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The megacity of Beijing has experienced frequent severe fine particle pollution during the last decade. Although the sources and formation mechanisms of aerosol particles have been extensively investigated on the basis of ground measurements, real-time characterization of aerosol particle composition and sources above the urban canopy in Beijing is rare. In this study, we conducted real-time measurements of nonrefractory submicron aerosol (NR-PM1) composition at 260m at the 325m Beijing Meteorological Tower (BMT) from 10 October to 12 November 2014, by using an aerosol chemical speciation monitor (ACSM) along with synchronous measurements of size resolved NR-PM1 composition at near ground level using a High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS). The NR-PM1 composition above the urban canopy was dominated by organics (46 %), followed by nitrate (27 %) and sulfate (13 %). The high contribution of nitrate and high NO-3 =SO2-4 mass ratios illustrate an important role of nitrate in particulate matter (PM) pollution during the study period. The organic aerosol (OA) was mainly composed by secondary OA (SOA), accounting for 61% on an average. Different from that measured at the ground site, primary OA (POA) correlated moderately with SOA, likely suggesting a high contribution from regional transport above the urban canopy. The Asia-Pacific Economic Cooperation (APEC) summit with strict emission controls provides a unique opportunity to study the impacts of emission controls on aerosol chemistry. All aerosol species were shown to have significant decreases of 40-80% during APEC from those measured before APEC, suggesting that emission controls over regional scales substantially reduced PM levels. However, the bulk aerosol composition was relatively similar before and during APEC as a result of synergetic controls of aerosol precursors such as SO2, NOx, and volatile organic compounds (VOCs). In addition to emission controls, the routine circulations of mountain-valley breezes were also found to play an important role in alleviating PM levels and achieving the "APEC blue" effect. The evolution of vertical differences between 260m and the ground level was also investigated. Our results show complex vertical differences during the formation and evolution of severe haze episodes that are closely related to aerosol sources and boundary layer dynamics. [ABSTRACT FROM AUTHOR]

Accurate forecasting of PM2.5 concentrations serves as a critical tool for mitigating air pollution. This study introduces a novel hybrid prediction model, termed MIC-CEEMDAN-CNN-BiGRU, for short-term forecasting of PM2.5 concentrations using a 24-hour historical data window. Utilizing the Maximal Information Coefficient (MIC) for feature selection, the model integrates Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Convolutional Neural Network (CNN), and Bidirectional Recurrent Gated Neural Network (BiGRU) to optimize predictive accuracy. We used 2016 PM2.5 monitoring data from Beijing, China as the empirical basis of this study and compared the model with several deep learning frameworks. RNN, LSTM, GRU, and other hybrid models based on GRU, respectively. The experimental results show that the prediction results of the hybrid model proposed in this question are more accurate than those of other models, and the R2 of the hybrid model proposed in this paper improves the R2 by nearly 5 percentage points compared with that of the single model; reduces the MAE by nearly 5 percentage points; and reduces the RMSE by nearly 11 percentage points. The results show that the hybrid prediction model proposed in this study is more accurate than other models in predicting PM2.5. [ABSTRACT FROM AUTHOR]

During the "Parade Blue" period in 2015, Beijing and its surrounding areas implemented mandatory temporary source control strategies, which provided experimental conditions for studying the effects of source emission control measures on the sources of atmospheric PM2.5. Analyzing the source contribution rate of the main particulate matters via the source analysis method of the receptor model is an important method for studying the atmospheric pollution. Previous studies on the "Parade Blue" period only discussed the change in PM2.5 concentration during the source control period and the source non-control period, but did not select appropriate emission sources and acceptor components to analyze the contribution ratio of each emission source to fine particulate matter pollution. In this paper, based on the receptor component spectrum and emission source component spectrum, the chemical mass balance receptor model was used for source analysis. The results showed that outdoor PM2.5 concentration was 26.31 μg/m3 in the source control period, which was less than the 40.08 μg/m3 in the source non-control period. In the source control period, motor vehicle emissions, industrial combustion and urban fugitive dust contributed significantly to the fine particulate pollution, accounting for 76–81%, 8–9% and 11–16%, respectively. In the source non-control period, the contributions of motor vehicle emissions and industrial combustion accounted for 57–59% and 41–43%, respectively, significantly higher than that of urban fugitive dust, which accounted for less than 2%. The correlation between the contribution rate of emission sources and the source control strategy was studied and analyzed during the "Parade Blue" period, and the effectiveness of the source control strategy was proved. [ABSTRACT FROM AUTHOR]

Beijing suffers from poor air quality, particularly during wintertime haze episodes when concentrations of PM 2.5 (particulate matter with a diameter < 2.5 µ m) can peak at > 400 µ g m -3. Black carbon (BC), an aerosol which strongly absorbs solar radiation, can make up to 10 % of PM 2.5 in Beijing. BC is of interest due to its climatic and health impacts. BC has also been found to impact planetary boundary layer (PBL) meteorology. Through interacting with radiation and altering the thermal profile of the lower atmosphere, BC can either suppress or enhance PBL development depending on the properties and altitude of the BC layer. Previous research assessing the impact of BC on PBL meteorology has been investigated through the use of regional models, which are limited both by resolution and the chosen boundary layer schemes. In this work, we apply a high-resolution model (UCLALES-SALSA) that couples an aerosol and radiative transfer model with large-eddy simulation (LES) to quantify the impact of BC at different altitudes on PBL dynamics using conditions from a specific haze episode which occurred from 1–4 December 2016 in Beijing. Results presented in this paper quantify the heating rate of BC at various altitudes to be between 0.01 and 0.016 K/h per µ g/m 3 of BC, increasing with altitude but decreasing around PBL top. Through utilising a high-resolution model which explicitly calculates turbulent dynamics, this paper showcases the impact of BC on PBL dynamics both within and above the PBL. These results show that BC within the PBL increases maximum PBL height by 0.4 % but that the same loading of BC above the PBL can suppress PBL height by 6.5 %. Furthermore, when BC is present throughout the column, the impact of BC suppressing PBL development is further maximised, with BC causing a 17 % decrease in maximum PBL height compared to only scattering aerosols. Assessing the impact of these opposite effects, in this paper, we present a mechanism through which BC may play a prominent role in the intensity and longevity of Beijing's pollution episodes. [ABSTRACT FROM AUTHOR]

PM2.5 and PM10 in the atmosphere seriously affect human health and air quality, a situation which has aroused widespread concern. In this paper, we analyze the temporal and spatial distribution of PM2.5 and PM10 concentrations from 2016 to 2021 based on real-time monitoring data. In addition, we also explore the influence of meteorological conditions on pollutants. The results show that PM2.5 and PM10 concentrations are similarly distribution in temporal and spatial from 2016 to 2021, and the average concentrations of both show a decreasing trend. The ratio of PM2.5 to PM10 is decreasing, indicating that the proportion of fine particles is declining. PM2.5 and PM10 concentrations are higher in spring and winter, but lower in summer. Spatially, it shows a gradual shift from the characteristic of "high in the south and low in the north" to a uniform homogenization across districts. The spatial distribution of PM2.5 and PM10 mass concentrations is synchronous by applying empirical orthogonal functions (EOF). The first EOF pattern exhibits a consistent characteristic of high in the southeast and low in the northwest. The second pattern EOF reflects the effect of impairing PM2.5 concentrations in the southeast during the winter of 2016–2018. The PM2.5 and PM10 concentrations are significantly negatively correlated with wind speed and precipitation in both spring and winter. On the other hand, from the perspective of the circulation situation, the southeasterly and weak westerly wind in spring produce convergence resulting in higher particulate matter concentrations in the south than in the north in Beijing. The westerly wind is flatter at 700 hPa geopotential height, which is conducive to the formation of stationary weather. The vertical direction of airflow in spring and winter is dominated by convergence and sinking, indicating the weak dispersion ability of the atmosphere. The reason for the accumulation of particulate matter at the surface is investigated, which is beneficial to provide the theoretical basis for air quality management and pollution control in Beijing. [ABSTRACT FROM AUTHOR]

Over the past few decades, due to human activities, industrialization, and urbanization, air pollution has become a life-threatening factor in many countries around the world. Among air pollutants, Particulate Matter with a diameter of less than 2.5 μ m ( P M 2.5 ) is a serious health problem. It causes various illnesses such as respiratory tract and cardiovascular diseases. Hence, it is necessary to accurately predict the P M 2.5 concentrations in order to prevent the citizens from the dangerous impact of air pollution beforehand. The variation of P M 2.5 depends on a variety of factors, such as meteorology and the concentration of other pollutants in urban areas. In this paper, we implemented a deep learning solution to predict the hourly forecast of P M 2.5 concentration in Beijing, China, based on CNN-LSTM, with a spatial-temporal feature by combining historical data of pollutants, meteorological data, and P M 2.5 concentration in the adjacent stations. We examined the difference in performances among Deep learning algorithms such as LSTM, Bi-LSTM, GRU, Bi-GRU, CNN, and a hybrid CNN-LSTM model. Experimental results indicate that our method "hybrid CNN-LSTM multivariate" enables more accurate predictions than all the listed traditional models and performs better in predictive performance. [ABSTRACT FROM AUTHOR]

