Atmospheric Particles Research Articles

Contribution of chemical composition to oxidative potential of atmospheric particles at a rural and an urban site in the Po Valley: Influence of high ammonia agriculture emissions

The present study investigates the chemical composition and oxidative potential (OP) of PM10 particles at two sites in the Po Valley (Norther Italy), with the aim of evidence the impact of high level of atmosphere ammonia (NH3). Field measurements were conducted in a rural location (Bertonico) close to farms strongly impacted by high ammonia emissions from agriculture and livestock husbandry. The urban site was in the metropolitan area of Milan. The NH3 concentrations observed at the rural site were about 5 times higher than those at the urban location, generating higher levels of secondary inorganic aerosol (ΣSIA) at Bertonico (16.6 ± 6.33 μg m−3) than at Milan 12.6 ± 4.93 μg m−3. The oxidative potential measured with the ascorbic acid assay (OPAAV) was almost triple in Milan than at Bertonico, namely 1.48 ± 1.08 nmol min−1 m−3 and 0.44 ± 0.23 nmol min−1 m−3, respectively, while the measured OPDTTV responses were similar at both sites, close to ∼ 0.5 ± 0.3 nmol min−1 m−3. These results suggested that the SIA components don't significantly contribute to the PM10 oxidative reactivity, although they account for most of the PM10 mass. Despite such an OP-inactivity, the SIA components resulted significantly correlated with both OPAAV and OPDTTV responses. This may be likely due to their inter-correlation with other redox-active components, such as the secondary organic species, which are synergically produced along with the SIA formation. In addition, an increase in the metals reactivity towards the OP assays, may be associated with the PM10 acidic environment produced by enhanced HNO3 and H2SO4 levels. Therefore, the contribution of the SIA to PM oxidative toxicity cannot be ignored in assessing health risk associated with PM exposure.

Measurement report: Dust and anthropogenic aerosols' vertical distributions over northern China dense aerosols gathered at the top of the mixing layer

Abstract. Over the past decades, northern China has been suffering from persistent air pollution caused by both fine and coarse atmospheric particles. Although there are plenty of theoretical and observational studies on aerosols in northern China, most of them only consider total aerosol concentrations and focus on heavy pollution episodes; the long-term vertical distributions of dust (coarse) and anthropogenic aerosols (fine) and their relationships with the mixing layer height (MLH) have not been revealed. In this study, the dust and anthropogenic aerosols' mass concentration and the MLH were retrieved by polarization Raman lidar over Beijing from May 2019 to February 2022. We found that large amounts of anthropogenic aerosols accumulate at the top of the mixing layer, which is most noticeable in summer, with monthly mean mass concentration up to 57 µg m−3. It is mainly influenced by the southward transport in the upper air, where the atmosphere is relatively stable and moist, favoring hygroscopic growth of particles. Dust mass concentration is discontinuous in the vertical direction, not only on the ground but also in lofted layers that reach up to several kilometers. The heights of these lofted dust layers exhibited apparent seasonal dependence, with the height of the main dust layer gradually ascending from 1.1 km to about 2.5 km from April to June and below 3 km from October to December. In addition, there is a significant negative correlation between bottom anthropogenic aerosols' mass concentration and the MLH, and an inverse function fit is more suitable to characterize this relationship, while the relationship between bottom dust mass concentration and the MLH is insignificant. These results will enhance our understanding of the sophisticated interactions between dust and anthropogenic aerosols, the MLH, and regional transport in northern China. It will also help to refine atmospheric chemistry models and improve surface prediction capabilities.

Acidity in rainwater and airborne suspended particles in the southwestern coast of the East Sea (Sea of Japan): Their potential impact on seawater total alkalinity

Our understanding of the impact of atmospheric acid deposition on marine carbonate system remains limited, largely due to a lack of data regarding acidity present in atmospheric particles and precipitation. Previous research has relied on the electroneutrality-based ion balance method for indirect estimation of atmospheric acidity. In this study, atmospheric samples collected at a coastal site of South Korea were mixed with seawater to measure the change in seawater total alkalinity (ΔTAAPL) associated with atmospheric proton loading. For the precipitation samples, the measured ΔTAAPL and electroneutrality-based estimates showed a significant correlation. However, we did not observe similar results for the atmospheric particle samples. Furthermore, the decrease in oceanic TA due to ΔTAAPL was substantially smaller than that in dissolved inorganic carbon from concurrent nitrogen fertilization. Consequently, the adverse impact of acid deposition on ocean acidification or air-sea exchange of CO2 appears to be insignificant on a short-term scale.

