Indoor Environmental Quality: Lighting and Acoustics

Indoor Environmental Quality: Lighting and Acoustics S Altomonte, P Rutherford, and R Wilson, The University of Nottingham, Nottingham, United Kingdom Ó 2017 Elsevier Inc. All rights reserved.

Introduction: Indoor Environmental Quality Growing concerns on the environmental, social, and economic sustainability of buildings (IPCC, 2014)dand awareness that people in developed countries today spend almost 90% of their time in indoor spaces (Schweizer et al., 2007)dhave triggered a substantial body of research on the effects that (hygro)thermal, olfactory, luminous, and acoustic indoor environmental qualities (IEQ) have over human comfort, performance, and health (Hedge, 2000). However, although inadequate IEQ has been found to adversely affect comfort anddin the workplacedreduce job performance (Lamb and Kwok, 2016), buildings design might not yet be sufficiently informed by a comprehensive understanding of how environmental forces influence the well-being, perception, and behavior of their users (Lan et al., 2014). In fact, other than being driven by individually quantifiable physical factors, occupants’ response to IEQ is triggered by a combination of stimuli where physiological and psychological dimensions must also be taken into account. In this context, research has shown that thermal sensation and air quality are often ranked by building users with a higher perceived importance towards their comfort and health rather than light and sound (Humphreys, 2005; Frontczak and Wargocki, 2011). This is also reflected in standards and regulations, wheredlikely striving for targets of carbon neutrality and energy efficiencydcriteria pertaining to temperature, humidity, and pollutant control are conventionally given priority over lighting and acoustic conditions (Altomonte et al., 2015). Yet, recent studies have provided evidence that the luminous and sonic environments are most influential on human perception and behavior, and significantly contribute, individually and combined, towards the regulation of their physical, physiological, and psychological well-being. These environments, and the processes that take place within them, are described below.

The Luminous Environment The Physics of Light The luminous environment comprises the band of electromagnetic spectrum between 380 and 780 nm that is detected by the human eye and interpreted as vision (CIE, 2014). The eye, however, does not respond equally to all visible wavelengths, being most sensitive to light at about 555 nm (green-yellow) under bright conditions (photopic), and at about 505 nm (blue-green) in dim conditions (scotopic). The CIE (International Commission on Illumination) standard photopic and scotopic sensitivity curvesdrespectively, the spectral luminous efficiency functions V(l) and V0 (l), weighted to the characteristics of the two main visual photoreceptors in the eye, cones and rodsdare generally used in practical applications. The human eye can react dynamically to luminous stimuli, allowing a wide range of lighting scenes to be received (adaptation) and accommodated (focusing), adjusting more or less rapidly to changes in lighting levels, and ensuring a perception of colors. Several metrics have been developed to evaluate the lighting performance of buildings, focusing on quantitative aspects of the luminous radiation to achieve energy balance for lighting and heating/cooling needs and to afford visual task performance (light availability and distribution), and on qualitative features that contribute to visual comfort and satisfaction (e.g., glare, color rendering, etc.), that influence the health and well-being of occupants (e.g., physio-psychological stimulation). A lighting strategy generally involves more than making calculations based on the use of conventional photometric measures such as: luminous flux (visible energy radiated over unit of time, lumens), illuminance (density of luminous flux, lux), and luminance (luminous intensity per unit area of light in a given direction, candelas per square meter). In fact, it also requires consideration of potential sources of visual discomfort and a proper balancing between natural and artificial lighting.

The Measures of Light Since lighting design encompasses a number of goals, the effectiveness of a strategy can be evaluated by various metrics and indicators. Among common static measures, the daylight factor is one of the oldest and is defined as the ratio between external and internal illuminancedtaken at a point or as an average over the entire spacedunder a CIE fully overcast sky (Moon and Spencer, 1942). Recently, climate-based daylight modeling (CBDM) has been proposed as a method to complement static indicators, taking into account the presence of sunlight and the variability of climates across daily and seasonal patterns (Mardaljevic et al., 2009). Among CBDM metrics: the daylight autonomy describes the fraction of the occupied time during a year when a certain threshold illuminance (e.g., 300 or 500 lux) at a specific point is exceeded and no electric lighting is needed (Reinhart et al., 2006); the spatial daylight autonomy is an extension of the previous metric and describes the percentage of floor area exceeding a certain illuminance threshold for a given time fraction of the year within a predefined time frame (Aries and Wienold, 2015); the useful daylight illuminance bins the illuminance values occurring in a space into different categories (Nabil and Mardaljevic, 2005); the annual sunlight exposure is the percentage of an analysis area that, without considering window shading, exceeds a specified illuminance level from direct sunlight (e.g., 1000 lux) for more than a stated number of hours per year (e.g., 250 hours) (Meek and Van Den Wymelenberg, 2014). In lighting design, the term luminous efficacy of radiation (LER) defines the ratio of a light source’s luminous flux to its optical radiation power (or the ratio of its illuminance to its irradiance). The greatest value for LER is 683 lm W 1, corresponding to

