Biogas circulation for improving the promotive effect of zero-valent iron on anaerobic digestion of swine manure

Hou, Yaoqi; Xia, Qing; Zhang, Biao; Bian, Yixuan; Lei, Zhongfang; Huang, Weiwei

doi:10.1016/j.biteb.2022.101319

Cited by 2 publications

(1 citation statement)

References 52 publications

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“…The working volume reduction of the reactor is due to the accumulation of material at its bottom and directly affects the CH 4 production of the plant by altering the organic loading rate (OLR) and hydraulic retention time (HRT). Proper mixing usually enhances CH 4 production by improving the substrate, enzyme and microorganism distribution through the formation of a homogenous mixture, wherein the solids retention time (SRT) equals the HRT [35,36]. Nonetheless, inadequate mixing conditions usually lead to solid stratification, formation of dead zones, and accumulation of material in sections where the agitation system is ineffective and at the bottom of the reactor; thus, SRT differs from HRT [29,35].…”

Section: Introductionmentioning

confidence: 99%

Simulation of the Working Volume Reduction through the Bioconversion Model (BioModel) and Its Validation Using Biogas Plant Data for the Prediction of the Optimal Reactor Cleaning Period

Tsitsimpikou,

Kalamaras,

Lithourgidis

et al. 2023

Sustainability

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The present study focuses on the working volume reduction of anaerobic reactors in biogas plants, which is caused by inorganic material accumulation and inadequate mixing and affects methane production and plant profitability. Precipitation phenomena lead to periodic reactor cleaning processes, which complicate the operation of the plant and increase its operating costs. For this purpose, the bioconversion model (BioModel) was utilized by modifying its conditions to accurately simulate the reduction of the working volume of a biogas plant facing precipitation problems for a study period of 150 days. The modified BioModel exhibited notable results in the prediction of methane production, with an average deviation of 1.97% from the plant’s data. After validation, based on the model results, an equation was set up to predict the optimal reactor cleaning period. Incidentally, the optimal cleaning time was calculated at 5.1 years, which is very close to the period during which the cleaning of the reactors of the studied biogas plant took place (5.5 years). The findings of this research showed that the modified BioModel, along with the developed equation, can be effectively used as a tool for the prediction of the optimal reactor cleaning period.

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