• Journal of Wetlands Research
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• v.25 no.4
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• pp.408-416
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• 2023

The IUCN Red List of Ecosystems serves as a global standard for assessing and identifying ecosystems at high risk of biodiversity loss, providing scientific evidence necessary for effective ecosystem management and conservation policy formulation. The IUCN Red List of Ecosystems has been designated as a key indicator (A.1) for Goal A of the Kunming-Montreal Global Biodiversity Framework. The assessment of the Red List of Ecosystems discerns signs of ecosystem collapse through specific criteria: reduction in distribution (Criterion A), restricted distribution (Criterion B), environmental degradation (Criterion C), changes in biological interaction (Criterion D), and quantitative estimation of the risk of ecosystem collapse (Criterion E). Since 2014, the IUCN Red List of Ecosystems has been evaluated in over 110 countries, with more than 80% of the assessments conducted in terrestrial and inland water ecosystems, among which tropical and subtropical forests are distributed ecosystems under threat. The assessment criteria are concentrated on spatial signs (Criteria A and B), accounting for 68.8%. There are three main considerations for applying the Red List of Ecosystems assessment domestically: First, it is necessary to compile applicable terrestrial ecosystem types within the country. Second, it must be determined whether the spatial sign assessment among the Red List of Ecosystems categories can be applied to the various small-scale ecosystems found domestically. Lastly, the collection of usable time series data (50 years) for assessment must be considered. Based on these considerations, applying the IUCN Red List of Ecosystems assessment domestically would enable an accurate understanding of the current state of the country's unique ecosystem types, contributing to global efforts in ecosystem conservation and restoration.

• Journal of Korean Society for Atmospheric Environment
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• v.31 no.4
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• pp.330-344
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• 2015

Semi-continuous measurements of $PM_{2.5}$ mass, organic and elemental carbon were made for the period of January to October 2014, at six national air monitoring stations in Korea. OC and EC concentrations showed a clear seasonal variation with the highest in winter (January) and the lowest in summer (August). In winter, the high carbonaceous concentrations were likely influenced by increased fuel combustion from residential heating. OC and EC concentrations varied by monitoring stations with 5.9 and $1.7{\mu}g/m^3$ in Joongbu area, 4.2 and $1.2{\mu}g/m^3$ in Honam area, 4.0 and $1.3{\mu}g/m^3$ in Yeongnam area, 3.7 and $1.6{\mu}g/m^3$ in Seoul Metropolitan area, 3.0 and $0.8{\mu}g/m^3$ in Jeju Island, 2.9 and $0.7{\mu}g/m^3$ in Baengnyeong Island respectively. The concentrations of OC and EC comprised 9.6~ 15.5% and 2.4~ 4.7% of $PM_{2.5}$. Urban Joongbu area located adjacent to the intersection of several main roads showed the highest carbon concentration among six national air monitoring station. On the other hand, background Baengnyeong Island showed the lowest carbon concentration and the highest OC/EC ratio (4.5). During the haze episode, OC and EC were enhanced with increase in $PM_{2.5}$ about 1.3~ 3 and 1.3~ 4.0 times respectively. The concentrations of OC, EC in the Asian dust case are about 1~ 2.4 times greater than in the nondust case. The origins of air mass pathways arriving at Seoul, using the backward trajectory analysis, can be mostly classified into 6 groups (Sector I Northern Korea including the sea of Okhotsk, Sector II Northern China including Mongolia, Sector III Southern China, Sector IV South Pacific area, Sector V Japan, Sector VI Southern Korea area). When an air mass originating from northern China and Mongolia, the OC concentrations were the most elevated, with a higher OC/EC ratio (2.4~ 3.3), and accounting for 17% of $PM_{2.5}$ mass on average.

• Journal of Korean Society of Forest Science
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• v.98 no.4
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• pp.409-416
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• 2009

Forest biomass estimation is essential for greenhouse gas inventories and terrestrial carbon accounting. Remote sensing allows for estimating forest biomass over a large area. This study was conducted to estimate forest biomass and to produce a forest biomass map for Muju county using forest biomass conversion table developed by field plot data from the 5th National Forest Inventory and Landsat TM-5. Correlation analysis was carried out to select suitable independent variables for developing regression models. It was resulted that the height class, crown closure density, and age class were highly correlated with forest biomass. Six regression models were used with the combination of these three stand variables and verified by validation statistics such as root mean square error (RMSE) and mean bias. It was found that a regression model with crown closure density and height class (Model V) was better than others for estimating forest biomass. A biomass conversion table by model V was produced and then used for estimating forest biomass in the study site. The total forest biomass of the Muju county was estimated about 8.8 million ton, or 128.3 ton/ha by the conversion table.

