The Sustainability Coefficient of Urban Open Space Illumination Compliance as a Subjective Indicator of Environmental Comfort

Abstract

Smart lighting of public open spaces plays a crucial role in creating sustainable cities. Investing in optimal methods for improving the energy efficiency of urban lighting systems has become strategic for the economic, technological, and social development of cities. In addition to technical considerations such as energy efficiency and photometric measurements, lighting design should also take into account the subjective aspect of visual safety. However, measuring lighting efficiency in terms of human perception can be challenging because people’s perceptions vary and depend on the urban and architectural context. To address this issue, a sustainability coefficient of outdoor lighting ambiences (Sn) is presented to quantify the compliance of urban open spaces with sustainable lighting design. This coefficient combines two subjective factors: illumination likability and perceived illuminance intensity. The study uses the SEC methodology (suitable for everyone, environmentally accepted, cost-effective), which provides insight into the factors that influence the Sn value. The results showed significant correlations between psychological and aesthetic-functional factors and the Sn, while sociological factors had little influence. The validity of the Sn in a realistic environment can be confirmed. The main reasons for certain Sn levels were identified and possible solutions were proposed, ranging from changes in lighting intensity to architectural redesigns, to improve environmental comfort in urban environments. This study paves the way for a deeper understanding of the role of urban lighting in shaping environmental comfort and human behavior.

1. Introduction

Before the mid-18th century, people mainly relied on natural light from the sun and moon, with artificial lighting being rare. The introduction of artificial lighting in the mid-18th century revolutionized illumination, impacting urban planning and architecture [1]. By the late 1800s, streetlamps became widespread, marking a shift toward more economical lighting solutions [2]. Early streetlamps, often made from decorative materials like cast iron, not only improved visibility and safety but also added aesthetic value to public spaces [3].

In recent years, conventional light sources such as incandescent bulbs, fluorescent tubes and halogen lamps have been replaced by energy-efficient LED lighting, which has reduced the energy and operating costs of streetlights by over 46% [4]. The need to combat climate change and rising fuel costs is driving this change and pushing for better energy management [5,6]. Lighting accounts for one-fifth to one-sixth of global electricity consumption [7]. The advent of electricity led to simpler streetlights, while neon signs, billboards and shop fronts became prominent features of the cityscape [8,9]. Monuments and green spaces were also illuminated to attract attention and beautify public spaces [9]. In order to create sustainable cities at night, eight key aspects of urban lighting were identified: 1. social; 2. safety, security and wayfinding; 3. cultural and heritage; 4. environmental; 5. regulatory and legal; 6. night-time economy; 7. public health and wellbeing; and 8. technological [10]. Sustainable lighting is today highly subjected to technological advances in design with energy efficient light sources [11]. There is a wide range of research on the topic of outdoor lighting for public spaces. These include studies on street lighting [12,13,14,15,16], advertising lighting [17], security lighting [18,19,20], architectural lighting [21,22], and smart lighting. Smart lighting refers to lighting technology that is designed for energy efficiency, user convenience, and enhanced functionality through automation and connectivity. The transition from traditional to smart street lighting has provided significant advancements in terms of energy savings, automation, maintenance efficiency, and environmental benefits. Smart lighting systems enable cities to reduce operational costs, enhance sustainability, and improve the safety and comfort of public spaces. Smart lighting can significantly reduce energy consumption while enhancing user satisfaction and overall productivity. Studies have demonstrated that implementing smart lighting systems in commercial buildings can lead to energy savings of up to 35% [23]. Smart lighting is not only used indoors but also outdoors, where it offers similar benefits.

The use of intelligent dynamic street lighting systems that adapt to the presence and behavior of users can illuminate the streets only when and where it is necessary. In this way, it provides a solution to the problems of energy waste and light pollution [24,25] associated with traditional street lighting methods [13,26,27]. Currently, artificial lighting is responsible for the expansion of illuminated outdoor areas at a rate of 2.2% per year [28]. This change in the environment due to the amount and spectrum of light also triggers unwanted disturbances for humans and other living beings [29]. Recognizing and capitalizing on these challenges becomes crucial in curbing excessive nighttime illumination.

Investing in the optimal measures for improving the energy efficiency of urban lighting systems has become strategic for the economic, technological, and social development of cities [30]. Alongside technical advancements, various institutions such as the Commission Internationale de l’Eclairage (CIE) [31], the Illuminating Engineering Society of North America (IESNA) [32], and the International Dark-Sky Association (IDA) [33] have advocated for setting lighting restrictions based on the specific functions of different areas. These areas, which require light pollution control, are categorized into different light management zones, considering the varying lighting needs. This approach ensures that outdoor lighting is not uniformly restricted in all areas [17].

By optimizing power consumption, luminaire efficiency, and reducing upward light, effective street lighting with minimal environmental impact can be achieved [14]. According to the Commission Internationale de l’Eclairage (CIE), street lighting serves three key functions: ensuring safe movement for all road users, enhancing pedestrian visibility and security, and improving environmental aesthetics day and night [34]. Guidelines offer quantitative recommendations on luminance, spectral power distribution, and spatial light distribution, alongside energy and environmental criteria [33]. However, lighting efficiency cannot be fully quantified due to varying human perceptions, influenced by urban and architectural contexts [11,28]. Laze’s study [33] shows that despite meeting CIE standards, user dissatisfaction indicates a need for designs aligned with public expectations.

By optimizing power consumption, luminaire efficiency and reducing upward-directed light, effective street lighting can be achieved with minimal environmental impact [14]. According to the Commission Internationale de l’Eclairage (CIE), street lighting fulfils three important functions: ensuring safe traffic for all road users, improving the visibility and safety of pedestrians, and improving environmental aesthetics day and night [34].

Guidelines provide quantitative recommendations on luminance, spectral power distribution and spatial light distribution as well as energy and environmental criteria [33]. However, lighting efficiency cannot be fully quantified because human perception varies and is influenced by the urban and architectural context [11,28]. The study by Laze [33] shows that, despite compliance with CIE standards, user dissatisfaction indicates the need for design based on public expectations.

This article examines users’ cognitive and emotional perceptions of the nocturnal environment and how these perceptions influence rational lighting decisions. As Doulos notes, the design of lighting systems is of greater importance than simply selecting luminaires based on cost and energy efficiency [14]. Perception is influenced by variables such as gender, age, experience, culture, and spatial context [11]. Psychological, sociological, and aesthetic factors are crucial. Reduced night-time lighting can improve privacy, facilitate observation of the night sky, and reduce energy costs and light pollution, all of which contribute to sustainable urban development.

In terms of energy efficiency, illuminance is a quantifiable parameter. However, sustainable lighting must also take into account user perception, which varies depending on the spatial context, including the urban and architectural environment. Lighting should be used exactly where it is needed and effective. An optimal balance between lighting needs, aesthetics, and intensity is crucial, as the same luminaire can create different visual effects depending on the spatial conditions.

Focusing on a user-centered approach to physical environmental experience, the following questions are addressed:

Is urban lighting necessary for users, and if so, where is it necessary?

To what extent is it necessary to light public areas?

How can we incorporate the human dimension into the artificial night lighting of public open spaces?

Does the lighting arrangement of a particular place or object meet the expectations of the public?

Based on the research questions raised, a hypothesis emerges that has far-reaching implications for the comprehensive management of open space lighting, but at the same time is relatively simple methodologically and quickly leads to results of great significance.

The null hypothesis here is:

Hypothesis 1 (H1).

Due to the complexity of the problem, it is not possible to establish a suitable and simple method for evaluating the quality of the lighting ambience of various urban open spaces.

The alternative hypothesis is set up:

Hypothesis 2 (H2).

It is possible to develop a suitable and simple method for evaluating the quality of the lighting ambience in various urban open spaces.

