Using total adenosine triphosphate (tATP) measurements for cyanobacterial bloom monitoring and response assessment during algaecide treatments.

Total adenosine triphosphate (tATP) was investigated for its potential as a rapid indicator of cyanobacterial growth and algaecide effectiveness. tATP and other common bloom monitoring parameters were measured over the growth cycles of cyanobacteria and green algae in laboratory cultures and examined at a drinking water source during an active bloom. Strong correlations (R2>0.78) were observed between tATP and chlorophyll-a in cyanobacteria cultures. tATP offered greater sensitivity by increasing two orders of magnitude approximately 7 d before changes in chlorophyll-a or optical density were observed in Lyngbya sp. and Dolichospermum sp. cultures. Increases in tATP per cell coincided with the onset of exponential growth phases in lab cultures and increase in cell abundance in field samples, suggesting that ATP/cell is a sensitive indicator that may be used to identify the development of blooms. Bench-scale trials using samples harvested during a bloom showed that tATP exhibited a clear dose-response during copper sulfate (CuSO4) and hydrogen peroxide (H2O2) treatment compared to chlorophyll-a and cell counts, indicating that cellular production and storage of ATP decreases even when live and dead cells cannot be distinguished. During Copper (Cu) algaecide application at a reservoir used as a drinking water source, tATP and cell counts decreased following initial algaecide application; however, the bloom rebounded within 10 d showing that the Cu algaecide only has limited effectiveness. In this case, tATP was a sensitive indicator to bloom rebounding after algaecide treatments and correlated positively with cell counts (R2=0.7). These results support the use of tATP as a valuable complementary bloom monitoring tool for drinking water utilities to implement during the monitoring and treatment of cyanobacterial blooms.

A review of foam fractionation for the removal of per- and polyfluoroalkyl substances (PFAS) from aqueous matrices.

The detection of per- and polyfluoroalkyl substances (PFAS) in aqueous matrices is an emerging environmental concern due to their persistent, bioaccumulative and toxic properties. Foam fractionation has emerged as a viable method for removing and concentrating PFAS from aqueous matrices. The method exploits the surface-active nature of the PFAS to adsorb at the air-liquid interfaces of rising air bubbles, resulting in foam formation at the top of a foam fractionator. The removal of PFAS is then achieved through foam harvesting. Foam fractionation has gained increasing attention owing to its inherent advantages, including simplicity and low operational costs. The coupling of foam fractionation with destructive technologies could potentially serve as a comprehensive treatment train for future PFAS management in aqueous matrices. The PFAS-enriched foam, which has a smaller volume, can be directed to subsequent destructive treatment technologies. In this review, we delve into previous experiences with foam fractionation for PFAS removal from various aqueous matrices and critically analyse their key findings. Then, the recent industry advancements and commercial projects that utilise this technology are identified. Finally, future research needs are suggested based on the current challenges.

Monitoring of cyanobacterial breakthrough and accumulation by in situ phycocyanin probe system within full-scale treatment plants.

Worldwide, there has been an increase in the presence of potentially toxic cyanobacterial blooms in drinking water sources and within drinking water treatment plants (DWTPs). The objective of this study is to validate the use of in situ probes for the detection and management of cyanobacterial breakthrough in high and low-risk DWTPs. In situ phycocyanin YSI EXO2 probes were devised for remote control and data logging to monitor the cyanobacteria in raw, clarified, filtered, and treated water in three full-scale DWTPs. An additional probe was installed inside the sludge holding tank to measure the water quality of the surface of the sludge storage tank in a high-risk DWTP. Simultaneous grab samplings were carried out for taxonomic cell counts and toxin analysis. A total of 23, 9, and 4 field visits were conducted at the three DWTPs. Phycocyanin readings showed a 93-fold fluctuation within 24 h in the raw water of the high cyanobacterial risk plant, with higher phycocyanin levels during the afternoon period. These data provide new information on the limitations of weekly or daily grab sampling. Also, different moving averages for the phycocyanin probe readings can be used to improve the interpretation of phycocyanin signal trends. The in situ probe successfully detected high cyanobacterial biovolumes entering the clarification process in the high-risk plant. Grab sampling results revealed high cyanobacterial biovolumes in the sludge for both high and low-risk plants.

