A compartmental model of anaerobic digester for improved description of the process performance

Understanding anaerobic digester (AD) performance relates to the complex interplay between hydrodynamics and kinetics. The latter is not straightforward and has been tackled by means of models. However, the computational burden to run such a model in a dynamic way is still too large. Here, a simplified compartmental model (CM) is derived from a CFD model (hydrodynamics). Compatibility of the CM and CFD model was tested by comparing the RTD curve of a virtual pulse tracer test. Subsequently, the CM was integrated with ADM1 in each compartment and the steady state performance was compared with that of a CSTR model with ADM1

Linking CFD and kinetic models in anaerobic digestion using a compartmental model approach

Understanding mixing behavior and its impact on conversion processes is essential for the operational stability and conversion efficiency of anaerobic digestion (AD). Mathematical modelling is a powerful tool to achieve this. Direct linkage of Computational Fluid Dynamics (CFD) and the kinetic model is, however, computationally expensive, given the stiffness of the kinetic model. Therefore, this paper proposes a compartmental model (CM) approach, which is derived from a converged CFD solution to understand the performance of AD under non-ideal mixing conditions and with spatial variation of substrates, biomass, pH, and specific biogas and methane production. To quantify the effect of non-uniformity on the reactor performance, the CM implements the Anaerobic Digestion Model 1 (ADM1) in each compartment. It is demonstrated that the performance and spatial variation of the biochemical process in a CM are significantly different from a continuously stirred tank reactor (CSTR) assumption. Hence, the assumption of complete mixed conditions needs attention concerning the AD performance prediction and biochemical process non-uniformities

Partial integration of ADM1 into CFD : understanding the impact of diffusion on anaerobic digestion mixing

Sufficient mixing is crucial for the proper performance of anaerobic digestion (AD), creating a homogeneous distribution of soluble substrates, biomass, pH, and temperature. The opaqueness of the sludge and mode of operation make it challenging to study AD mixing experimentally. Therefore, hydrodynamics modelling employing computational fluid dynamics (CFD) is often used to investigate this mixing. However, CFD models mostly do not include biochemical reactions and, hence, ignore the effect of diffusion-induced transport on AD heterogeneity. The novelty of this work is the partial integration of Anaerobic Digestion Model no. 1 (ADM1) into the CFD model. The aim is to better understand the effect of advection–diffusion transport on the homogenization of soluble substrates and biomass. Furthermore, AD homogeneity analysis in terms of concentration distribution is proposed rather than the traditional velocity distributions. The computed results indicate that including diffusion-induced transport affects the homogeneity of AD

Challenges for Cost-Effective Microalgae Anaerobic Digestion

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The use of a silicone-based biomembrane for microaerobic H2S removal from biogas

A lab-scale bio-membrane unit was developed to improve H2S removal from biogas through microaeration. Biomembrane separated biogas from air and consisted of a silicone tube covered by microaerobic biofilm. This setup allowed efficient H2S removal while minimizing biogas contamination with oxygen and nitrogen. The transport and removal of H2S, N-2, O-2, CH4 and CO2 through bare membrane, wet membrane and biomembrane was investigated. Membrane allowed the transfer of gases through it as long as there was enough driving force to induce it. H2S concentration in biogas decreased much faster with the biomembrane. The permeation of gases through the membranes decreased in order: H2S > CO2 > CH4 > O-2 > N-2. H2S removal efficiency of more than 99% was observed during the continuous experiment. Light yellow deposits on the membrane indicated the possible elemental sulfur formation due to biological oxidation of H2S. Thiobacillus thioparus was detected by FISH and PCR-DGGE

Evaluation of Membrane Integrity Monitoring Methods for Hollow Fiber Nanofiltration Membranes:Applicability in Gray Water Reclamation Systems

Source-separated gray water reclamation using nanofiltration as an advanced post-treatment option has received substantial interest in meeting the growing water demand. During reclamation, membrane integrity is crucial to ensure the water’s safety. This study evaluated several chemical and novel microbial indicators as indirect membrane integrity-monitoring methods for hollow fiber nanofiltration membranes in reclamation schemes. Under normal conditions, high retention of divalent ions and organic matter and near-complete removal of Escherichia coli (E. coli) were observed. Limited removal of the antibiotic gene (ARG) tetO was observed due to low feed concentrations and a higher detection limit (LOD). While 16S rRNA and ARG sul1 were not limited by their LODs, lower removals were observed, most likely due to free-floating DNA passing through the membranes. A broken fiber in a pilot-scale module reduced organic matter and microorganism removal substantially, while flux and ion rejection remained similar. Predictions made using the observed results and a previously proposed model allowed for the evaluation of the selected methods in upscaled reclamation systems. Based on these results, it was concluded that microorganisms could be employed as indicators in indirect membrane integrity-monitoring methods in large-scale reclamation schemes, while UV254nm absorbance (used in organic matter determination) could be a viable solution in pilot-scale systems.</p

Development and validation of novel PCR primers for identification of plasmid-mediated colistin resistance (mcr) genes in various environmental settings

