Source apportionment of PM2.5 in Seoul, South Korea and Beijing, China using dispersion normalized PMF

Source apportionment of PM2.5 using dispersion normalized positive matrix factorization (DN-PMF) in Beijing and Baoding, China

Fine particulate matter (PM2.5) samples were collected in two neighboring cities, Beijing and Baoding, China. High-concentration events of PM2.5 in which the average mass concentration exceeded 75 µg/m3 were frequently observed during the heating season. Dispersion Normalized Positive Matrix Factorization was applied for the source apportionment of PM2.5 as minimize the dilution effects of meteorology and better reflect the source strengths in these two cities. Secondary nitrate had the highest contribution for Beijing (37.3 %), and residential heating/biomass burning was the largest for Baoding (27.1 %). Secondary nitrate, mobile, biomass burning, district heating, oil combustion, aged sea salt sources showed significant differences between the heating and non-heating seasons in Beijing for same period (2019.01.10-2019.08.22) (Mann-Whitney Rank Sum Test P < 0.05). In case of Baoding, soil, residential heating/biomass burning, incinerator, coal combustion, oil combustion sources showed significant differences. The results of Pearson correlation analysis for the common sources between the two cities showed that long-range transported sources and some sources with seasonal patterns such as oil combustion and soil had high correlation coefficients. Conditional Bivariate Probability Function (CBPF) was used to identify the inflow directions for the sources, and joint-PSCF (Potential Source Contribution Function) was performed to determine the common potential source areas for sources affecting both cities. These models facilitated a more precise verification of city-specific influences on PM2.5 sources. The results of this study will aid in prioritizing air pollution mitigation strategies during the heating season and strengthening air quality management to reduce the impact of downwind neighboring cities.

Evaluating the representativeness of atmospheric PM2.5 data for indoor exposure: insights from concentrations, chemical compositions, and sources

Studies relied on atmospheric PM2.5 data to estimate health risks and sources, but its representativeness for indoor air remains unclear. This study placed an atmospheric PM2.5 sampler on the rooftop of a three-story building, and indoor and outdoor (balcony) samples were collected from study houses within a 5 km radius of the atmospheric sampling site during low and high PM2.5 seasons to evaluate the representativeness of atmospheric PM2.5 data. The average PM2.5 concentrations were 15.4 ± 7.1 μg/m3 (indoor), 18.9 ± 7.0 μg/m3 (outdoor), and 13.9 ± 6.1 μg/m3 (atmospheric). Atmospheric PM2.5 concentrations were significantly associated with indoor and outdoor PM2.5, but outdoor PM2.5 concentrations were higher. Source identification revealed that traffic-related emission was a major contributor to PM2.5 across all sites and seasons, while long-range transport from China was another source during the high PM2.5 season based on lead isotope ratios. Crustal elements and construction dust, identified through positive matrix factorization, were higher in both indoor and outdoor air than in the atmosphere. Elements from industrial or traffic emissions showed similar concentrations across different sampling sites. The average ratios of indoor to outdoor or atmospheric PM2.5 concentrations were 0.84 ± 0.27 and 1.18 ± 0.37, respectively. In conclusion, atmospheric PM2.5 can be used to estimate PM2.5 exposure and element concentrations from industrial or traffic emissions in indoors; however, it underestimates the contributions of crustal elements and construction dust. Ambient PM2.5 samples from outdoor or atmospheric environments should be considered when comparing their influence on indoor air across studies.

Distribution and potential sources of iodine in particulate matter at an industrial city in Northwest China

Iodine plays a key role in atmospheric chemistry that can significantly affect the atmospheric oxidation capacity. Although the oceans are the main reservoir of iodine on Earth, iodine is also widely present in the terrestrial environment. Therefore, a comprehensive understanding of the present sources of iodine in inland areas is warranted for the evaluation of its environmental effect. In this study, we conducted monitoring of total iodine in particulate matter (PM) in the Shihezi (SHZ) over 11 months using a high-pressure confined microwave digestion technique and an inductively coupled plasma mass spectrometer (ICP-MS). The mean concentrations of total iodine in PM2.5 and PM10 were 2.60 ± 1.81 ng/m3 and 2.90 ± 1.92 ng/m3, respectively, at the same time, it shows the change characteristics of winter > spring > summer > autumn. Eight water-soluble ions were used as auxiliary parameters for multivariate statistics, including principal component analysis (PCA) and absolute principal component score-multivariate linear regression (APCS-MLR), to estimate the potential source assignments of PM iodine. PCA extracted four possible sources, respectively, and APCS-MLR indicated that anthropogenic activities, such as coal combustion and industrial emissions, were the primary potential sources of iodine, followed by certain unknown sources. This study indicated that anthropogenic activities were an important source of atmospheric iodine in the inland regions.

