Indoor Chemical Air Contaminants in Main Prayer Hall during Jumaat Prayer in Mosques with Different Mechanical Ventilation

Muslims generally pray five times a day. Every Friday, adult male Muslims congregate to perform Jumaat prayer, causing increased number of worshippers in mosques and vehicle movements. Consequently, indoor chemical air contaminants are produced inside and outside mosques. This study evaluated the compliance of indoor chemical air contaminants (CO, O3, TVOC, CH2O, and PM10) during Jumaat and Asar prayers in two mosques having different mechanical ventilations (i.e., air conditioning and non-air conditioned system) with the guideline limit recommended by Malaysia’s Industrial Code of Practice. Chemical air contaminants were monitored from 1200HH to 1700H in the air-conditioned mosque and from 1200H to 1730H in the non-air conditioned system mosque, which were the times for Jumaat and Asar prayers. The monitoring was conducted from November 2016 to March 2017, during the Northeast monsoon. Results showed that the mean concentrations of the four chemical air contaminants in both mosques did not exceed the acceptable guideline limit. The mean CO, TVOC, CH2O, and PM10 concentrations in the air-conditioned mosque were 0.29 ppm, 354.09 ppb, 31.28 ppb, and 13.45 μg/m3; those in the non-air conditioned system mosque were 2.36 ppm, 344.32 ppb, 19.78 ppb, and 49.91 μg/m3, respectively. However, the air-conditioned mosque’s maximum PM10 concentration of 164.48 μg/m3 exceeded the acceptable guideline limit of 150 μg/m3. Moreover, both mosques’ mean O3 concentrations of 140 and 80 ppb exceeded the limit of 50 ppb, respectively. These results suggested that the concentrations of three chemical air contaminants (TVOC, O3, and CH2O) in the air-conditioned mosque were higher than those in the non-air conditioned system mosque possibly because of the inadequate ventilation system inside the air-conditioned building. Therefore, air-conditioned mosques should have a good ventilation system to provide suitable temperature and humidity for the Jemaah, as well as sufficient amounts of air to remove indoor chemical air contaminants

Distribution and temporal behaviour of O3 and NO2 near selected schools in Seberang Perai, Pulau Pinang and Parit Buntar, Perak, Malaysia

Air quality has deteriorated in urban areas as a result of increased anthropogenic activities. Quantitative information on the influence of meteorological conditions on several pollutants in a tropical climate is still lacking. Real-time ozone (O3) and nitrogen dioxide (NO2) levels were measured nearby selected schools in Malaysia to examine the impact of meteorological factors on monitoring pollutants. The results showed the overall 10 min average concentrations of the main parameters during school holiday were 24 ppb (O3) and 33 ppb (NO2) while during school day the overall 10 min average concentrations were 26 ppb (O3) and 51 ppb (NO2). Although there are no minimum requirements for short-term exposure by MAAQG, if compared to 1 h average requirements, all concentrations were still below the suggested values. Regarding spatial distribution, a different trend in pollutant concentration among the schools was observed because of the influence of temperature (AT) and wind speed (WS). The results were verified by Pearson correlation, where signifi cant correlations (p<0.01) were determined between air pollutants and meteorological factors, which were temperature, wind speed and relative humidity. Meanwhile, the distribution of O3 was moderately correlated with NO2. However, the results of multivariate analysis indicate that temperature and relative humidity had the most significant influence on the formation of O3. In summary, the results of this study showed that all precursors and meteorological parameters contribute to the production of O3. Hence, reducing O3 precursors, which are emitted by vehicles, is essential to lessening the exposure to O3

