Long-Term Evolution of Anthropogenic Heat Fluxes into a Subsurface Urban Heat Island

2013 ◽  
Vol 47 (17) ◽  
pp. 9747-9755 ◽  
Author(s):  
Kathrin Menberg ◽  
Philipp Blum ◽  
Axel Schaffitel ◽  
Peter Bayer
Keyword(s):  
Urban Heat Island ◽  
Long Term Evolution ◽  
Heat Fluxes ◽  
Anthropogenic Heat ◽  
Heat Island ◽  
Term Evolution ◽  
Urban Heat

scholarly journals Trend Analysis of Urban Heat Island Intensity According to Urban Area Change in Asian Mega Cities

2019 ◽  
Vol 12 (1) ◽  
pp. 112 ◽  
Author(s):  
Kyungil Lee ◽  
Yoonji Kim ◽  
Hyun Chan Sung ◽  
Jieun Ryu ◽  
Seong Woo Jeon
Keyword(s):  
Urban Heat Island ◽  
Urban Area ◽  
Anthropogenic Heat ◽  
Heat Island ◽  
Individual Factor ◽  
Long Term Trends ◽  
Urban Heat ◽  
Increasing Trends ◽  
Mega Cities

Urban heat island (UHI) is a phenomenon that occurs in cities worldwide. Therefore, there is an increasing need for studies on the changes in UHI intensity and long-term trends based on macroscopic characteristics related to urbanization. In this study, changes in seasonal UHI intensity based on urban area were analyzed for eight Asian mega cities from 1992–2012. The results indicate that the change in pattern of UHI intensity varies for different cities and seasons. UHI intensity increased as the urban area size increased. Furthermore, the dependency of UHI intensity on the economic situation was also demonstrated. With respect to the seasons, significantly increasing trends appeared during the summer. Moreover, depending on urban characteristics such as geography and climate, increasing trends appeared during other seasons. Population was also found to affect UHI intensity by generating anthropogenic heat; however, its effect as an individual factor appeared to be insignificant. This is a macroscale study that analyzes the effect of urban area size on UHI intensity. Future studies on urbanization factors and levels influencing the UHI intensity using higher resolution materials are required

scholarly journals Characterization of the subsurface urban heat island and its sources in the Milan city area, Italy

2021 ◽  
Author(s):  
Alberto Previati ◽  
Giovanni B. Crosta
Keyword(s):  
Urban Heat Island ◽  
Urban Areas ◽  
Heat Fluxes ◽  
Shallow Aquifer ◽  
Heat Island ◽  
Groundwater Temperature ◽  
City Area ◽  
Groundwater Environment ◽  
Urban Heat ◽  
The Impact

AbstractUrban areas are major contributors to the alteration of the local atmospheric and groundwater environment. The impact of such changes on the groundwater thermal regime is documented worldwide by elevated groundwater temperature in city centers with respect to the surrounding rural areas. This study investigates the subsurface urban heat island (SUHI) in the aquifers beneath the Milan city area in northern Italy, and assesses the natural and anthropogenic controls on groundwater temperatures within the urban area by analyzing groundwater head and temperature records acquired in the 2016–2020 period. This analysis demonstrates the occurrence of a SUHI with up to 3 °C intensity and reveals a correlation between the density of building/subsurface infrastructures and the mean annual groundwater temperature. Vertical heat fluxes to the aquifer are strongly related to the depth of the groundwater and the density of surface structures and infrastructures. The heat accumulation in the subsurface is reflected by a constant groundwater warming trend between +0.1 and + 0.4 °C/year that leads to a gain of 25 MJ/m2 of thermal energy per year in the shallow aquifer inside the SUHI area. Future monitoring of groundwater temperatures, combined with numerical modeling of coupled groundwater flow and heat transport, will be essential to reveal what this trend is controlled by and to make predictions on the lateral and vertical extent of the groundwater SUHI in the study area.

scholarly journals Quantitative Analysis of Factors Contributing to Urban Heat Island Intensity

2012 ◽  
Vol 51 (5) ◽  
pp. 842-854 ◽  
Author(s):  
Young-Hee Ryu ◽  
Jong-Jin Baik
Keyword(s):  
Urban Heat Island ◽  
Single Layer ◽  
Anthropogenic Heat ◽  
Heat Island ◽  
Impervious Surfaces ◽  
Additional Heat ◽  
Urban Geometry ◽  
Causative Factors ◽  
Urban Heat ◽  
Vertical Walls

