Next Article in Journal
Energy Solutions for Decarbonization of Industrial Heat Processes
Previous Article in Journal
Predicting CO2 and H2 Solubility in Pure Water and Various Aqueous Systems: Implication for CO2–EOR, Carbon Capture and Sequestration, Natural Hydrogen Production and Underground Hydrogen Storage
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Energies
Volume 17
Issue 22
10.3390/en17225727
energies-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

A Paradox of LED Road Lighting: Reducing Light Pollution Is Not Always Linked to Energy Savings

by
Irena Fryc
1,
Maciej Listowski
1,
Christophe Martinsons
2,
Jiajie Fan
3 and
Dariusz Czyżewski
4,*
1
Faculty of Electrical Engineering, Bialystok University of Technology, Wiejska 45d, 15-351 Bialystok, Poland
2
CSTB, Centre Scientifique et Technique du Bâtiment, Division Acoustique, Vibrations, Eclairage et Electromagnétisme, Saint Martin d’Heres, 75016 Paris, France
3
Institute of Future Lighting, Academy for Engineering & Technology, Fudan University, and Shanghai Research Center for Silicon Carbide Power Devices Engineering & Technology, Shanghai 200433, China
4
Faculty of Electrical Engineering, Warsaw University of Technology, Pl. Politechniki 1, 00-661 Warsaw, Poland
*
Author to whom correspondence should be addressed.
Energies 2024, 17(22), 5727; https://doi.org/10.3390/en17225727
Submission received: 25 October 2024 / Revised: 8 November 2024 / Accepted: 13 November 2024 / Published: 15 November 2024
(This article belongs to the Section B: Energy and Environment)
Browse Figures
Versions Notes

Abstract

:
A variety of LED types can be employed for street and road lighting purposes. White phosphor-converted LEDs represent the most widely used option. However, amber LEDs are increasingly being used to reduce some negative effects associated with light pollution. These LEDs can be manufactured using both phosphor-converted and monochromatic direct chip technologies. This paper addresses the link between the reduction in short-wavelength light emissions which contribute to sky glow and the energy efficiency of LED-based road lighting. This paper focuses on an example illustrating the common misconception that reducing light pollution also means saving energy. Through the consideration of how spectral power distribution influences both mesopic vision and the amount of emitted blue light, it has been concluded that while monochromatic direct amber LEDs consume more energy than their white or amber phosphor-converted counterparts, their use in outdoor lighting is justifiable due to their potential effects of reducing sky brightness.

