Design and characterization of a new oxidation flow reactor for laboratory and long-term ambient studies
Bibliographic record
Abstract
Abstract. Oxidation flow reactors (OFRs) are frequently used to study the formation and evolution of secondary aerosol (SA) in the atmosphere and have become valuable tools for improving the accuracy of model simulations and for depicting and accelerating realistic atmospheric chemistry. Driven by rapid development of OFR techniques and the increasing appreciation of their wide application, we designed a new all-Teflon reactor, the Particle Formation Accelerator (PFA) OFR, and characterized it in the laboratory and with ambient air. A series of simulations and experiments were performed to characterize (1) flow profiles in the reactor using computational fluid dynamics (CFD) simulations, (2) the UV intensity distribution in the reactor and the influence of it and varying O3 concentration and relative humidity (RH) on the resulting equivalent OH exposure (OHexp), (3) transmission efficiencies for gases and particles, (4) residence time distributions (RTDs) for gases and particles using both computational simulations and experimental verification, (5) the production yield of secondary organic aerosol (SOA) from oxidation of α-pinene and m-xylene, (6) the effect of seed particles on resulting SA concentration, and (7) SA production from ambient air in Riverside, CA, US. The reactor response and characteristics are compared with those of a smog chamber (Caltech) and of other oxidation flow reactors: the Toronto Photo-Oxidation Tube (TPOT), the Caltech Photooxidation Flow Tube (CPOT), the TUT Secondary Aerosol Reactor (TSAR), quartz and aluminum versions of Potential Aerosol Mass reactors (PAMs), and the Environment and Climate Change Canada OFR (ECCC-OFR). Our studies show that (1) OHexp can be varied over a range comparable to that of other OFRs; (2) particle transmission efficiency is over 75 % in the size range from 50 to 200 nm, after minimizing static charge on the Teflon surfaces; (3) the penetration efficiencies of CO2 and SO2 are 0.90 ± 0.02 and 0.76 ± 0.04, respectively, the latter of which is comparable to estimates for LVOCs; (4) a near-laminar flow profile is expected based on CFD simulations and suggested by the RTD experiment results; (5) m-xylene SOA and α-pinene SOA yields were 0.22 and 0.37, respectively, at about 3 × 1011 molec. cm−3 s OH exposure; (6) the mass ratio of seed particles to precursor gas has a significant effect on the amount of SOA formed; and (7) during measurements of SA production when sampling ambient air in Riverside, the mass concentration of SA formed in the reactor was an average of 1.8 times that of the ambient aerosol at the same time.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".