Overcoming organic and nitrogen overload in thermophilic anaerobic digestion of pig slurry by coupling a microbial electrolysis cell

The combination of the anaerobic digestion (AD) process with a microbial electrolysis cell (MEC) coupled to an ammonia stripping unit as a post-treatment was assessed both in series operation, to improve the quality of the effluent, and in loop configuration recirculating the effluent, to increase the AD robustness. The MEC allowed maintaining the chemical oxygen demand removal of the whole system of 46 ± 5% despite the AD destabilization after doubling the organic and nitrogen loads, while recovering 40 ± 3% of ammonia. The AD-MEC system, in loop configuration, helped to recover the AD (55% increase in methane productivity) and attained a more stable and robust operation. The microbial population assessment revealed an enhancement of AD methanogenic archaea numbers and a shift in eubacterial population. The AD-MEC combined system is a promising strategy for stabilizing AD against organic and nitrogen overloads, while improving the quality of the effluent and recovering nutrients for their reutilization.Postprint (author's final draft

Unravelling the active microbial community in a thermophilic anaerobic digester-microbial electrolysis cell coupled system under different conditions

Thermophilic anaerobic digestion (AD) of pig slurry coupled to a microbial electrolysis cell (MEC) with a recirculation loop was studied at lab-scale as a strategy to increase AD stability when submitted to organic and nitrogen overloads. The system performance was studied, with the recirculation loop both connected and disconnected, in terms of AD methane production, chemical oxygen demand removal (COD) and volatile fatty acid (VFA) concentrations. Furthermore, the microbial population was quantitatively and qualitatively assessed through DNA and RNA-based qPCR and high throughput sequencing (MiSeq), respectively to identify the RNA-based active microbial populations from the total DNA-based microbial community composition both in the AD and MEC reactors under different operational conditions. Suppression of the recirculation loop reduced the AD COD removal efficiency (from 40% to 22%) and the methane production (from 0.32 to 0.03 m3m-3d-1). Restoring the recirculation loop led to a methane production of 0.55 m3m-3d-1concomitant with maximum MEC COD and ammonium removal efficiencies of 29% and 34%, respectively. Regarding microbial analysis, the composition of the AD and MEC anode populations differed from really active microorganisms. Desulfuromonadaceae was revealed as the most active family in the MEC (18%–19% of the RNA relative abundance), while hydrogenotrophic methanogens (Methanobacteriaceae) dominated the AD biomass.Postprint (author's final draft

Nitrogen removal in a two-chambered microbial fuel cell: Establishment of a nitrifying-denitrifying microbial community on an intermittent aerated cathode

A microbial fuel cell (MFC) was used to study nitrogen dynamics and its feasibility for high strength wastewater treatment. Intermittent aeration was applied on the cathode chamber accomplishing the establishment of a simultaneous nitrifying-denitrifying microbial community. A total of 30.4% of the N-NH4 + migrated through the ion exchange membrane being primarily nitrified at the cathode chamber. When intermittent aeration was applied in the cathode, denitrification also occurred achieving 17.8% of nitrate removal without acetate addition, and 41.2% with acetate addition. The microbial community analysis revealed that the nitrification process at the cathode chamber could be explained due to a high predominance of Nitrosomonas sp. as ammonia-oxidising bacteria and other Comamonadaceae phylotypes as potential denitrifiers. Parallel batch denitrification assays, carried out outside the MFC using the cathode effluent, confirmed the existence of heterotrophic denitrification processes with other well known denitrifying dominant phylotypes enrichment (Burkholderiadaceae, Comamonadaceae, Alcaligenaceae).Postprint (author's final draft

Removal of volatile fatty acids and ammonia recovery from unstable anaerobic digesters with a microbial electrolysis cell

Continuous assays with a microbial electrolysis cell (MEC) fed with digested pig slurry were performed to evaluate its stability and robustness to malfunction periods of an anaerobic digestion (AD) reactor and its feasibility as a strategy to recover ammonia. When performing punctual pulses of volatile fatty acids (VFA) in the anode compartment of the MEC, simulating a malfunction of the AD process, an increase in the current density was produced (up to 14 times, reaching values of 3500 mA m-2) as a result of the added chemical oxygen demand (COD), especially when acetate was used. Furthermore, ammonium diffusion from the anode to the cathode compartment was enhanced and the removal efficiency achieved up to 60% during daily basis VFA pulses. An AD-MEC combined system has proven to be a robust and stable configuration to obtain a high quality effluent, with a lower organic and ammonium contentPeer ReviewedPostprint (published version

Improving anaerobic digestion stability, effluent quality and ammonia recovering with a microbial electrolysis cell integrated system

