Displaying publications 41 - 60 of 453 in total

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  1. Evaluation performance of time series approach for forecasting air pollution index in Johor, Malaysia
    Nur Haizum Abd Rahman, Muhammad Hisyam Lee, Suhartono, Mohd Talib Latif
    Sains Malaysiana, 2016;45:1625-1633.
    The air pollution index (API) has been recognized as one of the important air quality indicators used to record the
    correlation between air pollution and human health. The API information can help government agencies, policy makers
    and individuals to prepare precautionary measures in order to eliminate the impact of air pollution episodes. This study
    aimed to verify the monthly API trends at three different stations in Malaysia; industrial, residential and sub-urban areas.
    The data collected between the year 2000 and 2009 was analyzed based on time series forecasting. Both classical and
    modern methods namely seasonal autoregressive integrated moving average (SARIMA) and fuzzy time series (FTS) were
    employed. The model developed was scrutinized by means of statistical performance of root mean square error (RMSE).
    The results showed a good performance of SARIMA in two urban stations with 16% and 19.6% which was more satisfactory
    compared to FTS; however, FTS performed better in suburban station with 25.9% which was more pleasing compared
    to SARIMA methods. This result proved that classical method is compatible with the advanced forecasting techniques in
    providing better forecasting accuracy. Both classical and modern methods have the ability to investigate and forecast
    the API trends in which can be considered as an effective decision-making process in air quality policy.
    Matched MeSH terms: Air Pollutants; Air Pollution
  2. Fulltext A new hybrid fuzzy time series model with an application to predict PM10 concentration
    Alyousifi Y, Othman M, Husin A, Rathnayake U
    Ecotoxicol Environ Saf, 2021 Dec 20;227:112875.
    PMID: 34717219 DOI: 10.1016/j.ecoenv.2021.112875
    Fuzzy time series (FTS) forecasting models show a great performance in predicting time series, such as air pollution time series. However, they have caused major issues by utilizing random partitioning of the universe of discourse and ignoring repeated fuzzy sets. In this study, a novel hybrid forecasting model by integrating fuzzy time series to Markov chain and C-Means clustering techniques with an optimal number of clusters is presented. This hybridization contributes to generating effective lengths of intervals and thus, improving the model accuracy. The proposed model was verified and validated with real time series data sets, which are the benchmark data of actual trading of Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and PM10 concentration data from Melaka, Malaysia. In addition, a comparison was made with some existing fuzzy time series models. Furthermore, the mean absolute percentage error, mean squared error and Theil's U statistic were calculated as evaluation criteria to illustrate the performance of the proposed model. The empirical analysis shows that the proposed model handles the time series data sets more efficiently and provides better overall forecasting results than existing FTS models. The results prove that the proposed model has greatly improved the prediction accuracy, for which it outperforms several fuzzy time series models. Therefore, it can be concluded that the proposed model is a better option for forecasting air pollution parameters and any kind of random parameters.
    Matched MeSH terms: Air Pollution*
  3. Fulltext Interventions to mitigate indoor air pollution: A cost-benefit analysis
    Irfan M, Cameron MP, Hassan G
    PLoS One, 2021;16(9):e0257543.
    PMID: 34559814 DOI: 10.1371/journal.pone.0257543
    Globally, around three billion people depend upon solid fuels such as firewood, dry animal dung, crop residues, or coal, and use traditional stoves for cooking and heating purposes. This solid fuel combustion causes indoor air pollution (IAP) and severely impairs health and the environment, especially in developing countries like Pakistan. A number of alternative household energy strategies can be adopted to mitigate IAP, such as using liquefied petroleum gas (LPG), natural gas, biogas, electric stoves, or improved cook stoves (ICS). In this study, we estimate the benefit-cost ratios and net present value of these interventions over a ten-year period in Pakistan. Annual costs include both fixed and operating costs, whereas benefits cover health, productivity gains, time savings, and fuel savings. We find that LPG has the highest benefit-cost ratio, followed by natural gas, while ICS has the lowest benefit-cost ratio. Electric stoves and biogas have moderate benefit-cost ratios that nevertheless exceed one. To maximize the return on cleaner burning technology, the government of Pakistan should consider encouraging the adoption of LPG, piped natural gas, and electric stoves as means to reduce IAP and adopt clean technologies.
