Source apportionment and health risk assessment of PM10 in a naturally ventilated school in a tropical environment

A review of relevant parameters for assessing indoor air quality in educational facilities

Indoor air quality (IAQ) in educational facilities is crucial due to the extended time students spend in those environments, affecting their health, academic performance, and attendance. This paper aimed to review relevant parameters (building characteristics and factors related with occupancy and activities) for assessing IAQ in educational facilities, and to identify the parameters to consider when performing an IAQ monitoring campaign in schools. It also intended to identify literature gaps and suggest future research directions. A narrative literature review was conducted, focusing on seven key parameters: building location, layout and construction materials, ventilation and air cleaning systems, finishing materials, occupant demographics, occupancy, and activities. The findings revealed that carbon dioxide (CO2) levels were predominantly influenced by classroom occupancy and ventilation rates, while particulate matter (PM) concentrations were significantly influenced by the building's location, design, and occupant activities. Furthermore, this review highlighted the presence of other pollutants, such as trace metals, polycyclic aromatic hydrocarbons (PAHs), carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), and radon, linking them to specific factors within the school environment. Different IAQ patterns, and consequently different parameters, were observed in various school areas, including classrooms, canteens, gymnasiums, computer rooms, and laboratories. While substantial literature exists on IAQ in schools, significant gaps still remain. This study highlighted the need for more studies in middle and high schools, as well as in other indoor microenvironments within educational settings beyond classrooms. Additionally, it underscored the need for comprehensive exposure assessments, long-term studies, and the impacts of new materials on IAQ including the effects of secondary reactions on surfaces. Seasonal variations and the implications of emerging technologies were also identified as requiring further investigation. Addressing those gaps through targeted research and considering the most updated standards and guidelines for IAQ, could lead to define more effective strategies for improving IAQ and safeguarding the students' health and performance.

How international conflicts and global crises can intertwine and affect the sources and levels of air pollution in urban areas

This paper analyses the intertwined impacts of the 2018 US sanctions on Iran and the COVID-19 pandemic (as examples of unplanned international conflicts and global crises) on the source and extent of air pollution in Tehran, the capital of Iran. The impacts are parametrized using the levels of criteria air pollutants (CAP) for 5 years (2015-2020), which were previously deweathered using the promising machine learning technique of Random Forest (RF). The absolute principal component scores-multiple linear regression (APCS-MLR) method and the bivariate polar plot (BPP) technique are used here to analyze the source apportionment profile of the city for the business as usual (BAU; 2015 to 2018), sanctions (2019), and COVID-19 and sanctions (2020) intervals. The results show the severe impact of the 2018 US sanctions on Tehran's air quality (AQ); O3, NO2, CO, PM2.5, and PM10 levels increased by 117%, 55%, 20%, 35%, and 10%, respectively, while SO2 levels decreased by 30%. The sanctions also triggered a number of events, such as the disruption of the high-grade fuel supply chain and the Mazut crisis, which directly or indirectly accelerated the photochemical production of local tropospheric ozone to some extent. Sanctions also disrupted Tehran's AQ response to the pandemic, with CAP levels decreasing by only 2-7% during the pandemic. The ozone and PM10 BPPs show that the source apportionment profile of the city is dominated by local anthropogenic emission sources, especially urban transport, after the sanctions and the pandemic. Results also show that the impact of soft wars, such as the US sanctions against Iran, on urban air quality degradation is much stronger than that of hard wars, such as the Russia-Ukraine war.

To breathe or not to breathe: Inhalational exposure to heavy metals and related health risk

This study reviewed scientific literature on inhalation exposure to heavy metals (HMs) in various indoor and outdoor environments and related carcinogenic and non-carcinogenic risk. A systematic search in Web of Science, Scopus, PubMed, Embase, and Medline databases yielded 712 results and 43 articles met the requirements of the Population, Exposure, Comparator, and Outcomes (PECO) criteria. Results revealed that HM concentrations in most households exceeded the World Health Organization (WHO) guideline values, indicating moderate pollution and dominant anthropogenic emission sources of HMs. In the analyzed schools, universities, and offices low to moderate levels of air pollution with HMs were revealed, while in commercial environments high levels of air pollution were stated. The non-carcinogenic risk due to inhalation HM exposure exceeded the acceptable level of 1 in households, cafes, hospitals, restaurants, and metros. The carcinogenic risk for As and Cr in households, for Cd, Cr, Ni, As, and Co in educational environments, for Pb, Cd, Cr, and Co in offices and commercial environments, and for Ni in metros exceeded the acceptable level of 1 × 10-4. Carcinogenic risk was revealed to be higher indoors than outdoors. This review advocates for fast and effective actions to reduce HM exposure for safer breathing.

