Elevated levels of dissolved microcystins (MCs) in source water due to rapid cell lysis of harmful cyanobacterial blooms may pose serious challenges for drinking water treatment. Catastrophic cell lysis can result from outbreaks of naturally-occurring cyanophages - as documented in Lake Erie during the Toledo water crisis of 2014 and in 2019, or through the application of algaecides or water treatment chemicals. Real-time detection of cyanobacterial cell lysis in source water would provide a valuable tool for drinking water plant and reservoir managers. In this study we explored two real-time fluorescence-based devices, PhycoSens and PhycoLA, that can detect unbound phycocyanin (uPC) as a potential indication of cell lysis and MCs release. The PhycoSens was deployed at the Low Service pump station of the City of Toledo Lake Erie drinking water treatment plant from July 15 to October 19, 2022 during the annual cyanobacteria bloom season. It measured major algal groups and uPC in incoming lake water at 15-min intervals during cyanobacteria dominant and senescence periods. Intermittent uPC detections from the PhycoSens over a three-month period coincided with periods of increasing proportions of extracellular MCs relative to total (intracellular and extracellular) MCs, indicating potential for uPC use as an indicator of cyanobacterial cell integrity. Following exposures of laboratory-cultured MCs-producing Microcystis aeruginosa NIES-298 (120 mu g chlorophyll/L) to cyanophage Ma-LMM01, copper sulfate (0.5 and 1 mg Cu/L), sodium carbonate peroxyhydrate (PAK (R) 27, 6.7 and 10 mg H2O2/L), and potassium permanganate (2.5 and 4 mg/L), appearance of uPC coincided with elevated fractions of extracellular MCs. The PhycoLA was used to monitor batch samples collected daily from Lake Erie water exposed to algaecides in the laboratory. Concurrence of uPC signal and surge of dissolved MCs was observed following 24-h exposures to copper sulfate and PAK 27. Overall results indicate the appearance of uPC is a useful indicator of the onset of cyanobacterial cell lysis and the release of MCs when MCs are present.

A new instrument for indicative tests of treated ballast water is presented here. The principle of the new bbe 10 cells is based on the evaluation of the variable fluorescence of chlorophyll-a in living algal cells. The performance of the bbe 10cells is demonstrated using data obtained during various studies. We show that a very high resolution and sensitivity of the instrument is necessary, due to the fact that varying cell numbers of differing taxa and cell sizes may produce the same chlorophyll-a response. Linearity over a range of 104 cells/ml was proven. The comparative performance of instruments from different manufacturers was assessed during the cruise on the German research vessel Meteor in 2016, which was organized and financed by the German Federal Maritime and Hydrographic Agency (BSH). During the evaluation of raw and treated samples taken between Cape Verde and Hamburg (Germany), the precision and accuracy of the bbe 10cells instrument compared to microscope counts was determined to be better than 0.2 cells/ml. In addition results obtained during independent validation experiments of the bbe 10cells by (a) NIOZ (Dutch Royal Institute for Sea Research), (b) data from laboratory, and (c) UV treatment by the Ballast Water Management System (BWMS) developed by Cathelco, will be analyzed and discussed. We will be demonstrating that indicative methods for the analysis of ballast water need to achieve a precision of better than 1 cell/ml to deliver reliable results.

Algal pollution in water sources has posed a serious problem. Estimating algal concentration in advance saves time for drinking water plants to take measures and helps us to understand causal chains of algal dynamics. This paper explores the possibility of building a short-term algal early warning model with online monitoring systems. In this study, we collected high-frequency data for water quality and weather conditions in shallow and eutrophic Lake Taihu by an in situ multi-sensor system (BIOLIFT) combined with a weather station. Extracted chlorophyll-a from water samples and chlorophyll-a fluorescence differentiated according to different algal classeses verified that chlorophyll-a fluorescence continuously measured by BIOLIFT only represent chlorophyll-a of green algae and diatoms. Stepwise linear regression was used to simulate the chlorophyll-a fluorescence changing rate of green algae and diatoms together (Delta Chl(a-f)%) and phycocyanin fluorescence concentration (blue-green algae) on the water surface layer (CyanoS). The results show that nutrients (total N, NO3-N, NH4-N, total P) were not necessary parameters for short-term algal models. Delta Chl(a-f)% is greatly influenced by the seasons, so seasonal partition of data before modeling is highly recommended. CyanoS(max) and Delta Chl(a-f%) were simulated by only using multi-sensor and meteorological data (R-2 = 0.73; 0.75). All the independent variables (wave, water temperature, relative humidity, depth, cloud cover) used in the model were measured online and predictable. Wave height is the most important independent variable in the shallow lake. This paper offers a new approach to simulate and predict the algal dynamics, which also can be applied in other surface water. (C) 2020 Elsevier Ltd. All rights reserved.

