Re-vitalizing Wastewater: Nutrient Recovery and carbon capture through Microbe-Algae synergy using Omics-Biology.

Increasing amounts of wastewater is the most pervasive and challenging environmental problem globally. Conventional treatment methods are costly and entail huge energy and carbon consumption and greenhouse gas emissions. Owing to their unique ability of carbon capturing and resource recovery, microalgae-microbiome based treatment is a potential approach and is widely used for carbon-neutral wastewater treatment. Microalgae-bacteria synergy (i.e., the functionally beneficial microbial synthetic communities) performs better and enhances carbon-sequestration and nutrient recovery from wastewater treatment plants. This review presents a comprehensive information regarding the potential of microalgae-microbiome as a sustainable agent for wastewater and discusses synergistic approaches for effective nutrient removal. Moreover, this review discusses, the role of omics-biology and Insilco approaches in unravelling and understanding the algae-microbe synergism and their response toward wastewater treatment. Finally, it discusses various microbiome engineering approaches for developing the effective microalgae-bacteria partners for carbon sequestration and nutrient recovery from wastewater, and summarizes future research perspectives on microalgae-microbiome based bioremediation.

Optimisation of analytical methods for tuberculosis drug detection in wastewater: A multinational study.

Wastewater-based epidemiology (WBE) is a robust tool for disease surveillance and monitoring of pharmaceutical consumption. However, monitoring tuberculosis (TB) drug consumption faces challenges due to limited data availability. This study aimed to optimise methods for detecting TB drugs in treated and untreated wastewater from four African countries: South Africa, Nigeria, Kenya, and Cameroon. The limit of detection (LOD) for these drugs ranged from a minimum of 2.20 (±1.02) for rifampicin to a maximum of 2.95 (±0.79) for pyrazinamide. A parallel trend was observed concerning the limit of quantification (LOQ), with rifampicin reporting the lowest average LOQ of 7.33 (±3.44) and pyrazinamide showing the highest average LOQ of 9.81 (±2.64). The variance in LOD and LOQ values could be attributed to factors such as drug polarity. Erythromycin and rifampicin exhibited moderately polar LogP values (2.6 and 2.95), indicating higher lipid affinity and lower water affinity. Conversely, ethambutol, pyrazinamide, and isoniazid displayed polar LogP values (-0.059, -0.6, and -0.7), suggesting lower lipid affinity and greater water affinity. The study revealed that storing wastewater samples for up to 5 days did not result in significant drug concentration loss, with concentration reduction remaining below 1 log throughout the storage period. Application of the optimised method for drug detection and quantification in both treated and untreated wastewater unveiled varied results. Detection frequencies varied among drugs, with ethambutol consistently most detected, while pyrazinamide and isoniazid were least detected in wastewater from only two countries. Most untreated wastewater samples had undetectable drug concentrations, ranging from 1.21 ng/mL for erythromycin to 54.61 ng/mL for isoniazid. This variability may suggest differences in drug consumption within connected communities. In treated wastewater samples, detectable drug concentrations ranged from 1.27 ng/mL for isoniazid to 10.20 ng/mL for ethambutol. Wastewater treatment plants exhibited variable removal efficiencies for different drugs, emphasising the need for further optimisation. Detecting these drugs in treated wastewater suggests potential surface water contamination and subsequent risks of human exposure, underscoring continued research's importance.

Metabolic Syndrome Frequency in Type 2 Diabetics Using International Diabetes Federation (IDF) Criteria Analysis.

