Enhancing Urban Microclimates: Potential Benefits of Greenery Strategies in a Semi-Arid Environment

Abstract

The emergence of sustainable development gives greenery an important role in urban planning, namely, by recognizing its environmental potential. However, the rapid urbanization that most cities have experienced in the absence of a sustainable urban policy has led to the establishment of urban realms dominated by manmade constructions. This research aims to evaluate the greening’s effect on the urban climate within the semi-arid city of Djelfa (Algeria) during summertime by assigning the most appropriate greenery strategy to ensure optimal thermal conditions. Using a numerical model built with the ENVI-met tool and validated through measurements in situ, four different scenarios are simulated, starting with the existing area and then changing the greenery strategies. The outputs include meteorological parameters and thermal comfort indices (PET and UTCI). The results show that the green area generates a cool island within the urban fabric, with the peak daytime air temperature being reduced by about 4.75 °C. Vegetation densification in the urban space has a higher cooling performance than greening buildings during the daytime. In the evening, the canopy effect of trees is lower and the wind velocity is reduced, which is the main driver in cooling the city at nighttime.

1. Introduction

With the growth of environmental concerns and awareness about the severity of rapid urbanization and pollution from human activities, including global warming, air pollution, and the urban heat island effect, environmental protection has risen to the top of local and global agendas [1]. In this context, urban vegetation occupies a prominent place in the scientific discourse and emerges as an integral component of sustainable development due to its various benefits, including those for the ecosystem, natural balance, and socio-economic services [2].

Urban areas typically experience warmer temperatures than rural areas, a phenomenon known as the “urban heat island (UHI) effect”. This difference is the most commonly deployed measure for reporting urban climate change in environmental studies [3]. The UHI effect not only reduces residents’ comfort but also increases energy consumption and, in some cases, poses health risks to vulnerable people [4,5,6]. The intensity of such a phenomenon depends on several factors, including climate, anthropogenic heat sources, urbanization, and planning choices. Unwise planning choices, such as the excessive use of artificial materials in urban surfaces, can exacerbate the UHI effect [7]. From a general perspective, urban greenery has the potential to mitigate the UHI effect by reducing air temperatures and enhancing urban microclimates [8]. However, the interaction between green structures and local environments requires careful examination due to the unique characteristics of each area.

Numerous studies have explored environmental issues associated with urban areas, including the mitigation of the urban heat island effect, considerations of thermal comfort, and various factors influencing the urban microclimate, using experimental and numerical methods. These studies have been conducted in diverse climatic contexts worldwide, including China [9,10], Canada [11], Hong Kong [12], Australia [13], Malaysia [14,15], Sri Lanka [16], and the Netherlands [17].

A survey by Edward et al. [12] in Hong Kong examined the cooling effects of greening and showed that appropriate greening significantly improved the urban microclimate, reducing the urban air temperature at ground level during the summer. They found that trees had a more pronounced impact on the thermal comfort of pedestrians close to the ground compared to grass surfaces, while green roofs proved to be less efficient. Nor et al. [15] conducted a tropical study investigating the effect of vegetation on the urban microclimate of residents, using GIS and ERDAS software to monitor climate change. Their results indicated a substantial reduction in land surface temperatures in vegetated areas.

Using the ENVI-met software v.5.1, Gaochuan et al. [18] evaluated the effect of green roofs’ morphological characteristics in a subtropical climate on pedestrian cooling. The model was calibrated to show a strong correlation between measured and simulated air temperature, indicating that the numerical model agreed well with the current environment. Thus, this tool was validated through field measurements and used by Mohammad et al. [14] to investigate the effect of urban forms on outdoor thermal comfort. They found that thermal comfort is greatly influenced by the duration of direct sunlight and the mean radiant temperature, which, in turn, is affected by urban morphology. Yupeng and Dian [9] examined typical urban planning styles in Xi’an, China, evaluating the impact of various urban typologies on urban climate change. They found that the thermal environment is altered by high-density residential construction. While this might be beneficial to reduce the UHI effect during the day, it poses challenges for heat dissipation at night. Indeed, previous studies, along with others not mentioned, also confirm the reliability and accuracy of ENVI-met model outputs, making it one of the preferred software tools for conducting simulations in a wide range of work.

