Seasonal variation and size distribution of aromatic acids in urban aerosols in Beijing, China.

Aromatic acids are an integral component of organic acids in the atmosphere, contributing to the formation of climate-altering brown carbon (BrC). To better understand the sources and formation processes of aromatic acids, we collected size-segregated particulate matter samples in urban Beijing from April 2017 to January 2018, which were analyzed using solvent-extraction followed by gas chromatography/mass spectrometry. Phthalic acid (o-PhA) had the greatest average annual concentration, followed by terephthalic acid (p-PhA), 4-hydroxybenzoic acid (4-OHBA), dehydroabietic acid (DA), syringic acid (SA), 3-hydroxybenzoic acid (3-OHBA), isophthalic acid (m-PhA), and vanillic acid (VA). We identified distinct seasonal variations in aromatic acids, with o-PhA peaking in summer due to photochemical activity, while p-PhA and 4-OHBA elevated in autumn and summer, respectively, influenced by open waste and biomass burning. Wintertime variations in all aromatic acids were driven by complex meteorology and increased anthropogenic emissions, including rural biomass burning for cooking and heating. Particle size distribution of aromatic acids was affected by seasonal agricultural activities and dust storms, multiple emission sources, and formation mechanisms. The o-PhA has predominantly bimodal distribution, with diverse sources and complex formation mechanisms including gas- and aqueous-phase chemistry. The applicability of o-PhA as a tracer for specific secondary organic aerosols has been questioned due to its potential primary sources. The 3-OHBA, 4-OHBA, VA, SA, and DA exhibited bimodal or trimodal patterns during haze and non-haze periods across different particle size ranges. The seasonal variation in VA/SA and VA/4-OHBA ratios demonstrated the complexity of biomass burning types, influenced by season, particle size, meteorological conditions, and combustion sources.

Can we reach consensus on the dominant sulfate formation pathway in China's haze?

Atmospheric sulfate aerosols contribute significantly to air pollution and climate change. Sulfate formation mechanisms during winter haze events in northern China have recently received considerable attention, with more than 10 studies published in high-impact journals. However, the conclusions from in-field measurements, laboratory studies, and numerical simulations are inconsistent and even contradictory. Here, we propose a physically based yet simple method to clarify the debate on the dominant sulfate formation pathway. Based on the hazes evolving in the synoptic scale, first, a characteristic sulfate formation rate is derived using the Eulerian mass conservation equation constrained by in situ observations. Then, this characteristic value is treated as a guideline to determine the dominant sulfate formation pathway with a 0D chemical box model. Our observation-derived results establish a linkage between studies from laboratory experiments and chemical transport model simulations. A convergent understanding could therefore be reached on sulfate formation mechanisms in China's wintertime haze. This method is universal and can be applied to various haze conditions and different secondary products.

Probing the capacity of a spatiotemporal deep learning model for short-term PM2.5 forecasts in a coastal urban area.

Accurate forecast of fine particulate matter (PM2.5) is crucial for city air pollution control, yet remains challenging due to the complex urban atmospheric chemical and physical processes. Recently deep learning has been routinely applied for better urban PM2.5 forecasts. However, their capacity to represent the spatiotemporal urban atmospheric processes remains underexplored, especially compared with traditional approaches such as chemistry-transport models (CTMs) and shallow statistical methods other than deep learning. Here we probe such urban-scale representation capacity of a spatiotemporal deep learning (STDL) model for 24-hour short-term PM2.5 forecasts at six urban stations in Rizhao, a coastal city in China. Compared with two operational CTMs and three statistical models, the STDL model shows its superiority with improvements in all five evaluation metrics, notably in root mean square error (RMSE) for forecasts at lead times within 12 h with reductions of 49.8 % and 47.8 % respectively. This demonstrates the STDL model's capacity to represent nonlinear small-scale phenomena such as street-level emissions and urban meteorology that are in general not well represented in either CTMs or shallow statistical models. This gain of small-scale representation in forecast performance decreases at increasing lead times, leading to similar RMSEs to the statistical methods (linear shallow representations) at about 12 h and to the CTMs (mesoscale representations) at 24 h. The STDL model performs especially well in winter, when complex urban physical and chemical processes dominate the frequent severe air pollution, and in moisture conditions fostering hygroscopic growth of particles. The DL-based PM2.5 forecasts align with observed trends under various humidity and wind conditions. Such investigation into the potential and limitations of deep learning representation for urban PM2.5 forecasting could hopefully inspire further fusion of distinct representations from CTMs and deep networks to break the conventional limits of short-term PM2.5 forecasts.