Background The cluster of metabolic abnormalities known as metabolic syndrome has a significant association with the onset of type 2 diabetes mellitus (T2DM) and cardiovascular disease. The objective of this study was to evaluate the occurrence rate of metabolic syndrome among a group of patients diagnosed with T2DM, according to the standards set by the International Diabetes Federation (IDF). Methodology A descriptive cross-sectional study was conducted at Chandka Medical College, Larkana, Pakistan, from June 2019 to 2020. Using the IDF criteria for metabolic syndrome, 131 type 2 diabetics over age 30 were purposively sampled, excluding specific medical conditions and medications. Trained nurses recorded patient demographics, waist circumference, and blood pressure. Relevant laboratory tests were conducted, and metabolic syndrome prevalence was determined. Data were analyzed using IBM SPSS Statistics for Windows, Version 19, (Released 2010; IBM Corp., Armonk, New York, United States), considering both quantitative and qualitative variables. Results The research found that the occurrence of metabolic syndrome was 87.2%. It is worth mentioning that age did not have a considerable connection with metabolic syndrome incidence (p=0.873), as the overwhelming majority of participants in both groups were aged over 40 years. However, there was a clear link (p=0.001) between gender and the 'no metabolic syndrome' group, with more males in this category. Additionally, blood pressure was significantly linked to metabolic syndrome (p=0.001), with most individuals having normal blood pressure in the 'no metabolic syndrome' group. Although serum triglyceride levels were not significantly associated with metabolic syndrome (p=0.222), serum HDL cholesterol levels had a significant relationship (p<0.0001), where most people possessed HDL levels ≥40mg/dl in the 'no metabolic syndrome' category. Conclusion The findings of this investigation demonstrated a substantial occurrence of metabolic syndrome in patients with T2DM, wherein notable links were detected with gender, blood pressure, and HDL cholesterol levels. However, no significant correlation was observed with age or serum triglycerides. These results emphasize the necessity for an all-inclusive metabolic care approach for individuals with T2DM.

Removal and risk assessment of emerging contaminants and heavy metals in a wastewater reuse process producing drinkable water for human consumption.

This study focuses on the removal and risk assessment of twenty emerging contaminants (ECs) and heavy metals in a REMIX water treatment plant (RWTP) that produces drinking water from combination of wastewater reuse and desalination. The membrane biological reactor (MBR) exhibit removal rates exceeding 95% of pharmaceuticals like acetaminophen, trimethoprim, diclofenac, naproxen, and emtricitabine. The efficiency of brackish reverse osmosis (BWRO) in removing ECs is highlighted, showing substantial efficacy with reduction rates of 99.5%, 75.5%, and 51.2% for sulfamethoxazole, venlafaxine, and benzotriazole, respectively. The advanced oxidation process based on Fenton process reveals removal (>95%) of emtricitabine, efavirenz, and carbamazepine. The study confirms that the combination of treatment units within the RWTP effectively removes heavy metals (>90%), complying with acceptable limits. Risk quotient (RQ) calculations indicate the efficiency of the RWTP in EC removal, serving as benchmarks for public acceptance of reclaimed water. In the context of heavy metals, the study concludes negligible cancer risks associated with reclaimed water consumption over a lifetime. Quantitative structure-activity relationship and occurrence, persistence, bioaccumulation and toxicity (OPBT) models were used to assess EC risk. The study screened and identified potential persistant, bio accumulating and toxic PBT ECs. Critical control points (CCPs) in the RWTP are identified, with brackish and seawater reverse osmosis (BWRO and SWRO) and advanced oxidation process (AOP) recognized as pivotal in hazard management. The study provides valuable insights on the removal of ECs and heavy metals in a wastewater reuse process and demonstrates potential of adopted process configuration in supplying safe drinking water from wastewater recycling.

Digitalization of phosphorous removal process in biological wastewater treatment systems: Challenges, and way forward.

