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Numerical study of an algorithm for air pollution sources identification with in situ and remote sensing measurement data. / Penenko, A. V.; Gochakov, A. V.; Antokhin, P. N.

25th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics. ed. / Gennadii G. Matvienko; Oleg A. Romanovskii. SPIE, 2019. 112085B (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11208).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Penenko, AV, Gochakov, AV & Antokhin, PN 2019, Numerical study of an algorithm for air pollution sources identification with in situ and remote sensing measurement data. in GG Matvienko & OA Romanovskii (eds), 25th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics., 112085B, Proceedings of SPIE - The International Society for Optical Engineering, vol. 11208, SPIE, 25th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics 2019, Novosibirsk, Russian Federation, 30.06.2019. https://doi.org/10.1117/12.2540901

APA

Penenko, A. V., Gochakov, A. V., & Antokhin, P. N. (2019). Numerical study of an algorithm for air pollution sources identification with in situ and remote sensing measurement data. In G. G. Matvienko, & O. A. Romanovskii (Eds.), 25th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics [112085B] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11208). SPIE. https://doi.org/10.1117/12.2540901

Vancouver

Penenko AV, Gochakov AV, Antokhin PN. Numerical study of an algorithm for air pollution sources identification with in situ and remote sensing measurement data. In Matvienko GG, Romanovskii OA, editors, 25th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics. SPIE. 2019. 112085B. (Proceedings of SPIE - The International Society for Optical Engineering). doi: 10.1117/12.2540901

Author

Penenko, A. V. ; Gochakov, A. V. ; Antokhin, P. N. / Numerical study of an algorithm for air pollution sources identification with in situ and remote sensing measurement data. 25th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics. editor / Gennadii G. Matvienko ; Oleg A. Romanovskii. SPIE, 2019. (Proceedings of SPIE - The International Society for Optical Engineering).

BibTeX

@inproceedings{53c7dbe54ea44977ad34980178ff41fa,
title = "Numerical study of an algorithm for air pollution sources identification with in situ and remote sensing measurement data",
abstract = "The results of the inverse source problem solution for an atmospheric chemistry transport and transformation model for in situ and remote sensing measurement data are compared. The algorithm based on the ensembles of the adjoint problem solutions is applied to solve the inverse problem. The solutions are compared in the Novosibirsk city inverse modeling scenario.",
keywords = "adjoint ensemble, atmospheric chemistry, in situ measurements, inverse source problem, Novosibirsk city, remote sensing data",
author = "Penenko, {A. V.} and Gochakov, {A. V.} and Antokhin, {P. N.}",
year = "2019",
month = dec,
day = "18",
doi = "10.1117/12.2540901",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Matvienko, {Gennadii G.} and Romanovskii, {Oleg A.}",
booktitle = "25th International Symposium on Atmospheric and Ocean Optics",
address = "United States",
note = "25th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics 2019 ; Conference date: 30-06-2019 Through 05-07-2019",

}

RIS

TY - GEN

T1 - Numerical study of an algorithm for air pollution sources identification with in situ and remote sensing measurement data

AU - Penenko, A. V.

AU - Gochakov, A. V.

AU - Antokhin, P. N.

PY - 2019/12/18

Y1 - 2019/12/18

N2 - The results of the inverse source problem solution for an atmospheric chemistry transport and transformation model for in situ and remote sensing measurement data are compared. The algorithm based on the ensembles of the adjoint problem solutions is applied to solve the inverse problem. The solutions are compared in the Novosibirsk city inverse modeling scenario.

AB - The results of the inverse source problem solution for an atmospheric chemistry transport and transformation model for in situ and remote sensing measurement data are compared. The algorithm based on the ensembles of the adjoint problem solutions is applied to solve the inverse problem. The solutions are compared in the Novosibirsk city inverse modeling scenario.

KW - adjoint ensemble

KW - atmospheric chemistry

KW - in situ measurements

KW - inverse source problem

KW - Novosibirsk city

KW - remote sensing data

UR - http://www.scopus.com/inward/record.url?scp=85077959050&partnerID=8YFLogxK

U2 - 10.1117/12.2540901

DO - 10.1117/12.2540901

M3 - Conference contribution

AN - SCOPUS:85077959050

T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - 25th International Symposium on Atmospheric and Ocean Optics

A2 - Matvienko, Gennadii G.

A2 - Romanovskii, Oleg A.

PB - SPIE

T2 - 25th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics 2019

Y2 - 30 June 2019 through 5 July 2019

ER -

ID: 23188092