Since the inception of the first green building certification schemes in the 1990s—e.g. Building Research Establishment Environmental Assessment Method (BREEAM) in the UK and Leadership in Energy and Environmental Design (LEED) in the US—most systems have shared aspirations: (1) to mitigate climate change by minimising energy, material and water use, site disturbance, and waste generation; and (2) to promote human comfort, health, wellbeing and occupant experience within the built environment. Yet, despite its foundational place in green building practice, the priority on human health and wellbeing has changed significantly over time (Figure 1).
Green building rating tools emerged, in part, as a reaction to the implementation of energy efficiency measures following the energy crisis of the 1970s (left side of Figure 1). An exclusive focus on energy performance in early years often resulted in undesirable secondary effects on occupants, such as reduced wellbeing and increase in sick building syndrome (SBS) symptoms and other illnesses, and this regardless of the effective energy efficiency of buildings (Mølhave 1989; Sundell et al. 1994; Tham et al. 2015; Wolkoff 2020). Studies often related the incidence of these health outcomes to inadequate ventilation as well as exposures to various physical, biological and chemical hazards (Joshi 2008). Therefore, early green certification schemes emphasised environmental health threats, notably tobacco smoke, asbestos and radon. In the late 1990s, the focus on environmental health risks was largely replaced by debates about the emissions from building materials (e.g. polyvinylchloride—PVC). In the early 2000s, growing awareness about the threat of global climate change again shifted priorities. This time the attention moved toward the global health consequences of greenhouse gas (GHG) emissions. In this context, a focus on indoor environmental quality (IEQ) was seen as myopic, even selfish. Over the last decade, yet another shift was observed with the emergence of the prevailing notion of ‘healthy buildings’. It is important to emphasise that each ‘era’ in the development of green certification schemes was characterised by a concern for the connection between buildings and human health; however, attention and focus for this connection has changed dramatically over time.
The current green building paradigm is driven by the convergence of factors including:
These factors have inspired a new generation of rating tools focused on supporting occupant experience, such as WELL v2 (International WELL Building Institute 2020), Living Building Challenge 4.0 (International Living Future Institute 2021) and FitWel (FitWel, GSA 2019). Yet, despite the growing attention to these issues, there is still inconsistent evidence in the scientific literature of the ability of rating systems to achieve their intended outcomes (e.g. Khoshbakht et al. 2018; Steinemann et al. 2017; Licina et al. 2019; Lee et al. 2019). Evidence from field studies measuring relative improvements in occupant satisfaction with IEQ and perceived wellbeing in green-certified buildings remains ambiguous and variable across performance metrics (Gou et al. 2012; Altomonte & Schiavon 2013; Ravindu et al. 2015; Sediso & Lee 2016; Lee et al. 2020). Surveys in green-certified buildings have also suggested that, under some performance categories, the minimum standard requirement of an 80% occupant satisfaction rate is seldom met (Frontczak et al. 2012; Karmann et al. 2018; Pastore & Andersen 2019; Lee et al. 2019; Graham et al. 2021). These findings emphasise the need for green building certifications to critically re-evaluate current IEQ criteria, raise and fulfil expectations, and prioritise real-world IEQ and health outcomes (Colton et al. 2015).
Several authors have provided systematic reviews of the IEQ performance in green-certified buildings (Lee & Kim 2008; Fowler et al. 2011; Todd et al. 2013; CBE 2014; Zuo & Zhao 2014; Allen et al. 2015; Cedeño Laurent et al. 2018; Khoshbakht et al. 2018; Geng et al. 2019; Allen & Macomber 2020; McArthur & Powell 2020; Worden et al. 2020; Ascione et al. 2022). However, less attention has been given to specific, actionable, guidance for the improvement of rating systems.