Evidence of Surface-Tension Lowering of Atmospheric Aerosols by Organics from Field Observations in an Urban Atmosphere: Relation to Particle Size and Chemical Composition.

Surface-active organics lower the aerosol surface tension (σs/a), leading to enhanced cloud condensation nuclei (CCN) activity and potentially exerting impacts on the climate. Quantification of σs/a is mainly limited to laboratory or modeling work for particles with selected sizes and known chemical compositions. Inferred values from ambient aerosol populations are deficient. In this study, we propose a new method to derive σs/a by combining field measurements made at an urban site in northern China with the κ-Köhler theory. The results present new evidence that organics remarkably lower the surface tension of aerosols in a polluted atmosphere. Particles sized around 40 nm have an averaged σs/a of 53.8 mN m-1, while particles sized up to 100 nm show σs/a values approaching that of pure water. The dependence curve of σs/a with the organic mass resembles the behavior of dicarboxylic acids, suggesting their critical role in reducing the surface tension. The study further reveals that neglecting the σs/a lowering effect would result in lowered ultrafine CCN (diameter <100 nm) concentrations by 6.8-42.1% at a typical range of supersaturations in clouds, demonstrating the significant impact of surface tension on the CCN concentrations of urban aerosols.

Rapid hydrolysis of NO2 at High Ionic Strengths of Deliquesced Aerosol Particles.

Nitrogen dioxide (NO2) hydrolysis in deliquesced aerosol particles forms nitrous acid and nitrate and thus impacts air quality, climate, and the nitrogen cycle. Traditionally, it is considered to proceed far too slowly in the atmosphere. However, the significance of this process is highly uncertain because kinetic studies have only been made in dilute aqueous solutions but not under high ionic strength conditions of the aerosol particles. Here, we use laboratory experiments, air quality models, and field measurements to examine the effect of the ionic strength on the reaction kinetics of NO2 hydrolysis. We find that high ionic strengths (I) enhance the reaction rate constants (kI) by more than an order of magnitude compared to that at infinite dilution (kI=0), yielding log10(kI/kI=0) = 0.04I or rate enhancement factor = 100.04I. A state-of-the-art air quality model shows that the enhanced NO2 hydrolysis reduces the negative bias in the simulated concentrations of nitrous acid by 28% on average when compared to field observations over the North China Plain. Rapid NO2 hydrolysis also enhances the levels of nitrous acid in other polluted regions such as North India and further promotes atmospheric oxidation capacity. This study highlights the need to evaluate various reaction kinetics of atmospheric aerosols with high ionic strengths.

Major source categories of PM2.5 oxidative potential in wintertime Beijing and surroundings based on online dithiothreitol-based field measurements.

Fine particulate matter (PM2.5) causes millions of premature deaths each year worldwide. Oxidative potential (OP) has been proposed as a better metric for aerosol health effects than PM2.5 mass concentration alone. In this study, we report for the first time online measurements of PM2.5 OP in wintertime Beijing and surroundings based on a dithiothreitol (DTT) assay. These measurements were combined with co-located PM chemical composition measurements to identify the main source categories of aerosol OP. In addition, we highlight the influence of two distinct pollution events on aerosol OP (spring festival celebrations including fireworks and a severe regional dust storm). Source apportionment coupled with multilinear regression revealed that primary PM and oxygenated organic aerosol (OOA) were both important sources of OP, accounting for 41 ± 12 % and 39 ± 10 % of the OPvDTT (OP normalized by the sampled air volume), respectively. The small remainder was attributed to fireworks and dust, mainly resulting from the two distinct pollution events. During the 3.5-day spring festival period, OPvDTT spiked to 4.9 nmol min-1 m-3 with slightly more contribution from OOA (42 ± 11 %) and less from primary PM (31 ± 15 %). During the dust storm, hourly-averaged PM2.5 peaked at a very high value of 548 µg m-3 due to the dominant presence of dust-laden particles (88 % of total PM2.5). In contrast, only mildly elevated OPvDTT values (up to 1.5 nmol min-1 m-3) were observed during this dust event. This observation indicates that variations in OPvDTT cannot be fully explained using PM2.5 alone; one must also consider the chemical composition of PM2.5 when studying aerosol health effects. Our study highlights the need for continued pollution control strategies to reduce primary PM emissions, and more in-depth investigations into the source origins of OOA, to minimize the health risks associated with PM exposure in Beijing.

