scholarly journals Effect of Sampietrini Pavers on Urban Heat Islands

2021 ◽  
Vol 18 (24) ◽  
pp. 13108
Author(s):  
Laura Moretti ◽  
Giuseppe Cantisani ◽  
Marco Carpiceci ◽  
Antonio D’Andrea ◽  
Giulia Del Serrone ◽  
...  
Keyword(s):  
Air Temperature ◽  
Urban Areas ◽  
Lower Surface ◽  
Early Morning ◽  
Urban Heat Islands ◽  
Predicted Mean Vote ◽  
Heat Islands ◽  
The Road ◽  
Road Pavement ◽  
Microclimatic Conditions

Cool pavements are reflective and/or permeable pavements that improve microclimate of urban areas where heat islands cause discomfort to citizens. Stone pavements lower surface temperatures and reduce the amount of heat absorbed. This study assessed, using ENVI-met 4.3 LITE software, how air temperature and predicted mean vote depend on physical properties of the road pavement. A comparative microclimatic analysis was implemented on a rectangular square in Rome (Italy) in the summer, paved in three different ways: asphalt, traditional sampietrini, and permeable sampietrini. The model considered local weather parameters, surrounding fabric, and vegetation to give reliable results in terms of numerical and graphical output using the application tool Leonardo. The tested pavement types affected air temperature during the day, but did not influence this variable in the early morning. Permeable sampietrini pavement was more effective than traditional sampietrini pavement in reducing air temperature compared to the current asphalt surface. The road pavement did not, however, affect human comfort in terms of predicted mean vote. The obtained results are useful for further investigation of parameters that could modify the microclimatic conditions of urban areas.

Automated detection of urban heat islands based on satellite imagery, digital surface models, and a low-cost sensor network                                     

2021 ◽  
Author(s):  
Sebastian Schlögl ◽  
Nico Bader ◽  
Julien Gérard Anet ◽  
Martin Frey ◽  
Curdin Spirig ◽  
...  
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Rural Areas ◽  
Urban Areas ◽  
Low Cost ◽  
Urban Heat Islands ◽  
Heat Islands ◽  
Micro Scale ◽  
Air Temperatures ◽  
Urban Heat

<p>Today, more than half of the world’s population lives in urban areas and the proportion is projected to increase further in the near future. The increased number of heatwaves worldwide caused by the anthropogenic climate change may lead to heat stress and significant economic and ecological damages. Therefore, the growth of urban areas in combination with climate change can increase future mortality rates in cities, given that cities are more vulnerable to heatwaves due to the greater heat storage capacity of artificial surfaces towards higher longwave radiation fluxes.</p><p>To detect urban heat islands and resolve the micro-scale air temperature field in an urban environment, a low-cost air temperature network, including 450 sensors, was installed in the Swiss cities of Zurich and Basel in 2019 and 2020. These air temperature data, complemented with further official measurement stations, force a statistical air temperature downscaling model for urban environments, which is used operationally to calculate hourly micro-scale air temperatures in 10 m horizontal resolution. In addition to air temperature measurements from the low-cost sensor network, the model is further forced by albedo, NDVI, and NDBI values generated from the polar-orbiting satellite Sentinel-2, land surface temperatures estimated from Landsat-8, and high-resolution digital surface and elevation models.</p><p>Urban heat islands (UHI) are processed averaging hourly air temperatures over an entire year for each grid point, and comparing this average to the overall average in rural areas. UHI effects can then be correlated to high-resolution local climate zone maps and other local factors.</p><p>Between 60-80 % of the urban area is modeled with an accuracy below 1 K for an hourly time step indicating that the approach may work well in different cities. However, the outcome may depend on the complexity of the cities. The model error decreases rapidly by increasing the number of spatially distributed sensor data used to train the model, from 0 to 70 sensors, and then plateaus with further increases. An accuracy below 1 K can be expected for more than 50 air temperature measurements within the investigated cities and the surrounding rural areas. </p><p>A strong statistical air temperature model coupled with atmospheric boundary layer models (e.g. PALM-4U, MUKLIMO, FITNAH) will aid to generate highly resolved urban heat island prediction maps that help decision-makers to identify local heat islands easier. This will ensure that financial resources will be invested as efficiently as possible in mitigation actions.</p>

scholarly journals A spatially-explicit approach to simulate urban heat islands in complex urban landscapes

