The Minamata Convention on Mercury, a program of the United Nations with delegates from at least 150 countries, is dedicated to improving global health by phasing out the use of mercury in manufacturing, banning new mercury mines, and limiting mercury emissions. Last month, 147 countries (out of a global total of 195) agreed to phase out florescent lighting globally and completely by 2027.
According to the appliance efficiency non-profit, CLASP, the phase out will, between 2027 and 2050:
Avoid 2.7 gigatons of CO2 emissions,
Eliminate 158 tons of mercury pollution, both from the light bulbs themselves and from avoided mercury emissions from coal-fired power plants,
Save US$1.13 trillion on electricity bills.
Early fluorescent lamps were being tested by Thomas Edison and Nicola Tesla in the 1890s, but it took several advances before they were ready for commercial use around the 1940s. According to the Department of Energy, by 1951 more light was being produced in the US by fluorescent lamps than by incandescent lamps. But, this always came at a cost. Fluorescent lamps work by passing an electric current through gaseous mercury, which emits ultraviolet light, which in turn is converted to visible light by the phosphors that line the fluorescent tube. When discarded (and eventually broken) the mercury would enter the environment, which is why the EPA began encouraging fluorescent lamp recycling and mercury recovery in the mid-2000s. Mercury is a neurotoxin, and symptoms of prolonged and/or acute exposures include:
Emotional changes (such as mood swings, irritability, nervousness, excessive shyness)
Neuromuscular changes (such as weakness, muscle atrophy, twitching)
Poor performance on tests of mental function
So, after around 70 years as the dominant commercial light source, and 10 years of decline after the introduction of LEDs, the fluorescent lamp has joined kerosene, whale oil, and others as an historical or legacy light source.
We’ve known for a while that the day was coming, and now it’s here. Effective yesterday retailers will no longer be permitted to sell most incandescent lamps (which includes halogen lamps) in the U.S. There are some exceptions for things like bug lights, but not many.
Replacement lamps for sale now must produce at least 45 lumens per watt, which is easily achieved by LEDs but impossible with incandescents.
The Department of Energy estimates that consumers will save about $3 billion per year. ( Of course, this assumes they buy quality lamps that don’t fail within a year, which is a real problem with off brand, and even some name brand, lamps.)
As part of the conversation around Diversity, Equity, Inclusion, and Respect there’s been a lot of discussion about color rendering and skin tone. I recently heard one speaker say something like, “We know that historical SPDs are racist.” I don’t think that’s accurate or helpful. Here’s why.
Since the development of the fluorescent lamp, the first priority for lamp manufacturers has been maximizing efficacy – getting the most lumens per watt. That’s still largely true today, even though LEDs are so efficient that there’s a lot of room for other considerations. An exclusive focus on efficacy inevitably results in poor color rendering, so the second priority has been acceptable (not maximized) color rendering. In other words, manufacturers have tried to find the right balance between efficacy and quality, but they emphasize efficacy.
When evaluating color rendering, manufacturers only look at the numbers. Whether it’s a calculation of CRI, Rf, Rg, or something else, it’s all done mathematically. There’s no interest in comparing the calculated values with empirical observations. The eight colors used to calculate CRI are a limited range that don’t include a representation of skin, as shown below.
The 99 colors used for TM-30 calculations span the color space and are not weighted toward any hue, tint, or value, as shown below.
So, there’s never been a focus on caucasian skin tone to the detriment of others because skin tone isn’t part of the evaluation.
Does that mean that all skin tones are rendered equitably? Honestly, we don’t know. On one hand, there’s no reason to think that we evaluate skin tone differently than we evaluate other surfaces. It’s reasonable to expect that a high fidelity source, for example, that give cars, apples, and kittens a good color appearance will do the same for human skin.
On the other hand, we don’t have good studies to confirm that. It may be that we hold different criteria for evaluating skin than we do for apples, resulting in the need for a separate skin tone rendering metric. Again, today we just don’t know.
