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TROPOMI NO2 Tropospheric Column Data: Regridding to 1 km Grid-Resolution and Assessment of their Consistency with In Situ Surface Observations

https://doi.org/10.3390/rs12142212
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/2016jd025483openalex-snapshot
High‐resolution NO2 observations from the Airborne Compact Atmospheric Mapper: Retrieval and validation
inferredcites →https://doi.org/10.1002/2017jd027523openalex-snapshot
The 2016 Southeastern U.S. Drought: An Extreme Departure From Centennial Wetting and Cooling
inferredcites →https://doi.org/10.1002/9781118136188openalex-snapshot
Geostatistics
inferredcites →https://doi.org/10.1007/978-3-540-75776-4openalex-snapshot
Differential Optical Absorption Spectroscopy
inferredcites →https://doi.org/10.1007/978-3-662-05294-5openalex-snapshot
Multivariate Geostatistics
inferredcites →https://doi.org/10.1016/j.atmosenv.2016.04.038openalex-snapshot
Impacts of control strategies, the Great Recession and weekday variations on NO 2 columns above North American cities
inferredcites →https://doi.org/10.1016/j.envpol.2019.113875openalex-snapshot
A hybrid kriging/land-use regression model with Asian culture-specific sources to assess NO2 spatial-temporal variations
inferredcites →https://doi.org/10.1016/j.physd.2006.09.017openalex-snapshot
A Bayesian tutorial for data assimilation
inferredcites →https://doi.org/10.1016/j.rse.2011.09.027openalex-snapshot
TROPOMI on the ESA Sentinel-5 Precursor: A GMES mission for global observations of the atmospheric composition for climate, air quality and ozone layer applications
inferredcites →https://doi.org/10.1016/s1352-2310(98)00217-9openalex-snapshot
Climatic forcing of nitrogen oxides through changes in tropospheric ozone and methane; global 3D model studies
inferredcites →https://doi.org/10.1021/acs.est.5b02882openalex-snapshot
National Spatiotemporal Exposure Surface for NO2: Monthly Scaling of a Satellite-Derived Land-Use Regression, 2000–2010
inferredcites →https://doi.org/10.1021/acs.est.5b05099openalex-snapshot
Satellite-Based NO2 and Model Validation in a National Prediction Model Based on Universal Kriging and Land-Use Regression
inferredcites →https://doi.org/10.1021/es103578xopenalex-snapshot
National Satellite-Based Land-Use Regression: NO2 in the United States
inferredcites →https://doi.org/10.1029/2003jd003962openalex-snapshot
Error analysis for tropospheric NO 2 retrieval from space
inferredcites →https://doi.org/10.1029/2007jd009235openalex-snapshot
Ground‐level nitrogen dioxide concentrations inferred from the satellite‐borne Ozone Monitoring Instrument
inferredcites →https://doi.org/10.1029/2009jd012399openalex-snapshot
Testing and improving OMI DOMINO tropospheric NO2 using observations from the DANDELIONS and INTEX‐B validation campaigns
inferredcites →https://doi.org/10.1029/2018gl081095openalex-snapshot
High‐Resolution Mapping of Nitrogen Dioxide With TROPOMI: First Results and Validation Over the Canadian Oil Sands
inferredcites →https://doi.org/10.1029/jd095id02p01837openalex-snapshot
The sensitivity of ozone to nitrogen oxides and hydrocarbons in regional ozone episodes
inferredcites →https://doi.org/10.1038/s41598-017-15909-1openalex-snapshot
Severe Pollution in China Amplified by Atmospheric Moisture
inferredcites →https://doi.org/10.1051/epjconf/201817610002openalex-snapshot
Atmospheric NO2 profiles measured with lidar during the CINDI-2 campaign
inferredcites →https://doi.org/10.1080/13658816.2019.1667501openalex-snapshot
Spatio-temporal regression kriging for modelling urban NO 2 concentrations
inferredcites →https://doi.org/10.1109/tgrs.2006.872333openalex-snapshot
The ozone monitoring instrument
