Erratum to “Enhancing urban heat island mitigation in region 12 Tehran: integrating greenery and high albedo materials for improved thermal comfort” [Energy Build. 339 (2025) 115724

As cities and their population are subjected to climate change and urban heat islands, it is paramount to have the means to understand the local urban climate and propose mitigation measures, especially at neighbourhood, local and building scales. A framework is presented, where the urban climate is studied by coupling a meteorological model to a building-resolved local urban climate model, and where an urban climate model is coupled to a building energy simulation model. The urban climate model allows for studies at local scale, combining modelling of wind and buoyancy with computational fluid dynamics, radiative exchange and heat and mass transport in porous materials including evaporative cooling at street canyon and neighbourhood scale. This coupled model takes into account the hygrothermal behaviour of porous materials and vegetation subjected to variations of wetting, sun, wind, humidity and temperature. The model is driven by climate predictions from a mesoscale meteorological model including urban parametrisation. Building energy demand, such as cooling demand during heat waves, can be evaluated. This integrated approach not only allows for the design of adapted buildings, but also urban environments that can mitigate the negative effects of future climate change and increased urban heat islands. Mitigation solutions for urban heat island effect and heat waves, including vegetation, evaporative cooling pavements and neighbourhood morphology, are assessed in terms of pedestrian comfort and building (cooling) energy consumption.

Ignoring Urban Heat Island (UHI) effects may lead to an underestimation of the building cooling demand. This study investigates the impact of the UHI on the cooling demand in hot-humid cities, employing the Local Climate Zones (LCZs) classification framework combined with the Urban Weather Generator (UWG) model to simulate UHI effects and improve building performance simulations. The primary aim of this research is to quantify the influence of different LCZs within urban environments on variations in the cooling energy demand, particularly during heat waves, and to explore how these effects can be incorporated into building energy models. The findings reveal significant discrepancies in both the average and peak cooling demand when UHI effects are ignored, especially during nighttime. The most intense UHI effect was observed in LCZ 2.1, characterized by compact mid-rise and high-rise buildings, leading to a cooling demand increase of more than 20% compared to suburban data during the heat waves. Additionally, building envelope thermal performance was found to influence cooling demand variability, with improved thermal properties reducing energy consumption and stabilizing demand. This research contributes to the theoretical understanding of how urban microclimates affect building energy consumption by integrating LCZ classification with UHI simulation, offering a more accurate approach for building energy predictions. Practically, it highlights the importance of incorporating LCZs into building energy simulations and provides a framework that can be adapted to cities with different climatic conditions, urban forms, and development patterns. This methodology can be generalized to regions other than hot-humid areas, offering insights for improving energy efficiency, mitigating UHI effects, and guiding urban planning strategies to reduce the building energy demand in diverse environments.

Assessing Impact of Material Transition and Thermal Comfort Models on Embodied and Operational Energy in Vernacular Dwellings (India)

Sensitivity analysis of physical parameterizations in WRF for urban climate simulations and heat island mitigation in Montreal

Trade-off between urban heat island mitigation and air quality in urban valleys

Data-driven optimization reveals the impact of Urban Heat Island effect on the retrofit potential of building envelopes

High albedo materials to counteract heat waves in cities: An assessment of meteorology, buildings energy needs and pedestrian thermal comfort

Urban Heat Island (UHI) mitigation research has been carried out for a long time but it requires to be sharpened to enrich mitigation strategies. In Bandung, maximum temperature has been increasing from 330C to 350C in 30 years. Bandung is getting hotter which can exaggerate the negative impact of UHI mainly in the downtown area. Suitable UHI mitigation strategies are needed to lower urban temperature. UHI mitigation has involved the use of heat-absorbing and covering man-made materials with vegetation such as green wall and roof system. Content analysis of UHI precedents and some preliminary studies are applied to assess prerequisites of UHI mitigation. The analysis showed adaptation opportunities of UHI mitigation strategy on buildings and environmental physical components. The mitigation strategies may vary depending on the typology of buildings (roof and wall) by using reflective materials, while outside the building by increasing vegetation to maximize evaporation to lower the temperature.

Urban design has a profound impact on the local climate, which can result in changes in temperature distribution and energy demand. The Urban Heat Island (UHI), a well-documented issue where cities typically experience higher temperatures than the cooler rural surroundings that envelop them, is closely tied to urban design and its geometrical features. This increase in temperature can lead to increased energy consumption, particularly for air conditioning, as populations strive to maintain thermal comfort. Within this framework, this paper seeks to advance our comprehension of the influence of urban design on the Urban Heat Island (UHI) effect and building energy requirements. It makes a valuable contribution to the expanding body of research in this field, offering insightful guidance on optimal urban design strategies tailored to diverse climate zones in Morocco. To achieve these goals, we explore multiple urban design scenarios incorporating variations in building heights, street aspect ratios, building layout configurations, and street orientations. We employ the Urban Weather Generator and EnergyPlus for our analysis, with the former enabling the generation of synthetic weather data that accounts for the UHI effect in urban contexts, and the latter facilitating building energy simulations. The simulation results reveal a wide-ranging hourly variation in Urban Heat Island (UHI) intensity, spanning from 11°C to -5°C across the cities under study. Among these cities, Ifrane, Marrakesh, and Fes exhibit the highest average annual UHI intensity. Incorporating UHI considerations into energy simulations has yielded notable outcomes. Low-rise buildings experience a reduction in total energy requirements, while mid-rise and high-rise buildings exhibit an increase. For instance, adopting an urban design scenario featuring 20-story buildings and a street aspect ratio of 0.33 led to a rise in total energy demands between 8% and 19%. Furthermore, the street aspect ratio (H/W) emerges as the primary driver of UHI, whereas street orientation and building layout exert the most substantial influence on building energy requirements. Inefficient building layouts result in a significant increase in building energy needs, ranging from 106% to 121%, while less energy-efficient street orientations lead to total energy needs escalating by 28% to 76%.

