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Fulltext Occupancy implications on indoor air quality (IAQ) in selected primary school classrooms around Kuantan, Pahang

Hazrin AH, Maryam Z, Hizrri A, Mohd Shukri MA, Norhidayah A, Samsuddin N

Malaysian Journal of Public Health Medicine, 2017;17 Special(1): 95-105.

The effects of children’s exposure on high concentration of airborne pollutants at schools often associated with increased rate of absenteeism, low productivities and learning performances, and development of respiratory problems. Recent studies have found that the presence of occupants in the classroom seems to give major effect towards the elevation of concentration of airborne pollutants in indoors. In order to evaluate and further understand on the significance of occupancy factor on IAQ, this study has been designed to determine and compare the level of selected physical (particulate matter (PM)) and chemical (carbon dioxide (CO2) and temperature) IAQ parameters and biological contaminants via colony forming unit (CFUm-3 ) for bacteria and fungi inside the selected classrooms during occupied and non-occupied period (first objective). The second objective is to describe the possible sources of airborne pollutants inside the classrooms at the selected primary schools around Kuantan, Pahang. Assessments of physical and chemical IAQ were done by using instruments known as DustMate Environmental Dust Detector and VelociCalc® MultiFunction Ventilation Meter 9565.The data were recorded every 30 minutes for 8 hours during schooldays and weekend at the selected sampling point in the classrooms. For microbial sampling, Surface Air System Indoor Air Quality (SAS IAQ) was used to capture the bacteria and fungi. The data obtained were compared with the established standard reference known as the Industrial Code of Practice on Indoor Air Quality (2010) constructed by the Department of Occupational Safety and Health (DOSH), Malaysia. This study has found that some of the IAQ parameters in the selected classrooms were exceeding the established standards during occupied period in schooldays compared to non-occupied period during weekend. Findings of this study provide the insights for future research including the site selection of school, arrangement of the classrooms and numbers of students per class.

Matched MeSH terms: Air Pollution*
Impact of air pollutants on climate change and prediction of air quality index using machine learning models

Ravindiran G, Rajamanickam S, Kanagarathinam K, Hayder G, Janardhan G, Arunkumar P, et al.

Environ Res, 2023 Dec 15;239(Pt 1):117354.
PMID: 37821071 DOI: 10.1016/j.envres.2023.117354

The impact of air pollution in Chennai metropolitan city, a southern Indian coastal city was examined to predict the Air Quality Index (AQI). Regular monitoring and prediction of the Air Quality Index (AQI) are critical for combating air pollution. The current study created machine learning models such as XGBoost, Random Forest, BaggingRegressor, and LGBMRegressor for the prediction of the AQI using the historical data available from 2017 to 2022. According to historical data, the AQI is highest in January, with a mean value of 104.6 g/gm, and the lowest in August, with a mean AQI value of 63.87 g/gm. Particulate matter, gaseous pollutants, and meteorological parameters were used to predict AQI, and the heat map generated showed that of all the parameters, PM2.5 has the greatest impact on AQI, with a value of 0.91. The log transformation method is used to normalize datasets and determine skewness and kurtosis. The XGBoost model demonstrated strong performance, achieving an R2 (correlation coefficient) of 0.9935, a mean absolute error (MAE) of 0.02, a mean square error (MSE) of 0.001, and a root mean square error (RMSE) of 0.04. In comparison, the LightGBM model's prediction was less effective, as it attained an R2 of 0.9748. According to the study, the AQI in Chennai has been increasing over the last two years, and if the same conditions persist, the city's air pollution will worsen in the future. Furthermore, accurate future air quality level predictions can be made using historical data and advanced machine learning algorithms.

Matched MeSH terms: Air Pollutants*; Air Pollution*
A systematic review of financial implications of air pollution on health in Asia

Jaafar H, Razi NA, Azzeri A, Isahak M, Dahlui M

Environ Sci Pollut Res Int, 2018 Oct;25(30):30009-30020.
PMID: 30187406 DOI: 10.1007/s11356-018-3049-0

Economic losses due to health-related implications of air pollution were huge and incurred significant burdens towards healthcare providers. The objective of this study is to systematically review published literature on the financial implications of air pollution on health in Asia. Four databases: PubMed, Scopus, NHS Economic Evaluation Database (NHS EED), and Web of Science (WoS) were used to identify all the relevant articles. It was limited to all articles that had been published in the respected databases from January 2007 until March 2017. Twenty-four articles were included in this review. Five of the 24 studies (20.8%) reported financial implications of air pollution-related disease through value of statistical life (VOSL) which ranged from USD180 million to USD2.2 billion, six (25%) studies used cost of illness (COI) to evaluate air pollution-related morbidity and found that the cost ranged from USD5.4 million to USD9.1 billion. Another six studies (25%) used a combination of VOSL and COI for both mortality and morbidity valuation and found that the financial implications ranging from USD253 million to USD2.9 billion. Thirteen (54.2%) studies reported healthcare cost associated with both hospital admission and outpatient visit, five (20.1%) on hospital admission only, and one (4.2%) on outpatient visit only. Economic impacts of air pollution can be huge with significant deterioration of health among the Asians.