This paper fills this gap by synthesising research and practitioners’ experience to propose a new framework for the design and operation of green building rating systems. In doing so, the research evidence here presented is based on a critical synthesis of the existing literature drawn from widely used databases such as Web of Science, Scopus and Google Scholar. The intent of the selection process was to identify relevant high-quality papers on which the authors’ reflections could be grounded. This was done in two steps: by systematic bibliographic search and by supplementary literature additions. The systematic bibliographic search relied on the following keywords: green buildings; sustainable buildings; green-certification; rating systems; indoor environment; IEQ assessment; occupant satisfaction; and occupant comfort. The search included papers published between 2005 and September 2021, although a more substantial emphasis was given to papers issued in the last decade so as to address contemporary developments in green building certifications. Altogether, more than 100 papers focusing on IEQ assessment in green-certified buildings were selected and reviewed: including analyses related to physical measurements of IEQ, occupant satisfaction with IEQ, productivity, and health. Additional literature was also included in the synthesis regardless of the certification status of the buildings analysed, and the year of publication, when original aspects related to IEQ and occupant comfort and health were presented. The presented synthesis also included the comprehensive review of the rating system and IEQ credit requirements from a dozen green building certification schemes. Criteria for exclusion from the review included: papers not based on actual measured data; studies missing clear and robust methods for data collection and analyses; and papers exclusively based on results from building simulation and modelling. In the literature search, the selection was intentionally focused on IEQ aspects related to the foundational elements of thermal comfort, lighting, acoustics and indoor air quality, and to specific propositions of critical advancements within green certification schemes. However, studies were included that recognise the broader relevance of human experience in the building industry beyond the mere attainment of IEQ scores or actual green certification.
In order to give recommendations that could be relevant to building design practice, and to the potential development of green rating systems, the present authors decided to go beyond the simple synthesis of the otherwise sparse, and broadly archival, literature. Instead, the study also relied on the ‘grey’ literature (e.g. government reports, white papers, certification schemes documentation, etc.) and on the authors’ collective long-term practical experience in the green building industry at a global level.
On these bases, one of the primary objectives of this paper consisted of identifying key scientific and practical insights that could help to form an integrated vision for future directions in green building certification.
The paper is structured as follows. It starts with a synthesis of the current evidence of the relationship between green building design and outcomes, including consolidated knowledge on IEQ performance and occupant satisfaction in green-certified and non-certified buildings (Section 2). A systematised approach to relevant research (Section 3) and practice-based observations and challenges are then presented that identify what hinders green buildings’ performance (Section 4). Based on the literature and observations outlined in Sections 3 and 4, Section 5 sets the foundation for researchers and decision-makers to capture immediate and long-term green building opportunities. While attention is centred on rating schemes, the proposed recommendations could find application in any building development, with or without certification. Based on this, Section 6 depicts an envisioned future for green-certified buildings.
A critical and constructive analysis of IEQ and green building rating systems is predicated on an understanding of the intent of these tools and prevailing representation of strategies intended to improve occupant experience. Green building rating systems integrate a specific theory of change with structural elements intended to encourage and recognise superior practices and, in some cases, performance. The theory of change is generally understood to be rooted in transparency and competitive differentiation. Rating systems provide information about practices and performance that would otherwise be invisible and undervalued by market actors. Ratings codify a set of purported best practices and identify specific performance levels that are understood to represent superior outcomes.
Most rating tools have a concept analogous to systems goals. These are programmatic aspirations such as climate protection, health promotion or biodiversity conservation. These goals are pursued with a combination of essential elements, often called prerequisites (or preconditions), and optional criteria, also known as credits. Goals, prerequisites and flexibility in their application are not scientific or technical questions. Fundamentally, they are an expression of the values of the community that supports the scheme.
IEQ issues provide clear examples of the importance of intent in the design of rating system criteria. For example, LEED building design and construction rating systems have credits intended to encourage access to daylight. The metrics used in current credits (USGBC 2021) are mostly based on work plane illuminance, with the goal of reducing the need for energy-dependent electric lighting. This is an important intent; however, work plane illuminance is not necessarily correlated to the perception of visual comfort, nor is it a valuable indicator for assessing the availability of biologically active luminous stimulation (Blume et al. 2019). The latter objective is seen as increasingly relevant to occupants’ circadian wellbeing, alertness, mood, sleep quality and other factors.
