scholarly journals Urban Heat Island and Its Interaction with Heatwaves: A Review of Studies on Mesoscale

2021 ◽  
Vol 13 (19) ◽  
pp. 10923
Author(s):  
Jing Kong ◽  
Yongling Zhao ◽  
Jan Carmeliet ◽  
Chengwang Lei

With rapid urbanization, population growth and anthropogenic activities, an increasing number of major cities across the globe are facing severe urban heat islands (UHI). UHI can cause complex impacts on the urban environment and human health, and it may bring more severe effects under heatwave (HW) conditions. In this paper, a holistic review is conducted to articulate the findings of the synergies between UHI and HW and corresponding mitigation measures proposed by the research community. It is worth pointing out that most studies show that urban areas are more vulnerable than rural areas during HWs, but the opposite is also observed in some studies. Changes in urban energy budget and major drivers are discussed and compared to explain such discrepancies. Recent studies also indicate that increasing albedo, vegetation fraction and irrigation can lower the urban temperature during HWs. Research gaps in this topic necessitate more studies concerning vulnerable cities in developing countries. Moreover, multidisciplinary studies considering factors such as UHI, HW, human comfort, pollution dispersion and the efficacy of mitigation measures should be conducted to provide more accurate and explicit guidance to urban planners and policymakers.

HortScience ◽  
1997 ◽  
Vol 32 (3) ◽  
pp. 509A-509
Author(s):  
Derald A. Harp ◽  
Edward L. McWilliams

Urban areas have average annual temperatures 2–3°C warmer than surrounding rural areas, with daily differences of 5–6°C common. A suggested reason for this temperature difference is the extensive use of concrete, asphalt, and other building materials in the urban environment. Vegetation can moderate these temperatures by intercepting incoming radiation. The influence of vegetation patterns on the magnitude of urban and micro-urban “heat islands” (UHI and MUHI, respectively) is compared for several cities including Houston, Austin, College Station, and Ft. Worth, Texas; Huntsville, Ala.; and Gainesville, Fla. Temperatures for all cities studied were greatest in the built-up areas and dropped off in suburban areas and adjacent rural areas. In Houston, surrounding rice fields were 3–5°C cooler than urban areas. Heavily built-up areas of Austin were 2–4°C warmer than parks and fields outside of the city. In all of the cities, large parks were typically 2–3°C cooler than adjacent built-up areas. Large shopping malls varied in nocturnal winter and summer temperature, with winter temperatures near door openings 2–3°C warmer, and summer daytime temperatures as much as 17°C cooler beneath trees. This effect seemed to persist at the microclimatic scale. Areas beneath evergreen trees and shrubs were warmer in the winter than surrounding grass covered areas. Video thermography indicated that the lower surfaces of limbs in deciduous trees were warmer than the upper surfaces. Overall, vegetation played a significant role, both at the local and microscale, in temperature moderation.


2021 ◽  
Author(s):  
Sebastian Schlögl ◽  
Nico Bader ◽  
Julien Gérard Anet ◽  
Martin Frey ◽  
Curdin Spirig ◽  
...  