Encyclopedia of Sustainable Technologies, Volume 2

http://dx.doi.org/10.1016/B978-0-12-409548-9.10196-4

221

222

Indoor Environmental Quality: Lighting and Acoustics

monochromatic light at 555 nm. This ratio represents the relative effectiveness with which human color vision is stimulated by the distribution of wavelengths emitted by a light source. Luminous efficacy is also often used to represent the ratio between the luminous flux emitted by a light source to its input electrical power (Houser et al., 2015). Other important metrics are: color temperature, defined as the temperature of a black body emitting light of comparable spectral composition than that of the light source considered; chromaticity, the property of a color stimulus defined by its chromaticity coordinates; the special color rendering index (Ri), which measures the degree to which the psychophysical color of a CIE test color sample illuminated by a test illuminant conforms to that of the same sample illuminated by a reference illuminant, once allowance has been made for chromatic adaptation; the general color rendering index (CRI or Ra), which is defined as the mean of the CIE special color rendering indices for a specific set of eight test color samples (CIE, 2014). To better respond to contemporary lighting requirements (also due to the advent of self-luminous computer screens, tablets, and smartphones) and to deliver better lighting at lower environmental and social costs, several other metrics are under discussion for their inclusion in lighting standards (Boyce and Smet, 2014). Among these: the lighting energy numeric indicator is defined as the annual energy consumed by a lighting installation per square meter of lit area (kWh m 2 year 1); the mean room surface exitance represents the ambient density of diffusely interreflected luminous flux within the volume of a space; the target/ ambient illumination ratio forms a design procedure for first lighting the space and then any significant objects in it (Cuttle, 2013). In terms of visual comfort and satisfaction, several indices have been proposed to evaluate the sensation of glare, although predicting subjective evaluations of visual sensation remains an underlying problem (Altomonte, 2009). Glare can be broadly divided in three categories: (1) disability glare, which is caused by bright areas in the field of view with greater luminance than that to which the eyes can adapt to. This type of glare consists of an instantaneous “physiological” phenomenon that impairs the vision (Vos, 2003); (2) veiling glare, which is caused by reflections on specular or diffusive materials that might reduce the contrast and visibility of the task; and (3) discomfort glare, a “psychological” sensation that does not necessarily impair vision in the short term and can remain unnoticed to observers, although it can cause headaches or eyestrain after long exposure. Although disability glare has been comprehensively characterized, the understanding of the process linked to the occurrence and magnitude of discomfort glare is still incomplete. Several indices have been proposed to quantify discomfort glare from small sources (e.g., artificial lighting), such as: the visual comfort probability (Luckiesh and Guth, 1949), the British glare index (Peterbridge and Hopkinson, 1950), the Illuminating Engineering Society glare index (Robinson et al., 1962), the CIE glare index (Einhorn, 1979), and the unified glare rating (UGR) (Sorensen, 1987). For discomfort glare generated by large luminous sources (e.g., windows), indices include: the daylight glare index (Chauvel et al., 1982), the new daylight glare index (Nazzal, 2005), and the daylight glare probability (Wienold and Christoffersen, 2006). Although some of these metrics have been implemented in standards (EN 12464-1, 2011), there is a widely held view that they do not provide consistent prediction of the discomfort reported by subjects, particularly when originating from daylight (Tregenza and Loe, 2014). In fact, the level of disturbance generated from a light source has also been associated with the nature of the task and personal tolerance (Hopkinson, 1973). In addition, discomfort glare from windows has been found to be more acceptable than from artificial lighting (Hopkinson, 1971; Osterhaus, 2005), particularly when the glare source is associated with an interesting view (Tuaycharoen and Tregenza, 2005, 2007). However, it is still unknown whether this increased tolerance is a short-term effect, gradually disappearing after prolonged viewing, or one that endures, particularly if the scene is highly dynamic. Most of the glare indices herein mentioned are based on four fundamental parameters: the luminance of the source, the luminance of the background, the solid angle subtended by the source to the observer’s eye, and the position index of the source relative to the line of sight (the daylight glare probability also includes consideration of the vertical illuminance at the eye). Yet, other parameters have been associated with the occurrence and perceived magnitude of visual discomfort. Among these, an increasing tolerance to glare has been detected as the day progresses (Kent et al., 2015a), this trend being mostly evident for subjects not having ingested caffeine and for earlier chronotypes (a personal trait linked to preferences for diurnal activity periods and sleep habits) (Kent et al., 2015b). Direct effects of task difficulty and fatigue, and an inverse influence of food intake, were also detected in reported glare sensation (Altomonte et al., 2016). These findings are consistent with research in the psychophysiological and behavioral sciences that found tiredness from long hours of work and the ingestion of stimulants to be associated with heightened arousal and sensitization to luminous stimuli (Emdad et al., 1998; Burke et al., 2015).These studies, therefore, suggest that there might be other variables than those included in glare formulae that cause variability in the level of visual sensation reported by subjects (Tregenza and Wilson, 2011), supporting the need for interdisciplinary research on the potential links between visual sensation, biological processes, and psychological response.

Nonvisual Effects of Light Several daily (circadian) and seasonal (circannual) biological rhythms in the human body, in fact, are strongly influenced by the luminous stimuli received at the eye. These responses to retinal illumination are commonly referred to as nonvisual, since they originate in the eye but are separate from other aspects of vision (CIE, 2015a). In the short term, retinal illumination can contribute to suppression of the pineal hormone melatonin (the “sleep” hormone, whose secretion is associated with the body preparing for sleep), stimulate the production of cortisol (the “stress” hormone), regulate heart rate, core body temperature, and many other neurophysiological processes (e.g., alertness, psychomotor reaction times, pupillary constriction, etc.). In the long term, nonvisual effects of light can influence the synchronization of the endogenous circadian clock to the daily light–dark cycle, and affect various neurobehavioral functions (e.g., attention and other emotional responses). Nonvisual responses are mainly attributed to a particular class of intrinsically photosensitive retinal ganglion cells (ipRGCs) that achieve photoreception through expression of melanopsin, an opsin photopigment (Provencio et al., 1998; Berson et al., 2002). Nonvisual

Indoor Environmental Quality: Lighting and Acoustics

223

responses are, however, also influenced by extrinsic signals originating in rods and cones (Lucas et al., 2014). ipRGCs have a direct neuronal connection to the suprachiasmatic nuclei (SCNs) in the hypothalamus. The SCN exhibits an endogenous rhythm, but with a periodicity that is not exactly 24 h. For this reason, the circadian pacemaker needs to be reset every day to the light–dark cycle of the Earth’s rotation so as to prevent the free-running of the endogenous clock from the external time rhythmicity (Lockley, 2009). Several studies have attempted to define a spectral weighting function to predict the nonvisual effects of light (Brainard et al., 2001; Thapan et al., 2001; Enezi et al., 2011; Rea, 2015). However, established knowledge in this field is still premature, although it is generally accepted that nonvisual responses depend upon the intensity, duration, timing, spectrum, and history of light exposure (CIE, 2015b). In addition, neuroimaging studies have shown that the nonvisual effects of light may also result from involvement of limbic cortical areas that increase emotional responses, enhancing arousal and mood regulation (Vandewalle et al., 2009). In particular, mood has been found to be influenced by a complex interaction between circadian phases and duration of prior wakefulness. Circadian disruptions, in fact, often result in mood alterations, while mood also deteriorates as sleep propensity increases. Luminous stimuli, thus, can affect human response through their synchronizing/phase-shifting effects on the circadian clock but also via their alerting effects, both during the day as at night. In this context, lightdparticularly when accompanied by dynamic viewsdhas long been considered as contributing to stress reduction (Ulrich, 1979), enhancing patients’ recovery (Ulrich, 1984) and inducing calmative effects (Kaplan and Kaplan, 1989). Pleasurable feelings aroused by visual stimuli have also been found in judging color, a perceptual response triggered by, and related to, the spectral distribution of luminous radiation (Houser et al., 2015). However, whether the association between color, physiological reactions (e.g., heart and respiration rate), and psychological responses (e.g., mood, emotions) is direct or indirect is yet to be clarified (Lengen, 2015).

