Sodium Persulfate and Potassium Permanganate Inhibit Methanogens and Methanogenesis in Stored Liquid Dairy Manure
Bibliographic record
Abstract
Stored liquid dairy manure is a hotspot for methane (CH4) emission, thus effective mitigation strategies are required. We assessed sodium persulfate (Na2S2O8), potassium permanganate (KMnO4), and sodium hypochlorite (NaOCl) for impacts on the abundance of microbial communities and CH4 production in liquid dairy manure. Liquid dairy manure treated with different rates (1, 3, 6, and 9 g or mL L−1 slurry) of these chemicals or their combinations were incubated under anoxic conditions at 22.5 ± 1.3°C for 120 d. Untreated and sodium 2‐bromoethanesulfonate (BES)‐treated manures were included as negative and positive controls, respectively, whereas sulfuric acid (H2SO4)‐treated manure was used as a reference. Quantitative real‐time polymerase chain reaction was used to quantify the abundances of bacteria and methanogens on Days 0, 60, and 120. Headspace CH4/CO2 ratios were used as a proxy to determine CH4 production. Unlike bacterial abundance, methanogen abundance and CH4/CO2 ratios varied with treatments. Addition of 1 to 9 g L−1 slurry of Na2S2O8 and KMnO4 reduced methanogen abundance (up to ∼28%) and peak CH4/CO2 ratios (up to 92‐fold). Except at the lowest rate, chemical combinations also reduced the abundance of methanogens (up to ∼17%) and CH4/CO2 ratios (up to ninefold), although no impacts were observed when 3% NaOCl was used alone. With slurry acidification, the ratios reduced up to twofold, whereas methanogen abundance was unaffected. Results suggest that Na2S2O8 and KMnO4 may offer alternative options to reduce CH4 emission from stored liquid dairy manure, but this warrants further assessment at larger scales for environmental impacts and characteristics of the treated manure. Core Ideas Chemical oxidants were assessed for potential effects on methanogens and methane production. The abundance of methanogens and CH4 production were affected by Na2S2O8 and KMnO4. Na2S2O8 and KMnO4 had similar effects on CH4 production compared with acidification. Na2S2O8 and KMnO4 may provide options to mitigate CH4 emissions from stored liquid dairy manure.
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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 | 0.000 |
| 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 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".