scholarly journals Quantitative evaluation of the uncertainty sources for the modeling of atmospheric CO<sub>2</sub> concentration within and in the vicinity of Paris city

2020 ◽  
Author(s):  
Jinghui Lian ◽  
François-Marie Bréon ◽  
Grégoire Broquet ◽  
Bo Zheng ◽  
Michel Ramonet ◽  
...  
Keyword(s):  
Boundary Conditions ◽  
Co2 Emissions ◽  
Large Scale ◽  
Transport Model ◽  
Co2 Concentration ◽  
Inversion Method ◽  
Different Boundary Conditions ◽  
Paris Area ◽  
The City ◽  
Atmospheric Inversion

Abstract. The top-down atmospheric inversion method that couples atmospheric CO2 observations with an atmospheric transport model has been used extensively to quantify CO2 emissions from cities. However, the potential of the method is limited by several sources of misfits between the measured and modeled CO2 that are of different origins than the targeted CO2 emissions. This study investigates the critical sources of errors that can compromise the estimates of the city-scale emissions and identifies the signal of emissions that has to be filtered when doing inversions. A set of one-year forward simulations is carried out using the WRF-Chem model at a horizontal resolution of 1 km focusing on the Paris area with different anthropogenic emission inventories, physical parameterizations and CO2 boundary conditions. The simulated CO2 concentrations are compared with in situ observations from six continuous monitoring stations located within Paris and its vicinity. Results highlight large nighttime observation-model misfits, especially in winter within the city, which are attributed to large uncertainties in the diurnal profile of anthropogenic emissions as well as to errors in the vertical mixing near the surface in the WRF-Chem model. The nighttime biogenic respiration to the CO2 concentration is a significant source of modeling errors during the growing season outside the city. When winds are from continental Europe and the CO2 concentration of incoming air masses is influenced by remote emissions and large-scale biogenic fluxes, differences in the simulated CO2 induced by the two different boundary conditions (CAMS and CarbonTracker) can be of up to 5 ppm. Our results suggest three selection criteria for the CO2 data to be assimilated for the inversion of CO2 emissions from Paris (i) discard data that appear as statistical outliers in the model-data misfits which are interpreted as model's deficiencies under complex meteorological conditions; (ii) use only afternoon urban measurements in winter and suburban ones in summer; (iii) test the influence of different boundary conditions in inversions. If possible, using additional observations to constrain the boundary inflow, or using CO2 gradients of upwind-downwind stations, rather than absolute CO2 concentration, as atmospheric inversion inputs.

scholarly journals Sensitivity to the sources of uncertainties in the modeling of atmospheric CO<sub>2</sub> concentration within and in the vicinity of Paris

2021 ◽  
Vol 21 (13) ◽  
pp. 10707-10726
Author(s):  
Jinghui Lian ◽  
François-Marie Bréon ◽  
Grégoire Broquet ◽  
Thomas Lauvaux ◽  
Bo Zheng ◽  
...  
Keyword(s):  
Boundary Conditions ◽  
Co2 Emissions ◽  
Vertical Mixing ◽  
Co2 Concentration ◽  
Atmospheric Modeling ◽  
Inversion Method ◽  
Model Data ◽  
Co2 Concentrations ◽  
Paris Area ◽  
The City

Abstract. The top-down atmospheric inversion method that couples atmospheric CO2 observations with an atmospheric transport model has been used extensively to quantify CO2 emissions from cities. However, the potential of the method is limited by several sources of misfits between the measured and modeled CO2 that are of different origins than the targeted CO2 emissions. This study investigates the critical sources of errors that can compromise the estimates of the city-scale emissions and identifies the signal of emissions that has to be filtered when doing inversions. A set of 1-year forward simulations is carried out using the WRF-Chem model at a horizontal resolution of 1 km focusing on the Paris area with different anthropogenic emission inventories, physical parameterizations, and CO2 boundary conditions. The simulated CO2 concentrations are compared with in situ observations from six continuous monitoring stations located within Paris and its vicinity. Results highlight large nighttime model–data misfits, especially in winter within the city, which are attributed to large uncertainties in the diurnal profile of anthropogenic emissions as well as to errors in the vertical mixing near the surface in the WRF-Chem model. The nighttime biogenic respiration to the CO2 concentration is a significant source of modeling errors during the growing season outside the city. When winds are from continental Europe and the CO2 concentration of incoming air masses is influenced by remote emissions and large-scale biogenic fluxes, differences in the simulated CO2 induced by the two different boundary conditions (CAMS and CarbonTracker) can be of up to 5 ppm. Nevertheless, our results demonstrate the potential of our optimal CO2 atmospheric modeling system to be utilized in atmospheric inversions of CO2 emissions over the Paris metropolitan area. We evaluated the model performances in terms of wind, vertical mixing, and CO2 model–data mismatches, and we developed a filtering algorithm for outliers due to local contamination and unfavorable meteorological conditions. Analysis of model–data misfit indicates that future inversions at the mesoscale should only use afternoon urban CO2 measurements in winter and suburban measurements in summer. Finally, we determined that errors related to CO2 boundary conditions can be overcome by including distant background observations to constrain the boundary inflow or by assimilating CO2 gradients of upwind–downwind stations rather than by assimilating absolute CO2 concentrations.

