Oil palm (Elaeis guineensis) agriculture is rapidly expanding and requires large areas of land in the tropics to meet the global demand for palm oil products. Land cover conversion of peat swamp forest to oil palm (large- and small-scale oil palm production) is likely to have negative impacts on microhabitat conditions. This study assessed the impact of peat swamp forest conversion to oil palm plantation on microclimate conditions and soil characteristics. The measurement of microclimate (air temperature, wind speed, light intensity and relative humidity) and soil characteristics (soil surface temperature, soil pH, soil moisture, and ground cover vegetation temperature) were compared at a peat swamp forest, smallholdings and a large-scale plantation. Results showed that the peat swamp forest was 1.5-2.3 °C cooler with significantly greater relative humidity, lower light intensities and wind speed compared to the smallholdings and large-scale plantations. Soil characteristics were also significantly different between the peat swamp forest and both types of oil palm plantations with lower soil pH, soil and ground cover vegetation surface temperatures and greater soil moisture in the peat swamp forest. These results suggest that peat swamp forests have greater ecosystem benefits compared to oil palm plantations with smallholdings agricultural approach as a promising management practice to improve microhabitat conditions. Our findings also justify the conservation of remaining peat swamp forest as it provides a refuge from harsh microclimatic conditions that characterize large plantations and smallholdings.
Solar energy is a major type of renewable energy, and its estimation is important for decision-makers. This study introduces a new prediction model for solar radiation based on support vector regression (SVR) and the improved particle swarm optimization (IPSO) algorithm. The new version of algorithm attempts to enhance the global search ability for the PSO. In practice, the SVR method has a few parameters that should be determined through a trial-and-error procedure while developing the prediction model. This procedure usually leads to non-optimal choices for these parameters and, hence, poor prediction accuracy. Therefore, there is a need to integrate the SVR model with an optimization algorithm to achieve optimal choices for these parameters. Thus, the IPSO algorithm, as an optimizer is integrated with SVR to obtain optimal values for the SVR parameters. To examine the proposed model, two solar radiation stations, Adana, Antakya and Konya, in Turkey, are considered for this study. In addition, different models have been tested for this prediction, namely, the M5 tree model (M5T), genetic programming (GP), SVR integrated with four different optimization algorithms SVR-PSO, SVR-IPSO, Genetic Algorithm (SVR-GA), FireFly Algorithm (SVR-FFA) and the multivariate adaptive regression (MARS) model. The sensitivity analysis is performed to achieve the highest accuracy level of the prediction by choosing different input parameters. Several performance measuring indices have been considered to examine the efficiency of all the prediction methods. The results show that SVR-IPSO outperformed M5T and MARS.
Riparian areas hold vast number of flora and fauna with exceptional contributions to the ecosystem. A study was conducted in Sungai Sepetang, Sungai Rembau and Sungai Chukai to identify the insect community in a riparian zone of Peninsular Malaysia. Sampling was conducted in six consecutive months from December 2017 to May 2018 during both day and night using sweep nets. Twenty sampling stations (S1-S20) had been assembled along the riverbanks with an average distance of 200 m between each station. The 17,530 collected insects were from 11 orders and consisted of Diptera, Coleoptera, Hemiptera, Hymenoptera, Lepidoptera, Neuroptera, Orthoptera, Blattodea, Thysanoptera, Mantodea and Odonata. The three most abundant orders were Diptera (33.84%; 5933 individuals), Coleoptera (28.82%; 5053 individuals) and Hemiptera (25.62%: 4491 individuals). The collected insect community consisted of different guilds such as the scavenger, predator, herbivore, pollinator and parasitoid. Sungai Sepetang and Sungai Rembau were dominated by mangrove flora, Sonneratia caseolaris (Myrtales: Lythraceae), while Sungai Chukai was dominated by Barringtonia racemosa. There was a significant difference (p < 0.05) in the composition of insects between the three rivers though clustering analysis showed that the insect communities in Sungai Sepetang and Sungai Rembau were 100% similar compared to Sungai Chukai which consisted of a totally different community. There is a significant negative correlation between abundance of insects with salinity and wind speed at Sungai Chukai and Sungai Sepetang.