Source apportionment for indoor air pollution: Current challenges and future directions

Source apportionment (SA) for indoor air pollution is challenging due to the multiplicity and high variability of indoor sources, the complex physical and chemical processes that act as primary sources, sinks and sources of precursors that lead to secondary formation, and the interconnection with the outdoor environment. While the major indoor sources have been recognized, there is still a need for understanding the contribution of indoor versus outdoor-generated pollutants penetrating indoors, and how SA is influenced by the complex processes that occur in indoor environments. This paper reviews our current understanding of SA, through reviewing information on the SA techniques used, the targeted pollutants that have been studied to date, and their source apportionment, along with limitations or knowledge gaps in this research field. The majority (78 %) of SA studies to date focused on PM chemical composition/size distribution, with fewer studies covering organic compounds such as ketones, carbonyls and aldehydes. Regarding the SA method used, the majority of studies have used Positive Matrix Factorization (31 %), Principal Component Analysis (26 %) and Chemical Mass Balance (7 %) receptor models. The indoor PM sources identified to date include building materials and furniture emissions, indoor combustion-related sources, cooking-related sources, resuspension, cleaning and consumer products emissions, secondary-generated pollutants indoors and other products and activity-related emissions. The outdoor environment contribution to the measured pollutant indoors varies considerably (<10 %- 90 %) among the studies. Future challenges for this research area include the need for optimization of indoor air quality monitoring and data selection as well as the incorporation of physical and chemical processes in indoor air into source apportionment methodology.

Multi-year monitoring of atmospheric dust fall as a sink for lead in an agro-industrial and petrochemical city of Argentina. Geo-accumulation and ecological risk assessment

A multi-year monitoring data set of potentially harmful elements (PHEs), which are present in the chemical composition of atmospheric settleable particulate matter (SPM) in the urban, industrial and port areas in Bahía Blanca, was studied in order to assess potential ecological risk. The selected PHEs were metal elements of local and regional environmental importance (Cd, Cr, Cu, Ni, Pb, and Zn). Seventeen sampling campaigns were carried out between April 2013 and September 2019. After the microwave-assisted acid digestion of samples, the total contents of the PHEs were determined by ICP-OES. The annual dry deposition rate, the indexes associated with the potential ecological risk (RI) and the degree of geo-accumulation (Igeo) of each PHE were calculated. The results indicated that: (a) there are 3 groups (I, II, III) of PHEs with differentiated concentration levels, ranked I (Pb > Zn > Cu) > II (Cr ≈ Ni) > III (Cd) (p < 0.01) in all the studied areas; (b) the median of the total deposition rate was 1 mg cm-2. month-1 with a significant relative contribution of Pb; (c) a considerable increase in geo-accumulation of Pb indicated that SPM was functioning as a sink for Pb, and also reflected a significant progressive increase in the potential ecological risk in all sites (p < 0.01); and (d) there were chemometrically identified potential sources of Pb, Cu and Zn emissions that would be associated mainly to the resuspension of dust from geogenic, industrial and urban origin, and to a lesser extent, to other gaseous emissions of the industrial sector. This work highlights three major aspects of environmental assessment: (a) the value of continuous monitoring as an important tool to detect long-term trends; (b) the importance of the role of dust fall as a useful environmental indicator of lead geo-accumulation; and (c) the great utility of geo-accumulation and potential ecological risk indices as rapid quantitative assessment tools of environmental pollution.

The Influence of Traffic-Related Air Pollution (TRAP) in Primary Schools and Residential Proximity to Traffic Sources on Histone H3 Level in Selected Malaysian Children

