Online fluorescence spectroscopy for the real-time evaluation of the microbial quality of drinking water

Temporal drivers of tryptophan-like fluorescent dissolved organic matter along a river continuum

Tryptophan-like fluorescence (TLF) is used to indicate anthropogenic inputs of dissolved organic matter (DOM), typically from wastewater, in rivers. We hypothesised that other sources of DOM, such as groundwater and planktonic microbial biomass can also be important drivers of riverine TLF dynamics. We sampled 19 contrasting sites of the River Thames, UK, and its tributaries. Multivariate mixed linear models were developed for each site using 15 months of weekly water quality observations and with predictor variables selected according to the statistical significance of their linear relationship with TLF following a stepwise procedure. The variables considered for inclusion in the models were potassium (wastewater indicator), nitrate (groundwater indicator), chlorophyll-a (phytoplankton biomass), and Total bacterial Cells Counts (TCC) by flow cytometry. The wastewater indicator was included in the model of TLF at 89 % of sites. Groundwater was included in 53 % of models, particularly those with higher baseflow indices (0.50-0.86). At these sites, groundwater acted as a negative control on TLF, diluting other potential sources. Additionally, TCC was included positively in the models of six (32 %) sites. The models on the Thames itself using TCC were more rural sites with lower sewage inputs. Phytoplankton biomass (Chlorophyll-a) was only used in two (11 %) site models, despite the seasonal phytoplankton blooms. It is also notable that, the wastewater indicator did not always have the strongest evidence for inclusion in the models. For example, there was stronger evidence for the inclusion of groundwater and TCC than wastewater in 32 % and 5 % of catchments, respectively. Our study underscores the complex interplay of wastewater, groundwater, and planktonic microbes, driving riverine TLF dynamics, with their influence determined by site characteristics.

Fluorescence Spectroscopy Based Identification of Pseudomonas Aeruginosa and Escherichia Coli Suspensions

In this article, Fluorescence spectroscopy has been employed for the identification of Pseudomonas aeruginosa (PA) and Escherichia coli (E. coli) in water suspension. Emission spectra of PA and E. coli suspensions have been acquired by using excitation wavelengths from 270 to 420 nm with steps of 10 nm to explore their spectral features. It has been found that the emission spectra of tryptophan, tyrosine, NADH and FAD, being the intracellular biomolecules present in both bacteria, can be used as fingerprints for their identification, differentiation and quantification. Both bacterial strains can clearly be differentiated from water and from each other by using λex 270-290 nm through spectral analysis and from λex: 300-500 nm by applying statistical analysis. Furthermore, calibration curves for different bacterial loads of PA and E. coli suspensions have been produced between colonies forming units per ml (CFUs/ml) the integrated intensities of their emission spectra. CFUs/ml of both bacterial suspensions have been determined through plate count method which was used as cross-reference for the analysis of emission spectra of both bacterial suspensions. These curves may be used to estimate CFU/ml of both PA and E. coli in unknown water suspensions by determining the integrating intensity of their emission spectra.

Fluorescence spectroscopy in the detection and management of disinfection by-product precursors in drinking water treatment processes: A review

Monitoring and prevention of the formation of disinfection by-products (DBPs) is paramount in drinking water treatment plants (DWTP) to ensure human health safety. This review provides an overview of how fluorescence techniques are developed to predict DBP formation and to evaluate the reduction of fluorescence components and DBPs following individual DWTP processes. Evidence has shown that common DBPs, nitrogenous DBPs and specific emerging DBPs exhibit positive linear relationships with terrestrial, anthropogenic, tryptophan-like, and eutrophic humic-like fluorescence. Due to the interrelationships of both regulated and emerging DBP types with fluorescence components, the limitations arise when attempting to predict emerging DBPs solely through linear relationships. Monitoring the reduction of DBP precursors after each treatment process can be achieved by studying the relationship between fluorescence components and DBPs. During the coagulation process, highest reduction rates are observed for terrestrial humic-like fluorescence. Advanced treatments such as granular, powdered, silver-impregnated activated carbon, magnetic ion exchange resins, and reverse osmosis, have revealed a significant reduction of fluorescent DBP precursors, ranging from 53% to 100%. During chlorination, the reduction rate follows the order: terrestrial humic-like > microbial humic-like > protein/tryptophan-like fluorescence. This review provides insights into the reduction of fluorescence signatures following individual DWTP processes, which offers information regarding DBP formation. These insights could assist in optimizing the treatment process to more effectively manage DBP formation. For the identification of emerging DBP generation, the utilization of advanced models is imperative to precisely predict emerging DBPs and to more accurately trace DBP precursors within DWTPs.

In Situ Water Quality Monitoring Using an Optical Multiparameter Sensor Probe

Optical methods such as ultraviolet/visible (UV/Vis) and fluorescence spectroscopy are well-established analytical techniques for in situ water quality monitoring. A broad range of bio-logical and chemical contaminants in different concentration ranges can be detected using these methods. The availability of results in real time allows a quick response to water quality changes. The measuring devices are configured as portable multi-parameter probes. However, their specification and data processing typically cannot be changed by users, or only with difficulties. Therefore, we developed a submersible sensor probe, which combines UV/Vis and fluorescence spectroscopy together with a flexible data processing platform. Due to its modular design in the hardware and software, the sensing system can be modified to the specific application. The dimension of the waterproof enclosure with a diameter of 100 mm permits also its application in groundwater monitoring wells. As a light source for fluorescence spectroscopy, we constructed an LED array that can be equipped with four different LEDs. A miniaturized deuterium-tungsten light source (200-1100 nm) was used for UV/Vis spectroscopy. A miniaturized spectrometer with a spectral range between 225 and 1000 nm permits the detection of complete spectra for both methods.

Fluorescence Spectroscopy Based Characterization of Pseudomonas Aeruginosa Suspension

In this article, optical characterization of Pseudomonas aeruginosa (PA) suspension has been performed by using Fluorescence spectroscopy. Optical density (OD) and plate count methods have been employed as a reference for the analysis of emission spectra of Pseudomonas aeruginosa in water suspension. Emission spectra of PA suspension has been acquired by using excitation wavelengths from 270 to 420 nm with step of 10 nm to explore its spectral behavior. It has been found that emission spectra of tryptophan, tyrosine, NADH and FAD, the intracellular biomolecules of bacteria, can be used as finger prints for the detection of Pseudomonas aeruginosa. Furthermore, the effect of water matrix on the spectral emission of Pseudomonas aeruginosa has been investigated that might be one of the limitation of Fluorescence spectroscopy for complex water matrices. Moreover, a calibration curve has been produced between ODs600 of Pseudomonas aeruginosa suspensions of different bacterial load and integrated intensities of the emission spectra of same samples. These ODs600 and integrating intensities have been further vetted through plate count method by determining their corresponding colony forming units per ml (CFU/ml). This calibration curve may be used to determine CFU/ml of Pseudomonas aeruginosa in water sample by determining integrating intensity of its emission spectrum.

