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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]

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 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]

Korea will launch the Geostationary Environment Monitoring Spectrometer (GEMS) instrument in 2018 onboard the Geostationary Korean Multi-Purpose Satellite to monitor tropospheric gas concentrations with high temporal and spatial resolutions. The purpose of this study is to examine the performance of total column ozone (TCO) measurements from ground-based Pandora and Brewer instruments that will be used for validation of the GEMS ozone product. Satellite measurements can be used to detect erroneous outliers at a particular ground station, which deviate significantly from co-located satellite measurements relative to other stations. This is possible because a single satellite retrieval algorithm is used to process the entire satellite dataset, and instrument characteristics typically change slowly over the life of the satellite. Thus, the short-term stability (months) of satellite measurements can be used to estimate the performance of the ground-based measurement network as well as to identify potential problems at individual stations. As a reference for satellite ozone measurements, we have selected TCO data derived from OMI-TOMS V8.5 algorithm, because it is a robust algorithm that has been well studied to identify its various error sources. We validated ground-based Brewer and Pandora TCO measurements using OMI-TOMS TCO data collected over South Korea from March 2012 to December 2014. The Brewer TCO measurements at Pohang showed significant deviation from overall seasonal variation during the study period. In addition, in the presence of clouds, Pandora TCO measurements are unusually ∼7% higher than OMI-TOMS TCO data. To filter out these cloud-contaminated data, we applied a Kalman filter to the Pandora measurements. The diurnal variation in the Kalman-filtered Pandora data agrees well with the Brewer data, and the correlation of Kalman-filtered Pandora data with OMI-TOMS TCO is significantly improved from 0.89 to 0.99 at Seoul and from 0.93 to 0.99 at Busan. [ABSTRACT FROM AUTHOR]