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Diss Factsheets

Administrative data

distribution modelling
Type of information:
other: publication
Adequacy of study:
supporting study
Study period:
3 (not reliable)
Rationale for reliability incl. deficiencies:
significant methodological deficiencies

Data source

Reference Type:

Materials and methods

water - sediment

Test material

Constituent 1
Chemical structure
Reference substance name:
EC Number:
EC Name:
Cas Number:
Molecular formula:
Specific details on test material used for the study:
Study area
The Rybnik dam reservoir was built in 1972 for the needs of the Rybnik power plant S.A. as a result of dividing the valley of the Ruda River (Odra River tributary) with an earth dam. This reservoir is part of a technological system as the source of water used in the power plant for cooling power facilities.
The areas of the watershed that feed the reservoir as well as riparian areas have very varied management: industrial areas (plants and slag heaps), urban and rural development, forest complexes (coniferous and deciduous). The reservoir is located in one of the most industrialized areas in Poland (the Upper Silesian District), which affects the contamination of the reservoir. The Upper Silesian District is a region with an enormous concentration of industry, mainly hard coal mining and the electric power industry, hence strong attention is directed to the studies of Upper Silesian area surface water contamination.

Sample collection
The samples were collected using an Ekman sampler from three set locations. The top layer of the sediment was collected from 0-15 cm. Pore water for testing was isolated from the whole sediment by centrifugation (3000 rpm, 30 min.), filtered on a 0.45 lm filter, and placed in 50 cm3 polypropylene conical test tubes. The pore water samples were stored in the dark at 4°C until they were used in the toxicity test. All the sediment samples after the decantation of overlying water and isolation of pore water were refrigerated until analyzed.

Study design

Test substance input data:
Chemical analyses
The sediments were analyzed for parameters such as granulometric composition, pH, conductivity, organic matter, total heavy metal concentration. The pH was measured, organic matter concentration was determined by loss-on-ignition for 8 h at 450°C. Total element concentration in the sediments was assessed after hot digestion in a mixture of HNO3 and HClO3 (3:2 v/v) acids. Heavy metal concentrations were analyzed using ICP-AES method . The speciation analysis of metals was performed using the three-step method of sequential fractionation by means of the modified BCR technique:
- fraction I—exchangeable and acid-soluble fraction, extractable with CH3COOH, pH 2;
- fraction II—forms associated with free Fe and Mn oxides, extractable with NH2OHHCl, pH 1.5;
- fraction III—forms bound to organic matter, extractable with hot H2O2, and the mineralization products re-extracted with CH3COONH4 at pH 2
- The residue (fraction IV) from step 3 was hot digested in a mixture of HNO3 and HClO3 acids (3:2) v/v. After each 1280 A. Baran, M. Tarnawki 123 step the extracts were separated from the solid residue by centrifugation at 3000 rpm for 20 min, & the supernatant liquids were decanted
The residues were washed by adding distilled water, shaken for 15 min on an end-over-end shaker, and centrifuged for 20 min at 3000 rpm.
Metal concentrations in the obtained solutions were assessed using ICP-AES method. Accuracy of the performed analyses was tested using reference material. The sediment and all pore water samples were analyzed in three replicates for which the relative standard deviations (%RSDs) were less than 10 % for all metals. The analytical results of the quality control samples showed good agreement with the certified values. The recovery of metal reached by sequential extraction technique was assessed by comparing the sum of the metal extracted in four steps (P fractions I–IV) with total metal concentration, using a mixture of HNO3 and HClO3 (3:2 v/v) acids for each sample. The results showed that the percentage of recovery ranged from 75 to 97 % for Cr. The results were verified statistically using the Statistica 10 software package.

Environmental properties:
Evaluation of the environmental significance of metals in sediments
To assess metal concentrations in sediment, 2 guidelines were applied in these studies. The assessment of bottom sediment contamination with heavy metals was based on threshold effect concentration (TEC) & probable effect concentration (PEC) methods. These indices establish values which are to be considered as a threshold value of TEC as well as a probable value of PEC. The sediment samples were predicted to be non-toxic if the measured concentrations of a chemical substance were lower than the corresponding TEC. Similarly, the samples were predicted to be toxic if the corresponding PECs were exceeded in the field-collected sediments. Samples with contaminant concentrations between the TEC and PEC were predicted to be neither toxic nor non-toxic. The other guideline was risk assessment code (RAC) classification based on the percentage of metal in the exchangeable and acid-soluble fraction (fraction I).
Risk Assessment Code indicates:
no risk: 1 %
low risk: 1-10 %
medium risk: 11-30 %
high risk: 31-50 %
very high risk: 50 %

