High-time-resolution PM2.5 source apportionment based on multi-model with organic tracers in Beijing during haze episodes

Source apportionment of particle-bound polycyclic aromatic hydrocarbons (PAHs), oxygenated PAHs (OPAHs), and their associated long-term health risks in a major European city

Many studies have drawn attention to the associations of oxygenated polycyclic aromatic hydrocarbons (OPAHs) with harmful health effects, advocating for their systematic monitoring alongside simple PAHs to better understand the aerosol carcinogenic potential in urban areas. To address this need, this study conducted an extensive PM2.5 sampling campaign in Athens, Greece, at the Thissio Supersite of the National Observatory of Athens, from December 2018 to July 2021, aiming to characterize the levels and variability of polycyclic aromatic compounds (PACs), perform source apportionment, and assess health risk. Cumulative OPAH concentrations (Σ-OPAHs) were in the same range as Σ-PAHs (annual average 4.2 and 5.6 ng m-3, respectively). They exhibited a common seasonal profile with enhanced levels during the heating seasons, primarily attributed to residential wood burning (RWB). The episodic impact of biomass burning was also observed during a peri-urban wildfire event in May 2021, when PAH and OPAH concentrations increased by a factor of three compared to the monthly average. The study period also included the winter 2020-2021 COVID-19 lockdown, during which PAH and OPAH levels decreased by >50 % compared to past winters. Positive matrix factorization (PMF) source apportionment, based on a carbonaceous aerosol speciation dataset, identified PAC sources related to RWB, local traffic (gasoline vehicles) and urban traffic (including diesel emissions), as well as an impact of regional organic aerosol. Despite its seasonal character, RWB accounted for nearly half of Σ-PAH and over two-thirds of Σ-OPAH concentrations. Using the estimated source profiles and contributions, the source-specific carcinogenic potency of the studied PACs was calculated, revealing that almost 50 % was related to RWB. These findings underscore the urgent need to regulate domestic biomass burning at a European level, which can provide concrete benefits for improving urban air quality, towards the new stricter EU standards, and reducing long-term health effects.

24-hour average PM2.5 concentration caused by aircraft in Chinese airports from Jan. 2006 to Dec. 2023

Since 2006, the rapid development of China's aviation industry has been accompanied by a significant increase in one of its emissions, namely, PM2.5, which poses a substantial threat to human health. However, little data is describing the PM2.5 concentration caused by aircraft activities. This study addresses this gap by initially computing the monthly PM2.5 emissions of the landing-take-off (LTO) stage from Jan. 2006 to Dec. 2023 for 175 Chinese airports, employing the modified BFFM2-FOA-FPM method. Subsequently, the study uses the Gaussian diffusion model to measure the 24-hour average PM2.5 concentration resulting from flight activities at each airport. This study mainly draws the following conclusions: Between 2006 and 2023, the highest recorded PM2.5 concentration data at all airports was observed in 2018, reaching 5.7985 micrograms per cubic meter, while the lowest point was recorded in 2022, at 2.0574 micrograms per cubic meter. Moreover, airports with higher emissions are predominantly located in densely populated and economically vibrant regions such as Beijing, Shanghai, Guangzhou, Chengdu, and Shenzhen.

High-time resolution PM2.5 source apportionment assisted by spectrum-based characteristics analysis

Characteristics extraction and anomaly analysis based on frequency spectrum can provide crucial support for source apportionment of PM2.5 pollution. In this study, an effective source apportionment framework combining the Fast Fourier Transform (FFT)- and Continuous Wavelet Transform (CWT)-based spectral analyses and Positive Matrix Factorization (PMF) receptor model is developed for spectrum characteristics extraction and source contribution assessment. The developed framework is applied to Beijing during the winter heating period with 1-h time resolution. The spectrum characteristics of anomaly frequency, location, duration and intensity of PM2.5 pollution can be captured to gain an in-depth understanding of source-oriented information and provide necessary indicators for reliable PMF source apportionment. The combined analysis demonstrates that the secondary inorganic aerosols make relatively high contributions (50.59 %) to PM2.5 pollution during the winter heating period in Beijing, followed by biomass burning, vehicle emission, coal combustion, road dust, industrial process and firework emission sources accounting for 15.01 %, 11.00 %, 10.70 %, 5.31 %, 3.88 %, and 3.51 %, respectively. The source apportionment result suggests that combining frequency spectrum characteristics with source apportionment can provide consistent rationales for understanding the temporal evolution of PM2.5 pollution, identifying the potential source types and quantifying the related contributions.

Sources and composition of elemental carbon during haze events in North China by a high time-resolved study

Despite the implementation of stringent emission reduction measures in the past year, severe winter haze events still occurred frequently in North China, with only marginal decreases observed in elemental carbon (EC) concentrations. EC not only constitutes a fraction of particle mass but also interacts with boundary layer and influences haze formation. Given the complex composition of EC, characterizing its sources and composition during haze processes is challenging yet crucial for understanding haze formation and evolution. Here, hourly-resolution PM2.5 samples were collected during three different haze event (P1-P3) in the North China Plain to investigate dynamic changes in EC source across different haze processes. The average EC concentrations and char/soot ratios were 9.94 ± 4.80 μgC·m-3, 14.5 ± 6.93 μgC·m-3, 15.9 ± 5.54 μgC·m-3, and 2.42 ± 0.98, 2.70 ± 0.88, 2.61 ± 0.95 for P1, P2 and P3, respectively. Backward trajectory analysis showed distinct variations in EC concentration and composition under the influence of different air masses during the three haze events, with local air masses influenced days exhibiting higher EC concentrations and char/soot ratios. The char/soot ratio based diagnostic method suggested that EC was predominantly influenced by coal combustion and vehicle emissions. Further positive matrix factorization analysis suggested that biomass burning and residential coal combustion were the main contributors of EC (58 %) and played a dominant role in driving variations in EC concentrations during haze episodes. Potential source contribution function analysis results highlight that local biomass burning and residential coal combustion could be major reason for the EC elevation in different haze events. Our results provide valuable insights into the sources and composition of EC during haze events, facilitating the implementation of effective measures for mitigating both EC and PM pollution.

