A comprehensive study of the chemical composition of rainwater was carried out from October 2016 to September 2017 in the equatorial tropical rainforest region of northwestern Borneo. Monthly cumulative rainwater samples were collected from different locations in the Limbang River Basin (LRB) and were later categorized into seasonal samples representing northeast monsoon (NEM), southwest monsoon (SWM), and inter-monsoon (IM) periods. Physical parameters (pH, EC, TDS, DO, and turbidity), major ions (HCO3-, Cl-, Ca2+, Mg2+, Na+, and K+) and trace metals (Co, Ni, Cd, Fe, Mn, Pb, Zn, and Cu) were analyzed from collected rainwater samples. Rainwater is slightly alkaline with mean pH higher than 5.8. Chloride and bicarbonate are the most abundant ions, and the concentration of major ions in seasonal rainwater has shown slight variation which follows a descending order of HCO3-> Cl-> Na+ > Ca2+ > Mg2+ > K+ in NEM and Cl- > HCO3- > Na+ > Ca2+ > K+ > Mg2+ in SWM and Cl- > HCO3- > Na+ > Ca2+ > Mg2+ > K+ in IM period. Trace metals such as Fe and Ni have shown dominance in seasonal rainwater samples, and all the metals have shown variation in concentration in different seasons. Variation in chemical characteristic of seasonal rainwater samples identified through piper diagram indicates dominance of Ca2+-Mg2+-HCO3- and mixed Ca2+-Mg2+-Cl- facies during NEM, SWM, and IM periods. Statistical analysis of the results through two-way ANOVA and Pearson's correlation also indicates significant variation in physico-chemical characteristics. This suggests a variation in contributing sources during the monsoon seasons. Factor analysis confirmed the source variation by explaining the total variance of 79.80%, 90.72%, and 90.52% with three factor components in NEM, SWM, and IM rainwater samples with different loading of parameters. Enrichment factor analysis revealed a combined contribution of marine and crustal sources except K+ which was solely from crustal sources. Sample analysis of backward air mass trajectory supports all these findings by explaining seasonal variation in the source of pollutants reaching the study area. Overall, the results show that the chemical composition of seasonal rainwater samples in LRB was significantly influenced by natural as well as anthropogenic processes. These include (long-range and local) industrial activities, fossil fuel combustion, forest burning, transportation activities including road transport and shipping activities, and land-derived soil dust along with chemical constituents carried by seasonal wind.
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.
Malaysian Borneo has a lower population density and is an area known for its lush rainforests. However, changes in pollutant profiles are expected due to increasing urbanisation and commercial-industrial activities. This study aims to determine the variation of surface O3concentration recorded at seven selected stations in Malaysian Borneo. Hourly surface O3data covering the period 2002 to 2013, obtained from the Malaysian Department of Environment (DOE), were analysed using statistical methods. The results show that the concentrations of O3recorded in Malaysian Borneo during the study period were below the maximum Malaysian Air Quality Standard of 100ppbv. The hourly average and maximum O3concentrations of 31 and 92ppbv reported at Bintulu (S3) respectively were the highest among the O3concentrations recorded at the sampling stations. Further investigation on O3precursors show that sampling sites located near to local petrochemical industrial activities, such as Bintulu (S3) and Miri (S4), have higher NO2/NO ratios (between 3.21 and 5.67) compared to other stations. The normalised O3values recorded at all stations were higher during the weekend compared to weekdays (unlike its precursors) which suggests the influence of O3titration by NO during weekdays. The results also show that there are distinct seasonal variations in O3across Borneo. High surface O3concentrations were usually observed between August and September at all stations with the exception of station S7 on the east coast. Majority of the stations (except S1 and S6) have recorded increasing averaged maximum concentrations of surface O3over the analysed years. Increasing trends of NO2and decreasing trends of NO influence the yearly averaged maximum of O3especially at S3. This study also shows that variations of meteorological factors such as wind speed and direction, humidity and temperature influence the concentration of surface O3.
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.
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.