    Matched MeSH terms: Air Pollution, Indoor*
  4. Fulltext Energy Optimization Using a Case-Based Reasoning Strategy
    González-Briones A, Prieto J, De La Prieta F, Herrera-Viedma E, Corchado JM
    Sensors (Basel), 2018 Mar 15;18(3).
    PMID: 29543729 DOI: 10.3390/s18030865
    At present, the domotization of homes and public buildings is becoming increasingly popular. Domotization is most commonly applied to the field of energy management, since it gives the possibility of managing the consumption of the devices connected to the electric network, the way in which the users interact with these devices, as well as other external factors that influence consumption. In buildings, Heating, Ventilation and Air Conditioning (HVAC) systems have the highest consumption rates. The systems proposed so far have not succeeded in optimizing the energy consumption associated with a HVAC system because they do not monitor all the variables involved in electricity consumption. For this reason, this article presents an agent approach that benefits from the advantages provided by a Multi-Agent architecture (MAS) deployed in a Cloud environment with a wireless sensor network (WSN) in order to achieve energy savings. The agents of the MAS learn social behavior thanks to the collection of data and the use of an artificial neural network (ANN). The proposed system has been assessed in an office building achieving an average energy savings of 41% in the experimental group offices.
    Matched MeSH terms: Air Conditioning; Air Filters
  5. Fulltext Safety of air travel during the ongoing COVID-19 pandemic
    Bhuvan KC, Shrestha R, Leggat PA, Ravi Shankar P, Shrestha S
    Travel Med Infect Dis, 2021;43:102103.
    PMID: 34111566 DOI: 10.1016/j.tmaid.2021.102103
    Matched MeSH terms: Air Travel*
  6. Air pollution and cardiorespiratory hospitalization, predictive modeling, and analysis using artificial intelligence techniques
    Usmani RSA, Pillai TR, Hashem IAT, Marjani M, Shaharudin R, Latif MT
    Environ Sci Pollut Res Int, 2021 Oct;28(40):56759-56771.
    PMID: 34075501 DOI: 10.1007/s11356-021-14305-7
    Air pollution has a serious and adverse effect on human health, and it has become a risk to human welfare and health throughout the globe. One of the major effects of air pollution on health is hospitalizations associated with air pollution. Recently, the estimation and prediction of air pollution-based hospitalization is carried out using artificial intelligence (AI) and machine learning (ML) techniques, i.e., deep learning and long short-term memory (LSTM). However, there is ample room for improvement in the available applied methodologies to estimate and predict air pollution-based hospital admissions. In this paper, we present the modeling and analysis of air pollution and cardiorespiratory hospitalization. This study aims to investigate the association between cardiorespiratory hospitalization and air pollution, and predict cardiorespiratory hospitalization based on air pollution using the artificial intelligence (AI) techniques. We propose the enhanced long short-term memory (ELSTM) model and provide a comparison with other AI techniques, i.e., LSTM, DL, and vector autoregressive (VAR). This study was conducted at seven study locations in Klang Valley, Malaysia. The utilized dataset contains the data from January 2006 to December 2016 for five study locations, i.e., Klang (KLN), Shah Alam (SA), Putrajaya (PUJ), Petaling Jaya (PJ), and Cheras, Kuala Lumpur (CKL). The dataset for Banting contains data from April 2010 to December 2016, and the data for Batu Muda, Kuala Lumpur, contains data from January 2009 to December 2016. The prediction results show that the ELSTM model performed significantly better than other models in all study locations, with the best RMSE scores in Klang study location (ELSTM: 0.002, LSTM: 0.013, DL: 0.006, VAR: 0.066). The results also indicated that the proposed ELSTM model was able to detect and predict the trends of monthly hospitalization significantly better than the LSTM and other models in the study. Hence, we can conclude that we can utilize AI techniques to accurately predict cardiorespiratory hospitalization based on air pollution in Klang Valley, Malaysia.
    Matched MeSH terms: Air Pollution*
  7. Sulfur dioxide removal: An overview of regenerative flue gas desulfurization and factors affecting desulfurization capacity and sorbent regeneration
    Hanif MA, Ibrahim N, Abdul Jalil A
    Environ Sci Pollut Res Int, 2020 Aug;27(22):27515-27540.
