Size Distribution Characteristics Research Articles

A hybrid GBPSO algorithm for permeability estimation using particle size distribution and porosity

Particle size distribution measurements can be used for permeability estimation, and it is widely accepted that there exhibits a certain degree of correlation between permeability and porosity. In this paper, an efficient, low-cost, and reliable approach is used to develop an empirical correlation for estimating permeability based on particle size distribution characteristics and porosity in two modes: mode #1 includes 5% (D5), 10% (D10) and 60% (D60) of the cumulative passing particle size distribution curve and porosity for situations where porosity is known, and mode #2 where porosity is unknown. To optimize the coefficient of the proposed relationships, genetic-binary particle swarm optimization algorithm is used. A database consisting of 50 samples collected from four wells drilled in two neighboring pads in Western Canada were used, and their permeability values were predicted successfully. A validation based on a reference study and an application of sand completion design based on the finding of this study are also discussed. The novelties of the proposed approach are examining the effect of fines content, investigating the full range of particle size distribution curve, and using a hybrid intelligent method to optimize the coefficients of the correlations. In addition to sand completion deigns purposes, the proposed method can be used in enhanced oil recovery studies, reservoir management, and reservoir simulation applications.

The Influence of Coal Meso-Structure on Adsorption Characteristics of Coking and Lean Coal

The non-uniform adsorption characteristics of coal strictly restrict the development and utilization of CBM, and the structure of coal is the fundamental reason for its non-uniform adsorption of methane. To investigate the fundamental causes of methane adsorption capacity differences in coal with various meso-structures, small coking coal and lean coal samples were subjected to isothermal adsorption, computed tomography (CT) scanning, scanning electron microscopy (SEM), and mercury intrusion porosimetry (MIP) to obtain the correlation between the meso-structure of coal and its non-uniform adsorption characteristics. The reasons for the differences in methane adsorption capacity between the specimens were summarized from the perspectives of material and structural heterogeneities, meso-morphology and pore size distribution. The following conclusions could be drawn: (1) The coal samples with different heterogeneity degrees exhibit varying methane adsorption capacities. (2) Compared to the specific surface area, the mineral composition exerts a greater influence on the adsorption capacity of the coal samples. (3) The gas adsorption capacities of the coal samples with similar meso-morphology and pore size distribution characteristics are similar, while among the coal samples with similar pore size distributions but different meso-morphologies, the gas adsorption capacities significantly differ.

Influence of particle size on diffuse particulate pollutants in combined sewer systems

Since combined sewer systems are still considered as a threat to urban water environment, understand their pollution transport process and load distribution characteristics during rainfall-runoff events would assist to mitigate urban stormwater pollution. In this study, built-up and wash-off processes of particulate pollutants on road surface and in sewer were synchronously observed during eight natural rainfall events in the combined sewer system in Zhuhai, Southern China. Field observation results showed the significant influence of particles size distribution characteristics on TSS concentration. High TSS concentrations (Road runoff, >200 mg/L; combined sewer runoff, >150 mg/L) usually contained relatively coarse particles (>100 μm) during the eight rainfall events, but the counter argument. Combined sewer runoff had a particle size coarser than road runoff. The relationship between the event means concentration (EMC) of TSS from road and combined sewer runoff varied with rainfall. EMC of TSS in road runoff were higher than that in sewer runoff during small rainfall, while that in combined sewer runoff were higher during large rainfall. The results also showed that 65.2 % of total nitrogen (TN) loadings and 62.3 % of total phosphorous (TP) loadings in the catchment came from combined sewer sediments, while 58.6 % of chemical oxygen demand (COD) loadings came from road runoff, which were mainly determined by the content of each pollutant in the sewer sediments and road-deposited sediments (RDS). Additionally, high pollutant loads phases (drainage of pollutant loads faster than runoff at a given incremental time during an event) of road runoff occurred earlier than that of combined sewer runoff. These findings can provide a basis for the type selection and scale determination of stormwater control measures in combined sewer systems.