Is biomagnetic leaf monitoring still an effective method for monitoring the heavy metal pollution of atmospheric particulate matter in clean cities?

The development of a reasonable method for predicting heavy metals (HMs) pollution in atmospheric particulate matter (PM) remains challenging. This paper presents an elution-filtration method to collect PM from the surface of Osmanthus fragrans in a very clean area (Guiyang, China). The aim is to evaluate the effectiveness of biomagnetic leaf monitoring as a simple and rapid method for assessing HMs pollution in clean cities. For this purpose, we determined the magnetic parameters and concentrations of selected HMs in PM samples to investigate their relationships. The results showed that the magnetic minerals in PM samples were mainly low coercivity ferrimagnetic minerals, with a small amount of high coercivity minerals. The types of magnetic minerals were generally single, and the magnetic domain state was pseudo-single domain (PSD). There was a significant correlation between magnetic parameters and the heavy metal (HM) concentrations in PM. Low-field magnetic susceptibility (χ) could be used as an ideal proxy for determining anthropogenic HM pollution. Traffic emissions were the main atmospheric pollution source in urban Guiyang. Due to the incomplete traffic network and large traffic flow, traffic congestion (TC) often occurred at road intersections in the northwest and southwest corners of the city, resulting in the highest concentration of magnetic minerals and the most severe PM pollution. To mitigate atmospheric PM pollution and protect public health, it is strongly recommended that municipal authorities prioritize urban planning and traffic management to address TC. Measures should be implemented urgently to alleviate stop-and-go traffic.

High-spatiotemporal-resolution mapping of PM2.5 traffic source impacts integrating machine learning and source-specific multipollutant indicator

Traffic sources are a major contributor to fine particulate matter (PM2.5) pollution, with their emissions and diffusion exhibiting complex spatiotemporal patterns. Receptor models have limitations in estimating high-resolution source contributions due to insufficient observation networks of PM2.5 compositions. This study developed a source apportionment method that integrates machine learning and emission-based integrated mobile source indicator (IMSI) to rapidly and accurately estimate PM2.5 traffic source impacts with high spatiotemporal resolution in the Beijing-Tianjin-Hebei region. Firstly, we utilized multisource data and developed various machine learning models to optimize the traffic-related pollutant concentration fields simulated by a chemical transport model. Results demonstrated that the Extreme Gradient Boosting (XGBoost) model exhibited excellent prediction accuracy of nitrogen oxide (NO2), carbon oxide (CO), and elemental carbon (EC), with the cross-validated R values increasing to 0.87-0.92 and error indices decreasing by 50-67%. Furthermore, we estimated and predicted daily mappings of PM2.5 traffic source impacts using the IMSI method based on optimized concentration fields, which improved spatially resolved source contributions to PM2.5. Our findings reveal that PM2.5 traffic source impacts display significant spatial heterogeneity, and these hotspots can be precisely identified during the pollution processes with sharp changes. The evaluation results indicated that there is a good correlation (R of 0.79) between PM2.5 traffic source impacts by IMSI method and traffic source contributions apportioned by a receptor model at Beijing site. Our study provides deeper insights of estimating the spatiotemporal distribution of PM2.5 source-specific impacts especially in regions without PM2.5 compositions, which can provide more complete and timely guidance to implement precise air pollution management strategies.

Insights into quantitative evaluation technology of PM2.5 transport at multi-perspective and multi-spatial and temporal scales in the north China plain

Cross-border transport is a crucial factor affecting air quality, while how to quantify the transport contribution through different technologies at multi-perspective and multi-scale have not been fully understood. This study established three quantification techniques, and conducted a systematic assessment of PM2.5 transport over the North China Plain (NCP) based on numerical simulations and vertical observations. Results suggested that the annual local emissions, inter-urban and outer-regional transport contributed 44.5%-64.6%, 15.2%-27.9% and 18.0%-28.2% of total surface PM2.5 concentrations, respectively, with transport intensity stronger in July and April, yet weaker in January and October. The southwest-northeast, northeast-southwest, and southeast-northwest were three prevailing transport directions near the surface. By comparison, the annual PM2.5 transport contribution below the atmospheric boundary layer height increased by 16.8%-24.5% in Beijing, Tianjin and Shijiazhuang, with inter-urban and outer-regional contribution of 29.8%-32.1% and 18.5%-23.1%. Furthermore, observed fluxes from fixed-point and vehicle-based mobile lidar were in good agreement with the simulated flux. PM2.5 net flux intensity varied with height, with generally larger at the middle- and high-altitude layer than that of low-altitude layer. In the early, during and late period of haze peak formation (Stage Ⅰ, Ⅱ, Ⅲ, respectively), the largest absolute flux intensity on average was Stage Ⅱ (566.7 t/d), followed by Stage Ⅲ (307.0 t/d) and Ⅰ (191.4 t/d). Besides, external transport may dominate the second concentration peak, while local emissions may play a more vital role in the first and third peaks. It has been noted that joint prevention and control measures should be proposed 1-2 days before reaching PM2.5 extremes. These findings could improve our understanding of transport influence mechanism of PM2.5 and propose effective emission reduction measures in the NCP region.

