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首页> 外文期刊>Bioresource Technology: Biomass, Bioenergy, Biowastes, Conversion Technologies, Biotransformations, Production Technologies >Statistical modeling and optimization of biomass granulation and COD removal in UASB reactors treating low strength wastewaters
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Statistical modeling and optimization of biomass granulation and COD removal in UASB reactors treating low strength wastewaters

机译:UASB反应器中处理低浓度废水的生物质制粒和COD去除的统计模型和优化

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The aim of this work was to study the influence of influent chemical oxygen demand (COD), upflow velocity of wastewater, and cationic polymer additives in inoculum, on biomass granulation and COD removal efficiency in upflow anaerobic sludge blanket (UASB) reactor for treating low strength wastewater. Statistical models were formulated based on these three variables to optimize the biomass granulation and COD removal efficiency in UASB reactors using a two-level, full factorial design. For the thick inoculum used in this study, having suspended solids (SS) >80 g/l and volatile suspended solids (VSS) to SS ratio <0.3, cationic polymer additives in the inoculum showed adverse effect on biomass granulation and COD removal efficiency. It is concluded that for such thick inoculum, granulation can be obtained while treating low strength Wastewaters in UASB reactor by selecting proper combination of influent COD and liquid upflow velocity so as to represent the organic loading rate (OLR) greater than 1.0 kg COD/m(3) d. Validation of model predictions for treatment of synthetic wastewater and actual sewage reveals the efficacy of these models for enhancing granulation and COD removal efficiency. (C) 2007 Elsevier Ltd. All rights reserved.
机译:这项工作的目的是研究进水厌氧污泥床(UASB)反应器中进水化学需氧量(COD),废水的上流速度和接种物中阳离子聚合物添加剂对上流厌氧污泥床(UASB)反应器中生物质颗粒化和COD去除效率的影响。强度废水。基于这三个变量,建立了统计模型,以采用两级全因子设计优化UASB反应器中的生物质颗粒化和COD去除效率。对于本研究中使用的浓稠接种物,其悬浮固体(SS)> 80 g / l,而挥发性悬浮固体(VSS)与SS的比率<0.3,则接种物中的阳离子聚合物添加剂对生物质颗粒化和COD去除效率产生不利影响。结论是,对于这样厚的接种物,通过选择进水COD和液体上流速度的适当组合代表有机负荷率(OLR)大于1.0 kg COD / m,可以在UASB反应器中处理低浓度废水的同时获得制粒作用(3)d。对用于处理合成废水和实际污水的模型预测的验证揭示了这些模型在提高制粒和去除COD效率方面的功效。 (C)2007 Elsevier Ltd.保留所有权利。

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