N: 90 S: -90 E: 180 W: -180
Description
This is Level-3 daily global gridded (0.25x0.25 degree) Nitrogen Dioxide Product (OMNO2d). OMNO2d data product is a Level-3 Gridded Product where pixel level data of good quality are binned and "averaged" into 0.25x0.25 degree global grids. This product contains Total column NO2 and Total Tropospheric Column NO2, for all atmospheric conditions, and for sky conditions where cloud fraction is less than 30 percent.
Nitrogen dioxide is an important chemical species in both, the stratosphere where it plays a key role in ozone chemistry, and in the troposphere where it is a precursor to ozone production. In the troposphere, it is produced in various combustion processes and in lightning and is an indicator of poor air quality.
The OMNO2d data are stored in version 5 EOS Hierarchical Data Format (HDF-EOS). Each file contains data from the day lit portion of the orbit (~14 orbits). The average file size for the OMNO2d data product is about 12 Mbytes.
Product Summary
Citation
Citation is critically important for dataset documentation and discovery. This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use and Citation Guidance.
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Publications Citing This Dataset
| Title | Year Sort ascending | Author | Topic |
|---|---|---|---|
| The Predictive Power of Combining Chemical and Dynamical Variables for | Strode, Sarah, Duncan, Bryan, Anderson, Daniel, Oman, Luke D., Orbe, Clara, Deushi, Makoto, Jockel, Patrick, Manyin, Michael | Tropopause, Surface Pressure, Air Temperature, Upper Air Temperature, Total Precipitable Water, Water Vapor, Cloud Height, Cloud Top Pressure, Cloud Top Temperature, Cloud Vertical Distribution, Emissivity, Sea Surface Temperature, Skin Temperature, Carbon Monoxide, Geopotential Height, Humidity, Water Vapor Profiles, Cloud Liquid Water/Ice, Outgoing Longwave Radiation, Methane, Atmospheric Ozone, Nitrogen Dioxide | |
| A Novel Machine Learning-Based Algorithm for Retrieving Remote-Sensing Reflectance from Multispectral Observations of the Geostationary Meteorological Satellite ... | An, Ni, Shi, Chong, Bao, Yuhai, Shang, Huazhe, Yin, Shuai, Tang, Chenqian, Yao, Ruijie, Letu, Husi | Nitrogen Dioxide | |
| High-Resolution Machine-Learning Reconstruction and Spatio-Temporal Analysis of Tropospheric OMI NO2 over Bangladesh (20132023) | Swa, Mahbuba Hasnat, Malitha, Sadit Bihongo, Sarwaruddin Chowdhury, A.M. | Nitrogen Dioxide | |
| Machine Learning-Based Estimation of Surface NO2 Concentrations over China: A Comparative Analysis of Geostationary (GEMS) and Polar-Orbiting (TROPOMI) Satellite Data | Ma, Yijin, Wang, Yi, Wang, Jun, Tao, Minghui, Kim, Jhoon, Wu, Chenyang, Zhang, Shanshan | Nitrogen Dioxide | |
| Global Atmospheric Pollution During the Pandemic Period (COVID-19) | Alvim, Debora Souza, Suski, Cassio Aurelio, Herdies, Dirceu Luis, Fontana, Caio Fernando, de Toledo, Eliza Miranda, Khalid, Bushra, Oyerinde, Gabriel, dos Reis, Andre Luiz, da Costa Coelho, Simone Marilene Sievert, DAmelio Felippe, Monica Tais Siqueira, Lamano, Mauricio | Nitrogen Dioxide | |
| Sub-seasonal and spatial variations in ozone formation and co-control potential for secondary aerosols in the Guanzhong basin, central China | Wang, Ruonan, Zhang, Ningning, Wu, Jiarui, Jiang, Qian, Yu, Jiaoyang, Lu, Yuxuan, Tie, Xuexi | Nitrogen Dioxide, Carbon And Hydrocarbon Compounds | |
| NO2 Emission Estimation in Ho Chi Minh City, Vietnam Using Modeling and OMI Satellite Data | Minh, Vo Thi Tam, Nguyen, Ly Sy Phu | Nitrogen Dioxide | |
| Nonlinear ozone response to extreme high temperature in a subtropical megacity basin: Integrated observation and modeling analysis | Xu, Tingting, Gao, Xilin, Jiang, Shuqiao, Hu, Kai, Peng, Zhuohao, Zhao, Xilin, Tang, Xiaolu | Carbon And Hydrocarbon Compounds, Nitrogen Dioxide | |
