Using a modified dredging elutriate testing approach to evaluate potential aquatic impacts associated with dredging a large freshwater industrial harbor
Bibliographic record
Abstract
Abstract Potential adverse impacts to the aquatic environment should be minimized whenever possible during an environmental dredging project by selecting realistic and technically feasible environmental targets. These targets need to balance short term impacts with the longer term benefit of removing contaminated sediments from the environment. Environmental dredging is part of the planned remediation of Randle Reef (a 60 hectare zone of mostly PAH-contaminated sediments) in Hamilton, Ontario, Canada. In this study, we describe the results of dredging elutriate toxicity testing (DETE) to assess the potential risks from dredging this PAH contaminated site. A modified elutriate preparation method intended as an alternative measure of conditions within the dredging plume was assessed with both standard water column species (Daphnia magna and fathead minnow [Pimephales promelas]) and alternative benthic and epibenthic test organisms (Chironomus dilutus and Hyalella azteca). The standard DETE test was also conducted with H. azteca to compare with the modified DETE results. The greatest toxic response was seen in the alternative test species; however, the modified DETE method resulted in less toxicity than the standard protocol. The relationship between toxicity results and chemical and/or physical characteristics of the samples was examined, but differences in toxicity could only be explained by differences in the total suspended solids concentrations in the elutriate samples. Challenges associated with DETE assessment of PAH-contaminated sediments and the implications for establishing dredging benchmarks are discussed. Integr Environ Assess Manag 2017;13:155–166. © 2016 SETAC Key Points We identify how the DRET and DETE methods were used and adapted to assess potential site-specific toxicity to organisms exposed to the plume generated by dredging of Hamilton Harbour. We found that numerical data provides the foundation but is not the only aspect when setting guidance for a dredging project. We discuss the value as well as sources of uncertainty in the use of DETE for the derivation of environmental benchmarks for dredging. PAH-contaminated sites pose unique challenges for sediment managers due to the heterogeneity and oily nature of the sediment, and toxicity cannot easily be related to chemical concentrations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".