A research product for tropospheric NO<sub>2</sub> columns from Geostationary Environment Monitoring Spectrometer based on Peking University OMI NO<sub>2</sub> algorithm
<p>Tropospheric vertical column densities (VCDs) of nitrogen dioxide (<span class="inline-formula">NO<sub>2</sub></span>) retrieved from sun-synchronous satellite instruments have provided abundant <span class="inline-formula">NO<sub>2<...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2023-10-01
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| Series: | Atmospheric Measurement Techniques |
| Online Access: | https://amt.copernicus.org/articles/16/4643/2023/amt-16-4643-2023.pdf |
| _version_ | 1797661273023840256 |
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| author | Y. Zhang J. Lin J. Kim H. Lee J. Park H. Hong M. Van Roozendael F. Hendrick T. Wang T. Wang P. Wang P. Wang Q. He K. Qin Y. Choi Y. Kanaya J. Xu P. Xie P. Xie X. Tian S. Zhang S. Wang S. Cheng X. Cheng J. Ma T. Wagner R. Spurr L. Chen H. Kong M. Liu |
| author_facet | Y. Zhang J. Lin J. Kim H. Lee J. Park H. Hong M. Van Roozendael F. Hendrick T. Wang T. Wang P. Wang P. Wang Q. He K. Qin Y. Choi Y. Kanaya J. Xu P. Xie P. Xie X. Tian S. Zhang S. Wang S. Cheng X. Cheng J. Ma T. Wagner R. Spurr L. Chen H. Kong M. Liu |
| author_sort | Y. Zhang |
| collection | DOAJ |
| description | <p>Tropospheric vertical column densities (VCDs) of nitrogen dioxide (<span class="inline-formula">NO<sub>2</sub></span>) retrieved from sun-synchronous satellite instruments have provided abundant <span class="inline-formula">NO<sub>2</sub></span> 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 <span class="inline-formula">NO<sub>2</sub></span> at an
unprecedented hourly resolution during the daytime. Here we present a research product for tropospheric <span class="inline-formula">NO<sub>2</sub></span> VCDs, referred to as
POMINO–GEMS (where POMINO is the Peking University OMI <span class="inline-formula">NO<sub>2</sub></span> 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 <span class="inline-formula">NO<sub>2</sub></span> slant column densities (SCDs). We then derive tropospheric <span class="inline-formula">NO<sub>2</sub></span> 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 <span class="inline-formula">O<sub>2</sub></span>–<span class="inline-formula">O<sub>2</sub></span> algorithm by using ancillary parameters consistent with those used in <span class="inline-formula">NO<sub>2</sub></span> AMF calculations.</p>
<p>The initial retrieval of POMINO–GEMS tropospheric <span class="inline-formula">NO<sub>2</sub></span> VCDs for June–August 2021 exhibits strong hotspot signals over megacities and
distinctive diurnal variations over polluted and clean areas. POMINO–GEMS <span class="inline-formula">NO<sub>2</sub></span> VCDs agree with the POMINO–TROPOMI v1.2.2 product (<span class="inline-formula"><i>R</i>=0.98</span>; NMB <span class="inline-formula">=</span> 4.9 %) over East Asia, with slight differences associated with satellite viewing geometries and cloud and aerosol properties affecting the <span class="inline-formula">NO<sub>2</sub></span> retrieval. POMINO–GEMS also shows good agreement with the following: OMNO2 (Ozone Monitoring Instrument (OMI) <span class="inline-formula">NO<sub>2</sub></span> Standard Product) v4 (<span class="inline-formula"><i>R</i>=0.87</span>; NMB <span class="inline-formula">=</span> <span class="inline-formula">−</span>16.8 %); and GOME-2 (Global Ozone Monitoring Experiment-2) GDP (GOME Data Processor) 4.8 (<span class="inline-formula"><i>R</i>=0.83</span>; NMB <span class="inline-formula">=</span> <span class="inline-formula">−</span>1.5 %) <span class="inline-formula">NO<sub>2</sub></span> products. POMINO–GEMS shows small biases against ground-based MAX-DOAS (multi-axis differential optical absorption spectroscopy) <span class="inline-formula">NO<sub>2</sub></span> VCD data at nine sites (NMB <span class="inline-formula">=</span> <span class="inline-formula">−</span>11.1 %), with modest or high correlation in diurnal variation at six urban and suburban sites
(<span class="inline-formula"><i>R</i></span> 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 (<span class="inline-formula"><i>R</i>=0.81</span>). Surface <span class="inline-formula">NO<sub>2</sub></span> concentrations estimated from POMINO–GEMS VCDs are consistent with measurements from the Ministry of Ecology and Environment of China for spatiotemporal variation (<span class="inline-formula"><i>R</i>=0.78</span>; NMB <span class="inline-formula">=</span> <span class="inline-formula">−</span>26.3 %) and diurnal variation at all, urban, suburban and rural sites (<span class="inline-formula"><i>R</i>≥0.96</span>). POMINO–GEMS data will be made freely available for users to study the spatiotemporal variations, sources and impacts of <span class="inline-formula">NO<sub>2</sub></span>.</p> |
