Particle Number Concentration Research Articles

7 Construction and Characterization of a Thermal Spray Coating Aerosol Generator

Abstract Thermal spray coating (TSC) is a surface treatment process whereby feedstock material is sprayed onto surfaces under pressure where it solidifies and forms a solid coating. In metal TSC processes, large quantities of aerosols, including fine and ultrafine metal particles are generated. However, exposure assessment for TSC is lacking. The goal of this study was to construct a TSC aerosol generation system and to characterize the physicochemical properties of aerosols generated during coating processes. A computer-controlled, automated electric arc wire-TSC aerosol generator system was built in an enclosed room, where a rotary motor rotates a metal feedstock pipe in circular and up-and-down directions to allow even deposition of coating material on the pipe surface. The characteristics of aerosolized particles during spray coating using a stainless-steel wire (PMET 720) showed that: 1) respirable mass concentrations ranged from 142–218 mg/m3 (3 spray shots with each shot of 1-sec during 20-min sampling), 2) diameter of peak particle number concentrations was between 360 nm and 400 nm, 3) mass median aerodynamic diameter determined by an impactor ranged from 290–370 nm, 4) particle morphology was observed to be diverse including chain-like agglomerates and spherical and cylinder-like shapes, and 5) metal composition was 80% iron, 17% chromium, and 3% manganese with trace amounts of nickel and copper. These findings are limited to one wire type and suggests the need for further investigations evaluating various parameters (e.g., wire/powder types, high/low energy, ventilation on/off) to obtain emission rates and recommend control measures.

Snapshots of wintertime urban aerosol characteristics: Local sources emphasized in ultrafine particle number and lung deposited surface area

Urban air fine particles are a major health-relating problem. However, it is not well understood how the health-relevant features of fine particles should be monitored. Limitations of PM2.5 (mass concentration of sub 2.5 μm particles), which is commonly used in the health effect estimations, have been recognized and, e.g., World Health Organization (WHO) has released good practice statements for particle number (PN) and black carbon (BC) concentrations (2021). In this study, a characterization of urban wintertime aerosol was done in three environments: a detached housing area with residential wood combustion, traffic-influenced streets in a city centre and near an airport. The particle characteristics varied significantly between the locations, resulting different average particle sizes causing lung deposited surface area (LDSA). Near the airport, departing planes had a major contribution on PN, and most particles were smaller than 10 nm, similarly as in the city centre. The high hourly mean PN (>20 000 1/cm3) stated in the WHO's good practices was clearly exceeded near the airport and in the city centre, even though traffic rates were reduced due to a SARS-CoV-2-related partial lockdown. In the residential area, wood combustion increased both BC and PM2.5, but also PN of sub 10 and 23 nm particles. The high concentrations of sub 10 nm particles in all the locations show the importance of the chosen lower size limit of PN measurement, e.g., WHO states that the lower limit should be 10 nm or smaller. Furthermore, due to ultrafine particle emissions, LDSA per unit PM2.5 was 1.4 and 2.4 times higher near the airport than in the city centre and the residential area, respectively, indicating that health effects of PM2.5 depend on urban environment as well as conditions, and emphasizing the importance of PN monitoring in terms of health effects related to local pollution sources.

Performance of surface finished polyester filter media exposed to different dust types with the variation of dust concentration

Emissions of dust from industrial plants pose the greatest threat to environment and human health. Pulse-jet cleaning is the most efficient system to control industrial emissions. The present study consisted of four surface-treated filter media exposed to two dust types at three dust concentrations. The filtration performance in terms of filter efficiency is determined by the PM emissions, number concentration and gravimetric mass emissions of particles. Additionally, the filter performance is assessed by residual pressure drop and depth of dust penetration. The dust emissions, residual pressure drop, and depth of dust penetration are found to be lowest for needle-punched membrane (NPM) media. Apart from NPM, the needle-punched spun-laced water-repellent finished media showed better results than the other two surface filters used conventionally. For residual pressure drop, dust type contributes more at lower dust concentration levels. However, media (surface finish) surpasses the effect of dust type at higher dust concentration levels.

