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LEUKOS: The Journal of the Illuminating Engineering Society of North America Publication details, including instructions for authors and subscription information: http://ies.tandfonline.com/loi/ulks20 A Critical Investigation of Common Lighting Design Metrics for Predicting Human Visual Comfort in Offices with Daylight Kevin Van Den Wymelenberga & Mehlika Inanicib a University of Idaho Integrated Design Lab, Boise, Idaho, USA b University of Washington, Architecture, Seattle, Washington, USA Published online: 20 Feb 2014.
To cite this article: Kevin Van Den Wymelenberg & Mehlika Inanici (2014) A Critical Investigation of Common Lighting Design Metrics for Predicting Human Visual Comfort in Offices with Daylight, LEUKOS: The Journal of the Illuminating Engineering Society of North America, 10:3, 145-164 To link to this article: http://dx.doi.org/10.1080/15502724.2014.881720
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A Critical Investigation of Common Lighting Design Metrics for Predicting Human Visual Comfort in Offices with Daylight
Kevin Van Den Wymelenberg1 and ABSTRACT Existing visual comfort metrics are reviewed and critiqued based 2 Mehlika Inanici upon their ability to explain the variability in human subjective responses in a daylit 1 University of Idaho Integrated private office laboratory environment. Participants (n = 48) evaluated visual comfort Design Lab, Boise, Idaho, USA 2University of Washington, and preference factors, totaling 1488 discreet appraisals, and luminance-based met- Architecture, Seattle, rics were captured with high dynamic range images and illuminance-based metrics Washington, USA were recorded. Vertical illuminance outperformed all commonly referenced visual comfort metrics including horizontal illuminance, IES luminance ratios, daylight glare probability (DGP), and daylight glare index (DGI). The bounded border- line between comfort and discomfort is introduced, and preliminary visual comfort design criteria are proposed for several existing metrics. Fundamental limitations of glare indices are documented, and the implications of inconsistent application of luminance ratio calculation methods are quantified. Future research is detailed.
KEYWORDS daylight glare, daylight metrics, luminance ratio, vertical illuminance, visual comfort
1. INTRODUCTION It is generally accepted that daylight and views help to create healthy, comfortable, and productive work environments for users and therefore should be included in Downloaded by [University of Washington Libraries] at 08:59 20 February 2014 contemporary office spaces. Equally understood is the need to minimize discomfort glare, disability glare, and veiling glare for occupants in spaces with daylight. In cur- Received 23 September 2013, revised rent practice, design guidance to support visual comfort in daylit spaces has revolved 6 January 2014, accepted 7 January primarily around horizontal illumination, simple luminance ratios, and, in advanced 2014. Address correspondence to Kevin Van applications, absolute luminance thresholds or glare indices. The application of Den Wymelenberg, University of luminance-based techniques remains primarily within the research community and Idaho Integrated Design Lab, they have gained little traction among design practitioners. Both illuminance- and Architecture, 306 S. 6th Street, Boise, ID 83702, USA. E-mail: luminance-based methods suffer from an established lack of confidence or con- [email protected] sensus by the research and design communities regarding what metrics should be Color versions of one or more of implemented and what criteria are recommended. This is primarily because there the figures in this article can be found online at www.tandfonline. is presently inadequate human visual comfort research to support consensus-based com/ulks. design recommendations.
145 This article presents original research from a 6-month bounds of human acceptance and preference in spaces repeated-measures experimental design in which 48 par- with daylight, it stands to reason that luminance-based ticipants assessed their visual comfort in a private daylit metrics will more closely correlate with subjective accep- office. It begins with a brief review of common visual tance and preference measures than illuminance because comfort metrics (both illuminance and luminance based) luminance more closely relates to human perception of and recommended criteria. It identifies the strengths and brightness (see discussion in Cuttle [2004]). This section limitations of these metrics and recommends revised mea- reviews luminance ratios, absolute luminance values, and surement techniques and design criteria as relevant. Finally, glare indices that have been used to characterize visual it establishes the need for future research to develop a new preference and acceptance of the luminous environment. suite of luminance-based analysis metrics. 1.2.1. Luminance ratios 1.1. Illuminance-Based Metrics Current recommendations by the IES [DiLaura and others 2011, p. 12.20] list the maximum luminance ratios in Due to its ease of use and low cost to measure, horizon- daylight settings as “20:1 between daylight-media and tal illumination is the most widely applied architectural daylight-media-adjacent-surfaces.” No specific references lighting design metric. However, even under electric light are offered for the IES’s 20:1 recommendation, and other sources only, illuminance preference varies greatly, from ratios cite the previous handbook [Rea 2000], which also 100 to 800 lux [Boyce and others 2006; Newsham and lacks substantial reference to original research. Few previ- Veitch 2001; Veitch and Newsham 2000], and has a mean ous studies describing preferred luminance ratios in set- value between 400 and 500 lux. It has been reported that tings with daylight are available. Halonen and Lehtovaara the choice of any fixed horizontal illumination value will [1995] reported that under a wide range of daylight con- only be preferred by at most 55% of the users [Boyce et al. ditions, participants (n = 20) preferred average luminance 2006]. Few studies have reported user preference for illu- ratios of a white paper-based task and a light-colored back mination under daylight conditions alone. One found that wall opposite the window ranging from approximately 300 lux of daylight was preferred (n = 20) [Laurentin 1:2.25–10 with an average of approximately 1:5. Note that and others 2000] and another study, conducted primarily ratios using window luminance values were not reported. during sunny winter days, found a wide range of pre- Sutter and others [2006] found that a space with daylight ferred desktop daylight illuminance and a preferred mean was comfortable for users with luminance ratios of 1:6:20 of 3623 lux (n = 18) [Van Den Wymelenberg and others (task: adjacent: remote), twice as extreme as those tradi- 2010]. tionally recommend by the IES (1:3:10) but in line with the new recommendation for daylight media (1:20). The 1.2. Luminance-Based Metrics authors also found that users tolerated up to 1:50 as long as it was restricted to relatively small areas, comprising less As noted previously, human acceptance and preference than 5% of the field of view. vary widely under primarily electrically illuminated spaces. Due to the complexities related to daylight in buildings (for example, variability with time of day, time of year, 1.2.2. Glare indices Downloaded by [University of Washington