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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 this study, the WRF-Chem v4.4 model was utilized to evaluate the sensitivity of O 3 simulations with three bottom-up emission inventories (EDGAR-HTAP v2 and v3 and KORUS v5) using surface and aircraft data in East Asia during the Korea-United States Air Quality (KORUS-AQ) campaign period in 2016. All emission inventories were found to reproduce the diurnal variations of O 3 and its main precursor NO 2 as compared to the surface monitor data. However, the spatial distributions of the daily maximum 8 h average (MDA8) O 3 in the model do not completely align with the observations. The model MDA8 O 3 had a negative (positive) bias north (south) of 30° N over China. All simulations underestimated the observed CO by 50 %–60 % over China and South Korea. In the Seoul Metropolitan Area (SMA), EDGAR-HTAP v2 and v3 and KORUS v5 simulated the vertical shapes and diurnal patterns of O 3 and other precursors effectively, but the model underestimated the observed O 3 , CO, and HCHO concentrations. Notably, the model aromatic volatile organic compounds (VOCs) were significantly underestimated with the three bottom-up emission inventories, although the KORUS v5 shows improvements. The model isoprene estimations had a positive bias relative to the observations, suggesting that the Model of Emissions of Gases and Aerosols from Nature (MEGAN) version 2.04 overestimated isoprene emissions. Additional model simulations were conducted by doubling CO and VOC emissions over China and South Korea to investigate the causes of the model O 3 biases and the effects of the long-range transport on the O 3 over South Korea. The doubled CO and VOC emission simulations improved the model O 3 simulations for the local-emission-dominant case but led to the model O 3 overestimations for the transport-dominant case, which emphasizes the need for accurate representations of the local VOC emissions over South Korea. [ABSTRACT FROM AUTHOR]

In this study, the WRF-Chem v4.4 model was utilized to evaluate three bottom-up emission inventories (EDGAR-HTAP v2, v3, and KORUS v5) using surface and aircraft data in East Asia during the Korea-United States Air Quality (KORUS-AQ) campaign period in 2016. All emission inventories were found to reproduce the diurnal variations of O3 and NO2 as compared to the surface monitor data. However, the spatial distributions of the daily maximum 8-hour average (MDA8) O3 in the model do not completely align with the observations. The model MDA8 O3 had a negative (positive) bias north (south) of 30°N over China. All simulations underestimated the observed CO by 50-60% over China and South Korea. In the Seoul Metropolitan Area (SMA), EDGAR-HTAP v2, v3, and KORUS v5 simulated the vertical shapes and diurnal patterns of O3 and other precursors effectively, but the model underestimated the observed O3, CO and HCHO concentrations. Notably, the model aromatic VOCs were significantly underestimated with the three bottom-up emission inventories, although the KORUS v5 shows improvements. The model isoprene estimations had a positive bias relative to the observations, suggesting that the Model of Emissions of Gases and Aerosols from Nature (MEGAN) version 2.04 overestimated isoprene emissions. Additional model simulations were conducted by doubling CO and VOC emissions over China and South Korea to investigate the causes of the model O3 biases and the effects of the long-range transport on the O3 over South Korea. The doubled CO and VOC emission simulations improved the model O3 simulations for the local emission dominant case, but led to the model O3 overestimations for the transport dominant case, which emphasizes the need for accurate representations of the local VOC emissions over South Korea. [ABSTRACT FROM AUTHOR]

