The Impact of Building Windows on Occupant Well-Being: A Review Integrating Visual and Non-Visual Pathways with Multi-Objective Optimization

Abstract

This review investigates the role of building windows in supporting occupant well-being through access to natural views and daylight. This review synthesizes recent interdisciplinary research from environmental psychology, building science, and human physiology to examine how windows impact cognitive performance, psychological restoration, and circadian health. Drawing on 304 peer-reviewed studies from 2000 to 2024, the review identifies two core pathways: visual effects—related to daylight availability, glare control, and view quality—and non-visual effects—linked to circadian entrainment and neuroendocrine regulation via ipRGCs. These effects interact yet compete, necessitating a multi-objective optimization approach. This paper evaluates commonly used metrics for visual comfort, circadian-effective lighting, and view quality and discusses their integration in design frameworks. The review also highlights the potential of adaptive facade technologies and artificial window systems to balance human-centered lighting goals with energy efficiency. A research roadmap is proposed to support future integrative design strategies that optimize both visual and non-visual outcomes in diverse architectural contexts.

1. Introduction

The built environment, encompassing workplaces, residences, educational institutions, and healthcare centers significantly influences the well-being of occupants who spend nearly 80% of their time indoors. Windows, a ubiquitous element, exert a profound influence beyond simply controlling light and ventilation in indoor spaces. By providing natural light in controlled amounts and access to views of the outdoor environment [1], windows offer a potential solution to a growing concern: space occupants spend significant portions of time indoors and have underexposure to natural light and views [2]. This underexposure is linked to potential mental and physical health problems [3]. Therefore, researchers are increasingly interested in the correlation between window features and occupant well-being, recognizing the potential of windows to mitigate the negative effects of a primarily indoor environment [4]. The potential impact of windows on occupants’ well-being is worth further exploration, as clarified as follows.

First, window views may promote psychological restoration. The presence and type of view from office windows can significantly influence occupants’ connection to the natural world. Studies indicate that access to natural views may lead to reduced stress, a positive mood, and improved cognitive function [5]. Within this context, view access, view content, and view clarity were considered as three main factors of view quality [6]. Previous studies show that the complexity of psychological reactions to window views, with different compositions and elements, results in difficulties to evaluate the window view quality comprehensively.

While natural daylight offers numerous benefits, it is crucial to consider its intensity level, distribution, and the possibility of causing discomfort glare [7]. The daylight illuminance distributed across the indoor space varies with the climate, season, and time of day due to the sun’s dynamic position and the cloud coverage in the sky [8], which can influence the occupants’ task performance [9] and energy consumption for artificial lighting and air conditioning of the room [10]. Currently, simulation models of daylight have been developed to analyze the temporal-spatial changes of daylight [11].

Discomfort glare occurs when the amount of daylight is beyond the occupants’ needs. Excessive luminance or brightness creates a feeling of annoyance or discomfort and even impairs visual acuity [12]. This can be induced by direct sunlight entering through windows, reflecting off shiny surfaces, or a high luminance contrast between the window and the surrounding environment. Whether bright light is perceived as a glare source may depend on the occupants’ activities in the space. For instance, in the workspace, the bright sunlight through the window can cause veiling glare on the digital screens and paper [13]. When the workers are focusing on the task, the discomfort glare can also lead to eye strain, headaches, and fatigue, ultimately reducing workers’ productivity and well-being [14]. However, the bright sunlight through the window may not be rated as discomfort glare but be regarded as a scene of interest in a cultural center or a restaurant [15]. Therefore, the evaluation of visual comfort and discomfort glared caused by the building windows needs to be specified in terms of different spaces and occupants.

Furthermore, indoor daylight exposure via windows triggers non-visual or non-image-forming (NIF) responses in occupants through intrinsically photosensitive retinal ganglion cells (ipRGCs) [16]. Compared to artificial lighting, natural light offers a broader, more optimal spectrum and adequate intensity, contributing to its growing recognition for regulating circadian rhythms, promoting alertness, and potentially enhancing cognitive function [17]. In indoor spaces with limited natural light access, such as the patients’ rooms, offices, and classrooms, insufficient exposure may disrupt workers’ circadian rhythms, leading to decreased productivity, sleep disturbances, and negative moods [18].

The scope of the research, as presented in Figure 1, is concentrated on the investigation of both visual and non-visual pathways associated with daylight transmission through building side windows. Aspects such as indoor heat gain and acoustics related to daylight are beyond the scope of this research. Building upon numerous prior studies on the impact of windows on occupant well-being, this state-of-the-art review aims to synthesize and critically examine the existing literature. This study focuses on views and daylight exposure provided by building windows as independent variables and visual comfort, stress, attention, and circadian health as dependent variables. By analyzing these relationships, the impact of building windows on occupant physiological and psychological health through different pathways is investigated. This comprehensive review seeks to establish a deeper understanding of the potential benefits associated with well-designed office spaces. This knowledge can then inform architects, designers, and employers in creating work environments that prioritize worker well-being and optimize workplace productivity.

2. Material and Methods

To conduct this study, a comprehensive literature review was performed using the Web of Science Core Collection (WOSCC) database. The search covered the period from January 2000 to April 2024 and focused on publications across the disciplines of human physiology, environmental psychology, and building science. The entire process of literature identification, collection, and analysis was implemented following a structured protocol, as detailed below.

2.1. Literature Collection Strategy

Windows were conceptualized as architectural apertures that integrate environmental, physiological, and psychological functions. As part of the building envelope, windows contribute to visual and thermal comfort, energy performance, and human well-being by enabling daylight entry, outdoor views, and ventilation. In this study, the focus was placed on three core visual effects of windows:

(a)

As restorative view channels fulfilling biophilic needs.

(b)

As glare sources affecting visual task performance.

(c)

As light exposure elements influencing circadian health.

Based on this, four research questions were formulated to guide the search strategy:

(1)

How has the research evolved in different disciplinary domains over time?

(2)

How do windows contribute to psychological restoration in workplace settings, and what window characteristics influence this effect?

(3)

How does daylight through windows affect visual comfort, and how is discomfort glare quantified?

(4)

How does daylight exposure through windows support circadian health, and what are the design parameters that influence entrainment?

To capture relevant literature, we developed a Boolean logic search string, applied to the “Topic” field, (including title, abstract, author keywords, and Keywords Plus), using the following logic:

(“building window” OR aperture OR fenestration OR “window glazing”) AND

(“connection to outdoor nature” OR “view out” OR “view to nature” OR “nature exposure” OR “window view” OR “nature view” OR “view quality” OR daylight OR “Biophilic Design” OR greenery OR daylighting OR “natural light” OR glare OR “discomfort glare” OR “visual comfort” OR “visual discomfort” OR “Daylight illuminance” OR illuminance OR luminance OR “circadian lighting” OR “circadian system” OR “circadian rhythm” OR “circadian stimulus” OR “non-image forming effect of light” OR “equivalent melanopic lux” OR “melanopic Equivalent Daylight Illuminance”) AND

(“public health” OR health OR well-being OR well-being OR recovery OR restoration OR stress OR productivity OR attention OR “task performance” OR “cognitive performance” OR cognition OR mood OR emotion OR “circadian rhythm” OR “circadian health” OR eyestrain OR headache)

The following filters were applied during the literature search: the time span was set from 2000 to 2024; the language was limited to English; only articles and review papers were included as the document type; and the research areas were restricted to Environmental Sciences, Architecture, Psychology, Engineering, and Public Health to ensure relevance to the interdisciplinary scope of this study.

Studies were included if they met the following criteria: (a) they investigated a building window or simulated window as either a view portal or a source of light exposure; (b) the research setting was indoors during daytime, under either real or simulated daylight conditions. Conversely, studies were excluded if they focused exclusively on outdoor spaces or non-daylit interiors or were otherwise unrelated to human-centered window performance. The workflow of the literature screening process was presented in Figure 2.

This initial query returned 581 publications; then, 277 works were filtered or screened out. The remaining 304 papers were imported into bibliometric software and further screened manually based on predefined criteria.

2.2. Bibliometric Analysis

As a widely used method for the description and analysis of published papers, bibliometrics uses citations, keywords, and publication data to track trends, identify influential works and researchers, and understand the overall landscape of a particular field with the help of mathematics and statistics to quantify the distribution pattern of literature. In this study, the bibliometric analysis software, CiteSpace 5.7.R6 (USA) and VOS viewer (NL), were used to show the original distribution pattern with interconnections and clusters of the keywords in the time zone with a period of 22 years and 304 literature records.

In CiteSpace, the bibliometric analysis was performed over the period of 2000–2024 using one-year time slices. Keywords and cited references were selected as the primary node types to capture thematic trends and influential publications. The thresholding strategy followed g-index scaling (top items per slice), and clustering was performed using the Log-Likelihood Ratio (LLR) algorithm. To enhance the clarity of the visual network, pruning techniques such as Pathfinder and sliced network pruning were applied.

In VOSviewer, keyword co-occurrence and citation network visualizations were generated to reveal key thematic domains and author/institution collaboration patterns. A manual review of the most cited clusters and emerging keywords was then conducted to synthesize trends and align them with the three primary research areas: biophilic views, visual comfort, and circadian lighting.

3. Bibliometric Analysis Results

3.1. The Development Process of Building Window Research

The annual number of publications, as shown in Figure 3, reflects that the development of research related to the impact of windows on humans can be divided into three stages. The first stage is in the period before 2007. There were few studies closely related to this topic at that time. Then, at the second stage, from 2008 to 2017, the average growth rate of publications was 54.5%, with about five articles a year. In the last stage, from 2018 to date, there is a rapid growth with an average of 27 articles/year, increasing from nearly 55 to 235 articles with a growth rate of 45.7%.

Meanwhile, the ratio of different window-related topics reflects the priority of researchers’ concerns. At the first and second stages, the visual impact of window daylight was the main concern. Numerous studies explored the quantitative indexes of discomfort glare caused by daylight and validated them in the laboratory and field, especially in classrooms and offices. “Window view” also emerged in several articles but was mostly considered as an element in a comprehensive evaluation of indoor space quality or spatial comfort. The non-visual effects of light (or circadian lighting) suddenly became a part of window research in 2015, when the quantification of the circadian effectiveness of light launched in the indoor lighting area. After 2019, the number of publications related to the psychological impact of window view quality increased, especially focused on the scenes of workspace and domestic space.

Among the research areas shown in Figure 4, most articles are published in the fields of construction and building technology (125 articles), engineering (112 articles), civil engineering (89 articles), social science (SSCI, 67 articles), environmental studies (62 articles), and energy and fuels (54 articles) in the past twenty years. A small portion of articles were published in the areas of “public, environmental, and occupational health” (20 articles), optics (18 articles), and psychology (12 articles). Recently, some also emerged in areas of urban studies (22 articles), green and sustainable science and technology (21 articles) in the latest years. The articles on engineering and environmental studies show a relatively higher centrality, indicating better concentration on the topic. It is worth mentioning that as a comprehensive subject involved in multidisciplinary research, some articles cross areas of engineering [19,20,21], psychology [22,23,24], and social science [25,26] exhibiting multidisciplinary research.

Accordingly, articles were published in various journals corresponding to different research areas, as shown in Figure 5 and

Table 1. Publication source of the articles.

Source	Count	Citations	Link
Building and Environment	49	1672	6265
Energy and Buildings	22	744	2713
Sustainability	12	108	1394
Buildings	9	36	1290
International Journal of Environmental Research and Public Health	9	421	1267
Leukos	9	262	1999
Indoor and Built Environment	8	108	716
Journal of Building Engineering	8	111	1197
Lighting Research & Technology	7	264	1620
Solar Energy	7	66	817
Energies	6	58	632
Urban Forestry & Urban Greening	6	227	838
Applied Sciences-Basel	4	15	926
Environment and Behavior	4	159	674
Landscape and Urban Planning	4	71	478
Applied Energy	3	325	301
Building Research and Information	3	252	144
Building Simulation	3	18	250
Chronobiology International	3	33	323
Journal of Environmental Psychology	3	16	453
Proceedings of The CIE Conference	3	4	363
Renewable & Sustainable Energy Reviews	3	252	835
Science and Technology for The Built Environment	3	12	579
Scientific Reports	3	7	462

. Eight journals belong to the building research area, among which “Building and Environment” published the most (49 articles in total) and was cited 1672 times, making the greatest link strength with other journals. Following it is “Energy and Buildings” with 22 articles, 744 citations, and the second-highest link strength. In the lighting area, “Leukos” and “Lighting Research & Technology” have a similar number of publications and citations, with fewer than ten papers and over 260 citations. Then, in the energy area, “Applied Energy” and “Renewable & Sustainable Energy Reviews” have only three papers, but have over 325 and 252 citations, respectively. Moreover, in the environmental psychology research field, three journals published 16 articles with nearly 600 citations. Similarly, two journals in the urban and landscape research area published ten papers with nearly 300 citations. Other journals in the medical research area and comprehensive studies have fewer publications with lower citations.

Among different countries, researchers in the USA were the first to begin investigating the topic in 2002. They have also published the most papers on the subject, accounting for approximately 20% of the global total. China ranks second with roughly 10% of the publications, although their research began in 2014, about twelve years later than the USA. Excluding South Korea, Canada, and Norway, other countries initiated research after 2014, and they all contribute less than 5% of the total publications. Research conducted in various countries or locations with diverse climates and contexts may yield differing results regarding the impact of windows in buildings, as shown in Figure 6.