Assessment of discrepancies in PM2.5 modeling and heavy metal associated health implications in Tier 2 and 3 non-attainment cities: EDGAR-driven WRF-Chem vs. field data in Alwar and Amritsar

The study investigates the discrepancies between WRF-Chem modelled and on-field measured water-soluble inorganic ions (WSIIs) and trace metals in under-researched non-attainment Tier 2 and Tier 3 Indian cities, Alwar and Amritsar. PMF-PSCF analysis concluded that in Alwar, sources included Secondary Inorganic Aerosols (SIA) and Coal Combustion (32 % in winter) and Crustal Emissions (27 % in summer), while in Amritsar, Brake and Tyre Abrasion (28 % in winter) and Crustal Emissions (68 % in summer) were predominant. A comprehensive health impact assessment using the U.S. EPA risk assessment model revealed that despite lower PM2.5 concentrations in Alwar compared to Amritsar, carcinogenic risks were notably higher, exceeding those observed in Tier 1 cities like Delhi. WRF-Chem model simulations, while insightful, underestimated concentrations of several ionic and metallic species. The limitations of these models highlight the need for more detailed and updated emission inventories, with finer temporal and spatial resolutions, to improve model accuracy in Tier 2 and Tier 3 Indian cities.

Long-term effects of emission reduction measures on PM2.5 sources and children's lung function in Jinan, China

Many studies have reported the damaging effect of PM2.5 on the lung function of school-age children, but the potential impact of different PM2.5 sources remains unclear. This study analyzed the composition of PM2.5 at a sampling site in Jinan City between 2014 and 2020. Coinciding with the implementation of the environmental protection policies in Jinan, the study time was segmented into three distinct periods. PM2.5 and its components (such as metals and polycyclic aromatic hydrocarbons) gradually decreased across these periods. The results of the Positive Matrix Factorization (PMF) showed that the concentrations of PM2.5 were reduced to varying degrees for different sources. The generalized linear model, after adjustment, found that increased industrial emissions were associated with decreased FVC (OR: 0.92, 95%CI: 0.87-0.98) and FEV1 (OR: 0.91, 95%CI: 0.86-0.96) in girls during Period 1. In Period 2, biomass burning and road dust were associated with a decrease in FVC (OR: 0.91, 95%CI: 0.84-0.99) and FEV1 (OR 0.92, 95%CI: 0.85-0.99) for boys, and in the same period, the reductions in FVC (OR: 0.90, 95%CI: 0.83-0.97), FEV1 (OR: 0.91, 95%CI: 0.85-0.97) and PEF (OR: 0.77, 95% CI: 0.68-0.90) in girls were associated with gasoline combustion. No source was found to be associated with a decrease in lung function among school-age children in Period 3 when air quality improved substantially. The results suggest that the environmental protection policy in Jinan City has controlled PM2.5 pollution levels to some extent, which may have improved children's lung function.

Chemical composition, multiple sources, and health risks of PM2.5: A case study in Linyi, China's plate and logistics capital

Elucidating the chemical composition, sources, and health risks of fine particulate matter (PM2.5) is crucial for effectively preventing and controlling air pollution. This study collected PM2.5 samples in Linyi from November 10, 2021, to October 15, 2022, spanning the period of the 2022 Winter Olympics and Paralympics. The analysis focused on seasonal variations in the chemical composition of PM2.5, including water-soluble ions, inorganic elements, and carbonaceous aerosols. Results from the random forest model indicated that control measures during the Olympics and Paralympics reduced PM2.5 concentrations by 21.5% in Linyi. Organic matter was the dominant component of PM2.5, followed by NO3-, SO42-, and NH4+. Among secondary inorganic ions, SO42- exhibited the highest concentration in summer, while NO3- and NH4+ showed the lowest concentrations. The inorganic elements S, K, Fe, and Si had high mean annual concentrations, underscoring the need for targeted control measures for plate production, bulk coal burning, and biomass combustion in Linyi. The organic carbon (OC) to elemental carbon ratio (17.7-20.5) in Linyi was high, highlighting the importance of addressing secondary OC pollution. According to the positive matrix factorization model, coal burning, and the secondary formation processes of sulfate and nitrate were the dominant sources of PM2.5. Backward air mass trajectories revealed substantial contributions from the southeastern, local, and southwestern regions of Linyi. This suggests the need for enhanced regional joint prevention and control efforts between Linyi and neighboring cities, such as Rizhao and Jining in Shandong Province, as well as northern cities in Jiangsu Province. The highest non-carcinogenic and carcinogenic risks (CRs) were associated with As. coal burning posed significant noncarcinogenic risks and a moderate CR, contributing 41.7% and 44.0% of the total health risk, respectively. These findings are crucial for developing effective air pollution prevention and control strategies.

