Secondary Inorganic Components Research Articles

Differential Cytotoxicity and Inflammatory Responses to Particulate Matter Components in Airway Structural Cells.

Particulate matter (PM) is a major component of ambient air pollution. PM exposure is linked to numerous adverse health effects, including chronic lung diseases. Air quality guidelines designed to regulate levels of ambient PM are currently based on the mass concentration of different particle sizes, independent of their origin and chemical composition. The objective of this study was to assess the relative hazardous effects of carbonaceous particles (soot), ammonium nitrate, ammonium sulfate, and copper oxide (CuO), which are standard components of ambient air, reflecting contributions from primary combustion, secondary inorganic constituents, and non-exhaust emissions (NEE) from vehicular traffic. Human epithelial cells representing bronchial (BEAS-2B) and alveolar locations (H441 and A549) in the airways, human lung fibroblasts (HFL-1), and rat precision-cut lung slices (PCLS) were exposed in submerged cultures to different concentrations of particles for 5-72 h. Following exposure, cell viability, metabolic activity, reactive oxygen species (ROS) formation, and inflammatory responses were analyzed. CuO and, to a lesser extent, soot reduced cell viability in a dose-dependent manner, increased ROS formation, and induced inflammatory responses. Ammonium nitrate and ammonium sulfate did not elicit any significant cytotoxic responses but induced immunomodulatory alterations at very high concentrations. Our findings demonstrate that secondary inorganic components of PM have a lower hazard cytotoxicity compared with combustion-derived and indicative NEE components, and alveolar epithelial cells are more sensitive to PM exposure. This information should help to inform which sources of PM to target and feed into improved, targeted air quality guidelines.

Investigating trends and causes of simultaneous high pollution from PM2.5 and ozone in China, 2015–2023

The spatiotemporal variation characteristics of simultaneous high pollution (SHP) from surface fine particulate matter (PM2.5) and ozone (O3) were explored on the basis of hourly observation data in 1092 sites from 2015 to 2023 across China. Statistics show that the frequency and intensity of SHP days are highest in North China, followed by South China. Seasonally, SHP days occur more frequently in spring and autumn across China, accounting for 43% and 27% over nine years, respectively. The number of SHP days across national sites first decreased (by 48.63% from 2015 to 2021) but then increased (by 49.37% from 2021 to 2023). Gridded PM2.5 component data were analyzed to explore these variations. Despite reductions in anthropogenic emissions, the proportion of secondary inorganic components in PM2.5 increased by 4.51%, 3.6%, and 5.41% in Beijing-Tianjin-Hebei, FenWei Plain, and Yangtze River Delta on SHP days from 2015 to 2021. Concurrently, the detrended PM2.5 and O3 concentrations showed significant positive correlations in most regions. These phenomena may be related to high O3 concentrations and meteorological conditions. The weather analysis reveals that specific weather conditions contribute to the occurrence of SHP, with notable spatial variations: cyclonic low-pressure systems with high temperatures in northern China, anticyclonic high-pressure systems with high temperatures and low humidity in central China, and east winds in southern China. These conditions may promote secondary pollutant formation and hinder pollutant dispersion. In addition, the increase in primary PM2.5 on SHP days after 2021 underscores the importance of controlling anthropogenic emissions. Overall, a comprehensive approach is essential to tackle the SHP challenge.

Diagnosing drivers of PM2.5 simulation biases in China from meteorology, chemical composition, and emission sources using an efficient machine learning method

Abstract. Chemical transport models (CTMs) are widely used for air pollution modeling, which suffer from significant biases due to uncertainties in simplified parameterization, meteorological fields, and emission inventories. Accurate diagnosis of simulation biases is critical for the improvement of models, interpretation of results, and management of air quality, especially for the simulation of fine particulate matter (PM2.5). In this study, an efficient method with high speed and a low computational resource requirement based on the tree-based machine learning (ML) method, the light gradient boosting machine (LightGBM), was designed to diagnose CTM simulation biases. The drivers of the Community Multiscale Air Quality (CMAQ) model biases are compared to observations obtained by simulating PM2.5 concentrations from the perspectives of meteorology, chemical composition, and emission sources. The source-oriented CMAQ was used to diagnose the influences of different emission sources on PM2.5 biases. The model can capture the complex relationship between input variables and simulation bias well; meteorology, PM2.5 components, and source sectors can partially explain the simulation bias. The CMAQ model underestimates PM2.5 by −19.25 to −2.66 µg m−3 in 2019, especially in winter and spring and during high-PM2.5 events. Secondary organic components showed the largest contribution to the PM2.5 simulation bias for different regions and seasons (13.8 %–22.6 %) of all components. Relative humidity, cloud cover, and soil surface moisture were the main meteorological factors contributing to PM2.5 bias in the North China Plain, Pearl River Delta, and northwestern China, respectively. Primary and secondary inorganic components from residential sources showed the two largest contributions to this bias (12.05 % and 12.78 %), implying large uncertainties in this sector. The ML-based methods provide valuable complements to traditional-mechanism-based methods for model improvement, with high efficiency and low reliance on prior information.

