The effect of clouds and precipitation on the aerosol concentrations and composition in a boreal forest environment
dc.contributor.author | Isokääntä, S | |
dc.contributor.author | Kim, P | |
dc.contributor.author | Mikkonen, S | |
dc.contributor.author | Kühn, T | |
dc.contributor.author | Kokkola, H | |
dc.contributor.author | Yli-Juuti, T | |
dc.contributor.author | Heikkinen, L | |
dc.contributor.author | Luoma, K | |
dc.contributor.author | Petäjä, T | |
dc.contributor.author | Kipling, Z | |
dc.contributor.author | Partridge, D | |
dc.contributor.author | Virtanen, A | |
dc.date.accessioned | 2022-10-04T13:09:11Z | |
dc.date.issued | 2022-09-13 | |
dc.date.updated | 2022-10-04T11:48:27Z | |
dc.description.abstract | Atmospheric aerosol particle concentrations are strongly affected by various wet processes, including below and in-cloud wet scavenging and in-cloud aqueous-phase oxidation. We studied how wet scavenging and cloud processes affect particle concentrations and composition during transport to a rural boreal forest site in northern Europe. For this investigation, we employed air mass history analysis and observational data. Long-term particle number size distribution (∼15 years) and composition measurements (∼8 years) were combined with air mass trajectories with relevant variables from reanalysis data. Some such variables were rainfall rate, relative humidity, and mixing layer height. Additional observational datasets, such as temperature and trace gases, helped further evaluate wet processes along trajectories with mixed effects models. All chemical species investigated (sulfate, black carbon, and organics) exponentially decreased in particle mass concentration as a function of accumulated precipitation along the air mass route. In sulfate (SO4) aerosols, clear seasonal differences in wet removal emerged, whereas organics (Org) and equivalent black carbon (eBC) exhibited only minor differences. The removal efficiency varied slightly among the different reanalysis datasets (ERA-Interim and Global Data Assimilation System; GDAS) used for the trajectory calculations due to the difference in the average occurrence of precipitation events along the air mass trajectories between the reanalysis datasets. Aqueous-phase processes were investigated by using a proxy for air masses travelling inside clouds. We compared air masses with no experience of approximated in-cloud conditions or precipitation during the past 24 h to air masses recently inside non-precipitating clouds before they entered SMEAR II (Station for Measuring Ecosystem–Atmosphere Relations). Significant increases in SO4 mass concentration were observed for the latter air masses (recently experienced non-precipitating clouds). Our mixed effects model considered other contributing factors affecting particle mass concentrations in SMEAR II: examples were trace gases, local meteorology, and diurnal variation. This model also indicated in-cloud SO4 production. Despite the reanalysis dataset used in the trajectory calculations, aqueous-phase SO4 formation was observed. Particle number size distribution measurements revealed that most of the in-cloud SO4 formed can be attributed to particle sizes larger than 200 nm (electrical mobility diameter). Aqueous-phase secondary organic aerosol (aqSOA) formation was non-significant. | en_GB |
dc.description.sponsorship | European Union Horizon 2020 | en_GB |
dc.description.sponsorship | Knut och Alice Wallenbergs Stiftelse | en_GB |
dc.description.sponsorship | Academy of Finland | en_GB |
dc.description.sponsorship | Itä-Suomen Yliopisto | en_GB |
dc.identifier.citation | Vol. 22(17), pp. 11823-11843 | en_GB |
dc.identifier.doi | https://doi.org/10.5194/acp-22-11823-2022 | |
dc.identifier.grantnumber | 821205 | en_GB |
dc.identifier.grantnumber | 638703 | en_GB |
dc.identifier.grantnumber | 865799 | en_GB |
dc.identifier.grantnumber | 2015.0162 | en_GB |
dc.identifier.grantnumber | 317373 | en_GB |
dc.identifier.grantnumber | 317390 | en_GB |
dc.identifier.grantnumber | 337550 | en_GB |
dc.identifier.grantnumber | 325022 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/131084 | |
dc.identifier | ORCID: 0000-0002-5970-901X (Partridge, Daniel) | |
dc.language.iso | en | en_GB |
dc.publisher | European Geosciences Union / Copernicus Publications | en_GB |
dc.relation.url | https://smear.avaa.csc.fi/download | en_GB |
dc.relation.url | http://ebas.nilu.no/ | en_GB |
dc.relation.url | https://www.ready.noaa.gov/HYSPLIT_traj.php | en_GB |
dc.rights | © Author(s) 2022. Open access. This work is distributed under the Creative Commons Attribution 4.0 License. | en_GB |
dc.title | The effect of clouds and precipitation on the aerosol concentrations and composition in a boreal forest environment | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2022-10-04T13:09:11Z | |
dc.identifier.issn | 1680-7316 | |
dc.description | This is the final version. Available on open access from the European Geosciences Union via the DOI in this record | en_GB |
dc.description | Data availability: Raw data were collected by INAR, University of Helsinki. Field data (particle number size distributions, meteorological variables, black carbon, and trace gases) are available from https://smear.avaa.csc.fi/download (last access: 20 February 2022; Ministry of Education and Culture of Finland and CSC, 2022). The ACSM data on aerosol composition are available from the EBAS database at http://ebas.nilu.no/ (last access: 20 February 2022; NILU, 2022). The pre-processed HYSPLIT trajectory data can be obtained from the corresponding author, and the trajectories can be freely calculated at the web page https://www.ready.noaa.gov/HYSPLIT_traj.php (last access: 14 October 2021; NOAA ARL, 2021). | en_GB |
dc.identifier.eissn | 1680-7324 | |
dc.identifier.journal | Atmospheric Chemistry and Physics | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2022-08-17 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2022-09-13 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2022-10-04T13:05:08Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2022-10-04T13:09:16Z | |
refterms.panel | B | en_GB |
refterms.dateFirstOnline | 2022-09-13 |
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