Soot formation of renewable gasoline: From fuel chemistry to particulate emissions from engines

Renewable fuels are essential to meet climate protection goals, especially for decarbonizing the existing vehicle fleet. In addition, optimized and specially designed fuels allow emissions to be avoided before they occur. This paper presents fuel effects on emission characteristics of six chemically complex gasoline blends compliant with the DIN EN 228 standard and one ethanol/gasoline blend, focusing on particle emissions. First, the sooting propensity of the fuels was examined using different soot indices, such as the Particulate Matter Index (PMI), the Oxygen Extended Sooting Index (OESI), the Yield Sooting Index (YSI), and the soot threshold (φST), which is drawn on measurements of the particle number (PN) density in the exhaust gas of a laminar flat flame. Second, PN emissions (particle number concentration) from a production-calibrated turbo gasoline direct injection engine with four cylinders were investigated. Third, soot precursor chemistry was investigated using a laminar flow reactor at atmospheric pressure. Finally, correlations to fuels’ volatility and chemical characteristics were made for the complete data set. Based on the soot precursor chemistry in the homogeneous gas phase reaction, the analysis shows that engine PN emissions are primarily influenced by fuel chemistry for the investigated engine conditions. In particular, the composition of the hydrocarbon fraction is decisive, with the heavy C9+ aromatics and the upper distillate significantly influencing soot formation. In order to reduce PN engine emissions, future fuels should contain fewer soot-increasing hydrocarbon fractions.

Measurement report: Atmospheric fluorescent bioaerosol concentrations measured during 18 months in a coniferous forest in the south of Sweden

Abstract. Biological aerosol particles affect human health, are essential for microbial and gene dispersal, and have been proposed as important agents for atmospheric processes. However, the abundance and size distributions of atmospheric biological particles are largely unknown. In this study we used a laser-induced fluorescence instrument to measure fluorescent biological aerosol particle (FBAP) concentrations for 18 months (October 2020–April 2022) at a rural, forested site in Sweden. The aim of this study was to investigate FBAP number concentrations (NFBAP) over time and analyze their relationship with meteorological parameters. NFBAP was highest in summer and lowest in winter, exhibiting a ∼ 5-fold difference between these seasons. The median NFBAP was 0.0050, 0.0025, 0.0027, and 0.0126 cm−3 in fall, winter, spring, and summer, respectively, and constituted ∼ 0.1–0.5 % of the total supermicron particle number concentration. NFBAP was dominated by the smallest measured size fraction (1–3 µm), suggesting that the main portions of the biological particles measured were due to single bacterial cells, fungal spores, and bacterial agglomerates. NFBAP was significantly correlated with increasing air temperature (P<0.01) in all seasons. For most of the campaign NFBAP was seen to increase with wind speed (P<0.01), while the relationship with relative humidity was for most of the campaign nonsignificant (46 %) but for a large part (30 %) negative (P<0.05). Our results indicate that NFBAP was highest during warm and dry conditions when wind speeds were high, suggesting that a major part of the FBAP in spring and summer was due to mechanical aerosol generation and release mechanisms. In fall, relative humidity may have been a more important factor in bioaerosol release. This is one of the longest time series of atmospheric FBAPs, which are greatly needed for estimates of bioaerosol background concentrations in comparable regions.

Experimental studies on the particulate matter emission characteristics of a lateral swirl combustion system for direct injection diesel engines

To analyze the particulate emission characteristics of a lateral swirl combustion system (LSCS), experimental research on a single-cylinder diesel engine was done and compared against the Turbocharger-Charge Air Cooling-Diesel Particle Filter Series combustion system (TCDCS) at different conditions. Compared to the TCDCS, the LSCS presents better combustion performance and lower total particle emission characteristics: As for the LSCS, the vast majority of the particle number size distributions shifted downward, indicating a decrease in the particle number concentration. The total particle number and mass concentrations of the LSCS decreased by 8.7–62.4% and 15.2–55.6% at various loads. The number concentration of particles smaller than approximately 8 nm increased for the LSCS, which can be attributed to the higher temperature and more thorough fuel/air mixture, facilitating the oxidation of large particles into small particles. Combined with the simulation, the LSCS perfectly exerts the wall-flow-guided effect, remarkably improving the fuel/air mixing quality and reducing the local over-concentration regions, which can inhibit the formation of particles. Hence, the LSCS effectively reduces the particle number and mass concentrations, exhibiting excellent particulate emission characteristics.

