This study presents a comprehensive analysis of aerosol evolution in the Paris urban plume using innovative coordinated airborne and ground-based observations. The research addresses an important scientific question regarding how aerosol composition and optical properties evolve during 2-6 hours of atmospheric aging, with significant implications for improving aerosol parameterizations in models and remote sensing retrievals. The manuscript is generally well-written with rigorous methodology, but several aspects of the analysis and interpretation require strengthening to fully support the conclusions. I recommend minor revision before publication.

Specific Comments

1. Organic aerosol characterization needs strengthening: The manuscript would benefit from more detailed analysis of organic aerosol sources and oxidation states. While the study correctly identifies organic aerosol as the dominant PM1 component, the lack of source apportionment (e.g., PMF analysis) and oxidation state analysis (O:C ratios or f44/f43 ratios from mAMS or ToF-ACSM data) limits the mechanistic understanding of the observed changes. These analyses would better support the conclusions about secondary organic aerosol formation and its role in aerosol evolution.
2. Quantitative comparison of organic aerosol contributions: At line 393, when comparing with other aircraft studies showing organic aerosol dominance in urban plumes, provide specific percentage contributions of organic aerosol in-plume versus out-plume (background) conditions to facilitate direct comparison and intuitive understanding.
3. SSA wavelength dependence interpretation requires revision: At line 418, there appears to be confusion between AAE and SAE in the interpretation. More importantly, the attribution of SSA(450nm) < SSA(630nm) solely to BrC influence is problematic. Figure 4 shows this pattern occurs in only 3 of 6 flights (A032, A036, A033), while the other three flights (A027a, A031, A034) show the opposite pattern. The interpretation should consider that SSA wavelength dependence results from the combined effects of SAE (size-dependent scattering) and AAE (composition-dependent absorption). For example, when BC dominates (AAE≈1), SSA increases with wavelength if SAE > 1 (characteristic of small particles). The analysis should examine SAE and AAE variations together and provide flight-specific explanations considering particle size effects.
4. Particle size distribution interpretation needs stronger evidence: Section 3.2 attributes increased 80-200nm particles in-plume to secondary aerosol formation, but this attribution lacks strong support. The cited literature compares urban versus downwind suburban sites, which is not directly analogous to the in-plume versus out-plume comparison in this study. Since urban emissions naturally contain high concentrations of 80-200nm particles, the observed increase could reflect primary urban emissions. A more appropriate comparison would be with PRG urban site measurements, though instrument detection limits may constrain this approach.
5. Clarify particle versus gas-phase pollution discrepancies: At line 455, the statement that particle mass increases are less pronounced than gas-phase pollutant increases is puzzling given that Figure 2a shows substantial rBC and NO₂ enhancements (approximately doubling in-plume). This discrepancy warrants discussion of potential mechanisms such as deposition processes, dilution effects, or measurement artifacts, and an explanation of why rBC shows strong enhancement while other particle components do not.
6. Ensure consistent size ranges for volume-effective radius: At line 457, clarify whether the volume-effective radius calculation uses consistent size ranges for aircraft (80-1000 nm) and ground (30-1000 nm) measurements, and discuss the potential impact of any differences on comparability.
7. Refine Ox/ΔCO ratio analysis: At lines 474-477, specify whether Flight A027b (noon flight with potentially stronger photochemistry) was excluded from the Ox/ΔCO analysis, and compare in-plume versus out-plume Ox/ΔCO values to better characterize photochemical processing differences.
8. Validate complex refractive index values: The CRI real parts as low as 1.3 in Figure 8 are unexpectedly low given the chemical composition (~60% organic and 40% inorganic components with CRI=1.53). This suggests either methodological issues or exceptionally low organic aerosol CRI values that require explanation. Correlation with O:C ratios from AMS data would help validate these results and provide insights into organic aerosol aging.