Over the past few decades, Djelfa, like many Algerian cities, has experienced rapid urbanization and uncontrolled sprawl driven by population growth and rural migration. This has led to a chaotic situation as public authorities have focused on the construction of infrastructure, housing, and extensive facilities to meet the basic needs of the inhabitants while neglecting planning and urban management. As a result, the urban environments created lack sufficient environmental quality. This is particularly concerning in a region characterized by a semi-arid climate, where the quality of the urban environment is highly sought after.

Djelfa’s center represents the most vegetated part of the city. Older districts were built with vegetation as an essential component of the urban landscape, incorporating a variety of forms such as gardens, squares, and tree-lined streets. In contrast, the newer urban extensions allocate minimal space to vegetation, perpetuating the dominance of concrete in the city’s urban spaces at the expense of greenery.

Therefore, the purpose of this article is to study one of the primary benefits of green cover in the urban environment, namely, its impact on microclimate and outdoor comfort, particularly during hot periods, to identify suitable strategies for ensuring optimum climatic conditions. The study is carried out during a typical summer day in Djelfa, Algeria. Through this work, we aim to encourage city actors to embrace nature, promoting urban greening in areas currently dominated by concrete, and highlighting the inseparable relationship between green landscapes and sustainable development, with these natural elements occupying a central place in urban planning. Additionally, this investigation promotes sustainable urban development and advocates for the integration of digital tools in planning, setting a precedent for advancing both theory and practice in urban studies.

2. Materials and Methods

In this study, we chose numerical modeling using the ENVI-met software to simulate the effect of urban greening on the microclimate and, simultaneously, to optimize outdoor thermal comfort through green strategies. First, the ENVI-met model was validated through experimental measurements, followed by an exploration of various simulation scenarios, as illustrated in Figure 1.

2.1. The Study Area

Djelfa is a province in Algeria’s central high plateaus, situated 300 km south of the capital, Algiers (see Figure 2). Our study is conducted in the center of Djelfa, located between 2° and 5° east longitude and between 33° and 35° north latitude, at an elevation of 1138 m. According to the Köppen–Geiger climate classification system, Djelfa experiences a semi-arid climate characterized by a dry season extending from May to mid-September. The average maximum temperature throughout the year is 33.5 °C in July, while the minimum is 0.5 °C in January. Prevailing winds primarily originate from the northeast and northwest with oceanic and northern influences. Djelfa receives an average annual rainfall ranging from 250 to 300 mm but with significant year-to-year variations.

Over recent decades, the city has undergone remarkable population growth, increasing from 25,628 inhabitants in 1966 to 288,228 inhabitants in 2008, accounting for 26.4% of the province’s total population according to the last census. This rapid demographic expansion is attributable to the city’s local and regional attractiveness. Additionally, the city’s vegetation offers significant biological diversity, with a variety of plant and tree species that thrive in specific climatic and physical conditions.

For our research, we have chosen an area in the center of the city, known as the “beautiful shadow district”, encompassing 66,816 square meters (348 m × 192 m). This area is characterized by a compact urban environment composed mainly of residential buildings, houses, and villas with a few public buildings; moreover, it exhibits various urban forms, with building heights ranging from 3 m to 12 m. There is a variety of vegetation, including gardens (such as the Garden of Freedom), squares, and tree-lined streets. Trees play an integral role in the urban fabric, enhancing the urban living environment by providing coolness, shade, and aesthetic appeal (Figure 2). Our meticulous morphological analysis enables the collection of essential input data, covering architectural patterns, building materials, vegetation structures, and the road network. These data form the critical foundation upon which we construct comprehensive and realistic models.