Mitigation of Respirable Aerosol Particles from Speech and Language Therapy Exercises

Phonation and speech are known sources of respirable aerosol in humans. Voice assessment and treatment manipulate all the subsystems of voice production, and previous work (Saccente-Kennedy et al., 2022) has demonstrated such activities can generate >10 times more aerosol than conversational speech and 30 times more aerosol than breathing. Aspects of voice therapy may therefore be considered aerosol generating procedures and pose a greater risk of potential airborne pathogen (eg, SARS-CoV-2) transmission than typical speech. Effective mitigation measures may be required to ensure safe service delivery for therapist and patient. To assess the effectiveness of mitigation measures in reducing detectable respirable aerosol produced by voice assessment/therapy. We recruited 15 healthy participants (8 cis-males, 7 cis-females), 9 of whom were voice-specialist speech-language pathologists. Optical Particle Sizers (OPS) (Model 3330, TSI) were used to measure the number concentration of respirable aerosol particles (0.3 µm-10 µm) generated during a selection of voice assessment/therapy tasks, both with and without mitigation measures in place. Measurements were performed in a laminar flow operating theatre, with near-zero background aerosol concentration, allowing us to quantify the number concentration of respiratory aerosol particles produced. Mitigation measures included the wearing of Type IIR fluid resistant surgical masks, wrapping the same masks around the end of straws, and the use of heat and moisture exchange microbiological filters (HMEFs) for a water resistance therapy (WRT) task. All unmitigated therapy tasks produced more aerosol than unmasked breathing or speaking. Mitigation strategies reduced detectable aerosol from all tasks to a level significantly below, or no different to, that of unmasked breathing. Pooled filtration efficiencies determined that Type IIR surgical masks reduced detectable aerosol by 90%. Surgical masks wrapped around straws reduced detectable aerosol by 96%. HMEF filters were 100% effective in mitigating the aerosol from WRT, the exercise that generated more aerosol than any other task in the unmitigated condition. Voice therapy and assessment causes the release of significant quantities of respirable aerosol. However, simple mitigation strategies can reduce emitted aerosol concentrations to levels comparable to unmasked breathing.

Data analysis for the characterization of nanoparticles with single particle inductively coupled plasma mass spectrometry: From microsecond to millisecond dwell times.

Single particle-inductively coupled plasma-mass spectrometry (SP-ICP-MS) has become a powerful technique for the characterization of nanoparticles (NPs). However, the accuracy of the characterization of NPs by SP-ICP-MS is greatly affected by the data acquisition rate and the way of data processing. For SP-ICP-MS analysis, ICP-MS instruments typically apply microsecond to millisecond dwell times (10 μs-10ms). Considering the duration of one nanoparticle event in the detector is 0.4-0.9ms, NPs will show different data forms when working with microsecond and millisecond dwell times. In this work, the effects of dwell times from microsecond to millisecond (50 μs, 100 μs, 1ms and 5ms) on the data forms in SP-ICP-MS analysis are discussed. The data analysis and data processing for different dwell times is discussed in detail, including the measurement of transport efficiency (TE), the distinction of signal and background, the evaluation of diameter limit of detection (LODd) and the quantification of mass, size and particle number concentration (PNC) of NPs. This work provides data support for the data processing process and aspects to be considered in the characterization of NPs by SP-ICP-MS, which is expected to provide guidance and reference for researchers in SP-ICP-MS analysis.