Fabrication and optimization of paper chips from calcinated Fe-MOFs for rapid and in situ visual detection of tetracyclines in water environments

Antibiotics such as tetracyclines (TCs) have become a major threat to ecosystem safety and human health, as their abuse has caused the occurrence and proliferation of antibiotic-resistant bacteria and genes. Currently, there is still a lack of convenient in situ methods for the detection and monitoring of TC pollution in actual water systems. This research reports a paper chip based on the complexation of iron-based metal organic frameworks (Fe-MOFs) and TCs for rapid and in situ visual detection of representative oxytetracycline (OTC) pollution in water environments. The optimized complexation sample NH₂-MIL-101(Fe)- 350 obtained by calcination at 350 °C exhibited the highest catalytic activity and was then used for paper chip fabrication by printing and surface modification. Notably, the paper chip demonstrated a detection limit as low as 17.11 nmol L^-1 and good practicability in reclaimed water, aquaculture wastewater, and surface water systems, with OTC recovery rates of 90.6-111.4%. More importantly, the presence of dissolved oxygen (9.13-12.7 mg L^-1), chemical oxygen demand (0.52-12.1 mg L^-1), humic acid (< 10 mg L^-1), Ca²⁺, Cl^-, and HPO₄^2- (< 0.5 mol L^-1) had negligible interference on the detection of TCs by the paper chip. Therefore, this work has developed a promising method for rapid and in situ visual monitoring of TC pollution in actual water environments.

One-step fluorometric determination of multiple-component dissolved organic matter in aquatic environments

Dissolved organic matter (DOM) is ubiquitous in aqueous environments and is composed of different components that play different but important roles in the migration and the fate of pollutants, emergence of the disinfect byproduct, thus requiring quantitative characterization. However, until now, simultaneous quantification of the main contents in DOM, i.e., saccharides, proteins, and humic substances, has been difficult, impeding us from understanding and predicting the environmental behaviors of typical pollutants. In this work, a fluorescence approach based on the excitation emission matrix (EEM), combined with a new algorithm, denoted matrix reconstruction coupled with prior linear decomposition (MR-PLD), was developed to quantify multiple DOM simultaneously. First, a set of simulated water samples consisting of glucose, tryptones, and humic acid (HA) were analyzed using MR-PLD to validate the feasibility of the method. The DOM components could be reliably determined with a higher accuracy than parallel factor analysis (PARAFAC) and Parallel Factor Framework-Linear Regression (PFFLR), also with a more convenient procedure than conventional PLD. Second, both actual simulated and experimental methods were performed to test the anti-interference performance of MR-PLD, indicating that the quantification of DOM would not be significantly impacted by other fluorophores. Finally, several actual water samples from natural waters and wastewater treatment plants were also analyzed to confirm the robustness of this method in actual aqueous environments. This study provides a new approach to characterize DOM with EEM, contributing to its convenient concentration monitoring and the further exploration of the environmental impacts.

Can online particle counters and electrochemical sensors distinguish normal periodic and aperiodic drinking water quality fluctuations from contamination?

Early warning systems monitoring the quality of drinking water need to distinguish between normal quality fluctuations and those caused by contaminants. Thus, to decrease the number of false positive events, normal water quality fluctuations, whether periodic or aperiodic, need to be characterized. For this, we used a novel flow-imaging particle counter, a light-scattering particle counter, and electrochemical sensors to monitor the drinking water quality of a pressure zone in a building complex for 109 days. Data were analyzed to determine the feasibility of the sensors and particle counters to distinguish periodic and aperiodic fluctuations from real-life contaminants. The concentrations of particles smaller than 10 μm and N, Small, Large, and B particles showed sudden changes recurring daily, likely due to the flow rate changes in the building complex. Conversely, the concentrations of larger than 10 μm particles and C particles, in addition to the responses of electrochemical sensors, remained in their low typical values despite flow rate changes. The aperiodic events, likely resulting from an abnormally high flow rate in the water mains due to maintenance, were detected using particle counters and electrochemical sensors. This study provides insights into choosing water quality sensors by showing that machine learning-based particle classes, such as B, C, F, and particles larger than 10 μm are promising in distinguishing contamination from aperiodic and periodic fluctuations while the use of other particle classes and electrochemical sensors may require dynamic baseline to decrease false positive events in an early warning system.

Research on Small-Scale Detection Instrument for Drinking Water Combined Laser Spectroscopy and Conductivity Technology

In order to realize rapid and accurate evaluation of drinking water quality, a small-scale water quality detection instrument is designed in this paper that can detect two representative water quality parameters: the permanganate index and total dissolved solids (TDS). The permanganate index measured by the laser spectroscopy method can achieve the approximate value of the organic matter in water, and the TDS measured by the conductivity method can obtain the approximate value of the inorganic matter in water. In addition, to facilitate the popularization of civilian applications, the evaluation method of water quality based on the percent-scores proposed by us is presented in this paper. The water quality results can be displayed on the instrument screen. In the experiment, we measured the water quality parameters of the tap water as well as those after the primary and secondary filtration in Weihai City, Shandong Province, China. The testing results show that the instrument can quickly detect dissolved inorganic and organic matter, and intuitively display the water quality evaluation score on the screen. The instrument designed in this paper has the advantages of high sensitivity, high integration, and small volume, which lays the foundation for the popularity of the detection instrument.

Multiple fluorescence approaches to identify rapid changes in microbial indicators at karst springs

Karst springs are globally important for drinking water supply but are often also exceptionally vulnerable to contamination. Such springs usually exhibit strong variation in microbial water quality in sharp response to rainfall events, thus, posing a health hazard to consumers of water supplied from these sources. The rapid detection of such changes is extremely important as well as being able to establish a link to the sources of such pollution, so that appropriate measures can be taken both in terms of immediate protection of human health and the management of karst aquifers. In this study, a fluorescence-based multi-parameter approach was trialed in order to evaluate which methods can be used to monitor rainfall-induced rapid changes in microbial water quality at karst springs, as well as determine whether such changes can be linked to sources of human effluent contamination. The results from three monitoring periods at two karst springs revealed marked responses to rainfall events for all of the microbial parameters measured. Total cell count (TCC) measurements using flow cytometry (FCM) showed very strong positive correlations with the more conventionally monitored faecal indicator bacteria (FIB) and total coliforms (TC), indicating that such a fluorescence-based and cultivation-independent technique can be very useful to indicate rapid changes in microbial water quality at karst springs. Furthermore, very strong positive correlations were also found between tryptophan-like fluorescence (TLF) measurements and concentrations of all monitored microbial parameters, again demonstrating that such a fluorescence-based approach can also be useful for detecting rapid changes in concentrations of traditional faecal indicators. Interestingly, it was found that fluorescent whitening compounds (FWCs) signals do not necessarily follow temporal variations of microbial indicators. However, the frequency of detection of positive FWCs signals may still reveal useful information about the overall magnitude of human wastewater effluent impacts on karst aquifer systems.

Waterbird guilds predict environmental attributes of inland saline aquatic ecosystems on multi-spatial scales

Inland saline waters in Central Asia constitute an important part of steppe ecosystems, providing considerable ecological functions and ecosystem services. Here we aim to present a multi-spatial scale analysis of nutrient cycling and transport waterbird guilds, and the environmental attributes of saline-soda aquatic ecosystems in Kazakhstan. The density, biomass, and diversity of waterbird guilds was determined in the case of three nutrient cycling and transport guilds: a) net-importer (IM), b) importer-exporter (IMEX), c) net-exporter (EX), according to the Boros's guild classification method, and for several traditional feeding guilds: carnivorous, herbivorous, invertebrate eater, omnivorous and piscivorous. Our results revealed that waterbird guilds, as predictors represented by the complete waterbird community, are in close relationship with several (N = 12) environmental attributes of inland saline waters through complex trophic linkages of waterbird populations on multi-spatial scales. The density and the biomass of the EX and IMEX guilds are strongly and positively correlated (i) with the productivity metrics of habitats (e.g., CHL, GPP), indicating their trophic position, and (ii) with water depth. We found significant correlations among guild density, biomass, diversity and environmental attributes on multi-spatial scales for IMEX and EX. Our results revealed that IMEX predicts the surrounding environment of aquatic habitats, whereas EX species are substantial environmental predictors of aquatic ecosystems. However, the diversity metric had valid models only with EX. The herbivorous and omnivorous guilds, that feed chiefly on plant materials consist mainly of IMEX and EX duck species, which were positively related to grassland coverage and the shoreline development index. As a methodological result, here we present a novel approach, the guild transport index, which has more robust relationships with environmental attributes than individual guilds, thus it provides a complex evaluation of the nutrient cycling by birds between aquatic and terrestrial environments on multi-spatial scales.