Dehazing in hyperspectral images: the GRANHHADA database.

In this study, we present an analysis of dehazing techniques for hyperspectral images in outdoor scenes. The aim of our research is to compare different dehazing approaches for hyperspectral images and introduce a new hyperspectral image database called GRANHHADA (GRANada Hyperspectral HAzy Database) containing 35 scenes with various haze conditions. We conducted three experiments to assess dehazing strategies, using the Multi-Scale Convolutional Neural Network (MS-CNN) algorithm. In the first experiment, we searched for optimal triplets of spectral bands to use as input for dehazing algorithms. The results revealed that certain bands in the near-infrared range showed promise for dehazing. The second experiment involved sRGB dehazing, where we generated sRGB images from hyperspectral data and applied dehazing techniques. While this approach showed improvements in some cases, it did not consistently outperform the spectral band-based approach. In the third experiment, we proposed a novel method that involved dehazing each spectral band individually and then generating an sRGB image. This approach yielded promising results, particularly for images with a high level of atmospheric dust particles. We evaluated the quality of dehazed images using a combination of image quality metrics including reference and non-reference quality scores. Using a reduced set of bands instead of the full spectral image capture can contribute to lower processing time and yields better quality results than sRGB dehazing. If the full spectral data are available, then band-per-band dehazing is a better option than sRGB dehazing. Our findings provide insights into the effectiveness of different dehazing strategies for hyperspectral images, with implications for various applications in remote sensing and image processing.

Improved Configurational Sampling Protocol for Large Atmospheric Molecular Clusters.

The nucleation process leading to the formation of new atmospheric particles plays a crucial role in aerosol research. Quantum chemical (QC) calculations can be used to model the early stages of aerosol formation, where atmospheric vapor molecules interact and form stable molecular clusters. However, QC calculations heavily depend on the chosen computational method, and when dealing with large systems, striking a balance between accuracy and computational cost becomes essential. We benchmarked the binding energies and structures and found the B97-3c method to be a good compromise between the accuracy and computational cost for studying large cluster systems. Further, we carefully assessed configurational sampling procedures for targeting large atmospheric molecular clusters containing up to 30 molecules (approximately 2 nm in diameter) and proposed a funneling approach with highly improved accuracy. We find that several parallel ABCluster explorations lead to better guesses for the cluster global energy minimum structures than one long exploration. This methodology allows us to bridge computational studies of molecular clusters, which typically reach only around 1 nm, with experimental studies that often measure particles larger than 2 nm. By employing this workflow, we searched for low-energy configurations of large sulfuric acid-ammonia and sulfuric acid-dimethylamine clusters. We find that the binding free energies of clusters containing dimethylamine are unequivocally more stable than those of the ammonia-containing clusters. Our improved configurational sampling protocol can in the future be applied to study the growth and dynamics of large clusters of arbitrary compositions.

A comprehensive survey of reference materials for their use in quality assurance for the determination of Np-237 in environmental samples

Neptunium-237 (237Np) is one of the most hazardous radionuclides of public concern due to its radiological toxicity, long half-life and high environmental mobility. Standard reference materials (SRMs) with well characterized 237Np activity concentrations are valuable for method development and validation of 237Np determination in environmental samples. In this study, a comprehensive literature survey of 237Np activity concentrations in 25 SRMs was carried out covering the various matrices of sediment, soil, seawater, atmospheric particles, and biota. After data screening, arithmetic mean of the activity concentrations of 237Np in literatures were calculated as statistical values (SVs). Then, accuracies of different instrument analyses and acid digestion methods were evaluated based on the SVs. Finally, by optimizing the sector field ICP-MS analytical method, 237Np activity concentration in JSAC-0471 soil SRM was measured. The application of SVs provides 237Np activity concentration information in more SRMs. Besides SRMs certified by technically validated procedures, SRMs with SVs and the measurement of JASC-0471 provide more options for suitable selection of SRMs for 237Np determination.

