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Multivariate statistical methods for evaluating biodegradation of mineral oil.
Jan H Christensen1, Asger B Hansen, Ulrich Karlson
1Department of Natural Sciences, Royal Veterinary and Agricultural University, Thorvaldsensvej 40, 1871 Frederiksberg C, Denmark. jch@kvl.dk
Journal of Chromatography. A
|October 1, 2005
Summary
Two novel methods effectively evaluate mineral oil biodegradation using gas chromatography-mass spectrometry and principal component analysis. These techniques differentiate bacterial strain impacts on polycyclic aromatic compounds, aiding environmental spill and bioremediation assessments.
Area of Science:
- Environmental Science
- Analytical Chemistry
- Microbiology
Background:
- Environmental spills of mineral oil pose risks.
- Natural attenuation and bioremediation are key mitigation strategies.
- Accurate evaluation of these processes is crucial.
Purpose of the Study:
- Develop and validate two methods for assessing mineral oil biodegradation.
- Compare the efficacy of different bacterial strain mixtures in degrading oil components.
- Analyze the impact of microbial activity on polycyclic aromatic compounds (PACs).
Main Methods:
- Gas chromatography-mass spectrometry (GC-MS) in selected ion monitoring (SIM) mode for compound-specific data.
- Data preprocessing including derivative calculation, alignment, normalization, or peak identification and ratio calculation.
- Principal component analysis (PCA) applied to chromatograms or diagnostic ratios to study oil fate.
Main Results:
- Both developed methods provided comparable results in evaluating biodegradation.
- Principal component analysis effectively differentiated the effects of various bacterial consortia (R, U, M).
- Specific PAC isomer patterns revealed distinct microbial degradation capabilities and metabolic activities.
Conclusions:
- The developed GC-MS and PCA-based methods are effective for evaluating natural attenuation and bioremediation of mineral oil.
- Bacterial strain mixtures significantly influence PAC isomer degradation patterns.
- These methods offer objective insights into microbial degradation processes for environmental monitoring.