Libraries] at 08:59 20 February 2014 sky condition, view quantity, view quality, extremes of Glare indices have been used to evaluate visual com- brightness values, discomfort glare, et cetera) the bounds fort in the luminous environment. Two recent literature of human preference are wider in spaces with daylight. reviews provide historical overviews of the multitude of Several attributes provide moderating effects to subjective glare indices [Eble-Hankins and Waters 2004; Osterhaus preference assessments in daylit spaces. For example, recent 2005]. However, there are only two glare indices intended research [Tuaycharoen 2011; Tuaycharoen and Tregenza for use in daylit environments. The first, the daylight glare 2005, 2007] has identified and begun to quantify the mod- index (DGI) was developed by Hopkinson and his col- erating effects that the quality of a view has on human leagues [Hopkinson 1972; Hopkinson and Collins 1963] assessment of glare from daylight (brightness accompa- using large-area electric light glare sources and updated by nied by a better view is rated as less glaring). Though it Chauvel and others [1982] in a setting with daylight but is unlikely that any single measurement type (illuminance, without sunlight or reflected sunlight. The second, day- luminance, view quality) will adequately describe the light glare probability (DGP), was developed by Wienold
146 K. Van Den Wymelenberg and M. Inanici and Christoffersen [2006] as an attempt to improve upon 2. METHODOLOGY the DGI. Laboratory research included daylong, longitudinal (one The DGP tries to define “the probability that a person day in summer and one day in fall), repeated-measure is disturbed instead of the glare magnitude” [Wienold and experiments with 48 participants (45 repeated) in a mock Christoffersen 2006, p. 753]. Wienold and Christoffersen private office space in Boise, Idaho. Each participant spent [2006] found that the DGP outperformed the DGI, but one working day, during two different times of the year, this must be qualified in several ways. First, the DGP in the mock office environment. They assessed a range of equation was created to provide the best fit to the given visual conditions from very bright to very dim, under high data, whereas the DGI was developed to fit a different data sun angles to low sun angles (time of day and year), under set. Second, the DGP is a binary measure (comfortable or naturally occurring sky conditions, and experienced mul- uncomfortable) rather than a four-point linear scale (such tiple prescribed and user-defined light modifying elements as is the case with the DGI). Third, the DGP was devel- (blind height, blind tilt, ambient electric lighting levels). oped using only clear stable skies. Fourth, this correlational This laboratory research built upon the methods employed fit was conducted on mean data from several bins along the in two pilot studies [Newsham and others 2008; Van Den range of the DGP rather than from continuous data. And Wymelenberg and others 2010]. Extensive illuminance fifth, other researchers [Painter and others 2009; Van Den and luminance data were collected as shown in Fig. 1. Wymelenberg and others 2010] have demonstrated limita- Nearly 1500 high dynamic range (HDR) data sets were tions to the DGP model when tested on data sets generated analyzed encompassing 16 experimental conditions across with other similar spaces. Still, the DGP has been shown 93 participant-days. to outperform the DGI [Van Den Wymelenberg and oth- ers 2010] in other tests. The basic equation for the DGP 2.1. Research Setting includes vertical illuminance at the eye (Ev) as a primary input in addition to the common glare equation vari- Human factors tests were conducted using two identical ables (luminance of the glare sources and the background rooms (Figs. 1 and 2) in Boise, Idaho (43◦ N and 116◦ W). and the size, location, and angular displacement of glare Each room measured 4.4 m × 3.7 m, 16.3 m2 (14 ft sources). 4in.× 12 ft 3 in., 176 ft2) and had a southwest-facing Downloaded by [University of Washington Libraries] at 08:59 20 February 2014
Fig. 1 Research setting, equipment room (left); participant room (right); with data collection equipment annotated.
Common Lighting Design Metrics 147 Fig. 2 Research setting, equipment room, participant perspective (left); daylight guidance blinds (right).
window (35.5◦ west of south). One room was for the the University of Idaho Boise general community and research participant (participant room) and the other room alumni by program administrators at the University of hosted the lighting data collection instrumentation (equip- Idaho.Participants chose to be compensated in one of two ment room) to ensure data accuracy and to provide a ways. The participant either elected to be entered into a natural working environment for participants. raffle with a chance to win a prize worth $500 or elected Each room had a double-pane window (0.64 visible to receive a $75 gift card each day. light transmission) centered on the southwest wall with aluminum frames that extended from the floor to 2.7 m high and measured 2.3 m wide. A daylight guidance 2.4. Procedures semiperforated motorized louver blind was mounted inside The experiment was conducted between June 29 and the window frame (Fig. 2, right). The automated blind December 19, 2011, from 8:30 AM to 4:00 PM for a controls were disabled and the participants controlled the total of 93 participant-days. As expected, sky conditions motorized blinds manually from the computer interface or varied throughout this period, but sunny days were most with a remote control. A single T5HO dimmable recessed prevalent representing 94% of hours in the first round direct electric light source (30–800 lux at desktop) was (June 29–September 20) and 71% of the hours in the located approximately in the center of the room and was second round (September 21–December 19). A typical controlled with a remote control. Reflectances were as fol- participant’s day is outlined in Table 1. Upon arrival, par- lows: white walls (73.7%), ceiling (80.8%), floor (10.8%) ticipants reviewed and signed a consent form and were desk (39.3%), and back of blinds when closed (20.3%). given basic training about how to operate the blinds and A 0.56-m (diagonal screen dimension) LCD computer electric lights and how to complete the questionnaire and monitor (max screen luminance of 130 cd/m2 measured at
Downloaded by [University of Washington Libraries] at 08:59 20 February 2014 objective performance tasks. To avoid sequence bias, the a distance of 1 m) and paper document holder were located order that each group of conditions was presented was on the desk. changed monthly. A total of 16 conditions are outlined in Table 1 (annotated as C1–C16). 2.3. Participants A total of 48 people (24 female, 24 male) participated 2.5. Questionnaire Items in the first round of the study and 45 (22 female, 23 male) repeated participation in the second round Each of the 16 lighting conditions included a questionnaire of the study. Participants were recruited to create three module. First, the participant was asked to confirm that age-balanced (18–29 years, 30–49 years, 50–70 years) he or she had created the lighting condition according to and gender-balanced groups. Participants were identified the given description. Then the following questions were using a recruitment e-mail sent to individuals within asked:
148 K. Van Den Wymelenberg and M. Inanici TABLE 1 Typical participant-day
