scholarly journals Detecting the Responses of CO2 Column Abundances to Anthropogenic Emissions from Satellite Observations of GOSAT and OCO-2

2021 ◽  
Vol 13 (17) ◽  
pp. 3524
Author(s):  
Mengya Sheng ◽  
Liping Lei ◽  
Zhao-Cheng Zeng ◽  
Weiqiang Rao ◽  
Shaoqing Zhang
Keyword(s):  
Co2 Emissions ◽  
Urban Areas ◽  
Atmospheric Transport ◽  
Southern Oscillation ◽  
Regional Scale ◽  
Co2 Concentration ◽  
Anthropogenic Emissions ◽  
Urban Agglomerations ◽  
Anthropogenic Co2

The continuing increase in atmospheric CO2 concentration caused by anthropogenic CO2 emissions significantly contributes to climate change driven by global warming. Satellite measurements of long-term CO2 data with global coverage improve our understanding of global carbon cycles. However, the sensitivity of the space-borne measurements to anthropogenic emissions on a regional scale is less explored because of data sparsity in space and time caused by impacts from geophysical factors such as aerosols and clouds. Here, we used global land mapping column averaged dry-air mole fractions of CO2 (XCO2) data (Mapping-XCO2), generated from a spatio-temporal geostatistical method using GOSAT and OCO-2 observations from April 2009 to December 2020, to investigate the responses of XCO2 to anthropogenic emissions at both global and regional scales. Our results show that the long-term trend of global XCO2 growth rate from Mapping-XCO2, which is consistent with that from ground observations, shows interannual variations caused by the El Niño Southern Oscillation (ENSO). The spatial distributions of XCO2 anomalies, derived from removing background from the Mapping-XCO2 data, reveal XCO2 enhancements of about 1.5–3.5 ppm due to anthropogenic emissions and seasonal biomass burning in the wintertime. Furthermore, a clustering analysis applied to seasonal XCO2 clearly reveals the spatial patterns of atmospheric transport and terrestrial biosphere CO2 fluxes, which help better understand and analyze regional XCO2 changes that are associated with atmospheric transport. To quantify regional anomalies of CO2 emissions, we selected three representative urban agglomerations as our study areas, including the Beijing-Tian-Hebei region (BTH), the Yangtze River Delta urban agglomerations (YRD), and the high-density urban areas in the eastern USA (EUSA). The results show that the XCO2 anomalies in winter well capture the several-ppm enhancement due to anthropogenic CO2 emissions. For BTH, YRD, and EUSA, regional positive anomalies of 2.47 ± 0.37 ppm, 2.20 ± 0.36 ppm, and 1.38 ± 0.33 ppm, respectively, can be detected during winter months from 2009 to 2020. These anomalies are slightly higher than model simulations from CarbonTracker-CO2. In addition, we compared the variations in regional XCO2 anomalies and NO2 columns during the lockdown of the COVID-19 pandemic from January to March 2020. Interestingly, the results demonstrate that the variations of XCO2 anomalies have a positive correlation with the decline of NO2 columns during this period. These correlations, moreover, are associated with the features of emitting sources. These results suggest that we can use simultaneously observed NO2, because of its high detectivity and co-emission with CO2, to assist the analysis and verification of CO2 emissions in future studies.

scholarly journals Sensitivity of simulated CO<sub>2</sub> concentration to regridding of global fossil fuel CO<sub>2</sub> emissions

2014 ◽  
Vol 7 (3) ◽  
pp. 3575-3593
Author(s):  
X. Zhang ◽  
K. R. Gurney ◽  
P. Rayner ◽  
Y. Liu ◽  
S. Asefi-Najafabady
Keyword(s):  
Co2 Emissions ◽  
Urban Areas ◽  
Fossil Fuel ◽  
Atmospheric Transport ◽  
Co2 Concentration ◽  
Point Sources ◽  
Atmospheric Co2 ◽  
Atmospheric Co2 Concentration ◽  
Dynamical Consistency ◽  
Oceanic Carbon