The absorption by atmospheric nitrogen dioxide (N[O.sub.2]) gas in the visible has been traditionally neglected in the retrieval of oceanic parameters from satellite measurements. Recent measurements of N[O.sub.2] from spaceborne sensors show that over the Eastern United States the N[O.sub.2] column amount often exceeds 1 Dobson Unit (~2.69 x [10.sup.16] molecules/[cm.sup.2]). Our radiative transfer sensitivity calculations show that under high N[O.sub.2] conditions (~1 x [10.sup.16] molecules/[cm.sup.2]) the error in top-of-atmosphere (TOA) reflectance in the blue channels of the sea-viewing wide field-of-view sensor (SeaWiFS) and moderate-resolution imaging spectroradiometer (MODIS) sensors is approximately 1%. This translates into approximately 10% error in water-leaving radiance for clear waters and to higher values (>20%) in the coastal areas. We have developed an atmospheric-correction algorithm that allows an accurate retrieval of normalized water-leaving radiances (nLws) in the presence of N[O.sub.2] in the atmosphere. The application of the algorithm to 52 MODIS scenes over the Chesapeake Bay area show a decrease in the frequency of negative nLw estimates in the 412 nm band and an increase in the value of nLws in the same band. For the particular scene reported in this paper, the mean value of nLws in the 412 nm band increased by 17%, which is significant, because for the MODIS sensor the error in nLws attributable to the digitization error in the observed TOA reflectance over case 2 waters is ~2.5%. OCIS codes: 010.1310, 010.4450, 290.1310, 290.4210, 290.5890.

During the ACE-Asia field campaign, unprecedented amounts of aerosol property data in East Asia during springtime were collected from an array of aircraft, shipboard, and surface instruments. However, most of the observations were obtained in areas downwind of the source regions. In this paper, the newly developed satellite aerosol algorithm called 'Deep Blue' was employed to characterize the properties of aerosols over source regions using radiance measurements from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS). Based upon the Angstrom exponent derived from the Deep Blue algorithm, it was demonstrated that this new algorithm is able to distinguish dust plumes from fine-mode pollution particles even in complex aerosol environments such as the one over Beijing. Furthermore, these results were validated by comparing them with observations from AERONET sites in China and Mongolia during spring 2001. These comparisons show that the values of satellite-retrieved aerosol optical thickness from Deep Blue are generally within 20%-30% of those measured by sunphotometers. The analyses also indicate that the roles of mineral dust and anthropogenic particles are comparable in contributing to the overall aerosol distributions during spring in northern China, while fine-mode particles are dominant over southern China. The spring season in East Asia consists of one of the most complex environments in terms of frequent cloudiness and wide ranges of aerosol loadings and types. This paper will discuss how the factors contributing to this complexity influence the resulting aerosol monthly averages from various satellite sensors and, thus, the synergy among satellite aerosol products. Index Terms--Aerosols, desert, Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging Spectro-Radiometer (MISR), remote sensing, satellite applications, Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Terra.

The Ozone Monitoring Instrument (OMI) onboard the NASA Earth Observing System (EOS) Aura spacecraft is a nadir-viewing spectrometer that measures solar reflected and backscattered light in a selected range of the ultraviolet and visible spectrum. The instrument has a 2600-km-wide viewing swath, and it is capable of daily, global contiguous mapping. We developed and implemented a surface ultraviolet (UV) irradiance algorithm for OMI that produces noontime surface spectral UV irradiance estimates at four wavelengths (305, 310, 324, and 380 nm). Additionally, noontime erythemal dose rate and the erythemal dally dose are estimated. The OMI surface UV algorithm inherits from the surface UV algorithm developed by NASA Goddard Space Flight Center for the Total Ozone Mapping Spectrometer (TOMS). The OMI surface UV irradiance products are produced and archived in HDF5-EOS format by Finnish Meteorological Institute. The accuracy of the surface UV estimates depend on UV wavelength and atmospheric and other geolocation specific conditions ranging from 7%to 30%. A postprocessing aerosol correction can be applied at sites with additional ground-based measurements of the aerosol absorption optical thickness. The current OMI surface UV product validation plan is presented. Index Terms--Algorithms, software verification and validation, solar radiation, ultraviolet radiation effects.

Quantitative assessment of the UV effects on aquatic ecosystems requires an estimate of the in-water radiation field. Actual ocean UV reflectances are needed for improving the total ozone retrievals from the total ozone mapping spectrometer (TOMS) and the ozone monitoring instrument (OMI) flown on NASA's Aura satellite. The estimate of underwater UV radiation can be done on the basis of measurements from the TOMS/OMI and full models of radiative transfer (RT) in the atmosphere-ocean system. The Hydrolight code, modified for extension to the UV, is used for the generation of look-up tables for in-water irradiances. A look-up table for surface radiances generated with a full RT code is input for the Hydrolight simulations. A model of seawater inherent optical properties (IOPs) is an extension of the Case 1 water model to the UV. A new element of the IOP model is parameterization of particulate matter absorption based on recent in situ data. A chlorophyll product from ocean color sensors is input for the IOP model. Verification of the in-water computational scheme shows that the calculated diffuse attenuation coefficient [K.sub.d] is in good agreement with the measured [K.sub.d]. OCIS codes: 010.1290, 010.4450, 280.0280.