Assessing the effectiveness of an urban CO2 monitoring network through the COVID-19 lockdown natural experiment

2021 ◽  
Author(s):  
Jinghui Lian ◽  
Thomas Lauvaux ◽  
Hervé Utard ◽  
Grégoire Broquet ◽  
François-Marie Bréon ◽  
...  
Keyword(s):  
Real Time ◽  
Co2 Emissions ◽  
Transport Model ◽  
Monitoring Network ◽  
Co2 Concentration ◽  
Mitigation Measures ◽  
Potential Contribution ◽  
Activity Data ◽  
Co2 Monitoring ◽  
The City

&lt;p&gt;Quantitative monitoring of CO2 sources and sinks over cities is needed to support the urban adaptation and mitigation measures, but it is a challenging task. The Paris metropolitan area is a highly built-up and densely populated region in France. The two national COVID-19 forced confinements that are 1) effective on March 17th, with a duration of 55 days until May 11th, 2) effective on October 30th, with a duration of 46 days until December 15th provide an opportunity to assess the behaviour and robustness of the dedicated atmospheric inversion system for estimating the city-scale CO2 emissions.&lt;/p&gt;&lt;p&gt;In this study, the atmospheric Bayesian inversion approach that couples six in-situ continuous CO2 monitoring stations with the WRF-Chem transport model at 1-km horizontal resolutions has been used to quantify the impacts of lockdown on CO&lt;sub&gt;2&lt;/sub&gt; emissions for the Paris megacity. The prior emission estimate was from the Origins inventory, a near-real-time dataset of fossil fuel CO2 emissions by sector (transportation, residential, tertiary, industry and sink) at 1km&amp;#178; and hourly resolution recently developed by Origins.earth. Estimates of CO2 emissions were retrieved from the inversion by assimilating CO2 concentration gradients between upwind-downwind stations using a refined configuration of the existing Parisian inversion system developed by Br&amp;#233;on et al. (2015) and Staufer et al. (2016). A set of experiments was performed to assess the sensitivity of the posterior CO2 estimates to the changes in different inversion setups, including the selection of observations, prior flux uncertainties and error correlations. We also analyzed the potential contribution of the expanding CO2 monitoring network, in particular the two newly built urban stations in the city center since 2014, to the inverse modeling systems.&lt;/p&gt;&lt;p&gt;The optimized CO2 estimates show decreases of around 42% and 25% in anthropogenic CO2 emissions during the first and second lockdowns respectively when compared with the same period in past two years. Both lockdown emission reduction estimates from the inversion are consistent with recent estimates from activity data (resp. 37% and 19%), suggesting that our near-real time monitoring system is able to detect and quantify short-term variations at the whole-city level.&lt;/p&gt;

scholarly journals Atmospheric inversion for cost effective quantification of city CO<sub>2</sub> emissions

2015 ◽  
Vol 15 (21) ◽  
pp. 30693-30756 ◽  
Author(s):  
L. Wu ◽  
G. Broquet ◽  
P. Ciais ◽  
V. Bellassen ◽  
F. Vogel ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Land Surface ◽  
Power Plants ◽  
Energy Use ◽  
Residential Buildings ◽  
Co2 Concentration ◽  
Road Transport ◽  
Inversion Method ◽  
Atmospheric Measurements ◽  
Atmospheric Inversion

