Longlong Wang (Avtor), Samo Stanič (Avtor), Klemen Bergant (Avtor), William Eichinger (Avtor), Asta Gregorič (Avtor), Griša Močnik (Avtor), Luka Drinovec (Avtor)

Povzetek

Vipava valley in southwest Slovenia is a representative hot-spot for complex mixtures of different aerosol types of both anthropogenic and natural origin in mountainous terrain. An investigation of aerosol properties throughout the troposphere in different atmospheric conditions was made possible by a deployment of a two-wavelength polarization Raman lidar system combining with in-situ measurements in the valley (in the town of Ajdovščina) from September 2017. Using its aerosol identification capabilities, which are based on particle depolarization ratio and lidar ratio measurements, it was possible to identify predominant aerosol types in the observed atmospheric structures, for example in different atmospheric layers in the case of stratified atmosphere. Primary anthropogenic aerosols within the valley were found to be mainly emitted from two sources: individual domestic heating systems, which mostly use biomass fuel, and from traffic. A considerable fraction of natural aerosols (for example mineral dust and sea salt), transported over large distances, were observed both above and entering into the planetary boundary layer. According to the properties of different aerosol types, backscatter contribution of each aerosol type was evaluated and the corresponding extinction contribution was derived from lidar observations. Statistical analysis of the presence of different aerosol types was performed on the entire available dataset from 2017 and 2018.

Ključne besede

lidar;aerosol type;Vipava valley;

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.12 - Objavljeni povzetek znanstvenega prispevka na konferenci
Organizacija: UNG - Univerza v Novi Gorici
UDK: 52
COBISS: 5275643 Povezava se bo odprla v novem oknu
Št. ogledov: 3540
Št. prenosov: 0
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

URN: URN:SI:UNG
Vrsta dela (COBISS): Delo ni kategorizirano
Strani: 1 str.
ID: 10990418