Global estimates of gap-free and fine-scale CO2 concentrations during 2014-2020 from satellite and reanalysis data

Carbon dioxide (CO2) is a crucial greenhouse gas with substantial effects on climate change. Satellite-based remote sensing is a commonly used approach to detect CO2 with high precision but often suffers from extensive spatial gaps. Thus, the limited availability of data makes global carbon stocktaking challenging. In this paper, a global gap-free column-averaged dry-air mole fraction of CO2 (XCO2) dataset with a high spatial resolution of 0.1° from 2014 to 2020 is generated by the deep learning-based multisource data fusion, including satellite and reanalyzed XCO2 products, satellite vegetation index data, and meteorological data. Results indicate a high accuracy for 10-fold cross-validation (R2 = 0.959 and RMSE = 1.068 ppm) and ground-based validation (R2 = 0.964 and RMSE = 1.010 ppm). Our dataset has the advantages of high accuracy and fine spatial resolution compared with the XCO2 reanalysis data as well as that generated from other studies. Based on the dataset, our analysis reveals interesting findings regarding the spatiotemporal pattern of CO2 over the globe and the national-level growth rates of CO2. This gap-free and fine-scale dataset has the potential to provide support for understanding the global carbon cycle and making carbon reduction policy, and it can be freely accessed at https://doi.org/10.5281/zenodo.7721945.

Toward High Precision XCO2 Retrievals From TanSat Observations: Retrieval Improvement and Validation Against TCCON Measurements

TanSat is the 1st Chinese carbon dioxide (CO2) measurement satellite, launched in 2016. In this study, the University of Leicester Full Physics (UoL-FP) algorithm is implemented for TanSat nadir mode XCO2 retrievals. We develop a spectrum correction method to reduce the retrieval errors by the online fitting of an 8th order Fourier series. The spectrum-correction model and its a priori parameters are developed by analyzing the solar calibration measurement. This correction provides a significant improvement to the O2 A band retrieval. Accordingly, we extend the previous TanSat single CO2 weak band retrieval to a combined O2 A and CO2 weak band retrieval. A Genetic Algorithm (GA) has been applied to determine the threshold values of post-screening filters. In total, 18.3% of the retrieved data is identified as high quality compared to the original measurements. The same quality control parameters have been used in a footprint independent multiple linear regression bias correction due to the strong correlation with the XCO2 retrieval error. Twenty sites of the Total Column Carbon Observing Network (TCCON) have been selected to validate our new approach for the TanSat XCO2 retrieval. We show that our new approach produces a significant improvement on the XCO2 retrieval accuracy and precision when compared to TCCON with an average bias and RMSE of -0.08 ppm and 1.47 ppm, respectively. The methods used in this study can help to improve the XCO2 retrieval from TanSat and subsequently the Level-2 data production, and hence will be applied in the TanSat operational XCO2 processing.

Retrieval and Validation of XCO2 from TanSat Target Mode Observations in Beijing

Satellite observation is one of the main methods used to monitor the global distribution and variation of atmospheric carbon dioxide (CO2). Several CO2 monitoring satellites have been successfully launched, including Japan’s Greenhouse Gases Observing SATellite (GOSAT), the USA’s Orbiting Carbon Observatory-2 (OCO-2), and China’s Carbon Dioxide Observation Satellite Mission (TanSat). Satellite observation targeting the ground-based Fourier transform spectrometer (FTS) station is the most effective technique for validating satellite CO2 measurement precision. In this study, the coincident observations from TanSat and ground-based FTS were performed numerous times in Beijing under a clear sky. The column-averaged dry-air mole fraction of carbon dioxide (XCO2) obtained from TanSat was retrieved by the Department for Eco-Environmental Informatics (DEEI) of China’s State Key Laboratory of Resources and Environmental Information System based on a full physical model. The comparison and validation of the TanSat target mode observations revealed that the average of the XCO2 bias between TanSat retrievals and ground-based FTS measurements was 2.62 ppm, with a standard deviation (SD) of the mean difference of 1.41 ppm, which met the accuracy standard of 1% required by the mission tasks. With bias correction, the mean absolute error (MAE) improved to 1.11 ppm and the SD of the mean difference fell to 1.35 ppm. We compared simultaneous observations from GOSAT and OCO-2 Level 2 (L2) bias-corrected products within a ±1° latitude and longitude box centered at the ground-based FTS station in Beijing. The results indicated that measurements from GOSAT and OCO-2 were 1.8 ppm and 1.76 ppm higher than the FTS measurements on 20 June 2018, on which the daily observation bias of the TanSat XOC2 results was 1.87 ppm. These validation efforts have proven that TanSat can measure XCO2 effectively. In addition, the DEEI-retrieved XCO2 results agreed well with measurements from GOSAT, OCO-2, and the Beijing ground-based FTS.

