GI2.3

How to cite: Igarashi, Y., Kenji, N., Wada, T., Wakiyama, Y., Onda, Y., and Moritaka, S.: Factors controlling the dissolved 137Cs seasonal fluctuations in the Abukuma River under the influence of the Fukushima Nuclear Power Plant accident, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3340, https://doi.org/10.5194/egusphere-egu22-3340, 2022.

This study presents the temporal variations in riverine ¹³⁷Cs concentrations and fluxes to the ocean during high-flow events in three coastal river catchments contaminated by the Fukushima Daiichi Nuclear Power Plant accident. River water samples were collected at points downstream in the Niida, Ukedo, and Takase Rivers during three high-flow events that occurred in 2019–2020. Variations in both the dissolved ¹³⁷Cs concentration and ¹³⁷Cs concentration in suspended solids appeared to reflect the spatial pattern of the ¹³⁷Cs inventory in the catchments, rather than variations in physico-chemical properties. Negative relationships between the ¹³⁷Cs concentration and δ¹⁵N in suspended sediment were found in all rivers during the intense rainfall events, suggesting an increased contribution of sediment from forested areas to the elevated ¹³⁷Cs concentration. The ¹³⁷Cs flux ranged from 0.33 to 18 GBq, depending on the rainfall erosivity. The particulate ¹³⁷Cs fluxes from the Ukedo River were relatively low compared with the other two rivers and were attributed to the effect of the Ogaki Dam reservoir upstream. The ratio of ¹³⁷Cs desorbed in seawater to ¹³⁷Cs in suspended solids ranged from 2.8% to 6.6% and tended to be higher with a higher fraction of exchangeable ¹³⁷Cs. The estimated potential release of ¹³⁷Cs from suspended solids to the ocean was 0.048–0.57 GBq, or 0.8–6.2 times higher than the direct flux of dissolved ¹³⁷Cs from the river. Episodic sampling during high-flow events demonstrated that the particulate ¹³⁷Cs flux depends on catchment characteristics and controls ¹³⁷Cs transfer to the ocean. 

How to cite: Wakiyama, Y., Niida, T., Takata, H., Taniguchi, K., Kurosawa, H., Fujita, K., and Konoplev, A.: A comparative study of riverine 137Cs dynamics during high-flow events at three contaminated river catchments in Fukushima, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3442, https://doi.org/10.5194/egusphere-egu22-3442, 2022.

Bottom sediments of lakes and dam reservoirs can provide an insight into understanding the dynamics of ¹³⁷Cs strongly bound to sediment particles. On this premise, a number of cores of bottom sediments were collected in deep parts of lakes Glubokoe, Azbuchin, and Cooling Pond in close vicinity of the Chernobyl NPP in Ukraine, in Schekino reservoir (Upa River) in the Tula region of Russia (2018) and in Ogaki reservoir (Ukedo River) in Fukushima contaminated area (2019). Each layer of bottom sediments can be attributed to a certain time of suspended particles sedimentation. With ¹³⁷Cs activity concentration in a given layer of bottom sediments corresponding to ¹³⁷Cs concentration on suspended matter at that point in time, we were able to reconstruct the post-accidental dynamics of particulate ¹³⁷Cs activity concentrations. Using experimental values of the distribution coefficient K_d, changes in the dissolved ¹³⁷Cs activity concentrations were estimated. The annual mean particulate and dissolved ¹³⁷Cs wash-off ratios were also calculated for the period after the accidents. Interestingly, the particulate ¹³⁷Cs wash-off ratios for the Ukedo River at Ogaki dam were found to be similar to those for the Pripyat River at Chernobyl in the same time period after the accident, while the dissolved ¹³⁷Cs wash-off ratios in the Ukedo River were an order of magnitude lower than the corresponding values in the Pripyat River. The estimates of particulate and dissolved ¹³⁷Cs concentrations in Chernobyl cases were in reasonable agreement with monitoring data and predictions using the semi-empirical diffusional model. However, both the particulate and dissolved ¹³⁷Cs activity concentrations and wash-off ratios in the Ukedo River declined faster during the first eight years after the FDNPP accident than predicted by the diffusional model, most likely, due to greater natural attenuation and, to some extent, remediation measures implemented on the catchments in Fukushima.