Evaluating Ultrasonicator Performance for Cyanobacteria Management at Freshwater Sources.

Algal blooms consisting of potentially toxic cyanobacteria are a growing source water management challenge faced by water utilities globally. Commercially available sonication devices are designed to mitigate this challenge by targeting cyanobacteria-specific cellular features and aim to inhibit cyanobacterial growth within water bodies. There is limited available literature evaluating this technology; therefore, a sonication trial was conducted in a drinking water reservoir within regional Victoria, Australia across an 18-month period using one device. The trial reservoir, referred to as Reservoir C, is the final reservoir in a local network of reservoirs managed by a regional water utility. Sonicator efficacy was evaluated through qualitative and quantitative analysis of algal and cyanobacterial trends within Reservoir C and surrounding reservoirs using field data collected across three years preceding the trial and during the 18-month duration of the trial. Qualitative assessment revealed a slight increase in eukaryotic algal growth within Reservoir C following device installation, which is likely due to local environmental factors such as rainfall-driven nutrient influx. Post-sonication quantities of cyanobacteria remained relatively consistent, which may indicate that the device was able to counteract favorable phytoplankton growth conditions. Qualitative assessments also revealed minimal prevalence variations of the dominant cyanobacterial species within the reservoir following trial initiation. Since the dominant species were potential toxin producers, there is no strong evidence that sonication altered Reservoir C's water risk profiles during this trial. Statistical analysis of samples collected within the reservoir and from the intake pipe to the associated treatment plant supported qualitative observations and revealed a significant elevation in eukaryotic algal cell counts during bloom and non-bloom periods post-installation. Corresponding cyanobacteria biovolumes and cell counts revealed that no significant changes occurred, excluding a significant decrease in bloom season cell counts measured within the treatment plant intake pipe and a significant increase in non-bloom season biovolumes and cell counts as measured within the reservoir. One technical disruption occurred during the trial; however, this had no notable impacts on cyanobacterial prevalence. Acknowledging the limitations of the experimental conditions, data and observations from this trial indicate there is no strong evidence that sonication significantly reduced cyanobacteria occurrence within Reservoir C.

A review on microalgae-mediated biotechnology for removing pharmaceutical contaminants in aqueous environments: Occurrence, fate, and removal mechanism.

Pharmaceutical compounds in aquatic environments have been considered as emerging contaminants due to their potential risks to living organisms. Microalgae-based technology showed the feasibility of removing pharmaceutical contaminants. This review summarizes the occurrence, classification, possible emission sources, and environmental risk of frequently detected pharmaceutical compounds in aqueous environments. The efficiency, mechanisms, and influencing factors for the removal of pharmaceutical compounds through microalgae-based technology are further discussed. Pharmaceutical compounds frequently detected in aqueous environments include antibiotics, hormones, analgesic and non-steroidal anti-inflammatory drugs (NSAIDs), cardiovascular agents, central nervous system drugs (CNS), antipsychotics, and antidepressants, with a concentration ranging from ng/L to µg/L. Microalgae-based technology majorly remove the pharmaceutical compounds through bioadsorption, bioaccumulation, biodegradation, photodegradation, and co-metabolism. This review identifies the opportunities and challenges for microalgae-based technology and proposed suggestions for future studies to tackle challenges. The findings of this review advance our understanding of the occurrence and fate of pharmaceutical contaminants in aqueous environments, highlighting the potential of microalgae-based technology for pharmaceutical contaminants removal.

An exploration of challenges associated with machine learning for time series forecasting of COVID-19 community spread using wastewater-based epidemiological data.

