Indoor Air Quality Assessment Research Articles

Assessment of Indoor Air Quality in School Facilities: An Educational Experience of Pathways for Transversal Skills and Orientation (PCTO)

Assessment of Indoor Air Quality in School Facilities: An Educational Experience of Pathways for Transversal Skills and Orientation (PCTO)

A Method for Predicting Indoor CO2 Concentration in University Classrooms: An RF-TPE-LSTM Approach

Classrooms play a pivotal role in students’ learning, and maintaining optimal indoor air quality is crucial for their well-being and academic performance. Elevated CO2 levels can impair cognitive abilities, underscoring the importance of accurate predictions of CO2 concentrations. To address the issue of inadequate analysis of factors affecting classroom CO2 levels in existing models, leading to suboptimal feature selection and limited prediction accuracy, we introduce the RF-TPE-LSTM model in this study. Our model integrates factors that affect classroom CO2 levels to enhance predictions, including occupancy, temperature, humidity, and other relevant factors. It combines three key components: random forest (RF), tree-structured Parzen estimator (TPE), and long short-term memory (LSTM). By leveraging these techniques, our model enhances the predictive capabilities and refines itself through Bayesian optimization using TPE. Experiments conducted on a self-collected dataset of classroom CO2 concentrations and influencing factors demonstrated significant improvements in the MAE, RMSE, MAPE, and R2. Specifically, the MAE, RMSE, and MAPE were reduced to 2.96, 5.54, and 0.60%, respectively, with the R2 exceeding 98%, highlighting the model’s effectiveness in assessing indoor air quality.

Quantification of cooking oil fumes using non-catalytic transesterification: A reliable method for indoor air quality assessment

Cooking oil fumes (COFs), which are aerosols formed via the interaction of water and oil (triglycerides, TGs), contribute to the incidence of lung cancer. Control of indoor COF concentrations has not yet been established, as reliable methods for quantifying COFs have not been developed. This study aimed to quantify COFs based on the derivatization of TGs via a non-catalytic transesterification reaction. Our investigation into the thermolytic behaviors of oil confirmed that COFs generated at ≤ 200 °C primarily consisted of oil and water vapor. Alkali-catalyzed transesterification is commonly used for the derivatization of TGs. However, it is sensitive to impurities such as free fatty acids and water, leading to side reactions. Furthermore, this reaction requires additional purification steps to separate the catalyst and has long reaction times (≥120 min). In contrast, non-catalytic transesterification is not sensitive to impurities and can achieve a conversion yield of over 97 wt% within 1 min. The conversion yield of non-catalytic transesterification was higher than that of the alkali-catalyzed method, indicating that non-catalytic transesterification could be a more reliable method for quantifying COFs. Additionally, the concentration of COFs determined using non-catalytic derivatization was higher than that obtained using the conventional aerosol analysis method (PM gravimetric method). This approach addresses a critical gap in current practices, offering a valuable tool for assessing and regulating COF levels in indoor spaces. Consequently, this contributes to broader efforts aimed at mitigating potential adverse health effects associated with exposure to COFs.

Robot-assisted indoor air quality monitoring and assessment: a systematic review

Robot-assisted indoor air quality monitoring and assessment: a systematic review

The association between indoor air quality and respiratory health symptoms among preschool children in Penang, Malaysia

ABSTRACT A cross-sectional study was conducted among 126 preschool children aged 4–6 years in traffic, industrial, and suburban areas of Penang, Malaysia, to determine their exposure to indoor air pollutants and their associations with respiratory symptoms. A standardised and validated questionnaire was used to collect data on respiratory health symptoms among respondents. An indoor air quality assessment was conducted in selected preschools that included temperature, relative humidity, air velocity, volatile organic compounds (VOCs), and particulate matter (PM2.5, and PM10). There were significant differences in median concentrations of PM2.5, PM10 and relative humidity among study groups. Statistical analysis showed significant associations between air pollutants in preschool with respiratory symptoms. Factors that influenced the increased likelihood of cough and phlegm were linked to the increase in PM2.5 exposure. This study suggests regular classroom cleaning and routine maintenance of air conditioners to be done inside the preschools.

