the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 21 Jul 2021
Global soil NO emissions for Atmospheric Chemical Transport Modelling: CAMS-GLOB-SOIL v2.2
Abstract. We present a dataset of global soil NO emissions comprising gridded monthly data and the corresponding 3-hourly weight factors, suitable for atmospheric chemistry modelling. Data are provided globally at 0.5° × 0.5° degrees horizontal resolution, and with monthly time resolution over the period 2000–2018. Emissions are provided as total values and also with separate data for soil NO emissions from background biome values, and those induced by fertilizers/manure, pulsing effects, and atmospheric deposition, so that users can include, exclude or modify each component if wanted.
This paper presents the emission algorithms and their data-sources, some comments on the availability of soil NO emissions in other inventories (and how to avoid double-counting), and finally some preliminary modelling results and comparison with observed data.
This dataset was constructed as part of the Copernicus Atmosphere Monitoring Service (CAMS), with the dataset referred to as CAMS-GLOB-SOIL v2.2. These data are available through the Copernicus Atmosphere Data Store (ADS) system, (https://doi.org/10.24380/kz2r-fe18, last access June 2021, Simpson 2021a) or through the Emissions of atmospheric Compounds and Compilation of Ancillary Data (ECCAD) system (https://eccad.aeris-data.fr/, last access June 2021). For review purposes, ECCAD has set up an anonymous repository where a subset of the CAMS-GLOB-SOIL v2.2 data can be accessed directly (https://eccad.aeris-data.fr/essd-surf-emis-cams-soil/, Last access July 2021, Simpson 2021b).
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RC1: 'Comment on essd-2021-221', Anonymous Referee #1, 20 Aug 2021
Review of “Global soil NO emissions for Atmospheric Chemical Transport Modelling: CAMS-GLOB-SOIL v2.2”
General comments:
This study implemented the YL95 soil NO emissions scheme with various updates from other publications in the EMEP MSC-W chemistry transport model, and generated global soil NO emissions at the spatial resolution of 0.5 degree by 0.5 degree during 2000-2018. Soil NO is a significant contributor to global NO emissions, and generating global NO emissions inventory is important. However, it is very difficult to find innovation in this study, thus I cannot recommend its publication in ESSD.
Specific comments:
- This study just implemented an old NO emissions scheme with various updates from other publications, but it lacks innovation. Moreover, Weng et al. (2020) has already generated global soil NO emissions at the resolution of 0.5 degree by 0.625 degree for 1980-2017. What is the innovation of this study compared with Weng et al. (2020). A little finer resolution is not sufficient to make it publish.
- Although Sect. 3.3.2 explain a bit, I still cannot understand why use air temperature rather than soil temperature. Do you mean soil temperature has very large uncertainty or it requires more coding work to implement?
- The introduction lacks the review of current soil NOx emission algorithm.
- Line 3: delete “degrees”
- There are many grammar errors, and the writing should be polished.
References
Weng, H., Lin, J., Martin, R., Millet, D. B., Jaeglé, L., Ridley, D., et al. (2020). Global high-resolution emissions of soil NOx, sea salt aerosols, and biogenic volatile organic compounds. Scientific Data, 7(1), 148. https://doi.org/10.1038/s41597-020-0488-5
Citation: https://doi.org/10.5194/essd-2021-221-RC1 -
AC1: 'Reply on RC1', David Simpson, 24 Aug 2021
The comment was uploaded in the form of a supplement: https://essd.copernicus.org/preprints/essd-2021-221/essd-2021-221-AC1-supplement.pdf
-
RC2: 'Comment on essd-2021-221', Anonymous Referee #2, 23 Aug 2021
Title: Review of "Global soil NO emissions for Atmospheric Chemical Transport
Modelling: CAMS-GLOB-SOIL v2.2"Summary: This manuscript provides an overview of methods used to develop the latest (v2.2) version of CAMS soil NO emissions globally. It includes descriptions of the driving datasets, the underlying calculations, and a comparison to the current literature. This is a substantial contribution that will enhance the use and citability of the CAMS dataset.
