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Aerosol particles acting as cloud condensation nuclei (CCN) or ice-nucleating particles (INPs) play a major role in the formation and glaciation of clouds. Thereby they exert a strong impact on the radiation budget of the Earth. Data on abundance and properties of both types of particles are sparse, especially for remote areas of the world, such as the Southern Ocean (SO). In this work, we present unique results from ship-borne aerosol-particle-related in situ measurements and filter sampling in the SO region, carried out during the Antarctic Circumnavigation Expedition (ACE) in the austral summer of 2016–2017. An overview of CCN and INP concentrations over the Southern Ocean is provided and, using additional quantities, insights regarding possible CCN and INP sources and origins are presented. CCN number concentrations spanned 2 orders of magnitude, e.g. for a supersaturation of 0.3 % values ranged roughly from 3 to 590 cm−3. CCN showed variable contributions of organic and inorganic material (inter-quartile range of hygroscopicity parameter κ from 0.2 to 0.9). No distinct size dependence of κ was apparent, indicating homogeneous composition across sizes (critical dry diameter on average between 30 and 110 nm). The contribution of sea spray aerosol (SSA) to the CCN number concentration was on average small. Ambient INP number concentrations were measured in the temperature range from −5 to −27 ∘C using an immersion freezing method. Concentrations spanned up to 3 orders of magnitude, e.g. at −16 ∘C from 0.2 to 100 m−3. Elevated values (above 10 m−3 at −16 ∘C) were measured when the research vessel was in the vicinity of land (excluding Antarctica), with lower and more constant concentrations when at sea. This, along with results of backward-trajectory analyses, hints towards terrestrial and/or coastal INP sources being dominant close to ice-free (non-Antarctic) land. In pristine marine areas INPs may originate from both oceanic sources and/or long-range transport. Sampled aerosol particles (PM10) were analysed for sodium and methanesulfonic acid (MSA). Resulting mass concentrations were used as tracers for primary marine and secondary aerosol particles, respectively. Sodium, with an average mass concentration around 2.8 µg m−3, was found to dominate the sampled, identified particle mass. MSA was highly variable over the SO, with mass concentrations up to 0.5 µg m−3 near the sea ice edge. A correlation analysis yielded strong correlations between sodium mass concentration and particle number concentration in the coarse mode, unsurprisingly indicating a significant contribution of SSA to that mode. CCN number concentration was highly correlated with the number concentration of Aitken and accumulation mode particles. This, together with a lack of correlation between sodium mass and Aitken and accumulation mode number concentrations, underlines the important contribution of non-SSA, probably secondarily formed particles, to the CCN population. INP number concentrations did not significantly correlate with any other measured aerosol physico-chemical parameter.

Growth of fine aerosol particles is investigated during the Aerosol-CCN-Cloud Closure Experiment campaign in June 2013 at an urban site near Beijing. Analyses show a high frequency （- 50%） of fine aerosol particle growth events, and show that the growth rates range from 2.1 to 6.5 nm h-1 with a mean value of - 5.1 nm h-1. A review of previous studies indicates that at least four mechanisms can affect the growth of fine aerosol particles： vapor condensation, intramodal coagulation, extramodal coagulation, and multi-phase chemical reaction. At the initial stage of fine aerosol particle growth, condensational growth usually plays a major role and coagulation efficiency generally increases with particle sizes. An overview of previous studies shows higher growth rates over megacity, urban and boreal forest regions than over rural and oceanic regions. This is most likely due to the higher condensational vapor, which can cause strong condensational growth of fine aerosol particles. Associated with these multiple factors of influence, there are large uncertainties for the aerosol particle growth rates, even at the same location.

Atmospheric aerosols formed by nucleation of vapors affect radiative forcing and therefore climate. However, the underlying mechanisms of nucleation remain unclear, particularly the involvement of organic compounds. Here, we present high-resolution mass spectra of ion clusters observed during new particle formation experiments performed at the Cosmics Leaving Outdoor Droplets chamber at the European Organization for Nuclear Research. The experiments involved sulfuric acid vapor and different stabilizing species, including ammonia and dimethylamine, as well as oxidation products of pinanediol, a surrogate for organic vapors formed from monoterpenes. A striking resemblance is revealed between the mass spectra from the chamber experiments with oxidized organics and ambient data obtained during new particle formation events at the Hyytiälä boreal forest research station. We observe that large oxidized organic compounds, arising from the oxidation of monoterpenes, cluster directly with single sulfuric acid molecules and then form growing clusters of one to three sulfuric acid molecules plus one to four oxidized organics. Most of these organic compounds retain 10 carbon atoms, and some of them are remarkably highly oxidized (oxygen-to-carbon ratios up to 1.2). The average degree of oxygenation of the organic compounds decreases while the clusters are growing. Our measurements therefore connect oxidized organics directly, and in detail, with the very first steps of new particle formation and their growth between 1 and 2 nm in a controlled environment. Thus, they confirm that oxidized organics are involved in both the formation and growth of particles under ambient conditions.

