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Antoszewski, P.; Świerk, D.; Krzyżaniak, M. Climate-Resilient and Climate-Neutral City. Encyclopedia. Available online: https://encyclopedia.pub/entry/21564 (accessed on 05 July 2024).
Antoszewski P, Świerk D, Krzyżaniak M. Climate-Resilient and Climate-Neutral City. Encyclopedia. Available at: https://encyclopedia.pub/entry/21564. Accessed July 05, 2024.
Antoszewski, Patryk, Dariusz Świerk, Michał Krzyżaniak. "Climate-Resilient and Climate-Neutral City" Encyclopedia, https://encyclopedia.pub/entry/21564 (accessed July 05, 2024).
Antoszewski, P., Świerk, D., & Krzyżaniak, M. (2022, April 11). Climate-Resilient and Climate-Neutral City. In Encyclopedia. https://encyclopedia.pub/entry/21564
Antoszewski, Patryk, et al. "Climate-Resilient and Climate-Neutral City." Encyclopedia. Web. 11 April, 2022.
Climate-Resilient and Climate-Neutral City
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The urban heat island (UHI) effect is the main problem regarding a city’s climate. It is the main adverse effect of urbanization and negatively affects human thermal comfort levels as defined by physiological equivalent temperature (PET) in the urban environment. Blue and green infrastructure (BGI) solutions may mitigate the UHI effect. First, however, it is necessary to understand the problem from the degrading side. Researchers related to urban planning, architecture, and climatology are developing the city-UHI relationship’s mechanics and effective mitigation strategies based on the already-known dependencies. What the future urban environment should look like in order to be resilient to climate change and to be climate neutral are examined here.

UHI mitigation strategy UHI intensity BGI PET built-up environment parameters urban space parameterization urbanized environment street canyon climate changes

1. Introduction

1.1. The Urban Heat Island (UHI) Effect–Causes, Effects, and Countermeasure

The UHI effect describes the solar radiation balance, which for urbanized areas is low compared to non-urbanized areas. The UHI intensity is based on the temperature difference between the measurements taken in the city and at reference stations outside the city. Measurements are performed in various scales depending on the research needs [1][2] and using terrestrial equipment or remote sensing. Over a century of observing, the UHI effect has become the best-described climate change phenomenon [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19].
For millennia, humanity has been modifying the natural landscape by transforming its coverage patterns for its own purposes. However, in recent decades, the increased intensity of these changes related to rapid and uncontrolled urbanization contributes massively to natural environment degradation and rises with city expansion [20][21][22]. Recently, the aggressive urbanization effects in the form of the UHI effect have increased and the emergence of local climate anomalies have been noticeable. For this reason, it is widely believed that increased city temperatures are a direct result of excessive urbanization.
A positive radiation balance is recorded in all cities throughout the year [23][24][25][26]. However, the UHI effect intensity shows diurnal, seasonal [4][6][27], and geographical variability, which will differ for cities in various climatic zones [28][29]. Solar radiation intensity, air temperature, relative humidity, and wind speed affect UHI appearance and its course [9][30][31][32][33][34][35][36]. The distribution of the UHI effect inside the city and its intensity depend on the degree of development of the area, interior geometry, and materials used [13][37][38][39][40][41]. Urban factors affect, among other things, increased solar exposure, absorption of short-wave radiation and trapping of long-wave radiation, reduction of the radiation reflection coefficient, increase of the radiation absorption rate, heat capacity, shift of the emission phase, changes in the dominant winds patterns, reduction of wind speed and its humidity, reduced evaporation, post-transport cooling, and turbulent and convective heat transport [42][43][44][45][46][47][48][49][50][51]. In addition, the built-up area density and the anthropogenic heat emission (buildings heating and cooling, transport and industry fumes emission, and general air pollution) [52][53] increase the latent heat gains. There is also a dangerous cause-and-effect loop in this case. The increased UHI intensity increases the temperatures inside the buildings and forces their occupants to cool them. On the other hand, the building’s cooling causes an additional increase in the temperature outside the building. The cause-and-effect loop closes, increasing the heat gain in the city canyons.
The UHI increase caused by the deteriorating quality of the urban environment impacts the overall increase in air temperature in the city, air circulation reduction, heatwaves intensity and frequency, and the concentration of the pollutants [54][55][56][57][58][59][60]. Those factors reduce the internal and external thermal comfort referred to as physiological equivalent temperature (PET) and increase morbidity and mortality [61][62][63][64][65][66][67]. In addition, they can be associated with health problems such as exhaustion, heat shock, thermoregulation processes disturbance, and cardiovascular stress [68][69].
Global warming will undoubtedly increase the frequency, duration, and intensity of related heat waves [70][71]. Therefore, it is necessary to counteract its formation now, bearing in mind that UHI mitigation also reduces the climate change rate [72][73].

1.2. Countermeasure Strategies

Researchers related to urban planning, architecture, and climatology are developing the city-UHI relationship’s mechanics and effective mitigation strategies based on the already-known dependencies [74][75].
Many tools have been developed to mitigate the elevated city temperature related to (1) reducing the emission of anthropogenic heat, (2) increasing albedo and evapotranspiration, (3) introducing nature-based solutions such as the blue and green infrastructure (BGI), (4) the use of regenerative design practices taking into account the local climate, and (5) modification of city geometry and de-urbanization [76][77][78][79][80][81][82][83][84][85][86][87][88][89][90]. However, the most efficient and striking root cause solution seems to be creating the BGI, which is introducing and increasing greenery and water object areas [91].
In previous studies, the researchers carried out a qualitative systematization of the BGI object parameters influencing the UHI effect mitigation (Table 1).
Table 1. The review of the blue-green infrastructure (BGI) element parameters relevant to urban heat island (UHI) effect mitigation [92].
BGI
Structure
Parameter Family Dominant Parameter
Water structure Geometrical Area
Morphological Degree of vegetation along the bank
Topographical Wind exposure (trend of cold transfer)
Green area Geometrical Area
Morphological Percentage of an area covered by trees
Topographical Exposure to solar radiation/degree of shading by surrounding structures
Greenery along the street Geometrical Tree crown width/diameter
Morphological Leaf size/leaf area index (LAI)
Topographical Canyon geometry/height/width
Green roof Geometrical Substrate layer thickness
Morphological Degree of hydration/moisture of the substrate
Topographical Height of structure above the ground/distance from the nearest BGI (synergy)
Green wall Geometrical Degree of vegetation coverage of a building/the extent of the green wall
Morphological Leaf width/leaf area/foliage density/LAI
Topographical Orientation relative to the sun
It has been proven that the BGI solutions, understood as vegetation and water objects, can significantly affect the urban microclimate by reducing the ambient temperature and increasing humidity. In addition, greenery definitely affects air quality by absorbing harmful gases, carbon dioxide, aromatic hydrocarbons, and dust, while replenishing the air with oxygen, essential oils, and alleles and ionizing them. Requiring supplementation is the development of the topic from the degrading side, i.e., examining the quality parameters of the urbanized space elements affecting the UHI intensity increase. Understanding the context and its impact on the local thermal image is necessary for the most accurate selection of the BGI parameters to reduce the ambient temperature.

2. Discussion and Urban Design Strategy Recommendations

2.1. Out-of-Scale Parameters

The basic property of urban space is its solar exposure influencing the internal energy balance [93]. This is referred to as the sky view factor (SVF). By scientists in general, SVF was considered the basic indicator determining mainly the geometry of the city canyon. However, SVF is a qualitative parameter; therefore, its translation into urban planning is problematic [94]. To understand what is responsible for the city’s chiaroscuro distribution, researchers need to break SVF into smaller elements. Land cover with buildings [95], building density [95][96], building volume [95], aspect ratio [97][98], building symmetry [96], building element proportions [95], building orientation [99], building height [99], and the presence and size of trees [100] and other shading elements [101] are parameters that build up SFV. SVF is positively associated with land surface temperature (LST) [102][103], atmospheric temperature (AT) [104][105][106][107][108][109][110], and the UHI effect [111][112][113][114], both during the day [115][116][117][118][119][120][121] and at night [122][123][124][125][126][127][128][129] in all seasons [130]. Only after a deeper analysis, can the complicated pattern of dependencies governing SVF be seen. The availability of the sun changes with the season changes, and the growing season seems to have an obvious influence on this change [124]. The same level of SVF affects incoming radiation during the day and outgoing radiation at night [124][129]. At the same time, it can hinder sunlight access and retain the heat accumulated in the urban tissue. Moreover, solar availability is a basic element influencing the albedo efficiency [131], emissivity [132], and convective air movements related mainly to the heating of various surfaces [133][134].
The type of land cover is partly responsible for the temperature distribution within the city. Different city zones affect PET and UHI differently because of their function and class [135]. The type of coverage is characterized by its specific anthropogenic emission, pollutant concentration, a combination of spatial parameters such as the density of buildings and roads, and the size of impervious surfaces that receive solar radiation. For this reason, residential, commercial, and industrial zones have a particular impact on increasing intra-city temperatures [136][137][138][139]. The industrial areas are characterized by the highest pavement temperatures, high gas emissions, and energy consumption, increasing the daily anthropogenic heat. Accordingly, they are considered the main UHI propagation points [140] with a limited contribution to the overall city’s UHI effect because of the small total area [136]. Commercial spaces are also characterized by high anthropogenic heat. In this case, it is result of high daily energy consumption, traffic, and crowds of people [141]. Finally, the residential area may be the largest radiator of anthropogenic heat during the day, mainly from space heating and cooling [142]. This zone, similar to the office, education, health, tourist, and religious zones, usually has a low built-up area density and high green area coverage, which reduces the impact of heat emission on the UHI effect [135]. The most favorable type of cover for PET and UHI are green areas, agricultural lands, and water objects [143][144][145][146][147][148].
The thermal behavior of an urban unit is directly influenced by its size. In the forest case, its size is of great importance for the inside temperature and humidity amplitude. However, this dependence is inversely analogous for urbanized areas. Research shows that the larger the city, the higher the temperature. However, one must deal with a specific hierarchy resulting from the original city size in this case. Increasing the large city size will bring more significant changes than increasing a small city size. It happens because of the number and density of urbanized areas showing higher temperatures and the synergy among the elements [149][102][137]. The densification of various urbanized areas may disturb that relationship’s linearity. Aggregated smaller cities may have a higher UHI intensity than large cities with low building density [150].
Another temperature modulator of an urban unit is its degree of centrality. A greater degree of centralization shows many city hotspots and thus the higher UHI levels. This dependence is built by spatially complex street layouts with a high degree of irregularities, with more intersections, greater density of impervious surfaces, a more significant number and density of buildings with irregular distribution and shapes, and the related anthropogenic heat [151][152][153] characteristic for a centralized city. This description perfectly reflects the center’s image of an old and large city [101].
The distance from heat sinks, both cold and hot, affects the temperatures inside an urban unit [116]. The proximity to the unit’s center (a city or a housing estate) increases the local temperature [154][155]. Distance to a cooler green area heat sink is impactful throughout the day [119]. The closer the green areas are, the cooler it is during the day [156] and it is slightly warmer at night [154]. A similar relationship can be noticed concerning water objects [157]. These diurnal differences are related to the thermal capacity of water, heat retention under the canopy of trees, and the landscape context [158].

2.2. Material Properties

This scale shows the thermal behavior of the city’s basic building material and the impact of its thermal properties on the immediate and farther surroundings. In this context, the significant thermal parameters of building materials include surface permeability for water, heat capacity, albedo, insulation and conductivity degree, absorption rate, diffusivity, and emissivity.
One of the essential material parameters is the permeability or porosity of the pavement. This affects the intensity of evapotranspiration and has a significant impact on the temperature of pedestrian and road surfaces [159][160], the UHI effect [161], and the high AT duration [141]. Due to their structure, green areas [107], both with predominantly high or low greenery, are characterized by the highest degree of transpiration [120][159]. The effect of evaporative cooling from permeable surfaces is noticeable within 150 m. Since the intensity of evapotranspiration is influenced by the temperature of the city air, the lower temperature can be felt, especially in summer. Literature reports that the daytime temperature may drop by 3.4 °C and night temperature by 1.2 °C because of the use of permeable surfaces [161].
Besides its evident influence on building temperature, thermal insulation impacts the city air temperature because of the energy exchange between the building and the canyon [162]. Poor thermal insulation increases the intensity of this exchange. The impact of this parameter on the city’s energy balance becomes more important, especially in winter, when building heating prevails [128]. The size of the heat exchanger is not insignificant. With the increase of the building wall area determined by the canyon height, the effect is multiplied, which is noticeable in the rise of the canyon temperature [128][163].
The decrease in the thermal conductivity of the pavement reduces heat absorption [164] and contributes to the formation of higher pavement temperatures [165]. In turn, increasing the conductivity parameter contributes to greater heat transmission into the pavement, which may be dangerous for underground infrastructure [159][166].
Increasing thermal diffusivity reduces the daytime ambient temperature and raises the night temperature [112]. An example of a material with high diffusivity is a granite surface [159].
The radiation absorption rate is another parameter that strongly influences the pavement temperature. Reducing the absorption rate can significantly lower the temperature of the material [165][167] and bring more significant thermal benefits to the city than the increase in emissivity [165].
The materials’ heat capacity depends on, among other things, the density, mass, and material albedo [168]. For this reason, both hard construction materials such as asphalt, concrete, and dense bricks and natural surfaces such as grass/soil and water are characterized by high heat capacity. These surfaces have a greater tendency to store large amounts of heat in their volume. This property affects the time shift in heat release because the heat absorbed during the day will be released to the atmosphere at night [169][170][171]. The capacity of the pavement can be increased by manipulating the density and thickness of the pavement foundation. Increasing these parameters causes an increase in thermal capacity [172]. On the other hand, its decrease is caused by an increase in the material’s porosity, i.e., its density, in fact [172]. Thermal mass, which has similar dependencies, has a more significant impact on the city-scale temperature [44]. In this case, it is possible to manipulate the building’s density, volume, and area. A higher building density similarly increases the area thermal mass [120]. On a larger scale, the stored heat does not affect the average air temperature but significantly affects the amplitude and phases [44]. The stored heat reduces the city temperature fluctuations but, on the other hand, it increases the intensity of UHI [128][166][167]. Moreover, the district’s high heat capacity may increase anthropogenic heat resulting from cooling rooms in the summer [150]. For example, old city centers tend to have a high thermal mass, and therefore PET in these districts during the day is much lower, and nighttime UHI is much higher than in newer districts [120][173]. The thermal mass can be modulated with the canyon’s shape [48] by increasing or reducing the area of the walls of the building [120]. However, this dependence is only available for canyons with a high degree of surface development [174].
The urban surface emissivity results from the physical and chemical material structure [175]. It has a significant impact on the energy balance of the canyon, influencing the total radiation emitted from it [162][175]. During the day, the emissivity influence is invisible. At night, it can cause temperature drops [112][165] even by 0.3 °C with a change of 0.1 in emissivity unit [176]. The emissivity can be modulated by the housing estate geometry [132], using so-called cold materials [177], or painting the material surface with special film-forming paints [178]. Decreasing the emissivity of roofing materials may reduce a building’s thermal losses [178]. Thus, reducing emissivity may decrease anthropogenic heat emissions caused by heating or cooling buildings.

2.3. Building Scale Design Parameters

This scale shows the influence of building parameters on both its internal and external thermal behavior. On this scale, one can notice the significant impact of two groups of parameters on temperature changes. Those groups are the building geometry determined by its surface, shape, height, and anthropogenic emissions related to air-conditioning use and energy efficiency.

2.3.1. Envelope Geometry

The building area size significantly affects the UHI effect [179][180][181], both during the day and at night [118]. Increasing the building area leads to an increase in LST [182] and extends the duration of high air temperature. This relationship is more evident in commercial than residential buildings [141]. Despite the negative impact of buildings’ large area on temperature, in the initial phase of increasing the building floor area factor, a reduction in the heating energy consumption can be noted [183]. This means that the ideal proportions of the building area should be found, which will not significantly affect the LST and reduce anthropogenic emissions.
The shape of a building influences the local thermal environment and daytime comfort in different ways [96][139]. An increase in the complexity of a building shape may lead to the LST increase because of increased solar exposure of facades [156]. However, the increased facade surface area may contribute to more intense energy exchange between built-up areas and vegetation [156][184]. In addition, shortening the length of the building itself may improve thermal comfort and help avoid the occurrence of ventilation shade on the other side of the building [54]. The above dependencies suggest that buildings with compact and regular plans are the best for the external thermal environment if there is no greenery near the building [185].
Building height is one of the most critical factors affecting temperature [186][143] and UHI [135]. It influences the local thermal environment around the building, changing the conditions of insolation and ventilation [187][188]. As the building height increases, the LST and the daily temperature amplitude increase [129]. Buildings with a height of 10 m show the highest temperature amplitude during the day [186][189]. The significance of the building height is strongly dependent on solar exposure [190][191], which is modulated by the density of the surroundings [94][192]. For this reason, the temperature amplitude of the high parts of the building will always be higher [129]. In the case of a pillar-based building, raising the height of the building increases the wind flow underneath the building, especially in the corner zones, which slightly improves the PET around the area [193]. Increasing the height of a highly exposed building increases the evapotranspiration cooling effect of nearby trees [54][143]. The building height by shadowing determines the energy consumption of buildings [194].

