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Record W1994234098 · doi:10.5194/acp-12-3405-2012

Dry deposition fluxes and deposition velocities of seven trace metal species at five sites in central Taiwan – a summary of surrogate surface measurements and a comparison with model estimations

2012· article· en· W1994234098 on OpenAlexaff
Leiming Zhang, Guor‐Cheng Fang, C. K. Liu, Yiliang Huang, Jen‐Chieh Huang, Chao-Yang Huang

Bibliographic record

VenueAtmospheric chemistry and physics · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsEnvironment and Climate Change Canada
FundersNational Science Council
KeywordsDeposition (geology)ChemistryFlux (metallurgy)MetalEnvironmental chemistryTrace metalAnimal scienceAnalytical Chemistry (journal)GeologyBiology

Abstract

fetched live from OpenAlex

Abstract. Daily air concentrations and dry deposition fluxes of seven metal species were monitored at five sites in central Taiwan for five or six days every month from September 2009 to August 2010. Annual average concentrations at the five sites were in the range of 2.8 to 3.6 ng m−3 for As, 25 to 82 ng m−3 for Mn, 1900 to 2800 ng m−3 for Fe, 69 to 109 ng m−3 for Zn, 18 to 33 ng m−3 for Cr, 60 to 110 ng m−3 for Cu, and 25 to 40 ng m−3 for Pb. Annual average dry deposition fluxes were on the order of 3, 20, 400, 50, 25, 50, and 50 μg m−2 day−1 for As, Mn, Fe, Zn, Cr, Cu, and Pb, respectively. Annual average dry deposition velocities (Vd) for the seven metal species ranged from 0.18 to 2.22 cm s−1 at these locations. Small seasonal and geographical variations, e.g. from a few percent to a factor of 2 for different species and/or at different locations, were found in the measured concentrations, fluxes, and Vds. The measured fluxes and air concentrations had moderate to good correlations for several of the species at several of the sites (e.g. Fe, Zn, and Mn at most of the sites), but had either weak or no correlations for the other species or at the other sites (e.g. As at Sites I and III, Zn and Cr at Site IV, and Cu at most of the sites). The latter cases were believed to have large uncertainties in the flux measurements using surrogate surfaces. Sensitivity tests were conducted for particle Vds using a size-segregated particle dry deposition model, assuming various combinations of three lognormal size distributions representing fine particles (PM2.5), coarse particles (PM2.5–10), and super-sized particles (PM10+), respectively. It was found that the measured dry deposition fluxes can be reproduced reasonably well using the size-segregated particle dry deposition model if the mass fractions of the metal species in PM2.5, PM2.5–10 and PM10+ were known. Significant correlations between the modeled and the measured daily fluxes were found for those cases that were believed to have small uncertainties in the flux measurements.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.033
GPT teacher head0.260
Teacher spread0.227 · 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 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

Citations38
Published2012
Admission routes1
Has abstractyes

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