The effect of atmospherically relevant aminium salts on water uptake

Abstract. Atmospheric new particle formation is initiated by clustering of gaseous precursors, such as small acids and bases. The hygroscopic properties of those precursors therefore affect the hygroscopic properties of aerosol particles. In this work, the water uptake of different salts consisting of atmospheric small acids and amines was studied computationally using the conductor-like screening model for real solvents (COSMO-RS). This method allows for the prediction of water activities in atmospherically relevant salts that have not been included in other thermodynamics models. Water activities are reported here for binary aqueous salt solutions, as well as ternary solutions containing proxies for organic aerosol constituents. The order of the studied cation species regarding water activities is similar in sulfate, iodate, and methylsulfonate, as well as in bisulfate and nitrate. Predicted water uptake strengths (in mole fraction) conform to the following orders: tertiary > secondary > primary amines and guanidinos > amino acids. The addition of water-soluble organic to the studied salts generally leads to weaker water uptake compared to pure salts. On the other hand, water-insoluble organic likely phase separates with aqueous salt solutions, leading to minimal effects on water uptake.

Seasonal Disparities of Human Health Risk and Particle-Bound Metal Characteristics Associated with Atmospheric Particles in a Fishery Harbor.

The effects of atmospheric pollution from ship emissions have been considered for several harbors worldwide. The health risk assessment and source apportionment of particle-bound metals in a fishery harbor were investigated in this study. The most abundant metal elements in particulate matter (PM) on all sampling days in three seasons were Fe (280.94 ± 136.93 ng/m3), Al (116.40 ± 71.25 ng/m3), and Zn (110.55 ± 26.70 ng/m3). The ratios of V/Ni were 1.44 ± 0.31, 1.48 ± 0.09 and 1.87 ± 0.06 in PM10, PM2.5, and PM1, respectively. Meanwhile, the ratios higher than 1 indicated that fuel oil combustion from ship emission in fishery harbor. The highest deposits of total particle-bound metals in the human respiratory tract were in the head airway (HA), accounting for 76.77 ± 2.29% of the total particle-bound metal concentration, followed by 5.32 ± 0.13% and 2.53 ± 0.15% in the alveolar region (AR) and tracheobronchial (TB) region, respectively. The total cancer risk (CR) of inhalation exposure to local residents exceeded 10-6. Mean total CR values followed the sequence: autumn (1.24 × 10-4) > winter (8.53 × 10-5) > spring (2.77 × 10-6). Source apportionment of related metal emissions was mobile pollution emissions (vehicle/boat) (37.10-48.92%), metal fumes of arc welding exhaust (19.68-34.42%), spray-painting process (12.34-16.24%), combustion emissions (6.32-13.12%), and metal machining processes (9.04-16.31%) in Singda fishing harbor. These results suggest that proper control of heavy metals from each potential source in fishing harbor areas should be carried out to reduce the carcinogenic risk of adverse health effects.

Conditionally Background Level of Aerosol Pollution of Near-Surface Air in Moscow and One of Its Suburbs: Seasonal Variations

The data of continuous observations of aerosol composition in the near-surface atmosphere in Moscow (in the city center) and in Moscow region (near Zvenigorod, Moscow region) for three years, from autumn 2019 to the end of 2022, are analyzed. The obtained data were compared with the results of observations on the Moscow network stations “Mosecomonitoring”. The concept of conditionally background aerosol pollution of the atmosphere in Moscow is introduced for those days when the average daily concentration of PM10 is less than the MPC value (60 µg/m3). Previously, the authors found that all episodes of increased aerosol pollution in Moscow with daily average PM10 concentration higher than the MPC value, are associated either with the presence of a close local source in the city itself, or with the long-range transport of fire aerosols and/or dust from other territories to the Moscow region. The average daily PM2.5 concentration in the city and the suburb is lower than the MPC (35 µg/m3) all year round. The days corresponding to the introduced conditional background make up more than 91% over three years in the center of Moscow. Such a conditional background is formed by both natural and anthropogenic sources of aerosols, and not only of local, but also of remote origin. It implicitly takes into account the influence of meteorological conditions on sources and sinks of aerosols, as well as advective air mass transport of aerosol to and from the city. Seasonal variations in mass concentration of PM10, PM2.5 particles and individual chemical elements, as well as in the distribution of chemical elements by the size of aerosol particles in near-surface atmosphere under conditionally background pollution are analyzed. The emphasis is placed on the similarity and difference in the conditionally background near-surface aerosol for the city and the suburb in different seasons.

