Tuning the Spectrum of Outdoor Light Sources to the Ambient Spectrum

Abstract

Artificial light at night (ALAN) is now considered as a driver of evolution, possibly harmful to biodiversity, which constitutes a threat to the terrestrial and marine environment, and as such falls under Sustainable Development Goals (SDGs) 14 and 15. One way of mitigating its impact on the environment is to select an environment-friendly light spectrum, which is made more easily with current LED technologies. In this paper, we propose to adapt the spectrum of the lamps to that of the immediate environment. It makes it possible not to disturb the light environment of animals and plants at night and during the twilight period, at least from a spectral point of view, while ensuring the usual functions of lighting for humans. Apart from its own merit, the proposed concept may also contribute to SDG 13 by saving energy compared to current approaches based on long wavelengths light. The proposed idea may be implemented in various ways and deserves to be discussed in the lighting community and tested in real settings.

1. Introduction

1.1. Artificial Light at Night

Artificial lights change the environment of both humans and non-humans. It was invented by a now extinct species, homo erectus [1,2], and has been much improved since, in particular with gas lighting in the nineteenth century and electricity in the twentieth century. In 2014, the Nobel Prize was awarded to a discovery that enabled the rapid and invasive deployment of LEDs across the planet [3].

The development of artificial light at night (ALAN) makes it possible to extend social life beyond the hours illuminated by the sun [4] by facilitating human activity at night, formerly the realm of nocturnal species [5]. But in a context marked by a biodiversity crisis on a planetary scale [6], a number of researchers have promoted limiting the impact of ALAN on the environment [7,8,9,10], in line with Sustainable Development Goal (SDG) 15 (Life on Land) and also SDG 14 (Life below Water) [11,12,13], when considering the lighting of coastal areas and river banks [14]. It is to such an extent that ALAN is now considered a driver of the evolution of species [15,16]. Meanwhile, a sober use of ALAN also contributes to SDG 13, to Take urgent action to combat climate change and its impacts, by reducing greenhouse gas emissions [12,17].

An important stream of research developed in the 2010s, with experiments first showing the effects of ALAN on the behaviour of some species considered individually [7,18], and then on the equilibrium changes within ecosystems [19,20,21]. Some studies have focused on insects [22,23] and plants [24], while others have addressed entire food webs [25,26]. The effect on biodiversity, that is to say on the diversity of living [27], is more difficult to address directly, however, an important study has pointed out that the drop in biodiversity is greater in (nocturnal) moths than in (diurnal) butterflies [28], suggesting a possible impact of ALAN on the loss of biodiversity of moths.

1.2. Colour and Light Spectrum

Light is usually described by two characteristics, intensity and colour. Intensity, when it comes to light, is not proportional to the number of photons, but to what humans see of the electromagnetic radiation that reaches our retinas. This perceived light intensity was defined a century ago by the CIE [29]. More specifically, a reference curve was defined, known as $V\left(\lambda \right)$, describing the relative sensitivity of a standard human observer to any wavelength of visible light. This, in turn, led to the adoption of the candela as a unit of luminous intensity, that is, one of the seven base units of the International System.

The second main property of light is its colour, which depends on the light spectrum, wavelengths between 380 nm and 780 nm are perceived with different colours, and a mixture of wavelengths is perceived with a colour, which depends on the intensity distribution of the energy across wavelengths, i.e., of the light spectrum [30]. Colour is therefore a psychological attribute of what we see, and to be able to describe it quantitatively, it was necessary to establish a relationship between what we see and measurable physical quantities. This led to the definition of a reference observer by the CIE [31,32], then to various reference documents in human colorimetry [33,34,35] up to the current reference documents [36,37,38].

2. Impact of the Light Spectrum on Living Species at Night

But colour, as defined by the CIE, is an anthropogenic concept: many living species have spectral sensitivities to light very different from those of humans [39]. Animals and plants use what we call colour for a variety of tasks, from object detection to orientation and judging the time of day.

2.1. Varieties of Spectral Sensitivities

2.1.1. Spectral Sensitivity of Vertebrates

Opsins are a vast family of proteins involved in photoreception in the eyes of vertebrates, including rods and cones in humans. They have evolved into many variants that have different spectral sensitivities [40,41]. The variety of spectral sensitivities among underwater and coastal species is also well documented [42]. Marine species, like their terrestrial counterparts, are synchronised to the rhythms of the moon and the sun, but they have evolved by adapting to the light that reaches the depth where they live. For instance, measurements in the Plymouth estuary in Cornwall allowed for computing ALAN exposure at different depths, taking into account all the junk in the water that scatters or absorbs light [43]. Green light penetrates the water best, and red reaches the shallowest depths. It is no surprise thus that marine species evolved very different spectral sensitivities, compared to terrestrial animals.

