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Although the urban heat island (UHI) phenomenon is more commonly studied in summer, its influence is also important in winter. In this study, the authors focused on the winter UHI in Ljubljana (Slovenia) and its impact on the urban population, as well as in comparison with a UHI study from 2000. Through a combination of mobile and stationary temperature measurements in different parts of the city, the winter intensity of the UHI in Ljubljana was studied in a dense spatial network of measurements. It was found that the intensity of the winter UHI in Ljubljana decreases as winters become warmer and less snowy. The results showed that the winter UHI in Ljubljana intensifies during the night and reaches the greatest intensity at sunrise. During the winter radiation type of weather, the warmest part of Ljubljana reaches an intensity of 3.5 °C in the evening. In total, 22% of the urban area is in the evening UHI intensity range of 2–4 °C, and 65% of the urban population lives in this range. In the morning, the UHI in Ljubljana has a maximum intensity of 5 °C. The area of >4 °C UHI intensity covers 7% of the urban area, and 28% of the total urban population lives in this area. Higher temperatures in urban centers in winter lead to a longer growing season, fewer snow cover days, lower energy consumption and cold stress, and lower mortality from cold-related diseases compared to the colder periphery.

This paper empirically analyses the relationship between urban form and Urban Heat Island (UHI) in a dataset of 523 European cities that matches remotely sensed land-use and surface temperature data. A UHI anomaly is defined as an uninterrupted streak of days where the temperature differential measured at 12.00 AM between the city core and its surroundings is higher than a given threshold. From this definition, three UHI indicators are obtained: mean intensity, mean duration of the event and occurrence rate. We study the influence of urban morphology on the UHI indictors with a Heckman model. A sample selection bias is detected for mean intensity and mean duration. The estimation results also show that some urban morphological features have a mitigating effect, while some others play a role at the adaptation level.

This study aimed to accurately grasp the impact mechanism and change rule of buildings and green spaces on land surface temperature (LST), which is of great significance for alleviating urban heat islands (UHIs) and formulating adaptation measures. Taking Jinan, China, as the study area, combined multisource remote sensing data were used in this study to construct an index system of the influencing factors. We used a spatial regression model to explore the relative contribution of the influencing indicators on LST. We also drew a marginal utility curve to quantify the heating/cooling effect of the leading indicators. The results showed that, firstly, among the 3D building indicators, the leading indicators affecting LST were the degree of spatial convergence (SCD) and the building surface area (BSA). Among the green space indicators, the largest patch index (LPI), green coverage rate (GCR), and edge density (ED) were significantly negatively correlated with LST. Secondly, when we considered the 15 indicators comprehensively, SCD was the most influential indicator, with a contribution of 24.7%, and the contribution of the green space indicators to LST was significantly reduced. Thirdly, among the leading indicators, SCD was positively correlated with LST. When SCD was less than 60%, LST increased by about 0.38 °C for every 10% increase. When GCR > 44%, LST was significantly reduced, and when GCR > 62%, a cooling effect of 1.1 °C was observed. Beyond this threshold, the cooling effect will not improve significantly. This study shows that when 3D buildings are densely distributed and crowded, the cooling effect of green space will be limited to some extent by 3D buildings. The key to mitigating UHIs is to rationally configure and optimize the spatial structure of 3D buildings.