This study aimed to investigate the association between traffic-related air pollution (TRAP) exposure and histone H3 modification among school children in high-traffic (HT) and low-traffic (LT) areas in Malaysia. Respondents' background information and personal exposure to traffic sources were obtained from questionnaires distributed to randomly selected school children. Real-time monitoring instruments were used for 6-h measurements of PM₁₀, PM_2.5, PM₁, NO₂, SO₂, O₃, CO, and total volatile organic compounds (TVOC). Meanwhile, 24-h measurements of PM_2.5-bound black carbon (BC) were performed using air sampling pumps. The salivary histone H3 level was captured using an enzyme-linked immunosorbent assay (ELISA). HT schools had significantly higher PM₁₀, PM_2.5, PM₁, BC, NO₂, SO₂, O₃, CO, and TVOC than LT schools, all at p < 0.001. Children in the HT area were more likely to get higher histone H3 levels (z = -5.13). There were positive weak correlations between histone H3 level and concentrations of NO₂ (r = 0.37), CO (r = 0.36), PM₁ (r = 0.35), PM_2.5 (r = 0.34), SO₂ (r = 0.34), PM₁₀ (r = 0.33), O₃ (r = 0.33), TVOC (r = 0.25), and BC (r = 0.19). Overall, this study proposes the possible role of histone H3 modification in interpreting the effects of TRAP exposure via non-genotoxic mechanisms.

Exposure to Particulate PAHs on Potential Genotoxicity and Cancer Risk among School Children Living Near the Petrochemical Industry

This study aimed to assess the association of exposure to particle-bound (PM_2.5) polycyclic aromatic hydrocarbons (PAHs) with potential genotoxicity and cancer risk among children living near the petrochemical industry and comparative populations in Malaysia. PM_2.5 samples were collected using a low-volume sampler for 24 h at three primary schools located within 5 km of the industrial area and three comparative schools more than 20 km away from any industrial activity. A gas chromatography-mass spectrometer was used to determine the analysis of 16 United States Environmental Protection Agency (USEPA) priority PAHs. A total of 205 children were randomly selected to assess the DNA damage in buccal cells, employing the comet assay. Total PAHs measured in exposed and comparative schools varied, respectively, from 61.60 to 64.64 ng m^-3 and from 5.93 to 35.06 ng m^-3. The PAH emission in exposed schools was contributed mainly by traffic and industrial emissions, dependent on the source apportionment. The 95th percentiles of the incremental lifetime cancer risk estimated using Monte Carlo simulation revealed that the inhalation risk for the exposed children and comparative populations was 2.22 × 10^-6 and 2.95 × 10^-7, respectively. The degree of DNA injury was substantially more severe among the exposed children relative to the comparative community. This study reveals that higher exposure to PAHs increases the risk of genotoxic effects and cancer among children.

Particulate bound polycyclic aromatic hydrocarbons over Dhauladhar region of the north-western Himalayas

A systematic yearlong study was carried out in Dhauladhar region of the North-Western Himalayas to investigate dynamics in the composition and concentration of particulate bound polycyclic aromatic hydrocarbons (PAHs) and their source(s) activity. PM₁₀ samples were collected for 24 h, once every week during January 2015-January 2016, at an urban mid-altitude site (Dharamshala) and a rural low-altitude site (Pohara). PAHs were identified and quantified using high performance liquid chromatography coupled with UV-detector. Seasonal average concentration of total PAHs followed a pattern: Summer > Winter > Autumn > Spring in the region. Seasonal average values of molecular diagnostic ratios indicated significant contribution from non-traffic (biomass burning and coal combustion) sources also during winter and spring season, whereas, traffic emissions (gasoline and diesel) were the dominant source at both the locations throughout the year in the region. The Principal Component Analysis deciphered a) emissions from gasoline driven vehicles b) diesel engine exhaust emissions c) biomass/wood burning source d) coal combustion and e) waste incineration and burning of oil/tar as major sources of PAHs in the region. Annual mean values of total Benzo(a)Pyrene Equivalent were much higher than 1 ng.m-3 over both the locations indicating higher lung cancer risk to the people living in this part of the Himalayas.

Air quality warning system based on a localized PM2.5 soft sensor using a novel approach of Bayesian regularized neural network via forward feature selection

It is highly significant to develop efficient soft sensors to estimate the concentration of hazardous pollutants in a region to maintain environmental safety. In this paper, an air quality warning system based on a robust PM_2.5 soft sensor and support vector machine (SVM) classifier is reported. The soft sensor for the estimation of PM_2.5 concentration is proposed using a novel approach of Bayesian regularized neural network (BRNN) via forward feature selection (FFS). Zuoying district of Taiwan is selected as the region of study for implementation of the estimation system because of the high pollution in the region. Descriptive statistics of various pollutants in Zuoying district is computed as part of the study. Moreover, seasonal variation of particulate matter (PM) concentration is analyzed to evaluate the impact of various seasons on the increased levels of PM in the region. To investigate the linear dependence of concentration of different pollutants to the concentration of PM_2.5, Pearson correlation coefficient, Kendall's tau coefficient, and Spearman coefficient are computed. To achieve high performance for the PM_2.5 estimation, selection of appropriate forward features from the input variables is carried out using FFS technique and Bayesian regularization is incorporated to the neural network system to avoid the overfitting problem. The comparative evaluation of performance of BRNN/FFS estimation system with various other methods shows that our proposed estimation system has the lowest mean square error (MSE), root mean square error (RMSE), and mean absolute error (MAE). Moreover, the coefficient of determination (R-squared) is around 0.95 for the proposed estimation method, which denotes a good fit. Evaluation of the SVM classifier showed good performance indicating that the proposed air quality warning system is efficient.

