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Spaceborne NO2 column observations from two high‐resolution instruments, TROPOMI onboard Sentinel‐5 Precursor and OMI on Aura, reveal unprecedented NO2 decreases over China, South Korea, Western Europe and the U.S. as a result of public health measures enforced to contain the coronavirus disease outbreak (Covid‐19) in January‐April 2020. The average NO2 column drop over all Chinese cities amounts to ‐40% relative to the same period in 2019, and reaches up to a factor of ~2 at heavily hit cities, e.g. Wuhan, Jinan, while the decreases in Western Europe and the U.S. are also significant (‐20 to ‐38%). In contrast with this, although Iran is also strongly affected by the disease, the observations do not show evidence of lower emissions, reflecting more limited health measures., Key Points Satellite NO2 data show substantial decreases by 40% on average over Chinese cities due to lockdown measures against the Covid‐19 outbreakWestern Europe and U.S. display robust NO2 decreases in 2020, 20‐38% relative to the same period in 2019Satellite NO2 observations above Iran, a region strongly affected by coronavirus, do not show clear evidence of lower emissions

Results from the first assessment of air quality over the Canadian oil sands–one of the largest industrial undertakings in human history–using satellite remote sensing observations of two pollutants, nitrogen dioxide (NO2) and sulfur dioxide (SO2), are presented. High-resolution maps were created that revealed distinct enhancements in both species over an area (roughly 30 km × 50 km) of intensive surface mining at scales of a few kilometers. The magnitude of these enhancements, quantified in terms of total mass, are comparable to the largest seen in Canada from individual sources. The rate of increase in NO2between 2005 and 2010 was assessed at 10.4 ± 3.5%/year and resulted from increases both in local values as well as the spatial extent of the enhancement. This is broadly consistent with both surface-measurement trends and increases in annual bitumen production. An increase in SO2 was also found, but given larger uncertainties, it is not statistically significant.

[1] This article focuses on the validation of the total ozone column (TOC) data set acquired by the Global Ozone Monitoring Experiment (GOME) and the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) satellite remote sensing instruments using the Total Ozone Retrieval Scheme for the GOME Instrument Based on the Ozone Monitoring Instrument (TOGOMI) and Total Ozone Retrieval Scheme for the SCIAMACHY Instrument Based on the Ozone Monitoring Instrument (TOSOMI) retrieval algorithms developed by the Royal Netherlands Meteorological Institute. In this analysis, spatially colocated, daily averaged ground-based observations performed by five well-calibrated Brewer spectrophotometers at the Iberian Peninsula are used. The period of study runs from January 2004 to December 2009. The agreement between satellite and ground-based TOC data is excellent (R2 higher than 0.94). Nevertheless, the TOC data derived from both satellite instruments underestimate the ground-based data. On average, this underestimation is 1.1% for GOME and 1.3% for SCIAMACHY. The SCIAMACHY-Brewer TOC differences show a significant solar zenith angle (SZA) dependence which causes a systematic seasonal dependence. By contrast, GOME-Brewer TOC differences show no significant SZA dependence and hence no seasonality although processed with exactly the same algorithm. The satellite-Brewer TOC differences for the two satellite instruments show a clear and similar dependence on the viewing zenith angle under cloudy conditions. In addition, both the GOME-Brewer and SCIAMACHY-Brewer TOC differences reveal a very similar behavior with respect to the satellite cloud properties, being cloud fraction and cloud top pressure, which originate from the same cloud algorithm (Fast Retrieval Scheme for Clouds from the Oxygen A-Band (FRESCO+)) in both the TOSOMI and TOGOMI retrieval algorithms.

[1] In this paper we present the validation results of the operational vertical ozone profiles retrieved from the nadir observations by the Ozone Monitoring Instrument (OMI) aboard the NASA Earth Observing System (EOS) Aura platform. The operational ozone profile retrieval algorithm was developed at the Royal Netherlands Meteorological Institute and the OMI mission data has been processed and made publicly available. Advantages of these nadir sounded ozone profiles are the excellent spatial resolution at nadir and daily global coverage while the vertical resolution is limited to 6–7 km. Comparisons with well-validated ozone profile recordings by the Microwave Limb Sounder (MLS) and the Tropospheric Emission Spectrometer (TES), both aboard the NASA EOS-Aura platform, provide an excellent opportunity for validation because of the large amount of collocations with OMI due to the instruments significant geographical overlap. In addition, comparisons with collocated ozone profiles from the Stratospheric Aerosol and Gas Experiment (SAGE-II), the Halogen Occultation Experiment (HALOE), the Global Ozone Monitoring by the Occultation of Stars (GOMOS) and the Optical Spectrograph and Infrared Imager System (OSIRIS) satellite instruments and balloon-borne electrochemical concentration cell (ECC) ozonesondes are presented. OMI stratospheric ozone profiles are found to agree within 20% with global correlative data except for both the polar regions during local spring. For ozone in the troposphere OMI shows a systematic positive bias versus the correlative data sets of order 60% in the tropics and 30% at midlatitude regions. The largest source of error in the tropospheric ozone profile is the fit to spectral stray light in the operational algorithm.

