• Journal of Life Science
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• v.34 no.5
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• pp.304-312
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• 2024

This study was conducted to characterize strain Y10, isolated from discarded chicken feathers. Strain Y10 was identified as Bacillus amyloliquefaciens through phenotypic and 16S rRNA gene analysis. B. amyloliquefaciens Y10 exhibited plant growth-promoting activities, including the production of fungal cell-degrading enzymes (cellulase, lipase, protease, and pectinase), siderophores, ammonia, and indoleacetic acid. Furthermore, strain Y10 was able to inhibit the mycelial growth of several phytopathogenic fungi. When 0.1% sucrose as a carbon source and 0.05% casein as a nitrogen source were added to the basal medium, adjusted to pH 10, and cultured at 35℃, the degradation rate of chicken feathers by strain Y10 was about two times higher than that of the basal medium, with the feathers almost completely degraded in four days. Strain Y10 also degraded various keratin substrates, including duck feathers, wool, and human nails. It was confirmed that the feather hydrolyzates prepared using strain Y10 exhibited antioxidant activities, such as 1,1-diphenyl-2-picrylhydrazyl radical scavenging activity (EC₅₀ = 0.38 mg/ml) and superoxide dismutase-like activity (EC₅₀ = 183.7 mg/ml). These results suggest that B. amyloliquefaciens Y10 is a potential candidate for the development of bioinoculants and feed additives applicable to the agricultural and livestock industries, as well as the microbiological treatment of keratin waste.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.13 no.2
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• pp.121-128
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• 2008

As an aquatic ecotoxicity test method, a bioassay using the inhibition of sporualtion of the green macroalga, Ulva pertusa, has been developed. Optimal test conditions determined for photon irradiance, pH, salinity and temperature were $100\;{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$, $7{\sim}9$, $25{\sim}35\;psu$ and $15{\sim}20^{\circ}C$, respectively. The validity of the test endpoint was evaluated by assessing the toxicity of four metals (Cd, Cu, Pb, Zn) and elutriates of sewage or waste sludge collected from 9 different locations. When the metals were assayed, the $EC_{50}$ values indicated the following toxicity rankings: Cu ($0.062\;mg{\cdot}L^{-1}$) > Cd ($0.208\;mg{\cdot}L^{-1}$) > Pb ($0.718\;mg{\cdot}L^{-1}$) > Zn ($0.776\;mg{\cdot}L^{-1}$). When compared with other commonly used bioassays of metal pollution listed on US ECOTOX database, the sporualtion test proved to be the most sensitive. Ulva sporulation was significantly inhibited in all elutriates with the greatest and least effects observed in elutriates of sludge from industrial waste ($EC_{50}=6.78%$) and filtration bed ($EC_{50}=15.0%$), respectively. The results of the Spearman rank correlation analysis for $EC_{50}$ data versus the concentrations of toxicants in the sludge presented a significant correlation between toxicity and four heavy metals(Cd, Cu, Pb, Zn). The method described here is sensitive to toxicants, simple to use, easy to interpret and economical. It is also easy to procure samples and maintain cultures. The present method would therefore probably make a useful assessment of aquatic toxicity of a wide range of toxicants. In addition, the genus Ulva has a wide geographical distribution and species have similar reproductive processes, so the test method would have a potential application worldwide.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.25 no.3
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• pp.380-391
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• 2015