1. Introduction

The installation of street lighting serves two primary purposes: to enhance both the safety of pedestrians and road traffic and the visual appeal of the area. Researchers have conducted extensive studies on the optimal design of street lighting to ensure user comfort [1] and desired lighting conditions [2,3]. This involves maintaining the appropriate contrast between the object and the background [4], while limiting glare [5] to ensure comfortable viewing [6]. Additionally, studies have focused on minimizing the operating costs [7] and limiting ambient light pollution [8,9,10]. Contemporary photometric requirements for road lighting are presented in the CIE Technical Reports: CIE 88-1990 Guide for the Lighting of Road Tunnels and Underpasses [11], CIE 115-2010 “Lighting of roads for motor and pedestrian traffic” [12], and the European Standard EN 13201-2 “Road lighting—Part 2” [13]. So, the number and geometric arrangement of luminaires needed for specific types of roadways are calculated on the basis of the requirements given by these documents. The Figure 1 showing spectral power distributions of high h-pressure sodium (HPS) and low-pressure sodium (LPS) which presents the prevailing technologies for outdoor lighting for a considerable period of time. This was due to a number of factors, including their luminous efficacy (around 100 lm/W), long lifespan, and relatively low maintenance costs in comparison to older technologies such as incandescent or mercury vapor lamps.
Nowadays, white phosphor-converted light-emitting diodes (White pc-LEDs) [14,15] are gradually replacing C-MH, HPS, and LPS lamps for road lighting [16]. The introduction of White pc-LEDs into road lighting was driven by a number of factors, including their high luminous efficacy reaching 170 lm/W, but in popular practical road lighting implementations, this level is 120 lm/W [17,18,19] (if technology other than White pc-LED lighting technology is considered, for example white perovskite light-emitting diodes (pe-LEDs), the luminous efficacy can reach 200 lm/W [20,21], but this technology is not popular due to problems with stability and manufacturing consistency [20,22]). Also, their compact dimensions that facilitate the precise shaping of the luminous intensity distribution (LID) of the luminaire [23], their robust durability in outdoor illumination applications [24], the potential for a high number of LEDs to be utilized in a single luminaire, which, although limited by the size of the luminaire head, still enables the attainment of almost any desired luminous flux from the luminaire [25], the simplicity of luminous flux control and the capacity to modify the power and luminous flux in accordance with the intended application [26,27], their ability to withstand shocks [28], which is particularly crucial in the illumination of overpasses or bridges, and their lifespan now being longer than that of sodium lamps [29] makes them advantageous.
In contemporary lighting installations, White pc-LEDs [30,31] with a nominal correlated color temperature (CCT) of 4000 K and chromaticity within the 7-step 4000 K ANSI quadrangle [32,33] are preferred in many countries. However, some countries such as France now impose the mandatory use of CCT values less than 3000 K [34,35]. In order to identify the suitable LEDs that meet the specified generic requirements of a CCT of 4000 K and the chromaticity of 7 steps, the publicly available databases “Real Light Source SPDs and Color Data for Use in Research” [30] and “EMPIR 15SIB07 Photo LED—Database of LED product spectra” [31] were considered in this work. These databases contain 298 entries on LED sources that align with the desired criteria. Figure 2a illustrates their spectral distributions and Figure 2b presents their chromaticities. White pc-LEDs emit a broad spectrum of light with a significant blue content and an emission peak located around 450–470 nm. The wavelengths in that spectral range scatter more effectively in the atmosphere than longer wavelengths, and this fact increases the chance that a photon emitted upward returns to Earth as sky glow [36,37]. Moreover, this blue-rich spectrum has been demonstrated to increase glare [38] but also disrupt wildlife behavior [39,40], with a negative impact [41,42] on flora [43], fauna [44,45], and ecosystems [46,47,48]. The majority of animals, including many insects, are adapted to living in a nocturnal world [49]. In the absence of light, they can hide from predators, feed, hunt, and reproduce. Additionally, the numerous species are more sensitive to short-wavelength light [50,51], whereas amber-colored light induces less effects on them. Furthermore, exposure to artificial light, especially at night, represents a potential threat to human health [52]. This is due to the fact that it causes perturbations of the human biological clock, affecting the circadian rhythm, sleep, and other issues [53,54].
To mitigate these undesirable occurrences, some recent recommendations were made to promote the use of low-CCT orange-colored LEDs in outdoor lighting [55] with spectral power distribution (SPD) somewhat comparable to that of sodium lamps [56]. Such LEDs are called amber LEDs. Their narrow spectral distribution and the absence of short-wavelength light offer significant advantages over traditional White pc-LEDs for protecting wildlife-sensitive areas that need to be illuminated [42]. Amber LEDs emit light predominantly in the orange spectral range, typically between 590 nm and 620 nm, through two possible distinct mechanisms. Direct emission amber LEDs (amber de-LEDs) emit orange light directly from their chip with a luminous efficacy around 40 lm/W [57]. Phosphor-converted amber LEDs (Amber pc-LEDs) utilize the phosphor coating that converts blue light emitted by the LED chip into longer-wavelength amber light with luminous efficacy values around 100 lm/W. It is important to note that the luminous efficacy values of these LEDs are lower than those of both White pc-LEDs and legacy HPS and LPS lamps. Nevertheless, amber LEDs offer the possibility of being precisely controlled by “smart city” control systems, which is not feasible with sodium lamps. In addition, the reduced maintenance costs associated with them make them a preferred choice over legacy lamps [58]. It is crucial to recognize that in order to maintain the same illuminance levels, the consumption of electricity will be significantly higher when utilizing amber LED technology in comparison to White pc-LED [57,59].
The SPDs of currently available amber LEDs are illustrated in Figure 3a. The chromaticities are represented as the yellow dots for amber pc-LEDs and as the orange dots for amber de-LEDs (Figure 3b) in the CIE color space diagram. This type of diagram is also used by manufacturers to categorize amber LEDs based on zones of chromaticity tolerance. It is also important to note that different manufacturers have markedly disparate tolerance ranges for this purpose. The AE J578 APR2020 [58] standard incorporates the tolerances of amber chromaticities utilized by multiple manufacturers for the characterization of their products. Figure 3b provides a visual representation of the amber zone boundaries as defined by the standard SAE J578 APR2020 [58,60]. It is important to note that the normative chromaticity range for amber illumination is considerably broader than that of conventionally manufactured amber light-emitting diodes (LEDs) (Figure 3b). This issue is not the consequence of technological limitations as the technology used in LED manufacturing does not impose the restrictions on the ability to produce amber LEDs with chromaticities covering the full range permitted by the standards [58,61]. It is therefore possible that in the future, amber LEDs with chromaticities different from the current state of the art may become widely used.
From the perspective of outdoor lighting design, it is of paramount importance to assess whether an amber LED manufactured using any technology (characterized by the chromaticity point’s location being inside the amber zone) presents a comparable impact on light pollution, as quantified by state-of-the-art methods employed by researchers [58,63,64]. For this purpose, different existing numerical metrics are used below.
The Azul (Azul is the Spanish word for blue)-to-photopic ratio (A/P ratio) describes the ratio of a light source’s SPD S T λ between 380 nm and 500 nm to its luminous output assessed using the standard photopic luminous efficiency function V(λ). The A/P ratio (Equation (1)) is used, for instance, by The Technical Office for the Protection of Sky Quality (TOPC) of the Institute of Astrophysics of the Canary Islands (IAC). This authority defined two different upper limits for the allowed night lights: 0.25 and a more restrictive 0.15 [65].
A / P = ∫ 380 500 S T λ d λ ∫ 380 780 S T λ · V ( λ ) d λ
In addition to SPDs, certain consideration should be given to the impact of perceived brightness levels. At the level of road luminance recommended by the standard EN 13201 [13,66], the vision of the observer (a driver, a pedestrian, etc.) falls in the mesopic regime, corresponding to an intermediate range between photopic vision (typical of daytime vision) and scotopic vision (dark-adapted vision) [67,68]. As presented in CIE 191:2010 [69], in the mesopic range, the spectral sensitivity of the human eye V m e s o ,   l a m p λ depends on the averaged luminance level L a v λ and the SPD of the given light. This CIE document also details the method for determining the eye spectral sensitivity function in this luminance range. The mesopic sensitivity is calculated (Equation (2)) as a linear combination of the photopic V(λ) [70] and the scotopic V′(λ) spectral sensitivity functions. In Equation (2), the parameter m is the adaptation coefficient and M(m) is a normalization factor ensuring that the maximum value of V m e s o ,   l a m p λ is unity. The parameter m reflects the transition between photopic and scotopic vision. It is calculated iteratively based on the photopic luminance and scotopic luminance in the visual field. The detailed algorithm used to calculate its value is provided by the CIE 191:2010 document. As m approaches 1, the vision becomes fully photopic (V(λ)), and as m decreases toward 0, the vision shifts toward scotopic sensitivity (V′(λ)).
V m e s o ,   l a m p λ = 1 M m · m · V λ + 1 − m · V ′ λ
When the human eye is adapted to the mesopic conditions created by a given lighting installation, the perceived luminance L m e s o ,   l a m p has a different value to the averaged photopic luminance Lav [71]. The mesopic luminance (cd/m2) of a visual adaptation field can be calculated as follows:
L m e s o ,   l a m p = K m ,   l a m p ∫ 0 ∞ V m e s o ,   l a m p λ · L a v λ d λ
L a v λ is the luminance of the photopic condition, and K m ,   l a m p corresponds to the human eye’s maximum luminous efficacy [68]. The K m ,   l a m p factor is the photometric radiation equivalent which allows for the calculation of photometric values for the visible range (380–780) nm based on the power emitted by the light source. For mesopic vision, the K m ,   l a m p factor will be variable and will depend on the spectral distribution of the light source in question and the luminance level achieved, e.g., on the road. The value of K m ,   l a m p depends on both the L a v λ luminance level and SPD of light. The value of K m ,   l a m p is determined (Equation (4)) from the definition of the candela (SI system), taking into account that for monochromatic radiation of 555 nm, the value of K m ,   l a m p is 683 lm/W.
K m ,   l a m p = 683   l m · W − 1 V m e s o ,   l a m p f o r   λ = 555.55   n m  
The Mesopic Flux Ratio (MFR) metric (Equation (5)) [72] can be used to evaluate the light level perceived by the human eye under mesopic visual conditions. The Mesopic Flux Ratio (MFR) is a metric used to evaluate the luminous flux required by a given light source with an SPD S T λ to achieve the same mesopic brightness as a high-pressure sodium (HPS) lamp, which serves as a reference. The MFR reflects how the human eye perceives light under mesopic conditions where both photopic and scotopic vision are engaged. Combining this metric with the A/P enables a more comprehensive assessment, making it easier to determine the relationship between perceived brightness and light pollution for various types of light sources.
M F R = K m ,   l a m p · ∫ 380 780 S T λ · V m e s o ,   l a m p ( λ ) d λ K m ,   H P S · ∫ 380 780 S H P S λ · V m e s o ,   H P S ( λ ) d λ
The introduction of the Mesopic Flux Ratio metric simplifies the complex relationship between the potential for sky glow and the luminous flux required to achieve the same mesopic luminance as HPS lighting.