Evaluating drivers of PM2.5 air pollution at urban scales using interpretable machine learning

Reducing urban fine particulate matter (PM2.5) concentrations is essential for China to achieve the Sustainable Development Goals (SDGs). Identifying the key drivers of PM2.5 will enable the development of targeted strategies to reduce PM2.5 levels. This study introduces a machine-learning model that combines CatBoost and the Tree-Structured Parzen Estimator (TPE) to analyze PM2.5 concentration across 297 cities between 2000 and 2021. SHapley Additive exPlanations (SHAP) were employed to identify the primary factors influencing urban PM2.5 concentrations. The study revealed that the proposed model has high accuracy in predicting urban PM2.5 concentrations, achieving a coefficient of determination (R2) score of 96.44%. Socioeconomic and industrial activity are key drivers of PM2.5 concentrations. This study not only quantifies the primary factors exacerbating or alleviating pollution for each city or province during the 2000-2021 period but also evaluates the influence of operational factors such as technological and public financial expenditures. In 2000, the main contributors to pollution in four heavily polluted cities included substantial nitrogen oxide emissions, inadequate technology investments, and excessive population density and liquefied gas consumption. Due to the rapid reduction in nitrogen oxide emissions, pollution levels in these cities have improved substantially. In the future, the most effective strategies for pollution reduction in these cities will focus on controlling population density and slowing down mining development. The proposed framework serves as a robust evaluation tool and can propose tailored strategies to control PM2.5 concentrations effectively in each city.

Chemical characterization and source identification of PM2.5 in the Huaxi urban area of Guiyang

In 2020, 123 PM2.5 samples were collected across different seasons in Huaxi District, Guiyang. The primary chemical components of PM2.5, including water-soluble ions (WSIIs), metallic elements, organic carbon (OC), and elemental carbon (EC), were analyzed. During the sampling period, the average PM2.5 concentration was 39.7 ± 22.3 µg/m2. Chemical mass closure (CMC) was used to reconstruct PM2.5 mass, yielding a reconstructed concentration of 29.1 ± 16.5 µg/m2. The major components were organic matter (OM), sulfate + nitrate + ammonium (SNA), and mineral dust (MD), with mean concentrations of 12.2 ± 6.3 µg/m2, 8.2 ± 4.0 µg/m2, and 6.3 ± 4.6 µg/m2, respectively. From clean days (CD) to lightly-moderately polluted days (LMPD), nitrate oxidation ratio (NOR) increased from 0.09 to 0.16, while sulfate oxidation ratio (SOR) and OC/EC ratio rose by 21.7% and 13.5%, indicating stronger secondary reactions on polluted days. The study also examined changes in chemical components under different atmospheric oxidizing and humidity conditions, revealing that sulfate and nitrate concentrations increased with relative humidity (RH) between 60 and 80%, while other components, especially MD, showed a declining trend due to hygroscopic growth and subsequent gravitational settling and precipitation. The average NO3-/SO42- ratio was 0.67, indicating that fixed sources such as industrial and coal emissions were the main contributors to PM2.5. This study provides insights into the chemical composition, pollution processes, and formation mechanisms of PM2.5, which are crucial for developing effective air pollution control strategies. Furthermore, source apportionment was conducted with the positive matrix factorization (PMF) model. The Coal combustion, secondary, traffic, Industrial and dust source contributions to the PM2.5 mass were approximately 30.5%, 20.0%, 18.3%,16.7% and 14.5%, respectively.

