Radionuclide atmospheric transport after the forest fires in the Chernobyl Exclusion zone in 2015-2018: An impact of the source term parameterization and input meteorological data on modeling results

2020 ◽  
Author(s):  
Mykola Talerko ◽  
Ivan Kovalets ◽  
Shigekazu Hirao ◽  
Mark Zheleznyak ◽  
Yuriy Kyrylenko ◽  
...  
Keyword(s):  
Real Time ◽  
Forest Fires ◽  
Source Term ◽  
Atmospheric Transport ◽  
Meteorological Data ◽  
Atmospheric Dispersion ◽  
Lagrangian Model ◽  
Wildland Fires ◽  
Exclusion Zone ◽  
The Impact

<p>The highly contaminated Chernobyl exclusion zone (ChEZ) still remains a potential source of the additional atmosphere radioactive contamination due to forest fires there. The possible radionuclide transport outside the ChEZ in the direction of populated regions (including Kyiv, 115 km from the ChEZ borders) and its consequences for people health is a topic of a constant public concern in Ukraine and neighboring countries. The problem of additional radiation exposure of fire-fighters and other personnel within the ChEZ during forest fires is actual too. The reliable models of radionuclide rising and following atmospheric transport, which should be integrated with data of stationary and mobile radiological monitoring, are necessary for real-time forecast and assessment of consequences of wildland fires.</p><p>Results of intercomparison of models developed within the set of the national and international projects are presented, including: i) the point source term model of Atmospheric Dispersion Module (ADM) of the real -time online decision support system for offsite nuclear emergency – RODOS, which development was funded by EU; ii) the specialized new tool for modeling radionuclide dispersion from the polygons of the fired areas using the Lagrangian model LASAT incorporated into RODOS system; iii) the Lagrangian-Eulerian atmospheric dispersion model LEDI using a volume source term and including a module for calculation of  parameters of a convective plume  formed over a fire area; iv) the Lagrangian model of Fukushima University. All atmospheric transport models use the results of the numerical weather forecast model WRF as the input meteorological information.</p><p>The models evaluation was carried out using the measurement data during large wildland fires occurred in ChEZ in 2015 and June 2018, including the <sup>137</sup>Cs and <sup>90</sup>Sr volume activity measured with the monitoring network within the Zone and results due to special measurements with a mobile radiological laboratory outside it.</p><p>The sensitivity of atmospheric transport modeling results was estimated to: 1) internal parameterization of different models, first of all, parameterization of the value of the deposited radionuclide fraction re-entering into the atmosphere during forest fires, 2) different parameterization of the source term formed due to the forest fire; 3) quality of input meteorological information, including the space and time step of the used WRF model grid, and the impact of chosen parameterization of some WRF modules (e.g. the atmospheric boundary layer module) on the atmospheric transport model results. Additionally, results of forest fires consequences modeling was compared which were obtained with different sets of input meteorological data: the WRF forecast of metrological fields (on-line calculations) and the similar WRF calculations on the base of objective analysis results.</p>

Exploring forecast variability during volcanic ash cloud events 

2021 ◽  
Author(s):  
Frances Beckett ◽  
Ralph Burton ◽  
Fabio Dioguardi ◽  
Claire Witham ◽  
John Stevenson ◽  
...  
Keyword(s):  
Real Time ◽  
Volcanic Ash ◽  
Atmospheric Transport ◽  
Dispersion Model ◽  
Meteorological Data ◽  
Atmospheric Dispersion ◽  
Dispersion Models ◽  
British Geological Survey ◽  
Volcanic Ash Cloud ◽  
Ash Cloud

<p>Atmospheric transport and dispersion models are used by Volcanic Ash Advisory Centers (VAACs) to provide timely information on volcanic ash clouds to mitigate the risk of aircraft encounters. Inaccuracies in dispersion model forecasts can occur due to the uncertainties associated with source terms, meteorological data and model parametrizations. Real-time validation of model forecasts against observations is therefore essential to ensure their reliability. Forecasts can also benefit from comparison to model output from other groups; through understanding how different modelling approaches, variations in model setups, model physics, and driving meteorological data, impact the predicted extent and concentration of ash. The Met Office, the National Centre for Atmospheric Science (NCAS) and the British Geological Survey (BGS) are working together to consider how we might compare data (both qualitatively and quantitatively) from the atmospheric dispersion models NAME, FALL3D and HYSPLIT, using meteorological data from the Met Office Unified Model and the NOAA Global Forecast System (providing an effective multi-model ensemble). Results from the model inter-comparison will be used to provide advice to the London VAAC to aid forecasting decisions in near real time during a volcanic ash cloud event. In order to facilitate this comparison, we developed a Python package (ash-model-plotting) to read outputs from the different models into a consistent structure. Here we present our framework for generating comparable plots across the different partners, with a focus on total column mass loading products. These are directly comparable to satellite data retrievals and therefore important for model validation. We also present outcomes from a recent modelling exercise and discuss next steps for further improving our forecast validation.</p>