Matched MeSH terms: Air Pollutants/analysis; Air Pollutants/economics; Air Pollution/analysis; Air Pollution/economics*
Two-way switch: Maximizing productivity of tilted panel in membrane bioreactor

Eliseus A, Bilad MR, Nordin NAHM, Khan AL, Putra ZA, Wirzal MDH, et al.

J Environ Manage, 2018 Dec 15;228:529-537.
PMID: 30273771 DOI: 10.1016/j.jenvman.2018.09.029

Membrane fouling is a major challenge in membrane bioreactors (MBRs) and its effective handling is the key to improve their competitiveness. Tilting panel system offers significant improvements for fouling control but is strictly limited to one-sided panel. In this study, we assess a two-way switch tilting panel system that enables two-sided membranes and project its implications on performance and energy footprint. Results show that tilting a panel improves permeance by up to 20% to reach a plateau flux thanks to better contacts between air bubbles and the membrane surface to scour-off the foulant. A plateau permeance could be achieved at aeration rate of as low as 0.90 l min-1, a condition untenable by vertical panel even at twice of the aeration rate. Switching at short periods (<5min) can maintain the hydraulic performance as in no-switch (static system), enables application of a two-sided switching panel. A comparison of vertical panel under 1.80 l min-1 aeration rate with a switching panel at a half of the rate, switched at 1 min period shows ≈10% higher permeance of the later. Since periodic switching consumes a very low energy (0.55% of the total of 0.276 kWh m-3), with reduction of aeration by 50%, the switching tilted panel offers 41% more energy efficient than a referenced full-scale MBR (0.390 kWh m-3). Overall results are very compelling and highly attractive for significant improvements of MBR technologies.

Matched MeSH terms: Air
Intensity-duration-frequency approach for risk assessment of air pollution events

Masseran N, Mohd Safari MA

J Environ Manage, 2020 Jun 15;264:110429.
PMID: 32217317 DOI: 10.1016/j.jenvman.2020.110429

Intensity-duration-frequency (IDF) curves can serve as useful tools in risk assessment of extreme environmental events. Thus, this study proposes an IDF approach for evaluating the risk of expected occurrences of extreme air pollution as measured by an air pollution index (API). Hourly data of Klang city in Malaysia from 1997 to 2016 are analyzed. For each year, a block maxima size is determined based on four different monsoon seasons. Generalized extreme value (GEV) distribution is used as a model to represent the probabilistic behavior of maximum intensity of the API, which is derived from each block. Based on the GEV model, the IDF curves are developed to estimate the extreme pollution intensities that correspond to various duration hours and return periods. Considering the IDF curves, we found that for any duration hour, the magnitude of pollution intensity tends to be high in parallel with increasing return periods. In fact, a high-intensity pollution event that poses a high risk of affecting the environment is less frequent than low-intensity pollution. In conclusion, the IDF curves provide a good basis for decision makers to assess the expected risk of extreme pollution events in the future.

Matched MeSH terms: Air Pollutants*; Air Pollution*
Modeling the transition behaviors of PM10 pollution index

Masseran N, Safari MAM

Environ Monit Assess, 2020 Jun 17;192(7):441.
PMID: 32557137 DOI: 10.1007/s10661-020-08376-1

Modeling and evaluating the behavior of particulate matter (PM10) is an important step in obtaining valuable information that can serve as a basis for environmental risk management, planning, and controlling the adverse effects of air pollution. This study proposes the use of a Markov chain model as an alternative approach for deriving relevant insights and understanding of PM10 data. Using first- and higher-order Markov chains, we analyzed daily PM10 index data for the city of Klang, Malaysia and found the Markov chain model to fit the PM10 data well. Based on the fitted model, we comprehensively describe the stochastic behaviors in the PM10 index based on the properties of the Markov chain, including its states classification, ergodic properties, long-term behaviors, and mean return times. Overall, this study concludes that the Markov chain model provides a good alternative technique for obtaining valuable information from different perspectives for the analysis of PM10 data.

