Nuclear Emergency Response Research Articles

Effective population monitoring for determination of the thyroidal radioiodine content of the public following a nuclear accident in Japan

After a nuclear accident, population monitoring is necessary to determine the radiation exposure levels of the affected population. One of the monitoring components is direct thyroid measurements to assess the internal thyroid dose (mainly from 131I with a relatively short physical half-life: 8.02 days). These measurements are particularly important for young children but were not adequately performed after the 2011 Fukushima Daiichi Nuclear Power Plant (FDNPP) accident. Herein we propose a feasible and robust method to obtain as much reliable human data as possible for the dose reconstructions following a nuclear accident. The method employs three types of measurements: simplified, additional, and detailed measurements. The simplified measurements are performed using conventional NaI(Tl) survey meters to quickly triage heavily exposed individuals. The additional measurements are conducted using mobile whole-body counters to detect cesium (Cs; with longer retention in the body) as a tracer of 131I. And the detailed measurements are taken using spectrometric devices; they provide the most reliable data and are used to confirm the other measurements. We also discussed the target subjects and the monitoring period based on the experiences gained following the FDNPP accident. The early post-nuclear-accident phase is the most important period for the dose reconstruction for the affected populations; however, it is also the most challenging period in terms of allocating the necessary monitoring resources. It is thus vital that all countries that operate nuclear power plants establish and maintain a system for nuclear emergency preparedness and response.

Development of local-scale high-resolution atmospheric dispersion and dose assessment system

ABSTRACT We have developed a local-scale high-resolution atmospheric dispersion and dose assessment system (LHADDAS) for safety and consequence assessment of nuclear facilities and emergency response to nuclear accidents or deliberate release of radioactive materials in built-up urban areas. This system comprises three parts: preprocessing of input files and main calculation by a local-scale high-resolution atmospheric dispersion model using large-eddy simulation (LOHDIM-LES) and a real-time urban dispersion simulation model based on a lattice Boltzmann method (CityLBM), and postprocessing of dose calculation by a simulation code powered by lattice dose-response functions (SIBYL). LHADDAS has a broad utility and performs excellently in (1) simulating turbulent flows, plume dispersion, and dry deposition under realistic meteorological conditions; (2) simulating real-time tracer dispersion using a locally mesh-refined lattice Boltzmann method; and (3) estimating the air dose rates of radionuclides from air concentrations and surface deposition in consideration of the influence of individual buildings and structures. This system is promising for use in the safety assessment of nuclear facilities (as an alternative to wind tunnel experiments), detailed pre/post-analyses of local-scale radioactive plume dispersion in case of nuclear accidents and quick response to emergencies resulting from the deliberate release of radioactive materials by terrorist attacks in central urban district areas.

Design and simulation of a counter measure analysis system in a decision support system ONERS for nuclear emergency

In this work, a Counter Measures Analysis System (CMAS) is developed in the Online Nuclear Emergency Response System (ONERS) to suggest protective actions for minimizing radiation exposure to people during accidental releases of radionuclides to the environment. CMAS is designed with PHP, Java and MySQL database engine in Web-GIS environment to enable online computations and visualization of results. CMAS maps the dispersion model simulated radiological doses to each village unit by spatial aggregation of dose from all the grid cells contained within village unit and delineates the domain into areas assigned with several protective actions taking into account of dose criteria. It also computes residual and averted doses along with timing of different protective actions in each village. The effectiveness of CMAS is tested by simulating the consequences for a hypothetical accident. Results suggest that CMAS provides realistic estimates of protective actions following the spatial dispersion and dose pattern at each village unit. Comparison with conventional grid-based calculations indicate CMAS provides more practical suggestion of protection strategy compared to grid-based suggestions due to the conservative nature of estimates and attribution of all necessary information for emergency management. Sensitivity tests with respect to accident source term and dose criteria indicate that CMAS produces corresponding variation in impacted areas and protective actions confirming consistent performance.

