Influence Of Urban Heat Island Research Articles

Impact of Urban Heat Island on Formation of Precipitation in Indian Western Coastal Cities

Rapid urbanization is leading to a drastic hike in anthropogenic activities and urban surface alterations. As a result, there are many repercussions, one of them being higher temperatures in urban areas when compared to rural areas. This phenomenon is termed Urban Heat Island (UHI). The impacts of urban surface characteristics, climate, and population density on UHI have been extensively studied. However, the influence of UHI on the local climate remains elusive. Relatively few studies demonstrate interrelation between UHI, population density, and unanticipated precipitation events. Therefore, it is important to comprehend the connection as it can impact extreme temperature events like heat waves and unanticipated precipitation events like flash flooding. The objective of this study is to investigate the association between UHI, population density, and precipitation in the summer and winter seasons in Indian Western Coastal Cities. To comprehend this association, a hypothesis test employing the Spearman rank correlation coefficient is conducted for 1991, 2001, 2011, and 2021. From the study, it is found that in summer, the surface temperature is directly proportional to population density and inversely proportional to precipitation. In winter the contrary relation is observed. This study also provides the seasonal variation and temporal evolution of the correlation among the parameters. This research will aid in making informed decisions for urban planning and addressing climate change.

Automated Mapping of Urban Heat Island to Predict Land Surface Temperature and Land use/cover Change Using Machine Learning Algorithms: Mansoura City

Urban heat island (UHI) frequency and emergence are strongly associated with variations in land use/land cover (LU/LC) and land surface temperature (LST). This study investigates the impact of LU/LC class changes on LST based on the distribution of UHI spot maps in Mansoura city, Egypt, using Landsat satellite images from 1991 to 2021. Based on these estimated LU/LC and LST maps, machine learning algorithms, cellular automata, and artificial neural network approaches were used to predict future changes in LU/LC and LST for 2031. The influence of UHI may be quantified using the urban thermal field variance index (UTFVI). The geographic information system (GIS) add-in UHI calculator ArcGIS tool was created because we considered the spatial consequences of employing remote sensing data. This tool includes all the methods and procedures for calculating LST and UHI. The analysis revealed a positive correlation between LST and normalized difference built-up index and a negative correlation between LST and normalized difference vegetation index. The forecasted results for 2031 also show that the built-up area will grow roughly 20%, with a considerable drop in vegetation by 18%. If the city's fast urbanization continues, more than 40% of Mansoura will have land surface temperatures above 45°C by 2031. Avoiding dense built-up areas and growing vegetation spaces remain efficient means of minimizing the influence of UTFVI in urban construction practice. Therefore, this research will help to achieve sustainable development by providing essential insights into the complicated interplay between diverse aspects of urban settings and promoting city competency.

Spatiotemporal mechanism of urban heat island effects on human health—Evidence from Tianjin city of China

The increasingly intensifying global warming and urban heat island (UHIs) are seriously damaging the physical and mental health of urban residents. However, the spatiotemporal evolution of how high temperatures affect human health in megacities remains unclear. Therefore, in this study, with Tianjin during 2006–2020 as an example, and based on data from meteorological stations, Landsat remote sensing images, and point of interest big data, this study applied hot- and cold-spot statistics and remote sensing retrieval in numerical modeling and established an appraisal system to assess how and to what extent UHIs affect resident health. The results showed that the overall influence of UHIs on respiratory and cardiovascular diseases and mental health increased to 373 km2 in area and two levels in intensity; the influence was mainly concentrated in the downtown area, with a rising influence level. Owing to the dual-core structure of the city, the influence was distributed along the main traffic lines in Binhai New District, having a strong influence in the area mainly concentrated in the southeastern part. Many cold spots clustered in the central urban area to cool the thermal environment: the cooled area was 6.5 times larger than the area of intense cooling influence. Our study provides a method for identifying health risks in urban spaces, lays a theoretical foundation to improve the planning of urban green space systems, and offers some decision-making guidance for the planning of healthy cities.

