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Review

Microbial Contamination Detection in Water Resources: Interest of Current Optical Methods, Trends and Needs in the Context of Climate Change

by
Aude-Valérie Jung
1,2,3,4,*,
Pierre Le Cann
2,3,4,
Benoit Roig
2,3,4,5,
Olivier Thomas
2,3,4,
Estelle Baurès
2,3,4 and
Marie-Florence Thomas
1,4
1
School of Environmental Engineering (EME), Campus de Ker Lann, Avenue Robert Schuman, Bruz 35170, France
2
EHESP Rennes, Sorbonne Paris Cité, Avenue du Professeur Léon Bernard-CS 74312, Rennes Cedex 35043, France
3
INSERM, UMR IRSET Institut de Recherche sur la Santé l'Environnement et le Travail - 1085, LERES, Rennes 35043, France
4
European University of Brittany (UEB), 5 Boulevard Laënnec, Rennes 35000, France
5
Deparment of Sciences, Nîmes University, Rue du docteur George Salan, Nîmes 30000, France
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2014, 11(4), 4292-4310; https://doi.org/10.3390/ijerph110404292
Submission received: 21 November 2013 / Revised: 10 April 2014 / Accepted: 11 April 2014 / Published: 17 April 2014

Abstract

:
Microbial pollution in aquatic environments is one of the crucial issues with regard to the sanitary state of water bodies used for drinking water supply, recreational activities and harvesting seafood due to a potential contamination by pathogenic bacteria, protozoa or viruses. To address this risk, microbial contamination monitoring is usually assessed by turbidity measurements performed at drinking water plants. Some recent studies have shown significant correlations of microbial contamination with the risk of endemic gastroenteresis. However the relevance of turbidimetry may be limited since the presence of colloids in water creates interferences with the nephelometric response. Thus there is a need for a more relevant, simple and fast indicator for microbial contamination detection in water, especially in the perspective of climate change with the increase of heavy rainfall events. This review focuses on the one hand on sources, fate and behavior of microorganisms in water and factors influencing pathogens’ presence, transportation and mobilization, and on the second hand, on the existing optical methods used for monitoring microbiological risks. Finally, this paper proposes new ways of research.

Graphical Abstract

1. Introduction

In the context of international regulations, the contamination of water bodies by organic micropollutants is the subject of constant interest and is always under investigation. Although at the origin of numerous outbreaks of gastrointestinal diseases and public health concerns, microbial contamination is rarely considered [1], even if some studies have shown consistent and significant association between heavy rainfall events and waterborne disease outbreaks [2,3] and climate change consequences [4]. A lack of studies concerning waterborne diseases correlated with extreme events (such as droughts and floods) has recently been mentioned by a review of reviews [5]. Despite a regulatory framework, microbial quality is often a source of impairment of the compliance of drinking water supply [6], in particular for small scale water systems (SSWS) [7,8] and private water supplies [9,10,11]. Additionally, water quality is known to be affected by increased microbial pollution under extreme weather conditions (climate change) and requires more systematic studies [12,13]. Monitoring objectives consist in directly targeting the sources of contamination, by using simple and rapid indicators but are mainly focused on parameters such as faecal bacteria (E. coli or Enterococci). Enteric viruses, that play a major role in waterborne diseases, are rarely investigated due to the detection limits of commonly applied methods [14,15]. Consequently, even when complying with microbiological water quality standards, the endemic part of waterborne acute gastroenteritis (AGE) may vary from 0 to 40% [16,17] excluding the smallest supply water systems (<500 inhabitants) for which the syndromic surveillance is ineffective.
For many years, analytical approaches have been developed for knowledge improvement concerning microorganisms’ nature and origins. More recently, different studies have shown the importance of an ecological (sediment and aquatic plants role) approach [18,19,20,21,22,23]. Although PCR is often used in microbial source tracking, it has not found widespread application in microbial monitoring programs due to its targeted approach for specific microbial genera or species [24,25]. MST tools proposed for the identification of the origin of faecal pollution are well documented in the literature [21,26,27,28,29,30]. Except for these methods and the conventional bacterial culture (standardized), some alternative ones are available, such as methods based on the exploitation of the optical properties of water. The interest in optical methods for microbial detection may be justified by the optical effects (mainly absorption and light diffusion) of microorganisms often adsorbed on colloids or particles. The effect of interaction between light and matter can be exploited to detect bacteria or viruses either as free particles or attached to organo-mineral complexes capable of modifying the optical properties of surfaces.
This review focuses on: (1) sources, fate, behavior of microorganisms in water and factors influencing pathogens’ presence, transport and mobilization, and (2), on optical methods for microbial contamination monitoring.

2. Sources, Fate and Behavior of Microorganisms in Water

The microbial contamination of water is often of faecal nature related to humans (water sewage treatment plants, combined sewage overflow (CSO), non-collective sewage systems), domesticated animals (manure spreading, pit stock overflow), or wildlife. The main origins of microbial contamination of natural aquatic resources are discharges of water treatment plants, decontamination stations, hospitals, industries considered as point sources, etc. Correlation between pathogens concentrations and urban activities is well documented (e.g., [31,32]). On the other hand, diffuse sources (slurry, manure, sludge application…) may also be considered. The abundance and importance of pathogens in water depend on factors such as the contamination level, pathogens’ persistence in water bodies, biological reservoirs (including aquatic plants and sediments) and the ability of pathogens to be transported [33]. The land use management practices and the size of the watershed also influence the survival of microorganisms [34,35,36]. According to George et al. [37], streams flowing through areas partly or fully covered with pastures are more contaminated than those running through forests and cultivated areas.

2.1. Fate in Sediments and in Submerged Aquatic Vegetation

Sediments and submerged aquatic vegetation (SAV) are important reservoirs of microorganisms [18,30,38]. For example, Badgley et al. [18] have shown that SAV harbored significantly higher mean densities of Enterococci than sediments, which themselves harbored higher densities than water. The high Enterococci densities observed in SAV are mainly due to increase nutrient availability as well as protection from UV radiation. Sediments can contain 10-times more viruses than water [33]. The microorganisms survival in different sediment types with different particle size and organic carbon content have been studied by Garzio-Hadzick et al. [39]. Their results revealed that sediments with small particle size and high organic carbon content could extended pathogens’ survival. Chandran et al. [40] concluded that sediments could act as a reservoir of pathogenic bacteria and exhibit a potential health hazards from possible resuspension and subsequent ingestion during recreational activities. The role of granulometric distribution of particles for microorganisms’ survival is also important for their transport during high flow events.
The behavior of microorganisms is also influenced by hydrometeorological changes such as heavy rainfalls which are likely to increase with climate change [12]. Thus, microorganisms associated with sediments or SAV, are put back into suspension and could lead to water contamination [18,33]. Re-suspension of sediments during or shortly after rainfall events was studied by Cho et al. [41] in order to investigate E. coli behavior regarding different bottom sediment textures of three streams for artificial high-flow events. A bacteria transport model was proposed, but additional research was needed to understand which and how sediment properties affect the parameters of streambed E. coli released into the water column.