Wet scavenging is an efficient pathway for the removal of particulate matter (PM) from the atmosphere. High levels of PM have been a major cause of air pollution in Beijing but have decreased sharply under the Air Pollution Prevention and Control Action Plan launched in 2013. In this study, 4 years of observations of wet deposition have been conducted using a sequential sampling technique to investigate the detailed variation in chemical components through each rainfall event. We find that the major ions, SO 42- , Ca 2+ , NO 3- , and NH 4+ , show significant decreases over the 2013–2017 period (decreasing by 39 %, 35 %, 12 %, and 25 %, respectively), revealing the impacts of the Action Plan. An improved method of estimating the below-cloud scavenging proportion based on sequential sampling is developed and implemented to estimate the contribution of below-cloud and in-cloud wet deposition over the four-year period. Overall, below-cloud scavenging plays a dominant role to the wet deposition of four major ions at the beginning of the Action Plan. The contribution of below-cloud scavenging for Ca 2+ , SO 42- , and NH 4+ decreases from above 50 % in 2014 to below 40 % in 2017. This suggests that the Action Plan has mitigated PM pollution in the surface layer and hence decreased scavenging due to the washout process. In contrast, we find little change in the annual volume weighted average concentration for NO 3- where the contribution from below-cloud scavenging remains at ∼ 44 % over the 2015–2017 period. While highlighting the importance of different wet scavenging processes, this paper presents a unique new perspective on the effects of the Action Plan and clearly identifies oxidized nitrogen species as a major target for future air pollution controls. [ABSTRACT FROM AUTHOR]

Beijing, as a representative megacity in China, is experiencing some of the most severe air pollution episodes in the world, and its fast urbanization has led to substantial urban and peri-urban disparities in both health status and air quality. Uncertainties remain regarding the possible causal links between individual air pollutants and health outcomes, with spatial comparative investigations of these links lacking, particularly in developing megacities. In light of this challenge, Effects of AIR pollution on cardiopuLmonary disEaSe in urban and peri-urban reSidents in Beijing (AIRLESS) was initiated, with the aim of addressing the complex issue of relating multi-pollutant exposure to cardiopulmonary outcomes. This paper presents the novel methodological framework employed in the project, namely (1) the deployment of two panel studies from established cohorts in urban and peri-urban Beijing, with different exposure settings regarding pollution levels and diverse sources; (2) the collection of detailed measurements and biomarkers of participants from a nested case (hypertensive) and control (healthy) study setting; (3) the assessment of indoor and personal exposure to multiple gaseous pollutants and particulate matter at unprecedented spatial and temporal resolution with validated novel sensor technologies; (4) the assessment of ambient air pollution levels in a large-scale field campaign, particularly the chemical composition of particulate matter. Preliminary results showed that there is a large difference between ambient and personal air pollution levels, and the differences varied between seasons and locations. These large differences were reflected on the different health responses between the two panels. [ABSTRACT FROM AUTHOR]

Limited evidence was seen as the association between fine particulate matter (PM2.5) and physician visits for allergic rhinitis (AR), especially in countries with extreme air pollution exposure. This paper addressed the issues about the association between PM2.5 and daily outpatient visits for AR among individuals residing in Beijing, China. Data on daily outpatient visits for AR obtained from Beijing Medical Claim Data for Employees and daily PM2.5 concentrations available from US embassy reports were linked by date from January 1, 2010, to June 30, 2012. A time-series analysis was conducted with a generalized additive Poisson model to assess the association between PM2.5 and AR, adjusting for daily average temperature, relative humidity, day of the week, calendar time, and public holiday. Totally, 229,685 outpatient visits for AR were included in the analysis. The daily mean (SD) concentration of PM2.5 was 99.5 (75.3) μg/m3 during the study period. We found that a 10-μg/m3 increase in PM2.5 content was associated with a 0.47% (95% CI: 0.39% to 0.55%) increase in the number of outpatient visits on the same day. Furthermore, results from subgroup analyses suggested that the association was consistently significant among the groups of different ages (< 65 years and ≥ 65 years) and gender. However, this study failed to find a statistically significant association in the autumn season but found significant positive associations during the spring and summer seasons (P for interaction < 0.001). This study indicated a possible association between PM2.5 and AR outpatients, which may benefit further researches in studying PM2.5 and its influence on diseases in a real and seriously air-polluted context. [ABSTRACT FROM AUTHOR]

With the rapid development of industry, studies on lead pollution in total suspended particulate matter (TSP) have received extensive attention. This paper analyzed the concentration and pollution sources of lead in the Cuihu Wetland in Beijing during the period of 2016–2017. The results show that the lead contents in TSP in the Cuihu Wetland were approximately equal in summer and spring, greater in winter, and greatest in autumn. The corresponding lead concentrations were 0.052, 0.053, 0.101, and 0.115 ng/m³, respectively. We compared the 206Pb/207Pb data with other materials to further understand the potential sources of atmospheric lead. The mean values of 206Pb/207Pb from spring to winter were 1.082, 1.098, 1.092, and 1.078, respectively. We found that the lead sources may be associated with coal burning, brake and tire wear, and vehicle exhaust emissions. We also calculated the enrichment factor values for the four seasons, and the values were all much greater than 10, indicating that the lead pollution is closely related to human activities. [ABSTRACT FROM AUTHOR]

As major chemical components of airborne fine particulate matter (PM 2.5), organic carbon (OC) and elemental carbon (EC) have vital impacts on air quality, climate change, and human health. Because OC and EC are closely associated with fuel combustion, it is helpful for the scientific community and policymakers assessing the efficacy of air pollution control measures to study the impact of control measures and regional transport on OC and EC levels. In this study, hourly mass concentrations of OC and EC associated with PM 2.5 were semi-continuously measured from March 2013 to February 2018. The results showed that annual mean OC and EC concentrations declined from 14.0 to 7.7 µgm-3 and from 4.0 to 2.6 µgm-3 , respectively, from March 2013 to February 2018. In combination with the data of OC and EC in previous studies, an obvious decreasing trend in OC and EC concentrations was found, which was caused by clean energy policies and effective air pollution control measures. However, no obvious change in the ratios of OC and EC to the PM 2.5 mass (on average, 0.164 and 0.049, respectively) was recorded, suggesting that inorganic ions still contributed a lot to PM 2.5. Based on the seasonal variations in OC and EC, it appeared that higher OC and EC concentrations were still observed in the winter months, with the exception of winter of 2017–2018. Traffic policies executed in Beijing resulted in nighttime peaks of OC and EC, caused by heavy-duty vehicles and heavy-duty diesel vehicles being permitted to operate from 00:00 to 06:00 (China standard time, UTC + 8, for all times throughout the paper). In addition, the fact that there was no traffic restriction in weekends led to higher concentrations on weekends compared to weekdays. Significant correlations between OC and EC were observed throughout the study period, suggesting that OC and EC originated from common emission sources, such as exhaust of vehicles and fuel combustion. OC and EC levels increased with enhanced SO2 , CO, and NOx concentrations while the O3 and OC levels were enhanced simultaneously when O3 concentrations were higher than 50 µgm-3. Non-parametric wind regression analysis was performed to examine the sources of OC and EC in the Beijing area. It was found that there were distinct hot spots in the northeast wind sector at wind speeds of approximately 0–6 km h -1 , as well as diffuse signals in the southwestern wind sectors. Source areas further away from Beijing were assessed by potential source contribution function (PSCF) analysis. A high-potential source area was precisely pinpointed, which was located in the northwestern and southern areas of Beijing in 2017 instead of solely in the southern areas of Beijing in 2013. This work shows that improvement of the air quality in Beijing benefits from strict control measures; however, joint prevention and control of regional air pollution in the regions is needed for further improving the air quality. The results provide a reference for controlling air pollution caused by rapid economic development in developing countries. [ABSTRACT FROM AUTHOR]

Featured Application: This work has several applications: (a) to reveal spatiotemporal variations of PM2.5 across urban landscapes; (b) to assess the long-term impacts of PM2.5 on human health; (c) to support government policy decision-making; and (d) to provide valuable information to the public. High-spatiotemporal-resolution PM2.5 data are critical to assessing the impacts of prolonged exposure to PM2.5 on human health, especially for urban areas. Satellite-derived aerosol optical thickness (AOT) is highly correlated to ground-level PM2.5, providing an effective way to reveal spatiotemporal variations of PM2.5 across urban landscapes. In this paper, Multi-Angle Implementation of Atmospheric Correction (MAIAC) AOT and ground-based PM2.5 measurements were fused to estimate daily ground-level PM2.5 concentrations in Beijing for 2013–2017 at 1 km resolution through a linear mixed effect model (LMEM). The results showed a good agreement between the estimated and measured PM2.5 and effectively revealed the characteristics of its spatiotemporal variations across Beijing: (1) the PM2.5 level is higher in the central and southern areas, while it is lower in the northern and northwestern areas; (2) the PM2.5 level is higher in autumn and winter, while it is lower in spring and summer. Moreover, annual PM2.5 concentrations decreased by 24.03% for the whole of Beijing and 31.46% for the downtown area from 2013 to 2017. The PM2.5 data products we generated can be used to assess the long-term impacts of PM2.5 on human health and support relevant government policy decision-making, and the methodology can be applied to other heavily polluted urban areas. [ABSTRACT FROM AUTHOR]

Energy consumption has promoted a continuous development for economy and society, but it has also brought serious environmental pollution problems which endanger public health. In order to focus on the impact of PM 2.5 emissions from future energy consumption on human health better, this paper estimated PM 2.5 emissions caused by energy consumption in Beijing in 2020,2025 and 2030 by setting the baseline scenario, emission reduction scenario, intensified emission reduction scenario and the data of the base year 2015, which will be 162.6 thousand tons, 195.9 thousand tons and 235.9 thousand tons in the baseline scenario, 143.1 thousand tons, 151.8 thousand tons and 160.9 thousand tons under the emission reduction scenario, and 132.6 thousand tons, 130.2 thousand tons, 127.9 thousand tons under the intensified emission reduction scenario. Finally the paper measured the number of different health effect ends caused by PM 2.5 emissions and the economic loss. The results showed that there was a rapid increase, a mild increase and a moderate decrease in energy consumption and PM 2.5 emissions in Beijing under the three scenarios from 2015 to 2030. Besides, under the same scenario and the same concentration level baseline, the number of the internal medicine (over the age of 15) was the largest, and the economic loss caused by total death rate was the biggest. This article provides suggestions to reduce PM 2.5 emissions and public health effect ends for Beijing in the future. [ABSTRACT FROM AUTHOR]