| Long-term trends and chemometric analysis of atmospheric air quality matrices in Nigeria (20032023) using NASA GIOVANNI satellite data | Omokpariola, Daniel Omeodisemi, Nduka, John Kanayochukwu, Anagboso, Martin Osita, Omokpariola, Patrick Leonard | Absorption, Radiative Forcing, Atmospheric Carbon Dioxide, Tropopause, Surface Pressure, Air Temperature, Upper Air Temperature, Total Precipitable Water, Water Vapor, Cloud Height, Cloud Top Pressure, Cloud Top Temperature, Cloud Vertical Distribution, Emissivity, Sea Surface Temperature, Skin Temperature, Carbon Monoxide, Geopotential Height, Humidity, Water Vapor Profiles, Cloud Liquid Water/Ice, Outgoing Longwave Radiation, Methane, Atmospheric Ozone, Sulfur Dioxide, Carbon And Hydrocarbon Compounds, Nitrogen Dioxide, Aerosol Optical Depth/Thickness, Atmospheric Ozone, Reflectance, Aerosol Extinction, Aerosol Optical Depth/Thickness, Aerosol Optical Depth/Thickness | |
| Air pollution modulates trends and variability of the global methane budget | Zhao, Yuanhong, Zheng, Bo, Saunois, Marielle, Ciais, Philippe, Hegglin, Michaela I., Lu, Shengmin, Li, Yifan, Bousquet, Philippe | Nitrogen Dioxide | |
| Air quality trends and regimes in South Korea inferred from 20152023 surface and satellite observations | Oak, Yujin J., Jacob, Daniel J., Pendergrass, Drew C., Dang, Ruijun, Colombi, Nadia K., Chong, Heesung, Lee, Seoyoung, Kuk, Su Keun, Kim, Jhoon | Sulfur Dioxide, Nitrogen Dioxide, Carbon And Hydrocarbon Compounds | |
| A global land daily 10-km-resolution surface ozone dataset from 20132022 | Wang, Rui, Shen, Huanfeng, Zeng, Chao, Chen, Jiajia, Wang, Yuan, Li, Yuyu | Atmospheric Ozone, Sea Level Pressure, Surface Pressure, Pressure Thickness, U/V Wind Components, U/V Wind Components, Potential Vorticity, Vertical Wind Velocity/Speed, Vertical Profiles, Upper Air Temperature, Air Temperature, Relative Humidity, Specific Humidity, Atmospheric Water Vapor, Cloud Liquid Water/Ice, Cloud Fraction, Altitude, Geopotential Height, Ozone Profiles, Nitrogen Dioxide, Reflectance, Atmospheric Carbon Monoxide, Tropospheric Ozone, Carbon Monoxide, Air Mass/Density | |
| Modeling on the drought stress impact on the summertime biogenic isoprene emissions in South Korea | Jeong, Yong-Cheol, Wang, Yuxuan, Li, Wei, Kim, Hyeonmin, Park, Rokjin J., Momeni, Mahmoudreza | Carbon And Hydrocarbon Compounds, Nitrogen Dioxide | |
| Spatiotemporal analysis of tropospheric nitrogen dioxide hotspot over Lahore Division in Pakistan | Zeeshan, Muhammad | Nitrogen Dioxide | |
| Star photometry with all-sky cameras to retrieve aerosol optical depth at nighttime | Roman, Roberto, Gonzalez-Fernandez, Daniel, Antuna-Sanchez, Juan Carlos, Herrero del Barrio, Celia, Herrero-Anta, Sara, Barreto, Africa, Cachorro, Victoria E., Doppler, Lionel, Gonzalez, Ramiro, Ritter, Christoph, Mateos, David, Kouremeti, Natalia, Copes, Gustavo, Calle, Abel, Granados-Munoz, Maria Jose, Toledano, Carlos, de Frutos, Angel M. | Nitrogen Dioxide | |
| Understanding macroeconomic indicators affected by COVID-19 containment policies in the United States: a scoping review | Cho, Jeong-Yeon, Prakash, Tejashree, Lam, Wayne, Seegert, Nathan, Samore, Matthew H, Pavia, Andrew T, Nelson, Richard E, Chaiyakunapruk, Nathorn | Nitrogen Dioxide | |
| Variability of satellite-based tropospheric nitrogen dioxide column abundance in the last 20 years over ten Mexican metropolitan areas measured by the Ozone ... | Cardenas, Claudia I. Rivera, Hernandez, Karina Gonzalez | Nitrogen Dioxide, Nitrogen Dioxide | |
| Elucidating Contributions of Anthropogenic and Soil NOx Emissions Changes to O3 Trends Over China | Sha, Tong, Yang, Siyu, Chen, Qingcai, Wei, Jing, Ma, Mingchen, Gao, Yang, Zhu, Yufan, Hu, Yan, Boersma, K. Folkert, Wang, Jun | Nitrogen Dioxide, Carbon And Hydrocarbon Compounds | |
| Estimating daily surface O3 concentrations in China from 2005 to 2023 based on the STMO3Net model | Zeng, Qiaolin, Qi, Yaoyu, Fan, Meng, Chen, Liangfu, Tao, Jinhua, Zhu, Hao, Liu, Sizhu, Zhu, Yuanyuan | Nitrogen Dioxide, Atmospheric Ozone, Reflectance | |
