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Article

Exploring Thermal Discomfort during Mediterranean Heatwaves through Softscape and Hardscape ENVI-Met Simulation Scenarios

1
Department of Civil Engineering, University of West Attica, 12241 Egaleo, Greece
2
School of Applied Arts and Sustainable Design, Hellenic Open University, 26335 Patras, Greece
3
Department of Interior Architecture, University of West Attica, 12243 Egaleo, Greece
4
Department of Mechanical Engineering, University of West Attica, 12241 Egaleo, Greece
5
University of Tours, CEDEX 1, 37020 Tours, France
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(14), 6240; https://doi.org/10.3390/su16146240 (registering DOI)
Submission received: 21 June 2024 / Revised: 16 July 2024 / Accepted: 18 July 2024 / Published: 22 July 2024

Abstract

:
The study examines the effectiveness of various design strategies in alleviating the impacts of heatwaves in the Mediterranean region, focusing on a densely populated post-refugee urban area in Greece. By analyzing five different design scenarios, the study aims to identify the most efficient approach to mitigate thermal stress outdoors. The five design scenarios include changes in albedo values and coatings and alterations in the number and type of trees. The methodology includes a literature review, field work and microclimate simulations with the use of ENVI-met 5.6.1. The study evaluates ENVI-met data through potential air temperature, PET and UTCI analysis. The experimental results indicate that the most effective strategy is associated with urban greening. In particular, increasing tree cover considerably reduces air temperature, PET and UTCI values by 4 to 10 degrees Celsius. This finding highlights the potential of urban greening to enhance thermal comfort and combat heatwave effects. The research findings may be useful to landscape architects and urban designers, in light of a more climate-responsive urban design in the Mediterranean region. Future research may also assess the combined impact of multiple mitigation strategies on a larger scale, informing evidence-based policies for heatwave resilience.

1. Introduction

Global warming is associated with significant socio-economic and environmental challenges, affecting the quality of life in cities and urban areas. To address these challenges, the United Nations have established “Sustainable Development Goals” (SDGs, 2015), highlighting the need for urgent mitigation and adaptation measures [1,2]. In particular, Goal 13 focuses on climate action, as an effort to combat climate change. In line with SDG 13, urban planning policies try to incorporate sustainable interventions at various scales [3]. Efforts to achieve the SDGs are actively pursued in the Mediterranean region, which faces unique environmental, social and economic challenges [4]. Among these challenges, prolonged heatwaves act as major environmental stressors, having extensive impacts on society, the economy, the environment and public health [5,6]. It is important to note that the majority of Mediterranean heatwaves were recorded in the first decade of the 21st century [7]. Heatwaves often exceed local temperature norms (more than 35 °C to 40 °C) [8,9,10,11], persisting during night hours and posing significant health risks, particularly for vulnerable demographics such as the elderly, children and individuals with pre-existing medical condition [8,9,10,11]. Temperature fluctuations in summer are linked to meridional patterns, indicating a northward shift of current climate zones [4,12].
Urbanization in the Mediterranean region plays a pivotal role in climate change and energy consumption, as it is associated with the urban heat island effect (UHI) [9,13,14]. This leads to higher energy costs, potential blackouts and the disruption of daily life and economic activities [15,16]. Outdoor work becomes more challenging, outdoor recreational activities may be curtailed and tourism-related industries may suffer due to reduced visitor numbers and cancellations [17,18]. To enhance urban resilience, official policies employ a variety of strategies. From this point of view, landscape design is an essential tool in combating heatwaves and forming sustainable, resilient and livable cities [19]. The integration of softscape design elements holds the potential to ameliorate heatwave effects, enhancing the overall quality of life [20]. In this direction, relevant studies underscore the significance of the city block as a critical factor, in terms of sustainable urban planning and design [21].
However, there are evident discrepancies in green space distribution in many cities around the world, often correlating with socio-economic inequalities [22]. Wealthier neighborhoods tend to have more green spaces, which can lead to health disparities in deprived areas [23,24,25]. For the urban poor, who may lack adequate shelter or resources, the challenge of achieving thermal comfort outdoors becomes particularly pronounced [26,27]. Green gentrification poses significant social and economic challenges, as it may deteriorate inequalities, disrupt social networks and erode the cultural fabric of communities [28].
With an effort to focus on deprived areas, the authors have chosen a post-refugee urban area in Athens as a case study. The area was designed in the aftermath of the Asia Minor catastrophe of 1922. Numerous problems exist in the selected neighborhood, including energy poverty and poor urban infrastructures. The study evaluates the effect of different landscape design strategies to improve thermal discomfort during Mediterranean heatwaves. While the study presented in this manuscript is part of an academic program investigating the effects of heat waves in disadvantaged urban areas, it also explores the challenges of incorporating innovative technological approaches into engineering education, with a specific focus on sustainable urban planning. Particularly, it aims at providing concrete responses to one sustainable development goal (SDG 13), in terms of urban design in densely populated urban neighborhoods [1]. Following this introduction, which includes a brief explanation of key features in urban design as softscape and hardscape, as well as an overview of related work, Section 2 explains the materials and methods employed. The results are presented in Section 3. Section 4 provides further discussion comparing the study’s findings to other relevant studies. Finally, Section 5 concludes with findings that could pave the way for further analysis and research.

1.1. Elements of Landscape Design: Softscape and Hardscape

Urban design employs soft and hard landscape techniques, so as to enhance the aesthetics and functionality of outdoor spaces. Soft landscape design integrates living elements like soil, plants and trees to create natural, aesthetically pleasing environments [29]. It involves careful plant selection based on climate, soil, maintenance needs and visual appeal, while incorporating sustainable practices such as native species, water-efficient irrigation and low-maintenance schemes [30,31,32]. Hard landscape design includes non-living elements like pathways, patios, walls, fences and lighting. These elements serve structural purposes, define spaces and create functional zones [33]. High-albedo materials are often used in hardscape elements to reflect solar radiation, reducing heat absorption and mitigating the urban heat island effect [34]. Material selection in hardscaping considers durability, aesthetic appeal, cost and context compatibility [35]. On account of this classification, the current study experiments with softscape and hardscape techniques employed in the urban design of outdoor spaces. Thus, the ENVI-met simulation scenarios are clustered into two distinct categories: hardscape and softscape design approaches.
In particular, tree types are selected for their shading abilities to enhance outdoor thermal comfort. Given this, the current study employes different canopy shapes of adult trees in its ENVI-met simulation scenarios, so as to explore their shading effects during Mediterranean heatwaves. Overall, landscape design and architecture are crucial for creating sustainable, resilient and livable urban spaces, balancing aesthetic and functional needs while considering environmental impacts and community well-being.