2. Materials and Methods

Road lighting should be designed to ensure good visibility for drivers and pedestrians [73,74,75]. In this study, we examine a typical 7 m wide road (Figure 4, Table 1) with moderate photometric requirements. This type of road has been lit in accordance with the European Standard [66] M4 lighting class requirements (Table 2). This kind of lighting is seen to offer an optimal balance between safety, visibility, and energy efficiency for medium levels of traffic [76,77].
In order to obtain the M4-class road lighting parameters, the typical luminaires based on White pc-LEDs [57,76], amber pc-LEDs, and amber de-LEDs [57] were employed (Table 3). Three luminaires with an identical luminous flux of 9002 lm and an identical luminous intensity distribution curve were considered. Due to the different luminous efficacy values of the different types of LEDs, the number of individual LEDs depends on the chosen type of LED. In the luminaires under consideration, 78 White pc-LEDs were used, 95 amber pc-LEDs were needed, and 316 amber de-LEDs luminaire were required. The luminaires utilizing White pc-LEDs operate at 90 W, which means significantly lower electricity consumption in comparison to amber LEDs which consumed 110 W for the amber pc LED technology and 273 W for the amber de LED technology [57].
To evaluate the relationship between energy consumption and light pollution potential, the 298 real SPDs of White pc-LEDs covering the 4000 K ANSI chromaticity range were considered. Given that only a limited number of amber LEDs are currently commercially available (see Figure 3), their technologically feasible SPDs were modeled [78] using spectral modeling techniques, specifically Gaussian functions [79,80,81]. This approach enabled the creation of the equivalent number of SPDs for both amber pc-LEDs (Figure 5a) and amber de-LEDs (Figure 5b) to match the number of White pc-LEDs.
Figure 6 provides a visual representation of the chromaticities of amber pc-LEDs and amber de-LEDs evenly distributed across the amber zone in the CIE 1931 chromaticity diagram.

3. Results and Discussion

The parameters of interest were calculated. Descriptive statistics were computed and are displayed in the box plot graphs. The symbol “x” on these boxes represents the mean of the given data set, while the middle line denotes the median of the set. The interquartile range (IQR) is represented by the height of the box plot. The limits of the box indicate the first (25%) and third quartile (75%). The outliers have been identified based on the data set and are indicated with a diamond symbol. The term “outlier” is defined as a value that exceeds 1.5 times the interquartile range (IQR). In the event that outliers are present, the whiskers extending from the box indicate the highest and lowest non-outlier values. In the absence of outliers, the whiskers represent the highest and lowest values within the set.
The A/P values presented in Figure 7a indicate that typical White pc-LEDs with the nominal correlated color temperature of 4000 K have a high potential to contribute to sky glow, exceeding the threshold of 0.25 defined by some light pollution regulations [65]. In contrast, significantly lower values are observed for amber pc-LEDs (Figure 7b) and amber de-LEDs (Figure 7c). The further box plot analysis shows that 50% of the A/P values for White pc-LEDs fall between 0.825 and 0.875, while the range is from 0.05 to 0.15 for amber pc-LEDs, and the range is from 0 to 0.0015 for amber de-LEDs.
However, for the required luminance level (Lav) of 0.75 cd/m2 for the M4 road class, the mesopic luminance favors the SPD of White pc-LEDs, which leads to a brighter perception of the road in comparison with high-pressure sodium (HPS) lamps (Figure 8a). The perceived mesopic luminance for amber pc-LEDs (with 50% of values between 0.68 and 0.70) is close to that of HPS lamps ( L m e s o ,   l a m p = 0.710), while the maximum mesopic luminance reaches 0.675 for amber de-LEDs, making them appear less bright. White pc-LEDs give the highest perceived mesopic luminance, with values ranging from 0.80 to 0.83. This necessitates the additional luminous flux for amber pc-LEDs and amber de-LEDs to match the mesopic brightness of the widely used White pc-LEDs.
As shown in Figure 7, while “low-impact” amber LED lighting (amber pc-LEDs and amber de-LEDs) significantly reduces sky glow compared to HPS lamps, it would require a higher luminous flux to achieve the same mesopic luminance. However, as shown in Figure 8, HPS lamps would require an even higher luminous flux to achieve the same mesopic luminance. For amber pc-LEDs, the MFR (Figure 9) ranges from 0.948 to 1.01, indicating that up to 5.2% more luminous flux is needed in some cases, while in others the difference is negligible (it is less than 1%). Amber de-LEDs are less efficient, with MFR values between 0.935 and 0.95, meaning that 5% to 6.5% more luminous flux is required to match the mesopic luminance of HPS lamps. In contrast, White pc-LEDs require 12% to 17% less luminous flux to achieve the same mesopic luminance.

