Effect of diesel exhaust particles on RANK/RANKL expression in in vivo and in vitro models of middle ear inflammation.

OBJECTIVE: Increasing evidence suggests a link between middle ear inflammation and the development of diesel exhaust particles (DEPs). Chronic middle ear inflammation can lead to bone damage and remodeling. This study aimed to explore the impact of DEPs on the expression of interleukin (IL)-6 and RANKL under conditions of middle ear inflammation. METHODS: DEPs were collected by burning fuel in a diesel engine at the Gwangju Institute of Science and Technology. Human middle ear epithelial cells were cultured to 70-80% confluence in culture plates and then treated with DEPs at concentrations of 0, 5, 10, 20, 40, and 80 µg/mL for 24 h. Cell viability was assessed manually. B6.SJL mice, aged 9 weeks, were exposed to DEPs at a concentration of 200 µg/m3 for 1 h daily over a period of 28 days. The expression levels of IL-6, tumor necrosis factor α, RANKL, and RANK were evaluated using hematoxylin and eosin staining and western blot analysis of the harvested middle ear samples. RESULTS: The viability of human middle ear epithelial cells was found to decrease in a dose-dependent manner after 24 h. The mRNA expression level of IL-6 exhibited the most significant increase at the 48-h mark. In contrast, the mRNA expression levels of RANKL and RANK showed a marked increase as early as 6 h post-exposure, with both genes subsequently displaying a time-dependent decrease. Histological analysis revealed that the middle ear mucosa was thicker in the group exposed to DEPs compared to the control group. Additionally, the protein expression levels of IL-6 and RANKL were elevated in the DEP-exposed group relative to the normal control group. CONCLUSIONS: We confirmed the expression of osteoclast-related proteins in the mouse middle ear. These results imply that air pollutants might affect RANKL/RANK signaling, which is associated with bone remodeling.

New health index derived from oxidative potential and cell toxicity of fine particulate matter to assess its potential health effect.

Toxicological data and exposure levels of fine particulate matters (PM2.5) are necessary to better understand their health effects. Simultaneous measurements of PM2.5 oxidative potential (OP) and cell toxicity in urban areas (Beijing, China and Gwangju, Korea) reveal their dependence on chemical composition. Notably, acids (Polar), benzocarboxylic acids, and Pb were the chemical components that affected both OP and cell toxicity. OP varied more significantly among different locations and seasons (winter and summer) than cell toxicity. Using the measured OP, cell toxicity, and PM2.5 concentration, a health index was developed to better assess the potential health effects of PM2.5. The health index was related to the sources of PM2.5 derived from the measured chemical components. The contributions of secondary organic aerosols and dust to the proposed health index were more significant than their contributions to PM2.5 mass. The developed regression equation was used to predict the health effect of PM2.5 without further toxicity measurements. This new index could be a valuable health metric that provides information beyond just the PM2.5 concentration level.

Rational design of hybrid sensor arrays combined synergistically with machine learning for rapid response to a hazardous gas leak environment in chemical plants.

Combinations of semiconductor metal oxide (SMO) sensors, electrochemical (EC) sensors, and photoionization detection (PID) sensors were used to discriminate chemical hazards on the basis of machine learning. Sensing data inputs were exploited in the form of either numerical or image data formats, and the classification of chemical hazards with high accuracy was achieved in both cases. Even a small amount of gas sensing or purging data (input for ∼30 s) input can be exploited in machine-learning-based gas discrimination. SMO sensors exhibit high performance even in a single-sensor mode, presumably because of the intrinsic cross-sensitivity of metal oxides, which is otherwise considered a major disadvantage of SMO sensors. EC sensors were enhanced through synergistic integration of sensor combinations with machine learning. For precision detection of multiple target analytes, a minimum number of sensors can be proposed for gas detection/discrimination by combining sensors with dissimilar operating principles. The Type I hybrid sensor combines one SMO sensor, one EC sensor, and one PID sensor and is used to identify NH3 gas mixed with sulfur compounds in simulations of NH3 gas leak accidents in chemical plants. The portable remote sensing module made with a Type I hybrid sensor and LTE module can identify mixed NH3 gas with a detection time of 60 s, demonstrating the potential of the proposed system to quickly respond to hazardous gas leak accidents and prevent additional damage to the environment.

