scholarly journals The Adaptable 4A Inversion (5AI): Description and first XCO<sub>2</sub> retrievals from OCO-2 observations

2020 ◽  
Author(s):  
Matthieu Dogniaux ◽  
Cyril Crevoisier ◽  
Raymond Armante ◽  
Virginie Capelle ◽  
Thibault Delahaye ◽  
...  
Keyword(s):  
Greenhouse Gas ◽  
Optimal Estimation ◽  
Total Carbon ◽  
Sources And Sinks ◽  
Dry Air ◽  
Global Challenge ◽  
Spectral Residual ◽  
Spectroscopic Information ◽  
Global Coverage ◽  
Residual Correction

Abstract. A better understanding of greenhouse gas surface sources and sinks is required in order to address the global challenge of climate change. Spaceborne remote estimations of greenhouse gas atmospheric concentrations can offer the global coverage that is necessary to improve the constraint on their fluxes, thus enabling a better monitoring of anthropogenic emissions. In this work, we introduce the Adaptable 4A Inversion (5AI) inverse scheme that aims to retrieve geophysical parameters from any remote sensing observation. The algorithm is based on Bayesian optimal estimation relying on the Operational version of the Automatized Atmospheric Absorption Atlas (4A/OP) radiative transfer forward model along with the Gestion et Étude des Informations Spectroscopiques Atmosphériques: Management and Study of Atmospheric Spectroscopic Information (GEISA) spectroscopic database. Here, the 5AI scheme is applied to retrieve the column-averaged dry-air mole fraction of carbon dioxide (XCO2) from measurements performed by the Orbiting Carbon Observatory-2 (OCO-2) mission, and uses an empirically corrected absorption continuum in the O2 A-band. For airmasses below 3.0, XCO2 retrievals successfully capture the latitudinal variations of CO2, as well as its seasonal cycle and long-term increasing trend. Comparison with ground-based observations from the Total Carbon Column Observing Network (TCCON) yields a difference of 1.33 ± 1.29 ppm, which is similar to the standard deviation of the Atmospheric CO2 Observations from Space (ACOS) official products. We show that the systematic differences between 5AI and ACOS results can be fully removed by adding an average calculated – observed spectral residual correction to OCO-2 measurements, thus underlying the critical sensitivity of retrieval results to forward modelling. These comparisons show the reliability of 5AI as a Bayesian optimal estimation implementation that is easily adaptable to any instrument designed to retrieve column-averaged dry-air mole fractions of greenhouse gases.

scholarly journals The Adaptable 4A Inversion (5AI): description and first <i>X</i><sub>CO<sub>2</sub></sub> retrievals from Orbiting Carbon Observatory-2 (OCO-2) observations

2021 ◽  
Vol 14 (6) ◽  
pp. 4689-4706
Author(s):  
Matthieu Dogniaux ◽  
Cyril Crevoisier ◽  
Raymond Armante ◽  
Virginie Capelle ◽  
Thibault Delahaye ◽  
...  
Keyword(s):  
Greenhouse Gas ◽  
Optimal Estimation ◽  
Estimation Algorithm ◽  
Total Carbon ◽  
Computational Time ◽  
Dry Air ◽  
Global Challenge ◽  
Spectroscopic Information ◽  
Residual Correction ◽  
The Impact

Abstract. A better understanding of greenhouse gas surface sources and sinks is required in order to address the global challenge of climate change. Space-borne remote estimations of greenhouse gas atmospheric concentrations can offer the global coverage that is necessary to improve the constraint on their fluxes, thus enabling a better monitoring of anthropogenic emissions. In this work, we introduce the Adaptable 4A Inversion (5AI) inverse scheme that aims to retrieve geophysical parameters from any remote sensing observation. The algorithm is based on the Optimal Estimation algorithm, relying on the Operational version of the Automatized Atmospheric Absorption Atlas (4A/OP) radiative transfer forward model along with the Gestion et Étude des Informations Spectroscopiques Atmosphériques: Management and Study of Atmospheric Spectroscopic Information (GEISA) spectroscopic database. Here, the 5AI scheme is applied to retrieve the column-averaged dry air mole fraction of carbon dioxide (XCO2) from a sample of measurements performed by the Orbiting Carbon Observatory-2 (OCO-2) mission. Those have been selected as a compromise between coverage and the lowest aerosol content possible, so that the impact of scattering particles can be neglected, for computational time purposes. For air masses below 3.0, 5AI XCO2 retrievals successfully capture the latitudinal variations of CO2 and its seasonal cycle and long-term increasing trend. Comparison with ground-based observations from the Total Carbon Column Observing Network (TCCON) yields a bias of 1.30±1.32 ppm (parts per million), which is comparable to the standard deviation of the Atmospheric CO2 Observations from Space (ACOS) official products over the same set of soundings. These nonscattering 5AI results, however, exhibit an average difference of about 3 ppm compared to ACOS results. We show that neglecting scattering particles for computational time purposes can explain most of this difference that can be fully corrected by adding to OCO-2 measurements an average calculated–observed spectral residual correction, which encompasses all the inverse setup and forward differences between 5AI and ACOS. These comparisons show the reliability of 5AI as an optimal estimation implementation that is easily adaptable to any instrument designed to retrieve column-averaged dry air mole fractions of greenhouse gases.

