2011, Rose, D., Gunthe, S.S., Su, H., Garland, R.M., Yang, H., Berghof, M., Cheng, Y.F., Wehner, B., Achtert, P., Nowak, A., Wiedensohler, A., Takegawa, N., Kondo, Y., Hu, M., Zhang, Y., Andreae, M.O., Pöschl, U.

Size-resolved chemical composition, mixing state, and cloud condensation nucleus (CCN) activity of aerosol particles in polluted mega-city air and biomass burning smoke were measured during the PRIDE-PRD2006 campaign near Guangzhou, China, using an aerosol mass spectrometer (AMS), a volatility tandem differential mobility analyzer (VTDMA), and a continuous-flow CCN counter (DMT-CCNC). The size-dependence and temporal variations of the effective average hygroscopicity parameter for CCN-active particles (κa) could be parameterized as a function of organic and inorganic mass fractions (forg, finorg) determined by the AMS: κa,p=κorg·forg + κinorg·finorg. The characteristic κ values of organic and inorganic components were similar to those observed in other continental regions of the world: κorg≈0.1 and κinorg≈0.6. The campaign average κa values increased with particle size from ~0.25 at ~50 nm to ~0.4 at ~200 nm, while forg decreased with particle size. At ~50 nm, forg was on average 60% and increased to almost 100% during a biomass burning event. The VTDMA results and complementary aerosol optical data suggest that the large fractions of CCN-inactive particles observed at low supersaturations (up to 60% at S≤0.27%) were externally mixed weakly CCN-active soot particles with low volatility (diameter reduction <5% at 300 °C) and effective hygroscopicity parameters around κLV≈0.01. A proxy for the effective average hygroscopicity of the total ensemble of CCN-active particles including weakly CCN-active particles (κt) could be parameterized as a function of κa,p and the number fraction of low volatility particles determined by VTDMA (φLV): κt,p=κa,p−φLV·(κa,p−κLV). Based on κ values derived from AMS and VTDMA data, the observed CCN number concentrations (NCCN,S≈102–104 cm−3 at S = 0.068–0.47%) could be efficiently predicted from the measured particle number size distribution. The mean relative deviations between observed and predicted CCN concentrations were ~10% when using κt,p, and they increased to ~20% when using only κa,p. The mean relative deviations were not higher (~20%) when using an approximate continental average value of κ≈0.3, although the constant κ value cannot account for the observed temporal variations in particle composition and mixing state (diurnal cycles and biomass burning events). Overall, the results confirm that on a global and climate modeling scale an average value of κ≈0.3 can be used for approximate predictions of CCN number concentrations in continental boundary layer air when aerosol size distribution data are available without information about chemical composition. Bulk or size-resolved data on aerosol chemical composition enable improved CCN predictions resolving regional and temporal variations, but the composition data need to be highly accurate and complemented by information about particle mixing state to achieve high precision (relative deviations <20%).

2022, Man, Ruiqi, Wu, Zhijun, Zong, Taomou, Voliotis, Aristeidis, Qiu, Yanting, Größ, Johannes, van Pinxteren, Dominik, Zeng, Limin, Herrmann, Hartmut, Wiedensohler, Alfred, Hu, Min

