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The inactivation time for the SARS CoV-2 virus, mostly by a portion of UVB spectrum (290–315 nm) in sunlight, has been estimated using radiative transfer calculations and a relative wavelength sensitivity virus inactivation action spectrum ALS. The action spectrum is adjusted for the SARS CoV-2 virus using a derived UV dose D90 = 3.2 J/m2 for 90% inactivation to match laboratory results for the inactivation of SARS CoV-2 virus droplets on steel mesh. Estimation of the time for 90% inactivation T90 at a specific geographic location can be simplified using the commonly published or calculated UV index (UVI). The use of UVI has the advantage that information on the amount of ozone, the site altitude, and the degree of cloud cover are built into the published UVI calculation. Simple power-law T90(UVI) = a UVIb fitting equations are derived that provide estimates of T90(UVI) for 270 specific locations. Using the results from the 270 locations, a generalized latitude θ dependence is presented for the coefficients a(θ) and b(θ) that enables T90(θ, UVI) to be estimated for 60°S ≤ θ ≤ 60°N and for noon and 2 h around local solar noon.

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.

Multi-axis differential optical absorption spectroscopy (MAX-DOAS) and direct sun NO2 vertical column network data are used to investigate the accuracy of tropospheric NO2 column measurements of the GOME-2 instrument on the MetOp-A satellite platform and the OMI instrument on Aura. The study is based on 23 MAX-DOAS and 16 direct sun instruments at stations distributed worldwide. A method to quantify and correct for horizontal dilution effects in heterogeneous NO2 field conditions is proposed. After systematic application of this correction to urban sites, satellite measurements are found to present smaller biases compared to ground-based reference data in almost all cases. We investigate the seasonal dependence of the validation results as well as the impact of using different approaches to select satellite ground pixels in coincidence with ground-based data. In optimal comparison conditions (satellite pixels containing the station) the median bias between satellite tropospheric NO2 column measurements and the ensemble of MAX-DOAS and direct sun measurements is found to be significant and equal to −34 % for GOME-2A and −24 % for OMI. These biases are further reduced to −24 % and −18 % respectively, after application of the dilution correction. Comparisons with the QA4ECV satellite product for both GOME-2A and OMI are also performed, showing less scatter but also a slightly larger median tropospheric NO2 column bias with respect to the ensemble of MAX-DOAS and direct sun measurements.

While solar eclipses are known to greatly diminish the visible radiation reaching the surface of the Earth, less is known about the magnitude of the impact. We explore both the observed and modeled levels of change in surface radiation during the eclipse of 2017. We deployed a pyranometer and Pandora spectrometer instrument to Casper, Wyoming, and Columbia, Missouri, to measure surface broadband shortwave (SW) flux and atmospheric properties during the 21 August 2017 solar eclipse event. We performed detailed radiative transfer simulations to understand the role of clouds in spectral and broadband solar radiation transfer in the Earth's atmosphere for the normal (non-eclipse) spectrum and red-shift solar spectra for eclipse conditions. The theoretical calculations showed that the non-eclipse-to-eclipse surface flux ratio depends strongly on the obscuration of the solar disk and slightly on the cloud optical depth. These findings allowed us to estimate what the surface broadband SW flux would be for hypothetical non-eclipse conditions from observations during the eclipse and further to quantify the impact of the eclipse on the surface broadband SW radiation budget. We found that the eclipse caused local reductions of time-averaged surface flux of about 379 W m−2 (50 %) and 329 W m−2 (46 %) during the ∼3 h course of the eclipse at the Casper and Columbia sites, respectively. We estimated that the Moon's shadow caused a reduction of approximately 7 %–8 % in global average surface broadband SW radiation. The eclipse has a smaller impact on the absolute value of surface flux reduction for cloudy conditions than a clear atmosphere; the impact decreases with the increase in cloud optical depth. However, the relative time-averaged reduction of local surface SW flux during a solar eclipse is approximately 45 %, and it is not sensitive to cloud optical depth. The reduction of global average SW flux relative to climatology is proportional to the non-eclipse and eclipse flux difference in the penumbra area and depends on cloud optical depth in the Moon's shadow and geolocation due to the change in solar zenith angle. We also discuss the influence of cloud inhomogeneity on the observed SW flux. Our results not only quantify the reduction of the surface solar radiation budget, but also advance the understanding of broadband SW radiative transfer under solar eclipse conditions.

UVB in sunlight, 290–315 nm, can inactivate SARS CoV and SARS CoV-2 viruses on surfaces and in the air. Laboratory exposure to ultraviolet irradiance in the UVC range inactivates many viruses and bacteria in times less than 30 min. Estimated UVB inactivation doses from sunlight in J/m2 are obtained from UVC measurements and radiative transfer calculations, weighted by a virus inactivation action spectrum, using OMI satellite atmospheric data for ozone, clouds, and aerosols. For SARS CoV, using an assumed UVC dose near the mid-range of measured values, D90 = 40 J/m2, 90% inactivation times T90 are estimated for exposure to midday 10:00–14:00 direct plus diffuse sunlight and for nearby locations in the shade (diffuse UVB only). For the assumed D90 = 40 J/m2 model applicable to SARS CoV viruses, calculated estimates show that near noon 11:00–13:00 clear-sky direct sunlight gives values of T90 < 90 min for mid-latitude sites between March and September and less than 60 min for many equatorial sites for 12 months of the year. Recent direct measurements of UVB sunlight inactivation of the SARS CoV-2 virus that causes COVID-19 show shorter T90 inactivation times less than 10 min depending on latitude, season, and hour. The equivalent UVC 254 nm D90 dose for SARS CoV-2 is estimated as 3.2 ± 0.7 J/m2 for viruses on a steel mesh surface and 6.5 ± 1.4 J/m2 for viruses in a growth medium. For SARS CoV-2 clear-sky T90 on a surface ranges from 4 min in the equatorial zone to less than 30 min in a geographic area forming a near circle with solar zenith angle < 60O centered on the subsolar point for local solar times from 09:00 to 15:00 h.

