scholarly journals Optimization of Oil Removal by Sugarcane Bagasse using Response Surface Methodology

2021 ◽  
Vol 4 (2) ◽  
pp. 82-87
Author(s):  
Asilah Ahmad Samsuir ◽  
Norhisyam Ismail ◽  
Rozidaini Mohd Ghazi
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Sugarcane Bagasse ◽  
Contact Time ◽  
Oil Pollution ◽  
Oil Removal ◽  
Industrial Growth ◽  
Synthetic Oil ◽  
Exploration And Production ◽  
Oil Wastewater

Oily wastewater is one of the environmental concerns nowadays. The seriousness of oil pollution problem comes in sync with the expansion of oil exploration and production activities, as well as industrial growth around the world. In this study, the ability of sugarcane bagasse in removing oil in synthetic oil wastewater was investigated. Parameters affecting oil removal such as concentrations of synthetic oil wastewater, biosorbent dosage and contact time were optimized using Response Surface Methodology (RSM) via Box Behnken Design. Sugarcane bagasse showed excellent efficiency in removing oil with percentage removal up to 98.73% at 1.3 h contact time with 3.06 g of biosorbent dosage and 16.9% of synthetic oil wastewater concentration. The use of sugarcane bagasse in removing oil in water was successfully prove in this study.

scholarly journals Optimization of Crude Oil Biodegradation of Fungi Isolated from Refinery Effluent Site using Response Surface Methodology

2021 ◽  
Vol 17 (4) ◽  
pp. 257-268
Author(s):  
U.C. Odili ◽  
F.B. Ibrahim ◽  
E.M. Shaibu-modagbe ◽  
H.I. Atta
Keyword(s):  
Response Surface Methodology ◽  
Crude Oil ◽  
Response Surface ◽  
Removal Efficiency ◽  
Contact Time ◽  
Experimental Result ◽  
Oil Removal ◽  
Refinery Effluent ◽  
Response Surface Optimization ◽  
Crude Oil Removal

The activities involved in the production and exploration of crude oil has constantly polluted the environment. This study investigated the ability of an indigenous fungus to utilize petroleum hydrocarbon. Response Surface Methodology was used to optimize the effects of pH, microbial concentration (spores/ml), and contact time (days) on the crude oil removal efficiency in refinery effluent. Monocillium sp. was isolated and used for the treatment of refinery effluent due to its predominance in the contaminated soil. Twenty experimental runs were analyzed to determine the effect of pH, microbial concentration and contact time on the oil removal efficiency. From theexperimental results obtained, a maximum oil removal efficiency of 98.42 % was achieved at a pH of 6.5, contact time of 14 days, and a microbial concentration of 3 spores/ml. The results obtained showed the percentage of crude oil removal in the effluent sample  increased with an increase in time. Optimization of the experimental result was achieved at a removal efficiency of 98.59 %, a contact time of 13.96 days, a pH of 6.85, and a microbial concentration of 3.01 spores/ml. The findings of this study revealed that Monocillium sp. is a viable hydrocarbon degrader, and can be used in the bioremediation of petroleum contaminated environments. Keywords: Response surface, optimization, bioremediation, hydrocarbon, removal efficiency, Monocillium sp.

scholarly journals Removal of Pharmaceutical Micropollutants with Integrated Biochar and Marine Microalgae

2020 ◽  
Vol 9 (1) ◽  
pp. 4
Author(s):  
Amin Mojiri ◽  
Maedeh Baharlooeian ◽  
Reza Andasht Kazeroon ◽  
Hossein Farraji ◽  
Ziyang Lou
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Response Surface Methodology ◽  
Cell Viability ◽  
Response Surface ◽  
Contact Time ◽  
Marine Microalgae ◽  
Chaetoceros Muelleri ◽  
Mean Squared Errors ◽  
High Concentrations

Using microalgae to remove pharmaceuticals and personal care products (PPCPs) micropollutants (MPs) have attracted considerable interest. However, high concentrations of persistent PPCPs can reduce the performance of microalgae in remediating PPCPs. Three persistent PPCPs, namely, carbamazepine (CBZ), sulfamethazine (SMT) and tramadol (TRA), were treated with a combination of Chaetoceros muelleri and biochar in a photobioreactor during this study. Two reactors were run. The first reactor comprised Chaetoceros muelleri, as the control, and the second reactor comprised Chaetoceros muelleri and biochar. The second reactor showed a better performance in removing PPCPs. Through the response surface methodology, 68.9% (0.330 mg L−1) of CBZ, 64.8% (0.311 mg L−1) of SMT and 69.3% (0.332 mg L−1) of TRA were removed at the initial concentrations of MPs (0.48 mg L−1) and contact time of 8.1 days. An artificial neural network was used in optimising elimination efficiency for each MP. The rational mean squared errors and high R2 values showed that the removal of PPCPs was optimised. Moreover, the effects of PPCPs concentration (0–100 mg L−1) on Chaetoceros muelleri were studied. Low PPCP concentrations (<40 mg L−1) increased the amounts of chlorophyll and proteins in the microalgae. However, cell viability, chlorophyll and protein contents dramatically decreased with increasing PPCPs concentrations (>40 mg L−1).

