# Measurement of Circadian Effectiveness in Lighting for Office Applications
[77], the CS value of white light sources can be approximated with sufficient accuracy from measurements of the photopic illuminance \(E_{\
u}\) in lux and the colorimetric \(2^{\circ}\) chromaticity coordinate \(z\) by using  
\[\text{CS}(z,E_{\
u})= \begin{cases}0.7-\frac{0.7}{1+0.016781\cdot(z\cdot E_{ \
u}^{1.509265})^{2.268904}}&\text{if $z>0.195$}\\ 0.7-\frac{0.7}{1+0.011376\cdot(z\cdot E_{\
u})^{1.109998}}&\text{if $z\leq 0.195$} \end{cases} . \tag{5}\]  
The approximation of Equation (5) is valid for white light sources in the range from 10 lx to 10,000 lx, with both \(z\) and \(E_{\
u}\) being captured vertically at eye level using standard measurement equipment. This, in particular, facilitates field measurements as the determination of CS according to [PERSON] et al. 's model definition of Equations (1)-(4) requires either an expensive spectroradiometer or at least a very specific measurement device, a so-called Daisymeter [78; 79], both of which must be considered as non-standard equipment in lighting practice. Compared to the original CS calculation, [PERSON] et al. 's approximation showed a maximal prediction error \(|\text{ACS}|_{\text{max}}\) of less than 0.058, as validated on a large database of measured absolute light spectra (\(n=7923\)) of various white light sources including LED lamps and luminaires, conventional incandescent and fluorescent emitters, and daylight (mixed-)illumination conditions. Even though the CS metric has successfully been applied in various laboratory and field studies to quantify lighting interventions and to explore the correlations between the lighting conditions and different choices of physiologically and clinically relevant outcome measures [80; 81; 82; 83; 84; 85], it must be stated that the underlying model still shows some fundamental limitations that, for the sake of completeness, should not remain unmentioned here. First of all, the model framework proposed by [PERSON] et al. pools two different sets of nocturnal melatonin suppression data collected under distinct experimental conditionswithout explicitly accounting and correcting for potential idiosyncrasies that can be expected due to the different timing, duration, and intensities of light exposure used by the respective study protocols and, thus, are likely to have a non-negligible impact on the model fit. Second, the resulting circadian light CL\({}_{\text{A}}\) definition and with it the CS metric both show a discontinuity at \(B_{\lambda}=0\). Despite the evidence provided from literature that the discontinuity approximates the experimentally observed spectral opponency effect that requires a subadditive component to be an essential feature of the corresponding spectral sensitivity function [45, 46, 56], it appears to be physiologically and biologically implausible that a minimal change in the lighting conditions may cause such a massive difference in the output. Third, the impact of pupil area is not considered by the CS definition. A systematic investigation of circadian phototransduction for different pupil sizes--independent of the luminous stimulus--would therefore be required to achieve a more comprehensive and adequate modeling [70]. Fourth, the current model is not capable of predicting effects of temporal dynamics, for example caused by intermittent light exposures (c.f., [86, 87]) or, more generally speaking, by dynamically changing lighting conditions. Fifth, the CS metric is solely based on melatonin suppression data collected during the nighttime hours. Even though it is constraint by the neuroanatomy, neurophysiology, and operating characteristics of the human circadian system [68] and, thus, capable of describing certain light-induced effects reasonably well, it does not address the wide range of potential biological responses that could be measured as a result of suitable light exposure (e.g., phase shifting, core body temperature, alertness, etc.) [69].