Nitrate dominates the chemical composition of PM2.5 during haze event in Beijing, China

Changes in source contributions to the oxidative potential of PM2.5 in urban Xiamen, China

The toxicity of PM2.5 does not necessarily change synchronously with its mass concentration. In this study, the chemical composition (carbonaceous species, water-soluble ions, and metals) and oxidative potential (dithiothreitol assay, DTT) of PM2.5 were investigated in 2017/2018 and 2022 in Xiamen, China. The decrease rate of volume-normalized DTT (DTTv) (38%) was lower than that of PM2.5 (55%) between the two sampling periods. However, the mass-normalized DTT (DTTm) increased by 44%. Clear seasonal patterns with higher levels in winter were found for PM2.5, most chemical constituents and DTTv but not for DTTm. The large decrease in DTT activity (84%-92%) after the addition of EDTA suggested that water-soluble metals were the main contributors to DTT in Xiamen. The increased gap between the reconstructed and measured DTTv and the stronger correlations between the reconstructed/measured DTT ratio and carbonaceous species in 2022 were observed. The decrease rates of the hazard index (32.5%) and lifetime cancer risk (9.1%) differed from those of PM2.5 and DTTv due to their different main contributors. The PMF-MLR model showed that the contributions (nmol/(min·m3)) of vehicle emission, coal + biomass burning, ship emission and secondary aerosol to DTTv in 2022 decreased by 63.0%, 65.2%, 66.5%, and 22.2%, respectively, compared to those in 2017/2018, which was consistent with the emission reduction of vehicle exhaust and coal consumption, the adoption of low-sulfur fuel oil used on board ships and the reduced production of WSOC. However, the contributions of dust + sea salt and industrial emission increased.

Role of gas-particle conversion of ammonia in haze pollution under ammonia-rich environment in Northern China and prospects of effective emission reduction

As an important precursor of secondary inorganic aerosols (SIAs), ammonia (NH3) plays a key role in fine particulate matter (PM2.5) formation. In order to investigate its impacts on haze formation in the North China Plain (NCP) during winter, NH3 concentrations were observed at a high-temporal resolution of 1 min by using the SP-DOAS in Tai'an from December 2021 to February 2022. During the observation period, the average NH3 concentration was 11.84 ± 5.9 ppbv, and it was determined as an ammonia-rich environment during different air quality conditions. Furthermore, the average concentrations of sulfate (SO42-), nitrate (NO3-) and ammonium (NH4+) were 9.54 ± 5.97 μg/m3, 19.09 ± 14.18 μg/m3 and 10.72 ± 6.53 μg/m3, respectively. Under the nitrate-dominated atmospheric environment, aerosol liquid water content (ALWC) was crucial for NH3 particle transformation during haze aggravation, and the gas-particle partitioning of ammonia played an important role in the SIAs formation. The reconstruction of the molecular composition further indicated that ammonium nitrate (NH4NO3) plays a dominant role in the increase of PM2.5 during haze events. Consequently, future efforts to mitigate fine particulate pollution in this region should focus on controlling NH4NO3 levels. In ammonia-rich environments, NO3- formation is more dependent on the concentration of nitric acid (HNO3). The sensitive analysis of TNO3 (HNO3 + NO3-) and NHX (NH3 + NH4+) reduction using the thermodynamic model suggested that the NO3- concentration decreases linearly with the reduction of TNO3. And the concentration of NO3- decreases rapidly only when NHX is reduced by 50-60 %. Reducing NOX emissions is the most effective way to alleviate nitrate pollution in this region.

Understanding secondary particles in a regional site of Yangtze River Delta: Insights from mass spectrometric measurement

Submicron particulate matter (PM1) poses significant risks to health risks and global climate. In this study, secondary organic aerosols (SOA) and inorganic compositions were examined for their physicochemical characteristics and evolution using high-resolution aerosol instruments in Changzhou over one-month period. The results showed that transport accompanied by regional static conditions leaded to the occurrence of heavy pollution. In addition, regional generation and local emissions also leaded to the occurrence of light and moderate pollution during the observation period in Changzhou. Organic aerosols (OA) and nitrate (NO3-) accounted for 45 % and 23 % of PM1, respectively. The increase in PM1 was dominated by the contribution of NO3- and OA. SOA was dominance in OA (63 % with 40 % MO-OOA), which was higher than primary organic aerosols (POA). Besides, photochemical reactions and the high oxidizing nature of the urban atmosphere promoted the production of OA, especially MO-OOA in Changzhou. Our results highlight that secondary particles contribute significantly to PM pollution in Changzhou, underlining the importance of controlling emissions of gaseous precursors, especially under high oxidation conditions.

Identifying Driving Factors of Atmospheric N2O5 with Machine Learning

Dinitrogen pentoxide (N2O5) plays an essential role in tropospheric chemistry, serving as a nocturnal reservoir of reactive nitrogen and significantly promoting nitrate formations. However, identifying key environmental drivers of N2O5 formation remains challenging using traditional statistical methods, impeding effective emission control measures to mitigate NOx-induced air pollution. Here, we adopted machine learning assisted by steady-state analysis to elucidate the driving factors of N2O5 before and during the 2022 Winter Olympics (WO) in Beijing. Higher N2O5 concentrations were observed during the WO period compared to the Pre-Winter-Olympics (Pre-WO) period. The machine learning model accurately reproduced ambient N2O5 concentrations and showed that ozone (O3), nitrogen dioxide (NO2), and relative humidity (RH) were the most important driving factors of N2O5. Compared to the Pre-WO period, the variation in trace gases (i.e., NO2 and O3) along with the reduced N2O5 uptake coefficient was the main reason for higher N2O5 levels during the WO period. By predicting N2O5 under various control scenarios of NOx and calculating the nitrate formation potential from N2O5 uptake, we found that the progressive reduction of nitrogen oxides initially increases the nitrate formation potential before further decreasing it. The threshold of NOx was approximately 13 ppbv, below which NOx reduction effectively reduced the level of night-time nitrate formations. These results demonstrate the capacity of machine learning to provide insights into understanding atmospheric nitrogen chemistry and highlight the necessity of more stringent emission control of NOx to mitigate haze pollution.

Insights into anthropogenic impact on atmospheric inorganic aerosols in the largest city of the Tibetan Plateau through multidimensional isotope analysis

Particulate inorganic nitrogen aerosols (PIN) significantly influence air pollution and pose health risks worldwide. Despite extensive observations on ammonium (pNH4+) and nitrate (pNO3-) aerosols in various regions, their key sources and mechanisms in the Tibetan Plateau remain poorly understood. To bridge this gap, this study conducted a sampling campaign in Lhasa, the Tibetan Plateau's largest city, with a focus on analyzing the multiple isotopic signatures (δ15N, ∆17O). These isotopes were integrated into a Bayesian mixing model to quantify the source contributions and oxidation pathways for pNH4+ and pNO3-. Our results showed that traffic was the largest contributor to pNH4+ (31.8 %), followed by livestock (25.4 %), waste (21.8 %), and fertilizer (21.0 %), underscoring the impact of vehicular emissions on urban NH3 levels in Lhasa. For pNO3-, coal combustion emerged as the largest contributor (27.3 %), succeeded by biomass burning (26.3 %), traffic emission (25.3 %), and soil emission (21.1 %). In addition, the ∆17O-based model indicated a dominant role of NO2 + OH (52.9 %) in pNO3- production in Lhasa, which was similar to previous observations. However, it should be noted that the NO3 + volatile organic component (VOC) contributed up to 18.5 % to pNO3- production, which was four times higher than the Tibetan Plateau's background regions. Taken together, the multidimensional isotope analysis performed in this study elucidates the pronounced influence of anthropogenic activities on PIN in the atmospheric environment of Lhasa.

Size-resolved water-soluble organic carbon and its significant contribution to aerosol liquid water

Size-segregated aerosols collected in Beijing from 2021 to 2022 were used to investigate the contribution of organic aerosols to the aerosol liquid water content (ALWC), the influencing factors of ALWC, and the concentrations and size distribution characteristics of water-soluble organic carbon (WSOC) after clean air actions. The results showed that the concentration of WSOC in particulate matter (PM)1.8 was 3.52 ± 2.43 μg/m3 during the sampling period. Obvious changes were observed in the size distribution of WSOC after clean air actions, which may be attributed to the enhancement of atmospheric oxidation capacity and the decrease in PM concentration. The contribution of organic aerosols to the ALWC in fine PM was 18.1 % during the sampling period, which was more significant at lower particles concentration and smaller particle size ranges. The ambient relative humidity (RH) and the ratio of NO3-/SO42- had an apparent influence on ALWC. The continuous increase in the nitrate proportion significantly reduced the deliquescence point of the aerosols, making them prone to hygroscopic growth at lower RH. Analysis of the relation among nitrogen oxidation ratio (sulfur oxidation ratio), ALWC and PM1.8 mass concentrations suggests that organic matter has a significant effect on the formation of secondary inorganic aerosols in the initial phase of pollution formation and plays a crucial role in aerosol pollution formation in Beijing. These results are conducive to understanding the formation mechanism of aerosols and provide scientific data and theoretical support for the formulation of more effective emission-reduction measures.

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.

