Estimating the risk of cyanobacterial occurrence using an index integrating meteorological factors: application to drinking water production

Climate change intensifies algal biomass resurgence in eutrophic Lake Taihu, China

Climate change can significantly alter phytoplankton growth and proliferation, which would counteract restoration efforts to control algal blooms. However, the knowledge is limited about the quantitative evaluation of the causal effect of algal biomass resurgence in large shallow lakes where there is no significant improvement after long term lake restoration. Here, a bucket process-based phytoplankton dynamic model is developed to quantify the contributions of climate change and nutrients concentration changes to phytoplankton biomass resurgence after 2014 in hypereutrophic Lake Taihu, China. Compared to 2008-2014, the mean water temperature (WT) and the mean phosphate are higher, the mean photosynthetically active radiation (PAR), the mean total suspended solids (TSS), and the mean dissolved inorganic nitrogen (DIN) are lower, during 2015-2020. Their contribution to algal biomass resurgence during 2015-2020 is WT (+58.7 %), PAR (-2.6 %), TSS (+23.2 %), DIN (-22.1 %) and phosphate (+42.7 %), respectively. Climate change (WT, PAR, and TSS), which contributed +64.9 % to the phytoplankton biomass resurgence, underscores the urgent need to continuously take more effective measures to reduce nutrient emissions to offset the effects of climate change in Lake Taihu and in other eutrophic lakes.

MODIS Terra and Aqua images bring non-negligible effects to phytoplankton blooms derived from satellites in eutrophic lakes

Phytoplankton-induced lake eutrophication has drawn ongoing interest on a global scale. One of the most popular remote sensing satellite data for observing long-term dynamic changes in phytoplankton is Moderate-resolution Imaging Spectroradiometer (MODIS). However, it is worth noting that MODIS provides two images with different transit times: Terra (local time, about 10:30 am) and Aqua (local time, about 1:30 pm), which may result in a considerable bias in monitoring phytoplankton bloom areas due to the rapid migration of phytoplankton under wind or hydrodynamic conditions. To analyze this quantitatively, we selected MODIS Terra and Aqua images to generate datasets of phytoplankton bloom areas in Lake Taihu from 2003 to 2022. The results showed that Terra more frequently detected larger ranges of phytoplankton blooms than Aqua, whether on daily, monthly, or annual scales. In addition, long-term trend changes, seasonal characteristics, and abrupt years also varied with different transit times. Terra detected mutation years earlier, while Aqua displayed more pronounced seasonal characteristics. There were also differences in sensitivity to climate factors, with Terra being more responsive to temperature and wind speed on monthly and annual scales, while Aqua was more sensitive to nutrient and meteorological factors. These conclusions have also been further confirmed in Lake Chaohu, Lake Dianchi, and Lake Hulun. In conclusion, our findings strongly advocate for a linear relationship to fit Terra to Aqua results to mitigate long-term monitoring errors of phytoplankton blooms in inland lakes (R2 = 0.70, RMSE = 101.56). It is advised to utilize satellite data with transit times between 10 am and 1 pm to track phytoplankton bloom changes and to consider the diverse applications resulting from the transit times of Terra and Aqua.

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.

Algal biomass mapping of eutrophic lakes using a machine learning approach with MODIS images

Algal blooms are a widespread issue in eutrophic lakes. Compared with the satellite-derived surface algal bloom area and chlorophyll-a (Chla) concentration, algae biomass is a more stable way to reflect water quality. Although satellite data have been adopted to observe the water column integrated algal biomass, the previous methods mostly are empirical algorithms, which are not stable enough for widespread use. This paper proposed a machine learning algorithm based on Moderate Resolution Imaging Spectrometer (MODIS) data to estimate the algal biomass, which was successfully applied to a eutrophic lake in China, Lake Taihu. This algorithm was developed by linking Rayleigh-corrected reflectance to in situ algae biomass data in Lake Taihu (n = 140), and the different mainstream machine learning (ML) methods were compared and validated. The partial least squares regression (PLSR) (R² = 0.67, mean absolute percentage error (MAPE) = 38.88 %) and support vector machines (SVM) (R² = 0.46, MAPE = 52.02 %) performed poor satisfactory. In contrast, random forest (RF) and extremely gradient boosting tree (XGBoost) algorithms had higher accuracy (RF: R² = 0.85, MAPE = 22.68 %; XGBoost: R² = 0.83, MAPE = 24.06 %), demonstrating greater application potential in algal biomass estimation. Field biomass data were further used to estimate the RF algorithm, which showed acceptable precision (R² = 0.86, MAPE < 7 mg Chla). Subsequently, sensitivity analysis showed that the RF algorithm was not sensitive to high suspension and thickness of aerosols (rate of change <2 %), and inter-day and consecutive days verification showed stability (rate of change <5 %). The algorithm was also extended to Lake Chaohu (R² = 0.93, MAPE = 18.42 %), demonstrating its potential in other eutrophic lakes. This study for algae biomass estimation provides technical means with higher accuracy and greater universality for the management of eutrophic lakes.