This study reports on airborne measurements of aerosol properties and gases at various downwind distances from Paris and compares them to a ground site within the city.  The topic is well suited for this journal and is of scientific interest. Overall, the findings are that there are relatively minor changes in species concentrations with plume age, and also in comparison to the urban site, which makes the analysis and interpretation of the data more difficult (ie, testing if there are real differences).  A major issue is that the interpretation tends to assume a Lagrangian-type of experiment, which is not proven – specifically the comparisons with the ground based urban site. 

Although the data are self-consistent, (OA/dCO increases, BrC increases), all these changes are small. The authors use statistical test to decide if there is a difference or not, which is commendable, but it would also be good to include an uncertainty analysis to help with the interpretation. For example, error bars (sensitivity analysis) in Figure 10 added to the CRI (real and imaginary) for this data would be useful.  It would also support (or not) some of the conclusions, eg, that including plume changes are needed to correctly assess optical properties of aerosols.  Also an uncertainty analysis when comparing parameters from various measurement locations would be helpful, especially for the inferred optical properties, these could be fairly high.  Another weakness was specifying the particle size ranges covered for each aerosol measurement, which seemed to be handled rather haphazardly throughout. This includes inlets and instrument measurement size ranges. Maybe this could be added to Table S1.

Overall, these are difficult measurements, and the authors have done a reasonable job presenting them, although the findings are not striking, they are important.

Specific comments.

I would just note that calling the plumes heavy and light pollution could lead to some confusion.  Ie, the term light pollution has a specific meaning that differs from how it is used here.

Discuss limitations of one ground site being representative of the Paris metropolitan region emissions to which the downwind data are compared.  Ie, how do aircraft data closest to the city compare?

State why is AMS NO3- referred to as pNO3, while none of the other species use a similar type of acronym?  (Ie, since not classifying as ions, NO3 could be interpreted as the nitrate radical)?

Line 171, what is the implication of the 0.75 slope of volume from AMS vs number size distribution and density.  The slope and correlation is given but there is no interpretation. Does this main AMS mass may be systematically off by 25%? 

Give particle size ranges over which the SP2 and A2S2 can measure.

In equations 4 and 5 explicitly state where the absorption coefficients at 630 and 450 comes from – what instrument.  Does it come from the measured extinction minus the scattering coefficients.  I suspect there is significant uncertainty associated with the calculated absorption coefficients.

Give a possible range of calculated BrC absorption coefficient since it is determined by difference between measurements with associated uncertainties and depends on aerosol properties that can be variable (BC AAE=1 ). Also, the assumption is made that there is no BrC light absorption at 630 nm, which may not be true (see publications on tar BrC or dark BrC (d-BrC)). What are the implications of this assumption?

Discussion on volume increases between lines 450 and 455.  Specify what the diameter range is associated with the discussed volume increase.

Line 478 and on. Is it possible to make such a definite statement that because Org/dCO in the plume was higher than at the Paris ground site that it must be due to SOA formation (30%).  Same applies for other species discussed in a similar way. This is not a true Lagrangian experiment.

What is the effect of not considering background concentrations when normalizing by CO (in minus out of plume CO, ie y/dCO, where y is the variable of interest)? Normally one also subtracts the out of plume concentrations for the species in both the numerator and denominator (dy/dCO). In this case it is only done for the denominator.  A good way to do this is from the slope of the species of interest (y) vs CO. It removes the backgrounds (intercept) and shows how consistent the excess mixing ratio is. Eg, if the correlation is poor, it provides insight on if this number makes much sense if calculated only based on averages.

How was the AAE determined? Seems highly uncertain if just based on absorption measured at two different wavelengths.  Could this account for substantial scatter in Fig 9?  I suggest that a discussion is needed on how AAE varies with choice of wavelengths.

Line 574 and on.  Is there a plot that can show that AAE increased with plume age? 