Synergistic Integration of Machine Learning with Microstructure/Composition-Designed SnO2 and WO3 Breath Sensors.

A high-performance semiconductor metal oxide gas sensing strategy is proposed for efficient sensor-based disease prediction by integrating a machine learning methodology with complementary sensor arrays composed of SnO2- and WO3-based sensors. The six sensors, including SnO2- and WO3-based sensors and neural network algorithms, were used to measure gas mixtures. The six constituent sensors were subjected to acetone and hydrogen environments to monitor the effect of diet and/or irritable bowel syndrome (IBS) under the interference of ethanol. The SnO2- and WO3-based sensors suffer from poor discrimination ability if sensors (a single sensor or multiple sensors) within the same group (SnO2- or WO3-based) are separately applied, even when deep learning is applied to enhance the sensing operation. However, hybrid integration is proven to be effective in discerning acetone from hydrogen even in a two-sensor configuration through the synergistic contribution of supervised learning, i.e., neural network approaches involving deep neural networks (DNNs) and convolutional neural networks (CNNs). DNN-based numeric data and CNN-based image data can be exploited for discriminating acetone and hydrogen, with the aim of predicting the status of an exercise-driven diet and IBS. The ramifications of the proposed hybrid sensor combinations and machine learning for the high-performance breath sensor domain are discussed.

Proteomic analysis reveals activation of platelet- and fibrosis-related pathways in hearts of ApoE-/- mice exposed to diesel exhaust particles.

Air pollution is an environmental risk factor linked to multiple human diseases including cardiovascular diseases (CVDs). While particulate matter (PM) emitted by diesel exhaust damages multiple organ systems, heart disease is one of the most severe pathologies affected by PM. However, the in vivo effects of diesel exhaust particles (DEP) on the heart and the molecular mechanisms of DEP-induced heart dysfunction have not been investigated. In the current study, we attempted to identify the proteomic signatures of heart fibrosis caused by diesel exhaust particles (DEP) in CVDs-prone apolipoprotein E knockout (ApoE-/-) mice model using tandem mass tag (TMT)-based quantitative proteomic analysis. DEP exposure induced mild heart fibrosis in ApoE-/- mice compared with severe heart fibrosis in ApoE-/- mice that were treated with CVDs-inducing peptide, angiotensin II. TMT-based quantitative proteomic analysis of heart tissues between PBS- and DEP-treated ApoE-/- mice revealed significant upregulation of proteins associated with platelet activation and TGFß-dependent pathways. Our data suggest that DEP exposure could induce heart fibrosis, potentially via platelet-related pathways and TGFß induction, causing cardiac fibrosis and dysfunction.

Characteristics of fine particles from incense burning at temple premises of Kathmandu Valley, Nepal.

The impact of incense burning on ambient air quality was investigated by measuring the concentrations of fine particles (PM2.5), elemental carbon (EC), organic carbon (OC), and their oxidative potential (OP) at three temple premises in Kathmandu Valley, Nepal. These temples, namely, Bajrabarahi, Bagalamukhi, and Bhadrakali, are located in three distinct environments: forest, residential, and roadside, respectively. During the incense burning event days, the PM2.5 concentration at Bhadrakali (431.4 µgm-3) was significantly higher than that measured at the Bagalamukhi (135.2 µgm-3) and Bajrabarahi (84.7 µgm-3) temple premises. This observation is consistent with the fact that Bhadrakali Temple had the highest intensity of incense burning. Additionally, the temple premises were also influenced by vehicular emissions from transportation facilities. Carbonaceous aerosols significantly increased during incense burning events, indicating that incense burning contributes significantly to the formation of primary and secondary OC. Moreover, the OP of PM2.5 during the incense burning event days was higher compared to non-event days (p < 0.05), suggesting an elevated health risk due to the increased concentration and toxicity of fine particles. These findings highlight the substantial impact of incense burning on air quality in temple premises, emphasizing the need to implement effective strategies to mitigate the associated health risks.

