Controlling Multicolor LED Luminaires

Public Disclosure

Ian Ashdown, P. Eng., FIES

Senior Scientist, Lighting Analysts Inc.

[Please send all comments to]

First, a disclaimer: this is not a commercial announcement!

San Jose, CA, USA: March 31, 2016. LED Engin, Inc. announces the world’s first 7-color, high power LED to be produced on a single emitter. The compact LZ704MU00 emitter enables the design of stage or architectural lighting that produces sophisticated effects over the full color spectrum. Its RGBW die are complemented by phosphor-converted (PC) amber, cyan and violet to provide richer, wide-ranging color effects. PC amber delivers the same saturation as regular amber but with 5 times the flux at temperature, cyan fills the spectrum gap between blue and green, and violet enables black or crisp white lighting effects. Typical stage and studio applications include moving heads with zoom optics and round wash lights. In architectural lighting, the emitters enhance the performance of everything from static lights to linear wash lights…

FIG. 1 – LED Engin seven-color LED package (

FIG. 1 – LED Engin seven-color LED package (

The reason for this lengthy quote from LED Engin’s press release is that it succinctly introduces the background to this blog article. Multicolor LED luminaires are nothing new – the theatrical lighting industry saw them introduced nearly a decade ago, with products such as the ETC Selador Desire series of seven-color LED luminaires (FIG. 2).

FIG. 2 – ETC Selador Desire seven-color LED luminaire (

FIG. 2 – ETC Selador Desire seven-color LED luminaire (

What is new and significant about the LED Engin product announcement is that having seven different color LED dice in a single package enables manufacturers to design potentially more-compact luminaires that do not exhibit multicolor shadows at close range.

What is equally significant, however, is that there is a problem with multicolor LED luminaires, a serious problem that has been basically overlooked for the past decade. This blog article offers a potential solution.

A Matter of Control

To understand the problem, first consider color-changing LED modules with red, green, and blue (RGB) LEDs. Generating a specific color is a simple matter of choosing the appropriate ratios of the red, green, and blue LED intensities. For example, if we want to generated 4150 K white light, we might choose the intensity ratios shown in FIG. 3.

FIG. 3 – Three-color 4150K white light source spectral power distribution.

FIG. 3 – Three-color 4150 K white light source spectral power distribution.

As any theatrical lighting designer will quickly point out, however, there are two problems with RGB LED modules and luminaires. First, their color gamuts are fairly limited. In particular, they are typically unable to produce saturated blue, violet, and cyan colors (e.g., FIG. 4).

FIG. 4 – Typical RGB LED module color gamut.

FIG. 4 – Typical RGB LED module color gamut.

Second, the lack of spectral radiant flux between approximately 550 nm and 600 nm, generally perceived as yellow light, results in yellow objects illuminated by RGB light sources appearing dull and lifeless in comparison to an equivalent white light source. Given a choice, most theatrical lighting designers would probably choose a conventional quartz-halogen luminaire (with a color temperature of 3200 K) and a Rosco 202 Half CT Blue polyester color filter to raise its color temperature to approximately 4150 K. For professional stage lighting, color quality is paramount.

The disadvantage, of course, is that even with motorized color filter wheels, quartz halogen luminaires offer limited dynamic color opportunities. If the designer needs to change colors during or between scenes, multiple luminaires are generally required. This is why multicolor LED luminaires are so attractive – with six or seven colors, they provide larger color gamuts (e.g., FIG. 5), smooth transitions between colors are possible, and they do not suffer from the color rendering issues of RGB luminaires.

FIG. 5 – Six-color LED module color gamut.

FIG. 5 – Six-color LED module color gamut.

The problem is that there are now six or seven LED intensities to control if you need to generate a specified color. Unlike RGB LED modules, there are basically an infinite number of LED intensity combinations to choose from.

As an example, suppose we are given a six-color LED module with the following colors:

  • Blue (440 nm)
  • Cyan (495 nm)
  • Green (525 nm)
  • Amber (595 nm)
  • Red (630 nm)
  • White (3000K)

We need to generate 4150 K white light, for which we find through laborious trial and error with a colorimeter are the two solutions shown in Figures 6A and 6B – two very different solutions with radically different spectral power distributions (SPDs), and with relative LED intensity ratios shown in Table 1. (The luminous efficacies and quantities of LEDs per color vary; the intensities are in relation to their full power settings – see FIG. 7.)

Figure 6A – Six-color 4150K white light SPD (first example).

FIG. 6A – Six-color 4150K white light SPD (first example).

FIG. 6B – Six-color 4150K white light SPD (second example).

FIG. 6B – Six-color 4150K white light SPD (second example).

Color Example 1 Example 2
Red 1.00 1.00
Amber 1.00 0.18
Green 0.85 0.51
Cyan 0.18 0.00
Blue 0.20 0.10
White 1.00 1.00
Intensity 2712 1471
CRI Ra 62 27

Table 1 – Multicolor LED relative intensities comparison

The important point here is that while both solutions may look the same visually, the second example generates only 54 percent as much luminous flux (i.e., lumens) as the first example. (This makes sense, of course, as the human eye is more sensitive to amber light than it is to red light.)

Another point is that the first example not only generates more luminous flux, but it also has much better color rendering properties due to the greater amount of amber light. (A CRI Ra value of 62 versus 27.)

This is the problem with multicolor LED luminaires – how do you choose the “best” solution from an infinite number of relative intensity ratios for a given color? It depends, of course, on whether “best” means maximum luminous intensity or color rendering properties, such as the CIE Ra and R9 color rendering metrics for white light. (There are no established color rendering metrics for chromatic illumination, but they conceivably could be developed.)

The situation is exacerbated if you need to transition between two colors while maintaining constant intensity. Multicolor LED luminaires are clearly capable of doing this, but you need to determine the best solution for all the intermediate colors, preferably fifty or more times a second during the transition to prevent visible flickering.

Manufacturers of multicolor LED luminaires have overlooked this problem from the beginning. The ETC Selador Desire products, for example, present the user with one DMX512 intensity control channel per color, plus a master intensity control channel for all colors. It is a control solution that offers no solution.

To be fair, the manufacturers cannot be faulted for taking this approach. In mathematical terms, the choice of relative intensity ratios is an “overdetermined” problem, where the number of variables (e.g., the number of LED colors) exceeds the number of outputs (e.g., the three broad color bands that the human eye is sensitive to).

This is not to say that the problem is unsolvable – it is. If a million monkeys with typewriters will eventually reproduce all the works of Shakespeare, we can take the same approach (albeit with fewer monkeys) to determining the best solution for a given color.

The “we” in this situation are the luminaire manufacturers and designers. It is basically a product design problem that does not involve the end user. What follows is a reasonably detailed outline of the design of an effective user interface for multicolor LED luminaires.

Solving the Problem

We begin with the acknowledgement that we need to know something about the optical, electrical, and thermal properties of the different color LEDs in order to predict how much light they will generate under various operating conditions. Specifically, we need to know for each color LED:

  • Spectral power distribution
  • Luminous efficacy (lumens per watt)
  • Maximum current (at full intensity)
  • Forward voltage
  • Dynamic resistance
  • LED package thermal resistance
  • LED substrate temperature

We also need to specify the desired color, or “target chromaticity,” expressed in CIE 1931 xy chromaticity coordinates. (Note that the spectral power distribution is dependent on the LED junction temperature.)

Controlling Multicolor LED Luminaires - FIG. 7

FIG. 7 – SSL Designer system parameters.

A proof-of-concept program called SSL Designer™ was developed for this approach, with a screenshot of the above system parameters shown in Figure 7.

Given this information, it is possible to calculate the absolute spectral power distribution for each color LED. These SPDs can then be scaled by the relative intensity ratios (shown in FIG. 8 as channel pulse width modulation duty cycles), following which they are summed and the luminous intensity calculated. (With a bit more work, color rendering metrics such as CIE Ra and R9 for white light applications can also be calculated.)

FIG. 8 – Ten best relative intensity ratio solutions for specified color.

There are ten relative intensity ratio solutions shown in FIG. 8, but these are the best (in the sense of maximum luminous intensity) of tens of thousands of randomly selected solutions that have been evaluated. Of course, it is highly unlikely that a random choice of relative intensity ratios will generate the desired target chromaticity, but some solutions will be closer than others. An evolutionary computation approach called a genetic algorithm is therefore used to intelligently and quickly select and refine those solutions that satisfy the target chromaticity criterion (and optionally one or more color rendering metric criteria), and to order them accordingly as the best solutions. Again in mathematical terms, the genetic algorithm “converges” to the best solutions.

Not shown in Figure 8 is the ability to calculate the best solutions for hundreds of different target chromaticities, which are then stored in memory. When the user later specifies a desired color, the program finds the best solution for the nearest matching color, then uses this to “seed” the initial randomly selected solutions. The genetic algorithm can then converge much more quickly to the best solution.

An RGB Solution

In practice, the user needs to specify both the desired color and intensity. This can be done using CIE xyY values, where xy represent the CIE 1931 chromaticity coordinates (shown as the horizontal and vertical axes in FIG. 5), and Y represents the intensity (expressed as a percentage of maximum intensity). This approach is, however, not as intuitive as the RGB settings most lighting designers are familiar with.

Fortunately, there is a simple solution. Referring to the six-color LED module color gamut shown in FIG. 5, we can completely enclose the six-sided color gamut in a triangle defined by the xy chromaticities of virtual red, green, and blue LEDs (FIG. 9). It does not matter that the red LED chromaticity lies outside the horseshoe-shaped spectral locus and so represents a physically impossible color. What does matter is that the RGB values can be used to represent any color (and intensity) within the six-color LED module color gamut.

FIG. 9 – Virtual RGB LED module color gamut.

FIG. 9 – Virtual RGB LED module color gamut.

The mathematics needed to transform the RGB values to CIE xyY values are straightforward to calculate – a task that is performed by the luminaire’s microcontroller. From the user’s perspective, all that is needed are three DMX512 channels to control the luminaire, which will appear to behave as an RGB LED luminaire with enhanced color rendering capabilities.

A decade ago, this approach would have been impractical due to the computing power requirements. Today, however, it is both practical and economical to embed a microcontroller in the luminaire that will perform the necessary calculations in real time (i.e., milliseconds).

Public Service

The SSL Designer software developed to demonstrate this novel approach is a proof-of-concept program that simulates a multicolor LED luminaire on a desktop computer. Following standard industry practice, it would make sense to apply for a patent on the invention and license the technology to theatrical luminaire manufacturers.

Most countries have differing intellectual property laws, but they all agree that if an invention is publicly disclosed prior to filing a patent application, it is ineligible for patent protection. This blog article therefore represents an intentional and deliberate public disclosure of the invention. Specifically, this invention has been released into the public domain. No patent application has been filed, and so lighting manufacturers and designers are both free and encouraged to implement the above royalty-free approach in their multicolor LED luminaire products.

In the spirit of published patents, there are numerous implementation details that have been glossed over in this article. However, the details that have been presented are “sufficient for one skilled in the art” to implement the invention “without undue experimentation” (35 U.S.C. 112(a), Anyone curious about the implementation details of SSL Designer is welcome to contact the author with questions.

Multicolor LED luminaires have been commercially available for nearly ten years. It is time for the luminaire manufacturers and designers to make them truly useful.


The Kruithof Curve

A Pleasing Solution

Ian Ashdown, FIES

Chief Scientist, Lighting Analysts Inc.

[ Please send comments to ]

Related Posts

Kruithof Reconsidered

UPDATE 16/04/09 – This metastudy:

Fotois, S. 2106. “A Revised Kruithof Graph Based on Empirical Data,” Leukos. (Published online 08 April 2016, DOI 10.1080/15502724.2016.1159137.)

critically examined 29 studies in which the Kruithof curve was investigated. The author concluded that “… these [studies] do not support Kruithof. For pleasant conditions, these data suggest only avoiding low illuminances and do not favor any CCT.”

After 75 years of misconception and misuse, may this finally mark the end of the Kruithof Curve. If a lighting designer has a personal preference for warm or cool colors, fine – but please, do not try to justify it with scientific mumbo-jumbo.

[UPDATE 15/01/20 – Added Bartleson (1960) reference.]

Lighting designers today will surely recognize the Kruithof curve, in which the color temperature of the light source is related to a range of illuminances that we find “pleasing.” In its modern form, the Kruithof curve has become supposedly irrefutable evidence that the correlated color temperature (CCT) of LED-based lighting should not exceed 4000K for indoor applications.Kruithof - FIG 1FIG. 1 – Kruithof curve, modern version (source: Wikipedia).

In the process, luminaire manufacturers are being lambasted for promoting products with CCTs of 5000K and higher. Worse, some government agencies and non-profit organizations are adopting CCT limits that are presumably based on the Kruithof curve. The DesignLights Consortium, for example, stipulates that luminaires on its Qualified Products List must have CCTs of 5000K or less for most indoor applications.

Unfortunately, the modern version of the Kruithof curve is different from what A. A. Kruithof published 75 years ago. The upper and lower curves are approximately the same, but their interpretation is different from what Kruithof intended. In fact, the Kruithof curve appears to have been basically misinterpreted for the past three-quarters of a century.

The Kruithof curve itself was thoroughly debunked a quarter-century ago with three exhaustive studies involving up to 400 participants (as opposed to two people in Kruithof’s study, including himself). The Kruithof curve was somewhat belatedly removed from the IES Lighting Handbook five years ago (IES 2010).

This article is however not so much about the validity of the Kruithof curve as it is about a careful re-examination of his 1941 paper. While Kruithof has been rightly criticized over the years for not providing experimental details, he wrote enough for us to infer how he arrived at his findings. When you realize that he was working with early prototypes of the first fluorescent lamps, it is in itself an interesting story.

