Synergy of Urban Heat, Pollution, and Social Vulnerability in One of America's Most Rapidly Growing Cities: Houston, We Have a Problem.

During the first two decades of the twenty-first century, we analyze the expansion of urban land cover, urban heat island (UHI), and urban pollution island (UPI) in the Houston Metropolitan Area (HMA) using land cover classifications derived from Landsat and land/aerosol products from NASA's Moderate Resolution Imaging Spectroradiometer. Our approach involves both direct utilization and fusion with in situ observations for a comprehensive characterization. We also examined how social vulnerability within the HMA changed during the study period and whether the synergy of UHI, UPI, and social vulnerability enhances environmental inequalities. We found that urban land cover within the HMA increased by 1,345.09 km2 and is accompanied by a 171.92 (73.93) % expansion of the daytime (nighttime) UHI. While the UPI experienced an overall reduction in particulate pollution, the magnitude of change is smaller compared to the surroundings. Further, the UPI showed localized enhancement in particulate pollution caused by increases in vehicular traffic. Our analysis found that the social vulnerability of the HMA urban regions increased during the study period. Overall, we found that the urban growth during the first two decades of the twenty-first century resulted in a synergy of UHI, UPI, and social vulnerability, causing an increase in environmental inequalities within the HMA.

The urban island: climatic suitability of Linepithema humile (Hymenoptera: Formicidae) and the role of cities in the invasion of the Western Palearctic.

Urban environments often present environmental conditions that facilitate the introduction and establishment of nonnative and invasive species. These can expand their range into areas with unfavorable climates by taking advantage of the ecological and climatic homogenization of cities, bypassing the ecological barriers presented by the surrounding environment. One way to monitor the expansion of these species is using potential distribution models. We used as a model species the Argentine ant, Linepithema humile (Hymenoptera: Formicidae) whose invasion has caused serious consequences for biodiversity and economic losses worldwide. We used the average result of six different algorithms and used climatic variables and population density as a proxy for the urbanization level in the Western Palearctic to build the predictive model. The model indicates this ant prefers to inhabit areas with Mediterranean and Temperate Oceanic climates and that its suitability depends on two main factors: the continentality (temperature annual range) and the degree of urbanization. The species is predicted to be absent in areas with large temperature contrasts throughout the year, particularly in rural and peri-urban areas (i.e. adjacent to urban areas) of inland regions. Conversely, the species has a predilection for coastal and urban areas where environmental conditions are attenuated by the influence of the sea or the "urban heat island" effect in the case of inland cities. In this sense, cities act as "bioclimatic islands" facilitating the establishment of the Argentine ant as a reservoir, enlarging its distribution into climatically nonoptimal areas, and promoting its future expansion in a scenario of global warming and socioeconomic change.

Investigating the effects of the greenery increase on air temperature, ventilation and cooling energy demand in Melbourne with the Weather Research and Forecasting model and Local Climate Zones.

Vegetation has a well-known potential for mitigating urban overheating. This work aims to explore the effects of enhancing urban greenery in Melbourne (Australia) through a configuration of the Weather Research and Forecasting (WRF) model including the Building Effect Parameterization and the Local Climate Zones and presents novelties in: i) covering two-months and ii) focusing on air circulation and buildings cooling energy demand through the ventilation coefficient (VC) and the cooling degree hours (CDHs). A control case and two "what-if" scenarios with a growing green coverage equal to 35 % (control case), 50 % (modest increase) and 60 % (robust increase) have been designed and then simulated for January and February 2019. Outcomes reveal a maximum drop in 2 m temperature of approximately 0.4 °C and 0.8 °C at 14:00 LT for the modest and robust green increase scenario, respectively. The urban-rural energy surplus for cooling buildings is reduced and even counterbalanced. Peak CDHs decrease from 143 °C·h of the control case to 135 °C·h (modest increase) and 126 °C·h (robust increase), while they measure 137 °C·h in the non-urban areas. Average wind speed increases by 0.8 m/s (equal to 22 % with respect to the control case). Furthermore, adding urban greenery has an unfavorable implication on VC (maximum reduction of 500 m2s-1) with a consequent deterioration of the transport and dispersion of pollutants. Middle- and high-density classes are touched more than low-density by the VC reduction. In addition, the benefits of enhancing urban greenery concern physiologically and psychologically the quality of life of the dwellers.