The Design of Lighting The use of natural and artificial lighting in buildings has to respond at once to the demands of the users and to the needs of the building, finding a balance between requirements of light transmission, protection, and distribution. Specifying lighting solutions can be a complex taskddependent on climate, orientation, functions, etc.dwhere many variables can diverge from each other, making selection and optimization difficult (Altomonte, 2009). Daylight from windows, with its variations in intensity, directionality, and spectral composition, can positively influence the comfort and well-being of building users, and also bring tangible energy savings, as long as it minimizes energy demands for artificial lighting and is balanced against thermal requirements (e.g., solar gains, heat losses, etc.). Yet, daylight through windows can also imply major drawbacks. Luminance ratios in the field of view should always be contained within specific limits: too large, and it will be difficult for the eyes to adapt; too small, and it might be hard to estimate depths and distances. As the eye attempts to even out the contrast between different surfaces, areas of high luminance in the background of a visual task should be avoided to reduce the risk of tiredness and visual stress (Altomonte, 2009). A daylight strategy including a view out can also strongly impact on perception, offering relief from visual muscle strain, relaxation, and spatiotemporal orientation. In this context, the window-to-wall ratio and the geometry of openings are particularly important. Wide windows placed high in the wall are generally more efficient for lighting and solar energy penetration than low vertical windows. However, floor-to-ceiling openings offer all three layers conducive to good view quality: upperddistant, the sky; middlednatural or human-made objects, such as fields, trees, hills or buildings; and, lowerdthe foreground, including plants, pavements, etc. (Bell and Burt, 1995). The presence of external views is one of the criteria by which daylighting and shading systems are designed and operated. The palette of devices available is very broad and new products are constantly being implemented to increase daylight penetration, improve distribution and uniformity, control sunlight, and reduce glare. Shading systems can range from simple static (e.g., louvers, overhangs, fins, etc.) to adaptable and dynamic elements (e.g., roller or venetian blinds, switchable glazing, etc.) and/or their combinations. These systems can minimize the occurrence of visual discomfort and, when mounted externally to the glazing, reduce the risk of solar overheating. However, they should always ensure a perception of the outside, and possibly be adjustable based on weather conditions and users’ desires. In terms of light distribution, a combination of diffuse and direct lighting can enhance recognition of objects and liven up the environment. Spatial contrast, directionality of lighting, and variations, in fact, are fundamental to the appearance of a space (Rockcastle and Andersen, 2014). To enhance the lighting of the built environment, daylight strategies should be properly complementeddand, at times, supplementeddby adequate artificial lighting systems that allow a proper illumination of spaces and perception of colors. A good combination between the two can generally allow to gradually dim the amount of electric light required when natural illumination is sufficient. Natural and artificial light are, however, fundamentally different, primarily in terms of their spectral quality. Daylight typically shows a smooth curve spectrum with energy content across all frequencies, whereas artificial lighting systems produce generally discontinuous spectra spiking at different wavelengths depending on lamp type. Artificial lighting can be direct, indirect, or a combination of both. Several adjustable lighting systems should be preferred to evenly-distributed ceiling luminaries, with fixtures and lighting circuits being grouped by areas of similar daylight availability. In terms of the correlated color temperature (CCT) of artificial lighting, the choice should be made by the function of the space, thus also involving psychological aspects such as the impression of warmth, relaxation, clarity, etc. As the intensity and spectral composition of daylight shows significant variations during the day, a dynamically controlled artificial lighting system should guarantee variation in both color and lighting levels. A control system able to dim artificial light and/or turn luminaries off when there is sufficient daylight or after occupancy may enhance energy savings and proper light distribution. Dimming control is generally accepted by users since changes in light levels are less abrupt, while fully automated systems without local override should be avoided (Altomonte, 2009).

224

Indoor Environmental Quality: Lighting and Acoustics

As of lamp types, these can be divided based on the physical process by which electrical energy is converted into radiant energy: heating a metal filament; passing current through a gas; or using a semiconductor device. In addition, some lamp types use the principle of fluorescence, by which radiant energy is absorbed by a material and reradiated at different frequencies (Tregenza and Loe, 2014). In the traditional incandescent lamp, a glass bulb containing an inert gas surrounds a filament that is heated up by an electric current until it glows white hot (2800 K). In the tungsten-halogen lamp, halogen is added to the inert gas, providing a higher CCT (3000 K) and a whiter appearance. Incandescent lamps have typically low cost, short life (1000–2000 h), and low efficacy (12–20 lm W 1), but good color rendering properties (CRI 100). In discharge lamps (e.g., fluorescent low-pressure mercury vapor, compact fluorescent, cold cathode, induction, high-pressure discharge, metal halide lamps, etc.), a tube is fitted with electrodes at its extremities and is filled with a gas (e.g., mercury or sodium vapor). A high voltage, produced by an electrical control circuitry, is applied between the electrodes to ionize the gas. The light output (wavelength and CCT) depends on the gas utilized in the tube and on its pressure, and is generally characterized by a discontinuous spectrum with bands of radiation at specific wavelengths. Discharge lamps are characterized by moderate life (up to 30,000 h), medium to good efficacy (up to 140 lm W 1), a wide range of color appearance (2700–6500 K) and color rendering (CRI 19–90). Finally, light-emitting diodes (LEDs) use the principle of electroluminescence occurring when electrons are repositioned in a junction between two semiconductors. When an electric current is applied, radiation in narrow spectral bands is emitted from the junction. White light can be obtained from these narrow-band emissions by housing together LEDs of different spectral output. Considering the rapid advances in technology and reduction in costs, LEDs represent a very promising development in lighting, primarily due to their very long life time (typically 70,000 h), small size, good efficiency (30–100 lm W 1) and color rendering properties (CRI 80-96), and their capacity to produce light of different spectral quality (2500–10,000 K) (Tregenza and Loe, 2014). International standards specify lighting design recommendations for a wide range of activities according to visual comfort criteria, although these are still generally limited to horizontal light availability (maintained illuminance), glare from small lighting sources (UGR), and color properties (CRI) (EN 12464-1, 2011). Some certification systems, such as the WELL standard in the United States, are starting to address awareness of the nonvisual effects of light (Delos Living, 2015), even if most specifications for lighting installations are still centered on the photopic and scotopic spectral sensitivity without taking into account the melanopsin-based photoreceptive system. In this regard, however, CIE warns of the difficulties of making tailored lighting recommendations due to the yet incomplete understanding of the input–output characteristics between light stimulus, visual and nonvisual responses (CIE, 2015b). Yet, simultaneous consideration of physical, physiological, and behavioral stimulation from natural and artificial lighting should be consistently reflected in the design and operation of buildings (Boyce, 2014). In terms of luminous signals, visual and nonvisual responses should be given an equal emphasis in the definition of a lighting strategy that facilitates visual performance, provides luminous comfort, allows an esthetic appreciation of a space, fosters interpersonal communication, is conducive to a positive mood and good biological entraining, and reflects the needs of buildings’ energy balance.

