Remote sensing of CO2 and CH4 using solar absorption spectrometry with a low resolution spectrometer

Throughout the last few years solar absorption Fourier Transform Spectrometry (FTS) has been further developed to measure the total columns of CO2 and CH4. The observations are performed at high spectral resolution, typically at 0.02 cm(-1). The precision currently achieved is generally better than 0.25%. However, these high resolution instruments are quite large and need a dedicated room or container for installation. We performed these observations using a smaller commercial interferometer at its maximum possible resolution of 0.11 cm(-1). The measurements have been performed at Bremen and have been compared to observations using our high resolution instrument also situated at the same location. The high resolution instrument has been successfully operated as part of the Total Carbon Column Observing Network (TCCON). The precision of the low resolution instrument is 0.32% for XCO2 and 0.46% for XCH4. A comparison of the measurements of both instruments yields an average deviation in the retrieved daily means of 0.2% for CO2. For CH4 an average bias between the instruments of 0.47% was observed. For test cases, spectra recorded by the high resolution instrument have been truncated to the resolution of 0.11 cm(-1). This study gives an offset of 0.03% for CO2 and 0.26% for CH4. These results indicate that for CH4 more than 50% of the difference between the instruments results from the resolution dependent retrieval. We tentatively assign the offset to an incorrect a-priori concentration profile or the effect of interfering gases, which may not be treated correctly

Pressure broadening in the 2v_3 band of methane and its implication on atmospheric retrievals

N_2-broadened half widths and pressure shifts were obtained for transitions in the 2ν_3 methane band. Laboratory measurements recorded at 0.011 cm^(−1) resolution with a Bruker 120 HR Fouriertransform spectrometer were analysed from 5860 to 6185 cm^(−1). A 140 cm gas cell was filled with methane at room temperature and N_2 as foreign gas at pressures ranging from 125 to 900 hPa. A multispectrum nonlinear constrained least squares approach based on Optimal Estimation was applied to derive the spectroscopic parameters by simultaneously fitting laboratory spectra at different ambient pressures assuming a Voigt line-shape. At room temperature, the half widths ranged between 0.030 and 0.071 cm^(−1) atm^(−1), and the pressure shifts varied from –0.002 to –0.025 cm^(−1) atm^(−1) for transitions up to J"=10. Especially for higher rotational levels, we find systematically narrower lines than HITRAN predicts. The Q and R branch of the new set of spectroscopic parameters is further tested with ground based direct sun Fourier transform infrared (FTIR) measurements where systematic fit residuals reduce by about a factor of 3–4. We report the implication of those differences on atmospheric methane measurements using high-resolution ground based FTIR measurements as well as low-resolution spectra from the SCanning Imaging Absorption SpectroMeter for Atmospheric ChartographY (SCIAMACHY) instrument onboard ENVISAT. We find that for SCIAMACHY, a latitudinal and seasonally varying bias of about 1% can be introduced by erroneous broadening parameters

Methane spectroscopy in the near infrared and its implication on atmospheric retrievals

International audienceN2-broadened half widths and pressure shifts were obtained for transitions in the Q and R branches of the 2?3 methane band. Laboratory measurements were done from 5985 to 6185 cm?1 using spectra recorded at 0.011 cm?1 resolution with a Bruker 120 HR Fourier transform spectrometer. A 140 cm gas cell was filled with methane at room temperature and N2 as foreign gas at pressures ranging from 125 to 900 hPa. A multispectrum nonlinear constrained least squares approach based on Optimal Estimation was applied to derive the spectroscopic parameters by simultaneously fitting laboratory spectra at different ambient pressures assuming a Voigt line-shape. At room temperature, the half widths ranged between 0.030 and 0.071 cm?1 atm?1, and the pressure shifts varied from ?0.002 to ?0.025 cm?1 atm?1 for transitions up to J"=10. Especially for higher rotational levels, we find systematically narrower lines than HITRAN predicts. The new set of spectroscopic parameters is further tested with ground based direct sun FTIR measurements where fit residuals reduce by about a factor of 3?4. We report the implication of those differences on atmospheric methane measurements using high-resolution ground based FTIR measurements as well as low-resolution spectra from the SCIAMACHY instrument onboard ENVISAT. We find that for SCIAMACHY, a latitudinal and seasonally varying bias of about 1% can be introduced by erroneous broadening parameters