The starting point for the research presented here is the cognition that a high-quality lighting ambience is primarily geared to the needs of users in order to ensure their visual well-being, quality of perception, and the fulfillment of the required visual tasks. Everything is subordinate to it. At the same time, a high-quality lighting ambience leads to more efficient energy consumption and a reduction in light pollution. To verify hypotheses, we need to develop a simple, quick method that can serve as a basic criterion for analyzing outdoor lighting ambiences. Standardized units of measurement are also required.

The main contribution of the research presented here is to demonstrate the usefulness of the Sustainability coefficient for urban open space illumination compliance as a basic tool for assessing the quality of the lighting ambience of all urban open spaces such as streets, squares, and parks.

2. The Sustainability Coefficient of Outdoor Lighting Ambiences

The sense of sight is generally the preferred and most valuable sense to perceive and interact with the environment [35]. Trends in urban cityscape dynamics rely heavily on the visual perception of citizens to carry out their daily life [36]. In urban environments, the focus of lighting goes beyond linear structures (streets). It also includes public places such as squares [37,38] and parks [39,40,41] that serve as gathering places where people engage in various activities in open spaces [42]. These activities include walking, running, standing, sitting, socializing, playing, in-line skating, rollerblading, and sightseeing [43]. While many of these activities occur primarily during daylight hours, there is a desire to extend them to nighttime hours as well. However, these areas, which are characterized by architectural and advertising lighting, tend to be unevenly lit.

Jurševska [44] reveals a quartet of recurring elements in the design of nocturnal urban landscapes. First, the illumination of significant and iconic urban features improves navigability and enhances the unique character of the city after dark. Second, creating safe thoroughfares that connect communities and lighting community centers fosters community spirit. Third, lighting historic sites or areas with unique ambiance adds to the nighttime charm. Finally, engaging with private stakeholders and citizens is critical to creating a unified aesthetic for the city at night. Nowadays, human-centric lightning is a major aspect of interest to influence mental states [45]. This influence of light on humans can impact positively or negatively through visual perception of radiation [29]. In urban environments, various forms of experiential information, such as images, sounds, and artifacts, contribute significantly to how individuals interact with the space around them [46]. For instance, the images from murals, billboards, and decorations on buildings not only serve aesthetic purposes but also convey specific messages associated with the city’s identity and functions.

Determining the optimal lighting level, whether it is “just right”, “too much”, or “too little”, is a complex task. Often, emphasis is placed on illuminance criteria without considering the overall target environment. A well-lit object that stands out against a dark background is visually arresting. However, reducing the contrast between the illuminated object and the dark environment can make it difficult to perceive spatial order, while excessive darkness is also undesirable. Sometimes the quality of lighting is in line with all standards and recommendations, but users still feel unsafe and uncomfortable [47]. Therefore, the question arises as to what extent the lighting makes sense.

The first preliminary empirical study to solve this challenge was conducted by Rozman Cafuta et al. [48]. The sustainability coefficient (S) as the subjective quotient of the mean value of the illumination likability (L) and the perceived illuminance intensity (I) were presented (Equation (1)).

S = L/I

(1)

The sustainability coefficient (S) is a subjective measure that has no physical basis, as both values—illumination likability and illuminance intensity—are determined based on the average ratings of the subjects’ opinions. Illuminance intensity is a subjective factor and is not compatible with the technical factor of illuminance. However, the coefficient very effectively expresses our expectation to achieve the highest possible likability with the lowest possible illuminance.

A preliminary study—Phase 1—was already partially presented [48] in 2023.

Table 1. Assessments of the sustainability coefficient.

Case of Consideration	Illumination Likability (L)		Illuminance Intensity (I)		L/I	${\overline{\mathit{x}}}_{\mathbf{L}}-{\overline{\mathit{x}}}_{\mathbf{I}}$	t	2p	r
	$\overline{\mathit{x}}$L	σ	$\overline{\mathit{x}}$I	σ
1 Gosposka Street	3.12	0.727	3.30	0.677	0.95	0.180	–2.656	0.009	0.198
2 Poštna Street	3.16	0.073	2.87	0.780	1.10	0.290	4.441	0.000	0.512
3 Vojašniška Street	3.24	0.947	2.90	0.824	1.12	0.335	4.964	0.000	0.448
4 Štukelj Square	4.09	0.911	4.10	0.822	0.98	0.011	–0.141	0.888	0.283
5 Castle Square	3.34	0.803	3.28	0.727	1.02	0.067	1.214	0.226	0.534
6 Main Square	3.25	0.831	3.40	0.830	0.96	0.145	–2.469	0.014	0.517
7 Slomšek Square	3.34	0.803	3.28	0.727	1.02	0.067	1.214	0.226	0.534
8 Liberty Square	3.05	0.868	2.86	0.847	1.07	0.188	2.880	0.005	0.523
9 Park	3.14	0.955	2.53	0.851	1.24	0.607	7.803	0.000	0.345
10 Market	2.66	0.887	2.56	0.926	1.03	0.097	1.430	0.155	0.539
11 Ski Slope	3.88	0.927	3.89	0.965	1.00	0.011	–0.147	0.883	0.416
12 Clinical Center	3.00	0.765	3.33	0.778	0.90	0.329	–4.566	0.000	0.310
13 Pedestrian Bridge	3.41	1.098	2.80	0.893	1.22	0.605	7.914	0.000	0.524
14 University	3.71	0.902	3.68	0.838	1.01	0.036	0.558	0.578	0.459
15 Theatre	3.74	0.822	3.62	0.822	1.03	0.115	1.712	0.089	0.451
16 City Hall	3.33	0.919	3.35	0.889	0.99	0.018	–0.268	0.789	0.543
17 Football Stadium	3.52	0.994	3.60	1.058	0.98	0.082	–0.943	0.247	0.344
18 Shopping Center	3.46	1.107	4.25	0.819	0.81	0.786	–9.036	0.000	0.228
19 Chapel	3.42	0.986	2.78	1.017	1.23	0.644	7.510	0.000	0.339
20 Liberation Monument	2.84	0.902	2.52	0.038	1.13	0.325	4.928	0.000	0.598
21 Plague Monument	3.20	0.903	3.21	0.949	1.00	0.006	−0.088	0.930	0.575
22 Slomšek Monument	3.20	0.789	3.05	0.926	1.05	0.022	0.286	0.024	0.454

$\overline{x}$, arithmetic mean; σ, standard deviation; t, value difference arithmetic test; 2p, bidirectional level of statistical significance; r, Pearson product–moment correlation coefficient.

is now supplemented with additional locations or objects. The empirical study comprised a group of 200 participants, equally divided into 100 men and 100 women aged between 18 and 35 years. All participants were students of different disciplines at the University of Maribor in Slovenia. The same participants also were used later in following phases (Phase 2 and Phase 3) the presentation of which is the main purpose of this article. Initially, 12 locations (1–12) and 10 objects (13–22) were selected according to the principle of diversity. All respondents were familiar with all cases and rated on a 5-point rating scale how much the lighting arrangement met their expectations regarding illumination likability and illuminance intensity.

The results of Phase 1 (Table 1 [48]) show that a higher sustainability coefficient corresponds to more sustainable lighting. The sustainability coefficient, which is calculated in the sixth column of Table 1, is usually around 1.00. Values above 1.00 indicate that likability surpasses illuminance. The correlation coefficient (r = 0.198 to 0.598) indicates a weak to moderate correlation between illuminance and likability in all cases. The results of the t-test show significant differences in both directions for most cases. Where 2p > 0.05, there are no statistically significant differences. Cases such as Castle Square and Slomšek Square, the university, the theatre, the market, the ski slope and the plague monument have S ≥ 1.00 at the same time. The ski slope and the plague monument are included in this group despite a negative t-test result because rounding to two decimal places gives an S value of 1.00.

