scholarly journals Changes in the Water Temperature of Rivers Impacted by the Urban Heat Island: Case Study of Suceava City

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1343 ◽  
Author(s):  
Andrei-Emil Briciu ◽  
Dumitru Mihăilă ◽  
Adrian Graur ◽  
Dinu Iulian Oprea ◽  
Alin Prisăcariu ◽  
...  

Cities alter the thermal regime of urban rivers in very variable ways which are not yet deciphered for the territory of Romania. The urban heat island of Suceava city was measured in 2019 and its impact on Suceava River was assessed using hourly and daily values from a network of 12 water and air monitoring stations. In 2019, Suceava River water temperature was 11.54 °C upstream of Suceava city (Mihoveni) and 11.97 °C downstream (Tişăuţi)—a 3.7% increase in the water temperature downstream. After the stream water passes through the city, the diurnal thermal profile of Suceava River water temperature shows steeper slopes and earlier moments of the maximum and minimum temperatures than upstream because of the urban heat island. In an average day, an increase of water temperature with a maximum of 0.99 °C occurred downstream, partly explained by the 2.46 °C corresponding difference between the urban floodplain and the surrounding area. The stream water diurnal cycle has been shifted towards a variation specific to that of the local air temperature. The heat exchange between Suceava River and Suceava city is bidirectional. The stream water diurnal thermal cycle is statistically more significant downstream due to the heat transfer from the city into the river. This transfer occurs partly through urban tributaries which are 1.94 °C warmer than Suceava River upstream of Suceava city. The wavelet coherence analyses and ANCOVA (analysis of covariance) prove that there are significant (0.95 confidence level) causal relationships between the changes in Suceava River water temperature downstream and the fluctuations of the urban air temperature. The complex bidirectional heat transfer and the changes in the diurnal thermal profiles are important to be analysed in other urban systems in order to decipher in more detail the observed causal relationships.

2021 ◽  
Author(s):  
Shihan Chen ◽  
Yuanjian Yang ◽  
Fei Deng ◽  
Yanhao Zhang ◽  
Duanyang Liu ◽  
...  

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.


2019 ◽  
Vol 23 (Suppl. 4) ◽  
pp. 1035-1042 ◽  
Author(s):  
Andrea Vallati ◽  
Luca Mauri ◽  
Chiara Colucci

Urban heat island has significant impacts on buildings? energy consumption. The phenomenon is associated with increased urban air temperatures compared to the air temperature of the surrounding rural or suburban areas. The ambient air temperature growth due to climate changes and the urban heat island phenomenon are dramatically increasing the cooling demand in buildings. This is worsened by irradiation conditions, construction technologies, and subjective comfort expectations. This paper examines the impact of the urban environment on the energy demand of buildings, considering the case of two districts of the city of Rome, Italy: one is representative of a central zone, the other of a rural zone. Weather data were then used to calculate the thermal demand of a typical Italian building, ideally located in the monitored areas of the city. Standalone building with modified weather file was modeled in TRNSYS. Results show that urban heat island intensity causes an increase in cooling demand up to +33% for the urban area (+20% for the rural area) compared to the demand calculated using weather data from airportual areas. On the other hand, urban heat island intensity has a positive effect on heating demand which turns out to decrease up to -32% for the urban area (-14% for the rural area).


2010 ◽  
Vol 49 (10) ◽  
pp. 2159-2166 ◽  
Author(s):  
Hadas Saaroni ◽  
Baruch Ziv

Abstract This study proposes a method for estimating the canopy-layer net urban heat island (UHI) in regions with complex terrain that lack preurban observations. The approach is based on a linear relationship between the urban–rural temperature difference (ΔTu−r), measured via screen-level air temperature, and the population of the city, which was found to have the highest correlation with observations. The linear relation is extrapolated to zero population to yield the desired preurban value. The difference between the zero population ΔTu−r and the current one is proposed to represent the net UHI. Given the uncertainties of the population method, the relatively short time period of the temperature record, and possible inhomogeneity in the data, the results should be regarded as a first-order approximation of the net UHI contribution. The UHI was evaluated for an arid city, Beer Sheba, Israel, for the minimum and maximum air temperatures for the summer and the winter. The study region resembles the combined effect of complex terrain (i.e., the concave topography of the city in contrast with the plateau landscape surrounding it), the UHI, and the regional warming trend. The study assumes that the regional warming does not affect the ΔTu−r. The concave topography of the city dominates over the UHI contribution during nighttime, resulting in an average lower minimum temperature in the city relative to the rural area. This difference has decreased considerably during the study period and has even reversed for the summer nights toward the end of the period. The estimated net UHI contribution in Beer Sheba varies between +0.8° and +3.1°C, with the highest values during the night hours. The high positive UHI during the night is in line with previous studies. The positive UHI in the summer implies further aggravation of heat stress beyond that occurring, and that predicted to increase, over the region.


