The Occurrence of Skeletons of Silicoflagellata and Other Siliceous Bioparticles in Floral Honeys.

Siliceous marine microfossils were unexpectedly discovered during the analysis of flower honey samples from Poland and Tunisia. The microfossils were represented by protist with siliceous skeletons: silicoflagellates, diatoms, and endoskeletal dinoflagellates. This is the first record of such microfossils in honeys. Based on the high percent of anemophilous pollen grains and spores in the sample, it was hypothesized that silicoflagellates were deposited from the air onto the nectariferous flowers, then bees harvested them with the nectar. Based on the comparison of pollen content of honeys and flowering calendar of Tunisia, the harvest time of honey was identified as a period between 1 April and 31 May 2011. Trajectory analysis of air masses in this period confirmed that siliceous microfossils could be aerosolized by wind from the rocks of the so-called Tripoli Formation of Messinian age (6-7 Ma). Similar to the Tunisian case, the Polish trajectory simulation also supports the hypothesis of atmospheric transport of silicoflagellates from outcrops of Oligocene age in the Polish Outer Carpathians. In the case of diatom content of honey, however, the source can be both natural (wind) and artificial (diatomaceous earth filters). For a correct determination, natural sources of siliceous bioparticles, such as wind transport from nearby outcrops should be also considered. Silicoflagellates could be used as complementary indicators of the geographical origin of honeys collected in areas characterized by diatomite outcrops, supporting the results obtained with other methods; thus, such indicators merit further studies within the area of honey authenticity.

A review of numerical models to predict the atmospheric dispersion of radionuclides.

The field of atmospheric dispersion modeling has evolved together with nuclear risk assessment and emergency response systems. Atmospheric concentration and deposition of radionuclides originating from an unintended release provide the basis of dose estimations and countermeasure strategies. To predict the atmospheric dispersion and deposition of radionuclides several numerical models are available coupled with numerical weather prediction (NWP) systems. This work provides a review of the main concepts and different approaches of atmospheric dispersion modeling. Key processes of the atmospheric transport of radionuclides are emission, advection, turbulent diffusion, dry and wet deposition, radioactive decay and other physical and chemical transformations. A wide range of modeling software are available to simulate these processes with different physical assumptions, numerical approaches and implementation. The most appropriate modeling tool for a specific purpose can be selected based on the spatial scale, the complexity of meteorology, land surface and physical and chemical transformations, also considering the available data and computational resource. For most regulatory and operational applications, offline coupled NWP-dispersion systems are used, either with a local scale Gaussian, or a regional to global scale Eulerian or Lagrangian approach. The dispersion model results show large sensitivity on the accuracy of the coupled NWP model, especially through the description of planetary boundary layer turbulence, deep convection and wet deposition. Improvement of dispersion predictions can be achieved by online coupling of mesoscale meteorology and atmospheric transport models. The 2011 Fukushima event was the first large-scale nuclear accident where real-time prognostic dispersion modeling provided decision support. Dozens of dispersion models with different approaches were used for prognostic and retrospective simulations of the Fukushima release. An unknown release rate proved to be the largest factor of uncertainty, underlining the importance of inverse modeling and data assimilation in future developments.

Numerical simulations of atmospheric dispersion of iodine-131 by different models.

Nowadays, several dispersion models are available to simulate the transport processes of air pollutants and toxic substances including radionuclides in the atmosphere. Reliability of atmospheric transport models has been demonstrated in several recent cases from local to global scale; however, very few actual emission data are available to evaluate model results in real-life cases. In this study, the atmospheric dispersion of 131I emitted to the atmosphere during an industrial process was simulated with different models, namely the WRF-Chem Eulerian online coupled model and the HYSPLIT and the RAPTOR Lagrangian models. Although only limited data of 131I detections has been available, the accuracy of modeled plume direction could be evaluated in complex late autumn weather situations. For the studied cases, the general reliability of models has been demonstrated. However, serious uncertainties arise related to low level inversions, above all in case of an emission event on 4 November 2011, when an important wind shear caused a significant difference between simulated and real transport directions. Results underline the importance of prudent interpretation of dispersion model results and the identification of weather conditions with a potential to cause large model errors.

Predictability of the dispersion of Fukushima-derived radionuclides and their homogenization in the atmosphere.

Long-range simulation of the dispersion of air pollutants in the atmosphere is one of the most challenging tasks in geosciences. Application of precise and fast numerical models in risk management and decision support can save human lives and can diminish consequences of an accidental release. Disaster at Fukushima Daiichi nuclear power plant has been the most serious event in the nuclear technology and industry in the recent years. We present and discuss the results of the numerical simulations on dispersion of Fukushima-derived particulate (131)I and (137)Cs using a global scale Lagrangian particle model. We compare concentrations and arrival times, using two emission scenarios, with the measured data obtained from 182 monitoring stations located all over the Northern Hemisphere. We also investigate the homogenization of isotopes in the atmosphere. Peak concentrations were predicted with typical accuracy of one order of magnitude showing a general underestimation in the case of (131)I but not for (137)Cs. Tropical and Arctic plumes, as well as the early detections in American and European midlatitudes were generally well predicted, however, the later regional-scale mixing could not be captured by the model. Our investigation highlights the importance of the parameterization of free atmospheric turbulence.

Short and long term dispersion patterns of radionuclides in the atmosphere around the Fukushima Nuclear Power Plant.

The Chernobyl accident and unfortunately the recent accident at the Fukushima 1 Nuclear Power Plant are the most serious accidents in the history of the nuclear technology and industry. Both of them have a huge and prolonged impact on environment as well as human health. Therefore, any technological developments and strategies that could diminish the consequences of such unfortunate events are undisputedly the most important issues of research. Numerical simulations of dispersion of radionuclides in the atmosphere after an accidental release can provide with a reliable prediction of the path of the plume. In this study we present a short (one month) and a long (11 years) term statistical study for the Fukushima 1 Nuclear Power Plant to estimate the most probable dispersion directions and plume structures of radionuclides on local scale using a Gaussian dispersion model. We analyzed the differences in plume directions and structures in case of typical weather/circulation pattern and provided a statistical-climatological method for a "first-guess" approximation of the dispersion of toxic substances. The results and the described method can support and used by decision makers in such important cases like the Fukushima accident.