English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

One of the main issues arising from the comparison of ground-basedand satellite measurements is the difference in spatial representativeness,which for locations with inhomogeneous spatial distribution of pollutants maylead to significant differences between the two data sets. In order toinvestigate the spatial variability of tropospheric NO2 within asub-satellite pixel, a campaign which lasted for about 6 months washeld in the greater area of Thessaloniki, Greece. Threemulti-axial differential optical absorption spectroscopy (MAX-DOAS) systemsperformed measurements of tropospheric NO2 columns at different sitesrepresentative of urban, suburban and rural conditions. The directcomparison of these ground-based measurements with corresponding products from the Ozone Monitoring Instrument onboard NASA's Aura satellite (OMI/Aura) showed good agreement over the rural and suburban areas, while the comparison with the Global Ozone Monitoring Experiment-2 (GOME-2) onboard EUMETSAT'sMeteorological Operational satellites' (MetOp-A and MetOp-B) observations is good only over the rural area. GOME-2A and GOME-2B sensors show an averageunderestimation of tropospheric NO2 over the urban area of about10.51 ± 8.32  ×  1015 and 10.21 ± 8.87  × 1015 molecules cm−2,respectively. The mean difference between ground-based and OMI observations issignificantly lower (6.60 ± 5.71  ×  1015 molecules cm−2). The differences found in the comparisons of MAX-DOAS data with the different satellite sensors can be attributed to the higher spatial resolution of OMI, as well as the different overpass times and NO2 retrieval algorithms of the satellites. OMI data were adjusted using factors calculated by an air quality modeling tool, consisting of the Weather Research and Forecasting (WRF) mesoscale meteorological model and the Comprehensive Air Quality Model with Extensions (CAMx) multiscale photochemical transport model. This approach resulted in significant improvement of the comparisons over the urban monitoring site. The average difference of OMI observations from MAX-DOAS measurements wasreduced to −1.68 ± 5.01  ×  1015 molecules cm−2

atmospheric chemistry and physics

Comparisons of ground-based tropospheric NO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; MAX-DOAS measurements to satellite observations with the aid of an air quality model over the Thessaloniki area, Greece