Source identification of heavy metals and metalloids in soil using open-source Tellus database and their impact on ecology and human health

The presence of heavy metals and metalloids (metal(loid)s) in the food chain is a global problem, and thus, metal(loid)s are considered to be Potentially Toxic Elements (PTEs). Arsenic (As), lead (Pb), mercury (Hg), and cadmium (Cd) are identified as prominent hazards related to human health risks throughout the food chain. This study aimed to carry out a source attribution for metal(loid)s in shallow topsoil of north-midlands, northwest, and border counties of the Republic of Ireland, followed by an assessment of the potential ecological and human health risks. The positive Matrix Factorization (PMF) was used for source characterization of PTEs, followed by the Monte Carlo simulation method, used for a probabilistic model to evaluate potential human health risks. The mean concentrations of prioritized metal(loid)s in the topsoil range in the order of Pb (28.83 mg kg-1) > As (7.81 mg kg-1) > Cd (0.51 mg kg-1) > Hg (0.11 mg kg-1) based on the open-source Tellus dataset. This research identified three primary sources of metal(loid) pollution: geogenic sources (36 %), mixed sources of historical mining and natural origin (33 %), and anthropogenic activities (31 %). The ecological risk assessment showed that Ireland's soil exhibits low-moderate pollution levels however, concerns remain for Cd and As levels. All metal(loid)s except Cd showed acceptable non-carcinogenic risk, while Cd and As accounted for high to moderate potential cancer risks. Potato consumption (if grown on land with elevated metal(loid) levels), Cd concentration in soil, and bioaccumulation factor of Cd in potatoes were the three most sensitive parameters. In conclusion, metal(loid)s in Ireland present low to moderate ecological and human health risks. It underscores the need for policies and remedial strategies to monitor metal(loid) levels in agricultural soil regularly and the production of crops with low bioaccumulation in regions with elevated metal(loid) levels.

Evaluation of the potentially toxic elements and radionuclides in the soil sample of Novaya Zemlya in the Arctic Circle

The study presented here elucidate the concentrations of radionuclides and potentially toxic elements in the soil samples around the Novaya Zemlya in the Russian Arctic zone, determined using HPGe gamma spectrometry, inductively coupled plasma optical emission spectrometry and direct mercury analyzer. The average detected concentrations for 226Ra, 232Th, 40K, 235U and 137Cs were 36.40, 46.06, 768, 2.06 and 4.71 Bq/kg, respectively. At many sampling sites, the concentrations of potentially toxic elements (Zn, Cu, Pb, Cd, Ni, and Cr) were higher than the natural levels. Positive Matrix Factorization analysis revealed the contribution of oil dumps (32%), natural sources (16%), bird colonies (32%) and atmospheric deposition (20%) for elevated elements content. In the case of radionuclides, the natural occurring contamination (38%) was primary source followed by dumped material (32%) and bird colonies (30%). The radiological risk from radionuclides was relatively high, yet still under permissible levels. For potentially toxic elements, Fe was predominant non-carcinogenic pollutant and Ni emerged as major carcinogenic contaminant. Keeping in view the high content of some elements, future studies are required to keep the human and ecological risk low, and to establish scientific grounds for the contribution of settled bird species. The findings of the study advance the present knowledge about the contamination of the study area and lays the path for further effort.

Particulate matter pollution and older adult health: global trends and disparities, 1991-2021

Background

Particulate matter pollution (PMP) is a major global health concern, with the older adult being particularly vulnerable. This study aimed to analyze global trends in PMP-related deaths and disability-adjusted life years (DALYs) among the older adult from 1991 to 2021.

Methods

Using data from the Global Burden of Disease Study 2021, we examined the impacts of ambient particulate matter pollution (APMP) and household air pollution from solid fuels (HAP-SF). We analyzed trends across different regions, socioeconomic development levels, age groups, and genders.

Results

APMP-related older adult deaths increased from 1,745,000 to 3,850,000, and DALYs from 32,000,000 to 70,000,000. However, age-standardized mortality rate decreased from 384 to 337 per 100,000. HAP-SF-related deaths decreased from 2,700,000 to 2,100,000, and DALYs from 54,000,000 to 42,000,000. Age-standardized mortality rate for HAP-SF declined from 580 to 188 per 100,000. High APMP burden was concentrated in Asia, Africa, and the Middle East, while high HAP-SF burden was found in parts of Africa and South Asia. East Asia had the highest APMP-related older adult deaths (1,680,000) with an age-standardized mortality rate (ASMR) of 619 per 100,000. For HAP-SF, South Asia bore the heaviest burden with 1,020,000 deaths and an ASMR of 616 per 100,000. Females consistently experienced higher age-standardized DALYs rate than males for both APMP and HAP-SF across all regions and years. APMP burden showed a weak negative correlation with the Socio-demographic Index (SDI) at the regional level (r = -0.25, p < 0.001) but no significant correlation at the country level. HAP-SF burden exhibited strong negative correlations with SDI at both regional (r = -0.74, p < 0.001) and country levels (r = -0.83, p < 0.001).