Influence of urban heat islands on seasonal aerosol acidity and aerosol liquid water content in humid subtropical Hong Kong, South China

Aerosol acidity governs many important atmospheric processes that modulate the composition and mass concentrations of atmospheric aerosols. Temperature and RH are two key drivers of aerosol acidity. Increasing levels of urbanization in humid subtropical South China have led to the frequent occurrence of urban heat islands (UHIs) in the region. However, the effects that UHIs have on aerosol acidity in cities in South China are currently unknown. In this study, we investigated the effects of UHIs on aerosol acidity and aerosol liquid water concentrations at two urban sites with different land use characteristics in Hong Kong, South China, in winter and summer from 2011 to 2019. Our results showed that the UHI effect resulted in both urban sites having significantly higher temperatures and lower RH than the refence rural site. Higher UHI intensities were observed in winter, but RH differences between the urban and rural sites were the greatest in summer. Temperature and RH changes associated with the UHI effect resulted in urban aerosols having aerosol liquid water concentrations that were up to 6 to 7 times lower than rural aerosols, and urban aerosols being more acidic than rural aerosols by as much as 1.16 pH units. While the pH differences between urban and rural aerosols correlated with temperature and RH differences induced by the UHI effect, these correlations were season-dependent due to differences in the winter and summer aerosol compositions. In addition, although the UHI was most intense in winter, pH differences between urban and rural aerosols were the largest in summer. Changes in temperature, RH, and aerosol liquid water concentrations linked to the UHI effect were found to lead to substantial reductions (by as much as 38%) in the partitioning of semi-volatile basic and acidic species NH3 and HNO3 to the aerosol phase. Our results indicate that changes in the aerosol acidity, aerosol liquid water concentrations, and gas-aerosol partitioning associated with UHIs have significant implications for aqueous urban aerosol chemistry in Hong Kong. Since UHIs will intensify in many cities in South China in the future due to their increasing levels of urbanization and a warming climate, changes in urban aerosol acidity and liquid water concentrations induced by intensifying UHIs need to be considered when modeling urban aerosol composition and levels in the region.

Solar Geoengineering Modeling and Applications for Mitigating Global Warming: Assessing Key Parameters and the Urban Heat Island Influence

In this paper, solar geoengineering modeling is presented with a goal to simplify reverse forcing assessments and the capability to apply it to a wide variety of applications. Results find improvements on sun-shade space mirror and desert surface treatment estimates, stratosphere sun-dimming methods, and the Urban Heat Islands (UHIs) influence. A heat amplification parameter is added to the model allowing it to be applied to UHI estimates. UHI amplification effects are due to the large solar area of buildings, reduction of wind cooling, solar canyons, and so forth. The UHI reverse forcing requirements are assessed with amplification estimates of 3.1 and 5.2, yielding 7.6% to 12.7% of gross global warming could be due to the urbanization effect, respectively. The gross warming 7.6% estimate, accurately compares to the author's prior study, and the 12.7% represents very recent results by other authors from new measurement methods. Key issues are pointed out that without including a heat amplification estimate and other modeling parameters, the UHI intensity, that likely dominates the urbanization warming effect could be severely underestimated, yielding urbanization estimates possibly as low as 2.4%. It is important to identify possible reasons where underestimates may occur from a modeling perspective to help understand controversies that may be occurring. The new model helps to clarify such parameters, allows for a significant reduction in complexity and calibration, and is shown to be helpful for numerous solar geoengineering applications including the serious need to reduce the UHI effect worldwide. Solar geoengineering solutions will require a lot of creativity, in addition to modeling, suggestions are provided for drought relief ideas and Paris Accord goals required for any successful urban solar geoengineering coordinated effort.

Influence of Urban Heat Island and River Breezes on Precipitation Patterns in the Brazilian Amazon Rainforest

Influence of Urban Heat Island and River Breezes on Precipitation Patterns in the Brazilian Amazon Rainforest

Effects of air temperature, humidity, and wind velocity distribution on indoor cooling load and outdoor human thermal environment at urban scale

In recent years, adaptations to extreme urban high temperatures such as awnings, louvers, directional reflectors, misters, and evaporative materials have been expected to address the outdoor human thermal environment under the influence of urban heat islands. In order to implement these countermeasure technologies in appropriate locations in urban areas, it is necessary to identify the locations where the countermeasure technologies are needed. It is also important to understand the distribution of thermal environmental indicators at the urban scale so that the results can be reflected in urban planning. In this study, I analyzed the distribution of thermal environmental indices during the summer days using mesoscale weather research and forecasting model. I analyzed the distribution of thermal environmental indices in the coastal cities of Tokyo, Osaka, and Nagoya, where there is concern about the increase in indoor cooling load and the risk of heat stoke due to the increase in humidity caused by the inflow of sea breezes, and examined the possible adverse effects of increased humidity. In the three areas, although humidity was high near the coast, the thermal environment indices, wet bulb globe temperature, standard new effective temperature, and physiological equivalent temperature, were low due to low air temperatures and high wind velocities. The enthalpy increased slightly, but the effect on the indoor cooling load was small. It also compares the distribution of thermal environment indices and the effects of the introduction of adaptation measures. Solar shading is more effective than moving to near the coast, urban ventilation and mist spray.