Abstract. Errors in the specification or utilization of fossil fuel CO2 emissions within carbon budget or atmospheric CO2 inverse studies can alias the estimation of biospheric and oceanic carbon exchange. A key component in the simulation of CO2 concentrations arising from fossil fuel emissions is the spatial distribution of the emission near coastlines. Finite grid resolution can give rise to mismatches between the emissions and simulated atmospheric dynamics which differ over land or water. We test these mismatches by examining simulated global atmospheric CO2 concentration driven by two different approaches to regridding fossil fuel CO2 emissions. The two approaches are: (1) a commonly-used method that allocates emissions to gridcells with no attempt to ensure dynamical consistency with atmospheric transport; (2) an improved method that reallocates emissions to gridcells to ensure dynamically consistent results. Results show large spatial and temporal differences in the simulated CO2 concentration when comparing these two approaches. The emissions difference ranges from −30.3 Tg C gridcell−1 yr−1 (−3.39 kg C m−2 yr−1) to +30.0 Tg C gridcell−1 yr−1 (+2.6 kg C m−2 yr−1) along coastal margins. Maximum simulated annual mean CO2 concentration differences at the surface exceed ±6 ppm at various locations and times. Examination of the current CO2 monitoring locations during the local afternoon, consistent with inversion modeling system sampling and measurement protocols, finds maximum hourly differences at 38 stations exceed ±0.10 ppm with individual station differences exceeding −32 ppm. The differences implied by not accounting for this dynamical consistency problem are largest at monitoring sites proximal to large coastal urban areas and point sources. These results suggest that studies comparing simulated to observed atmospheric CO2 concentration, such as atmospheric CO2 inversions, must take measures to correct for this potential problem and ensure flux and dynamical consistency.

scholarly journals Long-Term (1951–2007) Rainfall Trends around Six Indian Cities: Current State, Meteorological, and Urban Dynamics

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Shailesh Kumar Kharol ◽  
D. G. Kaskaoutis ◽  
Anu Rani Sharma ◽  
Ramesh P. Singh
Keyword(s):  
Urban Areas ◽  
Statistical Significance ◽  
Spatiotemporal Variability ◽  
Anthropogenic Emissions ◽  
Urban Dynamics ◽  
Current State ◽  
Rainfall Trends ◽  
Indian Cities ◽  
Rainy Days

The present study focuses on analyzing the precipitation trends over six Indian cities during the summer monsoon (June–September) covering the period 1951–2007 and also attempting to investigate possible urban forcing and dynamics by examining the variation in precipitation in the upwind and downwind directions. The analysis shows negative trends in the total number of rainy days over Hyderabad (−10.4%), Kanpur (−7.1%), Jaipur (−10.5%), and Nagpur (−4.8%) and positive trends over Delhi (7.4%) and Bangalore (22.9%). On the other hand, decreases of −21.3%, −5.9%, −14.2%, and −14.6% in seasonal rainfall are found over Delhi, Hyderabad, Jaipur, and Kanpur, respectively, whereas Bangalore and Nagpur show 65.8% and 13.5% increase. The lesser rainfall and rainy days, along with the mostly declining trend, in the downwind directions of the cities may imply an urban influence in precipitation associated with the increased anthropogenic emissions due to expansion of the urban areas and the increase of population. However, the large spatiotemporal variability of precipitation and the lack of statistical significance in the vast majority of the trends do not allow the extraction of safe conclusion concerning the aerosol-precipitation interactions around Indian cities.

scholarly journals Lifetime of Anthropogenic Climate Change: Millennial Time Scales of Potential CO2 and Surface Temperature Perturbations

2009 ◽  
Vol 22 (10) ◽  
pp. 2501-2511 ◽  
Author(s):  
M. Eby ◽  
K. Zickfeld ◽  
A. Montenegro ◽  
D. Archer ◽  
K. J. Meissner ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Temperature Anomaly ◽  
Surface Air Temperature ◽  
Maximum Temperature ◽  
Carbon Cycle Model ◽  
Anthropogenic Co2 ◽  
Climatic Impacts ◽  
Air Temperature Anomaly ◽  
Time Required

Abstract Multimillennial simulations with a fully coupled climate–carbon cycle model are examined to assess the persistence of the climatic impacts of anthropogenic CO2 emissions. It is found that the time required to absorb anthropogenic CO2 strongly depends on the total amount of emissions; for emissions similar to known fossil fuel reserves, the time to absorb 50% of the CO2 is more than 2000 yr. The long-term climate response appears to be independent of the rate at which CO2 is emitted over the next few centuries. Results further suggest that the lifetime of the surface air temperature anomaly might be as much as 60% longer than the lifetime of anthropogenic CO2 and that two-thirds of the maximum temperature anomaly will persist for longer than 10 000 yr. This suggests that the consequences of anthropogenic CO2 emissions will persist for many millennia.