Antibiotic resistance is considered one of the biggest threats to public health and has become a major concern for governments and international organizations. Combating this problem starts with improving global surveillance of antibiotic resistance genes (ARGs) and applying standardized protocols, both in a clinical and environmental context, in agreement with the One Health approach. Exceptional efforts should be directed to controlling ARGs conferring resistance to Critically Important Antimicrobials (CIA). In this study, a systematic literature review to synthesize data on the identification of mcr genes using a PCR technique was performed. Additionally, a novel set of PCR primers for mcr-1 – mcr-9 genes detection was proposed. The developed primers were in silico and experimentally validated by comparison with mcr-specific PCR primers reported in the literature. This validation, besides being a proof-of-concept for primers’ usefulness, provided insight into the distribution of mcr genes in municipal wastewater, clay and river sediments, glacier moraine, manure, seagulls and auks feces and daphnids from four countries. This analysis proved that commonly used primers may deliver false results, and some mcr genes may be overlooked in tested samples. Newly-developed PCR primers turned out to be relevant for the screening of mcr genes in various environments.info:eu-repo/semantics/publishedVersio

Quantitative NMR microscopy of iron transport in methanogenic aggregates

Transport of micronutrients (iron, cobalt, nickel, etc.) within biofilms matrixes such as methanogenic granules is of high importance, because these are either essential or toxic for the microorganisms living inside the biofilm. The present study demonstrates quantitative measurements of metal transport inside these biofilms using T1 weighted 3D RARE. It is shown that iron(II)-EDTA diffusion within the granule is independent of direction or the inner structure of the granules. Assuming position dependence of the spin-lattice relaxivity, Fick’s law for diffusion in a sphere can be applied to simulate the diffusion within the methanogenic granules under investigation. A relatively low diffusion coefficient of 2.5*10-11 m2·s-1 was obtained for iron diffusion within the methanogenic granule

Candidate biomarkers of antibiotic resistance for the monitoring of wastewater and the downstream environment

Urban wastewater treatment plants (UWTPs) are essential for reducing the pollutants load and protecting water bodies. However, wastewater catchment areas and UWTPs emit continuously antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs), with recognized impacts on the downstream environments. Recently, the European Commission recommended to monitor antibiotic resistance in UWTPs serving more than 100 000 population equivalents. Antibiotic resistance monitoring in environmental samples can be challenging. The expected complexity of these systems can jeopardize the interpretation capacity regarding, for instance, wastewater treatment efficiency, impacts of environmental contamination, or risks due to human exposure. Simplified monitoring frameworks will be essential for the successful implementation of analytical procedures, data analysis, and data sharing. This study aimed to test a set of biomarkers representative of ARG contamination, selected based on their frequent human association and, simultaneously, rare presence in pristine environments. In addition to the 16S rRNA gene, ten potential biomarkers (intI1, sul1, ermB, ermF, aph(3′’)-Ib, qacEΔ1, uidA, mefC, tetX, and crAssphage) were monitored in DNA extracts (n = 116) from raw wastewater, activated sludge, treated wastewater, and surface water (upstream and downstream of UWTPs) samples collected in the Czech Republic, Denmark, Israel, the Netherlands, and Portugal. Each biomarker was sensitive enough to measure decreases (on average by up to 2.5 log-units gene copy/mL) from raw wastewater to surface water, with variations in the same order of magnitude as for the 16S rRNA gene. The use of the 10 biomarkers allowed the typing of water samples whose origin or quality could be predicted in a blind test. The results show that, based on appropriate biomarkers, qPCR can be used for a cost-effective and technically accessible approach to monitoring wastewater and the downstream environment.info:eu-repo/semantics/publishedVersio

Biomarkers for monitoring antibiotic resistance in aquatic environments

The occurrence of antimicrobial resistance raises concerns as a human health threat that can be propagated through the environment. Wastewater discharge into the environment is an important source for antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs). Sewage collection and urban wastewater treatment plants (UWTPs) are major barriers that reduce environmental contamination by sewage-derived pathogens and nutrients. However, the continuous discharge of ARB and ARGs through wastewater, including when well-functioning UWTPs are available, is unavoidable. Regular and integrated antibiotic resistance monitoring in both wastewater and receiving water bodies would contribute to improve control measures. However, monitoring processes are not harmonized being the choice of suitable biomarkers a first limitation. In this study, we tested 10 selected potential antibiotic resistance biomarkers, which have been described has being associated to humans, and rare in clean environments - intI1, sul1, ermB, ermF, aph(3’’)-Ib, qacEΔ1, uidA, mefC, tetX and crAssphage. The public database MGnify (https://www.ebi.ac.uk/metagenomics/; hosted by EMBL-EBI), was screened using the filters corresponding to origin - human gut, wastewater, sewage, and fresh water. These biomarkers and the 16S rRNA gene were monitored by quantitative PCR (qPCR) tested in raw wastewater, activated sludge, treated wastewater and surface water (upstream and downstream the UWTP) samples, collected from different countries (Portugal, Czech Republic, Denmark, The Netherlands, and Israel). The abundance of the 10 potential biomarkers decreased on average by up to 2.5 log-units gene copies/mL of sample from raw wastewater to surface water, due to treatment and/or dilution in surface water. A clustering analysis of samples based on biomarkers abundance, grouped the samples according to the (waste)water type. This classification was confirmed when 12 anonymous (waste)water samples were analysed in a blind test. The tested biomarkers were observed to differentiate different types of sample, permitting the assessment of wastewater treatment efficiency or of impacts of UWTPs discharge or others in aquatic environments. The selection of suitable biomarkers that can typify different water sources and levels of ARG contamination, along with harmonized qPCR procedures, can facilitate regular and integrated legal requirements to antibiotic resistance monitoring in wastewater and related aquatic environments.info:eu-repo/semantics/publishedVersio