    PMID: 32415453 DOI: 10.1007/s11356-020-09191-4
    Numerous mitigation techniques have been incorporated to capture or remove SO2 with flue gas desulfurization (FGD) being the most common method. Regenerative FGD method is advantageous over other methods due to high desulfurization efficiency, sorbent regenerability, and reduction in waste handling. The capital costs of regenerative methods are higher than those of commonly used once-through methods simply due to the inclusion of sorbent regeneration while operational and management costs depend on the operating hours and fuel composition. Regenerable sorbents like ionic liquids, deep eutectic solvents, ammonium halide solutions, alkyl-aniline solutions, amino acid solutions, activated carbons, mesoporous silica, zeolite, and metal-organic frameworks have been reported to successfully achieve high SO2 removal. The presence of other gases in flue gas, e.g., O2, CO2, NOx, and water vapor, and the reaction temperature critically affect the sorption capacity and sorbent regenerability. To obtain optimal SO2 removal performance, other parameters such as pH, inlet SO2 concentration, and additives need to be adequately governed. Due to its high removal capacity, easy preparation, non-toxicity, and low regeneration temperature, the use of deep eutectic solvents is highly feasible for upscale utilization. Metal-organic frameworks demonstrated highest reported SO2 removal capacity; however, it is not yet applicable at industrial level due to its high price, weak stability, and robust formulation.
    Matched MeSH terms: Air Pollutants*
  8. Fulltext Waste heat recovery research - a systematic bibliometric analysis (1991 to 2020)
    Kuah CT, Koh QY, Rajoo S, Wong KY
    Environ Sci Pollut Res Int, 2023 Jun;30(28):72074-72100.
    PMID: 35716302 DOI: 10.1007/s11356-022-21377-6
    Human usage of non-renewable energy resources has caused many environmental issues, which include air pollution, global warming, and climate irregularities. To counter these issues, researchers have been seeking after alternative renewable energy sources and ways to manage energy more efficiently. This is where energy recovery technologies such as waste heat recovery (WHR) come into play. WHR is a form of waste to energy conversion. Waste heat can be captured and converted into usable energy instead of dumping it into the environment. In the more recent years, the WHR research field has gained great attention in the scientific community as well as in some energy-intensive industries. This article presents a bibliometric overview of the academic research on WHR over the span of 30 years from 1991 to 2020. A total of 5682 documents from Web of Science (WoS) have been retrieved and analyzed using various bibliometric methods, including performance analysis and network analysis. The analyses were performed on different actors in the field, i.e., funding agencies, journals, authors, organizations, and countries. In addition, several network mappings were done based on co-citation, co-authorship, and co-occurrences of keywords analyses. The research identified the most productive and influential actors in the field, established and emergent research topics, as well as the interrelations and collaboration patterns between different actors. The findings can be a robust roadmap for further research in this field.
    Matched MeSH terms: Air Pollution*
  9. Fulltext Hospital indoor air quality and its relationships with building design, building operation, and occupant-related factors: A mini-review
    Ibrahim F, Samsudin EZ, Ishak AR, Sathasivam J
    Front Public Health, 2022;10:1067764.
    PMID: 36424957 DOI: 10.3389/fpubh.2022.1067764
    Indoor air quality (IAQ) has recently gained substantial traction as the airborne transmission of infectious respiratory disease becomes an increasing public health concern. Hospital indoor environments are complex ecosystems and strategies to improve hospital IAQ require greater appreciation of its potentially modifiable determinants, evidence of which are currently limited. This mini-review updates and integrates findings of previous literature to outline the current scientific evidence on the relationship between hospital IAQ and building design, building operation, and occupant-related factors. Emerging evidence has linked aspects of building design (dimensional, ventilation, and building envelope designs, construction and finishing materials, furnishing), building operation (ventilation operation and maintenance, hygiene maintenance, access control for hospital users), and occupants' characteristics (occupant activities, medical activities, adaptive behavior) to hospital IAQ. Despite the growing pool of IAQ literature, some important areas within hospitals (outpatient departments) and several key IAQ elements (dimensional aspects, room configurations, building materials, ventilation practices, adaptive behavior) remain understudied. Ventilation for hospitals continues to be challenging, as elevated levels of carbon monoxide, bioaerosols, and chemical compounds persist in indoor air despite having mechanical ventilation systems in place. To curb this public health issue, policy makers should champion implementing hospital IAQ surveillance system for all areas of the hospital building, applying interdisciplinary knowledge during the hospital design, construction and operation phase, and training of hospital staff with regards to operation, maintenance, and building control manipulation. Multipronged strategies targeting these important determinants are believed to be a viable strategy for the future control and improvement of hospital IAQ.