Particle hygroscopicity plays a key role in determining the particle deposition in the human respiratory tract (HRT). In this study, the effects of hygroscopicity and mixing state on regional and total deposition doses on the basis of the particle number concentration for children, adults, and the elderly were quantified using the Multiple-Path Particle Dosimetry model, based on the size-resolved particle hygroscopicity measurements at HRT-like conditions (relative humidity = 98 %) performed in the North China Plain. The measured particle population with an external mixing state was dominated by hygroscopic particles (number fraction = (91.5 ± 5.7) %, mean ± standard deviation (SD); the same below). Particle hygroscopic growth in the HRT led to a reduction by around 24 % in the total doses of submicron particles for all age groups. Such a reduction was mainly caused by the growth of hygroscopic particles and was more pronounced in the pulmonary and tracheobronchial regions. Regardless of hygroscopicity, the elderly group of people had the highest total dose among three age groups, while children received the maximum total deposition rate. With 270 nm in diameter as the boundary, the total deposition doses of particles smaller than this diameter were overestimated, and those of larger particles were underestimated, assuming no particle hygroscopic growth in the HRT. From the perspective of the daily variation, the deposition rates of hygroscopic particles with an average of (2.88 ± 0.81) × 109 particles h-1 during the daytime were larger than those at night ((2.32 ± 0.24) × 109 particles h-1). On the contrary, hydrophobic particles interpreted as freshly emitted soot and primary organic aerosols exhibited higher deposition rates at nighttime ((3.39 ± 1.34) × 108 particles h-1) than those in the day ((2.58 ± 0.76) × 108 particles h-1). The traffic emissions during the rush hours enhanced the deposition rate of hydrophobic particles. This work provides a more explicit assessment of the impact of hygroscopicity and mixing state on the deposition pattern of submicron particles in the HRT. Copyright:

2018, Schmale, Julia, Henning, Silvia, Decesari, Stefano, Henzing, Bas, Keskinen, Helmi, Sellegri, Karine, Ovadnevaite, Jurgita, Pöhlker, Mira L., Brito, Joel, Bougiatioti, Aikaterini, Kristensson, Adam, Kalivitis, Nikos, Stavroulas, Iasonas, Carbone, Samara, Jefferson, Anne, Park, Minsu, Schlag, Patrick, Iwamoto, Yoko, Aalto, Pasi, Äijälä, Mikko, Bukowiecki, Nicolas, Ehn, Mikael, Frank, Göran, Fröhlich, Roman, Frumau, Arnoud, Herrmann, Erik, Herrmann, Hartmut, Holzinger, Rupert, Kos, Gerard, Kulmala, Markku, Mihalopoulos, Nikolaos, Nenes, Athanasios, O'Dowd, Colin, Petäjä, Tuukka, Picard, David, Pöhlker, Christopher, Pöschl, Ulrich, Poulain, Laurent, Prévôt, André Stephan Henry, Swietlicki, Erik, Andreae, Meinrat O., Artaxo, Paulo, Wiedensohler, Alfred, Ogren, John, Matsuki, Atsushi, Yum, Seong Soo, Stratmann, Frank, Baltensperger, Urs, Gysel, Martin

Aerosol-cloud interactions (ACI) constitute the single largest uncertainty in anthropogenic radiative forcing. To reduce the uncertainties and gain more confidence in the simulation of ACI, models need to be evaluated against observations, in particular against measurements of cloud condensation nuclei (CCN). Here we present a data set - ready to be used for model validation - of long-term observations of CCN number concentrations, particle number size distributions and chemical composition from 12 sites on 3 continents. Studied environments include coastal background, rural background, alpine sites, remote forests and an urban surrounding. Expectedly, CCN characteristics are highly variable across site categories. However, they also vary within them, most strongly in the coastal background group, where CCN number concentrations can vary by up to a factor of 30 within one season. In terms of particle activation behaviour, most continental stations exhibit very similar activation ratios (relative to particles 20nm) across the range of 0.1 to 1.0% supersaturation. At the coastal sites the transition from particles being CCN inactive to becoming CCN active occurs over a wider range of the supersaturation spectrum. Several stations show strong seasonal cycles of CCN number concentrations and particle number size distributions, e.g. at Barrow (Arctic haze in spring), at the alpine stations (stronger influence of polluted boundary layer air masses in summer), the rain forest (wet and dry season) or Finokalia (wildfire influence in autumn). The rural background and urban sites exhibit relatively little variability throughout the year, while short-term variability can be high especially at the urban site. The average hygroscopicity parameter, calculated from the chemical composition of submicron particles was highest at the coastal site of Mace Head (0.6) and lowest at the rain forest station ATTO (0.2-0.3). We performed closure studies based on -Köhler theory to predict CCN number concentrations. The ratio of predicted to measured CCN concentrations is between 0.87 and 1.4 for five different types of . The temporal variability is also well captured, with Pearson correlation coefficients exceeding 0.87. Information on CCN number concentrations at many locations is important to better characterise ACI and their radiative forcing. But long-term comprehensive aerosol particle characterisations are labour intensive and costly. Hence, we recommend operating migrating-CCNCs to conduct collocated CCN number concentration and particle number size distribution measurements at individual locations throughout one year at least to derive a seasonally resolved hygroscopicity parameter. This way, CCN number concentrations can only be calculated based on continued particle number size distribution information and greater spatial coverage of long-term measurements can be achieved.