2020 ◽  
Author(s):  
Martí Bosch ◽  
Maxence Locatelli ◽  
Perrine Hamel ◽  
Roy P. Remme ◽  
Jérôme Chenal ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Air Temperature ◽  
Urban Areas ◽  
Heat Waves ◽  
Urban Heat Islands ◽  
Land Use Land Cover ◽  
Heat Islands ◽  
Urban Heat ◽  
Cooling Model

Abstract. Mitigating urban heat islands has become an important objective for many cities experiencing heat waves. Despite notable progress, the spatial relationship between land use/land cover patterns and the distribution of air temperature remains poorly understood. This article presents a reusable computational workflow to simulate the spatial distribution of air temperature in urban areas from their land use/land cover data. The approach employs the InVEST urban cooling model, which estimates the cooling capacity of the urban fabric based on three biophysical mechanisms, i.e., tree shade, evapotranspiration and albedo. An automated procedure is proposed to calibrate the parameters of the model to best fit air temperature observations from monitoring stations. In a case study in Lausanne, Switzerland, spatial estimates of air temperature obtained with the calibrated model show that the urban cooling model outperforms spatial regressions based on satellite data. This represents two major advances in urban heat island modeling. First, unlike in black-box approaches, the calibrated parameters of the urban cooling model can be interpreted in terms of the physical mechanisms that they represent and can therefore help understanding how urban heat islands emerge in a particular context. Second, the urban cooling model requires only land use/land cover and reference temperature data and can therefore be used to evaluate synthetic scenarios such as master plans, urbanization prospects, and climate scenarios. The proposed approach provides valuable insights into the emergence of urban heat islands which can serve to inform urban planning and assist the design of heat mitigation policies.

scholarly journals A spatially explicit approach to simulate urban heat mitigation with InVEST (v3.8.0)

2021 ◽  
Vol 14 (6) ◽  
pp. 3521-3537
Author(s):  
Martí Bosch ◽  
Maxence Locatelli ◽  
Perrine Hamel ◽  
Roy P. Remme ◽  
Jérôme Chenal ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Air Temperature ◽  
Urban Areas ◽  
Heat Waves ◽  
Spatial Relationship ◽  
Urban Heat Islands ◽  
Heat Islands ◽  
Urban Heat ◽  
Cooling Model

Abstract. Mitigating urban heat islands has become an important objective for many cities experiencing heat waves. Despite notable progress, the spatial relationship between land use and/or land cover patterns and the distribution of air temperature remains poorly understood. This article presents a reusable computational workflow to simulate the spatial distribution of air temperature in urban areas from their land use and/or land cover data. The approach employs the InVEST urban cooling model, which estimates the cooling capacity of the urban fabric based on three biophysical mechanisms: tree shade, evapotranspiration and albedo. An automated procedure is proposed to calibrate the parameters of the model to best fit air temperature observations from monitoring stations. In a case study in Lausanne, Switzerland, spatial estimates of air temperature obtained with the calibrated model show that the urban cooling model outperforms spatial regressions based on satellite data. This represents two major advances in urban heat island modeling. First, unlike in black-box approaches, the calibrated parameters of the urban cooling model can be interpreted in terms of the physical mechanisms that they represent; therefore, they can help promote an understanding of how urban heat islands emerge in a particular context. Second, the urban cooling model requires only land use and/or land cover and reference temperature data and can, therefore, be used to evaluate synthetic scenarios such as master plans, urbanization prospects and climate scenarios. The proposed approach provides valuable insights into the emergence of urban heat islands which can serve to inform urban planning and assist the design of heat mitigation policies.

scholarly journals Green roofs and cool materials as retrofitting strategies for urban heat island mitigation: Case study in Belgrade, Serbia

2018 ◽  
Vol 22 (6 Part A) ◽  
pp. 2309-2324
Author(s):  
Marija Lalosevic ◽  
Mirko Komatina ◽  
Marko Milos ◽  
Nedzad Rudonja
Keyword(s):  
Green Roofs ◽  
Urban Heat Islands ◽  
Temperature Changes ◽  
Heat Islands ◽  
Air Temperatures ◽  
Urban Heat ◽  
Microclimatic Conditions ◽  
Typical Summer ◽  
Planning And Construction ◽  
The Impact