    Matched MeSH terms: Air Pollution, Indoor*
  10. Fulltext Benefit Modeling and Analysis of Wind Power Generation under Social Energy Economy and Public Health
    Liu Y, Abdul Karim Z, Khalid N, Said FF
    J Environ Public Health, 2022;2022:5635853.
    PMID: 35719856 DOI: 10.1155/2022/5635853
    Wind is a renewable energy source. Overall, using wind to produce energy has fewer effects on the environment than many other energy sources. Wind and solar energy provide public health and environmental benefits to the social. Wind turbines may also reduce the amount of electricity generation from fossil fuels, which results in lower total air pollution and carbon dioxide emissions. In order to better optimize the effect of social energy economic management and facilitate the multiobjective decision making of coordinated development of energy and socioeconomic environment, a modeling and analysis method of economic benefits of wind power generation based on deep learning is proposed. In this paper, based on the principle of deep learning, the evaluation indicators of wind power economic benefits are excavated, a scientific and reasonable economic benefit evaluation system is constructed, a wind power economic benefit analysis model supported by public management is constructed, and the steps of wind power economic benefit analysis are simplified. It is concluded that the modeling and analysis method of wind power economic benefits based on deep learning has high practicability in the actual application process, which is convenient for the prediction and analysis of energy demand for social and economic development.
    Matched MeSH terms: Air Pollution*
  11. Biomonitoring of Exposures to Solvents and Metals in Electronics Manufacturing Facilities in Batam, Indonesia
    Lee JH, Gatera VA, Smith T, Panimbang F, Gonzalez A, Abdulah R, et al.
    New Solut, 2024 Feb;33(4):220-235.
    PMID: 38112404 DOI: 10.1177/10482911231218478
    Concerns about chemical exposure in the electronics manufacturing industry have long been recognized, but data are lacking in Southeast Asia. We conducted a study in Batam, Indonesia, to evaluate chemical exposures in electronics facilities, using participatory research and biological monitoring approaches. A convenience sample of 36 workers (28 exposed, 8 controls) was recruited, and urine samples were collected before and after shifts. Five solvents (acetone, methyl ethyl ketone, toluene, benzene, and xylenes) were found in 46%-97% of samples, and seven metals (arsenic, cadmium, cobalt, tin, antimony, lead, and vanadium) were detected in 60%-100% of samples. Biological monitoring and participatory research appeared to be useful in assessing workers' exposure when workplace air monitoring is not feasible due to a lack of cooperation from the employer. Several logistical challenges need to be addressed in future biomonitoring studies of electronics workers in Asia in factories where employers are reluctant to track workers' exposure and health.
    Matched MeSH terms: Air Pollutants, Occupational*
  12. Radiological impacts of the amang processing industry on neighbouring residents
    Ismail B, Redzuwan Y, Chua RS, Shafiee W
    Appl Radiat Isot, 2001 Mar;54(3):393-7.
    PMID: 11214872
    The processing of amang (one of a number of tin-tailing products) for its valuable minerals has associated with the radiological and environmental problems. The processing and stockpiling of amang and ilmenite in open-air spaces, subject as it is to environmental influences, gives rise to a potential for affecting residents in adjacent area. A case study was carried out in a residential area neighbouring a typical amang plant to investigate the radiological impact to the residents. The average Effective Dose rates, calculated based on the contributions of Effective Dose rates from inhaled suspended radioactive dust, radon-thoron and their progeny, and external gamma radiation, were determined for selected houses. Results show that the occupants of those houses received Effective Dose rate, which cannot be differentiated from background. The major contributor to the average Effective Dose rate came from external radiation sources. Inhaled radon and its progeny was the second major contributor.
    Matched MeSH terms: Air Pollutants, Radioactive/adverse effects*; Air Pollutants, Radioactive/analysis; Air Pollution, Indoor/adverse effects; Air Pollution, Indoor/analysis
  13. Fulltext Long-term exposure to outdoor and household air pollution and blood pressure in the Prospective Urban and Rural Epidemiological (PURE) study
    Arku RE, Brauer M, Ahmed SH, AlHabib KF, Avezum Á, Bo J, et al.
    Environ Pollut, 2020 Jul;262:114197.