Based on the mean sea level pressure field and 10-meter wind field across eastern China, weather patterns were classified using principal component analysis in the T-model (T-PCA), and four weather conditions were identified. Weather conditions and meteorological factors affecting the winter PM2.5 concentration in the Beijing–Tianjin–Hebei (BTH) region and the Yangtze River Delta (YRD) were also analyzed. The results showed that there were significant differences in the PM2.5 distribution between BTH and the YRD under different weather conditions. The intensity and path of cold air played important roles in regulating the PM2.5 concentration distribution in eastern China. For the BTH region, under type 2 and type 4 conditions, the weather was stable, and heavy pollution frequently occurred; however, under type 1 and type 3 conditions, cold air was active, and the air quality improved. For the YRD, both type 1 and type 4 conditions lead to high PM2.5 concentrations in this region. Type 1 cold air flows southward along the northwestern path and is beneficial for transporting pollutants from BTH to the YRD, causing a high probability of PM2.5 pollution. Conversely, the southward movement of type 3 cold air along the eastern path was beneficial for pollutant diffusion in the YRD. [ABSTRACT FROM AUTHOR]

Haze is a pollution phenomenon that has become increasingly frequent in recent years, primarily composed of SO2, NOx, and particulate matter. Since the “PM2.5 Crisis” in 2013, the Beijing-Tianjin-Hebei region has been plagued by haze. After a series of high-intensity management activities, the air quality in Beijing has continued to improve. To investigate the effectiveness of the haze control measures in Beijing, a dynamic management model was constructed using the system dynamics approach and implemented using Stella software. The model is simulated and evaluated the contribution to different governance strategies (increasing investment in science and technology innovation, reducing motor vehicle ownership, reducing coal consumption, and a combination policy) to reduce haze in Beijing from 2010 to 2025. The validity and robustness of the model were verified through model testing and validation. The simulation results showed that: (1) the combination policy has the most significant effect on reducing energy consumption and pollution emissions, which would reduce energy consumption by 38.93 million tons and pollution emissions by 128.33 thousand tons in 2025, (2) among the single treatment measures, reducing industrial coal consumption is the most effective measure to reducing haze, (3) it is necessary to strengthen the joint prevention and control of the Beijing-Tianjin-Hebei region in the future to promote the sustainable development of the regional environment. [ABSTRACT FROM AUTHOR]

Nitrogen oxide radicals (NOx≡NO+NO2) emitted by fuel combustion are important precursors of ozone and particulate matter pollution, and NO 2 itself is harmful to public health. The Geostationary Environment Monitoring Spectrometer (GEMS), launched in space in 2020, now provides hourly daytime observations of NO 2 columns over East Asia. This diurnal variation offers unique information on the emission and chemistry of NOx , but it needs to be carefully interpreted. Here we investigate the drivers of the diurnal variation in NO 2 observed by GEMS during winter and summer over Beijing and Seoul. We place the GEMS observations in the context of ground-based column observations (Pandora instruments) and GEOS-Chem chemical transport model simulations. We find good agreement between the diurnal variations in NO 2 columns in GEMS, Pandora, and GEOS-Chem, and we use GEOS-Chem to interpret these variations. NOx emissions are 4 times higher in the daytime than at night, driving an accumulation of NO 2 over the course of the day, offset by losses from chemistry and transport (horizontal flux divergence). For the urban core, where the Pandora instruments are located, we find that NO 2 in winter increases throughout the day due to high daytime emissions and increasing NO2/NOx ratio from entrainment of ozone, partly balanced by loss from transport and with a negligible role of chemistry. In summer, by contrast, chemical loss combined with transport drives a minimum in the NO 2 column at 13:00–14:00 local time (LT). Segregation of the GEMS data by wind speed further demonstrates the effect of transport, with NO 2 in winter accumulating throughout the day at low winds but flat at high winds. The effect of transport can be minimized in summer by spatially averaging observations over the broader metropolitan scale, under which conditions the diurnal variation in NO 2 reflects a dynamic balance between emission and chemical loss. [ABSTRACT FROM AUTHOR]

The PM 2.5 problem is proving to be a major public crisis and is of great public-concern requiring an urgent response. Information about, and prediction of PM 2.5 from the perspective of atmospheric dynamic theory is still limited due to the complexity of the formation and development of PM 2.5 . In this paper, we attempted to realize the relevance analysis and short-term prediction of PM 2.5 concentrations in Beijing, China, using multi-source data mining. A correlation analysis model of PM 2.5 to physical data (meteorological data, including regional average rainfall, daily mean temperature, average relative humidity, average wind speed, maximum wind speed, and other pollutant concentration data, including CO, NO 2 , SO 2 , PM 10 ) and social media data (microblog data) was proposed, based on the Multivariate Statistical Analysis method. The study found that during these factors, the value of average wind speed, the concentrations of CO, NO 2 , PM 10 , and the daily number of microblog entries with key words ‘Beijing; Air pollution’ show high mathematical correlation with PM 2.5 concentrations. The correlation analysis was further studied based on a big data's machine learning model- Back Propagation Neural Network (hereinafter referred to as BPNN) model. It was found that the BPNN method performs better in correlation mining. Finally, an Autoregressive Integrated Moving Average (hereinafter referred to as ARIMA) Time Series model was applied in this paper to explore the prediction of PM 2.5 in the short-term time series. The predicted results were in good agreement with the observed data. This study is useful for helping realize real-time monitoring, analysis and pre-warning of PM 2.5 and it also helps to broaden the application of big data and the multi-source data mining methods. [ABSTRACT FROM AUTHOR]

Persistent PM 2.5 pollution poses a serious threat to human health. Developing an accurate urban regional PM 2.5 forecasting is of practical significance for environmental protection. However, previous studies have mostly focused on individual monitoring stations, neglecting the influence of neighboring stations, which limits forecasting accuracy. Additionally, the PM 2.5 of a single monitoring station cannot reflect the overall situation of a region. Therefore, this paper develops a novel PM 2.5 spatiotemporal forecasting framework that combines graph convolutional module, temporal convolutional module, linear module. It enables the forecasting of PM 2.5 concentrations at multiple stations and multiple time steps in the future. Concretely, we utilize a mixed graph convolutional network to extract the spatial features of PM 2.5. Then, an improved temporal convolutional network, the second-order residual temporal convolutional network, is developed to capture complex temporal features. Following the classical "linear and non-linear" modeling strategy, a linear module is added to the forecasting framework. Experiments on the real air pollution dataset from Beijing demonstrate that our framework outperforms the state-of-the-art baselines. • Extracting and fusing spatiotemporal features of PM2.5 is crucial for prediction. • A novel spatiotemporal forecasting framework is proposed. • A second-order residual TCN is developed to extract complex temporal features. • Experiments on real air pollution dataset show our framework's superiority. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

PM2.5 concentration in Beijing China has become a focus for government and common people. It has been explored through source apportionment that heating generates significant influence on PM2.5 concentration in Beijing. However, there has still been great difficulty of quantitatively measuring the impact. In this paper, the author, taking PM2.5 in Beijing as research object, establishes a model of heating influence on PM2.5 emission. Data about the city's boiler number, distribution, fuel consumption as well as rural fuel consumption have been obtained through questionnaire. With the adoption of coefficients for producing and emitting pollutants, influence of heating factors in Beijing on PM2.5 concentration is evaluated quantitatively. High accuracy of the model in the paper has been proved through comparison with data of 2014 Beijing PM2.5 concentration monitored by Chinese Ministry of Environmental Protection. According to evaluation result 10.9, heating contributes to 13.7% of PM2.5 emission in Beijing, 9.9% and 3.8% from the six urban districts and rural areas respectively. It has been suggested that measures including decreasing heating temperature should be adopted to alleviate PM2.5 pollutions in Beijing. [ABSTRACT FROM AUTHOR]

Due to rapid urbanization and industrialization, atmospheric fine particulate matter (PM2.5) has become a primary urban pollutant, seriously affecting air quality and resident health. Existing airborne remote sensing and ground sensor monitoring can efficiently collect PM2.5 data. It is urgent yet challenging to fully use these two monitoring modes to analyze the spatial distribution and dynamic changes of PM2.5. This paper proposes a method to analyze the spatiotemporal characteristics of urban PM2.5 concentration using airborne and ground monitoring data. The method utilizes the boundary dimension and the radius dimension to describe the spatial distribution characteristics of PM2.5 and then adopts wavelet analysis to detect the fluctuation periods of PM2.5 concentration. Case study was performed based on the moderate-resolution imaging spectroradiometer (MODIS) data and the daily ground monitoring concentration of PM2.5 from 2014 to 2017 in Beijing. The decrease results of boundary dimension indicate that the changes in PM2.5 concentration tend to be slower over time, and the fluctuation amplitude gradually becomes smaller. The increase results closer to 2.0 in the radius dimensions suggest that the PM2.5 distribution becomes more uniform, indicating that the pollution control in Beijing had achieved initial success. The frequency results of wavelet analysis reveal that PM2.5 concentration in Beijing is mainly subject to periodic variation of 190 days. These findings can help us to gain deeper insight into the complex spatiotemporal characteristics of urban PM2.5. [ABSTRACT FROM AUTHOR]

Due to the advantage of high spatial coverage, using satellite-retrieved aerosol optical depth (AOD) data to estimate PM2.5 and PM10 mass concentrations is a current research priority. Statistical models are the common method of PM estimation currently, which do not require the knowledge of complex chemical and physical interactions. However, the statistical models rely on station data, which results in less accurate PM estimation concentrations in areas where station data are missing. Hence, a new hybrid model, with low dependency on on-site data, was proposed for PM2.5 and PM10 mass concentration estimation. The Gaofen-1 satellite and MODIS data were employed to estimate PM2.5 and PM10 concentrations with 100 m spatial resolution in Beijing, China. Then, the estimated PM2.5/10 mass concentration data in 2020 were employed to conduct a spatio-temporal analysis for the investigation of the particulate matter characteristic in Beijing. The estimation result of PM2.5 was validated by the ground stations with R2 ranging from 0.91 to 0.98 and the root mean square error (RMSE) ranging from 4.51 μg/m3 to 17.04 μg/m3, and that for PM10 was validated by the ground stations with R2 ranging from 0.85 to 0.98 and the RMSE ranging from 6.98 µg/m3 to 29.00 µg/m3. The results showed that the hybrid model has a good performance in PM2.5/10 estimation and can improve the coverage of the results without sacrificing the effectiveness of the model, providing more detailed spatial information for urban-scale studies. [ABSTRACT FROM AUTHOR]