Direct use of large-footprint lidar waveforms to estimate aboveground biomass

Many studies have established the strong connections between aboveground biomass and lidar height metrics; however, these relationships are site-specific. Field data required to derive these relationships are not readily available in many cases. We developed a model to estimate plot-level aboveground biomass density (AGBD) directly from large-footprint lidar waveform measurements. An individual tree-based aboveground biomass (AGB)-height allometric relationship was scaled up to the plot level using lidar-waveform sensed tree height and crown size distribution characteristics. The AGBD was estimated based on a waveform/foliage profile-weighted height-based allometric equation. The AGBD-height scaling exponent was then built on the allometric relationships of tree height with stem diameter and crown volume with tree height. Global vegetation structure data analysis demonstrated that one general model (scaling exponent ~ 1.6–1.8) works reasonably well across all global forest biomes except boreal forests (scaling exponent ~ 0.9). We applied the model to estimate aboveground biomass in two distinct geographic regions: temperate deciduous/conifer forests in the northeastern USA and a montane conifer forest in Sierra National Forest in California. Local vegetation structural data analysis leads to a consistent height scaling exponent for these two distinct biomes, slightly different from the global data analysis results. This model produced optimal AGBD estimates using the local height scaling exponent value. Adequate AGBD estimates with the general height scaling exponent value were also provided by our model. Our analysis suggests one general allometric relationship between plot-level AGBD and large-footprint lidar waveforms. Integrating local structure allometric relationships improve the predictive accuracy of the model. Our model outperformed the lidar height metrics-based approach for AGBD estimates and overcame the biomass underestimation problem using height metrics for high biomass regions. This model could potentially serve as a general and robust model for monitoring forest carbon stocks using large-footprint lidar waveform measurements such as the Global Ecosystem Dynamics Investigation (GEDI) mission at the continental and global scales. The model could be a framework for integrating a demography-based terrestrial ecosystem model and GEDI global mission measurements to improve global carbon stock and flux estimates.

Characteristics of orographic raindrop size distribution in the Tianshan Mountains, China

Characteristics of orographic raindrop size distribution (DSD) in the Tianshan Mountains, China are studied based on second-generation OTT Particle Size Velocity disdrometer installed at the top (Tianchi, 43.88°N, 88.12°E, 1941.8 m above sea level) and the foot stations (Urumqi, 43.79°N, 87.65°E, 935 m above sea level) from June to August 2020 and 2021. For the overall rainfall, the concentration of drops of all sizes in Tianchi is greater than that in Urumqi. Furthermore, in both regions, small drops (diameter < 1 mm) primarily contributed to the total number concentration, and both small drops and mid-size drops (1 ≤ diameter ≤ 3 mm) had important contributions to the rainfall rate. For the DSD of different rain rate classes, the concentration of mid-size drops is higher in the first two rain rate classes in Urumqi than that in Tianchi, while the opposite is true when the rain rate exceeds 5 mm h−1. Meanwhile, the concentration of small drops is higher in the first two rain rate classes in Tianchi than that in Urumqi, while the opposite is true for small drops in partial diameter, as the rain rate class increases. In addition, two kinds of rainfall kinetic energy (rainfall kinetic energy flux: KEtime and the rainfall kinetic energy content: KEmm) and various rainfall kinetic energy-rainfall intensity relations (KEtime/KEmm –R relations) were derived based on DSD data. Further, the possible thermo-dynamical and microphysical processes that cause the dissimilarities in DSD between Urumqi and Tianchi are also discussed in this work. Affected by the difference in altitude between the top and the foot stations, the foot station had relatively hotter and drier conditions in the near-surface layer than the top station during the rainfall period, so the evaporation rate of small drops was higher at the foot station than that at the top station, resulting in fewer small drops at the foot station. Meanwhile, lower black body temperature, and stronger seeder-feeder mechanism at the top station during the rainfall period may be partly responsible for more mid-size drops and large size drops (diameter > 3 mm) at the top station

Microphysical Analysis of Precipitation in the Central and Eastern Margins of the Tibetan Plateau