Strengthening Military Defense Resources to Non-Military in Facing Nuclear Emergencies to Support National Defense

Indonesia has the potential for a nuclear emergency, so it is necessary to prepare resources to deal with nuclear emergencies to minimize losses. A nuclear emergency caused by a nuclear reactor accident is a non-military defense sector as the main component supported by other elements of the nation's power. Nuclear Biology and Chemical Company of the Indonesian Armed Forces Army (Kizinubika) is another element of the nation's power that provides reinforcement in non-military defense in the face of nuclear emergencies. The purpose of this study is to strengthen the Kizinubika resources for the Nuclear Energy Supervisory Agency (Bapeten) and the Directorate for the Management of Nuclear Facilities at the National Research and Innovation Agency (DPFKN-BRIN) in dealing with nuclear emergencies in order to support national defense. This type of research is qualitative by using literature study, observation, and interview methods. Internal resource criteria are determined based on the Resources Based View (RBV) theory. The results of the study in the form of recommended resources in strengthening the Kizinubika against Bapeten and DPFKN-BRIN in the form of; (1) The use of the Kizinubika facility as a joint training facility and infrastructure; (2) The use of special equipment Kizinubika in support of nuclear emergency response; (3) Kizinubika's strategic location close to DPFKN-BRIN supports speed in emergency response; (4) Use of Kizinubika's Human Resources through joint training in increasing the quantity and quality of training; and (5) Kizinubika's internal organizational relations support the task of dealing with nuclear emergencies.

Automated method for concurrent determination of thorium (230Th, 232Th) and uranium (234U, 235U, 238U) isotopes in water matrices with ICP-MS/MS

High-efficiency analysis of Th and U isotopes are important technical issues encountered in the fields such as environment monitoring and nuclear emergency responses.

Research on Practical Training Teaching Reform of Nuclear Accident Emergency Response Course Based on Immersive VR Technology

Aiming at the problems of backward teaching methods and poor effects of nuclear accident emergency practical training, on the basis of combing and analyzing the current situation and problems of nuclear accident emergency practical training teaching, this paper studies the technical difficulties and solutions of immersive VR technology applied to nuclear accident emergency practical training teaching, and researches and explores how immersive VR technology can be integrated into the reform of nuclear accident emergency practical training teaching.

Source term determination with elastic plume bias correction

Estimation of a source term, i.e. release rate, of atmospheric radionuclide emissions is of key interest for nuclear emergency response and further accident analysis. The source term estimate is, however, often very inaccurate due to biases in atmospheric transport and used meteorological analysis. We propose a method for atmospheric plume bias correction which uses not only concentrations modeled at a measuring site but also the information on concentration gradient from the neighborhood of each measuring site, i.e. information already available from the atmospheric transport model. To properly regularize the model, we propose an elastic model of the plume bias correction based on regularization with the use of known topology of the measurement network. The proposed plume bias correction method can be coupled with an arbitrary source term estimation algorithm and can be instantly applied to any other atmospheric release of hazardous material. We demonstrate the method in two real cases. First, we use data from the European Tracer Experiment to validate the methodology. Second, we use data from the 106Ru occurrence over Europe in 2017 to demonstrate the methodology in a more demanding case where agreement with state-of-the-art estimates is shown with much better reconstruction of measurements.

Design and performance evaluation of a 4[formula omitted]-view gamma camera with mosaic-patterned 3D position-sensitive scintillators

Gamma hotspots imaging is of dramatic demand in nuclear-related industrial and homeland security activities such as nuclear facilities monitoring, nuclear emergency response and border inspection. Gamma cameras with mechanical collimation (i.e., coded-aperture) have reduced sensitivity, limited FOV and are typically heavy-weighted. Compton cameras with electrical collimation can achieve higher sensitivity as well as being capable of performing portable 4π-view imaging. However, imageable isotopes of Compton cameras are limited to middle- or high-energy ones. We have previously proposed the concept to image gamma hotspots with a 3-D position-sensitive scintillation detector. This approach achieves high sensitivity, 4π-view FOV and is effective in a wide energy range. In this work, we present a novel gamma camera design aiming for high-resolution gamma imaging. The proposed detector consists of interspaced GAGG(Ce) scintillators that form a mosaic pattern, which is coupled to SiPM arrays on both ends. 3-D photon interaction position information is measured with a dual-end-readout technique. The measured interaction positions for detected photon events are rebinned into the projection data, and the gamma image is reconstructed using a maximum likelihood expectation maximization (MLEM) algorithm. We perform Monte Carlo simulations and experiments to evaluate the performance of the proposed gamma camera design for imaging 99mTc and 137Cs sources. Results show that the proposed gamma camera achieves a positioning accuracy of less than 1° for a 99mTc source and 3° for a 137Cs source. It can clearly resolve two 99mTc sources with 10° separation and two 137Cs point sources with 23° separation, as well as a 2 × 6 99mTc point-source-array with 20° separation clearly. We conclude that the proposed gamma camera design is profitable in portability, FOV, sensitivity, image resolution and energy range. It has promising application potential in fast and accurate radiation monitoring tasks in nuclear security applications.

