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The relationship between urban geometry and microclimate is crucial in urban planning and climatology, significantly affecting outdoor comfort and energy consumption. Compact, dense buildings provide shading in summer, while openness is preferred in winter to maximize sunlight access. Courtyards, as climate-responsive structures, can create localized microclimates tailored to specific climatic conditions. Various components, including geometry, openness, orientation, wall materials, and green cover, influence the microclimate within a courtyard. While previous studies have primarily focused on hot and arid climates, there is a notable research gap concerning the thermal behavior of courtyards in cold and semi-arid regions. This study seeks to fill this gap by evaluating the impact of different courtyard geometries on outdoor thermal comfort specifically in semi-dry and cold climates by exploring optimal configurations for orientation, form, height-to-width ratios, and plan aspect ratios, the research offers strategies that improve both summer and winter microclimates. The study examined the combined effects of geometry and orientation on shading and wind speed in courtyards, modeling their influence on microclimates during warm summers and cold winters using ENVI-met software. Thermal performance indices, specifically PET and UTCI, were employed to assess the courtyards in Tehran. The findings reveal that a height-to-width ratio of 3:1 significantly improves thermal comfort, resulting in a UTCI difference of 19 °C. Furthermore, the model with a 2:1 plan aspect ratio exhibited a UTCI that was 6.7 °C lower than that of the 3:1 ratio. These findings provide valuable insights for designing contemporary courtyards that optimize thermal comfort in similar climates. • ENVI-met simulates geometric effects on courtyard comfort in cold semi-arid climates. • North-south oriented courtyards enhance thermal comfort in cold conditions. • Height-to-width ratio of 3:1 enhances thermal comfort, yielding a 19 °C UTCI difference. • The UTCI is 6.7 °C lower in the model with an aspect ratio of 2:1 than 3.1 (L/W). • Aspect ratios of 1:1 and 2:1 minimize discomfort in both winter and summer. [ABSTRACT FROM AUTHOR]

As the European Union transitions towards cleaner energy production, significant emphasis is placed on the use of photovoltaic (PV) panels on roofs. Although PV panels offer the advantage of renewable energy generation, they alter the energy balance of roofs and increase heat emissions into the atmosphere. This raises concerns about their potential to intensify the urban heat island (UHI). Hence, this study evaluates the effects of eight different roof models, including four roof types, analyzed both with and without PV panels, on the UHI in the Mediterranean, a region experiencing increasingly urban overheating. Convective heat fluxes are used as a clear indicator. The models were conducted using EnergyPlus simulations throughout the year. Roof types include a typical Mediterranean roof, a cool roof, a soil roof and an extensive green roof. The main results indicate an intensification of the UHI for all roof types when PV panels are installed, both in summer and winter. However, among the PV-panelled roof types, the cool roof is effective in reducing the UHI impact compared to the other roofs during both seasons. Contrary, in winter, the extensive green roof with PV panels increases the impact on the UHI among all roof types the strongest. • PV panels increase UHI impact across all roof types. • Non-irrigated green roofs with PV panels do not reduce UHI impact. • Unirrigated green roofs have the highest UHI impact in winter. • Cool roofs, with or without PV panels, mitigate UHI impact. [ABSTRACT FROM AUTHOR]

Intra-urban induced heating (IUIH) in hot desert cities exhibits distinct patterns and complex diurnal interactions with built environment features, differing significantly from those in temperate areas and remains not fully understood. Understanding how various built environment features contribute to intra-urban thermal variability is an essential first step in developing sub-diurnal targeted heat mitigation strategies. This study presents a data-driven examination of IUIH dynamics in Kuwait's desert metropolis. Near-surface air temperature observations were collected using high-resolution loop-type traverses at selected hours during a representative summer day to determine IUIH variability. The diurnal impacts of built environment features were modeled using an ensemble learning approach and interpreted with SHapley Additive exPlanations. Among several candidate machine learning regressors evaluated, Random Forest demonstrated strong predictive power (R2 = 0.954) with acceptable error (RMSE = 0.096, MAPE = 0.001) and least bias (MBE = 0.008). The study's significance lies in its assessment framework that emphasizes explainability of sub-diurnal dynamics, offering detailed insights that challenge traditional assumptions and inform both immediate local climate interventions and strategic urban planning. The findings reveal that simple day-evening comparatives might overlook nuanced sub-diurnal dynamics, such as potential irrigation-induced warming by shrubs observed at mid-day and the complex trade-offs between radiative and transpirative processes by trees in the afternoon and evening. Additionally, the study identifies cooling effects associated with natural land cover, presenting a critical optimization challenge between compact and open urban forms to effectively modulate near-surface air temperatures. • Targeted heat mitigation can benefit from intra-urban and sub-diurnal analysis. • Intra-urban induced heating examined using tree-based ensemble models. • Predictive power of RF models strongest at 2 km buffers (R2 = 0.95, RMSE = 0.1 °C). • Day-evening comparatives underestimate predictor-response dynamics. • Findings underscore temporal considerations in urban climate interventions. [ABSTRACT FROM AUTHOR]

The development of integrated urban services requires the implementation of informative tools that provide a balance between quality, time and costs for air quality assessment. Within this framework, three modeling techniques with different levels of complexity were compared during a winter inversion episode against PM 10 concentrations measured in a built-up area in Prague (Czech Republic) characterized by heavy traffic. Although the Gaussian model ATEM satisfied the common statistical-performance criteria, the predictions poorly represented the spatial variability of concentrations in the study domain. The Lagrangian model GRAL provided a better simulation of the effects of terrain and vortice formation inside street canyons, but tended to overpredict the influence of these phenomena. Finally, the most sophisticated of the three models, the Large-Eddy Simulation model PALM, demonstrated the best performance based on an exhaustive analysis of the model outputs in the temporal and spatial dimensions. After model comparison, a sensitivity test of the selected models to the driving meteorology and emissions inputs was carried out. While advanced models can simulate complex urban environments, their suitability for use in urban planning is subject to further considerations, such as computational cost, user expertise, and the usefulness of the output. Thanks to increasing computation power and intensive work on the entire modeling chain, sophisticated models could become routine tools for use in regulatory applications, contributing to future integrated urban service provision. • Selection of dispersion models should include a spatio-temporal assessment. • Meteorological input and resuspension emissions are important sources of uncertainty. • LES models provide a thorough set of data valuable for integrated urban services. [ABSTRACT FROM AUTHOR]

The relationship between urban form and localized air temperature has been studied extensively using linear regression. However, the findings remain inconsistent, and few studies have explored alternative data modeling techniques. With the rise of machine learning, there is an opportunity to explore new methods in urban climatology research. This study aims to test the hypothesis that machine learning models, rather than linear regression, can better explain and predict urban air temperature fluctuations in space and time. Measurements of air temperature were conducted at street level in Hong Kong. Urban form characteristics surrounding the measurement locations were extracted from geo-spatial databases and street view imagery. The datasets were then used to test the performance of linear regression, Artificial Neural Network (ANN), and Random Forest (RF) in predicting the spatial-temporal temperature fluctuations. The results indicate that the relationships between urban form and air temperature are predominantly non-linear. Both ANN and RF outperformed linear regression in prediction, with an MAE of 0.43 °C and 0.33 °C respectively. This study highlights the potentials of machine learning models in advancing knowledge of the impact of urban form on localized air temperature. • Machine learning algorithms were used to model localized air temperature in urban street canyons. • 4000+ temperature measurements were obtained in Hong Kong using mobile and stationary sensors. • The relationship between air temperature and surrounding urban form was predominantly non-linear. • The mean absolute error for RF prediction is 0.33 °C, 0.43°Cfor ANN, both outperformed regression. • There is a need to scrutinize data modeling techniques in the study of urban heat and urban form. [ABSTRACT FROM AUTHOR]

Because of climate change, present-day buildings will be subject to more extreme conditions by the end of the century. Indoor overheating will increase in summer, resulting in severe thermal discomfort or significant cooling needs to avoid heat stress. Existing buildings therefore need to be adapted. However, current renovation strategies are generally aimed at reducing heating energy consumption. This study presents a methodology for assessing the impact of climate change during summer and heatwave periods on indoor overheating of an existing building within an urban context. The proposed methodology is applied to the case study of a French urban dwelling within an energy-efficient renovated building. The thermo-aeraulic dwelling model built on TRNSYS and CONTAM, as well as the urban heat island model implemented on UWG, are calibrated and validated thanks to a field measurement campaign of a multi-family building in Lyon during the summer of 2022. Results show that thermal discomfort will rise sharply by the end of the century, and could reach extreme levels in the worst emission scenario. Use of windows and solar protections allows to reduce the percentage of time over 28 °C from 40 % to 54 % depending on the future scenario. Ventilation by opening windows, which is the most commonly used cooling passive strategies, continue to be essential to reduce indoor overheating in high insulated building under future climates. However, its efficiency is very dependent of occupant behaviour. [Display omitted] • Meteorological files of the future climate of an urban district are generated. • Dwelling and UHI models are calibrated and validated using in-situ measurements. • Indoor thermal discomfort is expected to rise sharply with climate change. • Ventilation is essential to limit overheating in energy-efficient dwellings. [ABSTRACT FROM AUTHOR]