Through the observation and study of the raindrop spectrum, we can not only explore the evolution law of precipitation but also understand the microphysical characteristics of different types of precipitation clouds. This paper uses the raindrop spectrum data observed at Naqu Station, Yushu Station, Linzhi Station, and Emei Mount Station, as well as cloud radar data in the Yushu region in the Tibetan Plateau. Raindrop spectral characteristics are studied, and the raindrop size distribution (DSD) characteristics of the four stations are analyzed. The results are as follows: (1) The overall raindrop spectral concentration of the four stations decreases with the increase in particle size after the peak value. The downtrend is most gentle at the peak. (2) All rain intensity levels show the characteristics of multiple vertices. At Linzhi Station, Naqu Station and Yushu Station, the particles with a diameter of &lt;1 mm contributed the most to the precipitation rate, while the particles with a diameter of &lt;1 mm at Emei Mount Station contributed the least to the precipitation rate. (3) The precipitation in the central and eastern margins of the Tibetan Plateau is dominated by small and medium-sized particles, accounting for 95–99% of the precipitation particle number concentration. (4) The raindrop spectra of the three types of precipitation clouds at the four sites are all cumulonimbus precipitation Cumulonimbus in the uppermost layer, stratiform cloud precipitation stratiform cloud in the lowermost layer, and mixed cloud precipitation stratiform cloud in between. (5) Cloud radar analysis of precipitation structure shows that cumulonimbus and mixed clouds develop vigorously, and the highest cloud height can reach 13 km, but the average precipitation duration of mixed clouds is shorter than that of cumulonimbus; stratiform clouds develop relatively smoothly, with cloud heights of 6–7 km, the average precipitation duration is the shortest.

Wetting-drying cycle effect on the compressibility of lime-treated soil accounting for wetting fluid nature and aggregate size

The durability, which refers to the ability of earthen structures to ensure their functionality over time while maintaining their required mechanical performance, is a key issue in evaluating the effectiveness of lime treatment. In this study, the effect of wetting-drying cycles on the compressibility and the microstructure was investigated with lime-treated/untreated samples considering the wetting fluid and the maximum aggregate size (S0.4, Dmax = 0.4 mm; S5, Dmax = 5 mm) effects. Results showed that the wetting-drying cycles caused an increase of void ratio and changed the bi-modal porosity to tri-modal characteristics for the untreated samples, while it led to a reversible variation of void ratio and an unchanged bi-modal pore size distribution characteristics for lime-treated samples, indicating the soil improvement by lime treatment. Thereby, the wetting-drying cycles made the compression curve of untreated samples change from convex to linear shape, while their effect was visible but not significant for the lime-treated soil. Higher decrease of macro-pore void ratio with loading was obtained on the lime-treated samples under wetting-drying cycles compared to the as-compacted samples, indicating a slight softening of soil structure by the wetting-drying cycles. Regarding the effect of wetting fluid nature, synthetic seawater resulted in a higher compressibility than deionised water. This was attributed to the presence of higher quantity of macro-pores in the samples wetted by synthetic seawater induced by the shrinkage of clay fraction. The aggregate size had slight effect on the compressibility of as-compacted samples due to their similar production of cementitious compounds and matric suction. Nevertheless, after wetting-drying cycles, the lime-treated samples S5 had lower decrease of macro-pore void ratio than the lime-treated samples S0.4, due to the significant reduction of macro-pore population with wetting-drying cycles.

Automated Identification of Characteristic Droplet Size Distributions in Stratocumulus Clouds Utilizing a Data Clustering Algorithm

Abstract Droplet-level interactions in clouds are often parameterized by a modified gamma fitted to a “global” droplet size distribution. Do “local” droplet size distributions of relevance to microphysical processes look like these average distributions? This paper describes an algorithm to search and classify characteristic size distributions within a cloud. The approach combines hypothesis testing, specifically, the Kolmogorov–Smirnov (KS) test, and a widely used class of machine learning algorithms for identifying clusters of samples with similar properties: density-based spatial clustering of applications with noise (DBSCAN) is used as the specific example for illustration. The two-sample KS test does not presume any specific distribution, is parameter free, and avoids biases from binning. Importantly, the number of clusters is not an input parameter of the DBSCAN-type algorithms but is independently determined in an unsupervised fashion. As implemented, it works on an abstract space from the KS test results, and hence spatial correlation is not required for a cluster. The method is explored using data obtained from the Holographic Detector for Clouds (HOLODEC) deployed during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign. The algorithm identifies evidence of the existence of clusters of nearly identical local size distributions. It is found that cloud segments have as few as one and as many as seven characteristic size distributions. To validate the algorithm’s robustness, it is tested on a synthetic dataset and successfully identifies the predefined distributions at plausible noise levels. The algorithm is general and is expected to be useful in other applications, such as remote sensing of cloud and rain properties. Significance Statement A typical cloud can have billions of drops spread over tens or hundreds of kilometers in space. Keeping track of the sizes, positions, and interactions of all of these droplets is impractical, and, as such, information about the relative abundance of large and small drops is typically quantified with a “size distribution.” Droplets in a cloud interact locally, however, so this work is motivated by the question of whether the cloud droplet size distribution is different in different parts of a cloud. A new method, based on hypothesis testing and machine learning, determines how many different size distributions are contained in a given cloud. This is important because the size distribution describes processes such as cloud droplet growth and light transmission through clouds.