PM10 analysis for three industrialized areas using extreme value

One of the concerns of the air pollution studies is to compute the concentrations of one or more pollutants’ species in space and time in relation to the independent variables, for instance emissions into the atmosphere, meteorological factors and parameters. One of the most significant statistical disciplines developed for the applied sciences and many other disciplines for the last few decades is the extreme value theory (EVT). This study assesses the use of extreme value distributions of the two-parameter Gumbel, two and three-parameter Weibull, Generalized Extreme Value (GEV) and two and three-parameter Generalized Pareto Distribution (GPD) on the maximum concentration of daily PM10 data recorded in the year 2010 - 2012 in Pasir Gudang, Johor; Bukit Rambai, Melaka; and Nilai, Negeri Sembilan. Parameters for all distributions are estimated using the Method of Moments (MOM) and Maximum Likelihood Estimator (MLE). Six performance indicators namely; the accuracy measures which include predictive accuracy (PA), coefficient of determination (R2), Index of Agreement (IA) and error measures that consist of Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Normalized Absolute Error (NAE) are used to find the goodness-of-fit of the distribution. The best distribution is selected based on the highest accuracy measures and the smallest error measures. The results showed that the GEV is the best fit for daily maximum concentration for PM10 for all monitoring stations. The analysis also demonstrates that the estimated numbers of days in which the concentration of PM10 exceeded the Malaysian Ambient Air Quality Guidelines (MAAQG) of 150 mg/m3 are between ½ and 1½ days

Procedural Effects on Controlling Natural Disasters (Landslides and Flash Floods) Based on Environmental Degradation from Development in Malaysia

In recent years, Malaysia's growing population and accelerating economic conditions have resulted in the construction of high-rise condominiums and the expansion of settlements and lifelines across hilly areas. Natural disasters are always happening in Malaysia, with landslides and flash floods as the main problems and common natural disasters. This problem occurs annually due to rising numbers of development in Malaysia involving land clearance and rapid construction, especially in hilly areas. Under such circumstances, research was conducted on landslide and flash flood incidences in Malaysia from 2020 until 2022. The assessment in this research was done using the matrix method commonly used in Environmental Impact Assessment (EIA). The results gained by using those method shows that both landslides and flash flood naturally happen in the last quarter of a year, which are in December and January for both landslides and flash flood disaster. The highest score for landslide incidences was in Putrajaya and Kuala Lumpur with 8.4; in contrast, 9.2, the highest average score recorded for flash floods, happened in Selangor, Pahang, Kelantan, Kuala Lumpur, Melaka, Negeri Sembilan, Perak, and Terengganu. Both of these incidents occurred in December 2021. This situation shows that both natural and man-made affect the occurrence of the tragedy in Malaysia. Heavy rainfall and rapid development lead to this problem. Compliance with general guidelines from contractors, developers and agencies may reduce the number of these disasters in the future. Hence, it will help to prevent soil erosion and slope failure that frequently occurs in Malaysia

Modeling The Fiuctuational And Transformation Characteristics Of Peak Ground Level Ozone in Malaysian Ambient Air

Ground level ozone (O3) is a noxious air pollutant that Imposed adverse effect to human health, crop yield and the environment. Hence, it is important to understand their fluctuation and transformation characteristic which is still regarded at its infancy stage in Malaysia to properly design abatement and control strategies. Therefore, this study aimed to Investigate the characteristics of O3 fluctuation and transformation from its precursors as well as to introduce the critical conversion point (COP) of O3 formation. Next hour O3 prediction models during daily, daytime, nighttime and critical conversion time were also developed using multiple linear regression and principal component regression to predict O3 concentrations in different group of monitoring stations. This study consists of 18 areas across Malaysia from 1999 to 2010. Although an ovenwhelming majority of the recorded data are below the prescribed levels in the Malaysian Ambient Air Quality Guidelines, total of 1,988 hour of exceedences have been recorded with majority contributed by Shah Alam. O3 diurnal cycles suggest a unimodal peak between 12 pm to 4 pm, while minimum concentration is consistently measured on 8 am. Results of PCA showed the contributions to O3 variation by NO2, NO, T and UVB is up to 80%, whereas the composite diurnal plots confirmed that variation is highly depend on NO2 and NO concentrations. The CCP of O3 formation were identified to occur in between 8 am to 11 am. MLR model based on cluster group during daily exhibited optimal performance in terms of coefficient of determination, prediction accuracy, and index of agreement with values of 0.9351, 0.9671 and 0.9831, respectively. Although the optimal model was during daily, the developed models using critical conversion time were more consistent with minimal differences between MLR and PGR in terms of error and accuracy. Effective ground level ozone control, need strategic, systematic and concerted efforts amongenvironmental related agencies in Malaysi