Ecotoxicity tests
In the first stage, a battery of screening bioassays was conducted on the sediment and pore water. The toxicity assessment was performed using the following tests:
Phytotoxkit (sed.),
Phytotestkit (pore water),
Ostracodtoxkit F (sed.),
Microtox (sediment elutriate, pore water).
The sensitivity of this 6-day biotest was compared with the 10-day amphipod crustacean test Hyalella azteca and 10-day assay with the midgelarva Chironomus riparius.
Toxicity results were expressed as percent effect (PE %). In the second stage, after determining the percent effect for each bioassay, the sample was classified into one of 5 classes according to the highest toxicity indicated by at least 1 test:
I—no acute tox. PE<20 %
II—slight acute tox. 20 % <= PE < 50 %
III—acute tox. 50 % <= PE < 75 %
IV—high acute tox. 75 % <= PE<100 %;
V—very high acute tox.PE >= 100 %

Results and discussion

Applicant's summary and conclusion

The lowest mobility from the bottom sediments was found in chromium. Organic matter is likely to be the most important factor controlling metal distribution and mobility in the studied sediments.
Executive summary:

The total heavy metal concentration in the sediments was between 125 and 197 mg Cr kg-1 d.m.

Since mobility and potential toxicity of heavy metals are generally dependent on their existing chemical forms, it is important to identify the fractions of heavy metals in sediments.

The Potential Mobile Fraction (P1–3) ranged from 65 to 69 % Cr of the total concentration of the metals. However, the mobile fraction MF (fraction I) ranged 0.89 to

1 % Cr of total concentration of the metals. The order of the PMF in the studied sediments was the lowest for Cr.

According to the Risk Assessment Code, low risk was assessed for chromium release.

The correlation analysis performed on the data enabled the identification of possible common characteristics of heavy metals in the sediment, as well as evaluation of the

potential of organic matter, pH and granulometric composition in order to control metal mobility. Results show that fraction I of Cr was positively correlated with sand.

Additionally, fraction I of Cr was negatively correlated with silt. Based on the correlation matrices obtained for faction II of the heavy metals, two clearly distinct metal groups may be distinguished: one for Zn, Pb, Ni, and another for Cr, Cu, Cd.

The first group of metals bound with faction II (forms associated with free Fe and Mn oxides) negatively correlated with sand and organic matter. However, they were positively correlated strongly with silt. The second group of metals showed the opposite correlations. Data indicate that fraction III and fraction IV of the metals including Cr showed a negatively significant correlation with sand and organic matter. However, these fractions correlated positively with silt. The PMF (PI–III) of the metals correlated positively with sand and organic matter, and negatively with silt. Total concentration of Cr showed a similar relation with properties of the sediments. A positive

correlation was recorded between total concentration of both metals and clay, and pH (Table 1). However, total concentration of Cr was negatively correlated with

organic matter. To sum up, the correlation analysis found that organic matter, sand and silt significantly affected the mobility and potential mobility of the metals.

The potential metal fractions PMF PI–III showed a generally significant negative correlation with the toxicity of the samples (Table 1).

Positive significant correlations between the concentration of organic matter and the total metal concentration (r = 0.76 for Cr (p < 0.05)) confirm the considerable share of organic matter in the binding of heavy metals. Sediment organic matter also significantly affected the distribution of the metals among different geochemical fractions. Sand and silt content also significantly affected mobility and potential mobility of the metals.

The analysis of total concentrations of metals and their fractionation showed that sediments of the Rybnik reservoir are contaminated with heavy metals, which is an effect

of intensive human impact of the area where the reservoir is located. Organic matter is likely to be an important factor which controls metal distribution and mobility in the

studied sediments. The highest amount of Cr and other metals was associated with fraction III (organic), which indicates that this form of metals was dominant in sediments

of the Rybnik reservoir. Sand and silt also significantly affected the distribution of metals among different geochemical fractions. Sediments from the Rybnik reservoir were toxic, but the used organisms showed different sensitivity. Moreover, the studies showed a higher toxicity in solid phases and whole sediment than in the pore water.

Additionally, the total metal concentrations correlated in a significantly positive way with the response of the test organisms.

In conclusion, a multitrophic battery of different test species allows toxicity levels to be correctly evaluated, reducing the uncertainty in sediment quality assessments.