Seasonal Variation in Microphysical Characteristics of Precipitation at the Entrance of Water Vapor Channel in Yarlung Zangbo Grand Canyon

Mêdog is located at the entrance of the water vapor channel in the Yarlung Zangbo Grand Canyon (YGC). This area has the largest annual accumulated rainfall totals and precipitation frequency on the Tibetan Plateau (TP). This paper investigates the seasonal variation in raindrop size distribution (DSD) characteristics in Mêdog based on disdrometer observations from 1 July 2019 to 30 June 2020. The DSD characteristics are examined under six rain rate classes and two rainfall types (stratiform and convective) in the winter, premonsoon, monsoon and postmonsoon periods. The highest (lowest) concentration of small raindrops is observed in monsoon (winter) precipitation, whereas large raindrops predominate in premonsoon precipitation. For stratiform rainfall, the mean mass-weighted mean diameter (Dm) exhibits overlooked differences in the four periods, while the mean normalized intercept parameter (Nw) is significantly higher in the monsoon period than in the other three periods. The convective rainfall in the monsoon and postmonsoon periods is characterized by a high concentration of limited-size drops and can be classified as maritime-like. This is probably attributed to abundant warm and humid airflow transported by the Indian Ocean monsoon into Mêdog. The westerly winds prevail over the TP during the premonsoon period, and thereby the premonsoon convective rainfall in Mêdog has a larger mean Dm and a lower mean Nw. In addition, the relationships of radar reflectivity Z and rain rate R for different precipitation types in different periods are also derived. A better understanding of the seasonal variation in the microphysical characteristics of precipitation in Mêdog is important for improving the microphysical parameterization scheme and the precipitation forecast of models on the TP.

Effects of coalification on nano-micron scale pore development: From bituminous to semi-anthracite

Surface atom functionalization and the variation of aliphatic/aromatic structures within coal macromolecules are key factors to determine the pore structures within coalification. The characteristics of nano-micron scale pore structures were analyzed with the aid of coupled fluid intrusion and molecular probe technologies. Results indicate that the cleavage of long-chain aliphatic structures enhances the size of the pore throat and reduces the specific surface area and pore volume of the mesopores (2–50 nm). Macropores (>50 nm) were slightly impacted by coalification and their development was primarily controlled by diagenesis. Micropores (<2 nm) overall increase with the enhancement of aromatization and condensation polymerization; however, in the stage of low volatile bituminous, the blocking of minerals or low boiling hydrocarbon solids will temporarily reduce micropores. Meanwhile, similar surface structures and functional groups lead to similar characteristics of the pore size distribution for mesopores and micropores. Furthermore, the peak value of microporous pore volume migrates to the smaller pore size, and pores <0.4 nm in size generated from clearances among the aromatic layers gradually become dominant with coalification. The macropores fractal dimension (Df1) is not only related to coalification. However, the heterogeneity and surface roughness of micropores (Dm) and mesopores (Dv2) are controlled by coalification. Dv1 of mesopores is affected by diagenesis. The pore walls are contributed by aliphatic structures before the third coalification jump. Meanwhile, micropores among aliphatic structures developed relatively independently and small-scale pore networks frequently exist within them. Accompanied by the cleavage of aliphatic structures, the aliphatic structures around the pore walls will be gradually replaced by the aromatic structure. Micropores of relative independence are decreased, and large-scale pore networks are gradually formed. The pore morphology developed to be more complex and strongly heterogeneous. In addition, high-density oxygen/nitrogen/sulfur functionalization will increase the micropores.