Abstract. Cities, currently covering only a very small portion (< 3 %) of the world's land surface, directly release to the atmosphere about 44 % of global energy-related CO2, and are associated with 71–76 % of CO2 emissions from global final energy use. Although many cities have set voluntary climate plans, their CO2 emissions are not evaluated by Monitoring, Reporting and Verification (MRV) procedures that play a key role for market- or policy-based mitigation actions. Here we propose a monitoring tool that could support the development of such procedures at the city scale. It is based on an atmospheric inversion method that exploits inventory data and continuous atmospheric CO2 concentration measurements from a network of stations within and around cities to estimate city CO2 emissions. We examine the cost-effectiveness and the performance of such a tool. The instruments presently used to measure CO2 concentrations at research stations are expensive. However, cheaper sensors are currently developed and should be useable for the monitoring of CO2 emissions from a megacity in the near-term. Our assessment of the inversion method is thus based on the use of several types of hypothetical networks, with a range of numbers of sensors sampling at 25 m a.g.l. The study case for this assessment is the monitoring of the emissions of the Paris metropolitan area (~ 12 million inhabitants and 11.4 Tg C emitted in 2010) during the month of January 2011. The performance of the inversion is evaluated in terms of uncertainties in the estimates of total and sectoral CO2 emissions. These uncertainties are compared to a notional ambitious target to diagnose annual total city emissions with an uncertainty of 5 % (2-sigma). We find that, with 10 stations only, which is the typical size of current pilot networks that are deployed in some cities, the uncertainty for the 1-month total city CO2 emissions is significantly reduced by the inversion by ~ 42 % but still corresponds to an annual uncertainty that is two times larger than the target of 5 %. By extending the network from 10 to 70 stations, the inversion can meet this requirement. As for major sectoral CO2 emissions, the uncertainties in the inverted emissions using 70 stations are reduced significantly over that obtained using 10 stations by 32 % for commercial and residential buildings, by 33 % for road transport and by 18 % for the production of energy by power plants, respectively. With 70 stations, the uncertainties from the inversion become of 15 % 2-sigma annual uncertainty for dispersed building emissions, and 18 % for emissions from road transport and energy production. The inversion performance could be further improved by optimal design of station locations and/or by assimilating additional atmospheric measurements of species that are co-emitted with CO2 by fossil fuel combustion processes with a specific signature from each sector, such as carbon monoxide (CO). Atmospheric inversions based on continuous CO2 measurements from a large number of cheap sensors can thus deliver a valuable quantification tool for the monitoring and/or the verification of city CO2 emissions (baseline) and CO2 emission reductions (commitments).

scholarly journals An attempt at estimating Paris area CO<sub>2</sub> emissions from atmospheric concentration measurements

2015 ◽  
Vol 15 (4) ◽  
pp. 1707-1724 ◽  
Author(s):  
F. M. Bréon ◽  
G. Broquet ◽  
V. Puygrenier ◽  
F. Chevallier ◽  
I. Xueref-Remy ◽  
...  
Keyword(s):  
Urban Area ◽  
Co2 Emissions ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Co2 Concentration ◽  
Surface Fluxes ◽  
Atmospheric Concentration ◽  
Paris Area ◽  
Direct Model ◽  
Concentration Measurements

Abstract. Atmospheric concentration measurements are used to adjust the daily to monthly budget of fossil fuel CO2 emissions of the Paris urban area from the prior estimates established by the Airparif local air quality agency. Five atmospheric monitoring sites are available, including one at the top of the Eiffel Tower. The atmospheric inversion is based on a Bayesian approach, and relies on an atmospheric transport model with a spatial resolution of 2 km with boundary conditions from a global coarse grid transport model. The inversion adjusts prior knowledge about the anthropogenic and biogenic CO2 fluxes from the Airparif inventory and an ecosystem model, respectively, with corrections at a temporal resolution of 6 h, while keeping the spatial distribution from the emission inventory. These corrections are based on assumptions regarding the temporal autocorrelation of prior emissions uncertainties within the daily cycle, and from day to day. The comparison of the measurements against the atmospheric transport simulation driven by the a priori CO2 surface fluxes shows significant differences upwind of the Paris urban area, which suggests a large and uncertain contribution from distant sources and sinks to the CO2 concentration variability. This contribution advocates that the inversion should aim at minimising model–data misfits in upwind–downwind gradients rather than misfits in mole fractions at individual sites. Another conclusion of the direct model–measurement comparison is that the CO2 variability at the top of the Eiffel Tower is large and poorly represented by the model for most wind speeds and directions. The model's inability to reproduce the CO2 variability at the heart of the city makes such measurements ill-suited for the inversion. This and the need to constrain the budgets for the whole city suggests the assimilation of upwind–downwind mole fraction gradients between sites at the edge of the urban area only. The inversion significantly improves the agreement between measured and modelled concentration gradients. Realistic emissions are retrieved for two 30-day periods and suggest a significant overestimate by the AirParif inventory. Similar inversions over longer periods are necessary for a proper evaluation of the optimised CO2 emissions against independent data.