inferredcites →https://doi.org/10.1109/tgrs.2016.2565722openalex-snapshot
A Deterministic Method for Profile Retrievals From Hyperspectral Satellite Measurements
inferredcites →https://doi.org/10.1111/j.1467-9868.2007.00633.xopenalex-snapshot
Fixed Rank Kriging for Very Large Spatial Data Sets
inferredcites →https://doi.org/10.1117/12.830413openalex-snapshot
Tropospheric profile of NO 2 over the Po Valley measured with scan DOAS spectrometer
inferredcites →https://doi.org/10.1126/science.1174760openalex-snapshot
Improved Attribution of Climate Forcing to Emissions
inferredcites →https://doi.org/10.1175/1520-0469(1999)056<0127:smoamm>2.0.co;2openalex-snapshot
SCIAMACHY: Mission Objectives and Measurement Modes
inferredcites →https://doi.org/10.1175/1520-0469(1999)056<0151:tgomeg>2.0.co;2openalex-snapshot
The Global Ozone Monitoring Experiment (GOME): Mission Concept and First Scientific Results
inferredcites →https://doi.org/10.3390/rs10070994openalex-snapshot
Maximizing the Information Content of Ill-Posed Space-Based Measurements Using Deterministic Inverse Method
inferredcites →https://doi.org/10.3390/rs10111763openalex-snapshot
Downscaling of Satellite OPEMW Surface Rain Intensity Data
inferredcites →https://doi.org/10.3390/rs9060519openalex-snapshot
Ground-Level NO2 Concentrations over China Inferred from the Satellite OMI and CMAQ Model Simulations
inferredcites →https://doi.org/10.3390/s20082352openalex-snapshot
Optimal Interpolation for Infrared Products from Hyperspectral Satellite Imagers and Sounders
inferredcites →https://doi.org/10.5194/acp-17-11403-2017openalex-snapshot
A high-resolution and observationally constrained OMI NO 2 satellite retrieval
inferredcites →https://doi.org/10.5194/acp-18-15921-2018openalex-snapshot
Relationships between the planetary boundary layer height and surface pollutants derived from lidar observations over China: regional pattern and influencing factors
inferredcites →https://doi.org/10.5194/acp-19-5417-2019openalex-snapshot
Vertical profiles of NO2, SO2, HONO, HCHO, CHOCHO and aerosols derived from MAX-DOAS measurements at a rural site in the central western North China Plain and their relation to emission sources and effects of regional transport
inferredcites →https://doi.org/10.5194/acp-19-5853-2019openalex-snapshot
Near-surface and path-averaged mixing ratios of NO 2 derived from car DOAS zenith-sky and tower DOAS off-axis measurements in Vienna: a case study
inferredcites →https://doi.org/10.5194/acp-9-3867-2009openalex-snapshot
Validation of urban NO 2 concentrations and their diurnal and seasonal variations observed from the SCIAMACHY and OMI sensors using in situ surface measurements in Israeli cities
inferredcites →https://doi.org/10.5194/amt-10-759-2017openalex-snapshot
Structural uncertainty in air mass factor calculation for NO 2 and HCHO satellite retrievals
inferredcites →https://doi.org/10.5194/amt-13-205-2020openalex-snapshot
Comparison of TROPOMI/Sentinel-5 Precursor NO 2 observations with ground-based measurements in Helsinki
inferredcites →https://doi.org/10.5194/amt-4-1905-2011openalex-snapshot
An improved tropospheric NO 2 column retrieval algorithm for the Ozone Monitoring Instrument
inferredcites →https://doi.org/10.5194/amt-5-457-2012openalex-snapshot
The Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI): design, execution, and early results
inferredcites →https://doi.org/10.5194/amt-6-3613-2013openalex-snapshot
Kalman filter physical retrieval of surface emissivity and temperature from geostationary infrared radiances
inferredcites →https://doi.org/10.5194/amt-8-2981-2015openalex-snapshot
Kalman filter physical retrieval of surface emissivity and temperature from SEVIRI infrared channels: a validation and intercomparison study
