the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 18 Oct 2021
Biomass burning events measured by lidars in EARLINET – Part 2: Optical properties investigation
Abstract. Biomass burning episodes measured at 14 stations of the European Aerosol Research Lidar Network (EARLINET) over 2008–2017 were analysed using the methodology described in "Biomass burning events measured by lidars in EARLINET – Part 1: Data analysis methodology" (Adam et al., 2020, this issue). The smoke layers were identified in lidar optical properties profiles. A number of 795 layers for which we measured at least one intensive parameter was analysed. These layers were geographically distributed as follows: 399 layers observed in South-East Europe, 119 layers observed in South-West Europe, 243 layers observed in North-East Europe, and 34 layers observed in Central Europe. The mean layer intensive parameters are discussed following two research directions: (I) the long-range transport of smoke particles from North America, and (II) the smoke properties (fresh versus aged), separating the smoke events into four continental source regions (European, North American, African, Asian or a mixture of two), based on back trajectory analysis. The smoke detected in Central Europe (Cabauw, Leipzig, and Hohenpeißenberg) was mostly transported from North America (87 % of fires). In North-East Europe (Belsk, Minsk, Warsaw) smoke advected mostly from Eastern Europe (Ukraine and Russia), but there was a significant contribution (31 %) from North America. In South-West Europe (Barcelona, Evora, Granada) smoke originated mainly from the Iberian Peninsula and North Africa (while 9 % were originating in North America). In the South-East Europe (Athens, Bucharest, Potenza, Sofia, Thessaloniki) the origin of the smoke was mostly local (only 3 % represented North America smoke). The following features, correlated with the increased smoke travel time (corresponding to aging) were found: the colour ratio of the lidar ratio (i.e., the ratio of the lidar ratio at 532 nm to the lidar ratio at 355 nm) and the colour ratio of the backscatter Ångström exponent (i.e., the ratio of the backscatter-related Angstrom exponent for the pair 532 nm – 1064 nm to the one for the pair 355 nm – 532 nm) increase, while the extinction Ångström exponent and the colour ratio of the particle depolarization ratio (i.e., the ratio of the particle linear depolarization ratio at 532 nm to the particle depolarization ratio at 355 nm) decrease. The smoke originating from all continental regions can be characterized on average as aged smoke, with a very few exceptions. In general, the long range transported smoke shows higher lidar ratio and lower depolarization ratio compared to the local smoke.
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RC1: 'Comment on acp-2021-759', Anonymous Referee #2, 03 Nov 2021
This is a follow-on study from Adam et al (2020), using the results of that analysis to examine the properties and origins of smoke layers detected by the EARLINET network. The enormous amount of data collected by EARLINET and the careful analysis presented in the first paper provides the opportunity for some meaningful statistics, which are very much needed as we become ever more aware of forest fires in our warming world. However, the paper requires major revision before being suitable for publication.
- The greatest weakness in the presentation of the paper lies in the Introduction, where we learn almost nothing about the results of previous studies of smoke transport – simply providing a long list of references is not sufficient to set the context. What have other authors found? What is the gap in their results that this paper is going to fill? A more thorough Introduction needs to prepare the reader for the methodology and approach that this paper uses. As it is, the paper just presents statistics with no context. A cursory ‘literature survey’ pops up in the results section (Section 4 page 6 lines 5-14), but this is not the right place nor it is anywhere near comprehensive enough.
- Also required is a clear description of what the lidars measure and how the intensive variables inform us about aerosol properties. Towards the end of the paper, for example, lidar ratio is explicitly referred to as ‘absorption’, but nowhere in the paper is there an explanation of why the authors make this connection (nor even clear references to that effect). On p.7 l.26-9 the paper simply states that this is so with no explanation. It would be better to provide a clear explanation in the Methods section of what the intensive variables tell us – that would then justify why they are used. There is discussion on p.4 of fresh and aged smoke which could be extended for this purpose. Bear in mind that there will be readers of this paper who are not intimately familiar with Raman lidars.
