the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Measurement Report: Small effect of regional sources on black carbon properties and concentrations in Southern Sweden background air
- 1Division of Nuclear Physics, Lund University, Box 118, 221 00 Lund, Sweden
- 2Environment Department, City of Malmö, 208 50 Malmö, Sweden
- 3Department of Environmental Research, Center for Physical Sciences and Technology, Savanorių ave. 231, 02300 Vilnius, Lithuania
- 4Department of Environmental Science, iClimate, Aarhus University, Roskilde, Denmark
- 5Laboratory of Atmospheric Chemistry, Paul Scherrer Institute (PSI), 5232 Villigen PSI, Switzerland
- 6Ergonomics and Aerosol Technology, Lund University, Box 118, 221 00 Lund, Sweden
- anow at: Swedish Environmental Protection Agency, 10648 Stockholm, Sweden
- bnow at: National Research Centre for the Working Environment, 2100 Copenhagen, Denmark
- 1Division of Nuclear Physics, Lund University, Box 118, 221 00 Lund, Sweden
- 2Environment Department, City of Malmö, 208 50 Malmö, Sweden
- 3Department of Environmental Research, Center for Physical Sciences and Technology, Savanorių ave. 231, 02300 Vilnius, Lithuania
- 4Department of Environmental Science, iClimate, Aarhus University, Roskilde, Denmark
- 5Laboratory of Atmospheric Chemistry, Paul Scherrer Institute (PSI), 5232 Villigen PSI, Switzerland
- 6Ergonomics and Aerosol Technology, Lund University, Box 118, 221 00 Lund, Sweden
- anow at: Swedish Environmental Protection Agency, 10648 Stockholm, Sweden
- bnow at: National Research Centre for the Working Environment, 2100 Copenhagen, Denmark
Abstract. Soot, or black carbon (BC), aerosol is a major climate forcer with severe health effects. The impacts depend strongly on particle number concentration, size and mixing state. This work reports on two field campaigns at nearby urban and rural sites, 65 km apart, in southern Sweden during late summer 2018. BC was measured using a single particle soot photometer (SP2) and Aethalometers (AE33). Differences in BC concentrations between the sites are driven primarily by local traffic emissions. Equivalent and refractory BC mass concentrations at the urban site were on average a factor 2.2 and 2.5 higher than at the rural site. Peaks in rush hour BC mass concentrations at the urban site were up to a factor ~4 higher than the background levels. The number fraction of particles containing a soot core was significantly higher in the city. BC particles at the urban site were on average smaller by mass and had less coating owing to fresh traffic emissions. The organic components of the fresh plumes were similar in mass spectral signature to “hydrocarbon-like organic aerosol” (HOA), commonly associated with traffic. Despite the intense local traffic (~30 000 vehicles passing per day), PM1, including organic aerosol, was dominated by aged continental air masses even at the curbside site. The fraction of thickly coated particles at the urban site was highly correlated with the mass concentrations of all measured chemical species of PM1, consistent with aged, internally mixed aerosol. Trajectory analysis for the whole year showed that air masses arriving at the rural site from eastern Europe contained approximately double the amount of BC compared to air masses from western Europe. Furthermore, BC from the largest region emissions in the Malmö/Copenhagen urban area transported to the rural site is discernable above background levels only when precipitation events are excluded.
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Erik Ahlberg et al.
Status: closed
-
RC1: 'Comment on acp-2022-156', Anonymous Referee #1, 03 Jun 2022
REVIEW Preprint acp-2022-156
The work presented by Ahlberg and coauthors investigates the variability of black carbon properties at an urban and rural site in southern Sweden. This manuscript fulfils the requirements of a “Measurement report” since it treats specific aerosol measurements and processes confined in a restricted area and time. However, the manuscript is structured as a full “Research Article” and falls a bit short on certain aspects of data analysis and interpretation. The final consequence is that the motivations, methods and goals are not always clear. I recommend major revision and resubmission. I hope that the major and specific comments listed below will help the authors in the rebuttal process.
MAJOR COMMENTS
First, there is an evident problem with sections and subsections. The article is organized without subsections; thus the assimilation of the scientific message becomes particularly complicated. The structure should be modified including subsections in the “methods” and result “sections”.
The overall motivation behind the paper is unclear. The authors mentioned climatic and health implications, but these are described very generally without a local (Swedish) perspective. The manuscript does not provide enough measurement time to address climatic issues but could draw a nice, even if very short, picture of air quality. I think this should be the redline of the entire manuscript and should include as motivation: the health impact of aerosol emission in Sweden (e.g. death per year), the history of Swedish reduction strategies and subsequent effects.
There is nothing that can be practically done about this, but the fact that the urban and background measurements are not simultaneous is the weakest point of the manuscript. The authors should convince the reader that the background aerosol population do not change drastically from July to October. Till that point, the results shown in Figures 1,2,3 could be affected by many atmospheric processes such as precipitation, and changes in emission large scale circulation. Potentially due to this problem, the goal of the authors is not always clear.
Technically speaking there are some additional soft spots. It is very much not clear how the absorption data were treated and corrected, as a consequence the data are quite questionable. See specific comments. Moreover, the Aethalometer data are not essential to the scope of the paper since the SP2 provides mass concentration, size distribution and mixing state proxy.
It must be described more clearly when ACTRIS data (absorption and chemical composition) were used. The reader realizes only towards the end of the manuscript that a year-long dataset was used. No description or introduction to these data is ever given.
SPECIFIC COMMENTS
L17: health effect is mentioned also in the introduction, but it is never really explained.
L34 It is an odd way to start a paper. I would remove the first sentence since it might apply to all atmospheric species.
L36: this is the motivation of your work and also the first sentence of the abstract. Still, I have zero ideas about how BC affects the climate and human health.
L40-41: I would provide an example for all properties or not report any example. Listing only the lensing effect does not add any relevant information since absorption enhancement is not a topic of the paper.
L46-47: it appears like the reference for transport and deposited dose is missing.
L50: Health and toxicity are mentioned a couple of times, but it is not yet explained how fundamental properties are connected to health.
L55-56: main take-home message is summarized here. I think it does not belong to the introduction. Potentially makes more sense as a final statement of the abstract.
L60-61: Please provide some evidence supporting your statement. July September is a long-time gap. I expect different dilution due to boundary layer height (I imagine lower temperature in October), different precipitation and washout, or different chemistry due to shorter sunlight duration…
L71-72: SP2 is not yet introduced. Move this last sentence to the instrumentation section. Since you mention turbulent flux. Can you estimate a loss fraction?
L74: This chapter is extremely long and complex. I would add a table listing the deployed instruments and measured variables at the two sites.
L80: is good practice to provide the name, city and country of the manufacturer. Missing everywhere in the manuscript.
L87: is this the saving rate of the SP2? A person not familiar with the SP2 would not understand what was does it mean. I think is not so important to be mentioned.
L90-91: What do you mean by “not satisfactory”? Was the reason connected to a wrong sizing of the DMA or a decrease in the performances of the SP2 (decreasing laser power, misalignment)? Are then the data valid?
L98: 62 nm is a very small diameter, but those particles will not contribute significantly to the total mass. My issue with this choice is that most, if not the totality, of previous SP2 paper, reports rBC particles starting from 80-90 nm…which I might consider the safe side. Considering that you do not provide any counting efficiency, I do not understand why you chose such a low cut-off.
L104: the coating is not directly measured by these two detectors. I would use caution with these statements since people might think that the SP2 directly provides coating thickness of BC-containing particles, which is well far from reality.
L106-111: I am genuinely confused by this explanation. Are talking of delay-time or LEO-fit. To me, it appears like a mixture of the two. Please rewrite it. If the position-sensitive detector was not used is not worth mentioning, since it adds confusion.
L114: since you mention Weingartner…what Cref value was used? Was it calculated for this specific aethalometer or taken from Weingartner or Collaud-Coen or Zanatta? These papers are based on AE31 though and not AE33.
L125-133: Please add the chemical species identified by the SP-AMS. If all presented rBC mass is derived from the SP2 the calibration for refractory material is even described? In what sense the SP-AMS at the urban site did not provide robust results (instrument malfunction, wrong calibration)? Is this the reason why all AMS graphs at the urban site are plotted with arbitrary units? I have the feeling that this issue and the SP2 calibration problem (L90) undermine the credibility (accuracy, reproducibility) of the dataset and, as a consequence, the full manuscript. The authors should explain in more detail why and how the SP2 and SP-AMS data are still reliable despite the technical issues.
L145: just a comment to point out that 64 nm of electric-mobility diameter does not correspond to 64 nm of mass equivalent diameter.