An attention temporal convolutional network-based hybrid approach to simulating indoor air pollutants and their determinants in classroom and office spaces

Accurately assessing and source tracing indoor air quality (IAQ) is crucial for implementing targeted interventions to improve IAQ. This study aimed to investigate the concentrations and underlying determinants of multiple indoor air pollutants in classrooms and office spaces of educational buildings and develop a robust model for precise IAQ assessment and simulation. A walkthrough-based inspection with continuous monitoring of indoor and outdoor PM2.5, PM10, NO2, and O3 was conducted in ten educational buildings in Gainesville, Florida. IAQ dynamics and determinants were systematically compared across spaces to discern setting-specific patterns. An Evolutionary Polynomial Regression method-assisted Attention Temporal Convolution Network (EPR-ATCN) model was developed to assess and predict IAQ. The results revealed that the influencing factors of indoor pollutants in classrooms and offices were similar, but the contribution proportion and weight of each factor differed. Street distance, wall damage, indoor relative humidity, and air conditioning vent size were identified as key determinants for most indoor pollutants. The EPR-ATCN models significantly outperformed Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) ANN-based models in simulating indoor environments of both classrooms (RMSE: 1.6, 2.4 and 4.9) and offices (RMSE: 1.3, 2.9 and 5.1). Follow-up studies exploring IAQ in similar architectural and environmental settings may accordingly reference these findings.

Assessment of indoor air quality of the furniture manufacturers in Binh Duong industrial parks, Vietnam

Abstract Wood furniture and related products are created from raw wood and or wood products that require cutting, sanding, and other handling activities that generate wood dust. Exposure to indoor factory air pollutants can have significant health consequences for workers and nearby communities. Therefore, it was necessary to implement the assessment of indoor air quality in furniture manufacturers. This study mainly aimed to assess the indoor air quality status of physical and chemical aspects at 3 different furniture factories. Each sample was analysed for eight parameters including TSP, PM10, PM2.5, noise, temperature, humidity, wind, and light. Sampling and sample handling techniques were performed based on the usage test methods of Vietnam standards. The concentrations of TSP (194 – 493 μg/m3), PM10 (106.7 – 153.8 μg/m3), PM2.5 (72.8 – 95.6 μg/m3); and, the variables of noise (70.4 – 80.3 dBA), temperature (29.4 – 32.4 °C), humidity (58.0 – 69.4 %), wind (0.29 – 0.49) and light (327 – 573) these considered at 3 furniture manufacturers were within the allowable thresholds of QCVN 02:2019/BYT (Permissible exposure limit value of dust at the workplace), QCVN24:2016/BYT (Permissible exposure levels of noise in the workplace), QCVN26:2016/BYT (Permissible value of microclimate in the workplace); and, QCVN22:2016/BYT (Permissible levels of lighting in the workplace). However, long-term direct exposure of workers to these pollutants would also result in potential health risks. This study also suggested the management and technical control solutions to contribute to improving air quality for furniture manufacturers.

Systematic framework for quantitative assessment of Indoor Air Quality under future climate scenarios; 2100s Projection of a Belgian case study

Alteration of Indoor Air Quality (IAQ) levels in the context of changing climate is correlated with shifting air pollutant emissions, variations in ambient climate, and the mitigation/adaptation strategies applied in buildings to deal with increasing extreme weather events and energy demands. In this study, firstly, a systematic modeling-based framework for the quantitative assessment of the impacts of future building retrofit and climate scenarios on IAQ is presented. After describing the framework, its practical implementation in a demonstrative case study is presented. The proposed framework includes three main parts: i) IAQ measurements, ii) IAQ model design, and iii) future IAQ state evaluation. Regarding the case study, fabricated indoor monitoring devices (O3, CO, NO, NO2, PM2.5, PM10, VOCs, air temperature, relative humidity, and air pressure) based on Low-Cost Sensors were developed, and calibrated with reference analyzers. An indoor measurement campaign was conducted in a naturally ventilated residential building (+2 exhaust fans) in the Wallonia region, south of Belgium (summer of 2021). An IAQ model was designed in the multizone IAQ and ventilation software, CONTAM. The validation and calibration processes were carried out with the aid of experimental data from the indoor measurement campaign. The calibrated IAQ model showed a total conformity of +95 % from the average concentration perspective. Finally, predicted future outdoor air pollution and indoor and outdoor climate data of the case study were fed to the IAQ model (basis-year 2021), and indoor contaminant levels under different climate scenarios were quantitatively assessed till 2100.