    PMID: 32146361 DOI: 10.1016/j.envpol.2020.114197
    Exposure to air pollution has been linked to elevated blood pressure (BP) and hypertension, but most research has focused on short-term (hours, days, or months) exposures at relatively low concentrations. We examined the associations between long-term (3-year average) concentrations of outdoor PM2.5 and household air pollution (HAP) from cooking with solid fuels with BP and hypertension in the Prospective Urban and Rural Epidemiology (PURE) study. Outdoor PM2.5 exposures were estimated at year of enrollment for 137,809 adults aged 35-70 years from 640 urban and rural communities in 21 countries using satellite and ground-based methods. Primary use of solid fuel for cooking was used as an indicator of HAP exposure, with analyses restricted to rural participants (n = 43,313) in 27 study centers in 10 countries. BP was measured following a standardized procedure and associations with air pollution examined with mixed-effect regression models, after adjustment for a comprehensive set of potential confounding factors. Baseline outdoor PM2.5 exposure ranged from 3 to 97 μg/m3 across study communities and was associated with an increased odds ratio (OR) of 1.04 (95% CI: 1.01, 1.07) for hypertension, per 10 μg/m3 increase in concentration. This association demonstrated non-linearity and was strongest for the fourth (PM2.5 > 62 μg/m3) compared to the first (PM2.5 
    Matched MeSH terms: Air Pollutants/analysis*; Air Pollution/analysis*; Air Pollution, Indoor/analysis*
  14. Analysis of Southeast Asian pollution episode during June 2013 using satellite remote sensing datasets
    Vadrevu KP, Lasko K, Giglio L, Justice C
    Environ Pollut, 2014 Dec;195:245-56.
    PMID: 25087199 DOI: 10.1016/j.envpol.2014.06.017
    In this study, we assess the intense pollution episode of June 2013, in Riau province, Indonesia from land clearing. We relied on satellite retrievals of aerosols and Carbon monoxide (CO) due to lack of ground measurements. We used both the yearly and daily data for aerosol optical depth (AOD), fine mode fraction (FMF), aerosol absorption optical depth (AAOD) and UV aerosol index (UVAI) for characterizing variations. We found significant enhancement in aerosols and CO during the pollution episode. Compared to mean (2008-2012) June AOD of 0.40, FMF-0.39, AAOD-0.45, UVAI-1.77 and CO of 200 ppbv, June 2013 values reached 0.8, 0.573, 0.672, 1.77 and 978 ppbv respectively. Correlations of fire counts with AAOD and UVAI were stronger compared to AOD and FMF. Results from a trajectory model suggested transport of air masses from Indonesia towards Malaysia, Singapore and southern Thailand. Our results highlight satellite-based mapping and monitoring of pollution episodes in Southeast Asia.
    Matched MeSH terms: Air Pollutants/analysis; Air Pollution/analysis; Air Pollution/statistics & numerical data*
  15. Statistical analysis of PM₁₀ concentrations at different locations in Malaysia
    Sansuddin N, Ramli NA, Yahaya AS, Yusof NF, Ghazali NA, Madhoun WA
    Environ Monit Assess, 2011 Sep;180(1-4):573-88.
    PMID: 21136287 DOI: 10.1007/s10661-010-1806-8
    Malaysia has experienced several haze events since the 1980s as a consequence of the transboundary movement of air pollutants emitted from forest fires and open burning activities. Hazy episodes can result from local activities and be categorized as "localized haze". General probability distributions (i.e., gamma and log-normal) were chosen to analyze the PM(10) concentrations data at two different types of locations in Malaysia: industrial (Johor Bahru and Nilai) and residential (Kota Kinabalu and Kuantan). These areas were chosen based on their frequently high PM(10) concentration readings. The best models representing the areas were chosen based on their performance indicator values. The best distributions provided the probability of exceedances and the return period between the actual and predicted concentrations based on the threshold limit given by the Malaysian Ambient Air Quality Guidelines (24-h average of 150 μg/m(3)) for PM(10) concentrations. The short-term prediction for PM(10) exceedances in 14 days was obtained using the autoregressive model.
    Matched MeSH terms: Air Movements; Air Pollutants/analysis*; Air Pollution/statistics & numerical data*
  16. Indoor air pollution evaluation with emphasize on HDI and biological assessment of HDA in the polyurethane factories
    Mirmohammadi M, Hakimi Ibrahim M, Ahmad A, Kadir MO, Mohammadyan M, Mirashrafi SB
    Environ Monit Assess, 2010 Jun;165(1-4):341-7.