2015 ◽  
Vol 23 (3) ◽  
pp. 8-16 ◽  
Author(s):  
Petr Dobrovolný ◽  
Lukáš Krahula

AbstractThis study seeks to quantify the effects of a number of factors on the nocturnal air temperature field in a medium-sized central European city located in complex terrain. The main data sources consist of mobile air temperature measurements and a geographical database. Temperature measurements were taken along several profiles through the city centre and were made under a clear sky with no advection. Altogether nine sets of detailed measurements, in all seasons, were assembled. Altitude, quantity of vegetation, density of buildings and the structure of the transportation (road) system were considered as explanatory variables. The result is that the normalized difference vegetation index (NDVI) and the density of buildings were the most important factors, each of them explaining a substantial part (more than 50%) of overall air temperature variability. Mobile measurements with NDVI values as a covariate were used for interpolation of air temperature for the entire study area. The spatial variability of nocturnal air temperature and UHI intensity in Brno is the main output presented. Air temperatures interpolated from mobile measurements and NDVI values indicate that the mean urban heat island (UHI) intensity in the early night in summer is at its highest (approximately 5 °C) in the city centre and decreases towards the suburban areas.


2020 ◽  
Author(s):  
Mikhail Varentsov ◽  
Timofey Samsonov ◽  
Pavel Konstantinov ◽  
Pavel Kargashin ◽  
Daniel Fenner ◽  
...  

<p>The presented study is devoted to the investigation of the spatial patterns of the urban-induced air temperature anomaly, known as the urban heat island (UHI) effect, based on the example of Moscow megacity. The numerous previous studies have already shown that Moscow exhibits urban-induced climatic effects (Varentsov e al., 2018) and could serve as a good test-bed for urban climate studies. In the presented study, we have further analyzed the UHI using high-quality observations from the official meteorological networks in Moscow region as well as the uncertified crowdsourcing observations from Netatmo network. The official meteorological networks include more than 70 observational sites in the city and surroundings, while the Netatmo network additionally provides the data from more than 1500 citizen weather stations (CWSs) in Moscow region. Previous studies have shown that CWS observations could be used for urban climate studies after application of the special quality control and filtering routines (Meier et al., 2017).</p><p>The analysis performed for a number of summer and winter seasons has revealed the seasonal variations of the UHI spatial patterns. In order to investigate the driving factors of the observed spatial heterogeneity of the air temperature within the city, we have analyzed its linkages with different qualitative and quantitative parameters of the urban environment, including the Local Climate Zone (LCZ) type, the impervious area fraction, building density, vegetation area fraction, etc. These parameters were obtained using the Landsat and Sentinel satellite images, Copernicus Global Land Cover data and OpenStreetMap data. We have shown that the UHI spatial patterns are shaped both by local and non-local driving factors. The factors such as LCZ type represent the local features of the urban environment, while the non-local drivers represent the influence of remote parts of the megacity, transformed by the atmospheric diffusion and advection. The non-local effects are reflected e.g. in the dependence between the UHI intensity and the distance from the city center; in the differences between similar LCZs, located in the different parts of the city; in the heat advection to the leeward side of the city. The findings of the study clearly illustrate the importance of taking the non-local effects into consideration in urban planning applications, biometeorological assessments and when applying the LCZ approach for big cities.</p><p><strong>Acknowledges:</strong> The processing and analysis of the official and crowdsourcing observations were supported by Russian Foundation for Basic Research (project no. 19-35-70009). The analysis of the impervious surface area fraction data was supported by Russian Foundation for Basic Research (project no. 18-35-20052). The analysis of the impacts of urban vegetation on the urban heat island was supported by Russian Science Foundation (project no. 19-77-30012).</p><p><strong>References: </strong></p><p>Meier F., Fenner D., Grassmann T., Otto M., & Scherer D. (2017). Crowdsourcing air temperature from citizen weather stations for urban climate research. Urban Climate, 19, 170–191.</p><p>Varentsov M., Wouters H., Platonov V., & Konstantinov P. (2018). Megacity-Induced Mesoclimatic Effects in the Lower Atmosphere: A Modeling Study for Multiple Summers over Moscow, Russia. Atmosphere, 9(2), 50.</p>


2018 ◽  
Vol 7 (3.2) ◽  
pp. 597
Author(s):  
Yuri Golik ◽  
Oksana Illiash ◽  
Nataliia Maksiuta

The concept of "heat-island effect", its structure and features of formation over the city are given. The climatic and other features of the city that influence the formation of this phenomenon are mentioned.  The data on functioning in the city of the municipal production enterprise of the heat economy is indicated. The traditional method for determining the formation of the urban "heat-island effect" is described. The data and comparative graphs on the temperature regimes of the city and region are presented. The possibility of influencing architectural features of the city on the formation of the "heat-island-effect" is determined. According to the obtained results, further integrated researches are proposed for obtaining reliable results of the given question. 