KISTI remote control room for CDF and Belle II collider experiments.

Particle collider experiments would be continued even when one is not present at the laboratory (on-site). To achieve this, we require an e-Science paradigm of studying particle physics anytime anywhere. One of the components for establishing this paradigm is a remote control room for data acquisition (DAQ). We developed and embedded a remote control room at the Korea Institute of Science and Technology Information (KISTI). Since then, we have been adopting on/offline shifts for conducting collider experiments at KISTI, that is, the experiments are done even when we are not on-site. In this paper, we introduce our experience of our remote control room for both CDF and Belle II experiments. This remote control room includes international networks, security, DAQ systems, data transfers, and monitoring systems. We also presented the results of the shifts done in the remote control room at KISTI.

Metal contents and size distributions of brake and tire wear particles dispersed in the near-road environment.

Traffic related non-tailpipe particulate matter emissions can rival the continuously decreasing tailpipe emissions in modern fleets. Non-tailpipe emissions have become the dominating source of traffic emissions in California already. This study measured ambient PM2.5 and PM10 concentrations at near road environments for two major highways in California, I-5 in Anaheim and I-710 in Long Beach. A total of 51 elements were measured from filter samples collected over four-hour intervals for a two-week period in the winter of 2020 before the statewide lockdown by the COVID-19 pandemic. Iron was the most abundant element in ΔPM10 (differences between downwind and upwind sites), contributing to 30 % and 24 % of total measured elements in ΔPM10 at the I-5 and I-710 locations, respectively. Iron correlated highly with other brake wear markers (e.g., titanium, copper, barium, manganese, and zirconium) with coefficient of determination (r2) ranging from 0.67 to 0.90 in both PM2.5 and PM10. Silicon was the second most abundant element, contributing to 21 % of total measured elements in ΔPM2.5 and ΔPM10. Silicon showed strong correlations with crustal elements such as calcium (r2 = 0.90), aluminum (r2 = 0.96), and potassium (r2 = 0.72) in ΔPM2.5, and the correlations were even higher in ΔPM10. Barium had a weak correlation with zinc, a commonly used maker for tire wear, with r2 = 0.63 and r2 = 0.11 for ΔPM10 at the I-5 and I-710 locations respectively. Barium showed a positive correlation with crosswind speed and could serve as a good brake wear PM marker. Hourly PM2.5 concentrations of iron and zinc showed cyclic peaks from 0800 to 1000 h at I-5 during weekdays. Particle mass distributions showed peaks near ~7 µm, while particle number distributions showed peaks near 2.1 µm and 6.5 µm, respectively. This is consistent with brake wear and road dust size ranges previously reported.

Comparison of the sources and oxidative potential of PM2.5 during winter time in large cities in China and South Korea.

Regional air pollution is rising in Northeast Asia due to increasing energy consumption resulting from a growing population and intensifying industrialization. This study analyzes the sources of air pollution using fine particulate matter (PM2.5) sampling from the atmosphere over Korea and China. We then use this analysis to further investigate the relationship between organic compounds (source tracers) and the oxidative potential of PM2.5. The PM2.5 concentration during winter measured at a measurement stations in Korea showed no significant variation year-to-year. The PM2.5 concentrations measured during winter at a site near Beijing, China were 62.45 µg/m3 in 2018 and 33.07 µg/m3 in 2020. The sources, as determined from PMF, were analyzed at a site in Korea, the sources as secondary nitrate (34.10 %), secondary sulfate (20.20 %), coal combustion (4.01 %), vehicle emission (8.55 %), cooking and biomass burning (18.39 %), dust (8.45 %), and SOA (6.29 %) were identified. At a site in China, secondary nitrate (17.54 %), secondary sulfate (12.03 %), coal combustion (15.53 %), vehicle emission (12.43 %), cooking and biomass burning (9.25 %), dust (26.40 %), secondary organic aerosol (6.82 %) were identified. Our results show secondary organic carbon had a positive association with oxidative potential in Korea while primary organic carbon presented higher correlation with oxidative potential in China. Further, the ECMWF Reanalysis v5 (ERA5) wind field during the high PM2.5 events demonstrated airflow from the west coast of China resulting in high polar organic compounds at the Korean monitoring site. The results further support that aged PM2.5, which contains secondary products, leads to increased oxidative potential. The results presented explain the high concentrations of secondary products and the impact on the biological activities of PM2.5, supporting additional actions to address the impacts of long-range transport of PM2.5.

