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Is CO2 a good proxy for indoor air quality in classrooms? Part 1: The interrelationships between thermal conditions, CO2 levels, ventilation rates and selected indoor pollutants
Abstract
Current indoor air quality (IAQ) guidelines in school buildings are framed around thermal conditions, carbon dioxide (CO2) levels and corresponding ventilation rates without considering specific indoor pollution levels. Drawing on detailed monitoring data from a sample of 18 classrooms from six London schools, the aim of this paper is to highlight behavioural and environmental factors that affect pollution levels in classrooms, and evaluate the adequacy of CO2 as an overall predictor for IAQ using multilevel modelling. Together with elimination of indoor emission sources, keeping the temperatures below 26℃, and preferably below 22℃ depending on season, may limit total volatile organic compounds below thresholds associated with sensory irritations. The models suggested that after removing dust reservoirs from the classrooms, lowering average indoor CO2 levels below 1000 ppm by increasing ventilation rates can limit indoor airborne particulate matter concentrations below recommended annual WHO 2010 guidelines. Uncontrolled infiltration rates may increase indoor NO2 levels and microbial counts of fungal and bacterial groups, whose presence is associated with wet and moist materials. Overall, indoor CO2 levels were a useful proxy for indoor investigations as they can prevent overheating, dilute pollutants with indoor sources and purge concentrations of airborne particles; however, they were a poor predictor of traffic related pollutants. Practical implications of the findings on the UK policy and building design industry are discussed.
... The World Health Organization (WHO) reported 3.2 million deaths yearly due to indoor air pollution [7]. In classrooms and office buildings, carbon dioxide (CO 2 ) is generally regarded as an indicator of IAQ and ventilation, since elevated levels of CO 2 are linked to poor ventilation [8][9][10]. The maximum allowable concentration of CO 2 is an essential parameter in determining IAQ, since humans are the primary source of CO 2 generation through the natural exhalation process. ...
... Educational institutions and dormitories need more attention regarding ventilation rate (VR) and IAQ due to their high occupancy rates and specific character associated with human health and working efficiency [10]. Excluding combustion from stoves and heaters, human respiration is the main contributor to indoor CO 2 , which directly increases with the number of occupants in residential, commercial, and public buildings [1,2]. ...
... The measurement of CO2 indoors and its relation to IAQ and ventilation have been the subject of many research studies [10,51,52]. Three techniques using CO2 as a tracer gas to measure the indoor air change rate are build-up, steady-state, and decay [53,54]. ...
Indoor air quality (IAQ) in higher education institutions’ dormitories, without mechanical ventilation, is a significant concern for students’ health due to prolonged occupancy in cold regions. The present investigation assessed IAQ by measuring two dormitories’ CO2, temperature, and relative humidity with the presence of one, two, three, and four occupants in the United Kingdom. Considering the possibility of natural ventilation by opening the windows in the summer, IAQ was monitored using two sensors located at 1 m and 2 m heights from the floor level of the dormitories in July. The tracer mass balance model showed close agreement with the monitored IAQ levels, with a direct relationship observed between occupant numbers and CO2 build-up. CO2 levels exceeded 1000 ppm within an hour during occupancy and closed ventilation, with air exchange rates between 0.12 and 0.2 h⁻¹, increasing to 1334, 1259, 1884, and 2064 ppm after 30 min with one, two, three, and four occupants, respectively. Desired IAQ standards (1000 ppm) were achieved in 13, 33, 80, and 86 min for one, two, three, and four occupants after starting natural ventilation by opening 20% of the windows. The analysis of variance affirmed the effect of occupancy on IAQ, while the impact of height (1 m and 2 m) on CO2 levels was insignificant. This study underscores the need to effectively ventilate the partial opening of windows in dormitories to mitigate CO2 build-up, ensuring the desired ambient environment within dormitory rooms during summers in cold regions.
... On average, classrooms accommodate four times more people per square metre than typical office spaces [9]. The high occupancy densities (ODs) in school classrooms result in high internal gains and emissions of body odour together with various occupant-generated indoor pollutants [14]. Children are more vulnerable to indoor air pollutants than adults because their bodies and organs are actively developing [15]. ...
... CO2 levels are the primary metric for assessing VR and IAQ in classrooms [10,14] and are increasingly referenced in ventilation and IAQ standards [24]. CO2 represents a practical and easily measured proxy for ventilation rates (VR) in occupied spaces [25,26]. ...
... Research has indicated that classrooms with CO2 concentrations exceeding 1000 ppm are potentially under-ventilated [28][29][30][31][32][33], with ideal VR maintaining indoor CO2 concentration levels between 600 and 1000 ppm [34][35][36]. Elevated classroom CO2 concentrations have been associated with increased concentrations of indoor pollutants [14,37], a decrease in occupant satisfaction with IAQ [38], an increase in the frequency of IAQ-related health symptoms [2,39], increased absenteeism [3,5], and a reduction in both learning performance and staff productivity [40,41]. ...
Indoor air quality (IAQ) in schools significantly impacts occupant health and academic performance, especially in naturally ventilated (NV) classrooms, where CO2 levels are often elevated. This systematic review synthesises findings from 125 studies, examining CO2 as an indicator of ventilation rates (VRs) and its impact on IAQ, health, and academic performance in NV primary school classrooms. This analysis highlights seasonal and temporal variations in CO2 concentrations, revealing a median CO2 concentration of 1487 ppm across 2444 classrooms, with 81% exceeding the recommended 1000 ppm threshold. Influencing factors include VR, occupant density, generation rates, and occupant behaviours. Increased VRs consistently lowered CO2 levels and enhanced IAQ. CO2 concentrations correlated with particulate matter, volatile organic compounds, bioeffluents, microbial concentrations, and bacteria and fungi levels, but not with traffic-related pollutants like NO2, which is associated with asthma prevalence. Elevated CO2 levels consistently correlated with fatigue, headaches, respiratory symptoms, reduced academic performance and absenteeism, suggesting potential socio-economic benefits of increased VRs. However, effective IAQ management requires balancing ventilation with considerations of thermal comfort, noise, and outdoor pollutants. The findings highlight the need for standardised IAQ indices and CO2 monitoring protocols, offering insights for future research, intervention design, and investment aimed at enhancing classroom environments.
... Several occupational environments (e.g., offices, schools and hospitals) have been studied. Schools have been investigated to quantify the exposure levels of pupils to gaseous pollutants (NO 2 , CO 2 , O 3 , VOCs), aerosols (including bioaerosols such as fungi and bacteria) and polybrominated diphenyl ethers (PBDEs) in dust (21)(22)(23)(24)(25)(26)(27)(28)(29). The impacts of building construction and ventilation rates were also investigated in relation to concentration levels in UK classrooms (23,28,(30)(31)(32). ...
... Schools have been investigated to quantify the exposure levels of pupils to gaseous pollutants (NO 2 , CO 2 , O 3 , VOCs), aerosols (including bioaerosols such as fungi and bacteria) and polybrominated diphenyl ethers (PBDEs) in dust (21)(22)(23)(24)(25)(26)(27)(28)(29). The impacts of building construction and ventilation rates were also investigated in relation to concentration levels in UK classrooms (23,28,(30)(31)(32). Indoor air pollution levels were also monitored during working hours in offices focusing on levels of PM 2.5 , NO 2 and VOCs related to cleaning and smoking activities (33,34) or to ventilation rates in natural and mechanically ventilated working places (35,36). ...
... The type of sampler is highly variable and depends on the pollutant and type of analysis. Aerosol species (PM 10 , PM 2.5 , PM 1.0 ) measurements were carried out mainly using active sampling techniques, with only a small number of articles using passive samplers (23)(24)(25). Gravimetric sampling was used for indoor air measures (55,56) and for personal exposure studies (57). Optical counters were widely used for aerosol measurements in personal exposure studies (20,37,39,58) and indoor air (16,41). ...
The global attention on indoor air quality is progressively increasing as people spend ca. 80 to 90% of their lives indoors. Therefore, a substantial fraction of exposure to air pollution occurs in different indoor environments. However, there is a lack of information on how different time and activity dependent sources and built environment characteristics affect air pollutant emissions and their distribution. There is an urgent need to develop indoor emissions inventories to estimate the contribution of multiple and time-dependent sources and activities to air pollutant emissions. This paper reviews the current state-of-the-art of indoor air pollution research in the UK, categorises the published literature according to pollutant types, built environments and activities, provides an overview of typical levels of indoor air pollutants with a focus on UK-specific measurements and identifies the research gaps and future directions to progress towards developing indoor emission inventories. In the UK, researchers have investigated indoor air quality since the nineties producing many studies from different perspectives. However, a cohesive methodological approach is lacking in most of the studies. Several important sources/species are not represented, ancillary information relating to environment characteristics (volumes and ventilation) and occupants' behaviours during the measurements is not reported and too little information on the indoor–outdoor continuum is provided. Despite the gaps identified, the existing evidence base on indoor air pollution in the UK can be categorised in an easy-to-use database of indoor air pollutant concentrations and characteristic emission rates for specific activities, pollutants and environments. This will provide a platform for designing standardised approaches for indoor air quality measurements and the development of activity-based indoor emission inventories, which will be a step-change in indoor air pollution research in the UK and globally.
... The findings reveal the causes of indoor contaminants because of air-blown dust from traffic on roads, activity patterns and cleanliness levels in classrooms, automobile emissions from roadside traffic, industrial emissions from nearby industries, paint emissions, and emissions from building materials. A longitudinal study in five primary schools in London has been performed, involving 15 classrooms (Chatzidiakou et al. 2015a(Chatzidiakou et al. , 2015b. According to the findings, the prevalence of asthma attacks among children in urban schools is more than in suburban schools. ...
... According to a study by Chatzidiakou et al., installing hard tiles may result in lower indoor PM 10 and PM 1 concentrations than carpeting by an average of 38 g/m 3 and 29 g/m 3 , respectively (Chatzidiakou et al. 2015a(Chatzidiakou et al. , 2015b. They recommended that the school adopt fleecy cleaning cloths, switch the carpeted floor out for hard tiles, and use cleaning supplies wisely in order to reduce VOCs exposure. ...
The primary route of COVID-19 infection is airborne transmission, which occurs when an infected person's aerosol droplets are inhaled. To mitigate the spread of the airborne virus, maintaining proper indoor air quality (IAQ) levels is essential. Children are more vulnerable to poor IAQ because they breathe more air per unit of weight and are more susceptible to heat, cold and moisture. Cohesive information based on interventions to control IAQ is essential for making informed decisions on their deployment and greater uptake. We seek to fill this information gap by synthesizing the available scientific literature through this comprehensive study which examines the indoor air pollutants in school buildings and their respective health effects on children with the latest policy interventions and proposes a path for the future school environment. It is reported that high carbon dioxide (CO2) level causes lethargy and sleepiness leading to poor school attendance, volatile organic compounds (VOCs) cause contact dermatitis, allergic rhinitis, conjunctivitis and lung cancer, particulate matter (PM) causes cardiovascular disease and asthma. Proper ventilation improved the test scores of students and chalkboards usage resulted in chalk dust, contributing to PM10 concentration. The leading causes of poor IAQ are inappropriate building envelopes, inadequate ventilation and lack of appropriate legislative interventions. No one technique has been identified as the only effective way to limit exposure to contaminants, but their combined use can be efficient in the majority of situations. For the best effects, more research is required on evaluating integrated interventions and how to synchronize their operations.
... Adequate ventilation must be ensured for providing safer and healthier classroom environment for students, because during classroom hours, the occupation density is high (close to 1.8 m 2 /pupil) and students inhale more indoor air (Theodosiou and Ordoumpozanis, 2008). Although CO 2 is not an air pollutant, but still can be considered as a proxy for classroom air quality (Chatzidiakou et al., 2015), maintaining proper ventilation to maintain better air quality in classroom. Majd et al. (2019) found that physical defects in the school building, such as cracks and holes in the walls, broken windows and peeling wallpaper or paint, were associated with higher indoor NO 2 concentrations. ...
... School playgrounds expose children to particulate matter and other vehicular emissions due to their closer proximity to roads or their location along a major road (Famuyiwa et al., 2018).. Some other structural measures include relocating the playgrounds and free flow spaces to the less polluted areas of the school premises, relocating pedestrian entrance, co-ordinating start and finish time with nearby schools, and providing additional space for scooter or cycle parking (Toolkit, 2018). Chatzidiakou et al. (2015) found in their study that providing hard-tiles flooring may lead to an average of 38 μg/m 3 and 29 μg/m 3 lower indoor PM 10 and PM 1 respectively, as compared to the carpeted floor. They suggested that replacing the carpeted floor with hard-tiles, proper selection of cleaning products and fleecy cleaning cloth introduced in the classroom can limit the exposure to TVOCs.. School buildings play an important role in maintaining better IAQ and to prevent health problems in students, therefore, school infrastructure upgradation should be carried out by schools at regular interval. ...