Wastewater-based epidemiology (WBE) has gained increasing attention as a complementary tool to conventional surveillance methods with potential for significant resource and labour savings when used for public health monitoring. Using WBE datasets to train machine learning algorithms and develop predictive models may also facilitate early warnings for the spread of outbreaks. The challenges associated with using machine learning for the analysis of WBE datasets and timeseries forecasting of COVID-19 were explored by running Random Forest (RF) algorithms on WBE datasets across 108 sites in five regions: Scotland, Catalonia, Ohio, the Netherlands, and Switzerland. This method uses measurements of SARS-CoV-2 RNA fragment concentration in samples taken at the inlets of wastewater treatment plants, providing insight into the prevalence of infection in upstream wastewater catchment populations. RF's forecasting performance at each site was quantitatively evaluated by determining mean absolute percentage error (MAPE) values, which was used to highlight challenges affecting future implementations of RF for WBE forecasting efforts. Performance was generally poor using WBE datasets from Catalonia, Scotland, and Ohio with 'reasonable' or better forecasts constituting 0 %, 5 %, and 0 % of these regions' forecasts, respectively. RF's performance was much stronger with WBE data from the Netherlands and Switzerland, which provided 55 % and 45 % 'reasonable' or better forecasts respectively. Sampling frequency and training set size were identified as key factors contributing to accuracy, while inclusion of too many unnecessary variables (or e.g., flow data) was identified as a contributing factor to poor performance. The contribution of catchment population on forecast accuracy was more ambiguous. This study determined that the factors governing RF's forecast performance are complicated and interrelated, which presents challenges for further work in this space. A sufficiently accurate further iteration of the tool discussed within this study would provide significant but varying value for public health departments for monitoring future, or ongoing outbreaks, assisting the implementation of on-time health response measures.

Impact of Stagnation on the Diversity of Cyanobacteria in Drinking Water Treatment Plant Sludge.

Health-related concerns about cyanobacteria-laden sludge of drinking water treatment plants (DWTPs) have been raised in the past few years. Microscopic taxonomy, shotgun metagenomic sequencing, and microcystin (MC) measurement were applied to study the fate of cyanobacteria and cyanotoxins after controlled sludge storage (stagnation) in the dark in a full-scale drinking water treatment plant within 7 to 38 days. For four out of eight dates, cyanobacterial cell growth was observed by total taxonomic cell counts during sludge stagnation. The highest observed cell growth was 96% after 16 days of stagnation. Cell growth was dominated by potential MC producers such as Microcystis, Aphanocapsa, Chroococcus, and Dolichospermum. Shotgun metagenomic sequencing unveiled that stagnation stress shifts the cyanobacterial communities from the stress-sensitive Nostocales (e.g., Dolichospermum) order towards less compromised orders and potential MC producers such as Chroococcales (e.g., Microcystis) and Synechococcales (e.g., Synechococcus). The relative increase of cyanotoxin producers presents a health challenge when the supernatant of the stored sludge is recycled to the head of the DWTP or discharged into the source. These findings emphasize the importance of a strategy to manage cyanobacteria-laden sludge and suggest practical approaches should be adopted to control health/environmental impacts of cyanobacteria and cyanotoxins in sludge.

Evidence-Based Framework to Manage Cyanobacteria and Cyanotoxins in Water and Sludge from Drinking Water Treatment Plants.

Freshwater bodies and, consequently, drinking water treatment plants (DWTPs) sources are increasingly facing toxic cyanobacterial blooms. Even though conventional treatment processes including coagulation, flocculation, sedimentation, and filtration can control cyanobacteria and cell-bound cyanotoxins, these processes may encounter challenges such as inefficient removal of dissolved metabolites and cyanobacterial cell breakthrough. Furthermore, conventional treatment processes may lead to the accumulation of cyanobacteria cells and cyanotoxins in sludge. Pre-oxidation can enhance coagulation efficiency as it provides the first barrier against cyanobacteria and cyanotoxins and it decreases cell accumulation in DWTP sludge. This critical review aims to: (i) evaluate the state of the science of cyanobacteria and cyanotoxin management throughout DWTPs, as well as their associated sludge, and (ii) develop a decision framework to manage cyanobacteria and cyanotoxins in DWTPs and sludge. The review identified that lab-cultured-based pre-oxidation studies may not represent the real bloom pre-oxidation efficacy. Moreover, the application of a common exposure unit CT (residual concentration × contact time) provides a proper understanding of cyanobacteria pre-oxidation efficiency. Recently, reported challenges on cyanobacterial survival and growth in sludge alongside the cell lysis and cyanotoxin release raised health and technical concerns with regards to sludge storage and sludge supernatant recycling to the head of DWTPs. According to the review, oxidation has not been identified as a feasible option to handle cyanobacterial-laden sludge due to low cell and cyanotoxin removal efficacy. Based on the reviewed literature, a decision framework is proposed to manage cyanobacteria and cyanotoxins and their associated sludge in DWTPs.