Microphysical Characteristics of Raindrop Size Distribution and Implications for Radar Rainfall Estimation Over the Northeastern Tibetan Plateau

AbstractRaindrop size distribution (DSD) observations with OTT PARSIVEL2 disdrometers at Dari and Delingha in the northeast of the Tibetan Plateau (TP) during summer 2019 and 2020 were utilized to investigate the DSD characteristics and DSD‐based polarimetric radar quantitative precipitation estimation (QPE) relations on the X, Ku, and Ka bands. The DSD characteristics were examined for different rain rates (R) and for stratiform and convective rainfall types. The raindrop spectra became wider and flatter as the R increased. Gamma parameters N0, μ, and λ (representing intercept, shape, and slope parameters, respectively) were smaller for convective compared to stratiform rainfall, corresponding to the broader and flatter convective raindrop spectra. The μ–λ and Dm–log10Nw relationships were also examined in our study. There was a significant μ–λ correlation, with a quadratic function relationship. The summer convective rainfall at both Dari and Delingha showed continental‐like clusters based on the Dm–log10Nw relationship. The DSD‐based two‐parameter polarimetric radar QPE relations (R(Zh, ZDR), R(KDP, ZDR)), and one‐parameter relations (R(Zh), R(KDP)) at the X, Ku, and Ka bands were proposed, and the R computed from DSD was implemented to evaluate these relations. The performance of two‐parameter models was stronger than that of one‐parameter models. Moreover, R(Zh, ZDR) and R(KDP, ZDR) performed better for the X and Ku bands, while the R(KDP, ZDR) model performed best for the Ka band. The ground‐based Ka/Ku band measurement Z at Dari was used to evaluate the Z–R and R−Dm QPE relations. The R−Dm relations had a better performance compared to the Z–R relations. The Ku radar‐derived R series are more consistent with the DSD measured counterparts. The research of the dual‐polarization radar parameter models is vital to develop radar QPE algorithms on the TP.

The effect of pore microstructure on strength and chloride ingress in blended cement based on low kaolin clay

The objective of this study is to analyse the mechanical and durability properties of a high-performance mortars based on low grade kaolin clay and the effect of electrical conductivity and pore microstructure on the chloride penetration resistance. A total of six mixes were prepared with binary and ternary binders in which a high volume of cement was replaced by low-grade calcined kaolin clay, fly ash and limestone powder. The percentage of kaolinite in the clay used from the Southeast European region was less than 20%. The variations in compressive strength and chloride transport coefficient were analysed experimentally and related to the pore structure and electrical conductivity. Compressive strength, chloride migration and diffusion coefficients, and bulk conductivity were determined using mortar samples, while the pore size distribution was determined by mercury intrusion porosimetry (MIP) on hardened cement paste after 7,28, and 90 days of curing. To understand the capillary absorption of these mixtures, sorptivity indices were measured after 28 and 90 days. The experimental characteristics of the pore size distribution, such as mean pore entry radius (r0.5), permeable porosity (P), capillary porosity (ɸ), and critical pore diameter (rc), were calculated using the cumulative data of the intruded volume as a function of pressure obtained by MIP. In addition, the extrusion-intrusion curve was used to calculate the pore entrapment fraction (α) and the degree of inter-connectivity of the pore structure. The evolution of pore structure parameters was monitored for up to 90 days and their effects on strength and chloride penetration were studied in detail. The results showed that all mixes (even those with low kaolinite content) can be used in high performance cement systems and the pore structure has a limited effect on chloride penetration.

Influence of COVID-19 Prevention and Control Measures on PM2.5 Concentration, Particle Size Distribution, Chemical Composition, and Source in Zhengzhou, China

The COVID-19 lockdown was a typical occurrence of extreme emission reduction, which presented an opportunity to study the influence of control measures on particulate matter. Observations were conducted from January 16 to 31, 2020 using online observation instruments to investigate the characteristics of PM2.5 concentration, particle size distribution, chemical composition, source, and transport before (January 16-23, 2020) and during (January 24-31, 2020) the COVID-19 lockdown in Zhengzhou. The results showed that the atmospheric PM2.5 concentration decreased by 4.8% during the control period compared with that before the control in Zhengzhou. The particle size distribution characteristics indicated that there was a significant decrease in the mass concentration and number concentration of particles in the size range of 0.06 to 1.6 μm during the control period. The chemical composition characteristics of PM2.5 showed that secondary inorganic ions (sulfate, nitrate, and ammonium) were the dominant component of PM2.5, and the significant increase in PM2.5 was mainly owing to the decrease in NO3- concentration during the control period. The main sources of PM2.5 identified by the positive matrix factorization (PMF) model were secondary sources, combustion sources, vehicle sources, industrial sources, and dust sources. The emissions from vehicle sources, industrial sources, and dust sources decreased significantly during the control period. The results of analyses using the backward trajectory method and potential source contribution factor method indicated that the effects of transport from surrounding areas on PM2.5 concentration decreased during the control period. In summary, vehicle and industrial sources should be continuously controlled, and regional combined prevention and control should be strengthened in the future in Zhengzhou.

