scholarly journals PMIF v1.0: assessing the potential of satellite observations to constrain CO<sub>2</sub> emissions from large cities and point sources over the globe using synthetic data

2020 ◽  
Vol 13 (11) ◽  
pp. 5813-5831 ◽  
Author(s):  
Yilong Wang ◽  
Grégoire Broquet ◽  
François-Marie Bréon ◽  
Franck Lespinas ◽  
Michael Buchwitz ◽  
...  
Keyword(s):  
Power Plants ◽  
Transport Model ◽  
Time Windows ◽  
Full Range ◽  
European Space Agency ◽  
Synthetic Data ◽  
Uncertainty Reduction ◽  
Horizontal Resolution ◽  
Point Sources ◽  
Large Cities

Abstract. This study assesses the potential of satellite imagery of vertically integrated columns of dry-air mole fractions of CO2 (XCO2) to constrain the emissions from cities and power plants (called emission clumps) over the whole globe during 1 year. The imagery is simulated for one imager of the Copernicus mission on Anthropogenic Carbon Dioxide Monitoring (CO2M) planned by the European Space Agency and the European Commission. The width of the swath of the CO2M instruments is about 300 km and the ground horizontal resolution is about 2 km resolution. A Plume Monitoring Inversion Framework (PMIF) is developed, relying on a Gaussian plume model to simulate the XCO2 plumes of each emission clump and on a combination of overlapping assimilation windows to solve for the inversion problem. The inversion solves for the 3 h mean emissions (during 08:30–11:30 local time) before satellite overpasses and for the mean emissions during other hours of the day (over the aggregation between 00:00–08:30 and 11:30–00:00) for each clump and for the 366 d of the year. Our analysis focuses on the derivation of the uncertainty in the inversion estimates (the “posterior uncertainty”) of the clump emissions. A comparison of the results obtained with PMIF and those from a previous study using a complex 3-D Eulerian transport model for a single city (Paris) shows that the PMIF system provides the correct order of magnitude for the uncertainty reduction of emission estimates (i.e., the relative difference between the prior and posterior uncertainties). Beyond the one city or few large cities studied by previous studies, our results provide, for the first time, the global statistics of the uncertainty reduction of emissions for the full range of global clumps (differing in emission rate and spread, and distance from other major clumps) and meteorological conditions. We show that only the clumps with an annual emission budget higher than 2 MtC yr−1 can potentially have their emissions between 08:30 and 11:30 constrained with a posterior uncertainty smaller than 20 % for more than 10 times within 1 year (ignoring the potential to cross or extrapolate information between 08:30–11:30 time windows on different days). The PMIF inversion results are also aggregated in time to investigate the potential of CO2M observations to constrain daily and annual emissions, relying on the extrapolation of information obtained for 08:30–11:30 time windows during days when clouds and aerosols do not mask the plumes, based on various assumptions regarding the temporal auto-correlations of the uncertainties in the emission estimates that are used as a prior knowledge in the Bayesian framework of PMIF. We show that the posterior uncertainties of daily and annual emissions are highly dependent on these temporal auto-correlations, stressing the need for systematic assessment of the sources of uncertainty in the spatiotemporally resolved emission inventories used as prior estimates in the inversions. We highlight the difficulty in constraining the total budget of CO2 emissions from all the cities and power plants within a country or over the globe with satellite XCO2 measurements only, and calls for integrated inversion systems that exploit multiple types of measurements.

scholarly journals PMIF v1.0: an inversion system to estimate the potential of satellite observations to monitor fossil fuel CO<sub>2</sub> emissions over the globe

2020 ◽  
Author(s):  
Yilong Wang ◽  
Grégoire Broquet ◽  
François-Marie Bréon ◽  
Franck Lespinas ◽  
Michael Buchwitz ◽  
...  
Keyword(s):  
Power Plants ◽  
Fossil Fuel ◽  
Transport Model ◽  
Time Windows ◽  
Full Range ◽  
European Space Agency ◽  
Relative Difference ◽  
Uncertainty Reduction ◽  
Horizontal Resolution ◽  
One Year

