TiCl₄ 응집을 이용한 조류제거

김경민(Kyung-Min Kim),오흥현(Heung-Hyun Oh),박지원(Ji-Won Park),최종진(Jong-Jin Choi),안종화(Johng-Hwa Ahn) 대한환경공학회 2019 대한환경공학회지 Vol.41 No.6

본 연구에서는 응집제 TiCl4의 조류제거 효율을 관찰하기 위해 jar test를 이용하여 급속교반속도(110~170 rpm), 완속교반속도(20~60 rpm), 주입농도(0.02~0.48 mM), pH (1~12) 등에 따른 클로로필 a 및 탁도 제거율을 관찰하였다. 실험기간 동안 사용한 시료의 클로로필 a는 105.7 ± 10.2 μg/L, 탁도는 17.5 ± 5.7 NTU (nephelometry turbidity unit)였다. 급속교반의 경우 실험범위 내에선 교반속도에 관계없이 높은 클로로필 a (90~94%) 및 탁도(91~93%) 제거효율을 보였다. 완속교반의 경우 클로로필 a는 30 rpm (96%)에서, 탁도는 30 rpm 이상(90% 이상)에서 가장 높은 제거효율을 보였다. 주입농도 실험에서 클로로필 a와 탁도는 TiCl₄의 농도가 증가할수록 제거효율이 증가하는 경향을 보였다. 클로로필 a는 0.25 mM, 탁도는 0.39 mM 이상에서 90% 이상의 제거효율을 보였다. pH의 경우 클로로필 a는 3~8에서 90% 이상, 탁도는 6 이상에서 87% 이상의 제거효율을 보였다. 따라서 클로로필 a와 탁도를 동시에 90% 이상의 제거효율을 얻기 위한 조건은 급속교반속도에 관계없이 완속교반 30 rpm, 주입농도 0.39 mM, pH 6~8로 나타났다. This study evaluated the efficiency of titanium tetrachloride (TiCl₄) on chlorophyll-a (105.7 ± 10.2 μg/L) and turbidity (17.5 ± 5.7 NTU (nephelometry turbidity unit)) removals in a pond water compared to aluminum potassium sulfate (AlK(SO₄)₂). Jar-test experiments were performed at various mixing speeds (rapid: 110~170 rpm, slow: 20~60 rpm), coagulant doses (0.02~0.48 mM), and pH levels (1~12) to determine the conditions at which chlorophyll-a and turbidity removals were most efficient. Within the experimental range, the chlorophyll-a (90~94%) and turbidity (91~93%) removals were high regardless of rapid-mixing speed. The maximum chlorophyll-a removal was 96% at 30 rpm of slow-mixing speed and turbidity removal was ≥90% at ≥30 rpm of slow-mixing speed. The chlorophyll-a removal and turbidity efficiencies increased as TiCl4 concentration ([TiCl₄]) increased. The chlorophyll-a removal at [TiCl4]=0.25 mM and the turbidity removal at [TiCl₄]=0.39 mM were ≥90%. The chlorophyll-a removals at pH=3~8 were ≥90% and the turbidity removals at pH≥6 were ≥87%. Therefore, the conditions with ≥90% chlorophyll-a and turbidity removals were slow mixing=30 rpm, [TiCl4]≥0.39 mM, and 6≤pH≤8 regardless of rapid-mixing speed.

SWMM과 인공신경망을 이용한 미 계측 하천의 클로로필a 추정에 관한 연구

강태욱 ( Tae Uk Kang ),이상호 ( Sang Ho Lee ),김일규 ( Il Kyu Kim ),이남주 ( Nam Ju Lee ) 한국물환경학회 2011 한국물환경학회지 Vol.27 No.5

Chlorophyll-a is a major water quality indicator for an algal bloom in streams and lakes. The purpose of the study is to estimate chlorophyll-a concentration in tributaries of the Seonakdonggang by an artificial neural network (ANN). As the tributaries are ungauged streams, a watershed runoff and quality model was used to simulate water quality parameters. The tributary watersheds include urban area and thus Storm Water Management Model (SWMM) was used to simulate TN, TP, BOD, COD, and SS. SWMM, however, can not simulate chlorophyll-a. The chlorophyll-a series data from the tributaries were estimated by the ANN and the simulation results of water quality parameters using SWMM. An assumption used is as follows: the relation between water quality parameters and chlorophyll-a in the tributaries of the Seonakdonggang would be similar to that in the mainstream of the Seonakdonggang. On the assumption, the measurement data of water quality and chlorophyll-a in the mainstream of the Seonakdonggang were used as the learning data of the ANN. Through the sensitivity analysis, the learning data combination of water quality parameters was determined. Finally, chlorophyll-a series were estimated for tributaries of the Seonakdonggang by the ANN and TN, TP, BOD, COD, and temperature data from those streams. The relative errors between the estimated and measured chlorophyll-a were approximately 40~50%. Though the errors are somewhat large, the estimation process for chlorophyll-a may be useful in ungauged streams.