Knowledge-guided machine learning reveals pivotal drivers for gas-to-particle conversion of atmospheric nitrate

Particulate nitrate, a key component of fine particles, forms through the intricate gas-to-particle conversion process. This process is regulated by the gas-to-particle conversion coefficient of nitrate (ε(NO3-)). The mechanism between ε(NO3-) and its drivers is highly complex and nonlinear, and can be characterized by machine learning methods. However, conventional machine learning often yields results that lack clear physical meaning and may even contradict established physical/chemical mechanisms due to the influence of ambient factors. It urgently needs an alternative approach that possesses transparent physical interpretations and provides deeper insights into the impact of ε(NO3-). Here we introduce a supervised machine learning approach-the multilevel nested random forest guided by theory approaches. Our approach robustly identifies NH4+, SO42-, and temperature as pivotal drivers for ε(NO3-). Notably, substantial disparities exist between the outcomes of traditional random forest analysis and the anticipated actual results. Furthermore, our approach underscores the significance of NH4+ during both daytime (30%) and nighttime (40%) periods, while appropriately downplaying the influence of some less relevant drivers in comparison to conventional random forest analysis. This research underscores the transformative potential of integrating domain knowledge with machine learning in atmospheric studies.

Nitrogen and oxygen isotope characteristics, formation mechanism, and source apportionment of nitrate aerosols in Wuhan, Central China

Understanding the sources and formation mechanisms of nitrate in PM2.5 is important for effective and precise prevention and control of particulate matter pollution. In this study, we detected stable nitrogen and oxygen isotope signatures of NO- 3 (expressed as δ15N-NO- 3 and δ18O-NO3-) in PM2.5 samples in Wuhan, the largest city in central China. The sources and formation pathways of NO3- were quantitatively analyzed using the modified version of the Bayesian isotope mixing (MixSIR) model, and the regional transport characteristics of NO3- were analyzed using the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model and concentration-weighted trajectory (CWT) method. The results showed that NO3- significantly contributed to the ambient PM2.5 pollution and its driving effect increased with the gradient of pollution level. The average δ15N-NO3- and δ18O-NO3- values were 4.7 ± 0.9 ‰ and 79.7 ± 2.9 ‰, respectively. δ15N-NO3- and δ18O-NO3- were more enriched in winter and increased dramatically in heavily polluted days. The reaction pathway of NO2 + OH dominated nitrate formation in summer, while the reaction pathway of N2O5+ H2O dominated in other seasons and contributed more in polluted days than clean days. The contributions of vehicle emission, coal combustion, biomass burning, biogenic soil emission, and ship emission sources to NO3- were 26.4 %, 23.4 %, 22.8 %, 15.3 %, and 12.1 %, respectively. In addition to local emissions, air mass transport from the northern China had a significant impact on particulate NO3- in Wuhan. Overall, we should pay special attention to vehicle and ship emissions and winter coal combustion emissions in future policymaking.

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.

Exposure to Airborne PM2.5 Water-Soluble Inorganic Ions Induces a Wide Array of Reproductive Toxicity

Water-soluble inorganic ions (WSIIs, primarily NH4+, SO42-, and NO3-) are major components in ambient PM2.5, but their reproductive toxicity remains largely unknown. An animal study was conducted where parental mice were exposed to PM2.5 WSIIs or clean air during preconception and the gestational period. After delivery, all maternal and offspring mice lived in a clean air environment. We assessed reproductive organs, gestation outcome, birth weight, and growth trajectory of the offspring mice. In parallel, we collected birth weight and placenta transcriptome data from 150 mother-infant pairs from the Rhode Island Child Health Study. We found that PM2.5 WSIIs induced a broad range of adverse reproductive outcomes in mice. PM2.5 NH4+, SO42-, and NO3- exposure reduced ovary weight by 24.22% (p = 0.005), 14.45% (p = 0.048), and 16.64% (p = 0.022) relative to the clean air controls. PM2.5 SO42- exposure reduced the weight of testicle by 5.24% (p = 0.025); further, mice in the PM2.5 SO42- exposure group had 1.81 (p = 0.027) fewer offspring than the control group. PM2.5 NH4+, SO42-, and NO3- exposure all led to lower birth than controls. In mice, 557 placenta genes were perturbed by exposure. Integrative analysis of mouse and human data suggested hypoxia response in placenta as an etiological mechanism underlying PM2.5 WSII exposure's reproductive toxicity.

Wintertime fine aerosol particles composition and its evolution in two megacities of southern and northern China

Study on fine aerosols composition can help understand the particles formation and is crucial for improving the accuracy of model simulations. Based on field data measured by a Q-ACSM (Quadrupole-Aerosol Chemical Speciation Monitor), we have comprehensively compared the characteristics, evolution, and potential formation mechanisms of the components in NR-PM2.5 during wintertime at two megacities (Beijing and Guangzhou) of southern and northern China. We show that as PM pollution intensifies, the mass fraction of the primary aerosols (e.g., COA, HOA) in PM2.5 in Guangzhou increased, along with a slight decline in proportion of both the secondary organic (SOA) and inorganic (SIA) aerosols; In contrast, in Beijing, the proportion of the SIA ramped up from 28 % to 53 % with the pollution evolution; and the fraction of SOA in total OA also increased due to a substantial increment in the proportion of MO-OOA (from 29 % to 48 %), suggesting a significance of the secondary processes in worsening aerosols pollution in Beijing. Our further analysis demonstrates a leading role of aqueous pathway in the secondary formation of aerosols at the Beijing site, presenting an exponential rising of SIA and SOA with the relative humidity (RH) increase. Compared to Beijing, however, we find that the photochemical oxidation other than aqueous process in Guangzhou plays a more critical role in those secondary aerosols formation. Combined with the Hysplit trajectory model, we identify the high humid conditions in Guangzhou are typically affected by clean marine air masses, explaining the slower response of secondary components to the RH changes. Moreover, the particles in Guangzhou were observed less hygroscopic that is adverse to the aerosol aqueous chemistry. The results provide basis for the precise control of PM pollution in different regions across China and would be helpful in improving model simulations.

Response of organic aerosol in Beijing to emission reductions during the XXIV Olympic Winter Games

Organic aerosol (OA) serves as a crucial component of fine particulate matter. However, the response of OA to changes in anthropogenic emissions remains unclear due to its complexity. The XXIV Olympic Winter Games (OWG) provided real atmospheric experimental conditions on studying the response of OA to substantial emission reductions in winter. Here, we explored the sources and variations of OA based on the observation of aerosol mass spectrometer (AMS) combined with positive matrix factorization (PMF) analysis in urban Beijing during the 2022 Olympic Winter Games. The influences of meteorological conditions on OA concentrations were corrected by CO and verified by deweathered model. The CO-normalized primary OA (POA) concentrations from traffic, cooking, coal and biomass burning during the OWG decreased by 39.8 %, 23.2 % and 65.0 %, respectively. Measures controlling coal and biomass burning were most effective in reducing POA during the OWG. For the CO-normalized concentration of secondary OA (SOA), aqueous-phase related oxygenated OA decreased by 51.8 % due to the lower relative humidity and emission reduction in precursors, while the less oxidized‑oxygenated OA even slightly increased as the enhanced atmospheric oxidation processes may partially offset the efficacy of emission control. Therefore, more targeted reduction of organic precursors shall be enhanced to lower atmospheric oxidation capacity and mitigate SOA 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.

Unpacking the factors contributing to changes in PM2.5-associated mortality in China from 2013 to 2019

From 2013 to 2019, a series of air pollution control actions significantly reduced PM2.5 pollution in China. Control actions included changes in activity levels, structural adjustment (SA) policy, energy and material saving (EMS) policy, and end-of-pipe (EOP) control in several sources, which have not been systematically studied in previous studies. Here, we integrate an emission inventory, a chemical transport model, a health impact assessment model, and a scenario analysis to quantify the contribution of each control action across a range of major emission sources to the changes in PM2.5 concentrations and associated mortality in China from 2013 to 2019. Assuming equal toxicity of PM2.5 from all the sources, we estimate that PM2.5-related mortality decreased from 2.52 (95 % confidence interval, 2.13-2.88) to 1.94 (1.62-2.24) million deaths. Anthropogenic emission reductions and declining baseline incidence rates significantly contributed to health benefits, but population aging partially offset their impact. Among the major sources, controls on power plants and industrial boilers were responsible for the highest reduction in PM2.5-related mortality (∼80 %), followed by industrial processes (∼40 %), residential combustion (∼40 %), and transportation (∼30 %). However, considering the potentially higher relative risks of power plant PM2.5, the adverse effects avoided by their control could be ∼2.4 times the current estimation. Our power plant sensitivity analyses indicate that future estimates of source-specific PM2.5 health effects should incorporate variations in individual source PM2.5 effect coefficients when available. As for the control actions, while activity levels increased for most sources, SA policy significantly reduced the emissions in residential combustion and industrial boilers, and EOP control dominated the contribution in health benefits in most sources except residential combustion. Considering the emission reduction potential by source and control actions in 2019, our results suggest that promoting clean energy in residential combustion and enforcing more stringent EOP control in the iron and steel industry should be prioritized in the future.