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's Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ, conducted in 2011–2014) campaign in the United States and the joint NASA and National Institute of Environmental Research (NIER) Korea–United States Air Quality Study (KORUS-AQ, conducted in 2016) in South Korea were two field study programs that provided comprehensive, integrated datasets of airborne and surface observations of atmospheric constituents, including nitrogen dioxide (NO2), with the goal of improving the interpretation of spaceborne remote sensing data. Various types of NO2 measurements were made, including in situ concentrations and column amounts of NO2 using ground- and aircraft-based instruments, while NO2 column amounts were being derived from the Ozone Monitoring Instrument (OMI) on the Aura satellite. This study takes advantage of these unique datasets by first evaluating in situ data taken from two different instruments on the same aircraft platform, comparing coincidently sampled profile-integrated columns from aircraft spirals with remotely sensed column observations from ground-based Pandora spectrometers, intercomparing column observations from the ground (Pandora), aircraft (in situ vertical spirals), and space (OMI), and evaluating NO2 simulations from coarse Global Modeling Initiative (GMI) and high-resolution regional models. We then use these data to interpret observed discrepancies due to differences in sampling and deficiencies in the data reduction process. Finally, we assess satellite retrieval sensitivity to observed and modeled a priori NO2 profiles. Contemporaneous measurements from two aircraft instruments that likely sample similar air masses generally agree very well but are also found to differ in integrated columns by up to 31.9 %. These show even larger differences with Pandora, reaching up to 53.9 %, potentially due to a combination of strong gradients in NO2 fields that could be missed by aircraft spirals and errors in the Pandora retrievals. OMI NO2 values are about a factor of 2 lower in these highly polluted environments due in part to inaccurate retrieval assumptions (e.g., a priori profiles) but mostly to OMI's large footprint (>312 km2).

In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 d during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, the Netherlands (51.97∘ N, 4.93∘ E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were (1) to characterise and better understand the differences between a large number of multi-axis differential optical absorption spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, (2) to define a robust methodology for performance assessment of all participating instruments, and (3) to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen collision complex (O4) and ozone (O3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region, and NO2 in an additional (smaller) wavelength range in the visible region. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in a unique set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the selected reference (which is obtained from the median of either all data sets or a subset), and the rms error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the consistency between all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.

The Geostationary Environment Monitoring Spectrometer (GEMS) is scheduled for launch in February 2020 to monitor air quality (AQ) at an unprecedented spatial and temporal resolution from a geostationary Earth orbit (GEO) for the first time. With the development of UV–visible spectrometers at sub-nm spectral resolution and sophisticated retrieval algorithms, estimates of the column amounts of atmospheric pollutants (O3, NO2, SO2, HCHO, CHOCHO, and aerosols) can be obtained. To date, all the UV–visible satellite missions monitoring air quality have been in low Earth orbit (LEO), allowing one to two observations per day. With UV–visible instruments on GEO platforms, the diurnal variations of these pollutants can now be determined. Details of the GEMS mission are presented, including instrumentation, scientific algorithms, predicted performance, and applications for air quality forecasts through data assimilation. GEMS will be on board the Geostationary Korea Multi-Purpose Satellite 2 (GEO-KOMPSAT-2) satellite series, which also hosts the Advanced Meteorological Imager (AMI) and Geostationary Ocean Color Imager 2 (GOCI-2). These three instruments will provide synergistic science products to better understand air quality, meteorology, the long-range transport of air pollutants, emission source distributions, and chemical processes. Faster sampling rates at higher spatial resolution will increase the probability of finding cloud-free pixels, leading to more observations of aerosols and trace gases than is possible from LEO. GEMS will be joined by NASA’s Tropospheric Emissions: Monitoring of Pollution (TEMPO) and ESA’s Sentinel-4 to form a GEO AQ satellite constellation in early 2020s, coordinated by the Committee on Earth Observation Satellites (CEOS).

Near-surface air quality (AQ) observations over coastal waters are scarce, a situation that limits our capacity to monitor pollution events at land-water interfaces. Satellite measurements of total column (TC) nitrogen dioxide (NO2) observations are a useful proxy for combustion sources but the once daily snapshots available from most sensors are insufficient for tracking the diurnal evolution and transport of pollution. Ground-based remote sensors like the Pandora Spectrometer Instrument (PSI) that have been developed to verify space-based total column NO2 and other trace gases are being tested for routine use as certified AQ monitors. The KORUS-OC (Korea-United States Ocean Color) cruise aboard the R/V Onnuri in May-June 2016 represented an opportunity to study AQ near the South Korean coast, a region affected by both local/regional and long-distance pollution sources. Using PSI data in direct-sun mode and in situ sensors for shipboard ozone, CO and NO2, we explore, for the first time, relationships between TC NO2 and surface AQ in this coastal region. Three case studies illustrate the value of the PSI as well as complexities in the surface-column NO2 relationship caused by varying meteorological conditions. Case Study 1 (25-26 May 2016) exhibited a high correlation of surface NO2 to TC NO2 measured by both PSI and Aura's Ozone Monitoring Instrument (OMI) but two other cases displayed poor relationships between in situ and TC NO2 due to decoupling of pollution layers from the surface. With suitable interpretation the PSI TC NO2 measurement demonstrates good potential for working with upcoming geostationary satellites to advance diurnal tracking of pollution.

EPIC (Earth Polychromatic Imaging Camera) raw level-0 (L0) data in one channel is a 12-bit 2048x2048 pixels image array plus auxiliary data such as telemetry, temperature readings, cloud, aerosol, ocean surface and vegetation properties, sulfur dioxide, etc. The EPIC L1a processor applies a series of correction steps on the L0 data to convert them into corrected count rates (level-1a or L1a data): Dark correction, Enhanced pixel detection, Read wave correction, Latency correction, Non-linearity correction, Temperature correction, Conversion to count rates, Flat fielding, and Stray light correction. L1a images should have all instrumental effects removed and only need to be multiplied by one single number for each wavelength to obtain radiances, which are the basis for all higher-level EPIC products, such as ozone and sulfur dioxide total column amounts, vegetation index, cloud, aerosol, ocean surface and vegetation properties, etc. This paper gives an overview of the mathematics and the pre-launch and on-orbit calibration behind each correction step.

