Mixing states and secondary formation processes of organic nitrogen-containing single particles in Guangzhou, China.

Organic nitrogen (ON) compounds play a significant role in the light absorption of brown carbon and the formation of organic aerosols, however, the mixing state, secondary formation processes, and influencing factors of ON compounds are still unclear. This paper reports on the mixing state of ON-containing particles based on measurements obtained using a high-performance single particle aerosol mass spectrometer in January 2020 in Guangzhou. The ON-containing particles accounted for 21% of the total detected single particles, and the particle count and number fraction of the ON-containing particles were two times higher at night than during the day. The prominent increase in the content of ON-containing particles with the enhancement of NOx mainly occurred at night, and accompanied by high relative humidity and nitrate, which were associated with heterogeneous reactions between organics and gaseous NOx and/or NO3 radical. The synchronous decreases in ON-containing particles and the mass absorption coefficient of water-soluble extracts at 365 nm in the afternoon may be associated with photo-bleaching of the ON species in the particles. In addition, the positive matrix factorization analysis found five factors dominated the formation processes of ON particles, and the nitrate factor (33%) mainly contributed to the production of ON particles at night. The results of this study provide unique insights into the mixing states and secondary formation processes of the ON-containing particles.

Chemical characterization and source attribution of organic pollutants in industrial wastewaters from a Chinese chemical industrial park.

Accelerated urbanization and industrialization have led to an alarming increase in the generation of wastewater with complex chemical contents. Industrial wastewaters are often a primary source of water contamination. The chemical characterization of different industrial wastewater types is an essential task to interpret the chemical fingerprints of wastewater to identify pollution sources and develop efficient water treatment strategies. In this study, we conduct a non-target chemical analysis for the source characterization of different industrial wastewater samples collected from a chemical industrial park (CIP) located in southeast China. The chemical screening identified volatile and semi-volatile organic compounds that included dibutyl phthalate at a maximum concentration of 13.4 µg/L and phthalic anhydride at 35.9 µg/L. Persistent, mobile, and toxic (PMT) substances among the detected organic compounds were identified and prioritized as high-concern contaminants given their impact on drinking water resources. Moreover, a source analysis of the wastewater collected from the wastewater outlet station indicated that the dye production industry contributed the largest quantities of toxic contaminates (62.6%), and this result was consistent with the ordinary least squares and heatmap results. Thus, our study utilized a combined approach of a non-target chemical analysis, a pollution source identification method, and a PMT assessment of different industrial wastewater samples collected from the CIP. The results of the chemical fingerprints of different industrial wastewater types as well as the results of the PMT assessment benefit risk-based wastewater management and source reduction strategies.

Detection of polycyclic aromatic hydrocarbons using a high performance-single particle aerosol mass spectrometer.

The real-time detection of the mixing states of polycyclic aromatic hydrocarbons (PAHs) and nitro-PAHs in ambient particles is of great significance for analyzing the source, aging process, and health effects of PAHs and nitro-PAHs; yet there is still few effective technology to achieve this type of detection. In this study, 11 types of PAH and nitro-PAH standard samples were analyzed using a high performance-single particle aerosol mass spectrometer (HP-SPAMS) in lab studies. The identification principles 'parent ions' and 'mass-to-charge (m/z) = 77' of each compound were obtained in this study. It was found that different laser energies did not affect the identification of the parent ions. The comparative experiments of ambient atmospheric particles, cooking and biomass burning emitted particles with and without the addition of PAHs were conducted and ruled out the interferences from primary and secondary organics on the identification of PAHs. Besides, the reliability of the characteristic ions extraction method was evaluated through the comparative study of similarity algorithm and deep learning algorithm. In addition, the real PAH-containing particles from vehicle exhaust emissions and ambient particles were also analyzed. This study improves the ability of single particle mass spectrometry technology to detect PAHs and nitro-PAHs, and HP-SPAMS was superior to SPAMS for detecting single particles containing PAHs and nitro-PAHs. This study provides support for subsequent ambient observations to identify the characteristic spectrum of single particles containing PAHs and nitro-PAHs.