1.2. Evaluation of Different Landscape Scenarios via ENVI-Met

The procedure of evaluating different design scenarios involves a thorough examination of the site’s climatic characteristics, encompassing factors such as temperature fluctuations, solar radiation exposure, prevailing wind patterns and levels of humidity [36]. This analysis points out locations susceptible to heat accumulation. Employing computer simulation models to predict thermal conditions in different landscape setups may benefit the comparison of different design scenarios [28]. ENVI-met software 5.6.1, focusing on microscale meteorological models, is able to provide a replication of microclimate dynamics, enabling the assessment of thermal comfort parameters [37]. This approach may facilitate further development towards sustainable and resilient cities in the era of climate change.
In academic discourse, the universal thermal climate index (UTCI) and the physiological equivalent temperature (PET) are both used to evaluate human thermal comfort or stress under different environmental conditions, such as temperature, wind, humidity and radiation. While UTCI offers a comprehensive assessment of outdoor thermal conditions by considering various factors influencing human temperature perception, PET calculates the air temperature that would result in the same physiological response as the current conditions [38,39,40]. Despite their methodological differences, both metrics aim to assess and improve thermal environments for human comfort. Existing literature has already demonstrated that the acceptable air temperature ranges between 17.0 and 21.0 °C during cooler periods and 26.0 and 32.0 °C during warmer periods of the year for cities like Athens [41]. Moreover, existing studies in the greater Athens region have delved into further analysis of thermal comfort employing UTCI and PET. Previous studies suggest that, particularly in Mediterranean cities, urban design efforts may need to prioritize addressing thermal discomfort during the prolonged and intense heat of the warmer periods of the year. The utilization of both PET and UTCI is based on their recognition as well-established bioclimatic indices frequently employed in various research studies. The thermal sensation scale of these indices has been modified to more accurately reflect the thermal conditions characteristic of Mediterranean climates. Adhering to the methodology outlined in previous studies [42], the authors determined that incorporating these two renowned bioclimatic indices to assess the thermal comfort conditions of the examined area would enhance the validity of the study’s findings (Table 1 and Table 2).
Despite evidence supporting the effectiveness of plantation as a primary method for enhancing thermal comfort in outdoor environments, its predominant utilization in urban spaces primarily serves aesthetic, utilitarian and recreational purposes in the majority of cases [42]. Focusing on various softscaping techniques, grass coverage mitigates reflected radiation, albeit with a restricted impact in open areas [44]. Trees have also proved effective in ameliorating thermal stress in outdoor spaces. The existing literature suggests that positioning trees strategically to facilitate air circulation and shading plays a pivotal role in mitigating both shortwave and long-wave radiation, preventing excessive solar absorption and minimizing heat retention within the built environment. Therefore, strategically distributing sparse vegetation within urban areas can maximize shading and enhance thermal comfort in hot and dry climates. A 50-year simulation study compared the impacts of green, black and white roofs. Both white and green roofs reduce urban regional temperatures by increasing urban albedo levels. Additionally, green roofs provide further benefits through evaporative cooling in the area [45].
In this context, the current research attempted to evaluate the environmental response of different design scenarios, through the lens of an architectural landscape perspective, in a city block located in a densely populated neighborhood. The study took place during Mediterranean heatwaves in July 2023. The aim of the research was to form a general guidelines tool to be applied in densely populated areas with a view to mitigating thermal discomfort, corresponding to previously mentioned SDGs. The research questions revolve around a comparison of the impact of different urban design techniques (softscape and hardscape) and are formed as follows:
  • Softscaping Techniques
RQ1: To what extent does the combination of softscaping techniques such as green roofs and extended soil and grass surfaces affect thermal discomfort during Mediterranean heatwaves?
RQ2: To what extent does the addition of adult trees alone (along alleyways and roads and in the middle of the block) affect thermal discomfort during Mediterranean heatwaves?
  • Hardscaping Techniques
RQ3: To what extent do high-albedo materials affect thermal discomfort during Mediterranean heatwaves?
In alignment with RQ1, the study took into consideration all horizontal surfaces that may contribute to albedo changes, including pavement blocks and building roofs. Green roof implementation was applied on the concrete roofs of the larger buildings of the block and not on the tiled roofs of the old refugee houses, with a view to keeping a realistic outlook towards future regeneration. RQ2 focuses on the role of adult trees alone in ameliorating thermal stress, in comparison to other combined softscaping strategies. RQ3 emphasizes the role of high-albedo materials in the context of a hardscaping design approach. Given the above-mentioned research questions, the study compares the ability of different design strategies to ameliorate heat stress during Mediterranean heatwaves, evaluating popular softscaping and hardscaping techniques.

