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Svetlozar Velizarov - One of the best experts on this subject based on the ideXlab platform.

  • 2d Fluorescence Spectroscopy for monitoring ion exchange membrane based technologies reverse electrodialysis red
    Water Research, 2016
    Co-Authors: Sylwin Pawlowski, Claudia F Galinha, Joao G Crespo, Svetlozar Velizarov
    Abstract:

    Reverse electrodialysis (RED) is one of the emerging, membrane-based technologies for harvesting salinity gradient energy. In RED process, fouling is an undesirable operation constraint since it leads to a decrease of the obtainable net power density due to increasing stack electric resistance and pressure drop. Therefore, early fouling detection is one of the main challenges for successful RED technology implementation. In the present study, two-dimensional (2D) Fluorescence Spectroscopy was used, for the first time, as a tool for fouling monitoring in RED. Fluorescence excitation-emission matrices (EEMs) of ion-exchange membrane surfaces and of natural aqueous streams were acquired during one month of a RED stack operation. Fouling evolvement on the ion-exchange membrane surfaces was successfully followed by 2D Fluorescence Spectroscopy and quantified using principal components analysis (PCA). Additionally, the efficiency of cleaning strategy was assessed by measuring the membrane Fluorescence emission intensity before and after cleaning. The anion-exchange membrane (AEM) surface in contact with river water showed to be significantly affected due to fouling by humic compounds, which were found to cross through the membrane from the lower salinity (river water) to higher salinity (sea water) stream. The results obtained show that the combined approach of using 2D Fluorescence Spectroscopy and PCA has a high potential for studying fouling development and membrane cleaning efficiency in ion exchange membrane processes.

  • 2d Fluorescence Spectroscopy for monitoring ion exchange membrane based technologies reverse electrodialysis red
    Water Research, 2016
    Co-Authors: Sylwin Pawlowski, Claudia F Galinha, Joao G Crespo, Svetlozar Velizarov
    Abstract:

    Reverse electrodialysis (RED) is one of the emerging, membrane-based technologies for harvesting salinity gradient energy. In RED process, fouling is an undesirable operation constraint since it leads to a decrease of the obtainable net power density due to increasing stack electric resistance and pressure drop. Therefore, early fouling detection is one of the main challenges for successful RED technology implementation. In the present study, two-dimensional (2D) Fluorescence Spectroscopy was used, for the first time, as a tool for fouling monitoring in RED. Fluorescence excitation-emission matrices (EEMs) of ion-exchange membrane surfaces and of natural aqueous streams were acquired during one month of a RED stack operation. Fouling evolvement on the ion-exchange membrane surfaces was successfully followed by 2D Fluorescence Spectroscopy and quantified using principal components analysis (PCA). Additionally, the efficiency of cleaning strategy was assessed by measuring the membrane Fluorescence emission intensity before and after cleaning. The anion-exchange membrane (AEM) surface in contact with river water showed to be significantly affected due to fouling by humic compounds, which were found to cross through the membrane from the lower salinity (river water) to higher salinity (sea water) stream. The results obtained show that the combined approach of using 2D Fluorescence Spectroscopy and PCA has a high potential for studying fouling development and membrane cleaning efficiency in ion exchange membrane processes.

Sylwin Pawlowski - One of the best experts on this subject based on the ideXlab platform.

  • 2d Fluorescence Spectroscopy for monitoring ion exchange membrane based technologies reverse electrodialysis red
    Water Research, 2016
    Co-Authors: Sylwin Pawlowski, Claudia F Galinha, Joao G Crespo, Svetlozar Velizarov
    Abstract:

    Reverse electrodialysis (RED) is one of the emerging, membrane-based technologies for harvesting salinity gradient energy. In RED process, fouling is an undesirable operation constraint since it leads to a decrease of the obtainable net power density due to increasing stack electric resistance and pressure drop. Therefore, early fouling detection is one of the main challenges for successful RED technology implementation. In the present study, two-dimensional (2D) Fluorescence Spectroscopy was used, for the first time, as a tool for fouling monitoring in RED. Fluorescence excitation-emission matrices (EEMs) of ion-exchange membrane surfaces and of natural aqueous streams were acquired during one month of a RED stack operation. Fouling evolvement on the ion-exchange membrane surfaces was successfully followed by 2D Fluorescence Spectroscopy and quantified using principal components analysis (PCA). Additionally, the efficiency of cleaning strategy was assessed by measuring the membrane Fluorescence emission intensity before and after cleaning. The anion-exchange membrane (AEM) surface in contact with river water showed to be significantly affected due to fouling by humic compounds, which were found to cross through the membrane from the lower salinity (river water) to higher salinity (sea water) stream. The results obtained show that the combined approach of using 2D Fluorescence Spectroscopy and PCA has a high potential for studying fouling development and membrane cleaning efficiency in ion exchange membrane processes.

