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Radon potential mapping is challenging due to the limited availability of information. In this study, a new modeling process using deep learning models based on convolution neural network (CNN), long short-term memory (LSTM), and recurrent neural network (RNN) is presented to predict radon potential in the northwestern part of Gangwon Province, South Korea. The used data in this study are in two sets of dependent variables (measured soil gas radon concentrations) and independent variables (radon conditioning factors: lithology; distance from lineament; mean soil calcium oxide [Cao], potassium oxide [K2O], and ferric oxide [Fe2O3] concentrations; effective soil depth; topsoil texture; and soil drainage). The models were validated based on the area under the receiver operating curve (AUC), mean squared error (MSE), root mean square error (RMSE), and standard deviation (StD). The CNN model with AUC values of 0.906 and 0.905 in the learning and testing stages, respectively, is introduced as the optimal model. The lowest StD, MSE, and RMSE values were from the CNN, LSTM, and RNN models, respectively. Our results show that the use of deep learning models to generate radon potential maps is promising and reliable. [ABSTRACT FROM AUTHOR]

The black pottery unearthed from the Hanseong Baekje archaeological site in Seoul, South Korea was characterized by type using different techniques. The samples were classified into three types depending on their coloring pattern. There was no observable difference in the mineral and major element composition of the black colored part and raw material soil part of each sample. However, differences in magnetic properties and carbon content reflect the characteristics of each type and part of the sample. These results help to distinguish the mechanisms for black color development between reductive fired black pottery and soot-coated black pottery. [ABSTRACT FROM AUTHOR]

Sludge powder with stainless-steel corrosion products generated from the long-term contaminated-waste fluid tank of a nuclear power plant was compressed into a cylindrical shape by a hydraulic press at room temperature. The cylindrical sludge was wrapped in molten Al in a carbon crucible and cooled and hardened at room temperature. Subsequently, the encapsulated sludge was heated and compressed by the hot isostatic pressing (HIP) process. The Al capsule was melted and separated from the cylindrical solidified sludge. In solidified sludge, the leachability indices of Co, Fe, Cr, and Ni were 17.5 ± 0.0736, 13.4 ± 0.0952, 11.2 ± 0.0952, and 16.9 ± 0.0739, respectively. This satisfies Korea's criterion for the disposal of solidified radioactive waste, which is a leachability index of more than 6. • Simulated sludge consists of Fe 2 O 3 , Cr 2 O 3 , NiO and cobalt powder was solidified by HIP (Hot Isostatic Pressing) process. Ferro frit, a glass material, was used as solidification auxiliary material. Due to HIP process, using a relatively small amounts of ferro frit (10 %), large amounts of simulated sludge can be stably solidified. • To treat powder material in HIP process, powder should be packaged by metal capsule and sealed. In previous other research, stainless-steel canister encapsulation method including complex process as welding and degassing was used. However, in our study, molten aluminum encapsulation method was used, and encapsulation process became easier and more concise. • Using new encapsulation in our study, solidified sludge treated by HIP process was stable in aspect of leaching resistance. And after HIP process, removing of capsule and separation of solidified sludge and aluminum capsule was easy. Since the melting point of aluminum was relatively low as 660 °C , when aluminum capsule was removed and separated, solidified sludge was not damaged. And there was no significant dispersion of sludge materials from solidified sludge to aluminum. [ABSTRACT FROM AUTHOR]

During the operation of a pilot plant from July 2010 to January 2011 for the development of bank filtration along the Nakdong River, iron and manganese were detected on average as high as 23.99 and 3.45 mg/L, respectively. These levels are dozens of times higher than those found in standard quality Korean drinking water (less than 0.3 and 0.05 mg/L for iron and manganese, respectively). If the Nakdong River were to be used as a water resource, it would not only produce color or scale in the piping system but also result in an increase in water treatment costs. Therefore, this study used by EPANET-MSX modeling to investigate the behaviors of iron and manganese in a piping system. Additionally, it assessed the possibility of color or scale formation when the bank filtrate was passed through a pipe with 38 km length and 2,600–2,800 mm diameter. The modeling result predicted that if the transport was done without reducing iron to a certain level, approximately 5300 ton/year of ferric oxide and 324 NTU of turbidity would be produced in the piping system, whereas manganese would have no effect owing to insufficient oxidants. If the iron was reduced up to 3.0 mg/L by aeration pretreatment, the ferric oxide and turbidity were predicted to be approximately 746 ton/year and 57 NTU, respectively. Furthermore, in the case of a reduction up to 0.3 mg/L by the pretreatment, the levels were predicted to be about 75 ton/year and 5.9 NTU, respectively. [ABSTRACT FROM PUBLISHER]

The adverse health effects associated with the inhalation and ingestion of naturally occurring radon gas produced during the uranium decay chain mean that there is a need to identify high-risk areas. This study detected radon-prone areas using a geographic information system (GIS)-based probabilistic and machine learning methods, including the frequency ratio (FR) model and a convolutional neural network (CNN). Ten influencing factors, namely elevation, slope, the topographic wetness index (TWI), valley depth, fault density, lithology, and the average soil copper (Cu), calcium oxide (Cao), ferric oxide (Fe 2 O 3), and lead (Pb) concentrations, were analyzed. In total, 27 rock samples with high activity concentration index values were divided randomly into training and validation datasets (70:30 ratio) to train the models. Areas were categorized as very high, high, moderate, low, and very low radon areas. According to the models, approximately 40% of the study area was classified as very high or high risk. Finally, the radon potential maps were validated using the area under the receiver operating characteristic curve (AUC) analysis. This showed that the CNN algorithm was superior to the FR method; for the former, AUC values of 0.844 and 0.840 were obtained using the training and validation datasets, respectively. However, both algorithms had high predictive power. Slope, lithology, and TWI were the best predictors of radon-affected areas. These results provide new information regarding the spatial distribution of radon, and could inform the development of new residential areas. Radon screening is important to reduce public exposure to high levels of naturally occurring radiation. [Display omitted] • Geogenic radon potential maps are generated using FR and CNN methods. • Slope, lithology, and TWI have significant influence on modelling radon level. • Approximately 20% of the study area is classified as very high risk for radon gas. [ABSTRACT FROM AUTHOR]