Phosphorus in wastewater poses a significant environmental threat, leading to water pollution and eutrophication. However, it plays a crucial role in the water-energy-resource recovery-environment (WERE) nexus. Recovering Phosphorus from wastewater can close the phosphorus loop, supporting circular economy principles by reusing it as fertilizer or in industrial applications. Despite the recognized importance of phosphorus recovery, there is a lack of analysis of the cyber-physical framework concerning the WERE nexus. Advanced methods like automatic control, optimal process technologies, artificial intelligence (AI), and life cycle assessment (LCA) have emerged to enhance wastewater treatment plants (WWTPs) operations focusing on improving effluent quality, energy efficiency, resource recovery, and reducing greenhouse gas (GHG) emissions. Providing insights into implementing modeling and simulation platforms, control, and optimization systems for Phosphorus recovery in WERE (P-WERE) in WWTPs is extremely important in WWTPs. This review highlights the valuable applications of AI algorithms, such as machine learning, deep learning, and explainable AI, for predicting phosphorus (P) dynamics in WWTPs. It emphasizes the importance of using AI to analyze microbial communities and optimize WWTPs for different various objectives. Additionally, it discusses the benefits of integrating mechanistic and data-driven models into plant-wide frameworks, which can enhance GHG simulation and enable simultaneous nitrogen (N) and Phosphorus (P) removal. The review underscores the significance of prioritizing recovery actions to redirect Phosphorus from effluent to reusable products for future considerations.

Metagenomics insights into microbiome and antibiotic resistance genes from free living amoeba in chlorinated wastewater effluents.

Free living amoeba (FLA) are among the organisms commonly found in wastewater and are well-established hosts for diverse microbial communities. Despite its clinical significance, there is little knowledge on the FLA microbiome and resistome, with previous studies relying mostly on conventional approaches. In this study we comprehensively analyzed the microbiome, antibiotic resistome and virulence factors (VFs) within FLA isolated from final treated effluents of two wastewater treatment plants (WWTPs) using shotgun metagenomics. Acanthamoeba has been identified as the most common FLA, followed by Entamoeba. The bacterial diversity showed no significant difference (p > 0.05) in FLA microbiomes obtained from the two WWTPs. At phylum level, the most dominant taxa were Proteobacteria, followed by Firmicutes and Actinobacteria. The most abundant genera identified were Enterobacter followed by Citrobacter, Paenibacillus, and Cupriavidus. The latter three genera are reported here for the first time in Acanthamoeba. In total, we identified 43 types of ARG conferring resistance to cephalosporins, phenicol, streptomycin, trimethoprim, quinolones, cephalosporins, tigecycline, rifamycin, and kanamycin. Similarly, a variety of VFs in FLA metagenomes were detected which included flagellar proteins, Type IV pili twitching motility proteins (pilH and rpoN), alginate biosynthesis genes AlgI, AlgG, AlgD and AlgW and Type VI secretion system proteins and general secretion pathway proteins (tssM, tssA, tssL, tssK, tssJ, fha, tssG, tssF, tssC and tssB, gspC, gspE, gspD, gspF, gspG, gspH, gspI, gspJ, gspK, and gspM). To the best of our knowledge, this is the first study of its kind to examine both the microbiomes and resistome in FLA, as well as their potential pathogenicity in treated effluents. Additionally, this study showed that FLA can host a variety of potentially pathogenic bacteria including Paenibacillus, and Cupriavidus that had not previously been reported, indicating that their relationship may play a role in the spread and persistence of antibiotic resistant bacteria (ARBs) and antibiotic resistance genes (ARGs) as well as the evolution of novel pathogens.

Innovative determination of the specific anammox activity for anammox sludge from continuous flow reactors: A comparison between continuous flow test and batch test.

A novel method for measuring specific anammox activity (SAA) was proposed based on continuous flow tests to accurately determine the SAA of anammox sludge from continuous flow reactors, resolving the challenges of inaccurate SAA assessment caused by substrate shock to anammox bacteria. Results showed SAA of expanded granular sludge bed sludge via batch tests (0.101 ± 0.018 g-N·g-VSS-1·d-1) was lower than continuous flow tests (0.206 ± 0.010 g-N·g-VSS-1·d-1) (p < 0.05), highlighting the impact of substrate shock. Conversely, SAA of sequencing batch reactor sludge assessed via batch tests (0.878 ± 0.008 g-N·g-VSS-1·d-1) was higher than continuous flow tests (0.809 ± 0.005 g-N·g-VSS-1·d-1) (p < 0.01), attributed to endogenous denitrification. The advantages of continuous flow tests over batch tests included milder feeding way, stricter anaerobic conditions, and minimal sampling impact on system. Our study contributes to more accurate measurements of SAA of anammox sludge from continuous flow reactors, favoring long-term robust operation of anammox reactors.