  • 2d Fluorescence Spectroscopy for monitoring ion exchange membrane based technologies reverse electrodialysis red
    Water Research, 2016
    Co-Authors: Sylwin Pawlowski, Claudia F Galinha, Joao G Crespo, Svetlozar Velizarov
    Abstract:

    Reverse electrodialysis (RED) is one of the emerging, membrane-based technologies for harvesting salinity gradient energy. In RED process, fouling is an undesirable operation constraint since it leads to a decrease of the obtainable net power density due to increasing stack electric resistance and pressure drop. Therefore, early fouling detection is one of the main challenges for successful RED technology implementation. In the present study, two-dimensional (2D) Fluorescence Spectroscopy was used, for the first time, as a tool for fouling monitoring in RED. Fluorescence excitation-emission matrices (EEMs) of ion-exchange membrane surfaces and of natural aqueous streams were acquired during one month of a RED stack operation. Fouling evolvement on the ion-exchange membrane surfaces was successfully followed by 2D Fluorescence Spectroscopy and quantified using principal components analysis (PCA). Additionally, the efficiency of cleaning strategy was assessed by measuring the membrane Fluorescence emission intensity before and after cleaning. The anion-exchange membrane (AEM) surface in contact with river water showed to be significantly affected due to fouling by humic compounds, which were found to cross through the membrane from the lower salinity (river water) to higher salinity (sea water) stream. The results obtained show that the combined approach of using 2D Fluorescence Spectroscopy and PCA has a high potential for studying fouling development and membrane cleaning efficiency in ion exchange membrane processes.

Claudia F Galinha - One of the best experts on this subject based on the ideXlab platform.

  • 2d Fluorescence Spectroscopy for monitoring ion exchange membrane based technologies reverse electrodialysis red
    Water Research, 2016
    Co-Authors: Sylwin Pawlowski, Claudia F Galinha, Joao G Crespo, Svetlozar Velizarov
    Abstract:

    Reverse electrodialysis (RED) is one of the emerging, membrane-based technologies for harvesting salinity gradient energy. In RED process, fouling is an undesirable operation constraint since it leads to a decrease of the obtainable net power density due to increasing stack electric resistance and pressure drop. Therefore, early fouling detection is one of the main challenges for successful RED technology implementation. In the present study, two-dimensional (2D) Fluorescence Spectroscopy was used, for the first time, as a tool for fouling monitoring in RED. Fluorescence excitation-emission matrices (EEMs) of ion-exchange membrane surfaces and of natural aqueous streams were acquired during one month of a RED stack operation. Fouling evolvement on the ion-exchange membrane surfaces was successfully followed by 2D Fluorescence Spectroscopy and quantified using principal components analysis (PCA). Additionally, the efficiency of cleaning strategy was assessed by measuring the membrane Fluorescence emission intensity before and after cleaning. The anion-exchange membrane (AEM) surface in contact with river water showed to be significantly affected due to fouling by humic compounds, which were found to cross through the membrane from the lower salinity (river water) to higher salinity (sea water) stream. The results obtained show that the combined approach of using 2D Fluorescence Spectroscopy and PCA has a high potential for studying fouling development and membrane cleaning efficiency in ion exchange membrane processes.

  • 2d Fluorescence Spectroscopy for monitoring ion exchange membrane based technologies reverse electrodialysis red
    Water Research, 2016
    Co-Authors: Sylwin Pawlowski, Claudia F Galinha, Joao G Crespo, Svetlozar Velizarov
    Abstract:

    Reverse electrodialysis (RED) is one of the emerging, membrane-based technologies for harvesting salinity gradient energy. In RED process, fouling is an undesirable operation constraint since it leads to a decrease of the obtainable net power density due to increasing stack electric resistance and pressure drop. Therefore, early fouling detection is one of the main challenges for successful RED technology implementation. In the present study, two-dimensional (2D) Fluorescence Spectroscopy was used, for the first time, as a tool for fouling monitoring in RED. Fluorescence excitation-emission matrices (EEMs) of ion-exchange membrane surfaces and of natural aqueous streams were acquired during one month of a RED stack operation. Fouling evolvement on the ion-exchange membrane surfaces was successfully followed by 2D Fluorescence Spectroscopy and quantified using principal components analysis (PCA). Additionally, the efficiency of cleaning strategy was assessed by measuring the membrane Fluorescence emission intensity before and after cleaning. The anion-exchange membrane (AEM) surface in contact with river water showed to be significantly affected due to fouling by humic compounds, which were found to cross through the membrane from the lower salinity (river water) to higher salinity (sea water) stream. The results obtained show that the combined approach of using 2D Fluorescence Spectroscopy and PCA has a high potential for studying fouling development and membrane cleaning efficiency in ion exchange membrane processes.

Joao G Crespo - One of the best experts on this subject based on the ideXlab platform.

  • 2d Fluorescence Spectroscopy for monitoring ion exchange membrane based technologies reverse electrodialysis red
    Water Research, 2016
    Co-Authors: Sylwin Pawlowski, Claudia F Galinha, Joao G Crespo, Svetlozar Velizarov
    Abstract:

    Reverse electrodialysis (RED) is one of the emerging, membrane-based technologies for harvesting salinity gradient energy. In RED process, fouling is an undesirable operation constraint since it leads to a decrease of the obtainable net power density due to increasing stack electric resistance and pressure drop. Therefore, early fouling detection is one of the main challenges for successful RED technology implementation. In the present study, two-dimensional (2D) Fluorescence Spectroscopy was used, for the first time, as a tool for fouling monitoring in RED. Fluorescence excitation-emission matrices (EEMs) of ion-exchange membrane surfaces and of natural aqueous streams were acquired during one month of a RED stack operation. Fouling evolvement on the ion-exchange membrane surfaces was successfully followed by 2D Fluorescence Spectroscopy and quantified using principal components analysis (PCA). Additionally, the efficiency of cleaning strategy was assessed by measuring the membrane Fluorescence emission intensity before and after cleaning. The anion-exchange membrane (AEM) surface in contact with river water showed to be significantly affected due to fouling by humic compounds, which were found to cross through the membrane from the lower salinity (river water) to higher salinity (sea water) stream. The results obtained show that the combined approach of using 2D Fluorescence Spectroscopy and PCA has a high potential for studying fouling development and membrane cleaning efficiency in ion exchange membrane processes.

  • 2d Fluorescence Spectroscopy for monitoring ion exchange membrane based technologies reverse electrodialysis red
    Water Research, 2016
    Co-Authors: Sylwin Pawlowski, Claudia F Galinha, Joao G Crespo, Svetlozar Velizarov
    Abstract:

    Reverse electrodialysis (RED) is one of the emerging, membrane-based technologies for harvesting salinity gradient energy. In RED process, fouling is an undesirable operation constraint since it leads to a decrease of the obtainable net power density due to increasing stack electric resistance and pressure drop. Therefore, early fouling detection is one of the main challenges for successful RED technology implementation. In the present study, two-dimensional (2D) Fluorescence Spectroscopy was used, for the first time, as a tool for fouling monitoring in RED. Fluorescence excitation-emission matrices (EEMs) of ion-exchange membrane surfaces and of natural aqueous streams were acquired during one month of a RED stack operation. Fouling evolvement on the ion-exchange membrane surfaces was successfully followed by 2D Fluorescence Spectroscopy and quantified using principal components analysis (PCA). Additionally, the efficiency of cleaning strategy was assessed by measuring the membrane Fluorescence emission intensity before and after cleaning. The anion-exchange membrane (AEM) surface in contact with river water showed to be significantly affected due to fouling by humic compounds, which were found to cross through the membrane from the lower salinity (river water) to higher salinity (sea water) stream. The results obtained show that the combined approach of using 2D Fluorescence Spectroscopy and PCA has a high potential for studying fouling development and membrane cleaning efficiency in ion exchange membrane processes.

Jonathan D Posner - One of the best experts on this subject based on the ideXlab platform.