Objectives: The objective of this study is to assess airborne particulate matter pollution and its effect on health of residents living near Ansim Briquette Fuel Complex and its vicinities. Also, this study measured and analyzed the concentration of TSP, $PM_{10}$, $PM_{2.5}$, and heavy metals which influences on the environmental and respiratory disease in Ansim Briquette Fuel Complex, Daegu, Korea. Methods: In this study, we analyzed various environmental pollutants such as particulate matter and heavy metals from Ansim Briquette Fuel Complex that adversely affected local residents's health. In particular, we verified the concentration distribution and characteristics of exposure for TSP, $PM_{10}$, and $PM_{2.5}$ among particulate matters, and heavy metals(Cd, Cr, Cu, Mn, Ni, Pb, Fe, Zn, and Mg). In that regard, the official test method on air pollution in Korea for analysis of particulate matter and heavy metal in atmosphere were conducted. The large capacity air sampling method by the official test method on air pollution in Korea were applied for sampling of heavy metals in atmosphere. In addition, we evaluated the concentration of seasonal environmental pollutants for each point of residence in Ansim Briquette Fuel Complex and surrounding area. The sampling measured periods for air pollutants were from August 11, 2013 to February 21, 2014. Furthermore, we measured and analyzed the seasonal concentrations(summer, autumn and winter). Results: The average concentration for TSP, $PM_{10}$, and $PM_{2.5}$ by direct influence area at Ansim Briquette Fuel Complex were 1.7, 1.4 and 1.9 times higher than reference region. In analysis results of seasonal concentrations for particulate matter in four direct influence and reference area, concentration levels for winter were generally somewhat higher than concentrations for summer and autumn. The average concentrations for Cd, Cr, Mn, Ni, Pb, Fe, and Zn in direct influence area at Ansim Briquette Fuel Complex were $0.0008{\pm}0.0004{\mu}g/Sm^3$, $0.0141{\pm}0.0163{\mu}g/Sm^3$, $0.0248{\pm}0.0059{\mu}g/Sm^3$, $0.0026{\pm}0.0011{\mu}g/Sm^3$, $0.0272{\pm}0.0084{\mu}g/Sm^3$, $0.4855{\pm}0.1862{\mu}g/Sm^3$, and $0.3068{\pm}0.0631{\mu}g/Sm^3$, respectively. In particularly, the average concentrations for Cd, Cr, Mn, Ni, Pb, Fe, and Zn in direct influence area at Ansim Briquette Fuel Complex were 1.9, 3.6, 2.1, 1.9, 1.4, 2.6, and 1.2 times higher than reference area, respectively. The continuous monitoring and management were required for some heavy metals such as Cr and Ni. Moreover, the average concentration in winter for particulate matter in direct influence area at Ansim Briquette Fuel Complex were generally higher than concentrations in summer and autumn. Also, average concentrations for TSP, $PM_{10}$, and $PM_{2.5}$ were from 1.5 to 2.0 times, 1.2 to 1.8 times, and 1.1 to 2.3 times higher than reference area, respectively. In results for seasonal atmospheric environment, TSP, $PM_{10}$, $PM_{2.5}$, and heavy metal concentrations in direct influence area were higher than reference area. Especially, the concentrations in C station were a high level in comparison with other area. Conclusions: In the results, some particulate matters and heavy metals were relatively high concentration, in order to understand the environmental pollution level and health effect in surrounding area at Ansim Briquette Fuel Complex. The concentration of some heavy metals emitted from direct influence area at Ansim Briquette Fuel Complex were relatively higher than reference area. In particular, average concentration for heavy metals in this study were higher than average concentrations in air quality monitoring station for heavy metal for 7 years in Deagu metropolitan region. Especially, the residents near Ansim Briquette Fuel Complex may be exposed to the pollutants(TSP, $PM_{10}$, $PM_{2.5}$, and heavy metals, etc) emitted from the factories in Ansim Briquette Fuel Complex.

• Solar Energy
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• v.13 no.2_3
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• pp.65-78
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• 1993

An overdose of fossil fuel for greenhouse heating causes not only the high cost and low quality of agricultural products, but also the environmental pollution of farm village. To solve these problems it is desirable to maximize the solar energy utilization for the heating of greenhouse in winter season. In this study phase change materials were selected to store solar energy concentratively for heating the greenhouse and their characteristics of thermal energy storage were analyzed. The results were summarized as follows. The organic $C_{28}H_{58}$, and the inorganic $CH_3COONa{\cdot}3H_2O\;and\;Na_2SO_4{\cdot}10H_2O$ were selected as low temperature latent heat storage materials. The equation of critical radius was derived to define the generating mechanism of the maximum latent heat of phase change materials. The melting point of $C_{28}H_{58}$ was $62^{\circ}C$, and the latent heat was $50.0{\sim}52.0kcal/kg$. The specific heat of liquid and solid phase was $0.54{\sim}0.69kcal/kg^{\circ}C$ and $0.57{\sim}0.75kcal/kg^{\circ}C$ respectively. The melting point of $CH_3COONa{\cdot}3H_2O$ was $61{\sim}62^{\circ}C$, the latent heat was $64.9{\sim}65.8$ kcal/kg and the specific heat of liquid and solid phase was respectively $0.83kcal/kg^{\circ}C$ and $0.51{\sim}0.52kcal/kg^{\circ}C$. The melting point of $Na_2SO_4{\cdot}10H_2O$ was $30{\sim}30.9^{\circ}C$, the latent heat was 53.0 kcal/kg and the specific heat of liquid and solid phase was respectively $0.78{\sim}0.89kcal/kg^{\circ}C$ and $0.50{\sim}0.7kcal/kg^{\circ}C$ When the urea of 21.85% was added to control the melting point of $Na_2SO_4{\cdot}10H_2O$ and the phase change cycles were repeated from 0 to 600, the melting point was $16.7{\sim}16.0^{\circ}C$ and the latent heat was $36.0{\sim}28.0kcal/kg^{\circ}C$.