Condition order was changed monthly to avoid bias
Time (min) Activity Description
Put blinds down and rotated closed and electric lights on at full power to begin each participant-day 9:50 (50) Conditions 1–3 by participant C1—Participant directed to create MP daylight environment C2—Participant directed to improve environment by adding electric light C3—Participant directed to worsen environment by adjusting electric light 10:40 (10) Morning break Put blinds all the way up and turn the electric lights off 10:50 (50) Conditions 4–6 by participant C4—Participant directed to create JU glare daylight environment C5—Can participant improve environment adding electric light? C6—Participant directed to just correct the glare problem by adjusting blinds 11:40 (20) Condition 7 by participant C7—Participant directed to create MP integrated lighting environment 12:00 (60) Lunch break Put blinds all the way up and turn the electric lights off 13:00 (50) Conditions 8–10 by researcher with C8—Participant directed to create MP daylighting environment participant confirmation C9—Researcher sets an intentionally dark scene (blinds all the way down and no electric lights) C10—Participant directed to create JU glare scene from daylight alone 13:50 (20) Afternoon break Put blinds all the way up and turn the electric lights off 14:10 (50) Conditions 11–13 by researcher C11—Participant directed to create and maintain their MP with participant confirmation integrated lighting environment C12—Leaving electric light as previous, researcher closes blinds all the way C13—Leaving electric light as previous, participant directed to open blinds just enough to create a JU glare scene Put blinds all the way up and turn the electric lights off 15:00 (50) Conditions 14–16 by researcher C14—Participant directed to create and maintain their MP with participant confirmation integrated lighting environment C15—Leaving blinds as pervious, participant directed to dim electric light until just too dim (or until off) C16—Leaving blinds as previous, participant directed to increase electric lights until just too bright (or until on full) 15:50 (10) Debrief/dismiss
Rate the following statements using the scale provided 6. The computer screen is legible and does not have (a 7-point Likert-type scale, 7 = very strongly agree,6= reflections. (QU6) Downloaded by [University of Washington Libraries] at 08:59 20 February 2014 strongly agree,5= agree,4= neither agree nor disagree,3= 7. The lighting is distributed well. (QU7) disagree,2= strongly disagree,1= very strongly disagree): Rate the following using the semantic differential scale 1. This is a visually comfortable environment for office provided (from too bright to too dim): work. (QU1) 2. I am pleased with the visual appearance of the office. 1. When I look up from my desk the scene I see in front (QU2) of me seems: (front_scene) 3. I like the vertical surface brightness. (QU3) 2. When I look to my left the scene that I see seems: 4. I am satisfied with the amount of light for computer (left_scene) work. (QU4) 3. When I look to my right the scene that I see seems: 5. I am satisfied with the amount of light for paper-based (right_scene) reading work. (QU5) 4. I find the ceiling to be: (ceiling)
Common Lighting Design Metrics 149 2.6. Analysis Methods to luminance measures. “C8” refers to condition eight (that is, participant is directed to create an MP daylight environ- All data were collected in discrete files, and scripts were ment during the afternoon) and “C10” refers to condition used to conduct data cleaning and organization. The val- 10 (that is, participant is directed to create a JU daylight idated HDR capture procedure has been shown to result environment in the afternoon). Therefore, it follows that in less than 10% error in scene luminance values [Inanici “C8C10” refers to analysis of data from conditions 8 and 2006]. In addition to basic descriptive statistics, inferen- 10 together (that is, MP compared to JU daylight envi- tial statistical methods including one-way and two-way, ronments captured during the afternoon). “QU1” refers to paired and unpaired t tests (95% confidence interval), and question 1. Pearson correlations were employed. Several regions of interest, or masks, were studied in detail. “Mask 01” represents the full 180◦field of view 3. RESULTS (Fig. 3, right). “Mask 03” references a circular task zone encompassing the keyboard and monitor (Fig. 3,left),and For the sake of brevity, several abbreviations are used a multiplier of the mean luminance value of this mask was throughout the rest of the article. MP refers to “most used to identify the glare sources in order to calculate the preferred” scenes, and JU refers to “just uncomfortable” DGP metric within the whole scene. “Mask 08” references scenes. “E” refers to illuminance measures and “L” refers the masked region of the window (Fig. 4,left).“COV”
Fig. 3 Mask 03 encompasses a circular task about the computer monitor and keyboard (left); Mask 01 encompasses the entire 180◦ × 180◦ scene (right). Downloaded by [University of Washington Libraries] at 08:59 20 February 2014
Fig. 4 Mask 08 encompasses the entire window “daylight source” (left), Mask 03 encompasses a circular task about the computer monitor and keyboard (right).
150 K. Van Den Wymelenberg and M. Inanici refers to coefficient of variation or the standard deviation Table 2 and Table 3 indicate the relative ability of metrics divided by the mean. to discern between MP and JU conditions.
3.1. Variability 3.2. Correlation Matrix Tables 2 and 3 illustrate the variability of selected met- Table 4 presents squared correlation coefficients, using rics across participants for comfortable daylit scenes and the Pearson pairwise method, between selected lighting uncomfortable daylit scenes, respectively. Not surprisingly, metrics and questionnaire items for conditions C1, C2, the participant variability within and between MP and JU C4, C6, C7, C8, C10, C11, C13, and C14 (hereafter conditions is high and there is substantial overlap between the composite data set). Note that some conditions (C3, conditions (Figs. 5–7). That said, comparisons between C5, C9, C12, C15, C16) were ignored in these analyses
TABLE 2 MP daylit scenes (C1C8) with score of 5 or higher on QU1 (that is, participant directed to create MP daylighting environment while he or she rated score of 5 and higher on “This is a visually comfortable environment for office work.”)
MP daylit scenes (C1C8) with score of 5 or higher on QU1
Min. 1st Quartile Median Mean 3rd Quartile Max. σ
Illuminance E horizontal at desktop (lux) 52 419 950 1119 1387 4910 994 E at ceiling (lux) 33 345 759 1026 1526 3013 787 E vertical at camera (lux) 55 352 665 708 976 2602 436 Luminance Mean L scene (cd/m2) 35 142 241 268 358 805 164 Standard deviation of scene L (cd/m2) 57 370 598 696 953 4588 530 COV of scene luminance 1.23 2.13 2.57 2.58 2.89 5.83 0.76 98th percentile of scene L (cd/m2) 195 1050 2056 2249 3080 8992 1534 % Scene exceeding 2000 cd/m2 0.0% 0.7% 2.1% 2.1% 3.1% 6.5% 1.6% Mean L window: Mean L task 1.60 10.38 15.50 15.88 20.45 56.84 8.40 DGI (findglare default) 1.10 7.43 11.12 10.19 12.60 16.38 3.40 DGP (5∗ Mean L task) 16.5% 19.7% 21.4% 21.4% 23.0% 34.6% 2.7% Mean L window (cd/m2) 74 577 1001 1068 1473 3618 659
TABLE 3 All JU scenes (C4C5C10C13) with score of 3 or lower on QU1 (that is, participant directed to create JU glare daylight environment while he or she scored 3 or lower on “This is a visually comfortable environment for office work.”)
