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Nitrogen oxides (NOx = NO + NO2) play a crucial role in the formation of ozone and secondary inorganic and organic aerosols, thus affecting human health, global radiation budget, and climate. The diurnal and spatial variations in NO2 are functions of emissions, advection, deposition, vertical mixing, and chemistry. Their observations, therefore, provide useful constraints in our understanding of these factors. We employ a Regional chEmical and trAnsport model (REAM) to analyze the observed temporal (diurnal cycles) and spatial distributions of NO2 concentrations and tropospheric vertical column densities (TVCDs) using aircraft in situ measurements and surface EPA Air Quality System (AQS) observations as well as the measurements of TVCDs by satellite instruments (OMI: the Ozone Monitoring Instrument; GOME-2A: Global Ozone Monitoring Experiment – 2A), ground-based Pandora, and the Airborne Compact Atmospheric Mapper (ACAM) instrument in July 2011 during the DISCOVER-AQ campaign over the Baltimore–Washington region. The model simulations at 36 and 4 km resolutions are in reasonably good agreement with the regional mean temporospatial NO2 observations in the daytime. However, we find significant overestimations (underestimations) of model-simulated NO2 (O3) surface concentrations during nighttime, which can be mitigated by enhancing nocturnal vertical mixing in the model. Another discrepancy is that Pandora-measured NO2 TVCDs show much less variation in the late afternoon than simulated in the model. The higher-resolution 4 km simulations tend to show larger biases compared to the observations due largely to the larger spatial variations in NOx emissions in the model when the model spatial resolution is increased from 36 to 4 km. OMI, GOME-2A, and the high-resolution aircraft ACAM observations show a more dispersed distribution of NO2 vertical column densities (VCDs) and lower VCDs in urban regions than corresponding 36 and 4 km model simulations, likely reflecting the spatial distribution bias of NOx emissions in the National Emissions Inventory (NEI) 2011.

Airborne and ground-based Pandora spectrometer NOspan classCombining double low line"inline-formula"2/span column measurements were collected during the 2018 Long Island Sound Tropospheric Ozone Study (LISTOS) in the New York City/Long Island Sound region, which coincided with early observations from the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) instrument. Both airborne- and ground-based measurements are used to evaluate the TROPOMI NOspan classCombining double low line"inline-formula"2/span Tropospheric Vertical Column (TrVC) product v1.2 in this region, which has high spatial and temporal heterogeneity in NOspan classCombining double low line"inline-formula"2/span. First, airborne and Pandora TrVCs are compared to evaluate the uncertainty of the airborne TrVC and establish the spatial representativeness of the Pandora observations. The 171 coincidences between Pandora and airborne TrVCs are found to be highly correlated (span classCombining double low line"inline-formula"ir/i2Combining double low line/spanthinsp;0.92 and slope of 1.03), with the largest individual differences being associated with high temporal and/or spatial variability. These reference measurements (Pandora and airborne) are complementary with respect to temporal coverage and spatial representativity. Pandora spectrometers can provide continuous long-term measurements but may lack areal representativity when operated in direct-sun mode. Airborne spectrometers are typically only deployed for short periods of time, but their observations are more spatially representative of the satellite measurements with the added capability of retrieving at subpixel resolutions of 250thinsp;mthinsp;span classCombining double low line"inline-formula"×/spanthinsp;250thinsp;m over the entire TROPOMI pixels they overfly. Thus, airborne data are more correlated with TROPOMI measurements (span classCombining double low line"inline-formula"ir/i2Combining double low line0.96/span) than Pandora measurements are with TROPOMI (span classCombining double low line"inline-formula"ir/i2Combining double low line0.84/span). The largest outliers between TROPOMI and the reference measurements appear to stem from too spatially coarse a priori surface reflectivity (0.5span classCombining double low line"inline-formula"g /span) over bright urban scenes. In this work, this results during cloud-free scenes that, at times, are affected by errors in the TROPOMI cloud pressure retrieval impacting the calculation of tropospheric air mass factors. This factor causes a high bias in TROPOMI TrVCs of 4thinsp;%-11thinsp;%. Excluding these cloud-impacted points, TROPOMI has an overall low bias of 19thinsp;%-33thinsp;% during the LISTOS timeframe of June-September 2018. Part of this low bias is caused by coarse a priori profile input from the TM5-MP model; replacing thesespan idCombining double low line"page6114"/ profiles with those from a 12thinsp;km North American Model-Community Multiscale Air Quality (NAMCMAQ) analysis results in a 12thinsp;%-14thinsp;% increase in the TrVCs. Even with this improvement, the TROPOMI-NAMCMAQ TrVCs have a 7thinsp;%-19thinsp;% low bias, indicating needed improvement in a priori assumptions in the air mass factor calculation. Future work should explore additional impacts of a priori inputs to further assess the remaining low biases in TROPOMI using these datasets./.

