Articles | Volume 23, issue 7
https://doi.org/10.5194/acp-23-4577-2023
© 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-23-4577-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Apr 2023
Research article |
| 14 Apr 2023
| 14 Apr 2023
Identifying and accounting for the Coriolis effect in satellite NO2 observations and emission estimates
School of Physics and Astronomy, University of Leicester, Leicester, UK
Roger Timmis
Environment Agency, c/o Lancaster University, Lancaster, UK
Emma J. S. Ferranti
School of Engineering, University of Birmingham, Edgbaston, UK
Joshua D. Vande Hey
School of Physics and Astronomy, University of Leicester, Leicester, UK
Centre for Environmental Health and Sustainability, University of Leicester, Leicester, UK
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Cited articles
Åkerblom, F.: Recherches sur les courants les plus bas de l'atmosphère
au-dessus de Paris, par F. Åkerblom, E. Berling, 1908. a
Anema, J. C. S.: An automated approach to estimate carbon monoxide emissions
from steel plants by utilizing TROPOMI satellite measurements, Thesis, TU Delft, http://resolver.tudelft.nl/uuid:bedc2f78-3f43-4e3c-aa49-532fdc9d2110, 2021. a
Beirle, S., Boersma, K. F., Platt, U., Lawrence, M. G., and Wagner, T.:
Megacity Emissions and Lifetimes of Nitrogen Oxides Probed from Space,
Science, 333, 1737–1739, https://doi.org/10.1126/science.1207824, 2011. a, b, c, d
Beirle, S., Borger, C., Dorner, S., Li, A., Hu, Z. K., Liu, F., Wang, Y., and
Wagner, T.: Pinpointing nitrogen oxide emissions from space, Science
Advances, 5, https://doi.org/10.1126/sciadv.aax9800, 2019. a
Beirle, S., Borger, C., Dörner, S., Eskes, H., Kumar, V., de Laat, A., and Wagner, T.: Catalog of NOx emissions from point sources as derived from the divergence of the NO2 flux for TROPOMI, Earth Syst. Sci. Data, 13, 2995–3012, https://doi.org/10.5194/essd-13-2995-2021, 2021. a, b
Clarisse, L., Van Damme, M., Clerbaux, C., and Coheur, P.-F.: Tracking down global NH3 point sources with wind-adjusted superresolution, Atmos. Meas. Tech., 12, 5457–5473, https://doi.org/10.5194/amt-12-5457-2019, 2019. a
Dammers, E., McLinden, C. A., Griffin, D., Shephard, M. W., Van Der Graaf, S., Lutsch, E., Schaap, M., Gainairu-Matz, Y., Fioletov, V., Van Damme, M., Whitburn, S., Clarisse, L., Cady-Pereira, K., Clerbaux, C., Coheur, P. F., and Erisman, J. W.: NH3 emissions from large point sources derived from CrIS and IASI satellite observations, Atmos. Chem. Phys., 19, 12261–12293, https://doi.org/10.5194/acp-19-12261-2019, 2019. a
de Foy, B., Wilkins, J. L., Lu, Z., Streets, D. G., and Duncan, B. N.: Model
evaluation of methods for estimating surface emissions and chemical lifetimes
from satellite data, Atmos. Environ., 98, 66–77,
https://doi.org/10.1016/j.atmosenv.2014.08.051, 2014. a, b
de Foy, B., Lu, Z., Streets, D. G., Lamsal, L. N., and Duncan, B. N.: Estimates
of power plant NOx emissions and lifetimes from OMI NO2 satellite retrievals,
Atmos. Environ., 116, 1–11,
https://doi.org/10.1016/j.atmosenv.2015.05.056, 2015. a, b, c, d
Ekman, V. W.: On the influence of the earth's rotation on ocean-currents, Ark. Mat. Astr. Fys., 2, 1–52,
1905. a
Eskes, H., van Geffen, J., Sneep, M., Veefkind, P., Niemeijer, S., and Zehner, C.: S5P Nitrogen Dioxide v02.03.01 intermediate reprocessing on the S5P-PAL system, S5P-PAL Data Portal [data set], https://data-portal.s5p-pal.com/products/no2.html, last access: July 2022. a
Eskom: Matimba Power Station Emissions reports, https://www.eskom.co.za/dataportal/emissions/ael/matimba-c2/, last access: 1 July 2022. a
Global Energy Observatory, Google, KTH Royal Institute of Technology in Stockholm, Enipedia, World Resources Institute, 2018: Global Power Plant Database, World Resources Institute [data set], https://datasets.wri.org/dataset/globalpowerplantdatabase, last access: 1 July 2022. a
Goldberg, D. L., Lu, Z. F., Streets, D. G., de Foy, B., Griffin, D., McLinden,
C. A., Lamsal, L. N., Krotkov, N. A., and Eskes, H.: Enhanced Capabilities of
TROPOMI NO2: Estimating NOx from North American Cities and Power Plants,
Environ. Sci. Technol., 53, 12594–12601,
https://doi.org/10.1021/acs.est.9b04488, 2019. a, b, c, d
Goldberg, D. L., Anenberg, S. C., Griffin, D., McLinden, C. A., Lu, Z., and
Streets, D. G.: Disentangling the Impact of the COVID-19 Lockdowns on Urban
NO2 From Natural Variability, Geophys. Res. Lett., 47, 1–11,
https://doi.org/10.1029/2020gl089269, 2020. a
Hakkarainen, J., Szeląg, M. E., Ialongo, I., Retscher, C., Oda, T., and Crisp,
D.: Analyzing nitrogen oxides to carbon dioxide emission ratios from space: A
case study of Matimba Power Station in South Africa, Atmos. Environ.:
X, 10, 100110, https://doi.org/10.1016/j.aeaoa.2021.100110, 2021. a, b, c, d, e, f
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D.,
Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.:
The ERA5 global reanalysis, Q. J. Roy.
Meteorol. Soc., 146, 1999–2049, 2020. a, b
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on pressure levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.bd0915c6, 2023. a
Ialongo, I., Stepanova, N., Hakkarainen, J., Virta, H., and Gritsenko, D.:
Satellite-based estimates of nitrogen oxide and methane emissions from gas
flaring and oil production activities in Sakha Republic, Russia, Atmos.
Environ.: X, 11, 100114,
https://doi.org/10.1016/j.aeaoa.2021.100114, 2021. a
Marais, E., Pandey, A. K., Van Damme, M., Clarisse, L., Coheur, P.-F.,
Shephard, M. W., Cady-Pereira, K., Misselbrook, T., Zhu, L., Luo, G., and Yu,
F.: UK ammonia emissions estimated with satellite observations and J. Geophys. Res.-Atmos., 126, e2021JD035237,
https://doi.org/10.1029/2021JD035237, 2021. a
Marshall, J. and Plumb, R. A.: Atmosphere, ocean and climate dynamics: an
introductory text, Academic Press, ISBN 9780080556703, 2016. a
Pommier, M., McLinden, C. A., and Deeter, M.: Relative changes in CO emissions
over megacities based on observations from space, Geophys. Res.
Lett., 40, 3766–3771, https://doi.org/10.1002/grl.50704, 2013. a
Pope, R. J., Arnold, S. R., Chipperfield, M. P., Latter, B. G., Siddans, R.,
and Kerridge, B. J.: Widespread changes in UK air quality observed from
space, Atmos. Sci. Lett., 19, e817,
https://doi.org/10.1002/asl.817, 2018. a
Pope, R. J., Kelly, R., Marais, E. A., Graham, A. M., Wilson, C., Harrison, J. J., Moniz, S. J. A., Ghalaieny, M., Arnold, S. R., and Chipperfield, M. P.: Exploiting satellite measurements to explore uncertainties in UK bottom-up NOx emission estimates, Atmos. Chem. Phys., 22, 4323–4338, https://doi.org/10.5194/acp-22-4323-2022, 2022. a
Potts, D. A., Ferranti, E. J. S., Timmis, R., Brown, A. S., and Vande Hey,
J. D.: Satellite Data Applications for Site-Specific Air Quality Regulation
in the UK: Pilot Study and Prospects, Atmosphere, 12, 1659, https://doi.org/10.3390/atmos12121659,
2021. a, b
Seinfeld, J. H. and Pandis, S. N.: Atmospheric chemistry and physics: from air
pollution to climate change, John Wiley & Sons, ISBN 9780471178156, 2016. a
Shah, V., Jacob, D. J., Li, K., Silvern, R. F., Zhai, S., Liu, M., Lin, J., and Zhang, Q.: Effect of changing NOx lifetime on the seasonality and long-term trends of satellite-observed tropospheric NO2 columns over China, Atmos. Chem. Phys., 20, 1483–1495, https://doi.org/10.5194/acp-20-1483-2020, 2020. a
Sorbjan, Z.: Air pollution meteorology, AIR QUALITY MODELING-Theories,
Methodologies, Computational Techniques and Available Databases and Software,
1, Chapter 4, ISBN 978-1-4757-4465-1, 2003. a
Valin, L. C., Russell, A. R., and Cohen, R. C.: Variations of OH radical in an
urban plume inferred from NO2 column measurements, Geophys. Res.
Lett., 40, 1856–1860, https://doi.org/10.1002/grl.50267, 2013. a
Veefkind, J. P., Aben, I., McMullan, K., Förster, H., de Vries, J., Otter, G.,
Claas, J., Eskes, H. J., de Haan, J. F., Kleipool, Q., van Weele, M.,
Hasekamp, O., Hoogeveen, R., Landgraf, J., Snel, R., Tol, P., Ingmann, P.,
Voors, R., Kruizinga, B., Vink, R., Visser, H., and Levelt, P. F.: TROPOMI on
the ESA Sentinel-5 Precursor: A GMES mission for global observations of the
atmospheric composition for climate, air quality and ozone layer
applications, Remote Sens. Environ., 120, 70–83,
https://doi.org/10.1016/j.rse.2011.09.027, 2012.
a
Wang, K., Wu, K., Wang, C., Tong, Y., Gao, J., Zuo, P., Zhang, X., and Yue, T.:
Identification of NOx hotspots from oversampled TROPOMI NO2 column based on
image segmentation method, Sci. Total Environ., 803, 150007,
https://doi.org/10.1016/j.scitotenv.2021.150007, 2022. a
Short summary
With the launch of the TROPOspheric Monitoring Instrument (TROPOMI) in 2017, it is now possible to observe pollutants emitted from individual industrial facilities on a daily basis around the globe. By using observations of nitrogen dioxide (NO2) from 16 different industrial sites, we show how the Coriolis effect influences the trajectory of these emission plumes as well as how the additional curvature can lead to a substantial underestimation of the calculated emissions.
With the launch of the TROPOspheric Monitoring Instrument (TROPOMI) in 2017, it is now possible...
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