Permanganate and ozone are often used in drinking water treatment plants for the oxidation of taste and odor compounds, toxins, and algae as well as the reduction of mussel activity. The disadvantage of an overuse of such oxidants is the potential lysis of cyanobacterial cells. Cell lysis causes taste and odor components as well as toxins to be released into the water, which results in the need for even more treatment to remove these compounds completely. Our research in the CLIENT-SIGN project investigated an innovative method to monitor the lysis of cyanobacteria cells: increases in a specific fluorescence emission spectrum of the cyanobacteria pigment phycocyanin were used as a proxy for cell lysis and other compounds (taste/odor, toxins) leaving the cells. We call this form of phycocyanin "free phycocyanin" or "unbound phycocyanin". By monitoring free phycocyanin via a relatively fast and inexpensive measurement, water utilities will be better able to optimize the dosage of pre-oxidation compounds to remove extracellular compounds while preventing the lysing of cells. Laboratory studies and a case study at Yangcheng Lake (adjacent to Lake Taihu, Yangcheng Lake Water Treatment Plant, Suzhou Industrial Park, China) are presented herein. An online surveillance system that monitors incoming raw water and the water after pre-oxidation is proposed to better cope with changing water conditions.

The Tai Hu (Tai Lake) is used as a raw water reservoir for approximately ten million inhabitants predominantly in Jiangsu province, China. Algal/cyanobacterial blooms occur frequently in the eutrophic shallow lake and present a challenge for drinking water treatment. Furthermore, occasionally taste and odor (T&O) problems have been reported in drinking water. Due to the impacts of wastewater and surface water runoff, pesticides and emerging pollutants such as pharmaceutical compounds must be considered as well. In our study, a large spectrum of emerging pollutants was analyzed in the northern part of Tai Hu. In a Zhushan Bay wetland, emerging pollutants such as perfluorooctanoic acid (PFOA) and the pharmaceuticals ibuprofen and diazepam were detected. Additionally, pesticides were present in the lake water in concentrations of 0.1-0.5 mu g/L. The occurrence of antibiotic resistances at the microbial level was examined in water and sediment samples. In particular the antibiotic resistance genes sul1 and sul2, which encode for resistance against sulfonamide antibiotics, were detected in all samples. Furthermore, the tetracycline resistance gene tet(C) was detected frequently and tet(B) in 10% of the samples. Also, the genes blaTEM and ermB were detected in Tai Hu samples encoding for resistances against beta-lactams and macrolides, respectively. The T&O problems observed in drinking water of the Tai Hu region could not be attributed to the algae burden T&O compounds such as geosmin or 2-MIB. This study demonstrates the effects on the water treatment process caused by high amounts of dissolved organic carbon (DOC) and dissolved organic nitrogen (DON). The elevated concentration of organic compounds in raw water results in a short life span of ozone during advanced treatment. In the disinfection process, the remaining nitrogen-containing organic compounds undergo subsequent reactions. In particular, amino acids might trigger the formation of chloramine-type T&O compounds. Amino acids were detected in raw water samples taken at the inlets of the Tai Hu water treatment plants and were shown to be present in fluctuating concentrations. Most probably, lysis of algae cells during drinking water treatment due to oxidation processes such as pre-ozonation results in the release of intracellular compounds and elevated aqueous phase concentrations of DOC and DON (containing proteins, peptides, and amino acids). In laboratory experiments, it was shown that algae could be removed effectively by ultrafiltration, thus proving to be a suitable pretreatment process while avoiding cell disruption and subsequent formation of T&O compounds. Based on analysis of Tai Hu field samples and laboratory experiments, pilot-scale proof-of-concept studies were developed. Future studies will focus on online monitoring of drinking water treatment performance including the precursors of T&O compounds. Also, the removal of emerging chemical and microbiological pollutants will be emphasized in order to ensure high-quality drinking water.