This research was supported by Science and Technology Research Partnership for Sustainable Development (SATREPS), Japan Science and Technology Agency (JST)/Japan International Cooperation Agency (JICA) (JPMJSA1603), by bilateral project No. 18-55-50002 of Russian Foundation for Basic Research (RFBR) and Japan Society for the Promotion of Science (JSPS), and JSPS Project KAKENHI (B) 18H03389.

How to cite: Konoplev, A., Wakiyama, Y., Wada, T., Igarashi, Y., Laptev, G., Golosov, V., Ivanov, M., Komissarov, M., and Nanba, K.: Vertical distribution of 137Cs in bottom sediments as representing the time changes of water contamination: Chernobyl and Fukushima, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6698, https://doi.org/10.5194/egusphere-egu22-6698, 2022.

Lake Onuma on Mt. Akagi (Gunma Prefecture, Japan) is a closed lake with an average water residence time of 2.3 years. The activity concentration of radioactive cesium in the lake was high shortly after the Fukushima accident. According to Suzuki et al. [1] and Watanabe [2], after a filtration process, Cs-137 are separated into two groups: particulate form and dissolved form. These two forms appears to have very different concentration profiles with each other,  when the Cs-137 concentration plotted against the sampled water depths. In the present study, we are going to model those behavior of particulate/dissolved forms with an emphasis on the depth dependency.

We consider a creation-annihilation process of plankton for the model of the particulate form, since diatom shells are found to be a major constituent of the particulate Cs-137 [2]. We set  ∂P/∂t = f(x,t)  and  f(x,t) = χ(x) cos(ωt) (0 ≤ x ≤ L(water column height), t > 0),  where P=P(x,t) is the activity concentration of the particulate form. The term f(x,t) is the rate of the net production of the plankton at a specific location x at a specific time t. Seasonal cycle is also taken into account by the cosine function (we neglect the phase shift here). The function χ(x), depends solely on water depth x, is responsible for dynamics or inhomogeneity of lake water, such as circulation, stratification or a thermocline. We assume that such a water structure relates to the production rate of plankton through the function χ(x). Thus, we may obtain the concentration of particulate Cs-137. For the dissolved concentration S(x,t), we use the classical diffusion equation with the diffusivity K being dependent on both space and time (i.e. K(x,t)), namely ∂S/∂t =  ∇•(K(x,t) ∇S). Here S=S(x,t) is the activity concentration of the dissolved form. The total activity concentration C(x,t) is the sum of P(x,t) and S(x,t). Using the pair of the equations, we can reproduce the followings. (1) depth profiles of each of the soluble- and particulate activity concentration and (2) depth profiles of the total Cs-137 concentration.

 [1] Suzuki, K. et al., Sci. Tot. Env. (2018)

 [2] Watanabe, S. et al.,  Proc. 20^th Workshop on Environmental Radioactivity (2019)

How to cite: Hatano, Y., Akasaki, K., Suetomi, E., Okada, Y., Suzuki, K., and Watanabe, S.: Modeling the depth dependence of Cs-137 concentration in Lake Onuma, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1235, https://doi.org/10.5194/egusphere-egu22-1235, 2022.

Radiocesium deposited in the forest canopy is transferred to the forest floor by rainwater and　litterfall. Among them, stemflow likely increases the radiocesium inventory by concentrating rainwater around the trunk. However, the effects of stemflow on the influx of radiocesium into forest soil have not been evaluated quantitatively. In this study, the fluxes of rainwater via stemflow, throughfall, and soil infiltration water were observed. The concentration of dissolved ¹³⁷Cs was measured in a cedar forest in Fukushima Prefecture, Japan. Soil infiltration water was collected at 5 cm and 20 cm depths at the distant point from the tree trunk (Bt), and the base of the tree trunk (Rd), where the influence of stemflow was strong. The observations were conducted during the period from September 2019 to November 2021. During the observation period, an experiment was conducted to intercept the inflow of rainwater via the throughfall or stemflow, and the change in soil infiltration water was observed. The observation results showed that the infiltration flux of radiocesium into the forest soil was significantly higher at the Rd site and about three times larger than at the Bt site. Particularly at the 20 cm depth at the Rd site, the soil infiltration water flux increased with the stemflow. The stemflow exclusion resulted in the dcrease of radiocesium flux by about 70% at all depths at the Rd site. These results suggest that the stemflow increases the input of radiocesium to the base of the tree trunk and facilitates its transfer to the deeper soil layers.

