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A Google Earth map (Data SIO, NOAA, U. S. Navy, NGA, GEBCO © 2018 Google) showing the GOSAT specific point observations around Alice Springs (cyan circles labeled "Obs#") . The ground-based site is securely fenced and located at the airport, ca. 14 km south of the town center. The magenta circle shows a 60 km radius from the site, for visual reference. The inset shows the EM27 during the measurements.
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In this study, we present ground-based measurements of column-averaged dry-air mole fractions (DMFs) of CO2 (or XCO2) taken in a semiarid region of Australia with an EM27/SUN portable spectrometer equipped with an automated clamshell cover. We compared these measurements to space-based XCO2 retrievals from the Greenhouse Gases Observing Satellite (...
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... it is able to observe specific points, i.e., it can view targets with angles up to ±20 • along the satellite track and by ±30 • across the track. Specific point observations over Alice Springs were requested from July 2016, in preparation for the campaign in September. Five locations within 100 km of the center of Alice Springs were targeted (see Fig. 3). We only used the specific point observation data to compare with the EM27. However, to construct the time series shown in ...
Citations
... For instance, the Environmental Satellite (Envisat) can provide global column-mean dry-air mole fractions of CO 2 (XCO 2 ) and CH 4 (XCH 4 ) at a coarse resolution of 30×60 km 2 with the payload of the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (Burrows et al., 1995;Beirle et al., 2018). The Thermal and Near-Infrared Sensor for carbon Observations -Fourier Transform Spectrometer on board the Greenhouse Gases Observing Satellite (GOSAT) (Hamazaki et al., 2005;Velazco et al., 2019) can produce ∼ 10 km XCO 2 and XCH 4 over the globe based on three spectral bands. Orbiting Carbon Observatory 2 and 3 (OCO-2 and OCO-3) Doughty et al., 2022) carry three-channel grating spectrometers to generate globally covered XCO 2 at a much finer spatial resolution of 1.29 × 2.25 km 2 . ...
Precise and continuous monitoring of long-term carbon dioxide (CO2) and methane (CH4) over the globe is of great importance, which can help study global warming and achieve the goal of carbon neutrality. Nevertheless, the available observations of CO2 and CH4 from satellites are generally sparse, and current fusion methods to reconstruct their long-term values on a global scale are few. To address this problem, we propose a novel spatiotemporally self-supervised fusion method to establish long-term daily seamless XCO2 and XCH4 products from 2010 to 2020 over the globe on grids of 0.25∘. A total of three datasets are applied in our study, including the Greenhouse Gases Observing Satellite (GOSAT), the Orbiting Carbon Observatory 2 (OCO-2), and CAMS global greenhouse gas reanalysis (CAMS-EGG4). Attributed to the significant sparsity of data from GOSAT and OCO-2, the spatiotemporal discrete cosine transform is considered for our fusion task. Validation results show that the proposed method achieves a satisfactory accuracy, with standard deviations of bias (σ) of ∼1.18 ppm for XCO2 and 11.3 ppb for XCH4 against Total Carbon Column Observing Network (TCCON) measurements from 2010 to 2020. Meanwhile, the determination coefficients (R2) of XCO2 and XCH4 reach 0.91 or 0.95 (2010–2014 or 2015–2020) and 0.9 (2010–2020), respectively, after fusion. Overall, the performance of fused results distinctly exceeds that of CAMS-EGG4, which is also superior or close to those of GOSAT and OCO-2. In particular, our fusion method can effectively correct the large biases in CAMS-EGG4 due to the issues from assimilation data, such as the unadjusted anthropogenic emission inventories for COVID-19 lockdowns in 2020. Moreover, the fused results present coincident spatial patterns with GOSAT and OCO-2, which accurately display the long-term and seasonal changes in globally distributed XCO2 and XCH4. The daily global seamless gridded (0.25∘) XCO2 and XCH4 from 2010 to 2020 can be freely accessed at https://doi.org/10.5281/zenodo.7388893 (Wang et al., 2022a).
... Previous studies show the versatile deployment options of the instruments around the world A. Butz et al., 2017;André Butz et al., 2022;Hedelius et al., 2016;Kille et al., 2019Kille et al., , 2019F. Klappenbach et al., 2015;Knapp et al., 2021;Luther et al., 2019;Velazco et al., 2019;Viatte et al., 2017). Since no consistent automatization software exists, Pyra, as an open-source automation, will potentially unify the measurement procedure and facilitate data acquisition. ...
... The network provides column average dry mole fractions (DMFs) of numerous gases, including carbon dioxide (CO 2 ), methane (CH 4 ), nitrous oxide (N 2 O), hydrofluoric acid (HF), and carbon monoxide (CO). These observations have been used to infer or evaluate natural and anthropogenic carbon fluxes (e.g., Yang et al., 2007;Chevallier et al., 2011;Keppel-Aleks et al., 2012;Basu et al., 2013;Fraser et al., 2013;Ott et al., 2015;Peng et al., 2015;Deng et al., 2016;Wang et al., 2016;Feng et al., 2017;Hedelius et al., 2018;Crowell et al., 2019;Babenhauserheide et al., 2020;Dogniaux et al., 2021;Sussmann and Rettinger, 2020;Zhang et al., 2021;Villalobos et al., 2021), to study carbon transport (e.g., Keppel-Aleks et al., 2012;Polavarapu et al., 2016), and to provide ground truth values for spacebased measurements of CO 2 and CH 4 , including the Greenhouse gas Observing Satellites (GOSAT and GOSAT-2, e.g., Butz et al., 2011;Cogan et al., 2012;Schepers et al., 2012;Boesch et al., 2013;Frankenberg et al., 2013;Liu et al., 2013;Oshchepkov et al., 2013;Yoshida et al., 2013;Dils et al., 2014;Inoue et al., 2014;Heymann et al., 2015;Ohyama et al., 2015;Parker et al., 2015;Dupuy et al., 2016;Inoue et al., 2016;Kulawik et al., 2016;Schepers et al., 2016;Liang et al., 2017a;Ohyama et al., 2017;Velazco et al., 2019), TanSat (Yang et al., 2020), the Orbiting Carbon Observatories (OCO-2 and OCO-3, e.g., Liang et al., 2017a, b;Wunch et al., 2017;Kiel et al., 2019), and the Tropospheric Monitoring Instrument (TROPOMI, e.g., Borsdorff et al., 2019;Schneising et al., 2019;Lorente et al., 2021). ...
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.
... The atmospheric CO2 concentration is continuously increasing, and accurate measurement of changes in the concentration of atmospheric CO2 is a prerequisite to determining its influence on climate change. Several networks have been established in the world for the precise monitoring of atmospheric CO2 including the Global Atmospheric Watch (GAW) sites [6], the Collaborative Carbon Column Observing Network (COCCON) [7,8], and the Total Carbon Column Observing Network (TCCON) [9]. However, the measurements obtained from these ground stations are not sufficient for the accurate monitoring of atmospheric CO2 at regional and global scales due to certain limitations including their uneven distribution and limited spatial coverage [10]. ...