The arctic seasonal cycle of total column CO2 and CH4 from ground-based solar and lunar FTIR absorption spectrometry

Solar absorption spectroscopy in the near infrared has been performed in Ny-Ålesund (78.9° N, 11.9° E) since 2002; however, due to the high latitude of the site, the sun is below the horizon from October to March (polar night) and no solar absorption measurements are possible. Here we present a novel method of retrieving the total column dry-air mole fractions (DMFs) of CO2 and CH4 using moonlight in winter. Measurements have been taken during the polar nights from 2012 to 2016 and are validated with TCCON (Total Carbon Column Observing Network) measurements by solar and lunar absorption measurements on consecutive days and nights during spring and autumn. The complete seasonal cycle of the DMFs of CO2 and CH4 is presented and a precision of up to 0.5 % is achieved. A comparison of solar and lunar measurements on consecutive days during day and night in March 2013 yields non-significant biases of 0. 66 ± 4. 56 ppm for xCO2 and −1. 94 ± 20. 63 ppb for xCH4. Additionally a model comparison has been performed with data from various reanalysis models

Atmospheric greenhouse gases retrieved from SCIAMACHY: comparison to ground-based FTS measurements and model results

SCIAMACHY onboard ENVISAT (launched in 2002) enables the retrieval of global long-term column-averaged dry air mole fractions of the two most important anthropogenic greenhouse gases carbon dioxide and methane (denoted XCO_2 and XCH_4). In order to assess the quality of the greenhouse gas data obtained with the recently introduced v2 of the scientific retrieval algorithm WFM-DOAS, we present validations with ground-based Fourier Transform Spectrometer (FTS) measurements and comparisons with model results at eight Total Carbon Column Observing Network (TCCON) sites providing realistic error estimates of the satellite data. Such validation is a prerequisite to assess the suitability of data sets for their use in inverse modelling. It is shown that there are generally no significant differences between the carbon dioxide annual increases of SCIAMACHY and the assimilation system CarbonTracker (2.00 ± 0.16 ppm yr^(−1) compared to 1.94 ± 0.03 ppm yr−1 on global average). The XCO_2 seasonal cycle amplitudes derived from SCIAMACHY are typically larger than those from TCCON which are in turn larger than those from CarbonTracker. The absolute values of the northern hemispheric TCCON seasonal cycle amplitudes are closer to SCIAMACHY than to CarbonTracker and the corresponding differences are not significant when compared with SCIAMACHY, whereas they can be significant for a subset of the analysed TCCON sites when compared with CarbonTracker. At Darwin we find discrepancies of the seasonal cycle derived from SCIAMACHY compared to the other data sets which can probably be ascribed to occurrences of undetected thin clouds. Based on the comparison with the reference data, we conclude that the carbon dioxide data set can be characterised by a regional relative precision (mean standard deviation of the differences) of about 2.2 ppm and a relative accuracy (standard deviation of the mean differences) of 1.1–1.2 ppm for monthly average composites within a radius of 500 km. For methane, prior to November 2005, the regional relative precision amounts to 12 ppb and the relative accuracy is about 3 ppb for monthly composite averages within the same radius. The loss of some spectral detector pixels results in a degradation of performance thereafter in the spectral range currently used for the methane column retrieval. This leads to larger scatter and lower XCH_4 values are retrieved in the tropics for the subsequent time period degrading the relative accuracy. As a result, the overall relative precision is estimated to be 17 ppb and the relative accuracy is in the range of about 10–20 ppb for monthly averages within a radius of 500 km. The derived estimates show that the SCIAMACHY XCH_4 data set before November 2005 is suitable for regional source/sink determination and regional-scale flux uncertainty reduction via inverse modelling worldwide. In addition, the XCO2 monthly data potentially provide valuable information in continental regions, where there is sparse sampling by surface flask measurements

Global atmospheric budget of acetaldehyde: 3-D model analysis and constraints from in-situ and satellite observations