Diesel exhaust particles induce human umbilical vein endothelial cells apoptosis by accumulation of autophagosomes and caspase-8 activation.

Diesel exhaust particles (DEP) are risk factors for endothelial cells (ECs) dysfunction. However, the mechanism by which DEP induce ECs apoptosis remains unclear. Here, we investigated how DEP induce death of human umbilical vein ECs (HUVECs), with a focus on the autophagy-mediated apoptotic pathway. DEP induced dose-dependent HUVECs death and exposure to the IC50 concentration of DEP (70 µg/ml) led to apoptosis. DEP phosphorylated Beclin-1 (Ser93) and increased protein levels of p62 and LC3BII and the number of LC3B puncta, indicating autophagy initiation. DEP increased expression of pro- and mature forms of cathepsin D, which increases lysosomal activity. However, DEP suppressed expression of the soluble N-ethylmaleimide-sensitive factor attachment protein receptor proteins (STX17, VAMP8, SNAP29, YKT6, and STX7) to inhibit autolysosome formation, resulting in accumulation of autophagosomes. LC3B, p62, and caspase-8 form a tertiary complex in accumulated autophagosomes, which is known to serve as a platform for caspase-8 activation. Indeed, DEP activates caspase-8 and pretreatment with a caspase-8 inhibitor suppressed DEP-induced apoptosis. Furthermore, depletion of p62 decreased caspase-8 and caspase-3 activation and inhibited the DEP-induced apoptosis. Taken together, these findings demonstrated that DEP induced HUVECs apoptosis by inhibiting autophagosome maturation and identified caspase-8 as a novel mediator of DEP-induced ECs apoptosis.

Chromism-Integrated Sensors and Devices for Visual Indicators.

The bifunctionality of chromism-integrated sensors and devices has been highlighted because of their reversibility, fast response, and visual indication. For example, one of the representative chromism electrochromic materials exhibits optical modulation under ion insertion/extraction by applying a potential. This operation mechanism can be integrated with various sensors (pressure, strain, biomolecules, gas, etc.) and devices (energy conversion/storage systems) as visual indicators for user-friendly operation. In this review, recent advances in the field of chromism-integrated systems for visual indicators are categorized for various chromism-integrated sensors and devices. This review can provide insights for researchers working on chromism, sensors, or devices. The integrated chromic devices are evaluated in terms of coloration-bleach operation, cycling stability, and coloration efficiency. In addition, the existing challenges and prospects for chromism-integrated sensors and devices are summarized for further research.

Morphological and chemical classification of fine particles over the Yellow Sea during spring, 2015-2018.

Airborne fine particles can affect climate change and human health; moreover, they can be transported over significant distances. However, studies on characteristics of individual particles and their morphology, elemental composition, aging processes, and spatial distribution after long-range transport over the Yellow Sea are limited. Therefore, in this study, we conducted shipborne measurements of fine particulate matter of less than 2.5 µm in diameter (PM2.5) over the Yellow Sea and classified the individual particles into seven types based on their morphology and composition. Overall, the percentage of organic-rich particles was the highest, followed by that of sea spray, sulfur-rich, dust, metals, fly ash, soot, and other particles. Near Shandong, China, the percentage of fly ash and sulfur-rich particles increased, while an increased percentage of only sulfur-rich particles was observed near the Korean Peninsula. In the open sea, the PM2.5 concentrations were the lowest, and sea spray particles predominated. During the cruises, three types (Types 1, 2, and 3) of events with substantially increased PM2.5 concentrations occurred, each with different dominant particles. Type 1 events frequently featured air masses from northern China and Mongolia with high wind speeds and increased dust particles. Type 2 events involved air masses from China with high wind speeds; fly ash, soot, organic-rich particles, and the sulfate percentage in PM2.5 increased. Type 3 events displayed stagnant conditions and local transport (from Korea); soot, dust particles, and the secondary sulfate and nitrate percentages in PM2.5 increased. Thus, different types of transport affected concentrations and dominant types of fine particles over the Yellow Sea during spring.

