• Title/Summary/Keyword: 2-Methylisoborneol

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A Study on the Removal of Taste and Odor Compounds by Activated Carbon Adsorption (활성탄(活性炭) 흡착(吸着)에 의한 취기유발물질(臭氣誘發物質) 제거(除去)에 관(關)한 연구(硏究) -GEOSMIN, 2-MIB를 중심으로-)

  • Kim, Han Seung;Kwon, Bong Kee;Park, Chung Hyun
    • Journal of Korean Society of Water and Wastewater
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    • v.8 no.2
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    • pp.12-24
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    • 1994
  • The occurrence of objectionable tastes and odors in drinking water is a common and widespread problem. The most troublesome odors are usually those described as muddy or earthy-musty. Two organic compounds which have been implicated as the cause of earthy-musty odor problems in water are geosmin and 2-Methylisoborneol. These earthy-musty organics have been shown to be metabolites of actinomycetes and blue green algae. The purpose of this paper is to describe adsorbability in removing these two oder causing compounds(geosmin and 2-MIB) upon various conditions like pH variation, adding humic acid and different activated carbon. The conclusion of this study are as followings. In batch test, carbon dosage is 10mg/100ml for geosmin and 15mg/100ml for 2-MIB. Both were in equilibrium state after 60 hours. In model simulation, F-P model described experiment data and modelling data appropriately in geosmin but F-S model not. In case of 2-MIB, models didn't describe relation between experiment and modelling data well. Two causative agents of earthy-musty odor compounds, geosmin and 2-MIB, are strongly adsorbed by activated carbon either coconut or brown. There appears to be no effect of pH (3,7,9) on adsorption of these two organics. Activated carbon proved to be more effective for removing geosmin than for removing 2-MIB. When activated carbon is. used in removing these two organics, the removal of these appeared to be adversely affected by back ground organic compounds, such as humic substances, due to competitive adsorption.

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Technical and Strategic Approach for the Control of Cyanobacterial Bloom in Fresh Waters (담수수계에서 남조류 증식억제의 기술적, 전략적 접근)

  • Lee, Chang Soo;Ahn, Chi-Yong;La, Hyun-Joon;Lee, Sanghyup;Oh, Hee-Mock
    • Korean Journal of Environmental Biology
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    • v.31 no.4
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    • pp.233-242
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    • 2013
  • Cyanobacteria (blue-green algae) are not only the first oxygenic organisms on earth but also the foremost primary producers in aquatic environment. Massive growth of cyanobacteria, in eutrophic waters, usually changes the water colour to green and is called as algal (cyanobacterial) bloom or green tide. Cyanobacterial blooms are a result of high levels of primary production by certain species such as Microcystis sp., Anabaena sp., Oscillatoria sp., Aphanizomenon sp. and Phormidium sp. These cyanobacterial species can produce hepatotoxins or neurotoxins as well as malodorous compounds like geosmin and 2-methylisoborneol (MIB). In order to solve the nationwide problem of hazardous cyanobacterial blooms in Korea, the following technically and strategically sound approaches need to be developed. 1) As a long-term strategy, reduction of the nutrients such as phosphorus and nitrogen in our water bodies to below permitted levels. 2) As a short term strategy, field application of combination of already established bloom remediation techniques. 3) Development of emerging convergence technologies based on information and communication technology (ICT), environmental technology (ET) and biotechnology (BT). 4) Finally, strengthening education and creating awareness among students, public and industry for effective reduction of pollution discharge. Considering their ecological roles, a complete elimination of cyanobacteria is not desirable. Hence a holistic approach mentioned above in combination to addressing the issue from a social perspective with cooperation from public, government, industry, academic and research institutions is more pragmatic and desirable management strategy.

