Search Results (225)

The process of urbanization has intensified the urban heat environment, with the degradation of thermal conditions closely linked to the morphological characteristics of different functional zones. This study delineated urban functional areas using a multivariate dataset and investigated the seasonal and threshold effects of landscape and architectural features on land surface temperature (LST) through boosted regression tree (BRT) modeling and Spearman correlation analysis. The key findings are as follows: (1) LST exhibits significant seasonal variation, with the strongest urban heat island effect occurring in summer, particularly within industry, business, and public service zones; residence zones experience the greatest temperature fluctuations, with a seasonal difference of 24.71 °C between spring and summer and a peak temperature of 50.18 °C in summer. (2) Fractional vegetation cover (FVC) consistently demonstrates the most pronounced cooling effect across all zones and seasons. Landscape indicators generally dominate the regulation of LST, with their relative contribution exceeding 45% in green land zones. (3) Population density (PD) exerts a significant, seasonally dependent dual effect on LST, where strategic population distribution can effectively mitigate extreme heat events. (4) Mean building height (MBH) plays a vital role in temperature regulation, showing a marked cooling influence particularly in residence and business zones. Both the perimeter-to-area ratio (LSI) and frontal area index (FAI) exhibit distinct seasonal variations in their impacts on LST. (5) This study establishes specific indicator thresholds to optimize thermal comfort across five functional zones; for instance, FVC should exceed 13% in spring and 31.6% in summer in residence zones to enhance comfort, while maintaining MBH above 24 m further aids temperature regulation. These findings offer a scientific foundation for mitigating urban heat waves and advancing sustainable urban development. Full article

Due to global warming, the impact of heat waves on the sentimental health of urban residents has significantly intensified. However, the associative mechanism between diverse urban functional layouts and residents’ emotions at the street scale remains underexplored. Taking the five core urban areas of Chengdu as an example, this study used natural language processing technology to quantify the sentiments in social media texts and combined traditional geographical information for spatial analysis and correlation analysis, to explore the spatial distribution pattern of sentiments during heat waves (SDHW), as well as the correlation between SDHW and the functional categories of streets (FCS). The findings are as follows: (1) There are significant differences in the spatial distribution pattern of residents’ sentiments in the five core urban areas, and positive emotions within the Second Ring Road exhibit a higher proportion than those of peripheral areas, while negative sentiments are more gathered in the eastern area. (2) The street categories of green space, park, and public show a significant promoting role on residents’ positive sentiments. (3) There is an association between the industrial and commercial categories and negative sentiments, and the impact of the traffic category on residents’ sentiments shows spatial differences. (4) The combination of the residential category and other functional categories has a strong correlation with sentiments, indicating that a reasonable functional combination within residential areas plays a crucial role in promoting residents’ positive sentiments. The current study revealed the influence mechanism of the functional categories of streets on residents’ sentiments during heat waves, providing a scientific basis from the sentimental dimension for the optimization of street functional categories, heat wave emergency management, and the construction of resilient cities. Full article

Urban environments are increasingly affected by extreme weather conditions, posing significant risks to vulnerable populations, such as the homeless. This research applies geospatial analysis to identify areas of extreme heat and moisture within the Athens metropolitan area in Greece. The analysis utilizes satellite-derived land surface temperature (LST), vegetation density index (NDVI), build-up density index (NDBI), Topographic Wetness Index (TWI), and other terrain-based factors to develop high-fidelity risk zones. These zones are critical for informing targeted interventions and policy measures aimed at protecting vulnerable groups from heat waves and extreme moisture. This research integrates a geospatial analysis approach for mapping and evaluating heat and moisture vulnerability zones. This approach integrates remote sensing data, GIS-based modeling, and terrain analysis. The findings can provide local authorities and social services with the necessary information to design adaptive strategies for climate change resilience. Full article

