scholarly journals Quantifying CO2 Emissions of Power Plants With CO2 and NO2 Imaging Satellites

2021 ◽  
Vol 2 ◽  
Author(s):  
Gerrit Kuhlmann ◽  
Stephan Henne ◽  
Yasjka Meijer ◽  
Dominik Brunner
Keyword(s):  
Mass Balance ◽  
Temporal Variability ◽  
Energy Demand ◽  
Power Plants ◽  
Detection Algorithm ◽  
Point Sources ◽  
Sources Of Information ◽  
Total Uncertainty ◽  
Balance Approach ◽  
Mass Balance Approach

One important goal of the Copernicus CO2 monitoring (CO2M) mission is to quantify CO2 emissions of large point sources. We analyzed the feasibility of such quantifications using synthetic CO2 and NO2 observations for a constellation of CO2M satellites. Observations were generated from kilometer-scale COSMO-GHG simulations over parts of the Czech Republic, Germany and Poland. CO2 and NOX emissions of the 15 largest power plants (3.7–40.3 Mt CO2 yr−1) were quantified using a data-driven method that combines a plume detection algorithm with a mass-balance approach. CO2 and NOX emissions could be estimated from single overpasses with 39–150% and 33–116% uncertainty (10–90th percentile), respectively. NO2 observations were essential for estimating CO2 emissions as they helped detecting and constraining the shape of the plumes. The uncertainties are dominated by uncertainties in the CO2M observations (2–72%) and limitations of the mass-balance approach to quantify emissions of complex plumes (25–95%). Annual CO2 emissions could be estimated with 23–119% and 18–65% uncertainties with two and three satellites, respectively. The uncertainty in the temporal variability of emissions contributes about half to the total uncertainty. The estimated uncertainty was extrapolated to determine uncertainties for point sources globally, suggesting that two satellites would be able to quantify the emissions of up to 300 point sources with <30% uncertainty, while adding a third satellite would double the number to about 600 point sources. Annual NOX emissions can be determined with better accuracy of 16–73% and 13–52% with two and three satellites, respectively. Estimating CO2 emissions from NOX emissions using a CO2:NOX emission ratio may thus seem appealing, but this approach is significantly limited by the high uncertainty in the emission ratios as determined from the same CO2M observations. The mass-balance approach studied here will be particularly useful for estimating emissions in countries where power plant emissions are not routinely monitored and reported. Further reducing the uncertainties will require the development of advanced atmospheric inversion systems for emission plumes and an improved constraint on the temporal variability of emissions using additional sources of information such as other satellite observations or energy demand statistics.

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

<p>In this study, we analyse the capability of the Copernicus CO<sub>2</sub> monitoring (CO2M) satellite mission to quantify the CO<sub>2</sub> emissions of individual power plants, which is one of the prime goals of the mission. The study relies on synthetic CO<sub>2</sub> and NO<sub>2</sub> satellite observations over parts of the Czech Republic, Germany and Poland and quantifies the CO<sub>2</sub> and NO<sub>x</sub> emissions of the 15 largest power plants in that region using a data-driven mass-balance approach.</p><p>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<sub>2</sub> observations. Afterwards, a mass-balance approach was applied to individual plumes to estimate CO<sub>2</sub> and NO<sub>x</sub> 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.</p><p>Individual CO<sub>2</sub> emissions were estimated with an accuracy <65% for a source strength >10 Mt CO<sub>2</sub> yr<sup>-1</sup>, while NO<sub>x</sub> emissions >10 kt NO<sub>2</sub> yr<sup>-1 </sup>were estimated with <56% accuracy. NO<sub>2</sub> observations were essential for detecting the plume and constraining the shape of the Gaussian curve. With three CO2M satellites, annual CO<sub>2</sub> emissions were estimated with an uncertainty <30% for source strengths larger than 10 Mt yr<sup>-1</sup>, which includes an estimate of the uncertainty in the temporal variability of emissions. Annual NO<sub>x</sub> emissions were estimated with an uncertainty <21%. Since NO<sub>x</sub> emissions can be determined with better accuracy, estimating CO<sub>2</sub> emissions directly from the NO<sub>x</sub> emissions by applying a representative CO<sub>2</sub>:NO<sub>x</sub> emission ratio  seems appealing but this approach was found to suffer significantly from the high uncertainty in the  CO<sub>2</sub>:NO<sub>x</sub> emission ratios determined from the same CO2M observations.</p><p>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<sup>-1</sup> that account for about 20 % of global anthropogenic CO<sub>2</sub> emissions. However, the mass-balance approach used here has relatively high uncertainties that are dominated by the uncertainties in the estimated CO<sub>2</sub> 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.</p>