Satellite data from the Ozone Measuring Instrument (OMI) and Earth Polychromatic Imaging Camera (EPIC) are used to study long-term changes and global distribution of UV erythemal irradiance E(ζ,φ,z,t) (mW m−2) and the dimensionless UV index E ∕ (25 m Wm−2) over major cities as a function of latitude ζ, longitude φ, altitude z, and time t. Extremely high amounts of erythemal irradiance (12 < UV index ) are found for many low-latitude and high-altitude sites (e.g., San Pedro, Chile, 2.45 km; La Paz, Bolivia, 3.78 km). Lower UV indices at some equatorial or high-altitude sites (e.g., Quito, Ecuador) occur because of persistent cloud effects. High UVI levels (UVI > 6) are also found at most mid-latitude sites during the summer months for clear-sky days. OMI time-series data starting in January 2005 to December 2018 are used to estimate 14-year changes in erythemal irradiance ΔE, total column ozone ΔTCO3, cloud and haze transmission ΔCT derived from scene reflectivity LER, and reduced transmission from absorbing aerosols ΔCA derived from absorbing aerosol optical depth τA for 191 specific cities in the Northern Hemisphere and Southern Hemisphere from 60∘ S to 60∘ N using publicly available OMI data. A list of the sites showing changes at the 1 standard deviation level 1σ is provided. For many specific sites there has been little or no change in E(ζ,φ,z,t) for the period 2005–2018. When the sites are averaged over 15∘ of latitude, there are strong correlation effects of both short- and long-term cloud and absorbing aerosol change as well as anticorrelation with total column ozone change ΔTCO3. Estimates of changes in atmospheric transmission ΔCT (ζ, φ, z, t) derived from OMI-measured cloud and haze reflectivity LER and averaged over 15∘ of latitude show an increase of 1.1±1.2 % per decade between 60 and 45∘ S, almost no average 14-year change of 0.03±0.5 % per decade from 55∘ S to 30∘ N, local increases and decreases from 20 to 30∘ N, and an increase of 1±0.9 % per decade from 35 to 60∘ N. The largest changes in E(ζ,φ,z,t) are driven by changes in cloud transmission CT. Synoptic EPIC radiance data from the sunlit Earth are used to derive ozone and reflectivity needed for global images of the distribution of E(ζ,φ,z,t) from sunrise to sunset centered on the Americas, Europe–Africa, and Asia. EPIC data are used to show the latitudinal distribution of E(ζ,φ,z,t) from the Equator to 75∘ for specific longitudes. EPIC UV erythemal images show the dominating effect of solar zenith angle (SZA), the strong increase in E with altitude, and the decreases caused by cloud cover. The nearly cloud-free images of E(ζ,φ,z,t) over Australia during the summer (December) show regions of extremely high UVI (14–16) covering large parts of the continent. Zonal averages show a maximum of UVI = 14 in the equatorial region seasonally following latitudes where SZA = 0∘. Dangerously high amounts of erythemal irradiance (12 < UV index < 18) are found for many low-latitude and high-altitude sites. High levels of UVI are known to lead to health problems (skin cancer and eye cataracts) with extended unprotected exposure, as shown in the extensive health statistics maintained by the Australian Institute of Health and Welfare and the United States National Institute of Health National Cancer Institute.