2. Materials and Methods

The selected case study is part of the urban agglomeration of the capital of Greece, belonging to the Mediterranean climate zone. As part of Athens, the selected area experiences a hot Mediterranean/dry summer subtropical climate, classified as Csa according to the Köppen–Geiger classification [46]. This climate is characterized by mild temperatures with moderate seasonality. The neighborhood selected as the case study was established as a post-refugee urban settlement in the 1930s to accommodate Asia Minor refugees following the Asia Minor catastrophe of 1922 [47]. The former refugee enclave suffers today from poor housing conditions and energy poverty, being inhabited by vulnerable households comprising mostly elderly people and immigrants. All these refugee housing types share common attributes, such as a lack of insulation, a lack of central heating and, in many cases, a lack of air conditioners [48]. The surrounding outdoor spaces are poorly equipped and covered with conventional low-albedo materials. Nonetheless, the historical and cultural value of the area is rather high, since it narrates a significant chapter of Greek history in the 20th century. The effort towards holistic approaches, in terms of urban planning and design, encompass a combination of social, cultural and environmental factors [49].
For the purposes of this study, the authors opted to focus on one city block located within the interwar refugee enclave. The area of study possesses both opportunities and challenges. On the one hand, there is great potential because of the existence of intermediate open public spaces and dispersed pedestrian alleyways. On the other hand, the area has poor urban infrastructure. The cityscape of the selected area is characterized by residential buildings of different heights, volumes and scales; it is a mixture of outdated refugee housing stock and recent apartment buildings. Building heights in the area of study vary from 3 m to 15 m (Figure 1). Buildings on the eastern side of the block are higher than the rest, framing a barrier between the east side of the block and the rest of the neighborhood. All buildings are found at the perimeter of the block, creating a type of urban atrium that plays a critical role in access to sunlight and ventilation [50]. The width of the area is 76 m and the length is 50 m, covering an area of 3800 m2. The area of the open space is estimated to be 1400 m2. This covers 37% of the city block’s total area. From this 1400 m2, around 343 m2 are covered with soil and around 20.3 m2 with grass (Table 3). It is important to mention that there are differences in the quality and efficiency of insulation. Constructions after 1980 have moderate insulation, while the refugee houses have no insulation, neither on roofs nor on the walls.
The authors chose a day within the July 2023 heatwave to explore the levels of thermal discomfort in the outdoor spaces by implementing five different design scenarios, each corresponding to the research questions (RQs). Research includes a pre-field work stage, a field work stage and a post-field work stage (Figure 2). The authors chose to investigate the impact of surface albedo on thermal discomfort, as well as the effect of natural shading provided by trees. Given this, the five design scenarios were clustered into two main categories, softscape and hardscape, corresponding to the three research questions. The authors conducted field work in the selected neighborhood so as to identify the utility patterns of outdoor spaces. Data regarding high and low temperature, as well as wind speed and minimum and maximum relative humidity, were derived from the meteosearch website. According to pertinent literature, ENVI-met software is able to accurately simulate micrometeorological conditions and thermal comfort in the greater Athens region. The variable demonstrating the most successful simulation, as indicated by its attainment of the highest validation scores, was air temperature, a critical meteorological factor influencing individuals’ thermal perception. In particular, on 23 July, when all the ENVI-met 5.6.1 simulations ran, the highest temperature was recorded at 15:00, reaching up to 41.7 °C (approximately 42 Celsius degrees) and the lowest at 06:00, recorded as 30.9 °C. On the same day, the minimum relative humidity was calculated as 23% at 15:00 and the maximum relative humidity as 54% at 06:00. The wind direction was described as southerly and wind speed was documented as 4.6 km/h, which is equal to 1.27 m/s. For all five design scenarios including the baseline, a total duration of 48 h was used per simulation, starting at 05:00 a.m., using simple force meteorology at ENVI-met-core. All results are presented in local standard time (LST).
The five design scenarios include the following. Scenario 1 (baseline): the existing spatial configuration, low-albedo materials on existing hardscape elements, various trees of about 10 to 15 m height (Figure 3).
Combined Softscaping Techniques—Scenario 2: Scenario 2 corresponds to RQ1, putting emphasis on soil surfaces. The intermediate space in the city block was covered with softscape elements as grass and soil. Also, concrete paving blocks were replaced by wooden planks (0.80 albedo) suitable for outdoor spaces. Moreover, green roofs were applied to the tops of three large building (Figure 4). According to the field work, tenants of the smaller buildings make use of the roof top for various activities. Given this fact, the authors decided not to propose interventions that were not compatible to the needs of the citizens. The surrounding streets kept their low-albedo coatings.
Combined Softscaping Techniques–Scenario 3: Scenario 3 also corresponds to RQ1, putting emphasis on grass surfaces. In this scenario, emphasis is given to increasing grass surfaces. The central area of the city block was covered with grass, and perimetrical wooden planks were used. Two new conic trees, of 5 m heights, with a dense canopy and medium trunks, were added. Green roofs were implemented on the top of the three larger buildings, as in scenario 2. The surrounding streets kept their low-albedo coatings (Figure 5).
Adult trees as a Softscaping Technique—Scenario 4: Scenario 4 corresponds to RQ2, employing an increased number of adult trees in the middle of the block and an increased number of adult trees along surrounding streets and alleyways. For the purposes of scenario 4, the authors significantly increased the number of trees while keeping the existing landscape design of the block and the existing low-albedo surfaces (Figure 6).
Hardscaping Techniques—Scenario 5: Scenario 5 corresponds to RQ3, revolving around the impact of high-albedo coatings on thermal discomfort. It used the spatial arrangement of scenario 1 but applied high-albedo coatings on hardscape elements. The percentage of grass and soil were the same as in scenario 1. There were no green roofs in this design scenario, as it followed the general layout of the baseline scenario, as shown in Figure 7.
Employing the five above-mentioned design scenarios, the authors compared and contrasted PET, UTCI and potential air temperature (calculated at 1.4 m) in the area of study for three different times in the day; 10:00 in the morning, 15:00 in the afternoon and 20:00 in the evening. It is important to mention that the evening hours were chosen based on the local community’s evening gatherings during the summer period, which usually took place from 19:00 to 22:00, according to our field work. The peak hours were identified as being between 19:30 and 21:30 in the evening. The analysis of the results paid special attention to the central area of the city block, since it functions as a focal point for the social life of the neighborhood, facilitating social interaction and exchange. Moreover, the authors compared and contrasted all scenarios to the baseline scenario, through the use of the Leonardo application in ENVI-met 5.6.1. This comparison facilitates further discussion on the five scenarios in terms of thermal comfort/discomfort.

3. Results

3.1. Scenario 1: Existing Spatial Arrangement (Baseline)

During the July 2023 heatwave, and particularly on 23 July, temperatures were rather high in the area of study; the PET was classified as the category “Strong heat stress” (35–41 °C on the original scale and over 39 °C on the Mediterranean PET scale). This classification held during the morning and until the late afternoon. In the evening, a decrease in air temperature values was recorded, classifying the area into the “moderate heat stress” category according to the Mediterranean PET scale. To be more specific, at 10:00 in the morning, the east side of the block received direct sunlight, which contributed to a temperature rise to 39.94 °C. The intermediate space in the center of the block presented lower temperatures (37.2–38.3 °C) (Figure 8a). This was owed, to a large extent, to the shadows of the three large buildings that frame the northeast side of the block. In addition, the presence of soil, trees and grass in the central area of the block contributed to lower temperatures compared with the east side, which is covered by conventional low-albedo coatings (used/dirty gray pavement blocks). Similarly to potential air temperature, there were fluctuation patterns in PET and UTCI in the selected city block. To be more specific, PET values on the east side of the block were estimated to be between 48.14 and 50.59 °C, indicating strong heat stress according to the Mediterranean PET scale (Figure 8b). At the east side, lower PET values were observed among roadside trees, showing a decrease of about 2.5 °C. There were linear zones of lower PET values (37.8–44.28 °C) aligned with the shadows of the buildings. PET values in the central area of the selected city block varied between 46.2 and 53.93 °C (Figure 8b). The UTCI values followed similar spatial distributions to their PET equivalents. In particular, UTCI values were higher on the east side of the block (42.28–47.18 °C), lower among roadside vegetation (up to 42 °C) and lower among the shadows of buildings (35.56–39.8 °C) (Figure 8c). In the central area of the block, lower UTCI values were observed in certain enclaves covered with a combination of soil, grass and trees (39.8–43.5 °C) (Figure 8c). The upper corner of the central area on the western side of the block showed higher UTCI values of around 47.18 °C.
At 15:00, when the maximum air temperature and the minimum relative humidity were documented, air temperature values were higher (41.5–44.15 °C) on the western side of the city block, an area covered with conventional low-albedo coating (used/dirty pavement blocks) (Figure 9a). The east side of the block enjoyed lower air temperature values of around 39.7 °C, while the central part of the block presented an air temperature fluctuation between 40.6 and 41.9 °C. PET values were higher on the northern and western sides of the block (51.9–56.78 °C) and lower on the eastern and southeastern sides (41.98–43.85 °C) (Figure 9b). As depicted in Figure 9b, warm air penetrated from the pedestrian alley on the western side of the block, creating a linear warmer enclave that reached the central area. In general, PET values in the central area of the block varied between 41.98 and 47 °C. The area fell into the “strong heat stress” category according to the Mediterranean PET scale, with temperature values over 39 Celsius degrees. UTCI values showed a similar spatial distribution pattern compared to PET, with the western side showing higher UTCI values for this time of the day (51.58–53.09 °C) (Figure 9c). UTCI values in the central area of the block ranged between 39.6 and 45 °C.
In the evening, around 20:00 p.m., the potential air temperature values fluctuated between 36.22 and 38.1 °C, with an exception of a small cooler enclave found on the upper northeastern side of the block (around 36.12 °C) (Figure 10a). The surrounding streets on the western and southern sides present the highest air temperature values (of more than 37.9 °C), which is relevant to their low-albedo asphalt coating. The central area of the block recorded air temperature values between 36.7 and 37.16 °C. PET values were aligned with the spatial distribution patterns of potential air temperature, as well as the UTCI values. To be more specific, PET values on the surrounding western and southern streets were estimated to be between 38.9 and 40.26 °C, while lower values were found in the central and northeastern areas of the block (37.9–38.92 °C) (Figure 10b). The area fell into the “moderate heat stress” category according to the Mediterranean PET scale. As for UTCI, the surrounding western and southern streets recorded values between 36.47 and 37.15 °C, while the inner part of the block recorded lower values of around 36.24 °C (Figure 10c). It is important to mention that potential air temperaure, PET and UTCI values were lower in the parts of the block covered wih soil and grass.