Seasonal characterization of chemical and optical properties of water-soluble organic aerosol in Beijing.

Water-soluble organic aerosol (WSOA) plays a crucial role in altering radiative forcing and impacting human health. However, our understanding of the seasonal variations of WSOA in Chinese megacities after the three-year clean air action plan is limited. In this study, we analyzed PM2.5 filter samples collected over one year (2020-2021) in Beijing to characterize the seasonal changes in the chemical and optical properties of WSOA using an offline aerosol mass spectrometer along with spectroscopy techniques. The mean mass concentration of WSOA during the observation period was 8.84 ± 7.12 µg m-3, constituting approximately 64-67 % of OA. Our results indicate the contribution of secondary OA (SOA) increased by 13-28 % due to a substantial reduction in primary emissions after the clean air action plan. The composition of WSOA exhibited pronounced seasonal variations, with a predominant contribution from less oxidized SOA in summer (61 %) and primary OA originating from coal combustion and biomass burning during the heating season (34 %). The mass absorption efficiency of WSOA at 365 nm in winter was nearly twice that in summer, suggesting that WSOA from primary emissions possesses a stronger light-absorbing capability than SOA. On average, water-soluble brown carbon accounted for 33-48 % of total brown carbon absorption. Fluorescence analysis revealed humic-like substances as the most significant fluorescence component of WSOA, constituting 82 %. Furthermore, both absorption and fluorescence chromophores were associated with nitrogen-containing compounds, highlighting the role of nitrogen-containing species in influencing the optical properties of WSOA. The results are important for chemical transport models to accurately simulate the WSOA and its climate effects.

Short-Term Effects of Primary and Secondary Particulate Matter on Ceramide Metabolism, Pro-Inflammatory Response, and Blood Coagulation.

Evidence of the precise biological pathway responsible for acute cardiovascular events triggered by particulate matter (PM) exposure from anthropogenic emissions is sparse. We investigated the associations of biomarkers relevant to the pathophysiology of atherothrombosis (ceramide metabolism, pro-inflammatory response, and blood coagulation) with primary and secondary components in particulate matter with aerodynamic diameters less than 2.5 µm (PM2.5). A total of 152 healthy participants were followed with four repeated clinical visits between September 2019 and January 2020 in Beijing. Exposure to ambient inorganic aerosols (sulfate, nitrate, ammonium, and chloride), as well as organic aerosols (OA) in PM2.5, was measured by a real-time aerosol chemical speciation monitor, and sources of OA were performed by positive matrix factorization. We found significant increases of 101.9-397.9% in ceramide indicators associated with interquartile-range increases in inorganic aerosols and OA prior to 72 h of exposure. Higher levels of organic and inorganic aerosols in PM2.5 were associated with increases of 3.1-6.0% in normal T cells regulated upon activation and expressed and secreted relevant to the pro-inflammatory response; increases of 276.9-541.5% were observed in D-dimers relevant to coagulation. Detrimental effects were further observed following OA exposure from fossil fuel combustion. Mediation analyses indicated that ceramide metabolism could mediate the associations of PM2.5 components with pro-inflammatory responses. Our findings expand upon the current understanding of potential pathophysiological pathways of cardiovascular events posed by ambient particulates and highlight the importance of reducing primary and secondary PM from anthropogenic combustions.

Trimethylamine from Subtropical Forests Rival Total Farmland Emissions in China.

Many types of living plants release gaseous trimethylamine (TMA), making it a potentially important contributor to new particle formation (NPF) in remote areas. However, a panoramic view of the importance of forest biogenic TMA at the regional scale is lacking. Here, we pioneered nationwide mobile measurements of TMA across a transect of contiguous farmland in eastern China and a transect of subtropical forests in southern China. In contrast to the farmland route, TMA concentrations measured during the subtropical forest route correlated significantly with isoprene, suggesting potential TMA emissions from leaves. Our high time-resolved concentrations obtained from a weak photo-oxidizing atmosphere reflected freshly emitted TMA, indicating the highest emission intensity from irrigated dryland (set as the baseline of 10), followed by paddy field (7.1), subtropical evergreen forests (5.9), and subtropical broadleaf and mixed forests (4.3). Extrapolating their proportions roughly to China, subtropical forests alone, which constitute half of the total forest area, account for nearly 70% of the TMA emissions from the nation's total farmland. Our estimates, despite the uncertainties, take the first step toward large-scale assessment of forest biogenic amines, highlighting the need for observational and modeling studies to consider this hitherto overlooked source of TMA.

