Effects of natural light on improving the lighting and energy efficiency of buildings: toward low energy consumption and CO₂ emission

Abstract

Visual information acquisition is essential for our daily lives, with vision relying on the presence of light. Lighting systems serve the fundamental purpose of enabling vision. This study aims to contribute to sustainable architectural design by emphasizing the efficient utilization of natural daylight. Specifically, the design of skylights or light wells in low–lateral-area, deep-depth structures is of significant importance. While current design criteria consider skylight dimensions and the skylight-to-building height ratio, these factors alone may not suffice for optimal skylight design. To achieve an appropriate lighting and architectural design for such structures, it is essential to evaluate the factors influencing the required amount of daylight on different floors. This study aims to investigate the impact of skylights and light wells on the energy consumption and CO₂ emissions of a four-storey building located in Hail, Kingdom of Saudi Arabia. The physical parameters of skylights and light wells were analyzed, taking into account various aspects that affect the amount of light reaching different levels. The findings highlight the significant influence of skylight size on the light reaching the building’s floors. For square skylights, reducing the well index (increasing skylight size) exponentially increases the daylight factor. Furthermore, this study evaluates the annual energy consumption and carbon dioxide emissions of the building, considering the daylighting factor. The results demonstrate that skylights contribute to increased solar heat gain, thermal conductance, and artificial lighting efficiency. Notably, as the lighting factor of the building increases from 3% to 6%, there is an annual decrease of 3% in CO₂ emissions.

1 INTRODUCTION

The majority of the information we acquire from our environment is visual in nature [1]. Vision is the most crucial human sense, and without light, humans cannot see. The lighting system’s primary function is to allow us to see [2]. In general, it is believed that improper lighting prevents the human visual system from operating at peak efficiency [3]. If a person is exposed to insufficient lighting, real information may be lost and the likelihood of errors among the workforce rises [4]. Additionally, in such a condition, weak visual signals cause images to be produced for a lengthy time [5]. Appropriate lighting throughout the day can boost human function, increase secretion of melatonin, lower body temperature at night, and eventually improve the quality of sleep, therefore it is apparent that proper lighting is essential in professional environments [6]. Lighting intensity is one of the most important concepts in lighting engineering, as it is the basis for measuring the amount of light on visible surfaces in places and businesses, and on which lighting standards are formulated [7]. Clearly, our most significant sense is vision, and for this reason, lighting engineering is of vital importance. Lighting engineering defines the definitions of lighting and its concepts, as well as the quantitative and qualitative limits of their concepts and the means of their provision. Consequently, training in lighting engineering is necessary [8]. The utilization of a skylight positioned on the roof of an atrium is a common practice in commercial malls, as it serves as an effective means of illuminating the central area of the structure. Nevertheless, the ingress of solar radiation and its accompanying heat into the building, alongside the presence of daylight, can result in an excessive cooling load [9].

Due to the current environmental and energy crises and CO₂ emissions, the focus of numerous scientific disciplines has shifted to the utilization of clean energy [10–14]. One of the most important sources of renewable energy in recent years has been the sun, which has been introduced in a variety of methods, one of which has received less attention than others, the use of sunlight to illuminate the interior areas of buildings [15–18]. Natural daylight and its efficient utilization are among the variables that reduce energy consumption and contribute to sustainable architecture design [19–21]. The historical significance of natural light in the development of architecture cannot be overlooked. Temperature, location, and access to natural light have always been essential architectural considerations for architects [22, 23]. Existing records in the field of utilizing daylight in accordance with varying climates and building styles are diverse [24]. By evaluating and comparing how light is dispersed by different skylights in rooms, it appears that the space with a skylight in the ceiling has better conditions in terms of brightness and daylong light homogeneity [25].

The incorporation of light wells as apertures in the flooring to facilitate the propagation and dispersion of natural lighting was accompanied by the inclusion of skylights or similar adaptations. The study investigated the geometric properties of light wells in relation to their impact on daylighting and energy efficiency. Previous research has focused on the influence of size alone, while others have considered a combination of size, height, orientation, and wall vertical angle [26–28]. The dimensions, elevation, and alignment of light wells are significant factors in the utilization of the stack effect for natural ventilation, alongside their role in providing daylighting [29]. The study investigated the utilization of horizontal gaps linked to light wells as a means of achieving buoyancy-driven natural ventilation, taking into account the influence of external wind directions [30].

Wright et al. [31] researched the optimum amount of natural light and lighting for daily tasks in interior environments. Al-Obaidi et al. [32] examined the influence of the quality of daylight and the energy received from the glass materials of skylights at different hours on the interior atmosphere of a building. They compared glass and translucent plastic materials in this study. It appears that plastic transmissive materials are better insulated than glass materials in terms of thermal transfer coefficient and transparency, if two or three layers of these materials are required to apply insulation in glass materials; which is also not cost-effective. However, materials should be selected and implemented based on the location and type of space. Bakr et al. [33] studied the existing guidelines for the design of skylights in Egypt, and based on the sky circumstances in that region, they tested and assessed numerous variables in the skylights by adjusting their relative position. It was determined that the maximum light received was between the angles of 0 and 90 degrees to the north and the minimum light received was between the angles of 45 and 135 degrees. Furthermore, by examining the width of the skylights, it was determined that a width of less than 4 meters has no effect on the proper reception of lighting, whereas a width of greater than 6 meters causes glare on the fourth floor of the building. Goharian et al. [34] developed and refined daylight assist devices for light wells. These devices were designed to efficiently redirect light from the sky towards the bottom of the well, and afterwards emit it into the intended area. The study design yields a complete and standardized answer that may be applied across various latitudes. In their study, Goharian et al. [35] conducted a thorough examination of the light-well arrangement. They employed a hierarchical approach to identify potential issues and determine the benefits of optimizing the configuration to effectively utilize direct sunlight. A complete technique has been established to standardize the optimization solution by examining five latitudes that encompass low, middle, and high latitudes.

In light of environmental crises and the trend of utilizing clean energy in various disciplines, including architecture, one of the most significant actions that can be taken is maximizing the use of natural light to reduce the amount of electricity used for indoor lighting. It is important to note that in many instances, structures with limited lateral area and high depth cannot be avoided, and in terms of lighting, daylight must be taken advantage of through ceiling skylights, which poses a difficulty. The adequacy of these dimensions and areas in supplying the necessary light design for the spaces based on the land’s occupation level is unclear, and there is no published formula to compute this ratio. Consequently, the primary objective of this study is to conduct a scientific investigation to determine the correct and fundamental criteria for the dimensions of ceiling skylights based on scientific documentation, so that it can influence the reduction of electrical energy consumption in residential buildings. A parametric investigation of how daylight is received from ceiling skylights in a four-storey residential building in Hail, Saudi Arabia, will be addressed. These parameters include skylight dimensions, lighting well dimensions, reflective properties of wall surfaces and floor window beetles, window dimensions, skylight cap position, etc., in four- and three-way skylights, and will be done in a wide range of dimensions, shapes, and reflection coefficients of surfaces. Meanwhile, the effect of the daylight factor on building energy consumption and CO₂ emissions will be evaluated in the aforementioned building.

2 MATERIALS AND MEHODS

As a light source, a horizontal window is nearly three times as effective as a vertical window [36]. A roof window can increase the amount of light that enters a room, but a skylight with a well-designed light well will provide uniform illumination [37]. Moreover, the skylight distributes light more equitably and is less affected by interior and exterior obstacles [38]. Daylight factor is expressed as the ratio between the light intensity on a given surface and the light intensity on a horizontal surface in an unobstructed outdoor environment, which is determined by Eq. 1 [39].

$$ \begin{equation} \mathrm{DF}=\frac{{\mathrm{E}}_{\mathrm{i}}}{{\mathrm{E}}_0}\times 100\left(\%\right) \end{equation}$$

(1)

where E_i is the intensity of light on a certain surface inside and E₀ is simultaneously the intensity of light in the external environment on a horizontal surface in an unobstructed place. For a particular situation, this coefficient is constant under wide variations of outdoor lighting conditions. The higher the daylight factor, the better; but the recommended amount for visual work is about 1.5 up to 2% and for relatively difficult jobs about 2.5 to 4%.