Profiling pathogenic protozoan and their functional pathways in wastewater using 18S rRNA and shotgun metagenomics.

Despite extensive research, little is known about the composition of eukaryotic protists in environmental samples. This is due to low parasite concentrations, the complexity of parasite diversity, and a lack of suitable reference databases and standardized protocols. To bridge this knowledge gap, this study used 18S rRNA short amplicon and shotgun metagenomic sequencing approaches to profile protozoan microbial communities as well as their functional pathways in treated and untreated wastewater samples collected from different regions of South Africa. Results demonstrated that protozoan diversity (Shannon index P-value = 0.03) and taxonomic composition (PERMANOVA, P-value = 0.02) was mainly driven by the type of wastewater samples (treated & untreated) and geographic location. However, these WWTPs were also found to contain a core community of protozoan parasites. The untreated wastewater samples revealed a predominant presence of free-living, parasitic, and potentially pathogenic protists typically found in humans and animals, ranging from Alveolata (27 %) phylum (Apicomplexa and Ciliophora) to Excavata (3.88 %) (Discoba and Parasalia) and Amoebozoa (2.84 %) (Entamoeba and Acanthamoeba). Shotgun metagenomics analyses in a subset of the untreated wastewater samples confirmed the presence of public health-importance protozoa, including Cryptosporidium species (3.48 %), Entamoeba hystolitica (6.58 %), Blastocystis hominis (2.91 %), Naegleria gruberi (2.37 %), Toxoplasma gondii (1.98 %), Cyclospora cayetanensis (1.30 %), and Giardia intestinalis (0.31 %). Virulent gene families linked to pathogenic protozoa, such as serine/threonine protein phosphatase and mucin-desulfating sulfatase were identified. Additionally, enriched pathways included thiamine diphosphate biosynthesis III, heme biosynthesis, Methylerythritol 4-Phosphate Pathway, methyl erythritol phosphate (MEP), and pentose phosphate pathways. These findings suggest that protozoan pathogens may possess metabolic and growth potential within WWTPs, posing a severe risk of transmission to humans and animals if inadequately disinfected before release. This study provides a baseline for the future investigation of diverse protozoal communities in wastewater, which are of public health importance.

Anthelmintic resistance in soil-transmitted helminths: One-Health considerations.

The One-Health approach recognizes the intricate connection between human, animal, and environmental health, and that cooperative effort from various professionals provides comprehensive awareness and potential solutions for issues relating to the health of people, animals, and the environment. This approach has increasingly gained appeal as the standard strategy for tackling emerging infectious diseases, most of which are zoonoses. Treatment with anthelmintics (AHs) without a doubt minimizes the severe consequences of soil-transmitted helminths (STHs); however, evidence of anthelmintic resistance (AR) development to different helminths of practically every animal species and the distinct groups of AHs is overwhelming globally. In this regard, the correlation between the application of anthelmintic drugs in both human and animal populations and the consequent development of anthelmintic resistance in STHs within the context of a One-Health framework is explored. This review provides an overview of the major human and animal STHs, treatment of the STHs, AR development and drug-related factors contributing towards AR, One-Health and STHs, and an outline of some One-Health strategies that may be used in combating AR.

Surveillance of multidrug-resistant tuberculosis in sub-Saharan Africa through wastewater-based epidemiology.