In fact, the IES Color Committee is looking at this right now. We’ve started with an effort to gather as many studies as we can find – though there are very few that focus on skin rendering. The next step is to evaluate the literature to determine if additional study is needed, and what such a study (or studies) would require and evaluate. The hard part is funding the studies, and that would be the next step. Eventually, we’d have some solid science from high quality studies that would tell us if skin tone is evaluated differently than other surfaces, and if so what the calculation of a skin tone metric should include. The goal is to use the appropriate TM-30 measures (remember, there are 149 of them) to evaluate skin tone rendering, and to add a skin tone metric (maybe Rs) to TM-30, if needed.
If you’re interested in joining the task group looking at this, please contact me.
Recently, a corporate client asked me to specify only LED fixtures with a lifetime of 100,000 hours, and preferred fixtures with a life of 200,000 hours. I don’t know where they came up with these numbers, but my reply was that an L70 of 100,000 hours or more cannot be validated through standard testing procedures. Here’s why.
To begin with, LEDs themselves don’t experience catastrophic failure the way incandescent and fluorescent lamps do. The don’t stop making light, but their output declines over time. Today the generally accepted calculation of the life of an LED is called L70, which is the length of time before the light output has fallen to 70% of initial output.
The IES approved lifetime calculation method begins by collecting data using the procedure described in LM-80 (ANSI/IES LM-80 Measuring Maintenance of Light Output Characteristics of Solid-State Light Sources). Please note that LM-80 measures “LED packages, arrays, and modules” not fully fabricated fixtures, and there’s some dispute about whether or not testing bare modules is appropriate. However, it does permit module manufacturers to test once and derive a lifetime, rather than every fixture manufacturer testing every fixture with every module they want to offer, which would be incredibly burdensome and expensive.
LM-80 requires a minimum collection time of 6,000 hours (250 days) but sets no upper limit. If manufacturers want to use the data they’ve collected and project future performance they use the calculation procedure in TM-21 (ANSI/IES TM-21 Projecting Long-Term Luminous, Photon, and Radiant Flux Maintenance of LED Light Sources). Importantly, TM-21 only permits data to be projected to six times the LM-80 data collection time period. This is because of uncertainties involved with longer predictions (see PS-10-08 IES Position on LED Product Lifetime Prediction at https://www.ies.org/advocacy/position-statements/ps-10-18-ies-position-on-led-product-lifetime-prediction/). So, an L70 of 50,000 hours is based on at least 8,333 hours of LM-80 testing. That’s 347 days.
Thus, to say that an LED has an L70 100,000 hour life would require a data collection period of 16,667 hours (695 days), or 1,390 days (3.8 years of continuous testing) for a life of 200,000 hours. Today, no LED manufacturer conducts LM-80 tests for that extended period of time because the lifetime of a given LED product is too short. By the time you’ve finished a 4 year long test, the LED being tested is out of production and replaced by something new. In the future, when the LED industry has matured and we’re no longer seeing continuous improvements in efficacy, color rendering, etc., they may test for that long, but not now.
Where do these 100,000 hour and longer lifetimes come from? It seems that some manufacturers are using an internally generated prediction to get to these numbers. The thing is, we don’t know what’s involved in that prediction, which means we can’t validate it or compare it to any other prediction. We just have to take their word for it. With the LM-80/TM-21 procedure, on the other hand, we know that testing labs, regardless of who or where, are using the same procedure and their results should be consistent and repeatable. That allows us to reliably, confidently compare fixtures by any number of manufacturers.
In September at ArchLIGHT Summit, Tony Esposito and I gave a series of demonstrations on the spectral flexibility of LEDs and the possibilities they present with regard to color rendering. While there we spoke to Sam Koerbel on his LytePod podcast about the basics of the new measures introduced in Annex E, and discuss why TM-30’s multi-dimensional approach to quantifying color preference is superior to the old-standby in the industry: CRI. Our discussion is now available. Give it a listen.
