scholarly journals Crowdsourcing Urban Air Temperature Data for Estimating Urban Heat Island and Building Heating/Cooling Load in London

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 5208
Author(s):  
Kit Benjamin ◽  
Zhiwen Luo ◽  
Xiaoxue Wang
Keyword(s):  
Urban Heat Island ◽  
Urban Climate ◽  
Building Energy ◽  
Spatial Density ◽  
Small Scale ◽  
Heat Island ◽  
Local Climate ◽  
Investigation Methods ◽  
Crowdsourced Data ◽  
Urban Heat

Urban heat island (UHI) effects significantly impact building energy. Traditional UHI investigation methods are often incapable of providing the high spatial density of observations required to distinguish small-scale temperature differences in the UHI. Crowdsourcing offers a solution. Building cooling/heating load in 2018 has been estimated in London, UK, using crowdsourced data from over 1300 Netatmo personal weather stations. The local climate zone (LCZ) scheme was used to classify the different urban environments of London (UK). Inter-LCZ temperature differences are found to be generally consistent with LCZ temperature definitions. Analysis of cooling degree hours in July shows LCZ 2 (the densest urban LCZ in London) had the highest cooling demand, with a total of 1550 cooling degree hours. The suburban related LCZs 5 and 6 and rural LCZs B and D all had about 80% of the demand of LCZ 2. In December, the rural LCZs A, B and D had the greatest heating demand, with all recording around 5750 heating degree hours. Urban LCZs 2, 5 and 6 had 91%, 86% and 95% of the heating demand of LCZ D, respectively. This study has highlighted both advantages and issues with using crowdsourced data for urban climate and building energy research.

Climate Bubbles: Games to Monitor Urban Climate

Leonardo ◽  
2011 ◽  
Vol 44 (1) ◽  
pp. 64-65
Author(s):  
Drew Hemment ◽  
Carlo Buontempo ◽  
Alfie Dennen
Keyword(s):  
Urban Heat Island ◽  
Air Flow ◽  
Urban Climate ◽  
Heat Island ◽  
Local Climate ◽  
Flow Circulation ◽  
Urban Heat ◽  
The City

Climate Bubbles was a playful, participatory mass observation project on local climate. Bubble blowing games were devised to enable people across the city of Manchester to test air flow circulation and, by sharing the results online, enabled the Met Office to create a snapshot of the effect the Urban Heat Island has on wind.

scholarly journals Comments about Urban Bioclimate Aspects for Consideration in Urban Climate and Planning Issues in the Era of Climate Change

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 546
Author(s):  
Andreas Matzarakis
Keyword(s):  
Climate Change ◽  
Urban Heat Island ◽  
Urban Climate ◽  
Heat Island ◽  
Adaptation Measures ◽  
Mitigation And Adaptation ◽  
Urban Heat

In the era of climate change, before developing and establishing mitigation and adaptation measures that counteract urban heat island (UHI) effects [...]

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 Including Urban Heat Island in Bioclimatic Early-Design Phases: A Simplified Methodology and Sample Applications

2021 ◽  
Vol 13 (11) ◽  
pp. 5918
Author(s):  
Giacomo Chiesa ◽  
Yingyue Li
Keyword(s):  
Urban Heat Island ◽  
Urban Climate ◽  
Temperate Climate ◽  
Heat Island ◽  
Climate Data ◽  
Degree Days ◽  
Climate Conditions ◽  
Early Design ◽  
Correct Definition ◽  
Urban Heat

Urban heat island and urban-driven climate variations are recognized issues and may considerably affect the local climatic potential of free-running technologies. Nevertheless, green design and bioclimatic early-design analyses are generally based on typical rural climate data, without including urban effects. This paper aims to define a simple approach to considering urban shapes and expected effects on local bioclimatic potential indicators to support early-design choices. Furthermore, the proposed approach is based on simplifying urban shapes to simplify analyses in early-design phases. The proposed approach was applied to a sample location (Turin, temperate climate) and five other climate conditions representative of Eurasian climates. The results show that the inclusion of the urban climate dimension considerably reduced rural HDD (heating degree-days) from 10% to 30% and increased CDD (cooling degree-days) from 70% to 95%. The results reveal the importance of including the urban climate dimension in early-design phases, such as building programming in which specific design actions are not yet defined, to support the correct definition of early-design bioclimatic analyses.

scholarly journals LINKING THE LOCAL CLIMATE ZONES AND LAND SURFACE TEMPERATURE TO INVESTIGATE THE SURFACE URBAN HEAT ISLAND, A CASE STUDY OF SAN ANTONIO, TEXAS, U.S.

2018 ◽  
Vol IV-3 ◽  
pp. 277-283 ◽  
Author(s):  
Chunhong Zhao
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
San Antonio ◽  
Heat Island ◽  
Climate Zones ◽  
Local Climate ◽  
Local Climate Zones ◽  
Urban Heat

The Local Climate Zones (LCZs) concept was initiated in 2012 to improve the documentation of Urban Heat Island (UHI) observations. Despite the indispensable role and initial aim of LCZs concept in metadata reporting for atmospheric UHI research, its role in surface UHI investigation also needs to be emphasized. This study incorporated LCZs concept to study surface UHI effect for San Antonio, Texas. LCZ map was developed by a GIS-based LCZs classification scheme with the aid of airborne Lidar dataset and other freely available GIS data. Then, the summer LST was calculated based Landsat imagery, which was used to analyse the relations between LST and LCZs and the statistical significance of the differences of LST among the typical LCZs, in order to test if LCZs are able to efficiently facilitate SUHI investigation. The linkage of LCZs and land surface temperature (LST) indicated that the LCZs mapping can be used to compare and investigate the SUHI. Most of the pairs of LCZs illustrated significant differences in average LSTs with considerable significance. The intra-urban temperature comparison among different urban classes contributes to investigate the influence of heterogeneous urban morphology on local climate formation.

Urban heat island estimation from improved selection of urban and rural stations by DTW algorithm

2021 ◽  
Author(s):  
Yonghong Hu ◽  
Gensuo Jia ◽  
Jinlong Ai ◽  
Yong Zhang ◽  
Meiting Hou ◽  
...  
Keyword(s):  
Urban Heat Island ◽  
Urban Climate ◽  
Global Scale ◽  
Heat Island ◽  
Climate Effect ◽  
Urban Heat ◽  
The Difference ◽  
Temperature Records ◽  
Dynamic Time ◽  
Selection Of

Abstract Typical urban and rural temperature records are essential for the estimation and comparison of urban heat island effects in different regions, and the key issues are how to identify the typical urban and rural stations. This study tried to analyze the similarity of air temperature sequences by using dynamic time warping algorithm (DTW) to improve the selection of typical stations. We examined the similarity of temperature sequences of 20 stations in Beijing and validated by remote sensing, and the results indicated that DTW algorithm could identify the difference of temperature sequence, and clearly divide them into different groups according to their probability distribution information. The analysis for station pairs with high similarity could provide appropriate classification for typical urban stations (FT, SY, HD, TZ, CY, CP, MTG, BJ, SJS, DX, FS) and typical rural stations (ZT, SDZ, XYL) in Beijing. We also found that some traditional rural stations can’t represent temperature variation in rural surface because of their surrounding environments highly modified by urbanization process in last decades, and they may underestimate the urban climate effect by 1.24℃. DTW algorithm is simple in analysis and application for temperature sequences, and has good potentials in improving urban heat island estimation in regional or global scale by selecting more appropriate temperature records.

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