Comparing model skills for deterministic versus ensemble dispersion modelling: The Fukushima Daiichi NPP accident as a case study

Atmospheric dispersion models are crucial for nuclear risk assessment and emergency response systems since they rapidly predict air concentrations and deposition of released radionuclides, providing a basis for dose estimations and countermeasure strategies. Atmospheric dispersion models are associated with relatively large and often unknown uncertainties that are mostly attributed to meteorology, source terms and parametrisation of the dispersion model. By developing methods that can provide reliable uncertainty ranges for model outputs, decision makers have an improved basis for handling nuclear emergency situations.In the present work, model skill of the Severe Nuclear Accident Programme (SNAP) model was quantified by employing an ensemble method in which 51 meteorological realisations from a numerical weather prediction model were combined with 9 source term descriptions for the accidental 137Cs releases from Fukushima Daiichi Nuclear Power Plant during 14th–17th March 2011. The meteorological forecast was compared to observations of wind speed from 30 meteorological stations.The 459 dispersion realisations were compared with hourly observations of activity concentrations from 100 air filter stations. Exclusive use of deterministic meteorology resulted in most members of the dispersion ensemble showing too low concentration values, however this was mitigated by applying ensemble meteorology. Ensemble predictions, including both the meteorological and source term ensemble, show an overall higher prediction skill compared to individual meteorology and source term runs, with true predictive rate accuracy increasing from 30%–50% to 70%–90%, with a decrease in positive predictive rate accuracy from 75%–80% to 65%–75%. Skill scores and other ensemble indicators also showed improvements in using ensembles of source terms and meteorology. From the present study on the Fukushima accident there are strong indications that ensemble predictions improve the basis for decision making in the early phase after a nuclear accident, which emphasises the importance of including ensemble prediction in nuclear preparedness tools of the future.

Validation of a modified FLEXPART model for short-range radiological dispersion and dose assessments in ONERS Decision Support System

Online Nuclear Emergency Response System (ONERS) is a GIS based Decision Support System developed for the management of Off-Site Nuclear Emergencies at Nuclear Power Plant (NPP) sites in India. As part of this development, the FLEXPART model is modified to compute atmospheric dispersion using observations from the local meteorological tower for the estimation of concentration and radiological dose over short-range range in realtime. In this work, the modified FLEXPART is validated for dose assessments using gamma dose rate measurements by Autonomous Gamma Dose Loggers installed around the Pressurized Heavy Water Reactor (PHWR) of Madras Atomic Power Station (MAPS) at Kalpakkam site in southeast India. The plume exposure dose is computed in two pathways i) cloudshine dose by incorporating a point kernel algorithm ii) submersion dose by semi-infinite plume method using FLEXPART. Comparison of model estimates with detector data for the 8-day period (01–08 December 2017) covering various atmospheric conditions indicates that the simulated cloud gamma dose rate is in good agreement with observed dose under stable, neutral, and unstable conditions with a coefficient of determination of 0.66, 0.73 and 0.49 respectively. The overestimation of dose under unstable conditions could be due to underestimation of mixed layer height (h) and convective velocity scale (w*) computed using the local similarity approach while using tower data, which needs further insights for improvements.

Multi-modal global surveillance methodology for predictive and on-demand characterization of localized processes using cube satellite platforms and deep learning techniques