Retrievals of total column NO2 (TCNO2) are compared for 14 sites from the Ozone Measuring Instrument (OMI using OMNO2-NASA v3.1) on the AURA satellite and from multiple ground-based PANDORA spectrometer instruments making direct-sun measurements. While OMI accurately provides the daily global distribution of retrieved TCNO2, OMI almost always underestimates the local amount of TCNO2 by 50 % to 100 % in polluted areas, while occasionally the daily OMI value exceeds that measured by PANDORA at very clean sites. Compared to local ground-based or aircraft measurements, OMI cannot resolve spatially variable TCNO2 pollution within a city or urban areas, which makes it less suitable for air quality assessments related to human health. In addition to systematic underestimates in polluted areas, OMI's selected 13:30 Equator crossing time polar orbit causes it to miss the frequently much higher values of TCNO2 that occur before or after the OMI overpass time. Six discussed Northern Hemisphere PANDORA sites have multi-year data records (Busan, Seoul, Washington DC, Waterflow, New Mexico, Boulder, Colorado, and Mauna Loa), and one site in the Southern Hemisphere (Buenos Aires, Argentina). The first four of these sites and Buenos Aires frequently have high TCNO2 (TCNO2 > 0.5 DU). Eight additional sites have shorter-term data records in the US and South Korea. One of these is a 1-year data record from a highly polluted site at City College in New York City with pollution levels comparable to Seoul, South Korea. OMI-estimated air mass factor, surface reflectivity, and the OMI 24 km × 13 km FOV (field of view) are three factors that can cause OMI to underestimate TCNO2. Because of the local inhomogeneity of NOx emissions, the large OMI FOV is the most likely factor for consistent underestimates when comparing OMI TCNO2 to retrievals from the small PANDORA effective FOV (measured in m2) calculated from the solar diameter of 0.5∘.

Near-surface air quality (AQ) observations over coastal waters are scarce, a situation that limits our capacity to monitor pollution events at land-water interfaces. Satellite measurements of total column (TC) nitrogen dioxide (NO(2)) observations are a useful proxy for combustion sources but the once daily snapshots available from most sensors are insufficient for tracking the diurnal evolution and transport of pollution. Ground-based remote sensors like the Pandora Spectrometer Instrument (PSI) that have been developed to verify space-based total column NO(2) and other trace gases are being tested for routine use as certified AQ monitors. The KORUS-OC (Korea-United States Ocean Color) cruise aboard the R/V Onnuri in May-June 2016 represented an opportunity to study AQ near the South Korean coast, a region affected by both local/regional and long-distance pollution sources. Using PSI data in direct-sun mode and in situ sensors for shipboard ozone, CO and NO(2), we explore, for the first time, relationships between TC NO(2) and surface AQ in this coastal region. Three case studies illustrate the value of the PSI as well as complexities in the surface-column NO(2) relationship caused by varying meteorological conditions. Case Study 1 (25-26 May 2016) exhibited a high correlation of surface NO(2) to TC NO(2) measured by both PSI and Aura’s Ozone Monitoring Instrument (OMI) but two other cases displayed poor relationships between in situ and TC NO(2) due to decoupling of pollution layers from the surface. With suitable interpretation the PSI TC NO(2) measurement demonstrates good potential for working with upcoming geostationary satellites to advance diurnal tracking of pollution.

TEMPO was selected in 2012 by NASA as the first Earth Venture Instrument, for launch between 2018 and 2021. It will measure atmospheric pollution for greater North America from space using ultraviolet and visible spectroscopy. TEMPO observes from Mexico City, Cuba, and the Bahamas to the Canadian oil sands, and from the Atlantic to the Pacific, hourly and at high spatial resolution (~2.1 km N/S×4.4 km E/W at 36.5°N, 100°W). TEMPO provides a tropospheric measurement suite that includes the key elements of tropospheric air pollution chemistry, as well as contributing to carbon cycle knowledge. Measurements are made hourly from geostationary (GEO) orbit, to capture the high variability present in the diurnal cycle of emissions and chemistry that are unobservable from current low-Earth orbit (LEO) satellites that measure once per day. The small product spatial footprint resolves pollution sources at sub-urban scale. Together, this temporal and spatial resolution improves emission inventories, monitors population exposure, and enables effective emission-control strategies. TEMPO takes advantage of a commercial GEO host spacecraft to provide a modest cost mission that measures the spectra required to retrieve ozone (O), nitrogen dioxide (NO), sulfur dioxide (SO), formaldehyde (HCO), glyoxal (CHO), bromine monoxide (BrO), IO (iodine monoxide), water vapor, aerosols, cloud parameters, ultraviolet radiation, and foliage properties. TEMPO thus measures the major elements, directly or by proxy, in the tropospheric O chemistry cycle. Multi-spectral observations provide sensitivity to O in the lowermost troposphere, substantially reducing uncertainty in air quality predictions. TEMPO quantifies and tracks the evolution of aerosol loading. It provides these near-real-time air quality products that will be made publicly available. TEMPO will launch at a prime time to be the North American component of the global geostationary constellation of pollution monitoring together with the European Sentinel-4 (S4) and Korean Geostationary Environment Monitoring Spectrometer (GEMS) instruments.

MAX-DOAS and direct sun NO2 vertical column network data are used to investigate the accuracy of tropospheric NO2 column measurements of the GOME-2 instrument on the MetOP-A satellite platform and the OMI instrument on Aura. The study is based on 23 MAX-DOAS and 16 direct sun instruments at stations distributed worldwide. A method to quantify and correct for horizontal dilution effects in heterogeneous NO2 field conditions is proposed. After systematic application of this correction to urban sites, satellite measurements are found to present smaller biases compared to ground-based reference data in almost all cases. We investigate the seasonal dependence of the validation results, as well as the impact of using different approaches to select satellite ground pixels in coincidence with ground-based data. In optimal comparison conditions (satellite pixels containing the station) the median bias between satellite tropospheric NO2 column measurements and the ensemble of MAX-DOAS and direct sun measurements is found to be significant and equal to −36 % for GOME-2A and −20 % for OMI. These biases are further reduced to −24 % and −8 % respectively, after application of the dilution correction. Comparisons with the QA4ECV satellite product for both GOME-2A and OMI is also performed, showing less scatter but also a slightly larger median tropospheric NO2 column bias with respect to the ensemble of MAX-DOAS and direct sun measurements.

The San Joaquin Valley (SJV) of California has one of the nation's most severe wintertime PM2.5 pollution problems. The DISCOVER-AQ (Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality) field campaign took place in the SJV from January 16 to February 6, 2013. It captured two PM2.5 pollution episodes with peak 24-h concentrations approaching 70 μg/m3. Using meteorological fields generated from WRFv3.6, CMAQv5.0.2 was applied to simulate PM2.5 formation in the SJV from January 10 through February 10, 2013. Overall, the model was able to capture the observed accumulation of PM2.5 within the simulation period. The model was able to produce increased concentrations of ammonium nitrate and organic carbon, which are two major components of wintertime PM2.5 in the SJV. Comparison to measurements made by aircraft showed that there was general agreement between observed and modeled daytime vertical distributions of selected gas and particulate species, reflecting the adequacy of modeled daytime mixing layer heights. Excess ammonia predicted by the model implied that ammonium nitrate formation was limited by the availability of nitric acid, consistent with observations. Evaluation of the ammonium nitrate diurnal profile revealed that the observed morning increase of ammonium nitrate was also evident from the model. This paper demonstrates that the CMAQ model is able to simulate elevated wintertime PM2.5 formation observed in the SJV during the DISCOVER-AQ 2013 period, which featured both climatic (i.e., 2011–2014 California Drought) and emissions differences compared to a previous large air quality field campaign in the SJV during 1999–2000. Keywords: CMAQ, DISCOVER-AQ, PM2.5 modeling, San joaquin valley

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 push-broom 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) campaign 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 %.