The contribution of countries and world regions in global CO2 emissions as an indicator of changes in the global geo-ecological panorama

2019 ◽  
pp. 120-129
Author(s):  
D. L. Lopatnikov
Keyword(s):  
Co2 Emissions ◽  
Developed Countries ◽  
Spatial Transformation ◽  
The Past ◽  
Anthropogenic Co2 ◽  
Global Environmental ◽  
The World ◽  
The Many ◽  
Long Term Trend

Anthropogenic CO2 emissions are currently considered by the UN and other authoritative international organizations engaged in monitoring changes in the Earth’s biogeosphere as one of the main indicators of the global environmental situation. According to the official Doctrine of Sustainable Development, anthropogenic CO2 emissions are one of the main causes of global warming. The article examines the dynamics of CO2 emissions by countries and regions of the world from the 1970s to the 2010s. The correlation between the volume of CO2 emissions and changes in the overall territorial distribution of the world economy has been demonstrated. Over the past fifty years, the geography of anthropogenic CO2 emissions by countries and macro-regions of the world has changed dramatically. The share of the most economically developed countries in the volume of CO2 emissions has decreased. The main epicenter of anthropogenic CO2 emissions has shifted to the countries belonging to the semi-periphery of the world. The movement of the main foci of anthropogenic CO2 emissions on the world map reflects qualitative shifts in the global geoecological panorama over the past fifty years. The dynamics and spatial transformation of anthropogenic CO2 emissions is an illustration of the long-term trend of the change from negative to positive through the cycle of multidirectional shifts of one of the many ecologically significant processes on Earth.

scholarly journals Detecting long-term changes in point source fossil CO<sub>2</sub> emissions with tree ring archives

2016 ◽  
Author(s):  
E. D. Keller ◽  
J. C. Turnbull ◽  
M. W. Norris
Keyword(s):  
Point Source ◽  
Co2 Emissions ◽  
Tree Ring ◽  
Power Plants ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Model Simulation ◽  
Point Sources ◽  
Long Term Changes

Abstract. We examine the utility of tree ring 14C archives for detecting long term changes in fossil CO2 emissions from a point source. Trees assimilate carbon from the atmosphere during photosynthesis, in the process faithfully recording the average atmospheric 14C content in each new annual tree ring. Using 14C as a proxy for fossil CO2, we examine interannual variability over six years of fossil CO2 observations between 2004-05 and 2011-12 from two trees growing near the Kapuni Natural Gas Plant in rural Taranaki, New Zealand. We quantify the amount of variability that can be attributed to transport and meteorology by simulating constant point source fossil CO2 emissions over the observation period with the atmospheric transport model WindTrax. We compare model simulation results to observations and calculate the amount of change in emissions that we can detect with new observations over annual or multi-year time periods given both measurement uncertainty of 1ppm and the modelled variation in transport. In particular, we ask, what is the minimum amount of change in emissions that we can detect using this method, given a reference period of six years? We find that changes of 42% or more could be detected in a new sample from one year at the same observation location, or 22% in the case of four years of new samples. This threshold lowers and the method becomes more practical the more the size of the signal increases. For point sources 10 times larger than the Kapuni plant (a more typical size for power plants worldwide), it would be possible to detect sustaine d emissions changes on the order of 10% given suitable meteorology and observations.

scholarly journals Regional uncertainty of GOSAT XCO<sub>2</sub> retrievals in China: quantification and attribution

2018 ◽  
Vol 11 (3) ◽  
pp. 1251-1272 ◽  
Author(s):  
Nian Bie ◽  
Liping Lei ◽  
ZhaoCheng Zeng ◽  
Bofeng Cai ◽  
Shaoyuan Yang ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Land Surface ◽  
Transport Model ◽  
Point Sources ◽  
Western Desert ◽  
Anthropogenic Emissions ◽  
Desert Grassland ◽  
Chemical Transport Model ◽  
Anthropogenic Co2 ◽  
Comparison Results

