Number Concentration Research Articles

Concentration‐number (C‐N) fractal models reveal the distribution pattern of the elements in ancient nephrite measured by portable X‐ray fluorescence: Based on nephrite objects excavated from different sites in Nanyang, Henan Province

AbstractChanges in the composition of various chemical elements in ancient nephrite artifacts due to prolonged burial are critical factors that should not be underestimated. However, the increasingly stringent heritage management has made many techniques impractical. Consequently, portable X‐ray fluorescence (pXRF) has become an indispensable nondestructive field analysis method. This paper aims to make use of the pXRF dataset to distinguish which elements tested are endogenous or exogenous, as well as to gauge which elements have been affected by stronger burial effects. More specifically, we carry out this work on the example of 103 pieces of nephrite excavated from different cemeteries in the Nanyang area. In addition to traditional statistical techniques, a new tool, the concentration‐number (C‐N) fractal method can shed new light on the analysis of the distribution patterns of different elements in excavated nephrite. The anomalous boundaries generated by the method have clear geochemical significance and can be delineated between background zone and disturbed regions. The degree of resistance of different elements to fluctuations in external factors was assessed, which has a direct relationship with the content of the buried soil. Considering the richness of the model, it has the potential to be used in archaeometrics.

Refining Bacteriuria as a Risk Factor for Complications After Urethroplasty: Identifying the Culprit

To determine which bacteria are associated with an increased risk of 90-day complications after urethroplasty. Preoperative bacteriuria is associated with an increased risk of complications after urethroplasty. However, it remains unclear which specific micro-organisms are the primary drivers of this morbidity. A single-institution, 2-surgeon retrospective review was performed on patients undergoing urethroplasty from 08/2003 to 06/2021. Preoperative bacteriuria was considered significant when the patient had a mixed culture with ≥108 CFU/L or an identifiable micro-organism with ≥106 CFU/L. Descriptive statistics were used to summarize the results and chi-square was used to determine the association between 90-day complications (Clavien ≥2) and clinical characteristics/bacteria. Out of 1611 patients, 23.2% (373) had significant preoperative bacteriuria. The most common pathogens included coagulase-negative staphylococcus 18.5% (69), mixed growth 15.8% (59), Escherichia coli 10.7% (40), and Enterococcus 14.2% (53). 7.9% (128/1611) experienced a significant 90-day complication (Clavien-Dindo ≥2). Gram-negative bacilli including E coli, Pseudomonas sp, Klebsiella sp, Serratia sp, Citrobacter sp, Achromobacter sp, Stenotrophomonas sp, and Morganella sp were associated with higher rates of postoperative complications (14.2%; P=.01) as well as Enterococcus sp (15.1%; P=.03). However, gram-positive cocci (7.9%; P=.97), gram-positive bacilli (11.8%; P=.47), mixed growth (5.1%; P=.54) and Candida (16.7%; P=.27) were not. Neither escalating concentrations of bacteria (P=.44) or number of strains (P=.08) were associated with increased risk of complications. The main driver of bacteriuria-related complications after urethroplasty are gram-negative bacilli and Enterococcus sp. Patients with bacteriuria related to other micro-organisms can likely proceed with urethroplasty without increased risk of postoperative complications.

Influence of the Reynolds number from Reτ = 150 to 210 on size-dependent bipolar charging

We recently found wall-bounded turbulence to suppress and control bipolar triboelectric charging of particles of identical material. This control is due to fluid modifying the motion of light particles. Thus, the particles’ charge distribution depends on their Stokes number distribution. More specifically, fluid forces narrow the bandwidth of the charge distribution, and bipolar charging reduces dramatically. Consequently, not the smallest but mid-sized particles collect the most negative charge. However, the influence of the Reynolds number or particle concentration on bipolar charging of polydisperse particles is unknown. This paper presents the charging simulations of same-material particles the in different wall-bounded flows. In a comprehensive study, we vary the Reynolds number from Reτ = 150 to 210 and the particle number density from 4 × 109m-3 to 1 × 1010m-3 to further explore the influence of the carrier flow on bipolar charging. We model charge transfer based on the balance of transferable charge species. Such species can represent adsorbed ions transferred during collisions or free electrons captured into a lower energy state on the other surface. The turbulent flow is modeled via Direct Numerical Simulations (DNS) and is coupled to the particulate phase modeled via the Discrete Element Method (DEM). Overall, our multiphysics approach couples the fluid dynamics, electric field, triboelectric charging, and particle momentum into one complex simulation.