Este estudio viene a completar la línea de investigaciones sobre la evolución térmica de la región mediterránea española iniciada en el Plan Nacional de Clima (1999). Una línea que ha tratado de evaluar la magnitud del calentamiento climático registrado en la región mediterránea española. En el presente trabajo se ha realizado una revisión rigurosa de las conclusiones previamente alcanzadas (Quereda et al., 2000, 2016, 2020) sobre la magnitud y la naturaleza del calentamiento climático registrado en la región. Revisión que se ha fundamentado en tres ejes. El primero ha sido la actualización de 22 series de temperaturas históricas regionales entre 1950 y 2020. Los resultados de este análisis han sido contrastados con los obtenidos complementariamente en dos nuevos ejes de investigación. El primero de ellos ha sido la realización de un plan experimental encaminado a comparar la evolución térmica del observatorio urbano de Castellón (Casino Antiguo) con los datos de temperatura registrada en observatorios de su entorno situados en zonas menos afectadas de la actividad humana. Los resultados de este plan, relativos al periodo 2001-2020, han evidenciado tanto la existencia del efecto térmico de la urbanización (UHI), como su magnitud. La segunda investigación ha consistido en el análisis de la evolución térmica registrada en el observatorio de las Islas Columbretes (a 28 millas de la costa de Castellón). Esta serie climática insular, analizada así por primera vez, ha implicado una revisión de las conclusiones y tendencias establecidas en estudios anteriores. Los valores obtenidos, si bien obligan a revisar la magnitud del UHI, han mostrado una gran coherencia con la magnitud del calentamiento climático obtenido en el análisis central de las 22 series térmicas completas regionales. Un calentamiento climático real que ha mostrado un valor secular de 1,4 a 1,6 ºC. This study completes a line of research on the thermal evolution of the Spanish Mediterranean region started in the National Climate Plan (1999). A line that has tried to evaluate the magnitude of the climatic warming registered in the Spanish Mediterranean region. In the present work, a rigorous review of the conclusions previously reached (Quereda et al., 2000, 2016, 2020) on the magnitude and nature of the climatic warming recorded in the region has been made. The review is based on three axes. The first is the updating of the regional historical temperature series between 1950 and 2020. The results of this analysis have been compared with those obtained in a complementary manner in two new lines of research. The first of which was an experimental plan aimed at comparing the thermal evolution of the urban observatory of Castellón (Casino Antiguo) with the temperature data registered in nearby observatories located in areas less affected by human activity. The results of this plan, relative to the 2001-2020 period, have shown the existence of the thermal effect of urbanization (UHI) as well as its magnitude. The second investigation consisted in the analysis of the thermal evolution recorded in the Columbretes Islands observatory (28 miles off the coast of Castellón). This insular climate series, thus analysed for the first time, has involved a review of the conclusions and trends established in our previous studies. Although the values obtained make it necessary to review the magnitude of the UHI, they have shown great consistency with the magnitude of climate warming obtained in the central analysis of the 22 complete regional thermal series. A real climate warming is shown with a secular value of 1.4 to 1.6 ºC. El presente trabajo ha sido posible gracias a un Convenio con la Excelentísima Diputación Provincial de Castellón (proyecto 2021-0042, exp 974/2021).

Quick population increase and the desire for urbanization are the main drivers for accelerating urban expansion on agricultural lands in Egypt. This issue is obvious in governorates with no desert backyards. This study aims to (1) explore the trend of Land Use Land Cover Change (LULCC) through the period of 1991–2018; (2) upgrade the reliability of predicting LULCC by integrating the Cellular Automata (CA)-Markov chain and fuzzy analytical hierarchy process (FAHP); and (3) perform analysis of urbanization risk on LST trends over the Gharbia governorate for the decision makers to implement effective strategies for sustainable land use. Multi-temporal Landsat images were used to monitor LULCC dynamics from 1991 to 2018 and then simulate LULCC in 2033 and 2048. Two comparable models were adopted for the simulation of spatiotemporal dynamics of land use in the study area: CA-Markov chain and FAHP-CA-Markov chain hybrid models. The second model upgrades the potential of the CA-Markov chain for prediction by its integration with FAHP, which can determine the locations of high potential to be urbanized. The outcomes stated a significant LULCC in Gharbia during the study period—specifically, urban sprawl on agricultural land, and this trend is predicted to carry on. The agricultural sector represented 91.2% in 1991 and reduced to 83.7% in 2018. The built-up area is almost doubled by 2048 with respect to 2018. The regression analysis revealed the LST increase due to urbanization, causing an urban heat island phenomenon. Criteria-based analysis reveals the district’s vulnerability to rapid urbanization, which is efficient for data-gap zones. The simulation results make sense since the FAHP-CA-Markov simulated the LULCC in a thoughtful way, considering the driving forces of LULCC, while the CA-Markov chain results were relatively random. Therefore, the FAHP-CA-Markov chain is the pioneer to be relied upon for future projection. The findings of this work provide a better understanding of LULCC trends over the years supporting decision makers toward sustainable land use. Thus, further urbanization should be planned to avert the loss of agricultural land and uninterrupted increasing temperatures.