2016, Wu, Z.J., Zheng, J., Shang, D.J., Du, Z.F., Wu, Y.S., Zeng, L.M., Wiedensohler, A., Hu, M.

Simultaneous measurements of particle number size distribution, particle hygroscopic properties, and size-resolved chemical composition were made during the summer of 2014 in Beijing, China. During the measurement period, the mean hygroscopicity parameters (κs) of 50, 100, 150, 200, and 250 nm particles were respectively 0.16  ±  0.07, 0.19  ±  0.06, 0.22  ±  0.06, 0.26  ±  0.07, and 0.28  ±  0.10, showing an increasing trend with increasing particle size. Such size dependency of particle hygroscopicity was similar to that of the inorganic mass fraction in PM1. The hydrophilic mode (hygroscopic growth factor, HGF  >  1.2) was more prominent in growth factor probability density distributions and its dominance of hydrophilic mode became more pronounced with increasing particle size. When PM2.5 mass concentration was greater than 50 μg m−3, the fractions of the hydrophilic mode for 150, 250, and 350 nm particles increased towards 1 as PM2.5 mass concentration increased. This indicates that aged particles dominated during severe pollution periods in the atmosphere of Beijing. Particle hygroscopic growth can be well predicted using high-time-resolution size-resolved chemical composition derived from aerosol mass spectrometer (AMS) measurements using the Zdanovskii–Stokes–Robinson (ZSR) mixing rule. The organic hygroscopicity parameter (κorg) showed a positive correlation with the oxygen to carbon ratio. During the new particle formation event associated with strongly active photochemistry, the hygroscopic growth factor or κ of newly formed particles is greater than for particles with the same sizes not during new particle formation (NPF) periods. A quick transformation from external mixture to internal mixture for pre-existing particles (for example, 250 nm particles) was observed. Such transformations may modify the state of the mixture of pre-existing particles and thus modify properties such as the light absorption coefficient and cloud condensation nuclei activation.

2017, Kuang, Ye, Zhao, Chunsheng, Tao, Jiangchuan, Bian, Yuxuan, Ma, Nan, Zhao, Gang

Aerosol hygroscopicity is crucial for understanding roles of aerosol particles in atmospheric chemistry and aerosol climate effects. Light-scattering enhancement factor f (RH, λ) is one of the parameters describing aerosol hygroscopicity, which is defined as f (RH, λ) = δsp(RH, λ)=δsp(dry, λ), where δsp(RH, λ) or δsp(dry, λ) represents δsp at wavelength λ under certain relative humidity (RH) or dry conditions. Traditionally, an overall hygroscopicity parameter κ can be retrieved from measured f (RH, λ), hereinafter referred to as κf(RH), by combining concurrently measured particle number size distribution (PNSD) and mass concentration of black carbon. In this paper, a new method is proposed to directly derive κf(RH) based only on measurements from a three-wavelength humidified nephelometer system. The advantage of this newly proposed approach is that κf(RH) can be estimated without any additional information about PNSD and black carbon. This method is verified with measurements from two different field campaigns. Values of κf(RH) estimated from this new method agree very well with those retrieved by using the traditional method: all points lie near the 1 : 1 line and the square of correlation coefficient between them is 0.99. The verification results demonstrate that this newly proposed method of deriving κf(RH) is applicable at different sites and in seasons of the North China Plain and might also be applicable in other regions around the world.