Influence of a large commercial airport on the ultrafine particle number concentration in a distant residential area under different wind conditions and the impact of the COVID-19 pandemic

Exposure to ultrafine particles has a significant influence on human health. In regions with large commercial airports, air traffic and ground operations can represent a potential particle source. The particle number concentration was measured in a low-traffic residential area about 7 km from Frankfurt Airport with a Condensation Particle Counter in a long-term study. In addition, the particle number size distribution was determined using a Fast Mobility Particle Sizer.The particle number concentrations showed high variations over the entire measuring period and even within a single day. A maximum 24 h-mean of 24,120 cm−3 was detected. Very high particle number concentrations were in particular measured when the wind came from the direction of the airport. In this case, the particle number size distribution showed a maximum in the particle size range between 5 and 15 nm. Particles produced by combustion in jet engines typically have this size range and a high potential to be deposited in the alveoli. During a period with high air traffic volume, significantly higher particle number concentrations could be measured than during a period with low air traffic volume, as in the COVID-19 pandemic.A large commercial airport thus has the potential to lead to a high particle number concentration even in a distant residential area. Due to the high particle number concentrations, the critical particle size, and strong concentration fluctuations, long-term measurements are essential for a realistic exposure analysis.

Cloud-Resolving ICON Simulations of Secondary Ice Production in Arctic Mixed-Phase Stratocumuli Observed during M-PACE

Abstract Field measurements and modeling studies suggest that secondary ice production (SIP) may close the gap between observed Arctic ice nucleating particle (INP) concentrations and ice crystal number concentrations ni. Here, we explore sensitivities with respect to the complexity of different INP parameterizations under the premise that ni is governed by SIP. Idealized, cloud-resolving simulations are performed for the marine cold air outbreak cloud deck sampled during the Mixed-Phase Arctic Cloud Experiment (M-PACE) with the Icosahedral Nonhydrostatic (ICON) model. The impact of the droplet shattering (DS) of raindrops and collisional breakup (BR) in addition to the existing Hallet–Mossop rime splintering mechanism were investigated. Overall, 12 different model experiments (12-h runs) were performed and analyzed. Despite the considerable amount of uncertainty remaining with regard to SIP mechanisms and their process representation in numerical models, we conclude from these experiments that (i) only simulations where DS dominates the SIP signal (potentially amplified by BR) capture observed ice-phase and liquid-phase cloud properties, and (ii) SIP events cluster around the convective outflow region and are structurally linked to mesoscale cloud organization. In addition, interactions with primary nucleation parameterizations of varied complexity were investigated. Here, our simulations show that (i) a stable long-lived mixed-phase cloud (MPC) can be maintained in the absence of primary nucleation once SIP is established, (ii) experiments using a computationally more efficient relaxation-based parameterization of primary nucleation are statistically invariant from simulations considering prognostic INP, and (iii) primary nucleation at cloud-top controls the areal extent of the mixed-phase cloud region, and reduces SIP efficacy via DS due to increased depletion of cloud liquid throughout the entire cloud column. Significance Statement Secondary ice production (SIP) remains a key challenge in our understanding of boundary layer mixed-phase clouds. Here, we use sensitivity experiments performed with the ICON model at the cloud-resolving scale to explore potential interactions between primary nucleation, SIP, and mesoscale cloud organization. We simulate an Arctic single-layer cold air outbreak stratocumulus deck that was sampled during the M-PACE campaign. We find that once established, SIP alone is sufficient to maintain the mixed-phase cloud state until the end of the simulation. Our sensitivity analysis also shows that numerically more efficient treatments of immersion freezing are statistically invariant from simulations with a full prognostic INP budget.