Cases such as the city hall, Štukelj Square, and the football stadium also show 2p > 0.05 with S < 1.00, indicating no statistically significant differences between the averages. In all cases where no significant differences were found, the sustainability coefficient (S) is very close to 1.00, specifically between 0.98 and 1.03. Since this range overlaps with S > 1.00, it can be considered as an interval in which the lighting of urban open spaces remains compliant, defined as S ≥ 0.98. The threshold S = 0.98 represents the lowest rounded value at which no significant difference between illumination likability and illuminance intensity is observed. In this study, all but five cases where S < 0.98 were classified as compliant.

The lighting compliance value was determined on the basis of the statistical parameters of 22 cases. In all cases where S ≥ 0.98 (Sn ≥ 1.00), the lighting is adequate and lighting compliance is achieved. To simplify the expression, a normalized value Sn was introduced, which sets the boundary of the closed interval to 1.00 (as shown in Equation (2)).

Sn = S + Δ S
Δ S = 0.02

(2)

In cases where Sn < 1.00, the lighting is not adequate and lighting compliance is not achieved. The illumination intensity exceeds the likability, resulting in higher energy consumption compared to scenarios where lighting compliance is met. This relationship can also be expressed mathematically, as shown in Equation (3).

$$\mathrm{S}\mathrm{n}\left\{\begin{array}{c}\ge 1.00,\mathrm{l}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}\mathrm{i}\mathrm{n}\mathrm{g}\mathrm{i}\mathrm{s}\mathrm{a}\mathrm{d}\mathrm{e}\mathrm{q}\mathrm{u}\mathrm{a}\mathrm{t}\mathrm{e}\\ <1.00,\mathrm{l}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}\mathrm{i}\mathrm{n}\mathrm{g}\mathrm{i}\mathrm{s}\mathrm{n}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{d}\mathrm{e}\mathrm{q}\mathrm{u}\mathrm{a}\mathrm{t}\mathrm{e}\end{array}\right.$$

(3)

The sustainability coefficient (Sn) serves as a theoretical framework for evaluating the visual quality and potential of a particular place. Its use standardizes psychological measurements in consistent units. While a single application can provide results for assessing the visual qualities of a place, it can also be applied multiple times to compare the results before and after spatial changes or to observe the evolution of a space over time.

New ideas are gradually emerging in the scientific community. The basic definition of the sustainability coefficient (Sn) still leaves questions unanswered, as it gives an estimate of something that cannot be measured precisely, such as human opinion. Proving the validity and applicability of the sustainability coefficient was the next research step. Does the Sn value reflect environmental comfort? Is there a correlation between the values of the sustainability coefficient and the subjective indicators of lighting efficiency?

We can assume that the value of the sustainability coefficient warns us against excessive lighting. The subjective perception of intense lighting with low lighting sympathy only leads to energy loss and light pollution. This could be the main benefit of the sustainability coefficient.

In essence, achieving an optimal Sn is a multi-layered endeavor that requires a nuanced approach that harmoniously combines technical lighting adjustments with architectural and environmental considerations. The challenge is to design spaces that not only meet the quantitative criteria of adequate lighting, but also satisfy the aesthetic and functional preferences of users. This delicate balance is the cornerstone for creating spaces that are both functional and inviting.

3. The Integral Role of Lighting in Urban Environment

The integral role of lighting in an urban environment cannot be overstated, as it impacts various aspects of city life, community wellness, and urban development. In the design of cities, certain areas or elements are commonly considered focal points that deserve special attention. These include entrance areas, major thoroughfares, pedestrian walkways, entrances to train stations and bus stops, urban green spaces, waterfront areas, prominent city skylines, panoramic views inside and outside city limits, and new urban developments that must establish a harmonious relationship with the existing urban fabric while maintaining their own unique identity [3]. These visual features can be enhanced by the use of artificial lighting at night. The components that are most commonly illuminated include transportation infrastructure such as roads, railroads, and airports; public spaces such as plazas and parks; industrial facilities; commercial buildings; institutional facilities; sports fields; cultural landmarks; and construction sites and advertising structures.

Phases 2–4 followed and are now presented for the first time in this paper. The same group of 200 participants, (100 males and 100 females) was used in all four research phases. In Phase 2, a survey focused on highlighting the importance of lighting various urban surfaces and objects. The main objective of this study part was to find out whether the urban areas deemed paramount for illumination align with the perception that they are indispensable. Using a five-level evaluation matrix, participants rated eight different types of public spaces and six facilities that are often the focus of urban lighting. The results highlighted the zones where lighting is perceived to be essential and the areas where lighting could usefully be curtailed to reduce energy expenditures or reduce light pollution.

Table 2. Analysis of Lighting Significance in Different Urban Areas.

	Subject of Illumination	Importance Value		Missing Value		$\left|\mathbf{Difference}\right|\overline{\mathit{x}}$	t	2p	r
		$\overline{\mathit{x}}$	σ	$\overline{\mathit{x}}$	σ
Public Surfaces	Arterial roads	3.66	0.917	3.23	1.114	0.430	6.237	0.000	0.559
	Urban local roads	3.51	0.919	3.36	1.032	0.145	2.438	0.016	0.634
	Pedestrian zones in centre	3.97	0.763	3.76	0.905	0.215	3.709	0.000	0.528
	Streets of medieval town	3.81	0.837	3.51	1.027	0.300	4.823	0.000	0.571
	Urban squares	3.90	0.868	3.62	0.960	0.285	4.972	0.000	0.611
	Footpaths in city park	3.56	0.944	3.34	1.127	0.215	3.352	0.000	0.629
	Sport objects surfaces	3.13	1.022	2.98	1.154	0.150	2.174	0.031	0.604
	Parking lots	3.06	1.013	2.93	1.077	0.125	1.925	0.056	0.616
Public Objects	Facade of shopping malls	2.77	1.121	2.51	1.169	0.255	3.730	0.000	0.644
	Facade of public buildings	2.85	0.972	2.59	1.094	0.255	4.462	0.000	0.700
	Façade of sacral buildings	3.60	1.121	3.65	1.247	–0.065	–0.783	0.435	0.653
	Bridge construction	3.75	0.902	3.39	1.097	0.360	5.712	0.000	0.618
	Statues and monuments	2.97	0.972	2.58	1.077	0.395	5.877	0.000	0.574
	Greenery (trees, shrubs)	2.15	1.034	2.00	1.051	0.145	2.188	0.030	0.596

$\overline{x}$, arithmetic mean; σ, standard deviation; t, value difference arithmetic test; 2p, bidirectional level of statistical significance; r, Pearson product–moment correlation coefficient.

shows the comparative assessment between the perceived importance value of lightning and the subjective assessment of the lack of value of lightning on different public areas and objects. The results show that lighting plays an important role as a spatial factor in most cases, affecting both public spaces and objects. The average rating of importance is between 2.15 and 3.90. Public areas such as pedestrian zones in the city center, streets of the mediaeval town, and urban squares achieve the highest importance value (3.97, 3.81, 3.90). At the same time, the lighting of these areas would also be missed the most. On the other hand, the lighting of objects does not seem to be so important, and one could easily do without it. A slightly higher value is achieved by illuminated objects, such as bridge construction and facades of sacral buildings, which respondents would not want to do without. Such a result can be largely attributed to the local spatial identity of the city of Maribor. Plant lighting has the lowest value, which is consistent with the lowest evaluation of the importance of lighting. In this scenario, respondents are most willing to accept a reduction in lighting. Conversely, respondents are more likely to agree to reduce lighting in the downtown area, which happens to have the highest average importance rating. The remaining cases generally fall between these two extremes.