inferredcites →https://doi.org/10.5194/gmd-9-1111-2016openalex-snapshot
OMI NO 2 column densities over North American urban cities: the effect of satellite footprint resolution

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4751540openalex-extracted
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inferred← citeshttps://doi.org/10.1002/env.2723openalex-snapshot
A spatiotemporal analysis of NO2 concentrations during the Italian 2020 COVID‐19 lockdown
inferred← citeshttps://doi.org/10.1007/978-3-030-91260-4_92-1openalex-snapshot
State of Air Quality in Zimbabwe: A Link to SDG 3.9
inferred← citeshttps://doi.org/10.1007/978-3-031-17465-0_92openalex-snapshot
State of Air Quality in Zimbabwe: A Link to SDG 3.9
inferred← citeshttps://doi.org/10.1007/s00704-025-05480-5openalex-snapshot
Investigation of Urban Heat Islands and modeling of Land Surface Temperature over selected Indian cities using MODIS products
inferred← citeshttps://doi.org/10.1016/j.apr.2026.103066openalex-snapshot
Advances and challenges of machine learning in satellite-based atmospheric NO2 monitoring
inferred← citeshttps://doi.org/10.1016/j.atmosenv.2024.120326openalex-snapshot
Impact of the implementation of Madrid's low emission zone on NO2 concentration using Sentinel-5P/TROPOMI data
inferred← citeshttps://doi.org/10.1016/j.atmosenv.2025.121447openalex-snapshot
Synergistic use of satellite and in-situ data for policy-relevant air quality information: A case study on Belgium
inferred← citeshttps://doi.org/10.1016/j.atmosenv.2026.121904openalex-snapshot
Estimating surface-level NO2 concentrations in the Madrid region using Sentinel-5P observations and ground-based meteorological data with machine learning approaches
inferred← citeshttps://doi.org/10.1016/j.cacint.2020.100051openalex-snapshot
Analysis of the NO2 tropospheric product from S5P TROPOMI for monitoring pollution at city scale
inferred← citeshttps://doi.org/10.1016/j.envpol.2024.125553openalex-snapshot
Enhanced validation and application of satellite-derived formaldehyde data for assessing photochemical pollution in the Chinese Greater Bay Area
inferred← citeshttps://doi.org/10.1016/j.envres.2022.112873openalex-snapshot
A methodological proposal to evaluate the health hazard scenario from COVID-19 in Italy
inferred← citeshttps://doi.org/10.1016/j.heliyon.2022.e09978openalex-snapshot
NO2 pollution over selected cities in the Po valley in 2018–2021 and its possible effects on boosting COVID-19 deaths
inferred← citeshttps://doi.org/10.1016/j.isprsjprs.2025.09.028openalex-snapshot
Harmonizing satellite and ground NO2 observations in China: A multi-sensor framework for scenario-specific calibration
inferred← citeshttps://doi.org/10.1016/j.jclepro.2021.128599openalex-snapshot
Google Earth Engine based spatio-temporal analysis of air pollutants before and during the first wave COVID-19 outbreak over Turkey via remote sensing
inferred← citeshttps://doi.org/10.1016/j.rsase.2023.100990openalex-snapshot
Sentinel satellite data monitoring of air pollutants with interpolation methods in Guayaquil, Ecuador
inferred← citeshttps://doi.org/10.1016/j.rsase.2023.101083openalex-snapshot
TROPOMI NO2 Sentinel-5P data in the Community of Madrid: A detailed consistency analysis with in situ surface observations
inferred← citeshttps://doi.org/10.1016/j.rsase.2024.101143openalex-snapshot
Spatio-temporal trend analysis of air pollutants during COVID-19 over Korba district, Chhattisgarh (India) using Google Earth Engine
inferred← citeshttps://doi.org/10.1016/j.rsase.2025.101682openalex-snapshot
Spatial representativeness of NO2 monitoring stations with respect to Sentinel-5P satellite based estimates