Cube satellites (CubeSats) present a unique platform for monitoring localized processes anywhere within the Earth's surface or atmosphere using novel data analysis techniques. A CubeSat system equipped with adequate sensors and data analytics capabilities can provide an autonomous characterization surveillance method for the phenomena of interest. CubeSats are advantageous over conventional satellites in certain remote monitoring applications because of their reduced costs and higher simplicity due to the availability of commercially-off-the-shelf components. The CubeSat surveillance system developed in this paper focused on phenomena of interest surrounding the nuclear fuel cycle in support of nuclear non-proliferation and emergency response. To observe the phenomena, a constellation of 3U and 6U CubeSats deployed from the ISS with adequate components was chosen. Four different sensor configurations were identified for remote sensing: panchromatic/multispectral in the visible and near-infrared spectrum, multispectral in infrared spectrum, hyperspectral in infrared spectrum, and multispectral in ultraviolet spectrum. While a panchromatic/multispectral sensor configuration has CubeSat flight heritage at the required spatial resolutions, the other three sensor types need future development to meet signature and system requirements. Once each sensor onboard the CubeSat system collects data on a target of interest, the onboard computers would then apply the deep learning-based characterization methodology developed in this paper to identify phenomena. Four surrogate datasets containing representative simplified “images” were created for each sensor type to train the characterization methodology. A convolutional neural network was applied to each dataset and produced recall rates for the phenomena between 89.7% and 99.3% and precision rates between 92.3% and 99.9%. Each phenomenon's presence probability from each network is then combined into a final characterization solution for a target area. This paper covers multiple interdisciplinary areas to develop the foundation for a CubeSat surveillance system focused on phenomena surrounding the nuclear fuel cycle.

Development of local-scale high-resolution atmospheric dispersion model using large-eddy simulation part 6: introduction of detailed dose calculation method

ABSTRACT We developed a LOcal-scale High-resolution atmospheric DIspersion Model using Large-Eddy Simulation (LOHDIM-LES) for the safety assessment of nuclear facilities and emergency responses to accidental or deliberate releases of radioactive materials. In parts 1–5 of this series, the basic performance was examined by comparing with wind tunnel or field experimental results on plume dispersion over various complex surface geometries under ideal and realistic atmospheric conditions. In this study, we introduced a dose calculation method that can simulate air dose rate distributions by considering shielding effects and inhomogeneous distribution of radioactive materials in the air and on the ground and building surfaces. First, we conducted LESs of radioactive plume dispersion and dry deposition in building array and investigated the basic performance of the dose calculation method by comparison with that of Monte-Carlo based three-dimensional radiation transport simulations by Particle and Heavy-Ion Transport code System (PHITS). Then, we compared the LOHDIM-LES results with actual air dose rate obtained from the monitoring posts in a nuclear facility. The observed data were reasonably simulated. Thus, we completed LOHDIM-LES, which can simulate plume dispersion, dry deposition, and air dose rates from complex distributions of radionuclides considering the influence of individual buildings under realistic meteorological conditions.

Multi-scenario validation of CALMET-RIMPUFF for local-scale atmospheric dispersion modeling around a nuclear powerplant site with complex topography

The CALMET-RIMPUFF is composed of the California Meteorological Model and the Risø Mesoscale PUFF model, which provides refined atmospheric dispersion modeling for nuclear emergency response. Because the performance of an atmospheric dispersion model can be case-sensitive, a multi-scenario validation is important to understand a model's behavior and limits. In this study, a multi-scenario validation of CALMET-RIMPUFF was performed based on six wind tunnel experiments simulating a real China's nuclear powerplant site with complex topographies and dense buildings. The CALMET-RIMPUFF simulations were compared with the measurements of the vertical wind profiles, 2D ground wind and concentration fields, both qualitatively and quantitatively. The results demonstrate that the CALMET-RIMPUFF can simulate the ground-level wind with acceptable accuracies. For vertical wind profiles, the accuracies show high dependencies on the local topography and building layout. The simulated ground concentrations generally agree well with the measurements, though the plume axis showed slight discrepancies from the measurements in three cases. Because the CALMET-RIMPUFF lacks a building effect module, it shows noticeable discrepancies in the building area. However, such discrepancies do not propagate to the downwind mountainous and sea areas, which the accuracies are quite satisfactory. Thus, the CALMET-RIMPUFF is capable for local-scale modeling at this site.

Enhancing neutron radiation resistance of silicon-based semiconductor devices through isotope separation and enrichment

Different isotopes may exhibit different resistance against the displacement damage induced by neutron radiations. To examine the difference in silicon isotopes, we calculate the damage functions of 28Si, 29Si, 30Si and the natural silicon under intermediate neutron (10−6–0.1 MeV) and fast neutron (>0.1 MeV) radiations based on radiation damage theory and the Neutron Nuclear Reaction Evaluation Database (ENDF/B-VIII.0). Their accumulative displacement per atom (DPA) values under the neutron radiation of nuclear accident emergency response or cosmic space are also investigated. The calculated radiation damage functions and DPAs indicate that 30Si endures at least 10–15% less displacement damage compared with 28Si, 29Si and the natural silicon under intermediate and fast neutron radiations. Therefore, we propose to use 30Si-enriched silicon in semiconductor devices to enhance the neutron radiation resistance and extend the service life in radiative circumstances.