- The greatest flaw in the methodology of this paper is the use of single 10-day back-trajectories to infer the origin of the smoke layers measured. This is such a severe limitation that it could even be taken as grounds to reject the paper. Nowhere is there a discussion of the huge uncertainties in back-trajectories, or of the need for clusters of them to decide whether the flow is sufficiently non-dispersive to make them valid. Over 10 days in the troposphere most trajectories will be highly dispersive. This means that attributing source regions to the measurements is fraught with error. In addition, as the authors do recognise but do nothing about, the passage of a trajectory 9 km above a fire only implies a causal link if the fire plumes extended to 9 km, which in most cases they don’t. I realise that this may well be an intractable problem, and that the results of this study may be novel enough to publish anyway, but the paper must discuss how the uncertainty in their source apportionment methodology affects the conclusions they draw. (Crudely, it makes any attempt to draw a distinction between different source regions null and void).
- Section 3.1 lines 20 - 30. A number of features in fig.1 are discussed here but it is not possible to relate them to the figure as that is organised by layer number not date (and for the first point discussed not even a date is given). Please point out exactly where in fig 1 the discussion is addressing in each case.
- Section 3.1 lines 31 – p.6 l.3. The text here needs to be more quantitative and again refer exactly to the supporting evidence in fig.1. Terms like ‘moderate’, ‘high’ and ‘low’ are out of place here because the reader doesn’t know the context within which these comparators sit. Furthermore, is there enough evidence to support sweeping generalisations like that on absorption, based on what looks like one event? The section also requires proper referencing to support the interpretations being presented.
- The authors should carefully consider moving Fig 7 to the Supplement and removing the final paragraph of 4.2.1 which is descriptive and offers no interpretation of any value.
Typos and minor corrections (of which there are many more than listed here)
p.2 l.21 ‘indicate that climate change’
p.2 l.30 EARLINET provides remote-sensing lidar measurements not ground-based measurements. The lidars are on the ground but the measurements are not.
p.3 l.6 origins
p.3 l.8 ‘This paper presents Part 2 of the investigation …………EARLINET, focussing on interpreting the results’
p.3 l.20 ‘averages over1 h’
p.3 l.22 ‘presence of smoke layers’
p.3 l.22-3 ‘…..stations, typically by means of……’
p.3 l.28 ‘described in detail in Part 1’
p.4 l.6 ‘middle points of a 1 km grid’
p.4 l.12 ‘criterion is presented in Table 2’
p.4 l.13. Why do you explain BAE and PDR but not the other acronyms here? Either define all of them or just refer the reader to Appendix A.
p.4 l.25 ‘which allowed the degree of oxidation in BB aerosol to be estimated’
p.5 l.14 and fig 1 caption ‘layer altitudes’
p.5 l.16 and fig 1 caption ‘the literature’
Fig 1 caption last line ‘panel titles’
p.5 l.27 ‘….reported in the literature, but still within….’
p.5 l.30 delete ‘the’
p.6 l.5 ‘with’ instead of ‘by’
p.6 l.6 ‘discuss stratospheric’
p.6 l.7 you can’t have a single event lasting six months. What exactly did Baars et al do?
p.6 l.9 you abruptly transition from previous studies to results from this study with no explanation. You need to explain to the reader that you are now presenting your own results.
p.6 l.16. Replace the sentence ‘For a straightforward comparison, we reproduce the figure for the South-East region from Part 1’ by ‘(Note that the figures for the south-east region are the same as Figure 11 in Part 1)’
p.6 l.18 delete ‘a number of’
p.6 l.27 ‘Eastern Europe’, also delete ‘region’
p.6 l.30 replace ‘contained a’ with ‘observed’, and omit ‘the’ before Cabauw.
p.7 l.2, 4 and 6 ‘Eastern Europe’, also ‘Southern’ on l.6
p.7 l.8 ‘Events where small particles are transported in the boundary layer from these regions to North-West Europe…..’
