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).

Satellite retrievals of column mass loading of volcanic ash are incorporated into the HYSPLIT transport and dispersion modeling system for source determination, bias correction, and forecast verification of probabilistic ash forecasts of a short eruption of Bezymianny in Kamchatka. The probabilistic forecasts are generated with a dispersion model ensemble created by driving HYSPLIT with 31 members of the NOAA global ensemble forecast system (GEFS). An inversion algorithm is used for source determination. A bias correction procedure called cumulative distribution function (CDF) matching is used to very effectively reduce bias. Evaluation is performed with rank histograms, reliability diagrams, fractions skill score, and precision recall curves. Particular attention is paid to forecasting the end of life of the ash cloud. We find indications that the simulated dispersion of the ash cloud does not represent the observed dispersion well, resulting in difficulty simulating the observed evolution of the ash cloud area. This can be ameliorated with the bias correction procedure. Individual model runs struggle to capture the exact placement and shape of the small pieces of ash left near the end of the clouds lifetime. The ensemble tends to be overconfident, but does capture the range of possibilities of ash cloud placement. Probabilistic forecasts such as ensemble relative frequency of exceedance and agreement in percentile levels are suited for strategies in which areas with certain concentrations or mass loadings of ash need to be avoided with a chosen amount of confidence. [ABSTRACT FROM AUTHOR]

Satellite observations have the potential to provide an accurate picture of atmospheric chemistry and air quality on a variety of spatial and temporal scales. A key consideration in the design of new instruments is the spatial resolution required to effectively monitor air quality from space. In this paper, vario-grams have been used to address this issue by calculating the horizontal length scales of ozone within the boundary layer and free troposphere using both in situ aircraft data from five different NASA aircraft campaigns and simulations with an air-quality model. For both the observations and the model, the smallest scale features were found in the boundary layer, with a characteristic scale of about 50 km which increased to greater than 150 km above the boundary layer. The length scale changes with altitude. It is shown that similar length scales are derived based on a totally independent approach using constituent lifetimes and typical wind speeds. To date, the spaceborne observations of tropospheric constituents have been from several instruments including TOMS, GOME, MOPITT, TES, and OMI which, in general, have different weighting functions that need to be considered, and none really measures at the surface. A further complication is that most satellite measurements (such as those of OMI and GOME) are of the vertically integrated column. In this paper, the length scales in the column measurements were also of the order of 50 km. To adequately resolve the 50-km features, a horizontal resolution of at least 10 km would be desirable. Index Terms--Air-quality observations, length scales, variograms.

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]

This work presents a new high resolution NO2 dataset derived from the standard NASA Ozone Monitoring Instrument (OMI) NO2 version 3.0 retrieval that can be used to estimate surface level concentrations. The standard NASA product uses NO2 vertical profile shape factors from a 1.25° × 1° (~ 110 × 110 km) resolution Global Model Initiative (GMI) model simulation to calculate air mass factors, a critical value used to determine observed tropospheric NO2 vertical columns. To better estimate vertical profile shape factors, we use a high resolution Community Multi-scale Air Quality (CMAQ) model simulation (1.33 × 1.33 km) to generate tropospheric air mass factors and tropospheric NO2 columns during summertime in the eastern United States. Results show OMI NO2 tropospheric columns in this new product increase by up to 160 % in city centers, and decrease by 20-50 % in the rural areas outside of urban areas when compared to the operational product. This new product shows much better agreement with the Pandora NO2 spectrometer measurements acquired during the DISCOVER-AQ Maryland field campaign. Furthermore, the correlation between this satellite product and EPA NO2 monitors in urban areas has improved dramatically: r2 = 0.60 in new product, r2 = 0.39 in operational product, signifying that this new product is a better indicator of surface concentrations than the operational product. Our work emphasizes the need to use high resolution models to re-calculate satellite data in areas with large spatial heterogeneities in NOx emissions. Although the current work is focused on the eastern United States, the methodology developed in this work can be applied to other world regions to produce high-quality region-specific NO2 satellite retrievals. [ABSTRACT FROM AUTHOR]

An observation-constrained box model based on the Carbon Bond mechanism, version 5 (CB05), was used to study photochemical processes along the NASA P-3B flight track and spirals over eight surface sites during the September 2013 Houston, Texas deployment of the NASA Deriving Information on Surface Conditions from COlumn and VERtically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaign. Data from this campaign provided an opportunity to examine and improve our understanding of atmospheric photochemical oxidation processes related to the formation of secondary air pollutants such as ozone (O3/. O3 production and its sensitivity to NOx and volatile organic compounds (VOCs) were calculated at different locations and times of day. Ozone production efficiency (OPE), defined as the ratio of the ozone production rate to the NOx oxidation rate, was calculated using the observations and the simulation results of the box and Community Multiscale Air Quality (CMAQ) models. Correlations of these results with other parameters, such as radical sources and NOx mixing ratio, were also evaluated. It was generally found that O3 production tends to be more VOC-sensitive in the morning along with high ozone production rates, suggesting that control of VOCs may be an effective way to control O3 in Houston. In the afternoon, O3 production was found to be mainly NOx -sensitive with some exceptions. O3 production near major emissions sources such as Deer Park was mostly VOC-sensitive for the entire day, other urban areas near Moody Tower and Channelview were VOC-sensitive or in the transition regime, and areas farther from downtown Houston such as Smith Point and Conroe were mostly NOx - sensitive for the entire day. It was also found that the control of NOx emissions has reduced O3 concentrations over Houston but has led to larger OPE values. The results from this work strengthen our understanding of O3 production; they indicate that controlling NOx emissions will provide air quality benefits over the greater Houston metropolitan area in the long run, but in selected areas controlling VOC emissions will also be beneficial. [ABSTRACT FROM AUTHOR]