生物反应器
废水
过程(计算)
污水处理
生化工程
膜生物反应器
废水回用
无氧运动
工艺工程
环境科学
化学
工程类
废物管理
计算机科学
生物
操作系统
有机化学
生理学
作者
Chungheon Shin,Sebastien Tilmans,Felipe Chen,Craig S. Criddle
标识
DOI:10.1016/j.cej.2021.131912
摘要
• A model was developed to simulate system-level performance of AnMBRs. • Membrane pore sizes affects hydrolysis of particulate and colloidal COD. • The model is applicable to both CSTR-AnMBR and SAF-MBR configurations. • Independently acquired parameters were used to predict SAF-MBR performance. • The developed model simulates dynamic performance of the AnMBR with <10% error. Anaerobic treatment of municipal wastewater that produces energy and low levels of biosolids for disposal has the potential to replace conventional aerobic processes. Here we propose a generic model for anaerobic membrane bioreactors (AnMBRs) that incorporates hydrolysis and dispersed growth microbial metabolism of particulate and soluble substrates, including a size-exclusion constraint based upon the pore size of submerged membranes. The model can be expanded to include attached growth systems, such as anaerobic fluidized bed reactors (AFBRs) within the staged anaerobic fluidized membrane bioreactor (SAF-MBR) system. Model development entailed: (1) acquisition of key kinetic metabolic parameters based on independent batch studies, (2) creation of a matrix of metabolic processes, and (3) development of a model that describes the relevant mass balances in the system. The utility of the model is demonstrated for dynamic simulations of a pilot-scale second generation SAF-MBR treating municipal wastewater (SAF-MBR 2.0). System outputs include the COD of the system effluent (= permeate), recirculated bulk COD and MLSS, gas production rate and composition, and dissolved methane concentration. These parameters are critical for system design and assessment. Predictions of performance by a pilot-scale system agreed well with monitored values, typically with less than 10% error, indicating that the developed model and independent batch assays for model calibration can enable reliable systems-level performance simulations.
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