Fine-scale geographic risk assessment of oxybenzone sunscreen pollution within Hanauma Bay using hydrodynamic characterization and modeling
Bibliographic record
Abstract
Hanauma Bay's coral reef system is threatened by sunscreen pollution. Understanding the hydrodynamic nature of the bay is crucial for understanding the transport and fate of pollutants within the bay. This study conducted a comprehensive hydrodynamic analysis, revealing significant aspects of current patterns and their influence on sunscreen pollutant behavior. The analysis demonstrated the formation of flows that drive currents parallel to the shoreline, resulting in increased pollutant retention time over sensitive reef areas. Direct flushing currents were identified as playing a role in reducing pollution buildup. Particle dynamics analysis highlighted the importance of considering temporal dynamics and their implications for pollutant pathways, particularly through the swash zone during high tide phases. The study identified primary current patterns near the reef area and emphasized the circular behavior within the water body, affecting corals' susceptibility to bleaching in the southwestern part of Hanauma bay. To understand where oxybenzone concentrations were a threat to wildlife, we created a geographic model that integrated ecological risk assessment with hydrodynamic behavior in a given system, which we designate the Risk Quotient Plume - the geographic area where the concentration is above the threat level for a chemical. The study found high oxybenzone concentrations throughout the bay, threatening coral, fish, and algae populations. Oxybenzone's distribution indicated a serious threat to the entire back reef habitat and a hinderance to coral restoration efforts. The study also emphasizes the need to consider the hydrodynamic behavior of pollutants and their interaction with microplastics in the bay. Overall, the findings provide insights into hydrodynamics and pollutant dispersion in Hanauma Bay, supporting effective pollution management and conservation strategies.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".