Abstract. The regional uncertainty of the column-averaged dry air mole fraction of CO2 (XCO2) retrieved using different algorithms from the Greenhouse gases Observing SATellite (GOSAT) and its attribution are still not well understood. This paper investigates the regional performance of XCO2 within a latitude band of 37–42° N segmented into 8 cells in a grid of 5° from west to east (80–120° E) in China, where typical land surface types and geographic conditions exist. The former includes desert, grassland and built-up areas mixed with cropland; and the latter includes anthropogenic emissions that change from small to large from west to east, including those from the megacity of Beijing. For these specific cells, we evaluate the regional uncertainty of GOSAT XCO2 retrievals by quantifying and attributing the consistency of XCO2 retrievals from four algorithms (ACOS, NIES, OCFP and SRFP) by intercomparison. These retrievals are then specifically compared with simulated XCO2 from the high-resolution nested model in East Asia of the Goddard Earth Observing System 3-D chemical transport model (GEOS-Chem). We also introduce the anthropogenic CO2 emissions data generated from the investigation of surface emitting point sources that was conducted by the Ministry of Environmental Protection of China to GEOS-Chem simulations of XCO2 over the Chinese mainland. The results indicate that (1) regionally, the four algorithms demonstrate smaller absolute biases of 0.7–1.1 ppm in eastern cells, which are covered by built-up areas mixed with cropland with intensive anthropogenic emissions, than those in the western desert cells (1.0–1.6 ppm) with a high-brightness surface from the pairwise comparison results of XCO2 retrievals. (2) Compared with XCO2 simulated by GEOS-Chem (GEOS-XCO2), the XCO2 values from ACOS and SRFP have better agreement, while values from OCFP are the least consistent with GEOS-XCO2. (3) Viewing attributions of XCO2 in the spatio-temporal pattern, ACOS and SRFP demonstrate similar patterns, while OCFP is largely different from the others. In conclusion, the discrepancy in the four algorithms is the smallest in eastern cells in the study area, where the megacity of Beijing is located and where there are strong anthropogenic CO2 emissions, which implies that XCO2 from satellite observations could be reliably applied in the assessment of atmospheric CO2 enhancements induced by anthropogenic CO2 emissions. The large inconsistency among the four algorithms presented in western deserts which displays a high albedo and dust aerosols, moreover, demonstrates that further improvement is still necessary in such regions, even though many algorithms have endeavored to minimize the effects of aerosols scattering and surface albedo.

scholarly journals Anthropogenic carbon dioxide source areas observed from space: assessment of regional enhancements and trends

2012 ◽  
Vol 12 (12) ◽  
pp. 31507-31530
Author(s):  
O. Schneising ◽  
J. Heymann ◽  
M. Buchwitz ◽  
M. Reuter ◽  
H. Bovensmann ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Urban Areas ◽  
Yangtze River ◽  
The United States ◽  
Yangtze River Delta ◽  
River Delta ◽  
Anthropogenic Emissions ◽  
World Population ◽  
Positive Trend ◽  
Anthropogenic Co2

Abstract. Urban areas, which are home to the majority of today's world population, are responsible for more than two-thirds of the global energy-related carbon dioxide emissions. Given the ongoing demographic growth and rising energy consumption in metropolitan regions particularly in the developing world, urban-based emissions are expected to further increase in the future. As a consequence, monitoring and independent verification of reported anthropogenic emissions is becoming more and more important. It is demonstrated using SCIAMACHY nadir measurements that anthropogenic CO2 emissions can be detected from space and that emission trends might be tracked using satellite observations. This is promising with regard to future satellite missions with high spatial resolution and wide swath imaging capability aiming at constraining anthropogenic emissions down to the point-source scale. By subtracting retrieved background values from those retrieved over urban areas we find significant CO2 enhancements for several anthropogenic source regions, namely 1.3 &amp;pm; 0.7 ppm for the Rhine-Ruhr metropolitan region and the Benelux, 1.1 &amp;pm; 0.5 ppm for the East Coast of the United States, and 2.4 &amp;pm; 0.9 ppm for the Yangtze River Delta. The order of magnitude of the enhancements is in agreement with what is expected for anthropogenic CO2 signals. The larger standard deviation of the retrieved Yangtze River Delta enhancement is due to a distinct positive trend of 0.3 &amp;pm; 0.2 ppm yr−1, which is quantitatively consistent with anthropogenic emissions from the Emission Database for Global Atmospheric Research (EDGAR) in terms of percentual increase per year. Potential contributions to the retrieved CO2 enhancement by several error sources, e.g. aerosols, albedo, and residual biospheric signals due to heterogeneous seasonal sampling, are discussed and can be ruled out to a large extent.

