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A research product for tropospheric NO2 columns fromGeostationary Environment Monitoring Spectrometerbased on Peking University OMI NO2 algorithm
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Tropospheric vertical column densities (VCDs) of nitrogen dioxide (NO2) retrieved from sun-synchronous satellite instruments have provided abundant NO2 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 NO­2 at an unprecedented hourly resolution during the daytime. Here we present a research product for tropospheric NO2 VCDs, referred to as POMINO-GEMS. We develop a hybrid retrieval method combining GEMS, TROPOMI and GEOS-CF data to generate hourly tropospheric NO2 slant column densities (SCDs). We then derive tropospheric NO2 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 O2-O2 algorithm by using ancillary parameters consistent with those used in NO2 AMF calculations.Initial retrieval of POMINO-GEMS tropospheric NO2 VCDs for June–August 2021 exhibits strong hotspot signals over megacities and distinctive diurnal variations over polluted and clean areas. POMINO-GEMS NO2 VCDs agree with the POMINO-TROPOMI v1.2.2 product (R = 0.98, and NMB = 4.9%) over East Asia, with slight differences associated with satellite viewing geometries and cloud and aerosol properties affecting the NO2 retrieval. POMINO-GEMS also shows good agreement with OMNO2 v4 (R = 0.87, and NMB = −16.8%) and GOME-2 GDP 4.8 (R = 0.83, and NMB = −1.5%) NO2 products. POMINO-GEMS shows small biases against ground-based MAX-DOAS NO2 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 of POMINO-GEMS correlates well with mobile-car MAX-DOAS measurements in the Three Rivers’ Source region on the Tibetan Plateau (R = 0.81). Surface NO2 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, and NMB = –26.3%) as well as 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 NO2.
Title: A research product for tropospheric NO2 columns fromGeostationary Environment Monitoring Spectrometerbased on Peking University OMI NO2 algorithm
Description:
Tropospheric vertical column densities (VCDs) of nitrogen dioxide (NO2) retrieved from sun-synchronous satellite instruments have provided abundant NO2 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 NO­2 at an unprecedented hourly resolution during the daytime.
Here we present a research product for tropospheric NO2 VCDs, referred to as POMINO-GEMS.
We develop a hybrid retrieval method combining GEMS, TROPOMI and GEOS-CF data to generate hourly tropospheric NO2 slant column densities (SCDs).
We then derive tropospheric NO2 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 O2-O2 algorithm by using ancillary parameters consistent with those used in NO2 AMF calculations.
Initial retrieval of POMINO-GEMS tropospheric NO2 VCDs for June–August 2021 exhibits strong hotspot signals over megacities and distinctive diurnal variations over polluted and clean areas.
POMINO-GEMS NO2 VCDs agree with the POMINO-TROPOMI v1.
2.
2 product (R = 0.
98, and NMB = 4.
9%) over East Asia, with slight differences associated with satellite viewing geometries and cloud and aerosol properties affecting the NO2 retrieval.
POMINO-GEMS also shows good agreement with OMNO2 v4 (R = 0.
87, and NMB = −16.
8%) and GOME-2 GDP 4.
8 (R = 0.
83, and NMB = −1.
5%) NO2 products.
POMINO-GEMS shows small biases against ground-based MAX-DOAS NO2 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 of POMINO-GEMS correlates well with mobile-car MAX-DOAS measurements in the Three Rivers’ Source region on the Tibetan Plateau (R = 0.
81).
Surface NO2 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, and NMB = –26.
3%) as well as 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 NO2.
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