2.1.2. Spectral Sensitivity of Insects

At night, some insects are attracted to light (this is called phototactic behaviour), and this attraction depends partly on the spectrum of the lamps (for example, many of them are attracted to UV rays). A quantitative, two-step model for estimating the attractiveness of a light source for insects has been proposed [44]. The first part of the model is an action spectrum that globally represents the spectral response of a population of insects, using a linear combination of the spectral sensitivities of typical insect photoreceptors. This led to an index, the ILA (Insect Light Attraction), associated with the spectrum of a source. Then, a second logistic function estimates the attractiveness of the source as a function of this ILA and the source flux.

2.1.3. Spectral Sensitivity of Plants

Plant responses to light involve not only photosynthesis (ALAN does not impact photosynthesis, the intensities are too low.) but also a set of regulatory mechanisms involving photosensitive sensors that affect flowering, germination, orientation, etc. [45].

• Phytochromes are sensitive to red light [46,47]. They are present in plants in two forms, $P_r$ and $P_{fr}$. Light between 650 and 670 nm (red) transforms $P_r$ into $P_{fr}$, while light between 705 and 740 nm (extreme red) does the opposite, resulting in a spectrum-dependent balance between the two forms. It is the proportion of $P_r$ that controls physiological mechanisms such as bud development, flower opening, and senescence. Phytochromes have been described as assessing the time of day, as the spectrum of the sky changes at sunrise and sunset.
• Phototropins are sensitive to blue light [48] and, as their name suggests, control the orientation of plants toward light.
• Cryptochromes are sensitive between 390 and 530 nm (blue, violet, and UV-A). They play a role in regulating the circadian clock and are involved in phototropism [49].

Light sources emitting in the red spectrum are therefore likely to disrupt the mechanisms regulated by phytochromes, while those emitting in the blue spectrum can disrupt the activities of cryptochromes and phototropins.

2.2. Disorientation

Some vertebrates, including migratory birds, perceive the magnetic field using biological sensors [50] such as magnetite particles and biochemical reactions occurring in the retina [51]; this second mechanism partially depends on ambient light. Some amphibians also exhibit sensitivity to the magnetic field that depends on the spectrum of ambient light, with orientation varying depending on the spectral composition [52].

For example, a laboratory study was conducted on passerines that migrate annually at dawn and dusk between Australia and Tasmania. It examined how the birds orient themselves based on the spectral distribution of light [53]. Different spectra were tested, and the main result is that red light produces disorientation. It is unlikely that these birds do not see red light; rather, their orientation system has a spectral sensitivity primarily in the red, unlike their spatial vision.

In a full-scale experiment on a North Sea island, migratory birds were observed and their behaviour was classified according to whether or not they were attracted to a lamp whose spectrum changed every hour [54]. It was found that the birds were disoriented (attracted) by red and white lights, much less by green light, and almost not at all by blue light; this effect is more pronounced on overcast days. These results suggest red-free light sources may avoid disturbing migratory birds.

2.3. Colour Vision at Night

Although studies on this subject are very incomplete, many species (unlike humans) have a form of colour vision at night [55,56]. For example, hawk-moths (like many insects) have several classes of photoreceptors that are hardwired to see in colour. These moths have been shown to be able to discriminate colours: they received a reward (sugar) when they landed on the correct colour [57]. They were able to distinguish blue from yellow at all light levels tested (1, 0.01, and 0.0001 ${\mathrm{cd}/\mathrm{m}}^2$). An additional experiment revealed their ability to discriminate colours even when the lighting changed (colour constancy [58]). The authors believe that these mechanisms are widespread among moths. The adaptive advantage that colour vision gives these animals at night must have offset the disadvantages associated with the loss of temporal and spatial sensitivity.

3. Towards a Tradeoff

ALAN alters the conditions in which living species perceive the environment, which in turn alters the behaviour of certain nocturnal and crepuscular species, and even the balance within ecosystems. This is the main reason why SDGs 14 and 15 are impacted by ALAN. To mitigate the impact of ALAN on the environment, the precautionary principle suggests not lighting more than is necessary for human needs. Since total extinction of the ALAN is not realistic, lighting strategies for the mitigation of adverse impacts have been proposed [59,60,61]. Among these, an important aspect concerns the spectrum of light sources. As seen above in Section 2, the variety of spectral sensitivities between species makes it difficult to adapt the ALAN spectrum to all living species at once.

