• Journal of the Mineralogical Society of Korea
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• v.21 no.4
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• pp.425-434
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• 2008

Arsenic contamination in soil and groundwater has recently been one of the most serious environmental concerns. This arsenic contamination can be originated from natural or anthropogenic sources. It has been well known that arsenic behavior in geo-environmental is controlled by various oxides or hydroxides, such as those of iron, manganese, and aluminum, and clay minerals. Among those, particularly, iron (oxy)hydroxides are the most effective scavengers for arsenic. For this reason, this study characterized arsenic adsorption of magnetite which is a kind of iron oxide in nature. The physicochemcial features of the magnetite were investigated to evaluate adsorption of arsenite [As(III)] and arsenate [As(V)] onto magnetite. In addition to experiments on adsorption equilibria, kinetic experiments were also conducted. The point of zero charge (PZC) and specific surface area of the laboratory-synthesized magnetite used as an arsenic adsorbent were measured 6.56 and $16.6\;g/m^2$, which values seem to be relatively smaller than those of the other iron (oxy)hydroxides. From the results of equilibria experiments, arsenite was much more adsorbed onto magnetite than arsenate, indicating the affinity of arsenite on magnetite is larger than arsenate. Arsenite and arsenate showed adsorption maxima at pHs 7 and 2, respectively. In particular, adsorption of arsenate decreased with increase in pH as a result of electrical repulsion caused by anionic arsenate and negatively-charged surface of magnetite. These results indicate that the surface charge of magnetite and the chemical speciation of arsenic should be considered as the most crucial factors in controlling arsenic. The results of kinetic experiments show that arsenate was adsorbed more quickly than arsenite and adsorption of arsenic was investigated to be mostly completed within the duration of 4 hours, regardless of chemical speciation of arsenic. When the results of kinetic experiments were fitted to a variety of kinetic models proposed so far, power function and elovich model were evaluated to be the most suitable ones which can simulate adsorption kinetics of two kinds of arsenic species onto magnetite.

• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.461-472
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• 2022

Natural and anthropogenic factors cause forest types to continuously change. Since the ratio of forest area by forest type is important information for identifying the characteristics of national forest resources, an accurate understanding of the prospect of forest type change is required. The study aim was to use National Forest Inventory (NFI) time-series data to understand the characteristics of forest type change and to estimate future prospects of nationwide forest type change. We used forest type change information from the fifth and seventh NFI datasets, climate, topography, forest stand, and disturbance variables related to forest type change to analyze trends and characteristics of forest type change. The results showed that the forests in Korea are changing in the direction of decreasing coniferous forests and increasing mixed and broadleaf forests. The forest sites that were changing from coniferous to mixed forests or from mixed to broadleaf forests were mainly located in wet topographic environments and climatic conditions. The forest type changes occurred more frequently in sites with high disturbance potential (high temperature, young or sparse forest stands, and non-forest areas). We used a climate change scenario (RCP 8.5) to establish a forest type change model (SVM) to predict future changes. During the 40-year period from 2015 to 2055, the SVM predicted that coniferous forests will decrease from 38.1% to 28.5%, broadleaf forests will increase from 34.2% to 38.8%, and mixed forests will increase from 27.7% to 32.7%. These results can be used as basic data for establishing future forest management strategies.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.48-59
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• 2023

Ground-level ozone affects human health and plant growth. Ozone is produced by chemical reactions between oxides of nitrogen (NOx) and volatile organic compounds (VOCs) from anthropogenic and biogenic sources. In this study, two different land cover and emission factor datasets were input to the MEGAN v2.1 emission model to examine how these parameters contribute to the biogenic emissions and ozone production. Four input sensitivity scenarios (A, B, C and D) were generated from land cover and vegetation emission factors combination. The effects of BVOCs emissions by scenario were also investigated. From air quality modeling result using CAMx, maximum 1 hour ozone concentrations were estimated 62 ppb, 60 ppb, 68 ppb, 65 ppb, 55 ppb for scenarios A, B, C, D and E, respectively. For maximum 8 hour ozone concentration, 57 ppb, 56 ppb, 63 ppb, 60 ppb, and 53 ppb were estimated by scenario. The minimum difference by land cover was up to 25 ppb and by emission factor that was up to 35 ppb. From the modeling performance evaluation using ground ozone measurement over the six regions (East Seoul, West Seoul, Incheon, Namyangju, Wonju, and Daegu), the model performed well in terms of the correlation coefficient (0.6 to 0.82). For the 4 urban regions (East Seoul, West Seoul, Incheon, and Namyangju), ozone simulations were not quite sensitive to the change of BVOC emissions. For rural regions (Wonju and Daegu) , however, BVOC emission affected ozone concentration much more than previously mentioned regions, especially in case of scenario C. This implies the importance of biogenic emissions on ozone production over the sub-urban to rural regions.