In the Beginning

The year was 1941. Captain America made his first appearance in a comic book, Europe was being torn asunder by World War II … and Philips Research was quietly developing its own fluorescent lamp technology in Eindhoven, the Netherlands. As part of this effort, Philips Technical Review published a paper by A. A. Kruithof titled, “Tubular Luminescence Lamps for General Illumination” (Kruithof 1941).

Kruithof’s paper was primarily about fluorescent lamp technology, which had been commercially released by General Electric in 1938. His experimental meter-long T12 “luminescence lamp” (FIG .2) was designed have a luminous flux output of 1000 lumens.

Kruithof - FIG 2FIG. 2 – Philips “luminescence” lamp (from Kruithof 1941).

Halophosphate-based phosphors were not invented until the following year (McKeag and Ranby 1942), and so these “white” fluorescent lamps used a combination of cadmium borate, willemite (zinc orthosilicate), and magnesium tungstate, which respectively fluoresce red, green, and blue when excited by the ultraviolet radiation emitted by the mercury-argon gas fill.

By themselves, the phosphors resulted in maximum luminous efficacies of approximately 70 lumens per watt for willemite and 35 lumens per watt for cadmium borate and magnesium tungstate. By combining the phosphors in various proportions, it was possible to generate white light with CCTs ranging from 2650K to 10000K.

Kruithof fabricated fluorescent lamps with CCTs of approximately 4200K and 5800K, plus a third lamp type that was so far off the blackbody curve as to be considered colored rather than white. Comparing these to the extant incandescent lamp technology with its typical 15 lumens per watt luminous efficacy, Kruithof was well justified in writing, “These properties give reason to expect that luminescent lamps will be widely used in the future.”

Kruithof also performed an extensive analysis of the color rendering capabilities of his lamps by observing the color shifts of 313 color cards (as opposed to the eight colors used for the CIE General Colour Rendering Index Ra). Using the phosphor and visible mercury line spectra published in his paper, it is possible to estimate CRI values of his lamps as:

Lamp CCT Ra R9
4200K 36 -110
5800K 54 -60

As for the original form of the Kruithof curve (FIG. 3), the paper includes a description of what the author referred to decades later as a “pilot study” of lamp CCT versus illuminance level. To fully understand this study, it is necessary to quote Kruithof (1941) extensively, beginning with:

“In the first place at a given level of illumination it is found that the colour temperature must lie within certain limits if the effect of the illumination is to be pleasing. Roughly, it may be said that a low or a high colour temperature corresponds to a low or a high level of illumination, respectively. We have investigated this relation experimentally somewhat more closely by introducing in a room a variable number of electric lamps whose current (i.e., the temperature of the filaments) could be varied.”

Kruithof - FIG. 3FIG. 3 – Kruithof curve, original version (from Kruithof 1941).

With vague phrases like “pleasing” illumination, “a room,” and a “variable number of electric lights,” we can at best only infer the experimental conditions that were used to develop this curve.

Kruithof continues:

“Below the lowest curve the illumination is ‘dim’ (at low colour temperature) or ‘cold’ (at high colour temperature). Above the highest curve the unnatural colour reproduction was unpleasant.”

There are two items of immediate interest here:

  1. Kruithof used the adjectives “dim” and “cold” rather than the modern interpretation of “appears bluish.”
  2. Kruithof used the adjectives “unnatural” and “unpleasant” rather than “appears reddish.”

It could be argued that the modern interpretation is intuitively valid, but that is not the point. Kruithof measured a specific psychometric parameter that he termed “pleasing” illumination. Recasting the results to support a different hypothesis effectively invalidates the experiment.

In terms of the illumination referenced in FIG. 1 appearing reddish or blush, it must be noted here that no academic studies published to date support this hypothesis. The modern form of the Kruithof curve appears to be an interpretation with no scientific evidence to support it.


“These obviously vague limits within which the illumination is considered ‘pleasing’ could in our experiments be determined at least with an accuracy of 20 or 30 percent.”

This is a blazing red flag that something may be seriously wrong with this study – how can you measure something as subjective as “pleasing” with an accuracy of 20 to 30 percent in terms of illuminance? What Kruithof said – without providing any evidence – is that we can apparently tell the difference between say 100 lux and 125 lux of illumination. This is not a side-by-side comparison of two illuminated surfaces, but by simply walking into a room and deciding whether or not the colors are “unnatural.”

Much has been written in the following years that Kruithof did not provide any significant details of his experimental apparatus or protocols, and so it is difficult to accept the Kruithof curve as being valid. However, the rest of his paper is reasonably detailed and informative, indicating that Kruithof was a careful researcher. He must therefore have had some reason for claiming an accuracy of 20 to 30 percent.

Continuing with Kruithof, the extensive caption he wrote for FIG. 3 reads in part:

“The left-hand part of the limiting curves, up to a colour temperature of 2850 ºK, is recorded by allowing electric lamps with variable (decreased) current to burn in a room, and varying the number of lamps. The illumination intensity on a table 80 cm high was here measured. In the right-hand part the lowest level which does not give the impression of coldness was determined by experiments with daylight itself and with the daylight luminescence lamps to be described below.”

This is all frustratingly vague, but there is a key point: “… varying the number of lamps.”


“The shape of the upper curve has been extrapolated in this region with the help of the fact that in direct sunlight (colour temperature 5000 ºK) even with the highest illumination intensities occurring (104 or 105 lux) the colour rendering is never found ‘unnatural’.”

This is a crucial quote in that Kruithof decided that direct sunlight was not – and by definition could not – be “unnatural.” This brings us back to the question of the upper curve for color temperatures below 2850K (FIG. 3), where dimmed incandescent lamps were used.

Looking deeper into the question of “unnatural color reproduction,” Kruithof stated that he used a selection of color cards from the Ostwald Color Atlas, a contemporary color classification scheme of the Munsell color system we use today (FIG. 4). With respect to this, he wrote:

“While the colour rendering can be judged by comparison when luminescence is used in combination with other light and the designation of the colour impression obtained and the saturation of the colour obtained must agree, when only luminescence lamps are used no comparison is possible. In judging the colour rendering therefore in this case one must have recourse to ‘colour memory’ which is chiefly confined only to the designation of colours.”

Kruithof - FIG. 4FIG. 4 – Ostwald color atlas (source: Wikipedia).

This is even more puzzling in that our ability to recall colors is mediocre at best. In general, we tend to remember colors as being more saturated than they really were (Bartleson 1960). It therefore makes even less sense that an accuracy (or more properly repeatability) of 20 to 30 percent could be perceived.

It does make sense, however, if Kruithof switched lamps on and off to vary the illuminance while maintaining constant color temperature. This would be a form of flicker photometry. We are mostly insensitive to absolute illuminances, but we are highly sensitive to changes in illuminance. Switching illumination levels would reveal even subtle changes in the perceived chromaticities of the color cards.

… which brings us to the first of two color appearance effects, the Bezold-Brücke hue shift effect. This effect was first reported in the 1870s, but it was not studied extensively until the 1930s (Purdy 1931). Even then, the study was published in the American Journal of Psychology. A lamp research engineer like Kruithof could be excused for not being aware of the paper and its implications.

The Bezold-Brücke effect results in perceived color hues changing with changes in luminance. As shown in FIG. 5, the wavelength shifts required to maintain constant perceived hue for monochromatic colors can be huge, particularly for red and cyan, with a ten-fold increase in luminance. The effect on Kruithof’s color cards would have been generally less noticeable, but may have been still evident with, for example, saturated red colors.

Kruithof - FIG. 5FIG. 5 – Bezold-Brücke effect for monochromatic light (from Wyszecki & Stiles 1982, Fig. 2(5.9))

The second color appearance effect would not have been known to Kruithof because it was not reported until the 1950s. The Hunt effect (Hunt 1950, 1952, 1953) results in the perceived chroma (i.e., colorfulness) of illuminated objects increasing with increased illuminance. This effect is important enough to have been built into the CIECAM02 color appearance model that is widely used for color management for displays, printers, and other imaging devices.

For a given CCT, Kruithof presumably began with a low illumination level and then increased the illuminance until color appearance of the color cards more or less matched his color memory of them. The changes in perceived color would presumably be due to both the Bezold-Brücke and Hunt effects.

As however he continued increasing the illuminance, the continuation of these effects would result in the colors no longer matching his color memory. This would result in, to use Kruithof’s own words, “unnatural color reproduction.”

If Kruithof had reduced the daylight illuminance using, for example, neutral density filters, he would likely have observed the same behavior. However, even if he had done so, the time taken to move the filters into position would likely have masked the color differences. He also would have had the conundrum of having to call natural daylight “unnatural” and “unpleasant.”

In Kruithof’s defense, he may have been one of the first researchers to observe the Bezold-Brücke and Hunt effects using white light illumination with constant CCT. Certainly color shifts with changes in CCT were well-known at the time and modeled by the von Kries chromatic adaptation model. Color shifts with constant CCT were, however, a different matter.

Kruithof was certainly aware of the color shifts that his fluorescent lamps produced, as shown by FIG. 6 and FIG. 7, where the circled areas labelled ‘2’ represent “clearly appreciable” color shifts.

Kruithof - FIG. 6FIG.6 – Color shifts between daylight and 5800K fluorescent lamp (from Kruithof 1941).

Kruithof - FIG. 7.FIG. 7– Color shifts between electric light and 4200K fluorescent lamp (from Kruithof 1941).

Interestingly, Kruithof wrote:

“Most colours are somewhat less saturated in luminescence light than in daylight.”

which is exactly what you would expect from the Hunt effect. Nevertheless, Kruithof had little choice but to describe the 5800K lamp as generating “pleasing” illumination above some threshold.

It must be emphasized, however, that this is only a hypothesis – it would need a carefully designed large-scale experiment to determine whether in fact the Bezold-Brücke and/or Hunt effects can satisfactorily explain Kruithof’s results. Even then, it will be impossible to know with any certainty because Kruithof described his experiments so frugally. On the other hand, they at least offer a plausible explanation of his claim to 20 to 30 percent repeatability.

Time Marches On

If Kruithof considered his work to be a mere “pilot study,” the follow-up studies have been anything but. Bodman (1967) for example performed studies wherein he varied the illuminance in a conference room illuminated by fluorescent lamps. Remarkably, more than 400 subjects took part in these studies. Like Kruithof, he found that people had a preferred illuminance range over which 90 percent of the subjects found the lighting to be “good.” However, As can be seen from FIG. 8, the preferences appear to be influenced more by the lamp spectral power distributions than by their CCTs. At the time that these studies were conducted, “deluxe” fluorescent lamps had CRI values of 90 or so, but warm white fluorescent lamps with their halophosphate phosphors had CRI values as low as 50.

Kruithof - FIG. 8FIG. 8 – Preferred illuminance range versus fluorescent lamp type (from Bodman 1961)

What are interesting are the terms that Bodman’s subjects used to describe the lighting (FIG. 9). The warm white fluorescent lighting (CCT < 3000K) was described as “excessive” and “artificial” (terms which may have influenced by the low CRI values) at high illuminances, but for white (CCT » 4000K) and daylight (CCT > 6000K), the terms used were “pleasant” and “lively.” This is consistent with what you might expect from an increase in colorfulness as provided by the Hunt effect.

Average Illuminance (lux) Color of light
Warm white White Daylight
< 700 Not unpleasant Dim Cool
700 – 3000 Pleasant Pleasant Neutral
> 3000 Excessive, artificial Pleasant, lively Pleasant

FIG. 9 – Subjective impressions of illumination levels (Bodman 1961).

Boyce and Cuttle (1990) performed similar experiments using fluorescent lamps with CCTs ranging from 2700K to 6300K, and with average illuminances ranging from 30 to 600 lux, to illuminate a small office space. All of the fluorescent lamps had CRI values ranging from 82 to 85.

Doing a detailed statistical analysis of 410 questionnaires completed by 15 subjects who spent 20 minutes becoming visually adapted to the room, the authors found that the lamp CCT had no statistically significant influence on the subjective assessments. Instead, the major factor in both color discrimination tests and subjective assessments was illuminance.

Interestingly, none of the subjects who were unfamiliar with lighting design used the terms “warm” or “cool” to describe the lighting.

Davis and Ginthner (1990) also performed similar experiments with 40 test subjects. Using 2750K and 5000K fluorescents lamps with CRI values of 90 and illuminance levels of 270, 600, and 1350 lux, they confirmed the findings of Boyce and Cuttle (1990) that the subjective ratings of preference were influenced by illuminance only. They also found that low light levels were rated as less colorful than high light levels for the same CCT, which again suggests the Hunt effect.

Finally, Viénot et al. (2008) performed experiments designed to investigate the validity of the Kruithof curve using LED modules rather than fluorescent lamps. To ensure high CRI with variable color temperature, they used LED clusters with independently-controlled blue, cyan, green, amber, orange, red, cool white, and warm white LEDs. These provided CRI values from 91 to 96 over an illuminance range of 150, 300, and 600 lux and a CCT range of 2700K, 4000K, and 6500K.

Unlike the previous studies, however,the  Viénot et al. (2008) experimental setup was not a room but a light booth measuring some 41 x 35 x 38 cm (16 x 14 x 15 inches) that had an 80-degree field of view with a dark surround. It is debatable whether the results of the 20 subjects can be applied to offices spaces, but the authors concluded that:

“In one sense, we have validated Kruithof’s statement that high CCT at low illuminance is unpleasant. Nevertheless, we cannot conclude that low CCT should be confined to low illuminance to arouse pleasant sensations.”


