Assessment of chemicals and radionuclides compositions in hot springs water of Peninsular Malaysia / Nurul Latiffah Abd Rani

Hot springs water has been associated with healing of various types of skin diseases. Despite their therapeutic effects which are known worldwide, there are limited reports on the physicochemical characteristics of hot springs water in Peninsular Malaysia. Therefore, an attempt was made to determine the concentrations of major cations, anions and sulphur including naturally occurring radioactive material (NORM). There are 43 locations of hot springs water with 67 sources identified in Peninsular Malaysia which cover almost all states. Chemicals and radionuclides compositions measured in this study include Na+, K+, Ca2+, Mg2+, S, Cf, SO42', U and Th. Concentrations of Na, K, Ca and S were analysed using Energy Dispersive X-ray Fluorescence (EDXRF) while Mg2+, U and Th were analysed using Inductively Coupled Plasma Optical Emission Spectrometer (ICP-OES). Ion chromatography (IC) was used to analyse C1‘, HCO3 ' and SO42'. Results obtained from the analysis of Na, K, Ca and S done by Energy Dispersive X-ray Fluorescence (EDXRF) were verified using Inductively Coupled Plasma Optical Emission Spectrometer (ICP-OES). The results signified that locations of the hot springs water give different concentrations of chemical due to different geological formations that indirectly contributed to the different effects of therapeutic properties. From the PCA there could be two sources of the hydro chemicals in the hot water springs; granite rock for U and Th, and other cations and anions from other types of rock formation. Additionally, the hot springs water were also classified based on Piper diagram; which was later mapped based on the measured water hydrochemical data. The hot water springs generally can be classified into three types namely type I (Ca-HCOs), type II (Na-Cl) and type III (Na-HCOs). Out of 67 hot springs water sources, 61 of the locations fall into type III (Na-HCOs). Furthermore, ingestion toxicity dose and annual ingestion dose were calculated to identify the dose could obtain if it had been used as a drinking water. In term of health and safety, in general most of hot springs water does not comply with the guidelines use for balneotherapy as well as for drinking. Air Hangat Langkawi, Gersik and Air Panas Terong which falls in type II (Na-Cl) has been identified based on physicochemical properties has been identified the most potent to be used for balneotherapy

Development of missing data prediction model for carbon monoxide

Carbon monoxide (CO) is one of the most important pollutants since it is selected for API calculation. Therefore, it is paramount to ensure that there is no missing data of CO during the analysis. There are numbers of occurrences that may contribute to the missing data problems such as inability of the instrument to record certain parameters. In view of this fact, a CO prediction model needs to be developed to address this problem. A dataset of meteorological and air pollutants value was obtained from the Air Quality Division, Department of Environment Malaysia (DOE). A total of 113112 datasets were used to develop the model using sensitivity analysis (SA) through artificial neural network (ANN). SA showed particulate matter (PM10) and ozone (O3) were the most significant input variables for missing data prediction model of CO. Three hidden nodes were the optimum number to develop the ANN model with the value of R2 equal to 0.5311. Both models (artificial neural network-carbon monoxide-all parameters (ANN-CO-AP) and artificial neural network-carbon monoxide-leave out (ANN-CO-LO)) showed high value of R2 (0.7639 and 0.5311) and low value of RMSE (0.2482 and 0.3506), respectively. These values indicated that the models might only employ the most significant input variables to represent the CO rather than using all input variables

The evaluation on artificial neural networks (ANN) and multiple linear regressions (MLR) models over particulate matter (PM10) variability during haze and non-haze episodes: A decade case study

The comprehensives of particulate matter studies are needed in predicting future haze occurrences in Malaysia. This paper presents the application of Artificial Neural Networks (ANN) and Multiple Linear Regressions (MLR) coupled with sensitivity analysis (SA) in order to recognize the pollutant relationship status over particulate matter (PM10) in eastern region. Eight monitoring studies were used, involving 14 input parameters as independent variables including meteorological factors. In order to investigate the efficiency of ANN and MLR performance, two different weather circumstances were selected; haze and non-haze. The performance evaluation was characterized into two steps. Firstly, two models were developed based on ANN and MLR which denoted as full model, with all parameters (14 variables) were used as the input. SA was used as additional feature to rank the most contributed parameter to PM10 variations in both situations. Next, the model development was evaluated based on selected model, where only significant variables were selected as input. Three mathematical indices were introduced (R2, RMSE and SSE) to compare on both techniques. From the findings, ANN performed better in full and selected model, with both models were completely showed a significant result during hazy and non-hazy. On top of that, UVb and carbon monoxide were both variables that mutually predicted by ANN and MLR during hazy and non- hazy days, respectively. The precise predictions were required in helping any related agency to emphasize on pollutant that essentially contributed to PM10 variations, especially during haze period

