Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2026, V. 23, No. 2, pp. 84-94
On the determination of content and sources of nitrogen dioxide in the troposphere based on measurements from the Resurs-P satellite
O.V. Postylyakov 1 , A.S. Khristova 1, 2 , A.I. Chulichkov 2, 1 , A.N. Borovsky 1 , Iu.S. Mukhartova 2 , A.A. Makarenkov 3 1 A.M. Obukhov Institute of Atmospheric Physics RAS, Moscow, Russia
2 Lomonosov Moscow State University, Moscow, Russia
3 Ryazan State Radio Engineering University named after V. F. Utkin, Ryazan, Russia
Accepted: 23.12.2025
DOI: 10.21046/2070-7401-2026-23-2-84-94
The Resurs-P satellite is equipped with a hyperspectral instrument, named GSA, that records scattered solar radiation in the spectral range covering the NO2 absorption band. The authors previously developed a method for determining the two-dimensional field of integrated NO2 content in the troposphere based on high-spatial-resolution GSA/Resurs-P measurements. The paper describes the data used as input for this study, briefly reviewing the results obtained during experimental measurements by the GSA/Resurs-P equipment on September 29, 2016, and a chemical transport model developed for interpreting highly detailed measurements. The paper develops and compares three methods for solving the inverse problem of determining the spatial distribution of NOx sources based on the NO2 distribution fields obtained by GSA/Resurs-P. The first results from applying the developed methods are presented. The nonlinear quadratic programming method, which took into account the non-negativity of the NO2 source density, yielded a result with better source localization that was less distorted by noise compared to the biased linear estimate and the projection of this estimate, which took into account the non-negativity of the source density.
Keywords: space measurements, GSA, Resurs-P, nitrogen dioxide sources, emissions inventory, differential spectroscopy, chemical-transport modeling, optimal statistical estimation, Fourier transform, quadratic programming, gradient projection method
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