2.2. Transport and Fate of Microorganisms

The associations between microorganisms and sediments influence their survival but also their transport characteristics [42]. Moreover the fate and transport of faecal bacteria are highly related to the governing sediment transport processes [38]. The transport of viruses linked to particles is particularly influenced by attachment to mineral surfaces and inactivation [43]. This adsorption can be reversible under other environmental conditions such as pH variations [44]. The microbial partitioning between the freely suspended and particulate attached phases during transport along overland flow pathways was studied by Soupir and Mostaghimi [45]. Rainfall simulations conducted on large-scale field plots showed that the majority of E. coli and Enterococci are transported from the fresh manure source in an unattached state, with only 4.8% of E. coli and 13% of Enterococci associated with particles. The average percent of attached E. coli or Enterococci is less than 3% with sparsely vegetated cover. In a laboratory-scale model system developed to investigate the transport mechanisms of E. coli in overland flow across saturated soils, E. coli appeared to be attached predominantly to small particles (<2 μm) and hence remained unattenuated during transport [45]. Moreover, microorganisms could be considered in hydric resources as biological particles transported by advection [33]. For example, Bekhit et al. [46] were interested in the role of colloids on the mobility of microorganisms and micropollutants in groundwater. They proposed a conceptual model to take into account the different physiochemical and biological processes, reaction kinetics, and transport mechanisms of the combined system (contaminant–colloids–bacteria). Different results have been obtained for natural aquatic media such as lakes and reservoirs. In particular, a review of Brookes et al. [47] explained the factors controlling pathogens transport and distribution, the respective role of dispersion, dilution and horizontal and vertical transport in such media. Contrary to lab-scale models, settling of pathogens particles operates with more complex hydrodynamic processes. Their results showed that all of the tested microbial indicators (Escherichia coli, Enterococci, Clostridium perfringens, aerobic spores, somatic coliphages, Cryptosporidium spp. and Giardia spp.) were associated with larger sized particle (>63.3 μm), except C. perfringens spores which were associated with particles size in the range of 45.5−63.3 μm. This granulometric distribution of the associated particles has important effects on the retention of microorganisms by settling and transfer into sediments [48,49]. Abudalo et al. [50] and Searcy et al. [51] precised that the environmental impact of protozoan parasites is closely related to their extended survival in contrasting climatic conditions and disinfection processes, and to their ability to interact with other organic or nonorganic particles [52]. The latter phenomenon governs their transport, retention (by settling) and/or release, and survival in the transition from land to sea.
In addition to Auer and Niehaus [53], Ferguson et al. [54], Sinton et al. [55] and Noble et al. [56] suggest that fecal indicator bacteria (FIB) inactivation rates (also referred to as a “die-off” or “decay” rate) vary under different environmental conditions, including solar radiation and water temperature. The FIB inactivation rate variability in response to other factors, such as water column depth, is not as well-understood, and has been recommended as an area for future research [57].

2.3. Influence of Hydrometeorological Conditions

Microorganisms’ transportation is particularly influenced by hydrometeorological conditions. Indeed microbial contamination of surface water increases during heavy rainfalls with water combined sewage overflows (CSOs) or agricultural land run-offs [33,58]. Rainfall increases the suspended matter content of small streams as well as their fecal contamination, with fecal coliforms mainly adsorbed on particles [37]. Rainfall events can also increase human enteric virus load in natural waters impacted by CSOs and stormwater leading to higher risk of gastroenteritis in recreational activities or shellfish consumption [59]. This risk has been evaluated using quantitative microbial risk assessment showing the dominance of norovirus in swimming-associated gastroenteritis [60]. Heavy rainfalls may also led to catchment area flooding with a strong increase of water turbidity, this last being considered as a non-questionable indicator of potential contamination by aquatic pathogens [61,62]. Several prospective epidemiological studies in France have also shown that groundwater influenced by surface water could be the cause of gastrointestinal infections in an endemic level [61,63], especially during rainfall events in karstic environment.
Figure 1. Schematic synthesis of source and fate of allochtonous microorganisms in water.
Figure 1. Schematic synthesis of source and fate of allochtonous microorganisms in water.
Ijerph 11 04292 g001
Water temperature variation plays also a role in the hydrodynamic distribution of microorganisms. In temperate areas, lakes are generally stratified during summer (with warmer water at the surface). Destratification occurs with heavy rains or storms, modifying the convection movements of particles containing microorganisms, moving them to the surface [64,65,66]. In a recent work, Wyer et al. [66] studied the variation of fecal indicators in four streams during a moderate rainfall. They demonstrated, thanks to microbial source tracking (MST), that the transfer time varies from minutes to hours, according to the hydrological conditions and sites characteristics. Table 1 presents some relevant studies dealing with pathogen interactions with particulate and colloidal phases in the aquatic compartment. Finally, Figure 1 proposes a schematic synthesis of source and fate of allochtonous microorganisms in water. From the resource to usages, the human pressure increases with production of drinking water and public use of recreational waters. From sedimentation to resuspension, the biological reservoirs are submitted to physicochemical and biological reactions on the one hand, and to hydrochemical and hydrological factors in water bodies on the other hand. Moreover, the external runoffs from anthropogenic and natural sources are considered as punctual and diffuse contribution, depending on climate change.
Table 1. Pathogens interactions studies with particulate and colloidal phases in the aquatic compartment.
Table 1. Pathogens interactions studies with particulate and colloidal phases in the aquatic compartment.
Type of pathogensMatrixWater BodyReferencesComments
BacteriaParticlesKarstic aquifer[67]Connections with the surface responsible for turbid and bacterial contaminations
Bacteria groupsColloidsGroundwater[46]Modelisation of transport mechanisms of the combined system (contaminant&#x2013;colloids&#x2013;bacteria)
Lakes[47]Correlation between size particles and transport and distribution after a storm
Recreational waters[66]Connection between microbial tracers and fecal indicator organisms
E. coli, EnterococciParticlesRun-off[68]Rainfall simulations for erodible soil particles and sparsely vegetable soils
[45]run-off
E. coliSedimentsRivers[41]Modelisation of bacteria transport during rainfall events
Virus
Norovirus
ColloidsRivers[69]Direct spillage of wastewater in river during heavy rains
MixtureColloidsDistributed water[3]Correlation of heavy rains with gastroenteritis epidemics
Particles River, karstic water[17]Correlation of turbidity, flow rate and gastroenteritis epidemics
Others
Giardia cyst
Protozoan parasites groups
ColloidsRivers[70]Correlation with rainy events
ParticlesWaterbeds soils[52]Interaction between parasites and particles (organic and inorganic)
As a consequence, the demand for faster and reliable monitoring methods and approaches is also increasing, with for example rapid molecular methods, although these methods do not allow a real-time control, contrary to optical methods [24].

