The Langat River in Malaysia has been experiencing anthropogenic input from urban, rural and industrial activities for many years. Sewage contamination, possibly originating from the greater than three million inhabitants of the Langat River Basin, were examined. Sediment samples from 22 stations (SL01-SL22) along the Langat River were collected, extracted and analysed by GC-MS. Six different sterols were identified and quantified. The highest sterol concentration was found at station SL02 (618.29 ng/g dry weight), which situated in the Balak River whereas the other sediment samples ranged between 11.60 and 446.52 ng/g dry weight. Sterol ratios were used to identify sources, occurrence and partitioning of faecal matter in sediments and majority of the ratios clearly demonstrated that sewage contamination was occurring at most stations in the Langat River. A multivariate statistical analysis was used in conjunction with a combination of biomarkers to better understand the data that clearly separated the compounds. Most sediments of the Langat River were found to contain low to mid-range sewage contamination with some containing 'significant' levels of contamination. This is the first report on sewage pollution in the Langat River based on a combination of biomarker and multivariate statistical approaches that will establish a new standard for sewage detection using faecal sterols.
This paper presents Gene-Expression Programming (GEP), which is an extension to the genetic programming (GP) approach to predict the total bed material load for three Malaysian rivers. The GEP is employed without any restriction to an extensive database compiled from measurements in the Muda, Langat, and Kurau rivers. The GEP approach demonstrated a superior performance compared to other traditional sediment load methods. The coefficient of determination, R(2) (=0.97) and the mean square error, MSE (=0.057) of the GEP method are higher than those of the traditional method. The performance of the GEP method demonstrates its predictive capability and the possibility of the generalization of the model to nonlinear problems for river engineering applications.
Poor water quality is a serious problem in the world which threatens human health, ecosystems, and plant/animal life. Prediction of surface water quality is a main concern in water resource and environmental systems. In this research, the support vector machine and two methods of artificial neural networks (ANNs), namely feed forward back propagation (FFBP) and radial basis function (RBF), were used to predict the water quality index (WQI) in a free constructed wetland. Seventeen points of the wetland were monitored twice a month over a period of 14 months, and an extensive dataset was collected for 11 water quality variables. A detailed comparison of the overall performance showed that prediction of the support vector machine (SVM) model with coefficient of correlation (R(2)) = 0.9984 and mean absolute error (MAE) = 0.0052 was either better or comparable with neural networks. This research highlights that the SVM and FFBP can be successfully employed for the prediction of water quality in a free surface constructed wetland environment. These methods simplify the calculation of the WQI and reduce substantial efforts and time by optimizing the computations.
This study performed an assessment on the beneficial of the Clean Development Mechanism (CDM) application on waste treatment system in a local palm oil industry in Malaysia. Life cycle assessment (LCA) was conducted to assess the environmental impacts of the greenhouse gas (GHG) reduction from the CDM application. Calculations on the emission reduction used the methodology based on AM002 (Avoided Wastewater and On-site Energy Use Emissions in the Industrial Sector) Version 4 published by United Nations Framework Convention on Climate Change (UNFCC). The results from the studies showed that the introduction of CDM in the palm oil mill through conversion of the captured biogas from palm oil mill effluent (POME) treatment into power generation were able to reduce approximate 0.12 tonnes CO2 equivalent concentration (tCO2e) emission and 30 kW x hr power generation per 1 tonne of fresh fruit bunch processed. Thus, the application of CDM methodology on palm oil mill wastewater treatment was able to reduce up to 1/4 of the overall environment impact generated in palm oil mill.
Chitosan-tripolyphosphate (CTPP) beads were synthesized, characterized and were used for the adsorption of Pb(II) and Cu(II) ions from aqueous solution. The effects of initial pH, agitation period, adsorbent dosage, different initial concentrations of heavy metal ions and temperature were studied. The experimental data were correlated with the Langmuir, Freundlich and Dubinin-Radushkevich isotherm models. The maximum adsorption capacities of Pb(II) and Cu(II) ions in a single metal system based on the Langmuir isotherm model were 57.33 and 26.06 mg/g, respectively. However, the beads showed higher selectivity towards Cu(II) over Pb(II) ions in the binary metal system. Various thermodynamic parameters such as enthalpy (DeltaH degrees), Gibbs free energy (DeltaG degrees) and entropy (DeltaS degrees) changes were computed and the results showed that the adsorption of both heavy metal ions onto CTPP beads was spontaneous and endothermic in nature. The kinetic data were evaluated based on the pseudo-first and -second order kinetic and intraparticle diffusion models. Infrared spectra were used to elucidate the mechanism of Pb(II) and Cu(II) ions adsorption onto CTPP beads.
Palm ash, an agriculture waste residue from palm-oil industry in Malaysia, was investigated as a replacement for the current expensive methods of removing direct blue 71 dye from an aqueous solution. The experimental data were analyzed by the Langmuir and Freundlich models of adsorption. Equilibrium data fitted well with Freundlich model in the range of 50-600mg/L. The equilibrium adsorption capacity of the palm ash was determined with the Langmuir equation and found to be 400.01mg dye per gram adsorbent at 30 degrees C. The rates of adsorption were found to conform to the pseudo-second-order kinetics with good correlation. The results indicate that the palm ash could be employed as a low-cost alternative to commercial activated carbon.