NASA deployed the GeoTASO airborne UV–visible spectrometer in May–June 2017 to produce high-resolution (approximately 250 m×250 m) gapless NO2 datasets over the western shore of Lake Michigan and over the Los Angeles Basin. The results collected show that the airborne tropospheric vertical column retrievals compare well with ground-based Pandora spectrometer column NO2 observations (r2=0.91 and slope of 1.03). Apparent disagreements between the two measurements can be sensitive to the coincidence criteria and are often associated with large local variability, including rapid temporal changes and spatial heterogeneity that may be observed differently by the sunward-viewing Pandora observations. The gapless mapping strategy executed during the 2017 GeoTASO flights provides data suitable for averaging to coarser areal resolutions to simulate satellite retrievals. As simulated satellite pixel area increases to values typical of TEMPO (Tropospheric Emissions: Monitoring Pollution), TROPOMI (TROPOspheric Monitoring Instrument), and OMI (Ozone Monitoring Instrument), the agreement with Pandora measurements degraded, particularly for the most polluted columns as localized large pollution enhancements observed by Pandora and GeoTASO are spatially averaged with nearby less-polluted locations within the larger area representative of the satellite spatial resolutions (aircraft-to-Pandora slope: TEMPO scale =0.88; TROPOMI scale =0.77; OMI scale =0.57). In these two regions, Pandora and TEMPO or TROPOMI have the potential to compare well at least up to pollution scales of 30×1015 molecules cm−2. Two publicly available OMI tropospheric NO2 retrievals are found to be biased low with respect to these Pandora observations. However, the agreement improves when higher-resolution a priori inputs are used for the tropospheric air mass factor calculation (NASA V3 standard product slope =0.18 and Berkeley High Resolution product slope =0.30). Overall, this work explores best practices for satellite validation strategies with Pandora direct-sun observations by showing the sensitivity to product spatial resolution and demonstrating how the high-spatial-resolution NO2 data retrieved from airborne spectrometers, such as GeoTASO, can be used with high-temporal-resolution ground-based column observations to evaluate the influence of spatial heterogeneity on validation results.

Nitrogen oxides (NOx = NO + NO2) play a crucial role in the formation of ozone and secondary inorganic and organic aerosols, thus affecting human health, global radiation budget, and climate. The diurnal and spatial variations of NO2 are functions of emissions, advection, deposition, vertical mixing, and chemistry. Their observations, therefore, provide useful constraints in our understanding of these factors. We employ a Regional chEmical and trAnsport model (REAM) to analyze the observed temporal (diurnal cycles) and spatial distributions of NO2 concentrations and tropospheric vertical column densities (TVCDs) using aircraft in situ measurements, surface EPA Air Quality System (AQS) observations, as well as the measurements of TVCDs by satellite instruments (OMI: the Ozone Monitoring Instrument; and GOME-2A: Global Ozone Monitoring Experiment – 2A), ground-based Pandora, and the Airborne Compact Atmospheric Mapper (ACAM) instrument, in July 2011 during the DISCOVER-AQ campaign over the Baltimore-Washington region. The model simulations at 36- and 4-km resolutions are in reasonably good agreement with the temporospatial NO2 observations in the daytime. However, nighttime mixing in the model needs to be enhanced to reproduce the observed NO2 diurnal cycle in the model. Another discrepancy is that Pandora measured NO2 TVCDs show much less variation in the late afternoon than simulated in the model. Relative to the 36-km model simulations, the 4-km model results show larger biases compared to the observations due largely to the larger spatial variations of NO2 in the model when the spatial resolution is increased from 36 to 4 km, although the biases are often comparable to the ranges of the observations. The high-resolution aircraft ACAM observations show a more dispersed distribution of NO2 vertical column densities (VCDs) and lower VCDs in urban regions than 4-km model simulations, reflecting likely the spatial distribution bias of NOx emissions in the National Emissions Inventory (NEI) 2011 at high resolution.