The Aural Environment Our ability to listen has been fundamental to the evolution of our species, a “crucial interface between the individual and the environment” (Truax, 2000). Through speech and music, it provides an essential vehicle by which we communicate and express our moods and emotions, thereby allowing us to both transact and interact with those around us and with society as a whole. Yet, its origins are more primal than this. Within minutes of their birth, infants have the ability to turn their heads towards a sound source (Wertheimer, 1961), this “orienting reflex” (Sokolov, 1963) no doubt being key to the survival of our species. In this context, listening plays an essential role in the process by which an observer visually examines, forms an opinion of, and responds to the environment. This brings us to the concept of soundscape (Schafer, 1977). Described by (Truax, 1978) as “an environment of sound (or sonic environment) with emphasis on the way it is perceived and understood by the individual, or by a society”, the everyday soundscapes we encounter play a main role in the way we experience our environment. The “familiar soundscape”, according to Garrioch (2003), helps to “create a sense of belonging: part of the ‘feel’ of a particular city, town or neighborhood, a key component of people’s sense of place”. This relationship between people, sound, and their environment provides an interesting vehicle from where auditory aspects of IEQ can be explored. This is of course not without its challenges. In fact, given that improperly designed soundscapes impact negatively on health and well-beingdand evidence illustrates that environmental noise is a public health problem (WHO, 2011)dit is obvious that more consideration needs to be given to sound as a key factor in building design. Sound impacts fundamentally our psychology, emotions, behavior, social interactions, identity, and our relationships with time, space, and place, being in part the reception of an often complex blend of acoustic signals modified during the journey from their source, and in part a conscious or subconscious response that our brain makes to the information contained within these signals. Although the mathematics used to describe and quantify sound generation, its propagation through space, and its interaction with materials and surfaces can be complex, it does describe a behavior that is largely deterministic. The interpretation of sound once it has been captured by the hearing system is far more nuanced: it can be highly personal, and vary continuously (Augoyard and Torgue, 2008).

The Properties of Sound We are enveloped in a continuous but mixed medium of gases, liquids, and solids, which by virtue of possessing the property of elasticity, connects us to any sources of sound present in our environment. Any disturbance that results in the deformation of this

Indoor Environmental Quality: Lighting and Acoustics

225

medium will be propagated away from the source of excitation, transmitting energy in the form of a wave. This energy envelops an ever increasing volume of space, undergoing reflection, transmission, and diffraction as it encounters any boundaries between different media. Its ultimate destination is low grade heat: the wave energy is dissipated due largely to the imperfect elasticity of the medium itself, or to viscous effects at boundaries between fluid and solid components of the medium. We represent the final destination for the energy that is destined to intercept our hearing system. This energy undergoes a chain of conversion processes that ultimately result in nervous signals presented for our brains to interpret.

The sound source

Acoustic waves take the form of pressure fluctuations above and below atmospheric pressure, which under standard conditions travel away from the source at a speed of around 340 m s 1. Many of the common acoustic generation mechanisms may be observed in musical instruments, but also have direct parallels outside the musical realm (e.g., aerodynamic excitation of a solid causing it to vibrate). Sound generation is an energy conversion process: energy is transferred from the source of excitation into the wave field, manifesting itself as pressure fluctuations. The more effective the process of sound generation, the greater power transmitted by the wave, and the larger the amplitude of these pressure fluctuations (p; unit Pa) above and below atmospheric pressure. It is this characteristic of an acoustic wave that is responsible for the sensation of loudness. For the majority of everyday exposure, the peak amplitude of the acoustic pressure is relatively small: typically, less than 1 Pa. In terms of pressure-related phenomena, sound is mostly a very subtle flux flowing through the environment. The time-varying behavior of the excitation source is reflected in the shape of the pressure fluctuations sent out into the space that surrounds them. Simple sources, such as a tuning fork, give rise to “simple” sinusoidal waveforms. The number of complete wave cycles generated in a second describes the frequency (f; unit Hz) of the sound. In contrast, the majority of everyday sound sources are more complex, generating more compound waveforms that are a composite of many different frequency components. It is this characteristic of a wave that carries information about what created it and often about the environment, based on how it has been modified in the journey between source and receiver.

The transmission path The processes of modification of sound can be divided into two main categories: geometrical and interactional. The interactions that occur when a sound wave is incident on solid materials are the basis for many of the design strategies that seek to either emphasize or “eliminate” sound. The geometric influences on sound are a consequence of the wave field traveling away from the source through a volume of space, and describing an ever increasing area of wave front. For simple sources suspended in space, sound radiates spherically from its origin (hemispherically, if located on a surface) and the consequences of the process of geometric spreading are easy to quantify. If it is assumed that the power traveling through a spherical wave front remains constant at any distance from the source, the power flowing through a unit area of wave front, or the acoustic intensity (I; unit W m 2), will decrease the further you are from the acoustic origin. Given that the area of a sphere is proportional to the square of its radius, the relationship between acoustic intensity and separation between source and receiver obeys the inverse square law. Every time this separation is doubled, the acoustic intensity reduces to a quarter of its value. This explains why sound sources get quieter as we move away from them. Geometric spreading behavior is evident around many sources of sound, typically during that part of a wave’s journey prior to its interaction with a solid surface. Thereafter, its journey becomes more complex and difficult to predict, with the processes of reflection, diffraction, and transmission affecting both the direction in which the wave travels and the energy that it carries with it.