The significant contribution of nitrate to a severe haze event in the winter of Guangzhou, China

A severe haze pollution occurred in Guangzhou from January 14 to 16, 2021, during which the mass concentration of PM2.5 ranged from 76 to 243 μg m-3. This level of pollution was rarely observed in recent years considering the improved air quality in Guangzhou. Therefore, it is crucial to comprehensively study the formation mechanisms of this severe haze pollution to prevent its reoccurrence. During the haze period, the concentrations of NO and NO2 sharply increased by 7.4 and 3.8 times, respectively, and total volatile organic compounds (TVOCs) increased 7 times, suggesting enhanced primary emissions from vehicles due to stagnant meteorological conditions. Nitrate concentration (43 ± 20 μg m-3) increased 6.7 times and became the dominant species in PM2.5 during the haze period. Notably, gaseous NH3, HONO and HNO3 also exhibited a sharp increase, suggesting the important role of nitrate chemistry in the evolution of haze pollution. The simulation results from chemical box model revealed that the OH + NO2 reaction was the dominant formation pathway for nitrate production (82 %) during the haze period. The net production rate of ROx radicals (including OH, HO2 and RO2) was 4.4 times higher during the haze period (5.8 ppb h-1) compared to the pre-haze period (1.3 ppb h-1). This was mainly attributed to the enhanced HONO and OVOCs photolysis, which increased from 0.6 ppb h-1 to 3.1 ppb h-1 and 0.4 ppb h-1 to 2.1 ppb h-1, respectively. Furthermore, the sensitivity tests demonstrated the reductions in VOCs and NOx were both beneficial for controlling nitrate production by influencing OH production and N2O5 uptake rate. These findings provide insights into the formation mechanisms of nitrate production during severe haze pollution and suggest that joint mitigation of PM2.5 and O3 can be achieved through the control of VOCs emission.

An overview of atmospheric aerosol and their effects on human health

Epidemiologic investigations have previously been published in more than 200 papers, and several studies have examined the impacts of particle air pollution on health. The main conclusions now being made about the epidemiological evidence of particle pollution-induced health impacts are discussed in this article. Although there is no universal agreement, most reviewers conclude that particulate air pollution, particularly excellent combustion-cause contamination prevalent in many municipal and manufacturing environments, is a significant risk for cardiopulmonary sickness and mortality. Most epidemiological research has concentrated on the impacts of acute exposure, although the total public health implications of chronic acquaintance's outcome may be more extraordinarily significant. According to some reviewers, prolonged, repeated exposure raises the risk of cardiorespiratory death and chronic respiratory illness. A more general (but still universal) agreement is that short-term particle pollution exposure has been shown to aggravate pre-existing pulmonary and cardiovascular diseases and increase the number of community members who become sick, require medical treatment, or die. Several in-depth studies conducted in the global and Indian regions are addressed.

Nitrogen isotopes suggest agricultural and non-agricultural sources contribute equally to NH3 and NH4+ in urban Beijing during December 2018

Agricultural and non-agricultural sources emission contribute to atmospheric ammonia (NH₃) and particulate ammonium (NH₄⁺). However, our understanding on the sources of NH₃ and NH₄⁺ in PM_2.5 (particles smaller than 2.5 μm) during the winter period in the urban atmosphere is limited. Here, we measured the concentrations and stable nitrogen isotopic composition (δ¹⁵N) of NH₃ and NH₄⁺ in parallel during December 2018 in urban Beijing to assess the non-agricultural and agricultural sources contributions to NH₃ and NH₄⁺ in ambient air based on the Chemical Transport Model (CTM), a Bayesian isotope mixing model (SIMMR), and the δ¹⁵N signatures that we developed. Our study found weekly NH₄⁺ and NH₃ concentrations were on average 2.5 ± 1.4 μg m^-3 and 3.8 ± 1.7 μg m^-3, respectively during December 2018. Weekly concentration weighted δ¹⁵N(NH₄⁺) values ranged from 4.5‰ to 13.7‰ with an average value of 8.2 ± 3.9‰ during December 2018. After accounting for nitrogen isotopic fractionation from NH₃ gas to NH₄⁺ conversion, initial δ¹⁵N(NH₃) values ranged from -22.5‰ to -12.8‰ with an average value of -17.4 ± 3.5‰. Further, weekly measured δ¹⁵N(NH₃) values ranged from -22.2‰ to -10.2‰ (after correction) with an average value of -15.6 ± 5.3‰ during December 2018. Results from two different isotope-based method showed non-agricultural sources contributed 31.2%-63.1%, with an average value of 47.5 ± 14.6%, to NH₄⁺ and 32.3%-71.2%, with an average of 53.4 ± 16.1%, to ambient NH₃ during December 2018 in Beijing. Results from CMAQ-ISAM suggest non-agricultural sources contributed on average 66.2 ± 1.9% to ambient NH₄⁺ and 66.4 ± 1.9% to ambient NH₃ during December 2018. Results from this study suggest that agricultural and non-agricultural sources nearly equally contributed to NH₃ and NH₄⁺ in urban Beijing during December 2018 with an uncertainty range of 13%-19% between isotope-based methods and CTM method.

Abundant nitrogen oxide and weakly acidic environment synergistically promote daytime particulate nitrate pollution

Nitrate is formed through the chemical production of gas-phase nitric acid and subsequent partitioning to the aerosol phase during the daytime. Many studies in the past separated these two aspects, even though they occur simultaneously in the atmosphere. To better understand the nitrate formation mechanism and effectively mitigate its production, it is necessary to consider the synergy between these two mechanisms. For this, we analyze hourly-speciated ambient observations data, with EK&TMA (Empirical Kinetic & Thermodynamic Modeling Approach) map to comprehensively explore the factors controlling nitrate production. Results show that precursor NO₂ concentration and aerosol pH, which are related to anthropogenic activities, are the two major factors for chemical kinetics production and gas/particle thermodynamic partitioning processes respectively. Abundant NO₂ and weakly acidic environments are favorable conditions for daytime particulate nitrate pollution, thus collaborative control of coal source, vehicle source, and dust source is needed to alleviate nitrate pollution.

Profiling Microbiota from Multiple Sites in the Respiratory Tract to Identify a Biomarker for PM2.5 Nitrate Exposure-Induced Pulmonary Damages

The microbiota present in the respiratory tract (RT) responds to environmental stimuli and engages in a continuous interaction with the host immune system to maintain homeostasis. A total of 40 C57BL/6 mice were divided into four groups and exposed to varying concentrations of PM_2.5 nitrate aerosol and clean air. After 10 weeks of exposure, assessments were conducted on the lung and airway microbiome, lung functions, and pulmonary inflammation. Additionally, we analyzed data from both mouse and human respiratory tract (RT) microbiomes to identify possible biomarkers for PM_2.5 exposure-induced pulmonary damages. On average, 1.5 and 13.5% inter-individual microbiome variations in the lung and airway were explained by exposure, respectively. In the airway, among the 60 bacterial OTUs (operational taxonomic units) > 0.05% proportion, 40 OTUs were significantly affected by PM_2.5 exposure (FDR ≤ 10%). Further, the airway microbiome was associated with peak expiratory flow (PEF) (p = 0.003), pulmonary neutrophil counts (p = 0.01), and alveolar 8-OHdG oxidative lesions (p = 0.0078). The Clostridiales order bacteria showed the strongest signals. For example, the o_Clostridiales;f_;g_ OTU was elevated by PM_2.5 nitrate exposure (p = 4.98 × 10^-5) and negatively correlated with PEF (r = -0.585 and p = 2.4 × 10^-4). It was also associated with the higher pulmonary neutrophil count (p = 8.47 × 10^-5) and oxidative lesion (p = 7.17 × 10^-3). In human data, we confirmed the association of airway Clostridiales order bacteria with PM_2.5 exposure and lung function. For the first time, this study characterizes the impact of PM_2.5 exposure on the microbiome of multiple sites in the respiratory tract (RT) and its relevance to airflow obstructive diseases. By analyzing data from both humans and mice, we have identified bacteria belonging to the Clostridiales order as a promising biomarker for PM_2.5 exposure-induced decline in pulmonary function and inflammation.

Heterogeneous uptake of NO2 by sodium acetate droplets and secondary nitrite aerosol formation

The high NO₃^- concentration in fine particulate matters (PM_2.5) during heavy haze events has attracted much attention, but the formation mechanism of nitrates remains largely uncertain, especially concerning heterogeneous uptake of NO_X by aqueous phase. In this work, the heterogeneous uptake of NO₂ by sodium acetate (NaAc) droplets with different NO₂ concentrations and relative humidity (RH) conditions is investigated by microscopic Fourier transform infrared spectrometer (micro-FTIR). The IR feature changes of aqueous droplets indicate the acetate depletion and nitrite formation in humid environment. This implies that acetate droplets can provide the alkaline aqueous circumstances caused by acetate hydrolysis and acetic acid (HAc) volatilization for nitrite formation during the NO₂ heterogeneous uptake. Meanwhile, the nitrite formation will exhibit a pH neutralizing effect on acetate hydrolysis, further facilitating HAc volatilization and acetate depletion. The heterogeneous uptake coefficient increases from 5.2 × 10^-6 to 1.27 × 10^-5 as RH decreases from 90% to 60% due to the enhanced HAc volatilization. Furthermore, no obvious change in uptake coefficient with different NO₂ concentrations is observed. This work may provide a new pathway for atmospheric nitrogen cycling and secondary nitrite aerosol formation.