With climate change affecting buildings differently across various local climates, there's a heightened focus on local microclimates and their impact on building energy consumption. Urban microclimates change the buildings' energy dynamics by influencing local weather patterns while building operations affect these patterns and microclimates through feedback. This paper provides a comprehensive review of tools and applications used for examining the feedback interaction between building operation and energy, and urban microclimate. This study collects, analyses, and classifies tools and applications related to Urban Building Energy Modeling (UBEM) and Urban Climate Modeling (UCM) and particularly focuses on the combination of these tools through Multi-Domain Urban Scale Energy Modeling (MD-USEM), enabling efficient information exchange between urban microclimate and building energy models. The building-microclimate exchange of information may occur as either a one-way impact or a two-way interaction, a distinction that is thoroughly examined in the final section with an in-depth analysis of the relevant literature. • Urban Building Energy Modeling and Urban Climate Modeling tools are presented. • Co-Simulation strategies for coupling microclimate and building are reviewed. • Three types of the reciprocal impacts of microclimate and building are discussed. • Building-microclimate information exchange is assessed through MD-USEM application. [ABSTRACT FROM AUTHOR]

The land surface temperature (LST) of urban streets is significantly influenced by the surrounding urban environment. In the cold areas of northern China, this influence exhibits a seasonal pattern. Currently, in areas with noticeable seasonal variations, the coupling effects of urban elements on the annual stability of street LST remain unclear. This study developed a new metric, Normalized Winter-Summer Land Surface Temperature Difference, to measure the year-round LST stability of campus streets. Three key urban elements affecting street-level LST in winter and summer were identified: building, vegetation, and land. The influencing characteristics for winter and summer LST were quantified and ranked respectively. The study reveals that the green space ratio dominates summer LST, while fraction vegetation coverage, leaf area index and average building height dominate winter LST. We found that morphological characteristics of buildings and vegetation cannot fully explain the impact of the urban physical environment on street-level LST. For winter street LST studies, greater emphasis should be placed on non-morphological characteristics and land. Based on the impact mechanisms and critical thresholds of key features in winter and summer, this study establishes an interpretable spatial classification method. By assigning seasonal weights to influencing features, it provides comprehensive design strategies that consider both winter and summer features to enhance annual LST stability and climate resilience in urban spaces facing extreme meteorological conditions. • A new metric for assessing LST stability of streets in cold areas was developed. • Design strategies to improve annual street LST stability were proposed. • Morphological features can't fully explain the urban elements' impact on street LST. • Street LST research should emphasis non-morphological characteristics, especially in winter. • Consider non-morphological characteristics in street LST studies to avoid potential biases. [ABSTRACT FROM AUTHOR]

Climate change is expected to aggravate urban microclimatic conditions and have adverse effects on human morbidity and mortality. However, there is limited knowledge on the impact of climate change on urban microclimate and human health for actual urban areas. In this study, we investigate the impact of climate change on urban microclimate and pedestrian thermal comfort within a complex district in Nicosia, Cyprus. Two climatic scenarios are considered: (i) current scenario based on meteorological conditions derived from field measurements performed in 2010, and (ii) future scenario for which meteorological conditions of 2050 are based on downscaled Regional Climate Models (RCMs). URANS CFD simulations are performed for the period of 9–10 July with a 1-h time-step. The results show that by 2050, the maximum air temperature at the pedestrian height of the case study area can increase by 2.3 °C which can increase heat-related mortality by more than 240 %. The UTCI is expected to significantly increase especially in the afternoon hours with up to a 4.3 °C increase at 20:00. The "very strong heat stress" conditions (UTCI: 38–46 °C) are expected to prevail for a longer period during the day, increasing from 3.3 to 6.6 h. In addition, the "extreme heat stress" conditions (UTCI: >46 °C) are expected to apply in parts of the area. This prolonged exposure to heat stress can incite additional health risks. • Computational framework for analysis of future urban microclimate. • Assessment of climate change impact on urban microclimate. • Investigation of future outdoor thermal comfort and heat-related mortality. • Air temperature can increase by 2.3 °C leading to 240 % increase of mortality. • Most significant UTCI increase is in the afternoon hours reaching up to 4.3 °C. [ABSTRACT FROM AUTHOR]

Urban spatial expansion is a critical aspect of urbanization, but it must occur in a manner that ensures the sustainable development of the urban climate. The primary objective of this study was to assess the population exposure risk of urban heat island (UHI) effect from the perspective of urban spatial expansion. Additionally, the population weighted urban heat island intensity (UHII) index (Ep) was proposed to compare the population exposure risk of UHI effects in different types of urban spatial expansion in China during the summer of 2005–2020. It was found that, in China, urban land increased by an area of 74,894 km2 (1.01-fold) from 2005 to 2020. Leapfrogging emerged as the predominant pattern of urban spatial expansion and was primarily driven by the conversion of cropland to urban land. It witnessed a significant increase in the area covered by UHIs of 107,119 km2 (1.20-fold), accompanied by a rise in the UHII of 0.12 °C in China. Notably, the UHII for infilling urban expansion was significantly higher at 2.03 °C, in contrast to 1.66 °C for edge expansion and 1.47 °C for leapfrogging. Correspondingly, the Ep was markedly larger under the infilling urban expansion (2.10 °C) in contrast to edge expansion (1.75 °C) and leapfrogging (1.67 °C). However, edge expansion dominated the newly developed urban land, contributing to 18.60 % of the Ep, which was still far less than the contribution of the pre-existing urban land to Ep (61.24 %). Importantly, the dominant driver of the increased Ep was the increasing UHII. This study established a connection between inevitable urban spatial expansion and the population exposure risk of UHI effect, providing a strong theoretical basis and practical guidance for the active adaptation and mitigation of urban environmental hazards in urban regions. • Assessing population exposure risk of UHI is crucial. • The population weighted UHII index was proposed. • Leapfrogging was the main pattern of urban spatial expansion. • The UHII and Ep for infilling urban expansion was significantly higher. • The dominant driver of the augmented Ep was the increasing UHII. [ABSTRACT FROM AUTHOR]

Rapid urbanization has altered the environment and climate, necessitating a thorough grasp of urban thermal dynamics for sustainable development. The lack of detailed urban information poses a considerable challenge. This study employs the Local Climate Zone (LCZ) framework to delve into the intricate relationship between land surface temperature (LST) zones and both 2/3D urban characteristics. The LCZ map for Bojnourd city, Iran, was prepared, consisting of eleven classes categorized into five built types and six land cover types. The mean LST in the summer of 2021 was derived from Landsat8 using the split-window algorithm (SWA) and divided into seven thermal zones. The research reveals distinctive spatial patterns of LCZs across various Land LST zones. Notably, LCZ2 (Compact mid-rise) and LCZ 3 (Compact low-rise), despite differing heights, share the same thermal zone (Zone3), suggesting influences beyond height on thermal zoning. In contrast, LCZ5 (Open midrise), situated in a cooler thermal zone (Zone2), features more vegetation and taller trees, exhibiting a lower LST range compared to LCZ2 and LCZ3. Class-level metrics (AREA_MN and LPI) offer a similar description of LCZ spatial patterns, while landscape-level metrics like SHDI and IJI provide a more insightful depiction of spatial patterns. The study found that the most appropriate spatial pattern for improving urban thermal conditions involves considering a set of factors such as vegetation presence, land cover proximity, height, and density. This ensures sustainable and green urban development that is in tune with climate change and promotes balanced and harmonious thermal patterns in the urban environment. • LCZs exhibited displayed unique spatial distributions within various LST zones. • Urban thermal environment diversity is crucial for climate change mitigation. • PLAND is key in revealing LCZ dominance and thermal zone contributions. • Neighborhood and proximity of LCZs affect thermal zone formation. • In Zone 1, the cooling effect is notably influenced by LCZ A with dense and tall trees. [ABSTRACT FROM AUTHOR]

Urban energy balance models can simulate the localized climate and fluxes in urban areas. They are often evaluated using real urban site observations. However, uncertainties in anthropogenic emission, geometry and materials can hinder interpretation. These uncertainties can be eliminated by scaled outdoor models. We assess the performance of a single-layer urban canopy model (SLUCM) offline in predicting surface energy balance (SEB) fluxes within a street canyon-like urban configuration using field measurements from a scaled outdoor setup in Guangzhou, China. We utilize observations of SEB fluxes and surface temperature from a homogenous scaled urban site characterized by street canyons. The scaled observations in June–December 2020 in a dense urban environment with a height-to-width ratio (H/W) of 2 are employed to assess seasonal variations in model performance. Additionally, the December data from two distinct urban scenarios (H/W = 2(2020) and 0.5(2019)) are utilized to compare model performance in deep and shallow street canyon settings. Results show that Q S (R 2 = ∼0.47, RMSE = ∼46.0) is the most challenging to predict, followed by Q H (R 2 = ∼0.92, RMSE = ∼65.5), Q* (R 2 = ∼0.99, RMSE = ∼39.5), L ↑(R 2 = ∼0.95, RMSE = ∼33.7), and K ↑(R 2 = ∼0.99, RMSE = ∼6.2). SLUCM faces difficulties simulating L↑ particularly during nighttime and cloudy conditions. It also tends to underestimate daytime net radiation (Q *), especially during hot, humid months. Moreover, H/W ratio slightly affects SLUCM's performance in simulating SEB fluxes under dry cool conditions denser urban settings (H/W = 2) show better model performance in K↑, Q H , and Q S but worse performance in L↑ and Q*. • ●SEB components evaluated across different seasons and skies for H/W = 2 and 0.5. • Q S is hardest to predict (R 2 = ∼0.47, RMSE = ∼46.0), followed by Q H , Q* , L ↑, K ↑. • SLUCM predicts SEB components better on cool dry days than on hot humid days. • SLUCM predicts SEB components better on clear days than cloudy days. • In cool, dry conditions SLUCM performs better for H/W = 2 case for K ↑, Q H , and Q S. [ABSTRACT FROM AUTHOR]