Reported malicious codes incident within Malaysia’s landscape: Time series modelling and a timeline analysis

The advancement of technology is such a marvel in these modern days. As countries embrace the vast progress of cyber-technology, the risk of cyber threats increases. Malicious codes have been one of the most menacing threats in the cyberspace. This research aims to investigate the outliers in the dataset timeline analysis. The data will be analysed to see the outliers and recognize what the crucial factor of the outliers in the data is. Then, the outliers will be investigated, and the findings will be constructed chronologically for the timeline analysis. The data also will be forecasted to predict the trend from May 2022 until December 2024. The predictive algorithms proposed are Autoregressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), and NeuralProphet. The best model is chosen by the least values of mean absolute error (MAE), root mean squared error (RMSE), and mean absolute percentage error (MAPE). The outcome of this research is presented in an interactive dashboard as a deployment of this project. The results from the analysis showed that the best forecasting model is LSTM and from the forecasted data using this model, it can be seen the trend of incident increases until 2023, then decreases to 2024

Characterization of Chemical Composition in Fine Particles (PM2.5) from Industrial Site in Malaysia

This research aims to investigate variations of fine Particulate Matter (PM2.5) and chemical composition in an industrialized area. Concentration levels of fine Particulate Matter (PM2.5) were continuously monitored at three sampling site S1, S2 and S3. The variations of PM2.5 concentration were analysed using descriptive statistics, time series plot, diurnal plot and correlation. Source apportionment and factor analysis were carried out using the chemical composition data from ICP-OES. Meteorological effects on PM2.5 concentration were used to investigate the effects on PM2.5 concentration. The results showed that, the average PM2.5 concentration was 19.75 ± 12, 46.68 ± 27, and 20.55 ± 9 ?g m-3 at sites in a S1, S2 and S3, respectively. The highest PM2.5 concentration was recorded in S2 (115 ?g m-3). The PM2.5 concentration in the diurnal plot exhibited an inversed unimodal pattern during morning (7:00 to 9:00) and evening (16:00 to 18:00). PM2.5 concentration in S2 on weekends was 36% lower than that on weekdays. PM2.5 was found to exhibit an inversed relation with wind speed and temperature. Although wind speed had a negative association with PM2.5 in S1 and S2, a positive correlation was observed at S3. Source apportionment from factor analysis distinguished three groups of possible sources; crustal materials (Al, K, Sr, Ti and Na), vehicles emission (Cr, Fe, Mn, Zn and Ni) and industrial activities (Ca, Mg and Pb)

Dependency of biological contaminants on temperature and relative humidity within praying halls of mosques

The widespread use of Air Conditioning Split Units (ACSU) to cool the air inside mosques may pose potential adverse health effects, secondary to exposure to biological contaminants. To address this issue, the dependencies of biological contaminants (bacteria and fungi) on temperature (T) and relative humidity (RH) of the ‘mosques’ indoor air were evaluated. A total of 25 mosques were investigated during the periods in which their respective congregators were performing Zohor or Friday, and Asar prayers. The recorded average indoor bacteria and fungi concentrations were 382.6±143.9 cfu/m3 and 229.4±165.5 cfu/m3, respectively. However, the study found that masses of bacteria aerosol within the indoors of certain mosques (10 out of 17 ACSU mosques and 1 out of 8 non-ACSU mosques) exceeded the limit recommended by Malaysian standard for indoor air quality (500 cfu/m3). Meanwhile, the results of regression analyses suggested that T and RH of the indoor air have high influence on airborne bacteria and fungi. The variations in bacteria concentrations due to the influence of T and RH in ACSU mosques (T= 92.3%; RH= 90.3%) were higher than in non-ACSU mosques (T= 82.75%; RH= 81.7%) whereas the variations in fungi concentrations in non-ACSU mosques (T=70.45%; RH= 71.45%) were higher than in ACSU mosques (T= 66.05%; RH= 60.7%). This research shows that the growth of bacteria and fungi within the prayer halls of mosques in Malaysia is very much dependent on its indoor T and RH

