urban thermal environment
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Urban Climate ◽  
2022 ◽  
Vol 41 ◽  
pp. 101034
Author(s):  
Ping Yu Fan ◽  
Kwok Pan Chun ◽  
Ana Mijic ◽  
Daphne Ngar-Yin Mah ◽  
Qing He ◽  
...  

Atmosphere ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1159
Author(s):  
Igor Žiberna ◽  
Nataša Pipenbaher ◽  
Daša Donša ◽  
Sonja Škornik ◽  
Mitja Kaligarič ◽  
...  

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.


2021 ◽  
Vol 13 (17) ◽  
pp. 3415
Author(s):  
Haipeng Ye ◽  
Zehong Li ◽  
Ninghui Zhang ◽  
Xuejing Leng ◽  
Dan Meng ◽  
...  

Deterioration of the urban thermal environment, especially in megacities with intensive populations and high densities of impervious surfaces, is a global issue resulting from rapid urbanization. The effects of landscape patterns on the urban thermal environment within a single area or single period have been well documented. Few studies, however, have explored whether the effects can be adapted to various cities at different urbanization stages. This paper investigated the variations of these effects in the five largest and highly urbanized megacities of China from 1990 to 2020 using various geospatial approaches, including concentric buffer analysis, correlation analysis, and hierarchical ridge regression models. The results indicated that the effects of landscape patterns on the urban thermal environment were greatly variable at different urbanization stages. Although landscape composition was more important than landscape configuration in determining the urban thermal environment, the standard coefficients of composition metrics continuously decreased from 1990 to 2020. However, configuration metrics, such as patch density, edge density, and shape complexity, could affect the land surface temperature (LST) to a larger extent at the highly urbanized stage. The urbanization process could also affect the cooling effect of urban green space. At the initial stage of rapid urban expansion in approximately 2000, urban green space explained the most variation in LST, with a value as high as 10%. To maximize the cooling effect, the spatial arrangement of urban green space should be highlighted in the region that was 10–15 km from the city center, where the mean LST experienced a significant decline. These results may provide deeper insights into improving the urban thermal environment by targeted strategies in optimizing landscape patterns for areas at different urbanization stages.


Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1058
Author(s):  
Xuefan Zhou ◽  
Hong Chen

Summer extreme high-temperatures occur frequently in large cities; urban spatial form is the primary factor affecting the urban thermal environment. Thus, planning and arranging urban spaces is a key approach to regulating urban microclimates. Studies into how urban spatial forms influence the formation of urban microclimates have been carried out for multiple cities in warm and hot regions; however, few studies of this kind have been carried out for cities in cold regions. In this study, we analyze Zhengzhou, a city located in a cold region of China, using summer 2017 measurement data to determine why high temperatures develop in cold areas. We investigated how temperature and humidity vary during the morning, at noon, and in the evening given different land use properties (commercial and residential) and different spatial forms (building height, building density, green coverage rate, and plot ratio); we then studied the correlation between urban spatial form and the urban thermal environment. Our research results indicate that the commercial district’s thermal microclimate was related to PR and BH in the afternoon and GCR in the morning and at night. In the residential district, the key urban morphology factors related to its thermal microclimates were BD, PR, and GCR during almost the whole day.


2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Jikang Wan ◽  
Min Zhu

The contribution degree of different surface factors (complexity and heterogeneity) in the urban interior to the urban thermal environment has become an issue of increasing concern under changing climate. In this paper, the multiple linear regression analysis methods to analyze the contribution degree of different surface factors to the urban thermal environment were based on seven urban built-up areas. At the same time, the LST of the same type of factors in the same city will have a difference of ±2.5°C due to the different surrounding features. At the same time, the LST of the same ground object in the same city will be ±2.5°C different because of the difference of the surrounding ground object. The environmental LST and the mean LST of other surface factors were significantly correlated, and the root mean square error was 3.52. This study first classifies the ground features with different attributes, conducts LST statistics for each category, and conducts multivariate linear analysis, instead of setting some fuzzy exponent and forcing a threshold to calculate. The purpose is to explore the contribution of different reflectivity ground objects to the urban thermal environment.


2021 ◽  
pp. 108224
Author(s):  
Xuan Chen ◽  
Jiachuan Yang ◽  
Rui Zhu ◽  
Man Sing Wong ◽  
Chao Ren

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