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Record W2804215957 · doi:10.2134/jeq2018.01.0054

Sodium Persulfate and Potassium Permanganate Inhibit Methanogens and Methanogenesis in Stored Liquid Dairy Manure

2018· article· en· W2804215957 on OpenAlexafffund
Jemaneh Habtewold, Robert J. Gordon, Paul Voroney, Vera Sokolov, Andrew VanderZaag, Claudia Wagner‐Riddle, Kari E. Dunfield

Bibliographic record

VenueJournal of Environmental Quality · 2018
Typearticle
Languageen
FieldEngineering
TopicAnaerobic Digestion and Biogas Production
Canadian institutionsAgriculture and Agri-Food CanadaWilfrid Laurier UniversityUniversity of Guelph
FundersUniversity of Guelph
KeywordsMethanogenChemistryManurePotassium permanganateMethanogenesisSlurrySodiumAnimal sciencePersulfateEnvironmental chemistryFood scienceAgronomyMethaneInorganic chemistryBiologyEnvironmental engineeringBiochemistryEnvironmental science

Abstract

fetched live from OpenAlex

Stored liquid dairy manure is a hotspot for methane (CH 4 ) emission, thus effective mitigation strategies are required. We assessed sodium persulfate (Na 2 S 2 O 8 ), potassium permanganate (KMnO 4 ), and sodium hypochlorite (NaOCl) for impacts on the abundance of microbial communities and CH 4 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 (H 2 SO 4 )‐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 CH 4 /CO 2 ratios were used as a proxy to determine CH 4 production. Unlike bacterial abundance, methanogen abundance and CH 4 /CO 2 ratios varied with treatments. Addition of 1 to 9 g L −1 slurry of Na 2 S 2 O 8 and KMnO 4 reduced methanogen abundance (up to ∼28%) and peak CH 4 /CO 2 ratios (up to 92‐fold). Except at the lowest rate, chemical combinations also reduced the abundance of methanogens (up to ∼17%) and CH 4 /CO 2 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 Na 2 S 2 O 8 and KMnO 4 may offer alternative options to reduce CH 4 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 CH 4 production were affected by Na 2 S 2 O 8 and KMnO 4 . Na 2 S 2 O 8 and KMnO 4 had similar effects on CH 4 production compared with acidification. Na 2 S 2 O 8 and KMnO 4 may provide options to mitigate CH 4 emissions from stored liquid dairy manure.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.595
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.239
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2018
Admission routes2
Has abstractyes

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