How to cite: Kato, H., Iida, H., Shinozuka, T., Niwano, Y., and Onda, Y.: Effects of stemflow on radiocesium infiltration into the forest soil, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10817, https://doi.org/10.5194/egusphere-egu22-10817, 2022.

Most of the territory of the Chernobyl Exclusion Zone (CEZ) is covered by forest. Forest of CEZ have accumulated a significant part of the radioactive release and for many years have served as a barrier to the non spreading of the radionuclide contamination outside the CEZ.

According to the classification of wildfire danger, the forests of CEZ belong to high, above average and medium classes, making cases of wildfires as quite common.

Poor, sod-podzolic soils of Ukrainian Polesye contribute to the entry the activity of ⁹⁰Sr and ¹³⁷Cs in plant biomass. During wildfires some of the radionuclides contained in combustion products of biomass are emitted into the atmosphere. Biologically important radionuclides such as ⁹⁰Sr, ¹³⁷Cs, plutonium isotopes and ²⁴¹Am bound to fine aerosols - combustion products - can be transported with atmospheric flows over the long range, causing secondary radioactive fallout and forming additional inhalation dose loads on the population.

Lack of the actual information on the source term (rate of emission of radionuclides) does not allow reliable modeling of the radiological impact of wildfires. To address this issue, we have proposed a methodology that allows for operational assessments of the dynamics of radionuclide emissions into the atmosphere from wildfires in the CEZ.

The basic parameters for the calculations are

• cartographic data on the density of radionuclide contamination of the territory of the CEZ;
• classification of the territory of the CEZ according to the distributive features of forests and meadows;
• classification of CEZ forests according to taxa characteristics to estimate amount of stored fuel biomass (kg/m²);
• experimental data on the transfer of radionuclides from soil to the main components of biomass for the calculation of radionuclide inventory in fuel biomass (Bq/m²). Thus, for meadows the main fuel component is grass turf, while for forest these are litter, wood, bark and pine needles.
• experimental data on emission factors of radionuclides from fuel biomass.

Implementation of the proposed algorithm in the form of GIS application makes it possible to assess the dynamics of radionuclide emission into the atmosphere by delineation the fire areas on the CEZ map. The NASA WorldView interactive mapping web application can be used to estimate the temporal and spatial characteristics of the wildfire while it is being developed. The contouring of the area affected by fire is carried out according to the analysis of the cluster of thermal points. Also, operational contouring of wildfire can be carried out using data delivered from unmanned aerial vehicles.

The application of the proposed algorithm for the analysis of the dynamics of ¹³⁷Cs emissions into the atmosphere from the April 2020 wildfire showed a good agreement with the data reported by various authors who used the method of inverse simulation. Improving the accuracy of calculations according to the proposed algorithm can be done by rectifying radionuclide emission factors and taking into account fire intensity data, which in turn can affect both the radionuclide emission factor and the degree of burnout of plant biomass.

How to cite: Protsak, V., Laptev, G., Voitsekhovych, O., Hinchuk, T., and Korychenskyi, K.: Methodology for estimating the emission of radionuclides into the atmosphere from wildfires in the Chernobyl Exclusion Zone, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11620, https://doi.org/10.5194/egusphere-egu22-11620, 2022.

European seas such as, Baltic, North, and Norwegian Seas are mostly affected areas by the accident at the Chernobyl nuclear power plant (CNPP) in 1986. Since Fukushima Daiichi nuclear power plant (FDNPP) is located on the coast of the North Pacific Ocean in east Japan, its accident resulted in the release of large amounts of radiocesium to the surrounding coastal marine environment (i.e. the waters off Fukushima and neighboring prefectures). The temporal change of radiocaesium concentration in seawater after both accidents was largely dependent on their submarine topography: The Baltic Sea is a semi-closed basin, while Norwegian and North Seas, and the waters off Fukushima and neighboring prefectures is directly connected to open-water. Although concentration of radioacesium (¹³⁷Cs) in the surface water of the Baltic Sea (central part) continuously decreased, the values in 1996, ten years after the accident, were even higher than pre-accident level in 1985. On the other hand, in the waters off Fukushima and neighboring prefectures ¹³⁷Cs concentrations in 2020, nine years after the accident, are approaching the pre-accident levels of 2010. The quick decrease is attributable to the intrusion or mixing of water masses with low ¹³⁷Cs.

How to cite: Takata, H.: Temporal trends of radio-cesium concentration in the marine environment after the Chernobyl and Fukushima Dai-ichi Nuclear Power Plant accidents, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10644, https://doi.org/10.5194/egusphere-egu22-10644, 2022.

Radioactive cesium (¹³⁷Cs) is distributed in the global ocean due to global fallout by atmospheric nuclear weapons tests, releases from reprocessing plants in Europe, and supplied to the ocean by the Fukushima Daiichi Nuclear Power Plant (1F NPP) accident. In order to detect future contamination by radionuclides, it is necessary to understand the global distribution of radionuclides such as ¹³⁷Cs. For this purpose, observed data have been summarized in a historical database (MARIS) by IAEA. The spatio-temporal density of the observations varies widely, therefore simulation by an ocean general circulation model (OGCM) can be helpful in the interpretation of these observations.

In order to clarify the behavior of ¹³⁷Cs in the global ocean, OGSM simulations were conducted. Parallel Ocean Program version 2 (POP2) of the Community Earth System Model version 2 (CESM2) is employed. The horizontal resolution is 1.125 degree of longitude, and from 0.28 degree to 0.54 degree of latitude. There are 60 vertical levels with a minimum spacing of 10 m near the ocean surface, and increased spacing with depth to a maximum of 250 m. The simulated period was from 1945 to 2030 with the circulation forced by repeating (“Normal Year”) atmospheric conditions. As input sources of ¹³⁷Cs to the model, global fallout from atmospheric nuclear tests, releases from reprocessing plants in Europe, and input from the 1F NPP accident were considered. It was assumed that the input conditions in 2020 would continue after 2020.

The simulated ¹³⁷Cs activity agrees well with the observed data in the database, especially in the Atlantic and Pacific Oceans where the observation density is large. Since ¹³⁷Cs undergoes radioactive decay with a half-life of 30 years, the inventory for each basin is the difference between the decay corrected cumulative input and flux. In the North Pacific, the inventory reached its maximum in 1966 due to the global fallout by atmospheric nuclear weapons tests. Fluxes from the North Pacific to the Indian Ocean, Arctic Ocean, and Central Pacific were positive, and the North Pacific was a source of supply for other ocean basins. The 1F NPP accident caused a 20% increase in the inventory in 2011. In the North Atlantic, the inventory reaches its maximum in the late 1970s, due to the releases from the reprocessing plant. The outflow flux from the North Atlantic to the Greenland Sea is larger than the other fluxes and is a source of supply to other ocean basins. After 2000, the inflow flux to the North Pacific from the Labrador Sea and the South Atlantic is larger than the outflow flux.

The time series of ¹³⁷Cs inventory in each ocean basin and the fluxes among ocean basins were quantitatively analyzed by OGCM simulations, and the predictions for the next 10 years were made.  The ¹³⁷Cs activity concentrations by global fallout can be detected in the global ocean after 2030. The OGCM simulations will be useful in planning future observations to fill the gaps in the database.

How to cite: Tsumune, D., Bryan, F., Lindsay, K., Misumi, K., Tsubono, T., and Aoyama, M.: Estimation of 137Cs inventories in each ocean basin by a global ocean general circulation model for the global database interpolation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11022, https://doi.org/10.5194/egusphere-egu22-11022, 2022.

Chlorine 36 (³⁶Cl, T_1/2 = 301,000 years) is a radionuclide with natural and anthropogenic origin that can be rejected accidentally during decommissioning of nuclear power plants or chronically during recycling of nuclear waste. Once emitted into the atmosphere, ³⁶Cl (gas and particles) can be transferred to the soil and vegetal cover by dry and wet deposition. However, knowledge of these deposits is very scarce. Because of its relatively high mobility in the geosphere and its high bioavailability, ³⁶Cl fate in the environment should be studied for environmental and human impact assessments. So, the objective of this work is to determine the dry deposition rates of chlorine 36 on grassland. Grass is studied, as it is a link in the human food chain via cow's milk.

In order to achieve this objective, a method for extracting the chlorine contained in plant leaves has been developed. This method consists in heating the dried and grounded plant sample in presence of sodium hydroxide. A temperature gradient up to 450°C allows the extraction to be carried out in two stages: (i) The chlorides with a strong affinity for alkaline environments are first extracted from the plant and preserved in sodium hydroxide; (ii) The organic matter is then destroyed by combustion and the sodium hydroxide crystallised. Brought out from the oven, the dry residue is dissolved in ultrapure water and chemically prepared for the measurement of chlorine 36. This extraction method was validated by its application to NIST standards of peach and apple leaves. The average extraction efficiency of chlorides was 83 ± 3%.