3.2. Combined Softscaping Techniques—Scenario 2: Emphasis on Soil Surfaces

In design scenario 2, the authors explored potential differences in the microclimate conditions of the selected city block after increasing the soil and grass surface areas by 40.5 and 10%, respectively. In this scenario, typical concrete paving blocks were replaced by wooden planks, a popular paving material that plays a versatile and aesthetic role in landscape design, adding warmth, texture and functionality to outdoor spaces. At 10:00 in the morning, potential air temperature in the city block varied between 36.12 and 38.1 °C; however, temperatures were lower than in scenario 1 in the central area of the block, which is the focal point of the neighborhood (Figure 11a). To be more specific, the enclaves with the lower temperatures were larger in size than in scenario 1. In particular, in scenario 2, we observed a smoother spatial distribution of potential air temperature, which was estimated at around 38 °C, in the central area of the block. The central area of the block, which plays a pivotal role for the social life of the neighborhood, recorded temperature values from 37.7 to 38.91 °C. The spatial distribution of potential air temperature fluctuation patterns, PET and UTCI were similar to scenario 1. However, after delving into PET and UTCI analysis, the study results show that the central area of the block enjoyed relatively low values, compared to scenario 1. In scenario 2, PET values varied between 38.7 and 56.24 °C, with cooler enclaves found between buildings, among roadside trees and in clusters of vegetation, located in the central area of the block (Figure 11b). In scenario 1, PET values in the central part of the block at 10:00 were estimated to be between 37.8 and 58.59 °C, indicating a significant decrease. The lowest values were found between buildings and in clusters with vegetation and soil. Scenario 2 presented UTCI values ranging from 36.49 to 49.68 °C, with the lower values found in the shade of adjacent buildings (around 36.4, Figure 11c).
Evaluating scenario 2 (Figure 12a–c), at 15:00, which was the peak hour for maximum air temperature, the results showed an air temperature variation between 39.92 and 44.32 °C, with the western side being hotter than the rest of the block. The potential air temperature in the central part of the block fluctuated between 39.92 and 40.85 °C, while, in scenario I, temperature values ranged between 39.70 and 44.15 °C. PET values in scenario II showed similar spatial distribution patterns to scenario I, and the area fell again into the ‘strong heat stress category’. PET values in scenario II in the central part of the block were around 42.41 °C, while, in scenario I, they ranged between 42 and 45 °C. There was still a linear hotter enclave across the block, where hot air penetrated through the pedestrian alley. As in scenario I, the eastern and southern sides of the block had lower temperature and PET values, especially between buildings. As for UTCI, values in scenario II were found to be between 40.10 and 53.69 °C. The highest UTCI values were observed on the western and northern surrounding streets (48.36–49.51 °C). UTCI and PET values in the central part of the block were smoothly distributed, with large enclaves with consistent temperature values of around 42 and 40 °C, respectively (Figure 12b,c).
Delving into the potential air temperature at 20:00, in the selected city block, after applying the changes proposed by scenario II, the research results showed a temperature fluctuation between less than 36.25 and 38.11 °C (Figure 13a). Lower air temperatures were observed in the northern part of the block (around 36 °C), while higher temperatures were found in the lower eastern part and the southern part of the block. Similar spatial distribution patterns of air temperature, PET and UTCI values were documented. In the central part of the block, PET values varied between 38.78 and 40.45 °C, again classifying the area into the “strong heat stress” category (>39 °C), according to the Mediterranean PET scale (Figure 13b). UTCI values varied between 35.11 and 37.43 °C, with the higher values found on the outer southern and western sides of the block (around 37.16 °C). In the central part of the block, the UTCI values ranged between 35.68 and 36.31 °C (Figure 13c).

3.3. Combined Softscaping Techniques—Scenario 3: Emphasis on Grass Surfaces

In scenario 3, the authors explored the impact of a significant increase (223%) in grass surface area, adding also two trees of 5 m height in the central part of the city block. As the simulation results showed, at 10:00, air temperature values in the area of study varied between 36.69 and 40.56 °C (Figure 14a). At 10:00, in the central area of the block, which is the focal point for social interaction among tenants, air temperature values were estimated at around 37.43 and 38.5 °C. In scenario 1, the potential air temperature in the center of the block ranged between 37.4 and 38.3 °C, showing that there was no significant impact on thermal discomfort after applying grass over the central part of the block. As for scenario 2, where soil surfaces were prevalent in the central area of the block, temperature values varied from 37.7 to 38.91 °C, showing that scenario 3 offered a slight temperature decrease. PET values in scenario 3 at 10:00 fluctuated between 38.87 and 59.01 °C (Figure 14b). Lower PET values were identified between buildings (around 38 °C), while PET values in the central part of the block varied between 49.62 and 54.5 °C (strong heat stress). In scenario 1, PET values in the center of the block varied between 39.7 and 54.5 °C. As for UTCI, in scenario 3, the central area of the block presented a fluctuation of values between 43.27 and 48.87 °C. Lower UTCI values were found in the shade of buildings, while higher values were observed along the pedestrian alley located on the southwestern side of the block. Relatively cooler enclaves were associated with the existing trees in the middle of the block (Figure 14c). However, temperature values were still high, indicating strong heat stress.
Studying the microclimate conditions of the block at 15:00 in scenario 3, the potential air temperature values were higher on the northwest and the western sides of the block and especially in the surrounding streets (around 44 °C). The inner part of the block enjoyed lower temperatures, from 39.94 to 41.27 °C (Figure 15a). The spatial distribution patterns of PET were similar to the previous two design scenarios, and the values ranged from 42.38 to 42.93 °C in the central part of the block (Figure 15b). UTCI values in the central part of the block fluctuated around 40 °C (Figure 15c). Hot air entered the inner part of the block through the two alleys, creating hotter linear enclaves, as observed in the two previous scenarios. PET values in the central part of the block fluctuated around 42 °C, while the PET values of the surrounding streets were recorded as 56 to 57 °C. UTCI values in the central part of the block were estimated to be around 40.5 °C (strong heat stress), while higher values were documented along the northwest and western outer sides of the block. Air temperatures at 20:00 were lower, as expected, compared to daytime, estimated as 36.2 °C in the cooler northeast enclave and as around 37 °C in the central area of the block (Figure 16a). Streets adjacent to the southern and western sides had significantly higher air temperature values (Figure 16a). PET values on the northern outer side of the block were recorded as being less than 37.75 °C, defining a small enclave with moderate heat stress (Figure 16b). It is important to mention that, in this enclave, trees of 5m height are found. The inner central part of the block had PET values ranging from 38.5 to 38.75 °C, and was classified into the “moderate heat stress” category of the Mediterranean PET scale (Figure 17b). PET values along the two alleys and along the western and southern surrounding streets were higher, at about 40 to 40.4 °C (Figure 16b). UTCI values in the northern cooler enclave were estimated at around 35.10 °C, while, in the inner part of the block, they were at 36.31 °C. UTCI values in the surrounding streets (lower east, south and west sides) were even higher, reaching up to 37.4 °C (Figure 16c).