The mechanism of aerosol pollution transport remains highly elusive owing to the myriad of influential factors. In this study, ground station data, satellite data, ground-based LiDAR remote sensing data, sounding data, ERA5 reanalysis and a backward trajectory model were combined to investigate the formation process and optical properties of winter aerosol pollution in Beijing and surrounding areas. The analysis of ground station data shows that compared to 2019 and 2021, the pandemic lockdown policy resulted in a decrease in the total number of pollution days and a decrease in the average concentration of particulate matter in the Beijing area in 2020. The terrain characteristics of the Beijing-Tianjin-Hebei (BTH) made it prone to northeast and southwest winds. The highest incidence of aerosol pollution in Beijing occurs in February and March during the spring and winter seasons. Analysis of a typical heavy aerosol pollution process in the Beijing area from 28 February to 5 March 2019 shows that dust and fine particulate matter contributed to the primary pollution; surface air temperature inversion and an average wind speed of less than 3 m/s were conducive to the continuous accumulation of pollutants, which was accompanied by the oxidation reaction of NO2 and O3, forming photochemical pollution. The heavy aerosol pollution was transmitted and diffused towards the southeast, gradually eliminating the pollution. Our results provide relevant research support for the prevention and control of aerosol pollution. [ABSTRACT FROM AUTHOR]

Fine particulate matter (PM 2.5) samples were collected between November 2020 and October 2021 at the Minzu University of China in Beijing, and the n -alkyl nitrate concentrations in the PM 2.5 samples were determined to investigate n -alkyl nitrate pollution and formation mechanisms. C 9 –C 16 n -alkyl nitrate standards were synthesized, and the n -alkyl nitrate concentrations in PM 2.5 were determined by gas chromatography triple quadrupole mass spectrometry. Temporal trends in and correlations between particulate-bound n -alkyl nitrate, ozone, PM 2.5 , and nitrogen dioxide concentrations were investigated to assess the relationships between particulate-bound n -alkyl nitrate concentrations and gas-phase homogeneous reactions in the photochemical process and speculate the particulate-bound n -alkyl nitrates' formation mechanisms. The n -alkyl nitrate concentrations in the PM 2.5 samples were 9.67–2730 pg m -3 , and the mean was 578 pg m -3. The n -alkyl nitrate homologue group concentrations increased as the carbon chain length increased; i.e., long-chain n -alkyl nitrates contributed more than short-chain n -alkyl nitrates to the total n -alkyl nitrate concentrations in PM 2.5. The n -alkyl nitrate concentrations clearly varied seasonally and diurnally, the concentrations decreasing in the order winter > spring > autumn > summer and the mean concentrations being higher at night than in the day. The particulate-bound n -alkyl nitrate and ozone concentrations significantly negatively correlated despite gas-phase alkyl nitrate and ozone concentrations previously being found to positively correlate. This indicated that long-chain alkyl nitrates may not be produced during gas-phase homogeneous reactions. The particulate-bound n -alkyl nitrate concentrations followed the same trends as and significantly positively correlated with the PM 2.5 and nitrogen dioxide concentrations. Nitrogen dioxide is an important contributor of nitrates in particulate matter. This indicated that particulate-bound n -alkyl nitrates may form through non-homogeneous reactions between alkanes and nitrates on particulate matter surfaces. As secondary pollutants, particulate-bound alkyl nitrates are important components of PM 2.5 during haze events and strongly affect haze pollution and atmospheric visibility. [ABSTRACT FROM AUTHOR]

This study examined the impact of temporary air quality control measures on reducing pollutants during the 2022 Winter Olympics in China, utilizing real-time monitoring data from 2017 and 2022 to assess spatial and temporal variations in critical air pollutant concentrations. The results showed that concentrations of PM2.5, PM10, CO, SO2, and NO2 in the Beijing–Tianjin–Hebei region during the Olympic Games showed a marked decrease compared to the historical period, with reductions of 36.59%, 20.35%, 33.95%, 28.90%, and 22.70%, respectively. Significant north–south spatial differences were observed in Beijing, Tianjin, and Hebei Province during the Olympic period. The cities of Zhangjiakou, Chengde, Qinhuangdao, Beijing, and Tangshan showed the most significant pollution reduction. Based on assessments conducted during the Olympic period, it was noted that more than 95% of the daily average concentrations of pollutants are below the maximum values set by the World Health Organization for the interim target. Our research shows that provisional regulations effectively control the emission of air pollutants, providing a solid reference and basis for ensuring air quality during major international events. [ABSTRACT FROM AUTHOR]

From 1990 to 2017, the number of vehicles in China increased sharply from 5 million to 310 million, and vehicle emissions became one of the major sources of air pollution. Among the main sources of PM 2.5 in Beijing, the contributions from vehicle sources increased from 5.6% (2000) to 31.1% (2012) to 45% (2017). In 2010, the CO, hydrocarbon (HC), NO x , and particulate matter (PM) emissions of yellow-label vehicles (YLVs) accounted for 46.1%, 47.9%, 63.1% and 86.1% of the total emissions from on-road vehicles. In recent years, China has been implementing a YLV scrappage subsidy policy to control air pollution, and this policy has cost several hundred billion yuan nationwide. However, China has not evaluated the costs and benefits of the policy. Many people question whether the YLV scrappage subsidy policy is worthwhile, but all the stakeholders involved complicate the process of accurately evaluating the true value of the policy. In this study, we evaluated and compared the costs and benefits of the policy in the Beijing-Tianjin-Hebei (BTH) region based on 1.362 million YLVs from 2008 to 2015. Because of the implementation of the policy, the PM 2.5 , PM 10 , NO x , CO and HC emissions in the BTH region decreased by 16.46, 18.12, 174.44, 669.11, and 91.64 kt, respectively, in 2008–2015. The results show that the policy played an important role in reducing pollutant emissions and improving environmental quality in the BTH region. The costs, benefits, and net benefits of the policy were 13.69, 34.03, and 20.34 billion yuan , respectively. The cost-benefit ratio in the BTH region was 1:2.49; at the city scale, Beijing ranked first (1:7.27), and the cost-benefit ratios of Tianjin and Hebei Province were 1:2.06 and 1:1.14, respectively. Of the 13 cities in the BTH region, Beijing had the highest net benefits, amounting to 16.43 billion yuan , while Handan City has the lowest net benefits, amounting to −0.58 billion yuan. The results may provide scientific support for the promotion of older vehicle and diesel vehicle scrappage subsidy policies, the development of cost-benefit analysis (CBA), and effective environmental decision-making in China. • Based on net number of scrappage YLVs, net benefits of the policy are calculated. • This paper estimates costs and benefits of the policy based on 1.27 million YLVs. • The costs, benefits, and net benefits are 13.69, 34.03, and 20.34 billion yuan. • The results help China promote vehicle scrappage subsidy policy on a large scale. • The results promote the development of the cost-benefit analysis in China. [ABSTRACT FROM AUTHOR]

The concentrations of fine particulate matter (PM) and ozone in Beijing often exceed healthful levels in recent years, therefore China is to taking steps to improve Beijing's air quality for the 2008 Olympic Games. In this paper, the Models-3 Community Multiscale Air Quality (CMAQ) Modeling System was used to investigate a heavy air pollution episode in Beijing during 3-7 April 2005 to obtain the basic information of how heavy air pollution formed and the contributions of local sources and surround emissions. The modeling domain covered from East Asia with four nested grids with 81 to 3 km horizontal resolution focusing on urban Beijing. This was coupled with a regional emissions inventory with a 10 km resolution and a local 1 km Beijing emissions database. The trend of predicted concentrations of various pollutants agreed reasonably well with the observations and captured the main features of this heavy pollution episode. The simulated column concentration distribution of PM was correlated well with the MODIS remote sensing products. Control runs with and without Beijing emissions were conducted to quantify the contributions of non-Beijing sources (NBS) to the Beijing local air pollution. The contributions of NBS to each species differed spatially and temporally with the order of PM2.5>PM10>SO2> soil for this episode. The percentage contribution of NBS to fine particle (PM2.5) in Beijing was averaged about 39%, up to 53% at the northwest of urban Beijing and only 15% at southwest. The spatial distribution of NBS contributions for PM10 was similar to that for PM2.5, with a slightly less average percentage of about 30%. The average NBS contributions for SO2 and soil (diameter between 2.5µm and 10µm) were 18% and 10%. In addition, the pollutant transport flux was calculated and compared at different levels to investigate transport pathway and magnitude. It was found that the NBS contribution correlated with the transport flux, contributing 60% of PM10 concentration in Beijing at the time of transport flux peak during a strong episode with a transport path from southwest to northeast. [ABSTRACT FROM AUTHOR]

