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Urban Heat Island (UHI) is the result of accelerated urbanization and it is created when natural land covers replaced by heat-absorbing surfaces such as Asphalt, Cement and etc. Therefore, the main objective of this study is analysis of temperature pattern in three different surfaces such as asphalt, soil and grass in Tehran city during the April 2...
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... can be seen in Fig. 6, the temperature of land covers was not completely sinusoidal pattern because of the effect of cloud cover so that there are some fluctuations on surface temperature trend during the day. To understand the impact of cloud cover on temperature changes, variation of cloud cover during the day was displayed in Fig.7 ...
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... These 2 floor surface temperatures were selected as being representative of common flooring materials in sunny days, respectively, of grass or pavement with a medium reflectance surface (average 37 • C) and asphalt or other similar pavements with low reflectance (average 39 • C). Further details and reasoning behind this can be found in previous studies such as [48,49]. ...
... These 2 floor surface temperatures were selected as being representative of common flooring materials in sunny days, respectively, of grass or pavement with a medium reflectance surface (average 37 °C) and asphalt or other similar pavements with low reflectance (average 39 °C). Further details and reasoning behind this can be found in previous studies such as [48,49]. 3. Defining alternative scenarios by associating the shade/cover material features and RayMan cloudy indexes. ...
Forecasts of a drastic increase in temperatures in the coming decades are driving the adoption of design strategies and solutions to improve the livability of urban environments. Increasing attention is being paid to the thermal comfort of open spaces by both designers and researchers. Nature-based solutions and man-made devices to improve the comfort of outdoor spaces during summer are spreading, but effective, easy simulation and design support tools for this purpose are still lacking, as most of the available software such as ENVI-met or RayMan cannot model such devices. As Physiological Equivalent Temperature (PET) is one of the most relevant and comprehensive indicators of Outdoor Thermal Comfort (OTC), this study aims to investigate PET variations of different artificial shading systems and propose a simplified methodology for assessing them through analytical simulations with RayMan software. When modeling the shading elements, the trick adopted for this purpose is to associate different cloud densities with the shading provided by the screens, thus overcoming a gap that affects the software. The procedure is digitally tested in a covered courtyard case study in Bologna (Italy). Diverse options proposed by the designers for textile screening materials have been compared, showing that these reduce by at least 1 °C the PET-gauged thermal stress. Beyond specific results, the main outcome of this study is the procedure developed to simulate sun-shading sail effects on OTC by means of RayMan, which can support designers in planning effective solutions for open space livability in summertime.
... The foremost reason for UHIs is that urbanization leads to an increase in impervious surfaces that absorb heat, and a decrease in natural vegetation [3]. Numerous studies have shown that the temperature of ordinary asphalt can be 15 to 20 • C higher than that of grass [4][5][6][7]. In our cities, the amount of vegetation is decreasing, and growing amounts of impervious pavements now cover the cities, causing heat islands [8]. ...
... For the flow of air on an infinite flat plate, L = 0.15 m [45]. The Reynold's number is given by Eq. (6). ...
As the world becomes more urbanized, concerns are growing about the phenomenon of urban heat islands (UHIs). In addition to the environmental function of stormwater management, pervious concrete (PC) pavements are also a solution that can help mitigate increasing urban temperatures, through cooling by evaporation. Several studies in the literature have focused on the evaporative cooling effect of PC, which requires the presence of water either from precipitation or irrigation. However, in countries that have dry summers and where watering techniques are complicated to implement, in hot weather and dry conditions, PC can have a higher temperature than traditional impermeable concrete. The main objective of this paper is therefore to study the influence of thermophysical parameters on the surface temperature of PC, with a view to designing a mix that minimizes its surface temperature in dry conditions. The thermal behavior of PC and ordinary impermeable concrete (OC) in dry condition have been studied both analytically and experimentally. All heat fluxes involved in the energy balance at the surface of both pavements were analyzed. The results show that PC has a surface temperature up to 6 ◦C higher than OC during the day and up to 4 ◦C lower during the night. Increasing the thermal conductivity of the pervious concrete makes the surface temperature of PC lower during the day but higher at night. On the other hand, increasing albedo makes the surface temperature of the pavement lower both during the day and during the night. Finally, the sensitivity study shows that the albedo has a greater influence on the maximum surface temperature of the PC than does thermal conductivity. To decrease the maximum temperature of PC, it is recommended to avoid the use of lightweight aggregates and to use finer and lighter colored aggregates (to increase the albedo), having high thermal conductivity. This mix optimization may be limited by the hydraulic properties of the PC due to its influence on the open porosity.
... To estimate the ground temperature, regression analysis was used for each of the three ground materials (Equation (3)). Shamsipour et al. [23] and Ariawan et al. [24] proposed the regression analysis to estimate ground temperature using air temperature. The ground temperature was used as a dependent variable and the air temperature as an independent variable. ...
Cities inadvertently create warmer and drier urban climate conditions than their surrounding areas through urbanization that replaces natural surfaces with impervious materials. These changes cause heat-related health problems and many studies suggest microclimatic urban design (MUD) as an approach to address these problems. In MUD-related research, although terrestrial radiation plays an important role in human thermal comfort and previous studies use thermal comfort models to identify human heat stress, few studies have addressed the effect of terrestrial radiation. This study develops the ground ratio factor (GRF) model to estimate the different terrestrial radiation according to different ground conditions. Three types of ground materials (asphalt, concrete, and grass) were considered in the model, and field studies were conducted in humid subtropical climate (Cfa) zone during the hot season (13 July to 19 September 2020). The model was validated by comparing the predicated terrestrial radiation (PTR) from the model with the actual terrestrial radiation (ATR). The results showed that there is a statistically significant strong correlation between PTR and ATR. The model can contribute to MUD strategies by updating existing human energy budget models, which can lead to the measurement of more accurate human thermal comfort for mitigating thermal environments.
