Urban Microclimate Research Articles

The Concurrent Effect of Building Height Diversity and Cool Pavement Materials on Air Temperature Near the Surface of an Urban Facade: A Case Study of Shahriar Street In Esfahan, Iran

The rise in urban temperatures is a significant threat to the urban heat island effect, increasing building energy demand. This increase is worrisome because the supply of renewable energy is a big challenge. The approach to improving the urban microclimate offers a promising solution. This research investigates the concurrent effect of urban morphological parameters and physical characteristics of urban surfaces, such as cool materials, on the urban microclimate near the building's facades in an urban street. This evaluation was conducted by ENVI-met(v4). The results show that the concurrent effects of increasing building height diversity and by using cool pavement materials are more helpful in reducing the average air temperature of an urban street. Because the amount of shade and wind speed increased as building height variety increased, the absorption of solar radiation decreased as pavement material albedo increased. As a result, these two parameters reduced air temperature by 0.8 °C. Also in the combined scenario of increasing building height diversity and by using cool pavement materials, the air temperature near the building's facades was reduced by 1°C on the first and second floors and by approximately 0.5°C on the upper floors.

The Synergistic Relationship between Urban Building Energy Performance, Microclimate, and Urban Elements

The Synergistic Relationship between Urban Building Energy Performance, Microclimate, and Urban Elements

A mathematical model for rapid estimation of solar radiation in urban canyons with trees and its applications

Street-level solar radiation estimation can help to better understand the influence of solar radiation on urban microclimate, outdoor thermal comfort and health, solar energy utilization, and building energy savings. However, existing urban canyon radiation models based on Monte Carlo ray tracing are challenging to apply in real practice due to limited applicability and high computational efforts. A flexible and robust mathematical model for solar radiation in urban canyons is proposed in this study to estimate solar radiation potential at the street level quickly and can be applied to the urban scale. The newly developed model considers the effect of trees on street canyon radiative transfer based on some assumptions and simplifications. Using the matrix method to resolve the infinite number of multi-reflections, the model accurately predicts solar radiation inside the street canyon compared to experimental data. The maximum root mean square error (RMSE) in the model prediction is 52.7 W/m2 and 14.5 W/m2, respectively, for urban canyons without and with trees in the studied case. And the Pearson correlation coefficient (r) is above 0.987 for all scenarios. An open-source Python script module for the model application is provided and can be integrated with other models or software platforms. The model has been used to estimate solar potential on the street and urban scales taking Chongqing city, China as an example. It is proven that the model is helpful for rapid assessment of solar radiation at the street and urban scales, serving urban design and planning.

An analytical urban temperature model with building heterogeneity using geometric optical theory

The enhancement of the living conditions in big cities since the end of the last century is closely related to changes in the thermal environment and besides in urban microclimate, particularly for metropolitan areas. In this context, a knowledge of the spatial and temporal variability of urban heat island (UHI) became an increasing matter of concern, which can be measured from land surface temperature (LST). Actually, LST can be derived from thermal infrared (TIR) remote sensing observations to ensure the necessary spatial and time frequency coverage. But a full exploitation of satellite TIR data cannot be achieved without accounting for the strong anisotropy of urban landscape. Hitherto, a poor investigation was focused on the modeling and the analysis of the directional anisotropies of LSTs considering the complexity of urban building surfaces (e.g., heterogeneity of building morphology and temperature distribution) whereas it is fundamental to establish reliable critical indicators derived from energy balance. Herein, we propose an analytical model to simulate the angular signatures of urban temperatures, in which the geometric optical theory is considered to model the direct radiances of the main components (i.e., sunlit and shaded street, roof and wall). The built model assumes a random distribution of low/middle-rise and high-rise buildings, which depicts realistically the heterogeneity of urban architectural distribution. We evaluated the proposed model using both measured datasets from airborne and satellite sensors and a simulated dataset from a 3D ray-tracing model so-called discrete anisotropic radiative transfer (DART). Results indicate that 1) the proposed model is effective for simulating directional anisotropies of LSTs, with a root mean square error (RMSE) lower than 0.90 °C and R2 > 0.49 for comparison with measured datasets; and 2) the directional anisotropies of LSTs are significantly affected by variations in building height, with values possibly exceeding 1.5 °C. The proposed model can be perceived as a useful tool to analyze the contribution of each component and to assess the impact of urban structure. Furthermore, it can serve to improve urban radiation budget estimations in mixed pixels.