The metrics used in certification tools are intimately linked to the last link in the chain: documentation and performance evaluation. Rating systems need to be cognisant of the ability to evaluate criteria at a given phase in the life-cycle of a project. For example, occupant surveys are a valuable tool to gauge satisfaction in use; however, occupants are unlikely to be present when a building is delivered. Consequently, design teams—and, in turn, rating system developers—look for proxies that can predict satisfaction before occupants are present or postpone certification until later in operation, which may be too late to provide the intended market impact (i.e. value for green buildings).
The description of these elements—goals, prerequisites, metrics and reviews—is needed to create the foundations for recommendations for the future development of rating system and green building practice more generally. The following sections attempt to articulate specific, actionable opportunities to improve these elements to promote better, more consistent, health IEQ outcomes.
Several studies have analysed the energy performance of green-certified buildings against the general building stock (Newsham et al. 2009; Scofield 2009, 2013). Conversely, as illustrated in Figure 2 and summarised below, fewer studies have focused on understanding the self-reported satisfaction with IEQ expressed by their occupants (e.g. Allen et al. 2015; Altomonte et al. 2017, 2019; Altomonte & Schiavon 2013; Schiavon & Altomonte 2014; Lee et al. 2019, 2020). An even smaller number of studies have measured physical IEQ parameters (e.g. Newsham et al. 2013; Liang et al. 2014; Tham et al. 2015; MacNaughton et al. 2017; Lee et al. 2019; Pastore & Andersen 2019; Licina & Langer 2021), while there is only sparse research comparing health indicators between certified and non-certified buildings (e.g. Thiel et al. 2014) (Figure 2).
Various studies have reported positive associations with green certification, including:
These positive effects have been seen both in new construction (Lee et al. 2019) and in renovations and retrofits (Lee et al. 2020). However, this empirical evidence has, at times, been difficult to consistently substantiate (Tham et al. 2015; Khoshbakht et al. 2018; Lee et al. 2019; Cheung et al. 2021) or to directly correlate with the intentions of green certification IEQ credits (Altomonte et al. 2019). Conversely, the magnitude of the effects that green rating has exerted on occupants has not consistently matched predictions based on the investments and costs incurred. For instance, some studies have reported identical, or even impaired, IEQ performance of green-certified buildings relative to the non-certified building stock (Brown & Cole 2009; Gou et al. 2012; Altomonte & Schiavon 2013; Ravindu et al. 2015; Tham et al. 2015; Altomonte et al. 2017; Sediso & Lee 2016). Even when evidence suggested higher performance in green-certified buildings, it has often not been ascertained to what extent the expectations of building occupants and the so-called ‘halo’ effect might have influenced perceptions. No clear mechanisms have been provided to explain the relationships between outcomes and specific actions and decisions taken in green-certified buildings.
Research has shown that IEQ performance can be improved by providing specific mandatory certification requirements (Lee et al. 2019) and promoting the attainment of higher certification levels such as Gold and Platinum (Pyke 2020). In some studies, measures of IEQ satisfaction have been collected before and after relocation into a green-certified building with the same occupant cohort (e.g. Singh et al. 2010; Agha-Hossein et al. 2013; Colton et al. 2014; MacNaughton et al. 2016; Licina & Yildirim 2021).
Only a few studies performed physical measurements in green-certified buildings of parameters characterising IEQ alone or in combination with subjective assessment (e.g. Newsham et al. 2013; Liang et al. 2014; Tham et al. 2015; MacNaughton et al. 2017; Lee et al. 2019; Pastore & Andersen 2019). While such studies are essential for alleviating research design challenges such as bias, dependent effort and misclassification, they are typically short term and focused on individual IEQ factors. Direct inter-comparability of physical measurements of IEQ and corresponding occupancy satisfaction data is rare.
In summary, the majority of data on IEQ and occupant outcomes in green-certified buildings is based on subjective ratings, with only a few cases reporting evidence on work performance (e.g. MacNaughton et al. 2017) or absenteeism (e.g. Sustainability Victoria Group & Kador Group 2006). Despite the studies suggesting that green-certified buildings can enhance IEQ and support human wellbeing, direct data on objective health measures are limited and inconsistent. This makes it challenging to establish quantitative relationships between green certifications and health in real-world indoor environments, also due to the fact that buildings are characterised by diverse populations, with different sensitivities, profiles and dynamic exposure requirements.