Pollution characteristics and transformation mechanisms of secondary inorganic components during winter heavy pollution in Handan city in 2018–2020

The mechanism of secondary transformation of nitrate and sulfate under different relative humidity (RH), and different atmospheric oxidizing conditions is still controversial. This study focuses on the winter heavy pollution process in Handan city from 2018 to 2020, and the following results were obtained: The average concentration of PM2.5 showed a decreasing trend from year to year, but the SNA (SO42−, NO3− and NH4+) showed an increasing trend from year to year, and the concentration of nitrate exceeded that of sulfate. During the haze formation period from 2018 to 2020, a significant disparity was observed in NO2 and SO2 emissions, with NO2 emissions surpassing those of SO2. Mobile sources were found to contribute more emissions than fixed sources, particularly during the haze persistence period (HP). However, sulfate conversion outweighed nitrate conversion. HighRH and photochemical reactions induced by ozone favored the formation of nitrate and sulfate, which formated heavy haze. When 40% ≤ RH ≤ 70%, atmospheric oxidants (Ox = O3 + NO2) concentration was the highest, nitrogen oxidation ratio (NOR) and sulfur oxidation ratio (SOR) increased rapidly, and nitrate was mainly generated by photochemical reactions during daytime. When RH > 70% and the concentration of Ox was low, RH will weaken the photochemical intensity. Therefore, the liquid-phase oxidation reaction of N2O5 contributed significantly to atmospheric nitrate at night, and the liquid-phase oxidation reaction of sulfate was faster than the gas-phase one. Local emissions contributed significantly to particulate matter pollution during heavy pollution in 2018–2020, and the main sources were secondary conversion, coal combustion, biomass burning, and road dust.

Influence of atmospheric oxidation capacity on atmospheric particulate matters concentration in Lanzhou

The atmospheric oxidation capacity (AOC) reflects the removal rate of atmospheric pollutants, and this index is typically characterized by the oxidant concentration or total reaction rate. The AOC plays a crucial role in the formation of atmospheric particulate matters and serves as an important indicator for studying changes in the concentration. In this study, we analyse the characteristics of atmospheric oxidants in Lanzhou based on data in the year of 2020 and 2021 retrieved from the Atmospheric Comprehensive Observation Station in Lanzhou. Empirical equations are applied to estimate the impact of atmospheric oxidative properties secondary generation concentrations of atmospheric particulate matters with different particle sizes. The results indicate that the annual average values of Ox were 146 μg/m3 in 2020 and 139 μg/m3 in 2021. The AOC was the highest in summer and lowest in winter. The correlation coefficient between O3 and Ox was significantly higher than that between NO2 and Ox, suggesting that O3 exerted a greater impact on the AOC in Lanzhou. A low AOC (MDA8 O3 ≤ 100 μg/m3) promoted the oxidation process of VOCs and other precursors, leading to the generation of secondary aerosols and subsequent formation of secondary particles. There were negative correlations between Ox and atmospheric particulate matters, secondary inorganic components, sulfur oxidation ratio (SOR) and nitrogen oxidation ratio (NOR), indicating that excessively high levels of Ox could inhibit the conversion rate of SO2 and NO2 into their respective forms to a certain extent.