In co-occurrence analysis of keywords shown in

Table 2. The co-occurring keywords and the frequency of main keywords.

Co-Occurrence of Keywords
Density of Co-Occurrence Keywords
Main Keywords with High Frequency
Keywords	Count	Centrality	Year
visual comfort	85	0.08	2009
mental health	83	0.04	2004
daylight	76	0.05	2008
window view	67	0.14	2004
performance	57	0.08	2007
health	55	0.03	2007
workplace	52	0.06	2003
energy efficiency	50	0.06	2014
window	49	0.13	2004
bright light	49	0.16	2002
circadian rhythm	49	0.15	2002
impact	44	0.08	2012
simulation	43	0.09	2008
exposure	43	0.18	2002
design	36	0.05	2014
environment	35	0.09	2007
biophilic design	33	0.03	2009
building	26	0.08	2009
thermal comfort	21	0.06	2013
sleep	19	0.03	2017
preference	16	0.02	2016
satisfaction	15	0.09	2004

, “Daylight” and “daylighting” are highly connected to “visual comfort”, “discomfort glare”, “health”, and “performance”, around which are “shading devices”, “window design”, “luminance”, “illuminance”, and “offices”. Then, “window view” was linked with “sunlight”, “recovery”, “landscape”, “preference”, “anxiety”, “depression”, “wellbeing”, and “exposure”. Meanwhile, “exposure” is a bridge word between “health” and “sleep” along with “retinal ganglion cells”, “melatonin”, “phase”, “therapy”, “circadian lighting”, and “action spectrum”. Between “sleep” and “daylight”, “light”, “daylighting”, “system”, and “circadian stimulus” were nested. Moreover, the density of co-occurrence keywords shows a high density of co-occurring keywords in the group of “visual comfort”, “performance”, “daylight”, followed by the group of “health”, “window view”, and “recovery”. The publication number is lower in “sleep” and “exposure” group.

The Table 2 also presents the most frequently occurring keywords, among which, “visual comfort”, “mental health”, “daylight”, “window view”, “performance”, “health”, “workspace”, and “energy efficient” are counted over 50 times. Except for “energy efficient”, other keywords with high frequency mostly occurred before 2010. The main keywords could be classified into independent variables related to windows (such as daylight, window view, workplace, bright light, and biophilic design), dependent variables of humans (visual comfort, mental health, performance, circadian rhythm, thermal comfort, sleep, preference, and satisfaction), and other issues (energy efficiency, simulation, and design).

Figure 7 visualizes the keywords with the strongest citation bursts over the past two decades, indicating periods of heightened scholarly attention. The keywords that recorded the strongest citation bursts show that “mental health” has the greatest strength (4.03), which began in 2020. Other keyword citations, such as “design” (3.5), “impact” (3.39), “biophilic design” (2.15), and “green space” (1.87), began in the same year but have less strength. The “Roller shade” had the earliest citation bursts in 2012 and ends in 2019 with a strength of 2.19. The citation bursts of “discomfort glare”, “daylit space”, and “validation” began in 2016 and ended in 2019 with the strengths of 2.71, 2.19, and 1.85, respectively. Moreover, “benefit”, “sleep”, “exposure”, and “circadian lighting” began in 2016 and ended in 2023, with the strengths of 2.25, 2.02, 1.93, and 1.82, respectively. Notable high-impact terms include mental health (4.03), design (3.50), and impact (3.39), all emerging around 2020 and reflecting a shift in research priorities toward well-being-centered and integrative window/daylighting strategies. The emergence of terms such as circadian lighting, roller shade, and discomfort glare further suggests a growing focus on both non-visual and visual comfort dimensions in recent years.

Figure 8 presents a timeline-based visualization of co-occurring keywords, grouped into thematic clusters and plotted along a temporal axis using CiteSpace. It shows the first topic of “#0 visual comfort” of the window has the largest cluster and began in 2004. It concerned health related issues, such as “wellbeing”, “mental health”, “work stress” in the past twenty years, during which, the “indoor plant”, “preference”, “behavior”, and “vegetation” were recognized as influential elements. The second topic of “#1 light exposure” from window daylight was likely based on “metric”, “phase”, and “simulation”. Then ten years later, the topic concerns more on “façade” (or “glass window”) and its interaction with “solar power”. The third topic, “#2 discomfort glare” of window daylight, concerns “UV control”, “performance” and “perception” of space occupants before 2010. Then, “roller shade”, “daylight space” and “optimization” was concerned in 2016. Finally, the research direction shifted to “Electrochromic glazing” and “smart window” recently. The fourth topic of “#3 window view” began in 2004; it became a “social issue”, concerning “privacy in public” and “community” in 2007. Then, after 2019, it began to concern “green space”, “urban”, and “greenery”. The fifth topic of “#4 energy savings” began in 2004 concerning satisfaction and ended in 2013. The “#5 Sleep” is the last topic concerning “exposure”, “circadian rhythm”, and “bright light” in 2002, then in 2016, it related to “stroke patient”, “action spectrum”, and “therapy”.

By analyzing the reference record of the search, the source of the fundamental theory related to the visual-related impact of windows could be tracked, as shown in

Table 3. The most cited references by the included studies (Web of Science).

	Author	Time	Title	Journal	Citation	Link
The impact of window view	Ulrich RS [27]	1984	View through a window may influence recovery from surgery	Science	62	229
	Aries MB et al.	2010	Windows, view, and office characteristics predict physical and psychological discomfort.	J. Environ. Psychol.	43	192
	Ulrich RS et al. [22]	1991	Stress recovery during exposure to natural and urban environments.	J. Environ. Psychol.	42	165
	Kaplan S [29]	1995	The restorative benefits of nature: Toward an integrative framework.	J. Environ. Psychol.	39	164
	Leather P et al.	1998	Windows in the workplace: Sunlight, view, and occupational stress.	Environ. Behav.	28	137
	Kaplan R [30]	2001	The nature of the view from home: Psychological benefits.	Environ. Behav.	29	109
	Chang CY	2005	Human response to window views and indoor plants in the workplace.	HortScience	24	107
	Kaplan R	1993	The role of nature in the context of the workplace.	Landscape Urban Plan	18	96
	Sop Shin W [2]	2007	The influence of forest view through a window on job satisfaction and job stress. Scandinavian journal of forest research.	Scand. J. For. Res.	19	91
	Li D et al.	2016	Impact of views to school landscapes on recovery from stress and mental fatigue.	Landscape Urban Plan	18	90
	Ko WH et al. [6]	2020	The impact of a view from a window on thermal comfort, emotion, and cognitive performance.	Build Environ	22	84
	Markus TA [28]	1967	The function of windows—A reappraisal.	Building Science	16	79
	Berto R	2005	Exposure to restorative environments helps restore attentional capacity.	J. Environ. Psychol.	15	76
The visual comfort of window daylight	Wienold J et al.	2006	Evaluation methods and development of a new glare prediction model for daylight environments with the use of CCD cameras.	Energ Buildings	48	146
	Reinhart CF et al. [31]	2001	Validation of dynamic RADIANCE-based daylight simulations for a test office with external blinds.	Energ Buildings	23	99
	Reinhart CF et al. [32]	2006	Dynamic daylight performance metrics for sustainable building design.	Leukos	23	96
	Nabil A et al. [33]	2006	Useful daylight illuminances: A replacement for daylight factors.	Energ Buildings	34	86
	Nabil A et al. [34]	2005	Useful daylight illuminance: a new paradigm for assessing daylight in buildings.	Lighting Res Technol	24	82
	Galasiu AD et al.	2006	Occupant preferences and satisfaction with the luminous environment and control systems in daylit offices: a literature review.	Energ Buildings	21	77
	Jakubiec JA et al. [35]	2012	The ‘adaptive zone’–A concept for assessing discomfort glare throughout daylit spaces.	Lighting Res Technol	17	76
	Carlucci S et al. [36]	2015	A review of indices for assessing visual comfort with a view to their use in optimization processes to support building integrated design.	Renew Sust Energ Rev	24	72
	Reinhart CF et al. [37]	2011	The daylighting dashboard–A simulation-based design analysis for daylit spaces.	Build Environ	15	65
	Hopkinson RG [38]	1972	Glare from daylighting in buildings.	Appl Ergon	19	58
The NIF effect of window daylight	Lucas RJ et al.	2014	Measuring and using light in the melanopsin age.	Trends Neurosci	37	177
	Thapan K et al. [39]	2001	An action spectrum for melatonin suppression: evidence for a novel non-rod, non-cone photoreceptor system in humans.	J. Physiol.	34	163
	Berson DM et al. [40]	2002	Phototransduction by retinal ganglion cells that set the circadian clock.	Science	34	153
	Brainard GC et al. [41]	2001	Action spectrum for melatonin regulation in humans: evidence for a novel circadian photoreceptor.	J Neurosci	31	153
	Rea MS et al. [42]	2012	Modelling the spectral sensitivity of the human circadian system.	Lighting Res Technol	22	125
	Figueiro MG et al. [43]	2017	The impact of daytime light exposures on sleep and mood in office workers.	Sleep Health	24	121
	Rea MS et al. [44]	2005	A model of phototransduction by the human circadian system.	Brain Res. Rev	19	107
	Boubekri M et al.	2014	Impact of windows and daylight exposure on overall health and sleep quality of office workers: a case-control pilot study.	J. Clin. Sleep Med.	20	100
	Andersen M et al.	2012	A framework for predicting the non-visual effects of daylight–Part I: photobiology-based model.	Lighting Res Technol	20	84
	Khalsa SB et al.	2003	A phase response curve to single bright light pulses in human subjects.	J. Physiol.	16	84
	Viola AU et al.	2008	Blue-enriched white light in the workplace improves self-reported alertness, performance and sleep quality.	Scand J Work Env Hea	20	83
	Acosta I et al.	2017	Analysis of circadian stimulus allowed by daylighting in hospital rooms.	Lighting Res Technol	15	79
	Rea MS et al.	2018	Light as a circadian stimulus for architectural lighting.	Lighting Res Technol	17	71

. The top cited sources can be classified into three topics: the impact of window views, the visual comfort of window daylighting, and the non-image-forming (NIF) effect of window daylighting, as shown in

Table 4. Benchmark values for window view in EN 17037 standard [45].

Variables	Degree of Visual Linkage
	At Least	Middle	High
Horizontal view angle depending on window width	>14°	>28°	>54°
Distance of external obstacles from the structure	>6 m	>20 m	>50 m
Layers that must be visible from at least 75% of the used area -Sky -Landscape (artificial and/or natural) -Floor	Landscape layer included	Including at least two layers	All layers included

. In the topic of window views, Ulrich’s work [27] is the earliest research (published in 1984) with the most impact (published in Science and cited 62 times in those 250 publications) and the greatest link strength (229). Before that, Markus [28] published the earliest paper with impact in this area in 1967 in Building Science. In the period before 2000s, Ulrich [22,27], Kaplan [29], and Kaplan [30] devoted most work in journals related to environmental psychology. After 2010, the research with a fair impact gradually published in the area of building research. The most recent highly influential source is by Ko et al. [6], published in Building and Environment in 2020, with 20 citations in the present dataset and a total link strength of 84.

In the domain of visual comfort related to window daylight, Reinhart et al. [31,32,37] made notable contributions with three key publications, while the work of Wienold et al. [46] received the highest number of citations among the retrieved articles. The cited sources in this area concentrated on discomfort glare rating metrics, daylight simulation, and measurement. Hopkinson [38] authored one of the earliest influential articles on glare in 1972. Nabil et al. [33,34] published two articles to exhibit and promote the use of “useful daylight illuminances” in 2005 and 2006. The most recent highly cited contributions were made by Jakubiec et al. [35] and Carlucci et al. [36], both published nearly a decade ago.

The development of research in the topic of the non-image-forming (NIF) effect of window daylighting was relatively later when compared to the other two research topics. The original sourced research is from Thapan et al. [39], Berson et al. [40], and Brainard et al. [41], they identified an unknown circadian photoreceptor system in human eyes at that time and found an action spectrum of light to regulate the human melatonin. Since then, the NIF of light and the quantification of circadian-effective light in daylight has become an important issue in the research on the impact of building windows. Rea et al. [42,44], and Figueiro et al. [43] bridged the gap between the physiological theory and the engineering of buildings and lighting from 2012 to 2018. They devoted several articles to quantifying the circadian light received by human eyes and applied the quantification method to the field of indoor spacse.

3.2. The Psychological Impact of Window View

Indoor window views of natural elements—such as greenery, sky, and water—are increasingly recognized for their capacity to elicit positive psycho-physiological responses through several interrelated mechanisms. Ulrich’s Stress Recovery Theory (SRT) [47] posits that exposure to natural scenes evokes immediate emotional relief and facilitates physiological recovery by reducing stress-related indicators such as blood pressure and heart rate. Complementarily, Kaplan and Kaplan’s Attention Restoration Theory (ART) [29] explains that natural environments engage involuntary attention, allowing the recovery of directed attention and mitigating cognitive fatigue. These restorative effects are underpinned by the biophilia hypothesis [48], which suggests an innate human affinity for nature that enhances psychological comfort, cognitive clarity, and emotional well-being in built environments.