The receiver The interaction of sound with the human hearing system is complex but, at a purely functional level, fulfills two key tasks: (1) zooming in on very subtle sounds, often buried in a complex soundscape and (2) estimating the direction from which the sound is traveling from the way sound waves diffract around the head. Our ability to detect very low acoustic pressures provides evolutionary advantage by avoiding becoming prey. Within Nature, there is a need also to tolerate very high sound pressures, such as in the case of thunder claps. What results is a very wide range of pressures for our hearing system to accommodate (from about 10 5 Pa at the threshold of hearing, to 102 Pa for some loud events), but with the vast majority of everyday exposure being from pressures that occur at only fractions of a Pascal. This need to “focus” on low acoustic pressures, and de-emphasize high acoustic pressures, is reflected in the measures used to quantify our perception of the loudness of sound. This makes use of a logarithmic scale that is tied into the decibel system for quantifying power, W: Lw ¼ 10 log

W Wo

unit; dB re: 1012 W




where Lw is the sound power level expressed in decibels and Wo is a reference pressure (typically, 10 12 W). The reference pressure effectively allows us to dictate what power 0 dB should equate to. As sound pressure is related to sound power through p2, sound pressure levels, Lp (i.e., acoustic pressure expressed in decibels), take on a slightly different form: Lp ¼ 10 log

p2 p2o

unit; dB re: 2  105 Pa




here, the reference pressure is taken as 2  10 5 Pa to approximate our threshold of hearing.

226

Indoor Environmental Quality: Lighting and Acoustics

Our response to the frequency content of an acoustic signal follows a similar pattern, with greater emphasis being placed on the lower frequencies. The method used to quantify this response differs from that used for quantifying loudness, and has its origins in music. The range of audible frequencies, approximately 20–20,000 Hz in healthy listeners, is divided into octavesdeach grouping of frequencies in an octave is twice that of the octave that precedes it and half of the octave that follows it. Within this frequency range, the sensitivity of our hearing varies, peaking around the middle of the frequencies contained within speech (which lie between about 120 and 4000 Hz), and rolling off towards the infrasound and ultrasound regions at low and high frequency, respectively.

The Measures of Sound To quantify sound, we typically use measuring equipment that serves as a proxy for our ears, and analysis techniques that do part of the work performed by our brain in interpreting the information recorded. Microphones convert acoustic energy into calibrated electrical signals that can either be recorded for later analysis or processed in real time and stored if desired. In many cases, the analysis will be carried out for a single point in space and so will contain information that is unique, dictated by the relative positions of the measurement point and the sources of sound contributing to the acoustic field at that point. Completing measurements at a number of discrete points (or use of a moving microphone) allows a spatially averaged “picture” of the sound field to be established. The need to quantify the acoustic field is often to demonstrate compliance with regulatory requirements or to compare the characteristics of a sound field with those intended through a process of design. Perhaps the simplest question that may be answered through measurement is: how loud is the sound we are experiencing? Converting a sound pressure signal into decibels offers a measure that roughly matches the way in which our hearing system responds to the intensity of sound. Measuring sound pressure level (Lp) in this way does not account for the roll off in the sensitivity of our hearing system to low and high frequency. This is typically accommodated by modifying the linear response of the microphone, or rather the signal it produces, using an A-weighting. This yields an A-weighted sound pressure level (LA; unit dB(A)), which will be similar to unweighted levels if the sound field contains the majority of its energy in the mid frequencies, and lower than unweighted levels if there are dominant high or low frequency components. This combination of weighting and use of a decibel scale provides measurements that roughly reflect our perception of sound. In making measurements, it is unusual to focus on instantaneous sound pressure levels, as typically we will be interested in quantifying the characteristics of a sound field as it plays out over a period of time. One of the simplest measures that accommodates the time-varying nature of many sound sources is the equivalent continuous sound pressure level (Leq; unit, dB or dB(A), stated along with the period of time over which the measurement was taken). This replaces the measured, time-varying sound pressure level, with a single notional continuous sound pressure level that, if present at the measurement point, would contain an equivalent amount of acoustic energy. The ability to quantify sound in this way allows us to specify maximum background noise levels for the environments we design. Linked to these are targets that acknowledge the links between long term exposure to environmental noise and its negative impact on people’s health and well-being (WHO, 2011). Where there is potential for sound to cause permanent damage to hearing, the relationship between equivalent continuous sound pressure level and the acoustic energy associated with any given period of exposure to a noise source makes it possible to define maximum permissible exposure doses. These doses are frequently regulated for, and set out either maximum permissible sound pressure levels for a given period of exposure, or maximum permissible periods of exposure to a given noise source. The use of long term Leq measurements has the effect of smoothing out any temporal variation that may be present in the acoustic field. While this may not be a problem in many instances, we are frequently interested in understanding what the typical background level is within the environment, and whether there are any significant noise events that rise above this. Monitoring an acoustic signal to generate a statistical distribution of sound pressure levels provides the data required to generate statistical sound pressure levels (Ln, where n is the percentage of time any given sound pressure level is exceeded). Background levels are typically represented using the L90 measure (i.e., the sound pressure level that is exceeded 90% of the time) and peak events by the L10 measure. In sound fields where there is very little variation in levels with time, the L90, L10, and Leq measures will all be very similar, indicating a low dynamic range. The appearance of events within the soundscape that stand out above the general background will begin to drive the L90 and L10 measures apart. Just as delving into the time-varying nature of a sound field can yield useful information about the environment, so too can exploring the distribution of acoustic energy across the range of frequencies we are interested in. The ability to transform the captured acoustic signal from the time domain to the frequency domain opens up the possibility of spectral analysis. Being able to quantify where energy resides within the frequency domain is very useful in understanding the mechanisms that may be giving rise to noise generation, attenuation, or isolation and assists greatly in the diagnosis or design of the acoustic environment, or any sources of noise that are contributing to it.