We construct a global atmospheric budget for acetaldehyde using a 3-D model of atmospheric chemistry (GEOS-Chem), and use an ensemble of observations to evaluate present understanding of its sources and sinks. Hydrocarbon oxidation provides the largest acetaldehyde source in the model (128 Tg a<sup>−1</sup>, a factor of 4 greater than the previous estimate), with alkanes, alkenes, and ethanol the main precursors. There is also a minor source from isoprene oxidation. We use an updated chemical mechanism for GEOS-Chem, and photochemical acetaldehyde yields are consistent with the Master Chemical Mechanism. We present a new approach to quantifying the acetaldehyde air-sea flux based on the global distribution of light absorption due to colored dissolved organic matter (CDOM) derived from satellite ocean color observations. The resulting net ocean emission is 57 Tg a<sup>−1</sup>, the second largest global source of acetaldehyde. A key uncertainty is the acetaldehyde turnover time in the ocean mixed layer, with quantitative model evaluation over the ocean complicated by known measurement artifacts in clean air. Simulated concentrations in surface air over the ocean generally agree well with aircraft measurements, though the model tends to overestimate the vertical gradient. PAN:NO<sub>x</sub> ratios are well-simulated in the marine boundary layer, providing some support for the modeled ocean source. We introduce the Model of Emissions of Gases and Aerosols from Nature (MEGANv2.1) for acetaldehyde and ethanol and use it to quantify their net flux from living terrestrial plants. Including emissions from decaying plants the total direct acetaldehyde source from the land biosphere is 23 Tg a<sup>−1</sup>. Other terrestrial acetaldehyde sources include biomass burning (3 Tg a<sup>−1</sup>) and anthropogenic emissions (2 Tg a<sup>−1</sup>). Simulated concentrations in the continental boundary layer are generally unbiased and capture the spatial gradients seen in observations over North America, Europe, and tropical South America. However, the model underestimates acetaldehyde levels in urban outflow, suggesting a missing source in polluted air. Ubiquitous high measured concentrations in the free troposphere are not captured by the model, and based on present understanding are not consistent with concurrent measurements of PAN and NO<sub>x</sub>: we find no compelling evidence for a widespread missing acetaldehyde source in the free troposphere. We estimate the current US source of ethanol and acetaldehyde (primary + secondary) at 1.3 Tg a<sup>−1</sup> and 7.8 Tg a<sup>−1</sup>, approximately 60{%} and 480% of the corresponding increases expected for a national transition from gasoline to ethanol fuel

Towards understanding the variability in biospheric CO2 fluxes:Using FTIR spectrometry and a chemical transport model to investigate the sources and sinks of carbonyl sulfide and its link to CO2

Understanding carbon dioxide (CO2) biospheric processes is of great importance because the terrestrial exchange drives the seasonal and interannual variability of CO2 in the atmosphere. Atmospheric inversions based on CO2 concentration measurements alone can only determine net biosphere fluxes, but not differentiate between photosynthesis (uptake) and respiration (production). Carbonyl sulfide (OCS) could provide an important additional constraint: it is also taken up by plants during photosynthesis but not emitted during respiration, and therefore is a potential means to differentiate between these processes. Solar absorption Fourier Transform InfraRed (FTIR) spectrometry allows for the retrievals of the atmospheric concentrations of both CO2 and OCS from measured solar absorption spectra. Here, we investigate co-located and quasi-simultaneous FTIR measurements of OCS and CO2 performed at five selected sites located in the Northern Hemisphere. These measurements are compared to simulations of OCS and CO2 using a chemical transport model (GEOS-Chem). The coupled biospheric fluxes of OCS and CO2 from the simple biosphere model (SiB) are used in the study. The CO2 simulation with SiB fluxes agrees with the measurements well, while the OCS simulation reproduced a weaker drawdown than FTIR measurements at selected sites, and a smaller latitudinal gradient in the Northern Hemisphere during growing season when comparing with HIPPO (HIAPER Pole-to-Pole Observations) data spanning both hemispheres. An offset in the timing of the seasonal cycle minimum between SiB simulation and measurements is also seen. Using OCS as a photosynthesis proxy can help to understand how the biospheric processes are reproduced in models and to further understand the carbon cycle in the real world