<p>Today, more than half of the world’s population lives in urban areas and the proportion is projected to increase further in the near future. The increased number of heatwaves worldwide caused by the anthropogenic climate change may lead to heat stress and significant economic and ecological damages. Therefore, the growth of urban areas in combination with climate change can increase future mortality rates in cities, given that cities are more vulnerable to heatwaves due to the greater heat storage capacity of artificial surfaces towards higher longwave radiation fluxes.</p><p>To detect urban heat islands and resolve the micro-scale air temperature field in an urban environment, a low-cost air temperature network, including 450 sensors, was installed in the Swiss cities of Zurich and Basel in 2019 and 2020. These air temperature data, complemented with further official measurement stations, force a statistical air temperature downscaling model for urban environments, which is used operationally to calculate hourly micro-scale air temperatures in 10 m horizontal resolution. In addition to air temperature measurements from the low-cost sensor network, the model is further forced by albedo, NDVI, and NDBI values generated from the polar-orbiting satellite Sentinel-2, land surface temperatures estimated from Landsat-8, and high-resolution digital surface and elevation models.</p><p>Urban heat islands (UHI) are processed averaging hourly air temperatures over an entire year for each grid point, and comparing this average to the overall average in rural areas. UHI effects can then be correlated to high-resolution local climate zone maps and other local factors.</p><p>Between 60-80 % of the urban area is modeled with an accuracy below 1 K for an hourly time step indicating that the approach may work well in different cities. However, the outcome may depend on the complexity of the cities. The model error decreases rapidly by increasing the number of spatially distributed sensor data used to train the model, from 0 to 70 sensors, and then plateaus with further increases. An accuracy below 1 K can be expected for more than 50 air temperature measurements within the investigated cities and the surrounding rural areas. </p><p>A strong statistical air temperature model coupled with atmospheric boundary layer models (e.g. PALM-4U, MUKLIMO, FITNAH) will aid to generate highly resolved urban heat island prediction maps that help decision-makers to identify local heat islands easier. This will ensure that financial resources will be invested as efficiently as possible in mitigation actions.</p>


2013 ◽  
Vol 52 (9) ◽  
pp. 2051-2064 ◽  
Author(s):  
Dan Li ◽  
Elie Bou-Zeid

AbstractCities are well known to be hotter than the rural areas that surround them; this phenomenon is called the urban heat island. Heat waves are excessively hot periods during which the air temperatures of both urban and rural areas increase significantly. However, whether urban and rural temperatures respond in the same way to heat waves remains a critical unanswered question. In this study, a combination of observational and modeling analyses indicates synergies between urban heat islands and heat waves. That is, not only do heat waves increase the ambient temperatures, but they also intensify the difference between urban and rural temperatures. As a result, the added heat stress in cities will be even higher than the sum of the background urban heat island effect and the heat wave effect. Results presented here also attribute this added impact of heat waves on urban areas to the lack of surface moisture in urban areas and the low wind speed associated with heat waves. Given that heat waves are projected to become more frequent and that urban populations are substantially increasing, these findings underline the serious heat-related health risks facing urban residents in the twenty-first century. Adaptation and mitigation strategies will require joint efforts to reinvent the city, allowing for more green spaces and lesser disruption of the natural water cycle.


2020 ◽  
Author(s):  
Sarah Safieddine ◽  
Maya George ◽  
Cathy Clerbaux ◽  
Ana Paracho ◽  
Anne Boynard ◽  
...  

<p>IASI is a versatile mission, allowing the measurement of both meteorological parameters such as temperature and atmospheric composition for infrared absorbing species. With its long observation record and frequent overpasses, IASI is able to follow changes at different spatial scales. We studied IASI’s capability to track the anthropogenic signature associated with large cities, both in terms of temperature fingerprint (urban heat islands) and carbon monoxide (CO) content, a good tracer of human activity (transport, heating, and industrial activities). For this study we averaged the IASI data available since the launch of the first IASI, in order to increase the signal to noise, and allow discriminating the city from its surroundings. For skin temperatures we show that some cities experience much warmer temperatures than nearby rural areas, with day and night differences, whereas other urban areas appear as cold urban islands when surrounded by deserts Examples will be shown and compare with MODIS observations. For CO emitted by human activities, we identified some cities that stand out from their background, and were able to compare their CO associated signatures with measurements provided by other available spaceborne instruments such as Mopitt and TROPOMI.</p>