Abstract. This study assesses the potential of satellite imagery of vertically integrated columns of dry-air mole fractions of CO2 (XCO2) to constrain the emissions from cities and power plants (called emission clumps) over the whole globe during one year. The imagery is simulated for one imager of the Copernicus mission on Anthropogenic Carbon Dioxide Monitoring (CO2M) planned by the European Space Agency and the European Commission. The width of the swath of the CO2M instruments is about 300 km and the ground horizontal resolution is about 2 km resolution. A Plume Monitoring Inversion Framework (PMIF) is developed, relying on a Gaussian plume model to simulate the XCO2 plumes of each emission clump and on a combination of overlapping assimilation windows to solve for the inversion problem. The inversion solves for the 3 h mean emissions (during 8:30–11:30 local time) before satellite overpasses and for the mean emissions during other hours of the day (over the aggregation between 0:00–8:30 and 11:30–0:00) for each clump and for the 366 days of the year. Our analysis focuses on the derivation of the uncertainty in the inversion estimates (the “posterior uncertainty”) of the clump emissions. A comparison of the results obtained with PMIF and those from a previous study using a complex 3-D Eulerian transport model for a single city (Paris) shows that the PMIF system provides the correct order of magnitude for the uncertainty reduction of emission estimates (i.e. the relative difference between the prior and posterior uncertainties). Beyond the one or few large cities studied by previous studies, our results provide, for the first time, the global statistics of the uncertainty reduction of emissions for the full range of global clumps (differing in emission rate and spread, and distance from other major clumps) and meteorological conditions. We show that only the clumps with an annual emission budget higher than 2 MtC per year can potentially have their emissions between 8:30 and 11:30 constrained with a posterior uncertainty smaller than 20 % for more than 10 times within one year (ignoring the potential to cross or extrapolate information between 8:30–11:30 time windows on different days). The PMIF inversion results are also aggregated in time to investigate the potential of CO2M observations to constrain daily and annual emissions, relying on the extrapolation of information obtained for 8:30–11:30 time windows during days when clouds and aerosols do not mask the plumes, based on various assumptions regarding the temporal auto-correlations of the uncertainties in the emission estimates that are used as a prior knowledge in the Bayesian framework of PMIF. We show that the posterior uncertainties of daily and annual emissions are highly dependent on these temporal auto-correlations, stressing the need of systematic assessment of the sources of uncertainty in the spatiotemporally-resolved emission inventories used as prior estimates in the inversions. We highlight the difficulty to constrain global and national fossil fuel CO2 emissions with satellite XCO2 measurements only, and calls for integrated inversion systems that exploit multiple types of measurements.

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 A local- to national-scale inverse modeling system to assess the potential of spaceborne CO<sub>2</sub> measurements for the monitoring of anthropogenic emissions

2021 ◽  
Vol 14 (1) ◽  
pp. 403-433
Author(s):  
Diego Santaren ◽  
Grégoire Broquet ◽  
François-Marie Bréon ◽  
Frédéric Chevallier ◽  
Denis Siméoni ◽  
...  
Keyword(s):  
Wind Speed ◽  
Power Plants ◽  
Western Europe ◽  
Transport Model ◽  
Strong Dependence ◽  
Point Sources ◽  
Anthropogenic Emissions ◽  
Modeling Framework ◽  
Wide Range ◽  
Regional Budgets