“When the colour rendering index is very high and the light spectrum is under control, there is no indication that high colour temperature is judged more pleasant than low colour temperature at higher illuminance levels.”


There have been many more studies related to the Kruithof curve, including Cockram et al. (1970), Denk et al. (2014), Dikel et al. (2014), Fotois et al. (2013), Hu et al. (2006), Ishi and Kakitsuba (2003), Juslén (2006), Küller et al. (2006), Logadóttir and Christoffersen (2008), Mills et al. (2007), Naoyuki and Tomimatsu (2005), Navvab (2001), Park et al. (2010), Pinto et al. 2008), Weintraub (2000), and Zhai (2014).

None of these, however, are as focused or comprehensive as those of Bodman (1967), Boyce and Cuttle (1990), and Davis and Ginthner (1990). The common conclusion of these authors is that while dim lighting at any CCT is seen as unpleasant, there is no observational evidence in support of Kruithof’s upper curve (FIG. 3).

What this discussion has shown, however, is that Kruithof may not have meant “unpleasant” in the sense of poor lighting quality, but rather in the sense of optimal color reproduction.

It must remembered that Kruithof was working with incandescent lamps with CCTs varying from 1800K to 2850K, 4000K and 5800K fluorescent lamps that probably had CRI values of less than 60, and “natural” daylight with unknown CCT. He likely would have never seen chromaticity shifts with changes in illuminance at constant CCT prior to his experiments, and probably (and quite reasonably) saw them as unnatural and hence unpleasant. This despite the fact that he observed exactly this when comparing his 5800K lamp with daylight, and explicitly commented on the fact.


The conclusion is straightforward, and indeed was established more than a quarter-century ago with three major studies: the Kruithof curve is essentially meaningless. There is no upper boundary to “pleasant” illumination at any CCT, and the best that can be said about the lower boundary is the obvious: dim lighting can be unpleasant, regardless of the CCT.

At the same time, however, Kruithof deserves credit for having been the first to investigate the topic. His failure to describe his experiments in more detail is regrettable, but perhaps understandable. Done as a pilot study, the brief discussion in his paper is basically a progress report with preliminary findings.

It has basically been through our continued misunderstanding of his term “pleasing” that the Kruithof curve continues to persist in lighting design practice. If Kruithof were able to comment on this today, he would likely have only two words to say (in Dutch):

“Stop daarmee!” (English translation: “Stop that!”)


Bartleson, C. J. 1960. “Memory Colors of Familiar Objects,” Journal of the Optical Society of America 50(1):73-77.

Bodman, H. W. 1967. “Quality of Interior Lighting Based on Luminance,” Transactions of the Illuminating Engineering Society of Great Britain 32(1):22.

Boyce, P. R., and C. Cuttle. 1990. “Effect of Correlated Colour Temperature on the Perception of Interiors and Colour Discrimination,” Lighting Research and Technology 22(1):19-36.

Cockram, A. H., J. B. Collins, and F. J. Langdon. 1970. “A Study of User Preferences for Fluorescent Lamp Colours for Daytime and Night-Time Lighting,” Lighting Research & Technology 2(4):249-256.

Davis, R. G., and D. N. Ginthner. 1990. “Correlated Color Temperature, Illuminance Level, and the Kruithof Curve,” Journal of the Illuminating Engineering Society 19(1):27-38.

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Dikel, E. E., G. J. Burns, J. A. Veitch, S. Mancini, and G. R. Newsham. 2014. “Preferred Chromaticity of Color-Tunable LED Lighting,” Leukos 10(2):101­-115.

Fotois, S., S. Atli, C. Cheal, K. Houser, and A. Logadóttir. 2013. “Lamp Spectrum and Spatial Brightness at Photopic Levels: A Basis for Developing a Metric,” Lighting Research and Technology 0:1-23.

Hu, X., K. W. Houser, and D. K. Tiller. 2006. “Higher Colour Temperature Lamps May Not Appear Brighter,” Leukos 3(1):69-81.

Hunt, R. W. G. 1950. “The Effects of Daylight and Tungsten Light-Adaptation on Color Perception,” Journal of the Optical Society of America 40(6):362-371.

Hunt, R. W. G. 1952. “Light and Dark Adaptation and the Perception of Color,” Journal of the Optical Society of America 42(3):190-199.

Hunt, R. W. G. 1953. “The Perception of Color in 1º Fields for Different States of Adaptation,” Journal of the Optical Society of America 43(6):479-484.

IES. 2010. IES Lighting Handbook, Tenth Edition. New York, NY: Illuminating Engineering Society.

Ishi, M., and N. Kakitsuba. 2003. “Preferred Color Temperatures at 200 lx during Exposure to Cool or Warm Environments for Middle-Aged Female Subjects,” Journal of the Human-Environmental System 6(2):93-100.

Juslén, H. 2006. Influence of the Colour Temperature of Preferred Lighting Level in an Industrial Work Area Devoid of Daylight,” Ingineria Illuminatului 18(8):25-36.

Kruithof, A. A. 1941. “Tubular Luminescence Lamps for General Illumination,” Philips Technical Review Vol. VI, No. 3, pp. 65-73.

Küller, R., S. Ballal, T. Laike, B. Mikellidesa, and G. Tonello. 2006. “The Impact of Light and Colour on Psychological Mood: A Cross-Cultural Study of Indoor Work Environments,” Ergonomics 49(14):1496-1507.

Logadóttir, A., and J. Christoffersen. 2008. “Individual Dynamic Lighting Control in a Daylit Space,” Proc. Eleventh International Conference on Indoor Air Quality and Climate (Indoor Air 2008). Technical University of Denmark.

McKeag, A. H., and P. W. Ranby. 1942. Great Britain Patent 578,192. Improvements in Luminescent Materials.

Mills, P. R., S. C. Tomkins, and L. J. M. Schlangen. 2007. “The Effect of High Correlated Colour Temperature Office Lighting on Employee Wellbeing and Work Performance,” Journal of Circadian Rhythms 5(2):1-9.

Naoyuki, O., and N. Tomimatsu. 2005. “Preference on Illuminance and Colour Temperature of Interior for Various Behavior Settings,” Proc. 2005 Annual Conference of the Illuminating Engineering Institute of Japan (in Japanese).

Navvab, M. 2001. “A Comparison of Visual Performance under High and Low Colour Temperature Fluorescent Lamps,” Journal of the Illuminating Engineering Society 30(2):170-175.

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Pinto, D. P., J. M. M. Linhares, and S. M. C. Nascimento. 2008. “Correlated Color Temperature Preferred by Observers for Illumination of Artistic Paintings,” Journal of the Optical Society of America 25(3):623-630.

Purdy, D. M. 1931. “Spectral Hue as a Function of Intensity,” American Journal of Psychology 43:541-559.

Wyszecki, G., and W. Stiles. 1982. Color Science: Concepts and Methods, Quantitative Data and Formulae, Second Edition. New York, NY: John Wiley & Sons.

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In Search of Luminance

Understanding What We See

Ian Ashdown, P. Eng., FIES

Chief Scientist, Lighting Analysts Inc.

[ Please send comments to ]

The IES Lighting Handbook, Tenth Edition (IES 2010), describes luminance as “perhaps the most important quantity in lighting design and illuminating engineering.” This is an accurate but curious description, as the editors neglected to include an entry for Section 5.7.3, Luminance, in the handbook’s index.

The section itself is a mere five paragraphs long, informing the curious reader that luminance is the “local surface density of light emitting power in a particular direction,” defined mathematically as:

In Search of Luminance - EQN 1

which for most readers will be completely and absolutely … opaque.

This is unfortunate, as luminance is undeniably the most important quantity, and indeed the most fundamental concept, in lighting design and illuminating engineering. More than a mathematical definition, professional lighting designers need to understand what it is that we see.

Luminance Understood

To understand luminance, we begin with a parallel beam of light. Ignore any thoughts of surfaces or light sources; just imagine a beam of light traveling through empty space in a given direction. Imagine also that this beam has a finite width; say, a rectangular beam one meter on a side.

If we take a cross-section of this beam at any point along its length, we can measure so many lumens of light (i.e., photons per second) per unit area. In photometric terms, this is the luminous flux Φ per unit area, or luminous flux density, of the beam. Being parallel, the beam does not diverge or converge, and so the luminous flux density remains constant along the length of the beam.

Now, what happens if the beam illuminates a real or imaginary surface at an angle? We have this:

In Search of Luminance - FIG 1

FIG. 1 – Illuminance of a surface A

The luminous flux per unit area received by the surface A is determined by the cosine of the angle of incidence θ from the surface normal n. Conceptually, as the angle of incidence becomes greater (i.e., more oblique), the illuminance E (lumens per unit area) of the surface decreases. The expression A cos θ represents the projected area of the illuminated surface, and is equal to the cross-sectional area of the beam.

This is nothing more than Lambert’s Cosine Law (Lambert 1760):

In Search of Luminance - EQN 2

If we imagine the area A as being infinitesimally small, we can designate it as dA (for “differential area”). Similarly, the amount of luminous flux Φ within the infinitesimally narrow beam approaches zero, and so we designate it as dΦ. This gives us:

In Search of Luminance - EQN 3

This is basic high school algebra! Ignore the symbols and concentrate on the underlying physical concept.

We can further imagine the beam not as a parallel beam that is infinitesimally narrow, but as an elemental cone whose infinitesimal solid angle we designate as . (See the previous article Solid Angles for an explanation of this concept.)

In Search of Luminance - FIG 2

FIG. 2 – Luminance of a differential surface dA

With this, we have the conceptual framework to understand the formal definition of luminance:

In Search of Luminance - EQN 4

where the factor d2Φ does not mean that the symbol d is being squared. Rather, it simply means that the luminous flux dΦ is being divided by the solid angle of the elemental cone dω and the area dA. Further, the parameter ψ indicates that the luminance may also vary when the beam is rotated horizontally by angle ψ around the surface normal n.

What this equation is saying is that the luminance L of the surface dA is equal to the amount of luminous flux Φ (lumens) leaving dA in the direction θ and contained within the elemental cone (i.e., parallel beam) dω. This is equivalent to the IES Lighting Handbook description of “local surface density of light emitting power in a particular direction.”

There is an important but underappreciated corollary to this definition of luminance. Recalling that the surface can be real or imaginary, we can imagine placing an imaginary surface that is perpendicular to the beam direction (i.e., θ is equal to zero) anywhere along its length. What this means is that the luminance of a parallel beam of light is constant along its length. In other words, luminance is not an intrinsic property of the surface, but of the beam itself. (As an example, the sky has a measurable luminance when viewed from the ground, but it has no real surface.)

Dispensing with the mathematics, we can therefore say:

Luminance is the amount of luminous flux per unit area as measured in a parallel beam of light in a given direction.

Photometry is traditionally taught using the concept that luminance is a property of real or imaginary surfaces. The problem with this approach is that you cannot easily explain why participating media such as the atmosphere, smoke, fog, colloidal suspensions in water, and so forth have measurable luminance. Thinking of luminance as a property of a beam of light rather than of surfaces eliminates this difficulty.

Luminance Perceived

How do we perceive luminance? Imagine that you are looking at a blank sheet of matte white paper. Being an approximately ideal diffuser (except at very oblique angles), this paper will scatter incident light equally in all directions.

Now, imagine that each point of the paper’s surface is a point source of light. In accordance with the inverse square law, the luminous flux density of this light will decrease with the square of the distance from the point source. That is:

In Search of Luminance - EQN 5

where I is the intensity of the point source, d is the distance from the source, and E is the illuminance of a surface (such as the cornea of your eye) at that distance … so why do we see and measure the luminance of the paper as being constant with distance?

To answer this, we need to look at the eye itself, which basically consists of a lens that focuses images onto the cones and rods of the retina. Each cone and rod has a finite width, and so it receives light from a finite area of the surface of the paper.

In Search of Luminance - FIG 3

FIG. 3 – Eye focusing a parallel beam onto the retina

But wait! This area of the paper is dependent on the distance of the paper from the eye. Moreover, it is proportional to the square of the distance … which exactly cancels out the inverse square law for a single point source. Therefore, we perceive the luminance of a finite area surface as being constant regardless of its distance from the eye.

There is a counterexample that emphasizes this point: the night sky. Even though the actual diameter of a star may be a million miles or so, it is so far away that we perceive its light as a parallel beam that is focused onto a single rod or cone of our retina. The luminance of this beam is constant, and so we see the star as having a specific perceived brightness (or visual magnitude). The inverse square law still applies to the star’s emitted light, however – it is after all a point source – and so its magnitude depends on its distance from the Earth. All other things being equal, more distant stars are inherently fainter.

How the eye sees a parallel beam of light, however, is the key point: wherever we look, we see luminance. We do not see luminous intensity or illuminance; we see the luminance of beams of light. Luminance really is the fundamental concept of lighting design.


A famous 20th-century physicist (whose name I regrettably cannot recall, even with Google’s assistance) once observed that until you can visualize a problem, you cannot truly understand the mathematics that describe it. He was likely referring to quantum mechanics, which nobody yet fully understands, but the observation still applies. In particular, knowing the mathematical definition of luminance is not enough; we must understand the concept of luminance. With this understanding, we can better understand its importance to lighting design and illumination engineering.


IES. 2010. IES Lighting Handbook, Tenth Edition. New York, NY: Illuminating Engineering Society of North America.

Lambert, J. H. 1760. Photometria (in Latin). English translation by D. L. DiLaura, 2001. New York, NY: Illuminating Engineering Society of North America.

Smith, W. 2008. Modern Optical Engineering, Fourth Edition. New York, NY: McGraw-Hill.