METHODS OF APPLYING THE ENVIRONMENTAL APPROACH IN ARCHITECTURAL DESIGN IN MODERN RESIDENTIAL COMPLEXES

The purpose of this work is the design of the environment and landscapes associated with human life, requires, on the one hand, taking into account the values and potential of the environment, and on the other hand, taking into account human needs. This design of the environment must be persistently pursued through interaction and balance with the environment. The purpose of this study was to propose strategies for applying an ecological approach to architectural design in modern residential complexes. The research method is descriptive-analytical and applied. Performing this study, both field and documentary methods, data were collected, analyzed and integrated. In order to highlight Weakness and internal weakness, as well as external opportunities and threats, we used the SWOT analysis model, identifying the most preferred design strategies, as well as integrating the landscapes of the external and internal environment using the QSPM matrix. The results showed that the most preferred strategy for designing open areas and landscapes with an ecological vision and improving visual quality is the approach of spatial and visual continuation with the internal atmosphere of residential complexes. Today it has become obvious that in large cities of the Earth the natural component of the environment is noticeably reduced and a particularly topical issue, for the past decades, is the appeal of the world architectural community to the environmental aspects of design and construction, contributing to the comfortable, sustainable development of urban space favorable social and environmental logical microclimate of the architectural environment.

Setting up the ENVI-met digital tool to evaluate climatic conditions at an urban scale: a case study of Djelfa, Algeria

Urbanization has radically transformed natural landscapes, giving rise to complex urban environments worldwide. This transformation poses unique challenges in terms of climatic conditions. We emphasize the crucial importance of understanding urban microclimates shaped by geographical, architectural and human factors, requiring meticulous management for sustainable urban planning. These multifaceted factors interact to produce spatial variations in solar exposure, temperature and wind conditions, leading to distinct microclimatic pockets within cities. This underlines the imperative need for sustainable urban planning and design that takes account of their impact. Our field survey is located in Djelfa, Algeria, featuring a semi-arid to arid climate with continental influences. This article presents a methodology involving a detailed morphological analysis of the urban fabric, focusing on its structure, vegetation cover and spatial characteristics. It describes the use of ENVI-met, a powerful microclimate simulation tool offering a complete three-dimensional modeling system that integrates various urban elements, including buildings, streets and green spaces. Our spatial considerations guarantee model accuracy, with a rigorous geometry validation process maintaining model fidelity. The tool produces invaluable output data, including air temperature, relative humidity and thermal comfort indices. This paper emphasizes on the application of the model in Djelfa, Algeria, highlighting its potential in evaluating thermal condition in urban environments. The results of our study highlight significant temperature and humidity disparities between urbanized and green areas in the survey area, with temperature differences of up to 6°C during the day. Urbanized areas consistently have higher air temperatures and lower humidity levels, particularly during the day. Conversely, green spaces, including gardens and tree-lined areas, exhibit lower temperatures and higher humidity levels, offering valuable respite from heat stress. The use of the Physiological Equivalent Temperature (PET) index allows us to assess thermal comfort, revealing variations in heat stress levels across the urban landscape. This research highlights the crucial importance of integrating green infrastructure into urban planning to improve thermal comfort and livability in cities. Furthermore, our study reveals the value of advanced tools like ENVI-met in understanding urban microclimates and provides valuable information for sustainable urban development and climate adaptation strategies.

Field Measurement of the Dynamic Interaction between Urban Surfaces and Microclimates in Humid Subtropical Climates with Multiple Sensors.

Forcing pathways between urban surfaces (impervious and pervious pavers) and near-surface air temperature were measured and investigated with a network of multiple sensors. Utilizing field data measured between April 2021 and May 2022, and assuming that the influential variables follow the basic heat-transfer energy-balance equations, multiple regression-based statistical models were built to predict the surface temperature and near-surface air temperature (0.05 m, 0.5 m, 1 m, 2 m, and 3 m) of one impervious paver site and one pervious paver site in Taipei City, Taiwan. Evaporative cooling was found to be more influential on the pervious paver with a statistically significant influence on the microclimate up to 1.8 m (and up to 0.7 m for the impervious paver), using in situ data with an ambient air temperature higher than 24 °C. The surface temperature is mainly affected by solar shortwave radiation and ambient air temperature. As for near-surface air temperature, ambient air temperature is the most influential factor, followed by surface temperature. The importance of surface temperature indicates the influence of upwelling longwave radiation on the microclimate. The predictive equations show that pervious surfaces can help cities with hot and humid climates fight the changing climate in the future.

