Modelling Biogas Fermentation from Anaerobic Digestion: Potato Starch Processing Wastewater Treated Within an Up flow Anaerobic Sludge Blanket

Philip Antwi, Jianzheng Li, E. Shi, P. Boadi, Frederick Ayivi
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引用次数: 3

Abstract

Herein, a modeling approach to predict biogas yield within a mesophilic (35 ± 1°C) upflow anaerobic sludge blanket (UASB) reactor treating potato starch processing wastewater (PSPW) for pollutant removal was conducted. HRTs and seven anaerobic process-related parameters viz; chemical oxygen demand (COD), ammonium (), alkalinity, total Kjeldahl Nitrogen, total phosphorus, volatile fatty acids (VFAs) and pH with average concentration of 4028.91, 110.09, 4944.67, 510.47, 45.20, 534.44 mg/L and 7.09, respectively, were used as input variables (x) to develop stochastic models for predicting biogas yield from the anaerobic digestion of PSPW. Based on the prediction accuracy of the models, it was established that, prediction of biogas yield from the UASB with the combination of COD, NH4+ and HRT, or COD, NH4+, HRT and VFAs as input variables proved more efficient as opposed to HRT, alkalinity, total Kjeldahl Nitrogen, total phosphorus and pH. Highest coefficient of determination (R2) observed was 97.29%, suggesting the efficiency of the models in making predictions. The developed models efficiencies concluded that the models could be employed to control the dynamic anaerobic process within UASBs since prediction of biogas obtained in the UASB agreed with the experimental result.
厌氧消化沼气发酵模拟:马铃薯淀粉加工废水在上流厌氧污泥毯内处理
本文采用中温(35±1°C)上流式厌氧污泥毯(UASB)反应器处理马铃薯淀粉加工废水(PSPW)去除污染物,建立了预测沼气产量的建模方法。hrt和7个厌氧工艺相关参数;以平均浓度分别为4028.91、110.09、4944.67、510.47、45.20、534.44 mg/L和7.09的化学需氧量(COD)、铵盐(铵)、碱度、总凯氏定氮(kkeldahl Nitrogen)、总磷(total phosphorus)、挥发性脂肪酸(volatile fatty acids, VFAs)和pH为输入变量(x),建立预测PSPW厌氧消化产气量的随机模型。结果表明,以COD、NH4+和HRT组合或COD、NH4+、HRT和VFAs为输入变量预测UASB沼气产量比以HRT、碱度、总凯氏定氮、总磷和ph为输入变量的预测效率更高,最高决定系数(R2)为97.29%,说明模型的预测效率较高。建立的模型的效率表明,该模型可以用于控制UASB内的动态厌氧过程,因为在UASB中获得的沼气预测与实验结果一致。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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