Shaping the Acoustic Environment The basis of the measures answering questions about how the environment modifies the sound emitted by a source is the impulse response of a room, and this can be thought of as the signal that would be recorded after a short pulse of sound is introduced into a space (ISO3382-3, 2012). This signal comprises the sound that travels directly from the source to the measurement point, attenuated by spherical spreading. The direct sound will be followed by sound that has undergone one or more reflections from the room boundaries and any other surfaces present. These components travel further and so arrive later. Having undergone

Indoor Environmental Quality: Lighting and Acoustics

227

reflections, they would have lost acoustic energy and so will be quieter. This process continues until the process of absorption renders the acoustic field inaudible. The most commonly used measure to quantify the acoustic character of a space is the reverberation time (T; unit s), and this may be derived from the impulse response. It is defined as the time taken for the sound pressure in a room to decay by 60 dB, and is related directly to the volume of the space and indirectly to the effectiveness with which it is able to absorb acoustic energy at its boundaries. As a general rule, the larger a room is, the longer its reverberation time will be, as sound must travel further before it meets the room boundaries and is reflected back into the space. In a similar vein, rooms with more absorption will tend to have shorter reverberation times as the amount of energy removed on each reflection is greater. This relationship is useful when designing rooms, allowing the reverberation time to be dictated by selecting materials that provide sufficient absorption so as to balance the effect of room volume (ISO3382-3, 2012). Design targets for reverberation time are linked to the function that the room is intended to support (BB93, 2015). As a general rule, some reverberation is desirable. In fact, our experience leads us to expect that sound produced within interior spaces persists for a period after it is created. Additionally, reverberation helps to reinforce the direct component of the sound field and can be helpful in large spaces where people located far from the source can sometimes struggle to hear. However, while achieving an appropriate reverberation time is a key prerequisite for delivering an environment capable of supporting an effective acoustic field, it is not the sole criterion. Developments in the field of psychoacoustics have yielded a number of additional measures that help quantify the effectiveness of strategies intended to refine the design process. In a space for music, these help to inform decisions about how to distribute the audience relative to the performance, the geometry of the room and the materiality of its surfaces in terms of their reflective, absorptive, and diffusive properties. Conversely, the design of a space to support speech-based activities needs to provide a reverberation time that offers a balance between reinforcing the direct sound and masking it, and minimize extraneous sources of noisedhere intended as unwanted sound. The Speech transmission index (STI; dimensionless) is a measure that is frequently used to quantify the effectiveness of spaces and may be derived from the room impulse response measured in the presence of any background noise sources. Rated between 0 (“bad”) and 1 (“excellent”), this metric has been correlated with speech intelligibility, which is related to the human perception of speech. Given the impact that unwanted sound can have on the acoustic quality of a space, it is useful to look at measures to protect an environment from noise. In the case of the acoustic field surrounding a building, the positioning of physical barriers between the source and any vulnerable positions on the building façade (typically windows) can yield significant reductions in incident sound pressure levels. These barriers may be stand-alone structures (e.g., positioned close to the source or the receiver) or they may be provided in the building itself. The effectiveness of such strategies is related in the first instance to the change in path length (the difference in distance the sound has to travel from source to receiver before and after the intervention) and quantified as an insertion loss (IL; unit, dB). In almost all cases, the key features present in sound insulating construction are mass and continuity. This combination will reflect a significant proportion of the incident sound and seek to limit the vibration of the structure in response to the incident wave. The heavier the construction, the more effective this strategy is, and the greater the level of sound insulation provided. Mass can be traded off against isolation, if multiple leaf construction is used. Such an approach can yield high levels of sound insulation using relatively lightweight construction. The performance of acoustic separating elements can be quantified using the airborne sound reduction index (R; unit dB). This is defined as the difference in sound power level between the source side and the protected side of the construction. Furnished with the sound pressure level of the sound incident on the boundaries of the protected space, the sound reduction index may be used to estimate the transmitted sound pressure level, and hence whether target background noise levels have been achieved (ISO15712-1, 2005; ISO15712-3, 2005). Approaches that consider the direct transmission path between neighboring spaces offer an approximate, but often overestimated, picture of acoustic protection. The fact that any given structural element is typically connected to a number of others means that there are numerous additional paths via which sound can enter and exit the building fabric. This additional structural transmission will reduce the effective insulation offered by separating elements; however, it is possible to quantify (and so, account for) it in the design process (ISO10848-1, 2006). In addition to addressing risks posed by airborne sources of excitation, it is important also to consider the potential risk posed by direct excitation of the building structure. This has the potential to feed significant amounts of energy into the building fabric, which is then free to travel for relatively long distances as structural waves, often with little attenuation. The overarching strategy to counter this risk is to isolate the source of vibration from the building structure (ISO15712-2, 2005). The strategy outlined above provides a means of protecting highly sensitive spaces that are located within a building where maintaining structure borne sound within reasonable limits is the primary aim. Clearly, these approaches for protecting spaces from noise need to sit within a basket of strategies designed to ensure the wider environmental requirements of a space are met. Of these, provisions for lighting and ventilation have the greatest propensity to work against the needs for acoustic insulation. As a general rule, anything that threatens the integrity of the acoustic envelope presents a potential source of sound propagation risk, hence reinforcing the need for an integrated approach in the design of buildings that can effectively promote the comfort, performance, and health and well-being of their users.

Conclusions In Dec. 2015, almost 200 nations committed to the goal to “accelerate the reduction of global greenhouse gas emissions” (COP21, 2015), pushing the agenda of energy efficiency and carbon abatement to a core position in the construction industry. Yet, “buildings don’t use energy, people do!” (Janda, 2011). Occupants greatly impact buildings’ energy demands, exercising actions to achieve, restore, or

228

Indoor Environmental Quality: Lighting and Acoustics

maintain comfort in response to changes in their environment (Humphreys and Nicol, 1998). This, however, presents a substantial challenge, since one of the causes of the performance gap often detected between predicted and measured building energy expenditure relates to the yet incomplete characterization of the processes driving users’ responses to environmental stimuli (de Wilde, 2014). Although existing knowledge can provide guidance to the design process, the development of models to predict at design stage the users’ responses to IEQ parametersdand the consequent impact of their behaviors on buildings’ energy performancedis still at an infancy stage (Altomonte and Schiavon, 2013; Schiavon and Altomonte, 2014). Research and practice, in fact, have mostly focused on individual components of the indoor environment, this resulting in discrete performance indicators and distinct dose–response threshold values. Yet, to enhance human comfort and well-beingdand to allow energy savings in operationddesign strategies need to move beyond addressing and optimizing single parameters. For example, in terms of the luminous and aural environments, various studies have analyzed whether (and how) these physical forces may combine and synergistically interact, or rather antagonistically cancel each other, to influence occupants’ perception and behavior (Frassinetti et al., 2002; Liebl et al., 2012; Kaposvari et al., 2015). In essence, the design of comfortable and healthy buildings should be considered as a multifactor challenge that acknowledges the continuous and dynamic interactions between occupants and their environment, while also taking into account personal characteristics and inter/intraindividual differences (Parsons, 2000). Building occupants are exposed to whole “integrated” environments, whose design and assessment require consideration of both main (unimodal) and cumulative (crossmodal) effects between IEQ components. However, there are still several uncertainties in terms of how environmental parameters affect users, how people adapt and compensate for perceived discomfort, and how changes in building design and IEQ regulations can drive occupants’ comfort and well-being. Considering that most of the research to date has occurred under highly controlled laboratory conditions, there is a need to complement our knowledge on the effects of light, sound, and other environmental forces on building users in field applications, so as to deepen our understanding of the complex physical, physiological, and psychological processes underlying human perception and behavior in built spaces.

