Including impacts of microplastics in marine water and sediments in life cycle assessment
Bibliographic record
Abstract
Microplastics (MPs) pose a threat to marine ecosystems. When released, MPs first reach the water column, where they can be ingested by pelagic species. MPs can then reach marine sediments, a potential sink, where they may affect sediment-dwelling species. However, current life cycle impact assessment (LCIA) methods do not consider the impact of MPs in sediments, providing an incomplete picture when comparing environmental profiles of products and services. This work builds on the MarILCA working group characterization factors (CFs) by computing updated physical effects on biota CFs that include both water and sediment compartments, as previous factors did not consider the latter. A simplified fate of MPs in the marine environment is modelled, combining fate in water and sediments and differentiating between MP polymers, sizes, and shapes. A combined exposure and effect factor for MPs in sediments (EEF sed ) is developed, calculated from a hazardous concentration for 20 % of species (HC20), derived from a species sensitivity distribution (SSD) of effect concentrations of 10 % (EC10) values. A methodology accounting for species feeding behaviour is proposed to derive ecosystem-level impacts via exposure through different compartments, expressed as the potentially affected fraction (PAF) of marine species. Combining the fate, EEF sed , and EEF w (water) yielded updated marine CFs including impacts on both water and sediment-dwelling biota. CFs were tested in a textile LCA case study. Sediments were found to be a sink for high-density MPs, with EEF sed (16 PAF m 3 /kg) significantly lower than the previously reported EEF w (1068 PAF m 3 /kg). Developed marine CFs range from 34 to 5.4 × 10 8 PAF m 3 d/kg and are available for use in environmental decision-making.
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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 | 0.001 | 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 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".