sugar industry is one of the industries that produce a high amount of
pollutant since its wastewater contains high amount of organic material, biochemical
oxygen demand (bod) and chemical oxygen demand (cod). if this waste is
discharged without a proper treatment into the watercourse, it can cause problem to aquatic
life and environment. for the primary treatment process, sugar wastewater can be treated
by using chemical precipitation method which involves coagulation process. currently,
ferric chloride has been used as the coagulant but it consumes more alkalinity and
corrosive. in this study, the suitable coagulant to be used to treat the wastewater from sugar
industry and the optimum conditions to achieve high percentage removal of cod was
determined. the characteristic of the wastewater was firstly determined. then, the most
suitable coagulant to be used for the treatment was studied by determining their efficiency
to reduce cod and tss in the wastewater at different dosages. aluminium sulphate
(alum), ferric chloride and polyaluminium chloride (pac) were chosen to be studied for
suitable coagulant. The optimum condition of the coagulant (ph, coagulant dosage, fast
mixing speed) was determined by using design expert software. results showed that alum
can be used to effectively remove 42.9% of cod and 100% of tss at high dosage (50
mg/l). the optimum condition of alum was at ph 5.2, 10 mg/l of alum and 250 rpm of
mixing speed. this shows that at optimum condition, alum can be used to treat wastewater
from sugar industry.
The utilization of agroindustry wastes such as sugarcane bagasse (SCB) for
cellulase production could help to reduce the problem of lignocellulosic wastes. Thus, this
study aimed to use the sugarcane bagasse as a substrate in the production of fungal
cellulases via solid-state fermentation of Aspergillus niger. The variables of solid-state
fermentation condition of A. niger such as sugarcane bagasse particle size (400 and 600
µm), inoculum size (2% (v/v) and 5% (v/v), medium pH (5 and 7), and fermentation time (5
and 15 days) were screened using two-level factorial design (Design expert software, StatEase Inc., Version 8.0). Filter paper activity (FPA) was determined to quantify the
produced enzymes activity. The observation on the structure and physicochemical changes
of SCB before and after SSF using scanning electron microscopy (SEM) and optical
microscope was also conducted. Analysis of variance (ANOVA) shows that the significant
parameters of SSF that affected the cellulose production were particle size of SCB and
inoculum size–pH interaction.
This work aims at optimizing the media constituents for citric acid production from oil palm empty fruit bunches (EFB) as renewable resource using artificial neural networks (ANN) approach. The bioconversion process was done through solid state bioconversion using Aspergillus niger. ANN model was built using MATLAB software. A dataset consists of 20 runs from our previous work was used to develop ANN. The predictive and generalization ability of ANN and the results of RSM were compared. The determination coefficients (R2-value) for ANN and RSM models were 0.997 and 0.985, respectively, indicating the superiority of ANN in capturing the non-linear behavior of the system. Validation process was done and the maximum citric acid production (147.74 g/kg-EFB) was achieved using the optimal solution from ANN which consists of 6.1% sucrose, 9.2% mineral solution and 15.0% inoculum.
Boron has been classified as a drinking water pollutant in many countries. It is harmful to many plants, exceptionally sensible plants, and human health. Therefore, boron level needs to be decreased to 0.3 mg/L for drinking water and within 0.5 mg/L to 1 mg/L for irrigation water. In this study, various operational parameters namely pH, contact time and liquid/solid ratio were investigated to determine the potential of using date seed (or date pit or date stone) to remove boron from seawater. This study's main objective was to determine boron adsorption capacities of date seeds prepared by various methods (i.e., powdered, activated, acid-treated and defatted seed) by batch adsorption process using boron contaminated synthetic seawater. The process parameters of the selected biosorbent among the four date seed preparations methods were optimized. The surface characteristics were analyzed by using Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscope (SEM). The results showed that acid-treated date seed was the best biosorbent in terms of removing 89.18% boron from aqueous solution at neutral pH, liquid to solid ratio of 5 within 2 hours of reaction time at room temperature (25°C±2°C).
A green technology of biodiesel production focuses on the use of enzymes as the catalyst. In enzymatic biodiesel synthesis, suitable solvent system is very essential to reduce the inhibition effects of the solvent to the enzymes. This study produced ethanol-based biodiesel from a low-cost sludge palm oil (SPO) using locally-produced Candida cylindracea lipase from fermentation of palm oil mill effluent (POME) based medium. The optimum levels of ethanol-to-SPO molar ratio and enzyme loading were found to be 4:1 and 10 U/25 g of SPO respectively with 54.4% w/w SPO yield of biodiesel and 21.7% conversion of free fatty acid (FFA) into biodiesel. Addition of tert-butanol at 2:1 tert-butanol-to-SPO molar ratio into the ethanol-solvent system increased the yield of biodiesel to 71.6% w/w SPO and conversion of FFA into biodiesel to 28.8%. The SPO and ethanol have promising potential for the production of renewable biodiesel using enzymatic-catalyzed esterification and transesterification.