Determination of Heavy Metals in Indoor Dust in the Vicinity of Kota Thermal Power Plant under Meteorological Influence at an Industrial City

Nowadays, the assessment of indoor air quality becomes quite significant owing to the extensive residing time spent by people at work place or at office. Keeping this in mind, this study aims at determining concentrations of selected anthropogenic origin metals (Cu, Pb, Cd and Zn) and crustal origin metals (Ca and Fe) in 47 dust samples obtained from indoor environment of houses in the industrial Kota city, India in summer months (March, April and May, 2022) and October 2022 under meteorological influence. On looking at the comparative concentration of the studied anthropogenic origin metals (Cu, Pb, Cd and Zn) Zn is found to be in highest concentration followed by Pb, Cu and Cd respectively. During summer season, meteorological parameters such as speed and direction of wind, relative humidity, temperature have been observed which are found to affect the concentration of metals. The wind rose indicates the sampling sites facing predominant North wind direction (21.20%) from point source Kota Thermal Power Plant (KTPP) in summer were closest to the source and hence encountered the highest metal burden. It is inferred from Enrichment factor, Pearson’s correlations and principal component analysis that coal burning at Kota Thermal Power Plant is the major source of heavy metal burden accompanied by other anthropogenic actions in the study area.

Volatile Carbonyl Compounds Emission in Dry-Process Fibreboard: Identification through a Selective GDME-HPLC-DAD-MS/MS Method

This work presents a novel application of gas-diffusion microextraction (GDME) for the extraction and identification of volatile carbonyl compounds from a dry-process fibreboard (MDF) by combining high-performance liquid chromatography with diode array detection (HPLC–DAD) and mass spectrometry (MS). GDME is a simple, inexpensive, and environmentally friendly technique that allows the simultaneous extraction and derivatization with 2,4-dinitrophenylhydrazine (DNPH) of selected volatiles. The extraction conditions were optimized using design of experiments through a 24 full fractional design followed by a Box–Behnken design, resulting in 35 min of extraction at 45 °C using 500 µL of DNPH 0.15%. The analysis of commercial MDF samples with different characteristics, such as thickness or colour, showed a distinct emission profile of volatile carbonyls. The principal emitting compounds found were formaldehyde, acetaldehyde, acetone, butanal, pentanal, hexanal, heptanal, octanal, and nonanal. A total of 25 compounds were identified using MS, including saturated and unsaturated aldehydes, ketones, dicarbonyls, and benzaldehyde-derivatives. This method can be a valuable tool for the qualitative evaluation of VOCs released from wood-based panels and for the assessment of indoor-air quality.

Preconcentrating sensor systems toward indoor low-concentration VOC detection by goal-oriented, sequential, inverse design strategy

The techniques capable of accurately and effectively detecting low-concentration volatile organic compounds (VOCs) are promising for environmental contaminant monitoring and non-invasive disease diagnosis. However, low-concentration measurement and selective quantification of multiple components are two major challenges for VOC detection. This work proposes the idea of a sensing system that incorporates preconcentration and multiple sensor arrays to address the two challenges. The design principles and strategies of the sensing system were discussed, as well as the key requirements and challenges of each step of the design process. We further developed a goal-oriented, sequential, inverse design method for an accurate sensing system of indoor VOCs, enabling the realization of high cross-selectivity detection. We also demonstrate the potential and feasibility of the sensing system with a preconcentrator through illustrative examples. The proposed system is expected to be scalable and intermittent, moving it closer to reliable, commercial, and portable near real-time determinations of specific VOC concentrations. It would promote the effectiveness of indoor air quality (IAQ) assessments and interventions.

