Association between Air Quality and Children’s Restorative Experience: A Systematic Review

Ling Wang; Qiuyi Yang; Qingqing Sun

doi:10.3390/atmos13111815

Abstract

Prior studies conducted within the realm of environmental psychology and public health have shown that air pollution exposure exerts significant effects on both physical and psychological well-being, especially for children. The roles of air pollution exposure are being increasingly recognized as essential factors influencing children’s restoration. This systematic review provides an overview of existing knowledge of the impact of air pollution on children’s mental health and restorative experience in both outdoor and indoor environments. A list of keywords for paper selection was derived from a systematic investigation of the literature on children’s restorative environments. A total of 228 studies were initially identified, 18 of which met the eligibility criteria. This systematic review summarizes distinctive categories of air pollutants and discusses the assessments for both air pollution exposure and children’s restorative outcomes. Additionally, 16 barriers in air pollution exposure to children’s restorative experience were identified. The findings of this systematic review were concluded in an integrated framework, which have important implications for developing evidence-based and cross-disciplinary research on the air quality and children’s restoration.

Keywords:

air pollution; particulate matter; children’s perceived restorativeness; mental health outcome; environmental evaluation; attention-deficit hyperactivity disorder

1. Introduction

1.1. Background

A large range of research has identified the restorative impact of nature on people’s physical and psychological health, yet little is narrowed down to the impact of the air quality on children’s mental health and well-being. This systematic review identifies pertinent themes in published multi-disciplinary literature relating to the impact of air pollution on children’s physical and psychological health. It provides an overview of what has been researched in the relationships between air pollution exposure and children’s health.

The literature on restorative environments has been expanding rapidly, among which the importance of nature on people’s restorative experience has aroused great attention. Apart from the field of environmental psychology, restoration reflects its potential on other broad research realms, including public health, outdoor recreation, developmental psychology, and sociology. Restorative experiences refer to the renewal of resources (physical, psychological, and social) that have been depleted in meeting the demands of everyday life [1]. Much of the literature shows that exposure to natural settings could facilitate the process of restoration [2,3], thus stimulating working and improving health and well-being [4]. Among the literature on children’s restorative experience, there are some common types of environmental exposure, including UV radiation from the sun, plants, vegetation, noise, and air pollution, to name but a few.

Air quality, as an essential part of environmental features, has been reported to be associated with health by a number of studies [5]. Currently, air pollution is suggested as one of the largest health threats among all of the environmental risk factors. Various studies have proved that long-term exposure to air pollution contributes to adverse mental health outcomes [5]. Specifically, air pollution exposure is also correlated with attention deficit, fatigue, and other psychological problems, negatively affecting the restorative process [6]. Considering children’s vulnerability to the physiologic effects of pollutants, air quality has considerate impact on the mental health of children [7].

1.2. Objectives

Children within early childhood to 18 years of age are included in this systematic review. Since past literature has not included any systematic study on the role of air pollution exposure as a contributor to children’s restorative experience, it is, thus, important to delve deeper into this topic. The main goal of this article is to investigate:

What past literature has focused on the air pollution exposure on children’s restorative experience, including psychological health outcomes, attention, stress, anxiety, etc.?
Which tools and assessments have been applied to examine the impact of air pollution exposure on children’s restorative experience?
What are the barriers in research of air pollution exposure and children’s restorative experience?

2. Previous Literature Related to Children’s Restorative Experience: A Review

One of the most important theories that guide many of these studies related to restoration is the Attention Restoration Theory (ART) which links the restorativeness of environments to the restoration of attentional resources [2,3]. Attention restoration theory (ART) emphasizes four features of environments that could facilitate restoration: being-away, fascination, extent, and compatibility [3]. Past literature shows that there are several specific metrics in mental health that are used to examine children’s perceived restorativeness [8,9,10,11,12,13]. Table 1 showcases 13 works in the literature related to children’s restorative experience and analyzes the methodologies, descriptions, findings, and outcome measurements for children’s perceived restorativeness.

Table 1. Analysis of Literature Related to Children’s Restorative Experience.

Attention Restoration Theory (ART) links the restorativeness of environments to the restoration of attention resources [2,3]. On the basis of this theory, attention ability is considered as an important metric correlated with perceived restorativeness [10]. Attentional ability is especially important in research conducted in indoor school environments [11,13] and has been paid greater attention in studies targeted at children with Attention Deficit Hyperactivity Disorder (ADHD) [9]. Psychological stress is another important indicator of perceived restorativeness when discussing children’s restorative experience with an exposure to nature. Prior research has shown that restorative environments can contribute to reducing stress [14,15,16,17]. Third, psychological well-being is considered as an indicator of children’s restoration as well. In studying the relationship between environment and children’s restorative experience, well-being can be divided into three aspects, namely emotional, cognitive, and social [9]. Noticeably, social wellness, which indicates healthy relationships with others, is rarely mentioned. Social well-being indicates the process of sharing, developing, and sustaining meaningful relationships with others.