• Journal of environmental and Sanitary engineering
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• v.24 no.4
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• pp.1-26
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• 2009

We conclude the following with air pollution data measured from city measurement net administered and managed in Gwangju for the last 7 years from January in 2001 to December in 2007. In addition, some major statistics governed by Gwangju city and data administered by Gwangju as national official statistics obtained by estimating the amount of national air pollutant emission from National Institute of Environmental Research were used. The results are as follows ; 1. The distribution by main managements of air emission factory is the following ; Gwangju City Hall(67.8%) > Gwangsan District Office(13.6%) > Buk District Office(9.8%) > Seo District Office(5.5%) > Nam District Office(3.0%) > Dong District Office(0.3%) and the distribution by districts of air emission factory ; Buk District(32.8%) > Gwangsan District(22.4%) > Seo District(21.8%) > Nam District(14.9%) > Dong District(8.1%). That by types(Year 2004~2007 average) is also following ; Type 5(45.2%) > Type 4(40.7%) > Type 3(8.6%) > Type 2(3.2%) > Type 1(2.2%) and the most of them are small size of factory, Type 4 and 5. 2. The distribution by districts of the number of car registrations is the following ; Buk District(32.8%) > Gwangsan District(22.4%) > Seo District(21.8%) > Nam District(14.9%) > Dong District(8.1%) and the distribution by use of car fuel in 2001 ; Gasoline(56.3%) > Diesel(30.3%) > LPG(13.4%) > etc.(0.2%). In 2007, there was no ranking change ; Gasoline(47.8%) > Diesel(35.6%) > LPG(16.2%) >etc.(0.4%). The number of gasoline cars increased slightly, but that of diesel and LPG cars increased remarkably. 3. The distribution by items of the amount of air pollutant emission in Gwangju is the following; CO(36.7%) > NOx(32.7%) > VOC(26.7%) > SOx(2.3%) > PM-10(1.5%). The amount of CO and NOx, which are generally generated from cars, is very large percentage among them. 4. The distribution by mean of air pollutant emission(SOx, NOx, CO, VOC, PM-10) of each county for 5 years(2001~2005) is the following ; Buk District(31.0%) > Gwangsan District(28.2%) > Seo District(20.4%) > Nam District(12.5%) > Dong District(7.9%). The amount of air pollutant emission in Buk District, which has the most population, car registrations, and air pollutant emission businesses, was the highest. On the other hand, that of air pollutant emission in Dong District, which has the least population, car registrations, and air pollutant emission businesses, was the least. 5. The average rates of SOx for 5 years(2001~2005) in Gwangju is the following ; Non industrial combustion(59.5%) > Combustion in manufacturing industry(20.4%) > Road transportation(11.4%) > Non-road transportation(3.8%) > Waste disposal(3.7%) > Production process(1.1%). And the distribution of average amount of SOx emission of each county is shown as Gwangsan District(33.3%) > Buk District(28.0%) > Seo District(19.3%) > Nam District(10.2%) > Dong District(9.1%). 6. The distribution of the amount of NOx emission in Gwangju is shown as Road transportation(59.1%) > Non-road transportation(18.9%) > Non industrial combustion(13.3%) > Combustion in manufacturing industry(6.9%) > Waste disposal(1.6%) > Production process(0.1%). And the distribution of the amount of NOx emission from each county is the following ; Buk District(30.7%) > Gwangsan District(28.8%) > Seo District(20.5%) > Nam District(12.2%) > Dong District(7.8%). 