The spread of multidrug-resistant tuberculosis (MDR-TB) is a serious public health issue, particularly in developing nations. The current methods of monitoring drug-resistant TB (DR-TB) using clinical diagnoses and hospital records are insufficient due to limited healthcare access and underreporting. This study proposes using Wastewater-Based Epidemiology (WBE) to monitor DR-TB in six African countries (Ghana, Nigeria, Kenya, Uganda, Cameroon, and South Africa) and examines the impact of treated wastewater on the spread of TB drug-resistant genes in the environment. Using droplet-digital polymerase chain reaction (ddPCR), the study evaluated untreated and treated wastewater samples in selected African countries for TB surveillance. There was a statistically significant difference in concentrations of genes conferring resistance to TB drugs in wastewater samples from the selected countries (p-value<0.05); South African samples exhibited the highest concentrations of 4.3(±2,77), 4.8(±2.96), 4.4(±3,10) and 4.7(±3,39) log copies/ml for genes conferring resistance to first-line TB drugs (katG, rpoB, embB and pncA respectively) in untreated wastewater. This may be attributed to the higher prevalence of TB/MDR-TB in SA compared to other African countries. Interestingly, genes conferring resistance to second-line TB drugs such as delamanid (ddn gene) and bedaquiline (atpE gene) were detected in relatively high concentrations (4.8(±3,67 and 3.2(±2,31 log copies/ml for ddn and atpE respectively) in countries, such as Cameroon, where these drugs are not part of the MDR-TB treatment regimens, perhaps due to migration or the unapproved use of these drugs in the country. The gene encoding resistance to streptomycin (rrs gene) was abundant in all countries, perhaps due to the common use of this antibiotic for infections other than TB. These results highlight the need for additional surveillance and monitoring, such as WBE, to gather data at a community level. Combining WBE with the One Health strategy and current TB surveillance systems can help prevent the spread of DR-TB in populations.

GC-MS based untargeted metabolomics reveals the metabolic response of earthworm (Eudrilus eugeniae) after chronic combinatorial exposure to three different pesticides.

In this study GC-MS-based untargeted metabolomics was used to identify the metabolic response of earthworm; Eudrilus eugeniae exposed to sub-lethal concentrations of chlorpyrifos-CHL, cypermethrin-CYP, Glyphosate-GLY, and Combined-C (all three pesticides) at the concentrations of 3, 6, and 12 mg/kg. Principal component analysis of the obtained datasets revealed a clear distinction between the control and treatment groups. The mean weight of the worms in the treated groups decreased significantly (p < 0.05). Among the identified metabolites, oleic acid (~ 93.47%), lysine (~ 92.20%), glutamic acid (~ 91.81%), leucine (~ 90.20%), asparagine (~ 94.20%), methionine (~ 92.27%), malic acid (~ 93.37%), turanose (~ 95.04%), maltose (~ 92.36%), cholesta-3,5-diene (~ 86.11%), galactose (~ 93.20%), cholesterol (~ 91.56%), tocopherol (~ 85.09%), decreased significantly (p < 0.05), whereas myoinositol (~ 83%) and isoleucine (78.09%) increased significantly (p < 0.05) upon exposure to the CHL, CYP, GLY, and C. Overall, the findings suggest that earthworms might be a new entry point for the pesticides into the food chain. The present study highlights that metabolomics can be a reliable approach to understand the effect of different xenobiotics including pesticides on the metabolic response of earthworms.

Exploring the role of wastewater-based epidemiology in understanding tuberculosis burdens in Africa.