Level of polychlorinated biphenyls (PCBs) in selected marine fish (pelagic) from Straits of Malacca

Fish is a good source of protein, supply important vitamins and other essential nutrients including essential fatty acids (EFA), the EPA and DHA which help to reduce risk of death from coronary heart diseases. However, diet and food of animals’ origin are the most predominant sources of polychlorinated biphenyls (PCBs) to human which accounts to over 90%, with fish as one of the major routes of contaminants in human body. PCBs are a group of extremely stable aromatic chlorinated compounds which are relatively resistant to biological degradation and very persistent in the environment. This study has identified the type and level of 12 congeners of PCBs that are most toxic to humans. The maximum permitted level of PCBs in muscles meat of fish and fishery products is 4 pg/g, as recommended by World Health Organization (WHO) using the WHO-TEFs. Meanwhile, the highest amount of PCBs concentration was in Rastrelliger kanagurta (Indian mackerel), with the level of PCBs at 1.37 pg/g wet weight. Other species like Scomberomorus guttatus (Spanish mackerel), Pampus argenteus (Silver pompret), Megalapsis cordyla (Hardtail scad), Eleutheronema tradactylum (Fourfinger threadfin) and Chirocentrus dorab (Dorab wolfherring) showed PCBs levels ranging from 0.35 pg/g to 1.05 pg/g wet weight. Thus, the PCBs in all the samples were below the permitted level. It can be concluded that the studied pelagic fish are safe to consume. Although the levels were not high, it is still important to set limits for the PCBs in fish and shellfish species so as to make a better estimation of the risk of exposure to human through dietary intake of fish, specifically fatty fish to meet nutritional requirement for EPA and DHA

Transformational characteristics of ground-level ozone during high particulate events in urban area of Malaysia

Observations of ground-level ozone (O3), nitric oxide (NO), nitrogen dioxide (NO2), particulate matter (PM10) and meteorological parameter (temperature, relative humidity and wind speed) fluctuations during high particulate event (HPE) and non-HPE in Malaysia have been conducted for 2 years (2013 and 2014). The study focuses on urban areas, namely, Shah Alam, Petaling Jaya and Bandaraya Melaka. The diurnal variations of ground-level O3 concentration were higher during HPE than those during non-HPE in all urban areas. The concentration of O3 fluctuated more in 2014 than 2013 due to the higher incidences of HPE. Temperature and wind speed fluctuated with higher PM10, NO2 and NO concentrations during HPE than those during non-HPE in all urban sites. Relative humidity was lower during HPE than that during non-HPE. Positive correlations were found between PM10 and ozone during HPE for Shah Alam and Petaling Jaya with 0.81 and 0.79, respectively. Meanwhile, negative correlation (− 0.76) was recorded for Bandaraya Melaka. The non-HPE correlation of PM10 and O3 showed negative values for all locations except Petaling Jaya (0.02). Temperature and wind speed shows a strong positive correlation with ozone for all locations during HPE and non-HPE with the highest at Shah Alam (0.97). Inverse relationships were found between relative humidity and O3, in which the highest was for Shah Alam (− 0.96) in 2013 and Shah Alam (− 0.97) and Bandaraya Melaka (− 0.97) in 2014. The result of the ozone best-fit equation obtained an R2 of 0.6730. The study parameters had a significant positive relationship with the ozone predictions during HPE