• Title/Summary/Keyword: Real time observation

Search Result 471, Processing Time 0.028 seconds

Performance Evaluation of Monitoring System for Sargassum horneri Using GOCI-II: Focusing on the Results of Removing False Detection in the Yellow Sea and East China Sea (GOCI-II 기반 괭생이모자반 모니터링 시스템 성능 평가: 황해 및 동중국해 해역 오탐지 제거 결과를 중심으로)

  • Han-bit Lee;Ju-Eun Kim;Moon-Seon Kim;Dong-Su Kim;Seung-Hwan Min;Tae-Ho Kim
    • Korean Journal of Remote Sensing
    • /
    • v.39 no.6_2
    • /
    • pp.1615-1633
    • /
    • 2023
  • Sargassum horneri is one of the floating algae in the sea, which breeds in large quantities in the Yellow Sea and East China Sea and then flows into the coast of Republic of Korea, causing various problems such as destroying the environment and damaging fish farms. In order to effectively prevent damage and preserve the coastal environment, the development of Sargassum horneri detection algorithms using satellite-based remote sensing technology has been actively developed. However, incorrect detection information causes an increase in the moving distance of ships collecting Sargassum horneri and confusion in the response of related local governments or institutions,so it is very important to minimize false detections when producing Sargassum horneri spatial information. This study applied technology to automatically remove false detection results using the GOCI-II-based Sargassum horneri detection algorithm of the National Ocean Satellite Center (NOSC) of the Korea Hydrographic and Oceanography Agency (KHOA). Based on the results of analyzing the causes of major false detection results, it includes a process of removing linear and sporadic false detections and green algae that occurs in large quantities along the coast of China in spring and summer by considering them as false detections. The technology to automatically remove false detection was applied to the dates when Sargassum horneri occurred from February 24 to June 25, 2022. Visual assessment results were generated using mid-resolution satellite images, qualitative and quantitative evaluations were performed. Linear false detection results were completely removed, and most of the sporadic and green algae false detection results that affected the distribution were removed. Even after the automatic false detection removal process, it was possible to confirm the distribution area of Sargassum horneri compared to the visual assessment results, and the accuracy and precision calculated using the binary classification model averaged 97.73% and 95.4%, respectively. Recall value was very low at 29.03%, which is presumed to be due to the effect of Sargassum horneri movement due to the observation time discrepancy between GOCI-II and mid-resolution satellite images, differences in spatial resolution, location deviation by orthocorrection, and cloud masking. The results of this study's removal of false detections of Sargassum horneri can determine the spatial distribution status in near real-time, but there are limitations in accurately estimating biomass. Therefore, continuous research on upgrading the Sargassum horneri monitoring system must be conducted to use it as data for establishing future Sargassum horneri response plans.

Fluorine Plasma Corrosion Resistance of Anodic Oxide Film Depending on Electrolyte Temperature

