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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 NO2and 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 Onnuriin 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 NO2and surface AQ in this coastal region. Three case studies illustrate the value of the PSI and complexities in the surface‐column NO2relationship caused by varying meteorological conditions. Case Study 1 (25–26 May 2016) exhibited a high correlation of surface NO2to TC NO2measured by both PSI and Aura's Ozone Monitoring Instrument, but two other cases displayed poor relationships between in situ and TC NO2due to decoupling of pollution layers from the surface. With suitable interpretation the PSI TC NO2measurement demonstrates good potential for working with upcoming geostationary satellites to advance diurnal tracking of pollution. Pandora NO2total column and coincident surface O3, NO2, and CO were measured off coastal Korea in May–June 2016Relationship between Pandora column and surface NO2depends on meteorology with only one of three cases well correlatedAir pollution along Korean coast originates from both South Korean and regional sources

Aerosol optical thickness (τaer) is a fundamental parameter for analyzing aerosol loading and associated radiative effects. The τaercan 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 τaercan 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 τaerretrieval 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 τaerand 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 τaerdemonstrated 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 τaerretrievals at short wavelengths in the UV. The continuous spectrum of τaerfrom 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. Spectral aerosol optical thickness retrieval algorithm was developed based on the Langley calibration methodDeveloped empirical stray light correction method considerably improved aerosol optical thickness retrievals at ultraviolet wavelengthsRetrieved spectral aerosol optical thickness provides the key constraints for additional aerosol properties and trace gas retrievals

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 NOxemissions in the Houston‐Galveston‐Brazoria area. We convert slant column densities to vertical columns using a radiative transfer model with (i) NO2profiles 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 NO2absorption line, and (iii) high‐resolution surface albedo constrained by ground‐based spectrometers. We characterize errors in the GCAS NO2columns by comparing them to Pandora measurements and find a striking correlation (r> 0.74) with an uncertainty of 3.5 × 1015molecules 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. We constrain anthropogenic NOxemissions by Kalman filter using the NO2observations from GCAS sensorConstrained emissions counterbalance the well‐documented positive bias of 1 × 1 km2regional model against surface observationsGCAS provides a unique opportunity to detect and constrain an emission event anomaly in the Houston area

The absorption by atmospheric nitrogen dioxide (NO_2) gas in the visible has been traditionally neglected in the retrieval of oceanic parameters from satellite measurements. Recent measurements of NO_2 from spaceborne sensors show that over the Eastern United States the NO_2 column amount often exceeds 1 Dobson Unit (∼2.69×10^16 molecules/cm^2). Our radiative transfer sensitivity calculations show that under high NO_2 conditions (∼1×10^16 molecules/cm^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 NO_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%.

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 Kd is in good agreement with the measured Kd.

Comparison of measured UV irradiance with estimates from satellite observation is potentially effective for the validation of data from the two sources. Summer data from ten Canadian Brewer sites were compared in this study with noon UV irradiance estimated from total ozone mapping spectrometer (TOMS) measurements. In general, TOMS estimates can successfully reproduce long-term and major short-term UV variations. However, there are some systematic differences between the measurements at the ground and satellite-retrieved UV irradiance. From 3 to 11 of the Brewer-TOMS difference can be attributed to the Brewer angular response error. This error depends on the solar zenith angle and cloud conditions, and is different from instrument to instrument. When the angular response of the Brewer instrument is considered and applied, the Brewer data are still lower than TOMS-estimated UV irradiance by 9 to 10 on average at all sites except one. The difference is close to zero at one station (Saturna Island), possibly due to its much cleaner air. The bias can be seen in clear sky conditions and at the 324-nm wavelength, i.e., it is not related to local cloud conditions or absorption by ozone or SO2.© 2002 Society of Photo-Optical Instrumentation Engineers.

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 ω0from 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). 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