Blue Light Hazard … or Not?

Argumentum ab Auctoritate

Ian Ashdown, P. Eng., FIES

Chief Scientist, Lighting Analysts Inc.

[ Please send comments to ]

As a professional lighting designer, you will likely have read about the “blue light hazard” associated with white light-emitting diodes. You will have seen warnings like this (Willmorth 2014a):

“… long term exposure to blue light at 441nm caused lesions on the retinas of rhesus monkeys.”

and recommendations like this from the same author:

“Use the lowest CCT LED color with the highest CRI available to suit the lighting application – including avoidance of high CCT (> 5000K), low CRI (<80) sources altogether, and eliminate use of blue-light rich products, such as those generating >5500K at <65CRI.”

and even this (Kitchel 2000):

“…all persons with vision problems should be removed from a light environment where the predominant light waves are a temperature above 3500K or a wavelength less than approximately 500 nm.”

It is a confusing situation for lighting designers, as there are well-documented vision and health benefits to the use of high-CCT lighting. These benefits include circadian rhythm entrainment (e.g., Holzman 2010) and improved visibility (e.g., Berman et al. 2006). Taken together, the recommendations are at best contradictory.

As always, “… there is a need for more focused research leading to practical recommendations on this subject” (Willmorth 2014a). In the meantime however, lighting designers need to make informed decisions on behalf of their clients. What to do?

There is no short answer. As this article demonstrates, the issue of blue light causing retinal lesions is based on a misunderstanding of vision research work done in the 1970s. It is still an open question as to whether long-term chronic exposure to blue light may cause vision problems, but the evidence to date (known to this author at least) is not persuasive. [Update 14/11/08 – see concluding paragraphs and SCENIHR (2012).]

[UPDATE 14/12/11 – See revised concluding paragraphs and GLA 2012.]

The recommendation above – “Use the lowest CCT LED color with the highest CRI available to suit the lighting application” – also highlights the danger to journalists when combining reviews of the academic literature with design recommendations. While it could be construed from the article that this recommendation is based on concerns about vision problems, it is instead advice that the author would communicate to any client (Willmorth 2014b), regardless of the academic literature.

To be perfectly clear, this article is in no way meant as a criticism of Willmorth (2014a). It is instead an exploration of how scientific research can be misinterpreted and then promulgated in good faith as scientific fact. It is a problem that all science journalists face, myself included.

More to the point however, this article attempts to clarify some of the issues concerning the “blue light hazard.” As lighting designers, it is important to realize that direct viewing of extremely high-brightness LEDs may cause eye damage. At the same time, it is important to understand that these concerns are distinct from everyday interior lighting design practices.


Lighting Research Center researcher John Bullough published “The Blue-Light Hazard: A Review” in the Journal of the Illuminating Engineering Society (Bullough 2000), in which he summarized the research on the role of short-wavelength (i.e. deep blue) light and ultraviolet radiation in retinal damage. Quoting from this paper:

“For practical purposes with ‘white’ light sources, any condition resulting in direct exposure to luminances under 10,000 cd/m2 is unlikely to present a risk of photochemical injury to the retina. For such sources, calculation of the blue light hazard is not necessary.”

Putting this into context:

“… might lead one to believe [that] fluorescent lamps present greater risk than incandescent lamps, because they produce a greater portion of their light in the short-range portion of the visible spectrum. However, because fluorescent lamps also have low luminances (T12 lamps: 8,000 cd/m2; T8 lamps: 11,000 cd/m2; T5 lamps: 20,000 cd/m2), their potential risk for photochemical injury is negligible …”

Bullough examined potential risks in the context of medical equipment, industrial equipment, and high-flux theatrical lighting. In terms of extremely high-brightness LEDs, there is clearly a risk in viewing them directly. People with aphakia (absence of the lens of the eye, often due to surgical removal) may also be at risk. In general however, there is no blue light hazard for interior lighting applications.

Trust in Authority

So where did the current “blue light hazard” meme originate? Willmorth (2014a) notwithstanding, why are lighting designers now being advised to avoid high-CCT lighting wherever and whenever possible?

The underlying problem is that lighting designers cannot be expected to follow the medical literature on which these recommendations may be based. How many people for example outside of the medical profession read such journals as Epidemiology and Biostatistics or Investigative Ophthamology & Visual Science? (How many people can even spell “ophthalmology” correctly, for that matter?)

The solution is beguilingly simple: trust in those who are experts in such matters. Lighting designers read trade journals such as Lighting Design & Application and Architectural SSL because of these publications’ reputation for accurate and useful information. Their technical articles are after all either written by qualified experts, or by staff writers who consult them.

Who we trust however is subject to the logical fallacy of argumentum ab auctoritate, or “argument from authority” (including trust in those who, like me, quote Latin phrases). In more colloquial terms, “Just because you say it’s so don’t make it so!”

To illustrate this argument, consider the quotation above (Willmorth 2014a):

“… long term exposure to blue light at 441nm caused lesions on the retinas of rhesus monkeys.”

The article in question is titled, “The Dark Side of BLUE LIGHT,” which was written by Kevin Willmorth, Consulting Editor for Architectural SSL. Educated at the University of Phoenix, he has over 33 years of experience in lighting design and product development. Given this, there is no reason to question his authority per se. However, we need to ask where this worrisome statement came from.

Like most trade journals, Architectural SSL has an aversion to publishing full references in its technical articles. There are two likely reasons for this: 1) very few readers will be interested in reading the referenced papers; and 2) full references consume valuable advertising space. Regardless of the reasons, the author can do no more than identify the name of the researcher and possibly the paper’s title in the text of the article.

In other words, trust in authority.

Full References

Thankfully, Willmorth was fairly specific in referencing (in the same sentence) “The Effects of Blue Light on Ocular Health (Kitchel, E. American Printing House for the Blind.” (The more common alternative is to simply say, “According to …”) A simple Web search leads directly to It is an online article, but it was originally published in the Journal of Visual Impairment and Blindness (Kitchel 2000).

Elaine Kitchel is Low Vision Project Leader at the American Printing House for the Blind, with a Masters of Education from the University of Arizona. In her review article, she writes:

“In an early study conducted by Ham, Ruffolo, Mueller and Guerry, (1980) rhesus monkeys were exposed to high‑intensity blue light at 441nm for a duration of 1000 seconds. Two days later lesions were formed in the retinal pigmented epithelium (RPE.) These lesions consisted of an ‘inflammatory reaction accompanied with clumping of melanosomes and some macrophage invasion with engulfment of melanosomes which produce hypopigmentation of the RPE’ (Ham et al., 1980, p.1110).”

We now have a reference for the original quote, including a page number … or do we? Once again, the article does not include references, rather unhelpfully stating, “A bibliography is available separately.” Fourteen years after publication, it is unlikely that this unnamed document will still be available.

Trust in authority.

Monkey Business

Fortunately, it is possible with some effort to ascertain the proper reference. It is:

Ham, W. T., Jr., H. A. Mueller, J. J. Ruffolo Jr., and D. Guerry. 1980. “The Nature of Retinal Radiation Damage: Dependence on Wavelength, Power Level, and Exposure Time,” Vision Research 20(12):1105-1111.

William T. Ham and his fellow researchers were at the time associated with the Department of Biophysics, Virginia Commonwealth University (Richmond, VA). Vision Research being a highly respected peer-reviewed journal, their paper of course included copious references.

Trust in authority? Not quite … if you obtain and read the review paper, you will find no mention of “blue light at 441 nm” on page 1110. Here is what the authors wrote:

“Histological data, Ham et al., (1978), on the retina of the rhesus monkey demonstrate that short wavelength light plays a role in the clumping and phagocytosis of melanin. The appearance of a mild lesion in the RPE of the rhesus monkey at 90 days postexposure suggests a striking similarity to senile macular degeneration. In the opinion of the authors, long-term, chronic exposure to short wavelength light is a strong contributing factor to senile macular degeneration.”

This is an interesting observation that is apparently still valid – see for example Berman and Clear (2014) – but it is not what we are after.

In reading the full paper, there is an interesting figure caption on page 1107:Blue Light Hazard - FIG. 3Fig. 3 – Retinal response in the same eye as Fig. 2 at 2 days after a 1000 sec exposure to 441 nm light (10 nm bandpass). The image diameter at the retina was 1 mm, and the radiant exposure was 33 J/cm2. (Source: Ham et. al. 1980.)

This microphotograph of a rhesus monkey’s retina is from research reported by Ham et al. (1978), which was based on an earlier paper (Ham et al. 1976), both listed in the references. The arrows in the image indicate the observed lesions.

It helps to have some appreciation of the nature of this research. Ten rhesus monkeys were anesthetized and laser beams shone into their eyes in order to determine the damage threshold for various beam intensities and wavelengths. The primates were then later “sacrificed” and their eyes dissected to obtain the microphotographs showing possible radiation damage. This is clearly not the sort of research that can be conducted on human subjects.

In their paper, the authors reported the following radiation damage thresholds for a 441.6 nm helium-cadmium laser:

1 second 16 seconds 100 seconds 1000 seconds
0.91 watts / cm2 0.41 watts / cm2 0.20 watts / cm2 0.03 watts / cm2

(A joule is one watt-second, so 0.03 watts per square centimeter for 1,000 seconds is 30 joules/cm2, as indicated in Figure 3 above.)

In their 1978 paper, the authors replaced the laser beam with a 2,500-watt xenon lamp and a 6 nm bandwidth interference filter at 441 nm with associated optics to focus the beam onto a 1-mm diameter region of the monkey’s retina for up to 1,000 seconds. (Kids, don’t try this science experiment at home …)

Grim and disturbing details aside, we have finally answered the question – where did the information quoted by Kitchel and through her by Willmorth come from?

What we have not answered however is the question of whether this research is relevant to the “blue light hazard” issue.

Inadmissible Evidence

It is true that Ham et al. (1976, 1978) established that exposure to blue light can cause retinal lesions, however microscopic. However, maximum exposure times of 1,000 seconds (16 minutes) are hardly “long-term exposure” as described by Willmorth (2014). Simply put, the research of Ham et al. did not address the issue of long-term exposure to blue light.

Equally interesting is this quote: (Ham et al. 1976):

“… the solar retinal irradiance at 440 nm for a 20-nm spectral band is approximately 0.20 W/cm2 at midday for an eye gazing directly at the Sun at sea level for a 2-mm diameter pupil. In comparison, the threshold irradiance for a 100-sec exposure to the 441-nm laser line of He-Cd is 0.20 W/cm2. Thus, sungazing at bright midnoon for 100 sec can produce a threshold lesion … those subject to exposure to bright sunlight over long periods should take precautions to shield their eyes from the short wavelengths of solar radiation.”

In other words, what Ham et al. discovered through careful experiment was the glaringly obvious: do not stare at the noonday sun without blinking for longer than 100 seconds. [UPDATE 17/05/17: Changed “fifteen minutes” to “100 seconds.”] This is not mockery of their research – Ham et al. were investigating the distinction between thermal and photochemical effects of high-intensity light on the retina. Their comparison with sungazing, while instructive, was merely by way of analogy to put the beam intensity levels into context for the reader.

This is not to say that long-term chronic exposure to blue-rich light does not result in adverse health effects, including cataracts and age-related macular degeneration. Ham et al. did their work nearly forty years ago. There may well be more recent research that is relevant to the “blue light hazard,” such as for example Shang et al. (2014). (Whether this fundamentally flawed paper is applicable to human vision is a separate issue.)

Regardless, the research of Ham et al. is “inadmissible evidence” (to use the legal expression) with respect to the long-term effects of blue light exposure. It is not a question as to whether it is right or wrong, but simply that it does not apply.

The problem – the real problem – is that journalists are expected to interpret academic research for the general public. Like Willmorth and Kitchel, they may have considerable knowledge in their fields of expertise. Unfortunately, the “blue light hazard” issue intersects research fields in both lighting and medicine. As such, journalists need to take particular care in interpreting published papers on the topic. For whatever reason, there was some miscommunication in this case.


To summarize, there may possibly be persuasive evidence that long-term chronic exposure to blue-rich (i.e., high CCT) lighting may adversely affect our vision and health. Articles such as “The Dark Side of BLUE LIGHT” (Willmorth 2014a) and “The Effects of Blue Light on Ocular Health” (Kitchel 2000) have referred to the academic research literature (Ham et al. 1980) as evidence of danger. Unfortunately, all that this research proved in the context of the “blue light hazard” was the obvious: do not stare at the noonday sun without blinking for longer than 100 seconds. [UPDATE 17/05/17: Changed “fifteen minutes” to “100 seconds.”]

As Kevin Willmorth said, “… there is a need for more focused research leading to practical recommendations on this subject.” In the meantime however, this author at least is still looking for persuasive evidence that there is any significant blue light hazard associated with high-CCT LED lighting.

At the same time, I agree with Kevin when he says (Willmorth 2014b), “I cannot recommend [that] anyone apply poor-quality, low color performance light sources of any type when alternative are available” … but this is just our opinion. In the absence of evidence to the contrary, there does not appear to be any scientific reason to be concerned about blue-rich lighting in typical interior environments.

UPDATE – November 8, 2014

In 2010, the French Agency for Food, Environmental and Occupational Health & Safety (ANSES) published a 310-page report (in French) titled, “Health Effects of Lighting Systems Using Light-Emitting Diodes (LEDs)” (ANSES 2010), with an English-language opinion and summary (ANSES 2010b). Page 3 of the summary reads:

“Some scientific studies [Dawson et al., 2001, Ueda et al., 2009], based on laboratory experiments with blue LEDs conducted on monkeys, give reason to suspect a danger for the retina related to exposure to light-emitting diodes.”