3.1. Public Lighting

Each lamp technology (e.g., HPS, LPS, mercury vapor, LED) corresponds to a specific type of light spectra. Controlling the light spectrum may be useful to mitigate the adverse effects of ALAN and support SDGs 14 and 15: for instance, it has been advocated that the broadest spectra are potentially those with the greatest impact on the environment. Following this line of reasoning, LPS may be preferred as it is silent in most wavelengths; however, this may be a problem for species that need colour vision at night [62].

3.1.1. Optimal Wavelengths

Has the transition from low-pressure sodium (LPS) lamps (with a colour rendering index close to zero) to more modern sources offering better colour rendering helped animals in their nocturnal lives? Does it help some more than others? To assess the impact of the lamp spectrum, the spectral sensitivity of many species was collected [39]. The response of their visual systems was calculated as a function of the lamp type (LPS, HPS, LED, and metal halide) [63]. Optimal wavelengths were estimated for more than 200 species (spiders, insects, birds, reptiles, and mammals) by calculating the visibility of contrasts at different wavelengths. The authors compared, on the one hand, the vision of each species as a function of the lamp type, and on the other hand, the way in which the vision of each species is degraded for each type of lamp. As expected, the impact of a given lighting system depends on the species. Making an optimal choice for all species is thus not possible; the best one can do is to chose which species are a priority to protect.

3.1.2. Field Experiments

Field experiments are very difficult to conduct on these subjects. One of the first real-life experiments on the effect of ALAN on animal populations lasted 4 years, at eight experimental sites at the edge of forests, and made it possible to count and observe the behaviour of several species (moths, mice, bats, birds, plants) under different night-time lighting conditions [64]. At each site, several types of sources were installed and compared, with different spectra: a green source, which does not disturb migratory birds, a red one, which does not disturb insects, and a white one. All sources were UV-free and the ground illuminance levels were identical. No effect of lighting was observed on the number of species or the total number of butterflies. The only spectrum-related effect concerned bats: the red source was found to be equivalent to the control condition (without lighting), while bats were more numerous with white lights, and even more numerous with green lights; these bats, called pipistrelles, are known to feed on insects around light points. One might think this is no big deal, but the resulting decline in insect numbers marks a shift in the balance of the local ecosystem.

We have seen that phytochromes play a role in many plants’ biological clocks. This was tested in a field experiment [19] in a nature reserve in Cornwall. Grass squares of 4 × 4 m were lit at night with either white or amber LEDs. The composition (in terms of species), biomass, and flowering time was monitored in each condition. Comparisons between the different lighting schemes suggests that amber LEDs have an effect at least as strong as white LEDs; however, dimming and partial extinction strategies attenuate the effects of ALAN, suggesting a dose effect rather than a threshold effect.

3.1.3. UV Vision

The function of street lighting is that humans can see at night, so illuminating with wavelengths that humans cannot see is useless. However, technological constraints mean that lamps often also illuminate a little in infrared and ultraviolet. The light leakage in UV has been investigated by comparing the main types of lamps on the market, estimating the potentially negative effects on two insect species, a butterfly and an aphid, which can see in UV [65]. Both species are diurnal, but are likely to be attracted to lamps at night. Five lamps were considered: HPS, LPS, metal halide, mercury vapour, and LED. The calculation is spectral, and different atmospheric conditions were simulated, showing for instance that since aphids are very sensitive in the yellow band, it is with SBP sources that they see the most light. For butterflies, LEDs and HPS appear to be the most effective, i.e., best seen at constant ground-level photopic lux. In other words, if we light effectively for humans, we disturb diurnal butterflies at night.

3.1.4. Current Trends

A common conception is that broad spectra are potentially those with the greatest environmental impact [66]. The use of very narrow-spectrum lamps, such as low-pressure sodium (LPS), was already identified in the 1970s as a useful measure to protect night-sky vision by astronomers [67]. Regarding living species, the problem with this strategy is that it relies on an implicit assumption: the absence of a dose effect, i.e., that the amount of light does not matter. Unfortunately, experiments showing an impact of dimming suggest that dose effects can occur [24,68].