What controls aerosol δ15N-NO3-? NOx emission sources vs. nitrogen isotope fractionation

Atmospheric δ¹⁵N-NO₃^- has been used to reveal NO_x (NO + NO₂) sources as NO₃^- is the ultimate sink of NO_x. However, it remains questionable whether the nitrogen isotope fractionation among NO_y (NO, NO₂, NO₃, N₂O₅, HNO₃ and NO₃^-) engender the misjudgment of NO_x emission sources by affecting δ¹⁵N-NO_y. To explore this issue, we integrated the dataset of aerosol δ¹⁵N-NO₃^- values and ratios of f_NO2 (f_NO2 = NO₂/(NO₂ + NO)), calculated the nitrogen isotope fractionation factors (Δ_s) among NO_y, compared the total energy consumption in Beijing-Tianjin-Hebei region (BTH) from 2013 to 2018. Results showed that, although the total energy consumption structure changed from 2013 to 2018 in BTH, there were fewer interannual variances of aerosol δ¹⁵N-NO₃^- values. Nitrogen isotope fractionation factors between NO and NO₂ (Δ₀), NO₂ and NO₃ (Δ₂), NO₂ and N₂O₅ (Δ₃), NO₂ and ClONO₂ (Δ₄) also displayed less interannual variations from 2013 to 2018 in BTH. But both aerosol δ¹⁵N-NO₃^- and Δ_s displayed significant seasonal patterns, and there was significant relationship between monthly aerosol δ¹⁵N-NO₃^- and Δ_s, which suggested that Δ_s have important influence on shaping aerosol δ¹⁵N-NO₃^- and further discriminating NO_x emission sources. This study implies that we should refine the Δ_s when employing atmospheric δ¹⁵N-NO₃^- to quantify NO_x source allocation.

Molecular tracers, mass spectral tracers and oxidation of organic aerosols emitted from cooking and fossil fuel burning sources

Secondary organic aerosol (SOA) composes a substantial fraction of atmospheric particles, yet the formation and aging mechanism of SOA remains unclear. Here we investigate the initial oxidation of primary organic aerosol (POA) and further aging of SOA in winter Beijing by using aerosol mass spectrometer (AMS) measurements along with offline molecular tracer analysis. Multilinear engine (ME-2) source apportionment was conducted to capture the characteristic of source-related SOA, and connect them with specific POA. Our results show that urban cooking and fossil fuel burning sources contribute significantly (17 % and 20 %) to total organic aerosol (OA) in winter Beijing. Molecular tracer analysis by two-dimensional gas chromatography-time-of-flight mass spectrometer (GC × GC-ToF-MS) reveals that cooking SOA (CSOA) is produced through both photooxidation and aqueous-phase processing, while less oxidized SOA (LO-SOA) is the photooxidation product of fossil fuel burning OA (FFOA) and may experience aqueous-phase aging to form more-oxidized oxygenated OA (MO-OOA). Furthermore, CHO_{m/z 69} and CHO_{m/z 85} are mass spectral tracers indicating the initial photooxidation, while CHO₂⁺ and C₂H₂O₂⁺ imply further aqueous-phase aging of OA. Tracer analysis indicates that the formation of diketones is involved in the initial photooxidation of POA, while the formation of glyoxal and diacids is involved in the further aqueous-phase aging of SOA.

The Effect of CaO on the CO and NOx Emission Characteristics of Fast-Growing Grass Combustion

Fast-growing grass is a biomass material with characteristics such as high temperature and drought resistance; rapid growth and development; and repeated germination and cutting. Therefore, it is a popular biomass fuel. It is required that the pollutants produced during the biomass combustion process are appropriately controlled. For this purpose, our study analyses the influence of combustion temperature and calcium oxide (CaO) on the nitrogen oxides (NOx) and carbon monoxide (CO) emission characteristics of fast-growing grass combustion using the biomass combustion flue gas analysis and testing platform. The results of our analysis revealed that CaO additive can simultaneously reduce the peak and total NOx emissions at 750 °C. Particularly, 5% CaO demonstrated a significant control effect on the NOx emission from the fast-growing grass combustion process, with a peak and total emissions reduction of 47.05% and 56.81%, respectively. In addition, with an increase in temperature, the CO emission curve attains a second peak higher than the first peak, and the peak and total emissions show a decreasing trend.

Contributions of various driving factors to air pollution events: Interpretability analysis from Machine learning perspective

The air quality in China has been improved substantially, however fine particulate matter (PM_2.5) still remain at a high level in many areas. PM_2.5 pollution is a complex process that is attributed to gaseous precursors, chemical, and meteorological factors. Quantifying the contribution of each variable to air pollution can facilitate the formulation of effective policies to precisely eliminate air pollution. In this study, we first used decision plot to map out the decision process of the Random Forest (RF) model for a single hourly data set and constructed a framework for analyzing the causes of air pollution using multiple interpretable methods. Permutation importance was used to qualitatively analyze the effect of each variable on PM_2.5 concentrations. The sensitivity of secondary inorganic aerosols (SIA): SO₄^2-, NO₃^- and NH₄⁺ to PM_2.5 was verified by Partial dependence plot (PDP). Shapley Additive Explanation (Shapley) was used to quantify the contribution of drivers behind the ten air pollution events. The RF model can accurately predict PM_2.5 concentrations, with determination coefficient (R²) of 0.94, root mean square error (RMSE) and mean absolute error (MAE) of 9.4 μg/m³ and 5.7 μg/m³, respectively. This study revealed that the order of sensitivity of SIA to PM_2.5 was NH₄⁺＞NO₃^-＞SO₄^2-. Fossil fuel and biomass combustion may be contributing factors to air pollution events in Zibo in 2021 autumn-winter. NH₄⁺ contributed 19.9-65.4 μg/m³ among ten air pollution events (APs). K, NO₃^-, EC and OC were the other main drivers, contributing 8.7 ± 2.7 μg/m³, 6.8 ± 7.5 μg/m³, 3.6 ± 5.8 μg/m³ and 2.5 ± 2.0 μg/m³, respectively. Lower temperature and higher humidity were vital factors that promoted the formation of NO₃^-. Our study may provide a methodological framework for precise air pollution management.

Transport Pathways of Nitrate Formed from Nocturnal N2O5 Hydrolysis Aloft to the Ground Level in Winter North China Plain

Particulate nitrate (NO₃^-) has currently become the major component of fine particles in the North China Plain (NCP) during winter haze episodes. However, the contributions of formation pathways to ground NO₃^- in the NCP are not fully understood. Herein, the NO₃^- formation pathways were comprehensively investigated based on model simulations combined with two-month field measurements at a rural site in the winter NCP. The results indicated that the nocturnal chemistry of N₂O₅ hydrolysis aloft could contribute evidently to ground NO₃^- at the rural site during the pollution episodes with high aerosol water contents, achieving the contribution percentages of 25.2-30.4% of the total. In addition to the commonly proposed vertical mixing of breaking nocturnal boundary layer in the early morning, two additional transport pathways (frontal downdrafts and downslope mountain breezes) in the nighttime were found to make higher contributions to ground NO₃^-. Considering the dominant role (69.6-74.8%) of diurnal chemistry in NO₃^- formation, reduction of NO_x emissions in the daytime may be an effective control measure for reducing regional NO₃^- in the NCP.

Causes of the unexpected slowness in reducing winter PM2.5 for 2014-2018 in Henan Province

Toughest-ever clean air actions in China have been implemented nationwide to improve air quality. However, it was unexpected that from 2014 to 2018, the observed wintertime PM_2.5 (particulate matter with an aerodynamic diameter of less than 2.5 μm) concentrations showed an insignificant decrease in Henan Province (HNP), a region in the west of the North China Plain. Emission controls seem to have failed to improve winter air quality in HNP, which has caused great confusion in formulating the next air improvement strategy. We employed a deweathering technique to decouple the impact of meteorological conditions. The results showed that the deweathered PM_2.5 trend was -3.3%/yr in winter from 2014 to 2018, which had a larger decrease than the observed concentrations (-0.9%/yr), demonstrating that emission reduction was effective at improving air quality. However, compared with the other two megacity clusters, Beijing-Tianjin-Hebei (BTH) (-8.4%/yr) and Yangtze River Delta (YRD) (-7.4%/yr), the deweathered decreasing trend of PM_2.5 for HNP remained slow. The underlying mechanism driving the changes in PM_2.5 and its chemical components was further explored, using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). Model simulations indicated that nitrate dominated the increase of PM_2.5 components in HNP and the proportions of nitrate to total PM_2.5 increased from 22.4% in January 2015 to 39.7% in January 2019. There are two primary reasons for this phenomenon. One is the limited control of nitrogen oxide emissions, which facilitates the conversion of nitric acid to particulate nitrate by ammonia. The other is unfavourable meteorological conditions, particularly increasing humidity, further enhancing nitrate formation through multiphase reactions. This study highly emphasizes the importance of reducing nitrogen oxide emissions owing to their impact on the formation of particulate nitrate in China, especially in the HNP region.