Modeling study of the atmospheric transport of radioactivity after wildland fires and a dust storm in the Chernobyl Exclusion Zone in April 2020

2021 ◽  
Author(s):  
Mykola Talerko ◽  
Tatiana Lev ◽  
Ivan Kovalets ◽  
Mark Zheleznyak ◽  
Yasunori Igarashi ◽  
...  
Keyword(s):  
Effective Dose ◽  
Forest Fires ◽  
Dust Storm ◽  
Emission Factor ◽  
Atmospheric Transport ◽  
Internal Exposure ◽  
Radioactive Aerosol ◽  
Wildland Fires ◽  
Exclusion Zone ◽  
Chernobyl Npp

<p>In April 2020, the largest forest fire occurred in the Chernobyl Exclusion Zone (ChEZ) in its history. The results of modeling the atmospheric transport of radioactive aerosols released into the atmosphere as a result of wildland fires in the ChEZ and around it are presented. The atmospheric transport model LEDI, developed at the Institute for Safety Problems of NPPs, and the Atmospheric Dispersion Module of the real -time online decision support system for offsite nuclear emergency RODOS, which development was funded by the EU, were used. The <sup>137</sup>Cs activity concentration in the surface air is calculated on a regional scale (in Ukraine) and a local scale (within the ChEZ). The <sup>137</sup>Cs activity in the surface air of Kyiv (115 km from the ChEZ borders) is found to have reached 2–4 mBq m<sup>−3</sup> during the period April 3–20. The modeling results are generally consistent with measured data pertaining to radioactive contamination in Kyiv, within the ChEZ, and areas around four operating nuclear power plants in Ukraine.</p><p>A method for estimating the radionuclide activity emissions during wildland fires in radioactively contaminated areas is proposed. This method is based on satellite data of the fire radiative power (FRP), the radionuclide inventory in the fire area, and an emission factor for radioactive particles. A method was applied for forest fires in the ChEZ in April 2020. Preliminary estimations of an emission factor are made using FRP values obtained from NASA's MODIS and VIIRS active fire products.</p><p>On April 16, 2020, a strong dust storm was observed in the ChEZ, which coincided with the period of intense wildland fires. The additional <sup>137</sup>Cs activity raised by the dust storm from burned areas in the meadow biocenoses was estimated to be about 162 GBq, i.e. up to 20% of the total activity emitted into the air during the entire period of forest fires on April 3-20, 2020. According to the modeling results, during April 16-17, the input of resuspension of radioactive particles due to a dust storm was up to 80-95% of the total <sup>137</sup>Cs activity in the surface air near the Chernobyl NPP. In Kyiv, this value decreased to only about 4%.</p><p>The total effective dose to the population of Kyiv during the fire period is estimated to be 5.7 nSv from external exposure and the inhalation of <sup>137</sup>Cs and <sup>90</sup>Sr, rising to 30 nSv by the end of 2020. This is about 0.003% of the annual permissible level of exposure of the population. A committed effective dose up to 200-500 nSv is estimated for the personnel of the Chernobyl NPP from the radioactive aerosol inhalation during the 2020 forest fires, which is not more than 0.05% of the established control levels of internal exposure for them.</p>

scholarly journals The Environmental Effects of the April 2020 Wildfires and the Cs-137 Re-Suspension in the Chernobyl Exclusion Zone: A Multi-Hazard Threat

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 467
Author(s):  
Rocío Baró ◽  
Christian Maurer ◽  
Jerome Brioude ◽  
Delia Arnold ◽  
Marcus Hirtl
Keyword(s):  
Air Quality ◽  
Nuclear Power ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Point Of View ◽  
Plume Dispersion ◽  
Exclusion Zone ◽  
Fire Plume ◽  
Mean Values ◽  
The Impact