2.1 Light well

The shape of the light well the inner area of the skylight, which is usually in the shape of a rectangular cube, is known as the light well [40]. The lighting performance of a light well depends exactly on its geometric ratio. The shape of a light well can be described by a number [41]. For example, the well index, which expresses the relationship between the level of light transmission and skylights (Eq. 2)

$$ \begin{equation} {w}_i=\frac{\mathrm{H}\left(\mathrm{W}+\mathrm{L}\right)}{2\mathrm{WL}}. \end{equation}$$

(2)

Where W, H and L, are the width, height, and length of the light well, respectively. This parameter allows comparisons to be made between several forms of skylights associated with a building of a certain height. For example, for a skylight with a fixed height and a square cross section, w_i is appropriate; that is, by increasing the side of the skylight to a constant height, w_i decreases, and in general, increasing w_i means that the well is deeper or its opening is reduced. A schematic of a building with a light well is shown in Fig. 1.

Figure 1

Schematic representation of a building featuring a light well.

2.2 Lighting definition and calculations

Here is the definition of the subject and an example of lighting calculations. For lighting calculations, a four-storey building was considered with a skylight that transmits daylight through the light well and through the window to the spaces adjacent to the floors. The purpose is to parametrically study the components affecting the amount of light that enters the floors of the building.

The height of each floor is 3.2 meters, the depth of each room is 5 meters, and the windows on each floor are 1 meter above the room’s floor. All surfaces’ reflective properties are diffused, and calculations for the three positions of four- and three-way skylights are based on the daylight factor. Skylight and windows pass coefficient: τ_g = 0.85, The reflection coefficient of the wall and ceiling is ρ_w = 0.75 and the reflection coefficient of the room floor and skylight: ρ_f = 0.45. Floor windows are considered to be meters higher. The daylight factor means the average points on the floor of the room and is calculated using a method known as the radiosity method with point-to-point algorithm in this study. Surfaces are separated into a network of different pieces in the radiosity approach, assuming that each piece of surface is a lambert reflector, meaning it has a constant brightness and is directionless. The law of cosine amber can be used to compute the flux that exits each piece of the surface; as a result, each piece of the surface receives light and then reflects it back into space. The operation is repeated until all of the reflected fluxes have been absorbed. In summary, assuming energy balance, this method calculates how much light is reflected from a given surface due to energy exchange with neighboring surfaces. In short, this method calculates how much light is reflected from a certain surface due to the exchange of energy with other surfaces, assuming energy balance (Eq. 3). For a closed chamber, assuming energy balance, we can write:

$$ \begin{equation} {\mathrm{j}}_{\mathrm{i}}\mathrm{dA}{\mathrm{A}}_{\mathrm{i}}={\mathrm{E}}_{\mathrm{i}}\mathrm{dA}{\mathrm{A}}_{\mathrm{i}}+{\rho}_{\mathrm{i}}{\int}_{{\mathrm{A}}_{\mathrm{j}}}\kern0.1em {\mathrm{F}}_{\mathrm{i}\mathrm{j}}{\mathrm{j}}_{\mathrm{j}}\mathrm{dA}{\mathrm{j}}_{\mathrm{j}}, \end{equation}$$

(3)

Figure 2

Comparison between the present study and a) Laouadi and Atif [42] and b) Littlefair [43].

So that for radiosity, E is the optical energy emitted per unit area and per unit time, ρ is the reflection coefficient, F_ij is the visibility coefficient, i the fraction of energy that leaves the particle surface and reaches level 1, and A is the cross section due to equilibrium. Energy is a reciprocal Eq. 4:

$$ \begin{equation} {\mathrm{F}}_{\mathrm{i}\mathrm{j}}{\mathrm{dA}}_{\mathrm{i}}={\mathrm{F}}_{\mathrm{j}\mathrm{i}}\mathrm{d}{\mathrm{A}}_{\mathrm{j}} \end{equation}$$

(4)

By applying it to Eq. 3 and a little simplification, we have:

$$ \begin{equation} {\mathrm{j}}_{\mathrm{i}}={\mathrm{E}}_{\mathrm{i}}+{\rho}_{\mathrm{i}}\sum_{\mathrm{j}=1}^{\mathrm{n}}\kern0.1em {\mathrm{j}}_{\mathrm{j}}{\mathrm{F}}_{\mathrm{j}\mathrm{i}} \end{equation}$$

(5)

The next equation is known as the radiolytic equation, which must be applied to each surface piece in the model. Therefore, the model is completely analyzed by solving the N equation of the unknown N at the same time, which is called the complete radiocast matrix method (Eq. 6):

$$ \begin{equation} \left[\begin{array}{@{}cccc@{}}1-{\rho}_1{\mathrm{F}}_{11}& -{\rho}_1{\mathrm{F}}_{12}& \dots & -{\rho}_1{\mathrm{F}}_{1\mathrm{n}}\\ {}-{\rho}_2{\mathrm{F}}_{21}& 1-{\rho}_2{\mathrm{F}}_{22}& \dots & -{\rho}_2{\mathrm{F}}_{2n}\\ {}\dots & \dots & \dots & \dots \\ {}-{\rho}_{\mathrm{n}}{\mathrm{F}}_{\mathrm{n}1}& -{\rho}_{\mathrm{n}}{\mathrm{F}}_{\mathrm{n}2}& \dots & 1-{\rho}_{\mathrm{n}}{\mathrm{F}}_{\mathrm{n}\mathrm{n}}\end{array}\right]\left[\begin{array}{@{}c@{}}{\mathrm{j}}_1\\ {}{\mathrm{j}}_2\\ {}\dots \\ {}{\mathrm{j}}_{\mathrm{n}}\end{array}\right]=\left[\begin{array}{@{}c@{}}{\mathrm{E}}_1\\ {}{\mathrm{E}}_2\\ {}\dots \\ {}{\mathrm{E}}_{\mathrm{n}}\end{array}\right] \end{equation}$$

(6)

E₁ is usually zero (except for fragments of the surface that emit visible light). In the above relation, radiosity unknowns are surface patches, by solving which, radiosity is obtained for all surface patches.

After obtaining the radioactivity of all surfaces, the light intensity can be obtained at any specific point inside the chamber using Eq. 7.

$$ \begin{equation} {\mathrm{H}}_{\mathrm{p}}=\sum_{\mathrm{j}=1}^{\mathrm{N}}\kern0.1em {\mathrm{j}}_{\mathrm{j}}{\mathrm{F}}_{\mathrm{p}-\mathrm{j}} \end{equation}$$

(7)

In this regard, H_p is the intensity of light at point p and F_p-i is the differential visibility coefficient of point p relative to the surface piece of z, which can be calculated. The problem-solving process is that first the light that is illuminated through the wellhead’s light is calculated (Eqs. 8 and 9).

Horizontal lighting:

$$ \begin{equation} {J}_{\mathrm{sky}\mathrm{light}-\mathrm{h}}=\tau \left({q}_{\mathrm{sky}}+{q}_{\mathrm{sun}}\cos {\theta}_s\right) \end{equation}$$

(8)

Vertical lighting:

$$ \begin{equation} {J}_{\mathrm{sky}\mathrm{light}-\mathrm{v}}=\tau \left({q}_{\mathrm{sky}}+{q}_{\mathrm{sun}}\sin {\theta}_s\right) \end{equation}$$

(9)

The J_skylight is the radiance of the radiant city, and q_sky is the brightness of the sky, the q_sun is the intensity of direct sunlight and θ is the angle of the sun’s rays with the vertical line (angle of the apex).

Then, the inner surface of the skylight is subdivided into various elements, and the visibility coefficients of all surfaces are calculated relative to one another using Eq. 5 for all possible separate levels of writing. N then solves the resulting N unknown equation to obtain the adipocytes of all segments (Eq. 10).

$$ \begin{equation} {J}_{\mathrm{win}-\mathrm{in}}=\frac{1-\rho }{\rho }{J}_{\mathrm{win}-\mathrm{out}} \end{equation}$$

(10)

The J_win-in and J_win-out, respectively, are the radiographs of the window panes facing the room and facing the skylight, and the reflection coefficient of the window panes. Then, the previous procedure is repeated for the interior parts of the room and the radiosity obtains all the separate levels.

Figure 3

Daylight factor and well index relation for different floors.

Figure 4

Daylight factor relation with w_i of different windows pass the coefficient of the room’s inner walls for the first floor.

3 RESULTS AND DISCUSSION

In this section, the validity of the results is initially confirmed by comparing them to the experimental and numerical findings of other researchers. The study conducted by Laouadi and Atif [42] has been utilized to validate the present research model’s findings. They provide Eq. 11 for determining the light coefficient in the reflector’s central floor area. In addition, a comparison was made between the analytical results of the average illuminance coefficient for the areas adjacent to the illumination provided by Littlefair (as described in Eq. 12) [43] and the results of the present investigation, across a range of w_i values. Figs. 2a and2b provide a comparison between the present study’s findings and the results derived from Eqs. 11 and 12, respectively.

$$ \begin{align} {\mathrm{DF}}_{\mathrm{cf}}&=\&103.56-121.09\mathrm{wi}+64.203{\mathrm{wi}}^2-17.61{\mathrm{wi}}^3\notag\\&\quad+2.393{\mathrm{wi}}^4-0.1267{\mathrm{wi}}^5; \end{align}$$

(11)

$$ \begin{equation} {\mathrm{DF}}_{\mathrm{av}}=\frac{2{\mathrm{A}}_{\mathrm{w}}{\mathrm{T}}_{\mathrm{s}}{\mathrm{DF}}_{\mathrm{v}}}{{\mathrm{A}}_{\mathrm{s}}\left(1-{\mathrm{R}}_{\mathrm{s}}^2\right)}, \end{equation}$$

(12)

where, A_w is the net surface of the floor window glass per square meter, T_s is the glass transmittance coefficient, A_s is the area of the entire room level by square meter, R_s is the average reflection coefficient of the room and DF_v is the light factor average on the window glass of the room.

Figure 5

The percentage increase of the daylight factor in different w_i (the reflection coefficient from wells wall is about 0.55).

Figure 6

Sensitivity analysis of daylight factor on building energy parameters and CO₂ emission.

Figure 7

Daylight factor effects on building energy consumption.

RMSE_Eq11 = 0.79 and RMSE_Eq12 = 0.84 indicate a high degree of concordance between the outcomes of the current model and the previously established analytical results. To facilitate future investigations, it is therefore plausible to refine and expand the current model.

This section’s objective is to determine the relationship between the attenuation of the daylight factor to the floors and the trend of the light coefficient’s variation with respect to the skylight’s dimensions. In Fig. 3, the daylight factor for each floor’s rooms is plotted as a function of w_i.

