Enhanced real-time cyanobacterial fluorescence monitoring through chlorophyll-a interference compensation corrections

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.

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.

A probabilistic decision support tool for prediction and management of rainfall-related poor water quality events for a drinking water treatment plant

A data-driven Bayesian Network (BN) model was developed for a large Australian drinking water treatment plant, whose raw water comes from a river into which a number of upstream dams outflow water and smaller tributaries flow. During wet weather events, the spatial distribution of rainfall has a crucial role on the incoming raw water quality, as runoff from specific sub-catchments usually causes significant turbidity and conductivity issues, as opposed to larger dam outflows which have typically better water quality. The BN relies on a conceptual model developed following expert consultation, as well as a combination of different types (e.g. water quality, flow, rainfall) and amount (e.g. high-frequency, daily, scarce depending on variable) of historical data. The validated model proved to have acceptable accuracy in predicting the probability of different incoming raw water quality ranges, and can be used to assess different scenarios (e.g. timing, flow) of dam water releases, for the purpose of achieving dilution of the tributary's poor-quality water and mitigate related drinking water treatment challenges.

Improvement of In Vivo Fluorescence Tools for Fast Monitoring of Freshwater Phytoplankton and Potentially Harmful Cyanobacteria

The use of multi-wavelength spectrofluorometers for the fast detection of algal taxa, based on chlorophyll a (Chl-a) emission spectra, has become a common practice in freshwater water management, although concerns about their accuracy have been raised. Here, inter-laboratory comparisons using monoalgal cultures have been performed to assess the reliability of different spectrofluorometer models, alongside Chl-a extraction methods. Higher Chl-a concentrations were obtained when using the spectrofluorometers than extraction methods, likely due to the poor extraction efficiencies of solvents, highlighting that traditional extraction methods could underestimate algal or cyanobacterial biomass. Spectrofluorometers correctly assigned species to the respective taxonomic group, with low and constant percent attribution errors (Chlorophyta and Euglenophyceae 6-8%, Cyanobacteria 0-3%, and Bacillariophyta 10-16%), suggesting that functioning limitations can be overcome by spectrofluorometer re-calibration with fresh cultures. The monitoring of a natural phytoplankton assemblage dominated by Chlorophyta and Cyanobacteria gave consistent results among spectrofluorometers and with microscopic observations, especially when cell biovolume rather than cell density was considered. In conclusion, multi-wavelength spectrofluorometers were confirmed as valid tools for freshwater monitoring, whereas a major focus on intercalibration procedures is encouraged to improve their reliability and broaden their use as fast monitoring tools to prevent environmental and public health issues related to the presence of harmful cyanobacteria.

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.

Spatiotemporal BME characterization and mapping of sea surface chlorophyll in Chesapeake Bay (USA) using auxiliary sea surface temperature data