7. The distribution of the amount of carbon monoxide emission in Gwangju is shown as Road transportation(82.0%) > Non industrial combustion(10.6%) > Non-road transportation(5.4%) > Combustion in manufacturing industry(1.7%) > Waste disposal(0.3%). And the distribution of the amount of carbon monoxide emission from each county is the following ; Buk District(33.0%) > Seo District(22.3%) > Gwangsan District(21.3%) > Nam District(14.3%) > Dong District(9.1%). 8. The distribution of the amount of Volatile Organic Compound emission in Gwangju is shown as Solvent utilization(69.5%) > Road transportation(19.8%) > Energy storage & transport(4.4%) > Non-road transportation(2.8%) > Waste disposal(2.4%) > Non industrial combustion(0.5%) > Production process(0.4%) > Combustion in manufacturing industry(0.3%). And the distribution of the amount of Volatile Organic Compound emission from each county is the following ; Gwangsan District(36.8%) > Buk District(28.7%) > Seo District(17.8%) > Nam District(10.4%) > Dong District(6.3%). 9. The distribution of the amount of minute dust emission in Gwangju is shown as Road transportation(76.7%) > Non-road transportation(16.3%) > Non industrial combustion(6.1%) > Combustion in manufacturing industry(0.7%) > Waste disposal(0.2%) > Production process(0.1%). And the distribution of the amount of minute dust emission from each county is the following ; Buk District(32.8%) > Gwangsan District(26.0%) > Seo District(19.5%) > Nam District(13.2%) > Dong District(8.5%). 10. According to the major source of emission of each items, that of oxides of sulfur is Non industrial combustion, heating of residence, business and agriculture and stockbreeding. And that of NOx, carbon monoxide, minute dust is Road transportation, emission of cars and two-wheeled vehicles. Also, that of VOC is Solvent utilization emission facilities due to Solvent utilization. 11. The concentration of sulfurous acid gas has been 0.004ppm since 2001 and there has not been no concentration change year by year. It is considered that the use of sulfurous acid gas is now reaching to the stabilization stage. This is found by the facts that the use of fuel is steadily changing from solid or liquid fuel to low sulfur liquid fuel containing very little amount of sulfur element or gas, so that nearly no change in concentration has been shown regularly. 12. Concerning changes of the concentration of throughout time, the concentration of NO has been shown relatively higher than that of $NO_2$ between 6AM~1PM and the concentration of $NO_2$ higher during the other time. The concentration of NOx(NO, $NO_2$) has been relatively high during weekday evenings. This result shows that there is correlation between the concentration of NOx and car traffics as we can see the Road transportation which accounts for 59.1% among the amount of NOx emission. 13. 49.1~61.2% of PM-10 shows PM-2.5 concerning the relationship between PM-10 and PM-2.5 and PM-2.5 among dust accounts for 45.4%~44.5% of PM-10 during March and April which is the lowest rates. This proves that particles of yellow sand that are bigger than the size $2.5\;{\mu}m$ are sent more than those that are smaller from China. This result shows that particles smaller than $2.5\;{\mu}m$ among dust exist much during July~August and December~January and 76.7% of minute dust is proved to be road transportation in Gwangju.

