Sports Lighting Regulations

Play Ball and Play Fair!

Ian Ashdown, P. Eng., FIES

Senior Scientist, Lighting Analysts Inc.

[ Please send all comments to allthingslighting@gmail.com ]

This blog article has a somewhat frustrating history. About a year ago, I was asked to volunteer my time to write a primer of light and color as it relates to sports lighting regulations. I was told the name of the organization I was volunteering my time for, but I did not pay much attention – it seemed like a good cause.

I should have perhaps paid more attention before agreeing to volunteer – the Green Sports Alliance is not the poorest of socially responsible organizations.

Upon completing the primer, I was told that it was far too technical for its intended audience. Hopefully, you as my readers will disagree.

Sports Lighting Requirements

Sports lighting has specific requirements that may not be familiar to many lighting designers. The Illuminating Engineering Society publishes detailed recommendations related to sports lighting (IES 2009, 2010a, 2015), while various professional sports organizations have their own specific requirements (for example, FIFA 2007, FIH 2011, NCAA 2010a and 2010b, and Lewis and Brill 2013).

Illuminance

In sports lighting, there are two forms of illuminance measurements that are of interest: horizontal illuminance and vertical illuminance.

Horizontal illuminance is typically measured on a horizontally oriented imaginary surface one meter (~3 feet) above the field surface. Multiple measurements are usually measured (or calculated during the lighting design phase) on a grid. The National Football League, for example (Lewis and Brill 2013), specifies a grid spacing of 5 meters (~16 feet).

Vertical illuminance is measured on a vertically oriented imaginary surface. Unlike horizontal illuminance, both the position and orientation of the vertical surface must be specified. To understand why, consider a vertical surface illuminated by a single light source (FIG. 1).

FIG. 5 – Illuminance of surface depends on angle of illumination

FIG. 1 – Illuminance of surface depends on angle of illumination

As the angle of illumination decreases, the lumens per square meter decrease as well, until at grazing angles the surface is barely illuminated at. This can clearly be seen with a sphere illuminated by a single light source (FIG. 2).

FIG. 6 – Sphere illuminated by a single distant light source

FIG. 2 – Sphere illuminated by a single distant light source

In practice, there will be multiple luminaires illuminating the field, each of which will contribute to the illumination of a vertical surface – such as a player’s face. It is therefore important to ensure that the vertical illuminance is within minimum and maximum limits so that the players’ faces and team numbers can always be seen.

With this in mind, the “falloff” in illuminance with distance from a single luminaire must also be kept in mind. As shown in FIG. 3, a light source S illuminates two imaginary surfaces, the first one at distance d from the light source, and the second at twice the distance. Both surfaces receive the same amount of light (lumens) from S, but the area of the second surface is four times that of the first. Consequently, its illuminance (lumens per square meter) is only one-quarter that of the first surface.

FIG. 7 – Inverse Square Law

FIG. 3 – Inverse Square Law

Generalizing this to any distance, it is easy to see that the illuminance from a single luminaire will decrease, or “fall off,” according to the square of the distance. This is the basis of the inverse square law used by lighting designers.

Finally, “TV illuminance” is occasionally used for television broadcasting purposes (IES 2015). It is the illuminance measured at a position on the playing field when the illuminance meter is aimed directly at a specified camera position.In practice, of course, multiple luminaires are used to (more or less) evenly illuminate a playing field.

Uniformity

Uniformity of illumination is important for sports. It enables both the players and the spectators to easily follow the action, and it provides consistent lighting for the television cameras and photographers. Sports field lighting for internationally televised events must meet exacting standards, while more leeway is generally allowed for other events.

There are three measures (or more properly metrics) used to specify the desired uniformity of horizontal and vertical illuminance on the playing field. The simplest metric is the maximum-to-minimum ratio, commonly referred to as the uniformity ratio. Using NFL requirements as an example, horizontal illuminance is designated Eh, and so the uniformity ratio is expressed as Ehmax/Ehmin. Using a measurement grid for the playing field with 5-meter spacing, this ratio for all measurement values must be 1.4:1 or less.

