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The Manila Trench subduction zone is an active convergent plate margin between the South China Sea and northern Philippines. This strongly indicates a high probability for larger earthquakes that could potentially trigger a tsunami in the future and anticipated to affect neighboring countries such as Malaysia which has power plants near the coastal areas. The potential disastrous impact of tsunami waves on a power plant causes loss of lives, damage to assets, and loss of electricity for the coastal communities similar to year 2011 Tohoku tsunami in Japan. Therefore, application of shallow water equation (SWE) in tsunami modelling namely generation and propagation phase and nonlinear shallow water equation (NSWE) for run-up and inundation phase of a tsunami event are pertinent in simulating various scenarios of tsunami. Results from tsunami simulation is used as tsunami lateral load. Linear Static Analysis is then utilized to analyze stability of 275-kV transmission tower.

Nowadays, Malaysia is facing real problem on traffic issues such as traffic congestion, deficiency of land for parking space and increasing vehicle volume. Cycling is one of alternative approach of transportation to overcome traffic issues. This objective of this study is to forecast the travel demand using E-bike in University and comparison of carbon footprint reduces between E-bikes and motorize vehicle. UNITEN has launched a program called Electric Palled-Assisted Biked (EPAB) as topromotes the usage of E-Bikes as their main mode of transportation in UNITEN Putrajaya campus. All the travellingdata have been recording using Application Strava. The CO2 emission and fuel cost for those particular tripshave also addressed in these studies.The result found that 107.27 daily trips were generated by E-bikes in UNITEN Putrajaya campus. The study also found that 88 percent of CO2emission is reduced when substituting car with E-bikes. An astonishing 560.918kg of CO2 was prevented from releasing to the atmosphere. Cycling has been proven as one of alternative option in developed countries to reduce the vehicle volume on the road. Further studies on these topic is highly recommend by increasing the number of participant in future.

The massive destruction and loss caused by the 2004 Sumatra–Andaman tsunami were attributed to the lack of knowledge on tsunami and low regional detection and communication systems for early warning in that region. This study aimed to identify locations at risk of impending tsunami from Andaman Sea for the safety of community and proper development planning at the coastal areas by providing an updated and revised inundation maps. The last study on this area was conducted several years ago which open the possibility to new findings. Generated by tsunami simulation models, the maps illustrate the extent and level of inundation to which the coastal community and infrastructure would be subjected. As a result of coastal changes and availability of better topographic data, the existing inundation maps for the coastal areas of northwest Peninsular Malaysia at risk to impending tsunami from the Andaman Sea are revised. This paper documented the computational setup leading to the generation of the revised inundation maps. The tsunami simulation model TUNA was used to simulate the generation, propagation, and subsequent run-up and inundation of tsunamis triggered by earthquakes of moment magnitudes (Mw) 8.5, 9.0, and 9.25 along the Sunda Trench. From the simulations, it was found that at Mw 9.25, Balik Pulau, Pulau Pinang would be subjected to inundation of as far as 3.47 km with 5.40-m-deep inundation at the highest section.

This study assessed the physical and chemical parameters related to indoor air quality (IAQ) at Universiti Tenaga Nasional (UNITEN) and the IAQ of selected campus buildings were compared with guidelines provided by DOSH. This study is especially important as students spend most of their time indoors thus making them more vulnerable to exposure to indoor contaminants. Seven sampling locations around the UNITEN campus were selected which all have different layout. The method of data collection is based on Industry Code of Practice on Indoor Air Quality 2010 (ICOP). The indoor contaminants were recorded using real-time monitoring method and the parameters of interest are the Particulate Matter (PM2.5 and PM10), Total Volatile Organic Compound (TVOC), relative humidity and temperature. Results show that the parameters of IAQ level in UNITEN is at a safe level as it is well below the DOSH permissible limit. One-way ANOVA analysis was used to identify whether or not the mean of the IAQ parameters specifically PM2.5, PM10 and TVOC are the same and belongs to the same population. Statistical analysis also shows that there was no significant difference in IAQ level between all sampling locations (P≤0.05).