AbstractThis study identifies causative factors of the urban heat island (UHI) and quantifies their relative contributions to the daytime and nighttime UHI intensities using a mesoscale atmospheric model that includes a single-layer urban canopy model. A midlatitude city and summertime conditions are considered. Three main causative factors are identified: anthropogenic heat, impervious surfaces, and three-dimensional (3D) urban geometry. Furthermore, the 3D urban geometry factor is subdivided into three subfactors: additional heat stored in vertical walls, radiation trapping, and wind speed reduction. To separate the contributions of the factors and interactions between the factors, a factor separation analysis is performed. In the daytime, the impervious surfaces contribute most to the UHI intensity. The anthropogenic heat contributes positively to the UHI intensity, whereas the 3D urban geometry contributes negatively. In the nighttime, the anthropogenic heat itself contributes most to the UHI intensity, although it interacts strongly with other factors. The factor that contributes the second most is the impervious-surfaces factor. The 3D urban geometry contributes positively to the nighttime UHI intensity. Among the 3D urban geometry subfactors, the additional heat stored in vertical walls contributes most to both the daytime and nighttime UHI intensities. Extensive sensitivity experiments to anthropogenic heat intensity and urban surface parameters show that the relative importance and ranking order of the contributions are similar to those in the control experiment.

scholarly journals A High-Resolution Monitoring Approach of Canopy Urban Heat Island using Random Forest Model and Multi-platform Observations

2021 ◽  
Author(s):  
Shihan Chen ◽  
Yuanjian Yang ◽  
Fei Deng ◽  
Yanhao Zhang ◽  
Duanyang Liu ◽  
...  
Keyword(s):  
High Resolution ◽  
Random Forest ◽  
Urban Heat Island ◽  
Air Temperature ◽  
Anthropogenic Heat ◽  
Heat Island ◽  
Model Framework ◽  
Rapid Urbanization ◽  
Urban Heat ◽  
The City

Abstract. Due to rapid urbanization and intense human activities, the urban heat island (UHI) effect has become a more concerning climatic and environmental issue. A high spatial resolution canopy UHI monitoring method would help better understand the urban thermal environment. Taking the city of Nanjing in China as an example, we propose a method for evaluating canopy UHI intensity (CUHII) at high resolution by using remote sensing data and machine learning with a Random Forest (RF) model. Firstly, the observed environmental parameters [e.g., surface albedo, land use/land cover, impervious surface, and anthropogenic heat flux (AHF)] around densely distributed meteorological stations were extracted from satellite images. These parameters were used as independent variables to construct an RF model for predicting air temperature. The correlation coefficient between the predicted and observed air temperature in the test set was 0.73, and the average root-mean-square error was 0.72 °C. Then, the spatial distribution of CUHII was evaluated at 30-m resolution based on the output of the RF model. We found that wind speed was negatively correlated with CUHII, and wind direction was strongly correlated with the CUHII offset direction. The CUHII reduced with the distance to the city center, due to the de-creasing proportion of built-up areas and reduced AHF in the same direction. The RF model framework developed for real-time monitoring and assessment of high-resolution CUHII provides scientific support for studying the changes and causes of CUHII, as well as the spatial pattern of urban thermal environments.

scholarly journals Spatial and Temporal Structure of the Urban Heat Island in Seoul

2005 ◽  
Vol 44 (5) ◽  
pp. 591-605 ◽  
Author(s):  
Yeon-Hee Kim ◽  
Jong-Jin Baik
Keyword(s):  
Urban Heat Island ◽  
Temporal Structure ◽  
Temperature Data ◽  
Total Variance ◽  
Anthropogenic Heat ◽  
Urban Heat Island Intensity ◽  
Heat Island ◽  
Near Surface ◽  
Average Maximum ◽  
Urban Heat

Abstract The spatial and temporal structure of the urban heat island in Seoul, Korea, is investigated using near-surface temperature data measured at 31 automatic weather stations (AWSs) in the Seoul metropolitan area for the 1-yr period from March 2001 to February 2002. The urban heat island in Seoul deviates considerably from an idealized, concentric heat island structure, mainly because of the location of the main commercial and industrial sectors and the local topography. Relatively warm regions extend in the east–west direction and relatively cold regions are located near the northern and southern mountains. Several warm cores are observed whose intensity, size, and location are found to vary seasonally and diurnally. Similar to previous studies, the urban heat island in Seoul is stronger in the nighttime than in the daytime and decreases with increasing wind speed and cloud cover, but it is least developed in summer. The average maximum urban heat island intensity is 2.2°C over the 1-yr period and it is 3.4°C at 0300 local standard time (LST) and 0.6°C at 1500 LST. The reversed urban heat island is occasionally observed in the afternoon, but its intensity is very weak. An empirical orthogonal function (EOF) analysis is performed to find the dominant modes of variability in the Seoul urban heat island. In the analysis using temperature data that are averaged for each hour of the 1-yr period, the first EOF explains 80.6% of the total variance and is a major diurnal mode. The second EOF, whose horizontal structure is positive in the eastern part of Seoul and is negative in the western part, explains 16.0% of the total variance. This mode is related to the land use type and the diurnal pattern of anthropogenic heat release. In the analysis using temperature data at 0300 LST, the leading four modes explain 72.4% of the total variance. The first EOF reflects that the weakest urban heat island intensity is in summer. It is found that the urban heat island in Seoul is stronger on weekdays than weekends.