Analysis of urine using electronic tongue towards non-invasive cancer diagnosis

Electronic tongues (e-tongues) have been broadly employed in monitoring the quality of food, beverage, cosmetics, and pharmaceutical products, and in diagnosis of diseases, as the e-tongues can discriminate samples of high complexity, reduce interference of the matrix, offer rapid response. Compared to other analytical approaches using expensive and complex instrumentation as well as required sample preparation, the e-tongue is non-destructive, miniaturizable and on-site method with little or no preparation of samples. Even though e-tongues are successfully commercialized, their application in cancer diagnosis from urine samples is underestimated. In this review, we would like to highlight the various analytical techniques such as Raman spectroscopy, infrared spectroscopy, fluorescence spectroscopy, and electrochemical methods (potentiometry and voltammetry) used as e-tongues for urine analysis towards non-invasive cancer diagnosis. Besides, different machine learning approaches, for instance, supervised and unsupervised learning algorithms are introduced to analyze extracted chemical data. Finally, capabilities of e-tongues in distinguishing between patients diagnosed with cancer and healthy controls are highlighted.

A case study: The deployment of a novel in situ fluorimeter for monitoring biological contamination within the urban surface waters of Kolkata, India

The quality and health of many of our vital freshwater systems are poor. To tackle this with ever increasing pressures from anthropogenic and climatic changes, we must improve water quality monitoring and devise and implement more appropriate water quality parameters. Recent research has highlighted the potential for Peak T fluorescence (tryptophan-like fluorescence, TLF) to monitor microbial activity in aquatic systems. The VLux TPro (Chelsea Technologies Ltd., UK), an in situ real-time fluorimeter, was deployed in different urban freshwater bodies within Kolkata (West Bengal, India) during March 2019. This study is the first to apply this technology in surface waters within a densely populated urban area. Spot-sampling was also undertaken at 13 sampling locations enabling physicochemical analysis, bacterial enumeration and determination of nutrient (nitrate and phosphate) concentrations. This case study has demonstrated the ability of an in situ fluorimeter, VLux TPro, to successfully identify both biological contamination events and potential elevated microbial activity, related to nutrient loading, in complex surface freshwaters, without the need for expensive and time-consuming laboratory analysis.

DOM tracking and prediction of rural domestic sewage with UV-vis and EEM in the Yangtze River Delta, China

Compared with the urban sewage treatment plants, the operation of rural decentralized sewage facilities is trapped by the absence of professionals, thus having to be run dependently on the self-adaptive operation of the facilities, which makes timely monitoring particularly important. In this study, organic pollutants in rural domestic sewage and urban domestic sewage are analyzed using ultraviolet-visible (UV-vis) absorption spectroscopy, fluorescence excitation-emission matrix (EEM) and Fourier transform infrared reflectance (FTIR). Compared with the UV-vis absorption spectrum, EEM can not only make up the deficiency in the detection of some easily degradable organics in sewage, but also reveal the transformation of different components, thus indicating timely the treatment progress of rural sewage. Linear fitting of COD and spectrum shows that UV₂₅₄ combined with fluorescence excitation-emission at Ex/Em = 250/330 nm might be more suitable for the prediction of COD in rural water than the UV₂₅₄ alone. This is of great significance for guiding the self-adaptive operation of rural domestic sewage facilities, improving their stability and efficiency, so as to improve the rural living environment.

A continuous, in-situ, near-time fluorescence sensor coupled with a machine learning model for detection of fecal contamination risk in drinking water: Design, characterization and field validation

We designed and validated a sensitive, continuous, in-situ, remotely reporting tryptophan-like fluorescence sensor and coupled it with a machine learning model to predict high-risk fecal contamination in water (>10 colony forming units (CFU)/100mL E. coli). We characterized the sensor's response to multiple fluorescence interferents with benchtop analysis. The sensor's minimum detection limit (MDL) of tryptophan dissolved in deionized water was 0.05 ppb (p <0.01) and its MDL of the correlation to E. coli present in wastewater effluent was 10 CFU/100 mL (p <0.01). Fluorescence response declined exponentially with increased water temperature and a correction factor was calculated. Inner filter effects, which cause signal attenuation at high concentrations, were shown to have negligible impact in an operational context. Biofouling was demonstrated to increase the fluorescence signal by approximately 82% in a certain context, while mineral scaling reduced the sensitivity of the sensor by approximately 5% after 24 hours with a scaling solution containing 8 times the mineral concentration of the Colorado River. A machine learning model was developed, with TLF measurements as the primary feature, to output fecal contamination risk levels established by the World Health Organization. A training and validation data set for the model was built by installing four sensors on Boulder Creek, Colorado for 88 days and enumerating 298 grab samples for E. coli with membrane filtration. The machine learning model incorporated a proxy feature for fouling (time since last cleaning) which improved model performance. A binary classification model was able to predict high risk fecal contamination with 83% accuracy (95% CI: 78% - 87%), sensitivity of 80%, and specificity of 86%. A model distinguishing between all World Health Organization established risk categories performed with an overall accuracy of 64%. Integrating TLF measurements into an ML model allows for anomaly detection and noise reduction, permitting contamination prediction despite biofilm or mineral scaling formation on the sensor's lenses. Real-time detection of high risk fecal contamination could contribute to a major step forward in terms of microbial water quality monitoring for human health.

Mixing of arsenic-rich groundwater and surface water in drinking water distribution systems: Implications for contaminants, disinfection byproducts and organic components

The utilization of groundwaters containing high levels of arsenic (As) for drinking water purposes presents major health and economic challenges for water utilities. One low-cost approach is to mix arsenic-rich groundwater (GW) with arsenic-free surface waters (SW) to achieve acceptable As levels. In this study we investigated the effect of different mixing ratios on water quality in an eastern Croatian water distribution system (WDS). To investigate the effects of mixing on drinking water quality, we measured the organic matter (OM) composition, disinfection byproduct (DBP) and metal concentrations in differently mixed ratios of GW and SW within the WDS. Fluorescence analysis revealed that the GW and SW had similar OM composition, with an almost equal ratio of humic- and protein-like OM throughout the WDS despite fluorescence indices revealing slightly different OM sources between the two water types. The tyrosine-like OM component was more variable, increasing during warmer months and towards the end of the WDS, most likely due to enhanced biofilm formation. Arsenic concentrations decreased to below 10 μg/L in the second half of the sampling campaign. Acceptable water quality was achieved after a period of destabilization and solubilization of loose deposits within the WDS resulting in their mobilization caused by water quality changes. Principal component and classification analysis, regression models and Spearman correlation coefficients revealed an association between As, OM and DBP concentrations with these correlations suggestive of their role in As mobilization in the WDS. Changing source waters, with different OM content and characteristics, corresponded to variable As release within the WDS.