Measurement of the mixing state of PAHs in individual particles and its effect on PAH transport in urban and remote areas and from major sources.

Although recent laboratory simulations have demonstrated that organic matter prevents the degradation of polycyclic aromatic hydrocarbons (PAHs), their role in the long-range transport of PAHs in the real atmosphere remains poorly understood. In this study, we measured the chemical composition and mixing state of PAHs-containing individual particles in aerosols from three sources, one urban area and one remote area. PAHs-containing particles were classified into five types: organic carbon (OC), potassium mixed with organic carbon (KOC), potassium mixed with sodium (KNa), Krich and PAH-rich. The PAH-rich and KOC particles were the main types of particles produced by vehicle exhaust/coal burning and biomass burning, respectively, accounting for >50% of the PAHs-containing particles. It was found that organic matter enhancement of PAHs-containing particles occurs in the ambient atmosphere, with organic-rich (OC and KOC) particles accounting for >90%. Further analysis revealed that the increase in the fractions of PAHs was related to the mixing state with organic compounds due to the protection of organics against PAHs and/or the aging of PAHs-containing particles. The results of this study improve our understanding of the chemical composition and mixing state of PAHs particles in atmospheric aerosols from emission sources and urban and remote areas, and provide field observation evidence to support the promotion of the study of long-range transport of PAHs by organics.

Enhanced mixing state of black carbon with nitrate in single particles during haze periods in Zhengzhou, China.

Black carbon (BC) plays an important role in air quality and climate change, which is closely associated with its mixing state and chemical compositions. In this work the mixing state of BC-containing single particles was investigated to explore the evolution process of ambient BC particles using a single particle aerosol mass spectrometer (SPAMS) in March 2018 in Zhengzhou, China. The BC-containing particles accounted for 61.4% of total detected ambient single particles and were classified into five types including BC-nitrate (BC-N, 52.3%) as the most abundant species, followed by BC-nitrate-sulfate (BC-NS, 22.4%), BCOC (16.8%), BC-fresh (BC-F, 4.5%) and BC-sulfate particles (BC-S, 4.0%). With enhancement of the ambient nitrate concentration, the relative peak area (RPA) of nitrate in BC-N and BCNS particles both increased, yet only the number fraction (Nf) of BCN particles increased while the Nf of BC-NS particles decreased, suggesting that the enhanced mixing state of BC with nitrate was mainly due to the increase in the ambient nitrate mass concentration. In addition, the Nf of BC-N decreased from 65.3% to 28.4% as the absorbing Ångström exponents (AAE) of eBC increased from 0.75 to 1.45, which indicated the reduction of light absorption ability of aged BC particles with the enhanced formation of BC-N particles. The results of this work indicated a change in the mixing state of BC particles due to the dominance of nitrate in PM2.5, which also influenced the optical properties of aged BC particles.

Paulownia C-geranylated flavonoids: their structural variety, biological activity and application prospects.

Paulownia species, especially their flowers and fruits, are traditionally used in Chinese herbal medicines for the treatment of infectious diseases. C-geranylated flavonoids were found to be the major special metabolites in Paulownia flowers and fruits, and 76 C-geranylated flavonoids had been isolated and characterized thus far. Structural variations in Paulownia C-geranylated flavonoids are mainly due to the complicated structural modifications in their geranyl substituents. These natural compounds have attracted much attention because of their various biological activities, including antioxidation, anti-inflammation, cytotoxic activity and various enzymatic inhibitions, etc. Among them, diplacone, a major Paulownia component, was considered to have promise for applications in medicine. This paper summarizes the information from current publications on Paulownia C-geranylated flavonoids, with a focus on their structural variety, key spectroscopic characteristics, biological activity with structure-activity relationships and application prospects. We hope that this paper will stimulate further investigations of Paulownia species and this kind of natural product.

Persistent sulfate formation from London Fog to Chinese haze.

