bibtype A - Abstract
ARLID 0557855
utime 20231122150600.4
mtime 20220602235959.9
title (primary) (eng) Two stage inversion method for microplastics emission estimation
specification
page_count 1 s.
media_type E
serial
ARLID cav_un_epca*0558165
title EGU General Assembly 2022
publisher
place Göttingen
name European Geosciences Union
year 2022
keyword microplastics emission
keyword two-stage inversion algorithm
keyword FLEXPART
author (primary)
ARLID cav_un_auth*0267768
name1 Tichý
name2 Ondřej
institution UTIA-B
full_dept (cz) Adaptivní systémy
full_dept (eng) Department of Adaptive Systems
department (cz) AS
department (eng) AS
full_dept Department of Adaptive Systems
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0363740
name1 Evangeliou
name2 N.
country NO
author
ARLID cav_un_auth*0101207
name1 Šmídl
name2 Václav
institution UTIA-B
full_dept (cz) Adaptivní systémy
full_dept Department of Adaptive Systems
department (cz) AS
department AS
full_dept Department of Adaptive Systems
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url http://library.utia.cas.cz/separaty/2022/AS/tichy-0557855.pdf
cas_special
project
project_id GA20-27939S
agency GA ČR
ARLID cav_un_auth*0391986
abstract (eng) The goal of this contribution is to explore two-stage inversion algorithm for spatio-temporal emission estimation (2D and time) from deposition measurements of microplastics and microfibers from Western USA. We consider the linear inversion model formulated as y = M x , where y is the measurement vector, M is source-receptor-sensitivity matrix computed using\nLagrangian particle dispersion model FLEXPART, and x is the unknown emission vector from given spatial element. The inverse problem is typically ill-conditioned due to the measurements sparsity, hence, we propose two stage algorithm for inversion of this type. First, we run the inversion algorithm for the whole spatial domain, hence, we obtain averaged emission from each spatial element of the considered spatial domain. Second, we use the estimated emission from the first step (common for all spatial elements) as a prior emission in the second step where the inversion problem is considered for each spatial element separately. We demonstrate that this approach regularizes the inversion problem of spatio-temporal emission from sparse measurements, concretely on microplastics and microfibers emission estimation in Western USA.
action
ARLID cav_un_auth*0431912
name EGU General Assembly 2022
dates 20220523
mrcbC20-s 20220527
place Vienna / Online
url https://www.egu22.eu/
country AT
RIV BC
FORD0 10000
FORD1 10200
FORD2 10201
reportyear 2023
num_of_auth 3
mrcbC52 4 O 4o 20231122150600.4
presentation_type PR
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0332281
mrcbC61 1
confidential S
arlyear 2022
mrcbTft \nSoubory v repozitáři: 0557855.pdf
mrcbU14 SCOPUS
mrcbU24 PUBMED
mrcbU34 WOS
mrcbU63 cav_un_epca*0558165 EGU General Assembly 2022 Göttingen European Geosciences Union 2022