Enhancement of methane production and antibiotic resistance genes reduction by ferrous chloride during anaerobic digestion of swine manure

Disinfectant polyhexamethylene guanidine triggered simultaneous efflux pump antibiotic- and metal-resistance genes propagation during sludge anaerobic digestion

The environmental transmission of antibiotic resistance genes (ARGs) and metal resistance genes (MRGs) exerted devastating threats to global public health, and their interactions with other emerging contaminants (ECs) have raised increasing concern. This study investigated that the abundances of ARGs and MRGs with the predominant type of efflux pump were simultaneously increased (8.4-59.1%) by disinfectant polyhexamethylene guanidine (PHMG) during waste activated sludge (WAS) anaerobic digestion. The aggregation of the same microorganisms (i.e., Hymenobacter and Comamonas) and different host bacteria (i.e., Azoarcus and Thauera) were occurred upon exposure to PHMG, thereby increasing the co-selection and propagation of MRGs and ARGs by vertical gene transfer. Moreover, PHMG enhanced the process of horizontal gene transfer (HGT), facilitating their co-transmission by the same mobile genetic elements (20.2-223.7%). Additionally, PHMG up-regulated the expression of critical genes (i.e., glnB, trpG and gspM) associated with the HGT of ARGs and MRGs (i.e., two-component regulatory system and quorum sensing) and exocytosis system (i.e., bacterial secretion system). Structural equation model analysis further verified that the key driver for the simultaneous enrichment of ARGs and MRGs under PHMG stress was microbial community structure. The study gives new insights into the aggravated environmental risks and mechanisms of ECs in sludge digestion system, providing guidance for subsequent regulation and control of ECs.

An overview of the occurrence, impact of process parameters, and the fate of antibiotic resistance genes during anaerobic digestion processes

Antibiotic resistance genes (ARGs) have emerged as a significant global health threat, contributing to fatalities worldwide. Wastewater treatment plants (WWTPs) and livestock farms serve as primary reservoirs for these genes due to the limited efficacy of existing treatment methods and microbial adaptation to environmental stressors. Anaerobic digestion (AD) stands as a prevalent biological treatment for managing sewage sludge and manure in these settings. Given the agricultural utility of AD digestate as biofertilizers, understanding ARGs' fate within AD processes is essential to devise effective mitigation strategies. However, understanding the impact of various factors on ARGs occurrence, dissemination, and fate remains limited. This review article explores various AD treatment parameters and correlates to various resistance mechanisms and hotspots of ARGs in the environment. It further evaluates the dissemination and occurrence of ARGs in AD feedstocks and provides a comprehensive understanding of the fate of ARGs in AD systems. This review explores the influence of key AD parameters such as feedstock properties, pretreatments, additives, and operational strategies on ARGs. Results show that properties such as high solid content and optimum co-digestion ratios can enhance ARG removal, while the presence of heavy metals, microplastics, and antibiotics could elevate ARG abundance. Also, operational enhancements, such as employing two-stage digestion, have shown promise in improving ARG removal. However, certain pretreatment methods, like thermal hydrolysis, may exhibit a rebounding effect on ARG levels. Overall, this review systematically addresses current challenges and offers future perspectives associated with the fate of ARGs in AD systems.

Tracing the transfer characteristics of antibiotic resistance genes from swine manure to biogas residue and then to soil

Based on laboratory simulation experiments and metagenomic analysis, this study tracked the transmission of antibiotic resistance genes (ARGs) from swine manure (SM) to biogas residue and then to soil (biogas residue as organic fertilizer (OF) application). ARGs were abundant in SM and they were assigned to 11 categories of antibiotics. Among the 383 ARG subtypes in SM, 43 % ARG subtypes were absent after anaerobic digestion (AD), which avoided the transfer of these ARGs from SM to soil. Furthermore, 9 % of the ARG subtypes in SM were introduced into soil after amendment with OF. Moreover, 43 % of the ARG subtypes in SM were present in OF and soil, and their abundances increased slightly in the soil amended with OF. The bacterial community in the soil treated with OF was restored to its original state within 60 to 90 days, probably because the abundances of ARGs were elevated but not significantly in the soil. Network analysis identified 31 potential co-host bacteria of ARGs based on the relationships between the bacteria community members, where they mainly belonged to Firmicutes, followed by Bacteroidetes, Actinobacteria, and Proteobacteria. This study provides a basis for objectively evaluating pollution by ARGs in livestock manure for agricultural use.