Quantitative assessment of interplay between urbanization dynamics and land surface temperature variations using generalized additive model coupled PDP for sustainable urban planning and management.

The mountainous region of Asir is experiencing rapid and unsystematic urbanization leading to an increase in land surface temperatures (LST), which poses a challenge to human well-being and ecological balance. Therefore, it is necessary to study the interaction between land use and land cover (LULC)-induced urbanization and LST using advanced geostatistical techniques. In addition, understanding the urbanization process and urban density is essential for effective urban planning and management. The aim of this study was to investigate the interaction between the urbanization process, urban density and the associated LST. Using the Random Forest Algorithm, LULC mapping was conducted for the years 1990, 2000 and 2020. Metrics such as land cover change rate (LCCR), land cover index (LCI), landscape expansion index (LEI), mean landscape expansion index (MLEI) and area-weighted landscape expansion index (AWLEI) were used to understand urbanization processes and LULC changes. Convolutional kernels were used to model urban density, and the mono-window algorithm was applied to analyse LST in the selected years. In addition, the study assessed the Surface Urban Heat Island (SUHI) contribution index to LULC and used Generalized Additive Models (GAMs) in conjunction with Partial Dependence Plots (PDPs) to understand the relationship between urbanization processes, urban density and LST. In a detailed 30-year study, the application of the RF algorithm showed significant shifts in LULC with an overall validation accuracy of over 85%. Urban areas grew dramatically from 69.40 km2 in 1990 to 338.74 km2 in 2020, while water areas decreased from 1.51 to 0.54 km2. Dense vegetation increased from 43.36 to 52.22 km2, indicating positive ecological trends. The LST analysis showed a general warming, with the mean LST increasing from 40.51 °C in 1990 to 46.73 °C in 2020 and the highest temperature category (50-60 °C) increasing from 0.78 to 33.35 km2. The built-up area of cities tripled between 1990 and 2020, with the Landscape Expansion Index reflecting significant growth in suburban areas. The modeling of urban density shows increasing urbanization in the centre, which will expand significantly to the east by 2020. The contribution of LULC to LST and the Urban Heat Island (SUHI) effect was evident, with built-up areas showing a constant temperature increase. GAMs confirmed a statistically significant relationship between urban density and LST, with different effects for different types of urban expansion. This comprehensive study quantitatively sheds light on the complicated dynamics of urbanization, land cover change and temperature variation and provides important insights for sustainable urban development.

Effects of urbanization on cloud-to-ground lightning strike frequency: a global perspective.

Urbanization tends to increase local lightning frequency (i.e. the 'lightning enhancement' effect). Despite many urban areas showing lightning enhancement, the prevalence of these effects is unknown and the drivers underlying these patterns are poorly quantified. We conducted a global assessment of cloud-to-ground lightning flashes (lightning strikes) across 349 cities to evaluate how the likelihood and magnitude of lightning enhancement vary with geography, climate, air pollution, topography and urban development. The likelihood of exhibiting lightning enhancement increased with higher temperature and precipitation in urban areas relative to their natural surroundings (i.e. urban heat islands and elevated urban precipitation), higher regional lightning strike frequency, greater distance to water bodies and lower elevations. Lightning enhancement was stronger in cities with conspicuous heat islands and elevated urban precipitation effects, higher lightning strike frequency, larger urban areas and lower latitudes. The particularly strong effects of elevated urban temperature and precipitation indicate that these are dominant mechanisms by which cities cause local lightning enhancement.

Spatiotemporal changes of urban heat island effect relative to land surface temperature: a case study of Jinan City, China.