Apparent temperature (AP) and ground-level aerosol pollution (PM 2.5) are important factors in human health, particularly in rapidly growing urban centers in the developing world. We quantify how changes in apparent temperature – that is, a combination of 2 m air temperature, relative humidity, surface wind speed, and PM 2.5 concentrations – that depend on the same meteorological factors along with future industrial emission policy may impact people in the greater Beijing region. Four Earth system model (ESM) simulations of the modest greenhouse emissions RCP4.5 (Representative Concentration Pathway), the "business-as-usual" RCP8.5, and the stratospheric aerosol intervention G4 geoengineering scenarios are downscaled using both a 10 km resolution dynamic model (Weather Research and Forecasting, WRF) and a statistical approach (Inter-Sectoral Impact Model Intercomparison Project – ISIMIP). We use multiple linear regression models to simulate changes in PM 2.5 and the contributions meteorological factors make in controlling seasonal AP and PM 2.5. WRF produces warmer winters and cooler summers than ISIMIP both now and in the future. These differences mean that estimates of numbers of days with extreme apparent temperatures vary systematically with downscaling method, as well as between climate models and scenarios. Air temperature changes dominate differences in apparent temperatures between future scenarios even more than they do at present because the reductions in humidity expected under solar geoengineering are overwhelmed by rising vapor pressure due to rising temperatures and the lower wind speeds expected in the region in all future scenarios. Compared with the 2010s, the PM 2.5 concentration is projected to decrease by 5.4 µ g m -3 in the Beijing–Tianjin province under the G4 scenario during the 2060s from the WRF downscaling but decrease by 7.6 µ g m -3 using ISIMIP. The relative risk of five diseases decreases by 1.1 %–6.7 % in G4, RCP4.5, and RCP8.5 using ISIMIP but has a smaller decrease (0.7 %–5.2 %) using WRF. Temperature and humidity differences between scenarios change the relative risk of disease from PM 2.5 such that G4 results in 1 %–3 % higher health risks than RCP4.5. Urban centers see larger rises in extreme apparent temperatures than rural surroundings due to differences in land surface type, and since these are also the most densely populated, health impacts will be dominated by the larger rises in apparent temperatures in these urban areas. [ABSTRACT FROM AUTHOR]

Determining accurate PM2.5 pollution concentrations and understanding their dynamic patterns are crucial for scientifically informed air pollution control strategies. Traditional reliance on linear correlation coefficients for ascertaining PM2.5-related factors only uncovers superficial relationships. Moreover, the invariance of conventional prediction models restricts their accuracy. To enhance the precision of PM2.5 concentration prediction, this study introduces a novel integrated model that leverages feature selection and a clustering algorithm. Comprising three components—feature selection, clustering, and integrated prediction—the model first employs the non-dominated sorting genetic algorithm (NSGA-III) to identify the most impactful features affecting PM2.5 concentration within air pollutants and meteorological factors. This step offers more valuable feature data for subsequent modules. The model then adopts a two-layer clustering method (SOM+K-means) to analyze the multifaceted irregularity within the dataset. Finally, the model establishes the Extreme Learning Machine (ELM) weak learner for each classification, integrating multiple weak learners using the AdaBoost algorithm to obtain a comprehensive prediction model. Through feature correlation enhancement, data irregularity exploration, and model adaptability improvement, the proposed model significantly enhances the overall prediction performance. Data sourced from 12 Beijing-based monitoring sites in 2016 were utilized for an empirical study, and the model's results were compared with five other predictive models. The outcomes demonstrate that the proposed model significantly heightens prediction accuracy, offering useful insights and potential for broadened application to multifactor correlation concentration prediction methodologies for other pollutants. [ABSTRACT FROM AUTHOR]

Urban vegetation can be viewed as compensation to the environmental drawbacks of urbanization. However, its ecosystem function is not well known and, for urban planning, vegetation is mainly considered as an element of urban design. This article argues that planning practice needs to re-examine the impact of vegetation cover in the urban fabric given our evaluation of vegetation’s effects on air quality, including the law. In this paper, we use the method of microclimate simulation in Beijing city as an example, using the three-dimensional microclimate model ENVI-met, to evaluate these effects. The results are summarized as follows: (1) the concentration of pollutants in the winter is generally greater than that of the summer, (2) higher wind speed favors ventilation inside the streets, reducing the concentration of particulate matter, and (3) block effect on particulate matter of different vegetations which corresponds to the structures are shrub and grass vegetation combine > bushes and trees combine > shrub > tree > no greenery. [ABSTRACT FROM AUTHOR]

Fine particulate matter (PM 2.5) pollution is still one of China's most important environmental issues, especially in northern cities during wintertime. In this study, intensive real-time measurement campaigns were conducted in Xi'an, Shijiazhuang, and Beijing to investigate the chemical characteristics and source contributions of PM 2.5 and explore the formation of heavy pollution for policy implications. The chemical compositions of PM 2.5 in the three cities were all dominated by organic aerosol (OA) and nitrate (NO 3-). Results of source apportionment analyzed by a hybrid environmental receptor model (HERM) showed that the secondary formation source contributed more to PM 2.5 compared to other primary sources. Biomass burning was the dominant primary source in the three pilot cities. The contribution of coal combustion to PM 2.5 is non-negligible in Xi'an and Shijiazhuang but is no longer an important contributor in the capital city of Beijing due to the execution of a strict coal-banning policy. The potential formation mechanisms of secondary aerosol in the three cities were further explored by establishing the correlations between the secondary formation sources and aerosol liquid water content (ALWC) and Ox (O3+NO2) , respectively. The results showed that photochemical oxidation and aqueous-phase reaction were two important pathways of secondary aerosol formation. According to source variations, air pollution events that occurred in campaigns were classified into three types: biomass-combustion-dominated, secondary-formation-source-dominated, and a combination of primary and secondary sources. Additionally, this study compares the changes in chemical composition and source contributions of PM 2.5 in past decades. The results suggest that the clean-energy replacements for rural households should be urgently encouraged to reduce the primary source emissions in northern China, and collaborative control on ozone and particulate matter needs to be continuously promoted to weaken the atmosphere oxidation capacity for the sake of reducing secondary aerosol formation. [ABSTRACT FROM AUTHOR]

New particle formation (NPF) and growth are a major source of atmospheric fine particles. In polluted urban environments, NPF events are frequently observed with characteristics distinct from those in clean environments. Here we simulate NPF events in urban Beijing with a discrete-sectional model that couples cluster dynamics and multicomponent particle growth. In the model, new particles are formed by sulfuric acid–dimethylamine nucleation, while particle growth is driven by particle coagulation and the condensation of sulfuric acid, its clusters, and oxygenated organic molecules (OOMs). A variable simulation domain in the particle size space is applied to isolate newly formed particles from preexisting ones, which allows us to focus on new particle formation and growth rather than the evolution of particles of non-NPF origin. The simulation yields a rich set of information including the time-dependent NPF rates, the cluster concentrations, the particle size distributions, and the time- and size-specific particle chemical compositions. These can be compared with the field observations to comprehensively assess the simulation–observation agreement. Sensitivity analysis with the model further quantifies how metrics of NPF events (e.g., particle survival probability) respond to model input variations and serves as a diagnostic tool to pinpoint the key parameter that leads to simulation–observation discrepancies. Seven typical NPF events in urban Beijing were analyzed. We found that with the observed gaseous precursor concentrations and coagulation sink as model inputs, the simulations roughly captured the evolution of the observed particle size distributions; however, the simulated particle growth rate was insufficient to yield the observed particle number concentrations, survival probability, and mode diameter. With the aid of sensitivity analysis, we identified under-detected OOMs as a likely cause for the discrepancy, and the agreement between the simulation and the observation was improved after we modulated particle growth rates in the simulation by adjusting the abundance of OOMs. [ABSTRACT FROM AUTHOR]

Beijing, the capital city of China, has achieved remarkable progress in terms of an improvement in air quality under strict control policies in the past 10 years from various sources. In this paper, the characteristics of fine particulate matter (PM2.5) and O3 in January 2013 and 2018 in Beijing are discussed on the basis of daily sample analysis and hourly monitoring data. It was found that the PM2.5 pollution for the month of January in Beijing has been greatly curbed. The SO42− concentration and proportion of PM2.5 decreased, while the proportions of NO3− and NH4+ increased. Organic matter represented the major component during the two periods with the proportions of 31.7% ± 8.2% and 31.4% ± 9.8%. The results of the Hybrid Single Particle Lagrangian Integrated Trajectory (Hysplit) model and Potential Source Contribution Function (PSCF) method showed that air mass from southern nearby regions accounted for 34% and 10% in 2013 and 2018, respectively, which was closely related to the pollution period. Thus, the input direction of air mass in January 2018 was more conducive to the diffusion of pollutants. Modeling results of the Weather Research and Forecasting model (WRF) coupled with Comprehensive Air Quality Model Extensions (CAMx) indicated that the contribution of industry sources to PM2.5 and O3 decreased from 2013 to 2018, while mobile sources increased. This was mainly due to the different control policies on various emission sources. In terms of O3 sources, more control measurements should be taken on volatile organic compounds (VOCs) due to its prominent effect on O3 concentration in both periods. The reduction in emissions and the meteorological conditions both contributed effectively to the sharp decrease in PM2.5 concentration. However, the change in weather conditions had the greater impact on the decrease in PM2.5 concentration, while the reduction in emissions was weakened as a function of this change. [ABSTRACT FROM AUTHOR]

Over the past decades, China has been facing severe airborne pollution associated with atmospheric fine particulate matter (PM 2.5 ). Much attention has been paid to the physical transport of PM 2.5 emissions. However, the embodied emissions, namely the emissions transferred through economic activities, have seldom been investigated. In this paper, embodied emission of PM 2.5 from each sector of Beijing is quantified based on input–output analysis (IOA). Forty-two economic sectors from the input–output table are aggregated into fifteen components. Furthermore, the mutual interactions and control relationship within those sectors have been revealed by using ecological network analysis (ENA) to identify the dominant sectors. The results show that, in 2010, 34% of the total PM 2.5 emissions, or 59.4 kt PM 2.5 , were indirect emissions traded through economic sectors within Beijing. According to the results of ENA, we found that “Smelting & Pressing of Metals“, “Metal Products” and “Nonmetal Mineral Products“ are the top three sectors with the highest control levels while “Agriculture”, “Catering Services” and “Residential Services” are the lowest-ranking sectors among the system. The network confirms that sectors related to heavy industry are the dominant sectors driving the embodied PM 2.5 emissions in the whole system. Compared to the conventional approaches for tracking PM 2.5 emissions, ENA may provide a practical way to reveal the mechanisms of embodied PM 2.5 emission flows via socioeconomic activities from a holistic perspective. [ABSTRACT FROM AUTHOR]