A prototype of SiPM-based scintillator Compton camera with capacitive multiplexing readout

Compton camera is capable of visualizing the distribution of radioactivity based on the Compton scattering kinematics, and can be applied in nuclear accident emergency response, radioactivity decontamination, homeland security and etc. A prototype of Compton camera has been constructed consisting of two 4×4 SiPM-Ce: GAGG scintillator arrays. The signals of a SiPM array were converted into 4 position-weighted outputs with capacitive network circuit and collected by a CAEN digitizer. Two-dimensional flood images and energy responses of two detector modules were obtained. The average energy resolution of single elements of the two detector modules was 6.6% FWHM at 662 keV. Imaging performance of the prototype camera was evaluated with a 137Cs point source and a 22Na point source. Efficiency of the prototype for the 137Cs point source located right in front was measured to be 0.09%. The angular resolution of a 137Cs point source placed right in front of the camera was 7.2° FWHM. Isotopic images of the two gamma-ray sources were obtained with spatial resolutions of 8.2° FWHM for 137Cs and 8.8° FWHM for 22Na.

Моделювання вторинного радіоактивного забруднення повітря в Україні внаслідок вітрового під-йому радіонуклідів.

The paper presents the results of the simulation of secondary air pollution scenario in Ukraine due to the wind lift of anthropogenic radionuclides during a dust storm in April 2020. A variant of the Bagnold formula was used to parameterize the intensity of radionuclide resuspension. To set the initial pollution of the territory of Ukraine, the reconstruction of meteorological conditions and fallout of Cs-137 after the disaster at the Chernobyl nuclear power plant was carried out through the use of the RODOS nuclear emergency response system and the WRF meteorological model. For the normalized root-mean-square error of the calculated total fallout in the 50-km zone around the Chernobyl NPP the value NMSE=4,5 was obtained. A decrease in the levels of pollution of the Earth's surface during the time after the accident due to radioactive decay and other environmental processes was estimated. The distribution of contamination of the Earth's surface obtained in this way was used to assess the intensity of wind rise and atmospheric transport of radionuclides during a dust storm on April 16–18, 2020. The calculations were carried out using the CALPUFF model. The input meteorological data were the results of the WRF-Ukraine weather forecasting system. In the calculation of secondary contamination, the effect of fires in the Chernobyl Exclusion Zone (ChEZ) was not taken into account. The calculated average daily concentrations of Cs-137 in the air were maximum for the first day of the dust storm (April 16), when the wind speed was maximum (13 m/s with gusts up to 19 m/s). Average daily concentrations on April 16 ranged from the background values (5,8·10-6 Bq/m3 in Kyiv) to 2,2·10-3 Bq/m3 (ChNPP). The obtained estimates are much less than the permissible concentrations (0.8 Bq/m3). At the same time consideravle exceedance of background values were predicted in a large part of Ukraine – from Rivne NPP (2,2·10-5 Bq/m3) to Kharkiv (1,3·10-5 Bq / m3). In the vicinity of the ChEZ in the cities of Chernihiv and Slavutich, the obtained estimates of daily average concentration were 1,6·10-4 Bq/m3 and 3,2·10-4 Bq/m3 respectively.

Методи та інформаційні системи ідентифікації джерел радіоактивних атмосферних за-бруднень шляхом оберненого моделювання

The paper reviews the methods for identifying an unknown source of pollution by inverse mod-eling and information systems for air pollution forecasting and analysis. Several different for-eign and Ukrainian air pollution forecasting systems, such as the European Union's Nuclear Emergency Response System RODOS, have been developed on the basis of atmospheric transport models. However, the key data that determine the quality of forecasting in such sys-tems are the characteristics of the emission sources. In the case of detection of pollution from an unknown emission source, there should be performed inverse simulation. The use of the RODOS system, as well as other existing forecasting systems for such a task is possible but it requires multiple manual start of calculations of atmospheric transfer models in the reverse mode. Presented in the paper results of the application of inverse modeling methods during ra-diation incidents of the last decade demonstrate that modern methods of inverse modeling are sufficiently developed to set the task of automating inverse modeling in information systems for air pollution analysis and forecasting. Even though these methods not always can exactly identify the source of emissions due to the lack of measurements and poor conditioning of the inverse atmospheric transport problem, their application always leads to a significant reduction (by an order of magnitude or more) in the search for unknown sources compared to the detec-tion of pollutants. At present, in the existing forecasting systems the methods of inverse model-ing are only partially automated, namely for the case of known location and unknown emissions of the source of pollution. Therefore, this paper proposes the architecture of the future system for identifying unknown sources of emissions by inverse modeling.

