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

Authors :
Y. Zhang
J. Lin
J. Kim
H. Lee
J. Park
H. Hong
M. Van Roozendael
F. Hendrick
T. Wang
P. Wang
Q. He
K. Qin
Y. Choi
Y. Kanaya
J. Xu
P. Xie
X. Tian
S. Zhang
S. Wang
S. Cheng
X. Cheng
J. Ma
T. Wagner
R. Spurr
L. Chen
H. Kong
M. Liu
Source :
Atmospheric Measurement Techniques, Vol 16, Pp 4643-4665 (2023)
Publication Year :
2023
Publisher :
Copernicus Publications, 2023.

Abstract

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 (where POMINO is the Peking University OMI NO2 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 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. The 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; 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 the following: OMNO2 (Ozone Monitoring Instrument (OMI) NO2 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 %) NO2 products. POMINO–GEMS shows small biases against ground-based MAX-DOAS (multi-axis differential optical absorption spectroscopy) 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 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 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; 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 NO2.

Details

Language :
English
ISSN :
18671381, 18678548, and 23283254
Volume :
16
Database :
Directory of Open Access Journals
Journal :
Atmospheric Measurement Techniques
Publication Type :
Academic Journal
Accession number :
edsdoj.b12be232832545228700d14aa21186f2
Document Type :
article
Full Text :
https://doi.org/10.5194/amt-16-4643-2023