3.4. Increased Number of Adult Trees as a Softscaping Technique—Scenario 4

For the purposes of scenario 4, the authors significantly increased the number of trees, both in the central area of the block and along the surrounding streets. We also strategically placed trees at the entrance of the two alleyways. Starting with an evaluation of scenario 4 during morning hours, at 10:00, general improvements in all thermal stress indicators were recorded. To be more specific, as presented in Figure 17a, roadside trees decreased the air temperature values, compared to previous scenarios. Air temperature values in the central area of the block were less than 34.65 °C (Figure 17a). It is important to mention that this air temperature value is the lowest compared to the previous four scenarios. PET and UTCI values were considerably lower in all parts of the block, compared to data from the previous four scenarios. In particular, PET values in the central area of the block ranged between 35.76 and 36.40 °C, classifying the area into the “moderate heat stress” category for the first time during morning hours (Figure 17b). PET values were higher along the surrounding streets; however, the presence of the tree line managed to mitigate thermal discomfort by reducing the air temperature to around 43 °C. As we move away from the roadside trees, air temperature values rise significantly (Figure 17b). As in the previous scenarios, at 10:00, the east side of the block was hotter; however, the presence of the tree line improved temperature values along streets and alleyways. As for UTCI values, the central area of the block enjoyed the lowest values of all the previous scenarios, which fluctuated between 34 and 37 °C (Figure 17c). UTCI values in the outer part of the block were higher (Figure 17c) than the central area, but lower than in the other four scenarios.
Evaluating scenario 4, during peak hours for thermal stress and discomfort, improved temperature values were documented compared to the other four scenarios. Particularly, air temperature values at 15:00 in the central area of the block were around 38.4 °C. Temperature values along the surrounding streets were 2–3 °C higher (Figure 18a). PET at 15:00 also showed improved values compared to the other four scenarios. The central area of the block had a PET value of less than 38.8 °C (moderate heat stress), while the surrounding streets on the western side of the block had higher PET values (around 54.3 °C). Streets on the western side of the block received direct sunlight at 15:00, as in the previous scenarios, but PET values improved because of the added tree line (Figure 18b). UTCI values were again improved compared to the other four scenarios. Specifically, UTCI values in the central area of the block were estimated to be less than 37.55 °C. UTCI values on the western surrounding streets were calculated as approximately 49.18 °C. UTCI values on the outer western side of the block were higher than on the eastern side and in the central area, and were estimated as above 49 °C (Figure 18c).
Evaluating the microclimate conditions of scenario 4 at 20:00, a significant temperature decrease was observed, compared to the other four scenarios. To be more specific, the potential air temperature in the central area of the block ranged between 34.97 and 36 °C, which was the lowest value of the five scenarios (Figure 19a). PET and UTCI values in the central area of the block were around 36 and 34 °C, respectively (Figure 19b,c). PET and UTCI values were lower in the surrounding streets and along the alleyways than in the other four scenarios.

3.5. Hardscaping Techniques—Scenario 5: High-Albedo Materials

In design scenario 5, the authors replaced low-albedo coatings with high-albedo coatings, keeping the number of trees and the overall design untouched. As presented in Figure 20a, at 10:00, the potential air temperature values ranged from 35.36 to 39.28 °C. The highest values (of around 39 °C) were recorded on the eastern surrounding streets, which kept their low-albedo coatings. The majority of the city block enjoyed air temperature values of around 35.36 to 36.60 °C, which were the lower than in scenarios 1, 2 and 3. Higher temperature values could be traced along the adjacent eastern street, which received direct sunlight during that time of the day. High-albedo coatings, together with the existing soil, grass and tree arrangement, contributed to a sheltered area in the middle of the block, where the air temperature was consistently about 36 °C (Figure 20a). Thus, air temperature values were considerably lower than in previous design scenarios. As for PET, lower values were found between buildings, because of the shade cast, while PET values in the central part of the block reached up to 46.66 °C (strong heat stress, Figure 20b). UTCI values were lower between buildings (less than 38.72 °C) and higher on the inner northwest side of the block. The central area of the block recorded UTCI values from 38.72 to 45 °C (Figure 20c).
Studying the microclimatic conditions of the block at 15:00, the research results revealed a potential air temperature variation between 39.34 and 42.45 °C (Figure 21a), with the highest values found on the southern, western and northern outer sides of the block. The central area of the block presented temperature variation between 39.46 and 40.6 °C. The spatial distribution patterns of PET values were similar to the previous scenarios. PET values varied from 43.93 to 57.63 °C (strong heat stress), with the lowest values found in the inner part of the block (around 43 °C) and on the outer eastern side (Figure 21b). As far as UTCI is concerned, similar spatial distribution patterns were observed as in the previous scenarios and as for PET values. UTCI values in the center of the block were less than 40.87 °C, except for the hotter enclaves, because of hot air entering through the alleys (Figure 21c). These hotter linear enclaves were thinner compared to scenarios 1, 2 and 3, probably because of the presence of high-albedo coatings.
Observing air temperature values in the area at 20:00, a significant temperature decrease was recorded compared to morning and afternoon hours. The air temperature ranged between 35.98 and 38.02 °C (Figure 22a). There was a cooler area in the northern part of the block that fell into the “moderate heat stress” category (Figure 22a). The inner part of the block, the nodal point for the neighborhood, showed a mean air temperature of about 36.8 °C. PET values in the inner part of the block were documented as around 39.68 °C, while the outer west and south sides of the block were hotter (40.16 to 41.34 °C), because of their low-albedo coatings. UTCI values followed the spatial distribution of the PET values, ranging from 36.21 to 38.37 °C (Figure 22c). The inner part of the block had UTCI values of around 36 °C.