Improving the spatiotemporal coverage of remote sensing (RS) products, such as sea surface chlorophyll concentration (SSCC), can offer a better understanding of the spatiotemporal SSCC distribution for ocean management purposes. In the first part of this work, 834 in-situ SSCC measurements of the SeaBASS-NASA (National Aeronautics and Space Administration) during 2002-2016 served as the empirical dataset. A moving window with ±3 days and ±0.5° centered at each of the in-situ SSCC measurements established a search neighborhood for Moderate Resolution Imaging Spectroradiometer Level 2 (MODIS L2) SSCC and MODIS L2 sea surface temperature (SST) data, and the matched SSCC and SST data were used for building a linear SSCC-SST relationship. The unmatched SST was introduced to the linear model for generating soft SSCC data with uniform distributions. The inherent spatiotemporal dependency of the SSCC distribution was then represented by the Bayesian maximum entropy (BME) method, which incorporated the soft SSCC data as auxiliary variable for SSCC estimation and mapping purposes. The results showed that a 75.3% accuracy improvement of remote SSCC retrieval in terms of R² can be achieved by BME-based method compared to the original MODIS L2 product. Subsequently, the BME-based method was applied to obtain daily SSCC dataset in Chesapeake Bay (USA) during the period 2010-2019. It was found that the SSCC distribution exhibited a decreasing spatial trend from the upper bay to the outer bay, whereas decreasing and increasing temporal trends were detected during the periods 2011-2014 and 2016-2019, respectively. The generalized Cauchy process was used to quantitatively describe the autocorrelation SSCC function in the Chesapeake Bay. The results showed that the outer bay exhibited the strongest long-range dependence among the four sub-regions, whereas the middle bay exhibited the weakest long-range dependence. Finally, one-point and two-point stochastic site indicators (SSIs) were employed to explore the spatiotemporal SSCC characteristics in Chesapeake Bay. The one-point SSI results showed that nearly 100% of the upper, middle and the lower bay areas experienced a high SSCC level (>5 mg/m³) during the entire study period. The area with SSCC >5 mg/m³ in the outer bay increased a lot during the winter season, but the area with SSCC >10 or 20 mg/m³ decreased significantly in the upper, middle and lower bay. Simultaneously, the SSCC dispersion in these areas was rather small during the winter season. On the other hand, the two-point SSI results showed that although the SSCC levels differ among the four sub-regions, but the SSCC connectivity structures between pairs of points also displayed some similarities in terms of their spatiotemporal dependency. In conclusion, the proposed BME-based method was shown to be a promising remote SSCC mapping technique that exhibited a powerful ability to improve both accuracy and coverage of RS products. The SSIs can be also used to explore the spatiotemporal characteristics of a variety of natural attributes in waters.

Light-induced fluorescence quenching leads to errors in sensor measurements of phytoplankton chlorophyll and phycocyanin

Optical sensors for fluorescence of chlorophyll a (f-Chl a) and phycocyanin (f-PC) are increasingly used as a proxy for biomass of algae and cyanobacteria, respectively. They provide measurements at high-frequency and modest cost. These sensors require site-specific calibration due to a range of interferences. Light intensity affects the fluorescence yield of cyanobacteria and algae through light harvesting regulation mechanisms, but is often neglected as a potential source of error for in-situ f-Chl a and f-PC measurements. We hypothesised that diel light variations would induce significant f-Chl a and f-PC suppression when compared to dark periods. We tested this hypothesis in a controlled experiment using three commercial fluorescence probes which continuously measured f-Chl a and f-PC from a culture of the cyanobacterium Dolichospermum variabilis as well as f-Chl a from a culture of the green alga Ankistrodesmus gracilis in a simulated natural light regime. Under light, all devices showed a significant (p<0.01) suppression of f-Chl a and f-PC compared to measurements in the dark. f-Chl a decreased by up to 79% and f-PC by up to 59% at maximum irradiance compared to dark-adapted periods. Suppression levels were higher during the second phase of the diel cycle (declining light), indicating that quenching is dependent on previous light exposure. Diel variations in light intensity must be considered as a significant source of bias for fluorescence probes used for algal monitoring. This is of high relevance as most monitoring activities take place during daytime and hence f-Chl a and f-PC are likely to be systematically underestimated under bright conditions. Compensation models, design modifications to fluorometers and sampling design are discussed as suitable alternatives to overcome light-induced fluorescence quenching.

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.

Sensitivity Analysis and Optimization of a Radiative Transfer Numerical Model for Turbid Lake Water

Remote sensing can detect and map algal blooms. The HydroLight (Sequoia Scientific Inc., Bellevue, Washington, DC, USA) model generates the reflectance profiles of various water bodies. However, the influence of model parameters has rarely been investigated for inland water. Moreover, the simulation time of the HydroLight model increases as the amount of input data increases, which limits the practicality of the HydroLight model. This study developed a graphical user interface (GUI) software for the sensitivity analysis of the HydroLight model through multiple executions. The GUI software stably performed parameter sensitivity analysis and substantially reduced the simulation time by up to 92%. The GUI software results for lake water show that the backscattering ratio was the most important parameter for estimating vertical reflectance profiles. Based on the sensitivity analysis results, parameter calibration of the HydroLight model was performed. The reflectance profiles obtained using the optimized parameters agreed with observed profiles, with R2 values of over 0.98. Thus, a strong relationship between the backscattering coefficient and the observed cyanobacteria genera cells was identified.