Knowledge, beliefs and behaviours related to second-hand smoke and smoking in the home: a qualitative study with men in Malaysia

Introduction Despite the health risks associated with second-hand smoke (SHS) exposure, smoking in the home is common in Malaysia, and almost exclusively a male behaviour. This study explored male smokers’ knowledge, beliefs and behaviours related to SHS exposure and smoking in the home, to guide future intervention development. Methods Twenty-four men who smoked and lived in Klang Valley, Kuantan or Kuala Terengganu took part in semi-structured interviews which explored knowledge and beliefs regarding SHS in the home, and associated home smoking behaviours. Data were managed and analysed using the framework approach. Results There was limited knowledge regarding the health risks associated with SHS: the smell of SHS in the home was a more prominent concern in most cases. Many had no rules in place restricting home-smoking, and some suggested that smoking in specific rooms and/or near windows meant SHS was not ‘shared’ with other household members. A few fathers had created but not maintained a smoke-free home prior to and/or after their children were born. Desire to smoke in the home conflicted with men’s sense of responsibility as the head of the household to protect others and set a good example to their children. Conclusions Men’s home-smoking behaviours are shaped by a lack of understanding of the health risks associated with SHS exposure. Gaining a broader understanding of the factors that shape men’s decisions to create a smoke-free home is important to facilitate the development of culturally-appropriate interventions that address their responsibility to protect other household members from SHS exposure. Implications Our findings highlight the need for public information campaigns in Malaysia to educate men who smoke regarding the health harms associated with SHS in the home and the ways in which SHS travels and lingers in household air. This is important given men’s concerns about SHS often focus on the smell of cigarette smoke in the home. Our findings suggest a number of potential avenues for future intervention development, including household and community-level initiatives which could build on men’s sense of responsibility as the head of the household and/or their general desire to protect their family.Output Status: Forthcoming/Available Onlin

Assessing indoor air quality using chemometric models

The objectives of this study are to identify the significant variables and to verify the best statistical method for determining the effect of indoor air quality (IAQ) at 7 different locations in Universiti Sultan Zainal Abidin, Terengganu, Malaysia. The IAQ data were collected using in-situ measurement. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), linear discrimination analysis (LDA), and agglomerative hierarchical clustering (AHC) were used to classify the significant variables as well as to compare the best method for determining IAQ levels. PCA verifies only 4 out of 9 parameters (PM10, PM2.5, PM1.0, and O3) and is the significant variable in IAQ. The PLS-DA model classifies 89.05% correct of the IAQ variables in each station compared to LDA with only 66.67% correct. AHC identifies three cluster groups, which are highly polluted concentration (HPC), moderately polluted concentration (MPC), and low-polluted concentration (LPC) area. PLS-DA verifies the groups produced by AHC by identifying the variables that affect the quality at each station without being affected by redundancy. In conclusion, PLS-DA is a promising procedure for differentiating the group classes and determining the correct percentage of variables for IAQ

Determination of selected heavy metals in airborne particles in industrial area: a baseline study

This study focuses on airborne heavy metal pollution in the industrial area. Eight points from Paka and Gebeng Industrial Area respectively were selected for this study within two monsoon seasons. The samples were analysed for heavy metals (Cd, As, Cu, Fe, Ni, Pb, and Zn) by using inductively coupled plasma mass spectrometry (ICP-MS). The results showed that the mean concentration value of As, Pb and Cd for Paka were 0.005 mg/L ± 0.001, 0.107 mg/L ± 0.088, and 0.010 mg/L ± 0.008, respectively and Gebeng were 0.004 mg/L ± 0.002, 0.069 mg/L ± 0.059 and 0.005 mg/L ± 0.004, respectively in the southwest monsoon - much higher than the target value by European Commission in Directive 2004/107/EC and Directive 2008/50/EC. It could be concluded that the industrial and transportation emission were the major source of heavy metals in the atmosphere along the Paka and Gebeng Industrial Area

Imputation methods on daily PM10 data (2010-15)