It has also been suggested that short-wavelength light radiation (the blue part of the spectrum) is the most harmful to the environment. The rationale is that these wavelengths impact the melatonin cycle and thus sleep regulation in vertebrates; moreover, many nocturnal species (animal and plant) are sensitive to them (e.g., turtles [69], insects [44,70], marine species [43], and plant cryptochromes [71]). This has led to recommendations to limit these wavelengths in outdoor lighting (see Section 3.2) so as not to visually saturate the light sensors of these species, dazzle them, or create lures that could disorient them, spatially or temporally [72]. It seemed all the more necessary to limit light emission in short wavelengths since LEDs have a spectral peak in the blue range [10,73] and are becoming the standard in lighting.

3.2. Standards

In France, for instance, these recommendations have resulted in regulations of urban and road lighting in terms of Correlated Colour Temperature, or CCT [74], which should not be higher than 3000 K. The CCT is derived from the spectrum of the light source, but the same colour temperature can be obtained from lamps with different spectra. Unfortunately, if a lamp $L_1$ has a spectrum $S_1\left(\lambda \right)$, which produces a colour temperature $T_1$, adding a monochromatic red lamp $L_R$ (with spectrum $S_R\left(\lambda \right)$) to $L_1$ lowers the source’s CCT. In other words, if a lamp has a CCT that is too high and does not comply with the CCT threshold proposed by the regulation [74], it can be made compliant by adding more red light. Since humans are not very sensitive to red light, the illuminance produced by the lamp would not increase much, and there is no need to decrease the intensity of $L_1$ in order to keep the same illumination level. This trick allows manufacturers to circumvent the legislator’s intention, which was not to disturb wildlife by adding light in long wavelengths. Moreover, using long-wavelength lamps leads to increased energy consumption if illuminance levels are to be maintained, which is not only expensive but also goes against SDG 13. Indeed, using wavelengths at which the human visual system is poorly efficient, we need to increase the power of the light sources to meet visibility objectives for humans.

4. Problem Statement

The usual definition of colour accounts for the perception of light by humans. Other species, which use light as a source of energy or as a source of spatial and temporal information, have different perceptions which cannot be described from the colour perceived by humans, but only from the light spectrum [75]. This is one of the issues raised by current recommendations regarding the light source spectrum.

By supporting the development of sources that emit a lot of light in long wavelengths (in the red), we may create artificial lures for plant phytochromes (see Section 2.1.3) [71] and disorient migratory birds [50,54]. By concentrating the wavelengths of a light source in a narrow band, we degrade colour perception, including the perception of colour contrasts and the detection of specific colours. We may consider this a lesser evil if it only concerned humans, but some species need to see colours at night [55,56,57,76], and for them the loss of colour vision associated with spectrum changes may have an impact on their ecological fitness [15].

These are examples of a more general phenomenon. Plants and animals use photoreceptors with very different action spectra from each other [39,42,75], with the net result that any choice of spectrum is an arbitration between different species. By illuminating a certain way, we advantage some and disadvantage others, and thus shift the ecological balance between species within the local ecosystem.

5. A Neutral Spectrally Tuned Lamp

The proposal described below is based on a critique of the ideas presented above regarding the choice of a spectrum for artificial lighting at night. Since ALAN is an anthropogenic disturbance of the environment, which modifies both the intensity of light and its spectral composition, one might simply wish not to disturb the spectrum of night-time light without changing the illuminance level. We propose a general framework to reach this goal. It is a smart lighting concept, and dedicated technical solutions should be tested in real settings, regarding their feasibility and cost. Future research is also needed in order to assess the effectiveness of our proposal in terms of SDGs 14 and 15.

5.1. Overview

Figure 1 is a sketch of a smart lighting system where a sensor (1) continuously measures the spectrum of ambient light (which includes components from the sky, the Moon, etc.). These measures are broadcasted (2) to a network of local luminaries equipped with receivers (3). A micro-controller (4) attached to the luminaire or to the sensor (if all lamps in the network have the same spectral characteristics) adapts the lamp emission spectrum to the ambient spectrum. This computation is constrained by a requirement regarding the illuminance at the ground level (5), which should be fixed by the lighting designer.

In this architecture, the illuminance level is kept constant while the spectral content of the light varies slowly depending on the spectral content of the sky. Since most lighting standards are expressed in terms of illuminance, these changes should not alter the visibility of targets (pedestrians, traffic signs, etc.) or the level of risk on the road. Indeed, the main visual cue associated with visibility and road safety is the luminance contrast [77], which should not vary much if the illuminance level remains unchanged. Consistently, normative documents such as EN 13-201 use either illuminance or luminance as the criterion for mitigating road accidents. Therefore, we do not expect the proposed approach to have any impact on human contrast perception or road safety.