Chemical Characterization of Rural Organic Aerosol in the North China Plain Using Ultrahigh-Resolution Mass Spectrometry

Atmospheric organic aerosol (OA) affects air quality and human health. However, compared with urban areas, the chemical composition and temporal distribution of OA in rural regions are still not well understood. In this study, one-year atmospheric particles with an aerodynamic equivalent diameter of ≤2.5 μm (PM2.5) were collected at a rural site in Quzhou County, the North China Plain (NCP), from August 2020 to July 2021. OA in PM2.5 samples were analyzed with an ultrahigh-performance liquid chromatograph (UHPLC) coupled to an ultrahigh-resolution Orbitrap mass spectrometer in negative mode (ESI−). The results show that the chemical composition and properties of OA varied in different seasons. According to the hierarchical cluster analysis, the molecular formulas of winter OA were close to those in spring, whereas the chemical composition of OA in summer and autumn was similar. The O/C ratio of summer OA was the highest at 1.21, followed by that in autumn (0.92) and spring (0.87), while the winter OA had the lowest O/C ratio of 0.64. It indicates that, compared to the other three seasons, OA underwent more intense oxidation processes in the summer. Moreover, winter OA contained more aromatic compounds with a relative peak abundance fraction of 40%, which may be related to anthropogenic sources (e.g., coal burning) in the winter in the NCP. In addition, biomass burning is considered an important source of OA in the rural region of Quzhou County, the NCP, in all seasons.

Assessing the role of atmospheric dispersion vs. emission strength in the southern Po Valley (Italy) using dispersion-normalised multi-time receptor modelling

In this paper, we applied the Dispersion Normalised Positive Matrix Factorisation (DN-PMF) approach recently proposed in the literature to provide a more realistic picture of the relative importance of emission strength vs. atmospheric dispersion conditions. The disentanglement of such effects is of great concern in pollution hot spots like the Po Valley (Italy), where particulate matter limit values are exceeded despite the existing abatement measures. To explore the potentiality of the DN-PMF approach – still scarcely applied in the literature – a well-chemically characterised PM1 (atmospheric particles with aerodynamic diameter <1 μm) dataset comprising samples collected at different time resolutions at an urban background site (Bologna) in the southern Po Valley was used. Indeed, it is well known that shallow mixing layers promote pollutant accumulation but this observation is not enough to exclude an enhancement of emission strength which could be tackled by appropriate abatement strategies.The source apportionment of sub-micron sized aerosols having a quite long atmospheric residence time in a complex environment like the Po Valley - which is also strongly impacted by secondary aerosol formation on a basin-scale - is generally quite challenging when using receptor models. Due to the availability of a huge dataset with variables having multiple time resolutions, in this work the DN-PMF was implemented in a multi-time resolution approach (MT) to achieve a better source identification and to gain knowledge about the relative importance of atmospheric dilution vs. emissions. A comparison between results obtained by the application of the regular multi time resolution (REG-MT) vs. the DN-MT approach is presented here for the five factors identified (nitrate-dominated, sulphate-dominated, biomass burning, mineral dust, and urban aerosol). The first interesting outcome is that REG-MT and DN-MT results do not point at significant differences in temporal patterns for aerosol components and sources impacting at the basin-scale (i.e. sulphate- and nitrate-dominated aerosol, biomass burning) thus suggesting that the diel modulation of these PM1 emissions is somehow masked by the stronger variability of the mixing layer. Conversely, contributions from local sources with more pronounced diel variation like traffic are quite well reproduced by DN-MT and the ambient concentrations are enhanced compared to REG-MT. This is an important piece of information highlighting that PM1 concentrations from local sources have been likely underestimated by REG-MT assessments.To our knowledge, this is one of the very few applications of DN-MT and the first one at a European site where the huge effort made to implement air pollution containment measures is still not very much effective in reducing PM levels; moreover, in this paper a detailed discussion about the possible interpretation of the output of DN-MT in terms of temporal patterns is reported.