scholarly journals Quantifying CO<sub>2</sub> emissions of a city with the Copernicus Anthropogenic CO<sub>2</sub> Monitoring satellite mission

2020 ◽  
Author(s):  
Gerrit Kuhlmann ◽  
Dominik Brunner ◽  
Grégoire Broquet ◽  
Yasjka Meijer
Keyword(s):  
Mass Balance ◽  
Temporal Variability ◽  
Transport Model ◽  
Co2 Flux ◽  
Detection Algorithm ◽  
Satellite Observations ◽  
Lower Sensitivity ◽  
Satellite Mission ◽  
Balance Approach ◽  
Mass Balance Approach

Abstract. We investigate the potential of the Copernicus Anthropogenic Carbon Dioxide (CO2) Monitoring (CO2M) mission, a proposed constellation of CO2 imaging satellites, to estimate the CO2 emissions of a city on the example of Berlin, the capital of Germany. On average, Berlin emits about 20 Mt CO2 yr−1 during satellite overpass (11:30 local time). The study uses synthetic satellite observations of a constellation of up to six satellites generated from one year of high-resolution atmospheric transport simulations. The emissions were estimated by (1) an analytical atmospheric inversion applied to the plume of Berlin simulated by the same model that was used to generate the synthetic observations, and (2) a mass-balance approach that estimates the CO2 flux through multiple cross-sections of the city plume detected by a plume detection algorithm. The plume was either detected from CO2 observations alone or from additional nitrogen dioxide (NO2) observations on the same platform. The two approaches span the range between the optimistic assumption of a perfect transport model that provides an accurate prediction of plume location and CO2 background, and the pessimistic assumption that plume location and background can only be determined reliably from the satellite observations. Often unfavorable meteorological conditions allowed to successfully apply the analytical inversion to only 11 out of 61 overpasses per satellite per year on average. From a single overpass, the instantaneous emissions of Berlin could be estimated with an average precision of 3.0 to 4.2 Mt yr−1 (15–21 % of emissions during overpass) depending on the assumed instrument noise ranging from 0.5 to 1.0 ppm. Applying the mass balance approach required the detection of a sufficiently large plume, which on average was only possible on 3 overpasses per satellite per year when using CO2 observations for plume detection. This number doubled to 6 estimates when the plumes were detected from NO2 observations due to the better signal-to-noise ratio and lower sensitivity to clouds of the measurements. Compared to the analytical inversion, the mass balance approach had a lower precision ranging from 8.1 to 10.7 Mt yr−1 (40–53 %), because it is affected by additional uncertainties introduced by the estimation of the location of the plume, the CO2 background field, and the wind speed within the plume. These uncertainties also resulted in systematic biases, especially without the NO2 observations. An additional source of bias were non-separable fluxes from outside of Berlin. Annual emissions were estimated by fitting a low-order periodic spline to the individual estimates to account for the temporal variability of the emissions. The analytical inversion was able to estimate annual emissions with an accuracy of  40 %)) when using the CO2 observations alone. When using the NO2 observations to detect the plume, the accuracy could be greatly improved to 22 % and 13 % with two and three satellites, respectively. Using the complementary information provided by the CO2 and NO2 observations on the CO2M mission, it should be possible to quantify annual emissions of a city like Berlin with an accuracy of about 10 to 20 %, even in the pessimistic case that plume location and CO2 background have to be determined from the observations alone. This requires, however, that the temporal coverage of the constellation is sufficiently high to resolve the temporal variability of emissions.