  • Shin, Jae-Soo;Kim, Minjoong;Song, Je-beom;Jeong, Nak-gwan;Kim, Jin-tae;Yun, Ju-Young
    • Applied Science and Convergence Technology
    • /
    • v.27 no.1
    • /
    • pp.9-13
    • /
    • 2018
  • Samples of anodic oxide film used in semiconductor and display manufacturing processes were prepared at different electrolyte temperatures to investigate the corrosion resistance. The anodic oxide film was grown on aluminum alloy 6061 by using a sulfuric acid ($H_2SO_4$) electrolyte of 1.5 M at $0^{\circ}C$, $5^{\circ}C$, $10^{\circ}C$, $15^{\circ}C$, and $20^{\circ}C$. The insulating properties of the samples were evaluated by measuring the breakdown voltage, which gradually increased from 0.43 kV ($0^{\circ}C$) to 0.52 kV ($5^{\circ}C$), 1.02 kV ($10^{\circ}C$), and 1.46 kV ($15^{\circ}C$) as the electrolyte temperature was increased from $0^{\circ}C$ to $15^{\circ}C$, but then decreased to 1.24 kV ($20^{\circ}C$). To evaluate the erosion of the film by fluorine plasma, the plasma erosion and the contamination particles were measured. The plasma erosion was evaluated by measuring the breakdown voltage after exposing the film to $CF_4/O_2/Ar$ and $NF_3/O_2/Ar$ plasmas. With exposure to $CF_4/O_2/Ar$ plasma, the breakdown voltage of the film slightly decreased at $0^{\circ}C$, by 0.41 kV; however, the breakdown voltage significantly decreased at $20^{\circ}C$, by 0.83 kV. With exposure to $NF_3/O_2/Ar$ plasma, the breakdown voltage of the film slightly decreased at $0^{\circ}C$, by 0.38 kV; however, the breakdown voltage significantly decreased at $20^{\circ}C$, by 0. 77 kV. In addition, for the entire temperature range, the breakdown voltage decreased more when sample was exposed to $NF_3/O_2/Ar$ plasma than to $CF_4/O_2/Ar$ plasma. The decrease of the breakdown voltage was lower in the anodic oxide film samples that were grown slowly at lower temperatures. The rate of breakdown voltage decrease after exposure to fluorine plasma was highest at $20^{\circ}C$, indicating that the anodic oxide film was most vulnerable to erosion by fluorine plasma at that temperature. Contamination particles generated by exposure to the $CF_4/O_2/Ar$ and $NF_3/O_2/Ar$ plasmas were measured on a real-time basis. The number of contamination particles generated after the exposure to the respective plasmas was lower at $5^{\circ}C$ and higher at $0^{\circ}C$. In particular, for the entire temperature range, about five times more contamination particles were generated with exposure to $NF_3/O_2/Ar$ plasma than for exposure to $CF_4/O_2/Ar$ plasma. Observation of the surface of the anodic oxide film showed that the pore size and density of the non-treated film sample increased with the increase of the temperature. The change of the surface after exposure to fluorine plasma was greatest at $0^{\circ}C$. The generation of contamination particles by fluorine plasma exposure for the anodic oxide film prepared in the present study was different from that of previous aluminum anodic oxide films.

Validation of Extreme Rainfall Estimation in an Urban Area derived from Satellite Data : A Case Study on the Heavy Rainfall Event in July, 2011 (위성 자료를 이용한 도시지역 극치강우 모니터링: 2011년 7월 집중호우를 중심으로)

  • Yoon, Sun-Kwon;Park, Kyung-Won;Kim, Jong Pil;Jung, Il-Won
    • Journal of Korea Water Resources Association
    • /
    • v.47 no.4
    • /
    • pp.371-384
    • /
    • 2014
  • This study developed a new algorithm of extreme rainfall extraction based on the Communication, Ocean and Meteorological Satellite (COMS) and the Tropical Rainfall Measurement Mission (TRMM) Satellite image data and evaluated its applicability for the heavy rainfall event in July-2011 in Seoul, South Korea. The power-series-regression-based Z-R relationship was employed for taking into account for empirical relationships between TRMM/PR, TRMM/VIRS, COMS, and Automatic Weather System(AWS) at each elevation. The estimated Z-R relationship ($Z=303R^{0.72}$) agreed well with observation from AWS (correlation coefficient=0.57). The estimated 10-minute rainfall intensities from the COMS satellite using the Z-R relationship generated underestimated rainfall intensities. For a small rainfall event the Z-R relationship tended to overestimated rainfall intensities. However, the overall patterns of estimated rainfall were very comparable with the observed data. The correlation coefficients and the Root Mean Square Error (RMSE) of 10-minute rainfall series from COMS and AWS gave 0.517, and 3.146, respectively. In addition, the averaged error value of the spatial correlation matrix ranged from -0.530 to -0.228, indicating negative correlation. To reduce the error by extreme rainfall estimation using satellite datasets it is required to take into more extreme factors and improve the algorithm through further study. This study showed the potential utility of multi-geostationary satellite data for building up sub-daily rainfall and establishing the real-time flood alert system in ungauged watersheds.

MicroRNA Expression Profiling in Cell and Mouse Models of Fabry Disease to Identify Biomarkers for Fabry Disease Nephropathy (파브리병의 바이오마커 발굴을 위한 파브리 마우스와 세포모델에서의 microRNA 발현 분석)