scholarly journals Intercomparison of atmospheric CO<sub>2</sub> and CH<sub>4</sub> abundances on regional scales in boreal areas using Copernicus Atmosphere Monitoring Service (CAMS) analysis, COllaborative Carbon Column Observing Network (COCCON) spectrometers, and Sentinel-5 Precursor satellite observations

2020 ◽  
Vol 13 (9) ◽  
pp. 4751-4771
Author(s):  
Qiansi Tu ◽  
Frank Hase ◽  
Thomas Blumenstock ◽  
Rigel Kivi ◽  
Pauli Heikkinen ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Greenhouse Gas ◽  
Gas Sensors ◽  
Reasonable Agreement ◽  
Satellite Observations ◽  
Model Data ◽  
Sources And Sinks ◽  
Dry Air ◽  
Portable Spectrometers ◽  
Monitoring Service

Abstract. We compare the atmospheric column-averaged dry-air mole fractions of carbon dioxide (XCO2) and methane (XCH4) measured with a pair of COllaborative Carbon Column Observing Network (COCCON) spectrometers at Kiruna and Sodankylä (boreal areas). We compare model data provided by the Copernicus Atmosphere Monitoring Service (CAMS) between 2017 and 2019 with XCH4 data from the recently launched Sentinel-5 Precursor (S5P) satellite between 2018 and 2019. In addition, measured and modeled gradients of XCO2 and XCH4 (ΔXCO2 and ΔXCH4) on regional scales are investigated. Both sites show a similar and very good correlation between COCCON retrievals and the modeled CAMS XCO2 data, while CAMS data are biased high with respect to COCCON by 3.72 ppm (±1.80 ppm) in Kiruna and 3.46 ppm (±1.73 ppm) in Sodankylä on average. For XCH4, CAMS values are higher than the COCCON observations by 0.33 ppb (±11.93 ppb) in Kiruna and 7.39 ppb (±10.92 ppb) in Sodankylä. In contrast, the S5P satellite generally measures lower atmospheric XCH4 than the COCCON spectrometers, with a mean difference of 9.69 ppb (±20.51 ppb) in Kiruna and 3.36 ppb (±17.05 ppb) in Sodankylä. We compare the gradients of XCO2 and XCH4 (ΔXCO2 and ΔXCH4) between Kiruna and Sodankylä derived from CAMS analysis and COCCON and S5P measurements to study the capability of detecting sources and sinks on regional scales. The correlations in ΔXCO2 and ΔXCH4 between the different datasets are generally smaller than the correlations in XCO2 and XCH4 between the datasets at either site. The ΔXCO2 values predicted by CAMS are generally higher than those observed with COCCON with a slope of 0.51. The ΔXCH4 values predicted by CAMS are mostly higher than those observed with COCCON with a slope of 0.65, covering a larger dataset than the comparison between S5P and COCCON. When comparing CAMS ΔXCH4 with COCCON ΔXCH4 only in S5P overpass days (slope = 0.53), the correlation is close to that between S5P and COCCON (slope = 0.51). CAMS, COCCON, and S5P predict gradients in reasonable agreement. However, the small number of observations coinciding with S5P limits our ability to verify the performance of this spaceborne sensor. We detect no significant impact of ground albedo and viewing zenith angle on the S5P results. Both sites show similar situations with the average ratios of XCH4 (S5P/COCCON) of 0.9949±0.0118 in Kiruna and 0.9953±0.0089 in Sodankylä. Overall, the results indicate that the COCCON instruments have the capability of measuring greenhouse gas (GHG) gradients on regional scales, and observations performed with the portable spectrometers can contribute to inferring sources and sinks and to validating spaceborne greenhouse gas sensors. To our knowledge, this is the first published study using COCCON spectrometers for the validation of XCH4 measurements collected by S5P.