Characteristics and Generation Mechanism of Secondary Inorganic Ions in PM2.5 in Changsha-Zhuzhou-Xiangtan City Group

Secondary inorganic ions, the main components of atmospheric PM2.5, are a dominant contributor to haze formation. The detailed characteristics and main generation mechanism of secondary inorganic ions in PM2.5 are still unclear in the Changsha-Zhuzhou-Xiangtan City Group, which is suffering from severe haze pollution, particularly in the autumn and winter seasons. For our study, we collected PM2.5 samples in November 2020 and January 2021 from four urban sites in the Changsha-Zhuzhou-Xiangtan City Group. Secondary inorganic components such as SO42-, NO3-, and NH4+ in PM2.5 were quantified. The average values(μg·m-3) of ρ(SO42-), ρ(NO3-), and ρ(NH4+) in autumn and winter were(5.2±2.5) and(7.9±4.8),(4.1±2.2) and(7.2±4.2), and(17.1±10.5) and(7.8±5.2), respectively. During the heavy haze pollution events in winter, the sum of ρ(SO42-), ρ(NO3-), and ρ(NH4+)(SNA) contributed 72.7% to the growth of PM2.5 mass concentration, and ρ(NO3-) accounted for 41.2%. This result suggested that the generation of NO3- was the key factor leading to the formation of winter haze pollution. In the polluted stage, high aerosol water content(AWC) promoted the rapid secondary generation of SNA, whereas adverse meteorological conditions also led to the accumulation of pollutants. The values of sulfur oxidation rate(SOR) and nitrogen oxidation rate(NOR) were still high in the dissipation stage. It indicated that the PM2.5 concentration fell due to the reduction in primary emissions and favorable weather conditions in dissipation, instead of the weakening of secondary generation of SNA. Compared to that in autumn, the higher AWC concentration, pH value, and lower temperature in winter were the main factors for the higher ρ(NO3-)/ρ(PM2.5) and NOR values in the Changsha-Zhuzhou-Xiangtan City Group. At the same time, the heterogeneous reaction was the main generation pathway of NO3-, when the AWC concentration was high in winter. Affected by aerosol pH value and generation rate, the liquid-phase oxidation reactions of H2O2 and SO2 were the main generation pathways of SO42- in autumn and winter in the Changsha-Zhuzhou-Xiangtan City Group. Compared to that in autumn, the higher AWC was more conducive to forming SO42-, which led to higher SOR in winter.

Atmospheric Oxidation Capacity and Its Impact on the Secondary Inorganic Components of PM2.5 in Recent Years in Beijing: Enlightenment for PM2.5 Pollution Control in the Future

In recent years, the concentrations of PM2.5 in urban ambient air in China have been declining; however, the strong atmospheric oxidation capacity (AOC) represents challenges to the further reduction of PM2.5 concentration and the continuous improvement of ambient air quality in China in the future, since the overall AOC is still at a high level. For this paper, based on ground observation data recorded in Beijing from 2016 to 2019, the variation in AOC was characterized according to the concentration of odd oxygen (OX = O3 + NO2). The concentrations of the primary and secondary components of PM2.5 were analyzed using empirical formulas, the correlation between AOC and the concentrations of secondary PM2.5 and the secondary inorganic components (SO42−, NO3−, NH4+, and SNA) in Beijing were explored, the impact of atmospheric photochemical reaction activity on the generation of atmospheric secondary particles was evaluated, and the impact of atmospheric oxidation variations on PM2.5 concentrations and SNA in Beijing was investigated. The results revealed that OX concentrations reached their peak in 2016 and reached their lowest point in 2019. The OX concentrations followed a descending seasonal trend of summer, spring, autumn, and winter, along with a spatial descending trend from urban observation stations to suburban stations and background stations. The degree of photochemical activity and the magnitude of the AOC have a large influence on the production of atmospheric secondary particles. When the photochemical reaction was more active and the AOC was stronger, the mass concentrations of the secondary generated PM2.5 fraction were higher and accounted for a higher proportion of the total PM2.5 mass concentrations. In the PM2.5 fraction, SNA accounted for 50.7% to 94.4% of the total mass concentrations of water-soluble inorganic ions in the field observations. Higher concentrations of the atmospheric oxidant OX in ambient air corresponded to a higher sulfur oxidation ratio (SOR) and nitrogen oxidation ratio (NOR), suggesting that the increase in AOC could promote the increase of PM2.5 concentration. Based on a relationship analysis of SOR, NOR, and OX, it was inferred that the relationship between OX and SOR and the relationship between OX and NOR were both nonlinear. Therefore, when establishing PM2.5 control strategies in Beijing in the future, the impact of the AOC on PM2.5 generation should be fully considered, and favorable measures should be taken to properly regulate the AOC, which would be more effective when carrying out further control measures regarding PM2.5 pollution.