Déjà vu, non?

The remainder of the summary offers recommendations that are reasonable in view of the photobiological risks of high-brightness LEDs. However, the risk of having the “reason to suspect” statement taken out of context in support of the “blue light hazard” meme remains.

Reading the referenced papers of course provides more information. Dawson et al. (2001) sacrificed five rhesus monkeys after exposing them to between 5 and 54 joules/cm2 of blue light from a 458 nm argon laser. Again, this is roughly equivalent to staring at the noonday sun without blinking for 3 to 25 minutes.

Ueda et al. (2009) sacrificed eight monkeys (two rhesus and six long-tailed macaque) after exposing them to between 20 and 60 joules/cm2 from Nichia NSPB550S blue LEDs with a dominant wavelength of 465 nm. Similar to the earlier studies of Hall et al. (1976), they reported retinal lesions after exposure to 35 joules/cm2, but no detectable results after exposure to 20 joules/cm2.

Blue Light Hazard - Macaque

Long-tailed macaque (photo credit: Lea Maimone)

There must be something apparently irresistible about such studies, as van Norren et al. (2011) provide a critical review of no fewer than 56 papers on the topic. What is interesting is that the results of eight such experiments (including Ham et al. 1976) yielded essentially the same results for rabbits and monkeys:

Blue Light Hazard - Norren

Dose for retinal damage versus wavelength. Source: Fig. 1(b), van Norren et al. (2011)

while the results for rodents (including both albino and pigmented rats) were equally similar. To summarize these results, do not stare at the noonday sun without blinking for longer than 100 seconds. [UPDATE 17/05/17: Changed “fifteen minutes” to “100 seconds.”] Once again, the evidence that long-term chronic exposure to blue-rich (i.e., high CCT) lighting may adversely affect our vision and health is not persuasive.

A much more interesting publication was recently published by the International Energy Agency (IEA 2014). Providing a wealth of information on the photobiological hazards of solid-state lighting, it concludes in Section 5.6.3, Potential Effects of Long-term Exposures, that:

“The ICNIRP exposure limit values do not take into account the possibility of an exposure over an entire lifetime. Very little is known about the effects of lifelong cumulated exposures to blue light emitted by LEDs. According to the Scientific Committee on Emerging and Newly Identified Health risks (SCENIHR) of the European Commission [SCENIHR 2012], no evidence was found indicating that blue light from artificial lighting belonging to Risk Group 0 would have any impact on the retina graver than that of sunlight. The SCENIHR states that IEC 62471 gives limits that are protective against acute effects, while longterm effects are only marginally considered and estimated to be of negligible or small risk.”

Following the paper trail to its end, we have (SCENIHR 2012):

“Evidence from in vitro experiments suggest that blue light at 10 W/m2 induces photochemical retinal damages (Class II) up on acute (hours) exposure, and animal experiments and in vitro studies suggest that cumulative blue light exposure below the levels causing acute effects also can induce photochemical retinal damage.

“There is no consistent evidence from epidemiological studies regarding the effect of long-term exposure to sunlight (specifically the blue component of sunlight) and photochemical damage to the retina (particularly to the retinal pigment epithelium), which may contribute to age-related macular degeneration (AMD) later in life. Whether exposure from artificial light could have effects related to AMD is uncertain.

“There is no evidence that artificial light from lamps belonging to RG0 or RG1 would cause any acute damage to the human eye. Studies dedicated to investigating whether retinal lesions can be induced by artificial light during normal lighting conditions are not available. Lamp types belonging to RG2 and higher are usually meant to be used by professionals in locations where they do not pose a risk. Chronic exposure to blue light from improperly used lamps could, in theory, induce photochemical retinal damage in certain circumstances. There is however no evidence that this constitutes a risk in practice. It is unlikely that chronic exposures to artificial light during normal lighting conditions could induce damage to the cornea, conjunctiva or lens.”

and finally from the abstract (ibid):

There is no evidence that blue light from artificial lighting belonging to Risk Group 0 (“exempt from risk”) would have any impact on the retina graver than that of sunlight. Blue light from improperly used lamps belonging to Risk Groups 1, 2, or 3 could, in theory, induce photochemical retinal. There is no evidence that this constitutes a risk in practice. Other damages to the eye from chronic artificial light exposure during normal lighting conditions are unlikely. Exposure to light at night (independent of lighting technology) while awake (e.g. shift work) may be associated with an increased risk of breast cancer and also cause sleep, gastrointestinal, mood and cardiovascular disorders.

In the end, we have no option but to appeal to authority (argumentum ab auctoritate). SCENIHR (2012) represents the opinions of a dozen medical professionals who are presumed experts in the field. The difference however is that they are specifically addressing the issue of “blue light hazard” with full knowledge (circa 2012) of existing lighting technologies. Their 118-page report includes a staggering 341 references to the academic literature.

[UPDATE 14/12/11: The Global Lighting Association, representing ten regional lighting industry associations from around the world, released a white paper in March 2012 with the abbreviated title “Optical Safety of LEDs.” There are two versions, one being a 22-page document with a detailed and in-depth analysis of the photobiological risks of common “white light” lamp types, and the other being a 4-page abridged document. Their well-documented position statement is simple: “… based on accepted and widely adopted safety standards for lamps, is that all general lighting sources, including LED and CFL sources (either lamps or systems) and luminaires, can be safely used by the consumer when used as intended.”]

There may be medical studies yet to be conducted that will demonstrate a blue light hazard for solid-state lighting in typical interior lighting applications. However, the absence of such evidence to date is highly persuasive: there is no scientific reason to be concerned about blue-rich lighting in typical interior environments.


ANSES. 2010a. Effets sanitaires des systèmes d’éclairage utilisant des diodes électroluminescentes (LED). Maisons-Alfort, France: French Agency for Food, Environmental and Occupational Health & Safety.

ANSES. 2010b. Opinion of the French Agency for Food, Environmental and Occupational Health & Safety in response to the internally-solicited request entitled “Health Effects of Lighting Systems Using Light-Emitting Diodes (LEDs).” Maisons-Alfort, France: French Agency for Food, Environmental and Occupational Health & Safety.

Berman, S., M. Navvab, M. J. Martin, and J. Sheedy. 2006. “A Comparison of Traditional and High Color Temperature Lighting on the Near Acuity of Elementary School Children,” Lighting Research & Technology 38(1):41-52.

Berman, S., and R. Clear. 2013. “Another Blue Light Hazard?,” Lighting Design & Application 43(3):65-68.

Bullough, J. D. 2000. “The Blue-Light Hazard: A Review,” Journal of the Illuminating Engineering Society 29(2):6-14.

Dawson, W., T. Nakanishi-Ueda, D. Armstrong, D. Reitze, D. Samuelson, M. Hope, S. Fukuda, M. Matsuishi, T. Ozawa, T. Ueda and R. Koide. 2001. “Local Fundus Response to Blue (LED and Laser) and Infrared (LED and Laser) Sources,” Experimental. Eye Research 73:137-147.

GLA. 2012. Optical and Photobiological Safety of LED, CFLs, and Other High Efficiency General Lighting Sources. Global Lighting Association.

Ham, W. T., Jr., and D. H. Sliney. 1976. “Retinal Sensitivity to Damage from Short Wavelength Light,” Nature 260:153-154.

Ham, W. T., Jr., J. J. Ruffolo Jr., H. A. Mueller. A. M. Clarke, and M. E. Moon. 1978. “Histologic Analysis of Photochemical Lesions Produced in Rhesus Retina by Short-wave-length Light,” Investigative Ophthamology & Visual Science 17(10):1029-1035.

Ham, W. T., Jr., H. A. Mueller, J. J. Ruffolo Jr., and D. Guerry. 1980. “The Nature of Retinal Radiation Damage: Dependence on Wavelength, Power Level, and Exposure Time,” Vision Research 20(12):1105-1111.

Holzman, D. C. 2010. “What’s in a Color? The Unique Human Health Benefits of Blue Light,” Environmental Health Perspectives 118(1):A22-A27.

IEA. 2014. Energy Efficient End-Use Equipment (4E) Solid State Lighting Annex – Potential Health Issues of Solid State Lighting Final Report. Paris, France: International Energy Agency.

Kitchel, E. 2000. “The Effects of Blue Light on Ocular Health,” Journal of Visual Impairment and Blindness 94(6):399-403.

SCENIHR. 2010. Health Effects of Artificial Light. Brussels, Belgium: European Commission (Scientific Committee on Emerging and Newly Identified Health Risks).

Shang, Y.-M., G.-S. Wang, D. Sliney, C.-H. Yang, and L.-L. Lee. 2014. “White Light-Emitting Diodes (LEDs) at Domestic Lighting Levels and Retinal Injury in a Rat Model,” Environmental Health Perspectives 122(3):269-276.

Ueda, T., T. Nakanishi-Ueda, H. Yasuhara, R. Koide, and W. W. Dawson. 2011. “Eye Damage Control by Reduced Blue Illumination,” Experimental Eye Research 89:863-868.

van Norren, D., and T. G. M. F. Gorgels. 2011. “The Action Spectrum of Photochemical Damage to the Retina: A Review of Monochromatic Threshold Data,” Photochemistry and Photobiology 87:747-753.

Willmorth, K. 2014a. “The Dark Side of BLUE LIGHT,” Architectural SSL 05.14, pp. 12-16.

Willmorth, K. 2014b. Personal communication.

In the Blood

Lighting Design for Medical Diagnosis

Ian Ashdown, P. Eng., FIES

Chief Scientist, Lighting Analysts Inc.

[ Please send comments to ]

We most often think of lighting design in terms of lumens, color temperature, and CRI, but there are occasional situations where a deeper analysis is required. One such situation is as close as your doctor’s office: the examination room.

An examination room is typically windowless and illuminated only by linear fluorescent lamps. In examining the patient’s skin for anything from bruises to lesions, the doctor relies on experience to assess skin color. Anything that influences this perceived color should be a concern, for it could potentially lead to a misdiagnosis.

As lighting designers, our usual criterion for selecting light sources is the CIE General Colour Rendering Index (CRI) metric (CIE 1995). Anyone who remembers the first generation of white light LED products will recognize that CIE Special Colour Rendering Index R9 is also important, as it determines the red content needed for acceptable skin tones.

This however may not be enough for applications involving medical diagnosis. It is an interesting exercise to ask what determines our skin color and whether different illuminants might lead to unexpected changes in perceived color.

Skin Color

Skin color shows large variations across continental populations, but it is mostly due to the concentration of two biopolymers: eumelanin and pheomelanin (e.g., Parra 2007). Eumelanin is dark brown to black in color, while pheomelanin is yellow to reddish brown. Our skin produces melanin in response to exposure to ultraviolet radiation, causing the skin to visibly tan. (Melanin is a highly effective natural sunscreen.)

By itself, melanin is not particularly interesting from a lighting design perspective. As shown in FIG. 1, it has a smooth spectral absorption spectrum that increases monotonically with decreasing wavelength. Changes in the spectral power distribution of the light source will have little effect on perceived color as long as the light sources have the same correlated color temperature (CCT) and similar CRI values.


FIG. 1 – Melanin absorption spectrum (Kollias [1995]).

A secondary but still important determinant of skin color is the hemoglobin in our blood. It is responsible for example for the reddish color of sunburnt skin, as well as the inflammation that accompanies many skin infections. Its presence becomes more noticeable in fair-skinned individuals.

There are two types of hemoglobin in our blood – oxygenated (designated HbO2) and deoxygenated (designated Hb). Unlike melanin, they have rather complex spectral absorption spectra, as shown in in FIG. 2.

Hemoglobin Spectra

FIG. 2 – Hemoglobin absorption spectra (Prahl [1999]).

The contributions of both melanin and hemoglobin are evident in FIG. 3, which shows the variation in spectral reflectance of the inner upper arms (chosen to avoid suntan issues) of subjects from several different continental populations. Those with dark skin have smooth spectral reflectance distributions characteristic of melanin, while those with fair skin have complex spectral reflectance distributions due to the contribution of hemoglobin.

Skin reflectanceFIG. 3 – Skin spectral reflectance (Parra [2007]).


What is interesting about FIG. 3 is that Caucasian skin exhibits a pronounced dip in reflectance at 430 nm, presumably due to the absorption spectrum of both oxygenated and deoxygenated hemoglobin. This corresponds almost exactly with the narrowband emission of blue light from linear fluorescent lamps, which peaks at 435 nm as shown in FIGs. 4A – 4C.

Halophosphate fluorescent lamp spectra (CIE 2004)

FIG. 4A – Halophosphate fluorescent lamp spectra (CIE 2004).

Broadband fluorescent lamp spectra (CIE 2004)

FIG. 4B – Broadband fluorescent lamp spectra (CIE 2004).

Triphosphor fluorescent lamp spectra (CIE 2004)

FIG. 4C – Triphosphor fluorescent lamp spectra (CIE 2004).

By comparison, FIG. 5 shows the spectral power distribution of a typical white light phosphor-coated LED (in this case a Philips Luxeon K LED array). The phosphor pump LED has a peak wavelength of 450 nm.


FIG. 5 – White light phosphor-coated LED spectra (Philips Lumileds 2014).

The hypothesis is this: even if an LED-based replacement lamp for a linear fluorescent lamp has the same CCT and similar CRI, the LED peak wavelength is not centered on the absorption peak of hemoglobin. As shown in FIG. 3, Caucasian skin reflectance at 450 nm can be some 25 percent greater than at 430 nm. Certainly increasing the amount of blue light from an RGB luminaire by 25 percent changes the color of the emitted light. The question is whether this will change the perceived skin color for medical diagnosis.

