Terrestrial Toxicity of Synthetic Gas-to-Liquid versus Crude Oil–Derived Drilling Fluids in Soil
Bibliographic record
Abstract
Unlike most other conventional petroleum products that are derived from crude oil, gas-to-liquids (GTLs) are petroleum products that are synthesized from natural gas (methane). This process results in GTL products having no sulfur and low aromatic content, so they should have less impact on human health and the environment compared with crude oil-derived products. The GTLs have been registered for use as nonaqueous base fluids (NABFs) in drilling muds, which aid in the process of drilling wells for oil and gas extraction; it is through these uses and others that they enter terrestrial environments. The primary objective of the present study was to determine whether GTLs were less toxic to terrestrial soil biota than conventional NABFs used for land-based drilling, such as diesel and low-toxicity mineral oil (LTMO). A second objective was to understand the fate and impact of these fluids under more realistic soil and aging conditions of a common west Texas (USA) oil-producing region (i.e., sandy loam soil with low organic matter and a hot arid climate). Acute terrestrial toxicity studies were conducted on the soft-bodied terrestrial invertebrate earthworm (Eisenia fetida) along with 3 plant species-alfalfa (Medicago stavia), thickspike wheatgrass (Elymus lanceolatus), and fourwing saltbrush (Atriplex canescens). We also assessed changes in microbial community structure of the soils following additions of NABF. Overall, the GTL NABFs had lower toxicity compared with conventional NABFs like diesel and LTMO, as measured by invertebrate toxicity, plant seed germination, and impact on the microbial community. Environ Toxicol Chem 2020;39:721-730. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.
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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 | 0.000 | 0.000 |
| 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".