A significant challenge in the treatment of low-level radioactive wastewater is the effective purification of low-concentration radionuclides.Silica-based adsorbents are advantageous for the deep-purification of low-concentration metal ions.This study investigates three primary types of silica-based adsorbents: functionalized mesoporous silica, various modified zeolites, and mesoporous calcium silicate hydrate (C-S-H).These adsorbents were synthesized and their deep-purification effects on heavy metals and radionuclides were compared.The results indicated that mesoporous silica showed relatively poor adsorption for most metal ions.Zeolites outperformed mesoporous silica, with Zn framework-modified zeolites showing enhanced adsorption for several metal ions.Notably, C-S-H displayed superior adsorption performance, achieving high adsorption capacities for various metal ions and radionuclides.Specifically, at a dose of 0.5 g/L, the adsorption efficiency of C-S-H for numerous radionuclides in nuclear power plant wastewater exceeded 92-99%, highlighting its potential for practical applications.An in-depth anal. of the phys. and chem. structure and the adsorption mechanisms of C-S-H revealed its large mesoporous structure and electrostatic attraction to cations across a wide pH range.Multivalent cations were removed through exchange with Ca²⁺ in C-S-H, whereas monovalent cations were removed through exchange with Na⁺ in C-S-H.The cyclic structure of silica-oxygen tetrahedra in C-S-H, which promotes large pore formation and provides abundant ion exchange sites, underpins its excellent adsorption properties.This study offers valuable insights for the selection and application of silica-based materials in radioactive wastewater treatment.

01 Apr 2025·Radiation Physics and Chemistry

Postulated nuclear power plant accident in the Po valley (Italy) and application of the ICRP publication 146 recommendations

Author: D′Arienzo, Marco ; Biancotto, Sergio

A large release of radioactive material, consequence of a supposed nuclear power plant (NPP) accident, is simulated in the densely populated and productive area of the Italian Po Valley, using wind speed and atm. stability conditions characteristic of the region.The first step of the anal. is the evaluation of the dose received by the public during the plume passage through the HotSpot code.The second step is the calculation of dose in the years following the accident through the RESRAD-ONSITE code, considering soil and food-chain contamination.The third step is the dose reduction obtained with protective actions, mainly iodine prophylaxis and shelter in place.Recommendations contained in the International Commission on Radiol. Protection (ICRP) Publication 146 are applied, with the goal of maintaining the public dose below the ICRP recommended Reference Levels.The influence of the height of the release is also analyzed.Without implementing protective measures, the public may be exposed to a dose of up to 2.9 x 10² mSv, although this is confined to a fairly restricted area.However, the dose can be greatly reduced by appropriate and preplanned protective actions.The use of ICRP Reference Levels is of overwhelming importance in guiding protective actions and helping authorities to make balanced decisions.

01 Feb 2025·Nuclear Engineering and Design

Comparative radiological impact of LOCA and RDD scenarios: An AI-enhanced assessment using HotSpot code

Author: Najar, Merouane ; Ali, Mohsen M. M. ; Lilia, Djebara ; Maglas, Najeeb N. M. ; Fadul, Alaa ; Qiang, Zhao ; Alwarqi, M. Salah ; AL-Osta, Ahmed

This study provides a comprehensive radiol. assessment of two hypothetical incidents: a Loss of Coolant Accident (LOCA) at a nuclear reactor and a Radiol. Dispersal Device (RDD) detonation, both simulated in Dhamar City, Yemen, using the HotSpot Health Physics Code.We evaluated the dispersion of radioactive materials under consistent atm. conditions to assess their environmental and human health impacts.Our anal. was based on two parameters: sampling time and exposure duration.For sampling time, the Total ED Equivalent (TEDE) was measured at specific intervals.After 2000 min, the TEDE for LOCA was 47 Sv, significantly higher than 0.0033 Sv for the RDD within a 1 km² area.In the initial moments of the explosion, the doses were 340 Sv for LOCA and 0.042 Sv for RDD, showing a dramatic decrease over time.For exposure duration, the LOCA scenario, results in a TEDE of 150 Sv after one year.In contrast, the RDD leads to a TEDE of 0.17 Sv after the same period.The LOCA scenario results in higher radiation doses due to multiple radionuclides with varying decay rates, causing a rapid increase in dose.In contrast, the RDD scenario shows a slower dose accumulation due to the long half-life of ¹³⁷Cs.This study introduces an AI-enhanced approach to radiol. assessments of LOCA and RDD incidents, using an Artificial Neural Network (ANN) model comprised of classification and regression sub-models.The classification sub-model accurately identifies the nature of the radiation event, while the regression sub-model estimates the distance of the explosion within 80 km radius from the explosion epicenter.With a predictive accuracy of 100% in classification and over 99% in regression, the model significantly improves the effectiveness and speed of emergency response strategies, offering critical advancements in radiol. safety measures.The impact on human organs was more severe in LOCA, with doses to the liver, skin, lungs, thyroid gland, brain, and kidneys exceeding those from the RDD by factors ranging from 55 to 6000.The findings stress the need for strong safety measures, long-term monitoring, and preparedness, especially in regions like Yemen, while highlighting the potential long-term environmental and health impacts of nuclear incidents and the importance of effective response and recovery plans.

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