This study investigates the impact of heatwaves on the thermal comfort and well-being of elderly individuals living alone during heatwaves, focusing on two contrasting residential typologies in the Atlantic climate of Spain: a dense urban area and low-density peri-urban setting. A mixed-methods approach was used, combining in situ environmental monitoring, adaptive comfort modelling, and user-centred data from surveys and interviews based on the De Jong-Gierveld Loneliness Scale. The results show that both dwellings exceeded recommended indoor temperature thresholds during heatwaves, especially at night, contributing to sleep disturbance, cardiovascular stress, and emotional discomfort. Despite 85% of participants indicating that outdoor activities help them to mitigate not-wanted loneliness, architectural barriers often hinder such engagement. Over half reported having no balcony or terrace, which may have further intensified social isolation. Field data collected during 2022 summer heatwaves recorded maximum daytime temperatures of 30 °C and night-time peaks of 28.7 °C, exceeding the 25 °C threshold. The adaptive comfort evaluation classified both cases as Class 4 (severe discomfort). The urban dwelling showed consistent moderate discomfort (Category 3), likely due to poor ventilation and urban heat island effects. The peri-urban case, despite lacking the heat island influence, showed worse thermal conditions, especially during the day. Architectural barriers, poor thermal performance, and the lack of semi-outdoor spaces may exacerbate isolation among elderly people during extreme heat events. Full article

Heat waves affect the health and quality of life of older adults, particularly in urban environments. However, there is limited understanding of how extreme temperatures influence their mobility. This research aims to understand the pedestrian mobility patterns of older adults during heat waves in Madrid, analyzing environmental and sociodemographic factors that condition such mobility. Geospatial data from the mobile phones of individuals aged 65 and older were analyzed, along with information on population, housing, urban density, green areas, and facilities during July 2022. Multiple linear regression models and Moran’s I spatial autocorrelation were applied. The results indicate that pedestrian mobility among older adults decreased by 7.3% during the hottest hours, with more pronounced reductions in disadvantaged districts and areas with limited access to urban services. The availability of climate shelters and health centers positively influenced mobility, while areas with a lower coverage of urban services experienced greater declines. At the district level, inequalities in the availability of urban infrastructure may exacerbate the vulnerability of older adults to extreme heat. The findings underscore the need for urban policies that promote equity in access to infrastructure and services that mitigate the effects of extreme heat, especially in disadvantaged areas. Full article

Urban settings in West Africa are increasingly experiencing extreme weather events, such as heat waves, floods, and windstorms. Climate phenomena exacerbated by global climate change are not unique to this region but reflect a broader trend of worldwide environmental changes. However, how local communities in tropical cities in the global south adapt to these extreme events is not fully understood. Understanding local adaptation strategies is crucial in enhancing our ability to develop context-specific policies that address climate vulnerabilities. This study aimed to analyse the adaptation and mitigation strategies employed by the urban residents of Abuja and Ouagadougou in response to recurrent floods, heat waves, and windstorms. To investigate adaptation and mitigation strategies for climate change in urban areas, this study collected quantitative data from a sample of 840 households in Abuja and 840 households in Ouagadougou. The results revealed that the participants of each city used different strategies to adapt to and mitigate heat waves, floods, and windstorms. However, the level of adoption of these measures differed among the respondents. The findings revealed a low level of adoption of climate change mitigation measures. Context-specific policies must prioritise strengthening local adaptation strategies, addressing socioeconomic disparities, and fostering urban design solutions tailored to each city’s unique environmental and infrastructural challenges. Full article