Satellites are an effective source of atmospheric carbon dioxide (CO2) monitoring; however, city-scale monitoring of atmospheric CO2 through space-borne observations is still a challenging task due to the trivial change in atmospheric CO2 concentration compared to its natural variability and background concentration. In this study, we attempted to evaluate the potential of space-based observations to monitor atmospheric CO2 changes at the city scale through simple data-driven analyses. We used the column-averaged dry-air mole fraction of CO2 (XCO2) from the Carbon Observatory 2 (OCO-2) and the anthropogenic CO2 emissions provided by the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) product to explain the scenario of CO2 over 120 districts of Pakistan. To study the anthropogenic CO2 through space-borne observations, XCO2 anomalies (MXCO2) were estimated from OCO-2 retrievals within the spatial boundary of each district, and then the overall spatial distribution pattern of the MXCO2 was analyzed with several datasets including the ODIAC emissions, NO2 tropospheric column, fire locations, cropland, nighttime lights and population density. All the datasets showed a similarity in the spatial distribution pattern. The satellite detected higher CO2 concentrations over the cities located along the China–Pakistan Economic Corridor (CPEC) routes. The CPEC is a large-scale trading partnership between Pakistan and China and large-scale development has been carried out along the CPEC routes over the last decade. Furthermore, the cities were ranked based on mean ODIAC emissions and MXCO2 estimates. The satellite-derived estimates showed a good consistency with the ODIAC emissions at higher values; however, deviations between the two datasets were observed at lower values. To further study the relationship of MXCO2 and ODIAC emissions with each other and with some other datasets such as population density and NO2 tropospheric column, statistical analyses were carried out among the datasets. Strong and significant correlations were observed among all the datasets.
... Keppel-Aleks et al., 2012;Polavarapu et al., 2016), and to provide ground-truth values for space-based measurements of CO 2 and CH 4 , including the Greenhouse gas Observing Satellites (GOSAT and GOSAT-2, e.g. Butz et al., 2011;Cogan et al., 2012;Schepers et al., 20 2012; Boesch et al., 2013;Frankenberg et al., 2013;Liu et al., 2013;Oshchepkov et al., 2013;Yoshida et al., 2013;Dils et al., 2014;Inoue et al., 2014;Heymann et al., 2015;Ohyama et al., 2015;Parker et al., 2015;Dupuy et al., 2016;Inoue et al., 2016;Kulawik et al., 2016;Schepers et al., 2016;Liang et al., 2017a;Ohyama et al., 2017;Velazco et al., 2019), TanSat (Yang et al., 2020), the Orbiting Carbon Observatories (OCO-2 and OCO-3, e.g. Liang et al., 2017a, b;Wunch et al., 2017;Kiel et al., The TCCON instruments are solar-viewing Bruker 125HR (high resolution) Fourier transform infrared (FT-IR) spectrometers, which record an interferogram once every few minutes. ...
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 description of CO2, CH4, N2O, HF, and CO in the stratosphere. We show that the revised priors agree well with independent in situ and space-based measurements and improve the total column retrievals.
... There are several networks in the world observing the mole fractions of GHGs and their trends including the Global Atmosphere Watch (GAW) program of the World Meteorological Organization (WMO) [4], satellite constellations [7][8][9], the Total Carbon Column Observing Network (TCCON) [10], and the Collaborative Carbon Column Observing Network (COCCON) [11,12]. Long-term observation of surface atmospheric CO 2 was first started at the Mauna Loa Observatory (MLO) in 1958 by David Keeling and provided direct evidence of an increase in CO 2 mole fractions [1, 13,14]. ...
... TCCON is conducting high-precision XCO 2 and XCH 4 observations with more than 20 global sites using ground-based Fourier transform spectrometers (Bruker IFS125), providing an ideal validation dataset for satellite-and model-retrieved column mole fractions [7,[16][17][18][19][20]. However, the instrumentation used in TCCON is expensive and requires expert maintenance; the portable Bruker EM27/SUN FTIR spectrometer provides a mobile, easy-to-deploy, and low-cost complement to obtain more observations in different underlying surfaces, such as urban areas, deserts, and oceans [7,11,12,18,[21][22][23][24]. China has several background observatories monitoring greenhouse gases continuously for more than 10 years, operated by the China Meteorological Administration, including one global background observatory (Waliguan) and six regional background observatories across China [25]. ...
... Atmosphere 2022, 13, 571 4 of 17 detector between 5000 and 12,000 cm −1 , while CO spectra were measured by an extended InGaAs detector below 5000 cm −1 [12]. The EM27/SUN was placed on an outdoor desk (~1 m above the ground) at the CRCS. ...