• Journal of Korean Society of Forest Science
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• v.102 no.4
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• pp.543-549
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• 2013

This study was conducted to evaluate age-specific and generalized allometric equations and biomass expansion factors (BEFs) for each tree component across three age-sequence stands (35-year-old, 51-year-old, 62-year-old) of black pine (Pinus thunbergii Parl.) in Jinju, located in the western part of Gyeongnam province, Korea. Biomass in each tree component, i.e. foliage, branch, and stem, was quantified by destructive tree harvesting. Allometric regression equations were significant (P<0.05) with diameter at breast height (DBH) or combination of DBH and height ($DBH^2H$) accounting for 55-98% of the variation (as indicated by coefficients of determination, $R^2$) in aboveground biomass except for foliage biomass of the 62-year-old stand. Generalized allometric equations can be used to estimate the biomass of black pine stands because the slopes of age-specific equations over 35-year-old stands were not significantly different by the age-sequence. The stem density and biomass expansion factor (BEFs) were not significantly different (P>0.05) from different stand ages and ranged from 0.45 to $0.51gcm^{-3}$, and from 1.32 to 1.38, respectively. The results indicate that allometric equations, stem density and aboveground BEFs in the matured black pine over 35-year-old are little influenced by different stand ages.

• Journal of Korean Society of Forest Science
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• v.103 no.2
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• pp.175-181
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• 2014

This study was conducted to evaluate stand density-specific and generalized allometric equations, and biomass expansion factors (BEFs) for two stand densities (high density of 47-year-old: $667tree{\cdot}ha^{-1}$; low density of 49-year-old: $267tree{\cdot}ha^{-1}$) of Cryptomeria japonica plantations in Namhae-gun, located in the southern Korea. Biomass in each tree component, i.e. foliage, branch, and stem, was quantified by destructive tree harvesting. Allometric regression equations of each tree component were significant (P<0.05) with diameter at breast height (DBH) accounting for 80-96% of the variation except for branch biomass in high density or foliage and cone biomass in low density. Generalized allometric equations can be used to estimate the biomass of C. japonica plantations because the slopes of allometric equations were not significantly different by the stand density. The biomass expansion factors (BEFs) were significantly lower in the high stand density (1.33) than in the low stand density (1.50). The results indicate that BEFs were affected by different stand density, while allometric equations were little related to the stand density.

• Journal of Forest and Environmental Science
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• v.22 no.1
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• pp.1-12
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• 2006

This study was carried out to compile year 2001 forest resource statistics for the State of Virginia. USA. Virginia has 15.8 million acres (6.4 million ha) of forested 1and, accounting for 62% of the landcover with non-industrial private forest landowners owning 77% of the forested area. Deciduous forests make up 78% of Virginia's forests. Total tree volume is 26.5 billion cubic ft, of which average volume per acre is $1.677ft^3/ac(117m^3/ha)$. The overall annual volume of roundwood output is $543\;million\;ft^3$. Tree growth exceeds removals by $271\;million\;ft^3$ each year for all species statewide. Average net forest land loss in Virginia is 20,000 acre (8,094 ha) per year. In 1999, the forest products industry contributed over $25.4 billion to Virginia's economy while providing over 248,000 jobs. Among forest industries logging contributes to the economy at over $863 million/yr; timber accounts for the greatest amount (28%) of the total market value of Virginia's agricultural crops. Revenue received from stumpage by landowners exceeded $345 million/yr. In their entirety. Virginia's forests provide over $30.5 billion in annual return. including $3 billion for recreation and $1.9 billion for carbon sequestation and pollution control.

• 한국해양학회지
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• v.30 no.4
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• pp.341-354
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• 1995

Fluorescence characteristic and amino acids composition of organic matter were determined from extracted seawater samples at eight stations in the East Sea of Korea. Organic compounds have been extracted onto C-18 Sep-Pak cartridges. Three dimensional excitation/emission fluorescence contouring of extracts showed two markedly distinct characterized fluoroscopies representing protein-like biomacromolecule and humic-like geomacromolecule. Protein-like biomacromolecule showing fluorescence maxima at 280 nm/330 nm (excitation/emission) were abundant in the surface mixed layer and then apparently decreased below the thermocline at most stations. It suggests that source of biomacromolecule is comely related with vigorous biological synthetic activity in the surface layer and bacteria decompose its biologically labile components near the thermocline and in the deeper layer. On the other hand, humiliate geomacromolecule showing fluorescence maxima at 330 nm/430 nm (excitation/emission) were low in the surface mixed layer implying photochemical oxidation and then increased below the thermocline at most stations. It suggests that geomacromolecule might be transformed by condensation of bio-refractoryorganic fraction after decomposition of biomacromolecule and particulate organic carbon derived from the surface mixed layer. HPLC measurements of amino acids showed similar composition between seawater and extracted organic macromolecule after hydrolysis. Glycine, serine and alanine were predominant, accounting for more than 50% of total amino acids. Dissolved free amino acids of seawater were more abundant in the surface layer(0.7∼1.8 uM) than the deeper layer (0.2∼0.4 uM). D/L racemic ratio of alanine of extracted organic matter showed lower value in the surface layer than the deeper layer. It suggests that biomacromolecule predominant in the surface layer is relatively young, rapidly recycling and biologically labile.