Empirical research into the psychological impact of window views originated from Ulrich’s study [27] in 1984, which found that postoperative patients with natural views from their hospital rooms experienced shorter stays, required fewer potent analgesics, and received more favorable evaluations from nursing staff. These findings indicated that indoor natural views could dampen sympathetic nervous system activity, promote parasympathetic recovery, and provide a cognitive distraction from pain and clinical stress [47]. Subsequent studies extended this inquiry to workplaces, educational and residential settings, where window views were found to reduce employee stress and enhance attention restoration in students—contexts marked by sustained cognitive and emotional demands. For workers, intermittent exposure to nature through windows enables micro-restorative experiences and fosters mental detachment during breaks, thereby enhancing resilience to occupational stress [1,2]. For students, such views support attentional functioning, increase environmental satisfaction, and potentially boost learning motivation [49,50]. Among residential populations, particularly individuals with reduced mobility such as older adults, natural window views offer a crucial form of passive nature exposure that contributes to mood regulation and psychological resilience [51,52].

Recognizing that windows are not the sole conduit for biophilic stimuli, researchers later explored alternatives such as indoor plants [53] and vertical greenery [54] to replicate the restorative effects of natural views. More recently, emotional and mood-related responses to view quality have also gained attention, particularly during the COVID-19 pandemic [52,55], when indoor visual environments played a critical role in mental well-being.

Among the researched papers (N = 112), 72 of them are empirical studies regarding window view quality as the independent variable (IV) and occupants’ satisfaction, mental health, and physical health as the dependent variables (DV). Nearly 42% of the papers are based on field investigations using questionnaires to measure satisfaction and well-being subjectively, as shown in

Table A1. Field or online investigation on the restorative effects of window view.

Author	Location	Space	Sample Size	View Feature (as Independent Variables)	Responded Measures (as Dependent Variables)
Sop Shin W (2007)	Korea	Office	931	Existence of forest views through windows in workplaces and absence of forest views through windows in workplaces.	Job satisfaction and stress
Lottrup L et al. (2013)	Sweden	Office	439	Views with different workplace greenery index (WGI)	Stress and workplace attitude
Lottrup L et al. (2015)	Denmark	Office	402	Window view with different element	Job satisfaction and well-being
Gilchrist K et al. (2015)	UK	Office	366	Explore the impact of viewing and using greenspace	Employee well-being
Raanaas RK et al. (2016)	Norway	Healthcare center	16	Indoor plants and view of nature	Relaxation and emotion
Bjørnstad S et al. (2016)	Norway	Office	565	Different indoor nature contact	Less job stress: (B = −0.18, CI = −0.318 to −0.042) Less subjective health complaints: (B = −0.278, CI = −0.445 to −0.112) Less sickness absence: (B = −0.061, CI = −0.009 to −0.002)
Dreyer BC et al. (2018)	Canada	Office	213	Window view: with vs. without view	Well-being Psycho-environmental potential
Wang CH et al. (2019)	Taiwan	Hospital	296	Windows with different daylight exposure and window	Satisfaction of window view, dosage of PCA use (p = 0.057), perceived pain (BPI) (p = 0.046), pain severity (p = 0.004)
van Heezik Y et al. (2020)	New Zealand	Home	72 (elder)	Different nature engagement	Emotion or mood
Chang CC et al. (2020)	Singapore	Home and office	1262	Frequency, duration, and diversity of nature experiences Presence or absence of nature views from windows Natural space coverage	Life satisfaction, nature experience, and connection with nature
Dzhambov AM et al. (2021)	Bulgaria	Home	323	Indoors greenery experienced: with vs. without	Restorative quality
Mihandoust S et al. (2021)	USA	Hospital	625	View from the bed position: with window vs. without window	Satisfactory with the stay and care
Raanaas RK et al. (2021)	Norway	Hospital	278 (patient)	Three window view: blind vs. panoramic nature view vs. partially nature view blocked by buildings	Mental health
Kley S et al. (2021)	Germany	Home	1886	Different presence of green elements in window view	Satisfaction and reconsidering residential relocate
Pearson AL et al. (2021)	USA	Home	56 (63yr)	Different contacts with nature: outdoor vs. indoor or near-home	Relief stress: nature window view (84%) vs. images of nature (71%) vs. audio of nature through window (66%)
Yusli NA et al. (2021)	Malaysia	School	192	Window view different presence of nature elements	Psychological well-being, perceived restorativeness for activity
Mintz KK et al. (2021)	Isreal	Home	776	Different contact with nature: nature near home vs. nature viewed from home windows vs. being in nature on the preceding day	Well-being measures (positive affect, negative affect, vitality, happiness, and stress)
Liu C et al. (2022)	China	Home	3401	Different types of window view: waterscape vs. green plants vs. buildings	Subjective evaluation releasing anxiety the satisfaction of window view: waterscape (2.98), followed by green plants (2.33) and buildings (0.83)
Mascherek A at al. (2022)	USA	Hospital	244 (patient)	Two window view (building vs. green space) Different intensity of window daylight	Length of stay
Garrido-Cumbrera M et al. (2022)	Spain	Home	3109 (39.7 yr)	Quality of view from home, use of window views, elements of nature in the home, and views of green or blue spaces from home	Well-being and depression
Bi W et al. (2022)	China	Home	508	Green view (degree of window greenness, average daily frequency of looking out the window, and duration of looking out the window)	Mental health (depression and anxiety)
Zhang Z et al. (2023)	China	Home	1331	Five different views: open green space vs. partly open green space vs. closed green space vs. partly open blue space vs. partly open squares	Exposure to home greenery, psychological statement, landscape preference
Li H et al. (2024)	China	-	292 (students)	Different number of trees seen from the window: less than three vs. three or more	Nature connectedness, mental well-being (B = 2.462; 95%CI = 1.469 to 3.464; p < 0.01)
Zhang J et al. (2024)	China	Home	1007	Window view with different green volume ratio GVR, green window ratio GWR	Sleep quality

of Appendix A. Before 2018, most research [1,2,24,25,26,56] based on the scenario of the workplace focused on employees’ well-being (N = 2916 in total). In those studies, the IV was set to “with a window view vs. without window view” or “presence of outside greenery vs. absence of outside greenery”. Correspondingly, the DV was set to “job satisfaction or workplace altitude”, “job stress or health complaints”, and comprehensive evaluation of “wellbeing”. They proved window views with natural elements might trigger restorative effects on space occupants. Some research [24] also considered “personal nature contact” as a mediating variable between the independent and dependent variables. After 2019, homes and hospitals were recognized as crucial spaces demanding for spatial comfort and health promoting elements, then, more investigations were conducted on patients and residents [57,58,59,60]. The IV setting became more precise, considering the layout (shape, size, and height) and texture (with blinds or tinted glaze) of the window and the elements’ composition (ratio of nature elements, such as sky, plants, and water, view distance, and building distance) of the view. The DV focused more on mood disorders in mental health and suggested mechanisms behind the impact: the mental health-supportive effects of indoor greenery can be explained by increased feelings of being away while in indoor spaces [61]. A recent study also considered sleep quality as a DV for elderly residents [62].

Meanwhile, the other 58% of the related papers are based on experiments to measure the psychological and physiological effects in the scenarios of classrooms, offices, hospitals, and homes, as shown in

Table A2. Experiment implemented on the restorative effect of window view.

Reference	Location	Space	Sample Size	Duration	View Feature (IV)	Baseline	Measures (DV)	DV- Psy	DV-Physil
Chang CY et al. (2005)	Taiwan	Office (virtual)	38 (student)	15 s	6 indoor views (3 without windows, and 3 with different window views)	Without window view or indoor plants	EEG, EMG, BVP, and state-anxiety	+	+
Friedman B et al. (2008)	USA	Office (field)	7	16 weeks	-	-	Window impression, work performance and health, social interaction related to the window	+
Konstantzos I et al. (2015)	USA	Small room (field)	18	-	14 shading fabrics of different transparency and color	-	Impressions of clarity or view, visibility, view accuracy	+
Li D et al. (2016)	USA	School (field)	94 (student)	-	3 views (without window, with window view to building façade, with window to green space	No window	Attentional function and physiological stress	+	+
Nejati A et al. (2016)	USA	Hospital (virtual)	958	-	Direct access to the outdoors through a balcony, an outdoor view through a window, a nature artwork, and an indoor plant	No nature element	Restorative value	+
Mangone G et al. (2017)	Netherland	Office (virtual)	64 and 33	-	11 indoor and 5 outdoor scenes	-	Work activity evaluation and space perception	+
Wang R et al. (2018)	China	School (virtual)	323 (23.1 yr)	-	20 images of campus and 15 images of classroom	-	Self-rating method of SRRS of emotion, physiology, cognition, and behavior.	+
Olszewska-Guizzo A et al. (2018)	Singapore	Virtual	29	23 min	36 images of window view with different green coverage and floor level	-	EEG		+
Jamrozik A et al. (2019)	USA	Office (field)	10	2 weeks	Mesh shades vs. dynamic tint vs. blackout shade	Blackout shade	Cognitive function satisfaction eyestrain	+	+
Vásquez NG et al. (2019)	Brazil	School (virtual)	84 children	-	Different types of window view	-	Preferred type of view	+
Chung WK et al. (2019)	Hong Kong	Virtual	46	-	20 scenarios of window view (12 scenarios in different distance between buildings) and 8 scenarios of window view with audition	-	Perceived oppressiveness and noise annoyance	+
Chamilothori K et al. (2019)	Switzerland	Office (virtual)	72 (25.9 yr)	30 min	Three façade mode (irregular, regular, and blinds), two context scenarios (work and social)	A neutral scene without window view	Subjective evaluations (how pleasant, interesting, and exciting the space was perceived) and physiological responses (heart rate and skin conductance)	+	+
Yeom S et al. (2020)	Korea	School (virtual)	37	3 min	WWR (20%, 40%, 60%, and 80%)	-	Satisfaction	+
Yin J et al. (2020)	USA	Office (virtual)	100	6 min	With or without windows, with or without indoor plants	No biophilic condition	Physiological acute stress reaction psychological indicator of anxiety	+	+
Ko WH et al. (2020)	USA	Office (field)	86	1 h	With and without windows.	Without windows	Subjective evaluations (e.g., thermal perception, emotion), skin temperature and cognitive performance tests	+	+
Gao C et al. (2020)	China	Hospital (virtual)	54	-	Window or digital nature, outdoor green window view, or indoor plants, warm color wall or cold color wall	-	Skin conductance and perceived restorative outcomes (psychological measurement)	+	O
Nezamdoost A et al. (2020)	USA	Hospital (virtual)	442	-	2000 view photos	-	View quality score	+
Elsadek M et al. (2020)	China	Office (field)	30	5 min	Window view of green space.	Window view of urban space	EEG, heart rate variability, and skin conductance. mood and feelings	+	+
Engell T et al. (2020)	Norway	-	9	10 min	Window view of a natural environment	Plain interior wall without window view	Choice reaction time (CRT) and heart rate variability (HRV)	+	+
Masoudinejad S et al. (2020)	Iran	Virtual	212 (students)	20 min	Window box with view to sky and outdoor greenery	-	Restorative quality (being away, fascination), restoration likelihood, or preference	+
Drobne S et al. (2021)	Slovenia	School (virtual)	135	-	20 different view contents (natural vs. urban views, building distance)	-	Positive and negative reaction	+
Schmid HL et al. (2021)	Germany	Home (virtual)	87	-	Different composition of window view	-	View preference	+
Rodriguez F et al. (2021)	Australia	Office (virtual)	48	40 s	View types (i.e., corridor, courtyard, roof, and wall)	-	Preference and restoration questionnaires	+
Fikfak A et al. (2022)	Slovenia	-	88 (student)	-	5 window view with different distances and greenery	-	Window view quality	+
Mihara K et al. (2022)	Singapore	-	26	5 min	Closed blind and window view	Close blind condition	Skin temperature, skin conductance, heart-rate variability, EEG, and cognition test	+	+
Jiang Y et al. (2022)	China	Office (field)	20	40 min	With and without window view, and three temperatures	-	Arterial oxygen saturation (SpO2) and heart rate variability (HRV), and subjective questionnaires.	+	+
Zhang M et al. (2023)	China	-	95	-	18 shapes, 3 views	Blank view	Visual preference	+
Sharam LA et al. (2023)	Australia	Office (virtual)	55 and 57	-	Window with nature view, window with blinds	No window condition	Cognitive function, creativity, alertness, and executive attention		+
Rhee JH et al. (2023)	Korea	Office (field)	30	5 min	Indoor (some vegetation), and semi-indoor (a large amount of vegetation and view to sky)	Indoor without biophilic elements	Restoration, cognitive function, and EEG	+	+
Gu J et al. (2023)	China	Office (field)	20	15 min	With and without AW, three temperature and three illumination levels	Without AW condition	SPO2, pulse rate, body temperature, blood pressure, and subjective thermal perception	+	O
Wang F et al. (2023)	China	Home (field)	394	-	Different roof types, sites, and floor level	-	Perceived sensory dimensions (PSDs) and short-version revised restoration scale (SRRS)	+
Cha K et al. (2023)	Korea	Classroom (virtual)	144 (5–8 yr)	10 min	Classroom size (large vs. small) and window view (natural vs. built environment)	Small room without window view	Executive functions and physiological stress responses (cortisol and heart rate variability (HRV))	+	+
Ko WH et al. (2023)	USA	Hospital (virtual)	40	30 min	Window view with different geometric variables (i.e., view angles, glazing area WWR, window distance, viewing direction and percentage of window view area in the visual field (PWV))	-	Occupants’ satisfaction	+
Abd-Alhamid F et al. (2024)	UK	Office (virtual)	25	4 min	3 WWR (10%, 20%, 30%) *2 layouts (narrow, wide)	-	View perception physiology stress recovery	+	+
Yao T et al. (2024)	China	-	160	10 min	Three main types of window view (balanced type, 9, partially balanced type 3, extreme type,3, and no window view, control group)	No window view condition	Physiology stress (EEG), physiological attention (HR, SpO2, DBP, SBP), and emotions (BPOMS)	+	+

of Appendix A. All of the papers revealed a significant impact of window views on view satisfaction, mental health, or mood. In the experimental design, twelve studies were conducted in rooms (N = 331 in total), and only four were long term (over several weeks, N = 33) with repeated measures. However, other papers on this topic are based on virtual scenes (VR or image display, N = 2278 in total), with a total sample size nearly seven times larger than the field studies.