The in situ Production of Aquatic Fluorescent Organic Matter in a Simulated Freshwater Laboratory Model

Dissolved organic matter (DOM) is ubiquitous throughout aquatic systems. Fluorescence techniques can be used to characterize the fluorescing proportion of DOM, aquatic fluorescent organic matter (AFOM). AFOM is conventionally named in association with specific fluorescence “peaks,” which fluoresce in similar optical regions as microbially-derived proteinaceous material (Peak T), and terrestrially-derived humic-like compounds (Peaks C/C+), with Peak T previously being investigated as a tool for bacterial enumeration within freshwaters. The impact of anthropogenic nutrient loading on the processing of DOM by microbial communities is largely unknown. Previous laboratory studies utilizing environmental freshwater have employed growth media with complex background fluorescence, or very high nutrient concentrations, preventing the investigation of AFOM production under a range of more representative nutrient concentrations within a matrix exhibiting very low background fluorescence. We describe a laboratory-based model with Pseudomonas aeruginosa that incorporates a low fluorescence growth matrix consisting of a simulated freshwater (SFW), representative of low-hardness freshwater systems allowing controlled nutrient conditions to be studied. The effects of microbial processing of DOM as a function of available nitrogen, phosphorous, and dissolved organic carbon (DOC) in the form of glucose were investigated over 48 h at highly resolved time increments. The model system demonstrates the production of a range of complex AFOM peaks in the presence and absence of DOC, revealing no linear relationship between cell numbers and any of the peaks for the bacterial species studied, with AFOM peaks increasing with microbial cell number, ranging from 55.2 quinine sulfate units (QSU) per 10⁶ cells to 155 QSU per 10⁶ cells (p < 0.05) for Peak T during the exponential growth phase of P. aeruginosa under high nutrient conditions with 5 mg L⁻¹ DOC. Nutrient and DOC concentration was found to cause differential production of autochthonous- or allochthonous-like AFOM, with lower DOC concentrations resulting in higher Peak T production relative to Peaks C/C+ upon the addition of nutrients, and high DOC concentrations resulting in higher Peak C/C+ production relative to Peak T. Our results show the production of allochthonous-like AFOM from a simple and non-fluorescent carbon source, and provide uncertainty in the use of Peak T as a reliable surrogate for specific bacterial enumeration, particularly in dynamic or nutrient-impacted environments, pointing toward the use of fluorescence as an indicator for microbial metabolism.

Seasonality of enteric viruses in groundwater-derived public water sources

We investigated the seasonal prevalence of seven enteric viruses in groundwater-derived public water sources distributed across the dominant aquifers of England. Sampling targeted four periods in the hydrological cycle with typically varying microbial risks, as indicated using a decade of Escherichia coli prevalence data. Viruses were concentrated onsite by filtration of raw groundwater, and extracted nucleic acid (NA) was amplified by qPCR or RT-qPCR. Seven out of eight sources, all aquifers, and 31% of samples were positive for viral NA. The most frequently detected viral NA targets were Hepatitis A virus (17% samples, 63% sites), norovirus GI (14% samples, 38% sites), and Hepatitis E virus (7% samples, 25% sites). Viral NA presence was episodic, being most prevalent and at its highest concentration during November and January, the main groundwater recharge season, with 89% of all positive detects occurring during a rising water table. Seasonal norovirus NA detections matched its seasonal incidence within the population. Viral NA is arriving with groundwater recharge, as opposed to persisting for long-periods within the saturated zone. Neither total coliforms nor E. coli were significant predictors of viral NA presence-absence, and there was limited co-occurrence between viruses. Nevertheless, a source with an absence of E. coli in regularly collected historical data is unlikely to be at risk of viral contamination. To manage potential groundwater viral contamination via risk assessment, larger scale studies are required to understand key risk factors, with the evidence here suggesting viral NA is widespread across a range of typical microbial risk settings.

In-situ fluorescence spectroscopy is a more rapid and resilient indicator of faecal contamination risk in drinking water than faecal indicator organisms

Faecal indicator organisms (FIOs) are limited in their ability to protect public health from the microbial contamination of drinking water because of their transience and time required to deliver a result. We evaluated alternative rapid, and potentially more resilient, approaches against a benchmark FIO of thermotolerant coliforms (TTCs) to characterise faecal contamination over 14 months at 40 groundwater sources in a Ugandan town. Rapid approaches included: in-situ tryptophan-like fluorescence (TLF), humic-like fluorescence (HLF), turbidity; sanitary inspections; and total bacterial cells by flow cytometry. TTCs varied widely in six sampling visits: a third of sources tested both positive and negative, 50% of sources had a range of at least 720 cfu/100 mL, and a two-day heavy rainfall event increased median TTCs five-fold. Using source medians, TLF was the best predictor in logistic regression models of TTCs ≥10 cfu/100 mL (AUC 0.88) and best correlated to TTC enumeration (ρ_s 0.81), with HLF performing similarly. Relationships between TLF or HLF and TTCs were stronger in the wet season than the dry season, when TLF and HLF were instead more associated with total bacterial cells. Source rank-order between sampling rounds was considerably more consistent, according to cross-correlations, using TLF or HLF (min ρ_s 0.81) than TTCs (min ρ_s 0.34). Furthermore, dry season TLF and HLF cross-correlated more strongly (ρ_s 0.68) than dry season TTCs (ρ_s 0.50) with wet season TTCs, when TTCs were elevated. In-situ TLF or HLF are more rapid and resilient indicators of faecal contamination risk than TTCs.

Live-Cell Systems in Real-Time Biomonitoring of Water Pollution: Practical Considerations and Future Perspectives

Continuous monitoring and early warning of potential water contamination with toxic chemicals is of paramount importance for human health and sustainable food production. During the last few decades there have been noteworthy advances in technologies for the automated sensing of physicochemical parameters of water. These do not translate well into online monitoring of chemical pollutants since most of them are either incapable of real-time detection or unable to detect impacts on biological organisms. As a result, biological early warning systems have been proposed to supplement conventional water quality test strategies. Such systems can continuously evaluate physiological parameters of suitable aquatic species and alert the user to the presence of toxicants. In this regard, single cellular organisms, such as bacteria, cyanobacteria, micro-algae and vertebrate cell lines, offer promising avenues for development of water biosensors. Historically, only a handful of systems utilising single-cell organisms have been deployed as established online water biomonitoring tools. Recent advances in recombinant microorganisms, cell immobilisation techniques, live-cell microarrays and microfluidic Lab-on-a-Chip technologies open new avenues to develop miniaturised systems capable of detecting a broad range of water contaminants. In experimental settings, they have been shown as sensitive and rapid biosensors with capabilities to detect traces of contaminants. In this work, we critically review the recent advances and practical prospects of biological early warning systems based on live-cell biosensors. We demonstrate historical deployment successes, technological innovations, as well as current challenges for the broader deployment of live-cell biosensors in the monitoring of water quality.

Using machine learning classification to detect simulated increases of de facto reuse and urban stormwater surges in surface water

Water quality events such as increases in stormwater or wastewater effluent in drinking water sources pose hazards to drinking water consumers. Stormwater and wastewater effluent enter Lake Mead-an important drinking water source in the southwest USA-via the Las Vegas Wash. Previous studies have applied machine learning and online instruments to detect contamination in water distribution systems. However, alert systems at drinking water intakes would provide more time for corrective action. An array of online instruments measuring pH, conductivity, redox potential, turbidity, temperature, tryptophan-like fluorescence, UV absorbance (UVA₂₅₄), TOC, and chlorophyll-a was fed raw water directly from Lake Mead. Wastewater effluent, dry weather Las Vegas Wash, and storm-impacted Las Vegas Wash samples were blended into the instrument inlets at known ratios to simulate three types of adverse water quality events. Data preprocessing was conducted to correct for diurnal patterns or instrument drift. Supervised machine learning was conducted using previously published models in R. Ninety-nine models were screened on the raw data. Eight high-performing models were evaluated in-depth and optimized. Weighted k-Nearest Neighbors, Single C5.0 Ruleset, Mixture Discriminant Analysis, and an ensemble of these three models had accuracy over 97% when assigning test set data among three classes (Normal, Event, or Maintenance). The ensemble detected all event types at the earliest timepoint and had one false positive that was not a lag error (i.e., consecutively following a true positive). Omitting Maintenance, the Adaboost model had over 99% test set accuracy and zero false positives that were not lag errors. Data preprocessing was beneficial, but the optimal methods were model-specific. All nine water quality variables were useful for most models, but UVA₂₅₄ and turbidity were most important.