Abundant NO2 column measurements from airborne and ground-based Pandora spectrometers were collected as part of the 2018 Long Island Sound Tropospheric Ozone Study (LISTOS) in the New York City/Long Island Sound region and coincided with early measurements from the Sentinel-5P TROPOMI instrument. Both airborne- and ground-based measurements are used to evaluate the TROPOspheric Monitoring Instrument (TROPOMI) NO2 Tropospheric Vertical Column (TrVC) product v1.2 in this region, which has high spatial and temporal heterogeneity in NO2. First, airborne and Pandora TrVCs are compared to evaluate the uncertainty of the airborne TrVC and establish the spatial representativeness of the Pandora observations. The 171 coincidences between Pandora and airborne TrVCs are found to be highly correlated (r2=0.92 and slope of 1.03) with the biggest individual differences being associated with high temporal and/or spatial variability. These reference measurements (Pandora and airborne) are complementary with respect to temporal coverage and spatial representivity. Pandora spectrometers can provide continuous long-term measurements but may lack areal representivity when operated in direct-sun mode. Airborne spectrometers are typically only deployed for short periods of time, but their observations are more spatially representative of the satellite measurements with the added capability of retrieving at subpixel resolutions of 250 m × 250 m over the entire TROPOMI pixels they overfly. Thus, airborne data are more correlated with TROPOMI measurements (r2=0.96) than Pandora measurements are with TROPOMI (r2=0.84). The largest outliers between TROPOMI and the reference measurements are caused by errors in the TROPOMI retrieval of cloud pressure impacting the calculation of tropospheric air mass factors in cloud-free scenes. This factor causes a high bias in TROPOMI TrVCs of 4–11 %. Excluding these cloud-impacted points, TROPOMI has an overall low bias of 19–33% during the LISTOS timeframe of June–September 2018. Part of this low bias is caused by coarse a priori profile input from TM5-MP model; replacing these profiles with those from a 12 km NAMCMAQ analysis results in a 12–14 % increase in the TrVCs. Even with this improvement, the TROPOMI-NAMCMAQ TrVCs have a 7–19 % low bias, indicating needed improvement in a priori assumptions in the air mass factor calculation. Future work should explore additional impacts of a priori inputs to further assess the remaining low biases in TROPOMI using these datasets.

Next generation air quality sensors are currently planned to launch within the next couple of years. The Tropospheric Emissions: Monitory of Pollution (TEMPO-United States) and Geostationary Environment Monitoring Sensor (GEMS-South Korea) are two such missions that will probe the boundary layer/lower troposphere at unprecedented spatial and temporal scales. These missions are designed to provide constraints on chemical forecast models and specifically to answer the question: "What are the temporal and spatial variations of emissions of gases and aerosols important for air quality and climate?" In preparation for these missions a number of airborne air quality field missions have been performed to collect data at similar spatial and temporal scales, and during relevant seasonal air quality episodes including fires. This data is being used to improve the trace gas retrieval algorithms and explore the unique spatial scales and diurnal patterns that will be encountered when the geostationary experiments are operational. This overview will present details of two of the instruments used during these campaigns, the GeoCAPE Airborne Simulator (GCAS) and the Geostationary Trace Gas and Aerosol Sensor Optimization (GeoTASO) instruments. Maintained at the Goddard Space Flight Center's Radiometric Calibration and Development Facility (RCDF), these instruments are similar in design and sensitivty to what will be measured on-orbit by the TEMPO and GEMS sensors. Results of the retrieval of high spatial resolution nitrogen dioxide and formaldehyde will presented. Examples of vertical column retrievals will be presented under various source/weather conditions as well as the uncertainties that result from both instrument and radiative transfer assumptions.