| first_indexed | 2024-03-11T18:43:02Z |
| format | Article |
| id | doaj.art-b12be232832545228700d14aa21186f2 |
| institution | Directory Open Access Journal |
| issn | 1867-1381 1867-8548 |
| language | English |
| last_indexed | 2024-03-11T18:43:02Z |
| publishDate | 2023-10-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Measurement Techniques |
| spelling | doaj.art-b12be232832545228700d14aa21186f22023-10-12T09:54:35ZengCopernicus PublicationsAtmospheric Measurement Techniques1867-13811867-85482023-10-01164643466510.5194/amt-16-4643-2023A research product for tropospheric NO<sub>2</sub> columns from Geostationary Environment Monitoring Spectrometer based on Peking University OMI NO<sub>2</sub> algorithmY. Zhang0J. Lin1J. Kim2H. Lee3J. Park4H. Hong5M. Van Roozendael6F. Hendrick7T. Wang8T. Wang9P. Wang10P. Wang11Q. He12K. Qin13Y. Choi14Y. Kanaya15J. Xu16P. Xie17P. Xie18X. Tian19S. Zhang20S. Wang21S. Cheng22X. Cheng23J. Ma24T. Wagner25R. Spurr26L. Chen27H. Kong28M. Liu29Laboratory for Climate and Ocean–Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, ChinaLaboratory for Climate and Ocean–Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, ChinaDepartment of Atmospheric Sciences, Yonsei University, Seoul, South KoreaDivision of Earth Environmental System Science Major of Spatial Information Engineering, Pukyong National University, Busan, South KoreaDivision of Earth Environmental System Science Major of Spatial Information Engineering, Pukyong National University, Busan, South KoreaNational Institute of Environmental Research, Incheon, South KoreaBelgian Institute for Space Aeronomy (BIRA-IASB), Brussels, BelgiumBelgian Institute for Space Aeronomy (BIRA-IASB), Brussels, BelgiumCNRC & LAGEO, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, ChinaUniversity of Chinese Academy of Sciences, Beijing 100049, ChinaCNRC & LAGEO, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, ChinaUniversity of Chinese Academy of Sciences, Beijing 100049, ChinaSchool of Environment and Geoinformatics, China University of Mining and Technology, Xuzhou, Jiangsu 221116, ChinaSchool of Environment and Geoinformatics, China University of Mining and Technology, Xuzhou, Jiangsu 221116, ChinaDepartment of Environmental Science, Hankuk University of Foreign Studies, Yongin, South KoreaResearch Institute for Global Change, Japan Agency for Marine–Earth Science and Technology (JAMSTEC), Yokohama 2360001, JapanKey Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Science, Hefei 230031, ChinaUniversity of Chinese Academy of Sciences, Beijing 100049, ChinaKey Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Science, Hefei 230031, ChinaInformation Materials and Intelligent Sensing Laboratory of Anhui Province, Institutes of Physical Science and Information Technology, Anhui University, Hefei, Anhui 230601, ChinaShanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, ChinaShanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, ChinaState Key Laboratory of Severe Weather & Institute of Tibetan Plateau Meteorology, Chinese Academy of Meteorological Sciences, Beijing 100081, ChinaState Key Laboratory of Severe Weather & Institute of Tibetan Plateau Meteorology, Chinese Academy of Meteorological Sciences, Beijing 100081, ChinaState Key Laboratory of Severe Weather & Institute of Tibetan Plateau Meteorology, Chinese Academy of Meteorological Sciences, Beijing 100081, ChinaSatellite Remote Sensing, Max Planck Institute for Chemistry, 55020 Mainz, GermanyRT Solutions Inc., Cambridge, MA 02138, USACollege of Urban and Environmental Sciences, Peking University, Beijing 100871, ChinaLaboratory for Climate and Ocean–Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, ChinaR&D Satellite Observations Department, Royal Netherlands Meteorological Institute, De Bilt, the Netherlands<p>Tropospheric vertical column densities (VCDs) of nitrogen dioxide (<span class="inline-formula">NO<sub>2</sub></span>) retrieved from sun-synchronous satellite instruments have provided abundant <span class="inline-formula">NO<sub>2</sub></span> 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 <span class="inline-formula">NO<sub>2</sub></span> at an unprecedented hourly resolution during the daytime. Here we present a research product for tropospheric <span class="inline-formula">NO<sub>2</sub></span> VCDs, referred to as POMINO–GEMS (where POMINO is the Peking University OMI <span class="inline-formula">NO<sub>2</sub></span> 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 <span class="inline-formula">NO<sub>2</sub></span> slant column densities (SCDs). We then derive tropospheric <span class="inline-formula">NO<sub>2</sub></span> 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 <span class="inline-formula">O<sub>2</sub></span>–<span class="inline-formula">O<sub>2</sub></span> algorithm by using ancillary parameters consistent with those used in <span class="inline-formula">NO<sub>2</sub></span> AMF calculations.