A thorough comprehension of moist heat (MH) variations across Local Climate Zones (LCZ) during both heat wave (HW) and non-heat waves (NHW) is crucial for mitigating heat stress in residents and urban climate. However, the LCZ-based MH differences between HW and NHW, and their climatic disparities, remain unclear. Here we investigated the heat index difference between HW and NHW (ΔHI) of LCZs across six climate zones (29 Chinese cities), based on three-year (2017–2019) hourly air temperature and relative humidity data collected from 675 stations. The results showed that (1) the ΔHI in high-rise LCZs (LCZ 1 and 4) exceeded that of mid- and low-rise LCZs (LCZ 2, 3, 5, 6, and 8) across cities, indicating that high-rise LCZs in non-shaded area face greater heat risks during HWs and therefore require special attention. Nevertheless, LCZ 9, a low-rise LCZ type, still exhibited a higher daytime ΔHI (8.2 °C) due to its high coverage of vegetation. This implies that the addition of vegetation in urban planning requires caution, and a re-evaluation of its combined effects on MH from evaporative cooling and increased humidification is quite necessary. (2) The ΔHI of LCZs peaked in the north subtropical (NS) climate zone, followed by mid subtropical and warm temperate, mid temperate, plateau temperate and south subtropical. This suggests that NS cities require greater mitigation of heat stress during HWs. We believe that these results are helpful for better understanding the MH responses of LCZs to HWs and the design of urban heat mitigation strategies. • LCZ-based HI differences between heat and non-heat waves (ΔHI) are analyzed. • ΔHI in high-rise LCZs are higher than in mid- and low-rise LCZs. • LCZ 9 exhibits a higher daytime ΔHI due to higher relative humidity. • ΔHI peaks in the north subtropical climate zone. [ABSTRACT FROM AUTHOR]

Improving the urban wind climate yields substantial advantages, encompassing enhanced public health, increased pedestrian safety, improved building energy efficiency, and effective heat stress mitigation. In the past two decades, the prominence of surrogate models in urban wind environment studies has grown remarkably. These models efficiently approximate dynamic wind behaviors, expediting predictions and compressing design cycles from months to days. Constructing an accurate and reliable surrogate model requires careful consideration of four crucial aspects: problem formulation, sample selection, surrogate modeling, and uncertainty quantification. Problem formulation necessitates the selection of surrogate predictors and response variables to faithfully represent the relationship between building/urban form and wind behaviors. While sample selection can be executed through four major methods, including the classic and modern design of experiment methods, adaptive and intelligent sampling method, and generative design techniques. Furthermore, this paper conducts a comprehensive review of the latest literature to juxtapose the advantages and limitations of diverse surrogate models, and it also unveils key strategies for constructing effective surrogate models. Additionally, the study underscores an often-overlooked aspect in surrogate optimization studies—the quantification of uncertainty in surrogate predictions, an important element for ensuring design robustness. To address this, we discuss three approaches for quantifying surrogate model prediction errors: deterministic, possibilistic, and probabilistic methods. Finally, we introduce a novel rule-based approach for surrogate model construction. This approach not only prioritizes robustness of surrogate models but also provides solutions for improving the urban wind environment across varying design problem scales, design sample sizes, and levels of urban airflow non-linearity. • Advancements in surrogate models applied to improve urban wind environment are systematically reviewed. • Sampling, modeling, and uncertainty quantification are summarized for surrogate construction. • Deterministic, possibilistic, and probabilistic uncertainty measures are explained. • A rule-based surrogate module selection scheme is proposed. [ABSTRACT FROM AUTHOR]

Human thermal responses can vary based on individuals' thermal histories. Although comparative studies on thermal comfort have been conducted in different regions, research is still limited regarding the differences in thermal responses among people living in the same city but having emigrated from diverse climates. Addressing this gap, this study, conducted in Beijing between 2021 and 2022, involved on-site meteorological measurements and questionnaire surveys, collecting a total of 1,370 questionnaires. The objective was to examine the differences in thermal response among individuals from different climatic backgrounds post-migration and assess the implications for urban design improvements. The study findings revealed the following: 1) Southern migrants exhibited a higher neutral Universal Thermal Climate Index (UTCI) compared to northern migrants (20.2 °C vs. 18.7 °C). 2) In terms of the acceptable temperature range (TAR) for 1 h, southern migrants showed a greater tolerance for hot conditions compared to northern migrants (4.4–30.8 °C vs. 0.6–28.6 °C), but less tolerant for cold conditions. 3) The transient acceptable range was considerably wider than the 1-h TAR. 4) Residents feeling thermally neutral at present had lower demands for urban design improvements. Our results highlight the importance of considering diversity of thermal response and implementing targeted management and planning interventions. The study is expected to provide practical recommendations for creating more livable and sustainable urban environments. • An attempt to identify the thermal responses of migrants. • Southern migrants had a higher tolerance for hot conditions than northern migrants. • The transient acceptable range was wider than 1-h acceptable range. • Current thermal sensation influences demands for urban design improvements. [ABSTRACT FROM AUTHOR]

One of the most effective, economical, environmentally friendly, and easily applied methods used to combat the overheating of urban areas is properly arranging the urban landscape. In particular, road networks play an important role in the heating of urban areas and occupy the most area among the different types of public spaces. Hence, it is evident that street landscape design methods represent a significant resource for enhancing urban climate change resilience. In this study, the effect of plantation of streets with trees on the local climate was investigated for Istanbul and Antalya in Turkey. In the comparison of these two cities, four pattern types (discrete low-rise, discrete mid-rise, discrete high-rise, compact low/mid-rise) that are common in both were used. The simulations were performed by BPNN method that used the synthetic images obtained by manipulating the original satellite images. By this way, as a result of the simulations, the synthetic surface temperature images of planted streets were obtained. The climatic changes were examined by applying thermal change detection analysis and cooling distance analysis for the streets that were planted with trees. According to these results, street tree plantation leads to a cooling effect that extends up to 50 m in Istanbul and up to 300 m in Antalya varying according to the urban pattern type. When the results were compared between the discrete pattern types, it was found that the cooling effect due to street tree planting in the low-rise was effective up to longer distances than the high-rise pattern types. • Created synthetic images are effective data that can be used to predict LST. • Using BPNN is suitable for detecting of thermal changes. • Plantation of the streets is an effective nature-based solution to cooling the cities. • In densely built-up urban centers, tree planting is an easy way to combat UHI. • Satellite images can be used for monitoring the future. [ABSTRACT FROM AUTHOR]

This paper quantifies the impacts of the Jacob K. Javits Convention Center (JJCC) green roof and the nearby redevelopment of Hudson Yards (Midtown West, Manhattan, New York City, NY) on the local microclimate. The analysis was performed using ENVI-met, a grid based, three-dimensional (3D) computational fluid dynamics model commonly used to simulate surface-plant-air interactions in urban settings. Using air temperature, relative humidity, and wind speed and direction measured onsite on July 22, 2014, a total of six simulations were run, comprising three different stages of redevelopment (e.g., in 2014, 2018, and 2021), with and without the JJCC green roof in place. Under the simulated climate conditions, the green roof reduced air temperature over the no-green roof (NoGR) condition, primarily on the north side of the JJCC. However, because of the nearby redevelopment, the cooling benefit provided by the roof decreased slightly over time. For example, at 1:00 p.m. the air temperature dropped from 0.75 K at roof level in 2014, to 0.65 K and 0.64 K in 2018 and 2021, respectively. Similarly, though to a lesser extent, the same trends were evident in the simulations at pedestrian level. The redevelopment of Hudson Yards reduced the sky view factor (SVF) and provided shading during the day, reducing daytime mean radiant temperature (MRT). However, the same buildings raised nighttime MRT. Together, the study provides insights into the growing understanding of how green roofs can impact the microclimate of complex urban environments. • Green roof's cooling efficacy was impacted by the morphology of nearby development. • Building reduced SFV and provided shade, reducing daytime and increasing nighttime MRT. • Complex interactions between buildings and green spaces define the urban microclimate. [ABSTRACT FROM AUTHOR]

