Standard

Air pollution modelling in urban environment based on a priori and reconstructed data. / Gochakov, A. V.; Penenko, A. V.; Antokhin, P. N. et al.

In: IOP Conference Series: Earth and Environmental Science, Vol. 211, No. 1, 012050, 17.12.2018.

Research output: Contribution to journal › Conference article › peer-review

Harvard

Gochakov, AV, Penenko, AV, Antokhin, PN & Kolker, AB 2018, 'Air pollution modelling in urban environment based on a priori and reconstructed data', IOP Conference Series: Earth and Environmental Science, vol. 211, no. 1, 012050. https://doi.org/10.1088/1755-1315/211/1/012050

APA

Gochakov, A. V., Penenko, A. V., Antokhin, P. N., & Kolker, A. B. (2018). Air pollution modelling in urban environment based on a priori and reconstructed data. IOP Conference Series: Earth and Environmental Science, 211(1), [012050]. https://doi.org/10.1088/1755-1315/211/1/012050

Vancouver

Gochakov AV, Penenko AV, Antokhin PN, Kolker AB. Air pollution modelling in urban environment based on a priori and reconstructed data. IOP Conference Series: Earth and Environmental Science. 2018 Dec 17;211(1):012050. doi: 10.1088/1755-1315/211/1/012050

Author

Gochakov, A. V. ; Penenko, A. V. ; Antokhin, P. N. et al. / Air pollution modelling in urban environment based on a priori and reconstructed data. In: IOP Conference Series: Earth and Environmental Science. 2018 ; Vol. 211, No. 1.

BibTeX

@article{af7b7d1ede2c4227b72e1ef77c326951,
title = "Air pollution modelling in urban environment based on a priori and reconstructed data",
abstract = "This paper presents preliminary results of the effectiveness analysis of an air quality forecasting system for the city of Novosibirsk with replenishment of the missing information on emission sources by solving an inverse problem with urban monitoring network data. In solving the inverse problem, a priori information about the location and mode of the sources is used. To simulate concentration distributions, the WRF-Chem model is used, and a simplified model of chemical transport is applied to solving the inverse problem. These models are offline coupled in a hybrid forecast system in order to improve the initial information about the spatial distribution of emission intensity and air quality forecast, respectively. The results of numerical experiments and their analysis are presented. The influence of an urban parameterization on the results of the forecast is shown.",
author = "Gochakov, {A. V.} and Penenko, {A. V.} and Antokhin, {P. N.} and Kolker, {A. B.}",
note = "Publisher Copyright: {\textcopyright} Published under licence by IOP Publishing Ltd.; International Conference and Early Career Scientists School on Environmental Observations, Modeling and Information Systems, ENVIROMIS 2018 ; Conference date: 05-07-2018 Through 11-07-2018",
year = "2018",
month = dec,
day = "17",
doi = "10.1088/1755-1315/211/1/012050",
language = "English",
volume = "211",
journal = "IOP Conference Series: Earth and Environmental Science",
issn = "1755-1307",
publisher = "IOP Publishing Ltd.",
number = "1",

}

RIS

TY - JOUR

T1 - Air pollution modelling in urban environment based on a priori and reconstructed data

AU - Gochakov, A. V.

AU - Penenko, A. V.

AU - Antokhin, P. N.

AU - Kolker, A. B.

N1 - Publisher Copyright: © Published under licence by IOP Publishing Ltd.

PY - 2018/12/17

Y1 - 2018/12/17

N2 - This paper presents preliminary results of the effectiveness analysis of an air quality forecasting system for the city of Novosibirsk with replenishment of the missing information on emission sources by solving an inverse problem with urban monitoring network data. In solving the inverse problem, a priori information about the location and mode of the sources is used. To simulate concentration distributions, the WRF-Chem model is used, and a simplified model of chemical transport is applied to solving the inverse problem. These models are offline coupled in a hybrid forecast system in order to improve the initial information about the spatial distribution of emission intensity and air quality forecast, respectively. The results of numerical experiments and their analysis are presented. The influence of an urban parameterization on the results of the forecast is shown.

AB - This paper presents preliminary results of the effectiveness analysis of an air quality forecasting system for the city of Novosibirsk with replenishment of the missing information on emission sources by solving an inverse problem with urban monitoring network data. In solving the inverse problem, a priori information about the location and mode of the sources is used. To simulate concentration distributions, the WRF-Chem model is used, and a simplified model of chemical transport is applied to solving the inverse problem. These models are offline coupled in a hybrid forecast system in order to improve the initial information about the spatial distribution of emission intensity and air quality forecast, respectively. The results of numerical experiments and their analysis are presented. The influence of an urban parameterization on the results of the forecast is shown.

UR - http://www.scopus.com/inward/record.url?scp=85059581495&partnerID=8YFLogxK

U2 - 10.1088/1755-1315/211/1/012050

DO - 10.1088/1755-1315/211/1/012050

M3 - Conference article

AN - SCOPUS:85059581495

VL - 211

JO - IOP Conference Series: Earth and Environmental Science

JF - IOP Conference Series: Earth and Environmental Science

SN - 1755-1307

IS - 1

M1 - 012050

T2 - International Conference and Early Career Scientists School on Environmental Observations, Modeling and Information Systems, ENVIROMIS 2018

Y2 - 5 July 2018 through 11 July 2018

ER -

ID: 18072327