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Source apportionment of particle number size distribution at the street canyon and urban background sites

  • Sami D. Harni*
  • , Minna Aurela
  • , Sanna Saarikoski
  • , Jarkko V. Niemi
  • , Harri Portin
  • , Hanna Manninen
  • , Ville Leinonen
  • , Pasi Aalto
  • , Phil K. Hopke
  • , Tuukka Petäjä
  • , Topi Rönkkö
  • , Hilkka Timonen
  • *Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

10 Citations (Scopus)
8 Downloads (Pure)

Abstract

Particle size is one of the key factors influencing how aerosol particles affect their climate and health effects. Therefore, a better understanding of particle size distributions from various sources is crucial. In urban environments, aerosols are produced in a large number of varying processes and conditions. This study intended to develop the source apportionment of urban aerosols by utilising a novel approach to positive matrix factorisation (PMF). The particle source profiles were detected in particle number size distribution data measured simultaneously in a street canyon and at a nearby urban background station between February 2015 and June 2019 in Helsinki, southern Finland. The novelty of the method is combining the data from both sites and finding profiles for the unified data. Five aerosol sources were found. Four of them were detected at both of the stations: slightly aged traffic (TRA2), secondary combustion aerosol (SCA), secondary aerosol (SecA), and long-range-transported aerosol (LRT). One of the sources, fresh traffic (TRA1) was only detected at a street canyon. The factors were identified based on available auxiliary data. Additionally, the trends of the found factors were studied, and statistically significant decreasing trends were found for TRA1 and SecA. A statistically significant increasing trend was found for TRA2. This work implies that traffic-related aerosols remain important in urban environments and that aerosol sources can be detected using only particle number size distribution data as input in the PMF method.

Original languageEnglish
Pages (from-to)12143-12160
Number of pages18
JournalAtmospheric Chemistry and Physics
Volume24
Issue number21
DOIs
Publication statusPublished - 30 Oct 2024
Publication typeA1 Journal article-refereed

Funding

The authors acknowledge the financial support of the European Union's Horizon Europe 2020 research and innovation programme, Technology Industries of Finland Centennial Foundation, Business Finland, participating companies, and New York State Energy Research and Development Authority. AI tools were used to improve the language of the article. This research has been supported by the European Union's Horizon 2020 research and innovation programme (grant nos. 101096133 (PAREMPI), 814978 (TUBE), and 101036245 (RI-URBANS); the Urban Air Quality 2.0 project, funded by Technology Industries of Finland Centennial Foundation; and the Black Carbon Footprint project, funded by Business Finland (grant no. 528/31/2019). The work in Rochester, NY, was funded by the New York State Energy Research and Development Authority under contract nos. 59802 and 125993.

FundersFunder number
European Union's Horizon Europe 2020 research and innovation programme
Teknologiateollisuuden 100-Vuotisjuhlasäätiö
Urban Air Quality
Horizon 2020814978, 101096133
Horizon 2020
New York State Energy Research and Development Authority59802, 125993
New York State Energy Research and Development Authority
TUBE101036245
Business Finland528/31/2019
Business Finland

    Publication forum classification

    • Publication forum level 3

    ASJC Scopus subject areas

    • Atmospheric Science

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