Optimization of the Photon Path Length Probability Density Function-Simultaneous (PPDF-S) Method and Evaluation of CO₂ Retrieval Performance Under Dense Aerosol Conditions

The photon path length probability density function-simultaneous (PPDF-S) algorithm is effective for retrieving column-averaged concentrations of carbon dioxide (XCO₂) and methane (XCH₄) from Greenhouse gases Observing Satellite (GOSAT) spectra in Short Wavelength InfraRed (SWIR). Using this method, light-path modification attributable to light reflection/scattering by atmospheric clouds/aerosols is represented by the modification of atmospheric transmittance according to PPDF parameters. We optimized PPDF parameters for a more accurate XCO₂ retrieval under aerosol dense conditions based on simulation studies for various aerosol types and surface albedos. We found a more appropriate value of PPDF parameters referring to the vertical profile of CO₂ concentration as a measure of a stable solution. The results show that the constraint condition of a PPDF parameter that represents the light reflectance effect by aerosols is sufficiently weak to affect XCO₂ adversely. By optimizing the constraint, it was possible to obtain a stable solution of XCO₂. The new optimization was applied to retrieval analysis of the GOSAT data measured in Western Siberia. First, we assumed clear sky conditions and retrieved XCO₂ from GOSAT data obtained near Yekaterinburg in the target area. The retrieved XCO₂ was validated through a comparison with ground-based Fourier Transform Spectrometer (FTS) measurements made at the Yekaterinburg observation site. The validation results showed that the retrieval accuracy was reasonable. Next, we applied the optimized method to dense aerosol conditions when biomass burning was active. The results demonstrated that optimization enabled retrieval, even under smoky conditions, and that the total number of retrieved data increased by about 70%. Furthermore, the results of the simulation studies and the GOSAT data analysis suggest that atmospheric aerosol types that affected CO₂ analysis are identifiable by the PPDF parameter value. We expect that we will be able to suggest a further improved algorithm after the atmospheric aerosol types are identified.

Modeling leaf CO2 assimilation and Photosystem II photochemistry from chlorophyll fluorescence and the photochemical reflectance index

We present a simple model to assess the quantum yield of photochemistry (Φ_P ) and CO₂ assimilation rate from two parameters that are detectable by remote sensing: chlorophyll (chl) fluorescence and the photochemical reflectance index (PRI). Φ_P is expressed as a simple function of the chl fluorescence yield (Φ_F ) and nonphotochemical quenching (NPQ): Φ_P  = 1-bΦ_F (1 + NPQ). Because NPQ is known to be related with PRI, Φ_P can be remotely assessed from solar-induced fluorescence and the PRI. The CO₂ assimilation rate can be assessed from the estimated Φ_P value with either the maximum carboxylation rate (V_cmax ), the intercellular CO₂ concentration (C_i ), or parameters of the stomatal conductance model. The model was applied to experimental data obtained for Chenopodium album leaves under various environmental conditions and was able to successfully predict Φ_F values and the CO₂ assimilation rate. The present model will improve the accuracy of assessments of gas exchange rates and primary productivity by remote sensing.

The TanSat mission: preliminary global observations

The Chinese global carbon dioxide monitoring satellite (TanSat) was launched successfully in December 2016 and has completed its on-orbit tests and calibration. TanSat aims to measure the atmospheric column-averaged dry air mole fractions of carbon dioxide (XCO₂) with a precision of 4 ppm at the regional scale, and in addition, to derive global and regional CO₂ fluxes. Progress towards these objectives is reviewed and the first scientific results from TanSat measurements are presented. TanSat on-orbit tests indicate that the Atmospheric Carbon dioxide Grating Spectrometer is in normal working status and is beginning to produce L1B products. The preliminary TanSat XCO₂ products have been retrieved by an algorithm and compared to NASA Orbiting Carbon Observatory-2 (OCO-2) measurements during an overlapping observation period. Furthermore, the XCO₂ retrievals have been validated against eight ground-site measurement datasets from the Total Carbon Column Observing Network, for which the preliminary conclusion is that TanSat has met the precision design requirement, with an average bias of 2.11 ppm. The first scientific observations are presented, namely, the seasonal distributions of XCO₂ over land on a global scale.