Nitrate is the most common contaminant in groundwater in Korea, as well as across the world. Reduction of nitrate to ammonia is one of the options available to remediate groundwater. In this study, nitrate in groundwater was removed using a zero-valent iron (ZVI) containing biochar synthesized by co-pyrolyzing iron oxide and sawdust biomass. Among the various biogases generated during the pyrolysis of biomass, CO and H 2 act as reducing agents to transform iron oxides to ZVI. Approximately 71% of nitrate was reduced to ammonium by ZVI-biochar at initial pH 2.0, and the reduction decreased sharply by the increase in pH. The mass of nitrate-N decreased is exactly same with the mass of ammonia-N formed. However, ammonium remained in the aqueous phase after reduction by ZVI-biochar, and the total nitrogen was not lowered. Acid-washed zeolite adsorbed most ammonium reduced by the ZVI-biochar and maintained the pH to acidic condition to facilitate the reduction of nitrate. The results of this study imply that nitrate-contaminated groundwater can be properly treated within the guidelines of water quality by synthesized ZVI-containing biochar. [Display omitted] • Co-pyrolysis of sawdust and iron oxide synthesized ZVI-biochar in one pot. • ZVI-biochar reduced nitrate to ammonium effectively. • ZVI-biochar did not adsorb ammonium, and total nitrogen was not changed. • Zeolite adsorbed the ammonium reduced by ZVI-biochar. [ABSTRACT FROM AUTHOR]

Application of electron acceptors such as ferric iron oxides and hydroxides for controlling methane (CH4) emission from wetland rice fields deserves special attention due to its dominant role over all other redox species in wetland soils. Silicate iron slag (hereafter, silicate fertilizer), a byproduct of steel industry containing electron acceptors, was applied in paddy field (Agronomy Farm, Gyeongsang National University, South Korea) at the rate of 0, 1, 2 and 4Mgha−1 to investigate their effects on reducing CH4 emissions from flood water rice (Oryza sativa, cv. Dongjinbyeo) farming during 2006–2007. CH4 emission rates measured by closed-chamber method decreased significantly (p <0.05) with increasing levels of silicate fertilizer application during rice cultivation. Soil redox potential (Eh) showed a contrasting response to CH4 emission rates. The concentrations of dissolved iron materials in percolated water, and the active and free iron oxides in soil significantly increased with the applications of silicate fertilizer, which acted as oxidizing agents and electron acceptors, and eventually suppressed CH4 emissions during the rice growing seasons. Total CH4 emission was decreased by 16–20% with 4Mgha−1 silicate fertilizer application and simultaneously rice grain yield was increased by 13–18%. Silicate fertilization significantly stimulated rice plant growth, especially root biomass, root volume and porosity, which might have improved rhizosphere oxygen concentration, and then partially contributed to reduce CH4 emission through enhancing methane oxidation. Therefore, silicate fertilizer could be a good soil amendment for reducing CH4 emission as well as increasing rice productivity in wetland paddy field. [Copyright &y& Elsevier]

Removal of toxic arsenite [As(III)] from the contaminated surface and groundwater is essential for human health. However, direct arsenite removal is difficult compared to arsenate [As(V)]. Therefore, the peroxidation of arsenite to arsenate is vital for its effective removal from water. Herein, we investigated the removal efficiency of arsenic from groundwater by oxidizing it with UV activated potassium persulfate (KPS) and subsequently adsorbing it on iron oxide impregnated granular activated carbon (FeO/GAC). A batch experiment was carried out to determine the adsorption kinetics and thermodynamics. Further, the effects of the adsorbent mass (FeO/GAC), C/Fe molar ratio, pH, arsenic concentration, competing anions, and humic acid in arsenic adsorption was studied. The characterization of FeO/GAC adsorbent was investigated by scanning electron microscopy (SEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Brunauer-Emmett-Teller (BET), and zeta potential measurements. Using the UV activated KPS and FeO/GAC, a ∼100% removal amount was achieved for 10 ppm of the arsenic solution in 1 h. Also, the effect of pH showed the highest removal efficiency in the pH range of 6.0–7.0 and it decreased dramatically at higher and lower pH values. The groundwater collected from Cheongyang in South Korea was spiked with 10 ppm of the arsenic (III) and more than 82% removal of arsenic was achieved in 90 min even in the presence of natural contaminants. Therefore, the results suggest that the UV activated KPS with FeO/GAC provides an effective method for treating highly-arsenic-contaminated water sources and this may be a viable alternative method over the existing methods. • Efficient oxidation of Arsenic in water using UV activated KPS followed by adsorption on an impregnated FeO/GAC adsorbent. • The arsenic removal efficiency was 100% in artificial water and 82% in groundwater collected from Cheongyang, South Korea. • Adsorption mechanism is associated with electrostatic interaction, ion exchange, surface complexation and coprecipitation. • The thermodynamic studies revealed that the adsorption process was endothermic, spontaneous and feasible. [ABSTRACT FROM AUTHOR]