Sulfate aerosols exert profound impacts on human and ecosystem health, weather, and climate, but their formation mechanism remains uncertain. Atmospheric models consistently underpredict sulfate levels under diverse environmental conditions. From atmospheric measurements in two Chinese megacities and complementary laboratory experiments, we show that the aqueous oxidation of SO2 by NO2 is key to efficient sulfate formation but is only feasible under two atmospheric conditions: on fine aerosols with high relative humidity and NH3 neutralization or under cloud conditions. Under polluted environments, this SO2 oxidation process leads to large sulfate production rates and promotes formation of nitrate and organic matter on aqueous particles, exacerbating severe haze development. Effective haze mitigation is achievable by intervening in the sulfate formation process with enforced NH3 and NO2 control measures. In addition to explaining the polluted episodes currently occurring in China and during the 1952 London Fog, this sulfate production mechanism is widespread, and our results suggest a way to tackle this growing problem in China and much of the developing world.

Real time analysis of lead-containing atmospheric particles in Guangzhou during wintertime using single particle aerosol mass spectrometry.

The toxic effects of lead on human health and the environment have long been a focus of research. To explore sources of lead in Guangzhou, China, we investigated atmospheric lead-containing particles (LCPs) during wintertime using a single particle aerosol mass spectrometer (SPAMS). Based on mass spectral features, LCPs were classified into eight major particle types, including Pb-Cl and Pb-Cl-Li (coal combustion and waste incineration), Pb-Cl-EC and Pb-Cl-OC (diesel trucks and coal combustion), Pb-Cl-Fe (iron and steel industry), Pb-Cl-AlSi (dust), Pb-Sec (secondary formation), and Pb-Cl-Zn (industrial process); these sources (in parentheses) were identified by comparing atmospheric LCP mass spectra with authentic Pb emission source mass spectra. Sampling periods with LCP number fractions (NFs) more than three times the average LCP NF (APF = 4.35%) and below the APF were defined as high LCP NF periods (HLFPs: H1, H3, and H5) and low LCP NF APF periods (LLFPs: L2 and L4), respectively. Diurnal patterns and high Pb-Sec content during LLFPs indicate that photochemical activity and heterogeneous reactions may have controlled Pb-Sec particle formation. The inverse Pb-Cl and Pb-Sec particle diurnal trends during LLFPs suggest the replacement of Cl by sulfate and nitrate. On average over the five periods, ~ 76% of the LCPs likely arose from coal combustion and/or waste incineration, which were dominant sources during all five periods, followed by diesel trucks during LLFPs and iron- and steel-related sources during HLFPs; HLFP LCPs arose mainly from primary emissions. These results can be used to more efficiently control Pb emission sources and prevent harm to human and environmental health from Pb toxicity.

Enhancing traditional Chinese medicine diagnostics: Integrating ontological knowledge for multi-label symptom entity classification.

In traditional Chinese medicine (TCM), artificial intelligence (AI)-assisted syndrome differentiation and disease diagnoses primarily confront the challenges of accurate symptom identification and classification. This study introduces a multi-label entity extraction model grounded in TCM symptom ontology, specifically designed to address the limitations of existing entity recognition models characterized by limited label spaces and an insufficient integration of domain knowledge. This model synergizes a knowledge graph with the TCM symptom ontology framework to facilitate a standardized symptom classification system and enrich it with domain-specific knowledge. It innovatively merges the conventional bidirectional encoder representations from transformers (BERT) + bidirectional long short-term memory (Bi-LSTM) + conditional random fields (CRF) entity recognition methodology with a multi-label classification strategy, thereby adeptly navigating the intricate label interdependencies in the textual data. Introducing a multi-associative feature fusion module is a significant advancement, thereby enabling the extraction of pivotal entity features while discerning the interrelations among diverse categorical labels. The experimental outcomes affirm the model's superior performance in multi-label symptom extraction and substantially elevates the efficiency and accuracy. This advancement robustly underpins research in TCM syndrome differentiation and disease diagnoses.