Urban areas are exposed to high traffic volume that can associate to the source of noise pollution. Noise pollution is ranked as the third most harmful environmental pollution after air and water. The objective of this study is to investigate the level of traffic noise pollution at the residential area of Puchong, Selangor. This study is carried out at two residential areas. The traffic volume and noise level data are collected at three different time intervals during weekday and weekend. A survey is conducted to investigate level awareness and health effect on surrounding affected communities. The result showed the traffic noise is ranging from 65 to 84 dB(A) during weekday and weekend. Based on the survey conducted, most of respondents aware that traffic is the highest contributor to noise pollution. The noise pollution condition is getting bad as compares to previous year.

Reliable forecasting of water level is essential for flood prevention, future planning and warning. This study proposed to forecast daily time series water level for Malaysia’s rivers based on deep learning technique namely long short-term memory (LSTM). The deep learning neural network is based on artificial neural network (ANN) and part of broader machine learning. In this study, forecasting models are developed for 1-h ahead of time at multiple lag time which are 1-h, 2-h and 3-h lag time denoted as LSTMt-1, LSTMt-2 and LSTMt-3, respectively. Forecasted water level is significant for determination of effected area, future planning and warning. Root mean square error (RMSE) and coefficient of determination (R2) are utilized to evaluate the performance of proposed forecasting models. An analysis of error in term of RMSE and R2 show that the proposed LSTMt-3 model outperformed other models for water level forecasting during training and testing phase.

Modern technology and life-style advancements have increased the demand for clean water. Based on this trend it is expected that our water resources will be under stress leading to a high probability of scarcity. This study aims to evaluate the environmental impacts of selected traditional food manufacturing products namely: tempe, lemang, noodle laksam, fish crackers and salted fish in Malaysia. The cradle-to-gate approach on water footprint assessment (WFA) of these selected traditional food products was carried out using Water Footprint Network (WFN) and Life Cycle Assessment (LCA). Freshwater eutrophication (FEP), marine eutrophication (MEP), freshwater ecotoxicity (FETP), marine ecotoxicity (METP) and water consumption (WCP), LCA were investigated using ReCiPe 2016 methodology. Water footprint accounting of blue water footprint (WFblue), green water footprint (WFgreen) and grey water footprint (WFgrey) were established in this study. It was found that total water footprint for lemang production was highest at 3862.13 m3/ton. The lowest total water footprint was found to be fish cracker production at 135.88 m3/ton. Blue water scarcity (WSblue) and water pollution level (WPL) of these selected food products were also determined to identify the environmental hotspots. Results in this study showed that the WSblue and WPL of these selected food products did not exceed 1%, which is considered sustainable. Based on midpoint approach adopted in this study, the characterization factors for FEP, MEP, FETP, METP and WCP on these selected food products were evaluated. It is recommended that alternative ingredients or product processes be designed in order to produce more sustainable lemang.

Coal-fired power is among the most significant electric generated in most developed countries. The environmental impact of coal-fired power plants is usually associated with air, water and waste pollution. Life cycle assessment (LCA) is a standard method used to evaluate the potential of environmental impacts of a product or process over its life cycle stages. This paper aims to review the application of LCA in evaluating the environmental impact of coal-fired power plant fields. The results were summarised in term of goal, scope, functional unit, system boundaries, impact assessment method and impact category.

Seaquake is a phenomenon where there are water disturbance at the sea, caused by earthquake or submarine eruption. The scope of this study focuses on tsunami simulation due to Manila Trench and Sulu Trench seaquake which is prone to harm Malaysia offshore areas. Manila Trench is a highly potential earthquake source that can generate tsunami in South China Sea. Meanwhile, Sulu Trench could be a threat to east of Sabah offshore areas. In this study, TUNA-M2 model was utilized to perform tsunami simulation at South China Sea and Sulu Sea. TUNA-M2 model applied Okada source model to create tsunami generation due to earthquake. It utilized linear shallow water equation during tsunami propagation with its radiant boundary condition. Five simulations performed at each study region. Forecast points at South China Sea areas were divided into three separate locations which are at the Peninsular Malaysia, west of Sabah and Sarawak offshore areas. Forecast points at Sulu Sea were focused at the east of Sabah offshore areas. This paper will present the simulation results of tsunami wave height and arrival time at various forecast points. The findings of this study show that the range of tsunami wave height at Sulu Sea is higher than that of South China Sea. The tsunami arrival time at Sulu Sea is less than South China Sea. It can be concluded that Sulu Sea poses worse tsunami threat than South China Sea to the Malaysian offshore areas.