2.3.2. Anthropogenic Emission

Japanese researchers believe about 40% of anthropogenic heat comes from buildings [195]. This contributes to UHI intensity and the thermal comfort deterioration at the pedestrian level, and extends the duration of the elevated temperature [100]. The heat emitted from buildings depends on their energy efficiency. A building’s energy efficiency is influenced mainly by the percentage of the building envelope, its material, and daytime sun exposure [194][196]. It depends less on the patterns of wind flow and air temperature [48][196]; therefore, the context contribution of the building location cannot be ruled out in this relationship. A building in a densely built-up area will be more energy efficient than an insulated building [197], especially if there are large roads in its immediate vicinity [198]. Excessive anthropogenic heat emitted from a building is highly correlated with two seasons: summer and winter. In winter, space and water heating are responsible for emissions [163]. In summer, the air conditioning used to cool rooms takes over [142][150].
Air conditioners installed outside the building affect local heat fluxes. They can raise the building’s ambient temperature by up to 1.7 °C [150]. Their effect on temperatures appears to be paradoxical and self-perpetuating. The increased temperature outside necessitates cooling inside the building. In this case, the heat emitted from the A/C heats the air outside, increasing the need to cool the building. In this way, air conditioners can significantly increase heat wave mortality [142]. Studies in France and Hong Kong show that this unfortunate loop can be broken by managing air conditioning in rooms [100][142]. Energy-saving A/C operation helps to reduce the emission of anthropogenic heat, the intensity of UHI, and the duration of elevated temperatures by up to 28%, especially at night [100].
Using a green roof or a cool roof [199] will help reduce both the cooling and heating load, the latter being more effective [200]. The green roof also has a slight influence on the ambient building temperature. However, effective space cooling depends on increased context density and its albedo decrease [148]. The problem of this solution is the maintenance itself in climate varieties that are less favorable for vegetation [201].

2.4. Street Canyon Scale Design Parameters

The scale of the city canyon includes buildings and a road, square, or other element forming its bottom. It may consist of both a canyon in the sense of a street with a parallel arrangement of buildings and closed courtyard arrangements. Elements in this scale have both local and supra-local impacts. The obvious factor to discuss is the canyon’s shape, which affects all its thermal relationships. In addition, the influence of orientation and shading elements on the local thermal environment of the canyon is noticeable compared to others.

2.4.1. Surface Geometry

The mutual height ratio to the canyon width is referred to as aspect ratio and denoted as H/W. This parameter is responsible for the cross-sectional geometry image of the street, square, or courtyard and tells about its depth/openness and, in a way, solar exposure. The canyon height and width modifies the thermal conditions in the street space [167][202][203][204]. One can observe a special relationship between the elements which create the canyon aspect ratio. The greater the canyon height, the narrower the canyon, and the higher the H/W ratio, the greater the canyon depth. The H/W influences the shading patterns [135] and wind [47][98][135], thermal mass [120], and canyon radiation balance [120]. It also significantly influences the LST, canyon air temperature fluctuations [98][102][120][128], the occurrence of the thermal peak at the pedestrians level, their thermal comfort [47][205], and less significantly the UHI [107][206]. It should be noted that the influence of the shape factor is more dominant in the case of road surface temperature than in the case of the roof temperature [117]. However, equalizing the canyon height and width blur this difference [129][173].
The canyon geometry dynamically influences its thermal behavior during the day and throughout the year [198][207][208][209][210][211], and changes in canyon depth have better mitigation potential for the nocturnal UHI [212][154]. Wide canyons are characterized by a rapid LST increase in the morning, and because of the greater heated surface area, they reach higher maximum temperatures earlier [198][213][214]. At night, their thermal response is better than the high canyons. The low H/W ratios canyons have much greater net longwave radiation exiting the canyon and more significant convective cooling [208][213]. As a result, they cool down faster and show a greater proportion of cool area than high H/W ratio street canyons [167]. That explains why wider canyons have a smaller overall UHI than deep canyons [173][214] despite a greater intensity variation during daytime [213][215]. As the aspect ratio increases in the morning, the UHI effect becomes the urban cool island (UCI) effect because of the strong shading effect [97][100]. By reducing the penetration of direct sunlight [198], higher H/W allows the bottom of the canyon to remain completely shaded and thus to heat slower [207]. The maximum short-wave radiation in such a canyon occurs around noon [198]. The increase in shaded areas results in lower maximum temperatures [120], daily temperature ranges [167], the mean radiant temperatures (Tmrt) [98], and the LST [107][111][216][217][218], especially walls with greater sun exposure [213]. Human thermal comfort is also improved [98][219]. That can be seen in the courtyards case. Their deepening can lower their air temperatures by about 2–2.5 °C [220][221]. The deep canyon is cooler in the afternoon than the shallow one [222]. However, the situation changes in the late afternoon. At night, the higher street aspect ratio and symmetry result in less outgoing net longwave radiation by reducing SVF, air cooling, and multiple radiation reflections inside the canyon, resulting in a thermal trap effect [188][196][207]. Those increase the air temperature [217][222][223], PET [205] and the UHI [198][215][223] compared to shallow and open canyons [224]. Even a small change in the canyon geometry at low shape factor values can cause heat island condensation [120]. However, the H/W impact on the UHI only gains importance for buildings higher than two stories [146] or a ratio greater than 1.3–1.5 [97][184]. The canyon smoothness and symmetry also contribute to a slight temperature increase at night [96]. The seasonal relationship correlates with solar access variability and is more pronounced in summer than in winter, depending on the different angles of sunlight incidence [207][209][210][211][225][226]. The temperature difference between the deep and shallow canyons drops significantly during the winter [207]. Due to the greater sunlight access, shallow canyons in winter have the highest daily Tmrt and are more comfortable than deep ones [227][207]. However, the increased street width does not improve thermal comfort equally in all orientations during the winter [204]. Increasing the building height and reducing the street width initially increases the minimum and average daytime and night temperatures [228]. The lower solar angle and the higher H/W ratio of the courtyard increase the reflected long-wave buildings’ radiation and reduce heat dissipation. This effect can increase with the building’s height until the H/W ratio is 5.5 [209]. Above this ratio, less and less sun reaches the canyon bottom.
The relationship between the canyon geometry and the wind environment is quite complex. It affects both the wind speed [98] and the nature of the canyon air circulation [47][135] and can cause mechanical turbulence [176]. The importance of geometry becomes apparent when one intends to use wind cooling [223]. In open canyons, the convection cooling quality is more significant than in narrow and closed canyons [98]. However, this relationship can be modulated. When the wind directions are parallel to the canyon, it is possible to increase the wind speed by increasing the H/W ratio [98][229]. In this scenario even a deeper street canyon allows weaker wind loads to penetrate to the pedestrian level [230]. Where the predominant wind directions are transverse to the canyon, great depth is not suitable for pedestrian level ventilation [208][230]. The wind speed reduction in this configuration is caused by the formation of vortices between buildings [198] and the increased air displacement above the roofs [207]. In this case, the high canyon smoothness and symmetry work unfavorably [96]. Increasing the asymmetry may be helpful [193]. The step-down canyons always have a higher temperature under high and low wind speeds than step-up canyons [231]. In addition, reducing the buildings’ heights at intersections to two floors may increase the canyons’ wind speeds. At the same time, this may reduce temperatures by 0.2 °C [201]. Care should be taken in modulating the wind environment to keep the canyon temperature down. In hot conditions of warmer climate variety, the H/W reduction can lead to canyon convection heating and warm air flowing from outside the urban unit [98][223].
The canyon geometry is not affected only by the aspect ratio itself [185]. The canyon space also has important thermal geometric features, mainly its symmetry. There can be various openings, recesses, protrusions, and the building’s facade elements, e.g., balconies or arcades [96][98]. Opinions on the effect of spacing between buildings along the street are divided. Some studies confirm their significant impact on temperature [225], others are negligible [156]. This is probably related to the prevailing wind patterns and street orientation. In studies conducted in China, wider spacing between buildings along the street resulted in poorer thermal comfort for pedestrians [216]. In studies conducted in the USA, the ground surface temperature decreased with increasing mean distances between buildings [156]. It is possible that several canyon configuration parameters may dominate the effect of spacing on the temperature. The canyon’s length does not significantly affect the thermal comfort at the level of pedestrians [47], but its elongation results in a more evenly distributed temperature during the day [232]. The effect of urban canyon width on the UHI effect may be multiplied by the simultaneous increase in the percentage of road coverage [119][135]. Wider streets also result in more significant traffic, which may intensify the UHI effect caused by increased heat and exhaust emissions in the canyon [135].

2.4.2. Street Orientation

The street orientation affects the duration and intensity of solar radiation introduced into city canyons [120][168]. Therefore, its importance in modulating the canyon temperature is mainly influenced by the radiation intensity [219]. When a day is sunny, the orientation determines the air temperature and soil temperature. The orientation effect is neglected when the day is cloudy [233][234]. That relationship also occurs with regard to the seasons [97]. Canyon orientation is a parameter that produces intra-city thermal anomalies [120][235]. It affects thermal comfort [152][174][216], including size and duration of pedestrian-level thermal peaks [205]. Moreover, it shows a strong linear correlation with the temperature of the ground surface [174], walls [213], and the intensity of AT or UHI [152]. Street orientation determines the average ground radiation intensity stronger than the average facade radiation intensity [234]. Depending on the direction of the prevailing winds, the canyon’s orientation may also increase or decrease its speed [168] and increase the humidity [48], which affects the way the temperature is percepted.
By ingerention in the shadow areas, the canyon’s area density differentiates the daily air temperature between streets oriented in different configurations [222]. The orientation influence weakens when a canyon’s built-up area density and the H/W ratio decrease [174]. In a narrow canyon, orientation is not correlated or is slightly correlated with canyon air temperature, both in summer and winter [97]. However, it contributes to lower wind speeds [180], which positively concerns PET in the winter [97]. In addition, increasing the direction variation in the narrow street may result in less radiation infiltration into the canyon, irrespective of the street main direction [207]. In a wide canyon, orientation entails significant variations in wall surface temperatures during all seasons [97].
The N–S direction provides the shortest period of solar radiation in canyons [171], and the shading percentages on horizontal surfaces vary very little over the year. Hence, shading in the streets along the N–S axis is much more favorable than on the streets along the E–W axis, both in summer and winter [226][236]. Although the mean Tmrt is similar in the N–S and E–W canyons [227], the number of Tmrt hours exceeds the threshold values for moderate and robust heat stress. Therefore, the stress may be higher in the N–S canyons than in the E–W canyons [227][97][236]. In the N–S canyon, the opposite facades are equally shaded throughout the year, but the hourly temperature distribution of these walls varies. During the day, the western wall temperature rises faster. Still, the eastern wall, which has a higher solar load, shows greater amplitudes of daily temperatures and higher maximum temperatures [213]. The daily temperature amplitude of the east and west walls can be greater than that of the canyon air [213]. This relationship is visible above the fourth floor and on the ground floor (radiation from the ground) [237]. The lowest Tmrt can be observed in the shaded areas of the east-facing walls [238]. The temperature of these walls rises until 10 a.m. and then drops [48]. The subsequent increase in Tmrt starts on the west-facing wall around 3 p.m., but there is no heat stress until 5 p.m. From 8 p.m., there is a Tmrt decrease [239]. The spatial N–S canyon air distribution and the WE and E walls become much more uniform at nighttime [213]. The best thermal comfort conditions for streets along the N–S axis are found for medium and high H/W ratio values (0.8–3.0) [226][236][240]. This way, it reduces the daily temperature amplitude and equalizes the differences in the diurnal temperature range (DTR) and maximum temperature of canyon walls [213]. For this reason, both the W and E canyon facades have more favorable conditions than the southern facades [236]. Increasing the H/W ratio significantly reduces cooling loads and increases heating loads in the canyon [241]. Increasing the spacing between buildings along the N–S street may lower Tmrt and improve pedestrians’ thermal comfort [216]. Moreover, the shortening of N–S streets contributes to arcaded streets cooling [240].
The E–W direction provides the most extended duration of direct sunlight in the canyon and courtyard [226][236], and it is considered a warmer thermal configuration [222][236]. Due to the northern exposure of the canyon wall, the E–W orientation is exposed to sunlight from early morning. The result is the earliest maximum surface temperature [208]. Depending on the season, high Tmrt only occurs for few hours, from 11 a.m. until approximately 3–5 p.m. [239], when it reaches its highest level. After this time, due to the solar radiation blocking, the absorbed heat is relatively quickly released into the surrounding environment [48][239]. However, it increases AT [208][226]; hence, thermal stress may be felt almost until 8 p.m. [239]. The increased H/W ratio for the E–W streets has no significant effect on the shading percentages [222][236]; therefore, it does not lower PET levels [219] and has little effect on daytime air temperatures [222]. On the E–W axis, the low H/W ratios (0.6–3.0) can therefore represent PET outside the comfort zone for most of the day [219]. With the H/W ratio above 3.0, it is possible to achieve a satisfactory daily thermal comfort level on the E–W streets [227][219]. A low H/W ratio (<0.6) is the most favorable in terms of solar gain in summer and winter for southern facades. As a result of short-wave and long-wave reflections, radiation emitted from the south-facing canyon walls can have an exceptionally high Tmrt [238], especially on low floors [208]. The Tmrt difference between the north and south walls can be 20 °C [227]. Increasing the H/W ratio on E–W streets reduces cooling loads and significantly increases heating loads [236][241]. Increasing the spacing between buildings along the E–W-oriented street increases cooling loads [241], and narrowing the spacing reduces Tmrt and improves PET [216]. Increasing the canyon’s length in the E–W direction extends the duration of solar radiation. It increases the street temperature [201][242], but in the case of arcaded streets, it improves their cooling [240].
The shading intensity of diagonal streets is similar in all their rotation configurations. It is between the N–S and E–W axis streets’ shading intensity [236]. SE–NW street canyons provide more shade, higher wind speed [216], and better pedestrian thermal comfort conditions than other scenarios [216]. The H/W ratio impact on the number of sunlight hours suddenly decreases for street orientation angles of less than 30°. In comparison, when the street orientation angle exceeds 60°, the H/W ratio impact increases rapidly. The H/W ratio increase in the NW–SE canyons considerably reduces their daily temperature amplitude [222]. Diagonal streets with a H/W ratio between 1.5 and 3.0 can provide satisfactory thermal comfort conditions for most of the day [242], similar to streets on the N–S axis [219][236]. For H/W ratios higher than 1.3, diagonal canyons are similar to the E–W axis streets in terms of solar access to building facades in winter [236]. A closer look at the facade’s thermal dependencies in diagonal configurations shows that the maximum temperatures for the NE facade appear in the early morning. They are lower than the SW facades, where the maximum temperatures appear around noon. The NE facade minimum temperatures in the late afternoon are higher than SW facades, where the minimum temperature is measured in the early morning [162]. The SSW facade has higher maximum temperatures than the NNE elements. The most significant differences observed between these directions are visible in the afternoon and the lowest in the early morning [237].

2.4.3. Canopy Properties

The trees and free-standing building elements’ presence in the canyon modifies its shadow patterns. During the day, this directly leads to a reduction in LST and PET [188][205]. At night, it increases its temperature by obstructing the long-wave radiation exit from the canyon [173][243]. This type additionally intensively reduces the wind speed at the pedestrian level [214][243]. The temperature level changes in street canyons associated with the trees’ presence depend on the tree crown-cover size [244][245], their planting density [193], their height [100], and solar exposure [220]. Small greenery elements in the canyon will only affect the local thermal conditions [242]. Due to more effective radiation shading and more substantial turbulent transport, tall trees have a more beneficial effect on the canyon temperature than small trees [100].
The city canyons’ geometry significantly modifies the trees’ thermal behavior in alleviating the street microclimate [243][244]. Due to changes in sun exposure, canyon shallowing and widening increase the trees’ cooling effect in the canyon. [216][244]. Research shows that high-tree-coverage streets can achieve better cooling quality when the H/W aspect ratio exceeds 0.67 [240]. For H/W aspect ratio = 1.0, increasing tree cover or reducing the spacing between trees may result in better tree shading and cooling during the day and a night temperature increase [242]. For H/W aspect ratio = 1.2 small and low-crown trees can generate a lower wind speed at the pedestrian level [243]. When the H/W aspect ratio = 2.0, both small-crowned and large-crowned trees may have the most significant air temperature cooling ability in daytime [225][243] and heating ability at night in the canyon [243]. When the H/W aspect ratio ≥ 3.0, the shadow cast by building walls can dominate the trees’ shading. Their influence on temperature reduction becomes less critical [243]. Dredging a canyon without increasing the number of trees reduces the cooling effect because the evapotranspiration cooling energy has to handle a larger air volume [174][220]. Adding trees in this situation could lower the temperature by as much as 4.5 °C on a summer afternoon [220][225]. For the high H/W aspect ratio, the diffusive planting of small-crowned trees favors street ventilation. It is a more preferable solution for summer cooling in these canyons than the higher density of trees and large-crowned trees [243]. This relationship is inversely proportional to the low H/W aspect ratio [100]. A large-canyon tree area in the canyon with a high H/W aspect ratio may adversely affect the tall building thermal load. Street albedo, enhanced by the color of tree leaves, can multiply the radiation reflections reaching the upper reaches of the canyon [188].