Maximizing the Volume of Collocated Data from Two Coordinated Suborbital Platforms

Abstract Suborbital (e.g., airborne) campaigns that carry advanced remote sensing and in situ payloads provide detailed observations of atmospheric processes, but can be challenging to use when it is necessary to geographically collocate data from multiple platforms that make repeated observations of a given geographic location at different altitudes. This study reports on a data collocation algorithm that maximizes the volume of collocated data from two coordinated suborbital platforms and demonstrates its value using data from the NASA Aerosol Cloud Meteorology Interactions Over the western Atlantic Experiment (ACTIVATE) suborbital mission. A robust data collocation algorithm is critical for the success of the ACTIVATE mission goal to develop new and improved remote sensing algorithms, and quantify their performance. We demonstrate the value of these collocated data to quantify the performance of a recently developed vertically resolved lidar + polarimeter–derived aerosol particle number concentration (Na) product, resulting in a range-normalized mean absolute deviation (NMAD) of 9% compared to in situ measurements. We also show that this collocation algorithm increases the volume of collocated ACTIVATE data by 21% compared to using only nearest-neighbor finding algorithms alone. Additional to the benefits demonstrated within this study, the data files and routines produced by this algorithm have solved both the critical collocation and the collocation application steps for researchers who require collocated data for their own studies. This freely available and open-source collocation algorithm can be applied to future suborbital campaigns that, like ACTIVATE, use multiple platforms to conduct coordinated observations, e.g., a remote sensing aircraft together with in situ data collected from suborbital platforms. Significance Statement This study describes a data collocation (i.e., selection) process that aims to maximize the volume of data identified to be simultaneously collected in time and space from two coordinated measurement platforms. The functional utility of the resultant dataset is also demonstrated by extending the validation of aerosol particle number concentration derived from standard lidar and polarimeter data products from a suborbital mission that used two aircraft platforms.

High-concentration measurements with optical aerosol spectrometers by signal fluctuation analysis

Optical aerosol measurement systems can be classified into single-particle counting techniques and ensemble techniques. In single-particle counting instruments, such as optical aerosol spectrometers, each particle is analyzed individually. This allows for the accurate measurement of the number concentration and the size distribution of the measured aerosol. Current aerosol spectrometers suffer from a limited concentration range due to coincidence errors. In contrast, ensemble techniques, such as photometers, are suitable for high-concentration measurements. One major drawback of such instruments is that they only provide information about one aerosol property, which is typically the mass concentration. A new ensemble technique for the simultaneous measurement of two aerosol properties, namely particle size and concentration, was developed and experimentally verified. The results show that the median particle size (D50) of a monodisperse aerosol can be determined with a deviation of about 10 %, and the concentration with a deviation of about 30 %. With individual instrument calibration, the accuracy can be further improved to approximately 5 % with respect to particle size and 10 % with respect to concentration. The method may be either implemented as a standalone measurement device or, as an add-on for e. g. optical particle spectrometers in the form of a high-concentration mode.

Los Angeles Basin's air quality transformation: A long-term investigation on the impacts of PM regulations on the trends of ultrafine particles and co-pollutants

This study investigates the long-term trends of ambient ultrafine particles (UFPs) and associated airborne pollutants in the Los Angeles Basin from 2007 to 2022, focusing on the indirect effects of regulations on UFP levels. The particle number concentration (PNC) of UFPs was compiled from previous studies in the area, and associated co-pollutant data, including nitrogen oxides (NOx), carbon monoxide (CO), elemental carbon (EC), organic carbon (OC), and ozone (O3), were obtained from the chemical speciation network (CSN) database. Over the study period, a general decrease was noted in the PNC of UFPs, NOx, EC, and OC, except for CO, the concentration trends of which did not exhibit a consistent pattern. UFPs, NOx, EC, and OC were positively correlated, while O3 had a negative correlation, especially with NOx. Our analysis discerned two distinct sub-periods in pollutant trends: 2007–2015 and 2016–2022. For example, there was an overall decrease in the PNC of UFPs at an annual rate of −850.09 particles/cm3/year. This rate was more pronounced during the first sub-period (2007–2015) at −1814.9 particles/cm3/year and then slowed to −227.21 particles/cm3/year in the second sub-period (2016–2023). The first sub-period (2007–2015) significantly influenced pollutant level changes, exhibiting more pronounced and statistically significant changes than the second sub-period (2016–2022). Since 2016, almost all primary pollutants have stabilized, indicating a reduced impact of current regulations, and emphasizing the need for stricter standards. In addition, the study included an analysis of Vehicle Miles Traveled (VMT) trends from 2007 to 2022 within the Los Angeles Basin. Despite the general increase in VMT, current regulations and cleaner technologies seem to have successfully mitigated the potential increase in increase in PNC. Overall, while a decline in UFPs and co-pollutant levels was observed, the apparent stabilization of these levels underscores the need for more stringent regulatory measures and advanced emission standards.

