the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 27 Nov 2023
Aggravated surface O3 pollution primarily driven by meteorological variation in China during the early COVID-19 pandemic lockdown period
Abstract. Due to the lockdown during the COVID-19 pandemic in China from late January to early April in 2020, a significant reduction of primary air pollutants has been identified by satellite and ground observations. However, this reduction is in contrast with the increase of surface O3 concentration in many parts of China during the same period. The reasons for this contrast are studied here from two perspectives: emission changes and inter-annual meteorological variations. Based on top-down constraints of NOx emissions from TROPOMI measurements and GEOS-Chem model simulations, our analysis reveals that NOx and volatile organic compound (VOC) emission reductions as well as meteorological variations lead to 8 %, -3 %, and 1 % changes in O3 over North China, respectively. In South China, however, we find that meteorological variations cause ~30 % increases in O3, which is much larger than -1 % and 2 % changes due to VOC and NOx emission reductions, respectively, and the overall O3 increase is consistent with the surface observations. The higher temperature is the main reason that leads to the surface O3 increase in South China. Overall, inter-annual meteorological variations have a larger impact than emission reductions on the aggravated surface O3 pollution in China during the early lockdown period of COVID-19 pandemic.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-2723', Anonymous Referee #1, 11 Dec 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2723/egusphere-2023-2723-RC1-supplement.pdf
- AC1: 'Reply on RC1', Zhendong Lu, 21 Apr 2024
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RC2: 'Comment on egusphere-2023-2723', Anonymous Referee #2, 29 Feb 2024
This work investigated the reasons for the increase of surface ozone concentrations in perspectives of emission changes and meteorological variations. It’s found that meteorological variation is the major driving force to the ozone increase in South China. The paper is informative and generally well organized. My major concern is the negative bias of TROPOMI data (~20% based on previous validations), especially over urban areas, and the effect to the results due to the bias.
My detailed comments are listed below.
- Line 126-127: not clear about what this means. Do you mean the difference between NOx, NOy, and NOz? Please specify this.
- Line 166-167: is the optimization done day by day, or on a monthly basis?
- Line 216-217: the anthropogenic VOC emissions in China has grown significantly from 2010-2017, driven by solvent use. I don’t think it can be ignored.
- Line 221-222: can you elaborate more on the HCHO uncertainties?
- Figure 2. For (c), it seems that the VOC emission changes are mainly from biogenic or open biomass burning for Southeast Asia, instead of anthropogenic sources.
- Line 294: previous validations have found that TROPOMI NO2 product has negative bias of ~20%, especially over urban areas (Verhoelst et al., 2021, Judd et al., 2020, Li et al., 2021). How will this bias affect the validation and your conclusions?
References:
Verhoelst, T., Compernolle, S., Pinardi, G., Lambert, J.-C., Eskes, H. J., Eichmann, K.-U., et al. (2021). Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks. Atmospheric Measurement Techniques, 14(1), 481–510. https://doi.org/10.5194/amt-14-481-2021
Judd, L. M., Al-Saadi, J. A., Szykman, J. J., Valin, L. C., Janz, S. J., Kowalewski, M. G., et al. (2020). Evaluating Sentinel-5P TROPOMI tropospheric NO2 column densities with airborne and Pandora spectrometers near New York City and Long Island Sound. Atmospheric Measurement Techniques, 13(11), 6113–6140. https://doi.org/10.5194/amt-13-6113-2020
Li, M., McDonald, B. C., McKeen, S. A., Eskes, H., Levelt, P., Francoeur, C., Harkins, C., He, J., Barth, M., Henze, D. K., Bela, M. M., Trainer, M., de Gouw, J. A., and Frost, G. J.: Assessment of Updated Fuel-Based Emissions Inventories Over the Contiguous United States Using TROPOMI NO2 Retrievals, Journal of Geophysical Research: Atmospheres, 126, e2021JD035484, https://doi.org/10.1029/2021JD035484, 2021.
Citation: https://doi.org/10.5194/egusphere-2023-2723-RC2 - AC2: 'Reply on RC2', Zhendong Lu, 21 Apr 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-2723', Anonymous Referee #1, 11 Dec 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2723/egusphere-2023-2723-RC1-supplement.pdf
- AC1: 'Reply on RC1', Zhendong Lu, 21 Apr 2024
-
RC2: 'Comment on egusphere-2023-2723', Anonymous Referee #2, 29 Feb 2024
This work investigated the reasons for the increase of surface ozone concentrations in perspectives of emission changes and meteorological variations. It’s found that meteorological variation is the major driving force to the ozone increase in South China. The paper is informative and generally well organized. My major concern is the negative bias of TROPOMI data (~20% based on previous validations), especially over urban areas, and the effect to the results due to the bias.
My detailed comments are listed below.
- Line 126-127: not clear about what this means. Do you mean the difference between NOx, NOy, and NOz? Please specify this.
- Line 166-167: is the optimization done day by day, or on a monthly basis?
- Line 216-217: the anthropogenic VOC emissions in China has grown significantly from 2010-2017, driven by solvent use. I don’t think it can be ignored.
- Line 221-222: can you elaborate more on the HCHO uncertainties?
- Figure 2. For (c), it seems that the VOC emission changes are mainly from biogenic or open biomass burning for Southeast Asia, instead of anthropogenic sources.
- Line 294: previous validations have found that TROPOMI NO2 product has negative bias of ~20%, especially over urban areas (Verhoelst et al., 2021, Judd et al., 2020, Li et al., 2021). How will this bias affect the validation and your conclusions?
References:
Verhoelst, T., Compernolle, S., Pinardi, G., Lambert, J.-C., Eskes, H. J., Eichmann, K.-U., et al. (2021). Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks. Atmospheric Measurement Techniques, 14(1), 481–510. https://doi.org/10.5194/amt-14-481-2021
Judd, L. M., Al-Saadi, J. A., Szykman, J. J., Valin, L. C., Janz, S. J., Kowalewski, M. G., et al. (2020). Evaluating Sentinel-5P TROPOMI tropospheric NO2 column densities with airborne and Pandora spectrometers near New York City and Long Island Sound. Atmospheric Measurement Techniques, 13(11), 6113–6140. https://doi.org/10.5194/amt-13-6113-2020
Li, M., McDonald, B. C., McKeen, S. A., Eskes, H., Levelt, P., Francoeur, C., Harkins, C., He, J., Barth, M., Henze, D. K., Bela, M. M., Trainer, M., de Gouw, J. A., and Frost, G. J.: Assessment of Updated Fuel-Based Emissions Inventories Over the Contiguous United States Using TROPOMI NO2 Retrievals, Journal of Geophysical Research: Atmospheres, 126, e2021JD035484, https://doi.org/10.1029/2021JD035484, 2021.
Citation: https://doi.org/10.5194/egusphere-2023-2723-RC2 - AC2: 'Reply on RC2', Zhendong Lu, 21 Apr 2024
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Yi Wang
Daven K. Henze
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(2808 KB) - Metadata XML