Search

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 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.

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]

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 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]

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]

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 (NO 2 ), with the goal of improving the interpretation of spaceborne remote sensing data. Various types of NO 2 measurements were made, including in situ concentrations and column amounts of NO 2 using ground- and aircraft-based instruments, while NO 2 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 NO 2 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 NO 2 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 NO 2 fields that could be missed by aircraft spirals and errors in the Pandora retrievals. OMI NO 2 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 km 2 )., Competing Interests: Competing interests. The authors declare that they have no conflict of interest.

Vertical column density (VCD) of nitrogen dioxide (NO2) was measured using Pandora spectrometers at six sites on the Korean Peninsula during the Megacity Air Pollution Studies-Seoul (MAPS-Seoul) campaign from May to June 2015. To estimate the tropospheric NO 2 VCD, the stratospheric NO 2 VCD from the Ozone Monitoring Instrument (OMI) was subtracted from the total NO 2 VCD from Pandora. European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis wind data was used to analyze variations in tropospheric NO 2 VCD caused by wind patterns at each site. The Yonsei/SEO site was found to have the largest tropospheric NO 2 VCD (1.49 DU on average) from a statistical analysis of hourly tropospheric NO 2 VCD measurements. At rural sites, remarkably low NO 2 VCDs were observed. However, a wind field analysis showed that trans-boundary transport and emissions from domestic sources lead to an increase in tropospheric NO 2 VCD at NIER/BYI and KMA/AMY, respectively. At urban sites, high NO 2 VCD values were observed under conditions of low wind speed, which were influenced by local urban emissions. Tropospheric NO 2 VCD at HUFS/Yongin increases under conditions of significant transport from urban area of Seoul according to a correlation analysis that considers the transport time lag. Significant diurnal variations were found at urban sites during the MAPS-Seoul campaign, but not at rural sites, indicating that it is associated with diurnal patterns of NO 2 emissions from dense traffic.

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; 26 ma.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 (0-5km). 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; R 2 = 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±0.02DU; and R 2 = 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.

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 δ(13)CO2 depletion in an urban region with two large coal-fired power plants with distinct scrubbing technologies that have resulted in ∆NOx/∆CO2 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 ∆NOx/∆CO2 and ∆SO2/∆CO2 derived from in situ atmospheric observations agree with those reported by in-stack 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 ∆NO2/∆CO2 ratios indicate that a large fraction (70-75%) of the region is polluted. We demonstrate that the column emission ratios of ∆NO2/∆CO2 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.