Students spend nearly one third of their typical day in the school environment, where they may be exposed to harmful air pollutants. A consolidated knowledge base of interventions to reduce this exposure is required for making informed decisions on their implementation and wider uptake. We attempt to fill this knowledge gap by synthesising the existing scientific literature on different school-based air pollution exposure interventions, their efficiency, suitability, and limitations. We assessed technological (air purifiers, HVAC - Heating Ventilation and Air Conditioning etc.), behavioural, green infrastructure, structural, school-commute and policy and regulatory interventions. Studies suggest that the removal efficiency of air purifiers for PM2.5, PM10, PM1 and BC can be up to 57 %, 34 %, 70 % and 58 %, respectively, depending on the air purification technology compared with control levels in classroom. The HVAC system combined with high efficiency filters has BC, PM10 and PM2.5 removal efficiency up to 97 %, 34 % and 30 %, respectively. Citizen science campaigns are effective in reducing the indoor air pollutants' exposure up to 94 %. The concentration of PM10, NO2, O3, BC and PNC can be reduced by up to 60 %, 59 %, 16 %, 63 % and 77 %, respectively as compared to control conditions, by installing green infrastructure (GI) as a physical barrier. School commute interventions can reduce NO2 concentration by up to 23 %. The in-cabin concentration reduction of up to 77 % for PM2.5, 43 % for PNC, 89 % for BC, 74 % for PM10 and 75 % for NO2, along with 94 % reduction in tailpipe emission of total particles, can be achieved using clean fuels and retrofits. No stand-alone method is found as the absolute solution for controlling pollutants exposure, their combined application can be effective in most of the scenarios. More research is needed on assessing combined interventions, and their operational synchronisation for getting the optimum results.
... The CO 2 concentration is an indicator of the retention of harmful substances, as its concentration increases with inadequate ventilation in buildings [18][19][20][21][22]. Many countries have regulatory standards and guidelines to maintain CO 2 concentrations below a fixed level (around 1000 to 1500 ppm) within buildings such as offices, schools, and houses [18,22,23]. ...
... 2.1. CO 2 Concentration as an Indicator of IAQ CO 2 concentration is widely utilized as a comprehensive indicator of air pollution in IAQ [18][19][20][21][22]. Table 1 summarizes the CO 2 concentration standards and guidelines for various countries [18,22,23]. ...
Indoor air quality (IAQ) in houses is often deteriorated by chemical substances emitted from heating, building materials, or other household goods. Since it is difficult for occupants to recognize air pollution, they rarely understand the actual conditions of the IAQ. An investigation into the actual condition of IAQ in houses was therefore conducted in this study. Carbon dioxide (CO2) concentrations in 24 occupied houses was measured, and the results from our analysis showed that the use of combustion heaters increased the concentration of CO2 and led to indoor air pollution. Results indicate that as outdoor temperature decreased, the frequency of ventilation decreased simultaneously, and CO2 concentration increased. Results of the questionnaire survey revealed that the actual IAQ in each house did not match the level of awareness its occupants had regarding ventilation. Along with this difficulty in perceiving air pollution, the lack of knowledge about ventilation systems and the effects of combustion heating may be additional barriers to IAQ awareness.
... Investigations into classroom air quality and student responses have indicated a strong link between air quality and students' attention processes, with high levels of CO 2 concentration leading to reduced attention span and decision-making abilities among students [25][26][27]. Beyond investigations concerning CO 2 concentration and its effects on occupants' well-being, findings from several researchers have indicated that, in practical terms, CO 2 concentration can serve as a proxy for IAQ acceptability [6,9,22,28,29], the appropriateness of air exchange, and whether sufficient fresh air is being introduced into indoor environments [28,30]. ...
The quality of indoor environments within educational settings significantly impacts the health, safety, and comfort of occupants. In this manuscript, a simplified Classroom Indoor Air Quality (CIAQ) Risk Index, aimed at assessing the potential ability of classrooms to maintain CO2 levels within acceptable limits, is introduced. Comprising three primary components—the likelihood of surpassing predefined CO2 thresholds, the potential number of individuals exposed, and the classroom’s capacity to withstand or mitigate threats—this index serves as a valuable compliance tool during both the design phase and operational management of educational spaces. Additionally, apart from presenting the index framework, a sensitivity case study analysis is carried out to verify the suitability of the proposed method and the sensitivity of the factors involved. Through this analysis, the robustness of the CIAQ Risk Index in various scenarios is demonstrated. By quantifying and evaluating potential risks associated with indoor air quality, the CIAQ Risk Index contributes to ongoing efforts to create healthier indoor environments. Furthermore, it facilitates the identification of budgetary mitigation strategies that should positively affect the air quality; among those, an intervention, retrofitting, and ventilation improvements can be listed. Through proactive risk identification and appropriate actions, including regulation adjustments and ventilation strategies, the reduction in health problems, the enhancement of well-being, and the improvement of overall performance and quality of life for educational communities can be achieved.
... Modern demand-controlled ventilation systems use real-time measurements of carbon dioxide (CO 2 ) concentration levels to adjust the ventilation rate, providing good indoor air quality during high occupancy and reducing energy consumption during low occupancy [14,15]. CO 2 is a useful metric for estimating ventilation rates and modelling indoor air quality, because its concentration strongly correlates with human-emitted air pollutants (bioeffluents) and volatile organic compounds [16][17][18]. The negative effects of poor indoor air quality on cognition and health are often linked to bioeffluents and volatile organic compounds [4,19]. ...
... Sensory irritation as well, under specific environmental conditions, can be caused by some VOCs in the air (7). Elevated carbon dioxide (CO 2 ) levels are a sound indicator of poor IAQ, and are used as guidelines for the IAQ of school buildings (8). These compounds potentially irritate the nose, eyes, and throat, and result in symptoms of nausea, headache, dizziness, and fatigue (2). ...
Indoor air quality (IAQ) in educational environments significantly impacts student health and productivity. This research presents an electronic system for monitoring IAQ, focusing on detecting carbon dioxide (CO) and volatile organic compounds (VOCs) using a microcontroller-based prototype. Inspired by previous research linking poor IAQ with student performance, this system was developed to measure and analyze these parameters for use in educational facilities. The proposed system utilizes commercially available Arduino-based sensors and components, enabling real-time data collection and analysis. Preliminary results indicate that the system detects changes in CO and VOCs levels in real-time. The system was designed to wirelessly send real-time sensor readings to an online dashboard, which allows for sharing the data to the cloud. The data can be internally shared with the members of an institution to allow for intervention if necessary. This research emphasizes sensor calibration and validation, ensuring the system's readiness for real-world classroom settings, and offering a practical solution to improve IAQ in educational environments.
... Although indoor pollutant levels have decreased since the 1950s, increased indoor occupancy (80-90% of daily activities) driven by technological advancements and energy-efficient building designs has elevated exposure risks and long-term health impacts [46]. Reducing indoor CO 2 levels below 1000 ppm through increased ventilation has been shown to lower particulate matter concentrations to within WHO guidelines [47]. Elevated CO 2 levels in poorly ventilated environments have been associated with reduced cognitive performance, increased work errors, and symptoms such as fatigue and headaches. ...
This study explores energy consumption, thermal performance, and indoor environmental quality (IEQ) in terminal buildings. Through detailed thermal analysis, this research identifies key sources of heat loss, such as thermal bridges in walls and windows, which significantly increase energy demands for heating. IEQ measurements show that the lack of mechanical ventilation, combined with high passenger densities, frequently leads to CO2 levels exceeding recommended thresholds, highlighting the urgent need for improved ventilation systems. Energy requirements were calculated based on the TS 825 standard and compared to actual consumption data, showing that optimizing boiler settings could save 22% of heating energy without any additional investment. Simulations and economic analyses further showed that adding thermal insulation to the building envelope and installing double-glazed windows with improved U-values could achieve significant energy savings and reduce CO2 emissions, all with favorable payback periods. A life cycle assessment (LCA) was conducted to evaluate the environmental impact of these interventions, demonstrating significant reductions in the airport’s carbon footprint. The findings underscore the importance of aligning operational standards with international guidelines, such as ASHRAE and CIBSE, to ensure thermal comfort and optimize energy use.
... Standards provide thresholds of CO 2 concentration emitted by users breathing in an indoor space as an indicator of IAQ. CO 2 levels over 1000 ppm indicate an indoor air potential problem [6]. When this limit is overcome, air becomes stagnant [7]. ...
The success of educational institutions is fundamentally intertwined with the well-being and academic progress of their students. In this context, indoor air quality (IAQ) and thermal comfort play a critical role in creating conducive learning environments that support both health and academic performance. This work evaluates six ventilation systems and strategies for enhancing IAQ and thermal comfort, which prevail in educational buildings in the Spanish region of Catalonia. To do so, a multi-criteria analysis is performed based on the Analytic Hierarchy Process (AHP) method, considering economic, social, and environmental aspects. Ventilation systems are pairwise compared in terms of six criteria: initial and maintenance cost, classroom air quality, students’ thermal comfort in summer and winter, and energy consumption. Subsequently, weighted combinations of these criteria are established to rank the ventilation systems under five case scenarios. The results indicate that natural ventilation systems, particularly those with atriums and courtyards (N-AAC), offer a balanced solution, achieving satisfactory IAQ and thermal comfort while being more cost-effective and environmentally sustainable in certain contexts. The variation in the best solution across different scenarios demonstrates that the optimal choice is highly context-dependent, influenced by factors such as budget, climate, and infrastructure. This research provides a valuable foundation and methodology for decision-makers in educational institutions, supporting the selection of ventilation systems that maximize sustainability while enhancing students’ comfort and fostering learning environments.
... Sensory irritation as well, under specific environmental conditions, can be caused by some VOCs in the air (Wolkoff, 2013). Elevated carbon dioxide (CO 2 ) levels are a valid indicator of poor IAQ, and are used as guidelines for the IAQ of school buildings (Chatzidiakou et al., 2015). These compounds potentially irritate the nose, eyes, and throat, and result in symptoms of nausea, headache, dizziness, and tiredness (Saini et al., 2020). ...
... When CO 2 concentrations exceed 1000 ppm, individuals may experience dizziness and fatigue [9]. As many indoor pollutants are positively correlated with CO 2 concentrations, monitoring changes in CO 2 concentration can serve as an indicator for controlling indoor air quality [10,11]. ...
Natural ventilation has become a focal point due to its positive impact on indoor air quality, expanding its role in addressing thermal comfort issues in schools. Despite previous studies exploring various approaches to enhance natural ventilation, factors such as classrooms facing non-windward directions and optimal window opening sizes have not been adequately considered. This lack of consideration poses challenges for implementation in school environments. To address this issue, this study employed response surface methodology, back-propagation neural network, and multiple linear regression to investigate the effects of different factors on natural ventilation. Experiments were conducted in classrooms facing nonwindward directions, measuring indoor air changes per hour (ACH) during peak noon temperatures. Thermal comfort was assessed using the predicted mean vote (PMV). The experimental results showed that single window openings provided better thermal comfort compared to cross window openings while maintaining indoor CO2 concentrations below 1000 ppm. Furthermore, subsequent analysis revealed that the opening size (open and open/gap) increases the range of ACH, suggesting avenues for future research to enhance natural ventilation practices. This underscores natural ventilation’s potential in maintaining indoor thermal comfort and CO2 levels under challenging conditions.
... Des études montrent que la terre est un matériau hygroscopique, généralement poreux qui adsorbe et désorbe les molécules d'eau dans leur environnement (Collet et al., 2010;Tchiotsop et al., 2022), mais peu d'analyse de cas en exploitation prouve que la bauge participe au confort hygrique d'un bâtiment. De plus, la qualité de l'air suscite un intérêt grandissant puisqu'une concentration trop élevée en particules fines et en CO2 peut causer des nausées, de la fatigue et des maladies (Chatzidiakou et al., 2015;Jones, 1999). Or, la qualité d'air intérieur des bâtiments en terre reste encore très méconnue. ...
RESUME Le changement climatique et l'augmentation des gaz à effet de serre suscitent un intérêt croissant pour des solutions de construction durables et respectueuses de l'environnement tels que les constructions en terre. Dans cette perspective, le projet européen CobBauge a donné naissance à un bâtiment prototype instrumenté dont les murs multicouches sont composés de bauge et de terre allégée. L'analyse des données issues de cette instrumentation révèle une possible contribution des éléments en bauge et en terre allégée sur la régulation de l'humidité, de la concentration en CO2 et des particules fines de taille inférieure à 2,5 µm (PM2.5). Au final, ce cas d'étude montre que l'utilisation de matériaux géo-sourcés peut avoir un impact sur la qualité de l'air au sein du bâtiment et augmenter le confort des habitants. Mots-clefs Bauge, Terre allégée, Qualité des ambiances, Bâtiment prototype Modalité de présentation Poster
... Studies focusing on children's performance and cognitive abilities suggest a noteworthy correlation with exposure to carbon dioxide levels. Chatzidiakou, Mumovic, and Summerfield [63] propose that monitoring carbon dioxide serves as a useful proxy for assessing Indoor Air Quality (IAQ), indicating lower indoor pollutants and toxic particle elimination. However, a study challenges the concept that carbon dioxide exposure solely causes declines in children's cognitive performance, highlighting the multifaceted nature of IAQ effects [61]. ...
