Semi-continuous anaerobic digestion of a food industry wastewater in an anaerobic filter

Berardino, Santino Di; Costa, Sara Alexandra Teixeira da; Converti, Attílio

doi:10.1016/s0960-8524(99)00080-2

Cited by 45 publications

(22 citation statements)

References 10 publications

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“…(unpublished data) and Di Berardino et al data [19] (Fig. 3), the error slightly increased when the exact time was used; however, both errors are very similar.…”

Section: Accumulation Methodsmentioning

confidence: 55%

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The Slope Method: A Tool for Analyzing Semi-Continuous Data

Smith

Holtzapple

2010

Appl Biochem Biotechnol

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The MixAlco process is a biorefinery that converts lignocellulose into useful chemicals and hydrocarbon fuels via mixed-acid fermentation. For a semi-continuous-staged fermentation train, during each transfer, discrete amounts of material are moved between fermentors and data are tabulated. Because of natural day-to-day variations, the data are inherently noisy. To calculate performance parameters (e.g., yield, conversion, selectivity, productivity), the average flowrate of each stream component must be determined. To minimize error associated with noise, three data analysis methods were compared: Average, Accumulation, and Slope. The Average method determines the flowrate by averaging the amounts moved each transfer. The Accumulation method stores the solids and liquids that exit the fermentation train in separate vessels. After an extended time period, the mass in each storage vessel is measured so the average flowrate can be calculated. The Slope method calculates the flowrate of material in each stream from the slope of the moving cumulative sum with respect to time. For all three methods, the measured rates were virtually identical; thus accuracy was not affected by the method. However, for the examples presented, the Average method had >40% error and the Slope method <4% error; thus, precision was significantly affected by the method. The Accumulation method calculated the flowrate with a single data point so it is not possible to determine the statistical error.

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“…(unpublished data) and Di Berardino et al data [19] (Fig. 3), the error slightly increased when the exact time was used; however, both errors are very similar.…”

Section: Accumulation Methodsmentioning

confidence: 55%

“…1a of Di Berardino et al [19], and Fig. 3 data set M2 of Alvarez and Lidén [20]) were obtained from the literature.…”

Section: Validationmentioning

confidence: 99%

The Slope Method: A Tool for Analyzing Semi-Continuous Data

Smith

Holtzapple

2010

Appl Biochem Biotechnol

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“…The average of the influent NH 4 ϩ -N concentration was ϳ140 mg/L, and it increased gradually with the depth, apparently because of ammonification. ORP is an excellent indicator for checking system stability and degree of anaerobiosis.…”

Section: Resultsmentioning

confidence: 98%

“…These microbial layers are able to utilize the percolating organics. [3][4][5] The size of the media and the nature of the microbial activity are the two major differences between the trickling filter and aging landfill systems. Although the anaerobic process present in landfill settings has a lower reaction rate, landfill systems operate for long retention times.…”

Section: Introductionmentioning

confidence: 99%

Determination of Schulze Equation for Chemical Oxygen Demand Reduction Using Stabilized Landfill Refuse Media

Fan

2005

Journal of the Air & Waste Management Association

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Three columns each with 770 cm 2 of surface area and 60 -105 cm effective depth were set up for this study. These columns were filled with compacted, stabilized refuse. High-strength brewery wastewaters were uniformly trickled down the medium. Overall, 16 runs with various organic loadings were tested and the results demonstrated that the stabilized refuse had excellent capability in removing chemical oxygen demand (COD). The COD removal efficiency reached 95% at a depth of 60 cm at Q ϭ 8 L/day for the initial COD of ϳ6000 mg/L and the efficiency increased to Ͼ99% at a depth of 90 cm (organic loading of 0.69 kg/m 3 /day). As would be expected, the filter performance is a function of flow rate, influent COD concentration, and bed depth. The Schulze equation is able to predict the COD removal performance well. The variations of pH, oxidation reduction potential, and volatile fatty acids indicated that the acidogenesis reaction occurred in the upper layers. INTRODUCTIONLandfill leachate strength varies with precipitation, dependent on the nature of the municipal solid waste (MSW), the age of the landfill, and the type of land filling,

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“…Mean COD, BOD, TSS and oil and grease values analyzed in the effluent were all in agreement with the standards set by the regulatory authorities. Berardino et al (2000) provided the experimental results of semi-continuous tests of the anaerobic digestion of confectionery wastewater, carried out at different residence times and organic loads in a laboratory-scale upflow anaerobic filter at mesophilic conditions with a working reactor volume of 10 L. COD removal rates didn't fall below 80% under the whole range of conditions, while a maximum removal rate of 92% was achieved. Ozturk & Altinbas (2008) evaluated the treatment performance of one of the main confectionery industries in Turkey.…”

Section: Anaerobic Treatment Applications For the Treatment Of Confecmentioning

confidence: 99%