ABSTRACT
Anaerobic digestion (AD) has become a popular technique for organic waste management while offering economic and environmental advantages. As AD becomes increasingly prevalent worldwide, research efforts are primarily focused on optimizing its processes. During the operation of AD systems, the occurrence of unstable events is inevitable. So far, numerous conclusions have been drawn from full and lab-scale studies regarding the driving factors of start-up perturbations. However, the lack of standardized practices reported in start-up studies raises concerns about the comparability and reliability of obtained data. This study aims to develop a knowledge database and investigate the possibility of applying machine learning techniques on experimentation-extracted data to assist start-up planning and monitoring. Thus, a standardized database referencing 75 cases of start-up of one-stage wet continuously-stirred tank reactors (CSTR) processing agricultural, industrial, or municipal organic effluent in mono-digestion from 31 studies was constructed. 10 % of the total observations included in this database concern failed start-up experiments. Then, correlations between the parameters and their impacts on the start-up duration were studied using multivariate analysis and a model-based ranking methodology. Insights into trends of choices were highlighted through the correlation analysis of the database. As such, scenarios favoring short start-up duration were found to involve relatively low retention times (average initial and final hydraulic retention times, (HRTi) and (HRTf) of 26.25 and 20.6 days, respectively), high mean organic loading rates (average OLRmean of 5.24 g VS·d-1·L -1) and the processing of highly fermentable substrates (average feed volatile solids (VSfeed) of 81.35 g L-1). The model-based ranking of AD parameters demonstrated that the HRTf, the VSfeed, and the target temperature (Tf) have the strongest impact on the start-up duration, receiving the highest relative scores among the evaluated AD parameters. The database could serve as a reference for comparison purposes of future start-up studies allowing the identification of factors that should be closely controlled.
Subject(s)
Bioreactors , Anaerobiosis , Waste Management/methodsABSTRACT
Up to half of the organic fraction of an urban wastewater is made up of particulate settleable solids (PSS). In activated sludge process (AS) this material is rapidly adsorbed on to microbial flocs but is only slowly and partially degraded. To better understand and predict the degradation kinetics observed, a determination of the proportion of hydrolytic bacteria is required. As inoculum is usually added in the biodegradation tests, a comparison is required between the roles of bacteria introduced with the inoculum and those attached to the substrate. In this work, respirometric batch experiments were performed on PSS collected from upstream or downstream of the sewers of Toulouse city. Toilet paper (TP) and cellulose, two model particulate substrates, were also investigated. To understand the role of the active biomass in hydrolysis, increasing concentrations of AS were added to a certain amount of PSS or TP. No correlation was observed between the concentration of AS and the rate and duration of degradation of the particulate matter. Simulations performed after calibration of the model ASM-1 allowed the fraction of hydrolytic bacteria to be estimated in both the substrate and the AS-inoculum. Only a very small fraction of the bacteria of AS and of the substrate samples were found to be efficient for hydrolysis. Hydrolysis was mainly initiated by a small proportion of the microorganisms, and especially by cells already attached to PSSs. Moreover, the fraction of bacteria able to hydrolyse large particles present in an inoculum of AS depended on the initial contamination of the surface of the particles.
