Impact of Ragweed Pollen Daily Release Intensity on Long-Range Transport in Western Europe

Round 1

Reviewer 1 Report

Impact of ragweed pollen daily release intensity on long-range transport in western Europe

General comments

Interesting study for a new proposal to be used in dispersive models, very promising for pollen forecasting. Although the results are very good for phenological metrics and correlation, the results are of the predictive capability are modest for pollen intensity. The authors should discuss more in this sense, and explain the improvements to address this aspect in future works. While the operational predictive capability of the models and methodology is good, the conceptual background for the aerobiology of ragweed should be profoundly improved. Also, some relevant literature should be updated. Some points are not appropriate for an aerobiological study, for example the methodological explanation about the aerobiological procedure or the pollen season definition criterion. After addressing these points, the work could be considered for publication since the scientific interest for the readers of this journal.

Specific comments

1. Abstract: You may include a couple of lines at the beginning of the abstract defining the context of this work.
2. Abstract: The aims of the work should be clear. What are the objectives? Only to evaluate the meteorological conditions, or also to forecast the daily pollen concentrations?
3. Abstract (line 1): Better "...the most favourable meteorological conditions to...".
4. Abstract (lines 8-9): In order to achieve a more informative abstract, the authors may include results about the validation of the models and the predictive capability.
5. Introduction (line 12): The first time that the name of the species appears it should include the name of the authority of the taxonomic classification: "Ambrosia artemisiifolia L.".
6. Introduction (lines 14-17): Forecasting models of ragweed have been widely developed and only few examples are exposed here. Please, include other more recent examples.
7. Introduction (lines 20-22): I think you missed important works in this regard (Lake et al. 2017; Lugonja et al. 2019; Schaffner et al. 2020).

Lake, I. R., Jones, N. R., Agnew, M., Goodess, C. M., Giorgi, F., Hamaoui-Laguel, L., Semenov, M. A., Solomon, F., Storkey, J., Vautard, R., & Epstein, M. M. (2017). Climate Change and Future Pollen Allergy in Europe. Environmental Health Perspectives, 125(3), 385–391. https://doi.org/10.1289/EHP173

Lugonja, P., Brdar, S., Simović, I., Mimić, G., Palamarchuk, Y., Sofiev, M., & Šikoparija, B. (2019). Integration of in situ and satellite data for top-down mapping of Ambrosia infection level. Remote Sensing of Environment, 235, 111455. https://doi.org/10.1016/j.rse.2019.111455

Schaffner, U., Steinbach, S., Sun, Y., Skjøth, C. A., de Weger, L. A., Lommen, S. T., Augustinus, B. A., Bonini, M., Karrer, G., Šikoparija, B., Thibaudon, M., & Müller-Schärer, H. (2020). Biological weed control to relieve millions from Ambrosia allergies in Europe. Nature Communications, 11(1), 1745. https://doi.org/10.1038/s41467-020-15586-1

8. Introduction (lines 25-26): You mixed here different aspects with a clear point. Clarify some parts of the introduction.
9. Introduction (lines 31-50): You describe a kind of history of the aerobiological analysis on ragweed. However, I think it is more interesting grouping the literature based on the kind of study (study of the long-term variability, study of pollen sources, study of the short-term meteorological conditions, etc.) instead of a chronological description of the publications. Furthermore, the literature review should be updated.
10. Introduction (lines 51-74): I guess that for modellers the name of the dispersive models are very common, but can you include the non-abbreviated name of the model the first time when appears?
11. Introduction (lines 81-89): From my point of view, it is not necessary a scheme of the content of the manuscript, but clarify the aims of the study.
12. Methodology (lines 97-98): I agree, sometimes it is difficult to isolate the emissions from different pollen sources in distance. But the authors may cite some efforts carried out with this regard using both novel statistical approaches or phenological observations in field (Oteros et al. 2015; Rojo et al. 2015; Romero-Morte et al. 2018):

Oteros, J., García-Mozo, H., Alcázar, P., Belmonte, J., Bermejo, D., Boi, M., Cariñanos, P., Díaz de la Guardia, C., Fernández-González, D., González-Minero, F., Gutiérrez-Bustillo, A. M., Moreno-Grau, S., Pérez-Badía, R., Rodríguez-Rajo, F. J., Ruíz-Valenzuela, L., Suárez-Pérez, J., Trigo, M. M., Domínguez-Vilches, E., & Galán, C. (2015). A new method for determining the sources of airborne particles. Journal of Environmental Management, 155, 212–218. https://doi.org/10.1016/j.jenvman.2015.03.037

Rojo, J., & Pérez-Badia, R. (2015). Spatiotemporal analysis of olive flowering using geostatistical techniques. Science of The Total Environment, 505, 860–869. https://doi.org/10.1016/j.scitotenv.2014.10.022

Romero-Morte, J., Rojo, J., Rivero, R., Fernández-González, F., & Pérez-Badia, R. (2018). Standardised index for measuring atmospheric grass-pollen emission. Science of The Total Environment, 612, 180–191. https://doi.org/10.1016/j.scitotenv.2017.08.139