Urban areas tend to be warmer than their rural surroundings, well-known as the “urban heat island” effect. Higher nocturnal air temperature (Tair) is associated with adverse effects on human health, higher mortality rates, and higher energy consumption. Prediction of the spatial distribution of Tair is a step toward the “Smart City” concept, providing an early warning system for vulnerable populations. The study of the spatial distribution of urban Tair was thus far limited by the low spatial resolution of traditional data sources. Volunteered geographic information provides alternative data with higher spatial density, with citizen weather stations monitoring Tair continuously in hundreds or thousands of locations within a single city. In this article, the aim was to predict the spatial distribution of nocturnal Tair in Berlin, Germany, one day in advance at a 30-m resolution using open-source remote sensing and geodata from Landsat and Urban Atlas, crowdsourced Tair data, and machine learning (ML) methods. Results were tested with a “leave-one-date-out” training scheme (testingcrowd) and reference Tair data (testingref). Three ML algorithms were compared-Random Forest (RF), Stochastic Gradient Boosting, and Model Averaged Neural Network. The optimal model based on accuracy and computational speed is RF, with an average root mean square error (RMSE) for testingcrowd of 1.16 °C (R2 = 0.512) and RMSE for testingref of 1.97 °C (R2 = 0.581). Overall, the most important geographic information system (GIS) predictors were morphometric parameters and albedo. The proposed method relies on open-source datasets and can, therefore, be adapted to many cities worldwide.

The urban heat island (UHI) effect is a serious health risk for people living in cities and thus calls for effective mitigation strategies in urban areas. Satellite data enable monitoring of the surface urban heat island (SUHI) over large areas at high spatial resolution. Here we analysed SUHI in the city of Stuttgart (Germany) based on land surface temperature (LST) data from Landsat at 30 m resolution. The overall SUHI in Stuttgart decreased by 1.4 °C between the investigated time periods 2004–2008 and 2016–2020, while the absolute LST increased by 2.5 °C. We identified local hotspots of strong warming and cooling in Stuttgart through the change in SUHI and categorised them based on the predominant land cover change occurring at the hotspot using the Normalised Difference Vegetation Index (NDVI) from Landsat as well as visual information on land cover changes from Google Earth Pro. The establishment of green roofs, as well as albedo changes, are predominantly responsible for cooling spots, while warming spots are mostly associated with the sealing of surfaces. This highlights that vegetation has a dominant influence on SUHI development in Stuttgart. Combining satellite-based LST data with visual information thus provides an effective method to identify local warming and cooling hotspots, which allows monitoring of the success of city policies against heat stress and guides future policy.

Nowadays, cities are the preferred location for more than half of the human population and the places where major human-perceived climate change impacts occur. In an increasingly urbanized world, it is essential to represent such areas adequately in Numerical Weather Prediction (NWP) models, not only to correctly forecast air temperature, but also the human heat stress and the micro-climate phenomena induced by the cities. Among them, the best known is the Urban Heat Island (UHI) effect, which refers to the significantly higher temperatures experienced by a metropolitan area than its rural surroundings. Currently, the COSMO model employs a zero-order urban description, which is unable to correctly reproduce the UHI effect: cities are simply represented as natural lands with increased surface roughness length and reduced vegetation cover. However, the reproduction of the urban climate features in NWP and regional climate models is possible with the use of the so-called urban canopy models, that are able to parameterize the interaction between the urbanized surface and the overlying atmosphere. In this context, a new bulk parameterization scheme, TERRA_URB (TU), has been developed within the COSMO Consortium. TU offers an intrinsic representation of urban physics: the effect of buildings, streets and other man-made layers on the surface-atmosphere interaction is described by parameterizing the impervious water balance, translating the 3D urban-canopy parameters into bulk parameters with the Semi-empirical Urban canopy parameterization (SURY) and using the externally calculated anthropogenic heat flux as additional heat source. In this work, we present high-resolution simulations with the TU scheme, for different European cities, Turin, Naples and Moscow. An in-depth evaluation and verification of the performances of the recent COSMO version with TU scheme and new implemented physical parameterizations, such the ICON-like surface-layer turbulence scheme and the new formulation of the surface temperature, have been carried out. The validation concerned the 2-meter temperature and was performed for 1- or 2-week selected periods over the 3 European cities characterized by different environment and climate, namely the Moscow megacity in Russia and Turin and Naples in Italy. Even if the three domains are morphologically different, the results follow a common behavior. In particular, the activation of TERRA_URB provides a substantial improvement in capturing the UHI intensity and improving air temperature forecasts in urban areas. Potential benefits in the model performance also arise from a new turbulence scheme and the representation of skin-layer temperature (for vegetation). Our model framework provides promising perspectives for enhancing urban climate modelling, although further investigations are needed.