The exposure of children to PM2.5 and dust in indoor and outdoor school classrooms in Kuala Lumpur City Centre

It is important to assess indoor air quality in school classrooms where the air quality may significantly influence school children's health and performance. This study aims to determine the concentrations of PM_2.5 and dust chemical compositions in indoor and outdoor school classroom located in Kuala Lumpur City Centre. The PM_2.5 concentration was measured from 19th September 2017-16th February 2018 using an optical PM_2.5 sensor. Indoor and outdoor dust was also collected from the school classrooms and ion and trace metal concentrations were analysed using ion chromatography (IC) and inductively couple plasma-mass spectrometry (ICP-MS) respectively. This study showed that the average indoor and outdoor 24 h PM_2.5 was 11.2 ± 0.45 µg m^-3 and 11.4 ± 0.44 µg m^-3 respectively. The 8 h PM_2.5 concentration ranged between 3.2 and 28 µg m^-3 for indoor and 3.2 and 19 µg m^-3 for outdoor classrooms. The highest ion concentration in indoor dust was Ca²⁺ with an average concentration of 38.5 ± 35.0 µg g^-1 while for outdoor dust SO₄^2- recorded the highest ion concentration with an average concentration of 30.6 ± 9.37 µg g^-1. Dominant trace metals in both indoor and outdoor dust were Al, Fe and Zn. Principle component analysis-multiple linear regression (PCA-MLR) demonstrated that the major source of indoor dust was road dust (69%), while soil dominated the outdoor dust (74%). Health risk assessment showed that the hazard quotient (HQ) value for non-carcinogenic trace metals was < 1 while the total cancer risk (CR) value for carcinogenic elements was below the acceptable limit for both indoor and outdoor dust through dermal and inhalation pathways, but not the ingestion pathway. This study suggests indoor contributions of PM_2.5 concentrations are due to the activities of the school children while the compositions of indoor and outdoor dust are greatly influenced by the soil/earth source plus industrial and traffic contribution.

Sequential prediction of quantitative health risk assessment for the fine particulate matter in an underground facility using deep recurrent neural networks

Particulate matter with aerodynamic diameter less than 2.5 µm (PM_2.5) in indoor public spaces such as subway stations, has represented a major public health concern; however, forecasting future sequences of quantitative health risk is an effective method for protecting commuters' health, and an important tool for developing early warning systems. Despite the existence of several predicting methods, some tend to fail to forecast long-term dependencies in an effective way. This paper aims to implement a multiple sequences prediction of a comprehensive indoor air quality index (CIAI) traced by indoor PM_2.5, utilizing different structures of recurrent neural networks (RNN). A standard RNN (SRNN), long short-term memory (LSTM) and a gated recurrent unit (GRU) structures were implemented due to their capability of managing sequential, and time-dependent data. Hourly indoor PM_2.5 concentration data collected in the D-subway station, South Korea, were utilized for the validation of the proposed method. For the selection of the most suitable predictive model (i.e. SRNN, LSTM, GRU), a point-by-point prediction on the PM_2.5 was conducted, demonstrating that the GRU structure outperforms the other RNN structures (RMSE = 21.04 µg/m³, MAPE = 32.92%, R² = 0.65). Then, this model is utilized to sequentially predict the concentration and quantify the health risk (i.e. CIAI) at different time lags. For a 6-h time lag, the proposed model exhibited the best performance metric (RMSE = 29.73 µg/m³, MAPE = 29.52%). Additionally, for the rest of the time lags including 12, 18 and 24 h, achieved an acceptable performance (MAPE = 29-37%).