Principal component analysis (PCA) and correlation have been used to study the variability of particle mass and particle number concentrations (PNC) in a tropical semi-urban environment. PNC and mass concentration (diameter in the range of 0.25->32.0 μm) have been measured from 1 February to 26 February 2013 using an in situ Grimm aerosol sampler. We found that the 24-h average total suspended particulates (TSP), particulate matter ≤10 μm (PM10), particulate matter ≤2.5 μm (PM2.5) and particulate matter ≤1 μm (PM1) were 14.37 ± 4.43, 14.11 ± 4.39, 12.53 ± 4.13 and 10.53 ± 3.98 μg m(-3), respectively. PNC in the accumulation mode (<500 nm) was the most abundant (at about 99 %). Five principal components (PCs) resulted from the PCA analysis where PC1 (43.8 % variance) predominates with PNC in the fine and sub-microme tre range. PC2, PC3, PC4 and PC5 explain 16.5, 12.4, 6.0 and 5.6 % of the variance to address the coarse, coarser, accumulation and giant fraction of PNC, respectively. Our particle distribution results show good agreement with the moderate resolution imaging spectroradiometer (MODIS) distribution.
This study analyzes two wind-induced upwelling mechanisms, namely, Ekman transport and Ekman pumping that occur during the southwest monsoon. The results suggest that the coastline of the east coast of Peninsular Malaysia (ECPM) is affected by upwelling with spatiotemporal variations. Characterization of upwelling by using wind-induced upwelling indexes (UIW) indicate the existence of favorable upwelling conditions from May to September. Upwelling intensity increased in May and peaked in August before declining in September, decreasing intensity from the southern tip towards the northern tip along the coastline of the ECPM. The existence of upwelling along the ECPM has resulted in an important difference between the SSTs of the inshore and the oceanic regions. Nonetheless, the use of the SST gradient between the inshore and the oceanic SSTs to characterize upwelling (UISST) was found to be unsuitable because the SST along the ECPM was affected by water advection from the Java Sea and incessant changes in the SST. In order to indicate the major contributor of wind-induced upwelling along the ECPM in terms of the spatiotemporal scale, a comparison between Ekman transport and Ekman pumping was drawn by integrating Ekman pumping with respect to the distance where the positive wind stress curl existed. The estimation of Ekman transport and Ekman pumping indicated that Ekman pumping played a major role in contributing towards upwelling in any particular month during the southwest monsoon along the entire coastline of the ECPM as compared to Ekman transport, which contributed towards more than half of the total upwelling transport. By dividing the ECPM into three coastal sections, we observed that Ekman pumping was relatively predominant in the middle and northern coasts, whereas both Ekman transport and Ekman pumping were equally prevalent in the southern coast.
Annual air temperature data obtained from twenty-two meteorological stations across Malaysia are modeled using multiple regression. A correlation test was conducted to find statistical relationship between each of the dependent variables: annual maximum and annual average air temperature and predictor variables: longitude, latitude, elevation and wind speed. Regression models using least square estimation method were developed relating the dependent variables to independent variables and the adequacy of the models is determined by the coefficient of determination. The result shows that the longitude and wind speed factors have a significant influence on the annual air temperature in Malaysia.
The vector autoregressive (VAR) approach is useful in many situations involving model development for multivariables
time series. VAR model was utilised in this study and applied in modelling and forecasting four meteorological variables.
The variables are n rainfall data, humidity, wind speed and temperature. However, the model failed to address the
heteroscedasticity problem found in the variables, as such, multivariate GARCH, namely, dynamic conditional correlation
(DCC) was incorporated in the VAR model to confiscate the problem of heteroscedasticity. The results showed that the use
of the VAR coupled with the recognition of time-varying variances DCC produced good forecasts over long forecasting
horizons as compared with VAR model alone.
This paper focuses on detecting outliers in the circular data which follow the wrapped normal distribution. We considered four discordance tests based on M, C, D and A statistics. The cut-off points of the four tests were obtained and the performance of the detection procedures was studied via simulations. In general, we showed that the discordance test based on the A statistic outperforms the other tests in all cases. For illustration, the city of Kuantan wind direction data set was considered.
A depth-averaged numerical model was developed to study tidal circulation and suspended sediment transport in the gulf of Khambhat along the west coast of India. The spatial resolution of the model is 750m x 750m. A 2-D fine resolution (150 m x 150 m) model for the lower part of the Narmada estuary is coupled with the coarser gulf model to simulate the flow features in the lower estuary. The model dynamics and basic formulation remain the same for both the gulf model and the estuary model. The models are barotropic, based on the shallow water equations and neglect horizontal diffusion and wind stress terms in the momentum equations. The models are fully non-linear and use a semi-explicit finite difference scheme to solve mass, momentum, and advection- diffusion equation for suspended sediments in a horizontal plane. The erosion and deposition have been computed by an empirically developed source and sink term in the suspended sediment equation. The tide in the gulf is mainly represented in the model by the semi-diurnal M2 constituent. Meanwhile, fresh water discharge from the rivers joining the gulf had also been considered. Numerical experiments were carried out to study the circulation and suspended sediment concentrations in the gulf and estuarine region.
