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Record W2014666525 · doi:10.2134/jeq2005.0253

Utilization of Biosolids during the Phytoremediation of Hydrocarbon‐Contaminated Soil

2006· article· en· W2014666525 on OpenAlexafffund
Stephen J. Dickinson, P. Michael Rutherford

Bibliographic record

VenueJournal of Environmental Quality · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of Northern British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsBiosolidsPhytoremediationSewage sludgeSoil waterChemistryLoamEnvironmental chemistryAgronomyAmendmentSoil conditionerEnvironmental scienceSoil contaminationSewageEnvironmental engineeringSoil science

Abstract

fetched live from OpenAlex

Addition of anaerobically digested sewage sludge (biosolids) to soil may improve conditions for phytoremediation of petroleum hydrocarbons (PHCs) through improved soil chemical, biological, and physical properties. A 32-wk greenhouse study investigated three rates of biosolids addition (0, 13.34, and 26.68 g oven-dry biosolids kg(-1) oven-dry soil) and the presence or absence of smooth brome (Bromus inermis Leyss. cv. Carlton) plants on the removal of diesel (3.5 g kg(-1) oven-dry soil) in an industrial, sandy loam soil. Diesel PHCs were divided into two fractions based on equivalent normal straight-chain boiling point ranges (F2: nC10-nC16; F3: nC16-nC34). The addition of biosolids did not increase the extent of PHC degradation but did result in significantly greater first-order decay constants compared to unamended controls. Overall, the presence of plants did not increase the rate or extent of PHC degradation, relative to that observed in unamended, non-vegetated soils. Vegetation was, however, an important factor within the biosolids-amended soils as was observed by a greater extent of PHC degradation. Some of this decrease was attributed to plant-induced removal of biosolids components that were contributing to the F3 fraction. Overall, the low-amendment rate (13.34 g oven-dry biosolids kg(-1) oven-dry soil) was considered to be the most effective treatment because it produced the greatest overall PHC degradation rate (0.226 wk(-1) for total PHCs) and resulted in the greatest recovery of biosolids-derived N by smooth brome (26.6%).

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score0.469

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 studies0.0000.001
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 head0.223
Teacher spread0.214 · 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 designObservational
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

Citations10
Published2006
Admission routes2
Has abstractyes

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