163 research outputs found

    Reducing the impact of source brightness fluctuations on spectra obtained by Fourier-transform spectrometry

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    We present a method to reduce the impact of source brightness fluctuations (SBFs) on spectra recorded by Fourier-transform spectrometry (FTS). Interferograms are recorded without AC coupling of the detector signal (DC mode). The SBF are determined by low-pass filtering of the DC interferograms, which are then reweighted by the low-pass, smoothed signal. Atmospheric solar absorption interferograms recorded in DC mode have been processed with and without this technique, and we demonstrate its efficacy in producing more consistent retrievals of atmospheric composition. We show that the reweighting algorithm improves retrievals from interferograms subject to both gray and nongray intensity fluctuations, making the algorithm applicable to atmospheric data contaminated by significant amounts of aerosol or cloud cover

    Trace gas emissions from savanna fires in northern Australia

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    We present analyses of near‐infrared ground‐based Fourier transform infrared solar absorption spectra recorded from a site in Darwin, Northern Territory, Australia (12.4°S, 130.9°E) from August 2005 to June 2008. Total column amounts of carbon monoxide derived from these spectra show a very clear annual cycle, with evidence of transported pollution from Indonesian fires in 2006. Aerosol optical depth measurements from the same site show a similar annual cycle but without exceptional values in 2006, suggesting significant loss of aerosol loading in the transported and aged smoke. In addition, we report the first ever measurements by remote sensing solar Fourier transform infrared of emission ratios with respect to carbon monoxide for formaldehyde (0.022 ± 0.007), acetylene (0.0024 ± 0.0003), ethane (0.0020 ± 0.0003), and hydrogen cyanide (0.0018 ± 0.0003) from Australian savanna fires. These are derived from mid‐infrared spectra recorded through smoke plumes over Darwin on 20 separate days. The only previous measurements of emission ratios for formaldehyde and hydrogen cyanide from Australian savanna fires involved cryogenic trapping and storage of samples that were gathered in very fresh smoke. The results reported here are nearly an order of magnitude higher (but in agreement with laboratory studies), suggesting losses in the collection, storage, or transfer of the gases in the earlier measurements and/or chemical production of these reactive gases within the smoke plumes. Emission ratios for acetylene and ethane from this work are in broad agreement with other literature values

    Satellite and ground-based measurements of XCO2 in a remote semiarid region of Australia

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    In this study, we present ground-based measurements of column-averaged dry-air mole fractions (DMFs) of CO2 (or XCO2) taken in a semiarid region of Australia with an EM27/SUN portable spectrometer equipped with an automated clamshell cover. We compared these measurements to space-based XCO2 retrievals from the Greenhouse Gases Observing Satellite (GOSAT). Side-by-side measurements of EM27/SUN with the Total Carbon Column Observing Network (TCCON) instrument at the University of Wollongong were conducted in 2015-2016 to derive an XCO2 scaling factor of 0.9954 relative to TCCON. Although we found a slight drift of 0.13 % over 3 months in the calibration curve of the EM27/SUN vs. TCCON XCO2, the alignment of the EM27/SUN proved stable enough for a 2-week campaign, keeping the retrieved Xair values, another measure of stability, to within 0.5 % and the modulation efficiency to within 2 %. From the measurements in Alice Springs, we confirm a small bias of around 2 ppm in the GOSAT M-gain to H-gain XCO2 retrievals, as reported by the NIES GOSAT validation team. Based on the reported random errors from GOSAT, we estimate the required duration of a future campaign in order to better understand the estimated bias between the EM27/SUN and GOSAT. The dataset from the Alice Springs measurements is accessible at https://doi.org/10.4225/48/5b21f16ce69bc (Velazco et al., 2018)

    Improving atmospheric CO\u3csub\u3e2\u3c/sub\u3e retrievals using line mixing and speed-dependence when fitting high-resolution ground-based solar spectra

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    A quadratic speed-dependent Voigt spectral line shape with line mixing (qSDV + LM) has been included in atmospheric trace-gas retrievals to improve the accuracy of the calculated CO2 absorption coefficients. CO2 laboratory spectra were used to validate absorption coefficient calculations for three bands: the strong 20013 ← 00001 band centered at 4850 cm−1, and the weak 30013 ← 00001 and 30012 ← 00001 bands centered at 6220 cm−1 and 6340 cm−1 respectively, and referred to below as bands 1 and 2. Several different line lists were tested. Laboratory spectra were best reproduced for the strong CO2 band when using HITRAN 2008 spectroscopic data with air-broadened widths divided by 0.985, self-broadened widths divided by 0.978, line mixing coefficients calculated using the exponential power gap (EPG) law, and a speed-dependent parameter of 0.11 used for all lines. For the weak CO2 bands, laboratory spectra were best reproduced using spectroscopic parameters from the studies by Devi et al. in 2007 coupled with line mixing coefficients calculated using the EPG law. A total of 132,598 high-resolution ground-based solar absorption spectra were fitted using qSDV + LM to calculate CO2 absorption coefficients and compared to fits that used the Voigt line shape. For the strong CO2 band, the average root mean square (RMS) residual is 0.49 ± 0.22% when using qSDV + LM to calculate the absorption coefficients. This is an improvement over the results with the Voigt line shape, which had an average RMS residual of 0.60 ± 0.21%. When using the qSDV + LM to fit the two weak CO2 bands, the average RMS residual is 0.47 ± 0.19% and 0.51 ± 0.20% for bands 1 and 2, respectively. These values are identical to those obtained with the Voigt line shape. Finally, we find that using the qSDV + LM decreases the airmass dependence of the column averaged dry air mole fraction of CO2 retrieved from the strong and both weak CO2 bands when compared to the retrievals obtained using the Voigt line shape