The Influence of CLBP Window Size on Urban Vegetation Type Classification Using High Spatial Resolution Satellite Images

Urban vegetation can regulate ecological balance, reduce the influence of urban heat islands, and improve human beings’ mental state. Accordingly, classification of urban vegetation types plays a significant role in urban vegetation research. This paper presents various window sizes of completed local binary pattern (CLBP) texture features classifying urban vegetation based on high spatial-resolution WorldView-2 images in areas of Shanghai (China) and Lianyungang (Jiangsu province, China). To demonstrate the stability and universality of different CLBP window textures, two study areas were selected. Using spectral information alone and spectral information combined with texture information, imagery is classified using random forest (RF) method based on vegetation type, showing that use of spectral information with CLBP window textures can achieve 7.28% greater accuracy than use of only spectral information for urban vegetation type classification, with accuracy greater for single vegetation types than for mixed ones. Optimal window sizes of CLBP textures for grass, shrub, arbor, shrub-grass, arbor-grass, and arbor-shrub-grass are 3 × 3, 3 × 3, 11 × 11, 9 × 9, 9 × 9, 7 × 7 for urban vegetation type classification. Furthermore, optimal CLBP window size is determined by the roughness of vegetation texture.

Using Light Reflectance to Assess Phenology Stresses Impacted by Urban Heat Island in Karbala

The influence of Urban Heat Island on urban phenology assessment beside the impact of climate change on seriously deteriorated Mimosa (Albizia julibrissin) leaves. This research focuses on the light reflectance from Mimosa leaves to assess the water stress, nitrogen deficiency and serious damage. Healthy leaves absorb blue and red light and reflect green light. Light absorption beyond WB 5 (1150– 1300 nm) is high due to leaf water content. The spectrum regions wherein relatively little absorption will occur can be seen in the range from 500 to 600 nm (WB1 and WB2) and the region from 700 to 1200 nm (WB4 and WB5). When waves are longer than 1200 nm, water vapor absorption rises very steeply, while absorption of the red and blue regions of the visible spectrum is very strong. When Leaf Area Index increases the reflectance in chlorophyll, absorption decreases. There is a sharp increase in WB3 to WB5 and in WB4 to WB6 reflection of Leaf Area Index 0.52-1.0 and 1.0-1.5 respectively and a decrease in reflectance beyond WB6. With a natural background of trees, light reflectivity was compared under wet and dry soil conditions. Red and near infrared affected the reflectivity due to its critical to the land cover.

Decline in surface urban heat island intensity in India during heatwaves

Heatwaves cause human mortality around the world and are projected to rise in the future. Despite the influence of urban heat island (UHI) on heatwaves, the role of UHI on heatwave intensification in urban areas in India remains unrecognized. Here using in situ, satellite observations, and model simulations, we show that urban areas in India do not intensify heatwaves. The frequency of hot-days has significantly (p-value <0.05) increased in urban areas during 1951–2016. The frequency of hot-nights has also increased in the majority of urban areas in India except those located in Indo-Gangetic Plain (IGP). We show that a decline in the frequency of hot-nights (−4.5 ± 1.6 hot-nights) in IGP during 1951–2016 is mainly due to intensive irrigation in the region. We confirm the influence of irrigation on land surface temperature (LST) over IGP using simulations from Community Land Model (CLM4). Our results show that Surface Urban Heat Island (SUHI) intensity in major urban areas in India declines during heatwaves both during the day (−0.3 ± 0.7 °C) and night (−0.3 ± 0.4 °C) from the reference SUHIs. Surrounding non-urban areas (44.5 ± 5.5 °C) are warmer than urban areas (43.7 ± 6.8 °C) during heatwaves due to the absence of vegetation. Our results have implications for policy related to health impacts during heatwaves.

The influence of urban heat islands and socioeconomic factors on the spatial distribution of Aedes aegypti larval habitats.