2.5. Design Parameters of Neighborhood Cluster Scale

As the scale increases, the relationship complexity between the elements that make up urban areas increases. At this hierarchy level, the high synergy that characterizes the ecosystem is noticeable. Allelopathic compounds, both antagonistic and non-antagonistic, can be found here. Understanding the urban unit as an interconnected network of abiotic and biotic objects allows researchers to grasp how the areas of coverage, density, and spatial configuration affect its temperatures.

2.5.1. Coverage Area

Covering with elements of the urbanized environment is one of the indicators of the intensity of development, showing a close relationship with the surface temperatures [246][247]. Impermeable surfaces in the neighborhood unit represented by buildings and roads have constant high LST and UHI [126][137], and modulation of the coverage parameter strongly influences their variability [248][249][250][251]. The increase of paved surface coverage leads to LST and UHI increases [252]. Increasing the built-up area coverage by 1% may cause a rise of the UHI effect intensity up to 1.7% [135]. On the other hand, a 1% reduction may cause a decrease in the night-time near-surface air temperature by 0.1 °C [249]. Urbanization degree is proportional to the distance from the city center [153] and size-dependent urban area [137]. It is also inversely proportional to the greenery area [250][253]. Therefore, it seems logical that old cities are usually characterized by the highest concentration of impervious surfaces [101]. Large-scale architecture and infrastructure and a high percentage of commercial and industrial areas [190][135] have a high UHI correlation. It is worth mentioning that the modernistic districts from the 1950s–1960s are better in terms of the number of porous surfaces than the currently built districts and those from earlier centuries [179]. This is related to the Athens Charter implementation.
The building cover ratio in a given area significantly impacts the intensity of AT, LST, UHI, and PET [107][254]. As it increases, the degree of pedestrian-level ventilation decreases [255], and the LST and UHI intensity increase [256]. In China, with a 10% increase in building land cover within a 500 m radius, a daily Tmax increase of approximately 3.4 °C was noted [152]. The correlation of building cover with temperature can be positive and negative [256] and may similarly affect the nighttime and daytime UHI [145][170]. These relations are distinguished by the type of land cover, building materials’ thermal properties, and exposure of the urbanized environment to solar radiation [126]. Increasing the building cover degree may reduce the maximum Tmrt during the daytime by reducing the canyon’s solar exposure [257]. A stronger positive correlation between building cover and temperature is noticed at night. That correlation results from the heat release after dusk from the housing estate thermal mass [251][258] and the anthropogenic heat trapped in the canyons [108]. The time at which the highest correlation is achieved depends on the temperature level on a given day and occurs later in the nights after hot days compared to the nights after cool days [183]. The influence of land cover on air temperature strongly correlates with built-up area density [94]. In a dense context, the percentage of built-up coverage has a greater impact on the increase in UHI than its density itself [201]. In this context, reducing buildings’ land cover would increase solar exposure for buildings and paved surfaces and thus affects the radiation and temperature increase [259]. However, paradoxically reducing the temperature in densely built-up areas is possible with a building cover increase [156]. There is, however, a limitation. The adjustable LST range decreases when the built-up area exceeds a certain critical threshold. This means the ability to mitigate high temperatures by adjusting the built-up area is also limited [147]. This ability is evidenced by the fact that, in some specific cases, increasing the land cover index in high-density regions may increase the temperature and UHI [94]. A possible reason for this is the reduced convection cooling at the pedestrian level [255]. In such a situation, it is necessary to reduce the coverage density to mitigate the UHI [94]. These dependencies may explain the lack of correlation between the building cover percentage and the UHI intensity in some studies [202].
The road coverage degree strongly correlates with the AT, UHI, and PET intensity [152]. Its increase within the city leads to a rise in LST [147][182] and enhances the UHI effect [151]. Due to the increased thermal mass, the duration of high air temperature is also extended [212], making the city’s microclimatic conditions more stable throughout the day. Unfortunately, this also contributes to the formation of the nighttime UHI. An increase in the road surface ratio causes a temperature increase [170]. That is especially true when the roads are highly congested—this increases the anthropogenic heat in the area [150].
Green area coverage is a significant predictor of elevated temperature for the neighboring unit scale [206], explaining up to 50% of the variability of intra-city temperatures [152]. There is a strong negative linear correlation between greenery coverage and the intensity of AT, UHI, PET [260][261][262], LST [218], and buildings’ peak cooling loads [199]. There is also a positive correlation with soil permeability, urban spaces water capacity, ground surface shade percentage, and wind speed [133]. The surfaces may have a similar daily effect on the UHI [126], significantly reducing the peak air temperature and the UHI during the day [261][263] and at night [264]. In a study conducted in China, a 10% increase in green area coverage decreased the mean UHI by approximately 0.94 °C in a 250 m radius [152]. Green area coverage shows a positive relationship with the SVF. Increasing the exposure of green areas to direct solar compensation results in better plant conditions and greater efficiency of evaporative cooling. Due to the above, these cover types cool the space exceptionally well in summer and in warmer climate types [151].
The water object coverage percentage shows a strong negative linear correlation with the LST, AT, UHI, and PET intensity [152]. The cooling effect of water reservoirs also depends on their size, location, and wind direction [103]. For example, after reducing the lake’s surface in the built-up area of Wuhan by 130 km2, the UHI intensity increased by 0.2 °C–0.4 °C [265].

2.5.2. Elements’ Density

The density of the urbanized area is an urban geometry parameter that significantly affects the minimum temperature, LST, and UHI intensity [183]. This parameter is the most complex, as increasing the built-up area’s density may have a negative [156] or a positive impact on the LST and UHI [143][144][145]—depending on the climate type. Its importance is greater [163] in warmer regions than in cooler areas [156]. The urbanized area’s density is a hybrid parameter that describes the mutual synergistic relationship of other parameters, such as population density, anthropogenic heat, the vegetation ratio, building and road coverage, building height, and spatial configuration [149][120]. There is also a group of parameters such as the floor area ratio (FAR) related to density but primarily determining the building development volume. They significantly impact the thermal building mass and the shade patterns [120]. These parameters also negatively correlate with the LST and AT [266]. The influence of these aspects makes it challenging to infer one universal relation. The collective effect of all the elements influencing the density is the final density effect on the city temperatures [120][262].
The buildings and roads coverage density are mainly responsible for the density of land development. The influence of the building cover density on the ambient temperature rises with the increase of the built-up space radius [251]. The density is negatively correlated with the distance from the urban center [153]. The built-up area density parameter significantly influences the solar exposure of the housing estate [187]. As the built-up area density increases, the average SVF decreases [267]. A similar relationship occurs for the building’s volume [95], but it has a more substantial effect in already densely built-up areas [185]. The influence of these parameters on the air temperature is significant, but its distribution shows diurnal differences [261]. An increase in the buildings’ cover density and their volume can reduce the AT [187][263], the surface temperature of the lower canyon parts [117][268], and the heat stress at the pedestrian and UHI levels during the sunny hours of the day [148][263]. Those are easy to see in the example of squares. Their temperature can be even 18 °C higher than that of dense built-up areas [259]. During a cloudy day, densely built-up areas remain warmer, but the difference in Tmrt between dense and scarce contexts decreases because of the reduced radiation intensity [259]. The increase of built-up areas’ volume and density can reduce the wind speed and the convective heat transfer. That increases the thermal mass, thus having a more substantial impact on the radial energy absorption and lower SVF leading to the thermal trap effect [180][187]. That leads to the growth of wall, street, and air temperatures in canyons and causes the nighttime UHI [198][187]. These dependencies are appropriate for warm seasons. In colder seasons, a temperature rise associated with high built-up areas’ density may be desirable to provide better thermal comfort [227][186]. The density is related to the anthropogenic heat emission [120]. A higher proportion of building walls means more anthropogenic heat and significantly influences the LST and UHI [135][145]. Depending on the season and context, it may positively or negatively affect thermal comfort and the environment. The increase in the built-up areas’ density reduces the annual energy demand [197][269] but makes the heating load more sensitive to solar radiation [183][266]. Moreover, intensified anthropogenic heat emitted from buildings may modify the thermal response of other city geometry parameters [270].
There is a particular paradox for the built-up areas’ density parameter—the total area of roofs, facades, and streets changes with an increase or a decrease of those areas [191][268]. That means one can increase the surface temperature by increasing or decreasing the building density. By increasing the density, researchers increase the fractional area of the roofs. As roofs get hotter more easily than streets, the UHI increases as the fractional roof cover increases [191]. On the other hand, researchers increase the sun exposure of road surfaces by reducing the density. Since roads are associated with a low albedo, they strongly influence UHI [117][192]. The solution to this situation is to manipulate the density by changing the height. In this way, it is possible to increase the shadow area without changing the fractional roof cover [191] and reduce the surface temperature as a result [192]. At a constant high density, the spatial configuration of blocks has a dominant effect on surface temperatures [144]. The increase in density for interlaced and linear block systems reduces the daily UHI [115], and the simultaneous increase in height and building density increases the frontal area index (FAI) [186][255] and night UHI effect [104]. This relationship can be seen in Hong Kong, where a 10% density and height reduction resulted in a 10% UHI reduction [262]. This shows how the density and configuration of construction objects on the estate are strongly correlated.
The road surface density depends on the urbanization degree of the area [253]. The LST and UHI are positively correlated with the coverage density of roads, parking lots, and sidewalks [271][272]. This is directly influenced by the thermophysical properties of the materials used for the construction [135]. However, the road connections density alone is insufficient to understand the relationship between city texture and the UHI effect. Other factors, such as road connection size and capacity, are also important determinants of the UHI effect intensity [135]. The areas closer to the functional city center are characterized by more significant node and communication link density, making these areas warmer than the rest [151][155]. The UHI effect is negatively affected by a higher transit route density. The reason may be trivial—faster vehicle traffic and the absence of congestion reduce the amount of heat, pollutants, and greenhouse gases discharged into the canyon [135]. Scattered and anisometric settlements are associated with more traffic, affecting higher emissions [248][273]. Therefore, increasing the built-up areas’ density can help deal with anthropogenic heat emission problems [135].
The vegetation density is determined by its height, cover type, and greenery amount. It depends on the growing season during a year, too. In addition to shade patterns, the density of the vegetation models the airflow [180][274]. Increasing the greenery density within a green area reduces not only the daily LST [136][137] but also the wind speed [180][274] and the convective cooling effect. Increasing the vegetation patch density reduces temperature [156][252], especially at night [115][228]. Increasing the edge density of these patches reduces the ambient LST by having a larger heatsink contact area with the paved area and increased energy flow between them [156]. The vegetation cover density is negatively correlated with the built-up areas’ density [120][145]. The more dense built-up area ensures greater efficiency of green roofs and green facades [148]. An increase in built-up area density increases green infrastructure’s impact on the LST changes [144]. However, after exceeding a certain density threshold, other variables related to the housing estate spatial configuration, e.g., the heights of buildings, begin to significantly impact the lowering of temperature by vegetation [270].

2.5.3. Spatial Pattern

The 2D and 3D composition of the housing estate, which consists of the mutual spatial relationship and the configuration of green areas, water objects, streets, and blocks of flats, is significantly related to the LST and UHI [168][174].
The spatial distribution of the impervious surface within the estate, significantly when fragmented and insulated, can increase the LST [186]. On the other hand, increasing hardened surfaces with complex shapes sometimes cools the study area because of a more extensive contact between built-up areas and vegetation [156]. However, the relationship emergence condition is the presence of green spaces in the vicinity. The permeable surface system of green areas may play an essential role during intense solar radiation [54]. A compact green-space layout is generally accompanied by more significant amounts of permeable land [179]. An evenly distributed complex shape pattern of trees and its high dispersion can provide more shade and enhance energy exchange between green spaces and built-up areas while reducing the LST [156][179]. Moreover, low plants’ scattered distribution and irregular shapes can help mitigate the UHI effect [190]. In the case of water objects located within the estate, their cooling effect depends on their location in the urbanized area and wind directions [103].
The layout of buildings may be the most influential factor in changing the thermal environment during the day [54]. Different urban designs affect the insolation and ventilation patterns of the housing estate diversely [275] and thus determine their thermal efficiency during the day and at night. Clustered blocks of flats raise the AT and LST [212][190] because of the higher roof surface density and a lower greenery percentage. Therefore, the dispersed distribution of buildings facilitates the LST reduction [190], allowing the introduction of other mitigation features into the estate. It has been proven that the surface temperature and thermal comfort outside free-standing blocks of flats are slightly influenced by street orientation and H/W. The vegetation has a stronger influence [174]. Thus, in the absence of sufficient greenery, a higher open-space factor increases the UHI effect [206][272] and Tmrt because of increased direct sunlight exposure [238]. Regular block of flats patterns may facilitate air circulation in the canyon [135]. Higher irregularity in the layout of buildings, and the complexity of their shapes and diversity, affects wind patterns and also increases LST and UHI levels through higher solar exposure [156][259].
The dense linear apartment block systems that make up the city canyon have the highest UHI level [276] because they provide a long solar radiation duration for the estate [131][169] in the case of incorrect spatial orientation. By controlling the direction of the linear form, it is possible to influence both passive cooling and heating of the blocks of flats [131]. This way, the apartment block orientation as a whole has a significant impact on energy consumption, especially for high linear systems [269]. The windward buildings are blocking the airflow [229]. Therefore, adjusting the building blocks’ layout and orientation concerning the prevailing wind directions is essential. Proper arrangement of buildings can positively affect urban porosity, create wind corridors, strengthen the narrowing effect in the ventilation corridor, and increase wind speed [229][255] and thus can shorten the duration of high air temperatures in the area [141]. On the other hand, inappropriate building arrangements and orientation, increased building density, asymmetry, and the number of alleys may block the airflow, resulting in increased temperature at night [96][229]. For example, suppose the binary system is perpendicular to the wind directions. In that case, its ventilation and thermal comfort in summer can be improved by increasing the space between buildings along the road and creating small green areas [204][255]. However, this treatment will lower thermal comfort in winter [204]. An example of traditional Greek city development shows how to eliminate this problem by using small linear blocks of flats and a complicated street pattern [97].
Although building arrangements may negatively affect air circulation, they provide more shade [229]. Therefore, the closed layout of the apartment blocks is characterized by a more comfortable thermal environment during the day [229][269], provided that the H/W ratio is high. However, the low SVF associated with this system may result in poor radiant cooling capacity and thus increase the nighttime temperature [264][265]. The low H/W ratio of the closed apartment blocks layout increases its LST [264]. Nevertheless, the natural compactness of the apartment blocks with a peripheral configuration makes these systems more suitable in an urban environment than linear systems [115].
The average building height significantly affects the ambient temperature [122][163] and wind patterns [169][187]. It also determines the shading value in densely populated urban areas [255][259][267]. Therefore, greater building heights indicate a lower AT and a better outdoor comfort level [268][261]. Building height can influence cooling efficiency through its relationship to the UHI formation and propagation. Up to a certain height, the building’s height strongly influences the evapotranspiration cooling and the shade provision by the vegetation in the estate [143]. When buildings are lower than trees, the buildings do not obstruct the cool horizontal airflow and do not reduce the cooling capacity [117][230]. As the buildings’ heights increase, the average wind speed above buildings increases [217]. However, it harms the ventilation at the pedestrian level [230] and increases the internal heat gain by thermal trapping [104]—especially in public and residential areas [190]. The buildings’ heights increase the urban unit’s FAI, thus blocking the natural wind corridors [131]. Due to all these unfavorable relationships in the case of high buildings, the influence of ventilation significance on city air temperatures rises [44]. It is worth introducing a gradual lowering of buildings in the direction of prevailing winds to reduce the FAI [131]. It is also possible to modulate the urban roughness, determined by the differences in the buildings’ heights. This affects both the shadow distribution and the wind speed and direction in urban areas [141]. Hence, it may also impact the UHI effect [191][163]. Identical building heights lead to a stronger vertical turbulent movement favorable for pedestrian-level ventilation [230] and increase the albedo [268]. However, an increase in the difference in building height increases the shadow area and the aerodynamic roughness. That affects convective district cooling positively, especially at night [191]. It should be remembered that high surface roughness values make it challenging for adequate wind ventilation [141] through the vortices generated. It can be concluded that the benefits of this parameter modulation in an urban environment can be obtained by carefully mixing the building heights [115][131].
For the elongated apartment blocks’ shapes and increased H/W ratios, block orientation becomes a vital parameter influencing temperature rise and energy consumption [184][213][269]. Buildings facing south have the highest daytime temperatures for the northern hemisphere because of insolation [229]. Although these are suitable conditions for a low-energy urban form, this solution’s balance of losses and profits loses to other savings forms [269].

