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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/amt-2019-252
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2019-252
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 23 Aug 2019

Submitted as: research article | 23 Aug 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).

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

Cristina Ruiz Villena1, Jasdeep S. Anand1, Roland J. Leigh1,a, Paul S. Monks2, Claire E. Parfitt3, and Joshua D. Vande Hey1 Cristina Ruiz Villena et al.
  • 1Department of Physics and Astronomy, Earth Observation Science Group, University of Leicester, Leicester, UK
  • 2Department of Chemistry, University of Leicester, Leicester, UK
  • 3Thales Alenia Space UK Ltd, Bristol, UK
  • anow at: EarthSense Systems Ltd, Leicester, UK

Abstract. The use of satellite NO2 data for air quality studies is increasingly revealing the need for observations with higher spatial and temporal resolution. The study of the NO2 diurnal cycle, global sub-urban scale observations, and identification of emission point sources are some examples of important applications not possible at the resolution provided by current instruments. One way to achieve increased spatial resolution is to reduce the spectral information needed for the retrieval, allowing both dimensions of conventional 2-D detectors to be used to record spatial information.

In this work we investigate the use of ten discrete wavelengths with the well-established Differential Optical Absorption Spectroscopy (DOAS) technique for NO2 slant column density (SCD) retrievals. To test the concept we use a selection of individual OMI and TROPOMI Level 1B swaths from various regions around the world which contain a mixture of clean and heavily polluted areas. To discretise the data we simulate a set of Gaussian optical filters centred at various key wavelengths of the NO2 absorption cross section. We perform SCD retrievals of the discrete data using a simple implementation of the DOAS algorithm and compare the results with the corresponding Level 2 SCD products, namely QA4ECV for OMI and the operational TROPOMI product.

For OMI the overall results from our discrete-wavelength retrieval are in very good agreement with the Level 2 data (mean difference < 5 %). For TROPOMI the agreement is good (mean difference < 11 %), with lower uncertainty owing to its higher signal-to-noise ratio. These discrepancies can be mostly explained by the differences in retrieval implementation. There are some larger differences around the centre of the swath and over water. While further research is needed to address specific retrieval issues, our results indicate that our method has potential. It would allow for simpler, more economic satellite instrument designs for NO2 monitoring at high spatial and temporal resolution. Constellations of small satellites with such instruments on board would be a valuable complement to current and upcoming high-budget hyperspectral instruments.

Cristina Ruiz Villena et al.
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Status: final response (author comments only)
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Cristina Ruiz Villena et al.
Cristina Ruiz Villena et al.
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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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