the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Comparison of two oxidation flow reactors for measuring aged aerosol from passenger car exhaust
Abstract. Oxidation flow reactors (OFRs) are a practical way to assess the secondary aerosol (SecA) mass formation potential of any gas mixture of interest in relatively short processing timescales. In this study, two OFRs were assembled in parallel and used to investigate the photochemical aging and formation of secondary aerosol from exhaust emissions of seven passenger cars. The potential aerosol mass OFR (PAM-OFR) and the Dekati OFR (DOFR) have differences in reactor volume, wall material, residence time and ultraviolet (UV) wavelengths, but the particle number and mass size distributions measured after them were comparable when averaged over the transient driving cycle. The average secondary particle mass emission factor (EF) for all 34 cycles was 22.90 mg km-1 for the PAM-OFR and 15.77 mg km-1 for the DOFR. The fuel and exhaust after-treatment technology affected the difference between the PAM-OFR and the DOFR EFs. With gasoline cars, fast bursts of SecA formation during cold start and highway driving were captured more clearly by the DOFR, which led to DOFR EFs exceeding PAM-OFR EFs. However, with modern diesel cars, the CNG car or hybrid cars that all produced low fresh PM emissions, the SecA mass EFs were higher from the PAM-OFR than from the DOFR. OH exposure did not cause the differences in emission factors between the OFRs, because the OH exposure range was small. Background SecA formation from the PAM-OFR was visible in the particle size distributions of the cleanest cars, which was corrected for in the EF calculations. On average, the PAM-OFR produced more background particle mass (9.10 μg m-3) than the DOFR (0.36 μg m-3).
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Status: open (until 25 Apr 2026)
- RC1: 'Comment on egusphere-2026-224', Anonymous Referee #1, 24 Mar 2026 reply
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Summary:
The authors present an informative comparison of the secondary organic aerosol produced after photochemical aging of various passenger cars in two different oxidation flow reactors (OFR). This work is important for better understanding the results and validity of data produced by OFR experiments and furthers our understanding of the aerosols generated by a variety of different types of passenger vehicles. The manuscript is well written, the topic relevant to the community, and the experimental methods are clearly described and well thought out. Some parts of the results could be further elaborated on and some small technical points could improve the manuscript. Therefore, I recommend this manuscript undergo minor revisions before the final publication, as described in the specific comments below.
Specific comments:
Pg. 11 Figure 5: Please include the x-axis title "Cycle Index" for clarity. Were measurement errors calculated for the EF shown in this figure? It would be useful to understand which measurements were within the measurement uncertainty and which ones represent significant differences in the EF.
Pg. 13 Lines 357 – 365: It would be interesting to see the temperature dependent results visualized. Would it be possible to plot these results?
Pg. 14 Lines 403 – 405: The authors note that sampling lines, OFR walls and tail pipe history can affect observed concentrations. It is clear how the authors came to this conclusion regarding the OFR walls given the data in Fig. 4 while the cars were parked. However, sampling line and tail pipe history would affect both OFRs used here. Do the authors have other data to support the claims regarding sampling line and tail pipe history?
Pg. 17 Lines 487 – 499: The authors note that too high NOx can consume all OH radicals and lead to an underestimation of secondary aerosols. Could this be mitigated by changing the OH radical concentration in scenarios with high NOx?
Technical corrections:
This manuscript uses a large number of abbreviations some of which are non-standard or may have different meanings in different fields. I frequently found myself scrolling back in the document to find definitions in order to fully understand the writing. Therefore, I would encourage the authors to reduce the use of non-standard abbreviations to improve readability. For example, SecA, DOFR, TSAR, ED, RTT, DR, CS, EAS