A comparison of satellite observations with the XCO2 surface obtained by fusing TCCON measurements and GEOS-Chem model outputs

Ground observations can capture CO₂ concentrations accurately but the number of available TCCON (Total Carbon Column Observing Network) sites is too small to support a comprehensive analysis (i.e. validation) of satellite observations. Atmospheric transport models can provide continuous atmospheric CO₂ concentrations in space and time, but some information is difficult to generate with model simulations. The HASM platform can model continuous column-averaged CO₂ dry air mole fraction (XCO₂) surface taking TCCON observations as its optimum control constraints and an atmospheric transport model as its driving field. This article presents a comparison of the satellite observations with a HASM XCO₂ surface obtained by fusing TCCON measurements with GEOS-Chem model results. We first verified the accuracy of the HASM XCO₂ surface using six years (2010-2015) of TCCON observations and the GEOS-Chem model XCO₂ results. The validation results show that the largest MAE of bias between the HASM results and observations was 0.85ppm and the smallest MAE was only 0.39ppm. Next, we modeled the HASM XCO₂ surface by fusing the TCCON measurements and GEOS-Chem XCO₂ model results for the period 9/1/14 to 8/31/15. Finally, we compared the GOSAT and OCO-2 observations with the HASM XCO₂ surface and found that the global OCO-2 XCO₂ estimates more closely resembled the HASM XCO₂ surface than the GOSAT XCO₂ estimates.

The Orbiting Carbon Observatory-2 early science investigations of regional carbon dioxide fluxes

NASA's Orbiting Carbon Observatory-2 (OCO-2) mission was motivated by the need to diagnose how the increasing concentration of atmospheric carbon dioxide (CO2) is altering the productivity of the biosphere and the uptake of CO2 by the oceans. Launched on 2 July 2014, OCO-2 provides retrievals of the column-averaged CO2 dry-air mole fraction ([Formula: see text]) as well as the fluorescence from chlorophyll in terrestrial plants. The seasonal pattern of uptake by the terrestrial biosphere is recorded in fluorescence and the drawdown of [Formula: see text] during summer. Launched just before one of the most intense El Niños of the past century, OCO-2 measurements of [Formula: see text] and fluorescence record the impact of the large change in ocean temperature and rainfall on uptake and release of CO2 by the oceans and biosphere.

Combining XCO2 measurements derived from SCIAMACHY and GOSAT for potentially generating global CO2 maps with high spatiotemporal resolution

Global warming induced by atmospheric CO₂ has attracted increasing attention of researchers all over the world. Although space-based technology provides the ability to map atmospheric CO₂ globally, the number of valid CO₂ measurements is generally limited for certain instruments owing to the presence of clouds, which in turn constrain the studies of global CO₂ sources and sinks. Thus, it is a potentially promising work to combine the currently available CO₂ measurements. In this study, a strategy for fusing SCIAMACHY and GOSAT CO₂ measurements is proposed by fully considering the CO₂ global bias, averaging kernel, and spatiotemporal variations as well as the CO₂ retrieval errors. Based on this method, a global CO₂ map with certain UTC time can also be generated by employing the pattern of the CO₂ daily cycle reflected by Carbon Tracker (CT) data. The results reveal that relative to GOSAT, the global spatial coverage of the combined CO₂ map increased by 41.3% and 47.7% on a daily and monthly scale, respectively, and even higher when compared with that relative to SCIAMACHY. The findings in this paper prove the effectiveness of the combination method in supporting the generation of global full-coverage XCO₂ maps with higher temporal and spatial sampling by jointly using these two space-based XCO₂ datasets.

Atmospheric CO2 column measurements with an airborne intensity-modulated continuous wave 1.57 μm fiber laser lidar

The 2007 National Research Council (NRC) Decadal Survey on Earth Science and Applications from Space recommended Active Sensing of CO(2) Emissions over Nights, Days, and Seasons (ASCENDS) as a midterm, Tier II, NASA space mission. ITT Exelis, formerly ITT Corp., and NASA Langley Research Center have been working together since 2004 to develop and demonstrate a prototype laser absorption spectrometer for making high-precision, column CO(2) mixing ratio measurements needed for the ASCENDS mission. This instrument, called the multifunctional fiber laser lidar (MFLL), operates in an intensity-modulated, continuous wave mode in the 1.57 μm CO(2) absorption band. Flight experiments have been conducted with the MFLL on a Lear-25, UC-12, and DC-8 aircraft over a variety of different surfaces and under a wide range of atmospheric conditions. Very high-precision CO(2) column measurements resulting from high signal-to-noise ratio (>1300) column optical depth (OD) measurements for a 10 s (~1 km) averaging interval have been achieved. In situ measurements of atmospheric CO(2) profiles were used to derive the expected CO(2) column values, and when compared to the MFLL measurements over desert and vegetated surfaces, the MFLL measurements were found to agree with the in situ-derived CO(2) columns to within an average of 0.17% or ~0.65 ppmv with a standard deviation of 0.44% or ~1.7 ppmv. Initial results demonstrating ranging capability using a swept modulation technique are also presented.