4. Conclusions

This study reveals that implementing amber LED lighting with a low potential for sky glow and low impact on fauna and flora may lead to increasing energy consumption. This conclusion challenges the common belief that saving energy and protecting the environment can be simultaneously achieved.
While amber de-LEDs consume significantly more energy than White pc-LEDs, they are highly effective in reducing sky glow. This fact makes them a suitable choice for environmentally sensitive areas where protecting the nocturnal ecosystems and limiting light pollution are priorities. Despite their higher energy demands, their use can be justified when environmental considerations outweigh economic factors.
In contrast, amber pc-LEDs offer a practical compromise between energy efficiency and light pollution mitigation. Although they currently are less energy-efficient than White pc-LEDs, their reduced contribution to sky glow makes them a viable alternative for road lighting, particularly where both cost efficiency and environmental impact must be balanced.
The introduction of the Mesopic Flux Ratio (MFR) provides a quantitative framework for understanding the trade-offs between energy consumption and the potential for light pollution. The findings demonstrate that reducing sky glow through amber de-LED technology and amber pc-LED technology may require increased energy consumption to achieve the same mesopic luminance ( L m e s o ,   l a m p ) in comparison with White pc-LEDs. However, advancements in LED technologies, particularly amber de-LEDs, will undoubtedly improve their luminous efficacy, enhancing their potential in future lighting applications. The U.S. Department of Energy predicts that the luminous efficacy of amber de-LEDs will improve by ~200% within the next decade [82], potentially expanding their use in outdoor lighting applications.
In conclusion, the selection of LED technology for outdoor lighting must be weighed with the balance between energy savings and environmental impacts. It requires the careful consideration of how different spectral power distributions impact the potential for light pollution and energy efficiency. With the current state of technology, amber pc-LEDs seem to offer a balanced solution where both energy efficiency and night sky preservation are the key concerns.

Author Contributions

Conceptualization, I.F.; methodology, I.F.; software, I.F.; formal analysis, I.F., M.L., C.M., J.F. and D.C.; data curation, I.F., M.L., C.M., J.F. and D.C.; writing—original draft preparation, I.F.; writing—review and editing, I.F., M.L., C.M., J.F. and D.C.; visualization, M.L. All authors have read and agreed to the published version of the manuscript.

Funding

The APC was funded by Warsaw University of Technology: Open Science V program.

Data Availability Statement

The data sets presented in this article are not readily available because the data are part of an ongoing study.