3.6. Comparing and Contrasting the Five Design Scenarios

Comparing design scenarios in ENVI-met involves setting up and simulating different urban configurations to analyze their impact on microclimatic conditions. This procedure may prove beneficial for urban designers for a better understanding of the best practices during unfavorable outdoor thermal conditions, as in the case of extreme temperature highs. In the current study, the authors chose to experiment with different softscaping and hardscaping techniques. By comparing different scenarios, stakeholders can make informed decisions to enhance environmental sustainability and livability in urban environments, given that simulation results facilitate further applications of sustainable design in outdoor urban spaces. As presented below in Table 4, scenario 4, which involved the considerable addition of new adult trees, documented better mean potential air temperature, mean PET and mean UTCI values, as found in surrounding streets and in the central part of the city block, at 10:00 a.m., 15:00 p.m. and 20:00 p.m. The mean values were calculated with the help of the presented diagrams in Section 3.1, Section 3.2, Section 3.3, Section 3.4 and Section 3.5. The combined softscaping techniques of scenarios 2 and 3 did not prove as beneficial as expected, retaining mean potential air temperature, mean PET and mean UTCI values similar to the baseline scenario (Table 4, scenario 2 and 3). As for scenario 5, which employed high-albedo coatings, there was a decrease in mean air temperature, mean PET and mean UTCI values, but this was not as significant as that found in scenario 4.
Delving into the comparison of the five scenarios, the authors also compared each design scenario to the existing arrangement, through the use of the Leonardo application in ENVI-met 5.6.1. The chosen key parameters for the comparison were potential air temperature, PET and UTCI at 15:00, when the highest levels of air temperature and the lowest levels of relative humidity were documented. The comparison between scenario 1(baseline) and scenario 4 (increased number of trees) shows a significant difference in potential air temperature, with absolute values varying from 0.36 °C to 2.77 °C. These air temperature differences are the highest compared to the rest of the design scenarios. Based on PET values, scenario 4 achieved the classification of the area into the “moderate heat stress” category during morning, afternoon and evening hours, while, in scenarios 2 and 3, the morning and afternoon hours fell into the “strong heat stress" category, as described in the previous chapters. In addition, in scenario 5 (high-albedo materials), morning hours were classified into the “moderate heat stress” category, but afternoon hours fell into the “strong heat stress” category, especially in the central area of the block, which was the focal point of this study. This means that scenario 5 did not prove as effective as scenario 4 during peak hours of thermal discomfort.
The comparison between scenario 2 (emphasis on soil surfaces) and baseline shows that there were only slight temperature differences, varying from 0.17 °C to 0.42 °C. Similar results were found through the comparison, in terms of absolute differences in potential air temperature between scenario 1 (baseline) and scenario 3 (emphasis on grass surfaces), values for which varied from 0.17 °C to 0.41 °C. The comparison between scenario 1 and scenario 5 (high-albedo coatings) indicated better results for absolute potential air temperature differences, ranging from 0.35 °C to 1.32 °C during the hours of high thermal discomfort. Taking into account these results, an increased number of trees facilitates the amelioration of heat stress during Mediterranean heatwaves, while the use of high-albedo coatings on hardscape elements may also improve thermal discomfort in outdoor spaces, but this has, however, a lower impact than increased adult tree vegetation.

4. Discussion

Academic discourse on urban landscape design spans across various disciplines including environmental science, landscape architecture, urban planning and public health [49]. With the increasing frequency and intensity of heatwaves due to climate change, there is growing interest in using softscaping as a strategy for climate change adaptation and resilience. Academic discourse explores the effectiveness of softscaping in mitigating heat-related risks, paving the way for resilient urban environments. However, not all softscape elements are effective for the mitigation of thermal stress and discomfort, especially during Mediterranean heatwaves. Given this, the current study, employing three research questions, attempted to evaluate the effectiveness of soil and grass surfaces (RQ1), high-albedo coatings (RQ2) and the addition of new trees (RQ3) in a given city block in Athens, Greece.
Starting with the evaluation of increased grass and soil surfaces (RQ1), the research findings are aligned with results from other studies, underscoring the limited effect of grass on thermal stress [51,52]. As indicated by this study’s results, even an increase of 223% of grass surface has a limited impact on thermal discomfort, since it does not affect direct incoming radiation. As found during the ENVI-met simulations, at 15:00, the temperature decrease varies from 0.17 to 0.41 °C in scenario 3, compared to scenario 1. During evening hours, when an expected temperature reduction is observed, there is a decrease of about 0.4 °C in scenario 3. Similar are the effects of soil surfaces on overall thermal discomfort, as ensured by comparing scenarios 2 and 3 to the baseline scenario (scenario 1). Moving forward to the evaluation of high-albedo coatings (RQ3), the study’s findings indicate that high-albedo materials may affect thermal discomfort, providing lower air temperature, PET and UTCI values. This finding is aligned with previous studies conducted in the Mediterranean region [53]. In particular, when comparing scenarios 1 and 5, differences in air temperature values range from 0.35 to 1.82 °C.
As far as the addition of new adult trees is concerned (RQ2), this proved to be the most effective strategy, affecting air temperature not only in the central area of the selected block but also on the surrounding streets and in the alleyways. This strategy proved to have a significant impact on thermal discomfort, providing protection from solar radiation. As mentioned in previous studies conducted in the metropolitan area of Athens, a limited number of trees plays a significant role in thermal discomfort during the summer period [41]. In this study, scenario 4 had improved values in all the examined categories. In fact, a potential decrease of 2.8 °C was recorded in the central part of the block, when comparing baseline scenario to scenario 4 at 15:00. PET values showed a significant decrease (4–10 °C) during morning hours, which continued during the afternoon and evening. UTCI values were also improved, compared to other strategies including grass and soil surfaces and high-albedo materials. It is important to mention that the geometry of the tree canopy plays an important role in terms of shading. The added trees have a heart-shaped canopy that provides a wider shaded area compared to the cylindric canopy that the existing trees have.
Apart from the impact on thermal discomfort, the increase in vegetation contributes to biophilic design principles, which emphasize the connection between humans and nature in the built environment. Studies demonstrate the positive effects of exposure to natural elements on mental health, stress reduction and overall well-being. Academic discourse explores how incorporating softscaping elements in outdoor spaces can enhance these benefits. Relevant studies also address issues of equity and social justice related to access to green spaces and thermal comfort. Taking into account all of the above, this research highlights the importance of ensuring that softscaping and UHI mitigation interventions benefit all members of the community, particularly those in underserved or marginalized areas. The selection of the specific case study neighborhood puts in the forefront the issue of degraded Asia Minor post-refugee urban settlements, found scattered in the urban fabric of Athens. The implementation of UHI mitigation strategies in areas with outdated housing reserve might function as a strategy to combat thermal comfort inequalities in urban areas. Moreover, the results of this study can be taken into consideration by landscape architects and urban planners in order to achieve the optimum cooling effect, when designing or reconstructing urban areas in cities with similar climatic characteristics. Therefore, the current findings may provide essential knowledge for the development of urban design guidelines under Mediterranean climate conditions.

5. Conclusions

Heatwaves within the Mediterranean region constitute a notable concern due to their frequent occurrence, heightened intensity and consequential implications for both human welfare and the ecological equilibrium. Such events manifest with regularity, particularly during the summer season, enduring for extended periods, often spanning several days to weeks, during which temperatures markedly surpass customary levels. These episodes are typified by extreme thermal conditions, frequently surpassing 40 degrees Celsius, thereby posing substantial health hazards, especially to susceptible demographics. The current study explored the environmental response of five different design scenarios during the July 2023 heatwave in the Mediterranean region. The five scenarios, including the baseline scenario, employed different strategies, such as an increase in grass and soil surface area, the application of high-albedo materials and the addition of new tree species. This case study from Greece was employed so as to delve into critical factors affecting thermal stress in outdoor areas. The area of study is a post-refugee urban neighborhood, densely populated. The selection of the case study underscores the necessity for interventions in outdoor spaces in deprived areas, characterized by high urban density, that suffer from energy poverty. Based on the research results, the effect of albedo changes—including high-albedo coatings—proved weaker compared to increasing tree species in mitigating thermal discomfort during heatwaves. From this point of view, interventions may put emphasis on increasing the number of trees, as this proved to be the most efficient of all the implemented strategies. In particular, a significant decrease in air temperature, PET and UTCI values was recorded, ranging between 4 and 10 °C. Further research in this direction may delve into the analysis of larger urban enclaves, so as to check the impact of combined UHI mitigation strategies in terms of thermal comfort during the hot summer period in the Mediterranean region.