Landsat 8호 영상을 이용한 진양호의 클로로필 a 농도의 공간분포와 영양상태 분석

장민원 ( Min Won Jang ),조현경 ( Hyun Kyung Cho ),김상민 ( Sang Min Kim ) 한국물환경학회 2019 한국물환경학회지 Vol.35 No.1

The purpose of this study is to evaluate the nutritional status of Lake Jinyang using Landsat 8 satellite image band correlated with chlorophyll-a, which is also related to algae proliferation. We selected 20 Landsat 8 images dating from 2013 to 2017, taken close to water quality measurement date when the cloud cover was less than 20 %. Based on the results of the previous studies, analyzing the correlation between chlorophyll-a, and Landsat 8 satellite image band, we selected near infrared wavelength, band 5 which is closely related to the population of algae. The nutritional status was classified using the Aizaki trophic state index (TSIm). The results of the regression equation between band 5 and the observed chlorophyll-a data was used to calculate chlorophyll-a for the image data from 2013 to 2017. The concentration of chlorophyll-a ranged from 3 to 16.1 mg/m³. To illustrate the spatial distribution of chlorophyll-a within the lake, the chlorophyll-a concentration was divided into five grades. The images on October 14, 2014 and April 10, 2016 showed relatively high value of chlorophyll-a, while January 18, 2015 and December 6, 2016 chlorophyll-a value were below 5. The images on October 14, 2014 and April 10, 2016 were rated as eutrophic status in most areas. The results of simulating water quality for the day when the water quality was not measured resulted to an approximate value for the Panmun station while the Naedong station needed some corrections.

담수호 수질관리를 위한 측정자료의 통계적 분석방법 연구

제갈선동,김진 한국수자원학회 2024 한국수자원학회논문집 Vol.57 No.1

본 연구는 공개된 수질측정 자료를 이용하여 담수호의 수질변화추이를 분석하고 수질항목의 이상여부의 판단기준을 마련하며, 자료로부터 부영양화의 지표인 Chlorophyll-a를 예측할 수 있는 회귀모형을 구성하여 담수호 관리에 이용할 수 있는 방안을 검토하고자 하였다. 이에 따라 서해안 담수호 3개소를 선정하여 약 20년간의 수질항목자료를 회귀분석 방법으로 분석하고, 각 수질항목의 연중 주기적인 변화를 나타내는 회귀식과 신뢰도 95%에서의 표준편차를 산정함으로서 이상 여부의 판단방법을 제시하였다. 또한 불규칙한 관측일로부터 Chlorophyll-a의 시간적 변화율을 산정하고, 다른 수질항목간의 상관관계 분석 및 회귀모형을 구성하여 분석함으로서 수질측정 자료만을 이용하여 Chlorophyll-a의 변화를 예상할 수 있는 방법을 제시하였다. 본 연구결과는 통계학적 모형에 의한 근사적인 수질예측방법으로서 향후 수질측정 자료의 양적·질적 개선이 이루어진다면 담수호 수질관리에 기여할 것으로 기대된다. As using public monitoring data, analysing a trends of water quality change, establishing a criteria to determine abnormal status and constructing a regression model that can predict Chlorophyll-a, an indicator of eutrophication, was studied. Accordingly, the three freshwater lakes were selected, approximately 20 years of water quality monitoring data were analyzed for periodic changes in water quality each year using regression analysis, and a method for determining abnormalities was presented by the standard deviation at confidence level 95%. By calculating the temporal change rate of Chlorophyll-a from irregular observed data, analyzing correlations between the rate and other water quality items, and constructing regression models, a method to predict changes in Chlorophyll-a was presented. The results of this study are expected to contribute to freshwater lake water quality management as an approximate water quality prediction method using the statistical model.

