2014, Pietikäinen, J.-P., Mikkonen, S., Hamed, A., Hienola, A.I., Birmili, W., Kulmala, M., Laaksonen, A.

This work describes improvements in the regional aerosol–climate model REMO-HAM in order to simulate more realistically the process of atmospheric new particle formation (NPF). A new scheme was implemented to simulate OH radical concentrations using a proxy approach based on observations and also accounting for the effects of clouds upon OH concentrations. Second, the nucleation rate calculation was modified to directly simulate the formation rates of 3 nm particles, which removes some unnecessary steps in the formation rate calculations used earlier in the model. Using the updated model version, NPF over Europe was simulated for the periods 2003–2004 and 2008–2009. The statistics of the simulated particle formation events were subsequently compared to observations from 13 ground-based measurement sites. The new model shows improved agreement with the observed NPF rates compared to former versions and can simulate the event statistics realistically for most parts of Europe.

2013, Westervelt, D.M., Pierce, J.R., Riipinen, I., Trivitayanurak, W., Hamed, A., Kulmala, M., Laaksonen, A., Decesari, S., Adams, P.J.

Aerosol nucleation occurs frequently in the atmosphere and is an important source of particle number. Observations suggest that nucleated particles are capable of growing to sufficiently large sizes that they act as cloud condensation nuclei (CCN), but some global models have reported that CCN concentrations are only modestly sensitive to large changes in nucleation rates. Here we present a novel approach for using long-term size distribution observations to evaluate a global aerosol model's ability to predict formation rates of CCN from nucleation and growth events. We derive from observations at five locations nucleation-relevant metrics such as nucleation rate of particles at diameter of 3 nm (J3), diameter growth rate (GR), particle survival probability (SP), condensation and coagulation sinks, and CCN formation rate (J100). These quantities are also derived for a global microphysical model, GEOS-Chem-TOMAS, and compared to the observations on a daily basis. Using GEOS-Chem-TOMAS, we simulate nucleation events predicted by ternary (with a 10−5 tuning factor) or activation nucleation over one year and find that the model slightly understates the observed annual-average CCN formation mostly due to bias in the nucleation rate predictions, but by no more than 50% in the ternary simulations. At the two locations expected to be most impacted by large-scale regional nucleation, Hyytiälä and San Pietro Capofiume, predicted annual-average CCN formation rates are within 34 and 2% of the observations, respectively. Model-predicted annual-average growth rates are within 25% across all sites but also show a slight tendency to underestimate the observations, at least in the ternary nucleation simulations. On days that the growing nucleation mode reaches 100 nm, median single-day survival probabilities to 100 nm for the model and measurements range from less than 1–6% across the five locations we considered; however, this does not include particles that may eventually grow to 100 nm after the first day. This detailed exploration of new particle formation and growth dynamics adds support to the use of global models as tools for assessing the contribution of microphysical processes such as nucleation to the total number and CCN budget.

2010, Spracklen, D.V., Carslaw, K.S., Merikanto, J., Mann, G.W., Reddington, C.L., Pickering, S., Ogren, J.A., Andrews, E., Baltensperger, U., Weingartner, E., Boy, M., Kulmala, M., Laakso, L., Lihavainen, H., Kivekäs, N., Komppula, M., Mihalopoulos, N., Kouvarakis, G., Jennings, S.G., O'Dowd, C., Birmili, W., Wiedensohler, A., Weller, R., Gras, J., Laj, P., Sellegri, K., Bonn, B., Krejci, R., Laaksonen, A., Hamed, A., Minikin, A., Harrison, R.M., Talbot, R., Sun, J.

We synthesised observations of total particle number (CN) concentration from 36 sites around the world. We found that annual mean CN concentrations are typically 300–2000 cm−3 in the marine boundary layer and free troposphere (FT) and 1000–10 000 cm−3 in the continental boundary layer (BL). Many sites exhibit pronounced seasonality with summer time concentrations a factor of 2–10 greater than wintertime concentrations. We used these CN observations to evaluate primary and secondary sources of particle number in a global aerosol microphysics model. We found that emissions of primary particles can reasonably reproduce the spatial pattern of observed CN concentration (R2=0.46) but fail to explain the observed seasonal cycle (R2=0.1). The modeled CN concentration in the FT was biased low (normalised mean bias, NMB=−88%) unless a secondary source of particles was included, for example from binary homogeneous nucleation of sulfuric acid and water (NMB=−25%). Simulated CN concentrations in the continental BL were also biased low (NMB=−74%) unless the number emission of anthropogenic primary particles was increased or a mechanism that results in particle formation in the BL was included. We ran a number of simulations where we included an empirical BL nucleation mechanism either using the activation-type mechanism (nucleation rate, J, proportional to gas-phase sulfuric acid concentration to the power one) or kinetic-type mechanism (J proportional to sulfuric acid to the power two) with a range of nucleation coefficients. We found that the seasonal CN cycle observed at continental BL sites was better simulated by BL particle formation (R2=0.3) than by increasing the number emission from primary anthropogenic sources (R2=0.18). The nucleation constants that resulted in best overall match between model and observed CN concentrations were consistent with values derived in previous studies from detailed case studies at individual sites. In our model, kinetic and activation-type nucleation parameterizations gave similar agreement with observed monthly mean CN concentrations.