For the determination of dry deposition rates, 1m² of grass was exposed every 2 weeks at the IRSN La Hague technical platform (PTILH) located 2 km downwind from Orano la Hague, a chronic source of low-level chlorine 36 emissions. A mobile shelter with automatic humidity detection covered the grass during rainy episodes. In proximity to the grass, atmospheric chlorine was also sampled at the same frequency as the grass. Gaseous chlorine was sampled by bubbling in sodium hydroxide and by an AS3000 sampler containing activated carbon cartridge. Particulate chlorine was collected on a composite (teflon and glass fibre) filter. Chlorine 36 was measured by accelerated mass spectrometry ASTER (Accelerator for Earth Sciences, Environment and Risks) at CEREGE, Aix-en-Provence, France. All samples were subjected to a succession of chemical preparations in order to remove the sulphur 36 (an isobaric interferent) and to collect the chlorides in the form of AgCl pastilles. The results show a chlorine 36 deposition flux on the grass of 2.94.10² at/m².s with a deposition velocity in dry weather v_{d(gas+particles)} = 8.10^-4 m/s for a contribution of 65.5% of particulate chlorine 36 and 34.5% of gaseous chlorine 36. Based on these experimental results, a modelling of the dry and wet deposits will be carried out considering the parameters related to the canopy and the atmospheric turbulence.

How to cite: Deo, S., Hebert, D., Benedetti, L., Vitorge, E., Lourino Cabana, B., Guillou, V., and Maro, D.: Dry deposition velocity of chlorine 36 on grassland, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-666, https://doi.org/10.5194/egusphere-egu22-666, 2022.

Wet deposition has been identified as a critical impactor for the modelling of ¹³⁷Cs in the Fukushima Daiichi Nuclear power plant (FDNPP) accident. However, it is difficult to simulate due to the involvement of close interaction between various complicated meteorological and physical processes during the wet deposition process. The limitation of measurement of the in-cloud and below-cloud scavenging also contribute to the uncertainty in wet deposition modeling, leading to the great variation of ¹³⁷Cs wet deposition parameterization. These variations can be amplified further by inaccurate meteorological input, making simulation of radionuclide transport sensitive to the choice of wet scavenging parameterization. Moreover, simulations can also be influenced by differences between radionuclide transport models, even if they adopt similar parameterization for wet scavenging. Although intensively investigated, wet deposition simulation is still subject to uncertainties of meteorological inputs and wet scavenging modeling, leading to biased ¹³⁷Cs transport prediction.

To improve modeling of ¹³⁷Cs transport, both in- and below-cloud wet scavenging schemes were integrated into the Weather Research and Forecasting-Chemistry (WRF-Chem) model, yielding online coupled modeling of meteorology and the two wet scavenging processes. Overall, 25 combinations of different in- and below-cloud scavenging schemes of ¹³⁷Cs, covering most wet scavenging schemes reported in the literature, were integrated into WRF-Chem. Additionally, two microphysics schemes were compared to improve the simulation of precipitation. These 25 models and the ensemble mean of 9 representative models were systematically compared with a previous below-cloud-only WRF-Chem model, using the cumulative deposition and atmospheric concentrations of ¹³⁷Cs measurements. The findings could elucidate the range of variation among these schemes both within and across the five in-cloud groups, reveal the behaviors and sensitivities of different schemes in different scenarios.

The results revealed that the Morrison's double moment cloud microphysics scheme improves the simulation of rainfall and deposition pattern. Furthermore, the integration of the in-cloud schemes in WRF-Chem substantially reduces the bias in the cumulative deposition simulation, especially in the Nakadori and Tochigi regions where light rain dominated. For atmospheric concentration of ¹³⁷Cs, those models with in-cloud schemes that consider cloud parameters showed better and more stable performance, among which Hertel-Bakla performed best for atmospheric concentration and Roselle-Apsimon performed best for both deposition and atmospheric concentration. In contrast, the in-cloud schemes that rely solely on rain intensity were found sensitive to the meteorological conditions and showed varied performance in relation to the plume events examined. The analysis based on the spatial pattern shows that the Roselle scheme, which considers cloud liquid water content and depth, can achieve a more balanced allocation of ¹³⁷Cs between the air and the ground in these two cases than that achieved by the empirical power function scheme Environ. The ensemble mean achieves satisfactory performance except for one plume event, but still outperforms most models. The range of variation of the 25 models covered most of the measurements, reflecting the reasonable capability of WRF-Chem for modeling ¹³⁷Cs transport.

