| Autor: |
Aliaga, Diego, Tuovinen, Santeri, Zhang, Tinghan, Lampilahti, Janne, Li, Xinyang, Ahonen, Lauri, Kokkonen, Tom, Nieminen, Tuomo, Hakala, Simo, Paasonen, Pauli, Bianchi, Federico, Worsnop, Doug, Kerminen, Veli-Matti, Kulmala, Markku |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| ISSN: |
2940-3391 |
| Popis: |
Here we introduce a new method, termed “Nano Ranking Analysis,” for characterizing new particle formation (NPF) from atmospheric observations. Using daily variations of the particle number concentration at sizes immediately above the continuous mode of molecular clusters, here in practice 2.5–5 nm - ΔN2.5–5, we can determine the occurrence and estimate the strength of atmospheric NPF events. After determining the value of ΔN2.5–5 for all the days during a period under consideration, the next step of the analysis is to rank the days based on this simple metric. The analysis is completed by grouping the days either into a number of percentile intervals based on their ranking or into a few modes in the distribution of log(ΔN2.5–5) values. Using five years (2018–2022) of data from the SMEAR II station in Hyytiälä, Finland, we found that the days with higher (lower) ranking values had, on average, both higher (lower) probability of NPF events and higher (lower) particle formation rates. The new method provides probabilistic information about the occurrence and intensity of NPF events and is expected to serve as a valuable tool to define the origin of newly formed particles at many types of environments that are affected by multiple sources of aerosol precursors. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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