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Data · dataset · 2023

Elemental characterization of PM2.5 aerosol samples in Beirut city and source apportionment investigation (Metadata RADIATE TA Proposal 23003187-ST)

Listed in Istituto Nazionale di Fisica Nucleare. Centro Nazionale Analisi Fotogrammi

Proposal title "Elemental characterization of PM2.5 aerosol samples in Beirut city and source apportionment investigation".

Description

Measurements carried out at the external beam set-up for atmospheric aerosol analysis of the INFN LABEC accelerator laboratory, on 21 April 2023. Hands-off mode. \n\n The samples in this proposal concern approximately 250 and were collected from Beirut City using ISAP sampler between 2020 and 2022.

The main feature of the sampling campaign was to sample twice a week, on Wednesdays and Sundays. For 24 hours, PM2.5 samples were collected on 47 mm Teflon filters in urban areas \n\n Around 250 airborne PM2.5 samples were collected from Beirut City, Lebanon, using an ISAP sampler between 2020 and 2022. The main feature of the sampling campaign was to sample twice a week, on Wednesdays and Sundays.

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For 24 hours, the PM2.5 were deposited on 47 mm Teflon filters in urban areas with an air volume of approximately 55 m 3 . The expected air pollution sources that could contribute to the elemental and organic content of PM2.5 can be natural or anthropogenic origin, such as dust storm, fires, transportation vehicles, random burning of waste, diesel generators, etc. These samples were analyzed by PIXE technique using an extracted proton beam of 3.0 MeV (energy on target) to determine their elemental composition.

A set of elemental standards and an aerosol reference standard (NIST 2783) were analyzed as well for quality assurance purposes and to check the accuracy of quantitative results.

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Atmospheric sciences 74%
Provenance · 1 source records, 7 field assertions
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Istituto Nazionale di Fisica Nucleare. Centro Nazionale Analisi Fotogrammi771492 d agoJSON v1
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concepts[field].anzsrc:group:3701enrichment · openaccessrepository ittaxonomy-embedding@1.1.0title+keywords+description (74%)
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