Icaritin-loaded PLGA nanoparticles activate immunogenic cell death and facilitate tumor recruitment in mice with gastric cancer

This study aimed to explore the anti-tumor effect of icaritin loading poly (lactic-co-glycolic acid) nanoparticles (refer to PLGA@Icaritin NPs) on gastric cancer (GC) cells. Transmission Electron Microscope (TEM), size distribution, zeta potential, drug-loading capability, and other physicochemical characteristics of PLGA@Icaritin NPs were carried out. Furthermore, flow cytometry, confocal laser scanning microscope (CLSM), Cell Counting Kit-8 (CCK-8), Transwell, Elisa assay and Balb/c mice were applied to explore the cellular uptake, anti-proliferation, anti-metastasis, immune response activation effects, and related anti-tumor mechanism of PLGA@Icaritin NPs in vitro and in vivo. PLGA@Icaritin NPs showed spherical shape, with appropriate particle sizes and well drug loading and releasing capacities. Flow cytometry and CLSM results indicated that PLGA@Icaritin could efficiently enter into GC cells. CCK-8 proved that PLGA@Icaritin NPs dramatically suppressed cell growth, induced Lactic dehydrogenase (LDH) leakage, arrested more GC cells at G2 phase, and inhibited the invasion and metastasis of GC cells, compared to free icaritin. In addition, PLGA@Icaritin could help generate dozens of reactive oxygen species (ROS) within GC cells, following by significant mitochondrial membrane potentials (MMPs) loss and excessive production of oxidative-mitochondrial DNA (Ox-mitoDNA). Since that, Ox-mitoDNA further activated the releasing of damage associated molecular pattern molecules (DAMPs), and finally led to immunogenic cell death (ICD). Our in vivo data also elaborated that PLGA@Icaritin exerted a powerful inhibitory effect (∼80%), compared to free icaritin (∼60%). Most importantly, our results demonstrated that PLGA@Icaritin could activate the anti-tumor immunity via recruitment of infiltrating CD4+ cells, CD8+ T cells and increased secretion of cytokine immune factors, including interferon-γ (IFN-γ) tumor necrosis factor-α (TNF-α) and interleukin-1 (IL-1).++ Our findings validate that the successful design of PLGA@Icaritin, which can effectively active ICD and facilitate tumor recruitment in GC through inducing mitoDNA oxidative damage.

Development of MoO3-CdO nanoparticles based sensing device for the detection of harmful acetone levels in our skin and body via nail paint remover

Acetone plays a vital role as a cleanser for current cosmetic –products particularly nail paint, gels, fairness creams, face-wash, etc. Inhaling of acetone during cleaning skin and face can cause severe health issues which demand a highly sensitive acetone sensor. Formation of cadmium oxide (CdO) nanoparticles, two-dimensional molybdenum oxide (2D MoO3) nanosheets, and MoO3-CdO nanoparticles were investigated in terms of physical characteristics using the X-ray diffraction (XRD), Scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS), Dynamic light scattering (DLS) and UV–visible absorption analysis. Characterization studies witnessed the formation of MoO3-CdO nanoparticles with a characteristic energy band gap, crystallite size, and particle size distribution as 3.80 eV, 38.69 nm, and 2–50 nm, respectively. As fabricated MoO3-CdO nanoparticles-based sensor exhibited an excellent response of 13.48 at 25 ppm with rapid response and recovery times of 6.95 s and 8.34 s respectively. Acetone sensing studies were also conducted for the products of a few commercial companies like Acetone pure, Beauty Company, and Lakme in nail polish removers. The study of MoO3-CdO nanoparticles may be used for acetone sensing in cosmetic applications.