3. Materials and Methods

3.1. Analytical Framework

According to the research objectives, this study can be divided into three steps: (1) data collection, (2) data analysis, and (3) discussion, implication, and conclusion (Figure 1). On the basis of the keywords selected in the theoretical background and the inclusion and exclusion criteria, the literature review is conducted for data collection. Grounded theory is applied to identify characteristics of literature review including categories, assessment tools, and barriers. Then the Delphi method is used to determine the relationships among deliverables. After data analysis, implications of research on air quality and children’s restorative experience are proposed and conclusions are made.

Figure 1. The Analytical Framework.

3.2. Paper Selection for Literature Review

As the key for systematic review, a search strategy was developed for data collection. In order to identify and retrieve accurate results in the intersection of children, restoration, and air quality, five search terms were provided. On the basis of the analysis of literature related to children’s restoration, children’s restorative experience is assessed through five components including attention, stress, cognitive development, mental health, and emotion. In order to assess the association between air quality and children’s restorative experience, the search strategy identified five keywords and terms including (1) children attention air, (2) children stress air, (3) children cognitive air, (4) children mental air, and (5) children emotion air. The relevant literature was identified through electronic searches including Web of Science, PubMed, and Embase published from January 2018. Additional records were identified through manual searching and screening.

3.3. Inclusion and Exclusion Criteria

The inclusion criteria are shown in Table 2: (1) studies related to psychological health; (2) studies related to air quality; (3) studies targeting children; (4) studies focusing on the association of air quality and children’s restoration; and (5) focusing on neuroscience.

Table 2. Inclusion and Exclusion Criteria.

4. Results

A total of 228 articles were identified through combined database searches and manual searching. After removing duplicates, 18 studies met the defined inclusion criteria (Table 3).

Table 3. Paper Selection Process.

The steps followed to select studies, and the search strategies used, are shown in Figure 2. Extracted data from the literature include author, year, country, category, exposure assessment methods/pollutants, outcome assessment, barriers, and gaps, as is shown in Table 4.

Figure 2. The Systematic Literature Search with Inclusion and Exclusion Criteria.

Table 4. Extracted Data of Included Literature.

Six of the qualified studies were conducted in North America, five in Europe, four in the UK, one in Australia, and one in Asia (Figure 3). Nine studies focused on the ambient air pollution and four studies specifically focused on the residential air pollution. Traffic-related air pollutants (TRAP) was also a popular area for studying its impact on children’s restorative experience. Three studies examined traffic-related air pollutants (TRAP), one of which was conducted in classrooms. There are also three studies focusing on indoor air quality on children’s restorative experience (Figure 4).

Figure 3. Country Distribution of the Literature.

Figure 4. Categories of Air Pollution in the Literature.

4.1. Outdoor Air Pollutants on Children’s Restorative Experience

In the study of the impact of ambient air pollution on children’s restorative experience, thirteen articles targeted at outdoor air quality (Figure 5). The outdoor air pollutants could be categorized into particulate air pollution (PM₁₀, PM_2.5, UFPs, and EC/BC) and gaseous air pollution (NO₂, NO_x, SO₂, O₃, and CO). Amid the literature of outdoor particulate air pollution on children’s restorative experience, most articles (64.3 percent) explored the association between PM_2.5 exposure and children’s restorative domain, whereas 63.3 percent of studies focused on NO₂ exposure on children’s restorative experience when examining gaseous air pollutants. Overall, PM_2.5 and NO₂ exposure are two main air pollutants associated with children’s restorative domain.

Figure 5. Outdoor Air Pollutants Distribution.

A total of fourteen associations were found regarding ambient particulate air pollutants on children’s restorative experience (PM₁₀; n = 3 studies, PM_2.5; n = 9 studies, UFPs; n = 1 studies, EC/BC; n = 1 studies). Two studies found no association between particulate matter and children’s restorative experience [25,31]. However, one study showed statistical associations between PM₁₀ and the relative risk of ADHD on children [39]. In terms of studies on PM_2.5 and children’s restorative experience, nine associations were investigated in which four significant associations were observed [25,26,30,40]. The negative effects of PM_2.5 on children’s restorative domains include cognitive abilities, stress, emotional and behavioral problems, depression, anxiety, or ADHD. It is worth noting that the effects of PM_2.5 on children’s restorative domain differ specifically in different areas [30]. Roberts et al. suggested that associations between PM_2.5 exposure and symptoms of depression are statistically significant, but no significant associations were observed between PM_2.5 exposure and later symptoms of anxiety or ADHD [30]. Black and elemental carbon (BC and EC), as a component of particulate matter, are emitted from combustion. One study investigated the association between EC/BC and self-reported symptoms of depression and anxiety [34]. Meanwhile, the study by Yolton et al. also illustrated the associations between UFPs (ultrafine particles) and self-reported symptoms of depression and anxiety [34,43,44]. In total, there is more evidence about the detrimental effects of PM on children’s restorative experience, compared with EC/BC and UFPs in the particulate air pollutants category.