Again using the NFL requirements, vertical illuminance is designated Ev, and the uniformity ratio Evmax/Evmin must also be 1.4:1 or less.

The NFL requirements go further in specifying that: 1) the ratio of the average horizontal illuminance Ehavg to average vertical illuminance Evavg as seen from camera #1 (that is, with each vertical surface facing the camera) must be between 1.0 and 2.0, with a target value of 1.5; 2) the ratio of vertical illuminances at any point on the field between the four imaginary vertical surfaces facing the four sides of the field shall be between 0.6 and 0.9; and 3) the average vertical illuminance Evavg facing towards camera #1 shall not be less that Evavg for the other three orthogonal (that is, right-angle) orientations. In other words, it can get complicated.

The second uniformity metric is the coefficient of variation, designated CV. Without delving into the mathematics of this statistical value, it can be likened to the point spread in sports betting. (If you must know the details, the equation is:

Sports Lighting Primer - EQN. 1

with details left to the interested reader – see [IES 2009, 2015].) It is basically a measure of how “smooth” the lighting distribution is across the playing field.

The third metric is the uniformity gradient, designated UG. It is defined as the ratio between illuminance values between adjacent measuring points on a square grid. Whereas CV describes the average non-uniformity for the entire field, UG describes the maximum nom-uniformity. It is particularly important in sports with fast-moving balls and the like, as changes in illuminance can make it more difficult to judge their speed.

Visual Glare

Visual glare occurs when the luminance of the luminaires within the observer’s field of view (either a player or spectator) is sufficiently greater than the average luminance to which the observer’s eye have adapted. It may cause visual discomfort (in response to which we tend to squint), or it may impair the vision of objects and details (such as past-moving balls and the like).

As a psychophysiological phenomenon, glare is both literally and figuratively “in the eye of the beholder.” All lighting researchers can do is present subjects in a laboratory with a lighting setup and ask them to rate the glare on a subjective scale. While it cannot be directly measured in the field, a glare rating metric, designated GR, can be calculated (typically at the design phase) in accordance with CIE 112-1994, Glare Evaluation System for Use with Outdoor Sports and Area Lighting (CIE 1994).

Central to these calculations are five parameters:

  1. The luminances of the luminaires as seen by the observer;
  2. The angular extent of the luminaires in the observer’s field of view;
  3. The position of the luminaires in the observer’s field of view relative to the line of sight;
  4. The number of luminaires in the observer’s field of view; and
  5. The average luminance of the observer’s entire field of view.

It is important to note that the GR metric depends on where the observer is positioned relative to the luminaires, and the line of sight direction. Consequently, any GR requirements must specify these parameters. The NFL requirements, for example, require that GR be less than 40 for all main cameras (Lewis and Brill 2013).

Color

Many sports organizations specify the allowable correlated color temperature, designated CCT, for sports field lighting. For example:

Organization CCT
FIFA ≥ 4000K
FIH > 4000K
NCAA > 3600K
NFL 5600K (alternatively 5000K to 7000K)

where the symbol ‘K’ represents kelvins (where one kelvin is equal to one degree Celsius).

To put these numbers into context, quartz halogen and warm white LED lamps typically have CCTs of approximately 3000K, metal halide lamps typically have CCTs of 4000K, and daylight LED lamps typically have CCTs of 5000K.

FIG. 8 – Light source correlated color temperatures

FIG. 4 – Light source correlated color temperatures

Our eyes adapt quite well to light sources with different CCTs, ranging from 2700K for 100-watt incandescent lamps to 10000K for the blue sky. Even though the light itself may look colored (FIG. 8), objects seen under these light sources appear to have approximately the same colors, with whites looking white.

The same is not true with television and digital cameras, however, which must be adjusted (color-balanced) to display the colors we expect to see. This is why it is important that all the luminaires in a sports lighting installation have approximately the same CCT. If they do not, the television cameras will display annoying color shifts as they pan across the field.