Response of phytoplankton community composition to physicochemical and meteorological factors under different hydrological conditions in Lake Diefenbaker

Changes in hydro-meteorological conditions due to warming climate and the operation of reservoirs may support algal blooms. Lake Diefenbaker is a large reservoir on the Canadian Prairies. Annual flow volume from its major tributary, the South Saskatchewan River (SSR), varies with precipitation and temperature in the Rocky Mountains. Furthermore, plans are underway to increase water abstraction from Lake Diefenbaker for irrigation. Therefore, we used a nine-year dataset that comprised a drought year (1984), four consecutive high flow years (2011 to 2014), and four subsequent low flow years (2015 to 2018) to investigate how these changes could affect the major phytoplankton groups and cyanobacterial community. Diatoms (38.5%) were the most abundant phytoplankton, followed by cryptomonads (28.9%) under low and high flow years. Diatoms were associated with greater mixing in late spring and fall, whereas the cryptomonads were related to the high nutrients from spring flow. Cyanobacteria (79.3%) contributed the greatest to the total phytoplankton biomass under drought; we hypothesized that the high abundance of cyanobacteria during drought was associated with thermocline deepening and subsequent internal loading of nutrients. Microcystis, a potential bloom-forming and toxin-producing genus, was dominant during the drought and correlated with reduced water level, increased air temperature, and moderate wind speed. Although its biomass was low, another potential bloom-forming and toxin-producing genus, Aphanizomenon, was present in low and high flow years. Aphanizomenon was correlated with decreased SSR flow and increased particulate carbon to particulate phosphorus ratios, which may be related to their ability to cope with P limitation. These results highlight that Lake Diefenbaker and other similar reservoirs are vulnerable to an increase in potential toxic cyanobacteria species with future expectations of climate warming and water abstraction.

Research progress on influencing factors on compost maturity and cyanobacteria toxin degradation during aerobic cyanobacteria composting: a review

Cyanobacterial bloom is by far one of the most common water quality hazards. As cyanobacteria are rich in nitrogen, phosphorus, and other organic matter, the potential for beneficial use of cyanobacteria is promising. Aerobic composting is currently a hot topic of research in cyanobacteria treatment, which can effectively achieve reduction, recycling, and removal of the harmful impact of cyanobacteria. In this review, the characteristics of cyanobacteria in aerobic composting processes, the effects of physical, chemical, and biological factors on the composting process, and the degradation of microcystic toxins were systematically discussed and summarized. This review epitomizes the large quantities of research data collected by many scholars around the world to address the characteristics of "one low and five highs" in the aerobic cyanobacterial composting process. The composting techniques developed are effective and easy to adopt in the real world, such as adjusting the substrate C/N ratio and moisture content and use of chemical and biological additives to achieve reduction, recycling, and detoxication of the cyanobacterial wastes. The aim of this comprehensive review is to provide theoretical guidance and reference for further development and application of aerobic cyanobacteria composting technology.