Different from the investigations, the experimental studies (N = 40) could control the window view, which is the IV, more rigorously by setting its layout according to the research purpose. Some studies chose several rooms with different orientations in the same building or used image displays on the wall to simulate the window, while others used VR equipment to display a full-size view to the participants. Then, the ratio of green plants, sky, building height and distance, the window-to-wall ratio (WWR), and the window height (above the floor) of the room could be modeled purposefully. Meanwhile, the experimental studies also facilitated testing physiological stress and cognitive function performance to show the physiological impact of window view in 19 studies, by measuring EEG (Electroencephalography), EMG (Electromyography), BVP (Blood Volume Pulse), EDA (electrodermal activity), heart rate, skin temperature, blood oxygen saturation (SpO₂), etc., 17 of them presented an evident physiological response to different window views, while only two studies declared insignificant physiological responses (Gu J et al. [63], N = 20, and Gao et al. [23], N = 54, respectively).

Across both field investigations and experimental studies, the restorative effects of window views are consistently supported. The findings demonstrate a wide range of benefits, including improved psychological well-being, such as reduced stress, enhanced mood, and greater life satisfaction, to measurable physiological responses (e.g., lower heart rate variability, improved EEG patterns, and reduced cortisol levels). These positive effects were observed in various settings—homes, offices, hospitals, and schools—and across diverse populations. Both long term field data and short term experimental results converge to suggest that not only the presence of a window but also the quality, content, and characteristics of the view significantly influence restorative outcomes.

Based on numerous experimental studies mentioned above, the framework of the window view quality evaluation was concluded in some research. Ko et al. [64] proposed three primary variables to evaluate view quality: the access, content, and clarity of the window view. The “view content” is the sum of visual features in the window view, such as the nature (greenery, water, sky, and etc.), urban elements (buildings, streets, and etc.), and dynamic features (people, cars, birds, and etc. in movement) in the visual field, the layout or composition of the view, and view distance, which might be influenced by the site plan of the building, the floor plan of the room, and the position of the occupants’ eyes. Recently, Kent et al. (2023) [65] developed a predictive model (N = 451) of window view preference using machine learning methods. Cho et al. (2023) [66] proposed that movement and change of window view could strengthen the occupants’ engagement and connectivity to their surrounding environment. The features of view content are related to esthetic evaluation and might show individual differences. Meanwhile, the “view access” is to evaluate how much of the window view can be perceived by the occupants, which may be influenced by the layout of the room, window design (window size, shape, and height), view distance in the room, and view angles to the window. Moreover, the “view clarity” evaluated how clearly the window view could be seen, which was influenced by the texture of the window glaze (such as the spectral transmittance of the glass) and blinds (such as the spatial frequency of the light shield). The European Standard “EN 17037: Daylight of Buildings (2018)” [45] proposed some benchmark values for window view, including the view angle, view distance, and layers, which are used in daylighting design currently. However, the current standard proposed requirements for general scenario and did not refine for the health impact on vulnerable group, such as the elder people, patients, and children.

Additionally, several studies have highlighted the positive psychological effects of artificial windows [63,67,68,69,70], which serve as substitutes for traditional side windows in underground or other windowless environments. Although findings [70,71] regarding their physiological impacts remain inconsistent across studies, artificial windows have consistently been shown to enhance lighting perception and improve visual comfort. This body of research provides a solid foundation for the further development and application of artificial windows in more extreme environments, such as submarines, spacecraft, settlements in polar regions, and even on Mars.

In general, the previous studies have explored some influential factors between “window view” and “occupants’ wellbeing”. The layout, green elements, landmarks, and moving features of the window view may induce a restorative effect and influence the occupants’ satisfaction with the environment and even with the job. At present, the window view content has become a hot topic in urban planning and landscape design [72], while the window view access has been widely considered in architecture and indoor design [73]. It is worth mentioning that although window views would bring a positive psychological impact [27], they can also bring glare with direct light from the sun; therefore, there is a trade-off between sunlight shield and view clarity in window design. Accordingly, window view clarity has become a key factor when developing novel glazing materials and sunshades in the building technology sector.

3.3. The Visual Comfort of Window Daylight

The 137 studies identified on visual comfort related to window daylight predominantly focus on two core aspects: the availability of daylight and the discomfort glare it may induce. These studies emphasize that visual comfort is fundamentally governed by the balance between adequate illuminance for task performance [74] and the mitigation of discomfort glare [38]. Sufficient daylight availability enhances task visibility by ensuring appropriate luminance levels, contrast, and uniformity, thereby supporting visual efficiency and reducing eye strain [75]. However, when daylight introduces excessive luminance contrasts—particularly through direct sunlight or bright window areas within the visual field—it can result in discomfort glare, which impairs visual clarity and causes distraction or annoyance [75].

As summarized in Table 5, a variety of metrics have been developed to quantify these dual aspects of daylight-related visual comfort, enabling designers to optimize indoor environments that support both functional and perceptual visual needs. The 137 studies on visual comfort related to window daylight generally focus on the availability of daylight and the discomfort glare it can cause.

The daylight factor (DF) and uniformity of illuminance (U_O) are the earliest and most widely used index to assess daylighting efficiency, influenced by factors such as orientation, geometry, and window design [76,77], as shown in Figure 9. Beyond this, it is important to analyze the specific distribution of light levels contributed by daylight. To address this, a set of plane-illuminance-based indices has been developed to evaluate daylight levels over time or across an entire space. For instance, daylight autonomy (DA) in photopic vision represents the percentage of time a specific test point (or area) meets a target illuminance level E_P. In some studies [78,79,80], DA analysis sets target illuminances of 300 lx, 150 lx, and 3000 lx as the lower threshold for fully daylit, partially daylit, and the upper threshold for over-daylit levels, respectively. Unlike DA, which predicts the percentage of annual occupied time, spatial daylight autonomy (_SDA) [81] quantifies the percentage of space that meets the required illuminance levels. While DF, DA (or _SDA), and E_P measure daylight from the sky, annual sunlight exposure (ASE) assesses whether direct sunlight provides a sufficient light exposure dose. Moreover, unlike the one-tailed DA and ASE tests, useful daylight illuminance (UDI) [34] and spatial useful daylight illuminance (_SUDI) [82] are two-tailed tests, requiring an illuminance range with both minimum and maximum values. UDI and _SUDI account for the adaptation range of human eyes, thereby excluding conditions of insufficient brightness and discomfort glare. In addition to visual effects of daylight from windows, recent studies also recognized the impact of windows on non-visual effects in humans.

Too much daylight or high luminance contrast might cause discomfort glare in indoor spaces. At first, the luminance and luminance ratio were used to quantify the level of glare [83,84]. Subsequently, the influence of the size, brightness, position, and ambient conditions of the glare sources on perceived discomfort glare level were realized. Additionally, discomfort glare index (DGI) [38], discomfort glare probability (DGP) [85], and predicted glare sensation vote (PGSV) [86] were proposed as three main strain indices to evaluate discomfort glare. PGSV has a limitation of glare source with large size. In the searched studies, over 20% of the studies used DGI, while nearly 40% of the studies used DGP to predict discomfort glare. Meanwhile, a recent study found that simplified metric, the vertical illuminance (E_V), was also effective in predicting glare [87]. Similar to the study on daylight accessibility, discomfort glare evaluation also needs to be extended to the spatial-temporal dimension, which was presented as annual DGP in a few of the studies [88,89].

Table 5. A summary of metrics to evaluate visual comfort in daylight space.

	Index	Definition	Typical Threshold/Range
Daylight availability	Daylight factor (DF)	Ratio of indoor to outdoor illuminance under an overcast sky	2–5% [90]
	Uniformity (UO)	Ratio of minimum to average or maximum illuminance	0.4 [91,92]
	Plane illuminance (Ep)	Horizontal illuminance on a target plane.	Target: 300 lx in 50% of the space in 50% of the time Minimum: 100 lux over 95% of the space in the same period [93]
	Daylight autonomy (DA)	Percentage of time daylight meets illuminance needs	DA300 ≥ 50% [94]
	Spatial daylight autonomy (SDA)	Percentage of space with Ep at least a lx for more than b% of occupied hours within a year	SDA300/50% ≥ 55% [91]
	Annual sunlight exposure (ASE)	Percentage of space receiving at least a lx direct sunlight for more than b hrs/year	ASE1000,250 ≤ 10% [91]
	Useful daylight illuminance (UDI)	Percentage of time that daylight illuminance stays in a to b lx range within a year in less than.	Supplemental: UDIs (100–300 lux), useful/autonomous: UDIa (300–3000 lux), excessive/glare: UDI-e (>3000 lux) [34].
	Spatial useful daylight illuminance (SUDIa-b/c%)	Percentages of space maintained by EP (a to b in illuminance, e.g., 300 lx to 3000 lx) range at and above c% (e.g., 50%) of the time.	SUDI300-3000/50% ≥ 55% [94]
Discomfort glare	Discomfort glare index (DGI)	Discomfort glare caused by daylight in indoor spaces is based on the following variables: -The position, size, and luminance of light sources (e.g., sunlight). -The average luminance and size of the window. -The veiling luminance (Lb).	16: just perceptible glare 20: just acceptable glare 26: just an uncomfortable glare 28: just intolerable glare Recommend DGI ≤ 22 for most space
	New discomfort glare index (DGIN)	Updated DGI based on the following variables: -Average unshielded luminance of the outdoors. -The background luminance. -The size and luminance of the window.	Similar to DGI
	Discomfort glare probability (DGP)	Probability that occupants in a space will experience discomfort glare from daylight, which is predicted by the following variables: -Vertical illuminance (EP). -The position, size, and luminance of the glare source.	DGP ≤ 0.35: Imperceptible 0.35 < DGP ≤ 0.40: Perceptible but generally acceptable 0.40 < DGP ≤ 0.45: Disturbing and discomfort. DGP > 0.45: Intolerable
	Simplified discomfort glare probabilities (DGPs)	Simplified DGP is determined by the following variables: -The vertical illuminance (EV).	Similar to DGP
	Predicted glare sensation vote (PGSV)	Perceived discomfort glare rating, with the following variables: -The average luminance of the window plane. -Veiling luminance (Lb). -Solid angle of the glare source.	PGSV = 0: Imperceptible PGSV = 1: Acceptable PGSV = 2: Uncomfortable PGSV ≥ 3: Intolerable
	Vertical illuminance (EV)	Vertical illuminance measured at eye positions aiming to view directions.	150 lx ≤ EV ≤ 3000 lx [91,95]

Table 5. A summary of metrics to evaluate visual comfort in daylight space.