How to measure and control indoor air quality based on intelligent digital twin platforms: A case study in China

In order to address the current disparity between indoor air quality assessment, prediction, and control, this study proposes an intelligent management approach for indoor air quality based on digital twin platforms. By collecting and fusing multi-level, and multi-dimensional data at the physical level, a comprehensive data integration and analysis platform is established in the digital realm, encompassing the ‘Sense-Integrate-Retrieve-Analyze-Feedback’ framework. Various digital technologies, such as the Internet of Things (IoT), Building Information Modeling (BIM), and machine learning, are utilized to integrate and visualize multi-source heterogeneous data through a lightweight web-based interface so that data retrieval, rapid prediction, and intelligent control are feasible based on various backend algorithm models. Compared to traditional measurement methods, this system offers broader spatiotemporal coverage, increased mobility, and less disruption to physical infrastructure, which underscores the sophistication of monitoring technology, data integration, and environmental management. The proposed intelligent platform has been validated in a traditional Chinese dwelling, and practical results demonstrate that most air quality problems occur in the early morning of winter while this system can swiftly predict and issue control signals for adjustments in occupied spaces exceeding predefined healthy thresholds. Field measurements confirmed that most air quality problems can be solved within 30 min after their appearance. By eliminating data silos through real-time synchronization and remote intelligent control via the digital platform, it bridges the gap between problem identification by managers and problem resolution by end-users, ensuring timely responses to indoor air quality concerns.

Risk analysis for preventive conservation of heritage collections in Mediterranean museums: case study of the museum of fine arts in Alexandria (Egypt)

The impacts of climate change on heritage collections in Mediterranean museums are serious and lead to accelerated material degradation, loss of value, increasing conservation costs and climatisation. Climate change scenarios and simulation models have been developed to predict the extreme and average future environmental conditions and to assess the future long-term risks caused by global warming for museum buildings and their collections in Mediterranean countries, with Egypt being particularly at risk. This paper presents the results of the risk analysis of the indoor and outdoor environments in Alexandria Museum of Fine Arts (AMFA) in Egypt to provide an overview of the current situation of conservation and museum management and to provide evidence-based data to support decision-making regarding preventive conservation given the museum's limited funding, capacity and resources. Unfortunately, the air quality in the museum cannot be considered satisfactory and specific measures need to be taken to improve the level of air quality and museum and building management. The results enabled an assessment of indoor air quality and provided information on potential risks to the museum building and collections, including variations in temperature (T) and relative humidity (RH), concentrations of NO2, SO2, O3, CO2, acetic and formic acid and lighting conditions, as well as the location and management of the museum. The results necessitate the development of a preventive conservation plan to address the challenges associated with high T/RH fluctuations and pollution pressure. This requires more regular use of the HVAC system within certain T/RH set points as well as minimising light exposure and the use of UV-filtering glazing. Care should be taken to ensure that housekeeping and emergency preparedness reduce the damping and salt florescence in the museum building. However, dealing with the impact of climate change on indoor and outdoor environments and museum collections in Mediterranean museums requires a holistic and adaptive approach that includes joint collaboration, research, training and strategic planning to ensure the long-term preservation of valuable cultural heritage collections in different climates with customised adaptations based on local environmental conditions, resources and needs. Resilience planning should be region-specific and take into account the potential impacts of extreme weather events, sea level rise and other climate-related challenges.

Detection of C6H6, CO2, and H2S gases on arsenic (As) and cobalt (Co) doped quantum dots (QDs) nanostructured materials

Abstract Gas sensors exhibit significant potential due to their widespread use in various applications, such as food packaging, indoor air quality assessment, and real-time monitoring of man-made gas emissions to mitigate global warming. The utilization of nanostructured materials for sensor and adsorbent surfaces has seen remarkable growth over time, though substantial efforts are still needed to develop more efficient adsorbents. Consequently, this study investigates the viability of metal-doped quantum dots (QDs) as prospective gas-sensing and adsorption materials. Density functional theory (DFT) calculations employing the 6-311 + G(d,p) basis set and three functionals (B3LYP, B3LYP-GD3(BJ), and ɷB97XD) were utilized for this investigation. Three environmentally and health-significant gases (C6H6, CO2, and H2S) were chosen as adsorbates on arsenic (As) and cobalt (Co) functionalized QDs to assess the performance and sensing capabilities of resulting QD surfaces. The analysis encompassed computation of adsorption energy, thermodynamic properties, non-covalent interactions, natural bond orbital analysis, and other topological aspects for both the surfaces and gases. The outcomes indicate that the GP_As functionalized surface exhibits a lower energy gap, rendering it more reactive and sensitive toward the respective gases (C6H6, CO2, and H2S). Moreover, the calculated adsorption energies of the investigated systems indicate thermodynamic favorability and spontaneity. Notably, our findings suggest that QD_As surfaces possess superior adsorption potential for H2S compared to the other gases examined; nonetheless, all studied QD surfaces demonstrate significant adsorption capacities for C6H6, CO2, and H2S gases.