With inoculum sludge from a conventional activated sludge wastewater treatment plant, three sequencing batch reactors (SBRs) fed with synthetic wastewater were operated at different high temperatures (30, 40 and 50±1°C) to study the formation of aerobic granular sludge (AGS) for simultaneous organics and nutrients removal with a complete cycle time of 3h. The AGS were successfully cultivated with influent loading rate of 1.6CODg(Ld)(-1). The COD/N ratio of the influent wastewater was 8. The results revealed that granules developed at 50°C have the highest average diameter, (3.36mm) with 98.17%, 94.45% and 72.46% removal efficiency observed in the system for COD, ammonia and phosphate, respectively. This study also demonstrated the capabilities of AGS formation at high temperatures which is suitable to be applied for hot climate conditions.
Biological aerated filter (BAF), sand filtration (SF), alum and Moringa oleifera coagulation were investigated as a pre-treatment for reducing the organic and biofouling potential component of an ultrafiltration (UF) membrane in the treatment of lake water. The carbohydrate content was mainly responsible for reversible fouling of the UF membrane compared to protein or dissolved organic carbon (DOC) content. All pre-treatment could effectively reduce these contents and led to improve the UF filterability. Both BAF and SF markedly led to improvement in flux than coagulation processes, and alum gave greater flux than M. oleifera. This was attributed to the effective removal and/or breakdown of high molecular weight (MW) organics by biofilters. BAF led to greater improvement in flux than SF, due to greater breakdown of high MW organics, and this was also confirmed by the attenuated total reflection-Fourier transform infrared spectroscopy analysis. Coagulation processes were ineffective in removing biofouling potential components, whereas both biofilters were very effective as shown by the reduction of low MW organics, biodegradable dissolved organic carbon and assimilable organic carbon contents. This study demonstrated the potential of biological pre-treatments for reducing organic and biofouling potential component and thus improving flux for the UF of lake water treatment.
The efficiency of phenol degradation via Fenton reaction using mixture of heterogeneous goethite catalyst with homogeneous ferrous ion was analyzed as a function of three independent variables, initial concentration of phenol (60 to 100 mg /L), weight ratio of initial concentration of phenol to that of H2O2 (1: 6 to 1: 14) and, weight ratio of initial concentration of goethite catalyst to that of H2O2 (1: 0.3 to 1: 0.7). More than 90 % of phenol removal and more than 40% of TOC removal were achieved within 60 minutes of reaction. Two separate models were developed using artificial neural networks to predict degradation percentage by a combination of Fe3+ and Fe2+ catalyst. Five operational parameters were employed as inputs while phenol degradation and TOC removal were considered as outputs of the developed models. Satisfactory agreement was observed between testing data and the predicted values (R2Phenol = 0.9214 and R2TOC= 0.9082).
Cross-linked chitosan/sepiolite composite was prepared from sepiolite clay and chitosan, and was cross-linked using epichlorohydrin. Among the various weight ratio percentage of chitosan and sepiolite clay composites, CS50SP50 was selected as the best adsorbent for both methylene blue (MB) and reactive orange 16 (RO 16). At an optimum adsorbent dosage of 0.2g/100mL, the effects of initial dye concentration (25-400mg/L) and pH (3-11) on MB and RO 16 adsorption onto CS50SP50 composite were studied. Monolayer adsorption capacities of CS50SP50 composite for MB and RO 16 were 40.986mg/g and 190.965mg/g, respectively at 30°C. Freundlich, Langmuir and Temkin isotherms applied on the adsorption data for both the dyes reveal that data fitted best for Freundlich model. For both the dyes pseudo-second-order kinetics were found to describe the adsorption process better than pseudo-first-order kinetics. The adsorption capacity of CS50SP50 composite for both the dyes was found better compared to previous studies thus making it potentially low-cost adsorbent for removal of both cationic and reactive dyes.
The effects of ozonation, anion exchange resin (AER) and UV/H2O2 were investigated as a pre-treatment to control organic fouling (OF) of ultrafiltration membrane in the treatment of drinking water. It was found that high molecular weight (MW) organics such as protein and polysaccharide substances were majorly responsible for reversible fouling which contributed to 90% of total fouling. The decline rate increased with successive filtration cycles due to deposition of protein content over time. All pre-treatment could reduce the foulants of a Ultrafiltration membrane which contributed to the improvement in flux, and there was a greater improvement of flux by UV/H2O2 (61%) than ozonation (43%) which in turn was greater than AER (23%) treatment. This was likely due to the effective removal/breakdown of high MW organic content. AER gave greater removal of biofouling potential components (such as biodegradable dissolved organic carbon and assimilable organic carbon contents) compared to UV/H2O2 and ozonation treatment. Overall, this study demonstrated the potential of pre-treatments for reducing OF of ultrafiltration for the treatment of drinking water.