Katabatic winds dramatically affect the polar climate. Their activity depends on density of air and temperature in the source region. This paper presents for first time an analysis of the precipitable water vapour (PWV) variability and its relation to a katabatic event at Scott Base station, Antarctica. A significant effect in their characteristics toward calculation of a reliable user accuracy in GPS applications is addressed. Our investigations using the data between 21st and 30th of November 2002 showed that the PWV profile exhibited an irregular pattern with a maximum value of 7.38 mm (~ 6 mm on average), and was more strongly influenced by relative humidity than by wind speed activity. The dominant wind flow during this period was from the North-Northeast (blowing from the Ross Sea) with a median speed of 4.96 ms–1. The PWV was high when the temperature was between –15ºC and –11ºC. During the dates identified as a katabatic event between 21:30 UT of 28th November and 18:40 UT on 29th November, the wind blew from the Southeast-South direction (from the Ross Ice Shelf) with a maximum speed of 10.92 ms–1. The PWV increased ~1.4 mm (23%) from the mean value, indicating severe wind during this event which had pronounced effect on GPS observations.
An air fin cooler system consists of a tube bundle that is used to cool the various processing fluids in process industries that utilizes air as a cooling medium. The said tubes failed when exposed to corrosive environment(s). Tubes located at the bottom row of the air fin cooler were corroded as a result of exposure to rain water, brought in by induced air when the wind blows. The tube material is A179 Carbon steel. Two tubes, namely Tube A and Tube B along with an aluminum fin in each tube were investigated. A leak was observed on tube A, probably due to Corrosion Under Deposit mechanism. A general corrosion attack was observed at tube B, and macroscopic analysis showed that the corrosion occurred along the grain boundaries, which consist of ferrite and pearlite. Microanalysis showed that the corrosion product on the outer surface of the tube consists of Fe, O, S and Cl elements. It is concluded that the humid environment contains corrosive elements such as S and Cl. EDAX analysis on the fin showed that the material is pure aluminum. However, the aluminum was corroded by galvanized corrosion and produced brittle Al2O3 as a result.
This paper introduces a method for modification of the formula of the fractal box counting dimension. The method is based on the utilization of the probability distribution formula in the fractal box count. The purpose of this method is to use it for the discrimination of oil spill areas from the surrounding features e.g. sea surface and look-alikes in RADARSAT-1 SAR data. The result showed that the new formula of the fractal box counting dimension was able to discriminate between oil spills and look-alike areas. The low wind area had the highest fractal dimension peak of 2.9, as compared to the oil slick and the surrounding rough sea. The maximum error standard deviation of the low wind area was 0.68 which performed with a 2.9 fractal dimension value.
In this paper, four types of circular probability distribution were used to evaluate which circular probability distribution gives the best fitting for southwesterly Malaysian wind direction data, namely circular uniform distribution, von Mises distribution, wrapped-normal distribution and wrapped-Cauchy distribution. The four locations chosen were Alor Setar, Langkawi, Melaka and Senai. Two performance indicators or goodness of fit tests which are mean circular distance and chord length were used to test which distribution give the best fitting.
Difficulties in controlling the effects of outdoor thermal environment on the human body are attracting considerable research attention. This study investigated the outdoor thermal comfort of urban pedestrians by assessing their perceptions of the tropical, micrometeorological, and physical conditions via a questionnaire survey. Evaluation of the outdoor thermal comfort involved pedestrians performing various physical activities (sitting, walking, and standing) in outdoor and semi-outdoor spaces where the data collection of air temperature, globe temperature, relative humidity, wind speed, solar radiation, metabolic activity, and clothing insulation data was done simultaneously. A total of 1011 participants were interviewed, and the micrometeorological data were recorded under outdoor and semi-outdoor conditions at two Malaysian university campuses. The neutral temperatures obtained which were 28.1 °C and 30.8 °C were within the biothermal acceptable ranges of 24-34 °C and 26-33 °C of the PET thermal sensation ranges for the outdoor and semi-outdoor conditions, respectively. Additionally, the participants' thermal sensation and preference votes were highly correlated with the PET and strongly related to air and mean radiant temperatures. The findings demonstrated the influence of individuals' thermal adaptation on the outdoor thermal comfort levels. This knowledge could be useful in the planning and designing of outdoor environments in hot and humid regions to create better thermal environments.
The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system's modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.
Water scarcity is a global concern, as the demand for water is increasing tremendously and poor management of water resources will accelerates dramatically the depletion of available water. The precise prediction of evapotranspiration (ET), that consumes almost 100% of the supplied irrigation water, is one of the goals that should be adopted in order to avoid more squandering of water especially in arid and semiarid regions. The capabilities of feedforward backpropagation neural networks (FFBP) in predicting reference evapotranspiration (ET0) are evaluated in this paper in comparison with the empirical FAO Penman-Monteith (P-M) equation, later a model of FFBP+Genetic Algorithm (GA) is implemented for the same evaluation purpose. The study location is the main station in Iraq, namely Baghdad Station. Records of weather variables from the related meteorological station, including monthly mean records of maximum air temperature (Tmax), minimum air temperature (Tmin), sunshine hours (Rn), relative humidity (Rh) and wind speed (U2), from the related meteorological station are used in the prediction of ET0 values. The performance of both simulation models were evaluated using statistical coefficients such as the root of mean squared error (RMSE), mean absolute error (MAE) and coefficient of determination (R2). The results of both models are promising, however the hybrid model shows higher efficiency in predicting ET0 and could be recommended for modeling of ET0 in arid and semiarid regions.