Retrieving aerosol properties from satellite remote sensing over a bright surface is a challenging problem in the research of atmospheric and land applications. In this paper we propose a new approach to retrieve aerosol properties over surfaces such as arid, semiarid, and urban areas, where the surface reflectance is usually very bright in the red part of visible spectrum and in the near infrared, but is much darker in the blue spectral region (i.e., wavelength Index Terms--Aerosols, algorithm, desert, remote sensing, satellite applications, terrestrial atmosphere.

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. [ABSTRACT FROM AUTHOR]

The SMART‐s (Spectral Measurements for Atmospheric Radiative Transfer—spectroradiometer) acquires Sun/sky observations for retrieving optimal information on trace gases and aerosols with minimal assumptions. Overall, the algorithm of SMART‐s incorporates a series of retrievals, from fundamental quantities (i.e., column abundance of trace gases and aerosol loading) to higher‐order geophysical parameters (e.g., aerosol physicochemical properties and vertical profiles), utilizing Sun/sky spectral radiance measurements. This paper describes the theoretical basis for column retrievals of trace gases and aerosols. Associated profile retrievals will be presented in follow‐up papers. The current algorithm retrieves the fine/coarse mode of the particle size distribution and spectral complex index of refraction and, thereby, the spectral aerosol single‐scattering albedo ω0. SMART‐s retrieval is unique particularly in its high spectral resolution of the complex index of refraction and ω0 from near‐ultraviolet to near‐infrared wavelengths, which is pivotal information for atmospheric chemistry, climate and other inversions. We theoretically assessed information content and retrieval accuracy of the algorithm and compared different type of measurements including the Aerosol Robotic Network (AERONET) and standard Pandora. For the same levels of radiometric accuracy, SMART‐s measurements provide the most informative aerosol retrievals based on theoretical error analyses. Higher spectral resolution measurements are particularly beneficial for particle size distribution and fine‐mode refractive index retrievals. We applied this algorithm to the AERONET Sun/sky measurements at Kanpur, India, in 2016 to assess algorithm consistency. Even with different assumptions and numerical methods for the inversion, SMART‐s retrieved aerosol parameters agreed well with the AERONET operational products (e.g., absolute mean bias errors less than 0.01 for ω0). Key Points: The SMART‐s algorithm retrieves aerosol particle size distributions and spectral complex index of refraction from about 310 to 800 nmWe applied the SMART‐s algorithm to the AERONET Sun/sky measurements and the retrievals were consistent with the operational products of AERONETHigh spectral resolution of the SMART‐s retrievals can provide unique information for atmospheric chemistry, air quality, and climate studies [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 TC 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 and 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, 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. Key Points: Pandora NO2 total column and coincident surface O3, NO2, and CO were measured off coastal Korea in May–June 2016Relationship between Pandora column and surface NO2 depends on meteorology with only one of three cases well correlatedAir pollution along Korean coast originates from both South Korean and regional sources [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 %. [ABSTRACT FROM AUTHOR]

The Korea-United States Air Quality Study (KORUS-AQ) 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 (37.5232°N, 27.1260°E; 26ma.s.l.) and at a nearby rural site downwind of the city at the Mount Taehwa research forest site (37.3123°N, 127.3106°E; 160ma.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 and 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 vs. aircraft-integrated in situ data showed that Pandora values were larger by 16% with a constant offset of 0.22DU (Dobson units; R²=0:68). Pandora HCHO columns were also compared with columns calculated from the surface in situ measurements over Olympic Park by assuming a wellmixed lower atmosphere up to a ceilometer-measured mixedlayer 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=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 concentra-tions 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. [ABSTRACT FROM AUTHOR]