Chlorophyll and phycocyanin in-situ fluorescence in mixed cyanobacterial species assemblages: Effects of morphology, cell size and growth phase

Cyanobacteria harmful blooms can represent a major risk for public health due to potential release of toxins and other noxious compounds in the water. A continuous and high-resolution monitoring of the cyanobacteria population is required due to their rapid dynamics, which has been increasingly done using in-situ fluorescence of phycocyanin (f-PC) and chlorophyll a (f-Chl a). Appropriate in-situ fluorometers calibration is essential because f-PC and f-Chl a are affected by biotic and abiotic factors, including species composition. Measurement of f-PC and f-Chl a in mixed species assemblages during different growth phases - representative of most field conditions - has received little attention. We hypothesized that f-PC and f-Chl a of mixed assemblages of cyanobacteria may be accurately estimated if taxa composition and fluorescence characteristics are known. We also hypothesized that species with different morphologies would have different fluorescence per unit cell and biomass. We tested these hypotheses in a controlled culture experiment in which photosynthetic pigment fluorescence, chemical pigment extraction, optical density and microscopic enumeration of four common cyanobacteria species (Aphanocapsa sp, Microcystis aeruginosa, Dolichospermum circinale and Raphidiopsis raciborskii) were quantified. Both monocultures and mixed cultures were monitored from exponential to late stationary growth phases. The sum of fluorescence of individual species calculated for mixed samples was not significantly different than measured fluorescence of mixed cultures. Estimated and measured f-PC and f-Chl a of mixed cultures had higher correlations and smaller absolute median errors when estimations were based on fluorescence per biomass instead of fluorescence per cell. Largest errors were overestimations of measured fluorescence for species with different morphologies. Fluorescence per cell was significantly different among most species, while fluorescence per unit biomass was not, indicating that conversion of fluorescence to biomass reduces species-specific bias. This study presents new information on the effect of species composition on cyanobacteria fluorescence. Best practices of deployment and operation of fluorometers, and data-driven models supporting in-situ fluorometers calibration are discussed as suitable solutions to minimize taxa-specific bias in fluorescence estimates.

Identifying key drivers of harmful algal blooms in a tributary of the Three Gorges Reservoir between different seasons: Causality based on data-driven methods

Intense harmful algal blooms (HABs) can occur in the backwaters of tributaries supplying large-scale reservoirs. Due to the characteristics of process-based models and difficulties in modelling complex nonlinear processes, traditional models have difficulties disentangling the driving factors of HABs. In this study, we used data-driven methods (i.e., correlation analysis and machine-learning models) to identify the most important drivers of HABs in the Xiangxi River, a tributary of the Three Gorges Reservoir, China (2017-2018), for the dry season (from October to mid-April) and wet season (from April to September). We utilized the maximal information coefficient (MIC) combined with a time lag strategy and prior knowledge to quantitatively identify the driving variables of HABs. An extra trees regression (ETR) model was developed to assess the relative importance of causal variables driving algal blooms for the different periods. The results showed that water temperature was the most important driver for the duration of the study, followed by total nitrogen. Nitrogen had a stronger effect on algal blooms than phosphorus during both the wet and dry seasons. HABs were mainly affected by ammonia nitrogen in the wet season and by other forms of nitrogen in the dry season. In contrast, rather than the water temperature and nutrients, the operation of the Three Gorges Dam (difference between inflow and outflow discharge rate) was the most significant factor for algal blooms during the dry season, but its influence sharply declined during the wet season. This study showed that the key drivers of HABs can differ between seasons and suggests that HAB management should take seasonality into account.

Modeling the sensitivity of cyanobacteria blooms to plausible changes in precipitation and air temperature variability

Many recent studies have attributed the observed variability of cyanobacteria blooms to meteorological drivers and have projected blooms with worsening societal and ecological impacts under future climate scenarios. Nonetheless, few studies have jointly examined their sensitivity to projected changes in both precipitation and temperature variability. Using an Integrated Assessment Model (IAM) of Lake Champlain's eutrophic Missisquoi Bay, we demonstrate a factorial design approach for evaluating the sensitivity of concentrations of chlorophyll a (chl-a), a cyanobacteria surrogate, to global climate model-informed changes in the central tendency and variability of daily precipitation and air temperature. An Analysis of Variance (ANOVA) and multivariate contour plots highlight synergistic effects of these climatic changes on exceedances of the World Health Organization's moderate 50 μg/L concentration threshold for recreational contact. Although increased precipitation produces greater riverine total phosphorus loads, warmer and drier scenarios produce the most severe blooms due to the greater mobilization and cyanobacteria uptake of legacy phosphorus under these conditions. Increases in daily precipitation variability aggravate blooms most under warmer and wetter scenarios. Greater temperature variability raises exceedances under current air temperatures but reduces them under more severe warming when water temperatures exceed optimal values for cyanobacteria growth more often. Our experiments, controlled for wind-induced changes to lake water quality, signal the importance of larger summer runoff events for curtailing bloom growth through reductions of water temperature, sunlight penetration and stratification. Finally, the importance of sequences of wet and dry periods in generating cyanobacteria blooms motivates future research on bloom responses to changes in interannual climate persistence.