Assessment of traffic-related chemical components in ultrafine and fine particles in urban areas in Vietnam

Ultrafine particles (UFPs or PM_0.1; aerodynamic diameter ≤ 0.1 μm) were monitored at a roadside site (RS) in a populated area of Hanoi, Vietnam. Meanwhile, UFPs and fine particles (FPs or PM_2.5, aerodynamic diameter ≤ 2.5 μm) were monitored at an ambient site (AS), located at an on-campus a university, approximately 200 m away from the RS. Sampling was conducted in different seasons-summer, winter, and the transitional periods of summer-to-winter and winter-to-summer (STP and WTP, respectively). Carbonaceous and ionic species in UFPs and FPs-rarely investigated in the study area-were analyzed to observe the seasonal variations, characteristics of UFPs near the roadway, and spatial differences between the sites. The UFPs concentration at the AS was in the order of winter > STP > WTP > summer, whereas that of the FPs was winter > WTP > STP > summer. This seasonal variation of particle concentration was possibly affected by the meteorological conditions, which contribute to the highest concentration in winter. The higher FPs concentration in WTP than in STP resulted from the substantial increase in ionic concentrations, particularly sulfate, nitrate, and ammonium. This result indicates the effect of secondary formation processes under drizzle-like weather, which is typical during WTP in northern Vietnam. Compared with UFPs at the AS, traffic-related emissions were more noticeable in UFPs at the RS, including a higher EC concentration and lower OC/EC ratio. The possibility of particle growth under favorable conditions, including the presence of gas-phase pollutants and the availability of surface areas owing to high UFPs concentration in Hanoi, may explain the low correlation of the chemical components between UFPs and FPs in the sites. This study serves as a reference for further investigation of the relationship between UFPs and FPs under highly polluted conditions in big cities in Vietnam in future studies.

Fine particulate pollution driven by nitrate in the moisture urban atmospheric environment in the Pearl River Delta region of south China

To identify potential sources of fine particles (PM_2.5, with aerodynamic diameter (D_a) ≤ 2.5 μm) in urban Dongguan of south China, a comprehensive campaign was carried out in the whole 2019. Hourly PM_2.5 and its dominant chemical components including organic carbon (OC), elemental carbon (EC), water-soluble inorganic ions (WSIIs) and thirteen elements were measured using online instruments. Gaseous pollutants including NH₃, HNO₃, NO₂, NO and O₃ and meteorological parameters were also synchronously measured. PM_2.5 was dominated by carbonaceous aerosols in summer and by WSIIs in the other seasons. PM_2.5 and its dominant chemical components mostly peaked around noon (10:00-14:00 LST). Furthermore, high PM_2.5 levels during the daytime were closely related with the increased NO₃^- levels. The high mass concentrations of NO₃^- in urban Dongguan during the daytime were likely related with regional transport of NO₃^- from suburban Dongguan, which was originated from the reaction between NO₂ and O₃ under the moisture condition during the nighttime. Seven major source factors for PM_2.5 including secondary sulfate, ship emission, traffic emission, secondary nitrate, industrial processes, soil dust and coal combustion were identified by positive matrix factorization (PMF) analysis, which contributed 26 ± 14%, 16 ± 16%, 16 ± 10%, 14 ± 11%, 12 ± 11%, 8 ± 6% and 8 ± 6%, respectively, to annual PM_2.5 mass concentration. Although secondary sulfate contributed much more than secondary nitrate to PM_2.5 on annual basis, the latter exceeded the former source factor when daily PM_2.5 mass concentration was higher than 60 μg m^-3, indicating the critical role nitrate played in PM_2.5 episode events.

Aqueous-phase chemistry of atmospheric phenolic compounds: A critical review of laboratory studies

Phenolic compounds (PhCs) are crucial atmospheric pollutants typically emitted by biomass burning and receive particular concerns considering their toxicity, light-absorbing properties, and involvement in secondary organic aerosol (SOA) formation. A comprehensive understanding of the transformation mechanisms on chemical reactions in atmospheric waters (i.e., cloud/fog droplets and aerosol liquid water) is essential to predict more precisely the atmospheric fate and environmental impacts of PhCs. Laboratory studies play a core role in providing the fundamental knowledge of aqueous-phase chemical transformations in the atmosphere. This article critically reviews recent laboratory advances in SOA formation from the aqueous-phase reactions of PhCs. It focuses primarily on the aqueous oxidation of PhCs driven by two atmospheric reactive species: OH radicals and triplet excited state organics, including the important chemical kinetics and mechanisms. The effects of inorganic components (i.e., nitrate and nitrite) and transition metal ions (i.e., soluble iron) are highlighted on the aqueous-phase transformation of PhCs and on the properties and formation mechanisms of SOA. The review is concluded with the current knowledge gaps and future perspectives for a better understanding of the atmospheric transformation and SOA formation potential of PhCs.

Responses of sulfate and nitrate to anthropogenic emission changes in eastern China - in perspective of long-term variations

We investigate responses of sulfate (SO₄^2-) and nitrate (NO₃^-) to anthropogenic emission changes in 2006-2017 by fixing meteorology at the 2009 level using nested 3D chemical transport model GEOS-Chem. We find that sulfate concentration decreases following SO₂ emissions, but with a relatively smaller reduction rate (by 16 % in North China Plain (NCP) and 28 % in Yangtze River Delta (YRD)) due to larger sulfur oxidation ratio (SOR) at lower SO₂ level. SOR follows a power law with SO₂ emissions in general except in winter in NCP, when and where both SO₂ emission reduction and atmospheric oxidation capacity are critical to the inter-annual variations of SOR. Nitrate concentration ([pNO₃^-]) decreases along with NOx emission reduction in summer, but increases slightly in winter in 2011-2017. Equilibrium with gas phase HNO₃, NO₃^- in particle phase (pNO₃^-) is determined by total HNO₃ (TN = [pNO₃^-] + [gHNO₃]) oxidized from NO₂ and gas-particle partitioning (ε(NO₃^-) = [pNO₃^-]/TN). TN is decreasing faster in summer (~33 %) than in winter (~25 %) in 2011-2017. In contrast, ε(NO₃^-) changes marginally in summer (within 5 %) but increases by 36 % in NCP and by 51 % in YRD in winter in 2006-2017. The increasing of ε(NO₃^-) in winter is attributed to the strong reduction of [pSO₄^2-], which increases the relative abundance of NH₃ and thus favors partitioning of NO₃^- to the particle phase. The effect of increasing ε(NO₃^-) overcomes that of decreasing TN in winter. We suggest reduce SO₂ emissions to further reduce [pSO₄^2-] in eastern China. In addition, we recommend reduce NOx emissions in summer, and reduce atmospheric oxidation capacity and relative abundance of NH₃ in winter to reduce [pNO₃^-].

Chemical characterization, formation mechanisms and source apportionment of PM2.5 in north Zhejiang Province: The importance of secondary formation and vehicle emission

PM_2.5 affects air quality, therefore, chemical evolution, formation mechanism and source identification of PM_2.5 are essential to help figure out mitigation measures. PM_2.5 and its constituents were comprehensively characterized with highly time-resolved measurements from 2019 to 2020 in north Zhejiang Province (Shanxi, SX) for the first time, with an emphasis on the contribution of secondary formation and vehicle emission to PM_2.5. Secondary inorganic ions (sulfate: 3.86 μg/m³, nitrate: 7.82 μg/m³ and ammonium: 4.59 μg/m³, SNA) were found to be the major components (54%) in PM_2.5 (29.70 μg/m³). The highly consistence of nitrate, sulfate and secondary organic compounds (SOC) with Ox (NO₂ + O₃) or RH indicated the importance of photochemical oxidation and heterogeneous reaction in different scenarios. Higher atmospheric oxidative potential facilitated the SOC formation in spring. The PM_2.5 mass was apportioned to eight sources resolved by positive matrix factorization (PMF): secondary nitrate (9.63 μg/m³), secondary sulfate (5.14 μg/m³), vehicle emission (7.26 μg/m³), coal combustion (2.39 μg/m³), biomass burning (1.38 μg/m³), soil dust (0.86 μg/m³), industry emission (0.50 μg/m³), and ship emission (0.32 μg/m³). Secondary nitrate (35%) and sulfate (19%) formation and vehicle emission (26%) were the main factors contributing to the PM_2.5. Furthermore, the contribution of secondary nitrate formation increased with elevating PM_2.5 concentration. Regional transport was synthetically studied by chemical and backward trajectory analysis, reflecting that secondary nitrate contributed severely to the air quality at SX, while vehicle emission contribution enhanced when atmosphere was stagnant. This study first provides long-term comprehensive chemical characterization and source apportionments of PM_2.5 pollution in north Zhejiang, which may provide some guidance for the air pollution control.