2.2. Measurement of Meteorological Parameters

In this study, the meteorological measuring instrument used was a Testo 480 “0563 4800”. This device is equipped with digital probes for measuring wind speed, air temperature, and humidity. The instrument’s features are detailed in

Table 1. Meteorological measuring instruments.

Parameters	Symbol	Unit	Instrument	Range	Accuracy	Probe Type
Air temperature	Ta	°C	Testo 480 0563 4800	−20 to +70 °C	±0.5 °C	Part no. 0636 9743
Relative humidity	RH	%	Testo 480 0563 4800	0 to 100%RH	±(1.0%Rh +0.7% of mv) 0 to 90%RH ±(1.4%Rh +0.7% of mv) 90 to 100%RH	Part no. 0636 9743
Wind speed	Va	m/s	Testo 480 0563 4800	+0.10 to + 15.00 m/s	±(0.1 m/s +1.5% of mv)	Part no. 0635 9343

[19].

The field measurements included three meteorological parameters: air temperature (Ta), relative humidity (RH), and wind speed (Va). These measurements were conducted on a typical summer day, 29 July 2019, over a 15 h duration. The investigation focused on the hours when people are most likely to engage in outdoor activities, spanning from 7:00 am to 10:00 pm, with readings taken at two-hour intervals at ten representative points strategically distributed throughout the study area. To minimize the influence of surrounding surfaces on the recorded data [10], all instruments were installed 1.5 m above the ground and positioned at least one meter away from nearby buildings. Figure 3 illustrates the locations of the ten measurement points within the study area.

2.3. Building the ENVI-Met Model

In this study, the simulation was performed with the help of the ENVI-met model, which is among the most common dynamic simulation tools [20]. ENVI-met is a holistic three-dimensional modeling system founded on the basic laws of fluid and thermal dynamics. It is designed to analyze microscale thermal interactions within urban environments [21]. ENVI-met offers a typical spatial resolution of 0.5 m and a temporal resolution of 1–5 s. It can simulate microscale interactions between various urban surfaces, vegetation, and the atmosphere, allowing us to monitor the impact of small-scale urban design modifications on microclimate in diverse contexts [22,23].

Modeling with ENVI-met enables the incorporation of building materials, surface types, and vegetation to assess their effects on the local environment and contribute to the design of measures to mitigate factors, including urban heat stress. This numerical prognostic model can facilitate the planning of future urban environments that promote sustainable living conditions. Additionally, ENVI-met simulations produce various output data, including meteorological parameters such as air temperature, wind speed, relative humidity, and thermal comfort indices (PMV/PPD, PET, UTCI, and SET).

To create our three-dimensional models, we utilized the ENVI-met Suite program Spaces and digitized the basic model to reflect the actual conditions of the study area. Three additional scenarios were developed based on the first model, each involving changes in vegetation (

Table 2. Input data and initial settings for ENVI-met model.

Model Location
Name of location		Djelfa, Algeria
Position	Latitude (°)	34.68°
	Longitude (°)	3.26°
Model Geometry
Domaine size		348 m × 192 m
Model dimension		X-Grids = 190	Y-Grids = 108	Z-Grids = 30
Size of grid cell		dx = 2 m	dY = 2 m	dZ = 1 m
Model rotation out of grid from north		14°
Height of 3D model TOP		30 m
Highest point building + DFM		30 m
Difference model top to highest point		18 m > hmax		(hmax = 12 m)
Distance from buildings to model border		6–9 Grids		(4–8)

provides input data and basic settings for creating the 3D model).

For optimal results, following the recommendations outlined in the guidelines governing the boundary conditions of the software [24], the horizontal distance between buildings and the border should be zero or at least equal to the height of the closest building. Vertically, there should be sufficient space between the building/DEM top and the model border, with a distance at least equal to the highest element in the model, typically resulting in around 4–8 cells of open space at each border.

