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Akademický článek

Characterization of volatile organic compounds and submicron organic aerosol in a traffic environment

Autor: S. Saarikoski, H. Hellén, A. P. Praplan, S. Schallhart, P. Clusius, J. V. Niemi, A. Kousa, T. Tykkä, R. Kouznetsov, M. Aurela, L. Salo, T. Rönkkö, L. M. F. Barreira, L. Pirjola, H. Timonen

Publikováno v: Atmospheric Chemistry and Physics, Vol 23, Pp 2963-2982 (2023)

Urban air consists of a complex mixture of gaseous and particulate species from anthropogenic and biogenic sources that are further processed in the atmosphere. This study investigated the characteristics and sources of volatile organic compounds (VO

Externí odkaz: https://doaj.org/article/c7d59f3d19694aea90498123dcea9821

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Akademický článek

Atmospherically Relevant Chemistry and Aerosol box model – ARCA box (version 1.2)

Autor: P. Clusius, C. Xavier, L. Pichelstorfer, P. Zhou, T. Olenius, P. Roldin, M. Boy

Publikováno v: Geoscientific Model Development, Vol 15, Pp 7257-7286 (2022)

We introduce the Atmospherically Relevant Chemistry and Aerosol box model ARCA box (v.1.2.2). It is a zero-dimensional process model with a focus on atmospheric chemistry and submicron aerosol processes, including cluster formation. A novel feature i

Externí odkaz: https://doaj.org/article/3d34a7864fed414a90546403541982c0

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Akademický článek

Secondary aerosol formation in marine Arctic environments: a model measurement comparison at Ny-Ålesund

Autor: C. Xavier, M. Baykara, R. Wollesen de Jonge, B. Altstädter, P. Clusius, V. Vakkari, R. Thakur, L. Beck, S. Becagli, M. Severi, R. Traversi, R. Krejci, P. Tunved, M. Mazzola, B. Wehner, M. Sipilä, M. Kulmala, M. Boy, P. Roldin

Publikováno v: Atmospheric Chemistry and Physics, Vol 22, Pp 10023-10043 (2022)

In this study, we modeled the aerosol particle formation along air mass trajectories arriving at the remote Arctic research stations Gruvebadet (67 m a.s.l.) and Zeppelin (474 m a.s.l.), Ny-Ålesund, during May 2018. The aim of this study was to impr

Externí odkaz: https://doaj.org/article/cf48584521fc4ea09a5891812b0e9e02

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Report

Neural Network Emulator for Atmospheric Chemical ODE

Autor: Liu, Zhi-Song, Clusius, Petri, Boy, Michael

Modeling atmospheric chemistry is complex and computationally intense. Given the recent success of Deep neural networks in digital signal processing, we propose a Neural Network Emulator for fast chemical concentration modeling. We consider atmospher

Externí odkaz: http://arxiv.org/abs/2408.01829