Enhanced anaerobic digestion of human feces by ferrous hydroxyl complex (FHC): Stress factors alleviation and microbial resistance improvement

Anaerobic digestion (AD) offers a reliable strategy for resource recovery from source-separated human feces (HF), but is limited by a disproportionate carbon/nitrogen (C/N) ratio. Ferrous hydroxyl complex (FHC) was first introduced into the HF-AD system to mediate methanogenesis. Mono-digestion of undiluted HF was inhibited by high levels of volatile fatty acids (VFAs), ammonia, and hydrogen sulfide (H2S). FHC addition at optimum dosage (500-1000 mg/L) increased the cumulative methane (CH4) yield by 22.7%, enhanced the peak value of daily CH4 production by 60.5%, and shortened the lag phase by 24.7%. H2S concentration in biogas was also greatly decreased by FHC via precipitation. FHC mainly facilitated the hydrolysis, acidification, and methanogenesis processes. The production and transformation of VFAs were optimized in the presence of FHC, thus relieving acid stress. FHC elevated the activities of alkaline protease, cellulase, and acetate kinase by 32.3%, 18.2%, and 30.3%, respectively. Microbial analysis revealed that hydrogenotrophic methanogens prevailed in mono-digestion at high HF loading but were weakened after FHC addition. FHC also enriched Methanosarcina, thereby expanding the methanogenesis pathway and improving the resistance to ammonia stress. This work would contribute to improving the methanogenic performance and resource utilization for HF anaerobic digestion.

Dissemination of sulfonamide resistance genes in digester microbiome during anaerobic digestion of food waste leachate

The preeminence of sulfonamide drug resistance genes in food waste (FW) and the increased utilization of high-strength organic FW in anaerobic digestion (AD) to enhance methane production have raised severe public health concerns in wastewater treatment plants worldwide. In this regard, the dissemination patterns of different sulfonamide resistance genes (sul1 and sul2) and their impact on the digester core microbiota during AD of FW leachate (FWL) were evaluated. The presence of various sulfonamide antibiotics (SAs) in FWL digesters improved the final methane yield by 37 % during AD compared with FWL digesters without SAs. Microbial population shifts towards hydrolytic, acidogenic, and acetogenic bacteria in the phyla Actinobacteriota, Bacteroidota, Chloroflexi, Firmicutes, Proteobacteria, and Synergistota occurred due to SA induced substrate digestion and absorption through active transport; butanoate, propanoate, and pyruvate metabolism; glycolysis; gluconeogenesis; the citrate cycle; and pentose phosphate pathway. The initial dominance of Methanosaeta (89-96 %) declined to 47-53 % as AD progressed and shifted towards Methanosarcina (40 %) in digesters with the highest SA concentrations at the end of AD. Dissemination of sul1 depended on class 1 integron gene (intl1)-based horizontal gene transfer to pathogenic members of Chloroflexi, Firmicutes, and Patescibacteria, whereas sul2 was transmitted to Synergistota independent of intl1. Low susceptibility and ability to utilize SAs during methanogenesis shielded methanogenic archaea against selection pressure, thus preventing them from interacting with sul or intl1 genes, thereby minimizing the risk of antibiotic resistance development. The observed emergence of cationic antimicrobial peptide, vancomycin, and β-lactam resistance in the core microbiota during AD of FWL in the presence of SAs suggests that multidrug resistance caused by bacterial transformation could lead to an increase in the environmental resistome through wastewater sludge treatment.

Prediction of biogas production of industrial scale anaerobic digestion plant by machine learning algorithms

In the anaerobic digestion (AD) process there are some difficulties in maintaining process stability due to the complexity of the system. The variability of the raw material coming to the facility, temperature fluctuations and pH changes as a result of microbial processes cause process instability and require continuous monitoring and control. Increasing continuous monitoring, and internet of things applications within the scope of Industry 4.0 in AD facilities can provide process stability control and early intervention. In this study, five different machine learning (ML) algorithms (RF, ANN, KNN, SVR, and XGBoost) were used to describe and predict the correlation between operational parameters and biogas production quantities collected from a real-scale anaerobic digestion plant. The KNN algorithm had the lowest accuracy in predicting total biogas production over time, while the RF model had the highest prediction accuracy of all prediction models. The RF method produced the best prediction, with an R² of 0.9242, and it was followed by XGBoost, ANN, SVR, and KNN (with R² values of 0.8960, 0.8703, 0.8655, 0.8326, respectively). Real-time process control will be provided and process stability will be maintained by preventing low-efficiency biogas production with the integration of ML applications into AD facilities.

An extensive assessment of seasonal rainfall on intracellular and extracellular antibiotic resistance genes in Urban River systems

Rainfall events are responsible for the accelerated transfer of antibiotic-resistant contaminants to receiving environments. However, the specific profiles of various ARG types, including intra- and extracellular ARGs (iARGs and eARGs) responding to season rainfall needed more comprehensive assessments. Particularly, the key factors driving the distribution and transport of iARGs and eARGs have not been well characterized. Results revealed that the absolute abundance of eARGs was observed to be more than one order of magnitude greater than that of iARGs during the dry season in the reservoir. However, the absolute abundance of iARGs significantly increased after rainfall (p < 0.01). Meanwhile, seasonal rainfall significantly decreased the diversity of eARGs and the number of shared genes between iARGs and eARGs (p < 0.01). Results of structural equation models (SEM) and network analysis showed the rank and co-occurrence of influencing factors (e.g., microbial community, MGEs, environmental variables, and dissolved organic matter (DOM)) concerning the changes in iARGs and eARGs. DOM contributed majorly to eARGs in the reservoir and pathogens was responsible for eARGs in the river during the wet season. Network analysis revealed that the tnp-04 and IS613 genes-related MGEs co-occurred with eARGs in the dry and wet seasons, which were regarded as potential molecular indicators to shape eARGs profiles in urban rivers. Besides, the results demonstrated close relationships between DOM fluorescence signatures and two-typed ARGs. Specifically, humic acid was significantly and positively correlated with the eARGs in the reservoir during the wet season, while fulvic acid-like substances exhibited strong correlations of iARGs and eARGs in the river during the dry season (p < 0.01). This work provides extensive insights into the potential effect of seasonal rainfall on the dynamic distribution of iARGs and eARGs and the dominance of DOM in driving the fate of two-typed ARGs in urban river systems.

Effect of pH on the mitigation of extracellular/intracellular antibiotic resistance genes and antibiotic resistance pathogenic bacteria during anaerobic fermentation of swine manure

Effects of various initial pH values (i.e., 3, 5, 7, 11) during anaerobic fermentation of swine manure on intracellular and extracellular antibiotic resistance genes (iARGs and eARGs) and ARG-carrying potential microbial hosts were investigated. The abundance of almost all iARGs and eARGs decreased by 0.1-1.7 logs at pH 3 and pH 5. The abundance of only three iARGs and eARGs decreased by 0.1-0.9 logs at pH 7 and pH 11. Under acidic initial fermentation conditions (pH 3 and pH 5), the ARG removal effect was more pronounced. Acidic conditions (pH 3 and pH 5) significantly reduced the diversity and abundance of the microbial community, thereby eliminating many potential ARG hosts and antibiotic-resistant pathogenic bacteria (ARPB). Therefore, the study results contribute to the investigation of the effects of swine manure anaerobic fermentation on the removal and risk of contamination of ARGs and ARPB.

Performance and Characterization of Bi-Metal Compound on Activated Carbon for Hydrogen Sulfide Removal in Biogas

This study reports on the synthesis of bi-metal compound (BMC) adsorbents based on commercial coconut activated carbon (CAC), surface-modified with metal acetate (ZnAc₂), metal oxide (ZnO), and the basic compounds potassium hydroxide (KOH) and sodium hydroxide (NaOH). The adsorbents were then characterized by scanning electron microscopy and elemental analysis, microporosity analysis through Brunauer-Emmett-Teller (BET) analysis, and thermal stability via thermogravimetric analysis. Adsorption-desorption test was conducted to determine the adsorption capacity of H₂S via 1 L adsorber and 1000 ppm H₂S balanced 49.95% for N₂ and CO₂. Characterization results revealed that the impregnated solution homogeneously covered the adsorbent surface, morphology, and properties. The adsorption test result reveals that the ZnAc₂/ZnO/CAC_B had a higher H₂S breakthrough adsorption capacity and performed at larger than 90% capability compared with a single modified adsorbent (ZnAc₂/CAC). Therefore, the synthesized BMC adsorbents have a high H₂S loading, and the abundance and low cost of CAC may lead to favorable adsorbents in H₂S captured.

Exploration of machine learning algorithms for predicting the changes in abundance of antibiotic resistance genes in anaerobic digestion

The land application of digestate from anaerobic digestion (AD) is considered a significant route for transmitting antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) to ecosystems. To date, efforts towards understanding complex non-linear interactions between AD operating parameters with ARG/MGE abundances rely on experimental investigations due to a lack of mechanistic models. Herein, three different machine learning (ML) algorithms, Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Artificial Neural Network (ANN), were compared for their predictive capacities in simulating ARG/MGE abundance changes during AD. The models were trained and cross-validated using experimental data collected from 33 published literature. The comparison of model performance using coefficients of determination (R²) and root mean squared errors (RMSE) indicated that ANN was more reliable than RF and XGBoost. The mode of operation (batch/semi-continuous), co-digestion of food waste and sewage sludge, and residence time were identified as the three most critical features in predicting ARG/MGE abundance changes. Moreover, the trained ANN model could simulate non-linear interactions between operational parameters and ARG/MGE abundance changes that could be interpreted intuitively based on existing knowledge. Overall, this study demonstrates that machine learning can enable a reliable predictive model that can provide a holistic optimization tool for mitigating the ARG/MGE transmission potential of AD.

Substrate complexity affects the prevalence and interconnections of antibiotic, metal and biocide resistance genes, integron-integrase genes, human pathogens and virulence factors in anaerobic digestion

Anaerobic digestion (AD) is widely used to treat livestock manure that harbors diverse pollutants (resistance genes (ARGs), metal/biocide resistance genes (MBRGs), integron-integrase genes, human pathogens and pathogen virulence factors (VFs)). However, the interplays of these pollutants and the effects of substrate complexity on pollutants in AD are elusive. This study investigated the dynamics of these pollutants and bacterial communities during AD of swine manure, by metatranscriptomic sequencing and amplicon sequencing of 16 S rRNA and 16 S rRNA gene. The pollutant profiles and bacterial communities differed across AD processes, nevertheless with consistent dominance of ARGs of multi-drugs, tetracycline, aminoglycoside and rifamycin, MBRGs of multi-biocides, multi-metals, copper and arsenic, the integron-integrase gene intI1, potential pathogens of Escherichia coli, Streptococcus gallolyticus and Clostridium perfringens, VFs involved in pathogen adherence, and bacterial phyla of Firmicutes, Bacteroidetes and Proteobacteria. Reduced substrate complexity (replacing a part of swine manure, a complex substrate, with a simple substrate, apple waste or fructose) decreased the prevalence and stochastic turnover of ARGs and MBRGs. Network analyses revealed decreased interplays among pollutants under reduced substrate complexity. Our findings provide a mechanical understanding of diverse pollutants dynamics during AD, and reveal the importance of substrate complexity in controlling prevalence and interplays of pollutants.