The issue is complicated by the finite width of the emitted blue light in the blue region of the spectrum. The LED has a full width half maximum (FWHM) value of 35 nm, while the fluorescent lamps appear to have FWHM values of less than 10nm. (The CIE lamp spectra are tabulated in units of 5 nm.)

The best way to test this hypothesis then is to calculate the theoretical perceived skin color (technically its chromaticity) using the lamp spectra and the worst-case skin (Caucasian) spectral reflectance distribution.

Calculation Method

The calculation method is quite simple. We have the fluorescent lamp spectra tabulated at 5 nm, courtesy of Table T.6, “Relative spectral power distributions of illuminants representing typical fluorescent lamps,” from CIE 15:2004, Colorimetry (CIE 2004), over the range of 400 to 700 nm. To ensure comparable CCTs, we choose CIE F6 (4150 K), CIE F9 (4150K), and CIE F11 (4000K).

Philips does not provide tabulated spectral power distribution data for their Luxeon products, but it is easy enough to digitize the data using for example the freeware program Plot Digitizer ( Again, the 4000K product is selected.

Finally, the skin reflectance data can be digitized from the PDF file of the paper by Parra (2007).

With this, the CIE 1931 tristimulus coordinates X, Y, Z for each light source can be calculated as the sums:

Tristimulus equations

where s is the skin reflectance at the designated wavelength, E is the relative light source intensity, and x-bar, y-bar, and z-bar are the CIE color matching function values (from CIE 2004). From these, we can calculate the CIE 1931 xy chromaticity values as:

Chromaticity equations

If we choose the CIE F11 triphosphor lamp as our reference illuminant, this gives us:

Light Source CCT x y dx dy JND
F6 4150K 0.395 0.398 -0.009 +0.011 2
F9 4150K 0.393 0.383 -0.011 -0.004 1
F11 4000K 0.404 0.387 +0.000 0.000 0
Luxeon K 4000K 0.398 0.388 -0.006 +0.001 0

where JND represent one MacAdam ellipse (MacAdam 1942), or a “just noticeable difference” in perceived color under laboratory conditions from that of the reference lamp.

The halophosphate F6 fluorescent lamp results provide a useful sanity check. These 1970s-era lamps had very low red content and consequently CRIs in the low 70s. They tended to lend greenish color casts to Caucasian skin, which is shown by the two-MacAdam ellipse color shift towards green.

For modern triphosphor fluorescent lamps, however, we can see that there should be no perceptible color shift for normal skin color if they are replaced with white phosphor-coated LED products. In other words, the hypothesis is disproven.


This analysis necessarily considers normal Caucasian skin color only, based on the published results of Parra [2007]. It does not consider the abnormal skin colors due to for example hypoxia (low oxygenated blood levels). Such conditions are most often diagnosed using quantitative techniques, such as pulse oximetry (which measures the relative difference in transmittance of Hb and HbO2 at visible and infrared wavelengths.) Research is also being conducted into whether “spectrally-tuned” light sources might increase the contrast of various skin conditions when viewed in visible light – see for example Litorja et al. (2007, 2009, and 2010), amd Murai et al. (2012).

More important, this analysis has not been experimentally verified or peer-reviewed, and must not be taken as medical advice. If the question is asked, all that can be said is that, “theoretical analysis indicates that there should be no difference in the use of fluorescent versus LED-based replacement lamps for medical diagnosis of skin conditions.” If necessary, this analysis should be experimentally confirmed by a qualified physician who will be using the facility being designed.


It is interesting that this analysis has produced what is effectively a negative result. As such, it is unlikely that it would be accepted for publication by a peer-reviewed journal. Regardless, the result (subject to the disclaimer) itself is informative for lighting designers.

Taking a broader view, this analysis highlights the need for an industry standard for the electronic transfer of spectral data, much as IES LM-63-02 and EULUMDAT enable the electronic transfer of photometric data. It is frustrating and error-prone to have to manually digitize spectral data from scans of printed documents and screen captures of PDF files.

Fortunately, this situation is about to change. As of this writing, the IES Board has approved the publication of IES TM-27-14, IES Standard Format for the Electronic Transfer of Spectral Data. This document is scheduled for ANSI, and hopefully IEC, approval as an international standard. Once lamp and LED module manufacturers adopt this data format for their product specifications, studies such as this will become considerably easier to perform.


The topic of this blog posting arose from discussions with fellow members of the Human Centric Lighting Committee.

Update 2014/06/25

One of the joys of self-publishing through blogs is that you can post new information as it becomes available.

Cyanosis is the appearance of a blue or purplish discoloration of the skin due to the tissues near the skin surface having low oxygen saturation. I was aware of this medication condition while writing this article, but decided against discussing it on the advice of my family doctor, who had not seen a case of it in 25 years of family and sports medicine practice. If it is seen at all, it is likely in the emergency room, where pulse oximeters are usually available.

Regardless, there is a paper on the topic – “Lighting for Clinical Observation of Cyanosis” – (Midolo and Sergeyeva [2007]) and a government standard that lamps for hospital lighting in Australia and New Zealand must meet (AS/NZS [1997]) – the Cyanosis Observation Index (COI). There is also a now-outdated article on why older-style triphosphor lamps manufactured in the 1990s were not suitable for hospital lighting (LightLab [1997]).

Related to this is an interesting Philips white paper, “The Role of Lighting in Promoting Well-Being and Recovery within Healthcare” (Schlangen 2010). This 32-page publication on human-centric lighting for healthcare provides over 100 useful references to the literature.


AS/NZS. 1997. AS/NZS 1680.2.5:1997, Interior Lighting, Part 2.5: Hospital and Medical Tasks. Standards Australia.

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

CIE. 2004. CIE 15:2004, Colorimetry. Vienna, Austria: Commission Internationale de l’Eclairage.

Kollias, N. 1995. “The Spectroscopy of Human Melanin Pigmentation,” in L. Zeise et al., Eds., Melanin: Its Role in Human Photoprotection. Overland Park, KS: Valdenmar Publishing Company.

LightLab. 1997. Why Tri-Phosphor Lamps are Unsuitable for Hospital Lighting, Lab Notes Issue 4. Clontarf, Australia: LightLab International.

Litorja, M., S. W. Brown, M. E. Nadal, D. Allen, and A. Gorbach. 2007. “Development of Surgical Lighting for Enhanced Color Contrast,” Proc. Medical Imaging 2007, SPIE Vol. 61510K.

Litorja, M., S. W. Brown, C. Lin, and Y. Ohno. 2009. “Illuminants as Visualization Tool for Clinical Diagnostics and Surgery,” Proc. Advanced Biomedical and Clinical Diagnostic Systems VII, SPIE Vol. 71691B.

Litorja, M., and B. Ecker. 2010. “Use of a Spectrally Tunable Source to Explore Improvement in Chromatic Contrast for Illumination of Tissues,” Proc. Emerging Digital Micromirror Device Based Systems and Applications II, SPIE Vol. 759607.

MacAdam, D. L. 1942. “Visual Sensitivities to Color Differences in Daylight,” J. Optical Society of America 32(5):247-274.

Midolo, N. A., and L. Sergeyeva. 2007. “Lighting for Clinical Observation of Cyanosis,” The Australian Hospital Engineer 30(2):38-46.

Murai, K., H. Kawahiri, and H. Haneishi. 2012. “Improving Color Appearance of Organ in Surgery by Optimally Designed LED Illuminant,” Proc. World Congress on Medical Physics and Biomedical Engineering,” IFMBE Proceedings 39:1010-1013.

Parra, E. J. 2007. “Human Pigmentation Variation: Evolution, Genetic Basis, and Implications for Public Health,” Yearbook of Physical Anthropology 50:85-105.

Philips. 2010. White Paper: The Role of Lighting in Promoting Well-Being and Recovery within Healthcare. Koninklijke Philips Electronics N.V.

Philips Lumileds. 2014. Luxeon K Datasheet DS102. Philips Lumileds Lighting Company.

Prahl, S. 1999. “Optical Absorption of Hemoglobin,”

Zijlstra, W. G., A. Buursma and O. W. van Assendelft. 2000. “Visible and Near Infrared Absorption Spectra of Human and Animal Haemoglobin,” Utrecht, Netherlands: VSP Publishing.

Giving Light

A New Philosophy for Lighting Design

Ian Ashdown, P. Eng., FIES

Chief Scientist, Lighting Analysts Inc.

[ Please send comments to ]

Giving light … this phrase symbolizes a new philosophy of lighting design, a philosophy in the sense of how we think about the lighting design process. Much like the modernist movement in architectural design a century ago, it offers a reconciliation of lighting design practices with today’s rapid technological advancements and societal changes.

The innovations we are seeing in lighting hardware today are fascinating, but we are as always in danger of seeing these innovations in terms of existing technology. It is much like the first automobiles, which looked just like what they were called – horseless carriages. In some cases, these early and primitive vehicles came complete with buggy whip holders. As useless as they were, these accessories symbolized the inability of designers to fully adopt the new technology of internal combustion (and yes, electric) engines. The horse may have been absent, but it was still basically a 19th-century carriage.

Fig. 1 - ElectrobatFig. 1 – Electrobat – first successful electric car (1894)

We may laugh at the silliness of such thinking, but in reality we are no different. Look at today’s solid-state lighting: we insist on emulating century-old incandescent lamp form factors and worse, attempting to control them with AC phase-cut dimmers. We may mutter about market acceptance and existing installations, but the truth is that we are not all that comfortable imagining what is possible with solid state lighting technology.

The innovations we are seeing in lighting hardware are not only fascinating, but part of a much larger movement now called the Internet of Things. Just as the first mobile phones have brought us today’s smartphones, today’s seemingly unrelated innovations in solid-state lighting are about to lead us into a brave new world of lighting design that we are only beginning to understand.

The question is, do we as lighting designers want to quietly accept whatever products the large corporations may develop and market, or do we want to direct the development of this brave new world?

We begin with a look at our current philosophy …

The Philosophy of Lighting

For the past eight hundred millennia or more [1], we have had a clear and persistent understanding of light and lighting. Simply put, we view light as an intrinsic property of the light source. It is a world view that has both informed and limited how we approach the art and science of lighting design.

Our ancestors were intimately familiar with, and likely revered, fire as a source of light and lighting. Certainly fire occupied a central role in the religious beliefs of Zoroastrianism and Hinduism. Agni, the Vedic god of fire and sacrifice, took the form of fire, lightning, and the Sun. In Abrahamic theologies, the universe began with fiat lux – “let there be light.”

We are no different today. We have a much better understanding of the physics of fire and its derivatives (including the cosmological “Big Bang”, first introduced as a theory some eight centuries ago [2]), but we arguably still perceive and understand light and lighting as our distant ancestors did. It does not matter whether it is a burning torch, an incandescent lamp, or an organic light-emitting diode (OLED) – we think of emitted light as an intrinsic property of the light source.

We extend this thinking – this philosophy – to our lighting systems in terms of controlling the emitted light. From trimming the wick of a smoking tallow candle to sending digital commands to wireless lighting networks from our smartphones, we similarly view lighting control as an intrinsic property of the lighting system.

There is a German word – Weltanschauung – that translates as “world view.” It is a framework of ideas and beliefs that form a global description through which we interpret our world and interact with it. In this sense, our understanding of light and lighting is very much a world view. We intuitively think of light as something which illuminates the space around us and of lighting systems as something that we interact with. Light and lighting systems are an integral part of this experiential world.

We have of course undergone numerous paradigm shifts (aka “revolutions”) in lighting over the past two centuries or so, including gas lighting, incandescent lamps, fluorescent and high-intensity discharge lamps, electronic ballasts, fiber optics, solid-state lighting, and more. However, we have done so without changing how we think about light and lighting. To us, a light source is just that – a source of light.

A Lighting Abstraction

“Let me give light, but let me not be light.”

Portia, The Merchant of Venice

Fig. 2 - Portia

FIG. 2 – Ellen Terry as Portia by Albert Joseph Moore (c. 1885)

Shakespeare most likely meant “give light” in the sense of Portia having loose morals within her pending marriage. The phrase however is too evocative to ignore. The thought of us “giving light” is clearly an abstraction, but it is an exceedingly useful one from our perspective. It shifts the focus from designing for the illuminated environment to designing for people. The distinction is subtle but important.

But why an abstraction? The answer is that something as broad as a philosophy requires us to look at lighting design without being encumbered by any particular technology or hardware issues.

We all have our desires and preferences in terms of lighting, including intensity and dynamics, color temperature and color, and directionality and modeling. Wherever possible, we interact with lighting systems to satisfy our preferences. We turn the lights on and off when we enter or leave our offices, we dim the lights during a presentation in the conference room, and we open and close the blinds in response to daylight and weather conditions. We currently think of this in terms of controlling the light sources, of light being an intrinsic property of the light source.

Thinking …

What however if we turn this thinking – this philosophy – on its head? What if we consider light and light as intrinsic properties of ourselves? In this sense, we may abstractly “give light” to the environments we happen to be in.

Fig. 3 - The Thinker

Fig. 3 – The Thinker by Auguste Rodin (1879 – 1889)

We may give light to our personal environments, including private offices and our residences. However, we also implicitly follow social norms. We rarely for example consider adjusting the lighting in common areas when other people are present, and we do not even think about controlling the lighting in public spaces such as restaurants, theatres, and hotel lobbies. Outdoor lighting in particular we simply accept for what it is, although we may occasionally complain about poor lighting design.