Particulate organic emissions from incense-burning smoke: Chemical compositions and emission characteristics

Incense burning is a common practice in Asian cultures, releasing hazardous particulate organics. Inhaling incense smoke can result in adverse health effects, yet the molecular compositions of incense-burning organics have not been well investigated due to the lack of measurement of intermediate-volatility and semi-volatile organic compounds (I/SVOCs). To elucidate the detailed emission profile of incense-burning particles, we conducted a non-target measurement of organics emitted from incense combustion. Quartz filters were utilized to trap particles, and organics were analyzed by a comprehensive two-dimensional gas chromatography-mass spectrometer (GC × GC-MS) coupled with a thermal desorption system (TDS). To deal with the complex data obtained by GC × GC-MS, homologs are identified mainly by the combination of selected ion chromatograms (SICs) and retention indexes. SICs of 58, 60, 74, 91, and 97 were utilized to identify 2-ketones, acids, fatty acid methyl esters, fatty acid phenylmethyl esters, and alcohols, respectively. Phenolic compounds contribute the most to emission factors (EFs) among all chemical classes, taking up 24.5 % ± 6.5 % of the total EF (96.1 ± 43.1 μg g-1). These compounds are largely derived from the thermal degradation of lignin. Biomarkers like sugars (mainly levoglucosan), hopanes, and sterols are extensively detected in incense combustion fumes. Incense materials play a more important role in shaping emission profiles than incense forms. Our study provides a detailed emission profile of particulate organics emitted from incense burning across the full-volatility range, which can be used in the health risk assessments. The data processing procedure in this work could also benefit those with less experience in non-target analysis, especially GC × GC-MS data processing.

Aqueous-Phase Reactions of Anthropogenic Emissions Lead to the High Chemodiversity of Atmospheric Nitrogen-Containing Compounds during the Haze Event

Nitrogen-containing organic compounds (NOCs), a type of important reactive-nitrogen species, are abundant in organic aerosols in haze events observed in Northern China. However, due to the complex nature of NOCs, the sources, formation, and influencing factors are still ambiguous. Here, the molecular composition of organic matters (OMs) in hourly PM2.5 samples collected during a haze event in Northern China was characterized using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). We found that CHON compounds (formulas containing C, H, O, and N atoms) dominated the OM fractions during the haze and showed high chemodiversity and transformability. Relying on the newly developed revised-workflow and oxidation-hydrolyzation knowledge for CHON compounds, 64% of the major aromatic CHON compounds (>80%) could be derived from the oxidization or hydrolyzation processes. Results from FT-ICR MS data analysis further showed that the aerosol liquid water (ALW)-involved aqueous-phase reactions are important for the molecular distribution of aromatic-CHON compounds besides the coal combustion, and the ALW-involved aromatic-CHON compound formation during daytime and nighttime was different. Our results improve the understanding of molecular composition, sources, and potential formation of CHON compounds, which can help to advance the understanding for the formation, evolution, and control of haze.

Spatiotemporal characteristics of air pollutants and their associated health risks in '2+26' cities in China during 2016-2020 heating seasons

To understand characteristics of air pollutants and their associated health risks in recent heating seasons in China, ambient monitoring data of six air pollutants in '2 + 26' cities in Beijing-Tianjin-Hebei and its surrounding areas (known as the BTH2+26 cities) during 2016-2020 heating seasons was analyzed. Results show that daily average concentrations of PM2.5, PM10, SO2, NO2, and CO dropped significantly in BTH2+26 cities from the 2016-2017 heating season to 2019-2020 heating season, while 8h O3 increased markedly. During 2016-2020 heating seasons, annual average values of total excess risks (ERtotal) were 2.3% mainly contributed by PM2.5 (54.4%) and PM10 (36.1%). With PM2.5 pollution worsening, PM10 and NO2 were the important contribution factors of the enhanced ERtotal. Higher health-risk based air quality index (HAQI) values were mainly concentrated in the western Hebei and northern Henan. HAQI showed spatial agglomeration effect in four heating seasons. Impact factors of HAQI varied in different heating seasons. These findings can provide useful insights for China to further propose effective control strategies to alleviate air pollution in the future.

Source apportionment of PM2.5 using organic/inorganic markers and emission inventory evaluation in the East Mediterranean-Middle East city of Beirut

Source contributions to PM_2.5 concentrations were evaluated in Greater Beirut (Lebanon), a typical East Mediterranean-Middle East (EMME) city, using Positive Matrix Factorization with two approaches. The first approach included only inorganic species (PMF-trad) and the other approach added organic markers (PMF-org). PMF-org identified 4 additional sources, and large discrepancies in contributions were observed for some major sources found in both approaches, highlighting the importance of including organic markers. The traffic factor was underestimated in PMF-trad by 2 to 7 folds. Moreover, results showed that this city is prone to high desert dust concentrations originating from uncontrollable dust storm events, like all cities in the Middle East. A PM_2.5 mitigation plan taking into account the potency of the identified sources was developed. Sources like diesel generators or traffic presented smaller contributions in term of mass compared to desert dust, however the health impact of the latter is relatively small and actions should target sources with the highest potency. Local emission inventories in the EMME region are scarce and studies typically rely on global emission inventories for local air quality management plans, but these inventories significantly underestimate Beirut's road transport emissions by more than an order of magnitude.

Exploring the contributions of major emission sources to PM2.5 and attributable health burdens in China

Ambient fine particulate matter (PM_2.5) pollution is the principal environmental risk factor for health burdens in China. Identifying the sectoral contributions of pollutant emissions sources on multiple spatiotemporal scales can help in the formulation of specific strategies. In this study, we used sensitivity analysis to explore the specific contributions of seven major emission sources to ambient PM_2.5 and attributable premature mortality across mainland China. In 2016, about 60% of China's population lived in areas with PM_2.5 concentrations above the Chinese Ambient Air Quality Standard of 35 μg/m³. This percentage was expected to decrease to 35% and 39% if industrial and residential emissions were fully eliminated. In densely populated and highly polluted regions, residential sources contributed about 50% of the PM_2.5 exposure in winter, while industrial sources contributed the most (29-51%) in the remaining seasons. The three major sectoral contributors to PM_2.5-related deaths were industry (247,000 cases, 35%), residential sources (219,000 cases, 31%), and natural sources (87,000, 12%). The relative contributions of the different sectors varied in the different provinces, with industrial sources making the largest contribution in Shanghai (65%), while residential sources predominated in Heilongjiang (63%), and natural sources dominated in Xinjiang (82%). The contributions of the agricultural (11%), transportation (6%), and power (3%) sources were relatively low in China, but emissions mitigation was still effective in densely populated areas. In conclusion, to effectively alleviate health burdens across China, priority should be given to controlling residential emissions in winter and industrial emissions all year round, taking additional measures to curb emissions from other sources in urban hotspots, and formulating air pollution control strategies tailored to local conditions.