inferred← citeshttps://doi.org/10.1016/j.rse.2023.113514openalex-snapshot
Evaluating TROPOMI and MODIS performance to capture the dynamic of air pollution in São Paulo state: A case study during the COVID-19 outbreak
inferred← citeshttps://doi.org/10.1016/j.rse.2024.114321openalex-snapshot
Estimating surface NO2 concentrations over Europe using Sentinel-5P TROPOMI observations and Machine Learning
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2023.162833openalex-snapshot
Air quality trends and implications pre and post Covid-19 restrictions
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2023.165569openalex-snapshot
NO2 emissions from oil refineries in the Mississippi Delta
inferred← citeshttps://doi.org/10.1016/j.uclim.2021.100900openalex-snapshot
Environmental impact of COVID-19 led lockdown: A satellite data-based assessment of air quality in Indian megacities
inferred← citeshttps://doi.org/10.1021/acs.est.3c03230openalex-snapshot
Air Pollution Inequality in the Denver Metroplex and its Relationship to Historical Redlining
inferred← citeshttps://doi.org/10.1029/2021jd034797openalex-snapshot
COVID‐19 Induced Fingerprints of a New Normal Urban Air Quality in the United States
inferred← citeshttps://doi.org/10.1073/pnas.2421679122openalex-snapshot
Quantifying the impact of air pollution from coal-fired electricity generation on crop productivity in India
inferred← citeshttps://doi.org/10.1080/10106049.2023.2169374openalex-snapshot
Spatio-temporal air quality assessment in Tehran, Iran, during the COVID-19 lockdown periods
inferred← citeshttps://doi.org/10.1109/etecte55893.2022.10007417openalex-snapshot
Machine Learning for Area-Wide Monitoring of Surface Level Concentration of NO2 Using Remote Sensing Data
inferred← citeshttps://doi.org/10.1109/ingarss67683.2025.11583972openalex-snapshot
Tracking Air Pollution in Peri-Urban Hyderabad, India Using Remote Sensing Data
inferred← citeshttps://doi.org/10.1109/mgrs.2024.3398434openalex-snapshot
Estimation of Surface-Level NO2 Using Satellite Remote Sensing and Machine Learning: A review
inferred← citeshttps://doi.org/10.1117/12.2599774openalex-snapshot
Assessment of air quality with TROPOMI during COVID-19 pandemic: NO2 over the Po valley
inferred← citeshttps://doi.org/10.1117/12.2684037openalex-snapshot
Spatiotemporal behavior of atmospheric pollutant ingredients over Bulgaria, based on open access GAMS data
inferred← citeshttps://doi.org/10.1126/sciadv.abm9909openalex-snapshot
Globally ubiquitous negative effects of nitrogen dioxide on crop growth
inferred← citeshttps://doi.org/10.1145/3538637.3538862openalex-snapshot
Diesel GenSat
inferred← citeshttps://doi.org/10.1186/s40068-026-00477-zopenalex-snapshot
An integrated remote sensing-machine learning framework for assessing plant air pollution tolerance using satellite-derived air quality and reanalysis meteorological data
inferred← citeshttps://doi.org/10.12677/aep.2025.155088openalex-snapshot
Satellite-Based Quantification of Nitrogen Dioxide Effects on Vegetation Productivity in China
inferred← citeshttps://doi.org/10.17816/humeco678829openalex-snapshot
Atmospheric pollution in Cherepovets according to remote sensing
inferred← citeshttps://doi.org/10.21203/rs.3.rs-3836743/v1openalex-snapshot
Assessment of the Environmental Impacts of the COVID-19 Lockdown: Spatio-Temporal Distribution of Air Pollutants in Egypt (Case Study: Alexandria Maritime Port - Egypt)
inferred← citeshttps://doi.org/10.2139/ssrn.4825200openalex-snapshot
No2 Data from Air Quality Networks and Sentinel-5p: Relationship with O3 and Meteorological Variables in the Three Most Populated Cities in Spain
inferred← citeshttps://doi.org/10.2139/ssrn.4862063openalex-snapshot