scholarly journals Carbon balance of China constrained by CONTRAIL aircraft CO<sub>2</sub> measurements

2014 ◽  
Vol 14 (6) ◽  
pp. 7683-7709
Author(s):  
F. Jiang ◽  
H. M. Wang ◽  
J. M. Chen ◽  
T. Machida ◽  
L. X. Zhou ◽  
...  
Keyword(s):  
Transport Model ◽  
Carbon Sink ◽  
Terrestrial Ecosystem ◽  
Co2 Flux ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Inversion Method ◽  
Climate Factors ◽  
Mean Climate ◽  
Atmospheric Co2 Concentrations

Abstract. Terrestrial CO2 flux estimates in China using atmospheric inversion method are beset with considerable uncertainties because very few atmospheric CO2 concentration measurements are available. In order to improve these estimates, nested atmospheric CO2 inversion during 2002–2008 is performed in this study using passenger aircraft-based CO2 measurements over Eurasia from the Comprehensive Observation Network for Trace gases by Airliner (CONTRAIL) project. The inversion system includes 43 regions with a focus on China, and is based on the Bayesian synthesis approach and the TM5 transport model. The terrestrial ecosystem carbon flux modeled by the BEPS model and the ocean exchange simulated by the OPA-PISCES-T model are considered as the prior fluxes. The impacts of CONTRAIL CO2 data on inverted China terrestrial carbon fluxes are quantified, the improvement of the inverted fluxes after adding CONTRAIL CO2 data are rationed against climate factors and evaluated by comparing the simulated atmospheric CO2 concentrations with three independent surface CO2 measurements in China. Results show that with the addition of CONTRAIL CO2 data, the inverted carbon sink in China increases while those in South and Southeast Asia decrease. Meanwhile, the posterior uncertainties over these regions are all reduced. CONTRAIL CO2 data also have a large effect on the inter-annual variation of carbon sinks in China, leading to a better correlation between the carbon sink and the annual mean climate factors. Evaluations against the CO2 measurements at three sites in China also show that the CONTRAIL CO2 measurements have improved the inversion results.

scholarly journals An attempt at estimating Paris area CO<sub>2</sub> emissions from atmospheric concentration measurements

2014 ◽  
Vol 14 (7) ◽  
pp. 9647-9703 ◽  
Author(s):  
F. M. Bréon ◽  
G. Broquet ◽  
V. Puygrenier ◽  
F. Chevallier ◽  
I. Xueref-Rémy ◽  
...  
Keyword(s):  
Boundary Conditions ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Current System ◽  
A Priori ◽  
Temporal Correlation ◽  
Atmospheric Concentration ◽  
Sources And Sinks ◽  
Paris Area ◽  
Concentration Measurements

Abstract. Atmospheric concentration measurements are used to adjust the daily to monthly budget of CO2 emissions from the AirParif inventory of the Paris agglomeration. We use 5 atmospheric monitoring sites including one at the top of the Eiffel tower. The atmospheric inversion is based on a Bayesian approach, and relies on an atmospheric transport model with a spatial resolution of 2 km with boundary conditions from a global coarse grid transport model. The inversion tool adjusts the CO2 fluxes (anthropogenic and biogenic) with a temporal resolution of 6 h, assuming temporal correlation of emissions uncertainties within the daily cycle and from day to day, while keeping the a priori spatial distribution from the emission inventory. The inversion significantly improves the agreement between measured and modelled concentrations. However, the amplitude of the atmospheric transport errors is often large compared to the CO2 gradients between the sites that are used to estimate the fluxes, in particular for the Eiffel tower station. In addition, we sometime observe large model-measurement differences upwind from the Paris agglomeration, which confirms the large and poorly constrained contribution from distant sources and sinks included in the prescribed CO2 boundary conditions These results suggest that (i) the Eiffel measurements at 300 m above ground cannot be used with the current system and (ii) the inversion shall rely on the measured upwind-downwind gradients rather than the raw mole fraction measurements. With such setup, realistic emissions are retrieved for two 30 day periods. Similar inversions over longer periods are necessary for a proper evaluation of the results.