Oxidative Potential Characterization of Different PM2.5 Sources and Components in Beijing and the Surrounding Region

With the implementation of air pollution control measures, the concentration of air pollutants in the North China Plain has exhibited a downward trend, but severe fine particulate matter (PM_2.5) pollution remains. PM_2.5 is harmful to human health, and the exploration of its source characteristics and potential hazards has become the key to mitigating PM_2.5 pollution. In this study, PM_2.5 samples were collected in Beijing and Gucheng during the summer of 2019. PM_2.5 components, its oxidative potential (OP), and health risks were characterized. The average PM_2.5 concentrations in Beijing and Gucheng during the sampling period were 34.0 ± 6.1 μg/m³ and 37.1 ± 6.9 μg/m³, respectively. The principal component analysis (PCA) results indicated that the main sources of PM_2.5 in Beijing were vehicle exhaust and secondary components and that the main sources in Gucheng were industrial emissions, dust and biomass combustion. The OP values were 91.6 ± 42.1 and 82.2 ± 47.1 pmol/(min·m³), respectively, at these two sites. The correlation between the chemical components and the OP values varied with the PM_2.5 sources at these two locations. The health risk assessment results demonstrated that Cr and As were potentially carcinogenic to all populations at both sites, and Cd posed a potential carcinogenic risk for adults in Gucheng. Regional cooperation regarding air pollution control must be strengthened to further reduce PM_2.5 pollution and its adverse health effects.

Diesel exhaust PM2.5 greatly deteriorates fibrosis process in pre-existing pulmonary fibrosis via ferroptosis

Fine particulate matter (PM2.5) has been widely reported to contribute to the pathogenesis of pulmonary diseases. The direct hazardous effect of PM2.5 on the respiratory system at high concentrations in vitro and in vivo have been well identified. However, its effect on the pre-existing respiratory diseases of patients at environment-related concentrations remains unclear. Diesel exhaust PM2.5 as a primary representative of ambient PM2.5 fine particles were used to investigated the effect of PM2.5 on the fibrosis progression of existing pulmonary fibrosis disease models. This study reported that PM2.5 could result in the enhanced sensitivity to fibrotic response, which may be ascribed to ferroptosis induced by PM2.5 in damaged lung areas. Proteomic analysis revealed that the upregulation of HO-1 as a key mechanism in the ferroptosis and exacerbation of pulmonary fibrosis induced by PM2.5. As a result, HO-1 degraded heme-containing protein and released iron in fibrotic cells, leading to generation of mitochondrial ROS and impaired mitochondrial function. Transmission electron microscopic assay verified that PM2.5 entered the mitochondria of fibrotic cells and was accompanied by significant mitochondrial morphological changes characterized by increased mitochondrial membrane density and reduced mitochondrial size. The HO-1 inhibitor zinc protoporphyrin and mitochondrion-targeted antioxidant Mito-TEMPO significantly attenuated PM2.5-induced ferroptosis and exacerbation of fibrosis. In addition, AMPK-ULK1 axis-triggered autophagy activation and NCOA4-mediated degradation of ferritin by autophagy were found to be related to the PM2.5-induced ferroptosis of fibrotic cells. As evidenced by the inhibition of autophagy with 3-methyladenine or AMPK inhibitor, NCOA4 knockdown decreased intracellular iron accumulation and lipid peroxidation, thereby relieving PM2.5-induced epithelial-mesenchymal transition and cell death in fibrotic cells. Overall, this study provided experimental support for the idea that PM2.5 greatly deteriorates fibrosis process in pre-existing pulmonary fibrosis, and HO-1-mediated mitochondrial dysfunction and NCOA4-mediated ferritinophagy are jointly required for the PM2.5-induced ferroptosis and enhanced fibrosis effects.

Enhanced commercial cooking inventories from the city scale through normalized emission factor dataset and big data

Cooking emission inventories always have poor spatial resolutions when applying with traditional methods, making their impacts on ambient air and human health remain obscure. In this study, we created a systematic dataset of cooking emission factors (CEFs) and applied it with a new data source, cooking-related point of interest (POI) data, to build up highly spatial resolved cooking emission inventories from the city scale. Averaged CEFs of six particulate and gaseous species (PM, OC, EC, NMHC, OVOCs, VOCs) were 5.92 ± 6.28, 4.10 ± 5.50, 0.05 ± 0.05, 22.54 ± 20.48, 1.56 ± 1.44, and 7.94 ± 6.27 g/h normalized in every cook stove, respectively. A three-field CEF index containing activity and emission factor species was created to identify and further build a connection with cooking-related POI data. A total of 95,034 cooking point sources were extracted from Beijing, as a study city. In downtown areas, four POI types were overlapped in the central part of the city and radiated into eight distinct directions from south to north. Estimated PM/VOC emissions caused by cooking activities in Beijing were 4.81/9.85 t per day. A 3D emission map showed an extremely unbalanced emission density in the Beijing region. Emission hotspots were seen in Central Business District (CBD), Sanlitun, and Wangjing in Chaoyang District and Willow and Zhongguancun in Haidian District. PM/VOC emissions could be as high as 16.6/42.0 kg/d in the searching radius of 2 km. For PM, the total emissions were 417.4, 389.0, 466.9, and 443.0 t between Q1 and Q4 2019 in Beijing, respectively. The proposed methodology is transferrable to other Chinese cities for deriving enhanced commercial cooking inventories and potentially highlighting the further importance of cooking emissions on air quality and human health.