Matched MeSH terms: Air Pollutants/analysis*; Air Pollution/analysis*
Evaluation of air quality in Sunway City, Selangor, Malaysia from a mobile monitoring campaign using air pollution micro-sensors

Lee CC, Tran MV, Choo CW, Tan CP, Chiew YS

Environ Pollut, 2020 Oct;265(Pt A):115058.
PMID: 32806396 DOI: 10.1016/j.envpol.2020.115058

Due to the increase of the human population and the rapid industrial growth in the past few decades, air quality monitoring is essential to assess the pollutant levels of an area. However, monitoring air quality in a high-density area like Sunway City, Selangor, Malaysia is challenging due to the limitation of the local monitoring network. To establish a comprehensive data for air pollution in Sunway City, a mobile monitoring campaign was employed around the city area with a duration of approximately 6 months, from September 2018 to March 2019. Measurements of air pollutants such as carbon dioxide (CO2) and nitrogen dioxide (NO2) were performed by using mobile air pollution sensors facilitated with a GPS device. In order to acquire a more in-depth understanding on traffic-related air pollution, the measurement period was divided into two different time blocks, which were morning hours (8 a.m.-12 p.m.) and afternoon hours (3 p.m.-7 p.m.). The data set was analysed by splitting Sunway City into different zones and routes to differentiate the conditions of each region. Meteorological variables such as ambient temperature, relative humidity, and wind speed were studied in line with the pollutant concentrations. The air quality in Sunway City was then compared with various air quality standards such as Malaysian Air Quality Standards and World Health Organisation (WHO) guidelines to understand the risk of exposure to air pollution by the residence in Sunway City.

Matched MeSH terms: Air Pollutants/analysis*; Air Pollution/analysis*
Measurement of radon/thoron and its daughter nuclides in room air

Suppian R, Vegandraj S, Kandaiya S

Int J Rad Appl Instrum A, 1992 Jul;43(7):937-8.
PMID: 1321104

Pumping air through a soft tissue which acts as a membrane is a relatively easy and quick method to collect and measure radon/thoron and its daughter nuclides in air. Analysis of the activity of the radionuclides can be calculated using an alpha counter which has been calibrated. In this method the activity of radon/thoron cannot be separated from the activity of radionuclides already present in the aerosol or dust particles.

Matched MeSH terms: Air Pollutants, Radioactive/analysis*; Air Pollution, Indoor/analysis*
Fulltext Assessment of indoor thermal comfort temperature and related behavioural adaptations: a systematic review

Arsad FS, Hod R, Ahmad N, Baharom M, Ja'afar MH

Environ Sci Pollut Res Int, 2023 Jun;30(29):73137-73149.
PMID: 37211568 DOI: 10.1007/s11356-023-27089-9

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.

Matched MeSH terms: Air Conditioning*; Air Pollution, Indoor*
Changes in global NO2 pollution by shipping during the COVID-19 lockdown: Implication for sustainable marine operations

Athul S, Kuttippurath J, Patel VK

J Hazard Mater, 2025 Jan 05;481:136482.
PMID: 39556909 DOI: 10.1016/j.jhazmat.2024.136482

Severe restrictions on human travel and consumption during the lockdown (LD) have affected global marine traffic and operations. The LD period is ideal for studying the emissions as there were restricted human activities. Although several pollutants are emitted by ships, the most important is nitrogen dioxide (NO2), and can be considered an indicator of shipping emissions. Therefore, we examine the changes in NO2 pollution over the shipping lanes, ports and coasts across the globe during LD. Here, we find a significant decline in NO2 during LD over the major lanes, including the USA-Europe trade routes through the North Atlantic Ocean, Asia-Middle East through the Arabian Sea, Interasia, and Intereuropean through the North Sea and Baltic Sea, about 10-20%, as analysed form the TROPOMI satellite measurements. A similar reduction over the sea straight pass, such as the Cape of Good Hope and the Strait of Malacca is also estimated. Furthermore, the major global ports of Callao, Santos, Antwerp, Rotterdam, Busan, Tubarao, Richards Bay, Barcelona, Durban and Chennai exhibit a significant decrease in NO2 during LD, about 30%. The decline in NO2 over the shipping routes and ports can be attributed to reduced cargo, passenger, fishing and tanker vessel density due to the LD restrictions; consistent with the emission inventory analysis. Henceforth, this study suggests strict environmental policies in the shipping sector to curb emissions, as pollution is a great concern for public health in the port cities and coastal regions.