COVID-19 has improved awareness of the importance of appropriate indoor air quality (IAQ) in indoor spaces, particularly in classrooms where children are expected to learn. Research has shown that poor IAQ and temperature levels affect the cognitive performance of children. In this paper, we critically compare IAQ standards for New Zealand’s Designing Quality Learning Spaces (DQLS Document) against international benchmarks from the Organization for Economic Co-operation and Development (OECD) countries, including ASHRAE 62.1, CIBSE TM57, EN-15251, WHO AQGs, and Building Bulletins 99 and 101. The aim was to ascertain the robustness of New Zealand’s DQLS document, identify areas of superiority, and recommend the required improvement for appropriate IAQ and thermal comfort in classrooms. This comparison review focuses on IAQ parameters: CO2 levels, temperature, ventilation rates, room size, occupant density, and occupancy rates. The findings illuminate a slight lag in New Zealand’s DQLS standards compared to her international counterparts. For instance, while New Zealand’s standards align closely with WHO standards for IAQ concerning temperature and ventilation rates, the recommended CO2 range appears slightly inadequate (800 to 2000 ppm) along with occupancy and classroom size for effectively controlling classroom pollutant growth. This paper emphasises the need to align New Zealand’s IAQ and thermal comfort standards with optimal OECD benchmarks. The identified disparities present opportunities for improving learning spaces in terms of CO2 concentration, size of classroom, and occupant density in schools in New Zealand to meet globally recognised standards, ultimately creating a healthier and more conducive learning environment.
... Moreover, the dependency of Italian classrooms on natural ventilation systems leads to growing indoor air pollutants and IAQ reduction in those spaces [7]. carbon dioxide (CO 2 ) is a good bio-effluent indicator [8], thus its concentration rate commonly is used as the primary indicator of IAQ [9] [10]. Additionally, the COVID-19 pandemic has prompted renewed interest in the assessment of IAQ in school classrooms [11] [12]. ...
Indoor air quality (IAQ) in school buildings is a fundamental requirement that influences students' health and academic productivity. This paper employs the Internet of Things (IoT) technology to develop a cost-effective and multi-function sensor network system that monitors indoor air parameters such as temperature, relative humidity (RH), carbon dioxide equivalent (CO 2 eq), and total volatile organic compounds (TVOC). In addition, the sensor collects occupants' feedbacks through a user-friendly command board and makes it possible to estimate the ventilation efficiency of a room, thanks to the connection with additional sensors capable to monitor the opening and closing patterns of windows and doors. An experimental procedure was conducted in a school classroom to test the system's performance, present the methodology for data reading, and evaluate indoor air quality. The system has demonstrated its efficacy in raising awareness among users about indoor air quality and has proven to be an effective tool for qualitative and quantitative control of natural ventilation. These systems present new opportunities for the aggregation of multi-source data and for creating pollution distribution maps in the future, leveraging the system's low cost and wide reach. The main results showed low user sensitivity to air quality and TVOC content, while a better understanding of temperature and CO 2 levels was observed, but without a complete understanding of the actual measurement data. However, simultaneous opening of windows and doors can provide the recommended ventilation rate for health (4 L/s per person) and decrease all concentrations below 1500 ppm. The device developed and the tested procedure can therefore contribute to systemic monitoring of the phenomenon, predicting patterns of opening and closing of windows and improving ventilation management in spaces. The paper also contains a series of electrical specifications and material selection criteria to support the construction of the device.
... Although the research community debates the impact of carbon dioxide on human health, it has been largely accepted that carbon dioxide levels are a useful proxy of the quality of air and the likelihood of the existence of other pollutants in the air [28]. As stressed out by ASHRAE in their 2022 position document on indoor carbon dioxide, indoor CO 2 levels are a useful tool in IAQ assessments when users properly understand the associated limitations, but they do not provide an overall indication of IAQ since these emissions are not related to other contaminants that are not linked to occupancy, such as building materials and furniture [29]. ...
... Replacement of building materials and furniture is Indoor Air also a strategy that belongs to structural measures [78,79]. The carpeted floor with hard tiles, proper selection of cleaning products, and fleecy cleaning cloth introduced in the classroom can limit exposure to TVOCs [80]. Physical defects in the school building, such as cracks and holes in the walls, broken windows, and peeling wallpaper or paint, were associated with higher indoor NO2 concentrations [81]. ...
The air quality in classrooms significantly impacts school children’s health and learning performance. It has been reported worldwide that classroom air quality does not meet the required standard and actions are pledged for improvement. However, it poses a challenge for decision-making in terms of prioritising taking-up measures. The aim of this study is to propose a method of identifying the action measures for improving classroom air quality and prioritising them. Case studies in the UK and China were conducted, and the key measures were identified through literature studies, open-ended questionnaire surveys, and workshop discussions, which are classified into three categories: B1, policy; B2, technology; and B3, information sharing. The analytical hierarchy process (AHP) is applied in the prioritisation of the action measures. A total of 138 teachers and parents from China and the UK participated in this case study. The genetic algorithm-optimised Hadamard product (GAOHP) method is applied to justify the consistency ratio (CR) within the required threshold value in order to ensure the consistency of the subjective perception and the accuracy of comparative weights. The results show that item B2, technology, is the most desired measure by both Chinese and British parents and teachers, despite the deviation from the optimal choice in China and the UK. Among the proposed action measures, the UK respondents strongly expected air purifiers with natural ventilation as opposed to their Chinese counterparts preferring to share the real-time status of classroom air quality. Our work will provide strong support for the subsequent selection of indoor air quality improvement strategies for schools.
... The interest in CO 2 as a proxy indicator of IAQ [96] stems from the fact that the measurement of this relatively inert gas is fairly cheap, and most of the existing mechanical air systems have inbuilt capabilities to measure this gas. Yet, the association of CO 2 with bioaerosols is an emerging research interest that needs to be emphasized. ...
Indoor Air Quality (IAQ) in schools has received attention over the past decades but still lacks specific standards and regulations. This study aimed to review the impact of bioaerosol activity in indoor environments on acute respiratory diseases and explore whether carbon dioxide can be used as an indicator of bioaerosol and respiratory diseases in indoor environments in K-12 school systems. Findings suggest a lack of a consensual approach to evaluate bioaerosols impacting IAQ in indoor infrastructures, particularly in school environments; an elevated CO2 concentration inside the school classrooms was not uncommon, and the evidence of unsatisfactory and degraded IAQ (surpassing ASHRAE standards) at public schools in rural and urban settings in one of the North Central County, Florida. It was found that CO2 levels can be associated with bioaerosol activity, and sufficient ventilation within the space substantially reduces the airborne time of respiratory droplets and CO2 levels. CO2 monitoring can act as an effective, low-cost alternative to surveying or detecting the prevalence of respiratory diseases, which may hold strength through establishing critical CO2 thresholds and, thereafter associating it with the infectious doses of pathogen activity.
... The generalization of findings to the entire Region is not possible due to the dearth of data for many low-income and lower-middle-income nations. High CO2 levels in a closed learning environment divert students' attention and make them queasy in classrooms (Chatzidiakou et al., 2015). A classroom study with a controlled environment found that students' learning status improved on different tests in a room with a good level of ventilation and decreased levels of CO2 (Haverinen-Shaughnessy & Shaughnessy, 2015). ...
The research aimed to determine the effects of Micro-Environmental Factors (MEFs) on students’ learning. Students’ learning was measured in controlled and uncontrolled MEFs within classroom. Researcher explored the effects of MEFs on students’ learning and find out the relationship between them. For this study, the experimental research design was used. In the first step, The Classroom Environmental Monitoring System (CEMS) was developed using (COTS) sensors to measure MEFs like temperature, CO2, humidity, and luminosity. In second step a test was conducted to evaluate students' learning. Data were collected by experiment in twelve (12) government and eighteen (18) private colleges of division Bahawalpur. Data analysis was performed in python using Logit, Probit Regression models, and Artificial Neural Network (ANN). The result of this study reveals that MEFs have impact on the students’ learning and both the variables are correlated. Henceforth, monitoring the MEFs during teaching learning process ultimately enhanced the learning of students.
... Another 2015 study investigated if CO2 is a good proxy for classroom IAQ in the United Kingdom. The study found a reduced classroom CO2 to be related to measured classroom pollutants such as particulate matter (PM) concentration to fall below WHO upper limit recommendation (Chatzidiakou et al. 2015). ...
Children are vulnerable to environmental stress and pollution due to their weak organ system, and they spend a substantial amount of their time in school. There is a continuous need to assess their school and classroom environmental condition to make sure that they always conform to standard.
This study aims to assess the impact of different indoor environmental quality parameters in United States of America schools on student absence rate. The synergistic association of classroom temperature, relative humidity, carbon dioxide, noise, pressure, and cleaning effectiveness on student absence rate is lacking in literature.
Data analytic software with artificial intelligence capacity was used to analyse measurement data (temperature, relative humidity, carbon dioxide, noise, pressure, and adenosine triphosphate on high contact surfaces as a surrogate for cleaning effectiveness) from 140 classrooms in 46 United State of America schools along with student absence rate that was retrieved from the school register. Descriptive statistics, correlation and both simple linear and multiple linear regression analysis were done to make inform inference on the measured data.
Classroom indoor temperature significantly correlated with classroom relative humidity (r = -0.4, p < 0.001). There was no statistically significant synergistic effect of all the measured or a combination of the measured indoor environmental quality parameters on absence rate per student. Indoor classroom temperature unilaterally predicted absence rate per student (p = 0.04). 4
It is necessary to respond to poor indoor environmental quality in schools promptly, as it can negatively affect student comfort, performance, and attendance in school. It could also create a negative image for the school, affect community trust, and strain the relationships between the school administration and parents. Approved indoor environmental quality standard should always be adhered to in school settings.
... The relationship between IAQ conditions in enclosed spaces and the susceptibility of building occupants to sickness and disease transmission is supported by a long history of evidence [9][10][11][12][13]. For decades, indoor C02 concentration has been accepted as a proxy for indoor fresh air rate and found to negatively impact cognition at high indoor concentrations [14,15]. Recent studies have begun to identify correlations between poor IAQ and COVID-19 vulnerability and mortality as well [16][17][18][19]. ...
Transmission of airborne disease is a concern in many indoor spaces. Recent studies have identified correlations between poor indoor air quality (IAQ) and COVID-19 vulnerability and mortality. Studying the role building design and ventilation play in both the spread and mitigation of airborne viruses in high-density spaces is thus imperative. However, guidance for IAQ improvement and COVID-19 risk mitigation is general and insufficient for specific application in at-risk spaces like British Columbia’s (BC) patient settings and long-term care homes. What remains underdefined is a workflow for translating site specific data on indoor aerosol spread into actionable tools health officials can use towards building retrofit and intervention planning. The objective of this project was thus to develop a library of ‘digital twin’ models of at-risk indoor spaces that can provide accurate and rapid investigations of indoor air quality improvement measures using computation fluid dynamics (CFD) software. To calibrate these models, 41 repeated controlled experiments of aerosol dispersion and removal were conducted to assess the ventilation patterns of a 4-bed hospital room. From these experiments, a 3D CFD model of the room was created using the RhinoCFD modelling package, calibrated with measured IAQ sensor data, and validated against the results of the live study. This paper presents the methodology and in-progress results of this CFD modelling process.
... Opening a window can be an efficient way to remove hot indoor temperatures. On the other hand, good ventilation improves the thermal environment and helps remove indoor pollutants from a building (Chatzidiakou et al. 2015;Lipczynska et al. 2015). Performing this method will help improve thermal comfort and health. ...
Thermal comfort is linked to our health, well-being, and productivity. The thermal environment is one of the main factors that influence thermal comfort and, consequently, the productivity of occupants inside buildings. Meanwhile, behavioural adaptation is well known to be the most critical contributor to the adaptive thermal comfort model. This systematic review aims to provide evidence regarding indoor thermal comfort temperature and related behavioural adaptation. Studies published between 2010 and 2022 examining indoor thermal comfort temperature and behavioural adaptations were considered. In this review, the indoor thermal comfort temperature ranges from 15.0 to 33.8 °C. The thermal comfort temperature range varied depending on several factors, such as climatic features, ventilation mode, type of buildings, and age of the study population. Elderly and younger children have distinctive thermal acceptability. Clothing adjustment, fan usage, AC usage, and open window were the most common adaptive behaviour performed. Evidence shows that behavioural adaptations were also influenced by climatic features, ventilation mode, type of buildings, and age of the study population. Building designs should incorporate all factors that affect the thermal comfort of the occupants. Awareness of practical behavioural adaptations is crucial to ensure occupants' optimal thermal comfort.
... The usefulness of CO 2 concentration metric stems from the principles that room occupants generate CO 2 dependent on body mass and levels of physical activity [39] and when indoor CO 2 concentration is elevated above the outdoor level, it can be used to evaluate indoor ventilation using established tracer gas measurement techniques [40,41]. Studies on CO 2 concentrations and ventilation rates in schools have reported the mean threshold range of 1000-1500 ppm [42] effecting recommendations of ventilation rates above 7.5 to 9.5 Ls -1 per student [25,[43][44][45][46]. ...