    The Australian methane budget: Interpreting surface and train-borne measurements using a chemistry transport model

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    We investigate the Australian methane budget from 2005-2008 using the GEOS-Chem 3D chemistry transport model, focusing on the relative contribution of emissions from different sectors and the influence of long-range transport. To evaluate the model, we use in situ surface measurements of methane, methane dry air column average (XCH 4) from ground-based Fourier transform spectrometers (FTSs), and train-borne surface concentration measurements from an in situ FTS along the north-south continental transect. We use gravity anomaly data from Gravity Recovery and Climate Experiment to describe the spatial and temporal distribution of wetland emissions and scale it to a prior emission estimate, which better describes observed atmospheric methane variability at tropical latitudes. The clean air sites of Cape Ferguson and Cape Grim are the least affected by local emissions, while Wollongong, located in the populated southeast with regional coal mining, samples the most locally polluted air masses (2.5% of the total air mass versus \u3c1% at other sites). Averaged annually, the largest single source above background of methane at Darwin is long-range transport, mainly from Southeast Asia, accounting for ~25% of the change in surface concentration above background. At Cape Ferguson and Cape Grim, emissions from ruminant animals are the largest source of methane above background, at approximately 20% and 30%, respectively, of the surface concentration. At Wollongong, emissions from coal mining are the largest source above background representing 60% of the surface concentration. The train data provide an effective way of observing transitions between urban, desert, and tropical landscapes. Copyright Copyright 2011 by the American Geophysical Union

    Calibration of TCCON column-averaged CO2: the first aircraft campaign over European TCCON sites

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    The Total Carbon Column Observing Network (TCCON) is a ground-based network of Fourier Transform Spectrometer (FTS) sites around the globe, where the column abundances of CO2, CH4, N2O, CO and O2 are measured. CO2 is constrained with a precision better than 0.25% (1-σ). To achieve a similarly high accuracy, calibration to World Meteorological Organization (WMO) standards is required. This paper introduces the first aircraft calibration campaign of five European TCCON sites and a mobile FTS instrument. A series of WMO standards in-situ profiles were obtained over European TCCON sites via aircraft and compared with retrievals of CO2 column amounts from the TCCON instruments. The results of the campaign show that the FTS measurements are consistently biased 1.1% ± 0.2% low with respect to WMO standards, in agreement with previous TCCON calibration campaigns. The standard a priori profile for the TCCON FTS retrievals is shown to not add a bias. The same calibration factor is generated using aircraft profiles as a priori and with the TCCON standard a priori. With a calibration to WMO standards, the highly precise TCCON CO2 measurements of total column concentrations provide a suitable database for the calibration and validation of nadir-viewing satellite

    Bayesian atmospheric tomography for detection and quantification of methane emissions : application to data from the 2015 Ginninderra release experiment

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    Detection and quantification of greenhouse-gas emissions is important for both compliance and environment conservation. However, despite several decades of active research, it remains predominantly an open problem, largely due to model errors and assumptions that appear at each stage of the inversion processing chain. In 2015, a controlled-release experiment headed by Geoscience Australia was carried out at the Ginninderra Controlled Release Facility, and a variety of instruments and methods were employed for quantifying the release rates of methane and carbon dioxide from a point source. This paper proposes a fully Bayesian approach to atmospheric tomography for inferring the methane emission rate of this point source using data collected during the experiment from both point-and path-sampling instruments. The Bayesian framework is designed to account for uncertainty in the parameterisations of measurements, the meteorological data, and the atmospheric model itself when performing inversion using Markov chain Monte Carlo (MCMC). We apply our framework to all instrument groups using measurements from two release-rate periods. We show that the inversion framework is robust to instrument type and meteorological conditions. From all the inversions we conducted across the different instrument groups and release-rate periods, our worst-case median emission rate estimate was within 36% of the true emission rate. Further, in the worst case, the closest limit of the 95% credible interval to the true emission rate was within 11% of this true value

    Preliminary validation of column-averaged volume mixing ratios of carbon dioxide and methane retrieved from GOSAT short-wavelength infrared spectra

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    Column-averaged volume mixing ratios of carbon dioxide and methane retrieved from the Greenhouse gases Observing SATellite (GOSAT) Short-Wavelength InfraRed observation (GOSAT SWIR XCO2 and XCH4 ) were compared with the reference calibrated data obtained by ground-based high-resolution Fourier Transform Spectrometers (g-b FTSs) participating in the Total Carbon Column Observing Network (TCCON). Preliminary results are as follows: the GOSAT SWIR XCO2 and XCH4 (Version 01.xx) are biased low by 8.85 ±4.75 ppm (2.3±1.2 %) and 20.4±18.9 ppb (1.2±1.1 %), respectively. The standard deviation of the GOSAT SWIR XCO2 and XCH4 is about 1% after correcting the negative biases of XCO2 and XCH4 by 8.85 ppm and 20.4 ppb, respectively. The latitudinal distributions of zonal means of the GOSAT SWIR XCO2 and XCH4 show similar features to those of the g-b FTS data except for the negative biases in the GOSAT data
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