Benthic cyanobacteria: A utility-centred field study.

Although there is growing evidence that benthic cyanobacteria represent a significant source of toxins and taste and odour (T&O) compounds in water bodies globally, water utilities rarely monitor for them. Benthic cyanobacteria grow in an array of matrices such as sediments, biofilms, and floating mats, and they can detach and colonize treatment plants. The occurrence of compounds produced by benthic species across matrix and climate types has not been systematically investigated. Consequently, there is a lack of guidance available to utilities to monitor for and mitigate the risk associated with benthic cyanobacteria. To assess toxin and T&O risk across climatic zones and provide guidance to water utilities for the monitoring of benthic mats, two field surveys were conducted across three continents. The surveys examined the occurrence of six secondary metabolites and associated genes, namely, geosmin, 2-methylisoborneol (MIB), anatoxin-a, saxitoxin, microcystin, and cylindrospermopsin, in benthic environmental samples collected across three climates (i.e., temperate, sub-tropical, and tropical) and a range of matrix types. Existing enzyme-linked immunosorbent assays (ELISAs) and qPCR assays and were used to measure compound concentrations and their associated genes in samples. A novel qPCR assay was designed to differentiate the production of MIB by actinobacteria from that of cyanobacteria. MIB occurrence was higher in warmer climates than temperate climates. Cyanobacteria in benthic mats were the major producers of taste and odour compounds. Floating mats contained significantly higher concentrations of geosmin and saxitoxins compared to other matrix types. Samples collected in warmer areas contained significantly more saxitoxin and cylindrospermopsin than samples collected in temperate climates. While these trends were mainly indicative, they can be used to establish monitoring practices. These surveys demonstrate that benthic mats are significant contributors of secondary metabolites in source water and should be monitored accordingly. Benthic cyanobacteria were the sole producers of T&O in up to 17% of the collected samples compared to actinobacteria, which were sole producers in only 1% of the samples. The surveys also provided a platform of choice for the transfer of methodologies and specific knowledge to participating utilities to assist with the establishment of monitoring practices for benthic cyanobacteria and associated secondary metabolites.

A review of microscopic cell imaging and neural network recognition for synergistic cyanobacteria identification and enumeration.

Real-time cyanobacteria/algal monitoring is a valuable tool for early detection of harmful algal blooms, water treatment efficacy evaluation, and assists tailored water quality risk assessments by considering taxonomy and cell counts. This review evaluates and proposes a synergistic approach using neural network image recognition and microscopic imaging devices by first evaluating published literature for both imaging microscopes and image recognition. Quantitative phase imaging was considered the most promising of the investigated imaging techniques due to the provision of enhanced information relative to alternatives. This information provides significant value to image recognition neural networks, such as the convolutional neural networks discussed within this review. Considering published literature, a cyanobacteria monitoring system and corresponding image processing workflow using in situ sample collection buoys and on-shore sample processing was proposed. This system can be implemented using commercially available equipment to facilitate accurate, real-time water quality monitoring.

Advancements in detection and removal of antibiotic resistance genes in sludge digestion: A state-of-art review.

Sludge from wastewater treatment plants can act as a repository and crucial environmental provider of antibiotic resistance genes (ARGs). Over the past few years, people's knowledge regarding the occurrence and removal of ARGs in sludge has broadened remarkably with advancements in molecular biological techniques. Anaerobic and aerobic digestion were found to effectively achieve sludge reduction and ARGs removal. This review summarized advanced detection and removal techniques of ARGs, in the last decade, in the sludge digestion field. The fate of ARGs due to different sludge digestion strategies (i.e., anaerobic and aerobic digestion under mesophilic or thermophilic conditions, and in combination with relevant pretreatment technologies (e.g., thermal hydrolysis pretreatment, microwave pretreatment and alkaline pretreatment) and additives (e.g., ferric chloride and zero-valent iron) were systematically summarized and compared in this review. To date, this is the first review that provides a comprehensive assessment of the state-of-the-art technologies and future recommendations.