  • Jung, Namhee;Park, Saeyoung;Jeon, Yeo Jin;Choi, Yoonyoung;Jung, Sung-Chul
    • Journal of The Korean Society of Inherited Metabolic disease
    • /
    • v.15 no.3
    • /
    • pp.127-137
    • /
    • 2015
  • Purpose: The main aim of this study was to compare and analyze expression profiles of microRNAs (miRNAs) to establish miRNA signature of Fabry nephropathy related epithelial mesenchymal transition (EMT). Methods: Expression profiles of miRNAs in kidney tissue samples and cell lines from normal and Fabry disease mouse model were examined by miRNA expression microarray analysis followed by quantitative real-time polymerase chain reaction analysis (qRT-PCR). Results: In the miRNA expression microarray analysis of Fabry mouse kidney tissues compared to wild type mouse, 5 and 3 miRNAs among 1,247 miRNAs examined were up- and down-regulated, respectively. Among them, miR-149-5p was down-regulated about 2-fold in Fabry kidney samples. The down-regulations of miR-149-5p were observed in kidney tissues of under 35 week-old-Fabry mice. However, this down-regulation was not observed in kidney tissues of 42 week-old Fabry mice. In SV40 MES 13 cells, mouse mesangial cells, treated with globotriaosylsphingosine (lyso-Gb3), miR-149-5p was also downregulated. The down-regulation of miR-149-5p induced up-regulation of its target genes related to EMT. Conclusion: The miRNA expression array and qRT-PCR results show that miR-149-5p expression was decreased in kidney tissues of Fabry mice compared to wild type mice under 35 weeks of age. Along with the observation of miR-149-5p expression in Fabry disease cell models, these results indicate that the down-regulated miR-149-5p were related to the biological response of mesangial cells to lyso-Gb3 and also have influence to the transcriptional up-regulation of its target genes. These results suggest miR-149-5p might play important roles in the Fabry nephropathy.

Quality Control of Agro-meteorological Data Measured at Suwon Weather Station of Korea Meteorological Administration (기상청 수원기상대 농업기상 관측요소의 품질관리)

  • Oh, Gyu-Lim;Lee, Seung-Jae;Choi, Byoung-Choel;Kim, Joon;Kim, Kyu-Rang;Choi, Sung-Won;Lee, Byong-Lyol
    • Korean Journal of Agricultural and Forest Meteorology
    • /
    • v.17 no.1
    • /
    • pp.25-34
    • /
    • 2015
  • In this research, we applied a procedure of quality control (QC) to the agro-meteorological data measured at the Suwon weather station of Korea Meteorological Administration (KMA). The QC was conducted through six steps based on the KMA Real-time Quality control system for Meteorological Observation Data (RQMOD) and four steps based on the International Soil Moisture Network (ISMN) QC modules. In addition, we set up our own empirical method to remove erroneous data which could not be filtered by the RQMOD and ISMN methods. After all these QC procedures, a well-refined agro-meteorological dataset was complied at both air and soil temperatures. Our research suggests that soil moisture requires more detailed and reliable grounds to remove doubtful data, especially in winter with its abnormal variations. The raw data and the data after QC are now available at the NCAM website (http://ncam.kr/page/req/agri_weather.php).

Object Tracking Based on Exactly Reweighted Online Total-Error-Rate Minimization (정확히 재가중되는 온라인 전체 에러율 최소화 기반의 객체 추적)

  • JANG, Se-In;PARK, Choong-Shik
    • Journal of Intelligence and Information Systems
    • /
    • v.25 no.4
    • /
    • pp.53-65
    • /
    • 2019
  • Object tracking is one of important steps to achieve video-based surveillance systems. Object tracking is considered as an essential task similar to object detection and recognition. In order to perform object tracking, various machine learning methods (e.g., least-squares, perceptron and support vector machine) can be applied for different designs of tracking systems. In general, generative methods (e.g., principal component analysis) were utilized due to its simplicity and effectiveness. However, the generative methods were only focused on modeling the target object. Due to this limitation, discriminative methods (e.g., binary classification) were adopted to distinguish the target object and the background. Among the machine learning methods for binary classification, total error rate minimization can be used as one of successful machine learning methods for binary classification. The total error rate minimization can achieve a global minimum due to a quadratic approximation to a step function while other methods (e.g., support vector machine) seek local minima using nonlinear functions (e.g., hinge loss function). Due to this quadratic approximation, the total error rate minimization could obtain appropriate properties in solving optimization problems for binary classification. However, this total error rate minimization was based on a batch mode setting. The batch mode setting can be limited to several applications under offline learning. Due to limited computing resources, offline learning could not handle large scale data sets. Compared to offline learning, online learning can update its solution without storing all training samples in learning process. Due to increment of large scale data sets, online learning becomes one of essential properties for various applications. Since object tracking needs to handle data samples in real time, online learning based total error rate minimization methods are necessary to efficiently address object tracking problems. Due to the need of the online learning, an online learning based total error rate minimization method was developed. However, an approximately reweighted technique was developed. Although the approximation technique is utilized, this online version of the total error rate minimization could achieve good performances in biometric applications. However, this method is assumed that the total error rate minimization can be asymptotically achieved when only the number of training samples is infinite. Although there is the assumption to achieve the total error rate minimization, the approximation issue can continuously accumulate learning errors according to increment of training samples. Due to this reason, the approximated online learning solution can then lead a wrong solution. The wrong solution can make significant errors when it is applied to surveillance systems. In this paper, we propose an exactly reweighted technique to recursively update the solution of the total error rate minimization in online learning manner. Compared to the approximately reweighted online total error rate minimization, an exactly reweighted online total error rate minimization is achieved. The proposed exact online learning method based on the total error rate minimization is then applied to object tracking problems. In our object tracking system, particle filtering is adopted. In particle filtering, our observation model is consisted of both generative and discriminative methods to leverage the advantages between generative and discriminative properties. In our experiments, our proposed object tracking system achieves promising performances on 8 public video sequences over competing object tracking systems. The paired t-test is also reported to evaluate its quality of the results. Our proposed online learning method can be extended under the deep learning architecture which can cover the shallow and deep networks. Moreover, online learning methods, that need the exact reweighting process, can use our proposed reweighting technique. In addition to object tracking, the proposed online learning method can be easily applied to object detection and recognition. Therefore, our proposed methods can contribute to online learning community and object tracking, detection and recognition communities.

