Report on the use of the satellite data and data fusion techniques, based on the near real time data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00020699%3A_____%2F19%3AN0000172" target="_blank" >RIV/00020699:_____/19:N0000172 - 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

Report on the use of the satellite data and data fusion techniques, based on the near real time data

Popis výsledku v původním jazyce

Within the SAMIRA project, an important task was a development of data fusion methods combining in situ measurements, satellite observations and chemical transport modelling (CTM) outputs. These three sources are mutually complimentary – in situ measurements provide accurate actual levels of concentrations, satellite data provide reasonably continuous observations of spatial patterns and modelling outputs provide spatially continuous coverage of given area. None of these datasets on its own is ideal for mapping purposes due to either substantial data gaps, insufficient spatial resolution, or large uncertainties. For the combination of different data sources, a range of various methods can be used to create spatial concentration fields. Such methods are often referred to as 'data assimilation' and 'data fusion'. Data fusion is a subset of data assimilation methods in a wider sense. One of the often used data fusion methods is residual kriging. In this report, the data fusion has been applied in near real time (NRT). NRT data are examined for four pollutants (NO2, SO2, PM10, and PM2.5) at two spatial domains, namely the Czech Republic and the most of the Europe (covering all four relevant countries, i.e. Czech Republic, Poland, Romania and southern Norway). Two time steps are taken into account – hourly data for all pollutants and daily only for PM10, and PM2.5.

Název v anglickém jazyce

Report on the use of the satellite data and data fusion techniques, based on the near real time data

Popis výsledku anglicky

Within the SAMIRA project, an important task was a development of data fusion methods combining in situ measurements, satellite observations and chemical transport modelling (CTM) outputs. These three sources are mutually complimentary – in situ measurements provide accurate actual levels of concentrations, satellite data provide reasonably continuous observations of spatial patterns and modelling outputs provide spatially continuous coverage of given area. None of these datasets on its own is ideal for mapping purposes due to either substantial data gaps, insufficient spatial resolution, or large uncertainties. For the combination of different data sources, a range of various methods can be used to create spatial concentration fields. Such methods are often referred to as 'data assimilation' and 'data fusion'. Data fusion is a subset of data assimilation methods in a wider sense. One of the often used data fusion methods is residual kriging. In this report, the data fusion has been applied in near real time (NRT). NRT data are examined for four pollutants (NO2, SO2, PM10, and PM2.5) at two spatial domains, namely the Czech Republic and the most of the Europe (covering all four relevant countries, i.e. Czech Republic, Poland, Romania and southern Norway). Two time steps are taken into account – hourly data for all pollutants and daily only for PM10, and PM2.5.

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

10511 - Environmental sciences (social aspects to be 5.7)

Projekt

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Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2019

Kód důvěrnosti údajů

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