Tuberculosis (TB) remains a persistent challenge to public health and presents a substantial menace, especially in developing nations of sub-Saharan Africa. It exerts a considerable strain on healthcare systems in these regions. Effective control requires reliable surveillance, which can be improved by incorporating environmental data alongside clinical data. Molecular advances have led to the development of alternative surveillance methods, such as wastewater-based epidemiology. This studyinvestigated the presence, concentration, and diversity of Mycobacterium tuberculosis complex, the cause of TB, in from six African countries: Ghana, Nigeria, Kenya, Uganda, Cameroon, and South Africa. Samples were collected from wastewater treatment plants. All samples were found to contain Mycobacterium species that have been linked to TB in both humans and animals, including Mycobacterium tuberculosis complex, Mycobacterium tuberculosis, Mycobacterium bovis, Mycobacterium africanum, and Mycobacterium caprae, at varying concentrations. The highest median concentration was found in Ghana, reaching up to 4.7 Log copies/ml for MTBC, 4.6 Log copies/ml for M. bovis, and 3.4 Log copies/ml for M. africanum. The presence of M. africanum outside of West Africa was found in South Africa, Kenya, and Uganda and could indicate the spread of the pathogen. The study underscores the usefulness of wastewater-based epidemiology for tracking TB and shows that even treated wastewater may contain these pathogens, posing potential public health risks.

Modeling and optimization of chlorpyrifos and glyphosate biodegradation using RSM and ANN: Elucidating their degradation pathways by GC-MS based metabolomics.

Ongoing and extensive use of pesticides negatively impact the environment and human health. Microbe-based remediation bears importance as it is an eco-friendly and cost-effective technique. The present study investigated chlorpyrifos (CHL) and glyphosate (GLY) degrading potential of Bacillus cereus AKAD 3-1, isolated from the soybean rhizosphere. Optimization and validation of different process variables were carried out by response surface methodology (RSM) and artificial neural network (ANN). Critical parameters which affect the degradation process are initial pesticide concentration, pH, and inoculum size. At optimum conditions, the bacterial strain demonstrated 94.52% and 83.58% removal of chlorpyrifos and glyphosate, respectively. Both Central-composite design (CCD-RSM) and ANN approaches proved to perform well in modeling and optimizing the growth conditions. The optimum ANN-GA model resulted in R2 ≥ 0.99 for chlorpyrifos and glyphosate, while in the case of RSM, the obtained R2 value was 0.96 and 0.95, respectively. Results indicated that the process variables significantly (p < 0.05) impact chlorpyrifos and glyphosate biodegradation. Moreover, the predicted RSM model had a "lack of fit p-value" of "0.8849" and "0.2502" for chlorpyrifos and glyphosate, respectively. GC-MS analysis revealed that the strain first converted chlorpyrifos into 3,5,6-trichloro pyridin-2-ol & O, O-diethyl O-hydrogen phosphorothiate. Later, these intermediate metabolites were broken and completely mineralized into non-toxic by-products. Similarly, glyphosate was first converted into 2-(methylamino) acetic acid and amino-oxyphosphonic acid, which were further mineralized without any toxic by-products. Taken together, the results of this study clarify the biodegradation pathways and highlights the promising potential of B. cereus AKAD 3-1 in the bioremediation of chlorpyrifos and glyphosate-polluted environments.

Assessing the potential for nevirapine removal and its ecotoxicological effects on Coelastrella tenuitheca and Tetradesmus obliquus in aqueous environment.