Acknowledgments

The author would like to express his gratitude to the Warsaw University of Technology for funding the possibility of publishing the results of the conducted research.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Burattini, C.; Bisegna, F.; De Santoli, L. Street luminance and night-time walking comfort: A new perspective for the urban lighting design. J. Urban Des. 2024, 1–19. [Google Scholar] [CrossRef]
  2. Wren, B.; Locke, S. Upgraded Rig Lighting Improves Night Time Visibility While Reducing Stray Light and the Threat to Dark Skies in West Texas. In All Days; SPE: Denver, CO, USA, 2015; p. SPE-173492-MS. [Google Scholar] [CrossRef]
  3. Fotios, S. A Revised Kruithof Graph Based on Empirical Data. Leukos 2017, 13, 3–17. [Google Scholar] [CrossRef]
  4. Dunbar, C. Necessary Values of Brightness Contrast in Artificially Lighted Streets. Light. Res. Technol. 1938, 3, 187–195. [Google Scholar] [CrossRef]
  5. Lin, Y.; Liu, Y.; Sun, Y.; Zhu, X.; Lai, J.; Heynderickx, I. Model predicting discomfort glare caused by LED road lights. Opt. Express 2014, 22, 18056. [Google Scholar] [CrossRef]
  6. Liu, M.; Zhang, B.; Luo, T.; Liu, Y.; Portnov, B.A.; Trop, T.; Jiao, W.; Liu, H.; Li, Y.; Liu, Q. Evaluating Street Lighting Quality in Residential Areas by Combining Remote Sensing Tools and a Survey on Pedestrians’ Perceptions of Safety and Visual Comfort. Remote Sens. 2022, 14, 826. [Google Scholar] [CrossRef]
  7. Fryc, I.; Czyżewski, D.; Fan, J.; Gălăţanu, C.D. The Drive towards Optimization of Road Lighting Energy Consumption Based on Mesopic Vision—A Suburban Street Case Study. Energies 2021, 14, 1175. [Google Scholar] [CrossRef]
  8. Fryc, I.; Tabaka, P. Outdoor Areas Lighting with LEDs—The Competition Between Scotopic Efficacy and Light Pollution. Photonics Lett. PL 2019, 11, 75. [Google Scholar] [CrossRef]
  9. Tatro, K. Light Energy: Our Wasted Resource. Consilience 2020, 22, 65–72. [Google Scholar] [CrossRef]
  10. Fotios, S.; Robbins, C.; Uttley, J. A comparison of approaches for investigating the impact of ambient light on road traffic collisions. Light. Res. Technol. 2021, 53, 249–261. [Google Scholar] [CrossRef]
  11. CIE 88-1990; Guide for the Lighting of Road Tunnels and Underpasses. CIE: Vienna, Austria, 1990.
  12. CIE 115-2010; Lighting of Roads for Motor and Pedestrian Traffic. CIE: Vienna, Austria, 2010.
  13. EN 13201; Road Lighting-Part 2: Performance Requirements. CEN: Brussels, Belgium, 2015.
  14. Cho, J.; Park, J.H.; Kim, J.K.; Schubert, E.F. White light-emitting diodes: History, progress, and future. Laser Photonics Rev. 2017, 11, 1600147. [Google Scholar] [CrossRef]
  15. Listowski, M.; Supronowicz, R. Color quality consideration when switching from FL to LED. Photonics Lett. PL 2022, 14, 56. [Google Scholar] [CrossRef]
  16. Sȩdziwy, A.; Basiura, A.; Wojnicki, I. Roadway Lighting Retrofit: Environmental and Economic Impact of Greenhouse Gases Footprint Reduction. Sustainability 2018, 10, 3925. [Google Scholar] [CrossRef]
  17. Narukawa, Y.; Ichikawa, M.; Sanga, D.; Sano, M.; Mukai, T. White light emitting diodes with super-high luminous efficacy. J. Phys. D Appl. Phys. 2010, 43, 354002. [Google Scholar] [CrossRef]
  18. Baten, M.Z.; Alam, S.; Sikder, B.; Aziz, A. III-Nitride Light-Emitting Devices. Photonics 2021, 8, 430. [Google Scholar] [CrossRef]
  19. Zhang, S.; Liang, M.; Yan, Y.; Huang, J.; Li, Y.; Feng, T.; Zhu, X.; Li, Z.; Xu, C.; Wang, J.; et al. High Luminous Efficacy Phosphor-Converted Mass-Produced White LEDs Achieved by AlN Prebuffer and Transitional-Refraction-Index Patterned Sapphire Substrate. Nanomaterials 2022, 12, 1638. [Google Scholar] [CrossRef]
  20. Xiao, P.; Yu, Y.; Cheng, J.; Chen, Y.; Yuan, S.; Chen, J.; Yuan, J.; Liu, B. Advances in Perovskite Light-Emitting Diodes Possessing Improved Lifetime. Nanomaterials 2021, 11, 103. [Google Scholar] [CrossRef]
  21. Diouf, B.; Muley, A.; Pode, R. Issues, Challenges, and Future Perspectives of Perovskites for Energy Conversion Applications. Energies 2023, 16, 6498. [Google Scholar] [CrossRef]
  22. Weng, S.; Yu, G.; Zhou, C.; Lin, F.; Han, Y.; Wang, H.; Huang, X.; Liu, X.; Hu, H.; Liu, W.; et al. Challenges and Opportunities for the Blue Perovskite Quantum Dot Light-Emitting Diodes. Crystals 2022, 12, 929. [Google Scholar] [CrossRef]
  23. Wei, S.; Zhu, Z.; Ma, D. Efficient and compact freeform optics design for customized LED lighting. Opt. Laser Technol. 2023, 167, 109775. [Google Scholar] [CrossRef]
  24. Huang, J.; Golubovic, D.S.; Koh, S.; Yang, D.; Li, X.; Fan, X.J.; Zhang, G.Q. Degradation Mechanisms of Mid-Power White-Light LEDs Under High-Temperature–Humidity Conditions. IEEE Trans. Device Mater. Relib. 2015, 15, 220–228. [Google Scholar] [CrossRef]
  25. Magielse, R.; Frens, J.W. Hyvve—A Modular and Flexible Light System. In Proceedings of the 2013 9th International Conference on Intelligent Environments, Athens, Greece, 16–17 July 2013; ISBN 978-0-7695-5038-1. [Google Scholar]
  26. Lee, S.H.; Kwon, J.K. Distributed dimming control for LED lighting. Opt. Express 2013, 21, A917. [Google Scholar] [CrossRef] [PubMed]
  27. Zielinska-Dabkowska, K.M.; Bobkowska, K. Rethinking Sustainable Cities at Night: Paradigm Shifts in Urban Design and City Lighting. Sustainability 2022, 14, 6062. [Google Scholar] [CrossRef]
  28. Abulkhanov, S.; Goryainov, D.; Strelkov, Y. The effect of vibration on the performance of lighting devices. In Proceedings of the 2020 International Conference on Dynamics and Vibroacoustics of Machines (DVM), Samara, Russia, 16–18 September 2020. [Google Scholar] [CrossRef]