It is observed that the daylight factor decreases exponentially with respect to the distance from the skylight in the floor rooms. Because R² is so near to one, it can be deduced that the trend of changes in the brightness ratio is equal to (H/L) exponential. As can be observed, increasing the side of the skylight improves the average daylight factor in each floor dramatically. The average daylight factor in each class can be calculated using the trend line formulae as Eq. 13 (n is floor number).

$$ \begin{equation} \mathrm{DF}={\mathrm{DF}}_0\times {\mathrm{e}}^{-\mathrm{\alpha} \times wi}, \end{equation}$$

(13)

where,

$$ \begin{align}\begin{aligned} &{\mathrm{DF}}_0= 0.5883\text{n}+1.9071;\\ & \alpha= -2.7417\text{n}+15.846. \end{aligned}\end{align}$$

(14)

3.1 Reflection coefficient

The effect of wall surface reflection coefficient can be attributed to two distinct areas: room wall surfaces and lighting well wall surfaces, which are investigated separately. This condition is considered for one level because the effect of the room wall reflection coefficient is the same for all floors. Fig. 4 depicts the daylight factor of the fifth-floor rooms in the reflection coefficients of 0.3, 0.4, 0.5, and 0.6 of the room walls.

Figure 8

Daylight factor effects on building CO₂ emission.

As shown in Fig. 5, raising the reflection coefficient of the room walls from 0.3 to 0.5 (a 50% increase) raises the average daylight factor of the average room on all levels by 20% while also increasing the reflection coefficient of the room walls. Increasing from 0.5 to 0.7 (33%) results in a 19% rise. It may be concluded that raising the reflection coefficient of the room’s walls sharply raises the daylight factor. The results reveal that the reflection coefficient is increased. Because the rate of increase of the coefficient of brightness of the well’s wall differs for each class, this was demonstrated in Fig. 5. The trend of changes in the coefficient of brightness with increasing the reflection coefficient of the well wall shows that the effect of the reflection coefficient on increasing the daylight factor is greater in all classes in smaller dimensions of the skylight, and this increase is a line whose slope is higher in the lower floors. Second, in a specific side of the skylight, the percentage increase in daylight factor is relative to the reflection coefficient. The lower is higher, which is supported by the effect of the skylight floor’s reflection.

Typically, the normal reflection coefficient of a skylight due to glare effects ranges between 0.2 and 0.3. The daylight factor of the lower floors appears to be significantly affected by the skylight floor’s reflection coefficient. The daylight factor of floors in various wi for floor reflection coefficients of 0.1, 0.2, and 0.3 is calculated. As can be seen, the rate at which the daylight factor increases in smaller rooms on all floors is slower. Due to the increased reflective surface of the skylight floor, larger skylight dimensions can be justified in this instance. Second, as anticipated, the daylight factor increases more than the reflection coefficient in the lower floors; thus, increasing the reflection coefficient of the skylight from 1.03 increases the average daylight factor on the first, second, third, and fourth floors by 20, 8, 4, and 1.5%, respectively.

The daylight factor is impacted by the skylight’s size. Initially, for a specific level of skylight, two modes of rectangular cross-section and square mode are evaluated. At a specific level of the skylight, the floors facing the larger side of the skylight have a higher daylight factor, but the square mode transmits more light to the other floors, with the exception of the top floor. The average daylight factor in the floors increases exponentially with decreasing w_i (increasing the side of the skylight) for various degrees of skylights. As can be seen, the rate of increase of the daylight factor accelerates as the skylight level increases at higher elevations.

First, for all floors, larger skylights (smaller w_i) have a higher window glass transmittance, and, second, increasing the window glass transmittance linearly increases the daylight factor of the respective floors. It grows such that increasing the transmittance of the window glass of the floors from 0.7 to 0.9 (a 28% increase in transmittance) increases the brightness of the floors by 9, 10, 14, and 19% on the first, second, third, and fourth floors, respectively. The result is that the coefficient of penetration is greater than the coefficient of brightness in the uppermost rooms.

