In order to better manage anthropogenic CO2 emissions, improved methods of quantifying emissions are needed at all spatial scales from the national level down to the facility level. Although the ...Orbiting Carbon Observatory 2 (OCO‐2) satellite was not designed for monitoring power plant emissions, we show that in some cases, CO2 observations from OCO‐2 can be used to quantify daily CO2 emissions from individual middle‐ to large‐sized coal power plants by fitting the data to plume model simulations. Emission estimates for U.S. power plants are within 1–17% of reported daily emission values, enabling application of the approach to international sites that lack detailed emission information. This affirms that a constellation of future CO2 imaging satellites, optimized for point sources, could monitor emissions from individual power plants to support the implementation of climate policies.
Plain Language Summary
Burning coal for electricity generation accounts for more than 40% of humanity's current global CO2 emissions. To better manage CO2 emissions, improved methods of quantifying emissions are needed at all spatial scales. Although the Orbiting Carbon Observatory 2 (OCO‐2) satellite was not designed for monitoring power plant emissions, we show that in select cases, CO2 observations from OCO‐2 can be used to quantify daily CO2 emissions from individual middle‐ to large‐sized coal power plants by fitting the data to a simple model. Demonstrating the method on U.S. power plants with reliable reported emission data enabled application of the approach to international sites that have less or lower quality information available on emissions. Space agencies around the world are currently exploring how to design satellite missions to help address climate change and support Monitoring, Reporting and Verification (MRV) of CO2 emissions for climate agreements. This work affirms that a constellation of CO2 imaging satellites, with a design optimized for point sources, could monitor CO2 emissions from individual fossil fuel burning power plants to support that objective.
Key Points
The combustion of coal for electricity generation accounts for more than 40% of global anthropogenic CO2 emissions
Orbiting Carbon Observatory 2 observations can be used to quantify CO2 emissions from individual coal power plants, in selected cases
This work suggests that a future constellation of CO2 imaging satellites could monitor fossil fuel power plant CO2 emissions to support climate policy
The 2015-2016 El Niño led to historically high temperatures and low precipitation over the tropics, while the growth rate of atmospheric carbon dioxide (CO
) was the largest on record. Here we ...quantify the response of tropical net biosphere exchange, gross primary production, biomass burning, and respiration to these climate anomalies by assimilating column CO
, solar-induced chlorophyll fluorescence, and carbon monoxide observations from multiple satellites. Relative to the 2011 La Niña, the pantropical biosphere released 2.5 ± 0.34 gigatons more carbon into the atmosphere in 2015, consisting of approximately even contributions from three tropical continents but dominated by diverse carbon exchange processes. The heterogeneity of the carbon-exchange processes indicated here challenges previous studies that suggested that a single dominant process determines carbon cycle interannual variability.
The TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel 5 Precursor (S5-P) satellite provides methane (CH4) measurements with high accuracy and exceptional temporal and spatial ...resolution and sampling. TROPOMI CH4 measurements are highly valuable to constrain emissions inventories and for trend analysis, with strict requirements on the data quality. This study describes the improvements that we have implemented to retrieve CH4 from TROPOMI using the RemoTeC full-physics algorithm. The updated retrieval algorithm features a constant regularization scheme of the inversion that stabilizes the retrieval and yields less scatter in the data and includes a higher resolution surface altitude database. We have tested the impact of three state-of-the-art molecular spectroscopic databases (HITRAN 2008, HITRAN 2016 and Scientific Exploitation of Operational Missions – Improved Atmospheric Spectroscopy Databases SEOM-IAS) and found that SEOM-IAS provides the best fitting results. The most relevant update in the TROPOMI XCH4 data product is the implementation of an a posteriori correction fully independent of any reference data that is more accurate and corrects for the underestimation at low surface albedo scenes and the overestimation at high surface albedo scenes. After applying the correction, the albedo dependence is removed to a large extent in the TROPOMI versus satellite (Greenhouse gases Observing SATellite – GOSAT) and TROPOMI versus ground-based observations (Total Carbon Column Observing Network – TCCON) comparison, which is an independent verification of the correction scheme. We validate 2 years of TROPOMI CH4 data that show the good agreement of the updated TROPOMI CH4 with TCCON (−3.4 ± 5.6 ppb) and GOSAT (−10.3 ± 16.8 ppb) (mean bias and standard deviation). Low- and high-albedo scenes as well as snow-covered scenes are the most challenging for the CH4 retrieval algorithm, and although the a posteriori correction accounts for most of the bias, there is a need to further investigate the underlying cause.