The extreme effects of urban heat island (UHI) on energy consumption, air quality, and human health are significantly detrimental. Increasing the albedo of urban surfaces has been proposed as a potentially efficient mitigation strategy. In this study the Weather Research and Forecasting (WRF) mesoscale model has been used to simulate the urban climate of Rome (Italy).Four different scenarios have been analyzed: the Base Scenario as control case; the Base-ALB Scenario, in which the albedo of roof, walls and road have been increased; the Morph Scenario in which the morphology of urban area has been parameterized more accurately; the Morph-ALB Scenario in which the urban albedo of the improved model has been increased. This study demonstrates that a more accurate parametrization of the urban morphology leads to a more accurate representation of UHI phenomenon. The simulation results show that albedo increase leads to the decrease of the 2-m air temperature at day-time and at night-time. Albedo increase offers very promising results in terms of UHI mitigation, reducing the temperature in the urban area by up to 4 °C at daytime and a little increased (up to 1 °C) in some locations at night time, compared to the control cases.

Urbanization is closely associated with land use land cover (LULC) changes that correspond to land surface temperature (LST) variation and urban heat island (UHI) intensity. Major districts of Bangladesh have a large population base and commonly lack the resources to manage fast urbanization effects, so any rise in urban temperature influences the population both directly and indirectly. However, little is known about the impact of rapid urbanization on UHI intensity variations during the winter dry period in the major districts of Bangladesh. To this end, we aim to quantify spatiotemporal associations of UHI intensity during the winter period between 2000 and 2019 using remote-sensing and geo-spatial tools. Landsat-8 and Landsat-5 imageries of these major districts during the dry winter period from 2000 to 2020 were used for this purpose, with overall precision varying from 81% to 93%. The results of LULC classification and LST estimation showed the existence of multiple UHIs in all major districts, which showed upward trends, except for the Rajshahi and Rangpur districts. A substantial increase in urban expansion was observed in Barisal > 32%, Mymensingh > 18%, Dhaka > 17%, Chattogram > 14%, and Rangpur > 13%, while a significant decrease in built-up areas was noticed in Sylhet < −1.45% and Rajshahi < −3.72%. We found that large districts have greater UHIs than small districts. High UHI intensities were observed in Mymensingh > 10 °C, Chattogram > 9 °C, and Barisal > 8 °C compared to other districts due to dense population and unplanned urbanization. We identified higher LST (hotspots) zones in all districts to be increased with the urban expansion and bare land. The suburbanized strategy should prioritize the restraint of the high intensity of UHIs. A heterogeneous increase in UHI intensity over all seven districts was found, which might have potential implications for regional climate change. Our study findings will enable policymakers to reduce UHI and the climate change effect in the concerned districts.

Landsat-8 surface temperature and the European Space Agency land cover are used to assess the impact of land cover on the Urban Heat Island (UHI) and Urban Heat Sink (UHS). We analyzed five Moroccan cities selected for their different local climate, size, and typology during summer at three different spatial scales. The results show multiple causes defining the different forms and amplitudes of the UHI, namely: the ambient climate, the proximity to the sea, the presence of landscaped areas, and the color of building roofs and walls. Contrary to what was expected, the vegetation was not systematically an island of coolness, either because of its typology or its irrigation status. In the coastal cities of Tangier and Casablanca, UHIs around 20 °C are observed on the seaside, whereas a UHS of up to 11 °C is observed between the city center and the southern periphery of Casablanca. A moderate amplitude UHI of 7 °C is formed in the mountainous city of Ifrane. For cities built in desert-like environments, well-defined UHSs between 9 °C and 12 °C are observed in Smara and Marrakech, respectively. At a finer scale, towns recorded lower temperatures than their immediate surroundings, which are attributed to evaporation from irrigated plants.

The human population is increasing. The ongoing urbanization process, in conjunction with climate change, is causing larger environmental footprints. Consequently, quality of life in urban systems worldwide is under immense pressure. Here, the seasonal characteristics of Maribor’s urban thermal environment were studied from the perspectives of surface urban heat island (SUHI) and urban heat island (UHI) A remote sensing thermal imagery time series and in-situ measurements (stationary and mobile) were combined with select geospatial predictor variables to model this atmospheric phenomenon in its most intensive season (summer). Finally, CMIP6 climate change scenarios and models were considered, to predict future UHI intensity. Results indicate that Maribor’s UHI intensity maximum shifted from winter to spring and summer. The implemented generalized additive model (GAM) underestimates UHI intensity in some built-up parts of the study area and overestimates UHI intensity in green vegetated areas. However, by the end of the century, UHI magnitude could increase by more than 60% in the southern industrial part of the city. Such studies are of particular concern, in regards to the increasing frequency of heat waves due to climate change, which further increases the (already present) heat stress in cities across the globe.