The impact of biomass burning emissions on aerosol concentrations and depositions in the northern South China Sea region

The impact of biomass burning (BB) emissions on concentrations and depositions of major aerosol components in the northern South China Sea (NSCS) region (105∼115°E and 15∼21°N) from December 2020 to April 2021 has been investigated using the WRF-chem model (weather research and forecasting model coupled with chemistry) in combination with aerosol composition measurement at a mountain site in the Hainan Island of China. Model comparisons with observations in Hainan demonstrated the effectiveness of WRF-chem in simulating aerosol components (PM2.5, black carbon (BC), organic matter (OM), sulfate, nitrate, and ammonium) in the NSCS region. The influences of BB emissions were significant on near-surface PM2.5, BC, and OM but nearly negligible on secondary inorganic components (i.e., sulfate, nitrate, and ammonium). The NSCS regional and period mean PM2.5, BC, and OM concentrations were 17.2 μg/m3, 0.65 μg/m3, and 6.7 μg/m3, in which 20%, 13%, and 35%, respectively, were from BB emissions. The mean PM2.5, BC, and OM deposition fluxes were 73.8 mg/m2/month, 2.9 mg/m2/month, and 29.3 mg/m2/month, respectively, and 22%, 15%, and 38% of these depositions were from BB emissions. Dry deposition dominated the removal of aerosols. For both aerosol concentrations and depositions, the influences of BB emissions exhibited evidently larger contributions in spring (March and April) than those in winter (December to February). Most of the BB emissions were from mainland Southeast Asia (MSEA), in terms of period mean, 79%, 72%, and 81% of the BB PM2.5, BB BC, and BB OM concentrations and 82%, 77%, and 83% of their depositions in the NSCS region were attributed to the MSEA region. The results of this study suggested that BB emissions have strong implications for air quality and biogeochemical cycle of the NSCS region.

Real-time, single-particle chemical composition, volatility and mixing state measurements of urban aerosol particles in southwest China

To investigate the volatility of atmospheric particulates and the evolution of other particulate properties (chemical composition, particle size distribution and mixing state) with temperature, a thermodenuder coupled with a single particle aerosol mass spectrometer was used to conduct continuous observations of atmospheric fine particles in Chengdu, southwest China. Because of their complex sources and secondary reaction processes, the average mass spectra of single particles contained a variety of chemical components (including organic, inorganic and metal species). When the temperature rose from room temperature to 280°C, the relative areas of volatile and semi-volatile components decreased, while the relative areas of less or non-volatile components increased. Most (> 80%) nitrate and sulfate existed in the form of NH4NO3 and (NH4)2SO4, and their volatilization temperatures were 50–100°C and 150–280°C, respectively. The contribution of biomass burning (BB) and vehicle emission (VE) particles increased significantly at 280°C, which emphasized the important role of regional biomass burning and local motor vehicle emissions to the core of particles. With the increase in temperature, the particle size of the particles coated with volatile or semi-volatile components was reduced, and their mixing with secondary inorganic components was significantly weakened. The formation of K-nitrate (KNO3) and K-sulfate (KSO4) particles was dominated by liquid-phase processes and photochemical reactions, respectively. Reducing KNO3 and BB particles is the key to improving visibility. These new results are helpful towards better understanding the initial sources, pollution formation mechanisms and climatic effects of fine particulate matter in this megacity in southwest China.

Dramatic changes in aerosol composition during the 2016–2020 heating seasons in Beijing–Tianjin–Hebei region and its surrounding areas: The role of primary pollutants and secondary aerosol formation

