The impact of improved aerosol priors on near-infrared measurements of carbon dioxide

Abstract. The Orbiting Carbon Observatory-2 (OCO-2) was launched in 2014 with the goal of measuring the column-averaged dry-air mole fraction of carbon dioxide (XCO2) with sufficient precision and accuracy to infer regional carbon sources and sinks. One of the primary sources of error in near-infrared measurements of XCO2 is the scattering effects of cloud and aerosol layers. In this work, we study the impact of ingesting better informed aerosol priors from the Goddard Earth Observing System Model, Version 5 (GEOS-5) into the OCO-2 ACOS V8 retrieval algorithm with the objective of reducing the error in XCO2 from real measurements. Multiple levels of both aerosol setup complexity and uncertainty on the aerosol priors were tested, ranging from a mostly unconstrained aerosol optical depth (AOD) setup to ingesting full aerosol profiles with high confidence. We find that using co-located GEOS-5 aerosol types and AODs with low uncertainty results in a small improvement in the retrieved XCO2 against the Total Carbon Column Observing Network relative to V8. In contrast, attempting to use modeled vertical information in the aerosol prior to improve the XCO2 retrieval generally gives poor results, as aerosol models struggle with the vertical placement of aerosol layers. To assess regional differences in XCO2, we compare our results to a global CO2 model validation suite. We find that the GEOS-5 setup performs better than V8 over northern Africa and central Asia, with the standard deviation of the XCO2 error reduced from 2.12 to 1.83 ppm, due to a combination of smaller prior AODs and lower prior uncertainty. In general, the use of better informed aerosol priors shows promise but may be restricted by the current accuracy of aerosol models.

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The Impact of Improved Aerosol Priors on Near-Infrared Measurements of Carbon Dioxide

10.5194/amt-2018-366 ◽

2018 ◽

Author(s):

Robert R. Nelson ◽

Christopher W. O'Dell

Keyword(s):

Carbon Dioxide ◽

Near Infrared ◽

Carbon Sources ◽

Total Carbon ◽

Primary Sources ◽

Retrieval Algorithm ◽

Sources And Sinks ◽

Earth Observing System ◽

Infrared Measurements ◽

The Impact

Abstract. The Orbiting Carbon Observatory-2 (OCO-2) was launched in 2014 with the goal of measuring the column-averaged dry-air mole fraction of carbon dioxide (XCO2) with sufficient precision and accuracy to infer regional carbon sources and sinks. One of the primary sources of error in near-infrared measurements of XCO2 is the scattering effects of cloud and aerosol layers. In this work, we study the impact of ingesting intelligent aerosol priors from the Goddard Earth Observing System Model, Version 5 (GEOS-5) into the OCO-2 ACOS V8 retrieval algorithm with the objective of reducing the error in XCO2 from real measurements. Multiple levels of both aerosol setup complexity and uncertainty on the aerosol priors were tested, ranging from a mostly unconstrained aerosol optical depth (AOD) setup to ingesting full aerosol profiles with high confidence. We find that using co-located GEOS-5 aerosol types and AODs with low uncertainty results in a small improvement in the retrieved XCO2 against the Total Carbon Column Observing Network relative to V8. In contrast, attempting to use modeled vertical information in the aerosol prior to improve the XCO2 retrieval generally gives poor results, as aerosol models struggle with the vertical placement of aerosol layers. To assess regional differences in XCO2, we compare our results to a global CO2 model validation suite. We find that the GEOS-5 setup performs better than V8 over Northern Africa and Central Asia, with the standard deviation of the XCO2 error reduced from 2.12 ppm to 1.83 ppm, due to a combination of smaller prior AODs and lower prior uncertainty. In general, the use of more intelligent aerosol priors shows promise but is currently restricted by the accuracy of aerosol models.

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The impact of improved satellite retrievals on estimates of biospheric carbon balance

Atmospheric Chemistry and Physics ◽

10.5194/acp-20-323-2020 ◽

2020 ◽

Vol 20 (1) ◽

pp. 323-331 ◽

Cited By ~ 2

Author(s):

Scot M. Miller ◽

Anna M. Michalak

Keyword(s):