The Characteristics of Raindrop Size Distribution at Windward and Leeward Side over Mountain Area

To analyze the difference in the microphysical development characteristics of orographic rainfall, several Parsivel disdrometers were installed along the windward and leeward slope of a mountain. There were differences in the raindrop size distribution according to the difference in height and distance from the center of the mountain. In low-altitude coastal areas and adjacent areas, the number concentration of raindrops smaller than 1 mm was relatively lower than in mountainous areas, and the rain rate increased with the growth in the size of the raindrops. On the other hand, a higher rain rate was observed as the number concentration of raindrops smaller than 1 mm increased in the hillside area. The increase in the number concentration of small raindrops was evident at the LCL (lifting condensation level) altitude. The main factors affecting the increase in the rain rate on the windward and leeward slopes were the concentration of raindrops and the growth of raindrops, which showed regional differences. As a result of a PCA (principal component analysis), it was found that raindrop development by vapor deposition and weak convection were the main rainfall development characteristics on the windward and leeward slopes, respectively. The difference in regional precipitation development characteristics in mountainous areas affects the parameters of the rainfall estimation relational expression. This means that the rainfall relation calculated through the disdrometer observation data observed in a specific mountainous area can cause spatial and quantitative errors.

Activated polymorphonuclear derived extracellular vesicles are potential biomarkers of periprosthetic joint infection.

Extracellular vesicles (EVs) are considered as crucial players in a wide variety of biological processes. Although their importance in joint diseases or infections has been shown by numerous studies, much less is known about their function in periprosthetic joint infection (PJI). Our aim was to investigate activated polymorphonuclear (PMN)-derived synovial EVs in patients with PJI. (1) Is there a difference in the number and size of extracellular vesicles between periprosthetic joint aspirates of patients with PJI and aseptic loosening? (2) Are these vesicles morphologically different in the two groups? (3) Are there activated PMN-derived EVs in septic samples evaluated by flow cytometry after CD177 labelling? (4) Is there a difference in the protein composition carried by septic and aseptic vesicles? Thirty-four patients (n = 34) were enrolled into our investigation, 17 with PJI and 17 with aseptic prosthesis loosening. Periprosthetic joint fluid was aspirated and EVs were separated. Samples were analysed by nanoparticle tracking analysis (NTA) and transmission electron microscopy (TEM) and flow cytometry (after Annexin V and CD177 labelling). The protein content of the EVs was studied by mass spectrometry (MS). NTA showed particle size distribution in both groups between 150 nm and 450 nm. The concentration of EVs was significantly higher in the septic samples (p = 0.0105) and showed a different size pattern as compared to the aseptic ones. The vesicular nature of the particles was confirmed by TEM and differential detergent lysis. In the septic group, FC analysis showed a significantly increased event number both after single and double labelling with fluorochrome conjugated Annexin V (p = 0.046) and Annexin V and anti-CD177 (p = 0.0105), respectively. MS detected a significant difference in the abundance of lactotransferrin (p = 0.00646), myeloperoxidase (p = 0.01061), lysozyme C (p = 0.04687), annexin A6 (p = 0.03921) and alpha-2-HS-glycoprotein (p = 0.03146) between the studied groups. An increased number of activated PMN derived EVs were detected in the synovial fluid of PJI patients with a characteristic size distribution and a specific protein composition. The activated PMNs-derived extracellular vesicles can be potential biomarkers of PJI.

Comparison of summer raindrop size distribution characteristics in the western and central Tianshan Mountains of China

AbstractThe microphysical processes of cloud and precipitation in the Tianshan Mountains still remain unclear due to the complex terrain and the lack of ground‐based observational data. In this study, the characteristics of summer raindrop size distribution (RSD) in the western and central Tianshan Mountains of China were investigated in 2020 and 2021. According to the average raindrop spectra, the RSD characteristics exhibit significant differences that the concentration of medium and large particles is relatively higher at Zhaosu than that at Tianchi. Weak precipitation prevails in the Tianshan Mountains most of the time, yet moderate rainfall and heavy rainfall have a great impact on the accumulated rainfall amount. For each rainfall rate class, raindrops of diameter less than 0.75mm have a lower concentration and raindrops of diameter greater than 3 mm have a higher concentration at Zhaosu as compared to those at Tianchi. Compared with Tianchi, Zhaosu has a larger mass‐weighted mean diameter (Dm) and a lower normalized intercept parameter (log10Nw). Compared with the classical convective spectrum, the RSDs at both Zhaosu and Tianchi are similar to the continental convective cluster. The relationships between the shape and slope (μ–Λ), and radar reflectivity and rainfall rate (Z–R) exhibit a significant difference in the western and central Tianshan Mountains of China.