[1] Multi-sensor cloud height observations are investigated and compared in terms of vertical and latitudinal distributions of monthly mean cloud occurrence frequency (COF). Although this study emphasizes the standard Multiangle Imaging SpectroRadiometer (MISR) cloud top height (CTH) retrieval, the strengths and weakness among different passive and active remote sensing techniques with respect to cloud detection and height assessment are also discussed. The standard MISR CTH retrieval is less sensitive to high thin cirrus than the Atmospheric Infrared Sounder (AIRS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), but MISR provides more accurate CTH retrievals in the middle and lower troposphere compared with other passive sensors, especially for clouds in the planetary boundary layer.

Dutch Aerosol and Nitrogen Dioxide Experiments for Validation of OMI and SCIAMACHY (DANDELIONS) is a project that encompasses validation of spaceborne measurements of NO2 by the Ozone Monitoring Instrument (OMI) and Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), and of aerosol by OMI and Advanced Along-Track Scanning Radiometer (AATSR), using an extensive set of ground-based and balloon measurements over the polluted area of the Netherlands. We present an extensive data set of ground-based, balloon, and satellite data on NO2, aerosols, and ozone obtained from two campaigns within the project, held during May-June 2005 and September 2006. We have used these data for first validation of OMI NO2, and the data are available through the Aura Validation Data Center website for use in other validation efforts. In this paper we describe the available data, and the methods and instruments used, including the National Institute of Public Health and the Environment (RIVM) NO2 lidar. We show that NO2 from Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) compares well with in situ measurements. We show that different MAX-DOAS instruments, operating simultaneously during the campaign, give very similar results. We also provide unique information on the spatial homogeneity and the vertical and temporal variability of NO2, showing that during a number of days, the NO2 columns derived from measurements in different directions varied significantly, which implies that, under polluted conditions, measurements in one single azimuth direction are not always representative for the averaged field that the satellite observes. In addition, we show that there is good agreement between tropospheric NO2 from OMI and MAX-DOAS, and also between total NO2 from OMI and direct-sun observations. Observations of the aerosol optical thickness (AOT) show that values derived with three ground-based instruments correspond well with each other, and with aerosol optical thicknesses observed by OMI. Copyright 2008 by the American Geophysical Union. U7 - Export Date: 2 August 2010 U7 - Source: Scopus U7 - Art. No.: D16S46

[1] This paper presents a comparison of NO 2 data measured with the Ozone Monitoring Instrument (OMI) on board the EOS-AURA satellite with ground-based direct-Sun Brewer measurement data. Since its deployment in July 2004, OMI has provided more than 2 years of daily high-resolution (∼13 x 24 km 2 at nadir) NO 2 vertical column density maps. We describe the retrieval, which includes an estimation of the stratospheric and tropospheric fraction of total NO 2 columns, the air mass factor (AMF) correction based on detected tropospheric NO 2 enhancements, and the generation of the gridded data product. We present a validation study of the gridded NO 2 data set using data from a Brewer MK3 double monochromator in direct-Sun mode located at NASA Goddard Space Flight Center in Greenbelt, Maryland, USA. Monthly averages of coinciding measurements correlate well (r = 0.9) but OMI data are about 25% lower than the Brewer measurement data (slope 0.75, intercept -0.38 x 10 15 molecules/cm 2 ). We present a detailed uncertainty analysis for both ground and satellite data and discuss the possible reasons for the observed differences.

[1] We present an analysis of in situ NO2 measurements from aircraft experiments between summer 2004 and spring 2006. The data are from the INTEX-A, PAVE, and INTEX-B campaigns and constitute the most comprehensive set of tropospheric NO2 profiles to date. Profile shapes from INTEX-A and PAVE are found to be qualitatively similar to annual mean profiles from the GEOS-Chem model. Using profiles from the INTEX-B campaign, we perform error-weighted linear regressions to compare the Ozone Monitoring Instrument (OMI) tropospheric NO2 columns from the near-real-time product (NRT) and standard product (SP) with the integrated in situ columns. Results indicate that the OMI SP algorithm yields NO2 amounts lower than the in situ columns by a factor of 0.86 (±0.2) and that NO2 amounts from the NRT algorithm are higher than the in situ data by a factor of 1.68 (±0.6). The correlation between the satellite and in situ data is good (r = 0.83) for both algorithms. Using averaging kernels, the influence of the algorithm's a priori profiles on the satellite retrieval is explored. Results imply that air mass factors from the a priori profiles are on average slightly larger (∼10%) than those from the measured profiles, but the differences are not significant.