13. Methodology (line 108): Laaidi et al. (2003) is a study using the aerobiological procedure but I think it is not the most apropriate reference for cite the method. Please, explain better this and include methodological references as those for the operational device (Hirst, 1952) for the standardised methods (Galan et al. 2014):

Galán, C., Smith, M., Thibaudon, M., Frenguelli, G., Oteros, J., Gehrig, R., Berger, U., Clot, B., Brandao, R., & EAS QC Working Group. (2014). Pollen monitoring: Minimum requirements and reproducibility of analysis. Aerobiologia, 30(4), 385–395. https://doi.org/10.1007/s10453-014-9335-5

Hirst, J. M. (1952). An automatic volumetric spore trap. Annals of Applied Biology, 39(2), 257–265. https://doi.org/10.1111/j.1744-7348.1952.tb00904.x

14. Methodology (line 110): Change "represnetative" by "representative".
15. Methodology (lines 109-110): I agree that a pollen trap has a good representation of the regional surroundings in about 30km (Maya-Manzano et al. ), but you note also that the spatial representativeness depends on the pollen taxa (Rojo et al. 2016; Oteros et al. 2017):

Oteros, J., Valencia, R. M., Del Río, S., Vega, A. M., García-Mozo, H., Galán, C., Gutiérrez, P., Mandrioli, P., & Fernández-González, D. (2017). Concentric Ring Method for generating pollen maps. Quercus as case study. Science of The Total Environment, 576, 637–645.

Rojo, J., Orlandi, F., Pérez-Badia, R., Aguilera, F., Ben Dhiab, A., Bouziane, H., Díaz de la Guardia, C., Galán, C., Gutiérrez-Bustillo, A. M., Moreno-Grau, S., Msallem, M., Trigo, M. M., & Fornaciari, M. (2016). Modeling olive pollen intensity in the Mediterranean region through analysis of emission sources. Science of The Total Environment, 551–552, 73–82. https://doi.org/10.1016/j.scitotenv.2016.01.193

16. Methodology (lines 130-133): The pollen season definition is a controversial issue in aerobiology. I do not mean that the use of 95% criterion is incorrect. But it should be case by case interpreted for selecting the best method (Bastl et al. 2018). Anyway, again the citation of Laaidi et al., 2013 is not the most appropriate in this point.

Bastl, K., Kmenta, M., & Berger, U. E. (2018). Defining Pollen Seasons: Background and Recommendations. Current Allergy and Asthma Reports, 18(12). https://doi.org/10.1007/s11882-018-0829-z

16. Section 3 (lines 176-178): Please, include the appropriate citation for referrencing the E-OBS gridded dataset.
17. Section 3 (table 5): Please, include here the descriptions of abbreviations too. It would be easier for the reader.
18. Section 3: Is wind direction included in the analysis? It appears an important factor (Rojo et al. 2015; Maya-Manzano et al. 2017). How wind direction factor is considered in the models?

Maya-Manzano, J. M., Sadyś, M., Tormo-Molina, R., Fernández-Rodríguez, S., Oteros, J., Silva-Palacios, I., & Gonzalo-Garijo, A. (2017). Relationships between airborne pollen grains, wind direction and land cover using GIS and circular statistics. Science of The Total Environment, 584–585, 603–613. https://doi.org/10.1016/j.scitotenv.2017.01.085

Rojo, J., Rapp, A., Lara, B., Fernández-González, F., & Pérez-Badia, R. (2015). Effect of land uses and wind direction on the contribution of local sources to airborne pollen. Science of The Total Environment, 538, 672–682. https://doi.org/10.1016/j.scitotenv.2015.08.074

19. Section 4 (lines 256-258): Discuss this aspect based on this most recent publication (Lugonja et al. 2019):

Lugonja, P., Brdar, S., Simović, I., Mimić, G., Palamarchuk, Y., Sofiev, M., & Šikoparija, B. (2019). Integration of in situ and satellite data for top-down mapping of Ambrosia infection level. Remote Sensing of Environment, 235, 111455. https://doi.org/10.1016/j.rse.2019.111455

20. Section 5 (lines 358-363): I do not know if it is applied in this context, but I guess that the model has been calibrated for the rest of years, and then tested in 2010 (independent year not included in the training). Is it correct? Clarify this aspect in Methodology. The authors explained the reasons because 2010 was used as independent year for external validation, but would it be possible to use a left-one-out cross-validation, as I think a more realistic approach?
21. Section 5 (lines 366-367): Better use coefficient of determination (R2) for the validation (predicted vs. observed) instead of the Pearson correlation statistic.
22. Section 5 (lines 368-369): Explain the causes of understimation of the models. What parts of the models should be improved, the pollen source abundance?
23. Section 5 (Figure 4): The authors validate the prediction based on temporal time-series (table 6 and figure 3). However, it is not observed a clear spatial validation. Could it be done in Figure 4 obtaining a spatial map for observed values using regression-kriging? (Rojo et al. 2016). Then, this observed map could be also compared with the predictions for the three approaches (spatial SD, RMSE, etc.).