There are however socially-accepted exceptions to the rule. The introduction of solid-state lighting a decade ago brought with it a wealth of interactive public art displays wherein viewer interaction was not only encouraged, but often considered an integral component of the display. The artist in effect provided the public with a mostly blank canvas on which to express their lighting preferences.

Fig. 4 - Philips Lighting Lumiblade OLEDs

Fig. 4 – Philips Lighting Lumiblade OLEDs

After ten years, the novelty of such displays has mostly gone. These were however early examples of people giving light to their illuminated environments.

Personal Lighting Control

There are other examples of giving light to public spaces where different people may have different lighting preferences. Networked lighting systems for offices have been around for the past twenty years or so, with the first commercial system arguably being the Ergolight system from what is now Philips Ledalite. Its original product features today form the backbone of most networked lighting systems.

Fig. 5 - Philips Ledalite Ergolight

Fig. 5 – Philips Ledalite Ergolight (1996)

What is interesting about these lighting control systems is that they provide each worker with a considerable degree of control over the lighting of their workspaces. They can dim and switch the downlight from the overhead luminaires, while integral occupancy sensors and timers can dim or turn off the lighting when the worker is not present. Integral photosensors can also be used to implement daylight harvesting where appropriate.

What is surprising is that since its introduction, the concept of personal lighting control has never been seriously challenged. Numerous academic studies have shown that office workers in general approve of such lighting control systems [3]. Even better, their use contributes significantly to energy savings.

As lighting designers, we have therefore been enabling people to give light to their workplace environments for the past two decades. It has been a fundamental change in how we think about light and lighting design – a change so subtle that we barely noticed that it had occurred. More than an abstraction, giving light has long been an accepted lighting design practice.

But now it is time to take this design philosophy to a new and more exciting level …

Our Networked Society

In 1959, the futurist Arthur C. Clarke wrote, “… the time will come when we will be able to call a person anywhere on Earth merely by dialing a number” [4]. A little over half a century later, there are reportedly some 4.5 billion mobile phone users in almost constant communication with each other. We are, in the words of the phone manufacturer Ericsson, a globally “networked society” [5].

Fig. 6 - Arthur C. Clarke

Fig. 6 – Arthur C. Clarke – Profiles of the Future

This is another change in our world view – who could have imagined a decade ago that we would so dependent today on cellular phones and smartphones for our daily activities? Even this however is only the beginning of the revolution – the Internet of Things (IoT) will connect us to almost every device and service imaginable in our daily lives. Analysts at Gartner, Inc. have predicted that by 2020, the installed base of IoT devices will be 26 billion units [6].

Lighting systems will of course be an important part of all this. Going beyond interactive public art displays and personal lighting control in open offices, we will soon have the technology to control lighting systems to a much greater extent than we do now. As lighting designers, we need to understand this technology and imagine the ways in which we can design lighting systems that benefit the user.

If we are to avoid thinking in terms of “horseless carriages,” we need to look beyond the technologies to the lighting design process itself. The philosophy of giving light provides the necessary mental framework. With such a framework in mind, we can consider the implementation details.

Identification and Geolocation

To control lighting systems, we first need to communicate with them. While such topics as wireless communications and networks may seem outside the realm of lighting design, they are anything but. It is not necessary to understand the technical details, but it is necessary to understand what is possible with today’s mobile communication devices.

Most of us are aware that law enforcements agencies can track mobile phones through cell towers and global positioning system (GPS) satellites and determine their position (“geolocation”) to within some 500 feet or so. This is however but one example of “real-time location services” [7]. Using a combination of GPS, cell tower communications, WiFi hot spots, and Bluetooth Low Energy (BLE) devices, it is possible to geolocate a mobile phone in three dimensions with an accuracy of approximately two feet with 95 percent accuracy whenever the device is turned on [8].

We may not always carry our smartphones with us, but the trend today is towards smartwatches, wearable computers that are as unobtrusive as old-fashioned wrist watches. Featuring a long and growing list of capabilities, these will likely become indispensable accessories for life in our networked society. With GPS and BLE capabilities, they will also – with our permission – tell the world who and where we are.

FIG. 7 - Samsung Galaxy Gear 2 Smartwatch

Fig. 7 – Samsung Galaxy Gear 2 Smartwatch

Public Profile

“You have zero privacy anyway – get over it.”

Scott McNealy, Sun Microsystems CEO (1999)

The operative word here is permission. We object to our loss of privacy mostly because it is being constantly invaded by corporations and governments without our knowledge, let alone our permission. Corporations harvest our personal information for the purposes of targeted advertising and business intelligence, while governments track us for various political reasons (and increasingly simply because they can). Commercial services such as for example Apple’s iBeacon have been developed expressly for commercial interests to track our movements and present us with targeted advertising … without our permission.

Suppose however that we consciously choose to publicly broadcast this information. Rather than having commercial and political interests trying to surreptitiously determine our preferences, we could maintain public profiles of ourselves. More than simple lists, these profiles would be even more richly detailed than those maintained by the retailers and credit card companies – but fully under our individual control. More important, these profiles would be electronically bound to our physical presence (albeit stored “somewhere in the cloud”). They would in a very real sense be an intrinsic property of ourselves.

With this capability, we can choose to tell the world who and where we are. In terms of lighting systems, all we need to do is to wirelessly broadcast a unique identifier; the system can then access our public profile via the Internet to determine our desires and preferences related specifically to lighting (if we so choose).

Visible Light Communications

From a lighting designer’s perspective, this is where it becomes interesting. The first lighting networks introduced some twenty years ago relied on wired RS-485 communications. These were superseded by faster Ethernet communications, and more recently by wireless mesh networks such as Zigbee Light Link [9].

An unfortunate disadvantage of wireless networks is that there can be numerous devices operating at the same frequency. As with shared Internet access and mobile phone usage, too many devices attempting to communicate at the same time may result in unacceptably poor system performance. This situation will only get worse as the Internet of Things gains traction.

Visible light communications, often referred to as “LiFi,” provides a solution. Beginning in the 1970s, inventors began developing modulation techniques for fluorescent lamps that enabled the broadcasting of audio signals using general illumination [10]. These saw some commercial success [11], but it was the development of light-emitting diodes and solid-state lighting that has renewed particular interest in the technology [12].

Fig. 8 - US Patent 3900404

Fig. 8 – US Patent 3,900,404 – Optical Communication System

The LiFi Advantage

LiFi offers several advantages over wireless communications. It is for example primarily line-of-sight, which results in potentially more secure communications. Solid-state lighting can also be modulated at high frequencies, providing up to four times the bandwidth of 3G mobile phone systems. Further, there are no restrictions on the carrier frequency or spectrum licensing requirements, so multiple systems can easily co-exist.

The one disadvantage is that LiFi is basically a broadcast system. Luminaires with LiFi capabilities can broadcast information, but receiving devices generally require infrared or wireless transmitters to respond. A local WiFi router or Bluetooth transceiver can for example receive the responses and communicate with the luminaires using Ethernet or a wireless network.

The true advantage of LiFi however is that it is no longer necessary for the lighting system to geolocate occupants with accuracies of a foot or less. All that is needed is for the luminaires to continually broadcast their unique identifiers, and for the occupant’s smartphone or smartwatch to detect these identifiers with its camera or a photosensor. The device can then wirelessly respond, “I see you” with the occupant’s public profile identifier. This is an exceedingly brief transaction that minimizes the device’s battery power requirements.

What is exciting about this is that this is not some futurist’s wish list for advanced technology. The technology already exists, and it is already being commercialized.

Commercial Products

Royal Philips recently introduced an “intelligent in-store LED lighting system” that communicates information to shoppers via their smartphones and LED-based luminaires [14]. All the shoppers have to do is to point their smartphone cameras at the nearest overhead luminaire.

Fig. 9 - Philips Connected Retail Lighting System

Fig. 9 – Philips Connected Retail Lighting System

Philips has even more recently introduced a “smartphone-controlled connected office lighting system” [14]. This system enables office workers to control both the lighting and room temperature using their smartphones in communication with the overhead luminaires and Power over Ethernet (PoE). The feature set is no different from what was offered two decades ago with networked lighting systems, but now the communication relies on LiFi rather than wired network cables.

There are undoubtedly many more such products to come. However, they are still based on light as an intrinsic property of the light source. Something more is needed to implement the abstraction of “giving light.”

Intelligent Lighting Control

Lighting researchers have been looking at the possibility of intelligent lighting control in buildings for over a decade [15]. Often referred to as “ambient intelligence” and “auto-adaptive” lighting, the basic approach has been to use artificial intelligence (AI) techniques such as neural networks and fuzzy logic to learn a user’s lighting preferences by observing their behavior [16]. Most of the research has assumed a single or typical user, although some work has been done on reconciling different users’ preferences [17].

An advantage of intelligent lighting control is that by learning the user’s behavior, it can anticipate what sort of lighting is desired without the user having to interact with manual controls. This may work well for offices and residences where the system has the opportunity to learn the user’s behavior, but it does not work well otherwise. At best, the system must default to an anonymous “typical user” whose behavior is the average of many users. (Regardless, intelligent lighting controls typically result in energy savings.)

This is where the “networked society” concept has so much to offer. If an intelligent lighting control system can identify the user and access their public profile, it can determine the user’s desires and preferences and respond accordingly [18]. Even better, it can observe the user’s behavior and update their public profile if desired. Learning goes from a single isolated system to wherever the user encounters intelligent lighting control systems, often without the user even being aware of their presence.

Fig. 10 - US Patent App 20120184299

Fig. 10 – US Patent Application 2012/0184299

Public Places

The research to date has mostly focused on offices and residences, but it becomes even more interesting when public spaces are considered. Examples include retail stores and shopping malls, restaurants and hotel lobbies, bars and nightclubs, and even outdoor plazas and public parks at night. Normally, we never consider interacting with the lighting of such spaces. With public profiles however, we can easily give light to these environments in a socially acceptable manner.

As a prosaic example, consider walking through a park at night. Municipalities are already equipping pole-mounted walkway lighting with WiFi transceivers and occupancy sensors, which is all the technology that is needed for someone to turn on the lights using a smartphone [19]. It is a small step from here for the lighting system to recognize the person through their public profile and set the lights for a particular path.

Fig. 11 - Lighting in Public Places

Fig. 11 – Lighting in public places

More interesting examples arise when we consider light itself as a social medium. Color in particular can be used to announce the arrival of VIPs at a nightclub or to announce goals during a game at a sports bar. Light levels in restaurants can adapt to the preferences of patrons and their activities. The list goes on with possibilities that are limited only by the creativity of the lighting designers who develop the systems and the users who interact with them.

Language of Light

If anything, we may need to invent a new “language of light,” a non-verbal means of expressing not only our desires and preferences for lighting, but also of expressing our moods and social standing. More than likely, this will evolve by itself in the manner of cultural norms. We may however be surprised, if the prior introduction of personal lighting control is any indication. We may embrace the concept of giving light with the same aplomb as we have exhibited in adopting smartphones. It will become interwoven into the fabric of our lives, with our children wondering what light switches were for.

Just as it is difficult to explain a philosophy in five hundred words or less, it is difficult to explain the nuances of light as an intrinsic property of ourselves and the concept of “giving light” in a single discussion. It is all too easy to think of new technologies in term of what they replace, much as today’s LED lamps closely resemble A19 incandescent lamps. It is even more difficult here in that there are no new technologies involved; we already have the tools that we need.

All that is needed is for lighting designers to adopt a new philosophy and consider the possibilities.


  1. Zhong, M., et al. 2014 “On the Possible Use of Fire by Homo Erectus at Zhoukoudian, China.” Chinese Science Bulletin 59(3):335-343.
  2. Bower, R. G., et al. 2014. “A Medieval Universe: Mathematical Modeling of the 13th Century Universe of Robert Grossteste.” Available from
  3. Galasiu, A. D., G. R. Newsham, C. Suvagau, and D. M. Sander. 2007. “Energy Saving Lighting Control Systems for Open-Plan Offices: A Field Study,” Leukos 4(1):7-29.
  4. Clarke, A. C. 1962. Profiles of the Future: An Inquiry into the Limits of the Possible. New York: Harper and Row.
  5. Ericsson. 2013. Ericsson Mobility Report – On the Pulse of the Networked Society. Stockholm, Sweden: Ericsson.
  6. Anon. 2013. “Gartner Says the Internet of Things Installed Base Will Grow to 26 Billion Units by 2020.” Gartner, Inc.
  7. ISO/IEC FDIS 24730 – Real-Time Locating Systems (RTLS).
  8. Woodman, O., and R. Harle. 2008. “Pedestrian Localization for Indoor Environments,” Proc. Tenth International Conference on Ubiquitous Computing, pp. 114-123.
  9. See
  10. Dachs, M. R. 1975. US Patent 3,900,404. Optical Communication System.
  11. For example, Talking Lights LLC (
  12. Daukantus, P. 2014. “Optical Wireless Communications: The New Hot Spots?,” Optics & Photonics News 25(3):34-41.
  13. EuroShop Retail Trade Fair, February 2014 (Dusseldorf, Germany).
  14. Light + Building, March 2014. (Frankfurt, Germany).
  15. Guillemin, A., and N. Morel. 2001. “An Innovative Lighting Controller Integrated in a Self-Adaptive Building Control System,” Energy and Buildings 33:477-487.
  16. Vainio, A.-M., M. Valtonen, and J. Vanhala. 2008. “Proactive Fuzzy Control and Adaptation Methods for Smart Homes,” IEEE Intelligent Systems 23(2):42-49.
  17. Granderson, J., and A. Agogino. et al. 2006. “Intelligent Office Lighting: Demand-Responsive Conditioning and Increased User Satisfaction,” Leukos 2(3):185-198.
  18. Loveland, D., A. Vermeullen, and I. Ashdown. 2012. US Patent Application 2012/0184299, Systems and Methods for Managing Interaction with Controllable Lighting Networks.
  19. Badger, E. 2013. “The Streetlight of the Future Will Do So Much More Than Light Your Streets.” The Atlantic Cities, March 13, 2013.