Highlights • Mean city centre winter UHI intensity was +2.3 °C reaching maximum of +9.9 °C. • Winter UHI reduces cold-related mortality by 15% (266 deaths avoided). • This compares with increased mortality of 36% (96 deaths) in summer. • Winter UHI continues to have a protective effect in future climate., Exposure to heat has a range of potential negative impacts on human health; hot weather may exacerbate cardiovascular and respiratory illness or lead to heat stroke and death. Urban populations are at increased risk due to the Urban Heat Island (UHI) effect (higher urban temperatures compared with rural ones). This has led to extensive investigation of the summertime UHI and its effects, whereas far less research focuses on the wintertime UHI. Exposure to low temperature also leads to a range of illnesses, and in fact, in the UK, annual cold-related mortality outweighs heat-related mortality. It is not clearly understood to what extent the wintertime UHI may protect against cold related mortality. In this study we quantify the UHI intensity in wintertime for a heavily urbanized UK region (West Midlands, including Birmingham) using a regional weather model, and for the first time, use a health impact assessment (HIA) to estimate the associated impact on cold-related mortality. We show that the population-weighted mean winter UHI intensity was +2.3 °C in Birmingham city center, and comparable with that of summer. Our results suggest a potential protective effect of the wintertime UHI, equivalent to 266 cold-related deaths avoided (~15% of total cold-related mortality over ~11 weeks). When including the impacts of climate change, our results suggest that the number of heat-related deaths associated with the summer UHI will increase from 96 (in 2006) to 221 in the 2080s, based on the RCP8.5 emissions pathway. The protective effect of the wintertime UHI is projected to increase only slightly from 266 cold-related deaths avoided in 2009 to 280 avoided in the 2080s. The different effects of the UHI in winter and summer should be considered when assessing interventions in the built environment for reducing summer urban heat, and our results suggest that the future burden of temperature-related mortality associated with the UHI is likely to increase in summer relative to winter.

Considering the new IPCC report and its recent suggestions, it is important to pay serious attention to the Urban Heat Island issue. In this study, satellite images acquired by the Worldview3 sensor (WV3) were processed to classify the different kinds of urban surface and to compute the albedo value for each surface. Then several UHI mitigation scenarios were analyzed, varying selectively the surface albedo by choosing solar reflective materials. Clay tile pitched roofs, dark roofs and parking areas were considered as “modifiable surfaces” and their albedo values were increased on the basis of the literature and of data made available by product manufacturers. For each proposed scenario, the reduction of intensity of the Urban Heat Island effect (ATD), the energy saving brought by lower absorption of air conditioning systems (ΔE) and the consequent cost savings were calculated. All the scenarios proved to be convenient and with a relatively fast return on investment. In particular, two scenarios involving the modification of several surfaces at the same time proved to be the most promising ones from the perspective of a public administration, with significant benefits on the well-being of the population, as well as with similar and relatively short payback periods.

Extreme heat events at urban centers in combination with air pollution pose a serious risk to human health. Among these are financially distressed cities and neighborhoods that are facing enormous challenges without the scientific and technical capacity for planning and mitigation. The city of Camden is one of those economically distressed areas with a predominantly minority population, a high unemployment rate, high poverty rates, and poor air quality (PM2.5 and ozone), and it remains vulnerable to heat events. This paper focuses on studying a coupled effect of Urban Heat Islands (UHIs) and Ozone-PM2.5 pollution at the neighborhood-scale in the city of Camden, using fine scale remotely sensed land-surface temperature and air quality data from the Community Multiscale Air Quality (CMAQ) Modelling System in the Geographic Information Systems (GIS) platform. To assess the impact of urban microclimate on the city of Camden, NJ, residents’ health, we identified several environmental and social parameters as the root causes of vulnerability imposed by extreme-heat and poor air quality. Vulnerability in terms of environment and social wellbeing was spatially quantified as two conceptual vulnerability-index models (i.e., environmental vulnerability index (EVI) and a social vulnerability index (SVI)) using multiple linear regression algorithm. Factors such as remotely sensed earth surface properties, built-environment components, air quality, and socio-economic data were incorporated in a holistic geographic approach to quantify the combined effect. Surface temperature gradient and Proportional Vegetation (Pv) generated from 30 m resolution Landsat 8 were sampled along with other variables in the city of Camden, NJ. Models incorporating Pv suggest better fit than models with normalized difference vegetation index (NDVI). Water fraction (33.5%,32.4%), percentage imperviousness (32.5%, 32%), Pv (20.5%, 19.6%), and digital elevation model (DEM) (9%, 8%) have the highest contributions in both models. Two output maps identified the vulnerable neighborhoods in the city through comprehensive GIS analysis: Lanning Square, Bergen Square, Central Waterfront, Gateway, Liberty Park, and Parkside. This can provide useful information for planners and health officials in targeting areas for future interventions and mitigations.