Eleven associations were discovered on gaseous air pollutants (NO₂; n = 7 studies, SO₂; n = 1 studies, O₃; n = 1 studies, NO_x; n = 1 studies, CO; n = 1 studies). Eight studies examined the associations between NO₂ exposure and children’s restorative domain, with one study reporting no association [31] and another study examining insufficient evidence [32]. The negative effects of NO₂ on children’s restorative domains included depression, conduct disorder, anxiety, or ADHD. There were also two studies examining the association between SO₂ and children’s restorative experience [36,40]. Three studies identified the association between NO_x, O₃, and CO and children’s restorative domain separately [25,31,40]. Overall, the number of studies reporting an association between air pollution and children’s restorative experience was relatively higher compared with the number of studies reporting no association.

4.2. Indoor Air Pollutants on Children’s Restorative Experience

There were three articles focusing on indoor air quality on children’s restorative experience [29,36,38]. There were two studies examining the roles of both outdoor air pollution and indoor air quality in children’s restorative domain, especially the cognitive ability and mental health [36,38]. When exploring indoor air pollutants, damp or condensation and secondhand smoke exposures were often measured. Specifically, Tª, relative humidity, black carbon (BC), CO₂, and PM_2.5 were some of the common exposures in the indoor air quality [29].

4.3. Children’s Restorative Outcome

When studying the impact of air quality on children’s restorative outcomes, several outcome measurements were used, including cognitive ability, attention, mental health disorder, anxiety, depression, behavior, and emotion (Figure 6). Attention level was examined in six studies, among which three studies focused on children with ADHD. Cognitive ability and anxiety were mentioned in four articles separately. As a type of emotional disorders, anxiety was found to be highly associated with air quality both indoor and outdoor. However, only one study examined the behavioral disorders in children considering its difficulty and complexity.

Figure 6. Categories of Children’s Restorative Outcome Measurements.

4.4. Barriers in Air Quality Studies in Children’s Restorative Experience

4.4.1. Data from the Literature Review

Through this literature review of a number of articles, we have acquired some knowledge concerning the association between air quality and children’s restorative experience. However, certain gaps and barriers in the literature are evident. According to these 18 articles, 16 barriers were summarized, as shown in Table 5. Among all 16 barriers, “lack of tools to capture individual level air pollution exposure accurately” (B01) was mentioned the most. Air pollution exposure was measured mostly using central monitors, while individual level exposure measurement is missing. “Difficulties in characterizing cumulative exposure at different developmental stages and age ranges or over the entire life-course” (B05), “lack of air pollution exposure data from daycares and school areas where children spend a large amount of time” (B08), and “inability to control other environmental confounds associated with or that vary within environments” (B13) are the other three main barriers.

Table 5. Barriers Obtained from the Literature Review.

4.4.2. Categories of Barriers

Sixteen barriers in studies between air quality and children’s restorative experience were classified by spindle coding, and they were divided into assessment tool, research scale, spatial and temporal difficulties, considered confounders, cross-disciplinary studies, and indoor and outdoor difference, as shown in Table 6. After applying grounded theory, no new concepts and categories were discovered, indicating a saturation of research.

Table 6. The Categories of Determined Barriers.

There remain various barriers in assessment tools for both air pollution exposure assessment and restorative-related assessment. One of the biggest barriers in measuring air pollution exposure is the lack of tools to capture individual level air pollution exposure accurately. In the study by Ahmed et al., ambient pollution in the neighborhood instead of children’s personal exposure in specific locations was assessed [30]. Personal monitors are suggested to capture individual exposure, which could also combine other factors, such as individual activity patterns and the time spent outdoors together [25,28,29]. Such a barrier in individual level air pollution exposure could be blamed on the lack of measurement of short-term timescales of air pollution exposure. In terms of children’s restorative outcomes, combination in measurements for ambulatory monitoring with ecological momentary assessment of stress is suggested [27,42].

Research scale is another barrier in studies related to air pollution exposure and children’s restorative experience, including the age range and population size. Many studies in this field focus on early childhood, with a few studies centering on adolescents [31]. Roberts et al. and Gignac et al. suggest comprehensively exploring exposures and outcomes over the entire life course, especially at the later stages of children’s development [30,33].