Ten wavelength channels of calibrated radiance image data from the sunlit Earth are obtained every 65 min during Northern Hemisphere summer from the EPIC (Earth Polychromatic Imaging Camera) instrument on the DSCOVR (Deep Space Climate Observatory) satellite located near the Earth–Sun Lagrange 1 point (L1), about 1.5 million km from the Earth. The L1 location permitted seven observations of the Moon's shadow on the Earth for about 3 h during the 21 August 2017 eclipse. Two of the observations were timed to coincide with totality over Casper, Wyoming, and Columbia, Missouri. Since the solar irradiances within five channels (λi = 388, 443, 551, 680, and 780 nm) are not strongly absorbed in the atmosphere, they can be used for characterizing the eclipse reduction in reflected radiances for the Earth's sunlit face containing the eclipse shadow. Five channels (λi = 317.5, 325, 340, 688, and 764 nm) that are partially absorbed in the atmosphere give consistent reductions compared to the non-absorbed channels. This indicates that cloud reflectivities dominate the 317.5–780 nm radiances reflected back to space from the sunlit Earth's disk with a significant contribution from Rayleigh scattering for the shorter wavelengths. An estimated reduction of 10 % was obtained for spectrally integrated radiance (387 to 781 nm) reflected from the sunlit Earth towards L1 for two sets of observations on 21 August 2017, while the shadow was in the vicinity of Casper, Wyoming (42.8666° N, 106.3131° W; centered on 17:44:50 UTC), and Columbia, Missouri (38.9517° N, 92.3341° W; centered on 18:14:50 UTC). In contrast, when non-eclipse days (20 and 23 August) are compared for each wavelength channel, the change in reflected light is much smaller (less than 1 % for 443 nm compared to 9 % (Casper) and 8 % (Columbia) during the eclipse). Also measured was the ratio REN(λi) of reflected radiance on adjacent non-eclipse days divided by radiances centered in the eclipse totality region with the same geometry for all 10 wavelength channels. The measured REN(443 nm) was smaller for Columbia (169) than for Casper (935), because Columbia had more cloud cover than Casper. REN(λi) forms a useful test of a 3-D radiative transfer models for an eclipse in the presence of optically thin clouds. Specific values measured at Casper with thin clouds are REN(340 nm) = 475, REN(388 nm) = 3500, REN(443 nm) = 935, REN(551 nm) = 5455, REN(680 nm) = 220, and REN(780 nm) = 395. Some of the variability is caused by changing cloud amounts within the moving region of totality during the 2.7 min needed to measure all 10 wavelength channels.

NASA deployed an airborne UV/Visible spectrometer, GeoTASO, in May–June 2017 to produce high resolution (approximately 250 × 250 m), gapless NO2 datasets over the western shore of Lake Michigan and over the Los Angeles Basin. Results show that the airborne tropospheric vertical column retrievals compare well with ground-based Pandora spectrometer column NO2 observations (r2 = 0.91 and slope of 1.03). Apparent disagreements between the two measurements can be sensitive to the coincidence criteria and are often associated with large local variability, including rapid temporal changes and also spatial heterogeneity that may be observed differently by the sunward viewing Pandora observations. The gapless mapping strategy executed during the 2017 GeoTASO flights provides data suitable for averaging to coarser areal resolutions to simulate satellite retrievals. As simulated satellite pixel area increases to values typical of TEMPO, TROPOMI, and OMI, the agreement with Pandora measurements is degraded as localized polluted plumes observed by Pandora are spatially averaged over larger areas (aircraft-to-Pandora slope: TEMPO scale = 0.88; TROPOMI scale = 0.77; OMI scale = 0.57). This behavior suggests that satellite products are representative of individual Pandora observations up to a certain pollution scale that depends on satellite spatial resolution. In these two regions, Pandora and TEMPO or TROPOMI have the potential to compare well up to pollution scales of 30 x 1015 molecules cm−2. Two publicly available OMI tropospheric NO2 retrievals are both found to be biased low with respect to Pandora observations (NASA V3 Standard Product slope = 0.18 and Berkeley High Resolution Product slope = 0.30). However, the agreement improves when higher resolution a priori inputs are used for the tropospheric air mass factor calculation. Overall, this work explores best practices for satellite validation strategies by showing the sensitivity to product spatial resolution and demonstrates how the high spatial resolution NO2 data retrieved from airborne spectrometers, such as GeoTASO, can be used with high temporal resolution surface observations to evaluate the influence of spatial heterogeneity on validation results.

The GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator (GCAS) was developed in support of NASA's decadal survey GEO-CAPE geostationary satellite mission. GCAS is an airborne pushbroom remote sensing instrument, consisting of two channels which make hyperspectral measurements in the ultraviolet/visible (optimized for air quality observations) and the visible/near-infrared (optimized for ocean color observations). The GCAS instrument participated in its first intensive field campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) in Texas in September 2013. During this campaign, the instrument flew on a King Air B-200 aircraft during 21 flights on 11 days to make air quality observations over Houston, Texas. We present GCAS trace gas retrievals of nitrogen dioxide (NO2) and formaldehyde (CH2O), and compare these results with trace gas columns derived from coincident in situ profile measurements of NO2 and CH2O made by instruments on a P-3B aircraft, and with NO2 observations from ground-based Pandora spectrometers operating in direct sun and scattered light modes. GCAS tropospheric column measurements correlate well spatially and temporally with columns estimated from the P-3B measurements for both NO2 (r2 = 0.89) and CH2O (r2 = 0.54) and with Pandora direct sun (r2 = 0.85) and scattered light (r2 = 0.94) observed NO2 columns. Coincident GCAS columns agree in magnitude with NO2 and CH2O P-3B-observed columns to within 10 %, but are larger than scattered light Pandora tropospheric NO2 columns by 33 % and direct sun Pandora NO2 columns by 50 %.

Ten wavelength channels of calibrated radiance image data from the Sunlit Earth are obtained every 65 minutes during Northern Hemisphere summer from the DSCOVR/EPIC instrument located near the Earth-Sun Lagrange-1 point (L 1 ), 1.5 million km from the Earth. The L 1 location permitted seven observations of the Moon’s shadow on the Earth for about 3 hours during the 21 August 2017 eclipse. Two of the observations were timed to be over Casper, Wyoming and Columbia, Missouri. Since, the solar irradiances within 5 channels (λ i = 388, 443, 551, 680, and 780 nm) are not strongly absorbed in the atmosphere, they can be used for characterizing eclipse reduction in reflected radiances for the sunlit face of the Earth containing the eclipse shadow. Five channels (λ i = 317.5, 325, 340, 688, and 764 nm) that are partially absorbed in the atmosphere give consistent reductions compared to the non-absorbed channels. This indicates that cloud reflectivities dominate the 317.5 to 780 nm radiances reflected back to space from the sunlit Earth’s disk with a strong contribution from Rayleigh scattering for the shorter wavelengths. A reduction of 9.7 ± 1.7 % in the radiance (387 to 781 nm) reflected from the Earth towards L 1 was obtained for the set of observations on 21 August 2017, while the shadow was in the vicinity of Casper, Wyoming (42.8666° N, 106.3131° W, centered on 17:44:50 UTC). In contrast, when successive non-eclipse days are compared for each wavelength channel, the change in reflected light is much smaller (less than 1 % for 443 nm compared to 9 % during the eclipse). Also measured was the spatially averaged ratio R EN (λ i ) > of reflected radiance within the eclipse totality region to radiances for the same geometry on adjacent non-eclipse days for all 10 wavelength channels. The measured R EN (443 nm) > was smaller for Columbia (35) than for Casper (122), because Columbia had more cloud cover than Casper. R EN (λ i ) forms a useful test of 3-D radiative transfer models for an eclipse in the presence of optically thin clouds. A previously published clear-sky model (Emde and Mayer, 2007) shows results for a nearly overhead eclipse had R EN (340 nm)=1.7 x 10 4 compared to the maximum measured non-averaged R EN (340) at Casper of 515 ± 27 with optically thin clouds under similar geometrical conditions.

The Airborne Compact Atmospheric Mapper (ACAM), an ultraviolet/visible/near-infrared spectrometer, has been flown on board the NASA UC-12 aircraft during the DISCOVER-AQ (Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality) campaigns to provide remote sensing observations of tropospheric and boundary layer pollutants from its radiance measurements. To improve the trace gas retrieval from ACAM measurements, we perform detailed characterization and verification of ACAM slit functions. The wavelengths and slit functions of ACAM measurements are characterized for the air quality channel (~304–500 nm) through cross-correlation with a high-resolution solar irradiance reference spectrum after necessarily accounting for atmospheric gas absorption and the Ring effect in the calibration process. The derived slit functions, assuming a hybrid combination of asymmetric Gaussian and top-hat slit functions, agree very well with the laboratory-measured slit functions. Comparisons of trace gas retrievals between using derived and measured slit functions demonstrate that the cross-correlation technique can be reliably used to characterize slit functions for trace gas retrievals.