Thoughts on Color Rendering

Ian Ashdown, P. Eng., FIES

Chief Scientist, Lighting Analysts Inc.

[ Please send comments to ]

UPDATE 14/10/06 – LightingEurope, the “Voice of the Lighting Industry,” has just published their LightingEurope Position Paper on Color Quality. To summarize:

1. LightingEurope supports to continue the use of the existing Color Fidelity metric CRI including eight reference colors.

2. LightingEurope supports to keep legal minimum requirements on CRI on the current level as defined in the EU Eco-design Regulation.

Lamp with a CRI of 90 or above, good. Lamp with a CRI of less than 80, bad. Is there anything else that lighting designers need to know about the Color Rendering Index (CRI) metric?

To be brutally honest … no. Despite all that has been written on the topic over the past decade, the importance of CRI to everyday lighting design today is minimal at best.

What is (or perhaps was) important is the history of color rendering metrics and the influence they had on fluorescent and LED lamp design. We can mostly ignore the issues of color rendering today precisely because of the CRI metric.

If you want to make senior citizens shudder, ask them what it was like to work in an office in the 1950s with fluorescent lighting. The linear fluorescent lamps of the time used calcium halophosphate phosphors that had a well-deserved reputation for making skin tones appear a sickly gray-green. Brightly-colored fabrics also looked disagreeably different from being viewed under daylight or incandescent lighting conditions.

Figure 1

FIG. 1 – Halophosphate lamp spectrum

Fluorescent lamp manufacturers could address this problem by varying the phosphor composition of their lamps. However, phosphors are expensive, and it is always difficult to convince consumers to pay more for products on the promise that they will “look better.” What was needed was an industry-standard metric.

Beginning in 1948, the Commission Internationale de l’Eclairage (CIE) began the quarter-century process of developing what is now the CIE General Colour Rendering Index, commonly referred to as the CRI metric (CIE 1995). The first version was published in 1965, and it was revised in 1974 to include the psychophysiological effects of chromatic adaptation.

An excellent description of the metric is available from Wikipedia (“color rendering index”), so there is no reason to repeat it here. All that needs to be said is its definition:

Color rendering: effect of an illuminant on the color appearance of objects by conscious or subconscious comparison with their color appearance under a reference illuminant.

and a reminder that the two illuminants (i.e., light sources) must have the same correlated color temperature (CCT).

This metric worked reasonably well for ranking linear fluorescent lamps from the era. Quartz halogen lamps had CRIs of nearly 100, while warm white fluorescent lamps typically had CRIs between 50 and 60. These lamps were particularly deficient in the red region of the spectrum (see Fig. 1), with warm white lamps having CRI R9 values as low as -111. (No, that is not a misprint; CRI values for specific test colors can be negative.)

Fluorescent lamp manufacturers could increase the red emission by mixing strontium and calcium halophosphates to create so-called “deluxe” phosphors. Lamps using these phosphors could achieve CRIs of approximately 90, but at the cost of roughly a one-third decrease in luminous efficacy (lumens output per electrical watt input).

This situation changed in the 1970s with two important discoveries:

  1. Lamps with improved luminous efficacy and very good color rendering properties could theoretically be achieved with three narrow-band (red, green and blue) lamp spectra (Thornton 1971); and
  2. The development of rare-earth phosphors for Thornton’s “triphosphor” lamps with CRIs of approximately 85 (Verstegen et al. 1974).

Figure 2

FIG. 2 – Rare-earth triphosphor lamp spectrum

By themselves, these two discoveries may or may not have had a significant impact on the manufacture of fluorescent lamps. Looking back, the lighting industry at the time had little to no interest in color rendering issues.

What the lamp manufacturers did have however was a metric to compare products with, and with this the opportunity for an effective marketing campaign. As a result, the otherwise-obscure CRI metric appeared in every manufacturer’s catalogs and sales literature, and it sold lamps.

With CRIs in the range of 85, triphosphor lamps have very good but not excellent color rendering properties. Lamp manufacturers therefore developed so-called “broadband” phosphors with four or five emission bands. With these, CRIs of 90 or so could be achieved.

Figure 3

FIG. 3 – Rare-earth broadband lamp spectrum

Marketing aside, did this really matter? For most commercial applications, the answer was probably no. In 1986, the CIE Guide on Indoor Lighting (CIE 1986) offered this helpful table:

CRI Ra Examples of Usage
> 90 Color matching, art galleries
80 – 90 Homes, restaurants, textile industry
60 – 80 Offices, schools, light industry
40 – 60 Heavy industry
20 – 40 Outdoors

Table 1 – CRI examples of usage

True, this list was likely influenced by the availability of halophosphate fluorescent lamps for indoor use, clear mercury vapor HID lamps for high-bay factory luminaires, and low-pressure sodium (LPS) lamps for roadway and area lighting. Still, it indicated how the CIE viewed its own metric at the time. CRI values were meant to be used as design guides rather than as precise numbers.

More tellingly, van Trigt (1999) presented a scholarly review of the CRI metric, in which he stated that “only a difference of some five points in the index is considered meaningful.”

The problem is that while the CRI metric Ra can be calculated from the measured lamp spectral power distribution (SPD) with arbitrary precision, it is nevertheless based on a mathematical model (the von Kries transformation) of psychophysiological behavior. Given this, it makes sense that the difference between CRI values of for example 88 and 90 is essentially meaningless.

In a sense, the CRI metric has served its purpose in promoting the development and commercialization of rare-earth lamp phosphors. With fluorescent lamp CRIs typically being in the range of 85 to 95 these days, lighting designers and consumers have little need to know anything other than “90 and above good, less than 80 bad.”

But then along came solid-state lighting …

The first commercially-produced SSL luminaire designed expressly for architectural applications was the TIR Systems Lexel, introduced at LightFair in April 2005 (Whitaker 2005). Based on a red-green-blue, high-flux LED die design, it generated white light whose color temperature could be varied from 3000 to 6500 kelvins.

Compared to the cool white LEDs with YAG phosphors and CRIs of approximately 75 available at the time, the white light produced by the Lexel was widely acclaimed by the trade show attendees, particularly for its color rendering properties.

Figure 4

FIG. 4 – LightFair 2005 – TIR Systems Lexel™

What the attendees did not know was that (ahem) the CRI Ra value varied from 25 at 3000K to 40 at 6500K (Speier and Salsbury 2006). By the standards of CIE 29.2, this was barely good enough for outdoor lighting only, along with clear MV and LPS lamps.

This seems odd, particularly when you compare the RGB LED lamp spectrum (FIG. 5) with that of a typical rare-earth triphosphor fluorescent lamp spectrum (FIG. 2). Based on this, you might guess that the CRI should be 85 to 90, not 25 to 40.

Figure 5

FIG. 5 – RGB LED lamp module spectrum

The answer lies in the dominant wavelengths of the emission peaks. Thornton (1974) calculated that the ideal dominant wavelengths (what he called “prime colors”) for triphosphor lamps were 450 nm (blue), 545 nm (green), and 610 nm (red). The dominant wavelengths of the Lexel – and indeed most color-changing RGB LED luminaires on the market today – were 465 nm, 525 nm, and 615 nm. If you were to change the green wavelength from 525 nm to 545 nm, the CRI would be 85 or so.

Unfortunately, the maximum dominant wavelength of reasonably efficient green InGaN LEDs is approximately 530 nm. The white light produced by color-changing RGB LED luminaires looks wonderful, but it is doomed have unacceptably low CRI values.

If anything, this is an example of the abject failure of the CRI metric to predict the color rendering properties of RGB LED luminaires. CIE Technical Committee 1-62 acknowledged this problem (CIE 2007), and recommended the development of a new and improved color rendering metric for all white light sources.

CIE Technical Committee 1-69 was therefore established in 2008 to “investigate new methods for assessing the colour rendition properties of white-light sources used for illumination, including solid-state light sources, with the goal of recommending new assessment procedures.” The committee investigated over a dozen proposals, but could only agree to bitterly disagree on any new metrics. As of this writing, the committee has yet to release its final report.

In response, the CIE recently established two new committees to further study the issue:

TC 1-90: Colour Fidelity Index. To evaluate available indices based on colour fidelity for assessing the colour quality of white- light sources with a goal of recommending a single colour fidelity index for industrial use.

TC 1-91: New Methods for Evaluating the Colour Quality of White-Light Sources. To evaluate available new methods for evaluating the colour quality of white-light sources with a goal of recommending methods for industrial use.

with reports due no earlier than 2015.

Despite numerous calls from the lighting industry for some clarity on color rendering metrics (e.g., Whitaker 2010, Colombo 2013), it is unlikely that the CIE will respond for at least a few more years.

Again however, does any of this really matter? The solid-state lighting industry effectively gave up waiting a number of years ago and began using CIE Special Colour Rendering Index R9 in addition to Ra to quantify the color rendering properties of white light sources (including both semiconductor and organic LEDs) for saturated red colors. While this combination of Ra and R9 is not a perfect solution, it is nonetheless a recognized industry standard, and it generally works (especially for marketing literature).

More to the point however is that the solid-state lighting industry has, like the fluorescent lamp industry before it, mostly outgrown the need for color rendering metrics. As long as the lamp module CRI is 80 or above – which is the case for most commercial products these days – there is little need to worry about CRI except for applications requiring critical color judgment.

With this, it is interesting to look at another industry that relies on the CRI metric: architectural glass. If you think about it, daylight illuminating interior spaces is spectrally filtered by glass windows and curtain walls. What is the CRI of daylight inside the building? If it is less than 80, it is in danger of being banned altogether by the US Environmental Protection Agency in accordance with the minimum CRI requirements of its ENERGY STAR program (EPA 2013).  (Just kidding … I think.)

It may surprise lighting designers to know that there is a European standard (BSI 2011) that specifies the calculation of indoor daylight CRI values, assuming a 6500 K daylight (CIE D65) illuminant. Architectural glass manufacturers publish CRI values for different thicknesses of their glass and window assemblies, and it can be calculated using the International Glazing Database ( and the freeware Optics 6 program from LBNL (

You might think that bronze glass for example would significantly affect the color of indoor daylight, but this is not the case. Taking one manufacturer (Pilkington Glass) as an example, most of their products have CRIs in the mid-90s, with the lowest (Ra of 77) being for their Solar-E Arctic Blue low-emissivity glass with a blue body tint.

More interesting perhaps is that most architectural glass products have similar spectral transmittance spectra (Gombos et al. 2008). They are so similar in fact that the CIE has defined two “indoor daylight illuminants” (ID50 and ID65) that correspond to CIE daylight illuminants D50 and D65 as seen through generic architectural glass (CIE 2009).

As you might expect from architectural glass, the slight greenish tint is due to absorption of red light. This increases the effective color temperature of the incident D50 and D65 daylight to 5100 and 6600 kelvins, respectively.

Figure 6

FIG. 6 – Indoor Daylight ID50 spectrum (5100K)

Figure 7

FIG. 7 – Indoor Daylight ID65 spectrum (6600K)

What makes this interesting for lighting designers is that architects and clients may obsess over the need for “high-CRI lighting” in their buildings. If the design involves both electric lighting and daylighting, one response could be to ask about the CRI of the building glass. If it is less than 90, there may be little point in worrying about the electric lighting.

Lamp with a CRI of 90 or above, good. Lamp with a CRI of less than 80, bad. This, plus the knowledge that “only a difference of some five points in the index is considered meaningful” is likely all you need to know (or talk) about CRI for most lighting design projects.


BSI. 2011. BS EN 410:2011, Glass in Building. Determination of Luminous and Solar Characteristics of Glazing. London, United Kingdom: British Standards Institution.

CIE. 1986. Guide on Interior Lighting. CIE 29:2-1986. Vienna, Austria: CIE Central Bureau.

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

CIE. 2007. Colour Rendering of White LED Light Sources, CIE 177:2007. Vienna, Austria: CIE Central Bureau.

CIE. 2009. Indoor Daylight Illuminants. CIE 184:2009. Vienna, Austria: CIE Central Bureau.

Colombo, E. 2013. “Opinion: Choose a Colour Rendering Metric Now,” Lighting Research and Technology 45:520.

EPA. 2013. ENERGY STAR Program Requirements for Integral LED Lamps. Washington, DC: Environmental Protection Agency.

Gombos, K., et al. 2008. “Proposal for an Indoor Daylight Illuminant,” Color Research & Application 34(1):18-25.

Speier, I., and M. Salsbury. 2006. “Color Temperature Tunable White Light LED System,” Proc.  6th International Conference on Solid State Lighting, SPIE Vol. 6337, 63371F.

Thornton, W. A. 1971. “Luminosity and Color Rendering Capability of White Light,” Journal of the Optical Society of America 61:1155-1163.

van Trigt, C. 1999. Color Rendering, a Reassessment. Color Research & Application 24(3):197-206.

Verstegen, J. M. P. J. 1974. “New Class of Phosphors for ‘Deluxe’ Fluorescent Lamps,” Lighting Research and Technology 6:31-32.

Whitaker, T. 2005. “TIR’s LEXEL Platform Provides Cost-Effective LED Lighting,” LEDs Magazine, July, pp. 19-21.

Whitaker, T. 2010. “Search Continues for Replacement for Color Rendering Index,” LEDs Magazine, July/August, p. 59.