This study presents a data-driven comparison of thermal comfort in traditional underground Shavadan spaces and above-ground residential environments across summer and winter in a hot and semi-humid climate. Field surveys conducted in Dezful, Iran, combined ASHRAE-based thermal sensation votes with measurements of environmental and personal parameters. Four datasets representing seasonal and spatial conditions were developed, and six machine-learning models (SVM-RBF, Random Forest, XGBoost, LightGBM, AdaBoost, and backpropagation neural networks) were optimized using Optuna and evaluated through five-fold stratified crossvalidation. The results indicate that model performance strongly depends on both season and spatial context. In summer above-ground spaces, ensemble boosting models achieved among the highest predictive accuracy (ACC approximate to 0.89). In contrast, predictive performance was lower in the thermally stable summer Shavadan (maximum ACC approximate to 0.69), where nonlinear classifiers such as SVM-RBF performed best due to clustered thermal responses around neutrality. In winter above-ground spaces, several models exhibited comparable accuracy (ACC approximate to 0.75-0.77), while imbalance-aware metrics revealed persistent challenges in minority-class discrimination. Across all winter scenarios, the conventional PMV model showed weak agreement with observed thermal sensation. Feature-importance and partial-dependence analyses consistently identified air temperature as the dominant factor influencing thermal perception, while other variables played secondary roles, particularly in winter conditions. Overall, the findings highlight the limitations of static comfort indices and emphasize the need for context-specific, data-driven thermal comfort modeling, while confirming the effectiveness of underground Shavadan spaces in moderating thermal stress during extreme summer conditions.

OBJECTIVES:Climate change and global warming are major threats for human health and impact the burden of infectious diseases. We investigated the effect of heat stress days (max. perceived temperature ≥32°C) on the incidence of Staphylococcus aureus bacteremia (SAB) and Escherichia coli bacteremia (ECB). METHODS:We performed a post-hoc analysis of a prospective multicenter cohort study with inclusion of all reported SAB and ECB episodes at six tertiary care centers in Germany from 01/2017-12/2019. The effect of the number of heat stress days on the incidence of bacteremia episodes was modelled by a negative binomial regression model with and without underlying seasonal trend. RESULTS:In the prospective multicenter cohort, we included 2870 episodes of SAB and 4421 episodes of ECB. For both entities, we found a significant seasonal variation over the year (ECB peak-to-trough ratio: 1.33, 95% CI: 1.23-1.45, p < 0.001); SAB peak-to-trough ratio: 1.19 (95% CI: 1.07-1.32, p < 0.001), especially in the subgroup of community-acquired ECB (1.47, 95%-CI: 1.32-1.64, p < 0.001). In the model with incorporation of an underlying seasonal trend, we discovered no overall significant association with the number of heat stress days for SAB and ECB. However, in the subgroup of patients with hospital-acquired SAB, we found a significant association after two days of heat (IRR 1.45, 95%-CI: 1.17-1.82, p = 0.001), that remained significant also in a sensitivity analysis focusing on summer days only (IRR 1.50, 95%-CI: 1.18-1.91, p = 0.001). However, after inclusion of an underlying seasonal trend, the incidence of bacteremia cases remained significantly associated with heat stress days only in the subgroup of patients with hospital-acquired SAB. CONCLUSION:Apart from seasonal trends, heat days did not seem to influence the incidence of SAB and ECB overall. The observed association of SAB with heat days in the subgroup of hospital-acquired SAB needs confirmation in further studies.

Urban heat risk is increasing, while fixed monitoring networks remain too sparse and coarse to resolve the pedestrian-scale variability, especially radiative loads, that governs outdoor thermal stress. This short communication advances the concept of climate walks, defined as route-based, human-centred field campaigns that build on earlier work on “thermal walks”, and presents them as a practice-ready methodology for design-relevant evidence. We define climate walks as structured, route-based, georeferenced assessments that pair high-resolution mobile microclimate measurements with synchronous in-situ human responses to capture transient, spatially heterogeneous conditions along actual walks. We synthesize key methodological features, such as dynamic, stop-and-go protocols; human-centred sensing; multisensory extensions; accessible kits from research-grade to low-cost platforms; and emerging diagnostics, and show how these produce actionable design measures. We discuss limitations and challenges, including lags and thermal memory, instrumentation and, index choice under transients, and the need for protocol harmonization. We then propose a research agenda to investigate dynamic conditions of outdoor thermal comfort, develop time-resolved, memory-aware comfort metrics, test indices under motion, mainstream multisensory models, and shift practice from isolated cool spots to connected, route-scale cool sequences. Together, these steps link biometeorology to actionable urban planning and design for heat-resilient, attractive public spaces.