Single particle mass spectral signatures from on-road and non-road vehicle exhaust particles and their application in refined source apportionment using deep learning.

With advances in vehicle emission control technology, updating source profiles to meet the current requirements of source apportionment has become increasingly crucial. In this study, on-road and non-road vehicle particles were collected, and then the chemical compositions of individual particles were analyzed using single particle aerosol mass spectrometry. The data were grouped using an adaptive resonance theory neural network to identify signatures and establish a mass spectral database of mobile sources. In addition, a deep learning-based model (DeepAerosolClassifier) for classifying aerosol particles was established. The objective of this model was to accomplish source apportionment. During the training process, the model achieved an accuracy of 98.49 % for the validation set and an accuracy of 93.36 % for the testing set. Regarding the model interpretation, ideal spectra were generated using the model, verifying its accurate recognition of the characteristic patterns in the mass spectra. In a practical application, the model performed hourly source apportionment at three specific field monitoring sites. The effectiveness of the model in field measurement was validated by combining traffic flow and spatial information with the model results. Compared with other machine learning methods, our model achieved highly automated source apportionment while eliminating the need for feature selection, and it enables end-to-end operation. Thus, in the future, it can be applied in refined and online source apportionment of particulate matter.

Influence of ozone pollution on the mixing state and formation of oxygenated organics containing single particles.

The formation and aging processes of oxygenated organic molecules (OOMs) are important for understanding the formation mechanisms of secondary organic aerosols (SOAs) in the field. In this study, we investigated the mixing states of OOM particles by identifying several oxygenated species along with the distributions of secondary organic carbon (SOC) during both clean and ozone (O3)-polluted periods in July and September of 2022 in Guangzhou, China. OOM-containing particles accounted for 57 % and 49 % of the total detected single particles in July and September, respectively. Most of the OOM particles were internally mixed with sulfate and nitrate, while elemental carbon and hydrocarbon species were absent. Despite the higher SOC/OC ratio in September (81 %) than it in July (72 %), comparative investigations of the mass spectra, diurnal patterns, and distributions of OOM particles revealed the same composition and aging states of OOMs in two O3 pollution periods. As the O3 concentration increased from the clean to the polluted periods, the ratio of SOC to OC increased along with the relative abundance of secondary OOM particles among total OOM particles. In contrast, the relative abundance of OC-type OOM particles gradually decreased, indicating the conversion of hydrocarbon species into OOMs as the SOC/OC ratio increased. Both the bulk analysis of SOC from filter measurement and the mixing states of OOM particles suggested that OOM production and degree of oxidation were higher in the O3-polluted periods than in the clean periods. These results elucidate the effects of O3 pollution on the OOM formation process and offer new perspectives for the joint investigation of SOA production based on filter sampling and single-particle measurements.

Characteristics of Volatile Organic Compounds Emitted from Airport Sources and Their Effects on Ozone Production.

In recent years, commercial air transport has increased considerably. However, the compositions and source profiles of volatile organic compounds (VOCs) emitted from aircraft are still not clear. In this study, the characteristics of VOCs (including oxygenated VOCs (OVOCs)) emitted from airport sources were measured at Shenzhen Bao'an International Airport. The results showed that the compositions and proportions of VOC species showed significant differences as the aircraft operating state changed. OVOCs were the dominant species and accounted for 63.17%, 58.44%, and 51.60% of the total VOC mass concentration during the taxiing, approach, and take-off stages. Propionaldehyde and acetone were the main OVOCs, and dichloromethane and 1,2-dichloroethane were the main halohydrocarbons. Propane had the highest proportion among all alkanes, while toluene and benzene were the predominant aromatic hydrocarbons. Compared with the source profiles of VOCs from construction machinery, the proportions of halogenated hydrocarbons and alkanes emitted from aircraft were significantly higher, as were those of propionaldehyde and acetone. OVOCs were still the dominant VOC species in aircraft emissions, and their calculated ozone formation potential (OFP) was much higher than that of other VOC species at all stages of aircraft operations. Acetone, propionaldehyde, formaldehyde, acetaldehyde, and ethylene were the greatest contributors to ozone production. This study comprehensively measured the distribution characteristics of VOCs, and its results will aid in the construction of a source profile inventory of VOCs emitted from aircraft sources in real atmospheric environments.

