• 한국환경보건학회지
• /
• 제36권6호
• /
• pp.480-495
• /
• 2010

This study evaluated the distribution of the concentrations of nano-particles and heavy metals (08-Pb, Cr, Zn, As, Fe, 09-Pb, Cr, Zn, Cu, Ni, Mn) in Seoul, Chungnam A and Gwangyang from August to December, in 2008 5 times each in the Seoul area, 5 times in and Chungnam A area and from August to November, in 2009 14 times in the Chungnam A area, 8 times in the Gwangyang area. The examined results showed high concentration level from $PM_1$ through $PM_{0.1}$ in all three areas. These results were obtained the concentration of particles by diameter and statistically significant in Stage5 (1.0-0.56 ${\mu}m$) from the result of conducting Kruskal-Wallis H test (p < 0.05). In the case of the heavy metal concentration included in 0.10-0.056 ${\mu}m$, 0.056 ${\mu}m$, the lead concentration of Chungnam Asan area was 6.49 ng/$m^3$ and 9.93 ng/$m^3$, which was higher than 3.05 ng/$m^3$ and 4.22 ng/$m^3$ of Seoul, respectively. The concentration of iron in Seoul was 9.28 ng/$m^3$ and 13.24 ng/$m^3$, that appeared higher than 2.38 ng/$m^3$ and 3.23 ng/$m^3$ of Chungnam A area, respectively. The concentration level was similar to other metals except lead and iron in Chungnam A area and Seoul. From the concentration of heavy metal included in 0.10-0.056 ${\mu}m$, 0.056 ${\mu}m$, the lead concentration of Chungnam A area was 0.31 ng/$m^3$ and 0.12 ng/$m^3$ while Gwangyang was 0.28 ng/$m^3$, 0.06 ng/$m^3$. Thus Chungnam A area showed higher lead concentration than Gwangyang. The manganese concentration of Chungnam A area was 0.12 ng/$m^3$ and 0.03 ng/$m^3$ while Gwangyang was 0.21 ng/$m^3$ and 0.08 ng/$m^3$. Therefore, the concentration of Gwangyang appeared higher than that of Chunnam A area. These two metals showed statistically significant in 0.056 ${\mu}m$ (p < 0.05, p < 0.01). Among the concentration of heavy metal in all regions, the result demonstrated that the order of higher concentration is arsenic > iron > zinc > chrome > lead > nickel > copper > manganese.

• 한국산업보건학회지
• /
• 제1권1호
• /
• pp.89-99
• /
• 1991

The metal concentrations in lungs from 12 coal workers' pneumoconiosis(CWP) patients and 6 controls, who were not exposed occupationally to coal mine dust and metals during their life time, were analyzed by atomic absorption spectrophotometry. 1. Copper, lead, nickel, magnesium, manganese, zinc and iron concentrations in lungs of CWP patients were $1.10{\pm}0.088$, $1.12{\pm}0.068$, $0.22{\pm}0.020$, $113.7{\pm}1.31$, $0.19{\pm}0.012$, $10.2{\pm}1.54$, $426.7{\pm}2.63{\mu}g/g$ wet weight. 2. Copper, lead, nickel, magnesium, manganese, zinc and iron concentrations in lungs of controls were $1.10{\pm}0.013$, $0.85{\pm}0.007$, $0.10{\pm}0.008$, $87.6{\pm}1.29$, $0.18{\pm}0.005$, $10.6{\pm}1.44$, $164.9{\pm}3.29{\mu}g/g$ wet weight. 3. The ratios of concentrations for copper, lead, nickel, magnesium, manganese, zinc, and iron in lungs for CWP patients and controls were 1 : 1, 1.32 : 1, 2.20 : 1, 1.30 : 1, 1.06 : 1, 0.92 : 1, 2.58 : 1, respectively. There were significant differences in concentrations of lead, nickel, magnesium, iron by group(p<0.05). 4. There was no significant difference in metal concentrations of right upper lobe, right lower lobe, left upper lobe and left lower lobe for both CWP patients and controls (p>0.05, p>0.05). 5. In CWP patients lead was well correlated with nickel showing a rank correlation coefficient of 0.533, and zinc was correlated with copper showing a rank correlation coefficient of 0.476. 6. The concentrations of copper, nickel, maganese, and zinc in Korean CWP patients were lower than those in foreign CWP patients.