​ Abstract Background Individual heat protection depends on conditional behaviours that are activated when risk cues cross meaningful thresholds. Unlike Ultraviolet (UV) protection - where decades of preventive communication have ingrained clear behavioural triggers - heat guidance still offers vague cues that rarely specify when protective action is required. Methods We conducted a population-representative vignette experiment in Germany (n = 2,003). Using days sampled from actual past weather forecasts in an ecologically valid weather-app format as cues we investigate when and how people decide to protect themselves against both heat and UV exposure. Using composite behavioural indices, weighted regression, LASSO feature selection and spline-based exposure-response models, we identified the cues that drive protective behaviour and the presence of threshold responses. Findings Heat-protective behaviour displayed no population-level threshold, rising only gradually. Participants consistently relied on the maximum air temperature, not the perceived temperature that better reflects thermos-physiological heat stress and includes more climate parameters. In contrast, UV protection showed a sharp behavioural threshold at UVI 7-8, aligned with WHO messaging. Interpretation These findings reveal a critical gap: existing heat communication fails to provide effective behavioural cues. Establishing clear, actionable heat thresholds and actions is essential to improve public readiness for escalating heat extremes. Funding For this project there was no dedicated funding available.

Although heatwaves are typically defined by meteorological thresholds over consecutive days, their health impacts often extend far beyond periods of elevated temperatures [...]

Accurate solar radiation data are fundamental for solar energy research. Reliable databases are essential to quantify their spatiotemporal variability. Although long-term ground-based radiometric measurements are considered the most reliable source of global horizontal irradiance data, they are prone to inaccuracies and often lacking in many regions. This study analyzes hourly global horizontal irradiance data from 14 datasets spanning more than 50 countries to assess data availability, data quality, and statistical as well as spatiotemporal characteristics. A comprehensive stepwise quality control procedure reviews existing and new quality tests to identify suspicious data points or entire implausible time series. After quality control, 1,618 out of 2,147 stations were retained: 289 with 2-5 years, 806 with 6-15 years, and 523 with more than 15 years of reliable data in the study period 1991-2020. This highlights that measurement sites with persistent long-term, high-quality data are scarce. While analyzing long-term changes and trends remains challenging, time-frequency analysis enables estimation of the time scales contributing most to variability at each location. Depending on the site, 47.2 % to 75.2 % of total variance is explained by deterministic cycles at the semi-daily, daily, and annual scales. The contribution of different time scales primarily depends on latitude, but is also influenced by topography and local conditions. Insights gained from quality-controlled ground-based data can be combined with global reanalysis and satellite data to better characterize spatiotemporal variability in global solar radiation and improve solar energy potential estimations from local to global scale.

Walking benefits both physical and mental health. Arabian Peninsula, as one of the regions with highest physical inactivity rates, faces significant barriers to outdoor walking due to the extreme hot climate. This study defined thermal walkability as whether thermal conditions support outdoor walking based on a thermal index, modified Physiologically Equivalent Temperature, and investigated its spatial and temporal (both seasonal and diurnal) distribution and long-term trends across the Arabian Peninsula over the period 1986-2024. The results showed a pronounced seasonal contrast: October-April features widespread thermally walkable conditions for most non-sleeping hours, with little decadal change; while summer and transitional months experienced poor thermal walkability, with thermally walkable hours mainly around sunrise and after sunset, and the probability of thermal walkability during these periods was declining significantly. The meteorological drivers of thermally unwalkable conditions for four major cities were identified based on the results of logistic regression and random forest models. Air temperature and solar radiation turned out to be the primary determinants while wind velocity and vapour pressure have weak effects across hot-arid to hot-humid climates. These findings highlight the necessity for region- and time-specific mitigation and adaptation strategies against the reduced thermal walkability and offer valuable references for policymakers to create supportive environments for outdoor walking.