An ultrasensitive fluorimetric sensor for pre-screening of water microbial contamination risk

In recent years, global efforts have been directed towards the development of water safety routines, consequently demanding cost-effective sensors capable of detecting outbreaks at early stages. This work reports the development and study of an original in-field tryptophan fluorimetric sensor as a potential indicator of real-time microbial contamination in water. The sensor excitation and emission wavelengths were selected with respect to the coliform bacteria tryptophan peak; 280 nm for excitation and 330 nm for emission. The in-lab tests with standard samples show a detection limit of 4.89 nM (≈0.1 μg/l) for L-tryptophan. The sensor exhibited good linearity over three orders of magnitude and considerable detection reproducibility, which was confirmed during calibration tests. Small-scale in situ tests showed that the sensor was better correlated with coliform bacteria than other online sensors such as turbidity. This suggests that the fluorimetric tryptophan sensor can be integrated into early warning systems that quickly assess changes in water microbial quality.

Automated Targeted Sampling of Waterborne Pathogens and Microbial Source Tracking Markers Using Near-Real Time Monitoring of Microbiological Water Quality

Waterborne pathogens are heterogeneously distributed across various spatiotemporal scales in water resources, and representative sampling is therefore crucial for accurate risk assessment. Since regulatory monitoring of microbiological water quality is usually conducted at fixed time intervals, it can miss short-term fecal contamination episodes and underestimate underlying microbial risks. In the present paper, we developed a new automated sampling methodology based on near real-time measurement of a biochemical indicator of fecal pollution. Online monitoring of β-D-glucuronidase (GLUC) activity was used to trigger an automated sampler during fecal contamination events in a drinking water supply and at an urban beach. Significant increases in protozoan parasites, microbial source tracking markers and E. coli were measured during short-term (<24 h) fecal pollution episodes, emphasizing the intermittent nature of their occurrence in water. Synchronous triggering of the automated sampler with online GLUC activity measurements further revealed a tight association between the biochemical indicator and culturable E. coli. The proposed event sampling methodology is versatile and in addition to the two triggering modes validated here, others can be designed based on specific needs and local settings. In support to regulatory monitoring schemes, it should ultimately help gathering crucial data on waterborne pathogens more efficiently during episodic fecal pollution events.

Tryptophan-like fluorescence as a high-level screening tool for detecting microbial contamination in drinking water

Regular monitoring of drinking water quality is vital to identify contamination of potable water supplies. Testing for microbial contamination is important to prevent transmission of waterborne disease, but establishing and maintaining a water quality monitoring programme requires sustained labour, consumables and resources. In low resource settings such as developing countries, this can prove difficult, but measuring microbial contamination is listed as a requirement of reaching the UN's Sustainable Development Goal 6 for water and sanitation. A nine-month water quality monitoring programme was conducted in rural Malawi to assess the suitability of tryptophan-like fluorescence (TLF), an emerging method for rapidly detecting microbial contamination, as a drinking water quality monitoring tool. TLF data was compared with thermotolerant coliforms (TTCs, E. coli) and inorganic hydrochemical parameters. A large (n = 235) temporal dataset was collected from five groundwater drinking water sources, with samples collected once or twice weekly depending on the season. The results show that TLF can indicate a broader contamination risk but is not as sensitive to short term variability when compared to other faecal indicators. This is likely due to a broad association of TLF with elevated DOC concentrations from a range of different sources. Elevated TLF may indicate preferential conditions for the persistence of TTCs and/or E. coli, but not necessarily a public health risk from microbial contamination. TLF is therefore a more precautionary risk indicator than microbial culturing techniques and could prove useful as a high-level screening tool for initial risk assessment. For widespread use of TLF to be successful, standardisation of TLF values associated with different levels of risk is required, however, this study highlights the difficulties of equating TLF thresholds to TTCs or E. coli data because of the influence of DOC/HLF on the TLF signal.

Characteristics of the chromophoric dissolved organic matter of urban black-odor rivers using fluorescence and UV-visible spectroscopy

Urban black-odor water (BOW) is a typical phenomenon seen in the urban water environment; it is caused by excessive pollution by organic matter and other pollutants, such as nitrogen and phosphorous. Chromophoric dissolved organic matter (CDOM) is a major optical fraction of dissolved organic matter. In this study, optical properties and components of CDOM were obtained from 178 river samples collected from five cities in China, the sample were investigated using absorption and fluorescence spectroscopy. The collected included 89 ordinary water (OW) samples, 63 mild BOW (MBOW), and 26 heavy BOW (HBOW) samples. Significant differences were found in the absorption spectra of the HBOW, MBOW, and OW samples, particularly in their optical parameters (the slope of the spectrum (S_275-295), and the ratio of two absorption coefficients of CDOM (E₂:E₃)). Additionally, the fluorescence intensity of the humic acid-like component (F₅) and soluble microbial by product-like component (F₄) obtained via the fluorescence regional integration (FRI) method were 3 and 4.2 times higher in HBOW than in OW, respectively; this could be used as an indicator to distinguish OW from BOW in urban rivers. The results obtained using the redundancy method and the strong negative correlation between F₄ and dissolved oxygen (DO) (r = - 0.56) suggested that the composition of CDOM could change significantly under different urban water environments (p < 0.01). Different correlations were also found between F₅, and a355, E₂:E₃, S_275-295 in different BOW levels, suggesting that the optical parameters of CDOM were mainly determined by the polluted organic matter originating from terrestrial sources with large molecular humic acid-like compounds; optical parameter a355 could distinguish BOW from OW. These findings are conducive in understanding the dynamics of organic matter pollution and to discover the composition and optical properties of the CDOM in urban BOW and OW, thereby providing an effective method for tracking the spatial characteristics of BOW in urban rivers using remote sensing technologies in areas with multiple sources of pollution.

Field Tracer Tests to Evaluate Transport Properties of Tryptophan and Humic Acid in Karst

The monitoring of water quality, especially of karst springs, requires methods for rapidly estimating and quantifying parameters that indicate contamination. In the last few years, fluorescence-based measurements of tryptophan and humic acid have become a promising tool to assess water quality in near real-time. In this study, we conducted comparative tracer tests in a karst experimental site to investigate the transport properties and behavior of tryptophan and humic acid in a natural karst aquifer. These two tracers were compared with the conservative tracer uranine. Fluorescence measurements were conducted with an online field fluorometer and in the laboratory. The obtained breakthrough curves (BTCs) and the modeling results demonstrate that (1) the online field fluorometer is suitable for real-time fluorescence measurements of all three tracers; (2) the transport parameters obtained for uranine, tryptophan, and humic acid are comparable in the fast flow areas of the karst system; (3) the transport velocities of humic acid are slower and the resulting residence times are accordingly higher, compared to uranine and tryptophan, in the slower and longer flow paths; (4) the obtained BTCs reveal additional information about the investigated karst system. As a conclusion, the experiments show that the transport properties of tryptophan are similar to those of uranine while humic acid is partly transported slower and with retardation. These findings allow a better and quantitative interpretation of the results when these substances are used as natural fecal and contamination indicators.