The total carbon column observing network

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.

Thermal and near infrared sensor for carbon observation Fourier-transform spectrometer on the Greenhouse Gases Observing Satellite for greenhouse gases monitoring

The Greenhouse Gases Observing Satellite (GOSAT) monitors carbon dioxide (CO(2)) and methane (CH(4)) globally from space using two instruments. The Thermal and Near Infrared Sensor for Carbon Observation Fourier-Transform Spectrometer (TANSO-FTS) detects gas absorption spectra of the solar short wave infrared (SWIR) reflected on the Earth's surface as well as of the thermal infrared radiated from the ground and the atmosphere. TANSO-FTS is capable of detecting three narrow bands (0.76, 1.6, and 2.0 microm) and a wide band (5.5-14.3 microm) with 0.2 cm(-1) spectral resolution (interval). The TANSO Cloud and Aerosol Imager (TANSO-CAI) is an ultraviolet (UV), visible, near infrared, and SWIR radiometer designed to detect cloud and aerosol interference and to provide the data for their correction. GOSAT is placed in a sun-synchronous orbit 666 km at 13:00 local time, with an inclination angle of 98 degrees . A brief overview of the GOSAT project, scientific requirements, instrument designs, hardware performance, on-orbit operation, and data processing is provided.

Retrievals of atmospheric CO2 from simulated space-borne measurements of backscattered near-infrared sunlight: accounting for aerosol effects

Retrievals of atmospheric carbon dioxide (CO2) from space-borne measurements of backscattered near-infrared sunlight are hampered by aerosol and cirrus cloud scattering effects. We propose a retrieval approach that allows for the retrieval of a few effective aerosol parameters simultaneously with the CO2 total column by parameterizing particle amount, height distribution, and microphysical properties. Two implementations of the proposed method covering different spectral bands are tested for an ensemble of simulated nadir observations for aerosol (and cirrus) loaded scenes over low- and mid-latitudinal land surfaces. The residual aerosol-induced CO(2) errors are mostly below 1% up to aerosol optical thickness 0.5. The proposed methods also perform convincing for scenes where cirrus clouds of optical thickness 0.1 overlay the aerosol.

Quantifying sources and sinks of trace gases using space-borne measurements: current and future science

We have been observing the Earth's upper atmosphere from space for several decades, but only over the past decade has the necessary technology begun to match our desire to observe surface air pollutants and climate-relevant trace gases in the lower troposphere, where we live and breathe. A new generation of Earth-observing satellites, capable of probing the lower troposphere, are already orbiting hundreds of kilometres above the Earth's surface with several more ready for launch or in the planning stages. Consequently, this is one of the most exciting times for the Earth system scientists who study the countless current-day physical, chemical and biological interactions between the Earth's land, ocean and atmosphere. First, I briefly review the theory behind measuring the atmosphere from space, and how these data can be used to infer surface sources and sinks of trace gases. I then present some of the science highlights associated with these data and how they can be used to improve fundamental understanding of the Earth's climate system. I conclude the paper by discussing the future role of satellite measurements of tropospheric trace gases in mitigating surface air pollution and carbon trading.

An atmospheric perspective on North American carbon dioxide exchange: CarbonTracker

We present an estimate of net CO(2) exchange between the terrestrial biosphere and the atmosphere across North America for every week in the period 2000 through 2005. This estimate is derived from a set of 28,000 CO(2) mole fraction observations in the global atmosphere that are fed into a state-of-the-art data assimilation system for CO(2) called CarbonTracker. By design, the surface fluxes produced in CarbonTracker are consistent with the recent history of CO(2) in the atmosphere and provide constraints on the net carbon flux independent from national inventories derived from accounting efforts. We find the North American terrestrial biosphere to have absorbed -0.65 PgC/yr (1 petagram = 10(15) g; negative signs are used for carbon sinks) averaged over the period studied, partly offsetting the estimated 1.85 PgC/yr release by fossil fuel burning and cement manufacturing. Uncertainty on this estimate is derived from a set of sensitivity experiments and places the sink within a range of -0.4 to -1.0 PgC/yr. The estimated sink is located mainly in the deciduous forests along the East Coast (32%) and the boreal coniferous forests (22%). Terrestrial uptake fell to -0.32 PgC/yr during the large-scale drought of 2002, suggesting sensitivity of the contemporary carbon sinks to climate extremes. CarbonTracker results are in excellent agreement with a wide collection of carbon inventories that form the basis of the first North American State of the Carbon Cycle Report (SOCCR), to be released in 2007. All CarbonTracker results are freely available at http://carbontracker.noaa.gov.