We addressed the potential associations among the temporal and spatial distribution of larval habitats of Aedes (Stegomyia) aegypti, the presence of urban heat islands and socioeconomic factors. Data on larval habitats were collected in Santa Bárbara d'Oeste, São Paulo, Brazil, from 2004 to 2006, and spatial and temporal variations were analysed using a wavelet-based approach. We quantified urban heat islands by calculating surface temperatures using the results of wavelet analyses and grey level transformation from Thematic Mapper images (Landsat 5). Ae. aegypti larval habitats were geo-referenced corresponding to the wavelet analyses to test the potential association between geographical distribution of habitats and surface temperature. In an inhomogeneous spatial point process, we estimated the frequency of occurrence of larval habitats in relation to temperature. The São Paulo State Social Vulnerability Index in the municipality of Santa Barbára d'Oeste was used to test the potential association between presence of larval habitats and social vulnerability. We found abundant Ae. aegypti larval habitats in areas of higher surface temperature and social vulnerability and fewer larval habitats in areas with lower surface temperature and social vulnerability.

From urban climate to energy consumption. Enhancing building performance simulation by including the urban heat island effect

Cities are dissipative structures. As such, cities generate heat, a phenomenon known as urban heat island (UHI). Even though the UHI is one of the most relevant effects of urbanization on urban climate, up-to-date methodologies to include it in the estimation of buildings’ energy consumption are still scarce. During the last 30 years, different methods and software have been developed to measure a thermal building's demand. Building performance simulation is commonly used to calculate heating and cooling demand. However, such techniques do not adequately include the urban heat island effect, which could have an extreme impact on a building's energy consumption. In fact, building operation is doubly connected with the urban environment: on the one hand, buildings generate heat that warms up the environment, and on the other hand, the urban environment alters building performance by the influence of UHI. In this paper, a methodology to incorporate the UHI effect in building performance simulation is proposed. Urban weather data were downscaled at the urban morphology building level to estimate the cooling demand of different types of residential buildings. The global energy penalty for the whole residential building stock was estimated in four South American Pacific coastal cities. The results indicate that when UHI is incorporated, an increase in energy demand between 15% and 200% can be expected. These results challenge the validity of current assessments performed in absence of the UHI effect. At the same time, these results open up the discussion for the inclusion of urban planning measures aiming at reducing the UHI effect on a building's energy demand.

Impact of Urban Heat Island under the Hanoi Master Plan 2030 on Cooling Loads in Residential Buildings

This study aims to evaluate the influence of urban heat island (UHI) under the Hanoi Master Plan 2030 on the energy consumption for space cooling in residential buildings. The weather conditions under the current and future status (master plan condition) simulated in the previous study (Trihamdani et al., 2014) were used and cooling loads in all the residential buildings in Hanoi over the hottest month were estimated under the simulated current and future conditions by using the building simulation program, TRNSYS (v17). Three most typical housing types in the city were selected for the simulation. The cooling loads of respective housing types were obtained in each of the districts in Hanoi. The results show that the total cooling loads over June 2010 is approximately 683 Terajoule (TJ) under the current status, but it is predicted to increase to 903 TJ under the master plan condition. The increment is largely due to the increase in number of households (203 TJ or 92%), but partially due to the increase in urban temperature, i.e. UHI effect (17 TJ or 8%). The increments in new built-up areas were found to be larger than those in existing built-up areas. The cooling load in apartment is approximately half of that in detached house, which is approximately half of that in row house. Moreover, it was seen that although sensible cooling loads increased with the increase in outdoor temperature, the latent cooling loads decreased due to the decrease in absolute humidity and the increase in air temperature.

Thermal seasons in Warsaw during the period 1961-2013

Abstract This study determines the approximate duration of the thermal seasons in Warsaw, and investigates their long-term variability. The measurement data come from the Ursynów meteorological station at the Warsaw University of Life Sciences (WULS) (λE 21°02’52’’, φN 52°09’38’’, 102.5 m a.s.l.), situated in the south of Warsaw, and comprise mean diurnal air temperatures for the years 1961-2013. In order to identify thermal seasons, the method of five-day rolling averages was applied, which revealed a substantial year-by-year variability. The achieved results were close to those found by other methods for stations situated within the same climatic region. Over the analysed period, winters and springs have become shorter, whereas the other two seasons have become longer. Nevertheless, the positive trend was only statistically significant for thermal summers. The increasing length of the thermal summer in Warsaw Ursynów may be due to the influence of urban heat islands in built-up areas.