A critical review on operation and performance of source water control strategies for cyanobacterial blooms: Part I-chemical control methods.

Cyanobacterial blooms produce nuisance metabolites (e.g., cyanotoxins and T&O compounds) thereby posing water quality management issues for aquatic sources used for potable water production, aquaculture, and recreation. A variety of in-lake/reservoir control measures are implemented to reduce the abundance of nuisance cyanobacteria biomass or decrease the amount of available phosphorous (P). This paper critically reviews the chemical control strategies implemented for in-lake/reservoir management of cyanobacterial blooms, i.e., algaecides and nutrient sequestering coagulants/flocculants, by highlighting (i) their mode of action, (ii) cases of successful and unsuccessful treatment, (iii) and factors influencing performance (e.g., water quality, process control techniques, source water characteristics, etc.). Algaecides generally result in immediate improvements in water quality and offer selective cyanobacterial control when peroxide-based alagecides are used. However, they have a range of limitations: causing cell lysis and release of cyanotoxins, posing negative impacts on aquatic plants and animals, leaving behind environmentally relevant treatment residuals (e.g., Cu in water and sediments), and offering only short-term bloom control characterized by cyanobacterial rebound. Coagulants/flocculants (alum, iron, calcium, and lanthanum bentonite) offer long-term internal nutrient control when external nutrient loading is controlled. Treatment performance is often influenced by background water quality conditions, and source water characteristics (e.g., surface area, depth, mixing regimes, and residence time). The reviewed case studies highlight that external nutrient load reduction is the most fundamental aspect of cyanobacterial control. None of the reviewed control strategies provide a comprehensive solution to cyanobacterial blooms.

A critical review on operation and performance of source water control strategies for cyanobacterial blooms: Part II-mechanical and biological control methods.

This review summarizes current knowledge on mechanical (artificial mixing, hypolimnetic aeration, dredging, and sonication) and biological (biomanipulation, macrophytes, and straws) methods for the management of cyanobacterial blooms in drinking water sources. Emphasis has been given to (i) the mechanism of cyanobacterial control, (ii) successful and unsuccessful case studies, and (iii) factors influencing successful implementation. Most mechanical and biological control strategies offer long-term control. However, their application can be cost-prohibitive and treatment efficacy is influenced by source water geometry and continual nutrient inputs from external sources. When artificial mixing and hypolimnetic oxygenation units are optimized based on source water characteristics, observed water quality benefits included increased dissolved oxygen contents, reduced internal loading of nutrients, and lower concentrations of reduced ions . Treatment efficacy during oxygenation and aeration was derailed by excessive sedimentation of organic matter and sediment characteristics such as low Fe/P ratios. Dredging is beneficial for contaminated sediment removal, but it is too costly to be a practical bloom control strategy for most systems. Sonication control methods have contradictory findings requiring further research to evaluate the efficacy and applicability for field-scale control of cyanobacteria. Biological control methods such as biomanipulation offer long-term treatment benefits; however, investigations on the mechanisms of field-scale cyanobacterial control are still limited, particularly with the use of macrophytes and straws. Each control method has site-specific strengths, limitations, and ecological impacts. Reduction of external nutrient inputs should still be a significant focus of restoration efforts as treatment benefits from mechanical and biological control were commonly offset by continued nutrient inputs.

Comparative Assessment of Physical and Chemical Cyanobacteria Cell Lysis Methods for Total Microcystin-LR Analysis.