Dynamics of nanocluster aerosol in the indoor atmosphere during gas cooking.

Nanocluster aerosol (NCA: particles in the size range of 1-3 nm) are a critically important, yet understudied, class of atmospheric aerosol particles. NCA efficiently deposit in the human respiratory system and can translocate to vital organs. Due to their high surface area-to-mass ratios, NCA are associated with a heightened propensity for bioactivity and toxicity. Despite the human health relevance of NCA, little is known regarding the prevalence of NCA in indoor environments where people spend the majority of their time. In this study, we quantify the formation and transformation of indoor atmospheric NCA down to 1 nm via high-resolution online nanoparticle measurements during propane gas cooking in a residential building. We observed a substantial pool of sub-1.5 nm NCA in the indoor atmosphere during cooking periods, with aerosol number concentrations often dominated by the newly formed NCA. Indoor atmospheric NCA emission factors can reach up to ∼1016 NCA/kg-fuel during propane gas cooking and can exceed those for vehicles with gasoline and diesel engines. Such high emissions of combustion-derived indoor NCA can result in substantial NCA respiratory exposures and dose rates for children and adults, significantly exceeding that for outdoor traffic-associated NCA. Combustion-derived indoor NCA undergo unique size-dependent physical transformations, strongly influenced by particle coagulation and condensation of low-volatility cooking vapors. We show that indoor atmospheric NCA need to be measured directly and cannot be predicted using conventional indoor air pollution markers such as PM2.5 mass concentrations and NO x (NO + NO2) mixing ratios.

The impact of vegetative and solid roadway barriers on particulate matter concentration in urban settings.

A potentially important approach for reducing exposure to traffic-related air pollution (TRAP) is the use of roadside barriers to reduce dispersion from highway sources to adjacent populated areas. The Trees Reducing Environmental Exposures (TREE) study investigated the effect of vegetative and solid barriers along major controlled-access highways in Atlanta, Georgia, USA by simultaneously sampling TRAP concentration at roadside locations in front of barriers and at comparison locations down-range. We measured black carbon (BC) mass concentration, particle number concentration (PNC), and the size distribution of ultrafine aerosols. Our sample sites encompassed the range of roadway barrier options in the Atlanta area: simple chain-link fences, solid barriers, and vegetative barriers. We used Generalized Linear Mixed Models (GLMMs) to estimate the effect of barrier type on the ratio of particle concentrations at the comparison site relative to the roadside site while controlling for covariates including wind direction, temperature, relative humidity, traffic volume, and distance to the roadway. Vegetative barriers exhibited the greatest TRAP reduction in terms of BC mass concentration (37% lower behind a vegetative barrier) as well as PNC (6.7% lower), and sensitivity analysis was consistent with this effect being more pronounced when the barrier was downwind of the highway. The ultrafine size distribution was comprised of modestly smaller particles on the highway side of the barrier. Non-highway particle sources were present at all sample sites, most commonly motor vehicle emissions from nearby arterials or secondary streets, which may have obscured the effect of roadside barriers.

قياس انبعاثات الجسيمات الصلبة وتوزيعها الناتجة من الوقود الحيوي في محرك التوربين الغازي المصغر

Atmospheric CO2 has been reported to be on a rapid increase in recent times mainly due to the rising consumption of fossil fuel for anthropogenic activities. Currently the situation is that of the 25% fossil fuel consumption by the transportation sector, aviation sector consumes about 13% of transport fuel consumption, which is the second biggest sector after road transportation. Therefore, the applications of biofuels have been increased in aviation. The aim of this work is to investigate and compare biodiesel and its blends with syntactic kerosene. The pollutants of particulate emissions and their size distributions were analyzed. Jet A1 and blends of Jet A1 and biodiesel in volume ratios of 90:10 (B10), 80:20 (B20), 70:30 (B30), 50:50 (B50) and 30:70 (B70) mixed with 2.5% turbine lubricating oil were tested. The fuels were tested at three load conditions (throttle settings): Full power, 70% and idle condition. Scanning Mobility Particle Sizer has been used to determine the particulate size distribution and the number of concentration of diluted exhaust gases. The results showed that particulates from all throttle settings showed uni-modal distribution characteristics. Particulate number concentration of each fuel increases with the increase in throttle position. The increase in biodiesel ratio in biodiesel blend has also increased the particulate size concentration. More particulates were seen to be produced with Jet A1 and lower blends of biodiesel. The engine also produces a significantly higher number of particles at full power for all fuel types. Keywords: Biodiesel, Micro Gas Turbine Engine, Scanning Mobility Particle Sizer, waste cooking oil, pollutants.

