Biogas Production Optimization in the Anaerobic Codigestion Process: A Critical Review on Process Parameters Modeling and Simulation Tools

IF 2.8 4区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY Journal of Chemistry Pub Date : 2024-04-08 DOI:10.1155/2024/4599371
Mohammed Kelif Ibro, Venkata Ramayya Ancha, Dejene Beyene Lemma
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Abstract

Many operational parameters, either discretely or collectively, can influence the biodegradation performance towards enhancing biogas yield and quality. Among the operating parameters, organic loading rate (OLR), inoculum-substrate ratio, and carbon-nitrogen ratio (C/N) are the most critical parameters in the optimization and enhancement of biogas yield. Optimization of the biogas production processes depends on the ability of anaerobic microorganisms to respond to variations in operational parameters such as pH, redox potential, and intermediate products to enhance the biogas yield. This review article focuses on the role of process parameters, kinetic models, artificial intelligence, Aspen Plus (AP), and anaerobic digestion model no. 1 (ADM1) in optimizing biogas yield via an anaerobic codigestion (AcoD) process. The review showed that biomaterials codigestion upgraded biogas yield to the extent of 400%, and organic removal efficiency reached up to 90% compared to a single substrate. In addition, the current work has verified that the kinetic model is the most effective tool for signifying that the hydrolysis phase is the rate-limiting step, whereas AP is the most effective tool in the design and optimization of the AcoD process parameters. The reviewed kinetic and AI models show strong correlation values ranging from 0.931 to 0.9991 and 0.8700 to 0.9998, respectively. The AcoD system involves complex chemical reactions, but AP might have limitations in representing such complex chemical processes with nonideal behavior and complicated reaction mechanisms. The design and optimization of AcoD with reliable input parameters are highly limited or nonexistent. The AcoD process design with AP opens fresh research opportunities, including improved efficiency, finding appropriate retention time, and saving time, as well as finding the optimum biogas yield. This review article gives an insightful understanding of AcoD process parameter optimization and valuable strategies for policy development enhancing sustainability in the biogas sector.
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厌氧联合消化工艺中的沼气生产优化:工艺参数建模和仿真工具评述
许多操作参数,无论是单独的还是集体的,都会影响生物降解性能,从而提高沼气产量和质量。在这些操作参数中,有机负荷率(OLR)、接种物与基质比和碳氮比(C/N)是优化和提高沼气产量的最关键参数。沼气生产过程的优化取决于厌氧微生物对 pH 值、氧化还原电位和中间产物等操作参数变化的反应能力,以提高沼气产量。这篇综述文章的重点是工艺参数、动力学模型、人工智能、Aspen Plus(AP)和厌氧消化模型 No.1(ADM1)在通过厌氧消化(AcoD)工艺优化沼气产量方面的作用。研究结果表明,与单一基质相比,生物材料联合消化可将沼气产量提高 400%,有机物去除效率高达 90%。此外,目前的工作还验证了动力学模型是表明水解阶段是限速步骤的最有效工具,而 AP 则是设计和优化 AcoD 工艺参数的最有效工具。经审查的动力学模型和人工合成模型分别显示出 0.931 至 0.9991 和 0.8700 至 0.9998 的强相关值。AcoD 系统涉及复杂的化学反应,但 AP 在表示这种具有非理想行为和复杂反应机制的复杂化学过程时可能存在局限性。使用可靠的输入参数进行 AcoD 的设计和优化非常有限或根本不存在。使用 AP 进行 AcoD 工艺设计开辟了新的研究机会,包括提高效率、寻找合适的停留时间、节省时间以及寻找最佳沼气产量。这篇综述文章深入浅出地介绍了 AcoD 工艺参数优化和有价值的沼气行业可持续发展政策制定策略。
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来源期刊
Journal of Chemistry
Journal of Chemistry CHEMISTRY, MULTIDISCIPLINARY-
CiteScore
5.90
自引率
3.30%
发文量
345
审稿时长
16 weeks
期刊介绍: Journal of Chemistry is a peer-reviewed, Open Access journal that publishes original research articles as well as review articles in all areas of chemistry.
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