Aerosol optical thickness (tau(aer))) is a fundamental parameter for analyzing aerosol loading and associated radiative effects. Tau(aer) can constrain many inversion algorithms using passive/active sensor measurements to retrieve other aerosol properties and/or the abundance of trace gases. In the next wave of spectroradiometric observations from geostationary platforms, we envision that a strategically distributed network of robust, well-calibrated ground-based spectroradiometers will comprehensively complement spaceborne measurements in spectral and temporal domains. Spectral tau(aer) can be accurately obtained from direct-Sun measurements based on the Langley calibration method, which allows for the analysis of distinct spectral features of the calibration results. In this study, we present a spectral tau(aer) retrieval algorithm for an in-house developed, field deployable spectroradiometer instrument covering wavelengths from ultraviolet to near infrared (UV-Vis-NIR). The spectral total optical thickness obtained from the Langley calibration method is partitioned into molecular and particulate components by utilizing a least-squares method. The resulting high temporal-resolution tau(aer) and Angstrom Exponent can be used effectively for cloud screening. The new algorithm was applied to months-long measurements acquired from the rooftop at NASA Goddard Space Flight Center's Building 33. The retrieved tau(aer) demonstrated excellent agreement with those from well-calibrated Aerosol Robotic Network (AERONET) sunphotometers at all overlapping wavelengths (correlation coefficients higher than 0.98). In addition, empirical stray light corrections considerably improved tau(aer) retrievals at short wavelengths in the UV. The continuous spectrum of tau(aer) from UV-Vis-NIR spectroradiometers is expected to provide more informative constraints for retrieval of additional aerosol properties such as refractive indices, size, and bulk vertical distribution.

Vertical column density (VCD) of nitrogen dioxide was measured using Pandora spectrometers at six sites on the Korean Peninsula during the Megacity Air Pollution Studies-Seoul (MAPS-Seoul) campaign from May to June 2015. To estimate the tropospheric nitrogen dioxide VCD, the stratospheric nitrogen dioxide VCD from the Ozone Monitoring Instrument (OMI) was subtracted from the total nitrogen dioxide VCD from Pandora. European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis wind data was used to analyze variations in tropospheric nitrogen dioxide VCD caused by wind patterns at each site. The Yonsei/SEO site was found to have the largest tropospheric nitrogen dioxide VCD (1.49 DU on average) from a statistical analysis of hourly tropospheric nitrogen dioxide VCD measurements. At rural sites, remarkably low nitrogen dioxide VCDs were observed. However, a wind field analysis showed that trans-boundary transport and emissions from domestic sources lead to an increase in tropospheric nitrogen dioxide VCD at NIER/BYI and KMA/AMY, respectively. At urban sites, high nitrogen dioxide VCD values were observed under conditions of low wind speed, which were influenced by local urban emissions. Tropospheric nitrogen dioxide VCD at HUFS/Yongin increases under conditions of significant transport from urban area of Seoul according to a correlation analysis that considers the transport time lag. Significant diurnal variations were found at urban sites during the MAPS Seoul campaign, but not at rural sites, indicating that it is associated with diurnal patterns of nitrogen dioxide emissions from dense traffic.

EPIC (Earth Polychromatic Imaging Camera) on board the DSCOVR (Deep Space Climate Observatory) spacecraft is the first earth science instrument located near the earth–sun gravitational plus centrifugal force balance point, Lagrange 1. EPIC measures earth-reflected radiances in 10 wavelength channels ranging from 317.5 to 779.5 nm. Of these channels, four are in the UV range 317.5, 325, 340, and 388 nm, which are used to retrieve O3, 388 nm scene reflectivity (LER: Lambert equivalent reflectivity), SO2, and aerosol properties. These new synoptic quantities are retrieved for the entire sunlit globe from sunrise to sunset multiple times per day as the earth rotates in EPIC's field of view. Retrieved ozone amounts agree with ground-based measurements and satellite data to within 3 %. The ozone amounts and LER are combined to derive the erythemal irradiance for the earth's entire sunlit surface at a nadir resolution of 18 × 18 km2 using a computationally efficient approximation to a radiative transfer calculation of irradiance. The results show very high summertime values of the UV index (UVI) in the Andes and Himalayas (greater than 18), and high values of UVI near the Equator at equinox.

Nitrogen dioxide (NO2) is a short-lived atmospheric pollutant that serves as an air quality indicator, and is itself a health concern. The Airborne Compact Atmospheric Mapper (ACAM) was flown on board the NASA UC-12 aircraft during the DISCOVER-AQ Maryland field campaign in July 2011. The instrument collected hyperspectral remote sensing measurements in the 304-910 nm range, allowing day-time observations of several tropospheric pollutants, including nitrogen dioxide (NO2), at an unprecedented spatial resolution of 1.5 × 1.1 km2. Retrievals of slant column abundance are based on the Differential Optical Absorption Spectroscopy (DOAS) method. For the Air Mass Factor (AMF) computations needed to convert these retrievals to vertical column abundance, we include high resolution information for the surface reflectivity by using bidirectional reflectance distribution function (BRDF) data from the Moderate Resolution Imaging Spectroradiometer (MODIS). We use high-resolution simulated vertical distributions of NO2 from the Community Multiscale Air Quality (CMAQ) and Global Modeling Initiative (GMI) models to account for the temporal variation in atmospheric NO2 to retrieve middle- and lower-tropospheric NO2 columns (NO2 below the aircraft). We compare NO2 derived from ACAM measurements with in-situ observations from NASA's P-3B research aircraft, total column observations from the ground-based Pandora spectrometers, and tropospheric column observations from the space-based OMI instrument. The high-resolution ACAM measurements not only give new insights into our understanding of atmospheric composition and chemistry through observation of sub-sampling variability in typical satellite and model resolutions, but they also provide opportunities for testing algorithm improvements for forthcoming geostationary air quality missions.

