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We present preliminary results in the development of a miniaturized gas correlation radiometer (GCR) for column trace gas measurements in the Martian atmosphere. The GCR is designed as an orbiting instrument capable of mapping multiple trace gases and identifying active regions on the Mars surface.
A Trace Gas Analyzer (TGA) with the ability to detect the presence of toxic contaminants in the Space Shuttle atmosphere within the subparts-per-million range is under development. The design is a modification of the miniaturized Gas Chromatograph-Mass Spectrometer (GCMS) developed for the Viking Mars Lander. An ambient air sample is injected onto the GC column from a constant volume sample loop and separated into individual compounds for identification by the MS. The GC-MS interface consists of an effluent divider and a silver-paladium separator, an electrochemical cell which removes more than 99.99% of the hydrogen carrier gas. The hydrogen is reclaimed and repressurized without affecting the separator efficiency, a feature which enables a considerable weight reduction in the carrier gas supply system.
Trace gases measured by the Atmospheric Trace Molecule Spectroscopy (ATMOS) instrument during the Mar/Apr 1992(AT-1), Apr 1993(AT-2), and Nov 1994(AT-3) space-shuttle missions have been mapped into equivalent latitude/potential temperature (EqL/0) coordinates.
The "Reanalysis for Stratospheric Trace Gas Studies" (ReSTS) project intends to provide a state-of-the-art meteorological dataset for use in chemistry-transport models (CTMs). The initial focus is on the period from May 1991 until April 1995, which encompasses the initial few years of observations from NASA's Upper Atmosphere Research Satellite (UARS) as well as the abrupt increase and slow decay of volcanic aerosol loading from Mount Pinatubo. The reanalysis is being performed using NASA's operational "GEOS-4" data assimilation system. The results presented in this paper will begin with an overview of the meteorology of the ReSTS period, validating the ReSTS data against independent analyses, followed by an evaluation of the system statistics (the "Observation minus Forecast" for different input data types). Some sensitivities to the assumptions made in the assimilation process will be presented, including aspects of the forecast model and the statistical model used in the observation-forecast merging. Aspects of trace-gas transport will be discussed, focussing on the on-line water vapor distribution (which is a quasi-inert trace gas in the stratosphere), off-line transport studies of ozone and selected long-lived species, as well as assimilated ozone. The results will be discussed in the context of transport studies and our ability to use reanalyzed datasets to examine long-term variations in the meteorology and composition of the middle atmosphere.
In order to re-examine trace gas transport in the middle atmosphere for the period May 1991 until April 1995, a "reanalysis" is being performed using an up-to-date version of the DAO's "GEOS" assimilation system. The Reanalysis for Stratospheric Trace-gas Studies (ReSTS) is intended to provide state-of-the-art estimates of the atmosphere during a period when the Upper Atmospheric Research Satellite provided a high density of trace-gas observations, and when the aerosol loading from the eruption of Mount Pinatubo contaminated the lower stratosphere, at the same time performing a natural tracer transport experiment. This study will present the first results from ReSTS, focussing on the improvements over the meteorological analyses produced by the then-operational GEOS-1 data assimilation system; emphasis will be placed on the improved representations of physical processes between GEOS-1 and the current GEOS-4 systems, highlighting the transport properties of the datasets. Alongside the production of a comprehensive atmospheric dataset, important components of ReSTS include performing sensitivity studies to the formulation of the assimilation system (including the representation of physical processes in the GCM, such as feedbacks between ozone/aerosols and meteorology) and to the inclusion of additional data types (including limb-sounding temperature data alongside the TOVS observations). Impacts of some of these factors on the analyzed meteorology and transport will be discussed. Of particular interest are attempts to determine the relative importance of various steps in the assimilation process to the quality of the final analyses.
Scattering and absorption by tropospheric aerosol particles have an effect on the airmass factor (AMF), a fundamental quantity for trace gas concentration retrieval by inversion of satellite measurements. The interference effect depends on the aerosols micro-physical and optical properties as well as the relative distribution of the tropospheric trace gas and aerosol load. Quantifying the aerosol impact on trace gas retrieval requires a sensitivity study using radiative transfer calculations. In this presentation we will describe a recently initiated effort to characterize the aerosol-related error in trace gas retrievals when the presence of aerosol particles is not accounted in the inversion procedure. A general description of the project will be presented and preliminary results on aerosol effects on SO2 retrieved concentrations will be discussed.