Matched MeSH terms: Air Pollutants/analysis; Air Pollution/analysis
The relationship between CO2 emission, energy consumption and economic growth in Malaysia: a three-way linkage approach

Sulaiman C, Abdul-Rahim AS

Environ Sci Pollut Res Int, 2017 Nov;24(32):25204-25220.
PMID: 28929456 DOI: 10.1007/s11356-017-0092-1

This study examines the three-way linkage relationships between CO2 emission, energy consumption and economic growth in Malaysia, covering the 1975-2015 period. An autoregressive distributed lag approach was employed to achieve the objective of the study and gauged by dynamic ordinary least squares. Additionally, vector error correction model, variance decompositions and impulse response functions were employed to further examine the relationship between the interest variables. The findings show that economic growth is neither influenced by energy consumption nor by CO2 emission. Energy consumption is revealed to be an increasing function of CO2 emission. Whereas, CO2 emission positively and significantly depends on energy consumption and economic growth. This implies that CO2 emission increases with an increase in both energy consumption and economic growth. Conclusively, the main drivers of CO2 emission in Malaysia are proven to be energy consumption and economic growth. Therefore, renewable energy sources ought to be considered by policy makers to curb emission from the current non-renewable sources. Wind and biomass can be explored as they are viable sources. Energy efficiency and savings should equally be emphasised and encouraged by policy makers. Lastly, growth-related policies that target emission reduction are also recommended.

Matched MeSH terms: Air Pollutants*
Fulltext Air filtration study to improve indoor air quality: a proposed study

Amir Abdullah, M.D., Abdullah, A.H., Leman, A.M.

Journal of Occupational Safety and Health, 2015;12(1):203-207.
MyJurnal

Indoor air quality has been a major public concern recently. Several health effects are related to this problem.
Findings from several studies have shown MVAC system as the main contributor for IAQ problem. Good practice of
maintenance and servicing is important to maintain MVAC system, especially the filter. Good air filtration for MVAC
system is needed to make sure adequate air is received by the occupants. This paper illustrated a recent study of air
filtration for MVAC system especially for several industries that used MVAC system in their premises. This paper also
proposed an air filtration study for a better air quality. Several Acts and Regulations related to Safety and Health were
identified to create the framework for the proposed study. Air filtration technique was used in this preliminary study
to set up guidelines to create safe and clean indoor spaces for workers and occupants.

Matched MeSH terms: Air Pollution; Air Pollution, Indoor
Fulltext Investigation of East Asian Emissions of CFC-11 Using Atmospheric Observations in Taiwan

Adcock KE, Ashfold MJ, Chou CC, Gooch LJ, Mohd Hanif N, Laube JC, et al.

Environ Sci Technol, 2020 Apr 07;54(7):3814-3822.
PMID: 32126759 DOI: 10.1021/acs.est.9b06433

Recent findings of an unexpected slowdown in the decline of CFC-11 mixing ratios in the atmosphere have led to the conclusion that global CFC-11 emissions have increased over the past decade and have been attributed in part to eastern China. This study independently assesses these findings by evaluating enhancements of CFC-11 mixing ratios in air samples collected in Taiwan between 2014 and 2018. Using the NAME (Numerical Atmospheric Modeling Environment) particle dispersion model, we find the likely source of the enhanced CFC-11 observed in Taiwan to be East China. Other halogenated trace gases were also measured, and there were positive interspecies correlations between CFC-11 and CHCl3, CCl4, HCFC-141b, HCFC-142b, CH2Cl2, and HCFC-22, indicating co-location of the emissions of these compounds. These correlations in combination with published emission estimates of CH2Cl2 and HCFC-22 from China, and of CHCl3 and CCl4 from eastern China, are used to estimate CFC-11 emissions. Within the uncertainties, these estimates do not differ for eastern China and the whole of China, so we combine them to derive a mean estimate that we term as being from "(eastern) China". For 2014-2018, we estimate an emission of 19 ± 5 Gg year-1 (gigagrams per year) of CFC-11 from (eastern) China, approximately one-quarter of global emissions. Comparing this to previously reported CFC-11 emissions estimated for earlier years, we estimate CFC-11 emissions from (eastern) China to have increased by 7 ± 5 Gg year-1 from the 2008-2011 average to the 2014-2018 average, which is 50 ± 40% of the estimated increase in global CFC-11 emissions and is consistent with the emission increases attributed to this region in an earlier study.