Mechanism of the effect of vertically propagating internal gravity waves on turbulence barrier and pollutant diffusion during heavy haze episodes

During heavy haze episodes, especially the cumulative stage (CS) of pollutants, strong turbulence intermittency and the resulting turbulence barrier effect (i.e., a phenomenon that turbulence at certain heights may disappear forming a laminar flow as if there is a barrier layer impeding the vertical turbulent exchange) suppress the vertical diffusion of pollutants, leading to high PM_2.5 concentrations. However, there are still some short-time removal processes of pollutants occurring at different heights in the CS, accompanied with interesting non-simultaneous drop or opposite variation of PM_2.5 concentrations at different heights. The ubiquitous internal gravity waves (IGWs) in the stable boundary layer (SBL) may play a critical role in the above situation, as they are closely related to the intermittent turbulence bursts appearing in the persistent weak turbulent motions. In this study, two representative heavy haze pollution cases were chosen to demonstrate the above speculation using five layers of turbulence data, two layers of pressure fluctuations and three layers of PM_2.5 concentrations. Results showed that the non-simultaneous drop or opposite variation of PM_2.5 concentrations was associated with the destruction of turbulence barrier by the vertical propagation of IGWs. IGWs generated by some certain mechanisms, such as nonhomogeneous terrain and wind shear around the low-level jet (LLJ), can propagate upward or downward with the upward or downward development of the temperature inversion layer. The vertically propagating IGWs then triggered intermittent increasing turbulence layer by layer. Turbulence between layers reconnected sequentially and turbulence barriers were broken in turn. The enhanced turbulent exchange expedited the pollutant diffusion, thus the PM_2.5 concentrations at different heights varied non-simultaneously even inversely. This study provides a good explanation for the positive effects of sub-mesoscale motions such as IGWs on triggering intermittent increasing turbulence and facilitating the diffusion of pollutants during heavy haze pollution events.

Chemical characterization, source apportionment, and health risk assessment of PM2.5 in a typical industrial region in North China

To clarify the chemical characteristics, source contributions, and health risks of pollution events associated with high PM_2.5 in typical industrial areas of North China, manual sampling and analysis of PM_2.5 were conducted in the spring, summer, autumn, and winter of 2019 in Pingyin County, Jinan City, Shandong Province. The results showed that the total concentration of 29 components in PM_2.5 was 53.4 ± 43.9 μg·m^-3, including OC/EC, water-soluble ions, inorganic elements, and metal elements. The largest contribution was from the NO₃^- ion, at 14.6 ± 14.2 μg·m^-3, followed by organic carbon (OC), SO₄^2-, and NH₄⁺, with concentrations of 9.3 ± 5.5, 9.1 ± 6.4, and 8.1 ± 6.8 μg·m^-3, respectively. The concentrations of OC, NO₃^-, and SO₄^2- were highest in winter and lowest in summer, whereas the NH₄⁺ concentration was highest in winter and lowest in spring. Typical heavy metals had higher concentrations in autumn and winter, and lower concentrations in spring and summer. The annual average sulfur oxidation rate (SOR) and nitrogen oxidation rate (NOR) were 0.30 ± 0.14 and 0.21 ± 0.12, respectively, with the highest SO₂ emission and conversion rates in winter, resulting in the SO₄^2- concentration being highest in winter. The average concentration of secondary organic carbon in 2019 was 2.8 ± 1.9 μg·m^-3, and it comprised approximately 30% of total OC. The concentrations of 18 elements including Na, Mg, and Al were between 2.3 ± 1.6 and 888.1 ± 415.2 ng·m^-3, with Ni having the lowest concentration and K the highest. The health risk assessment for typical heavy metals showed that Pb poses a potential carcinogenic risk for adults, whereas As may pose a carcinogenic risk for adults, children, and adolescents. The non-carcinogenic risk coefficients for all heavy metals were lower than 1.0, indicating that the non-carcinogenic risk was negligible. Positive matrix factorization analysis indicated that coal-burning emissions contributed the largest fraction of PM_2.5, accounting for 35.9% of the total. The contribution of automotive emissions is similar to that of coal, at 32.1%. The third-largest contributor was industrial sources, which accounted for 17.2%. The contributions of dust and other emissions sources to PM_2.5 were 8.4% and 6.4%, respectively. This study provides reference data for policymakers to improve the air quality in the NCP.

Health risk assessment and source apportionment of PM2.5-bound toxic elements in the industrial city of Siheung, Korea

The emission sources and their health risks of fine particulate matter (PM_2.5) in Siheung, Republic of Korea, were investigated as a middle-sized industrial city. To identify the PM_2.5 sources with error estimation, a positive matrix factorization model was conducted using daily mean speciated data from November 16, 2019, to October 2, 2020 (95 samples, 22 chemical species). As a result, 10 sources were identified: secondary nitrate (24.3%), secondary sulfate (18.8%), traffic (18.8%), combustion for heating (12.6%), biomass burning (11.8%), coal combustion (3.6%), heavy oil industry (1.8%), smelting industry (4.0%), sea salts (2.7%), and soil (1.7%). Based on the source apportionment results, health risks by inhalation of PM_2.5 were assessed for each source using the concentration of toxic elements portioned. The estimated cumulative carcinogenic health risks from the coal combustion, heavy oil industry, and traffic sources exceeded the benchmark, 1E-06. Similarly, carcinogenic health risks from exposure to As and Cr exceeded 1E-05 and 1E-06, respectively, needing a risk reduction plan. The non-carcinogenic risk was smaller than the hazard index of one, implying low potential for adverse health effects. The probable locations of sources with relatively higher carcinogenic risks were tracked. In this study, health risk assessment was performed on the elements for which mass concentration and toxicity information were available; however, future research needs to reflect the toxicity of organic compounds, elemental carbon, and PM_2.5 itself.