An ethylene trace gas technique was used to map out fluid transport and mixing within a circular to rectangular transition duct. Ethylene gas was injected at several points in a cross stream plane upstream of the transition duct. Ethylene concentration contours were determined at several cross stream measurement planes spaced axially within the duct. The flow involved a uniform inlet flow at a Mach number level of 0.5. Statistical analyses were used to quantitatively interpret the trace gas results. Also, trace gas data were considered along with aerodynamic and surface flow visualization results to ascertain transition duct flow phenomena. Convection of wall boundary layer fluid by vortices produced regions of high total pressure loss in the duct. The physical extent of these high loss regions is governed by turbulent diffusion.
An ethylene trace gas technique was used to map out fluid transport and mixing within a circular-to-rectangular transition duct. Ethylene gas was injected at several points in a cross stream plane upstream of the transition duct. Ethylene concentration contours were determined at several cross stream measurement planes spaced axially within the duct. The flow involved a uniform inlet flow at a Mach number level of 0.5. Statistical analyses were used to quantitatively interpret the trace gas results. Also, trace gas data were considered along with aerodynamic and surface flow visualization results to ascertain transition duct flow phenomena. Convection of wall boundary layer fluid by vortices produced regions of high total pressure loss in the duct. The physical extent of these high loss regions is governed by turbulent diffusion.
India is largely devoid of high-quality and reliable on-the-ground measurements of fine particulate matter (PM 2.5 ). Ground-level PM 2.5 concentrations are estimated from publicly available satellite Aerosol Optical Depth (AOD) products combined with other information. Prior research has largely overlooked the possibility of gaining additional accuracy and insights into the sources of PM using satellite retrievals of tropospheric trace gas columns. We evaluate the information content of tropospheric trace gas columns for PM 2.5 estimates over India within a modeling testbed using an Automated Machine Learning (AutoML) approach, which selects from a menu of different machine learning tools based on the data set. We then quantify the relative information content of tropospheric trace gas columns, AOD, meteorological fields, and emissions for estimating PM 2.5 over four Indian sub-regions on daily and monthly time scales. Our findings suggest that, regardless of the specific machine learning model assumptions, incorporating trace gas modeled columns improves PM 2.5 estimates. We use the ranking scores produced from the AutoML algorithm and Spearman’s rank correlation to infer or link the possible relative importance of primary versus secondary sources of PM 2.5 as a first step toward estimating particle composition. Our comparison of AutoML-derived models to selected baseline machine learning models demonstrates that AutoML is at least as good as user-chosen models. The idealized pseudo-observations (chemical-transport model simulations) used in this work lay the groundwork for applying satellite retrievals of tropospheric trace gases to estimate fine particle concentrations in India and serve to illustrate the promise of AutoML applications in atmospheric and environmental research.
Gas correlation radiometry (GCR) has been shown to be a sensitive and versatile method for detecting trace gases in Earth's atmosphere. Here, we present a miniaturized and simplified version of this instrument capable of mapping multiple trace gases and identifying active regions on the Mars surface. Reduction of the size and mass of the GCR instrument has been achieved by implementing a lightweight, 1 mm inner diameter hollow-core optical fiber (hollow waveguide) for the gas correlation cell. Based on a comparison with an Earth orbiting CO2 gas correlation instrument, replacement of the 10 meter mUltipass cell with hollow waveguide of equivalent pathlength reduces the cell mass from approx 150 kg to approx 0.5 kg, and reduces the volume from 1.9 m x 1.3 m x 0.86 m to a small bundle of fiber coils approximately I meter in diameter by 0.05 m in height (mass and volume reductions of >99%). This modular instrument technique can be expanded to include measurements of additional species of interest including nitrous oxide (N2O), hydrogen sulfide (H2S), methanol (CH3OH), and sulfur dioxide (SO2), as well as carbon dioxide (CO2) for a simultaneous measure of mass balance.