Carbon Balance ◽

Near Infrared ◽

Co2 Flux ◽

Retrieval Algorithm ◽

Co2 Uptake ◽

Near Infrared Radiation ◽

Sources And Sinks ◽

Satellite Retrievals ◽

The Impact ◽

Insight Into

Abstract. The Orbiting Carbon Observatory 2 (OCO-2) is NASA's first satellite dedicated to monitoring CO2 from space and could provide novel insight into CO2 fluxes across the globe. However, one continuing challenge is the development of a robust retrieval algorithm: an estimate of atmospheric CO2 from satellite observations of near-infrared radiation. The OCO-2 retrievals have undergone multiple updates since the satellite's launch, and the retrieval algorithm is now on its ninth version. Some of these retrieval updates, particularly version 8, led to marked changes in the CO2 observations, changes of 0.5 ppm or more. In this study, we evaluate the extent to which current OCO-2 observations can constrain monthly CO2 sources and sinks from the biosphere, and we particularly focus on how this constraint has evolved with improvements to the OCO-2 retrieval algorithm. We find that improvements in the CO2 retrieval are having a potentially transformative effect on satellite-based estimates of the global biospheric carbon balance. The version 7 OCO-2 retrievals formed the basis of early inverse modeling studies using OCO-2 data; these observations are best equipped to constrain the biospheric carbon balance across only continental or hemispheric regions. By contrast, newer versions of the retrieval algorithm yield a far more detailed constraint, and we are able to constrain CO2 budgets for seven global biome-based regions, particularly during the Northern Hemisphere summer when biospheric CO2 uptake is greatest. Improvements to the OCO-2 observations have had the largest impact on glint-mode observations, and we also find the largest improvements in the terrestrial CO2 flux constraint when we include both nadir and glint data.

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The impact of improved satellite retrievals on estimates of biospheric carbon balance

10.5194/acp-2019-382 ◽

2019 ◽

Author(s):

Scot M. Miller ◽

Anna M. Michalak

Keyword(s):

Carbon Balance ◽

Near Infrared ◽

Co2 Flux ◽

Retrieval Algorithm ◽

Co2 Uptake ◽

Near Infrared Radiation ◽

Sources And Sinks ◽

Satellite Retrievals ◽

The Impact ◽

Insight Into

Abstract. The Orbiting Carbon Observatory 2 (OCO-2) is NASA's first satellite dedicated to monitoring CO2 from space and could provide novel insight into CO2 fluxes across the globe. However, one continuing challenge is the development of a robust retrieval algorithm: an estimate of atmospheric CO2 from satellite observations of near infrared radiation. The OCO-2 retrievals have undergone multiple updates since the satellite's launch, and the retrieval algorithm is now on its ninth version. Some of these retrieval updates, particularly version 8, led to marked changes in the CO2 observations, changes of 0.5 ppm or more. In this study, we evaluate the extent to which current OCO-2 observations can constrain monthly CO2 sources and sinks from the biosphere, and we particularly focus on how this constraint has evolved with improvements to the OCO-2 retrieval algorithm. We find that improvements in the CO2 retrieval are having a potentially transformative effect on satellite-based estimates of the global biospheric carbon balance. The version 7 OCO-2 retrievals formed the basis of early inverse modeling studies using OCO-2 data; these observations are best-equipped to constrain the biospheric carbon balance across only continental or hemispheric regions. By contrast, newer versions of the retrieval algorithm yield a far more detailed constraint, and we are able to constrain CO2 budgets for seven global biome-based regions, particularly during the Northern Hemisphere summer when biospheric CO2 uptake is greatest. Improvements to the OCO-2 observations have had the largest impact on glint mode observations, and we also find the largest improvements in the terrestrial CO2 flux constraint when we include both nadir and glint data.

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The potential of clear-sky carbon dioxide satellite retrievals

Atmospheric Measurement Techniques ◽

10.5194/amt-9-1671-2016 ◽

2016 ◽

Vol 9 (4) ◽

pp. 1671-1684 ◽

Cited By ~ 8

Author(s):

Robert R. Nelson ◽

Christopher W. O'Dell ◽

Thomas E. Taylor ◽

Lukas Mandrake ◽

Mike Smyth

Keyword(s):

