EGU24-2169, updated on 08 Mar 2024
https://doi.org/10.5194/egusphere-egu24-2169
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

A research product for tropospheric NO2 columns fromGeostationary Environment Monitoring Spectrometerbased on Peking University OMI NO2 algorithm

Yuhang Zhang1, Jintai Lin1, Jhoon Kim2, Hanlim Lee3, Junsung Park3, Hyunkee Hong4, Michel Van Roozendael5, Francois Hendrick5, Ting Wang6,7, Pucai Wang6,7, Qin He8, Kai Qin8, Yongjoo Choi9, Yugo Kanaya10, Jin Xu11, Pinhua Xie7,11, Xin Tian12, Sanbao Zhang13, Shanshan Wang13, Siyang Cheng14, and the Yuhang Zhang*
Yuhang Zhang et al.
  • 1Peking University, School of Physics, Department of Atmospheric and Oceanic Sciences, Beijing, China (yuhang_zhang@pku.edu.cn)
  • 2Department of Atmospheric Sciences, Yonsei University, Seoul, South Korea
  • 3Division of Earth Environmental System Science Major of Spatial Information Engineering, Pukyong National University, Busan, South Korea
  • 4National Institute of Environmental Research, Incheon, South Korea
  • 5Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium
  • 6CNRC & LAGEO, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
  • 7University of Chinese Academy of Sciences, Beijing 100049, China
  • 8School of Environment and Geoinformatics, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China
  • 9Department of Environmental Science, Hankuk University of Foreign Studies, Yongin, South Korea
  • 10Research Institute for Global Change, Japan Agency for Marine–Earth Science and Technology (JAMSTEC), Yokohama 2360001, Japan
  • 11Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Science, Hefei 230031, China
  • 12Information Materials and Intelligent Sensing Laboratory of Anhui Province, Institutes of Physical Science and Information Technology, Anhui University, Hefei, Anhui 230601, China
  • 13Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
  • 14State Key Laboratory of Severe Weather & Institute of Tibetan Plateau Meteorology, Chinese Academy of Meteorological Sciences, Beijing 100081, China
  • *A full list of authors appears at the end of the 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. 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.

Yuhang Zhang:

xionghong Cheng(14), Jianzhong Ma(14), Thomas Wagner(15), Rober Spurr(16), Lulu Chen(17), Hao Kong(1), Mengyao Liu(18)

How to cite: Zhang, Y., Lin, J., Kim, J., Lee, H., Park, J., Hong, H., Van Roozendael, M., Hendrick, F., Wang, T., Wang, P., He, Q., Qin, K., Choi, Y., Kanaya, Y., Xu, J., Xie, P., Tian, X., Zhang, S., Wang, S., and Cheng, S. and the Yuhang Zhang: A research product for tropospheric NO2 columns fromGeostationary Environment Monitoring Spectrometerbased on Peking University OMI NO2 algorithm, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2169, https://doi.org/10.5194/egusphere-egu24-2169, 2024.