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 ◽  
...  

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.

2020 ◽  
Vol 13 (9) ◽  
pp. 4751-4771
Author(s):  
Qiansi Tu ◽  
Frank Hase ◽  
Thomas Blumenstock ◽  
Rigel Kivi ◽  
Pauli Heikkinen ◽  
...  

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.


2018 ◽  
Vol 11 (5) ◽  
pp. 3111-3130 ◽  
Author(s):  
Lianghai Wu ◽  
Otto Hasekamp ◽  
Haili Hu ◽  
Jochen Landgraf ◽  
Andre Butz ◽  
...  

Abstract. In this study we present the retrieval of the column-averaged dry air mole fraction of carbon dioxide (XCO2) from the Orbiting Carbon Observatory-2 (OCO-2) satellite observations using the RemoTeC algorithm, previously successfully applied to retrieval of greenhouse gas concentration from the Greenhouse Gases Observing Satellite (GOSAT). The XCO2 product has been validated with collocated ground-based measurements from the Total Carbon Column Observing Network (TCCON) for almost 2 years of OCO-2 data from September 2014 to July 2016. We found that fitting an additive radiometric offset in all three spectral bands of OCO-2 significantly improved the retrieval. Based on a small correlation of the XCO2 error over land with goodness of fit, we applied an a posteriori bias correction to our OCO-2 retrievals. In overpass averaged results, XCO2 retrievals have an SD of  ∼ 1.30 ppm and a station-to-station variability of  ∼ 0.40 ppm among collocated TCCON sites. The seasonal relative accuracy (SRA) has a value of 0.52 ppm. The validation shows relatively larger difference with TCCON over high-latitude areas and some specific regions like Japan.


2008 ◽  
Vol 8 (2) ◽  
pp. 5477-5536 ◽  
Author(s):  
O. Schneising ◽  
M. Buchwitz ◽  
J. P. Burrows ◽  
H. Bovensmann ◽  
M. Reuter ◽  
...  

Abstract. Carbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases. SCIAMACHY on ENVISAT is the first satellite instrument whose measurements are sensitive to concentration changes of the two gases at all altitude levels down to the Earth's surface where the source/sink signals are largest. We have processed three years (2003–2005) of SCIAMACHY near-infrared nadir measurements to simultaneously retrieve vertical columns of CO2 (from the 1.58 μm absorption band), CH4 (1.66 μm) and oxygen (O2 A-band at 0.76 μm) using the scientific retrieval algorithm WFM-DOAS. We show that the latest version of WFM-DOAS, version 1.0, which is used for this study, has been significantly improved with respect to its accuracy compared to the previous versions while essentially maintaining its high processing speed (~1 minute per orbit, corresponding to ~6000 single measurements, and per gas on a standard PC). The greenhouse gas columns are converted to dry air column-averaged mole fractions, denoted XCO2 (in ppm) and XCH4 (in ppb), by dividing the greenhouse gas columns by simultaneously retrieved dry air columns. For XCO2 dry air columns are obtained from the retrieved O2 columns. For XCH4 dry air columns are obtained from the retrieved CO2 columns because of better cancellation of light path related errors compared to using O2 columns retrieved from the spectrally distant O2 A-band. Here we focus on a discussion of the XCO2 data set. The XCH4 data set is discussed in a separate paper (Part 2). In order to assess the quality of the retrieved XCO2 we present comparisons with Fourier Transform Spectroscopy (FTS) XCO2 measurements at two northern hemispheric mid-latitude ground stations. To assess the quality globally, we present detailed comparisons with global XCO2 fields obtained from NOAA's CO2 assimilation system CarbonTracker. For the Northern Hemisphere we find good agreement with the reference data for the CO2 seasonal cycle and the CO2 annual increase. For the Southern Hemisphere, where significantly less data are available for averaging compared to the Northern Hemisphere, the CO2 annual increase is also in good agreement with CarbonTracker but the amplitude and phase of the seasonal cycle show systematic differences up to a few ppm arising partially from the O2 normalization. The retrieved XCO2 regional pattern at monthly resolution over various regions show clear corrrelations with CarbonTracker but also significant differences. Typically the retrieved variability is about 4 ppm (1% of 380 ppm) higher but depending on time and location differences can reach or even exceed 8 ppm. Based on the error analysis and on the comparison with the reference data we conclude that the XCO2 data set can be characterized by a single measurement retrieval precision (random error) of 1–2%, a systematic low bias of about 1.5%, and by a relative accuracy of about 1–2% for monthly averages at a spatial resolution of about 7°×7°. When averaging the SCIAMACHY XCO2 over all three years we find reasonable correlation with EDGAR anthropogenic CO2 emissions for Germany, The Netherlands and Belgium indicating that regionally elevated CO2 arising from regional anthropogenic CO2 emissions can be detected from space.