2.4. Simulation Setting

Using ENVI-guide, the simulation ran for 15 h, commencing at 7:00 am and concluding at 10:00 pm on a typical day, 29 July 2019. This period aligns with the times when people are most likely to engage in outdoor activities. The meteorological boundary conditions used included simply forcing, defining the various parameters (air temperature, relative humidity, and wind speed and direction) based on average meteorological data recorded by the Djelfa meteorological station, located approximately four kilometers from the study area. This station was supervised and operated by Algeria’s National Meteorological Center (CNM).

Table 3. Settings of the ENVI-met simulation.

Simulation Setting
Start date	19 July 2019
Star time	07:00
Total simulation time (h)	15 h
Air temperature (°C)	24-h cycle/CSV data
Relative humidity (%)	24-h cycle/CSV data
Wind speed (m/s)	1.46
Wind direction (°)	(N-O) 315
Roughness length (m)	0.1

outlines the input data and basic settings used in the simulation.

2.5. Simulation Scenarios

Four scenarios were simulated using ENVI-met (Figure 4). The investigation and comparison of the first two scenarios, “Scenario 01 and Scenario 02,” enable the evaluation of the impact of vegetation on urban microclimate and outdoor thermal comfort. The last two scenarios, “Scenario 03a and Scenario 04,” aim to further optimize microclimate conditions.

-

Scenario 01: original area

This primary scenario simulates the current conditions of the case study area, reflecting the existing microclimatic conditions. Utilizing the same meteorological data, topographical features, urban structures, and vegetation structure, we aimed to construct an accurate representation of the area as it currently exists. This approach enabled us to acquire a comprehensive understanding of the microclimate and thermal comfort parameters under the influence of natural environmental factors and existing urban elements.

-

Scenario 02: area without vegetation

In the second scenario, all greenery is removed from the study area, and grass is replaced with pavements. This is performed to further assess the direct influence of urban greenery on the environment. By observing and quantifying the alterations caused by the inclusion or exclusion of vegetation, we gain a better understanding of the essential role played by green elements in regulating the urban microclimate and outdoor thermal comfort.

-

Scenario 03: add more vegetation to urban space

To enhance thermal conditions in the urban space, the third scenario proposes increasing vegetation density by adding more trees and grass, resulting in an approximate 30% increase in vegetation cover.

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Scenario 04: greening the buildings

In the last scenario, increasing green surfaces by covering all the building surfaces with plants has been suggested. This vertical vegetation process is part of cities’ sustainable development approach.

2.6. The Output of Simulation: Index PET and UTCI

The ENVI-met Biomet post-processing tool calculates human thermal comfort indices based on the simulation data, providing various data required for this research, including meteorological variables such as air temperature, relative humidity, wind speed, and thermal comfort indices.

Two quantitative indices for assessing outdoor thermal comfort are utilized in this study. The first is the physiological equivalent temperature (PET), a suitable index for evaluating thermal comfort in urban microclimates [24]. Initially developed by Hoppe in 1999, the PET index is based on the Munich Energy Balance Model for Individuals (MEMI), which models the thermal conditions of the human body in a physiologically relevant manner. It goes beyond simple temperature measurements by considering complex interactions between climatic conditions and human responses, incorporating meteorological and thermophysiological parameters, clothing, and human activities [24].

The second index used is the universal thermal climate index (UTCI) [25,26], developed from the Fiala model and considered one of the most advanced thermophysiological models. This index formula sets itself apart from competing indices like the heat index or humidex by integrating a comprehensive range of parameters to provide a holistic assessment of thermal conditions. These factors include air temperature, mean radiant temperature, wind speed, humidity, physical activity, and clothing insulation. Moreover, it enables the prediction of thermal and local effects on the overall body.