Abstract. This work presents a flux inversion system which assesses the potential of new satellite imagery measurements of atmospheric CO2 for monitoring anthropogenic emissions at scales ranging from local intense point sources to regional and national scales. Such imagery measurements will be provided by the future Copernicus Anthropogenic Carbon Dioxide Monitoring Mission (CO2M). While the modeling framework retains the complexity of previous studies focused on individual and large cities, this system encompasses a wide range of sources to extend the scope of the analysis. This atmospheric inversion system uses a zoomed configuration of the CHIMERE regional transport model which covers most of western Europe with a 2 km resolution grid over northern France, western Germany and Benelux. For each day of March and May 2016, over the 6 h before a given satellite overpass, the inversion separately controls the hourly budgets of anthropogenic emissions in this area from ∼ 300 cities, power plants and regions. The inversion also controls hourly regional budgets of the natural fluxes. This enables the analysis of results at the local to regional scales for a wide range of sources in terms of emission budget and spatial extent while accounting for the uncertainties associated with natural fluxes and the overlapping of plumes from different sources. The potential of satellite data for monitoring CO2 fluxes is quantified with posterior uncertainties or uncertainty reductions (URs) from prior inventory-based statistical knowledge. A first analysis focuses on the hourly to 6 h budgets of the emissions of the Paris urban area and on the sensitivity of the results to different characteristics of the images of vertically integrated CO2 (XCO2) corresponding to the spaceborne instrument: the pixel spatial resolution, the precision of the XCO2 retrievals per pixel and the swath width. This sensitivity analysis provides a correspondence between these parameters and thresholds on the targeted precisions of emission estimates. However, the results indicate a large sensitivity to the wind speed and to the prior flux uncertainties. The analysis is then extended to the large ensemble of point sources, cities and regions in the study domain, with a focus on the inversion system's ability to separately monitor neighboring sources whose atmospheric signatures overlap and are also mixed with those produced by natural fluxes. Results highlight the strong dependence of uncertainty reductions on the emission budgets, on the wind speed and on whether the focus is on point or area sources. With the system hypothesis that the atmospheric transport is perfectly known, the results indicate that the atmospheric signal overlap is not a critical issue. All of the tests are conducted considering clear-sky conditions, and the limitations from cloud cover are ignored. Furthermore, in these tests, the inversion system is perfectly informed about the statistical properties of the various sources of errors that are accounted for, and systematic errors in the XCO2 retrievals are ignored; thus, the scores of URs are assumed to be optimistic. For the emissions within the 6 h before a satellite overpass, URs of more than 50 % can only be achieved for power plants and cities whose annual emissions are more than ∼ 2 MtC yr−1. For regional budgets encompassing more diffuse emissions, this threshold increases up to ∼ 10 MtC yr−1. The results therefore suggest an imbalance in the monitoring capabilities of the satellite XCO2 spectro-imagery towards high and dense sources.

scholarly journals Detectability of CO<sub>2</sub> emission plumes of cities and power plants with the Copernicus Anthropogenic CO<sub>2</sub> Monitoring (CO2M) mission

2019 ◽  
Vol 12 (12) ◽  
pp. 6695-6719 ◽  
Author(s):  
Gerrit Kuhlmann ◽  
Grégoire Broquet ◽  
Julia Marshall ◽  
Valentin Clément ◽  
Armin Löscher ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Power Plants ◽  
Atmospheric Transport ◽  
Detection Algorithm ◽  
Daily Basis ◽  
Horizontal Resolution ◽  
Low Noise ◽  
Point Sources ◽  
Added Value ◽  
Small Scale

