From the journal Environmental Science: Atmospheres Peer review history

11-Feb-2022

Dear Dr Borbon:

Manuscript ID: EA-ART-11-2021-000093
TITLE: O3-NOy photochemistry in boundary layer polluted plumes: insights from the MEGAPOLI (Paris), ChArMEx/SAFMED (North West Mediterranean) and DACCIWA (South West Africa) aircraft campaigns

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Dr Claudia Mohr

Associate Editor, Environmental Science: Atmospheres

************

Reviewer 1

General comments:
This paper presents a study of ozone formation photochemistry in boundary layer plumes sampled during airborne measurements. The observational data are from aircraft campaigns in Paris (MEGAPOLI project, July 2009), North West Mediterranean (ChArMEx/SAFMED project, July 2013) and South West Africa (DACCIWA project, June-July 2016). The three selected regions are very contrasting in terms of geography and emissions and hence well serve the purpose of this paper. The authors obtained data representing boundary layer plumes by careful data selections based on the meteorological and chemical conditions. They calculated/estimated and compared the Leighton ratios (an indicator of photostationary steady-state, PSS), ROx mixing ratios, ozone production rates (PO3) and ozone production efficiency (OPE) values for the plumes over the three regions. The results provide an insight into the photochemistry and ozone production within the plumes and add new observation-based values of Leighton ratio, ROx, PO3, and OPE, which are within the corresponding ranges reported in the literature. The major novelty of the paper is the defining of a new metric PROx (the CO-adjusted production rate of oxidants) by changing the ratio ∆[O3]/∆[CO] used in the literature to ∆[O3+NO2]/∆[CO]. PROx values were estimated for six of the plumes. In comparison with the PO3 values, the authors found inconsistency between PROx and PO3 for the Paris plumes and discussed the causes.
This paper is scientifically sound and contains some original results based on reliable measurements. It is a good example of ozone formation studies using observational data from contrasting environments, which are needed for promoting our understanding of atmospheric chemistry related to the formation of ozone and other oxidants. The proposed new metric PROx could be of interest for other researchers in air pollution and photochemistry. The topic fits the scope of Environmental Science: Atmospheres (ESA). The paper is generally well written. I recommend publication of this paper in ESA after minor revision.

Major comments:
1) PROx is proposed as a new metric for integrated photochemical production of the whole plume. However, the actual calculations of this metric are not clearly described. The assumptions applied and limitations are not mentioned. PROx is defined as the ratio ∆[Ox]/∆[CO] as a function of the processing time, and ∆[Ox] and ∆[CO] are the differences between the mixing ratios of Ox and CO inside the plume and their background values outside the plume (section 3.2.6). Although pollution centers like urban areas emit larger quantities of CO and reactive ozone precursors, emissions of these species along the transport way of the plume are also possible and sometimes significant (particularly in the MAGAPOLI case). This may complicate the calculations and interpretation of PROx because the mixing ratios of Ox and CO inside and outside the plume depend not only on the photochemical reactions and dilutions but also on the emissions of CO and ozone precursors. Another complicated situation is when ozone is significantly removed by its sink on the way of transport, like the DACCIWA case.
2) I have some different opinions regarding the discussions on the inconsistency between PO3 and PROx for Paris (the last paragraph in section 4.4). I think the low PO3 value does not necessarily mean the absence of photochemical ozone production inside the plume. Ozone should be significantly produced inside the plume but most of the produced ozone is removed by its reaction with NO, which leads to the production and accumulation of NO2. On the other hand, the relatively large PROx may be largely due to the production and accumulation of NO2, which is not well accounted for in the PO3 calculation. The uncertainty on PO3 might be a cause of the inconsistency. What about that on PROx? It is stated that the uncertainty on PROx is lower than 20%. How did you obtain the estimation? Each of the ∆[Ox]/∆[CO] points has its uncertainty and the average values for different processing time have large uncertainties (Figure 13). Did you consider these uncertainties in the calculations of PROx? It is suggest to make strict assessment of the uncertainty on PROx. In addition, CO measurements should be included in the paper, as they are important for you to obtain the ∆[Ox]/∆[CO] values.

