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 |
|
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 |
|