Orbital dynamics of "smart dust" devices with solar radiation pressure and drag

This paper investigates how perturbations due to asymmetric solar radiation pressure, in the presence of Earth shadow, and atmospheric drag can be balanced to obtain long-lived Earth centred orbits for swarms of micro-scale 'smart dust' devices, without the use of active control. The secular variation of Keplerian elements is expressed analytically through an averaging technique. Families of solutions are then identified where Sun-synchronous apse-line precession is achieved passively to maintain asymmetric solar radiation pressure. The long-term orbit evolution is characterized by librational motion, progressively decaying due to the non-conservative effect of atmospheric drag. Long-lived orbits can then be designed through the interaction of energy gain from asymmetric solar radiation pressure and energy dissipation due to drag. In this way, the usual short drag lifetime of such high area-to-mass spacecraft can be greatly extended (and indeed selected). In addition, the effect of atmospheric drag can be exploited to ensure the rapid end-of-life decay of such devices, thus preventing long-lived orbit debris

The Greenhouse Gas Climate Change Initiative (GHG-CCI): comparative validation of GHG-CCI SCIAMACHY/ENVISAT and TANSO-FTS/GOSAT CO₂ and CH₄ retrieval algorithm products with measurements from the TCCON

Column-averaged dry-air mole fractions of carbon dioxide and methane have been retrieved from spectra acquired by the TANSO-FTS (Thermal And Near-infrared Sensor for carbon Observations-Fourier Transform Spectrometer) and SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Cartography) instruments on board GOSAT (Greenhouse gases Observing SATellite) and ENVISAT (ENVIronmental SATellite), respectively, using a range of European retrieval algorithms. These retrievals have been compared with data from ground-based high-resolution Fourier transform spectrometers (FTSs) from the Total Carbon Column Observing Network (TCCON). The participating algorithms are the weighting function modified differential optical absorption spectroscopy (DOAS) algorithm (WFMD, University of Bremen), the Bremen optimal estimation DOAS algorithm (BESD, University of Bremen), the iterative maximum a posteriori DOAS (IMAP, Jet Propulsion Laboratory (JPL) and Netherlands Institute for Space Research algorithm (SRON)), the proxy and full-physics versions of SRON's RemoTeC algorithm (SRPR and SRFP, respectively) and the proxy and full-physics versions of the University of Leicester's adaptation of the OCO (Orbiting Carbon Observatory) algorithm (OCPR and OCFP, respectively). The goal of this algorithm inter-comparison was to identify strengths and weaknesses of the various so-called round- robin data sets generated with the various algorithms so as to determine which of the competing algorithms would proceed to the next round of the European Space Agency's (ESA) Greenhouse Gas Climate Change Initiative (GHG-CCI) project, which is the generation of the so-called Climate Research Data Package (CRDP), which is the first version of the Essential Climate Variable (ECV) "greenhouse gases" (GHGs). For XCO₂, all algorithms reach the precision requirements for inverse modelling (< 8 ppm), with only WFMD having a lower precision (4.7 ppm) than the other algorithm products (2.4–2.5 ppm). When looking at the seasonal relative accuracy (SRA, variability of the bias in space and time), none of the algorithms have reached the demanding < 0.5 ppm threshold. For XCH₄, the precision for both SCIAMACHY products (50.2 ppb for IMAP and 76.4 ppb for WFMD) fails to meet the < 34 ppb threshold for inverse modelling, but note that this work focusses on the period after the 2005 SCIAMACHY detector degradation. The GOSAT XCH₄ precision ranges between 18.1 and 14.0 ppb. Looking at the SRA, all GOSAT algorithm products reach the < 10 ppm threshold (values ranging between 5.4 and 6.2 ppb). For SCIAMACHY, IMAP and WFMD have a SRA of 17.2 and 10.5 ppb, respectively

Toward accurate CO_2 and CH_4 observations from GOSAT

The column-average dry air mole fractions of atmospheric carbon dioxide and methane (X_(CO_2) and X_(CH_4)) are inferred from observations of backscattered sunlight conducted by the Greenhouse gases Observing SATellite (GOSAT). Comparing the first year of GOSAT retrievals over land with colocated ground-based observations of the Total Carbon Column Observing Network (TCCON), we find an average difference (bias) of −0.05% and −0.30% for X_(CO_2) and X_(CH_4) with a station-to-station variability (standard deviation of the bias) of 0.37% and 0.26% among the 6 considered TCCON sites. The root-mean square deviation of the bias-corrected satellite retrievals from colocated TCCON observations amounts to 2.8 ppm for X_(CO_2) and 0.015 ppm for X_(CH_4). Without any data averaging, the GOSAT records reproduce general source/sink patterns such as the seasonal cycle of X_(CO_2) suggesting the use of the satellite retrievals for constraining surface fluxes