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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]

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]

Abstract: We combined detailed bio-optical measurements and radiative transfer modeling to perform an ‘optical closure’ experiment for an optically complex and biologically productive region of the Chesapeake Bay. We used this experiment to evaluate certain assumptions commonly used in bio-optical models, and to investigate which optical characteristics are most important to accurately model and interpret remote sensing ocean-color observations in these Case 2 waters. Direct measurements were made of the magnitude, variability, and spectral characteristics of backscattering and absorption that are critical for accurate parameterizations in satellite bio-optical algorithms and underwater radiative transfer simulations. We found that the ratio of backscattering to total scattering (i.e. the backscattering fraction, b b/b) varied considerably depending on particulate loading, distance from land, and mixing processes, and had an average value of 0.0128 at 530nm. Incorporating information on the magnitude, variability, and spectral characteristics of particulate backscattering into the radiative transfer model, rather than using a volume scattering function commonly assumed for turbid waters, was critical to obtaining agreement between model calculations and measured radiometric quantities. In-situ measurements of absorption coefficients need to be corrected for systematic overestimation due to scattering errors, and this correction commonly employs the assumption that absorption by particulate matter at near-infrared wavelengths is zero. Direct measurements, however, showed that particulate matter in the Bay had small, but non-zero, absorption in the 700–730nm wavelength region. Accounting for this residual particulate absorption when correcting in-situ measured absorption spectra for scattering errors was important in model simulations of water reflectance in the green wavelengths, where reflectance spectra in estuarine waters peak. Sun-induced chlorophyll fluorescence considerably affected the magnitude of water reflectance in the red wavelengths. Very good optical closure was obtained between independently measured water inherent optical properties and radiation fields, after applying the results from our detailed measurements to model bio-optical processes in these Case 2 waters. The good optical closure was consistent over the observed wide range of water optical characteristics. Average absolute percent differences between measured and model-estimated water-leaving radiances were 6.35% at 443nm, 7.73% at 554nm, and 6.86% at 670nm, considerably smaller than those presented in the few studies of optical closure performed previously in near shore waters of similar optical complexity. These results show that bio-optical processes can be confidently modeled in complex estuarine waters, and underscore the importance of accurate formulations for backscattering, long-wavelength particulate absorption, and chlorophyll fluorescence. [Copyright &y& Elsevier]

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 daily 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. [ABSTRACT FROM AUTHOR]

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 and, 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 <500 nm). In order to infer atmospheric properties from these data, a global surface reflectance database of 0.1° latitude by 0.1° longitude resolution was constructed over bright surfaces for visible wavelengths using the minimum reflectivity technique (e.g., finding the clearest scene during each season for a given location). The aerosol optical thickness and aerosol type are then determined simultaneously in the algorithm using lookup tables to match the satellite observed spectral radiances. Examples of aerosol optical thickness derived using this algorithm over the Sahara Desert and Arabian Peninsula reveal various dust sources, which are important contributors to airborne dust transported over long distances. Comparisons of the satellite inferred aerosol optical thickness and the values from ground-based Aerosol Robotic Network (AERONET) sun/sky radiometer measurements indicate good agreement (i.e., within 30%) over the sites in Nigeria and Saudi Arabia. This new algorithm, when applied to Moderate Resolution Imaging Spectroradiometer (MODIS), Sea-viewing Wide Field of view Sensor (SeaWiFS), and Global Imager (GLI) satellite data, will provide high spatial resolution (∼1 km) global information of aerosol optical thickness over bright surfaces on a daily basis. [ABSTRACT FROM AUTHOR]

Abstract: We used an extensive set of bio-optical data to examine the relationships between inherent optical properties and remotely sensed quantities in an optically complex and biologically productive region of the Chesapeake Bay. Field observations showed that the chlorophyll algorithms used by the MODIS (MODerate resolution Imaging Spectroradiometer) ocean color sensor (i.e. Chlor_a, chlor_MODIS, chlor_a_3 products) do not perform accurately in these Case 2 waters. This is because, at high concentrations of chlorophyll, all MODIS algorithms are based on empirical relationships between chlorophyll concentration and blue:green wavelength remote sensing reflectance (R rs) ratios that do not account for the typically strong blue-wavelength absorption by non-covarying, dissolved and non-algal particulate components. We found stronger correlation between chlorophyll concentration and red:green R rs ratios (i.e. R rs(677)/R rs(554)). Regionally-specific algorithms that are based on the phytoplankton optical properties in the red wavelength region provide a better basis for satellite monitoring of phytoplankton blooms in these Case 2 waters. Our estimates of f/Q (proportionality factor in the relationship between R rs and the ratio of water backscattering, b b, and absorption, a, coefficients, b b/(a + b b)) were not considerably different from f/Q previously estimated for same measurement geometry but Case 1 waters. Variation in surface b b significantly affected R rs magnitude across the visible spectrum and was most strongly correlated (R 2 =0.88) with observed variability in R rs at 670nm. Surface values of particulate backscattering were strongly correlated with non-algal particulate absorption, a nap (R 2 =0.83). These results, along with the measured backscattering fraction and non-algal particulate absorption spectral slope, indicate that suspended non-algal particles with high inorganic content are the major water constituents regulating b b variability in the studied region of the Chesapeake Bay. Remote retrieval of surface a nap from R rs(670) could be used in conjunction with inversion of UV-blue wavelengths to separate contribution by non-algal particles and colored dissolved organic matter to total light absorption, and monitor non-algal suspended particle concentration and distribution in these Case 2 waters. [Copyright &y& Elsevier]