Spatial Indices for Convivial Greenstreets

Streetside gardening is an informal, resident-initiated activity undertaken in dense urban areas worldwide. Yardless urban areas with a high incidence of informal streetside gardening are called Convivial Greenstreets (CG). Site investigations in European and several U.S. cities over the last decade suggest that social, ecological, and local climate benefits may be found where CG are most intense. The aim of this research is to fill a gap in the research literature by better understanding the spatial distribution of CG and the potential benefits associated with them. Using inner-core neighborhoods in Delft, The Netherlands, and Philadelphia, USA, as test cases, we devised a Convivial Greenstreet Intensity (CGI) index to provide a consistent method for mapping and comparing levels of streetside gardening activity across neighborhoods and cities. We show that CG spatial patterning and quantification of informal gardening intensity using in situ documentation and integrated GIS and Google Earth analyses are feasible and should prove useful as a basis for further research. With the development of a reliable method for measuring and mapping informal streetside gardening activity with a focus on visually accessible biomass, we hope that opportunities for investigating links between convivial greenstreets and urban microclimatic and physical and mental health will be facilitated.

DEEPURBANMODELLER (DUM): A PROCESS-INFORMED NEURAL ARCHITECTURE FOR HIGH-PRECISION URBAN SURFACE TEMPERATURE PREDICTION

Abstract. High-resoulution downscaling of surface climate metrics like urban surface temperature, is a crucial and ongoing research challenge in urban climatology and environmental studies. In this study we propose a groundbreaking Physics-Inspired Neural Architecture for Modeling (PINAM) called DeepUrbanModeller(DUM), designed specifically for urban microclimate temperature estimation. DeepUrbanModeller(DUM) harnesses process-based modelling and satellite remote sensing, and draws upon high-accuracy 3D point clouds to deliver precise estimations of urban Land Surface Temperature (LST) at ultra-high resolutions. By incorporating high-accuracy land surface geometric data sourced from 3D point clouds and guided by the principles of atmospheric physics linked to surface temperature, DeepUrbanModeller(DUM) creates a data-driven framework, informed by physical laws, to accurately model high-resolution temperature distributions a task challenging for numerical simulations or conventional machine learning. The DeepUrbanModeller(DUM) design integrates two key components: Global Physical Feature Interpretation (GPFI) and Local Urban Surface Insight (LUSI). The GPFI captures broader urban physical parameters, ensuring the estimates comply with relevant physical laws. The LUSI enhances estimation performance at high-resolution levels by utilizing a newly proposed Urban Detail Orientation Index (UDOI) derived from 3D point clouds. Experimental results demonstrate the DeepUrbanModeller(DUM)’s superior capability in estimating urban LST on a detailed 30-by-30 meter grid, achieving an estimation error of less than 0.2 Kelvin compared to satellite measurements, a performance surpassing traditional methodologies.

Urban Forest and Urban Microclimate

Urban environments are challenging places for urban greenspaces, especially for trees, which have the greatest impact on ecosystem service provisions [...]

A Review of Thermal Comfort Evaluation and Improvement in Urban Outdoor Spaces

Urban outdoor space is an important activity place for residents, and its thermal environment directly affects residents’ quality of life and physical and mental health. Due to global climate change and the acceleration of urbanization, the outdoor thermal comfort of urban residents has seriously declined, causing more and more scholars to pay attention to this problem and to carry out research. This paper summarizes the development history and evaluation principles of outdoor thermal comfort evaluation indices and sorts out the methods for achieving outdoor thermal comfort. This paper reviews the effects of urban climate, local microclimate, physiological, psychological, social, and cultural factors on outdoor thermal comfort. In addition, strategies for improving thermal comfort in urban outdoor spaces are discussed from the aspects of urban geometry, vegetation, surface materials, and water bodies. Finally, the existing problems and development directions of current urban outdoor space thermal comfort studies are pointed out. This review paper can provide a reference for the scientific planning and construction of urban outdoor spaces to improve people’s thermal comfort.