3. Optical Monitoring of Microbial Contamination: Current Methods, Trends and Needs

3.1. Current Trends: Turbidity, Particle Size Distribution (PSD) and Cytometry

The main simple and practical way to assess the microbiological risk of water contamination is turbidimetry, largely used in water treatment plants. Despite its lack of sensitivity (there is no direct relation between pathogens density in water and turbidity), the choice of this parameter is relevant because: (i) the suspended particles are a safe and supportive environment for pathogens and a place of protection against disinfectants; (ii) turbidity lowers the efficiency of disinfection processes by the presence of oxidisable associated organic matter; (iii) turbidity in the water network creates particle deposition and promotes the growth of biofilms with the potential presence of pathogens (Legionella, Pseudomonas, Aeromonas, Mycobacterium, etc.) [17,71]. For 10 years, the interest in using turbidity for the continuous monitoring of effluents quality has been widely demonstrated [72,73,74]. In a constant environment, the respect for strict procedures gives precise and reliable turbidity data, in the laboratory as well as in situ [75], with a high frequency acquisition (minute order). Moreover, if this parameter is known as a good indicator of suspended matters in sewage networks [76,77,78], the turbidity measurement of fresh waters is influenced by the particle size and shape of SS, the presence of plankton and the presence of dissolved humic substances. Some authors have tried to establish correlations between turbidity and parameters like water level, flow rate, or rain intensity [73,74] without success, excepted in the case of a dilution phenomenon following a short dry period before raining [79]. Pronk et al. [80] have studied the dynamics of organic carbon (OC), turbidity, faecal indicator bacteria and physicochemical parameters in a karst system near Yverdon, Switzerland. OC appears to be a better indicator for bacterial contamination than turbidity. Page et al. [81] have tried to correlate continuous physico-chemical measurements (temperature, electrical conductivity, turbidity, spectral absorption coefficient (SAC), and particle density) with the amount of faecal indicator bacteria, such as Escherichia coli and Enterococcus sp., discontinuously sampled in the aquatic media. No individual proxy indicator for bacterial contamination was found. However, the following of the river water infiltration could be assessed by electrical conductivity, temperature and SAC measurements.
Turbidity measurements are also often used for drinking water quality monitoring and within water treatment plants considering experimental approximate relations with the number of germs [82]. It is regulated by the Directive 98/83/CE for the distributed waters but not for resources, contrary to microbiological parameters considered in both cases. Even if turbidity measurements are often used as a run-off pollution indicator of resource water, the precise interpretation of this parameter as a sanitary threat indicator, remains difficult because of its sensibility to environmental factors as described before. Beaudeau et al. [17] have recently shown a significant and biologically plausible risk was highlighted on rivers. Turbidity of treated water may be considered as an exposure indicator which produces the more reproducible risks [71].
The physico-chemical characterization methods of particles (shape, size, surface properties) were recently considered in particular because of the sensitivity of turbidity to these parameters. Among them, Goldscheider et al. [83] used a portable field particles counter in order to explain the turbidity measurements by following the temporal evolution of particle size distribution (PSD) between 0.9 and 139 µm diameter. For karstic resources, turbidity measurements fail to accurately estimate microbiological contamination because of the variability of the hydroclimatic conditions and the presence of more or less large particles, remobilized by the first flush, followed by a very fine particle mix (about 1 µm), sometimes with the presence of pathogens coming from contaminated waters, confirming the results of Atteia and Kozel [84]. A very good correlation between turbidity and E. coli (R2 = 0.93) has been demonstrated for colloidal particles (0.9–1.5 µm).
Cytometry techniques are also based on optical principles and are now routinely used in microbiology, particularly for microbial ecology studies, unfortunately not on site. Flow cytometry can detect microorganisms at the cellular level from their optical properties (fluorescence and light scattering), to quantify and provide information on the individual characteristics of cells and information on the heterogeneity of cellular states in a population. It applies to the study of autotrophic and heterotrophic microorganisms the fluorescence properties of which are natural (pigments) or induced by probes targeting taxonomic targets and/or physiological. Particles analyzed in the environmental field are diverse and range from viruses to protozoa. The analysis time is less than 1 h and the number of cells analyzed is very high (around 107 colony forming unit/mL). In some cases it is possible to physically separate the cell functions of some of their optical properties in order to complete their analysis by other techniques (biochemical and molecular biology techniques) [85,86].

3.2. Trends in Optical Methods

3.2.1. Fluorescence Measurements

Although fluorescence measurements are well known for organics analysis (e.g., hydrocarbons), this method could also be considered for its interest in microbial sources tracking. The origin and contamination type of dissolved organic matter (DOM) has been characterized by fluorescence [87,88,89]. For example, in river water samples, both protein-like (tyrosine- and tryptophan-like) and fulvic-like and humic-like fluorescence were detected and the relative intensity of these signals was used as an indicator of slurry occurrence in drainage waters in agricultural area [89]. Jaffrezic et al. [90] propose the geochemical fluorescence index (GFI), to point out the difference between farm waste and human waste. GFI is the ratio between two regions of the fluorescence spectrum divided into biochemical and geochemical regions. Lefcourt et al. [91] have developed a field-portable fluorescence imagining system for detecting fecal contaminants for agricultural products.
Exploitation of the bacteriophage (or phage) life cycle and its accompanying species specificity can reduce much of the time and cost associated to classical methods such as gene sequencing, electrophoresis or repetitive sequence-based polymerase chain reaction (PCR). The well-characterized bacterial luciferase genes, encoded by the lux operon from the aquatic Gram-negative Vibrio fischeri are perhaps the most frequently used reporters for incorporation into recombinant phages and have many applications, namely for acute toxicity prediction for chemicals [92]. Other-component bacteriophage-based bioluminescent reporter systems were developed for the detection of Escherichia coli in environmental samples, for instance [93].

3.2.2. Biosensors

Biosensors combining the selectivity of biology with the processing power of microelectronics may also be considered through bio-recognition systems, generally enzymes or binding proteins such as immobilized antibodies. Biosensors have the potential for substantial improvements over standard methods and have been reported employing the full spectrum of biorecognition molecules and transduction methods for detection of waterborne pathogens, with oligonucleotide probes and antibodies being the most common [94]. These biosensors have been used in various fields such as environment or food processing for biorecognition of specific molecules, since they have a high sensitive detection capacity. However, several problems for waterborne pathogens detection may appear with regard to low concentration and many interfering enzymatic reactions in natural media [94]. In the literature, many examples for the detection of E. coli can be found, and among these studies, the transduction based methods, with fluorescence and chemiluminescence probes are the most used [94]. (Bio)sensing systems have benefited from the achievements of scientific and technological research from nanomaterials and nanotechnologies science [95]. Especially, nanoparticles, gold nanoparticles, graphene, quantum dots, have led to major advances in this field [96]. Various mass-sensitive techniques have also been applied for bacteria [94]. For these techniques, the limits of detection are around 100 cells/mL. Others techniques using nanocrystal biosensors are used for drinking water market, since they seem to be reliable and are in-situ techniques for monitoring multiple pathogens mixtures. Alternatively, many studies concerning protozoan biosensing detection can be related since the detection schemes applied to parasites and viruses too [94].

3.2.3. Spectrophotometric Methods

Spectrophotometric methods are potentially interesting for the detection of microbial contamination because of their use in particle characterization. As shown in the review and synthesis of Bowers and Binding [97], spectrophotometric methods are used for quantitative assessment of particle concentration in sea water, in order to study the effect on sunlight penetration into the sea. Astoreca et al. [98] have correlated the basic properties of the particles (concentration, composition, and size of suspended particles in sea water) with their light absorption properties in the visible and near-infrared regions. Stramski et al. [99] have proposed a database of the single-particle optical properties of marine microbial particles to better understand the ocean optics. This database (based on the optical properties depending on the particle size) includes representatives from five classes of particles: viruses, heterotrophic bacteria, cyanobacteria, small nanoplanktonic diatoms, and nanoplanktonic chlorophytes. More recently, Stadler et al. [100] have obtained good correlation between SAC254 (spectral absorption coefficient at 254 nm) and E. coli in karst water resources and propose that SAC254 may also be used as a real-time proxy to estimate the magnitude of faecal pollution during rainfall events. They precise that only diffuse faecal pollution sources with adequate soil contact are supposed to be quantifiable by the described approach.
Enlarging this approach, UV/Visible spectroscopy has lots of advantages to study the interactions between natural matrices and pollutants in dissolved and colloidal compartments [101]. The first advantage of this technique is to be rapid, direct and low cost. Several studies have proven the usefulness of such a technique in water quality monitoring, especially thanks to the complementarities with basic analysis such as dissolved biodegradable organic carbon [102], total organic carbon [103], by developing spectral exploitation techniques such as deconvolution or multi-wavelength treatment [104,105]. Owing to its good sensitivity, this technique could be useful to provide semi-quantitative information on the interactions between phases (organic carbon exchange) by direct monitoring, a non-specific pre-analysis preparation and at natural media concentrations.
Table 2. Characterization of particles by UV (water and wastewater).
Table 2. Characterization of particles by UV (water and wastewater).
ReferencesOptical domainsMeasurement/studyParticle size (µm)Suspended matter concentration (mg/L)
[98]Visible and near-infrared spectral regionsRelationships between the concentration, composition and size of suspended particles2.72–4600–90
[106]UV spectrophotometry and laser granulometryCharacterization of heterogeneous suspensions0.4–2 × 103100–670
[107]Coupling UV-spectrophotometry and laser granulometryHeterogeneous suspensions, quantitative approach (size and concentration)0.05–10310–350
[108]UV spectrophotometryStudy of the impact of mechanical treatments on wastewater solids by UV spectrophotometry10−3–10310–220
[109]UV spectrophotometry and laser granulometryStudy of UV–vis responses of mineral suspensions in water1–10010–250
The technique could also give information about compounds’ size by coupling UV/Visible spectroscopy to laser granulometry analysis [106,107,108,109]. Behro et al. [109] proposed a typology of UV responses of particles according to their size and a model spectrum of mineral colloids in order to obtain a better understanding of physical absorption phenomena. They showed that the UV responses of non-absorbing particles can be modeled even if the physical phenomena are complex and the refraction index and the shape of particles have not been taken into account.
Table 2 synthesizes some results obtained by spectrophotometry for the characterization of particles in heterogeneous suspensions including water and wastewater. Table 3 presents the main literature studies presented in Section 3.2.2 of the manuscript.