The approaching wind profiles have a significant impact on the wind load of the structures as well as the urban climate, pollutant diffusion, and thermal comfort. Therefore, the study of its evolution is gaining attention as the city sparrows. This paper aims to study the effects of topography and morphology on the characteristics of the approaching wind. Wind tunnel tests were conducted to observe the mean velocity profiles downstream of three kinds of common terrain, which are roughness change from open to urban exposure, open exposure behind mountain terrain, and urban exposure behind mountain terrain. The results show that the ESDU transitional model overestimates velocity inside the IBL and underestimates IBL heights compared with experimental results. The rough exposure behind the mountain leads to smaller recirculation zones and a shorter reattachment location downstream compared with that of open exposure behind mountain. In addition, the evolution of mean velocity profiles over urban exposure behind the mountain is also compared with the results estimated according to current wind load provisions. Unfortunately, none of the current wind load provisions yields a reasonable estimation of the mean velocity profiles. The study aims to provide useful references in the study of the wind environment in mountainous urban area and the estimation of wind load on structures, as well as the future codification of wind load provisions. • New profile becomes equilibrium again at about 1175 m downstream of roughness change. • The ESDU model overestimate velocity inside the IBL and underestimate IBL heights. • Flow separates at leeward slopes between 13° and 14.5°, irrespective of roughness. • The surface roughness behind the mountain leads to smaller recirculation zones. • Current provisions lack regulations on the mean wind profile behind mountains. [ABSTRACT FROM AUTHOR]

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. • Establish an interactive coupling method between an urban microclimate model and a physics-based building energy model. • The level of building energy model complexity has limited impacts on urban canyon temperatures. • Using a complex two-way coupling approach is necessary for modeling tall buildings at an urban scale. [ABSTRACT FROM AUTHOR]

Many empirical studies have examined the relationship between urban form and canopy layer urban heat island (CUHI). However, these studies mostly have used small sample sizes and statistical methods that assume CUHI responds linearly to urban form features. Additionally, the differences in the effect of urban form on CUHI at different time instances during the diurnal cycle have not received sufficient attention. To address these issues, this study employs a relatively large sample of 1,058 microclimate sensors in Seoul, Korea, and analyzes CUHI at 9 a.m., 3 p.m., and 9 p.m. on a typical summer day. Gradient boosting decision tree (GBDT) based regression model and linear regression model and their variants with spatial information were constructed and compared for each time instance. Results show that spatially explicit GBDT models had the highest accuracy. Feature importance analysis shows that built form factors such as mean building height were more important during the afternoon, while surface fractions such as road surface fraction had greater influences during the morning and nighttime. Partial dependence plots (PDPs) show that urban form features influence CUHI in a complex nonlinear manner that varies for each time instance. PDPs were further scrutinized based on their activation and threshold effects. GBDT model findings directionally aligned with linear regression, but they provided nuanced insights into the form-CUHI relationship. These findings help planners to better understand the complexity of urban climate and intervention required to reduce CUHI magnitude across the diurnal cycle. • Nonlinearity between urban form and canyon urban heat island (CUHI) is significant. • Spatially explicit gradient boosting predicted CUHI with highest accuracy. • Nonlinearity and importance of urban form features vary during the diurnal cycle. • Policymaking regarding CUHI should consider nonlinearity and temporal variation. • Randomness in machine learning models can impact interpretability results. [ABSTRACT FROM AUTHOR]

This study analyzes inter- and intra-zonal seasonal variability of surface urban heat islands (SUHIs) within the methodological framework of local climate zones (LCZs) in three central European cities (Prague, Brno and Novi Sad). These cities differ in urban area and structure as well as in topography and hinterland land-cover features. LCZs were delineated on the basis of a GIS-based classification method. Land surface temperature (LST) was derived from LANDSAT-8 scenes in the period 2013–2018. The first step was to detect seasonal SUHI intensity differences for built LCZ types and LST for land-cover types of LCZ. The results revealed the highest differences in summer and spring, and lowest in winter. The highest SUHI intensity values occur in densely built-up and industrial zones, and the lowest in sparsely-built city outskirts. The coolest LCZs based on LST were dense trees and water areas in spring and summer. The second step aimed to analyze the effects of vegetation on SUHI formation. Hence, 11 land cover subclasses (from dense trees to bush/scrub) were defined in order to research intra-zonal seasonal LST variability. The height and density of vegetation have substantial effects on intra-zonal variability of LST in land-cover types of LCZ, whereas differences between forest subclasses were relatively low. Finally, the character of the vegetation had a substantial influence on intra-zonal LCZ variability of LST and SUHI formation. Further research in this field could contribute to better understanding of micro- and mezzo-climate-scale patterns, as well as better adaptation to climate change in urban areas. Image 1 • Statistically significant seasonal SUHI variability between LCZs. • Highest SUHI differences between built and land cover classes occurred in summer. • Regional climate and city surrounding affect SUHI during winter, spring and autumn. • Statistically significant SUHI variability within LCZ land cover classes (A−C). • Density and tree/scrub pattern, together with land cover, affect seasonal SUHI. [ABSTRACT FROM AUTHOR]

Abstract The correct contextualisation of urban measurements is one of the challenges that urban climate researchers have been dealing with for decades. The Local Climate Zones scheme (LCZs) emerges as a system for characterising these measurements from the thermal perspective. The rapid embracing of the LCZs by researchers from many disciplines, altogether with its adoption for other purposes such as planning, has led to an inexistent or, at its best, flexible use of the source area definition. This practice might call into question the contextualisation of many measurements, highlighting the imperative need to shed light on the source area methods within the urban context. In this study, a systematic review is conducted to compile previous experiences in which the source area was applied in the built environment. Results obtained from the systematic search are summarized and presented according to three scales: the inertial sublayer, the roughness sublayer, and the urban canopy layer. These previous experiences are studied according to their methodological contribution to the source area definition, emphasizing those studies that have considered this concept altogether with the LCZ scheme. This review aims at promoting the knowledge about footprint methodologies and its correct application within the LCZs. Highlights • The source area definition within urban contexts was systematically reviewed. • Differences in the footprint adoption are related with the atmospheric scale. • The embracement of the source area by LCZ studies is low and very heterogeneous. • Choosing, estimating and reporting the source area should be standardised. • Further research is needed to develop reliable footprint tools within the UCL. [ABSTRACT FROM AUTHOR]

Abstract Harm due to global warming and the heat island effect to the urban environment has attracted scholarly attention. To explore differences in the thermal environment in the city and the reasons for these, we chose 55 fixed sample points from 7 land-use categories in Xi'an City and conducted a 3-year field measurement on the meteorological data of summer. In this research, 21 sample sites with different urban spatial features were screened and the temporal and spatial variability of the heat island intensity and physiological equivalent temperature in the summer daytime analyzed. Then 15 urban spatial indicator values of the research sample sites were calculated and bivariate correlations and regression analyses employing meteorological parameters conducted to probe their relationship. Results confirm building footprint ratio as the strongest predictive factor, explaining around 66% of the air temperature variability in the city. The green cover ratio is also a strong predictive factor, explaining approximately 50% of the variability of the heat island intensity. Finally, the reasonable range of urban planning indicator values were determined according to the threshold of designer indicators in China's Design Standard for the Thermal Environment of Urban Residential Areas. Accordingly, building footprint ratio should not be greater than 23.8%, the green cover ratio should not be less than 30%, and the green space ratio should not be lower than 19.5%. This study provides recommendations for developing environmental urban planning strategies. Graphical abstract Image 1 Highlights • The intra-urban variabilities of UHI intensity and PET are considerable. • Bfr, Gcr, and Ao are the most significant variables which have effects on urban climate. • Gcr has stronger explanatory power than Gsr in the variance of UHI intensity. • Different spatial indicators have different suitable research radii for the microclimate of Xi'an. [ABSTRACT FROM AUTHOR]

Sports centers are core spaces for urban sports and fitness, and reasonable layout of large public buildings can alleviate urban climate issues. But the adverse effects of planning and layout and surrounding urban microclimate on the thermal comfort of outdoor activity space are rarely considered. In this study, an EnergyPlus and Openfoam collaborative computing platform was constructed to calculate the universal thermal climate index of the outdoor space of sports center. By comparing the simulation results of sports centers in three severely cold cities, improving the wind environment of the site's microclimate was found to be key in improving thermal comfort, and the hours of overall site thermal comfort increased mainly in spring and autumn. In this paper, a design method combining numerical simulations and a convolutional neural network was proposed, which can effectively predict the thermal comfort performance of affected sites. The application of this prediction method to the design of the Yingkou Sports Center increased the hours of overall site thermal comfort by 15.01% compared with the original scheme. Synthesizing the results and methods of this study can provide an effective reference and analysis tool for the overall environmental performance of urban areas. • Numerical simulation and CNN were combined to predict sports center layout. • The influence of sports center microclimate and surrounding was explored. • The sports center layouts' impact on the outdoor thermal comfort was revealed. • Urban form indexes improving sports center outdoor thermal comfort were obtained. • Optimized sports center layout improved the outdoor thermal comfort hours by 15%. [ABSTRACT FROM AUTHOR]