Conclusion

Despite overall improvements, PMP continues to significantly impact older adult health globally, with substantial regional and gender disparities. These findings emphasize the need for targeted interventions, particularly in developing regions, and continued global efforts in air quality improvement and clean energy promotion.

Quantifying the pollution changes and meteorological dependence of airborne trace elements coupling source apportionment and machine learning

Airborne trace elements (TEs) present in atmospheric fine particulate matter (PM2.5) exert notable threats to human health and ecosystems. To explore the impact of meteorological conditions on shaping the pollution characteristics of TEs and the associated health risks, we quantified the variations in pollution characteristics and health risks of TEs due to meteorological impacts using weather normalization and health risk assessment models, and analyzed the source-specific contributions and potential sources of primary TEs affecting health risks using source apportionment approaches at four sites in Shandong Province from September to December 2021. Our results indicated that TEs experience dual effects from meteorological conditions, with a tendency towards higher TE concentrations and related health risks during polluted period, while the opposite occurred during clean period. The total non-carcinogenic and carcinogenic risks of TEs during polluted period increased approximately by factors of 0.53-1.74 and 0.44-1.92, respectively. Selenium (Se), manganese (Mn), and lead (Pb) were found to be the most meteorologically influenced TEs, while chromium (Cr) and manganese (Mn) were identified as the dominant TEs posing health risks. Enhanced emissions of multiple sources for Cr and Mn were found during polluted period. Depending on specific wind speeds, industrialized and urbanized centers, as well as nearby road dusts, could be key sources for TEs. This study suggested that attentions should be paid to not only the TEs from primary emissions but also the meteorology impact on TEs especially during pollution episodes to reduce health risks in the future.

Impact of terephthalic acid emissions from intensive nocturnal biomass incineration on oxidative potential in Seoul, South Korea

This study investigated the impact of large-scale incineration facilities on PM2.5 levels in Seoul during winter. Due to the challenge of obtaining accurate combustion data from external sources, heat supply records were used as a proxy for combustion activity. To assess health risks, dithiothreitol-oxidative potential (DTT-OP) was analyzed to identify potential hazards to human health. By comparing DTT-OP with PM2.5 sources related to combustion, the study aimed to understand the impact of local pollution sources on human health in Seoul. The diurnal analysis showed that oxidative potential (0.19 μM/m3) and the biomass burning factor (5.53 μg/m3) peaked between 4:00 and 8:00 AM, with lower levels observed from 12:00 to 20:00. A significant correlation was found between combustion sources and oxidative potential, with a high correlation coefficient (r2 = 0.92). The presence of terephthalic acid (TPA) in the Cellulose combustion source profile, which is produced by the pyrolysis of plastics like polyester fiber and polyethylene terephthalate (PET), further supported the link to emissions from incineration facilities. These findings suggest that the biomass burning source is strongly correlated with DTT-OP, indicating a significant association with health risks among various local sources of PM2.5 in Seoul.

Effects of seasonal management programs on PM2.5 in Seoul and Beijing using DN-PMF: Collaborative efforts from the Korea-China joint research

