Strategic Water Infrastructure Laboratory, University of Wollongong, Wollongong, NSW 2522, Australia.
Civil Engineering, College of Engineering and Informatics, National University of Ireland, Galway, Ireland.
Bioresour Technol. 2016 Dec;222:498-512. doi: 10.1016/j.biortech.2016.10.015. Epub 2016 Oct 6.
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.
厌氧共消化（AcoD）是一种实用的方法，可以同时管理有机废物并生产可再生能源。本综述表明需要提高 AcoD 建模能力，以模拟复杂的物理化学和生物化学过程。与单消化相比，AcoD 更容易受到过程不稳定的影响，因为它在更高的有机负荷和基质组成的显著变化下运行。这里提供的数据证实，对于 AcoD 的优化，模拟 pH 值和抑制性中间产物（如氨和有机酸）的瞬时变化是至关重要的。基于 ADM1 框架的机理模型已成为 AcoD 建模的规范。然而，当前 AcoD 模型中的关键特征，特别是系统性能与共底物特性、有机负荷和抑制机制之间的关系，仍未得到充分发展。还需要通过考虑 AcoD 过程中硫、磷和氮的转化和分布来预测沼气的数量和成分以及生物固体的质量。
