Microbial Response Following a Carboxymethyl Cellulose-Stabilized Sulfidated Nano Zero-Valent Iron Injection: A Long-Term Field Study
Bibliographic record
Abstract
Sulfidated nano zero-valent iron (S-nZVI), recognized for its high remediation efficiency, was evaluated in a field trial to assess its impact on microbial communities in subsurface environments contaminated with chlorinated volatile organic compounds (cVOCs). Over a 1.5 year monitoring period, groundwater samples were collected to track microbial responses following the injection of carboxymethyl cellulose (CMC)-stabilized and dithionite-sulfidated nZVI (CMC-S-nZVI). The study observed pronounced and prolonged biostimulatory effects at locations receiving notable amounts of CMC-S-nZVI, as evidenced by increased DNA and bacterial concentrations. 16S rRNA gene sequencing revealed the selective enrichment of organohalide-respiring bacteria (OHRB), including Dehalococcoidaceae, which played a crucial role in cVOCs biotic dechlorination. Numerical ecological analyses indicated a sustained shift in microbial community structures post injection. Additionally, Fe 3+ /sulfur-reducing OHRB, including some strains of Geobacter, Sulfurospirillum, and Desulfitobacterium, emerged as major components of the total bacterial population. These microorganisms likely utilized both injected and native sulfur and iron species to form iron sulfides, potentially contributing to abiotic dechlorination. This microbially mediated process may explain the complete dechlorination of cVOCs with minimal vinyl chloride accumulation. This study demonstrates the long-term adaptation of microorganisms to the injected CMC-S-nZVI and its effectiveness in removing cVOCs through a combination of abiotic and biotic processes.
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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) | 0.001 | 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) | 0.000 | 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 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".