Characteristics of sub-micron aerosols above the urban canopy in Beijing during warm seasons.

To understand the characteristics of atmospheric pollution above the urban canopy in warm seasons, the characteristics of sub-micron aerosol (PM1) was studied based on high-altitude observations at the Beijing 325 m meteorological tower. The PM1 at 260 m was 34, 29 and 21 µg m-3 in May 2015, June 2015, and June 2017, respectively, indicating a reduction in PM1 pollution above the urban canopy. Meanwhile, an overall decrease was also observed in the concentrations of all PM1 chemical species (excluding Chl and BC) and organic aerosol (OA) factors. Previous instances of heavy haze in Beijing often coincided with high humidity and stagnant weather conditions. However, the heightened pollution episodes in June 2017 were accompanied by high wind speeds and low relative humidity. Compared to May 2015, the contribution of secondary components to PM1 in June 2017 was more prominent, with the total proportion of SNA (sulfate, nitrate, and ammonium) and more-oxidized oxygenated OA (MO-OOA) to PM1 increased by approximately 10 %. Secondary species of NH4NO3, (NH4)2SO4, and MO-OOA, as well as black carbon, collectively contributed the vast majority of aerosol extinction coefficient (bext), with the four species contributing a total of ≥96 % to bext at 260 m. Hydrocarbon-like OA, cooking OA, and less-oxidized oxygenated OA have undergone significant reductions, so continued emphasis on controlling local sources to reduce these three aerosol species and addressing regional sources to further mitigate overall aerosol species is imperative. In lower pollution situation, the diurnal variation of PM was smoother, and its pollution sources were more regionally uniform, which might be attributed to the reduced diversity and complexity in the physical and chemical processes in air pollution.

Characterization of organic vapors by a Vocus proton-transfer-reaction mass spectrometry at a mountain site in southeastern China.

Biogenic and anthropogenic organic vapors are crucial precursors of ozone and secondary organic aerosol (SOA) in the atmosphere. Here we conducted real-time measurements of gaseous organic compounds using a Vocus proton-transfer-reaction mass spectrometer (Vocus PTR-MS) at the Shanghuang mountain site (1128 m a.s.l.) in southeastern China during November 2022. Our results revealed a substantial impact of mixed biogenic and anthropogenic compounds at the mountain site, with oxygenated volatile organic compounds (OVOCs) comprising 74 % of the organic vapors. Two distinct periods, characterized by sunny days (P1) and persistent cloud events (P2), were observed. P1 exhibited higher concentrations of biogenic-related emissions compared to P2. For instance, isoprene, monoterpenes, and sesquiterpenes during P1 were 2.4-2.9 times higher than those during P2. OVOCs such as acetaldehyde, MVK + MACR, acetone, and MEK also showed higher concentrations during P1, indicating a dominant source from the photochemical oxidation of biogenic VOCs. Anthropogenic-related VOCs like benzene and toluene had higher concentrations during P2, displaying different diurnal cycles compared to P1. Our analysis identified four biogenic-related factors dominated by isoprene and sesquiterpene oxidation products, and two anthropogenic-related factors. During P1, biogenic sources contributed approximately 80 % to total organic compounds, while during P2, anthropogenic sources, particularly the aromatic-related factor, increased from 16 % to 35 %. Furthermore, a unique factor characterized by C2 amines and C3 amides and periodic plumes indicated the influence of industrial emissions from regional transport. The study highlights the significant variations in sources and compositions of gaseous organic compounds at regional mountain sites due to changes in meteorology and photochemical processing, potentially impacting regional ozone and SOA formation.

Dominant contribution of combustion-related ammonium during haze pollution in Beijing.