Minor comments:
1) Subsection 3.2.2 does not parallel other subsections in section 3.2. And the uncertainty calculation applies only to the PSS condition (Eq. 1). It is suggest to move to somewhere after Eq. 1 or to make it a subsection independent of section 3.2 by adding uncertainty estimations of other resultants, such as PROx.
2) Lines 12-13 on page 11: Please check J(NO2) values for correctness and consistency with those in Figure 6.
3) Line 2 from the bottom on page 14: equation (5) or equation (6)?
4) Line 17 from the bottom on page 15: equation (5) or equation (6)?
5) Line 11 from the bottom on page 15: equation (6) or equation (7)?
6) Many figures in supplementary material are not mentioned in the text.
7) NOy appears in the title but it was measured only during DACCIWA and is less analyzed and discussed in the paper. A change of the paper title is suggested.

Reviewer 2

This is a valuable paper, which gives new insights into ozone photochemistry in different locations. The inclusion of observations from sub-Saharan Africa is particularly valuable, given the sparsity of data from this part of the world. Please find further comments attached.

This text has been copied from the PDF response to reviewers and does not include any figures, images or special characters.

The authors would like to thank the reviewers for their valuable comments. We addressed each point.
Review 1:
Major comments:
1/ PROx is proposed as a new metric for integrated photochemical production of the whole plume.
However, the actual calculations of this metric are not clearly described. The assumptions applied and
limitations are not mentioned. PROx is defined as the ratio ∆[Ox]/∆[CO] as a function of the processing
time, and ∆[Ox] and ∆[CO] are the differences between the mixing ratios of Ox and CO inside the plume
and their background values outside the plume (section 3.2.6). Although pollution centers like urban areas
emit larger quantities of CO and reactive ozone precursors, emissions of these species along the transport
way of the plume are also possible and sometimes significant (particularly in the MEGAPOLI case). This
may complicate the calculations and interpretation of PROx because the mixing ratios of Ox and CO inside
and outside the plume depend not only on the photochemical reactions and dilutions but also on the
emissions of CO and ozone precursors. Another complicated situation is when ozone is significantly
removed by its sink on the way of transport, like the DACCIWA case.
The authors:
In the revised section 3.2.5 we added details about PROx , the way PROx is estimated and a discussion on
the hypothesis underneath PROx. We report here the sentences that have been incorporated from line 22
on page 10 :
[…] Here, a CO-normalized oxidant production rate or PROx is established in order to quantify the efficiency of
the photochemical production rate inside the plume […] The mean ratio [Ox]-to-[CO] is calculated for each
plume transect and plotted as a function of the processing time. PROx (in ppb[Ox] ppb[CO]
-1 h
-1
) is derived from the
slope of a piecewise linear regression fit between ∆[]
∆[]
in each transect and the processing time. PROx integrates
the temporal evolution of the net photochemical production of the plume […]
The source as well as sink terms like the emission of CO along the flight trajectory or ozone removal by
dry/wet deposition could shape the PROx. This is originally discussed in the PROx section regarding ozone
removal during the DACCIWA flights. We rather discuss here the effect of potential emissions of CO along
the flight tracks and how it may affect the [CO] term. In addition to its direct anthropogenic origin, CO
can be also emitted by natural sources as already described in the literature: a direct oceanic source (Tran et
al., 2013) and its photochemical production from the oxidation of biogenic VOC (Gros et al., 2002 ; Worden
at al., 2018).
The potential oceanic source can be neglected even during the SAFMED flight as it may not affect the
[CO] term, the marine source being included in the background CO.
The trajectories of the MEGAPOLI flights were designed in order to fly over the plume leaving from the
whole Ile de France region which corresponds to the majority of the anthropogenic emissions from the
urban areas surrounding Paris (see maps below). The legs used for the PROx calculation started 50 km away
from the Paris center whatever the direction was (see the red circle on the maps below). The anthropogenic
emissions from surrounding areas (see emission map from AIRPARIF emission inventory from 2018) are
almost one to two orders of magnitude lower than the one from the Paris urban area. We can therefore
assume that the potential emissions along the flight path might be negligible. Moreover the background
signal levels of CO outside the plume are clearly lower than the ones inside the plumes suggesting that the
emissions from the surrounding areas are negligible. Moreover the analysis of the mixing ratio distribution