북서태평양의 표층엽록소 변동성

박지수,석문식,윤석,유신재 한국해양과학기술원 2008 Ocean and Polar Research Vol.30 No.3

We collected information on seasonal and interannual variability of surface chlorophyll a concentration between 1997-2007 from the Northwest Pacific Ocean. Satellite data were used to acquire chlorophyll a and sea surface temperature from six regions: East Sea/Ulleung Basin, East China Sea, Philippin Sea, Warm Pool region, Warm Pool North region, and Warm Pool East region. Mixed layer depth (MLD) was calculated from temperature profiles of ARGO floats data in four of the six regions during 2002-2007. In the East Sea/Ulleung Basin, seasonal variability of chlorophyll a concentration was attributed to seasonal change of MLD, while there was no significant relationship between chlorophyll a concentration and MLD in the Warm Pool region. Interannual anomaly in sea surface temperature were similar among the East Sea, East China Sea, Philippin Sea, and Warm Pool North region. The anomaly pattern was reversed in the Warm Pool East region. However, the anomaly pattern in the Warm Pool region was intermediate of the two patterns. In relation to chlorophyll a, there was a reversed interannual anomaly pattern between Warm Pool North and Warm Pool East, while the anomaly pattern in the Warm Pool region was similar to that of Warm Pool North except for the El Ni? years (1997/1998, 2002/2003, 2006/2007). However, there was no distinct relationship among other seas. Interestingly, in the Warm Pool and Warm Pool East regions, sea surface temperature showed a pronounced inverse pattern with chlorophyll a. This indicates a strong interrelationship among sea surface temperature-MLD-chlorophyll a in the regions. In the Warm Pool and Warm Pool East, zonal distribution of chlorophyll a concentration within the past 10 years has shown a good relationship with sea surface temperature which reflects ENSO variability.

Comparison of Composite Methods of Satellite Chlorophyll-a Concentration Data in the East Sea

Park, Kyung-Ae,Park, Ji-Eun,Lee, Min-Sun,Kang, Chang-Keun The Korean Society of Remote Sensing 2012 大韓遠隔探査學會誌 Vol.28 No.6

To produce a level-3 monthly composite image from daily level-2 Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll-a concentration data set in the East Sea, we applied four average methods such as the simple average method, the geometric mean method, the maximum likelihood average method, and the weighted averaging method. Prior to performing each averaging method, we classified all pixels into normal pixels and abnormal speckles with anomalously high chlorophyll-a concentrations to eliminate speckles from the following procedure for composite methods. As a result, all composite maps did not contain the erratic effect of speckles. The geometric mean method tended to underestimate chlorophyll-a concentration values all the time as compared with other methods. The weighted averaging method was quite similar to the simple average method, however, it had a tendency to be overestimated at high-value range of chlorophyll-a concentration. Maximum likelihood method was almost similar to the simple average method by demonstrating small variance and high correlation (r=0.9962) of the differences between the two. However, it still had the disadvantage that it was very sensitive in the presence of speckles within a bin. The geometric mean was most significantly deviated from the remaining methods regardless of the magnitude of chlorophyll-a concentration values. Its bias error tended to be large when the standard deviation within a bin increased with less uniformity. It was more biased when data uniformity became small. All the methods exhibited large errors as chlorophyll-a concentration values dominantly scatter in terms of time and space. This study emphasizes the importance of the speckle removal process and proper selection of average methods to reduce composite errors for diverse scientific applications of satellite-derived chlorophyll-a concentration data.

베이지안 추정을 이용한 팔당호 유역의 계절별 클로로필a 예측 및 오염특성 연구

김미아 ( Mi Ah Kim ),신유나 ( Yuna Shin ),김경현 ( Kyung Hun Kim ),허태영 ( Tae Young Heo ),유문규 ( Moon Kyu Yoo ),이수웅 ( Su Woong Lee ) 한국물환경학회 2013 한국물환경학회지 Vol.29 No.6

In recent years, eutrophication in the Paldang Lake has become one of the major environmental problems in Korea as it may threaten drinking water safety and human health. Thus it is important to understand the phenomena and predict the time and magnitude of algal blooms for applying adequate algal reduction measures. This study performed seasonal water quality assessment and chlorophyll-a prediction using Bayseian simple/multiple linear regression analysis. Bayseian regression analysis could be a useful tool to overcome limitations of conventional regression analysis. Also it can consider uncertainty inprediction by using posterior distribution. Generally, chlorophyll-a of a P2(Paldang Dam 2) site showed high concentration in spring and it was similar to that of P4(Paldang Dam 4) site. For the development of Bayseian model, we performed seasonal correlation. As a result, chlorophyll-a of a P2 site had a high correlation with P5(Paldang Dam 5) site in spring (r =0.786, p<0.05) and with P4 in winter (r =0.843, p<0.05). Based on the DIC (Deviance Information Criterion) value, critical explanatory variables of the best fitting Bayesian linear regression model were selected as a PO4-P (P2), Chlorophyll-a (P5) in spring, NH3-N (P2), Chlorophyll-a (P4), NH3-N (P4) in summer, DTP (P2), outflow (P2), TP (P3), TP (P4) fall, COD (P2), Chl-a (P4) and COD (P4) in winter. The results of chlorophyll-a prediction showed relatively hagh R2 and low RMSE values in summer and winter.

