Application of Response Surface Methodology for Optimization of Reactive Azo Dye Degradation Process by Fenton’s Oxidation

Dutta, Subhajit; Ghosh, Ananya; Moi, Sankar Ch.; Saha, Rajnarayan

doi:10.7763/ijesd.2015.v6.705

Cited by 16 publications

(8 citation statements)

References 19 publications

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“…(1). The statistical value from the performed test proves the validity of the model, considering the quantum of the nonsignificant value with lack of feat and significant value [12].…”

Section: Utilizing Response Surface Methodology For Cod Removal Potenmentioning

confidence: 59%

“…. The statistical value from the performed test proves the validity of the model, considering the quantum of the nonsignificant value with lack of feat and significant value . The model for response surface methodology proved to be very significant as it generates a higher Fisher's value of 187.8, and a low probability value, p < 0001.…”

Section: Resultsmentioning

confidence: 70%

“…S4, elaborates the influence of various factors in COD treatment process based on slope value and the range of change. The higher the slopes and range, the greater the influence on variable will be [12,13]. In this experiment, treatment time was found to be the key influential factor, then the biomass loading and pH, respectively.…”

Section: Sensitivity Analysismentioning

confidence: 66%

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Microflora from leaf debris is suitable for treatment of starch industry wastewater

Neogi

Dey

Chaterjee

2016

Engineering in Life Sciences

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Microflora from leaf debris is suitable for treatment of starch industry wastewaterBiological treatment of industrial waste is a widely practiced technique that generates comparatively less environmentally hazardous waste than other chemical treatment processes. Wet milling of maize generates huge amount of wastewater (5 m 3 /ton) of low pH with organic matter and nutrients. Anaerobic methanogenic and aerobic bacteria are mostly highly sensitive to low pH. The treatment of wastewater causes huge cost of chemical neutralization or hydraulic recirculation for maintaining neutral pH. In the present study, different microbial consortia isolated from cow dung, active sludge from an anaerobic reactor for treatment of industrial wastewater, and leaf debris from benthic soil were screened for tolerance against low pH and for potential of chemical oxygen demand (COD) removal in order to find out an alternative microbial population for industrial water treatment at low pH. The most effective consortia found from leaf debris were further investigated for optimal operation. The microscopic analysis of leaf debris sludge showed abundance of Gram-negative methanococci, which was found tolerant to low pH in plate culture method. On further investigation for COD removal from starch industry effluent, they were found to be most effective at pH 5 with highest COD removal rate of 70% and lowest biomass generation of 81%. Hence, it was concluded that the low pHtolerant methanogen bacteria, enriched from leaf debris sludge, is highly beneficial for anaerobic treatment of wastewater from several industries including corn starch industry by reducing cost of operation for neutralization to neutral pH and through reducing excess waste sludge production by the treatment system.

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“…(1). The statistical value from the performed test proves the validity of the model, considering the quantum of the nonsignificant value with lack of feat and significant value [12].…”

Section: Utilizing Response Surface Methodology For Cod Removal Potenmentioning

confidence: 59%

Section: Resultsmentioning

confidence: 70%

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Microflora from leaf debris is suitable for treatment of starch industry wastewater

Neogi

Dey

Chaterjee

2016

Engineering in Life Sciences

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“…It could be concluded that both factors X1 and X2 significantly affected the three responses. From the experimental results, statistical testing was carried out employing Fishers test for ANOVA and the statistical significance of the second-order model indicated that the regression is statistically significant (P<0.0001) for the first two responses while the third response statisti-cal data satisfied linear model; however, the lack of fit is not statistically significant at 99% confidence level, thus the residual variance for the models were insignificant [27,28]. The analysis of variance indicated significant effect of the independent variables on the responses.…”

Section: Experimental Designmentioning

confidence: 99%

Prediction and Optimization of Sulphur Trioxide Yield from Calcination of Aluminium Sulfate Using Central Composite Design