• 한국대기환경학회지
• /
• 제24권4호
• /
• pp.439-454
• /
• 2008

The purpose of this study was to extensively identify $PM_{10}$ sources and to estimate their contributions to the study area, based on the analysis of the $PM_{10}$ mass concentration and the associated inorganic elements, ions, and total carbon. The contribution of $PM_{10}$ sources was estimated by applying a receptor method because identifying air emission sources were effective way to control the ambient air quality. $PM_{10}$ particles were collected from May to November 2007 in the Yongin-Suwon bordering area. $PM_{10}$ samples were collected on quartz filters by a $PM_{10}$ high-volume air sampler. The inorganic elements (Al, Mn, V, Cr, Fe, Ni, Cu, Zn, Cd, Pb, Si, Ba, Ti and Ag) were analyzed by an ICP-AES after proper pre-treatments of each sample. The ionic components of these $PM_{10}$ samples ($Cl^_$, $NO_3^-$, $SO_4^{2-}$, $Na^+$, $NH_4^+$, $K^+$, $Ca^{2+}$, and $Mg^{2+}$) were analyzed by an IC. The carbon components (OC1, OC2, OC3, OC4, OP, EC1, EC2 and EC3) were also analyzed by DRI/OGC analyzer. Source apportionment of $PM_{10}$ was performed using a positive matrix factorization (PMF) model. After performing PMF modeling, a total of 8 sources were identified and their contribution were estimated. Contributions from each emission source were as follows: 13.8% from oil combustion and industrial related source, 25.4% from soil source, 22.1% from secondary sulfate, 12.3% from secondary nitrate, 17.7% from auto emission including diesel (12.1%) and gasoline (5.6%), 3.1% from waste incineration and 5.6% from Na-rich source. This study provides information on the major sources affecting air quality in the receptor site, and therefore it will help us maintain and manage the ambient air quality in the Yongin-Suwon bordering area by establishing reliable control strategies for the related sources.

• 한국대기환경학회지
• /
• 제29권1호
• /
• pp.74-85
• /
• 2013

Since the underground transportation system is a closed environment, indoor air quality problems may seriously affect many passengers' health. The purpose of this study was to understand $PM_{10}$ characteristics in the underground air environment and further to quantitatively estimate $PM_{10}$ source contributions in a Seoul Metropolitan subway station. The $PM_{10}$ was intensively collected on various filters with $PM_{10}$ aerosol samplers to obtain sufficient samples for its chemical analysis. Sampling was carried out in the M station on the Line-4 from April 21 to 28, July 13 to 21, and October 11 to 19 in the year of 2010 and January 11 to 17 in the year of 2011. The aerosol filter samples were then analyzed for metals, water soluble ions, and carbon components. The 29 chemical species (OC1, OC2, OC3, OC4, CC, PC, EC, Ag, Al, Ba, Cd, Cr, Cu, Fe, Mn, Ni, Pb, Si, Ti, V, Zn, $Cl^-$, $NO_3{^-}$, $SO_4{^{2-}}$, $Na^+$, $NH_4{^+}$, $K^+$, $Mg^{2+}$, $Ca^{2+}$) were analyzed by using ICP-AES, IC, and TOR after proper pretreatments of each sample filter. Based on the chemical information, positive matrix factorization (PMF) model was applied to identify the $PM_{10}$ sources and then six sources such as biomass burning, outdoor, vehicle, soil and road dust, secondary aerosol, ferrous, and brakewear related source were classified. The contributions rate of their sources in tunnel are 4.0%, 5.8%, 1.6%, 17.9%, 13.8% and 56.9% in order.

• 한국수산과학회지
• /
• 제44권5호
• /
• pp.554-559
• /
• 2011

To measure the proximate composition and mineral content of laver Porphyra yezoensis, we collected 30 raw and 30 dried laver from the major production area of the south coast of Korea (Busan, Goheung, Haenam, Wando). The approximate composition of a 100 g edible portion of raw laver was $89.9{\pm}1.4$ g moisture, $3.7{\pm}1.0$ g protein, $0.5{\pm}0.2$ g lipids, $2.1{\pm}1.8$ g carbohydrate and $3.9{\pm}0.6$ g ash. The approximate composition of a 100 g portion of dried laver was $8.9{\pm}1.6$ g moisture, $31.5{\pm}6.5$ g protein, $1.9{\pm}0.3$ g lipids, $48.4{\pm}6.5$ g carbohydrate and $9.3{\pm}1.1$ g ash. No clear regional variation in laver composition was observed. The mineral content of laver was expressed as dry weight. The mean macro mineral content per 100 g portion of raw laver was (in descending order): K ($1,979{\pm}863.0$ mg), Na ($1,063.2{\pm}498.8$ mg), P ($658.7{\pm}101.8$ mg), Mg ($432.3{\pm}83.5$ mg) and Ca ($394.2{\pm}136.5$ mg). In comparison, the mean micro mineral content of raw laver was (in descending order): Fe ($243.72{\pm}154.75\;{\mu}g/g$), Zn ($72.76{\pm}30.61\;{\mu}g/g$), Mn ($41.53{\pm}15.33\;{\mu}g/g$), Cu ($4.16{\pm}1.66\;{\mu}g/g$) and Ni ($0.43{\pm}0.70\;{\mu}g/g$) No clear regional variation in the mineral content of laver was observed; however, raw laver contained a higher mineral content than dried laver.

