particle phase
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2022 ◽  
Vol 22 (1) ◽  
pp. 155-171
Author(s):  
Arto Heitto ◽  
Kari Lehtinen ◽  
Tuukka Petäjä ◽  
Felipe Lopez-Hilfiker ◽  
Joel A. Thornton ◽  
...  

Abstract. The rate at which freshly formed secondary aerosol particles grow is an important factor in determining their climate impacts. The growth rate of atmospheric nanoparticles may be affected by particle-phase oligomerization and decomposition of condensing organic molecules. We used the Model for Oligomerization and Decomposition in Nanoparticle Growth (MODNAG) to investigate the potential atmospheric significance of these effects. This was done by conducting multiple simulations with varying reaction-related parameters (volatilities of the involved compounds and reaction rates) using both artificial and ambient measured gas-phase concentrations of organic vapors to define the condensing vapors. While our study does not aim at providing information on any specific reaction, our results indicate that particle-phase reactions have significant potential to affect the nanoparticle growth. In simulations in which one-third of a volatility basis set bin was allowed to go through particle-phase reactions, the maximum increase in growth rates was 71 % and the decrease 26 % compared to the base case in which no particle-phase reactions were assumed to take place. These results highlight the importance of investigating and increasing our understanding of particle-phase reactions.


Author(s):  
Masao Gen ◽  
Zhancong Liang ◽  
Ruifeng Zhang ◽  
Beatrix Rosette Go Mabato ◽  
Chak Keung Chan

Multiphase and heterogeneous photochemistry is an emerging component of atmospheric and air pollution research. It is primarily driven by reactions of photochemically produced free radicals in the particle phase with...


2021 ◽  
Vol 37 (6) ◽  
pp. 807-820
Author(s):  
Won Jin Jang ◽  
Min Su Han

A study on the Joseon Dynasty’s furnace walls, excavated from south Korea, was conducted to identify the correlations and differences of the furnace walls found in Jeolla and Gyeongsang regions. Three ruins in the Jeolla region and two in the Gyeongsang region were selected for the analysis. The results showed a layer change depending on the degree of plasticity and difference in the number of layers and particle phase. Furthermore, although the temperature to be subjected to heat was divided into 1300°C and 1100°C, it was not a phenomenon that appeared according to the region. Additionally, analysis result of major components revealed that the TiO2 content of most samples does not exceed 1wt%, This means that the furnace did not smelt iron sand or smelted it into low-titanium sand. This study indicated a slight similarity between the furnace walls found in the two regions, and the correlation was determined based on the nature of the ruins, raw materials of the metals ores, and composition of the raw materials constituting the furnace walls.


2021 ◽  
Author(s):  
Mao Du ◽  
Aristeidis Voliotis ◽  
Yunqi Shao ◽  
Yu Wang ◽  
Thomas J. Bannan ◽  
...  

Abstract. A combination of online and offline mass spectrometric techniques was used to characterize the chemical composition of secondary organic aerosol (SOA) generated from the photooxidation of α-pinene in an atmospheric simulation chamber. The filter inlet for gases and aerosols (FIGAERO) coupled with a high-resolution time-of-flight iodide chemical ionization mass spectrometer (I–ToF-CIMS) was employed to track the evolution of gaseous and particulate components. Extracts of aerosol particles sampled onto a filter at the end of each experiment were analyzed using ultra-performance liquid chromatography ultra-high-resolution tandem mass spectrometry (LC-Orbitrap MS). Each technique was used to investigate the major SOA elemental group contributions in each system. The online CIMS particle-phase measurements show that organic species containing exclusively carbon, hydrogen and oxygen (CHO group) dominate the contribution to the ion signals from the SOA products, broadly consistent with the LC-Orbitrap MS negative mode analysis which was better able to identify the sulphur-containing fraction. An increased abundance of high carbon number (nC ≥ 16) compounds additionally containing nitrogen (CHON group) was detected in the LC-Orbitrap MS positive ionisation mode, indicating a fraction missed by the negative mode and CIMS measurements. Time series of gas-phase and particle-phase oxidation products provided by online measurements allowed investigation of the gas-phase chemistry of those products by hierarchical clustering analysis to assess the phase partitioning of individual molecular compositions. The particle-phase clustering was used to inform the selection of components for targeted structural analysis of the offline samples. Saturation concentrations derived from near-simultaneous gaseous and particulate measurements of the same ions by FIGAERO-CIMS were compared with those estimated from the molecular structure based on the LC-Orbitrap MS measurements to interpret the component partitioning behaviour. This paper explores the insight brought to the interpretation of SOA chemical composition by the combined application of online FIGAERO-CIMS and offline LC-Orbitrap MS analytical techniques.


