[M-IS01] ENVIRONMENTAL, SOCIO-ECONOMIC, AND CLIMATIC CHANGES IN NORTHERN EURASIA

[MIS01-06] An inverse modeling approach to derive high-resolution surface GHG fluxes from measured GHG concentrations in the atmospheric boundary layer

*Iuliia Mukhartova^1,2、Alexander Olchev²、Ravil Gibadullin²、Andrey Sogachev⁴、Ibragim Kerimov³ (1.Lomonosov Moscow State University, Faculty of Physics, Department of Mathematics, GSP-1, Leninskie Gory, Moscow, 119991, Russia 、2.Lomonosov Moscow State University, Faculty of Geography, Department of Meteorology and Climatology, GSP-1, Leninskie Gory, Moscow, 119991, Russia 、3.Grozny State Oil Technical University, Isaeva av. 100, Grozny, 364024, Russia、4.A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Science, Leninsky Prospekt 33, Moscow, 119071, Russia)

キーワード：GHG fluxes, inverse problem, UAV concentration measurements, three-dimensional hydrodynamic E-ω model

Terrestrial ecosystems play a very important role in the regulation of atmospheric greenhouse gas (GHG) concentrations (IPCC 2021). Eddy covariance and chamber methods are the most widely used for GHG flux measurements in the field. These methods have many limitations, such as in flux measurements over non-uniform areas. In this case, remote sensing data and mathematical models can be very useful tools for flux estimation. The main objective of this proof-of-concept study is to explore the possibility of estimating carbon dioxide (CO2) and methane (CH4) fluxes over complex areas using an Unmanned Aircraft Vehicle (UAV) as a measurement platform for CO2 and CH4 concentration measurements. We propose and test a novel approach for estimating GHG fluxes using GHG concentration data collected by UAVs at two levels above the ground surface. Our approach is based on a three-dimensional hydrodynamic model to determine the airflow parameters that affect the distribution of GHG concentrations within the atmospheric boundary layer. The model was primarily designed to solve the forward problem, i.e., to compute the distribution of stationary GHG concentrations over a non-uniform surface, given the GHG fluxes at the lower boundary of the computational domain. The inverse problem of determining unknown GHG fluxes involves minimizing the difference between measured and modeled GHG concentrations at two levels above the ground surface. As an initial approximation in solving the inverse problem, we use a finite-difference approximation of GHG fluxes using concentrations measured at least at two levels above the canopy, as well as measured wind velocities or turbulence coefficients. A forested area in the foothills of the Greater Caucasus Mountains in Russia, characterized by highly complex topography and mosaic vegetation, was selected as the experimental area for the modeling study. This area is the subject of intensive studies of GHG fluxes using ground-based and remote sensing methods implemented within the Russian Pilot Project on Carbon Measurement Supersites. In our study, measured CO2 and CH4 concentrations were imitated by modeled data for given surface fluxes, vegetation distribution, and wind parameters. It allows to test the concept and to investigate the influence of the number of measurement points, level heights and GHG measurement accuracy on the accuracy of flux estimation from UAV data.
The study was supported by the state assignment of the Grozny State Oil Technical University (Project Reg. No. FZNU-2024-0002).