Sediment microbial fuel cells as a barrier to sulfide accumulation and their potential for sediment remediation beneath aquaculture pens
Bibliographic record
Abstract
Sediment microbial fuel cells (SMFCs) generate electricity through the oxidation of reduced compounds, such as sulfide or organic carbon compounds, buried in anoxic sediments. The ability to remove sulfide suggests their use in the remediation of sediments impacted by point source organic matter loading, such as occurs beneath open pen aquaculture farms. However, for SMFCs to be a viable technology they must remove sulfide at a scale relevant to the environmental contamination and their impact on the sediment geochemistry as a whole must be evaluated. Here we address these issues through a laboratory microcosm experiment. Two SMFCs placed in high organic matter sediments were operated for 96 days and compared to open circuit and sediment only controls. The impact on sediment geochemistry was evaluated with microsensor profiling for oxygen, sulfide, and pH. The SMFCs had no discernable effect on oxygen profiles, however porewater sulfide was significantly lower in the sediment microcosms with functioning SMFCs than those without. Depth integrated sulfide inventories in the SMFCs were only 20% that of the controls. However, the SMFCs also lowered pH in the sediments and the consequences of this acidification on sediment geochemistry should be considered if developing SMFCs for remediation. The data presented here indicate that SMFCs have potential for the remediation of sulfidic sediments around aquaculture operations.
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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) | 0.001 | 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".