How to cite: Zhuang, S., Dong, X., and Fang, S.: Sensitivity analysis on the wet deposition parameterization for 137Cs transport modeling following the Fukushima Daiichi Nuclear Power Plant accident, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-177, https://doi.org/10.5194/egusphere-egu22-177, 2022.

The nuclear emergency response for accidental release around the nuclear power plant site (NPPs) requires a fast and accurate estimate of the influence caused by gaseous hazardous pollutants spreading, which is critical for and preventing protecting lives, creatures, and the environment. However, as usual, the NPPs is consist of dense buildings and multi-type terrain, e.g. river and mountain, which poses challenges to atmospheric dispersion calculation for response tasks. Micro-SWIFT SPRAY (MSS) comprises both the diagnostic wind model and the dispersion model, which enables the airflows and atmospheric dispersion simulation with the meteorological and other inputs. For a small-scale scenario, especially, the separate module for obstacles influence modeling provides the potential capability of precise atmospheric dispersion. But the error behavior of such a scenario around a nuclear power plant site with complex topography remains to be further demonstrated. In this study, MSS is comprehensively evaluated against a wind tunnel experiment with a 1:600 scale for the small-scale (3 km × 3km) atmospheric dispersion modeling. Tens of buildings located in this scenario of a NPPs surrounded by a mountain and river. The evaluations for diagnostic wind modeling include the speed, direction, and distribution of horizontal airflows and vertical profile of speed at a representative site. And for the concentration calculation, horizontal distribution, axis profile, and vertical profile at a representative site. The results demonstrate the MSS can reproduce fine airflows near the buildings but overestimate the wind speed. The maximum deviation of vertical speed is around 2.09 m/s at the representative site. The simulated plume of concentration reproduces the highest concentration place and matches the observations well. The axis profile of concentration is underestimated and the vertical profile displays an increasing deviation with the height increase. Compared with the observations, the FAC5 and FAC2 of concentration simulation reach 0.945 and 0.891 in the entire calculation domain, which convinces the performance of MSS in small-scale modeling.

How to cite: Dong, X., Zhuang, S., and Fang, S.: Micro-SWIFT SPRAY modeling of atmospheric dispersion around a nuclear power plant site with complex topography, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-190, https://doi.org/10.5194/egusphere-egu22-190, 2022.

All radiological measurements acquired from airborne detectors suffer from the issues of geometrical signal dilution, signal attenuation and a complex interaction of the effective sampling area of the detector system with the 3D structure of the surrounding environment. Understanding and accounting for these variables is essential in recovering accurate dose rate maps that can help protect responding workforces in radiologically contaminated environments.

Two types of terrain-cognisant methods of improving source localisation and the contrast of airborne radiation maps are presented in this work, comprising of ‘Point Cloud Constrained 3D Backprojection’ and ‘Point Cloud Constrained Randomised Kaczmarz Inversion’. Each algorithm uses a combination of airborne gamma-spectrometry and 3D scene information collected by UAS platforms and have been applied to data collected with lightweight, simple (non-imaging) detector payloads at numerous locations across the Chornobyl Exclusion Zone (CEZ).

Common to both the algorithms is the projection of the photopeak intensity onto a point cloud representation of the environment, taking into account the position and orientation of the UAS in addition to the 3D response of the spectrometer. The 3D Backprojection method can be considered a relatively fast method of mapping of through proximity, in which the measured photopeak intensity is split over the point cloud according to the above factors. It is an additive technique, with each measurement increasing the overall magnitude of the radiation field assigned to the survey area, meaning that more measurements continues to increase the total radiation of the site. The total measured intensity of the solution is then normalised according to the time spent in proximity to each point in the scene, determined by splitting and projecting the nominal measurement time at each survey point over the point cloud according to the distance from the survey position. Thus accounting for sampling biases during the survey.