With the implementation of a series of air pollution mitigation strategies during the past decade, great air quality improvements have been observed in the BTH region. Despite of significant decreases in gaseous pollutants, such as SO2 and NO2, the enhancement of secondary aerosol formation was observed. NO3− has surpassed SO42− and OM to become the dominant PM2.5 component. We find that the reduction of POC mainly dominated the decreasing trend of OC. As for secondary inorganic components, the key processes or factors controlling the spatial-temporal variation characteristics were different. The areas with large SO42− concentrations corresponded well to those with high SO2 concentrations, while the synchronized NO3− better followed spatial patterns in O3 than NO2. From 2016 to 2020, the response of SO42− to SO2 was close to a linear function, while the reaction of NO3− to the decrease of NO2 displayed nonlinear behavior. Such different relationships indicated that SO42− was predominantly controlled by SO2, while NO3− was not only related to NO2 but also determined by the secondary conversion process. The ratios of SO42−, NO3−, NH4+, and OC to EC between 2016 and 2020 were generally higher than 1 in typical BTH cities, and the ratio of NO3− to EC was exceptionally high, with a range reaching up to 200 %. Besides, this ratio coincided well with the enhancement of Ox, indicating the potential role of Ox to secondary NO3− formation. The diurnal cycle of NO3−, O3, and NO2 concentration change rate indicated that the relative increase of O3 during nighttime may offset the effectiveness of NOX emission reduction. This study provided observational evidence of enhanced secondary NO3− formation with the rising trend of atmospheric oxidation and emphasized the importance of nighttime chemistry for NO3− formation in the BTH region.

Chemical characteristics and source apportionment of particulate matter (PM2.5) in Dammam, Saudi Arabia: Impact of dust storms

Atmospheric particulate matter (PM) is known to be harmful to human and environmental health, with factors including particle size and composition thought to be key drivers of toxicity. Understanding the composition and hence sources of PM is critical to distinguish between anthropogenic and natural impacts, and develop the most efficient air pollution mitigation policies. This distinction is particularly important in areas affected by dust storm activity from nearby arid regions, which may dominate long-term PM mass concentrations. In this work, 24-hour PM 2.5 samples were collected from two locations in Dammam city, Saudi Arabia during the winter and summer of 2018, and subjected to detailed analysis to assess the PM characteristics and sources. Offline chemical analysis of the samples utilied ICP/MS, ion chromatography and thermal decomposition for measurement of trace metals, ions and OC/EC concentrations, respectively. Positive Matrix Factorization (PMF) analyses were used to identify sources of PM 2.5 in Dammam. The mean PM 2.5 mass concentration in the summer was twice that in the winter at both locations, and crustal and secondary inorganic aerosol components dominated over other species in determining PM 2.5 mass concentrations at both seasons and locations. The PMF analysis identified six source factors, including crustal, nitrate-rich, sea salt, sulfate-rich, biomass burning and traffic sources. In addition, the impact of dust storms on PM 2.5 concentrations was analysed. Dust storms increased the 24-hour average concentration of PM 2.5 by three-fold, and that of crustal elements by five-fold while the impact of dust storms on components identified as anthropogenic in origin was limited. Overall, dust-storm activity accounted for 42% of PM 2.5 mass concentration; after accounting for this aspect, secondary inorganic components derived largely from primary pollutant emissions dominated the remaining PM 2.5 mass. • Comprehensive assessment of PM 2.5 composition and sources in Dammam, Saudi Arabia. • Average 24-hour PM 2.5 mass concentrations ranged from 54 to 121 ug/m 3 . • Dominant components found to be crustal elements, metals, organic and inorganic carbon. • Anthropogenic sources accounted for 40% of PM 2.5 mass, rising to 58% if dust storm periods were excluded. • These results highlight emissions control priorities to improve air quality in Saudi Arabia.

Evaluation of Extinction Effect of PM2.5 and Its Chemical Components during Heating Period in an Urban Area in Beijing–Tianjin–Hebei Region

PM2.5 pollution and visibility impairment has attracted wild public attention in urban China during the past decade. Field observation was carried out in Tianjin, China, during heating (HP) and non-heating periods (NHP). The IMPROVE (Interagency Monitoring of Protected Visual Environments) method was localized to better understand the quantitative impact of PM2.5 composition on extinction coefficient (Bext). Bext of organic mass (OM) was classified into that of primary organic aerosol (POA) and secondary organic aerosol (SOA). Bext of Rayleigh scattering was calculated based on observation data directly, instead of a fixed value in the original IMPROVE method. The mass extinction efficiency (MEE) of EC was also updated based on literature research. The estimation bias of reconstructed Bext was reduced from 4.8 Mm−1 to 0.8 Mm−1 with the localized algorithm. It was found that the secondary components contribute more than 40% of Bext, and ammonium sulfate (AS) and ammonium nitrate (AN) are the dominant components. The different formation pathway leads to significant difference in secondary inorganic components during HP and NHP. Based on the positive matrix factorization (PMF) model and localized IMPROVE method, secondary aerosols were identified as the main source contributing to both PM2.5 concentration (48.2%) and Bext (44.3%) during HP, followed by vehicular emission and coal combustion, biomass burning with municipal incinerators, fugitive dust, and steel processing.