Introduction on the Products and the Quality Management Plans for GOCI-II (천리안 해양위성 2호 산출물 및 품질관리 계획)

  • Lee, Sun-Ju;Lee, Kyeong-Sang;Han, Tae Hyun;Moon, Jeong-Eon;Bae, Sujung;Choi, Jong-kuk
    • Korean Journal of Remote Sensing
    • /
    • v.37 no.5_2
    • /
    • pp.1245-1257
    • /
    • 2021
  • GOCI-II, succeeding the mission of GOCI, was launched in February 2020 and has been in regular operation since October 2020. Korea Institute of Ocean Science and Technology (KIOST) processes and produces in real time Level-1B and 26 Level-2 outputs, which then are provided by Korea Hydrographic and Oceanographic Agency (KHOA). We introduced current status of regular GOCI-II operation and showed future improvement. Basic GOCI-II products including chlorophyll-a, total suspended materials, and colored dissolved organic matter concentration, are induced by OC4 and YOC algorithms, which were described in detail. For the full disk (FD), imaging schedule was established considering solar zenith angle and sun glint during the in-orbital test, but improved by further considering satellite zenith angle. The number of slots satisfying the condition 'Best Ocean' significantly increased from 15 to 78. GOCI-II calibration requirements were presented based on that by European Space Agency (ESA) and candidate fixed locations for calibrating local observation area were. The quality management of FD uses research ships and overseas bases of KIOST, but it is necessary to establish an international calibration/validation network. These results are expected to enhance the understanding of users for output processing and help establish detailed plans for future quality management tasks.

Establishment of Geospatial Schemes Based on Topo-Climatology for Farm-Specific Agrometeorological Information (농장맞춤형 농업기상정보 생산을 위한 소기후 모형 구축)

  • Kim, Dae-Jun;Kim, Soo-Ock;Kim, Jin-Hee;Yun, Eun-Jeong
    • Korean Journal of Agricultural and Forest Meteorology
    • /
    • v.21 no.3
    • /
    • pp.146-157
    • /
    • 2019
  • One of the most distinctive features of the South Korean rural environment is that the variation of weather or climate is large even within a small area due to complex terrains. The Geospatial Schemes based on Topo-Climatology (GSTP) was developed to simulate such variations effectively. In the present study, we reviewed the progress of the geospatial schemes for production of farm-scale agricultural weather data. Efforts have been made to improve the GSTP since 2000s. The schemes were used to provide climate information based on the current normal year and future climate scenarios at a landscape scale. The digital climate maps for the normal year include the maps of the monthly minimum temperature, maximum temperature, precipitation, and solar radiation in the past 30 years at 30 m or 270 m spatial resolution. Based on these digital climate maps, future climate change scenario maps were also produced at the high spatial resolution. These maps have been used for climate change impact assessment at the field scale by reprocessing them and transforming them into various forms. In the 2010s, the GSTP model was used to produce information for farm-specific weather conditions and weather forecast data on a landscape scale. The microclimate models of which the GSTP model consists have been improved to provide detailed weather condition data based on daily weather observation data in recent development. Using such daily data, the Early warning service for agrometeorological hazard has been developed to provide weather forecasts in real-time by processing a digital forecast and mid-term weather forecast data (KMA) at 30 m spatial resolution. Currently, daily minimum temperature, maximum temperature, precipitation, solar radiation quantity, and the duration of sunshine are forecasted as detailed weather conditions and forecast information. Moreover, based on farm-specific past-current-future weather information, growth information for various crops and agrometeorological disaster forecasts have been produced.