All JU scenes (C4C5C10C13) with score of 3 or lower on QU1
Min. 1st Quartile Median Mean 3rd Quartile Max. σ
Illuminance E horizontal at desktop (lux) 418 1435 2004 4288 2649 40,920 7142 Downloaded by [University of Washington Libraries] at 08:59 20 February 2014 E at ceiling (lux) 115 1295 1688 1904 2385 3799 815 E vertical at camera (lux) 51 1061 1402 1467 1755 4816 626
Luminance Mean L scene (cd/m2) 35 385 515 535 640 1568 233 Standard deviation of scene L (cd/m2) 93 976 1451 1587 2040 5278 867 COV of scene luminance 1.39 2.21 2.85 2.93 3.42 8.37 0.90 98th Percentile of scene L (cd/m2) 463 3392 4272 4426 5540 14,530 1893 % Scene exceeding 2000 cd/m2 0.0% 3.7% 4.5% 4.6% 5.2% 15.0% 2.1% Mean L window: Mean L task 3.62 18.26 23.59 22.87 27.32 51.82 7.40 DGI (findglare default) 0.00 10.92 12.75 12.18 14.20 18.39 2.97 DGP (5∗ mean L task) 16.8% 23.4% 25.4% 25.5% 27.2% 38.7% 3.4% Mean L window (cd/m2) 162 1702 2171 2123 2511 6128 803
Common Lighting Design Metrics 151 Desktop Illuminance Variability per Participant 10000 S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S
9000
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7000
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4000
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0
Participants Just Uncomfortable Most Preferred
Fig. 5 Variability in desktop illuminance in MP (red/left) and JU (blue/right) conditions by participant.
Window:Task Ratio Variability per Participant S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S 60
50
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Participants Just Uncomfortable Most Preferred
Fig. 6 Variability in the mean luminance ratio of window (Mask 08 Mean L): circular task (Mask 03 Mean L) for MP (red/left) and JU (blue/right) conditions by participant.
DGP Variability per Participant S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S 0.45
0.40
0.35
0.30 DGP
0.25
Downloaded by [University of Washington Libraries] at 08:59 20 February 2014 0.20
Participants Just Uncomfortable Most Preferred
Fig. 7 Variability in DGP (based upon 5∗ Mean L of task) in MP (red/left) and JU (blue/right) conditions by participant.
because these conditions had unique characteristics meant responses to QU4. Results from seven Likert items, four for other purposes. The designation of “filtered” was semantic differential (too dim–too bright) items, and appended to the condition string (for example, compos- the overall scene preference semantic differential (least ite_data_set_filtered) in cases where uncomfortable data preferred–most preferred; coded “light_in_scene”) item were filtered out of the MP data set and comfortable are summarized for selected metrics. These results are data were filtered out of the JU data set based upon the
152 K. Van Den Wymelenberg and M. Inanici Downloaded by [University of Washington Libraries] at 08:59 20 February 2014
TABLE 4 Selected r2 values ordered by “QU 4” (using “composite_data_set_filtered”)
Rank Common metrics of QU4 Likert_ front_ left_ right_ light_in_ QU4 interest (by QU4) QU1 QU2 QU3 Ranked QU5 QU6 QU7 all scene scene scene ceiling scene
1 E vertical at top of 0.239 0.200 0.150 0.260 0.118 0.283 0.213 0.250 0.104 0.131 0.298 0.091 0.049
monitor (Ev-monitor) 2 E vertical at camera 0.207 0.170 0.121 0.235 0.097 0.263 0.181 0.216 0.085 0.103 0.267 0.118 0.010
(Ev-eye) 3 Mean L scene 0.200 0.172 0.115 0.223 0.097 0.243 0.168 0.207 0.085 0.104 0.278 0.095 0.065 4 Standard deviation of 0.202 0.179 0.113 0.219 0.104 0.223 0.174 0.207 0.059 0.059 0.276 0.089 0.063 scene L 5 E at ceiling 0.182 0.167 0.117 0.216 0.118 0.251 0.169 0.206 0.097 0.143 0.221 0.090 0.000 6 DGP (5∗ mean L task) 0.198 0.163 0.108 0.216 0.093 0.226 0.167 0.199 0.077 0.086 0.281 0.070 0.057 ∗
153 7 DGP (5 mean L scene) 0.183 0.151 0.101 0.201 0.088 0.211 0.156 0.186 0.075 0.086 0.278 0.074 0.079 8 % Scene exceeding 0.152 0.120 0.082 0.162 0.060 0.189 0.113 0.148 0.090 0.088 0.214 0.076 0.055 2000 cd/m2 9 Irradiance vertical at 0.107 0.100 0.067 0.132 0.061 0.145 0.106 0.122 0.038 0.070 0.149 0.051 0.008 SW exterior (adj.) 10 E horizontal desktop 0.107 0.113 0.086 0.118 0.128 0.114 0.135 0.137 0.010 0.020 0.113 0.018 0.001 11 Mean L window: Mean 0.091 0.058 0.040 0.096 0.032 0.068 0.050 0.074 0.061 0.028 0.145 0.016 0.005 Ltask 12 E horizontal at top of 0.079 0.075 0.049 0.087 0.043 0.119 0.075 0.089 0.046 0.052 0.096 0.074 0.049 monitor 13 Mean L task: Mean L 0.058 0.042 0.039 0.076 0.014 0.085 0.045 0.059 0.047 0.041 0.081 0.028 0.000 scene 14 DGI (findglare default) 0.046 0.028 0.019 0.043 0.015 0.032 0.024 0.035 0.024 0.005 0.058 0.001 0.005 15 COV of scene luminance 0.051 0.050 0.030 0.038 0.032 0.031 0.050 0.048 0.000 0.000 0.043 0.017 0.004
Shading indicates r2 values in three categories: <0.1, >0.1 but <0.2, and >0.2. presented in ranked order by the item QU4. The metrics’
ranks with regard to QU4 is in the leftmost column of each table, and the abbreviated metric names are in the next col- umn to the right. Additionally, bolded text indicates that the metric’s r2 value was the highest ranked for a specific question. Pink fill indicates that the metric’s r2 value was greater than or equal to 0.20 and yellow fill indicates the metric’s r2 value was greater than or equal to 0.10 but less than 0.20. The following sections present results for several com- monly cited metrics. Note that none of the graphs used the “filtered” data; instead, they used the entire data set for the specified condition groups, C8 with C10 (hereafter, C8C10), and the composite data set. First, metrics were investigated for their ability to con- sistently differentiate between MP and JU scenes within subjects using results from C8C10. This pair of conditions was selected for two reasons. Firstly, C8 and C10 occurred within 30 min of one another, thus making these condi- tions ideal for analyses between MP and JU daylight scenes within subjects because they excluded most temporal con- founding factors (for example, variable sky conditions,