The large use of renewable sources and plug-in electric vehicles (PEVs) would play a critical part in achieving a low-carbon energy source and reducing greenhouse gas emissions, which are the primary cause of global warming. On the other hand, predicting the instability and intermittent nature of wind and solar power output poses significant challenges. To reduce the unpredictable and random nature of renewable microgrids (MGs) and additional unreliable energy sources, a battery energy storage system (BESS) is connected to an MG system. The uncoordinated charging of PEVs offers further hurdles to the unit commitment (UC) required in contemporary MG management. The UC problem is an exceptionally difficult optimization problem due to the mixed-integer structure, large scale, and nonlinearity. It is further complicated by the multiple uncertainties associated with renewable sources, PEV charging and discharging, and electricity market pricing, in addition to the BESS degradation factor. Therefore, in this study, a new variant of mixed-integer particle swarm optimizer is introduced as a reliable optimization framework to handle the UC problem. This study considers six various case studies of UC problems, including uncertainties and battery degradation to validate the reliability and robustness of the proposed algorithm. Out of which, two case studies defined as a multiobjective problem, and it has been transformed into a single-objective model using different weight factors. The simulation findings demonstrate that the proposed approach and improved methodology for the UC problem are effective than its peers. Based on the average results, the economic consequences of numerous scenarios are thoroughly examined and contrasted, and some significant conclusions are presented.
Over the last decades, the development of the Klang Valley (Malaysia), as an urban commercial and industrial area, has elevated the risk of atmospheric pollutions. There are several significant sources of air pollutants which vary depending on the background of the location they originate from. The aim of this study is to determine the trend and status of air quality and their correlation with the meteorological factors at different air quality monitoring stations in the Klang Valley. The data of five major air pollutants (PM(10), CO, SO(2), O(3), NO(2)) were recorded at the Alam Sekitar Sdn Bhd (ASMA) monitoring stations in the Klang Valley, namely Petaling Jaya (S1), Shah Alam (S2) and Gombak (S3). The data from these three stations were compared with the data recorded at Jerantut, Pahang (B), a background station established by the Malaysian Department of Environment. Results show that the concentrations of CO, NO(2) and SO(2) are higher at Petaling Jaya (S1) which is due to influence of heavy traffic. The concentrations of PM(10) and O(3,) however, are predominantly related to regional tropical factors, such as the influence of biomass burning and of ultra violet radiation from sunlight. They can, though, also be influenced by local sources. There are relatively stronger inter-pollutant correlations at the stations of Gombak and Shah Alam, and the results also suggest that heavy traffic flow induces high concentrations of PM(10), CO, NO(2) and SO(2) at the three sampling stations. Additionally, meteorological factors, particularly the ambient temperature and wind speed, may influence the concentration of PM(10) in the atmosphere.
Subsea cable laying process is a difficult task for an engineer due to many
uncertain situations which occur during the operation. It is very often that the cable being
laid out is not perfectly fit on the route being planned, which results in the formation of
slack. In order to control wastages during installation, the slack needs to be minimized
and the movement of a ship/vessel needs to be synchronized with the cable being laid out.
The current problem was addressed using a mathematical model by considering a number
of defining parameters such as the external forces, the cable properties and geometry. Due
to the complexity, the model is developed for a steady-state problem assuming velocity
of the vessel is constant, seabed is flat and the effect of wind and wave is insignificant.