Atmospheric new-particle formation (NPF) is an important source of climatically relevant atmospheric aerosol particles. NPF can be directly observed by monitoring the time-evolution of ambient aerosol particle size distributions. From the measured distribution data, it is relatively straightforward to determine whether NPF took place or not on a given day. Due to the noisiness of the real-world ambient data, currently the most reliable way to classify measurement days into NPF event/non-event days is a manual visualization method. However, manual labor, with long multi-year time series, is extremely time-consuming and human subjectivity poses challenges for comparing the results of different data sets. These complications call for an automated classification process. This article presents a Bayesian neural network (BNN) classifier to classify event/non-event days of NPF using a manually generated database at the SMEAR II station in Hyytiälä, Finland. For the classification, a set of informative features are extracted exploiting the properties of multi-modal log normal distribution fitted to the aerosol particle concentration database and the properties of the time series representation of the data at different scales. The proposed method has a classification accuracy of 84.2 % for determining event/non-event days. In particular, the BNN method successfully predicts all event days when the growth and formation rate can be determined with a good confidence level (often labeled as class Ia days). Most misclassified days (with an accuracy of 75 %) are the event days of class II, where the determination of growth and formation rate are much more uncertain. Nevertheless, the results reported in this article using the new machine learning-based approach points towards the potential of these methods and suggest further exploration in this direction.

As one of the largest inland megacities in Northwest (NW) China, Xi’an has been facing serious regional haze frequently, especially during winter. The composition of aerosols in Xi’an is highly complex due to its unique basinal topography and unique meteorological conditions. In this study, we characterized the morphology, size, and composition of individual aerosol particles collected during regional haze events at an urban site in Xi’an using Transmission Electron Microscopy (TEM) coupled with Energy-Dispersive X-ray Spectrometry (EDX). Six types of particles were identified based on their morphology and chemical composition, including organic (41.88%), sulfate (32.36%), soot (8.33%), mineral (7.91%), K-rich (5.13%), and fly ash particles (4.49%). These results demonstrate that the organic particles made a larger contribution to haze formation than the secondary inorganic particles during the sampling period. Size distribution and dominance suggest that organic and sulfate particles exert major control on the variation trends of particle size in haze. The coating thickness of organic-cored particles was about 369 nm and that of sulfate-cored particles was about 322 nm, implying that the organic particles were more aged than the sulfate particles. The results presented in this study provide further insights into understanding haze particle formation.

Particle size distribution is one of the important microphysical parameters to characterize the aerosol properties. The aerosol optical depth is used as the function of wavelength to study the particle size distribution of whole atmospheric column. However, the inversion equation of the particle size distribution from the aerosol optical depth belongs to the Fredholm integral equation of the first kind, which is usually ill-conditioned. To overcome this drawback, the integral equation is first discretized directly by using the complex trapezoid formula. Then, the corresponding parameters are selected by the L curve method. Finally the truncated singular value decomposition regularization method is employed to regularize the discrete equation and retrieve the particle size distribution. To verify the feasibility of the algorithm, the aerosol optical depths taken by a sun photometer CE318 over Yinchuan area in four seasons, as well as hazy, sunny, floating dusty and blowing dusty days, were used to retrieve the particle size distribution. In order to verify the effect of truncated singular value decomposition algorithm, the Tikhonov regularization algorithm was also adopted to retrieve the aerosol PSD. By comparing the errors of the two regularizations, the truncated singular value decomposition regularization algorithm has a better retrieval effect. Moreover, to understand intuitively the sources of aerosol particles, the backward trajectory was used to track the source. The experiment results show that the truncated singular value decomposition regularization method is an effective method to retrieve the particle size distribution from aerosol optical depth.

Ambient bioaerosols affect ecosystems and public health, but their seasonal variations and their contributions to aerosol particles are limitedly understood. Ambient bioaerosols in PM2.5 and PM10 samples were measured in Huangshi City, Hubei Province of China from April 2018 to December 2018. Bioaerosols were measured using a fluorescence microscope after staining with 4′, 6-diamino-2-phenylindole dihydrochloride (DAPI) following a direct staining technique. The bioaerosol number concentrations ranged from 0.12 to 15.69 # cm−3 for PM2.5 and 0.22 to 18.20 # cm−3 for PM10, with averages of 2.79 # cm−3 and 4.66 # cm−3, respectively. The bioaerosol concentrations of PM2.5 and PM10 varied significantly by seasons and were arranged in the following descending order: spring > fall > winter > summer. Bioaerosol numbers were dominated by fine particles of 0.37–2.5 μm diameter, while the spring bioaerosol particles were detected at the peak concentration of 0.56–1 μm diameter. Bioaerosol fractions accounted for 18.3 ± 10.6% PM10 mass and 13.7 ± 12.5% PM2.5 mass. Bioaerosol concentrations were increased during the haze event, but the increased amounts were not as large as those of the dust event, and higher bioaerosol contributions to PM were observed in the dust event than in the haze event. As enhanced emission controls have reduced PM concentrations in China, bioaerosols can be important contributors to PM mass.