... Most studies on interactions have been undertaken in schools or offices, and between IAQ and thermal quality. [104][105][106] For example, Chatzidiakou et al. 107 developed a model to demonstrate the relationship between indoor air temperature and CO 2 concentration. They found that a high CO 2 concentration (e.g. ...
Because of COVID-19, the indoor environmental quality (IEQ) in sports facilities has been a concern to environmental health practitioners. To develop an overall understanding of the available guidelines and standards and studies performed on IEQ in sports facilities, an extensive literature study was conducted, with the aim of identifying: (1) indicators that are being used to assess IEQ in different sports facilities; (2) indicators that are potentially interesting to be used to assess indoor air, in particular; (3) gaps in knowledge to determine whether sports facilities are safe, healthy and comfortable for people to stay and perform their activities. The outcome indicates that most current standards and previous investigations on IEQ in sports facilities mainly focused on dose-related indicators (such as ventilation rate), while building-related indicators (such as ventilation regime) and occupant-related indicators (such as IEQ preferences) were rarely considered. Little attention is given to the fact that ventilation systems may play an important role in the air quality of the location, and few investigations have been performed on the transmission of SARS-CoV-2. This study recommends more research into both occupant and building-related indicators as well as cross-modal effects between various IEQ factors for developing future standards on sports facilities.
... Recognizing that several factors related to IEQ can influence health and well-being of older adults, as a proof of concept, we decided to test our data collection platform by focusing on indoor thermal environment (i.e., temperature and humidity) and air quality because of their well-established influence on short-and long-term outcomes related to health and wellbeing, and availability of low-cost and easy-to-use smart sensors to measure them. Further, recognizing that there exist many indoor air pollutants with substantial impact on occupants' health and wellbeing, as a proof of concept, we selected CO 2 concentration because it is a measure of overall indoor air quality and adequacy of natural and/or mechanical ventilation (Batterman & Peng, 1995;Chatzidiakou et al., 2015;Scheff et al., 2000). Table 1 details the specific physiological variables and outcomes related to health and wellbeing that we aimed to collect. ...
Technology provides new opportunities to understand and optimize the relationship between the home indoor environmental quality and health outcomes in older adults. We aimed to establish proof-of-concept and feasibility of remote, real-time, high-frequency, and simultaneous monitoring of select environmental variables and outcomes related to health and wellbeing in older adults. Thirty-four participants (27 were female) with an average age (SD) of 81 years (±7.1) were recruited from community and supportive housing environments. Environmental sensors were installed in each home and participants were asked to use a wearable device on their finger and answer smartphone-based questionnaires on a daily basis. Further, a subgroup of participants were asked to complete tablet-based cognitive tests on a daily basis. Average compliance with the wearable (time worn properly/total time with device) was 81%. Participants responded to 69% of daily smartphone surveys and completed 80% of the prescribed cognitive tests. These results suggest that it is feasible to study the impact of the home thermal environment and air quality on biological rhythms, cognition, and other outcomes in older adults. However, the success of non-passive data collection elements may be contingent upon baseline cognition.
... For example, multilevel modelling was used to discuss the impact of behavioural and environmental factors on pollution levels. The study stated that the elimination of emission sources, increasing ventilation rates and adjusting the temperature depending on seasonal variations can help in controlling the Total Volatile Organic Compounds (TVOCs) level [21]. Also, the multi-criteria approach was used to investigate the influence of passive spaces on the environmental performance of buildings and optimization scenarios during the renovation process [22]. ...
... The average values of N 2 O concentration measured in laboratory are consistent with the typical atmospheric concentration of ~330 ppb [6] but slightly lower. The average values of CO 2 concentration are almost double compared to the typical outdoor CO 2 concentration ~400 ppm [45], but the measured values are consistent with the typical indoor CO 2 concentration [46]. In fact, in closed environments, the CO 2 levels strongly depend on the carbon dioxide emitted in human breath (~4-5 % of total exhalation) [47]. ...
We report on a gas sensor based on quartz-enhanced photoacoustic spectroscopy (QEPAS) able to detect multiple gas species for environmental monitoring applications, by exploiting a Vernier effect-based quantum cascade laser as the excitation source. The device emission spectrum consists of ten separated emission clusters covering the range from 2100 up to 2250 cm⁻¹. Four clusters were selected to detect the absorption features of carbon monoxide (CO), nitrous oxide (N2O), carbon dioxide (CO2), and water vapor (H2O), respectively. The sensor was calibrated with certified concentrations of CO, N2O and CO2 in a wet nitrogen matrix. The H2O absorption feature was used to monitor the water vapor within the gas line during the calibration. Minimum detection limits of 6 ppb, 7 ppb, and 70 ppm were achieved for CO, N2O and CO2, respectively, at 100 ms of integration time. As proof of concept, the QEPAS sensor was tested by continuously sampling indoor laboratory air and monitoring the analytes concentrations.
... It is debated whether these associations exist because the higher indoor CO2 concentrations are correlated with higher levels of other indoor-generated pollutants which are the causative agents of the adverse effects (Mudarri 1997;Persily 1997). Yet, as suggested by Chatzidiakou et al. (2015), CO2 concentration can be used as a good proxy for overall IAQ, with the exception of traffic-related pollutants. Moreover, other studies have underlined the direct negative impacts of CO2 on occupants, in the range of concentrations typically found in buildings. ...
... To date, several studies investigated the association between CO 2 and other indoor pollutants to test if CO 2 is an overall indicator for IAQ (Branco et al., 2019;Ramalho et al., 2015;Chatzidiakou et al., 2015;Zhao et al., 2008;Szczurek et al., 2015;Batterman and Peng, 1995;Liang et al., 2020). All these studies unanimously have come to the conclusion that CO 2 is a good indicator of bio-effluents from human occupants, but it is a poor predictor of other indoor air pollutants, such as particulate matter (PM) and volatile organic compounds (VOCs) emitted from non-human sources. ...
Daycare centers (DCCs) are where infants and toddlers (0–4 years old) spend the most time besides their homes. Given their higher susceptibility to the effects of air pollutants, as compared to older children and adults, indoor air quality (IAQ) is regarded as an essential parameter to monitor in DCCs. Recent advances in IAQ monitoring technologies have enabled the deployment of low-cost air quality monitors (LCMs) and single sensors (LCSs) to continuously monitor various indoor environments, and their performance testing should also be performed in the intended indoor applications. To our knowledge, there is no study evaluating the application of LCMs/LCSs in DCCs scenarios yet.
Therefore, this study is aimed to assess the response of five types of LCMs (previously not tested) and five LCSs to typical DCCs emission activities in detecting multiple IAQ parameters, i.e., particulate matter, carbon dioxide, total volatile organic compounds, temperature, and relative humidity. These LCMs/LCSs were compared to outcomes from research-grade instruments (RGIs). All the experiments were performed in a climate chamber, where three kinds of typical activities (background; arts-and-crafts; cleaning; [in a total of 32 events]) were simulated by recruited subjects at two typical indoor climatic conditions (cool and dry [20 ± 1 °C & 40 ± 10%], warm and humid [26 ± 1 °C & 70 ± 5%]).
Results showed that tested LCMs had the ability to capture DCCs activities by simultaneously monitoring multiple IAQ parameters, and LCMs/LCSs revealed a strong correlation with RGIs in most events (R² values from 0.7 to 1), but, for some events, the magnitude of responses varied widely. Sensirion SCD41, an emerging CO2 sensor built on the photoacoustic sensing principle, had a more accurate performance than all tested NDIR-based CO2 sensors/monitors. In general, the study implies that the selection of LCMs/LCSs for a specific application of interest should be based on emission characteristics and space conditions.
... A wide range of techniques exists to evaluate ventilation and indoor air quality. For single zones buildings, like shelters, the CO2 indoor concentration technique is widely adopted (Chatzidiakou et al., 2015;Batterman, 2017;ASHRAE, 2019). The use of CO2 as a tracer contaminant has been suggested from existing literature (Persily et al., 1997;Parent, et al., 1998;Gids de et al., 2010;Batterman, 2017). ...
In built environments, thermal comfort has a significant influence on human health, safety, and productivity. Its importance is more valued in thermally stressed environments that are characterized by extreme climatic conditions, where considerable amounts of energy are consumed to achieve indoor thermal comfort. The worldwide increased demand for energy and the environmental consequences of such a trend highlights the importance of this topic.
Energy and Environment are global and interrelated issues that are unconstrained by political borders. Hence, countries of the whole world must cooperate in order to find solutions to ensure the sustainability of natural resources for future generations. This reveals the importance of scientific gatherings like the 2nd International Conference of Comfort At The Extremes, [CATE’21], which was organised by the College of Engineering, Sultan Qaboos University, on 24th-26th October 2021. The conference provided a forum for scientists and researchers from different countries of the world and strengthens collaboration between them in the field of thermal comfort in thermally stressed environments. Researchers from more than 19 countries contributed to CATE’21 reflecting global interest in the subject.
These countries are from the MENA region (The Middle East and North Africa), the UK, Europe, Russia, Asia, the USA, and South America.
The conference attracted a good number of articles. From 83 submitted abstracts, 59 had been accepted with a retention of 71%. The accepted abstracts formed 44 papers, 15 abstracts, and 8 keynote speakers. Moreover, 8 of the papers had been further modified to be published in a special issue in The Journal of Engineering Research (TJER), published by the College of Engineering at Sultan Qaboos University (https://journals.squ.edu.om/index.php/tjer/issue/view/294/78).
... A wide range of techniques exists to evaluate ventilation and indoor air quality. For single zones buildings, like shelters, the CO2 indoor concentration technique is widely adopted (Chatzidiakou et al., 2015;Batterman, 2017;ASHRAE, 2019). The use of CO2 as a tracer contaminant has been suggested from existing literature (Persily et al., 1997;Parent, et al., 1998;Gids de et al., 2010;Batterman, 2017). ...
... CO 2 is often monitored as a proxy for occupancy in rooms [13,14]. People produce CO 2 proportionally to their body mass and metabolic rate. ...
CO2 is customarily used to control ventilation as it is a proxy for bio-effluents and pollutants related to the presence and activity of people in the room. However, CO2 could not be a satisfactory indicator for pollutants that do not have a metabolic origin, i.e., emissions from building materials or emissions from traffic. A methodology to select pollutants besides or instead of CO2 is presented in this article. This methodology sets to study (i) the suitable location to measure air pollutants and (ii) which parameters to measure. The answers to these two questions are based on correlation analysis between pollutants and indoor/outdoor ratios.
Measurements of CO2, air temperature, relative humidity, formaldehyde, and particulate matter have been taken in an office, an industrial kitchen, and a gym and are used to show how to apply the methodology. Correlations were studied in detrended (pre-whitened) time series. Studying correlations in detrended time series via cross-correlation functions is recommended because correlation coefficients may be overestimated because of the trends in the time series. In contrast to Pearson's correlation coefficient, the cross-correlation function studies the correlation between pollutants concurrently (as Pearson) but also at different time lags.
From the measurements we can conclude on the need to measure at least one parameter representing: 1) pollutants related to human activities 2) pollutants that infiltrate from processes like combustion or traffic outdoors, 3) pollutants related to combustion indoors, 4) pollutants related to degassing from building materials, 5) pollutants related to other “non-combustion-related activities” indoors and moisture loads.
https://authors.elsevier.com/a/1eEtu1HudN4EEL
This study investigates the air quality and ventilation effectiveness in a repurposed museum space with a hybrid ventilation system in Ljubljana, Slovenia. Focusing on CO 2 and particulate matter concentrations, the aim is to determine the correlation between these parameters and the suitability of the ventilation system following a change in space use. Measurements were conducted over a four-month period, analyzing data during different occupancy and ventilation scenarios. The study compares observed values with World Health Organization (WHO) guidelines, specifically targeting PM 2.5 , PM 10 , and CO 2 concentrations. Findings reveal inadequate ventilation in the repurposed museum space, even with hybrid ventilation. CO 2 concentrations correlated with PM 2.5 and PM 10 levels, suggesting CO 2 monitoring as an indirect indicator of overall air quality. Recommendations include improving ventilation efficiency and limiting occupancy to ensure adherence to air quality standards.
The predicted and measured carbon dioxide (CO2) emitted by human respiration into an occupied space has been used as an indicator for controlling buildings' ventilation rates. However, this application assumes a constant emission rate for the entire population. Conversely, new knowledge has shown that this variable depends on the number of people in the room and their sex, diet, height, and above all, body mass and metabolic rate. This paper applies the latter model and a previously used sampling approach to identify the variability of CO2 emission rates and excess CO2 concentrations in school classrooms in Chile, and compares them with those in the USA. This time, we collected data from local sources and public databases to model an evidence-based average classroom of 29 students-15 men and 14 women-following the Chilean regulations and the ASHRAE 62.1 and ASHRAE 241 standards for ventilation. Then, using Python and a Monte Carlo sampling approach, we calculated the emission rates for the local population in the classrooms of children between 5 and 18 years old. Results show that the mean body weights of the USA and Chilean child populations are statistically different, but the excess CO2 concentrations can vary by only 4% between demographics. The difference in excess CO2 concentrations between countries reflects their differences in occupancy densities. Finally, there is a significant difference in excess CO2 concentrations for the two standards but little difference between countries for the same standard.
