Using satellite data and data fusion techniques for air quality mapping

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00020699%3A_____%2F18%3AN0000155" target="_blank" >RIV/00020699:_____/18:N0000155 - isvavai.cz</a>

Výsledek na webu

<a href="https://meetingorganizer.copernicus.org/EGU2018/EGU2018-12392.pdf" target="_blank" >https://meetingorganizer.copernicus.org/EGU2018/EGU2018-12392.pdf</a>

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Using satellite data and data fusion techniques for air quality mapping

Popis výsledku v původním jazyce

Poster at EGU General Assembly 2018, 7–12 April 2018, Vienna, Austria. Air quality mapping plays an important role in informing the public about air pollution levels in various areas. For this purpose different sources of air quality data can be utilized, in particular in-situ measurements, air quality models and satellite observations. However, none of these data sources is fully sufficient for mapping purposes on its own due to either substantial data gaps, insufficient spatial resolution or large uncertainties.Withinthescopeof the SAMIRA (SAtellite based Monitoring Initiative for Regional Air quality) project, we have aimed to combine these different data sources using data fusion techniques to provide more accurate information within air quality mapping. We present first results of the on-going project where we applied multiple linear regression and spatial interpolation of its residuals (residual kriging) to combine data from in-situ measurements, chemical transport models and satellite observations over the Czech Republic and a major part of Europe. We examined mainly three pollutants (NO2, PM10 and PM2.5) at different temporal resolutions (annual, daily, hourly).

Název v anglickém jazyce

Using satellite data and data fusion techniques for air quality mapping

Popis výsledku anglicky

Poster at EGU General Assembly 2018, 7–12 April 2018, Vienna, Austria. Air quality mapping plays an important role in informing the public about air pollution levels in various areas. For this purpose different sources of air quality data can be utilized, in particular in-situ measurements, air quality models and satellite observations. However, none of these data sources is fully sufficient for mapping purposes on its own due to either substantial data gaps, insufficient spatial resolution or large uncertainties.Withinthescopeof the SAMIRA (SAtellite based Monitoring Initiative for Regional Air quality) project, we have aimed to combine these different data sources using data fusion techniques to provide more accurate information within air quality mapping. We present first results of the on-going project where we applied multiple linear regression and spatial interpolation of its residuals (residual kriging) to combine data from in-situ measurements, chemical transport models and satellite observations over the Czech Republic and a major part of Europe. We examined mainly three pollutants (NO2, PM10 and PM2.5) at different temporal resolutions (annual, daily, hourly).

Druh

O - Ostatní výsledky

CEP obor

—

OECD FORD obor

10509 - Meteorology and atmospheric sciences

Projekt

—

Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2018

Kód důvěrnosti údajů

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