Coupled mechanism of enhanced and inhibitory effects of nanoscale zero-valent iron on methane production and antibiotic resistance genes in anaerobic digestion of swine manure

In this study, the turning point for nanoscale zero-valent iron's (NZVI) promotion and inhibition effects of methane production coupled with the reduction of antibiotic resistance genes (ARGs) was investigated. Adding 150 mmol/L NZVI increased methane production by maximum of 23.8 %, which was due to the chemical reaction producing H₂ and enhancement of direct interspecies electron transfer (DIET) by NZVI. NZVI350 dramatically repressed methane generation by 48.0 %, which might be associated with the large quantity of reactive oxygen species (ROS) and excessive H₂ inhibiting the functioning of microorganisms. The fate of ARGs was significantly related to daily methane production, indicating that the more methane production finally generated, the less the abundance of ARGs at last left. The reduction of ARGs was enhanced by maximum of 61.0 %, which was attributed to the inhibition of vertical gene transfer (VGT) and horizontal gene transfer (HGT) caused by steric hindrance associated with NZVI corrosion.

Particle size effects in microbial characteristics in thermophilic anaerobic digestion of cattle manure containing copper oxide

Roles of bulk-, micron-, and nano-copper oxide (CuO) on methane production, microbial diversity, functions during thermophilic anaerobic digestion (AD) were investigated in this study. Results showed that bulk-, micron-, and nano-CuO promoted methane production by 27.8%, 47.6%. and 83.1% compared to the control group, respectively. Microbial community analysis demonstrated that different particle sizes could cause various shifts on bacteria community, while had little effect on archaeal diversity. Thereinto, bacteria belonging to phylum Firmicutes and Coprothermobacterota dominated in enhanced hydrolysis process in groups with nano-CuO and bulk-CuO, respectively, while micron-CuO had stronger promotion on the abundances of hydrolytic and fermentative bacteria belonging to families Peptostreptococcaceae, Caloramatoraceae, Erysipelotrichaceae, and Clostridiaceae, than other two CuO sizes. Metabolic pathways revealed that energy-related metabolism and material transformation in bacteria were only boosted by micron-CuO, and nano-CuO and bulk-CuO were important to methanogenic activity, stimulating energy consumption and methane metabolism, respectively.

Consideration of biological and inorganic additives in upgraded anaerobic digestion BioModel

This paper deals with the numerical simulation of biogas production in the anaerobic digestion process of organic waste. Special attention is focused on the modeling of the activities of biological and inorganic additives, which are used to enhance the process and reduce H₂S content in the biogas. For this purpose, an existing BioModel is upgraded with the modified Michaelis-Menten kinetics in order to model the enzymatic hydrolysis and with adequate modeling of physicochemical processes. The upgraded BioModel was calibrated with experimental data obtained from a full-scale biogas plant, used in combination with an active set optimization procedure; the relative agreement indices were 0.9376, 0.9419, 0.7957, and 0.7663 for biogas, CH₄, H₂, and H₂S flow rates, respectively. Statistical efficiency criteria differ up to 5% in model calibration and validation. The obtained results confirm the importance of additives modeling and the usefulness of the proposed model for industrial biogas plants' performance improvement.

Anaerobic treatment of swine manure under mesophilic and thermophilic temperatures: Fate of veterinary drugs and resistance genes

The effect of anaerobic treatment of swine manure at 35 °C (mesophilic) and 55 °C (thermophilic) on methane production, microbial community and contaminants of emerging concern was investigated. Pasteurization pretreatment and post treatment was also investigated in combination with anaerobic treatment at 35 °C. Specific methane production (SMP), 26 pharmaceutical compounds (PhACs) and five antibiotic resistance genes (ARGs) (qnrS, tetW, ermB, sul1 and bla_TEM) were evaluated. Mesophilic treatment resulted in the highest SMP regardless of whether pasteurization was applied. Marbofloxacin was the most abundant antibiotic in swine manure. In general, all groups of PhACs showed higher removals under thermophilic temperatures as compared to mesophilic. In general, pasteurization pretreatment followed by mesophilic anaerobic digestion provided the highest removals of ARGs. Finally, the genera Streptococcus, Clostridium and Pseudomonas which contain pathogenic species, were present in the swine manure. Streptococcus, which was the most abundant, was decreased during all the treatments, while the others only decreased under certain treatments.