Carbon dioxide (CO2) and methane (CH4) are the two major radiative forcing factors of greenhouse gases. In this study, surface and column mole fractions of CO2 and CH4 were first measured at a desert site in Dunhuang, west China. The average column mole fractions of CO2 (XCO2) and CH4 (XCH4) were 413.00 ± 1.09 ppm and 1876 ± 6 ppb, respectively, which were 0.90 ppm and 72 ppb lower than their surface values. Diurnal XCO2 showed a sinusoidal mode, while XCH4 appeared as a unimodal distribution. Ground observed XCO2 and XCH4 were compared with international satellites, such as GOSAT, GOSAT-2, OCO-2, OCO-3, and Sentinel-5P. The differences between satellites and EM27/SUN observations were 0.26% for XCO2 and −0.38% for XCH4, suggesting a good consistency between different satellites and ground observations in desert regions in China. Hourly XCO2 was close to surface CO2 mole fractions, but XCH4 appeared to have a large gap with CH4, probably because of the additional chemical removals of CH4 in the upper atmosphere. It is necessary to carry out a long-term observation of column mole fractions of greenhouse gases in the future to obtain their temporal distributions as well as the differences between satellites and ground observations.
... The current generation of satellite-based sensors provides improved observation density and better coverage for the Southern Hemisphere than can be achieved from ground-based instruments alone. Nevertheless, the satellite sensors require ground-based remote sensing instruments to validate their products within the Southern Hemisphere due to differences in viewing geometry and albedo that can impact retrieval accuracy (Velazco et al., 2019). As for the in situ networks, the number of groundbased remote sensing facilities in the Southern Hemisphere is limited. ...
This commentary paper from the recently formed International Global Atmospheric Chemistry (IGAC) Southern Hemisphere Working Group outlines key issues in atmospheric composition research that particularly impact the Southern Hemisphere. In this article, we present a broad overview of many of the challenges for understanding atmospheric chemistry in the Southern Hemisphere, before focusing in on the most significant factors that differentiate it from the Northern Hemisphere. We present sections on the importance of biogenic emissions and fires in the Southern Hemisphere, showing that these emissions often dominate over anthropogenic emissions in many regions. We then describe how these and other factors influence air quality in different parts of the Southern Hemisphere. Finally, we describe the key role of the Southern Ocean in influencing atmospheric chemistry and conclude with a description of the aims and scope of the newly formed IGAC Southern Hemisphere Working Group.
... The Department for Eco-Environmental Informatics (DEEI) of the State Key Laboratory of Resources and Environmental Information System of China has developed a TanSat Retrieval algorithm by combining the SCIATRAN radiation transfer model and OEM method. The XCO 2 bias of the DEEI algorithm was 2.62 ppm compared with the ground-based FTS measurement, with a standard deviation of 1.41 ppm [45]. We use the DEEI XCO 2 L2 data in this paper (Figure 5c). ...
The Fourier Transform Spectrometer (FTS) at the Beijing Satellite Meteorological Ground Station observed XCO2 (the dry carbon dioxide column) from 2 March 2016 to 4 December 2018. The validation results of ground-based XCO2, as well as GOSAT, OCO-2, and TanSat XCO2, show that the best temporal matching setting for ground-based XCO2 and satellite XCO2 is ±1 h, and the best spatial matching setting for GOSAT is 0.5° × 0.5°. Consistent with OCO-2, the best spatial matching setting of TanSat is 5° × 5° or 6° × 6°. Among GOSAT, OCO-2, and TanSat, the satellite observation validation characteristics near 5° × 5° from the ground-based station are obviously different from other spatial matching grids, which may be due to the different observation characteristics of satellites near 5° × 5°. To study the influence of local CO2 sources on the characteristics of satellite observation validation, we classified the daily XCO2 observation sequence into concentrated, dispersive, increasing, and decreasing types, respectively, and then validated the satellite observations. The results showed that the concentrated and decreasing sub-datasets have better validation performance. Our results suggest that it is best to use concentrated and decreasing sub-datasets when using the Beijing Satellite Meteorological Ground Station XCO2 for satellite validation. The temporal matching setting should be ±1 h, and the spatial matching setting should consider the satellites observation characteristics of 5° × 5° distance from the ground-based station.