There are also spatial and temporal difficulties in studying air pollution in different geographical areas and seasons. Several studies report the inability to capture data during vulnerable periods [38,40]. Geographical differences, such as different air quality in urban and rural environments, contribute to the differences in children’s restorative experience such as attention level, anxiety, and depression [26,35]. Lack of air pollution exposure data from daycares and school areas where children spend a large amount of time is another important barrier since it is proven that children do not spend most of their time at home [41,45,46].

Limitations in considered confounding variables in these studies serve as essential barriers. Other environmental confounds associated with children’s restorative experience include noise pollution, availability of green space, etc. [30,34,36,37]. Apart from difficulties in controlling for potential environmental confounders, inadequate consideration of socioeconomic status of children such as parental mental health status should be addressed [29,41]. Moreover, it is also difficult to control genetic factors in influencing children’s restorative experience [30,34,47].

In studying the association between air pollution exposure and children’s restorative experience, the difference in the indoor and outdoor environments should be considered. However, current research lacks clarification of the differences between indoor and outdoor air quality. Specifically, the ambient PM_2.5 concentration is different from that in indoor environments [32,48,49]. Similarly, there is still a lack of consideration of differences in time spent indoor and outdoor [42]. Furthermore, cross-disciplinary studies are also needed to explore association between air quality and children’s mental health [50]. For example, climate change should also be taken into account since climate change and air pollution could amplify mental health deficits, contributing to unsatisfied restorative experiences [51,52].

4.4.3. Determining the Relationships between Barriers

The Delphi method is a process used to arrive at a group opinion or decision by surveying a panel of experts [53]. When determining the relationships between barriers, the Delphi method was employed to explore the interrelationships among the identified 15 barriers. Eight experts experienced in the field of environmental health determined the interrelationships among all 16 barriers, which is illustrated in Table 7. The relationships matrix consists of 16 columns and 16 rows. In the matrix, the value of 1 indicates that the barrier in the row has influence on the barriers in the column, and 0 indicates no relationship.

Table 7. The Barrier Relationships Matrix.

4.4.4. Network Modeling

Figure 7 shows the network model reflecting the influence relationships and intensity among each barrier, obtained through data analysis of the interrelationships among the 16 barriers. Each vertex represents a barrier in air quality and children’s restorative experience, and the size of the vertex represent the significance of the influences. The network model consists of 16 vertexes and 36 edges.

Figure 7. The Barriers Network Model.

4.4.5. Analysis of Network Model

Degree centrality represents the connectedness of each barrier. The degree distribution of all vertices in studying air pollution exposure and children’s restorative experience is shown in Figure 8. The barrier “lack of tools to capture individual level air pollution exposure accurately” (B01) has the highest degree of 7, which indicates that it is in an essential position of assessing air quality and children’s restorative experience. The barrier “inability to control other environmental confounds associated with or that vary within environments” (B13) and “lack of consideration of differences in time spent indoor and outdoor” (B16) have the next highest degree with a value of 6.

Figure 8. Degree Centrality Analysis of Barriers.

Closeness centrality represents the reciprocal of the average path from one vertex to the other, reflecting whether it is easy to impact other vertices. The larger the value of the closeness centrality of the 16 barriers in studying association of air pollution exposure to children’s restorative experience, the greater the likelihood of its impact. (Figure 9) According to the closeness centrality analysis, “lack of tools to capture individual level air pollution exposure accurately” (B01), and “inability to control other environmental confounds associated with or that vary within environments” (B13) have the highest closeness centrality of 0.625 which is associated with the result of degree centrality analysis. Meanwhile, the barrier “lack of larger, population-based cohort studies” (B06) and “lack of consideration of differences in time spent indoor and outdoor” (B16) also have a high value of 0.577.

Figure 9. Closeness Centrality Analysis of Barriers.

Betweenness centrality represents the number of shortest relationship paths passing through each vertex, representing the significance of influence. The values of vertex betweenness centrality range from 0.533 to 16.975. (Figure 10) The study found that “inability to control other environmental confounds associated with or that vary within environments” (B13), “lack of larger, population-based cohort studies” (B06), and “lack of tools to capture individual level air pollution exposure accurately” (B01) are the top three vertices with the largest values of 16.975, 16.575, and 16.442, respectively. This indicates that controlling environmental confounders, conducting population-based studies, and capture individual level of air pollution exposure are the most influential barriers. It is worth noting that the barrier “inability to control other environmental confounds associated with or that vary within environments” (B13) and “lack of tools to capture individual level air pollution exposure accurately” (B01) also score the highest in the degree centrality which indicates their key significances in improving the study of association of air pollution exposure to children’s restorative experience.

Figure 10. Betweenness Centrality Analysis of Barriers.

