via the synchronized on-site monitoring of traffic noise and traffic flow on a representative arterial road in Guangzhou, China. The analysis reveals that nighttime equivalent continuous A-weighted sound levels (L_Aeq) are 3.0–4.0 dB(A) higher than those during the congested daytime peak, a phenomenon primarily driven by higher vehicle speeds under nighttime free-flow traffic conditions. The spatial analysis uncovers complex three-dimensional noise propagation dynamics specific to urban street canyons. Vertical profiling demonstrates a counterintuitive pattern where noise levels do not attenuate with building height, and upper floors experience marginally higher noise exposure than the ground floor, which is attributed to the canyon effect, where multiple sound wave reflections offset the natural distance attenuation. A validated three-dimensional computational model was further employed to evaluate the efficacy of noise mitigation strategies, showing that an integrated intervention combining porous asphalt pavement and acoustic barriers achieves a maximum noise attenuation of 19.9 dB(A) at ground-level receptors. This significant reduction stems from a synergistic effect: porous asphalt reduces noise at the source on a global scale, while acoustic barriers provide localized shielding for the lower floors of adjacent buildings. This research concludes that effective traffic noise control in high-density urban areas requires three-dimensional, multi-faceted strategies addressing noise source characteristics, transmission pathways, and receptor vulnerabilities. Full article

Under the dual pressures of global climate change and rapid urbanization, historic districts face the challenge of improving livability and adapting to climate conditions while preserving their historical fabric. While street greening is recognized as a key mitigation strategy, the lack of quantitative, spatially explicit guidelines often leads to indiscriminate planting and inefficient resource use in practice. Taking the historic districts of Nanjing—a representative city in China’s hot-summer and cold-winter region—as a case study, we systematically explored the comprehensive impacts of street orientation, height-to-width ratios (H/W), and spacing of street trees on the microclimate of the districts through empirical analysis and ENVI-met simulation. Then we constructed a typical street canyon model to simulate winter and summer conditions, and regression models were established to identify suitable SVF ranges for different street orientations. Results indicate that the recommended SVF ranges vary by street orientation: 0.3–0.5 for S–N, SE–NW, and NE–SW streets, and 0.4–0.6 for E–W streets. Crucially, denser planting does not always improve comfort. These evidence-based thresholds were applied to the renewal of Yongyuan Road. The study delivers spatially explicit guidelines in the form of quantitative planting thresholds to support climate-resilient street tree planning in historic districts, helping to enhance planting precision and resource efficiency. Full article