Displaying publications 1 - 20 of 193 in total

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  1. Adcock KE, Ashfold MJ, Chou CC, Gooch LJ, Mohd Hanif N, Laube JC, et al.
    Environ Sci Technol, 2020 04 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*
  2. 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*
  3. Ramakreshnan L, Aghamohammadi N, Fong CS, Bulgiba A, Zaki RA, Wong LP, et al.
    Environ Sci Pollut Res Int, 2018 Jan;25(3):2096-2111.
    PMID: 29209970 DOI: 10.1007/s11356-017-0860-y
    Seasonal haze episodes and the associated inimical health impacts have become a regular crisis among the ASEAN countries. Even though many emerging experimental and epidemiological studies have documented the plausible health effects of the predominating toxic pollutants of haze, the consistency among the reported findings by these studies is poorly understood. By addressing such gap, this review aimed to critically highlight the evidence of physical and psychological health impacts of haze from the available literature in ASEAN countries. Systematic literature survey from six electronic databases across the environmental and medical disciplines was performed, and 20 peer-reviewed studies out of 384 retrieved articles were selected. The evidence pertaining to the health impacts of haze based on field survey, laboratory tests, modelling and time-series analysis were extracted for expert judgement. In specific, no generalization can be made on the reported physical symptoms as no specific symptoms recorded in all the reviewed studies except for throat discomfort. Consistent evidence was found for the increase in respiratory morbidity, especially for asthma, whilst the children and the elderly are deemed to be the vulnerable groups of the haze-induced respiratory ailments. A consensual conclusion on the association between the cardiovascular morbidity and haze is unfeasible as the available studies are scanty and geographically limited albeit of some reported increased cases. A number of modelling and simulation studies demonstrated elevating respiratory mortality rates due to seasonal haze exposures over the years. Besides, evidence on cancer risk is inconsistent where industrial and vehicular emissions are also expected to play more notable roles than mere haze exposure. There are insufficient regional studies to examine the association between the mental health and haze. Limited toxicological studies in ASEAN countries often impede a comprehensive understanding of the biological mechanism of haze-induced toxic pollutants on human physiology. Therefore, the lack of consistent evidence among the reported haze-induced health effects as highlighted in this review calls for more intensive longitudinal and toxicological studies with greater statistical power to disseminate more reliable and congruent findings to empower the institutional health planning among the ASEAN countries.
    Matched MeSH terms: Air Pollutants/analysis*; Air Pollutants/toxicity
  4. Mohd Suhaimi Hamzah, Shamsiah Abdul Rahman, Abdul Khalik Wood
    MyJurnal
    Atmospheric Pollution due to airborne particle is a major concern to many cities in the Southeast Asian region, including Kuala Lumpur. Within the last six years air particulate samples have been collected from a site in Kuala Lumpur and measured for their PM10, PM2.5 and elemental concentrations. The results showed that the daily PM10 (
    Matched MeSH terms: Air Pollutants
  5. Ismail Sulaiman, Khairuddin Mohamad Kontol, Faizal Azrin Abdul Razalim, Azman Jaafar
    MyJurnal
    The objective of this study was to measure indoor radon concentrations in the expected high risk area around Ipoh in Kinta Valley, Perak. The area was chosen based on its own special characteristics. The measurements were carried out by means of long term exposure (3 months) using CR-39 solid state nuclear track detector. The mean indoor radon concentration in Ipoh was 45 Bq/m3 which is equivalent to effective dose of 1.1 mSv/y. This value was higher compared to low or normal area in Bangi, Selangor but comparable to the world average value reported by UNSCEAR. The maximum value of indoor radon concentration measured was 87 Bq/m3.
    Matched MeSH terms: Air Pollutants, Radioactive
  6. Li L, An J, Zhou M, Qiao L, Zhu S, Yan R, et al.
    Environ Sci Technol, 2018 Dec 18;52(24):14216-14227.
    PMID: 30288976 DOI: 10.1021/acs.est.8b01211
    An integrated source apportionment methodology is developed by amalgamating the receptor-oriented model (ROM) and source-oriented numerical simulations (SOM) together to eliminate the weaknesses of individual SA methods. This approach attempts to apportion and dissect the PM2.5 sources in the Yangtze River Delta region during winter. First, three ROM models (CMB, PMF, ME2) are applied and compared for the preliminary SA results, with information from PM2.5 sampling and lab analysis during the winter seasons. The detailed source category contribution of SOM to PM2.5 is further simulated using the WRF-CAMx model. The two pieces of information from both ROM and SOM are then stitched together to give a comprehensive information on the PM2.5 sources over the region. With the integrated approach, the detailed contributing sources of the ambient PM2.5 at different receptors including rural and urban, coastal and in-land, northern and southern receptors are analyzed. The results are compared with previous data and shows good agreement. This integrative approach is more comprehensive and is able to produce a more profound and detailed understanding between the sources and receptors, compared with single models.