The credible urban heat island (UHI) trend is crucial for assessing the effects of urbanization on climate. Land surface temperature (LST) and near surface air temperature (SAT) have been extensively used to obtain UHI intensities. However, the consistency of UHI trend between LST and SAT has rarely been discussed. This paper quantified the temporal stability and trend consistency between Moderate Resolution Imaging Spectroradiometer (MODIS) LST and in situ SAT. Linear regressions, temporal trends and coefficients of variations (CV) were analyzed based on the yearly mean, maximum and minimum temperatures. The findings in this study were: (1) Good statistical consistency (R2 = 0.794) and the same trends were found only in mean temperature between LST-UHI and SAT-UHI. There are 54% of cities that showed opposite temporal trends between LST-UHI and SAT-UHI for minimum temperature while the percentage was 38% for maximum temperature. (2) The high discrepancies in temporal trends were observed for all cities, which indicated the inadequacy of LST for obtaining reliable UHI trends especially when using the maximum and minimum temperatures. (3) The larger uncertainties of LST-UHI were probably due to high inter-annual fluctuations of LST. The topography was the predominant factor that affected the UHI variations for both LST and SAT. Therefore, we suggested that SAT should be combined with LST to ensure the dependable temporal series of UHI. This paper provided references for understanding the UHI effects on various surfaces.

This paper aims to investigate in details the specific of the nocturnal urban heat island in Iaşi city area during a particular heat wave in summer time. For this, we have conducted a series of expeditionary measurements on air temperature for the interval between 1 and 6 of August 2017 which was charaterized by excessive heat conditions. Air temperature measurements were made around midnight time and were performed along westeast transects crossing the city.The main results show an intensity of 3-4°C for the nocturnal urban heat island of Iaşi during heat wave condition. Beside this, the structure of the urban heat island was also influenced by the atmospheric stability which enhanced the occurence thermal inversion phenomena. In these conditions more dense cold air descends on the rivers valleys generating strong cooling of 4.0-5.0°C in low area of the city comparatively to the city center.

This research is motivated by the increasing threat of urban heat waves that are likely worsened by pervasive global warming and urbanization. Different regions of the city including urban, borderland and rural area will experience different levels of heat health risk. In this paper, we propose an improved approach to quantitatively assess Beijing’s heat health risk based on three factors from hazard, vulnerability and especially environment which is considered as an independent factor because different land use/cover types have different influence on ambient air temperatures under the Urban Heat Island effect. The results show that the heat health risk of Beijing demonstrates a spatial-temporal pattern with higher risk in the urban area, lower risk in the borderland between urban and rural area, and lowest risk in the rural area, and the total risk fluctuated dramatically during 2008–2011. To be more specific, the heat health risk was clearly higher in 2009 and 2010 than in 2008 and 2011. Further analysis with the urban area at sub-district level signifies that the impervious surface (urban area such as buildings, roads, et al. ) ratio is of high correlation with the heat health risk. The validation results show that the proposed method improved the accuracy of heat health risk assessment. We recommend that policy makers should develop efficient urban planning to accomplish Beijing’s sustainable development.