4. Conclusions

This review has shown that knowledge about pathogen transport mechanisms are partial, even if the role of particles and colloids is relatively well documented. Moreover there is a lack of methods (index, sensor) allowing onsite identification of microbial contaminants and dynamic exchanges of pathogens into different phases such as soluble, colloidal, and particulate. Concerning the first point, the improvement of the optical responses currently provided by turbidimetry could be an interesting solution to identify hazardous situations of water microbial contamination. Indeed, the pertinence of the turbidity measurement is limited, since nephelometric measurements are dependent on the presence of colloids that may interfere with the results.
Table 3. Synthesis of classical and trends in optical methods for pathogens detection.
Table 3. Synthesis of classical and trends in optical methods for pathogens detection.
Parameter/ReferencesKind of media/applications fields/pathogensInfluencing parameters for the studies/interferencesParticle size/Number of celldetected
Turbidity/[7]–[72,73,74,75,76,77,78,79,80]Natural and wastewatersPlankton, Humic substances10–103 µm
PSD/[3,84]Karstic watersHydroclimatical0.9–1.5 µm
Cytometry/[85,86]All fluorescent speciesOthers fluorescent species (e.g., humic-like substances) + light scatteringFrom virus to bacteria/107 colony forming unit/mL
Fluorescence, Bacteriophage life cycle/[87,88,89,90,91,92,93]River waters (tyrosine, tryptophan and fulvic-like substances, E. Coli, Vibrio fischeriLight-scattering, inner filters effects, bioluminescence interferencesFrom molecule to bacteria
Biosensors/[94,95,96]Environment, food process, militaryInterfering enzyme reactionsVirus to protozoan> 100 cells/mL
Spectrophotometry Methods/[97,98,99,100,101,102,103,104,105,106,107,108,109]Virus, bacteria, cyanobacteria, nanoplanktonic and chlorophytes diatomsLight scattering10−3–2 × 103 µm
* to have a correlation between the size and the measurement value.
Among the ways of improvement encountered, the relevance of UV-Visible spectra exploitation to obtain significant information about the chemical and granulometric composition of the particulate phase is underlined. Thus, the development of a simple physico-chemical proxy (UV visible exploitation) associated to other optical methods (particle size distribution, turbidimetry, fluorimetry…) should be a research path to obtain an indicator for hazardous situations.
For the second point, the development of a characterization procedure (static and dynamic) allowing the study of the exchanges between particles and the microbial agents, namely during heavy rainfall events (aggregates, resuspension…) is needed. The exchanges being related to the size, the concentration, and particles charges and nature, all these parameters should be considered. Moreover, different operational conditions (e.g., pH, conductivity, organic carbon concentration) must be also assessed to improve the knowledge of the matrix effect (environmental hazardous situations). As shown by the review, there is a real lack of temporal studies integrating the seasonal and hydrological parameters associated to heavy rainfall events with regard to health risk assessment.
All these research needs must be considered at fair value because of, in addition to the population health impact, the importance of cost management of waterborne diseases such as acute gastroenteritis is undeniable. The cost reduction, by a better anticipation of the sanitary degradation of natural water resources quality, is therefore an important economical issue. For the scientific point of view, the main question will be to complete the main exposure indicator (the turbidity measurement) with additional more specific parameters, especially hydrological conditions. This needs a multidisciplinary approach between hydrologists, chemists, microbiologists, water treatment managers and epidemiologists.
The outcomes of these studies could give arguments to water treatment managers to modify or adapt the water treatment processes, or a different way to manage their plants by taking into account an alert procedure proposed for hazardous situations, based on new indicators of microbial contamination.

Acknowledgments

The authors would like to thank IJERP Editors and the reviewers for their helpful comments.