NASA’s Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaign in the United States and the joint NASA and National Institute of Environmental Research (NIER) Korea-United States Air Quality Study (KORUS-AQ) in South Korea were two field study programs that provided comprehensive, integrated datasets of airborne and surface observations of atmospheric constituents, including nitrogen dioxide (NO2), with a goal of improving the interpretation of spaceborne remote sensing data. Various types of NO2 measurements were made, including in situ concentrations and column amounts of NO2 using ground- and aircraft-based instruments, while NO2 column amounts were being derived from the Ozone Monitoring Instrument (OMI) on the Aura satellite. This study takes advantage of these unique data sets by first evaluating in situ data taken from two different instruments on the same aircraft platform, comparing coincidently sampled profile-integrated columns from aircraft spirals with remotely sensed column observations from ground-based Pandora spectrometers, intercomparing column observations from the ground (Pandora), aircraft (in situ vertical spirals), and space (OMI), and evaluating NO2 simulations from coarse Global Modeling Initiative (GMI) and high-resolution regional models. We then use these data to interpret observed discrepancies due to differences in sampling and deficiencies in the data reduction process. Finally, we assess satellite retrieval sensitivity to observed and modeled a-priori NO2 profiles. Contemporaneous measurements from two aircraft instruments that likely sample similar air masses generally agree very well but are also found to differ in integrated columns by up to 33.3 %. These show even larger differences with Pandora, reaching up to 53.1 %, potentially due to a combination of strong gradients in NO2 fields that could be missed by aircraft spirals and errors in the Pandora retrievals. OMI NO2 values are about a factor of two lower in these highly polluted environments, due in part to inaccurate retrieval assumptions (e.g., a priori profiles), but mostly to OMI’s areal (> 312 km2) averaging.

Vertical column density (VCD) of nitrogen dioxide (NO2) was measured using Pandora spectrometers at six sites on the Korean Peninsula during the Megacity Air Pollution Studies-Seoul (MAPS-Seoul) campaign from May to June 2015. To estimate the tropospheric NO(2) VCD, the stratospheric NO(2) VCD from the Ozone Monitoring Instrument (OMI) was subtracted from the total NO(2) VCD from Pandora. European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis wind data was used to analyze variations in tropospheric NO(2) VCD caused by wind patterns at each site. The Yonsei/SEO site was found to have the largest tropospheric NO(2) VCD (1.49 DU on average) from a statistical analysis of hourly tropospheric NO(2) VCD measurements. At rural sites, remarkably low NO(2) VCDs were observed. However, a wind field analysis showed that trans-boundary transport and emissions from domestic sources lead to an increase in tropospheric NO(2) VCD at NIER/BYI and KMA/AMY, respectively. At urban sites, high NO(2) VCD values were observed under conditions of low wind speed, which were influenced by local urban emissions. Tropospheric NO(2) VCD at HUFS/Yongin increases under conditions of significant transport from urban area of Seoul according to a correlation analysis that considers the transport time lag. Significant diurnal variations were found at urban sites during the MAPS-Seoul campaign, but not at rural sites, indicating that it is associated with diurnal patterns of NO(2) emissions from dense traffic.

The NASA/Smithsonian Tropospheric Emissions: Monitoring of Pollution (TEMPO; tempo.si.edu) satellite instrument will measure atmospheric pollution and much more over Greater North America at high temporal resolution (hourly or better in daylight, with selected observations at 10 minute or better sampling) and high spatial resolution (10 km2 at the center of the field of regard). It will measure ozone (O3) profiles (including boundary layer O3), and columns of nitrogen dioxide (NO2), nitrous acid (HNO2), sulfur dioxide (SO2), formaldehyde (H2CO), glyoxal (C2H2O2), water vapor (H2O), bromine oxide (BrO), iodine oxide (IO), chlorine dioxide (OClO), as well as clouds and aerosols, foliage properties, and ultraviolet B (UVB) radiation. The instrument has been delivered and is awaiting spacecraft integration and launch in 2022. This talk describes a selection of TEMPO applications based on the TEMPO Green Paper living document (http://tempo.si.edu/publications.html). Applications to air quality and health will be summarized. Other applications presented include: biomass burning and O3 production; aerosol products including synergy with GOES infrared measurements; lightning NOx; soil NOx and fertilizer application; crop and forest damage from O3; chlorophyll and primary productivity; foliage studies; halogens in coastal and lake regions; ship tracks and drilling platform plumes; water vapor studies including atmospheric rivers, hurricanes, and corn sweat; volcanic emissions; air pollution and economic evolution; high-resolution pollution versus traffic patterns; tidal effects on estuarine circulation and outflow plumes; air quality response to power blackouts and other exceptional events.

In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 days during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, The Netherlands (51.97° N, 4.93° E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were to characterise and better understand the differences between a large number of Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, to discuss the performance of the various types of instruments and to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen dimer (O4) and ozone (O3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region and NO2 in an additional (smaller) wavelength range in the visible. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in an unprecedented set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the reference, and the RMS error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the measurement performance of all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.

We present the comparison of satellite-based OMI (Ozone Monitoring Instrument) NO2 products with ground-based observations in Helsinki. OMI NO2 total columns, available from NASA's standard product (SP) and KNMI DOMINO product, are compared with the measurements performed by the Pandora spectrometer in Helsinki in 2012. The relative difference between Pandora no. 21 and OMI SP total columns is 4 and −6 % for clear-sky and all-sky conditions, respectively. DOMINO NO2 retrievals showed slightly lower total columns with median differences about −5 and −14 % for clear-sky and all-sky conditions, respectively. Large differences often correspond to cloudy fall–winter days with solar zenith angles above 65°. Nevertheless, the differences remain within the retrieval uncertainties. The average difference values are likely the result of different factors partly canceling each other: the overestimation of the stratospheric columns causes a positive bias partly compensated by the limited spatial representativeness of the relatively coarse OMI pixel for sharp NO2 gradients. The comparison between Pandora and the new version (V3) of OMI NO2 retrievals shows a larger negative difference (about −30 %) than the current version (V2.1) because the revised spectral fitting procedure reduces the overestimation of the stratospheric column. The weekly and seasonal cycles from OMI, Pandora and NO2 surface concentrations are also compared. Both satellite- and ground-based data show a similar weekly cycle, with lower NO2 levels during the weekend compared to the weekdays as a result of reduced emissions from traffic and industrial activities. The seasonal cycle also shows a similar behavior, even though the results are affected by the fact that most of the data are available during spring–summer because of cloud cover in other seasons. This is one of few works in which OMI NO2 retrievals are evaluated in a urban site at high latitudes (60° N). Despite the city of Helsinki having relatively small pollution sources, OMI retrievals have proved to be able to describe air quality features and variability similar to surface observations. This adds confidence in using satellite observations for air quality monitoring also at high latitudes.