Background: Time-location information (time spent on commuting, indoors and outdoors around residential and work places and physical activity) and infiltrated outdoor pollution was less considered estimating individual exposure to ambient air pollution. Studies investigating the association between individual exposure to particulate matter (PM) with aerodynamic diameter < 10 μm (PM10) and < 2.5 μm (PM2.5) and carotid atherosclerosis presented inconsistent results. Moreover, combined effect of pollutants on carotid atherosclerosis was not fully explored. We aimed to investigate the association between long-term individual time-weighted average exposure to PM2.5 and PM10 and the risk of carotid atherosclerosis, and further explore the overall effect of co-exposure to pollutants on carotid atherosclerosis. Methods: The study population included 3069 participants derived from the Beijing Health Management Cohort (BHMC) study. Daily concentration of ambient air pollutants was estimated by land-use regression model at both residential and work addresses, and one- and two-year time-weighted average individual exposure was calculated by further considering personal activity pattern and infiltration of ambient air pollution indoors. We explored the association of PM2.5 and PM10 with carotid atherosclerosis and pooled the overall effect of co-exposure to ambient air pollutants by quantile g-computation. Results: A significant association between time-weighted average exposure to PM2.5 and PM10 and carotid atherosclerosis was observed. Per interquartile range increase in two-year exposure to PM2.5 (Hazard ratio (HR): 1.322, 95% confidence interval (CI): 1.219–1.434) and PM10 (HR:1.213, 95% CI: 1.116–1.319) showed the strongest association with carotid atherosclerosis, respectively. Individuals in higher quartiles of pollutants were at higher risk for carotid atherosclerosis compared with those in the lowest quartile group. Concentration response functions documented the nearly linear and nonlinear relationship and interpreted the upward trends of the risk for carotid atherosclerosis with increasing level of pollutant concentrations. Moreover, effect estimates for the mixture of pollutants and carotid atherosclerosis were larger than any of the individual pollutants (HR (95% CI) was 1.510 (1.338–1.704) and 1.613 (1.428–1.822) per quartile increase for one-year and two-year time-weighted average exposure, respectively). Conclusions: Individual time-weighted average exposure to PM2.5 and PM10 was associated with carotid atherosclerosis. Co-exposure to ambient air pollution was also positively associated with carotid atherosclerosis. [ABSTRACT FROM AUTHOR]

The high concentration of fine particles and gaseous pollutants makes polluted areas, such as the urban setting of North China Plain (NCP) of China, a different environment for new particle formation (NPF) compared to many clean regions. Such conditions also hold for other polluted environments in this region (for instance, the rural area of NCP), yet the underlying mechanisms for NPF remain less understood, owing to the limited observations of particles in the sub -3 nm range. Comprehensive measurements, particularly covering the particle number size distribution down to 1.3 nm, were conducted at a rural background site of Gucheng (GC) in the North China Plain (NCP) from 12 November to 24 December 2018. In total, five NPF events during the 39 effective days of measurements for the campaign were identified, with the mean particle nucleation rate (J1.3) and growth rate (GR 1.3–2.4) being 22.0 cm -3 s -1 and 3.9 nm h -1 , respectively. During these 5 d, NPF concurrently occurred at an urban site in Beijing. Sharing similar sources and transport paths of air masses arriving at our site to that of urban Beijing, we hypothesize that NPF events during these days in this region might be a regional phenomenon. The simultaneous occurrence of NPF in both places implies that H 2 SO 4 -amine nucleation, concluded for urban Beijing there, could probably be the dominating mechanism for NPF at our rural site. The higher concentration of sulfuric acid during many non-event days compared to that of event days indicates that the content of sulfuric acid may not necessarily lead to NPF events under current atmosphere. Only when the condensation sink or coagulation sink was significantly lowered, atmospheric NPF occurred, implying that condensation sinks (CSs) and coagulation sinks (CoagSs) are the dominating factors controlling the occurrence of NPF for the present rural environment of the NCP, which is quite similar to the feature seen in urban Beijing. [ABSTRACT FROM AUTHOR]

The impact of heterogeneous uptake of HO 2 on aerosol surfaces on radical concentrations and the O 3 production regime in Beijing in summertime was investigated. The uptake coefficient of HO 2 onto aerosol surfaces, γHO2 , was calculated for the AIRPRO campaign in Beijing, in summer 2017, as a function of measured aerosol soluble copper concentration, [Cu 2+ ] eff , aerosol liquid water content, [ALWC], and particulate matter concentration, [PM]. An average γHO2 across the entire campaign of 0.070±0.035 was calculated, with values ranging from 0.002 to 0.15, and found to be significantly lower than the value of γHO2=0.2 , commonly used in modelling studies. Using the calculated γHO2 values for the summer AIRPRO campaign, OH, HO 2 and RO 2 radical concentrations were modelled using a box model incorporating the Master Chemical Mechanism (v3.3.1), with and without the addition of γHO2 , and compared to the measured radical concentrations. The rate of destruction analysis showed the dominant HO 2 loss pathway to be HO 2 + NO for all NO concentrations across the summer Beijing campaign, with HO 2 uptake contributing <0.3 % to the total loss of HO 2 on average. This result for Beijing summertime would suggest that under most conditions encountered, HO 2 uptake onto aerosol surfaces is not important to consider when investigating increasing O 3 production with decreasing [PM] across the North China Plain. At low [NO], however, i.e. <0.1 ppb, which was often encountered in the afternoons, up to 29 % of modelled HO 2 loss was due to HO 2 uptake on aerosols when calculated γHO2 was included, even with the much lower γHO2 values compared to γHO2= 0.2, a result which agrees with the aerosol-inhibited O 3 regime recently proposed by Ivatt et al. (2022). As such it can be concluded that in cleaner environments, away from polluted urban centres where HO 2 loss chemistry is not dominated by NO but where aerosol surface area is high still, changes in PM concentration and hence aerosol surface area could still have a significant effect on both overall HO 2 concentration and the O 3 production regime. Using modelled radical concentrations, the absolute O 3 sensitivity to NO x and volatile organic compounds (VOCs) showed that, on average across the summer AIRPRO campaign, the O 3 production regime remained VOC-limited, with the exception of a few days in the afternoon when the NO mixing ratio dropped low enough for the O 3 regime to shift towards being NO x -limited. The O 3 sensitivity to VOCs, the dominant regime during the summer AIRPRO campaign, was observed to decrease and shift towards a NO x -sensitive regime both when NO mixing ratio decreased and with the addition of aerosol uptake. This suggests that if [NO x ] continues to decrease in the future, ozone reduction policies focussing solely on NO x reductions may not be as efficient as expected if [PM] and, hence, HO 2 uptake to aerosol surfaces continue to decrease. The addition of aerosol uptake into the model, for both the γHO2 calculated from measured data and when using a fixed value of γHO2=0.2 , did not have a significant effect on the overall O 3 production regime across the campaign. While not important for this campaign, aerosol uptake could be important for areas of lower NO concentration that are already in a NO x -sensitive regime. [ABSTRACT FROM AUTHOR]

On-road ammonia (NH 3) emissions play a significant role in fine particulate matter (PM 2.5) formation in urban areas, posing severe risks for human health. Limited studies have depicted the spatial and temporal variations of on-road NH 3 emissions, in particular lacking detailed quantification of their contributions within densely populated areas. In this study, we established a comprehensive vehicular NH 3 emission model and compiled a gridded on-road NH 3 emission inventory with high spatial (3 km × 3 km) and temporal (monthly) resolution for mainland China. China's annual vehicular NH 3 emissions are estimated to increase from 32.8 ± 1.7 to 87.1 ± 37.5 kt during the period of 2000–2019. Vehicular NH 3 emissions are significantly concentrated in densely populated areas, where agricultural emissions have relatively lower intensity. It is found that vehicular NH 3 emissions could exceed agricultural emissions in the grids containing 23.0 ± 2.1 % of the Chinese population in 2019 (approximately 326.6 ± 25.4 million people), and this ratio is up to 29.4 ± 3.0 % in winter. For extremely populous megacities such as Beijing and Shanghai, vehicular NH 3 emissions exceed agricultural emissions, where 69.2 ± 1.2 % and 72.0 ± 1.3 % of the population resides, respectively. Thus, the significant role of on-road NH 3 emissions in populated areas may have been underappreciated. This study gave a better insight into the absolute value and relative importance of on-road NH 3 emissions for different regions, seasons and population densities in China; this is important in terms of the implications for air quality. [ABSTRACT FROM AUTHOR]

The characteristics of n -alkanes and the contributions of various sources of fine particulate matter (PM 2.5) in the atmosphere in Beijing were investigated. PM 2.5 samples were collected at Minzu University of China between November 2020 and October 2021, and n -alkanes in the samples were analyzed by gas chromatography mass spectrometry. A positive matrix factorization analysis model and source indices (the main carbon peaks, carbon preference indices, and plant wax contribution ratios) were used to identify the sources of n -alkanes, to determine the contributions of different sources, and to explain the differences. The n -alkane concentrations were 4.51–153 ng m -3 (mean 32.7 ng m -3), and the particulate-bound n -alkane and PM 2.5 concentrations varied in parallel. There were marked seasonal and diurnal differences in the n -alkane concentrations (p<0.01). The n -alkane concentrations in the different seasons decreased in the order of winter > spring > summer > fall. The mean concentration of each homolog was higher at night than in the day in all seasons. Particulate-bound n -alkanes were supplied by common anthropogenic and biogenic sources, and fossil fuel combustion was the dominant contributor. The positive matrix factorization model results indicated five sources of n -alkanes in PM 2.5 , which were coal combustion, diesel vehicle emissions, gasoline vehicle emissions, terrestrial plant release, and mixed sources. Vehicle emissions were the main sources of n -alkanes, contributing 57.6 %. The sources of PM 2.5 can be indicated by n -alkanes (i.e., using n -alkanes as organic tracers). Vehicle exhausts strongly affect PM 2.5 pollution. Controlling vehicle exhaust emissions is key to controlling n -alkanes and PM 2.5 pollution in Beijing. [ABSTRACT FROM AUTHOR]