	Index	Definition	Typical Threshold/Range
Daylight availability	Daylight factor (DF)	Ratio of indoor to outdoor illuminance under an overcast sky	2–5% [90]
	Uniformity (UO)	Ratio of minimum to average or maximum illuminance	0.4 [91,92]
	Plane illuminance (Ep)	Horizontal illuminance on a target plane.	Target: 300 lx in 50% of the space in 50% of the time Minimum: 100 lux over 95% of the space in the same period [93]
	Daylight autonomy (DA)	Percentage of time daylight meets illuminance needs	DA300 ≥ 50% [94]
	Spatial daylight autonomy (SDA)	Percentage of space with Ep at least a lx for more than b% of occupied hours within a year	SDA300/50% ≥ 55% [91]
	Annual sunlight exposure (ASE)	Percentage of space receiving at least a lx direct sunlight for more than b hrs/year	ASE1000,250 ≤ 10% [91]
	Useful daylight illuminance (UDI)	Percentage of time that daylight illuminance stays in a to b lx range within a year in less than.	Supplemental: UDIs (100–300 lux), useful/autonomous: UDIa (300–3000 lux), excessive/glare: UDI-e (>3000 lux) [34].
	Spatial useful daylight illuminance (SUDIa-b/c%)	Percentages of space maintained by EP (a to b in illuminance, e.g., 300 lx to 3000 lx) range at and above c% (e.g., 50%) of the time.	SUDI300-3000/50% ≥ 55% [94]
Discomfort glare	Discomfort glare index (DGI)	Discomfort glare caused by daylight in indoor spaces is based on the following variables: -The position, size, and luminance of light sources (e.g., sunlight). -The average luminance and size of the window. -The veiling luminance (Lb).	16: just perceptible glare 20: just acceptable glare 26: just an uncomfortable glare 28: just intolerable glare Recommend DGI ≤ 22 for most space
	New discomfort glare index (DGIN)	Updated DGI based on the following variables: -Average unshielded luminance of the outdoors. -The background luminance. -The size and luminance of the window.	Similar to DGI
	Discomfort glare probability (DGP)	Probability that occupants in a space will experience discomfort glare from daylight, which is predicted by the following variables: -Vertical illuminance (EP). -The position, size, and luminance of the glare source.	DGP ≤ 0.35: Imperceptible 0.35 < DGP ≤ 0.40: Perceptible but generally acceptable 0.40 < DGP ≤ 0.45: Disturbing and discomfort. DGP > 0.45: Intolerable
	Simplified discomfort glare probabilities (DGPs)	Simplified DGP is determined by the following variables: -The vertical illuminance (EV).	Similar to DGP
	Predicted glare sensation vote (PGSV)	Perceived discomfort glare rating, with the following variables: -The average luminance of the window plane. -Veiling luminance (Lb). -Solid angle of the glare source.	PGSV = 0: Imperceptible PGSV = 1: Acceptable PGSV = 2: Uncomfortable PGSV ≥ 3: Intolerable
	Vertical illuminance (EV)	Vertical illuminance measured at eye positions aiming to view directions.	150 lx ≤ EV ≤ 3000 lx [91,95]

Among the searched papers, half of the papers evaluated the comprehensive performance of the building fenestration system, such as the optical filter glass (such as electrochromic glazing, or EC glazing), building envelope, venetian blinds (VBs), and sunshades. In these papers, along with thermal comfort and energy consumption, visual comfort is one of the key factors to develop a daylight control system and thus forms the multi-object optimization of daylighting with the help of machine learning models [94]. In those papers, about three-fourths of them used software (such as Radiance, Daysim, Ladybug, Honeybees, etc.) to simulate the Bidirectional Reflectance Distribution Function (BRDF) and Bidirectional Transmitted Distribution Function (BTDF) of glazing materials and then to evaluate the daylight emitted through the window and distributed across space. One-third of the studies conducted field experiments to test human subjects’ perception of the daylight availability and discomfort glare in indoor spaces with specific window-to-wall ratios (WWRs), sunshade forms and controls, and spectrum transmittance of glazing. Recently, studies [96,97,98] further integrated the quality of window view, daylighting availability, and discomfort glare and extended the scope of visual comfort to evaluate the quality of space.

Conclusively, the IVs in the related research are building fenestration system settings, such as the spectral transmittance of glazing, the control of VB, the forms of sunshades and building envelopes, and the geometry of the space. Meanwhile, the DVs are set as the visual comfort related to daylight (including daylight availability and discomfort glare), thermal comfort related to solar heat, and energy consumption on artificial lighting and air conditioning. In some field studies with human subjects [99], the DVs also include some non-visual effects, such as alertness, mood, and task performance, which will be discussed in the next section. Furthermore, there is a need to upgrade the metrics and indices of visual comfort related to daylight according to the new demand for light quality.

3.4. The Non-Visual Effect of Window Daylight

Previous studies show that the intrinsically photosensitive retinal ganglion cells (ipRGCs) in the human eye are sensitive to light independently of the photoreceptors (rods and cones) [40,41]. The ipRGCs are involved in regulating various physiological processes, which is referred to as the “non-image-forming (NIF) effect of light” and related to the human biological clock, sleep quality, daytime alertness, and even mood [42,43,44]. Daylight exposure, with its naturally optimal intensity, spectral composition (SPD), and timing, has long served as a primary means of regulating circadian physiology and endocrine function. It has been widely recognized as an effective non-pharmacological intervention for conditions such as seasonal affective disorder (SAD), Alzheimer’s disease, and insomnia. In indoor spaces, windows limit the daylight intensity and distribution [20], while the glazing influences the transmitted SPD [21]. With the advances in window and glazing technology, the circadian lighting availability of daylit spaces has become a concern in recent years.

To quantify the circadian effect of light, researchers have developed several metrics to weight the SPD of light and quantify the stimulus. As shown in

Table 6. Metrics to quantify the NIF effect of light.

Metrics	Number of Studies (N = 39)	Definition
Equivalent Melanopic Lux (EML) [101]	10	The effectiveness of light in stimulating the human circadian system depends on melanopsin sensitivity, a photopigment in the eye.
Melanopic Equivalent Daylight Illuminance (m-EDI) [102]	6	The equivalent illuminance of daylight to produce a biological effect comparable to that induced by the measured light.
Circadian light (CLA) [103]	2	The circadian-effective irradiance at the cornea incorporates spectral weighting based on human sensitivity, typically quantified by melatonin suppression after a 1 h exposure.
Circadian stimulus (CS) [103]	11	Quantifies the circadian stimulation from a one-hour exposure to light of specific intensity and wavelength, based on its capacity to suppress melatonin secretion.
Circadian action factor (aCV) [108]	1	The ratio of circadian luminous efficacy to photopic luminous efficacy of radiation
Melanopic/photopic ratio (M/P) [101]	2	The comparison between melanopic sensitivity (ipRGC activation) and the light source’s effectiveness in supporting photopic.
Melatonin suppression index (MSI) [104]	1	The impact of light exposure on melatonin suppression in a typical individual.
Circadian daylight autonomy (DAcircadian) [107]	1	The annual percentage of time during which daylight alone provides sufficient circadian-equivalent illuminance.
Useful daylight illuminance (UDINIF) [106]	1	The annual percentage of time during which the recommended melanopic equivalent daylight illuminance (mEDI) at eye level is achieved.
Non-visual effect (NVE) [107]	1	A ramp function characterizing the non-visual response to daylight as a function of visual illuminance under a D55 illuminant.
Cumulative annual non-visual effect (CNVE) [107]	1	Starting with the NVE, the cumulative annual non-visual effect over a given period can be assessed by calculating the average NVE.
Circadian stimulus autonomy (CSA) [105]	2	The proportion of the year during which daylight meets or exceeds a circadian stimulus threshold of 0.3.

. The most widely used circadian metrics are Equivalent Melanopic Lux (EML) [100], melanopic equivalent daylight illuminance (m-EDI) [101], and circadian stimulus (CS) [102]. Among these metrics, the performance of EML is similar to m-EDI, while the performance of CS is similar to MSI [103]. In this research, 71% of the papers used EML, m-EDI, CS, and MSI to quantify the circadian effect of daylight, respectively. Inspired by the analysis of visual comfort related to daylight, the circadian stimulus autonomy (CSA) [104], UDI_NIF [105], and DA_circadian [106] were extended from the UDI and DA indices to account for EML, m-EDI, or circadian stimulus (CS) in the calculations [105,107].

Similar to the impact of daylight on visual comfort, the impact of daylight on circadian health is influenced by independent variables such as the spectral transmittance of glazing, window-to-wall ratios (WWRs), window orientation, and shading systems. Differently, circadian light is concerned more with the light reaching the occupants’ eyes, so the position of viewpoint and direction of gazing also influence the efficiency of circadian light. The dependent variables related to circadian health include sleep quality, alertness, and mood. To quantify the impact of window daylight on occupants’ circadian health, numerous studies used daylight simulations (14 papers in total) and field measurements (20 papers in total) to calculate the daylight SPD that was transmitted by the window glazing and reached the occupant’s eye. Additionally, seven papers made systematic reviews and proposed workflows to calculate the temporal and spatial circadian-effective light distribution, as shown in

Table A5. Studies related to the impact of window daylight on occupants’ circadian health.

Literature	Research Goal	Location	Space	NIF Metrics	Simulation	Field	Framework or Review
Pechacek CS et al. (2008)	To analyze building architecture for circadian stimulus potential based on the state of the art in photobiology with three variables: lighting intensity, timing, and spectrum	USA	Healthcare architecture	Climate-based daylight autonomy (DA)		√
Bellia L et al. (2013)	To study daylight and electric light characteristics and also their impact on the human circadian system by calculating melatonin suppression.	Italy	Classroom	CS		√
Sander B et al. (2015)	To investigate the effect of bright blue-enriched versus blue-suppressed indoor light on sleep and well-being of healthy participants over 65 years	Denmark	home	E < 240 lx		√
Hraska J (2015)	To present and summarize a conceptual framework of chronobiological aspects of daylighting in built environment	Slovak	-	Biological action factor abiol v, acv, circadian effect of radiation Xbiol,			√
Khademagha P et al. (2016)	To present a theoretical framework for incorporating the non-image-forming effects of light into daylighting design in the built environment	Netherland	-	Spectrum, quantity, spatial distribution (directionality), timing, duration, and history			√
Acosta I et al. (2017)	To detail result of simulations used to determine the percentage of days that patients would receive a minimum level of circadian stimulation as a function of different window-to-wall ratio¸ orientations, surface reflectance, and latitudes	USA	Hospital	CS	√
West A et al. (2017)	To elucidate the influence of naturalistic light on patients during long term hospitalization in a real hospital setting	Denmark	Hospital	α-opic irradiance		√
Amundadottir ML et al. (2017)	A novel approach to daylight assessment is proposed concerning non-visual effects, visual interest, and gaze behavior.	Switzerland	-	Non-visual cumulative response RD	√
Konis K (2017)	A novel approach is developed to assess the duration of an effective stimulus on a daily basis, as well as the frequency an effective stimulus is present over the course of a year	USA	-	EML	√		√
Konis K (2018)	To evaluate the circadian stimulus potential of daylight provided by windows.	USA	Hospital (dementia care facilities)	EML		√
Krüger EL et al. (2018)	To explore the relationship between daylighting features and possible impacts on humans in regard to lighting preferences	German	Office	E (lx), CCT (K), DWl (nm) and the Circadian metric acv (circadian action factor)		√
Cai W et al. (2018)	Rule-of-thumb equations are proposed to guide circadian lighting design	China	-	Corneal illuminance EV	√
Acosta I et al. (2019)	To show the results of circadian stimulus autonomy, which is the percentage of days during the year when circadian stimulus is above a minimum threshold in typical classroom designs.	Spain	Educational space	CS, circadian stimulus autonomy (CSA)	√
West AS et al. (2019)	To demonstrate elevated melatonin plasma levels and evolved rhythmicity due to stimulation with naturalistic light.	Copenhagen	Hospital	-		√
West A et al. (2019)	Installed diurnal naturalistic light may reduce the known disrupted sleep quality and fatigue seen in post stroke patients.	Copenhagen	Hospital	-		√
Knoop M et al. (2020)	To present an overview of current knowledge on how the characteristics of daylight play a role in fulfilling these and other functions often better than electric lighting as conventionally delivered.	German	-	-			√
Potočnik J et al. (2020)	To evaluate the impact of different glazing types and internal wall colors on the non-visual potential of daylight	Slovenia	Office	RME—relative melanopic efficacy coefficient	√
Nagare R et al. (2021)	To explore how increasing circadian-effective light in residences affects circadian phase, sleep, vitality, and mental health.	USA	Residence	CS, CLA		√
Lu Y et al. (2021)	To investigate daylight’s impact on commuters’ circadian rhythms	Australia	Commuting trip	α-opic irradiance, CS, EML.		√
Goudriaan I et al. (2021)	To investigate the influence of indoor daylight and lighting on the health of older adults with dementia living.	-	Long term care facilities	-			√
Zeng Y et al. (2021)	To conduct field evaluations of non-visual effects in several typical office environments with different window orientations, then compare the calculation differences	China	Office	EML, CS		√
Bellia L and Fragliasso F (2021)	A brief historical excursus about the relationship between lighting practice and architecture throughout the centuries	-	Residence	DAcircadian, cumulative annual non-visual effect (CNVE), CS and circadian stimulus autonomy (CSA)			√
Ezpeleta S et al. (2021)	To analyze melanopic light in four teaching environments considering photopic indoor lighting, daylight depending on the window orientation, location of the observer in the room, and their line of view	Spain	Classroom	EML, mEDI		√
Potočnik J and Košir M (2021)	To address the extent to which indoor built environment parameters influence the characteristics of the indoor non-visual and visual luminous environment	Slovenia	Office	EML, CLA	√
Aguilar-Carrasco MT et al. (2021)	To propose assesses the combination of natural and electric lighting on circadian rhythms for operational environments.	Spain	Shift work	CS	√
Zeng Y et al. (2021)	To present a workflow to obtain optimal light outputs considering non-visual lighting requirements, in addition to traditional visual requirements.	China	Office	EML	√	√
Maskarenj M et al. (2022)	A tool and workflow to estimate Non-Image Forming (NIF) effects of light is proposed.	Belgium	Office	CS, M/P ratio	√
Zaniboni L et al. (2022)	Lighting quality and satisfaction were monitored in four physiotherapy centers	Italy and Denmark	Physiotherapy centers	EP		√
Mathew V et al. (2023)	To study various cases of lighting ambience to investigate the circadian lighting capability in terms of the circadian stimulus of the system under consideration.	India	Office	CS	√	√
Anaraki M et al. (2023)	To employ a simulation-based approach to investigate the influence of interior space configurations; in particular, office space’s partition layout, height, and optical properties on the circadian potential of the space.	IRAN	Office	EML	√
Englezou M et al. (2023)	To examine the variability of the natural lighting spectrum, focusing on light intensity, the spectrum itself, as well as variations across seasons and hours.	Cyprus	-	mEDI, mEDR		√
Ardabili NG et al. (2023)	To provide an overview of windows’ impact on human circadian health	-	-	EML, mEDI, CS, aCV, M/P, MSI			√
Lalande P et al. (2023)	To implement photobiological metrics of light by isolating the photopic (daytime vision) and melanopic (circadian clock) portions of the electromagnetic spectrum, and to spatialize daylight and artificial light in relation to landscapes and indoor architectural spaces	Canada	Office	EML		√
Stebelová K et al. (2024)	To find out the effect of a short wavelength light-reduced environment on the main hormone melatonin metabolite 6-sulfatoxymelatonin in urine (u-sMEL) and to test the connection between light exposure from the previous day and u-sMEL.	Slovakia	Office	Illuminance		√
Acosta I et al. (2023)	To ascertain the influence of natural daylight on the performance and health of teleworkers, considering a room at home analyzed in different locations, orientations, time schedules, and window shapes.	Spain	Office	Circadian stimulus autonomy (CSA)	√
Nazari M et al. (2023)	To investigate the non-visual effects of transmitted daylight through one clear and one smart glazing and evaluate the color appearance variations.	Norway	-	α-opic EDIs	√	√
Alkhatatbeh BJ (2023)	The optimization objectives include minimizing energy use and maximizing the horizontal (desk-plane) and vertical (corneal or eye-plane) daylighting levels.	USA	Classroom	UDINIF	√

