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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]

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]

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]