• Ocean and Polar Research
• /
• 제24권2호
• /
• pp.123-134
• /
• 2002

Seasonal variations of settling particles and metal fluxes were monitored at a nearshore site of Marian Cove, King Geroge Island, Antarctica from 28th February 1998 to 22nd January 2000. Near-bottom sediment traps were deployed at 30m water depth of the cove, and sampling bottles were recovered every month by SCUBA divers. Total particulate flux and metal concentrations were determined from the samples. Total particulate flux showed a distinct seasonality, high in austral summer and low in austral winter: the highest flux $(21.97g\;m^{-2}d^{-1})$ was found in February of 1999, and the lowest $(2.47g\;m^{-2}d^{-1})$ in September of 1998, when sea surface was frozen completely. Lithogenic particle flux accounted for 90% of the total flux, and showed a significantly negative correlation with the thickness of snow accumulation around the study site. It was suggested that the most of the lithogenic particles trapped in the bottles was transported by melt water stream from the surrounding land. Fluxes of Al, Fe, Ti, Mn, Zn, Cii, Co, Ni, Cr, Cd, and Pb showed similar seasonal variations with the total flux, and their averaged fluxes were 34000, 9000,960, 180, 13.8, 17.6, 3.0,2.1, 5.4, 0.02, and $1.5nmol\;m^{-2}d^{-1}$ respectively. Among the metals, Cu and Cd showed the most noticeable seasonal patterns. The Cd flux correlated positively with the fluxes of biogenic components while the Cu flux correlated with both the lithogenic and biogenic particle fluxes. The Cu flux peak in the late summer is likely related to a substantial amount of inflow of ice melt water laden with Cu-enriched lithogenic particles. On the other hands, the Cd flux peak in the early spring may be associated with the unusually early occurred phytoplankton bloom.

• Asian-Australasian Journal of Animal Sciences
• /
• 제31권4호
• /
• pp.607-615
• /
• 2018

Objective: This study was conducted to isolate the cellulolytic microorganism from the rumen of Holstein steers and characterize endoglucanase gene (Cel5A) from the isolated microorganism. Methods: To isolate anaerobic microbes having endoglucanase, rumen fluid was obtained from Holstein steers fed roughage diet. The isolated anaerobic bacteria had 98% similarity with Eubacterium cellulosolvens (E. cellulosolvens) Ce2 (Accession number: AB163733). The Cel5A from isolated E. cellulolsovens sp. was cloned using the published genome sequence and expressed through the Escherichia coli BL21. Results: The maximum activity of recombinant Cel5A (rCel5A) was observed at $50^{\circ}C$ and pH 4.0. The enzyme was constant at the temperature range of $20^{\circ}C$ to $40^{\circ}C$ but also, at the pH range of 3 to 9. The metal ions including $Ca^{2+}$, $K^+$, $Ni^{2+}$,$Mg^{2+}$, and $Fe^{2+}$ increased the endoglucanase activity but the addition of $Mn^{2+}$, $Cu^{2+}$, and $Zn^{2+}$ decreased. The Km and Vmax value of rCel5A were 14.05 mg/mL and $45.66{\mu}mol/min/mg$. Turnover number, Kcat and catalytic efficiency, Kcat/Km values of rCel5A was $96.69(s^{-1})$ and 6.88 (mL/mg/s), respectively. Conclusion: Our results indicated that rCel5A of E. cellulosolvens isolated from Holstein steers had a broad pH range with high stability under various conditions, which might be one of the beneficial characteristics of this enzyme for possible industrial application.