Standardization and validation of alternative cell lysis methods used for quantifying total cyanotoxins is needed to improve laboratory response time goals for total cyanotoxin analysis. In this study, five cell lysis methods (i.e., probe sonication, microwave, freeze-thaw, chemical lysis with Abraxis QuikLyseTM, and chemical lysis with copper sulfate) were assessed using laboratory-cultured Microcystis aeruginosa (M. aeruginosa) cells. Methods were evaluated for destruction of cells (as determined by optical density of the sample) and recovery of total microcystin-LR (MC-LR) using three M. aeruginosa cell densities (i.e., 1 × 105 cells/mL (low-density), 1 × 106 cells/mL (medium-density), and 1 × 107 cells/mL (high-density)). Of the physical lysis methods, both freeze-thaw (1 to 5 cycles) and pulsed probe sonication (2 to 10 min) resulted in >80% destruction of cells and consistent (>80%) release and recovery of intracellular MC-LR. Microwave (3 to 5 min) did not demonstrate the same decrease in optical density (<50%), although it provided effective release and recovery of >80% intracellular MC-LR. Abraxis QuikLyseTM was similarly effective for intracellular MC-LR recovery across the different M. aeruginosa cell densities. Copper sulfate (up to 500 mg/L Cu2+) did not lyse cells nor release intracellular MC-LR within 20 min. None of the methods appeared to cause degradation of MC-LR. Probe sonication, microwave, and Abraxis QuikLyseTM served as rapid lysis methods (within minutes) with varying associated costs, while freeze-thaw provided a viable, low-cost alternative if time permits.

Multi-proxy approaches to investigate cyanobacteria invasion from a eutrophic lake into the circumjacent groundwater.

To verify whether cyanobacteria can travel from eutrophic lakes into the surrounding groundwater, a large-scale field investigation, laboratorial incubations, and quartz column penetration tests were carried out in Lake Taihu (China). High-throughput sequencing of 16S rRNA gene amplicons indicated that cyanobacteria operational taxonomic units (OTUs) were present at fifteen out of forty total wells in four cardinal directions at varying distances from the shore of Lake Taihu, up to a maximum of forty-three kilometers. Six cyanobacteria genera were detected including Microcystis, Dolichospermum, Phormidium, Leptolyngbya, Pseudanabaena and Synechococcus. The proportions of Phormidium, Microcystis and Synechococcus OTUs in the total cyanobacterial community were 45.2%, 32.2% and 19.4%, respectively. The qRT-PCR results showed that cyanobacterial abundance decreased with increasing distance from the shore of Lake Taihu. Based on the microscopic analysis of cultures inoculated with groundwater, we found Microcystis, Dolichospermum and Phormidium. Five cyanobacterial genera were able to penetrate columns filled with quartz particles ranging from 100∼200 µm. Finer layers of quartz sands were found to be impenetrable. The rating of infiltration capabilities was Microcystis > Synechococcus > Nostoc > Phormidium > Cylindrospermopsis. Deficient concentrations of microcystins were found (< 1 µg L-1) in the groundwater samples. Based on the consideration of different factors (cyanobacterial composition in Lake Taihu, peripheral groundwater, and algal soil crusts), it was deduced that Microcystis likely originated from the lake. Still, Phormidium was probably originated from the soil infiltration. These results suggest that cyanobacteria and their toxins could travel in the groundwater, but this is a size-dependent mechanism.

Passive Sampling of SARS-CoV-2 for Wastewater Surveillance.

The shedding of pathogens by infected humans enables the use of sewage monitoring to conduct wastewater-based epidemiology (WBE). Although most WBE studies use data from large sewage treatment plants, timely data from smaller catchments are needed for targeted public health action. Traditional sampling methods, like autosamplers or grab sampling, are not conducive to quick ad hoc deployments and high-resolution monitoring at these smaller scales. This study develops and validates a cheap and easily deployable passive sampler unit, made from readily available consumables, with relevance to the COVID-19 pandemic but with broader use for WBE. We provide the first evidence that passive samplers can be used to detect SARS-CoV-2 in wastewater from populations with low prevalence of active COVID-19 infections (0.034 to 0.34 per 10,000), demonstrating their ability for early detection of infections at three different scales (lot, suburb, and city). A side by side evaluation of passive samplers (n = 245) and traditionally collected wastewater samples (n = 183) verified that the passive samplers were sensitive at detecting SARS-CoV-2 in wastewater. On all 33 days where we directly compared traditional and passive sampling techniques, at least one passive sampler was positive when the average SARS-CoV-2 concentration in the wastewater equaled or exceeded the quantification limit of 1.8 gene copies per mL (n = 7). Moreover, on 13 occasions where wastewater SARS-CoV-2 concentrations were less than 1.8 gene copies per mL, one or more passive samplers were positive. Finally, there was a statistically significant (p < 0.001) positive relationship between the concentrations of SARS-CoV-2 in wastewater and the levels found on the passive samplers, indicating that with further evaluation, these devices could yield semi-quantitative results in the future. Passive samplers have the potential for wide use in WBE with attractive feasibility attributes of cost, ease of deployment at small-scale locations, and continuous sampling of the wastewater. Further research will focus on the optimization of laboratory methods including elution and extraction and continued parallel deployment and evaluations in a variety of settings to inform optimal use in wastewater surveillance.