Plug-in fragrance diffusers are one of myriad volatile organic compound-containing consumer products that are commonly found in homes. The perturbing effects of using a commercial diffuser indoors were evaluated using a study group of 60 homes in Ashford, UK. Air samples were taken over 3 day periods with the diffuser switched on and in a parallel set of control homes where it was off. At least four measurements were taken in each home using vacuum-release into 6 L silica-coated canisters and with >40 VOCs quantified using gas chromatography with FID and MS (GC-FID-QMS). Occupants self-reported their use of other VOC-containing products. The variability between homes was very high with the 72 hour sum of all measured VOCs ranging between 30 and >5000 μg m-3, dominated by n/i-butane, propane, and ethanol. For those homes in the lowest quartile of air exchange rate (identified using CO2 and TVOC sensors as proxies) the use of a diffuser led to a statistically significant increase (p-value < 0.02) in the summed concentration of detectable fragrance VOCs and some individual species, e.g. alpha pinene rising from a median of 9 μg m-3 to 15 μg m-3 (p-value < 0.02). The observed increments were broadly in line with model-calculated estimates based on fragrance weight loss, room sizes and air exchange rates.
Occupants’ use of windows can influence the building energy demand, thermal conditions and indoor air quality. Researchers have made substantial efforts to develop probabilistic models to predict the window open/closed state. However, the hierarchical data structure and the heterogeneity in occupant behaviour have been generally neglected in previous modelling efforts. Multilevel modelling can provide an appropriate framework to handle this type of data structure and variability, but this method has rarely been used in the field. This study investigated room- and apartment-level variations in the effects of outdoor environmental variables on the window open state in low-energy apartment buildings in the UK using a multilevel modelling approach. The results showed that the room-level, rather than apartment-level, variation was statistically significant. Meanwhile, the room type (i.e., living room or bedroom) did not significantly affect the relationship between outdoor environmental variables and the window open state. The strength of this study is that the modelling accounted for the hierarchical structure of the data by simultaneously considering room-and apartment- level behavioural variations. By quantifying the significant diversity of occupant behaviour in the natural ventilation of residences, future research can more accurately estimate the variation in building energy and indoor air quality impacts.
Utilizar espaços internos é inerente aos seres humanos, que passam, em média, a maior parte do tempo nesses locais. As salas de aula são alvo de crescente preocupação científica sobretudo quando submetidas a baixas taxas de renovação de ar. O dióxido de carbono é, tradicionalmente, considerado um indicador da qualidade do ar interior (QAI). No ambiente escolar, altas concentrações desse gás estão relacionadas à diminuição da cognição e do desempenho dos estudantes. O objetivo deste estudo foi fazer uma revisão da literatura de artigos que tratam da QAI e dos níveis de CO2 em salas de aula com ventilação natural. A metodologia adotada foi a Revisão Sistemática da Literatura (RSL). Realizou-se uma seleção de artigos junto ao Portal de Periódicos da Capes e ScienceDirect, que resultou na inclusão e análise de 34 artigos. Como resultados, observou-se que, frequentemente, as salas de aula operam com concentrações médias de CO2 superiores a 1000 ppm, bem como, uma significativa relação pico-média, o que indica a baixa eficiência da renovação de ar. Os trabalhos indicaram que a ação dos usuários, por meio do julgamento subjetivo e do comportamento adaptativo, influenciou o aumento dos níveis desse gás, assim como a abertura de janelas e portas nos intervalos de aula não foi suficiente para manter a qualidade recomendada. Essa temática ganhou relevância devido à pandemia do COVID-19 em 2020, em que ficou evidente a necessidade de estratégias adequadas para a dispersão dos contaminantes.
Healthy building design is an emerging field of architecture and building engineering. Indoor air quality (IAQ) is an inevitable factor that should be considered in healthy building design due to its demonstrated links with human health and well-being. This paper proposes to integrate IAQ prediction into healthy building design by developing a simulation toolbox, termed i-IAQ, using MATLAB App Designer. Within the i-IAQ, users can input information of building layout and wall-openings and select air pollutant sources from the database. As an output, the toolbox simulates indoor levels of carbon dioxide (CO2), total volatile organic compounds (TVOC), inhalable particles (PM10), fine particles (PM2.5), nitrogen dioxide (NO2), and ozone (O3) during the occupied periods. Based on the simulation results, the toolbox also offers diagnosis and recommendations to improve the design. The accuracy of the toolbox was validated by a case study in an apartment where physical measurements of air pollutants took place. The results suggest that designers can integrate the i-IAQ toolbox in building design, so that the potential IAQ issues can be resolved at the early design stage at a low cost. The paper outcomes have the potential to pave a way towards more holistic healthy building design, and novel and cost-effective IAQ management.
Healthy indoor environments influence the comfort, health and wellbeing of the occupants. Monitoring the indoor temperature, relative humidity and CO2 levels in primary schools during the COVID-19 pandemic was mandated by a local authority in Scotland. The aim was to investigate the comfort and safety of the teachers and their pupils. This paper presents the measurements of indoor climate in 20 classrooms in four different primary schools in Scotland. The schools were of different architypes. The classrooms were of different sizes, orientations and occupancy, and had different ventilation systems. Ventilation was achieved either by manually opening the windows, or by a mechanical ventilation system. Indoor air temperature, relative humidity and carbon dioxide (CO2) concentrations were continuously monitored for one week during the heating season 2020/21. Occupancy and opening of the windows were logged in by the teachers. The ventilation rates in the classrooms were estimated by measuring the CO2 concentrations. On the 20 classrooms of the study, data of 19 were analysed. The results show that four of the five mechanically ventilated classrooms performed better than natural ventilation, which indicates that opening the windows depended on the customs and habits. Classrooms in naturally ventilated Victorian buildings have the worst average ventilation rate (4.38 L/s per person) compared to the other classrooms (5.8 L/s per person for the more recent naturally ventilated ones, and 6.08 L/s per person for the mechanically ventilated ones). The results of this preliminary study will be used as the basis to find ways to ensure adequate ventilation in natural ventilated classrooms.
Emerging data indicates that incumbent mechanical/physio-chemical air handling systems inadequately address common indoor air quality (IAQ) problems, including elevated CO2 levels and volatile organic compounds (VOCs), with compounding negative impacts to human health. Preliminary research suggests that active plant-based systems may synthetically address these challenges. However, in order to design system performance parameters, the significance of species selection and biogeochemical mechanisms of growth media design need further characterization towards an effective bioremediative interface with air handling systems. Here, through three different species across three different growth media designs, we investigate trade-offs between CO2 sequestration through photosynthesis and CO2 production by metabolically active root-zones (that may remediate VOCs). Across the species, hydroponic media produced 61% greater photosynthetic leaf area compared to organic media which produced 66% more root biomass. CO2 concentration changes driven by differing plant and growth media (organic vs. hydroponic) treatments were measured within a semi-sealed chamber. Repeated estimations of net CO2 concentrations throughout plant development revealed decreasing influxes of CO2 within the chamber over time, indicating evolving photosynthesis/respiration balances. Multivariate analysis indicates growth media design, through impacts to water availability, air flow rates and plant development, was a more significant driver of bioremediation performance metrics than species selection.
Since the COVID-19 pandemic, the ventilation of school buildings has attracted considerable attention from the general public and researchers. However, guidance to assess the ventilation performance in classrooms, especially during a pandemic, is still lacking. Therefore, aiming to fill this gap, this study conducted a full-scale laboratory study to monitor the CO 2 concentrations at 18 locations in a classroom setting under four different ventilation regimes. Additionally, a field study was carried out in two Dutch secondary schools to monitor the CO 2 concentrations in the real classrooms with different ventilation regimes. Both the laboratory and field study findings showed that CO 2 concentrations varied a lot between different locations in the same room, especially under natural ventilation conditions. The outcome demonstrates the need of monitoring the CO 2 concentration at more than one location in a classroom. Moreover, the monitored CO 2 concentration patterns for different ventilation regimes were used to determine the most representative location for CO 2 monitoring in classrooms. For naturally ventilated classrooms, the location on the wall opposite to windows and the location on the front wall (nearby the teacher) were recommended. For mechanically ventilated classrooms, one measurement location seemed enough because CO 2 was well-mixed under this ventilation regime.
Occupant behaviour (OB) is one of the main causes of the energy performance gap between buildings’ performance prediction versus reality, since, due to its uncertainty and unpredictability, it is often oversimplified in the building performance simulation (BPS). Hence, previous studies developed OB models, mainly in the residential and office contexts, in order to predict and represent human behaviour in BPS. Yet, school buildings are different from other typologies due to contextual factors (e.g., occupants’ age, different daily timetables and group rules) and are in a unique position to promote energy efficiency for tomorrow’s citizens. Assessing OB in schools can lead to an improvement of the indoor environment, especially in naturally ventilated buildings, where window operation behaviour directly impacts on the air change rates and, consequently, on the indoor air quality. This study addresses the knowledge gap on OB modelling for naturally ventilated (NV) and mixed-mode (MM) school buildings. The reviewed papers were organized in three main themes, namely (i) OB models for BPS of NV and MM buildings, (ii) OB research studies in NV and MM school buildings and (iii) potential changes on OB in school buildings due to the COVID-19 pandemic. The analysis focused on three phases of the OB modelling framework: data collection (pre-processing), model development (processing) and model implementation (post-processing). Important research gaps are identified, such as the reduced number of studies that cover the three phases of the modelling framework within the school buildings context and the need to better investigate the teachers’ behaviour and collective actions as important OB drivers in classrooms. Future research topics are also identified, such as which are the potential changes on actions’ drivers due to the COVID-19 pandemic in NV classrooms and to what extent they will be durable or ephemeral.
In the following, measurements of CO 2 levels in seven classrooms in four schools are reported. Measurements were taken for approximately one week in each classroom during the heating season and the time-varying ventilation rates estimated. The results of the experiments show CO 2 concentrations which are far beyond the guideline value of 1000 ppm (the average concentration during the occupied period was 1957 ppm). In some classrooms the level exceeded the range of the detector (4000ppm). Calculated air supply rates vary from unacceptably low levels to rates which are in line with guidance (the average occupied rate was 0.84 ac/h or 1.38 l/s.p). The occurrence of periods with acceptable supply rates, and the rates found during purge ventilation, show that the surveyed classrooms have the potential to provide adequate fresh air. Anecdotal evidence from the classroom teachers suggest that the reason enough fresh air is not being provided is the reluctance of staff to open windows: firstly because of the draughts this might cause, and secondly, because they are unaware of a problem.
The aim of this study was to explore if there is any evidence for demonstrable impacts of school building design on the learning rates of pupils in primary schools.Hypotheses as to positive impacts on learning were developed for 10 design parameters within a neuroscience framework of three design principles. These were tested using data collected on 751 pupils from 34 varied classrooms in seven different schools in the UK. The multi-level model developed explained 51% of the variability in the learning improvements of the pupils, over the course of a year. However, within this a high level of explanation (73%) was identified at the “class” level, linked entirely to six built environment design parameters, namely: colour, choice, connection, complexity, flexibility and light.The model was used to predict the impact of the six design parameters on pupil’s learning progression. Comparing the “worst” and “best” classrooms in the sample, these factors alone were found to have an impact that equates to the typical progress of a pupil over one year. It was also possible to estimate the proportionate impact of these built environment factors on learning progression, in the context of all influences together. This scaled at a 25% contribution on average.This clear evidence of the significant impact of the built environment on pupils’ learning progression highlights the importance of this aspect for policy makers, designers and users. The wide range of factors involved in this holistic approach still leaves a significant design challenge.
This study analyzed the reporting of multilevel modeling applications of a sample of 99 articles from 13 peer-reviewed journals in education and the social sciences. A checklist, derived from the methodological literature on multilevel modeling and focusing on the issues of model development and specification, data considerations, estimation, and inference, was used to analyze the articles. The most common applications were two-level models where individuals were nested within contexts. Most studies were non-experimental and used nonprobability samples. The amount of data at each level varied widely across studies, as did the number of models examined. Analyses of reporting practices indicated some clear problems, with many articles not reporting enough information for a reader to critique the reported analyses. For example, in many articles, one could not determine how many models were estimated, what covariance structure was assumed, what type of centering if any was used, whether the data were consistent with assumptions, whether outliers were present, or how the models were estimated. Guidelines for researchers reporting multilevel analyses are provided.
This study presents the performance evaluation of a tailor-made passive sampler developed for the monitoring of tropospheric ozone.
The performance of the passive sampler was tested in the field conditions in terms of accuracy, precision, blank values, detection limit, effects of some parameters such as sampling site characteristics and sampling period on the field blanks, self-consistency, experimental and theoretical uptake rates, shelf life and comparison with commercial passive samplers.