... In addition, the estimated T tg was 21.8 • C. The ground truth for grass temperature is hard to measure due to weak leaves and complex structures. Normally, grass temperature is almost the same as air temperature in a thermal equilibrium state [25]. In general, grass has high albedo and high emissivity (>0.95). ...
... Under no wind state, the assumption that grass temperature is almost the same as air temperature is reasonable. However, if the wind is strong, the evapotranspiration from the grass is an important factor which led to its lower temperature [25]. Figure 24 shows the estimated spectral atmospheric transmittance and emissivity, compared with MODTRAN and the ECOSTRESS grass library. ...
This paper presents a novel method for atmospheric transmittance-temperature-emissivity separation (AT2ES) using online midwave infrared hyperspectral images. Conventionally, temperature and emissivity separation (TES) is a well-known problem in the remote sensing domain. However, previous approaches use the atmospheric correction process before TES using MODTRAN in the long wave infrared band. Simultaneous online atmospheric transmittance-temperature-emissivity separation starts with approximation of the radiative transfer equation in the upper midwave infrared band. The highest atmospheric band is used to estimate surface temperature, assuming high emissive materials. The lowest atmospheric band (CO2 absorption band) is used to estimate air temperature. Through onsite hyperspectral data regression, atmospheric transmittance is obtained from the y-intercept, and emissivity is separated using the observed radiance, the separated object temperature, the air temperature, and atmospheric transmittance. The advantage with the proposed method is from being the first attempt at simultaneous AT2ES and online separation without any prior knowledge and pre-processing. Midwave Fourier transform infrared (FTIR)-based outdoor experimental results validate the feasibility of the proposed AT2ES method.
... The maximum surface temperature during the month of April is the outcome of a dry milieu, low wind speed and uprising intensity of insolation. Although the comparatively slight withdrawing pattern of surface temperature through the month of May is the effect of cloud cover and wind, there is at all times an inverse relationship between cloud cover and surface temperature (Shamsipour et al. 2013). As a general rule, utmost surface temperature of asphalt is connected to maximum absorption of sunbeams, while on the other hand, minimum in grass is caused by higher reflection. ...
The understanding of surface urban heat island pattern above Dibrugarh City has been studied through in situ observation using non-contact infrared thermometer for a period of 4 months by covering 16 selected locations. The chosen locations envelop both urban and suburban sites. The study draws attention to urban hot spots toward the central part of the city all through the different months in addition to the seasons, owing to heat retention supported by the built environment with fewer vegetation cover. Seasonally winter uncovered utmost variability of LST indicated by higher CV value. The core locations/sites witnessed a least amount of variability and continuity of higher LST throughout the learning months. At diurnal pattern, LST designated a sharp decrease from morning to afternoon period through winter months, while contrastingly summer months witnessed a sharp fall of LST from afternoon to night period. Among all the surfaces, asphalt pavement noticed maximum surface temperature with maximum variability in both diurnal and temporal scales. Maximum assimilation with fewer albedo of asphalt surface along with drier soil and grass comes across maximum LST in the internal part of the city. In addition, traffic, pollution and anthropogenic heat emission supported warmer surface temperature of asphalt, grass and bare soil, which on the whole put into the growth of higher surface heat. The stronger affirmative correlation coefficient amid the temperature of different surfaces with air temperature and comparatively weaker unconstructive correlation with relative humidity witnessed the dominant role of air temperature on overall surface urban heat island process.
... High water contents in soils, such as from irrigation, can increase the heat capacity, as can highly vegetated areas [10,15]. It has been found that surface temperatures can be 6 • C warmer in city centers compared to surrounding rural areas [16]; this phenomenon is known as urban heat island [17][18][19]. Urbanization also modifies the location of precipitation [9,[19][20][21][22][23][24]. ...
... Maps of the monthly average daily minimum temperature (Supplementary Material, Figure S3) showed absolute differences between 0.5 to 2 • C for the dry months, and values between 0.5 to 1.5 • C for the rainy months. These results are consistent with those of previous studies of the thermal behavior of urban land compared to vegetated land [17,18], where the largest near-surface temperature differences are observed during noon. Figure 4 shows the time series for the monthly average surface temperature for station 6 in January. ...
... In addition, during the night the highest minimum temperature was estimated. These results are consistent with the measured surface temperature profiles by Shamsipour et al. [17]. thermal behavior of urban land compared to vegetated land [17,18], where the largest near-surface temperature differences are observed during noon. ...
In atmospheric modeling, an accurate representation of land cover is required because such information impacts water and energy budgets and, consequently, the performance of models in simulating regional climate. This study analyzes the impact of the land cover data on an operational weather forecasting system using the Weather Research and Forecasting (WRF) model for central Mexico, with the aim of improving the quality of the operative forecast. Two experiments were conducted using different land cover datasets: a United States Geological Survey (USGS) map and an updated North American Land Change Monitoring System (NALCMS) map. The experiments were conducted as a daily 120 h forecast for each day of January, April, July, and September of 2012, and the near-surface temperature, wind speed, and hourly precipitation were analyzed. Both experiments were compared with observations from meteorological stations. The statistical analysis of this study showed that wind speed and near-surface temperature prediction may be further improved with the updated and more accurate NALCMS dataset, particularly in the forecast covering 48 to 72 h. The Root Mean Square Error (RMSE) of the average wind speed reached a maximum reduction of up to 1.2 m s⁻¹, whereas for the near-surface temperature there was a reduction of up to 0.6 °C. The RMSE of the average hourly precipitation was very similar between both experiments, however the location of precipitation was modified.