sun position). Secondly, C8 and C10 always occurred in Fig. 8 Ev measured in the participants’ viewing direction at the the afternoon, thus increasing the potential of creating top of monitor. JU scenes for C10 given the southwest-facing aperture. The participants were instructed to create their MP scene differentiates C10 (MP) from C8 (JU) scenes for most for C8 and a JU scene for C10 using blind controls to cases, especially where C10 Ev >1600 lux. There are sev- adjust daylight levels and distribution and were instructed eral cases where C10 scenes had lower Ev values than to leave the electric light off. Next, each metric was plot- other participant-day C8 cases. The single regression statis- ted using C8C10 data, ordered by the metric result, with tics can be seen in Table 5. Finally, Fig. 10 takes the data points color-coded by the subject response to QU1. C8C10 data, organizes it by the metric result, and color These plots are useful in discerning the most preferred and codes it by the response to QU1. This graphic reveals least preferred ranges of the metric as well as the typical three preliminary thresholds for criteria development as changeover range, described hereafter as the “bounded- described in Table 6. borderline between comfort and discomfort” (bounded-
Downloaded by [University of Washington Libraries] at 08:59 20 February 2014 BCD). These plots are therefore the most useful for indi- cating recommended performance criteria; however, these 3.4. Luminance Ratio of Window Daylight must be considered preliminary in nature. Due to space Source (Mask 08) to Circular Task (Mask 03) constraints, selected metrics are reported. Complete results The ratio of the mean luminance values between the day- are available elsewhere [Van Den Wymelenberg 2012]. light source (Mask 08 Mean L) and the circular task (Mask 03 Mean L) did not perform as well as most other exist-
3.3. EV at the Top of the Monitor in Viewing ing metrics. This metric (Mean L Window: Mean L Task) Direction can be interpreted to resemble the IES-recommended luminance ratio criteria of 1:10 (now 1:20) between the E measured in the participants’ viewing direction from v task and remote light surfaces. It did not have squared cor- the top of the monitor (E -monitor, shown in Fig. 8) v relation coefficients higher than 0.1 for any questionnaire represents the existing metric with the highest squared cor- items except for right_scene (r2 = 0.145). This metric relation coefficient for many of the questionnaire items. Figure154 9 shows the results for C8C10 with participant-days K. Van Den Wymelenberg and M. Inanici results ordered by C10 results. The metric correctly EvTop of Monitor (C8 & C10) 3000 2750 C8 2500 C10 2250 2000 1750 1500 (lux) 1250 1000 750 500 250 0
Participants Ranked by C10 Results
Fig. 9 Vertical Illuminance (Ev) at top of monitor (in participants’ viewing direction) for C8 (MP) and C10 (JU), participant-days ranked by C10 results.
TABLE 5 Ev-monitor single regression results the entire scene (Mask 01; Fig. 3, right) ranked bet-
C8C10: Ev-monitor (lux) ter than DGI but not as high as several existing simpler illuminance- or luminance-based metrics. Figure 13 shows DV r2 F-statistic DF P-value adj the results for C8C10 with participant-day results ordered C8C10 by C10 results. The metric correctly differentiates C10 QU1 0.1418 28.93 168 2.48E-07 (MP) from C8 (JU) scenes for cases where C10 was right_scene 0.1436 29.33 168 2.09E-07 greater than DGP of 24%. There are several cases where Composite_data_set C10 scenes had lower DGP values than other participant- QU1 0.1546 152.60 828 2.20E-16 day C8 cases. Figure 14 takes the C8C10 data, organizes it right_scene 0.2073 217.70 828 2.20E-16 by the metric result, and color codes it by the response to C8C10_filtered QU1. This graphic reveals three preliminary thresholds for QU1 0.3043 56.55 126 9.00E-12 criteria development as described in Table 8. right_scene 0.2741 283.00 126 1.37E-10 Composite_data_set_filtered QU1 0.2378 209.10 666 2.20E-16 right_scene 0.2971 283.00 666 2.20E-16 4. DISCUSSION
4.1. Edesktop
does not consistently differentiate C10 (MP) from C8 (JU) Edesktop is the most commonly referenced metric in scenes. Nearly all C10 scenes fall within the range of other daylighting design and research. Using the composite data
Downloaded by [University of Washington Libraries] at 08:59 20 February 2014 participant-day C8 scenes as shown in Fig. 11. Figure 12 set, the squared correlation coefficient for this metric with 2 = 2 = takes the C8C10 data, organizes it by the metric result, QU1 was adjr 0.09, for right_scene it was also adjr 2 = and color codes it by the response to QU1. This graphic 0.09, and for QU5 (paper-based reading) was adjr reveals one weak threshold of the bounded BCD that can 0.11, not as strong as Ev metrics detailed in Section 3.2. be identified and this is described in Table 7. In this study, the range of Edesktop in all MP conditions was 50–5000 lux with a mean of 1100 lux and a standard devi- ation of 850 lux. For MP conditions under daylight only, ∗ 3.5. Daylight Glare Probability Using 5 the Edesktop spanned the same range (50–5000 lux) with a Mean L of the Circular Task (Using Mask 03, mean of 1250 lux and a standard deviation of 1000 lux. Mask 01) For JU conditions only, Edesktop spanned a much wider range (400–41,000 lux) with a higher mean and standard The DGP based upon 5∗ Mean L of the circular task deviation (= 4300, σ = 7000 lux). Few previous studies (Mask 03; shown in Fig. 3, left) and calculated upon (outlined in Section 1.1) reported preferred Edesktop levels Common Lighting Design Metrics under daylight alone (300 lux) or in integrated lighting155 Ev Top of Monitor (C8 & C10) 3000 Likert Scale 2750 1234567 2500 3 2250
2000 2 3 1750 4 1 3 3 3 3 3 3 1500 2 2 5 1 2 3 3 2 2 (lux) 2 2 1 2 3 1250 1 5 3 3 5 5 5 6 3 3 7 5 5 6 6 1000 5 5 2 6 4 3 3 5 5 2 3 5 7 3 750 5 6 7 6 6 4 5 3 4 5 5 500 7 6 6 7 7 5 6 250 5 6 3 4 5 5 5 6 7 0 3 6 3 Ranked Results, Color−coded by QU1
Fig. 10 Vertical Illuminance (Ev) at top of monitor (in participants’ viewing direction) for C8 and C10, results ordered by metric and color-coded by response to QU1.