Aerosol ammonium (NH4+), mainly produced from the reactions of ammonia (NH3) with acids in the atmosphere, has significant impacts on air pollution, radiative forcing, and human health. Understanding the source and formation mechanism of NH4+ can provide scientific insights into air quality improvements. However, the sources of NH3 in urban areas are not well understood, and few studies focus on NH3/NH4+ at different heights within the atmospheric boundary layer, which hinders a comprehensive understanding of aerosol NH4+. In this study, we perform both field observation and modeling studies (the Community Multiscale Air Quality, CMAQ) to investigate regional NH3 emission sources and vertically resolved NH4+ formation mechanisms during the winter in Beijing. Both stable nitrogen isotope analyses and CMAQ model suggest that combustion-related NH3 emissions, including fossil fuel sources, NH3 slip, and biomass burning, are important sources of aerosol NH4+ with more than 60% contribution occurring on heavily polluted days. In contrast, volatilization-related NH3 sources (livestock breeding, N-fertilizer application, and human waste) are dominant on clean days. Combustion-related NH3 is mostly local from Beijing, and biomass burning is likely an important NH3 source (∼15%-20%) that was previously overlooked. More effective control strategies such as the two-product (e.g., reducing both SO2 and NH3) control policy should be considered to improve air quality.

Development of an automatic measurement system using atmospheric pressure photoionization ultrahigh-resolution mass spectrometry and application for on-line analysis of particulate matter.

On-line chemical characterization of atmospheric particulate matter (PM) with soft ionization technique and ultrahigh-resolution Mass Spectrometry (UHRMS) provides molecular information of organic constituents in real time. Here we describe the development and application of an automatic measurement system that incorporates PM2.5 sampling, thermal desorption, atmospheric pressure photoionization, and UHRMS analysis. Molecular formulas of detected organic compounds were deducted from the accurate (±10 ppm) molecular weights obtained at a mass resolution of 100,000, allowing the identification of small organic compounds in PM2.5. Detection efficiencies of 28 standard compounds were determined and we found a high sensitivity and selectivity towards organic amines with limits of detection below 10 pg. As a proof of principle, PM2.5 samples collected off-line in winter in the urban area of Beijing were analyzed using the Ionization Module and HRMS of the system. The automatic system was then applied to conduct on-line measurements during the summer time at a time resolution of 2 hr. The detected organic compounds comprised mainly CHON and CHN compounds below 350 m/z. Pronounced seasonal variations in elemental composition were observed with shorter carbon backbones and higher O/C ratios in summer than that in winter. This result is consistent with stronger photochemical reactions and thus a higher oxidation state of organics in summer. Diurnal variation in signal intensity of each formula provides crucial information to reveal its source and formation pathway. In summary, the automatic measurement system serves as an important tool for the on-line characterization and identification of organic species in PM2.5.

Development and evaluation of an online monitoring single-particle optical particle counter with polarization detection.

We developed a single-particle optical particle counter with polarization detection (SOPC) for the real-time measurement of the optical size and depolarization ratio (defined as the ratio of the vertical component to the parallel component of backward scattering) of atmospheric particles, the polarization ratio (DR) value can reflect the irregularity of the particles. The SOPC can detect aerosol particles with size larger than 500 nm and the maximum particle count rate reaches ∼1.8 × 105 particles per liter. The SOPC uses a modulated polarization laser to measure the optical size of particles according to forward scattering signal and the DR value of the particles by backward S and P signal components. The sampling rate of the SOPC was 106 #/(sec·channel), and all the raw data were processed online. The calibration curve was obtained by polystyrene latex spheres with sizes of 0.5-10 µm, and the average relative deviation of measurement was 3.96% for sub 3 µm particles. T-matrix method calculations showed that the DR value of backscatter light at 120° could describe the variations in the aspect ratio of particles in the above size range. We performed insitu observations for the evaluation of the SOPC, the mass concentration constructed by the SOPC showed good agreement with the PM2.5 measurements in a nearby state-controlled monitoring site. This instrument could provide useful data for source appointment and regulations against air pollution.

Changes in wintertime visibility across China over 2013-2019 and the drivers: A comprehensive assessment using machine learning method.