</p> <p>The initial retrieval of POMINO–GEMS tropospheric <span class="inline-formula">NO<sub>2</sub></span> VCDs for June–August 2021 exhibits strong hotspot signals over megacities and distinctive diurnal variations over polluted and clean areas. POMINO–GEMS <span class="inline-formula">NO<sub>2</sub></span> VCDs agree with the POMINO–TROPOMI v1.2.2 product (<span class="inline-formula"><i>R</i>=0.98</span>; NMB <span class="inline-formula">=</span> 4.9 %) over East Asia, with slight differences associated with satellite viewing geometries and cloud and aerosol properties affecting the <span class="inline-formula">NO<sub>2</sub></span> retrieval. POMINO–GEMS also shows good agreement with the following: OMNO2 (Ozone Monitoring Instrument (OMI) <span class="inline-formula">NO<sub>2</sub></span> Standard Product) v4 (<span class="inline-formula"><i>R</i>=0.87</span>; NMB <span class="inline-formula">=</span> <span class="inline-formula">−</span>16.8 %); and GOME-2 (Global Ozone Monitoring Experiment-2) GDP (GOME Data Processor) 4.8 (<span class="inline-formula"><i>R</i>=0.83</span>; NMB <span class="inline-formula">=</span> <span class="inline-formula">−</span>1.5 %) <span class="inline-formula">NO<sub>2</sub></span> products. POMINO–GEMS shows small biases against ground-based MAX-DOAS (multi-axis differential optical absorption spectroscopy) <span class="inline-formula">NO<sub>2</sub></span> VCD data at nine sites (NMB <span class="inline-formula">=</span> <span class="inline-formula">−</span>11.1 %), with modest or high correlation in diurnal variation at six urban and suburban sites (<span class="inline-formula"><i>R</i></span> 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 (<span class="inline-formula"><i>R</i>=0.81</span>). Surface <span class="inline-formula">NO<sub>2</sub></span> concentrations estimated from POMINO–GEMS VCDs are consistent with measurements from the Ministry of Ecology and Environment of China for spatiotemporal variation (<span class="inline-formula"><i>R</i>=0.78</span>; NMB <span class="inline-formula">=</span> <span class="inline-formula">−</span>26.3 %) and diurnal variation at all, urban, suburban and rural sites (<span class="inline-formula"><i>R</i>≥0.96</span>). POMINO–GEMS data will be made freely available for users to study the spatiotemporal variations, sources and impacts of <span class="inline-formula">NO<sub>2</sub></span>.</p>https://amt.copernicus.org/articles/16/4643/2023/amt-16-4643-2023.pdf |
| spellingShingle | Y. Zhang J. Lin J. Kim H. Lee J. Park H. Hong M. Van Roozendael F. Hendrick T. Wang T. Wang P. Wang P. Wang Q. He K. Qin Y. Choi Y. Kanaya J. Xu P. Xie P. Xie X. Tian S. Zhang S. Wang S. Cheng X. Cheng J. Ma T. Wagner R. Spurr L. Chen H. Kong M. Liu A research product for tropospheric NO<sub>2</sub> columns from Geostationary Environment Monitoring Spectrometer based on Peking University OMI NO<sub>2</sub> algorithm Atmospheric Measurement Techniques |
| title | A research product for tropospheric NO<sub>2</sub> columns from Geostationary Environment Monitoring Spectrometer based on Peking University OMI NO<sub>2</sub> algorithm |
| title_full | A research product for tropospheric NO<sub>2</sub> columns from Geostationary Environment Monitoring Spectrometer based on Peking University OMI NO<sub>2</sub> algorithm |
| title_fullStr | A research product for tropospheric NO<sub>2</sub> columns from Geostationary Environment Monitoring Spectrometer based on Peking University OMI NO<sub>2</sub> algorithm |
| title_full_unstemmed | A research product for tropospheric NO<sub>2</sub> columns from Geostationary Environment Monitoring Spectrometer based on Peking University OMI NO<sub>2</sub> algorithm |
| title_short | A research product for tropospheric NO<sub>2</sub> columns from Geostationary Environment Monitoring Spectrometer based on Peking University OMI NO<sub>2</sub> algorithm |
| title_sort | research product for tropospheric no sub 2 sub columns from geostationary environment monitoring spectrometer based on peking university omi no sub 2 sub algorithm |
| url | https://amt.copernicus.org/articles/16/4643/2023/amt-16-4643-2023.pdf |
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