Seasonal and spatial variations in biomarker baseline levels within Arctic populations of mussels (Mytilus spp.).

Climate change and pollution resulting from human activities in the Arctic require reliable monitoring systems in sentinel species. Mytilus spp. are used as sentinel species all around the world. The use of Mytilus spp. in environmental monitoring requires knowledge about natural variations in pollution biomarkers. Seasonal variations in baseline levels of biomarkers were studied over a year in the mussels from both upper and lower littoral zones in Rakkfjorden, Norway, as they underwent their annual reproductive cycle. Spatial variations of these biomarker baseline levels were measured in five mussel populations within a 60-km radius from Rakkfjorden to investigate universality of the results from the specific population of Rakkfjorden at a regional scale. Seasonal variations in biomarker baseline levels were revealed and seemed to be related to the reproductive state of the mussels and the tidal zone. The mussels appeared to be more sensitive to oxidative stress during gametogenesis in autumn and winter, when having lower lysosome membrane stability and lower baseline levels of antioxidant biomarkers. An increase in baseline levels of these biomarkers was reported during spawning in spring, however, it was not possible to reveal whether these changes were due to spawning, or to a higher metabolic activity in mussels in response to elevated water temperature and food abundance. The differences between the tidal zones were reflected in reduced size of the mussels from the upper littoral zone, their late spawning in the season and increased baseline levels of antioxidant biomarkers during the coldest month, indicating a more challenging environment in the upper littoral zone. The spatial study indicated that the biomarker baseline levels measured in Rakkfjorden were no different from the levels measured in the mussels from five other sites and thus, are representative for mussels on a regional scale.

The impact of submarine copper mine tailing disposal from the 1970s on Repparfjorden, northern Norway.

We investigate the state of sedimentological environment and contaminant status of Repparfjorden (N Norway) impacted by submarine disposal of mine tailings during the 1970s using sedimentological and geochemical properties of seventeen sediment cores. The impact of tailings disposal is mainly restricted to the inner fjord where the discharge occurred. Sediment cores retrieved from the inner fjord contain layers of mine tailings up to 9-cm thick, 3-9cm below the seafloor. Spreading of the tailing-related metal Cu and particles is limited to the inner fjord and to a 2cm layer in one core from the outer fjord. Two interrelated factors, fjord morphology and sedimentation rate, controlled the distribution of contaminant-laden tailings in the fjord. The mobility of Cu from buried contaminated sediments to the sediment-water interface in the inner fjord indicates that benthic communities have been continuously exposed to elevated Cu concentrations for nearly four decades.

Multivariate methods for evaluating the efficiency of electrodialytic removal of heavy metals from polluted harbour sediments.

Chemometrics was used to develop a multivariate model based on 46 previously reported electrodialytic remediation experiments (EDR) of five different harbour sediments. The model predicted final concentrations of Cd, Cu, Pb and Zn as a function of current density, remediation time, stirring rate, dry/wet sediment, cell set-up as well as sediment properties. Evaluation of the model showed that remediation time and current density had the highest comparative influence on the clean-up levels. Individual models for each heavy metal showed variance in the variable importance, indicating that the targeted heavy metals were bound to different sediment fractions. Based on the results, a PLS model was used to design five new EDR experiments of a sixth sediment to achieve specified clean-up levels of Cu and Pb. The removal efficiencies were up to 82% for Cu and 87% for Pb and the targeted clean-up levels were met in four out of five experiments. The clean-up levels were better than predicted by the model, which could hence be used for predicting an approximate remediation strategy; the modelling power will however improve with more data included.