  29. Meneghini, M.; Dal Lago, M.; Trivellin, N.; Meneghesso, G.; Zanoni, E. Degradation Mechanisms of High-Power LEDs for Lighting Applications: An Overview. IEEE Trans. Ind. Appl. 2014, 50, 78–85. [Google Scholar] [CrossRef]
  30. Royer, M. Real Light Source SPDs and Color Data for Use in Research, Version 2; Figshare: Boston, MA, USA, 2023. [CrossRef]
  31. Jost, S.; Thorseth, A.; Poikonen, T.; Blattner, P.; Gerloff, T.; Kokka, A.; Dekker, P.; Smid, M.; Ferrero, A.; Kubarsepp, T.; et al. EMPIR 15SIB07 PhotoLED-Database of LED Product Spectra; Technical University of Denmark: Copenhagen, Denmark, 2021. [Google Scholar] [CrossRef]
  32. ANSI C78.377-2017; American National Standard for Electric Lamps—Specifications for the Chromaticity of Solid State Lighting (SSL) Products. American National Standards Institute: New York, NY, USA, 2017.
  33. Supronowicz, R.; Fan, J.; Listowski, M.; Watras, A.; Fryc, I. Application of different metrics for describing light color quality of white LED. Photonics Lett. PL 2021, 13, 31. [Google Scholar] [CrossRef]
  34. Arrêté du 27 Décembre 2018 Relatif à la Prévention, à la Réduction et à la Limitation des Nuisances Lumineuses. 2018. Available online: https://www.legifrance.gouv.fr/eli/arrete/2018/12/27/TREP1831126A/jo/texte (accessed on 10 November 2024).
  35. Code de l’environnement. Available online: https://www.legifrance.gouv.fr/codes/texte_lc/LEGITEXT000006074220 (accessed on 10 November 2024).
  36. Kyba, C.C.M.; Altıntaş, Y.Ö.; Walker, C.E.; Newhouse, M. Citizen scientists report global rapid reductions in the visibility of stars from 2011 to 2022. Science 2023, 379, 265–268. [Google Scholar] [CrossRef]
  37. Hao, Y.; Wang, P.; Zhang, Z.; Xu, Z.; Jia, D. A Review of the Characteristics of Light Pollution: Assessment Technique, Policy, and Legislation. Energies 2024, 17, 2750. [Google Scholar] [CrossRef]
  38. Bará, S.; Bao-Varela, C.; Kocifaj, M. Modeling the artificial night sky brightness at short distances from streetlights. J. Quant. Spectrosc. Radiat. Transf. 2023, 296, 108456. [Google Scholar] [CrossRef]
  39. Torres, D.; Tidau, S.; Jenkins, S.; Davies, T. Artificial skyglow disrupts celestial migration at night. Curr. Biol. 2020, 30, R696–R697. [Google Scholar] [CrossRef]
  40. Touzot, M.; Dumet, A.; Secondi, J.; Lengagne, T.; Henri, H.; Desouhant, E.; Duchamp, C.; Mondy, N. Artificial light at night triggers slight transcriptomic effects on melatonin signaling but not synthesis in tadpoles of two anuran species. Comp. Biochem. Physiol. Part A Mol. Integr. Physiol. 2023, 280, 111386. [Google Scholar] [CrossRef]
  41. Falcón, J.; Torriglia, A.; Attia, D.; Viénot, F.; Gronfier, C.; Behar-Cohen, F.; Martinsons, C.; Hicks, D. Exposure to Artificial Light at Night and the Consequences for Flora, Fauna, and Ecosystems. Front. Neurosci. 2020, 14, 602796. [Google Scholar] [CrossRef]
  42. Méndez, A.; Prieto, B.; Aguirre, I.; Font, J.M.; Sanmartín, P. Better, not more, lighting: Policies in urban areas towards environmentally-sound illumination of historical stone buildings that also halts biological colonization. Sci. Total Environ. 2024, 906, 167560. [Google Scholar] [CrossRef] [PubMed]
  43. Yang, Y.; Liu, Q.; Pan, C.; Chen, J.; Xu, B.; Liu, K.; Pan, J.; Lagisz, M.; Nakagawa, S. Species sensitivities to artificial light at night: A phylogenetically controlled multilevel meta-analysis on melatonin suppression. Ecol. Lett. 2024, 27, e14387. [Google Scholar] [CrossRef] [PubMed]
  44. Dickerson, A.L.; Hall, M.L.; Jones, T.M. The effect of natural and artificial light at night on nocturnal song in the diurnal willie wagtail. Sci. Total Environ. 2022, 808, 151986. [Google Scholar] [CrossRef]
  45. Lockett, M.T.; Jones, T.M.; Elgar, M.A.; Gaston, K.J.; Visser, M.E.; Hopkins, G.R. Urban street lighting differentially affects community attributes of airborne and ground-dwelling invertebrate assemblages. J. Appl. Ecol. 2021, 58, 2329–2339. [Google Scholar] [CrossRef]
  46. Gaston, K.J.; Visser, M.E.; Hölker, F. The biological impacts of artificial light at night: The research challenge. Philos. Trans. R. Soc. B 2015, 370, 20140133. [Google Scholar] [CrossRef]
  47. Sanders, D.; Kehoe, R.; Tiley, K.; Bennie, J.; Cruse, D.; Davies, T.W.; Frank Van Veen, F.J.; Gaston, K.J. Artificial nighttime light changes aphid-parasitoid population dynamics. Sci. Rep. 2015, 5, 15232. [Google Scholar] [CrossRef]
  48. Gaston, K.J.; Bennie, J. Demographic effects of artificial nighttime lighting on animal populations. Environ. Rev. 2014, 22, 323–330. [Google Scholar] [CrossRef]
  49. Longcore, T.; Rich, C. Ecological light pollution. Front. Ecol. Environ. 2004, 2, 191–198. [Google Scholar] [CrossRef]
  50. Snowden, M.C.; Cope, K.R.; Bugbee, B. Sensitivity of Seven Diverse Species to Blue and Green Light: Interactions with Photon Flux. PLoS ONE 2016, 11, e0163121. [Google Scholar] [CrossRef]
  51. Longcore, T. A compendium of photopigment peak sensitivities and visual spectral response curves of terrestrial wildlife to guide design of outdoor nighttime lighting. Basic Appl. Ecol. 2023, 73, 40–50. [Google Scholar] [CrossRef]
  52. Martinsons, C. Environmental quality of outdoor lighting—Qualité environnementale de l’éclairage public: Comprendre et dépasser la réglementation sur les nuisances lumineuses. In Proceedings of the 2nd Research and Innovation Day, Cluster Lumière, Lyon, France, 26 January 2021. [Google Scholar] [CrossRef]
  53. Figueiro, M. Disruption of Circadian Rhythms by Light During Day and Night. Curr. Sleep Med. Rep. 2017, 3, 76–84. [Google Scholar] [CrossRef] [PubMed]