Author Contributions

Conceptualization, E.T.; methodology, E.T., A.T. and Z.K.; software, E.T. and A.T.; validation, E.T., A.M. and A.T.; formal analysis, E.T.; investigation, E.T. and M.S.; resources, E.T. and M.S.; data curation, E.T.; writing—original draft preparation, E.T. and A.M.; writing—review and editing, Z.K., M.S. and S.J.; visualization, M.S. and Z.K.; supervision, E.T.; project administration, E.T., M.S. and Z.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

Data are contained within the article.

Acknowledgments

The authors would like to thank the Department of Land Survey Engineering and Geoinformatics for hosting the ENVI-met simulations and especially Georgios Chloupis for providing technical support.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

UNUnited Nations
SDGSustainable Development Goals
UTCIUniversal Thermal Climate Index
PETPhysiologically Equivalent Temperature
LSTLocal Standard Time
UHIUrban Heat Island

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Figure 1. Map and aerial view (google maps) of the selected case study, in the refugee enclave of the Kapodistrian Municipality of Nikaia; source of background AutoCAD map: Laboratory of Spatial Planning and GIS, School of Architecture NTUA, 2013.
Figure 1. Map and aerial view (google maps) of the selected case study, in the refugee enclave of the Kapodistrian Municipality of Nikaia; source of background AutoCAD map: Laboratory of Spatial Planning and GIS, School of Architecture NTUA, 2013.
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Figure 2. Methodology scheme.
Figure 2. Methodology scheme.
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Figure 3. Scenario 1 (baseline) 2D and 3D ENVI-met models.
Figure 3. Scenario 1 (baseline) 2D and 3D ENVI-met models.
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Figure 4. Scenario 2, ENVI-met model, with coating materials.
Figure 4. Scenario 2, ENVI-met model, with coating materials.
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Figure 5. Scenario 3, 2D and 3D ENVI-met models.
Figure 5. Scenario 3, 2D and 3D ENVI-met models.
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Figure 6. Scenario 4, 2D and 3D ENVI-met models.
Figure 6. Scenario 4, 2D and 3D ENVI-met models.
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Figure 7. Scenario 5, 2D and 3D ENVI-met models.
Figure 7. Scenario 5, 2D and 3D ENVI-met models.
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Figure 8. (a) Scenario 1, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., potential air temperature. (b) Scenario 1, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., PET. (c) Scenario 1, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., UTCI.
Figure 8. (a) Scenario 1, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., potential air temperature. (b) Scenario 1, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., PET. (c) Scenario 1, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., UTCI.
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Figure 9. (a) Scenario 1, Simulation using ENVI-met, 23 July 2023, potential air temperature, 15:00 p.m. (b) Scenario 1, Simulation using ENVI-met, 23 July 2023, PET, 15:00 p.m. (c) Scenario 1, Simulation using ENVI-met, 23 July 2023, UTCI, 15:00 p.m.
Figure 9. (a) Scenario 1, Simulation using ENVI-met, 23 July 2023, potential air temperature, 15:00 p.m. (b) Scenario 1, Simulation using ENVI-met, 23 July 2023, PET, 15:00 p.m. (c) Scenario 1, Simulation using ENVI-met, 23 July 2023, UTCI, 15:00 p.m.
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Figure 10. (a) Scenario 1, Simulation using ENVI-met, 23 July 2023, potential air temperature, 20:00 p.m. (b) Scenario 1, Simulation using ENVI-met, 23 July 2023 PET, 20:00 p.m. (c) Scenario 1, Simulation using ENVI-met, 23 July 2023, UTCI, 20:00 p.m.
Figure 10. (a) Scenario 1, Simulation using ENVI-met, 23 July 2023, potential air temperature, 20:00 p.m. (b) Scenario 1, Simulation using ENVI-met, 23 July 2023 PET, 20:00 p.m. (c) Scenario 1, Simulation using ENVI-met, 23 July 2023, UTCI, 20:00 p.m.
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Figure 11. (a) Scenario 2, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., potential air temperature. (b) Scenario 2, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., PET. (c) Scenario 2, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., UTCI.
Figure 11. (a) Scenario 2, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., potential air temperature. (b) Scenario 2, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., PET. (c) Scenario 2, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., UTCI.
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Figure 12. (a) Scenario 2, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., potential air temperature. (b) Scenario 2, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., PET. (c) Scenario 2, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., UTCI.
Figure 12. (a) Scenario 2, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., potential air temperature. (b) Scenario 2, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., PET. (c) Scenario 2, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., UTCI.
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Figure 13. (a) Scenario 2, Simulation using ENVI-met, 23 July 2023, 20:00 p.m., potential air temperature. (b) Scenario 2, Simulation using ENVI-met, 23 July 2023, 20:00 p.m., PET. (c) Scenario 2, Simulation using ENVI-met, 23 July 2023, 20:00 p.m., UTCI.
Figure 13. (a) Scenario 2, Simulation using ENVI-met, 23 July 2023, 20:00 p.m., potential air temperature. (b) Scenario 2, Simulation using ENVI-met, 23 July 2023, 20:00 p.m., PET. (c) Scenario 2, Simulation using ENVI-met, 23 July 2023, 20:00 p.m., UTCI.
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Figure 14. (a) Scenario 3, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., potential air temperature. (b) Scenario 3, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., PET. (c) Scenario 3, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., UTCI.
Figure 14. (a) Scenario 3, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., potential air temperature. (b) Scenario 3, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., PET. (c) Scenario 3, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., UTCI.
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Figure 15. (a) Scenario 3, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., potential air temperature. (b) Scenario 3, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., PET. (c) Scenario 3, Simulation using ENVI-23 July 2023, 15:00 p.m., UTCI.
Figure 15. (a) Scenario 3, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., potential air temperature. (b) Scenario 3, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., PET. (c) Scenario 3, Simulation using ENVI-23 July 2023, 15:00 p.m., UTCI.
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Figure 16. (a) Scenario 3, Simulation using ENVI-met, 23 July 2023, 20:00 p.m., potential air temperature. (b) Scenario 3, Simulation using ENVI-met, 23 July 2023, 20:00 p.m., PET. (c) Scenario 3, Simulation using ENVI-met, 23 July 2023, 20:00 p.m., UTCI.