Assessing the benefits and management of urban forest in supporting low carbon city in Jakarta, Indonesia

Abstract. Aulia R, Kaswanto, Arifin HS, Mosyaftiani A, Syasita N, Wahyu A, Wiyoga H. 2023. Assessing the benefits and management of urban forest in supporting low carbon city in Jakarta, Indonesia. Biodiversitas 24: 6151-6159. Climate change is a phenomenon that has become a global concern including in urban areas. Jakarta is one of the most populated cities in Indonesia, reaching 10.56 million people in 2020 with high emissions levels due to high human activities. Thus, efforts to reduce carbon emissions to mitigate climate change are necessary in Jakarta one of which is through the concept of low carbon city and manifested in the establishment of Green Open Space (GOS), including urban forests. Urban forests aim to sequester and store carbon, and improve the urban microclimate. This research aimed to assess the benefits of urban forests in Jakarta in term of their capacity in carbon sequestration using i-Tree Eco tool, and analyse the management of urban forests related to the applicable regulations. To collect data on trees, this study created 49 plots scattered across Srengseng Urban Forest, Cipayung Urban Forest, Munjul Urban Forest, Rawa Malang Urban Forest, and Pondok Labu Urban Forest. Tree species, Diameter at Breast Height (DBH), total tree height, live tree height, crown base height, crown width, percent crown loss, and crown light exposure were all gathered. Furthermore, in-depth interviews with urban forest managers were performed to gather additional information on present management, including questions derived from Jakarta's green open space legislation to assess management efficacy. The results of the analysis of urban forest quality show that the health status of trees is one of the factors that indicate the quality of urban forests at the five study sites, with more than 50% of the total trees in fair condition (75- 90% health). The gross carbon sequestration of trees in five urban forests Jakarta is about 184.8 metric tons of carbon per year. Additionally, the in-depth interviews also test the mortality of the urban forest, a decent indicator of current management with estimates over the next 10 years, showing a slight increase in carbon sequestration and storage capacity. However, the mortality scenario leads to a trend toward a decrease in leaf area and the number of tree categories, especially in the Srengseng Urban Forest.

The vitality of native grassland plants in current urban climatic conditions in Gauteng, South Africa

Plants are essential components of urban microclimates, as they can help mitigate some of the adverse effects of urbanisation, enhance environmental quality, and thus contribute to overall species well-being and the sustainability of cities. Urban planners and policymakers often incorporate green infrastructure and urban greening into their strategies to create healthier and more livable urban environments. Plants are primary producers, serving as a baseline for the attraction and habitat of other species; they also provide vital ecosystem services, such as climate amelioration. Landscape designers and horticulturalists can influence plant selection through built environment interventions, increasing urban ecosystem services and benefits. Based on the evidence of native plant preferences by insects and people and their natural adaptation to regional climatic extremes, we tested, through an experimental study, the potential of native grassland plants to survive in assemblages in current urban environments. The study specifically monitored the tolerance of nine native grassland plant species to urban environments over six months in Gauteng, South Africa. A stratified random sampling was done by monitoring permanent quadrats in two purposefully engineered urban native gardens. Plant vitality was evaluated using chlorophyll a fluorescence. General climate data were obtained from a local weather station. Microclimatic temperature and humidity data were collected at each site and quadrat using Hygrochron High-Resolution Temperature and Humidity data loggers. The results indicated that all nine native plant species functioned with good photosynthetic health and can be recommended as resilient species that tolerate current urban conditions. Correlation studies indicated that two forb species, Haplocarpha lyrata and Scabiosa columbaria, showed great tolerance to current urban conditions. This vitality is likely contributed to their winter dormancy morphologically based on below-ground biomass, and their physiological adaptation to tolerate both wet and dry habitat conditions. This points to the potential of grassland forb species for urban use and the potential for climate adaptation in grassland areas.

Crown Density Relationship to Microclimate and Comfort Index in Telaga Sari City Forest, Balikpapan, East Kalimantan, Indonesia

The development of urban areas that are increasingly developing causes the area of green open space to decrease, and urban buildings that are increasingly denser result in an increase in local temperatures in the city. The presence of vegetation will provide cooler air. Furthermore, the urban microclimate is an interesting thing to correlate with the presence of vegetation somewhere. The Telaga Sari City Forest is one of Balikpapan’s green open space places. This research analyz the relationship between crown density microclimate and comfort index. The method for the percentage of crown density used Habitapp App. To measure the microclimate used Thermohygrometer, and Lux Meter. From the research results, it is known that, at the Telaga Sari City Forest there is a strong relationship between crown density and microclimate, namely light intensity, temperature, humidity, and the comfort index/THI, successively the multiple R values of 0.87, 0.83, 0.78 and 0.81. The linear equations namely y = -23.677x + 1986, y = -0.0317x + 31.096, y = 0.119x + 65.891 and y = -0.0232x + 29.007. In order to create a favorable microclimate in the city and provide green open space, it required to plant trees with high canopy density values.

