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Record W4247546189 · doi:10.5194/acpd-14-23415-2014

Prediction of gas/particle partitioning of polybrominated diphenyl ethers (PBDEs) in global air: a theoretical study

2014· preprint· en· W4247546189 on OpenAlexfundno aff
Y.-F. Li, Wan-Li Ma, Mengmeng Yang

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsnot available
FundersFundamental Research Funds for the Central UniversitiesNational Natural Science Foundation of ChinaNew York State Department of HealthNew York State Department of Health - Wadsworth CenterMinistry of EnvironmentTrent University
KeywordsNon-equilibrium thermodynamicsPartition coefficientPolybrominated diphenyl ethersThermodynamic equilibriumThermodynamicsRange (aeronautics)Partition (number theory)Particle (ecology)ChemistryPhysicsMathematicsMaterials scienceEcologyChromatographyPollutantCombinatoricsOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract. Gas/particle (G / P) partitioning for most semivolatile organic compounds (SVOCs) is an important process that primarily governs their atmospheric fate, long-range atmospheric transport potential, and their routs to enter human body. All previous studies on this issue have been hypothetically derived from equilibrium conditions, the results of which do not predict results from monitoring studies well in most cases. In this study, a steady-state model instead of an equilibrium-state model for the investigation of the G / P partitioning behavior for polybrominated diphenyl ethers (PBDEs) was established, and an equation for calculating the partition coefficients under steady state (KPS) for PBDE congeners (log KPS = log KPE + logα) was developed, in which an equilibrium term (log KPE = log KOA + logfOM −11.91, where fOM is organic matter content of the particles) and a nonequilibrium term (logα, mainly caused by dry and wet depositions of particles), both being functions of log KOA (octanol-air partition coefficient), are included, and the equilibrium is a special case of steady state when the nonequilibrium term equals to zero. A criterion to classify the equilibrium and nonequilibrium status for PBDEs was also established using two threshold values of log KOA, log KOA1 and log KOA2, which divide the range of log KOA into 3 domains: equilibrium, nonequilibrium, and maximum partition domains; and accordingly, two threshold values of temperature t, tTH1 when log KOA = log KOA1 and tTH2 when log KOA = log KOA2, were identified, which divide the range of temperature also into the same 3 domains for each BDE congener. We predicted the existence of the maximum partition domain (the values of log KPS reach a maximum constant of −1.53) that every PBDE congener can reach when log KOA ≥ log KOA2, or t ≤ tTH2. The novel equation developed in this study was applied to predict the G / P partition coefficients of PBDEs for the published monitoring data worldwide, including Asia, Europe, North America, and the Arctic, and the results matched well with all the monitoring data, except those obtained at e-waste sites due to the unpredictable PBDE emissions at these sites. This study provided evidence that, the new developed steady-state-based equation is superior to the equilibrium-state-based equation that has been used in describing the G / P partitioning behavior in decades. We suggest that, the investigation on G / P partitioning behavior for PBDEs should be based on steady state, not equilibrium state, and equilibrium is just a special case of steady state when nonequilibrium factors can be ignored. We also believe that our new equation provides a useful tool for environmental scientists in both monitoring and modeling research on G / P partitioning for PBDEs and can be extended to predict G / P partitioning behavior for other SVOCs as well.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.254
Teacher spread0.242 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2014
Admission routes1
Has abstractyes

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