Study on water quality prediction in water treatment plants using AI techniques (AI 기법을 활용한 정수장 수질예측에 관한 연구)

  • Lee, Seungmin;Kang, Yujin;Song, Jinwoo;Kim, Juhwan;Kim, Hung Soo;Kim, Soojun
    • Journal of Korea Water Resources Association
    • /
    • v.57 no.3
    • /
    • pp.151-164
    • /
    • 2024
  • In water treatment plants supplying potable water, the management of chlorine concentration in water treatment processes involving pre-chlorination or intermediate chlorination requires process control. To address this, research has been conducted on water quality prediction techniques utilizing AI technology. This study developed an AI-based predictive model for automating the process control of chlorine disinfection, targeting the prediction of residual chlorine concentration downstream of sedimentation basins in water treatment processes. The AI-based model, which learns from past water quality observation data to predict future water quality, offers a simpler and more efficient approach compared to complex physicochemical and biological water quality models. The model was tested by predicting the residual chlorine concentration downstream of the sedimentation basins at Plant, using multiple regression models and AI-based models like Random Forest and LSTM, and the results were compared. For optimal prediction of residual chlorine concentration, the input-output structure of the AI model included the residual chlorine concentration upstream of the sedimentation basin, turbidity, pH, water temperature, electrical conductivity, inflow of raw water, alkalinity, NH3, etc. as independent variables, and the desired residual chlorine concentration of the effluent from the sedimentation basin as the dependent variable. The independent variables were selected from observable data at the water treatment plant, which are influential on the residual chlorine concentration downstream of the sedimentation basin. The analysis showed that, for Plant, the model based on Random Forest had the lowest error compared to multiple regression models, neural network models, model trees, and other Random Forest models. The optimal predicted residual chlorine concentration downstream of the sedimentation basin presented in this study is expected to enable real-time control of chlorine dosing in previous treatment stages, thereby enhancing water treatment efficiency and reducing chemical costs.

Field Studios of In-situ Aerobic Cometabolism of Chlorinated Aliphatic Hydrocarbons