The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a test bed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA Falcon aircraft in its first intensive field measurement campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Earth Venture Mission over Houston, Texas, in September 2013. Measurements of backscattered solar radiation between 420 and 465 nm collected on 4 days during the campaign are used to determine slant column amounts of NO2 at 250 m × 250 m spatial resolution with a fitting precision of 2.2 × 1015 moleculescm−2. These slant columns are converted to tropospheric NO2 vertical columns using a radiative transfer model and trace gas profiles from the Community Multiscale Air Quality (CMAQ) model. Total column NO2 from GeoTASO is well correlated with ground-based Pandora observations (r = 0.90 on the most polluted and cloud-free day of measurements and r = 0.74 overall), with GeoTASO NO2 slightly higher for the most polluted observations. Surface NO2 mixing ratios inferred from GeoTASO using the CMAQ model show good correlation with NO2 measured in situ at the surface during the campaign (r = 0.85). NO2 slant columns from GeoTASO also agree well with preliminary retrievals from the GEO-CAPE Airborne Simulator (GCAS) which flew on the NASA King Air B200 (r = 0.81, slope = 0.91). Enhanced NO2 is resolvable over areas of traffic NOx emissions and near individual petrochemical facilities.

A 34-yr record of shortwave top-of-atmosphere (TOA) radiative cloud forcing is derived from UV Lambertian equivalent reflectivity (LER) data constructed using measured upwelling radiances from the Nimbus-7 Solar Backscatter Ultraviolet (SBUV) and from seven NOAA SBUV/2 instruments on polar-orbiting satellites. The approach is to scale the dimensionless UV LER data to match the CERES shortwave cloud radiative forcing when they are concurrent (2000–13). The underlying trends of this new longer-term CERES-like data record are solely based on the UV LER record. The good agreement between trends and anomalies of the CERES-like and CERES shortwave cloud forcing records during the overlapping data period supports using this new dataset for extended climate studies. The estimated linear trend for the shortwave TOA radiative forcing due to clouds from 60°S to 60°N is +1.47 W m−2 with a 0.11 uncertainty at the 95% confidence level over the 34-yr period 1980–2013.

The National Oceanic and Atmospheric Administration (NOAA) Deep Space Climate Observatory (DSCOVR) spacecraft was launched on 11 February 2015 and in June 2015 achieved its orbit at the first Lagrange point (L1), 1.5 million km from Earth toward the sun. There are two National Aeronautics and Space Administration (NASA) Earth-observing instruments on board: the Earth Polychromatic Imaging Camera (EPIC) and the National Institute of Standards and Technology Advanced Radiometer (NISTAR). The purpose of this paper is to describe various capabilities of the DSCOVR EPIC instrument. EPIC views the entire sunlit Earth from sunrise to sunset at the backscattering direction (scattering angles between 168.5° and 175.5°) with 10 narrowband filters: 317, 325, 340, 388, 443, 552, 680, 688, 764, and 779 nm. We discuss a number of preprocessing steps necessary for EPIC calibration including the geolocation algorithm and the radiometric calibration for each wavelength channel in terms of EPIC counts per second for conversion to reflectance units. The principal EPIC products are total ozone (O3) amount, scene reflectivity, erythemal irradiance, ultraviolet (UV) aerosol properties, sulfur dioxide (SO2) for volcanic eruptions, surface spectral reflectance, vegetation properties, and cloud products including cloud height. Finally, we describe the observation of horizontally oriented ice crystals in clouds and the unexpected use of the O2 B-band absorption for vegetation properties.

Coastal environments are highly dynamic, and are characterized by short-term, local-scale variability in atmospheric and oceanic processes. Yet, high-frequency measurements of atmospheric composition, and particularly nitrogen dioxide (NO2) and ozone (O3) dynamics, are scarce over the ocean, introducing uncertainties in satellite retrievals of coastal ocean biogeochemistry and ecology. Combining measurements from different platforms, the Korea-US Ocean Color and Air Quality field campaign provided a unique opportunity to capture, for the first time, the strong spatial dynamics and diurnal variability in total column (TC) NO2 and O3 over the coastal waters of South Korea. Measurements were conducted using a shipboard Pandora Spectrometer Instrument specifically designed to collect accurate, high-frequency observations from a research vessel, and were combined with ground-based observations at coastal land sites, synoptic satellite imagery, and air-mass trajectory simulations to assess source contributions to atmospheric pollution over the coastal ocean. TCO3 showed only small (

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 %.

Even though it was not designed as an exoplanetary research mission, the Deep Space Climate Observatory (DSCOVR) has been opportunistically used for a novel experiment, in which Earth serves as a proxy exoplanet. More than two years of DSCOVR Earth images were employed to produce time series of multi-wavelength, single-point light sources, in order to extract information on planetary rotation, cloud patterns, surface type, and orbit around the Sun. In what follows, we assume that these properties of the Earth are unknown, and instead attempt to derive them from first principles. These conclusions are then compared with known data about our planet. We also used the DSCOVR data to simulate phase angle changes, as well as the minimum data collection rate needed to determine the rotation period of an exoplanet. This innovative method of using the time evolution of a multi-wavelength, reflected single-point light source, can be deployed for retrieving a range of intrinsic properties of an exoplanet around a distant star.

The KORUS-AQ field study conducted during May–June 2016 offered the first opportunity to evaluate direct-sun observations of formaldehyde (HCHO) total column densities with improved Pandora spectrometer instruments. The measurements highlighted in this work were conducted both in the Seoul megacity area at the Olympic Park site (latitude: 37.5232° N, longitude: 127.1260° E, 26 m a.s.l.) and at a nearby rural site downwind of the city at the Mount Taehwa Research Forest site (latitude: 37.3123° N, longitude: 127.3106° E, 160 m a.s.l.). Evaluation of these measurements was made possible by concurrent ground-based in situ observations of HCHO at both sites as well as overflight by the NASA DC-8 research aircraft. The flights provided in situ measurements of HCHO to characterize its vertical distribution in the lower troposphere (0–5 km). Diurnal variation in HCHO total column densities followed the same pattern at both sites, with the minimum daily values typically observed between 6:00–7:00 local time, gradually increasing to a maximum between 13:00 and 17:00 before decreasing into the evening. Pandora vertical column densities were compared with those derived from the DC-8 HCHO in-situ measured profiles augmented with in-situ surface concentrations below the lowest altitude of the DC-8 in proximity to the ground sites. A comparison between 49 column densities measured by Pandora versus aircraft integrated in-situ data showed that Pandora values were larger by 16 % (intercept = 0.22 DU, R2 = 0.68). Pandora HCHO columns were also compared with columns calculated from the surface in-situ measurements over Olympic Park by assuming a well-mixed lower atmosphere up to a ceilometer measured mixed-layer height (MLH) and various assumptions about the small residual HCHO amounts in the free troposphere up to the tropopause. The best comparison (slope = 1.03 ± 0.03, intercept = 0.29 ± 0.02 DU and R2 of 0.78 ± 0.02) was achieved assuming equal mixing within ceilometer measured MLH combined with an exponential profile shape. These results suggest that diurnal changes in HCHO surface concentrations can be reasonably estimated from the Pandora total column and information on the mixed-layer height. More work is needed to understand the bias in the intercept and the slope relative to columns derived from the in-situ aircraft and surface measurements.