A meta-analysis reveals that operational parameters influence levels of antibiotic resistance genes during anaerobic digestion of animal manures

Anaerobic digestion (AD) has shown the potential to reduce the numbers and types of antibiotic-resistance genes (ARG) present in animal manures. However, the variability of the results has limited the ability to draw solid conclusions. To address this issue, we performed a series of meta-analyses to evaluate how AD of pig, cattle, and dairy manures affects ARG levels and how different parameters, such as temperature, pH, digestion times, and the addition of other substances (e.g., solids, antibiotics) influence ARG changes. Twenty studies with enough details on changes in ARG levels during the AD process were identified and used for the meta-analyses. The results suggested that AD could significantly reduce ARG levels regardless of the conditions of the process. Also, thermophilic AD was more effective than mesophilic AD at reducing ARGs, although this difference was only significant for pig manures. The results also suggested that long digestion times (>50 days) yielded better ARG reduction rates, and that the addition of solids from an external source (co-digestion) negatively affected the efficiency of ARG reduction. In general, the results suggested that ARG changes during AD could be linked to the abundance and activity of hydrolytic communities.

Improving the efficiency of anaerobic digestion of Molasses alcohol wastewater using Cassava alcohol wastewater as a mixed feedstock

Cassava alcohol wastewater (CAW) was utilized as a mixed feedstock to explore whether the addition of CAW could improve the anaerobic digestion of Molasses alcohol wastewater (MAW). The result showed that the rate of removal of the soluble chemical oxygen demand in the M treatment mixed with CAW was 70.13 ± 0.16%, which was significantly higher than that of the C treatment (only MAW), which was 61.23 ± 0.36%. Co-digestion in the M treatment resulted in higher methane production, achieving 23.89% increase in methane yield compared to C treatment. The addition of CAW helps to alleviate the accumulation of volatile fatty acids (397.06 ± 141.82 mg·L^-1), enhance the stability of system and promote the establishment of stable and active microbial communities. Microbial community structure analysis indicated that hydrolytic bacteria such as Bacteroidetes, Firmicutes, and Proteobacteria, and acetoclastic methanogens, including Methanosaeta and Methanosarcina were more abundant in the co-digests.

Novel insight into enhanced recoverability of acidic inhibition to anaerobic digestion with nano-bubble water supplementation

Nano-bubble water (NBW) has been proven to be effective in promoting organics utilization and CH₄ production during anaerobic digestion (AD) process, suggesting its potential in improving the stability of the AD process and thereby alleviating acidic inhibition. In this work, the effect of NBW on digestion stability and CH₄ production was investigated to evaluate the ability of NBW on AD recovery from acidic inhibition. Results showed that NBW supplementation increased the total alkalinity (TA) and partial alkalinity (PA), and reduced the ratio of VFA/TA, thus maintained the stability of the AD process. Generation/consumption of VFAs was also enhanced with NBW supplementation under acidic inhibition with pH values of 5.5, 6.0 and 6.5. The cumulative CH₄ production was 246-257 mL/g-VS in NBW groups, which was 12.1-17.2% higher than the control. Moreover, with NBW supplementation, the maximum CH₄ production rate was raised according to the modeling results.