Among all the options, the lighting of sacred buildings clearly stands out. Respondents would feel strongly affected by a reduction in this lighting, as reflected in a relatively high average score of 3.65 for the lack of light. However, respondents are aware that lighting of sacred buildings is not the most important aspect, as it is not among the highest rated, with an average score of 3.60.

The results of the t-test indicate that in most cases there is a statistically significant difference between the perceived importance of lighting and the situations in which there is no reduction. This means that, in general, respondents tend to agree with the possibility of reducing lighting in different scenarios. However, there are two exceptions to this trend. Sacred buildings and parking lots are areas where respondents are generally against reducing lighting. An analysis of the correlation coefficient (r) shows that all cases have moderately correlated distribution functions. The coefficient values range from 0.528 for lighting areas in pedestrian zones in the city center to 0.700 for lighting the facade of public buildings.

There is considerable variation in the perception of the importance of lighting among different types of public spaces and objects. These differences suggest a wide range of expectations and needs regarding urban lighting within the study sample population. The consistently low p-values for most lighting themes indicate a general consensus among participants about the importance of lighting in these areas. This indicates a shared understanding of the safety, aesthetic, and functional value of lighting in urban environments. Correlation coefficients indicate a moderate to strong linear relationship between importance and missing values for most subjects, indicating consistent perceptions of the value and dispensability of lighting across urban elements. The generally higher mean scores for importance for most subjects reflect a high level of agreement within the surveyed population regarding the need for lighting, underscoring its role as a key component in urban design and planning. Of note is the negative difference for the façade of sacred buildings, indicating a unique pattern of emphasizing the importance of lighting, possibly reflecting respect for the sanctity and original aesthetics of such buildings.

In essence, lighting is not only a functional component of the urban environment, but an essential component of the city’s identity, safety, functionality, aesthetics, and overall success. In general, public spaces such as urban thoroughfares, pedestrian zones in city centers, streets of mediaeval cities, and urban squares have a higher priority than specific objects such as building facades and plants. This may indicate that broad public spaces are preferred over individual objects in the perception of the importance of lighting. Given this observed trend, the focus of the research in Phases 3 and 4 shift to a more in-depth examination of these public spaces to explore the nuances and subtleties that determine their lighting needs and preferences.

4. Exploring the Validity of the Sustainability Coefficient (Sn) Through Subjective Indicators of Environmental Comfort

Descriptive and causal-experimental methods were used in Phase 3 of the study. Maribor, the second largest city in Slovenia, was chosen as the study location due to its central regional role in Lower Styria. The city lies between the Piramida and Kalvarija hills in the north and Pekrska gorca and Pohorje in the south. Here the Drava changes from a mountain stream to a calmer river as it flows into the Pannonian plain and is an important urban focal point. The left bank is characterized by historic squares, churches, and monuments, while the right bank consists mainly of residential and industrial areas. Maribor’s architecture combines eras from the Middle Ages to modern times. Medieval structures, squares, and cobblestone streets have been preserved in the old town.

4.1. Understanding the Role of the Sustainability Coefficient (Sn) in Measuring Environmental Well-Being

To explore the validity of the sustainability coefficient (Sn), the focus was on basic urban typologies such as the street, square, and city park. The final decision for the study site was influenced by the conviction of the users who argued for the illumination likability of these areas. When selecting sites for the more detailed analysis, we ensured that the average score for illumination likability was L ≥ 3.00. If the lighting attractiveness is lower, the calculation of Sn is not relevant because the site is not perceived as attractive regardless of the perceived illuminance intensity. With a value of 3.00 on a five-level evaluation scale, we can say with at least 60% probability that the illumination is likable. To capture the sustainability coefficient, we add a new constraint to it (Equation (4)).

$$\left\{\begin{array}{c}\mathrm{L}\ge 3.00,\mathrm{t}\mathrm{h}\mathrm{e}\mathrm{n}\mathrm{S}\mathrm{n}\mathrm{i}\mathrm{s}\mathrm{c}\mathrm{a}\mathrm{l}\mathrm{c}\mathrm{u}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{d}\\ \mathrm{L}<3.00,\mathrm{t}\mathrm{h}\mathrm{e}\mathrm{n}\mathrm{S}\mathrm{n}\mathrm{i}\mathrm{s}\mathrm{n}\mathrm{o}\mathrm{t}\mathrm{c}\mathrm{a}\mathrm{l}\mathrm{c}\mathrm{u}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{d}\end{array}\right.$$

(4)

In the context of a five-level evaluation scale, a rating of 3 functions as a median value and thus as a threshold for acceptability. People often view median values as neutral. Anything above the median value can be considered positive, while anything below it is potentially negative. Illumination likability above the median value means that the lighting is suitable for most users. This means that the lighting meets most needs and is generally acceptable. A value below 3.00 is considered unsatisfactory or inadequate, i.e., too dim, too strong, or annoying in some way.

The desire to achieve a high value for illumination likability encourages setting a high standard for lighting quality in public areas. This means that designers and contractors are more likely to focus on providing high-quality lighting with better and innovative lighting solutions.

In the main part of the research, we aimed to validate the sustainability coefficient Sn. The main focus was on streets (urban local streets, streets in pedestrian zones, streets in the medieval part of the city) and urban squares. These areas have the highest importance value and missing value in terms of environmental lighting (Table 1). After careful consideration, the category of city park was added as a basic urban category. In the cultural environment studied, it is not common to visit the park frequently at night. Nevertheless, respondents rated the importance value (3.56) and missing value (3.34) of footpath lighting in the city park as relatively high (Table 1). All basic urban settings were therefore covered: streets, squares, and parks.

Among all the possibilities, ten centrally located sites in the city of Maribor were selected according to the principle of diversity. The condition for selection was that the average value for illumination likability was ≥ 3.00. The following locations were selected:

(a) Streets: Gosposka Street (L1), Poštna Street (L2), Kocljeva Street (L3), Vojašniška street (L4);

(b) Squares: Leon Štukelj Square (L5), Castle Square (L6), Main Square (L7), Liberty square (L8);

(c) Parks: Slomšek Square (L9), City Park Maribor (L10).

A pocket park is situated at the Slomšek sSquare location (L9). It bears the name of a square but has all the features of a small park.

Further investigation evaluated the sustainability coefficient for each selected location. Before the experiment, all participants were familiarized with the research sites. They had visited these sites previously. All researched sites were evaluated using a questionnaire. The questionnaire was completed in a classroom, with large-scale images of each location projected on the wall to help participants remember and empathize with the environments. The respondents rated the relation between illumination likability and illuminance intensity on a five-level evaluation scale. The question of the questionnaire was the following: “Evaluate the illumination Likeability and the Illuminance Intensity of the listed locations”. The results are given in Table 2 and shown in Figure 1, Figure 2 and Figure 3.

The sustainability coefficient (Sn) varies from place to place, suggesting that people do not perceive lighting uniformly in different urban environments. This could be due to the different architectural features, the purpose of the areas, or the environmental conditions. The research results in

Table 3. Descriptive measurements of the illumination intensity and likability of the locations and the results of the sustainability coefficient.

	Case Study Location	Illumination Likability (L)		Illuminance Intensity (I)		Sn
		$\overline{\mathit{x}}$L	σ	$\overline{\mathit{x}}$I	σ
Street	L1 Gosposka Street	3.12	0.727	3.30	0.677	0.97
	L2 Poštna Street	3.16	0.073	2.87	0.780	1.12
	L3 Kocljeva Street	3.49	0.902	3.71	0.850	0.96
	L4 Vojašniška Street	3.24	0.947	2.90	0.824	1.14
Square	L5 Štukelj Square	4.09	0.911	4.10	0.822	1.00
	L6 Castle Square	3.34	0.803	3.28	0.727	1.04
	L7 Liberty Square	3.25	0.831	3.40	0.830	0.98
	L8 Main Square	3.05	0.863	2.86	0.847	1.09
Park	L9 Slomšek Square	3.34	0.803	3.28	0.727	1.04
	L10 City Park Maribor	3.14	0.955	2.53	0.851	1.26

$\overline{x}$, arithmetic mean; σ, standard deviation; Sn, normalized sustainability coefficient.

show that the value of Sn varies from 0.96 to 1.26. This means that there are significant differences among the studied locations, which can also be seen in Figure 2.