2021 ◽  
Author(s):  
Andreas Tilgner ◽  
Bastian Stieger ◽  
Dominik van Pinxteren ◽  
Gerald Spindler ◽  
Laurent Poulain ◽  
...  

<p>Organic acids are ubiquitous compounds in the troposphere and can affect human health, the climate, air quality, and the linked ecosystems. Depending on their solubility and volatility, they can partition in both gas phase and in the particle phase. In the particle phase, organic acids partly represent about 10% of the water-soluble organic matter. However, their partitioning between different phases is not fully understood yet. Therefore, an upgraded monitor for aerosols and gases in ambient air (MARGA) was applied for one year at the Central European TROPOS research site Melpitz to study the gas- and particle-phase partitioning of formic, acetic, propionic, butyric, glycolic, pyruvic, oxalic, malonic, succinic, malic, and methanesulfonic acid (MSA). Measured gas- and PM<sub>10</sub> particle-phase mean concentrations were 12−445 and 7−31 ng m<sup>-3</sup> for monocarboxylic acids (MCAs), between 0.6−8 and 4−31 ng m<sup>-3</sup> for dicarboxylic acids (DCAs), and 2 and 31 ng m<sup>-3</sup> for MSA, respectively. Assuming full dissolution in nonideal aerosol solutions, empirical noneffective Henry’s law constants (H<sub>emp</sub>) were calculated and compared with literature values (H<sub>lit</sub>). Calculated mean H<sub>emp</sub> were 4.5 × 10<sup>9</sup>−2.2 × 10<sup>10</sup> mol L<sup>−1</sup> atm<sup>−1</sup> for MCAs, 3.6 × 10<sup>10</sup>−7.5 × 10<sup>11</sup> mol L<sup>−1</sup> atm<sup>−1</sup> for DCAs, and 7.5 × 10<sup>7</sup> mol L<sup>−1</sup> atm<sup>−1</sup> for MSA and, thus, factors of 5.1 × 10<sup>3</sup>−9.1 × 10<sup>5</sup> and 2.5−20.3 higher than their corresponding H<sub>lit</sub> for MCAs and DCAs, respectively, and 9.0 × 10<sup>−5</sup> lower than H<sub>lit,MSA</sub>. Data analyses and thermodynamic calculations implicate that the formation of chemical association complexes and organic salts inhibits the partitioning of organic acids toward the gas phase and, thus, at least partly explains higher H<sub>emp</sub> values for both MCAs and summertime DCAs. Low H<sub>emp,MSA</sub> are also unexpected because of the high MSA solubility and are reported for the first time in this study. Overall, the results of the present study implicate that processes responsible for the observed stronger partitioning of carboxylic acids toward the particle phase need to be further investigated and accounted for in complex multiphase chemistry models as they affect the contribution of organic acids to secondary organic aerosol mass, their chemical processing, and lifetime.</p> <p> </p> <p> </p>