Predicting cyanobacterial biovolumes from phycocyanin fluorescence using a handheld fluorometer in the field

Toxic cyanobacterial blooms are becoming more prevalent in freshwater systems, increasing the need for monitoring to protect human health. Phycocyanin fluorescence sensors have been developed as tools for providing fast and cost-effective proxy measurements for cyanobacterial biomass. However, poor precision and low sensitivity in many of the probe sensors assessed to-date has restricted their potential for practical application in cyanobacterial monitoring programmes. In the present study, the sensitivity and accuracy of a handheld fluorometer, the CyanoFluor, was assessed using 12 cyanobacterial strains and samples from four different lakes collected weekly for 12 weeks. After the initial measurements, the samples were lysed by sonication, which we hypothesised would reduce inter and intra-specific differences. The CyanoFluor displayed high sensitivity (limit of quantification = 3.5 µg L^-1 of phycocyanin) and was able to detect cyanobacterial biovolumes to levels much lower than the threshold levels in current recreational guidelines worldwide. There were strong and significant phycocyanin to biovolume relationships (r² ≥ 0.88, P < 0.05) for all 12 cyanobacterial cultures. Collectively, strong relationships between phycocyanin fluorescence and cyanobacterial biovolumes were also identified in environmental samples (r² ≥ 0.78, P < 0.001), although weaker relationships were identified when lakes were analysed separately (r² = 0.06 - 0.90). There were differences in phycocyanin per biovolume between both cultured strains and lakes, highlighting innate interspecific differences that exist between cyanobacterial species. Lysis of samples consistently reduced variability between technical replicates, in cyanobacteria cultures (up to 87% reduction in sample variability) and environmental samples (71 - 93% reduction), indicating that it would be a useful methodological step to improve the repeatability of results. When guideline thresholds (aligned with currently enforced risk assessment categories) were modelled based on the most successful linear regression model, 74% of samples were assigned to the correct risk category. The sensitivity of the CyanoFluor and accuracy of the phycocyanin threshold models, indicates high potential for this method to be integrated into cyanobacterial monitoring programmes.

Effects of pre-ozonation on the cell characteristics and N-nitrosodimethylamine formation at three growth phases of Microcystis aeruginosa

Pre-oxidation in water treatment is considered an effective method to enhance the removal of algal cells and their exuded organic matters. However, pre-oxidation also alters the characteristics of algae and consequently influences disinfection processes. The existing studies mainly focused on the stationary growth phase, but little is known for the exponential and declined phases. The objectives of this study were to examine the effects of pre-ozonation on the integrity of algal cells, the release of algal organic matters, and the formation of disinfection by-products like N-nitrosodimethylamine (NDMA) from Microcystis aeruginosa (M. aeruginosa) at three growth phases. The results demonstrated that pre-ozonation was efficient to inactivate M. aeruginosa cells. The severity of M. aeruginosa cell damage increased as the ozone dosage increased from 0.5 to 2.0 mg/L. The damage of cell membranes resulted in the release of intracellular organic matters. Excitation-emission matrix spectra (EEMS) analysis indicated that ozone mainly reacted with soluble microbial products (SMP). With the increase of ozone concentration, although the trend of NDMA formation was similar for all three growth phases, more production of NDMA by algal cells was observed at the declined phase. In the post-disinfection process, chloramine showed the potential as a more suitable disinfectant than chlorination after pre-ozonation to minimize the NDMA formation. Therefore, appropriate pre-ozonation is beneficial to reduce the NDMA formation from exponential algae, while has no significant change during both stationary and declined phases.