The Total Carbon Column Observing Network Wunch, Debra; Toon, Geoffrey C.; Blavier, Jean-François L. ...
Philosophical transactions - Royal Society. Mathematical, Physical and engineering sciences/Philosophical transactions - Royal Society. Mathematical, physical and engineering sciences,
05/2011, Volume:
369, Issue:
1943
Journal Article
Peer reviewed
Open access
A global network of ground-based Fourier transform spectrometers has been founded to remotely measure column abundances of CO 2 , CO, CH 4 , N 2 O and other molecules that absorb in the ...near-infrared. These measurements are directly comparable with the near-infrared total column measurements from space-based instruments. With stringent requirements on the instrumentation, acquisition procedures, data processing and calibration, the Total Carbon Column Observing Network (TCCON) achieves an accuracy and precision in total column measurements that is unprecedented for remote-sensing observations (better than 0.25% for CO 2 ). This has enabled carbon-cycle science investigations using the TCCON dataset, and allows the TCCON to provide a link between satellite measurements and the extensive ground-based in situ network.
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 a particularly challenging remote-sensing observation because all but the largest emission sources and natural absorbers produce only small (< 0.25 %) changes in the background XCO2 field. High measurement precision is therefore essential to resolve these small variations, and high accuracy is needed because small biases in the retrieved XCO2 distribution could be misinterpreted as evidence for CO2 fluxes. To meet its demanding measurement requirements, each OCO-2 spectrometer channel collects 24 spectra s−1 across a narrow (< 10 km) swath as the observatory flies over the sunlit hemisphere, yielding almost 1 million soundings each day. On monthly timescales, between 7 and 12 % of these soundings pass the cloud screens and other data quality filters to yield full-column estimates of XCO2. Each of these soundings has an unprecedented combination of spatial resolution (< 3 km2/sounding), spectral resolving power (λ∕Δλ > 17 000), dynamic range (∼ 104), and sensitivity (continuum signal-to-noise ratio > 400). The OCO-2 instrument performance was extensively characterized and calibrated prior to launch. In general, the instrument has performed as expected during its first 18 months in orbit. However, ongoing calibration and science analysis activities have revealed a number of subtle radiometric and spectroscopic challenges that affect the yield and quality of the OCO-2 data products. These issues include increased numbers of bad pixels, transient artifacts introduced by cosmic rays, radiance discontinuities for spatially non-uniform scenes, a misunderstanding of the instrument polarization orientation, and time-dependent changes in the throughput of the oxygen A-band channel. Here, we describe the OCO-2 instrument, its data products, and its on-orbit performance. We then summarize calibration challenges encountered during its first 18 months in orbit and the methods used to mitigate their impact on the calibrated radiance spectra distributed to the science community.
In a 3.5-year long study, the long-term
performance of a mobile, solar absorption Bruker EM27/SUN spectrometer, used
for greenhouse gas observations, is checked with respect to a co-located
reference ...Bruker IFS 125HR spectrometer, which is part of the Total Carbon
Column Observing Network (TCCON). We find that the EM27/SUN is stable on
timescales of several years; the drift per year between the EM27/SUN and the
official TCCON product is 0.02 ppmv for XCO2 and 0.9 ppbv for
XCH4, which is within the 1σ precision of the comparison,
0.6 ppmv for XCO2 and 4.3 ppbv for XCH4. The bias between
the two data sets is 3.9 ppmv for XCO2 and 13.0 ppbv for
XCH4. In order to avoid sensitivity-dependent artifacts, the EM27/SUN
is also compared to a truncated IFS 125HR data set derived from
full-resolution TCCON interferograms. The drift is 0.02 ppmv for
XCO2 and 0.2 ppbv for XCH4 per year, with 1σ
precisions of 0.4 ppmv for XCO2 and 1.4 ppbv for XCH4,
respectively. The bias between the two data sets is 0.6 ppmv for
XCO2 and 0.5 ppbv for XCH4. With the presented long-term
stability, the EM27/SUN qualifies as an useful supplement to the existing
TCCON network in remote areas. To achieve consistent performance, such an
extension requires careful testing of any spectrometers involved by
application of common quality assurance measures. One major aim of the
COllaborative Carbon Column Observing Network (COCCON) infrastructure is to
provide these services to all EM27/SUN operators. In the framework of COCCON
development, the performance of an ensemble of 30 EM27/SUN spectrometers was
tested and found to be very uniform, enhanced by the centralized inspection
performed at the Karlsruhe Institute of Technology prior to deployment.