At present, outdoor thermal comfort assessment based on the Physiologically Equivalent Temperature (PET) index largely relies on the RayMan Pro software. However, the operation of RayMan Pro requires comprehensive meteorological inputs, multiple parameter settings, and a certain level of professional expertise. These requirements pose challenges for non-expert users and consequently limit the broader dissemination and practical application of the PET concept.To address these limitations, this study aims to develop simplified PET regression estimation formulas based on simulation results generated by RayMan Pro. Four key meteorological variables, namely solar radiation, air temperature, wind speed, and relative humidity, were parameterized to construct more than 640,000 simulated data combinations. Based on this dataset, regression models were developed and subsequently validated using observed meteorological data.According to the regression analysis results, two simplified PET estimation formulas were proposed: Formula 1, which excludes relative humidity, and Formula 2, which includes relative humidity. The validation results indicate that Formula 1 achieves sufficient estimation accuracy under hot climatic conditions and can be effectively applied for PET estimation.The simplified formulas proposed in this study can be applied to the generation of urban-scale PET spatial distribution maps, serving as practical tools for urban thermal environment planning and climate risk management. The findings provide an efficient approach for rapidly assessing heat stress risk under hot climatic conditions in Taiwan.

Heat and ultraviolet (UV) radiation are among the most consequential environmental stressors intensified by anthropogenic climate change [...]

Climate change has intensified the need for adaptation in urban environments, yet its integration into historic urban squares, where recreational activities were heavily concentrated, has remained underexplored. In this context, the study examined the square located between Hagia Sophia and the Blue Mosque, which is also defined as an urban recreation area and a focal point of culture-based tourism, during periods of extreme weather conditions and high flows of both local (n = 152), and international tourists (n = 236), evaluating it through different spatial activity typologies. A total of 388 participants were surveyed at 25 survey points within the square, while meteorological parameters were obtained from meteorological stations. The findings showed that the lowest level of heat stress across all typologies corresponded to "slight heat stress," while user responses varied according to spatial characteristics. In movement spaces, the absence of shading elements increased both heat stress and shade demand, whereas in stationary spaces, the presence of trees reduced heat stress but preferences for lower air humidity persisted even under shaded conditions. Sky openness was not identified as a direct determinant of thermal sensation, with meteorological and perceptual factors proving more influential. PET explained approximately 65% of the variation in MTSV among tourists, compared to 55% among local residents. Across typologies, only increases in air temperature negatively affected thermal satisfaction. Moreover, tourists perceived the square more holistically and reported higher satisfaction compared to locals, whose environmental demands were distinct. These results highlighted the importance of spatial activity typologies in shaping thermal experience and underlined the necessity of design strategies that extended beyond heat-mitigation measures. Holistic and flexible approaches that accounted for user profiles, activity types, and intensity of use were found to be essential for improving thermal comfort in historic urban squares with diverse spatial configurations.

Mean Radiant Temperature (MRT) has emerged as a critical parameter for evaluating human thermal comfort in built environments and microclimates across the globe. Defined as the uniform temperature of an imaginary enclosure where the radiant heat exchange with the human body matches that of the actual, non-uniform environment, MRT offers a comprehensive representation of radiative thermal exposure. Understanding MRT requires examining its relationship with human thermal indices, long-term fluctuations in outdoor settings, and impacts on human health and climate change patterns. This is a relevant topic for urban and landscape planners, architects, urban designers and health professionals, with accurate MRT assessment recognized as key to developing thermally comfortable spaces. Precise MRT measurement benefits occupants through improved thermal comfort conditions and energy efficiency. Furthermore, implementing MRT-informed design strategies helps reduce cooling demands, making it more affordable to maintain comfortable indoor and outdoor environments. This 'ten domains contribution' provides an overview of MRT's importance in human thermal comfort assessment, measurement and modelling techniques, relationships with indoor and outdoor environmental characteristics, implications for health studies and exposure during extreme heat events and heat waves, optimization strategies for buildings and HVAC systems, and future perspectives in the context of global to local climate change.

There is ongoing debate about the extent to which societies are insufficiently prepared for extreme heat and heatwaves [...]