Climate change amplifies heat wave effects on outdoor thermal comfort by increasing their frequency, duration, and intensity. The urban heat island effect worsens heat risks in cities and impacts resilience. Nature-based solution (NBS) with tree plantation was reported as an effective mitigation measure. This simulation study, by the well-validated ENVI-met model, aimed to investigate the impact of different tree planting strategies and building parameters on urban heat risk mitigation and microclimate during a typical hot summer day. Hypothetical skyscrapers and super high-rise buildings were assumed in the study site located in southern China. Adopting meteorological inputs from a typical year, the simulation results revealed that both mean radiant temperature (T_mrt) and physiological equivalent temperature (PET) were elevated (T_mrt > 60 °C and PET > 50 °C) in early afternoon in sunlit areas. Three mitigation approaches with different tree planting locations were investigated. While all approaches demonstrated effective cooling (PET down to <35 °C) in the proximity of trees, a superior approach for mitigating the heat risks was not evident. Within the building array, the shade of bulky structures also lowered T_mrt and PET to a thermally comfortable level in the late afternoon. Combining open-space tree planting with optimized building designs is recommended to mitigate heat risks and enhance urban resilience while promoting outdoor activities and their health benefits. Full article

Global warming and the increasing frequency and intensity of heat waves are resulting in more frequent unfavourable weather conditions for outdoor activities, especially during the summer. The building environment can alter weather conditions, resulting in higher temperatures (urban heat island). Human towers are cultural activities that typically take place outdoors and were declared a UNESCO Intangible Cultural Heritage in 2010. The objectives of this study are (i) to analyse the weather conditions (i.e., temperature and relative humidity) during the human tower exhibitions, (ii) to determine discomfort during the exhibitions based on the heat index (HI) resulting from the combination of temperature and humidity, and (iii) to compare records from the square with those recorded in the nearest automatic meteorological station (AMS) belonging to the Catalan Meteorological Service network. To determine the weather conditions in the squares during the human tower exhibitions, a pair of sensors recorded temperature and relative humidity data in six exhibitions performed in the summer of 2024. The temperature exceeded 30 °C in five of the six human tower exhibitions analysed. In the cases of the Santa Anna exhibition (El Vendrell) and the Sant Fèlix exhibition (Vilafranca del Penedès), one of the sensors recorded temperatures above 30 °C throughout the entire duration of the exhibition. There was a predominance of HI values falling within the caution threshold in the two sensors of three exhibitions and within the extreme caution threshold in the two sensors of the other three exhibitions. The temperature is higher in urban squares than in the surrounding rural areas. The key factor is the urban heat island phenomenon, which poses health risks to both human tower builders and attendees. Adaptation measures are therefore necessary to guarantee the safety of the participants. Full article

The intensification of extreme temperature events driven by climate change has heightened the vulnerability of urban areas to heatwaves, making it a critical environmental challenge. In this study, we investigate the spatial characteristics of urban heatwave vulnerability in Jungang-dong, Gangneung—a representative mid-sized coastal city in South Korea that experiences a strong urban heat island (UHI) effect due to the prevalent land–sea breeze dynamics, high building density, and low green-space ratio. A representative heatwave day (22 August 2024) was selected using AWS data from the Korea Meteorological Administration (KMA), and hourly meteorological conditions were applied to Computational Fluid Dynamics (CFD) simulations to model the urban microclimates. The thermal stress levels were quantitatively assessed using the Universal Thermal Climate Index (UTCI). The results indicated that, at 13:00, the surface temperatures reached 40 °C and the UTCI values peaked at 43 °C, corresponding to a “Very Strong Heat Stress” level. Approximately 17.4% of the study area was identified as being under extreme thermal stress, particularly in densely built-up zones, roadside corridors with high traffic, and pedestrian commercial areas. Based on these findings, we present spatial analysis results that reflect urban morphological characteristics to guide the optimal allocation of urban cooling strategies, including green (e.g., street trees, urban parks, and vegetated roofs), smart, and engineered infrastructure. These insights are expected to provide a practical foundation for climate adaptation planning and thermal environment improvement in mid-sized urban contexts. Full article