See also: Indoor Air Quality; Indoor Environmental Quality: Thermal Comfort; Indoor Environmental Qualitydventilation.

References Altomonte, S., 2009. Daylight for energy savings and psycho-physiological well-being in sustainable built environments. Journal of Sustainable Development 1 (3), 3–16. Altomonte, S., Kent, M., Tregenza, P., Wilson, R., 2016. Visual task difficulty and temporal influences in glare response. Building and Environment 95, 209–226. Altomonte, S., Rutherford, P., Wilson, R., 2015. Human factors in the design of sustainable built environments. Intelligent Building International 7 (4), 224–241. Special Issue: Workspaces Promoting Wellbeing. Altomonte, S., Schiavon, S., 2013. Occupant satisfaction in LEED and non-LEED certified buildings. Building and Environment 68, 66–76. Aries, M., Wienold, J., 2015. Lighting and daylighting for visual comfort and energy efficiency. In: Hopfe, C., McLeod, R. (Eds.), The Passivhaus designer’s manual: A technical guide to low and zero energy buildings. Routledge, Abingdon, OX, pp. 89–104. Augoyard, J.-F., Torgue, H., 2008. An instrumentation of the sound environment. In: Augoyard, J.-F., Torgue, H. (Eds.), Sonic experience: A guide to everyday sounds. McGillQueen’s University Press, Montreal, QC. BB93, 2015. Acoustic design of schools: Performance standards. Department for Education, London. Bell, J., Burt, W., 1995. Designing buildings for daylightdBR288. Building Research Establishment, London. Berson, D., Dunn, F., Takao, M., 2002. Photo-transduction by retinal ganglion cell that set the circadian clock. Science 295, 1070–1073. Boyce, P., 2014. Human factors factors in lighting, 3rd edn. CRC Press, New York. Boyce, P., Smet, K., 2014. LRT symposium ‘Better metrics forbetter lighting’. A summary. Lighting Research and Technology 46, 619–636. Brainard, G., et al., 2001. Action spectrum for melatonin regulation in humans: Evidence for a novel circadian photoreceptor. Journal of Neuroscience 21, 6405–6412. Burke, T., et al., 2015. Effects of caffeine on the human circadian clock in vivo and in vitro. Science Translational Medicine 7 (305), 305ra146. Chauvel, P., Collins, J., Dogniaux, R., Longmore, J., 1982. Glare from windows: Current views of problem. Lighting Research and Technology 14 (1), 31–46. CIE. (2014). International lighting vocabulary [Online]. Available from: http://eilv.cie.co.at/ (accessed 31.05.16). CIE, 2015. Technical note: Report on the first international workshop on circadian and neurophysiological photometry. Commission Internationale de l’Eclairage, Vienna. CIE, 2015. CIE statement on non-visual effects of light: Recommending proper light at the right time. CIEdCommission Internationale de l’Eclairage, Vienna. COP21, 2015. Adoption of the Paris agreement. United Nations Framework Convention on Climate Change, Paris. Cuttle, C., 2013. A new direction for general lighting practice. Lighting Research and Technology 45, 73–90. de Wilde, P., 2014. The gap between predicted and measured energy performance of buildings: A framework for investigation. Automation in Construction 41, 40–49. Delos Living, 2015. WELL building standard v1. Delis Living LLC, New York. Einhorn, H., 1979. Discomfort glare: A formula to bridge differences. Lighting Research and Technology 11 (2), 90–94. Emdad, R., et al., 1998. Psychophysiologic sensitization to headlight glare among professional drivers with and without cardiovascular disease. Journal of Occupational Health Psychology 3 (2), 147–160. EN 12464-1, 2011. Light and lightingdLighting of work places. European Committee for Standardization, CEN, Brussels. Enezi, J., et al., 2011. A “melanopic” spectral efficiency function predicts the sensitivity of melanopsin photoreceptors to polychromatic lights. Journal of Biological Rhythms 26 (4), 314–323. Frassinetti, F., Bolognini, N., Ladavas, E., 2002. Enhancement of visual perception by crossmodal visuo-auditory interaction. Experimental Brain Research 147 (3), 332–343. Frontczak, M., Wargocki, P., 2011. Literature survey on how different factors influence human comfort. Building and Environment 46, 922–937. Garrioch, D., 2003. Sounds of the city: The soundscape of early modern European towns. Urban History 30 (1), 5–25. Hedge, A., 2000. Where are we in understanding the effects of where we are? Ergonomics 43 (7), 1019–1029. Hopkinson, R., 1971. Glare from windows. Construction Research and Development Journal 2 (3), 98–105. Hopkinson, R., 1973. Glare from daylighting in buildings. Applied Ergonomics 3 (4), 206–215. Houser, K.W., Mossman, M.A., Smet, K.A.G., Whitehead, L., 2015. Tutorial: Color rendering and its applications in lighting. Leukos 12 (1–2), 7–26. Humphreys, M., 2005. Quantifying occupant comfort: Are combined indices of the indoor environment practicable? Building Research and Information 33 (4), 317–325.