Molecular signatures of organic particulates as tracers of emission sources

Chemical signature of airborne particulates and deposition dusts is subject of study since decades. Usually, three complementary composition markers are investigated, namely, (i) specific organic compounds; (ii) concentration ratios between congeners, and (iii) percent distributions of homologs. Due to its intrinsic limits (e.g., variability depending on decomposition and gas/particle equilibrium), the identification of pollution sources based on molecular signatures results overall restricted to qualitative purposes. Nevertheless, chemical fingerprints allow drawing preliminary information, suitable for successfully approaching multivariate analysis and valuing the relative importance of sources. Here, the state-of-the-art is presented about the molecular fingerprints of non-polar aliphatic, polyaromatic (PAHs, nitro-PAHs), and polar (fatty acids, organic halides, polysaccharides) compounds in emissions. Special concern was addressed to alkenes and alkanes with carbon numbers ranging from 12 to 23 and ≥ 24, which displayed distinct relative abundances in petrol-derived spills and exhausts, emissions from microorganisms, high vegetation, and sediments. Long-chain alkanes associated with tobacco smoke were characterized by a peculiar iso/anteiso/normal homolog fingerprint and by n-hentriacontane percentages higher than elsewhere. Several concentration ratios of PAHs were identified as diagnostic of the type of emission, and the sources of uncertainty were elucidated. Despite extensive investigations conducted so far, the origin of uncommon molecular fingerprints, e.g., alkane/alkene relationships in deposition dusts and airborne particles, remains quite unclear. Polar organics resulted scarcely investigated for pollution apportioning purposes, though they looked as indicative of the nature of sources. Finally, the role of humans and living organisms as actual emitters of chemicals seems to need concern in the future.

Characterization of carbonaceous substances emitted from residential solid fuel combustion using real-world data from the Beijing-Tianjin-Hebei region

Residential solid fuel emissions are among the most important sources of carbonaceous substances that exert harmful effects on air quality, human health and climate change. Considering the constantly updated emission reduction policies for residential solid fuel combustion in the Beijing-Tianjin-Hebei (BTH) region, the emission data for the source should updated in a timely manner. Testing was performed on residential solid fuel emissions in the BTH region, China. The emission factors and profiles of carbonaceous substances (including organic carbon (OC), elemental carbon (EC), EPA priority polycyclic aromatic hydrocarbons (EPAHs), methyl PAHs (MPAHs), and n-alkanes) emitted from residential solid fuels were obtained. The results showed the ranges of emission factors of PM_2.5, OC, EC, EPAHs, MPAHs and n-alkanes from residential solid fuel emissions were 1.92-17.6, 0.312-6.85, 0.066-2.33, 0.004-0.58, 0.003-0.87 and 0.009-0.39 g/kg fuel, respectively. The carbon fraction profiles showed that OC1, OC2, and EC1 were the major products of residential solid fuel combustion, and the non-polar organic matter profiles showed that Fluo and MFluo were dominant. The effects of combustion modes, types of stove and types of the fuel on emission characteristics of carbonaceous substances were discussed in detail. The emission factors of carbonaceous substances from the smoldering phase and traditional stove were higher than those from the flaming phase and improved stove, respectively, which was mainly controlled by the modified combustion efficiency (MCE). It was found that the emission factors of pollutants with decreasing MCE values sharply increased, especially when the MCE values were below 90%. Finally, some diagnostic ratios were discussed, and it was determined that residential coal combustion is considered to occur at MPAHs/PAHs higher than 1.5 and MFluo/Fluo higher than 5.

A clear north-to-south spatial gradience of chloride in marine aerosol in Chinese seas under the influence of East Asian Winter Monsoon

Particulate chloride is a major component of sea salt particles and plays a key role in atmospheric chemistry. Anthropogenic pollutants over the northeastern Asia can be transported to the adjacent seas through the northwest monsoon, which profoundly influences the chloride chemistry over the seas. In this study, spatial distribution of particulate chloride and its sources over the Chinese seas were investigated based on shipboard particle samplings especially online Single Particle Aerosol Mass Spectrometer (SPAMS) over Bohai Sea, North Yellow Sea, and South Yellow Sea (SYS) during a cruise in November 2012. A strong north-to-south (N-S) gradience in marine aerosol composition was found. The Cl^-/Na⁺ ratios in PM_2.5 and single particle composition by SPAMS indicated remarkable chloride enrichment in marine aerosol in the north (Bohai Sea), while depletion in southern SYS. The results of size distribution showed that particulate chloride had higher concentration in coarse particles, while the Cl^-/Na⁺ ratio was much higher in submicron particles. In the north (38-40°N), biomass burning, carbonaceous, and Pb-rich type particles had high fractions in all chloride-containing particles identified by SPAMS (on average 66%). Combining chemical composition with back trajectory, it was found that fine-mode chloride enrichment in the north was mainly due to anthropogenic emission especially coal combustion and biomass burning from northern China. However, the high fine-mode chloride depletion in the south (32-34°N) was probably due to acid replacement by sulfate in aged aerosol during atmospheric transport. Our new findings reveal that marine aerosol in Chinese seas would show a clear N-S pattern of more fresh and anthropogenic enriched particles in the north, but more aged aerosol in the south during the East Asia Winter Monsoon, which provides new insights for the quantitative assessment of anthropogenic impact on marine aerosol and future modeling study.