of Appendix A.

Meanwhile, several studies [109,110,111,112] compared the efficiency in promoting circadian health by increasing EML, m-EDI, and CS in the morning among EC glazing, VB, and Optical Louver Systems (OLSs). Meanwhile, the trade-off between increasing circadian light levels and decreasing discomfort glare (DGI, DGP, PGSV, or E_V) should be considered as the multi-objective optimization of the daylight system.

3.5. Multi-Objective Optimization of Window Design

While both view quality and daylight performance offer discrete benefits, they are often interdependent and in tension. For instance, maximizing window transparency may enhance view clarity and increase daylight penetration [113] but also intensify glare or overheating [114]. This complexity has led to the emergence of multi-objective optimization in architectural design.

State-of-the-art simulation tools and control strategies now allow designers to simultaneously model thermal performance, energy usage, daylight metrics, and circadian lighting conditions [115]. Studies have adopted algorithms that optimize the form, size, orientation, and glazing properties of windows to balance competing goals: reducing cooling loads, maximizing visual [78,116] and circadian [117] comfort, and ensuring privacy or security [118]. For example, electrochromic glazing can dynamically adjust transmittance in response to external conditions, enabling adaptability in view and glare control without sacrificing daylight access. As discussed in Section 3.3, approximately 50 studies (summarized in

Table A3. Field studies conducted to evaluate the visual comfort of occupants in daylit space.

Literature	Research Goal	Location	Space	Daylight Metric	If Human Involved
Dahlan ND et al. (2009)	To assess how occupants perceive visual conditions.	Malaysian	Hotel	DF, luminance	Y (sample size unknown)
Kim G and Kim JT (2010)	To compare big window and balcony	South Korea	Residence	DGI	N
Kim JT et al. (2012)	To develop a new discomfort glare index	Australia	-	UGP	Y (N = 48)
Shin HY et al. (2013)	To assess how occupants perceive visual environments of diverse luminous ambiences created by daylight.	Korea	Residence	EV, EP, window luminance	Y (N = 22)
Wymelenberg (2014)	To develop a research agenda of daylight discomfort glare	USA	-	DGI, DGP	N
Yao J (2014)	To test the impact of movable solar shades on energy, indoor thermal and visual comfort improvements.	China	-	DGI	N
Konis K. (2014)	To develop a visual discomfort model	USA	-	Luminance contrast ratio, DGI	Y (N = 14)
Borisuit A et al. (2015)	To test whether different photometric variables also influence visual perception and the comfort of the lighting, as well as subjective non-visual variables such as mood, alertness and well-being.	Switzerland	Office	EP	Y (N = 25)
Korsavi SS et al. (2016)	To test students’ evaluations on visual comfort through questionnaires in daylit and non-daylit areas in classrooms	Iran	Classroom	sDA, ASE	Y (N = 46)
Wymelenberg K and Inanici M (2016)	A new suite of visual comfort metrics is proposed and evaluated for their ability to explain the variability in subjective human responses.	USA	Office	DGP, DGI, VCP, UGR, CIE Glare Index, and the average luminance of the glare sources. basic luminance ratios, contrast ratios, comparisons of mean and standard deviation values between several masks (binocular, peripheral, horizontal 40 degree, etc.).	Y (N = 48)
Bian Yand Luo T (2017)	To find appropriate visual comfort metrics	China	Office	Ev, DGI, DGP, window/workplane luminance ratio.	Y (N = 19)
Nocera F et al. (2018)	To investigate the natural lighting performance and propose different technological solutions to improve the visual comfort in classrooms whilst also respecting the cultural value of built heritage.	Italy	School Heritage Building	Climate based daylight modeling (CBDM) metrics	N
Kaya SM, Afacan Y (2018)	To valuate daylight performance in an art museum to analyze the effects of daylight design features on visitors’ satisfaction in art museums.	Turkey	Museum	Daylight illuminance	Y (N = 100)
Bian Y et al. (2018)	To acquire the extent of the reduction in predicting glare when considered the ‘adaptive zone’.	China	Office	DGI, DGP, Ev	N
Kotopouleas and Nikolopoulou (2018)	To investigate thermal and lighting comfort needs under the scope of energy conservation.	UK	Airport		Y (N = 3087)
Suk JY (2019)	To investigate field measured visual parameters inside a daylit office space to define occupants’ visual comfort thresholds, particularly for a view direction parallel to windows.	USA	Office	EP, EV, luminance, contrast ratio (task area vs. sun patch), DGP, DGI, UGR, VCP, CGI. DGP, DGI	Y (N = 12)
Kwong (2020)	To evaluate visual performances in a highly glazed green building and the perceptions of the tenants towards their visual environment	Malaysia	Office	Light source luminance, work area EP, DGI	Y (N = 42)
Koohsari and Heidari (2022)	To present a multi-stage study on the control strategies of venetian blinds by considering visual comfort and daylight metrics, and through energy analyses	Iran	Office	EP, UDI, DAv, sDA, ASE, and simplified DGPs	Y (N = 30)
Shi L et al. (2021)	To determine the factors influencing the user assessment of daylight environments and define visual comfort thresholds for mass sports activities.	China	Gymnasium	Ev, luminance	Y (N = 9)
Wang C, Leung MY (2023)	To investigate the effects of older people’s subjective perceptions of the IVE on their visual-related physical health.	China	Residence	-	Y (N = 197)
Lee SJ and Song SY (2023)	To analyze and evaluate the performance of smart windows applied in residential buildings related to visual and thermal environments from various perspectives.	Korea	Residence	New daylight glare index (DGI_N), UDI	N

and

Table A4. Simulation studies conducted to evaluate the visual comfort of occupants in daylit space.