2020 ◽  
Author(s):  
Matthieu Dogniaux ◽  
Cyril Crevoisier ◽  
Raymond Armante ◽  
Virginie Capelle ◽  
Thibault Delahaye ◽  
...  

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.


2008 ◽  
Vol 8 (14) ◽  
pp. 3827-3853 ◽  
Author(s):  
O. Schneising ◽  
M. Buchwitz ◽  
J. P. Burrows ◽  
H. Bovensmann ◽  
M. Reuter ◽  
...  

Abstract. Carbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases. SCIAMACHY on ENVISAT is the first satellite instrument whose measurements are sensitive to concentration changes of the two gases at all altitude levels down to the Earth's surface where the source/sink signals are largest. We have processed three years (2003–2005) of SCIAMACHY near-infrared nadir measurements to simultaneously retrieve vertical columns of CO2 (from the 1.58 μm absorption band), CH4 (1.66 μm) and oxygen (O2 A-band at 0.76 μm) using the scientific retrieval algorithm WFM-DOAS. We show that the latest version of WFM-DOAS, version 1.0, which is used for this study, has been significantly improved with respect to its accuracy compared to the previous versions while essentially maintaining its high processing speed (~1 min per orbit, corresponding to ~6000 single measurements, and per gas on a standard PC). The greenhouse gas columns are converted to dry air column-averaged mole fractions, denoted XCO2 (in ppm) and XCH4 (in ppb), by dividing the greenhouse gas columns by simultaneously retrieved dry air columns. For XCO2 dry air columns are obtained from the retrieved O2 columns. For XCH4 dry air columns are obtained from the retrieved CO2 columns because of better cancellation of light path related errors compared to using O2 columns retrieved from the spectrally distant O2 A-band. Here we focus on a discussion of the XCO2 data set. The XCH4 data set is discussed in a separate paper (Part 2). In order to assess the quality of the retrieved XCO2 we present comparisons with Fourier Transform Spectroscopy (FTS) XCO2 measurements at two northern hemispheric mid-latitude ground stations. To assess the quality globally, we present detailed comparisons with global XCO2 fields obtained from NOAA's CO2 assimilation system CarbonTracker. For the Northern Hemisphere we find good agreement with the reference data for the CO2 seasonal cycle and the CO2 annual increase. For the Southern Hemisphere, where significantly less data are available for averaging compared to the Northern Hemisphere, the CO2 annual increase is also in good agreement with CarbonTracker but the amplitude and phase of the seasonal cycle show systematic differences (up to several ppm) arising partially from the O2 normalization most likely caused by unconsidered scattering effects due to subvisual cirrus clouds. The retrieved XCO2 regional pattern at monthly resolution over various regions show clear correlations with CarbonTracker but also significant differences. Typically the retrieved variability is about 4 ppm (1% of 380 ppm) higher but depending on time and location differences can reach or even exceed 8 ppm. Based on the error analysis and on the comparison with the reference data we conclude that the XCO2 data set can be characterized by a single measurement retrieval precision (random error) of 1–2%, a systematic low bias of about 1.5%, and by a relative accuracy of about 1–2% for monthly averages at a spatial resolution of about 7°×7°. When averaging the SCIAMACHY XCO2 over all three years we find elevated CO2 over the highly populated region of western central Germany and parts of the Netherlands ("Rhine-Main area") reasonably well correlated with EDGAR anthropogenic CO2 emissions. On average the regional enhancement is 2.7 ppm including an estimated contribution of 1–1.5 ppm due to aerosol related errors and sampling.


2018 ◽  
Vol 2 (3) ◽  
pp. 38 ◽  
Author(s):  
Kalathur Santhanam ◽  
Nuzhet Ahamed

With the increasing utilization of fossil fuels in today’s technological world, the atmosphere’s concentration of greenhouse gases is increasing and needs to be controlled. In order to achieve this goal, it is imperative to have sensors that can provide data on the greenhouse gases in the environment. The recent literature contains a few publications that detail the use of new methods and materials for sensing these gases. The first part of this review is focused on the possible effects of greenhouse gases in the atmosphere, and the second part surveys the developments of sensors for greenhouse gases with coverage on carbon nano-materials and composites directed towards sensing gases like CO2, CH4, and NOx. With carbon dioxide measurements, due consideration is given to the dissolved carbon dioxide gas in water (moisture). The density functional calculations project that Pd-doped single-walled carbon nanotubes are ideal for the development of NOx sensors. The current trend is to make sensors using 3D printing or inkjet printing in order to allow for the achievement of ppb levels of sensitivity that have not been realized before. This review is to elaborate on the need for the development of greenhouse gas sensors for climatic usage by using selected examples.