did not reveal any sudden increase of CO during the flights or any variation in its background levels during
one single flight. Regarding its biogenic photochemical origin from BVOC oxidation, the homogeneity of
the background CO levels outside the plumes suggest that there is no specific biogenic emission signature
and, at worse, it is included in the background estimation. For DACCIWA, we cannot exclude that some
anthropogenic emissions of CO occur during the plume transport as well as ozone sink. Given those
limitation we added a subsection in the section describing the PROx calculation principles (§ 3.2.5) from
lines 3-17 on page 18.
Legend: Spatialized annual emissions of Greenhouse Effect Gases (left-hand side) and NOx (right-hand side) from
the Ile de France region. The flight trajectories of the French ATR-42 aircraft started beyond the red circle. The star
is the airport location. https://www.airparif.asso.fr/en/monitor-pollution/emissions - lest access April 2nd 2022.
I have some different opinions regarding the discussions on the inconsistency between PO3 and PROx for
Paris (the last paragraph in section 4.4). I think the low PO3 value does not necessarily mean the absence
of photochemical ozone production inside the plume. Ozone should be significantly produced inside the
plume but most of the produced ozone is removed by its reaction with NO, which leads to the production
and accumulation of NO2. On the other hand, the relatively large PROx may be largely due to the
production and accumulation of NO2, which is not well accounted for in the PO3 calculation. The
uncertainty on PO3 might be a cause of the inconsistency. What about that on PROx? It is stated that the
uncertainty on PROx is lower than 20%. How did you obtain the estimation? Each of the ∆[Ox]/∆[CO]
points has its uncertainty and the average values for different processing time have large uncertainties
(Figure 13). Did you consider these uncertainties in the calculations of PROx? It is suggested to make strict
assessment of the uncertainty on PROx. In addition, CO measurements should be included in the paper, as
they are important for you to obtain the ∆[Ox]/∆[CO] values.
The authors:
We address 3 points in our answer one on the uncertainties, the other on the PO3 and PROx principles and
a final one on the CO measurements.
In order to be consistent with PO3, we calculated the uncertainty on PROx. It is based on the error type
derived from the linear least square regression analysis. The uncertainties are reported on Figure 13. Except
for flight 25 (±100%), the uncertainty on the slopes lies within 22% - 30%. Those numbers have been
updated in the text of the manuscript (lines 9-10 on page 18). For flight 25, the r2
is also lower compared to
other flights ; this flight was performed under stagnant and hot continental conditions : signals inside the
plume did not significantly differ from the one outside the plume. One should note that the uncertainty on
PROx is lower than the one on PO3 and does not exceed 30% (Figure 13) except for flight 25.
The calculation of PO3 by 3 = 2
[2
] − 3
[][3
] takes into account the ozone production which
is modulated by its titration with NO while PROx takes both into account by incorporating the NO2
accumulation. PO3 calculation also implies that NO is at steady state. When the aircraft crosses the fresh air
masses with high NO, the steady state conditions might not be encountered and ozone is titrated by NO We
elaborate more on this questions in the last section given the point of view discussed here (pages 18 and
19).
[…] In PO3 calculation, NO is assumed to be at the steady state. PROx assumes that there is no additional emission
of CO or ozone removal along the flight path to be able to quantify oxidant production […]
The CO measurements are included in the paper (see description in Table 1 with other trace gases).
Minor comments:
1) Subsection 3.2.2 does not parallel other subsections in section 3.2. And the uncertainty calculation
applies only to the PSS condition (Eq. 1). It is suggest to move to somewhere after Eq. 1 or to
make it a subsection independent of section 3.2 by adding uncertainty estimations of other
resultants, such as PROx.
The authors : we removed the subsection 3.2.2 and put it at the end of the previous sub-section 3.2.1.
2) Lines 12-13 on page 11: Please check J(NO2) values for correctness and consistency with those in
Figure 6.
The authors : we thank the evaluator for this remark. Indeed, we checked and found some inconsistency
for the DACCIWA flights. We corrected the values.
3) Line 2 from the bottom on page 14: equation (5) or equation (6)?
The authors : it is equation 6.
4) Line 17 from the bottom on page 15: equation (5) or equation (6)?
The authors : it is equation 6.
5) Line 11 from the bottom on page 15: equation (6) or equation (7)?
The authors : it is equation 7.
6) Many figures in supplementary material are not mentioned in the text.
The authors we checked and mentioned the figure when needed.
