A novel approach for the fractionation of organic components and microbial degraders in ADM1 and model validation based on the methanogenic potential

分馏 厌氧消化 化学 产甲烷 甲烷 环境化学 色谱法 有机化学
作者
Wenjie Guo,Dunjie Li,Zhipeng Zhang,Rongrong Mo,Yongzhen Peng,Yongmei Li
出处
期刊:Water Research [Elsevier]
卷期号:236: 119945-119945 被引量:6
标识
DOI:10.1016/j.watres.2023.119945
摘要

The anaerobic digestion model No 1 (ADM1), with fixed fractions of the substrate components, is currently used to simulate methane production during the anaerobic digestion (AD) of waste activated sludge (WAS). However, the goodness-of-fit for the simulation is not ideal due to the different characteristics of WAS from different regions. In this study, a novel methodology based on a modern instrumental analysis and 16S rRNA gene sequence analysis for the fractionation of organic components and microbial degraders in the WAS is investigated to modify the fractions of the components in the ADM1. The combination of Fourier transform infrared (FTIR), X-ray photoelectron spectroscopy (XPS), and nuclear magnetic resonance (NMR) analyses were used to achieve a rapid and accurate fractionation of the primary organic matters in the WAS that was verified using both the sequential extraction method and the excitation-emission matrix (EEM). The protein, carbohydrate, and lipid contents in the four different sludge samples measured using the above combined instrumental analyses were 25.0 – 50.0%, 2.0 – 10.0%, and 0.9 – 2.3%. The microbial diversity based on 16S rRNA gene sequence analysis was utilized to re-set the initial fractions of the microbial degraders in the ADM1. A batch experiment was utilized to further calibrate the kinetic parameters in the ADM1. Based on the above optimization of the stoichiometric and kinetic parameters, the ADM1 with full parameter modification for WAS (ADM1-FPM) simulated the methane production of the WAS very well with a Theil's inequality coefficient (TIC) of 0.049, which was increased by 89.8% than that of the default ADM1 fit. The proposed approach, with its rapid and reliable performance, demonstrated a strong application potential for the fractionation of organic solid waste and the modification of ADM1, which contributed to a better simulation of methane production during the AD of organic solid wastes.
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