Effects of hydrological and climatic variables on cyanobacterial blooms in four large shallow lakes fed by the Yangtze River

Shallow lakes, one of the most widespread water bodies in the world, are easily shifted to a new trophic state due to external interferences. Shifting hydrologic conditions and climate change can cause cyanobacterial harmful algal blooms (CyanoHABs) in shallow lakes, which pose serious threats to ecological integrity and human health. This study analyzed the effects of hydrologic and meteorological variables on cyanobacterial blooms in Yangtze-connected lakes (Lake Dongting and Poyang) and isolated lakes (Lake Chao and Tai). The results show that (i) chlorophyll-a (Chl-a) concentration tends to decrease exponentially with increasing relative lake level fluctuations (RLLF) and precipitation, but to increase linearly with increasing wind speed and air temperature; (ii) Chl-a concentrations in lakes were significantly higher when RLLF < 100, precipitation < 2.6 mm, wind speed > 2.6 m s^-1, or air temperature > 17.8 °C; (iii) the Chl-a concentration of Yangtze-isolated lakes was more significantly affected by water level amplitude, precipitation, wind speed and air temperature than the Yangtze-connected lakes; (iv) the RLLF and the ratio of wind speed to mean water depth could be innovative coupling factors to examine variation characteristics of Chl-a in shallow lakes with greater correlation than single factors.

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.

A systematic literature review of forecasting and predictive models for cyanobacteria blooms in freshwater lakes

Cyanobacteria harmful blooms (CyanoHABs) in lakes and reservoirs represent a major risk for water authorities globally due to their toxicity and economic impacts. Anticipating bloom occurrence and understanding the main drivers of CyanoHABs are needed to optimize water resources management. An extensive review of the application of CyanoHABs forecasting and predictive models was performed, and a summary of the current state of knowledge, limitations and research opportunities on this topic is provided through analysis of case studies. Two modelling approaches were used to achieve CyanoHABs anticipation; process-based (PB) and data-driven (DD) models. The objective of the model was a determining factor for the choice of modelling approach. PB models were more frequently used to predict future scenarios whereas DD models were employed for short-term forecasts. Each modelling approach presented multiple variations that may be applied for more specific, targeted purposes. Most models reviewed were site-specific. The monitoring methodologies, including data frequency, uncertainty and precision, were identified as a major limitation to improve model performance. A lack of standardization of both model output and performance metrics was observed. CyanoHAB modelling is an interdisciplinary topic and communication between disciplines should be improved to facilitate model comparisons. These shortcomings can hinder the adoption of modelling tools by practitioners. We suggest that water managers should focus on generalising models for lakes with similar characteristics and where possible use high frequency monitoring for model development and validation.

Relative effects of wind-induced disturbances and vegetation on tetrabromobisphenol A cycling in shallow lakes: Direct and indirect effects

The environmental concerns regarding the possible threats of tetrabromobisphenol A (TBBPA) to aquatic environments are increasing. However, information about TBBPA cycling in the water-vegetation-sediment systems of shallow lakes is limited. In a shallow lake, wind-induced disturbance is considered as the key factor of affecting the cycling of contaminants. To address this issue, the TBBPA distribution and elimination processes were simulated for three typical wind speeds by using an annular flume. Four forms of TBBPA were studied in these systems, including water, suspended solids (SS), vegetation and sediment. The results showed that the mass distributions of TBBPA in water, SS and vegetation increased remarkably while enhancing the wind-induced disturbances, which resulted from the release of TBBPA from the sediment through resuspension and adsorption-desorption processes. However, most of the TBBPA (up to 94%) still accumulated in the sediment. Wind-induced disturbances and vegetation both increased the TBBPA elimination rate in the water-vegetation-sediment systems. The half-life (T_1/2) of TBBPA in the fast wind condition was 16.1 ± 0.2 days, which was shorter than that in the static condition (29.8 ± 0.9 days). Compared to the systems without vegetation, the presence of vegetation shortened the T_1/2 by 7.3 days in the static condition. Furthermore, a structural equation model (SEM) was used to assess the direct and indirect effects of environmental factors on the TBBPA amounts in each form. The main effects of wind speed and vegetation in the TBBPA cycling of each form (except for the TBBPA on vegetation) were indirect by affecting the dissolved oxygen (DO), velocity and suspended solids concentration (SSC). Overall, the findings provide useful information about the fate of TBBPA and other related organic contaminants in shallow lake systems.

