Fingerprinting of petroleum hydrocarbons (PHC) and other biogenic organic compounds (BOC) in oil-contaminated and background soil samples
Bibliographic record
Abstract
Total petroleum hydrocarbons (TPH) or petroleum hydrocarbons (PHC) are one of the most widespread soil contaminants in Canada, the United States and many other countries worldwide. Clean-up of PHC-contaminated soils costs the Canadian economy hundreds of millions of dollars annually. In Canada, most PHC-contaminated site evaluations are based on the methods developed by the Canadian Council of the Ministers of the Environment (CCME). However, the CCME method does not differentiate PHC from BOC (the naturally occurring biogenic organic compounds), which are co-extracted with petroleum hydrocarbons in soil samples. Consequently, this could lead to overestimation of PHC levels in soil samples. In some cases, biogenic interferences can even exceed regulatory levels (300 μg g(-1) for coarse soils and 1300 μg g(-1) for fine soils for Fraction 3, C(16)-C(34) range, in the CCME Soil Quality Level). Resulting false exceedances can trigger unnecessary and costly cleanup or remediation measures. Therefore, it is critically important to develop new protocols to characterize and quantitatively differentiate PHC and BOC in contaminated soils. The ultimate objective of this PERD (Program of Energy Research and Development) project is to correct the misconception that all detectable hydrocarbons should be regulated as toxic petroleum hydrocarbons. During 2009-2010, soil and plant samples were collected from over forty oil-contaminated and paired background sites in various provinces. The silica gel column cleanup procedure was applied to effectively remove all target BOC from the oil-contaminated sample extracts. Furthermore, a reliable GC-MS method in combination with the derivatization technique, developed in this laboratory, was used for identification and characterization of various biogenic sterols and other major biogenic compounds in these oil-contaminated samples. Both PHC and BOC in these samples were quantitatively determined. This paper reports the characterization results of this set of 21 samples. In general, the presence of petroleum-characteristic alkylated PAH homologues and biomarkers can be used as unambiguous indicators of the contamination of oil and petroleum product hydrocarbons; while the absence of petroleum-characteristic alkylated PAH homologues and biomarkers and the presence of abundant BOC can be used as unambiguous indicators of the predominance of natural organic compounds in soil samples.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".