Estimation of gridded anthropogenic heat flux at the optimal scale by integrating SDGSAT-1 nighttime lights and geospatial data

Diverse human activities in megaregions have generated excellent anthropogenic heat (AH), which disrupts the urban energy balance and affects the urban climate. However, few studies have investigated the spatial scale effect (SSE) of estimating the multi-source AH flux (QF). Hence, this study proposes a method, i.e., a nighttime light index (NTLI)-based top-down inventory model, to investigate the optimal spatial scale (So) for estimating multi-source gridded QF at the county level and mapping gridded products for the central region of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) megaregion in 2018. The method combines the multi-scale (10–500 m) enhanced NTLI with a top-down inventory model. We generated the enhanced NTLI by integrating the Sustainable Development Science Satellite 1 (SDGSAT-1) nighttime lights (NTL), points of interest, and road network data. Then we analyzed the SSE of QF estimation to determine the So and evaluated the accuracy and characteristics of multi-source QF at the So. The results showed that (1) the So of estimation for six heat components varied between 10 m and 450 m, which related to the difference in energy source and spatial pattern; (2) considering the estimation accuracy, numerical characteristics, and spatial detail of critical urban features, the So of QF was 300 m; (3) the proposed method reduced the estimation error of QF more effectively than the NTL-based inventory model. The root mean square error (RMSE) decreased by 2.45–21.20 %, and the goodness of fit (R2) increased by 2.17–13.66 % among six heat components; and (4) our multi-source QF product at 300 m outperformed previous QF products in spatial heterogeneity and numerical accuracy. This study first explored the SSE of QF estimation and captured the spatial and numerical information of multi-source QF at the So, which could provide valuable knowledge for urban micro-climate.

Impact of Tree Leaf Area Density on Cooling and Ventilation of an Urban Neighborhood

The impact of trees during heat waves can be diverse, as their interaction with their surroundings depends on several parameters that modify shading, ventilation potential and transpiration rate. A multiscale coupled model is presented that allows the detailed analysis of the local impact of vegetation as a mitigation measure for urban heat islands. A case study is performed on an urban neighborhood in Zurich, Switzerland, with an aim to improve the understanding of physical processes in urban microclimate subjected to a heat wave. A parametric study presents the impact of varying the leaf area density (LAD) of the existing trees in the neighborhood. Comparisons of surface temperatures and rate of transpiration with available measured data show a good agreement. The results show that urban trees can reduce heat storage during the day due to shadowing, especially when they are in groups. The reduction in air temperature due to transpiration largely depends on LAD, wind-flow patterns and urban morphology. The results also indicate locations with an increase in air temperature due to the presence of trees.

Fourier neural operator for real-time simulation of 3D dynamic urban microclimate

Global urbanization has underscored the significance of urban microclimates for human comfort, health, and building/urban energy efficiency. However, analyzing urban microclimates requires considering a complex array of outdoor parameters within computational domains at the city scale over a longer period than indoors. As a result, numerical methods like Computational Fluid Dynamics (CFD) become computationally expensive when evaluating the impact of urban microclimates. The rise of deep learning techniques has opened new opportunities for accelerating the modeling of complex nonlinear interactions and system dynamics. Recently, the Fourier Neural Operator (FNO) has been shown to be very promising in accelerating solving the Partial Differential Equations (PDEs) and modeling fluid dynamic systems. In this work, we apply the FNO network for real-time three-dimensional (3D) urban microclimate simulation. For modeling large-scale urban microclimate problems, CityFFD simulates urban microclimate features based on the semi-Lagrangian approach and fractional stepping method with the Smagorinsky large eddy simulation model. In our simulation, the 1200 sequential time steps are used as training data. We retain and analyze the data from all stages, including the spin-up period, because we wish to understand how the flow develops transiently from initial conditions, and both one-step and sequential timestep predictions are analyzed. When applied to unseen data with different wind directions, the FNO model has a 0.3% one-step prediction error and a maximum error of 5%. A real-time simulation of urban microclimates in 3D is possible with the FNO approach, which is 25 times faster than the traditional numerical solver.

