Re-review of Donnou, Akpo, Ossohou, et al: Long-term measurements of ozone concentrations in semi-natural African ecosystems
SUMMARY AND RECOMMENDATIONS
The authors have responded very well to this Reviewer’s comments. Below are a few minor items.
In general, with a more focused paper, the messages about (1) climatology for INDAAF data and (2) more important, trends based on the data, come through clearly. The result is a very important TOAR II paper – maybe the only one – about African ozone trends. I recommend this be highlighted in a revised title: Long-term measurements of surface ozone and trends in semi-natural ecosystems in sub-Saharan African ecosystems.” The latter change is recommended because the paper does not include north African data from nations along the Mediterranean.
The most significant point the authors make about the trends is that they vary by site and season, as other TOAR II and pre-TOAR II studies have found. This needs to be emphasized. The Reviewer took the liberty of suggesting options for re-writing the manuscript “Abstract” and “Conclusion” so that the implications for TOAR II are clear and strong.
MINOR COMMENTS/CORRECTIONS/SUGGESTIONS
Line 138 – Better form to say low surface ozone… “recorded at many sites…”
Line 142 – Do you mean “ Lee et al. (2021) used models and measurements to estimate that 24% of boundary-layer ozone over Africa is estimated from biomass burning?” And what does that mean “over Africa” – the entire continent? Which regions? Important to clarify whether papers like Lee et al are using models or actual data
Lines 154-158. An awkward sentence – the meaning is not clear. Do you mean “Changing isoprene emissions, the temperature sensitivity of NOx and O3 chemistry (Brown et al., 2022) as well as meteorological changes have all been implicated in the seasonality and spatial patterns of ozone trends in the tropics (Stauffer et al., 2024)” ?
Line 219 - use a monthly…
Line 412 – In the dry savanna (insert ‘the’)
Line 609 – should read “during which” not during “what”
Line 612 – can delete “was evaluated and”
Line 640 – “densify” not a good word. Start sentence with Additional efforts must therefore be made through programs to enhance the density of monitoring networks…
Lines 835 to 840 – These sentences are confusing. In general you are using different criteria on uncertainties- (Mann-Kendall) and p-values. That is fine. Figures 14 and 15 provide excellent summaries of the results! In both cases it is seen that only 3-4 sites have annual trends with low confidence (p value >0.2). Figure 14 is very convincing that losses occur at a number of ecosystem types. Recommend that you revise text with less reference to uncertainty – the reader can see that in the Figures and also in a Table – recommend in the next paragraph that you add a Table.
The discussion in Section 3.1 would be easier to follow if you make a Table with the 4 columns: station name // trend in ppbv/decade // p value // addl comment on confidence level/ comment on related VOC or other trend. Line 837 – no need to say “there is very little chance … will occur.”
Line 856 – Start a new paragraph with “The absence…”
Lines 858-869. The Wang et al. (2022) is mostly a modeling study with satellite results; that is not a good comparison point for your observational study. Recommend you delete it in this part of the paper. Comparisons made with Gaudel et al (2020) are somewhat relevant and your points about the airport stations being more polluted and close to sources are excellent interpretations. Note, however, at Nairobi (Thompson et al., 2021) the ozonesonde changes are almost negligible, so even in urban areas trends can be modest.
You should add a new TOAR II paper in press: Gaudel et al. (2024). It will be published very soon and is a successor to the Gaudel et al. (2020). The new paper uses a lot of IAGOS aircraft data to derive trends ~1995-2019. However, the Supplemental Material in the paper (look at egusphere-2023-3095) reveals a large “jump” or discontinuity over IAGOS stations not only in Africa but over South America between 1994-1997. That jump is generally NOT seen in African or South American ozonesonde records (Witte et al., 2017; 2018) although there are only 3 central and South American stations with 20 year trends. Trends after 2000 (a paper in preparation by Van Malderen et al. (for TOAR II on TOAR II /HEGIFTOM ground based data: 2000-2022 – tropospheric ozone from spectrometers as well as sonde and aircraft profiles), also show quite modest trends. In summary, one can assume that Gaudel et al. (2020; 2024) report overestimates of African trends. Gaudel et al. (2024) also contains NEW OMI/MLS satellite data (newer than Hou et al.) that cover 2005-2019/2020. The new data have relatively small trends over Africa, an excellent reference for your paper.
Line 894 - Start the sentence with “The tests reveal…”
Lines 924 – Remember to use months not “spring” or “summer” for Irene because the seasons are opposite months in the southern hemisphere.
Suggested Text Changes in the Conclusion-
Line 961 – “In the semi-arid”
Starting at Line 972-
re. At 95% confidence intervals, Annual and seasonal trends (based on Mann-Kendall treatment, and low p-values) indicate that the Katibougou site in Mali and the Banizoumbou site in Niger experience a significant decrease in O3 concentrations, around -2.43 ppb/decade and -0.8 ppb decade, respectively, with a high certainty over the period 2000 to 2020. These likely results from downward trends of NO2 trends observed at Katibougou and reduced BVOC emissions at Banizoumbou. In contrast, a significant upward trend is reported at Zoetele (0.7 ppb decade) in Cameroon and Skukuza (3.4 ppb decade) in South Africa. These trends are attributed to the increase in BVOCs in Zoetele and increases in anthropogenic and biogenic [do you mean NOx, BVOC or both111??- clarify] emissions that affect Skukuza.
This study describes O3 levels in representative African biomes, as well as related photochemical and meteorological regimes related to seasonal concentrations and the derived trends. The results on regional trends variability and seasonal variations are consistent with published studies of African ozone data although in most cases, the INDAAF measurements are more rural than data taken at urban monitoring sites, including airports. The importance of developing, and maintaining long-term observations like the INDAAF project, with regular calibration and standards, cannot be overstated. In particular, for the INDAAF mostly agricultural locations, the data can be used to assess the impact of O3 dry deposition fluxes on African crops and the potential crop yield losses because of O3 toxicity to plants. Studies of ozone changes during the growing season can lead to action plans for achieving better food security. The ozone data provide invaluable constraints for models of chemical and climate processes in the atmosphere. With INDAAF data and improved models, there will be more confidence in future predictions of African air quality and the exposure of agriculture and the regional population to surface ozone. |