Comparative Analysis of PM2.5 and O3 Source in Beijing Using a Chemical Transport Model

For many years, Beijing has suffered from severe air pollution. At present, fine particulate matter (PM2.5) pollution in the winter and ozone (O3) pollution in the summer constitute serious environmental problems. In this study, the combination of a comprehensive air quality model with particulate matter source apportionment technology (CAMx-PAST) and monitoring data was used for the high-spatial resolution source apportionment of secondary inorganic components (SNA: SO42−, NO3−, and NH4+) in PM2.5; their corresponding precursor gases (SO2, NO2, and NH3); and O3 in the winter and summer over Beijing. Emissions from residents, industry, traffic, agriculture, and power accounted for 54%, 25%, 14%, 5%, and 2% of PM2.5 in the winter, respectively. In the summer, the emissions from industry, traffic, residents, agriculture, and power accounted for 42%, 24%, 20%, 10%, and 4% of PM2.5, respectively. The monthly transport ratio of PM2.5 was 27% and 46% in the winter and summer, respectively. The regional transport of residential and industrial emissions accounted for the highest proportion of PM2.5. The regional transport of emissions had a significant effect on the SO42− and NO3− concentrations, whereas SO2 and NO2 pollution were mainly affected by local emissions, and NH4+ and NH3 were mainly attributed to agricultural emissions. Industrial and traffic sources were two major emission sectors that contributed to O3 pollution in Beijing. The monthly transport ratios of O3 were 31% and 65% in the winter and summer, respectively. The high-spatial resolution regional source apportionment results showed that emissions from Langfang, Baoding, and Tangshan had the greatest impact on Beijing’s air pollution. This work’s methods and results will provide scientific guidance to support the government in its decision-making processes to manage the PM2.5 and O3 pollution issues.

THE INFLUENCING FACTORS OF SO42- AND NO3- IN PM10 IN JINHUA, CHINA

Sulfate (SO42-) and nitrate (NO3-) are the main secondary inorganic components in atmospheric particulates. It is of great significance to understand the formation and evolution of air pollution in the process of air pollution. In this study, samples of PM10 were collected in Jinhua City in eastern China from December 2019 to January 2020 and from June 2020 to August 2020, and also analyzed the influence of different meteorological conditions and gaseous pollutants on the formation of SO42- and NO3- in PM10. The results show that high relative humidity has a significant effect on the increase of sulfur oxidation rate (SOR) in winter, indicating that the winter liquid phase reaction is more conducive to the formation of SO42-. SOR and nitrogen oxidation rate (NOR) decrease with increasing temperature in winter, and increase with increasing temperature in summer. The light intensity has an important promoting effect on both SOR and NOR, indicating that the photochemical reaction is beneficial to the formation of SO42- and NO3-. Both the gaseous precursors SO2 and NO2 have significant promoting effects on the formation of SO42- and NO3- in winter, and the promoting effect of O3 on NOR is higher than that on SOR, indicating that atmospheric oxidation capacity has a greater effect on the formation of NO3-, and the effect of CO on SOR is higher than that on NOR, and there is a negative correlation with SOR.

Atmospheric Age Distribution of Primary and Secondary Inorganic Aerosols in a Polluted Atmosphere.