Indoor Environmental Quality: Lighting and Acoustics

229

Humphreys, M., Nicol, J., 1998. Understanding the adaptive approach to thermal comfort. ASHRAE Transactions 104 (1), 991–1004. IPCC, 2014. Climate change 2014: Synthesis report. Contribution of working groups I, II and III to the fifth assessment report of the intergovernmental panel on climate change. IPCC, Geneva. ISO10848-1, 2006. AcousticsdLaboratory measurement of the flanking transmission of airborne and impact sound between adjoining roomsdPart 1: Frame document. International Organization for Standardization, Geneva. ISO15712-1, 2005. Building acousticsdEstimation of acoustic performance of buildings from the performance of elementsdPart 1: Airborne sound insulation between rooms. International Organization for Standardization, Geneva. ISO15712-2, 2005. Building acousticsdEstimation of acoustic performance of buildings from the performance of elementsdPart 2: Impact sound insulation between rooms. International Organization for Standardization, Geneva. ISO15712-3, 2005. Building acousticsdEstimation of acoustic performance of buildings from the performance of elementsdPart 3: Airborne sound insulation against outdoor sound. International Organization for Standardization, Geneva. ISO3382-3, 2012. AcousticsdMeasurement of room acoustic parametersdPart 3: Open plan offices. International Organization for Standardization, Geneva. Janda, K., 2011. Buildings don’t use energy: People do. Architectural Science Review 54, 15–22. Kaplan, R., Kaplan, S., 1989. The experience of nature: A psychological perspective. University of California Davis, Davis, CA. Kaposvari, P., et al., 2015. Audio–visual integration through the parallel visual pathways. Brian Research 1624, 71–77. Kent, M., Altomonte, S., Tregenza, P., Wilson, R., 2015. Discomfort glare and time of day. Lighting Research and Technology 47, 641–657. Kent, M., Altomonte, S., Tregenza, P., Wilson, R., 2015. Temporal variables and personal factors in glare sensation. Lighting Research and Technology. http://dx.doi.org/10.1177/ 1477153515578310. Lamb, S., Kwok, K., 2016. A longitudinal investigation of work environment stressors on the performance and wellbeing of office workers. Applied Ergonomics 52, 104–111. Lan, L., Wargocki, P., Lian, Z., 2014. Thermal effects on human performance in office environment measured by integrating task speed and accuracy. Applied Ergonomics 45 (3), 490–495. Lengen, C., 2015. The effects of colours, shapes and boundaries of landscapes on perception, emotion, and mentalising processes promoting health and well-being. Health and Place 35, 166–177. Liebl, A., Haller, J., Jödicke, B., Baumgartner, H., 2012. Combined effects of acoustic and visual distraction on cognitive performance and well-being. Applied Ergonomics 43, 424–434. Lockley, S., 2009. Circadian rhythms: Influence of light on humans. In: Squire, L. (Ed.), Encyclopedia of neuroscience, vol. 2. Elsevier Academic Press, Amsterdam, pp. 971–988. Lucas, M., et al., 2014. Measuring and using light in the melanopsin age. Trends in Neurosciences 37 (1), 1–9. Luckiesh, M., Guth, S., 1949. Brightness in the visual field at the borderline between comfort and discomfort. Illuminating Engineering 44 (11), 650–670. Mardaljevic, J., Hescong, L., Lee, E., 2009. Daylight metrics and energy savings. Lighting Research and Technology 41 (3), 261–283. Meek, C., Van Den Wymelenberg, K., 2014. Daylighting and integrated lighting design. Routledge, Abingdon, OX. Moon, P., Spencer, D., 1942. Illumination from non-uniform sky. Illuminating Engineering 37 (10), 707–726. Nabil, A., Mardaljevic, J., 2005. Useful daylight illuminance: A new paradigm for assessing daylight in buildings. Lighting Research and Technology 37 (1), 41–59. Nazzal, A., 2005. A new evaluation method for daylight discomfort glare. International Journal of Industrial Ergonomics 35, 295–306. Osterhaus, W., 2005. Discomfort glare assessment and prevention for daylight applications in office environments. Solar Energy 79, 140–158. Parsons, K., 2000. Environmental ergonomics: A review of principles, methods and models. Applied Ergonimics 31, 581–594. Peterbridge, P., Hopkinson, R., 1950. Discomfort glare and the lighting of buildings. Lighting Research and Technology 25 (2), 39–79. Provencio, I., et al., 1998. Melanopsin: An opsin in melanophores, brain, and eye. Proceedings of the National Academy of Science of the United States of America 95 (1), 340–345. Rea, M., 2015. The lumen seen in a new light: Making distinctions between light lighting and neuroscience. Lighting Research and Technology 47, 259–280. Reinhart, C., Mardaljevic, J., Rogers, Z., 2006. Dynamic daylight performance metrics for sustainable building design. Leukos 3 (1), 7–31. Robinson, W., et al., 1962. The development of the IES glare index system. Lighting Research and Technology 21 (1), 9–26. Rockcastle, S., Andersen, M., 2014. Measuring the dynamics of contrast & daylight variability in architecture: A proof-of-concept methodology. Building and Environment 81, 320–333. Schafer, R., 1977. The tuning of the world. Random House, London. Schiavon, S., Altomonte, S., 2014. Influence of factors unrelated to environmental quality on occupant satisfaction in LEED and non-LEED certified buildings. Building and Environment 77, 148–159. Schweizer, C., et al., 2007. Indoor timedMicroenvironmentdActivity patterns in seven regions of Europe. Journal of Exposure Science and Environmental Epidemiology 17 (2), 170–181. Sokolov, A., 1963. Higher nervous functions: The orienting reflex. Annual Review of Physiology 25, 545–580. Sorensen, K., 1987. A modern glare index method. Proceedings of 21st commission internationale de l’Eclairage. CIE, Venice. Thapan, K., Arendt, J., Skene, D., 2001. An action spectrum for melatonin suppression: Evidence for a novel non-rod, non-cone photoreceptor system in humans. Journal of Physiology 535 (1), 261–267. Tregenza, P., Loe, D., 2014. The design of lighting, 2nd edn. Routledge, Abingdon, OX. Tregenza, P., Wilson, M., 2011. Daylighting – Architecture and Lighting Design. Routledge, Abingdon, OX. Truax, B., 1978. Handbook for Acoustic Ecology. ARC Publications, Burnaby, BC. Truax, B., 2000. Acoustic Communication, 2nd edn. Praeger, Santa Barbara, CA. Tuaycharoen, N., Tregenza, P., 2005. Discomfort glare from interesting images. Lighting Research and Technology 37 (4), 329–341. Tuaycharoen, N., Tregenza, P., 2007. View and discomfort glare from windows. Lighting Research and Technology 39, 171–184. Ulrich, R., 1979. Visual landscapes and psychological well-being. Landscape Research 4 (1), 17–23. Ulrich, R., 1984. View through a window may influence recovery from surgery. Science 27 (224), 420–421. Vandewalle, G., Maquet, P., Dijk, D., 2009. Light as a modulator of cognitive brain function. Trends in Cognitive Science 13 (10), 429–438. Vos, J., 2003. Reflections on glare. Lighting Research and Technology 35 (2), 163–176. Wertheimer, M., 1961. Psychomotor co-ordination of auditory and visual space at birth. Science 134, 1692. WHO, 2011. Burden of disease from environmental noise: Quantification of healthy life years lost in Europe. World Health Organisation, European Centre for Environment and Health, Copenhagen. Wienold, J., Christoffersen, J., 2006. Evaluation methods and development of a new glare prediction model. Energy and Buildings 38 (7), 743–757.