Optimization of biogas productivity in lab-scale by response surface methodology

Safari, Mahmood; Abdi, Reza; Adl, Mehrdad; Kafashan, Jalal

doi:10.1016/j.renene.2017.11.025

Cited by 58 publications

(26 citation statements)

References 14 publications

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“…Response Surface Optimisation of Biogas Potential in Co-Digestion of Miscanthus Fuscus and Cow Dung there is a relationship between the independent variables and the response, which explains the adequacy of the regression model (Safari et al, 2018). Thus, the experimental data points closer to the line of best fits indicated, the data was well fitted onto the model.…”

mentioning

confidence: 85%

“…Some of these widespread research technologies of renewable energy resources include municipal solid wastes, animal manures, fish waste, agricultural waste (El-Mashad & Zhang, 2010;Li et al, 2010) from a variety of feedstocks (Armah et al, 2017). However, the volume of livestock manure like cow dung is escalating, and inappropriate disposal can lead to adverse environmental and health problems such as eutrophication (Safari et al, 2018). In the same context,, Miscanthus Fuscus is a bamboo-like plant that grows rapidly up to 3 meters, generating a high yield of biomass with low ash content, suitable for use in electricity generation (Khanal, 2008;Sawatdeenarunat et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…The three-dimensional (3D) plot (a) shows the response surface for investigating the interactive effect of the pH and F/I ratio, and the 3D plot (b) shows the temperature and F/I ratio to maximise the biogas production within the experimental ranges. It is observed that the F/I ratio was the main contributing factor (Safari et al, 2018). Therefore, in finding the solution of the operating conditions, and with the desired goal of the model to maximise the biogas production, the optimum values for the process variables.…”

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confidence: 99%

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Response Surface Optimisation of Biogas Potential in Co-Digestion of Miscanthus Fuscus and Cow Dung

Tetteh¹,

Amano²,

Asante-Sackey³

et al. 2018

IJTech

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In this study, the effects of co-digestion operating conditions for the enhancement of biogas production from Miscanthus Fuscus mixed with cow dung, was investigated. The aforementioned organic wastes are good substrate resources for anaerobic co-digestion (AD) due to their high content of easily biodegradable materials. This source of effective and ecofriendly technology as AD is for generating energy from organic waste. Response surface methodology (RSM) based on the Box-Behnken (BBD) design was employed to evaluate and optimise four process variables: pH, temperature, and hydraulic retention time (HRT) and feedstock inoculum (F/I) ratio on the biogas production. This study signifies the interactions between the process conditions, and identifies the most significant variables of control in order to maximise the biogas production. A developed regression model established the relationship between the significant effect of the input variables and the response. The analysis of variance (ANOVA) showed a high coefficient of determination value (R 2 = 0.9997) at 95% confidence level. The results show that the F/I ratio has a major impact on biogas production. The model developed predicted values which were well fitted (P<0.005) with the values obtained from the experimental data. Thus, the regression model confirmed findings. The RSM and BBD employed proved to be economical and a reliable tool for modelling, optimizing and studying the interactive effects of the four process factors (pH, temperature, HRT and F/I ratio) for the biogas production.

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confidence: 85%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Response Surface Optimisation of Biogas Potential in Co-Digestion of Miscanthus Fuscus and Cow Dung

Tetteh¹,

Amano²,

Asante-Sackey³

et al. 2018

IJTech

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“…The significance of interaction terms justifies the hypothesis 243 that optimization study should consider both the main factors and interaction terms to sufficiently 244 explain the washing condition. The calculated lack of fit F-value of 1.12 is not significant 245 compared to the pure error which is good, as we want the model to fit the response and there is a 246 46% chance that an F value this large could happen due to noise (Safari et al 2018).…”

Section: Diesel Removal (%) =mentioning

confidence: 92%

Peer Review #1 of "Optimization of aeration enhanced surfactant soil washing for remediation of diesel-contaminated soils using response surface methodology (v0.1)"