The community multiscale air quality (CMAQ) model was modified to track the evolution of the atmospheric age (τ) distribution of primary particulate matter (PPM) and secondary inorganic aerosol components (nitrate, sulfate, and ammonium ion, NSA). The modified CMAQ gas and aerosol mechanisms represent the same species emitted at different times as an age-resolved mixture, using multiple age-tagged variables and a dynamic age-bin advancing scheme. The model was applied to study the spatial and temporal evolution of τ for PPM and NSA in January 2013 to understand the formation and regional transport of PM and the precursor gases during severe winter pollution episodes in China. The results showed that increases in PPM and NSA concentrations during high pollution periods in polluted urban areas were typically associated with increases in the mean atmospheric age (τ̅) due to the accumulation of local emissions and regional transport of aged pollutants. Some of the rapid sulfate growth events at the beginning of multiday air pollution episodes were driven by regional transport of aged particles. In heavily polluted cities, while most of the monthly average PPM had τ less than 10 h, more than half of the sulfate had τ greater than 20-30 h. Regional distributions showed that very aged sulfate particles with τ > 96 h accounted for a significant portion of the total sulfate and had a very broad spatial distribution. However, aged ammonium ions had very low concentrations. Aged nitrate also had lower concentrations and more limited spatial distributions than sulfate due to differences in the atmospheric lifetime between SO2 and NOx. The estimated NOx lifetime of approximately ∼24 h in China agrees with a satellite-based estimation of 21 h. Potential applications of the age distribution analysis include evaluating the impacts of meteorology on air quality and developing short-term emission control strategies.

Chemical Insights into Interfacial Effects in Inorganic Nanomaterials.

The interfaces between inorganic functional nanomaterials and their surface modifiers play important roles in determining their chemical and physical properties. In numerous situations, interfaces created by organic ligands or secondary inorganic components on inorganic nanomaterials induce significant effects to promote their performances. However, it still remains challenging to understand those interfacial effects at the molecular level. Herein, strategies via the design of model inorganic nanomaterials with well-defined and detectable interfaces to simplify the investigation of interfacial effects in inorganic nanomaterials are summarized. While atomically precise metal nanoclusters enable "seeing" how organic ligands are coordinated on metal surface to create nanoscale metal-organic interfaces, ultrathin low-dimensional nanomaterials modified with organic ligands make it possible to extract the metal-organic interface structure from the average signal to investigate how steric and electronic effects enhance catalysis. The molecular mechanisms of the interfacial effects in supported metal catalysts are disclosed by designing two unique structures of supported catalysts. The interfacial engineering approach will be further extended to optimize the performance and stability of perovskite solar cells. Finally, a perspective on the development of operando characterization techniques is provided to track the dynamic interfacial structures during catalysis.

Sources of particulate-matter air pollution and its oxidative potential in Europe

Particulate matter is a component of ambient air pollution that has been linked to millions of annual premature deaths globally1-3. Assessments of the chronic and acute effects of particulate matter on human health tend to be based on mass concentration, with particle size and composition also thought to play a part4. Oxidative potential has been suggested to be one of the many possible drivers of the acute health effects of particulate matter, but the link remains uncertain5-8. Studies investigating the particulate-matter components that manifest an oxidative activity have yielded conflicting results7. In consequence, there is still much to be learned about the sources of particulate matter that may control the oxidative potential concentration7. Here we use field observations and air-quality modelling to quantify the major primary and secondary sources of particulate matter and of oxidative potential in Europe. We find that secondary inorganic components, crustal material and secondary biogenic organic aerosols control the mass concentration of particulate matter. By contrast, oxidative potential concentration is associated mostly with anthropogenic sources, in particular with fine-mode secondary organic aerosols largely from residential biomass burning and coarse-mode metals from vehicular non-exhaust emissions. Our results suggest that mitigation strategies aimed at reducing the mass concentrations of particulate matter alone may not reduce theoxidative potential concentration. If theoxidative potential can be linked to major health impacts, it may be more effective to control specific sources of particulate matter rather than overall particulate mass.

Effect of Liquid Water Content of Particles and Acidity of Particulate Matter on the Formation of Secondary Inorganic Components in Xinjiang Petrochemical Industrial Area