This work details the simulation of tsunami waves generated by seaquakes in the Manila Trench and their effect on fixed oil and gas jacket platforms in waters offshore North Borneo. For this study, a four-leg living quarter jacket platform located in a water depth of 63m is modelled in SACS v5.3. Malaysia has traditionally been perceived to be safe from the hazards of earthquakes and tsunamis. Local design practices tend to neglect tsunami waves and include no such provisions. In 2004, a 9.3M w seaquake occurred off the northwest coast of Aceh, which generated tsunami waves that caused destruction in Malaysia totalling US$ 25 million and 68 deaths. This event prompted an awareness of the need to study the reliability of fixed offshore platforms scattered throughout Malaysian waters. In this paper, we present a review of research on the seismicity of the Manila Trench, which is perceived to be high risk for Southeast Asia. From the tsunami numerical model TUNA-M2, we extract computer-simulated tsunami waves at prescribed grid points in the vicinity of the platforms in the region. Using wave heights as input, we simulate the tsunami using SACS v5.3 structural analysis software of offshore platforms, which is widely accepted by the industry. We employ the nonlinear solitary wave theory in our tsunami loading calculations for the platforms, and formulate a platform-specific risk quantification system. We then perform an intensive structural sensitivity analysis and derive a corresponding platform-specific risk rating model.

Water treatment is the process to make the water reusable to consumers. There are several process to treat water such as chlorination, sedimentation and filtration. Water filtration is known to separate substance or object in contaminated water. Method of filtration is vary depending on the location of the targeted material whether it is dissolved in the suspended as a solid or fluid. This paper present a preliminary study to constructing a low-cost of water filter by using materials namely coarse aggregates, sand, activated carbon in additional of loofah and coconut fiber. The result was measured by analyzing the water parameter such as, Biochemical Oxygen Demand (BOD), Dissolve Oxygen (DO), turbidity, and colour. The result of raw water and filtered water are characterized according to the National Water Quality Standard (NWQS) for Malaysia. The final results from laboratory experiment showed a good improvement of water parameter during the application of coconut and loofah fiber in water filtration. The BOD5 result for coconut and loofah fiber model show significant improvement from class IV to class I and III.

Streamflow prediction has a significance influence on improving water supply management and flood prevention. The applications of artificial intelligence (AI) have been proved to have better performance as compared to conventional statistical method in streamflow prediction. Therefore, this study proposed on the development of streamflow prediction model AI techniques namely Bat algorithm (BA) and backpropagation neural network (BPNN). BA is an optimization technique, which is to optimize BPNN in deciding optimum parameters and then improve the prediction accuracy. The study area chosen is Kuantan river and Kenau river, located in Kuantan, Malaysia. Two prediction models are proposed in this study which are BPNN and hybrid Bat-BPNN. Monthly historical rainfall data, antecedent river flow data and meteorology parameters data for two different rivers were used as the input to the proposed models. The performance of the proposed prediction models for Kuantan river and Kenau river are then being compared and evaluated in term of RMSE and R2. It is found that hybrid model, Bat-BPNN yields lower RMSE and provides higher R2 as compared to BPNN model at both Kuantan river and Kenau river. Therefore, it can be concluded that, proposed hybrid model yields better performances as compared to BPNN model for monthly streamflow prediction.

