Phthalates and Other Plastic Additives in Surface Sediments of the Cross River System, S.E. Niger Delta, Nigeria: Environmental Implication
Bibliographic record
Abstract
Quantitative determination of phthalates and other plastic additives was carried out using GC-MS in order to understand the distribution and fate of these compounds in surface sediments of the Cross River System. Results show the concentration ranges (mean±standard deviation) of the three phthalates as: di(ethylhexyl)phthalate (DEHP; 1.97– 86.76 [24.06 ± 29.88 mg/kg dry weight dw]); di(n-butyl)phthalate (DnBP; 0.16 – 17.41 [3.25 ± 5.03 mg/kg dw]); di(isobutyl)phthalate (DiBP; 1.14 – 29.64 [9.82 ± 10.23 mg/kg dw]). However, examination of n-hexane procedural blank (used also in the study for clean-up protocol) GC trace revealed the presence of certain amounts of DEHP and tris-2,6-di(t-butyl)phenylphosphite (PhP) which interfere with the targeted analytes. Therefore, extract/blank (E/B) ratios were calculated and were in the range 1.05 – 12.54, indicating that the concentrations of DEHP and PhP previously assigned to the sediments were partly derived from laboratory artifacts. Differences in grain size distribution, partitioning behavior, volatility and solubility in the aqueous phase as well as localized influx may account for the observed spatial variation of phthalates and other plastic additives in the river system. The primary sources of these phthalates and tris-2,6-di(t-butyl)phenylphosphate (PhP’) were considered to be the result of direct discharge of untreated effluent/solid waste and emission arising from burning of refuse containing plastic materials, respectively. The occurrence of certain anti-oxidant degradation products in sediments (not in the blank) such as 2,6-di(t-butyl)-4-hydroxybenzaldehyde (HBA) and 2,6-di(t-butyl)quinine (Qn) and PhP’ (a compound proposed here as a possible marker for plastic combustion for the region/air basin), suggests that phthalates contamination had occurred before sample contact with laboratory artifacts.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".