scholarly journals Integrating Urban Form, Function, and Energy Fluxes in a Heat Exposure Indicator in View of Intra-Urban Heat Island Assessment and Climate Change Adaptation

Climate ◽  
2019 ◽  
Vol 7 (6) ◽  
pp. 75 ◽  
Author(s):  
Ilias Agathangelidis ◽  
Constantinos Cartalis ◽  
Mat Santamouris
Keyword(s):  
Climate Change ◽  
Heat Flux ◽  
Urban Heat Island ◽  
Urban Form ◽  
Heat Exposure ◽  
Geographical Information ◽  
Anthropogenic Heat ◽  
Heat Island ◽  
Anthropogenic Heat Flux ◽  
Urban Heat

Cities worldwide are getting warmer due to the combined effects of urban heat and climate change. To this end, local policy makers need to identify the most thermally vulnerable areas within cities. The Local Climate Zone (LCZ) scheme highlights local-scale variations; however, its classes, although highly valuable, are to a certain extent generalized in order to be universally applicable. High spatial resolution indicators have the potential to better reflect city-specific challenges; in this paper, the Urban Heat Exposure (UHeatEx) indicator is developed, integrating the physical processes that drive the urban heat island (UHI). In particular, the urban form is modeled using remote sensing and geographical information system (GIS) techniques, and used to estimate the canyon aspect ratio and the storage heat flux. The Bowen ratio is calculated using the aerodynamic resistance methodology and downscaled remotely sensed surface temperatures. The anthropogenic heat flux is estimated via a synergy of top–down and bottom–up inventory approaches. UHeatEx is applied to the city of Athens, Greece; it is correlated to air temperature measurements and compared to the LCZs classification. The results reveal that UHeatEx has the capacity to better reflect the strong intra-urban variability of the thermal environment in Athens, and thus can be supportive for adaptation responses. High-resolution climate projections from the EURO-CORDEX ensemble for the region show that the adverse effects of the existing thermal inequity are expected to worsen in the coming decades.

scholarly journals Impact of a Detailed Urban Parameterization on Modeling the Urban Heat Island in Beijing Using TEB-RAMS

2014 ◽  
Vol 2014 ◽  
pp. 1-11
Author(s):  
Lei Jiang ◽  
Lixin Lu ◽  
Lingmei Jiang ◽  
Yuanyuan Qi ◽  
Aqiang Yang
Keyword(s):  
Land Use ◽  
Urban Heat Island ◽  
Air Temperature ◽  
Metropolitan Area ◽  
Atmospheric Modeling ◽  
Anthropogenic Heat ◽  
Heat Island ◽  
Urban Heat ◽  
Four Levels ◽  
Geometric Morphology

The Town Energy Budget (TEB) model coupled with the Regional Atmospheric Modeling System (RAMS) is applied to simulate the Urban Heat Island (UHI) phenomenon in the metropolitan area of Beijing. This new model with complex and detailed surface conditions, called TEB-RAMS, is from Colorado State University (CSU) and the ASTER division of Mission Research Corporation. The spatial-temporal distributions of daily mean 2 m air temperature are simulated by TEB-RAMS during the period from 0000 UTC 01 to 0000 UTC 02 July 2003 over the area of 116°E~116.8°E, 39.6°N~40.2°N in Beijing. The TEB-RAMS was run with four levels of two-way nested grids, and the finest grid is at 1 km grid increment. An Anthropogenic Heat (AH) source is introduced into TEB-RAMS. A comparison between the Land Ecosystem-Atmosphere Feedback model (LEAF) and the detailed TEB parameterization scheme is presented. The daily variations and spatial distribution of the 2 m air temperature agree well with the observations of the Beijing area. The daily mean 2 m air temperature simulated by TEB-RAMS with the AH source is 0.6 K higher than that without specifying TEB and AH over the metropolitan area of Beijing. The presence of urban underlying surfaces plays an important role in the UHI formation. The geometric morphology of an urban area characterized by road, roof, and wall also seems to have notable effects on the UHI intensity. Furthermore, the land-use dataset from USGS is replaced in the model by a new land-use map for the year 2010 which is produced by the Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS). The simulated regional mean 2 m air temperature is 0.68 K higher from 01 to 02 July 2003 with the new land cover map.

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