Temperature affects the sorption of trace metals by macro- and microplastics within marine intertidal sediments: insights from a long-term laboratory-based study
Bibliographic record
Abstract
Macro- and microplastics and trace metals are significant pollutants in the marine environment and have been reported in all ecosystems around the world. The process of sorption/desorption of trace metals by macro- and microplastics is influenced by various factors, including the morphological characteristics of macro- and microplastics, their adsorption capacity, and environmental conditions. This research provides and discusses laboratory experimental findings on the sorption of trace metals cadmium (Cd), copper (Cu), lead (Pb), and zinc (Zn) by macro- and microplastics of polyethylene terephthalate (PETE) and high-density polyethylene (HDPE) within two contrasting marine intertidal sedimentary environments with high and low organic matter content under conditions of constant temperatures (T=- 4.0°C, T=+ 4.0°C, and T=+18.0°C). Our aim is to determine the effect of temperature on trace metal sorption onto macro- and microplastics. Temperature alters the metals’ sorption by plastic by altering the rate of reaching equilibrium and equilibrium concentration, whereas constant temperature had only a minor influence on the partitioning of trace metals. Sediment organic matter influences sorption dynamics at all three temperatures T=- 4.0°C, T=+ 4.0°C, and T=+18.0°C. This study enhances our understanding of how temperature can effect trace metals-plastic particle interactions in the marine intertidal sedimentary environment providing insight as to conditions that will create the greatest threat to higher trophic levels by providing an additional vector of Cd, Cu, Pb, and Zn exposure into benthic food webs.
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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) | 0.000 | 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".