scholarly journals Optimization of Crude Oil and PAHs Degradation by Stenotrophomonas rhizophila KX082814 Strain through Response Surface Methodology Using Box-Behnken Design

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Praveen Kumar Siddalingappa Virupakshappa ◽  
Manjunatha Bukkambudhi Krishnaswamy ◽  
Gaurav Mishra ◽  
Mohammed Ameenuddin Mehkri
Keyword(s):  
Response Surface Methodology ◽  
Crude Oil ◽  
Response Surface ◽  
Oxygen Demand ◽  
Inoculum Size ◽  
Coefficient Of Determination ◽  
Oil Removal ◽  
Box Behnken Design ◽  
Stenotrophomonas Rhizophila ◽  
Crude Oil Removal

The present paper describes the process optimization study for crude oil degradation which is a continuation of our earlier work on hydrocarbon degradation study of the isolate Stenotrophomonas rhizophila (PM-1) with GenBank accession number KX082814. Response Surface Methodology with Box-Behnken Design was used to optimize the process wherein temperature, pH, salinity, and inoculum size (at three levels) were used as independent variables and Total Petroleum Hydrocarbon, Biological Oxygen Demand, and Chemical Oxygen Demand of crude oil and PAHs as dependent variables (response). The statistical analysis, via ANOVA, showed coefficient of determination R2 as 0.7678 with statistically significant P value 0.0163 fitting in second-order quadratic regression model for crude oil removal. The predicted optimum parameters, namely, temperature, pH, salinity, and inoculum size, were found to be 32.5°C, 9, 12.5, and 12.5 mL, respectively. At this optimum condition, the observed and predicted PAHs and crude oil removal were found to be 71.82% and 79.53% in validation experiments, respectively. The % TPH results correlate with GC/MS studies, BOD, COD, and TPC. The validation of numerical optimization was done through GC/MS studies and   % removal of crude oil.

scholarly journals Response surface methodology approach for the optimisation of adsorption of hydrolysed polyacrylamide from polymer-flooding wastewater onto steel slag: a good option of waste mitigation

2017 ◽  
Vol 76 (4) ◽  
pp. 776-784 ◽  
Author(s):  
Mijia Zhu ◽  
Jun Yao ◽  
Zhonghai Qin ◽  
Luning Lian ◽  
Chi Zhang
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Removal Efficiency ◽  
Contact Time ◽  
Interactive Effect ◽  
Steel Slag ◽  
Oxygen Demand ◽  
Polymer Flooding ◽  
High Concentration ◽  
Adsorbent Dosage

Wastewater produced from polymer flooding in oil production features high viscosity and chemical oxygen demand because of the residue of high-concentration polymer hydrolysed polyacrylamide (HPAM). In this study, steel slag, a waste from steel manufacturing, was studied as a low-cost adsorbent for HPAM in wastewater. Optimisation of HPAM adsorption by steel slag was performed with a central composite design under response surface methodology (RSM). Results showed that the maximum removal efficiency of 89.31% was obtained at an adsorbent dosage of 105.2 g/L, contact time of 95.4 min and pH of 5.6. These data were strongly correlated with the experimental values of the RSM model. Single and interactive effect analysis showed that HPAM removal efficiency increased with increasing adsorbent dosage and contact time. Efficiency increased when pH was increased from 2.6 to 5.6 and subsequently decreased from 5.6 to 9.3. It was observed that removal efficiency significantly increased (from 0% to 86.1%) at the initial stage (from 0 min to 60 min) and increased gradually after 60 min with an adsorbent dosage of 105.2 g/L, pH of 5.6. The adsorption kinetics was well correlated with the pseudo-second-order equation. Removal of HPAM from the studied water samples indicated that steel slag can be utilised for the pre-treatment of polymer-flooding wastewater.

scholarly journals Biosorption of lead ions by exopolysaccharide producing Azotobacter sp.

2021 ◽  
Vol 42 (1) ◽  
pp. 40-50
Author(s):  
P. Dhevagi ◽  
◽  
S. Priyatharshini ◽  
A. Ramya ◽  
M. Sudhakaran ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Electron Microscope ◽  
Scanning Electron Microscope ◽  
Response Surface ◽  
Functional Groups ◽  
Contact Time ◽  
Sewage Water ◽  
Energy Dispersive ◽  
X Ray ◽  
Scanning Electron