scholarly journals Quantifying CO<sub>2</sub> emissions of a city with the Copernicus Anthropogenic CO<sub>2</sub> Monitoring satellite mission

2020 ◽  
Vol 13 (12) ◽  
pp. 6733-6754
Author(s):  
Gerrit Kuhlmann ◽  
Dominik Brunner ◽  
Grégoire Broquet ◽  
Yasjka Meijer
Keyword(s):  
Mass Balance ◽  
Transport Model ◽  
Co2 Flux ◽  
Detection Algorithm ◽  
Satellite Observations ◽  
Lower Sensitivity ◽  
Additional Source ◽  
Satellite Mission ◽  
Balance Approach ◽  
Mass Balance Approach

Abstract. We investigate the potential of the Copernicus Anthropogenic Carbon Dioxide (CO2) Monitoring (CO2M) mission, a proposed constellation of CO2 imaging satellites, to estimate the CO2 emissions of a city on the example of Berlin, the capital of Germany. On average, Berlin emits about 20 Mt CO2 yr−1 during satellite overpass (11:30 LT). The study uses synthetic satellite observations of a constellation of up to six satellites generated from 1 year of high-resolution atmospheric transport simulations. The emissions were estimated by (1) an analytical atmospheric inversion applied to the plume of Berlin simulated by the same model that was used to generate the synthetic observations and (2) a mass-balance approach that estimates the CO2 flux through multiple cross sections of the city plume detected by a plume detection algorithm. The plume was either detected from CO2 observations alone or from additional nitrogen dioxide (NO2) observations on the same platform. The two approaches were set up to span the range between (i) the optimistic assumption of a perfect transport model that provides an accurate prediction of plume location and CO2 background and (ii) the pessimistic assumption that plume location and background can only be determined reliably from the satellite observations. Often unfavorable meteorological conditions allowed us to successfully apply the analytical inversion to only 11 out of 61 overpasses per satellite per year on average. From a single overpass, the instantaneous emissions of Berlin could be estimated with an average precision of 3.0 to 4.2 Mt yr−1 (15 %–21 % of emissions during overpass) depending on the assumed instrument noise ranging from 0.5 to 1.0 ppm. Applying the mass-balance approach required the detection of a sufficiently large plume, which on average was only possible on three overpasses per satellite per year when using CO2 observations for plume detection. This number doubled to six estimates when the plumes were detected from NO2 observations due to the better signal-to-noise ratio and lower sensitivity to clouds of the measurements. Compared to the analytical inversion, the mass-balance approach had a lower precision ranging from 8.1 to 10.7 Mt yr−1 (40 % to 53 %), because it is affected by additional uncertainties introduced by the estimation of the location of the plume, the CO2 background field, and the wind speed within the plume. These uncertainties also resulted in systematic biases, especially without the NO2 observations. An additional source of bias was non-separable fluxes from outside of Berlin. Annual emissions were estimated by fitting a low-order periodic spline to the individual estimates to account for the seasonal variability of the emissions, but we did not account for the diurnal cycle of emissions, which is an additional source of uncertainty that is difficult to characterize. The analytical inversion was able to estimate annual emissions with an accuracy of < 1.1 Mt yr−1 (< 6 %) even with only one satellite, but this assumes perfect knowledge of plume location and CO2 background. The accuracy was much smaller when applying the mass-balance approach, which determines plume location and background directly from the satellite observations. At least two satellites were necessary for the mass-balance approach to have a sufficiently large number of estimates distributed over the year to robustly fit a spline, but even then the accuracy was low (> 8 Mt yr−1 (>40 %)) when using the CO2 observations alone. When using the NO2 observations to detect the plume, the accuracy could be greatly improved to 22 % and 13 % with two and three satellites, respectively. Using the complementary information provided by the CO2 and NO2 observations on the CO2M mission, it should be possible to quantify annual emissions of a city like Berlin with an accuracy of about 10 % to 20 %, even in the pessimistic case that plume location and CO2 background have to be determined from the observations alone. This requires, however, that the temporal coverage of the constellation is sufficiently high to resolve the temporal variability of emissions.

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