Taking into account measured instrumental line shape parameters for each
spectrometer, the resulting average bias across the ensemble with respect to
the reference EM27/SUN used in the long-term study in XCO2 is
0.20 ppmv, while it is 0.8 ppbv for XCH4. The average standard
deviation of the ensemble is 0.13 ppmv for XCO2 and 0.6 ppbv for
XCH4. In addition to the robust metric based on absolute differences,
we calculate the standard deviation among the empirical calibration factors.
The resulting 2σ uncertainty is 0.6 ppmv for XCO2 and
2.2 ppbv for XCH4. As indicated by the executed long-term study on
one device presented here, the remaining empirical calibration factor deduced
for each individual instrument can be assumed constant over time. Therefore
the application of these empirical factors is expected to further improve the
EM27/SUN network conformity beyond the scatter among the empirical
calibration factors reported above.
Carbon monoxide (CO) is an important atmospheric constituent affecting air quality, and methane (CH.sub.4) is the second most important greenhouse gas contributing to human-induced climate change. ...Detailed and continuous observations of these gases are necessary to better assess their impact on climate and atmospheric pollution. While surface and airborne measurements are able to accurately determine atmospheric abundances on local scales, global coverage can only be achieved using satellite instruments.
Optimal estimation retrievals of trace gas total columns require prior vertical profiles of the gases retrieved to drive the forward model and ensure the retrieval problem is mathematically well ...posed. For well-mixed gases, it is possible to derive accurate prior profiles using an algorithm that accounts for general patterns of atmospheric transport coupled with measured time series of the gases in questions. Here we describe the algorithm used to generate the prior profiles for GGG2020, a new version of the GGG retrieval that is used to analyze spectra from solar-viewing Fourier transform spectrometers, including the Total Carbon Column Observing Network (TCCON). A particular focus of this work is improving the accuracy of CO2, CH4, N2O, HF, and CO across the tropopause and into the lower stratosphere. We show that the revised priors agree well with independent in situ and space-based measurements and discuss the impact on the total column retrievals.
On 13 October 2017, the Tropospheric Monitoring Instrument
(TROPOMI) was launched on the Copernicus Sentinel-5
Precursor satellite in a sun-synchronous orbit. One of the
mission's operational data ...products is the total column
concentration of carbon monoxide (CO), which was released
to the public in July 2018. The current TROPOMI CO
processing uses the HITRAN 2008 spectroscopic data with
updated water vapor spectroscopy and produces a CO data
product compliant with the mission requirement of 10 %
precision and 15 % accuracy for single soundings.
Comparison with ground-based CO observations of the Total
Carbon Column Observing Network (TCCON) show systematic
differences of about 6.2 ppb and single-orbit
observations are superimposed by a significant striping
pattern along the flight path exceeding 5 ppb. In this
study, we discuss possible improvements of the CO data
product. We found that the molecular spectroscopic data
used in the retrieval plays a key role for the data
quality where the use of the Scientific Exploitation of
Operational Missions – Improved Atmospheric Spectroscopy
Databases (SEOM-IAS) and the HITRAN 2012 and 2016 releases
reduce the bias between TROPOMI and TCCON due to improved
CH4 spectroscopy. SEOM-IAS achieves the best
spectral fit quality (root-mean-square, rms,
differences between the simulated and measured spectrum)
of 1.5×10-10 mol s−1 m−2 nm−1 sr−1 and reduces the bias between TROPOMI and TCCON to
3.4 ppb, while HITRAN 2012 and HITRAN 2016 decrease the
bias even further below 1 ppb. HITRAN 2012 shows the
worst fit quality (rms = 2.5×10-10 mol s−1 m−2 nm−1 sr−1) of the tested cross sections
and furthermore introduces an artificial bias of about
-1.5×1017 molec cm−2 between TROPOMI CO and
the CAMS-IFS model in the Tropics caused by the H2O
spectroscopic data. Moreover, analyzing 1 year of
TROPOMI CO observations, we identified increased striping
patterns by about 16 % percent from November 2017 to
November 2018. For that, we defined a measure γ,
quantifying the relative pixel-to-pixel variation in CO in the
cross-track and along-track directions.
To mitigate this effect, we discuss two
destriping methods applied to the CO data a posteriori.
A destriping mask calculated per orbit by median filtering
of the data in the cross-track direction significantly
reduced the stripe pattern from γ=2.1 to γ=1.6.
However,
the destriping can be further improved, achieving γ=1.2 by
deploying a Fourier analysis and filtering of the
data, which not only corrects for stripe patterns in the
cross-track direction but also accounts for the
variability of stripes along the flight path.
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