| Title: |
Improving data analysis for size-segregated atmospheric aerosol samples |
| Authors: |
F. Crova; V. Bernardoni; A. C. Forello; S. Valentini; G. Valli; R. Vecchi |
| Contributors: |
F. Crova; V. Bernardoni; A.C. Forello; S. Valentini; G. Valli; R. Vecchi |
| Publisher Information: |
Società Italiana di Fisica |
| Publication Year: |
2021 |
| Collection: |
The University of Milan: Archivio Istituzionale della Ricerca (AIR) |
| Subject Terms: |
Settore FIS/07 - Fisica Applicata(Beni Culturali; Ambientali; Biol.e Medicin) |
| Description: |
Size-segregated atmospheric aerosol samples collected with cascade impactors can provide valuable information for the study of aerosol emission sources and processes, especially when size distributions of chemical compounds are retrieved. Nevertheless, such data are rare in the literature and, when available, they are often presented as discrete size distributions since data analysis is not straightforward, thus preventing to retrieve detailed modal structure information. For this reason, all the main steps for a robust analysis of size-segregated data are illustrated in this paper. The MICRON code was used to perform data inversion and a sensitivity test on the main input parameters (weights, smoothing parameter, and derivative order) was carried out to investigate how the output is affected by their variations. A method to fit the inverted distribution with log-normal functions and to validate the final output has been implemented and discussed through a case-study |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| Relation: |
info:eu-repo/semantics/altIdentifier/wos/WOS:000694009700017; volume:44; issue:1; firstpage:1; lastpage:10; numberofpages:10; journal:IL NUOVO CIMENTO C; https://hdl.handle.net/2434/844575 |
| DOI: |
10.1393/ncc/i2021-21013-x |
| Availability: |
https://hdl.handle.net/2434/844575; https://doi.org/10.1393/ncc/i2021-21013-x |
| Rights: |
info:eu-repo/semantics/openAccess |
| Accession Number: |
edsbas.BAE3B625 |
| Database: |
BASE |