The underlying causes for the inconsistent evidence of improved satisfaction, health and cognitive performance in green-certified buildings result, in part, from limitations of the prevailing research methods. A synthesis of the literature reveals substantial inconsistencies in the methods employed for data collection and analysis, and in the criteria adopted for driving inferences (Table 1).
|EXAMPLE OF RESEARCH DESIGN LIMITATIONS||SELECTED REFERENCES|
|Inconsistency between post-occupancy research hypotheses and design intents (e.g. evaluation for human-centric lighting versus design for work plane illumination)||Leder et al. (2016), Altomonte et al. (2019), Pastore & Andersen (2019)|
|Inconsistent and non-standardised occupant surveys||Meir et al. (2009), Duarte Roa et al. (2020)|
|Reliance on indirect and subjective metrics||Ucci & Godefroy (2020)|
|Little or no control of confounding variables, such as socio-economic, demographic or health factors||Evans & Kantrowitz (2002), Brown et al. (2015)|
|Limited or constrained efforts to establish rigorous peer or control groups for comparative studies or objective matching between green-certified and non-certified buildings||Newsham et al. (2013), Mac Naughton et al. (2017), Lee et al. (2019, 2020)|
|Limited consideration for sample size or statistical power||Brown & Cole (2009), Thatcher & Milner (2012), Agha-Hossein et al. (2013)|
As a result, it is often difficult or impossible to aggregate data across various studies to compare and benchmark performance and to draw more general conclusions.
In terms of the collection of physical measurements to characterise IEQ and to couple them with subjective assessments (Steinemann et al. 2017), attention should be given to the potential divergences between what is measured at the building level and what is perceived (and valued) by occupants (e.g. Bluyssen et al. 2011; Altomonte et al. 2020). Such spatial and temporal discrepancies might require differentiation of approaches and priority between:
A final common issue to address in study design is the inclusion and consideration of independent variables. Studies typically lack reporting information specific to rating level, categories, credits and metrics. This leads, among other impacts, to: (1) a difficulty in identifying the design features that influence building and occupant outcomes; (2) an assumption that attainment of a specific IEQ credit is directly related to improved IEQ and satisfaction; and (3) the supposition that certification level corresponds to IEQ level. While certification level could be considered an independent variable that is confounded by the inherent flexibility of various green rating systems, obtaining information at the category, credit or metric level is essential to drive the development of certification tools. Since implementation of green building practices varies by geographical location (relative to local or national requirements), building function (e.g. office, retail), rating system version and type, and other relevant circumstances (e.g. building typology, systems, etc.), the definition of design or operational features in green certification schemes could lead to inadequate and inconsistent independent variables.
Despite decades of research and practice, it is clear that the green building industry lacks a common framework for IEQ design and delivery. A recent paper by Wei et al. (2020) summarised nearly 100 measures and methods currently used by research and practice to benchmark IEQ in buildings.
For example, Wei et al. (2015) reported more than 40 metrics used to describe IAQ alone. This is due to the diversity of indoor air pollutants and their myriad impacts on health and cognitive performance. Researchers have attempted to synthesise these IAQ metrics with composite indexes, such as the attempts of Wargocki et al. (2021) and Salis et al. (2017) and other methods summarised therein. Salis et al. (2017) proposed a method to balance indicators of short- (acute) and long-term (chronic) effects on perceived air quality and health with reference to the exposure limits and disability adjusted life years (DALYs). Yet, this work has not yet been incorporated into mainstream rating tools.