Machine learning for anomaly detection in cyanobacterial fluorescence signals.

Many drinking water utilities drawing from waters susceptible to harmful algal blooms (HABs) are implementing monitoring tools that can alert them to the onset of blooms. Some have invested in fluorescence-based online monitoring probes to measure phycocyanin, a pigment found in cyanobacteria, but it is not clear how to best use the data generated. Previous studies have focused on correlating phycocyanin fluorescence and cyanobacteria cell counts. However, not all utilities collect cell count data, making this method impossible to apply in some cases. Instead, this paper proposes a novel approach to determine when a utility needs to respond to a HAB based on machine learning by identifying anomalies in phycocyanin fluorescence data without the need for corresponding cell counts or biovolume. Four widespread and open source algorithms are evaluated on data collected at four buoys in Lake Erie from 2014 to 2019: local outlier factor (LOF), One-Class Support Vector Machine (SVM), elliptic envelope, and Isolation Forest (iForest). When trained on standardized historical data from 2014 to 2018 and tested on labelled 2019 data collected at each buoy, the One-Class SVM and elliptic envelope models both achieve a maximum average F1 score of 0.86 among the four datasets. Therefore, One-Class SVM and elliptic envelope are promising algorithms for detecting potential HABs using fluorescence data only.

Life-cycle cost analysis of a hybrid algae-based biological desalination - low pressure reverse osmosis system.

To fully understand the economic viability and implementation strategy of the emerging algae-based desalination technology, this study investigates the economic aspects of algae-based desalination system by comparing the life-cycle costs of three different scenarios: (1) a multi-stage microalgae based desalination system; (2) a hybrid desalination system based on the combination of microalgae and low pressure reverse osmosis (LPRO) system; and (3) a seawater reverse osmosis (SWRO) desalination system. It is identified that the capital expenditure (CAPEX) and operational expenditure (OPEX) of scenario 1 are significantly higher than those of scenarios 2 and 3, when algal biomass reuse is not taken into consideration. If the revenues obtained from the algal biomass reuse are taken into account, the OPEX of scenario 1 will decrease significantly, and scenarios 2 and 3 will have the highest and lowest OPEX, respectively. However, due to the high CAPEX of scenario 1, the total expenditure (TOTEX) of scenario 1 is still 27% and 33% higher than those of scenarios 2 and 3, respectively. A sensitivity study is undertaken to understand the effects of six key parameters on water total cost for different scenarios. It is suggested that the electricity unit price plays the most important role in determining the water total cost for different scenarios. An uncertainty analysis is also conducted to investigate the effects and limitations of the key assumptions made in this study. It is suggested that the assumption of total dissolved solids (TDS) removal efficiency of microalgae results in a high uncertainty of life-cycle cost analysis (LCCA). Additionally, it is estimated that 1.58 megaton and 0.30 megaton CO2 can be captured by the algae-based desalination process for scenarios 1 and 2, respectively, over 20 years service period, which could result in approximately AU $18 million and AU $3 million indirect financial benefits for scenarios 1 and 2, respectively. When algal biomass reuse, CO2 bio-fixation and land availability are all taken into account, scenario 2 with hybrid desalination system is considered as the most economical and environmentally friendly option.