Many sports organizations also specify the minimum allowable color rendering index, designated CRI, for sports lighting. For example:

Organization CRI Ra
FIFA ≥ 65
FIH > 65
NCAA > 65
NFL ≥ 90

where the CRI Ra metric is a measure of the average color shift of various colors viewed under the light source when compared to viewing the colors under an incandescent or daylight source with the same CCT. A detailed explanation of color rendering is beyond the scope of this introductory chapter, but the topic is fully explained in CIE 13.3-1995, Method of Measuring and Specifying Colour Rendering Properties of Light Sources (CIE 1995).

In general, a minimum CRI of 65 is merely adequate, and is representative of what could be achieved with high-wattage metal halide lamps. With today’s solid-state lighting, a minimum CRI of 80 or greater is common, and CRIs of 90 and above are preferred.

It must also be emphasized that Ra metric represents the average color shift. Solid-state lighting products may also specify a CRI R9 metric, which represents the color shift specifically for red colors. A high R9 value is desirable, especially where team outfits feature saturated red colors.

In terms of television broadcast cameras, a more appropriate color rendering metric is the Television Lighting Consistency Index TLCI-2012 (EBU 2014). Like the CRI Ra metric, this is a measure of the average color shift of various colors viewed under the light source; the difference is that the observer is a color television camera rather than a human.

Spectrally Enhanced Lighting

There is some interest in the topic of spectrally enhanced lighting for sports field applications. For some visually demanding tasks, the recommended illuminance values can be reduced through the use of light sources with high blue content. A full discussion is presented in IES TM-24-13, An Optional Method for Adjusting the Recommended Illuminance for Visually Demanding Tasks Within IES Illuminance Categories P through Y Based on Light Source Spectrum (IES 2013).

It could be argued TM-24-13 can be applied to sports lighting, as it defines (p. 3) “visually demanding tasks” as “… tasks that are based on the ability to discern visual detail to ensure speed and/or accuracy.” In this situation, “visual detail” could be interpreted as a fast-moving ball or hockey puck.

Furthering the argument, TM-24-13 applies to illuminance categories P through Y, which the IES Lighting Handbook, 10th Edition (IES 2010a) defines in Table 4.1, Recommended Illuminance Targets, as interior and exterior lighting installations where the illuminance targets are in excess of 300 lux. Categories P (average 300 lux) through W (average 3000 lux) specifically include “some sports situations” (without defining them).

There are several problems, however. The first is that most sports organizations specify minimum horizontal and vertical illuminances without taking spectrally enhanced lighting into account. Any sports lighting that reduced these values based on TM-24-13 would not be in compliance with these specifications.

The second problem is that the recommended illuminance targets for sports lighting involving television broadcasting are based on the minimum illuminance requirements of the television cameras. These are of course independent of the human visual system, and so the reduced illuminance values calculated in accordance with TM-24-13 do not apply.

The third problem is the most crucial: the Illuminating Engineering Society issued a lengthy position statement (included in TM-24-13) that unequivocally states (in boldface type), “TM-24 should not be used for the development of energy policy or energy efficiency programs purposes for any lighting applications, as this goes against current IES recommendations.”

Light Pollution

Outdoor lighting illuminates not only objects on the ground, but the overhead sky as well. The International Dark-Sky Association reminds us that this unintentional light pollution threatens professional and amateur astronomy, disrupts nocturnal ecosystems, affects circadian rhythms of both humans and animals, and wastes over two billion dollars of electrical energy per year in the United States alone.

It might seem obvious that sports field lighting is a major contributor to light pollution, but this is true only in a local sense. According to a US Department of Energy study (DOE 2010), stadium lighting contributes a maximum of 6 percent (compared to 48 percent for roadway lighting and 34 percent for parking lot lighting) on a national scale. (This further assumes that the stadium lighting is always on at night.)

