scholarly journals Review on Urban Heat Island in China: Methods, Its Impact on Buildings Energy Demand and Mitigation Strategies

2021 ◽  
Vol 13 (2) ◽  
pp. 762
Author(s):  
Liu Tian ◽  
Yongcai Li ◽  
Jun Lu ◽  
Jue Wang
Keyword(s):  
Energy Consumption ◽  
Urban Heat Island ◽  
Building Energy ◽  
Design Stage ◽  
Heat Island ◽  
Building Energy Consumption ◽  
Rapid Urbanization ◽  
Substantial Impact ◽  
Urban Heat ◽  
The Impact

High population density, dense high-rise buildings, and impervious pavements increase the vulnerability of cities, which aggravate the urban climate environment characterized by the urban heat island (UHI) effect. Cities in China provide unique information on the UHI phenomenon because they have experienced rapid urbanization and dramatic economic development, which have had a great influence on the climate in recent decades. This paper provides a review of recent research on the methods and impacts of UHI on building energy consumption, and the practical techniques that can be used to mitigate the adverse effects of UHI in China. The impact of UHI on building energy consumption depends largely on the local microclimate, the urban area features where the building is located, and the type and characteristics of the building. In the urban areas dominated by air conditioning, UHI could result in an approximately 10–16% increase in cooling energy consumption. Besides, the potential negative effects of UHI can be prevented from China in many ways, such as urban greening, cool material, water bodies, urban ventilation, etc. These strategies could have a substantial impact on the overall urban thermal environment if they can be used in the project design stage of urban planning and implemented on a large scale. Therefore, this study is useful to deepen the understanding of the physical mechanisms of UHI and provide practical approaches to fight the UHI for the urban planners, public health officials, and city decision-makers in China.

scholarly journals Analysis of the urban heat island effects on building energy consumption

2014 ◽  
Vol 6 (1) ◽  
pp. 91-99 ◽  
Author(s):  
Susanna Magli ◽  
Chiara Lodi ◽  
Luca Lombroso ◽  
Alberto Muscio ◽  
Sergio Teggi
Keyword(s):  
Energy Consumption ◽  
Urban Heat Island ◽  
Building Energy ◽  
Heat Island ◽  
Building Energy Consumption ◽  
Urban Heat

Urban heat island impacts on building energy consumption: A review of approaches and findings

Energy ◽  
2019 ◽  
Vol 174 ◽  
pp. 407-419 ◽  
Author(s):  
Xiaoma Li ◽  
Yuyu Zhou ◽  
Sha Yu ◽  
Gensuo Jia ◽  
Huidong Li ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Urban Heat Island ◽  
Building Energy ◽  
Heat Island ◽  
Building Energy Consumption ◽  
Urban Heat

scholarly journals A Statistical–Dynamical Downscaling for the Urban Heat Island and Building Energy Consumption—Analysis of Its Uncertainties

2020 ◽  
Vol 59 (5) ◽  
pp. 859-883 ◽  
Author(s):  
Robert Schoetter ◽  
Julia Hidalgo ◽  
Renaud Jougla ◽  
Valéry Masson ◽  
Mario Rega ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Urban Heat Island ◽  
Dynamical Downscaling ◽  
Building Energy ◽  
Weather Type ◽  
Statistical Uncertainty ◽  
Heat Island ◽  
Building Energy Consumption ◽  
Urban Heat ◽  
Dynamical Uncertainty

AbstractHigh-resolution maps of the urban heat island (UHI) and building energy consumption are relevant for urban planning in the context of climate change mitigation and adaptation. A statistical–dynamical downscaling for these parameters is proposed in the present study. It combines a statistical local weather type approach with dynamical simulations using the mesoscale atmospheric model Meso-NH coupled to the urban canopy model Town Energy Balance. The downscaling is subject to uncertainties related to the weather type approach (statistical uncertainty) and to the numerical models (dynamical uncertainty). These uncertainties are quantified for two French cities (Toulouse and Dijon) for which long-term dense high-quality observations are available. The seasonal average nocturnal UHI intensity is simulated with less than 0.2 K bias for Dijon, but it is overestimated by up to 0.8 K for Toulouse. The sensitivity of the UHI intensity to weather type is, on average, captured by Meso-NH. The statistical uncertainty is as large as the dynamical uncertainty if only one day is simulated for each weather type. It can be considerably reduced if 3–6 days are taken instead. The UHI reduces the building energy consumption by 10% in the center of Toulouse; it should therefore be taken into account in the production of building energy consumption maps.

