Leaching model of an expanding coastal dumpsite considering climate change
Bibliographic record
Abstract
Coastal dumpsites, which are common in low- and middle-income countries, pose significant environmental threats due to the lack of containment systems and their vulnerability to erosion, flooding, and climate change. Neither field measurements nor mechanistic models are abundant in the literature to understand the relevant processes. We develop a simple yet generic leachate generation model, which integrates a 3-dimensional (3D) waste dumping module, a water balance module, and a pollutant transport module. The model is validated using the available information of the Thilafushi dumpsite in the Maldives, which is a typical example of Small Island Developing States (SIDS). The measured groundwater total dissolved solids (TDS) in nearby monitoring wells of the dumpsite match nicely with the modeling results using the dumpsite model and another pollutant transport in aquifer model. Furthermore, the model predicts that the cumulative releases of dissolved organic carbon, copper, and chromium will increase by 100-182% between 2022 and 2100 under the baseline scenario. Three climate change factors are investigated, including precipitation variation, temperature rise, and sea level rise, under three Shared Socioeconomic Pathway (SSP) scenarios. Temperature rise shows the most significant contribution to the increase in pollutant leaching due to increased leaching potential. The combined effect of temperature rise and precipitation variation will increase the cumulative release of Cu by up to 23% by 2100 under SSP585 compared to the baseline scenario. The established model is readily applicable to other coastal dumpsites in SIDS and coastal countries, which call for timely assessments and potential mitigations.
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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 | 0.000 | 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 | 0.001 |
| 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".