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AMT | Articles | Volume 13, issue 4
Atmos. Meas. Tech., 13, 1735–1756, 2020
https://doi.org/10.5194/amt-13-1735-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Atmos. Meas. Tech., 13, 1735–1756, 2020
https://doi.org/10.5194/amt-13-1735-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 07 Apr 2020

Research article | 07 Apr 2020

Discrete-wavelength DOAS NO2 slant column retrievals from OMI and TROPOMI

Cristina Ruiz Villena et al.

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Cited articles

Alvarado, L. M. A., Richter, A., Vrekoussis, M., Wittrock, F., Hilboll, A., Schreier, S. F., and Burrows, J. P.: An improved glyoxal retrieval from OMI measurements, Atmos. Meas. Tech., 7, 4133–4150, https://doi.org/10.5194/amt-7-4133-2014, 2014. a
Anand, J. S., Monks, P. S., and Leigh, R. J.: An improved retrieval of tropospheric NO2 from space over polluted regions using an Earth radiance reference, Atmos. Meas. Tech., 8, 1519–1535, https://doi.org/10.5194/amt-8-1519-2015, 2015. a
Boersma, K. F., Eskes, H. J., Veefkind, J. P., Brinksma, E. J., van der A, R. J., Sneep, M., van den Oord, G. H. J., Levelt, P. F., Stammes, P., Gleason, J. F., and Bucsela, E. J.: Near-real time retrieval of tropospheric NO2 from OMI, Atmos. Chem. Phys., 7, 2103–2118, https://doi.org/10.5194/acp-7-2103-2007, 2007. a
Boersma, K. F., Eskes, H. J., Dirksen, R. J., van der A, R. J., Veefkind, J. P., Stammes, P., Huijnen, V., Kleipool, Q. L., Sneep, M., Claas, J., Leitão, J., Richter, A., Zhou, Y., and Brunner, D.: An improved tropospheric NO2 column retrieval algorithm for the Ozone Monitoring Instrument, Atmos. Meas. Tech., 4, 1905–1928, https://doi.org/10.5194/amt-4-1905-2011, 2011. a, b
Boersma, K. F., Eskes, H., Richter, A., Smedt, I. D., Lorente, A., Beirle, S., van Geffen, J., Peters, E., Roozendael, M. V., and Wagner, T.: QA4ECV NO2 tropospheric and stratospheric column data from OMI [Dataset], https://doi.org/10.21944/qa4ecv-no2-omi-v1.1, 2017. a
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Short summary
We present a new method to derive NO2 concentrations from satellite observations that uses up to 30 times less spectral information than traditional methods. We tested the method using data from existing instruments OMI and TROPOMI and found our results agree with the reference data to 5 % and 11 %, respectively. Our method could allow for simpler instrument designs that can be used in low-cost constellations of small satellites for air quality monitoring at high spatial and temporal resolution.
We present a new method to derive NO2 concentrations from satellite observations that uses up to...
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