Atmospheric microplastics modelling and quantification using Gibbs sampler

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F25%3A00638917" target="_blank" >RIV/67985556:_____/25:00638917 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Atmospheric microplastics modelling and quantification using Gibbs sampler

Popis výsledku v původním jazyce

Atmospheric microplastics budget is estimated and associated uncertainties are quantified. We use microplastics measurement data from remote areas and national parks in the United States (Brahney et al., 2020) to estimate atmospheric microplastics budget. Since the number of unknowns in spatial-temporal domain (Eastern US) is much larger than the number of measurements, we regularize the space of possible solutions using spatial-temporal patterns from previously reported sources, namely mineral dust, road dust, agriculture, sea spray and ocean surface. In inversion scheme, we optimize measurements and patterns footprints linked to these measurements with the use of calculated source-receptor-sensitivities from the atmospheric transport model FLEXPART 11.

Název v anglickém jazyce

Atmospheric microplastics modelling and quantification using Gibbs sampler

Popis výsledku anglicky

Atmospheric microplastics budget is estimated and associated uncertainties are quantified. We use microplastics measurement data from remote areas and national parks in the United States (Brahney et al., 2020) to estimate atmospheric microplastics budget. Since the number of unknowns in spatial-temporal domain (Eastern US) is much larger than the number of measurements, we regularize the space of possible solutions using spatial-temporal patterns from previously reported sources, namely mineral dust, road dust, agriculture, sea spray and ocean surface. In inversion scheme, we optimize measurements and patterns footprints linked to these measurements with the use of calculated source-receptor-sensitivities from the atmospheric transport model FLEXPART 11.

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

10102 - Applied mathematics

Projekt

<a href="/cs/project/GA24-10400S" target="_blank" >GA24-10400S: Pokročilé bayesovské odhadování zdrojů atmosférického znečištění</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů