the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Secondary PM decreases significantly less than NO2 emission reductions during COVID lockdown in Germany
- 1Environmental Sensing and Modeling, Technical University of Munich (TUM), Munich, Germany
- 2School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA
- 3Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- 1Environmental Sensing and Modeling, Technical University of Munich (TUM), Munich, Germany
- 2School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA
- 3Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
Abstract. This study estimates the influence of anthropogenic emission reductions on the concentration of particulate matter with a diameter smaller than 2.5 μm (PM2.5) during the 2020 lockdown period in German metropolitan areas. After accounting for meteorological effects, PM2.5 concentrations during the spring 2020 lockdown period were 5 % lower compared to the same time period in 2019. However, during the 2020 pre-lockdown period (winter), meteorology accounted for PM2.5 concentrations were 19 % lower than in 2019. Meanwhile, meteorology accounted for NO2 concentrations dropped by 23 % during the 2020 lockdown period compared to an only 9 % drop for the 2020 pre-lockdown period, both compared to 2019. Meteorology accounted for SO2 and CO concentrations show no significant changes during the 2020 lockdown period compared to 2019. GEOS-Chem (GC) simulation with a COVID-19 emission reduction scenario based on the observations (23 % reduction in NOX emission with unchanged VOC and SO2) are consistent with the small reductions of PM2.5 during the lockdown and are used to identify the underlying drivers for this. Due to being in a NOX saturated ozone production regime, GC OH radical and O3 concentrations increased (15 and 9 %, respectively) during the lockdown compared to a Business As Usual (no lockdown) scenario. The increased O3 results in increased NO3 radical concentrations, primarily during the night, despite the large reductions in NO2. Thus, the oxidative capacity of the atmosphere is increased in all three important oxidants, OH, O3, and NO3. PM nitrate formation from gas-phase nitric acid (HNO3) is decreased during the lockdown as the increased OH concentration cannot compensate for the strong reductions in NO2 resulting in decreased day-time HNO3 formation from the OH + NO2 reaction. However, night-time formation of PM nitrate from N2O5 hydrolysis is relatively unchanged. This results from the fact that increased night-time O3 results in significantly increased NO3 which roughly balances the effect of the strong NO2 reductions on N2O5 formation. Ultimately, the only small observed decrease in lockdown PM2.5 concentrations can be explained by the large contribution of night-time PM nitrate formation, generally enhanced sulfate formation and slightly decreased ammonium. This study also suggests that high PM2.5 episodes in early spring are linked to high atmospheric ammonia concentrations combined with favorable meteorological conditions of low temperature and low boundary layer height. North-West Germany is a hot-spot of NH3 emissions, primarily emitted from livestock farming and intensive agricultural activities (fertilizer application), with high NH3 concentrations in the early spring and summer months. Based on our findings, we suggest that appropriate NOX and VOC emission controls are required to limit ozone, and that should also help reduce PM2.5. Regulation of NH3 emissions, primarily from agricultural sectors, could result in significant reductions in PM2.5 pollution.
Vigneshkumar Balamurugan et al.
Status: closed
-
RC1: 'Comment on acp-2022-87', Anonymous Referee #1, 02 Mar 2022
The manuscript entitled “Secondary PM decreases significantly less than NO2 emission
reductions during COVID lockdown in Germany” by Vigneshkumar Balamurugan et al. explored the drivers of slight decrease of PM2.5 compared to NO2 emission during COVID-19 lockdown in Germany. The manuscript provides valuable information for understanding PM pollution under rigorous emission reduction measures and efficiently directing PM mitigation in the future. It is recommended that this manuscript be reconsidered for publication after major revisions.
General comments:
Line 54:” The composition of PM thus varies greatly depending on time and location; for
example, in urban areas nitrate and organic aerosol often dominate in winter time”. More cases should be given to support this sentence.
Line 133:” The fractional change in meteorology accounted for pollutant concentration between 2020 and 2019, i.e., pollutant concentration changes between 2020 and 2019 due to emission changes only” This definition is misleading. According to your definition of ΔPM2.5(obs) and ΔPM2.5(GC), the ΔPM2.5(obs,emi) should be the change of PM2.5 caused only by emission. If so, relative descriptions in the whole paper should be revised correspondingly.
Line 170: We also compared the 2019 GC and 2019 observed in-situ PM2.5 concentrations and found that the GC and observed in-situ PM2.5 concentrations were in good agreement (R > 0.5 for all metropolitan areas, except Leipzig which has a R value of 0.39) (e.g.,Fig. 6 (c), for Cologne metropolitan area).” The performance of the model is the base of further analysis. Hence, more details of the statistical evaluation of the model performance for each site should be given. In addition, the agreement R is above 0.5 for most areas and is 0.39 for Leipzig. Personally, I think the R is not good enough.
Line 273:” The increase in OH radicals results from German metropolitan areas being in a NOX saturated regime”. From BAU to lockdown period, the meteorological condition changed, which could lead to higher temperature and higher solar radiation, and this has the potential to increase OH concentration. Hence, the influence of meteorological between different period in 2020 should be considered.
Line 281:”However, higher night-time NO3 levels result in higher nighttime HNO3 production from N2O5 hydrolysis, resulting in slightly lower night-time lockdown PM nitrate compared to BAU” According to Figure 4, the change of nighttime HNO3 production from N2O5 hydrolysis is small compared to that during daytime. In addition, both of the production and sink of HNO3 should be considered to explain its influence on PM concentration.
Specific comments:
The use of “emission accounted”, and “meteorology accounted” makes the discussion part puzzled. The authors are suggested to use more clear phases.
Figure 1: The part of ”Ground-truth measurements” is misleading, it should contain the observations data from 2019 and 2020.
-
AC1: 'Reply on RC1', Vigneshkumar Balamurugan, 15 Apr 2022
Dear Reviewer,
Thank you so much for taking the time to read and review our manuscript!
Please see the attachment for our response document (a point-by-point response) and track changes document.
Sincerely,
On behalf of all co-authors, Vigneshkumar Balamurugan
-
AC1: 'Reply on RC1', Vigneshkumar Balamurugan, 15 Apr 2022
-
RC2: 'Comment on acp-2022-87', Anonymous Referee #2, 14 Mar 2022
Review of “Secondary PM decreases significantly less than NO2 emission reductions during COVID lockdown in Germany” by Balamurugan et al.
Built on their previous work, the authors investigated the role of anthropogenic emissions on PM2.5 changes during the COVID-19 lockdown in Germany. After subtracting the meteorological effects, they found that NOx emission decreased by about 20% but there were small changes in PM2.5 concentrations. By applying modeling analysis, they attributed the small decrease of PM2.5 to increased formation of sulfate and nighttime nitrate, offsetting the decreased formation of ammonium and daytime nitrate. In addition, the authors also discussed the role of NH3 emission in driving high PM2.5 episodes. Overall, the study provides some interesting results and adds insights in the formation of secondary aerosols. The methodology is reasonable and the manuscript is well-written. I think it fits well within the scope of ACP journal. I would suggest its acceptance after the following comments are well addressed.
Comments:
The study focused on PM2.5 only, so I would suggest to replace “PM” by “PM2.5” in the title.
It seems fine to fix anthropogenic emissions at 2014 in the simulations, but it will be better if the authors could add some discussion about the emission changes from 2014 to 2019.
I am still concerned about the assumption of unchanged VOC emissions in response to COVID-19 lockdown, although the authors tried to justify this treatment in their reduction scenarios. If NOx emissions from transportation sector were strongly affected during the lockdown, there is a reduction in VOC emissions as well. What are the sectors mainly accounting for VOC emissions in Germany? More discussions are needed on this issue.
The explanation of ozone increases is not quite clear. It is possible that ozone formation efficiency was increased in response to NOx reduction under NOx-saturated regime. However, this reason might not work both for daytime ozone and nighttime ozone. In the cold season, ozone could be strongly titrated by NOx emissions which maybe directly increase ozone at night. I would like the authors add some analysis on the changes of Ox (NO2+O2) that can be used to isolate the effect from weakened titration.
I am wondering if there is ambient measurement for PM2.5 components. It deserves a comparison between simulated and observed PM2.5 species concentrations.
-
AC2: 'Reply on RC2', Vigneshkumar Balamurugan, 15 Apr 2022
Dear Reviewer,
Thank you so much for taking the time to read and review our manuscript!
Please see the attachment for our response document (a point-by-point response) and track changes document.
Sincerely,
On behalf of all co-authors, Vigneshkumar Balamurugan
-
AC2: 'Reply on RC2', Vigneshkumar Balamurugan, 15 Apr 2022
-
RC3: 'Comment on acp-2022-87', Anonymous Referee #3, 17 Mar 2022
The authors present measurements from ten metropolitan areas in Germany to evaluate the impact of lockdown restrictions on air pollutant concentrations. They use the GEOS-Chem (GC) chemical transport model to simulate the pollutant concentrations for 2020 and 2019 and derive the percent changes during the lockdowns to find that although NO2 reductions were evident PM concentrations did not drastically change. Furthermore, they discuss the impacts of the NOx reductions on radical and ozone concentrations as well as PM2.5 formation and the role of NH3 emissions on PM pollution. This paper is interesting and fits well within the scope of ACP after the following comments are answered.
Main comments:
My main concern is on the assumption that the VOC emissions did not change during the lockdowns based on a limited number of published studies that only account for a small fraction of the VOCs. Given that VOCs can originate from multiple sources that vary by season and meteorology I consider that there is limited confidence in this assumption. Furthermore, VOCs will be responsible for SOA in the model and can account for a significant part of the PM mass. I consider that a sensitivity analysis of the model to VOC changes would be a more honest approach and valuable addition to this study. The response of SOA to these changes and their relative influence compared to NH3 emissions, especially during PM pollution days, would indicate whether VOCs are also an essential source of PM pollution in future scenarios.
Given that this work is based on the WRF model it would be great to see a more detailed evaluation of the model for the different gas- and particle-phase components. Evaluation of the model at high and low concentration periods from previous years and how accurately they are predicted would be of value and give some context on the uncertainty of this approach. Evaluation of the chemical composition derived by the model to ambient observations would also be important. Are there any chemically speciated measurements in Germany during this period that the authors could compare their model to? If not, has this been done in the past and what was the agreement of the model to the observations?
Other comments:
Line 51: First time that VOCs are introduced
Line 225: Which VOCs? How much of the reactivity do they represent?
Line 235: What are the expected VOC emissions during the winter in Europe?
Line 290-294: OA formation and specifically SOA could also be affected by changes in VOC emissions both of biogenic and anthropogenic nature. Further discussion here would be of value.
Line 335-337: I find this statement a stretch given the number of other sources of PM pollution.
Line 339-348: Some statistics on how many days were the “simultaneous” or “independent” would be great here not only for one region but for all regions in Germany.
Figure 6: I find this figure hard to follow and the messages are not clear to me. It would be great if the timeseries panels fit the whole page and the “simultaneous” or “independent” periods are highlighted by the background color of the graphs. Adding the temperature and RH timeseries would be great too. The authors can also include the NH3 measurements in a different panel and the background colors could guide the reader's eye’s to evaluate whether there is a good or bad agreement between PM, NH3, RH, and temperature increases. Furthermore, it would be great to see a graph that highlights what happens in different regions of Germany and some more statistics on these trends to evaluate their importance.
-
AC3: 'Reply on RC3', Vigneshkumar Balamurugan, 15 Apr 2022
Dear Reviewer,
Thank you so much for taking the time to read and review our manuscript!
Please see the attachment for our response document (a point-by-point response) and track changes document.
Sincerely,
On behalf of all co-authors, Vigneshkumar Balamurugan
-
AC3: 'Reply on RC3', Vigneshkumar Balamurugan, 15 Apr 2022
Status: closed
-
RC1: 'Comment on acp-2022-87', Anonymous Referee #1, 02 Mar 2022
The manuscript entitled “Secondary PM decreases significantly less than NO2 emission
reductions during COVID lockdown in Germany” by Vigneshkumar Balamurugan et al. explored the drivers of slight decrease of PM2.5 compared to NO2 emission during COVID-19 lockdown in Germany. The manuscript provides valuable information for understanding PM pollution under rigorous emission reduction measures and efficiently directing PM mitigation in the future. It is recommended that this manuscript be reconsidered for publication after major revisions.
General comments:
Line 54:” The composition of PM thus varies greatly depending on time and location; for
example, in urban areas nitrate and organic aerosol often dominate in winter time”. More cases should be given to support this sentence.
Line 133:” The fractional change in meteorology accounted for pollutant concentration between 2020 and 2019, i.e., pollutant concentration changes between 2020 and 2019 due to emission changes only” This definition is misleading. According to your definition of ΔPM2.5(obs) and ΔPM2.5(GC), the ΔPM2.5(obs,emi) should be the change of PM2.5 caused only by emission. If so, relative descriptions in the whole paper should be revised correspondingly.
Line 170: We also compared the 2019 GC and 2019 observed in-situ PM2.5 concentrations and found that the GC and observed in-situ PM2.5 concentrations were in good agreement (R > 0.5 for all metropolitan areas, except Leipzig which has a R value of 0.39) (e.g.,Fig. 6 (c), for Cologne metropolitan area).” The performance of the model is the base of further analysis. Hence, more details of the statistical evaluation of the model performance for each site should be given. In addition, the agreement R is above 0.5 for most areas and is 0.39 for Leipzig. Personally, I think the R is not good enough.
Line 273:” The increase in OH radicals results from German metropolitan areas being in a NOX saturated regime”. From BAU to lockdown period, the meteorological condition changed, which could lead to higher temperature and higher solar radiation, and this has the potential to increase OH concentration. Hence, the influence of meteorological between different period in 2020 should be considered.
Line 281:”However, higher night-time NO3 levels result in higher nighttime HNO3 production from N2O5 hydrolysis, resulting in slightly lower night-time lockdown PM nitrate compared to BAU” According to Figure 4, the change of nighttime HNO3 production from N2O5 hydrolysis is small compared to that during daytime. In addition, both of the production and sink of HNO3 should be considered to explain its influence on PM concentration.
Specific comments:
The use of “emission accounted”, and “meteorology accounted” makes the discussion part puzzled. The authors are suggested to use more clear phases.
Figure 1: The part of ”Ground-truth measurements” is misleading, it should contain the observations data from 2019 and 2020.
-
AC1: 'Reply on RC1', Vigneshkumar Balamurugan, 15 Apr 2022
Dear Reviewer,
Thank you so much for taking the time to read and review our manuscript!
Please see the attachment for our response document (a point-by-point response) and track changes document.
Sincerely,
On behalf of all co-authors, Vigneshkumar Balamurugan
-
AC1: 'Reply on RC1', Vigneshkumar Balamurugan, 15 Apr 2022
-
RC2: 'Comment on acp-2022-87', Anonymous Referee #2, 14 Mar 2022
Review of “Secondary PM decreases significantly less than NO2 emission reductions during COVID lockdown in Germany” by Balamurugan et al.
Built on their previous work, the authors investigated the role of anthropogenic emissions on PM2.5 changes during the COVID-19 lockdown in Germany. After subtracting the meteorological effects, they found that NOx emission decreased by about 20% but there were small changes in PM2.5 concentrations. By applying modeling analysis, they attributed the small decrease of PM2.5 to increased formation of sulfate and nighttime nitrate, offsetting the decreased formation of ammonium and daytime nitrate. In addition, the authors also discussed the role of NH3 emission in driving high PM2.5 episodes. Overall, the study provides some interesting results and adds insights in the formation of secondary aerosols. The methodology is reasonable and the manuscript is well-written. I think it fits well within the scope of ACP journal. I would suggest its acceptance after the following comments are well addressed.
Comments:
The study focused on PM2.5 only, so I would suggest to replace “PM” by “PM2.5” in the title.
It seems fine to fix anthropogenic emissions at 2014 in the simulations, but it will be better if the authors could add some discussion about the emission changes from 2014 to 2019.
I am still concerned about the assumption of unchanged VOC emissions in response to COVID-19 lockdown, although the authors tried to justify this treatment in their reduction scenarios. If NOx emissions from transportation sector were strongly affected during the lockdown, there is a reduction in VOC emissions as well. What are the sectors mainly accounting for VOC emissions in Germany? More discussions are needed on this issue.
The explanation of ozone increases is not quite clear. It is possible that ozone formation efficiency was increased in response to NOx reduction under NOx-saturated regime. However, this reason might not work both for daytime ozone and nighttime ozone. In the cold season, ozone could be strongly titrated by NOx emissions which maybe directly increase ozone at night. I would like the authors add some analysis on the changes of Ox (NO2+O2) that can be used to isolate the effect from weakened titration.
I am wondering if there is ambient measurement for PM2.5 components. It deserves a comparison between simulated and observed PM2.5 species concentrations.
-
AC2: 'Reply on RC2', Vigneshkumar Balamurugan, 15 Apr 2022
Dear Reviewer,
Thank you so much for taking the time to read and review our manuscript!
Please see the attachment for our response document (a point-by-point response) and track changes document.
Sincerely,
On behalf of all co-authors, Vigneshkumar Balamurugan
-
AC2: 'Reply on RC2', Vigneshkumar Balamurugan, 15 Apr 2022
-
RC3: 'Comment on acp-2022-87', Anonymous Referee #3, 17 Mar 2022
The authors present measurements from ten metropolitan areas in Germany to evaluate the impact of lockdown restrictions on air pollutant concentrations. They use the GEOS-Chem (GC) chemical transport model to simulate the pollutant concentrations for 2020 and 2019 and derive the percent changes during the lockdowns to find that although NO2 reductions were evident PM concentrations did not drastically change. Furthermore, they discuss the impacts of the NOx reductions on radical and ozone concentrations as well as PM2.5 formation and the role of NH3 emissions on PM pollution. This paper is interesting and fits well within the scope of ACP after the following comments are answered.
Main comments:
My main concern is on the assumption that the VOC emissions did not change during the lockdowns based on a limited number of published studies that only account for a small fraction of the VOCs. Given that VOCs can originate from multiple sources that vary by season and meteorology I consider that there is limited confidence in this assumption. Furthermore, VOCs will be responsible for SOA in the model and can account for a significant part of the PM mass. I consider that a sensitivity analysis of the model to VOC changes would be a more honest approach and valuable addition to this study. The response of SOA to these changes and their relative influence compared to NH3 emissions, especially during PM pollution days, would indicate whether VOCs are also an essential source of PM pollution in future scenarios.
Given that this work is based on the WRF model it would be great to see a more detailed evaluation of the model for the different gas- and particle-phase components. Evaluation of the model at high and low concentration periods from previous years and how accurately they are predicted would be of value and give some context on the uncertainty of this approach. Evaluation of the chemical composition derived by the model to ambient observations would also be important. Are there any chemically speciated measurements in Germany during this period that the authors could compare their model to? If not, has this been done in the past and what was the agreement of the model to the observations?
Other comments:
Line 51: First time that VOCs are introduced
Line 225: Which VOCs? How much of the reactivity do they represent?
Line 235: What are the expected VOC emissions during the winter in Europe?
Line 290-294: OA formation and specifically SOA could also be affected by changes in VOC emissions both of biogenic and anthropogenic nature. Further discussion here would be of value.
Line 335-337: I find this statement a stretch given the number of other sources of PM pollution.
Line 339-348: Some statistics on how many days were the “simultaneous” or “independent” would be great here not only for one region but for all regions in Germany.
Figure 6: I find this figure hard to follow and the messages are not clear to me. It would be great if the timeseries panels fit the whole page and the “simultaneous” or “independent” periods are highlighted by the background color of the graphs. Adding the temperature and RH timeseries would be great too. The authors can also include the NH3 measurements in a different panel and the background colors could guide the reader's eye’s to evaluate whether there is a good or bad agreement between PM, NH3, RH, and temperature increases. Furthermore, it would be great to see a graph that highlights what happens in different regions of Germany and some more statistics on these trends to evaluate their importance.
-
AC3: 'Reply on RC3', Vigneshkumar Balamurugan, 15 Apr 2022
Dear Reviewer,
Thank you so much for taking the time to read and review our manuscript!
Please see the attachment for our response document (a point-by-point response) and track changes document.
Sincerely,
On behalf of all co-authors, Vigneshkumar Balamurugan
-
AC3: 'Reply on RC3', Vigneshkumar Balamurugan, 15 Apr 2022
Vigneshkumar Balamurugan et al.
Vigneshkumar Balamurugan et al.
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 483 | 190 | 18 | 691 | 10 | 12 |
- HTML: 483
- PDF: 190
- XML: 18
- Total: 691
- BibTeX: 10
- EndNote: 12
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1