TY - JOUR

T1 - Algorithms for the inverse modelling of transport and transformation of atmospheric pollutants

AU - Penenko, A. V.

PY - 2018/12/17

Y1 - 2018/12/17

N2 - When studying air quality, a key parameter for assessment and forecast is information on emission sources. In applications, this information is not fully available and can be compensated by air quality monitoring data and inverse modelling algorithms. Because of the rapid development of satellite chemical monitoring systems, they are becoming more useful in air quality studies. Such systems provide measurements in the form of concentration field images. In this paper, we consider an inverse source problem and a corresponding data assimilation problem for a chemical transport model. The problem of assimilation of data given as images is considered as a sequence of linked inverse source problems. Each individual inverse problem solution is carried out by variational and Newton-Kantorovich type algorithms. In the numerical experiment presented, an emission source of a primary pollutant is reconstucted via the concetration field of a secondary pollutant. Both data assimilation and inverse problem solution algorithms are capable of approximating the unknown source.

AB - When studying air quality, a key parameter for assessment and forecast is information on emission sources. In applications, this information is not fully available and can be compensated by air quality monitoring data and inverse modelling algorithms. Because of the rapid development of satellite chemical monitoring systems, they are becoming more useful in air quality studies. Such systems provide measurements in the form of concentration field images. In this paper, we consider an inverse source problem and a corresponding data assimilation problem for a chemical transport model. The problem of assimilation of data given as images is considered as a sequence of linked inverse source problems. Each individual inverse problem solution is carried out by variational and Newton-Kantorovich type algorithms. In the numerical experiment presented, an emission source of a primary pollutant is reconstucted via the concetration field of a secondary pollutant. Both data assimilation and inverse problem solution algorithms are capable of approximating the unknown source.

UR - http://www.scopus.com/inward/record.url?scp=85059594467&partnerID=8YFLogxK

U2 - 10.1088/1755-1315/211/1/012052

DO - 10.1088/1755-1315/211/1/012052

M3 - Conference article

AN - SCOPUS:85059594467

VL - 211

JO - IOP Conference Series: Earth and Environmental Science

JF - IOP Conference Series: Earth and Environmental Science

SN - 1755-1307

IS - 1

M1 - 012052

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 -