Response: This manuscript is well written, clearly organized, and well supported scientifically. There are a handful of places where addition information is needed or clarifications should be provided.
Line-by-Line:
- 185 to 188: The logic here is lacking for point (b). Why is T2 more directly interpretable in terms of ecosystem-specific values? I do not think that it is. Two meter temperature is likely to differ within these ecosystems due to surface interactions and evapotranspiration. It does not seem, to this reviewer, that point (b) supports either approach over the other.
- 190 to 192: Again, why does this specifically support the use of T2.
- 194: This section and others please specify how these choices compare to previous versions (v1, v2.1). It is currently unclear where sections 3.3, 3.4, 3.5, and 3.6 vary from previous versions.
- 204: Just to clarify... Inputs are from HEMCO, trends are from CEDS, and the ECLIPSE system is simply providing country codes? The sentence reads "with global NH3 emissions from ECLIPSEv5a database". I am getting mixed messages.
- 236: The equation formulation does not really match the text or tabular descriptions elsewhere, which I would summarize as (F = A(SMI) * f(T) * CRF). Can you either make the text/tables consistent or update the equation to match.
- 241: Please provide the temperature functions.
- 248 to 249: The intimation is that SM of 15% is better than accumulated precipitation, but that is not currently explicit. Can you clarify?
- 255 and 267: though not necessary, it would be nice to have equations to mirror other sections. Since the equation and the factors are identical for 4.2 and 4.3, consider a loading term instead of separate terms.
- 291 to 293: If I interpret correctly, each grid cell is assumed to have a 15% pulse of only the biome component. Then, that pulse is allocated based on the normalized sum of function (i) and (ii). This raises several questions: (1) why 15%? Is this a simplification of S11? If so, why not allow it to vary following S11? (2) The SMI approach appears to be novel and I do not see the results characterized anywhere. Can you show this? (3) What time smoothing function did you use? Can you show some representative results of the 14 day and SMI approaches?
- 306 to 307: rephrase
- 314 to 316: The smoothing function is not described (here and elsewhere). Is this a hanning window? If so, how wide?
- 318: S18 should be S11?
- 320 to 321: rephrase
- 322: You need to provide some evidence that this is a relevant concern. Under what conditions does this occur? A quick calculation shows that +20C difference occurs at 222 K. +10 C at 258 K. Are these temperatures important in the scheme of soil NO? If so, why not simply cap the difference rather than not apply it? Or why not apply Ta + 5?
- 343: co[n]sequence
- 350 aka Figure 6 caption: Brazil is at -46 degrees E or 46 W. Please update.
- 353 to 355: Could you perform a simple test case to establish the relevance of this assumption?
- Table 4: Is ozone daily max the 1-hour max or 8-hour max? Are the % biases the average at sites (Ns) or the overall biases? Same for RMSE and R2 and IOA.
Citation: https://doi.org/10.5194/essd-2021-221-RC2 -
RC3: 'Comment on essd-2021-221', Anonymous Referee #3, 05 Sep 2021
Review of “Global soil NO emissions for Atmospheric Chemical Transport Modelling: CAMS-GLOB-SOIL v2.2 “
This work introduces CAMS-GLOB-SOIL v2.2, a gridded soil NO emissions dataset provided at 0.5 x 0.5 degree spatial resolution and monthly time resolution. The data are produced using the EMEP MSC-W modelling system. The dataset would be a valuable addition to the community, and the discussion surrounding double counting of emissions between this dataset and other inventories is useful. However in its current state, the manuscript lacks a certain level of transparency regarding how these data are produced, particularly regarding the individual terms used within the emissions algorithm. Additional clarification is requested. See below for comments.
Comments:
- Section 2 is a valuable introduction to a variety of soil NOx models and how those models represent emissions, but only a marginal explanation of the overall “background”, or our current understanding, of soil NOx emissions is provided. I suggest renaming this section to “Previous Soil NOx Emissions Models”, or something along those lines.
- Line 175: How are the minimum and maximum soil water amounts determined?