Inherent optical properties of suspended particulate matter in the southern Baltic Sea in relation to the concentration, composition and characteristics of the particle size distribution; new forms of multicomponent parameterizations of optical properties

This paper reports on detailed studies of the relationship between the inherent optical properties (IOPs) of suspended particulate matter populations occurring in southern Baltic Sea waters, and the basic biogeochemical and morphological quantities enabling these populations to be generally characterized. Specifically, these IOPs are the spectral absorption coefficients by all particulate matter, phytoplankton pigments and detritus, the spectral scattering and backscattering coefficients by particles, and the backscattering ratio. The biogeochemical properties of suspended matter populations are characterized by measuring concentrations of suspended particulate matter (SPM), particulate organic matter (POM) and particulate inorganic matter (PIM), as well as concentrations of various phytoplankton pigments, including chlorophyll a (Chla). We also take particle size distributions (PSDs) into account. This diverse empirical material is used to describe how the typical relationships between the IOPs of suspended matter and the concentrations of the main water constituents (SPM or Chla) can be influenced by differences in the general composition and size distributions of the suspended matter. We statistically describe the possible impact on these relationships of the variability of composition ratios, such as POM/SPM and Chla/SPM, as well as the impact of the variability of certain characteristics calculated on the basis of PSDs: the average particle diameter weighted by the particle's projected area (DA), the average apparent density of particles (ρa), the average intracellular concentration of chlorophyll a (ci), and the corresponding products of these quantities. We also demonstrate the significant variability of the specific IOPs (SIOPs) by attempting to determine them in the classical way for our southern Baltic data, and we give a possible interpretation of this variability. On the basis of these analyses, we derive new, multicomponent IOP parameterizations that are functions of several variables. These new parameterizations enable the IOPs of suspended matter to be characterized and predicted with better accuracy than with the often-used standard one-component relationships.

Measurement report: Interpretation of wide-range particulate matter size distributions in Delhi

Abstract. Delhi is one of the world's most polluted cities, with very high concentrations of airborne particulate matter. However, little is known about the factors controlling the characteristics of wide-range particle number size distributions. Here, new measurements are reported from three field campaigns conducted in winter and pre-monsoon and post-monsoon seasons at the Indian Institute of Technology campus in the south of the city. Particle number size distributions were measured simultaneously, using a scanning mobility particle sizer and a GRIMM optical particle monitor, covering 15 nm to &gt;10 µm diameter. The merged, wide-range size distributions were categorized into the following five size ranges: nucleation (15–20 nm), Aitken (20–100 nm), accumulation (100 nm–1 µm), large fine (1–2.5 µm), and coarse (2.5–10 µm) particles. The ultrafine fraction (15–100 nm) accounts for about 52 % of all particles by number (PN10 is the total particle number from 15 nm to 10 µm) but just 1 % by PM10 volume (PV10 is the total particle volume from 15 nm to 10 µm). The measured size distributions are markedly coarser than most from other parts of the world but are consistent with earlier cascade impactor data from Delhi. Our results suggest substantial aerosol processing by coagulation, condensation, and water uptake in the heavily polluted atmosphere, which takes place mostly at nighttime and in the morning hours. Total number concentrations are highest in winter, but the mode of the distribution is largest in the post-monsoon (autumn) season. The accumulation mode particles dominate the particle volume in autumn and winter, while the coarse mode dominates in summer. Polar plots show a huge variation between both size fractions in the same season and between seasons for the same size fraction. The diurnal pattern of particle numbers is strongly reflective of a road traffic influence upon concentrations, especially in autumn and winter, although other sources, such as cooking and domestic heating, may influence the evening peak. There is a clear influence of diesel traffic at nighttime, when it is permitted to enter the city, and also indications in the size distribution data of a mode &lt; 15 nm, which is probably attributable to CNG/LPG vehicles. New particle formation appears to be infrequent and is, in this dataset, limited to 1 d in the summer campaign. Our results reveal that the very high emissions of airborne particles in Delhi, particularly from traffic, determine the variation in particle number size distributions.