Methane production improvement by modulation of solid phase immersion in dry batch anaerobic digestion process: Dynamic of methanogen populations
Introduction
Anaerobic digestion (AD) process is achieved by a consortium of microorganisms degrading organic matter of waste to produce a biogas composed of 50–70% of methane (valorized in electricity and heating) and a digestate with high agronomic values (used as a fertilizer). Several technologies of dry AD process are implemented according to the process temperature, the step number, the reactor configuration and the presence of mixing system. Dry anaerobic digestion generally occurs on waste with a total solid content superior to 15% (agricultural waste, food waste and industrial waste) (Karthikeyan and Visvanathan, 2013). Liquid phase is usually minimized in dry AD process, implying several constraints in process as humidity, temperature and microorganism repartitions. The liquid quantity improves biogas production (El-Mashad et al., 2006) by transporting and spreading microorganisms and metabolites in media (El-Mashad et al., 2006, Kusch et al., 2009, Shahriari et al., 2012). Increasing the recirculation frequency of inoculum improves the methane production until the second peak of methane flow in dry AD process (André et al., 2015).
A linear relation between water content and methanogenic activity has been established by Le Hyaric et al. (2011). Moreover, a high total solid content impacts on biogas production (Abbassi-Guendouz et al., 2012).
These phenomena understanding are possible due to the molecular biology methods developed since the 90’s. Furthermore, anaerobic microorganisms cultivation is difficult. Biomolecular tools can be used to monitor the process, to optimize anaerobic digestion and detect a potential drift of the process (Karakashev et al., 2005, Yu et al., 2005, Demirel and Scherer, 2008, Lee et al., 2009, Ike et al., 2010, Traversi et al., 2011, Traversi et al., 2012, Merlino et al., 2013, Williams et al., 2013, Guo et al., 2014, Town et al., 2014).
Methanogenic groups include the acetotrophic methanogens which transform acetate into methane and carbon dioxide (Ferry, 1992), and with the hydrogenotrophic methanogens which transform hydrogen and carbon dioxide into methane. The acetotrophic methanogens are always present in AD process. Operating and environmental parameters influence the activity and the diversity of methanogens. Karakashev et al. (2005) have used fluorescence in situ hybridization to observe the methanogenic diversity of 15 Danish biogas plants treating 50–500 tons of feedstock per day. These biogas plants have been operated at different conditions (temperature, hydraulic retention time and biogas production) implying the dominance of different methanogens orders. Diversity of methanogens depends on inoculum source and waste. Hydrogenotrophic methanogens ensure the stability and the efficiency of the AD process (Demirel and Scherer, 2008). A comparison between a single stage thermophilic and a two stage thermophilic AD process treating cattle manure has shown a similar range of hydrogenotrophic methanogens demonstrating that the reactor configuration in this case does not have any impact on the process (Nielsen et al., 2004).
Most of the studies analyze methanogenic dynamic in liquid processes; few data are available on dry processes. Degueurce et al. (2016) have quantified the bacterial and the archaeal communities on cattle manure in dry AD process. Dry batch AD process could be monitored, optimized and managed by using molecular biology.
The aim of this study was to optimize a dry batch AD process by modulation of the immersed part of cattle manure by using biomolecular tools, firstly to observe the consequence on the methane production and, secondly to understand methanogenic dynamic according to the reactor configuration. 60 L dry batch anaerobic reactors were implemented with two different configurations, with or without liquid reserve modulating the solid phase immersion. As a first step, DNA extractions of inoculum and cattle manure were optimized changing several parameters (thermal shock, mechanic shock). The quantitative real time PCR (qPCR) of methanogenic populations targeting 16S rRNA was implemented to quantify total Archaea, four orders of methanogens whether Methanococcales, Methanomicrobiales, Methanobacteriales, Methanosarcinales, and two families such as Methanosaetaceae and Methanosarcinaceae. An external validation of DNA extraction and qPCR method were made by an external laboratory. Methanogenic compositions of inoculum used in these experiments have then been compared to fresh manure and inoculum at the end of anaerobic digestion. The dynamic of methanogen populations was studied in order to explain the methane production difference between two reactor configurations according to the immersion of solid phase.
Section snippets
Chemical and microbial characterizations
Total solid (TS) and volatile solid (VS) contents were analyzed on cattle manure (22.0 ± 0.5% TS; 89.4 ± 0.6% VS) and inoculum (2.10 ± 0.5% TS; 54.2 ± 0.3% VS) at 105 °C during 12 h and 550 °C during 2 h, respectively relative to the standard methods (APHA, 1998, AFNOR NF U44-160, 1985). Analyses were made in duplicate.
Before anaerobic digestion, cattle manure (around 1 kg) and inocula (around 1 L) were sampling according to a sampling plan (Gy, 1988), in order to analyze the methanogen dynamics by the qPCR
DNA extraction validation
The both DNA extraction protocols were compared between the method described in Section 2.2.2, named as “optimized method” (column A) and the classical extraction method (column C) (Table 2). In this first part, the qPCR step was achieved by the ITE laboratory for both extraction protocols. The quantity of 16S rRNA gene copies with optimized method was higher than the classical method (about 100 times). The coefficient of variation was below 11% showing a low dispersion. The parameters of cell
Conclusions
The solid phase immersion was essential to produce more methane in dry AD process. DNA extraction and qPCR method were implemented and validated to quantify methanogens in liquid and solid phases during dry AD. Final quantities of methanogens converged toward the same level in several inocula at the end of AD. In liquid phase, methanogen dynamic showed few variations. Bio-molecular study of solid phase revealed a strong variation of Methanomicrobiales and Methanosarcinaceae. The improvement of
Acknowledgements
The authors want to thank Conseil Régional de Picardie for the financial support of this work and ANRT for the Ph.D grant of Laura André. The authors thank also Samir Dou for his help, Camille Brun and Quentin André for their careful reading of this manuscript.
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