Outdoor Lighting Percent Lumens
Roadway 48
Parking 34
Building exteriors 10
Stadiums 6
Billboards 1
Traffic signals 1

On a local scale, however, light pollution from stadiums and sports fields can be a concern, particularly for surrounding residential neighborhoods. This includes not only light that is reflected from the ground and illuminates the sky overhead, but also light trespass and glare from improperly shielded luminaires.

IES TM-15-11, Luminaire Classification System for Outdoor Luminaires (IES 2011a) and the Joint IDA-IES Model Lighting Ordinance (MLO) with User’s Guide (IES 2011b) provide detailed information on designing outdoor lighting systems that minimize unintended light pollution.

References

CIE. 1994. CIE 112-1994, Glare Evaluation System for Use within Outdoor Sports and Area Lighting. Vienna, Austria: Commission International de l’Eclairage.

CIE. 1995. CIE 13.3-1995, Method of Measuring and Specifying Colour Rendering Properties of Light Sources. Vienna, Austria: Commission International de l’Eclairage.

DOE. 2010. 2010 U.S. Lighting Market Characterization, U.S. Department of Energy Building Technologies Program.

EBU. 2014. Tech 3355, Method for the Assessment of the Colorimetric Properties of Luminaires: The Television Lighting Consistency Index (TLCI-2012) and the Television Luminaire Matching Factor (TLMF-2013. Geneva, Switzerland: European Broadcast Union.

FIFA. 2007. Football Stadiums: Technical Recommendations and Requirements, 4th Edition. Zurich, Switzerland: Fédération Internationale de Football Association.

FIH. 2011. Guide to the Artificial Lighting of Hockey Pitches, 6th Edition. Lausanne, Switzerland: International Hockey Federation.

IES. 2009. IES RP-6-09, Recommended Practice for Sports and Recreational Area Lighting. New York, NY: Illuminating Engineering Society.

IES. 2010a. IES Lighting Handbook, 10th Edition. New York, NY: Illuminating Engineering Society.

IES. 2011a. IES TM-15-11, Luminaire Classification System for Outdoor Luminaires. New York, NY: Illuminating Engineering Society.

IES. 2011b. Joint IDA-IES Model Lighting Ordinance (MLO) with User’s Guide. New York, NY: Illuminating Engineering Society.

IES. 2013. IES TM-24-13, An Optional Method for Adjusting the Recommended Illuminance for Visually Demanding Tasks Within IES Illuminance Categories P through Y Based on Light Source Spectrum. New York, NY: Illuminating Engineering Society.

IES. 2015. IES RP-6-15, Sports and Recreational Area Lighting. New York, NY: Illuminating Engineering Society.

Lewis, D., and S. Brill. 2013. Broadcast Lighting: NFL Stadium Lighting. The Design Lighting Group Inc.

NCAA. 2010a. NCAA Basketball Championships Best Lighting Practices. National Collegiate Athletic Association.

NCAA. 2010b. NCAA Best Lighting Practices. National Collegiate Athletic Association.

Appendix A

A.1.         What is Light?

A primer on sports lighting must answer the obvious question: what is light? The Oxford English Dictionary, the pre-eminent dictionary of the English language, describes light rather loosely as, “the natural agent that stimulates the sense of sight.” More technically, light is electromagnetic radiation.

What we see as visible light is only a tiny fraction of the electromagnetic spectrum, extending from very low-frequency radio waves through microwaves, infrared, visible light, and ultraviolet to x-rays and ultra-energetic gamma rays. Our eyes respond to visible light; detecting the rest of the electromagnetic spectrum requires an arsenal of scientific instruments ranging from radio receivers to scintillation counters.

Our interest however is solely in visible light – it is what we see when we look at the world.

A.2.         Quantifying Light

We can think of light as massless subatomic particles called photons. They are emitted by light sources such as metal halide lamps and light-emitting diodes (LEDs), and travel through space until they encounter physical objects. They may then be reflected, refracted, scattered, or absorbed. Some of those photons will intersect our eyes, enabling us to see (FIG. A1).