Adsorptive Removal of 2-Methylisoborneol and Geosmin in Raw Water Using Activated Carbon and Zeolite (활성탄과 제올라이트를 이용한 상수원수 중 이취미물질(2-MIB, Geosmin)의 흡착제거)

  • Choi, Jeong-Hwan;Lee, Hong-Jae;Kim, Won-Ju;Park, Hyun-Geoun;Cho, Ju-Sik;Heo, Jong-Soo
    • Korean Journal of Environmental Agriculture
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    • v.20 no.4
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    • pp.244-251
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    • 2001
  • This study was performed to investigate the recovery efficacy of 2-methylisobomeol (2-MIB) and Geosmin, odor contaminants produced by algae, by pretreatment techniques, and also to investigate both adsorption characteristics and removal efficiency to get some information for the effective removal of 2-MIB and Geosmin by batch experiments. In pretreatment experiments, the best recovery efficiency of both odorants at 0.2 and $2\;{\mu}g/L$ in raw water was 30 mL of sampling size, 9 g NaCl for salting out headspace of sampling phase and 40 minutes of adsorption. At the best condition, the recovery efficiency of 2-MIB was 85% at $0.2\;{\mu}g/L$ and 95% at $2\;{\mu}g/L$, whereas the efficiency of Geosmin was lower than that of 2-MIB : 61% at $0.2\;{\mu}g/L$ and 81% at $2\;{\mu}g/L$. In batch experiments, the removal efficiency of the Geosmin and 2-MIB by adsorbents using distilled water were increased in comparison with raw water, the efficiency in raw water was little different by their concentrations. When these results were applied to the Freundrich adsorption isotherm, the K value of 2-MIB for zeolite, coal activated carbon, and coconut activated carbon was 0.671, 1.811, and 1.340, respectively, and the value of Geosmin was 0.6125, 1.771, and 1.5191, respectively. Thus the adsorption efficiency of 2-MIB and Geosmin was in the order of zeolite, coconut activated carbon, coal activated carbon.

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Determination of geosmin and 2-MIB in Nakdong River using headspace solid phase microextraction and GC-MS (HS-SPME-GC/MS를 이용한 낙동강 수계 하천수 중 조류기원성 냄새물질 분석)

  • Lee, Injung;Lee, Kyoung-Lak;Lim, Tae-Hyo;Park, Jeong-Ja;Cheon, Seuk
    • Analytical Science and Technology
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    • v.26 no.5
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    • pp.326-332
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    • 2013
  • Geosmin and 2-methylisoborneol (2-MIB) are volatile organic compounds responsible for the majority of unpleasant taste and odor events in drinking water. Geosmin and 2-MIB are byproducts of blue-green algae (cyanobacteria) with musty and earthy odors. These compounds have odor threshold concentration at ng/L levels. It is needed to develop a sensitive method for determination of geosmin and 2-MIB to control the quality of drinking water. In this study, geosmin and 2-MIB in water samples were determined by gas chromatography-mass spectrometry (GC-MS) with headspace-solid phase microextraction (HS-SMPE). The detection limits of this method were 1.072 ng/L and 1.021 ng/L for geosmin and 2-MIB, respectively. Good accuracy and precision was also obtained by this method. Concentrations of the two compounds were measured in raw waters from Nakdong River in the cyanobacterial blooming season. Water bloom formed by cyanobacteria has been occurred currently in Nakdong River. It is needed to investigate the concentrations of geosmin and 2-MIB to control the quality of drinking water from Nakdong River. Both geosmin and 2-MIB were detected in raw waters from Nakdong River at concentrations ranging from 4 to 24 ng/L and 6 to 16 ng/L, respectively.

Pseudanabaena Species Diversity and Off-flavor Material (2-MIB) Production by Cyanobacteria in Korea (우리나라 Pseudanabaena 속 남조류 종다양성 및 남조류 기원 이취미 물질(2-MIB)의 발생)

  • Kim, Keonhee;Park, Chaehongk;Shim, Yeonbo;Kim, Nan-young;Lee, Soogone;Jang, Jaeyoung;Lee, Karam;Hwang, Soon-Jin
    • Journal of Korean Society on Water Environment
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    • v.37 no.5
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    • pp.381-397
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    • 2021
  • Off-flavor materials (geosmin and 2-methylisoborneol (2-MIB)) produced by microorganisms, such as, cyanobacteria and actinomycetes, cause freshwater use problems worldwide. Due to unpleasant taste and odor, these microorganisms have raised issues especially in drinking water resources. Recently, there has been increasing concern about 2-MIB and causal cyanobacteria, namely, Pseudanabaena, in Korea. However, material production and ecological dynamics remain largely unexplored. This study reviewed the distribution of Pseudanabaena, its species diversity, and the research trend of molecular ecology related to 2-MIB production in Korea. Based on published literature, we found that seven species of Pseudanabaena which include P. mucicola, P. limnetica, P. redekei, P. catenata, P. galeata, P. yagii, and P. cinerea appeared to occur in a variety of Korean water systems. All of these Pseudanabaena species were found in the North-Han River system (Lakes Soyang, Chuncheon, Uiam, and Paldang). Some of these species were also detected in other watersheds, but the precise species diversity was not identified. Species belonging to the Pseudanabaena genus are hard to classify through general microscopic alpha taxonomy, due to their very small cell size and similar morphological characters. Moreover, the potential of 2-MIB production cannot be detected by microscopic observation. Combining molecular ecological techniques, such as, environmental genomic materials (eDNA, eRNA) analyses to conventional methods could be useful to better understand the off-flavor material production and dynamics, thereby providing more efficient management strategies of freshwater systems.