We develop an approach to estimate and characterize trace gas retrievals in the presence of clouds in high spectral measurements of upwelling radiance in the infrared spectral region (650-2260/cm). The radiance contribution of clouds is parameterized in terms of a set of frequency-dependent nonscattering optical depths and a cloud height. These cloud parameters are retrieved jointly with surface temperature, emissivity, atmospheric temperature, and trace gases such as ozone from spectral data. We demonstrate the application of this approach using data from the Tropospheric Emission Spectrometer (TES) and test data simulated with a scattering radiative transfer model. We show the value of this approach in that it results in accurate estimates of errors for trace gas retrievals, and the retrieved values improve over the initial guess for a wide range of cloud conditions. Comparisons are made between TES retrievals of ozone, temperature, and water to model fields from the Global Modeling and Assimilation Office (GMAO), temperature retrievals from the Atmospheric Infrared Sounder (AIRS), tropospheric ozone columns from the Goddard Earth Observing System (GEOS) GEOS-Chem, and ozone retrievals from the Total Ozone Mapping Spectrometer (TOMS). In each of these cases, this cloud retrieval approach does not introduce observable biases into TES retrievals.
Three applications of the ethylene trace-gas technique to high-speed flows are described: flow-field tracking, air-to-air mixing, and bleed mass-flow measurement. The technique involves injecting a non-reacting gas (ethylene) into the flow field and measuring the concentration distribution in a downstream plane. From the distributions, information about flow development, mixing, and mass-flow rates can be dtermined. The trace-gas apparatus and special considerations for use in high-speed flow are discussed. A description of each application, including uncertainty estimates is followed by a demonstrative example.
An open-path laser spectrometer (OPLS) for measuring a concentration of a trace gas, the OPLS including an open-path multi-pass analysis region including a first mirror, a second mirror at a distance and orientation from the first mirror, and a support structure for locating the mirrors, a laser coupled to the analysis region and configured to emit light of a wavelength range and to enable a plurality of reflections of the emitted light between the mirrors, a detector coupled to the analysis region and configured to detect a portion of the emitted light impinging on the detector and to generate a corresponding signal, and an electronic system coupled to the laser and the detector, and configured to adjust the wavelength range of the emitted light from the laser based on the generated signal, and to measure the concentration of the trace gas based on the generated signal.
The AERONET (AErosol RObotic NETwork) ground-based suite of sunphotometers provides measurements of spectral aerosol optical depth (AOD), precipitable water and spectral sky radiance, which can be inverted to retrieve aerosol microphysical properties that are critical to assessments of aerosol-climate interactions. Because of data quality criteria and sampling constraints, there are significant limitations to the temporal and spatial coverage of AERONET data and their representativeness for global aerosol conditions. The 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) instrument, jointly developed by NASA Ames and PNNL with NASA Goddard collaboration, combines airborne sun tracking and AERONET-like sky scanning with spectroscopic detection. Being an airborne instrument, 4STAR has the potential to fill gaps in the AERONET data set. Dunagan et al. [2013] present results establishing the performance of the instrument, along with calibration, engineering flight test, and preliminary scientific field data. The 4STAR instrument operated successfully in the SEAC4RS [Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys] experiment in Aug./Sep. 2013 aboard the NASA DC-8 and in the DoE [Department of Energy]-sponsored TCAP [Two Column Aerosol Project, July 2012 & Feb. 2013] experiment aboard the DoE G-1 aircraft (Shinozuka et al., 2013), and acquired a wealth of data in support of mission objectives on all SEAC4RS and TCAP research flights. 4STAR provided direct beam measurements of hyperspectral AOD, columnar trace gas retrievals (H2O, O3, NO2; Segal-Rosenheimer et al., 2014), and the first ever airborne hyperspectral sky radiance scans, which can be inverted to yield the same products as AERONET ground-based observations. In addition, 4STAR measured zenith radiances underneath cloud decks for retrievals of cloud optical depth and effective diameter. In this presentation, we provide an overview of the new 4STAR capabilities for airborne field campaigns, with an emphasis on comparisons between 4STAR and AERONET sky radiances, and retrievals of aerosol microphysical properties based on sky radiance measurements, column trace gas amounts from spectral direct beam measurements and cloud property retrievals from zenith mode observations for a few select case studies in the SEAC4RS and TCAP experiments. We summarize the aerosol, trace gas, cloud and airmass characterization studies made possible by the combined 4STAR direct beam, and sky/zenith radiance observations.