Heavy metal quantification of classroom dust in school environment and its impacts on children health from Rawang (Malaysia)

This study aimed to determine bioavailable heavy metal concentrations (As, Cd, Co, Cu, Cr, Ni, Pb, Zn) and their potential sources in classroom dust collected from children's hand palms in Rawang (Malaysia). This study also aimed to determine the association between bioavailable heavy metal concentration in classroom dust and children's respiratory symptoms. Health risk assessment (HRA) was applied to evaluate health risks (non-carcinogenic and carcinogenic) due to heavy metals in classroom dust. The mean of bioavailable heavy metal concentrations in classroom dust found on children's hand palms was shown in the following order: Zn (1.25E + 01 μg/g) > Cu (9.59E-01 μg/g) > Ni (5.34E-01 μg/g) > Cr (4.72E-02 μg/g) > Co (2.34E-02 μg/g) > As (1.77E-02 μg/g) > Cd (9.60E-03 μg/g) > Pb (5.00E-03 μg/g). Hierarchical cluster analysis has clustered 17 sampling locations into three clusters, whereby cluster 1 (S3, S4, S6, S15) located in residential areas and near to roads exposed to vehicle emissions, cluster 2 (S10, S12, S9, S7) located near Rawang town and cluster 3 (S13, S16, S1, S2, S8, S14, S11, S17, S5) located near industrial, residential and plantation areas. Emissions from vehicles, plantations and industrial activities were found as the main sources of heavy metals in classroom dust in Rawang. There is no association found between bioavailable heavy metal concentrations and respiratory symptoms, except for Cu (OR = 0.03). Health risks (non-carcinogenic and carcinogenic risks) indicated that there are no potential non-carcinogenic and carcinogenic risks of heavy metals in classroom dust toward children health.

Health impact assessment from building life cycles and trace metals in coarse particulate matter in urban office environments

This study intends to determine the health impacts from two office life cycles (St.1 and St.2) using life cycle assessment (LCA) and health risk assessment of indoor metals in coarse particulates (particulate matter with diameters of less than 10µm). The first building (St.1) is located in the city centre and the second building (St.2) is located within a new development 7km away from the city centre. All life cycle stages are considered and was analysed using SimaPro software. The trace metal concentrations were determined by inductively couple plasma-mass spectrometry (ICP-MS). Particle deposition in the human lung was estimated using the multiple-path particle dosimetry model (MPPD). The results showed that the total human health impact for St.1 (0.027 DALY m^-2) was higher than St.2 (0.005 DALY m^-2) for a 50-year lifespan, with the highest contribution from the operational phase. The potential health risk to indoor workers was quantified as a hazard quotient (HQ) for non-carcinogenic elements, where the total values for ingestion contact were 4.38E-08 (St.1) and 2.59E-08 (St.2) while for dermal contact the values were 5.12E-09 (St.1) and 2.58E-09 (St.2). For the carcinogenic risk, the values for dermal and ingestion routes for both St.1 and St.2 were lower than the acceptable limit which indicated no carcinogenic risk. Particle deposition for coarse particles in indoor workers was concentrated in the head, followed by the pulmonary region and tracheobronchial tract deposition. The results from this study showed that human health can be significantly affected by all the processes in office building life cycle, thus the minimisation of energy consumption and pollutant exposures are crucially required.

Ambient fine particulate matter (PM2.5) in Canadian oil sands communities: Levels, sources and potential human health risk

An investigation of levels and potential sources affecting ambient fine particulate matter (PM_2.5) and associated risk to public health was undertaken at two Canadian oil sands communities (Fort McKay and Fort McMurray) using a 4-year dataset (2010-2013). Geometric mean concentrations of PM_2.5 at Fort McKay and Fort McMurray are not considered high and were 5.47μg/m³ (interquartile range, IQR=3.02-8.55μg/m³) and 4.96μg/m³ (IQR=3.20-7.04μg/m³), respectively. Carcinogenic risks of trace elements were below acceptable (1×10^-6) and/or within tolerable risk (1×10^-4), and non-carcinogenic risks were below a safe level of concern (hazard index=1). Positive matrix factorization (PMF) modeling revealed five sources, where fugitive dust appeared as the major contributor to PM_2.5 mass (Fort McKay: 32%, Fort McMurray: 46%) followed by secondary sulfate (31%, 42%) and secondary nitrate/biomass burning (26%, 8%). Other minor sources included a mining/mobile and a Mn-rich/Mn-Co-Zn-rich source. Source-specific risk values were also estimated and were well below acceptable and safe level of risks. Further work would be needed to better understand the contribution of secondary organic aerosols to PM_2.5 formation in these oil sands communities.