Geochemical Study of Coastal Sediments Influenced by River-Transported Pollution: Southern Evoikos Gulf, Greece

Angelidis, Michael O.; Aloupi, Maria

doi:10.1016/s0025-326x(99)00174-5

Cited by 65 publications

(31 citation statements)

References 10 publications

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“…The hierarchical clustering was carried out from data normalized to a zero mean and using Euclidian distances as a measure of similarity (Massart & Kaufman 1983). WordÕs method was selected because it possesses a small space-distorting effect and accesses more information on cluster content (Angelidis & Aloupi 2000).…”

Section: Discussionmentioning

confidence: 99%

Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of the Mahanadi river–estuarine system (India) – a case study

Sundaray¹,

Panda

Nayak

et al. 2006

Environ Geochem Health

146

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Spatial and temporal distributions of water quality using multivariate statistical techniques for the evaluation of nutrients (NO(2)-N, NO(3)-N, NH(4)-N, PO(4)-P, SiO(4)-Si, total N, total P) in relation to some physico-chemical features (DO, BOD, TSS, TDS, SO (4) (2-) , Cl(-)) were studied for 31 different stations of the Mahanadi river-estuarine system in the eastern part of India. The seasonal nutrient variations (except SiO(4)-Si) exhibit higher values during monsoon season in unpolluted stations and the reverse trends for polluted stations, which are related to agricultural run-off and regional anthropogenic activities respectively. Silicate shows a well defined pattern of distribution with a higher concentration during the monsoon, which is slightly removed from the estuarine water of Mahanadi during the pre-monsoon season. The results of R-mode factor analyses revealed that anthropogenic contributions are responsible for the increase in nutrients and the decrease in DO and pH levels of the water. The magnitude of BOD with respect to total N and P demonstrates the intensity of organic pollution in the system. The removal of silicate in the saline system is clearly visible through factor analysis and the different mode of association of TSS is reflected seasonally. The relationships among the stations are highlighted by cluster analysis, represented in dendograms to categorize different levels of contamination.

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Section: Discussionmentioning

confidence: 99%

Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of the Mahanadi river–estuarine system (India) – a case study

Sundaray¹,

Panda

Nayak

et al. 2006

Environ Geochem Health

146

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“…The physicochemical parameters like pH, EC, DO, BOD, COD, TDS, TSS, Cl − , SO 4 2− , hardness, alkalinity, NO 3 -N, NH 3 -N, Fe, Mn, Cu, Zn, Co, Ni, Pb, and Cr are used as variables. Ward's method was selected because it possesses a small space-distorting effect and assesses more information on cluster contents (Angelidis and Aloupi 2000). The dendograms indicate the status of pollution as well as the effect of contamination into the stations, which are categorized into different groups.…”

Section: Cluster Analysismentioning

confidence: 99%

Application of multivariate statistical techniques in hydrogeochemical studies—a case study: Brahmani–Koel River (India)

Sundaray

2009

Environ Monit Assess

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This study presents the usefulness of multivariate statistical techniques, such as correlation matrix, cluster analysis, and factor analysis, for the evaluation and interpretation of complex water quality data sets of Brahmani-Koel river along the Rourkela Industrial Complex, India, and the apportionment of pollution sources/factors. The correlation study suggests that dissolved heavy metals, biochemical oxygen demand (BOD), and chemical oxygen demand (COD) are contributed by anthropogenic sources. The results of R-mode factor analyses revealed that anthropogenic contributions are responsible for increase in metals of the river water, which is mainly responsible for contamination of the river. It also reflected that the level of pollution in the river was very high. The factor score plot and loading plot have been drawn, which indicate that the polluted stations are identified by the heavy metals. The relationships among the stations are highlighted by cluster analysis, represented in dendograms to categorize different levels of contamination. An attempt has been made to study the degree of contamination of the river waters by using a tool like enrichment ratio (ER). The ER for heavy metal concentrations concluded that metals like Ni, Co, Cr, and Fe are showing high enrichment with respect to global background and metal ions like Fe, Mn, Cu, and Zn show high enrichment with respect to local background.

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“…Cd and Zn originate primarily from anthropogenic sources, whereas the major part of the Fe and Al seem to come from natural sources. The labile Mn should not be attributed to possible anthropogenic source, because Mn tends to be present in less thermodinamically stable in sediment phases, such as Mn +2 , easily reducible Mn oxides and Mn enclosed in carbonate minerals (Angelidis and Aloupi, 2000).…”

Section: Enrichment Factormentioning

confidence: 99%

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Özkan¹

2012

Turk. J. Fish. Aquat. Sci.

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Geochemical Study of Coastal Sediments Influenced by River-Transported Pollution: Southern Evoikos Gulf, Greece

Cited by 65 publications

References 10 publications

Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of the Mahanadi river–estuarine system (India) – a case study

Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of the Mahanadi river–estuarine system (India) – a case study

Application of multivariate statistical techniques in hydrogeochemical studies—a case study: Brahmani–Koel River (India)

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