Central to the discussion on IEQ measures is the potential development of a framework for determining an overall IEQ quality rating based on the quality of its individual components (thermal, acoustic, visual and indoor air quality). Few examples of these attempts presenting thoughtful, and often novel, solutions towards IEQ assessment are shown in Table 2.
|EXAMPLES OF PROPOSED METHODS FOR IEQ ASSESSMENT||SELECTED REFERENCES|
|Rating of satisfaction with individual IEQ components with respect to the overall satisfaction with the indoor environment||Clausen et al. (1993), Alm et al. (1999), Jin et al. (2012)|
|IEQ index based on the functions describing the percentage of dissatisfied people across multiple IEQ parameters||Piasecki et al. (2017)|
|IEQ index based on five factors, including air temperature, relative humidity, CO2 concentration, horizontal illuminance and sound pressure level||Wong et al. (2018), Huang et al. (2012)|
|IEQ evaluation method based on the parameters prescribed by EN 16798-1 (2020)||Danza et al. (2020)|
|IEQ asset rating method for residential buildings linking design expectations with occupant evaluations||Larsen et al. (2020)|
|Method that combines measurements of energy performance, IEQ and wellbeing indicators||Magyar et al. (2021)|
|IEQ index based on combined IEQ measurements determined with reference to EN 16798-1 (2020) and WHO (2006) air quality guidelines||Wargocki et al. (2021), Mujan et al. (2021)|
Important in these proposals is the rating of the relative impact of different components of IEQ. For example, Frontczak & Wargocki (2011) summarised various studies combining indices of IEQ and concluded that, in the perception of building occupants, thermal comfort is often given slightly higher importance over indoor air quality and the acoustic environment, and much higher importance than visual comfort. However, the study also suggested that the existing evidence does not provide clear guidance on how to weigh IEQ components. The same conclusion was reported by Piasecki & Kostyrko (2018). Other studies emphasised that the relative importance of individual IEQ components can differ widely (e.g. within different socio-cultural and environmental contexts). These factors make it challenging to create a generally applicable unified IEQ index (Humphreys 2005). Even though some weighting methods have been proposed (e.g. Chiang et al. 2001; Buratti et al. 2018; Mujan et al. 2021), their robustness has not been widely tested. As a consequence, many rating systems default to giving equal weight to all IEQ components, assuming that they contribute equally to the overall IEQ performance. Although specific approaches vary, the present body of research suggests that a comprehensive IEQ index must include:
These core principles are a good starting point; however, there are conceptual and practical barriers to the development and application of a universally applicable IEQ benchmark.
It can also be noted there are also yet no standard modelling approaches to robustly simulate IEQ in buildings. This is also due to the complexity of the hypotheses (e.g. temporal scales, stochastic effects, etc.) that underlie such models, while the reliability of predictions might vary between different IEQ parameters.
During recent years in research and practice, a new emphasis has been given to design and operation criteria that move beyond the conventional categories of energy efficiency and IEQ and shift their focus from the building to the complex and multifaceted needs and requirements of their users (e.g. Bluyssen 2010; McArthur & Powell 2020). To support this change in thinking, new metrics and tools are required that can consistently encompass health and wellbeing outcomes. These must be coupled with new data-collection methods that are continuous and reliable without being intrusive, yet free from experimental biases (e.g. fatigue and Hawthorn effects).
A series of trade-offs might often need to be resolved to respond to targets of energy efficiency and occupant requirements in terms of comfort, satisfaction and wellbeing (Altomonte et al. 2020). Building occupants have an awareness and express their preferences with respect to their perceived sensory environment (e.g. warmer, more light, lower air speed) based on their current states, transient activities and immediate expectations (Rohde et al. 2020). However, they might have sparse understanding of the conditions necessary to maintain a building’s energy balance or the ranges and mixture of stimuli necessary to trigger their metabolic and physiological functions (e.g. circadian rhythms) over longer timeframes (e.g. on a daily, weekly or even seasonal basis), or their physical and mental health.
Substantial progress is being made by scientific research to better characterise the requirements of the various human systems, their internal connections and the variability of their responses. For example, instead of considering IEQ factors in isolation and under static conditions, recent studies have brought attention to the effect of cross-modal exposures (e.g. Castaldo et al. 2018), analysing human reactions to the synergistic or antagonistic combination of many different stimuli (e.g. Tang et al. 2020).