... Tasks that can be accomplished by performing differential measurements using several spectrometers which can be calibrated side by side in the framework of campaigns are easier to achieve. Many successful campaigns for quantifying GHG emission strengths from regions of interest, like cities, coal mines, large dairy farms, etc., by arranging several spectrometers around the source have been performed successfully using EM27/SUN spectrometers in the recent past Vogel et al., 2019;Makarova et al., 2021;Viatte et al., 2017;Kille et al., 2019;Butz et al., 2017;Luther et al., 2019). In this work, we introduce a COCCON station in Gobabeb, Namibia, where measurements have been conducted since January 2015. ...
In this study, we present column-averaged dry-air mole fractions of CO2 (XCO2), CH4 (XCH4) and CO (XCO) from a recently established measurement site in Gobabeb, Namibia. Gobabeb is a hyperarid desert site at the sharp transition zone between the sand desert and the gravel plains, offering unique characteristics with respect to surface albedo properties. Measurements started in January 2015 and are performed utilizing a ground-based Fourier transform infrared (FTIR) EM27/SUN spectrometer of the COllaborative Carbon Column Observing Network (COCCON). Gobabeb is the first measurement site observing XCO2 and XCH4 on the African mainland and improves the global coverage of ground-based remote-sensing sites. In order to achieve the high level of precision and accuracy necessary for meaningful greenhouse gas observations, we performed calibration measurements for 8 d between November 2015 and March 2016 with the COCCON reference EM27/SUN spectrometer operated at the Karlsruhe Institute of Technology. We derived scaling factors for XCO2, XCH4 and XCO with respect to the reference instrument that are close to 1.0. We compare the results obtained in Gobabeb to measurements from the Total Carbon Column Observing Network (TCCON) sites at Réunion Island and Lauder. We choose these TCCON sites because, while 4000 km apart, the instruments at Gobabeb and Réunion Island operate at roughly the same latitude. The Lauder station is the southernmost TCCON station and functions as a background site without a pronounced XCO2 seasonal cycle. We find a good agreement for the absolute Xgas values, apart from an expected XCH4 offset between Gobabeb and Lauder due to significantly different tropopause height, as well as representative intraday variability between TCCON and COCCON. Together with the absence of long-term drifts, this highlights the quality of the COCCON measurements. In the southern hemispheric summer, we observe lower XCO2 values at Gobabeb compared to the TCCON stations, likely due to the influence of the African biosphere. We performed coincident measurements with the Greenhouse Gases Observing Satellite (GOSAT), where GOSAT observed three nearby specific observation points, over the sand desert south of the station, directly over Gobabeb and over the gravel plains to the north. GOSAT H-gain XCO2 and XCH4 agree with the EM27/SUN measurements within the 1σ uncertainty limit. The number of coincident soundings is limited, but we confirm a bias of 1.2–2.6 ppm between GOSAT M-gain and H-gain XCO2 retrievals depending on the target point. This is in agreement with results reported by a previous study and the GOSAT validation team. We also report a bias of 5.9–9.8 ppb between GOSAT M-gain and H-gain XCH4 measurements which is within the range given by the GOSAT validation team. Finally, we use the COCCON measurements to evaluate inversion-optimized CAMS model data. For XCO2, we find high biases of 0.9 ± 0.5 ppm for the Orbiting Carbon Observatory-2 (OCO-2) assimilated product and 1.1 ± 0.6 ppm for the in situ-driven product with R2 > 0.9 in both cases. These biases are comparable to reported offsets between the model and TCCON data. The OCO-2 assimilated model product is able to reproduce the drawdown of XCO2 observed by the COCCON instrument at the beginning of 2017, as opposed to the in situ-optimized product. Also, for XCH4, the observed biases are in line with prior model comparisons with TCCON.