3.2 Building energy analysis

In this section, we analyze how the daylight factor impacts both the amount of energy consumed and the amount of greenhouse gases produced. A sensitivity analysis is carried out in the realm of building energy performance for the primary purpose of determining the significance of the contribution of input variables to output variance. In the present investigation, multiple linear regression was utilized to investigate a linear relationship between the output variable and the input variables. Additionally, the effect of the daily illumination factor on the performance of various building energy consumption and greenhouse gas emissions was determined. The standard regression coefficients (SRCs) for the daylight factor were computed, and Fig. 6 illustrates the findings obtained from those calculations. On the basis of the findings, it was established that the illumination factor has the potential to have a positive impact on the amount of energy used for lighting, whereas it has the potential to have a negative impact on the amount of energy used for cooling, although this effect is not very significant. In addition to the beneficial effects it has on the energy used for heating and lighting, it also has a significant impact on the emissions of greenhouse gases.

It has been widely observed that integrating daylight into a building generally leads to a decrease in the usage of artificial lighting energy. Nevertheless, it is crucial to acknowledge that this inclusion also results in a rise in both solar heat gain and thermal conductance, as depicted in Fig. 7. The duration of daylight hours in spring and summer leads to an increase in the utilization of cooling energy and subsequently, an increase in the cooling load. Conversely, during the colder seasons, the reduced daylight hours result in an increase in the utilization of heating. However, it is worth noting that the overall energy consumption experiences a slight decrease.

Fig. 8 illustrates the correlation between the lighting factor and the amount of CO₂ gas emitted from the building. The findings indicate that as the daylighting factor increases, there is a corresponding decrease in CO₂ emissions. Specifically, when the daylighting factor in the building increases from 3 to 6%, the average CO₂ gas emission demonstrates a 3% reduction throughout the year. This significant observation highlights the positive impact of daylight on reducing carbon emissions, emphasizing the importance of incorporating effective daylighting strategies in sustainable building design. The results underscore the potential of daylighting as a viable approach for achieving energy efficiency and environmental sustainability in the built environment.

4 CONCLUSIONS

In this particular investigation, a structure consisting of four levels was used to carry out the calculations for the illumination. When it came time to perform the calculations for the amount of illumination, the radiosity method was the one used. In the calculations for the lighting in the corners, the daylight factor was used, and the results were divided into three different positions: well-lit lighting wells, three-way lighting wells, and four-way lighting wells. The findings of the current study indicate that the skylight side has a considerable effect on the amount of light that enters the building’s floors; consequently, for a square skylight, decreasing the well index (raising the side of the skylight) raises the daylight factor exponentially more than raising the side of the skylight itself. Another aspect of this research that was investigated was the influence that the skylight wall reflection coefficient had on the floor daylight factor. The findings indicate that the influence of the reflection coefficient is amplified both when the dimensions of the skylight are reduced and when it is situated on lower floors; moreover, this increase is exponential. The effect of the skylight reflection coefficient was the subject of an additional case study that was carried out for the purpose of this study. According to the findings, the influence of the reflection coefficient of the skylight floor on the daylight factor is more pronounced at lower levels and in skylights with larger diameters. This is the case for both types of skylights. The size and dimensions of the skylight were also looked into as part of this research project as an additional aspect of the skylight. According to the findings, the design of a square skylight lets in the most light into the various levels of the building when compared to rectangular skylights with the same cross-section. In a three-way skylight, the rate at which the brightness of the rooms is increased by increasing the reflection coefficient of the well wall is almost constant in all dimensions of the skylight, in contrast to a four-way skylight; another difference is that the effect of the reflection coefficient of the well wall on increasing the daylight factor in the back rooms is greater than in the side rooms. It is well known that increasing the amount of natural daylight that is allowed into a building can result in a reduction in the amount of energy that is required for artificial lighting. This phenomenon has been thoroughly researched and documented. When installed in a building, skylights have the effect of lowering the amount of energy that is consumed by artificial lighting while at the same time raising the solar heat gain and increasing the thermal conductance of the building. When the lighting factor in the building is increased from 3 to 6%, there is a decrease of 3% in the average amount of CO₂ gas that is emitted over the course of an entire year. This is because there has been a reduction in the total amount of CO₂ emissions that have been released.

FUNDING

This research has been funded by Scientific Research Deanship at University of Ha’il, Saudi Arabia through project number RG-20220.