Combining the External Medical Knowledge Graph Embedding to Improve the Performance of Syndrome Differentiation Model.

The electronic medical records (EMRs) of traditional Chinese medicine (TCM) include a wealth of TCM knowledge and syndrome diagnosis information, which is crucial for improving the quality of TCM auxiliary decision-making. In practical diagnosis, one disease corresponds to one syndrome, posing considerable hurdles for the informatization of TCM. The purpose of this work was to create an end-to-end TCM diagnostic model, and the knowledge graph (KG) created in this article is used to improve the model's information and realize auxiliary decision-making for TCM disorders. We approached auxiliary decision-making for syndrome differentiation in this article as a multilabel classification task and presented a knowledge-based decision support model for syndrome differentiation (KDSD). Specifically, we created a KG based on TCM features (TCMKG), supplementing the textual representation of medical data with embedded information. Finally, we proposed fusing medical text with KG entity representation (F-MT-KER) to get prediction results using a linear output layer. After obtaining the vector representation of the medical record text using the BERT model, the vector representation of various KG embedded models can provide additional hidden information to a certain extent. Experimental results show that our method improves by 1% (P@1) on the syndrome differentiation auxiliary decision task compared to the baseline model BERT. The usage of EMRs can aid TCM development more efficiently. With the help of entity level representation, character level representation, and model fusion, the multilabel classification method based on the pretraining model and KG can better simulate the TCM syndrome differentiation of the complex cases.

Long-Term Observation of Mixing States and Sources of Vanadium-Containing Single Particles from 2020 to 2021 in Guangzhou, China.

The distribution of vanadium (V) in aerosols is commonly used to track ship exhaust emissions, yet the atmospheric abundance of V has been greatly reduced due to the implementation of a clean fuel policy. Recent research mainly discussed the chemical compositions of ship-related particles during specific events, yet few studies focus on the long-term changes of V in the atmosphere. In this study, a single-particle aerosol mass spectrometer was used to measure V-containing particles from 2020 to 2021 in Huangpu Port in Guangzhou, China. The long-term trend of the particle counts of V-containing particles declined annually, but the relative abundance of V-containing particles in the total single particles increased in summer due to the influence of ship emissions. Positive matrix factorization revealed that in June and July 2020, 35.7% of the V-containing particles were from ship emissions, followed by dust and industrial emissions. Furthermore, more than 80% of the V-containing particles were found mixing with sulfate and 60% of the V-containing particles were found mixing with nitrate, suggesting that the majority of the V-containing particles were secondary particles processed during the transport of ship emissions to urban areas. Compared with the small changes in the relative abundance of sulfate in the V-containing particles, the relative abundance of nitrate exhibited clear seasonal variations, with a high abundance in winter. This may have been due to the increased production of nitrate from high concentrations of precursors and a suitable chemical environment. For the first time, the long-term trends of V-containing particles in two years are investigated to demonstrate changes in their mixing states and sources after the clean fuel policy, and to suggest the cautious application of V as an indicator of ship emissions.

Emission factors and source profiles of volatile organic compounds from typical industrial sources in Guangzhou, China.