Author(s):  
Chi Chen ◽  
Dan Li ◽  
Trevor F. Keenan

Abstract Satellite observations show that the surface urban heat island intensity (SUHII) has been increasing over the last two decades. This is often accompanied by an increased urban-rural contrast of vegetation greenness. However, the contribution of uneven vegetation trends in urban and rural areas to the trend of SUHII is unclear, due to the confounding effects of climate change and changes in man-made amenities and anthropogenic heat sources. Here we use a data-model fusion approach to quantify such contributions during the peak growing season. We show that the LAIdif (the urban-rural difference of leaf area index) is increasing (P<0.05) in 189 of the selected 228 global megacities. The increasing trend of LAIdif from 2000 to 2019 accounts for about one quarter of the trend in satellite-derived SUHII, and the impact is particularly evident in places with rapid urbanization and rural cropland intensification. The marginal sensitivity of SUHII to LAIdif is the strongest in hot-humid megacities surrounded by croplands and in hot-dry megacities surrounded by mixed woody and herbaceous vegetation. Our study highlights the role of long-term vegetation trends in modulating the trends of urban-rural temperature differences.


2020 ◽  
Vol 33 (20) ◽  
pp. 9015-9030
Author(s):  
Y. T. Eunice Lo ◽  
Daniel M. Mitchell ◽  
Sylvia I. Bohnenstengel ◽  
Mat Collins ◽  
Ed Hawkins ◽  
...  

AbstractIn the United Kingdom, where 90% of residents are projected to live in urban areas by 2050, projecting changes in urban heat islands (UHIs) is essential to municipal adaptation. Increased summer temperatures are linked to increased mortality. Using the new regional U.K. Climate Projections, UKCP18-regional, we estimate the 1981–2079 trends in summer urban and rural near-surface air temperatures and in UHI intensities during day and at night in the 10 most populous built-up areas in England. Summer temperatures increase by 0.45°–0.81°C per decade under RCP8.5, depending on the time of day and location. Nighttime temperatures increase more in urban than rural areas, enhancing the nighttime UHI by 0.01°–0.05°C per decade in all cities. When these upward UHI signals emerge from 2008–18 variability, positive summer nighttime UHI intensities of up to 1.8°C are projected in most cities. However, we can prevent most of these upward nighttime UHI signals from emerging by stabilizing climate to the Paris Agreement target of 2°C above preindustrial levels. In contrast, daytime UHI intensities decrease in nine cities, at rates between −0.004° and −0.05°C per decade, indicating a trend toward a reduced daytime UHI effect. These changes reflect different feedbacks over urban and rural areas and are specific to UKCP18-regional. Future research is important to better understand the drivers of these UHI intensity changes.


2021 ◽  
Author(s):  
Anping Zhang ◽  
Xintao Ye ◽  
Xindong Yang ◽  
Jiacheng Li ◽  
Haofeng Zhu ◽  
...  

Abstract As a ubiquitous carcinogen, polycyclic aromatic hydrocarbons (PAHs) are closely related to anthropogenic activities. The process of urbanization leads to the spatial interlacing of farmlands and urbanized zones. However, field evidence on the influence of urbanization on the accumulation of PAHs in crops of peri-urban farmlands is lacking. This study comparatively investigated the urbanization-driven levels, compositions, and sources of PAHs in 120 paired plant and soil samples collected from the Yangtze River Delta in China and their species-specific human intake risks. The concentrations of PAHs in crops and soils in the peri-urban areas were 2407.92 ng g−1 and 546.64 ng g−1, respectively, which are significantly higher than those in the rural areas. The PAHs in the root were highly relevant to those in the soils (R2 = 0.63, p < 0.01), and the root bioconcentration factors were higher than 1.0, implying the contributions of root uptake to plant accumulations. However, the translocation factors in the peri-urban areas (1.57 ± 0.33) were higher than those in the rural areas (1.19 ± 0.14), indicating the enhanced influence through gaseous absorption. For the congeners, the 2- to 3-ring PAHs showed a higher plant accumulation potential than the 4- to 6-ring PAHs. Principal component and source analyses show that the PAHs in the peri-urban plants predominantly resulted from urbanization parameters, such as coal combustion, vehicle emissions, and biomass burning. The mean values of estimated dietary intake of PAHs from the consumption of peri-urban and rural crops were 9116 ng d−1 and 6601.83 ng d−1, respectively. The intake risks of different crops followed the order rice > cabbage > carrot > pea. Given the significant input of PAHs from urban to farmland, the influence of many anthropogenic pollutants arising from rapid urbanization should be considered when assessing the agricultural food safety.