• 한국대기환경학회지
• /
• 제27권6호
• /
• pp.711-722
• /
• 2011

This study is aimed to estimate the $PM_{2.5}$ source apportionment at Seoul intensive monitoring site located in Seoul metropolitan area. Time-resolved chemical compositions of $PM_{2.5}$ are measured in real time using ambient ion monitor, semi-continuous carbon monitor, and on-line XRF at Seoul intensive monitoring site in 2010. The mass concentration of $PM_{2.5}$ was simultaneously monitored with eight ionic species (${SO_4}^{2-}$, $NO_3{^-}$, $Cl^-$, $NH_4{^+}$, $Na^+$, $K^+$, $Mg^{2+}$, $Ca^{2+}$), two carbonaceous species (OC and EC), and fourteen elements (Si, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Zn, As, Se, Pb) in 1-hr interval. The data sets were then analyzed using EPA PMF version 3 to identify sources and contributions to $PM_{2.5}$ mass. EPA PMF modeling identified eight PM2.5 sources, including soil dust, secondary sulfate, secondary nitrate, motor vehicle, coal combustion, oil combustion, biomass burning, and municipal incineration. This study found that the average $PM_{2.5}$ mass was apportioned to anthropogenic sources such as motor vehicle, fuel combustion, and biomass burning (61%) and secondary aerosols, including sulfate and nitrate (38%).

• 한국대기환경학회지
• /
• 제22권5호
• /
• pp.590-603
• /
• 2006

Size-and time-resolved aerosol samples were collected using an eight-stage Davis rotating unit for monitoring (DRUM) sampler from 23 March to 29 April 2001 at Gosan, Jeju Island, Korea, which is one of the super sites of Asia-Pacific Regional Aerosol Characterization Experiment(ACE-Asia). These samples were analyzed using synchrotron X-ray fluorescence for 3-hr average concentrations of 19 elements including Al, Si, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, As, Se, Br, Rb, and Pb. The size-resolved data sets were then analyzed using the positive matrix factorization(PMF) technique to identify possible sources and estimate their contributions to particulate matter mass. PMF analysis uses the uncertainty of the measured data to provide an optimal weighting. Twelve sources were resolved in eight size ranges($0.09{\sim}12{\mu}m$) and included continental soil, local soil, sea salt, biomass/biofuel burning, coal combustion, oil combustion, municipal incineration, nonferrous metal source, ferrous metal source, gasoline vehicle, diesel vehicle, and volcanic emission. The PMF result of size-resolved source contributions showed that natural sources represented by local soil, sea salt, continental soil, and volcanic emission contributed about 79% to the predicted primary particulate matter(PM) mass in the coarse size range ($1.15{\sim}12{\mu}m$) while anthropogenic sources such as coal combustion and biomass/biofuel burning contributed about 58% in the fine size range($0.56{\sim}2.5{\mu}m$). The diesel vehicle source contributed mostly in ultra-fine size range($0.09{\sim}0.56{\mu}m$) and was responsible for about 56% of the primary PM mass.

• 자원환경지질
• /
• 제35권1호
• /
• pp.75-95
• /
• 2002

안동심성암체는 3개 암상으로 구분되는 동원성 마그마로부터 유래되었다. 이 암체는 전체적으로 중앙부에 각섬석 흑운모 토날라이트가 노출되고 이의 연변부에 흑운모 화강섬록암이 놓이며, 상단부(복동부)에 반상 흑운모 화강암이 놓인다. 결과적으로 이들은 토날라이트를 중심으로 하는 동심원상 분포를 하며, 중앙부에 고온 광물군의 고철질 암석이 우세하고 연변부와 상단부로 갓수록 보다 저온 광물군의 규장질 암석이 우세한 역누대를 나타낸다. 이 암체의 모드 및 화학 자료는 중앙부에서 연변부, 상단부 순으로 역누대 조성변화를 보여준다. 이 조성변화는 인접하는 암상간에서 매우 점이적으로 변화한다. 각섬석과 흑운모 등의 고철질 광물은 중앙부의 토날라이트에서 가장 풍부하고 연변부로 갈면서 감소하고 상단부로 갈수록 더욱 감소한다. 석영과 K-장석 등의 규장질 광물은 이와 반대로 변화한다. 화학적으로도 고철질 광물을 지배하는 원소들은 중앙부에서 최고치이고 이로부터 연변부와 상단부로 갈수록 점차 감소되는 양상을 보이며, 반면에 규장질 광물을 주로 지배하는 원소들은 이와 반대 양상을 나타낸다. 이 역누대 심성암체는 열중력확산작용과 분별결정작용에 의해 수정된 마그마챔버의 상부 규장질 부분 속으로 하부의 더 고철질 부분이 재이동(소생)된 결과이다. 진화의 초기 단계에 , 이 마그마챔비는 하부에 토날라이트질, 중부에 화강섬록암질, 상부에 화강암질 마그마를 갖는 화학적 조성누대를 이룬 암석화학계이었다. 후기 단계에 챔버 기저에서 더 고철질 마그마의 유입에 의해 하부의 토날라이트질 조성대가 상부의 규장질 조성대 속으로 재이동을 야기시켰다.