Machine- and Deep Learning Modelling Trends for Predicting Harmful Cyanobacterial Cells and Associated Metabolites Concentration in Inland Freshwaters: Comparison of Algorithms, Input Variables, and Learning Data Number (담수 유해남조 세포수·대사물질 농도 예측을 위한 머신러닝과 딥러닝 모델링 연구동향: 알고리즘, 입력변수 및 학습 데이터 수 비교)

  • Yongeun Park;Jin Hwi Kim;Hankyu Lee;Seohyun Byeon;Soon-Jin Hwang;Jae-Ki Shin
    • Korean Journal of Ecology and Environment
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    • v.56 no.3
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    • pp.268-279
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    • 2023
  • Nowadays, artificial intelligence model approaches such as machine and deep learning have been widely used to predict variations of water quality in various freshwater bodies. In particular, many researchers have tried to predict the occurrence of cyanobacterial blooms in inland water, which pose a threat to human health and aquatic ecosystems. Therefore, the objective of this study were to: 1) review studies on the application of machine learning models for predicting the occurrence of cyanobacterial blooms and its metabolites and 2) prospect for future study on the prediction of cyanobacteria by machine learning models including deep learning. In this study, a systematic literature search and review were conducted using SCOPUS, which is Elsevier's abstract and citation database. The key results showed that deep learning models were usually used to predict cyanobacterial cells, while machine learning models focused on predicting cyanobacterial metabolites such as concentrations of microcystin, geosmin, and 2-methylisoborneol (2-MIB) in reservoirs. There was a distinct difference in the use of input variables to predict cyanobacterial cells and metabolites. The application of deep learning models through the construction of big data may be encouraged to build accurate models to predict cyanobacterial metabolites.

Development of Optimum PAC Dose Prediction Program using $^{14}C$-radiolabled MIB and HSDM ($^{14}C$-radiolabeled MIB와 HSDM을 이용한 최적 PAC 투입량 예측프로그램의 개발)

  • Kim, Young-Il;Bae, Byung-Uk;Kim, Kyu-Hyoung;Hong, Hyun-Su;Westerhoff, Paul
    • Journal of Korean Society of Environmental Engineers
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    • v.27 no.10
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    • pp.1123-1128
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    • 2005
  • NIB(methylisoborneol) is an earthy/musty odor compound produced as a second metabolite by cyanobacteria and actinomycetes. MIB is not removed by conventional water treatment(coagulation, sedimentation, filtration) and its presence in tap water, even at low ng/L levels, can result in consumer complaints. PAC(powdered activated carbon) can effectively remove MIB when the correct dose is applied. But, since most operators in water treatment plants apply a PAC dose and then adjust that dose depending on direct observation (odor detection) after treatment, the result is often under-dose or eve,-dose. In this study, kinetic and isotherm tests using $^{14}C$-radiolabeled MIB were performed to determine coefficients for the HSDM(homogeneous surface diffusion model), including liquid film mass transfer coefficient($K_f$) and surface diffusion coefficient ($D_s$). The HSDM gave a reasonable fit and allowed prediction with the experimental data. Base on the HSDM, the authors developed an optimum PAC dose prediction program using the Excel spreadsheet. When the developed program was applied at two water treatment plants, the PAC dose based on the experience of operators in the water treatment plant was significantly different from that recommended by the newly developed program. If operators are willing to use the optimum PAC dose prediction program, it should solve dosing problems.