Comparing degree centrality, closeness centrality, and betweenness centrality analysis of barriers in environmental assessment for children’s restorative environments, “inability to control other environmental confounds associated with or that vary within environments” (B13), “lack of tools to capture individual level air pollution exposure accurately”(B01), “lack of larger, population-based cohort studies”(B06), “lack of consideration of differences in time spent indoor and outdoor ”(B16), and “lack of measurement of short-term timescales of air pollution exposure” (B03) are the top five barriers (Figure 11).

Figure 11. Contrasting Analysis: Degree Centrality, Closeness Centrality, and Betweenness Centrality of Barriers.

5. Discussion

Through the literature review of eighteen articles, we found that most studies show associations between air pollution and children’s restorative experience including stress, attention level, emotional deficit, and cognitive development. Most of the studies focus on the outdoor air pollution, whereas there are still a few studies focusing on the impact of indoor air quality on children’s restorative domain. Various types of air pollutants, including particulate and gaseous air pollutants, have been examined in children’s restorative experience, especially PM_2.5 exposure and NO₂ exposure. The study design of the literature included cohort and cross-sectional. In terms of the analysis on children’s restoration, restorative outcomes are specified into sub-categories and are measured through different assessment tools. Some studies suggest a difference in parent-reported and self-reported depression and anxiety which illustrates a difference in children and parents’ perspective of air pollution [34].

The relationships between air pollution and children’s restoration have received varied emphasis among study topics. However, we also found that one of the common problems in the literature is the lack of evidence to support the association. Papers stating the associations between air quality and children’s restorative experience are far more abundant than papers addressing their underlying mechanisms. One study shows that associations between air pollution and ADHD-MA in children is not significant, which requires further studies in epidemiological and biomedical fields to examine the molecular relationship between air pollution and ADHD symptoms [40]. The assessment tools for the exposure to air pollution is essential in determining pollution-related restorative outcomes in children [51,53]. However, not only should the measurements for both environmental exposure and children’s outcome exposure be improved, other barriers in assessing air pollution and children’s restorative experience should be addressed as well. Specifically, other related environmental confounds should be controlled in assessing air pollution exposure. For instance, although some studies indicate the potential role for childhood ambient air pollution exposure in the development of adolescent MDD, inclusion of environmental risk factors will be important in improving the analysis model [31].

Overall, the study of air pollution on children’s restorative experience can offer more meaningful results by more engaging more cross-disciplinary scholars in the field, including environmental psychology, health, epidemiology, and neuroscience. Considering the broad array of study topics on children’s restorative domain, there could be more novel perspectives in interpreting the impact of air quality on children’s restoration through collaboration among scholars and practitioners [46,47].

However, the limitations of our review are notable. First, our use of English language literature only may overlook some attention on air quality and children’s restoration toward Western culture. Nearly all papers we reviewed were studies from North America, Europe, or Australia. Consequently, the relevance of our findings to Asian, South American, and African landscapes, and among indigenous people globally is uncertain. Second, the classification criteria of children’s restorative experience need further scrutinization. The relationship between children’s restorative experience and mental health is not clear [54]. Third, the association between the air pollution and children’s restorative experience lack practical application in the field of environmental psychology, architecture, and urban planning. Questions such as how the impact of air quality on children’s restoration affect environmental design and child development need to be addressed in the future research.

6. Conclusions

This literature review suggests that a number of ambient air pollution exposures are associated with children’s restorative experiences, which is in parallel with previous findings on adults’ research. Apart from the categories of air pollutants in both outdoor and indoor environments, more attention has been paid to the influence on children’s perceived restorativeness. Barriers in studying air quality and children’s restorative experience are also identified and analyzed. For future studies of this emerging subject, there is still an urgent need for evidence-based research. This systematic review on air quality and children’s restorative experience encourages cross-disciplinary collaboration between researchers in various fields, planners, designers, and policy makers to create better environments for children’s mental health, well-being, and development.

Author Contributions

Conceptualization, Q.Y. and L.W.; methodology, L.W. and Q.Y.; software, Q.S.; validation, Q.S., L.W. and Q.Y.; formal analysis, Q.Y.; investigation, Q.S.; resources, L.W.; data curation, L.W.; writing—original draft preparation, L.W.; writing—review and editing, Q.Y. and Q.S.; visualization, Q.Y.; supervision, Q.S.; project administration, L.W.; funding acquisition, L.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. The Analytical Framework.

Figure 2. The Systematic Literature Search with Inclusion and Exclusion Criteria.

Figure 3. Country Distribution of the Literature.

Figure 4. Categories of Air Pollution in the Literature.

Figure 5. Outdoor Air Pollutants Distribution.

Figure 6. Categories of Children’s Restorative Outcome Measurements.

Figure 7. The Barriers Network Model.

Figure 8. Degree Centrality Analysis of Barriers.

Figure 9. Closeness Centrality Analysis of Barriers.

Figure 10. Betweenness Centrality Analysis of Barriers.