The increasing frequency and intensity of heat waves, combined with urban heat islands (UHIs), pose significant public health challenges. Implementing low-cost, real-time monitoring networks with distributed stations within the smart city framework faces obstacles in transforming urban spaces. Accurate data are essential for assessing these effects. This paper compares different network types in a medium-sized city in western Spain and their implications for UHI identification quality. The study first presents a purpose-built monitoring network using Open-Source platforms, IoT technology, and LoRaWAN communications, adhering to World Meteorological Organization guidelines. Additionally, it evaluates two citizen weather observer networks (CWONs): one from a commercial smart device company and another from a global community connecting environmental sensor data. The findings highlight several advantages of bespoke monitoring networks over CWON, including enhanced data accessibility and greater flexibility to meet specific requirements, facilitating adaptability and scalability for future upgrades. However, specialization is crucial for effective deployment and maintenance. Conversely, CWONs face limitations in network uniformity, data shadow zones, and insufficient knowledge of real sensor situations or component characteristics. Furthermore, CWONs exhibit some data inconsistencies in probability distribution and scatter plots during extreme heat periods, as well as improbable UHI temperature values. Full article

This study analyzes biometeorological conditions during summer heat events in 11 cities located in different regions of Poland in the summer months from 2020 to 2024. Heat days (defined as days with a maximum temperature exceeding 30 °C) and heatwaves (defined as at least three consecutive days with a maximum temperature above 30 °C) were identified. Biometeorological conditions were assessed based on the Universal Thermal Climate Index (UTCI) and heart rate (HR), assuming a metabolic heat production of 135 W∙m⁻² for an adult human. The indices were calculated using the BioKlima 2.6 software. The findings reveal that all cities experienced significant thermal stress during heat events. The maximum UTCI values during heat days indicated strong and very strong heat stress. During the most intense heatwaves, assessed using the Heat Wave Severity (HWS) index, these categories of heat stress occurred 20–30% of the time. Simultaneously, the mean daily heart rates exceeded the warning threshold of 90 beats per minute. Differences in biometeorological conditions were found between urban centers and places located outside the center, where strong heat conditions occurred less frequently. The results indicate that biometeorological conditions imposing thermal stress on the human body were present in all Polish cities during the analyzed five-year period. In Warszawa, Wrocław, and Rzeszów, heatwaves and heat stress occurred annually. Full article

In the recent decades, an ongoing increase in maximum temperature during summer has been observed in Poland, especially in the central-southern and southeastern areas. This raises the vulnerability of these regions not only to heat waves and drought but also to floods. The potential effect of compound heat waves and extreme rainfall events may be more serious than the effects of these events occurring separately. This research is the first attempt in Poland to investigate whether the presence of a heat wave increases the likelihood of extreme rainfall events, if so, by how much, and whether this changes with warming. For this purpose, we used daily maximum temperature values and 6 h precipitation datasets from 44 meteorological stations in Poland for the 1966–2024 period. It was proven that compound heat wave and extreme rainfall events occurred in Poland with spatially differentiated frequency. They occurred the least frequently on the coast and the most frequently in southwestern, southeastern, and northeastern Poland. The extreme rainfall occurred most often between noon and midnight on the last heat wave day. During these hours, the likelihood of extreme rainfall is, on average, 3.5 times higher than that expected according to climatology norms. With warming, the frequency of days with these compound events increases at the rate of 1.22 days per decade, and the frequency of compound events increases at a rate of 3.75 events per decade. Although a detailed analysis of the mechanisms responsible for such events is planned for further research, the preliminary study revealed that in most cases, the approach of a cold front with a mesoscale thundercloud system was responsible for heat wave termination with extreme rainfall. Since we cannot prevent the growing number of heat waves or heavy precipitation events that terminate the heat wave events in Poland, the adaptation strategy needs to be implemented to meet the sustainable development goals regarding climate actions. This refers primarily to urban planning, agriculture (agroecosystems), social health, and well-being. Full article