Transcriptional analysis of gasoline engine exhaust particulate matter 2.5-exposed human umbilical vein endothelial cells reveals the different gene expression patterns related to the cardiovascular diseases.

Particulate matter (PM) causes several diseases, including cardiovascular diseases (CVDs). Previous studies compared the gene expression patterns in airway epithelial cells and keratinocytes exposed to PM. However, analysis of differentially expressed gene (DEGs) in endothelial cells exposed to PM2.5 (diameter less than 2.5 µm) from fossil fuel combustion has been limited. Here, we exposed human umbilical vein endothelial cells (HUVECs) to PM2.5 from combustion of gasoline, performed RNA-seq analysis, and identified DEGs. Exposure to the IC50 concentrations of gasoline engine exhaust PM2.5 (GPM) for 24 h yielded 1081 (up-regulation: 446, down-regulation: 635) DEGs. The most highly up-regulated gene is NGFR followed by ADM2 and NUPR1. The most highly down-regulated gene is TNFSF10 followed by GDF3 and EDN1. Gene Ontology enrichment analysis revealed that GPM regulated genes involved in cardiovascular system development, tube development and circulatory system development. Kyoto Encyclopedia of Genes and Genomes and Reactome pathway analyses showed that genes related to cytokine-cytokine receptor interactions and cytokine signaling in the immune system were significantly affected by GPM. We confirmed the RNA-seq data of some highly altered genes by qRT-PCR and showed the induction of NGFR, ADM2 and IL-11 at a protein level, indicating that the observed gene expression patterns were reliable. Given the adverse effects of PM2.5 on CVDs, our findings provide new insight into the importance of several DEGs and pathways in GPM-induced CVDs.

When river water meets seawater: Insights into primary marine aerosol production.

The impact of inorganic salts and organic matter (OM) on the production of primary marine aerosols is still under debate. To constrain their impact, we investigated primary aerosols generated by a sea-spray generator chamber using surface water samples from rivers, estuaries, and seas that were collected along salinity gradients in two temperate Korean coastal systems and one Arctic coastal system. Salinity values showed an increasing trend along the river-estuary-coastal water transition, indicating the lowest amount of inorganic salts in the river but the highest amount in the sea. In river samples, the lowest number concentration of primary aerosol particles (1.01 × 103 cm-3) was observed at the highest OM content, suggesting that low salinity controls aerosol production. Moreover, the number concentration of primary aerosols increased drastically in estuarine (1.13 × 104 cm-3) and seawater (1.35 × 104 cm-3) samples as the OM content decreased. Our results indicate that inorganic salts associated with increasing salinity play a much larger role than OM in aerosol production in river-dominated coastal systems. Laboratory studies using NaCl solution supported the conclusion that inorganic salt is a critical factor in modulating the particles produced from river water and seawater. Accordingly, this study highlights that inorganic salts are a critical factor in modulating the production of primary marine aerosols.

Application of Single-Particle Mass Spectrometer to Obtain Chemical Signatures of Various Combustion Aerosols.