In many cities that have experienced rapid growth like Abu Dhabi, urban microclimate scenarios evolve rapidly as well and it is important to study the urban thermal dynamics continuously. The Local Climate Zone (LCZ) classification considers factors related to the physical properties like surface cover and surface structure of the city which allow to analyze urban heat flows. Abu Dhabi city is rapidly expanding and is characterized by highly heterogeneous types of built forms that comprise mainly of old mid-rise and modern high-rise buildings with varied degrees of vegetation cover in different parts of the city. The fact that it is a coastal city in a desert environment makes it quite unique. This paper presents an approach of studying urban heat flows in such heterogeneous setup. First, the city is classified into local climate zones using images acquired by Landsat Satellite. Numerical simulations are performed in the designated LCZs using a computational fluid dynamics software, Envi-met. The results of Envi-met are calibrated and validated using in-situ measurements across all four seasons. The calibrated models are then applied to study entire Abu Dhabi island across different seasons. The results indicate a clear presence of urban heat island (UHI) effect when averaged over the full day which is varying in different zones. The zones with high vegetation do not show large average UHI effect whereas the effect is significant in densely built zones. The study also validates previous observations on the inversion of UHI effect during the day and in terms of diurnal response.

The sky view factor (SVF) is essential to describe the urban climatology at scales below 100m. This proxy for net radiation depends on the height of the obstacles in its surroundings. The SVF was calculated from a rasterized point cloud height dataset (with 6 − 10 points per m2). The resulting SVF depends on grid-resolution, search radius and number of directions. Previous research related the diurnal maximum urban heat island (UHI) of the canopy layer to the diurnal temperature range, solar irradiance, wind speed, vegetation fraction and SVF. The goal of this study is to determine the sensitivity of the SVF and the impact on the UHI. Within the Netherlands a test area of 70km2 was selected, including: urban areas, meadows and forests. There is a high sensitivity for grid-resolution. Therefore the impact of the SVFs grid resolution on the maximum UHI is explored. Results show that the fourth largest city within the Netherlands, Utrecht, has a mean diurnal maximum UHI of 3.1 °C using a 1m SVF resolution. But, with a 3m SVF resolution the UHI is on average 0.6 °C lower. This highlights the significance of a fine grid resolution which can capture houses, alleys and trees.

The continuous city growth leads to the intensification of the Urban Heat Island effect (UHI) which involves several consequences for the in-habitant comfort. Countermeasures such as green roofs can mitigate the urban microclimate reducing the roof surface temperature and hence the surrounding air temperature. As most of the existing Italy building stock was built without or with poor thermal insulation, they need of interventions of energy retrofit. In particular, roofs are the component of the building envelope that are mainly engaged of both solar gains and thermal fluxes. Therefore, any interventions refurbishment should include the roof surface. This paper focuses on the analyses of the energy performance and the dynamic thermal behavior of a green roof implemented in an existing house-holiday situated in the south part of Sicily. Moreover, other two refurbishment scenarios that foresee the increase of the roof thermal insulation were analysed. Dynamic simulations have proven that the green roof reduce the energy needs, about 90% in the cooling period and 30% in the heating period; delays and attenuates the outdoor heat wave in comparison with traditional roofs, as well as diminishes the average daily temperature fluctuations. The reduction of the vegetated temperature area results about 10.0 °C lower than the one of a bare roof area.

This study analyzes the influence of urban-geographical variables on determining heat islands and proposes a model to estimate and spatialize the maximum intensity of urban heat islands (UHI). Simulations of the UHI based on the increase of normalized difference vegetation index (NDVI), using multiple linear regression, in Iporá (Brazil) are also presented. The results showed that the UHI intensity of this small city tended to be lower than that of bigger cities. Urban geometry and vegetation (UI and NDVI) were the variables that contributed the most to explain the variability of the maximum UHI intensity. It was observed that areas located in valleys had lower thermal values, suggesting a cool island effect. With the increase in NDVI in the central area of a maximum UHI, there was a significant decrease in its intensity and size (a 45% area reduction). It is noteworthy that it was possible to spatialize the UHI to the whole urban area by using multiple linear regression, providing an analysis of the urban set from urban-geographical variables and thus performing prognostic simulations that can be adapted to other small tropical cities.