L171: back trajectories are not shown
RESULTS AND DISCUSSION
L183-191: There is no context to your observation. Up to me, these are low concentration for being an urban site.
L186: it is already clear from its concentration that the curbside is not extremely polluted. At what percentage difference you would define extreme pollution? And based on what process?
F1: provide error bars. Does the analysis include the weekends?
L191: MAC of BC is not the only reason for the difference in AAE. Different AAE might be caused by a change in the chemical composition of absorbing aerosol or a change in the relative concentration of aerosol absorbing more light at the lower wavelength. If this is the case, MACbc will remain the same while AAE of total aerosol will increase.
L200-212: As it is also pointed out in the text, the rBC number fraction mostly depends on the diameter quantification limits of both the SP2 and especially DMA rather than on aerosol properties. So, I am not sure what should I retain out of this subchapter.
L213-223: Here several factors must be considered and I strongly believe that the SP2 size cut is not the problem. Even if the SP2 size range could be easily accounted for by fitting a lognormal to the size distribution. Anyhow, no details are reported about the correction used for the AE-33 and I believe the problems are more connected with absorption calculation rather than the SP2 detection range. I recalculated the MAC from the values reported in Table 1. I recalculated Babs by multiplying Mebc by 7.77 m2/g. Then I calculated MAC as the ratio of Babs and MrBC. So, I obtain MAC values above 25 m2/g. This value is very similar to the mass attenuation coefficient used in the past to convert directly attenuation coefficients to eBC in the old AE31. So, I cannot say what happened here exactly, but I think that no Cref or correction was applied. I think you need to do a bit of extra thinking here and reconsider the relevance and accuracy of eBC measurements.
L2017: was the 10-20% calculated or is it just a gentle guess? If it is calculated why is not applied to the measurements? Lensing effect cannot be excluded, but I hardly think that this is the main reason behind the eBC-rBC difference: You are using a MAC 1.6 times smaller than Swedish ambient values (Martinsson), while an additional 10-20% is coming from size cut. There is too much uncertainty to speak about absorption amplification.
L220-223: so why not use the Martinsson MAC? There is no explanation behind the choice of 7.77 m2/g.
F2: what is the small window in the plot?
L234: the fact that aerosol diameters are affected by cloud processing is true. I wonder how this is relevant to your study. If this is a general statement, please provide at least some references.
F3: legend should simply describe what is shown in the graph. Avoid adding interpretation of results, this belongs to the text. I am not sure what the crosses indicate. I imagine that whiskers are 10-90 percentile…missing
L242: very few people know what is the broadband channel. Since it is not essential information to interpret your result, I would remove it in the result section.
L245: these effective density measurements are interesting. You could show the mass distribution for all selected diameters…it would help to understand your text. I might have missed this info, but did you measure effective density at the rural site? Do you see this bimodal distribution?
L271: At what altitude the back trajectories are passing over Malmo?
F4: what is this arbitrary unit?
L275: No actual description is given for the one-year-long dataset. It is very confusing, especially without a dedicated subsection with numbering and title.
L300-320: did you use the one-year-long dataset for the malmo influence? Not clear to me. Specify the use of the 1year dataset. If not, I am not very persuaded that your 15 days measurements could show or not show any systematic impact of Malmo emission on background aerosol concentration.
L331: ok, but why?
L339: first-time HR-ToF-AMS is mentioned
L349-352: what are regional traffic sources? You clearly show that the urban environment is impacted by traffic; so, emission reduction policies will benefit the urban population. But it will have a less evident impact on rural locations. I find this final statement a bit confusing, I suggest rephrasing.
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RC2: 'Comment on acp-2022-156', Anonymous Referee #2, 27 Jun 2022
The article of Ahlberg et al. investigated black carbon concentrations, size distributions, mixing state and sources in two measurement campaigns in Southern Sweden; urban and rural locations. They measured BC by a single particle soot photometer and aethalometer, and complemented the measurements by number size distribution and PM1 chemical composition measurements. In addition to examine the characteristics of BC, the aim of this study was to investigate the contribution of regional sources and long-range transport to the observed BC concentrations.
BC concentrations were larger at the urban site than at the rural site, especially during the traffic rush hour. Also the number of particles having BC core was larger at the urban site and BC particles were smaller in size and had thinner coating. Based on the trajectory analysis, air masses coming from Eastern Europe comprised twice as much BC compared to Western Europe. Nearby Malmö/Copenhagen region impacted rural site BC concentrations only to some extent.
This article presented new results from the field measurements and had enough conclusions for a measurement report. However, the paper is missing a lot of details (for example the measurement sites and periods) and is therefore partly unclear for the reader. This paper merits publication in ACP measurement reports after addressing the comments given below.
General comments
The paper is confusing for the reader as there are so many different measurement periods that are not clearly described in text. For example, the rooftop urban site is only mentioned in one sentence even though the results from the rooftop are shown in supplemental material and discusses in text. Also, the one year measurements for BC are not mentioned in methods section at all. A table or figure listing all sites, instruments and measurement periods would help the reader to get an overall picture of the dataset utilized in the paper.
Specific comments
Title: The title does not cover all the aspects of the text. Based on the title, the study focuses on background air and the effect of regional sources, whereas to me, the object of this paper is much broader. I suggest considering to change the title to reflect better the whole study.
Abstract
lines 22-23: …. higher than the background levels… higher than background levels at the urban site or at the rural site? Specify
line 25: fresh plumes of traffic?
line 25: “hydrocarbon-like organic aerosol”, why parentheses?
Methods
lines 64 and 70: PM cut-off was different at urban and rural site (PM2.5 vs PM10). How much that impacted the BC results, can you estimate?
lines 64-65: add details of rooftop measurements
lines 71-72: Why SP2 sampling system is described here only for the rural site?
line 76: "During the latter part of the urban campaign, chemically resolved particle constituents were measured simultaneously at both sites…" were there simultaneous measurements only for the SP-AMS? Also for AE?
lines 128-129: It’s very difficult to understand why the mass concentrations from the SP-AMS could not be calculated at the urban site as the SMPS number size distributions can be converted to mass size distributions. Were there some issues with the SPMS data as well?
lines 133-139: traffic plumes, did you have any gas monitors (NOx, CO2, CO) that could have been used to indicate traffic plumes as well? How was the diurnal distribution of traffic plumes, were they detected only during rush hours?
line 157: APM was run only during five days in spring 2019; how comparable is this data to summer/autumn 2018 data in terms of weather and traffic volume/fleet?
lines 168-170: why the trajectory analysis was carried out only for the rural site, why not both sites?
Results and discussion
line 184-185: traffic intensity; any figure on that?
line 192: “The AAE is similar between the sites with small differences…” To me, 1.13 and 1.24 are not that similar. Could you speculate more the reasons for the difference? Also, AAE is smaller at traffic site than at rural site, is this typical trend?
lines 244-257: bimodal distribution, could you discuss more on the sources of two modes?
lines 270-271: “It was clear that SW winds had more occurrences of high eBC than e.g. NW winds.” I somewhat disagree with this sentence. It is clear that the occurrence of SW winds was higher but eBC concentrations are difficult to compare based on Fig. 5 since the occurrence of NW winds is so low. However, Fig 6. shows nicely larger concentration of eBC related to the SE winds.
lines 314-315, correlation of non-refractory-PM1 and thickly coated BC fraction (Fig 8); why 24-hour averaged data with only 15 data points? Why not for example 1-hour averaged data? Was it because of SP2 data?
line 317: non-refractory-PM1 (dominated by secondary material); HOA related to traffic plumes was discussed earlier but there is no data showing that organics were mostly secondary. Could you add some contributions for primary (HOA?) and secondary OA?
Summary and conclusions
lines 341-342 “…but composed of a small fraction of the total aerosol.” How much?
Supplemental material
Fig. S4: Add instruments and time-resolution of data
Technical corrections
line 185: …levels show are similar… correct
line 339: change HR-ToF-AMS to SP-AMS
- AC1: 'Comment on acp-2022-156', Erik Ahlberg, 19 Sep 2022
Status: closed
-
RC1: 'Comment on acp-2022-156', Anonymous Referee #1, 03 Jun 2022
REVIEW Preprint acp-2022-156
The work presented by Ahlberg and coauthors investigates the variability of black carbon properties at an urban and rural site in southern Sweden. This manuscript fulfils the requirements of a “Measurement report” since it treats specific aerosol measurements and processes confined in a restricted area and time. However, the manuscript is structured as a full “Research Article” and falls a bit short on certain aspects of data analysis and interpretation. The final consequence is that the motivations, methods and goals are not always clear. I recommend major revision and resubmission. I hope that the major and specific comments listed below will help the authors in the rebuttal process.
MAJOR COMMENTS
First, there is an evident problem with sections and subsections. The article is organized without subsections; thus the assimilation of the scientific message becomes particularly complicated. The structure should be modified including subsections in the “methods” and result “sections”.
The overall motivation behind the paper is unclear. The authors mentioned climatic and health implications, but these are described very generally without a local (Swedish) perspective. The manuscript does not provide enough measurement time to address climatic issues but could draw a nice, even if very short, picture of air quality. I think this should be the redline of the entire manuscript and should include as motivation: the health impact of aerosol emission in Sweden (e.g. death per year), the history of Swedish reduction strategies and subsequent effects.
There is nothing that can be practically done about this, but the fact that the urban and background measurements are not simultaneous is the weakest point of the manuscript. The authors should convince the reader that the background aerosol population do not change drastically from July to October. Till that point, the results shown in Figures 1,2,3 could be affected by many atmospheric processes such as precipitation, and changes in emission large scale circulation. Potentially due to this problem, the goal of the authors is not always clear.
Technically speaking there are some additional soft spots. It is very much not clear how the absorption data were treated and corrected, as a consequence the data are quite questionable. See specific comments. Moreover, the Aethalometer data are not essential to the scope of the paper since the SP2 provides mass concentration, size distribution and mixing state proxy.
It must be described more clearly when ACTRIS data (absorption and chemical composition) were used. The reader realizes only towards the end of the manuscript that a year-long dataset was used. No description or introduction to these data is ever given.
SPECIFIC COMMENTS
L17: health effect is mentioned also in the introduction, but it is never really explained.
L34 It is an odd way to start a paper. I would remove the first sentence since it might apply to all atmospheric species.
L36: this is the motivation of your work and also the first sentence of the abstract. Still, I have zero ideas about how BC affects the climate and human health.
L40-41: I would provide an example for all properties or not report any example. Listing only the lensing effect does not add any relevant information since absorption enhancement is not a topic of the paper.
L46-47: it appears like the reference for transport and deposited dose is missing.
L50: Health and toxicity are mentioned a couple of times, but it is not yet explained how fundamental properties are connected to health.
L55-56: main take-home message is summarized here. I think it does not belong to the introduction. Potentially makes more sense as a final statement of the abstract.
L60-61: Please provide some evidence supporting your statement. July September is a long-time gap. I expect different dilution due to boundary layer height (I imagine lower temperature in October), different precipitation and washout, or different chemistry due to shorter sunlight duration…
L71-72: SP2 is not yet introduced. Move this last sentence to the instrumentation section. Since you mention turbulent flux. Can you estimate a loss fraction?
L74: This chapter is extremely long and complex. I would add a table listing the deployed instruments and measured variables at the two sites.
L80: is good practice to provide the name, city and country of the manufacturer. Missing everywhere in the manuscript.
L87: is this the saving rate of the SP2? A person not familiar with the SP2 would not understand what was does it mean. I think is not so important to be mentioned.
L90-91: What do you mean by “not satisfactory”? Was the reason connected to a wrong sizing of the DMA or a decrease in the performances of the SP2 (decreasing laser power, misalignment)? Are then the data valid?
L98: 62 nm is a very small diameter, but those particles will not contribute significantly to the total mass. My issue with this choice is that most, if not the totality, of previous SP2 paper, reports rBC particles starting from 80-90 nm…which I might consider the safe side. Considering that you do not provide any counting efficiency, I do not understand why you chose such a low cut-off.
L104: the coating is not directly measured by these two detectors. I would use caution with these statements since people might think that the SP2 directly provides coating thickness of BC-containing particles, which is well far from reality.
L106-111: I am genuinely confused by this explanation. Are talking of delay-time or LEO-fit. To me, it appears like a mixture of the two. Please rewrite it. If the position-sensitive detector was not used is not worth mentioning, since it adds confusion.
L114: since you mention Weingartner…what Cref value was used? Was it calculated for this specific aethalometer or taken from Weingartner or Collaud-Coen or Zanatta? These papers are based on AE31 though and not AE33.
L125-133: Please add the chemical species identified by the SP-AMS. If all presented rBC mass is derived from the SP2 the calibration for refractory material is even described? In what sense the SP-AMS at the urban site did not provide robust results (instrument malfunction, wrong calibration)? Is this the reason why all AMS graphs at the urban site are plotted with arbitrary units? I have the feeling that this issue and the SP2 calibration problem (L90) undermine the credibility (accuracy, reproducibility) of the dataset and, as a consequence, the full manuscript. The authors should explain in more detail why and how the SP2 and SP-AMS data are still reliable despite the technical issues.
L145: just a comment to point out that 64 nm of electric-mobility diameter does not correspond to 64 nm of mass equivalent diameter.
L171: back trajectories are not shown
RESULTS AND DISCUSSION
L183-191: There is no context to your observation. Up to me, these are low concentration for being an urban site.
L186: it is already clear from its concentration that the curbside is not extremely polluted. At what percentage difference you would define extreme pollution? And based on what process?
F1: provide error bars. Does the analysis include the weekends?
L191: MAC of BC is not the only reason for the difference in AAE. Different AAE might be caused by a change in the chemical composition of absorbing aerosol or a change in the relative concentration of aerosol absorbing more light at the lower wavelength. If this is the case, MACbc will remain the same while AAE of total aerosol will increase.
L200-212: As it is also pointed out in the text, the rBC number fraction mostly depends on the diameter quantification limits of both the SP2 and especially DMA rather than on aerosol properties. So, I am not sure what should I retain out of this subchapter.
L213-223: Here several factors must be considered and I strongly believe that the SP2 size cut is not the problem. Even if the SP2 size range could be easily accounted for by fitting a lognormal to the size distribution. Anyhow, no details are reported about the correction used for the AE-33 and I believe the problems are more connected with absorption calculation rather than the SP2 detection range. I recalculated the MAC from the values reported in Table 1. I recalculated Babs by multiplying Mebc by 7.77 m2/g. Then I calculated MAC as the ratio of Babs and MrBC. So, I obtain MAC values above 25 m2/g. This value is very similar to the mass attenuation coefficient used in the past to convert directly attenuation coefficients to eBC in the old AE31. So, I cannot say what happened here exactly, but I think that no Cref or correction was applied. I think you need to do a bit of extra thinking here and reconsider the relevance and accuracy of eBC measurements.
L2017: was the 10-20% calculated or is it just a gentle guess? If it is calculated why is not applied to the measurements? Lensing effect cannot be excluded, but I hardly think that this is the main reason behind the eBC-rBC difference: You are using a MAC 1.6 times smaller than Swedish ambient values (Martinsson), while an additional 10-20% is coming from size cut. There is too much uncertainty to speak about absorption amplification.
L220-223: so why not use the Martinsson MAC? There is no explanation behind the choice of 7.77 m2/g.
F2: what is the small window in the plot?
L234: the fact that aerosol diameters are affected by cloud processing is true. I wonder how this is relevant to your study. If this is a general statement, please provide at least some references.
F3: legend should simply describe what is shown in the graph. Avoid adding interpretation of results, this belongs to the text. I am not sure what the crosses indicate. I imagine that whiskers are 10-90 percentile…missing
L242: very few people know what is the broadband channel. Since it is not essential information to interpret your result, I would remove it in the result section.
L245: these effective density measurements are interesting. You could show the mass distribution for all selected diameters…it would help to understand your text. I might have missed this info, but did you measure effective density at the rural site? Do you see this bimodal distribution?
L271: At what altitude the back trajectories are passing over Malmo?
F4: what is this arbitrary unit?
L275: No actual description is given for the one-year-long dataset. It is very confusing, especially without a dedicated subsection with numbering and title.
L300-320: did you use the one-year-long dataset for the malmo influence? Not clear to me. Specify the use of the 1year dataset. If not, I am not very persuaded that your 15 days measurements could show or not show any systematic impact of Malmo emission on background aerosol concentration.
L331: ok, but why?
L339: first-time HR-ToF-AMS is mentioned
L349-352: what are regional traffic sources? You clearly show that the urban environment is impacted by traffic; so, emission reduction policies will benefit the urban population. But it will have a less evident impact on rural locations. I find this final statement a bit confusing, I suggest rephrasing.
-
RC2: 'Comment on acp-2022-156', Anonymous Referee #2, 27 Jun 2022
The article of Ahlberg et al. investigated black carbon concentrations, size distributions, mixing state and sources in two measurement campaigns in Southern Sweden; urban and rural locations. They measured BC by a single particle soot photometer and aethalometer, and complemented the measurements by number size distribution and PM1 chemical composition measurements. In addition to examine the characteristics of BC, the aim of this study was to investigate the contribution of regional sources and long-range transport to the observed BC concentrations.
BC concentrations were larger at the urban site than at the rural site, especially during the traffic rush hour. Also the number of particles having BC core was larger at the urban site and BC particles were smaller in size and had thinner coating. Based on the trajectory analysis, air masses coming from Eastern Europe comprised twice as much BC compared to Western Europe. Nearby Malmö/Copenhagen region impacted rural site BC concentrations only to some extent.
This article presented new results from the field measurements and had enough conclusions for a measurement report. However, the paper is missing a lot of details (for example the measurement sites and periods) and is therefore partly unclear for the reader. This paper merits publication in ACP measurement reports after addressing the comments given below.
General comments
The paper is confusing for the reader as there are so many different measurement periods that are not clearly described in text. For example, the rooftop urban site is only mentioned in one sentence even though the results from the rooftop are shown in supplemental material and discusses in text. Also, the one year measurements for BC are not mentioned in methods section at all. A table or figure listing all sites, instruments and measurement periods would help the reader to get an overall picture of the dataset utilized in the paper.
Specific comments
Title: The title does not cover all the aspects of the text. Based on the title, the study focuses on background air and the effect of regional sources, whereas to me, the object of this paper is much broader. I suggest considering to change the title to reflect better the whole study.
Abstract
lines 22-23: …. higher than the background levels… higher than background levels at the urban site or at the rural site? Specify
line 25: fresh plumes of traffic?
line 25: “hydrocarbon-like organic aerosol”, why parentheses?
Methods
lines 64 and 70: PM cut-off was different at urban and rural site (PM2.5 vs PM10). How much that impacted the BC results, can you estimate?
lines 64-65: add details of rooftop measurements
lines 71-72: Why SP2 sampling system is described here only for the rural site?
line 76: "During the latter part of the urban campaign, chemically resolved particle constituents were measured simultaneously at both sites…" were there simultaneous measurements only for the SP-AMS? Also for AE?
lines 128-129: It’s very difficult to understand why the mass concentrations from the SP-AMS could not be calculated at the urban site as the SMPS number size distributions can be converted to mass size distributions. Were there some issues with the SPMS data as well?
lines 133-139: traffic plumes, did you have any gas monitors (NOx, CO2, CO) that could have been used to indicate traffic plumes as well? How was the diurnal distribution of traffic plumes, were they detected only during rush hours?
line 157: APM was run only during five days in spring 2019; how comparable is this data to summer/autumn 2018 data in terms of weather and traffic volume/fleet?
lines 168-170: why the trajectory analysis was carried out only for the rural site, why not both sites?
Results and discussion
line 184-185: traffic intensity; any figure on that?
line 192: “The AAE is similar between the sites with small differences…” To me, 1.13 and 1.24 are not that similar. Could you speculate more the reasons for the difference? Also, AAE is smaller at traffic site than at rural site, is this typical trend?
lines 244-257: bimodal distribution, could you discuss more on the sources of two modes?
lines 270-271: “It was clear that SW winds had more occurrences of high eBC than e.g. NW winds.” I somewhat disagree with this sentence. It is clear that the occurrence of SW winds was higher but eBC concentrations are difficult to compare based on Fig. 5 since the occurrence of NW winds is so low. However, Fig 6. shows nicely larger concentration of eBC related to the SE winds.
lines 314-315, correlation of non-refractory-PM1 and thickly coated BC fraction (Fig 8); why 24-hour averaged data with only 15 data points? Why not for example 1-hour averaged data? Was it because of SP2 data?
line 317: non-refractory-PM1 (dominated by secondary material); HOA related to traffic plumes was discussed earlier but there is no data showing that organics were mostly secondary. Could you add some contributions for primary (HOA?) and secondary OA?
Summary and conclusions
lines 341-342 “…but composed of a small fraction of the total aerosol.” How much?
Supplemental material
Fig. S4: Add instruments and time-resolution of data
Technical corrections
line 185: …levels show are similar… correct
line 339: change HR-ToF-AMS to SP-AMS
- AC1: 'Comment on acp-2022-156', Erik Ahlberg, 19 Sep 2022
Erik Ahlberg et al.
Data sets
Ahlberg et al 2022 ISSA figure data Erik Ahlberg https://doi.org/10.5281/zenodo.6559236
Erik Ahlberg et al.
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