Large-scale survey of seasonal drinking water quality in Malawi using in situ tryptophan-like fluorescence and conventional water quality indicators

Faecally-contaminated drinking water is a risk to human health, with the greatest risks to those living in developing countries. UN Sustainable Development Goal 6 aims to address this issue. Tryptophan-like fluorescence (TLF) shows potential as a rapid method for detecting microbial contamination in drinking water, which could reduce the spread of waterborne diseases. This study is the first to investigate the effectiveness of TLF for a large-scale survey using a randomised, spot-sampling approach. The large-scale survey took place in Malawi, sub-Saharan Africa, in the dry season (n = 183). A subset of sources were revisited at the end of the following wet season (n = 41). The effectiveness of TLF was assessed by comparing TLF results to thermotolerant coliforms (TTC), humic-like fluorescence (HLF), inorganic hydrochemical data and sanitary risk scores. The most prominent differences in microbial water quality were observed between source types, with little variation between districts and seasons. TLF, TTCs, turbidity and sanitary risk scores were all elevated at alternative sources (shallow wells and tap stands) compared to hand-pumped boreholes. In the dry season, 18% of hand-pumped boreholes showed TTC contamination, which increase to 21% in the wet season. Groundwater recharge processes are likely responsible for seasonal variability of inorganic hydrochemistry at hand-pumped boreholes. TLF was able to distinguish no and low WHO risk classes (TTC 0-9 cfu/100 mL) from medium, high and very high risk classes (TTC 10 - >1000 cfu/100 mL). TLF failed to distinguish between no and low risk classes, which limits the use of TLF for assessing water quality to drinking water standards. This dataset indicates that HLF may raise baseline TLF for samples with low TLF values, increasing false positives. Therefore, TLF is better suited as a rapid high-level water quality screening tool to assess moderate and high levels of faecal contamination.

In-situ fluorescence spectroscopy indicates total bacterial abundance and dissolved organic carbon

We explore in-situ fluorescence spectroscopy as an instantaneous indicator of total bacterial abundance and faecal contamination in drinking water. Eighty-four samples were collected outside of the recharge season from groundwater-derived water sources in Dakar, Senegal. Samples were analysed for tryptophan-like (TLF) and humic-like (HLF) fluorescence in-situ, total bacterial cells by flow cytometry, and potential indicators of faecal contamination such as thermotolerant coliforms (TTCs), nitrate, and in a subset of 22 samples, dissolved organic carbon (DOC). Significant single-predictor linear regression models demonstrated that total bacterial cells were the most effective predictor of TLF, followed by on-site sanitation density; TTCs were not a significant predictor. An optimum multiple-predictor model of TLF incorporated total bacterial cells, nitrate, nitrite, on-site sanitation density, and sulphate (r² 0.68). HLF was similarly related to the same parameters as TLF, with total bacterial cells being the best correlated (ρ_s 0.64). In the subset of 22 sources, DOC clustered with TLF, HLF, and total bacterial cells, and a linear regression model demonstrated HLF was the best predictor of DOC (r² 0.84). The intergranular nature of the aquifer, timing of the study, and/or non-uniqueness of the signal to TTCs can explain the significant associations between TLF/HLF and indicators of faecal contamination such as on-site sanitation density and nutrients but not TTCs. The bacterial population that relates to TLF/HLF is likely to be a subsurface community that develops in-situ based on the availability of organic matter originating from faecal sources. In-situ fluorescence spectroscopy instantly indicates a drinking water source is impacted by faecal contamination but it remains unclear how that relates specifically to microbial risk in this setting.

Tryptophan-like and humic-like fluorophores are extracellular in groundwater: implications as real-time faecal indicators

Fluorescent natural organic matter at tryptophan-like (TLF) and humic-like fluorescence (HLF) peaks is associated with the presence and enumeration of faecal indicator bacteria in groundwater. We hypothesise, however, that it is predominantly extracellular material that fluoresces at these wavelengths, not bacterial cells. We quantified total (unfiltered) and extracellular (filtered at < 0.22 µm) TLF and HLF in 140 groundwater sources across a range of urban population densities in Kenya, Malawi, Senegal, and Uganda. Where changes in fluorescence occurred following filtration they were correlated with potential controlling variables. A significant reduction in TLF following filtration (ΔTLF) was observed across the entire dataset, although the majority of the signal remained and thus considered extracellular (median 96.9%). ΔTLF was only significant in more urbanised study areas where TLF was greatest. Beneath Dakar, Senegal, ΔTLF was significantly correlated to total bacterial cells (ρs 0.51). No significant change in HLF following filtration across all data indicates these fluorophores are extracellular. Our results suggest that TLF and HLF are more mobile than faecal indicator bacteria and larger pathogens in groundwater, as the predominantly extracellular fluorophores are less prone to straining. Consequently, TLF/HLF are more precautionary indicators of microbial risks than faecal indicator bacteria in groundwater-derived drinking water.

Monitoring Approaches for Faecal Indicator Bacteria in Water: Visioning a Remote Real-Time Sensor for E. coli and Enterococci

A comprehensive review was conducted to assess the current state of monitoring approaches for primary faecal indicator bacteria (FIB) E. coli and enterococci. Approaches were identified and examined in relation to their accuracy, ability to provide continuous data and instantaneous detection results, cost, environmental awareness regarding necessary reagent release or other pollution sources, in situ monitoring capability, and portability. Findings showed that several methods are precise and sophisticated but cannot be performed in real-time or remotely. This is mainly due to their laboratory testing requirements, such as lengthy sample preparations, the requirement for expensive reagents, and fluorescent tags. This study determined that portable fluorescence sensing, combined with advanced modelling methods to compensate readings for environmental interferences and false positives, can lay the foundations for a hybrid FIB sensing approach, allowing remote field deployment of a fleet of networked FIB sensors that can collect high-frequency data in near real-time. Such sensors will support proactive responses to sudden harmful faecal contamination events. A method is proposed to enable the development of the visioned FIB monitoring tool.

Fluorescence-based monitoring of anthropogenic pollutant inputs to an urban stream in Southern California, USA

Fluorescence spectroscopy has been increasingly used to detect sewage and other anthropogenic contaminants in surface waters. Despite progress in successfully detecting bacterial and sewage inputs to rivers over diverse spatial scales, the use of fluorescence-based in-situ sensors to track contaminant inputs during storm events and to discern bacterial contamination from background natural organic matter (NOM) fluorescence have received less attention. A portable, submersible fluorometer equipped with tryptophan (TRP)-like and humic-like fluorescence sensors was used to track inputs of untreated wastewater added to natural creek water in a laboratory sewage spill simulation. Significant, positive correlations were observed between TRP fluorescence, the TRP:humic ratio, percent wastewater, and Escherichia coli concentrations, indicating that both the TRP sensor and the TRP:humic ratio tracked wastewater inputs against the background creek water DOM fluorescence. The portable fluorometer was subsequently deployed in an urban creek during a storm in 2018. The peak in TRP fluorescence was found to increase with the rising limb of the hydrograph and followed similar temporal dynamics to that of caffeine and fecal indicator bacteria, which are chemical and biological markers of potential fecal pollution. Results from this study demonstrate that tracking of TRP fluorescence intensity and TRP:humic ratios, with turbidity correction of sensor outputs, may be an appropriate warning tool for rapid monitoring of sewage or other bacterial inputs to aquatic environments.