The urban heat island (UHI) effect has become increasingly prevalent and significant with the accelerated pace of urbanization, posing challenges for urban planners and policymakers. To reveal the spatiotemporal variations of the urban heat island effect in Jinan City, this study utilized Landsat satellite images from 2009, 2014, and 2019, employing the classic Mono-Window algorithm to extract land surface temperature (LST). Additionally, Geodetector was introduced to conduct a detailed analysis of the relationship between LST in Jinan City and land cover types (vegetation, water bodies, and buildings). The results indicate a significant increase in the severity of the urban heat island effect in Jinan from 2009 to 2019, with the central urban area consistently exhibiting a high-intensity core heat island. Suburban areas of Jinan show a clear trend of merging their heat island effects with the central urban area. The combined area of strong cool island effect zones and cool island effect zones within water bodies reaches 89.7%, while the combined proportion of heat island and strong heat island effect zones in building areas is 62.2%. Vegetation cover (FVC) exerts the greatest influence among all factors on the intensity level of the urban heat island effect. These findings provide a reliable basis for decision-making related to urban planning and construction in Jinan City.

Evaluating Nature-based Solutions as urban resilience and climate adaptation tools: A meta-analysis of their benefits on heatwaves and floods.

Extreme weather events driven by climate change threaten the resilience of urban structures and urban dwellers. Nature-based Solutions (NbS) are an effective tool to reduce urban vulnerability to climate risks and, at the same time, develop more liveable urban areas. Despite the acknowledged positive impacts of individual observed NbS, numerous questions persist unanswered. While existing research supports NbS' positive influence on urban climate adaptation, the extent of their impact remains insufficiently studied. Understanding the magnitude of NbS impact is crucial for justifying their preference over non-NbS alternatives and, consequently, for securing public investment. Via a meta-analysis, this paper aims to contribute to research and practice by providing a more systematic assessment of NbS effects, offering urban planners and decision-makers a robust justification for their incorporation in climate change adaptation, urban resilience, and enhanced liveability. The results of the meta-analytic model indicate that the effect of NbS is indeed positive. When assessing the impact on temperature and flood protection, there is a general positive effect across the studied NbS. However, when evaluating an average effect, the task appears to be more complex due to methodological issues and limitations. The need to increase the formalisation of how the impact of NbS is measured and reported also emerges as a result. Replicable protocols would positively impact the formalisation of the literature on the topic and positively affect the evidence-based support for the implementation of NbS by urban decision-makers.

On urban microclimate spatial-temporal dynamics: Evidence from the integration of fixed and wearable sensing and mapping techniques.

Urban Heat Island (UHI) is acknowledged to generate harmful consequences on human health, and it is one of the main anthropogenic challenges to face in modern cities. Due to the urban dynamic complexity, a full microclimate decoding is required to design tailored mitigation strategies for reducing heat-related vulnerability. This study proposes a new method to assess intra-urban microclimate variability by combining for the first time two dedicated monitoring systems consisting of fixed and mobile techniques. Data from three fixed weather stations were used to analyze long-term trends, while mobile devices (a vehicle and a wearable) were used in short-term monitoring campaigns conducted in summer and winter to assess and geo-locate microclimate spatial variations. Additionally, data from mobile devices were used as input for Kriging interpolation in the urban area of Florence (Italy) as case study. Mobile monitoring sessions provided high-resolution spatial data, enabling the detection of hyperlocal variations in air temperature. The maximum air temperature amplitudes were verified with the wearable system: 3.3 °C in summer midday and 4.3 °C in winter morning. Physiological Equivalent Temperature (PET) demonstrated to be similar when comparing green areas and their adjacent built-up zone, showing up the microclimate mitigation contribution of greenery in its surrounding. Results also showed that mixing the two data acquisition and varied analysis techniques succeeded in investigating the UHI and the site-specific role of potential mitigation actions. Moreover, mobile dataset was reliable for elaborating maps by interpolating the monitored parameters. Interpolation results demonstrated the possibility of optimizing mobile monitoring campaigns by focusing on targeted streets and times of day since interpolation errors increased by 10% only with properly reduced and simplified input samples. This allowed an enhanced detection of the site-specific granularity, which is important for urban planning and policymaking, adaptation, and risk mitigation actions to overcome the UHI and anthropogenic climate change effects.