2021 ◽  
Vol 13 (17) ◽  
pp. 9617 ◽  
Author(s):  
Wesam M. Elbardisy ◽  
Mohamed A. Salheen ◽  
Mohammed Fahmy

In the Middle East and North Africa (MENA) region, studies focused on the relationship between urban planning practice and climatology are still lacking, despite the fact that the latter has nearly three decades of literature in the region and the former has much more. However, such an unfounded relationship that would consider urban sustainability measures is a serious challenge, especially considering the effects of climate change. The Greater Cairo Region (GCR) has recently witnessed numerous serious urban vehicular network re-development, leaving the city less green and in need of strategically re-thinking the plan regarding, and the role of, green infrastructure. Therefore, this study focuses on approaches to the optimization of the urban green infrastructure, in order to reduce solar irradiance in the city and, thus, its effects on the urban climatology. This is carried out by studying one of the East Cairo neighborhoods, named El-Nozha district, as a representative case of the most impacted neighborhoods. In an attempt to quantify these effects, using parametric simulation, the Air Temperature (Ta), Mean Radiant Temperature (Tmrt), Relative Humidity (RH), and Physiological Equivalent Temperature (PET) parameters were calculated before and after introducing urban trees, acting as green infrastructure types that mitigate climate change and the Urban Heat Island (UHI) effect. Our results indicate that an optimized percentage, spacing, location, and arrangement of urban tree canopies can reduce the irradiance flux at the ground surface, having positive implications in terms of mitigating the urban heat island effect.


2020 ◽  
Vol 9 (12) ◽  
pp. 726
Author(s):  
Md. Omar Sarif ◽  
Bhagawat Rimal ◽  
Nigel E. Stork

More than half of the world’s populations now live in rapidly expanding urban and its surrounding areas. The consequences for Land Use/Land Cover (LULC) dynamics and Surface Urban Heat Island (SUHI) phenomena are poorly understood for many new cities. We explore this issue and their inter-relationship in the Kathmandu Valley, an area of roughly 694 km2, at decadal intervals using April (summer) Landsat images of 1988, 1998, 2008, and 2018. LULC assessment was made using the Support Vector Machine algorithm. In the Kathmandu Valley, most land is either natural vegetation or agricultural land but in the study period there was a rapid expansion of impervious surfaces in urban areas. Impervious surfaces (IL) grew by 113.44 km2 (16.34% of total area), natural vegetation (VL) by 6.07 km2 (0.87% of total area), resulting in the loss of 118.29 km2 area from agricultural land (17.03% of total area) during 1988–2018. At the same time, the average land surface temperature (LST) increased by nearly 5–7 °C in the city and nearly 3–5 °C at the city boundary. For different LULC classes, the highest mean LST increase during 1988–2018 was 7.11 °C for IL with the lowest being 3.18 °C for VL although there were some fluctuations during this time period. While open land only occupies a small proportion of the landscape, it usually had higher mean LST than all other LULC classes. There was a negative relationship both between LST and Normal Difference Vegetation Index (NDVI) and LST and Normal Difference Moisture Index (NDMI), respectively, and a positive relationship between LST and Normal Difference Built-up Index (NDBI). The result of an urban–rural gradient analysis showed there was sharp decrease of mean LST from the city center outwards to about 15 kms because the NDVI also sharply increased, especially in 2008 and 2018, which clearly shows a surface urban heat island effect. Further from the city center, around 20–25 kms, mean LST increased due to increased agriculture activity. The population of Kathmandu Valley was 2.88 million in 2016 and if the growth trend continues then it is predicted to reach 3.85 million by 2035. Consequently, to avoid the critical effects of increasing SUHI in Kathmandu it is essential to improve urban planning including the implementation of green city technologies.


Atmosphere ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 123 ◽  
Author(s):  
Guglielmina Mutani ◽  
Valeria Todeschi

There is growing attention to the use of greenery in urban areas, in various forms and functions, as an instrument to reduce the impact of human activities on the urban environment. The aim of this study has been to investigate the use of green roofs as a strategy to reduce the urban heat island effect and to improve the thermal comfort of indoor and outdoor environments. The effects of the built-up environment, the presence of vegetation and green roofs, and the urban morphology of the city of Turin (Italy) have been assessed considering the land surface temperature distribution. This analysis has considered all the information recorded by the local weather stations and satellite images, and compares it with the geometrical and typological characteristics of the city in order to find correlations that confirm that greenery and vegetation improve the livability of an urban context. The results demonstrate that the land-surface temperature, and therefore the air temperature, tend to decrease as the green areas increase. This trend depends on the type of urban context. Based on the results of a green-roofs investigation of Turin, the existing and potential green roofs are respectively almost 300 (257,380 m2) and 15,450 (6,787,929 m2). Based on potential assessment, a strategy of priority was established according to the characteristics of building, to the presence of empty spaces, and to the identification of critical areas, in which the thermal comfort conditions are poor with low vegetation. This approach can be useful to help stakeholders, urban planners, and policy makers to effectively mitigate the urban heat island (UHI), improve the livability of the city, reduce greenhouse gas (GHG) emissions and gain thermal comfort conditions, and to identify policies and incentives to promote green roofs.


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