This paper demonstrates the environmental impacts of the wildfires occurring at the beginning of April 2020 in and around the highly contaminated Chernobyl Exclusion Zone (CEZ). Due to the critical fire location, concerns arose about secondary radioactive contamination potentially spreading over Europe. The impact of the fire was assessed through the evaluation of fire plume dispersion and re-suspension of the radionuclide Cs-137, whereas, to assess the smoke plume effect, a WRF-Chem simulation was performed and compared to Tropospheric Monitoring Instrument (TROPOMI) satellite columns. The results show agreement of the simulated black carbon and carbon monoxide plumes with the plumes as observed by TROPOMI, where pollutants were also transported to Belarus. From an air quality and health perspective, the wildfires caused extremely bad air quality over Kiev, where the WRF-Chem model simulated mean values of PM2.5 up to 300 µg/m3 (during the first fire outbreak) over CEZ. The re-suspension of Cs-137 was assessed by a Bayesian inverse modelling approach using FLEXPART as the atmospheric transport model and Ukraine observations, yielding a total release of 600 ± 200 GBq. The increase in both smoke and Cs-137 emissions was only well correlated on the 9 April, likely related to a shift of the focus area of the fires. From a radiological point of view even the highest Cs-137 values (average measured or modelled air concentrations and modelled deposition) at the measurement site closest to the Chernobyl Nuclear Power Plant, i.e., Kiev, posed no health risk.

Evaluation of the performance of different short-range atmospheric dispersion models for the monitoring of CH4 emissions from industrial facilities

2021 ◽  
Author(s):  
Bonaventure Fontanier ◽  
Pramod Kumar ◽  
Grégoire Broquet ◽  
Christopher Caldow ◽  
Olivier Laurent ◽  
...  
Keyword(s):  
High Frequency ◽  
Meteorological Data ◽  
Atmospheric Dispersion ◽  
Local Scale ◽  
Lagrangian Model ◽  
Dispersion Models ◽  
Industrial Facilities ◽  
Gaussian Plume ◽  
Gaussian Puff ◽  
Gaussian Puff Model

<p>Methane (CH<sub>4</sub>) is a powerful greenhouse gas which plays a major role in climate change. The accurate monitoring of emissions from industrial facilities is needed to ensure efficient emission mitigation strategies. Local-scale atmospheric inversions are increasingly being used to provide estimates of the rates and/or locations of CH<sub>4</sub> sources from industrial sites. They rely on local-scale atmospheric dispersion models, CH<sub>4</sub> measurements and inversion approaches. Gaussian plume models have often been used for local-scale atmospheric dispersion modelling and inversions of emissions, because of their simplicity and good performance when used in a flat terrain and relatively constant mean wind conditions. However, even in such conditions, failure to account for wind and mole fraction variability can limit the ability to exploit the full potential of these measurements at high frequency.</p><p>We study whether the accuracy of inversions can be increased by the use of more complex dispersion models. Our assessments are based on the analysis of 25 to 75-min CH<sub>4 </sub>controlled releases during a one-week campaign in October 2019 at the TOTAL’s TADI operative platform in Lacq, France (in a flat area). During this campaign, for each controlled release, we conducted near-surface in situ measurements of CH<sub>4</sub> mole fraction from both a mobile vehicle and a circle of fixed points around the emission area. Our inversions based on a Gaussian model and either the mobile or fixed-point measurements both provided estimates of the release rates with 20-30% precision.  </p><p>Here we focus on comparisons between modeling and inversion results when using this Gaussian plume model, a Lagrangian model “GRAL” and a Gaussian puff model. The parameters for the three models are based on high-frequency meteorological values from a single stationary 3D sonic anemometer. GRAL should have relatively good skills under low-wind speed conditions. The Gaussian puff is a light implementation of time-dependent modeling and can be driven by high-frequency meteorological data. The performance of these dispersion models is evaluated with various metrics from the observation field that are relevant for the inversion. These analyses lead to the exploration of new types of definitions of the observational constraint for the inversions with the Gaussian puff model, when using the timeseries from fixed measurement points. The definitions explore a range of metrics in the time domain as well as in the frequency domain.</p><p>Eventually, the Lagrangian model does not outperform the Gaussian plume model in these experiments, its application being notably limited by the short scales of the transport characteristics. On the other hand, the Gaussian puff model provides promising results for the inversion, in particular, in terms of comparison between the simulated and observed timeseries for fixed stations. Its performance when driven by a spatially uniform wind field is an incentive to explore the use of meteorological data from several sonic stations to parameterize its configuration. The fixed-point measurements are shown to allow for more robust inversions of the source location than the mobile measurements, with an average source localization error of the order of 10 m.</p>

scholarly journals Estimation of the Contribution of Dust Storm on April 16, 2020 to Radioactive Contamination of the Atmosphere During Forest Fires in the Exclusion Zone