LANDSAT과 KOMPSAT-2 데이터를 이용한 청주지역 도시열섬효과의 평가

Land surface temperature (LST) is an important factor in human health, thermal environment, heat balance, global change studies, and as control for climate change. The objective of this study was to assess the influence of Urban Heat Island (UHI) Effects on the LST and NDVI in Cheongju, Korea. The aim was to evaluate the effect of urban thermal environment for LST comparison of satellite-derived and in situ measured temperature. In this study, LANDSAT TM and KOMPSAT scene were used. The results indicated that the minimum LST is observed over dense forest as about <TEX>$21{\sim}25^{\circ}C$</TEX> and maximum LST is observed over industrial area of about <TEX>$28{\sim}32^{\circ}C$</TEX>. The estimated LST showed that industrial area, bare soils and built-up areas exhibit higher surface temperatures, while forest, water bodies, agricultural croplands, and dense vegetations have lower surface temperatures during the summer daytime. Result corroborates the fact that LST over land use/land cover (LULC) types are greatly influenced by the amount of vegetation and water bodies present. The LST of industrial area and urban center is higher than that of suburban area, so it is clearly proved that there are obvious UHIE in Cheongju.

Study of Night Ventilation Efficiency in Urban Environment: Technical and Legal Aspects

Study of Night Ventilation Efficiency in Urban Environment: Technical and Legal AspectsNight Ventilation is a critical technique of passive cooling, as it combines a significant decrease of cooling demand and improvement of thermal comfort and indoor air quality.The aim of the present paper is to study the technical and legal aspects of night ventilation in urban climatic conditions. The technical part examines the efficiency of night ventilation techniques for urban residential buildings. Moreover, the influence of urban heat island on the night ventilation effectiveness is studied. Urban heat provokes the degradation of urban air quality and causes changes in the urban area microclimate which reduce the night ventilation effectiveness as a passive cooling technique. Moreover, this paper studies the legal framework of energy efficiency in buildings and pinpoints the institutional deficiencies of the existing regulation regarding energy efficiency and passive cooling techniques

Mean wind field in the urban atmospheric boundary layer by sodar data

Two-year uninterrupted sodar measurements of vertical profiles of wind speed and direction in the height range 40 to 250-500 m were carried out in two points of Moscow megalopolis. Seasonal and diurnal courses of mean speed profiles, wind speed distributions, wind roses and occurrence of strong and weak wind speed events are shown. Influence of urban heat island and orography on wind field is discussed.

Irrigation cooling effect: Regional climate forcing by land‐use change

Regional detection of a greenhouse warming signal relies on extensive, long‐term measurements of temperature. The potentially confounding impact of land‐cover and land‐use change on trends in temperature records has mostly focused on the influence of urban heat islands. Here we use a regional climate model to show that a regional irrigation cooling effect (ICE) exists, opposite in sign to urban heat island effects. The magnitude of the ICE has strong seasonal variability, causing large dry‐season decreases in monthly mean and maximum temperatures, but little change in rainy‐season temperatures. Our model produced a negligible effect on monthly minimum temperature. In California, the modeled regional ICE is of similar magnitude, but opposite sign, to predictions for future regional warming from greenhouse gases. Given our results for California and the global importance of irrigated agriculture, past expansion of irrigated land has likely affected observations of surface temperature, potentially masking the full warming signal caused by greenhouse gas increases.

A Rare Long Record of Deep Soil Temperatures Defines Temporal Temperature Changes and an Urban Heat Island

A long-term set of deep soil temperature data collected over a 64-year period beginning in 1889 in a rural Illinois area provide a rare opportunity to assess the natural shifts in temperatures in a pristine environment without any urban or instrument bias. Temperatures from 1901 to 1951 increased 0.4 °C, and this was 0.2 °C less than nearby values from two high quality surface temperature data sets that supposedly are without any influence of urban heat islands, shifts in station locations or instrumentation, or other changes with time. Comparison of the soil values with surface air temperatures from a nearby weather station in a growing university community revealed a heat island effect of 0.6 °C. This value is larger than the adjustment based on population that has been recommended to eliminate the urban bias in long-term temperature trends in the U.S. Collectively, the results suggest that additional efforts may be needed to eliminate the urban influence on air temperatures, beyond techniques that simply use population as the basis. Population is only an approximation of urban factors affecting surface temperatures, and the heat island influences inherent in the values from weather stations in smaller communities which have been used as control, or data assumed to be unaffected by their urban environment in the adjustment procedures, have not been adequately accounted for.