Seasonal characteristics of outdoor thermal comfort and residential electricity consumption: A Snapshot in Bangkok Metropolitan Area

Outdoor thermal comfort negatively influences urban residents’ health and increases residential electricity consumption (REC) for cooling demand. This study adopted the remote sensing-based modified temperature-humidity index (MTHI) to monitor and assess seasonal and spatial characteristics of urban thermal comfort and its association with REC. Thermal comfort and REC have a strong correlation (p < 0.05) and the same seasonal patterns as regional climate patterns. Thermal comfort is mainly controlled by land use, land cover (LULC), and physical characteristics of the built environments. Among the physical features, the building height is the most prominent element stimulating thermal discomfort as it regulates other elements linking to urban microclimates, such as sky view factor and ventilation. The thermal comfort in a particular region will be remarkably improved when urban density and building height remain under 65.43% and 17.88 meters, respectively. A green space proportion above 18.9% is also a reference value to optimize thermal comfort in built environments. The most vulnerable regions because of thermal discomfort in the Bangkok Metropolitan Area (BMA) account for 21.4% of the dense urban centers, with a building density of 72.5% and a population density of 17,173 persons/km2. The research findings enrich the current knowledge of thermal comfort characteristics and REC, which are significantly helpful for regional planning to mitigate thermal discomfort in this megacity.

The Role of Urban Vegetation in Counteracting Overheating in Different Urban Textures

With growing global concerns about climate change, the significance of urban greenery in architecture and urban planning is becoming increasingly apparent. Urban vegetation naturally cools cities, provides comfort and clean air, and has positive social, health, and economic effects. It is essential to ensure passive thermal comfort and safeguard biodiversity. It is widely recognized that urban greenery not only withstands severe outdoor climatic events, but also symbiotically interacts with buildings and citizens. Several studies demonstrated the potential of vegetation to provide outdoor thermal comfort, air purification, noise reduction, and various other ecosystem services. To emphasize the potential of urban green spaces to interact with the local urban morphology in terms of microclimatic aspects, the research examines the dynamic connection between various urban textures and urban green spaces. This study emphasizes how urban green spaces, such as parks, green spaces, and urban greenery, respond to temperature variations in both the present scenario and the projected future. Central to this contribution is the examination of the relationship between urban vegetation and its potential to reduce and counteract urban overheating in both current and projected future scenarios. The aim is to evaluate the effectiveness of urban vegetation compared to dense urban textures. The interaction between urban block morphology, building types, vegetation, and microclimates is presented here for comparative assessment, highlighting the different thermal behaviour and outdoor comfort responses in various urban areas in current and projected scenarios. Using a microclimatic simulation tool, the research will delve deeper into the potential and constraints associated with the role of urban greens in addressing the increasing temperatures in climate change. This paper presents a comparative microclimatic evaluation of two selected green areas in Parma, Italy, within different urban contexts. The evaluation compares the current situation with a projected future scenario (2050) to determine the most effective factors for mitigating overheating phenomena in existing cities.

The interactive indoor-outdoor building energy modeling for enhancing the predictions of urban microclimates and building energy demands

There is a lack of an urban building energy modeling framework that considers the influence of surrounding buildings and local urban climate on building thermal performance. This can lead to inaccurate results since the thermal performance of individual buildings is heavily influenced by their surrounding built and climatic environment. This study establishes an interactive indoor-outdoor building energy modeling method to enhance the predictions of urban microclimates and building energy demands by coupling an urban physics model with a physics-based building energy model. Validation of the interactive coupling scheme uses field measurement datasets. Parametric simulation and analysis are conducted to understand the influence of the roof-to-canyon width ratio, canyon orientation, and ground vegetation fraction on canyon temperature, building energy consumption, and energy demand. Furthermore, the impacts of building energy model complexity (e.g., detailed vs. simplified building models) and coupling approaches on canyon temperature and building energy profiles are demonstrated using two case study buildings. In comparison with the one-way coupling approach, cooling energy consumption predicted with the dynamic two-way coupling approach varies by 3.5 % and 0.5 % for the detailed medium office building model and high-rise building model, respectively, and peak cooling demand varies by 8.4 % and 7.0 % for the detailed medium office building model and high-rise building model, respectively. This study also suggests that adopting a complex two-way coupling approach with environmental data exchange at various elevations is necessary for modeling tall buildings at the urban scale.