Role of base strength, cluster structure and charge in sulfuric-acid-driven particle formation

Myllys, N.; Kubečka, J.; Besel, V.; Alfaouri, D.; Olenius, T.; Smith, J. N.; Passananti, M.;
2019 | Atmos. Chem. Phys. | 19 (9753-9768)

Molecular-level understanding of synergistic effects in sulfuric acid–amine–ammonia mixed clusters

Myllys, N.; Chee, S.; Olenius, T.; Lawler, M.; Smith, J. N.;
2019 | JOURNAL OF PHYSICAL CHEMISTRY A | 123 (2420-2425)

Guanidine: A Highly Efficient Stabilizer in Atmospheric New-Particle Formation

Myllys, N.; Ponkkonen, T.; Passananti, M.; Elm, J.; Vehkamäki, H.; Olenius, T.
2018 | J Phys Chem A | 122 (4717-4729)

Impacts of future European emission reductions on aerosol particle number concentrations accounting for effects of ammonia, amines and organic species

Julin, J.; Murphy, B. N.; Patoulias, D.; Fountoukis, C.; Olenius, T.; Pandis, S. N.; Riipinen, I.
2018 | Environ. Sci. Technol. | 52 (692-700)

Robust metric for quantifying the importance of stochastic effects on nanoparticle growth

Olenius, T.; Pichelstorfer, L.; Stolzenburg, D.; Winkler, P. M.; Lehtinen, K. E. J.; Riipinen, I.
2018 | Sci Rep | 8

Exploring the potential of nano-Köhler theory to describe the growth of atmospheric molecular clusters by organic vapors using cluster kinetics simulations

Kontkanen, J.; Olenius, T.; Kulmala, M.; Riipinen, I.
2018 | Atmos. Chem. Phys. | 18 (13733-13754)

New particle formation and growth: Creating a new atmospheric phase interface

Olenius, T.; Yli-Juuti, T.; Elm, J.; Kontkanen, J.; Riipinen, I.
2018 | Elsevier Science Publishers | Physical Chemistry of Gas-Liquid Interfaces (315-352) | ISBN: 9780128136416

Formation of atmospheric molecular clusters consisting of sulfuric acid and C8H12O6 tricarboxylic acid

Elm, J.; Myllys, N.; Olenius, T.; Halonen, R.; Kurtén, T.; Vehkamäki, H.;
2017 | Phys Chem Chem Phys | 19 (4877-4886)

Effect of bisulfate, ammonia, and ammonium on the clustering of organic acids and sulfuric acid

Myllys, N.; Olenius, T.; Kurtén, T.; Vehkamäki, H.; Riipinen, I.; Elm, J.;
2017 | J Phys Chem A | 121 (4812-4824)

New particle formation from sulfuric acid and amines: Comparison of monomethylamine, dimethylamine, and trimethylamine

Olenius, T.; Halonen, R.; Kurtén, T.; Henschel, H.; Kupiainen-Määttä, O.; Ortega, I. K.; Jen, C. N.; Vehkamäki, H.; Riipinen, I.;
2017 | J. Geophys. Res.-Atmos. | 122 (7103-7118)

Temperature-dependent diffusion of H2SO4 in air at atmospherically relevant conditions: Laboratory measurements using laminar flow technique

Brus, D.; Skrabalová, L.; Herrmann, E.; Olenius, T.; Trávnicková, T.; Makkonen, U.; Merikanto, J.;
2017 | ATMOSPHERE | 8

Molecular-resolution simulations of new particle formation: Evaluation of common assumptions made in describing nucleation in aerosol dynamics models

2017 | Aerosol Sci Technol | 51 (4) (397-408)
atmospheric nano-particles , coagulation , condensation , events , growth , ions , number concentrations , size , sulfuric acid , supersaturated vapor

Aerosol dynamics models that describe the evolution of a particle distribution incorporate nucleation as a particle formation rate at a small size around a few nanometers in diameter. This rate is commonly obtained from molecular models that cover the distribution below the given formation size - although in reality the distribution of nanometer-sized particles cannot be unambiguously divided into separate sections of particle formation and growth. When incorporating nucleation, the distribution below the formation size is omitted, and the formation rate is assumed to be in a steady state. In addition, to reduce the modeled size range, the formation rate is often scaled to a larger size based on estimated growth and scavenging rates and the assumption that also the larger size is in a steady state. This work evaluates these assumptions by simulating sub-10 nm particle distributions in typical atmospheric conditions with an explicit molecular-resolution model. Particle formation is included either (1) dynamically, that is, the whole size range starting from single vapor molecules is modeled explicitly or (2) implicitly by using an input formation rate as is done in aerosol models. The results suggest that while each assumption can affect the outcome of new particle formation modeling, the most significant source of uncertainty affecting the formation rates and resulting nanoparticle concentrations is the steady-state assumption, which may lead to an overprediction of the concentrations by factors of approximately from two to even orders of magnitude. This can have implications for modeling and predicting atmospheric particle formation.

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