Abstract. High-resolution atmospheric transport simulations were used to investigate the potential for detecting carbon dioxide (CO2) plumes of the city of Berlin and neighboring power stations with the Copernicus Anthropogenic Carbon Dioxide Monitoring (CO2M) mission, which is a proposed constellation of CO2 satellites with imaging capabilities. The potential for detecting plumes was studied for satellite images of CO2 alone or in combination with images of nitrogen dioxide (NO2) and carbon monoxide (CO) to investigate the added value of measurements of other gases coemitted with CO2 that have better signal-to-noise ratios. The additional NO2 and CO images were either generated for instruments on the same CO2M satellites (2 km× 2 km resolution) or for the Sentinel-5 instrument (7.5 km× 7.5 km) assumed to fly 2 h earlier than CO2M. Realistic CO2, CO and NOX(=NO+NO2) fields were simulated at 1 km× 1 km horizontal resolution with the Consortium for Small-scale Modeling model extended with a module for the simulation of greenhouse gases (COSMO-GHG) for the year 2015, and they were used as input for an orbit simulator to generate synthetic observations of columns of CO2, CO and NO2 for constellations of up to six satellites. A simple plume detection algorithm was applied to detect coherent structures in the images of CO2, NO2 or CO against instrument noise and variability in background levels. Although six satellites with an assumed swath of 250 km were sufficient to overpass Berlin on a daily basis, only about 50 out of 365 plumes per year could be observed in conditions suitable for emission estimation due to frequent cloud cover. With the CO2 instrument only 6 and 16 of these 50 plumes could be detected assuming a high-noise (σVEG50=1.0 ppm) and low-noise (σVEG50=0.5 ppm) scenario, respectively, because the CO2 signals were often too weak. A CO instrument with specifications similar to the Sentinel-5 mission performed worse than the CO2 instrument, while the number of detectable plumes could be significantly increased to about 35 plumes with an NO2 instrument. CO2 and NO2 plumes were found to overlap to a large extent, although NOX had a limited lifetime (assumed to be 4 h) and although CO2 and NOX were emitted with different NOX:CO2 emission ratios by different source types with different temporal and vertical emission profiles. Using NO2 observations from the Sentinel-5 platform instead resulted in a significant spatial mismatch between NO2 and CO2 plumes due to the 2 h time difference between Sentinel-5 and CO2M. The plumes of the coal-fired power plant Jänschwalde were easier to detect with the CO2 instrument (about 40–45 plumes per year), but, again, an NO2 instrument could detect significantly more plumes (about 70). Auxiliary measurements of NO2 were thus found to greatly enhance the capability of detecting the location of CO2 plumes, which will be invaluable for the quantification of CO2 emissions from large point sources.

Quantifying CO2 emissions of power plants with the CO2M mission

2021 ◽  
Author(s):  
Gerrit Kuhlmann ◽  
Stephan Henne ◽  
Yasjka Meijer ◽  
Lukas Emmenegger ◽  
Dominik Brunner
Keyword(s):  
Mass Balance ◽  
Power Plants ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Detection Algorithm ◽  
Point Sources ◽  
Satellite Mission ◽  
Temporal Sampling ◽  
Balance Approach ◽  
Mass Balance Approach