Author Contributions

Aude-Valérie Jung had the original idea for the manuscript and, with all co-authors, carried out the design. Aude-Valérie Jung and Marie-Florence Thomas drafted the manuscript, which was revised by all authors. Pierre Le Cann and Benoit Roig verified especially the state of the art of the microbiological knowledges. Olivier Thomas conceived the study idea, critically revised the manuscript and corrected the English. All authors read and approved the final manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Hlavsa, M.C.; Roberts, V.A.; Anderson, A.R.; Hill, V.R.; Kahler, A.M.; Orr, M.; Garrison, L.E.; Hicks, L.A.; Newton, A.; Hilborn, E.D.; et al. Surveillance for waterborne disease outbreaks and other health events associated with drinking water—United States, 2007–2008. MMWR Surveill. Summ. 2011, 60, 1–32. [Google Scholar]
  2. Auld, H.; MacIver, D.; Klaassen, J. Heavy rainfall and waterborne disease outbreaks: The Walkerton example. J. Toxicol. Environ. Health. A 2004, 67, 1879–1887. [Google Scholar]
  3. Curriero, F.C.; Patz, J.A.; Rose, J.B.; Lele, S. The association between extreme precipitation and waterborne disease outbreaks in the United States, 1948–1994. Am. J. Public Health 2001, 91, 1194–1199. [Google Scholar] [CrossRef]
  4. Hunter, P.R. Climate change and waterborne and vector-borne disease. J. Appl. Microbiol. 2003, 94, 37S–46S. [Google Scholar] [CrossRef]
  5. Bouzid, M.; Hooper, L.; Hunter, P.R. The effectiveness of public health interventions to reduce the health impact of climate change: A systematic review of systematic reviews. PLoS One 2013, 8. [Google Scholar] [CrossRef] [Green Version]
  6. Blackburn, B.G.; Craun, G.F.; Yoder, J.S.; Hill, V.; Calderon, R.L.; Chen, N.; Lee, S.H.; Levy, D.A.; Beach, M.J. Surveillance for waterborne-disease outbreaks associated with drinking water—United States, 2001–2002. MMWR 2004, 53, 23–45. [Google Scholar]
  7. Pitkänen, T.; Karinen, P.; Miettinen, I.T.; Lettojärvi, H.; Heikkilä, A.; Maunula, R.; Aula, V.; Kuronen, H.; Vepsäläinen, A.; Nousiainen, L.-L.; et al. Microbial contamination of groundwater at small community water supplies in Finland. Ambio 2010, 40, 377–390. [Google Scholar]
  8. Risebro, H.L.; Breton, L.; Aird, H.; Hooper, A.; Hunter, P.R. Contaminated small drinking water supplies and risk of infectious intestinal disease: A prospective cohort study. PLoS One 2012, 7. [Google Scholar] [CrossRef]
  9. Rutter, M.; Nichols, G.L.; Swan, A.; De Louvois, J. A survey of the microbiological quality of private water supplies in England. Epidemiol. Infect. 2000, 124, 417–425. [Google Scholar] [CrossRef]
  10. Said, B.; Wright, F.; Nichols, G.L.; Reacher, M.; Rutter, M. Outbreaks of infectious disease associated with private drinking water supplies in England and Wales 1970–2000. Epidemiol. Infect. 2003, 130, 469–479. [Google Scholar]
  11. Kay, D.; Watkins, J.; Francis, C.A.; Wyn-Jones, A.P.; Stapleton, C.M.; Fewtrell, L.; Wyer, M.D.; Drury, D. The microbiological quality of seven large commercial private water supplies in the United Kingdom. J. Water Health 2007, 5, 523–538. [Google Scholar] [CrossRef]
  12. Bartram, J.; Corrales, L.; Davison, A.; Deere, D.; Drury, D.; Gordon, B.; Rinehold, A.; Stevens, M. Water Safety Plan Manual: Step-by-Step Risk Management for Drinking-Water Suppliers; World Health Organization: Geneva, Switzerland, 2009. [Google Scholar]
  13. Bates, B.C.; Kundzewicz, Z.W.; Wu, S.; Palutikof, J.P. Climate Change and Water. Technical Paper of the Intergovernmental Panel on Climate Change. IPCC Secretariat: Geneva, Switzerland, 2008; pp. 1–210. [Google Scholar]
  14. Hundesa, A.; Maluquer de Motes, C.; Bofill-Mas, S.; Binana-Gimenez, N.; Girones, R. Identification of human and animal adenoviruses and polyomaviruses for determination of sources of fecal contamination in the environment. Appl. Environ. Microbiol. 2006, 72, 7886–7893. [Google Scholar] [CrossRef]
  15. Poma, H.R.; Gutiérrez Cacciabue, D.; Garcé, B.; Gonzo, E.E.; Rajal, V.B. Towards a rational strategy for monitoring of microbiological quality of ambient waters. Sci. Total Environ. 2012, 433, 98–109. [Google Scholar] [CrossRef]
  16. Beaudeau, P.; Valdes, D.; Damien, M.; Stemfelet, M.; Seux, R. Natural and technical factors in faecal contamination incidents of drinking water in small distribution networks, France, 2003–2004: A geographical study. J. Water Health 2010, 8, 20–33. [Google Scholar] [CrossRef]
  17. Beaudeau, P.; Rambaud, L.; Galey, C.; le Tertre, A.; Zeghoun, A. Risque D’infections Sporadiques Lié à L’ingestion D’eau Du Robinet: L’émergence D’une Approche Epidémiologique. In Proceeding of Second National Congress Société Française Santé Environnement (SFSE), Paris, France, 14–15 December 2011.
  18. Badgley, B.D.; Nayak, B.S.; Harwood, V.J. The importance of sediment and submerged aquatic vegetation as potential habitats for persistent strains of Enterococci in a subtropical watershed. Water Res. 2010, 44, 5857–5866. [Google Scholar] [CrossRef]
  19. Meays, C.L.; Broersma, K.; Nordin, R.; Mazumder, A. Source tracking fecal bacteria in water: A critical review of current methods. J. Environ. Manag. 2004, 73, 71–79. [Google Scholar] [CrossRef]
  20. Blanch, A.R.; Belanche-Munoz, L.; Bonjoch, X.; Ebdon, J.; Gantzer, C.; Lucena, F. Tracking the origin of faecal pollution in surface water: An ongoing project within the European Union Research Programme. J. Water Health 2004, 2, 249–260. [Google Scholar]
  21. Field, K.G.; Samadpour, M. Fecal source tracking, the indicator paradigm, and managing water quality. Water Res. 2007, 41, 3517–3538. [Google Scholar] [CrossRef]
  22. Gourmelon, M.; Caprais, M.P.; Mieszkin, S.; Marti, R.; Wéry, N.; Jardé, E.; Derrien, M.; Jadas-Hécart, A.; Communal, P.Y.; Jaffrezic, A.; et al. Development of microbial and chemical MST tools to identify the origin of the faecal pollution in bathing and shellfish harvesting waters in France. Water Res. 2010, 44, 4812–4824. [Google Scholar] [CrossRef] [Green Version]
  23. Furtula, V.; Osachoff, H.; Derksen, G.; Juahir, H.; Colodey, A.; Chambers, P. Inorganic nitrogen, sterols and bacterial source tracking as tools to characterize water quality and possible contamination sources in surface water. Water Res. 2012, 46, 1079–1092. [Google Scholar] [CrossRef]
  24. Mesquita, S.; Noble, R.T. Recent Developments in Monitoring of Microbiological Indicators of Water Quality across a Range of Water Types. In Water Resources Planning, Development and Management; Wurbs, R., Ed.; Texas A&M University: College Station, TX, USA, 2013; Chapter 2. [Google Scholar]
  25. Plummer, J.D.; Long, S.C. Monitoring source water for microbial contamination: Evaluation of water quality measures. Water Res. 2007, 41, 3716–3728. [Google Scholar] [CrossRef]