Urban heat intensification increasingly exacerbates outdoor thermal comfort, posing challenges for urban planning and climate adaptation. Shading and ventilation are recognized strategies to mitigate thermal stress. However, most studies rely on physical indicators without calibration to local subjective responses. In Taiwan’s hot-humid climate, such approaches may inadequately reflect actual comfort, and the interaction between ventilation and solar radiation remains insufficiently explored. Integrating subjective perceptions with environmental data is therefore critical to refine thermal comfort range and understand how shading and sun exposure modulate ventilation effects.This study conducted field measurements (Air temperature, Globe temperature, Relative humidity, Wind speed) during the summer of 2025 at shaded and sun-exposed outdoor sites in Tainan, Taiwan. While simultaneously collecting participants’ personal characteristics and multi-dimensional subjective evaluations through questionnaire surveys, including Thermal Sensation Vote (TSV), Thermal Comfort Vote (TCV), Overall Comfort Vote (OCV), and environmental preference votes for temperature, wind, solar radiation, and humidity. Physiological Equivalent Temperature (PET) and mean radiant temperature (Tmrt) were calculated using RayMan Pro and ISO standard, respectively. Statistical analyses were then performed to examine discrepancies between objective physical conditions and subjective perceptions. Furthermore, considering human thermal adaptation under climate change, this study refines the conventional PET comfort range and establishes a localized assessment framework suitable for hot-humid environments.Results indicate that shading effectively reduces Tmrt, while ventilation enhances convective heat loss and lowers perceived temperature. For PET, ventilated conditions consistently outperformed no-wind scenarios, with reductions of approximately 1°C and 0.7°C in shaded and sun-exposed sites, respectively. Analysis of subjective human responses indicated that under shaded conditions, when wind speed exceeded 0.3m/s, approximately 81% of participants reported thermal comfort, and overall comfort increased with higher wind speeds. In contrast, under sun-exposed conditions, even with increasing wind speeds, TCV and OCV rarely reached the comfort threshold, suggesting that high solar radiation is the dominant factor limiting the effectiveness of ventilation. Nevertheless, when wind speed ranged between 0.3 m/s to 0.9m/s, comfort levels improved for about 20% of participants. Furthermore, using the PET neutral temperature in previous studies as a reference, and accounting for warming trends and thermal adaptation associated with climate change, the subjectively adjusted results indicate that thermal tolerance increases in both shaded and sun-exposed environments.This study demonstrates that the effectiveness of ventilation is strongly modulated by solar radiation. Under high-radiation conditions, shading should be prioritized to reduce thermal load, with ventilation serving as a complementary strategy to enhance overall comfort. The proposed PET adjustment model improves the accuracy of thermal comfort assessment in hot-humid climates, providing evidence-based guidance for urban planning and architectural design to optimize outdoor thermal environments.

Extreme weather conditions and climate‑related events increasingly shape daily life and the functioning of essential infrastructure. Human societies and built environments are vulnerable to a broad spectrum of environmental hazards, including forest fires, drought, rising sea levels, extreme precipitation and prolonged extreme heat and heat waves. Among these hazards, extreme heat poses one of the most immediate and pervasive risks, particularly in densely populated urban areas where people are exposed to intensified thermal stress. This exposure is expected to increase further in the coming decades as climate change progresses and urbanisation continues.Communicating effectively about heat therefore requires a comprehensive and multifaceted approach. It must address short‑term exposure during both daytime and nighttime, highlight the importance of cool shelters, and promote the creation and maintenance of urban areas with naturally lower thermal loads, such as parks, shaded streets, water features and green spaces. These environments not only reduce heat exposure but also support physical and mental well‑being during extreme weather events.Clear and targeted communication is essential to ensure that information, warnings and explanations reach the media, decision‑makers and the public in an appropriate and timely manner. Different target groups—such as vulnerable populations, health professionals, city planners or journalists—have distinct needs, expectations and decision‑making contexts. Communication strategies must therefore be tailored, easy to understand and enriched with practical solutions, behavioural recommendations and examples of effective adaptation measures. In addition to formal heat‑health warnings, messages should be framed in accessible language and supported by visual tools that help translate complex climate‑health relationships into actionable guidance.A series of examples will be presented and analysed, using heat as a central case to illustrate key principles of effective communication. These insights draw on recent experiences with public and media communication across Europe and highlight the growing importance of clear, science‑based messaging in a warming world.