TABLE 6 Ev (at top of monitor in participants’ viewing direction) environments (typically 400–800 lux) and the findings range and preliminary criteria from this study were generally higher than levels previ- C8C10: Ev-monitor (lux) range ously published. This is likely due to the abundant daylight Min. 1st Quartile Median Mean 3rd Quartile Max. σ resource available in this study. This study provides some guidance for determining 23 434 726 824 1145 5757 540 an upper horizontal illumination comfort threshold. One Preliminary criteria: could reference the mean Edesktop of JU scenes (4300 lux) x < 875 Likely to be comfortable or the upper threshold of the bounded-BCD approach (for > < 875 x 1250 Bounded-BCD this metric, approximately 2000 lux). These data could x > 1250 Likely to be uncomfortable be referenced by metrics that require an upper horizontal
Window:Task Ratio (C8 & C10)
55 C8 50 C10 45 40 35 Downloaded by [University of Washington Libraries] at 08:59 20 February 2014 30 25 20
Window:Task Ratio 15 10 5 0
Participants Ranked by C10 Results
Fig. 11 Ratio of mean luminance between the window (Mask 08) and the circular task (Mask 03) for C8 (MP) and C10 (JU), participant- days ranked by C10 results.
156 K. Van Den Wymelenberg and M. Inanici Window:Task Ratio (C8 & C10)
55 Likert Scale 17234 56 50 45 2 40 35 3
1 30 2 2 6 3 2 6 2 3 5 5 3 3 2 5 5 2 25 3 5 2 3 5 3 2 6 3 2 3 4 3 2 20 7 5 6 6 Window:Task Ratio 4 6 7 2 5 3 6 5 5 5 2 1 5 15 1 3 6 6 3 5 3 3 2 5 5 4 3 6 3 3 5 6 10 5 7 7 6 5 3 5 7 5 6 5 3 7 4 5 7 5 6 7 4 0
Ranked Results, Color−coded by QU1
Fig. 12 Ratio of mean luminance between the circular task (Mask 03) and window (Mask 08) for C8 and C10, results ordered by metric and color-coded by response to QU1.
TABLE 7 Mean L window: Mean L task range and preliminary illuminance threshold such as daylight saturation percent- criteria age [Collaborative for High Performance Schools 2009], C8C10: Mean L window: Mean L task range which, interestingly, suggests 400 fc (10 times the ambi- Min. 1st Quartile Median Mean 3rd Quartile Max. σ ent criteria of 40 fc; roughly 4300 lux) as the upper limit, or useful daylight illuminance [Mardaljevic and others 0.6 9.5 15.6 16.0 22.2 56.8 8.4 2009, 2012; Nabil and Mardalijevic 2005], which ref- Preliminary criteria: erences a lower level closer to the upper bounded-BCD x < 22 Likely to be comfortable (2000–3000 lux). However, as Fig. 5 demonstrates, any — Bounded-BCD upper horizontal illuminance threshold must be applied x > 22 Likely to be uncomfortable with knowledge that some individuals may accept, or even
DGP (C8 & C10)
0.35 C8 C10
0.3 Downloaded by [University of Washington Libraries] at 08:59 20 February 2014
0.25 DGP
0.2
0.15
Participants Ranked by C10 Results
Fig. 13 DGP based upon 5∗ Mean L of the circular task (Mask 03) using the entire scene (Mask 01) for C8 (MP) and C10 (JU), participant- days ranked by C10 results.
Common Lighting Design Metrics 157 DGP (C8 & C10)
0.35 Likert Scale 5 1234567
2
3
1 0.3 6
3 3 3 2 3 1 6 3 5 2 3 3 1 2 2 5 2 2 3 0.25 3 2 3 2 2 6 3 DGP 3 4 5 1 5 5 5 5 5 3 3 5 3 6 3 5 2 3 5 6 3 6 4 5 3 2 5 5 6 2 7 5 6 5 3 0.2 5 5 5 6 5 7 2 5 6 6 5 7 7 4 7 5 3 5 6 3 6 0.15
Ranked Results, Color−coded by QU1
Fig. 14 DGP based upon 5∗ Mean L of the circular task (Mask 03) using the entire scene (Mask 01) for C8 and C10, results ordered by metric and color-coded by response to QU1.
∗ TABLE 8 DGP (5 mean L task) range and preliminary criteria could be useful criteria for luminous environmental con- C8C10: DGP (5∗ mean L task) (%) range trol systems as well as in simulation-based design analysis, whereas the values from the seated users’ perspective are 1st 3rd limited to simulation-based design analysis because it is Min. Quartile Median Mean Quartile Max. σ not a feasible physical control point. It is interesting to 16.5% 21.1% 23.7% 23.8% 25.9% 35.8% 3.8% note that Ev, outperformed horizontal illuminance mea- Preliminary criteria: sures. The only horizontally measured illuminance metrics < x 23% Likely to be comfortable that ranked highest for any subjective item was Edesktop 23% > x < 25% Bounded-BCD for QU5 (r2 = 0.1282). It is not surprising that the > x 25% Likely to be uncomfortable horizontal illuminance measure ranked highly for the ques- tion addressing paper-based tasks (QU5) because paper- prefer, horizontal illuminance values as high as 5000 lux, based tasks are more often completed on a horizontal and only the most extreme cases can be confidently identi- surface. fied as uncomfortable.