Secondary species are dominant components of PM2.5 in Dushanzi, Xinjiang. It is crucial to investigate the conversion process of secondary components in the atmosphere for regional air pollution control. The water-soluble components were analyzed for samples collected from Dushanzi District of Xinjiang from September 2015 to July 2016. The results showed that the total water-soluble ions (TWSIs) showed a seasonal variation consistent with PM2.5, and the seasonal variation of the ions was in the order-winter (67.86 μg·m-3) > autumn (13.77 μg·m-3) > spring (10.09 μg·m-3) > summer (4.85 μg·m-3); secondary ions (NH4+, SO42-, and NO3-)-accounting for 98% of TWSIs in winter. The results of the aerosol thermodynamic model (E-AIM) that explores the particle liquid water and acidity in Dushanzi District showed that the particles in Dushanzi are acidic with an annual in-situ pH of 0.81, and the pH value of the winter samples was the highest (2.93). The seasonal variation of particles in water was of the order: winter (331.32 μg·m-3) > autumn (5.91 μg·m-3) > spring (5.46 μg·m-3) > summer (1.62 μg·m-3). The annual average nitrogen oxidation rate and sulfur oxidation rate were 0.13 and 0.47, respectively, indicating a secondary conversion of regional pollutants. Further analysis showed that the concentration of sulfate in the particle phase was significantly affected by liquid water content of particles and in-situ pH. The formation of nitrate was mainly caused by heterogeneous reactions under high water content of particle.

Wintertime aerosol properties in Beijing

Abstract. Severe wintertime haze events with exceedingly high levels of aerosols have occurred frequently in China in recent years, impacting human health, weather, and the climate. A better knowledge of the formation mechanism and aerosol properties during haze events is helpful for the development of effective mitigation policies. In this study, we present field measurements of aerosol properties at an urban site in Beijing during January and February 2015. A suite of aerosol instruments were deployed to measure a comprehensive set of aerosol chemical and physical properties. The evolution of haze events in winter, dependent on meteorological conditions, consistently involves new particle formation during the clean period and subsequently continuous growth from the nucleation mode particles to submicron particles over the course of multiple days. Particulate organic matter is primarily responsible for producing the nucleation mode particles, while secondary organic and inorganic components jointly contribute to the high aerosol mass observed during haze events. The average effective density and hygroscopic parameter (κ) of ambient particles are approximately 1.37 g cm−3 and 0.25 during the clean period and increase to 1.42 g cm−3 and 0.4 during the polluted period, indicating the formation of secondary inorganic species from the continuous growth of nucleation mode particles. Our results corroborate that the periodic cycles of severe haze formation in Beijing during winter are attributed to the efficient nucleation and secondary aerosol growth under high gaseous precursor concentrations and the stagnant air conditions, highlighting that reductions in emissions of aerosol precursor gases are critical for remedying secondary aerosol formation and thereby mitigating haze pollution.

Source apportionment and regional transport of anthropogenic secondary organic aerosol during winter pollution periods in the Yangtze River Delta, China

Since the concentrations of primary particles and secondary inorganic aerosol components have been reduced significantly due to stringent emission controls, quantifying the source contributions and regional transport of secondary organic aerosol (SOA) is critical to further improve air quality in eastern China. In this study, the Community Multiscale Air Quality (CMAQ) model coupled with the updated SAPRC-11 photochemical mechanism and a revised SOA module was applied to investigate the emission sector and regional contributions to SOA in winter 2015 (January 5–26, 2015) and 2016 (December 20, 2015–January 20, 2016) in the Yangtze River Delta (YRD). The model is generally capable of reproducing the observed SOA concentrations at the Qingpu Supersite in Shanghai. The observed and predicted SOA concentrations are 6.4 μg/m3 and 6.9 μg/m3 in winter 2015, and 5.7 μg/m3 and 9.6 μg/m3 in winter 2016. The mean fraction bias (MFB) of the hourly SOA predictions is 0.22 and 0.32, respectively. High SOA concentrations in the wintertime of YRD are mainly due to aromatic compounds and dicarbonyls (glyoxal and methylglyoxal), which, on average, account for 43% and 53% of total SOA, respectively. The average contributions of industrial, residential, and transportation sectors in the YRD region during the entire simulation periods are 61%, 22%, and 17%, respectively. At the Qingpu Supersite in Shanghai, the industrial sector contributes to as much as 65% of total SOA in the heavy pollution episode of 2016. The contributions from transportation and residential sectors are 16% and 17%, respectively, during the same episode. The industry emissions from the Jiangsu, Zhejiang, and Shanghai are major contributors to the SOA at the Qingpu supersite during the heavy-polluted episodes, accounting for 31%, 19%, and 14% of the total predicted SOA. This study represents the first detailed regional modeling study of source region contributions to SOA in the YRD region and the detailed analyses of SOA in two winters months complement the previous SOA source apportionment studies focusing on seasonal average contributions.