Nontarget profiling of organic compounds in a temporal series of hydraulic fracturing flowback and produced waters
Bibliographic record
Abstract
Hydraulic fracturing (HF) flowback and produced water (FPW) can be toxic to aquatic life but its chemical content is largely unknown, variable and complex. Seven FPW samples were collected from a HF operation in the Duvernay Formation (Alberta, Canada) over 30 days of flowback and characterized by a nontarget workflow based on high performance liquid chromatography - high resolution mass spectrometry (HRMS). A modified Kendrick mass defect plot and MS/MS spectral interpretation revealed seven series of homologues composed of ethylene oxide (i.e. -CH 2 CH 2 O-), among which a series of aldehydes was proposed as degradation products of polyethylene glycols , and two series of alkyl ethoxylate carboxylates could be proprietary HF additives. Many other ions were confidently assigned a formula by accurate mass measurement and were subsequently prioritized for identification by matching to records in ChemSpider and the US EPA's CompTox Chemistry Dashboard. Quaternary ammonium compounds , amine oxides , organophosphorous compounds , phthalate diesters and hydroxyquinoline were identified with high confidence by MS/MS spectra (Level 3), matching to reference spectra in MassBank (Level 2) or to authentic standards (Level 1). Temporal trends showed that most of the compounds declined in abundance over the first nine days of flowback, except for phthalate diesters and hydroxyquinoline that were still observed on Day 30 and had disappearance half-lives of 61 and 91 days, respectively. All the compounds followed first-order disappearance kinetics in flowback, except for polyoxygenated acids which followed second-order kinetics. This analysis and the workflow, based largely on public on-line databases, enabled profiling of complex organic compounds in HF-FPW, and will likely be useful for further understanding the toxicity and chemical fate of HF-FPW.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".