2.7. Validation of ENVI-Met Simulations

In line with previous studies conducted for this purpose, we primarily used air temperature for comparing simulated and measured data, as it is a crucial parameter for assessing the thermal conditions of a specific location [27]. Variations in ambient air temperature (Ta) are influenced by factors such as the thermal properties of the surrounding natural and artificial surfaces, ventilation conditions, and the degree of shading in the environment. As shown in Figure 5a, a strong correlation was observed between the simulation results and the measurements taken at five representative points (from 8 am to 8 pm). The correlation coefficient (R²) ranged from 0.9369 to 0.9826, indicating a high level of agreement between the simulation outputs and the measured data.

To further ensure the accuracy of the ENVI-met simulation model, we conducted a calibration by calculating key metrics such as the Mean Absolute Deviation (MAD), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) [28]. These metrics are widely used to quantify the agreement between simulated and observed values. The calculations are defined as follows:

$$MAD=\frac{1}{n} {\sum }_{k=1}^n\left|T_{mes}-T_{sim}\right|$$

$$RMSE=\sqrt{\frac{1}{n} {\sum }_{k=1}^n{\left(T_{mes}-T_{sim}\right)}^2}$$

$$MAPE=\frac{1}{n} {\sum }_{k=1}^n\left(\frac{\left|T_{mes}-T_{sim}\right|}{T_{mes}}\right)\times 100\%$$

where:

-

$T_{mes}$ is air temperature measured in degrees Celsius (°C);

-

$T_{sim}$ is air temperature simulated in degrees Celsius (°C);

-

$n$ is the total number of data being considered.

As shown in the

Table 4. Calibration of ENVI-met model and MAD, RMSE, and MAPE.

Points		MAD (°C)	RMSE (°C)	MAPE (%)
1	dx = 150	0.89	0.96	2.81
	dy = 37
	k = 5
2	dx = 138	0.95	1.04	2.90
	dy = 70
	k = 5
3	dx = 126	0.68	0.82	2.08
	dy = 55
	k = 5
4	dx = 111	1.10	1.24	3.12
	dy = 60
	k = 5
5	dx = 120	1.42	1.56	4.13
	dy = 75
	k = 5

below and Figure 5b, the MAD values fell within the range from 0.68 to 1.42 °C, the RMSE ranged from 0.82 to 1.56 °C, and the MAPE varied from 2.08 to 4.13%. These results affirm that the numerical model’s accuracy is satisfactory and has been successfully validated.

3. Results and Discussion

3.1. Evaluation of the Impact of Vegetal on Microclimate and Outdoor Comfort in the First Scenario

3.1.1. Air Temperature

Based on the ENVI-met simulation results for the first scenario (the base case), air temperatures exhibited a range between 25.31 °C and 42.02 °C from 8:00 to 22:00, with the highest recorded temperature occurring at 15:00. The figures above illustrate the simulation outputs of three distinct periods of the day.

Figure 6 illustrates the significant temperature fluctuations throughout the day. The temperature value reaches more than 38.52 °C at noon and can rise above 40.70 °C at 15:00, registering 42.02 °C as the maximum value during the whole day. The ‘heat stress zone’ was consistently observed to occur in the most densely urbanized areas and those exposed to intense direct sunlight, notably at point 4.

Conversely, the coolest temperatures are typically found in proximity to vegetation, particularly within green spaces like Freedom Park and private gardens. Here, temperatures remain below 33.72 °C at noon and under 37.50 °C at 15:00. It is worth noting the subtle temperature disparity between points seven and eight in the same park. The slightly higher temperature at point 7 (by approximately 0.32 °C) can be attributed to its location on non-grassed ground and thus direct exposure to solar radiation. Even at the daytime temperature peak at 15:00, the recorded lowest temperature of 37.27 °C is within the greenest urban fabric, with a deviation of up to 4.75 °C.

As the evening progresses, the cooling effect of vegetation gradually diminishes. After sunset, and up to 22:00, the influence of vegetation becomes reversed. Figure 6 reveals that, by 21:00, the highest temperature values exceeding 30 °C are recorded within the garden and the most vegetated spaces.