3. Conclusions and Recommendations for Future Research

3.1. Guidelines for Microclimatic City Design

The complete elimination of the UHI effect seems impossible in the current urbanization form. However, it is possible to improve the thermal city environment. Following some universal guidelines to improve the existing urban tissue and create the new one makes it possible to influence the entire city PET and UHI effect significantly. Only holistically planned preventive measures and interventions can make the city climate-neutral and make it resistant to the rapidly approaching climate change.
The guidelines based on the discussion chapter show a strong shifting vector of changing the current urban environment toward de-urbanization. This rather old concept returns in the climate change context of the 21st century and sheds a new “green light” on the city’s appearance in the future. As in the de-urbanization concept, the microclimatic design reduces and distributes rationally the built-up areas’ coverage and the density and height of the buildings, concerning the natural landscape and well-known weather patterns. The main principle of this design trend is to adjust the solar intensity as the leading energy carrier to the needs of the specific temperate climate type. In warmer varieties, less radiation will be needed to provide the same conditions as in colder regions. When planning the radiation balance in the urban areas, one cannot forget the vegetation duration appropriate for each space. It is necessary to consider both in situ and ex situ factors in microclimatic design because the city’s energy flow remains open [116]. The designers should not rely on wind cooling a city with a poor wind environment and avoid creating large and compact urbanized areas [273]. They should also intertwine building areas with forests and lakes, develop urbanized areas toward greenery, and create decentralized systems with highly amorphous, organic shapes. Inside the designed cities, they should diversify the environment, improve the distribution of buildings, roads, and BGI elements [133][137], reduce the amount of industrial and commercial areas, limit road transport (by planning ring roads and smart transport links), and promote a zero-emission life [90].

3.1.1. Material

When creating, introducing, or modifying city materials, one should pay particular attention to some of their properties. It is recommended to use materials with increased diffusivity, transmission, and a reduced speed of radiation absorption [165]. It is necessary to increase pavement permeability and the materials’ porosity [172]. Permeability can be increased by using various types of vegetation surfaces. Cities’ poor ventilation requires the extension of road material porosity [147]. When night ventilation is provided at a high level, materials with a high heat capacity, such as grass, stabilized sand, and granite, can be used [159]. In any other case, it is recommended to reduce the heat capacity and thermal mass using, for example, reclaimed asphalt pavement (RAP) materials [172] or limiting the thickness of the foundation layers [165]. The use of asphalt and concrete as a surface is strongly discouraged [159]. Thermal insulation of building partitions should be increased, especially in colder climate zones.
The urban areas’ albedo should be varied [154]. Retroreflective materials can be safely used on all hard surfaces and contexts [277][278][279]. The guidelines for high albedo materials are dependent on the area density. In the densely built-up areas, the albedo should not be increased. In this situation, attention should also be paid to the leaf’s albedo. It is safe to use high albedo materials only on the highest roofs. Increasing the albedo on each surface for low H/W ratio values is desirable. When increasing the albedo, the PCM and RR coatings, white paints and membranes, bituminous surfaces modified with oxides, colored roof tiles [280], and resin surfaces with exposed light-colored aggregate can be used [164]. It is necessary to ensure high color durability. Resin surfaces have significant limitations in use. It is recommended to use them as pavement surfaces for pedestrian use [178].

3.1.2. Building

In the case of buildings’ geometries, it is necessary to reduce both their floor and wall areas. This is essential for commercial and residential buildings. Facilities must take on a compact, regular, and simple form [185]. The best solution would be to use spherical, domed shapes [281]. In addition, the buildings’ heights should not be significant. It is suggested their heights should be in the range of 20–50 m [217] and much lower for buildings located near main roads [251]. The best solution is to place buildings on high pillars [255].
Increasing the buildings’ energy efficiency and reducing their thermal emissions is necessary [163][195]. For this purpose, one can use location-related, orientation, greenery, building covering materials, and cooling or heating solutions. One should also avoid using the A/C. If this is not possible, it is recommended to use A/C and heating in energy-saving mode and timers [100]. Instead, it is possible to use ground heat exchangers and water cooling [142]. It is also worth using other low-energy solutions. For example, RR materials are desirable to limit A/C usage [282]. A similar task is fulfilled by increasing the building albedo [163][199] and applying better insulation [163]. Green roofs effectively reduce cooling and heating loads [106][143]. In addition, buildings should be reasonably located in relation to chiaroscuro and wind corridors, depending on the desired effect.

3.1.3. Street Canyon

Proportions, orientation, and greenery patterns should be selected appropriately [174][221]. The designer’s primary goal should be to obtain a low solar exposure of the canyon [283], but the optimal value for a given climatic zone should be considered [207][234].
The most crucial guideline for canyon geometry is to reduce its height while increasing the tree crown cover [234][284]. In hotter types of climate where tree shade cannot be introduced, canyon height can be increased [209]. Limiting the canyons’ heights is especially important in the case of canyons that are transverse to the main winds. In this case, it is worth increasing a building’s height slightly on the leeward side and increasing the spacing between the buildings along the road. The depth of the street canyon oriented parallel to the airflow may be higher, but it is worth increasing their horizontal asymmetry and smoothness. Nevertheless, it is worth reducing the heights of buildings in the vicinity of intersections. Reducing the road surface area or increasing shading solutions is another critical issue. The answer is to use traffic circles, reducing traffic congestion and the anthropogenic heat increase.
There is no single preferred city canyon orientation. The desired direction varies with the climate zone and the need for sunlight or shade [120]. The best general solution seems to be the use of irregular road runs, in which the orientation changes from time to time, creating a balanced thermal environment. In addition, it is worth using diagonal streets [216][285]. In warmer temperate climates, the orientation of the roads along the N–S axis is suggested as the most appropriate [204][238]. In this situation, it is worth ensuring a considerable height of the canyon [219][285]. One can also reasonably increase the streets’ width to provide better comfort of their use [283]. It is also good to extend the road length unless it is an arcaded street. Streets oriented on the E–W axis are suggested as optimal for colder regions [242]. They may also be optimal in warmer climate zones, but only if the canyon is deep [240][285]. In that case, the canyon’s length should be shortened [201], and the spaces between buildings along the street should be increased.
Shaders (artificial or natural) in canyon space are generally considered a good solution [214][222]. A tree crown cover is preferable to artificial shaders for many ecological and microclimatical reasons [101]. The trees should be as tall as possible to create a lot of shade and ultimately cover most of the street. However, their use legitimacy should be considered, and the optimal tree species should be selected for the given canyon openness and orientation [238][244]. It is necessary to introduce trees into vast canyons [202][240]. In wide canyons, dense canopy cover and compact artificial shaders should be used. It is not recommended to introduce many trees into high canyons, and their canopy cover should be sparse [100][243]. Shading with greenery, arcades, or artificial shaders should be used to avoid the E–W-oriented streets overheating [210][240].

3.1.4. Neighborhood

During the construction of new neighborhood units, it is recommended to generally reduce the intensity of urban development [256] and manipulate the parameters of the spatial configuration to create the most diverse landscape. In this way, certain areas will lower daytime temperatures, and others will reduce nighttime temperatures, and the whole will ensure correct cross-ventilation [116]. It might seem the best development strategy for an urbanized area for its microclimate is the foundation of skyscrapers surrounded by greenery [286]. However, the efficient creation of an optimal thermal environment is also possible in other already existing conditions.
The main goal of microclimatic design on the city scale is to reduce the urban surfaces cover (impermeable) in favor of natural ones (pervious surfaces). The buildings and roads should be reduced, thus increasing the fraction of the green spaces and water object areas [252][258]. That is especially important in the context of very intensively built-up areas [201][286]. It is sometimes enough to decanalize rivers hidden underground during intense urbanization to increase the number of water objects.
Reducing the road and built-up area densities and volumes to increase the BGI coverage density is generally required to improve the urban climate [258][287]. The legitimacy of modulating the built-up area density depends on the climate type and the possibility of introducing tall greenery. For this reason, in warmer temperate climate zones, it will be justified to increase the built-up area density to ensure better thermal comfort in the urbanized area [207]. The transit road density may be increased, but only when accompanied by shading trees. It is not recommended to excessively increase the tree-planting density in green areas; instead, tree species with the desired parameters should be selected appropriately for the available space [179].
One should reasonably manipulate the area density by distributing the buildings horizontally and vertically [234]. A desirable solution is to lower the buildings’ heights and carefully differentiate the buildings’ sizes in apartment block areas [131][234], especially those with high building density [94][141]. In that case, the climate variation must be considered. In warmer regions, it will be preferable to increase the buildings’ heights to increase density [190] and decrease the heights of south-facing apartment blocks. Moreover, to maintain the same built-up areas density, it is possible to reduce the coverage area with low buildings in favor of tall buildings [137]. An essential aspect of creating a housing estate microclimate is to ensure even wind access throughout its area [141]. For this purpose, tall buildings must not be located on the neighborhood units’ outskirts from the prevailing wind’s side [131]. The same principle applies to tall buildings near water objects and green areas. The buildings’ heights may increase with the distance from the boundary and cooling objects. Nevertheless, it is worth adjusting the heights of the tallest buildings so that the roofs are under the tree crowns. The designers should modulate the buildings’ sizes to allow the wind and humid airflow to penetrate the housing estate’s interior [251]. They should plan uniform and compact green areas that are spatially interconnected [179]. In high-density built-up areas, one should create irregular green areas and fill any free space with them [147]. Green roofs and facades are recommended [107]. Even distribution of the tree crowns in the housing estate area should cover as much area as possible [54][251]. Water objects should be located from the windward side. It is crucial to not canalize streams and rivers on a given site [251].
The relationships of the shape, length of apartment blocks, and spaces between buildings should be rationally planned, considering the creation of insolation areas and wind corridors [229]. The best buildings’ covering pattern is dispersed distribution in the neighborhood greenery [54][147]. This principle also applies to the housing estate layout design [251], especially if the surroundings are excessively dense built-up areas [212]. It may also be helpful to use a variable apartment building configuration [212]. One should avoid building an estate as a closed structure of excessive depth [54]. Instead, it is better to use average building heights, which let the sunlight reach the bottom of the courtyard. Furthermore, designers should orient regular patterns relatively parallel to the prevailing wind directions while controlling the rotation relative to the optimal solar exhibition. Finally, free spaces between buildings appropriately oriented to the wind corridors are recommended.

3.2. Vision of Climate-Resilient and Climate-Neutral Cities

The urbanization principles need to be changed to eliminate the UHI effect and thus ensure optimal PET comfort in the city. In addition, the microclimatic approach to housing estate design may affect the scale of the changes. Still, the vision of a future temperature increase in a temperate climate zone requires researchers and designers to brainstorm and create ideas for preventing a simulated crisis.
According to the ecosystem pulse theory, each civilization’s violent disintegration is associated with an excessive complexity increase [288]. Research clearly shows that urban development and uncontrolled spatial configuration exacerbate the temperature difference between urban and non-urbanized areas. Vegetation is essential to achieving ecosystem climax, and progressive surface reduction leads to climate anomalies and crisis deepening.
In the contemporary understanding of urban planning, solar exposure is the most critical factor influencing the overheating of urbanized areas. Of course, there are more reasons. Still, using already known smaller-scale solutions, solar exposure can be transformed into something desirable together with the underground placement of the building. With this change of approach, the problem becomes the solution. Earthship-type buildings show that construction can be energy-saving and reduce emissions to virtually zero. In that case, the large thermal mass of buildings also becomes an advantage, and its internal microclimate is easier to control because of the constant lower temperatures prevailing underground [289]. Despite the modern name, life underground does not bear the hallmarks of modern times. Since prehistory, people worldwide have lived in earthworks [290][291] and archaeological research shows that even entire cities can be created this way [292].
The vision of the underground city seems abstract, but only in this way is it possible to ensure a parallel, undisturbed existence of nature and architecture. Building cities underground does not seem to be technically impossible, and that concept appears from time to time in urban planning and architecture [293]. The earthscraper is a skyscraper, only upside-down—instead of rising, the earthscraper is built deep into the ground. Building heating requirements will force designers working in the field of temperate climate area to change the apartment blocks’ spatial patterns, taking inspiration from warmer climates [169][294]. Creating neighborhoods covered with the earthscrapers and Earthship-type buildings surrounded by greenery, water features, and underground public transport can effectively solve the upcoming climate challenge.