The link below takes you to a recent LD+A Online article I wrote with Michael Royer and Jess Baker, It addresses some of the issues related to LED color names, and explains the ways colored LEDs are described, including dominant wavelength, peak wavelength, and chromaticity coordinates.
You may recall that in 2019 the Trump administration blocked a rule intended to phase out incandescent lamps and encourage a conversation to more energy efficient models, namely LEDs. If you don’t remember the New York Times and NPR both had articles, among many others.
Last week, the Consumer Federation of America and the National Consumer Law Center, along with 24 other groups across the country, urged the U.S. Department of Energy (DOE) Secretary Granholm to implement the efficiency standard for household lighting products mandated by Congress as soon as is practicable. They claim that “Each month of delay costs American consumers nearly $300 million in lost utility savings and results in another 800,000 tons of climate changing CO2 emissions over the lifetimes of the incandescent bulbs sold in that month.”
Yesterday an addendum to ANSI/ASHRAE/ICC/USGBC/IES Standard 189.1-2017 Standard for the Design of High-Performance Green Buildings was published. The addendum makes changes to Section 8.3.5, which covers lighting. One of the biggest changes is to add TM-30 color rendition criteria to the section on Indoor Lighting Quality. Here’s the relevant text:
18.104.22.168 Color Rendition. At least 95% of lighting power of nominally white lighting within each enclosed space shall be provided by luminaires that meet the following criteria at full light output in accordance with IES-TM-30, Annex E, P2 and F3: 1. Rf of at least 85 2. Rf,h1 of at least 85 3. Rg of at least 92 4. Rcs,h1 of at least -7% but no greater than +19%
Nominally white lighting is lighting that has chromaticity within the basic or extended nominal color correlated temperature (CCT) specifications of ANSI C78.377.
Where a lighting system is capable of changing its spectrum, it shall be capable of meeting the color rendition requirements within each nominal CCT of 2700 K, 3500 K, 4000 K, and 5000 K, as defined in ANSI C78.377, that the system is capable of delivering.
I hope that this is going to put more pressure on manufacturers to improve the color rendering of their luminaires as measured by TM-30, not CRI, and to provide TM-30 information on their cut sheets. If not, they’ll risk not being considered on projects that have TM-30 requirements.
Today’s post was going to be a reminder to take manufacturer provided education with a grain of salt. Last week I sat through a manufacturer’s presentation on color. There were some big errors and some that’s-not-quite-right errors that angered me. The information presented wasn’t hard to confirm, but whoever created the presentation didn’t so some of it was wrong. However, before I could start writing I received an email about a new color quality metric that was developed by Bridgelux. Here’s the scoop.
Last Thursday, May 14th, Bridgelux announced a new metric, Average Spectral Difference (ASD), which they claim quantifies the naturalness of a light source. The announcement is based on this white paper by Bridgelux. The white paper asserts that since we evolved under fire light and day light, human-centric lighting should use spectra that mimic these “natural” sources. Bridgelux says that, “ASD provides an objective measurement of how closely a light source matches natural light over the visible spectrum, averaging the differences of the spectral peaks and valleys between a light source and a standardized natural light source of the same CCT.”
Basically, ASD is a measurement of the difference between a “natural” spectrum and that of an electric light source. It is expressed as a percentage, with lower percentages equaling a closer match to the reference source and higher percentages equaling a larger difference between the two.