Estimated mortality attributable to the urban heat island during the record-breaking 2022 heatwave in London.

The United Kingdom experienced its most extreme heatwave to date during late July 2022, with maximum air temperatures exceeding 40 °C recorded for the first time in history on July 19th. High ambient temperatures have been statistically shown to lead to increased mortality. Higher nighttime temperatures that occur in more urbanised areas, called the urban heat island (UHI), may contribute to the mortality burden of heat. In this study, we applied health impact assessment methods with advanced urban climate modelling to estimate what contribution the UHI had on the mortality impact of the 10-25 July 2022 heatwave in Greater London. Estimated mortality due to heat and due to the UHI were compared with estimated mortality due to air pollution in the same period, based on monitored concentrations. We estimate that of the 1773 deaths in Greater London in this period 370 (95% confidence interval 328-410) could be attributed to heat. We estimate that 38% of these heat-related deaths could be attributed to the UHI. In the same period is estimate deaths attributable to PM2.5 were 20.6 (10.4-30.8) and to ozone were 52.3 (95% confidence interval 18.6-85.2). Despite not contributing to the record-breaking maximum air temperature observed during this period, the UHI may have contributed to the heatwave's mortality burden through raised nighttime temperature. While air pollutant concentrations were elevated during the period, deaths attributable to air pollution were relatively few compared to deaths attributable to heat.

Linking the macroclimatic niche of native lithophytic ferns and their prevalence in urban environments.

PREMISE: Vertical surfaces in urban environments represent a potential expansion of niche space for lithophytic fern species. There are, however, few records of differential success rates of fern species in urban environments. METHODS: The occurrence rates of 16 lithophytic fern species native to the northeastern USA in 14 biomes, including four urban environments differentiated by percentage of impervious surfaces, were evaluated. In addition, the natural macroclimatic ranges of these species were analyzed to test whether significant differences existed in climatic tolerance between species that occur in urban environments and species that do not. RESULTS: Three species appear to preferentially occur in urban environments, two species may facultatively occur in urban environments, and the remaining 11 species preferentially occur in nondeveloped rural environments. The natural range of fern species that occur in urban environments had higher summer temperatures than the range of species that do not, whereas other macroclimatic variables, notably winter temperatures and precipitation, were less important or insignificant. CONCLUSIONS: Vertical surfaces in urban environments may represent novel niche space for some native lithophytic fern species in northeastern USA. However, success in this environment depends, in part, on tolerance of the urban heat island effect, especially heating of impervious surfaces in summer.

Comprehensive spatiotemporal evaluation of urban growth, surface urban heat island, and urban thermal conditions on Java island of Indonesia and implications for urban planning.

Urban heat island (UHI) and thermal comfort conditions are among the impacts of urbanization, which have been extensively studied in most cities around the world. However, the comprehensive studies in Indonesia in the context of urbanization is still lacking. This study aimed to classify land use and land cover (LULC) and analyse urban growth and its effects on surface urban heat islands (SUHIs) and urban thermal conditions as well as contributing factors to SUHI intensity (SUHII) using remote sensing in the western part of Java Island and three focused urban areas: the Jakarta metropolitan area (JMA), the Bandung and Cimahi Municipalities (BC), and the Sukabumi Municipality (SKB). Landsat imagery from three years was used: 2000, 2009, and 2019. Three types of daytime SUHII were quantified, namely the SUHII of urban central area and two SUHIIs of urban sprawl area. In the last two decades, urban areas have grown by more than twice in JMA and SKB and nearly 1.5 times in BC. Along with the growth of the three cities, the SUHII in the urban central area has almost reached a magnitude of 6 °C in the last decade. Rates of land surface temperature change of the unchanged urban pixels have magnitudes of 0.25, 0.15, and 0.14 °C/year in JMA, SKB, and BC, respectively. The urban thermal field variance index (UTFVI) and discomfort index (DI) showed that the strongest SUHI effect was most prevalent in urban pixels and the regions were mostly in the very hot and hot categories. Anthropogenic heat flux and urban ratio have positive contributions to SUHII variation, while vegetation and water ratios are negative contributors to SUHII variation. For each city, the contributing factors have a unique magnitude that can be used to evaluate SUHII mitigation options.