scholarly journals Atmospheric CO<sub>2</sub> and CH<sub>4</sub> abundances on regional scales in boreal areas using CAMS reanalysis, COCCON spectrometers and Sentinel-5 Precursor satellite observations

2020 ◽  
Author(s):  
Qiansi Tu ◽  
Frank Hase ◽  
Thomas Blumenstock ◽  
Rigel Kivi ◽  
Pauli Heikkinen ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Greenhouse Gas ◽  
Gas Sensors ◽  
Reasonable Agreement ◽  
Satellite Observations ◽  
Model Data ◽  
Sources And Sinks ◽  
Dry Air ◽  
Portable Spectrometers ◽  
Monitoring Service

Abstract. We compare the atmospheric column-averaged dry-air mole fractions of carbon dioxide (XCO2) and methane (XCH4) measured with a pair of COCCON spectrometers at Kiruna and Sodankylä sites in boreal areas with model data provided by the Copernicus Atmosphere Monitoring Service (CAMS) and with XCH4 from the recently launched Sentinel-5 Precursor (S5P) satellite. Both sites show a similar and very good correlation between COCCON retrievals and the modeled CAMS XCO2 and XCH4 data. CAMS data are biased high with respect to COCCON in both XCO2 and XCH4, while the S5P satellite generally measures lower atmospheric XCH4 than the COCCON spectrometers. The gradients of XCO2 and XCH4 (ΔXCO2 and ΔXCH4) between Kiruna and Sodankylä derived from CAMS reanalysis and COCCON and S5P measurements are investigated to study the capability of detecting sources and sinks on regional scales. CAMS, COCCON and S5P predict gradients in reasonable agreement. However, the small number of observations coinciding with S5P limits our ability to verify the performance of this sensor. Overall, the results indicate that the COCCON instrument has the capability of measuring greenhouse gas (GHG) gradients on regional scales and observations performed with the portable spectrometers can contribute to inferring sources and sinks and to validating space borne greenhouse gas sensors.

scholarly journals The Greenhouse Gas Climate Change Initiative (GHG-CCI): comparative validation of GHG-CCI SCIAMACHY/ENVISAT and TANSO-FTS/GOSAT CO<sub>2</sub> and CH<sub>4</sub> retrieval algorithm products with measurements from the TCCON network

2013 ◽  
Vol 6 (5) ◽  
pp. 8679-8741 ◽  
Author(s):  
B. Dils ◽  
M. Buchwitz ◽  
M. Reuter ◽  
O. Schneising ◽  
H. Boesch ◽  
...  
Keyword(s):  
Climate Change ◽  
Greenhouse Gas ◽  
Weighting Function ◽  
Optimal Estimation ◽  
Total Carbon ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Data Sets ◽  
Change Initiative ◽  
The University

Abstract. Column-averaged dry-air mole fractions of carbon dioxide and methane have been retrieved from spectra acquired by the TANSO-FTS and SCIAMACHY instruments on board GOSAT and ENVISAT using a range of European retrieval algorithms. These retrievals have been compared with data from ground-based high-resolution Fourier Transform Spectrometers (FTS) 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" (GHG). For CO2, all algorithms reach the precision requirements for inverse modelling (< 8 ppb), 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 CH4, the precision for both SCIAMACHY products (50.2 ppb for IMAP and 76.4 ppb for WFMD) fail to meet the < 34 ppb threshold, 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 ppb and 10.5 ppb respectively.

scholarly journals Using the Mechanisms of the Paris Climate Agreement for Conservation and Reforestation in the Russian Federation .

Federalism ◽  
2020 ◽  
pp. 141-156
Author(s):  
A. V. Stetsenko ◽  
V. B. Uvarov
Keyword(s):  
Greenhouse Gas ◽  
Absorption Capacity ◽  
Domestic Investment ◽  
Global Challenge ◽  
Russian Economy ◽  
Or Groups ◽  
Russian Forests ◽  
The Russian Federation ◽  
Paris Climate Agreement ◽  
Climate Neutrality

The problem of climate change is a global challenge of the XXI century for all mankind. However, despite the adoption of the Paris climate agreement, which is designed to synchronize the actions of various countries, individual countries or groups of countries are taking the path of obtaining unilateral preferences under the pretext of fulfilling the obligations stipulated in the agreement. The article analyzes the challenges and risks that Russia may face in the absence of its own greenhouse gas regulation systems against the background of the declared and implemented in a number of countries policy of achieving zero greenhouse gas emissions. Ways to fully utilize the potential absorption capacity of Russian forests and other ecosystems in relation to the goals of the Paris climate agreement are considered. We are talking about potential effects for the Russian economy in the form of domestic investment in forest projects to absorb CO2, while increasing the competitiveness of Russian export products in the context of the introduction of protectionist measures by individual countries under the pretext of fighting for “climate neutrality”.

