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      Application of Chemometric Methods for Assessment and Modelling of Microbiological Quality Data Concerning Coastal Bathing Water in Greece

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          Abstract

          Background

          Worldwide, the aim of managing water is to safeguard human health whilst maintaining sustainable aquatic and associated terrestrial, ecosystems. Because human enteric viruses are the most likely pathogens responsible for waterborne diseases from recreational water use, but detection methods are complex and costly for routine monitoring, it is of great interest to determine the quality of coastal bathing water with a minimum cost and maximum safety.

          Design and methods

          This study handles the assessment and modelling of the microbiological quality data of 2149 seawater bathing areas in Greece over 10-year period (1997-2006) by chemometric methods.

          Results

          Cluster analysis results indicated that the studied bathing beaches are classified in accordance with the seasonality in three groups. Factor analysis was applied to investigate possible determining factors in the groups resulted from the cluster analysis, and also two new parameters were created in each group; VF1 includes E. coli, faecal coliforms and total coliforms and VF2 includes faecal streptococci/enterococci. By applying the cluster analysis in each seasonal group, three new groups of coasts were generated, group A (ultraclean), group B (clean) and group C (contaminated).

          Conclusions

          The above analysis is confirmed by the application of discriminant analysis, and proves that chemometric methods are useful tools for assessment and modeling microbiological quality data of coastal bathing water on a large scale, and thus could attribute to effective and economical monitoring of the quality of coastal bathing water in a country with a big number of bathing coasts, like Greece.

          Significance for public health

          The microbiological protection of coastal bathing water quality is of great interest for the public health authorities as well as for the economy. The present study proves that this protection can be achieved by monitoring only two microbiological parameters, E. coli and faecal streptococci/enterococci instead four microbiological parameters (the two mentioned above plus Total coliforms and Faecal coliforms) that are usually monitored today. As a consequence, countries, especially those with large quantities of coastal bathing sites, can perform microbiological monitoring of their bathing waters by checking only the mentioned two parameters, thus ensuring economies of scale. Thus, funds can be used in other actions to preserve the quality of coastal water and human health. This in turn, would aid in the assessment of the quality of coastal bathing waters and provide a more timely indication of bathing water quality, hence contributing to the immediate health protection of bathers.

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          Most cited references15

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          Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India)--a case study.

          This case study reports different multivariate statistical techniques applied for evaluation of temporal/spatial variations and interpretation of a large complex water-quality data set obtained during monitoring of Gomti River in Northern part of India. Water quality of the Gomti River, a major tributary of the Ganga River was monitored at eight different sites selected in relatively low, moderate and high pollution regions, regularly over a period of 5 years (1994-1998) for 24 parameters. The complex data matrix (17,790 observations) was treated with different multivariate techniques such as cluster analysis, factor analysis/principal component analysis (FA/PCA) and discriminant analysis (DA). Cluster analysis (CA) showed good results rendering three different groups of similarity between the sampling sites reflecting the different water-quality parameters of the river system. FA/PCA identified six factors, which are responsible for the data structure explaining 71% of the total variance of the data set and allowed to group the selected parameters according to common features as well as to evaluate the incidence of each group on the overall variation in water quality. However, significant data reduction was not achieved, as it needed 14 parameters to explain 71% of both the temporal and spatial changes in water quality. Discriminant analysis showed the best results for data reduction and pattern recognition during both temporal and spatial analysis. Discriminant analysis showed five parameters (pH, temperature, conductivity, total alkalinity and magnesium) affording more than 88% right assignations in temporal analysis, while nine parameters (pH, temperature, alkalinity, Ca-hardness, DO, BOD, chloride, sulfate and TKN) to afford 91% right assignations in spatial analysis of three different regions in the basin. Thus, DA allowed reduction in dimensionality of the large data set, delineating a few indicator parameters responsible for large variations in water quality. This study presents necessity and usefulness of multivariate statistical techniques for evaluation and interpretation of large complex data sets with a view to get better information about the water quality and design of monitoring network for effective management of water resources.
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            Assessment of the surface water quality in Northern Greece.

            The application of different multivariate statistical approaches for the interpretation of a large and complex data matrix obtained during a monitoring program of surface waters in Northern Greece is presented in this study. The dataset consists of analytical results from a 3-yr survey conducted in the major river systems (Aliakmon, Axios, Gallikos, Loudias and Strymon) as well as streams, tributaries and ditches. Twenty-seven parameters have been monitored on 25 key sampling sites on monthly basis (total of 22,350 observations). The dataset was treated using cluster analysis (CA), principal component analysis and multiple regression analysis on principal components. CA showed four different groups of similarity between the sampling sites reflecting the different physicochemical characteristics and pollution levels of the studied water systems. Six latent factors were identified as responsible for the data structure explaining 90% of the total variance of the dataset and are conditionally named organic, nutrient, physicochemical, weathering, soil-leaching and toxic-anthropogenic factors. A multivariate receptor model was also applied for source apportionment estimating the contribution of identified sources to the concentration of the physicochemical parameters. This study presents the necessity and usefulness of multivariate statistical assessment of large and complex databases in order to get better information about the quality of surface water, the design of sampling and analytical protocols and the effective pollution control/management of the surface waters.
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              Estimating the global burden of thalassogenic diseases: human infectious diseases caused by wastewater pollution of the marine environment.