This paper reviews the fault parameters used in the literatures of tsunami source simulations for the 26 December, 2004 Sumatra–Andaman tsunami, as well as understanding of the geology and geography of the Sunda Trench. Although the source of tsunami generation is exclusive, the parameters used in the simulations differ according to source of data, method of parameter derivation and modeling experiences. Hence, identification of possible future source generations and results for best fit parameters obtained from literature review are integrated to be used for future simulations. Based on the literature review conducted, it is clear that the parameters of tsunami source generation play a vital component and indication in amplifying effects in the coastal areas. Hence, earlier identification of possible fault rupture parameters in the Andaman Sea provides an information about the effects of the future risks of tsunami towards the west-coast of Malaysia.

This paper reviews methods applicable to assess the impact of tsunami forces on coastal structures. Countries affected by tsunamis have proven that this environmental disaster has costed billions of losses, such as the event occurred during year 2004 Andaman tsunami. Therefore, there is a need to assess the structural behaviour upon the impact of tsunami forces in order to minimize the damages and to ensure that coastal structures are able to sustain loading from high current-velocity waves. Currently in practice, there are two approaches of accessing the impacts of tsunami on structures namely physical modelling and experiment or numerical modelling and simulation. Numerical modelling methods are expected to produce acceptable analysis on the stability and condition of structures subjected to tsunami loadings since it incorporates several important parameters which are not implemented in physical modelling. The result from this study is expected to prompt engineers and relevant authorities to revise the current design guidelines on coastal structures which could sustain possible tsunami event in the future.

In recent years, studies regarding a new source of tsunami-genic earthquake at South China Sea region known as Manila Trench earthquake have attracted the attention of many researchers. It is expected that this subduction zone is capable to trigger large moment magnitude earthquake and affects countries located within South China Sea. The objective of this study is to project tsunami wave height and arrival time generated from Manila Trench earthquake towards coastal areas located along east-coast of Peninsular Malaysia. This study focuses on simulating tsunami at four different moment magnitudes by using TUNA-M2 model to record wave height and arrival time at the offshore areas. Then the Green’s law is used to approximate reliable tsunami wave height when approaching onshore. Results obtained in this study showed that tsunami waves from Manila Trench are estimated to arrive at coastal areas of east-coast Peninsular Malaysia between 9.1 to 10.25 hours post-earthquake occurrence. The observation points located at offshore of Kelantan are anticipated to experience the highest wave height as compared to other observation points located at offshore areas of Terengganu and Pahang. This study is important to the coastal communities as it provides vital information on possible tsunami occurrences in the future.

Accurate forecasting of streamflow is desired in many water resources planning and management, flood prevention and design development. In this study, the accuracy of two hybrid model, support vector machine - particle swarm optimization (SVM-PSO) and bat algorithm – backpropagation neural network (BA-BPNN) for monthly streamflow forecasting at Kuantan River located in Peninsular Malaysia are investigated and compared to regular SVM and BPNN model. Heuristic optimization namely PSO and BA are introduced to find the optimum SVM and BPNN parameters. The input parameters to the forecasting models are antecedent streamflow, historical rainfall and meteorological parameters namely evaporation, temperature, relative humidity and mean wind speed. Two performance evaluation measure, root mean square error (RMSE) and coefficient of determination (R2) were employed to evaluate the performance of developed forecasting model. It is found that, RMSE and R2 for hybrid SVM-PSO are 24.8267 m3/s and 0.9651 respectively while general SVM model yields RMSE of 27.5086 m3/s and 0.9305 of R2 for testing phase. Besides that, hybrid BA-BPNN produces RMSE, 17.7579 m3/s and R2, 0.7740 while BPNN model produces lower RMSE and R2 of 28.1396 m3/s and 0.5015 respectively. Therefore, the results indicate that hybrid model, SVM-PSO and Bat-BPNN yield better performance as compared to general SVM and BPNN, respectively in streamflow forecasting.

