A research product for tropospheric NO2 columns from Geostationary Environment Monitoring Spectrometer based on Peking University OMI NO2 algorithm

Zhang, Y.-H.; Lin, J.-T.; Kim, J.; Lee, H.; Park, J.; Hong, H.; Van Roozendael, M.; Hendrick, F.; Wang, T.; Wang, P.-C.; He, Q.; Qin, K.; Choi, Y.; Kanaya, Y.; Xu, J.; Xie, P.-H.; Tian, X.; Zhang, S.-B.; Wang, S.-S.; Cheng, S.-Y.; Cheng, X.-H.; Ma, J.-Z.; Wagner, T.; Spurr, R.; Chen, L.-L.; Kong, H.; Liu, M.-Y.

doi:10.5194/amt-16-4643-2023

journal · 2023

A research product for tropospheric NO2 columns from Geostationary Environment Monitoring Spectrometer based on Peking University OMI NO2 algorithm

Zhang, Y.-H., Lin, J.-T. ^*, Kim, J., Lee, H., Park, J., Hong, H., Van Roozendael, M., Hendrick, F., Wang, T., Wang, P.-C., He, Q., Qin, K., Choi, Y., Kanaya, Y., Xu, J., Xie, P.-H., Tian, X., Zhang, S.-B., Wang, S.-S., Cheng, S.-Y., Cheng, X.-H., Ma, J.-Z., Wagner, T., Spurr, R., Chen, L.-L., Kong, H., and Liu, M.-Y.

Atmospheric Measurement Techniques, 16(19), 4643–4665

Paper Supplement DOI

@article{zhang2023atmospheric,
  author  = {Zhang, Y.-H., Lin, J.-T., Kim, J., Lee, H., Park, J., Hong, H., Van Roozendael, M., Hendrick, F., Wang, T., Wang, P.-C., He, Q., Qin, K., Choi, Y., Kanaya, Y., Xu, J., Xie, P.-H., Tian, X., Zhang, S.-B., Wang, S.-S., Cheng, S.-Y., Cheng, X.-H., Ma, J.-Z., Wagner, T., Spurr, R., Chen, L.-L., Kong, H., and Liu, M.-Y.},
  title   = {A research product for tropospheric NO2 columns from Geostationary Environment Monitoring Spectrometer based on Peking University OMI NO2 algorithm},
  journal = {Atmospheric Measurement Techniques},
  volume  = {16},
  pages   = {4643–4665},
  year    = {2023},
  doi     = {10.5194/amt-16-4643-2023}
}

Abstract

Tropospheric vertical column densities (VCDs) of nitrogen dioxide ( NO 2 ) retrieved from sun-synchronous satellite instruments have provided abundant NO 2 data for environmental studies, but such data are limited by retrieval uncertainties and insufficient temporal sampling (e.g., once a day). The Geostationary Environment Monitoring Spectrometer (GEMS) launched in February 2020 monitors NO 2 at an unprecedented hourly resolution during the daytime. Here we present a research product for tropospheric NO 2 VCDs, referred to as POMINO–GEMS (where POMINO is the Peking University OMI NO 2 algorithm). We develop a hybrid retrieval method combining GEMS, TROPOMI (TROPOspheric Monitoring Instrument) and GEOS-CF (Global Earth Observing System Composition Forecast) data to generate hourly tropospheric NO 2 slant column densities (SCDs). We then derive tropospheric NO 2 air mass factors (AMFs) with explicit corrections for surface reflectance anisotropy and aerosol optical effects through parallelized pixel-by-pixel radiative transfer calculations. Prerequisite cloud parameters are retrieved with the O 2 – O 2 algorithm by using ancillary parameters consistent with those used in NO 2 AMF calculations. The initial retrieval of POMINO–GEMS tropospheric NO 2 VCDs for June–August 2021 exhibits strong hotspot signals over megacities and distinctive diurnal variations over polluted and clean areas. POMINO–GEMS NO 2 VCDs agree with the POMINO–TROPOMI v1.2.2 product ( R =0.98; NMB = 4.9 %) over East Asia, with slight differences associated with satellite viewing geometries and cloud and aerosol properties affecting the NO 2 retrieval. POMINO–GEMS also shows good agreement with the following: OMNO2 (Ozone Monitoring Instrument (OMI) NO 2 Standard Product) v4 ( R =0.87; NMB = − 16.8 %); and GOME-2 (Global Ozone Monitoring Experiment-2) GDP (GOME Data Processor) 4.8 ( R =0.83; NMB = − 1.5 %) NO 2 products. POMINO–GEMS shows small biases against ground-based MAX-DOAS (multi-axis differential optical absorption spectroscopy) NO 2 VCD data at nine sites (NMB = − 11.1 %), with modest or high correlation in diurnal variation at six urban and suburban sites ( R from 0.60 to 0.96). The spatiotemporal variation in POMINO–GEMS correlates well with mobile car MAX-DOAS measurements in the Three Rivers source region on the Tibetan Plateau ( R =0.81 ). Surface NO 2 concentrations estimated from POMINO–GEMS VCDs are consistent with measurements from the Ministry of Ecology and Environment of China for spatiotemporal variation ( R =0.78; NMB = − 26.3 %) and diurnal variation at all, urban, suburban and rural sites ( R ≥0.96 ). POMINO–GEMS data will be made freely available for users to study the spatiotemporal variations, sources and impacts of NO 2.

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