Carbon Dioxide ◽

Near Infrared ◽

Total Carbon ◽

Retrieval Algorithm ◽

Infrared Observations ◽

Clear Sky ◽

Aerosol Scattering ◽

Scattering Effects ◽

Thin Cloud ◽

Mean Square Errors

Abstract. Since the launch of the Greenhouse Gases Observing Satellite (GOSAT) in 2009, retrieval algorithms designed to infer the column-averaged dry-air mole fraction of carbon dioxide (XCO2) from hyperspectral near-infrared observations of reflected sunlight have been greatly improved. They now generally include the scattering effects of clouds and aerosols, as early work found that absorption-only retrievals, which neglected these effects, often incurred unacceptably large errors, even for scenes with optically thin cloud or aerosol layers. However, these “full-physics” retrievals tend to be computationally expensive and may incur biases from trying to deduce the properties of clouds and aerosols when there are none present. Additionally, algorithms are now available that can quickly and effectively identify and remove most scenes in which cloud or aerosol scattering plays a significant role. In this work, we test the hypothesis that non-scattering, or “clear-sky”, retrievals may perform as well as full-physics retrievals for sufficiently clear scenes. Clear-sky retrievals could potentially avoid errors and biases brought about by trying to infer properties of clouds and aerosols when none are present. Clear-sky retrievals are also desirable because they are orders of magnitude faster than full-physics retrievals. Here we use a simplified version of the Atmospheric Carbon Observations from Space (ACOS) XCO2 retrieval algorithm that does not include the scattering and absorption effects of clouds or aerosols. It was found that for simulated Orbiting Carbon Observatory-2 (OCO-2) measurements, the clear-sky retrieval had errors comparable to those of the full-physics retrieval. For real GOSAT data, the clear-sky retrieval had errors 0–20 % larger than the full-physics retrieval over land and errors roughly 20–35 % larger over ocean, depending on filtration level. In general, the clear-sky retrieval had XCO2 root-mean-square errors (RMSEs) of less than 2.0 ppm, relative to Total Carbon Column Observing Network (TCCON) measurements and a suite of CO2 models, when adequately filtered through the use of a custom genetic algorithm filtering system. These results imply that non-scattering XCO2 retrievals are potentially more useful than previous literature suggests, as the filtering methods we employ are able to remove measurements in which scattering can cause significant errors. Additionally, the computational benefits of non-scattering retrievals means they may be useful for certain applications that require large amounts of data but have less stringent error requirements.

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Carbon dioxide retrieval of Argus 1000 space data by using GENSPECT line-by-line radiative transfer model

Environment and Natural Resources Research ◽

10.5539/enrr.v9n3p77 ◽

2019 ◽

Vol 9 (3) ◽

pp. 77

Author(s):

R. K. Jagpal ◽

R. Siddiqui ◽

S. M. Abrarov ◽

B. M. Quine

Keyword(s):

Carbon Dioxide ◽

Radiative Transfer ◽

Greenhouse Effect ◽

Near Infrared ◽

Trace Gases ◽

Radiative Transfer Model ◽

Transfer Model ◽

Major Contributor ◽

Sources And Sinks ◽

Space Data

The micro-spectrometer Argus 1000 being in space continuously monitors the sources and sinks of the trace gases. It is commonly believed that among other gases CO_2 is the major contributor causing the greenhouse effect. Argus 1000 along its orbit gathers the valuable spectral data that can be analyzed and retrieved. In this paper we present the retrieval of CO_2 gas in the near infrared window 1580 to 1620 nm by using line-by-line code GENSPECT. The retrieved Argus 1000 space data taken over British Columbia on May 31, 2010 indicates an enhancement of CO_2 by about 30%.

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Atmospheric methane and carbon dioxide from SCIAMACHY satellite data: initial comparison with chemistry and transport models

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-4-7217-2004 ◽

2004 ◽

Vol 4 (6) ◽

pp. 7217-7279 ◽

Cited By ~ 4

Author(s):

M. Buchwitz ◽

R. de Beek ◽

J. P. Burrows ◽

H. Bovensmann ◽

T. Warneke ◽

...

Keyword(s):

Carbon Dioxide ◽

Reasonable Agreement ◽

Near Infrared ◽

Weighting Function ◽

Lower Surface ◽

Retrieval Algorithm ◽

Atmospheric Methane ◽

Mixing Ratios ◽

Data Products ◽

Carbon Dioxide Co2

Abstract. The remote sensing of the atmospheric greenhouse gases methane (CH4) and carbon dioxide (CO2) in the troposphere from instrumentation aboard satellites is a new area of research. In this manuscript, results obtained from observations of the up-welling radiation in the near-infrared by SCIAMACHY (Scanning Imaging Absorption spectroMeter for Atmospheric CHartographY), which flies on board ENVISAT, are presented. Vertical columns of CH4, CO2 and oxygen (O2) have been retrieved and the (air or) O2-normalized CH4 and CO2 column amounts, the dry air column averaged mixing ratios XCH4 and XCO2 derived. In this manuscript the first results, obtained by using the version 0.4 of the Weighting Function Modified (WFM) DOAS retrieval algorithm applied to SCIAMACHY data, are described and compared with global models. This is an important step in assessing the quality and information content of the data products derived from SCIAMACHY observations. This study investigates the behaviour of CO2 and CH4 in the period from January to October 2003. The SCIAMACHY greenhouse gas column amounts and their mixing ratios for cloud free scenes over land are shown to be in reasonable agreement with models. Over the ocean, as a result of the lower surface spectral reflectance and resultant low signal to noise with the exception of sun glint conditions, the accuracy of the individual data products is poorer. The measured methane column amounts agree with the model columns within a few percent. The inter-hemispheric difference of the methane mixing ratios, determined from single day cloud free measurements over land, is in the range 30–110 ppbv and in reasonable agreement with the corresponding model data (48–71 ppbv). For the set of individual measurements the standard deviations of the difference with respect to the models are in the range ~100–200 ppbv (5–10%) and ±14.4 ppmv (3.9%) for XCH