Volatile organic compounds (VOCs) are important precursors of ozone (O3) and fine particulate matter (PM2.5). An accurate depiction of the emission characteristics of VOCs is the key to formulating VOC control strategies. In this study, the VOC emission factors and source profiles in five industrial sectors were developed using large-scale field measurements conducted in Guangzhou, China (100 samples for the emission factors and 434 samples for the source profile measurements). The emission factors based on the actual measurement method and the material balance method were 1.6-152.4 kg of VOCs per ton of raw materials (kg/t) and 3.1-242.2 kg/t, respectively. The similarities between the emission factors obtained using these two methods were examined, which showed a coefficient of divergence (CD) of 0.34-0.72. Among the 33 subdivided VOC source profiles developed in this study, sources including light guide plate (LGP), photoresist mask, and plastic products were the first time developed in China. Due to regional diversities in terms of production technologies, materials, and products, the emission characteristics of the VOCs varied, even in the same sector, thereby demonstrating the importance of developing localized source profiles of VOCs. The ozone formation potential (OFP) of the shipbuilding and repair sector from fugitive emissions was the highest value among all the industrial sectors. Controlling the emissions of aromatics and OVOCs was critical to reducing the O3 growth momentum in industrial sectors. In addition, 1,2-dibromoethane showed high carcinogenic risk potentials (CRPs) during most of the industrial sectors and should be prioritized for controlling.

Secondary aerosol formation in incense burning particles by O3 and OH oxidation via single particle mixing state analysis.

Incense burning is a common religious activity that emits abundant gaseous and particulate pollutants into the atmosphere. During their atmospheric lifetime, these gases and particles are subjected to oxidation, leading to the formation of secondary pollutants. We examined the oxidation of incense burning plumes under O3 exposure and dark condition using an oxidation flow reactor connected to a single particle aerosol mass spectrometer (SPAMS). Nitrate formation was observed in incense burning particles, mainly attributable to the ozonolysis of nitrogen-containing organic compounds. With UV on, nitrate formation was significantly enhanced, likely due to HNO3/HNO2/NOx uptake triggered by OH chemistry, which is more effective than ozone oxidation. The extent of nitrate formation is insensitive to O3 and OH exposure, possibly due to the diffusion limitation on interfacial uptake. The O3-UV-aged particles are more oxygenated and functionalized than O3-Dark-aged particles. Oxalate and malonate, two typical secondary organic aerosol (SOA) components, were found in O3-UV-aged particles. Our work reveals that nitrate, accompanied by SOA, can rapidly form in incense-burning particles upon photochemical oxidation in the atmosphere, which could deepen our understanding of air pollution caused by religious activities.

Molecular distribution and stable carbon isotopic composition of dicarboxylic acids, ketocarboxylic acids, and α-dicarbonyls in size-resolved atmospheric particles from Xi'an City, China.

Size-resolved airborne particles (9-stages) in urban Xi'an, China, during summer and winter were measured for molecular distributions and stable carbon isotopic compositions of dicarboxylic acids, ketocarboxylic acids, and α-dicarbonyls. To our best knowledge, we report for the first time the size-resolved differences in stable carbon isotopic compositions of diacids and related compounds in continental organic aerosols. High ambient concentrations of terephthalic (tPh, 379 ± 200 ng m(-3)) and glyoxylic acids (ωC(2), 235 ± 134 ng m(-3)) in Xi'an aerosols during winter compared to those in other Chinese cities suggest significant emissions from plastic waste burning and coal combustions. Most of the target compounds are enriched in the fine mode (<2.1 µm) in both seasons peaking at 0.7-2.1 µm. However, summertime concentrations of malonic (C(3)), succinic (C(4)), azelaic (C(9)), phthalic (Ph), pyruvic (Pyr), 4-oxobutanoic (ωC(4)), and 9-oxononanoic (ωC(9)) acids, and glyoxal (Gly) in the coarse mode (>2.1 µm) are comparable to and even higher than those in the fine mode (<2.1 µm). Stable carbon isotopic compositions of the major organics are higher in winter than in summer, except oxalic acid (C(2)), ωC(4), and Ph. δ(13)C of C(2) showed a clear difference in sizes during summer, with higher values in fine mode (ranging from -22.8‰ to -21.9‰) and lower values in coarse mode (-27.1‰ to -23.6‰). The lower δ(13)C of C(2) in coarse particles indicate that coarse mode of the compound originates from evaporation from fine mode and subsequent condensation/adsorption onto pre-existing coarse particles. Positive linear correlations of C(2), sulfate and ωC(2) and their δ(13)C values suggest that ωC(2) is a key intermediate, which is formed in aqueous-phase via photooxidation of precursors (e.g., Gly and Pyr), followed by a further oxidation to produce C(2).