| Anthropogenic emissions dominate long-term trends of ozone production sensitivity in southeastern China derived from the ozone monitoring instrument | Hu, Baoye, Gao, Yue, Chen, Naihua, Zeng, Jinfeng, Liu, Taotao | Nitrogen Dioxide, Carbon And Hydrocarbon Compounds | |
| Changing tropospheric NO2 dynamics across Indian air pollution hotspots | Biswal, Akash, Katoch, Varun, Singh, Tanbir, Ravindra, Khaiwal, Singh, Vikas, Mor, Suman | Nitrogen Dioxide | |
| Comparative Spatial and Temporal Analysis of Atmospheric Pollutants Levels and Energy Consumption Emissions in Brazil: Pre and During COVID-19 Pandemic ... | Nadaleti, Willian Cezar, Correa, Anderson, De Souza, Eduarda Gomes, Cardozo, Emanuelle Soares, Dos Santos, Maele Costa, GOMES, Jeferson, Leandro, Diuliana | Nitrogen Dioxide | |
| Long-term observation of tropospheric NO2 in Vietnam from 2010 to 2023 | Thi Nguyen, Tuyet Nam, Tran, Phuoc Tan, Trinh, Tan Dat | Nitrogen Dioxide | |
| Machine Learning-Based Ground-Level NO2 Estimation in Istanbul: A Comparative Analysis of Sentinel-5P and GEOS-CF | Yagmur Aydin, Nur | Nitrogen Dioxide | |
| Investigating the influence of remote working conditions on tropospheric NO2 vertical column density over northern Italy observed by Aura/OMI | Engert, Rosina, Bichler, Renee, Bittner, Michael | Nitrogen Dioxide |
Variables
The table below lists the variables contained within a single granule for this dataset. Variables often contain observed or derived geophysical measurements collected from a variety of sources, including remote sensing instruments on satellite and airborne platforms, field campaigns, in situ measurements, and model outputs. The terms variable, parameter, scientific data set, layer, and band have been used across NASA’s Earth science disciplines; however, variable is the designated nomenclature in NASA’s Common Metadata Repository (CMR). Variable metadata attributes such as Name, Description, Units, Data Type, Fill Value, Valid Range, and Scale Factor allow users to efficiently process and analyze the data. The full range of attributes may not be applicable to all variables. Additional information on variable attributes is typically available in the data, user guide, and/or other product documentation.
For questions on a specific variable, please use the Earthdata Forum.
| Name Sort descending | Description | Units | Data Type | Fill Value | Valid Range | Scale Factor | Offset |
|---|---|---|---|---|---|---|---|
| HDFEOS/GRIDS/ColumnAmountNO2/Data Fields/ColumnAmountNO2 | Field=ColumnAmountNO2,StdField=ColumnAmountNO2Std,SolarZenithAngle=[0:85],VcdQualityFlags=~19,XTrackQualityFlagsModified=~[1:254],TerrainReflectivity=[0:1000] | molec/cm2 | float32 | -1.2676506002282E+30 | N/A | N/A | 0 |
| HDFEOS/GRIDS/ColumnAmountNO2/Data Fields/ColumnAmountNO2CloudScreened | Field=ColumnAmountNO2,StdField=ColumnAmountNO2Std,SolarZenithAngle=[0:85],CloudFraction=[0:300],VcdQualityFlags=~19,XTrackQualityFlagsModified=~[1:254],TerrainReflectivity=[0:1000] | molec/cm2 | float32 | -1.2676506002282E+30 | N/A | N/A | 0 |
| HDFEOS/GRIDS/ColumnAmountNO2/Data Fields/ColumnAmountNO2Trop | Field=ColumnAmountNO2Trop,StdField=ColumnAmountNO2TropStd,SolarZenithAngle=[0:85],VcdQualityFlags=~19,XTrackQualityFlagsModified=~[1:254],TerrainReflectivity=[0:1000] | molec/cm2 | float32 | -1.2676506002282E+30 | N/A | N/A | 0 |
| HDFEOS/GRIDS/ColumnAmountNO2/Data Fields/ColumnAmountNO2TropCloudScreened | Field=ColumnAmountNO2Trop,StdField=ColumnAmountNO2TropStd,SolarZenithAngle=[0:85],CloudFraction=[0:300],VcdQualityFlags=~19,XTrackQualityFlagsModified=~[1:254],TerrainReflectivity=[0:1000] | molec/cm2 | float32 | -1.2676506002282E+30 | N/A | N/A | 0 |
| HDFEOS INFORMATION/StructMetadata.0 | HDFEOS INFORMATION/StructMetadata.0 | N/A | OTHER | N/A | N/A | N/A | N/A |