Aim: Removal of lead from wastewater using Azotobacter species and optimisation of various parameters to maximise the adsorption of lead by response surface methodology as a tool. Methodology: The bacterial isolate UBI-7 recovered from sewage water irrigated soil was examined for its biosorption potential towards lead. The lead removal efficiency of Azotobacter salinestris was studied with respect to metal concentration (50-250 mg l-1), contact time (24-120 hrs), and pH (4-8).Using response surface methodology, these factors were optimized and R2 value obtained was 0.9710 for lead ions, which indicates the validity of the model. Observation with Fourier Transform Infrared (FTIR), Scanning Electron Microscope imaging (SEM) and Energy Dispersive X-ray Spectroscopic analysis (EDX) were carried out to confirm lead biosorption by Azotobacter salinestris. Results: The lead tolerant bacterium isolated from sewage water irrigated soil (UBI-7) was recognized as Azotobacter salinestris by 16S rRNA based gene sequence analysis. The highest removal percentage of Pb (61.54) was 50 mg l-1 in 72 hrs equilibration period. Interaction effect between different levels of Pb and different contact time of the solution were found to be significant. Lead biosorption by the organism was confirmed by the changes in stretching intensities of functional groups as well as appearance of strong OH stretching at 3291.69 cm-1. Images obtained from Scanning Electron Microscope and Energy Dispersive X-ray Spectroscopic studies of the bacteria (UBI-7) before and after biosorption clearly indicated lead adsorption. Interpretation: Current study proves that the functional groups of Azotobacter salinestris are involved in lead biosorption from aqueous solution which was confirmed through FTIR.EDX analysis also elucidated the lead absorption by the bacterial cells. Hence, this could be effectively utilized for decontamination of lead from the polluted environment. Key words: Azotobacter salinestris, Biosorption, Lead, Response surface methodology

scholarly journals Optimization and Modeling of Microcystin-LR Degradation by TiO2 Photocatalyst Using Response Surface Methodology

2020 ◽  
Author(s):  
Negar Jafari ◽  
Afshin Ebrahimi ◽  
Karim Ebrahimpour ◽  
Ali Abdolahnejad
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Removal Efficiency ◽  
Contact Time ◽  
High Performance ◽  
Operating Variables ◽  
Effective Removal ◽  
Positive Effect ◽  
Harmful Effects ◽  
Maximum Removal

Introduction: Microcystin-leucine arginine (MC-LR) is a toxin with harmful effects on the liver, kidney, heart, and gastrointestinal tract. So, effective removal of MC-LR from water resources is of great importance. The aim of this study was to remove microcystin-LR (MC-LR) from aqueous solution by Titanium Dioxide (TiO2). Materials and Methods: In the present study, TiO2, as a semiconductor, was used for photodegradation of MC-LR under ultraviolet light (UV). The Response Surface Methodology was applied to investigate the effects of operating variables such as pH (A), contact time (B), and catalyst dose (B) on the removal of MC-LR. The MC-LR concentration was measured by high-performance liquid chromatography (HPLC). Results: The results showed that single variables such as A, B, and C had significant effects on MC-LR removal (pvalue < 0.05). In other words, increase of the contact time and catalyst dose had a positive effect on enhancing the removal efficiency of MC-LR, but the effect of pH was negative. The analysis of variance showed that BC, A2, and C2 variables had a significant effect on the MC-LR removal (pvalue < 0.05). Finally, the maximum removal efficiency of MC-LR was 95.1%, which occurred at pH = 5, contact time = 30 minutes, and catalyst dose = 1 g/l. Conclusion: According to the findings, TiO2, as a photocatalyst, had an appropriate effect on degradation of the MC-LR.

scholarly journals ADSORPTION OF MALACHITE GREEN DYE USING SPENT COFFEE GROUND BIOCHAR: OPTIMISATION USING RESPONSE SURFACE METHODOLOGY

2020 ◽  
Vol 83 (1) ◽  
pp. 27-36
Author(s):  
Mardawani Mohamad ◽  
Rizki Wannahari ◽  
Rosmawani Mohammad ◽  
Noor Fazliani Shoparwe ◽  
Kwan Wei Lun ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Adsorption Capacity ◽  
Response Surface ◽  
Malachite Green ◽  
Contact Time ◽  
Quadratic Model ◽  
Adsorbent Dosage ◽  
Coffee Grounds ◽  
Spent Coffee Ground ◽  
Coffee Ground

Used coffee grounds usually end up as landfill. However, the unique structural properties of its porous surface make coffee grounds can be transformed into biochar and performed as an alternative low cost adsorbent. Malachite green (MG) is a readily water soluble dye which is used extensively in textile and aquaculture industries. The mordant complex structures of MG generate destructive effects to animals and environment. In this study, adsorption of malachite green using spent coffee ground biochar as adsorbent was investigated. The experiments were designed in two methods: classical and optimisation by response surface methodology. Three parameters were studied, which are adsorbent dosage, contact time and pH while the responses in this study are malachite green removal (%) and adsorption capacity (mg/g). Optimisation studies were performed using response surface methodology. Quadratic model was chosen for both response and studied using central composite design. The correlation coefficient, R2 for the quadratic model of malachite green removal (%) and adsorption capacity (mg/g) were 0.95 and 0.99, respectively. The optimum malachite green removal (%) predicted was found at 99.27%, by using 0.12 g of adsorbent dosage, 43.05 minutes of contact time and pH of 9.45 at desirability of 1.0. The optimum adsorption capacity (mg/g) predicted was found at 118.01 mg/g, by using 0.02 g of adsorbent dosage, 60 minutes of contact time and pH of 10.24 at desirability of 0.98. So, it was concluded that the spent coffee ground biochar can be used as an effective adsorbent for malachite green removal from aqueous solution.

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