Measurements of the molecular composition of organic aerosol (OA) constituents improve our understanding of sources, formation processes, and physicochemical properties of OA. One instrument providing such data at a time resolution of minutes to hours is the chemical ionization time-of-flight mass spectrometer with filter inlet for gases and aerosols (FIGAERO-CIMS). The technique collects particles on a filter, which are subsequently desorbed, and the evaporated molecules are ionized and analyzed in the mass spectrometer. However, long-term measurements using this technique and/or field deployments at several sites simultaneously require substantial human and financial resources. The analysis of filter samples collected outside the instrument (offline) may provide a more cost-efficient alternative and makes this technology available for the large number of particle filter samples collected routinely at many different sites globally. Filter-based offline use of the FIGAERO-CIMS limits this method, albeit to particle-phase analyses, which is likely at a reduced time resolution compared to online deployments. Here we present the application and assessment of offline FIGAERO-CIMS, using Teflon and quartz fiber filter samples that were collected in autumn 2018 in urban Beijing. We demonstrate the feasibility of the offline application with a "sandwich" sample preparation for the over 900 identified organic compounds with (1) high signal-to-noise ratios, (2) high repeatability, and (3) linear signal response to the filter loadings. Comparable overall signals were observed between the quartz fiber and Teflon filters for 12 and 24 h samples but with larger signals for semi-volatile compounds for the quartz fiber filters, likely due to adsorption artifacts. We also compare desorption profile (thermogram) shapes for the two filter materials. Thermograms are used to derive volatility qualitatively based on the desorption temperature at which the maximum signal intensity of a compound is observed (Tmax⁡). While we find that Tmax⁡ can be determined with high repeatability (± 5.7 ∘ C) from the duplicate tests for one filter type, we observe considerable differences in Tmax⁡ between the quartz and Teflon filters, warranting further investigation into the thermal desorption characteristics of different filter types. Overall, this study provides a basis for expanding OA molecular characterization by FIGAERO-CIMS to situations where and when deployment of the instrument itself is not possible. [ABSTRACT FROM AUTHOR]

Air pollution has become an increasingly serious environmental problem in China. Especially in winter, the air pollution in northern China becomes even worse due to winter heating. The "coal to gas" policy, which uses natural gas to replace coal in the heating system in winter, was implemented in Beijing in the year 2013. However, the effects of this policy reform have not been examined. Using a panel dataset of 16 districts in Beijing, this paper employs a first difference model to examine the impact of the "coal to gas" policy on air quality. Strong evidence shows that the "coal to gas" policy has significantly improved the air quality in Beijing. On average, the "coal to gas" policy reduced sulfur dioxide ( SO 2 ), nitrogen dioxide ( NO 2 ), particulate matter smaller than 10 µm (PM10), particulate matter smaller than 2.5 µm (PM2.5) and carbon monoxide (CO) by 12.08%, 4.89%, 13.07%, 11.94% and 11.10% per year, respectively. We find that the "coal to gas" policy is more effective in areas with less energy use efficiency. The finding of this paper suggests that the government should continue to implement the "coal to gas" policy, so as to alleviate the air pollution in Beijing, China. [ABSTRACT FROM AUTHOR]

Perfluorohexane sulfonic acid (PFHxS), one of the substitutes for perfluorooctane sulfonic acid (PFOS), has been widely discussed around the world. In this study, the atmospheric concentrations of PFHxS in Beijing in the summer and autumn of 2021 were monitored, and the gas–particle partitioning and wet and dry deposition characteristics were analyzed. The results show that the average total concentrations of PFHxS in Beijing in the summer and autumn were 1.61 pg/m3 and 1.41 pg/m3, respectively. The particulate fraction φ of PFHxS was about 48% during the research period, and there was a significant positive correlation between φ and air temperatures. The linear fitting relationship between log K p (gas–particle partition coefficient) and log P L (compound vapor pressure) showed that the absorption between the PFHxS molecule and particulate matter dominated the process of gas–particle partitioning. The total deposition flux of PFHxS was the largest in July and the smallest in October, with values of 55.2 and 23.7 ng/m2, respectively. During the study period, PFHxS in the atmosphere had no obvious health impacts on humans. However, with their extensive use, the possible harmful effects on children should be continuously investigated. [ABSTRACT FROM AUTHOR]

Seasonal and diurnal characteristics of the vertical profiles of aerosol properties are essential for detecting the regional transport and the climatic radiative effects of aerosol particles. We have studied the seasonal and diurnal characteristics of the vertical distribution of aerosols in urban Beijing from 2017 to 2021 based on long-term Raman–Mie LiDAR observations. The influence of the vertical distribution of aerosols, the meteorological conditions within the boundary layer, the optical–radiometric properties of aerosols, and their interconnections, were investigated during a heavy haze pollution event in Beijing from 8 to 15 February 2020 using both meteorological and sun photometer data. The aerosol extinction coefficient was highest in summer (0.4 km−1), followed by winter (0.35 km−1), and roughly equal in spring and autumn (0.3 km−1). The aerosol extinction coefficient showed clear daily variations and was different in different seasons as a result of the variation in the height of the boundary layer. During the haze pollution event, the particulate matter mainly consisted of scattered spherical fine particles and the accumulation time of pollutants measured via the AOD440nm and PM2.5 mass concentration was different as a result of the hygroscopic growth of the aerosol particles. This growth increased scattering and led to an increase in the aerosol optical depth. The vertical transport of particulate matter also contributed to the increase in the aerosol optical depth. [ABSTRACT FROM AUTHOR]

Staggered-peak production (SP)—a measure to halt industrial production in the heating season—has been implemented in North China Plain to alleviate air pollution. We compared the variations of PM1 composition in Beijing during the SP period in the 2016 heating season (SPhs) with those in the normal production (NP) periods during the 2015 heating season (NPhs) and 2016 non-heating season (NPnhs) to investigate the effectiveness of SP. The PM1 mass concentration decreased from 70.0 ± 54.4 μg m−3 in NPhs to 53.0 ± 56.4 μg m−3 in SPhs, with prominent reductions in primary emissions. However, the fraction of nitrate during SPhs (20.2%) was roughly twice that during NPhs (12.7%) despite a large decrease of NOx, suggesting an efficient transformation of NOx to nitrate during the SP period. This is consistent with the increase of oxygenated organic aerosol (OOA), which almost doubled from NPhs (22.5%) to SPhs (43.0%) in the total organic aerosol (OA) fraction, highlighting efficient secondary formation during SP. The PM1 loading was similar between SPhs (53.0 ± 56.4 μg m−3) and NPnhs (50.7 ± 49.4 μg m−3), indicating a smaller difference in PM pollution between heating and non-heating seasons after the implementation of the SP measure. In addition, a machine learning technique was used to decouple the impact of meteorology on air pollutants. The deweathered results were comparable with the observed results, indicating that meteorological conditions did not have a large impact on the comparison results. Our study indicates that the SP policy is effective in reducing primary emissions but promotes the formation of secondary species. [ABSTRACT FROM AUTHOR]

Atmospheric new particle formation (NPF) events are regularly observed in urban Beijing, despite high concentrations of background particles which, based on theory, should inhibit NPF due to high values of coagulation sink (CoagS). The survival probability, which depends on both CoagS and particle growth rate (GR), is a key parameter in determining the occurrence of NPF events as it describes the fraction of newly formed particles that survive from a smaller diameter to a larger diameter. In this study, we investigate and compare survival probabilities from 1.5 to 3 nm (J3/J1.5), from 3 to 6 nm (J6/J3), and from 6 to 10 nm (J10/J6) based on analytical formulae, cluster population simulations, and atmospheric observations from Beijing. We find that survival probabilities based on the cluster population simulations and one of the analytical formulae are in a good agreement. However, at low ratios between the background condensation sink (CS) and GR, and at high concentrations of sub-3 nm clusters, cluster–cluster collisions efficiently lower survival probabilities in the cluster population simulations. Due to the large concentrations of clusters and small particles required to considerably affect the survival probabilities, we consider it unlikely that cluster–cluster collisions significantly affect atmospheric survival probabilities. The values of J10/J6 observed in Beijing show high variability, most likely due to influences of primary particle emissions, but are on average in relatively good agreement with the values based on the simulations and the analytical formulae. The observed values of J6/J3 are mostly lower than those predicted based on the simulations and the analytical formulae, which could be explained by uncertainties in CS and GR. The observed values of J3/J1.5 at high CS / GR are much higher than predicted based on the simulations and the analytical formulae. We argue that uncertainties in GR or CS are unlikely to solely explain the observed values of J3/J1.5 under high CS conditions. Thus, further work is needed to better understand the factors influencing survival probabilities of sub-3 nm atmospheric particles in polluted environments. [ABSTRACT FROM AUTHOR]