In the context of global warming, improving energy-use efficiency is an important research topic in the fields of green buildings and eco-cities. There is an indivisible coupling relationship between the urban climate and urban building energy (UBE). Urban wind environments (UWE), including urban thermal and humid environment, is widely believed to have a significant impact on building energy consumption as a key microclimate element. However, despite decades of development of the UWE calculation module in numerical simulation tools, there is still a lack of reviews on the UWE impact mechanism on UBE. In this paper, the mechanisms of UWE influence on building energy consumption, building-scale simulation tools, and city-scale simulation tools, as well as the coupling and validation methods of these tools in the past decades are reviewed. Therefore, this study can provide the necessary foundation and general workflow for building physicists and urban climatologists to simulate and analyze the impact of UWE on UBE. The problem with the current building energy model and urban building energy modelling is that the UWE is not considered comprehensively, and CFD and other methods are used to obtain accurate results. The future challenge is to improve the accuracy of the energy consumption calculation from the perspective of UWE impact, optimize the calculation module, obtain a balance between calculation speed and accuracy, and propose validation and calibration guidelines focused on UWE impact on UBE. • This review summarizes the mechanisms and basic theoretical models of UWE impact on UBE. • A general workflow for quantifying the impact of UWE on UBE is given based on UWE characteristics. • An analysis of UWE in simulation methods and numerical simulation tools is given. • Proposes a general framework for validating and calibrating the impact of UWE on UBE. [ABSTRACT FROM AUTHOR]

As an essential part of urban parks, plant communities are of great importance in regulating the urban climate. Community structures and external elements are important factors influencing the microclimate effects of urban park communities. However, it remains unclear how these two factors affect the cooling and humidification effects of coniferous and broad-leaved communities. Taking Nanhu Park (Changchun) as a case study, we conducted measurements on the microclimate effects of 40 plant communities in summer. The results demonstrated that the optimal cooling effect of the communities occurred at about 15:00, and the humidification effect remained stable in the morning and increased after 12:00. The highest average cooling and humidification values in coniferous communities reached 3.38 °C and 17.23%, respectively, whereas those in the broad-leaved communities were 3.24 °C and 17.23%, respectively. Community structures were identified as the primary factor influencing the microclimate effects of broad-leaved communities, while the intensity of microclimate effects in coniferous communities was primarily influenced by the surrounding roads and water bodies. Our study provides insights for urban planners to comprehend the synergistic interaction between internal community structures and external elements and the microclimate effects of urban park communities. [Display omitted] • Microclimate beneath canopies of coniferous and broad-leaved plant communities was investigated from 9:00 to 17:00. • The cooling and humidification abilities of coniferous and broad-leaved communities are similar. • The microclimate effect of coniferous community is dominated by the distance from communities to roads and water body. • Plant community structure is the main factor influencing the microclimate effect of broad-leaved community. [ABSTRACT FROM AUTHOR]

ENVI-met is currently one of the most popular simulation tools of urban microclimates, used by researchers and designers alike. Yet, in recent years some concerns have been raised regarding the software's capability to accurately simulate the effects of solar irradiance on increased heat stress, especially in hot weather conditions. These concerns have eventually led to the implementation of a new radiation scheme in version 5 of the software. This study set out to evaluate whether this new scheme increased the software's accuracy in evaluating incoming shortwave and longwave radiation fluxes, expressed as Mean Radiant Temperature (MRT), by comparing monitored and simulated summertime values at 60 locations. Our results show that while ENVI-met's new version improved MRT simulation accuracy, the software systematically underestimated the magnitude of MRT in both shaded and unshaded summer conditions. Our MRT evaluation resulted in an RMSE of 6.08 °C in the shade and 13.32 °C at locations fully exposed to solar radiation, which may result in inaccurate and less severe appreciation of outdoor heat stress, especially when outdoor shade is missing. Based on our analysis, we suggest that the origin of error may stem from inaccurate representation of longwave radiation fluxes emitted by ground surfaces. [Display omitted] • Version 5 of ENVI-met seemed to improve MRT simulation accuracy under hot conditions. • Nevertheless, ENVI-met consistently underestimated the effect of solar radiation on heat stress. • MRT accuracy was significantly lower in unshaded locations, compared with shaded locations. • ENVI-met results accurately represent the significant reduction in heat stress in the shade. • Calculation time may still be an impediment to wide adoption of ENVI-met in design processes. [ABSTRACT FROM AUTHOR]

Decoupling the intricate relationship between three-dimensional (3D) urban morphology and local climate is paramount importance in the realm of adaptive urban planning. Research based on Local Climate Zone (LCZ) has exhibited promising potential for disentangling the interactive mechanisms between urban morphology and local climate. In this study, generative adversarial networks (GAN) were employed as surrogate models to facilitate the integration of LCZ and urban morphology data from six metropolises for associative training. Through comparative experiments involving quantitative and qualitative evaluations, a rapid and responsive 3D morphology prediction model was developed for LCZ classifications. The results demonstrated the superior convergence capabilities and accuracy of the Pix2pix model (RMSE = 0.187 and R2 = 0.878) when compared to the CycleGAN model (RMSE = 0.344 and R2 = 0.674). The predicted 3D morphologies showcased a pronounced alignment with their respective LCZs, as evidenced by the precise representation of open low-rise buildings and their interrelationships with the coastline in the Sydney sample, as well as the accurate portrayal of the complex urban morphology shaped by compact high-rise buildings and road networks in the Tokyo sample. Utilizing indices calculated from the 3D morphology, the model yielded an average overall accuracy (OA), kappa coefficient, and F1 score of 85.2%, 0.83, and 0.86, respectively, indicating the robustness and adaptability of the model. The framework presented in this research offers practitioners a solid foundation and valuable insights for enhancing the local climate in urban areas through the implementation of 3D generative design techniques. [Display omitted] • A GAN-based generation framework in response to LCZ classification was proposed. • The paired-image datasets of six cities were constructed to train the GAN models. • The Pix2pix model outperformed better than CycleGAN in terms of RMSE and R2. • The accuracy of LCZ calculated from 3D models proved the robustness of the method. [ABSTRACT FROM AUTHOR]

Heatwaves threaten human health and power systems. Urban climate is non-stationary and wide-spectrum, with high-frequency temperature and wind-speed variations that could overload power grids and expose people to extreme heat. In this study, Hilbert-Huang transform (HHT) was unprecedentedly used to decompose the urban-scale temperature (IMFθ 1 to IMFθ 6) and wind-speed (IMFW 1 to IMFW 6) signals during a 5-day heatwave event into 6 intrinsic mode functions (IMFs). The spatio-temporal characteristics, physical mechanism, and effective ranges of high-frequency components (IMF1 to IMF4) were unveiled. Temperature (wind speed) IMFθ 1 to IMFθ 4 (IMFW 1 to IMFW 4) had a temporal scale of 2.63 h (2.53 h), 5.88 h (5.78 h), 13.16 h (9.84 h), and 22.72 h (19.05 h); as well as a spatial scale of 2.31 km (0.99 km), 4.29 km (1.65 km), 5.94 km (2.64 km), and 6.6 km (2.97 km), respectively. The physical mechanisms of IMF1 to IMF4 were composed of turbulence and heat storage/release; disturbance induced by mountainous terrain and slope flows; land/sea breeze, together with anthropogenic heat. Besides, the peaked amplitudes of IMFθ 1 were most risky in compact/open high-rise urban (1.4 °C–1.6 °C) rather than rural (0.6 °C–1.0 °C) areas. The foothill areas within 8-km coverage were susceptible to IMFθ 2 (1 °C–2.1 °C). IMFθ 3 (0.6 °C–3.6 °C) was effective in urban areas within 10 km from coastline. IMFθ 4 (2.5 °C–3.5 °C) exhibited the most intense fluctuation in urban/suburban areas. The outcome provides references for policy makers to mitigate heat-related risks. [Display omitted] • HHT is applied to decompose short-term urban climate signals during a heatwave event. • Risky, high-frequency components of temperature and wind speed were extracted. • Spatio-temporal scales of high-frequency meteorological components were examined. • Implication from buildings, terrain, land/sea breeze, and anthropogenic heat to IMFs. • Revealed the effective ranges and susceptible urban areas for high-frequency components. [ABSTRACT FROM AUTHOR]

High-rise buildings have been promoted in high-density cities. The impact degree of urban high-rises on the building energy demand at the urban block scale is determined by many factors, including the effects of the vertical meteorological pattern (VMP), which have been discussed insufficiently. In this study, the VMP of urban areas in Xi'an, China was observed, and a building energy simulation model that revealed the "urban block form–outdoor climate–building energy" nexus was developed with the URBANopt plugin on the Grasshopper platform. The impacts of the VMP on the building heating and cooling energy demands of different urban blocks were then predicted. In January, the VMP led to building heating load increases of 0.7–1.6 kWh/m2 (16–52%) and 0.0–1.1 kWh/m2 (0–35%) in the residential and mixed-use blocks, respectively. In July, the ranges of the building cooling load changes produced by the effects of the VMP were 0.0–0.1 kWh/m2 (0–1%) and −0.3–0.2 kWh/m2 (−2%) in the residential and mixed-use blocks, respectively. Furthermore, the VMP affected the relationship between the urban block form and the building energy demand. Based on the relationship, we provided form-optimization advice for different functional urban blocks. The urban high-rise mechanisms in high-density cities and their impacts on the building energy demand were discovered in this study. This can help decision-makers to optimize urban planning while promoting urban sustainability. • A vertical meteorological pattern (VMP) for building energy simulations is developed. • Effects of VMP increase the building heating loads of urban blocks by 52% maximally. • Effects of VMP decrease the building cooling loads of urban blocks by 2% maximally. • Impacts of VMP on the block form – building energy demand relationship are evaluated. [ABSTRACT FROM AUTHOR]