New metrics and tools are recently becoming available to gather building and user data, under controlled or field study conditions, in order to better identify the environmental factors—or combinations thereof—that mostly matter to the perceptions and states of building occupants (e.g. Duarte Roa et al. 2020). This will allow the definition of more robust models to predict actions and behaviours in response to changes in indoor and outdoor settings and exposures (Hong et al. 2017; O’Brien et al. 2020).
IEQ is central to most widely used green building rating systems. However, current practices suffer from both the ‘equal weighting’ phenomena described above and the inherent flexibility available in voluntary rating tools. The BREEAM, LEED and Green Star rating schemes assign 10–20% of the rating value to IEQ criteria (Doan et al. 2017; Wei et al. 2020), and typically allow projects to select practices across multiple performance categories (e.g. energy, IEQ, transportation). This allows projects to achieve certification without an emphasis on IEQ, particularly for low-rated buildings (e.g. Silver versus Platinum). In practice, the implementation of IEQ practices varies significantly among green-certified projects, often lagging the adoption rate of energy-related criteria (Teichman et al. 2013).
Potential reasons for the predominant emphasis given to energy-related issues relative to IEQ may include the factors summarised in Figure 3. As previously mentioned, some new and recently updated green certification schemes have established prerequisites per each category (e.g. WELL v2, LEED v4.1), which reduce the possible trading of IEQ for energy related credits. However, the evidence of their effectiveness in delivering improved operational IEQ is still lacking.
Another important system-level design challenge for international green building certification schemes is often the lack of credit and scoring customisation at a global scale. Unlike local schemes, international green rating systems seldom emphasise needs based on specific regional, cultural, climatic and building characteristics—all to be recognised by customised IEQ credit scores. The lack of customisation in scoring might result in inconsistent recognition for different levels of effort and leadership. For instance, low indoor PM2.5 levels are equally awarded in countries with markedly different outdoor air pollution levels. A building located in an area of pristine air quality might be perceived as a global leader in a particular IEQ category, and yet a local laggard. Similarly, some green building programmes require a management plan for IEQ without giving specific directions, which can result in two buildings achieving radically different IEQ performance and yet obtaining the same certification level.
Trade-offs also occur within the IEQ credit category. Most rating systems encourage projects to select from a menu of IEQ practices and performance areas. This feature is designed to provide flexibility; however, it also creates a situation where teams may focus on one or a few metrics at the expense of others. This has the potential to create situations where projects do not address IEQ elements of concern for a specific building context.
The inclusion of different IEQ metrics varies widely across green building certification schemes (Wei et al. 2020). For IAQ, the most frequent proxies are limited to the level of CO2 and ventilation rate (Wei et al. 2015). The majority of certification schemes do not include health-relevant metrics such as secondary volatile organic compounds (SVOCs), various toxic chemicals, biological pollutants or a consideration of infectious diseases, circadian rhythms, electromagnetic fields, and personal control. The absence of many other health-relevant metrics often reflects financial and technical challenges, such as the cost of assessments or the lack of reliable reference benchmarks (Allen et al. 2015).
Within the IEQ category, it is also possible to have conflicts between strategies. For example, occupant-level control of thermal conditions may conflict with efforts to increase daylight penetration (Hodder & Parsons 2007; Tzempelikos et al. 2010). These are not necessarily defects in the intent or strategy; however, they do reflect the lack of an integrative framework to inform trade-offs. An additional challenge is the practice of ‘greenwashing’ through the introduction of new green building materials and products, or their unregulated alternatives, which might have not been comprehensively studied for health and safety (Dahl 2010; Steinemann et al. 2017).
Large global organisations for standardisation, rating and accreditations such as the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE), European Committee for Standardization (CEN), International Organization for Standardization (ISO), American Institute of Architects (AIA) and even various green building councils operate under a set of well-defined hierarchies, systems and revenue sources. They are linked to widely adopted ‘minimum’ codes and point systems that are considered relatively reserved towards the adoption of novel, forward-thinking, outcomes that include primary consideration of human health.