For streets, the Sn values are quite close to 1.00 (between 0.96 and 1.14). This indicates that the illumination likability and intensity on the streets are close. L4 Vojašniška Street stands out with the highest quotient of 1.14, indicating relatively higher likability compared to perceived brightness. In the squares, the Sn values are very close to 1.00 and range from 0.98 to 1.09, indicating that the lighting in the squares seems to be generally balanced in terms of likability and brightness. L5 Štukelj Square has a still satisfactory balanced score of 1.00. In the parks category, there is a slightly wider spread with Sn values of 1.04 and 1.26. L10 City Park Maribor stands out with a higher Sn value compared to all the sites studied (1.26), suggesting that its low illuminance is more sympathetic than one would expect based on brightness alone. The result obtained proves that illumination likability is not directly proportional to perceived illuminance intensity. Even less well-lit areas are very important for people’s well-being.

The standard deviations in illumination likability and intensity are quite close for most locations. This indicates that participant responses may be consistent. However, some locations such as L2 Poštna Street show a notable difference in the standard deviations of likability and intensity.

As seen in Figure 2, no location has a significantly low Sn value, indicating that the lighting of a location is perceived as too bright compared to its attractiveness. The majority of locations have an Sn value ≥1, indicating that the lighting compliance is achieved. This indicates that most of the locations have succeeded in balancing the illumination likability with the perceived brightness. No location is far below the threshold, three of them (L1 Gosposka Street, L3 Kocljeva Street, and L7 Liberty Square) are just below 1.00, indicating that lighting compliance has not been fully achieved in these areas. All three locations show a relatively high average value for illuminance intensity (l) value (3.30; 3.71; 3.40) compared to the other locations, but a relatively low illumination likability (L) value (3.12; 3.49; 3.25).

The Pearson product–moment correlation coefficient (r) between the average values of illuminance intensity and illumination likability is r = 0.841. This indicates a high positive correlation between the two variables. In principle, the higher the illuminance intensity, the greater the illumination likability. This situation is best illustrated by the example of L5 Leon Štukelj Square. However, it can happen that we illuminate too much and thus do not achieve greater illumination likability. In this case, unnecessary energy consumption and light pollution will only increase. The limit value Sn = 1.00 indicates the value up to which it makes sense to increase illuminance intensity in order to fulfil the two basic attributes of sustainability—reasonable energy consumption and low light pollution.

4.2. Assessing Subjective Indicators of Lighting Quality

The next objective in Phase 4 of the present study was to confirm the validity of the sustainability coefficient (Sn) by analyzing subjective indicators of environmental comfort for all selected sites. For this step, the SEC method (suitable for everyone, environmentally accepted, cost-effective) [11] was used. This assessment included an examination of the subjective indicators under the ‘suitability for everyone’ dimension. The complete model SEC is presented in the Supplementary Materials as Table S1. Each location was examined using the psychological, sociological, and aesthetic-functional factors with associated indicators and aspects using five-level questionnaire term options within two extremes. The complete table is presented in the Supplementary Materials as Table S2.

The standardized assessment of the sociological factor was further refined. The frequency of nighttime visits to a particular place is of paramount importance because it reveals how we subconsciously perceive that place during nighttime hours. This perception is expressed in our willingness to visit the place after dark. This is essentially related to our mental acceptance of a particular place and its illumination at night. We added to this aspect by examining the activities we are willing to undertake in each place. Activities such as walking, sitting, socializing, and playing were included in the study. This part of the survey was also conducted with the same group of 200 people that we used in the introduction and first part of the survey. The results are shown below.

The data collected by a questionnaire were statistically processed and analyzed. The results in the

Table 4. Descriptive measurements of the individual feeling indicator.

Case Study Location		Attraction		Pleasantness		Relaxation		Sn
		$\overline{\mathit{x}}$	σ	$\overline{\mathit{x}}$	σ	$\overline{\mathit{x}}$	σ
Street	L1 Gosposka Street	3.06	1.043	2.89	0.966	2.89	0.822	0.97
	L2 Poštna Street	2.85	1.220	2.91	1.214	2.84	1.029	1.12
	L3 Kocljeva Street	3.36	1.013	3.37	0.952	3.28	0.820	0.96
	L4 Vojašniška Street	3.08	1.127	2.95	1.138	3.06	1.117	1.14
Square	L5 Leon Štukelj Square	4.18	0.910	4.25	0.747	4.03	0.921	1.00
	L6 Castle Square	3.50	0.874	3.48	0.879	3.33	0.827	1.04
	L7 Liberty Square	2.16	0.979	2.23	1.044	2.37	0.963	0.98
	L8 Main Square	3.43	0.871	3.39	0.884	3.30	0.783	1.09
Park	L9 Slomšek Square	3.59	0.979	3.59	0.941	3.41	0.957	1.04
	L10 City Park Maribor	4.00	1.025	3.92	1.063	3.67	1.103	1.26

$\overline{x}$: arithmetic mean; σ: standard deviation.

,

Table 5. Descriptive measurements of the Attracting attention indicator.

Case Study Location		Composition		Arouse Interest		Stimulation		Sn
		$\overline{\mathit{x}}$	σ	$\overline{\mathit{x}}$	σ	$\overline{\mathit{x}}$	σ
Street	L1 Gosposka Street	2.86	1.004	2.94	1.011	2.95	0.963	0.97
	L2 Poštna Street	2.27	1.003	2.86	1.171	2.78	1.122	1.12
	L3 Kocljeva Street	2.68	0.868	3.17	0.996	3.14	0.981	0.96
	L4 Vojašniška Street	2.59	0.973	2.94	1.061	2.74	0.999	1.14
Square	L5 Leon Štukelj Square	3.12	1.167	4.25	0.813	4.10	0.862	1.00
	L6 Castle Square	2.76	0.840	3.17	0.936	2.96	0.870	1.04
	L7 Liberty Square	2.48	1.046	2.48	1.046	2.13	0.958	0.98
	L8 Main Square	2.74	0.816	3.12	0.990	2.74	0.816	1.09
Park	L9 Slomšek Square	2.89	0.986	3.61	0.939	3.42	0.960	1.04
	L10 City Park Maribor	2.67	1.052	3.95	0.993	3.74	1.091	1.26

$\overline{x}$, arithmetic mean; σ, standard deviation.

,

Table 6. Descriptive measurements of the overview and sense of safety indicators.

Case Study Location		Overview		Sense of Safety		Sn
		$\overline{\mathit{x}}$	σ	$\overline{\mathit{x}}$	σ
Street	L1 Gosposka Street	3.29	0.906	3.13	0.963	0.97
	L2 Poštna Street	2.79	1.115	2.78	1.152	1.12
	L3 Kneza K. Street	3.76	0.915	3.44	0.895	0.96
	L4 Vojašniška ulica	2.86	1.152	2.65	1.111	1.14
Square	L5 Leon Štukelj Square	4.40	0.679	4.13	0.814	1.00
	L6 Castle Square	3.65	0.890	3.44	0.883	1.04
	L7 Liberty Square	2.12	1.028	2.25	1.025	0.98
	L8 Main Square	3.58	0.870	3.30	0.919	1.09
Park	L9 A.M. Slomšek Square	3.31	1.039	3.29	1.000	1.04
	L10 City Park Maribor	3.52	1.027	3.25	1.189	1.26

$\overline{x},$ arithmetic mean; σ, standard deviation.

