Lead 210 and silicate profiles from sediments of the equatorial Pacific and South Atlantic

Particle mixing rates have been determined for 5 South Atlantic/Antarctic and 3 equatorial Pacific deep-sea cores using excess 210Pb and 32Si measurements. Radionuclide profiles from these siliceous, calcareous, and clay-rich sediments have been evaluated using a steady state vertical advection diffusion model. In Antarctic siliceous sediments210Pb mixing coefficients (0.04-0.16 cm**2/y) are in reasonable agreement with the 32Si mixing coefficient (0.2 or 0.4 cm**2/y, depending on 32Si half-life). In an equatorial Pacific sediment core, however, the 210Pb mixing coefficient (0.22 cm**2/y) is 3-7 times greater than the 32Si mixing coefficient (0.03 or 0.07 cm**2/y). The difference in 210Pb and 32Si mixing rates in the Pacific sediments results from: (1) non-steady state mixing and differences in characteristic time and depth scales of the two radionuclides, (2) preferential mixing of fine-grained clay particles containing most of the 210Pb activity relative to coarser particles (large radiolaria) containing the 32Si activity, or (3) the supply of 222Rn from the bottom of manganese nodules which increases the measured excess 210Pb activity (relative to 226Ra) at depth and artificially increases the 210Pb mixing coefficient. Based on 32Si data and pore water silica profiles, dissolution of biogenic silica in the sediment column appears to have a minor effect on the 32Si profile in the mixed layer. Deep-sea particle mixing rates reported in this study and the literature do not correlate with sediment type, sediment accumulation rate, or surface productivity. Based on differences in mixing rate among three Antarctic cores collected within 50 km of each other, local variability in the intensity of deep-sea mixing appears to be as important as regional differences in sediment properties.

137Cs concentrations in the southeastern Baltic Sea in 1997-2000

Variations of 137Cs concentration in the southeastern Baltic Sea were investigated over the period 1997-2000, i.e. in 11-14 years after the Chernobyl Nuclear Power Plant accident. Rate of "self-cleaning" proved to be very slow. Some results obtained in 1999 were almost the same as those measured after the accident, in 1986. Calculated results showed that "Chernobyl" caesium-137 would be "cleaned" in the Baltic Sea by 2020-2022. In 2000 average concentration had to be about 50-60 Bq/m**3. Sometimes mentioned concentrations were observed. In some cases higher concentrations averaging from 67 to 80 Bq/m**3 were registered in the southeastern Baltic Sea in 1999; and in some samples 137Cs concentrations were very high. They varied from 110 to 212 Bq/m**3. No steady correlation was observed between 137Cs concentration, salinity and temperature in surface water of the area. Distribution of radionuclide concentration sometimes depends on direction of water mass transport. Abnormally high concentrations of 137Cs in the southeastern Baltic Sea may result from additional radioactive waste discharge.

Annual 10Be concentrations from Lakes Tiefer See and Czechowskie AD1983-2009

Beryllium 10 concentrations (10Becon) were measured at annual resolution from varved sediment cores of Lakes Tiefer See (TSK) and Czechowskie (JC) for the period 1983-2009 (~solar cycles 22 and 23). Calibrating the 10Becon time-series against complementing proxy records from the same archive as well as local precipitation and neutron monitor data, reflecting solar forced changes in atmospheric radionuclide production, allowed (i) identifying the main depositional processes and (ii) evaluating the potential for solar activity reconstruction. 10Becon in TSK and JC sediments are significantly correlated to varying neutron monitor counts (TSK: r=0.5, p=0.05, n=16; JC: r=0.46, p=0.03, n=22). However, the further correlations with changes in organic carbon contents in TSK as well as varying organic carbon and detrital matter contents in JC point to catchment specific biases in the 10Becon time-series. In an attempt to correct for these biases multiple regression analysis was applied to extract an atmospheric 10Be production signal (10Be atmosphere). To increase the signal to noise ratio a 10Be composite record (10Be composite) was calculated from the TSK and JC 10Be atmosphere time-series. 10Becomposite is significantly correlated to variations in the neutron monitor record (r=0.49, p=0.01, n=27) and matches the expected amplitude changes in 10Be production between solar cycle minima and maxima. This calibration study on 10Be from two sites indicates the large potential but also, partly site-specific, limitations of 10Be in varved lake sediments for solar activity reconstruction.

(Table 1) 137Cs and 90Sr concentrations, salinity, and temperature in waters of the southeastern Baltic Sea on October 16, 2001

An analysis of variations in 137Cs and 90Sr concentrations in Baltic Sea surface waters after the accident at the Chernobyl nuclear power plant was performed. Instability of 137Cs concentrations during the short-term observations was found, when they differed 2- to 3-fold. Concentrations of 90Sr appeared to be more stable; meanwhile, their deviations sometimes exceeded ranges of experimental errors. By variations in the monthly average values of radionuclide concentrations in surface waters of the Baltic Sea in 1989-1995, no trend of water self-purification was observed. Theoretical results obtained confirmed a potential of formation and propagation of patches with increased concentrations of 137Cs in the southeastern Baltic Sea. The most reliable factor that controlled the process of self-purification of Baltic Sea water appeared to be the mean annual value of radionuclide concentration. Pronounced divergences were obtained between the measured and calculated mean annual concentrations of 137Cs and 90Sr in surface waters of the Baltic Sea in 1989-2001. These divergences are explained by potential influence of waters from the Gulf of Bothnia and by other additional supplies of radionuclides to marine environment, which were not included into mathematical models.