Non-dimensional system is used to scale the engineering parameters and grouped them
into only two main parameters which are the hydrodynamic drag of the fluid and the
bending stiffness of the cable. There are two solutions generated in this article; numerical
and asymptotic solutions. The result of these solutions suggests that the percentage of
slack can be reduced by the increase of the prescribed cable tension, and also the increase
in either the drag coefficient of the sea water or the bending stiffness of the cable, similarly
will result in lower slack percentage
It has come to attention that Malaysia have been aiming to build its own
nuclear power plant (NPP) for electricity generation in 2030 to diversify the national
energy supply and resources. As part of the regulation to build a NPP, environmental
risk assessment analysis which includes the atmospheric dispersion assessment has to
be performed as required by the Malaysian Atomic Energy Licensing Board (AELB)
prior to the commissioning process. The assessment is to investigate the dispersion of
radioactive effluent from the NPP in the event of nuclear accident. This article will focus
on current development of locally developed atmospheric dispersion modeling code
based on Gaussian Plume model. The code is written in Fortran computer language
and has been benchmarked to a readily available HotSpot software. The radionuclide
release rate entering the Gaussian equation is approximated to the value found in the
Fukushima NPP accident in 2011. Meteorological data of Mersing District, Johor of
year 2013 is utilized for the calculations. The results show that the dispersion of radionuclide
effluent can potentially affect areas around Johor Bahru district, Singapore
and some parts of Riau when the wind direction blows from the North-northeast direction.
The results from our code was found to be in good agreement with the one
obtained from HotSpot, with less than 1% discrepancy between the two.
Biomass burning is one of the main sources of air pollution in South East Asia, predominantly during the dry period between June and October each year. Sumatra and Kalimantan, Indonesia, have been identified as the regions connected to biomass burning due to their involvement in agricultural activities. In Sumatra, the Province of Riau has always been found to have had the highest number of hotspots during haze episodes. This study aims to determine the concentration of five major pollutants (PM10, SO2, NO2, CO and O3) in Riau, Indonesia, for 2006 and 2007. It will also correlate the level of air pollutants to the number of hotspots recorded, using the hotspot information system introduced by the Malaysian Centre for Remote Sensing (MACRES). Overall, the concentration of air pollutants recorded was found to increase with the number of hotspots. Nevertheless, only the concentration of PM10 during a haze episode is significantly different when compared to its concentration in non-haze conditions. In fact, in August 2006, when the highest number of hotspots was recorded the concentration of PM10 was found to increase by more than 20% from its normal concentration. The dispersion pattern, as simulated by the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT), showed that the distribution of PM10 was greatly influenced by the wind direction. Furthermore, the particles had the capacity to reach the Peninsular Malaysia within 42 hours of emission from the point sources as a consequence of the South West monsoon.
Singapore, an equatorial island in South East Asia, is influenced by a bi-annual reversal of wind directions which defines two monsoon seasons. We characterized the dynamics of the microbial communities of Singapore coastal waters by collecting monthly samples between February 2017 and July 2018 at four sites located across two straits with different trophic status, and sequencing the V6-V8 region of the small sub-unit ribosomal RNA gene (rRNA gene) of Bacteria, Archaea, and Eukaryota. Johor Strait, which is subjected to wider environmental fluctuations from anthropogenic activities, presented a higher abundance of copiotrophic microbes, including Cellvibrionales and Rhodobacterales. The mesotrophic Singapore Strait, where the seasonal variability is caused by changes in the oceanographic conditions, harboured a higher proportion of typically marine microbe groups such as Synechococcales, Nitrosupumilales, SAR11, SAR86, Marine Group II Archaea and Radiolaria. In addition, we observed seasonal variability of the microbial communities in the Singapore Strait, which was possibly influenced by the alternating monsoon regime, while no seasonal pattern was detected in the Johor Strait.
The Changbai (also known as "Baekdu") Mountain, on the border between China and North Korea, is the highest mountain (2750 m) in northeastern China. Recently, this mountain region has experienced a dramatic increase in air pollution, not only because of increasing volumes of tourism-derived traffic but also because of the long-range transport of polluted westerly winds passing through major industrial and urban cities in the eastern region of China. To assess the relative importance of the two sources of pollution, 16 polycyclic aromatic hydrocarbons (PAHs) as model substances were determined in the mountain soil. A total of 32 soil samples were collected from different sides of the mountain at different latitudes between July and August of 2009. The ∑PAH concentrations were within the range 38.5-190.1 ng g(-1) on the northern side, 117.7-443.6 ng g(-1) on the southern side, and 75.3-437.3 ng g(-1) on the western side. A progressive increase in the level of ∑PAHs with latitude was observed on the southern and western sides that face the westerly wind with abundant precipitation. However, a similar concentration gradient was not observed on the northern side that receives less rain and is on the leeward direction of the wind. The high-molecular-weight PAH compounds were predominant in the soils on the southern and western sides, while low-molecular-weight PAHs dominated the northern side soils. These findings show that the distribution of PAHs in the mountain soil is strongly influenced by the atmospheric long-range transport and cold trapping.
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.