A Simple Survey of the Preparation Situation for Resident's Evacuation in Japanese Prefectures After the Fukushima Daiichi Nuclear Power Plant Accident.

The Japanese government formulated the Nuclear Emergency Response Guidelines in response to the Fukushima Daiichi Nuclear Power Plant accident (FDNPP accident) caused by the Great East Japan Earthquake in March 2011. Under these guidelines, Japan has established its current nuclear disaster response system. This manuscript outlines the transition of Japan's nuclear disaster response system before and after the FDNPP accident and also shows the results of a questionnaire survey on the level of preparation the prefecture currently has for the evacuation of residents at the time of a nuclear disaster. About 70% of the prefectures where nuclear facilities are located or adjacent have completed or are in the process of completing evacuation plans, and all except one indicated they have the equipment needed to perform radiation contamination inspections of residents. These results suggest that activities are taking place throughout Japan to build a new disaster response system. It will be important to verify whether the evacuation manuals prepared by prefectural governments are effective through large-scale training and to develop human resources for performing radiation contamination inspections of evacuating residents.

Projecting thyroid cancer risk to the general public from radiation exposure following hypothetical severe nuclear accidents in Canada

A robust emergency management framework can limit radiation exposures and effectively minimise the potentially devastating consequences of a nuclear emergency. We projected thyroid cancer risk resulting from two hypothetical severe nuclear accidents occurring at the Darlington nuclear power plant (NPP) located in Ontario, Canada. Single- and multi-unit accidents were considered. A dose assessment was previously performed using the MELCOR Accident Consequences Code System. The generic criteria used to select the appropriate protective actions are described in the Ontario Provincial Nuclear Emergency Response Plan (PNERP). We hypothesised protection actions only within the 10 kilometre (km) radius of the NPP given the time sensitivity of iodine thyroid blocking. The excess risk of developing thyroid cancer was projected using the US National Cancer Institute’s radiation risk assessment tool RadRAT. We projected zero dose, and subsequently zero risk of developing thyroid cancer for people living within 10 km of the NPP, due to effective implementation of selected protective actions. Based on centreline doses, at the 12 km radius, excess childhood thyroid cancer risks for a one-year-old female as the most critical receptor were projected to be approximately 600% and 130% compared to the baseline were projected for the single- and multi-unit scenarios, respectively. The risk of developing thyroid cancer was projected to be low for adults for both scenarios. The results of this modelling study provide insights into the effectiveness of protective actions in reducing radiation-related thyroid cancer risk when considering hypothetical severe nuclear accidents. Implementation of select protective actions protects the population living near the Darlington NPP. The projected increase of developing thyroid cancer for children living beyond 10 km could potentially be eliminated with additional mitigation measures specified in the PNERP.

Design of a mobile dissolved air flotation system with high rate for the treatment of liquid radioactive waste

The global trend towards sustainable development with low carbon emissions has encouraged the expansion of nuclear energy. The nuclear reactors, under normal operating conditions or radiological emergency, generate different types of radioactive waste, mainly liquids and solids that require efficient and mobile treatment systems. This work presents the design proposal of a mobile dissolved air flotation system (mDAF) with a high rate for the treatment of liquid radioactive waste generated in the attention and response to radiological post-emergencies of nuclear power plants or environmental emergency responses associated with oil spills. The evidence obtained showed that the design used allows to reach, under the conditions of the experiment tested, removal levels higher than 95 % in the concentrations of oil waste, SO4−2, NO3-, PO3-3, Ni and Cr. Removal levels of approximately 94 % and 75 % for the total Co and 60Co, respectively, were achieved. It was possible to demonstrate the feasibility of designing a mDAF of low cost with enough versatility to treat radioactive liquid waste generated in a radiological post-emergency.