Can Cyanobacterial Diversity in the Source Predict the Diversity in Sludge and the Risk of Toxin Release in a Drinking Water Treatment Plant?

Conventional processes (coagulation, flocculation, sedimentation, and filtration) are widely used in drinking water treatment plants and are considered a good treatment strategy to eliminate cyanobacterial cells and cell-bound cyanotoxins. The diversity of cyanobacteria was investigated using taxonomic cell counts and shotgun metagenomics over two seasons in a drinking water treatment plant before, during, and after the bloom. Changes in the community structure over time at the phylum, genus, and species levels were monitored in samples retrieved from raw water (RW), sludge in the holding tank (ST), and sludge supernatant (SST). Aphanothece clathrata brevis, Microcystis aeruginosa, Dolichospermum spiroides , and Chroococcus minimus were predominant species detected in RW by taxonomic cell counts. Shotgun metagenomics revealed that Proteobacteria was the predominant phylum in RW before and after the cyanobacterial bloom. Taxonomic cell counts and shotgun metagenomic showed that the Dolichospermum bloom occurred inside the plant. Cyanobacteria and Bacteroidetes were the major bacterial phyla during the bloom. Shotgun metagenomics also showed that Synechococcus, Microcystis , and Dolichospermum were the predominant detected cyanobacterial genera in the samples. Conventional treatment removed more than 92% of cyanobacterial cells but led to cell accumulation in the sludge up to 31 times more than in the RW influx. Coagulation/sedimentation selectively removed more than 96% of Microcystis and Dolichospermum. Cyanobacterial community in the sludge varied from raw water to sludge during sludge storage (1-13 days). This variation was due to the selective removal of coagulation/sedimentation as well as the accumulation of captured cells over the period of storage time. However, the prediction of the cyanobacterial community composition in the SST remained a challenge. Among nutrient parameters, orthophosphate availability was related to community profile in RW samples, whereas communities in ST were influenced by total nitrogen, Kjeldahl nitrogen (N- Kjeldahl), total and particulate phosphorous, and total organic carbon (TOC). No trend was observed on the impact of nutrients on SST communities. This study profiled new health-related, environmental, and technical challenges for the production of drinking water due to the complex fate of cyanobacteria in cyanobacteria-laden sludge and supernatant.

Diversity Assessment of Toxic Cyanobacterial Blooms during Oxidation.

Fresh-water sources of drinking water are experiencing toxic cyanobacterial blooms more frequently. Chemical oxidation is a common approach to treat cyanobacteria and their toxins. This study systematically investigates the bacterial/cyanobacterial community following chemical oxidation (Cl2, KMnO4, O3, H2O2) using high throughput sequencing. Raw water results from high throughput sequencing show that Proteobacteria, Actinobacteria, Cyanobacteria and Bacteroidetes were the most abundant phyla. Dolichospermum, Synechococcus, Microcystis and Nostoc were the most dominant genera. In terms of species, Dolichospermum sp.90 and Microcystis aeruginosa were the most abundant species at the beginning and end of the sampling, respectively. A comparison between the results of high throughput sequencing and taxonomic cell counts highlighted the robustness of high throughput sequencing to thoroughly reveal a wide diversity of bacterial and cyanobacterial communities. Principal component analysis of the oxidation samples results showed a progressive shift in the composition of bacterial/cyanobacterial communities following soft-chlorination with increasing common exposure units (CTs) (0-3.8 mg·min/L). Close cyanobacterial community composition (Dolichospermum dominant genus) was observed following low chlorine and mid-KMnO4 (287.7 mg·min/L) exposure. Our results showed that some toxin producing species may persist after oxidation whether they were dominant species or not. Relative persistence of Dolichospermum sp.90 was observed following soft-chlorination (0.2-0.6 mg/L) and permanganate (5 mg/L) oxidation with increasing oxidant exposure. Pre-oxidation using H2O2 (10 mg/L and one day contact time) caused a clear decrease in the relative abundance of all the taxa and some species including the toxin producing taxa. These observations suggest selectivity of H2O2 to provide an efficient barrier against toxin producing cyanobacteria entering a water treatment plant.