Residual hydrocarbons in long-term contaminated soils: implications to risk-based management
Bibliographic record
Abstract
Petroleum hydrocarbon (PHC) contamination is a widespread and severe environmental issue affecting many countries' resource sectors. PHCs are mixtures of hydrocarbon compounds with varying molar masses that naturally attenuate at different rates. Lighter fractions attenuate first, followed by medium-molar-mass constituents, while larger molecules remain for longer periods. This results in significant regulatory challenges concerning residual hydrocarbons in long-term contaminated soils. This study examined the potential risks associated with residual PHC and its implications for risk-based management of heavily contaminated soils (23,000-26,000 mg PHC/kg). Ecotoxicological properties, such as seedling emergence and growth of two native plant species-small Flinders grass (Iseilema membranaceum) and ruby saltbush (Enchylaena tomentosa)-and earthworm survival tests in PHC-contaminated soils, were assessed. Additionally, the effects of aging on the attenuation of PHC in contaminated soils were evaluated. Toxicity responses of plant growth parameters were determined as no-observed-effect concentrations: 75%-100% for seedling emergence, < 25%-75% for plant shoot height, and 75%-100% for earthworm survival. After 42 weeks of aging, the total PHC levels in weathered soils decreased by 14% to 30% and by 67% in diesel-spiked soil due to natural attenuation. Dehydrogenase enzyme activity in soils increased during the initial aging period. Furthermore, a clear shift of bacterial communities was observed in the soils following aging, including enrichment of PHC-resistant and -utilizing bacteria-for example, Nocardia sp. This study underscores the potential of natural attenuation for eco-friendly and cost-effective soil management, underlining that its success depends on site-specific factors like water content and nutrient availability. Therefore, we recommend detailed soil assessments to evaluate these conditions prior to adopting a risk-based management approach.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.001 |
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 teacher head, 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".