Articles | Volume 23, issue 17
https://doi.org/10.5194/acp-23-9745-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-23-9745-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
01 Sep 2023
Research article |
| 01 Sep 2023
| 01 Sep 2023
Rapid O3 assimilations – Part 2: Tropospheric O3 changes accompanied by declining NOx emissions in the USA and Europe in 2005–2020
Rui Zhu
School of Earth and Space Sciences, University of Science and
Technology of China, Hefei, Anhui 230026, China
Zhaojun Tang
School of Earth and Space Sciences, University of Science and
Technology of China, Hefei, Anhui 230026, China
Xiaokang Chen
School of Earth and Space Sciences, University of Science and
Technology of China, Hefei, Anhui 230026, China
Xiong Liu
Center for Astrophysics | Harvard & Smithsonian, Cambridge, MA 02138, USA
School of Earth and Space Sciences, University of Science and
Technology of China, Hefei, Anhui 230026, China
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Cited articles
Boleti, E., Hueglin, C., Grange, S. K., Prévôt, A. S. H., and Takahama, S.: Temporal and spatial analysis of ozone concentrations in Europe based on timescale decomposition and a multi-clustering approach, Atmos. Chem. Phys., 20, 9051–9066, https://doi.org/10.5194/acp-20-9051-2020, 2020.
Chen, J., Jiang, Z., Li, R., Liao, C., Miyazaki, K., and Jones, D. B. A.:
Large discrepancy between observed and modeled wintertime tropospheric NO2
variabilities due to COVID-19 controls in China, Environ. Res. Lett., 17,
035007, https://doi.org/10.1088/1748-9326/ac4ec0, 2022.
Chen, X., Jiang, Z., Shen, Y., Li, R., Fu, Y., Liu, J., Han, H., Liao, H.,
Cheng, X., Jones, D. B. A., Worden, H., and Abad, G. G.: Chinese Regulations
Are Working—Why Is Surface Ozone Over Industrialized Areas Still High?
Applying Lessons From Northeast US Air Quality Evolution, Geophys. Res. Lett., 48, e2021GL092816, https://doi.org/10.1029/2021gl092816, 2021.
Crippa, M., Janssens-Maenhout, G., Dentener, F., Guizzardi, D., Sindelarova, K., Muntean, M., Van Dingenen, R., and Granier, C.: Forty years of improvements in European air quality: regional policy-industry interactions with global impacts, Atmos. Chem. Phys., 16, 3825–3841, https://doi.org/10.5194/acp-16-3825-2016, 2016.
Di, Q., Amini, H., Shi, L., Kloog, I., Silvern, R., Kelly, J., Sabath, M.
B., Choirat, C., Koutrakis, P., Lyapustin, A., Wang, Y., Mickley, L. J., and
Schwartz, J.: Assessing NO2 Concentration and Model Uncertainty with High
Spatiotemporal Resolution across the Contiguous United States Using Ensemble
Model Averaging, Environ. Sci. Technol., 54, 1372–1384,
https://doi.org/10.1021/acs.est.9b03358, 2020.
EEA (European Environment Agency): Surface O3 measurements, AirBase [data set], https://discomap.eea.europa.eu/map/fme/AirQualityExport.htm (last access: 22 August 2023), 2023.
Han, W., He, T.-L., Tang, Z., Wang, M., Jones, D., and Jiang, Z.: A comparative analysis for a deep learning model (hyDL-CO v1.0) and Kalman filter to predict CO concentrations in China, Geosci. Model Dev., 15, 4225–4237, https://doi.org/10.5194/gmd-15-4225-2022, 2022.
He, T.-L., Jones, D. B. A., Miyazaki, K., Huang, B., Liu, Y., Jiang, Z.,
White, E. C., Worden, H. M., and Worden, J. R.: Deep learning to evaluate US
NOx emissions using surface ozone predictions, J. Geophys. Res.-Atmos., 127,
e2021JD035597, https://doi.org/10.1029/2021jd035597, 2022.
Hoesly, R. M., Smith, S. J., Feng, L., Klimont, Z., Janssens-Maenhout, G., Pitkanen, T., Seibert, J. J., Vu, L., Andres, R. J., Bolt, R. M., Bond, T. C., Dawidowski, L., Kholod, N., Kurokawa, J.-I., Li, M., Liu, L., Lu, Z., Moura, M. C. P., O'Rourke, P. R., and Zhang, Q.: Historical (1750–2014) anthropogenic emissions of reactive gases and aerosols from the Community Emissions Data System (CEDS), Geosci. Model Dev., 11, 369–408, https://doi.org/10.5194/gmd-11-369-2018, 2018.
Huang, G., Liu, X., Chance, K., Yang, K., Bhartia, P. K., Cai, Z., Allaart, M., Ancellet, G., Calpini, B., Coetzee, G. J. R., Cuevas-Agulló, E., Cupeiro, M., De Backer, H., Dubey, M. K., Fuelberg, H. E., Fujiwara, M., Godin-Beekmann, S., Hall, T. J., Johnson, B., Joseph, E., Kivi, R., Kois, B., Komala, N., König-Langlo, G., Laneve, G., Leblanc, T., Marchand, M., Minschwaner, K. R., Morris, G., Newchurch, M. J., Ogino, S.-Y., Ohkawara, N., Piters, A. J. M., Posny, F., Querel, R., Scheele, R., Schmidlin, F. J., Schnell, R. C., Schrems, O., Selkirk, H., Shiotani, M., Skrivánková, P., Stübi, R., Taha, G., Tarasick, D. W., Thompson, A. M., Thouret, V., Tully, M. B., Van Malderen, R., Vömel, H., von der Gathen, P., Witte, J. C., and Yela, M.: Validation of 10-year SAO OMI Ozone Profile (PROFOZ) product using ozonesonde observations, Atmos. Meas. Tech., 10, 2455–2475, https://doi.org/10.5194/amt-10-2455-2017, 2017.
Jiang, Z.: KPP module for tagged-O3 simulation, Version 1, Zenodo [code], https://doi.org/10.5281/zenodo.7545944, 2023.
Jiang, Z., Worden, J. R., Jones, D. B. A., Lin, J.-T., Verstraeten, W. W., and Henze, D. K.: Constraints on Asian ozone using Aura TES, OMI and Terra MOPITT, Atmos. Chem. Phys., 15, 99–112, https://doi.org/10.5194/acp-15-99-2015, 2015.
Jiang, Z., McDonald, B. C., Worden, H., Worden, J. R., Miyazaki, K., Qu, Z.,
Henze, D. K., Jones, D. B. A., Arellano, A. F., Fischer, E. V., Zhu, L., and
Boersma, K. F.: Unexpected slowdown of US pollutant emission reduction in
the past decade, P. Natl. Acad. Sci. USA, 115, 5099–5104,
https://doi.org/10.1073/pnas.1801191115, 2018.
Jiang, Z., Zhu, R., Miyazaki, K., McDonald, B. C., Klimont, Z., Zheng, B.,
Boersma, K. F., Zhang, Q., Worden, H., Worden, J. R., Henze, D. K., Jones,
D. B. A., Denier van der Gon, H. A. C., and Eskes, H.: Decadal Variabilities
in Tropospheric Nitrogen Oxides Over United States, Europe, and China, J.
Geophys. Res.-Atmos., 127, e2021JD035872, https://doi.org/10.1029/2021jd035872, 2022.
Laughner, J. L. and Cohen, R. C.: Direct observation of changing NOx
lifetime in North American cities, Science, 366, 723–727,
https://doi.org/10.1126/science.aax6832, 2019.
Li, K., Jacob, D. J., Liao, H., Zhu, J., Shah, V., Shen, L., Bates, K. H.,
Zhang, Q., and Zhai, S.: A two-pollutant strategy for improving ozone and
particulate air quality in China, Nat. Geosci., 12, 906–910,
https://doi.org/10.1038/s41561-019-0464-x, 2019.
Li, M., Zhang, Q., Kurokawa, J.-I., Woo, J.-H., He, K., Lu, Z., Ohara, T., Song, Y., Streets, D. G., Carmichael, G. R., Cheng, Y., Hong, C., Huo, H., Jiang, X., Kang, S., Liu, F., Su, H., and Zheng, B.: MIX: a mosaic Asian anthropogenic emission inventory under the international collaboration framework of the MICS-Asia and HTAP, Atmos. Chem. Phys., 17, 935–963, https://doi.org/10.5194/acp-17-935-2017, 2017.
Liu, X., Bhartia, P. K., Chance, K., Spurr, R. J. D., and Kurosu, T. P.: Ozone profile retrievals from the Ozone Monitoring Instrument, Atmos. Chem. Phys., 10, 2521–2537, https://doi.org/10.5194/acp-10-2521-2010, 2010.
Macdonald, E., Otero, N., and Butler, T.: A comparison of long-term trends in observations and emission inventories of NOx, Atmos. Chem. Phys., 21, 4007–4023, https://doi.org/10.5194/acp-21-4007-2021, 2021.
Parrish, D. D., Law, K. S., Staehelin, J., Derwent, R., Cooper, O. R.,
Tanimoto, H., Volz-Thomas, A., Gilge, S., Scheel, H. E., Steinbacher, M.,
and Chan, E.: Lower tropospheric ozone at northern midlatitudes: Changing
seasonal cycle, Geophys. Res. Lett., 40, 1631–1636, https://doi.org/10.1002/grl.50303, 2013.
Petetin, H., Thouret, V., Fontaine, A., Sauvage, B., Athier, G., Blot, R., Boulanger, D., Cousin, J.-M., and Nédélec, P.: Characterising tropospheric O3 and CO around Frankfurt over the period 1994–2012 based on MOZAIC–IAGOS aircraft measurements, Atmos. Chem. Phys., 16, 15147–15163, https://doi.org/10.5194/acp-16-15147-2016, 2016.
Qu, Z., Jacob, D. J., Silvern, R. F., Shah, V., Campbell, P. C., Valin, L.
C., and Murray, L. T.: US COVID-19 Shutdown Demonstrates Importance of
Background NO2 in Inferring NOx Emissions From Satellite NO2 Observations, Geophys. Res. Lett., 48, e2021GL092783, https://doi.org/10.1029/2021GL092783, 2021.
Seltzer, K. M., Shindell, D. T., Kasibhatla, P., and Malley, C. S.: Magnitude, trends, and impacts of ambient long-term ozone exposure in the United States from 2000 to 2015, Atmos. Chem. Phys., 20, 1757–1775, https://doi.org/10.5194/acp-20-1757-2020, 2020.
Shen, L., Mickley, L. J., and Tai, A. P. K.: Influence of synoptic patterns on surface ozone variability over the eastern United States from 1980 to 2012, Atmos. Chem. Phys., 15, 10925–10938, https://doi.org/10.5194/acp-15-10925-2015, 2015.
Tang, Z., Chen, J., and Jiang, Z.: Discrepancy in assimilated atmospheric CO over East Asia in 2015–2020 by assimilating satellite and surface CO measurements, Atmos. Chem. Phys., 22, 7815–7826, https://doi.org/10.5194/acp-22-7815-2022, 2022.
The International GEOS-Chem User Community: GEOS-Chem, Version 12.8.1, Zenodo [code], https://doi.org/10.5281/zenodo.3837666, 2020.
Trickl, T., Vogelmann, H., Ries, L., and Sprenger, M.: Very high stratospheric influence observed in the free troposphere over the northern Alps – just a local phenomenon?, Atmos. Chem. Phys., 20, 243–266, https://doi.org/10.5194/acp-20-243-2020, 2020.
US EPA (Environmental Protection Agency): Overview of the Clean Air Act and Air Pollution, https://www.epa.gov/clean-air-act-overview (last access: 22 August 2023), 2023a.
US EPA (Environmental Protection Agency): Surface O3 measurements, AQS [data set], https://aqs.epa.gov/aqsweb/airdata/download_files.html#Raw (last access: 22 August 2023), 2023b.
van der Werf, G. R., Randerson, J. T., Giglio, L., Collatz, G. J., Mu, M., Kasibhatla, P. S., Morton, D. C., DeFries, R. S., Jin, Y., and van Leeuwen, T. T.: Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009), Atmos. Chem. Phys., 10, 11707–11735, https://doi.org/10.5194/acp-10-11707-2010, 2010.
Wang, X., Fu, T. M., Zhang, L., Lu, X., Liu, X., Amnuaylojaroen, T., Latif,
M. T., Ma, Y., Zhang, L., Feng, X., Zhu, L., Shen, H., and Yang, X.: Rapidly
Changing Emissions Drove Substantial Surface and Tropospheric Ozone
Increases Over Southeast Asia, Geophys. Res. Lett., 49, e2022GL100223,
https://doi.org/10.1029/2022gl100223, 2022.
Wespes, C., Hurtmans, D., Clerbaux, C., Boynard, A., and Coheur, P.-F.: Decrease in tropospheric O3 levels in the Northern Hemisphere observed by IASI, Atmos. Chem. Phys., 18, 6867–6885, https://doi.org/10.5194/acp-18-6867-2018, 2018.
Xue, L., Ding, A., Cooper, O., Huang, X., Wang, W., Zhou, D., Wu, Z.,
McClure-Begley, A., Petropavlovskikh, I., Andreae, M. O., and Fu, C.: ENSO
and Southeast Asian biomass burning modulate subtropical trans-Pacific ozone
transport, Natl. Sci. Rev., 8, nwaa132, https://doi.org/10.1093/nsr/nwaa132, 2021.
Yan, Y., Pozzer, A., Ojha, N., Lin, J., and Lelieveld, J.: Analysis of European ozone trends in the period 1995–2014, Atmos. Chem. Phys., 18, 5589–5605, https://doi.org/10.5194/acp-18-5589-2018, 2018.
Yang, K., Liu, X., and Bhartia, P.: OMI/Aura Vertical Ozone (O3) Profile (PROFOZ), Aura Validation Data Center (AVDC) [data set], NASA GSFC, https://avdc.gsfc.nasa.gov/pub/data/satellite/Aura/OMI/V03/L2/OMPROFOZ/ (last access: 22 August 2023), 2023.
Zheng, B., Zhang, Q., Tong, D., Chen, C., Hong, C., Li, M., Geng, G., Lei, Y., Huo, H., and He, K.: Resolution dependence of uncertainties in gridded emission inventories: a case study in Hebei, China, Atmos. Chem. Phys., 17, 921–933, https://doi.org/10.5194/acp-17-921-2017, 2017.
Zhu, R., Tang, Z., Chen, X., Liu, X. and Jiang, Z.: Zhu, R., Tang, Z., Chen, X., Jiang, Z., and Liu, X.: Rapid assimilations of O3 observations – Part 1: methodology and tropospheric O3 changes in China in 2015–2020, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2023-35, in review, 2023.
Ziemke, J. R., Oman, L. D., Strode, S. A., Douglass, A. R., Olsen, M. A., McPeters, R. D., Bhartia, P. K., Froidevaux, L., Labow, G. J., Witte, J. C., Thompson, A. M., Haffner, D. P., Kramarova, N. A., Frith, S. M., Huang, L.-K., Jaross, G. R., Seftor, C. J., Deland, M. T., and Taylor, S. L.: Trends in global tropospheric ozone inferred from a composite record of TOMS/OMI/MLS/OMPS satellite measurements and the MERRA-2 GMI simulation, Atmos. Chem. Phys., 19, 3257–3269, https://doi.org/10.5194/acp-19-3257-2019, 2019.
Short summary
Ozone Monitoring Instrument (OMI) and surface O3 observations are used to investigate the changes in tropospheric O3 in the USA and Europe in 2005–2020. The surface-based assimilations show limited changes in surface and tropospheric column O3. The OMI-based assimilations show larger decreases in tropospheric O3 columns in 2010–2014, related to a decline in free-tropospheric NO2. Analysis suggests limited impacts of local emissions decline on tropospheric O3 over the USA and Europe in 2005–2020.
Ozone Monitoring Instrument (OMI) and surface O3 observations are used to investigate the...
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