Natural ventilation is an energy-efficient approach to reduce the need for mechanical ventilation and air conditioning in buildings. However, traditionally weather data for building energy simulation are obtained from rural areas, which do not reflect the urban micrometeorological conditions. This study combines the Surface Urban Energy and Water Balance Scheme (SUEWS) and EnergyPlus to predict natural ventilation potential (NVP) and cooling energy saving in three idealised urban neighbourhoods with different urban densities in five Chinese cities of different climate zones. SUEWS downscales the meteorological inputs required by EnergyPlus, including air temperature, relative humidity, and wind speed profiles. The findings indicate that NVP and cooling energy saving differences between urban and rural areas are climate- and season-dependent. During summer, the urban-rural differences in natural ventilation hours are −43% to 10% (cf. rural) across all climates, while in spring/autumn, they range from −7% to 36%. The study also suggests that single-sided ventilation can be as effective as cross ventilation for buildings in dense urban areas. Our findings highlight the importance of considering local or neighbourhood-scale climate when evaluating NVP. We demonstrate a method to enhance NVP prediction accuracy in urban regions using EnergyPlus, which can contribute to achieving low-carbon building design. • SUEWS and EnergyPlus combined to evaluate urban buildings' natural ventilation potential. • Climate, building area fraction and season all influence natural ventilation potential. • Single-sided ventilation can be as effective as cross ventilation in dense urban areas. [ABSTRACT FROM AUTHOR]

Abstract Urban heat island (UHI) shows thermal intensification in urban areas compared to surrounding areas. Land surface temperature (LST) has been widely applied in assessing UHI. However, due to limitations of the LST retrieval method, few researchers attempted to track the long-term dynamics of UHI and their responses to progressive urbanization process based on Landsat series data. In this study, we improved the retrieval method to extract the average UHI intensity of Hangzhou city core in 1990–2010, and explored the dynamics of UHI composition and configuration in response to urbanization. Google Earth Engine (GEE) was applied to calculate the average UHI intensity in the study area. Hangzhou city core was heating up in study period with extensive conversions from neutral and cool area to heated area. The expansion of heated area initially radiated from the original urban core in linear configuration, and subsequently expanded to infill areas away from the core by replacing neutral and cool area. The significant differences in average UHI intensity between different land use and land cover (LULC) types can be observed: urban land had the highest value whereas forest and water body registered the lowest. The expansion of urban land at the expense of natural land had exceeded a threshold to induce spillover of heat energy from the former to the latter. The findings can inform nature-based solutions to optimize the thermal environment and livability of fast-growing subtropical cities. Highlights • Google Earth Engine calculated average UHI intensity to avoid cloud-cover data gaps. • Hangzhou city core converted notably from neutral & cool to heated area in 1990–2010. • Urban land had highest average UHI intensity whereas forest and water body the lowest. • Heated-area expansion increased its high overlay rate with urban land through time. • Urban-land expansion and natural-land shrinkage induced heat spilling to the latter. [ABSTRACT FROM AUTHOR]

The long-term impact of rapid urbanization on air temperature (T a ), relative humidity (RH), vapor pressure (VP) and human thermal comfort in the Cairo governorate of Egypt was analyzed. Land use change (LUC) between 1973 and 2017 were derived from Landsat satellite data. Next, non-parametric change point and trend detection algorithms were applied to T a , RH and VP over 1950–2017 to estimate the impacts of urbanization on urban climate. Three historical thermal comfort indices: temperature humidity index (THI), effective temperature index (ETI) and relative strain index (RSI) were estimated from climate data collected between 1950 and 2017 to assess the impact of urbanization on human thermal comfort. The results reveal substantial LUC, rapid increasing impervious surface areas in low-lying areas of Cairo at 75.2 km 2 /decade since the 1990s. Rapid urbanization had resulted in a statistically significant change point in T a after 1995 with a warming trend of 0.19 °C/decade, a negative trend in RH of 0.55%/decade and a rising trend in VP of 0.24 hPa/decade. Severe heat stress levels emerged and persisted every July–September since 1994. THI, ETI, and RSI show statistically significant change points at 1994 and a rising trend of 0.33 °C/decade, 0.29 °C/decade, and 0.06/decade, respectively. The highest thermal discomfort risk was found in urban areas of the old Cairo, but the risk is marginally smaller at new cities where there are vegetation covers. This study clearly demonstrates the impacts of rapid urbanization on the urban climate of hot-arid environment. [ABSTRACT FROM AUTHOR]

Pedestrian-level wind environment in urban areas has a significant impact on the quality of urban dwellers' daily life. For pedestrian-level wind studies in severe cold regions, the cooling effect of wind and related thermal discomfort in winter is quite significant. However, thermal effects of wind are not considered in most wind comfort studies and wind comfort generally only refers to the mechanical effects of wind on people. Therefore, particular consideration is given to the chilling effect of wind on exposed skin and risk of frostbite in winter, and a wind chill criterion based on the wind chill temperature is proposed in this study. The pedestrian-level wind conditions in seven representative residential areas summarized from cities in severe cold regions of China are assessed based on the wind mechanical comfort criterion of NEN 8100 and the wind chill criterion. CFD simulations are performed to provide the pedestrian-level aerodynamic information, and the simulation results are validated by wind tunnel experiments. The assessment results show that the wind mechanical comfort or wind chill criterion need to be combined when assessing the wind conditions in severe cold regions. From the perspective of wind mechanical comfort and wind chill, the multi-storey residential areas with hybrid-type and the enclosed-type layout are recommended in severe cold regions. Moreover, a strict control of building height in residential areas is important to improve the pedestrian-level wind mechanical comfort, but not very helpful to reduce the occurrence of frostbite in winter. [ABSTRACT FROM AUTHOR]

Several nature based and climate adaptive solutions have been proposed to improve cities resilience to the effects of global warming and restore natural processes in strongly anthropized areas. Green roofs are among the most efficient nature based solutions to address recurrent urban challenges, such as pluvial floods and urban heat islands. Various benefits offered by green roofs are rather known, such as their capacity to enhance buildings thermal insulation; green roofs also favor urban biodiversity, improving buildings aesthetic value and human well being. Multilayer green roofs (MGRs) are green roofs with an additional layer that increases their water storage capacity. Deep analyses on MGRs are still lacking due to their recent development, and the few works in literature are prevalently focused on their stormwater retention primary function. This work explores the thermal function of an experimental MGR prototype installed in Palermo (Italy), comparing its response to local climate with that of an unaltered portion of the rooftop through the analysis of surface temperature time series collected over a two years monitoring period. Performances are evaluated thought various daily thermal indices, also analyzing the role of the water stored into the system. Results contribute to raise awareness about the benefits arising from the use of MGRs in semi-arid Mediterranean urban areas, confirming, as main thermal advantage, their cooling effect, with mean daily surface temperature reduced by 8.4% outdoor and 5.8% indoor; performances increases with water storage and are particularly evident during the hot and dry summers that typically characterize such regions. [Display omitted] • Multilayer green roofs improve cities resilience to global warming. • Thermal response of a prototypal system in Italy was monitored for over 2 years. • Mean daily roof surface temperature is reduced by 8% (outdoor) and 6% (indoor). • Marked reductions of daily temperature excursions proved a thermal inertia gain. • Thermal performances of multilayer green roofs increase with water storage. [ABSTRACT FROM AUTHOR]

Numerous studies have explored multiple factors that affect the urban thermal environment. Most current studies focus on establishing the holistic quantitative relationships between the characteristics of urban thermal environmental factors and land surface temperature (LST), but less attention has been given to exploring urban subdivisions in detail. The local climate zone (LCZ) system has been proven effective in establishing the quantitative relationships between urban climate and spatial factors, thereby revealing the characteristics of LST spatial variations. This study utilized the random forest regression model to analyze the relative importance and marginal effects of the urban thermal environmental factors on seasonal LSTs based on the whole study area and the LCZ-derived built type area of Fuzhou city, known as a "furnace city" in southeastern China. The results show that: (1) Building morphology and spatial distribution exert a significant impact on LST, with the LST levels of different building forms ranked as open < compact and high-rise < mid-rise < low-rise. (2) Landscape composition exhibits the greatest influence on seasonal LSTs in the whole study city. (3) Building morphology emerges as the most influential category for LST in the LCZ built type area, with the standard deviation of building height having the highest relative importance at approximately 34%. (4) Concentrated compact low-rise self-built houses experience higher temperatures and should be a focus for future urban renewal efforts. We believe that these findings provide quantitative insights for urban heat island analysis and have substantial implications for climate-friendly urban planning. • Characterizing the impacts of urban thermal environmental factors. • Exploring the dominant factors influencing seasonal LSTs. • Evaluating the marginal effects of thermal environmental factors on seasonal LSTs. [ABSTRACT FROM AUTHOR]