Effective emission reduction measures have largely lowered the particulate concentration in China, but low-visibility events still occur frequently, greatly affecting people's daily life, travel, and health. In the context of carbon neutrality strategy and climate change, the mechanisms governing visibility changes may be undergoing a transformation. To address this critical issue, we have undertaken a comprehensive assessment by employing a novel approach that combines site observations, model-derived datasets, and machine learning techniques. Our analysis of the dataset shows varying degrees of improvement in wintertime visibility in regions such as North China, South China, and the Fenwei Plain over 2013-2019, but an unexpected deterioration (approximately 1 km yr-1) in central and southern China (CSC). We further elucidate key roles of PM2.5 reduction in these regions with visibility improvement; whereas the unsatisfactory visibility trend in CSC was caused by combined effect of relative humidity (RH) increase (47 %), aerosol hygroscopicity (κ) enhancement (9 %), and boundary layer (BLH) reduction (8 %), which greatly overwhelms the effect of PM2.5 reduction recently. Moreover, the study reveals a growing influence of RH on the wintertime visibility, reaching 40 % ± 24 % to the total contribution in 2019, while that of PM2.5 declined to 18 % ± 19 % and is expected to further diminish with emission reduction. Note those often-neglected factors-temperature, wind speed, BLH, and κ, account for over 40 % of the total contribution. Though the importance of aerosol hygroscopic growth to visibility was found decreasing recently, it retains non-negligible impacts on driving inter-annual visibility trends. This study yields innovative insights for air pollution control, underscoring the imperative of region-specific strategies to mitigate low-visibility events.

Model Simulations and Predictions of Hydroxymethanesulfonate (HMS) in the Beijing-Tianjin-Hebei Region, China: Roles of Aqueous Aerosols and Atmospheric Acidity.

Hydroxymethanesulfonate (HMS) has been found to be an abundant organosulfur aerosol compound in the Beijing-Tianjin-Hebei (BTH) region with a measured maximum daily mean concentration of up to 10 µg per cubic meter in winter. However, the production medium of HMS in aerosols is controversial, and it is unknown whether chemical transport models are able to capture the variations of HMS during individual haze events. In this work, we modify the parametrization of HMS chemistry in the nested-grid GEOS-Chem chemical transport model, whose simulations provide a good account of the field measurements during winter haze episodes. We find the contribution of the aqueous aerosol pathway to total HMS is about 36% in winter in Beijing, due primarily to the enhancement effect of the ionic strength on the rate constants of the reaction between dissolved formaldehyde and sulfite. Our simulations suggest that the HMS-to-inorganic sulfate ratio will increase from the baseline of 7% to 13% in the near future, given the ambitious clean air and climate mitigation policies for the BTH region. The more rapid reductions in emissions of SO2 and NOx compared to NH3 alter the atmospheric acidity, which is a critical factor leading to the rising importance of HMS in particulate sulfur species.

Severe photochemical pollution formation associated with strong HONO emissions from dew and guttation evaporation.

The unknown daytime source of HONO has been extensively investigated due to unexplained atmospheric oxidation capacity and current modelling bias, especially during cold seasons. In this study, abrupt morning increases in atmospheric HONO at a rural site in the North China Plain (NCP) were observed almost on daily basis, which were closely linked to simultaneous rises in atmospheric water vapor content and NH3 concentrations. Dew and guttation water formation was frequently observed on wheat leaves, from which water samples were taken and chemically analyzed for the first time. Results confirmed that such natural processes likely governed the daily nighttime deposition and daytime release of HONO and NH3, which have not been considered in the numerous HONO budget studies investigating its large missing daytime source in the NCP. The dissolved HONO and NH3 in leaf surface water droplets reached 1.4 and 23 mg L-1 during the morning on average, resulting in averaged atmospheric HONO and NH3 increases of 0.89 ± 0.61 and 43.7 ± 29.3 ppb during morning hours, with relative increases of 186 ± 212 % and 233 ± 252 %, respectively. The high atmospheric oxidation capacity contained within HONO was stored in near surface liquid water (such as dew, guttation and soil surface water) during nighttime, which prevented its atmospheric dispersion after sunset and protected it from photodissociation during early morning hours. HONO was released in a blast during later hours with stronger solar radiation, which triggered and then accelerated daytime photochemistry through the rapid photolysis of HONO and subsequent OH production, especially under high RH conditions, forming severe secondary gaseous and particulate pollution. Results of this study demonstrate that global ecosystems might play significant roles in atmospheric photochemistry through nighttime dew formation and guttation processes.

Significant Reductions in Secondary Aerosols after the Three-Year Action Plan in Beijing Summer.