The scientific literature reports that, among 31 green building rating systems from 30 countries worldwide, 39% rely on the ASHRAE 62.1 standard and 23% are based on the European EN 15251 and EN 13779 codes, whereas others rely on local regulations (Wei et al. 2015). These standards typically share features including (Persily 2015; ASHRAE 2017):
These codes and standards often function as an anchor for rating systems, which typically encourage incremental improvements relative to these baseline levels. This can make it difficult to encourage changes that researchers have shown to yield significant health and performance benefits. For example, increasing ventilation above code requirements is predicted to:
Despite this evidence, rating systems continue to use industry-accepted codes as a prerequisite for performance.
Green building rating systems criteria are organised around the life system of buildings, including design and construction, fit out, operation, and renovation. Their criteria reflect the opportunities and limitations of these phases:
All three situations create IEQ performance assessment challenges.
The constraints of project phasing and life-cycle are reflected in rating system requirements for performance measurement. Key constraints include:
Rating systems have traditionally responded to these factors with flexibility, assigning these criteria to optional credits, instead of prerequisites. A few systems require demanding performance verification in operation, yet even in these cases established protocols are often sporadic (Afroz et al. 2020). For example, WELL v2 and BEAM Plus (Hong Kong) require occasional performance testing once every three and five years, respectively (WELL 2021).
The limitations of discontinuous measurement requirements and the emergence of new, lower cost measurement technology have encouraged the adoption of continuous, distributed approaches to IEQ monitoring. Key features of these efforts include ubiquitous data, fast and iterative feedback, and place-based solutions (Morawska et al. 2018). Some certification schemes award additional points for efforts to continuously monitor certain IEQ components (e.g. WELL v2). These requirements, however, have limitations in terms of the number of monitored parameters, frequency of measurements and spatial density of sensors.
The use of low-cost continuous sensors is, however, often unable to capture certain indicators of interest (e.g. air pollutants), for which laboratory-based or industrial-hygiene methods would be necessary (e.g. Schieweck et al. 2018). None of the existing green building schemes demands continuous measurements of outdoor conditions. While there are new players working on the improvement of existing approaches (e.g. RESET, Arc Re-Entry1), various scientific, technological, legal and institutional barriers remain for more effective deployment of continuous sensing.
Specifically, expectations and the ability to measure physical conditions are not sufficiently matched by the development of methods for data analysis, scoring, interpretation and communication, which can result in a lack of evidence-based guidelines for sampling/analytics and metrics for building performance. Also, methodologies on how to use this information are sparse, resulting in large, but underused, data sets (Zanella et al. 2014). New players on the market increasingly create their own monitoring programmes and select elements that suit them best. This creates discrepancies in protocols and data infrastructure requirements across rating systems that limit comparability (Afroz et al. 2020) and the creation of benchmarks.
Rating systems are more than the sum of prerequisites and credits. They are implemented by professionals sharing a common understanding of the goals and a technical vocabulary. However, expectations for these professionals vary widely. Zhang et al. (2019) found that only 18 of 49 rating systems require an accredited team member. Specific to the issues in the present paper, it is also notable that IEQ is only a small fraction of training material and there is no requirement for prior experience or education. This means that rating system training is not likely to be a reliable predictor of IEQ expertise. Loose requirements for acquiring accreditations stem from the concern that posing stricter conditions might hinder the adoption of a certification scheme. Some rating system developers are filling this gap with specialised training, such as the WELL Accredited Professional and FitWel Ambassador credentials.
Since their inception, green building certification systems have had a profound influence on the construction industry globally, guiding building practitioners, owners and managers to shape the qualities of built spaces. This paper has explored the opportunities and challenges facing the green building industry seeking to improve the promotion of health and human experience. From the evidence-based research challenges summarised in Section 3, and the practical observations outlined in Section 4, two sets of complementary recommendations are now offered for researchers and rating system developers.