The aerodynamic characteristics of the wing-in-ground effect (WIG) craft model that has a noble configuration of a compound wing was experimentally investigated and Universiti Teknologi Malaysia (UTM) wind tunnel with and without endplates. Lift and drag forces, pitching moment coefficients, and the centre of pressure were measured with respect to the ground clearance and the wing angle of attack. The ground effect and the existence of the endplates increase the wing lift-to-drag ratio at low ground clearance. The results of this research work show new proposed design of the WIG craft with compound wing and endplates, which can clearly increase the aerodynamic efficiency without compromising the longitudinal stability. The use of WIG craft is representing an ambitious technology that will help in reducing time, effort, and money of the conventional marine transportation in the future.
Energy security and environmental measurements are incomplete without renewable energy; therefore, there is a dire need to explore new energy sources. Hence, this study aimed to measure the wind power potential to generate renewable hydrogen (H2), including its production and supply cost. This study used first-order engineering model and net present value to measure the levelized cost of wind-generated renewable hydrogen by using the data source of the Pakistan Meteorological Department and State Bank of Pakistan. Results showed that the use of surplus wind and renewable hydrogen energy for green economic production is suggested as an innovative project option for large-scale hydrogen use. The key annual running expenses for hydrogen are electricity and storage costs, which have a significant impact on the costs of renewable hydrogen. The results also indicated that the project can potentially cut carbon dioxide (CO2) pollution by 139 million metric tons and raise revenue for wind power plants by US$2998.52 million. The renewable electrolyzer plants avoided CO2 at a rate of US$24.9-36.9/ton under baseload service, relative to US$44.3/ton for the benchmark. However, in the more practical mid-load situation, these plants have significant benefits. Further, the wind-generated renewable hydrogen delivers 6-11% larger annual rate of return than the standard CO2 catch plant due to their capacity to remain running and supply hydrogen to the consumer through periods of plentiful wind and heat. Also, the measured levelized output cost of hydrogen (LCOH) was US$6.22/kgH2, and for the PEC system, it was US$8.43/kgH2. Finally, it is a mutually agreed consensus among environmental scientists that the integration of renewable energy is the way forward to increase energy security and environmental performance by ensuring uninterrupted clean and green energy. This application has the potential to address Pakistan's urgent issues of large-scale surplus wind- and solar-generated energy, as well as rising energy demand.
An exophilic population of the vector mosquito Anopheles balabacensis Baisas was investigated in two mark-recapture studies (16.ix-13.x.1986 and 6-26.i.1987) at an inland, foothill village in Sabah, Malaysia. Wild female mosquitoes were intercepted as they came to feed on man or buffalo, given a bloodmeal, marked with fluorescent dust and released. The recapture rate was about 12%. A new method of analysis is proposed which uses cross-correlation and a time series model. The estimated survival per oviposition cycle was 0.48-0.54 and the oviposition cycle interval 2-3 days.
Estimation and forecast of groundwater recharge and capacity of aquifer are essential issues in water resources investigation. In the current research, groundwater recharge, recharge coefficient and effective rainfall were determined through a case study using empirical methods applicable to the tropical zones. The related climatological data between January 2000 and December 2010 were collected in Selangor, Malaysia. The results showed that groundwater recharge was326.39 mm per year, effective precipitation was 1807.97 mm per year and recharge coefficient was 18% for the study area. In summary, the precipitation converted to recharge, surface runoff and evapotranspiration are 12, 32 and 56% of rainfall, respectively. Correlation between climatic parameters and groundwater recharge showed positive and negative relationships. The highest correlation was found between precipitation and recharge. Linear multiple regressions between
recharge and measured climatologic data proved significant relationship between recharge and rainfall and wind speed. It was also proven that the proposed model provided an accurate estimation for similar projects.