Literature	Research Goal	Location	Space	Daylight Metric
Ünver R et al. (2003)	To comprehensively evaluate building façade	Turkey	Office	Daylight illuminance
Ochoa CE et al. (2012)	To determine the suitability of combined optimization criteria on window sizing procedures for low energy consumption with high visual comfort and performance.	Netherlands	-	DF, uniformity ratio, UGR, DGI, DGP
Fernandes LL et al. (2013)	To evaluate lighting energy savings of split-pane electrochromic (EC) windows controlled to satisfy key visual comfort parameters.	USA	Office	EP
Yun G et al. (2014)	Evaluate visual comfort and building energy demand and suggest lighting and shading control strategies for visual comfort and building energy savings.	South Korea	Office	Ev
Shen E et al. (2014)	To provide a quantitative comparison of different control strategies	USA	-	EP
Fasi MA, Budaiwi IM (2015)	The present study focuses on investigating energy savings when daylight and artificial light are integrated.	Saudi Arabia	Office	DGI, DF
Huang Y, Niu JL (2015)	To analyze the energy performance and visual performance of the proposed glazing system	Hong Kong	Commercial building	EP
Yao J et al. (2016)	To investigate the impact of manual solar shades on indoor visual comfort	China	-	UDI, DIF, DGI, DGP
Acosta I et al. (2016)	To quantify visual comfort and energy consumption metrics for window models with different surface reflectance and the geometry.	Spain	Residence	DA, UDI
Atzeri AM et al. (2016)	To test the ability of a set of metrics to represent the performance of the envelope components when comparing building configurations characterized by high solar and daylighting gains and different window and shading configurations.	Italy	-	Local (time) availability metrics, zonal (time) availability metrics, instant (space) usability metrics, long term usability metrics
Acosta I et al. (2016)	To ascertain the influence of natural daylight on the performance and health of teleworkers	Italy	Home work	Circadian stimulus autonomy (CSA), DA
Xue P et al. (2016)	To reduce energy consumption without eroding residents’ satisfaction with luminous environment	Hong Kong	Residence	DA300, uniformity
Tzempelikos A and Chan YC (2016)	To present a comparison of modeling approaches for calculating shade optical properties and the potential effects on daylighting performance and visual comfort.	USA	-	EP
Shen H and Tzempelikos A (2017)	To present details of a simplified model-based shading control using as a variable criterion the “effective daylight” transmitted into the space	USA	-	Effective transmitted illuminance
Konstantzos et al. (2018)	To present a synthesis of the most recent metrics (visual comfort autonomy, lighting energy use, and view clarity) for assessing the visual environment performance of spaces with window shades.	-	-	VCA (defined as the portion of working hours in a year when a person in a specific position in the room is under comfortable conditions). DGP, EV
Jain S, Garg V (2018)	To analyze the performance and feasibility of various daylight prediction methods and their application in controlling blinds and integrated lighting system.	India	-	Illuminance level, DGI, PGSV, DGP
Calama-González et al (2018)	To provide a comparative assessment of ambient conditions in a standard room with an egg-crate device and in a non-shaded one	Spain	Hospital	Natural illuminance, artificial illuminance
Ko WH et al. (2018)	To propose and evaluate an integrated workflow that simultaneously uses ventilation, thermal, and luminous autonomy for the assessment of passive design strategies, introducing a potential way to integrate these three metrics in the design process.	USA	-	DA, sDA, UDI, ASE1,000/250h
Uribe D et al. (2018)	To investigate the potential of perforated exterior louvers for controlling solar heat gains through a fenestration system, providing visual comfort to the occupant and improving the energy performance of an office space in distinct climates based on integrated thermal and lighting simulations	Chile	Office	sDA, ASE, DGPs
Giovannini et al. (2018)	The performance of a double glazing unit (DGU) with a phase change material (PCM) layer embedded in the cavity was analyzed in terms of the visual comfort perceived by the occupants.	Italy	-	DGP, sUDI.
Al-Sallal KA et al. (2018)	To propose a comprehensive process that investigates daylighting performance with regards to museum lighting and visual comfort requirements in the UAE traditional courtyard buildings that were converted into heritage museums.	UAE	Museum	Illuminance, light exposure (klx*h/ yr), DGP (or annual DGP), DS (daylight safety), Spatial daylight safety (sDS), sDA, ASE, UDI
Ma’bdeh S and Al-Khatatbeh B (2019)	To improve the daylight provision in existing classrooms, by investigating various retrofit methods for passive daylighting techniques in northerly oriented classrooms.	Jordan	Classroom	EP, EV on the board
Ashrafian and Moazzen (2019)	The study focuses on the impact of different transparency ratios (WWR) and window combinations in two critical orientations (west and east) on occupants’ comfort and the energy demands of a classroom	Turkey	School	DF, illuminance distribution
Tabadkani et al. (2019)	To investigate the development process of ASF grounded parametric design tools with a focus towards its visual comfort indices through a controllable shading system	Australia	-	UDI, UDIoverlit and UDIunderlit DGP, DGI and comfort range for individual view angles (glare comfort)
Zanon et al. (2019)	To present an integrated index for evaluating the visual quality of an indoor environment in residential buildings. (VQI)	Italy	-	sDA, sDGP, UGR, maintained illuminance (Em), and CCT
Chinazzo (2021)	To present the combined effect of indoor temperature (19 °C, 22 °C, and 26 °C) and colored glazing (blue, orange, and neutral) on visual perception of daylight.	Switzerland	Office	-
Nundy S, Ghosh (2020)	The thermal and visual comfort of SPD-vacuum glazing was investigated for less energy-hungry adaptive building’s glazing or façade integration at temperate climate.	UK	-	Glare potential, UDI, and color properties
Lešnik M et al. (2020)	To define an optimal upgrade module design by regarding not only energy efficiency but also visual comfort aspects.	Slovenia	-	DF
Motamed et al. (2020)	To suggest a control approach to overcome the limitations of the rule-based control systems	Switzerland	Office	DGP, EP
Zhao S (2020)	To formulate a bi-phase optimization framework to search for facade fenestration geometries	China	-	sUDIa-b/c%
Davila and Fiorito (2021)	To explore a glazing material; performance as energy efficient system	Australia	-	UDI, DGP
Sorooshnia and Rashidi (2023)	To validate highly accurate fixed external shading systems with rectangular and tapered-form external shapes.	Sydney	Residence	Hourly DGP, EV
Eisazadeh et al. (2021)	Investigates the influence of glazing characteristics and shading device configuration on energy use and cost, daylighting performance and visual comfort	Belgium	Patient room	sDA300/50%, UDI100–3000lux (%), DGP < 0.4 (%), ASE1000,250 (%), EUI (kWh/m2), AUC (€/m2)
Ghosh et al. (2021)	The semitransparent windows was investigated by employing daylight glare analysis and three wavelength dependent transmission spectra for colour comfort analysis.	Saudi Arabia	Office	DGP, CRI, CCT
Omidi et al. (2022)	To investigate how the Orosi elements affect visual comfort, based on climate-based daylight metric	Iran	Residence	UDI, sDA, ASE, DGP
Assimakopoulos et al. (2021)	To analyze the application of the light shelves with multidisciplinary approach and thus, taking into account: daylight, electricity for lighting, cooling and heating needs and thermo-hygrometric comfort.	Italy	Student dormitory	Annual and daily illuminance
Heidari Matin et al. (2022)	To develop a series of photochromic coatings for window glass and measure the impact of such smart technologies on occupants’ visual comfort.	USA	-	DGP, UDI
Sorooshnia et al. (2022)	To optimize sunlight admission and maintain indoor comfort while minimizing energy consumption.	Australia	Dwelling	Minimizing energy use intensity (EUI), maximizing LEED quality view, sDA, ASE, minimizing predicted percentage dissatisfied (PPD); DGP, UDI.
Lami M et al. (2022)	To propose an image-processing based approach to quantify the vision quality through smart windows.	UK	-	Global EP, diffused EP, direct EV
Xue J et al. (2022)	To propose an improved design strategy based on IDEO design thinking by adding the step of diverging from the design scheme.	China	-	DGP
Baghoolizadeh et al. (2023)	To present a new approach for multi-objective optimization of the architectural specifications and control parameters of a smart shadow curtain	Iran	-	DGI
Khani A et al. (2022)	To develop a multi-purpose approach for optimizing classrooms in the hot and humid climate of Qeshm island.	Iran	Education building	UDI 100–2000 lx and sDA
Wu H and Zhang T (2022)	To develop a multi-objective optimization (MOO) considering the interaction among windows, apertures, shading, and materials	China	-	UDI, energy use intensity (EUI), thermal discomfort time percentage (TDP)
Wang Y et al. (2022)	The structural dimension parameters of shading system are optimized by the multi-objective genetic algorithm based on the lighting, energy consumption, and visual comfort in this study.	China	-	UDI450–2000 lx, sDA300/50%
Fakhari M and Fayaz R (2023)	To evaluate and prioritize the factors that have a significant impact on indoor daylight quality, by using post-occupancy evaluation to examine how different variables affect human visual comfort by taking into account the simultaneous and interactive effects of these variables.	Iran	-	NA
Alkhatatbeh et al. (2023)	The optimization objectives include minimizing energy use and maximizing the horizontal (desk-plane) and vertical (corneal or eye-plane) daylighting levels	USA	Classroom	UDI_IF_300-3000(image forming effect), UDI_NIF(non-image forming effect),
Ali LA and Mustafa. (2024)	To examines visual comfort in prayer halls by investigating the effectiveness of daylighting performance in different mosque morphologies.	Iran	-	EP, DF, DGP
Lotfabadi P et al. (2023)	The examined model leads to develop a standard strategy that can be used to evaluate visual comfort while maximizing energy performance in buildings with diverse functions and located in various climates.	Northern Cyprus	-	DA_con, UDI, DF. horizontal sight angle, outside distance of view, number of layers seen from inside, minimum direct sunlight hours, DGP, UGR
Mahdavinejad M et al. (2024)	To investigate the effect of facade geometry on visual comfort and energy consumption in four different climates of Iran and categorize each variable based on effectiveness for each location	Iran	Office	UDI, sDA300/50%, ASE1000, 250
Cannavale A et al. (2023)	Aiming at the assessment of energy and visual comfort benefits deriving from building integration of smart windows in a multistorey office building.	Italy	-	UDI-f (0-100), UDI-s (100-300), UDI-a (300-3000)
Tabadkani A et al. (2023)	To propose an integrated simulation-based workflow to adjust a roller shade for single occupied office space in a hot and arid climate	Australia	-	DGI
Marchini F et al. (2023)	Introducing photoluminescent materials as an innovative coating for smart window applications, exploring their potential for visual comfort.	Italy	-	DGP
Budaiwi IM, Abdul Fasi M (2023)	To determine energy savings are achievable with EC windows while addressing visual comfort.	Saudi Arabia	Office	DF, EP
Bian Y et al. (2023)	To develop a validated simulation method to assess the daylighting performance of the novel window system in daylight availability, visual comfort, and adequate window view.	China	Classroom	DA, contrast ratio on the board
Zheng C et al. (2023)	To propose a multi-objective optimization framework based on Pareto front solutions to optimize the energy, thermal and visual performance of dormitory buildings in a cold climate.	China	Dormitory	UDI
Kangazian A and Razavi SZ (2023)	155 unique DCSs are evaluated in cardinal and intercardinal orientations using a multi-criteria decision-making (MCDM) meth.	Iran	Office	UDI, spatial glare autonomy (sGA)
Mathew V et al. (2023)	To present climate-responsive control of switchable glazing using machine learning models.	India	-	EP, luminance (for glare), DGP, CCT
Potočnik and Košir (2023)	To analyze visual and non-visual comfort simulation efficiency.	Slovenia	-	Autonomy of circadian potential and circadian autonomy, DGP
Mesloub A et al. (2023)	To evaluate the visual comfort, overall energy consumption, and economic feasibility of multiple TDD configurations.	Arabia	Office	sDA_300,50%, DGP, ASE

of Appendix A) have applied multi-objective optimization approaches within this review. Among them, nearly 45 focused primarily on balancing energy efficiency with visual comfort. In the past five years, however, an emerging subset of research has expanded the optimization framework to include the non-visual effects of window daylight exposure [19,107,119,120], and the psychological impact of window view quality [96,98,99], reflecting a more holistic, occupant-centered approach to window design.

4. Discussion

Analysis of recent publication and citation trends shows growing research interest in the physiological and psychological effects of window views and the amount of daylight reaching occupants’ eyes through window glazing.

4.1. Current Evaluation Methods of Window View Quality

One of the central components in evaluating window benefits is the quality of the view it provides. Empirical studies and simulation-based evaluations have converged on three primary dimensions that define window view quality: visual access, visual clarity, and visual content [64]. Visual access [4] refers to the geometric relationship between occupants and the view, determined by variables such as window size, height, orientation, and occupants’ positioning. Visual clarity relates to the optical transparency of the window and any obstructions such as blinds, tinting, or patterned glazing, which may diminish the sharpness or vibrancy of the view [64]. Visual content considers the composition and type of scene visible through the window—nature elements (greenery, sky, water), urban forms, motion, and distance to focal points [121].

Recent studies have advanced the understanding of visual content by introducing computational frameworks that quantify scene components and predict occupants’ preferences using machine learning algorithms [65]. For instance, dynamic views—those with movement and natural changes—have been shown to foster greater restorative effects. However, while standards such as EN 17037 [45] provide basic thresholds for view angle and distance, they fall short of addressing user-centric psychological metrics and the needs of sensitive populations such as elderly individuals, patients, or children. The challenge lies in harmonizing subjective view quality—dependent on aesthetics, cultural context, and personal expectations—with objective quantification.

4.2. Current Evaluation Methods of Window Daylight

Beyond the psychological implications of views, the role of daylight remains fundamental to indoor environmental quality [36]. Current evaluation methods focus on both daylight availability and visual discomfort [122]. Indices such as daylight factor (DF) [76,77], daylight autonomy (DA) [78,79,80], spatial daylight autonomy (SDA) [81], and useful daylight illuminance (UDI) [82] have enabled building designers to measure and simulate how much and how consistently daylight reaches interior spaces. These metrics offer annual and spatially resolved insights into whether daylight levels meet visual task demands or exceed thresholds that might cause glare. On the discomfort side, metrics such as discomfort glare index (DGI), discomfort glare probability (DGP) [85], and Predicted Glare Sensation Vote (PGSV) [86] provide tools to predict visual annoyance. Recent innovations suggest that vertical illuminance at eye level [84] is a simpler yet effective predictor of perceived glare, aligning closely with field measurements. The sensitivity of these metrics to dynamic daylight patterns and user variation in glare tolerance was also discussed in some studies [123]. Previous studies have significant implications for integrating glare control with energy strategies, where shading or glazing treatments are applied to manage discomfort. Moreover, field studies increasingly show that daylight quality also impacts mood, alertness, and cognitive function—bridging the visual with the non-visual domain [99].

In addition to the visual effects of daylight, its non-image-forming (NIF) impacts—such as circadian rhythm regulation and melatonin suppression—have garnered increasing attention. Common evaluation metrics include EML [100], m-EDI [101], CS [102], CSA [105], DA_circadian [106], and UDI_NIF [105]. These indicators consider both spectral sensitivity and temporal exposure, enabling climate-based simulations of biologically effective daylight at eye level. Integrating such metrics into daylighting analysis supports a shift toward health-centered lighting design, though further refinement is needed to account for occupant behavior, gaze direction, and individual sensitivity.

4.3. The Potential of Artificial Windows Used in Windowless Spaces

Artificial windows—also referred to as virtual, simulated, or surrogate windows—have gained increasing attention as a solution for enhancing user experience in windowless indoor environments. These systems simulate visual access to outdoor scenes through digital displays, LED panels, or lightboxes that mimic sky conditions or natural landscapes. Though they cannot fully replicate the physiological and psychological benefits of real windows [70], growing evidence suggests that artificial windows can positively influence mood, reduce stress, and improve perceived environmental quality in enclosed spaces [69].

To enhance the efficacy of artificial windows, future research and design innovation should focus on several key aspects. First, dynamic daylight simulation—mimicking the diurnal rhythm of sunlight intensity and color temperature—could strengthen circadian entrainment and psychological realism. Second, spectral tuning technologies that approximate the melanopic content of natural light may improve non-visual physiological outcomes, such as alertness and sleep regulation. In particular, the development of light spectra and intensity profiles specifically calibrated to support circadian rhythms—for example, high melanopic equivalent daylight illuminance (mEDI) during daytime and low levels during the evening—could optimize the biological effectiveness of artificial windows. Third, the directionality of simulated light—reproducing the incident angles of natural sunlight—can enhance spatial cognition and visual comfort. Finally, incorporating motion-responsive or time-varying landscape imagery could foster a sense of connectedness to the outside world, thereby reinforcing biophilic effects.

Although artificial windows are not a complete substitute for real fenestration—lacking elements such as natural ventilation, multisensory environmental cues, and genuine depth perception [124]—they offer an important complement in space-constrained or isolated settings. Emerging applications range from hospitals, long term care facilities, and underground workspaces to more extreme environments such as submarines, polar research bases, and spacecraft, where natural light and views are entirely absent. In these contexts, artificial windows may serve as biologically informed, multisensory interfaces that help mitigate sensory deprivation, support circadian regulation, and promote psychological resilience.

Future research should continue to assess their performance across both visual and non-visual metrics and explore how multi-objective optimization frameworks—involving variables, such as spectrum, intensity, timing, spatial configuration, and user interaction—can be applied to design artificial windows that more closely emulate the functional roles of real daylight and views.

4.4. Integrating Human-Centric Needs Through Adaptive Façade Technologies

Traditional static glazing and fixed shading systems often struggle to balance the competing goals of visual comfort, circadian stimulation, energy efficiency, and view quality under dynamic daylight conditions. Recent innovations in dynamic facades, such as smart electrochromic glazing [125], adaptive shading [126], and artificial windows, offer adaptive and controllable responses to real-time environmental conditions and occupant demands.

Smart glazing technologies, for instance, can modulate visible light transmittance (T_vis) and solar heat gain coefficient (SHGC) in response to solar radiation [127], allowing for dynamic control of indoor luminance and glare while maintaining acceptable vertical illuminance for circadian entrainment [115]. When integrated with spectral tuning capabilities, such systems could further enhance non-visual lighting quality by maximizing melanopic content during morning hours and minimizing it during evening periods, thereby supporting healthy sleep-wake cycles.

Artificial window systems, using LED-based tunable panels, have shown potential to simulate outdoor views and dynamic daylight spectra in windowless environments such as hospitals or underground offices. Although current evidence is still emerging, such systems could be particularly beneficial for vulnerable populations (e.g., the elderly, shift workers) by restoring visual connection to nature and delivering targeted circadian-effective light exposures.