    PMID: 19444630 DOI: 10.1007/s10661-009-0950-5
    Today, many raw materials used in factories may have a dangerous effect on the physiological system of workers. One of them which is widely used in the polyurethane factories is diisocyanates. These compounds are widely used in surface coatings, polyurethane foams, adhesives, resins, elastomers, binders, and sealants. Exposure to diisocyanates causes irritation to the skin, mucous membranes, eyes, and respiratory tract. Hexamethylene diamine (HDA) is metabolite of hexamethylene diisocyanate (HDI). It is an excretory material by worker's urine who is exposed to HDI. Around 100 air samples were collected from five defined factories by midget impinger which contained dimethyl sulfoxide absorbent as a solvent and tryptamine as reagent. Samples were analyzed by high-performance liquid chromatography with EC\UV detector using NIOSH 5522 method of sampling. Also, 50 urine samples collected from workers were also analyzed using William's biological analysis method. The concentration of HDI into all air samples were more than 88 microg/m(3), and they have shown high concentration of pollutant in the workplaces in comparison with NIOSH standard, and all of the workers' urine were contaminated by HDA. The correlation and regression test were used to obtain statistical model for HDI and HDA, which is useful for the prediction of diisocyanates pollution situation in the polyurethane factories.
    Matched MeSH terms: Air Pollutants, Occupational/analysis*; Air Pollutants, Occupational/urine; Air Pollution, Indoor*
  17. Key factor in rice husk Ash/CaO sorbent for high flue gas desulfurization activity
    Dahlan I, Lee KT, Kamaruddin AH, Mohamed AR
    Environ Sci Technol, 2006 Oct 01;40(19):6032-7.
    PMID: 17051796
    Siliceous materials such as rice husk ash (RHA) have potential to be utilized as high performance sorbents for the flue gas desulfurization process in small-scale industrial boilers. This study presents findings on identifying the key factorfor high desulfurization activity in sorbents prepared from RHA. Initially, a systematic approach using central composite rotatable design was used to develop a mathematical model that correlates the sorbent preparation variables to the desulfurization activity of the sorbent. The sorbent preparation variables studied are hydration period, x1 (6-16 h), amount of RHA, x2 (5-15 g), amount of CaO, x3 (2-6 g), amount of water, x4 (90-110 mL), and hydration temperature, x5 (150-250 degrees C). The mathematical model developed was subjected to statistical tests and the model is adequate for predicting the SO2 desulfurization activity of the sorbent within the range of the sorbent preparation variables studied. Based on the model, the amount of RHA, amount of CaO, and hydration period used in the preparation step significantly influenced the desulfurization activity of the sorbent. The ratio of RHA and CaO used in the preparation mixture was also a significant factor that influenced the desulfurization activity of the sorbent. A RHA to CaO ratio of 2.5 leads to the formation of specific reactive species in the sorbent that are believed to be the key factor responsible for high desulfurization activity in the sorbent. Other physical properties of the sorbent such as pore size distribution and surface morphology were found to have insignificant influence on the desulfurization activity of the sorbent.
    Matched MeSH terms: Air Pollutants/isolation & purification*; Air Pollutants/chemistry; Air Pollution/prevention & control*
  18. Fulltext Indoor Particulate Matters, Microbial Count Assessments, and Wheezing Symptoms among Toddlers in Urban Day Care Centers in the District of Seremban, Malaysia
    Khamal R, Isa ZM, Sutan R, Noraini NMR, Ghazi HF
    Ann Glob Health, 2019 01 22;85(1).
    PMID: 30741516 DOI: 10.5334/aogh.2425
    INTRODUCTION: Indoor air quality in day care centers (DCCs) is an emerging research topic nowadays. Indoor air pollutants such as particulate matter (PM) and microbes have been linked to respiratory health effects in children, particularly asthma-related symptoms such as night coughs and wheezing due to early exposure to indoor air contaminants.

    OBJECTIVE: The aim of this study was to determine the association between wheezing symptoms among toddlers attending DCCs and indoor particulate matter, PM10, PM2.5, and microbial count level in urban DCCs in the District of Seremban, Malaysia.

    METHODS: Data collection was carried out at 10 DCCs located in the urban area of Seremban. Modified validated questionnaires were distributed to parents to obtain their children's health symptoms. The parameters measured were indoor PM2.5, PM10, carbon monoxide, total bacteria count, total fungus count, temperature, air velocity, and relative humidity using the National Institute for Occupational Safety and Health analytical method.