The data consists of actual generation-side auditing including the distribution of loads, seasonal load profiles, and types of loads as well as an analysis of local development planning of a resort island in the South China Sea. The data has been used to propose an optimal combination of hybrid renewable energy systems that able to mitigate the diesel fuel dependency on the island. The resort island selected is Tioman, as it represents the typical energy requirements of many resort islands in the South China Sea. The data presented are related to the research article "Optimal Combination of Solar, Wind, Micro-Hydro and Diesel Systems based on Actual Seasonal Load Profiles for a Resort Island in the South China Sea" [1].
The Southeast Asian (SEA) region is no stranger to forest fires - the region has been suffering from severe air pollution (known locally as 'haze') as a result of these fires, for decades. The fires in SEA region are caused by a combination of natural (the El Niño weather pattern) and manmade (slash-and-burn and land clearing for plantations) factors. These fires cause the emissions of toxic aerosols and pollutants that can affect millions of people in the region. Thus, this study aims to identify the impact of the SEA haze on the Southern region of the Malaysian Peninsula and Borneo region of East Malaysia using the entire air quality observation data at surface level in 2015. Overall, the concentration of PM10 was about two-fold higher during the haze period compared to non-haze period. The concentrations of CO, flux of CO and flux of BC were aligned with PM10 during the entire observation period. The wind field and cluster of trajectory indicated that the Southern Malaysian Peninsula and Borneo were influenced mainly from the wildfires and the combustion of peat soil in the Indonesian Borneo. This study finds that wildfires from Borneo impacted the Southern Malaysian Borneo more seriously than that from Sumatra region.
The presence of microplastics (MPs) in the atmosphere is a global concern because of its environmental and health impacts; however, the monsoonal transport of atmospheric MPs has not yet been investigated. To fully understand the effect of the monsoon on atmospheric MP transport, we conducted a study along the southeast coast of China during the East Asian summer monsoon (EASM). We found that the EASM transports atmospheric MPs back onto the continent at a flux of up to 212.977-213.433 kg/EASM/year. The backward trajectory and wind field results indicate that the EASM provides an effective MP transport pathway from Vietnam, the Philippines, and Malaysia to southeastern China. This suggests that only some of the airborne MPs over the ocean enter the marine ecosystem. The average abundance of atmospheric MPs over the sampling area was 0.39 items/100 m3 (0.39 ± 0.43 items/100 m3) during the EASM season, with high variability among the sampling sites. This study improves our understanding of the impact of the EASM on atmospheric MP transport, which can help quantify the contributions of atmospheric MPs to marine or terrestrial ecosystems.
In this study, we proposed integrated tools to evaluate the wind power potential, economic viability, and prioritize 15 proposed sites for the installation of wind farms. Initially, we used modified Weibull distribution model coupled with power law to assess the wind power potential. Secondly, we employed value cost method to estimate per unit cost ($/kWh) of proposed sites. Lastly, we used Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (F-TOPSIS) to rank the best alternatives. The results indicate that Pakistan has enormous wind power potential that cost varies from 0.06 $/kWh to 0.58 $/kWh; thus, sites S12, S13, S14, and S15 are considered as the most economic viable locations for the installation of wind power project, while remaining sites are considered to be less important, due to other complexities. The further analysis using Fuzzy-TOPSIS method reveals that site S13 is the most optimal location followed by S12, S14, and S14 for the development of wind power project. We proposed that government should formulate wind power policy for the implementation of wind power projects in order to meet energy demand of the country.
A three-dimensional Regional Ocean Modeling System is used to study the seasonal water circulations and transports of the Southern South China Sea. The simulated seasonal water circulations and estimated transports show consistency with observations, e.g., satellite altimeter data set and re-analysis data of the Simple Ocean Data Assimilation. It is found that the seasonal water circulations are mainly driven by the monsoonal wind stress and influenced by the water outflow/inflow and associated currents of the entire South China Sea. The intrusion of the strong current along the East Coast of Peninsular Malaysia and the eddies at different depths in all seasons are due to the conservation of the potential vorticity as the depth increases. Results show that the water circulation patterns in the northern part of the East Coast of Peninsular Malaysia are generally dominated by the geostrophic currents while those in the southern areas are due solely to the wind stress because of negligible Coriolis force there. This study clearly shows that individual surface freshwater flux (evaporation minus precipitation) controls the sea salinity balance in the Southern South China Sea thermohaline circulations. Analysis of climatological data from a high resolution Regional Ocean Modeling System reveals that the complex bathymetry is important not only for water exchange through the Southern South China Sea but also in regulating various transports across the main passages in the Southern South China Sea, namely the Sunda Shelf and the Strait of Malacca. Apart from the above, in comparision with the dynamics of the Sunda Shelf, the Strait of Malacca reflects an equally significant role in the annual transports into the Andaman Sea.
ir 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 significant 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