3.1.2. Index PET and UTCI

A comprehensive analysis was conducted of outdoor thermal comfort in our survey area over a fifteen-hour period, from 08:00 to 22:00, using the PET and UTCI indices calculated through Biomet. The PET index showed a wide range, from 21.00 °C to 49.40 °C, while UTCI values showed variations between 21.54 °C and 43.35 °C, with the highest values being recorded at 15:00. Our findings, illustrated in Figure 7 and Figure 8, provide an overview of the thermal conditions prevailing throughout the main scenario area during three distinct periods: midday, peak time (15:00), and after sunset.

Notably, a ‘neutral heat stress zone’ emerges during the nocturnal hours following sunset, lasting for approximately an hour after sunrise. During this period, outdoor thermal conditions fall within a range that is generally neither uncomfortably hot nor cold, promoting a comfortable outdoor environment. Conversely, the ‘heat stress zone’ predominates during the majority of daylight hours, characterized by varying degrees of discomfort due to heat, including four discernible stress levels: slight, moderate, strong, and extreme.

Furthermore, the presence of greenery significantly improves outdoor thermal comfort ratings, with a more pronounced effect observed in densely vegetated areas. Particularly around midday, as portrayed in Figure 7 and Figure 8, a notable reduction in thermal stress was observed in these areas compared to the mineralized urban landscape, roads, and areas directly exposed to the sun’s radiant heat. The divergence ranges from 0.7 °C to 7.01 °C in terms of PET (Figure 7) values and from 1.2 °C to 6.06 °C in terms of UTCI values (Figure 8). At 15:00, the reduction in thermal stress is even more pronounced, with PET values recording a potential decrease of up to 8.98 °C (Figure 7) and UTCI values down by 6.44 °C (Figure 8). Remarkably, the private gardens and Freedom’s Park show the most favorable thermal conditions throughout the day. However, it seems that the influence of vegetation becomes less perceptible in the evening and may even be reversed after sunset. At 21:00, Figure 7 shows a potential increase of 6.45 °C in PET values; on the other hand, Figure 8 illustrates an increase of 4.38 °C in UTCI values.

3.2. Comparison between Scenario 01 and Scenario 02

Several factors affect the thermal environment of urban areas, including plants, building materials, and urban morphology, making it difficult to determine the effect of plants on thermal conditions. Therefore, an alternative scenario was proposed based on the original case without vegetation cover (Scenario 02). Comparing these scenarios over the same period allows for assessing the impact of vegetation. The presence or absence of the vegetation element mainly causes variation in the UTCI or PET index and meteorological parameters.

3.2.1. Temperature

In the second scenario, after removing all the cover plants from the model (Scenario 02), we obtained the following results, as shown in Figure 9. These results indicate an increase in air temperature and a heightened impact of the urban heat island (UHI) effect on the urban environment. Specifically, the ambient temperature becomes 3.2 °C higher at 15:00 when the plants have been eliminated and the grass has been replaced with pavement.

In the figure below, temperature comparisons between two scenarios, SC01 and SC02, present deviations in air temperature at ten points over a 15-h period from 08:00 to 22:00. The average air temperatures ranged from 36.91 °C to 38.65 °C for SC01 and 28.36 °C to 39.86 °C for SC02, with the highest temperature being recorded at 15:00.

We observed an increase in air temperature when we removed the vegetation cover from the urban area, as shown in Figure 10. This increase amounted to about 1.51 °C at 8:00, peaking at 2.00 °C around 11:00. Subsequently, the deviation slightly decreased to 1.21 °C by 15:00, with some fluctuations leading to a 1.04 °C increase at the 19th hour. At sunset, the air temperature became nearly identical in both scenarios. The effect of the tree canopy can be contrasted with its impact throughout the day, as we recorded an air temperature that is 0.04 °C lower in the second scenario at 22:00 (Figure 10b). The temperature difference between the two scenarios is greatest at 11 o’clock because this is when the solar radiation is strongest and the vegetation cover is absent. The temperature difference then decreases slightly in the afternoon as the sun begins to set and the urban environment releases heat energy. At sunset, the amount of solar radiation reaching the surface is very low; therefore, the temperature in both scenarios begins to equalize.