    Matched MeSH terms: Air Pollutants
  7. Muhammad S, Long X
    Mar Pollut Bull, 2020 Sep;158:111422.
    PMID: 32753206 DOI: 10.1016/j.marpolbul.2020.111422
    China's seaborne foreign oil supply through the Malacca Strait is facing security challenges due to territorial disputes, pirate attacks, and geopolitics. To overcome these challenges, China plans to import oil through one of the corridors of the Belt and Road Initiative (BRI)-the China-Pakistan Economic Corridor (CPEC). This study estimated and compared ship emissions and their externalities associated with seaborne oil supply from the top five oil suppliers to China through the existing shipping route via the Malacca Strait and proposed route via CEPC. Ship activity-based methodology is applied to estimate the emissions of air pollutants (CO2, NOx, SO2, PM10, and CO) during cruising, maneuvering, and hoteling periods. The results show that the total ship emissions of China's seaborne oil supply can be significantly reduced from 6.2 million tons to 2.1 million tons via the CPEC route. While external cost can be reduced up to 65.9% via the CPEC route.
    Matched MeSH terms: Air Pollutants/analysis*
  8. 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*
  9. 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*
  10. 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*
  11. 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
  12. Md Yusof NF, Ramli NA, Yahaya AS, Sansuddin N, Ghazali NA, Al Madhoun W
    Environ Monit Assess, 2010 Apr;163(1-4):655-67.
    PMID: 19365611 DOI: 10.1007/s10661-009-0866-0
    There are many factors that influence PM(10) concentration in the atmosphere. This paper will look at the PM(10) concentration in relation with the wet season (north east monsoon) and dry season (south west monsoon) in Seberang Perai, Malaysia from the year 2000 to 2004. It is expected that PM(10) will reach the peak during south west monsoon as the weather during this season becomes dry and this study has proved that the highest PM(10) concentrations in 2000 to 2004 were recorded in this monsoon. Two probability distributions using Weibull and lognormal were used to model the PM(10) concentration. The best model used for prediction was selected based on performance indicators. Lognormal distribution represents the data better than Weibull distribution model for 2000, 2001, and 2002. However, for 2003 and 2004, Weibull distribution represents better than the lognormal distribution. The proposed distributions were successfully used for estimation of exceedences and predicting the return periods of the sequence year.
    Matched MeSH terms: Air Pollutants/analysis
  13. 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*
  14. 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*
  15. Thiruchelvam L, Dass SC, Zaki R, Yahya A, Asirvadam VS
    Geospat Health, 2018 05 07;13(1):613.
    PMID: 29772882 DOI: 10.4081/gh.2018.613
    This study investigated the potential relationship between dengue cases and air quality - as measured by the Air Pollution Index (API) for five zones in the state of Selangor, Malaysia. Dengue case patterns can be learned using prediction models based on feedback (lagged terms). However, the question whether air quality affects dengue cases is still not thoroughly investigated based on such feedback models. This work developed dengue prediction models using the autoregressive integrated moving average (ARIMA) and ARIMA with an exogeneous variable (ARIMAX) time series methodologies with API as the exogeneous variable. The Box Jenkins approach based on maximum likelihood was used for analysis as it gives effective model estimates and prediction. Three stages of model comparison were carried out for each zone: first with ARIMA models without API, then ARIMAX models with API data from the API station for that zone and finally, ARIMAX models with API data from the zone and spatially neighbouring zones. Bayesian Information Criterion (BIC) gives goodness-of-fit versus parsimony comparisons between all elicited models. Our study found that ARIMA models, with the lowest BIC value, outperformed the rest in all five zones. The BIC values for the zone of Kuala Selangor were -800.66, -796.22, and -790.5229, respectively, for ARIMA only, ARIMAX with single API component and ARIMAX with API components from its zone and spatially neighbouring zones. Therefore, we concluded that API levels, either temporally for each zone or spatio- temporally based on neighbouring zones, do not have a significant effect on dengue cases.
    Matched MeSH terms: Air Pollutants/analysis*
  16. Wijedasa LS, Sloan S, Page SE, Clements GR, Lupascu M, Evans TA
    Glob Chang Biol, 2018 10;24(10):4598-4613.