A novel Eulerian approach for modelling cyanobacteria movement: Thin layer formation and recurrent risk to drinking water intakes

Toxic cyanobacteria (CB) blooms are being reported in an increasing number of water bodies worldwide. As drinking water (DW) treatment can be disrupted by CB, in addition to long term management plans, short term operational decision-making tools are needed that enable an understanding of the temporal variability of CB movement in relation to drinking water intakes. In this paper, we propose a novel conservative model based on a Eulerian framework and compare results with data from CB blooms in Missisquoi Bay (Québec, Canada). The hydrodynamic model considered the effects of wind and light intensity, demonstrated that current understanding of cell buoyancy in relation to light intensity in full-scale systems is incomplete and some factors are yet to be fully characterized. Factors affecting CB buoyancy play a major role in the formation of a thin surface layer that could be of ecological importance with regards to cell concentrations and toxin production. Depending on velocities, wind contributes either to the accumulation or to the dispersion of CB. Lake recirculation effects have a tendency to create zones of low CB concentrations in a water body. Monitoring efforts and future research should focus on short-term variations of CB throughout the water column and the characterization of factors other than light intensity that affect cell buoyancy. These factors are critical for understanding the risk of breakthrough into treatment plants as well as the formation of surface scums and subsequent toxin production.

The relative importance of water temperature and residence time in predicting cyanobacteria abundance in regulated rivers

Despite a growing awareness of the problems associated with cyanobacterial blooms in rivers, and particularly in regulated rivers, the drivers of bloom formation and abundance in rivers are not well understood. We developed a Bayesian hierarchical model to assess the relative importance of predictors of summer cyanobacteria abundance, and to test whether the relative importance of each predictor varies by site, using monitoring data from 16 sites in the four major rivers of South Korea. The results suggested that temperature and residence time, but not nutrient levels, are important predictors of summer cyanobacteria abundance in rivers. Although the two predictors were of similar significance across the sites, the residence time was marginally better in accounting for the variation in cyanobacteria abundance. The model with spatial hierarchy demonstrated that temperature played a consistently significant role at all sites, and showed no effect from site-specific factors. In contrast, the importance of residence time varied significantly from site to site. This variation was shown to depend on the trophic state, indicated by the chlorophyll-a and total phosphorus levels. Our results also suggested that the magnitude of weir inflow is a key factor determining the cyanobacteria abundance under baseline conditions.

A new approach for the estimation of phytoplankton cell counts associated with algal blooms

This study proposes a method for estimating phytoplankton cell counts associated with an algal bloom, using satellite images coincident with in situ and meteorological parameters. Satellite images from Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), Operational Land Imager (OLI) and HJ-1 A/B Charge Couple Device (CCD) sensors were integrated with the meteorological observations to provide an estimate of phytoplankton cell counts. All images were atmospherically corrected using the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) atmospheric correction method with a possible error of 1.2%, 2.6%, 1.4% and 2.3% for blue (450-520nm), green (520-600nm), red (630-690nm) and near infrared (NIR 760-900nm) wavelengths, respectively. Results showed that the developed Artificial Neural Network (ANN) model yields a correlation coefficient (R) of 0.95 with the in situ validation data with Sum of Squared Error (SSE) of 0.34cell/ml, Mean Relative Error (MRE) of 0.154cells/ml and a bias of -504.87. The integration of the meteorological parameters with remote sensing observations provided a promising estimation of the algal scum as compared to previous studies. The applicability of the ANN model was tested over Hong Kong as well as over Lake Kasumigaura, Japan and Lake Okeechobee, Florida USA, where algal blooms were also reported. Further, a 40-year (1975-2014) red tide occurrence map was developed and revealed that the eastern and southern waters of Hong Kong are more vulnerable to red tides. Over the 40 years, 66% of red tide incidents were associated with the Dinoflagellates group, while the remainder were associated with the Diatom group (14%) and several other minor groups (20%). The developed technology can be applied to other similar environments in an efficient and cost-saving manner.

