Source and remediation for heavy metals of soils at an iron mine of Ulsan City,Korea

Ulsan mine produced the iron ore minerals of magnetite, arsenopyrite, and scheelite in 1992, and serpentine was developed from 1977 to 2002. The soils of the mine were contaminated by heavy metals such as As, Zn, Ni, and Cd. Heavy metals of Ni and Zn came mostly from serpentinite, and As was derived mainly from arsenopyrite in the scan-type iron ore body. As, Zn, and Ni were major contaminants, but Cd was a minor contaminant on a basis of Korean standard. The heavy metals in the deep depth (>?5 m) came from the host rocks, and those in the shallow depth (<?5 m) were derived from the organic–mineral complexation soil. The remediation plan was a soil washing for highly contaminated soils and the containment of clay materials for less contaminated soils. Even though the remediation methods were successful, the continuous monitoring and the analysis of monitoring data are still necessary for the conservation of soil and groundwater around the study area.     

Bastille Day storm: Global response of the terrestrial ring current

Global images of the Earth's inner magnetosphere and its response to the coronal mass ejection (CME) on the 15 July 2000 were obtained by the IMAGE spacecraft. The images were taken in energetic neutral atoms (ENA) by the High-Energy Neutral Atom (HENA) imager. ENAs are produced by charge exchange between the hot ion population of the magnetosphere and the cold neutral hydrogen geocorona. The ENA images show how plasma is injected into the nightside magnetosphere as the interplanetary magnetic field (IMF) turns strongly southward. As the IMF B _z increases and the storm intensity decreases, the ENA images show that the ring current becomes closed and symmetric as IMF B _z reaches positive values.     

Spring phytoplankton bloom in the fronts of the East China Sea

Frontal areas between warm and saline waters of the Kuroshio currents and colder and diluted waters of the East China Sea (ECS) influenced by the Changjiang River were identified from the satellite thermal imagery and hydrological data obtained from the Coastal Ocean Process Experiment (COPEX) cruise during the period between March 1^st and 10^th, 1997. High chlorophyll concentrations appeared in the fronts of the East China Seas with the highest chlorophyll-a concentration in the southwestern area of Jeju Island (~2.9 mg/m³) and the eastern area of the Changjiang River Mouth (~2.8 mg/m³). Vertical structures of temperature, salinity and density were similar, showing the fronts between ECS and Kuroshio waters. The water column was well mixed in the shelf waters and was stratified around the fronts. It is inferred that the optimal condition for light utilization and nutrients induced both from the coastal and deep waters enhances the high phytoplankton productivity in the fronts of the ECS. In addition, the high chlorophyll-a in the fronts seems to have been associated with the water column stability as well.     

Development of statistical prediction models for Changma precipitation: An ensemble approach

An ensemble statistical forecast scheme with a one-month lead is developed to predict year-to-year variations of Changma rainfall over the Korean peninsula. Spring sea surface temperature (SST) anomalies over the North Atlantic, the North Pacific and the tropical Pacific Ocean have been proposed as useful predictors in a previous study. Through a forward-stepwise regression method, four additional springtime predictors are selected: the northern Indian Ocean (NIO) SST, the North Atlantic SST change (NAC), the snow cover anomaly over the Eurasian continent (EUSC), and the western North Pacific outgoing longwave radiation anomaly (WNP (OLR)). Using these, three new prediction models are developed. A simple arithmetic ensemble mean produces much improved forecast skills compared to the original prediction model of Lee and Seo (2013). Skill scores measured by temporal correlation and MSSS (mean square error skill score) are improved by about 9% and 17%, respectively. The GMSS (Gerrity skill score) and hit rate based on a tercile prediction validation scheme are also enhanced by about 19% and 13%, respectively. The reversed NIO, reversed WNP (OLR), and reversed NAC are all related to the enhancement of a cyclonic circulation anomaly to the south or southwest of the Korean peninsula, which induces southeasterly moisture flux into the peninsula and increasing Changma precipitation. The EUSC predictor induces an enhancement of the Okhotsk Sea high downstream and thus strengthening of Changma front.     

Long-runout pyroclastic surge on a Cretaceous alluvial plain, Republic of Korea

Pyroclastic surge is a dilute and turbulent flow of volcanic gas and tephra that is commonly generated during explosive volcanic eruptions and can threaten lives along its flow paths. Assessing its travel distance and delineating future volcanic hazards have therefore been major concerns of volcanologists. Historical eruptions show that most pyroclastic surges travel a few tens of kilometres or less from their sources. Aeolian or aquagene processes have therefore been evoked for the emplacement of supposed surge deposits much beyond this distance. Here we show that a Cretaceous tuff bed in Korea was emplaced by an exceptionally powerful pyroclastic surge that flowed as far as the most powerful pyroclastic flows that formed the low-aspect-ratio ignimbrites (LARI). This has significant implications for interpreting ancient volcanic eruptions and delineating volcanic hazards by pyroclastic surges, and casts intriguing questions on the eruption dynamics and physics of long-runout pyroclastic surges and their distinction from LARI-forming pyroclastic flows.     

A systematic regional approach for climate change adaptation to protect biodiversity

Developing appropriate climate change adaptations to protect biodiversity requires taking into account the dynamics of agro-ecological and socio-economic change. A framework for approaching this problem was proposed, but not applied in detail, as part of a major biodiversity and climate change report prepared in Australia. This paper describes the first trial application of the method. It was applied across Vietnam as the Government is interested in identifying adaptation options and detailed data are readily available for its 65 provinces. The process involves identifying ecoregions and collating information for each region based on the current conditions and trends in biodiversity, population, income and agricultural production. Climate change scenarios are identified for each region, together with governance options. Educational needs and key adaptation actions are then identified for each region taking into account the agro-ecological and socio-economic input data. It is concluded that the framework could easily be applied in other countries and should assist the development of strategic adaptation options.     

Nuclear energy response in the EMF27 study

The nuclear energy response for mitigating global climate change across 18 participating models of the EMF27 study is investigated. Diverse perspectives on the future role of nuclear power in the global energy system are evident in the broad range of nuclear power contributions from participating models of the study. In the Baseline scenario without climate policy, nuclear electricity generation and shares span 0–66 EJ/year and 0–25 % in 2100 for all models, with a median nuclear electricity generation of 39 EJ/year (1,389 GWe at 90 % capacity factor) and median share of 9 %. The role of nuclear energy increased under the climate policy scenarios. The median of nuclear energy use across all models doubled in the 450 ppm CO₂e scenario with a nuclear electricity generation of 67 EJ/year (2,352 GWe at 90 % capacity factor) and share of 17 % in 2100. The broad range of nuclear electricity generation (11–214 EJ/year) and shares (2–38 %) in 2100 of the 450 ppm CO₂e scenario reflect differences in the technology choice behavior, technology assumptions and competitiveness of low carbon technologies. Greater clarification of nuclear fuel cycle issues and risk factors associated with nuclear energy use are necessary for understanding the nuclear deployment constraints imposed in models and for improving the assessment of the nuclear energy potential in addressing climate change.     

Estimation of Seasonal Representation of the Sea Water Temperature Profile Using Machine Learning and Its Effect on the Prediction of Underwater Acoustic Detection Performance

Ocean Science Journal - Seawater temperature and salinity profiles are important physical properties that represent oceanic environments and affect underwater acoustic detection prediction...