2021 ◽  
Author(s):  
Jian Zhang ◽  
Zhe Sun ◽  
Xiujun Wang ◽  
Xiaodong Kang

Abstract Due to the reservoir heterogeneity, there is still a lot of remaining oil that cannot be displaced by water flooding. Therefore, taking the whole injection-production flow field as the research object, the dominant channel is divided into macro and micro channel. Then the corresponding oil displacement system is adopted to realize the continuous flow diversion and effective expansion of swept volume. For micro channels, the soft microgel particle dispersion can be used. It is a novel flooding system developed in recent years. Due to its excellent performance and advanced mechanism, the oil recovery rate can be greatly improved. Soft microgel particle dispersion consists of microgel particles and its carrier fluid. After coming into porous media, its unique phenomenon of particle phase separation appears, which leads to the properties of "plugging large pore and leave the small one open", and the deformation and migration characteristic in the poros media. Therefore, particle phase separation of soft microgel particle dispersion is studied by using the microfluidic technology and numerical simulation. On this basis, by adopting the NMR and 3D Printing technology, the research on its oil displacement mechanism is further carried out. Furthermore, the typical field application cases are analyzed. Results show that, soft microgel particles have good performance and transport ability in porous media. According to the core displacement experiment, this paper presents the matching coefficient between microgels and pore throat under effective plugging modes. Also, the particle phase separation happens when injecting microgels into the core, which makes the particles enter the large pore in the high permeability layer and fluid enters into small pore. Therefore, working in cooperation, this causes no damage to the low permeability layer. On this basis, theoretically guided by biofluid mechanics, the mathematical model of soft microgel particle is established to simulate its concentration distribution, which obtained the quantitative research results. Furthermore, the micro displacement experiment shows that, microgels has unique deformation and migration characteristic in the poros media, which can greatly expand swept volume. The macro displacement experiment shows that, microgels have good oil displacement performance. Finally, the soft microgel particle dispersion flooding technology has been applied in different oilfields since 2007. Results show that these field trials all obtain great oil increasing effect, with the input-output ratio range of 2.33-14.37. And two field application examples are further introduced. Through interdisciplinary innovative research methods, the oil displacement effect and field application of soft microgel particle dispersion is researched, which proves its progressiveness and superiority. The research results play an important role in promoting the application of this technology.


2021 ◽  
pp. 118914
Author(s):  
Xiaoxiao Lin ◽  
Xiaofeng Tang ◽  
Zuoying Wen ◽  
Bo Long ◽  
Christa Fittschen ◽  
...  

2021 ◽  
Vol 14 (11) ◽  
pp. 7079-7101
Author(s):  
Rachel Atlas ◽  
Johannes Mohrmann ◽  
Joseph Finlon ◽  
Jeremy Lu ◽  
Ian Hsiao ◽  
...  

Abstract. Mixed-phase Southern Ocean clouds are challenging to simulate, and their representation in climate models is an important control on climate sensitivity. In particular, the amount of supercooled water and frozen mass that they contain in the present climate is a predictor of their planetary feedback in a warming climate. The recent Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES) vastly increased the amount of in situ data available from mixed-phase Southern Ocean clouds useful for model evaluation. Bulk measurements distinguishing liquid and ice water content are not available from SOCRATES, so single-particle phase classifications from the Two-Dimensional Stereo (2D-S) probe are invaluable for quantifying mixed-phase cloud properties. Motivated by the presence of large biases in existing phase discrimination algorithms, we develop a novel technique for single-particle phase classification of binary 2D-S images using a random forest algorithm, which we refer to as the University of Washington Ice–Liquid Discriminator (UWILD). UWILD uses 14 parameters computed from binary image data, as well as particle inter-arrival time, to predict phase. We use liquid-only and ice-dominated time periods within the SOCRATES dataset as training and testing data. This novel approach to model training avoids major pitfalls associated with using manually labeled data, including reduced model generalizability and high labor costs. We find that UWILD is well calibrated and has an overall accuracy of 95 % compared to 72 % and 79 % for two existing phase classification algorithms that we compare it with. UWILD improves classifications of small ice crystals and large liquid drops in particular and has more flexibility than the other algorithms to identify both liquid-dominated and ice-dominated regions within the SOCRATES dataset. UWILD misclassifies a small percentage of large liquid drops as ice. Such misclassified particles are typically associated with model confidence below 75 % and can easily be filtered out of the dataset. UWILD phase classifications show that particles with area-equivalent diameter (Deq)  < 0.17 mm are mostly liquid at all temperatures sampled, down to −40 ∘C. Larger particles (Deq>0.17 mm) are predominantly frozen at all temperatures below 0 ∘C. Between 0 and 5 ∘C, there are roughly equal numbers of frozen and liquid mid-sized particles (0.17<Deq<0.33 mm), and larger particles (Deq>0.33 mm) are mostly frozen. We also use UWILD's phase classifications to estimate sub-1 Hz phase heterogeneity, and we show examples of meter-scale cloud phase heterogeneity in the SOCRATES dataset.


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