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.

In the present study, we investigate the effects of signal to noise (SNR), slit function (FWHM), and aerosol optical depth (AOD) on the accuracy of formaldehyde (HCHO) vertical column density (HCHOVCD) using the ground-based direct-sun synthetic radiance based on differential optical absorption spectroscopy (DOAS). We found that the effect of SNR on HCHO retrieval accuracy is larger than those of FWHM and AOD. When SNR = 650 (1300), FWHM = 0.6, and AOD = 0.2, the absolute percentage difference (APD) between the true HCHOVCD values and those retrieved ranges from 54 (30%) to 5% (1%) for the HCHOVCD of 5.0 × 1015 and 1.1 × 1017 molecules cm−2, respectively. Interestingly, the maximum AOD effect on the HCHO accuracy was found for the HCHOVCD of 3.0 × 1016 molecules cm−2. In addition, we carried out the first ground-based direct-sun measurements in the ultraviolet (UV) wavelength range to retrieve the HCHOVCD using Pandora in Seoul. The HCHOVCD was low at 12:00 p.m. local time (LT) in all seasons, whereas it was high in the morning (10:00 a.m. LT) and late afternoon (4:00 p.m. LT), except in winter. The maximum HCHOVCD values were 2.68 × 1016, 3.19 × 1016, 2.00 × 1016, and 1.63 × 1016 molecules cm−2 at 10:00 a.m. LT in spring, 10:00 a.m. LT in summer, 1:00 p.m. LT in autumn, and 9:00 a.m. LT in winter, respectively. The minimum values of Pandora HCHOVCD were 1.63 × 1016, 2.23 × 1016, 1.26 × 1016, and 0.82 × 1016 molecules cm−2 at around 1:45 p.m. LT in spring, summer, autumn, and winter, respectively. This seasonal pattern of high values in summer and low values in winter implies that photo-oxidation plays an important role in HCHO production. The correlation coefficient (R) between the monthly HCHOVCD values from Pandora and those from the Ozone Monitoring Instrument (OMI) is 0.61, and the slope is 1.25.

A number of satellite‐based instruments have become an essential part of monitoring emissions. Despite sound theoretical inversion techniques, the insufficient samples and the footprint size of current observations have introduced an obstacle to narrow the inversion window for regional models. These key limitations can be partially resolved by a set of modest high‐quality measurements from airborne remote sensing. This study illustrates the feasibility of nitrogen dioxide (NO_2) columns from the Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) to constrain anthropogenic NO_x emissions in the Houston‐Galveston‐Brazoria area. We convert slant column densities to vertical columns using a radiative transfer model with (i) NO_2 profiles from a high‐resolution regional model (1 × 1 km^2) constrained by P‐3B aircraft measurements, (ii) the consideration of aerosol optical thickness impacts on radiance at NO_2 absorption line, and (iii) high‐resolution surface albedo constrained by ground‐based spectrometers. We characterize errors in the GCAS NO_2 columns by comparing them to Pandora measurements and find a striking correlation (r > 0.74) with an uncertainty of 3.5 × 10^(15) molecules cm^(−2). On 9 of 10 total days, the constrained anthropogenic emissions by a Kalman filter yield an overall 2–50% reduction in polluted areas, partly counterbalancing the well‐documented positive bias of the model. The inversion, however, boosts emissions by 94% in the same areas on a day when an unprecedented local emissions event potentially occurred, significantly mitigating the bias of the model. The capability of GCAS at detecting such an event ensures the significance of forthcoming geostationary satellites for timely estimates of top‐down emissions.

The collision-induced O2 complex, O2O2, is a very important trace gas for understanding remote sensing measurements of aerosols, cloud properties and atmospheric trace gases. Many ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements of the O2O2 optical depth require correction factors of 0.75 ± 0.1 to reproduce radiative transfer modeling (RTM) results for a nearly pure Rayleigh atmosphere. One of the potential causes of this discrepancy is uncertainty in laboratory-measured O2O2 absorption cross section temperature and pressure dependencies due to difficulties in replicating atmospheric conditions in the laboratory environment. This paper presents ground-based direct-sun (DS) and airborne multi-axis (AMAX) DOAS measurements of O2O2 absorption optical depths under actual atmospheric conditions in two wavelength regions (335–390 and 435–490 nm). DS irradiance measurements were made by the Washington State University research-grade Multi-Function Differential Spectroscopy Instrument instrument from 2007 to 2014 at seven sites with significant pressure (778 to 1013 hPa) and O2O2 profile-weighted temperature (247 to 275 K) differences. Aircraft MAX-DOAS measurements were conducted by the University of Colorado (CU) AMAX-DOAS instrument on 29 January 2012 over the Southern Hemispheric subtropical Pacific Ocean. Scattered solar radiance spectra were collected at altitudes between 9 and 13.2 km, with O2O2 profile-weighted temperatures of 231 to 244 K and nearly pure Rayleigh scattering conditions. Due to the well-defined DS air-mass factors during ground-based measurements and extensively characterized atmospheric conditions during the aircraft AMAX-DOAS measurements, O2O2 "pseudo" absorption cross sections, σ, are derived from the observed optical depths and estimated O2O2 column densities. Vertical O2O2 columns are calculated from the atmospheric sounding temperature, pressure and specific humidity profiles. Based on the ground-based atmospheric DS observations, there is no pressure dependence of the O2O2 σ within the measurement errors (3%). Two data sets are combined to derive the peak σ temperature dependence of the 360 and 477 nm dimer absorption bands from 231 to 275 K. DS and AMAX-derived peak σ ( O2O2) as a function of T can be described by a quadratic function at 360 nm and linear function at 477 nm with about 9% ± 2.5% per 44 K rate. Recent laboratory-measured O2O2 cross sections by Thalman and Volkamer (2013) agree with these "DOAS apparent" peak σ( O2O2) at 233, 253 and 273 K within 3%. Changes in the O2O2 spectral band shape at colder temperatures are observed for the first time in field data. Temperature effects on spectral band shapes can introduce errors in the retrieved O2O2 column abundances if a single room temperature σ( O2O2) is used in the DOAS analysis. Simultaneous fitting of σ( O2O2) at temperatures that bracket the ambient temperature range can reduce such errors. Our results show that laboratory-measured σ( O2O2) (Hermans, 2011, at 296 K and Thalman and Volkamer, 2013) are applicable for observations over a wide range of atmospheric conditions. Column densities derived using Hermans (2011) σ at 296 K require very small correction factors (0.94 ± 0.02 at 231 K and 0.99 ± 0.02 at 275 K) to reproduce theoretically calculated slant column densities for DS and AMAX-DOAS measurements. Simultaneous fitting of σ( O2O2) at 203 and 293 K further improved the results at UV and visible wavelengths for AMAX-DOAS.