Microanalysis of Active Nitrogen Oxides (RONS) Generation Characteristics during DC Negative Corona Discharge at a Needle-Plate Electrode

The DC negative corona of needle-plate electrodes can generate atmospheric pressure low-temperature plasma active particles, which have important effects on biological mutagenesis. The DC negative corona discharge of an air needle-plate electrode with effective consideration of NOx particles was simulated and the Trichel pulse current was obtained, focusing on the development of particles and the distribution of active nitrogen oxides (RONS) at four moments in the pulse process. The simulation results indicate that the positive ions (N2+ and O2+) and negative ions (O− and O2−) were closely related to the current changes, and the negative ions (O− and O2−) presented a typical stratification phenomenon. RONS (H2O2, O3, and NO) were approximately uniformly distributed above the level of the plate electrode at the same instant, with H2O2 and O3 except for the area below the needle tip. They trended to a cumulative increase in concentration with time. This study provides a theoretical basis for corona discharge plasma seed treatment technology.

Theoretical Investigation of Inorganic Particulate Matter: The Case of Water Adsorption on a NaCl Particle Model Studied Using Grand Canonical Monte Carlo Simulations

Sodium chloride (NaCl) represents the principal component of atmospheric particulates of marine origin. To gain a molecular-level understanding of the adsorption process of water vapor on the NaCl surface, Monte Carlo simulations performed in the Grand Canonical ensemble were carried out, considering the water adsorption at different water pressures on a NaCl(001) surface. The calculated adsorption isotherm shows four different regions, whose coverages correspond to those of the low-, transition-, high-, and pre-solution-coverage regions experimentally observed. Detailed analysis reveals how the structure of the adsorbed water molecules (islands, layer, and multi-layer) changes depending on water pressure, and how their orientation with respect to the surface varies with the distance from the surface. This detailed information further supports the picture coming from previous experimental IR absorption spectroscopy studies.

Pollution status, particle-size distribution and health impacts (people at different ages) of polybrominated diphenyl ethers in bedrooms

Polybrominated diphenyl ethers (PBDEs) are widely found in the environment owing to the widespread use of brominated flame retardants. In recent years, polybrominated diphenyl ethers have attracted increasing attention because of their harmful effects on human health, especially in children, and have been recognized as significant indoor environmental pollutants. In this study, PBDEs were detected in 80 samples of air, dust, and particulate matter from bedrooms in Hangzhou, indicating that PBDE pollutions in bedrooms occur widely. The median concentration of ∑8PBDEs in dust was 8.54 ng/g, whereas in air and particulate matter was 13.60 pg/m3 and 23.94 pg/m3, respectively. BDE-209 was the main congeners in particles and dust. The mass distribution of atmospheric particles in bedrooms showed a bimodal distribution, mainly in the segments of < 1.1 and 3.3 − 4.7 µm. Through the analysis of typical bedroom materials, the specific PBDEs concentration order was as follows: curtain < wallpaper < mattress < socket panel, with median concentrations of 21.90 µg/g, 45.74 µg/g, 46.31 µg/g and 74.85 µg/g, respectively. The possible sources of PBDEs in residential air, dust, particulate matter was mattress, curtains and mattresses, and mattress and curtains, respectively. Infants have the highest daily exposure dose (DED) for ∑5PBDEs in the air and particulate matter phases, while toddles have the highest DED in dust. The HQ（Hazard Quotient）of infants, toddlers, children, teenagers, and adults were 8.58E-05, 1.06E-04, 4.17E-05, 2.53E-05 and 1.09E-05, respectively, indicating that pollution in bedrooms will not negatively impact human health. However, related studies have shown that children are more likely to be exposed to PBDEs than adults. Therefore, for infants and young children with weaker resistance and long-term family environments, PBDEs pollution may harm their health and growth.

Atmospheric Chemistry of NH2SO3H in Polluted Areas: An Unexpected Isomerization of NH2SO3H in Acid-Polluted Regions.