Quantitative assessment and driving factors analysis of surface urban heat island of urban agglomerations in China based on GEE.

The urban heat island (UHI) effect generated by the development of high-speed urbanization has become one of the major problems affecting the urban ecological environment. As the main body of urbanization in China, China's urban agglomerations are the core areas of urban heat island effect. The purpose of this study is to study the spatial-temporal characteristics and driving factors of surface urban heat island in 19 urban agglomerations in China, with a view to providing theoretical references for the prevention of urban thermal environmental risks. Based on Google Earth Engine (GEE), this paper estimated the surface urban heat island intensity (SUHII) of 19 urban agglomerations in China from 2003 to 2019 using MODIS land surface temperature (LST) data. Correlation analysis and regression analysis were used to explore the correlation between the change of SUHII and driving factors. Finally, the driving factors of SUHII were detected by the geo-detector model. Results showed that (1) the SUHII of 19 urban agglomerations in arid and semi-arid areas of northwestern China is higher than that in humid areas of eastern and southeastern China. (2) The SUHII of 19 urban agglomerations in China generally shows a decreasing trend, and the spatial variation of the change trend is significant. (3) There are positive correlations between SUHII and reference evapotranspiration (ET0), population density (POP), gross domestic product (GDP), nitrogen dioxide (NO2), ozone (O3), and ultraviolet aerosol index (UVAI); negative correlations with normalized difference vegetation index (NDVI), DEM, sulfur dioxide (SO2), carbon monoxide (CO), and formaldehyde (HCHO); the correlations all pass the significance test of P < 0.05 and are statistically significant. (4) The factor detection results showed that NDVI, land cover type (LC), and UVAI were the main driving factors of SUHII. The interaction detection results showed that the interaction between O3 and UVAI had the most significant impact on SUHII.

Non-negligible clear-sky biases of satellite thermal infrared observations for analyzing surface urban heat island intensity: A case study in China.

Surface urban heat island (SUHI) intensity generally determined by satellite-derived clear-sky land surface temperature (LST) has ignored the impacts of cloud coverage and cannot reflect the real SUHI intensity. Only a few studies focus on the effects of this issue based on short-time LST datasets, which could contain non-negligible uncertainties to summarize reliable rules. To investigate the influence, the SUHI intensity (SUHII) clear-sky bias (CSB), which is defined as the SUHII difference between clear-sky and all-weather conditions, was investigated in 35 cities in China, based on clear-sky and all-weather LST datasets from 2003 to 2022. Results show that the two SUHIIs show similar spatial distribution patterns, with stronger SUHIs in southern China at daytime and weaker at nighttime. However, a non-negligible difference can be found between these two SUHIIs, with a SUHII CSB range of -1.43 to 2.27 °C at daytime and - 2.17 to 0.91 °C at nighttime. In terms of intra-annual variation, SUHII CSBs in similar climate regions exhibit similar patterns but different ranges due to their different natural properties. Generally, intra-annual variations of SUHII CSB can be divided into three groups, i.e., "Table Mountain", single peak, and single valley, varying across climate regions and years. The main reason for SUHII CSB was analyzed, i.e., spatial gaps of the data directly caused the SUHII CSB, and the thermal properties and meteorological conditions of the missing pixels affect the magnitude of the SUHII CSB. Taking the urban system as an example, this study has provided evidence of the non-negligible SUHII clear-sky bias to emphasize the importance of using all-weather LST for relevant studies.