Characterisation and calibration of low-cost PM sensors at high temporal resolution to reference-grade performance

Particulate Matter (PM) low-cost sensors (LCS) present a cost-effective opportunity to improve the spatiotemporal resolution of airborne PM data. Previous studies focused on PM-LCS-reported hourly data and identified, without fully addressing, their limitations. However, PM-LCS provide measurements at finer temporal resolutions. Furthermore, government bodies have developed certifications to accompany new uses of these sensors, but these certifications have shortcomings. To address these knowledge gaps, PM-LCS of two models, 8 Sensirion SPS30 and 8 Plantower PMS5003, were collocated for one year with a Fidas 200S, MCERTS-certified PM monitor and were characterised at 2 min resolution, enabling replication of certification processes, and highlighting their limitations and improvements. Robust linear models using sensor-reported particle number concentrations and relative humidity, coupled with 2-week biannual calibration campaigns, achieved reference-grade performance, at median PM2.5 background concentration of 5.5 μg/m3, demonstrating that, with careful calibration, PM-LCS may cost-effectively supplement reference equipment in multi-nodes networks with fine spatiotemporality.

Development of a detection system for gas-phase aromatics and other molecules ionizable by soft X-rays demonstrated using methyl salicylate

In the present study, we developed the detection method for gas-phase aromatics and other molecules ionizable by soft X-rays demonstrated using methyl salicylate which is one of the chemical warfare agent simulants by using soft X-ray and aerosol measurement techniques. The aromatic chemical compounds which have the benzene ring are well detected by the soft X-ray assisted detection method which converts gas vapors to nanoparticles through the photochemical processes. The present study reports on the formation of nanoparticles by describing the stage change during the soft X-ray irradiation: particle-free mode; nucleation mode; transition mode; accumulation mode; and stable mode. In a controlled environment, the empirical calibration curves can predict ppbv-level methyl salicylate vapor concentrations using particle number or volume concentration data obtained from the real-time aerosol detection instrument. We expect that this technology can be utilized for calibrating or intercomparing other instruments that measure methyl salicylate concentrations.

Quantifying the reduction of airborne infectious viral load using a ventilated patient hood

Healthcare workers treating SARS-CoV-2 patients are at risk of infection by respiratory exposure to patient-emitted, virus-laden aerosols. Source control devices such as ventilated patient isolation hoods have been shown to limit the dissemination of non-infectious airborne particles in laboratory tests, but data on their performance in mitigating the airborne transmission risk of infectious viruses are lacking. We used an infectious airborne virus to quantify the ability of a ventilated hood to reduce infectious virus exposure in indoor environments. We nebulized 109 plaque forming units (pfu) of bacteriophage PhiX174 virus into a ∼30-m3 room when the hood was active or inactive. The airborne concentration of infectious virus was measured by BioSpot-VIVAS and settle plates using plaque assay quantification on the bacterial host Escherichia coli C. The airborne particle number concentration (PNC) was also monitored continuously using an optical particle sizer. The median airborne viral concentration in the room reached 1.41× 105pfu/m3 with the hood inactive. When active, the hood reduced infectious virus concentration in air samples by 374-fold. The deposition of infectious virus on the surface of settle plates was reduced by 87-fold. This was associated with a 109-fold reduction in total airborne particle number escape rate. A personal ventilation hood significantly reduced airborne particle escape, considerably lowering infectious virus contamination in an indoor environment. Our findings support the further development of source control devices to mitigate nosocomial infection risk among healthcare workers exposed to airborne viruses in clinical settings.

Dominant Role of Arctic Dust With High Ice Nucleating Ability in the Arctic Lower Troposphere

AbstractRecent observations show that dust emitted within the Arctic (Arctic dust) has a remarkably high ice nucleating ability, especially between −20°C and −5°C, but its impacts on the number concentrations of ice nucleating particles (INPs) and radiative balance in the Arctic are not well understood. Here we incorporate an observation‐based ice‐nucleation parameterization indicating the high ice nucleating ability of Arctic dust into a global aerosol‐climate model. A simulation using this parameterization better reproduces INP observations in the Arctic and estimates >100 times higher dust INP number concentrations with ∼100% contribution from Arctic dust in the Arctic lower troposphere (>60°N and >700 hPa) during summer and fall (June–November) than a simulation applying a standard ice‐nucleation parameterization suitable for desert dust to Arctic dust. Our results demonstrate the importance of considering an ice‐nucleation parameterization suitable for Arctic dust when simulating INPs and their effects on aerosol‐cloud interactions in the Arctic.