  54. Martinsons, C.; Veitch, J.; Loughran, S.; Nixon, A.; Mate, R.; Harris, R.; Shen, L. Solid-State Lighting: Review of Health Effects. Proceedings of International Lighting Seminar: Perspectives on Sustainability, Performance, Health & Smart Lighting, London, UK, 14 May 2024; ISBN 978-1-83654-223-0. [Google Scholar]
  55. Willis, J.P. Protection of Dark-Sky Areas in the United States Through Development and Implementation of Warm-Light LED Fixtures. JSPG 2023, 22. [Google Scholar] [CrossRef]
  56. Kolláth, Z.; Dömény, A.; Kolláth, K.; Nagy, B. Qualifying lighting remodelling in a Hungarian city based on light pollution effects. J. Quant. Spectrosc. Radiat. Transf. 2016, 181, 46–51. [Google Scholar] [CrossRef]
  57. Catalog LumiLEDs Products. Available online: https://otmm.lumileds.com/adaptivemedia/f5fbe66cb9d857d62d895f92b8d6be3cc5919925 (accessed on 10 November 2024).
  58. Esposito, T.; Radetsky, L.C. Specifying Non-White Light Sources in Outdoor Applications to Reduce Light Pollution. Leukos 2023, 19, 269–293. [Google Scholar] [CrossRef]
  59. Available online: https://www.kurtzon.com/SPECS/CLEANROOM/L/KURTZON_SPEC_TL-FGRS-LED-AMBER-TW.pdf (accessed on 10 November 2024).
  60. SAE J 578-2020; Chromaticity Requirements for Ground Vehicle Lamps and Lighting Equipment. SAE: New York, NY, USA, 2020.
  61. Datasheet Xlamp-XE-G CLD-DS275 REV 5. Available online: https://downloads.cree-led.com/files/ds/x/XLamp-XE-G.pdf (accessed on 10 November 2024).
  62. Houser, K.W.; Wei, M.; David, A.; Krames, M.R.; Shen, X.S. Review of measures for light-source color rendition and considerations for a two-measure system for characterizing color rendition. Opt. Express 2013, 21, 10393. [Google Scholar] [CrossRef]
  63. Fryc, I.; Bisegna, F.; Tabaka, P. Lighting of recreation grounds as a source of sky glow—The influence of luminaire type on this phenomenon. In Proceedings of the 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe), Milan, Italy, 6–9 June 2017; pp. 1–4. [Google Scholar] [CrossRef]
  64. Fryc, I.; Tabaka, P. The night sky light pollution created by outdoor luminaires. Przegląd Elektrotechniczny 2017, 1, 48–51. [Google Scholar] [CrossRef]
  65. Dark and Quiet Skies for Science and Society. Report and Recommendations. Available online: https://www.iac.es/system/files/documents/2021-02/dqskies-book-29-12-20.pdf (accessed on 10 November 2024).
  66. EN 13201; Road Lighting Standards—Part 1 and Part 5. CEN: Brussels, Belgium, 2015.
  67. Eloholma, M.; Viikari, M.; Halonen, L.; Walkey, H.; Goodman, T.; Alferdinck, J.; Freiding, A.; Bodrogi, P.; Várady, G. Mesopic models—From brightness matching to visual performance in night-time driving: A review. Light. Res. Technol. 2005, 37, 155–173. [Google Scholar] [CrossRef]
  68. Dong, L.; Qin, L.; Xu, W.; Zhang, L. The Impact of LED Correlated Color Temperature on Visual Performance Under Mesopic Conditions. IEEE Photonics J. 2017, 9, 1–16. [Google Scholar] [CrossRef]
  69. CIE 191-2010; Recommended System for Mesopic Photometry Based on Visual Performance. CIE: Vienna, Austria, 2010.
  70. Listowski, M. The Role of Standard and Supplementary Recommended System for Mesopic Photometry Based on Visual Performance Observers in Accurate Illuminance measurements. Photonics Lett. Pol. 2024, 16, 52–54. [Google Scholar] [CrossRef]
  71. Fotios, S.; Cheal, C. Predicting lamp spectrum effects at mesopic levels. Part 1: Spatial brightness. Light. Res. Technol. 2011, 43, 143–157. [Google Scholar] [CrossRef]
  72. Fryc, I.; Bará, S.; Aubé, M.; Barentine, J.C.; Zamorano, J. On the Relation between the Astronomical and Visual Photometric Systems in Specifying the Brightness of the Night Sky for Mesopically Adapted Observers. Leukos 2022, 18, 447–458. [Google Scholar] [CrossRef]
  73. Peña-García, A.; Gómez-Lorente, D.; Espín, A.; Rabaza, O. New rules of thumb maximizing energy efficiency in street lighting with discharge lamps: The general equations for lighting design. Eng. Optim. 2016, 48, 1080–1089. [Google Scholar] [CrossRef]
  74. Valencia Pavón, N.G.; Aguila Téllez, A.; García Torres, M.; Rojas Urbano, J.; Krishnan, N. Optimal Selection of Distribution, Power, and Type of Luminaires for Street Lighting Designs Using Multi-Criteria Decision Model. Energies 2024, 17, 2194. [Google Scholar] [CrossRef]
  75. Peña-García, A.; Sędziwy, A. New considerations about light pollution in rural and protected areas based on a global perspective savings-pollution-safety: Impact on real installations. engrXiv 2017. [Google Scholar] [CrossRef]
  76. Czyżewski, D.; Fryc, I. The Influence of Luminaire Photometric Intensity Curve Measurements Quality on Road Lighting Design Parameters. Energies 2020, 13, 3301. [Google Scholar] [CrossRef]
  77. Rabaza, O.; Gómez-Lorente, D.; Pozo, A.M.; Pérez-Ocón, F. Application of a Differential Evolution Algorithm in the Design of Public Lighting Installations Maximizing Energy Efficiency. Leukos 2020, 16, 217–227. [Google Scholar] [CrossRef]
  78. Fryc, I.; Listowski, M.; Supronowicz, R.; Mozyrska, D.; Rosas, E.; Eppeldauer, G.; Csuti, P.; Ferrero, A. The spectral mismatch correction factor estimation using broadband photometer measurements and catalog parameters for tested white LED sources. Opt. Lasers Eng. 2025, 184, 108614. [Google Scholar] [CrossRef]
  79. Listowski, M. The real and modeled values of photometric and colorimetric parameters comparison of white LEDs operating at wide temperature range. Przegląd Elektrotechniczny 2022, 1, 59–63. [Google Scholar] [CrossRef]
  80. Supronowicz, R.; Fryc, I. The LED spectral power distribution modelled by different functions-how spectral matching quality affected computed LED color parameters. In Proceedings of the 2019 Second Balkan Junior Conference on Lighting (Balkan Light Junior), Plovdiv, Bulgaria, 19–21 September 2019; pp. 1–4. [Google Scholar] [CrossRef]