Manila Trench subduction zone is capable to produce high magnitude of earthquake event that can generate a deadliest tsunami disaster. The 2006 tsunami source workshop conducted by United States Geological Survey (USGS) had classified Manila Trench as the most hazardous potential earthquake generated tsunami source in South China Sea. The giant megathrust rupture from Manila Trench has the ability to create an earthquake as powerful as the Great Tohoku tsunami in 2011 and the Indian Ocean tsunami in 2004. This technical paper aims to review the fault parameters used by different researchers in investigating the possibility of tsunami occurrences generated from Manila Trench earthquake to the coastal areas of Terengganu, Malaysia which is located within the vicinity of South China Sea. The selected fault parameters were simulated by using TUNA model in order to study the potential effects of Manila Trench earthquake induced tsunami. The outcomes of the simulation are the wave height and wave arrival time. At the end of this technical paper, an intensive approach is implemented to select the most significant fault parameters that create the potential worst-case tsunami scenario towards Terengganu coastal areas in terms of the highest and fastest first wave arrived.

The application of artificial intelligence techniques for river flow forecasting can further improve the management of water resources and flood prevention. This study concerns the development of support vector machine (SVM) based model and its hybridization with particle swarm optimization (PSO) to forecast short term daily river flow at Upper Bertam Catchment located in Cameron Highland, Malaysia. Ten years duration of historical rainfall, antecedent river flow data and various meteorology parameters data from 2003 to 2012 are used in this study. Four SVM based models are proposed which are SVM1, SVM2, SVM-PSO1 and SVM-PSO2 to forecast 1 to 7 day ahead of river flow. SVM1 and SVM-PSO1 are the models with historical rainfall and antecedent river flow as its input, while SVM2 and SVM-PSO2 are the models with historical rainfall, antecedent river flow data and additional meteorological parameters as input. The performances of the proposed model are measured in term of RMSE and R2 . It is found that, SVM2 outperformed SVM1 and SVM-PSO2 outperformed SVM-PSO1 which meant the additional meteorology parameters used as input to the proposed models significantly affect the model performances. Hybrid models SVM-PSO1 and SVM-PSO2 yield higher performances as compared to SVM1 and SVM2. It is found that hybrid models are more effective in forecasting river flow at 1 to 7 day ahead at the study area.

Sumatra-Andaman tsunami was categorized as the third worst tsunami by the United State Geology Survey (USGS). The tsunami was triggered at 00:58:53 UTC by a massive earthquake with recorded moment magnitude of 9.1 at the west coast of North Sumatera. Malaysia is one of the countries affected by the 26th December 2004 tsunami. Others countries also affected by this event include Indonesia, Sri Lanka, Thailand, India, Maldives, Myanmar, Bangladesh, Somalia, Tanzania, Kenya and Yemen. The earthquake epicenter is located where the Indian Plate subducted under the Burma Plate. This tsunami event has raised the awareness of many people. Today, several tsunami numerical models have been developed to model and forecast tsunami events in the future. This paper reviews five tsunami numerical models namely TUNA, TUNAMI, COMCOT, MOST and ANN Tsunami Forecast. Most of these models have been used by other researchers to perform tsunami simulation based on Sumatera-Andaman tsunami event. Each model have their own similarities, differences and limitations. A non-mathematically intensive approach is employed to choose a suitable tsunami numerical model for the case study in Malaysian offshore areas. Future studies will be conducted using one of the tsunami numerical models.

Manila Trench is a potential generation source of tsunami in the South China Sea. Manila Trench is formed when Eurasian Plate is subducted under the Philippine Sea Plate. It has been classified as the most hazardous tsunami sources in USGS Tsunami Sources Workshop, 2006. The location of the trench begins at the north of Palawan, Philippines, continuing to the north along the west of Luzon, Philippine, and ends at Taiwan. The potential tsunami generated from Manila Trench affects Philippines and countries located in the vicinity of South China Sea including Malaysia. This chapter focuses on simulation of tsunami generation and tsunami wave propagation due to seismic activity in the Manila Trench. TUNA-M2 model is used to produce simulation results in terms of tsunami wave height and time of arrival of the first wave. The study area is Malaysian offshore reserves and operation where oil and gas platforms are located. There are three simulations performed at different moment magnitudes (M w: 7.0, 7.5, and 8.0). The result shows the range of wave heights at the Malay basin to be between 0.002 and 0.122 m, the range of wave heights at Sabah basin to be between 0.004 and 0.168 m, and the range of wave heights at Sarawak basin to be between 0.004 and 0.230 m. These results are useful in the future design of offshore platform structure and operation