,

Table 7. Descriptive measurements of the land use indicator.

Case Study Location		Usage Intensity		Sn
		$\overline{\mathit{x}}$	σ
Street	L1 Gosposka Street	2.32	1.055	0.97
	L2 Poštna Street	2.40	1.173	1.12
	L3 Kneza K. Street	1.83	0.882	0.96
	L4 Vojašniška Street	2.59	1.126	1.14
Square	L5 Leon Štukelj Square	2.20	1.047	1.00
	L6 Castle Square	2.22	1.046	1.04
	L7 Liberty Square	2.10	0.977	0.98
	L8 Main Square	2.53	1.116	1.09
Park	L9 A.M. Slomšek Square	2.52	1.160	1.04
	L10 City Park Maribor	1.77	0.895	1.26

$\overline{x}$, arithmetic mean; σ, standard deviation.

,

Table 8. Descriptive measurements of the indicator land use for activities.

	Case Study Location	Walking		Sitting		Socializing		Playing		Sn
L/I		$\overline{\mathit{x}}$	σ	$\overline{\mathit{x}}$	$\overline{\mathit{x}}$	σ	σ	$\overline{\mathit{x}}$	σ
Street	L1 Gosposka Street	3.60	0.957	1.99	0.913	2.24	0.999	1.50	0.730	0.97
	L2 Poštna Street	2.98	1.103	3.05	1.401	3.21	1.325	1.54	0.838	1.12
	L3 Kneza K. Street	3.74	0.898	2.36	1.125	2.32	1.092	1.58	0.835	0.96
	L4 Vojašniška Street	3.49	1.061	2.80	1.311	2.82	1.287	1.69	0.090	1.14
Square	L5 L. Štukelj Square	4.37	0.725	3.91	1.008	3.83	0.993	2.53	1.194	1.00
	L6 Castle Square	3.79	0.838	3.31	1.086	3.37	1.038	1.95	0.901	1.04
	L7 Liberty Square	2.64	1.043	1.92	0.945	2.04	0.994	1.49	0.757	0.98
	L8 Main Square	3.75	0.861	3.02	1.123	2.90	1.107	1.89	0.929	1.09
Park	L9 A.M. S. Square	3.75	0.849	3.01	3.11	3.30	1.142	3.11	1.086	1.04
	L10 City Park M.	3.85	0.993	3.55	3.67	3.34	1.266	3.67	1.086	1.26

$\overline{x}$, arithmetic mean; σ, standard deviation.

,

Table 9. Descriptive measurements of the site aesthetic indicator.

Case Study Location		Space Arrangement		Sn
		$\overline{\mathit{x}}$	σ
Street	L1 Gosposka Street	3.40	0.908	0.97
	L2 Poštna Street	3.12	1.020	1.12
	L3 Kneza K. Street	3.87	0.881	0.96
	L4 Vojašniška Street	3.32	1.006	1.14
Square	L5 Leon Štukelj Square	4.44	0.684	1.00
	L6 Castle Square	3.71	0.788	1.04
	L7 Liberty Square	2.73	1.037	0.98
	L8 Main Square	3.67	0.752	1.09
Park	L9 A.M. Slomšek Square	3.74	0.859	1.04
	L10 City Park Maribor	4.00	0.851	1.26

$\overline{x}$, arithmetic mean; σ, standard deviation.

and

Table 10. Descriptive measurements of the artificial light effect indicator during the night-time.

	Case Study Location	Comfort		Fascination		Compliance		Sn
		$\overline{\mathit{x}}$	σ	$\overline{\mathit{x}}$	σ	$\overline{\mathit{x}}$	σ
Street	L1 Gosposka Street	2.25	0.981	2.29	1.005	2.42	1.029	0.97
	L2 Poštna Street	3.08	0.924	2.33	1.170	2.53	1.164	1.12
	L3 Kneza K. Street	2.99	1.012	2.95	1.026	3.20	1.027	0.96
	L4 Vojašniška Street	3.00	0.995	2.33	1.071	3.02	1.150	1.14
Square	L5 Leon Štukelj Square	3.97	1.098	4.47	0.776	4.33	0.832	1.00
	L6 Castle Square	3.01	0.962	2.59	1.048	2.87	1.055	1.04
	L7 Liberty Square	2.63	0.937	1.71	0.884	2.09	1.023	0.98
	L8 Main Square	3.01	0.943	2.63	1.014	2.98	1.046	1.09
Park	L9 A.M. Slomšek Square	2.89	1.153	3.01	1.063	3.11	1.086	1.04
	L10 City Park Maribor	3.59	1.057	3.55	1.124	3.67	1.086	1.26

$\overline{x}$, arithmetic mean; σ, standard deviation.

represent the arithmetic mean and standard deviation σ evaluation according to the SEC model for 3 factors (psychological, sociological and aesthetic-functional), 7 indicators (individual feeling, attracting attention, orientation ability, sense of safety, land use, site aesthetic, and artificial light effect) and 13 aspects (attraction, pleasantness, relaxation, composition, arouse interest, stimulation, overview, safety, usage intensity, space arrangement, fascination, comfort, and compliance). The remaining two dimensions of the SEC model for the selected ten locations were not specifically studied in this context.

When analyzing the results, we mainly examined the parameters’ arithmetic mean and standard deviation, as well as a possible coincidence with the value of the coefficient Sn in relation to the interval Sn < 1.00 and Sn ≥ 1.00. We paid particular attention to the sites that were rated unsatisfactory (Sn < 1.00) and to the site that was rated Sn = 1.00 (still satisfactory balanced).

4.2.1. Psychological Indicators of Environmental Comfort

First, participants rated the featured location based on a psychological factor. This corresponds to the relevant metrics of the SEC model, which emphasize indicators such as individual feeling, attracting attention, orientation ability, and sense of safety. Participants rated aspects such as attraction, pleasantness, relaxation, composition, arousing interest, stimulation, overview, and safety using a five-level evaluation scale. The survey asked, “Imagine yourself in the location pictured. How would you rate the scene?” The options ranged from two opposite feelings, such as for example: 1, not attractive—5, attractive. A rating of 3 meant neutrality (for example, neither unattractive nor attractive). The comparative ratings for the individual aspects are shown in Table 4, Table 5 and Table 6. In order to increase the readability of the data, reference Sn values for individual locations have been added to each table.

L1 Gosposka Street has balanced scores, with a peak in overview (3.29), indicating a satisfactory overall view and safety (3.13). L2 Poštna Street scores slightly lower, with a low composition score (2.27), suggesting its design may lack harmony. Safety and stimulation are average. L3 Kocljeva Street scores high in attraction, pleasantness, and relaxation, with top marks in overview (3.76) and safety. L4 Vojašniška Street has average scores, with lower marks for composition and safety. L5 Leon Štukelj Square stands out in all categories, suggesting it is attractive and safe. L6 Castle Square is similarly appealing, with good overview scores. L7 Liberty Square scores the lowest, indicating it is less attractive and safe. L8 Main Square has strong, balanced scores, making it a central area. L9 Slomšek Square pocket park scores well, especially for interest and safety, offering a pleasant environment. L10 City Park Maribor scores high in attraction and interest, though its composition is a bit lower. Overall, L5 Leon Štukelj Square and L10 City Park Maribor are the most attractive, while L7 Liberty Square has the lowest scores. L10 City Park Maribor shows the most variability.