The overall objective of the project was the development of water management system solutions for a sustainable improvement of water quality in the city of Chaohu and in the Chao Lake. The Urban Water Resources Management (UWRM) concept is the innovative approach, which includes both efficient urban water management in urban and suburban areas, as well as interaction with aquatic ecosystems. Data and models for planning purposes and regional water management are made available by using a comprehensive online environmental information system for authorities and water suppliers. The Chao Lake plays a central role as an ecological and economic protection and raw water supplier for the drinking water supply of the population of the city of Chaohu. The research and development project (R&D Project) thus makes an important contribution to the sustainable development of the Chaohu region as part of the Masterplan Ecological Seascape Chaohu of the Anhui Provincial Government. The scientific and technical solutions are implemented in demonstration projects.

Inland waters are of great importance for scientists as well as authorities since they are essential ecosystems and well known for their biodiversity. When monitoring their respective water quality, in situ measurements of water quality parameters are spatially limited, costly and time-consuming. In this paper, we propose a combination of hyperspectral data and machine learning methods to estimate and therefore to monitor different parameters for water quality. In contrast to commonly-applied techniques such as band ratios, this approach is data-driven and does not rely on any domain knowledge. We focus on CDOM, chlorophyll a and turbidity as well as the concentrations of the two algae types, diatoms and green algae. In order to investigate the potential of our proposal, we rely on measured data, which we sampled with three different sensors on the river Elbe in Germany from 24 June–12 July 2017. The measurement setup with two probe sensors and a hyperspectral sensor is described in detail. To estimate the five mentioned variables, we present an appropriate regression framework involving ten machine learning models and two preprocessing methods. This allows the regression performance of each model and variable to be evaluated. The best performing model for each variable results in a coefficient of determination R 2 in the range of 89.9% to 94.6%. That clearly reveals the potential of the machine learning approaches with hyperspectral data. In further investigations, we focus on the generalization of the regression framework to prepare its application to different types of inland waters.

Lakes are important ecosystems that provide a number of ecosystem services including provision of drinking water, flood control, fisheries and in general a high natural, cultural and aesthetic value. Provisioning services from lakes are particularly relevant in regions where lakes supply drinking water. In these water bodies, a high water quality is of utmost importance in order to produce drinking water at required quantities and at affordable prices. High nutrient loading, eutrophication, and toxicant pollution, however, are growing stressors in many places, driving severe water quality deteriorations that harm domestic water supply, quality of life and social welfare. Fast growing urban areas are particularly vulnerable to these deteriorations in surface water resources, because waste, waste water, and chemical pollutants (heavy metals, pesticides, etc.) are affecting nearby aquatic ecosystems. While in river ecosystems these pollution pressures only affect water users further downstream, i.e. not directly the pollution producer responsible for the water quality deterioration, standing water bodies like lakes or reservoirs directly and often negatively feed back to the adjacent urban communities.

The Taihu (Tai lake) region is one of the most economically prospering areas of China. Due to its location within this district of high anthropogenic activities, Taihu represents a drastic example of water pollution with nutrients (nitrogen, phosphate), organic contaminants and heavy metals. High nutrient levels combined with very shallow water create large eutrophication problems, threatening the drinking water supply of the surrounding cities. Within the international research project SIGN (SinoGerman Water Supply Network, www.water-sign.de ), funded by the German Federal Ministry of Education and Research (BMBF), a powerful consortium of fifteen German partners is working on the overall aim of assuring good water quality from the source to the tap by taking the whole water cycle into account: The diverse research topics range from future proof strategies for urban catchment, innovative monitoring and early warning approaches for lake and drinking water, control and use of biological degradation processes, efficient water treatment technologies, adapted water distribution up to promoting sector policy by good governance. The implementation in China is warranted, since the leading Chinese research institutes as well as the most important local stakeholders, e.g. water suppliers, are involved.

The absence of contamination in drinking water is essential to protect public health. Online monitoring is a promising strategy to ensure a good drinking water quality. Online analysis techniques mainly cover physico‐chemical parameters e.g. pH‐value and turbidity. In comparison, the online detection of single contaminants is quite difficult and costly. A promising alternative is the rapid detection of abnormalities or changes in the water matrix by spectroscopic techniques such as absorbance or fluorescence (emission) spectroscopy.