Remediation of the antiretroviral (ARV) drug, nevirapine (NVP) has attracted considerable scientific attention in recent years due to its frequent detection and persistence in aquatic environments and potential hazards to living organisms. Algae-based technologies have been emerging as an environmentally friendly option for the removal of pharmaceutical compounds, but their ARV drug removal potential has not been fully explored yet. This study aimed to explore the ecotoxicity and removal potential of NVP by two microalgal species, Coelastrella tenuitheca and Tetradesmus obliquus. Lower environmental concentrations (up to 200 ng L-1) of NVP enhanced the microalgal growth, and the highest dry cell weight of 941.27 mg L-1 was obtained in T. obliquus at 50 ng L-1 NVP concentration. Both microalgae showed varying removal efficiencies (19.53-74.56%) when exposed to NVP concentration levels of up to 4000 ng L-1. At the late log phase (day 8), T. obliquus removed the highest percentage of NVP (74.56%), while C. tenuitheca removed 48% at an initial NVP concentration of 50 ng L-1. Photosynthetic efficiency (Fv/Fm and rETR) of the two microalgal species, however, was not affected by environmental concentrations of NVP (up to 4000 ng L-1) at the mid log phase of growth. SEM analysis demonstrated that both algal species produced distinct ridges on their cell surfaces after NVP uptake. In the ecotoxicity study, the calculated IC50 values of NVP (0-100 mg L-1) after 96 h of exposure were 23.45 mg L-1 (C. tenuitheca) and 18.20 mg L-1 (T. obliquus). The findings of the present study may contribute to a better understanding of the environmental hazards associated with NVP and the efficacy of microalgae in removing this pharmaceutical from aquatic environments.

Biological nitrogen removal from low carbon wastewater.

Nitrogen has traditionally been removed from wastewater by nitrification and denitrification processes, in which organic carbon has been used as an electron donor during denitrification. However, some wastewaters contain low concentrations of organic carbon, which may require external organic carbon supply, increasing treatment costs. As a result, processes such as partial nitrification/anammox (anaerobic ammonium oxidation) (PN/A), autotrophic denitrification, nitritation-denitritation and bioelectrochemical processes have been studied as possible alternatives, and are thus evaluated in this study based on process kinetics, applicability at large-scale and process configuration. Oxygen demand for nitritation-denitritation and PN/A is 25% and 60% lower than for nitrification/denitrification, respectively. In addition, PN/A process does not require organic carbon supply, while its supply for nitritation-denitritation is 40% less than for nitrification/denitrification. Both PN/A and nitritation-denitritation produce less sludge compared to nitrification/denitrification, which saves on sludge handling costs. Similarly, autotrophic denitrification generates less sludge compared to heterotrophic denitrification and could save on sludge handling costs. However, autotrophic denitrification driven by metallic ions, elemental sulfur (S) and its compounds could generate harmful chemicals. On the other hand, hydrogenotrophic denitrification can remove nitrogen completely without generation of harmful chemicals, but requires specialized equipment for generation and handling of hydrogen gas (H2), which complicates process configuration. Bioelectrochemical processes are limited by low kinetics and complicated process configuration. In sum, anammox-mediated processes represent the best alternative to nitrification/denitrification for nitrogen removal in low- and high-strength wastewaters.

Effects of antimicrobials in anammox mediated systems: critical review.

Anammox-mediated systems are thought to be cost-effective and efficient technologies for removing nitrogen from wastewater by converting nitrite and ammonium into dinitrogen gas. However, there are inhibitory substances that reduce the effectiveness and efficiency of these processes, preventing their widespread application. Antimicrobial agents are among these substances that have been observed to inhibit anammox-mediated processes. Therefore, this review provides a comprehensive overview of the effects of various antimicrobials on the anammox-based systems with emphasis on the effects in different reactor configurations, sludge types and microbial population of anammox-based systems. In addition, this review also discusses the mechanisms by which nitrifying bacteria are inhibited by the antimicrobials. Gaps in knowledge based on this review as well as future research needs have also been suggested. This review gives a better knowledge of antimicrobial effects on anammox-based systems and provides some guidance on the type of system to use to treat antimicrobial-containing wastewater using anammox-based processes.

Fluorescence and colorimetric LAMP-based real-time detection of human pathogenic Cryptosporidium spp. from environmental samples.