The effect of extensive and intensive green roofs on improving outdoor microclimate parameters of urban built environments is currently a worldwide focus of research. Due to the lack of reliable data for Belgrade, the impact of extensive and intensive green roof systems on mitigating the effects of urban heat islands and improving microclimatic conditions by utilizing high albedo materials in public spaces were studied. Research was conducted on four chosen urban units within existing residential blocks in the city that were representative of typical urban planning and construction within the Belgrade metropolitan area. Five different models (baseline model and four potential models of retrofitting) were designed, for which the temperature changes at pedestrian and roof levels at 07:00, 13:00, 19:00 h, on a typical summer day, and at 01:00 h, the following night in Belgrade were investigated. The ENVI-met software was used to model the simulations. The results of numerical modeling showed that utilizing green roofs in the Belgrade climatic area could reduce air temperatures in the surroundings up to 0.47, 1.51, 1.60, 1.80 ?C at pedestrian level and up to 0.53, 1.45, 0.90, 1.45 ?C at roof level for four potential retrofitting strategies, respectively.

scholarly journals Characterizing the Hourly Variation of Urban Heat Islands in a Snowy Climate City during Summer

2019 ◽  
Vol 16 (14) ◽  
pp. 2467 ◽  
Author(s):  
Chaobin Yang ◽  
Ranghu Wang ◽  
Shuwen Zhang ◽  
Caoxiang Ji ◽  
Xie Fu
Keyword(s):  
Land Use ◽  
Urban Area ◽  
Air Temperature ◽  
Temporal Variability ◽  
Spatial Information ◽  
Thermal Environment ◽  
Thermal Characteristics ◽  
Urban Heat Islands ◽  
Heat Islands ◽  
Urban Heat

Temporal variation of urban heat island (UHI) intensity is one of the most important themes in UHI studies. However, fine-scale temporal variability of UHI with explicit spatial information is sparse in the literature. Based on the hourly air temperature from 195 meteorological stations during August 2015 in Changchun, China, hourly spatiotemporal patterns of UHI were mapped to explore the temporal variability and the effects of land use on the thermal environment using time series analysis, air temperature profiling, and spatial analysis. The results showed that: (1) high air temperature does not indicate strong UHI intensity. The nighttime UHI intensity (1.51 °C) was much stronger than that in the daytime (0.49 °C). (2) The urban area was the hottest during most of the day except the period from late morning to around 13:00 when there was about a 40% possibility for an “inverse UHI intensity” to appear. Paddy land was the coolest in the daytime, while woodland had the lowest temperature during the nighttime. (3) The rural area had higher warming and cooling rates than the urban area after sunrise and sunset. It appeared that 23 °C was the threshold at which the thermal characteristics of different land use types changed significantly.

Estimating the expansion of urban areas and urban heat islands (UHI) in Ghana: a case study

2020 ◽  
Author(s):  
Isaac Buo ◽  
Valentina Sagris ◽  
Iuliia Burdun ◽  
Evelyn Uuemaa
Keyword(s):  
Urban Areas ◽  
Urban Heat Islands ◽  
Heat Islands ◽  
Urban Heat

scholarly journals Comparative Thermal Analysis of Different Cool Roof Materials for Minimizing Building Energy Consumption

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Y. Anand ◽  
A. Gupta ◽  
A. Maini ◽  
Avi Gupta ◽  
A. Sharma ◽  
...  
Keyword(s):  
Thermal Analysis ◽  
Urban Areas ◽  
Electricity Consumption ◽  
Building Envelope ◽  
Comfort Level ◽  
Urban Heat Islands ◽  
Heat Islands ◽  
Cool Roof ◽  
Cool Roofs ◽  
The Impact

The roof and walls in the urban areas contribute to major share in the absorption of solar radiations and also retard the outflow of the absorbed radiation from the building envelope, thereby increasing the global warming by inducing the heat island effect. The impact of using cool roof technologies on the thermal comfort of the office buildings has been estimated. Cool roofs reduce electricity consumption for maintaining the temperature of the air-conditioned buildings in the comfort level and also increase comfort in buildings merely not relying completely on cooling equipment. The cool roofs and cool pavements, however, can mitigate summer urban heat islands by improving indoor air quality and comfort. The thermal analysis of different materials has been carried out to analyze the impact of the rate of heat transfer on the building envelope and the results obtained indicate that different cool roof techniques are beneficial in maintaining the comfort level of the building which purely depends on the ambient temperature conditions.