If we compare the Sn values with the values of the psychological indicators, we can conclude that almost all locations (except L7 Liberty Square) are perceived as more or less likable with satisfactory values of the psychological indicators. L1 Gosposka Street and L3 Kocljeva Street do not meet the Sn ≥ 1.0 requirement, although the psychological indicators are around the average value. In this context, the illuminance intensity value is too high, and the places are perceived as too illuminated. In these two cases, the illumination level does not increase the value of the psychological factor, nor does it guarantee that the lighting is pleasant. Therefore, it is recommended to reduce the illumination level. L7 Liberty Square indicates a place that is not accepted by users because the values in all categories are extremely low. In this case, reducing the illuminance alone would not achieve the desired positive effect. In the comparative analysis of the coefficient Sn and the dispersion of the samples, represented by the standard deviation σ, we cannot find any correlation.

4.2.2. Sociological Indicators of Environmental Comfort

Based on the sociological factor, participants rated the land use and intensity of use of the site. On a five-point rating scale, they indicated how frequently they visit the site (e.g.: 1, never visit; 3, occasionally visit; 5, frequently visit). The survey asked, “How often do you visit the site during the dark hours of the day, evening, and night?” It is thought that a higher rate of visitation correlates with a wider range of activities undertaken there, such as walking, sitting, socializing, and playing. Data for both responses can be found in Table 7 and Table 8.

The results show that all studied sites have relatively low nighttime visitation (all are below the median). There are no major differences in visitation frequency. The location with the highest visit frequency is L4 Vojašniška Street with a value of 2.59, while the location with the lowest visit frequency is L10 City Park Maribor with a value of 1.77. In the studied cultural environment, it is not common to visit parks frequently at night.

We cannot find any correlation between the Sn values, standard deviation σ and sociological indicators. To gain a deeper understanding of these observations, we supplemented this aspect by examining the activities that people are willing to engage in at each site. We focused on specific activities such as walking, sitting, socializing, and playing. The nuances of how people interact with these spaces can offer insights that broad metrics like frequency of use cannot capture.

Table 8 provides a detailed overview of various activities. L5 Leon Štukelj Square and L10 Maribor City Park dominate as by far the most suitable locations for activities. L7 Liberty Square seems to be the least suitable location. As expected, the results show that not all the studied locations are equally suitable for activities. Location suitability is also indicated by the height of the Sn. We can see that locations with Sn < 1.00 also have a lower rating for individual activities than other locations with Sn ≥ 1.00. The value of Sn also indicates the suitability of the site for performing various activities.

4.2.3. Aesthetic-Functional Indicators of Environmental Comfort

Using the aesthetic-functional factors, participants assessed two primary indicators: site aesthetic, and artificial light effect. Evaluation criteria included aspects like space arrangement, fascination, comfort, and compliance, all rated on a five-level evaluation scale. The questionnaire posed two questions: “Visualize yourself in the depicted location. How would you rate its organization?” Ratings ranged from 1 (messy) to 5 (orderly). To assess the effect of the lighting, participants were asked, “How do you perceive the lighting?” Choices ranged from 1 (not fascinating) to 5 (fascinating), 1 (unpleasant glare) to 5 (pleasant glare), and 1 (incompatible) to 5 (compatible). The results of the comparison can be found in Table 9 and Table 10.

L1 Gosposka Street has a decent space arrangement (3.4), but the lighting lacks comfort (2.25) and fascination (2.29), and it does not quite meet nighttime aesthetic standards (2.42). L2 Poštna Street is more comfortable (3.08) but has average fascination (2.33) and compliance (2.53). L3 Kneza K. Street stands out with space arrangement (3.87) and decent compliance (3.2), though its lighting is only mildly captivating (2.95). L4 Vojašniška Street is well-structured (3.32), with balanced lighting and an average comfort score (3.0), but limited charm (2.33). L5 Leon Štukelj Square excels in design (4.44) and nighttime appeal (4.47), creating a soothing and captivating ambiance. L6 Castle Square is above average (3.71) but lacks strong fascination (2.59). L7 Liberty Square scores low in arrangement (2.73) and lighting charm (1.71), needing improvement. L8 Main Square offers a pleasant ambiance (3.01) and captivating lighting (2.63), with most standards met (2.98). L9 Slomšek Square has clean architecture (3.74) and lighting that provides safety and intrigue (3.01), though it is less captivating. L10 Maribor City Park excels in structure (4.0), comfort (3.59), and fascination (3.55), with lighting that meets standards well (3.67).

We cannot find any correlation between the Sn values, the standard deviation σ and the aesthetic-functional indicators of environmental comfort. Once again, L5 Leon Štukelj Square consistently performs best on all four parameters. It appears to be the most preferred or well-developed location among those listed, based on the categories of arrangement, comfort, fascination, and compliance. L7 Liberty Square performs the worst on three of the four parameters (arrangement, fascination, and compliance).

The majority of the analyzed locations have a Sn value of greater than or equal to 1.00, which means that the lighting compliance is achieved. This indicates that most of the locations have managed to achieve a balance between the illumination likability and the perceived illuminance intensity. No location is far below the threshold, although three of them are just below 1.00, suggesting that lighting compliance has not been fully achieved in these areas.

For locations with a Sn < 1.00, the lighting conditions need to be reviewed. Adjustments can be made either by improving the aesthetics or comfort of the lighting to make it more attractive, or by possibly reducing the intensity if it is perceived as too overwhelming. In contrast, locations with a Sn ≥ 1.00 have achieved a satisfactory balance, so no major changes are required unless other factors or feedback suggest otherwise.

4.3. Correlation Between Individual Aspects and Sn Coefficient Value

Sn is derived as a basic subjective measure that combines two subjective factors. It is a quantitative measure of the impact of the current state. Knowing its value gives us entry-level information about a location, but most importantly, it warns us of situations that are inappropriate, indicate an inappropriate economic situation due to excessive energy consumption, or indicate possible light pollution.

When looking at the evaluation results, as shown in Figure 3, we have relatively consistent values for the psychological and the aesthetic-functional factor. Only the sociological factor with the usage intensity aspect deviates slightly from the movement of the values of the other aspects. It is understandable that the coincidence is not absolute, as we are dealing with statistically determined values.

The validity of the sustainability coefficient Sn is also confirmed by the existing correlation between Sn and subjective indicators of environmental comfort. Figure 4 shows the correlation between psychological, sociological, aesthetic-functional factors and the Sn. The strength and direction of these relationships can provide insight into how changes in these aspects might affect Sn. The factors related to psychological aspects generally show a moderate correlation with Sn, whether positive or negative. Aesthetic-functional factors show varying correlations with Sn, with “comfort” showing the strongest positive relationship. As already shown in Figure 4, the correlation coefficient now confirms once again that sociological factors, in particular “Usage Intensity”, appear to have a negligible relationship with Sn.

Since we cannot prove the correlation between Sn and the sociological factor as a whole, we check whether there is at least a partial connection between Sn and individual activities. The results in Figure 5 show a very high positive correlation between Sn and the activities “playing” and “sitting”. In contrast, the correlation with “walking” is almost negligible. The activity “socializing” also shows a moderate positive correlation, but this is weaker compared to “playing” and “sitting”.

The results obtained are not surprising and are in line with Gehl’s theory. Gehl [49] (pp. 11–14) introduced a method based on probability theory to understand the effects of the physical environment on behavior. He hypothesized that the physical environment can influence the number of people using open spaces, the duration of individual activities, and the type of activities that occur. He categorized activities into three groups: “Necessary activities” (mandatory, with no choice for participants), “Optional activities” (voluntarily chosen by individuals) and “Social activities” (those that arise spontaneously under appropriate spatial conditions). Walking is a necessary activity that is carried out in all cities and under all spatial conditions, including spatial illumination. The relationship with Sn is therefore negligible. Socializing is an optional activity and shows a stronger positive correlation with Sn. Playing and sitting are social activities that show the strongest positive correlation with Sn.