- Line 179: It is claimed that a grid-averaged SMI is more physically meaningful than a grid-averaged volumetric soil moisture, but it's not clear why. Please elaborate.
- Line 185: The reasoning for using air temperature in place of the IFS-provided soil temperature is ambiguous. Why is it difficult to interpret soil temperature from a NWP model? It is implied that the IFS does not capture the complex nature of soil temperature. If that is the case, what evidence is there for air temperature being any more of a reliable metric than the IFS soil temperature? Ideally, a soil temperature product would be used if there is one available within the modelling system being used.
- Line 205: It is unclear what is meant by allowing emission rates to follow N-inputs.
- Line 230: While pulses may be the most dramatic short term soil NO events, daily changes in temperature and soil moisture can clearly cause discernable changes in emissions. Given that meteorological data used in this work have a 3-hr time resolution and the strong impact that soil moisture and temperature can have on daily time scales, why not provide daily data? Valuable detail is lost by providing a monthly averaged product.
- Line 236: I have some questions regarding Equation 3. The soil moisture function used is neither introduced nor explained. Is that function the same as was used in previous studies (e.g. Hudman et al. (2012)), or was a unique scaling function applied? Please add the soil moisture function and an explanation of it for clarity. Additionally, how is Abiome represented? Are the raw values from Table 2 being used alone here, or is this a function of soil nitrogen as was done in Hudman et al. (2012)? Again, please add equations and explanations throughout for individual functions. Otherwise, readers are left to guess how emissions are parameterized.
- Line 246: It is stated that a vol. SM of 15% “was said so correspond to” SMI of 0.5. Is there a reference to support this, or can this please be explained further? Does this not vary significantly by soil type?
- Line 250: It is unclear what “Aw rates” refers to.
- Line 288-289: Please elaborate more on the pulsing criteria. What is meant by “14-day rainfall criteria”? Does this mean that 14 consecutive dry days are required before a pulse can be considered? Further, does “changes in SMI of 0.01” mean both increases and decreases in SMI, or just increases?
- Line 291: Please rephrase this. Does this mean that annual pulse emissions are always estimated at 15% of annual biome emissions, regardless of how many pulses occur in a grid cell throughout a year? Or is this 15% value only applied to individual days where pulsing criteria are met? It is unclear from the wording.
- Line 317: Again, the reasoning for using air temperature is confusing, and the explanation in this section (section 4.7) appears to differ from the explanation that was given earlier (section 3.3.2).
- Lines 330 / 336: For Figures 4 and 5, please specify in the text and captions that these are annually- or monthly-averaged emissions, if that is the case.
- Line 340 / Figure 6: It is unclear what the factors shown in this figure represent, or how they were derived. Why were these 3 locations chosen (Brazil, Australia, France), and what is the main takeaway from this figure? The value added by including this information is not apparent.
Technical Corrections:
- This work contains numerous instances of short paragraphs which often seem to be separated arbitrarily, and which would still convey a coherent message if combined into one paragraph (e.g. all of section 3.2, much of section 4.2). There are also numerous paragraphs which are comprised of just one or two sentences, which should really be included with the preceding or following paragraph (e.g. starting on lines 7, 36, 91, 123, 182, 195, 449, 494, ...).
- Line 45: “anthropogenic”
- Line 146: missing open parenthesis
- Line 200: Is this supposed to say “year”, or “years”? If multiple years are used, please state which years were used specifically.
- Line 220: Some acronyms (e.g. YL95, SL11) are first formally defined here, after the acronyms are already used earlier on, e.g. line 149, and elsewhere.
- Line 306: “applied” instead of “applies”
- Line 315: “uncertainty” instead of “uncertain”
- Line 318: Undefined acronym “S18”
References:
Hudman, R. C., Moore, N. E., Mebust, A. K., Martin, R. V., Russell, A. R., Valin, L. C., and Cohen, R. C.: Steps towards a mechanistic model of global soil nitric oxide emissions: implementation and space based-constraints, Atmos. Chem. Physics, 12, 7779–7795, 2012.