scholarly journals The potential of satellite spectro-imagery for monitoring CO<sub>2</sub> emissions from large cities

2017 ◽  
Author(s):  
Grégoire Broquet ◽  
François-Marie Bréon ◽  
Emmanuel Renault ◽  
Michael Buchwitz ◽  
Maximilian Reuter ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Measurement Errors ◽  
Transport Model ◽  
Atmospheric Transport ◽  
European Space Agency ◽  
Image Resolution ◽  
Spatial Coverage ◽  
Paris Area ◽  
The Impact ◽  
Atmospheric Transport Model

Abstract. This study assesses the potential of 2 to 10 km resolution imagery of CO2 concentrations retrieved from the Short Wave Infra Red measurements of a space borne passive spectrometer for monitoring the spatially integrated emissions from the Paris area. Such imagery could be provided by missions similar to CarbonSat, which was studied as a candidate Earth Explorer 8 mission by the European Space Agency (ESA). This assessment is based on Observing System Simulation Experiments (OSSEs) with an atmospheric inversion approach at city scale. The inversion system solves for hourly city CO2 emissions and natural fluxes, or for these fluxes per main anthropogenic sector or ecosystem, during the 6 hours before a given satellite overpass. These 6 hours correspond to the period during which emissions produce CO2 plumes that can be identified on the image from this overpass. The statistical framework of the inversion accounts for the existence of some prior knowledge about the hourly emissions from an inventory based on energy use and carbon fuel consumption statistics. The link between the hourly or sectorial emissions and the vertically-integrated column of CO2 observed by the satellite is simulated using a coupled flux and atmospheric transport model. This coupled model is built with the information on the spatial and temporal distribution of emissions from the emission inventory produced by the local air-quality agency (Airparif) and a 2 km horizontal resolution atmospheric transport model. Tests are conducted for different realistic simulations of the spatial coverage, resolution, precision and accuracy of the imagery from sun-synchronous polar-orbing missions, corresponding to the specifications of CarbonSat and Sentinel-5 or extrapolated from these specifications. First, OSSEs are conducted with a rather optimistic configuration in which the inversion system is perfectly informed about the statistics of the limited number of error sources. These OSSEs indicate that the image resolution has to be finer than 4 km to decrease the uncertainty in the 6-hour mean emissions by more than 50 %. More complex experiments assess the impact of more realistic error estimates that current inversion methods do not properly account for, in particular the systematic measurement errors with spatially correlated patterns. These experiments highlight the difficulty to improve current knowledge on CO2 emissions for urban areas like Paris with CO2 observations from satellites, and call for more technological innovations in the remote sensing of vertically integrated columns of CO2 and in the inversion systems that exploit it.

scholarly journals Carbon balance of China constrained by CONTRAIL aircraft CO<sub>2</sub> measurements

2014 ◽  
Vol 14 (18) ◽  
pp. 10133-10144 ◽  
Author(s):  
F. Jiang ◽  
H. M. Wang ◽  
J. M. Chen ◽  
T. Machida ◽  
L. X. Zhou ◽  
...  
Keyword(s):  
Transport Model ◽  
Carbon Sink ◽  
Terrestrial Ecosystem ◽  
Co2 Flux ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Inversion Method ◽  
Climate Factors ◽  
Terrestrial Carbon ◽  
Atmospheric Co2 Concentrations