Transport and retention of Microcystis aeruginosa in porous media: Impacts of ionic strength, flow rate, media size and pre-oxidization

Due to the climate change and human activity, the frequency and intensity of algal blooms have increased significantly. Recent studies have shown that during the bloom event, evaluated levels of cyanobacteria could infiltrate the drinking water treatment process and emerge in the filtered and disinfected water, thus threatening the safety of the drinking water supply. Among these concerned cyanobacteria, Microcystis aeruginosa is one of the most commonly detected species that cause algal bloom in a fresh water body. The present work was designed to investigate the transport and retention behaviour of Microcystis aeruginosa in a packed column to resolve the mechanisms that drive the transport behaviour of Microcystis under various operational conditions. The results showed that lab-cultured Microcystis aeruginosa could effectively break through the packed column regardless of ionic strength, media size or flow rate, as well as the presence of dissolved organic matter in the water under the conditions investigated. Such behaviour significantly contradicts those of fluorescent microspheres, which are commonly considered as ideal colloids. In addition, the combined impacts of pre-oxidation technologies and filtration on Microcystis aeruginosa removal were tested systematically. It was found that even the cells have been lysed/oxidized, no significant improvement of cell removals were observed in packed column. This paper provides a significant and comprehensive record of transport and retention behaviour of Microcystis aeruginosa in porous media. The results found herein suggest that in addition to the effort preventing toxin release/exposure during bloom events in source water, engineers and researchers should also pay attention to the transport and retention of Microcystis aeruginosa and other algal cells in filters to minimize the risk of breakthrough of cyanobacteria cells in the drinking water treatment process.

In-situ fluorescence monitoring of cyanobacteria: Laboratory-based quantification of species-specific measurement accuracy

In recent years, in-situ fluorometers have been extensively deployed to monitor cyanobacteria in near real-time. Acceptable accuracy can be achieved between measured pigments and cyanobacteria biovolume provided the cyanobacteria species are known. However, cellular photosynthetic pigment content and measurement interferences are site and species specific and can dramatically affect sensor reliability. We quantified the accuracy of an in-situ fluorometer compared with traditional methods using mono- and mixed cultures of four different cyanobacterial species. We found: (1) lower pigment content in cultures in stationary phase, (2) higher precision with the sensor compared to traditional pigment quantification methods of measuring phycocyanin and chlorophyll a, (3) species-specific relationships between sensor readings and measurements related to biovolume, (4) overestimation of pigments in mixed compared with mono cultures, (5) dissolved organic matter causing a loss in signal proportional to its degree of aromaticity, and (6) potential to quantify the degree of cell lysis with a fluorescent dissolved organic matter sensor. This study has provided important new information on the strengths and limitations of fluorescence sensors. The sensor readings can provide accurate biovolume quantification and species determination for a number of bloom-forming species when sensors are properly compensated and calibrated.

Evaluating putative ecological drivers of microcystin spatiotemporal dynamics using metabarcoding and environmental data

Microcystin is a cyanobacterial hepatotoxin of global concern. Understanding the environmental factors that cause high concentrations of microcystin is crucial to the development of lake management strategies that minimize harmful exposures. While the literature is replete with studies linking cyanobacterial production of microcystin to changes in various nutrients, abiotic stressors, grazers, and competitors, no single biotic or abiotic factor has been shown to be reliably predictive of microcystin concentrations in complex ecosystems. We performed random forest regression analyses with 16S and 18S rRNA gene sequencing data and environmental data to determine which putative ecological drivers best explained spatiotemporal variation in total microcystin and several individual congeners in a eutrophic freshwater reservoir. Model performance was best for predicting concentrations of the congener MC-LR, with ca. 88% of spatiotemporal variance explained. Most of the variance was associated with changes in the relative abundance of the cyanobacterial genus Microcystis. Follow-up RF regression analyses revealed that factors that were the most important in predicting MC-LR were also the most important in predicting Microcystis population dynamics. We discuss how these results relate to prevailing ecological hypotheses regarding the function of microcystin.