2021 ◽  
Vol 20 ◽  
pp. 81-95
Author(s):  
M. M. Таlerko ◽  
◽  
Т. D. Lev ◽  
V. O. Кashpur ◽  
◽  
...  
Keyword(s):  
Forest Fires ◽  
Dust Storm ◽  
Nuclear Power ◽  
Activity Concentration ◽  
Total Activity ◽  
137Cs Activity ◽  
Wildland Fires ◽  
Exclusion Zone ◽  
137Cs Activity Concentration ◽  
Burned Areas

On April 16, 2020, a strong dust storm was observed in the northern regions of Ukraine, which coincided with the period of intense wildland fires in the Chornobyl exclusion zone. The activity of 137Cs in aerosol particles released into the atmosphere as a result of resuspension from burned areas in the meadow biocenoses in the exclusion zone is evaluated in the article. Resuspension of radioactively contaminated particles from burned areas formed after fires in meadow biocenoses of the exclusion zone can be a powerful source of air contamination in the zone itself, as well as increase of the radionuclides transport outside it. The total 137Cs activity that entered the atmosphere during the dust storm was estimated to be about 162 GBq, i. e. up to 20% of the total activity emitted in the air during the entire period of forest fires on April 3–20, 2020. The 137Cs emission from burned areas during the dust storm on April 16 and 17 amounted to 0.24% of the total stock of 137Cs activity in this territory. According to the results of modeling, the relative contribution of wildland fires and resuspension due to the dust storm on April 16 and 17 significantly depends on the distance to the emission sources. It was found that the resuspension of radioactive particles from burned areas during the dust storm determined 80–95% of the 137Cs activity concentration in the surface air near Chornobyl nuclear power plant and in Chornobyl city and the rest was due to the continuing forest fires in neighboring territories. The maximum 3-hour averaged value of the 137Cs activity concentration in the air due to resuspension from the burned areas was obtained for the location of the monitoring post VRP-750 of SSE “Ecocenter” to be about 28 mBq/m3 for the period 9–12 hours on April 16. In Kyiv, the 3-hour averaged 137Cs activity concentration due to the dust storm in the Exclusion Zone was calculated as 44 μBq/m3 in the period from 9 to 12 hours on April 17, 2020. This value was only about 4% of the total 137Cs activity in the air in this period.

scholarly journals An important fingerprint of wildfires on the European aerosol load

2011 ◽  
Vol 11 (20) ◽  
pp. 10487-10501 ◽  
Author(s):  
F. Barnaba ◽  
F. Angelini ◽  
G. Curci ◽  
G. P. Gobbi
Keyword(s):  
Eastern Europe ◽  
Central Europe ◽  
Forest Fires ◽  
Fine Fraction ◽  
Western Mediterranean ◽  
Radiation Budget ◽  
The Arctic ◽  
Wildland Fires ◽  
Continental Scale ◽  
The Impact

Abstract. Wildland fires represent the major source of fine aerosols, i.e., atmospheric particles with diameters <1 μm. The largest numbers of these fires occur in Africa, Asia and South America, but a not negligible fraction also occurs in Eastern Europe and former USSR countries, particularly in the Russian Federation, Ukraine and Kazakhstan. Besides the impact of large forest fires, recent studies also highlighted the crucial role played by routine agricultural fires in Eastern Europe and Russia on the Arctic atmosphere. An evaluation of the impact of these fires over Europe is currently not available. The assessment of the relative contribution of fires to the European aerosol burden is hampered by the complex mixing of natural and anthropogenic particle types across the continent. In this study we use long term (2002–2007) satellite-based fires and aerosol data coupled to atmospheric trajectory modelling in the attempt to estimate the wildfires contribution to the European aerosol optical thickness (AOT). Based on this dataset, we provide evidence that fires-related aerosols play a major role in shaping the AOT yearly cycle at the continental scale. In general, the regions most impacted by wildfires emissions and/or transport are Eastern and Central Europe as well as Scandinavia. Conversely, a minor impact is found in Western Europe and in the Western Mediterranean. We estimate that in spring 5 to 35% of the European fine fraction AOT (FFAOT) is attributable to wildland fires. The estimated impact maximizes in April (20–35%) in Eastern and Central Europe as well as in Scandinavia and in the Central Mediterranean. An important contribution of wildfires to the FFAOT is also found in summer over most of the continent, particularly in August over Eastern Europe (28%) and the Mediterranean regions, from Turkey (34%) to the Western Mediterranean (25%). Although preliminary, our results suggest that this fires-related, continent-wide haze plays a not negligible role on the European radiation budget, and possibly, on the European air quality, therefore representing a clear target for mitigation.