When reviewing the assessment of individual locations, we find the following situations for cases when it is Sn < 1.00:

(a) illuminance intensity is sufficient, but the location is not perceived as attractive enough (example L1 Gosposka Street), a complete architectural redesign is needed to increase Sn;

(b) the illuminance is too high, the location is otherwise perceived as attractive (example L3 Kocljeva Street), a lower illuminance is required to increase Sn;

(c) the illuminance intensity is not sufficient, and the location is not perceived as attractive (example L7 Liberty Square). Even if we increase the illumination intensity, this will not lead to a satisfactory result. A complete architectural redesign is required.

In cases where Sn ≥ 1.00, we tend towards the following scenarios:

(d) the illuminance intensity is low, but the location is perceived as attractive (example L10 City Park Maribor).

Otherwise, another scenario is possible where Sn is very close to 1.00:

(e) illuminance intensity is high; the location is perceived as attractive (example L5 Leon Štukelj Square).

In summary, it can be said that the results obtained using the SEC method correlate very well with the Sn values. The validity of the sustainability coefficient is confirmed. This also confirms the usefulness of using the sustainability coefficient as a basic tool for assessing the quality of the lighting ambience in all urban areas such as streets, squares, and parks. The calculation of the sustainability coefficient Sn provides sufficient information about the condition of outdoor lighting ambiences. Due to the existing correlation, Sn can replace the spatial analysis by individual factors and corresponding aspects.

5. Conclusions

In the urban environment, artificial night light fulfils a dual purpose: functionality and aesthetics. It ensures the safety of users and enhances the visual appeal of public spaces, from ornate streetlights to illuminated architectural marvels. But as the article describes, finding the right balance between functional benefit and visual pleasure is not easy. Individual perceptions, cultural nuances, and context-specific requirements must be taken into account when designing lighting solutions. This discourse on outdoor lighting emphasizes a paradigm shift from purely objective measures of illumination to subjective interpretations of visual comfort that depend on the needs of the user in a particular environment. The introduction of the sustainability coefficient (Sn) represents an innovative approach to assessing lighting quality. By capturing the mood of the public in terms of perceived illumination likability versus illuminance intensity, the Sn provides a unique tool to assess the “rightness” of lighting in public spaces.

The survey highlights the importance of lighting different urban facets, from focal points to wider public spaces. The feedback from 200 participants, students from the University of Maribor, offered insightful findings about their perceptions and values in relation to urban lighting. In light of the results, it is clear that while the need for lighting is unanimously recognized, the importance of lighting for different urban spaces and objects is perceived differently. These perceptions depend on specific needs, activities, and experiences. The empirical study focused on various urban typologies such as streets, squares, and parks. The sustainability coefficient (Sn) varied between the different locations, suggesting that individuals’ perception of lighting is not uniform across urban environments. These variations could be due to different architectural features, the intended purposes of the spaces, or the environmental conditions.

The subsequent phase of research aimed to confirm these observations. Using the SEC method (suitable for everyone, environmentally accepted, cost-effective) and SEC model, each site was analyzed for psychological, sociological, and aesthetic parameters. While most sites achieved consistently satisfactory results, there is a clear difference between outstanding sites and those in need of improvement. The SEC model proved invaluable in identifying these nuances. Applying the SEC methodology allowed for a comprehensive examination of the relationship between various factors and Sn. A key finding is that psychological and aesthetic-functional factors correlate moderately with Sn, while the sociological factors, particularly “Usage Intensity”, show minimal correlation. However, on closer inspection, the study found that individual activities within the sociological factor, such as “playing” and “sitting”, showed a strong positive correlation with Sn. This is related to Gehl’s theory [49], which categorizes activities and their potential relationships with the environment. The evaluation of individual locations revealed a range of scenarios resulting from the interplay between lighting intensity and aesthetic perception. These ranged from locations that needed a complete architectural overhaul to improve Sn to others that simply needed an adjustment in light intensity.

This study makes several important contributions to the scientific understanding of urban lighting and its relationship to environmental comfort and human behavior:

(1) Quantitative measurement with subjective components: In the study, the sustainability coefficient Sn is used as a quantifiable measure that includes two subjective components. Such measures provide a bridge between the quantitative and qualitative by providing objective metrics that nevertheless capture the nuances of human perception and experience.

(2) The lighting compliance value was established: For all case studies where Sn ≥ 1.00, lighting compliance is achieved, i.e., sustainable city lighting is also ensured towards efficient energy consumption and reduced light pollution.

(3) Correlation Insights: There are correlations between Sn and various psychological and aesthetic-functional factors. An extended factor analysis can provide valuable insights into the variables that influence environmental comfort the most. However, using the statistical coefficient Sn is an equivalent tool that allows us to get results faster.

(4) Deep dive into sociological factors: A detailed examination of the correlation of sociological factors and Sn, especially individual activities such as “playing”, “sitting” and “walking”, provides a more detailed understanding of human behavior in illuminated spaces. In conjunction with Gehl’s theory, this provides a solid framework for anticipating and shaping human activities in urban spaces. With the exception of walking, all activities correlate with Sn.

(5) Confirmation of the hypotheses: The research successfully confirms the hypothesis that it is possible to develop a suitable and simple method to assess the quality of the light ambience in different urban open spaces. The introduction of the sustainability coefficient (Sn) effectively quantifies the compliance of urban lighting with the principles of sustainable design by integrating subjective factors such as illumination likability and perceived illuminance intensity. We have confirmed that the value of the sustainability coefficient warns us against excessive lighting. The subjective perception of intense lighting with low lighting sympathy only leads to energy loss and light pollution. The results of the study confirm the effectiveness and applicability of the Sn in real environments and pave the way for improved lighting concepts in cities where environmental friendliness and visual safety are paramount.

(6) Recommendations for practical implications: The research offers actionable recommendations. These include possible adjustments to lighting intensity, aesthetic improvements, or even complete architectural redesigns. This practical dimension ensures that the results of the study can be directly applied in urban planning and design. The inclusion of specific places as case studies gives the results a real context that makes them comprehensible and implementable. It provides other cities or researchers with a benchmark against which they can compare their outputs or replicate the study in their own context.

In summary, it can be said that the sustainability coefficient (Sn) can be used normatively in urban planning to define sustainable and user-oriented lighting standards. By using Sn as a benchmark, cities can regulate lighting systems to meet thresholds for both energy efficiency and subjective factors, such as ease of lighting and perceived illuminance. Regular assessments using Sn can guide retrofit and optimization measures, while public procurement can require that lighting projects balance environmental sustainability and human-centered design. Sn can also be used in the redesign of cities to ensure that lighting improves environmental comfort, perceived safety, and aesthetic quality. In addition, incorporating Sn into sustainability certification programs and community feedback mechanisms can help align lighting solutions with public needs and environmental goals.

Future studies that delve deeper into public surfaces will be essential to further demystify the complicated dynamics of urban lighting preferences. To improve the generalizability of results, future studies should aim to analyze a broader range of urban locations, possibly across multiple cities or even countries. Longitudinal studies could also investigate how changes in urban lighting over time (either through technological advances or deliberate interventions) affect Sn value and people’s perception of spaces. With the advent of smart city technologies, future research could focus on how adaptive lighting systems that change according to time of day, density of people or specific events affect environmental comfort and Sn levels.

For the future, the author very much hopes that the use of the Sn coefficient will be a fundamental tool to assess the quality of outdoor lighting ambiences and an important aid to enrich the knowledge base, providing actionable insights to urban planners, designers, and policy makers. It is a simpler and faster method and an upgrade to SEC methodology or a similar methodology. Testing just two questions is just as effective. This insight is a fundamental contribution to the existing science.