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inferred← citeshttps://doi.org/10.24852/2411-7374.2023.1.10.15openalex-snapshot
ОЦЕНКА РИСКА ДЕГРАДАЦИИ ЛЕСНЫХ ГЕОСИСТЕМ ПОД ВОЗДЕЙСТВИЕМ ЗАГРЯЗНЕНИЯ АТМОСФЕРЫ НА ОСНОВЕ СЪЕМКИ СЕНСОРА TROPOMI СПУТНИКА SENTINEL-5P (НА ПРИМЕРЕ ВОСТОЧНОЙ ЧАСТИ БЕЛОРУССКОГО ПОЛЕСЬЯ)
inferred← citeshttps://doi.org/10.24852/2411-7374.2024.4.04.09openalex-snapshot
ОЦЕНКА РИСКА ЗАГРЯЗНЕНИЯ АТМОСФЕРЫ НА ОСНОВЕ КОСМИЧЕСКОЙ СЪЕМКИ SENTINEL-5P TROPOMI (НА ПРИМЕРЕ ВОСТОЧНОЙ ЧАСТИ БЕЛОРУССКОГО ПОЛЕСЬЯ)
inferred← citeshttps://doi.org/10.29333/ejgm/17047openalex-snapshot
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inferred← citeshttps://doi.org/10.30955/gnc2021.00758openalex-snapshot
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inferred← citeshttps://doi.org/10.30955/gnc2021.00777openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/nitrogen6020032openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/rs12213575openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/rs13050896openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/rs13101877openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/rs14122807openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/rs15020378openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/rs15163998openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/rs17122084openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/rs18111850openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/rs18132072openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/su17073031openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/su18062839openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/world2030025openalex-snapshot
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inferred← citeshttps://doi.org/10.3846/enviro.2026.2544openalex-snapshot
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inferred← citeshttps://doi.org/10.4209/aaqr.210153openalex-snapshot
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inferred← citeshttps://doi.org/10.4209/aaqr.210351openalex-snapshot
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inferred← citeshttps://doi.org/10.5194/acp-21-1759-2021openalex-snapshot
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inferred← citeshttps://doi.org/10.5194/acp-23-3905-2023openalex-snapshot
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inferred← citeshttps://doi.org/10.5194/acp-26-7933-2026openalex-snapshot
Satellite observations reveal heterogeneous atmospheric composition responses to rapid emission changes
inferred← citeshttps://doi.org/10.5194/amt-17-5903-2024openalex-snapshot
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inferred← citeshttps://doi.org/10.5194/amt-19-3063-2026openalex-snapshot
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inferred← citeshttps://doi.org/10.5194/egusphere-2022-1056-ac1openalex-snapshot
Reply on RC1
inferred← citeshttps://doi.org/10.5194/egusphere-2022-1056-rc1openalex-snapshot
Comment on egusphere-2022-1056
inferred← citeshttps://doi.org/10.5194/egusphere-2022-1056-rc2openalex-snapshot
Comment on egusphere-2022-1056
inferred← citeshttps://doi.org/10.5194/egusphere-2022-1056-rc3openalex-snapshot
Comment on egusphere-2022-1056
inferred← citeshttps://doi.org/10.52575/2712-7443-2024-48-2-210-220openalex-snapshot
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inferred← citeshttps://doi.org/10.59192/mapping.463openalex-snapshot
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inferred← citeshttps://doi.org/10.59324/ejmhr.2024.2(5).06openalex-snapshot
Integrated Approach for the Assessment of Real Risk of Population Exposure in Industrial Areas
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