My first thought was, “Oh, it’s CRI – Natural Edition” but in some ways it’s even worse. For starters, while Bridgelux presents a definition of “natural” light that is based on the illuminants we use as references for color fidelity calculations, there is no accepted definition of “naturalness” in the lighting industry, or most other industries for that matter. Obviously, a metric for something that has no industry-wide definition is of questionable value. The white paper says, “The reference source used by Bridgelux is the blackbody curve (BBC) for light sources of 4000K and below, and the daylight spectrum (i.e. standard illuminants such as D50, D57, and D65) for light sources of 5000K and above.” (Yes, there’s an obvious typo there because they’ve left a gap between 4000 K and 5000 K.) Second, like CRI it presents a single number with no additional information about where in the spectrum the differences occur, or if they are increases or decreases relative to the reference light source. Third, as a measurement of spectral difference alone, it disregards the fundamentals of human vision, including the principle of univariance and how perception changes with intensity, among other things.
I emailed a few colleagues on the IES Color Committee and found that they were already examining ASD. Some of the comments that came back were, “This is just a refresh of a spectral bands method. It says little about color rendering” and “This is very similar to the Film industry’s SSI developed by the Academy. It also suffers from the same problem. If the result isn’t 0% (or 100%) then it tells you nothing about where the differences are. Thus, it tells you nothing about whether two light sources will work together.”
Michael Royer at PNNL went further by looking at ASD with the sets of data in TM-30 Annex F that were used to develop the TM-30 Annex E recommendations. Here’s what he had to say. (You may have to right click and open the graphs in a new tab to see them clearly.)
First, spectral similarity metrics are not new at all—they predated CRI (e.g., Bouma spectral bands method from 1940s). For some reason they gained popularity again in the last decade or so. Here are some other examples:
B. H. Crawford. 1959. Measurement of Color Rendering Tolerances J. Opt. Soc. Am. 49, 1147-1156
Crawford, B. H. 1963. Colour-Rendering Tolerances and the Colour-Rendering Properties of Light Sources. Transactions of the Illuminating Engineering Society, 28: 50–65.
Kirkpatrick, D. 2004. Is solid state the future of lighting?” Proc. SPIE 5187, Third International Conference on Solid State Lighting.
Acosta I, Leon J, Bustamante P. 2018. Daylight spectrum index: a new metric to assess the affinity of light sources with daylighting. Energies 11 2545
Spectral similarity measures, like ASD, don’t relate to perceived naturalness or preference at all. They’re more closely correlated with color fidelity (e.g., Rf) but perform even worse in terms of correlation with perceived qualities because they don’t account for how the visual system works (they might have more use for understanding cameras, as used by SMTPE with SSI, linked above). I guess people just assume that a Plankian/Daylight spectrum is ideal. While smooth SPDs have advantages, Planckian/Daylight SPDs aren’t perceived as more natural or more preferred in typical architectural lighting scenarios. This has been shown over and over in experiments, where it’s become quite evident that certain deviations from Planckian are preferred/viewed more natural than others.
Here’s the correlation between ASD and rated naturalness/normalness, preference, and Rf for the three datasets used to develop TM-30 Annex E:
If you’re not up on your statistics, r2 is a measurement of how well data fits to a prediction or to the data average. 1.0 is a perfect fit. Generally, 0.7 or above indicate a strong statistical correlation, and values less than 0.3 indicate no relationship.
PNNL (combination of three studies):
Overall, it’s clear that ASD isn’t a tool for characterizing perceived naturalness (or preference) over a wide range of SPDs, and it probably has limited other uses. While spectral smoothness (as exemplified by the reference illuminants in ASD) is sometimes a useful goal, there are other metrics more rooted in human vision to better asses this characteristic. It’s a shame that ASD and the accompanying message will likely lead to confusion, especially when there’s enough to learn about color rendition already.
This is a good example of why it’s important to rely on metrics that have been vetted through a standardization process and to always be skeptical of marketing material.
So there you are. Take manufacturer’s education with a grain of salt. The same is true of their internally developed metrics. I’m not saying that they are intentionally deceiving anyone. but their goal is sales, not education. As Mike points out, this is why metrics need to go through a vetting process before we can use on them with confidence.
By the way, although I’ve mentioned the IES Color Committee and quoted a few of its members, this post doesn’t represent the opinions of the committee or of the IES.