2018 ◽  
Author(s):  
Lianghai Wu ◽  
Otto Hasekamp ◽  
Haili Hu ◽  
Jochen Landgraf ◽  
Andre Butz ◽  
...  

Abstract. In this study we present the retrieval of the column averaged dry air mole fraction of carbon dioxide (XCO2) from the Orbiting Carbon Observatory-2 (OCO-2) satellite observations using the RemoTeC algorithm, previously successfully applied to retrieval of greenhouse gas concentration from the Greenhouse Gases Observing Satellite (GOSAT). The XCO2 product has been validated with collocated ground based measurements from the Total Carbon Column Observing Network (TCCON) for almost 2 years of OCO-2 data from September 2014 to July 2016. We found that fitting an additive radiometric offset in all three spectral bands of OCO-2 significantly improved the retrieval. Based on a small correlation of the XCO2 error over land with fit residuals, we applied an a posteriori bias correction to our OCO-2 retrievals. In daily averaged results, XCO2 retrievals have a standard deviation ~ 1.30 ppm and a station-to-station variability of ~ 0.40 ppm among collocated TCCON sites. The seasonal relative accuracy (SRA) has a value of 0.52 ppm. The validation shows relatively larger difference with TCCON over high latitude areas and some specific regions like Japan.


2016 ◽  
Author(s):  
David Crisp ◽  
Harold R. Pollock ◽  
Robert Rosenberg ◽  
Lars Chapsky ◽  
Richard A. M. Lee ◽  
...  

Abstract. The Orbiting Carbon Observatory-2 (OCO-2) carries and points a three-channel imaging grating spectrometer designed to collect high-resolution, co-boresighted spectra of reflected sunlight within the molecular oxygen (O2) A-band at 0.765 microns and the carbon dioxide (CO2) bands at 1.61 and 2.06 microns. These measurements are calibrated and then combined into soundings that are analyzed to retrieve spatially resolved estimates of the column-averaged CO2 dry air mole fraction, XCO2. Variations of XCO2 in space and time are then analyzed in the context of the atmospheric transport to quantify surface sources and sinks of CO2. This is particularly challenging remote sensing observations because the all but the largest emission sources and natural absorbers produce only small (


2005 ◽  
Vol 5 (4) ◽  
pp. 941-962 ◽  
Author(s):  
M. Buchwitz ◽  
R. de Beek ◽  
J. P. Burrows ◽  
H. Bovensmann ◽  
T. Warneke ◽  
...  

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 on board ENVISAT are presented. Vertical columns of CH4, CO2 and oxygen (O2) have been retrieved and the (air or) O2-normalised 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. For the set of individual cloud free measurements over land the standard deviation of the difference with respect to the models is in the range ~100–200 ppbv (5–10%) for XCH4 and ~14–32 ppmv (4–9%) for XCO2. The inter-hemispheric difference of the methane mixing ratio, as determined from single day data, is in the range 30–110 ppbv and in reasonable agreement with the corresponding model data (48–71 ppbv). The weak inter-hemispheric difference of the CO2 mixing ratio can also be detected with single day data. The spatiotemporal pattern of the measured and the modelled XCO2 are in reasonable agreement. However, the amplitude of the difference between the maximum and the minimum for SCIAMACHY XCO2 is about ±20 ppmv which is about a factor of four larger than the variability of the model data which is about ±5 ppmv. More studies are needed to explain the observed differences. The XCO2 model field shows low CO2 concentrations beginning of January 2003 over a spatially extended CO2 sink region located in southern tropical/sub-tropical Africa. The SCIAMACHY data also show low CO2 mixing ratios over this area. According to the model the sink region becomes a source region about six months later and exhibits higher mixing ratios. The SCIAMACHY and the model data over this region show a similar time dependence over the period from January to October 2003. These results indicate that for the first time a regional CO2 surface source/sink region has been detected by measurements from space. The interpretation of the SCIAMACHY CO2 and CH4 measurements is difficult, e.g., because the error analysis of the currently implemented retrieval algorithm indicates that the retrieval errors are on the same order as the small greenhouse gas mixing ratio changes that are to be detected.


Sign in / Sign up

Export Citation Format

Share Document