• Journal of Environmental Policy
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• v.13 no.4
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• pp.3-49
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• 2014

Growing interest of stakeholders on corporate responsibilities for environment and tightening environmental regulations are highlighting the importance of environmental management more than ever. However, companies' awareness of the importance of environment is still falling behind, and related academic works have not shown consistent conclusions on the relationship between environmental performance and economic performance. One of the reasons is different ways of measuring these two performances. The evaluation scope of economic performance is relatively narrow and the performance can be measured by a unified unit such as price, while the scope of environmental performance is diverse and a wide range of units are used for measuring environmental performances instead of using a single unified unit. Therefore, the results of works can be different depending on the performance indicators selected. In order to resolve this problem, generalized and standardized performance indicators should be developed. In particular, the performance indicators should be able to cover the concepts of both environmental and economic performances because the recent idea of environmental management has expanded to encompass the concept of sustainability. Another reason is that most of the current researches tend to focus on the motive of environmental investments and environmental performance, and do not offer a guideline for an effective implementation strategy for environmental management. For example, a process improvement strategy or a market discrimination strategy can be deployed through comparing the environment competitiveness among the companies in the same or similar industries, so that a virtuous cyclical relationship between environmental and economic performances can be secured. A novel method for measuring eco-efficiency by utilizing Data Envelopment Analysis (DEA), which is able to combine multiple environmental and economic performances, is proposed in this report. Based on the eco-efficiencies, the environmental competitiveness is analyzed and the optimal combination of inputs and outputs are recommended for improving the eco-efficiencies of inefficient firms. Furthermore, the panel analysis is applied to the causal relationship between eco-efficiency and economic performance, and the pooled regression model is used to investigate the relationship between eco-efficiency and economic performance. The four-year eco-efficiencies between 2010 and 2013 of 23 companies are obtained from the DEA analysis; a comparison of efficiencies among 23 companies is carried out in terms of technical efficiency(TE), pure technical efficiency(PTE) and scale efficiency(SE), and then a set of recommendations for optimal combination of inputs and outputs are suggested for the inefficient companies. Furthermore, the experimental results with the panel analysis have demonstrated the causality from eco-efficiency to economic performance. The results of the pooled regression have shown that eco-efficiency positively affect financial perform ances(ROA and ROS) of the companies, as well as firm values(Tobin Q, stock price, and stock returns). This report proposes a novel approach for generating standardized performance indicators obtained from multiple environmental and economic performances, so that it is able to enhance the generality of relevant researches and provide a deep insight into the sustainability of environmental management. Furthermore, using efficiency indicators obtained from the DEA model, the cause of change in eco-efficiency can be investigated and an effective strategy for environmental management can be suggested. Finally, this report can be a motive for environmental management by providing empirical evidence that environmental investments can improve economic performance.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.5 no.3
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• pp.195-207
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• 2000

Organic and inorganic characteristics including bacterial cell number, enzyme activity, nutrients, and heavy metals have been monitored in twelve acrylic experimental tanks for two weeks to estimate and compare self-purification capacities in two Korean wet-land environments, tidal flat and rice field, which are possibly different with the environments in other countries because of their own climatic conditions. FW tanks, filled with rice field soils and fresh water, consist of FW1&2 (with paddy), FW3&4 (without paddy), and FW5&6 (newly reclaimed, without paddy). SW tanks, filled with tidal flat sediments and salt water, are SW1&2 (with anoxic silty mud), SW3&4 (anoxic mud), and SW5&6 (suboxic mud). Contaminated solution, which is formulated with the salts of Cu, Cd, As, Cr, Pb, Hg, and glucose+glutamic acid, was spiked into the supernatent waters in the tanks. Nitrate concentrations in supernatent waters as well as bacterial cell numbers and enzyme activities of soils in the FW tanks (except FW5&6) are clearly higher than those in the SW tanks. Phosphate concentrations in the SW1 tank increase highly with time compared to those in the other SW tanks. Removal rates of Cu, Cd, and As in supematent waters of the FW5&6 tanks are most slow in the FW tanks, while the rates in SW1&2 are most fast in the SW tanks. The rate for Pb in the SW1&2 tanks is most fast in the SW tanks, and the rate for Hg in the FW5&6 tanks is most slow in the FW tanks. Cr concentrations decrease generally with time in the FW tanks. In the SW tanks, however, the Cr concentrations decrease rapidly at first, then increase, and then remain nearly constant. These results imply that labile organic materials are depleted in the FW5&6 tanks compared to the FW1&2 and FW3&4 tanks. Removal of Cu, Cd, As from the supernatent waters as well as slow removal rates of the elements (including Hg) are likely due to the combining of the elements with organic ligands on the suspended particles and subsequent removal to the bottom sediments. Fast removal rates of the metal ions (Cu, Cd, As) and rapid increase of phosphate concentrations in the SW1&2 tanks are possibly due to the relatively porous anoxic sediments in the SW1&2 tanks compared to those in the SW3&4 tanks, efficient supply of phosphate and hydrogen sulfide ions in pore wates to the upper water body, complexing of the metal ions with the sulfide ions, and subsequent removal to the bottom sediments. Organic materials on the particles and sulfide ions from the pore waters are the major factors constraining the behaviors of organic/inorganic elements in the supernatent waters of the experimental tanks. This study needs more consideration on more diverse organic and inorganic elements and experimental conditions such as tidal action, temperature variation, activities of benthic animals, etc.