7) NOy appears in the title but it was measured only during DACCIWA and is less analyzed and
discussed in the paper. A change of the paper title is suggested
The authors : we agree with the fact that NOy is less discussed than the other NO and NO2 observations.
Even if it is less discussed in the paper, NOy includes different oxidized species used in the paper. For
instance NOz is used in Figure 12 to estimate the Ozone Production Efficiency (OPE). Therefore, we
decided to keep it in inside the title
Review 2
Specific comments
Terminology is not always consistent: sometimes PROx is used and sometimes Δ[Ox]/Δ[CO]. After it has
been defined, sticking to PROx is would be preferable.
The authors: we have double-checked the terminology in section 3.4.5 and it is correct. We would like to
emphazise that Δ[Ox]/Δ[CO] is different from PROx and this is the reason why we also use Δ[Ox]/Δ[CO].
Indeed PROx corresponds to the least square regression slope of Δ[Ox]/Δ[CO] as a function of the
processing time and is expressed a ppbOx.ppbCO per unit of time.
The region of Côte d’Ivoire, Ghana, Togo and Benin covered during the DACCIWA campaign is referred
to in the text as South West Africa. This term is more often used to refer to Namibia; I would advise
“southern West Africa
The authors: we agree with the suggestion to be consistent with Knippertz et al. (BAMS, 2015). We have
replaced South West Africa by southern West Africa in the core of the text when needed.
Fig. 1: how representative are these countries of the regions in general? Italy and France show quite different
ethylene trends, which suggests that the broad regions mentioned may not be well-represented by a single
country
The authors: indeed Italy and France do not show exactly the same trend of ethylene emissions. However,
the purpose here is to provide an overall picture of the trends of the Southern Europe/Mediterranean
countries without any a priori and Italy (western Basin) and Turkey (eastern Basin) are one of those
countries. The objective is rather to highlight contrasting trends. However, we slightly modified the sentence
related to figure 1 (lines 31-32 on page 3) which did not reflect the observed trends. The new sentence is :
While there is a is a clear increase in anthropogenic emissions in SWA, the trends in Western Europe and in the Mediterranean
are more contrasting depending on the species and on the country. On average a decreasing trend is observed.
p.6, Figs. 4, 5: The description and figures related to the choice of flights used in the analysis for the
SAFMED campaign are unclear. I do not understand why flight 51, which is not used in later analysis, has
been chosen to represent SAFMED in Fig. 4 instead of flights 46/47. In Fig. 5, where 46/47 are shown,
the NOx and O3 data are omitted, which means the reader cannot see the location of the plume. If the wind
is coming from the west, as indicated, where does the plume for this flight originate? It would be helpful to
include more clarification in both the text and figures.
The authors: figure 4 reports the time series of NOx for the “plume-like” flights like the one in the southern
sector of Genoa. Indeed any detectable changes in NOx concentrations are used as a plume criteria. This is
the reason why we report this flight as a first approach. However the increase of NOx does not match with
the expected location of the urban plume as compared to Paris (from line 6 on page 7). Moreover the
analysis of the wind confirms that this flight is not downwind the Genoa urban plume. This is the reason
why we excluded this flight for further investigation and selected flight 46 and 47 to capture the plumes
from Corsica Island. We added the ozone data for more clarity in Figure 5 as suggested. Such explanation
is provided from lines 9 on page 7.
p.11, Fig. 3: Humidity for the MEGAPOLI campaign is reported in g/kg in Fig. 3, while the other two
campaigns’ relative humidity is reported in %. In the text on p. 11, relative humidity in % is also reported
for the MEGAPOLI campaign. This change in unit is unexplained and makes it more difficult to compare
the different campaigns. Using % in all cases would be best, if this is possible
The authors: we changed the absolute humidity for MEGAPOLI in relative humidity in %. See figure 3.
p.11 paragraph 4: The values for J(NO2) in the text do not agree with those shown in Fig. 6. (From the
figure, it looks like the range is more like ~4x10-3 to ~9x10-3.)
The authors : we changed the text
p.13 paragraph 3: it is stated here that positive values for the Leighton ratio during DACCIWA was primarily
a result of frequent and intense rapid changes to J(NO2) and various compound mixing ratios. Later, on
p.14, it is stated that positive deviations suggest the influence of biogenic VOCs. This comes across as
contradictory. If both are possible reasons for the high Leighton ratios during DACCIWA, they should
both be mentioned here.
The authors : on page 13, the paragraph focuses on statistics and the potential linl between positive