Impact of urban form on building energy consumption in different climate zones of China

To improve the building’s energy efficiency many parameters should be assessed considering the building envelope, energy loads, occupation, and HVAC systems. Fenestration is among the most important variables impacting residential building indoor temperatures. So, it is crucial to use the most optimal energy-efficient window glazing in buildings to reduce energy consumption and at the same time provide visual daylight comfort and thermal comfort. Many studies have focused on the improvement of building energy efficiency focusing on the building envelope or the heating, ventilation, and cooling systems. But just a few studies have focused on studying the effect of glazing on building energy consumption. Thus, this paper aims to study the influence of different glazing types on the building’s heating and cooling energy consumption. A real case study building located under a semi-arid climate was used. The building energy model has been conducted using the OpenStudio simulation engine. Building indoor temperature was calibrated using ASHRAE’s statistical indices. Then a comparative analysis was conducted using seven different types of windows including single, double, and triple glazing filled with air and argon. Tripleglazed and double-glazed windows with argon space offer 37% and 32% of annual energy savings. It should be stressed that the methodology developed in this paper could be useful for further studies to improve building energy efficiency using optimal window glazing.

Dense cities usually experience the urban heat island (UHI) effect, resulting in higher ambient temperatures and increased cooling loads. However, the typical lack of combining climatic variables with building passive design parameters in significant evaluations hinders the consideration of the UHI effect during the building design stage. In that regard, a global sensitivity analysis was conducted to assess the significance of climatic variables and building design features in building energy simulations for an office building. Additionally, this study examines the UHI effect on building energy performance in Qatar, a hot-arid climate, using both measurement data and computational modeling. This study collects measurement data across Qatar and conducts computational fluid dynamics (CFD) simulations; the results from both methods serve as inputs in building energy simulation (BES). The results demonstrate that space cooling demand is more sensitive to ambient temperature than other climatic parameters, building thermal properties, etc. The UHI intensity is high during hot and transition seasons and reaches a maximum of 13 °C. BES results show a 10% increase in cooling energy demand for an office building due to the UHI effect on a hot day. The results of this study enable more informed decision-making during the building design process.

Despite the known effects of UHI on building energy consumption, there is currently a lack of generalizable methods to incorporate UHI into building energy simulations (BES) for accurate energy performance evaluation of urban buildings. The absence of generalizable methods is mainly due to the complex and interconnected relationships among the urban built environment, UHI and building energy performance which not only determine the magnitude of UHI intensity, but also its effects on the energy performance of buildings. With the overarching aim of enabling a generalizable UHI-BES integration method, this literature review examines the relationships between urban morphology, UHI and building energy consumption to determine the knowledge gaps that hinder the development of a robust and generalizable integration method. More specifically, this literature review presents a critical analysis of methods and data sources used in the existing literature to (1) derive UHI intensity based on urban built environment attributes, and (2) analyze the effect of calculated UHI intensities on the cooling, heating, and annual energy consumption of buildings. Methods and materials used by various studies are examined given their potentials for generalizability, level of accuracy and application possibility for BES purposes. Practical applications This review serves as a practical roadmap of the entire methodology of research focusing on relationship between urban morphology, UHI and building energy performance and may serve as a guideline to building professions who intend to incorporate UHI for more accurate energy analyses. Furthermore, the review identifies the various databases, software programs and methodological options to guide the future research as well as industry practice on the topic.

Effect of green wall installation on urban heat island and building energy use: A climate-informed systematic literature review

Detailed parametric analysis and measurements are required to reduce building energy usage while maintaining acceptable thermal conditions. This research suggested a system that combines Building Information Modeling (BIM), machine learning, and the non-dominated sorting genetic algorithm-II (NSGA II) to investigate the impact of building factors on energy usage and find the optimal design. A plugin is developed to receive sensor data and export all necessary information from BIM to MSSQL and Excel. The BIM model was imported to IDA Indoor Climate and Energy (IDA ICE) to execute an energy consumption simulation and then a pairwise test to produce the sample data set. To study the data set and develop a prediction model between building factors and energy usage, 11 machine learning algorithms are used. The best algorithm was Group Least Square Support Vector Machine (GLSSVM), later employed in NSGA II as the building energy consumption fitness function using Dynamo software. An NSGA II multi-objective optimization model is designed to reduce building energy consumption and optimize interior thermal comfort (measured by the predicted percentage of dissatisfied (PPD)). The Pareto front is calculated, and the optimum point approach is used to find the best combination of building envelope characteristics, HVAC setpoints, shading parameters, lighting, and air infiltration. The feasibility and effectiveness of the developed framework are demonstrated using a case study of an upper secondary school building in Norway; the results show that: (1) The GLSSVM has a unique capacity to forecast building energy use with high accuracy: R2 of 0.99, an RMSE of 1.2, MSE of 1.44, and MAE of 0.89; (2) Building energy consumption and thermal comfort may be successfully improved by the GLSSVM-NSGA II hybrid technique, which reduces energy consumption by 37.5% and increases thermal comfort by 33.5%, respectively.