scholarly journals Neural-network-based estimation of regional-scale anthropogenic CO<sub>2</sub> emissions using an Orbiting Carbon Observatory-2 (OCO-2) dataset over East and West Asia

2021 ◽  
Vol 14 (11) ◽  
pp. 7277-7290
Author(s):  
Farhan Mustafa ◽  
Lingbing Bu ◽  
Qin Wang ◽  
Na Yao ◽  
Muhammad Shahzaman ◽  
...  
Keyword(s):  
Neural Network ◽  
Carbon Dioxide ◽  
Co2 Emissions ◽  
Co2 Emission ◽  
Net Primary Productivity ◽  
Regional Scale ◽  
Mitigation Strategies ◽  
Generalized Regression Neural Network ◽  
Anthropogenic Co2 ◽  
East And West

Abstract. Atmospheric carbon dioxide (CO2) is the most significant greenhouse gas, and its concentration is continuously increasing, mainly as a consequence of anthropogenic activities. Accurate quantification of CO2 is critical for addressing the global challenge of climate change and for designing mitigation strategies aimed at stabilizing CO2 emissions. Satellites provide the most effective way to monitor the concentration of CO2 in the atmosphere. In this study, we utilized the concentration of the column-averaged dry-air mole fraction of CO2, i.e., XCO2 retrieved from a CO2 monitoring satellite, the Orbiting Carbon Observatory-2 (OCO-2), and the net primary productivity (NPP) provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate the anthropogenic CO2 emissions using the Generalized Regression Neural Network (GRNN) over East and West Asia. OCO-2 XCO2, MODIS NPP, and the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) CO2 emission datasets for a period of 5 years (2015–2019) were used in this study. The annual XCO2 anomalies were calculated from the OCO-2 retrievals for each year to remove the larger background CO2 concentrations and seasonal variability. The XCO2 anomaly, NPP, and ODIAC emission datasets from 2015 to 2018 were then used to train the GRNN model, and, finally, the anthropogenic CO2 emissions were estimated for 2019 based on the NPP and XCO2 anomalies derived for the same year. The estimated and the ODIAC CO2 emissions were compared, and the results showed good agreement in terms of spatial distribution. The CO2 emissions were estimated separately over East and West Asia. In addition, correlations between the ODIAC emissions and XCO2 anomalies were also determined separately for East and West Asia, and East Asia exhibited relatively better results. The results showed that satellite-based XCO2 retrievals can be used to estimate the regional-scale anthropogenic CO2 emissions, and the accuracy of the results can be enhanced by further improvement of the GRNN model with the addition of more CO2 emission and concentration datasets.

scholarly journals Decreasing Trends of Particle Number and Black Carbon Mass Concentrations at 16 Observational Sites in Germany from 2009 to 2018

2019 ◽  
Author(s):  
Jia Sun ◽  
Wolfram Birmili ◽  
Markus Hermann ◽  
Thomas Tuch ◽  
Kay Weinhold ◽  
...  
Keyword(s):  
Time Series ◽  
Black Carbon ◽  
Urban Areas ◽  
Mass Concentration ◽  
Particle Number ◽  
Regional Scale ◽  
Particle Diameter ◽  
Anthropogenic Emissions ◽  
Mitigation Policies ◽  
Mass Concentrations