Quantifying the source and formation of nitrate in PM2.5 using dual isotopes combined with Bayesian mixing model: A case study in an inland city of southeast China

Atmospheric nitrate has been attracting increasing attention because it is one of the important components of PM_2.5. Understanding the sources and formation mechanism of nitrate in PM_2.5 is essential to take effective measures to prevent and control the emission of nitrogen oxides in the atmosphere and reduce the formation of haze. In this study, PM_2.5 samples were collected from Ganzhou, an inland city in southeast China, during summer and winter. The concentrations of PM_2.5 and NO₃^- were determined, and the isotopic compositions of NO₃^- (δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^-) were analyzed in order to quantify the relative contributions of different emission sources and formation pathways of nitrate in PM_2.5. The results showed that PM_2.5 and NO₃^- concentrations were lower in summer (39.80 ± 11.10 μg·m^-3 and 1.79 ± 0.70 μg·m^-3) while higher in winter (69.85 ± 29.58 μg·m^-3 and 10.83 ± 9.89 μg·m^-3). The values of δ¹⁸O-NO₃^- and δ¹⁵N-NO₃^- ranged from 42.84‰ to 56.80‰ and from -11.17‰ to -2.08‰ in summer, while from 55.86‰ to 78.66‰ and from -10.63‰ to -1.88‰ in winter, respectively. The results of δ¹⁵N-NO₃^- combined with Bayesian isotope mixing model showed that the relative contributions of vehicle exhaust, soil microbial activity, biomass combustion and coal fired power plants were 59.3%, 28.5%, 8.7% and 3.4% in summer, while 65.1%, 20.1%, 10.6% and 4.1% in winter, respectively. The results of δ¹⁸O-NO₃^- combined with Bayesian isotope mixing model showed that the possible relative contributions of pathway 1 (P1) (NO₂ + ·OH), pathway 2 (P2) (NO₃ + HC) and pathway 3 (P3) (N₂O₅ + H₂O) were 73.5%, 12.4% and 14.1% in summer, while 41.6%, 28.9% and 29.5% in winter, respectively. Moreover, P2 and P3 contributed more when NO₃^- concentrations were higher, suggesting that P2 and P3 were of significance to the formation of nitrate in PM_2.5, especially during winter.

PM2.5 and water-soluble inorganic ion concentrations decreased faster in urban than rural areas in China

We investigated variations of PM_2.5 and water-soluble inorganic ions chemical characteristics at nine urban and rural sites in China using ground-based observations. From 2015 to 2019, mean PM_2.5 concentration across all sites decreased by 41.9 µg/m³ with a decline of 46% at urban sites and 28% at rural sites, where secondary inorganic aerosol (SIAs) contributed to 21% (urban sites) and 17% (rural sites) of the decreased PM_2.5. SIAs concentrations underwent a decline at urban locations, while sulfate (SO₄^2-), nitrate (NO₃^-), and ammonium (NH₄⁺) decreased by 49.5%, 31.3% and 31.6%, respectively. However, only SO₄^2- decreased at rural sites, NO₃^- increased by 21% and NH₄⁺ decreased slightly. Those changes contributed to an overall SIAs increase in 2019. Higher molar ratios of NO₃^- to SO₄^2- and NH₄⁺ to SO₄^2- were observed at urban sites than rural sites, being highest in the heavily polluted days. Mean molar ratios of NH₃/NH_x were higher in 2019 than 2015 at both urban and rural sites, implying increasing NH_x remained as free NH₃. Our observations indicated a slower transition from sulfate-driven to nitrate-driven aerosol pollution and less efficient control of NO_x than SO₂ related aerosol formation in rural regions than urban regions. Moreover, the common factor at urban and rural sites appears to be a combination of lower SO₄^2- levels and an increasing fraction of NO₃^- to PM_2.5 under NH₄⁺-rich conditions. Our findings imply that synchronous reduction in NO_x and NH₃ emissions especially rural areas would be effective to mitigate NO₃^--driven aerosol pollution.

Within- and cross-tissue gene regulations were disrupted by PM2.5 nitrate exposure and associated with respiratory functions

BACKGROUND

Pathogenesis of complex diseases often involves multiple organs/tissue-types. To date, the PM_2.5 exposure's toxic effects and induced disease risks were not studied at multi-tissue level.

METHODS

C57BL/6 mice (n = 40) were exposed to PM_2.5 NO₃^- and clean air, respectively, and afterwards assessed respiratory functions and transcriptome in relevant tissues: blood and lung. We constructed within- and cross-tissue gene regulation networks and identified network modules associated with exposure and respiratory functions.

RESULTS

PM_2.5 NO₃^- exposure elevated naïve B cells proportion in blood (p = 0.0028). Among the 6000 highest expressed genes in blood, 18.8 % (1133 genes) were altered by exposure at p ≤ 0.05 level, among which 763 genes were also associated with respiratory function (enrichment folds = 7.63, p = 2.7E-189). The exposure disrupted blood genes were primarily in the immunoregulation pathways. Both within- and cross-tissue gene network modules were perturbed by exposure and associated with respiratory function. An immunodeficiency related cross-tissue module of 555 genes was affected by exposure (p = 0.0023) and strongly correlated with FEV_0.05/FVC (r = 0.61 and p = 3E-5).

CONCLUSIONS

This study aims to fill in a major knowledge gap and investigated the effect of PM_2.5 exposure simultaneously in multiple tissues. We provided novel evidence that PM_2.5 NO₃^- exposure profoundly perturbed within- and cross-tissue gene regulations, and highlighted their roles in the etiology of respiratory decline.

Dust emission reduction enhanced gas-to-particle conversion of ammonia in the North China Plain

Ammonium salt is an important component of particulate matter with aerodynamic diameter less than 2.5 µm (PM_2.5) and has significant impacts on air quality, climate, and natural ecosystems. However, a fundamental understanding of the conversion kinetics from ammonia to ammonium in unique environments of high aerosol loading is lacking. Here, we report the uptake coefficient of ammonia (γ_NH3) on ambient PM_2.5 varying from 2.2 × 10^-4 to 6.0 × 10^-4 in the North China Plain. It is significantly lower than those on the model particles under simple conditions reported in the literature. The probability-weighted γ_NH3 increases obviously, which is well explained by the annual decrease in aerosol pH due to the significant decline in alkali and alkali earth metal contents from the emission source of dust. Our results elaborate on the complex interactions between primary emissions and the secondary formation of aerosols and the important role of dust in atmospheric chemistry.

Fine particulate matter (PM2.5/PM1.0) in Beijing, China: Variations and chemical compositions as well as sources

Particulate matter (i.e., PM_1.0 and PM_2.5), considered as the key atmospheric pollutants, exerts negative effects on visibility, global climate, and human health by associated chemical compositions. However, our understanding of PM and its chemical compositions in Beijing under the current atmospheric environment is still not complete after witnessing marked alleviation during 2013-2017. Continuous measurements can be crucial for further air quality improvement by better characterizing PM pollution and chemical compositions in Beijing. Here, we conducted simultaneous measurements on PM in Beijing during 2018-2019. Results indicate that annual mean PM_1.0 and PM_2.5 concentrations were 35.49 ± 18.61 µg/m³ and 66.58 ± 60.17 µg/m³, showing a positive response to emission controls. The contribution of sulfate, nitrate, and ammonium (SNA) played an enhanced role with elevated PM loading and acted as the main contributors to pollution episodes. Discrepancies observed among chemical species between PM_1.0 and PM_2.5 in spring suggest that sand particles trend to accumulate in the range of 1-2.5 µm. Pollution episodes occurred accompanied with southerly clusters and high formation of SNA by heterogeneous reactions in summer and winter, respectively. Results from positive matrix factorization (PMF) combined with potential source contribution function (PSCF) models showed that potential areas were seasonal dependent, secondary and vehicular sources became much more important compared with previous studies in Beijing. Our study presented a continuous investigation on PM and sources origins in Beijing, which provides a better understanding for further emission control as well as a reference for other cities in developing countries.

Seasonal variations in aerosol acidity and its driving factors in the eastern Indo-Gangetic Plain: A quantitative analysis

This study employs ISORROPIA-II for the evaluation of aerosol acidity and quantification of contributions from chemical species and meteorological parameters to acidity variation in the Indian context. PM_2.5 samples collected during summer (April-July 2018), post-monsoon (September-November 2018), and winter (December 2018-January 2019) from a rural receptor location in the eastern Indo-Gangetic Plain (IGP) were analyzed for ionic species, water-soluble organic carbon (WSOC), and organic and elemental carbon (OC, EC) fractions. This was followed by estimation of the in situ aerosol pH and liquid water content (LWC) using the forward mode of ISORROPIA-II, which is less sensitive to measurement uncertainty compared to the reverse mode, for a K⁺-Ca²⁺-Mg²⁺-NH₄⁺-Na⁺-SO₄^2--NO₃^--Cl^--H₂O system. Aerosol pH was moderately acidic (summer: 2.93 ± 0.67; post-monsoon: 2.67 ± 0.23; winter: 3.15 ± 0.34) and was most sensitive to SO₄^2- and total ammonium (TNH₃) variation. The LWC of aerosol showed an increasing trend from summer (16.6 ± 13.6 μg m^-3) through winter (32.9 ± 10.4 μg m^-3). With summer as the baseline, the largest changes in aerosol pH during the other seasons was driven by SO₄^2- (ΔpH: -0.70 to -0.82 units), followed by TNH₃ (ΔpH: +0.25 to +0.38 units) with K⁺ and temperature being significant only during winter (ΔpH: +0.51 and + 0.46 units, respectively). The prevalent acidity regime provided three major insights: i) positive summertime Cl^- depletion (49 ± 20%) as a consequence of SO₄^2- substitution increased aerosol pH by 0.03 ± 0.20 units and decreased LWC by 2.4 ± 5.9 μg m^-3; ii) the rate of strong acidity (H⁺_str) neutralization and the [H⁺_str]/[SO₄^2-] molar ratio suggested the existence of bounded acidity in ammonium-rich (winter) conditions; and iii) significant correlations between LWC, WSOC, and secondary organics during post-monsoon and winter pointed towards a possible indirect role of WSOC in enhancing LWC of aerosol, thereby increasing pH. Given the inability of proxies such as H⁺_str and charge ratios to accurately represent aerosol pH as demonstrated here, this study emphasizes the need for rigorous thermodynamic model-based evaluation of aerosol acidity in the Indian scenario.