South Korea and China have implemented increasingly stringent mitigation measures to reduce the health risks from PM2.5 exposure, jointly conducting a ground-based air quality observation study in Northeast Asia. Dispersion normalized positive matrix factorization (DN-PMF) was used to identify PM2.5 sources in Seoul and Beijing and assess the effectiveness of the seasonal management programs (SMPs) through a comparative study. Samples were collected during three periods: January-December 2019, September 2020-May 2021, and July 2021-March 2022. In Seoul, ten sources were resolved (Secondary nitrate: 8.67 μg/m3, 34 %, Secondary sulfate: 5.67 μg/m3, 22 %, Motor vehicle: 1.83 μg/m3, 7.2 %, Biomass burning: 2.30 μg/m3, 9.1 %, Residual oil combustion: 1.66 μg/m3, 6.5 %, Industry: 2.15 μg/m3, 8.5 %, Incinerator: 1.39 μg/m3, 5.5 %, Coal combustion: 0.363 μg/m3, 1.4 %, Road dust/soil: 0.941 μg/m3, 3.7 %, Aged sea salt: 0.356 μg/m3, 1.4 %). The SMP significantly decreased PM2.5 mass concentrations and source contributions of motor vehicle, residual oil combustion, industry, coal combustion, and biomass burning sources (p-value < 0.05). For Seoul, the reduction effects of the SMPs were evident even considering the influence of the natural meteorological variations and the responses to COVID-19. In Beijing, nine sources were resolved (Secondary nitrate: 12.6 μg/m3, 28 %, Sulfate: 8.27 μg/m3, 18 %, Motor vehicle: 3.77 μg/m3, 8.4 %, Biomass burning: 2.70 μg/m3, 6.0 %, Incinerator: 4.50 μg/m3, 10 %, Coal combustion: 3.52 μg/m3, 7.8 %, Industry: 5.01 μg/m3, 11 %, Road dust/soil: 2.92 μg/m3, 6.5 %, Aged sea salt: 1.63 μg/m3, 3.6 %). Significant reductions in PM2.5 mass concentrations and source contributions of industry, coal combustion, and incinerator (p-value < 0.05) were observed, attributed to the SMP and additional measures enforced before the 2022 Beijing Winter Olympics. Unlike comparing PM2.5 mass concentration variations using conventional methods, investigation of the source contribution variations of PM2.5 by using DN-PMF can provide a deeper understanding of the effectiveness of the air quality management policies.

Health risks and sources of trace elements and black carbon in PM2.5 from 2019 to 2021 in Beijing

A comprehensive health risk assessment of PM2.5 is meaningful to understand the current status and directions regarding further improving air quality from the perspective of human health. In this study, we evaluated the health risks of PM2.5 as well as highly toxic inorganic components, including heavy metals (HMs) and black carbon (BC) based on long-term observations in Beijing from 2019 to 2021. Our results showed that the relative risks of chronic obstructive pulmonary disease, lung cancer, acute lower respiratory tract infection, ischemic heart disease, and stroke decreased by 4.07%-9.30% in 2020 and 2.12%-6.70% in 2021 compared with 2019. However, they were still at high levels ranging from 1.26 to 1.77, in particular, stroke showed the highest value in 2021. Mn had the highest hazard quotient (HQ, from 2.18 to 2.56) for adults from 2019 to 2021, while Ni, Cr, Pb, As, and BC showed high carcinogenic risks (CR > 1.0×10-6) for adults. The HQ values of Mn and As and the CR values of Pb and As showed constant or slight upwards trends during our observations, which is in contrast to the downward trends of other HMs and PM2.5. Mn, Cr, and BC are crucial toxicants in PM2.5. A significant shrink of southern region sourcesof HMs and BCshrank suggests the increased importance of local sources. Industry, dust, and biomass burning are the major contributors to the non-carcinogenic risks, while traffic emissions and industry are the dominant contributors to the carcinogenic risks in Beijing.

Regulation-driven changes in PM2.5 sources in China from 2013 to 2019, a critical review and trend analysis

Identifying changes in source-specific fine particles (PM2.5) over time is essential for evaluating the effectiveness of regulatory measures and informing future policy decisions. After the extreme haze events in China during 2013-14, more comprehensive and stringent policies were implemented to combat PM2.5 pollution. To determine the effectiveness of these policies, it is necessary to assess the changes in the specific source types to which the regulations pertain. Multiple studies have been conducted over the past decade to apportion PM2.5. The purpose of this study was to explore the available literature and conduct a critical review of the reliable results. In total, 5008 articles were screened, but only 48 studies were included for further analysis given our inclusion criteria including covering a monitoring period of ≥1 year and having enough speciation data to provide mass closure. Using these studies, we analyzed temporal and spatial trends across China from 2013 to 2019. We observed the overall decrease in the concentration contributions from all main source categories. The reductions from industry, coal and heavy oil combustion, and the related secondary sulfate were more notable, especially from 2013 to 2016-17. The contributions from biomass burning initially decreased but then increased slightly after 2016 in some locations despite new constraints on agricultural and household burning practices. Although the contributions from vehicle emissions and related secondary nitrate decreased, they gradually became the primary contributors to PM2.5 by ∼2017. Despite the substantial improvements achieved by the air pollution regulation implementations, further improvements in air quality will require additional aggressive actions, especially those targeting vehicular emissions. Ultimately, source apportionment studies based on extended duration, fixed-site sampling are recommended to provide a more thorough understanding of the sources impacting areas and transformations in PM2.5 sources prompted by regulatory actions.