Figure 16. (a) Scenario 3, Simulation using ENVI-met, 23 July 2023, 20:00 p.m., potential air temperature. (b) Scenario 3, Simulation using ENVI-met, 23 July 2023, 20:00 p.m., PET. (c) Scenario 3, Simulation using ENVI-met, 23 July 2023, 20:00 p.m., UTCI.
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Figure 17. (a) Scenario 4, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., potential air temperature. (b) Scenario 4, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., PET. (c) Scenario 4, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., UTCI.
Figure 17. (a) Scenario 4, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., potential air temperature. (b) Scenario 4, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., PET. (c) Scenario 4, Simulation using ENVI-met, 23 July 2023, 10:00 a.m., UTCI.
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Figure 18. (a)Scenario 4, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., potential air temperature. (b) Scenario 4, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., PET. (c) Scenario 4, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., UTCI.
Figure 18. (a)Scenario 4, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., potential air temperature. (b) Scenario 4, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., PET. (c) Scenario 4, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., UTCI.
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Figure 19. (a) Scenario 4, Simulation using ENVI-met, 23 July 2023, 20:00 p.m., potential air temperature. (b) Scenario 4, Simulation using ENVI-met, 23 July 2023, 20:00 p.m., PET. (c) Scenario 4, Simulation using ENVI-met, 23 July 2023, 20:00 p.m., UTCI.
Figure 19. (a) Scenario 4, Simulation using ENVI-met, 23 July 2023, 20:00 p.m., potential air temperature. (b) Scenario 4, Simulation using ENVI-met, 23 July 2023, 20:00 p.m., PET. (c) Scenario 4, Simulation using ENVI-met, 23 July 2023, 20:00 p.m., UTCI.
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Figure 20. (a) Scenario 5, Simulation using ENVI-met, 23 July 2023, 10:00 p.m., potential air temperature. (b) Scenario 5, Simulation using ENVI-met, 23 July 2023, 10:00 p.m., PET. (c) Scenario 5, Simulation using ENVI-met, 23 July 2023, 10:00 p.m., UTCI.
Figure 20. (a) Scenario 5, Simulation using ENVI-met, 23 July 2023, 10:00 p.m., potential air temperature. (b) Scenario 5, Simulation using ENVI-met, 23 July 2023, 10:00 p.m., PET. (c) Scenario 5, Simulation using ENVI-met, 23 July 2023, 10:00 p.m., UTCI.
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Figure 21. (a) Scenario 5, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., potential air temperature. (b) Scenario 5, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., PET. (c) Scenario 5, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., UTCI.
Figure 21. (a) Scenario 5, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., potential air temperature. (b) Scenario 5, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., PET. (c) Scenario 5, Simulation using ENVI-met, 23 July 2023, 15:00 p.m., UTCI.
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Figure 22. (a) Simulation using ENVI-met, 23 July 2023, 20:00 p.m., potential air temperature. (b) Simulation using ENVI-met, 23 July 2023, 20:00 p.m., PET. (c) Simulation using ENVI-met, 23 July 2023, 20:00 p.m., UTCI.
Figure 22. (a) Simulation using ENVI-met, 23 July 2023, 20:00 p.m., potential air temperature. (b) Simulation using ENVI-met, 23 July 2023, 20:00 p.m., PET. (c) Simulation using ENVI-met, 23 July 2023, 20:00 p.m., UTCI.
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Table 1. PET scale original and Mediterranean.
Table 1. PET scale original and Mediterranean.
PET (°C)Thermal SensationHeat Stress AssessmentPET (°C)
Original Scale Mediterranean Scale
<4.1Very coldExtreme cold stress
4.1–8.0ColdStrong cold stress<0.7
8.1–13.0CoolModerate cold stress0.7–5.2
13.1–18.0Slightly coolSlight cold stress5.2–14.8
18.1–23.0ComfortableNo thermal stress14.8–23.8
23.1–29.0Slightly warmSlight heat stress23.8–31.2
29.1–35.0WarmModerate heat stress31.2–39.1
35.1–41.0HotStrong heat stress>39.1
>41.0Very hotExtreme heat stress
Table 2. UTCI scale original and Mediterranean [41,43].
Table 2. UTCI scale original and Mediterranean [41,43].
UTCI (°C) Heat Stress Assessment
Original ScaleMediterranean Scale
<−40.0<20.2Extreme cold stress
−27.0 to −40.020.2–21.5Very strong cold stress
−27.0 to −13.021.5–23.0Strong cold stress
−13.0–0.023–24.6Moderate cold stress
−9.024.6–27.0Slight cold stress
9.0–26.027.0–34.0 No thermal stress
26.0–32.034.0–36.8 Moderate heat stress
32.0–38.036.8–38.3Strong heat stress
38.0–46.038.3–39.9Very strong heat stress
>46>39.9Extreme heat stress
Table 3. The five landscape design scenarios, authors’ work.
Table 3. The five landscape design scenarios, authors’ work.
ScenariosGrass (m2)%Soil (m2)%Hardsc. (m2)%Trees (Nr)
5 m h15 m h
Scenario 120.31.4534324.5103674213
Scenario 220514.6084560.335025213
Scenario 3109778.30705233.816.7233
Scenario 420.31.4534324.5103674213
Scenario 520.31.4534324.51036744710
Table 4. Comparison of all five scenarios, mean potential air temperature, mean PET and UTCI values for all times; authors’ work.
Table 4. Comparison of all five scenarios, mean potential air temperature, mean PET and UTCI values for all times; authors’ work.
10:00 a.m.Mean Air Temp. °CMean PET °CMean UTCI °C
StreetsInner BlockStreetsInner BlockStreetsInner Block
Scenario 138.1037.7049.6350.8145.1940.80
Scenario 239.1038.0042.7542.0048.3042.15
Scenario 338.4037.1054.5047.2047.8041.90
Scenario 437.20<34.9047.6040.0042.5036.01
Scenario 536.9036.0054.0044.5045.0039.20
15:00 p.m.Mean air temp. °CMean PETMean UTCI
StreetsInner blockStreetsInner blockStreetsInner block
Scenario 141.3040.0049.843.8047.4042.10
Scenario 241.0040.0049.4042.0047.0039.50
Scenario 342.0040.0050.2545.0049.1542.00
Scenario 440.00<38.0046.45<38.9044.00<36.92
Scenario 540.6039.4049.0043.5046.6038.50
20:00 p.m.Mean air temp. °CMean PETMean UTCI
StreetsInner blockStreetsInner blockstreetsInner block
Scenario 136.9036.4038.9038.3536.2235.13
Scenario 236.8036.1038.2037.0035.7034.70
Scenario 336.5036.0040.1539.2037.4036.40
Scenario 435.7034.7537.55<35.9034.4533.80
Scenario 536.7036.0039.0037.3035.3934.60
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Tousi, E.; Tseliou, A.; Mela, A.; Sinou, M.; Kanetaki, Z.; Jacques, S. Exploring Thermal Discomfort during Mediterranean Heatwaves through Softscape and Hardscape ENVI-Met Simulation Scenarios. Sustainability 2024, 16, 6240. https://doi.org/10.3390/su16146240

AMA Style

Tousi E, Tseliou A, Mela A, Sinou M, Kanetaki Z, Jacques S. Exploring Thermal Discomfort during Mediterranean Heatwaves through Softscape and Hardscape ENVI-Met Simulation Scenarios. Sustainability. 2024; 16(14):6240. https://doi.org/10.3390/su16146240

Chicago/Turabian Style

Tousi, Evgenia, Areti Tseliou, Athina Mela, Maria Sinou, Zoe Kanetaki, and Sébastien Jacques. 2024. "Exploring Thermal Discomfort during Mediterranean Heatwaves through Softscape and Hardscape ENVI-Met Simulation Scenarios" Sustainability 16, no. 14: 6240. https://doi.org/10.3390/su16146240

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