Assessment of long-term particulate nitrate air pollution and its health risk in China

Air pollution is a major environmental and public health challenge in China and the Chinese government has implemented a series of strict air quality policies. However, particulate nitrate (NO₃⁻) concentration remains high or even increases at monitoring sites despite the total PM_2.5 concentration has decreased. Unfortunately, it has been difficult to estimate NO₃⁻ concentration across China due to the lack of a PM_2.5 speciation monitoring network. Here, we use a machine learning model incorporating ground measurements and satellite data to characterize the spatiotemporal patterns of NO₃⁻, thereby understanding the disease burden associated with long-term NO₃⁻ exposure in China. Our results show that existing air pollution control policies are effective, but increased NO₃⁻ of traffic emissions offset reduced NO₃⁻ of industrial emissions. In 2018, the national mean mortality burden attributable to NO₃⁻ was as high as 0.68 million, indicating that targeted regulations are needed to control NO₃⁻ pollution in China.

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We build a NO₃⁻ model using machine learning techniques incorporating satellite data

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We estimate spatiotemporal variations of NO₃⁻ concentration in China from 2005–2018

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In 2018, the national mean mortality burden attributable to NO₃⁻ was about 0.68 million

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Targeted regulations on vehicle emissions are needed to control NO₃⁻ pollution in China

Aerosol liquid water content of PM2.5 and its influencing factors in Beijing, China

Aerosol liquid water content (ALWC) has important influences on atmospheric radiation and aerosol chemical processes. In this work, the changes in ALWC of PM_2.5 were investigated over four seasons based on hourly monitoring of inorganic water-soluble ions and their gaseous precursors using the thermodynamic model ISORROPIA II. The results showed that the ALWC concentrations exhibited pronounced seasonal (autumn > summer > spring > winter) and diurnal variation characteristics. The sensitivity tests indicated that ALWC depended strongly on TSO₄ (total sulfate (gas and aerosols) expressed as equivalent H₂SO₄), followed by TNO₃ (total nitrate (gas and aerosols) expressed as equivalent HNO₃). The relatively low concentration of TCl (total chloride (gas and aerosols) expressed as equivalent HCl) limit its importance in the atmosphere. ALWC showed exponential growth features as a function RH in all four seasons. RH became the most influential factor on the variation of ALWC when RH exceeded 80% in all seasons. The seasonal average data showed that the ALWC increased from 2.92 μg·m^-3 to 75.83 μg·m^-3 when ambient RH increased from 30% to 90%, the associated sulfate, nitrate, and ammonium (abbreviated as SNA) mass fraction in PM_2.5 rose from 0.39 to 0.58 in the atmosphere. The ALWC facilitated the formation of SNA through gas-particle conversion and partitioning. The self-amplifying processes between ALWC and SNA enhanced aerosol formation. By modeling ALWC under different seasonal atmospheric scenarios, it was found that reductions in chemical species could reduce ALWC concentrations in different degrees. Based on the current emission conditions, controlling excess NH₃ emission could effectively reduce ALWC to a maximum of 45.71% in summer, indicating that NH₃ control was crucial for reducing ALWC and PM_2.5 concentrations under high levels of SO₄^2- and NO₃^-.

Machine learning combined with the PMF model reveal the synergistic effects of sources and meteorological factors on PM2.5 pollution

PM_2.5 pollution is a complex process mainly affected by emission sources and meteorological conditions. However, it is hard to accurately assess the effects of emission sources and meteorological conditions on the variation of PM_2.5 concentrations in the complex atmospheric environment. In this study, the Random Forest model with Shapley Additive exPlanations (RF-SHAP) and Partial Dependence Plot (RF-PDP) was combined with Positive Matrix Factorization (PMF) to evaluate the impacts of various factors on PM_2.5 pollution. The results show that anthropogenic emissions and meteorological conditions contributed about 67% (40.5 μg/m³) and 33% (19.7 μg/m³) to variation in PM_2.5 concentrations, respectively. Specifically, secondary nitrate (SN) had the greatest impact among all sources (about 45%). Hence, we further explore the impacts of the primary sources and meteorological conditions on SN formation. Coal combustion and vehicle emissions significantly contribute to the formation of SN by providing a large number of precursor NO_X. Additionally, the RF-PDP method was further employed to estimate the synergistic effects of primary sources and meteorological conditions on SN formation. The results help reveal strategies to simultaneously reduce SN by controlling primary emissions under suitable meteorological conditions. This work also suggests that the machine learning model can utilize online datasets well and provide a reliable approach for analyzing the causes of PM_2.5 pollution.

Significant reduction in atmospheric organic and elemental carbon in PM2.5 in 2+26 cities in northern China

To better understand the change characteristics and reduction in organic carbon (OC) and elemental carbon (EC) in particulate matter (PM) with a diameter of ≤2.5 μm (PM_2.5) driven by the most stringent clean air policies and pandemic-related lockdown measures in China, a comprehensive field campaign was performed to measure the carbonaceous components in PM_2.5 on an hourly basis via harmonized analytical methods in the Beijing-Tianjin-Hebei and its surrounding region (including 2 + 26 cities) from January 1 to December 31, 2020. The results indicated that the annual average concentrations of OC and EC reached as low as 6.6 ± 5.7 and 1.8 ± 1.9 μg/m³, respectively, lower than those obtained in previous studies, which could be attributed to the effectiveness of the Clean Air Action Plan and the impact of the COVID-19-related lockdown measures implemented in China. Marked seasonal and diurnal variations in OC and EC were observed in the 2 + 26 cities. Significant correlations (p < 0.001) between OC and EC were found. The annual average secondary OC levels level ranged from 1.8-5.4 μg/m³, accounting for 37.7-73.0% of the OC concentration in the 2 + 26 cities estimated with the minimum R squared method. Based on Interagency Monitoring of Protected Visual Environments (IMPROVE) algorithms, the light extinction contribution of carbonaceous PM to the total amount reached 21.1% and 26.0% on average, suggesting that carbonaceous PM played a less important role in visibility impairment than did the other chemical components in PM_2.5. This study is expected to provide an important real-time dataset and in-depth analysis of the significant reduction in OC and EC in PM_2.5 driven by both the Clean Air Action Plan and COVID-19-related lockdown policies over the past few years, which could represent an insightful comparative case study for other developing countries/regions facing similar carbonaceous PM pollution.

Modeling particulate nitrate in China: Current findings and future directions

Particulate nitrate (pNO3) is now becoming the principal component of PM2.5 during severe winter haze episodes in many cities of China. To gain a comprehensive understanding of the key factors controlling pNO3 formation and driving its trends, we reviewed the recent pNO3 modeling studies which mainly focused on the formation mechanism and recent trends of pNO3 as well as its responses to emission controls in China. The results indicate that although recent chemical transport models (CTMs) can reasonably capture the spatial-temporal variations of pNO3, model-observation biases still exist due to large uncertainties in the parameterization of dinitrogen pentoxide (N2O5) uptake and ammonia (NH3) emissions, insufficient heterogeneous reaction mechanism, and the predicted low sulfate concentrations in current CTMs. The heterogeneous hydrolysis of N2O5 dominates nocturnal pNO3 formation, however, the contribution to total pNO3 varies among studies, ranging from 21.0% to 51.6%. Moreover, the continuously increasing PM2.5 pNO3 fraction in recent years is mainly due to the decreased sulfur dioxide emissions, the enhanced atmospheric oxidation capacity (AOC), and the weakened nitrate deposition. Reducing NH3 emissions is found to be the most effective control strategy for mitigating pNO3 pollution in China. This review suggests that more field measurements are needed to constrain the parameterization of heterogeneous N2O5 and nitrogen dioxide (NO2) uptake. Future studies are also needed to quantify the relationships of pNO3 to AOC, O3, NOx, and volatile organic compounds (VOCs) in different regions of China under different meteorological conditions. Research on multiple-pollutant control strategies involving NH3, NOX, and VOCs is required to mitigate pNO3 pollution, especially during severe winter haze events.

Heterogeneous Reaction of Peroxyacetyl Nitrate on Real-World PM2.5 Aerosols: Kinetics, Influencing Factors, and Atmospheric Implications

The formation and decomposition of peroxyacetyl nitrate (PAN), an important atmospheric nitrogen oxide reservoir, can impact the level and cycling of free radicals and nitrogen compounds in the atmosphere. PAN sinks are poorly understood, highlighting the importance of elucidating the heterogeneous reaction of PAN on aerosol surfaces. Here, we report for the first time the uptake behavior, kinetics, and potential mechanism of PAN uptake on real-world aerosol PM_2.5 using a flow tube system. The uptake coefficients (γ) of PAN increased non-linearly from (1.5 ± 0.7) × 10^-5 at 0% relative humidity (RH) to (9.3 ± 2.0) × 10^-5 at 80% RH. The γ decrease with increasing initial PAN concentration is consistent with the Langmuir-Hinshelwood mechanism. Organic components of aerosols may promote heterogeneous loss of PAN through redox reactions. Higher γ occurs with higher water content, lower pH, and lower ionic strength in the aqueous phase of aerosols. The present study suggests that heterogeneous reaction of PAN on ambient aerosols plays a non-negligible role in the atmospheric PAN budget and provides new insights into the role of PAN in promoting atmospheric oxidation capacity during hazy periods with cold and wet weather conditions.

