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Record W4392959259 · doi:10.21203/rs.3.rs-4022532/v1

Temporal-Spatial Characteristics of Volatile Organic Compounds (VOCs) near Petrochemical Industrial Complex using PTR-ToF-MS

2024· preprint· en· W4392959259 on OpenAlexaff
Jong Bum Kim, Jeongho Kim, Kyung Hwan Kim, Kyucheol Hwang, Sechan Park, Sujin Noh, Seonyeop Lee, Jooyeon Lee, Duckshin Park

Bibliographic record

VenueResearch Square · 2024
Typepreprint
Languageen
FieldEnvironmental Science
TopicWater Quality Monitoring and Analysis
Canadian institutionsInstitute of Particle Physics
Fundersnot available
KeywordsPetrochemicalVolatile organic compoundEnvironmental chemistryEnvironmental scienceChemistryOrganic chemistryEnvironmental engineering

Abstract

fetched live from OpenAlex

Abstract Petrochemical complexes cause local air pollution and deteriorate the health of local residents by emitting a variety of volatile organic compounds (VOCs). This study used a real-time analysis system to check the spatiotemporal distribution of pollutants discharged from petrochemical complexes. The proton transfer reaction time of a flight mass spectrometer (PTR-ToF-MS) was used as the measurement system. We performed measurements from July 21 to 26, 2021, mobile observations from July 21 to 22, 2021 and fixed observations from July 23 to 26, 2021. Meteorological analysis indicated that the prevailing wind direction was northwesterly, and pollutants discharged from industrial complexes in upwind regions have a high impact on villages in downwind regions. Mobile observation confirmed high concentrations in the section with the village hall, raw petroleum storage, landfill, and petrochemical production process. Methanol and acetone were in high concentrations at all times, and the concentrations of acetaldehyde, acetone, acetic acid, methylethyl ketone, and toluene increased once the production process started. The concentrations of benzene, known carcinogens, were particularly high, at times exceeding the acceptable threshold, indicating the need for improvement measures in the future.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
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 score0.475
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.163
GPT teacher head0.386
Teacher spread0.223 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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