• Korean Journal of Soil Science and Fertilizer
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• v.41 no.3
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• pp.228-234
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• 2008

The purpose of this study was to predict environmental distribution of anthracene, benzene, benzo[a]pyrene, 1-methylphenanthrene and phenanthrene in a four phase biopile system - air, water, soil and non aqueous phase liquid (NAPL) phase using level I fugacity model. Soil samples used for this study were collected from three sites in the United Kingdom which were historically contaminated with petroleum hydrocarbons. The level I fugacities (f) for the five contaminants were markedly different, however, the fugacities of each contaminant in three soil samples did not show significant difference. NAPL and soil were the dominant phases for all five contaminants. Results of this study indicated that difference in percentage of organic carbon strongly influenced the partitioning behavior of the cntaminants. The presence of benzene calls for an urgent need for risk-based management of air and water phase. Whereas insignificant amount of chemicals leached in the water phase for other organic contaminants showing greatly reduced potential of groundwater contamination. Furthermore, this study helped us to confirm the association of risk critical contaminants with the residual saturation in treated soils. They also can be used to emphasize the importance of accounting for the partitioning behavior of both NAPL and soil phases in the process of the risk assessment of the sites contaminated with petroleum hydrocarbons.

• Economic and Environmental Geology
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• v.38 no.1
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• pp.91-99
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• 2005

Acid Rock Drainage(ARD) is the product formed by the atmospheric(i.e. by water, oxygen and carbon dioxide) oxidation of the relatively common iron-sulphur mineral pyrite($FeS_2$). ARD causes the acidification and heavy metal contamination of water and soil and the reduction of slope stability. In this paper the generation characteristics and the prediction of ARD of various cut slopes were studied. An attempt to classify the rocks into several groups according to their acid generation potentials was made. Acid Base Accounting(ABA) tests, commonly used as a screening tool in ARD predictions, were performed. Fourteen rock samples were classified into PAF(potentially acid forming) group and four rock samples into NAF(non-acid forming) group. The chemical analysis of water samples strongly suggested that ARD with high content of heavy metals and low pH could pollute the ground water and/or stream water.

• Journal of Environmental Science International
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• v.28 no.4
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• pp.413-422
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• 2019

The objective of this study was to estimate the trends of air quality in the study area by analyzing monthly and seasonal concentration trends obtained from sampled data. To this aim, the mass concentrations of $PM_{2.5}$ in the air were analyzed, as well as those of metals, ions, and total carbon within the $PM_{2.5}$. The mean concentration of $PM_{2.5}$ was $22.7{\mu}g/m^3$. The mass composition of $PM_{2.5}$ was as follows: 31.1% of ionic species, 2.2% of metallic species, and 26.7% of carbonic species (EC and OC). Ionic species, especially sulfate, ammonium, and nitrate, were the most abundant in the $PM_{2.5}$ and exhibited a high correlation coefficient with the mass concentration of $PM_{2.5}$. Seasonal variations of $PM_{2.5}$ showed a similar pattern to those of ionic and metallic species, with high concentrations during winter and spring. $PM_{2.5}$ also had a high correlation with the ionic species $NO_3{^-}$ and $NH_4{^+}$. In addition, $NH_4{^+}$ was highly correlated with $NO_3{^-}$. Through factor analysis, we identified four controlling factors, and determined the pollution sources using the United States Environmental Protection Agency(U.S. EPA) pollution profile. The first factor, accounting for 19.1% of $PM_{2.5}$ was attributed to motor vehicles and heating-related sources: the second factor indicated industry-related sources and secondary particles, and the other factors indicated soil, industry-related and marine sources. However, the pollution profile used in this study may be somewhat different from the actual situation in Korea, since it was obtained from US EPA. Therefore, to more accurately estimate the pollutants present in the air, a pollution profile for Korea should be produced.