FIG. 1 - Photons emitted by light source S

FIG. A1 – Photons emitted by light source S

The number of photons emitted by a typical light source per second is unimaginably large (think of the number ten followed by 30 to 40 zeroes), and so we express this quantity in lumens, where one lumen is approximately the number of photons emitted per second by a wax candle[1]. A typical light source will emit tens of thousands of lumens.

A.3.         Measuring Light

Photons emitted by light sources travel outwards in random directions. When these photons encounter a surface, they illuminate the surface (FIG. A2). From the perspective of the surface, it does not matter where the light comes from; it can be a single light source, multiple sources, or even the entire sky.

FIG. 2 - Light illuminating a surface A

FIG. A2 – Light illuminating a surface A

We can use a device called a photometer to measure the number of photons arriving at (incident upon) the surface per second. Of course, this number will depend on the surface area of the photometer’s sensor, and so we express the illuminance of the surface in terms of lumens per square meter, or lux. (Lumens per square foot are referred to as a foot-candle – please do not ask why.)

Note that the illuminated surface can be real or imaginary. We can, for example, imagine a “surface” positioned one meter above a physical surface, such as a playing field. The light will of course pass through this imaginary surface, but we can still measure its illuminance with a photometer (which is also called an “illuminance meter” by lighting designers or an “incident light meter” by photographers).

Illuminance is one of the two fundamental units of measurement for lighting designers. While we can measure illuminance with a photometer, we cannot see illuminance. For this, we need another fundamental unit of measurement.

Imagine looking at a computer display. The display consists of an array of a million or so pixels. We see each pixel because some of the photons it is emitting intersect our eye. We can therefore think of these photons as a ray of light, where all of the photons are traveling in the same direction. The more photons per second there are in the ray, the brighter the pixel appears to our eye. This is the luminance of the ray, sometimes referred to as “photometric brightness.”

FIG. 3 – Light ray from a computer display pixel as seen by observer

FIG. A3 – Light ray from a computer display pixel as seen by observer

Textbooks on lighting design typically define luminance as the property of a real or imaginary surface, which leads to the very confusing unit of measurement, “lumens per square meter per steradian,” or lm/m2-sr. It is much easier, however (and just as accurate), to think of luminance as a property of the light ray itself. (The light we see coming from the blue sky, for example, has luminance, but it does not have a real or imaginary surface.)

We can easily measure the luminance of a ray by using a telescope to focus a narrow beam of light onto a photometer sensor (FIG. A4). This is a luminance meter; it measures what we see.

FIG. 4 – Luminance meter

FIG. A4 – Luminance meter

[1] A century ago, national standards for measuring light relied on precisely specified wax candles made from spermaceti (whale oil).

Filtered LEDs and Light Pollution

An Astronomical Problem

Ian Ashdown, P. Eng., FIES

Chief Scientist, Lighting Analysts Inc.

[ Please send all comments to allthingslighting@gmail.com ]

UPDATE 2016/03/03 – Revised Figure 6.

The problem is astronomical – the blue light emitted by LED roadway luminaires has been shown to contribute to light pollution, especially when cool white LEDs are used. Blue light is preferentially scattered by air molecules, and so the higher the correlated color temperature (CCT), the greater the light pollution problem becomes. It is for this reason that the International Dark Sky Association requires a maximum CCT of 3000K for its Fixture Seal of Approval outdoor lighting certification program.

Sometimes, however, even warm white LED street lighting is not enough. For cities that are in close proximity to astronomical observatories, such as Flagstaff, AZ and the nearby US Naval Observatory Flagstaff Station, any amount of blue light is bad news.

Until recently, low-pressure sodium (LPS) street lighting has been the preferred choice. LPS luminaires are ideal light sources in that their monochromatic radiation (590 nm) is easily filtered out for astronomical observations. However, the large physical size of the lamps makes it difficult to control the luminous intensity distributions. For this and other reasons, municipalities are looking at “filtered LED” (FLED) street lighting as an option.