To guide building system retrofits for reducing building's operational carbon footprint, a micro-genetic optimization algorithm has been applied. The algorithm is integrated into the Vertical City Weather Generator (VCWG) urban physics model. The model is applied to low-rise residential houses of Toronto, a cold Canadian city, for annual estimations and reductions of electricity/gas consumption and retrofit cost from 2020 to 2100, every decade, under two Representative Concentration Pathway (RCP) climate change scenarios. The building system configuration utilizes a solar thermal collector, photovoltaic collector, wind turbine, building thermal energy storage, and heat pump. Fifteen building variables have been optimized. Compared to a base building, the proposed retrofitted system reduces the electricity consumption by up to 61.71 [%] and the gas consumption by up to 82.67 [%]. The annualized retrofit cost for a 20-year time horizon is about 10-15 thousand Dollars. Some optimized variables are sensitive to the climate change scenario over a long time horizon until 2100, which relate to the thermal energy storage system, phase change material, solar thermal collectors (and the associated working fluid flow rates), solar heat gain coefficient, and roof albedo. Other variables, relating to the ventilation/infiltration rates, building envelop thermal resistance, glazing ratio, wind turbine size, and photovoltaic collectors, do not show such sensitivity. The optimization process is computationally fast, and the solution obtained provides evidence for successful building system retrofits toward energy and cost savings for the climate of Toronto. • A micro-genetic optimization algorithm is applied for building energy and retrofit cost savings. • Fifteen building variables are optimized for a residential house in Toronto for 2020–2100. • The configured system saves up to 61.71% in electricity and 82.67% in gas consumption. • The retrofit cost is estimated as 10–15 thousand Dollars annually for a 20-year horizon. • The optimization algorithm and proposed system show evidence for real energy and cost savings. [ABSTRACT FROM AUTHOR]

Climate change and increasing urbanization call for the effective adaptation of cities to extreme heat. To improve the applicability of the research, sophisticated computational fluid dynamics models are being developed to capture the complexity of climate in a real urban environment, while a human-oriented paradigm is emerging concurrently. In this paper we present a synergy of these approaches by analyzing outdoor thermal exposure on five different pedestrian routes in Prague-Dejvice (Czech Republic), employing the PALM modeling system and realistic use-cases. Our simulations reveal important spatio-temporal variability in the Universal Thermal Climate Index (UTCI) in the urban neighborhood. Our findings particularly emphasize the negative effect of open spaces, such as gaps between buildings and shorter buildings, on the thermal exposure of pedestrians. These configurations allow more direct irradiation to reach ground level, while the other adverse climatic characteristics of midrise/highrise developments are largely preserved. The effect of urban greenery is quite variable during the day. Trees can reduce UTCI by up to 10 °C, but this strongly depends on the location (e.g., distance from neighboring buildings). Irrigated grass reduces UTCI by about 1.8 °C, but dried grass has little heat mitigation effect. In conclusion, our results suggest that expert-based knowledge together with sophisticated and fine-scale models can identify effective heat stress reduction measures without draconian changes to, or investments in, the urban environment. • Microscale meteorological modeling and pedestrian routes yields novel exposure information. • Fine-scale meteorological models can identify effective heat stress reduction measures. • Tree planting reductions of UTCI reach 10 K but depend strongly on local context. • Replacement of impervious surfaces with irrigated (dried) grass reduces UTCI around 1.8 K (0.1 K). [ABSTRACT FROM AUTHOR]

Urban planning, through urban design and land use allocation, affects urban climate dynamics and patterns at different vertical layers of the urban boundary layer and spatial multiscale. Climate-sensitive urban planning and design draws attention to the consideration of climate parameters and their explanatory factors as a relevant element in decision-making. Local climate zones, defined from urban design variables such as building density and building height, allow for the recognition of homogeneous units useful for directing planning actions that allow cities and their population to adapt their climate behavior. This research compares the meso-scale climatic characteristics of the local climate zones proposed by Stewart and Oke for Chilean large cities located on an extensive latitudinal gradient (roughly 18°S to 45°S), on the coast of Chile and inland. In particular, the relationship between the behavior of surface temperature and vegetation is evaluated through the average Normalized Difference Vegetation Index (NDVI) for the decade (2008–2018). The results account for differences in the behavior of surface temperatures between climatic zones. In turn, vegetation is inversely related to the surface temperature, making it possible to distinguish the differences inside the LCZ, it being warmer in areas where the NDVI is lower. • The recognition of local climatic zones was carried out in 20 Chilean cities. • We recognize differences associated to their different location between 17° and 53°S. • The compact low-rise B3 local climate zone is the warmest and more frequent. • In the north, bare soils are more abundant, and southwards, vegetated areas increase. • NDVI explains thermal differences: the higher the NDVI, the lower the temperature. [ABSTRACT FROM AUTHOR]

The limited available urban land in megacities is represented by large areas of impervious underlying surfaces and buildings, which are expressed by the basic urban fabric unit of the "city block." The concept of the Local Climate Zone (LCZ) scheme is capable of quantifying the combined influences that different urban elements have on block-scale local climates, rendering block-scale LCZ classification and block-scale-oriented LCZ map production crucial for climate-conscious urban planning and design. Taking the city of Guangzhou as a case study, deep learning was combined with the Convolutional Neural Network (CNN) to perform effective image recognition, vector cutting, and automatic area statistics based on multilevel road networks. Road network division, block area processing, characteristic parameter calculation, and LCZ classification were integrated to automatically generate block-scale-oriented LCZ maps, which was achieved via threshold contrast using the recommended parameter intervals of the calculated characteristic parameters. Basic land surface temperature (LST) data for summer to winter in Guangzhou were then applied, and correlation analysis was conducted between the block-scale LST vector and LCZ characteristic parameters. The results demonstrate the applicability and potential of the CNN algorithm for urban climate analysis. The developed CNN-based LCZ mapping approach prioritizes "block" scale analysis and typical characteristic parameters in each block are obtained with high calculation accuracy. This study contributes to guiding parameterized climate-sensitive urban planning. • A CNN deep learning method is applied for image recognition of urban elements. • CNN-based procedures are integrated to realize automatic block-scale LCZ maps. • Block-scale LCZ characteristic parameters are calculated. • Relationships between seasonal LST and LCZ characteristics are discussed. [ABSTRACT FROM AUTHOR]

Semi-open street roofs(SOSRs) have been confirmed to provide solar shading for pedestrians, usually improving outdoor thermal comfort but weakening urban ventilation in three-dimensional(3-D) urban districts. However, these positive and negative impacts have rarely been quantified together. Particularly, their impacts in two-dimensional(2-D) street canyons have not been investigated. Accordingly, by conducting computational fluid dynamic(CFD) simulations coupling turbulence and radiation processes, this study investigates the integrated influences of SOSRs on both ventilation/pollutant exposure risks and pedestrian-level outdoor thermal comfort in 2-D full-scale street canyons(aspect ratios AR = H/W = 1, 3, 5; W = 24 m). Isothermal and non-isothermal cases with three solar angles(LST0900, LST1200, LST1500) are considered. The pedestrian-level maximum normalized velocity(V pedmax /V inlet) and physiological equivalent temperature(PET) are analyzed for ventilation and thermal comfort assessment. SOSRs have an overall negative impact on present 2-D streets. Without SOSRs, only one main clockwise vortex exists when H/W = 1 and H/W = 3. Compared to the isothermal cases, LST0900 and LST1200 always strengthen this main vortex, while LST1500 weakens it slightly. The SOSRs may produce some secondary near-ground clockwise and counter-clockwise vortexes, which significantly reduce V pedmax /V inlet , i.e. from 0.33–0.44 to below 0.07 when H/W = 1 and 0.063–0.13 to 0.049 when H/W = 3. They also increase pedestrian-level PET by 0.9–10.4 °C(H/W = 1) and 0.1–4 °C(H/W = 3). When H/W = 5, two main vortexes appear in the isothermal case inducing much smaller V pedmax /V inlet of 0.004 and solar radiation significantly raises the V ped / V inlet to 3–25 times without SOSRs. The impacts of SOSRs are not as significant as those at H/W = 1 and 3. Overall, the SOSRs impact should be assessed before their application, especially in 2-D streets. • We assess how semi-open street roofs(SOSRs) affect urban climate in 2-D streets. • SOSRs weaken pedestrian wind too much, so worsen thermal comfort as H/W = 1,3. • SOSRs weaken ventilation/raise pollutant exposure as H/W = 1,3 but little as H/W = 5. • SOSRs should be assessed before application in 2-D streets, differing from 3-D. [ABSTRACT FROM AUTHOR]

Background Exposure to airborne ultrafine particle (UFP; <100 nm in aerodynamic diameter) is an emerging public health problem. Nevertheless, the benefit of using high efficiency particulate arrestance (HEPA) filtration to reduce UFP concentrations in homes is not yet clear. Methods We conducted a randomized crossover study of HEPA filtration without a washout period in 23 homes of low-income Puerto Ricans in Boston and Chelsea, MA (USA). Most participants were female, older adults who were overweight or obese. Particle number concentrations (PNC, a proxy for UFP) were measured indoors and outdoors at each home continuously for six weeks. Homes received both HEPA filtration and sham filtration for three weeks each in random order. Results Median PNC under HEPA filtration was 50–85% lower compared to sham filtration in most homes, but we found no benefit in terms of reduced inflammation; associations between hsCRP, IL-6, or TNFRII in blood samples and associations with indoor PNC were inverse and not statistically significant. Conclusions Limitations to our study design likely contributed to our findings. Limitations included carry-over effects, a population that may have been relatively unresponsive to UFP, reduction in PNC, even during sham filtration, that limited differences between HEPA and sham filtration, window opening by participants, and lack of fine-grained (room-specific) participant time-activity information. Our approach was similar to other recent HEPA intervention studies of particulate matter exposure and cardiovascular risk, suggesting that there may be a need to improve study designs. [ABSTRACT FROM AUTHOR]