p.7 l.11 Arctic (not arctic)
p.7 l.23 ‘results for the South-East region’
p.7 l.26-29 – this paragraph is out of place and should form part of an expanded Introduction or be included in the methodology section when lidar ratio is introduced. There should be more references to the link between absorption and lidar ratio as well.
p.8 l.2 ‘LR@355 being larger…’ (the verb in this sentence is ‘indicates’). ‘From the EU region’ on l.3
p.8 l.9 ‘the supplement’
p.8 l.15 ‘which are larger’
p.8 l.17 ‘between the NA and EUNA….’, then ‘the EUNA’ on the next line
p.8 l.22 ‘the South-West’
p.8 l.23 ‘the EU and AF’
p.8 l.24 ‘indicate a large’
p.8 l.25 ‘Similar, large, values … for the NA….’
p.8 l.26 ‘the EUAF’
p.8 l.27 ‘the AF’
p.8 l.28 ‘the North-East’
p.8 l.31 ‘the EU’
p.9 l.1 ‘the EUAF’
p.9 l.4 ‘the EU’ and ‘the NA’
p.9 l.7 Replace ‘We perform the analysis based on the mean IP values as a function of continental source region. We consider analysing the scatter plots between the different CRs and EAE, where, for each scatter plot, the mean values correspond to the same measurements. Still, different scatter plots can refer to slightly different sets of measurements.’ With ‘‘We present analyses of mean IP values as a function of continental source region by means of scatter plots between the different CRs and EAE’. I didn’t understand what you meant by ‘for each scatter plot, the mean values correspond to the same measurements.’
Fig 6 – why are there two ‘literature means’ on panels a-c and several on panels d-f?
p.9 l.23 ‘except for’. Also the lowest EAE is <0, not <0.5. The sentence degenerates into confusion. CRPDR < 1 means (not indicates) that PDR355 > PDR532 as that is how it is defined. It may indicate aged particles except that the next clause (l.24) contradicts this and says that PDR532 can be greater for either fresh or aged smoke. (This is why a clear literature survey earlier in the paper is so important). What are you trying to say?
p.9 l.24 Datasets cannot be statistically significant – what correlation exactly does this refer to?
p.9 l.25-6 ‘From fig 6a, a slight…..’
p.10 l.9 ‘the EU’
p.10 l.11 ‘a result’
p.10 l.12 ‘the EUNA’, ‘the EUAS’
p.10 l.32 ‘the NA’
p.10 l.33 ‘the EUNA’
p.11 l.1 ‘the local (EU) contribution determines whether …’
p.11 l.3 ‘the EU’ ‘particle size’
p.11 l. 5 ‘the EUAF ……… the EU’
p.11 l.13 ‘the EUAF’
p.12 l.10 and 11 ‘)’ after America.
p.12 l.13 ‘The analysis..’ – the sentence does not make sense and needs redrafting
p.12 l.15 change ‘helping identifying the smoke’ to ‘helps to identify smoke’
p.12 l. 30 ‘measurement regions’
p.13 l.2 ‘the ACTRIS’
p.13 l.3 ‘applied to’
p.13 l.4 ‘providing more … datasets’ or ‘providing a more …. dataset’
p.13 l.8. Remove double .. ‘shows the potential of the approach described’
p.13 l.10 ‘results obtained’ not ‘obtained results’
p.13 l.13 remove the sentence ‘This extension…’ It is superfluous and also flawed grammatically
Citation: https://doi.org/10.5194/acp-2021-759-RC1 -
AC1: 'Reply on RC1 and RC2', Mariana Adam, 04 Feb 2022
The comment was uploaded in the form of a supplement: https://acp.copernicus.org/preprints/acp-2021-759/acp-2021-759-AC1-supplement.pdf
-
RC2: 'Comment on acp-2021-759', Anonymous Referee #1, 23 Nov 2021
The manuscript deals with lidar-derived optical properties of fire smoke in the air over different parts of Europe. The observations cover fresh smoke events and events with aged smoke after long range transport (frequently from North America). The European Aerosol Research Lidar Network (EARLINET) data base is used for this study. Unfortunately, the amount of data is so low and even not of high quality (to my opinion) that clear messages and convincing conclusions cannot be drawn. I clearly see that the first author did her best, however, the available data set does not allow to write a sound scientific ‘story’ because numerous and high quality results are not available. Mariana Adam can just present some kind of a final report (of a not just very successful, big field campaign lasting over many, many years), rather than an article with well extracted results and findings. This is impossible with the used (poor) data set.