              This paper presents a preliminary attempt at obtaining an order-of-magnitude estimate of the global burden of disease (GBD) of human infectious diseases associated with swimming/bathing in coastal waters polluted by wastewater, and eating raw or lightly steamed filter-feeding shellfish harvested from such waters. Such diseases will be termed thalassogenic--caused by the sea. Until recently these human health effects have been viewed primarily as local phenomena, not generally included in the world agenda of marine scientists dealing with global marine pollution problems. The massive global scale of the problem can be visualized when one considers that the wastewater and human body wastes of a significant portion of the world's population who reside along the coastline or in the vicinity of the sea are discharged daily, directly or indirectly, into the marine coastal waters, much of it with little or no treatment. Every cubic metre of raw domestic wastewater discharged into the sea can carry millions of infectious doses of pathogenic microorganisms. It is estimated that globally, foreign and local tourists together spend some 2 billion man-days annually at coastal recreational resorts and many are often exposed there to coastal waters polluted by wastewater. Annually some 800 million meals of potentially contaminated filter-feeding shellfish/bivalves and other sea foods, harvested in polluted waters are consumed, much of it raw or lightly steamed. A number of scientific studies have shown that swimmers swallow significant amounts of polluted seawater and can become ill with gastrointestinal and respiratory diseases from the pathogens they ingest. Based on risk assessments from the World Health Organization (WHO) and academic research sources the present study has made an estimate that globally, each year, there are in excess of 120 million cases of gastrointestinal disease and in excess of 50 million cases of more severe respiratory diseases caused by swimming and bathing in wastewater-polluted coastal waters. Filter-feeding shellfish/bivalves, which are often harvested from wastewater-polluted areas of the sea, can effectively filter out and concentrate the microbial pathogens in the seawater. It can be roughly estimated that annually there are some 4 million cases of infectious hepatitis A and E (HAV/HEV), with some 40 thousand deaths and 40 thousand cases of long-term disability, mainly chronic liver damage, from consuming raw or lightly steamed filter-feeding shellfish/molluscs harvested globally from polluted coastal waters. The total global health impact of the thalassogenic diseases--human infectious diseases associated with pathogenic microorganisms from land-based wastewater pollution of the seas--is estimated to be about 3 million 'disability-adjusted life years' (DALY)/year, with an estimated economic loss of some 12 billion dollars per year. Due to the preliminary nature of the estimates in this study it is appropriate to assume that all of the above figures are no more than first approximations and that the true figures may be 50% higher or lower. Nevertheless, it is the author's belief that this study indicates that wastewater pollution of the sea results in a multi-billion dollar per year health burden and that preventing wastewater pollution of the sea is worthy of inclusion on the global agenda of marine pollution prevention and control.
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                Author and article information

                Journal
                J Public Health Res
                J Public Health Res
                JPHR
                Journal of Public Health Research
                PAGEPress Publications, Pavia, Italy
                2279-9028
                2279-9036
                10 December 2014
                02 December 2014
                : 3
                : 3
                : 357
                Affiliations
                [1 ]Department of Medical Laboratories, Technological Education Institute of Thessaly , Greece
                [2 ]Department of Animal Production, Technological Education Institute of Thessaly , Greece
                [3 ]NHS Trust Microbiology Department, United Lincolnshire Hospitals, Lincoln County Hospital , United Kingdom
                [4 ]Department of Hygiene and Epidemiology, School of Medicine, University of Thessaly , Greece
                Author notes
                Clinical Chemistry Section, Department of Medical Laboratories, Education and Technological Institute of Thessaly, 41110 Larissa, Greece. +30.241.068.4448 - +30.241.068.4650. papaioannou@ 123456teilar.gr

                Contributions: the authors contributed equally.

                Conflict of interests: the authors declare no potential conflict of interests.

                Article
                10.4081/jphr.2014.357
                4274499
                a344c09b-eae8-4f90-b627-e14040a93e82
                ©Copyright A. Papaioannou et al.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 23 September 2014
                : 01 December 2014
                Page count
                Figures: 2, Tables: 3, Equations: 1, References: 38, Pages: 8
                Categories
                Original Article

                public health,chemometric methods,coastal bathing quality,bacterial indicators,mediterranean

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