Impact of acidity and surface-modulated acid dissociation on cloud response to organic aerosol

Abstract. Acid dissociation of the organic aerosol fraction has the potential to impact cloud-activating properties by altering aqueous-phase H+ concentrations and water activity but is currently overlooked in most atmospheric aerosol models. We implemented a simple representation of organic acid dissociation in the aerosol–chemistry–climate box model ECHAM6.3–HAM2.3 and investigated the impact on aerosol-forming aqueous sulfur chemistry, cloud droplet number concentrations, and the shortwave radiative effect. Many atmospheric organic acids are also surface-active and may be strongly adsorbed at the surface of small aqueous droplets. The degree of dissociation has recently been observed for several atmospheric surface-active organics with Brönsted acid character to be significantly shifted in the surface, compared to the bulk aqueous solution. In addition to the well-known bulk acidity, we therefore introduced an empirical account of this surface-modulated dissociation to further explore the potential impact on aerosol climate effects. Malonic acid and decanoic acid were used as proxies for atmospheric organic aerosols of different surface-active and acid strengths. Both acids were found to yield sufficient hydrogen ion concentrations from dissociation in an aqueous droplet population to strongly influence aqueous aerosol sulfur chemistry, leading to enhanced cloud droplet number concentrations and a cooling shortwave radiative effect. Further considering the surface modulation of organic acid dissociation, the impact on cloud microphysics was smaller than according to the well-known bulk solution acidity but still significant. Our results show that organic aerosol acid dissociation can significantly influence predictions of aerosol and cloud droplet formation and aerosol–cloud–climate effects and that, even for a well-known bulk solution phenomenon such as acidity, it may be important to also consider the specific influence of surface effects when surface-active acids comprise a significant fraction of the total organic aerosol mass.

Modular Multiplatform Compatible Air Measurement System (MoMuCAMS): a new modular platform for boundary layer aerosol and trace gas vertical measurements in extreme environments

Abstract. The Modular Multiplatform Compatible Air Measurement System (MoMuCAMS) is a newly developed in situ aerosol and trace gas measurement platform for lower-atmospheric vertical profiling. MoMuCAMS has been primarily designed to be attached to a Helikite, a rugged tethered balloon type that is suitable for operations in cold and windy conditions. The system addresses the need for detailed vertical observations of atmospheric composition in the boundary layer and lower free troposphere, especially in polar and alpine regions. The MoMuCAMS encompasses a box that houses instrumentation, a heated inlet, a single-board computer to transmit data to the ground for in-flight decisions and a power distribution system. The enclosure can accommodate various combinations of instruments within its weight limit (e.g., 20 kg for a 45 m3 balloon). This flexibility represents a unique feature, allowing for the study of multiple aerosol properties (number concentration, size distribution, optical properties, chemical composition and morphology), as well as trace gases (e.g., CO, CO2, O3, N2O) and meteorological variables (e.g., wind speed and direction, temperature, relative humidity, pressure). Different instrumental combinations are therefore possible to address the specific scientific focus of the observations. It is the first tethered-balloon-based system equipped with instrumentation providing a size distribution for aerosol particles within a large range, i.e., from 8 to 3370 nm, which is vital to understanding atmospheric processes of aerosols and their climate impacts through interaction with radiation and clouds. Here we present a characterization of the specifically developed inlet system and previously unreported instruments, most notably the miniaturized scanning electrical mobility spectrometer and a near-infrared carbon monoxide monitor. As of December 2022, MoMuCAMS has been tested during two field campaigns in the Swiss Alps in winter and fall 2021. It was further deployed in Fairbanks, Alaska, USA, in January–February 2022, as part of the ALPACA (Alaskan Layered Pollution and Chemical Analysis) campaign and in Pallas, Finland, in September–October 2022, as part of the PaCE2022 (Pallas Cloud Experiment) study. Three cases from one of the Swiss Alpine studies are presented to illustrate the various observational capabilities of MoMuCAMS. Results from the first two case studies illustrate the breakup of a surface-based inversion layer after sunrise and the dilution of a 50–70 m thick surface layer. The third case study illustrates the capability of the system to collect samples at a given altitude for offline chemical and microscopic analysis. Overall, MoMuCAMS is an easily deployable tethered-balloon payload with high flexibility, able to cope with the rough conditions of extreme environments. Compared to uncrewed aerial vehicles (drones) it allows for observation of aerosol processes in detail over multiple hours, providing insights into their vertical distribution and processes, e.g., in low-level clouds, that were difficult to obtain beforehand.