How does the cladoceran Daphnia pulex affect the fate of Escherichia coli in water?

The faecal indicator Escherichia coli plays a central role in water quality assessment and monitoring. It is therefore essential to understand its fate under various environmental constraints such as predation by bacterivorous zooplankton. Whereas most studies have examined how protozooplankton communities (heterotrophic nanoflagellates and ciliates) affect the fate of E. coli in water, the capacity of metazooplankton to control the faecal indicator remains poorly understood. In this study, we investigated how the common filter-feeding cladoceran, Daphnia pulex, affects the fate of E. coli under different experimental conditions. Daphnia ingested E. coli and increased its loss rates in water, but the latter rates decreased from 1.65 d^-1 to 0.62 d^-1 after a 1,000-fold reduction in E. coli initial concentrations, due to lower probability of encounter between Daphnia and E. coli. The combined use of culture and PMA qPCR (viability-qPCR) demonstrated that exposure to Daphnia did not result into the formation of viable but non-culturable E. coli cells. In lake water, a significant part of E. coli population loss was associated with matrix-related factors, most likely due to predation by other bacterivorous biota and/or bacterial competition. However, when exposing E. coli to a D. pulex gradient (from 0 to 65 ind.L^-1), we observed an increasing impact of Daphnia on E. coli loss rates, which reached 0.47 d^-1 in presence of 65 ind.L^-1. Our results suggest that the filter-feeder can exert a non-negligible predation pressure on E. coli, especially during seasonal Daphnia population peaks. Similar trials using other Daphnia species as well as stressed E. coli cells will increase our knowledge on the capacity of this widespread zooplankter to control E. coli in freshwater resources. Based on our results, we strongly advocate the use of natural matrices to study these biotic interactions in order to avoid overestimation of Daphnia impact.

UV/persulfate preoxidation to improve coagulation efficiency of Microcystis aeruginosa

The performance of UV-activated persulfate (UV/PS) technology as preoxidation process to enhance Microcystis aeruginosa removal by subsequent coagulation-sedimentation was firstly evaluated. The results demonstrate that UV/PS preoxidation could successfully promote coagulation of algae cells through the effective neutralization of zeta potential, which was caused by the changes of cell morphology, size distribution and surface properties after simultaneous UV irradiation and formed reactive species (i.e. SO₄^- and HO) oxidation. Since excessive oxidation would cause cell rupture along with the release of organics, which could deteriorate coagulation efficiency, optimal PS dose (60mg/L) and UV dose (375mJ/cm²) were proposed to exist in this study. The concentrations of extracellular algal organic matter (AOM) sharply increased by 48.2% during the preoxidation period, while gradually decreased in the following coagulation and sedimentation. Most of the concerned disinfection by-products (DBPs) monotonically decreased or followed fluctuant reduction with increasing PS doses, whereas the trichloromethane, trichloroacetic acid and dichloroacetonitrile persistently increased, which was inferred to be related to the variation of AOM. This study suggests that UV/PS might be a potential pretreatment process to assist coagulation on the removal of algae.

Cyanotoxin degradation activity and mlr gene expression profiles of a Sphingopyxis sp. isolated from Lake Champlain, Canada

A bacterium capable of degrading five microcystin (MC) variants, microcystin-LR, YR, LY, LW and LF at an initial total concentration of 50 μg l^-1 in less than 16 hours was isolated from Missisquoi Bay, in the south of Quebec, Canada. Phylogenetic analysis of the 16S rRNA gene sequence identified the bacterium as Sphingopyxis sp., designated strain MB-E. It was shown that microcystin biodegradation activity was reduced at acidic and basic pH values. Even though no biodegradation occurred at pH values of 5.05 and 10.23, strain MB-E was able to degrade MCLR and MCYR at pH 9.12 and all five MCs variants tested at pH 6.1. Genomic sequencing revealed that strain MB-E contained the microcystin degrading gene cluster, including the mlrA, mlrB, mlrC and mlrD genes, and transcriptomic analysis demonstrated that all of these genes were induced during the degradation of MCLR alone or in the mixture of all five MCs. This novel transcriptomic analysis showed that the expression of the mlr gene cluster was similar for MCLR alone, or the mixture of MCs, and appeared to be related to the total concentration of substrate. The results suggested that the bacterium used the same pathway for the degradation of all MC variants.