    PMID: 29855120 DOI: 10.1111/gcb.14340
    Carbon emissions from drained peatlands converted to agriculture in South-East Asia (i.e., Peninsular Malaysia, Sumatra and Borneo) are globally significant and increasing. Here, we map the growth of South-East Asian peatland agriculture and estimate CO2 emissions due to peat drainage in relation to official land-use plans with a focus on the reducing emissions from deforestation and degradation (REDD+)-related Indonesian moratorium on granting new concession licences for industrial agriculture and logging. We find that, prior to 2010, 35% of South-East Asian peatlands had been converted to agriculture, principally by smallholder farmers (15% of original peat extent) and industrial oil palm plantations (14%). These conversions resulted in 1.46-6.43 GtCO2 of emissions between 1990 and 2010. This legacy of historical clearances on deep-peat areas will contribute 51% (4.43-11.45 GtCO2 ) of projected future peatland CO2 emissions over the period 2010-2130. In Indonesia, which hosts most of the region's peatland and where concession maps are publicly available, 70% of peatland conversion to agriculture occurred outside of known concessions for industrial plantation development, with smallholders accounting for 60% and industrial oil palm accounting for 34%. Of the remaining Indonesian peat swamp forest (PSF), 45% is not protected, and its conversion would amount to CO2 emissions equivalent to 0.7%-2.3% (5.14-14.93 Gt) of global fossil fuel and cement emissions released between 1990 and 2010. Of the peatland extent included in the moratorium, 48% was no longer forested, and of the PSF included, 40%-48% is likely to be affected by drainage impacts from agricultural areas and will emit CO2 over time. We suggest that recent legislation and policy in Indonesia could provide a means of meaningful emission reductions if focused on revised land-use planning, PSF conservation both inside and outside agricultural concessions, and the development of agricultural practices based on rehabilitating peatland hydrological function.
    Matched MeSH terms: Air Pollutants*
  17. Jabal MH, Abdulmunem AR, Abd HS
    J Air Waste Manag Assoc, 2019 01;69(1):109-118.
    PMID: 30215577 DOI: 10.1080/10962247.2018.1523070
    Plant (vegetable) oil has been evaluated as a substitute for mineral oil-based lubricants because of its natural and environmentally friendly characteristics. Availability of vegetable oil makes it a renewable source of bio-oils. Additionally, vegetable oil-based lubricants have shown potential for reducing hydrocarbon and carbon dioxide (CO2) emissions when utilized in internal combustion (IC) engines and industrial operations. In this study, sunflower oil was investigated to study its lubricant characteristics under different loads using the four-ball tribometer and the exhaust emissions were tested using a four-stroke, single-cylinder diesel engine. All experimental works conformed to American Society for Testing and Materials standard (ASTM D4172-B). Under low loads, sunflower oil showed adequate tribological characteristics (antifriction and antiwear) compared with petroleum oil samples. The results also demonstrated that the sunflower oil-based lubricant was more effective in reducing the emission levels of carbon monoxide (CO), CO2, and hydrocarbons under different test conditions. Therefore, sunflower oil has the potential to be used as lubricant of mating components.Implications: An experimental investigation of the characteristics of nonedible sunflower oil tribological behaviors and potential as a renewable source for biofluids alternative to the petroleum oils was carried out. The level of emissions of a four-stroke, single-cylinder diesel engine using sunflower oil as a biolubricant was evaluated.
    Matched MeSH terms: Air Pollutants/analysis*
  18. 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*
  19. Hamid HHA, Latif MT, Uning R, Nadzir MSM, Khan MF, Ta GC, et al.
    Environ Monit Assess, 2020 May 08;192(6):342.
    PMID: 32382809 DOI: 10.1007/s10661-020-08311-4
    Benzene, toluene, ethylbenzene and xylenes (BTEX) are well known hazardous volatile organic compounds (VOCs) due to their human health risks and photochemical effects. The main objective of this study was to estimate BTEX levels and evaluate interspecies ratios and ozone formation potentials (OFP) in the ambient air of urban Kuala Lumpur (KL) based on a passive sampling method with a Tenax® GR adsorbent tube. Analysis of BTEX was performed using a thermal desorption (TD)-gas chromatography mass spectrometer (GCMS). OFP was calculated based on the Maximum Incremental Reactivity (MIR). Results from this study showed that the average total BTEX during the sampling period was 66.06 ± 2.39 μg/m3. Toluene (27.70 ± 0.97 μg/m3) was the highest, followed by m,p-xylene (13.87 ± 0.36 μg/m3), o-xylene (11.49 ± 0.39 μg/m3), ethylbenzene (8.46 ± 0.34 μg/m3) and benzene (3.86 ± 0.31 μg/m3). The ratio of toluene to benzene (T:B) is > 7, suggesting that VOCs in the Kuala Lumpur urban environment are influenced by vehicle emissions and other anthropogenic sources. The average of ozone formation potential (OFP) value from BTEX was 278.42 ± 74.64 μg/m3 with toluene and xylenes being the major contributors to OFP. This study also indicated that the average of benzene concentration in KL was slightly lower than the European Union (EU)-recommended health limit value for benzene of 5 μg/m3 annual exposure.
    Matched MeSH terms: Air Pollutants*
  20. 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*
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