Elevated Gaseous Oxidized Mercury Revealed by a Newly Developed Speciated Atmospheric Mercury Monitoring System

Gaseous oxidized mercury (Hg²⁺) monitoring is one of the largest challenges in the mercury research field, where existing methods cannot simultaneously satisfy the measurement requirements of both accuracy and time precision, especially in high-particulate environments. Here, we verified that dual-stage cation exchange membrane (CEM) sampler is incapable of gaseous elemental mercury (Hg⁰) uptake even if particulate matter is trapped on CEM, whereas the Hg²⁺ capture efficiency of the sampler is more than 90%. We then developed a Cation Exchange Membrane-Coupled Speciated Atmospheric Mercury Monitoring System (CSAMS) by coupling the dual-stage CEM sampler with the commercial Tekran 2537/1130/1135 system and configuring a new sampling and analysis procedure, so as to improve the monitoring accuracy of Hg²⁺ and ensure the simultaneous measurement of Hg⁰, Hg²⁺, and Hg_p in 2 h time resolution. We deployed the CSAMS in urban Beijing in September 2021 and observed an unprecedented elevated Hg²⁺ during the daytime with an average amplitude of 510 pg m^-3. Using a zero-dimensional box model, the elevated Hg²⁺ production rate was attributed to high atmospheric oxidant concentrations, Hg⁰ heterogeneous and interfacial oxidation processes on the surface of atmospheric particles, or potential unknown oxidants.

Variations and Sources of Organic Aerosol in Winter Beijing under Markedly Reduced Anthropogenic Activities During COVID-2019

The COVID-19 outbreak provides a "controlled experiment" to investigate the response of aerosol pollution to the reduction of anthropogenic activities. Here we explore the chemical characteristics, variations, and emission sources of organic aerosol (OA) based on the observation of air pollutants and combination of aerosol mass spectrometer (AMS) and positive matrix factorization (PMF) analysis in Beijing in early 2020. By eliminating the impacts of atmospheric boundary layer and the Spring Festival, we found that the lockdown effectively reduced cooking-related OA (COA) but influenced fossil fuel combustion OA (FFOA) very little. In contrast, both secondary OA (SOA) and O3 formation was enhanced significantly after lockdown: less-oxidized oxygenated OA (LO-OOA, 37% in OA) was probably an aged product from fossil fuel and biomass burning emission with aqueous chemistry being an important formation pathway, while more-oxidized oxygenated OA (MO-OOA, 41% in OA) was affected by regional transport of air pollutants and related with both aqueous and photochemical processes. Combining FFOA and LO-OOA, more than 50% of OA pollution was attributed to combustion activities during the whole observation period. Our findings highlight that fossil fuel/biomass combustion are still the largest sources of OA pollution, and only controlling traffic and cooking emissions cannot efficiently eliminate the heavy air pollution in winter Beijing.

Characterization of peroxyacetyl nitrate (PAN) under different PM2.5 concentration in wintertime at a North China rural site

As a secondary pollutant of photochemical pollution, peroxyacetyl nitrate (PAN) has attracted a close attention. A four-month campaign was conducted at a rural site in North China Plain (NCP) including the measurement of PAN, O₃, NO_x, PM_2.5, oxygenated volatile organic compounds (OVOCs), photolysis rate constants of NO₂ and O₃ and meteorological parameters to investigate the wintertime characterization of photochemistry from November 2018 to February 2019. The results showed that the maximum and mean values of PAN were 4.38 and 0.93 ± 0.67 ppbv during the campaign, respectively. The PAN under different PM_2.5 concentrations from below 75 μg/m³ up to 250 μg/m³, showed different diurnal variation and formation rate. In the PM_2.5 concentration range of above 250 μg/m³, PAN had the largest daily mean value of 0.64 ppbv and the fastest production rate of 0.33 ppbv/hr. From the perspective of PAN's production mechanism, the light intensity and precursors concentrations under different PM_2.5 pollution levels indicated that there were sufficient light intensity and high volatile organic compounds (VOCs) and NO_x precursors concentration even under severe pollution level to generate a large amount of PAN. Moreover, the bimodal staggering phenomenon of PAN and PM_2.5 provided a basis that PAN might aggravate haze through secondary organic aerosols (SOA) formation.

Exploring sources and health risks of metals in Beijing PM2.5: Insights from long-term online measurements

To gain a comprehensive understanding of sources, health risks, and regional transport of PM_2.5-bound metals in Beijing, one-year continuous measurement (K, Fe, Ca, Zn, Pb, Mn, Ba, Cu, As, Se, Cr, and Ni) was conducted from December 2016 to November 2017 and Positive Matrix Factorization analysis (PMF) was applied for source apportionment. It was found that the seasonal variation of sources could vary significantly among metals. Sources of Ca, Ba, As, Se, and Cr did not show much seasonal variations, with the contribution of its predominant source higher than 35% in each season. However, the major sources of K, Fe, Zn, Pb, Mn, Cu, and Ni exhibited obvious seasonal variations. In addition, the characteristics of metals in haze episodes were comprehensively investigated. Haze episodes in Beijing were characterized by higher metal concentrations and health risks, which were about 2- 6 times higher than non-haze periods. Moreover, the types of haze episode were different in winter and spring. Haze episodes in winter were mostly influenced by coal combustion, the contribution of which increased greatly and accounted for about 30% of PM_2.5. The metals such as K, Zn, Pb, As, and Se significantly increased, which were mainly transported from south of Beijing. During haze episodes in spring, dust was an important source, which contributed to higher concentrations of crustal metals that transported from northwest of Beijing. To quickly and effectively identify source regions of metals in Beijing during haze episodes, a new diagnostic ratio method using Ca as a reference was developed. The ratios of some anthropogenic metals to Ca significantly increased when air mass was mainly from south of Beijing during haze episodes while the ratios remained constantly low in non-haze periods, when local emissions dominated. This method could be useful for rapid identification and control of metal pollution in Beijing.

Composition and sources of particulate matter in the Beijing-Tianjin-Hebei region and its surrounding areas during the heating season

This paper aimed to analyze the composition and pollution sources of particulate matter (PM) in the Beijing-Tianjin-Hebei region and its surrounding areas (henceforth the BTH region) during the heating season to support the mitigation and control of regional air pollution. Manual monitoring data from the China National Environmental Monitoring Network for Atmospheric PM in the BTH region were collected and analyzed during the 2016 and 2018 heating seasons. The positive definite matrix factor analysis (PMF) model was used to analyze the PM sources in BTH cities during the heating season. The main PM components were organic matter (OM), nitrate (NO₃^-), sulfate (SO₄^2-) and ammonium salt (NH₄⁺). Direct emission sources have decreased since 2016, indicating the effectiveness of governmental controls on these sources; however, secondary pollution showed an increasing trend, suggesting control measures should be strengthened. Daily regional average concentrations of OM, SO₄^2-, NH₄⁺, elemental carbon (EC), chloride (Cl^-) and trace elements all showed similar trends. When air quality worsened, the concentrations of the main PM components increased, but trends of change varied among components. In 2018, concentrations of OM and chloride were highest in the Taihang Mountains, and NO₃ concentrations were highest in Anyang, Hebi, Jiaozuo and Xinxiang. The SO₄^2- concentration was highest in the southern section of the Taihang Mountains. The NH₄⁺ and EC concentrations were generally highest in the central and southern regions. The concentration of crustal substances was highest in some cities in the north and central parts of the BTH region. In the 2018 heating season, the pollution level of five transmission channels showed an increasing trend in the Northwest, Southeast, Yanshan, South and Taihang Mountain channels. These findings provide a scientific basis for the continued management of atmospheric PM pollution.

Numerical Simulation of Topography Impact on Transport and Source Apportionment on PM2.5 in a Polluted City in Fenwei Plain

The unique energy structure, high intensity of coal production, and complex terrain, make Fenwei Plain a highly polluted region in China. In this study, we characterized the transport characteristic and sources of PM2.5 (the fraction of particulate matter ≤ 2.5 μm) in Sanmenxia, a polluted city in canyon terrain. The results showed that special topography in Sanmenxia had an important role in the transport of particulates. Sanmenxia is located between two northeast-southwest facing mountains, showing a special local circulation. The local circulation was dominated by a downslope wind at nighttime, while the cross−mountain airflow and zonal wind were dominant during the daytime in the canyon terrain. PM2.5 accumulated near Sanmenxia with the influence of downslope, zonal wind, and topography. The main regional transport paths could be summarized into an eastern path, a northern path, and a western path during the severe haze episodes. The PM2.5 source apportionment revealed by an on-line tracer-tagged of the Nested Air Quality Prediction Model System (NAQPMS) showed that the main regional sources of Sanmenxia were Yuncheng, Sanmenxia, and Weinan. The contribution to PM2.5 concentration in Sanmenxia was 39%, 25%, and 11%, respectively. The northern path had the most important impact on Sanmenxia. The results can provide scientific basis for the establishment of severe haze control in Sanmenxia and regional joint control.