Using satellite data and data fusion techniques for air quality mapping

Result code in 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>
Result on the web
<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
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Result language
angličtina
Original language name
Using satellite data and data fusion techniques for air quality mapping
Original language description
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).
Czech name
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Czech description
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Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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