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Record W2933059609 · doi:10.5194/acp-19-9715-2019

Secondary organic aerosol formation from <i>α</i> -pinene, alkanes, and oil-sands-related precursors in a new oxidation flow reactor

2019· article· en· W2933059609 on OpenAlexafffundabout
Kun Li, John Liggio, Patrick Lee, Chong Han, Qifan Liu, Shao‐Meng Li

Bibliographic record

VenueAtmospheric chemistry and physics · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsEnvironment and Climate Change Canada
FundersCanada's Oil Sands Innovation AllianceEnvironment and Climate Change Canada
KeywordsOil sandsChemistryTailingsNaphthaEnvironmental chemistryAerosolPineneChemical engineeringOrganic chemistryAsphaltCatalysisPhysical chemistryMaterials science

Abstract

fetched live from OpenAlex

Oil-sands (OS) operations in Alberta, Canada, are a large source of secondary organic aerosol (SOA). However, the SOA formation process from OS-related precursors remains poorly understood. In this work, a newly developed oxidation flow reactor (OFR), the Environment and Climate Change Canada OFR (ECCC-OFR), was characterized and used to study the yields and composition of SOA formed from OH oxidation of α -pinene, selected alkanes, and the vapors evolved from five OS-related samples (OS ore, naphtha, tailings pond water, bitumen, and dilbit). The derived SOA yields from α -pinene and selected alkanes using the ECCC-OFR were in good agreement with those of traditional smog chamber experiments but significantly higher than those of other OFR studies under similar conditions. The results also suggest that gas-phase reactions leading to fragmentation (i.e., C–C bond cleavage) have a relatively small impact on the SOA yields in the ECCC-OFR at high photochemical ages, in contrast to other previously reported OFR results. Translating the impact of fragmentation reactions in the ECCC-OFR to ambient atmospheric conditions reduces its impact on SOA formation even further. These results highlight the importance of careful evaluation of OFR data, particularly when using such data to provide empirical factors for the fragmentation process in models. Application of the ECCC-OFR to OS-related precursor mixtures demonstrated that the SOA yields from OS ore and bitumen vapors (maximum of ∼0.6–0.7) are significantly higher than those from the vapors from solvent use (naphtha), effluent from OS processing (tailings pond water), and from the solvent diluted bitumen (dilbit; maximum of ∼0.2–0.3), likely due to the volatility of each precursor mixture. A comparison of the yields and elemental ratios (H∕C and O∕C) of the SOA from the OS-related precursors to those of linear and cyclic alkane precursors of similar carbon numbers suggests that cyclic alkanes play an important role in the SOA formation in the OS. The analysis further indicates that the majority of the SOA formed downwind of OS facilities is derived from open-pit mining operations (i.e., OS ore evaporative emissions) rather than from higher-volatility precursors from solvent use during processing and/or tailings management. The current results have implications for improving the regional modeling of SOA from OS sources, for the potential mitigation of OS precursor emissions responsible for observed SOA downwind of OS operations, and for the understanding of petrochemical- and alkane-derived SOA in general.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.004
GPT teacher head0.166
Teacher spread0.162 · 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 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

Citations65
Published2019
Admission routes3
Has abstractyes

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