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1

Using factor analysis to evaluate sediment quality of a significant mining area in Turkey

100%

Cicek A. , Kose E. , Tokatli C.

Polish Journal of Environmental Studies

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2019

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tom 28

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nr 3

EN

Statistical applications have been used to evaluate ecosystem quality in recent years. Factor analysis (FA) is a powerful multivariate statistical technique widely used to evaluate environmental pollution. Seydisuyu Stream Basin is located in the Central Anatolia Region of Turkey and it is one of the most important branches of the Sakarya River. There is a globally important boron mine on the basin and the system is exposed to intensive agricultural, domestic, and industrial pollution. The aim of this study is to evaluate the sediment quality of Seydisuyu Stream Basin using FA. For this purpose, some micro and macro element accumulations including Cr, Ni, Cu, Zn, As, B, Pb, Fe, K, Mn, and Mg in sediment were investigated by collected samples on the basin from 15 stations (including 3 from Çatören Dam Lake and 2 from the Kunduzlar Dam Lake) in summer 2012. According to FA results, three factors explained 90.95% of the total variance. The first factor (F1), the “urban-industrial factor,” explained 47% of total variance; the second factor (F2), the “agricultural factor,” explained 28.31% of total variance; and the third factor (F3), named the “geological-mining factor,” explained 15.63% of total variance.

2

Pesticide accumulation in Turkey’s Meric River Basinwater and sediment

100%

Tokath C. , Kose E. , Cicek A. , Emiroglu O.

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nr 1

3

Groundwater quality of Turkmen Mountain, Turkey

100%

Tokatli C. , Kose E. , Cicek A.

Polish Journal of Environmental Studies

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2013

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tom 22

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nr 4

EN

This study was carried out to determine the groundwater quality of Türkmen Mountain, which provides drinking water to about 250,000 people, and to evaluate the water quality by using some multivariate statistical techniques. In this study, groundwater samples were collected from 18 stations on Türkmen Mountain in summer 2011. Some lymnological parameters and element levels in groundwater of the mountain were determined. Factor analysis (FA), cluster analysis (CA), and Pearson Correlation Index were applied to the results in order to estimate the data properly. The ArcGIS package program was used to make distribution maps of arsenic, boron, and total phosphorus (which were detected as the most critical parameters of the mountain) in order to provide visual summaries of element accumulations. Also, water samples were evaluated according to the criteria of SKKY (water pollution control regulation in Turkey) and evaluated as drinking water according to the criteria of TS266 (Turkish Standards Institute), the EC (European Communities), and WHO (World Health Organization). It was determined that arsenic accumulations of some stations exceeded the limit values specified by TS266, WHO, and the EC. Significant positive correlations were determined between arsenic and boron levels (p<0.01), and according to the FA results, the “Boron Works Factor,” which was strongly positive related to the variables of arsenic and boron, was identified as the most effective component for Türkmen Mountain (25.88% of total variance). As a result, in addition to the geological structure of the mountain, mining activities and mineral recovery processes are significant effective factors of groundwater quality of Türkmen Mountain.

4

Monitoring stream water quality: A statistical evaluation

100%

Kose E. , Tokatli C. , Cicek A.

Polish Journal of Environmental Studies

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2014

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tom 23

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nr 5

EN

Seydisuyu Stream Basin, known to be exposed to agricultural and domestic pollution, is one of the most important branches of the Sakarya River. In addition to the geologic structure of the basin, Kırka Boron Mine is one of the most important inorganic pollution sources for the system and also for the Sakarya River. In this study, the water quality of Seydisuyu Stream was evaluated by determining some physiochemical (temperature, conductivity, salinity, TDS, pH, ORP, dissolved oxygen, and nitrate) and chemical (boron and arsenic) parameters. Water samples were collected an average of 10 times per month between September 2011- September 2012 from Hamidiye Village, located at the downside of Seydisuyu Stream. All of the data obtained experimentally were compared according to the criteria of SKKY (Water Pollution Control Regulation in Turkey) and evaluated as drinking water according to the criteria of TS266 (Turkish Standards Institute), EC (European Communities), and WHO (World Health Organization). Cluster analysis (CA) was applied to the results to classify the seasons according to water quality by using the Past package program. Factor analysis (FA) was applied to the results to classify the affective factors on water quality, and Pearson Correlation Index was applied to the results to determine the relations of parameters by using the SPSS 17 package program. According to the results of FA, four factors explained 84.78% of the total variance and according to the results of CA, three statistically significant clusters were formed. In a macroscopic view, the monitoring station has class I-II water quality in terms of arsenic and class IV water quality in terms of boron. It was also determine that arsenic and boron accumulations in Seydisuyu Stream water were much higher than drinking water limits.

5

Boron and arsenic levels in water, sediment, and tissues of Carassius gibelio (Bloch, 1782) in a Dam Lake

75%

Cicek A. , Kose E. , Emiroglu O. , Tokatli C. , Baskurt S. , Sulun S.

Polish Journal of Environmental Studies

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2014

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tom 23

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nr 5

EN

The Seydisuyu River one of the tributaries of Sakarya River which is the third largest river system in Turkey. The Seydisuyu Basin includes one of the most important boron mines in world. Boron sources in the Seydisuyu Basin, fertilizers, and pesticides used in agricultural applications; geological structure of the basin and mining applications are resources important for boron and arsenic. Kunduzlar Dam Lake, which is one of the most important reservoirs of the Seydisuyu basin, was constructed for the Seyitgazi Plain in 1983. Boron and arsenic values were the two important contaminants determined around the region. B and As levels were determined in water and sediment of Kunduzlar Dam Lake and also B levels were identified in tissues of Carassius Gibelio. Water and sediment samples were collected seasonally between 2011-12. Also, muscle, gill, and liver tissues of Carassius Gibelio (Bloch, 1782) were examined in spring 2012. Arsenic and boron levels in water were found higher than permissible levels. In all tissues of Carassius Gibelio bioaccumulation factors (BAFs) for boron were remarkably high and boron accumulation levels in the muscle were lower than other tissues.

6

Sediment quality assessment in porsuk stream basin (Turkey) from a multi-statistical perspective

75%

Kose E. , Emiroglu O. , Cicek A. , Tokatli C. , Baskurt S. , Aksu S.

Polish Journal of Environmental Studies

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2018

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tom 27

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nr 2

EN

Porsuk Stream Basin is a significant aquatic habitat located in the middle of the Aegean and Central Anatolian Regions of Turkey. Similar to may aquatic habitats, it is exposed to intensive agricultural, domestic, and industrial pollution. The aim of this study was to determine the toxic element levels in Porsuk Stream Basin sediment and evaluate the detected data using a multi-statistical technique. For this purpose, sediment samples were collected from 18 stations selected on the basin (three of them located on Porsuk Dam Lake) in summer 2015, and zinc, copper, lead, cadmium, nickel, and chromium accumulations in sediment samples were determined. All the detected data were compared with the consensus-based threshold effect concentrations (TEC), and factor analysis (FA) also was applied to detected data in order to evaluate the contamination grades in the basin. According to detected data, although Cu, Pb, and Cd concentrations were detected below the limit values, Zn, Cr, and Ni concentrations exceeded the limit values in general. According to results of FA, 3 factors – industrial, agricultural, and lead – explained 81.56% of the total variance.