Several studies investigating the behavior and environmental distribution of rare earth elements (REEs) have been reviewed to determine the geochemical processes that may affect their concentrations and fractionation patterns in groundwater and whether these elements can be used as tracers for groundwater-rock interactions and groundwater flow paths in small catchments. Inductively coupled plasma-mass spectrometry (ICP-MS), equipped with an ultrasonic nebulizer and active-film multiplier detector, is routinely used as an analytical technique to measure REEs in groundwater, facilitating the analysis of dissolved REE geochemistry. This review focuses on the distribution of REEs in groundwater and their application as tracers for groundwater geochemistry. Our review of existing literature suggests that REEs in ice cores can be used as effective tracers for atmospheric particles, aiding the identification of source regions.
Ocean biogeochemistry plays a crucial role in sustaining the marine ecosystem and global carbon cycle. To investigate the oceanic biogeochemical responses to iron parameters in the tropical Pacific, we conducted sensitivity experiments using the Nucleus for European Modelling of the Ocean–Tracers of Ocean Phytoplankton with Allometric Zooplankton (NEMO-TOPAZ) model. Compared to observations, the NEMO-TOPAZ model overestimated the concentrations of chlorophyll and dissolved iron (DFe). The sensitivity tests showed that with increasing (+50%) iron scavenging rates, chlorophyll concentrations in the tropical Pacific were reduced by approximately 16%. The bias in DFe also decreased by approximately 7%; however, the sea surface temperature was not affected. As such, these results can facilitate the development of the model tuning strategy to improve ocean biogeochemical performance using the NEMOTOPAZ model.
This study provides comprehensive assessment results for the most recent high-resolution regional climatology in the East/Japan Sea by comparing with the various existing climatologies. This new high-resolution climatology is generated based on the Optimal Interpolation (OI) method with individual profiles from the World Ocean Database and gridded World Ocean Atlas provided by the National Centers for Environmental Information (NCEI). It was generated from the recent previous study which had a primary focus to solve the abnormal horizontal gradient problem appearing in the other high-resolution climatology version of NCEI. This study showed that this new OI field simulates well the mesoscale features including closed-curve temperature spatial distribution associated with eddy formation. Quantitative spatial variability was compared to the other four different climatologies and significant variability at 160 km was presented through a wavelet spectrum analysis. In addition, the general improvement of the new OI field except for warm bias in the coastal area was confirmed from the comparison with serial observation data provided by the National Fisheries Research and Development Institute’s Korean Oceanic Data Center.
Understanding the distribution of heavy metals in sediment is necessary because labile heavy metals can partition into the water column and bioaccumulate in aquatic organisms. Here we investigated six heavy metals (Co, Cu, Mn, Ni, Pb, and Zn) in sediment cores using a five-step sequential leaching method to examine the occurrence of heavy metals in the sediment. The results showed that all elements, except Mn, are depleted in the exchangeable and carbonate fractions. However, heavy metal concentrations are much higher in the Fe-Mn oxide and organic matter fractions, especially for Cu, indicating enrichment in the organic matter fraction. Furthermore, contamination parameters (contamination factor and geoaccumulation index) indicate that Mn contamination is high, primarily derived from anthropogenic sources, presenting a potential risk to ecosystems in the Nakdong River.
Investigating the physical and chemical properties of riverine wetlands is necessary to understand their distribution characteristics and depositional environment. This study investigated the physical (particle size, color, and type) and chemical properties (organic, inorganic, and moisture contents) of sediments in Samrak wetland, located in the Nakdong River estuary area in Busan, South Korea. The particle size analysis indicated that the hydraulic conductivity values for the coarse grain and the mixture of coarse and fine grains ranged from 2.03 to 3.49×10−1 cm s−1 and 7.18×10−3 to 1.24×10−7 cm s−1 , respectively. In-situ water quality and laboratory-based chemical analyses and radon-222 measurement were performed on groundwater and surface water in the wetland and water from the nearby Nakdong River. The physical and chemical properties of Samrak wetland was characterized by the sediments in the vertical and lateral direction. The concentrations of chemical components in the wetland groundwater were distinctly higher than those in the Nakdong River water though the wetland groundwater and Nakdong River water equally belonged to the Ca-HCO3 type.
Gravity Recovery and Climate Experiment (GRACE) gravimeter satellites observed the Earth gravity field with unprecedented accuracy since 2002. After the termination of GRACE mission, GRACE Follow-on (GFO) satellites successively observe global gravity field, but there is missing period between GRACE and GFO about one year. Many previous studies estimated terrestrial water storage (TWS) changes using hydrological models, vertical displacements from global navigation satellite system observations, altimetry, and satellite laser ranging for a continuity of GRACE and GFO data. Recently, in order to predict TWS changes, various machine learning methods are developed such as artificial neural network and multi-linear regression. Previous studies used hydrological and climate data simultaneously as input data of the learning process. Further, they excluded linear trends in input data and GRACE/GFO data because the trend components obtained from GRACE/GFO data were assumed to be the same for other periods. However, hydrological models include high uncertainties, and observational period of GRACE/GFO is not long enough to estimate reliable TWS trends. In this study, we used convolutional neural networks (CNN) method incorporating only climate data set (temperature, evaporation, and precipitation) to predict TWS variations in the missing period of GRACE/GFO. We also make CNN model learn the linear trend of GRACE/GFO data. In most river basins considered in this study, our CNN model successfully predicts seasonal and long-term variations of TWS change.
In this study, we investigated the difference in the affective characteristics between science-gifted students and general students through the positive experiences about science (PES) index. We also explored ways to apply the characteristics of gifted classes suggeseted by the teachers of this study, which had a positive effect on science-gifted students, to general science classes. For this study, a PES survey was carried on middle school science-gifted students enrolled in the gifted education center in the central region and general middle school students in the same area who had no experience in gifted education. Based on the survey result, we conducted in-depth interviews with teachers, having teaching experience with both science-gifted and general students. The results revealed that science-gifted students showed a significantly higher PES index than general students in all five areas of PES. The area with the largest difference between the two groups was science-related self-concept and the smallest was science academic emotion. Teachers suggested ways to apply the characteristics of science-gifted classes to general science classes, such as organizing general science classes around inquiry activities, supporting class materials such as MBL or tablets, reconstructing the classes using materials reflecting students’ needs, and changing the textbook content and narrative style, to induce students' interest and curiosity. Based on the study results, ways to enhance the PES through science classes for general students were proposed.
This study aimed to explore alignments among three curricula based on the contents of the university level curriculum. The 2015 revised curriculum, International Baccalaureate(IB), and Next Generation Science Standards(NGSS) were selected for this study, and a college textbook was analyzed to compare the curricula. As the age groups studying the curricular were different, we reorganized them according to school ages prior to conducting the study. The results of the analysis were: first, the contents of the 2015 revised curriculum did not sufficiently elaborate on the natural hazards related to humans, unlike the university level, IB PYP, and NGSS curricula. Third, there are different ways of introducing scientific vocabulary curricula, meaning that the number of scientific vocabularies in the 2015 revised curriculum was less than that in the IB, PYP, and NGSS.