This study has applied the concept of the hybrid PAC-UF process in the treatment of the final effluent of the palm oil industry for reuse as feedwater for low-pressure boilers. In a bench-scale set-up, a low-cost empty fruit bunch-based powdered activated carbon (PAC) was employed for upstream adsorption of biotreated palm oil mill effluent (BPOME) with the process conditions: 60 g/L dose of PAC, 68 min of mixing time and 200 rpm of mixing speed, to reduce the feedwater strength, alleviate probable fouling of the membranes and thus improve the process flux (productivity). Three polyethersulfone ultrafiltration membranes of molecular weight cut-off (MWCO) of 1, 5 and 10 kDa were investigated in a cross-flow filtration mode, and under constant transmembrane pressures of 40, 80, and 120 kPa. The permeate qualities of the hybrid processes were evaluated, and it was found that the integrated process with the 1 kDa MWCO UF membrane yielded the best water quality that falls within the US EPA reuse standard for boiler-feed and cooling water. It was also observed that the permeate quality is fit for extended reuse as process water in the cement, petroleum and coal industries. In addition, the hybrid system's operation consumed 37.13 Wh m(-3) of energy at the highest applied pressure of 120 kPa, which is far lesser than the typical energy requirement range (0.8-1.0 kWh m(-3)) for such wastewater reclamation.
The formation of struvite crystals or magnesium ammonium phosphate (MgNH4PO4) in palm oil mill effluent (POME) occurs as early as in the secondary stage of POME treatment system. Its growth continues in the subsequent tertiary treatment which reduces piping diameter, thus affecting POME treatment efficiency. Hypothesis. The beneficial use of the crystal is the motivation. This occurrence is rarely reported in scientific articles despite being a common problem faced by palm oil millers. The aim of this study is to characterize struvite crystals found in an anaerobic digester of a POME treatment facility in terms of their physical and chemical aspects. The compositions, morphology and properties of these crystals were determined via energy dispersive spectroscopy (EDS), elemental analysis, scanning electron microscopy (SEM) and x-ray diffraction (XRD). Solubility tests were carried out to establish solubility curve for struvite from POME. Finally, crystal growth experiment was done applying reaction crystallization method to demonstrate struvite precipitation from POME. Results showed that high phosphorous (P) (24.85 wt%) and magnesium (Mg) (21.33 wt%) content was found in the struvite sample. Elemental analysis detected carbon (C), hydrogen (H), nitrogen (N) and sulfur (S) below 4 wt%. The crystals analysed by XRD in this study were confirmed as struvite with 94.8% struvite mineral detected from its total volume. Having an orthorhombic crystal system, struvite crystals from POME recorded an average density of 1.701 g cm-3. Solubility curve of struvite from POME was established with maximum solubility of 275.6 mg L-1 at pH 3 and temperature 40 °C. Minimum solubility of 123.6 mg L-1 was recorded at pH 7 and temperature 25 °C. Crystal growth experiment utilizing POME as the source medium managed to achieve 67% reduction in phosphorous content. This study concluded that there is a potential of harnessing valuable nutrients from POME in the form of struvite. Struvite precipitation technology can be adapted in the management of POME in order to achieve maximum utilization of the nutrients that are still abundant in POME. At the same time maximization of nutrient extractions from POME will also reduce pollutants loading in the final discharge.
This research optimized the adsorption performance of rice husk char (RHC4) for copper (Cu(II)) from an aqueous solution. Various physicochemical analyses such as Fourier transform infrared spectroscopy (FTIR), field-emission scanning electron microscopy (FESEM), carbon, hydrogen, nitrogen, and sulfur (CHNS) analysis, Brunauer-Emmett-Teller (BET) surface area analysis, bulk density (g/mL), ash content (%), pH, and pHZPC were performed to determine the characteristics of RHC4. The effects of operating variables such as the influences of aqueous pH, contact time, Cu(II) concentration, and doses of RHC4 on adsorption were studied. The maximum adsorption was achieved at 120 min of contact time, pH 6, and at 8 g/L of RHC4 dose. The prediction of percentage Cu(II) adsorption was investigated via an artificial neural network (ANN). The Fletcher-Reeves conjugate gradient backpropagation (BP) algorithm was the best fit among all of the tested algorithms (mean squared error (MSE) of 3.84 and R2 of 0.989). The pseudo-second-order kinetic model fitted well with the experimental data, thus indicating chemical adsorption. The intraparticle analysis showed that the adsorption process proceeded by boundary layer adsorption initially and by intraparticle diffusion at the later stage. The Langmuir and Freundlich isotherm models interpreted well the adsorption capacity and intensity. The thermodynamic parameters indicated that the adsorption of Cu(II) by RHC4 was spontaneous. The RHC4 adsorption capacity is comparable to other agricultural material-based adsorbents, making RHC4 competent for Cu(II) removal from wastewater.