Anaerobic digestion (AD) is nowadays widely used for processing various kinds of wastes, as livestock manure. Despite it is considered as a robust process, when it is performed at thermophilic range, beside a number of advantages, it is more sensitive to inhibition due to diverse substances that may be present in the waste stream, as ammonia. Furthermore, the AD process does not modify the total content of N of the digestates. So, it is interesting to find new technologies that can help to maintain effluent quality within the desired limits, while recovering nutrients from the digestates.This research was funded by the Spanish Ministry of Economy and Competitiveness (INIA project RTA2012- 00096-00-00). Also financial support was received by the Catalan Government (pre-doctoral fellowship 2013FI_B 00014).Postprint (published version

Assessment of active methanogenic archaea in a methanol-fed upflow anaerobic sludge blanket reactor

Methanogenic archaea enrichment of a granular sludge was undertaken in an upflow anaerobic sludge blanket (UASB) reactor fed with methanol in order to enrich methylotrophic and hydrogenotrophic methanogenic populations. A microbial community assessment, in terms of microbial composition and activity—throughout the different stages of the feeding process with methanol and acetate—was performed using specific methanogenic activity (SMA) assays, quantitative real-time polymerase chain reaction (qPCR), and high-throughput sequencing of 16S ribosomal RNA (rRNA) genes from DNA and complementary DNA (cDNA). Distinct methanogenic enrichment was revealed by qPCR of mcrA gene in the methanol-fed community, being two orders of magnitude higher with respect to the initial inoculum, achieving a final mcrA/16S rRNA ratio of 0.25. High-throughput sequencing analysis revealed that the resulting methanogenic population was mainly composed by methylotrophic archaea (Methanomethylovorans and Methanolobus genus), being also highly active according to the RNA-based assessment. SMA confirmed that the methylotrophic pathway, with a direct conversion of methanol to CH4, was the main step of methanol degradation in the UASB. The biomass from the UASB, enriched in methanogenic archaea, may bear great potential as additional inoculum for bioreactors to carry out biogas production and other related processes.Postprint (author's final draft

Comparative assessment of raw and digested pig slurry treatment in bioelectrochemical systems

Both raw and anaerobically digested pig slurries were investigated in batch assays in two chambered bioelectrochemical systems (BES) run in Microbial Fuel Cell (MFC) and Microbial Electrolysis Cell (MEC) mode. Chemical Oxygen Demand (COD) removal, nitrogen recovery, cation transport and anode microbial population evolutions were assessed. The Anaerobic Digestion-MEC (AD-MEC) integrated system achieved the highest COD removal (60% in 48 h); while the maximum NH4+ removal efficiency (40%, with an ammonia flux of 8.86 g N–NH4+ d-1 m-2) was achieved in MFC mode fed with digested pig slurry in 24 h. On the other hand, the high pH (12.1) achieved in MEC mode (NaCl solution as catholyte), could favour ammonium recovery in a subsequent stripping and absorption process. Ammonia was the main cation involved in maintaining the electroneutrality between both compartments. Regarding microbial population, Desulfuromonadaceae, a known family of exoelectrogenic bacteria, was enriched under MEC mode, whereas hydrogenotrophic and methylotrophic methanogen phylotypes belonging to Thermoplasmatales were also favoured against acetotrophic Methanosaetaceae. From these results, the integration of anaerobic digestion in BES seems to be an interesting alternative for the treatment of complex substrates, since a polished effluent can be obtained and ammonium can be simultaneously recovered for further reuse as fertilizer.Postprint (author's final draft

Chroma Intra Prediction with attention-based CNN architectures

Neural networks can be used in video coding to improve chroma intra-prediction. In particular, usage of fully-connected networks has enabled better cross-component prediction with respect to traditional linear models. Nonetheless, state-of-the-art architectures tend to disregard the location of individual reference samples in the prediction process. This paper proposes a new neural network architecture for cross-component intra-prediction. The network uses a novel attention module to model spatial relations between reference and predicted samples. The proposed approach is integrated into the Versatile Video Coding (VVC) prediction pipeline. Experimental results demonstrate compression gains over the latest VVC anchor compared with state-of-the-art chroma intra-prediction methods based on neural networks.Comment: 27th IEEE International Conference on Image Processing, 25-28 Oct 2020, Abu Dhabi, United Arab Emirate

Chroma intra-prediction with attention-based CNN architectures

Neural networks can be used in video coding to im- prove chroma intra-prediction. In particular, usage of fully- connected networks has enabled better cross-component pre- diction with respect to traditional linear models. Nonetheless, state-of-the-art architectures tend to disregard the location of individual reference samples in the prediction process. This paper proposes a new neural network architecture for cross-component intra-prediction. The network uses a novel attention module to model spatial relations between reference and predicted samples. The proposed approach is integrated into the Versatile Video Coding (VVC) prediction pipeline. Experimental results demonstrate compression gains over the latest VVC anchor compared with state-of-the-art chroma intra-prediction methods based on neural networks

ACCIDENTE EN FAGAJESTO. ALCANTARILLA [Material gráfico]

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