Low-cost sensors (LCSs) emerge as a popular tool for urban micro-climate studies by offering dense observational coverage. This study evaluates the performance of PurpleAir (PA) sensors for ambient temperature monitoring—a key but underexplored aspect of their use. While widely used for particulate matter, PA sensors’ temperature data remain underutilized and lack thorough validation. For the first time, this research evaluates their accuracy by comparing PA temperature measurements with collocated high-precision temperature data loggers across a dense urban network in a humid subtropical U.S. county. Results show a moderate correlation with reference data (r = 0.86) but an average overestimation of 3.77 °C, indicating PA sensors are better suited for identifying temperature trends but not for precise applications like extreme heat events. We also developed and compared eight calibration methods to create a replicable model using readily available crowdsourced data. The best-performing model reduced RMSE and MAE by 51% and 47%, respectively, and achieved an R² of 0.89 compared to the uncalibrated scenario. Finally, the practical application of PA temperature data for identifying heat wave events was investigated, including an assessment of associated uncertainties. In sum, this work provides a crucial evaluation of PA’s temperature monitoring capabilities, offering a pathway for improved heat mapping, multi-hazard vulnerability assessments, and public health interventions in the development of climate-resilient cities. Full article

Extreme weather events and rising temperatures pose significant risks, not only in urban areas but also in metropolitan forests, that affect the well-being of the people who visit them. City forests are considered one of the best bets for mitigating high temperatures within civic areas. Such areas modulate microclimates in contemporary cities, offering environmental, social, and economic advantages. Therefore, comprehending the intricate relationships between municipal forests and the climatic changes of various destinations is crucial for attaining healthier and more sustainable city environments for people. In this research, the thermal comfort index (Modified Temperature–Humidity Index (MTHI)) has been analysed using Landsat images of six urban forests in London during July 2022, when the area first experienced record-breaking temperatures of over 40 °C. Our results show a significant growth in the MTHI that goes from 2.5 (slightly hot) under normal conditions to 3.4 (hot) during the heat wave period. This situation intensifies the environmental discomfort for visitors and highlights the necessity to enhance their adaptability to future temperature increases. In turn, it was found that the places most affected by heat waves are those that have grass cover or that have small associated buildings. Conversely, forested regions or those with lakes and/or ponds exhibit lower temperatures, which results in enhanced resilience. These findings are noteworthy in their concentration on one of the UK’s most severe heat waves and illustrate the efficacy of integrating spectral measurements with statistical analyses to formulate customized regional initiatives. Therefore, the results reported will allow the implementation of new planning and adaptation policies such as incorporating thermal comfort into planning processes, improving green and blue amenities, increasing tree densities that are resilient to rising temperatures, and increasing environmental comfort conditions in metropolitan forests. Finally, the applicability of this approach in similar urban contexts is highlighted. Full article

A total of 108 maximum Kolmogorov entropy (S_K) values, calculated by means of chaos theory, are obtained from 108 time series (TSs) (each consisting of 28,463 hourly data points). The total TSs are divided into 54 urban meteorological (temperature (T), relative humidity (RH) and wind speed magnitude (WS)) and 54 pollutants (PM₁₀, PM_2.5 and CO). The measurement locations (6) are located at different heights and the data recording was carried out in three periods, 2010–2013, 2017–2020 and 2019–2022, which determines a total of 3,074,004 data points. For each location, the sum of the maximum entropies of urban meteorology and the sum of maximum entropies of pollutants, S_{K, MV} and S_{K, P}, are calculated and plotted against h, generating six different curves for each of the three data-recording periods. The tangent of each figure is determined and multiplied by the average temperature value of each location according to the period, obtaining, in a first approximation, the magnitude of the entropic forces associated with urban meteorology (F_{K, MV}) and pollutants (F_{K, P}), respectively. It is verified that all the time series have a fractal dimension, and that the fractal dimension of the pollutants shows growth towards the most recent period. The entropic dynamics of pollutants is more dominant with respect to the dynamics of urban meteorology. It is found that this greater influence favors subdiffusion processes (α < 1), which is consistent with a geographic basin with lower atmospheric resilience. By applying a heavy-tailed probability density analysis, it is shown that atmospheric pollution states are more likely, generating an extreme environment that favors the growth of respiratory diseases and low relative humidity, makes heat islands more stable over time, and strengthens heat waves. Full article