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Record W4401893718 · doi:10.3389/fenvs.2024.1453306

Characterization of carbon dioxide emissions from late stage windrow composting

2024· article· en· W4401893718 on OpenAlexafffund
Travis Pennell, Louis‐Pierre Comeau, Kyle MacKinley, Sheldon Hann, Brandon Heung, Bob Kiely

Bibliographic record

VenueFrontiers in Environmental Science · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicComposting and Vermicomposting Techniques
Canadian institutionsDalhousie UniversityAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsCarbon dioxideEnvironmental scienceStage (stratigraphy)Greenhouse gasWaste managementEnvironmental chemistryChemistryEngineeringEcologyGeology

Abstract

fetched live from OpenAlex

As organic waste is converted to usable amendments via composting, there are large CO 2 emissions associated with the decomposition of organic matter via microorganisms. While the active composting phase produces the largest emissions over a short duration, compost can often be stored during and after the maturation phase for much longer periods of time, increasing cumulative emissions. As such, the objectives of this study were to examine the spatial and temporal variability associated with in situ emissions sampling while identifying the environmental and chemical controls on emissions in windrow composting facilities during and after the maturation phase. A total of 665 flux measurements were taken from four windrows representing different ages and compositions between June and November 2020. Factorial analysis of covariance (ANOVA) was used to determine the variability between sampling locations, while multiple linear regression was used to identify those parameters which had the most influence on CO 2 flux. Emissions showed significant variability over time that were attributed to ambient temperatures. During the summer, each windrow reached peak emissions between 5.0 and 32.3 g CO 2 m-2 hr-1. As temperatures cooled, the windrows saw a 62%–86% decline in emissions, generally falling below 2 g CO 2 m-2 hr-1. Significant differences occurred between the top-most sampling location and all others on the windrow, emitting between 33%–100% more CO 2 . The environmental controls of surface temperature, moisture content, and internal temperature showed the highest influence on emissions (R2 = 0.62). Chemical properties including organic nitrogen, carbon, pH, magnesium, and nitrate also showed significant influence (R2 = 0.43). This research has shown that environmental factors including temperature and moisture show the strongest influence over emission rates in mature compost. A significant negative effect of organic nitrogen on CO 2 flux was found, indicating that increased presence of organic nitrogen would aid in the retention of carbon after the maturation phase, acting to lower total emissions.

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)0.000
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 score0.498
Threshold uncertainty score0.218

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.009
GPT teacher head0.203
Teacher spread0.194 · 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

Citations5
Published2024
Admission routes2
Has abstractyes

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