The reasoning is simple: combine a white light LED with a yellow filter and you can eliminate the blue peak that plagues astronomical observations. Figure 1, for example, shows the spectral power distributions (SPDs) of 2700K and 5000K white light LEDs with their characteristic blue peaks, while Figure 2 shows the SPDs of the same LEDs combined with yellow filters. The blue peaks have not been alleviated; they have been completely eliminated.

FIG. 1 – White light LED spectral power distributions.

FIG. 1 – White light LED spectral power distributions.

FIG. 2 – Filtered white light LED spectral power distributions.

FIG. 2 – Filtered white light LED spectral power distributions.

So, FLEDs are good for astronomical purposes, but what about lighting design?

Luminous Efficacy

At first glance, you might assume that filtering out the blue light will significantly reduce luminous efficacy. Perhaps surprisingly, this is not the case. Based on the SPDs shown in Figure 1 and Figure 2, the loss of luminous efficacy is less than ten percent for both warm white and cool white LEDs,

As a practical example, the SPDs shown in the above figures were taken from the photometric laboratory test reports of two commercial products from CW Energy Solutions. The salient data for these products are:

  WW-CW8-450 CW-CW7-350
Luminaire efficacy (lumens / watt) 106 122
CIE 1931 chromaticity x = 0.5223 y = 0.4072 x = 0.4719 y = 0.5176
CRI Ra 55.1 38.8
CRI R9 -56.5 -81.9

Table 1 – CW Energy Solution filtered LED roadway luminaire product specifications

To be clear, this is not an endorsement of these commercial products. This information is being provided for educational purposes only.

Chromaticity

We can plot the chromaticity xy coordinates shown in Table 1 on a CIE 1931 chromaticity diagram (FIG. 3), but what do the actual colors look like? Unfortunately, most such diagrams reproduce the actual colors of the CIE 1931 color space very poorly. (Worse, it is impossible to display most saturated colors using the RGB color gamut of video displays.)

FIG. 3 – CIE 1931 xy chromaticity diagram. (Source: Wikipedia)

FIG. 3 – CIE 1931 xy chromaticity diagram. (Source: Wikipedia)

To answer this question, we can convert the xy chromaticity coordinates into CIE XYZ tristimulus values, and from there, assuming a video display with a 6500K white point, into RGB values for display. The chromaticity coordinates listed in Table 1 then appears much like these colors on a calibrated video display:

FIG. 4A - WW-CW8-450 light source color   

FIG. 4A – WW-CW8-450 light source color

FIG. 4B - CW-CW7-350 light source color

FIG. 4B – CW-CW7-350 light source color

These are clearly not the sort of “white light” luminaires we would normally use for retail or residential lighting … but wait, there is more to this than meets the eye.

Color Rendering Capabilities

Looking again at Table 1, we see that the CIE General Colour Rendering Index Ra values for these products are frankly abysmal – 55 for the filtered 2700k (warm white) LEDs and 38 for the filtered 5000K (cool white) LEDs. The CIE Special Colour Rendering Index R9 values are even worse, with values of -56.5 and -81.9 respectively.

(As a reminder, a CRI value of 100 means that there is no perceptible color shifts with the eight CRI test color samples viewed under the test and reference lamps. It is quite possible, however, to have negative CRI values for the Special CRI values. Low-pressure sodium lamps, for example, have a CRI Ra values of -17.)

It is also interesting, and indeed useful, for lighting designers to understand why these perceived color shifts occur. Johann von Kries, a physiological psychologist who investigated chromatic adaptation in human color vision, noted in 1905 that we tend to see white objects as “white” regardless of the color temperature of the dominant light source. He postulated that our visual system adjusts the “gain” of the signals received from the red-. green- and blue-sensitive cones[1] in our retinae that are responsible for our color vision (von Kries 1905).

von Kries’ theory was formalized by the polymath Herbert Ives in 1912 as the von Kries transform, a mathematical operation that forms the basis of the calculation method for the CIE Colour Rendering Indices. While this psychophysiological “gain adjustment” works well (but not perfectly) in enabling us to perceive white surfaces under light sources with different CCTs (e.g., from 2800K incandescent lighting to 8000K overcast daylight), it tends to distort our perception of colored surfaces. (By way of analogy, think of adjusting the bass and treble controls on an audio system – particular settings may work for some music, but be unsuitable for other music.)

