Grantee Research Project Results

Final Report: Real-Time Transformer Oil Polychlorinated Biphenyl Sensor

EPA Contract Number: EPD07082
Title: Real-Time Transformer Oil Polychlorinated Biphenyl Sensor
Investigators: Evenson, Carl R.
Small Business: Eltron Research & Development Inc.
EPA Contact: Richards, April
Phase: II
Project Period: May 1, 2007 through April 30, 2009
Project Amount: $212,294
RFA: Small Business Innovation Research (SBIR) - Phase II (2007) Recipients Lists
Research Category: SBIR - Waste , Hazardous Waste/Remediation , Small Business Innovation Research (SBIR)

Description:

Under this SBIR Phase II project, Eltron developed a portable system for analysis of polychlorinated biphenyl (PCB)-contaminated transformer oil. Raman spectroscopy and multivariate analysis were combined to create a rapid in situ sensor capable of simultaneous determination of PCB concentration and composition. The system utilized a submersible probe to provide essentially real-time analysis without removing transformer oil from its reservoir. Eltron’s Raman-based sensor combines the advantages of high sensitivity, low detection limits, and the ability to distinguish different Aroclors with a low per sample testing cost in a field deployable, hand-held unit.

Summary/Accomplishments (Outputs/Outcomes):

Aroclors 1016, 1232, 1242, 1254, and 1260 were added to five different transformer oils in varying concentrations. In addition, binary and ternary mixtures of Aroclors were prepared in transformer oil. Raman spectra were collected for each sample and a library of greater than 3,000 Raman spectra was assembled. Raman spectra were imported into Pirouette software for chemometric analysis testing. Both regression and classification modeling were performed. Multiple variables were tested with partial least squares regression modeling, including preprocessing techniques, transforms, wavenumber ranges, and maximum PCB concentration.

Regression models clearly showed the ability of the model to predict PCB concentration; the models, however, were not accurate enough at low PCB concentrations to be effective as PCB sensors. Typical errors observed were on the order of 10 percent. For transformers with low concentrations of PCBs (< 50 ppm), this error is too large for accurate real-time PCB monitoring. In an effort to improve the model accuracy, Surface Enhanced Raman Spectroscopy (SERS) was tested. Results were mixed. SERS did improve model accuracy for some transformer oils, but showed no improvement for other oils. Classification modeling showed that different transformer oils and different Aroclors within the same transformer oil could be predicted using a classification model.

Conclusions:

In this Phase II project, Eltron successfully demonstrated that a chemometric sensor based on Raman spectroscopy could be used to predict PCB concentrations in transformer oil. A library of greater than 3,000 Raman spectra was collected for model development in Pirouette chemometric software. Regression and classification modeling were performed. Regression models clearly showed the ability of the models to predict PCB concentration; however, the models were not accurate enough at low PCB concentrations to be effective as PCB sensors. In an effort to improve the model accuracy, SERS was tested. Results were mixed. SERS did improve model accuracy for some transformer oils, but not for other oils. Overall, the modeling results were not accurate enough to justify development of a hand-held Raman sensor prototype.

Supplemental Keywords:

small business, SBIR, EPA, polychlorinated biphenyls, PCB, Raman spectroscopy, portable real-time sensor, environmental monitoring, portable monitoring, hazardous waste removal, sustainable industry/business, scientific discipline, RFA, technology for sustainable environment, sustainable environment, environmental engineering, environmental monitoring, environmental technology, real-time measurement, hand-held Raman, chemometrics, PCB sensor, RFA, Scientific Discipline, Sustainable Industry/Business, Sustainable Environment, Technology for Sustainable Environment, Environmental Monitoring, Environmental Engineering, environmental technology, real time measurement, PCB

SBIR Phase I:

Real-Time Transformer Oil Polychlorinated Biphenyl Sensor | Final Report

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