Subtropical coastal regions are increasingly important public spaces within urban systems, yet microclimatic conditions and associated thermal outcomes of beaches and coastal areas remain understudied despite growing climate-related heat risks. The field study on Hailing Island, China, combined micrometeorological measurements with thermal perception assessment using thermal indices, including Physiologically Equivalent Temperature (PET), modified PET (mPET), Universal Thermal Climate Index (UTCI), and a human energy budget (EB) approach, to characterize the beach microclimate and evaluate human thermal responses. This study distinguishes between objective thermal stress and individual-reported thermal perception under self-selected exposure. Results showed that the beach surface had high albedo and increased reflected shortwave radiation, thereby intensifying the radiative heat load and contributing to daytime thermal stress. Sea breezes reduced thermal stress under typical sea–land breeze conditions. Tree-covered beach spaces exhibited improved thermal conditions, with denser canopies (e.g., Casuarina equisetifolia L.) providing stronger solar shielding than coconut canopies. Under unshaded beach conditions, air temperature and mean radiant temperature dominated thermal perception, while the influence of air humidity was partly linked to sea-breeze processes. Under tree-shaded conditions, wind speed and mean radiant temperature became the primary drivers. Users demonstrated adaptive behaviors, including preferential use of shaded areas and exposure management in beach zones. Calibrated thermoneutral ranges for beach users were identified as 20.9 to 30.4 °C (PET), 24.7 to 30.7 °C (mPET), 25.8 to 30.8 °C (UTCI), and − 56.1 to 34.8 W m− 2 (EB). These results provide evidence to support climate-responsive beach design and heat-mitigation strategies in subtropical coastal environments.

Thermal exposure risks in high-density urban environments directly impact pedestrian health. In the precincts surrounding Taipei 101, super-tall buildings induce complex street-level vortices that significantly attenuate near-ground wind speeds. This study investigates the coupling effects between anthropogenic heat emissions from air conditioning systems (AC) and urban street flow fields. AC exhaust heat is frequently trapped at the pedestrian level (1.5 m) by micro-scale vortices, and improper configurations lead to a pronounced Thermal Retention Effect.To establish a data-driven evaluation framework and translate simulation outputs into actionable building heat-discharge strategies, this research employs Large Eddy Simulation (LES) to conduct transient thermo-fluid flow-field modeling, validated through on-site measurements. For the 1.5 m near-ground micro-environment, Physiological Equivalent Temperature (PET) is adopted as the thermal stress index, integrating air temperature (Ta), wind speed (V), and mean radiant temperature (Tmrt).Recognizing that conventional CFD approaches struggle to provide quantitative weighting of heat-accumulation factors and to identify dominant thermal mechanisms, this study introduces a Machine Learning (ML) model to quantify the relative contributions of different AC installation positions to localized heat accumulation, thereby establishing an efficient and predictive thermal-load assessment framework.Results indicate that leeward vortices in dense residential districts produce a heat-retention rate of 60%, driving pedestrian-level PET into the Extreme Heat Stress category. ML feature-importance analysis reveals that the interaction between discharge positioning and vortex circulation is the dominant thermal driver. Optimization of AC configurations reduces the spatial extent of high heat-accumulation zones from 60% to 25%, significantly mitigating thermal vulnerability and localized heat hazards caused by Thermal Trapping.This study confirms that the coupling between street vortices and anthropogenic heat emissions is the primary physical driver of near-ground microclimate deterioration. By optimizing AC placement (windward, leeward, crosswind, or rooftop) via the ML model, localized heat loads within the urban canyon can be effectively removed through ventilation-enhanced heat dissipation, enabling a functional decoupling between building heat discharge and ambient flow fields.Keywords: Human Biometeorology; Urban Canyon; LES; Machine Learning; Physiological Equivalent Temperature (PET); Anthropogenic Heat; AC Configuration Optimization

OBJECTIVES:This study aimed to characterise the frequency of exertional heat stroke (EHS), did-not-finish (DNF) and medical encounter (MED) outcomes in elite Athletics competitions, and to evaluate their association with environmental, individual and race-related variables. Particular attention was given to the wet bulb globe temperature (WBGT), a thermal index widely used by international federations to estimate athlete heat strain. METHODS:Data were collected from 4938 athletes of both sexes participating in 80 World Athletics races held between 2019 and 2024 in five disciplines: long distance track events, marathon, racewalking, cross-country and trail-running. Spearman rank coefficient correlations, Pearson χ2 tests and negative binomial (NB) regressions were used to explore associations between outcomes (EHS, DNF, MED) and environmental, individual and race-related variables. The predictive ability of these variables was assessed using leave-one-out cross-validation to identify the best-performing univariable and multivariable models. RESULTS:EHS frequency was 8/1000 on average and 16/1000 when the WBGT was above 28.0°C, independent of sex (p=0.297) or discipline (p=0.980). DNF and MED were higher in marathon, racewalking and trail-running than shorter disciplines (p<0.001). Among variables, the mean radiant temperature showed the strongest univariable association with EHS (R²=0.11, p<0.001), while WBGT association was weaker (R²=0.04, p=0.018). Predictive accuracy was limited, with the best model having an error of 0.5±0.7 EHS per race. CONCLUSION:The risk of EHS is particularly high during elite endurance events in Athletics. While EHS was greater with higher WBGT and radiant temperatures, neither provided sufficient predictive accuracy for heat-related risk in elite endurance athletes. Future models should consider other factors such as heat acclimatisation and recent illness to enhance predictive ability.