Performance prediction of ZVI-based anaerobic digestion reactor using machine learning algorithms

The use of zero-valent iron (ZVI) to enhance anaerobic digestion (AD) systems is widely advocated as it improves methane production and system stability. Accurate modeling of ZVI-based AD reactor is conducive to predicting methane production potential, optimizing operational strategy, and gathering reference information for industrial design in place of time-consuming and laborious tests. In this study, three machine learning (ML) algorithms, namely random forest (RF), extreme gradient boosting (XGBoost), and deep learning (DL), were evaluated for their feasibility of predicting the performance of ZVI-based AD reactors based on the operating parameters collected in 9 published articles. XGBoost demonstrated the highest accuracy in predicting total methane production, with a root mean squared error (RMSE) of 21.09, compared to 26.03 and 27.35 of RF and DL, respectively. The accuracy represented by mean absolute percentage error also showed the same trend, with 14.26%, 15.14% and 17.82% for XGBoost, RF and DL, respectively. Through the feature importance generated by XGBoost, the parameters of total solid of feedstock (TS_f), sCOD, ZVI dosage and particle size were identified as the dominant parameters that affect the methane production, with feature importance weights of 0.339, 0.238, 0.158, and 0.116, respectively. The digestion time was further introduced into the above-established model to predict the cumulative methane production. With the expansion of training dataset, DL outperformed XGBoost and RF to show the lowest RMSEs of 11.83 and 5.82 in the control and ZVI-added reactors, respectively. This study demonstrates the potential of using ML algorithms to model ZVI-based AD reactors.

Phosphate substances transformation and vivianite formation in P-Fe containing sludge during the transition process of aerobic and anaerobic conditions

Excess sludge was considered as a promising raw material for phosphorus recovery. In this study, the P-Fe containing sludge came from the aerobic membrane bioreactor with electrocoagulation (EC), which was refluxed to the anaerobic unit for iron reduction. Under anaerobic condition, the ORP and pH maintained at -350 mV and 7.5, which exactly met the conditions for vivianite formation. According to the analysis of X-ray polycrystalline diffraction (XRD) and field emission scanning electron microscopy (FE-SEM), the final product of the sludge after anaerobic condition was mainly vivianite. Microbial analysis showed that there were iron reducing bacteria (IRB) in sludge before and after anaerobic process, including Dechloromonas, Desulfovibrio. Aeromonas and Methanobacterium. During the transition process of aerobic and anaerobic conditions, amorphous phosphate substances in P-Fe containing sludge could be transformed vivianite just with long term standing, which could promote the recovery of phosphate resource from wastewater.

Effect of ultrasonic and ozone pretreatment on the fate of enteric indicator bacteria and antibiotic resistance genes, and anaerobic digestion of dairy wastewater

In this study, the effect of ultrasound (US), ozone and US combined with ozone (US/ozone) pretreatments on the fate of enteric indicator bacteria and antibiotic resistance genes (ARGs), and anaerobic digestion (AD) of dairy wastewater was investigated. The pretreatment conditions included US power 200 W, ozone concentration 4.2 mg O₃/L, and pretreatment time 0-30 min. The results showed that US/ozone pretreatment was effective in the inactivation of enteric indicator bacteria. Total coliforms and enterococci were reduced by 99% and 92% after 30 min US/ozone pretreatment. Pretreatments could not decrease ARGs in absolute concentration, but could decrease ARGs in relative abundance. In the subsequent AD process, methane production increased more than 10% with 20 min ozone or 20 min US/ozone pretreatments. Pretreatment-AD together obviously inhibited the enrichment of ARGs in relative abundance. This study provided a pretreatment way to enhance methane production and to prevent the enrichment of ARGs.

Changes and distributions of antibiotic resistance genes in liquid and solid fractions in mesophilic and thermophilic anaerobic digestion of dairy manure

This study mainly explored the changes and distributions of antibiotic resistance genes (ARGs) in liquid fraction (L_F) and solid fraction (S_F) in anaerobic digestion (AD) of dairy manure. After mesophilic and thermophilic AD, the copy numbers of ARGs in L_F decreased by 0.06-1.80 logs while those in S_F increased by 0.08-7.85 logs, suggesting the enrichment of ARGs in S_F. Statistical analysis elucidated that high total solids promoted the enrichment of ARGs in S_F. The increased abundances of genera such as Ruminofilibacter, Treponema and Sphaerochaeta in S_F were responsible for the enrichment of most ARGs. These insights demonstrated the digested solid had the potential risks to promote the spread of ARGs in the environment, and the digested solid of livestock manure should be post-treated before the application.