Author(s):  
Kaufui V. Wong ◽  
Sarmad Chaudhry

Urban Heat Island Intensity (UHII) is calculated as the spatially-averaged temperature difference between an urban and its surrounding rural area. This concept, however, provides an umbrella for a range of diversified ideas that include the temperature difference between the densely developed urban area and least developed area or between two different built-up areas. There are also averages for the season, for the year, for multiple years, etc. and UHII quoted for the day and another for the night. The objective of this work is to examine the urban heat island effect for cities around the world, using readily available data. The innovation is in using data from the Landsat satellites for different cities previously not studied. Thermal images of the Earth were obtained and analyzed to produce surface temperature maps. These maps showed that the temperature in the urban environments were significantly higher than the temperature in the surrounding countryside, a defining characteristic of urban heat island. Furthermore, the urban and rural areas in the images were separated and analyzed individually to quantitatively measure the temperature difference. It was found that the UHII could be 0.3–5.1°C for the eleven cities investigated. Miami and Shenzen are two cities which seem to have been missed in previous studies because they were limited in their scope and responsibilities, and their methods required much more resources for the longer term studies. It is not the claim here that a UHI is definitively established by the analysis presented of the Landsat satellite data. The present work demonstrates the use of a possible planning tool in terms of understanding where urban areas may be subjected to additional heat. Our use of the method shows that a UHI is probably taking place at the time of observation, and precautionary notices should be sent out to the community to take preventative measures to ensure their health and wellbeing. The minimal resources required is the demonstration shown by our work of the usefulness of this method.


CivilEng ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 459-484
Author(s):  
Svetlana Vujovic ◽  
Bechara Haddad ◽  
Hamzé Karaky ◽  
Nassim Sebaibi ◽  
Mohamed Boutouil

Economic and social development of urban and rural areas continues in parallel with the increase of the human population, especially in developing countries, which leads to sustained expansion of impervious surface areas, particularly paved surfaces. The conversion of pervious surfaces to impervious surfaces significantly modifies local energy balance in urban areas and contributes to urban heat island (UHI) formation, mainly in densely developed cities. This paper represents a literature review on the causes and consequences of the UHI and potential measures that could be adopted to improve the urban microclimate. The primary focus is to discuss and summarise significant findings on the UHI phenomenon and its consequences, such as the impact on human thermal comfort and health, energy consumption, air pollution, and surface water quality deterioration. Regarding the measures to mitigate UHI, particular emphasis is given to the reflective and permeable pavements.


2021 ◽  
Vol 13 (16) ◽  
pp. 3177
Author(s):  
Talha Hassan ◽  
Jiahua Zhang ◽  
Foyez Ahmed Prodhan ◽  
Til Prasad Pangali Sharma ◽  
Barjeece Bashir

Urbanization is an increasing phenomenon around the world, causing many adverse effects in urban areas. Urban heat island is are of the most well-known phenomena. In the present study, surface urban heat islands (SUHI) were studied for seven megacities of the South Asian countries from 2000–2019. The urban thermal environment and relationship between land surface temperature (LST), land use landcover (LULC) and vegetation were examined. The connection was explored with remote-sensing indices such as urban thermal field variance (UTFVI), surface urban heat island intensity (SUHII) and normal difference vegetation index (NDVI). LULC maps are classified using a CART machine learning classifier, and an accuracy table was generated. The LULC change matrix shows that the vegetated areas of all the cities decreased with an increase in the urban areas during the 20 years. The average LST in the rural areas is increasing compared to the urban core, and the difference is in the range of 1–2 (°C). The SUHII linear trend is increasing in Delhi, Karachi, Kathmandu, and Thimphu, while decreasing in Colombo, Dhaka, and Kabul from 2000–2019. UTFVI has shown the poor ecological conditions in all urban buffers due to high LST and urban infrastructures. In addition, a strong negative correlation between LST and NDVI can be seen in a range of −0.1 to −0.6.


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