In dem Artikel werden zentrale Aspekte der Klimaanpassung in Städten und Einwirkungen auf Menschen systematisch herausgearbeitet und fachlich präzisiert. Die tatsächlichen Wirkmechanismen verschiedener Maßnahmen wie Begrünung, reflektierende Oberflächen, Wasservernebler, blaue Infrastruktur und technische Kühlung wurden realistisch eingeordnet. Dabei zeigte sich, dass viele Maßnahmen nur kleinräumig wirken und ihre Effekte häufig im Hinblick auf ihre Wirkung überschätzt werden. Gleichzeitig wurden rechtliche Rahmenbedingungen analysiert, die belegen, dass in Deutschland bereits zahlreiche rechtliche Vorgaben zur Klimaanpassung existieren. Die Hauptschwierigkeit liegt weniger im Fehlen von Gesetzen als in deren konsequenter Anwendung. Insgesamt wurde deutlich, dass Klimaanpassung aus vielen kleinen Bausteinen besteht, die gemeinsam wirksam werden. Die Ergebnisse unterstreichen die Bedeutung einer faktenbasierten, klaren und praxisorientierten Kommunikation, vor allem bei der richtigen Anwendung von Begriffen und Fakten sowie bei der Angabe nicht nur qualitativer, sondern auch quantitativer Informationen in Bezug auf die thermische Belastung von Menschen.

This research investigates the spatial variability of heating degree days (HDD) and cooling degree days (CDD) to advance climate zoning across North Africa. Using 30 years of high-resolution meteorological data (1989-2019) from 108 weather stations in Egypt, Libya, Tunisia, Algeria, Morocco, and Western Sahara, HDD and CDD values were calculated for six base temperatures (HDD: 12 degrees C-22 degrees C; CDD: 18 degrees C-28 degrees C) using NASA/POWER data. The findings reveal substantial climatic and topographical influences on thermal energy demands. Northern regions, particularly high-altitude locations like Bordj Bou Arreridj, Algeria, exhibited the highest HDD values, reaching 2932 at 18 degrees C, while southern desert areas, such as Adrar, Algeria, demonstrated extreme CDD values, peaking at 3169 at 18 degrees C. GIS-based spatial interpolation methods enhanced visualization, delineating detailed subclassifications within the Koppen-Geiger framework, increasing spatial resolution from 12 321 km2 to 3025 km2. For example, Algeria alone expanded from five to 35 sub-classifications. These refined zones reveal critical differences in energy demand, with northern cities requiring up to 10 times more heating energy, while southern cities demand up to eight times more cooling energy compared to coastal zones. The results provide an essential basis for updating regional building codes and optimizing HVAC designs, supporting climate adaptation and energy efficiency strategies tailored to North Africa's diverse climatic zones. By enhancing spatial resolution and refining classifications, this research transforms energy planning and thermal regulations in the region.

This study investigates the impact of street morphology and tree species on thermal comfort in Istanbul during the July 2023 El Niño event, focusing on worst-case scenarios. Field measurements were conducted in the most common street morphologies and compared with data obtained from meteorological stations (MS). Subsequently, the influence of tree presence were evaluated for the measured streets, and PET assessments were conducted by incorporating fisheye photographs of the most common tree species in the region into the SVF calculations. The results indicate that EW-oriented streets, particularly the Left Lateral, experience beyond extreme heat stress due to extended sun exposure. PET results from MS were inconsistent with local conditions. The analysis of Platanus orientalis, Populus canadensis, and Robinia pseudoacacia on PET in different street orientations showed reductions of 5–6 °C, particularly for the first two species during morning and midday. This equates to a PET reduction from Beyond extreme heat stress (I) to Extreme heat stress, for heat stress beyond 41 °C. Although this reduction is significant, tree shade had limited impact under such extreme heat. The study found that trees on the left side were more effective when placed on one side, while the right side provided stronger cooling when trees were on both sides in both E-W and N-S streets. Additionally, during the El Niño period, the influence of street morphology on thermal comfort in 'Csa' climates begins to reflect the conditions of 'BWh’ climates, with higher levels of heat stress. As climate change continues to intensify, these extreme heat conditions may become typical in the future.