Analysing the impact of day-night road traffic variation on ultrafine particle number size distribution and concentration at an urban site in the megacity Delhi

Air quality is the biggest threat in many urban cities globally. This study measured and analyzed aerosol number size distribution between 10 to 1090 nm in the megacity Delhi during 2022. The study examined the particle number concentration in the ultrafine (<100 nm) and accumulation (100–1000 nm) ranges during day and night in terms of source's intensity, emission patterns and local meteorological conditions. Nucleation mode particles (Nnuc, 10–30 nm) contributed ∼50 % during daytime in summer periods due to increased fresh traffic emissions. In the daytime, particle concentration was dominated by smaller sizes, such as Nnuc and Aitken mode particles (Natk, 30–100 nm), while in the nighttime, the particles were found in Aitken and Accumulation (Nacc, 100–1000 nm) modes. Nnuc and Natk were reduced by ∼45 % and 4 % at night, while Nacc increased by ∼34 %. The mean normalized aerosol number size distribution confirmed these findings, showing clearly that Nnuc dominated during the daytime, especially during peak rush hours, and during the night particles concentration was increased up to the sizes of 300 nm particles. The aerosol number size distribution and the changes experienced in the percentage of the concentration of the different particle size ranges highlight the role of engine exhaust emissions in the atmospheric aerosol population in urban areas. The findings of the study help to identify the different source's intensity and behavior during day and nighttime, which can be used for policy formulation and decision-making to mitigate air quality and its associated health impacts.

Modification of Microphysical Parameterization Schemes and Their Application in the Simulation of an Extremely Heavy Rainfall Event in Zhengzhou

AbstractIn the present study, the Morrison and Thompson microphysics schemes in the Weather Research and Forecasting model were improved and used to simulate a record‐breaking heavy rainfall event occurred in Henan Province over central China during 19–21 July 2021. In the modified schemes, the terminal velocity of graupel and initial cloud droplet concentration were adjusted based on sensitivity tests. Results showed that the modified Morrison scheme (MORR_MOD) better captured the spatial distribution and temporal evolution of precipitation than the original scheme (MORR). Specifically, it produced a 40‐hr cumulative rainfall amount of 963 mm and an extreme hourly rainfall rate of 157.7 mm, which were closer to observations than MORR. Analysis of the dynamic and microphysical structures of the extreme‐rain‐producing convective clusters revealed that MORR_MOD predicted stronger updrafts, higher rain mass content and larger mean mass diameter of raindrops than MORR. By analyzing the tendencies of rain mass and number concentration, it was found that MORR_MOD predicted stronger accretion rates of cloud droplets by rain and weaker auto‐conversion rates of cloud droplets than MORR, which contributed to the high rain mixing ratio and low number concentration, respectively. In addition, MORR_MOD predicted stronger diabatic heating rates than MORR, which were primarily attributed to stronger condensation of water vapor, and may have been the reason why MORR_MOD simulated stronger updrafts.