Effects of Dubai coastline extreme urbanization in land and sea on local near-surface climate variables patterns

2021 ◽  
Author(s):  
Emily Elhacham ◽  
Pinhas Alpert
Keyword(s):  
Urban Heat Island ◽  
Heat Island ◽  
Rapid Urbanization ◽  
Near Surface ◽  
Modis Data ◽  
The World ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
Coastal Urbanization ◽  
The Impact

<p>Over a billion people currently live in coastal areas, and coastal urbanization is rapidly growing worldwide. Here, we explore the impact of an extreme and rapid coastal urbanization on near-surface climatic variables, based on MODIS data, Landsat and some in-situ observations. We study Dubai, one of the fastest growing cities in the world over the last two decades. Dubai's urbanization centers along its coastline – in land, massive skyscrapers and infrastructure have been built, while in sea, just nearby, unique artificial islands have been constructed.</p><p>Studying the coastline during the years of intense urbanization (2001-2014), we show that the coastline exhibits surface urban heat island characteristics, where the urban center experiences higher temperatures, by as much as 2.0°C and more, compared to the adjacent less urbanized zones. During development, the coastal surface urban heat island has nearly doubled its size, expanding towards the newly developed areas. This newly developed zone also exhibited the largest temperature trend along the coast, exceeding 0.1°C/year on average.</p><p>Overall, we found that over land, temperature increases go along with albedo decreases, while in sea, surface temperature decreases and albedo increases were observed particularly over the artificial islands. These trends in land and sea temperatures affect the land-sea temperature gradient which influences the breeze intensity. The above findings, along with the increasing relative humidity shown, directly affect the local population and ecosystem and add additional burden to this area, which is already considered as one of the warmest in the world and a climate change 'hot spot'.</p><p> </p><p><strong>References:</strong></p><p>E. Elhacham and P. Alpert, "Impact of coastline-intensive anthropogenic activities on the atmosphere from moderate resolution imaging spectroradiometer (MODIS) data in Dubai (2001–2014)", <em>Earth’s Future</em>, 4, 2016. https://doi.org/10.1002/2015EF000325</p><p>E. Elhacham and P. Alpert, "Temperature patterns along an arid coastline experiencing extreme and rapid urbanization, case study: Dubai", submitted.</p>

scholarly journals Effect of Surface Temperature on Energy Consumption in a Calibrated Building: A Case Study of Delhi

Climate ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 71
Author(s):  
Priyanka Kumari ◽  
Sukriti Kapur ◽  
Vishal Garg ◽  
Krishan Kumar
Keyword(s):  
Land Use ◽  
Energy Consumption ◽  
Land Cover ◽  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Heat Island ◽  
Rapid Urbanization ◽  
Urban Heat

Rapid urbanization and associated land-use changes in cities cause an increase in the demand for electricity by altering the local climate. The present study aims to examine the variations in total energy and cooling energy demand in a calibrated building energy model, caused by urban heat island formation over Delhi. The study used Sentinel-2A multispectral imagery for land use and land cover (LULC) of mapping of Delhi, and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery for land surface temperature (LST) mapping during March 2018. It was observed that regions with dense built-up areas (i.e., with built-up area greater than 90%) had a higher annual land surface temperature (LST), i.e., 293.5 K and urban heat island intensity (UHII) ranging from 0.9 K–5.9 K. In contrast, lower annual values of LST (290K) and UHII (0.0–0.4 K) were observed in regions with high vegetation cover (53%). Statistical analysis reveals that a negative correlation exists between vegetation and nighttime LST, which is further confirmed by linear regression analysis. Energy simulations were performed on a calibrated building model placed at three different sites, identified on the basis of land use and land cover percentage and annual LST. Simulation results showed that the site located in the central part of Delhi displayed higher annual energy consumption (255.21 MWh/y) compared to the site located in the rural periphery (235.69 MWh/y). For all the three sites, the maximum electricity consumption was observed in the summer season, while the minimum was seen in the winter season. The study indicates that UHI formation leads to increased energy consumption in buildings, and thus UHI mitigation measures hold great potential for energy saving in a large city like Delhi.

scholarly journals Analysis of the Impact of Land Use on Spatiotemporal Patterns of Surface Urban Heat Island in Rapid Urbanization, a Case Study of Shanghai, China

2020 ◽  
Vol 12 (3) ◽  
pp. 1171 ◽  
Author(s):  
Hongyu Du ◽  
Fengqi Zhou ◽  
Chunlan Li ◽  
Wenbo Cai ◽  
Hong Jiang ◽  
...  
Keyword(s):  
Land Use ◽  
Urban Heat Island ◽  
Land Surface ◽  
Agricultural Land ◽  
Heat Island ◽  
Rapid Urbanization ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
The Impact

In the trend of global warming and urbanization, frequent extreme weather influences the life of citizens seriously. Shanghai, as a typical mega-city in China that has been successful in urbanization, suffers seriously from the urban heat island (UHI) effect. The research concentrates on the spatial and temporal pattern of surface UHI and land use. Then, the relation between them are further discussed. The results show that for the last 15 years, the UHI effect of Shanghai has been increasing continuously in both intensity and area. The UHI extends from the city center toward the suburban area. Along with the year, the ratio in area of Agricultural Land (AL), Wetland (WL), and Bare Land (BL) has decreased. On the contrary, Construction Land (CL) and Green Land (GL) have increased. The average land surface temperature (LST) rankings for each research year from high to low were all CL, BL, GL, AL, and WL. CL contributed the most to the UHI effect, while WL and GL contributed the most to mitigate the UHI. The conclusion provides practical advice aimed to mitigate the UHI effect for urban planning authorities.

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