Abstract. Terrestrial carbon dioxide (CO2) flux estimates in China using atmospheric inversion method are beset with considerable uncertainties because very few atmospheric CO2 concentration measurements are available. In order to improve these estimates, nested atmospheric CO2 inversion during 2002–2008 is performed in this study using passenger aircraft-based CO2 measurements over Eurasia from the Comprehensive Observation Network for Trace gases by Airliner (CONTRAIL) project. The inversion system includes 43 regions with a focus on China, and is based on the Bayesian synthesis approach and the TM5 transport model. The terrestrial ecosystem carbon flux modeled by the Boreal Ecosystems Productivity Simulator (BEPS) model and the ocean exchange simulated by the OPA-PISCES-T model are considered as the prior fluxes. The impacts of CONTRAIL CO2 data on inverted China terrestrial carbon fluxes are quantified, the improvement of the inverted fluxes after adding CONTRAIL CO2 data are rationed against climate factors and evaluated by comparing the simulated atmospheric CO2 concentrations with three independent surface CO2 measurements in China. Results show that with the addition of CONTRAIL CO2 data, the inverted carbon sink in China increases while those in South and Southeast Asia decrease. Meanwhile, the posterior uncertainties over these regions are all reduced (2–12%). CONTRAIL CO2 data also have a large effect on the inter-annual variation of carbon sinks in China, leading to a better correlation between the carbon sink and the annual mean climate factors. Evaluations against the CO2 measurements at three sites in China also show that the CONTRAIL CO2 measurements may have improved the inversion results.

scholarly journals The potential of satellite spectro-imagery for monitoring CO<sub>2</sub> emissions from large cities

2018 ◽  
Vol 11 (2) ◽  
pp. 681-708 ◽  
Author(s):  
Grégoire Broquet ◽  
François-Marie Bréon ◽  
Emmanuel Renault ◽  
Michael Buchwitz ◽  
Maximilian Reuter ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Measurement Errors ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Image Resolution ◽  
Spatial Coverage ◽  
Paris Area ◽  
Infrared Measurements ◽  
The Impact ◽  
Atmospheric Transport Model

Abstract. This study assesses the potential of 2 to 10 km resolution imagery of CO2 concentrations retrieved from the shortwave infrared measurements of a space-borne passive spectrometer for monitoring the spatially integrated emissions from the Paris area. Such imagery could be provided by missions similar to CarbonSat, which was studied as a candidate Earth Explorer 8 mission by the European Space Agency (ESA). This assessment is based on observing system simulation experiments (OSSEs) with an atmospheric inversion approach at city scale. The inversion system solves for hourly city CO2 emissions and natural fluxes, or for these fluxes per main anthropogenic sector or ecosystem, during the 6 h before a given satellite overpass. These 6 h correspond to the period during which emissions produce CO2 plumes that can be identified on the image from this overpass. The statistical framework of the inversion accounts for the existence of some prior knowledge with 50 % uncertainty on the hourly or sectorial emissions, and with ∼ 25 % uncertainty on the 6 h mean emissions, from an inventory based on energy use and carbon fuel consumption statistics. The link between the hourly or sectorial emissions and the vertically integrated column of CO2 observed by the satellite is simulated using a coupled flux and atmospheric transport model. This coupled model is built with the information on the spatial and temporal distribution of emissions from the emission inventory produced by the local air-quality agency (Airparif) and a 2 km horizontal resolution atmospheric transport model. Tests are conducted for different realistic simulations of the spatial coverage, resolution, precision and accuracy of the imagery from sun-synchronous polar-orbiting missions, corresponding to the specifications of CarbonSat and Sentinel-5 or extrapolated from these specifications. First, OSSEs are conducted with a rather optimistic configuration in which the inversion system is perfectly informed about the statistics of the limited number of error sources. These OSSEs indicate that the image resolution has to be finer than 4 km to decrease the uncertainty in the 6 h mean emissions by more than 50 %. More complex experiments assess the impact of more realistic error estimates that current inversion methods do not properly account for, in particular, the systematic measurement errors with spatially correlated patterns. These experiments highlight the difficulty to improve current knowledge on CO2 emissions for urban areas like Paris with CO2 observations from satellites, and call for more technological innovations in the remote sensing of vertically integrated columns of CO2 and in the inversion systems that exploit it.

scholarly journals Estimation of observation errors for large-scale atmospheric inversion of CO2 emissions from fossil fuel combustion

Tellus B ◽  
2017 ◽  
Vol 69 (1) ◽  
pp. 1325723 ◽  
Author(s):  
Yilong Wang ◽  
Grégoire Broquet ◽  
Philippe Ciais ◽  
Frédéric Chevallier ◽  
Felix Vogel ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Large Scale ◽  
Fossil Fuel ◽  
Fuel Combustion ◽  
Fossil Fuel Combustion ◽  
Atmospheric Inversion
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