[1] In this paper we present validation results of the total ozone column data products of the Ozone Monitoring Instrument (OMI) by using airborne observations by the CCD Actinic Flux Spectrometer (CAFS) instrument. CAFS was flown during Aura Validation Experiment (AVE) campaigns organized by NASA in support of the validation of EOS-Aura satellite data products. The accuracy of individual CAFS total ozone column estimates of 2.0% on average is sufficient to meet the OMI validation requirements of 3.0%. A climatology was used to estimate the ozone column below the aircraft altitude. AVE validation results show that the OMI-TOMS total ozone column data product is of overall high quality as CAFS and OMI-TOMS agree to within less than 1% with a standard deviation of 8 DU (2–3%) with no significant dependence on total ozone column, latitude, cloud fraction, or solar zenith angle. The primary shortcoming in OMI-DOAS collection 2 total ozone column data is the air mass factor reflected in the dependence on solar zenith angle of the CAFS and OMI-DOAS total ozone column difference. Fortunately, the CAFS aircraft data collected during AVE provided useful insights that could not be obtained in any other way into where OMI satellite data retrieval improvements were needed. For OMI-DOAS collection 3 the air mass factor issue has been solved by calibration optimization and retrieval algorithm improvements, bringing airborne CAFS and OMI-DOAS satellite data to agreement within less than 1.5% with a standard deviation of 9 DU (2–3%), in compliance with the OMI validation requirements.

[1] Verification of the geolocation assigned to individual ground pixels as measured by the Ozone Monitoring Instrument (OMI) aboard the NASA EOS-Aura satellite was performed by comparing geophysical Earth surface details as observed in OMI false color images with the high-resolution continental outline vector map as provided by the Interactive Data Language (IDL) software tool from ITT Visual Information Solutions. The OMI false color images are generated from the OMI visible channel by integration over 20-nm-wide spectral bands of the Earth radiance intensity around 484 nm, 420 nm, and 360 nm wavelength per ground pixel. Proportional to the integrated intensity, we assign color values composed of CRT standard red, green, and blue to the OMI ground pixels. Earth surface details studied are mostly high-contrast coast lines where arid land or desert meets deep blue ocean. The IDL high-resolution vector map is based on the 1993 CIA World Database II Map with a 1-km accuracy. Our results indicate that the average OMI geolocation offset over the years 2005–2006 is 0.79 km in latitude and 0.29 km in longitude, with a standard deviation of 1.64 km in latitude and 2.04 km in longitude, respectively. Relative to the OMI nadir pixel size, one obtains mean displacements of � 6.1% in latitude and � 1.2% in longitude, with standard deviations of 12.6% and 7.9%, respectively. We conclude that the geolocation assigned to individual OMI ground pixels is sufficiently accurate to support scientific studies of atmospheric features as observed in OMI level 2 satellite data products, such as air quality issues on urban scales or volcanic eruptions and its plumes, that occur on spatial scales comparable to or smaller than OMI nadir pixels.

[1] In this paper we present validation results of the total ozone column data products of the Ozone Monitoring Instrument (OMI) on board the NASA EOS-AURA satellite through comparisons with ground-based observations by Dobson and Brewer spectrophotometer instruments. Quality-controlled and archived total ozone column data from these ground-based instruments located at stations worldwide have been used to validate more than 2 a of total ozone column observations from OMI. There are two operationally available satellite total ozone column data products, based on the OMI-TOMS and the OMI-DOAS retrieval algorithms, respectively. Validation with ground-based data focused on global comparisons and seasonal dependence and the possible dependence on latitude and solar zenith angle. Our results show a globally averaged agreement of better than 1% for OMI-TOMS data and better than 2% for OMI-DOAS data with the ground-based observations. The OMI-TOMS data product is shown to be of high overall quality with no significant dependence on solar zenith angle or latitude. The OMI-DOAS data product shows no significant dependence on latitude except for the high latitudes of the Southern Hemisphere where it systematically overestimates the total ozone value. In addition a significant dependence on solar zenith angle is found between OMI-DOAS and ground-based data. Comparisons of satellite and ground-based data tend to show a marginal seasonal dependence even though it remains unclear whether this dependence originates from the ground-based or spaceborne observations.