Figure 11. Contrasting Analysis: Degree Centrality, Closeness Centrality, and Betweenness Centrality of Barriers.

Table 1. Analysis of Literature Related to Children’s Restorative Experience.

Author and Year	Methodology	Description	Findings	Outcome Measurements
van den Berg and Van den Berg (2011) [9]	Qualitative and Quantitative	This study examines the influence of contact with nature on children with ADHD comparing natural and built settings.	Nature provides a positive restorative environment for children with ADHD.	Attention, Stress
Collado and Staats (2016) [18]	Literature review	This article offers an overview of current restorative research with children.	Exposure to nature has restorative benefits to children.	/
Korpela et al. (2002) [19]	Qualitative and Quantitative	This study examined the role of restorative experience and self-regulation in the formation of children’s place preferences.	Children like to use their favorite places for restoration and emotion-regulation.	Emotion
Amicone et al. (2018) [10]	Quantitative: Pre- and post-test	This article conducted two field studies to test the hypothesized positive effect of recess time spent in a natural (vs. built) environment on pupils’ cognitive performance and their perceived restorativeness.	There is an increase in sustained attention after the natural environment condition and a decrease after the built environment condition.	Attention
Bagot (2004) [20]	Quantitative	This study uses school playgrounds and their school library to examine perceived restorative components for children.	School playgrounds have higher restoration potential than school libraries.	Mental health
Bagot, Allen, and Toukhsati (2015) [21]	Quantitative	This study examines the predictors of restorativeness of children’s school playgrounds, using Attention Restoration Theory.	Level of naturalness impacts children’s restorative experience, which is different from that of adults.	Stress, Restorative
Collado and Corraliza (2015) [22]	Quantitative	This study explores the relation between exposure to nature and environmental behaviors.	Exposure to nature could improve children’s restorative experience, resulting in pro-environmental behaviors.	Restoration, Attention
Corraliza et al. (2012) [23]	Quantitative	This study used Perceived Restoration Components Scale for Children (PRCS-C) to analyze the impact of nature in school playgrounds on children’s perceived restoration.	Including nature in school playgrounds has a positive effect on children’s perceived restoration.	Restoration, Attention
Kelz et al. (2015) [8]	Mixed methods: A pre–post, quasi-experimental design	This study investigated the influence of a redesign (greening) of a schoolyard on pupils’ physiological stress, psychological well-being, and executive functioning.	Students in the renovated schoolyard setting perceived the environment as more restorative following the redesign.	Stress, Well-being
Mårtensson et al. (2009) [12]	Quantitative	This study uses the outdoor play environment categories (OPEC), the sky view factor, and tools for behavior of attention to assess the restorative potential of green outdoor environments for children in preschool settings.	The restorative potential of green outdoor environments applies to preschool children. Meanwhile, environmental assessment tools, such as OPEC, can be useful.	Attention
Barbiero et al. (2021) [11]	Quantitative	This study compared a conventional learning environment with two nature-based environments created according to biophilic design to examine the relationship between biophilic design and children’s (1) attentional performance, (2) perceived restorativeness, and (3) affiliation with nature.	Learning environments with biophilic design are perceived as more restorative, supporting children’s attentional performance and connection with nature.	Attention
Van den Berg et al. (2017) [13]	Quantitative	This study evaluated the restorative impacts of green walls with living plants in classrooms of two elementary schools using a controlled, prospective design.	Empirical support for green walls as a means for restorative classroom design is provided.	Attention, Well-being
Bernardo et al. (2021) [24]	Quantitative: Pre- and post-test	This study uses pre-and-posttests to examine the effect of introducing greenery to the classroom in children’s cognitive performance.	Children’s sustained attention is increased with the presence of greenery in the classroom which indicates further implication of nature’s role in human–environment interactions.	Cognitive, Attention

Table 2. Inclusion and Exclusion Criteria.

Inclusion Criteria	Exclusion Criteria
Studies related to psychological health	Studies not related to psychological health Epidemiology studies, such as those related to oxidative stress Respiratory and cardiovascular health
Studies related to air quality	Studies not related to air quality
Studies targeting children	Studies not targeting children Studies targeting pregnancy
Studies focusing on the association of air quality and children’s restoration	Studies not focusing on the association of air quality and children’s restoration
Studies focusing on neuroscience	Studies focusing on neuroscience

Table 3. Paper Selection Process.

Database	“Children Attention Air”	“Children Stress Air”	“Children Cognitive Air”	“Children Mental Air”	“Children Emotion Air”	Subtotals Combining Keywords	Not Related to Psychological Health	Not Related to Air Quality	Not Targeting Children	Not Focusing on the Association	Focusing on Neuroscience	Literature Review	Remaining Papers
Web of Science	3	4	11	4	0	16	−3	−1	−4	−2	/	−2	4
PubMed	64	101	63	61	28	203	−58	−19	−53	−14	−37	/	22
Embase	1	2	7	4	0	9	−2	/	−1	−1	−2	/	3
subtotal													29
remaining papers after combining													18

Table 4. Extracted Data of Included Literature.