&lt;p&gt;In this study, we analyse the capability of the Copernicus CO&lt;sub&gt;2&lt;/sub&gt; monitoring (CO2M) satellite mission to quantify the CO&lt;sub&gt;2&lt;/sub&gt; emissions of individual power plants, which is one of the prime goals of the mission. The study relies on synthetic CO&lt;sub&gt;2&lt;/sub&gt; and NO&lt;sub&gt;2&lt;/sub&gt; satellite observations over parts of the Czech Republic, Germany and Poland and quantifies the CO&lt;sub&gt;2&lt;/sub&gt; and NO&lt;sub&gt;x&lt;/sub&gt; emissions of the 15 largest power plants in that region using a data-driven mass-balance approach.&lt;/p&gt;&lt;p&gt;The synthetic observations were generated for six CO2M satellites based on high-resolution simulations of the atmospheric transport model COSMO-GHG. To identify the emission plumes, we developed a plume detection algorithm that identifies the location, orientation and extent of multiple plumes from CO2M's NO&lt;sub&gt;2&lt;/sub&gt; observations. Afterwards, a mass-balance approach was applied to individual plumes to estimate CO&lt;sub&gt;2&lt;/sub&gt; and NO&lt;sub&gt;x&lt;/sub&gt; emissions by fitting Gaussian curves to the across-plume signals. Annual emissions were obtained by interpolating the temporally sparse individual estimates applying a low-order spline fit.&lt;/p&gt;&lt;p&gt;Individual CO&lt;sub&gt;2&lt;/sub&gt; emissions were estimated with an accuracy &lt;65% for a source strength &gt;10 Mt CO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;-1&lt;/sup&gt;, while NO&lt;sub&gt;x&lt;/sub&gt; emissions &gt;10 kt NO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;-1 &lt;/sup&gt;were estimated with &lt;56% accuracy. NO&lt;sub&gt;2&lt;/sub&gt; observations were essential for detecting the plume and constraining the shape of the Gaussian curve. With three CO2M satellites, annual CO&lt;sub&gt;2&lt;/sub&gt; emissions were estimated with an uncertainty &lt;30% for source strengths larger than 10 Mt yr&lt;sup&gt;-1&lt;/sup&gt;, which includes an estimate of the uncertainty in the temporal variability of emissions. Annual NO&lt;sub&gt;x&lt;/sub&gt; emissions were estimated with an uncertainty &lt;21%. Since NO&lt;sub&gt;x&lt;/sub&gt; emissions can be determined with better accuracy, estimating CO&lt;sub&gt;2&lt;/sub&gt; emissions directly from the NO&lt;sub&gt;x&lt;/sub&gt; emissions by applying a representative CO&lt;sub&gt;2&lt;/sub&gt;:NO&lt;sub&gt;x&lt;/sub&gt; emission ratio &amp;#160;seems appealing but this approach was found to suffer significantly from the high uncertainty in the&amp;#160; CO&lt;sub&gt;2&lt;/sub&gt;:NO&lt;sub&gt;x&lt;/sub&gt; emission ratios determined from the same CO2M observations.&lt;/p&gt;&lt;p&gt;Our study shows that CO2M should be able to quantify the emissions of the 400 largest point sources globally with emissions larger than 10 Mt yr&lt;sup&gt;-1&lt;/sup&gt; that account for about 20 % of global anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions. However, the mass-balance approach used here has relatively high uncertainties that are dominated by the uncertainties in the estimated CO&lt;sub&gt;2&lt;/sub&gt; background and the wind speed in the plume, and uncertainties associated with the sparse temporal sampling of the varying emissions. Estimates could be significantly improved if these parameters can be better constrained, e.g., with atmospheric transport simulations and independent observations.&lt;/p&gt;

scholarly journals 4D-Var assimilation of MIPAS chemical observations: ozone and nitrogen dioxide analyses

2008 ◽  
Vol 8 (20) ◽  
pp. 6169-6187 ◽  
Author(s):  
Q. Errera ◽  
F. Daerden ◽  
S. Chabrillat ◽  
J. C. Lambert ◽  
W. A. Lahoz ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Nitrogen Dioxide ◽  
Transport Model ◽  
Stratospheric Ozone ◽  
Michelson Interferometer ◽  
European Space Agency ◽  
Horizontal Resolution ◽  
Space Agency ◽  
Estimated Error ◽  
Assimilation System