  81. Fryc, I.; Listowski, M.; Supronowicz, R. Going beyond the 20th century color space to evaluate LED color consistency. Opt. Express 2023, 31, 38666. [Google Scholar] [CrossRef]
  82. Pattison, M.; Hansen, M.; Bardsley, N.; Thomson, G.; Gordon, K.; Wilkerson, A.; Lee, K.; Nubbe, V.; Donnelly, S. 2022 Solid-State Lighting R&D Opportunities; No. DOE/EE-2542; U.S. Department of Energy: Washington, DC, USA, 2022. Available online: https://www.energy.gov/sites/default/files/2022-02/2022-ssl-rd-opportunities.pdf (accessed on 10 November 2024).
Energies 17 05727 g001
Figure 1. The spectral power distribution (SPDs) of high-pressure sodium lamps (HPS) and low-pressure sodium lamps (LPS).
Figure 1. The spectral power distribution (SPDs) of high-pressure sodium lamps (HPS) and low-pressure sodium lamps (LPS).
Energies 17 05727 g001
Energies 17 05727 g002
Figure 2. (a) Spectral power distribution (SPD) of luminaires equipped with typical White pc-LEDs having nominal CCT of 4000 K; (b) chromaticity points corresponding to SPD plotted in (a).
Figure 2. (a) Spectral power distribution (SPD) of luminaires equipped with typical White pc-LEDs having nominal CCT of 4000 K; (b) chromaticity points corresponding to SPD plotted in (a).
Energies 17 05727 g002
Energies 17 05727 g003
Figure 3. (a) SPDs of amber LEDs made by different technologies [30,31,62], (b) chromaticity coordinates of amber LEDs (yellow and orange dots), and boundary of amber zone (blue line) given in standard SAE J578 APR2020 [60].
Figure 3. (a) SPDs of amber LEDs made by different technologies [30,31,62], (b) chromaticity coordinates of amber LEDs (yellow and orange dots), and boundary of amber zone (blue line) given in standard SAE J578 APR2020 [60].
Energies 17 05727 g003
Energies 17 05727 g004
Figure 4. The geometry of a typical road lighting installation of class M4 [41]. S is interdistance, H is luminaire mounting height, OH is overhang.
Figure 4. The geometry of a typical road lighting installation of class M4 [41]. S is interdistance, H is luminaire mounting height, OH is overhang.
Energies 17 05727 g004
Energies 17 05727 g005
Figure 5. SPDs of modeled amber LEDs (a) based on pc-LED technology and (b) based on DE (direct emission) LED technologies.
Figure 5. SPDs of modeled amber LEDs (a) based on pc-LED technology and (b) based on DE (direct emission) LED technologies.
Energies 17 05727 g005
Energies 17 05727 g006
Figure 6. Chromaticity points of amber LEDs under consideration.
Figure 6. Chromaticity points of amber LEDs under consideration.
Energies 17 05727 g006
Energies 17 05727 g007
Figure 7. The A / P ratio of LEDs under consideration. (a) White pc-LEDs, (b) amber pc-LEDs, and (c) amber de-LEDs.
Figure 7. The A / P ratio of LEDs under consideration. (a) White pc-LEDs, (b) amber pc-LEDs, and (c) amber de-LEDs.
Energies 17 05727 g007
Energies 17 05727 g008
Figure 8. The mesopic luminance values Lmeso for the same average photopic luminance of 0.75 cd/m2 created by LEDs under consideration (a) for White pc-LEDs, (b) for amber pc-LEDs, and (c) for amber de-LEDs.
Figure 8. The mesopic luminance values Lmeso for the same average photopic luminance of 0.75 cd/m2 created by LEDs under consideration (a) for White pc-LEDs, (b) for amber pc-LEDs, and (c) for amber de-LEDs.
Energies 17 05727 g008
Energies 17 05727 g009
Figure 9. Calculated MFR for different LED technologies: (a) White pc-LEDs, (b) amber pc-LEDs, and (c) amber de-LEDs.
Figure 9. Calculated MFR for different LED technologies: (a) White pc-LEDs, (b) amber pc-LEDs, and (c) amber de-LEDs.
Energies 17 05727 g009
Table 1. Geometric parameters of luminaire settings of M4-class road.
Table 1. Geometric parameters of luminaire settings of M4-class road.
Parameter Value
Interdistance (S) [m]43.5
Luminaire mounting height (H) [m]8.50
Overhang (OH) [m]1.50
Table 2. The M4 lighting class photometric parameter requirement according to EN 13201.
Table 2. The M4 lighting class photometric parameter requirement according to EN 13201.
Lighting
Class		Average
Luminance
Lav [cd/m2]
(Minimum
Maintained)		Overall
Uniformity
U0 [-]
(Minimum)		Longitudinal
Uniformity
Ui [-]
(Minimum)		Threshold
Increment
fTI [%]
(Maximum)		Edge
Illuminance
REI [-]
(Minimum)
M40.750.400.60150.30
Table 3. Luminaire parameters.
Table 3. Luminaire parameters.
Technical
Parameters		White pc-LED
Luminaire		Amber pc-LED
Luminaire		Amber de-LED
Luminaire
Number of LEDs [pcs.]7895316
Luminaire luminous flux [lm]900290029002
Luminaire power [W]90110274
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Fryc, I.; Listowski, M.; Martinsons, C.; Fan, J.; Czyżewski, D. A Paradox of LED Road Lighting: Reducing Light Pollution Is Not Always Linked to Energy Savings. Energies 2024, 17, 5727. https://doi.org/10.3390/en17225727

AMA Style

Fryc I, Listowski M, Martinsons C, Fan J, Czyżewski D. A Paradox of LED Road Lighting: Reducing Light Pollution Is Not Always Linked to Energy Savings. Energies. 2024; 17(22):5727. https://doi.org/10.3390/en17225727

Chicago/Turabian Style

Fryc, Irena, Maciej Listowski, Christophe Martinsons, Jiajie Fan, and Dariusz Czyżewski. 2024. "A Paradox of LED Road Lighting: Reducing Light Pollution Is Not Always Linked to Energy Savings" Energies 17, no. 22: 5727. https://doi.org/10.3390/en17225727

APA Style

Fryc, I., Listowski, M., Martinsons, C., Fan, J., & Czyżewski, D. (2024). A Paradox of LED Road Lighting: Reducing Light Pollution Is Not Always Linked to Energy Savings. Energies, 17(22), 5727. https://doi.org/10.3390/en17225727

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop