Abstract

Abstract. We describe a formaldehyde (HCHO) retrieval algorithm for the Geostationary Environment Monitoring Spectrometer (GEMS) that will be launched by the Korean Ministry of Environment in 2019. The algorithm comprises three steps: preprocesses, radiance fitting, and postprocesses. The preprocesses include a wavelength calibration, as well as interpolation and convolution of absorption cross sections; radiance fitting is conducted using a nonlinear fitting method referred to as basic optical absorption spectroscopy (BOAS); and postprocesses include air mass factor calculations and bias corrections. In this study, several sensitivity tests are conducted to examine the retrieval uncertainties using the GEMS HCHO algorithm. We evaluate the algorithm with the Ozone Monitoring Instrument (OMI) Level 1B irradiance/radiance data by comparing our retrieved HCHO column densities with OMI HCHO products of the Smithsonian Astrophysical Observatory (OMHCHO) and of the Quality Assurance for Essential Climate Variables project (OMI QA4ECV). Results show that OMI HCHO slant columns retrieved using the GEMS algorithm are in good agreement with OMHCHO, with correlation coefficients of 0.77–0.91 and regression slopes of 0.94–1.04 for March, June, September, and December 2005. Spatial distributions of HCHO slant columns from the GEMS algorithm are consistent with the OMI QA4ECV products, but relatively poorer correlation coefficients of 0.52–0.76 are found compared to those against the OMHCHO products. Also, we compare the satellite results with ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations. OMI GEMS HCHO vertical columns are 9 %–25 % lower than those of MAX-DOAS at Haute-Provence Observatory (OHP) in France, Bremen in Germany, and Xianghe in China. We find that the OMI GEMS retrievals have less bias than the OMHCHO and OMI QA4ECV products at OHP and Bremen in comparison with MAX-DOAS.

Highlights

  • Formaldehyde (HCHO) is mainly produced by the oxidation of nonmethane volatile organic compounds (NMVOCs), and it has been observed from space since the GOME instrument on the ERS-2 satellite first began conducting column measurements in 1995 (Chance et al, 2000)

  • Three different methods have been used with sunsynchronous satellite measurements in previous HCHO retrievals: the differential optical absorption spectroscopy (DOAS) method (De Smedt et al, 2008, 2012); a nonlinearized fitting method, which is known as basic optical absorption spectroscopy (BOAS) (Chance et al, 2000; González Abad et al, 2015, 2016); and principal component analysis (Li et al, 2015)

  • Resulting HCHO products are compared with Ozone Monitoring Instrument (OMI) products of other institutes for 1 month of each season (March, June, September, and December) in 2005 to provide seasonal variation in the Geostationary Environment Monitoring Spectrometer (GEMS) domain

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Summary

Introduction

Formaldehyde (HCHO) is mainly produced by the oxidation of nonmethane volatile organic compounds (NMVOCs), and it has been observed from space since the GOME instrument on the ERS-2 satellite first began conducting column measurements in 1995 (Chance et al, 2000). As sun-synchronous satellites have measurement frequencies of once or twice a day, they provide limited explorations of diurnal cycles and transboundary transport of air pollutants Their coarse spatial resolutions make discerning local source emissions difficult. To tackle the limitations inherent in low-orbiting satellites measurements, environmental geostationary satellites will be launched in 2019 (or later) by South Korea and the United States and in 2021 by the European Union, to monitor air quality over East Asia, North America, and Europe, respectively Instruments on board these geostationary satellites have spatial resolutions corresponding well with those of TROPOMI and high signal-to-noise ratios, and they will conduct column measurements of air pollutants every hour during the daytime.

GEMS instrument
HCHO algorithm description
Wavelength calibration and GEMS bandpass function
Convolution and reference spectra sampling
Radiance fitting
Air mass factor
Postprocesses
Uncertainty analysis
Random uncertainty
Systematic uncertainty
Uncertainty in AMF
Uncertainty in background correction
Results and validation
Retrieval of OMI HCHO
Comparison with other OMI products
Comparison with ground-based MAX-DOAS
Conclusions and discussions
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