There was an agreement (R (2) = 0.84) between the responses of passive sampler and the continuous automatic analyser. The accuracy of the sampler, expressed as percent relative error, was obtained lower than 15%. Method precision in terms of coefficient of variance for three simultaneously applied passive samplers was 12%. Sampler detection limit was 2.42 μg m(-3) for an exposure period of 1 week, and the sampler can be stored safely for a period of up to 8 weeks before exposure. Satisfactory self-consistency results showed that extended periods gave the same integrated response as a series of short-term samplers run side by side. The uptake rate of ozone was found to be 10.21 mL min(-1) in a very good agreement with the theoretical uptake rate (10.32 mL min(-1)). The results of the comparison study conducted against a commercially available diffusion tube (Gradko diffusion tube) showed a good linear relationship (R (2) = 0.93) between two passive samplers.
The sampler seems suitable to be used in large-scale measurements of ozone where no data are available or the number of existing automated monitors is not sufficient.
We measured volatile organic compound (VOC) exposures in multiple locations for a diverse population of children who attended two inner-city schools in Minneapolis, Minnesota. Fifteen common VOCs were measured at four locations: outdoors (O), indoors at school (S), indoors at home (H), and in personal samples (P). Concentrations of most VOCs followed the general pattern O approximately equal to S < P less than or equal to H across the measured microenvironments. The S and O environments had the smallest and H the largest influence on personal exposure to most compounds. A time-weighted model of P exposure using all measured microenvironments and time-activity data provided little additional explanatory power beyond that provided by using the H measurement alone. Although H and P concentrations of most VOCs measured in this study were similar to or lower than levels measured in recent personal monitoring studies of adults and children in the United States, p-dichlorobenzene was the notable exception to this pattern, with upper-bound exposures more than 100 times greater than those found in other studies of children. Median and upper-bound H and P exposures were well above health benchmarks for several compounds, so outdoor measurements likely underestimate long-term health risks from children's exposure to these compounds.
In contrast to the growth of fungi, the growth of mycobacteria in moisture-damaged building materials has rarely been studied.
Environmental mycobacteria were isolated from 23% of samples of moisture-damaged materials (n = 88). The occurrence of mycobacteria increased with increasing concentrations of fungi. Mycobacteria may contribute to indoor
exposure and associated adverse health effects.
Measurements of metabolic carbon dioxide concentration made in four classrooms in two schools are reported for both occupied and unoccupied periods. Measurements were taken for approximately one week in each classroom during the unheated season and the time-varying ventilation rates estimated. The results of the experiments show CO2 concentrations that are far beyond the guideline value of 1000 ppm (the maximum concentration during the occupied period was 3756 ppm). Calculated air supply rates vary from unacceptably low levels, to rates that are in line with guidance. The occurrence of periods with acceptable supply rates, and the rates found during purge ventilation, show that the surveyed classrooms have the potential to provide adequate fresh air. Inaccessible windows and ventilation openings, combined with lack of guidance on when and how to apply ventilation seems to be the primary reason for poor ventilation outside the heating season.
SAS PROC MIXED is a flexible program suitable for fitting multilevel models, hierarchical linear models, and individual growth models. Its position as an integrated program within the SAS statistical package makes it an ideal choice for empirical researchers and applied statisticians seeking to do data reduction, management, and analysis within a single statistical package. Because the program was developed from the perspective of a "mixed" statistical model with both random and fixed effects, its syntax and programming logic may appear unfamiliar to users in education and the social and behavioral sciences who tend to express these models as multilevel or hierarchical models. The purpose of this paper is to help users familiar with fitting multilevel models using other statistical packages (e.g., HLM, MLwiN, MIXREG) add SAS PROC MIXED to their array of analytic options. The paper is written as a step-by-step tutorial that shows how to fit the two most common multilevel models: (a) school effects models, designed for data on individuals nested within naturally occurring hierarchies (e.g., students within classes); and (b) individual growth models, designed for exploring longitudinal data (on individuals) over time. The conclusion discusses how these ideas can be extended straighforwardly to the case of three level models. An appendix presents general strategies for working with multilevel data in SAS and for creating data sets at several levels.
This study aims to assess the adequacy of current guidelines, framed around thermal comfort, estimated ventilation rates, and CO2 levels, for the provision of indoor air quality (IAQ) in school classrooms. It draws on detailed monitoring data from a sample of 18 classrooms from 6 London schools. Overheating during the non-heating season was identified in eight south-, south-east-, and east-facing classrooms in two Victorian and two contemporary schools. Four classrooms in these contemporary schools also failed to keep average indoor CO2 levels below 1500 ppm in the non-heating season. During the heating season, eight classrooms exceeded the daily average indoor CO2 levels. Mean indoor particulate matter (PM)10 and PM2.5 levels recorded in all classrooms in both seasons were higher than 20 and 10 μg/m3, respectively, indicating that school exposure during an academic year may exceed annual recommended WHO [2006. Air Quality Guidelines: Global Update 2005: Particulate Matter, Ozone, Nitrogen Dioxide, and Sulfur Dioxide. Copenhagen: WHO Regional Office for Europe; 2010. WHO Guidelines for Indoor Air Quality: Selected Pollutants. Copenhagen: WHO Regional Office for Europe.] guideline values in all classrooms. In both seasons, all classrooms were found to have indoor total volatile organic compounds levels (median: 269 ppb and interquartile range: 64–408 ppb) above guideline thresholds (130 ppb) associated with sensory irritations. Identification of specific volatile organic compounds indicated the presence of strong indoor sources including furniture, cleaning products, and teaching materials. Findings suggest that these school classrooms often have poor IAQ due to a combination of sub-optimal building operation and management practices. Furthermore, while CO2 and ventilation rates are a useful tool for IAQ assessment, findings indicate that consideration of specific pollutants is necessary to ensure a healthy indoor environment.
The overall aim of the study is to provide empirical evidence on indoor pollution levels to assist the formation of indoor air quality (IAQ) benchmarking of school buildings under operational conditions. This article is the second part of the study and aims to quantify seasonal variation of chemical and microbial levels in London schools. Passive diffusive sampling was employed for radon, NO2, and O3 measurements. Fungal and bacterial groups and allergens were sampled with suction-based methods in settled dust and endotoxin levels were sampled in dust collected with natural deposition. Biological contaminants were analysed with molecular, cultivation-independent methods. The strong temporal and spatial variability of outdoor NO2 levels affected indoor levels and is therefore an important consideration when selecting sites for new school buildings. There is a need to further clarify on the effect of finishing, such as wall-to-wall carpeting, which may act as a significant reservoir of irritants and allergens and impact school IAQ.
Researchers in comparative research increasingly use multilevel models to test effects of country-level factors on individual behavior and preferences. However, the asymptotic justification of widely employed estimation strategies presumes large samples and applications in comparative politics routinely involve only a small number of countries. Thus, researchers and reviewers often wonder if these models are applicable at all. In other words, how many countries do we need for multilevel modeling? I present results from a large-scale Monte Carlo experiment comparing the performance of multilevel models when few countries are available. I find that maximum likelihood estimates and confidence intervals can be severely biased, especially in models including cross-level interactions. In contrast, the Bayesian approach proves to be far more robust and yields considerably more conservative tests.
The increasing interest in indoor environmental quality of educational buildings has been underpinned by the rising incidence of asthma and respiratory disease among children, who spend a substantial amount of their lives on the school premises. The susceptibility of children to respiratory disease compared with adults has led to the formulation of regulatory frameworks for the school environment, which specifies maximum CO2 concentrations and minimum airflow rates. This article reviews the evidence that school buildings provide a healthy and satisfactory indoor environment for the occupants. It summarized air pollution levels reported from indoor air quality (IAQ) monitoring surveys and evidence linking school exposure with health responses from the occupants. In addition, environmental and behavioural factors affecting pollution levels in school buildings were examined. The analysis has highlighted the degraded IAQ in some schools that often exceed WHO guidelines, while health impacts of school exposure were reported for concentrations below current guidelines.
Modern building materials, once moistened, may provide ecological niches for various microbes that have not been well characterized. The aim of the current study was to determine whether fungal genera and actinobacteria were associated with seven types of moisture-damaged building materials by systematically describing the mycobiota and enumerating fungi and bacteria in these materials. Microbial analyses were obtained from 1140 visibly damaged samples of building material, viz. wood, paper, non-wooden building boards, ceramic products, mineral insulation materials, paints and glues, and plastics. Fungal and bacterial concentrations correlated well (r=0.6). The range of fungi and bacteria numbers was between 100 and in all materials, but significant differences in counts were observed between materials. Highest median concentrations of fungi were observed in wooden and paper materials, and lowest in samples of mineral insulation, ceramic products, and paints and glues. Concentrations of viable bacteria in mineral insulation materials were significantly lower than in wood, paper, ceramic products and plastics. A rich variety of fungi was found in wooden materials, with Penicillium and yeasts occurring most frequently. In paper materials, a clear difference from wood was the more frequent occurrence of Cladosporium and Stachybotrys. The most distinctive finding in gypsum boards was that Stachybotrys was common. Ceramic products and paints and glues seemed to favour Acremonium and Aspergillus versicolor. Yeasts and members of the Sphaeropsidales occurred often in parallel in most materials. This study confirms that microbial growth occurs in many different building materials and shows associations between fungal genera and the type of material.
SAS PROC MIXED is a flexible program suitable for fitting multilevel models, hierarchical linear models, and individual growth models. Its position as an integrated program within the SAS statistical package makes it an ideal choice for empirical researchers and applied statisticians seeking to do data reduction, management, and analysis within a single statistical package. Because the program was developed from the perspective of a "mixed" statistical model with both random and fixed effects, its syntax and programming logic may appear unfamiliar to users in education and the social and behavioral sciences who tend to express these models as multilevel or hierarchical models. The purpose of this paper is to help users familiar with fitting multilevel models using other statistical packages (e.g., HLM, MLwiN, MIXREG) add SAS PROC MIXED to their array of analytic options. The paper is written as a step-by-step tutorial that shows how to fit the two most common multilevel models: (a) school effects models, designed for data on individuals nested within naturally occurring hierarchies (e.g., students within classes); and (b) individual growth models, designed for exploring longitudinal data (on individuals) over time. The conclusion discusses how these ideas can be extended straighforwardly to the case of three level models. An appendix presents general strategies for working with multilevel data in SAS and for creating data sets at several levels.
This book covers a broad range of topics about multilevel modeling. The goal is to help readersto understand the basic concepts, theoretical frameworks, and application methods of multilevel modeling. Itis at a level also accessible to non-mathematicians, focusing on the methods and applications of various multilevel models and using the widely used statistical software SAS.Examples are drawn from analysis of real-world research data. © 2012 Higher Education Press and Walter de Gruyter GmbH & Co. KG, Berlin/Boston.
The measurement of indoor air pollutants and their health effects are less often studied due to the costs
of collection of such data. We have analysed the variability in the measurement of five indoor school air
pollutants: fine particulate matter of size <2.5 µm (PM2.5), nitrogen dioxide (NO2), and three Volatile
Organic Compounds (VOC), namely formaldehyde, acetaldehyde and acrolein, objectively measured over
five days of a week at representative points in more than 400 classrooms of 109 schools and courtyards in
six French cities spread out over the year. Separate 3-stage multilevel models were fitted to partition the
different nested variance components (i.e., classroom, school and city levels), and intra-class correlation
(ICC) coefficients were computed to bring out the similarities of pollutants’ concentrations among these
spatial units. The indoor PM2.5 and NO2 concentrations showed a high degree of similarity (ICC coefficients
equal to 76% and 81%, respectively) between the classrooms of a school (and city), whereas the
formaldehyde, acetaldehyde and acrolein concentrations showed low to moderate degree of similarity
(ICC coefficients equal to 25%, 36% and 57%, respectively) between the classrooms. We conclude that to
investigate the impact of indoor air pollutants, a multilevel approach taking into account the full design
of the study would be the most appropriate.
Previous studies have found that classrooms are often inadequately ventilated, with the resultant increased risk of negative impacts on the pupils. This paper describes a series of field measurements that investigated the indoor air quality, thermal comfort and acoustic performance of nine recently built secondary schools in England. The most significant conclusion is that the complex interaction between ventilation, thermal comfort and acoustics presents considerable challenges for designers. The study showed that while the acoustic standards are demanding it was possible to achieve natural ventilation designs that met the criteria for indoor ambient noise levels when external noise levels were not excessive. Most classrooms in the sample met the requirement of limiting the daily average CO2 concentration to below 1500 ppm but just a few met the need to readily provide 8 l/s per person of fresh air under the easy control of the occupants. It would seem that the basic requirement of 1500 ppm of CO2 is achieved as a consequence of the window areas being just sufficient to provide the minimum of 3 l/s per person at low and intermittent occupancy. Thermal comfort in the monitored classrooms was mostly acceptable but temperatures tended to be much higher in practice than the design assumed.