4.3. Luminance Ratios 4.2. E V The most common luminance-based metric referenced Downloaded by [University of Washington Libraries] at 08:59 20 February 2014 The highest overall squared correlation coefficient for by design guides and reported by daylighting research existing metrics reported (using the composite data set) are basic luminance ratios, typically between task: back- 1 was for right_scene and Ev at the top of the monitor ground and bright light source: task. The results from measured in the participants’ viewing direction, produc- Mean L Window: Mean L Task can be argued to repre- ing r2 = 0.298. The next highest squared correlation sent daylight source: task luminance ratio as outlined by coefficient for an illuminance-based metric was Ev at the current IES Lighting Handbook [DiLaura and others the participants’ viewpoint direction (r2 = 0.267). The 2011]. The squared correlation coefficient for this met- 2 bounded-BCD for Ev measured at the top of the monitor ricwithQU1wasadjr = 0.10 and for right_scene it was 2 was 875–1250 lux as shown in Fig. 10 (= 798 lux, adjr = 0.16 across the composite data set. According to the σ = 500 lux). As expected, similar criteria were identi- handbook, the result of this metric should not exceed 10:1 fied for Ev measured from seated participants’ eye position (20:1 is for daylight source to adjacent background). For (1000–1500 lux). The values from the top of the monitor this metric, the MP scenes range from 0.5:1 to 57:1 with
158 K. Van Den Wymelenberg and M. Inanici Example Comfortable Scene 373cd/m2 90th % Scene L 1400cd/m2 Mean L Window
1425cd/m2 5* Mean L Scene 1880cd/m2 Mean L Brightest 10% 1894cd/m2 Mean L Sources (5*mLTask)
3824cd/m2 98th % Scene L 4417cd/m2 Mean L Soures (5*mLScene) 8096cd/m2 Maximum Scene L
Fig. 15 Example comfortable scene with multiple source: task luminance ratios represented.
a mean of 14:1, and the JU scenes ranged from 3.6:1 to only the bright light source definition and produces a range 52:1 with a mean of 22:1. The mean values for the MP of luminance ratios from 5:1 to 102:1 for the same scene. luminance ratios (14:1) are within the range suggested by This wide range of results suggests that further calculation Egan [1983] and the 10th Lighting Handbook [DiLaura definition is required for this metric to be useful. Though and others 2011]; however, approximately half of the par- this metric, as interpreted in this article, does not consis- ticipants had one or more MP scenes with a luminance tently differentiate between MP and JU scenes (Fig. 12)
Downloaded by [University of Washington Libraries] at 08:59 20 February 2014 ratioinexcessof1:20(Fig. 6). or establish a clear bounded-BCD (Fig. 3), it is possible Existing literature does not explicitly state how these that other variations on this metric could prove stronger. luminance ratios should be calculated in spaces with day- The simplicity of this metric is its greatest strength, but light and the method dramatically impacts the result literature is not available to defend the current recommen- (Fig. 15). The regression analysis reported herein used dations [Boyce 1987a, b; Veitch 2001]. Future research is only the Mean L Window: Mean L Task luminance ratio; warranted to establish a consistently applicable calculation however, other luminance ratios are defensible within the method and defensible recommended criteria. current loose definition. Figure 15 illustrates several logical A few other promising luminance ratio metrics from interpretations of the luminance ratio metric as currently previous research are not reviewed in detail because defined for a single comfortable daylight-only scene. This their r2 results did not rank among the highest met- figure interprets the task definition consistently as Mask 03 rics investigated in this study. These include the COV (however, other masks could also be argued) and changes of the entire scene’s luminance (Mask 01) and the
Common Lighting Design Metrics 159 ratio of the 75th:25th luminance value in the entire of the scenes produced DGP results less than 25% across scene (X01_25th_to_75th_percentile). The new Lighting all conditions. Considering only JU scenes that were rated Handbook [DiLaura and others 2011] describes the coef- with a Likert score of 3 or lower on QU1 (that is, partic- ficient of variation, or standard deviation divided by mean ipants disagreed that the space was visually comfortable), (herein COV), as a useful metric for describing the “aver- 75% of the scene produced DGP values below 27%. Only age difference from the average” or the “dispersion of the three of 201 (1.5%) JU scenes rated as uncomfortable on data,” and Howlett and others [2007] suggested it as a QU1 were above DGP 35% and none were above 40%. promising metric in a scoping study. Though it is not a Finally, there was very little difference between the means simple luminance ratio of different regions within a scene, for DGP in MP conditions (21.6%) versus JU conditions it does address both adaptation and variance extremes, (24.2%). Together, these findings (in a space of similar similar to simple luminance ratios. Nonetheless, this met- character and orientation to the original DGP testbed) sug- ric produced squared correlation coefficients among the gest that the metric, as it is currently defined, may not lowest of existing metrics analyzed (Table 4). The same be sensitive enough for use as a daylighting design guide can be said for the ratio between the 25th and 75th per- or as part of an automated blind control algorithm as a centile luminance values in Mask 01, one of the strongest singular metric. It is possible that the view direction in metrics found previously [Newsham and others 2008]. this study (perpendicular to the window) as opposed to This underscores potential challenges to generalizability. the view direction in the original research [Wienold and Christoffersen 2006] used to create the DGP (45◦toward the window) partly explains the difference in DGP values 4.4. Daylight Glare Probability found. It is plausible that participants considered multiple DGP values were relatively low for the entire study with view directions in their subjective assessment of the scene. a maximum value of approximately 45%. The range of Therefore, it may be that improved correlation would DGP values for the entire data set is shown in Table 9.Itis result from using worst-case view direction for the calcu- surprising that some of the seemingly excessively glaring lation of DGP, in a sense a reverse interpretation of the scenes did not have higher DGP values. As shown in Fig. “adaptive zone” concept [Jakubiec and Reinhart 2012]. 14, the DGP consistently differentiates between MP and Together, Table 10 and Fig. 16 document another lim- JU conditions above a value of 25%; however, below this itation of task-based glare indices, and in this case DGP. threshold it did not do so reliably. This is to be expected Glare indices attempt to account for adaptation by incor- given that the DGP algorithm was founded upon a data set porating a glare source identification step that is typically that included very few data producing a DGP of 25% or based upon a multiplier of the mean luminance of the lower [Wienold and Christoffersen 2006]. Wienold [2009] task or the entire scene. When direct sunlight enters the and Reinhart and Wienold [2011] stated that DGP val- space and is perceived as glare, it can also be incorrectly ues below 35% are “imperceptible glare,” 36%–40% are included in the calculation of the adaptation component, “perceptible glare,” 41%–45% are “disturbing glare,” and essentially reducing the intensity or solid angle of the glare above 45% are “intolerable glare.” In this study, over 75% sources identified. This limitation can be exacerbated when
TABLE 9 Summary DGP results for all conditions (top) JU conditions rated below 3 on QU1 only (bottom) Downloaded by [University of Washington Libraries] at 08:59 20 February 2014 All conditions DGP results
DGP metric Min. 1st Quartile Median Mean 3rd Quartile Max.