Long-term source apportionment of PM2.5 across the contiguous United States (2000-2019) using a multilinear engine model

Identifying PM2.5 sources is crucial for effective air quality management and public health. This research used the Multilinear Engine (ME-2) model to analyze PM2.5 from 515 EPA Chemical Speciation Network (CSN) and Interagency Monitoring of Protected Visual Environments (IMPROVE) sites across the U.S. from 2000 to 2019. The U.S. was divided into nine regions for detailed analysis. A total of seven source types (tracers) were resolved across the country: (1) Soil/Dust (Si, Al, Ca and Fe); (2) Vehicle emissions (EC, OC, Cu and Zn); (3) Biomass/wood burning (K); (4) Heavy oil/coal combustion (Ni, V, Cl and As); (5) Secondary sulfate (SO42-); (6) Secondary nitrate (NO3-) and (7) Sea salt (Mg, Na, Cl and SO42-). Furthermore, we extracted and calculated secondary organic aerosols (SOA) based on the secondary sulfate and nitrate factors. Notably, significant reductions in secondary sulfate, nitrate, and heavy oil/coal combustion emissions reflect recent cuts in fossil-fueled power sector emissions. A decline in SOA suggests effective mitigation of their formation conditions or precursors. Despite these improvements, vehicle emissions and biomass burning show no significant decrease, highlighting the need for focused control on these persistent pollution sources for future air quality management.

Ambient volatile organic compounds in the Seoul metropolitan area of South Korea: Chemical reactivity, risks and source apportionment

The chemical reactivity, contribution of emission sources, and risk assessment of volatile organic compounds (VOCs) in the atmosphere of the Seoul metropolitan area (SMA) were analyzed. Datasets collected from 6 photochemical assessment monitoring stations (PAMS) of SMA from 2018 to 2021 were used. Alkenes and aromatics contributed significantly to ozone formation relative to the emission concentrations, and aromatics accounted for most of the secondary organic aerosols (SOA) formation in the SMA. The contributions of ozone and SOA formation were found to be notably higher at measurement stations in residential areas such as Guwol (GW) and Sosabon (SS) compared to other measurement stations. From the results of an emission source analysis, it was confirmed that anthropogenic sources such as combustion sources, vehicle exhaust, fuel evaporation, and solvent use had a significant effect at all measurement stations. Assessing the health risk, non-carcinogenic compounds were at acceptable level at all measurement stations. On the other hand, carcinogenic compounds were approaching risk level (10-4), thereby demanding immediate attention. The level of exposure to carcinogenic compounds increased by age group, and male was more vulnerable than female. It was found that SS had the highest level of exposure to carcinogens in the atmosphere of the population ages 60 or older. The health threat of the SMA population is expected due to direct exposure from inhalation of ambient toxic compounds and indirect exposure from ozone and PM2.5 formations through oxidation of VOCs. This study emphasizes the importance of addressing specific emission sources within the metropolitan area and developing comprehensive regional strategies to mitigate VOCs.

Disentangling fine particles (PM2.5) composition in Hanoi, Vietnam: Emission sources and oxidative potential

A comprehensive chemical characterization of fine particulate matter (PM2.5) was conducted at an urban site in one of the most densely populated cities of Vietnam, Hanoi. Chemical analysis of a series of 57 daily PM2.5 samples obtained in 2019-2020 included the quantification of a detailed set of chemical tracers as well as the oxidative potential (OP), which estimates the ability of PM to catalyze reactive oxygen species (ROS) generation in vivo as an initial step of health effects due to oxidative stress. The PM2.5 concentrations ranged from 8.3 to 148 μg m-3, with an annual average of 40.2 ± 26.3 μg m-3 (from September 2019 to December 2020). Our results obtained by applying the Positive Matrix Factorization (PMF) source-receptor apportionment model showed the contribution of nine PM2.5 sources. The main anthropogenic sources contributing to the PM mass concentrations were heavy fuel oil (HFO) combustion (25.3 %), biomass burning (20 %), primary traffic (7.6 %) and long-range transport aerosols (10.6 %). The OP activities were evaluated for the first time in an urban site in Vietnam. The average OPv levels obtained in our study were 3.9 ± 2.4 and 4.5 ± 3.2 nmol min-1 m-3 for OPDTT and OPAA, respectively. We assessed the contribution to OPDTT and OPAA of each PM2.5 source by applying multilinear regression models. It shows that the sources associated with human activities (HFO combustion, biomass burning and primary traffic) are the sources driving OP exposure, suggesting that they should be the first sources to be controlled in future mitigation strategies. This study gives for the first time an extensive and long-term chemical characterization of PM2.5, providing also a link between emission sources, ambient concentrations and exposure to air pollution at an urban site in Hanoi, Vietnam.