Ali¹

2020

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Surfactant-enhanced soil washing has been used for remediation of organic pollutants for an extended period, but its effectiveness and wide application was limited by the high concentration of surfactants utilized. In this work, the efficiency of conventional soil washing performance was enhanced by 12-25% through the incorporation of air bubbles into the low concentration surfactant soil washing system. Surfactant selection preexperiment using aerated and conventional soil washing reveals Brij 35 > TX100 > Tween 80 > Saponin in diesel oil removal. Optimization of the effect of time, surfactant concentration, pH, agitation speed, and airflow rate in five levels were undertaken using Response Surface Methodology (RSM) and Central composite design (CCD). The optimum degree of variables achieved was 90 min of washing time, 370 mg/l of concentration, washing pH of 10, 535 rpm of agitation speed and 7.2 l/min of airflow rate with 79.5 % diesel removal. The high predicted R 2 value of 0.9517 showed that the model could efficiently be used to predict diesel removal efficiency. The variation in efficiency of aeration assisted and conventional soil washing was variable depending on the type of surfactant, organic matter content of the soil, particle size distribution and level of pollutant weathering. The difference in removal efficiency of the two methods increases when the level of organic matter increases and when the particle size and age of contamination decreases. Abstract 18 Surfactant-enhanced soil washing has been used for remediation of organic pollutants for an extended period, but its 19 effectiveness and wide application was limited by the high concentration of surfactants utilized. In this work, the 20 efficiency of conventional soil washing performance was enhanced by 12-25% through the incorporation of air 21 bubbles into the low concentration surfactant soil washing system. Surfactant selection pre-experiment using aerated 22 and conventional soil washing reveals Brij 35 > TX100 > Tween 80 > Saponin in diesel oil removal. Optimization of 23 the effect of time, surfactant concentration, pH, agitation speed, and airflow rate in five levels were undertaken using 24 Response Surface Methodology (RSM) and Central composite design (CCD). The optimum degree of variables 25 achieved was 90 min of washing time, 370 mg/l of concentration, washing pH of 10, 535 rpm of agitation speed and 26 7.2 l/min of airflow rate with 79.5 % diesel removal. The high predicted R 2 value of 0.9517 showed that the model 27 could efficiently be used to predict diesel removal efficiency. The variation in efficiency of aeration assisted and 28 conventional soil washing was variable depending on the type of surfactant, organic matter content of the soil, particle 29 size distribution and level of pollutant weathering. The difference in removal efficiency of the two methods increases 30 when the level of organic matter increases and when the particle size and age of contamination decreases.

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“…Hence, the importance of research on the methodology of biogas production in small volumes. An example here may be seen in the latest literature, which addresses the subject of research in the laboratory scale of anaerobic digestion [39][40][41][42][43].…”

Section: Group Of Laboratorymentioning

confidence: 99%

Methodical Aspects of Biogas Production in Small-Volume Bioreactors in Laboratory Investigations

Kasprzycka

Kuna

2018

Energies

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The aim of this study was to develop a methodology to investigate the biofermentation process in small-volume fermenters. Dark serum bottles with a volume of 100-120 mL, tightly sealed with a rubber septum, were used as bioreactors. The optimum measurement conditions in this type of bioreactor comprise: (i) filling two-thirds of the maximum volume with a suspension; (ii) a 2% bioreactor loading (on a dry basis) and; (iii) the daily equalization of pressure by removing the biogas through the septum pierced with a syringe needle and the intensive mixing of the remaining suspension. The methane yield (quantity and dynamics) obtained in this type of bioreactor is analogous to that of industrial bioreactors or large-scale laboratory bioreactors. The use of small-volume bioreactors that can be incubated will facilitate the preliminary selection of analysed systems and provide an indication of those that should be investigated in large-scale bioreactors.

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Optimization of biogas productivity in lab-scale by response surface methodology

Cited by 58 publications

References 14 publications

Response Surface Optimisation of Biogas Potential in Co-Digestion of Miscanthus Fuscus and Cow Dung

Response Surface Optimisation of Biogas Potential in Co-Digestion of Miscanthus Fuscus and Cow Dung

Peer Review #1 of "Optimization of aeration enhanced surfactant soil washing for remediation of diesel-contaminated soils using response surface methodology (v0.1)"

Methodical Aspects of Biogas Production in Small-Volume Bioreactors in Laboratory Investigations

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