5.2. Constraints

Let’s see in more detail the main requirements of our proposal in terms of technical solution. The lamp must be electronically controlled, which is easy with current LED-based devices. Its spectrum must be modifiable within a short time constant, which is also the case with a lamp made of a bunch of LEDs with different spectra. The system will be all the more effective as the tuning of the source has degrees of freedom, with an ability to create spectra ranging from sunset to an overcast or starry night sky, with or without the Moon.

5.3. Sensor

An important feature of the device is that the measured spectrum, that of the sky, must be disturbed as little as possible by artificial light sources around that which is controlled, otherwise we would have created a cybernetic system with the input connected to the output. A simple way to get around this is to make the measurement at a high point once, and to broadcast the command across an entire lighting network with centralised management. This is the reason for including an optical system to the sensor, pointing to an area free of illumination from the lamps (the telescope in Figure 1).

5.4. Example of Implementation

Although the proposed concept may lead to various implementations, it may be useful to illustrate how it can be designed with current technologies. One may use, for instance, a mini-spectrometer in the visible range associated with a lens with a long focal length, looking at the sky, at the top of a building (providing power supply). The luminaires in a given green park area would be equipped with the same sets of six LEDs with known spectral power distributions. An Arduino microcontroller, fed by the spectrometer, would compute the target intensity of each of these LEDs in real time from the measured sky spectrum, and the result would be broadcast to the luminaires in the neighbourhood every minute, for instance using Bluetooth Low Energy (BLE) in a range of 100 m, with a mesh network if needed.

5.5. Time Course of the Lighting

Regarding the time course of changes in the artificial lighting, if one wishes to minimise disturbance in ecosystems, lighting changes must be slow, unlike what usually happens in urban lighting. This can be achieved by applying a temporal filter, ensuring that changes in the spectrum are not perceived as such by animals and plants living around.

5.6. Computation

The device should compute, from the measured spectrum and the possibilities offered by the lighting system, the spectrum which minimises the difference between the target spectrum (the sky) and the effective spectrum (the lamp). This step requires computing the dissimilarity between spectra. This is a non-trivial question, and the first move would be to use human-centric notions such as a distance in a colorimetric space [37]. It is an option, but we have preferred computing the dissimilarity in radiometric units as a more neutral approach given the variety of species concerned.

Considering a lamp that includes N light sources with their spectrum $S_i\left(\lambda \right)$ (e.g., a lamp with several LEDs of various spectra), the optimisation problem is to minimise the difference between the lamp spectrum $S\left(\lambda \right)$ and the environment spectrum $E\left(\lambda \right)$ measured by the sensor. It can be described as choosing the optimal weights ${\omega }_i$ for the spectra $S_i\left(\lambda \right)$ of the light sources under the constraint that the total illuminance (from a human point of view) is kept constant. The lamp spectrum is the sum of the light sources spectra:

$$S\left(\lambda \right)=\sum _1^N{\omega }_i{S}_i\left(\lambda \right)$$

(1)

The illuminance reaching the ground is proportional to

$$I\propto {\int }_{380}^{780}S\left(\lambda \right)V\left(\lambda \right)\delta \lambda =\sum _1^N{\omega }_i{\int }_{380}^{780}{S}_i\left(\lambda \right)V\left(\lambda \right)\delta \lambda$$

(2)

This can be written:

$$I\propto \sum _1^N{k}_i{\omega }_i$$

(3)

with

$$k_i={\int }_{380}^{780}{S}_i\left(\lambda \right)V\left(\lambda \right)\delta \lambda$$

(4)

The constraint that the illuminance should be kept constant can be reached from Equation (3): the choice of the ${\omega }_i$ will be restricted to values such that $\forall i,{\omega }_i\ge 0$ and $\sum k_i{\omega }_i=I$, where I is the target illuminance value. Then, using the scalar product between two spectra $S_1$ and $S_2$:

$$S_1.S_2={\int }_{380}^{780}{S}_1\left(\lambda \right)S_2\left(\lambda \right)\delta \lambda$$

(5)

we can compute the cosine similarity between E (the sky spectrum) and S (the light source spectrum) as

$$cs(S,E)={\displaystyle \frac{|S.E|}{\parallel S\parallel \times \parallel E\parallel }}$$