References

  1. Gonzalez-Trevizo, M.E.; Martinez-Torres, K.E.; Armendariz-Lopez, J.F.; Santamouris, M.; Bojorquez-Morales, G.; Luna-Leon, A. Research Trends on Environmental, Energy and Vulnerability Impacts of Urban Heat Islands: An Overview. Energy Build. 2021, 246, 111051.
  2. Martin, P.; Baudouin, Y.; Gachon, P. An Alternative Method to Characterize the Surface Urban Heat Island. Int. J. Biometeorol. 2015, 59, 849–861.
  3. Lontorfos, V.; Efthymiou, C.; Santamouris, M. On the Time Varying Mitigation Performance of Reflective Geoengineering Technologies in Cities. Renew. Energy 2018, 115, 926–930.
  4. Oke, T.R.; Johnson, G.T.; Steyn, D.G.; Watson, I.D. Simulation of Surface Urban Heat Islands under ‘Ideal’ Conditions at Night Part 2: Diagnosis of Causation. Bound. Layer Meteorol. 1991, 56, 339–358.
  5. Parsaee, M.; Joybari, M.M.; Mirzaei, P.A.; Haghighat, F. Urban Heat Island, Urban Climate Maps and Urban Development Policies and Action Plans. Environ. Technol. Innov. 2019, 14, 100341.
  6. Sachindra, D.A.; Ng, A.W.M.; Muthukumaran, S.; Perera, B.J.C. Impact of Climate Change on Urban Heat Island Effect and Extreme Temperatures: A Case-Study. Q. J. R. Meteorol. Soc. 2016, 142, 172–186.
  7. Sharifi, E.; Sivam, A.; Boland, J. Resilience to Heat in Public Space: A Case Study of Adelaide, South Australia. J. Environ. Plan. Manag. 2016, 59, 1833–1854.
  8. Zhao, L.; Lee, X.; Smith, R.B.; Oleson, K. Strong Contributions of Local Background Climate to Urban Heat Islands. Nature 2014, 511, 216–219.
  9. Oke, T.R. The Energetic Basis of the Urban Heat Island. Q. J. R. Meteorol. Soc. 1982, 108, 1–24.
  10. Oke, T.R.; Maxwell, G.B. Urban Heat Island Dynamics in Montreal and Vancouver. Atmos. Environ. 1975, 9, 191–200.
  11. Easterling, D.; Horton, B.; Jones, P.; Peterson, T.; Karl, T.R.; Parker, D.; Salinger, M.; Razuvayev, V.; Plummer, N.; Jamason, P.; et al. Maximum and Minimum Temperature Trends for the Globe. Science 1997, 277, 364–367.
  12. Karl, T.R.; Jones, P.D.; Knight, R.W.; Kukla, G.; Plummer, N.; Razuvayev, V.; Gallo, K.P.; Lindseay, J.; Charlson, R.J.; Peterson, T.C. A New Perspective on Recent Global Warming: Asymmetric Trends of Daily Maximum and Minimum Temperature. Bull. Am. Meteorol. Soc. 1993, 74, 1007–1024.
  13. Kwak, Y.; Park, C.; Deal, B. Discerning the Success of Sustainable Planning: A Comparative Analysis of Urban Heat Island Dynamics in Korean New Towns. Sustain. Cities Soc. 2020, 61, 102341.
  14. Grimmond, C.S.B.; Oke, T.R. An Evapotranspiration-Interception Model for Urban Areas. Water Resour. Res. 1991, 27, 1739–1755.
  15. Taha, H. Urban Climates and Heat Islands: Albedo, Evapotranspiration, and Anthropogenic Heat. Energy Build. 1997, 25, 99–103.
  16. Mitchell, V.G.; Mein, R.G.; McMahon, T.A. Modelling the Urban Water Cycle. Environ. Model. Softw. 2001, 16, 615–629.
  17. Peron, F.; Maria, M.M.D.; Spinazzè, F.; Mazzali, U. An Analysis of the Urban Heat Island of Venice Mainland. Sustain. Cities Soc. 2015, 19, 300–309.
  18. Kolokotroni, M.; Ren, X.; Davies, M.; Mavrogianni, A. London’s Urban Heat Island: Impact on Current and Future Energy Consumption in Office Buildings. Energy Build. 2012, 47, 302–311.
  19. Santamouris, M. Cooling the Buildings—Past, Present and Future. Energy Build. 2016, 128, 617–638.
  20. Salazar, A.; Baldi, G.; Hirota, M.; Syktus, J.; McAlpine, C. Land Use and Land Cover Change Impacts on the Regional Climate of Non-Amazonian South America: A Review. Glob. Planet. Change 2015, 128, 103–119.
  21. Shiflett, S.A.; Liang, L.L.; Crum, S.M.; Feyisa, G.L.; Wang, J.; Jenerette, G.D. Variation in the Urban Vegetation, Surface Temperature, Air Temperature Nexus. Sci. Total Environ. 2017, 579, 495–505.
  22. Norton, B.A.; Coutts, A.M.; Livesley, S.J.; Harris, R.J.; Hunter, A.M.; Williams, N.S.G. Planning for Cooler Cities: A Framework to Prioritise Green Infrastructure to Mitigate High Temperatures in Urban Landscapes. Landsc. Urban Plan. 2015, 134, 127–138.
  23. Santamouris, M. Analyzing the Heat Island Magnitude and Characteristics in One Hundred Asian and Australian Cities and Regions. Sci. Total Environ. 2015, 512–513, 582–598.
  24. Santamouris, M. Innovating to Zero the Building Sector in Europe: Minimising the Energy Consumption, Eradication of the Energy Poverty and Mitigating the Local Climate Change. Sol. Energy 2016, 128, 61–94.
  25. Taleb, D.; Abu-Hijleh, B. Urban Heat Islands: Potential Effect of Organic and Structured Urban Configurations on Temperature Variations in Dubai, UAE. Renew. Energy 2013, 50, 747–762.
  26. Shahrestani, M.; Yao, R.; Luo, Z.; Turkbeyler, E.; Davies, H. A Field Study of Urban Microclimates in London. Renew. Energy 2015, 73, 3–9.
  27. Arnfield, A.J. Two Decades of Urban Climate Research: A Review of Turbulence, Exchanges of Energy and Water, and the Urban Heat Island. Int. J. Climatol. 2003, 23, 1–26.
  28. Mirzaei, P.A.; Haghighat, F. Approaches to Study Urban Heat Island – Abilities and Limitations. Build. Environ. 2010, 45, 2192–2201.
  29. Oke, T.R. Boundary Layer Climates, 2nd ed.; Routledge: London, UK, 1987; ISBN 978-0-203-40721-9.
  30. Wong, K.V.; Paddon, A.; Jimenez, A. Review of World Urban Heat Islands: Many Linked to Increased Mortality. J. Energy Resour. Technol. 2013, 135, 022101.
  31. Rizwan, A.M.; Dennis, L.Y.C.; Liu, C. A Review on the Generation, Determination and Mitigation of Urban Heat Island. J. Environ. Sci. 2008, 20, 120–128.
  32. Santamouris, M.; Mihalakakou, G.; Papanikolaou, N.; Asimakopoulos, D.N. A Neural Network Approach for Modeling the Heat Island Phenomenon in Urban Areas during the Summer Period. Geophys. Res. Lett. 1999, 26, 337–340.
  33. Santamouris, M.; Kolokotsa, D. Urban Climate Mitigation Techniques; Routledge: London, UK, 2016; ISBN 978-1-315-76583-9.
  34. Santamouris, M. Cooling the Cities—A Review of Reflective and Green Roof Mitigation Technologies to Fight Heat Island and Improve Comfort in Urban Environments. Sol. Energy 2014, 103, 682–703.
  35. Rajagopalan, P.; Lim, K.C.; Jamei, E. Urban Heat Island and Wind Flow Characteristics of a Tropical City. Sol. Energy 2014, 107, 159–170.
  36. Lauwaet, D.; De Ridder, K.; Saeed, S.; Brisson, E.; Chatterjee, F.; van Lipzig, N.P.M.; Maiheu, B.; Hooyberghs, H. Assessing the Current and Future Urban Heat Island of Brussels. Urban Clim. 2016, 15, 1–15.
  37. Lehmann, S. Low Carbon Districts: Mitigating the Urban Heat Island with Green Roof Infrastructure. City Cult. Soc. 2014, 5, 1–8.
  38. Coseo, P.; Larsen, L. How Factors of Land Use/Land Cover, Building Configuration, and Adjacent Heat Sources and Sinks Explain Urban Heat Islands in Chicago. Landsc. Plan. 2014, 125, 117–129.
  39. Nakata-Osaki, C.M.; Souza, L.C.L.; Rodrigues, D.S. THIS—Tool for Heat Island Simulation: A GIS Extension Model to Calculate Urban Heat Island Intensity Based on Urban Geometry. Comput. Environ. Urban Syst. 2018, 67, 157–168.
  40. Santamouris, M. Minimizing Energy Consumption, Energy Poverty and Global and Local Climate Change in the Built Environment: Innovating to Zero. Causalities and Impacts in a Zero Concept World; Elsevier: Amsterdam, The Netherlands, 2019; ISBN 978-0-12-811417-9.
  41. Erell, E.; Pearlmutter, D.; Boneh, D.; Kutiel, P.B. Effect of High-Albedo Materials on Pedestrian Heat Stress in Urban Street Canyons. Urban Clim. 2014, 10, 367–386.
  42. Zakhour, S. The Impact of Urban Geometry on Outdoor Thermal Comfort Conditions in Hot-Arid Region. J. Civ. Eng. Archit. Res. 2015, 2, 862–875.
  43. Oke, T.R. Street Design and Urban Canopy Layer Climate. Energy Build. 1988, 11, 103–113.
  44. Wang, Y.; Li, Y.; Xue, Y.; Martilli, A.; Shen, J.; Chan, P.W. City-Scale Morphological Influence on Diurnal Urban Air Temperature. Build. Environ. 2020, 169, 106527.
  45. Papadopoulos, A.M. The Influence of Street Canyons on the Cooling Loads of Buildings and the Performance of Air Conditioning Systems. Energy Build. 2001, 33, 601–607.
  46. Britter, R.E.; Hanna, S.R. Flow and Dispersion in Urban Areas. Annu. Rev. Fluid Mech. 2003, 35, 469–496.
  47. Muniz-Gäal, L.P.; Pezzuto, C.C.; Carvalho, M.F.H.; de Mota, L.T.M. Urban Geometry and the Microclimate of Street Canyons in Tropical Climate. Build. Environ. 2020, 169, 106547.
  48. Kantzioura, A.; Kosmopoulos, P.; Zoras, S. Urban Surface Temperature and Microclimate Measurements in Thessaloniki. Energy Build. 2012, 44, 63–72.
  49. Terjung, W.H.; Louie, S.S.-F. Solar Radiation and Urban Heat Islands. Ann. Assoc. Am. Geogr. 1973, 63, 181–207.
  50. Jamei, E.; Rajagopalan, P.; Seyedmahmoudian, M.; Jamei, Y. Review on the Impact of Urban Geometry and Pedestrian Level Greening on Outdoor Thermal Comfort. Renew. Sustain. Energy Rev. 2016, 54, 1002–1017.
  51. Oke, T.R. Canyon Geometry and the Nocturnal Urban Heat Island: Comparison of Scale Model and Field Observations. J. Climatol. 1981, 1, 237–254.
  52. Yang, X.; Li, Y.; Luo, Z.; Chan, P.W. The Urban Cool Island Phenomenon in a High-Rise High-Density City and Its Mechanisms. Int. J. Climatol. 2017, 37, 890–904.
  53. Masson, V. A Physically-Based Scheme For The Urban Energy Budget In Atmospheric Models. Bound. Layer Meteorol. 2000, 94, 357–397.
  54. Yang, S.; Zhou, D.; Wang, Y.; Li, P. Comparing Impact of Multi-Factor Planning Layouts in Residential Areas on Summer Thermal Comfort Based on Orthogonal Design of Experiments (ODOE). Build. Environ. 2020, 182, 107145.
  55. Lee, D.O. Urban—Rural Humidity Differences in London. Int. J. Climatol. 1991, 11, 577–582.
  56. Livesley, S.J.; McPherson, E.G.; Calfapietra, C. The Urban Forest and Ecosystem Services: Impacts on Urban Water, Heat, and Pollution Cycles at the Tree, Street, and City Scale. J. Environ. Qual. 2016, 45, 119–124.
  57. Sailor, D.J.; Fan, H. Modeling the Diurnal Variability of Effective Albedo for Cities. Atmos. Environ. 2002, 36, 713–725.
  58. Santamouris, M. Regulating the Damaged Thermostat of the Cities—Status, Impacts and Mitigation Challenges. Energy Build. 2015, 91, 43–56.
  59. Sarrat, C.; Lemonsu, A.; Masson, V.; Guedalia, D. Impact of Urban Heat Island on Regional Atmospheric Pollution. Atmos. Environ. 2006, 40, 1743–1758.
  60. Agarwal, M.; Tandon, A. Modeling of the Urban Heat Island in the Form of Mesoscale Wind and of Its Effect on Air Pollution Dispersal. Appl. Math. Model. 2010, 34, 2520–2530.
  61. Krüger, E.L.; Minella, F.O.; Rasia, F. Impact of Urban Geometry on Outdoor Thermal Comfort and Air Quality from Field Measurements in Curitiba, Brazil. Build. Environ. 2011, 46, 621–634.
  62. Fahed, J.; Kinab, E.; Ginestet, S.; Adolphe, L. Impact of Urban Heat Island Mitigation Measures on Microclimate and Pedestrian Comfort in a Dense Urban District of Lebanon. Sustain. Cities Soc. 2020, 61, 102375.
  63. Rosso, F.; Pisello, A.L.; Cotana, F.; Ferrero, M. On the Thermal and Visual Pedestrians’ Perception about Cool Natural Stones for Urban Paving: A Field Survey in Summer Conditions. Build. Environ. 2016, 107, 198–214.
  64. Taleghani, M. Outdoor Thermal Comfort by Different Heat Mitigation Strategies—A Review. Renew. Sustain. Energy Rev. 2018, 81, 2011–2018.
  65. Iping, A.; Kidston-Lattari, J.; Simpson-Young, A.; Duncan, E.; McManus, P. (Re)Presenting Urban Heat Islands in Australian Cities: A Study of Media Reporting and Implications for Urban Heat and Climate Change Debates. Urban Clim. 2019, 27, 420–429.
  66. O’Malley, C.; Piroozfar, P.; Farr, E.R.P.; Pomponi, F. Urban Heat Island (UHI) Mitigating Strategies: A Case-Based Comparative Analysis. Sustain. Cities Soc. 2015, 19, 222–235.
  67. Gabriel, K.M.A.; Endlicher, W.R. Urban and Rural Mortality Rates during Heat Waves in Berlin and Brandenburg, Germany. Environ. Pollut. 2011, 159, 2044–2050.
  68. Rydin, Y.; Bleahu, A.; Davies, M.; Dávila, J.D.; Friel, S.; De Grandis, G.; Groce, N.; Hallal, P.C.; Hamilton, I.; Howden-Chapman, P.; et al. Shaping Cities for Health: Complexity and the Planning of Urban Environments in the 21st Century. Lancet 2012, 379, 2079–2108.
  69. McMichael, A.J.; Haines, J.A.; Slooff, R.; Sari Kovats, R.; World Health Organization. Climate Change and Human Health: An Assessment; World Health Organization: Geneva, Switzerland, 1996.
  70. Meehl, G.A.; Tebaldi, C. More Intense, More Frequent, and Longer Lasting Heat Waves in the 21st Century. Science 2004, 305, 994–997.
  71. Pascal, M.; Laaidi, K.; Ledrans, M.; Baffert, E.; Caserio-Schönemann, C.; Le Tertre, A.; Manach, J.; Medina, S.; Rudant, J.; Empereur-Bissonnet, P. France’s Heat Health Watch Warning System. Int. J. Biometeorol. 2006, 50, 144–153.
  72. Augusto, B.; Roebeling, P.; Rafael, S.; Ferreira, J.; Ascenso, A.; Bodilis, C. Short and Medium- to Long-Term Impacts of Nature-Based Solutions on Urban Heat. Sustain. Cities Soc. 2020, 57, 102122.
  73. Founda, D.; Santamouris, M. Synergies between Urban Heat Island and Heat Waves in Athens (Greece), during an Extremely Hot Summer (2012). Sci. Rep. 2017, 7, 10973.
  74. Boyko, C.T.; Cooper, R. Clarifying and Re-Conceptualising Density. Prog. Plan. 2011, 76, 1–61.
  75. Chokhachian, A.; Perini, K.; Giulini, S.; Auer, T. Urban Performance and Density: Generative Study on Interdependencies of Urban Form and Environmental Measures. Sustain. Cities Soc. 2020, 53, 101952.
  76. Aflaki, A.; Mirnezhad, M.; Ghaffarianhoseini, A.; Ghaffarianhoseini, A.; Omrany, H.; Wang, Z.-H.; Akbari, H. Urban Heat Island Mitigation Strategies: A State-of-the-Art Review on Kuala Lumpur, Singapore and Hong Kong. Cities 2017, 62, 131–145.
  77. Akbari, H.; Cartalis, C.; Kolokotsa, D.; Muscio, A.; Pisello, A.L.; Rossi, F.; Santamouris, M.; Synnefa, A.; Wong, N.H.; Zinzi, M. Local Climate Change and Urban Heat Island Mitigation Techniques—The State of the Art. J. Civ. Eng. Manag. 2016, 22, 1–16.
  78. Alchapar, N.L.; Correa, E.N. The Use of Reflective Materials as a Strategy for Urban Cooling in an Arid “OASIS” City. Sustain. Cities Soc. 2016, 27, 1–14.
  79. Barakat, A.; Ayad, H.; El-Sayed, Z. Urban Design in Favor of Human Thermal Comfort for Hot Arid Climate Using Advanced Simulation Methods. Alex. Eng. J. 2017, 56, 533–543.
  80. Huang, Q.; Meng, X.; Yang, X.; Jin, L.; Liu, X.; Hu, W. The Ecological City: Considering Outdoor Thermal Environment. Energy Procedia 2016, 104, 177–182.
  81. Stone, B., Jr.; Vargo, J.; Liu, P.; Habeeb, D.; DeLucia, A.; Trail, M.; Hu, Y.; Russell, A. Avoided Heat-Related Mortality through Climate Adaptation Strategies in Three US Cities. PLoS ONE 2014, 9, e100852.
  82. Leal Filho, W.; Echevarria Icaza, L.; Emanche, V.O.; Quasem Al-Amin, A. An Evidence-Based Review of Impacts, Strategies and Tools to Mitigate Urban Heat Islands. Int. J. Environ. Res. Public Health 2017, 14, 1600.
  83. Morakinyo, T.E.; Dahanayake, K.W.D.K.C.; Ng, E.; Chow, C.L. Temperature and Cooling Demand Reduction by Green-Roof Types in Different Climates and Urban Densities: A Co-Simulation Parametric Study. Energy Build. 2017, 145, 226–237.