Over the last few decades many bibliographical studies have been conducted on cool roofs, by analyzing both the energy performance during summer and winter seasons and their contribution in mitigating the urban heat island effect. This paper describes the experimentation carried out in three outdoor test cells to comparatively assess the behavior of a cool roof solution with respect to a ventilated-roof and a warm-roof. The monitored data have confirmed that in summer cool roofs are the best solution, with respect to traditional tile roofing, sensibly reducing surface temperatures as a function of the solar direct radiation level (15–25 °C for I > 600 W/m2 and 5–15 °C for I < 300 W/m2, independently of the season). Furthermore, cool roofs involve an energy saving related to summer cooling by about 20% as to a warm-roof and 15%–20% as to a vented-roof. During winter, cool roofs improve the heating energy performance of a vented-roof by about 12%, against a slightly increased consumption (

Local circulation dynamics have a strong impact on the climate evolution as they contribute to the redistribution of energy and scalars from the regional to the global scale. Mesoscale phenomena are driven by surface heat, momentum and moisture fluxes; the intensity and distribution of these forcings can be significantly modified by the urbanization. The present work describes numerical and experimental investigations of the flow over an urban area. The circulation arises from the temperature difference between the city and the suburbs, called the Urban Heat Island (UHI) phenomenon. The three-dimensional non-hydrostatic meteorological model WRF has been used to perform Large Eddy Simulations of the UHI flow and its evolution during the complete day-night cycle. The domain is assumed to be planar in the cross-flow direction and periodic lateral boundary conditions are imposed. The laboratory experiments are conducted in a thermally controlled water tank to simulate an initially stably stratified environment and an electric heater solidal with the bottom of the tank mimics the urban site. Image analysis techniques have been used to reconstruct the velocity fields, while temperatures are acquired by multiple thermocouple arrays. The high resolution of both the numerical and laboratory experiments allows a detailed characterization of both mean and turbulent properties of the UHI circulation. Present numerical and laboratory results, normalized by similarity theory scaling parameters, compare well with literature data.

Background Heatwaves present a significant health risk and the hazard is likely to escalate with the increased future temperatures presently predicted by climate change models. The impact of heatwaves is often felt strongest in towns and cities where populations are concentrated and where the climate is often unintentionally modified to produce an urban heat island effect; where urban areas can be significantly warmer than surrounding rural areas. The purpose of this interdisciplinary study is to integrate remotely sensed urban heat island data alongside commercial social segmentation data via a spatial risk assessment methodology in order to highlight potential heat health risk areas and build the foundations for a climate change risk assessment. This paper uses the city of Birmingham, UK as a case study area. Results When looking at vulnerable sections of the population, the analysis identifies a concentration of "very high" risk areas within the city centre, and a number of pockets of "high risk" areas scattered throughout the conurbation. Further analysis looks at household level data which yields a complicated picture with a considerable range of vulnerabilities at a neighbourhood scale. Conclusions The results illustrate that a concentration of "very high" risk people live within the urban heat island, and this should be taken into account by urban planners and city centre environmental managers when considering climate change adaptation strategies or heatwave alert schemes. The methodology has been designed to be transparent and to make use of powerful and readily available datasets so that it can be easily replicated in other urban areas.

The urban heat island (UHI) phenomenon may produce several cascade effects on citizens’ health, energy consumption and air quality. Numerical modelling is recognised to be a powerful tool for the analysis of the UHI, although the question of which model to use (as implied in the ‘fit-for-purpose’ approach) much depends on the application and on the result of satisfactory validation against field measurements. In this paper, two different modelling approaches are applied, namely the integral-semi-Gaussian model ADMS-TH and the CFD-based model ENVI-met, to assess the UHI phenomenon in a city of south Italy (Lecce). Modelling results are validated against field measurements collected during summer 2012. The results suggest that the integral model has the ability of capturing the UHI cycle at city scale, while CFD modelling did not provide any substantial improvements in terms of local geometric effects on temperature distribution.

Background & objectives: In the Carpathian Basin, the most northern populations of Phlebotomus (sandfly) species, including the two studied species (Phlebotomus mascittii and Phlebotomus neglectus), are reported from central Hungary. The most important limiting factor of the distribution of Phlebotomus species in the region is the annual minimum temperature which may be positively affected by the urban heat island and the climate change in the future. The main objective of the study is to prove and predict the overwintering possibility of Phlebotomus species in urban environment. Methods: Based on the latest reports of occurrence of sandfly species, climate envelope model was built for the period 1961-90 and 2025-50 to project the potential urban distribution of the species. The climatic data were obtained from RegCM regional climate model and MODIS satellite images. Results: The recent occurrence of the species in central Hungary indicates that Phlebotomus species can overwinter in non-heated shelters in built environment. Interpretation & conclusion: Jointly heat island and the increase of minimum temperature in winter due to climate change seem to be able to provide suitable environment for the studied species in urban areas to a great extent.