Meteorological and hydrological conditions driving the formation and disappearance of black blooms, an ecological disaster phenomena of eutrophication and algal blooms

Potentially toxic black blooms can disrupt drinking water treatment plants and have fatal effects on aquatic ecosystems; therefore, lake management is required to determine whether conditions are favorable for the formation and disappearance of black blooms in water supply sources. Long-term climate background, short-term thresholds of meteorological and hydrological conditions, and the duration of harmful algal blooms (HABs) were investigated as factors affecting the formation and disappearance of black blooms in hyper-eutrophic Lake Taihu. Long-term climate warming (0.31°C/decade), decreases in wind speed (0.26m/s per decade) and air pressure (0.16hPa/decade), and the increase in the meteorological index of black blooms (3.6days/decade) in Lake Taihu over the past 51years provided climate conditions conducive to the formation and occurrence of black blooms. A total of 16 black bloom events with an area larger than 0.1km(2) were observed from 2007 to 2014. Several critical thresholds for short-term meteorological and hydrological conditions were determined for the formation of black blooms, including a five-day average air temperature above 25°C, a five-day average wind speed <2.6m/s, average precipitation of five consecutive days close to 0, and continuous HAB accumulation for >5days. Heavy precipitation events, sudden cooling, and large wind disturbances were the driving factors of black blooms' disappearance. The use of a coupling model that combines the remote sensing of HABs with environmental, meteorological, and hydrological observations could permit an adequate and timely response to black blooms in drinking water sources.

Biodegradation of multiple microcystins and cylindrospermopsin in clarifier sludge and a drinking water source: Effects of particulate attached bacteria and phycocyanin

The effects of particulate attached bacteria (PAB) and phycocyanin on the simultaneous biodegradation of a mixture of microcystin-LR, YR, LY, LW, LF and cylindrospermopsin (CYN) was assessed in clarifier sludge of a drinking water treatment plant (DWTP) and in a drinking water source. The biomass from lake water and clarifier sludge was able to degrade all microcystins (MCs) at initial concentrations of 10µgL(-1) with pseudo-first order reaction half-lives ranging from 2.3 to 8.8 days. CYN was degraded only in the sludge with a biodegradation rate of 1.0×10(-1)d(-1) and a half-life of 6.0 days. This is the first study reporting multiple MCs and CYN biodegradation in the coagulation-flocculation sludge of a DWTP. The removal of PAB from the lake water and the sludge prolonged the lag time substantially, such that no biodegradation of MCLY, LW and LF was observed within 24 days. Biodegradation rates were shown to increase in the presence of C-phycocyanin as a supplementary carbon source for indigenous bacteria, a cyanobacterial product that accompanies cyanotoxins during cyanobacteria blooms. MCs in mixtures degraded more slowly (or not at all) than if they were degraded individually, an important outcome as MCs in the environment are often present in mixtures. The results from this study showed that the majority of the bacterial biomass responsible for the biodegradation of cyanotoxins is associated with particles or biological flocs and there is a potential for extreme accumulation of cyanotoxins within the DWTP during a transient bloom.

Impact of UV-H2O2 Advanced Oxidation and Aging Processes on GAC Capacity for the Removal of Cyanobacterial Taste and Odor Compounds

Cyanobacteria and their taste and odor (T&O) compounds are a growing concern in water sources globally. Geosmin and 2-methylisoborneol (MIB) are the most commonly detected T&O compounds associated with cyanobacterial presence in drinking water sources. The use of ultraviolet and hydrogen peroxide (H2O2) as an advanced oxidation treatment for T&O control is an emerging technology. However, residual H2O2 (>80% of the initial dose) has to be removed from water prior final disinfection. Recently, granular activated carbon (GAC) is used to remove H2O2 residual. The objective of this study is to assess the impact of H2O2 quenching and aging processes on GAC capacity for the removal of geosmin and MIB. Pilot columns with different types of GAC and presence/absence of H2O2 have been used for this study. H2O2 removal for the operational period of 6 months has no significant impact on GAC capacity to remove the geosmin and MIB from water.