Studies on Simultaneous Determination of Chlorophyll a and b, Pheophorbide a, and $\beta-Carotene$ in Chlorella and Spirulina Products

이영자,김소희,김진숙,한정아,서해점,임효정,최수영,Lee Young Ja,Kim So Hee,Kim Jin-Sook,Han Jeong A,Seo Hae Jeom,Lim Hyo Jeong,Choi Soo Young The Korean Society of Food Hygiene and Safety 2005 한국식품위생안전성학회지 Vol.20 No.3

역상 컬럼을 이용하여 건강기능식품 중 클로렐라 및 스피루리나제품에 함유되어 있는 엽록소 a, b,페오포르바이드 a 및 $\beta$-카로틴의 HPLC동시분석법을 확립하였으며, 첨가농도 $50\;\mug/ml$에서 엽록소 a, b, 페오포르바이드 a 및 $\beta$-카로틴에 대한 회수율시험결과, 각각 2.8, 6.0, 10.6 및 $10.4\%$의 상대표준편차와 70.3, 71.6, 60.1 및 $90.5\%$의 회수율을 각각 나타냈다. 이때 검출한계는 $0.1\sim1.0\;\mug/ml$, 정량한계는 $0.2\sim2.0\;\mug/ml$이었으며 검량선 상관계수도 0.995 이상의 직선성을 보여주었다. 국내유통 클로렐라 및 스피루리나제품에 대한 엽록소 a, b,페오포르바이드 a및 $\beta$-카로틴의 함유량을 분석한 결과 엽록소 a $121.g\sim543$, 엽록소 b $0.6\sim160.0$, 페오포르바이드 a 및 P-카로틴 $383.6\sim1713.7mg/ml$ 수준으로 나타났다. 엽록소 b의 함유량은 클로렐라제품에서 평균 374.0 mg/100 g 으로 스피루리나제품의 평균 10.5 mg/100 g 보다 30배 이상 함유하고 있는 것으로 확인되었다. 그러나 $\beta$-카로틴의 함유량은 스피루리나제품이 평균 1335.4 mg/100 g 로 클로렐라제품의 평균 495.0 mg/100 g 보다 평균 함유량에서 2.7배 높은 것으로 나타났다. 국내 건강기능식품공전 중 클로렐라 및 스피루리나제품의 엽록소 a b, 및 페오포르바이드 항목의 규격검사를 본 연구의 동시분석법으로 개정함으로써 각 성분 함량의 정량, 분석시간의 단축 및 비용절감 둥 시험방법을 크게 개선할 수 있을 것으로 기대된다. A simple and sensitive analysis method based on reverse phase (RP) HPLC with UV detector was developed for simultaneous determination of chlorophyll a and b, pheophorbide a and $\beta-Carotene$ in Chlorella and Spirulina products. For added concentration $(50\;\mug/ml)$ of chlorophyll a and b, pheophorbide a and $\beta-Carotene$, recoveries of those were 70.3, 71.6, 60.1 and $90.5\%$, respectively, with relative standard deviations of 2.8,6.0, 10.6 and $10.4\%$. Limit of detection and quantification had ranges of $0.1\sim1.0\;\mug/ml$ and $0.2\sim2.0\;\mug/ml$, respectively. Calibration curve was linear with correlation coefficient of 0.995 for chlorophyll a and b, pheophorbide a and $\beta-Carotene$. Results of simultaneous determination in Chlorella and Spirulina products were showed ranges of $121.g\sim543.0\;\mug/ml$ for chlorophyll a,$0.6\sim160.0\;\mug/ml$ for chlorophyll b, $19.2\sim60.3\;\mug/ml$ for pheophorbide a and $383.6\sim1713.7\;\mug/ml$ for $\beta-Carotene$, respectively. Chlorophyll b contents in Chlorella products were detected above 30 times level to those in Spirulina products. $\beta-Carotene$ contents in Spirulina products were detected 2.7 times level to those in Chlorella products.