This paper presents a temperature sensitivity method (TESEM) to accurately calculate total vertical NO2 column, atmospheric slant NO2 profile-weighted temperature (T), and to separate stratospheric and tropospheric columns from direct-sun (DS), ground-based measurements using the retrieved T. TESEM is based on differential optical absorption spectroscopy (DOAS) fitting of the linear temperature-dependent NO2 absorption cross section, σ (T), regression model (Vandaele et al., 2003). Separation between stratospheric and tropospheric columns is based on the primarily bimodal vertical distribution of NO2 and an assumption that stratospheric effective temperature can be represented by temperature at 27 km ± 3 K, and tropospheric effective temperature is equal to surface temperature within 3–5 K. These assumptions were derived from the Global Modeling Initiative (GMI) chemistry-transport model (CTM) simulations over two northern midlatitude sites in 2011. TESEM was applied to the Washington State University Multi-Function DOAS instrument (MFDOAS) measurements at four midlatitude locations with low and moderate NO2 anthropogenic emissions: (1) the Jet Propulsion Laboratory's Table Mountain Facility (JPL-TMF), CA, USA (34.38° N/117.68° W); (2) Pullman, WA, USA (46.73° N/117.17° W); (3) Greenbelt, MD, USA (38.99° N/76.84° W); and (4) Cabauw, the Netherlands (51.97° N/4.93° E) during July 2007, June–July 2009, July–August and October 2011, November 2012–May 2013, respectively. NO2 T and total, stratospheric, and tropospheric NO2 vertical columns were determined over each site.

Quantifying the aerosol absorption at ultraviolet (UV) wavelengths is important for monitoring air pollution using current (e.g., Aura/OMI) and future (e.g., TROPOMI, TEMPO, GEMS, and Sentinel-4) satellite measurements. Measurements of column atmospheric aerosol absorption (i.e., column effective imaginary refractive index (k), single scattering albedo (SSA), and aerosol absorption optical depth (AAOD)) are performed on the ground by the NASA AERONET in the visible (VIS) and near-infrared (NIR) wavelengths and in the UV-VIS-NIR by the SKYNET networks. Previous comparison studies have focused on visible and NIR wavelengths due to the lack of co-incident measurements of aerosol and gaseous absorption properties in the UV. This study compares the SKYNET-retrieved SSA in the UV with the SSA derived from a combination of AERONET, MFRSR, and Pandora (AMP) retrievals in Seoul, South Korea in spring and summer of 2016. The results show that the spectrally invariant surface albedo assumed in the SKYNET SSA retrievals leads to underestimated SSA compared to AMP values at near UV wavelengths. Re-processed SKYNET inversions using spectrally varying surface albedo, consistent with the AERONET retrieval improves agreement with AMP SSA. The combined AMP inversions allow for separating aerosol and gaseous (NO2 and O3) absorption and provides aerosol retrievals from the shortest UVB (305 nm) through visible to NIR wavelengths (870 nm).

The EPIC instrument onboard the DSCOVR spacecraft, located near the Earth-Sun gravitational plus centrifugal force balance point, Lagrange-1, measures Earth reflected radiances in 10 wavelength channels ranging from 317.5 nm to 779.5 nm. Of these channels, four are in the UV range 317.5, 325, 340, and 388 nm, which are used to retrieve O3, 388 nm scene reflectivity (LER Lambert Equivalent Reflectivity), SO2, and aerosol properties. These quantities are derived synoptically for the entire sunlit globe from sunrise to sunset every 68 minutes or 110 minutes for summer or winter at the receiving antenna in Wallops Island, Virginia, respectively. Depending on solar zenith angle, either 317.5 or 325 nm channels are combined with 340 and 388 nm to derive ozone amounts. As part of the ozone algorithm, the 388 nm channel is used to derive LER. The retrieved ozone amounts and LER are combined to derive the erythemal irradiance for the sunlit Earth's surface at a resolution of 18 × 18 km2 near the center of the Earth's disk using a computationally efficient approximation to a radiative transfer calculation of irradiance. Corrections are made for altitude above sea level and for the reduced transmission by clouds based on retrieved LER.

We assess the standard operational nitrogen dioxide (NO2) data product (OMNO2, version 2.1) retrieved from the Ozone Monitoring Instrument (OMI) onboard NASA's Aura satellite using a combination of aircraft and surface in~situ measurements as well as ground-based column measurements at several locations and a bottom-up NOx emission inventory over the continental US. Despite considerable sampling differences, NO2 vertical column densities from OMI are modestly correlated (r = 0.3–0.8) with in situ measurements of tropospheric NO2 from aircraft, ground-based observations of NO2 columns from MAX-DOAS and Pandora instruments, in situ surface NO2 measurements from photolytic converter instruments, and a bottom-up NOx emission inventory. Overall, OMI retrievals tend to be lower in urban regions and higher in remote areas, but generally agree with other measurements to within ± 20%. No consistent seasonal bias is evident. Contrasting results between different data sets reveal complexities behind NO2 validation. Since validation data sets are scarce and are limited in space and time, validation of the global product is still limited in scope by spatial and temporal coverage and retrieval conditions. Monthly mean vertical NO2 profile shapes from the Global Modeling Initiative (GMI) chemistry-transport model (CTM) used in the OMI retrievals are highly consistent with in situ aircraft measurements, but these measured profiles exhibit considerable day-to-day variation, affecting the retrieved daily NO2 columns by up to 40%. This assessment of OMI tropospheric NO2 columns, together with the comparison of OMI-retrieved and model-simulated NO2 columns, could offer diagnostic evaluation of the model.