Air quality in China has continuously improved during the Three-Year Action Plan (2018-2020); however, the changes in aerosol composition, properties, and sources in Beijing summer remain poorly understood. Here, we conducted real-time measurements of aerosol composition in five summers from 2018 to 2022 along with WRF-Community Multiscale Air Quality simulations to characterize the changes in aerosol chemistry and the roles of meteorology and emission reductions. Largely different from winter, secondary inorganic aerosol and photochemical-related secondary organic aerosol (SOA) showed significant decreases by 55-67% in summer, and the most decreases occurred in 2021. Comparatively, the decreases in the primary aerosol species and gaseous precursors were comparably small. While decreased atmospheric oxidation capacity as indicated by ozone changes played an important role in changing SOA composition, the large decrease in aerosol liquid water and small increase in particle acidity were critical for nitrate changes by decreasing gas-particle partitioning substantially (∼28%). Analysis of meteorological influences demonstrated clear and similar transitions in aerosol composition and formation mechanisms at a relative humidity of 50-60% in five summers. Model simulations revealed that emission controls played the decisive role in reducing sulfate, primary OA, and anthropogenic SOA during the Three-Year Action Plan, while meteorology affected more nitrate and biogenic SOA.

Revisiting the dynamics of gaseous ammonia and ammonium aerosols during the COVID-19 lockdown in urban Beijing using machine learning models.

The concentration of atmospheric ammonia (NH3) in urban Beijing substantially decreased during the COVID-19 lockdown (24 January to 3 March 2020), likely due to the reduced human activities. However, quantifying the impact of anthropogenic interventions on NH3 dynamics is challenging, as both meteorology and chemistry mask the real changes in observed NH3 concentrations. Here, we applied machine learning techniques based on random forest models to decouple the impacts of meteorology and emission changes on the gaseous NH3 and ammonium aerosol (NH4+) concentrations in Beijing during the lockdown. Our results showed that the meteorological conditions were unfavorable during the lockdown and tended to cause an increase of 8.4 % in the NH3 concentration. In addition, significant reductions in NOx and SO2 emissions could also elevate NH3 concentrations by favoring NH3 gas-phase partitioning. However, the observed NH3 concentration significantly decreased by 35.9 % during the lockdown, indicating a significant reduction in emissions or enhanced chemical sinks. Rapid gas-to-particle conversion was indeed found during the lockdown. Thus, the observed reduced NH3 concentrations could be partially explained by the enhanced transformation into NH4+. Therefore, the sum of NH3 and NH4+ (collectively, NHx) is a more reliable tracer than NH3 or NH4+ alone to estimate the changes in NH3 emissions. Compared to that under the scenario without lockdowns, the NHx concentration decreased by 26.4 %. We considered that this decrease represents the real decrease in NH3 emissions in Beijing due to the lockdown measures, which was less of a decrease than that based on NH3 only (35.9 %). This study highlights the importance of considering chemical sinks in the atmosphere when applying machine learning techniques to link the concentrations of reactive species with their emissions.

Recent Progress in Atmospheric Chemistry Research in China: Establishing a Theoretical Framework for the "Air Pollution Complex".

Atmospheric chemistry research has been growing rapidly in China in the last 25 years since the concept of the "air pollution complex" was first proposed by Professor Xiaoyan TANG in 1997. For papers published in 2021 on air pollution (only papers included in the Web of Science Core Collection database were considered), more than 24 000 papers were authored or co-authored by scientists working in China. In this paper, we review a limited number of representative and significant studies on atmospheric chemistry in China in the last few years, including studies on (1) sources and emission inventories, (2) atmospheric chemical processes, (3) interactions of air pollution with meteorology, weather and climate, (4) interactions between the biosphere and atmosphere, and (5) data assimilation. The intention was not to provide a complete review of all progress made in the last few years, but rather to serve as a starting point for learning more about atmospheric chemistry research in China. The advances reviewed in this paper have enabled a theoretical framework for the air pollution complex to be established, provided robust scientific support to highly successful air pollution control policies in China, and created great opportunities in education, training, and career development for many graduate students and young scientists. This paper further highlights that developing and low-income countries that are heavily affected by air pollution can benefit from these research advances, whilst at the same time acknowledging that many challenges and opportunities still remain in atmospheric chemistry research in China, to hopefully be addressed over the next few decades.