The inversion approach adapts algorithms routinely used in medical imaging for the unconstrained world in which the detector is no longer completely surrounding the subject/target. A forward projection model, based on the contribution of distant point sources to the detector intensity, is used to determine the relationship between the full set of measurements and the 3D scene. This results in a hypercube of linear equations where it is assumed every point in the scene contributes to the measured intensity. The algorithm randomly adds measurements from within the aerial set and back-projects this onto the point cloud, with the initial state of the solution set to emit no radiation. After a given number of iterations, the fit of the current solution to the original measurements is assessed though a least squares method and updated when this produces a fit better than the current best estimate. This continues to happen until a minimum value is reached before the divergence of the system, representing the most confident solution. Based on examples from both simulations and real world data, the improvement in contrast of airborne maps using this inversion method can make them equivalent to ground-based surveys, even when operating at 20 m AGL and above.

How to cite: Connor, D., Megson-Smith, D., Wood, K., Mackenzie, R., Connolly, E., White, S., Russell-Pavier, F., Ryan-Tucker, M., Martin, P., Verbelen, Y., Richardson, T., Smith, N., and Scott, T.: Mapping of Post-Disaster Environments using 3D Backprojection and Iterative Inversion Methods Optimised for Limited-Pixel Gamma Spectrometers on Unoccupied Aerial Systems (UAS)., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11571, https://doi.org/10.5194/egusphere-egu22-11571, 2022.

Considerable amounts of ¹⁴C in the nuclear reactor are generated by neutrons. It accumulates in reactor components, coolant, and cleaning systems, and partly is released into the environment as gaseous releases and as liquid effluents. Two RBMK-1500 type reactors were exploited at Ignalina NPP (Lithuania) 1983-2009. Releases from NPP radiocarbon accumulated in local biosphere by photosynthesis, including terrestrial and aquatic media, as INPP used Lake Drūkšiai as a cooling pond

Temporal variation of ¹⁴C in lake ecosystem was examined by analyzing measured radiocarbon concentration of the organic compounds (Alkali soluble-AS) and alkali insoluble-AIS) derived from the layers of the Drūkšiai lake bottom sediments. The lake sediment cores were sampled in 2013 and 2019, sliced to 1 cm layers and ¹⁴C concentration was measured of every layer. AS and AIS organic fractions of sediment samples were extracted by using the acid-base-acid method.

Tree ring cores were collected from Pinus Sylvestris pines around the Ignalina NPP site at different directions and distances. Cellulose extraction was performed with BABAB (base-acid-base-acid-bleach) procedure, and all samples were graphitized and measured by a single state accelerator mass spectrometry at Vilnius Radiocarbon facility. Tree rings ¹⁴C concentration analysis provides atmospheric radiocarbon concentration in locations around the nuclear object. This analysis provides an opportunity to evaluate the impact of a nuclear object on water and terrestrial ecosystems.

The results showed a pronounced increase of ¹⁴C above background up to 17.8 pMC in the tree rings during INPP exploitation as well during decommission (since 2010) periods. According to the recorded data in 2004-2017 of the local Ignalina NPP meteorological station, the prevailing wind direction was towards the North and East during warm and light time periods. The radiocarbon released from the INPP stack dilutes when it travels in a downwind direction from the INPP. However, even 6.6 km away from the INPP, the impact of the power plant is still clearly visible. By using our created Gaussian dispersion model, the estimated annual emissions of ¹⁴C activity from the Ignalina NPP to the air vary from year to year. When only the 1st INPP reactor Unit was operating in 1985-1987, average emissions were 1.2 TBq/year. Emissions almost doubled to 2.1 TBq/year in 1988, when the 2^nd Unit became operational. Later, emission levels increased. It could be explained by the large amount of ¹⁴C accumulating in the graphite of the RBMK reactor and its gradual release.

¹⁴C concentration profile analysis of the lake bottom sediments core revealed a significant impact of the Ignalina NPP on the Drūkšiai lake ecosystem. An increase of ¹⁴C concentration in the layers of bottom sediments by 80 pMC in the AS fraction and only by 9 pMC in the AIS fraction was observed, corresponding to the period about years of 1998-2003. The maximum peak in AS of 189 pMC was reached approximately in 2001, followed by gradual lake recovery. This radiocarbon peak in the lake represents a large single one-time pollution release. The critical period was in 2000s when maintenance works of the reactors were performed.

How to cite: Maceika, E., Barisevičiūtė, R., Juodis, L., Pabedinskas, A., Ežerinskis, Ž., Šapolaitė, J., Butkus, L., and Remeikis, V.: Retrospective assessment of 14C aquatic and atmospheric releases from Ignalina Nuclear Power Plant due to exploitation of two RBMK-1500 type reactors, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11502, https://doi.org/10.5194/egusphere-egu22-11502, 2022.