Effective Density and Mixing State of Aerosol Particles in a Near-Traffic Urban Environment

Research output: Contribution to journalJournal articleResearchpeer-review

  • Jenny Rissler
  • Erik Z Nordin
  • Axel C Eriksson
  • Patrik T Nilsson
  • Mia Frosch
  • Moa K Sporre
  • Aneta Wierzbicka
  • Birgitta Svenningsson
  • Jakob Löndahl
  • Maria E Messing
  • Staffan Sjogren
  • Hemmingsen, Jette Gjerke
  • Loft, Steffen
  • Joakim H Pagels
  • Erik Swietlicki

In urban environments, airborne particles are continuously emitted, followed by atmospheric aging. Also, particles emitted elsewhere, transported by winds, contribute to the urban aerosol. We studied the effective density (mass-mobility relationship) and mixing state with respect to the density of particles in central Copenhagen, in wintertime. The results are related to particle origin, morphology, and aging. Using a differential mobility analyzer-aerosol particle mass analyzer (DMA-APM), we determined that particles in the diameter range of 50-400 nm were of two groups: porous soot aggregates and more dense particles. Both groups were present at each size in varying proportions. Two types of temporal variability in the relative number fraction of the two groups were found: soot correlated with intense traffic in a diel pattern and dense particles increased during episodes with long-range transport from polluted continental areas. The effective density of each group was relatively stable over time, especially of the soot aggregates, which had effective densities similar to those observed in laboratory studies of fresh diesel exhaust emissions. When heated to 300 °C, the soot aggregate volatile mass fraction was ∼10%. For the dense particles, the volatile mass fraction varied from ∼80% to nearly 100%.

Original languageEnglish
JournalEnvironmental Science & Technology (Washington)
Issue number11
Pages (from-to)6300–6308
Number of pages9
Publication statusPublished - 3 Jun 2014

    Research areas

  • Aerosols, Cities, Denmark, Environmental Monitoring, Particle Size, Particulate Matter, Time Factors, Vehicle Emissions

ID: 132418136