  26. Edge, T.A.; Hill, S.; Seto, P.; Marasalek, J. Library-dependent and library-independent microbial source tracking to identify spatial variation in faecal contamination sources along a lake Ontario beach (Ontario, Canada). Water Sci. Technol. 2010, 62, 719–727. [Google Scholar] [CrossRef]
  27. Kortbaoui, R.; Locas, A.; Imbeau, M.; Payment, P.; Villemur, R. Universal mitochondrial PCR combined with species-specific dot-blot assay as a source-tracking method of human, bovine, chicken, ovine, and porcine in fecal-contaminated surface water. Water Res. 2009, 43, 2002–2010. [Google Scholar] [CrossRef]
  28. Lyautey, E.; Lu, Z.; Lapen, D.R.; Berkers, T.E.; Edge, T.A.; Topp, E. Optimization and validation of rep-PCR genotypic libraries for microbial source tracking of environmental Escherichia coli isolates. Can. J. Microbiol. 2010, 56, 651–659. [Google Scholar] [CrossRef]
  29. Lee, D.Y.; Weir, S.C.; Lee, H.; Trevors, J.T. Quantitative identification of fecal water pollution sources by TaqMan real-time PCR assays using Bacteriodales 16S rRNA genetic markers. Appl. Microbiol. Biotechnol. 2010, 88, 1373–1383. [Google Scholar] [CrossRef]
  30. Staley, C.; Reckhow, K.H; Lukasik, J.; Harwood, V.J. Assessment of sources of human pathogens and fecal contamination in a Florida freshwater lake. Water Res. 2012, 46, 5799–5812. [Google Scholar] [CrossRef]
  31. Marsalek, J.; Rochfort, Q.J. Urban wet-weather flows: Sources of fecal contamination impacting on recreational waters and threatening drinking-water sources. J. Toxicol. Environ. Health A. 2004, 6, 1765–1777. [Google Scholar] [CrossRef]
  32. Selvakumar, A.; Borst, M.J. Variation of microorganism concentrations in urban stormwater runoff with land use and seasons. J. Water Health 2006, 4, 109–124. [Google Scholar]
  33. Dechesne, M.; Soyeux, E.; Loret, J.F.; Westrell, T.; Stenström, T.A.; Gornik, V.; Koch, C.; Exner, M.; Stanger, M.; Agutter, P.; et al. Pathogens in Source Water, Microbiological Risk Assessment: A Scientific Basis for Managing Drinking Water Safety from Source to Tap; Microrisk European Project: Nieuwegein, The Netherlands, 2006; pp. 1–42. [Google Scholar]
  34. Ferguson, C.M.; Charles, K.; Deere, D.D. Quantification of microbial sources in drinking-water catchments. Crit. Rev. Environ. Sci. Technol. 2008, 39, 1–40. [Google Scholar] [CrossRef]
  35. Harmel, R.D.; Karthikeyan Gentry, R.; Srinivasan, T.R. Effects of agricultural management, land use and watershed scale on E.coli concentrations in runoff and stream flow. Trans. ASABE 2010, 53, 1833–1841. [Google Scholar] [CrossRef]
  36. James, E.; Joyce, M. Assessment and management of watershed microbial contaminants. Crit. Rev. Environ. Sci. Technol. 2004, 34, 109–139. [Google Scholar] [CrossRef]
  37. George, I.; Anzil, A.; Servais, P. Quantification of fecal coliform inputs to aquatic systems through soil leaching. Water Res. 2004, 38, 611–618. [Google Scholar] [CrossRef]
  38. Gao, G.; Falconer, R.A.; Lin, B. Numerical modelling of sediment bacteria interaction processes in surface waters. Water Res. 2011, 45, 1951–1960. [Google Scholar] [CrossRef]
  39. Garzio-Hadzick, A.; Shelton, D.R.; Hill, R.L.; Pachepsky, Y.A.; Guber, A.K.; Rowland, R. Survival of manure-borne E. coli in streambed sediment: Effects of temperature and sediment properties. Water Res. 2010, 44, 2753–2762. [Google Scholar] [CrossRef]
  40. Chandran, A.; Varghese, S.; Kandeler, E.; Thomas, A.; Hatha, M.; Mazumder, A. An assessment of potential public health risk associated with the extended survival of indicator and pathogenic bacteria in freshwater lake sediments. Int. J. Hyg. Environ. Health 2011, 214, 258–264. [Google Scholar] [CrossRef]
  41. Cho, K.H.; Pachepsky, Y.A.; Kim, J.H.; Guber, A.K.; Shelton, D.R.; Rowland, R. Release of Escherichia coli from the bottom sediment in a first-order creek: Experiment and reach-specific modeling. J. Hydrol. 2010, 391, 322–332. [Google Scholar] [CrossRef]
  42. Jamieson, R.; Joy, D.M.; Lee, H.; Kostaschuk, R.; Gordon, R. Transport and deposition of sediment-associated Escherichia coli in natural streams. Water Res. 2005, 39, 2665–2675. [Google Scholar] [CrossRef]
  43. Muirhead, R.W.; Collins, R.P.; Bremer, P.J. Interaction of Escherichia coli and soil particles in runoff. Appl. Environ. Microbiol. 2006, 72, 3406–3411. [Google Scholar] [CrossRef]
  44. Loveland, J.P.; Ryan, J.N.; Amy, G.L.; Harvey, R.W. The reversibility of virus attachment to mineral surfaces. Colloids Surf. A 1996, 107, 205–221. [Google Scholar] [CrossRef]
  45. Soupir, M.L.; Mostaghimi, S. Escherichia coli and Enterococci attachment to particles in runoff from highly and sparsely vegetated grassland. Wat. Air Soil Poll. 2011, 216, 167–178. [Google Scholar] [CrossRef]
  46. Bekhit, H.M.; El-Hordy, M.A.; Hassan, A.E. Contaminant transport in groundwater in the presence of colloids and bacteria: Model development and verification. J. Contam. Hydrol. 2009, 108, 152–167. [Google Scholar] [CrossRef]
  47. Brookes, J.D.; Antenucci, J.; Hipsey, M.; Burch, M.D.; Ashbolt, N.J.; Fergusson, C. Fate and transport of pathogens in lakes and reservoirs. Environ. Int. 2004, 30, 741–759. [Google Scholar]
  48. Garcia-Armisen, T.; Servais, P. Partitioning and fate of particle-associated E. coli in river waters. Water Environ. Res. 2009, 81, 21–28. [Google Scholar]
  49. Gutierrez, L.; Nguyen, T.H. Interactions between rotavirus and Suwannee River organic matter: Aggregation, deposition, and adhesion force measurement. Environ. Sci. Technol. 2012, 21, 8705–8713. [Google Scholar] [CrossRef]
  50. Abudalo, R.A.; Ryan, J.N.; Harvey, R.W.; Metge, D.W.; Landkamer, L. Influence of organic matter on the transport of Cryptosporidium parvum oocysts in a ferric oxyhydroxide-coated quartz sand saturated porous medium. Water Res. 2010, 44, 1104–1113. [Google Scholar] [CrossRef]
  51. Searcy, K.E.; Packman, A.I.; Atwill, E.R.; Harter, T. Association of Cryptosporidium parvum with suspended particles: Impact on oocyst sedimentation. Appl. Environ. Microbiol. 2005, 71, 1072–1078. [Google Scholar] [CrossRef]
  52. Dumètre, A.; Aubert, D.; Puech, P.H.; Hohweyer, J.; Azas, N.; Villena, I. Interaction forces drive the environmental transmission of pathogenic protozoa. Appl. Environ. Microbiol. 2012, 78, 905–912. [Google Scholar] [CrossRef]
  53. Auer, M.T; Niehaus, S.L. Modeling fecal-coliform bacteria. 1. Field and laboratory determination of loss kinetics. Water Res. 1993, 27, 693–701. [Google Scholar] [CrossRef]
  54. Ferguson, C.; Husman, A.M.D.; Altavilla, N.; Deere, D.; Ashbolt, N. Fate and transport of surface water pathogens in watersheds. Crit. Rev. Environ. Sci. Technol. 2003, 33, 299–361. [Google Scholar] [CrossRef]
  55. Sinton, L.W.; Finlay, R.K.; Lynch, P.A. Sunlight inactivation of fecal bacteriophages and bacteria in sewage-polluted seawater. Appl. Environ. Microbiol. 1999, 65, 3605–3613. [Google Scholar]
  56. Noble, R.; Lee, I.; Schiff, K. Inactivation of indicator microorganisms from various sources of faecal contamination in seawater and freshwater. J. Appl. Microbiol. 2004, 96, 464–472. [Google Scholar] [CrossRef]
  57. Gronewold, A.D.; Myers, L.; Swall, J.L.; Noble, R.T. Addressing uncertainty in fecal indicator bacteria dark inactivation rates. Water Res. 2011, 45, 652–664. [Google Scholar] [CrossRef]
  58. Delpla, I.; Baures, E.; Jung, A.-V.; Thomas, O. Impacts of rainfall events on runoff water quality in an agricultural environment in temperate areas. Sci. Total Environ. 2011, 409, 1683–1688. [Google Scholar]
  59. Hata, A.; Katayama, H.; Kojima, K.; Sano, S.; Kasuga, I.; Kitajima, M.; Furumai, H. Effects of rainfall events on the occurrence and detection efficiency of viruses in river water impacted by combined sewer overflows. Sci. Total Environ. 2013, 468, 757–763. [Google Scholar]
  60. McBride, G.B.; Stott, R.; Miller, W.; Bambic, D.; Wuertz, S. Discharge-based QMRA for estimation of public health risks from exposure to stormwater-borne pathogens in recreational waters in the United States. Water Res. 2013, 47, 5282–5297. [Google Scholar] [CrossRef]
  61. Beaudeau, P. Impact Sanitaire D’un Accident Sur le Réseau D’adduction en eau Potable du Havre, D’une Panne De Désinfection à FECAMP et de 4 Episodes de Turbidité Dans Des Secteurs Ruraux (Seine-Maritime, 1998). Rapport de la Direction Départementale des Affaires Sanitaires et Sociales de Seine-Maritime et du Laboratoire D’études et D’analyses de la Ville du Havre; Report for the Social and Sanitary Departmental Direction (Seine-Maritime) and the studies and analyses Laboratory (Havre): Havre, MT, USA, 1999. [Google Scholar]
  62. Beaudeau, P.; de Valk, H.; Vaillant, V.; Mannschott, C.; Tillier, C.; Mouly, D.; Ledrans, M. Lessons learned from ten investigations of waterborne gastroenteritis outbreaks, France, 1998–2006. J. Water Health 2008, 6, 491–502. [Google Scholar] [CrossRef]
  63. Zmirou, D.; Ferley, J.P.; Collin, J.F.; Charrel, M.; Berlin, J. A follow-up study of gastro-intestinal diseases related to bacteriologically substandard drinking water. Am. J. Public Health 1987, 77, 582–584. [Google Scholar] [CrossRef]
  64. Brookes, J.D.; Hipsey, M.R.; Burch, M.D.; Regel, R.H.; Linden, L.G.; Ferguson, C.M.; Antenucci, J.P. Relative value of surrogate indicators for detecting pathogens in lakes and reservoirs. Environ. Sci. Technol. 2005, 39, 8614–8621. [Google Scholar] [CrossRef]
  65. Hipsey, M.R.; Antenucci, J.P.; Brookes, J.D.; Burch, M.D.; Regel, R.H.; Davies, C.M.; Ashbolt, N.J.; Ferguson, C. Hydrodynamic of Pathogens in Lakes and Reservoirs; American Water Works Research Foundation: Denver, CO, USA, 2005; Report 91073F. [Google Scholar]
  66. Wyer, M.D.; Kay, D.; Watkins, J.; Davies, C.; Kay, C.; Thomas, R.; Porter, J.; Stapleton, C.M.; Moore, H. Evaluating short-term changes in recreational water quality during a hydrograph event using a combination of microbial tracers, environmental microbiology, microbial source tracking and hydrological techniques: A case study in Southwest Wales, UK. Water Res. 2011, 44, 4783–4795. [Google Scholar]
  67. Gargala, G. Evaluation Des Risques Humains et Environnementaux Associés à La Présence de Cryptosporidium Dans L’environnement Hydrique de Haute-Normandie. In Proceeding of Second National Congress Société Française Santé Environnement (SFSE), Paris, France, 14–15 December 2011.
  68. Soupir, M.L.; Mostaghimi, S.; Dillaha, T. Attachment of Escherichia coli and Enterococci to particles in runoff. J. Environ. Qual. 2010, 39, 1019–1027. [Google Scholar] [CrossRef]
  69. Tillaut, H.; Encrenaz, N.; Checlair, E.; Alexandre-Bird, A.; Gomes Do Esperito Santo, E.; Beaudeau, P. Epidémie de gastro-entérite, Isère, novembre 2002. Bull. Environ. Hydrol. 2004, 12, 47–48. [Google Scholar]
  70. Delbec, M.; Chesnot, T.; Mignard, C.; Duchemin, J. Risques Microbiologiques Emergents Pour la Ressource en Eau, Cas de L’agglomération Parisienne. In Proceeding of Second National Congress Société Française Santé Environnement (SFSE), Paris, France, 14–15 December 2011.
  71. Beaudeau, P.; Pascal, M.; Mouly, D.; Galey, C.; Thomas, O. Health risks associated with drinking water in a context of climate change in France: A review of surveillance requirements. J. Water Clim. Change 2011, 2, 230–246. [Google Scholar] [CrossRef]
  72. Aumond, M.; Joannis, C. Turbidity Monitoring in Sewage. In Proceeding of 10th International Conference on Urban Drainage, Copenhague, Denmark, 21–26 August 2005.
  73. Henckens, G.; Veldkamp, R.; Schuit, T. On Monitoring of Turbidity in Sewers. Global Solutions for Urban Drainage. In Proceedings of the Ninth International Conference on Urban Drainage (9ICUD), Portland, OR, USA, 8–13 September 2002.
  74. Langeveld, J.G.; Veldkamp, R.G.; Clemens, F. Suspended solids transport: An analysis based on turbidity measurements and event based fully calibrated hydrodynamic models. Water Sci. Technol. 2005, 52, 93–101. [Google Scholar]
  75. Ruban, G.; Bertrand-Krajewski, J.L.; Chebbo, G.; Gromaire, M.C.; Joannis, C. Accuracy and reproducibility of turbidity measurements in urban waste water. Houille Blanche. Revue Internationale de l'Eau 2006, 4, 129–135. [Google Scholar]
  76. Chebbo, G.; Bachoc, A.; Laplace, D.; Leguennec, B. The transfer of solids in combined sewer networks. Water Sci. Technol. 1995, 31, 95–105. [Google Scholar]
  77. Deletic, A.B.; Maksimovic, C.T. Evaluation of water quality factors in storm runoff from paved areas. J. Environ. Eng. 1998, 124, 869–879. [Google Scholar] [CrossRef]
  78. Maréchal, A. Relations Entre Caractéristiques de la Pollution Particulaire et Paramètres Optiques Dans Les Eaux Résiduaires Urbaines. PhD Thesis, Institut national polytechnique de Lorraine, Nancy, France, 2000. [Google Scholar]
  79. Grüning, H.; Orth, H. Investigations of the dynamic behaviour of the composition of combined sewage using on-line analyzers. Water Sci. Technol. 2002, 45, 77–83. [Google Scholar]
  80. Pronk, M.; Goldscheider, N.; Zopfi, J. Dynamics and interaction of organic carbon, turbidity and bacteria in a Karst aquifer system. Hydrogeol. J. 2006, 14, 473–484. [Google Scholar] [CrossRef]
  81. Page, R.M.; Scheidler, S.; Polat, E.; Svoboda, P.; Huggenberger, P. Faecal indicator bacteria: Groundwater dynamics and transport following precipitation and river water infiltration. Water Air Soil Pollut. 2012, 223, 2771–2782. [Google Scholar] [CrossRef]
  82. Hannouche, A.; Chebbo, G.; Ruban, G.; Tassin, B.; Joannis, C. Relation entre la turbidité et les matières en suspension en réseau d’assainissement unitaire. Techniques Sciences et Méthodes 2011, 10, 42–50. [Google Scholar]
  83. Goldscheider, N.; Pronk, M.; Zopfi, J. New insights into the transport of sediments and microorganisms in Karst groundwater by continuous monitoring of particle-size distribution. Geol. Croat. 2010, 63, 137–142. [Google Scholar]