Abstract. This paper discusses the global analyses of stratospheric ozone (O3) and nitrogen dioxide (NO2) obtained by the Belgian Assimilation System for Chemical Observations from Envisat (BASCOE). Based on a chemistry transport model (CTM) and the 4-dimensional variational (4D-Var) method, BASCOE has assimilated chemical observations of O3, NO2, HNO3, N2O, CH4 and H2O, made between July 2002 and March 2004 by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) onboard the European Space Agency (ESA) Environment Satellite (ENVISAT). This corresponds to the entire period during which MIPAS was operating at its nominal resolution. Our analyses are evaluated against assimilated MIPAS data and independent HALOE (HALogen Occultation Experiment) and POAM-III (Polar Ozone and Aerosol Measurement) satellite data. A good agreement is generally found between the analyses and these datasets, in both cases within the estimated error bars of the observations. The benefit of data assimilation is also evaluated by comparing a BASCOE free model run with MIPAS observations. For O3, the gain from the assimilation is significant during ozone hole conditions, and in the lower stratosphere. Elsewhere, the assimilation does not provide significant improvement. For NO2, the gain from the assimilation is realized through most of the stratosphere. Using the BASCOE analyses, we estimate the differences between MIPAS data and independent data from HALOE and POAM-III, and find results close to those obtained by classical validation methods involving only direct measurement-to-measurement comparisons. Our results extend and reinforce previous MIPAS data validation efforts by taking into account a much larger variety of atmospheric states and measurement conditions. This study discusses possible further developments of the BASCOE data assimilation system; these concern the horizontal resolution, a better filtering of NO2 observations, and the photolysis calculation near the lid of the model. The ozone analyses are part of the PROMOTE project and are publicly available via the BASCOE website (http://www.bascoe.oma.be/promote/).

scholarly journals A local to national-scale inverse modeling system to assess the potential of spaceborne CO<sub>2</sub> measurements for the monitoring of anthropogenic emissions

2020 ◽  
Author(s):  
Diego Santaren ◽  
Grégoire Broquet ◽  
François-Marie Bréon ◽  
Frédéric Chevallier ◽  
Denis Siméoni ◽  
...  
Keyword(s):  
Wind Speed ◽  
Power Plants ◽  
Western Europe ◽  
Transport Model ◽  
Strong Dependence ◽  
Point Sources ◽  
Anthropogenic Emissions ◽  
Modeling Framework ◽  
Wide Range ◽  
Regional Budgets

Abstract. This work presents a flux inversion system for assessing the potential of new satellite imagery measurements of atmospheric CO2 to monitor anthropogenic emissions at scales ranging from local intense point sources to regional and national scales. While the modeling framework keeps the complexity of previous studies focused on individual and large cities, this system encompasses a wide range of sources to extend the scope of the analysis. This atmospheric inversion system uses a zoomed configuration of the regional transport model CHIMERE which covers most of Western Europe with a 2-km resolution grid over Northern France, Western Germany and Benelux. For each day of March and May 2016, over the 6 hours before a given satellite overpass, the inversion controls separately the hourly budgets of anthropogenic emissions in this area from ~300 cities, power plants and regions. The inversion also controls hourly regional budgets of the natural fluxes. This enables the analysis of results at the local to regional scales for a wide range of sources in terms of emission budgets and spatial extent while accounting for the uncertainties associated with natural fluxes and the overlapping of plumes from different sources. The potential of satellite data to monitor CO2 fluxes is quantified by posterior uncertainties or uncertainty reductions (URs) from prior inventory-based statistical knowledge. A first analysis focuses on the hourly to 6-hour budgets of the emissions of the Paris urban area, and on the sensitivity of the results to different characteristics of the images of vertically integrated CO2 (XCO2) corresponding to the spaceborne instrument: the pixel spatial resolution, the precision of the XCO2 retrievals per pixel, and the swath width. This sensitivity analysis provides a correspondence between these parameters and thresholds on the targeted precisions on emission estimates. However, the results indicate a large sensitivity to the wind speed and to the prior flux uncertainties. The analysis is then extended to the large ensemble of point sources, cities and regions in the study domain, with a focus on the inversion system ability to monitor separately neighbor sources whose atmospheric signatures overlap and are also mixed with those produced by natural fluxes. Results highlight the strong dependence of uncertainty reductions to the emission budgets, to the wind speed and whether the focus is on point or area sources. With the system hypothesis that the atmospheric transport is perfectly known, the results indicate that the atmospheric signal overlap is not a critical issue. For the emissions within the 6-hours before a satellite overpass, UR of more than 50 % can only be achieved for power plants and cities whose annual emissions are more than ~2 MtC yr−1. For more regional budgets encompassing more diffuse emissions, this threshold increases up to ~10 MtC yr−1. The results suggest therefore an imbalance of the monitoring capabilities towards high and dense sources.