At the end, after careful reading and realizing how poor the available data set is, I cannot recommend publication. If this report would be published in its present form, most of the readers would conclude: Better not to use any EARLINET data. The amount is low and the quality is quite questionable, and in full contrast to what aerosol scientists expected when they are familiar with, e.g., the AERONET data base.
Citation: https://doi.org/10.5194/acp-2021-759-RC2
Status: closed
-
RC1: 'Comment on acp-2021-759', Anonymous Referee #2, 03 Nov 2021
This is a follow-on study from Adam et al (2020), using the results of that analysis to examine the properties and origins of smoke layers detected by the EARLINET network. The enormous amount of data collected by EARLINET and the careful analysis presented in the first paper provides the opportunity for some meaningful statistics, which are very much needed as we become ever more aware of forest fires in our warming world. However, the paper requires major revision before being suitable for publication.
- The greatest weakness in the presentation of the paper lies in the Introduction, where we learn almost nothing about the results of previous studies of smoke transport – simply providing a long list of references is not sufficient to set the context. What have other authors found? What is the gap in their results that this paper is going to fill? A more thorough Introduction needs to prepare the reader for the methodology and approach that this paper uses. As it is, the paper just presents statistics with no context. A cursory ‘literature survey’ pops up in the results section (Section 4 page 6 lines 5-14), but this is not the right place nor it is anywhere near comprehensive enough.
- Also required is a clear description of what the lidars measure and how the intensive variables inform us about aerosol properties. Towards the end of the paper, for example, lidar ratio is explicitly referred to as ‘absorption’, but nowhere in the paper is there an explanation of why the authors make this connection (nor even clear references to that effect). On p.7 l.26-9 the paper simply states that this is so with no explanation. It would be better to provide a clear explanation in the Methods section of what the intensive variables tell us – that would then justify why they are used. There is discussion on p.4 of fresh and aged smoke which could be extended for this purpose. Bear in mind that there will be readers of this paper who are not intimately familiar with Raman lidars.
- The greatest flaw in the methodology of this paper is the use of single 10-day back-trajectories to infer the origin of the smoke layers measured. This is such a severe limitation that it could even be taken as grounds to reject the paper. Nowhere is there a discussion of the huge uncertainties in back-trajectories, or of the need for clusters of them to decide whether the flow is sufficiently non-dispersive to make them valid. Over 10 days in the troposphere most trajectories will be highly dispersive. This means that attributing source regions to the measurements is fraught with error. In addition, as the authors do recognise but do nothing about, the passage of a trajectory 9 km above a fire only implies a causal link if the fire plumes extended to 9 km, which in most cases they don’t. I realise that this may well be an intractable problem, and that the results of this study may be novel enough to publish anyway, but the paper must discuss how the uncertainty in their source apportionment methodology affects the conclusions they draw. (Crudely, it makes any attempt to draw a distinction between different source regions null and void).
- Section 3.1 lines 20 - 30. A number of features in fig.1 are discussed here but it is not possible to relate them to the figure as that is organised by layer number not date (and for the first point discussed not even a date is given). Please point out exactly where in fig 1 the discussion is addressing in each case.
- Section 3.1 lines 31 – p.6 l.3. The text here needs to be more quantitative and again refer exactly to the supporting evidence in fig.1. Terms like ‘moderate’, ‘high’ and ‘low’ are out of place here because the reader doesn’t know the context within which these comparators sit. Furthermore, is there enough evidence to support sweeping generalisations like that on absorption, based on what looks like one event? The section also requires proper referencing to support the interpretations being presented.