Matched MeSH terms: Air Pollutants*
Fulltext Diurnal and daily variation of indoor radon concentration in a bedroom for the month of November 2007

Rosli H. Mahat

Journal of Nuclear and Related Technologies, 2010;2010(1):73-76.
MyJurnal

A month hourly measurement of radon concentration was taken in the bedroom of a two story link house in Kuala Lumpur. The house is a typical urban house in Malaysia, constructed with bricks, concrete and cement plaster. These materials are natural sources of radon in the house. The hourly radon concentration was found to vary from 0 pCiL-1 to 3 pCiL-1. It was found to peak during early morning and to minimize in the evening. The daily average radon concentration varied from 0.2 pCiL-1 to 1.0 pCiL-1.

Matched MeSH terms: Air Pollutants, Radioactive; Air Pollution, Radioactive
Fulltext Experiences of early air travel with pneumothorax after anterior spinal surgery

Wong AYF, Foo CH, Wong CC, Ohn KM

BMJ Case Rep, 2021 Aug 19;14(8).
PMID: 34413041 DOI: 10.1136/bcr-2021-243771

Anterior thoracic or thoracolumbar spinal surgery by retropleural approach always carries a risk of pneumothorax as its consequence. Conventionally, the Aerospace Medicine Association and the British Thoracic Society recommend 2 weeks delay of air travel for a patient with resolved postoperative pneumothorax. They also label active pneumothorax as an absolute contraindication for commercial air travel. Such a delay always causes psychological and financial stress to patients and family who are far from home. Here, we report three patients with postoperative pneumothorax, who insisted on early air travel despite being informed of the possible consequences.

Matched MeSH terms: Air Travel*
A systematic literature review of deep learning neural network for time series air quality forecasting

Zaini N, Ean LW, Ahmed AN, Malek MA

Environ Sci Pollut Res Int, 2022 Jan;29(4):4958-4990.
PMID: 34807385 DOI: 10.1007/s11356-021-17442-1

Rapid progress of industrial development, urbanization and traffic has caused air quality reduction that negatively affects human health and environmental sustainability, especially among developed countries. Numerous studies on the development of air quality forecasting model using machine learning have been conducted to control air pollution. As such, there are significant numbers of reviews on the application of machine learning in air quality forecasting. Shallow architectures of machine learning exhibit several limitations and yield lower forecasting accuracy than deep learning architecture. Deep learning is a new technology in computational intelligence; thus, its application in air quality forecasting is still limited. This study aims to investigate the deep learning applications in time series air quality forecasting. Owing to this, literature search is conducted thoroughly from all scientific databases to avoid unnecessary clutter. This study summarizes and discusses different types of deep learning algorithms applied in air quality forecasting, including the theoretical backgrounds, hyperparameters, applications and limitations. Hybrid deep learning with data decomposition, optimization algorithm and spatiotemporal models are also presented to highlight those techniques' effectiveness in tackling the drawbacks of individual deep learning models. It is clearly stated that hybrid deep learning was able to forecast future air quality with higher accuracy than individual models. At the end of the study, some possible research directions are suggested for future model development. The main objective of this review study is to provide a comprehensive literature summary of deep learning applications in time series air quality forecasting that may benefit interested researchers for subsequent research.

Matched MeSH terms: Air Pollution*
Integration of chemical health risk assessment (CHRA) and indoor air quality (IAQ) assessment: from a Malaysian perspective

Abdullah F, Jaafar MH, Ahmad MI, Ismail ZS

Int J Environ Health Res, 2024 May;34(5):2280-2298.
PMID: 37552824 DOI: 10.1080/09603123.2023.2243843

In Malaysia, chemical management in workplaces is managed under the Occupational Safety and Health Act 1994. Hence, the introduction of the Occupational Safety and Health (Use and Standards of Exposure of Chemicals Hazardous to Health) Regulations 2000 has strengthened the chemical management level in workplaces, including higher academic institutions. The introduction of chemical health risk assessment through the regulation required management to conduct the assessment at workplaces. Poor levels of Indoor Air Quality (IAQ) in chemical laboratories may also cause discomfort among workers when there is sick building syndrome in laboratories. IAQ is managed through the Industry Code of Practice on Indoor Air Quality 2010. Although both are different in method and approach, both are meant to ensure the workers' safety and comfort. This study is aimed to investigate the need to integrate both chemical health risk assessment and IAQ assessment in laboratories to ensure optimum safety levels among workers.

