Evaluation methods used for determining amount of contamination in the sediments and results
Sediment Characteristics results
Grain size distribution for the stations showed a similar result for stations 1,2, 4 and 5 with an overall domination of the fraction silt and lesser degree of clay. Largest silt content of station 1 is in the location of outlets from rivers Cakit and Körkun Creek. Station 3 was also dominated by silt but with a major component of sand as well, this station was closest to the mouth of Seyhan river. (Cevik et al. 2009.)
Organic content of the stations is highest for the stations with a major component of fines and lowest for station 3 with major sand fractions. This can be connected to the sand fractions specific surface area witch are smaller than silt and clay, also it can be connected to energy levels of the localities and different settling velocities of the fractions.
Metal contents for station 3 was in average the lowest.
Grain size for station 1-5. Cevik et al 2009.
Table of mean metal (μg g−1) and organic content in % for station 1-5. Cevik et al. 2009.
Total contents
Where total content of the metals in the sediments are analysed in the lab. This does not take into account relation to any other parameters of the samples such as ex. grain size or organic matter.
Can be misleading when just comparing values of samples from different sites and sediments. (Johannesson ,2002) That is why further methods is used to evaluate the results
Enrichment factor and Geoaccumulation index
To be able to evaluate if the total content of the metals is due to natural or anthropogenic factors the enrichment factor (EF) can be calculated and geoaccumulation index be used.
The EF is calculated by normalization using total concentrations compared to average crust or as in this study average shale concentrations (Mwamburi, 2003). Average shale is used as it is seen to be more appropriate for finer fraction samples. This is due to the fact that shale naturally integrate crustal material from different environments of the earth's surface as a sedimentary rock. The average crustal values are bulk value concentrations and does not show concentrations in relation to finer fractions. Comparison of average shale and crust shown in table below.
The elements most commonly used is Alumina or Iron.
This method is criticised by Reimann and De Caritat from 2005 as to not taking into account the regional variations that are significant. It is also suggested that concentrations should instead be compared to local backgrounds from deeper soil layers but this is also criticised that it does not take into account the difference in concentrations due to soil horizons and plants nutrition uptake affecting. They conclude that EF data should be used with more care and that regional raw data from soils might be more effective as a means to evaluate contamination levels. Since natural processes effects element ratios and thus can not be used to show contamination if not a special source for the pollutions were suspected. (Reimann et al. 2005)
Geoaccumulation index is used to compare sample concentrations to background values before the industrial revolution (Likuku et al. 2013). This can be calculated by using the geochemical background value for the element in question from average shale. This value is then adjusted using background matrix correction factor of 1,5 to account for lithogenic effects due to variations in the soils. (Çevik et al. 2009)
Table from Abrahim et al. 2008. Showing comparisons of selected element from averaged values.
Calculations of EF from Cevik et al. 2009
Calculations of geoaccumulation index from Cevic et al. 2009.
Results of EF calculations of the sediments showed that Cd had the highest with a value of 8.45 that represents moderate severe enrichment. Lower values for Cr (1.57) and Mn (1.12) represented minor enrichment.
GA Index results for the metal Cr showed moderately to strongly pollution in stations 1, 2, 4 and 5 and moderately polluted in station 3.
Enrichment factors in surface sediments of Seyhan dam. Cevik et al 2009.
Geoaccumulation Index results in sediments. Cevik et al. 2009
Statistical testing of single parameter relationships
Statistical methods were used to find out if there were any correlations between metal content and grain size or organic matter.
A Pearson multiple correlation analysis was used that measures the strength of association between two measured variables. This is shown by a linear correlation with a p value , between +1 and -1. Where 0 is no correlation and the extremes are good positive or negative correlations. (UWE, 2017)
Analyses was made that shows significant correlations, p value <0.01, between organic matter and all of the tested metals except for Na and Ca. Correlations, p value of <0.05, was also made between clay and Cr, Fe and K. Also negative correlations existed between sand fraction and Mn, Fe and K.
Table showing correlation organic matter to element content / grain size. (Çevik et al. 2009)
Sediment quality guidelines
These guidelines are used in freshwater environments to interpret sediment ecosystem health. Here probable effect concentrations and threshold effect concentrations was employed to identify harmful levels.