Determination of the Emission Rates of CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; Point Sources with Airborne Lidar

Wolff, Sebastian; Ehret, Gerhard; Kiemle, Christoph; Amediek, Axel; Quatrevalet, Mathieu; Wirth, Martin; Fix, Andreas

doi:10.5194/amt-2020-390

Cited by 6 publications

(8 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These studies are based on a small number of cases and are likely biased toward optimal observation conditions, while in our study the massbalance approach was applied to every detectable plume. Model studies show that in case of highly turbulent plumes, uncertainties of the order of 10-20% are obtained when applying a massbalance method even in the case where the 3D plume distribution and wind field is known perfectly (Kuhlmann et al, 2021;Wolff et al, 2020). Our results for power plants are also similar to those obtained for the city of Berlin, for which an uncertainty of about 50% was estimated for individual satellite overpasses (Kuhlmann et al, 2020a).…”

Section: Discussionsupporting

confidence: 81%

“…However, to quantify annual emissions, frequent estimates are crucial to reduce the uncertainties caused by hourly and daily fluctuations in emissions (Hill and Nassar, 2019). Consequently, all quantifiable plumes should be included for gaining a more representative annual estimate, even those derived under less optimal conditions, which may limit the individual accuracy of a mass balance approach (e.g., Kuhlmann et al, 2020a;Wolff et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Kuhlmann

Henne

Meijer

et al. 2021

Front. Remote Sens.

View full text Add to dashboard Cite

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.

show abstract

Section: Discussionsupporting

confidence: 81%

Section: Introductionmentioning

confidence: 99%

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

Kuhlmann

Henne

Meijer

et al. 2021

Front. Remote Sens.

View full text Add to dashboard Cite

show abstract

“…Facility-scale greenhouse gas emissions can be monitored in a variety of ways including stationary ground-based systems (Chen et al, 2016;Robinson et al, 2011), mobile groundbased measurements (Yacovitch et al, 2015), and aircraft observations (Conley et al, 2016;Duren et al, 2019;Sherwin et al, 2020;Wolff et al, 2020). Satellites are an attractive complementary observation platform since they have global coverage, employ the same measurement method for any observation site in the world, and can repeatedly revisit any facility in the world.…”

Section: Space-based Ghg Monitoringmentioning

confidence: 99%

The GHGSat-D imaging spectrometer

et al. 2021

View full text Add to dashboard Cite

Abstract. The demonstration satellite GHGSat-D, or “Claire”, launched on 21 June 2016, is the first in a planned constellation of small satellites designed and operated by GHGSat, Inc. to measure greenhouse gas emissions at the facility scale from space. Its instrument measures methane concentrations by collecting and spectrally decomposing solar backscattered radiation in the shortwave infrared using a compact fixed-cavity Fabry–Pérot imaging spectrometer. The effective spatial resolution of 50×50 m2 over targeted 12×12 km2 scenes is unprecedented for a space-based gas-sensing spectrometer. Here we report on the instrument design and forward model and retrieval procedure, and we present several examples of retrieved methane emissions observed over industrial facilities. We discuss the sources of error limiting the performance of GHGSat-D and identify improvements for our follow-on satellites. Claire's mission has proven that small satellites can be used to identify and quantify methane emissions from industrial facilities, enabling operators to take prompt corrective action.

show abstract

“…Page 2, line 37, sentence "However, at the moment no operating satellite mission is able to reliably quantify emissions from large power plants." Unclear what exactly is meant here taking into account publications such as Nassar et al, 2017, andReuter et al, 2019, which need to be cited (details see below in "References").…”

Section: C1mentioning

confidence: 99%

“….". The cross-sectional flux method has also been applied to satellite data, see Reuter et al, 2019. Please add this missing information.…”

Determination of the Emission Rates of CO<sub>2</sub> Point Sources with Airborne Lidar

Cited by 6 publications

References 42 publications

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

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

The GHGSat-D imaging spectrometer

Referee comments

Contact Info

Product

Resources

About