Demonstration of Tryptophan-Like Fluorescence Sensor Concepts for Fecal Exposure Detection in Drinking Water in Remote and Resource Constrained Settings

Low-cost, field-deployable, near-time methods for assessing water quality are not available when and where waterborne infection risks are greatest. We describe the development and testing of a novel device for the measurement of tryptophan-like fluorescence (TLF), making use of recent advances in deep-ultraviolet light emitting diodes (UV-LEDs) and sensitive semiconductor photodiodes and photomultipliers. TLF is an emerging indicator of water quality that is associated with members of the coliform group of bacteria and therefore potential fecal contamination. Following the demonstration of close correlation between TLF and E. coli in model waters and proof of principle with sensitivity of 4 CFU/mL for E. coli, we further developed a two-LED flow-through configuration capable of detecting TLF levels corresponding to “high risk” fecal contamination levels (>10 CFU/100 mL). Findings to date suggest that this device represents a scalable solution for remote monitoring of drinking water supplies to identify high-risk drinking water in near-time. Such information can be immediately actionable to reduce risks.

PARAFAC model as an innovative tool for monitoring natural organic matter removal in water treatment plants

The increase of fluorescent natural organic matter (fNOM) fractions during drinking water treatment might lead to an increased coagulant dose and filter clogging, and can be a precursor for disinfection by-products. Consequently, efficient fNOM removal is essential, for which characterisation of fNOM fractions is crucial. This study aims to develop a robust monitoring tool for assessing fNOM fractions across water treatment processes. To achieve this, water samples were collected from six South African water treatment plants (WTPs) during winter and summer, and two plants in Belgium during spring. The removal of fNOM was monitored by assessing fluorescence excitation-emission matrices datasets using parallel factor analysis. The removal of fNOM during summer for South African WTPs was in the range 69-85%, and decreased to 42-64% in winter. In Belgian WTPs, fNOM removal was in the range 74-78%. Principal component analysis revealed a positive correlation between total fluorescence and total organic carbon (TOC). However, TOC had an insignificant contribution to the factors affecting fNOM removal. Overall, the study demonstrated the appearance of fNOM in the final chlorinated water, indicating that fNOM requires a customised monitoring technique.

Quantification of bacteria in water using PLS analysis of emission spectra of fluorescence and excitation-emission matrices

Bacterial contamination of drinking water is a considerable concern for public health. Tryptophan-like fluorescence (TLF) has been widely suggested to enable fast and inexpensive monitoring and quantification of bacterial contamination of water. Typically, TLF is determined at a certain excitation (ex)/emission (em) wavelengths pair. The aim of this study was to assess fluorescence spectroscopy supported with partial least squares (PLS) algorithms as a tool for a rapid evaluation of the microbial quality of water, by comparing the use of a single ex/em wavelengths pair, of the spectrum of emission obtained at a single excitation wavelength to that of whole excitation-emission matrices (EEMs). For that, laboratory-grown Escherichia coli, Bacillus subtilis and Pseudomonas aeruginosa were studied as the model systems, as well as 90 groundwater samples from 6 different wells in Israel. The groundwater samples were characterized for fluorescence emission, coliforms, fecal coliforms, fecal streptococci and heterotrophic plate counts. The PLS analysis of emission spectra and, especially, of EEMs was capable of meaningfully reducing the detection limit of microorganisms in model systems, as compared with the single ex/em wavelengths pair-based determination commonly used, reaching a detection threshold as low as 10 CFU/ml. Use of PLS-analyzed EEMs becomes beneficial also in terms of correlation and similarity between the actual and predicted bacterial concentrations. Similarly, improved detection of bacteria was also achieved in groundwater samples. Furthermore, at a level of >10⁴ CFU/ml, use of EEMs coupled with PLS enabled discrimination between E. coli, B. subtilis and P. aeruginosa.

Optimal fluorescent-dye staining time for the real-time detection of microbes: a study of Saccharomyces cerevisiae

AIMS

To provide information on the time-dependent behaviour of microbe staining by fluorescent dyes in the order of seconds, which is important in terms of the recent rapid and online techniques for microbe measurements and/or environmental microbe analysis.

METHODS AND RESULTS

For combinations of yeast (Saccharomyces cerevisiae) and typical dyes, including DAPI (4',6-diamidino-2-phenylindole) and Auramine-O, a suspension of yeast cells in ultrapure water was injected into a dye solution in a micro cuvette placed inside a spectrofluorometer and the fluorescence intensity of the resulting solution was measured at 1 s intervals, starting immediately after the mixing and continued until the time for the maximum intensity using various concentrations of yeast and dyes. The relaxation time τ, which corresponds to ~63·2% of the maximum fluorescence intensity, was shown to decrease to below 1 s with increasing DAPI concentration, whereas it remained constant for 2-3 s with increasing Auramine-O concentration, for example at a yeast concentration of 100 µg ml^-1 .

CONCLUSIONS

For the conditions of yeast >10 µg ml^-1 , DAPI >1 µg ml^-1 and Auramine-O >0·1 µg ml^-1 , τ could be adjusted to below 5 s to achieve a rapid and stable staining.

SIGNIFICANCE AND IMPACT OF THE STUDY

Design and operating conditions for rapid and online measurements of microbes can be optimized.

In situ fluorescence measurements of dissolved organic matter: A review

There is a need for an inexpensive, reliable and fast monitoring tool to detect contaminants in a short time, for quick mitigation of pollution sources and site remediation, and for characterization of natural dissolved organic matter (DOM). Fluorescence spectroscopy has proven to be an excellent technique in quantifying aquatic DOM, from autochthonous, allochthonous or anthropogenic sources. This paper reviews the advances in in situ fluorescence measurements of DOM and pollutants in various water environments. Studies have demonstrated, using high temporal-frequency DOM fluorescence data, that marine autochthonous production of DOM is highly complex and that the allochthonous input of DOM from freshwater to marine water can be predicted. Furthermore, river measurement studies found a delayed fluorescence response of DOM following precipitation compared to turbidity and discharge, with various lags, depending on season, site and input of dissolved organic carbon (DOC) concentration. In addition, research has shown that blue light fluorescence (λ_emission = 430-500 nm) can be a good proxy for DOC, in environments with terrestrial inputs, and ultraviolet fluorescence (λ_emission = UVA-320-400 nm) for biochemical oxygen demand, and also E. coli in environments with sanitation issues. The correction of raw fluorescence data improves the relationship between fluorescence intensity and these parameters. This review also presents the specific steps and parameters that must be considered before and during in situ fluorescence measurement session for a harmonized qualitative and quantitative protocol. Finally, the strengths and weaknesses of the research on in situ fluorescence are identified.

Monitoring, sampling, and automated analysis

A review of the literature published in 2018 on topics related to monitoring, sampling, and automated analysis is presented. The review includes current developments in monitoring, sampling, and analysis of water, wastewater, and groundwater. This review includes the following sections: brief introduction; sample preparation and extraction techniques; real-time, high-frequency, and/or in situ monitoring (microbiological, inorganic, organic, metals, and others); passive monitoring; and the biosensors. In the end, the authors have discussed future of the topic. PRACTITIONER POINTS: Advances in monitoring, sampling and automated analysis of water and wastewater are summarized. Real-time, high-frequency, and in-situ monitoring and analysis of pollutants are summarized. Topics include sample preparation and extraction and passive monitoring, and biosensors for pollutants.