A review of the indoor air quality in residential Passive House dwellings

The Passive House (PH) Standard is a voluntary building energy performance standard focused upon reducing space heating demand to a very low level and therefore considered a viable climate change mitigation technology. Besides comfort and energy requirements, the PH standard also defines criteria with respect to ventilation. However, the question remains, how well do PH dwellings perform when they are occupied? Does the PH approach provide good indoor air quality (IAQ) for its occupants and how does IAQ compare to non-PH homes, in particular, naturally ventilated homes? Additionally, can PH certification improve the quality of installed ventilation systems? This paper summarizes indoor air quality relevant aspects of the PH standard and presents results from measurements examining in-use IAQ in more than 600 PH or PH-like, newly built or retrofitted dwellings. The results reveal that pollutant and carbon dioxide concentration are generally lower compared to naturally ventilated homes, presumably due to the requirement to install a balanced Mechanical Ventilation with Heat Recovery (MVHR) system. Results also suggest that the quality assurance measures of PH certification are capable of improving ventilation and IAQ performance. However, the lack of cooking fume capture requirements in the PH standard, in combination with efforts to avoid energy losses associated with a possible extraction kitchen hood, may lead to elevated particulate matter concentration in PHs. Future research on cooking induced IAQ impairment is encouraged to assess the effectiveness of recently published PH-specific recommendations. Future efforts in empirical IAQ research should also address the lack of high quality IAQ measurement data and the standardisation of IAQ assessment methods and protocols.

High-performance formaldehyde prediction for indoor air quality assessment using time series deep learning

High-performance formaldehyde prediction for indoor air quality assessment using time series deep learning

Bacteriological Evaluation of Indoor Air Quality in Some Selected Units at the University of Cape Coast Hospital in Ghana

A hospital is an environment solely for diagnosing and treating patients. Contemporary research, however, reveals the possibility of users contracting diseases due to many factors, such as poor air quality. This research, therefore, delves into the critical indoor air quality assessment domain, focusing on selected units within the University of Cape Coast Hospital, Ghana. The study’s primary objective was to conduct a comprehensive microbial assessment of indoor air quality in eight different units (emergency room, operating theater, out-patient department, consulting rooms, laboratory, male ward, female ward, and ear, nose, and throat unit) of the hospital, shedding light on potential airborne bacteria present. Indoor and outdoor air were sampled using Koch’s sedimentation method. Colony forming units per cubic meter of air (cfu/m3) were determined with the Omeliansky formula. The bacteriological load within the units revealed that the out-patient department had the highest bacterial concentration (139.2±60.32×102 cfu/m3), immediately followed by Outdoor (135.1±43.63×102 cfu/m3), whereas ear, nose, and throat unit recorded the least concentration (0.4±0.57×102 cfu/m3). The remaining units range between 135.1±43.63×102 cfu/m3 and 0.4±0.57×102 cfu/m3. The morphological characteristics of the seven observed bacterial isolates (GSB 1-7) showed the presence of two cocci and five rods. Isolates 1 and 4 had a rhizoid form, isolates 2,3, and 5 had a circular form, while isolates 6 and 7 had filamentous forms. All isolates showed positive gram tests, and endospores were detected in isolates 1, 4, and 6. Bacterial isolates were identified as Bacillus mycoides, Micrococcus luteus, Staphylococcus epidermidis, Bacillus circulans, Staphylococcus saprophyticus, Bacillus subtilis, and Micrococcus sp. These outcomes indicate bacterial contaminations in the indoor environment, likely to pose a significant risk to patients, workers, and visitor’s safety. Therefore, rigorous monitoring and mitigation strategies are essential to ensure a safer environment in healthcare settings.