Line 649 states the results show a clear evolution with downwind distance of the Paris plume.  Seems an overstatement without a full uncertainty analysis and possible limitations with how excess mixing ratios were determined. This applies to the complete final paragraph.

This manuscript investigates the evolution of aerosol composition, size distribution, and optical properties in the Paris urban plume using coordinated aircraft and ground-based measurements from the ACROSS campaign. The study compiles a comprehensive suite of measurements, providing a potentially valuable dataset for examining urban plume evolution. However, the current analysis has substantial methodological and interpretive limitations, particularly regarding the assumed Lagrangian framework, the treatment of statistical significance, and the interpretation of OA evolution. I therefore recommend the manuscript for publication following major revision.

Major Comments

1. The primary analysis relies on a Lagrangian assumption that PRG represents the fresh urban plume and that the same air masses are subsequently sampled by the aircraft. However, the trajectory analysis only shows that the sampled air masses passed over or near Greater Paris. It does not establish that the aircraft sampled the same air parcels measured at PRG. The ground site may be influenced by local emissions, while the aircraft may integrate emissions from the broader metropolitan area.
2. CO at PRG is obtained from an AIRPARIF site approximately 6 km away, while the background CO concentration is assumed to be identical to that derived from the corresponding flight. This inconsistency makes the comparison based on ΔCO normalization less convincing. In addition, ΔCO normalization accounts for dilution only when CO and the normalized species share the same emission sources. This assumption requires further justification.
3. Statistical significance needs to be interpreted with caution. The manuscript applies t-tests to aircraft and ground-based measurements that are temporally autocorrelated. Treating individual measurements as independent samples inflates the effective sample size and can produce artificially small p-values. A t-test is also not an appropriate primary criterion for identifying plume periods. In addition, statements that interpret p > 0.05 as evidence that two quantities are statistically similar are inappropriate. Failure to reject the null hypothesis does not demonstrate equivalence.
4. The interpretation of OA evolution relies mainly on bulk OA concentrations, OA fractions, and OA/ΔCO ratios. These metrics alone are insufficient to distinguish POA from SOA or to attribute downwind changes to SOA formation. Source apportionment of the AMS and ACSM mass spectra, such as positive matrix factorization, would provide more direct evidence.

Minor Comments

1. Line 165. Additional justification is needed for applying a constant CE = 0.5.
2. Line 269. The use of a constant factor of two to convert eBC to rBC requires additional justification, as this relationship is not universally applicable.
3. Line 290. Clarification is needed on whether the calculated inlet losses were applied to the measurements or only estimated.
4. Line 374. The division into light and heavy pollution using the median PM₁ concentration of 3 µg/m³ appears arbitrary and does not represent physically meaningful pollution regimes. It would be useful to assess whether the conclusions are sensitive to the choice of threshold.
5. Line 385. The discussion of northwest air masses during the southwest flight is confusing and should be clarified.
6. Figs. 1 and 2. Consider presenting the standard deviation in addition to the mean concentrations.
7. Line 415. BrC is inferred from AAE, not SAE.
8. Line 479. The increase in average OA fraction is relatively small (62.7% to 65.5% and 61.8% to 63.9%) and does not provide convincing evidence for SOA formation.
9. Fig. 10. A consistent color scheme throughout the manuscript (e.g., red for airborne observations and black for PRG measurements) would improve readability.

Technical Corrections

1. Line 127. The grammar in “Table S1 in the Supplementary” should be corrected.
2. Line 243. The grammar in “Ammonium nitrate and ammonium sulfate was used” should be corrected.
3. Lines 301. The text refers to Eqs. (3) and (4), but the displayed equations are numbered Eqs. (2) and (3). Please correct the cross-references. There also appears to be a typo in the exponent notation in Eq. (3).
4. Line 337. The grammar in “validity of the is identification approach” should be corrected.
5. Line 381. A period is missing.
6. The Supplement contains inconsistencies between section headings and table/figure captions that should be corrected.