Simulation study of radionuclide atmospheric transport after wildland fires in the Chernobyl Exclusion Zone in April 2020

2021 ◽  
Author(s):  
Mykola Таlerko ◽  
Ivan Коvalets ◽  
Тatiana Lev ◽  
Yasunori Igarashi ◽  
Olexandr Romanenko
Keyword(s):  
Simulation Study ◽  
Atmospheric Transport ◽  
Wildland Fires ◽  
Exclusion Zone

scholarly journals Real-time measurement of radionuclide concentrations and its impact on inverse modeling of <sup>106</sup>Ru release in the fall of 2017

2020 ◽  
Author(s):  
Ondřej Tichý ◽  
Miroslav Hýža ◽  
Václav Šmídl
Keyword(s):  
Real Time ◽  
Temporal Resolution ◽  
Inverse Modeling ◽  
Source Term ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Monitoring Data ◽  
The Real ◽  
Concentration Measurements ◽  
Atmospheric Transport Model

Abstract. Abstract Low concentrations of 106Ru were detected across Europe at the turn of September and October 2017. The origin of 106Ru has still not been confirmed; however, current studies agree that the release occurred probably near Mayak in the southern Urals. The source reconstructions are mostly based on an analysis of concentration measurements coupled with an atmospheric transport model. Since reasonable temporal resolution of concentration measurements is crucial for proper source term reconstruction, the standard one week sampling interval could be limiting. In this paper, we present an investigation of the usability of the newly developed AMARA and CEGAM real-time monitoring systems, which are based on the gamma-ray counting of aerosol filters. These high resolution data were used for inverse modeling of the 106Ru release. We perform backward runs of the Hysplit atmospheric transport model driven with meteorological data from the global forecast system (GFS) and we construct a source-receptor sensitivity (SRS) matrix for each grid cell of our domain. Then, we use our least-squares with adaptive prior covariance (LS-APC) method to estimate possible locations of the release and the source term of the release. On Czech monitoring data, the use of concentration measurements from the standard regime and from the real-time regime is compared and better source reconstruction for the real-time data is demonstrated in the sense of the location of the source and also the temporal resolution of the source. The estimated release location, Mayak, and the total estimated source term, 237 ± 107 TBq, are in agreement with previous studies. Finally, the results based on the Czech monitoring data are validated with the IAEA reported dataset with a much better spatial resolution, and the agreement between the IAEA dataset and our reconstruction is demonstrated.

Waldbrandmanagement im Kanton Wallis und Lehren aus dem Brand von Visp im Jahr 2011

2019 ◽  
Vol 170 (5) ◽  
pp. 251-257
Author(s):  
Philipp Gerold
Keyword(s):  
Forest Fires ◽  
Fire Management ◽  
Meteorological Data ◽  
Fire Danger ◽  
Fire Prevention ◽  
Good Test ◽  
Forest Protection ◽  
Management Concept ◽  
Prevention Activities ◽  
The Impact

Fire management in the canton of Valais and lessons learnt from the Visp fire 2011 Long-lasting dry weather conditions without precipitation in the Valais make the area very prone to forest fires. Following the large fire in Leuk in summer 2003, the cantonal authorities developed between 2006 and 2008 a fire management concept mainly focusing on prevention activities and on completing the water points net on the whole territory. A very important outcome of this concept is the definition of priority regions where a detailed fire prevention and control concept should be implemented. Concerning the fire danger rating, the canton of Valais acquired the “Incendi” system from the canton of Grisons, which uses meteorological data from the MeteoSwiss weather stations network to provide a daily calculation of several fire weather indices. In case of high fire danger, a fire ban in the open can be decreed basing on the cantonal fire law. The 110 ha large forest fire in Visp (2011) represented a very good test for the new cantonal fire management concept, especially for what concerns the impact on the forest protection functions. The very dry 2018 summer and the forecasted climatic change will in the future give a very central role to the fire prevention activities.

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