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Combinatorial use of environmental stresses and genetic engineering to increase ethanol titres in cyanobacteria

Biotechnology for Biofuels ◽

10.1186/s13068-021-02091-w ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Fraser Andrews ◽

Matthew Faulkner ◽

Helen S. Toogood ◽

Nigel S. Scrutton

Keyword(s):

Carbon Dioxide ◽

Ethanol Production ◽

Carbon Fixation ◽

Carbon Sources ◽

Environmental Stresses ◽

Pathway Engineering ◽

Bioethanol Production ◽

Biological Fixation ◽

Pcc 7942 ◽

The Impact

AbstractCurrent industrial bioethanol production by yeast through fermentation generates carbon dioxide. Carbon neutral bioethanol production by cyanobacteria uses biological fixation (photosynthesis) of carbon dioxide or other waste inorganic carbon sources, whilst being sustainable and renewable. The first ethanologenic cyanobacterial process was developed over two decades ago using Synechococcus elongatus PCC 7942, by incorporating the recombinant pdc and adh genes from Zymomonas mobilis. Further engineering has increased bioethanol titres 24-fold, yet current levels are far below what is required for industrial application. At the heart of the problem is that the rate of carbon fixation cannot be drastically accelerated and carbon partitioning towards bioethanol production impacts on cell fitness. Key progress has been achieved by increasing the precursor pyruvate levels intracellularly, upregulating synthetic genes and knocking out pathways competing for pyruvate. Studies have shown that cyanobacteria accumulate high proportions of carbon reserves that are mobilised under specific environmental stresses or through pathway engineering to increase ethanol production. When used in conjunction with specific genetic knockouts, they supply significantly more carbon for ethanol production. This review will discuss the progress in generating ethanologenic cyanobacteria through chassis engineering, and exploring the impact of environmental stresses on increasing carbon flux towards ethanol production.

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Study on effect CO2 diluent on fuel cоmbustion in methane-oxygen combustion chambers

Vestnik IGEU ◽

10.17588/2072-2672.2021.2.014-022 ◽

2021 ◽

pp. 14-22

Author(s):

I.I. Komarov ◽

D.M. Kharlamova ◽

A.N. Vegera ◽

V.Y. Naumov

Keyword(s):

Carbon Dioxide ◽

Combustion Chamber ◽

Combustion Process ◽

Methane Combustion ◽

Flame Stabilization ◽

Total Carbon ◽

Working Fluid ◽

Combustion Mechanism ◽

Combustion Chambers ◽

The Impact

Studying closed gas turbine cycles on supercritical carbon dioxide is currently a promising issue in the development of power energy sector in terms of increasing energy efficiency and minimizing greenhouse gas emissions into the atmosphere. Combustion of methane with oxygen in the combustion chamber occurs not in the nitrogen environment, but in the environment of carbon dioxide, that is the working fluid of the cycle, which is an inhibitor of chemical reactions. A large mass content of such a diluent of the reaction mixture in the volume of the chamber leads to the risks of significant chemical underburning, efficiency decrease of the combustion chamber and the cycle as a whole. The aim of the research is to study the kinetic parameters of the combustion of methane with oxygen in a supercritical CO2 diluent medium to ensure reliable and stable combustion of fuel by assessing the degree of the inhibitory effect of CO2 and determining its permissible amount in the active combustion zone of the combustion chamber. The research method is a numerical simulation of turbulent-kinetic processes of methane combustion in the combustion chamber using the reduced methane combustion mechanism. Ansys Fluent software package has been used. The authers have studied the impact of CO2 diluent on fuel cоmbustion in methane-oxygen combustion chambers. It is found that the combustor flame stabilization takes place if the content of СО2 diluent supplied to the mixture with oxidizer is 0,46–0,5 of mass fraction; additional СО2 diluent forms local low temperature zones which slow down the combustion process. When this happens, adding cooling СО2 into the flame stabilization zone should be eliminated. The study has found that no more than 20 % of the total carbon dioxide content should be supplied to the combustion chamber; to stabilize the flame and reduce its length, it is necessary to install blades to swirl the fuel and oxidizer mixed with CO2 at the inlet of the combustion chamber; CO2 supply for cooling should be carried out not less than 130 mm away from the burner mouth.