NH2SO3H is an effective nucleation agent for the formation of atmospheric aerosols and cloud particles. So, the ammonolysis of SO3 to form NH2SO3H without and with neutral (H2O) and basic (NH3) trace gases has been extensively investigated. However, the acidic trace gas X (X = H2SO4 and CH3SO3H)-assisted ammonolysis of SO3 is still up for debate. In this work, a comprehensive theoretical investigation of X-assisted ammonolysis of SO3 and its reverse reaction (the isomerization of NH2SO3H to form SO3-···NH3+) was carried out in the gas phase and at the air-water interface. The gas-phase results show that X-assisted isomerization of NH2SO3H to form SO3-···NH3+ is more energetically and kinetically favorable than its reverse reaction and the isomerization of NH2SO3H in the presence of H2O and NH3. Such unexpected findings revealed that gas-phase NH2SO3H is highly reactive in the presence of acidic trace gas in contrast to the high stability of NH2SO3H in neutral and basic conditions. At the air-water interface, the X-assisted isomerization reaction of NH2SO3H involves multiple water molecules. The loop structure of the reaction center (X···NH2SO3H···3H2O) promotes the transfer of protons in the water molecules to form the SO3-···NH3+ ion pair, which can then interact with several interfacial water molecules to form ammonium bisulfate. These interfacial reaction channels follow a stepwise mechanism and proceed at the picosecond time-scale. The findings of this study will contribute to a better understanding of the atmospheric behavior of NH2SO3H in polluted acidic trace gases.

Spatial and Temporal Variation of Particulate Matter (PM10 and PM2.5) and Its Health Effects during the Haze Event in Malaysia

This study aims to assess and compare levels of particulate matter (PM10 and PM2.5) in urban and industrial areas in Malaysia during haze episodes, which typically occur in the south west monsoon season. The high concentrations of atmospheric particles are mainly due to pollution from neighbouring countries. Daily PM concentrations were analysed for urban and industrial areas including Alor Setar, Tasek, Shah Alam, Klang, Bandaraya Melaka, Larkin, Balok Baru, and Kuala Terengganu in 2018 and 2019. The analysis employed spatiotemporal to examine how PM levels were distributed. The data summary revealed that PM levels in all study areas were right-skewed, indicating the occurrence of high particulate events. Significant peaks in PM concentrations during haze events were consistently observed between June and October, encompassing the south west monsoon and inter-monsoon periods. The study on acute respiratory illnesses primarily focused on Selangor. Analysis revealed that Klang had the highest mean number of inpatient cases for acute exacerbation of bronchial asthma (AEBA) and acute exacerbation of chronic obstructive pulmonary disease (AECOPD) with values of 260.500 and 185.170, respectively. Similarly, for outpatient cases of AEBA and AECOPD, Klang had the highest average values of 41.67 and 14.00, respectively. Shah Alam and Sungai Buloh did not show a significant increase in cases during periods of biomass burning. The statistical analysis concluded that higher concentrations of PM were associated with increased hospital admissions, particularly from June to September, as shown in the bar diagram. Haze episodes were associated with more healthcare utilization due to haze-related respiratory illnesses, seen in higher inpatient and outpatient visits (p &lt; 0.05). However, seasonal variability had minimal impact on healthcare utilization. These findings offer a comprehensive assessment of PM levels during historic haze episodes, providing valuable insights for authorities to develop policies and guidelines for effective monitoring and mitigation of the negative impacts of haze events.

Next-generation ice-nucleating particle sampling on board aircraft: characterization of the High-volume flow aERosol particle filter sAmpler (HERA)