Citation: https://doi.org/10.5194/essd-2021-221-RC3 -
RC4: 'Comment on essd-2021-221', Anonymous Referee #4, 12 Oct 2021
Competent assessment of modeling options to better understand NO emissions and their role in air quality (e.g. ozone) and GHG (e.g. N2O) but nothing about data quality, data uncertainty, data validation, and certainly no new data. Does not qualify for ESSD. Authors could check ESSD guidelines at https://www.earth-syst-sci-data.net/10/2275/2018/; they will likely recognize what what they have submitted does not fit. Many details in supplement.
Status: closed
-
RC1: 'Comment on essd-2021-221', Anonymous Referee #1, 20 Aug 2021
Review of “Global soil NO emissions for Atmospheric Chemical Transport Modelling: CAMS-GLOB-SOIL v2.2”
General comments:
This study implemented the YL95 soil NO emissions scheme with various updates from other publications in the EMEP MSC-W chemistry transport model, and generated global soil NO emissions at the spatial resolution of 0.5 degree by 0.5 degree during 2000-2018. Soil NO is a significant contributor to global NO emissions, and generating global NO emissions inventory is important. However, it is very difficult to find innovation in this study, thus I cannot recommend its publication in ESSD.
Specific comments:
- This study just implemented an old NO emissions scheme with various updates from other publications, but it lacks innovation. Moreover, Weng et al. (2020) has already generated global soil NO emissions at the resolution of 0.5 degree by 0.625 degree for 1980-2017. What is the innovation of this study compared with Weng et al. (2020). A little finer resolution is not sufficient to make it publish.
- Although Sect. 3.3.2 explain a bit, I still cannot understand why use air temperature rather than soil temperature. Do you mean soil temperature has very large uncertainty or it requires more coding work to implement?
- The introduction lacks the review of current soil NOx emission algorithm.
- Line 3: delete “degrees”
- There are many grammar errors, and the writing should be polished.
References
Weng, H., Lin, J., Martin, R., Millet, D. B., Jaeglé, L., Ridley, D., et al. (2020). Global high-resolution emissions of soil NOx, sea salt aerosols, and biogenic volatile organic compounds. Scientific Data, 7(1), 148. https://doi.org/10.1038/s41597-020-0488-5
Citation: https://doi.org/10.5194/essd-2021-221-RC1 -
AC1: 'Reply on RC1', David Simpson, 24 Aug 2021
The comment was uploaded in the form of a supplement: https://essd.copernicus.org/preprints/essd-2021-221/essd-2021-221-AC1-supplement.pdf
-
RC2: 'Comment on essd-2021-221', Anonymous Referee #2, 23 Aug 2021
Title: Review of "Global soil NO emissions for Atmospheric Chemical Transport
Modelling: CAMS-GLOB-SOIL v2.2"Summary: This manuscript provides an overview of methods used to develop the latest (v2.2) version of CAMS soil NO emissions globally. It includes descriptions of the driving datasets, the underlying calculations, and a comparison to the current literature. This is a substantial contribution that will enhance the use and citability of the CAMS dataset.
Response: This manuscript is well written, clearly organized, and well supported scientifically. There are a handful of places where addition information is needed or clarifications should be provided.
Line-by-Line:
- 185 to 188: The logic here is lacking for point (b). Why is T2 more directly interpretable in terms of ecosystem-specific values? I do not think that it is. Two meter temperature is likely to differ within these ecosystems due to surface interactions and evapotranspiration. It does not seem, to this reviewer, that point (b) supports either approach over the other.
- 190 to 192: Again, why does this specifically support the use of T2.
- 194: This section and others please specify how these choices compare to previous versions (v1, v2.1). It is currently unclear where sections 3.3, 3.4, 3.5, and 3.6 vary from previous versions.
- 204: Just to clarify... Inputs are from HEMCO, trends are from CEDS, and the ECLIPSE system is simply providing country codes? The sentence reads "with global NH3 emissions from ECLIPSEv5a database". I am getting mixed messages.