A single-particle mass spectrometer (SPMS) with laser ionization was constructed to determine the chemical composition of single particles in real time. The technique was evaluated using various polystyrene latex particles with different sizes (125 nm, 300 nm, 700 nm, and 1000 nm); NaCl, KCl, MgCO3, CaCO3, and Al2O3 particles with different chemical compositions; an internal mixture of NaCl and KCl; and an internal mixture of NaCl, KCl, and MgCl2 with different mixing states. The results show that the SPMS can be useful for the determination of chemical characteristics and mixing states of single particles in real time. The SPMS was then applied to obtain the chemical signatures of various combustion aerosols (diesel engine exhaust, biomass burning (rice straw), coal burning, and cooking (pork)) based on their single-particle mass spectra. Elemental carbon (EC)-rich and EC-organic carbon (OC) particles were the predominant particle types identified in diesel engine exhaust, while K-rich and EC-OC-K particles were observed among rice straw burning emissions. Only one particle type (ash-rich particles) was detected among coal burning emissions. EC-rich and EC-OC particles were observed among pork burning particles. The single-particle mass spectra of the EC or OC types of particles differed among various combustion sources. The observed chemical signatures could be useful for rapidly identifying sources of atmospheric fine particles. In addition, the detected chemical signatures of the fine particles may be used to estimate their toxicity and to better understand their effects on human health.

Synthesis of vertically aligned wafer-scale tantalum disulfide using high-Ar/H2S ratio plasma.

Nanostructural modification of two-dimensional (2D) materials has attracted significant attention for enhancing hydrogen evolution reaction (HER) activity. In this study, the nanostructure of TaS2films was controlled by controlling the Ar/H2S gas ratio used in plasma-enhanced chemical vapor deposition (PECVD). At a high Ar/H2S gas ratio, vertically aligned TaS2(V-TaS2) films were formed over a large-area (4 in) at a temperature of 250 °C, which, to the best of our knowledge, is the lowest temperature reported for PECVD. Furthermore, the plasma species formed in the injected gas at various Ar/H2S gas ratios were analyzed using optical emission spectroscopy to determine the synthesis mechanism. In addition, the 4 in wafer-scale V-TaS2was analyzed by x-ray photoelectron spectroscopy, transmission electron microscopy, and atomic force microscopy, and the HER performance of the as-synthesized TaS2fabricated with various Ar/H2S ratios was measured. The results revealed that, depending on the film structure of TaS2, the HER performance can be enhanced owing to its structural advantage. Furthermore, the excellent stability and robustness of V-TaS2was confirmed by conducting 1000 HER cycles and post-HER material characterization. This study provides important insights into the plasma-assisted nanostructural modification of 2D materials for application as enhanced electrocatalysts.

Potential sources, scavenging processes, and source regions of mercury in the wet deposition of South Korea.

In this study, the potential sources, scavenging processes, and emission regions for Hg in wet deposition were investigated in rural (Jeju), suburban (Gwangju), and urban sites (Incheon and Seoul) of South Korea. The annual volume-weighted mean concentrations of Hg in wet deposition were four to five times higher in Incheon (16.6 ng L-1) and Seoul (22.5 ng L-1) than in Jeju (4.0 ng L-1) and Gwangju (4.1 ng L-1). The variations in the Hg concentrations in wet deposition of Jeju and Gwangju were related to Cl-, Na+, Mg2+, and K+ originating from marine and crustal sources, and those in Incheon and Seoul were related to SO42-, NO3-, and NH4+ emitted from anthropogenic sources. The below-cloud scavenging was considered a major inclusion process of Hg in Jeju and Gwangju, while the within-cloud scavenging was suggested in Incheon and Seoul, based on the results of correlation analysis with Hg and major ions in wet deposition, and meteorological data. The cluster analysis of backward trajectories demonstrated that the Hg concentration in wet deposition was highest in the cluster transported from Hebei and Shandong of China in Gwangju, but in Seoul, the Hg concentrations of each cluster were comparable. This suggests that regional transport is the major source of Hg in the wet deposition of Gwangju while local transport provides substantial amount of Hg in the wet deposition of Seoul. This was further supported by the results of concentration-weighted trajectories: the most probable source region was east China for Gwangju, and the mid-west of South Korea and east China for Seoul. It is noted that the peak methylmercury concentrations were found every spring with simultaneous increases in atmospheric Al, Ca, Mg, and Fe concentrations, indicating a concurrence with Asian dust. The formation process of methylmercury in Asian dust should be confirmed in future studies.