- The authors should carefully consider moving Fig 7 to the Supplement and removing the final paragraph of 4.2.1 which is descriptive and offers no interpretation of any value.
Typos and minor corrections (of which there are many more than listed here)
p.2 l.21 ‘indicate that climate change’
p.2 l.30 EARLINET provides remote-sensing lidar measurements not ground-based measurements. The lidars are on the ground but the measurements are not.
p.3 l.6 origins
p.3 l.8 ‘This paper presents Part 2 of the investigation …………EARLINET, focussing on interpreting the results’
p.3 l.20 ‘averages over1 h’
p.3 l.22 ‘presence of smoke layers’
p.3 l.22-3 ‘…..stations, typically by means of……’
p.3 l.28 ‘described in detail in Part 1’
p.4 l.6 ‘middle points of a 1 km grid’
p.4 l.12 ‘criterion is presented in Table 2’
p.4 l.13. Why do you explain BAE and PDR but not the other acronyms here? Either define all of them or just refer the reader to Appendix A.
p.4 l.25 ‘which allowed the degree of oxidation in BB aerosol to be estimated’
p.5 l.14 and fig 1 caption ‘layer altitudes’
p.5 l.16 and fig 1 caption ‘the literature’
Fig 1 caption last line ‘panel titles’
p.5 l.27 ‘….reported in the literature, but still within….’
p.5 l.30 delete ‘the’
p.6 l.5 ‘with’ instead of ‘by’
p.6 l.6 ‘discuss stratospheric’
p.6 l.7 you can’t have a single event lasting six months. What exactly did Baars et al do?
p.6 l.9 you abruptly transition from previous studies to results from this study with no explanation. You need to explain to the reader that you are now presenting your own results.
p.6 l.16. Replace the sentence ‘For a straightforward comparison, we reproduce the figure for the South-East region from Part 1’ by ‘(Note that the figures for the south-east region are the same as Figure 11 in Part 1)’
p.6 l.18 delete ‘a number of’
p.6 l.27 ‘Eastern Europe’, also delete ‘region’
p.6 l.30 replace ‘contained a’ with ‘observed’, and omit ‘the’ before Cabauw.
p.7 l.2, 4 and 6 ‘Eastern Europe’, also ‘Southern’ on l.6
p.7 l.8 ‘Events where small particles are transported in the boundary layer from these regions to North-West Europe…..’
p.7 l.11 Arctic (not arctic)
p.7 l.23 ‘results for the South-East region’
p.7 l.26-29 – this paragraph is out of place and should form part of an expanded Introduction or be included in the methodology section when lidar ratio is introduced. There should be more references to the link between absorption and lidar ratio as well.
p.8 l.2 ‘LR@355 being larger…’ (the verb in this sentence is ‘indicates’). ‘From the EU region’ on l.3
p.8 l.9 ‘the supplement’
p.8 l.15 ‘which are larger’
p.8 l.17 ‘between the NA and EUNA….’, then ‘the EUNA’ on the next line
p.8 l.22 ‘the South-West’
p.8 l.23 ‘the EU and AF’
p.8 l.24 ‘indicate a large’
p.8 l.25 ‘Similar, large, values … for the NA….’
p.8 l.26 ‘the EUAF’
p.8 l.27 ‘the AF’
p.8 l.28 ‘the North-East’
p.8 l.31 ‘the EU’
p.9 l.1 ‘the EUAF’
p.9 l.4 ‘the EU’ and ‘the NA’
p.9 l.7 Replace ‘We perform the analysis based on the mean IP values as a function of continental source region. We consider analysing the scatter plots between the different CRs and EAE, where, for each scatter plot, the mean values correspond to the same measurements. Still, different scatter plots can refer to slightly different sets of measurements.’ With ‘‘We present analyses of mean IP values as a function of continental source region by means of scatter plots between the different CRs and EAE’. I didn’t understand what you meant by ‘for each scatter plot, the mean values correspond to the same measurements.’