    RESULTS: All 10 DCCs investigated had at least one indoor air quality parameter exceeding the acceptable level of standard guidelines. The prevalence of toddlers having wheezing symptoms was 18.9%. There was a significant different in mean concentration of PM2.5 and total bacteria count between those with and those without wheezing symptoms (P = 0.02, P = 0.006).

    CONCLUSIONS: Urban DCCs are exposed to many air pollutants that may enter their buildings from various adjacent sources. The particle concentrations and presence of microbes in DCCs might increase the risk of exposed children for respiratory diseases, particularly asthma, in their later life.

    Matched MeSH terms: Air Microbiology/standards; Air Pollution, Indoor/analysis; Air Pollution, Indoor/prevention & control
  19. Multiple linear regression and regression with time series error models in forecasting PM10 concentrations in Peninsular Malaysia
    Ng KY, Awang N
    Environ Monit Assess, 2018 Jan 06;190(2):63.
    PMID: 29306973 DOI: 10.1007/s10661-017-6419-z
    Frequent haze occurrences in Malaysia have made the management of PM10 (particulate matter with aerodynamic less than 10 μm) pollution a critical task. This requires knowledge on factors associating with PM10 variation and good forecast of PM10 concentrations. Hence, this paper demonstrates the prediction of 1-day-ahead daily average PM10 concentrations based on predictor variables including meteorological parameters and gaseous pollutants. Three different models were built. They were multiple linear regression (MLR) model with lagged predictor variables (MLR1), MLR model with lagged predictor variables and PM10 concentrations (MLR2) and regression with time series error (RTSE) model. The findings revealed that humidity, temperature, wind speed, wind direction, carbon monoxide and ozone were the main factors explaining the PM10 variation in Peninsular Malaysia. Comparison among the three models showed that MLR2 model was on a same level with RTSE model in terms of forecasting accuracy, while MLR1 model was the worst.
    Matched MeSH terms: Air Pollutants/analysis*; Air Pollution/analysis; Air Pollution/statistics & numerical data*
  20. An evaluation of direct measurement techniques for mercury dry deposition
    Lai SO, Huang J, Hopke PK, Holsen TM
    Sci Total Environ, 2011 Mar 1;409(7):1320-7.
    PMID: 21257194 DOI: 10.1016/j.scitotenv.2010.12.032
    In this project, several surrogate surfaces designed to directly measure Hg dry deposition were investigated. Static water surrogate surfaces (SWSS) containing deionized (DI), acidified water, or salt solutions, and a knife-edge surrogate surface (KSS) using quartz fiber filters (QFF), KCl-coated QFF and gold-coated QFF were evaluated as a means to directly measure mercury (Hg) dry deposition. The SWSS was hypothesized to collect deposited elemental mercury (Hg⁰), reactive gaseous/oxidized mercury (RGM), and mercury associated with particulate matter (Hg(p)) while the QFF, KCl-coated QFF, and gold-coated QFF on the KSS were hypothesized to collect Hg(p), RGM+Hg(p), and Hg⁰+RGM+Hg(p), respectively. The Hg flux measured by the DI water was significantly smaller than that captured by the acidified water, probably because Hg⁰ was oxidized to Hg²+ which stabilized the deposited Hg and decreased mass transfer resistance. Acidified BrCl, which efficiently oxidizes Hg⁰, captured significantly more Hg than other solutions. However, of all collection media, gold-coated QFFs captured 6 to 100 times greater Hg mass than the other surfaces, probably because there is no surface resistance for Hg⁰ deposition to gold surfaces. In addition, the Hg⁰ concentration is usually 100-1000 times higher than RGM and Hg(p). For all other media, co-located samples were not significantly different, and the combination of daytime plus nighttime results were comparable to 24-h samples, implying that Hg⁰, RGM and Hg(p) were not released after they deposited nor did the surfaces reach equilibrium with the atmosphere. Based on measured Hg ambient air concentrations and fluxes, dry deposition velocities of RGM and Hg⁰ to DI water and other surfaces were 5.6±5.4 and 0.005-0.68 cm s⁻¹ in this study, respectively. These results suggest surrogate surfaces can be used to measure Hg dry deposition; however, extrapolating the results to natural surface can be challenging.
    Matched MeSH terms: Air Movements; Air Pollutants/analysis*
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