Air pollution monitoring especially PM10 pollutant is very important since the air pollutant data originated from the continuous ambient air quality stations (CAAQS) usually had missing data due to the machine failure, routine maintenance and human error. In view of this fact, a study of PM10 imputation method was performed with the objective to determine the coefficient of determination (R2) and root mean square error (RMSE) in order to portray the goodness of fit for all of the imputation methods used (mean substitution, nearest neighbour and expectation maximization based algorithm (EMB)). The results of R2 obtained for 5%, 10%, 15%, 25% and 40% proportion of missing data using nearest neighbor imputation methods are 0.9318, 0.8126, 0.6546, 0.5458 and 0.3946, while RMSE are 7.47, 12.27, 16.68, 19.13 and 21.76, respectively. Meanwhile, results of R2 obtained for 5%, 10%, 15%, 25% and 40% proportion of missing data using mean imputation methods are 0.9274, 0.8117, 0.6484, 0.5400 and 0.3910, while RMSE are 7.47, 12.36, 16.90, 19.13 and 22.07, respectively. In the meantime, the results of R2 for EMB imputation method applied at 5%, 10%, 15%, 25% and 40% proportion of missing data are 0.9084, 0.8468, 0.7530, 0.5791 and 0.5004, while RMSE are 8.58, 11.18, 14.20, 18.53 and 20.48, respectively. A measure of performances (R2 and RMSE) for each imputation methods decreased and increase respectively as the percentages of simulated missing data increase

Evidence of recovery from the restriction movement order by Mann Kendall during the COVID-19 pandemic in Malaysia

At the end of December 2019, China faced severe acute respiratory syndrome Coronavirus-2 (COVID-19) which caused a "very high" risk assessment ranking. Unfortunately, it has spread all over the world and has caused a great number of fatalities. In view of this, a study of the non-parametric statistical method was carried out with the aim of detecting and quantifying the outbreak of COVID-19. From the univariate analysis, daily cases had the highest mean value indicating widespread data from the outbreak of COVID-19 in Malaysia. However, the worst output in the future during the RMO must be prepared with the help of the Government of Malaysia's Ministry of Health due to the high standard deviation value recorded. In addition, the western coast of Malaysia has been reported to have the most in comparison with the other regions. The Mann-Kendal test shows a declining trend pattern for new cases during RMO3 compared to RMO1, RMO2 and RMO4, with a dramatic increase in the Covid-19 outbreak during RMO1. Overall, the results show downward trends following the implementation of the RMO. These results have shown that the Malaysian Government has implemented an effective strategy to combat the COVID-19 outbreak

Measuring secondhand smoke in homes in Malaysia: A feasibility study comparing indoor fine particulate (PM2.5) concentrations following an educational feedback intervention to create smoke-free homes during the COVID-19 pandemic

Introduction Extensive regulations have been introduced to reduce secondhand smoke (SHS) exposure among non-smokers in Malaysia. However, there is still a need to encourage behavior change of smokers in relation to making homes smokefree. This feasibility study aimed to use low-cost air pollution monitors to quantify SHS concentrations in Malaysian households and to explore the practicality of using personalized feedback in educating families to make their homes smoke-free. Methods A total of 35 smokers in three states in Malaysia were recruited via snowball and convenience sampling methods. Indoor fine particulate (PM 2.5 ) concentrations in participants’ homes were measured for 7 days before and after educational intervention using a pre-defined template, which included personalized airquality feedback, and information on SHS impacts were given. The feedback was delivered over two 20-minute phone calls or in-person sessions following the completion of the air-quality measurements. Data were corrected for outdoor PM 2.5 concentrations from the nearest environmental monitor. Results Despite the challenges in conducting the project during COVID-19 pandemic, the delivery of the intervention was found to be feasible. Twenty-seven (77%) out of 35 participants completed PM 2.5 measurements and received a complete intervention. The median (IQR: 25th –75th percentile concentrations) SHS-PM 2.5 concentrations at baseline and follow-up were 18.3 μg/m 3 (IQR: 13.3–28.3) and 16.2 μg/m 3 (IQR: 10.4 – 25.6), respectively. There was a reduction of SHS-PM 2.5 concentrations at follow-up measurement in the houses of 17 participants (63%). The change in corrected indoor PM 2.5 concentrations between baseline and followup was not statistically significant (Z= -1.01, p=0.29). Conclusions This educational intervention, combining the use of a low-cost air particle counter with personalized air-quality feedback, was found to be feasible in the Malaysian setting. It has potential to trigger behavior change among smokers, reducing indoor smoking and consequent SHS concentrations, and increasing smoke-free home implementation. A large-scale trial is needed

Heavy metals in the air: analysis using Instrument, air pollution and human health - a review

Air pollution can harm human health, cause-effect to the environment and trigger factor to property damage. Various researches have proven the connection between air quality and human health. The previous research on epidemiology and laboratory studies demonstrated that ambient air pollutants (for example PM, O3, SO2 and NO2) contribute to various respiratory problems including bronchitis, emphysema and asthma. This present mini-review is to discuss the relationship between human health and air quality. This conceptual paper is focusing on the findings from air quality based on literature review and the significant health effects which related to it. Besides, the principle of analytical instrumentation is also being discussed in order to identify the best instrument in laboratory analysis