Effects of transport on a biomass burning plume from Indochina during EMeRGe-Asia identified by WRF-Chem
- 1Research Center for Environmental Changes, Academia Sinica, Taipei, Taiwan
- 2Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
- 3Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research, Karlsruhe, Germany
- 4Multiphase Chemistry Department, Max Planck Institute for Chemistry, Mainz, Germany
- 5Particle Chemistry Department, Max Planck Institute for Chemistry, Mainz, Germany
- 6Institute of Environmental Physics, University Bremen, Bremen, Germany
- 7Institute for Atmospheric Physics, Johannes Gutenberg University, Mainz, Germany
- 8Institute of Energy and Climate Research IEK-8, Forschungszentrum Jülich, Jülich, Germany
- anow at: Faculty of Physics and Earth Sciences, Leipzig Institute for Meteorology, University of Leipzig/Experimental Aerosol and Cloud Microphysics Department, Leibniz Institute for Tropospheric Research, Leipzig, Germany
- 1Research Center for Environmental Changes, Academia Sinica, Taipei, Taiwan
- 2Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
- 3Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research, Karlsruhe, Germany
- 4Multiphase Chemistry Department, Max Planck Institute for Chemistry, Mainz, Germany
- 5Particle Chemistry Department, Max Planck Institute for Chemistry, Mainz, Germany
- 6Institute of Environmental Physics, University Bremen, Bremen, Germany
- 7Institute for Atmospheric Physics, Johannes Gutenberg University, Mainz, Germany
- 8Institute of Energy and Climate Research IEK-8, Forschungszentrum Jülich, Jülich, Germany
- anow at: Faculty of Physics and Earth Sciences, Leipzig Institute for Meteorology, University of Leipzig/Experimental Aerosol and Cloud Microphysics Department, Leibniz Institute for Tropospheric Research, Leipzig, Germany
Abstract. The Indochina biomass burning (BB) season in springtime has a substantial environmental impact on the surrounding areas in Asia. In this study, we evaluated the environmental impact of a major long-range BB transport event on 19 March 2018 (a flight of the HALO research aircraft, flight F0319) preceded by a minor event on 17 March 2018 (flight F0317). Aircraft data obtained during the campaign in Asia of the Effect of Megacities on the transport and transformation of pollutants on the Regional to Global scales (EMeRGe) were available between 12 March and 7 April 2018. In the F0319, results of 1-min mean carbon monoxide (CO), ozone (O3), acetone (ACE), acetonitrile (ACN), organic aerosol (OA) and black carbon aerosol (BC) concentrations were up to 312.0 ppb, 79.0 ppb, 3.0 ppb, 0.6 ppb, 6.4 µg m−3, 2.5 µg m−3 respectively, during the flight, which passed through the BB plume transport layer (BPTL) between the elevation of 2000–4000 m over the East China Sea (ECS). During F0319, CO, O3, ACE, ACN, OA and BC maximum of the 1 minute average concentrations were higher in the BPTL by 109.0 ppb, 8.0 ppb, 1.0 ppb, 0.3 ppb, 3.0 µg m−3 and 1.3 µg m−3 compared to flight F0317, respectively. Sulfate aerosol, rather than OA, showed the highest concentration at low altitudes (<1000 m) in both flights F0317 and F0319 resulting from the continental outflow in the ECS.
The transport of BB aerosols from Indochina and its impacts on the downstream area was evaluated using a WRF-Chem model. Over the ECS, the simulated BB contribution demonstrated an increasing trend from the lowest values on 17 March 2018 to the highest values on 18 and 19 March 2018 for CO, fine particulate matter (PM2.5), OA, BC, hydroxyl radicals (OH), nitrogen oxides (NOx), total reactive nitrogen (NOy), and O3; by contrast, the variation of J(O1D) decreased as the BB plume’s contribution increased over the ECS. In the low boundary layer (<1000 m), the BB plume’s contribution to most species in the remote downstream areas was <20 %. However, at the BPTL, the contribution of the long-range transported BB plume was as high as 30–80 % for most of the species (NOy, NOx, PM2.5, BC, OH, O3, and CO) over South China (SC), Taiwan, and the ECS. BB aerosols were identified as a potential source of cloud condensation nuclei, and the simulation results indicated that the transported BB plume had an effect on cloud water formation over SC and the ECS on 19 March 2018. The combination of BB aerosol enhancement with cloud water resulted in a reduction of incoming shortwave radiation at the surface in SC and the ECS which potentially has significant regional climate implications.
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Chuan-Yao Lin et al.
Status: closed
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RC1: 'Comment on acp-2022-517', Anonymous Referee #1, 28 Oct 2022
In this paper the WRF-Chem atmospheric chemistry model is used to study the impact of biomass burning plumes in southeastern Asia. Overall the paper is well written. But there are a couple of major issues that need to be addressed before the paper considered for publication:
The fire plume rise and its simulation by WRF-Chem aren’t discussed in the paper, thought there is extensive analysis of the vertical distribution of the biomass burning plumes. The fire plume rise is an important process by which aerosol and gaseous species from wildland fires are injected into the free troposphere, where they can be transported to long distances. WRF-Chem has an 1D plume rise parameterization (Freitas et al.). It isn’t clear if this scheme was used, and how it performed, associated uncertainties and their imapact on the findings on the results presented here.
Figure 12 shows the effect of the smoke plume on cloud water. However, I can’t find any description of the model configuration on how the aerosol feedback on the meteorology is simulated in this study. There are several feedback mechanisms of the aerosols on meteorology. Although WRF-Chem contains a few parameterizations to simulate these processes, large uncertainties remain with respect accurate representation of the aerosol-radiation-microphysics interactions. Authors present the results for such complex phenomena in a single graph without thorough discussion and sensitivity analysis (e.g. direct vs. indirect feedback). Moreover, given the relatively low aerosol concentrations in the smoke plumes analyzed here the sensitivity of the simulated cloud water concentrations to smoke plumes seem to be overly large.
The concluding statements (L575-579) aren’t necessarily based on the findings from this study.
Minor comments:
It’d be helpful to add a Table to list the WRF-Chem model configuration. Some of the settings are listed in the text. Information on the lateral boundary conditions for the chemical species, their cycling between the subsequent simulations and fire plumerise are missing. How the wet removal of the gas and aerosol species are parameterized in the model?
The paper doesn’t provide any information about the measurement uncertainties for the chemical species. For instance, the AMS data (OA, sulfate concentrations reported here) usually have significant uncertainty due to the collection efficiency and cutoff size (<1micron).
L156: For WRF-Chem the more recent paper (Powers et al.) can be also cited.
L272: What do you mean by “stable”?
Chapter 3.3: this chapter needs to be shortened.
References:
- R. Freitas, K. M. Longo, R. Chatfield, D. Latham, M. Dias, M. O. Andreae, et al.Including the sub-grid scale plume rise of vegetation fires in low resolution atmospheric transport models.Atmospheric Chemistry and Physics 2007 Vol. 7 Issue 13 Pages 3385-3398
- G. Powers, J. B. Klemp, W. C. Skamarock, C. A. Davis, J. Dudhia, D. O. Gill, et al.THE WEATHER RESEARCH AND FORECASTING MODEL Overview, System Efforts, and Future Directions.Bulletin of the American Meteorological Society 2017 Vol. 98 Issue 8 Pages 1717-1737
- AC1: 'Reply on RC1', Chuan-yao Lin, 10 Dec 2022
-
RC2: 'Comment on acp-2022-517', Anonymous Referee #2, 30 Oct 2022
General comments:
The authors present chemical signature and transport of biomass burning plumes originating from Indochina peninsula and extending to northeast, using WRF-Chem simulations supported with airborne observations during EMeRGe-Asia campaign in March 2018. The meteorological field and transport mechanism are well described. The model captures the enhanced CO, BC, and OA, by comparing the simulations with and without the biomass burning influences, but tended to overestimate observations, pointing to the possibility that the FINNv1.5 emission inventory had high biases. The model analysis was extended to J values, HOx radicals, and CCN formation to estimate contributions from biomass burning.
Observational data to assess the regional impact of biomass burning plumes originating from Indochina peninsula have been still rare and thus the aircraft observations and the associated model simulations presented in this manuscript are important. However, more clarification is needed to justify some of the conclusions. First, the authors should be able to specify the locations and date of the fires likely affecting the studied events. Precipitation and cloud processes during the long-range transport should be mentioned even if negligible, to characterize potential loss of aerosol species and to fully attribute the differences to the emissions. The degrees of overestimation should be quantitatively assessed and mentioned in the abstract more clearly.
Second, details of chemical pathways that enhanced the OH and HO2 levels in the model should be described. This part is purely from model results - to prvide associated observational evidence is recommended (also for J values, cloud condensation nuclei and cloud water). Overall, revisions are necessary before considering publication.Specific comments.
1. Line 101. Similar to what?
2. Line 154. The authors state that OH and HO2 are listed in the HALO aircraft data but in fact they were not observed. (only HO2+RO2)
3. Line 178. Is acetone dominant for KET? For example, MACR and MVK from isoprene chemistry could also contribute? Emissions of acetone from anthropogenic and biomass burning should be briefly discussed.
4. Lines 184, 190, and 412. MICS-Asia III and TEDS emissions were used - for which year?
5. Line 200. Can the authors describe whether the intensity of biomass burning in Indochina peninsula during this particular period in 2018 was at normal level or not, in comparison to other years?
6. Line 203. It seems that the center of the high pressure system is present over the Japan (Japan Sea), rather than Korea.
7. Line 269. SO2 enhancement is attributed to Japan - perhaps volcanoes have contributed?
8. Line 311. Carmichael
9. Line 312. Figure 6b indicates biomass burning influence is spread to the north of 30 degN.
10. Line 338. As ACN and ACE contain oxygen and nitrogen in their molecules, they are not hydrocarbons.
11. Line 350 and 352. Use uppercase 1 for J(O1D).
12. Lines 351 and 479. Whether aerosols increase or decrease J(O1D) will be dependent on the assumed single-scattering albedo. Any evidence from direct observations of the J values?
13. Line 404. It is better to confirm that the CO hemispheric baseline is not overestimated.
14. Line 416. It is important to confirm that OA and BC have not been removed by wet deposition on the way of transport, to better attribute the model's overestimation to emissions.
15. Line 447. "detraining" is difficult to understand.
16. Line 457. The sentence starting with" The variation trend of PM2.5 ..." needs to be rewritten.
17. Line 471. Which processes were responsible for the OH and HO2 enhancement? How well VOCs emissions and chemistry were treated to describe the OH and HO2 budget?
18. Line 513. Any observational evidence of CCN or cloud water enhancement, attributable to the biomass burning plume?
19. Figure 3a, b: As the highest CO area is distant from Indochina peninsula on the day, the authors should be able to state the possible locations and date of fires producing the plumes.- AC2: 'Reply on RC2', Chuan-yao Lin, 10 Dec 2022
Status: closed
-
RC1: 'Comment on acp-2022-517', Anonymous Referee #1, 28 Oct 2022
In this paper the WRF-Chem atmospheric chemistry model is used to study the impact of biomass burning plumes in southeastern Asia. Overall the paper is well written. But there are a couple of major issues that need to be addressed before the paper considered for publication:
The fire plume rise and its simulation by WRF-Chem aren’t discussed in the paper, thought there is extensive analysis of the vertical distribution of the biomass burning plumes. The fire plume rise is an important process by which aerosol and gaseous species from wildland fires are injected into the free troposphere, where they can be transported to long distances. WRF-Chem has an 1D plume rise parameterization (Freitas et al.). It isn’t clear if this scheme was used, and how it performed, associated uncertainties and their imapact on the findings on the results presented here.
Figure 12 shows the effect of the smoke plume on cloud water. However, I can’t find any description of the model configuration on how the aerosol feedback on the meteorology is simulated in this study. There are several feedback mechanisms of the aerosols on meteorology. Although WRF-Chem contains a few parameterizations to simulate these processes, large uncertainties remain with respect accurate representation of the aerosol-radiation-microphysics interactions. Authors present the results for such complex phenomena in a single graph without thorough discussion and sensitivity analysis (e.g. direct vs. indirect feedback). Moreover, given the relatively low aerosol concentrations in the smoke plumes analyzed here the sensitivity of the simulated cloud water concentrations to smoke plumes seem to be overly large.
The concluding statements (L575-579) aren’t necessarily based on the findings from this study.
Minor comments:
It’d be helpful to add a Table to list the WRF-Chem model configuration. Some of the settings are listed in the text. Information on the lateral boundary conditions for the chemical species, their cycling between the subsequent simulations and fire plumerise are missing. How the wet removal of the gas and aerosol species are parameterized in the model?
The paper doesn’t provide any information about the measurement uncertainties for the chemical species. For instance, the AMS data (OA, sulfate concentrations reported here) usually have significant uncertainty due to the collection efficiency and cutoff size (<1micron).
L156: For WRF-Chem the more recent paper (Powers et al.) can be also cited.
L272: What do you mean by “stable”?
Chapter 3.3: this chapter needs to be shortened.
References:
- R. Freitas, K. M. Longo, R. Chatfield, D. Latham, M. Dias, M. O. Andreae, et al.Including the sub-grid scale plume rise of vegetation fires in low resolution atmospheric transport models.Atmospheric Chemistry and Physics 2007 Vol. 7 Issue 13 Pages 3385-3398
- G. Powers, J. B. Klemp, W. C. Skamarock, C. A. Davis, J. Dudhia, D. O. Gill, et al.THE WEATHER RESEARCH AND FORECASTING MODEL Overview, System Efforts, and Future Directions.Bulletin of the American Meteorological Society 2017 Vol. 98 Issue 8 Pages 1717-1737
- AC1: 'Reply on RC1', Chuan-yao Lin, 10 Dec 2022
-
RC2: 'Comment on acp-2022-517', Anonymous Referee #2, 30 Oct 2022
General comments:
The authors present chemical signature and transport of biomass burning plumes originating from Indochina peninsula and extending to northeast, using WRF-Chem simulations supported with airborne observations during EMeRGe-Asia campaign in March 2018. The meteorological field and transport mechanism are well described. The model captures the enhanced CO, BC, and OA, by comparing the simulations with and without the biomass burning influences, but tended to overestimate observations, pointing to the possibility that the FINNv1.5 emission inventory had high biases. The model analysis was extended to J values, HOx radicals, and CCN formation to estimate contributions from biomass burning.
Observational data to assess the regional impact of biomass burning plumes originating from Indochina peninsula have been still rare and thus the aircraft observations and the associated model simulations presented in this manuscript are important. However, more clarification is needed to justify some of the conclusions. First, the authors should be able to specify the locations and date of the fires likely affecting the studied events. Precipitation and cloud processes during the long-range transport should be mentioned even if negligible, to characterize potential loss of aerosol species and to fully attribute the differences to the emissions. The degrees of overestimation should be quantitatively assessed and mentioned in the abstract more clearly.
Second, details of chemical pathways that enhanced the OH and HO2 levels in the model should be described. This part is purely from model results - to prvide associated observational evidence is recommended (also for J values, cloud condensation nuclei and cloud water). Overall, revisions are necessary before considering publication.Specific comments.
1. Line 101. Similar to what?
2. Line 154. The authors state that OH and HO2 are listed in the HALO aircraft data but in fact they were not observed. (only HO2+RO2)
3. Line 178. Is acetone dominant for KET? For example, MACR and MVK from isoprene chemistry could also contribute? Emissions of acetone from anthropogenic and biomass burning should be briefly discussed.
4. Lines 184, 190, and 412. MICS-Asia III and TEDS emissions were used - for which year?
5. Line 200. Can the authors describe whether the intensity of biomass burning in Indochina peninsula during this particular period in 2018 was at normal level or not, in comparison to other years?
6. Line 203. It seems that the center of the high pressure system is present over the Japan (Japan Sea), rather than Korea.
7. Line 269. SO2 enhancement is attributed to Japan - perhaps volcanoes have contributed?
8. Line 311. Carmichael
9. Line 312. Figure 6b indicates biomass burning influence is spread to the north of 30 degN.
10. Line 338. As ACN and ACE contain oxygen and nitrogen in their molecules, they are not hydrocarbons.
11. Line 350 and 352. Use uppercase 1 for J(O1D).
12. Lines 351 and 479. Whether aerosols increase or decrease J(O1D) will be dependent on the assumed single-scattering albedo. Any evidence from direct observations of the J values?
13. Line 404. It is better to confirm that the CO hemispheric baseline is not overestimated.
14. Line 416. It is important to confirm that OA and BC have not been removed by wet deposition on the way of transport, to better attribute the model's overestimation to emissions.
15. Line 447. "detraining" is difficult to understand.
16. Line 457. The sentence starting with" The variation trend of PM2.5 ..." needs to be rewritten.
17. Line 471. Which processes were responsible for the OH and HO2 enhancement? How well VOCs emissions and chemistry were treated to describe the OH and HO2 budget?
18. Line 513. Any observational evidence of CCN or cloud water enhancement, attributable to the biomass burning plume?
19. Figure 3a, b: As the highest CO area is distant from Indochina peninsula on the day, the authors should be able to state the possible locations and date of fires producing the plumes.- AC2: 'Reply on RC2', Chuan-yao Lin, 10 Dec 2022
Chuan-Yao Lin et al.
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