Event-driven sorting algorithm-based Monte Carlo method with neighbour merging method for solving aerosol dynamics

A new event-driven sorting algorithm-based merging Monte Carlo (SAMMC) method is proposed and developed for solving the general dynamic equation in aerosol dynamics. A neighbour merging method is proposed to maintain a constant-volume and constant-number scheme with minimal interference to the numerical particle population, where absolute volume difference (AVD) and relative volume difference (RVD) are used as the crucial merging criteria. The SAMMC method can be used for simulating all aerosol dynamic processes with very high computational accuracy, especially effective in those aerosol dynamic processes generating additional numerical particles. In the present study, comprehensive computational conditions are used to study their impacts on computational accuracy and efficiency by comparing the SAMMC method to previous MC methods and analytical solutions. Numerical results show that the SAMMC method has excellent agreement with analytical solutions for all specified cases of different aerosol dynamic processes and shows higher computational accuracy than equal-weight-based MC methods. In addition, the computational accuracy of the SAMMC method in the total particle number concentration is much higher than those of the weighted fraction Monte Carlo (WFMC) method and sorting algorithm-based merging weighted fraction Monte Carlo (SAMWFMC) method in non-homogeneous coagulation. The SAMMC method can also achieve the same computational precision as the multi-Monte Carlo (MMC) method at only slightly higher computational cost in homogeneous coagulation. More importantly, the SAMMC method can deal with breakage-related processes and simultaneous coagulation and nucleation with very high computational accuracy and efficiency, while the numerical results of the MMC method may significantly deviate from analytical solutions due to the introduction of systematic errors. Furthermore, the RVD can achieve higher computational accuracy in multi-breakage modelling than AVD, but AVD and RVD have almost the same computational efficiency and accuracy in other aerosol dynamic processes.

Effects of the test aerosol on the performance of periodic technical inspection particle counters

A new scheme for periodical technical inspection (PTI) of diesel-engine exhaust based on the measurement of particle number (PN) concentration was recently introduced in several European countries. PN concentration is measured directly at the tailpipe using portable particle counters known as PN-PTI. The technical specifications of these instruments are defined at a national level, and the type-examination and verification procedures differ considerably among European countries. In this study, we examined how the choice of test aerosol can affect the counting efficiency profile of the PN-PTI sensors, the majority of which are based on diffusion charging (DC). Carbonaceous aerosols were produced by combustion and spark discharge generators, sodium chloride (NaCl) particles were generated from aqueous solutions using several commercially available nebulizers and silver particles were produced by a silver particle generator. In most cases, the response of DC-based sensors depended strongly on the morphology of the test particles. Comparison with a Euro 3 diesel engine without a diesel particle filter (DPF) indicated that the combustion aerosols generated by combustion generators were the best proxy for soot emitted by diesel vehicle engines. On the contrary, the use of NaCl and spark discharge particles as test aerosols led in some cases to an over- or underestimation of the PN concentration by up to about a factor of two. Moreover, our results showed that the response of each type of DC-based sensors is individual and, as a result, it is impossible to determine a generally applicable factor to correct for the impact of the test aerosol properties. We recommend that the verification of PN-PTI instruments be preferably performed with soot particles produced by a combustion generator (identical or similar to the one used during the type-examination) in order to avoid corrections for the impact of the material on the response of the instruments.