3.2.2. Index UTCI and PET

As shown in the following figures, the thermal comfort indexes were evaluated in the two scenarios, revealing an increase in both the PET and UTCI indexes in the second model compared to the base case. For example, at 15:00, PET values in the first scenario ranged from 40.42 °C to 49.40 °C, while, in the second scenario, these values were higher, ranging from 44.25 °C to 52.04 °C (see Figure 11). Furthermore, an increase in the UTCI index was recorded, with values ranging from 38.78 °C to 44.59 °C, compared to the values recorded in the base case, which ranged from 36.91 °C to 43.35 °C (see Figure 11).

Likewise, the results demonstrate that, in the model without vegetation, extreme heat stress pervades almost the entire urban fabric. This is in contrast to the base model, where heat stress had two levels: strong and extreme.

Furthermore, the deviation in comfort index values at ten points between two scenarios (SC01 and SC02) was analyzed during a 15-h period starting at 08:00 and ending at 22:00, with the results indicated in the figures below. In the initial case (Scenario 01), the average PET and UTCI values ranged from 25.04 °C to 43.99 °C and from 26.18 °C to 40.42 °C, respectively, with the maximum values being recorded at 15:00 (Figure 12a).

In contrast, the outputs in the second model without vegetation (Scenario 02) showed increased comfort index values throughout most of the day, as depicted in Figure 12a,b. From sunrise until 18:00, we observed an increase ranging between 1.92 °C and 3.72 °C for the PET index and between 1.40 °C and 2.72 °C for the UTCI index. At 19:00, the deviation reduced to 0.59 °C and 0.63 °C, respectively. However, after sunset, around 22:00, there was a decrease ranging from 1.64 °C to 2.08 °C in the PET index values and 1.11 °C to 1.71 °C in the UTCI index values. Based on the differences in the calculated thermal comfort indices, we can conclude that vegetation cover plays a significant role in reducing thermal stress in the urban fabric during the daytime.

These analyses have revealed the significant impact of vegetation cover on outdoor comfort indexes and temperature ranges, leading to the optimization of the urban environment’s thermal conditions through processes such as evapotranspiration and tree canopy effects [29,30]. Furthermore, it is evident that, in scenarios dominated by mineral surfaces, thermal stress increases notably in the absence of vegetation.

3.3. Optimization of the External Thermal Conditions

After establishing the reliability of our assumptions, the next phase of this work aims to further enhance the thermal conditions of the urban living environment by exploring alternative greening strategies. This includes intensifying tree coverage in the study area (Scenario 03) and conducting a vegetation process at the building scale (Scenario 04). Notably, the building envelope, representing the largest available surface in the urban fabric, offers the potential to incorporate vegetated walls and roofs.

The outcomes of the third (Figure 13a) and fourth (Figure 13b) scenarios were analyzed by comparing them with the base case depicted in Figure 6 and Figure 7. At 15:00, we observed a decrease in air temperature in Scenario 03, with values ranging from 35.86 °C to 41.42 °C. Most urban areas studied remained below 39.50 °C. Additionally, the PET and UTCI outdoor comfort indices decreased, mainly ranging from 38.25 °C to 45.90 °C and 37.60 °C to 41.50 °C, respectively. This suggests that increasing vegetation density (Scenario 03) contributes to enhanced cooling.

On the other hand, in Scenario 04, greening buildings showed a relatively smaller impact compared to the previous strategy. Simultaneously recorded values of the air temperature, PET index, and UTCI index ranged from 36.92 °C to 41.52 °C, 39.32 °C to 48.40 °C, and 36.28 °C to 43.25 °C, respectively. Furthermore, this impact was localized primarily near green walls and varied based on their proximity, predominantly affecting the built parts of the urban fabric, with limited influence on open spaces.