Here we present a field measurement of ClNO 2 (nitryl chloride) and N 2 O 5 (dinitrogen pentoxide) by a time-of-flight chemical ionization mass spectrometer (ToF-CIMS) with the Filter Inlet for Gas and AEROsols (FIGAERO) at a regional site in the Pearl River Delta during a photochemical pollution season from 26 September to 17 November 2019. Three patterns of air masses are sampled during this campaign, including the dominating air masses from the north and northeast urban regions (Type A), the southeast coast (Type B), and the South China Sea (Type C). The concentration of ClNO 2 and N 2 O 5 was observed to be much higher in Type A and B than in Type C, indicating that the urban nighttime chemistry is more active than the background marine regions. The N 2 O 5 uptake coefficient and ClNO 2 production yield were estimated based on the field measurement, and the performance of the previously derived parameterizations was assessed. The nighttime ClNO 2 correlated with particulate chloride and the mass concentration of fine particles (most likely due to aerosol surface area) suggested that the ClNO 2 formation was limited by the N 2 O 5 uptake at this site. By examining the relationship between particulate chloride and other species, we implied that anthropogenic emissions (e.g., biomass burning) rather than sea salt particles dominate the origin of particulate chloride, although the site was only about 100 km away from the ocean. A box model with detailed chlorine chemistry is used to investigate the impacts of ClNO 2 chemistry on atmospheric oxidation. Model simulations showed that the chlorine radical liberated by ClNO 2 photolysis during the next day had a slight increase in concentrations of OH, HO 2 , and RO 2 radicals, as well as minor contributions to RO 2 radical and O 3 formation (< 5 %, on daytime average), in all the three types of air masses. Relatively high contributions were observed in Type A and B. The overall low contributions of ClNO 2 to atmospheric oxidation are consistent with those reported recently from wintertime observations in China (including Shanghai, Beijing, Wangdu, and Mt. Tai). This may be attributed to the following: (1) relatively low particle mass concentration limited ClNO 2 formation; (2) other reactions channels, like nitrous acid (HONO), oxygenated volatile organic compounds (OVOCs, including formaldehyde), and ozone photolysis had a more significant radical formation rate during the ozone pollution episodes and weakened the ClNO 2 contribution indirectly. The results provided scientific insights into the role of nighttime chemistry in photochemical pollution under various scenarios in coastal areas. [ABSTRACT FROM AUTHOR]

Strict emission control policies implemented in two megacities of New York City (NYC) and Beijing show impacts on the non-linear relationship of their ozone (O3) and fine particulate matter (PM2.5) during summertime. Here we show these non-linear O3-PM2.5 relationships including a positive linear part reflecting the O3/PM2.5 co-occurrence and a negative power function part reflecting the O3 formation suppression by PM2.5 based on the multiyear surface observations. The control policies targeting sulfur dioxide and PM2.5, then volatile organic compounds and nitrogen oxides, changed the PM2.5 chemical composition which resulted in an increased linear slope that indicates a weaker O3 control effect than occurred for PM2.5. These policies also enhanced the relative PM2.5 suppression effect as shown by an increase in the power function coefficient. Model simulations suggest that regional equal percentage emission reductions for Beijing and other Chinese megacities will be necessary to avoid further increase in the O3/PM2.5 linear slope and continuing occurrences of high levels of ozone. [ABSTRACT FROM AUTHOR]

This study investigates the influence of the Chinese New Year (CNY) celebrations on local air quality in Beijing from 2013 through 2019. CNY celebrations include burning of fireworks and firecrackers, which consequently has a significant short-term impact on local air quality. In this study, we bring together comprehensive observations at the newly constructed Aerosol and Haze Laboratory at Beijing University of Chemical Technology – West Campus (BUCT-AHL) and hourly measurements from 12 Chinese government air quality measurement stations throughout the Beijing metropolitan area. These datasets are used together to provide a detailed analysis of air quality during the CNY over multiple years, during which the city of Beijing prohibited the use of fireworks and firecrackers in an effort to reduce air pollution before CNY 2018. Datasets used in this study include particulate matter mass concentrations (PM 2.5 and PM 10), trace gases (NO x , SO 2 , O 3 , and CO), and meteorological variables for 2013–2019; aerosol particle size distributions; and concentrations of sulfuric acid and black carbon for 2018 and 2019. Studying the CNY over several years, which has rarely been done in previous studies, can show trends and effects of societal and policy changes over time, and the results can be applied to study problems and potential solutions of air pollution resulting from holiday celebrations. Our results show that during the 2018 CNY, air pollutant concentrations peaked during the CNY night (for example, PM 2.5 reached a peak around midnight of over 250 µ g cm -3 , compared to values of less than 50 µ g cm -3 earlier in the day). The pollutants with the most notable spikes were sulfur dioxide, particulate matter, and black carbon, which are emitted in burning of fireworks and firecrackers. Sulfuric acid concentration followed the sulfur dioxide concentration and showed elevated overnight concentration. Analysis of aerosol particle number size distribution showed direct emissions of particles with diameters around 100 nm in relation to firework burning. During the 2019 CNY, the pollution levels were somewhat lower (PM 2.5 peaking at around 150 µ g cm -3 on CNY compared to values around 100 µ g cm -3 earlier in the day), and only minor peaks related to firework burning were observed. During both CNYs 2018 and 2019 secondary aerosol formation in terms of particle growth was observed. Meteorological conditions were comparable between these 2 years, suggesting that CNY-related emissions were less in 2019 compared to 2018. During the 7-year study period, it appears that there has been a general decrease in CNY-related emissions since 2016. For example, the peak in PM 2.5 in 2016 was over 600 µ g cm -3 , and in the years following, the peak was less each year, with a peak around 150 µ g cm -3 in 2019. This is indicative of the restrictions and public awareness of the air quality issues having a positive effect on improving air quality during the CNY. Going into the future, long-term observations will offer confirmation for these trends. [ABSTRACT FROM AUTHOR]

With a decrease in fine particulate matter (PM 2.5) due to the implementation of air pollution prevention-control measures, ozone (O 3) has risen in China especially in urban areas recently. It becomes more and more important to control air combined pollution with high concentration of PM 2.5 and O 3. We analyzed the characteristics of air combined pollution in Beijing from 2014 to 2019 in this paper. Results indicated that the trough O 3 showed an upward trend of 4.5 μg m−3 yr−1, while the peak decreased by −1.1 μg m−3 yr−1. There were three typical atmospheric chemical stages in the interaction between O 3 and PM 2.5 in summer through observations. The first was an intense photochemical stage with the synchronous and rapid growth of O 3 and PM 2.5. The O 3 concentration varied from 68 μg m−3 to 206 μg m−3 when PM 2.5 ≤ 35 μg m−3. While secondary inorganic ions (SNA) ranged from 2 to 21 μg m−3 especially SO 4 2− (0.8–12 μg m−3). The second was an aerosol chemical generation stage with the rapid increase of PM 2.5 and SNA under high O 3 concentration. O 3 was maintained at a high concentration between 198 μg m−3 and 241 μg m−3 when PM 2.5 was within the range of 35–125 μg m−3. SNA increased from 12 μg m−3 to 96 μg m−3. The third was a high PM 2.5 pollution stage suppressing the generation of O 3 when PM 2.5 ≥ 125 μg m−3. O 3 began to decline with the growth of PM 2.5 and decreased from 224 μg m−3 to 130 μg m−3. Ultraviolet radiation (UV) decreased from 13 MJ m−3 in the first to 8 MJ m−3 in this stage. [Display omitted] • The O 3 trough increased by 4.5 μg/m3 and the peak decreased by −1.1 μg/m3 per year in Beijing. • There were three typical processes in the interaction between O 3 and PM 2.5 in summer day. • The photochemical process was intense in dry-sunny days with the synchronous growth of O 3 and PM 2.5. • Aerosol chemical process intensified with a rapid growth of PM 2.5 and SNA in high O 3. • O 3 began to decline with the growth of PM 2.5 when PM 2.5 attenuated UV in a high level. [ABSTRACT FROM AUTHOR]

Atmospheric deposition is one of the main sources of dissolved iron (Fe) in the ocean surfaces. Atmospheric processes are recognized as controlling fractional Fe solubility (Fe sol %) in marine aerosol particles. However, the impact of these processes on Fe sol % remains unclear. One of the reasons for this is the lack of field observations focusing on the relationship between Fe sol % and Fe species in marine aerosol particles. In particular, the effects of organic ligands on Fe sol % have not been thoroughly investigated in observational studies. In this study, Fe species in size-fractionated aerosol particles in the Pacific Ocean were determined using X-ray absorption fine structure (XAFS) spectroscopy. The internal mixing states of Fe and organic carbon were investigated using scanning transmission X-ray microscopy (STXM). The effects of atmospheric processes on Fe sol % in marine aerosol particles were investigated based on the speciation results. Iron in size-fractionated aerosol particles was mainly derived from mineral dust, regardless of aerosol diameter, because the enrichment factor of Fe was almost 1 in both coarse (PM >1.3) and fine aerosol particles (PM 1.3). Approximately 80 % of the total Fe (insoluble + labile Fe) was present in PM >1.3 , whereas labile Fe was mainly present in PM 1.3. The Fe sol % in PM >1.3 was not significantly increased (2.56±2.53 %, 0.00 %–8.50 %, n=20) by the atmospheric processes because mineral dust was not acidified beyond the buffer capacity of calcite. In contrast, mineral dust in PM 1.3 was acidified beyond the buffer capacity of calcite. As a result, Fe sol % in PM 1.3 (0.202 %–64.7 %, n=10) was an order of magnitude higher than that in PM >1.3. The PM 1.3 contained ferric organic complexes with humic-like substances (Fe(III)-HULIS, but not Fe-oxalate complexes), and the abundance correlated with Fe sol %. Iron(III)-HULIS was formed during transport in the Pacific Ocean because Fe(III)-HULIS was not found in aerosol particles in Beijing and Japan. The pH estimations of mineral dust in PM 1.3 established that Fe was solubilized by proton-promoted dissolution under highly acidic conditions (pH < 3.0), whereas Fe(III)-HULIS was stabilized under moderately acidic conditions (pH 3.0–6.0). Since the observed labile Fe concentration could not be reproduced by proton-promoted dissolution under moderately acidic conditions, the pH of mineral dust increased after proton-promoted dissolution. The cloud process in the marine atmosphere increases the mineral dust pH because the dust particles are covered with organic carbon and Na. The precipitation of ferrihydrite was suppressed by Fe(III)-HULIS owing to its high water solubility. Thus, the organic complexation of Fe with HULIS plays a significant role in the stabilization of Fe that was initially solubilized by proton-promoted dissolution. [ABSTRACT FROM AUTHOR]