  84. Paramita, B.; Fukuda, H. Study on the Affect of Aspect Building Form and Layout Case Study: Honjo Nishi Danchi, Yahatanishi, Kitakyushu-Fukuoka. Procedia Environ. Sci. 2013, 17, 767–774.
  85. Phelan, P.E.; Kaloush, K.; Miner, M.; Golden, J.; Phelan, B.; Silva, H.; Taylor, R.A. Urban Heat Island: Mechanisms, Implications, and Possible Remedies. Annu. Rev. Environ. Resour. 2015, 40, 285–307.
  86. Salata, F.; Golasi, I.; de Lieto Vollaro, R.; de Lieto Vollaro, A. Urban Microclimate and Outdoor Thermal Comfort. A Proper Procedure to Fit ENVI-Met Simulation Outputs to Experimental Data. Sustain. Cities Soc. 2016, 26, 318–343.
  87. Tsilini, V.; Papantoniou, S.; Kolokotsa, D.-D.; Maria, E.-A. Urban Gardens as a Solution to Energy Poverty and Urban Heat Island. Sustain. Cities Soc. 2015, 14, 323–333.
  88. Yin, S.; Xiao, Y. Scale Study of Traditional Shophouse Street in South of China Based on Outdoor Thermal Comfort. Procedia Eng. 2016, 169, 232–239.
  89. Cole, R.J. Regenerative Design and Development: Current Theory and Practice. Build. Res. Inf. 2012, 40, 1–6.
  90. Sadri, H.; Zeybekoglu, S. Deurbanization and the Right to the Deurbanized City. ANDULI Rev. Andal. Cienc. Soc. 2018, 17, 205–219.
  91. Lin, B.B.; Meyers, J.; Beaty, R.M.; Barnett, G.B. Urban Green Infrastructure Impacts on Climate Regulation Services in Sydney, Australia. Sustainability 2016, 8, 788.
  92. Antoszewski, P.; Świerk, D.; Krzyżaniak, M. Statistical Review of Quality Parameters of Blue-Green Infrastructure Elements Important in Mitigating the Effect of the Urban Heat Island in the Temperate Climate (C) Zone. Int. J. Environ. Res. Public Health 2020, 17, 7093.
  93. Ramírez-Aguilar, E.A.; Lucas Souza, L.C. Urban Form and Population Density: Influences on Urban Heat Island Intensities in Bogotá, Colombia. Urban Clim. 2019, 29, 100497.
  94. Yuan, C.; Chen, L. Mitigating Urban Heat Island Effects in High-Density Cities Based on Sky View Factor and Urban Morphological Understanding: A Study of Hong Kong. Archit. Sci. Rev. 2011, 54, 305–315.
  95. Chen, L.; Ng, E.; An, X.; Ren, C.; Lee, M.; Wang, U.; He, Z. Sky View Factor Analysis of Street Canyons and Its Implications for Daytime Intra-Urban Air Temperature Differentials in High-Rise, High-Density Urban Areas of Hong Kong: A GIS-Based Simulation Approach. Int. J. Climatol. 2012, 32, 121–136.
  96. Guo, C.; Buccolieri, R.; Gao, Z. Characterizing the Morphology of Real Street Models and Modeling Its Effect on Thermal Environment. Energy Build. 2019, 203, 109433.
  97. Andreou, E.; Axarli, K. Investigation of Urban Canyon Microclimate in Traditional and Contemporary Environment. Experimental Investigation and Parametric Analysis. Renew. Energy 2012, 43, 354–363.
  98. Chatzidimitriou, A.; Yannas, S. Microclimate Design for Open Spaces: Ranking Urban Design Effects on Pedestrian Thermal Comfort in Summer. Sustain. Cities Soc. 2016, 26, 27–47.
  99. Ali, J.M.; Marsh, S.H.; Smith, M.J. Modelling the Spatiotemporal Change of Canopy Urban Heat Islands. Build. Environ. 2016, 107, 64–78.
  100. Huang, X.; Song, J.; Wang, C.; Chui, T.F.M.; Chan, P.W. The Synergistic Effect of Urban Heat and Moisture Islands in a Compact High-Rise City. Build. Environ. 2021, 205, 108274.
  101. Noro, M.; Busato, F.; Lazzarin, R. UHI Effect in the City of Padua: Simulations and Mitigation Strategies Using the Rayman and Envimet Model. Geogr. Pol. 2014, 87, 517–530.
  102. Guo, J.; Han, G.; Xie, Y.; Cai, Z.; Zhao, Y. Exploring the Relationships between Urban Spatial Form Factors and Land Surface Temperature in Mountainous Area: A Case Study in Chongqing City, China. Sustain. Cities Soc. 2020, 61, 102286.
  103. Cai, Z.; Han, G.; Chen, M. Do Water Bodies Play an Important Role in the Relationship between Urban Form and Land Surface Temperature? Sustain. Cities Soc. 2018, 39, 487–498.
  104. Duan, S.; Luo, Z.; Yang, X.; Li, Y. The Impact of Building Operations on Urban Heat/Cool Islands under Urban Densification: A Comparison between Naturally-Ventilated and Air-Conditioned Buildings. Appl. Energy 2019, 235, 129–138.
  105. Gál, T.; Lindberg, F.; Unger, J. Computing Continuous Sky View Factors Using 3D Urban Raster and Vector Databases: Comparison and Application to Urban Climate. Theor. Appl. Climatol. 2009, 95, 111–123.
  106. Bourbia, F.; Boucheriba, F. Impact of Street Design on Urban Microclimate for Semi Arid Climate (Constantine). Renew. Energy 2010, 35, 343–347.
  107. Erdem Okumus, D.; Terzi, F. Evaluating the Role of Urban Fabric on Surface Urban Heat Island: The Case of Istanbul. Sustain. Cities Soc. 2021, 73, 103128.
  108. Cheung, P.K.; Jim, C.Y. Effects of Urban and Landscape Elements on Air Temperature in a High-Density Subtropical City. Build. Environ. 2019, 164, 106362.
  109. Unger, J. Intra-Urban Relationship between Surface Geometry and Urban Heat Island: Review and New Approach. Clim. Res. 2004, 27, 253–264.
  110. Drach, P.; Krüger, E.L.; Emmanuel, R. Effects of Atmospheric Stability and Urban Morphology on Daytime Intra-Urban Temperature Variability for Glasgow, UK. Sci. Total Environ. 2018, 627, 782–791.
  111. Unger, J. Modelling of the Annual Mean Maximum Urban Heat Island Using 2D and 3D Surface Parameters. Clim. Res. 2006, 30, 215–226.
  112. Hamdi, R.; Schayes, G. Sensitivity Study of the Urban Heat Island Intensity to Urban Characteristics. Int. J. Climatol. 2008, 28, 973–982.
  113. Castaldo, V.L.; Rosso, F.; Golasi, I.; Piselli, C.; Salata, F.; Pisello, A.L.; Ferrero, M.; Cotana, F.; de Lieto Vollaro, A. Thermal Comfort in the Historical Urban Canyon: The Effect of Innovative Materials. Energy Procedia 2017, 134, 151–160.
  114. Dobrovolný, P.; Šezníčková, L.; Krahula, L. Spatial and Temporal Variability of Urban Heat Island Intensity in Brno (Czech Republic). Geophys. Res. Abstr. 2012, 14, 4165.
  115. Yang, F.; Lau, S.S.Y.; Qian, F. Summertime Heat Island Intensities in Three High-Rise Housing Quarters in Inner-City Shanghai China: Building Layout, Density and Greenery. Build. Environ. 2010, 45, 115–134.
  116. Giridharan, R.; Lau, S.S.Y.; Ganesan, S.; Givoni, B. Urban Design Factors Influencing Heat Island Intensity in High-Rise High-Density Environments of Hong Kong. Build. Environ. 2007, 42, 3669–3684.
  117. Yang, J.; Shi, Q.; Menenti, M.; Wong, M.S.; Wu, Z.; Zhao, Q.; Abbas, S.; Xu, Y. Observing the Impact of Urban Morphology and Building Geometry on Thermal Environment by High Spatial Resolution Thermal Images. Urban Clim. 2021, 39, 100937.
  118. Sugie, L.; Jaehyun, H.; Hyemin, C. Spatial and Temporal Effects of Built Environment on Urban Air Temperature in Seoul City, Korea: An Application of Spatial Regression Models. J. Asian Archit. Build. Eng. 2017, 16, 123–130.
  119. Ha, J.; Lee, S.; Park, C. Temporal Effects of Environmental Characteristics on Urban Air Temperature: The Influence of the Sky View Factor. Sustainability 2016, 8, 895.
  120. Elnahas, M.M. The Effects of Urban Configuration on Urban Air Temperatures. Archit. Sci. Rev. 2003, 46, 135–138.
  121. Kottmeier, C.; Biegert, C.; Corsmeier, U. Effects of Urban Land Use on Surface Temperature in Berlin: Case Study. J. Urban Plan. Dev. 2007, 133, 128–137.
  122. Lyu, T.; Buccolieri, R.; Gao, Z. A Numerical Study on the Correlation between Sky View Factor and Summer Microclimate of Local Climate Zones. Atmosphere 2019, 10, 438.
  123. Holmer, B.; Thorsson, S.; Eliasson, I. Cooling Rates, Sky View Factors and the Development of Intra-urban Air Temperature Differences. Geogr. Ann. Ser. A Phys. Geogr. 2007, 89, 237–248.
  124. Scarano, M.; Sobrino, J.A. On the Relationship between the Sky View Factor and the Land Surface Temperature Derived by Landsat-8 Images in Bari, Italy. Int. J. Remote Sens. 2015, 36, 4820–4835.
  125. Theeuwes, N.E.; Steeneveld, G.J.; Ronda, R.J.; Heusinkveld, B.G.; van Hove, L.W.A.; Holtslag, A.A.M. Seasonal Dependence of the Urban Heat Island on the Street Canyon Aspect Ratio. Q. J. R. Meteorol. Soc. 2014, 140, 2197–2210.
  126. Gerçek, D.; Güven, İ.T.; Oktay, İ.Ç. Analysis of the Intra-City Variation of Urban Heat Island and Its Relation to Land Surface/Cover Parameters. ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci. 2016, 3, 123.
  127. Shaker, R.R.; Altman, Y.; Deng, C.; Vaz, E.; Forsythe, K.W. Investigating Urban Heat Island through Spatial Analysis of New York City Streetscapes. J. Clean. Prod. 2019, 233, 972–992.
  128. Ali-Toudert, F. Exploration of the Thermal Behaviour and Energy Balance of Urban Canyons in Relation to Their Geometrical and Constructive Properties. Build. Environ. 2021, 188, 107466.
  129. Bennet, M.; Ewenz, C. Increased Urban Heat Island Effect Due to Building Height Increase. In MODSIM2013, Proceedings of the 20th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, Adelaide, Australia, 1–6 December 2013; Piantadosi, J., Anderssen, R.S., Boland, J., Eds.; Modelling and Simulation Society of Australia and New Zealand Inc.: Canberra, Australia, 2013; pp. 2242–2247.
  130. Lin, T.-P.; Matzarakis, A.; Hwang, R.-L. Shading Effect on Long-Term Outdoor Thermal Comfort. Build. Environ. 2010, 45, 213–221.
  131. Yang, F.; Lau, S.S.Y.; Qian, F. Urban Design to Lower Summertime Outdoor Temperatures: An Empirical Study on High-Rise Housing in Shanghai. Build. Environ. 2011, 46, 769–785.
  132. Yang, J.; Wong, M.S.; Menenti, M.; Nichol, J. Study of the Geometry Effect on Land Surface Temperature Retrieval in Urban Environment. ISPRS J. Photogramm. Remote Sens. 2015, 109, 77–87.
  133. Yang, F.; Qian, F.; Lau, S.S.Y. Urban Form and Density as Indicators for Summertime Outdoor Ventilation Potential: A Case Study on High-Rise Housing in Shanghai. Build. Environ. 2013, 70, 122–137.
  134. Shashua-Bar, L.; Hoffman, M.E. Geometry and Orientation Aspects in Passive Cooling of Canyon Streets with Trees. Energy Build. 2003, 35, 61–68.
  135. Erdem, U.; Cubukcu, K.M.; Sharifi, A. An Analysis of Urban Form Factors Driving Urban Heat Island: The Case of Izmir. Environ. Dev. Sustain. 2021, 23, 7835–7859.
  136. Li, J.; Song, C.; Cao, L.; Zhu, F.; Meng, X.; Wu, J. Impacts of Landscape Structure on Surface Urban Heat Islands: A Case Study of Shanghai, China. Remote Sens. Environ. 2011, 115, 3249–3263.
  137. Yang, J.; Zhan, Y.; Xiao, X.; Xia, J.C.; Sun, W.; Li, X. Investigating the Diversity of Land Surface Temperature Characteristics in Different Scale Cities Based on Local Climate Zones. Urban Clim. 2020, 34, 100700.
  138. Yang, Y.K.; Kang, I.S.; Chung, M.H.; Kim, S.; Park, J.C. Effect of PCM Cool Roof System on the Reduction in Urban Heat Island Phenomenon. Build. Environ. 2017, 122, 411–421.
  139. Nakano, A.; Bueno, B.; Norford, L.; Reinhart, C.F. Urban Weather Generator—A Novel Workflow for Integrating Urban Heat Island Effect within Urban Design Process. In Proceedings of the BS2015: 14th Conference of International Building Performance Simulation Association, Hyderabad, India, 7–9 December 2015; pp. 1901–1908.
  140. Henits, L.; Mucsi, L.; Liska, C.M. Monitoring the Changes in Impervious Surface Ratio and Urban Heat Island Intensity between 1987 and 2011 in Szeged, Hungary. Environ. Monit. Assess. 2017, 189, 86.
  141. Choi, Y.; Lee, S.; Moon, H. Urban Physical Environments and the Duration of High Air Temperature: Focusing on Solar Radiation Trapping Effects. Sustainability 2018, 10, 4837.
  142. Tremeac, B.; Bousquet, P.; de Munck, C.; Pigeon, G.; Masson, V.; Marchadier, C.; Merchat, M.; Poeuf, P.; Meunier, F. Influence of Air Conditioning Management on Heat Island in Paris Air Street Temperatures. Appl. Energy 2012, 95, 102–110.
  143. Perini, K.; Magliocco, A. Effects of Vegetation, Urban Density, Building Height, and Atmospheric Conditions on Local Temperatures and Thermal Comfort. Urban For. Urban Green. 2014, 13, 495–506.
  144. Sun, Y.; Gao, C.; Li, J.; Wang, R.; Liu, J. Quantifying the Effects of Urban Form on Land Surface Temperature in Subtropical High-Density Urban Areas Using Machine Learning. Remote Sens. 2019, 11, 959.
  145. Liu, W.; Feddema, J.; Hu, L.; Zung, A.; Brunsell, N. Seasonal and Diurnal Characteristics of Land Surface Temperature and Major Explanatory Factors in Harris County, Texas. Sustainability 2017, 9, 2324.
  146. Montávez, J.P.; Rodríguez, A.; Jiménez, J.I. A Study of the Urban Heat Island of Granada. Int. J. Climatol. 2000, 20, 899–911.
  147. Jia, J.; Liu, S.; Zhao, S.; Li, Y.; Zhang, Q.; Tang, W. Influences of Landscape Composition and Configuration on Land Surface Temperature in Wuhan, a “Furnace” City in China. In AGU Fall Meeting Abstracts; American Geophysical Union: Washington, DC, USA, 2020; #GC006-0001.
  148. Pigliautile, I.; Chàfer, M.; Pisello, A.L.; Pérez, G.; Cabeza, L.F. Inter-Building Assessment of Urban Heat Island Mitigation Strategies: Field Tests and Numerical Modelling in a Simplified-Geometry Experimental Set-Up. Renew. Energy 2020, 147, 1663–1675.
  149. Li, Y.; Schubert, S.; Kropp, J.P.; Rybski, D. On the Influence of Density and Morphology on the Urban Heat Island Intensity. Nat. Commun. 2020, 11, 2647.
  150. Salvati, A.; Palme, M.; Inostroza, L. Key Parameters for Urban Heat Island Assessment in A Mediterranean Context: A Sensitivity Analysis Using the Urban Weather Generator Model. IOP Conf. Ser. Mater. Sci. Eng. 2017, 245, 082055.
  151. Mathew, A.; Khandelwal, S.; Kaul, N. Spatial and Temporal Variations of Urban Heat Island Effect and the Effect of Percentage Impervious Surface Area and Elevation on Land Surface Temperature: Study of Chandigarh City, India. Sustain. Cities Soc. 2016, 26, 264–277.
  152. Xu, D.; Zhou, D.; Wang, Y.; Xu, W.; Yang, Y. Field Measurement Study on the Impacts of Urban Spatial Indicators on Urban Climate in a Chinese Basin and Static-Wind City. Build. Environ. 2019, 147, 482–494.
  153. Huang, J.-M.; Chang, H.-Y.; Wang, Y.-S. Spatiotemporal Changes in the Built Environment Characteristics and Urban Heat Island Effect in a Medium-Sized City, Chiayi City, Taiwan. Sustainability 2020, 12, 365.
  154. Giridharan, R.; Lau, S.S.Y.; Ganesan, S. Nocturnal Heat Island Effect in Urban Residential Developments of Hong Kong. Energy Build. 2005, 37, 964–971.
  155. Azhdari, A.; Soltani, A.; Alidadi, M. Urban Morphology and Landscape Structure Effect on Land Surface Temperature: Evidence from Shiraz, a Semi-Arid City. Sustain. Cities Soc. 2018, 41, 853–864.
  156. Zhou, W.; Huang, G.; Cadenasso, M.L. Does Spatial Configuration Matter? Understanding the Effects of Land Cover Pattern on Land Surface Temperature in Urban Landscapes. Landsc. Urban Plan. 2011, 102, 54–63.
  157. Lau, K.K.-L.; Chung, S.C.; Ren, C. Outdoor Thermal Comfort in Different Urban Settings of Sub-Tropical High-Density Cities: An Approach of Adopting Local Climate Zone (LCZ) Classification. Build. Environ. 2019, 154, 227–238.