A Novel Path Planning Algorithm for Truck Platooning Using V2V Communication.

In truck platooning, the leading vehicle is driven manually, and the following vehicles run by autonomous driving, with the short inter-vehicle distance between trucks. To successfully perform platooning in various situations, each truck must maintain dynamic stability, and furthermore, the whole system must maintain string stability. Due to the short front-view range, however, the following vehicles' path planning capabilities become significantly impaired. In addition, in platooning with articulated cargo trucks, the off-tracking phenomenon occurring on a curved road makes it hard for the following vehicle to track the trajectory of the preceding truck. In addition, without knowledge of the global coordinate system, it is difficult to correlate the local coordinate systems that each truck relies on for sensing environment and dynamic signals. In this paper, in order to solve these problems, a path planning algorithm for platooning of articulated cargo trucks has been developed. Using the Kalman filter, V2V (Vehicle-to-Vehicle) communication, and a novel update-and-conversion method, each following vehicle can accurately compute the trajectory of the leading vehicle's front part for using it as a target path. The path planning algorithm of this paper was validated by simulations on severe driving scenarios and by tests on an actual road. The results demonstrated that the algorithm could provide lateral string stability and robustness for truck platooning.

Comparison of physical and chemical characteristics and oxidative potential of fine particles emitted from rice straw and pine stem burning.

Agricultural burning and forest fires are common in Northeast Asia and contribute to the elevation of fine particulate pollution, which greatly affects air quality. In this study, chemical and physical attributes, as well as the oxidative potential of fine particles produced from rice straw and pine stem burning in a laboratory-scale chamber were determined. The burning of rice straw generated notably lower emissions of fine particles and elemental carbon (EC) than did the burning of pine stems. The longer retention of ultrafine particles was observed for rice straw burning likely caused by this material's longer period of initial flaming combustion. Organic carbon (OC), OC/EC, K+/OC, K+/EC, Zn, and alkanoic acid were higher in the fine particles of rice straw burning, while EC, K+/Cl-, Fe, Cr, Al, Cu, and levoglucosan were higher for pine stem burning particles. Chemical data were consistent with a higher hygroscopic growth factor and cloud formation potential and lower amount of agglomerated soot for rice straw burning particles. Rice straw burning particles displayed an oxidative potential seven times higher than that of pine stems.

Assessment of PM2.5-bound nitrogen-containing organic compounds (NOCs) during winter at urban sites in China and Korea.

In this study, ambient fine particles (PM2.5) were collected in two urban cities in China and Korea (Beijing and Gwangju, respectively) simultaneously in January 2018. Analysis of the nonpolar and semipolar organic matter (OM) using atmospheric pressure photoionization (APPI) Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) revealed that compounds containing only C, H, and O (CHO) and those containing C, H, O, and N (CHON) accounted for more than 90% of the total intensity of the OM peaks. Higher proportions of CHON compounds were observed during days with abnormally high PM2.5 concentrations at both sites than on regular or non-event days. The proportion of CHON species at the Beijing site was not correlated with secondary ionic species (i.e., NO3-, SO42-, and NH4+) or gaseous components (i.e., O3, NO2, and SO2). In contrast, the proportion of CHON species at the Gwangju site was positively correlated with the concentrations of particulate nitrate and ammonium ions, assuming that ambient ammonium nitrate plays a role in the atmospheric formation of nitrogen-containing organic compounds (NOCs) at the Gwangju site and that Gwangju is more strongly influenced by secondary aerosols than Beijing is. In particular, a significant proportion of the compounds observed at the Beijing site contained only C, H and N (CHN), while negligible amounts of CHN were detected at the Gwangju site. The CHN species in Beijing were identified as quinoline compounds and the corresponding -CH2 homologous series using complementary GC × GC-TOF MS analysis. These results suggest that NOCs and their -CH2 homologous series from primary emissions may be significant contributors to nonpolar and semipolar OM during winter in Beijing, while NOCs with high oxidation states, likely formed via ambient-phase nitrate-mediated reactions, may be the dominant OM constituents in Gwangju.