scholarly journals Detectability of CO<sub>2</sub> emission plumes of cities and power plants with the Copernicus Anthropogenic CO<sub>2</sub> Monitoring (CO2M) mission

2019 ◽  
Author(s):  
Gerrit Kuhlmann ◽  
Grégoire Broquet ◽  
Julia Marshall ◽  
Valentin Clément ◽  
Armin Löscher ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Power Plants ◽  
Atmospheric Transport ◽  
Detection Algorithm ◽  
Daily Basis ◽  
Horizontal Resolution ◽  
Low Noise ◽  
Point Sources ◽  
Added Value ◽  
Carbon Dioxide Co2

Abstract. High-resolution atmospheric transport simulations were used to investigate the potential for detecting carbon dioxide (CO2) plumes of the city of Berlin and neighboring power stations with the Copernicus Anthropogenic Carbon Dioxide Monitoring (CO2M) mission, which is a proposed constellation of CO2 satellites with imaging capabilities. The potential for detecting plumes was studied for satellite images of CO2 alone or in combination with images of nitrogen dioxide (NO2) and carbon monoxide (CO) to investigate the added value of measurements of other gases co-emitted with CO2 that have better signal-to-noise ratios. The additional NO2 and CO images were either generated for instruments on the same CO2M satellites (2×2 km2 resolution) or for the Sentinel-5 instrument (7×7 km2) assumed to fly two hours earlier than CO2M. Realistic CO2, CO and NO2 fields were simulated at 1×1 km2 horizontal resolution with COSMO-GHG model for the year 2015, and used as input for an orbit simulator to generate synthetic observations of columns of CO2, CO and NO2 for constellations of up to six satellites. A new plume detection algorithm was applied to detect coherent structures in the images of CO2, NO2 or CO against instrument noise and variability in background levels. Although six satellites with an assumed swath of 250 km were sufficient to overpass Berlin on a daily basis, only about 50 out of 365 plumes per year could be observed in conditions suitable for emission estimation due to frequent cloud cover. With the CO2 instrument only 6 and 16 of these 50 plumes could be detected assuming a high (σVEG50 = 1.0 ppm) and low noise (σVEG50 = 0.5 ppm) scenario, respectively, because the CO2 signals were often too weak. A CO instrument with specifications similar to the Sentinel-5 mission performed worse than the CO2 instrument, while the number of detectable plumes could be significantly increased to about 35 plumes with an NO2 instrument. Using NO2 observations from the Sentinel-5 platform instead resulted in a significant spatial mismatch between NO2 and CO2 plumes due to the two hour time difference between Sentinel-5 and CO2M. The plumes of the coal-fired power plant Jänschwalde were easier to detect with the CO2 instrument (about 40–45 plumes per year), but again, an NO2 instrument performed significantly better (about 70 plumes). Auxiliary measurements of NO2 were thus found to greatly enhance the capability of detecting the location of CO2 plumes, which will be invaluable for the quantification of CO2 emissions from large point sources.

scholarly journals Effects of point source emission heights in WRF–STILT: a step towards exploiting nocturnal observations in models

2021 ◽  
Author(s):  
Fabian Maier ◽  
Christoph Gerbig ◽  
Ingeborg Levin ◽  
Ingrid Super ◽  
Julia Marshall ◽  
...  
Keyword(s):  
Point Source ◽  
Power Plants ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Ground Level ◽  
Point Sources ◽  
Observation Site ◽  
Surface Source ◽  
Concentration Difference ◽  
Nearby Point

