Anaerobic co-digestion: A critical review of mathematical modelling for performance optimization. (December 2016)

• Record Type: Journal Article
• Authors: Xie, Sihuang; Hai, Faisal I.; Zhan, Xinmin; Guo, Wenshan; Ngo, Hao H.; Price, William E.; Nghiem, Long D.
• Is Part Of: Bioresource technology. Volume 222(2016)
• Page Start: 498
• Page End: 512
• Publication Date: 2016-12
• Subjects: Anaerobic co-digestion -- Biosolids quality -- Mathematical modelling -- Process stability -- Nutrient recovery -- Sewage sludge; Biomass -- Periodicals; Biomass energy -- Periodicals; Bioremediation -- Periodicals; Agricultural wastes -- Periodicals; Factory and trade waste -- Periodicals; Organic wastes -- Periodicals; Bioénergie -- Périodiques; Déchets agricoles -- Périodiques; Déchets industriels -- Périodiques; Déchets organiques -- Périodiques; Déchets (Combustible) -- Périodiques; 662.88
• DOI: 10.1016/j.biortech.2016.10.015
• Languages: English
• ISSNs: 0960-8524

Abstract

Highlights: AcoD operates at high OLRs under diverse co-substrates' properties and composition. Modelling requirements for AcoD are more complex than mono-digestion. pH variation & inhibitory intermediate accumulation are essential for AcoD modelling. ADM1-based model is sophisticated and an improved practicality is required for AcoD. Conversion & distribution of S, P, and N are underdeveloped in current AcoD models. Abstract: Anaerobic co-digestion (AcoD) is a pragmatic approach to simultaneously manage organic wastes and produce renewable energy. This review demonstrates the need for improving AcoD modelling capacities to simulate the complex physicochemical and biochemical processes. Compared to mono-digestion, AcoD is more susceptible to process instability, as it operates at a higher organic loading and significant variation in substrate composition. Data corroborated here reveal that it is essential to model the transient variation in pH and inhibitory intermediates (e.g. ammonia and organic acids) for AcoD optimization. Mechanistic models (based on the ADM1 framework) have become the norm for AcoD modelling. However, key features in current AcoD models, especially relationships between system performance and co-substrates' properties, organic loading, and inhibition mechanisms, remain underdeveloped. It is also necessary to predict biogas quantity and composition as well as biosolids quality by considering the conversion and distribution of sulfur, phosphorus, and nitrogen during AcoD.