Under the French national research program PRIMEQUAL, measurements of outdoor and indoor pollution have been performed in eight school buildings in La Rochelle (France) and its suburbs. The school buildings were either naturally ventilated by opening the windows or mechanically ventilated with minimum fresh air, and demonstrated various permeabilities. Ozone, nitrogen oxides (NO and NO2), and particulate matter (PM) (15 size intervals ranging from 0.3 to 20 μm) concentrations were monitored continuously indoors and outdoors for two 2-week periods. The indoor relative humidity, temperature, CO2 concentration (room occupancy), window openings and permeability of the building were also measured. Principal component analysis (PCA), a multivariate observation-based statistical method, was used to determine the parameters influencing the relationship between the outdoor and indoor concentration levels. After a brief description of the experimental data and methodology, the paper presents a detailed analysis of the PCA diagrams. This analysis leads to distinguish between positively correlated, negatively correlated and non-correlated variables. The main conclusions arising from the study are: (1) the influence of the room occupancy on the particle concentrations indoors changes with different particle sizes, (2) the building air-tightness and the outdoor concentration level greatly influence the indoor/outdoor (I/O) concentration ratios of ozone, and (3) indoor ozone and particles concentrations are negatively correlated, which may be the result of complex homogeneous and/or heterogeneous processes.
Several studies have investigated the health of children attending schools located near busy roads. In this study, we have measured personal exposure to traffic-related pollutants in children to validate exposure classification based on school location. Personal exposure to PM2.5, soot, NOx and NO2 was measured during four 48-h periods. The study involved 54 children attending four different schools, two of which were located within 100 m of a major road (one ring road and one freeway) and the other two were located at a background location in the city of Utrecht, The Netherlands. Outdoor monitoring was conducted at all school sites, during the personal measurements. A questionnaire was administered on time activity patterns and indoor sources at home. The outdoor concentration of soot was 74% higher at the freeway school compared to its matched background school. Personal exposure to soot was 30% higher. For NOx the outdoor concentration was 52% higher at the freeway school compared to its background school. The personal concentration of NOx was 37% higher for children attending the freeway school. Differences were smaller and insignificant for PM2.5 and NO2. No elevated personal exposure to air pollutants was found for the children attending the school near the ring road. We conclude that the school's proximity to a freeway can be used as a valid estimate of exposure in epidemiological studies on the effects of the traffic-related air pollutants soot and NOx in children.
Numerous epidemiological studies have demonstrated the association between particle mass (PM) concentration in outside air and the occurrence of health related problems and/or diseases. However, much less is known about indoor PM concentrations and associated health risks. In particular, data are needed on air quality in schools, since children are assumed to be more vulnerable to health hazards and spend a large part of their time in classrooms.On this background, we evaluated indoor air quality in 64 schools in the city of Munich and a neighbouring district outside the city boundary. In winter 2004–2005 in 92 classrooms, and in summer 2005 in 75 classrooms, data on indoor air climate parameters (temperature, relative humidity), carbon dioxide (CO2) and various dust particle fractions (PM10, PM2.5) were collected; for the latter both gravimetrical and continuous measurements by laser aerosol spectrometer (LAS) were implemented. In the summer period, the particle number concentration (PNC), was determined using a scanning mobility particle sizer (SMPS). Additionally, data on room and building characteristics were collected by use of a standardized form. Only data collected during teaching hours were considered in analysis. For continuously measured parameters the daily median was used to describe the exposure level in a classroom.The median indoor CO2 concentration in a classroom was 1603 ppm in winter and 405 ppm in summer. With LAS in winter, median PM concentrations of 19.8 μg m−3 (PM2.5) and 91.5 μg m−3 (PM10) were observed, in summer PM concentrations were significantly reduced (median PM2.5=12.7 μg m−3, median PM10=64.9 μg m−3). PM2.5 concentrations determined by the gravimetric method were in general higher (median in winter: 36.7 μg m−3, median in summer: 20.2 μg m−3) but correlated strongly with the LAS-measured results. In explorative analysis, we identified a significant increase of LAS-measured PM2.5 by 1.7 μg m−3 per increase in humidity by 10%, by 0.5 μg m−3 per increase in CO2 indoor concentration by 100 ppm, and a decrease by 2.8 μg m−3 in 5–7th grade classes and by 7.3 μg m−3 in class 8–11 compared to 1–4th class. During the winter period, the associations were stronger regarding class level, reverse regarding humidity (a decrease by 6.4 μg m−3 per increase in 10% humidity) and absent regarding CO2 indoor concentration. The median PNC measured in 36 classrooms ranged between 2622 and 12,145 particles cm−3 (median: 5660 particles cm−3).The results clearly show that exposure to particulate matter in school is high. The increased PM concentrations in winter and their correlation with high CO2 concentrations indicate that inadequate ventilation plays a major role in the establishment of poor indoor air quality. Additionally, the increased PM concentration in low level classes and in rooms with high number of pupils suggest that the physical activity of pupils, which is assumed to be more pronounced in younger children, contributes to a constant process of resuspension of sedimented particles. Further investigations are necessary to increase knowledge on predictors of PM concentration, to assess the toxic potential of indoor particles and to develop and test strategies how to ensure improved indoor air quality in schools.
A study on indoor–outdoor RSPM (PM10, PM2.5 and PM1.0) mass concentration monitoring has been carried out at a classroom of a naturally ventilated school building located near an urban roadway in Delhi City. The monitoring has been planned for a year starting from August 2006 till August 2007, including weekdays (Monday, Wednesday and Friday) and weekends (Saturday and Sunday) from 8:0 a.m. to 2:0 p.m., in order to take into account hourly, daily, weekly, monthly and seasonal variations in pollutant concentrations. Meteorological parameters, including temperature, rH, pressure, wind speed and direction, and traffic parameters, including its type and volume has been monitored simultaneously to relate the concentrations of indoor–outdoor RSPM with them. Ventilation rate has also been estimated to find out its relation with indoor particulate concentrations. The results of the study indicates that RSPM concentrations in classroom exceeds the permissible limits during all monitoring hours of weekdays and weekends in all seasons that may cause potential health hazards to occupants, when exposed. I/O for all sizes of particulates are greater than 1, which implies that building envelop does not provide protection from outdoor pollutants. Further, a significant influence of meteorological parameters, ventilation rate and of traffic has been observed on I/O. Higher I/O for PM10 is indicating the presence of its indoor sources in classroom and their indoor concentrations are strongly influenced by activities of occupants during weekdays.
Abstract
Abstract Indoor air quality (IAQ) parameters in 64 elementary and middle school classrooms in Michigan were examined for the purposes of assessing ventilation rates, levels of volatile organic compounds (VOCs) and bioaerosols, air quality differences within and between schools, and emission sources. In each classroom, bioaerosols, VOCs, CO2, relative humidity, and temperature were monitored over one workweek, and a comprehensive walkthough survey was completed. Ventilation rates were derived from CO2 and occupancy data. Ventilation was poor in many of the tested classrooms, e.g., CO2 concentrations often exceeded 1000 ppm and sometimes 3000 ppm. Most VOCs had low concentrations (mean of individual species <4.5 μg/m3); bioaerosol concentrations were moderate (<6500 count per m3 indoors, <41,000 count per m3 outdoors). The variability of CO2, VOC, and bioaerosol concentrations within schools exceeded the variability between schools. These findings suggest that none of the sampled rooms were contaminated and that no building-wide contamination sources were present. However, localized IAQ problems might remain in spaces where contaminant sources are concentrated and that are poorly ventilated.
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There are few incidence studies on sick building syndrome (SBS). We studied two-year change of SBS in Chinese pupils in relation to parental asthma/allergy (heredity), own atopy, classroom temperature, relative humidity (RH), absolute humidity (AH), crowdedness, CO₂, NO₂, and SO₂. A total of 1993 participated at baseline, and 1143 stayed in the same classrooms after two years. The prevalence of mucosal and general symptoms was 33% and 28% at baseline and increased during follow-up (P < 0.001). Twenty-seven percent reported at least one symptom improved when away from school. Heredity and own atopy were predictors of SBS at baseline and incidence of SBS. At baseline, SO₂ was associated with general symptoms (OR=1.10 per 100 μg/m³), mucosal symptoms (OR=1.12 per 100 μg/m³), and skin symptoms (OR=1.16 per 100 μg/m³). NO₂ was associated with mucosal symptoms (OR=1.13 per 10 μg/m³), and symptoms improved when away from school (OR=1.13 per 10 μg/m³). Temperature, RH, AH, and CO₂ were negatively associated with prevalence of SBS. Incidence or remission of SBS was not related to any exposure, except a negative association between SO₂ and new skin symptoms. In conclusion, heredity and atopy are related to incidence and prevalence of SBS, but the role of the measured exposures for SBS is more unclear.
Practical implications:
We found high levels of CO₂ indicating inadequate ventilation and high levels of SO₂ and NO₂, both indoors and outdoors. All schools had natural ventilation, only. Relying on window opening as a tool for ventilation in China is difficult because increased ventilation will decrease the level of CO₂ but increase the level of NO₂ and SO₂ indoors. Prevalence studies of sick building syndrome (SBS) might not be conclusive for causal relationships, and more longitudinal studies on SBS are needed both in China and other parts of the world. The concept of mechanical ventilation and air filtration should be introduced in the schools, and when planning new schools, locations close to heavily trafficked roads should be avoided.
Microbiological analysis of atmospheres witnessed substantial technical improvements in the 1940s to 1960s. May's cascade impactor and Hirst's spore trap allowed the counting of total cells but had limited capacity for identification of the spores. Bourdillon's sampler enabled the counting of cultivable fungi and their identification. A great step forward was given with the Andersen's six-stage impactor, which allowed discrimination of particles by size, counting of cultivable cells, and species identification. This period also witnessed the development of impingers, namely, the AGI-30 described by Malligo and Idoine, and the three-stage model designed by K. R. May. The 1990s to 2000s witnessed innovative discoveries on the biology of indoor fungi. Work carried out in several laboratories showed that indoor fungi can release groups of spores, individual spores and fungal fragments, and produce volatile organic compounds and mycotoxins. Integrating all findings a holistic interpretation emerged for the sick building syndrome. Healthy houses and buildings, with low indoor humidity, display no appreciable indoor fungal growth, and outdoor Cladosporium dominates. On the contrary, in sick houses and buildings, high indoor humidity allows fungal growth (mainly of Penicillium and Aspergillus), with concomitant release of conidia and fragments into the atmosphere. The intoxication probably results from a chronic exposure to volatile organic compounds and mycotoxins produced by Penicillium, Aspergillus, and Stachybotrys.
Relatively little is known about exposures to traffic-related particulate matter at schools located in dense urban areas. The purpose of this study was to examine the influences of diesel traffic proximity and intensity on ambient concentrations of fine particulate matter (PM(2.5)) and black carbon (BC), an indicator of diesel exhaust particles, at New York City (NYC) high schools. Outdoor PM(2.5) and BC were monitored continuously for 4-6 weeks at each of 3 NYC schools and 1 suburban school located 20 kilometers upwind of the city. Traffic count data were obtained using an automated traffic counter or video camera. BC concentrations were 2-3 fold higher at urban schools compared with the suburban school, and among the 3 urban schools, BC concentrations were higher at schools located adjacent to highways. PM(2.5) concentrations were significantly higher at urban schools than at the suburban school, but concentrations did not vary significantly among urban schools. Both hourly average counts of trucks and buses and meteorological factors such as wind direction, wind speed, and humidity were significantly associated with hourly average ambient BC and PM(2.5) concentrations in multivariate regression models. An increase of 443 trucks/buses per hour was associated with a 0.62 mug/m(3) increase in hourly average BC at a NYC school located adjacent to a major interstate highway. Car traffic counts were not associated with BC. The results suggest that local diesel vehicle traffic may be important sources of airborne fine particles in dense urban areas and consequently may contribute to local variations in PM(2.5) concentrations. In urban areas with higher levels of diesel traffic, local, neighborhood-scale monitoring of pollutants such as BC, which compared to PM(2.5), is a more specific indicator of diesel exhaust particles, may more accurately represent population exposures.
Collecting data from students within classrooms or schools, and collecting data from students on multiple occasions over time, are two common sampling methods used in educational research that often require multilevel modeling (MLM) data analysis techniques to avoid Type-1 errors. The purpose of this article is to clarify the seven major steps involved in a multilevel analysis: (1) clarifying the research question, (2) choosing the appropriate parameter estimator, (3) assessing the need for MLM, (4) building the level-1 model, (5) building the level-2 model, (6) multilevel effect size reporting, and (7) likelihood ratio model testing. The seven steps are illustrated with both a cross-sectional and a longitudinal MLM example from the National Educational Longitudinal Study (NELS) dataset. The goal of this article is to assist applied researchers in conducting and interpreting multilevel analyses and to offer recommendations to guide the reporting of MLM analysis results.
A middle school (grades 6 to 8) in a residential section of Springfield, Illinois, with no known air quality problems, was selected for a baseline indoor air quality survey. The study was designed to measure and evaluate air quality at the middle school with the objective of providing a benchmark for comparisons with measurements in schools with potential air quality problems. The focus of this article is on the development of emission factors for particulate matter and bioaerosols. The school was characterized as having no health complaints and good maintenance schedules. Four indoor locations including the cafeteria, a science classroom, an art classroom, the lobby outside the main office, and one outdoor location were sampled for various environmental comfort and pollutant parameters for one week in February 1997. Integrated samples (eight-hour sampling time) for respirable and total particulate matter, and short-term measurements (two-minute samples, three times per day) for bioaerosols were collected on three consecutive days at each of the sampling sites. Continuous measurements of carbon dioxide were logged at all locations for five days. Continuous measurements of respirable particulate matter were also collected in the lobby area. A linear relationship between occupancy and corresponding carbon dioxide and particle concentrations was seen. A completely mixed space, one compartment mass balance model with estimated CO2 generation rates and actual CO2 and particulate matter concentrations was used to model ventilation and pollutant emission rates. Emission factors for occupancy were represented by the slope of emission rate versus occupancy scatter plots. The following particle and bioaerosol emission factors were derived from the indoor measurements: total particles: 1.28 mg/hr/person-hr; respirable particles: 0.154 g/hr/person-hr; total fungi: 167 CFU/hr/person-min; thermophilic fungi: 35.8 CFU/hr/person-min; mesophilic fungi: 119 CFU/hr/person-min; total bacteria: 227 CFU/hr/person-min; gram-negative bacteria: 69.5 CFU/hr/person-min; gram-positive bacteria: 191 CFU/hr/person-min; Aspergillus: 17.0 CFU/hr/person-min; Penicillium: 161 CFU/hr/person-min; and yeasts: 16.4 CFU/hr/person-min.
In order to study the influence of furnishings and cleaning on the indoor air quality at school, 181 randomly chosen classrooms were investigated. The amounts of open shelves, textiles and other fittings were noted, data were gathered on cleaning routines, and a number of pollutants were measured in the classrooms. In classrooms with more fabrics there was more settled dust and the concentration of formaldehyde was higher. Classrooms with more open shelves had more formaldehyde, and more pet allergens in settled dust, and classrooms with a white board, instead of a chalk board, were less dusty. Classrooms mainly cleaned through wet mopping had more airborne viable bacteria but less settled dust than classrooms mainly cleaned by dry methods. In rooms where the desks and curtains were more often cleaned, the concentrations of cat and dog allergen in settled dust were lower. It is concluded that furnishings and textiles in the classroom act as significant reservoirs of irritants and allergens and have an impact on the indoor air quality at school.
Choosing the appropriate floor surface for a school environment is a complex issue. To assist school personnel in determining which flooring is best for their school, we studied the biocontaminant levels associated with carpeted and hard surface flooring. Two schools were selected, one predominantly tiled and one predominantly carpeted, as similar as possible with the exception of their floor coverings. Neither school was a "problem" building. Multiple biocontaminants were measured. For flooring, there were statistically significant differences for all the tested biocontaminants except fungi. The carpeted surfaces, being strong sinks, generally had higher surface loadings of the biocontaminants, while the airborne levels were significantly higher over tiled floors. Significant differences in airborne levels were found for dust mass, spores, fungi, beta-1,3 glucans, and endotoxins. The results suggest that carpet flooring was not the major contributor to airborne levels of biocontaminants in these two nonproblem schools.
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In the frame of the French national research program PRIMEQUAL (inter-ministry program for better air quality in urban environments), measurements of outdoor and indoor pollution have been carried out in eight schools in La Rochelle (France) and its suburbs. The buildings were naturally ventilated by opening the windows, or mechanically ventilated, and showed various air permeabilities. Ozone, nitrogen oxides (NO and NO(2)), and airborne particle (particle counts within 15 size intervals ranging from 0.3 to 15 mum) concentrations were continuously monitored indoors and outdoors for two 2-week periods. The indoor humidity, temperature, CO(2) concentration (an indicator of occupancy), window openings and building permeability were also measured. The temporal profiles of indoor and outdoor concentrations show ozone and nitrogen oxides behave differently: NO and NO(2) indoor/outdoor concentration ratios (I/O) were found to vary in a range from 0.5 to 1, and from 0.88 to 1, respectively, but no correlation with building permeability was observed. On the contrary, I/O ratios of ozone vary in a range from 0 to 0.45 and seem to be strongly influenced by the building air-tightness: the more airtight the building envelope, the lower the ratio. Occupancy, through re-suspension of previously deposited particles and possible particle generation, strongly influences the indoor concentration level of airborne particles. However, this influence decreases with particle size, reflecting the way deposition velocities vary as a function of size. The influence of particle size on deposition and penetration across the building envelope is also discussed by analyzing the I/O ratios measured when the buildings were unoccupied, by comparing the indoor concentrations measured when the buildings were occupied and when they were not (O/U ratios), and by referring to previously published studies focussing on this topic. Except one case, I/O were found to vary in the range from 0.03 to 1.79. All O/U are greater than one and increase up to 100 with particle size.
Practical implications:
Assessing children's total exposure requires the knowledge of outdoor and indoor air contaminant concentrations. The study presented here provides data on compared outdoor and indoor concentration levels in school buildings, as well as information on the parameters influencing the relationship between outdoor and indoor air quality. It may be used as a basis for estimating indoor concentrations from outdoor concentrations data, or as a first step in designing buildings sheltering children against atmospheric pollution.
With 63% of US children under 5 years of age in regular child care, day-care facilities could be an important source of exposure to indoor allergens.
This study examined levels of 7 indoor allergens in 89 day-care facilities in 2 North Carolina counties.
At each facility, a questionnaire was administered, observations were made, and vacuumed dust samples were collected from carpeted and noncarpeted areas of one room. Allergen concentrations were measured with antibody-based ELISAs.
Each allergen was detected in a majority of facilities (52% to 100%). Geometric mean concentrations were 5.19 mug/g for Alternaria alternata , 2.06 mug/g for Can f 1, 1.43 microg/g for Fel d 1, 0.21 U/g for Bla g 1, 0.20 microg/g for Der p 1, 0.10 microg/g for Der f 1, and 0.01 microg/g for Mus m 1. Concentrations for 5 of the 7 allergens were not statistically different from concentrations found in southern US homes sampled in the National Survey of Lead and Allergens in Housing. In rooms with carpet and hard-surfaced flooring, levels of A alternata , Can f 1, Der f 1, Der p 1, and Fel d 1 were statistically higher on carpet.
In this survey of day-care facilities in North Carolina, detectable levels of indoor allergens were commonly found. For many young children and day-care staff, day-care facilities might be a source of clinically relevant exposures to indoor allergens.
The 12-h mass concentration of PM(10), PM(2.5), and PM(1) was measured in a lecturing room by means of three co-located Harvard impactors. The filters were changed at 8 AM and at 8 PM to cover the periods of presence and absence of students. Concentrations were assessed by gravimetry. Ambient PM(10) data were available for corresponding 12-h intervals from the nearest state air-quality-monitoring network station. The data were pooled into four periods according to the presence and absence of students-Monday-Thursday day (workday daytime), Monday-Thursday night (workday night), Friday-Sunday day (weekend daytime), and Friday-Sunday night (weekend night). Average indoor workday daytime concentrations were 42.3, 21.9 and 13.7 microgm(-3), workday night were 20.9, 19.1 and 15.2 microgm(-3), weekend daytime were 21.9, 18.1 and 11.4 microgm(-3), and weekend night were 24.5, 21.3, and 15.6 microgm(-3) for PM(10), PM(2.5), and PM(1), respectively. The highest 12-h mean, median, and maximum (42.3, 43.0, and 76.2 microgm(-3), respectively) indoor concentrations were recorded on workdays during the daytime for PM(10). The statistically significant (r=0.68,P<0.0009) correlation between the number of students per hour per day and the indoor coarse fraction calculated as PM(10--2.5) during daytime on workdays indicates that the presence of people is an important source of coarse particles indoor. On workdays, the daytime PM(10) indoor/outdoor ratio was positively associated (r=0.93) with an increasing indoor coarse fraction (PM(10--2.5)), also indicating that an important portion of indoor PM(10) had its source inside the classroom. With the exception of the calculated coarse fraction (PM(10--2.5)), all of the measured indoor particulate matter fractions were significantly highly correlated with outdoor PM(10) and negatively correlated with wind velocity, showing that outdoor levels of particles influence their indoor concentrations.
A quantitative real-time PCR method was developed and used for determination of streptomycetes in indoor dust samples of five homes collected during three years. The specificity of the method was tested with 14 Streptomyces and ten non-streptomycetous species, revealing a high specificity for mesophilic streptomycetes. Thermophilic species and S. albus were not efficiently detected. The method gave reproducible results in replicate analyses of the same dust DNA as well as of duplicate DNA isolations. The amount of streptomycetes in house dust was lowest in winter, followed by summer, and highest in spring and fall. The greatest variation in Streptomyces-concentrations was observed in the spring and fall samples.
School classrooms are potentially important micro-environments for childhood exposures owing to the large amount of time children spend in these locations. While a number of airborne contaminants may be present in schools, to date few studies have examined ultrafine particle (0.02-1 microm) (UFP) levels in classrooms. In this study, our objective was to characterize UFP counts (cm(-3)) in classrooms during the winter months and to develop a model to predict such exposures based on ambient weather conditions and outdoor UFPs, as well as classroom characteristics such as size, temperature, relative humidity, and carbon dioxide levels. In total, UFP count data were collected on 60 occasions in 37 occupied classrooms at one elementary school and one secondary school in Pembroke, Ontario. On average, outdoor UFP levels exceeded indoor measures by 8989 cm(-3) (95% confidence interval (CI): 6382, 11596), and classroom UFP counts were similar at both schools with a combined average of 5017 cm(-3) (95% CI: 4300, 5734). Of the variables examined only wind speed and outdoor UFPs were important determinants of classrooms UFP levels. Specifically, each 10 km/h increase in wind speed corresponded to an 1873 cm(-3) (95% CI: 825, 2920) decrease in classroom UFP counts, and each 10000 cm(-3) increase in outdoor UFPs corresponded to a 1550 cm(-3) (95% CI: 930, 2171) increase in classroom UFP levels. However, high correlations between these two predictors meant that the independent effects of wind speed and outdoor UFPs could not be separated in multivariable models, and only outdoor UFP counts were included in the final predictive model. To evaluate model performance, classroom UFP counts were collected for 8 days at two new schools and compared to predicted values based on outdoor UFP measures. A moderate correlation was observed between measured and predicted classroom UFP counts (r=0.63) for both schools combined, but this relationship was not valid on days in which a strong indoor UFP source (electric kitchen stove) was active in schools. In general, our findings suggest that reasonable estimates of classroom UFP counts may be obtained from outdoor UFP data but that the accuracy of such estimates are limited in the presence of indoor UFP sources.
The objective of the study was to measure the indoor air quality in classrooms with special emphasis on particulate matter (PM 10) and carbon dioxide (CO(2)) and the impact of cleaning and ventilation.
PM 10 was analysed via gravimetric method and by laser beam technology. CO(2) was analysed by infrared sensors. Measurements were collected for 3 weeks; first week: "normal" cleaning (twice a week) and ventilation; second week: intensified cleaning (five times a week); third week: intensified cleaning and intensified ventilation.
Levels of PM 10 in the classrooms during the 3 weeks were 69+/-19microg/m(3) and they were dominated by occupancy and the persons' activity. Intensified cleaning showed a significant decrease in all classrooms (79+/-22 to 64+/-15microg/m(3)). The effect of ventilation on levels of PM10 was inconsistent - levels of CO(2) were very high in all schools and could be diminished by intensified ventilation (mean 1459 to 1051ppm).
Although further investigation is needed to study detailed characteristics of the PM 10 (size distribution, chemical identity) the data are sufficient to improve the cleaning and the ventilation in schools.
Department for Education: Guidance on ventilation, thermal comfort and indoor air quality in schools
- Dfe
DfE. Department for Education: Guidance on ventilation,
thermal comfort and indoor air quality in schools, 2014.
BS EN ISO 16000-1: 2006: Indoor air – Part 1: General aspects of sampling strategy
- British Standard
British Standard Institution. BS EN ISO 16000-1: 2006: Indoor air – Part 1: General aspects of sampling strategy.
Ergonomics of the thermal environment -Instruments for measuring physical quantities
British Standard Institution. BS EN ISO 7726: 2001:
Ergonomics of the thermal environment -Instruments for
measuring physical quantities. London: BSI, no. 1, 2001.
BS EN ISO 16000-15: 2008: Indoor air -Part 15: Sampling strategy for nitrogen dioxide
- British Standard Institution
British Standard Institution. BS EN ISO 16000-15:
2008: Indoor air -Part 15: Sampling strategy for nitrogen
dioxide (NO 2 ). London: BSI, 2008.
Ambient air quality -Diffusive samplers for the determination of concentrations of gases and vapours -Requirements and test methods
British Standard Institution. BS EN 13528-3: 2003:
Ambient air quality -Diffusive samplers for the determination of concentrations of gases and vapours -Requirements and test methods. London: BSI, 2003.