(6)

that is,

$$cs(S,E)={\displaystyle \frac{1}{\parallel S\parallel \times \parallel E\parallel }}\sum _1^N{\omega }_i{\int }_{380}^{780}{S}_i\left(\lambda \right)E\left(\lambda \right)\delta \lambda$$

(7)

The cosine similarity takes values between 0 and 1, close to 1 if the spectra are close to each other, close to 0 if they are far from each other. If we define ${\alpha }_i$ as

$${\alpha }_i={\int }_{380}^{780}{S}_i\left(\lambda \right)E\left(\lambda \right)\delta \lambda$$

(8)

the optimisation problem is to choose the ${\omega }_i$ leading to the smallest possible value of

$$cs(S,E)={\displaystyle \frac{1}{\parallel S\parallel }}\sum _1^N{\omega }_i{\alpha }_i$$

(9)

under the constraints that $\forall i,{\omega }_i\ge 0$ and $\sum k_i{\omega }_i=I$, with

$$\parallel S\parallel ={\int }_{380}^{780}{S}^2\left(\lambda \right)\delta \lambda =\sum _{i,j=1}^N{\omega }_i{\omega }_j{\int }_{380}^{780}{S}_i\left(\lambda \right)S_j\left(\lambda \right)\delta \lambda$$

(10)

In other words,

$$\parallel S\parallel =\sum _{i,j=1}^N{\omega }_i{\omega }_j{\beta }_{ij}$$

(11)

where

$${\beta }_{ij}={\int }_{380}^{780}{S}_i\left(\lambda \right)S_j\left(\lambda \right)\delta \lambda$$

(12)

and finally,

$$cs(S,E)={\displaystyle \frac{{\sum }_1^N{\omega }_i{\alpha }_i}{{\sum }_{i,j=1}^N{\omega }_i{\omega }_j{\beta }_{ij}}}$$

(13)

Here, a set of ${\beta }_{i,j}$ values is a characteristic of the lamp, and an optimisation algorithm would compute the optimal coefficients ${\omega }_i$ from the sky spectrum $E\left(\lambda \right)$ by maximizing the similarity $cs$ between E and S in Equation (13).

5.7. Phototactic Behaviour

The main problem that may arise with our proposal comes from phototactic behaviours, and other such behaviours where the Moon influences the direction of motion [59,78]. If the main perturbation that ALAN causes to the environment is by inducing phototactic behaviours, due to the fact that the light sources are confused with the Moon, then our proposal may be ineffective, and worse, may increase these unwanted phototactic behaviours.

Still, the proposed settings may be used in this case with a different optimisation function, in order to minimise phototaxis. Instead of adjusting the spectrum of the source so that it resembles the natural spectrum as closely as possible, it would be adjusted so that it is as different as possible from the natural spectrum. From Equation (6), the same line of reasoning would apply, only the target similarity between the two spectra would be minimum instead of maximum. For instance, if insects are attracted by a Moon-like spectrum, and the sky spectrum is close to the Moon spectrum, the proposed strategy would turn the ALAN spectrum as far as possible to the Moon spectrum, in the sense of the Moonlight Similarity Index (MSI) proposed by [79].

6. Conclusions

We propose a general framework in order to minimise the perturbations in the spectral distribution of the ALAN compared to the natural light that is received in the surroundings. This proposal is motivated by SDGs 14 and 15, aiming to minimise the impact of ALAN on terrestrial and sub-water ecosystems. It is also an alternative to a current trend focusing on long-wavelength lamps, which increases energy consumption, and therefore goes against SDG 13. Although it has been described below for public lighting, this concept can also be applied to private lighting (car parks, stations, stadiums, etc.) as well as automotive lighting.

At this stage, the concept of adjusting the ALAN spectrum in real time to match the expected spectrum without ALAN is not yet technically implemented. This is both a weakness and an asset. A weakness, because it cannot yet be fully demonstrated; an asset, because it offers many implementation options, concerning the sensor, the broadcast, the adjustable spectrum lamp, and the implementation of spectral calculation. Therefore, the next step will be to implement and test this idea in real conditions.

Our proposal may be considered somewhat controversial, as it goes against a trend in lighting research that favors low CCTs and long wavelengths. This is deliberate. We do not claim that our strategy is the only possible one, but we hope that our proposal will be examined and discussed as a working hypothesis that deserves to be scientifically tested in real life. Such a system may not be profitable today, but it might be worth trying one day, given the potential gains on SDGs 14 and 15.