Search Results (104)

Traditional Chinese villages, which have long supported villagers’ comfort level of daily activities, are increasingly affected by global climate change and rural reconstruction, prompting growing research interest in their outdoor microclimate design. This systematic review aims to synthesize and evaluate the outdoor microclimate spatial design mechanism studies in traditional Chinese villages noted for their uniqueness and complexity. Following the PRISMA method, this study was carried out on November 27, 2024, by retrieving studies from the Scopus and CNKI databases and applying predefined inclusion and exclusion criteria; 42 empirical studies were systematically reviewed. It identifies current research trends, summarizes concepts, frameworks, indicators, and methodologies with a focus on the design mechanisms considering scales, contexts, and user groups, and outlines directions for future research. The findings reveal a growing number of publications, with case studies predominantly concentrated on three concepts: physical microclimates, human comfort, and behavioral responses, characterized as distributed in south-east areas. Based on these concepts and their correlations, this study proposes a classification framework based on multiple scales, contexts, and user groups. Within this framework, the study found that relative humidity and PET (physiological equivalent temperature) emerge as the most commonly used indicators, while field measurements, simulations, surveys, and observations are identified as the primary methods. The review further reveals that unique outdoor spatial design characteristics shape physical microclimates, human comfort, and behavior indicators influenced by contexts and users from the macro to the micro scale. Future research should advance existing studies by enriching the current contextual framework and explore more microclimatic factors. This review offers a comprehensive overview and actionable insights for outdoor microclimate design, policymaking, and the promotion of climate adaptation and villagers’ public health in different traditional rural settings. Full article

Maintaining the required relative humidity values in the vehicle cabin is an important HVAC task, along with considerations related to the temperature, velocity, air pressure and noise. Deviation from the optimal values worsens the psycho-physiological state of the driver and affects the energy efficiency of the train. In this study, a model of liquid film formation on and removal from various cabin surfaces was constructed using the fundamental Navier–Stokes hydrodynamic equations. A special transport model based on the liquid vapor diffusion equation was used to simulate the air environment inside the cabin. The evaporation and condensation of surface films were simulated using the Euler film model, which directly considers liquid–gas and gas–liquid transitions. Numerical results were obtained using the RANS equations and a turbulence model by means of the finite volume method in Ansys CFD. Conjugate fields of temperature, velocity and moisture concentration were constructed for various time intervals, and the dependence values for the film thicknesses on various surfaces relative to time were determined. The verification was conducted in comparison with the experimental data, based on the protocol for measuring the microclimate indicators in workplaces, as applied to the train cabin: the average ranges encompassed temperature changes from 11% to 18%, and relative humidity ranges from 16% to 26%. Comparison with the results of other studies, without considering the phase transition and condensation, shows that, for the warm mode, the average air temperature in the cabin with condensation is 12.5% lower than without condensation, which is related to the process of liquid evaporation from the heated walls. The difference in temperature values for the model with and without condensation ranged from −12.5% to +4.9%. We demonstrate that, with an effective mode of removing condensate film from the window surface, including recirculation modes, the energy consumption of the climate control system improves significantly, but this requires a more accurate consideration of thermodynamic parameters and relative humidity. Thus, considering the moisture condensation model reveals that this variable can significantly affect other parameters of the microclimate in cabins: in particular, the temperature. This means that it should be considered in the numerical modeling, along with the basic heat transfer equations. Full article

Like other mega cities in China, Beijing is undergoing a large-scale urban renewal process. However, in the context of global warming and the goal of promoting human health and well-being, urban renewal should follow the principle of minimal intervention, draw inspiration from the condition of the climate and environment itself, and pursue the goal of common health and development between humans and non-human beings. This study takes the Panjiayuan Antique Market as the research object. Unlike previous studies that focused on the behavior patterns of vendors and buyers, this study focuses on the increase in users’ expectation on environmental thermal comfort when the Panjiayuan Antique Market transforms from a conventional commercial market into an urban public space. This study aimed to find a minimal intervention strategy suitable for urban public space renewal from the perspective of the microclimate, encouraging people to use outdoor public spaces more, thereby promoting physical and mental health, as well as social well-being. We used a mixed-methods approach comprising microclimate measurements, questionnaires (n = 254), and field measurements. Our results show that the mean radiant temperature (T_mrt) is the key factor that affects thermal comfort, and it is a comprehensive concept that is associated with other microclimate factors. Linking the quantitative sun-related factors, such as the solar position angle (SAA), the shadow area ratio (SAR), and direct sun hours (DSHs), we also found that the correlation between the T_mrt and physical spatial characteristics, such as the ratio of the visible sky (SVF), the aspect ratio (H/W), and orientation of the building layout, helped us to generate design strategies oriented by regulating microclimate, such as controlling thermal mass/radiant heating, solar radiation, and air convection. One of the significances of this study is its development of a design method that minimizes intervention in urban public spaces from the perspective of regulating the microclimate. In addition, this study proposes a new perspective of promoting people’s health and well-being by improving outdoor thermal comfort. Full article

Solar exposure and shading critically influence outdoor thermal comfort in residential areas, yet quantitative links between spatial morphology and microclimate remain insufficiently explored in cold-region cities. This study proposes a novel morphological indicator, the Insolation Shadow Ratio (ISR), to quantify sunlight–shade dynamics and investigates its correlation with outdoor thermal comfort (UTCI) in Xi’an, China. Combining field observations, microclimate simulations, and statistical analysis, we quantified ISR and UTCI across three representative outdoor spaces in a residential area. Photographic analysis and spatial parameterization were employed to calculate hourly ISR values. Significant correlations were observed between ISR and UTCI values. The measured data showed the strongest correlation at summer solstice at site C (Spearman’s r = 0.883, p < 0.01). GAM analysis of seasonal peak correlation data revealed that an optimal UTCI comfort range of 9 °C to 26 °C, corresponding to ISR thresholds of 0.0202–0.8384, achieved the highest autumn correlation at site C (r = 0.686, p < 0.01), while effectively balancing shade cooling effects and solar accessibility. The ISR framework provides a quantifiable tool for designers to optimize outdoor thermal environments and, when enhanced by parametric modeling tools, enables them to proactively optimize thermal performance during early-stage residential planning, offering a data-driven pathway for climate-resilient outdoor space design. 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

This study investigated the synergistic effects of vegetation configurations and microclimate factors on seasonal thermal comfort in a semi-enclosed university courtyard in Wuhan, located in China’s Hot Summer and Cold Winter climate zone (Köppen: Cfa, humid subtropical). By adopting a field measurement–simulation–validation framework, spatial parameters and annual microclimate data were collected using laser distance meters and multifunctional environmental sensors. A validated ENVI-met model (grid resolution: 2 m × 2 m × 2 m, verified by field measurements for microclimate parameters) simulated 15 vegetation scenarios with varying planting patterns, evergreen–deciduous ratios (0–100%), and ground covers. The Physiological Equivalent Temperature (PET) index quantified thermal comfort improvements relative to the baseline. The optimal grid-based mixed planting configuration (40% evergreen trees + 60% deciduous trees) significantly improved winter thermal comfort by raising the PET from 9.24 °C to 15.42 °C (66.98% increase) through windbreak effects while maintaining summer thermal stability with only a 1.94% PET increase (34.60 °C to 35.27 °C) via enhanced transpiration and airflow regulation. This study provides actionable guidelines for climate-responsive courtyard design, emphasizing adaptive vegetation ratios and spatial geometry alignment. Full article

Precision irrigation requires reliable estimates of crop evapotranspiration (ET) using site-specific crop and weather data inputs. Such estimates are needed at high resolutions which have been minimally explored for heterogeneous crops such as orchards. In addition, weather information for estimating ET is very often selected from sources that do not represent conditions like heterogeneous site-specific conditions. Therefore, a study was conducted to map geospatial ET and transpiration (T) of a high-density modern apple orchard using high-resolution aerial imagery, as well as to quantify the impact of site-specific weather conditions on the estimates. Five campaigns were conducted in the 2020 growing season to acquire small unmanned aerial system (UAS)-based thermal and multispectral imagery data. The imagery and open-field weather data (solar radiation, air temperature, wind speed, relative humidity, and precipitation) inputs were used in a modified energy balance (UASM-1 approach) extracted from the Mapping ET at High Resolution with Internalized Calibration (METRIC) model. Tree trunk water potential measurements were used as reference to evaluate T estimates mapped using the UASM-1 approach. UASM-1-derived T estimates had very strong correlations (Pearson correlation [r]: 0.85) with the ground-reference measurements. Ground reference measurements also had strong agreement with the reference ET calculated using the Penman–Monteith method and in situ weather data (r: 0.89). UASM-1-based ET and T estimates were also similar to conventional Landsat-METRIC (LM) and the standard crop coefficient approaches, respectively, showing correlation in the range of 0.82–0.95 and normalized root mean square differences [RMSD] of 13–16%. UASM-1 was then modified (termed as UASM-2) to ingest a locally calibrated leaf area index function. This modification deviated the components of the energy balance by ~13.5% but not the final T estimates (r: 1, RMSD: 5%). Next, impacts of representative and non-representative weather information were also evaluated on crop water uses estimates. For this, UASM-2 was used to evaluate the effects of weather data inputs acquired from sources near and within the orchard block on T estimates. Minimal variations in T estimates were observed for weather data inputs from open-field stations at 1 and 3 km where correlation coefficients (r) ranged within 0.85–0.97 and RMSD within 3–13% relative to the station at the orchard-center (5 m above ground level). Overall, the results suggest that weather data from within 5 km radius of orchard site, with similar topography and microclimate attributes, when used in conjunction with high-resolution aerial imagery could be useful for reliable apple canopy transpiration estimation for pertinent site-specific irrigation management. Full article

In response to the demands of climate change and urban sustainability, urban green space construction in China has rapidly expanded, while simultaneously giving rise to allergenic pollen pollution. Focusing on the central urban area of Xi’an, Shaanxi Province, China, this study utilizes urban surveys, field measurements, and pollen particle microscopy to analyze the seasonal variation in allergenic pollen pollution concentrations and the physical dispersion characteristics of allergenic pollen particles in residential areas. The study also examines the impact of urban residential area spatial layout on regulating allergenic pollen pollution. The results show that (1) allergenic pollen pollution in Xi’an’s residential areas exhibits significant seasonal characteristics, with spring, summer, and autumn being the primary seasons. The highest concentrations occur in spring, dominated by tree pollen, followed by summer and autumn with a predominance of herbaceous pollen. (2) Pollution concentrations in residential areas are affected by the diurnal temperature variation, with higher concentrations observed in public green spaces compared to residential green spaces and roadside green spaces. (3) Allergenic pollen pollution shows a layered characteristic in the vertical direction, with concentrations concentrated around 13 m above ground due to the effects of diurnal temperature variation and local microclimate. (4) Urban pollen pollution concentrations are positively correlated with high temperatures and negatively correlated with high humidity, while local circulations influence pollen dispersion concentrations in residential areas. (5) Design indicators such as plot ratio and building stagger affect the dispersion concentrations of allergenic pollen pollution in residential areas. The findings provide a scientific basis for optimizing residential area spatial design to mitigate allergenic pollen pollution and offer strategic guidance for improving the health and livability of urban environments. Full article

Ribbon waterfront parks in hot summer and cold winter regions play a crucial role in microclimate regulation and thermal comfort enhancement due to the combined effects of water bodies and vegetation. This study focuses on ribbon waterfront parks in Hefei. This study investigates the influence of park environmental factors (e.g., plant community characteristics, spatial configuration of water bodies, and plaza layouts) on the summer thermal environment through field measurements and ENVI-met numerical simulations. Based on field studies and a literature review, five environmental factors were selected as test variables: water body direction (S), tree planting density and arrangement (A), square distribution form (B), square location (C), and pavement material (D). Using orthogonal testing, 64 different environmental scenarios under four distinct water body orientations were designed and simulated using ENVI-met (Version 5.6.1), followed by a quantitative analysis of the simulation results. The findings reveal that the interaction between water body orientation and prevailing wind direction significantly influences the cooling efficiency in both the upwind and downwind regions. In addition, through orthogonal testing, Range Analysis (RA), and analysis of variance (ANOVA), the order of magnitude of the effect of each experimental factor on the Universal Thermal Climate Index (UTCI) can be derived: density and form of tree planting (A) > pavement material (D) > location of the square in the park (C) > forms of distribution of squares in the park (B). Finally, this study suggests various environmental factor-setting schemes for ribbon waterfront parks that are tailored to distinct microclimatic requirements. It also provides design recommendations to improve thermal comfort in parks based on the orientation of different water bodies. Furthermore, it offers specific references and foundations for planning, designing, optimising, and renovating waterfront parks of similar scales. Full article

Urban green spaces play a crucial role in mitigating the effects of urban microclimates. This study quantitatively explored how the spatial structural parameters of plant communities regulate microclimates during the hot summer in Zhuji City, Zhejiang Province. Field measurements and ENVI-met simulations were conducted to evaluate the microclimatic effects of different plant communities, including broadleaf and coniferous tree communities. Microclimatic variables, such as air temperature, relative humidity, and solar radiation, were analyzed. The results revealed that spatial structural parameters, such as Acanopy/H, sky view factor (SVF), and canopy density, significantly affected temperature reduction and humidity increase. Among these, the canopy-to-height ratio (Acanopy/H) was a promising potential factor influencing cooling. Simulations revealed that with a constant tree height, cooling and humidification benefits increased as Acanopy/H increased. However, with a constant canopy area, these benefits were greater when Acanopy/H ratio decreased. This study emphasizes the importance of spatial structural parameters in optimizing summer microclimatic regulation, providing key insights into urban green space design to enhance thermal comfort. These findings can guide the planning of climate-resilient plant landscapes in subtropical cities. Full article

As urbanization accelerates, the urban heat island effect and residents’ mental health issues are becoming increasingly severe. This study aims to explore the impact of the Urban Food Forest Program on urban environmental comfort, the mitigation of the heat island effect, and the mental health of middle-aged and elderly residents. The research methods include on-site field measurements and questionnaire surveys, which were used to analyze the environmental comfort of green spaces in urban heat island hotspots and assess participants’ mental health. The results indicate that the Urban Food Forest Program significantly reduced the surrounding environmental temperature, particularly in soil areas, with an average cooling effect of 2.4 °C. Regarding the mitigation of the heat island effect, the program effectively lowered the intensity of the heat island effect in surrounding areas, reducing it by 15%. Green spaces showed a notable positive impact on improving the urban microclimate, especially in alleviating the heat island effect. The mental health survey results revealed that male participants had significantly higher mental health scores than female participants (p = 0.017). Middle-aged and elderly individuals who participated in activities more than five times per week exhibited significantly better mental health, with their scores being 17% higher than those of the low-frequency participants. However, this study has several limitations. The relatively small sample size and limited observation period may affect the generalizability of the findings. Additionally, the study focused on a specific urban area, which may not fully represent the broader urban context. Future research should aim to expand the sample size, extend the observation period, and explore the impact of the Urban Food Forest Program in different urban settings to verify the findings’ robustness and applicability. Based on these findings, future efforts should focus on expanding green coverage, enhancing humidity regulation, and encouraging greater social and outdoor participation among middle-aged and elderly populations. Specifically, increasing activity frequency and promoting social interactions can further improve urban environmental quality and residents’ well-being. Full article

Amid global warming and urbanization, outdoor thermal comfort has become a critical consideration in landscape architecture. This study integrates a systematic review and bibliometric analysis of 1417 empirical studies (1980–2024) sourced from Web of Science, aiming to clarify the current state of research, identify core themes, and propose future directions. This study examines key evaluation models, the influence of spatial morphology, and their practical applications using keyword co-occurrence, citation networks, and thematic analyses. Findings show a significant rise in research over the past decade, particularly in tropical and subtropical regions. Core themes include thermal comfort indices (PMV, PET, and UTCI), microclimate regulation, and important spatial indicators (height-to-width ratio, sky view factor, and greening). The field is increasingly shifting towards simulation tools (such as ENVI-met and CFD) rather than traditional field measurements, with artificial intelligence emerging as a tool for predictive and regulatory purposes, though its application remains limited. However, much of the research focuses on small-scale morphological optimization and lacks a systematic framework for spatial representation. Future research should prioritize developing a comprehensive evaluation system adaptable to diverse landscapes, investigating the interplay between spatial form and thermal comfort, and advancing sustainable, low-carbon design strategies. The insights from this study provide a solid foundation for improving outdoor thermal comfort and guiding sustainable urban development through landscape architecture. Full article

The optical properties of urban envelope materials play a significant role in determining the energy balance of cities. The effective management of solar energy through these materials can help mitigate the urban heat island effect (UHI) and improve thermal comfort in urban spaces. The main objective of this study is to determine reliable methodologies for the optical characterization of opaque façade and pavement materials within urban enclosures. These methodologies should be cost-effective for implementation in emerging economies, enabling the collection of precise data for the development of urban energy simulation models. A social neighborhood in the city of Mendoza, Argentina, was selected as the case study. The optical properties of façade and pavement materials were characterized by spectrometric analysis (solar and visible reflectance, color coordinates) and in situ thermal emissivity. This research provides essential data for the development of more precise building and city simulation models, as well as for the identification of optimal materials to replace existing ones in the pursuit of strategies to reduce energy demand and enhance the urban microclimate. Full article

Solar greenhouses are essential facilities for agricultural production in northern China, where uneven internal environments pose significant challenges. This study established a numerical model of photothermal conditions in solar greenhouses. Utilizing COMSOL Multiphysics^TM, we established a microclimate model that encompasses the greenhouse exterior and the soil directly below it, without considering the crops. This model coupled multiphysical fields with fluid flow and heat transfer processes. The boundary conditions and initial values of the external environment and soil were derived from meteorological data and an efficient interpolation function method, with the time step updated every 1h. The results demonstrate that the simulated values were in good agreement with the measured values. Our findings reveal the temporal dynamics of radiation and temperature changes, as well as spatial heterogeneity, within solar greenhouses under different winter weather conditions. Additionally, the potential of integrating with other real-time monitoring and control models was discussed. This study provides a theoretical foundation for developing microclimate models and predicting photothermal environments in greenhouses. Full article

Agroforestry systems can influence the occurrence and abundance of pests and diseases because integrating crops with trees or other vegetation can create diverse microclimates that may either enhance or inhibit their development. This study analyzes the severity of coffee rust in two agroforestry systems in the provinces of Jaén and San Ignacio in the department of Cajamarca (Peru). This research used a quantitative descriptive approach, and 319 photographs were collected with a professional camera during field trips. The photographs were segmented, classified and analyzed using the deep learning MobileNet and VGG16 transfer learning models with two methods for measuring rust severity from SENASA Peru and SENASICA Mexico. The results reported that grade 1 is the most prevalent rust severity according to the SENASA methodology (1 to 5% of the leaf affected) and SENASICA Mexico (0 to 2% of the leaf affected). Moreover, the proposed MobileNet model presented the best classification accuracy rate of 94% over 50 epochs. This research demonstrates the capacity of machine learning algorithms in disease diagnosis, which could be an alternative to help experts quantify the severity of coffee rust in coffee trees and broadens the field of research for future low-cost computational tools for disease recognition and classification Full article