This study presents a novel approach to validate the capability of biometeorological indices to predict the likelihood of urban dwellers to be outside during midday. Over a period of ten months three Wi-Fi scanners were used in a public courtyard in Cambridge, MA, to record outside dwelling patterns. Based on encrypted MacIDs courtyard attendees could be divided into 16,000 regulars and 676,000 visitors. Universal Thermal Climate Index (UTCI) predictions based on a combination of measured microclimatic conditions and mean radiant temperature simulations using ENVI-met were shown to strongly correlate with the number of regulars present during lunchtime with coefficients of determination (R 2 ) of 92% during spring and 70% during summer/fall, respectively. Lunchtime attendance peaked for UTCI values in the thermal comfort and moderate heat stress ranges. In parallel, the probability for regulars to have lunch outside more than doubled during those UTCI conditions and the median lunchbreak length increased from 8 min to 12 min. These findings suggest that UTCI can be used as a reliable environmental performance metric to support the design and preservation of comfortable outdoor spaces. The reported use of public Wi-Fi data can help city governments to better understand – and potentially improve – the use of outdoor spaces while maintaining the privacy of their constituents. [ABSTRACT FROM AUTHOR]

Knowledge of the influence of land cover on air temperature in arid cities is scarce, yet essential for urban planners to select landscape design and management strategies which can improve livability and provide efficient landscape irrigation. The objectives of this study were to consider the effects of urban land use on air temperature changes in an arid city based on data collected in Isfahan, Iran at a local scale. This study reports a statistical analysis of temperature variation with respect to land use throughout the day and night. It is also the first study to report the effects of land cover on the time that daily minimum and maximum temperature occurs. The land use characteristics considered included green space, streets, buildings, population density and bare land. Air temperature was measured for 42-months at the canopy level of five intra urban sites and one reference site in a lightly developed suburban location. The temperature of all intra-urban sites was higher than the suburban reference site for a majority of observations during daytime throughout the year. The effect of land use on air temperature overnight was greater than daytime. The highest temperature difference occurred overnight in summer, with differences up to 12 °C when comparing an irrigated, vegetated site and the suburban site on an hourly basis. On average, the daily maximum temperature in urban areas occurred sooner than in the suburb in all seasons. The highest mean time difference was 78 min between the commercial–residential and suburban stations in summer. [ABSTRACT FROM AUTHOR]

Urban air temperature varies along time and space. This contribution proposes a methodology to model these variations from empirical models. Four air temperature networks are implemented in three west France cities. The period [1.4–1.8] of a normalized night is investigated. Three empirical models are established, in order to predict temporal and spatial air temperature variation. They are gathered under the name of model group . Urban heat island (UHI) intensity is explained according to one temporal model using meteorological variables. Temperature spatial variations are explained from two models using geographical informations averaged in a 500 m radius buffer circle. The first one represents the mean UHI value for a given location, the second the variability of the UHI around its mean value. 32 model groups are calibrated from data sampled by one network. The accuracy of their estimations is tested comparing estimated to observed values from the three other networks. The most accurate model is identified and its performances are analyzed. Night-time UHI intensity variations are explained all along the year by wind speed and nebulosity values calculated after sunset. During spring and summer season UHI variations are mainly driven by Normalized Difference Vegetation Index (NDVI) value whereas building density or surface density are predominant explicative variables during colder seasons. The model is finally applied to the city of Nantes during a summer night to illustrate the interest of this work to urban planning applications. Several warm areas located outside the city center are identified according to this method. Their high UHI value is mainly caused by their low NDVI value. [ABSTRACT FROM AUTHOR]

Over the last decade, significant efforts have been made to develop sophisticated physics-based urban simulators, given the undeniable need for sustainable-city initiatives to consider the potential impacts of climate change and massive urban growth. Nevertheless, even as a growing number of researchers have expanded their scope to the urban realm, there remain many problems resulting from the complexity of the urban microclimate, such as the Urban Heat Island (UHI) effect. This study is initiated with the intention to account for uncertainty in developing more coherent and integrated strategies concerning the energy and environmental issues in an urban system. The analysis builds upon the previously reported and updated Urban Weather Generator (UWG) to present a deep look into an existing urban microclimate system in Abu Dhabi (UAE). The case-specific baseline information is generated for the UWG and a global regression-based sensitivity analysis using the Monte Carlo technique is performed. Based on 30 candidate inputs covering the meteorological factors, urban characteristics, vegetation variables, and building systems, the uncertainty analysis indicates that the UWG is a fairly robust simulator to approximate the urban thermal behavior in downtown Abu Dhabi for different seasons. The identified significant factors will be the subject of future research to gain a higher resolution of critical urban simulation inputs, thereby providing more informed domain knowledge of the underlying mechanisms driving the microclimatic effect on the energy and environmental performances. [ABSTRACT FROM AUTHOR]

The development of modelling techniques to study the urban heat island effect by accurately evaluating solar heat gain in urban environments is presented. The modelling techniques consist of: a realistic geometrical modelling tool that reproduces real urban morphologies, a parallelized gridding algorithm that generates evenly distributed grids on urban facades, and efficient solar heat gain calculation algorithms for accelerated capturing of the solar irradiance impinging on urban surfaces. The developed techniques are validated against in-situ measurements in urban areas in Singapore with different scenarios covering a wide range of urban morphologies found across the city and various weather conditions, and applied to study solar heat gain distribution for existing and new towns. The simulation results reveal that the developed techniques are able to evaluate the effects of urban geometries, materials and tree shading on solar heat gain on urban surfaces, which provides insight into the fundamental physics applied to mitigate the urban heat island effect. [ABSTRACT FROM AUTHOR]

Within the contemporary city, the effects of urban climatology are increasingly elucidating the need for further climate responsive environments. So far however, and as global climate studies often present limited local specificity for urban planning and design, there has been a growing interest for complementary bottom-up perspectives which describe how efforts of adaptation can be locally initiated. Accompanying this interest, and orientated at a specific case study, this article presents the results of an empirical analysis that was undertaken during July of 2015 within one of Lisbon's iconic historical public spaces, Rossio. The study was built upon two foundational interrogations: (1) What are the principal microclimatic risk factors within the square that can affect pedestrian thermal comfort thresholds?; and, (2) How can the identified risk factors be translated into opportunities for public space design? In order to obtain an initial understanding of thermal comfort conditions, C omputational F luid D ynamic (CFD) and S hadow B ehaviour S imulations (SBS) simulations were undertaken to establish six P oints o f I nterest (POI) within the square. Subsequently, ambient temperature, surface temperature, relative humidity, wind speed, global radiation and S ky- V iew- F actor (SVF) were measured with on-site meteorological handheld equipment. In order to complement these examinations, Pedestrian Based Response (PBR) interviews were also conducted. Finally, through the application of the biometeorological RayMan model, the P hysiologically E quivalent T emperature (PET) index was used in order to: (i) obtain approximations of diurnal physiological stress around the square; and subsequently, (ii) propose conceptual public space design solutions to improve existing thermal comfort conditions in the square. [ABSTRACT FROM AUTHOR]

Improving city breathability has been confirmed as one feasible measure to improve pollutant dilution in the urban canopy layer (UCL). Building height variability enhances vertical mixing, but its impacts remain not completely explored. Therefore, both wind tunnel experiments and computational fluid dynamic (CFD) simulations are used to investigate the effect of building height variations (six height standard deviations σ H = 0%–77.8%) associated to building packing densities namely λ p / λ f = 0.25/0.375 (medium-density) and 0.44/0.67 (compact) on city breathability. Two bulk variables (i.e. the in-canopy velocity ( U C ) and exchange velocity ( U E )) are adopted to quantify the horizontal and vertical city breathability respectively, which are normalized by the reference velocity ( U ref ) in the free flow, typically set at z = 2.5 H 0 where H 0 is the mean building height. Both flow quantities and city breathability experience a flow adjustment process, then reach a balance. The adjustment distance is at least three times longer than four rows documented in previous literature. The medium-density arrays experience much larger U C and U E than the compact ones. U E is found mainly induced by vertical turbulent fluxes, instead of vertical mean flows. In height-variation cases, taller buildings experience larger drag force and city breathability than lower buildings and those in uniform-height cases. For medium-density and compact models with uniform height, the balanced U C / U ref are 0.124 and 0.105 respectively, moreover the balanced U E / U ref are 0.0078 and 0.0065. In contrast, the average U C / U ref in height-variation cases are larger (115.3%–139.5% and 125.7%–141.9% of uniform-height cases) but U E / U ref are smaller (74.4%–79.5% and 61.5%–86.2% of uniform-height cases) for medium-density and compact models. [ABSTRACT FROM AUTHOR]