scholarly journals Satellite and Ground-based Measurements of X<sub>CO<sub>2</sub></sub> in a Remote Semi-Arid Region of Australia

2019 ◽  
Author(s):  
Voltaire A. Velazco ◽  
Nicholas M. Deutscher ◽  
Isamu Morino ◽  
Osamu Uchino ◽  
Beata Bukosa ◽  
...  
Keyword(s):  
Greenhouse Gases ◽  
Calibration Curve ◽  
Arid Region ◽  
Total Carbon ◽  
Random Errors ◽  
Clam Shell ◽  
Dry Air ◽  
Semi Arid Region ◽  
The University ◽  
Semi Arid

Abstract. In this study, we present ground-based measurements of column-averaged dry-air mole fractions (DMFs) of CO2 (or XCO2) from an EM27/SUN portable spectrometer, equipped with an automated clam shell cover, taken in a semi-arid region of Australia. 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 calibration factor of 0.9954 relative to TCCON. Although we found a slight drift of .0125 % per month in the calibration curve of the EM27/SUN vs TCCON XCO2, the alignment of the EM27/SUN proved stable enough for a campaign, keeping the retrieved Xair values, a 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 improve the estimated bias between the EM27/SUN and GOSAT. The dataset from the Alice Springs measurements is accessible at http://dx.doi.org/10.4225/48/5b21f16ce69bc (Velazco et al., 2018).

scholarly journals Freight-related greenhouse gas emissions in the supply of spectacle and contact lenses

2021 ◽  
Vol 80 (1) ◽  
Author(s):  
Rayishnee Pillay ◽  
Nishanee Rampersad ◽  
Rekha Hansraj
Keyword(s):  
Climate Change ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Contact Lenses ◽  
Service Providers ◽  
Economic Sectors ◽  
Gas Emissions ◽  
Global Challenge ◽  
Related Distribution ◽  
Courier Service

Background: Climate change is a global challenge requiring mitigation from all economic sectors. Although the consequences of climate change are well documented, there are limited studies regarding greenhouse gas emissions generated by the optometric industry.Aim: This study explored the greenhouse gas emissions created from the freight-related distribution of spectacle and contact lenses to South Africa (SA) in 2019.Setting: Spectacle and contact lens distributors in SA and an optometric courier service in KwaZulu-Natal.Methods: Data from a survey completed by lens suppliers and a courier service provider in SA were used in a standardised emissions calculations tool.Results: The results indicate significant greenhouse gas emissions generated from the distribution of lenses in SA, which is of concern for climate change alleviation goals.Conclusion: It is recommended that practitioners in the optometric industry, and other healthcare service providers, calculate their emissions data, modify practices to support climate change mitigation and be cognisant of the effect of their practices on the environment.

scholarly journals The 2015–2016 carbon cycle as seen from OCO-2 and the global in situ network

2019 ◽  
Vol 19 (15) ◽  
pp. 9797-9831 ◽  
Author(s):  
Sean Crowell ◽  
David Baker ◽  
Andrew Schuh ◽  
Sourish Basu ◽  
Andrew R. Jacobson ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Carbon Sink ◽  
Total Carbon ◽  
Transport Models ◽  
New Information ◽  
Global Coverage ◽  
The Difference ◽  
The Tropics

Abstract. The Orbiting Carbon Observatory-2 has been on orbit since 2014, and its global coverage holds the potential to reveal new information about the carbon cycle through the use of top-down atmospheric inversion methods combined with column average CO2 retrievals. We employ a large ensemble of atmospheric inversions utilizing different transport models, data assimilation techniques, and prior flux distributions in order to quantify the satellite-informed fluxes from OCO-2 Version 7r land observations and their uncertainties at continental scales. Additionally, we use in situ measurements to provide a baseline against which to compare the satellite-constrained results. We find that within the ensemble spread, in situ observations, and satellite retrievals constrain a similar global total carbon sink of 3.7±0.5 PgC yr−1, and 1.5±0.6 PgC yr−1 for global land, for the 2015–2016 annual mean. This agreement breaks down in smaller regions, and we discuss the differences between the experiments. Of particular interest is the difference between the different assimilation constraints in the tropics, with the largest differences occurring in tropical Africa, which could be an indication of the global perturbation from the 2015–2016 El Niño. Evaluation of posterior concentrations using TCCON and aircraft observations gives some limited insight into the quality of the different assimilation constraints, but the lack of such data in the tropics inhibits our ability to make strong conclusions there.

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