The effects of energetic decoupling of phycobiliproteins (PBP) from photosystems in Nostoc sp. on the emission characteristics and fluorescence profiles of cyanobacterial photosynthetic apparatus and its components were studied using steady-state and time-resolved fluorescence emission. The steady-state measurements show a rise in fluorescence from PBP released at low ionic strength. The emission decay profile of Nostoc photosynthetic apparatus has two components with lifetimes 1.8 ns and about 0.1 ns but their relative contributions to the total emission decay vary, depending on the energetic coupling of phycobilisomes to photosystems. At low ionic strength, the contribution of the long-lived emission characteristic for free phycocyanin increased, confirming the detachment of PBP from the photosystems. We show that these effects can be used as a basis for improvement of cyanobacteria detection method. It is demonstrated that the fitting algorithm applied in the measurements with a FluoroProbe fluorometer (bbe Moldaenke, Schwentinental, Germany) can differentiate between coupled and uncoupled PBP. This approach may prove useful in monitoring the state of photosynthetic apparatus in cyanobacterial populations and their spatial distribution in water reservoirs.

The indicator function of the fluorescence signals of the cyanopigments phycocyanin and phycoerythrin as early warning parameters against the microcystins in drinking water was investigated by lab- and pilot-scale studies. The early warning function of the fluorescence signals was examined with regard to the signals' real-time character, their sensitivity and the behaviour of the cyanopigments in different treatment stages in comparison to microcystins. Fluorescence measurements confirmed the real-time character, since they can be carried out on-site without the pre-concentration of pigments. The limit of detection of phycoerythrin is determined at 0.7 microg/L and of phycocyanin at 5.3 microg/L respectively. If the pigment/microcystin ratio is known and calculated to be higher than 1, very low microcystin concentrations can be estimated by the fluorescence signals. The compared behaviour of both pigments and selected microcystins (MC-LR and MC-RR) during water treatment shows that pigments have an early warning function against microcystins in conventional treatment stages using pre-oxidation with permanganate, powdered-activated carbon and chlorination. In contrast, cyanopigments do not have an early warning function if chlorine dioxide is used as a pre-oxidant or final disinfection agent. In order to use pigment control measurements in drinking water treatment the initial pigment/toxin ratio of the raw water must be known.

Measuring chlorophyll fluorescence at five different wavelengths provides the discrimination of four phytoplankton groups. Here the problems associated with a free-falling depth profiler for phytoplankton discrimination are considered. When F0, F, and Fm are determined sequentially in the same measuring cell, then the algae inside the cell have a different light history. It depends on their different locations in the cell as caused by the induction curve of chlorophyll fluorescence. Mathematical algorithms are developed which enable the calculation of the concentrations of individual phytoplankton groups from the integral fluorescence signal (averaged for 1s) for different velocities of the falling probe. The theory requires the knowledge of the fluorescence behaviour of phytoplankton in stationary suspensions. The predictions of the model are compared with measurements in flowing suspensions containing chlorophyta, cyanobacteria, cryptophyta and diatoms. The comparison shows the reliability of the algorithms. The application of the algorithms is indispensable for dark-adapted cells and is less important for light-adapted cells.

Currently it is still extremely difficult to adequately sample populations of microalgae on sediments for large-scale biomass determination. We have now devised a prototype of a new benthic sensor (BenthoFluor) for the quantitative and qualitative assessment of microphytobenthos populations in situ. This sensor enables a high spatial and temporal resolution and a rapid evaluation of the community structure and distribution. These determinations are based on the concept that five spectral excitation ranges can be used to differentiate groups of microalgae, in situ, within a few seconds. In addition, because sediments contain a lot of yellow substances, which can affect the fluorescence and optical differentiation of the algae, the device was equipped with a UV-LED for yellow substances correction. The device was calibrated against HPLC with cultures and tested in the field. Our real-time approach can be used to monitor algal assemblage composition on sediments and is an ideal tool for investigations on the large-scale spatial and temporal variation of algal populations in sediments. Apart from the differentiation of algal populations, the BenthoFluor allows instantaneous monitoring of the chlorophyll concentrations and determination of which algae are responsible for this on the uppermost surface of sediments in the field and in experimental set-ups.