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Record W4390727077 · doi:10.1139/er-2023-0092

A review on the analytical methods, chemical structures, distribution characteristics, sources, and biogeochemical processes of dissolved black carbon

2024· review· en· W4390727077 on OpenAlexvenueno aff
Changlin Zhan, Aiai Shu, Yongming Han, Junji Cao, Xianli Liu

Bibliographic record

VenueEnvironmental Reviews · 2024
Typereview
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsnot available
FundersState Key Laboratory of Loess and Quaternary GeologyNatural Science Foundation of Hubei ProvinceNational Natural Science Foundation of China
KeywordsBiogeochemical cycledBcEnvironmental scienceCarbon cycleEnvironmental chemistryDissolved organic carbonCarbon fibersCarbon blackBiomass (ecology)Earth scienceChemistryMaterials scienceEcologyEcosystemGeologyBiology

Abstract

fetched live from OpenAlex

Incomplete combustion of biomass and fossil fuels yields a variety of chemically distinct pyrolysis residues collectively referred to as black carbon (BC). Among these residues, dissolved black carbon (DBC) constitutes the water-soluble fraction, making it a significant component of the global dissolved organic carbon (DOC) pool. Consequently, it exerts an impact on the aquatic carbon cycle and global climate change. Owing to its unique molecular structure, DBC exhibits reduced reactivity in aquatic environments, thereby influencing the toxicity and environmental geochemical behavior of organic pollutants and heavy metals. While recent years have seen a surge in studies on DBC, yielding valuable insights, significant knowledge gaps persist regarding the fate and cycling of DBC. This review consolidates the advancements in analytical and determination methods for DBC and offers a critical assessment of the advantages and limitations associated with various analytical techniques. Furthermore, it comprehensively surveys our current understanding of DBC, encompassing its molecular composition, spatial distribution, sources, and biogeochemical processes. The review also underscores prevailing challenges related to quantitative and qualitative methods and underscores research gaps concerning the physio-chemical transformation of DBC. The overarching aim is to advance our comprehension of the biogeochemical cycle of DBC.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.965
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.034
GPT teacher head0.291
Teacher spread0.257 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations7
Published2024
Admission routes1
Has abstractyes

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