Decision-Making System for the Diagnosis of Syndrome Based on Traditional Chinese Medicine Knowledge Graph.

The clinical informatization of traditional Chinese medicine (TCM) focuses on serving users and assisting in diagnosis. The rules of clinical knowledge play an important role in improving the TCM informatization service. However, many rules are difficult to find because of the complexity of the data in the current TCM syndrome prediction. Therefore, we proposed an end-to-end model, called Decision-making System for the Diagnosis of Syndrome (DSDS), which is based on the knowledge graph (KG) of TCM. This paper introduces the link prediction for the diagnosis of syndrome by dismantling medical records into multiple symptoms. In addition, based on the symptoms and predicted syndromes, the most relevant syndrome could be determined by the scoring and voting method in this paper. The results show that the accuracy of DSDS is 80.6%.

Real-time chemical characterization of single ambient particles at a port city in Chinese domestic emission control area - Impacts of ship emissions on urban air quality.

The domestic emission control area (DECA) policy has been implemented in China since 2017. However, its impact on ship emissions and in turn urban air quality is still unclear. In this study, real-time single particle measurements were carried out at a site in urban Guangzhou, about 1 km downwind of Huangpu Port, the largest maritime transport hub in southern China, in the summer of 2020 using a single particle aerosol mass spectrometer (SPAMS). During the campaign, the hourly averaged number fraction of ship emitted particles, using vanadium as a chemical indicator, varied from 0 to 14% with an average of 2 ± 1%. Ship emitted single particles contain organic carbon (OC), elemental carbon (EC), metals, sulfate and nitrate. More than 95% of ship emitted particles were sulfate-containing particles and the relative peak areas (RPAs) of sulfate and vanadium in the hourly average mass spectra of ship emitted particles were highly correlated (R2 = 0.85), suggesting the potential contribution of ship emissions to sulfate production in coastal cities. The relative abundance of OC and EC-related components in ship emitted particles varied and it was likely attributed to the different blending fluids used in the production of low sulfur fuels. The results from this study provide evidence for evaluating the effectiveness of the current regulations and guidance for future policy-making regarding the low sulfur fuel quality regulation and multiple-component control strategies.

Insights into the different mixing states and formation processes of amine-containing single particles in Guangzhou, China.

The formation processes of particulate amines are closely related to their emission sources and secondary reactions, which can be revealed through the investigation of their real-time mixing states in individual particles. The mixing states of methylamine (MA)-, trimethylamine (TMA)-, and diethylamine (DEA)-containing particles were studied using a high-performance single particle aerosol mass spectrometer (HP-SPAMS) in Guangzhou, China, in January 2020. The sharp increase in TMA particles was found to be closely associated with the increase in the ambient relative humidity (RH), while the MA- and DEA-containing particles were not similarly influenced by the changes in the RH. The prominent enrichment of secondary oxygenated organics in DEA particles during the daytime was consistent with the active period of photochemistry, implying that the sharp decrease in DEA particles in the afternoon was likely due to photo-oxidation of the DEA. The number fraction (Nf) of DEA particles, the Nf of the nitrate in the DEA particles, and the abundance of nitrate increased as the NOx content all increased during the nighttime, suggesting that the formation of DEA·HNO3 salt was the dominant pathway of particulate DEA production. These results are consistent with our previous measurements in Nanjing, confirming the general and distinct mixing states of TMA and DEA particles. Positive matrix factorization analysis revealed that the total fraction of the more oxidized organics factor and the less oxidized organics factor were much higher in the DEA particles (26.9 %) than in the TMA particles (9 %), confirming the significant enrichment of oxygenated species in the DEA particles. The different mixing states of the amines revealed the unique response of each type of amine to the same atmospheric environment, and the prominent mixing states of the DEA with secondary oxygenated species suggest the potential role of DEA in tracing the evolution of organic aerosols.