{"title":"An Algorithm for Identifying Pollution Sources with Non-Linear Measurement Operators","authors":"A. V. Penenko, E. V. Rusin, M. K. Emelyanov","doi":"10.1134/S1024856025701003","DOIUrl":null,"url":null,"abstract":"<p>The problem of atmospheric emission source identification from remote sensing data is considered. An algorithm for the problem solution based on a three-dimensional model of atmospheric pollutant transport and a nonlinear measurement model represented as a “differentiable black box” is suggested. The algorithm includes sensitivity operators and ensembles of solutions of adjoint equations. It was tested for a realistic scenario for identifying soot sources for the Baikal region with synthetic satellite Terra/MODIS measurements and showed its efficiency. Additionally, the measurement data decomposition modification of the algorithm is suggested, which reduces the relative error of retrieving the source function by 12% compared to the version without decomposition. The results can be used in the development of remote sensing data processing systems.</p>","PeriodicalId":46751,"journal":{"name":"Atmospheric and Oceanic Optics","volume":"38 6","pages":"838 - 846"},"PeriodicalIF":0.7000,"publicationDate":"2026-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric and Oceanic Optics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1134/S1024856025701003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"OPTICS","Score":null,"Total":0}
引用次数: 0
Abstract
The problem of atmospheric emission source identification from remote sensing data is considered. An algorithm for the problem solution based on a three-dimensional model of atmospheric pollutant transport and a nonlinear measurement model represented as a “differentiable black box” is suggested. The algorithm includes sensitivity operators and ensembles of solutions of adjoint equations. It was tested for a realistic scenario for identifying soot sources for the Baikal region with synthetic satellite Terra/MODIS measurements and showed its efficiency. Additionally, the measurement data decomposition modification of the algorithm is suggested, which reduces the relative error of retrieving the source function by 12% compared to the version without decomposition. The results can be used in the development of remote sensing data processing systems.
期刊介绍：
Atmospheric and Oceanic Optics is an international peer reviewed journal that presents experimental and theoretical articles relevant to a wide range of problems of atmospheric and oceanic optics, ecology, and climate. The journal coverage includes: scattering and transfer of optical waves, spectroscopy of atmospheric gases, turbulent and nonlinear optical phenomena, adaptive optics, remote (ground-based, airborne, and spaceborne) sensing of the atmosphere and the surface, methods for solving of inverse problems, new equipment for optical investigations, development of computer programs and databases for optical studies. Thematic issues are devoted to the studies of atmospheric ozone, adaptive, nonlinear, and coherent optics, regional climate and environmental monitoring, and other subjects.
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