  158. Shafizadeh-Moghadam, H.; Weng, Q.; Liu, H.; Valavi, R. Modeling the Spatial Variation of Urban Land Surface Temperature in Relation to Environmental and Anthropogenic Factors: A Case Study of Tehran, Iran. GIScience Remote Sens. 2020, 57, 483–496.
  159. Hendel, M.; Parison, S.; Grados, A.; Royon, L. Which Pavement Structures Are Best Suited to Limiting the UHI Effect? A Laboratory-Scale Study of Parisian Pavement Structures. Build. Environ. 2018, 144, 216–229.
  160. Lin, J.D.; Hsu, C.Y.; Paramitha, P.A.; Lee, J.C. The Study of Pavement Surface Temperature Behavior of Different Permeable Pavement Materials during Summer Time. Adv. Mater. Res. 2013, 723, 711–718.
  161. Wang, Y.; Zhang, Y.; Ding, N.; Qin, K.; Yang, X. Simulating the Impact of Urban Surface Evapotranspiration on the Urban Heat Island Effect Using the Modified RS-PM Model: A Case Study of Xuzhou, China. Remote Sens. 2020, 12, 578.
  162. Georgakis, C.; Santamouris, M. Experimental Investigation of Air Flow and Temperature Distribution in Deep Urban Canyons for Natural Ventilation Purposes. Energy Build. 2006, 38, 367–376.
  163. Ghadban, M.; Baayoun, A.; Lakkis, I.; Najem, S.; Saliba, N.A.; Shihadeh, A. A Novel Method to Improve Temperature Forecast in Data-Scarce Urban Environments with Application to the Urban Heat Island in Beirut. Urban Clim. 2020, 33, 100648.
  164. Pasetto, M.; Pasquini, E.; Giacomello, G.; Baliello, A. Innovative Pavement Surfaces as Urban Heat Islands Mitigation Strategy: Chromatic, Thermal and Mechanical Characterisation of Clear/Coloured Mixtures. Road Mater. Pavement Des. 2019, 20, S533–S555.
  165. Feng, D.; Gong, C. Sensitivity Analysis and Determination of the Effects of Asphalt Pavement Thermophysical Properties on the Temperature Field. J. Highw. Transp. Res. Dev. 2012, 6, 1–10.
  166. Dimoudi, A.; Kantzioura, A.; Zoras, S.; Pallas, C.; Kosmopoulos, P. Investigation of Urban Microclimate Parameters in an Urban Center. Energy Build. 2013, 64, 1–9.
  167. Chen, G.; Wang, D.; Wang, Q.; Li, Y.; Wang, X.; Hang, J.; Gao, P.; Ou, C.; Wang, K. Scaled Outdoor Experimental Studies of Urban Thermal Environment in Street Canyon Models with Various Aspect Ratios and Thermal Storage. Sci. Total Environ. 2020, 726, 138147.
  168. Fikfak, A.; Kosanović, S.; Konjar, M.; Grom, J.P.; Zbašnik-Senegačnik, M. The Impact of Morphological Features on Summer Temperature Variations on the Example of Two Residential Neighborhoods in Ljubljana, Slovenia. Sustainability 2017, 9, 122.
  169. Taleghani, M.; Kleerekoper, L.; Tenpierik, M.; Dobbelsteen, A. Outdoor Thermal Comfort within Five Different Urban Forms in The Netherlands. Build. Environ. 2014, 83, 65–78.
  170. Liao, F.-C.; Cheng, M.-J.; Hwang, R.-L.; Yang, W.-S. The Effect of Land Cover and Land Use on Urban Heat Island in Taiwan. In Proceedings of the World SB14, Barcelona, Spain, 28–30 October 2014; pp. 28–30.
  171. Taleghani, M.; Tenpierik, M.; van den Dobbelsteen, A.; Sailor, D.J. Heat in Courtyards: A Validated and Calibrated Parametric Study of Heat Mitigation Strategies for Urban Courtyards in the Netherlands. Sol. Energy 2014, 103, 108–124.
  172. Vargas-Nordcbeck, A.; Timm, D.H. Evaluation of Pavement Temperatures of Various Pavement Sections. In Transportation and Development Institute Congress 2011: Integrated Transportation and Development for a Better Tomorrow, Proceedings of the First Transportation and Development Institute Congress, Chicago, IL, USA, 13–16 March 2011; American Society of Civil Engineers: Reston, VA, USA, 2012; pp. 782–791.
  173. Johansson, E.; Grundström, K.; Rosenlund, H. Street Canyon Microclimate in Traditional and Modern Neighbourhoods in a Hot Dry Climate - a Case Study in Fez, Morocco. In Proceedings of the PLEA (Passive and Low Energy Architecture) Association, Florianópolis, Brazil, 2 January 2001; Pereira, F.O.R., Rüther, R., Souza, R.V.G., Afonso, S., da Cunha Neto, J.A.B., Eds.; Lund University: Lund, Sweden, 2001; pp. 661–665.
  174. Yahia, M.W.; Johansson, E. Influence of Urban Planning Regulations on the Microclimate in a Hot Dry Climate: The Example of Damascus, Syria. J. Hous. Built Env. 2013, 28, 51–65.
  175. Bokaie, M.; Zarkesh, M.K.; Arasteh, P.D.; Hosseini, A. Assessment of Urban Heat Island Based on the Relationship between Land Surface Temperature and Land Use/Land Cover in Tehran. Sustain. Cities Soc. 2016, 23, 94–104.
  176. Giannaros, C.; Nenes, A.; Giannaros, T.M.; Kourtidis, K.; Melas, D. A Comprehensive Approach for the Simulation of the Urban Heat Island Effect with the WRF/SLUCM Modeling System: The Case of Athens (Greece). Atmos. Res. 2018, 201, 86–101.
  177. Battista, G.; de Lieto Vollaro, E.; Grignaffini, S.; Ocłoń, P.; Vallati, A. Experimental Investigation about the Adoption of High Reflectance Materials on the Envelope Cladding on a Scaled Street Canyon. Energy 2021, 230, 120801.
  178. Gaffin, S.R.; Imhoff, M.; Rosenzweig, C.; Khanbilvardi, R.; Pasqualini, A.; Kong, A.Y.Y.; Grillo, D.; Freed, A.; Hillel, D.; Hartung, E. Bright Is the New Black—Multi-Year Performance of High-Albedo Roofs in an Urban Climate. Environ. Res. Lett. 2012, 7, 014029.
  179. Ronchi, S.; Salata, S.; Arcidiacono, A. Which Urban Design Parameters Provide Climate-Proof Cities? An Application of the Urban Cooling InVEST Model in the City of Milan Comparing Historical Planning Morphologies. Sustain. Cities Soc. 2020, 63, 102459.
  180. He, X.; Gao, W.; Wang, R. Impact of Urban Morphology on the Microclimate around Elementary Schools: A Case Study from Japan. Build. Environ. 2021, 206, 108383.
  181. Zwoliński, A.; Zwoliński, W. Analytical Study of the Impact of Greenery and Public Space Distribution on Land Surface Temperature in Mid-Size Cities of Poland. In PROJECTIONS—Proceedings of the 26th CAADRIA Conferencene, Hong Kong, China, 29 March–1 April 2021; Globa, A.A., van Ameijde, J., Fingrut, A., Kim, N., Lo, T.T.S., Eds.; The Chinese University of Hong Kong: Hong Kong, China, 2021; Volume 2, pp. 437–446.
  182. Chun, B.; Guldmann, J.-M. Spatial Statistical Analysis and Simulation of the Urban Heat Island in High-Density Central Cities. Landsc. Urban Plan. 2014, 125, 76–88.
  183. Li, Y.; Wang, D.; Li, S.; Gao, W. Impact Analysis of Urban Morphology on Residential District Heat Energy Demand and Microclimate Based on Field Measurement Data. Sustainability 2021, 13, 2070.
  184. Takebayashi, H.; Moriyama, M. Relationships between the Properties of an Urban Street Canyon and Its Radiant Environment: Introduction of Appropriate Urban Heat Island Mitigation Technologies. Sol. Energy 2012, 86, 2255–2262.
  185. Lin, P.; Song, D.; LAU, S.S.Y.; Hao, Q.I.N. Investigation of The Impacts of Urban Morphology on Summer-Time Urban Heat Island Using GIS And Field Measurement. Res. Sq. 2021, 1–28.
  186. Li, H.; Li, Y.; Wang, T.; Wang, Z.; Gao, M.; Shen, H. Quantifying 3D Building Form Effects on Urban Land Surface Temperature and Modeling Seasonal Correlation Patterns. Build. Environ. 2021, 204, 108132.
  187. Chen, S.; Lang, W.; Li, X.; Shen, C.; Fan, Q. Determining the Influence of Building Density on Heat Island Effect Using Baidu Map and Remote Sensing. Photogramm. Eng. Remote Sens. 2018, 84, 549–558.
  188. Loughner, C.P.; Allen, D.J.; Zhang, D.-L.; Pickering, K.E.; Dickerson, R.R.; Landry, L. Roles of Urban Tree Canopy and Buildings in Urban Heat Island Effects: Parameterization and Preliminary Results. J. Appl. Meteorol. Climatol. 2012, 51, 1775–1793.
  189. Alexander, C. Influence of the Proportion, Height and Proximity of Vegetation and Buildings on Urban Land Surface Temperature. Int. J. Appl. Earth Obs. Geoinf. 2021, 95, 102265.
  190. Huang, X.; Wang, Y. Investigating the Effects of 3D Urban Morphology on the Surface Urban Heat Island Effect in Urban Functional Zones by Using High-Resolution Remote Sensing Data: A Case Study of Wuhan, Central China. ISPRS J. Photogramm. Remote Sens. 2019, 152, 119–131.
  191. Yang, J.; Menenti, M.; Wu, Z.; Wong, M.S.; Abbas, S.; Xu, Y.; Shi, Q. Assessing the Impact of Urban Geometry on Surface Urban Heat Island Using Complete and Nadir Temperatures. Int. J. Climatol. 2021, 41, E3219–E3238.
  192. Guo, G.; Zhou, X.; Wu, Z.; Xiao, R.; Chen, Y. Characterizing the Impact of Urban Morphology Heterogeneity on Land Surface Temperature in Guangzhou, China. Environ. Model. Softw. 2016, 84, 427–439.
  193. Chen, L.; Mak, C.M. Integrated Impacts of Building Height and Upstream Building on Pedestrian Comfort around Ideal Lift-up Buildings in a Weak Wind Environment. Build. Environ. 2021, 200, 107963.
  194. Oh, M.; Jang, K.M.; Kim, Y. Empirical Analysis of Building Energy Consumption and Urban Form in a Large City: A Case of Seoul, South Korea. Energy Build. 2021, 245, 111046.
  195. Yuan, J.; Yamanaka, T.; Kobayashi, T.; Kitakaze, H.; Emura, K. Effect of Highly Reflective Building Envelopes on Outdoor Environment Temperature and Indoor Thermal Loads Using CFD and Numerical Analysis. E3S Web Conf. 2019, 111, 06031.
  196. Kalman, Y.; Pearlmutter, D.; Erell, E. Impact of Increasing the Height of Tel Aviv Buildings on Pedestrian Comfort and Building Energy Efficiency. In Proceedings of the 29th PLEA International Conference: Sustainable Architecture for a Renewable Future, Munich, Germany, 10–12 September 2013; pp. 1–7.
  197. Salvati, A.; Coch, H.; Morganti, M. Effects of Urban Compactness on the Building Energy Performance in Mediterranean Climate. Energy Procedia 2017, 122, 499–504.
  198. Nazarian, N.; Kleissl, J. CFD Simulation of an Idealized Urban Environment: Thermal Effects of Geometrical Characteristics and Surface Materials. Urban Clim. 2015, 12, 141–159.
  199. Santamouris, M.; Haddad, S.; Saliari, M.; Vasilakopoulou, K.; Synnefa, A.; Paolini, R.; Ulpiani, G.; Garshasbi, S.; Fiorito, F. On the Energy Impact of Urban Heat Island in Sydney: Climate and Energy Potential of Mitigation Technologies. Energy Build. 2018, 166, 154–164.
  200. Imran, H.M.; Kala, J.; Ng, A.W.M.; Muthukumaran, S. Effectiveness of Green and Cool Roofs in Mitigating Urban Heat Island Effects during a Heatwave Event in the City of Melbourne in Southeast Australia. J. Clean. Prod. 2018, 197, 393–405.
  201. Ramyar, R.; Zarghami, E.; Bryant, M. Spatio-Temporal Planning of Urban Neighborhoods in the Context of Global Climate Change: Lessons for Urban Form Design in Tehran, Iran. Sustain. Cities Soc. 2019, 51, 101554.
  202. Abreu-Harbich, L.V.; Labaki, L.C.; Matzarakis, A. Thermal Bioclimate in Idealized Urban Street Canyons in Campinas, Brazil. Theor. Appl. Climatol. 2014, 115, 333–340.
  203. Herrmann, J.; Matzarakis, A. Mean Radiant Temperature in Idealised Urban Canyons—Examples from Freiburg, Germany. Int. J. Biometeorol. 2012, 56, 199–203.
  204. Delpak, N.; Sajadzadeh, H.; Hasanpourfard, S.; Aram, F. The Effect of Street Orientation on Outdoor Thermal Comfort in a Cold Mountainous Climate. Preprints 2021, 2021050654.
  205. Lobaccaro, G.; Acero, J.A.; Sanchez Martinez, G.; Padro, A.; Laburu, T.; Fernandez, G. Effects of Orientations, Aspect Ratios, Pavement Materials and Vegetation Elements on Thermal Stress inside Typical Urban Canyons. Int. J. Environ. Res. Public Health 2019, 16, 3574.
  206. Sharifi, E.; Lehmann, S. Comparative Analysis of Surface Urban Heat Island Effect in Central Sydney. J. Sustain. Dev. 2014, 7, 23–24.
  207. Johansson, E. Influence of Urban Geometry on Outdoor Thermal Comfort in a Hot Dry Climate: A Study in Fez, Morocco. Build. Environ. 2006, 41, 1326–1338.
  208. Kantzioura, A.; Kosmopoulos, P.; Dimoudi, A.; Zoras, S. Experimental Investigation of Microclimatic Conditions in Relation to the Built Environment in a Central Urban Area in Thessaloniki (Northern Greece): A Case Study. Sustain. Cities Soc. 2015, 19, 331–340.
  209. Martinelli, L.; Matzarakis, A. Influence of Height/Width Proportions on the Thermal Comfort of Courtyard Typology for Italian Climate Zones. Sustain. Cities Soc. 2017, 29, 97–106.
  210. Chatzidimitriou, A.; Axarli, K. Street Canyon Geometry Effects on Microclimate and Comfort; A Case Study in Thessaloniki. Procedia Environ. Sci. 2017, 38, 643–650.
  211. Boccalatte, A.; Fossa, M.; Gaillard, L.; Menezo, C. Microclimate and Urban Morphology Effects on Building Energy Demand in Different European Cities. Energy Build. 2020, 224, 110129.
  212. Lan, Y.; Zhan, Q. How Do Urban Buildings Impact Summer Air Temperature? The Effects of Building Configurations in Space and Time. Build. Environ. 2017, 125, 88–98.
  213. Chen, G.; Charlie Lam, C.K.; Wang, K.; Wang, B.; Hang, J.; Wang, Q.; Wang, X. Effects of Urban Geometry on Thermal Environment in 2D Street Canyons: A Scaled Experimental Study. Build. Environ. 2021, 198, 107916.
  214. Bourbia, F.; Boucheriba, F.; Tebbani, H. Street Design and Outdoor Comfort for Semi Arid Climate; PLEA: Waging am See, Germany, 2005; pp. 1–6.
  215. Le, M.T.; Shukurov, I.; Shukurova, L.; Dmitrieva, A. A Study Case of Mathematical Calculation of Urban Heat Island Intensity Based on Urban Geometry. In Proceedings of the EECE 2019, St. Petersburg, Russia, 19–20 November 2019; Anatolijs, B., Nikolai, V., Vitalii, S., Eds.; Springer International Publishing: Cham, Switzerland, 2020; pp. 373–388.
  216. Zhang, Y.; Du, X.; Shi, Y. Effects of Street Canyon Design on Pedestrian Thermal Comfort in the Hot-Humid Area of China. Int. J. Biometeorol. 2017, 61, 1421–1432.
  217. Xi, C.; Ren, C.; Wang, J.; Feng, Z.; Cao, S.-J. Impacts of Urban-Scale Building Height Diversity on Urban Climates: A Case Study of Nanjing, China. Energy Build. 2021, 251, 111350.
  218. Equere, V.; Mirzaei, P.A.; Riffat, S. Definition of a New Morphological Parameter to Improve Prediction of Urban Heat Island. Sustain. Cities Soc. 2020, 56, 102021.
  219. Andreou, E. Thermal Comfort in Outdoor Spaces and Urban Canyon Microclimate. Renew. Energy 2013, 55, 182–188.
  220. Shashua-Bar, L.; Hoffman, M.E. Quantitative Evaluation of the Effects of Built-up Geometry and Trees on Diurnal Air Temperature in Canyon-Type Courtyards. In Advances in Building Technology; Anson, M., Ko, J.M., Lam, E.S.S., Eds.; Elsevier: Oxford, UK, 2002; pp. 1493–1500. ISBN 978-0-08-044100-9.
  221. Yamaoka, N.; Yoshida, H.; Tanabe, M.; Yamashita, M.; Koga, T. Simulation Study of the Influence of Different Urban Canyons Element on the Canyon Thermal Environment. Build. Simul. 2008, 1, 118–128.
  222. Jamei, E.; Rajagopalan, P. Effect of Street Design on Pedestrian Thermal Comfort. Archit. Sci. Rev. 2019, 62, 92–111.
  223. Giannopoulou, K.; Santamouris, M.; Livada, I.; Georgakis, C.; Caouris, Y. The Impact of Canyon Geometry on Intra Urban and Urban: Suburban Night Temperature Differences Under Warm Weather Conditions. Pure Appl. Geophys. 2010, 167, 1433–1449.