Olubajo

Makarfi

2019

PoS

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Sulphur trioxides are common toxic gaseous pollutants which can be produced from alternative routes via calcination of aluminum sulfate derived from kaolin clay. Its demand increases geometrically, thus the need to optimize the yield of SO 3 from the calcination of alum is essential. The rate of alum decomposition was monitored by the formation of SO 3 via thermogravimetric analysis and X-ray fluorescence analysis. This study aimed to evaluate the effect of calcination temperature and curing time on the SO 3 conversion and yields using Face Central Composite Design and optimize the process conditions to evaluate the maximum yield of SO 3 using response surface methodology and its effects and interactions were investigated between 800-900 °C at 60-180 minutes. Results indicated that experimental data satisfied second order polynomial regression model for SO 3 conversion and SO 3 yield from TG analysis while XRF analysis satisfied first order model respectively. An increase in SO 3 conversion and yields was observed as the calcination temperature and time were increased both independently and simultaneously. The calcination temperature was found to have a stronger influence compared to the calcination time. Validation indicated agreement between experimental and predicted values with a regression value of 97.8 %, 97.77 % and 97.67 % for SO 3 conversion, SO 3 yield via TG and XRF analyses respectively. Based on the ANOVA, the SO 3 yield via XRF produced the best model with R 2 pred of 91.98% while SO 3 yield via TG analysis and SO 3 conversion had R 2 pred of 79.99% and 78.01% respectively. Optimization of the production of SO 3 was carried out and the optimal condition for SO 3 conversion, SO 3 yield via TG and XRF analyes were 90.11 %, 91.67 % and 75.81 % respectively at an optimal calcination temperature of 877.43 o C and time of 155.04 minutes respectively.

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“…Optimization was performed to investigate the optimum experimental conditions and biogas yield. It determines the optimum desirability depending on the "goals" set for each of the factors and response [26] & [27]. In this study, the goal for initial pH, solids concentration and waste ratio were set to "in range", whereas the goal for biogas yield was set to "maximize".…”

Section: Acmentioning

confidence: 99%

Biogas Production from Combined Irish Potato and Poultry Wastes: Optimization and Kinetic Studies

Ibrahim¹,

Ahmed²,

Gutti³

et al. 2018

IJET

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The combination of Irish potato waste (IPW) and poultry waste (PW) can form a synergy resulting into an effective substrate for a better biogas production due to some materials they contain. In this work, optimization and kinetic study of biogas production from anaerobic digestion of IPW and PW was investigated. Response surface methodology (RSM) was applied to optimize conditions such as initial pH, solids concentrations and waste ratios. The anaerobic digestion of the two wastes was carried out in the mesophilic condition and Box-Behnken design (BBD) was used to develop and analyze a predictive model which describes the biogas yield. The results revealed that there is a good fit between the experimental and the predicted biogas yield as revealed by the coefficient of determination (R2) value of 97.93%. Optimization using quadratic RSM predicts biogas yield of 19.75% at the optimal conditions of initial pH value 7.28, solids concentration (w/v) 9.85% and waste ratio (IPW:PW) 45:55%. The reaction was observed to have followed a first order kinetics having R2 and relative squared error (RSE) values of 90.61 and 9.63% respectively. Kinetic parameters, such as rate constant and half-life of the biogas yield were evaluated at optimum conditions to be 0.0392 day-1 and 17.68 days respectively. The optimum conditions and kinetic parameters generated from this research can be used to design real bio-digesters, monitor substrate concentrations, simulate biochemical processes and predict performance of bio-digesters using IPW and PW as substrate.

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Application of Response Surface Methodology for Optimization of Reactive Azo Dye Degradation Process by Fenton’s Oxidation

Cited by 16 publications

References 19 publications

Microflora from leaf debris is suitable for treatment of starch industry wastewater

Microflora from leaf debris is suitable for treatment of starch industry wastewater

Prediction and Optimization of Sulphur Trioxide Yield from Calcination of Aluminium Sulfate Using Central Composite Design

Biogas Production from Combined Irish Potato and Poultry Wastes: Optimization and Kinetic Studies

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