Advances in IEQ will require targeted investment in critical knowledge gaps and technical capabilities. Table 3 summarises the key recommendations for researchers that could help overcome the current challenges of research development in green-certified buildings summarised in Section 3.
|CURRENT STATE||PROPOSED RESEARCH RECOMMENDATIONS|
|Inconsistency in methods leading to difficulties in robust benchmarking (see Section 3.1)||
|Lack of reporting of independent variables (see Section 3.1)||
|Lack of a clear consolidated framework for IEQ performance measurements (see Section 3.2)||
|Limited capacity of current modelling approaches to reliably predict IEQ and occupant outcomes in buildings (see Section 3.2)||
|Investigation of human responses to IEQ that are currently over-regulated within narrow and static ranges (targeting neutrality and average acceptability) (see Section 3.3)||
|Investigation of monotonic human responses to environmental stimuli (see Section 3.3)||
|Lack of collaboration across disciplines||
Rating systems turn scientific research and technical capabilities into practical market transformation tools. Section 4 above shows that they can be more effective in promoting human health and experience in buildings. Table 4 summarises key proposed recommendations for rating system developers that could help overcome existing limitations.
|CURRENT STATE||PROPOSED RECOMMENDATIONS|
|Relative priority on environmental/energy performance over health and experience. Variable adoption of indoor environmental quality (IEQ)-related credits (see Section 4.1)|
|Lack of customisation in IEQ scoring at a global scale (see Section 4.1)||
|Pursuing IEQ credits that are not of primary concern for a specific building context (see Section 4.2)||
|Focus on conventional categories of IEQ and exclusion of many health-relevant metrics (see Section 4.2)||
|Insufficient transparency in requirements and measured outcomes. Practice of ‘greenwashing’ (see Section 4.2)|
|Heavy reliance on base requirements from conventional IEQ standards (see Section 4.3)||
|Loose and sporadic requirements for occasional IEQ performance verification (see Section 4.5)||
|Absence of requirements for continuous monitoring that make IEQ performance based on design and not actual conditions (see Section 4.5)||
|Underdeveloped methods for sampling, data analysis, scoring, interpretation and communication (see Section 4.5)||
|Loose and insufficient requirements to acquiring professional accreditation (see Section 4.6)||
|Lack of flexibility to encompass future occupant needs and adverse events||
Green building certifications are powerful market transformation tools. Health and human experience have been central to these systems since their inception. Today, knowledge and expectations are rising, and it is important for rating systems to raise the bar for recognition. Imagining a graphical representation of building performance, the pyramid presented in Figure 4 proposes a potential progression towards what could be the ‘future of green’ (Tier 4).
The envisioned future of green buildings (‘Tier 4’) will define leadership in the green real-estate industry by directing efforts towards integrated management of human (subjective and objective IEQ, health and human experience) and environmental objectives (circularity, resources and energy use). These goals are intertwined. Provision of healthy IEQ should not compromise ecological integrity, globally and locally, or responsibility for the planet and its people. The ‘future of green’ implies a change of approach from the avoidance of poor performance to the multiplication of the physical, social and mental opportunities that can support people’s flourishing and thriving. This emerging knowledge needs to be effectively translated into new design opportunities, enhancing rather than restraining creativity, offering an inspiration rather than a verification, the promotion rather than the constraint of ingenuity and imagination, and perhaps also with a focus given primarily to adaptive and adjustable measurement methods rather than the use of absolute and prescriptive metrics. These Tier 4 buildings will need to recognise and encourage practices that drive positive behavioural change that also extend beyond the time of being present in these buildings.
It is time to critically examine the priorities reflected in long-standing rating systems. Recent events, such as the global threat of Covid-19, have launched a new set of values and priorities, while redefining the way human health is thought about. This is accompanied by a greater sense of urgency related to climate action and supply chain impacts. The Tier 4 buildings will need to reflect such new needs with novel science and technologies, negotiating between trade-offs and prioritising over the potential occurrence of conflicting requirements.
1For RESET, see https://www.reset.build/standard/air; and for Arc Re-Entry, see https://arcskoru.com/sites/default/files/Arc%20Guide%20to%20Re%20Entry%20v1.2.pdf/.
Some early phases of this synthesis paper were undertaken as part of a joint work with Dr Seema Bhangar. The authors appreciate both her encouragement to pursue this specific topic independently and her constructive feedback.
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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