A hybrid model for estimating the number concentration of ultrafine particles based on machine learning algorithms in central Taiwan

Modeling is a cost-effective measure to estimate ultrafine particle (UFP) levels. Previous UFP estimates generally relied on land-use regression with insufficient temporal resolution. We carried out in-situ measurements for UFP in central Taiwan and developed a model incorporating satellite-based measurements, meteorological variables, and land-use data to estimate daily UFP levels at a 1-km resolution. Two sampling campaigns were conducted for measuring hourly UFP concentrations at six sites between 2008–2010 and 2017–2021, respectively, using scanning mobility particle sizers. Three machine learning algorithms, namely random forest, eXtreme gradient boosting (XGBoost), and deep neural network, were used to develop UFP estimation models. The performances were evaluated with a 10-fold cross-validation, temporal, and spatial validation. A total of 1,022 effective sampling days were conducted. The XGBoost model had the best performance with a training coefficient of determination (R2) of 0.99 [normalized root mean square error (nRMSE): 6.52%] and a cross-validation R2 of 0.78 (nRMSE: 31.0%). The ten most important variables were surface pressure, distance to the nearest road, temperature, calendar year, day of the year, NO2, meridional wind, the total length of roads, PM2.5, and zonal wind. The UFP levels were elevated along the main roads across different seasons, suggesting that traffic emission is an important contributor to UFP. This hybrid model outperformed prior land use regression models and thus can provide more accurate estimates of UFP for epidemiological studies.

Emission Characteristics of Tyre Wear Particles from Light-Duty Vehicles

Tyre wear particle emissions have gained significant attention due to their harmful effects on the environment and human health. However, studies on tyre wear particles generated under chassis dynamometer conditions are still scarce. This study measures the instantaneous number concentrations and elemental species of tyre wear particles in different light-duty vehicle test cycles. The results show that the particle number (PN) concentrations of the US06 test cycle are much higher than those of the WLTC test cycle due to the larger and more frequent accelerations and decelerations in the former. High PN concentrations are observed during high driving speeds with rapid accelerations, while PN concentrations are much lower during low driving speed with rapid acceleration. Furthermore, tyre tread temperature is found to be related to the formation of tyre wear particles. The PN concentration in the second and third US06 test cycles are similar, indicating that once the tyre temperature exceeds the critical value, the tyres become heated to a steady state, and the PN concentrations will not be affected by the average temperature of the tyre. A low initial tyre temperature can produce high PN concentrations during the cold start phase of test cycles and prolong the time required for tyres to warm up. In addition, the particles contained a high mass fraction of Zn, which can serve as a tracer of tyre wear particles in non-exhaust particle tests of vehicles.

Occupational Exposure during the Production and the Spray Deposition of Graphene Nanoplatelets-Based Polymeric Coatings.

Graphene-based polymer composites are innovative materials which have recently found wide application in many industrial sectors thanks to the combination of their enhanced properties. The production of such materials at the nanoscale and their handling in combination with other materials introduce growing concerns regarding workers' exposure to nano-sized materials. The present study aims to evaluate the nanomaterials emissions during the work phases required to produce an innovative graphene-based polymer coating made of a water-based polyurethane paint filled with graphene nanoplatelets (GNPs) and deposited via the spray casting technique. For this purpose, a multi-metric exposure measurement strategy was adopted in accordance with the harmonized tiered approach published by the Organization for Economic Co-operation and Development (OECD). As a result, potential GNPs release has been indicated near the operator in a restricted area not involving other workers. The ventilated hood inside the production laboratory guarantees a rapid reduction of particle number concentration levels, limiting the exposure time. Such findings allowed us to identify the work phases of the production process with a high risk of exposure by inhalation to GNPs and to define proper risk mitigation strategies.

Firework smoke: Impacts on urban air quality and deposition in the human respiratory system