Abstract. Atmospheric ice-nucleating particle (INP) concentration data from the free troposphere are sparse but urgently needed to understand vertical transport processes of INPs and their influence on cloud formation and properties. Here, we introduce the new High-volume flow aERosol particle filter sAmpler (HERA) which was specially developed for installation on research aircraft and subsequent offline INP analysis. HERA is a modular system consisting of a sampling unit and a powerful pump unit, and it has several features which were integrated specifically for INP sampling. Firstly, the pump unit enables sampling at flow rates exceeding 100 L min−1, which is well above typical flow rates of aircraft INP sampling systems described in the literature (∼ 10 L min−1). Consequently, required sampling times to capture rare, high-temperature INPs (≥ −15 ∘C) are reduced in comparison to other systems, and potential source regions of INPs can be confined more precisely. Secondly, the sampling unit is designed as a seven-way valve, enabling switching between six filter holders and a bypass with one filter being sampled at a time. In contrast to other aircraft INP sampling systems, the valve position is remote-controlled via software so that manual filter changes during flight are eliminated and the potential for sample contamination is decreased. This design is compatible with a high degree of automation, i.e., triggering filter changes depending on parameters like flight altitude, geographical location, temperature, or time. In addition to presenting the design and principle of operation of HERA, this paper describes laboratory characterization experiments with size-selected test substances, i.e., SNOMAX® and Arizona Test Dust. The particles were sampled on filters with HERA, varying either particle diameter (300 to 800 nm) or flow rate (10 to 100 L min−1) between experiments. The subsequent offline INP analysis showed good agreement with literature data and comparable sampling efficiencies for all investigated particle sizes and flow rates. Furthermore, the collection efficiency of atmospheric INPs in HERA was compared to a straightforward filter sampler and good agreement was found. Finally, results from the first campaign of HERA on the High Altitude and LOng range research aircraft (HALO) demonstrate the functionality of the new system in the context of aircraft application.

Electric field and force characteristic of dust aerosol particles on the surface of high-voltage transmission line

High-voltage transmission lines play a crucial role in facilitating the utilization of renewable energy in regions prone to desertification. The accumulation of atmospheric particles on the surface of these lines can significantly impact corona discharge and wind-induced conductor displacement. Accurately quantifying the force exerted by particles adhering to conductor surfaces is essential for evaluating fouling conditions and making informed decisions. Therefore, this study investigates the changes in electric field intensity along branched conductors caused by various fouling layers and their resulting influence on the adhesion of dust particles. The findings indicate that as individual particle size increases, the field strength at the top of the particle gradually decreases and eventually stabilizes at approximately 49.22 kV/cm, which corresponds to a field strength approximately 1.96 times higher than that of an unpolluted transmission line. Furthermore, when particle spacing exceeds 15 times the particle size, the field strength around the transmission line gradually decreases and approaches the level observed on non-adhering surface. The electric field remains relatively stable. In a triangular arrangement of three particles, the maximum field strength at the tip of the fouling layer is approximately 1.44 times higher than that of double particles and 1.5 times higher compared to single particles. These results suggest that particles adhering to the transmission line have a greater affinity for adsorbing charged particles. Additionally, relevant numerical calculations demonstrate that in dry environments, the primary adhesion forces between particles and transmission lines follow an order of electrostatic force and van der Waals force. Specifically, at the minimum field strength, these forces are approximately 74.73 times and 19.43 times stronger than the gravitational force acting on the particles.

Cadmium Isotope Fractionations Induced by Foliar and Root Uptake for Rice Exposed to Atmospheric Particles: Implications for Environmental Source Tracing

Cadmium Isotope Fractionations Induced by Foliar and Root Uptake for Rice Exposed to Atmospheric Particles: Implications for Environmental Source Tracing

Deep Neutral Network-Based Electron Microscopy Image Recognition for Source Distinguishing of Anthropogenic and Natural Magnetic Particles.

Deep learning models excel at image recognition of macroscopic objects, but their applications to nanoscale particles are limited. Here, we explored their potential for source-distinguishing environmental particles. Transmission electron microscopy (TEM) images can reveal distinguishable features in particle morphology from various sources, but cluttered foreground objects and scale variations pose challenges to visual recognition models. In this proof-of-concept work, we proposed a novel instance segmentation model named CoMask to tackle these issues with atmospheric magnetic particles, a key species of PM2.5. CoMask features a densely connected feature extraction module to excavate multiscale spatial cues at the single-particle level and enlarges the receptive field size for improved representation capability. We also employed a collaborative learning strategy to further improve performance. Compared with other state-of-the-art models, CoMask was competitive on benchmark and TEM data sets. The application of CoMask not only enables the source-distinguishing of magnetic particles but also opens up a new vista for machine learning applications.