Public health concerns related to pathogenic protozoa are widespread, causing significant morbidity and mortality worldwide. Due to the lack of rapid and cost-effective diagnostic methods, timely treatment and control interventions are hindered. In this study, loop mediated isothermal amplification (LAMP) methods were optimised and evaluated for the rapid detection of human pathogenic Cryptosporidium species in environmental samples. Real-time fluorescence and colorimetric detection were tested simultaneously. As a reference method, the results were compared to the well-established droplet digital polymerase chain reaction (ddPCR) method. Both LAMP-based methods successfully detected the Cryptosporidium parvum (GP60 gene) and the entire Cryptosporidium genus (SAM gene) from environmental samples with 100% specificity and no cross-reactivity. Furthermore, both colorimetric and fluorescent methods demonstrated a high sensitivity, with the same limit of detection (LOD) of 1.1 copies of C. parvum per 25 µl reaction (0.02 ng/µl). For real-time fluorescence monitoring, the LAMP reaction can be completed within 28 min, and for visual detection, within 30 min. In addition, both fluorescent and colorimetric LAMP methods showed substantial agreement with the reference method (ddPCR) used. The developed protocols were able to detect C. parvum and Cryptosporidium spp. in 50-85% (n = 60) of environmental samples (treated and untreated wastewater, sludge, and surface water) compared to 58-98% (n = 60) detected by ddPCR. The results further demonstrate that LAMP is an efficient technique for detecting Cryptosporidium spp. in environmental samples due to its simplicity, low cost, sensitivity, and specificity. Therefore, it has great potential as a useful diagnostic tool for disease control and public health protection.

A probabilistic assessment of microbial infection risks due to occupational exposure to wastewater in a conventional activated sludge wastewater treatment plant.

Exposure to pathogens during wastewater treatment could result in significant health risks. In this paper, a probabilistic approach for assessing the risks of microbial infection for workers in an activated sludge wastewater treatment plant is presented. A number of exposure routes were modelled, including hand-to-mouth and droplet ingestion of untreated wastewater, droplet ingestion and inhalation of aerosols after secondary treatment, and ingestion of sludge during drying. Almost all workers exposed to untreated wastewater could be infected with the three selected potential pathogens of pathogenic E. coli, Norovirus and Cryptosporidium spp. Hand-to-mouth ingestion is the single most significant route of exposure at the head of works. There is also a risk of infections resulting from ingestion of droplets or inhalation of aerosols at the aeration tanks or contaminated hands at the clarifiers during secondary wastewater treatment. For sludge, the risks of infection with Norovirus was found to be the highest due to accidental ingestion (median risks of 2.2 × 10-2(±3.3 × 10-3)). Regardless of the point and route of exposure, Norovirus and Cryptosporidium spp. presented the highest risks. The study finds that occupational exposure to wastewater at wastewater treatment plants can result in significant viral and protozoan infections. This risk assessment framework can be used to establish and measure the success of risk reduction measures in wastewater treatment plants. These measures could include the use of personal protective equipment and adherence to strict personal hygiene.

Multidisciplinary characterization of nitrogen-removal granular sludge: A review of advances and technologies.

Nitrogen-removal granular sludge (NRGS) is a promising technology in wastewater treatment, with advantages of efficient nitrogen removal, less footprint, lower sludge production and energy consumption, and is a way for wastewater treatment plants to achieve carbon-neutrality. Aerobic granular sludge (AGS) and anammox granular sludge (AnGS) are two typical NRGS technologies that have attracted extensive attention. Mounting evidence has shown strong associations between NRGS properties and the status of NRGS systems; however, a holistic view is still missing. The aim of this article is to provide an overview of NRGS with an emphasis on characterization. Specifically, the integrated nitrogen transformation pathways inside NRGS and the performance of NRGS treating various wastewaters are discussed. NRGS properties are categorized as physical-, chemical-, biological- and systematical ones, presenting current advances and corresponding characterization technologies. Finally, the future prospects for furthering the mechanistic understanding and engineering application of NRGS are proposed. Overall, the technological advancements in characterization have greatly contributed to understanding NRGS properties, which are potential factors for optimizing the performance and evaluating the working status of NRGS. This review will provide guidance in characterizing NRGS properties and boost the introduction of novel characterization technologies.