The polyols arabitol and mannitol, recently proposed as source tracers for fungal spores, were used in this study to estimate fungal contributions to atmospheric aerosol. Airborne particulate matter (PM2.5 and PM10) was collected at Jianfengling Mountain, a tropical rainforest on Hainan Island situated off the south China coast, during spring and analyzed for arabitol and mannitol by high-performance anion exchange chromatography with pulsed amperometric detection (HPAEC-PAD). The average concentrations of arabitol and mannitol exhibited high values with averages of 7.0 and 16.0 ngm − 3 respectively in PM2.5 and 44.0 and 71.0ngm − 3 in PM10. The two tracers correlated well with each other, especially in the coarse mode aerosol (PM2.5 − 10), indicating they were mainly associated with coarse aerosol particles and had common sources. Arabitol and mannitol in PM10 showed significant positive correlations with relative humidity, as well as positive correlations with average temperature, suggesting a wet emissions mechanism of biogenic aerosol in the form of fungal spores. We made estimations of the contribution of fungal spores to ambient PM mass and to organic carbon, based on the observed ambient concentrations of these two tracers. The relative contributions of fungal spores to the PM10 mass were estimated to range from 1.6 to 18.2%, with a rather high mean value of 7.9%, and the contribution of fungal spores to organic carbon in PM10 ranged from 4.64 to 26.1%, with a mean value of 12.1%, implying that biological processes are important sources of atmospheric aerosol.

The NaCl-containing aerosol particles (NaCl-containing APs) are trapped in the coastal atmosphere, in which sodium chloride and other salt compounds, such as calcium sulfate and ammonium nitrate, form a core–shell composite structure. The excessive anthropogenic emissions of pollutants, such as SO 2 , NO x , NH 3 , and construction dust, as well as salt spray, provide the material supply, and the low wind speed, humid, and hot weather environment creates incubators for these indigenous NaCl-containing APs. They are easy to form in coastal haze-fog episodes, even accounting for about 45% of all haze APs. A homemade aerosol particle simulative generator (APSG, patent authorization ZL 2018 1 0,516,861.3) was designed to explore the formation mechanism of NaCl-containing APs, which provides an effective research platform for simulating the evolution of particle structure in natural environment. The simulated experiments carried out on the APSG have successfully bred the artificial NaCl-containing APs and the carbonate/sulfate core–shell structure with different carbonate transformation degrees. The evolution of carbonate/sulfate core–shell structure provides solid evidence for the oxidation of S(IV) by dissolved NO x to sulfate (SO 4 2− ). Then, the strong acid in the salt drop reacts with carbonate through metathesis reaction to form sulfate and nitrate. With the volatilization of the salt drop, sulfate and nitrate crystallize and precipitate successively to form a composite structure containing NaCl. By studying the structural evolution from semi-mature particles to mature particles, a guiding exploration method is provided for the formation mechanism of aerosol particles. Reducing anthropogenic emissions to cut off the material supply of haze granulation is a crucial and effective step to prevent haze-fog episodes and promote the blue sky project.

Radiocarbon analysis is a widely-used tool for source apportionment of aerosol particles. One of the big challenges of this method, addressed in this work, is to isolate elemental carbon (EC) for 14C analysis. In the first part of the study, we validate a two-step method (2stepCIO) to separate total carbon (TC) into organic carbon (OC) and EC against the EUSAAR_2 thermal-optical method regarding the recovered carbon concentrations. The 2stepCIO method is based on the combustion of OC in pure oxygen at two different temperature steps to isolate EC. It is normally used with a custom-built aerosol combustion system (ACS), but in this project, it was also implemented as a thermal protocol on a Sunset OC-EC analyzer. Results for the recovered EC mass concentration showed poor agreement between the 2stepCIO method on the ACS system and on the Sunset analyzer. This indicates that the EC recovery is sensitive not only to the temperature steps, but also to instrument-specific parameters, such as heating rates. We also found that the EUSAAR_2 protocol itself can underestimate the EC concentration on untreated samples compared to water-extracted samples. This is especially so for highly loaded filters, which are typical for 14C analysis. For untreated samples, the EC concentration on long-term filter samples (two to five days sampling time) was 20–45% lower than the sum of EC found on the corresponding 24-h filter samples. For water-extracted filter samples, there was no significant difference between long-term and the sum of daily filter samples. In the second part of this study, the 14C was measured on EC isolated by the 2stepCIO method and compared to methods from two other laboratories. The different methods agree well within their uncertainty estimates.