Two new multirotor uncrewed aerial vehicles (UAVs) for glaciogenic cloud seeding and aerosol measurements within the CLOUDLAB project

Abstract. Uncrewed aerial vehicles (UAVs) have become widely used in a range of atmospheric science research applications. Because of their small size, flexible range of motion, adaptability, and low cost, multirotor UAVs are especially well-suited for probing the lower atmosphere. However, their use so far has been limited to conditions outside of clouds, first because of the difficulty of flying beyond visual line of sight and second because of the challenge of flying in icing conditions in supercooled clouds. Here, we present two UAVs for cloud microphysical research: one UAV (the measurement UAV) equipped with a Portable Optical Particle Spectrometer (POPS) and meteorological sensors to probe the aerosol and meteorological properties in the boundary layer and one UAV (the seeding UAV) equipped with seeding flares to produce a plume of particles that can nucleate ice in supercooled clouds. A propeller heating mechanism on both UAVs allows for operating in supercooled clouds with icing conditions. These UAVs are an integral part of the CLOUDLAB project in which glaciogenic cloud seeding of supercooled low stratus clouds is utilized for studying aerosol–cloud interactions and ice crystal formation and growth. In this paper, we first show validations of the POPS on board the measurement UAV, demonstrating that the rotor turbulence has a small effect on measured particle number concentrations. We then exemplify the applicability for profiling the planetary boundary layer, as well as for sampling and characterizing aerosol plumes, in this case, the seeding plume. We also present a new method for filtering out high-concentration data to ensure good data quality of POPS. We explain the different flight patterns that are possible for both UAVs, namely horizontal or vertical leg patterns or hovering, with an extensive and flexible parameter space for designing the flight patterns according to our scientific goals. Finally, we show two examples of seeding experiments: first characterizing an out-of-cloud seeding plume with the measurement UAV flying horizontal transects through the plume and, second, characterizing an in-cloud seeding plume with downstream measurements from a POPS and a holographic imager mounted on a tethered balloon. Particle number concentrations and particle number size distributions of the seeding plume from the experiments reveal that we can successfully produce and measure the seeding plume, both in-cloud (with accompanying elevated ice crystal number concentrations) and out-of-cloud. The methods presented here will be useful for probing the lower atmosphere, for characterizing aerosol plumes, and for deepening our cloud microphysical understanding through cloud seeding experiments, all of which have the potential to benefit the atmospheric science community.

Modeling below-cloud scavenging of size-resolved particles in GEM-MACHv3.1

Abstract. Below-cloud scavenging (BCS) is the process of aerosol removal from the atmosphere between cloud base and the ground by precipitation (e.g., rain or snow), and affects aerosol number or mass concentrations, size distribution, and lifetime. An accurate representation of precipitation phases is important in treating BCS as the efficiency of aerosol scavenging differs significantly between liquid and solid precipitation. The impact of different representations of BCS on existing model biases was examined through implementing a new aerosol BCS scheme in the Environment and Climate Change Canada (ECCC) air quality prediction model GEM-MACH and comparing it with the existing scavenging scheme in the model. Further, the current GEM-MACH employs a single-phase precipitation for BCS: total precipitation is treated as either liquid or solid depending on a fixed environment temperature threshold. Here, we consider co-existing liquid and solid precipitation phases as they are predicted by the GEM microphysics. GEM-MACH simulations, in a local-area domain over the Athabasca oil sands areas, Canada, are compared with observed precipitation samples, with a focus on the particulate base cation NH4+; acidic anions NO3-, SO4=, HSO3- in precipitation; and observed ambient particulate sulfate, ammonium, and nitrate concentrations. Overall, the introduction of the multi-phase approach and the new scavenging scheme enhances GEM-MACH performance compared to previous methods. Including a multi-phase approach leads to altered SO4= scavenging and impacts the BCS of SO2 into the aqueous phase over the domain. Sulfate biases improved from +46 % to −5 % relative to Alberta Precipitation Quality Monitoring Program wet sulfate observations. At Canadian Air and Precipitation Monitoring Network stations the biases became more negative, from −10 % to −30 % for the tests carried out here. These improvements contrast with prior annual average biases of +200 % for SO4=, indicating enhanced model performance. Improvements in model performance (via scores for correlation coefficient, normalized mean bias, and/or fractional number of model values within a factor of 2 of observations) could also be seen between the base case and the two simulations based on multi-phase partitioning for NO3-, NH4+, and SO4=. Whether or not these improvements corresponded to increases or decreases in NO3- and NH4+ wet deposition varied over the simulation region. The changes were episodic in nature – the most significant changes in wet deposition were likely at specific geographic locations and represent specific cloud precipitation events. The changes in wet scavenging resulted in a higher formation rate and larger concentrations of atmospheric particle sulfate.