deviations and rapid changes in the Leigthon ratio terms. This the reason why we do not discuss any other
causes.
It would be valuable to highlight the link between biogenic VOCs influencing the Leighton ratio during
DACCIWA, and the high Leighton ratio in Brazil, which also has a lot of biogenic VOCinfluence
The authors: it is a very good suggestion to put in mirror the DACCIWA and Brazil results.
p.14 paragraph 3: It would be interesting to see the comparison of estimated ozone mixing ratios and
observations in a supplementary plot.
The authors: we calculated the ratio between predicted ozone and observed ozone. The ratios fluctuated
around unity at ±40%. An example is given for MEGAPOLI here. The modification is on line 26 on page
14.
 Fig. 10: The x-axis on the bottom-right plot is mislabelled.
The authors: we corrected the label.
 p.15 second paragraph: I found this paragraph difficult to understand. I would recommend thinking again
about the key message, and then re-writing to ensure it is completely clear.
The authors: we tried to simplify the concluding message even if we are not completely sure about the
reviewer’s expectations.
 p.15, paragraph 5: Should this be equation 7, not 6?
The authors : we change equation 6 b equation 7
 p.15, paragraph 5: In the previous section, the authors convincingly show that [ROx] is likely to contribute
significantly towards ozone production outside plumes in Paris, and both in and outside in SWA. If I have
understood this correctly, the formula used to establish PO3 does not include a term for [ROx] production,
so it is likely to be invalid in a number of cases explored here. The PO3 equation could be updated to include
a term for [ROx] production.
The authors : the formula used for PO3 implicitly includes a ROx (XO2)term as described in details in
Frost et al. during the ROSE campaign (1998) and by assuming NO is at steady state. The latter assumption
might explain why the use of PO3 formula might not be valid inside the plume.
 p.15 last paragraph: three American cities are listed but only PO3 values for two.
The authors: we added a third range.
 Several of the conclusions about the plume measured during the SAFMED campaign rest on observations
from a single flight, and during DACCIWA from just three. While this kind of limited dataset is, of course,
always a potential danger during this kind of field campaign, it is important to be careful about how
confidently some conclusions can be stated based on a limited dataset.
The authors: we agree with this remark and modulate the conclusions. However, while limited in number
the target flights have been selected because they can be considered as polluted plume flights in the boundary
layer.
 p.17: PROx, PO3 and, to some extent, OPE are compared. I would have liked to see much more depth
in this evaluation, considering the pros and cons for each approach, and concluding which is best under
which circumstances. For example Zhang et al. (2014, ACP, 10.5194/acp-14- 2267-2014) state that using
CO as a passive tracer could be invalid in a situation with elevated oxidants. Such criticisms are not explored
here, and the use of CO as a tracer is not carefully justified
The authors : we would like to go back to Zhang et al.’s study. They are studying intercontinental transport
from North America outflow with a typical transport time of 6 to 7 days. In our case, the transport time
does not exceed 10 hours. We calculated the residence time of CO (kOH = 1.44 10-13 cm3
.molec-1
.s-1
) for an
OH concentrations of 107 molec. cm-3 which is an upper limit. We find a residence time of 8 days which is
much higher than the 8-hour of processing time in the plumes of interest. There is no risk of CO lost given
the time scale of transport in our study. We added a comment in that sense in the text (lines 30 to 32 on
page 10. Following the comments from Reviewer 1, it is part of an in-depth discussion on the advantages
and limitations of the different metrics. In particular we agree to diagnose ozone enhancement by verifying
the assumption of negligible CO loss or CO emissions :
Here, the processing time does not exceed 10 hours. The residence time of CO (kOH = 1.44 10-13 cm3
.molec-1
.s-1
)
for an OH concentrations of 107 molec. cm-3
( upper limit) roughly equal 8 days which is much higher than the
average processing time. The loss of CO can be neglected.

16-Apr-2022

Dear Dr Borbon:

Manuscript ID: EA-ART-11-2021-000093.R1
TITLE: O3-NOy photochemistry in boundary layer polluted plumes: insights from the MEGAPOLI (Paris), ChArMEx/SAFMED (North West Mediterranean) and DACCIWA (South West Africa) aircraft campaigns

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Dr Claudia Mohr

Associate Editor, Environmental Science: Atmospheres

Reviewer 1

I think the authors have satisfactorily addressed my concerns and those of the other reviewer and removed the technical problems found in previous review. The revised manuscript reads well for me. I recommend publication of this paper in Environmental Science: Atmospheres.