Abstract. Anthropogenic emissions are a dominant contributor to air pollution. Consequently, mitigation policies have attempted to reduce anthropogenic pollution emissions in Europe since the 1990s. To evaluate the effectiveness of these mitigation policies, the German Ultrafine Aerosol Network (GUAN) was established in 2008, focusing on black carbon and sub-micrometer aerosol particles, especially ultrafine particles. In this investigation, trends of the size-resolved particle number concentrations (PNC) and the equivalent black carbon (eBC) mass concentration over a 10-year period (2009–2018) were evaluated for 16 observational sites for different environments among GUAN. The trend analysis was done for both, the full-length time series and on subsets of the time series in order to test the reliability of the results. The results show generally decreasing trends of both, the PNCs for all size ranges as well as eBC mass concentrations in all environments, except PNC in 10–30 nm at regional background and mountain sites. The annual slope of the eBC mass concentration varies between −7.7 % and −1.8 % per year. The slopes of the PNCs varies from −6.3 % to 2.7 %, −7.0 % to −2.0 %, and −9.5 % to −1.5 % per year (only significant trends) for 10–30 nm, 30–200 nm, and 200–800 nm particle diameter, respectively. The regional Mann-Kendall test yielded regional-scale trends of eBC mass concentration, N[30–200] and N[200–800] of −3.8 %, −2.0 % and −2.4 %, respectively, indicating an overall decreasing trend for eBC mass concentration and sub-micrometer PNC (except N[10–30]) all over Germany. The most significant decrease was observed on working days and during daytime in urban areas, which implies a strong evidence of reduced anthropogenic emissions. For the seasonal trends, stronger reductions were observed in winter. Possible reasons for this reduction can be the increased average ambient temperatures and wind speed in winter, which resulted in less domestic heating and stronger dilution. In addition, decreased precipitation in summer also diminishes the decrease of the PNCs and eBC mass concentration. For the period of interest, there were no significant changes in long-range transport patterns. The most likely factors for the observed decreasing trends are declining anthropogenic emissions due to emission mitigation policies of the European Union.

scholarly journals Regional uncertainty of GOSAT XCO<sub>2</sub> retrievals in China: Quantification and attribution

2017 ◽  
Author(s):  
Nian Bie ◽  
Liping Lei ◽  
Zhaocheng Zeng ◽  
Bofeng Cai ◽  
Shaoyuan Yang ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Land Surface ◽  
Transport Model ◽  
Point Sources ◽  
Western Desert ◽  
Anthropogenic Emissions ◽  
Taklimakan Desert ◽  
Dust Aerosols ◽  
Anthropogenic Co2 ◽  
Comparison Results

Abstract. The regional uncertainty of XCO2 (column-averaged dry air mole fraction of CO2) retrieved using different algorithms from the Greenhouse gases Observing SATellite (GOSAT) and its attribution are still not well understood. This paper investigates the regional performance of XCO2 within a band of 37° N–42° N segmented into 8 cells in a grid of 5° from west to east (80° E–120° E) in China, where there are typical land surface types and geographic conditions. The former include the various land covers of desert, grassland and built-up areas mixed with cropland, and the latter include anthropogenic emissions that tend to be small to large from west to east, including those from the megacity of Beijing. For these specific cells, we evaluate the regional uncertainty of GOSAT XCO2 retrievals by quantifying and attributing the consistency of XCO2 retrievals from five algorithms (ACOS, NIES, EMMA, OCFP, and SRFP) by intercomparison and particularly by comparing these with simulated XCO2 from the Goddard Earth Observing System 3-D chemical transport model (GEOS-Chem), the nested model in East Asia. We introduce the anthropogenic CO2 emissions data generated from the investigation of surface emitting point sources that was conducted by the Ministry of Environmental Protection of China to GEOS-Chem simulations of XCO2 over the Chinese mainland. The results indicate that (1) regionally, the five algorithms demonstrate smaller absolute biases between 0.9–1.5 ppm in eastern cells, which are covered by built-up areas mixed with cropland with intensive anthropogenic emissions, than those in the western desert cells with a high-brightness surface, 1.2–2.2 ppm from the pairwise comparison results of XCO2 retrievals. The inconsistency of XCO2 from the five algorithms tends to be high in the Taklimakan Desert in western cells, which is likely induced by high surface albedo in addition to dust aerosols in this region. (2) Compared with XCO2 simulated by GEOS-Chem (GEOS-XCO2), the XCO2 values of ACOS and SRFP better agree with GEOS-XCO2, while OCFP is the least consistent with GEOS-XCO2. (3) Viewing attributions of XCO2 in the spatio-temporal pattern, ACOS, SRFP and EMMA demonstrate similar patterns, while OCFP is largely different from the others. In conclusion, the discrepancy in the five algorithms is the smallest in eastern cells in the investigated band where the megacity of Beijing is located and where there are strong anthropogenic CO2 emissions, which implies that XCO2 from satellite observations could be reliably applied in the assessment of atmospheric CO2 enhancements induced by anthropogenic CO2 emissions. The large inconsistency among the five algorithms presented in western deserts with a high albedo and dust aerosols, moreover, demonstrates that further improvement is still necessary in such regions, even though many algorithms have endeavored to minimize the effects of aerosols and albedo.

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