... As a result of the decrease in fossil fuel consumption and vehicular traffic, global daily emissions of carbon dioxide (CO 2 ) decreased by about 17% in the first four months of 2020 compared with the same period in 2019 and the total emissions of CO 2 in 2020 are estimated to have decreased by about 8% using 2019 as the baseline year [7]. The estimated emission of CO 2 in China decreased by 10. [3][4][5][6][7][8][9][10][11].5% in the first quarter of 2020 relative to 2019 [7][8][9]. ...
... However, the 2020 lockdown is a unique case to test whether the concentration changes relating to human activities can be separated from the atmospheric measurements. The column-averaged dry-air mole fractions of a gas (Xgas) are less sensitive to vertical transport, and the horizontal gradient of Xgas has a more direct relationship with the regional-scale flux than in situ measurements of gas concentrations near the Earth's surface [10]. Sussmann and Rettinger [11] compared the long-term growth rates of XCO 2 before 2019 at several background Total Carbon Column Observing Network (TCCON) sites with the reference forecast rate based on an 8% reduction in annual emissions for 2020 and found the forecast value (with the COVID-19 effect) was significantly lower than the observed value (without the COVID-19 effect), indicating a slowing down of the growth in CO 2 , related to In this study, we focus on an analysis of anthropogenic CO 2 emission over a large urban region (a megacity like Beijing) using Xgas measurements. ...
... The IFS 125 HR data used in the TCCON have been widely accepted as a standard to calibrate portable Fourier transform spectrometer data [9,10]. We calibrate the results from the EM27 spectrometer using the IFS 125 HR Fourier transform spectrometer in Xianghe, Hebei [11]. ...
The COVID-19 pandemic has led to ongoing reductions in economic activity and anthropogenic emissions. Beijing was particular badly affected by lockdown measures during the early months of the COVID-19 pandemic. It has significantly reduced the CO2 emission and toxic air pollution (CO and NO2). We use column-averaged dry-air mole fractions of CO2 and CO (XCO2 and XCO) observed by a ground-based EM27/SUN Fourier transform spectrometer (FTS), the tropospheric NO2 column observed by MAX-DOAS and satellite remote sensing data (GOSAT and TROPOMI) to investigate the variations in anthropogenic CO2 emission related to COVID-19 lockdown in Beijing. The anomalies describe the spatio-temporal enhancement of gas concentration, which relates to the emission. Anomalies in XCO2 and XCO, and XNO2 (ΔXCO2, ΔXCO, and ΔXNO2) for ground-based measurements were calculated from the diurnal variability. Highly correlated daily XCO and XCO2 anomalies derived from FTS time series data provide the ΔXCO to ΔXCO2 ratio (the correlation slope). The ΔXCO to ΔXCO2 ratio in Beijing was lower in 2020 (8.2 ppb/ppm) than in 2019 (9.6 ppb/ppm). The ΔXCO to ΔXCO2 ratio originating from a polluted area was significantly lower in 2020. The reduction in anthropogenic CO2 emission was estimated to be 14.2% using FTS data. A comparable value reflecting the slowdown in growth of atmospheric CO2 over the same time period was estimated to be 15% in Beijing from the XCO2 anomaly from GOSAT, which was derived from the difference between the target area and the background area. The XCO anomaly from TROPOMI is reduced by 8.7% in 2020 compared with 2019, which is much smaller than the reduction in surface air pollution data (17%). Ground-based NO2 observation provides a 21.6% decline in NO2. The NO2 to CO2 correlation indicates a 38.2% decline in the CO2 traffic emission sector. Overall, the reduction in anthropogenic CO2 emission relating to COVID-19 lockdown in Beijing can be detected by the Bruker EM27/SUN Fourier transform spectrometer (FTS) and MAX-DOAS in urban Beijing.