An Experimental Study on the Fine Particle Emissions of Brake Pads According to Different Conditions Assuming Vehicle Deceleration with Pin-on-Disc Friction Test

Fine particles from vehicles occur in a range of particulate matter (PM) sizes and influence the roadside atmosphere. The contribution of fine dust from automobiles to road pollution has reportedly been extremely high. Researchers have estimated that non-exhaust fine dust originating from brakes, tires, clutches, and road surface wear rate is increasing. Several studies have shown that brake pads account for a significant proportion of non-exhaust emissions. In this study, a friction test using vehicle brake pads was carried out with a friction tester to reveal the harmfulness of brake pad particles by the driver’s driving habits. Conditions were made considering the pressure, vehicle speed, and temperature and assuming the amount of deceleration of the vehicle. Particle collection devices were used to analyze the concentration of number and the mass distribution of particles produced in the experiment, with a range from 6 nm to 7.3 μm to gauge the toxicity of particles. The results showed that the number concentration of fine particles tended to increase linearly with changes in vehicle deceleration (braking energy) in the particle diameter region around 0.75–7.3 μm. The number concentration of fine particles tended to increase exponentially in the particle diameter region around 71–120 nm. The rapid occurrence of ultrafine particles in nanometers varied depending on the test conditions.

Traceable characterization of hollow organosilica beads as potential reference materials for extracellular vesicle measurements with optical techniques

The concentration of cell-type specific extracellular vesicles (EVs) is a promising biomarker for various diseases. However, concentrations of EVs measured by optical techniques such as flow cytometry (FCM) or particle tracking analysis (PTA) in clinical practice are incomparable. To allow reliable and comparable concentration measurements suitable reference materials (RMs) and SI-traceable (SI—International system of units) methods are required. Hollow organosilica beads (HOBs) are promising RM candidates for concentration measurements of EVs based on light scattering, as the shape, low refractive index, and number concentration of HOBs are comparable to EVs of the respective size range that can be detected with current optical instrumentation. Here, we present traceable methods for measuring the particle size distribution of four HOB types in the size range between 200 and 500 nm by small-angle X-ray scattering (SAXS) and atomic force microscopy (AFM), as well as the number concentration by single-particle inductively coupled plasma mass spectrometry (spICP-MS). Based on the size and shape results, traceable reference values were obtained to additionally determine the refractive index of the shell of the HOB samples by FCM. Furthermore, the estimated refractive indexes of the HOBs plausibly agree with the refractive indexes of EVs of corresponding size. Due to their narrow size distribution and their similar shape, and low refractive index, all HOB samples studied are suitable RM candidates for calibration of the measured sample volume by optical methods within the photon wavelength range used, and thus for calibration of number concentration measurements of EVs in the size range indicated. This was confirmed as the number concentration values obtained by PTA and two independent flow cytometric measurements agreed with the concentration reference values obtained by two independent spICP-MS measurements within the calculated uncertainty limits.

Ultrasonic aerosol agglomeration: Manipulation of particle deposition and its impact on air filter pressure drop

Acoustic agglomeration is a technique that leverages on sound waves to promote the collision of aerosol particulate matter, thus leading to the formation of larger particle agglomerates. In this study, this acoustics-driven phenomenon is demonstrated for its usefulness as an aerosol pre-conditioning method to significantly enhance the efficiency of filtration systems in particle treatment processes. Specifically, favorable changes in pressure drop across the filters are observed as a result of receiving less particle mass, for which filters are shown to be able to have their operational life extended remarkably by more than 50%. The involved ultrasonic aerosol agglomeration mechanisms are unveiled through numerical simulations, and the effects of residence time, sound pressure level, and initial particle number concentration on agglomeration performances are experimentally investigated. In addition, validations and measurements of filter pressure drop are obtained through a series of experiments. This study provides a comprehensive overview to the design and performance characterization of acoustics-agglomeration-enhanced filtration systems, which could potentially derive energy savings for fan power in ventilation systems and be scaled up for applications in industrial plants for reducing carbon emissions.