Emergence of opposite trends in daytime and night-time urban heat island intensities in England

2020 ◽  
Author(s):  
Eunice Lo ◽  
Dann Mitchell ◽  
Sylvia Bohnenstengel ◽  
Mat Collins ◽  
Ed Hawkins ◽  
...  
Keyword(s):  
Urban Heat Island ◽  
Urban Areas ◽  
Urban Land Use ◽  
Urban Heat Islands ◽  
Urban Heat Island Effect ◽  
Heat Island ◽  
Night Time ◽  
Heat Islands ◽  
Island Effect ◽  
Urban Heat

<p>Urban environments are known to be warmer than their sub-urban or rural surroundings, particularly at night. In summer, urban heat islands exacerbate the occurrence of extreme heat events, posing health risks to urban residents. In the UK where 90% of the population is projected to live in urban areas by 2050, projecting changes in urban heat islands in a warming climate is essential to adaptation and urban planning.</p><p>With the use of the new UK Climate Projections (UKCP18) in which urban land use is constant, I will show that both summer urban and sub-urban temperatures are projected to increase in the 10 most populous built-up areas in England between 1980 and 2080. However, differential warming rates in urban and sub-urban areas, and during day and at night suggest a trend towards a reduced daytime urban heat island effect but an enhanced night-time urban heat island effect. These changes in urban heat islands have implications on thermal comfort and local atmospheric circulations that impact the dispersion of air pollutants. I will further demonstrate that the opposite trends in daytime and night-time urban heat island effects are projected to emerge from current variability in more than half of the studied cities below a global mean warming of 3°C above pre-industrial levels.</p>

scholarly journals The Influence of Vegetation on UHIs, MUHIs, and Microclimate of Selected Southern Cities

HortScience ◽  
1997 ◽  
Vol 32 (3) ◽  
pp. 509A-509
Author(s):  
Derald A. Harp ◽  
Edward L. McWilliams
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Building Materials ◽  
Urban Heat Islands ◽  
Shopping Malls ◽  
Heat Islands ◽  
Suburban Areas ◽  
Winter Temperatures ◽  
Urban Heat ◽  
The City

Urban areas have average annual temperatures 2–3°C warmer than surrounding rural areas, with daily differences of 5–6°C common. A suggested reason for this temperature difference is the extensive use of concrete, asphalt, and other building materials in the urban environment. Vegetation can moderate these temperatures by intercepting incoming radiation. The influence of vegetation patterns on the magnitude of urban and micro-urban “heat islands” (UHI and MUHI, respectively) is compared for several cities including Houston, Austin, College Station, and Ft. Worth, Texas; Huntsville, Ala.; and Gainesville, Fla. Temperatures for all cities studied were greatest in the built-up areas and dropped off in suburban areas and adjacent rural areas. In Houston, surrounding rice fields were 3–5°C cooler than urban areas. Heavily built-up areas of Austin were 2–4°C warmer than parks and fields outside of the city. In all of the cities, large parks were typically 2–3°C cooler than adjacent built-up areas. Large shopping malls varied in nocturnal winter and summer temperature, with winter temperatures near door openings 2–3°C warmer, and summer daytime temperatures as much as 17°C cooler beneath trees. This effect seemed to persist at the microclimatic scale. Areas beneath evergreen trees and shrubs were warmer in the winter than surrounding grass covered areas. Video thermography indicated that the lower surfaces of limbs in deciduous trees were warmer than the upper surfaces. Overall, vegetation played a significant role, both at the local and microscale, in temperature moderation.

scholarly journals A Comparative Study of various Indices for extraction urban impervious surface of Landsat 8 OLI

2019 ◽  
Vol 33 (2) ◽  
pp. 162-172
Author(s):  
Iswari Nur Hidayati ◽  
R Suharyadi
Keyword(s):  
Land Use ◽  
Urban Areas ◽  
Spectral Characteristics ◽  
Impervious Surface ◽  
Urban Heat Islands ◽  
Landsat 8 ◽  
Impervious Surfaces ◽  
Landsat 8 Oli ◽  
Heat Islands ◽  
Urban Heat

Impervious surface is one of the major land cover types of urban and suburban environment. Conversion of rural landscapes and vegetation area to urban and suburban land use is directly related to the increase of the impervious surface area. The impervious surface expansion is straight-lined with decreasing green spaces in urban areas. Impervious surface is one of indicator for detecting urban heat islands. This study compares various indices for mapping impervious surfaces using Landsat 8 OLI imagery by optimizing the different spectral characteristics of Landsat 8 OLI imagery. The research objectives are (1) to apply various indices for impervious surface mapping and (2) identifies impervious surfaces in urban areas based on multiple indices and provide recommendations and find the best index for mapping impervious surface in urban areas. In addition to utilizing the index, land use supervised classification method, maximum likelihood classification used for extracting built-up, and non-built-up areas. Accuracy assessment of this research used field data collection as primary data for calculating kappa coefficient, producer accuracy, and user accuracy. The study can also be extended to find the land surface temperature and correlate the impervious surface extraction data with urban heat islands.

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