Abstract
Abstract. Reliable techniques to infer greenhouse gas emission rates from localised sources require accurate measurement and inversion approaches. In this study airborne remote sensing observations of CO2 by the MAMAP instrument and airborne in situ measurements are used to infer emission estimates of carbon dioxide released from a cluster of coal-fired power plants. The study area is complex due to sources being located in close proximity and overlapping associated carbon dioxide plumes. For the analysis of in situ data, a mass balance approach is described and applied, whereas for the remote sensing observations an inverse Gaussian plume model is used in addition to a mass balance technique. A comparison between methods shows that results for all methods agree within 10 % or better with uncertainties of 10 to 30 % for cases in which in situ measurements were made for the complete vertical plume extent. The computed emissions for individual power plants are in agreement with results derived from emission factors and energy production data for the time of the overflight.
Highlights
Knowledge of emissions of the greenhouse gas carbon dioxide (CO2) originating from localised sources is often inadequate (Ciais et al, 2015; NRC, 2010)
In this study airborne remote sensing observations of CO2 by the MAMAP instrument and airborne in situ measurements are used to infer emission estimates of carbon dioxide released from a cluster of coalfired power plants
While the complete campaign covered other CO2 and CH4 emitting targets (Bovensmann et al, 2014), this study focuses on measurements obtained in an area with several lignite-fired power plants in western Germany on 15 August 2012
Summary
Knowledge of emissions of the greenhouse gas carbon dioxide (CO2) originating from localised sources is often inadequate (Ciais et al, 2015; NRC, 2010). Top-down estimates of localised sources are generally obtained using airborne or ground-based in situ measurements. The use of airborne remote sensing has demonstrated the ability to accurately estimate emissions All methods have their distinctive advantages and disadvantages. Ground-based in situ measurements are fairly low cost They generally do not sample the complete atmospheric boundary layer, which is necessary for an accurate emission estimate. Karion et al, 2013; Cambaliza et al, 2014; Caulton et al, 2014; Gordon et al, 2015; Lavoie et al, 2015) They require a dense flight pattern and assumptions, for example about the layer below the lowest flight track, have to be made. In contrast to in situ measurements, clear-sky conditions are mostly required as they measure backscattered solar
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