科研成果 by Year: 2013

2013
Wu Z, Birmili W, Poulain L, Poulain L, Merkel M, Fahlbusch B, van Pinxteren D, Herrmann H, Wiedensohler A. Particle hygroscopicity during atmospheric new particle formation events: implications for the chemical species contributing to particle growth. Atmospheric Chemistry and Physics. 2013;13:6637-6646.Abstract
This study examines the hygroscopicity of newly formed particles (diameters range 25-45 nm) during two atmospheric new particle formation (NPF) events in the German mid-level mountains during the Hill Cap Cloud Thuringia 2010 (HCCT-2010) field experiment. At the end of the NPF event involving clear particle growth, we measured an unusually high soluble particle fraction of 58.5% at 45 nm particle size. The particle growth rate contributed through sulfuric acid condensation only accounts for around 6.5% of the observed growth rate. Estimations showed that sulfuric acid condensation explained, however, only around 10% of that soluble particle fraction. Therefore, the formation of additional water-soluble matter appears imperative to explain the missing soluble fraction. Although direct evidence is missing, we consider water-soluble organics as candidates for this mechanism. For the case with clear growth process, the particle growth rate was determined by two alternative methods based on tracking the mode diameter of the nucleation mode. The mean particle growth rate obtained from the inter-site data comparison using Lagrangian consideration is 3.8 (+/- 2.6) nm h(-1). During the same period, the growth rate calculated based on one site data is 5.0 nm h(-1) using log-normal distribution function method. In light of the fact that considerable uncertainties could be involved in both methods, we consider both estimated growth rates consistent.
Wu ZJ, Poulain L, Henning S, Dieckmann K, Birmili W, Merkel M, van Pinxteren D, Spindler G, Muller K, Stratmann F, et al. Relating particle hygroscopicity and CCN activity to chemical composition during the HCCT-2010 field campaign. Atmospheric Chemistry and Physics. 2013;13:7983-7996.Abstract
Particle hygroscopic growth at 90% RH (relative humidity), cloud condensation nuclei (CCN) activity, and size-resolved chemical composition were concurrently measured in the Thuringer Wald mid-level mountain range in central Germany in the fall of 2010. The median hygroscopicity parameter values, kappa, of 50, 75, 100, 150, 200, and 250 nm particles derived from hygroscopicity measurements are respectively 0.14, 0.14, 0.17, 0.21, 0.24, and 0.28 during the sampling period. The closure between HTDMA (Hygroscopicity Tandem Differential Mobility Analyzers)-measured (kappa(HTDMA)) and chemical composition-derived (kappa(chem)) hygroscopicity parameters was performed based on the Zdanovskii-Stokes-Robinson (ZSR) mixing rule. Using size-averaged chemical composition, the kappa values are substantially overpredicted (30 and 40% for 150 and 100 nm particles). Introducing size-resolved chemical composition substantially improved closure. We found that the evaporation of NH4NO3, which may happen in a HTDMA system, could lead to a discrepancy in predicted and measured particle hygroscopic growth. The hygroscopic parameter of the organic fraction, kappa(org), is positively correlated with the O:C ratio (kappa(org) = 0.19 x (O:C) - 0.03). Such correlation is helpful to define the kappa(org) value in the closure study. kappa derived from CCN measurement was around 30% (varied with particle diameters) higher than that determined from particle hygroscopic growth measurements (here, hydrophilic mode is considered only). This difference might be explained by the surface tension effects, solution non-ideality, gas-particle partitioning of semivolatile compounds, and the partial solubility of constituents or non-dissolved particle matter. Therefore, extrapolating from HTDMA data to properties at the point of activation should be done with great care. Finally, closure study between CCNc (cloud condensation nucleus counter)-measured (kappa(CCN)) and chemical composition (kappa(CCN, chem)) was performed using CCNc-derived kappa values for individual components. The results show that the kappa(CCN) can be well predicted using particle size-resolved chemical composition and the ZSR mixing rule.