Enhancing indoor air quality and sustainable living in newly constructed apartments: insights from Dubai

This research paper examines Indoor Air Quality (IAQ) conditions in newly constructed apartments in Dubai to be more sustainable for residents to have healthier lifestyles. Enhanced airtightness and chemical-laden materials contribute to IAQ pollution in these buildings. The study aims to assess pollutant concentrations and variations based on building height. Measurements were conducted in 12 apartment units using the WHO’s IAQ assessment methodology. Most pollutants were within limits, but TVOC exceeded the Dubai Municipality’s standard, measuring at 2634.4 μg/m³, approximately nine times higher than the standard. HCHO (163.4 μg/m³) and toluene (551.4 μg/m³) were identified as significant pollutants with potential health effects. Analysis of pollutant concentrations based on building height revealed higher TVOC levels in upper areas, with 2,828 μg/m³ in the upper area compared to 2,443 μg/m³ in the lower area, indicating more severe indoor air pollution in Ethylbenzene and styrene also highest in upper areas, with ethylbenzene at 122 μg/m³ and styrene at 82 μg/m³ in the upper area, potentially due to elevated sources. Toluene and xylene concentrations were elevated in the middle area, with toluene at 574 μg/m³ and xylene at 321 μg/m³, likely influenced by materials and occupant activities. Benzene concentrations were consistent across all heights at 2.94 μg/m³, suggesting a common source. HCHO concentrations were relatively consistent but slightly higher in the middle and upper areas, with 171 μg/m³ in both, likely influenced by ventilation and emissions. While average pollutant concentrations met WHO standards, many units exceeded recommended limits, requiring targeted interventions. The study highlights the importance of addressing IAQ concerns and implementing strategies to reduce indoor air pollutants and improve ventilation. These findings contribute to IAQ knowledge in Dubai’s residential buildings, guiding policymakers, architects, and developers in effective policies and guidelines. Further research on seasonal variations and other IAQ factors is recommended for better understanding and long-term monitoring. Prioritizing IAQ in newly constructed apartments is crucial for healthier living in Dubai. The residential building sector can protect residents’ health by implementing appropriate measures while delivering upscale living experiences.

Indoor air quality and its determinants in underground shopping malls in Korea

Underground shopping malls (USMs) are often open or semi-open environments with interconnected passageways, resulting in the sharing of indoor air. However, indoor air quality (IAQ) within these spaces can vary due to many diverse emission sources. We investigated the relationships between IAQ and geographical areas, as well as IAQ and store types, within USMs, in Korea.In 2020, we studied 10 different USMs, with a total of 128 outlets. We conducted comprehensive IAQ assessments (including measurements of fine particles (PM2.5), aldehydes, and volatile organic compounds (VOCs)) in stores, passages, and outdoor areas. The stores were categorized into three types: clothing, fashion accessories, and food services. Additionally, we measured environmental factors such as CO2 levels and presence of storefront walls.PM2.5 levels were higher outdoors, whereas aldehyde and VOC levels exhibited elevations within passages and the interior of stores than in the outdoor environment. The store-to-passage ratios for PM2.5, individual aldehydes, and VOC concentrations ranged from 1.06 to 4.93. Formaldehyde and total VOC (TVOC) concentrations were found to be elevated in clothing and fashion accessory stores, whereas PM2.5 concentrations were more prominent in food service establishments. Specific individual compounds, including propionaldehyde, hexaldehyde, benzene, n-heptane, toluene, n-octane, xylene, d-limonene, n-undecane, n-dodecane, and ethylbenzene concentrations exhibited associations with store types. Multivariate regression models demonstrated positive associations between most aldehydes and VOCs with CO2 concentrations and presence of storefront walls.This study underscored variations within USMs based on area and store type. Aldehyde and VOC concentrations were notably higher in clothing and fashion accessory stores than in food service outlets; these elevations were closely linked to CO2 levels and presence of storefront walls. These findings suggest that monitoring CO2 levels within USM stores, optimizing air-conditioning systems, and designing future stores without storefront walls can collectively contribute to an overall improvement of IAQ within USMs.

Indoor Air Quality Assessment on Polygons for Solid Municipal Waste for Microbial Contamination and a Method of Cleaning It

Indoor Air Quality Assessment on Polygons for Solid Municipal Waste for Microbial Contamination and a Method of Cleaning It