Spatial Patterns of Microplastics in Surface Seawater, Sediment, and Sand Along Qingdao Coastal Environment
Bibliographic record
Abstract
Coastal environments, ecologically fragile zones, are subjected to great human pressures, particularly, xenobiotic pollutants such as microplastics (MPs) and trace metals. Yet, the impact of anthropogenic intervention on the spatial patterns of MPs in different coastal environmental compartments of Qingdao, a city located in the west Yellow Sea, is still unclear. Therefore, the spatial distribution, characteristics, and diversity of MPs (≥ 50 µm) in seawater, sediment, and sand samples collected from 10 zones intervened by different anthropogenic activities in Qingdao coastal environment were investigated. The abundance of MPs was 93.1 ± 63.5 items/m 3 in seawater, which was 4577 ± 2902 items/kg in sediments and 3602 ± 1708 items/kg in the beach sands. A spatial analysis indicated that the distribution characteristics of MPs, including abundance, color, and type, greatly varied among the zones with different extent of human activities. The highest abundance of MPs in the seawater was detected in the abandoned aquafarm, followed by harbors, beaches, estuary, sewage discharge areas, operational aquafarm, and rural areas, whereas the highest MP abundance in the sediments followed the order of harbor, sewage discharge, estuary, abandoned aquafarm, beaches, rural area, and operational aquafarm. The highest MP abundance in the scenic and recreational beach sands was, respectively, in the intertidal and supratidal zone. The transparent chlorinated polyethylene fragments with the relatively small size of 50–100 μm were the dominant MPs in the coastal environment. The higher physicochemical characteristic diversity in terms of size, color, shape, and type of MPs in the aquafarms, harbors, and recreational beach than those of the other zones, illustrated the higher complexity and diversity of MP pollution sources in these zones. These results jointly indicated that aquaculture, navigation, and tourism mainly determined MP spatial distribution patterns in the coastal environment of Qingdao. These results also extend the understanding of the inventory and fate of MPs in coastal environment, thus providing important data to establish effective strategies for abating MP pollution in marine ecosystems.
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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 | 0.002 |
| 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 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".