Matched MeSH terms: Air Pollution, Indoor*
Targeting microRNAs as a promising anti-cancer therapeutic strategy against traffic-related air pollution-mediated lung cancer

Kazemi Shariat Panahi H, Dehhaghi M, Guillemin GJ, Peng W, Aghbashlo M, Tabatabaei M

Cancer Metastasis Rev, 2024 Jun;43(2):657-672.
PMID: 37910296 DOI: 10.1007/s10555-023-10142-x

Air pollutants are increasingly emitted into the atmosphere because of the high dependency of humans on fossil-derived fuels. Wind speed and direction assisted high dispersibility and uncontrolled nature of air pollution across geo-/demographical borders, making it one of the major global concerns. Besides climate change, air pollution has been found to be associated with various diseases, such as cancer. Lung cancer, which is the world's most common type of cancer, has been found to be associated with traffic-related air pollution. Research and political efforts have been taken to explore green/renewable energy sources. However, these efforts at the current intensity cannot cope with the increasing need for fossil fuels. More specifically, political tensions such as the Russian-Ukraine war, economic tension (e.g., China-USA economic tensions), and other issues (e.g., pandemic, higher inflation rate, and poverty) significantly hindered phasing out fossil fuels. In this context, an increasing global population will be exposed to traffic-related air pollution, which justifies the current uptrend in the number of lung cancer patients. To combat this health burden, novel treatments with higher efficiency and specificity must be designed. One of the potential "life changer" options is microRNA (miRNA)-based therapy to target the expression of oncogenic genes. That said, this review discusses the association of traffic-related air pollution with lung cancer, the changes in indigenous miRNAs in the body during lung cancer, and the current status of miRNA therapeutics for lung cancer treatment. We believe that the article will significantly appeal to a broad readership of oncologists, environmentalists, and those who work in the field of (bio)energy. It may also gain the policymakers' attention to establish better health policies and regulations about air pollution, for example, by promoting (bio)fuel exploration, production, and consumption.

Matched MeSH terms: Air Pollutants/adverse effects
Fulltext Updates in Air Pollution: Current Research and Future Challenges

Vilcins D, Christofferson RC, Yoon JH, Nazli SN, Sly PD, Cormier SA, et al.

Ann Glob Health, 2024;90(1):9.
PMID: 38312715 DOI: 10.5334/aogh.4363

BACKGROUND: The United Nations has declared that humans have a right to clean air. Despite this, many deaths and disability-adjusted life years are attributed to air pollution exposure each year. We face both challenges to air quality and opportunities to improve, but several areas need to be addressed with urgency.
OBJECTIVE: This paper summarises the recent research presented at the Pacific Basin Consortium for Environment and Health Symposium and focuses on three key areas of air pollution that are important to human health and require more research.
FINDINGS AND CONCLUSION: Indoor spaces are commonly places of exposure to poor air quality and are difficult to monitor and regulate. Global climate change risks worsening air quality in a bi-directional fashion. The rising use of electric vehicles may offer opportunities to improve air quality, but it also presents new challenges. Government policies and initiatives could lead to improved air and environmental justice. Several populations, such as older people and children, face increased harm from air pollution and should become priority groups for action.

Matched MeSH terms: Air Pollution, Indoor*
Fulltext Classifying Sources Influencing Indoor Air Quality (IAQ) Using Artificial Neural Network (ANN)

Saad SM, Andrew AM, Shakaff AY, Saad AR, Kamarudin AM, Zakaria A

Sensors (Basel), 2015;15(5):11665-84.
PMID: 26007724 DOI: 10.3390/s150511665

Monitoring indoor air quality (IAQ) is deemed important nowadays. A sophisticated IAQ monitoring system which could classify the source influencing the IAQ is definitely going to be very helpful to the users. Therefore, in this paper, an IAQ monitoring system has been proposed with a newly added feature which enables the system to identify the sources influencing the level of IAQ. In order to achieve this, the data collected has been trained with artificial neural network or ANN--a proven method for pattern recognition. Basically, the proposed system consists of sensor module cloud (SMC), base station and service-oriented client. The SMC contain collections of sensor modules that measure the air quality data and transmit the captured data to base station through wireless network. The IAQ monitoring system is also equipped with IAQ Index and thermal comfort index which could tell the users about the room's conditions. The results showed that the system is able to measure the level of air quality and successfully classify the sources influencing IAQ in various environments like ambient air, chemical presence, fragrance presence, foods and beverages and human activity.

Matched MeSH terms: Air Pollution; Air Pollution, Indoor

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