Refined source apportionment of residential and industrial fuel combustion in the Beijing based on real-world source profiles

Residential and industrial emissions are considered as dominant contributors to ambient fine particulate matter (PM_2.5) in China. However, the contributions of residential and industrial fuel combustion are difficult to distinguish because specific source indicators are lacking. In this study, real-world source testing was performed on residential coal, biomass and industrial combustion, industrial processes, and diesel and gasoline vehicle source emissions in the Beijing-Tianjin-Hebei region, China. PM_2.5 emission factors and chemical profiles, including 97 compositions (e.g., carbonaceous matter, water-soluble ions, elements, EPA priority polycyclic aromatic hydrocarbons (EPAHs), methyl PAHs (MPAHs), and n-alkanes) were obtained for the aforementioned sources. The results showed high OC1, OC2, fluoranthene, methyl fluoranthene, and retene in emissions from residential coal combustion, high OC3, sulfate, Ca, and iron abundance in emissions from industrial combustion, and high Pb and Zn loadings in emissions from industrial processes. Furthermore, specific diagnostic ratios were determined to distinguish between residential and industrial fuel combustion. For example, the ratios of MPAHs/EPAHs (>1) and Mfluo/Fluo (>5) can be used as fingerprinting ratios to distinguish residential coal combustion from other sources. Finally, 1-h resolution refined source apportionments of PM_2.5 were conducted in Beijing during two haze events (EP1 and EP2) with a chemical mass balance (CMB) model based on the localized real-world source profiles established in this study. Source apportionment results of CMB showed that the contributions of industrial and residential fuel combustion were 19.4% and 30.8% in EP1 and 26.8% and 18.1% in EP2, respectively, which were comparable to the results of the positive matrix factorization model (R² = 0.82). This study provides valuable information for the successful and accurate determination of the contributions of residential and industrial fuel combustion to ambient PM_2.5.

Large contribution of non-priority PAHs in atmospheric fine particles: Insights from time-resolved measurement and nontarget analysis

Polycyclic aromatic hydrocarbons (PAHs), detrimental to human health, are key components contributing to the carcinogenicity of fine particles. The 16 priority PAHs listed by the United States Environment Protection Agency have been studied extensively. However, other than them, there is a large diversity of PAH species, whose atmospheric concentrations, risks, and variations remain elusive. Here, we carried out a time-resolved nontarget measurement in atmospheric PM_2.5 using an improved comprehensive two-dimensional gas chromatography mass spectrometry. The measurement conducted during a 5-day pollution episode at an urban site of Beijing with a time resolution of 2 h. The nontarget analysis of time-resolved chromatographic data was performed for screening PAHs. A total number of 85 PAHs were identified and quantified. We found that other than 16 EPA PAHs, other screened PAHs contributed 43.3% of the total PAH mass concentration and 40.8% poential health risks. Dynamic variations of mass concentrations and their potential health risks of the screened PAHs were captured during a short-term heavy pollution episode, during which the instantaneous PAHs concentrations were much higher than their average concentrations. This study shows the potential for application of nontarget analysis for online comprehensive two-dimensional gas chromatography mass spectrometry and highlights the importance of time-resolved measurement of PAHs in PM_2.5 and attention on extended PAHs species other than 16 EPA PAHs.

Oxidative potential and water-soluble heavy metals of size-segregated airborne particles in haze and non-haze episodes: Impact of the "Comprehensive Action Plan" in China

Air pollution is a major environmental health challenge in megacities, and as such a Comprehensive Action Plan (CAP) was issued in 2017 for Beijing, the capital city of China. Here we investigated the size-segregated airborne particles collected after the implementation of the CAP, intending to understand the change of oxidative potential and water-soluble heavy metal (WSHM) levels in 'haze' and 'non-haze' days. The DNA damage and the levels of WSHM were analyzed by Plasmid Scission Assay (PSA) and High-Resolution Inductively Coupled Plasma Mass Spectrometry (HR-ICP-MS) techniques. The PM mass concentration was higher in the fine particle size (0.43-2.1 μm) during haze days, except for the samples affected by mineral dust. The particle-induced DNA damage caused by fine sized particles (0.43-2.1 μm) exceeded that caused by the coarse sized particles (4.7-10 μm). The DNA damage from haze day particles significantly exceeded those collected on non-haze days. Prior to the instigation of the CAP, the highest value of DNA damage decreased, and DNA damage was seen in the finer size (0.43-1.1 μm). The Pearson correlation coefficient between the concentrations of water-soluble Pb, Cr, Cd and Zn were positively correlated with DNA damage, suggesting that these WSHM had significant oxidative potential. The mass concentrations of water-soluble trace elements (WSTE) and individual heavy metals were enriched in the finer particles between 0.43 μm to 1.1 μm, implying that smaller sized particles posed higher health risks. In contrast, the significant reduction in the mass concentration of water-soluble Cd and Zn, and the decrease of the maximum and average values of DNA damage after the CAP, demonstrated its effectiveness in restricting coal-burning emissions. These results have demonstrated that the Beijing CAP policy has been successful in reducing the toxicity of 'respirable' ambient particles.

Mechanism of haze pollution in summer and its difference with winter in the North China Plain

Heavy haze pollution usually occurs in winter. However, according to the enhanced atmospheric boundary layer (ABL) field experiments conducted in the North China Plain (NCP) from 17 June to 6 July 2019, heavy haze pollution may also occur in summer, although with a lower probability. Winter haze pollution is significantly affected by adverse boundary layer meteorological conditions, whereas our study shows different mechanisms of summer haze pollution from that of winter. In summer, PM_2.5 is distributed uniformly as a thick layer at a lighter pollution level; however, the PM_2.5 column content in summer exceeds that in winter, suggesting that the better air quality in summer is mainly due to improved diffusion conditions. In summer, even under haze conditions, the ABL can develop over 1000 m and has a large ventilation similar to clean periods, which indicates both favourable vertical diffusion conditions and advection capability of the summer ABL. Unlike in winter, the heavy haze pollution in summer is often caused by regional transport which is related to local circulation. To explore the influence of different scale systems on summer haze pollution, we applied the spectral analysis method to surface PM_2.5 concentrations. Strong periodicity of PM_2.5 concentrations is found in 4-9 d and 1 d, corresponding to the impacts of large-scale synoptic system changes and the ABL evolution, respectively. The influence of weather change is much stronger than that of the ABL evolution on PM_2.5 concentrations in summer. The resulting changes in PM_2.5 concentrations are approximately 45 μg/m³ and 15 μg/m³, respectively. There has been a consensus on the importance of emission control in winter. And this study shows that heavy haze pollution can also occur in summer and regional joint emission control should also be emphasized in summer.