  224. Thorsson, S.; Lindberg, F.; Björklund, J.; Holmer, B.; Rayner, D. Potential Changes in Outdoor Thermal Comfort Conditions in Gothenburg, Sweden Due to Climate Change: The Influence of Urban Geometry. Int. J. Climatol. 2011, 31, 324–335.
  225. Shashua-Bar, L.; Tzamir, Y.; Hoffman, M.E. Thermal Effects of Building Geometry and Spacing on the Urban Canopy Layer Microclimate in a Hot-Humid Climate in Summer. Int. J. Climatol. 2004, 24, 1729–1742.
  226. Achour-Younsi, S.; Kharrat, F. Outdoor Thermal Comfort: Impact of the Geometry of an Urban Street Canyon in a Mediterranean Subtropical Climate—Case Study Tunis, Tunisia. Procedia Soc. Behav. Sci. 2016, 216, 689–700.
  227. Lau, K.K.-L.; Lindberg, F.; Rayner, D.; Thorsson, S. The Effect of Urban Geometry on Mean Radiant Temperature under Future Climate Change: A Study of Three European Cities. Int. J. Biometeorol. 2015, 59, 799–814.
  228. Tong, S.; Wong, N.H.; Jusuf, S.K.; Tan, C.L.; Wong, H.F.; Ignatius, M.; Tan, E. Study on Correlation between Air Temperature and Urban Morphology Parameters in Built Environment in Northern China. Build. Environ. 2018, 127, 239–249.
  229. Jiang, Y.; Wu, C.; Teng, M. Impact of Residential Building Layouts on Microclimate in a High Temperature and High Humidity Region. Sustainability 2020, 12, 1046.
  230. Wang, W.; Ng, E. Large-Eddy Simulations of Air Ventilation in Parametric Scenarios: Comparative Studies of Urban Form and Wind Direction. Archit. Sci. Rev. 2018, 61, 215–225.
  231. Li, Z.; Zhang, H.; Wen, C.-Y.; Yang, A.-S.; Juan, Y.-H. Effects of Height-Asymmetric Street Canyon Configurations on Outdoor Air Temperature and Air Quality. Build. Environ. 2020, 183, 107195.
  232. Herbert, J.M.; Herbert, R.D. Simulation of the Effects of Canyon Geometry on Thermal Climate in City Canyons. Math. Comput. Simul. 2002, 59, 243–253.
  233. Carrasco, C.; Palme, M. Urban Form and Urban Materials as Controller of Urban Climate in Valparaiso, Chile. IOP Conf. Ser. Earth Environ. Sci. 2020, 503, 012049.
  234. Chatzipoulka, C.; Compagnon, R.; Nikolopoulou, M. Urban Geometry and Solar Availability on Façades and Ground of Real Urban Forms: Using London as a Case Study. Sol. Energy 2016, 138, 53–66.
  235. Athamena, K.; Sini, J.-F.; Rosant, J.-M.; Guilhot, J. Numerical Coupling Model to Compute the Microclimate Parameters inside a Street Canyon: Part I: Methodology and Experimental Validation of Surface Temperature. Sol. Energy 2018, 174, 1237–1251.
  236. Andreou, E. The Effect of Urban Layout, Street Geometry and Orientation on Shading Conditions in Urban Canyons in the Mediterranean. Renew. Energy 2014, 63, 587–596.
  237. Niachou, K.; Livada, I.; Santamouris, M. Experimental Study of Temperature and Airflow Distribution inside an Urban Street Canyon during Hot Summer Weather Conditions—Part I: Air and Surface Temperatures. Build. Environ. 2008, 43, 1383–1392.
  238. Lau, K.K.-L.; Ren, C.; Ho, J.; Ng, E. Numerical Modelling of Mean Radiant Temperature in High-Density Sub-Tropical Urban Environment. Energy Build. 2016, 114, 80–86.
  239. Targhi, M.Z.; Van Dessel, S. Potential Contribution of Urban Developments to Outdoor Thermal Comfort Conditions: The Influence of Urban Geometry and Form in Worcester, Massachusetts, USA. Procedia Eng. 2015, 118, 1153–1161.
  240. Yin, S.; Lang, W.; Xiao, Y. The Synergistic Effect of Street Canyons and Neighbourhood Layout Design on Pedestrian-Level Thermal Comfort in Hot-Humid Area of China. Sustain. Cities Soc. 2019, 49, 101571.
  241. Muhaisen, A.S.; Abed, H.M. Effect of Urban Geometry and Spacing on the Thermal Performance in the Mediterranean Climate of the Gaza Strip. J. Archit. Plan. 2014, 26, 1.
  242. Ketterer, C.; Matzarakis, A. Human-Biometeorological Assessment of Heat Stress Reduction by Replanning Measures in Stuttgart, Germany. Landsc. Urban Plan. 2014, 122, 78–88.
  243. Chen, T.; Yang, H.; Chen, G.; Lam, C.K.C.; Hang, J.; Wang, X.; Liu, Y.; Ling, H. Integrated Impacts of Tree Planting and Aspect Ratios on Thermal Environment in Street Canyons by Scaled Outdoor Experiments. Sci. Total Environ. 2021, 764, 142920.
  244. Coutts, A.M.; White, E.C.; Tapper, N.J.; Beringer, J.; Livesley, S.J. Temperature and Human Thermal Comfort Effects of Street Trees across Three Contrasting Street Canyon Environments. Theor. Appl. Climatol. 2016, 124, 55–68.
  245. Shashua-Bar, L.; Tsiros, I.X.; Hoffman, M. Passive Cooling Design Options to Ameliorate Thermal Comfort in Urban Streets of a Mediterranean Climate (Athens) under Hot Summer Conditions. Build. Environ. 2012, 57, 110–119.
  246. Weng, Q.; Liu, H.; Liang, B.; Lu, D. The Spatial Variations of Urban Land Surface Temperatures: Pertinent Factors, Zoning Effect, and Seasonal Variability. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2008, 1, 154–166.
  247. Smith, C.L.; Webb, A.; Levermore, G.J.; Lindley, S.J.; Beswick, K. Fine-Scale Spatial Temperature Patterns across a UK Conurbation. Clim. Change 2011, 109, 269–286.
  248. Zhang, X.; Estoque, R.C.; Murayama, Y. An Urban Heat Island Study in Nanchang City, China Based on Land Surface Temperature and Social-Ecological Variables. Sustain. Cities Soc. 2017, 32, 557–568.
  249. Shimazaki, Y.; Aoki, M.; Nitta, J.; Okajima, H.; Yoshida, A. Experimental Determination of Pedestrian Thermal Comfort on Water-Retaining Pavement for UHI Adaptation Strategy. Atmosphere 2021, 12, 127.
  250. Liu, K.; Zhang, X.; Li, X.; Jiang, H. Multiscale Analysis of Urban Thermal Characteristics: Case Study of Shijiazhuang, China. J. Appl. Remote Sens. 2014, 8, 083649.
  251. Lu, J.; Li, C.; Yu, C.; Jin, M.; Dong, S. Regression Analysis of the Relationship between Urban Heat Island Effect and Urban Canopy Characteristics in a Mountainous City, Chongqing. Indoor Built Environ. 2012, 21, 821–836.
  252. Zhao, H.; Zhang, H.; Miao, C.; Ye, X.; Min, M. Linking Heat Source–Sink Landscape Patterns with Analysis of Urban Heat Islands: Study on the Fast-Growing Zhengzhou City in Central China. Remote Sens. 2018, 10, 1268.
  253. Dobrovolný, P.; Krahula, L. The Spatial Variability of Air Temperature and Nocturnal Urban Heat Island Intensity in the City of Brno, Czech Republic. Morav. Geogr. Rep. 2015, 23, 8–16.
  254. Berger, C.; Rosentreter, J.; Voltersen, M.; Baumgart, C.; Schmullius, C.; Hese, S. Spatio-Temporal Analysis of the Relationship between 2D/3D Urban Site Characteristics and Land Surface Temperature. Remote Sens. Environ. 2017, 193, 225–243.
  255. Yuan, C.; Ng, E. Building Porosity for Better Urban Ventilation in High-Density Cities—A Computational Parametric Study. Build. Environ. 2012, 50, 176–189.
  256. Sun, F.; Liu, M.; Wang, Y.; Wang, H.; Che, Y. The Effects of 3D Architectural Patterns on the Urban Surface Temperature at a Neighborhood Scale: Relative Contributions and Marginal Effects. J. Clean. Prod. 2020, 258, 120706.
  257. Wei, R.; Song, D.; Wong, N.H.; Martin, M. Impact of Urban Morphology Parameters on Microclimate. Procedia Eng. 2016, 169, 142–149.
  258. Sun, C.-Y. A Street Thermal Environment Study in Summer by the Mobile Transect Technique. Theor. Appl. Climatol. 2011, 106, 433–442.
  259. Chatzipoulka, C.; Nikolopoulou, M.; Watkins, R. The Impact of Urban Geometry on the Radiant Environment in Outdoor Spaces. In Proceedings of the ICUC9—9th International Conference on Urban Climate jointly with 12th Symposium on the Urban Environment, Toulouse, France, 20–24 July 2015; pp. 1–6.
  260. Tsoka, S.; Tsikaloudaki, K.; Theodosiou, T. Urban Space’s Morphology and Microclimatic Analysis: A Study for a Typical Urban District in the Mediterranean City of Thessaloniki, Greece. Energy Build. 2017, 156, 96–108.
  261. Yang, Y.; Zhang, X.; Lu, X.; Hu, J.; Pan, X.; Zhu, Q.; Su, W. Effects of Building Design Elements on Residential Thermal Environment. Sustainability 2017, 10, 57.
  262. Wong, M.S.; Nichol, J.; Lee, K.-H. A Satellite View of Urban Heat Island: Causative Factors and Scenario Analysis. Korean J. Remote Sens. 2010, 26, 617–627.
  263. Lin, P.; Lau, S.S.Y.; Qin, H.; Gou, Z. Effects of Urban Planning Indicators on Urban Heat Island: A Case Study of Pocket Parks in High-Rise High-Density Environment. Landsc. Urban Plan. 2017, 168, 48–60.
  264. Mohegh, A.; Levinson, R.; Taha, H.; Gilbert, H.; Zhang, J.; Li, Y.; Tang, T.; Ban-Weiss, G.A. Observational Evidence of Neighborhood Scale Reductions in Air Temperature Associated with Increases in Roof Albedo. Climate 2018, 6, 98.
  265. Zhou, X.; Chen, H. Impact of Urbanization-Related Land Use Land Cover Changes and Urban Morphology Changes on the Urban Heat Island Phenomenon. Sci. Total Environ. 2018, 635, 1467–1476.
  266. Zhang, M.; Gao, Z. Effect of Urban Form on Microclimate and Energy Loads: Case Study of Generic Residential District Prototypes in Nanjing, China. Sustain. Cities Soc. 2021, 70, 102930.
  267. Mirzaee, S.; Özgun, O.; Ruth, M.; Binita, K.C. Neighborhood-Scale Sky View Factor Variations with Building Density and Height: A Simulation Approach and Case Study of Boston. Urban Clim. 2018, 26, 95–108.
  268. Yang, X.; Li, Y. The Impact of Building Density and Building Height Heterogeneity on Average Urban Albedo and Street Surface Temperature. Build. Environ. 2015, 90, 146–156.
  269. Vartholomaios, A. A Parametric Sensitivity Analysis of the Influence of Urban Form on Domestic Energy Consumption for Heating and Cooling in a Mediterranean City. Sustain. Cities Soc. 2017, 28, 135–145.
  270. Giridharan, R.; Lau, S.S.Y.; Ganesan, S.; Givoni, B. Lowering the Outdoor Temperature in High-Rise High-Density Residential Developments of Coastal Hong Kong: The Vegetation Influence. Build. Environ. 2008, 43, 1583–1595.
  271. Rhee, J.; Park, S.; Lu, Z. Relationship between Land Cover Patterns and Surface Temperature in Urban Areas. GISci. Remote Sens. 2014, 51, 521–536.
  272. Sharifi, E.; Lehmann, S. Correlation analysis of surface temperature of rooftops, streetscapes and urban heat island effect: Case study of central Sydney. J. Urban Environ. Eng. 2015, 9, 3–11.
  273. Zhou, B.; Rybski, D.; Kropp, J.P. The Role of City Size and Urban Form in the Surface Urban Heat Island. Sci. Rep. 2017, 7, 4791.
  274. Zhang, J.; Gou, Z.; Lu, Y.; Lin, P. The Impact of Sky View Factor on Thermal Environments in Urban Parks in a Subtropical Coastal City of Australia. Urban For. Urban Green. 2019, 44, 126422.
  275. Kedissa, C.; Outtas, S.; Belarbi, R. The Impact of Height/Width Ratio on the Microclimate and Thermal Comfort Levels of Urban Courtyards. Int. J. Sustain. Build. Technol. Urban Dev. 2016, 7, 174–183.
  276. Dirksen, M.; Ronda, R.J.; Theeuwes, N.E.; Pagani, G.A. Sky View Factor Calculations and Its Application in Urban Heat Island Studies. Urban Clim. 2019, 30, 100498.
  277. Castellani, B.; Nicolini, A.; Gambelli, A.M.; Filipponi, M.; Morini, E.; Rossi, F. Experimental Assessment of the Combined Effect of Retroreflective Façades and Pavement in Urban Canyons. IOP Conf. Ser. Mater. Sci. Eng. 2019, 609, 072004.
  278. Rossi, F.; Pisello, A.L.; Nicolini, A.; Filipponi, M.; Palombo, M. Analysis of Retro-Reflective Surfaces for Urban Heat Island Mitigation: A New Analytical Model. Appl. Energy 2014, 114, 621–631.
  279. Rossi, F.; Morini, E.; Castellani, B.; Nicolini, A.; Bonamente, E.; Anderini, E.; Cotana, F. Beneficial Effects of Retroreflective Materials in Urban Canyons: Results from Seasonal Monitoring Campaign. J. Phys. Conf. Ser. 2015, 655, 012012.
  280. Echevarría Icaza, L.; van der Hoeven, F.D.; van den Dobbelsteen, A. The Urban Heat Island Effect in Dutch City Centres: Identifying Relevant Indicators and First Explorations. In Implementing Climate Change Adaptation in Cities and Communities: Integrating Strategies and Educational Approaches; Leal Filho, W., Adamson, K., Dunk, R.M., Azeiteiro, U.M., Illingworth, S., Alves, F., Climate Change Management, Eds.; Springer International Publishing: Cham, Switzerland, 2016; pp. 123–160. ISBN 978-3-319-28591-7.
  281. Alsabry, A.; Truszkiewicz, P.; Szymański, K.; Łaskawiec, K.; Rojek, Ł. Analysis of Energy Consumption and Possibilities of Thermal-Modernization in Residential Buildings in Poland Case Study: The Town of Zielona Góra. Int. J. Appl. Mech. Eng. 2017, 22.
  282. Di Giuseppe, E.; Pergolini, M.; Stazi, F. Numerical Assessment of the Impact of Roof Reflectivity and Building Envelope Thermal Transmittance on the UHI Effect. Energy Procedia 2017, 134, 404–413.
  283. Dai, Q.; Schnabel, M.A. Thermal Comfort Levels Classified by Aspect Ratio and Orientation for Three Zones of a Street in Rotterdam. Archit. Sci. Rev. 2014, 57, 286–294.
  284. Tong, S.; Wong, N.H.; Tan, C.L.; Jusuf, S.K.; Ignatius, M.; Tan, E. Impact of Urban Morphology on Microclimate and Thermal Comfort in Northern China. Sol. Energy 2017, 155, 212–223.
  285. Huang, X.; Li, C.; Zhuang, Z. Analysis of Height-to-Width Ratio of Commercial Streets with Arcades Based on Sunshine Hours and Street Orientation. Appl. Sci. 2021, 11, 1706.
  286. Koopmans, S.; Ronda, R.; Steeneveld, G.-J.; Holtslag, A.A.M.; Klein Tank, A.M.G. Quantifying the Effect of Different Urban Planning Strategies on Heat Stress for Current and Future Climates in the Agglomeration of The Hague (The Netherlands). Atmosphere 2018, 9, 353.
  287. Liu, Y.; Li, Q.; Yang, L.; Mu, K.; Zhang, M.; Liu, J. Urban Heat Island Effects of Various Urban Morphologies under Regional Climate Conditions. Sci. Total Environ. 2020, 743, 140589.
  288. Ferguson, N. Complexity and Collapse: Empires on the Edge of Chaos. Foreign Aff. 2010, 89, 18.
  289. Kruis, N.J.; Heun, M.K. Analysis of the Performance of Earthship Housing in Various Global Climates. In Proceedings of the ES2007 Energy Sustainability, Long Beach, CA, USA, 27–30 June 2007; pp. 431–440.
  290. Sabján, T. Reconstructions of Medieval Pit-Houses. In The Rural House: From the Migration Period to the Oldest Still Standing Buildings, Proceedings of the Ruralia IV, Bad Bederkesa, Germany, 8–13 September 2001; Památky Archeologické; Archeologický ústav AV ČR: Prague, Czech Republic, 2002; Volume 15, pp. 320–332.
  291. Prinz, R.P. Hacking the Earthship: In Search of an Earth-Shelter That Works for Everybody; Archinia Press: Santa Fe, NM, USA, 2015; ISBN 0-9861155-1-7.
  292. Nývlt, V.; Musílek, J.; Čejka, J.; Stopka, O. The Study of Derinkuyu Underground City in Cappadocia Located in Pyroclastic Rock Materials. Procedia Eng. 2016, 161, 2253–2258.
  293. Kostigen, T. Humans v. Sky & Space. In Hacking Planet Earth. Technologies That Can Counteract Climate Change and Create a Better Future; Penguin Random House LLC: New York, USA, 2020; Volume 1, pp. 70–84.
  294. Bernstein, L.; Bosch, P.; Canziani, O.; Chen, Z.; Christ, R.; Riahi, K. IPCC, 2007: Climate Change 2007: Synthesis Report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change; IPCC: Geneva, Switzerland, 2008; 104p.
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