Fig 6 – why are there two ‘literature means’ on panels a-c and several on panels d-f?
p.9 l.23 ‘except for’. Also the lowest EAE is <0, not <0.5. The sentence degenerates into confusion. CRPDR < 1 means (not indicates) that PDR355 > PDR532 as that is how it is defined. It may indicate aged particles except that the next clause (l.24) contradicts this and says that PDR532 can be greater for either fresh or aged smoke. (This is why a clear literature survey earlier in the paper is so important). What are you trying to say?
p.9 l.24 Datasets cannot be statistically significant – what correlation exactly does this refer to?
p.9 l.25-6 ‘From fig 6a, a slight…..’
p.10 l.9 ‘the EU’
p.10 l.11 ‘a result’
p.10 l.12 ‘the EUNA’, ‘the EUAS’
p.10 l.32 ‘the NA’
p.10 l.33 ‘the EUNA’
p.11 l.1 ‘the local (EU) contribution determines whether …’
p.11 l.3 ‘the EU’ ‘particle size’
p.11 l. 5 ‘the EUAF ……… the EU’
p.11 l.13 ‘the EUAF’
p.12 l.10 and 11 ‘)’ after America.
p.12 l.13 ‘The analysis..’ – the sentence does not make sense and needs redrafting
p.12 l.15 change ‘helping identifying the smoke’ to ‘helps to identify smoke’
p.12 l. 30 ‘measurement regions’
p.13 l.2 ‘the ACTRIS’
p.13 l.3 ‘applied to’
p.13 l.4 ‘providing more … datasets’ or ‘providing a more …. dataset’
p.13 l.8. Remove double .. ‘shows the potential of the approach described’
p.13 l.10 ‘results obtained’ not ‘obtained results’
p.13 l.13 remove the sentence ‘This extension…’ It is superfluous and also flawed grammatically
Citation: https://doi.org/10.5194/acp-2021-759-RC1 -
AC1: 'Reply on RC1 and RC2', Mariana Adam, 04 Feb 2022
The comment was uploaded in the form of a supplement: https://acp.copernicus.org/preprints/acp-2021-759/acp-2021-759-AC1-supplement.pdf
-
RC2: 'Comment on acp-2021-759', Anonymous Referee #1, 23 Nov 2021
The manuscript deals with lidar-derived optical properties of fire smoke in the air over different parts of Europe. The observations cover fresh smoke events and events with aged smoke after long range transport (frequently from North America). The European Aerosol Research Lidar Network (EARLINET) data base is used for this study. Unfortunately, the amount of data is so low and even not of high quality (to my opinion) that clear messages and convincing conclusions cannot be drawn. I clearly see that the first author did her best, however, the available data set does not allow to write a sound scientific ‘story’ because numerous and high quality results are not available. Mariana Adam can just present some kind of a final report (of a not just very successful, big field campaign lasting over many, many years), rather than an article with well extracted results and findings. This is impossible with the used (poor) data set.
At the end, after careful reading and realizing how poor the available data set is, I cannot recommend publication. If this report would be published in its present form, most of the readers would conclude: Better not to use any EARLINET data. The amount is low and the quality is quite questionable, and in full contrast to what aerosol scientists expected when they are familiar with, e.g., the AERONET data base.
Citation: https://doi.org/10.5194/acp-2021-759-RC2
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Cited
3 citations as recorded by crossref.
- Can Forest Fires Be an Important Factor in the Reduction in Solar Power Production in India? U. Dumka et al. 10.3390/rs14030549
- Characterization of Extremely Fresh Biomass Burning Aerosol by Means of Lidar Observations B. De Rosa et al. 10.3390/rs14194984
- Combining Mie–Raman and fluorescence observations: a step forward in aerosol classification with lidar technology I. Veselovskii et al. 10.5194/amt-15-4881-2022