  84. Atteia, O.; Kozel, R. Particle size distributions in waters from a Karstic aquifer: From particles to colloids. J. Hydrol. 1997, 201, 102–119. [Google Scholar] [CrossRef]
  85. Ferrari, B.C.; Stoner, K.; Bergquist, P.L. Applying fluorescence based technology to the recovery and isolation of Cryptosporidium and Giardia from Industrial wastewater streams. Water Res. 2006, 40, 541–548. [Google Scholar] [CrossRef]
  86. King, D.N.; Brenner, K.P.; Rodgers, M.R. A critical evaluation of a flow cytometer used for detecting Enterococci in recreational waters. J. Water Health 2007, 5, 295–306. [Google Scholar]
  87. Parlanti, E.; Wörz, K.; Geoffroy, L.; Lamotte, M. Dissolved organic matter fluorescence spectroscopy as a tool to estimate biological activity in a coastal zone submitted to anthropogenic inputs. Org. Geochem. 2000, 31, 1765–1781. [Google Scholar] [CrossRef]
  88. Hudson, N.; Baker, A.; Reynolds, D. Fluorescence analysis of dissolved organic matter in natural, waste and polluted waters—A review. River Res. Appl. 2007, 23, 631–649. [Google Scholar] [CrossRef]
  89. Naden, P.S.; Old, G.H.; Eliot-Laize, C.; Granger, S.J.; Hawkins, J.M.B.; Bol, R.; Haygarth, P. Assessment of natural fluorescence as a tracer of diffuse agricultural pollution from slurry spreading in intensively-farmed grasslands. Water Res. 2010, 44, 1701–1712. [Google Scholar]
  90. Jaffrezic, A.; Jardé, E.; Pourcher, A.M.; Gourmelon, M.; Caprais, M.P.; Heddadj, D.; Cottinet, P.; Bilal, M.; Derrien, M.; Marti, R.; et al. Microbial and chemical markers: Runoff transfer in animal manure-amended soils. J. Environ. Qual. 2011, 40, 959–968. [Google Scholar] [CrossRef]
  91. Lefcourt, A.M.; Kim, M.S.; Chen, Y.-R. A transportable fluorescence imagining system for detecting fecal contaminants. Comput. Electron. Agr. 2005, 48, 63–74. [Google Scholar] [CrossRef]
  92. Shahid, P.; Venkataraman, C.; Mukherji, S. A review on advantages of implementing luminescence inhibition test (Vibrio fischeri) for acute toxicity prediction of chemicals. Environ. Int. 2006, 32, 265–268. [Google Scholar]
  93. Birmele, M.; Ripp, S.; Jegier, P.; Roberts, M.S.; Sayler, G; Garland, J.L. Characterization and validation of a bioluminescent bioreporter for the direct detection of Escherichia coli. J. Microbiol. Methods 2008, 75, 354–356. [Google Scholar] [CrossRef]
  94. Connelly, J.T.; Baeumner, A.J. Biosensors for the detection of waterborne pathogens. Anal. Bioanal. Chem. 2012, 402, 117–127. [Google Scholar] [CrossRef]
  95. Xu, X.; Ying, Y. Microbial biosensors for environmental monitoring and food analysis. Food Rev. Int. 2011, 27, 300–329. [Google Scholar] [CrossRef]
  96. Pérez-Lopez, B.; Merkoçi, A. Portable Chemical Sensors: Weapons against Bioterrorism. In Biosensors for Safety and Security Applications; Nikolelis, D.P., Ed.; Springer: Berlin, Germany, 2012; pp. 43–61. [Google Scholar]
  97. Bowers, D.G.; Binding, C.E. The optical properties of mineral suspended particles: A review and synthesis. Estuarine Coastal Shelf Sci. 2006, 67, 1–2. [Google Scholar] [CrossRef]
  98. Astoreca, R.; Doxaran, D.; Ruddick, K.; Rousseau, V.; Lancelot, C. Influence of suspended particle concentration, composition and size on the variability of inherent optical properties of the Southern North Sea. Continental Shelf Res. 2012, 35, 117–128. [Google Scholar] [CrossRef]
  99. Stramski, D.; Mobley, C.D. Effects of microbial particles on oceanic optics: A database of single-particle optical properties. Limnol. Oceanography 1997, 42, 538–549. [Google Scholar] [CrossRef]
  100. Stadler, H.; Klock, E.; Skritek, P.; Mach, R.L.; Zerobin, W.; Farnleitner, A.H. The spectral absorption coefficient at 254nm as a real-time early warning proxy for detecting faecal pollution events at alpine karst water resources. Wat. Sci. Technol. 2010, 62, 1898–1906. [Google Scholar] [CrossRef]
  101. Thomas, O.; Burgess, C. From Spectra to Qualitative and Quantitative Results. In UV-Visible Spectrophotometry of Water and Wastewater; Thomas, O., Burgess, C., Eds.; Elsevier: New York, NY, USA, 2007; pp. 1–360. [Google Scholar]
  102. Thomas, O.; Mazas, N.; Massiani, C. Determination of biodegradable dissolved organic carbon in waters with the use of UV absorptiometry. Environ. Technol. 1993, 14, 487–493. [Google Scholar] [CrossRef]
  103. Thomas, O.; El Khorassani, H.; Touraud, E.; Bitar, H. TOC vs. UV spectrophotometry for wastewater quality monitoring. Talanta 1999, 50, 743–749. [Google Scholar] [CrossRef]
  104. Thomas, O.; Gallot, S. UV multiwavelength absorptiometry (UVMA) for the examination of natural waters and wastewaters. Fresenius J. Anal. Chem. 1990, 338, 234–237. [Google Scholar] [CrossRef]
  105. Thomas, O.; Theraulaz, F.; Domeizel, M.; Massiani, C. UV spectral deconvolution: A valuable tool for wastewater quality determination. Environ. Technol. 1993, 14, 1187–1192. [Google Scholar] [CrossRef]
  106. Azema, N.; Pouet, M.-F.; Berho, C.; Thomas, O. Wastewater suspended solids study by optical methods. Colloids Surf. A 2002, 204, 131–140. [Google Scholar] [CrossRef]
  107. Bayle, S.; Azéma, N.; Berho, C.; Pouet, M.-F.; Lopez-Cuesta, J.-M.; Thomas, O. Study of heterogeneous suspensions: A new quantitative approach coupling laser granulometry and UV-visible spectrophotometry. Colloids Surf. A 2005, 262, 242–250. [Google Scholar] [CrossRef]
  108. Berho, C.; Pouet, M.-F.; Thomas, O. Study of the impact of mechanical treatments on waste water solids by UV spectrophotometry. Environ. Technol. 2003, 24, 1545–1551. [Google Scholar] [CrossRef]
  109. Berho, C.; Pouet, M.-F.; Bayle, S.; Azema, N.; Thomas, O. Study of UV-visible responses of mineral suspensions in water. Colloids Surf. A 2004, 248, 9–16. [Google Scholar] [CrossRef]

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Jung, A.-V.; Le Cann, P.; Roig, B.; Thomas, O.; Baurès, E.; Thomas, M.-F. Microbial Contamination Detection in Water Resources: Interest of Current Optical Methods, Trends and Needs in the Context of Climate Change. Int. J. Environ. Res. Public Health 2014, 11, 4292-4310. https://doi.org/10.3390/ijerph110404292

AMA Style

Jung A-V, Le Cann P, Roig B, Thomas O, Baurès E, Thomas M-F. Microbial Contamination Detection in Water Resources: Interest of Current Optical Methods, Trends and Needs in the Context of Climate Change. International Journal of Environmental Research and Public Health. 2014; 11(4):4292-4310. https://doi.org/10.3390/ijerph110404292

Chicago/Turabian Style

Jung, Aude-Valérie, Pierre Le Cann, Benoit Roig, Olivier Thomas, Estelle Baurès, and Marie-Florence Thomas. 2014. "Microbial Contamination Detection in Water Resources: Interest of Current Optical Methods, Trends and Needs in the Context of Climate Change" International Journal of Environmental Research and Public Health 11, no. 4: 4292-4310. https://doi.org/10.3390/ijerph110404292

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