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 [
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 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 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.
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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.
- -
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 (R
2) 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:
where:
- -
is air temperature measured in degrees Celsius (°C);
- -
is air temperature simulated in degrees Celsius (°C);
- -
is the total number of data being considered.
As shown in the
Table 4 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.
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.