  • excitation emission matrix Fluorescence Spectroscopy for combustion generated particulate matter source identification
    Atmospheric Environment, 2020
    Co-Authors: Jay W Rutherford, Neal Dawsonelli, Anne M Manicone, Gregory V Korshin, Igor Novosselov, Edmund Seto, Jonathan D Posner
    Abstract:

    Abstract The inhalation of particulate matter (PM) is a significant health risk associated with reduced life expectancy due to increased cardio-pulmonary disease and exacerbation of respiratory diseases such as asthma and pneumonia. PM originates from natural and anthropogenic sources including combustion engines, cigarettes, agricultural burning, and forest fires. Identifying the source of PM can inform effective mitigation strategies and policies, but this is difficult to do using current techniques. Here we present a method for identifying PM source using excitation emission matrix (EEM) Fluorescence Spectroscopy and a machine learning algorithm. We collected combustion generated PM2.5 from wood burning, diesel exhaust, and cigarettes using filters. Filters were weighted to determine mass concentration followed by extraction into cyclohexane and analysis by EEM Fluorescence Spectroscopy. Spectra obtained from each source served as training data for a convolutional neural network (CNN) used for source identification in mixed samples. This method can predict the presence or absence of the three laboratory sources with an overall accuracy of 89% when the threshold for classifying a source as present is 1.1 μg/m3 in air over a 24-h sampling time. The limit of detection for cigarette, diesel and wood are 0.7, 2.6, 0.9 μg/m3, respectively, in air assuming a 24-h sampling time at an air sampling rate of 1.8 L per minute. We applied the CNN algorithm developed using the laboratory training data to a small set of field samples and found the algorithm was effective in some cases but would require a training data set containing more samples to be more broadly applicable.

  • excitation emission matrix Fluorescence Spectroscopy for combustion generated particulate matter source identification
    Atmospheric Environment, 2020
    Co-Authors: Jay W Rutherford, Neal Dawsonelli, Anne M Manicone, Gregory V Korshin, Igor Novosselov, Edmund Seto, Jonathan D Posner
    Abstract:

    The inhalation of particulate matter (PM) is a significant health risk associated with reduced life expectancy due to increased cardio-pulmonary disease and exacerbation of respiratory diseases such as asthma and pneumonia. PM originates from natural and anthropogenic sources including combustion engines, cigarettes, agricultural burning, and forest fires. Identifying the source of PM can inform effective mitigation strategies and policies, but this is difficult to do using current techniques. Here we present a method for identifying PM source using excitation emission matrix (EEM) Fluorescence Spectroscopy and a machine learning algorithm. We collected combustion generated PM2.5 from wood burning, diesel exhaust, and cigarettes using filters. Filters were weighted to determine mass concentration followed by extraction into cyclohexane and analysis by EEM Fluorescence Spectroscopy. Spectra obtained from each source served as training data for a convolutional neural network (CNN) used for source identification in mixed samples. This method can predict the presence or absence of the three laboratory sources with an overall accuracy of 89% when the threshold for classifying a source as present is 1.1 μg/m3 in air over a 24-hour sampling time. The limit of detection for cigarette, diesel and wood are 0.7, 2.6, 0.9 μg/m3, respectively, in air assuming a 24-hour sampling time at an air sampling rate of 1.8 liters per minute. We applied the CNN algorithm developed using the laboratory training data to a small set of field samples and found the algorithm was effective in some cases but would require a training data set containing more samples to be more broadly applicable.

  • excitation emission matrix Fluorescence Spectroscopy for combustion generated particulate matter source identification
    ChemRxiv, 2019
    Co-Authors: Jay Rutherford, Neal Dawsonelli, Anne M Manicone, Gregory V Korshin, Igor Novosselov, Edmund Seto, Jonathan D Posner
    Abstract:

    The inhalation of particulate matter (PM) is a significant health risk associated with reduced life expectancy due to increased cardio-pulmonary disease and exacerbation of respiratory diseases such as asthma and pneumonia. PM originates from natural and anthropogenic sources including combustion engines, cigarettes, agricultural burning, and forest fires. Identifying the source of PM can inform effective mitigation strategies and policies, but this is difficult to do using current techniques. Here we present a method for identifying PM source using excitation emission matrix (EEM) Fluorescence Spectroscopy and a machine learning algorithm. We collected combustion generated PM2.5 from wood burning, diesel exhaust, and cigarettes using filters. Filters were weighted to determine mass concentration followed by extraction into cyclohexane and analysis by EEM Fluorescence Spectroscopy. Spectra obtained from each source were used as machine learning training data for source identification in mixed samples. This method can predict the presence or absence of the three laboratory sources with an overall accuracy of 89% when the threshold for classifying a source as present is 1.1 µg/m3 in air over a 24-hour sampling time. We apply this method to a small set of field samples to evaluate its effectiveness.