Author and Year	Country	Category	Exposure/Pollutants	Outcome	Barriers and Gaps
Shier et al. (2019) [25]	The USA	Ambient air pollution	Ambient concentrations of O₃, PM_2.5,and PM₁₀	Cognitive outcomes through reading and math tests	Lack of individual exposure to incorporate individual activity patterns and time spent outdoors; difficulties in characterizing cumulative exposure over the entire life-course; difference in accuracy
Thygesen et al. (2020) [26]	Denmark	Residential air pollution	NO₂ and PM_2.5 from air-modeling data	Clinical diagnoses of ADHD	Lack of comparison across other urban and rural environments; disregard of genetic factors in influencing mental health; lack of data from daycares where children usually spend time
Olson (2021) [27]	The USA (Los Angeles)	Ambient air pollution	Concentrations of three air pollutants (NO₂, PM_2.5, and O₃)	Mental health disorder using psychiatric emergency department visits	/
Yu and Weitzman (2021) [28]	/	/	/	/	Gaps in understanding the links between climate change, air pollution, and mental health
Junge et al. (2021) [29]	Spain (Barcelona)	Indoor air quality exposure at school	Tª, relative humidity, black carbon (BC), CO₂, and PM_2.5	Attention level	/
Roberts et al. (2019) [30]	The UK (England and Wales)	Residential air pollution	Annualized PM_2.5 and NO₂ concentrations	Anxiety, depression, conduct disorder, and attention deficit hyperactivity disorder	Lack of comparison across other urban and rural environments; disregard of genetic factors in influencing mental health; lack of information in school areas; inability to control other factors associated with or that vary within urban environments; lack of larger, population-based cohort studies; lack of comprehensive assessments of exposures and outcomes at different developmental stages
Latham et al. (2021) [31]	The UK	Ambient air pollution	Annual exposure to four pollutants–nitrogen dioxide (NO₂), nitrogen oxides (NO_X), and particulate matter <2.5 μm (PM_2.5) and <10 μm (PM₁₀)	The risk of developing major depressive disorder (MDD)	Lack of monitors to capture individual exposure accurately; inability to control other confounds associated with or that vary within environments; lack of comprehensive assessments of exposures and outcomes at different developmental stages
Ahmed et al. (2022) [32]	Australia	Ambient air pollution	Annual PM_2.5 and NO₂	Emotion and behavior, and developmental delay in communication and gross motor skills in children <13 years	Lack of monitors to capture individual exposure accurately; difficulties in exploring later stages of the children ’s development; inabiltiy to capture exposure during vulnerable periods of the scale of days to weeks; lack of clarification of the differences between indoor and outdoor air quality
Gignac et al. (2021) [33]	Spain (Barcelona)	Traffic-related air pollutants (TRAP) conducted in classrooms	Average levels of PM_2.5, black carbon (BC), CO₂, temperature, humidity	Attention level	Lack of measurement of short-term timescales of exposure; lack of comprehensive assessments of exposures and outcomes at different developmental stages and age ranges
Yolton et al. (2019) [34]	The USA (Cincinnati)	Traffic-related air pollution (TRAP)	Exposure to elemental carbon attributable to traffic (ECAT) including PM_2.5, elemental and black carbon (EC/BC), NO₂, and UFPs	Self-reported and parent-reported depression and anxiety	Exposure misclassification due to time spent away from the home; disregard of genetic factors in influencing mental health; inability to control other confounds associated with or that vary within environments
Ni et al. (2021) [35]	China (Shenzhen)	Ambient air pollution	Air pollution, including nitrogen dioxide (NO₂), sulfur dioxide (SO₂), particulate matter 2.5 (PM_2.5), ozone (O₃), etc.	Positive Youth Development and emotional disorders (i.e., anxiety, neuroticism, and withdrawal)	Lack of comparison across other urban and rural environments; lack of assessment tool for air quality exposure; inability to control other confounds associated with or that vary within environments
Midouhas et al. (2019) [36]	The UK (England and Wales)	Outdoor air pollution and indoor air quality	Outdoor (NO₂ and SO₂), indoor (damp or condensation and secondhand smoke exposures)	Emotional, conduct, and hyperactivity problems	Inability to control other confounds associated with or that vary within environments; inability to account for outdoor pollutants that may come from adjacent neighborhoods; lack of assessment tool for air quality exposure
Brunst et al. (2019) [37]	The USA (Cincinnati)	Traffic-related air pollution (TRAP)	TRAP exposure	Anxiety symptoms	Inability to control other confounds associated with or that vary within environments
Midouhas et al. (2018) [38]	The UK (England and Wales)	Outdoor air quality and indoor air quality	Outdoor (NO₂), indoor (damp or condensation and secondhand smoke exposures)	Cognitive ability	Lack of measurement of short-term timescales of exposure
Markevych et al. (2018) [39]	Germany	Outdoor air pollution and greenspace	Population-weighted mean values of PM₁₀, NO₂, and NDVI	ADHD incidence	Lack of monitors to capture individual exposure accurately; lack of consideration of medical and socioeconomic status
Saadeh et al. (2022) [40]	The USA (Pennsylvania)	Ambient air pollution	Daily measurements of air pollutants (SO₂, CO, and PM_2.5)	ADHD medication administration (ADHD-MA)	Lack of data from daycares and school areas where children spend a large amount of time; lack of data in different seasons
Rivas et al. (2019) [41]	Spain (Barcelona)	Residential air pollution	PM_2.5 exposure	Working memory, attentiveness, and conflict network	Lack of data from daycare and school areas where children spend a large amount of time; lack of consideration of medical and socioeconomic status
Miller et al. (2019) [42]	The USA (Northern California)	Residential air pollution	PM_2.5	Autonomic reactivity to social stress in adolescents, anxiety, and depression	Lack of consideration of differences in time spent indoor and outdoor; lack of measurement of short-term timescales of exposure; lack of comparison across other urban and rural environments; lack of improvements in assessment tool for physiological health