Applications of Photonics in Agriculture Sector: A Review

The agricultural industry has made a tremendous contribution to the foundations of civilization. Basic essentials such as food, beverages, clothes and domestic materials are enriched by the agricultural industry. However, the traditional method in agriculture cultivation is labor-intensive and inadequate to meet the accelerating nature of human demands. This scenario raises the need to explore state-of-the-art crop cultivation and harvesting technologies. In this regard, optics and photonics technologies have proven to be effective solutions. This paper aims to present a comprehensive review of three photonic techniques, namely imaging, spectroscopy and spectral imaging, in a comparative manner for agriculture applications. Essentially, the spectral imaging technique is a robust solution which combines the benefits of both imaging and spectroscopy but faces the risk of underutilization. This review also comprehends the practicality of all three techniques by presenting existing examples in agricultural applications. Furthermore, the potential of these techniques is reviewed and critiqued by looking into agricultural activities involving palm oil, rubber, and agro-food crops. All the possible issues and challenges in implementing the photonic techniques in agriculture are given prominence with a few selective recommendations. The highlighted insights in this review will hopefully lead to an increased effort in the development of photonics applications for the future agricultural industry.

Real-time detection of potable-reclaimed water pipe cross-connection events by conventional water quality sensors using machine learning methods

Risk of cross-connection is becoming higher due to greater construction of potable-reclaimed water dual distribution systems. Cross-connection events can result in serious health concerns and reduce public confidence in reclaimed water. Thus, reliable, cost-effective and real-time online detection methods for early warning are required. The current study carried out pilot-scale experiments to simulate potable-reclaimed water pipe cross-connection events for different mixing ratios (from 30% to 1%) using machine learning methods based on multiple conventional water quality parameters. The parameters included residual chlorine, pH, turbidity, temperature, conductivity, oxidation-reduction potential and chemical oxygen demand. The results showed that correlated variation occurred among water quality parameters at the time of the cross-connection event. A single parameter-based method can be effective at high mixing ratios, but not at low mixing ratios. The direct supporting vector machine (SVM)-based method managed to overcome this drawback, but coped poorly with abnormal readings of water parameter sensors. In that respect, a Pearson correlation coefficient (PCC)-SVM-based method was developed. It provided not only high detection performance under normal conditions, but also remained reliable when abnormal readings occurred. The detection accuracy and true positive rate of this method was still over 88%, and the false positive rate was below 12%, given a sudden variation of an individual water quality parameter. The receiver operating characteristic curves further confirmed the promising practical applicability of this PCC-SVM-based method for early detection of cross-connection events.

Effects of hairy crab breeding on drinking water quality in a shallow lake

The Yangcheng Lake, connected to Taihu, is partly served as drinking water source for Suzhou, China; the temporal and spatial changes of water quality parameters of it are investigated in this study. The Yangcheng Middle Lake with aquaculture area and the Yangcheng East Lake with important water intake are chosen to make a comparative investigation of the relationship between crab breeding and water quality. Phytoplankton community and the composition of dissolved organic matters (DOM) at different areas of the Yangcheng Lake are characterized with spectral fluorescence signatures. Results reveal that biopolymers and humic substances (HS) are the two major DOM compositions in the Yangcheng Lake. In the Yangcheng Middle Lake, the COD_Mn concentration at the large breeding area was lower than that in most other areas; while the concentration of algae and HS fluorescence intensity are positively correlated with each other in the Yangcheng Middle Lake. Crab breeding could accelerate nitrogen transformation and utilization. In summer and winter, the cumulative risk of building up potential harmful by-products such as DPBs caused by the biopolymers and HS is greater; the breeding of hairy crabs could reduce biopolymers and improve drinking water safety.

Tryptophan-like fluorescence as a measure of microbial contamination risk in groundwater

Microbial water quality is frequently assessed with a risk indicator approach that relies on Escherichia coli. Relying exclusively on E. coli is limiting, particularly in low-resource settings, and we argue that risk assessments could be improved by a complementary parameter, tryptophan-like fluorescence (TLF). Over two campaigns (June 2016 and March 2017) we sampled 37 water points in rural Kwale County, Kenya for TLF, E. coli and thermotolerant coliforms (total n = 1082). Using three World Health Organization defined classes (very high, high, and low/intermediate), risk indicated by TLF was not significantly different from risk indicated by E. coli (p = 0.85). However, the TLF and E. coli risk classifications did show disagreement, with TLF indicating higher risk for 14% of samples and lower risk for 13% of samples. Comparisons of duplicate/replicate results demonstrated that precision is higher for TLF (average relative percent difference of duplicates = 14%) compared to culture-based methods (average RPD of duplicates ≥ 26%). Additionally, TLF sampling is more practical because it requires less time and resources. Precision and practicality make TLF well-suited to high-frequency sampling in low resource contexts. Interpretation and interference challenges are minimised when TLF is measured in groundwaters, which typically have low dissolved organic carbon, relatively consistent temperature, negligible turbidity and pH between 5 and 8. TLF cannot be used as a proxy for E. coli on an individual sample basis, but it can add value to groundwater risk assessments by improving prioritization of sampling and by increasing understanding of spatiotemporal variability.

Microbial Processing and Production of Aquatic Fluorescent Organic Matter in a Model Freshwater System

Organic matter (OM) has an essential biogeochemical influence along the hydrological continuum and within aquatic ecosystems. Organic matter derived via microbial processes was investigated within a range of model freshwater samples over a 10-day period. For this, excitation-emission matrix (EEM) fluorescence spectroscopy in combination with parallel factor (PARAFAC) analysis was employed. This research shows the origin and processing of both protein-like and humic-like fluorescence within environmental and synthetic samples over the sampling period. The microbial origin of Peak T fluorescence is demonstrated within both synthetic samples and in environmental samples. Using a range of incubation temperatures provides evidence for the microbial metabolic origin of Peak T fluorescence. From temporally resolved experiments, evidence is provided that Peak T fluorescence is an indication of metabolic activity at the microbial community level and not a proxy for bacterial enumeration. This data also reveals that humic-like fluorescence can be microbially derived in situ and is not solely of terrestrial origin, likely to result from the upregulation of cellular processes prior to cell multiplication. This work provides evidence that freshwater microbes can engineer fluorescent OM, demonstrating that microbial communities not only process, but also transform, fluorescent organic matter.

Influence of dissolved organic matter (DOM) characteristics on dissolved mercury (Hg) species composition in sediment porewater of lakes from southwest China

The origin and composition of dissolved organic matter (DOM) in porewater of lake sediments is intricate and decisive for fate of pollutants including mercury (Hg). While there are many reports on the relationship between dissolved organic carbon concentration (DOC) and mercury (Hg) concentrations in aquatic systems, there are few in which DOM compositional properties, that may better explain the fate of Hg, have been the focus. In this study, porewaters from sediments of three lakes, Caihai Lake (CH), Hongfeng Lake (HF) and Wujiangdu Lake (WJD), all located in southwest China, were selected to test the hypothesis that DOM optical properties control the fate of Hg in aquatic ecosystems. Porewater DOM was extracted and characterized by UV-Vis absorption and fluorescence spectroscopy. A two end-member (autochthonous and allochthonous DOM) mixing model was used to unveil the origin of DOM in porewaters of the three lakes. Our results show a higher input of terrestrial DOM in the pristine lake CH, as compared to lakes HF and WJD lakes, which were both influenced by urban environments and enriched in autochthonous DOM. While the relationships between the concentrations of DOC and the different chemical forms of Hg forms were quite inconsistent, we found important links between specific DOM components and the fate of Hg in the three lakes. In particular, our results suggest that allochthonous, terrestrial DOM inhibits Hg(II) availability for Hg methylating micro-organisms. In contrast, autochthonous DOM seems to have been stimulated MeHg formation, likely by enhancing the activity of microbial communities. Indeed, DOM biodegradation experiments revealed that differences in the microbial activity could explain the variation in the concentration of MeHg. While relationships between concentrations of DOC and Hg vary among different sites and provide little information about Hg cycling, we conclude that the transport and transformation of Hg (e.g. the methylation process) are more strongly linked to DOM chemical composition and reactivity.