Particle number concentrations and size distributions resulting from the firework displays held in Budapest, Hungary every year on St. Stephen's Day were studied over a period of seven years. In the year most impacted, the total particle number concentration reached its peak measured level of 369 × 103 cm−3 5 min after the end of the display, and returned to the pre-event state within 45 min. The fireworks increased hourly mean concentrations by a factor of 5–6, whereas the concentrations in the diameter range of 100–1000 nm, in which the magnitude of the increase was the greatest, were elevated by a factor of 20–25. An extra particle size mode at 203 nm was manifested in the size distributions as result of the fireworks. The PM10 mass concentrations at peak firework influence and as 1-h mean increased 123 and 58 times, respectively, relative to the concentration before the display. The smoke was characterised by a relatively short overall atmospheric residence time of 25 min. Spatiotemporal dispersion simulations revealed that there were substantial vertical and horizontal concentration gradients in the firework plume. The affected area made up a large part of the city. Not only the spectators of the display at the venue and nearby areas, but the population located further away downwind of the displays and more distant, large and populous urban quarters were affected by the plume and its fallout. The fireworks increased the deposition rate in the respiratory system of females by a factor of 4, as a conservative estimate. The largest surface density deposition rates were seen in the segmental and sub-segmental bronchi, which represents an excessive risk to health. Compared to adults, children were more susceptible to exposure, with the maximum surface density deposition rates in their case being three times those of adults in the trachea.

Vertical distribution of inorganic nanoparticles in a Norwegian fjord

Due to the analytical challenges of detecting and quantifying nanoparticles in seawater, the data on distributions of NPs in the marine environment is limited to qualitative studies or by ensemble measurements subject to various analytical artifacts. Single particle inductively coupled plasma mass spectrometry (SP-ICP-MS) allows determination of individual inorganic NPs at environmentally relevant concentrations, yet only few studies have been conducted on selected elements in surface sea water. Here, a sequential multi-element screening method was developed and implemented to provide a first survey of the horizontal and vertical distributions of inorganic nanoparticles and trace elements in a pristine Norwegian fjord prospect for submarine tailings deposition. Statistical control of false-positive detections while minimizing the size detection limit was ensured using a novel raw signal processing. Scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) gave confirmative and qualitative information regarding particle morphology and composition. Following SP-ICP-MS screening for particles of 16 elements, particulate Al, Fe, Mn, Pb, Si and Ti were found and determined to mass concentrations in ng/L of 1–399, 1–412, below limit of detection (<LOD) - 269, <LOD - 1, <LOD - 1981 and <LOD - 127 ng/L with particle number concentrations up to 108 particles per liter. Total metals concentrations were at least an order of magnitude higher, at concentrations in μg/L of 1–12 for Al, 2–13 for Fe, 0.3–11 Mn, 0.02–0.5 for Pb, 46 to 318 Si and 0.04–0.4 for Ti. A strong depth dependence was observed for both trace elements and particles with concentrations increasing with depth. Our results provide a baseline for the fjord and new data on environmental levels of both total metals and metal containing nanoparticles including the vertical and horizontal distribution of natural nanoparticles.

Determination of the Particle Number Concentration, Size Distribution, and Species of Dominant Silver-Containing Nanoparticles in Soils by Single-Particle ICP-MS.

The potential risk of various silver-containing nanoparticles (AgCNPs) in soils is related to the concentration, size, and speciation, but their determination remains a great challenge. Herein, we developed an effective method for determining the particle number, size, and species of dominant AgCNPs in soils, including nanoparticles of silver (Ag NPs), silver chloride (AgCl NPs), and silver sulfide (Ag2S NPs). By ultrasonication wand-assisted tetrasodium pyrophosphate extraction, these AgCNPs were extracted efficiently from soils. Then, multistep selective dissolution of Ag NPs, AgCl NPs, and whole Ag NPs/AgCl NPs/Ag2S NPs was achieved by 1% (v/v) H2O2, 5% (v/v) NH3·H2O, and 10 mM thiourea in 2% (v/v) acetic acid, respectively. Finally, the particle number concentration and size distribution of AgCNPs in the extracts and the remaining AgCNP particle number concentration after each dissolution were determined by single-particle inductively coupled plasma mass spectroscopy for speciation of the dominant AgCNPs. AgCNPs were detected in all five soil samples with the concentrations of 0.23-8.00 × 107 particles/g and sizes of 16-110 nm. Ag2S NPs were the main form of AgCNPs in the examined soils with the percentage range of 53.98-69.19%, followed by AgCl NPs (11.42-23.31%) and Ag NPs (7.78-16.19%). Our method offers a new approach for evaluating the occurrence and potential risk of AgCNPs in environmental soils.