A Heat Emergency: Urban Heat Exposure and Access to Refuge in Richmond, VA.

The urban heat island effect exacerbates independent climate change-induced shifts toward longer, stronger, and more frequent heat extremes. Environmental inequity, driven by a history of racially motivated urban planning policies, has led particular demographics to bear the worst impacts of urban heat exposure and thus also climate change. These impacts cause adverse health outcomes in the form of heat emergencies. Through a novel demographic and spatial analysis of heat-related illness Emergency Medical Services data from Richmond, Virginia, this study investigates the relationships between heat health emergencies and intra-urban heat islands quantified through three heat exposure metrics. We also evaluate the accessibility of built refuge from urban heat in the form of public transit infrastructure, libraries, and government cooling centers in relation to these emergencies. We found that heat emergencies are inequitably distributed among racial, age, and socioeconomic groups in Richmond, particularly among residents identified as Male, Black or African American, 50+ years old, and experiencing mental health, intoxication, and/or homelessness. We found significant associations between the location of these heat emergencies and urban heat islands as estimated from remotely-sensed surface and community science-derived air temperature metrics, but not a co-estimated heat index. We also found that available refuge facilities are insufficiently located to protect individuals with reduced mobility across areas with the highest number of heat-related health emergencies. Community involvement in the mitigation and management of extreme heat threats, especially for those disproportionately impacted, is necessary to decrease the number of summertime heat illnesses.

Assessing the land use dynamics and thermal environment using geospatial techniques in the industrial city of Chotanagpur Plateau Region, India.

The phenomenon of urban heat island (UHI) is characterized by industrial, economic development, unplanned and unregulated land use as well as a rapid increase in urban population, resulting a warmer inner core in contrast to the surrounding natural environment, thus requiring immediate attention for a sustainable urban environment. This study examined the land use/land cover (LULC) change, pattern of spectral indices (Normalized Difference Vegetation Index, NDVI; Normalized Difference Water Index, NDWI; Normalized Difference Built-up Index, NDBI and Normalized Difference Bareness Index, NDBaI), retrieval of land surface temperature (LST) and Urban Thermal Field Variance Index (UTFVI) as well as identification of UHI from 2000 to 2022. The relationship among LST and LULC spectral indices was estimated using Pearson's correlation coefficient. The Landsat-5 (TM) and Landsat-8 (OLI/TIRS) satellite data have been used, and all tasks were completed through various geospatial tools like ArcGIS 10.8, Google Earth Engine (GEE), Erdas Imagine 2014 and R-Programming. The result of this study depicts over the period that built-up area and water bodies increased by 119.78 and 35.70%, respectively. On the contrary, fallow and barren decreased by 55.33 and 32.31% respectively over the period. The mean and maximum LST increased by 3.61 °C and 2.62 °C, and the study reveals that a high concentration of UTFVI and UHI in industrial areas, coal mining sites and their surroundings, but the core urban area has observed low LST and intensity of UHI than the peripheral areas due to maintained vegetation cover and water bodies. An inverse relationship has been found among LST, NDVI and NDWI, while adverse relationships were observed among LST, NDBI and NDBaI throughout the period. Sustainable environment planning is needful for the urban area, as well as the periphery region and plantation is one of the controlling measures of LST and UHI increment. This work provides the scientific base for the study of the thermal environment which can be one of the variables for planning of Asansol City and likewise other cities of the country as well as the world.

Analysis of urban residential greening in tropical climates using quantitative methods.

Urban green spaces play a crucial role in mitigating urban heat islands, providing shade, cooling, absorbing carbon dioxide, and releasing oxygen to enhance air quality. Understanding the user perceptions of residential greeneries is essential for effective planning and implementation of greening systems. This quantitative research explored user perceptions and preferences regarding residential greeneries through a structured questionnaire survey from 578 respondents. The responses from the densely populated Chennai city and the rest of Tamil Nadu, India, were analyzed. About 90% of residents are interested in having a garden, irrespective of location and residential characteristics. The most available space in Chennai's urban region is a balcony at 45%, followed by front and back gardens at 30% and vice versa for Chennai's suburban areas. The most preferred type is potted plants (30%) and climbers (20%) on balconies and near windows in Chennai. The most perceived challenges are installation and maintenance costs. The most influencing factors over the preference for greeneries and green walls are the house typology, house ownership, and site location. This study provides more insights to building designers and architects on planning and implementation of residential greeneries as per end users' preferences and perceptions.

Evaluating the impact of urbanization on the urban heat islands through integrated radius and non-linear regression approach.

Urban heat islands (UHIs) are a significant environmental problem, exacerbating the urban climate and affecting human health in the Asir region of Saudi Arabia. The need to understand the spatio-temporal dynamics of UHI in the context of urban expansion is crucial for sustainable urban planning. The aim of this study was to quantify the changes in land use and land cover (LULC) and urbanization, assess the expansion process of UHI, and analyze its connectivity in order to develop strategies to mitigate UHI in an urban context over a 30-year period from 1990 to 2020. Using remote sensing data, LULC changes were analyzed with a random forest model. LULC change rate (LCCR), land cover intensity (LCI), and landscape expansion index (LEI) were calculated to quantify urbanization. The land surface temperature for the study period was calculated using the mono-window algorithm. The UHI effect was analyzed using an integrated radius and non-linear regression approach, fitting SUHI data to polynomial curves and identifying turning points based on the regression derivative for UHI intensity belts to quantify the expansion and intensification of UHI. Landscape metrics such as the aggregation index (AI), landscape shape index (LSI), and four other matrices were calculated to assess UHI morphology and connectivity of the UHI. In addition, the LEI was adopted to measure the extent of UHI growth patterns. From 1990 to 2020, the study area experienced significant urbanization, with the built-up area increasing from 69.40 to 338.74 km2, an increase of 1.923 to 9.385% of the total area. This expansion included growth in peripheral areas of 129.33 km2, peripheral expansion of 85.40 km2, and infilling of 3.80 km2. At the same time, the UHI effect intensified with an increase in mean LST from 40.55 to 46.73 °C. The spatial extent of the UHI increased, as shown by the increase in areas with an LST above 50 °C from 36.58 km2 in 1990 to 133.52 km2 in 2020. The connectivity of the UHI also increased, as shown by the increase in the AI from 38.91 to 41.30 and the LSI from 56.72 to 93.64, reflecting a more irregular and fragmented urban landscape. In parallel to these urban changes, the area classified as UHI increased significantly, with the peripheral areas expanding from 23.99 km2 in the period 1990-2000 to 80.86 km2 in the period 2000-2020. Peripheral areas also grew significantly from 36.42 to 96.27 km2, contributing to an overall more pronounced and interconnected UHI effect by 2020. This study provides a comprehensive analysis of urban expansion and its thermal impacts. It highlights the need for integrated urban planning that includes strategies to mitigate the UHI effect, such as improving green infrastructure, optimizing land use, and improving urban design to counteract the negative effects of urbanization.

Assessing urban heat island mitigation potential of realistic roof greening across local climate zones: A highly-resolved weather research and forecasting model study.