The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a test bed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA Falcon aircraft in its first intensive field measurement campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Earth Venture Mission over Houston, Texas, in September 2013. Measurements of backscattered solar radiation between 420 and 465 nm collected on 4 days during the campaign are used to determine slant column amounts of NO2 at 250 m x 250 m spatial resolution with a fitting precision of 2.2 x 10(exp 15) molecules/sq cm. These slant columns are converted to tropospheric NO2 vertical columns using a radiative transfer model and trace gas profiles from the Community Multiscale Air Quality (CMAQ) model. Total column NO2 from GeoTASO is well correlated with ground-based Pandora observations (r = 0.90 on the most polluted and cloud-free day of measurements and r = 0.74 overall), with GeoTASO NO2 slightly higher for the most polluted observations. Surface NO2 mixing ratios inferred from GeoTASO using the CMAQ model show good correlation with NO2 measured in situ at the surface during the campaign (r = 0.85). NO2 slant columns from GeoTASO also agree well with preliminary retrievals from the GEO-CAPE Airborne Simulator (GCAS) which flew on the NASA King Air B200 (r = 0.81, slope = 0.91). Enhanced NO2 is resolvable over areas of traffic NOx emissions and near individual petrochemical facilities.
A widely tunable infrared spectrometer based on difference frequency generation (DFG) has been developed for organic trace gas detection by laser absorption spectroscopy. On-line measurements of concentration of various hydrocarbons, such as acetylene, benzene, and ethylene, were investigated using high-resolution DFG trace gas spectroscopy for highly sensitive detection.
The NASA Amazon Boundary Layer Experiment (ABLE 2A) based in Manaus, Brazil, in July and August 1985, is used to examine meteorological processes responsible for the vertical and horizontal transport of biogenic and anthropogenic trace gases generated over the Amazon basin. Direct sampling of the surrounding environment of deep convective clouds shows marked changes in the vertical distribution of the lower and midtroposphere concentration of O3 and such surface-derived species as CO, CO2, and NO. Thermodynamic observations, together with two-dimensional cloud model simulations, confirm vertical transports within the convection and provide a basis for an estimation of the magnitude and efficiency of cloud upward and downward exchanges. A distinction is drawn between local changes due to convective updrafts and downdrafts and convective overturning as a net result of the storm processes. Marked variability is seen in trace gas concentrations along horizontal flight paths in the vicinity of the convection. Interpretation of simultaneously measured thermodynamic quantities and trace gas concentrations provide the information to infer the presence and direction of atmospheric transports and/or the presence of anthropogenic influences.
Surface-level ozone (O3) pollution mitigation strategies rely on a clear understanding of the atmospheric chemical processes involving O3, NOx (nitric oxide (NO) + nitrogen dioxide (NO2)) and volatile organic compounds (VOCs). A robust spatiotemporal classification of O3 photochemical regimes with relative chemical sensitivity of local O3 formation to emission reductions of NOx (NOx-limited regime) versus VOCs (radical-limited regime) is required to design anthropogenic emission reduction policies in order to improve surface air quality. Numerous studies found that the ratio of satellite-retrieved Vertical Column Densities (VCDs) of formaldehyde (HCHO) to NO2 can diagnose O3 production sensitivity. However, uncertainty still remains about the accuracy of such estimates using satellite-based retrievals. This study conducts an investigation to identify how well satellite data can inform surface-level O3 sensitivity by validating satellite-based estimates against aircraft-based retrievals taken during the Long Island Sound Tropospheric Ozone Study (LISTOS-2018) and Ozone Water-Land Environmental Transition Study (OWLETS-2) field campaigns. For this study, we use HCHO and NO2 retrievals from the Ozone Monitoring Instrument (OMI) onboard the Aura satellite, and high spatiotemporal resolution TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (S5P) satellite. The Community Multiscale Air Quality (CMAQ) modelling system is used to provide trace gas vertical profiles to recalculate air mass factor for deriving consistent satellite-based VCDs. To demonstrate the ability of satellites to diagnose O3 production regimes, we validate satellite-derived O3 sensitivity regimes, along with the OMI and TROPOMI products applied, using HCHO and NO2 retrievals from the aircraft-based instruments: Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) spectrometer and Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) instruments deployed during the LISTOS-2018 and OWLETS-2 campaigns. The results of this work will advance our fundamental knowledge of the spatiotemporal evolution of the complex O3-NOx-VOC chemistry, and will advance our understanding about the quality of remote-sensing, suborbital, and satellite data for accurately observing surface-level O3 production sensitivity.