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Spatio-Temporal Consistency Evaluation of XCO2 Retrievals from GOSAT and OCO-2 Based on TCCON and Model Data for Joint Utilization in Carbon Cycle Research

Atmosphere ◽

10.3390/atmos10070354 ◽

2019 ◽

Vol 10 (7) ◽

pp. 354 ◽

Cited By ~ 5

Author(s):

Yawen Kong ◽

Baozhang Chen ◽

Simon Measho

Keyword(s):

Carbon Cycle ◽

Mole Fraction ◽

Transport Model ◽

Total Carbon ◽

Temporal Consistency ◽

Model Data ◽

Sources And Sinks ◽

Spatio Temporal ◽

The Impact

The global carbon cycle research requires precise and sufficient observations of the column-averaged dry-air mole fraction of CO 2 (XCO 2 ) in addition to conventional surface mole fraction observations. In addition, assessing the consistency of multi-satellite data are crucial for joint utilization to better infer information about CO 2 sources and sinks. In this work, we evaluate the consistency of long-term XCO 2 retrievals from the Greenhouse Gases Observing Satellite (GOSAT), Orbiting Carbon Observatory 2 (OCO-2) in comparison with Total Carbon Column Observing Network (TCCON) and the 3D model of CO 2 mole fractions data from CarbonTracker 2017 (CT2017). We create a consistent joint dataset and compare it with the long-term model data to assess their abilities to characterize the carbon cycle climate. The results show that, although slight increasing differences are found between the GOSAT and TCCON XCO 2 in the northern temperate latitudes, the GOSAT and OCO-2 XCO 2 retrievals agree well in general, with a mean bias ± standard deviation of differences of 0.21 ± 1.3 ppm. The differences are almost within ±2 ppm and are independent of time, indicating that they are well calibrated. The differences between OCO-2 and CT2017 XCO 2 are much larger than those between GOSAT and CT XCO 2 , which can be attributed to the significantly different spatial representatives of OCO-2 and the CT-transport model 5 (TM5). The time series of the combined OCO-2/GOSAT dataset and the modeled XCO 2 agree well, and both can characterize significantly increasing atmospheric CO 2 under the impact of a large El Niño during 2015 and 2016. The trend calculated from the dataset using the seasonal Kendall (S-K) method indicates that atmospheric CO 2 is increasing by 2–2.6 ppm per year.

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Retrieval of Stable Water Vapour Isotopologues from the TROPOMI Instrument

10.5194/egusphere-egu21-9864 ◽

2021 ◽

Author(s):

Tim Trent ◽

Hartmut Boesch ◽

Peter Somkuti ◽

Mathhias Schneider ◽

Farahnaz Khosrawi ◽

...

Keyword(s):

Water Vapour ◽

In Situ Measurements ◽

Climate Feedback ◽

Retrieval Algorithm ◽

Unique Contribution ◽

Water Vapour Content ◽

Infrared Measurements ◽

Water Isotopologues ◽

The Impact

Atmospheric moisture is a crucial factor for the redistribution of heat in the atmosphere, with a strong coupling between atmospheric circulation and moisture pathways responsible most climate feedback mechanisms. Conventional satellite and in situ measurements provide information on water vapour content and vertical distribution; however, observations of water isotopologues make a unique contribution to a better understanding of this coupling.In recent years, observations of water vapour isotopologue from satellites have become available from nadir thermal infrared measurements (TES, AIRS, IASI) which are sensitive to the free troposphere and from shortwave-infrared (SWIR) sensors (GOSAT, SCIAMACHY) that provide column-averaged concentrations including sensitivity to the boundary layer. The TROPOMI instrument on-board Sentinel 5P (S5p) measures SWIR radiance spectra that allow retrieval of water isotopologue columns but with much improved spatial and temporal coverage compared to other SWIR sensors promising a step-change for scientific and operational applications.Here we present the retrieval algorithm development for stable water isotopologues from TROPOMI as part of the ESA S5p Innovation programme.&#160; We also discuss the validation of these types of satellite products with fiducial in situ measurements, and challenges compared with other satellite measurements. Finally, we outline the roadmap for assessing the impact of TROPOMI data against state-of-the-art isotope enabled models.

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