Given their multifold benefits, green roofs are often considered to mitigate the urban heat island (UHI) effect. Most mesoscale studies consider 100 % green roof fraction or the same green roof fraction in each urban land use category while analysing the influence of green roofs on the UHI effect, which can overestimate their impact on UHI. Consequently, the impact of green roofs evaluated in these studies may not be suitable for informing policy decisions. Furthermore, the effect of morphologies on temperature reduction due to green roofs has not been previously studied. To address this gap, in this paper, we evaluate the impact of a realistic fraction of green roofs specific to the respective local climate zones (LCZ) on the UHI effect during a heatwave in Liège, Belgium, employing a high-resolution WRF study using the BEP-BEM parameterisation with LCZ land use classification. The realistic fraction is estimated for every LCZ class based on the average percentage of flat roofs observed in each LCZ class in Liège. Accordingly, distinct realistic fractions of green roofs are assigned to each LCZ class in WRF. We run the WRF simulation for the base scenario (without green roofs), extreme scenario (100 % green roof fraction), and realistic scenario. The results indicate a limited reduction in near-surface air and surface temperature in a realistic scenario, with a nighttime increase in temperature. Additionally, in the extreme scenario, the temperature reduction largely depends on the morphology. However, in a realistic scenario, it depends on the green roof fraction. Other indicators like heat index and UHI intensity also are not reduced considerably with realistic greening. Therefore, realistic roof greening alone will not be sufficient to achieve an impact on a city-scale.

Feeling hot is being hot? Comparing the mapping and the surveying paradigm for urban heat vulnerability in Vienna.

With rising global temperatures, cities increasingly need to identify populations or areas that are vulnerable to urban heat waves; however, vulnerability assessments may run into ecological fallacy if data from different scales are misconstrued as equivalent. We assess the heat vulnerability of 1983 residents in Vienna by measuring heat impacts, exposure, sensitivity and adaptive capacity with mirrored indicators in the mapping paradigm (i.e. census tract data referring to the geographic regions where these residents live) and the surveying paradigm (i.e. survey data referring to the residents' individual households). Results obtained in both paradigms diverge substantially: meteorological indicators of hot days and tropical nights are virtually unrelated to self-reported heat strain. Meteorological indicators are explained by mapping indicators (R2 of 15-40 %), but mostly not by surveying indicators. Vice versa, experienced heat stress and subjective heat burden are mostly unassociated with mapping indicators but are partially explained by surveying indicators (R2 of 2-4 %). The results suggest that the two paradigms do not capture the same components of vulnerability; this challenges whether studies conducted in the respective paradigms can complement and cross-validate each other. Policy interventions should first define which heat vulnerability outcome they target and then apply the paradigm that best captures the specific drivers of this outcome.

Composition of factors for local heat adaptation measures at the local level in cities of the mid-latitude - An approach for the south-west of Germany.

Traditional heat health warning systems focus on severe and extreme heat events at the district or regional level, often overlooking localized risk and protective factors such as healthcare access and urban green spaces. This approach considers less the varying impacts of heat within cities, including the phenomenon of Urban Heat Islands (UHIs) and the diverse needs of different populations. To address these shortcomings, a need for the development of an Urban Heat Health Warning and Information System (UHHWIS) that operates within the framework of Heat Health Action Plans is needed. Such a system integrates national acute heat health warnings with city-specific assessments of UHI effects and other relevant factors. The technical implementation of the UHHWIS involves the calculation and preprocessing of basic factors such as the Normalised Difference Vegetation Index (NDVI), imperviousness, and UHI intensity. Additionally, further factors are assessed, spatially processed, and provided in accordance with Open Geospatial Consortium (OGC) standards. An iso-area analysis is conducted to evaluate the accessibility of protective factors, such as urban green spaces, drinking wells, hospitals, physicians, and pharmacies, based on the city's road topology. One crucial factor considered in the system is the casting of shadows, which is influenced by both time and location and facilitated through deck.gl. The developed template encompasses all these components into a unified system aimed at protecting vulnerable and risk groups, such as the elderly, through resilient, climate-adapted urban planning. The system provides warnings and information tailored to the urban morphology and prevailing conditions, complemented by a catalogue of potential short- to long-term measures focused on behavioral changes and climate-resilient urban planning strategies. The template can be adapted for use in various European cities, offering valuable insights to decision-makers in city administration for mitigating thermal stress and enhancing resilience against urban heat nowadays and in future.