Abstract: Aerosol optical thickness (τaer) is a fundamental parameter for analyzing aerosol loading and associated radiative effects. The τaer 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 τaer 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 τaer 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 τaer and Ångström Exponent can be used effectively for cloud screening. The new algorithm was applied to month‐long measurements acquired from the rooftop at National Aeronautics and Space Administration Goddard Space Flight Center's Building 33. The retrieved τaer demonstrated excellent agreement with those from well‐calibrated Aerosol Robotic Network Sun photometers at all overlapping wavelengths (correlation coefficients higher than 0.98). In addition, empirical stray light corrections considerably improved τaer retrievals at short wavelengths in the UV. The continuous spectrum of τaer 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. [ABSTRACT FROM AUTHOR]

Abstract: 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 (NO2) columns from the Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) to constrain anthropogenic NOx emissions in the Houston‐Galveston‐Brazoria area. We convert slant column densities to vertical columns using a radiative transfer model with (i) NO2 profiles from a high‐resolution regional model (1 × 1 km2) constrained by P‐3B aircraft measurements, (ii) the consideration of aerosol optical thickness impacts on radiance at NO2 absorption line, and (iii) high‐resolution surface albedo constrained by ground‐based spectrometers. We characterize errors in the GCAS NO2 columns by comparing them to Pandora measurements and find a striking correlation (r > 0.74) with an uncertainty of 3.5 × 1015 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 250m?250m 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. [ABSTRACT FROM AUTHOR]

There is a pressing need to verify air pollutant and greenhouse gas emissions from anthropogenic fossil energy sources to enforce current and future regulations. We demonstrate the feasibility of using simultaneous remote sensing observations of column abundances of CO2, CO, and NO2 to inform and verify emission inventories. We report, to our knowledge, the first ever simultaneous column enhancements in CO2 (3–10 ppm) and NO2 (1–3 Dobson Units), and evidence of δ13CO2 depletion in an urban region with two large coal-fired power plants with distinct scrubbing technologies that have resulted in ΔNOx/ΔCO2 emission ratios that differ by a factor of two. Ground-based total atmospheric column trace gas abundances change synchronously and correlate well with simultaneous in situ point measurements during plume interceptions. Emission ratios of ΔNOx/ΔCO2 and ΔSO2/ΔCO2 derived from in situ atmospheric observations agree with those reported by instack monitors. Forward simulations using in-stack emissions agree with remote column CO2 and NO2 plume observations after fine scale adjustments. Both observed and simulated column ΔNO2/ΔCO2 ratios indicate that a large fraction (70–75%) of the region is polluted. We demonstrate that the column emission ratios of ΔNO2/ΔCO2 can resolve changes from day-to-day variation in sources with distinct emission factors (clean and dirty power plants, urban, and fires). We apportion these sources by using NO2, SO2, and CO as signatures. Our high-frequency remote sensing observations of CO2 and coemitted pollutants offer promise for the verification of power plant emission factors and abatement technologies from ground and space. [ABSTRACT FROM AUTHOR]

During the ACE-Asia field campaign, unprecedented amounts of aerosol property data in East Asia during springtime were collected from an array of aircraft, shipboard, and surface instruments. However, most of the observations were obtained in areas downwind of the source regions. In this paper, the newly developed satellite aerosol algorithm called "Deep Blue" was employed to characterize the properties of aerosols over source regions using radiance measurements from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS). Based upon the Angstrom exponent derived from the Deep Blue algorithm, it was demonstrated that this new algorithm is able to distinguish dust plumes from fine-mode pollution particles even in complex aerosol environments such as the one over Beijing. Furthermore, these results were validated by comparing them with observations from AERONET sites in China and Mongolia during spring 2001. These comparisons show that the values of satellite-retrieved aerosol optical thickness from Deep Blue are generally within 20%-30% of those measured by sunphotometers. The analyses also indicate that the roles of mineral dust and anthropogenic particles are comparable in contributing to the overall aerosol distributions during spring in northern China, while fine-mode particles are dominant over southern China. The spring season in East Asia consists of one of the most complex environments in terms of frequent cloudiness and wide ranges of aerosol loadings and types. This paper will discuss how the factors contributing to this complexity influence the resulting aerosol monthly averages from various satellite sensors and, thus, the synergy among satellite aerosol products. [ABSTRACT FROM AUTHOR]