Rojo, J., Orlandi, F., Pérez-Badia, R., Aguilera, F., Ben Dhiab, A., Bouziane, H., Díaz de la Guardia, C., Galán, C., Gutiérrez-Bustillo, A. M., Moreno-Grau, S., Msallem, M., Trigo, M. M., & Fornaciari, M. (2016). Modeling olive pollen intensity in the Mediterranean region through analysis of emission sources. Science of The Total Environment, 551–552, 73–82. https://doi.org/10.1016/j.scitotenv.2016.01.193

24. Conclussion: The conclussion section should be planned in a more general terms. Most of the information in this section could be included in the Result and Discussion section.

Author Response

Answers are in the attached PDF file.

Author Response File: Author Response.pdf

Reviewer 2 Report

The article deals with an interesting scientific problem. The authors clearly defined the aim of the article, but in the reviewer opinion the manuscript shows several serious failures. The authors cite quite old literature in their work. Most of the articles were published before 2015. They do not cite the most recent articles in which ambrosia pollen grains were studied. It is not fully known, whether in the article models from before almost 10 years, were used or the analyzes performed recently. The general information (line 156 – The meteorological variables are obtained from a simulation using the WRF regional model in its version 3.3.1) shows that it is an old version. In 2013 version 4 has already been released. Models, including meteorological ones, are being updated, so the results of research obtained a decade ago may be out of ate. Possible publication of the article in 2021 requires literature, data, methods and results being as current as possible. The reviewed work does not meet this requirement.

Other remarks:

Nie jest jasne, kiedy autorzy analizowali dane w latach 2005-2011, a kiedy tylko w 2010 roku? Ogólnie rzecz biorąc, wyniki, w tym tabele i liczby, zostały przedstawione wyłącznie na podstawie danych z 2010 r.

Autorzy powinni wziąć pod uwagę układ i fragmenty manuskryptu. Nie jest w pełni zrozumiałe, dlaczego tabela z datami rozpoczęcia i zakończenia pór pyłku została przedstawiona w powszechnie znanej formule i interpretacji współczynnika korelacji itp., podczas gdy zastosowane metody części nie były w przekonujący sposób uzasadnione i nie odnosiły się do obecnej literatury, np.

Dlaczego autorzy wykorzystali tylko dane między 3:00 a 12:00 UTC? Czy średnia dzienna wartość była obliczana tylko dla tych 6 godzin?

Nie jest jasne, jakie dane (co godzinę, codziennie) zostały wykorzystane w tabeli 4.

Dlaczego wyniki przedstawione w tabeli 5 są ograniczone tylko do tych 4 konkretnych stacji? Dlaczego brano pod uwagę tylko poranne pomiary, a nie inne części dnia, zwłaszcza 12:00 UTC?

Author Response

Answers are in the PDF attached file

Author Response File: Author Response.pdf

Reviewer 3 Report

Dear Authors,

Please find attached my review as a pdf file.

Reviewer

Comments for author File: Comments.pdf

Author Response

Answers are in the attached PDF file.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

The manuscript has been improved and almost all comments and suggestions have been addressed. In general, the authors argue well all points, but we request some clarifications and comments.

1. Abstract (lines 1-2): Perhaps better: "This study is dedicated to improve the analysis and forecasting of the ragweed pollen emission in the context of deterministic regional modelling".
2. Introduction (lines 53-85): The authors have updated the literature and clarified some points in this part, but only one paragraph is too much for all this information. Please, split coherently these lines in a couple of paragraphs.
3. Methodology (line 124): I guess you had here a mistake with the editor of bibliography.
4. Methodology (lines 143-144): The citation Romero-Morte et al. does not fit well here, please revise the previous comments of the previous round of review on this regard.
5. Methodology (lines 156-159): The authors should try to explain why they used the 5% method for defining the pollen season, not only to apply following the criterion of a previous work.
6. Section 3 (lines 247-248): About the wind direction the authors answered me "...the wind direction is not considered. This is due to two things : (i) the spatial scale of our modelling is 60km, then we consider that the variability of wind direction compared to local measurements can not give informations for the analysis, (ii) pollen emission only depends on wind speed". While I can understand that the spatial resolution determines the predictive variables included in these models, I do not understand the second reason. If only pollen emission is considered in this kind of models I think a great information is kept incomplete about the pollen dispersal, which I think is crucial to model the pollen exposure and the pollen amounts recorded in the pollen traps. Could the authors clarify this important point?

Author Response

The answers are in the PDF file

Author Response File: Author Response.pdf

Reviewer 2 Report

The manuscript has been sufficiently corrected and supplemented with newer literature. Only one note - please check the text on line 124. 

Author Response

The answers are in the PDF file.

Author Response File: Author Response.pdf