Table 5. Barriers Obtained from the Literature Review.

Code	Barrier	Key References
B01	Lack of tools to capture individual level air pollution exposure accurately	[25,31,32,35,36,39]
B02	Difference in accuracy of air pollution exposure geographically	[25]
B03	Lack of measurement of short-term timescales of air pollution exposure	[33,37,42]
B04	Lack of improvements in assessment tool for physiological health	[42]
B05	Difficulties in characterizing cumulative exposure at different developmental stages and age ranges or over the entire life-course	[25,30,31,32,33]
B06	Lack of larger, population-based cohort studies	[30]
B07	Lack of comparison across different geographical areas such as urban and rural environments	[26,30,35,42]
B08	Lack of air pollution exposure data from daycares and school areas where children spend a large amount of time	[26,30,34,40,41]
B09	Lack of air pollution exposure data in different seasons	[32,40]
B10	Inability to account for outdoor pollutants that may come from adjacent neighborhoods	[36]
B11	Inadequate consideration in socioeconomic status of children	[25,39,41]
B12	Disregard of genetic factors in influencing mental health	[26,30,34]
B13	Inability to control other environmental confounds associated with or that vary within environments	[30,31,34,36,37]
B14	Gaps in understanding the links among climate change, air pollution, and restoration	[28]
B15	Lack of clarification of the differences between indoor and outdoor air quality	[32]
B16	Lack of consideration of differences in time spent indoor and outdoor	[42]

Table 6. The Categories of Determined Barriers.

Category	Barrier Code
Assessment tool	B01, B02, B03, B04
Research scale	B05, B06
Spatial and temporal difficulties	B07, B08, B09, B10
Considered confounders	B11, B12, B13
Cross-disciplinary studies	B14
Indoor and outdoor difference	B15, B16

Table 7. The Barrier Relationships Matrix.

	B01	B02	B03	B04	B05	B06	B07	B08	B09	B10	B11	B12	B13	B14	B15	B16
B01	-	0	0	0	1	0	0	1	0	1	0	0	1	0	1	1
B02	0	-	0	0	0	1	1	0	0	1	0	0	0	0	1	0
B03	1	0	-	0	0	0	0	1	1	0	0	0	0	0	1	0
B04	0	0	0	-	1	0	0	0	0	0	1	1	0	0	0	1
B05	0	0	0	0	-	1	0	0	0	0	0	0	0	0	0	0
B06	0	0	0	0	0	-	1	0	0	0	0	0	0	1	0	0
B07	0	0	0	0	0	0	-	0	0	0	0	0	0	0	0	0
B08	0	1	0	0	0	0	0	-	0	0	0	0	0	0	0	1
B09	0	0	1	0	0	0	0	0	-	0	0	0	0	1	0	0
B10	0	0	0	0	0	0	1	0	0	-	0	0	0	0	1	0
B11	0	0	0	0	1	0	7	0	0	0	-	0	1	0	0	0
B12	0	0	0	0	0	0	0	0	0	0	0	-	1	0	0	0
B13	0	0	0	0	0	1	1	0	0	0	1	0	-	0	1	1
B14	0	0	0	0	0	0	0	0	0	0	0	0	0	-	0	0
B15	0	1	0	0	0	0	0	0	0	1	0	0	0	0	-	0
B16	0	0	0	1	0	0	0	0	0	0	1	1	1	0	0	-

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