Moreover, adaptive shading devices—such as kinetic louvers or fabric blinds with automated controls—can mitigate discomfort glare while preserving outward visibility and daylight penetration. When paired with real-time user feedback [128] or occupancy sensing [129], these systems can be fine-tuned to individual preferences and behaviors, addressing variability in age, sensitivity, and light history.

To fully realize the potential of these technologies, future research must integrate multi-domain performance metrics, including spatial view access, visual discomfort indices (e.g., DGP, PGSV), and melanopic-based indicators (e.g., m-EDI, CS). Coupling façade systems with occupant-centric data—such as gaze tracking, activity patterns, and chronotype assessments—will allow for dynamic light delivery tailored to both perceptual and physiological needs. Furthermore, simulation-based multi-objective optimization frameworks can guide early-stage design by evaluating trade-offs across views, glare, circadian impacts, and energy loads under diverse temporal and climatic conditions.

In summary, human-centric façade technologies represent a promising frontier for harmonizing visual and non-visual goals in architectural daylighting. Their successful implementation will depend not only on technical innovation but also on integrative design thinking, performance-based validation, and user-driven adaptation strategies.

4.5. Limitations and Potentials

Despite the broad scope of literature analyzed, several limitations persist. First, a considerable number of empirical studies rely heavily on short term, self-reported data collected in controlled or simulated environments—such as virtual reality (VR) scenes or static image displays. While these methods enable researchers to systematically manipulate and isolate specific window view characteristics (e.g., content type, visibility, and viewing angle), they often lack validity. That is, the psychological and physiological responses observed under simulated conditions may not accurately reflect occupant experiences in real-world settings, especially over extended periods. A fundamental limitation lies in the disconnect between virtual stimuli and actual environmental exposures. Most VR- or image-based experiments have not been rigorously calibrated against real physical environments, creating uncertainty regarding the generalizability of their findings. For example, static images or panoramic projections on flat screens fail to reproduce the full angular breadth or depth perception associated with natural window views in human peripheral vision, thereby reducing spatial immersion and altering visual engagement. Moreover, virtual environments tend to compress the luminance dynamic range and therefore cannot replicate critical light characteristics such as brightness gradients, sun movement, or temporal shifts in spectral composition—elements that strongly influence both glare perception and circadian stimulation. Future research should prioritize real-world studies to better capture the dynamic nature of occupant experiences with window-related lighting conditions. Particular attention should be given to the effects of temporal changes in luminance and spectrum, as well as to variations across diverse demographic groups, including differences in age, chronotype, and light sensitivity. Such efforts will be essential to developing more inclusive and responsive daylighting strategies.

Second, although significant research has explored the multi-objective optimization of visual comfort, circadian effectiveness, and energy consumption, far fewer studies have addressed how these factors interact with other environmental dimensions—such as acoustic comfort or indoor air quality—which can also affect occupants perceived well-being. Additionally, demographic diversity is often underrepresented: variables such as age, cultural background, and health conditions remain insufficiently explored, despite evidence suggesting that preferences and needs for window view quality vary considerably across user groups and building types.

Third, current simulation models rarely account for occupant behavior in a dynamic, temporally realistic manner. In actual settings, users frequently adjust blinds or shading devices, shift their positions, change visual tasks, and interact with their environment in ways that significantly influence exposure to light and views. These behavior-driven variations are difficult to capture with static models or single-occupancy assumptions. Therefore, future research should prioritize the development of behavior-integrated simulation frameworks capable of reflecting occupant movement, task variation, and adaptive control patterns throughout the day.

Moreover, while this review primarily focuses on the visual and non-visual light-related impacts of building windows, it is important to acknowledge that other environmental factors—such as acoustic comfort [130] and indoor air quality [131]—also significantly contribute to occupant well-being. These aspects are often interrelated with lighting conditions and may interact with psychological or physiological responses [132]. However, due to the scope of this review and the need for methodological focus, acoustic and air quality considerations were excluded from the main analysis. Future multidisciplinary research is encouraged to integrate these dimensions for a more comprehensive understanding of indoor environmental quality in relation to window design.

Therefore, future studies should aim to integrate longitudinal field research with high-resolution environmental sensing and wearable physiological monitoring. By capturing real-world exposure to daylight and viewing experiences over days or weeks, researchers can better link environmental design to cumulative effects on sleep, productivity, or mental health. There is a pressing need to develop composite indices that reflect the holistic experience of windows—not only as viewports or light sources, but as components of biophilic design, energy systems, and social interaction. These indices should integrate subjective, behavioral, and physiological dimensions and be adaptable to diverse building types and occupant profiles.

On the technological and practical side, advancements in smart glazing, adaptive facades, and personalized lighting systems offer promising directions. These technologies should be assessed not only for their energy performance but for their ability to dynamically support visual and circadian comfort across user contexts. Meanwhile, in terms of policy and practice, standards such as EN 17037 [45] can evolve to include health-based benchmarks and promote equity in access to high-quality window views and daylight. Architecture and urban design should also respond by ensuring that vulnerable populations—such as hospital patients, shift workers, or the elderly—receive adequate exposure to beneficial light and views.

Finally, interdisciplinary collaboration will be essential. Bridging environmental psychology, chronobiology, architecture, and data science will yield richer insights and more actionable design guidelines. While environmental psychologists bring valuable insights into how humans perceive, interpret, and emotionally respond to window views and daylighting, lighting experts offer the technical tools and models needed to simulate, quantify, and manipulate those environmental stimuli. Bridging these two research areas can significantly enhance the design and performance of windows as both psychological interfaces and optical systems.

5. Integrating Visual and Non-Visual Pathways in Multi-Objective Optimization of Windows

Building windows function as complex environmental interfaces that engage both visual and non-visual mechanisms, exerting multifaceted impacts on human well-being. From a visual perspective, windows serve as micro-scale portals to the external natural environment, offering views of sky, vegetation, and dynamic landscapes—an experience aligned with the biophilia hypothesis [48], which posits an innate human affinity for nature. This connection is not merely aesthetic; it activates visual-psychological pathways that can induce measurable restorative outcomes. According to Ulrich’s Stress Recovery Theory (SRT) [47], exposure to natural views through windows can rapidly attenuate sympathetic nervous system activity and reduce physiological arousal. Similarly, Kaplan’s Attention Restoration Theory (ART) [29] suggests that such views engage involuntary attention in a soft-fascinating manner, allowing direct attention to recover from fatigue. These responses—mediated through visual perception—are increasingly linked to adjustments in sympathetic nervous activity and improvements in mood, concentration, and overall mental health.

At the same time, windows provide essential access to daylight, enhancing indoor visibility and supporting visual performance. However, this benefit is double-edged: while moderate daylight improves task lighting and spatial brightness [79], excessive daylight can induce discomfort glare [81] and increase thermal load, undermining both occupant comfort and building energy efficiency. To better understand these effects, a dual-pathway framework is required, as shown in Figure 8. The visual pathway, mediated by photoreceptors and transmitted through the LGN to the visual cortex [12], governs perceptual outcomes such as clarity, contrast, luminance distribution, and glare. In parallel, the non-visual pathway—initiated by intrinsically photosensitive retinal ganglion cells (ipRGCs) projecting to the SCN—regulates circadian rhythms, melatonin secretion, and broader neuroendocrine functions [40,41]. These two systems operate concurrently but target distinct functional outcomes: while the visual pathway supports task-related performance and restorative perception, the non-visual pathway influences biological health and sleep-wake stability.

The non-image-forming (NIF) effects of daylight are highly time-dependent (stronger in the morning) and non-linear in their dose-response relationship—meaning that a threshold of light exposure dose exists to effectively promote circadian entrainment [42]. As a result, a comprehensive indicator system has emerged to guide performance evaluation and design. Visual metrics include horizontal and vertical daylight intensity (E_P, E_V), temporal-spatial indices such as UDI, DA, ASE, and _SDA, and glare indices such as DGI, DGP, and PGSV. Non-visual performance is assessed via melanopic-weighted metrics such as EML, m-EDI, CS, CL_A, and spatial indicators such as DA_circadian and UDI_NIF. These indicators enable precise quantification of how daylight affects both visual experience and biological rhythms.

Given the complex interaction between visual and non-visual effects, window design must balance multiple and sometimes competing goals. On the one hand, large, unobstructed glazing enhances visual access to nature, supports psychological restoration, and delivers circadian-effective daylight. On the other hand, these same design choices can cause glare, increase heat gain, and compromise privacy, particularly in open-plan or dense urban settings. Addressing this trade-off calls for human-centered, dynamic modeling that incorporates gaze behavior and visual field distribution. Since gaze angle [133] and direction [134] determine which parts of the retina receive visual and circadian-effective light, including these behavioral factors enhances the realism and effectiveness of design simulations.

Therefore, this inherent tension underscores the need for a multi-objective optimization framework that integrates daylight, view, health, and energy performance into a unified evaluation system. Effective solutions for window and daylighting design must comprehensively address multiple interrelated dimensions. First, visual comfort should be ensured by providing sufficient illuminance for task performance while minimizing discomfort from glare through appropriate shading, glazing, and spatial layout. Equally important is circadian stimulation, which involves delivering biologically effective light during daytime, especially the morning hours, to support circadian entrainment and overall health. View quality also plays a critical role, as windows offering clear, unobstructed views of natural elements at appropriate distances and angles can enhance psychological restoration and cognitive functioning. Additionally, energy efficiency must be maintained by balancing daylight admission with thermal control strategies to reduce both cooling demands and artificial lighting loads.

Lastly, user variability—including differences in gaze habits, age-related visual changes, light sensitivity, and prior light exposure—must be taken into account to develop responsive and inclusive lighting environments tailored to diverse occupant needs. Incorporating visual field geometry and feedback loops based on gaze angle allows for individualized assessments across both visual and non-visual domains, moving beyond generalized assumptions.

Advanced simulation workflows—such as climate-based daylight modeling, spectral analysis, and view content quantification—now make it feasible to explore and optimize this complex design space. When paired with machine learning algorithms or evolutionary optimization techniques (e.g., NSGA-II, MOEA/D) [135], designers can generate solutions tailored to specific building types, user groups, and geographic contexts, achieving effective trade-offs across competing objectives.

Ultimately, recognizing the multisensory, multisystem influence of windows reframes them as critical regulators of indoor environmental quality. This shift demands evidence-based, integrative, and user-centered design strategies that bridge visual perception, biological health, behavioral science, and computational optimization. As presented in Figure 10, by fully integrating visual and non-visual pathways along with human factors such as gaze and visual field, designers can develop daylighting systems that are not only sustainable and energy-efficient but also deeply supportive of occupant health and well-being.

6. Conclusions

This systematic review highlights the critical role of building windows in shaping the physiological and psychological well-being of occupants. Synthesizing findings across environmental psychology, chronobiology, architecture, lighting, and building science, this study confirms that window design influences occupants through three primary pathways: visual connection to nature (112 studies), daylight quality and glare (137 studies), and non-visual effects on circadian health (55 studies).

Access to natural window views that enhance biophilic connection in indoor spaces—featuring elements such as vegetation, sky, or water—has been shown to reduce stress, elevate mood, and support cognitive recovery. Key dimensions of view quality include visual content, access, and clarity. While standards such as EN 17037 offer guidance, they often fail to address subjective experiences or vulnerable populations, such as the elderly.

Daylight serves both visual and biological needs but can cause glare and fatigue if unmanaged. The development of simulation metrics—such as DF, DA, SDA, UDI, and DGP—has significantly advanced the ability to evaluate daylight conditions and predict visual comfort. However, these models must now be expanded to account for spatial-temporal dynamics, diverse occupant needs, and real-world behaviors.

Non-visual effects of light—such as those on alertness, hormone regulation, and sleep—are increasingly recognized. Metrics such as EML, CS, and m-EDI offer tools for quantifying circadian-effective light. Balancing these effects with visual comfort and energy use is a key challenge. The synthesis also underscores the need for multi-objective optimization in window and façade design. Strategies that maximize visual comfort, minimize glare, support circadian health, and improve energy performance require an integrated approach.

Moreover, this review underscores the importance of a holistic, human-centric approach to window design, one that fully integrates both visual and non-visual light pathways. Building windows serve not merely as architectural openings but as dynamic interfaces that modulate environmental light exposure, visual connection to nature, and occupant well-being. Optimizing their performance requires balancing competing demands—such as visual comfort, circadian stimulation, view quality, and energy efficiency—within an integrative, multi-objective framework. The emergence of adaptive facade technologies, including smart glazing, electrochromic systems, and automated shading, provides new opportunities to dynamically respond to these complex requirements, especially when informed by occupant-centric data such as gaze behavior, chronotype, and visual field geometry. Meanwhile, the application of artificial window systems in windowless or clinically sensitive environments offers a promising solution to simulate natural views and deliver biologically effective lighting. Moving forward, daylighting design must move beyond static metrics and compartmentalized evaluations toward a more integrated strategy that leverages advanced simulations, real-time sensing, and behavioral feedback. Such approaches are essential for achieving high-performing indoor environments that support visual performance, psychological restoration, and circadian health in diverse architectural and user contexts.