Abstract. An appropriate representation of point source emissions in atmospheric transport models is very challenging. In the Stochastic Time Inverted Lagrangian Transport model (STILT), all point source emissions are typically released from the surface, meaning that the actual emission stack height plus subsequent plume rise is not considered. This can lead to erroneous predictions of trace gas concentrations, especially during nighttime when vertical atmospheric mixing is minimal. In this study we use two WRF–STILT model approaches to simulate fossil fuel CO2 (ffCO2) concentrations: (1) the standard “surface source influence (SSI)” approach, and (2) an alternative “volume source influence (VSI)” approach, where nearby point sources release CO2 according to their effective emission height profiles. The comparison with 14C-based measured ffCO2 data from two-week integrated afternoon and nighttime samples collected at Heidelberg, 30 m above ground level, shows that the root-mean-square deviation (RMSD) between modelled and measured ffCO2 is indeed almost twice as high during night (RMSD = 6.3 ppm) compared to the afternoon (RMSD = 3.7 ppm) when using the standard SSI approach. In contrast, the VSI approach leads to a much better performance at nighttime (RMSD = 3.4 ppm), which is similar to its performance during afternoon (RMSD = 3.7 ppm). Representing nearby point source emissions with the VSI approach could, thus, be a first step towards exploiting nocturnal observations in STILT. To further investigate the differences between these two approaches, we conducted a model experiment in which we simulated the ffCO2 contributions from 12 artificial power plants with typical annual emissions of one million tons of CO2 and with distances between 5 and 200 km from the Heidelberg observation site. We find that such a power plant must be more than 50 km away from the observation site in order for the mean modelled ffCO2 concentration difference between the SSI and VSI approach to fall below 0.1 ppm.

scholarly journals 4D-Var Assimilation of MIPAS chemical observations: ozone and nitrogen dioxide analyses

2008 ◽  
Vol 8 (2) ◽  
pp. 8009-8057 ◽  
Author(s):  
Q. Errera ◽  
F. Daerden ◽  
S. Chabrillat ◽  
J. C. Lambert ◽  
W. A. Lahoz ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Nitrogen Dioxide ◽  
Transport Model ◽  
Stratospheric Ozone ◽  
Michelson Interferometer ◽  
European Space Agency ◽  
Horizontal Resolution ◽  
Space Agency ◽  
Free Model ◽  
Assimilation System

Abstract. This paper discusses the global analyses of stratospheric ozone (O3) and nitrogen dioxide (NO2) obtained by the Belgian Assimilation System for Chemical Observations from Envisat (BASCOE). Based on a chemistry transport model (CTM) and the 4-dimensional variational (4D-Var) method, BASCOE has assimilated chemical observations of O3, NO2, HNO3, N2O, CH4 and H2O, made between July 2002 and March 2004 by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) onboard the European Space Agency (ESA) Environment Satellite (ENVISAT). This corresponds to the entire period during which MIPAS was operating at its nominal resolution. Our analyses are evaluated against assimilated MIPAS data and independent HALOE (HALogen Occultation Experiment) and POAM-III (Polar Ozone and Aerosol Measurement) satellite data. A good agreement is generally found between the analyses and these datasets, in both cases within the estimated error bars of the observations. The benefit of data assimilation is also evaluated using a BASCOE free model run. For O3, the gain from the assimilation is significant during ozone hole conditions, and in the lower stratosphere. Elsewhere, the free model run is within the MIPAS uncertainties and the assimilation does not provide significant improvement. For NO2, the gain from the assimilation is realized through most of the stratosphere. Using the BASCOE analyses, we estimate the differences between MIPAS data and independent data from HALOE and POAM-III, and find results close to those obtained by classical validation methods involving only direct measurement-to-measurement comparisons. Our results extend and reinforce previous MIPAS data validation efforts by taking account of a much larger variety of atmospheric states and measurement conditions. This study discusses possible further developments of the BASCOE data assimilation system; these concern the horizontal resolution, a better filtering of NO2 observations, and the photolysis calculation near the lid of the model. The ozone analyses are publicly available via the PROMOTE project http://www.gse-promote.org).

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