- 236: The equation formulation does not really match the text or tabular descriptions elsewhere, which I would summarize as (F = A(SMI) * f(T) * CRF). Can you either make the text/tables consistent or update the equation to match.
- 241: Please provide the temperature functions.
- 248 to 249: The intimation is that SM of 15% is better than accumulated precipitation, but that is not currently explicit. Can you clarify?
- 255 and 267: though not necessary, it would be nice to have equations to mirror other sections. Since the equation and the factors are identical for 4.2 and 4.3, consider a loading term instead of separate terms.
- 291 to 293: If I interpret correctly, each grid cell is assumed to have a 15% pulse of only the biome component. Then, that pulse is allocated based on the normalized sum of function (i) and (ii). This raises several questions: (1) why 15%? Is this a simplification of S11? If so, why not allow it to vary following S11? (2) The SMI approach appears to be novel and I do not see the results characterized anywhere. Can you show this? (3) What time smoothing function did you use? Can you show some representative results of the 14 day and SMI approaches?
- 306 to 307: rephrase
- 314 to 316: The smoothing function is not described (here and elsewhere). Is this a hanning window? If so, how wide?
- 318: S18 should be S11?
- 320 to 321: rephrase
- 322: You need to provide some evidence that this is a relevant concern. Under what conditions does this occur? A quick calculation shows that +20C difference occurs at 222 K. +10 C at 258 K. Are these temperatures important in the scheme of soil NO? If so, why not simply cap the difference rather than not apply it? Or why not apply Ta + 5?
- 343: co[n]sequence
- 350 aka Figure 6 caption: Brazil is at -46 degrees E or 46 W. Please update.
- 353 to 355: Could you perform a simple test case to establish the relevance of this assumption?
- Table 4: Is ozone daily max the 1-hour max or 8-hour max? Are the % biases the average at sites (Ns) or the overall biases? Same for RMSE and R2 and IOA.
Citation: https://doi.org/10.5194/essd-2021-221-RC2 -
RC3: 'Comment on essd-2021-221', Anonymous Referee #3, 05 Sep 2021
Review of “Global soil NO emissions for Atmospheric Chemical Transport Modelling: CAMS-GLOB-SOIL v2.2 “
This work introduces CAMS-GLOB-SOIL v2.2, a gridded soil NO emissions dataset provided at 0.5 x 0.5 degree spatial resolution and monthly time resolution. The data are produced using the EMEP MSC-W modelling system. The dataset would be a valuable addition to the community, and the discussion surrounding double counting of emissions between this dataset and other inventories is useful. However in its current state, the manuscript lacks a certain level of transparency regarding how these data are produced, particularly regarding the individual terms used within the emissions algorithm. Additional clarification is requested. See below for comments.
Comments:
- Section 2 is a valuable introduction to a variety of soil NOx models and how those models represent emissions, but only a marginal explanation of the overall “background”, or our current understanding, of soil NOx emissions is provided. I suggest renaming this section to “Previous Soil NOx Emissions Models”, or something along those lines.
- Line 175: How are the minimum and maximum soil water amounts determined?
- Line 179: It is claimed that a grid-averaged SMI is more physically meaningful than a grid-averaged volumetric soil moisture, but it's not clear why. Please elaborate.
- Line 185: The reasoning for using air temperature in place of the IFS-provided soil temperature is ambiguous. Why is it difficult to interpret soil temperature from a NWP model? It is implied that the IFS does not capture the complex nature of soil temperature. If that is the case, what evidence is there for air temperature being any more of a reliable metric than the IFS soil temperature? Ideally, a soil temperature product would be used if there is one available within the modelling system being used.
- Line 205: It is unclear what is meant by allowing emission rates to follow N-inputs.
- Line 230: While pulses may be the most dramatic short term soil NO events, daily changes in temperature and soil moisture can clearly cause discernable changes in emissions. Given that meteorological data used in this work have a 3-hr time resolution and the strong impact that soil moisture and temperature can have on daily time scales, why not provide daily data? Valuable detail is lost by providing a monthly averaged product.