  • Semprini, Lewts
    • Proceedings of the Korean Society of Soil and Groundwater Environment Conference
    • /
    • 2004.04a
    • /
    • pp.3-4
    • /
    • 2004
  • Results will be presented from two field studies that evaluated the in-situ treatment of chlorinated aliphatic hydrocarbons (CAHs) using aerobic cometabolism. In the first study, a cometabolic air sparging (CAS) demonstration was conducted at McClellan Air Force Base (AFB), California, to treat chlorinated aliphatic hydrocarbons (CAHs) in groundwater using propane as the cometabolic substrate. A propane-biostimulated zone was sparged with a propane/air mixture and a control zone was sparged with air alone. Propane-utilizers were effectively stimulated in the saturated zone with repeated intermediate sparging of propane and air. Propane delivery, however, was not uniform, with propane mainly observed in down-gradient observation wells. Trichloroethene (TCE), cis-1, 2-dichloroethene (c-DCE), and dissolved oxygen (DO) concentration levels decreased in proportion with propane usage, with c-DCE decreasing more rapidly than TCE. The more rapid removal of c-DCE indicated biotransformation and not just physical removal by stripping. Propane utilization rates and rates of CAH removal slowed after three to four months of repeated propane additions, which coincided with tile depletion of nitrogen (as nitrate). Ammonia was then added to the propane/air mixture as a nitrogen source. After a six-month period between propane additions, rapid propane-utilization was observed. Nitrate was present due to groundwater flow into the treatment zone and/or by the oxidation of tile previously injected ammonia. In the propane-stimulated zone, c-DCE concentrations decreased below tile detection limit (1 $\mu$g/L), and TCE concentrations ranged from less than 5 $\mu$g/L to 30 $\mu$g/L, representing removals of 90 to 97%. In the air sparged control zone, TCE was removed at only two monitoring locations nearest the sparge-well, to concentrations of 15 $\mu$g/L and 60 $\mu$g/L. The responses indicate that stripping as well as biological treatment were responsible for the removal of contaminants in the biostimulated zone, with biostimulation enhancing removals to lower contaminant levels. As part of that study bacterial population shifts that occurred in the groundwater during CAS and air sparging control were evaluated by length heterogeneity polymerase chain reaction (LH-PCR) fragment analysis. The results showed that an organism(5) that had a fragment size of 385 base pairs (385 bp) was positively correlated with propane removal rates. The 385 bp fragment consisted of up to 83% of the total fragments in the analysis when propane removal rates peaked. A 16S rRNA clone library made from the bacteria sampled in propane sparged groundwater included clones of a TM7 division bacterium that had a 385bp LH-PCR fragment; no other bacterial species with this fragment size were detected. Both propane removal rates and the 385bp LH-PCR fragment decreased as nitrate levels in the groundwater decreased. In the second study the potential for bioaugmentation of a butane culture was evaluated in a series of field tests conducted at the Moffett Field Air Station in California. A butane-utilizing mixed culture that was effective in transforming 1, 1-dichloroethene (1, 1-DCE), 1, 1, 1-trichloroethane (1, 1, 1-TCA), and 1, 1-dichloroethane (1, 1-DCA) was added to the saturated zone at the test site. This mixture of contaminants was evaluated since they are often present as together as the result of 1, 1, 1-TCA contamination and the abiotic and biotic transformation of 1, 1, 1-TCA to 1, 1-DCE and 1, 1-DCA. Model simulations were performed prior to the initiation of the field study. The simulations were performed with a transport code that included processes for in-situ cometabolism, including microbial growth and decay, substrate and oxygen utilization, and the cometabolism of dual contaminants (1, 1-DCE and 1, 1, 1-TCA). Based on the results of detailed kinetic studies with the culture, cometabolic transformation kinetics were incorporated that butane mixed-inhibition on 1, 1-DCE and 1, 1, 1-TCA transformation, and competitive inhibition of 1, 1-DCE and 1, 1, 1-TCA on butane utilization. A transformation capacity term was also included in the model formation that results in cell loss due to contaminant transformation. Parameters for the model simulations were determined independently in kinetic studies with the butane-utilizing culture and through batch microcosm tests with groundwater and aquifer solids from the field test zone with the butane-utilizing culture added. In microcosm tests, the model simulated well the repetitive utilization of butane and cometabolism of 1.1, 1-TCA and 1, 1-DCE, as well as the transformation of 1, 1-DCE as it was repeatedly transformed at increased aqueous concentrations. Model simulations were then performed under the transport conditions of the field test to explore the effects of the bioaugmentation dose and the response of the system to tile biostimulation with alternating pulses of dissolved butane and oxygen in the presence of 1, 1-DCE (50 $\mu$g/L) and 1, 1, 1-TCA (250 $\mu$g/L). A uniform aquifer bioaugmentation dose of 0.5 mg/L of cells resulted in complete utilization of the butane 2-meters downgradient of the injection well within 200-hrs of bioaugmentation and butane addition. 1, 1-DCE was much more rapidly transformed than 1, 1, 1-TCA, and efficient 1, 1, 1-TCA removal occurred only after 1, 1-DCE and butane were decreased in concentration. The simulations demonstrated the strong inhibition of both 1, 1-DCE and butane on 1, 1, 1-TCA transformation, and the more rapid 1, 1-DCE transformation kinetics. Results of tile field demonstration indicated that bioaugmentation was successfully implemented; however it was difficult to maintain effective treatment for long periods of time (50 days or more). The demonstration showed that the bioaugmented experimental leg effectively transformed 1, 1-DCE and 1, 1-DCA, and was somewhat effective in transforming 1, 1, 1-TCA. The indigenous experimental leg treated in the same way as the bioaugmented leg was much less effective in treating the contaminant mixture. The best operating performance was achieved in the bioaugmented leg with about over 90%, 80%, 60 % removal for 1, 1-DCE, 1, 1-DCA, and 1, 1, 1-TCA, respectively. Molecular methods were used to track and enumerate the bioaugmented culture in the test zone. Real Time PCR analysis was used to on enumerate the bioaugmented culture. The results show higher numbers of the bioaugmented microorganisms were present in the treatment zone groundwater when the contaminants were being effective transformed. A decrease in these numbers was associated with a reduction in treatment performance. The results of the field tests indicated that although bioaugmentation can be successfully implemented, competition for the growth substrate (butane) by the indigenous microorganisms likely lead to the decrease in long-term performance.

  • PDF