DGP (5∗ mean L task) 16.49% 19.36% 21.64% 22.06% 23.97% 44.03% DGP (5∗ mean L scene) 16.49% 19.20% 21.53% 22.00% 24.08% 44.56% DGP (>2000 cd/m2) 16.49% 19.08% 21.54% 21.93% 24.07% 44.41% DGP (>5000 cd/m2) 16.49% 18.75% 21.00% 21.65% 24.11% 44.55%
JU scenes (C4C5C10C13_QU1_Likert_below_3) DGP results DGP (5∗ mean L task) 0.1678 0.2342 0.2539 0.2551 0.2716 0.3868 DGP (5∗ mean L scene) 0.1679 0.2305 0.2531 0.2534 0.2732 0.3662 DGP (>2000 cd/m2) 0.1649 0.2307 0.2536 0.254 0.2744 0.3802 DGP (>5000 cd/m2) 0.1649 0.2256 0.2542 0.2516 0.2725 0.3682
160 K. Van Den Wymelenberg and M. Inanici TABLE 10 DGP results from a MP and a JU scene for a single associated with subjective measures of human visual pref- participant, with other selected metrics erence and acceptance (using Likert-type and semantic Participant 36, round 2, 2011-10-17 differential questionnaire items) in an office space with C13 (JU) C14 (MP) daylight only and with both daylight and electric light (integrated lighting). The results are useful to provide / 2 Mean L scene (cd m ) 1092 1682 research-based recommendations for improved integrated Mean L task (cd/m2) 455 130 5∗ Mean L scene (cd/m2) 5460 8410 lighting design strategies, computational analysis methods, 5∗ Mean L task (cd/m2) 2275 650 and lighting and blind control technologies, and to guide DGP (5∗ mean L scene) 32% 45% future research: DGP (5∗ mean L task) 32% 44% Vertical illuminance and simple luminance metrics Standard deviation of scene L 3615 7300 (mean and standard deviation of scene luminance) outper- / 2 (cd m ) formed more complex metrics (such as DGP and DGI, or luminance ratios) for QU4, “I am satisfied with the amount of light for computer work.” Therefore, estab- calculating DGP by defining a task region as recommend lishing reliable vertical illuminance- and luminance-based by Evalglare [Wienold 2008]. In scenes where sunlight metrics and design criteria that can be referenced in enters the task region (Fig. 16, left, a), it can make the glare design stages, through additional research, should lead to source identification threshold artificially high and cause improved occupant satisfaction in spaces adhering to these glare sources to be missed. Ultimately, the resultant DGP criteria. can be lower than might otherwise be expected. Ev measured at a seated occupant’s eye position or at the Table 10 illustrates the difference between two scenes top of the monitor pointed in the same viewing direction captured on a sunny afternoon. The JU scene has a lower as the occupant were both more capable than horizontal DGP value (32%) than the MP scene (45%). Figure 16 illuminance measures of fitting the range of human sub- illustrates the same scenes graphically (JU at left, MP at jective responses to visual preference questionnaire items. right) where the first row shows the tone-mapped scenes Therefore, establishing reliable design criteria for Ev that (a), the second row shows the luminance false color (b), can be referenced in design stages should lead to improved and the third (c) and fourth (d) rows illustrate the glare occupant satisfaction in spaces adhering to these criteria. source identification results. It is interesting to note that in Preliminary bounded-BCD criteria for Ev measured near this example the glare source identification method (either the occupants’ point of view from this study range from five times the mean luminance of the circular task or the 1000 to 1500 lux. entire scene) does not produce meaningful differences in Desktop illuminance was among the weakest of the the DGP value. The comparison between the two scenes existing lighting design metrics. However, due to its ease of (MP and JU) clearly reveals the challenge presented to glare use and prevalence in practice, a range of upper horizontal metrics (DGP in this case) as sunlight slips through blinds illuminance comfort-based threshold (as used by daylight and increases the adaptation level. saturation percentage and useful daylight illuminance) is proposed. Upper horizontal illuminance thresholds should 5. CONCLUSION be set between 2000 and 4300 lux but must be applied Downloaded by [University of Washington Libraries] at 08:59 20 February 2014 with an understanding that some individuals may prefer This article provides the results of a 6-month-long human values as high as 5000 lux (during some parts of the year), factors research project replete with extensive lighting data thus confidently identifying only the most extreme cases as collection that aims to study the limitations of existing uncomfortable. illuminance- and luminance-based lighting quality guide- The luminance ratio between the mean luminance of lines, particularly in relation to visual comfort, in single- the daylight source (Mask 08 Mean L) and the mean occupancy office environments. A sample of 48 human luminance of the circular task (Mask 03 Mean L) did subjects was examined in a repeated-measures design in not yield squared correlation coefficients as high as other a mock office space under naturally occurring and sys- existing metrics with regard to the subjective visual com- tematically categorized daylight conditions. The following fort ratings. The bounded-BCD suggested by this study conclusions are reported to determine which lighting met- (22:1) is higher than existing recommendations, and rics (illuminance and luminance based) are more strongly the current IES recommendations are not supported by
Common Lighting Design Metrics 161 JU MP
aa
C13, 3:31pm C14, 2:16pm JU Daylight Glare, Electric same as C11 MP Integrated Daylight & Electric
cd/m2 2000 940 440 210 97 46 bb21 10
S036_2011-10-17-153101_c1 S036-2011-10-17-141648_c1
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Glare sources by 5*mL X03 Glare sources by 5*mL X03
Fig. 16 Limitation of the circular task (Mask 03, X03) multiplier for glare source identification when using DGP.
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