Figure 14a displays the variation in average air temperatures at ten points for scenarios SC03 and SC04 compared to the base case. In Scenario 03, we observed a reduction of approximately 0.5 °C at 8:00, which increased to 1.05 °C by 13:00. The cooling effect gradually decreased from 17:00 to the 20th hour, resulting in a reduction of 0.10 °C. At sunset, the air temperature approached the base case value, with minimal difference between SC01 and SC03. In contrast, Scenario 04 showed that the greening of buildings had a less pronounced cooling effect during the daytime compared to SC03 in the urban fabric, with a decrease ranging between 0.21 °C and 0.48 °C. However, in the evening, at 18:00, the highest temperature reduction was recorded, reaching up to 0.89 °C. From 20:00 to 22:00, the cooling effect decreased but remained more significant than in SC03, resulting in a temperature reduction of about 0.38 °C.

Figure 14b illustrates the variation in thermal comfort indexes. The PET and UTCI indicators exhibited changes consistent with temperature over time. Increasing the density of trees in the urban space provided greater outdoor comfort during the daytime compared to greening the buildings. In SC03, the deviation ranged from 0.78 °C to 2.16 °C for the PET index and from 0.54 °C to 1.52 °C for the UTCI index. This was approximately 1.86 °C and 1.37 °C higher than in SC04, respectively. Vegetation plays a vital role in improving thermal conditions in the living environment within the urban fabric. Our results confirm its impact on heat, with the extent of this effect depending on factors such as spatial arrangement, vegetation cover density, and the choice of vertical or horizontal greening processes.

4. Conclusions

The greening of cities emerges as one of the most effective strategies to mitigate environmental challenges arising from thermal imbalances that negatively affect the urban environment and the well-being of its residents. This research delves into the cooling effects of urban greening, employing the ENVI-met numerical model, which has been validated through in situ measurements. Our findings reveal that well-planned urban greening can positively influence the urban climate, even in semi-arid regions. It achieves this by significantly reducing both air temperatures. This microclimatic influence is primarily exerted through vegetation’s phenomena of evapotranspiration and shading. These processes create a protective canopy, preventing areas underneath from overheating due to solar radiation and exerting a noticeable impact on the surrounding areas. It is important to note, however, that green spaces may not consistently maintain moderate thermal conditions throughout the entire day. Instead, they play a vital role in reducing heat stress during daytime peak hours. An intriguing observation is that the cooling effect of vegetation gradually diminished as the evening progressed. After sunset, the influence of vegetation became reversed, with the highest temperature values exceeding 30 °C being recorded within the garden and in most vegetated spaces. This presents an interesting area for further exploration in future research.

Our exploration of various urban greening strategies has yielded valuable insights. The densification of vegetation intensifies the cooling effect during the day, offering enhanced shade and protection against the sun’s rays. This demonstrates a reduction of approximately 0.5 °C at 8:00, increasing to 1.05 °C by 13:00, showcasing a gradual cooling effect during the day. However, this effect diminishes as the evening approaches. Moreover, greening buildings had a less pronounced cooling effect than that of trees and grasses covering the ground during the daytime. Nevertheless, in the evening, green buildings showed a notable impact, with a temperature reduction of about 0.38 °C from 20:00 to 22:00, because, during the day, it limits sunlight on surfaces compared to concrete walls that could absorb heat and emit it during the evening and after sunset.

Furthermore, this study underscores the need for various stakeholders to reevaluate their current urban policies. It calls for the recognition of the necessity to develop comprehensive urban greening masterplans aimed at creating sustainable and green cities that promote both a local and global environmental balance. Simultaneously, integrating these modeling tools into urban interventions and planning processes paves the way for the establishment of favorable thermal conditions and facilitates the selection of the most suitable urban greening scenarios.