- Line 236: I have some questions regarding Equation 3. The soil moisture function used is neither introduced nor explained. Is that function the same as was used in previous studies (e.g. Hudman et al. (2012)), or was a unique scaling function applied? Please add the soil moisture function and an explanation of it for clarity. Additionally, how is Abiome represented? Are the raw values from Table 2 being used alone here, or is this a function of soil nitrogen as was done in Hudman et al. (2012)? Again, please add equations and explanations throughout for individual functions. Otherwise, readers are left to guess how emissions are parameterized.
- Line 246: It is stated that a vol. SM of 15% “was said so correspond to” SMI of 0.5. Is there a reference to support this, or can this please be explained further? Does this not vary significantly by soil type?
- Line 250: It is unclear what “Aw rates” refers to.
- Line 288-289: Please elaborate more on the pulsing criteria. What is meant by “14-day rainfall criteria”? Does this mean that 14 consecutive dry days are required before a pulse can be considered? Further, does “changes in SMI of 0.01” mean both increases and decreases in SMI, or just increases?
- Line 291: Please rephrase this. Does this mean that annual pulse emissions are always estimated at 15% of annual biome emissions, regardless of how many pulses occur in a grid cell throughout a year? Or is this 15% value only applied to individual days where pulsing criteria are met? It is unclear from the wording.
- Line 317: Again, the reasoning for using air temperature is confusing, and the explanation in this section (section 4.7) appears to differ from the explanation that was given earlier (section 3.3.2).
- Lines 330 / 336: For Figures 4 and 5, please specify in the text and captions that these are annually- or monthly-averaged emissions, if that is the case.
- Line 340 / Figure 6: It is unclear what the factors shown in this figure represent, or how they were derived. Why were these 3 locations chosen (Brazil, Australia, France), and what is the main takeaway from this figure? The value added by including this information is not apparent.
Technical Corrections:
- This work contains numerous instances of short paragraphs which often seem to be separated arbitrarily, and which would still convey a coherent message if combined into one paragraph (e.g. all of section 3.2, much of section 4.2). There are also numerous paragraphs which are comprised of just one or two sentences, which should really be included with the preceding or following paragraph (e.g. starting on lines 7, 36, 91, 123, 182, 195, 449, 494, ...).
- Line 45: “anthropogenic”
- Line 146: missing open parenthesis
- Line 200: Is this supposed to say “year”, or “years”? If multiple years are used, please state which years were used specifically.
- Line 220: Some acronyms (e.g. YL95, SL11) are first formally defined here, after the acronyms are already used earlier on, e.g. line 149, and elsewhere.
- Line 306: “applied” instead of “applies”
- Line 315: “uncertainty” instead of “uncertain”
- Line 318: Undefined acronym “S18”
References:
Hudman, R. C., Moore, N. E., Mebust, A. K., Martin, R. V., Russell, A. R., Valin, L. C., and Cohen, R. C.: Steps towards a mechanistic model of global soil nitric oxide emissions: implementation and space based-constraints, Atmos. Chem. Physics, 12, 7779–7795, 2012.
Citation: https://doi.org/10.5194/essd-2021-221-RC3 -
RC4: 'Comment on essd-2021-221', Anonymous Referee #4, 12 Oct 2021
Competent assessment of modeling options to better understand NO emissions and their role in air quality (e.g. ozone) and GHG (e.g. N2O) but nothing about data quality, data uncertainty, data validation, and certainly no new data. Does not qualify for ESSD. Authors could check ESSD guidelines at https://www.earth-syst-sci-data.net/10/2275/2018/; they will likely recognize what what they have submitted does not fit. Many details in supplement.
Data sets
CAMS-GLOB-SOIL v2.2 David Simpson and Sabine Darras https://doi.org/10.24380/kz2r-fe18
CAMS-GLOB-SOIL v2.2 subset for review David Simpson and Sabine Darras https://eccad.aeris-data.fr/essd-surf-emis-cams-soil/
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