The beauty of the von Kries transform, however, is that it enables us to mathematically predict the color shifts due to a given test illuminant. Given a set of test colors – the Gretag-Macbeth ColorChecker™ is an obvious choice – we can predict and display what these colors will look like (e.g., Figure 5).

FIG. 5 – Filtered LED color shifts from 6500K daylight.

FIG. 5 – Filtered LED color shifts from 6500K daylight.

True – these color shifts are starkly evident, and would be completely unacceptable for retail and residential lighting. However, we need to remember that the topic of discussion is roadway lighting, specifically where municipalities are considering replacing high-pressure sodium (HPS) lamps with LED modules. With this, we need to look at the SPD of a typical HPS lamp (Figure 6).

FIG. 6 – 2100K high-pressure sodium lamp spectral power distribution.

FIG. 6 – 2100K high-pressure sodium lamp spectral power distribution.

There are three points of interest here. First, the correlated color temperature (CCT) rating of 2100K is nominal – the CIE 1931 xy chromaticity coordinates of this lamp are not particularly close to the blackbody locus, and so by definition the CCT rating is technically meaningless (CIE 2004).

Second, HPS lamps have a CRI Ra value of 24 – worse than filtered LEDs.

Third – and this is the key point – most municipalities have been using HPS street lighting ever since it replaced the mostly unlamented mercury vapor street lighting in the 1980s. After thirty years of use, most residents have known nothing but their orange-yellow glow.

Putting aside the roadway luminaire manufacturers’ arguments that most people prefer “white” light, it is instructive to visualize the color rendering capabilities of filtered LEDs versus HPS lamps (FIG. 7).

FIG. 7 – Filtered LED color shifts from 2100K daylight.

FIG. 7 – Filtered LED color shifts from 2100K daylight.

What is there to say, other than “oh …”? The point is that color rendering under filtered LED illumination is no worse, and arguably somewhat better, than under today’s prevalent HPS roadway illumination. It is not the color of the roadway luminaires that is important; it is the perceived colors of the objects that they illuminate.

The deciding factor for most municipalities will likely be whether residents like, dislike, or are simply neutral regarding the color rendering capabilities of filtered LED roadway lighting. In many cases, a test installation will likely be needed. Before then, however, it is important not to dismiss filtered LEDs simply because they are not “white light.” Furthermore, it is equally important not to compare them with white light LEDs solely on the basis of their CCT, CRI, or chromaticity values.

Conclusions

The purpose of this article is not to promote filtered LEDs as an alternative to low-pressure sodium lamps, or even as a preferred solution to light pollution problems. Rather, it is an attempt to take the various metrics describing the color rendering qualities of filtered LEDs and visualize them.

How lighting designers, roadway luminaire manufacturers, municipal engineers, and community activists choose to use this information is beyond the scope of this article. All that needs to be said is, “a picture is worth a thousand words.”

Acknowledgements

Thanks to Bob Adams of CW Energy Solutions and Tim Robinson of Esterline Corporation for providing the product technical information used in this article.

Thanks to George Livadaras for reporting an error in Figure 6.

References

CIE. 1995. CIE 13.3-1995, Method of Measuring and Specifying Colour Rendering Properties of Light Sources. Vienna, Austria: CIE Central Bureau.

CIE. 2004. CIE 15:2004, Colorimetry, Thirds Edition. Vienna, Austria: CIE Central Bureau.

von Kries, J. 1905. Die Gesichtsempfindungen. Handbuch der Physiologie der Menschen.

[1] These are technically referred to as long-, medium-, and short-wavelength, or LMS, retinal cones.