Comparison of Composite Methods of Satellite Chlorophyll-a Concentration Data in the East Sea

박경애,박지은,이민선,강창근 대한원격탐사학회 2012 大韓遠隔探査學會誌 Vol.28 No.6

To produce a level-3 monthly composite image from daily level-2 Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll-a concentration data set in the East Sea, we applied four average methods such as the simple average method, the geometric mean method, the maximum likelihood average method, and the weighted averaging method. Prior to performing each averaging method, we classified all pixels into normal pixels and abnormal speckles with anomalously high chlorophyll-a concentrations to eliminate speckles from the following procedure for composite methods. As a result, all composite maps did not contain the erratic effect of speckles. The geometric mean method tended to underestimate chlorophyll-a concentration values all the time as compared with other methods. The weighted averaging method was quite similar to the simple average method, however, it had a tendency to be overestimated at high-value range of chlorophyll-a concentration. Maximum likelihood method was almost similar to the simple average method by demonstrating small variance and high correlation (r=0.9962) of the differences between the two. However, it still had the disadvantage that it was very sensitive in the presence of speckles within a bin. The geometric mean was most significantly deviated from the remaining methods regardless of the magnitude of chlorophyll-a concentration values. Its bias error tended to be large when the standard deviation within a bin increased with less uniformity. It was more biased when data uniformity became small. All the methods exhibited large errors as chlorophyll-a concentration values dominantly scatter in terms of time and space. This study emphasizes the importance of the speckle removal process and proper selection of average methods to reduce composite errors for diverse scientific applications of satellite-derived chlorophyll-a concentration data.

Remote Sensing을 이용한 통계학적 호소수질 모형에 관한 연구

김혜영 ( Kim Hea-young ),정태섭 ( Jeong Tae-seop ),김경수 ( Kim Kyung-su ) 한국환경기술학회 2001 한국환경기술학회지 Vol.2 No.1

원격탐사기법을 이용한 수질관리 방안을 모색하기 위해 측정된 자료와 위성데이터로부터 작성된 디지털 영상을 이용하여 호수의 부영양화와 가장 직접적인 관계가 있는 1) Chlorophyll-a에 영향을 미치는 수질인자를 통계분석을 통해 선정하고, 2) 위성데이터와 수질 실측지간의 상관관계를 통해 적용가능한 모형식을 유추하여 최종적으로 3) 유도된 회귀모델을 위성영상에 적용시켜 실측되지 않은 지역을 포함한 호수 전역의 농도분포도를 작성하여 원격탐사기법을 이용한 수질평가 가능성을 판단한다. 연구의 대상 지역은 대청호를 선정하였고, 분석에 이용된 수질자료는 1992년부터 1996년까지 5년간 대청호 5개 지역에서 측정된 pH, 수온, COD, BOD, TN, TP, Chlorophyll-a, SS 등 8가지 항목, 기상인자는 강수량, 일사량 등 2가지 항목이었다. 위성영상자료는 일본 RESTEC(Remote Sensing Technology Center)에서 제공한 Lansat TM자료를 이용하였다. 그 결과 1차 회귀 모형식과 2차 회귀모형식을 1995년 4월 1일, 6월 20일, 10월 10일자 위성영상에 적용시켜 Chlorophyll-a의 농도분포도는 1차 다중회귀 모형식 적용시 Chlorophyll-a의 농도의 높고 낮음에 관계없이 1:1선을 따라 고른 분포를 보였으며 2개 지점을 제외한 나머지 13개 지점의 예측치는 편차범위±1.5내에 있었다. 2차 회귀 모형식 적용시의 15개 지점의 예측값 모두 ±1.0 편차범위 내에 속해 1차 다중 회귀모델의 결과보다 훨씬 향상된 결과를 보여 수질관리 방안의 한 방법으로의 가능성을 나타냈다. This study is a trial for the effective water quality management of wide water systems like oceans and lakes. This introduced the remote sensing that acquired the information utilizing reflection character. The remote sensing model and statistic analysis of the accumulated water data were developed. The developed model analyzed precise degree. The results of this study are as follows; 1. The concentration of 8 water quality data ; pH, temperature, COD, BOD, T-N, T-P, SS and chlorophyll-a were investigated to detect variations. Statistic analysis shows that this variation follows one year cycle peaking at 6 months then declining to the original level. 2. The meteorological data : rainfall and solar radiation quantity were investigated. 3. A correlation between the reflective degree of the TM band and chlorophyll-a was found. The first and second order multi-regression model was used. 4. The concentration range of chlorophyll-a was reported by the first and second order multi-regression models which was applied by satellite image on June 20th 1995. In consequence,the latter`s application showed a high declination range ±1.5 and ±1.0 of measure value and estimate value between the first and second order multi―regression models.