Application and validation of the fugitive dust source emission inventory compilation method in Xiong'an New Area, China

The development of a refined fugitive dust emission inventory is vital for prevention and control of air pollution. In this study, a fugitive dust emission inventory of soil dust (SD), road dust (RD), and construction dust (CD) in Xiong'an New Area (XANA) for 2020 was developed by collecting activity data and combining remote sensing and field investigation data based on a popular compilation technology in China. The CALPUFF model was used to elucidate the contribution characteristics of dust sources to ambient particulate matter (PM), and the accuracy of the dust emission inventory compilation method was verified. The results show that the total emissions of PM₁₀ and PM_2.5 were 43,081.14 tons and 9701.69 tons, respectively. Meanwhile, RD and CD were the main emission sources, accounting for over 98.49% of the total emissions. The total contribution from the different types of dust sources to the ambient PM₁₀ was 42.59 μg/m³ (29.38%), with the contribution of RD (32.63 μg/m³, 22.51%) being approximately three times that of CD (9.78 μg/m³, 6.74%). Roads were the main source of fugitive dust, but large-scale infrastructure construction was the main cause of the high emission and high contribution of RD. The results show that the emission inventory compilation method can be used to estimate the emissions of dust sources, while the method used to calculate the emission of SD may be more suitable for dry and semi-dry areas with less rainfall. It was also found that when the dust emissions stay stable, the contribution of dust sources to the ambient PM₁₀ in different seasons can vary by 3-4 times. Therefore, under adverse meteorological conditions, it is necessary to strengthen the control of various dust sources and reduce the influence of human factors on them.

Chemical Characterization, Source, and SOA Production of Intermediate Volatile Organic Compounds during Haze Episodes in North China

The growth of secondary organic aerosols (SOA) is a vital cause of the outbreaks of winter haze in North China. Intermediate volatile organic compounds (IVOCs) are important precursors of SOA. Therefore, the chemical characteristics, source, and SOA production of IVOCs during haze episodes have attracted much attention. Hourly time resolution IVOC samples during two haze episodes collected in Hebei Province in North China were analyzed in this study. Results showed that: (1) the concentration of IVOCs measured was within the range of 11.3~85.1 μg·cm−3 during haze episodes, with normal alkanes (n-alkanes), polycyclic aromatic hydrocarbons (PAHs), branched alkanes (b-alkanes), and the residue unresolved complex mixture (R-UCM) accounting for 8.6 ± 2.3%, 6.8 ± 2.2%, 24.1 ± 3.8%, and 60.5 ± 6.5% of IVOCs, respectively. NC12-nC15 in n-alkanes, naphthalene and its alkyl substitutes in PAHs, b-alkanes in B12–B16 bins, and R-UCM in B12–B16 bins are the main components, accounting for 87.0 ± 0.2%, 87.6 ± 2.9%, 85.9 ± 5.4%, 74.0 ± 8.3%, respectively. (2) Based on the component characteristics of IVOCs and the ratios of n-alkanes/b-alkanes in emission sources and the hourly variation of IVOCs during haze episodes, coal combustion (CC), biomass burning (BB), gasoline vehicles (GV), and diesel vehicles (DV)were identified as important emission sources of IVOCs in Hebei Province. (3) During haze episodes, temporal variation of the estimated SOA production based on different methods (such as IVOCs concentration, OC/ECmin tracer, and the PMF model) were similar; however, the absolute values were different. This difference may be due to the transformation of IVOCs to SOA affected by various factors such as SOA production from different IVOC components, meteorological conditions, atmospheric oxidation, etc.

High Temporal Resolution Land Use Regression Models with POI Characteristics of the PM2.5 Distribution in Beijing, China

PM2.5 is one of the primary components of air pollutants, and it has wide impacts on human health. Land use regression models have the typical disadvantage of low temporal resolution. In this study, various point of interests (POIs) variables are added to the usual predictive variables of the general land use regression (LUR) model to improve the temporal resolution. Hourly PM2.5 concentration data from 35 monitoring stations in Beijing, China, were used. Twelve LUR models were developed for working days and non-working days of the heating season and non-heating season, respectively. The results showed that these models achieved good fitness in winter and summer, and the highest R2 of the winter and summer models were 0.951 and 0.628, respectively. Meteorological factors, POIs, and roads factors were the most critical predictive variables in the models. This study also showed that POIs had time characteristics, and different types of POIs showed different explanations ranging from 5.5% to 41.2% of the models on working days or non-working days, respectively. Therefore, this study confirmed that POIs can greatly improve the temporal resolution of LUR models, which is significant for high precision exposure studies.

Non-Linear Response of PM2.5 Pollution to Land Use Change in China

Land use change has an important influence on the spatial and temporal distribution of PM2.5 concentration. Therefore, based on the particulate matter (PM2.5) data from remote sensing instruments and land use change data in long time series, the Getis-Ord Gi* statistic and SP-SDM are employed to analyze the spatial distribution pattern of PM2.5 and its response to land use change in China. It is found that the average PM2.5 increased from 25.49 μg/m3 to 31.23 μg/m3 during 2000-2016, showing an annual average growth rate of 0.97%. It is still greater than 35 μg/m3 in nearly half of all cities. The spatial distribution pattern of PM2.5 presents the characteristics of concentrated regional convergence. PM2.5 is positively correlated with urban land and farmland, negatively correlated with forest land, grassland, and unused land. Furthermore, the average PM2.5 concentrations show the highest values for urban land and decrease in the order of farmland > unused land > water body > forest > grassland. The impact of land use change on PM2.5 is a non-linear process, and there are obvious differences and spillover effects for different land types. Thus, reasonably controlling the scale of urban land and farmland, optimizing the spatial distribution pattern and development intensity, and expanding forest land and grassland are conducive to curbing PM2.5 pollution. The research conclusions provide a theoretical basis for the management of PM2.5 pollution from the perspective of optimizing land use.