Effects of long-range transport on carboxylic acids, chlorinated VOCs, and oxidative potential in air pollution events

In the context of air quality research, the collection and analysis of fine particulate matter (PM2.5, with a diameter less than 2.5 μm) and volatile organic compound (VOCs) play a pivotal role in understanding and addressing environmental issues across the Korean Peninsula. PM2.5 and VOCs were collected over 4-hr intervals from October 17 to November 26, 2021 during the 2021 Satellite Integrated Joint Monitoring of Air Quality campaign at Olympic Park in the Republic of Korea to understand the factors controlling air quality over the Seoul Metropolitan Area. Source apportionment was performed using the positive matrix factorization (PMF) model incorporating PM2.5 and VOCs. The factor identified by chlorinated VOCs as a major component was presumed to be due to transboundary influx and was referred to as the long-range transport factor. The long-range transport factor of PM2.5 was composed of NO3-, SO42-, NH4+, and di-carboxylic acids. Back trajectory analysis showed that the airflows originated from China and passed through the west coast of Korea to the Korean Peninsula. In the PMF results using PM2.5 and VOCs, long-range transport factors were identified in both analyses, and the high correlation observed between these factors confirms that they were transported from abroad. The dithiothreitol oxidation potential normalized to quinine showed the highest oxidation potential during the same period as the long-range transport factors increased. In conclusion, PM2.5 from external sources significantly contribute to elevated levels of dithiothreitol assay-oxidative potential (DTT-OP) in Korea. The toxic concentration, expressed as the mean ± standard deviation, was determined to be 0.29 ± 0.05 μM/m³, peaking at 0.39 μM/m³. This level is 1.8 times higher than that observed outside the event period. A notable increase in secondary pollutants was observed during these periods. These pollutants are known to enhance oxidative potential, thereby potentially impacting human health.

When and why PM2.5 is high in Seoul, South Korea: Interpreting long-term (2015-2021) ground observations using machine learning and a chemical transport model

Seoul has high PM2.5 concentrations and has not attained the national annual average standard so far. To understand the reasons, we analyzed long-term (2015-2021) hourly observations of aerosols (PM2.5, NO3-, NH4+, SO42-, OC, and EC) and gases (CO, NO2, and SO2) from Seoul and Baekryeong Island, a background site in the upwind region of Seoul. We applied the weather normalization method for meteorological conditions and a 3-dimensional chemical transport model, GEOS-Chem, to identify the effect of policy implementation and aerosol formation mechanisms. The monthly mean PM2.5 ranges between about 20 μg m-3 (warm season) and about 40 μg m-3 (cold season) at both sites, but the annual decreasing rates were larger at Seoul than at Baengnyeong (-0.7 μg m-3 a-1 vs. -1.8 μg m-3 a-1) demonstrating the effectiveness of the local air quality policies including the Special Act on Air Quality in the Seoul Metropolitan Area (SAAQ-SMA) and the seasonal control measures. The weather-normalized monthly mean data shows the highest PM2.5 concentration in March and the lowest concentration in August throughout the 7 years with NO3- accounting for about 40 % of the difference between the two months at both sites. Taking together with the GEOS-Chem model results, which reproduced the elevated NO3- in March, we concluded the elevated atmospheric oxidant level increases in HNO3 (which is not available from the observation) and the still low temperatures in March promote rapid production of NO3-. We used Ox (≡ O3 + NO2) from the observation and OH from the GEOS-Chem as a proxy for the atmospheric oxidant level which can be a source of uncertainty. Thus, direct observations of OH and HNO3 are needed to provide convincing evidence. This study shows that reducing HNO3 levels through atmospheric oxidant level control in the cold season can be effective in PM2.5 mitigation in Seoul.

Insights into PM2.5 pollution of four small and medium-sized cities in Chinese representative regions: Chemical compositions, sources and health risks

Fine particles (PM2.5) pollution is still a severe issue in some cities in China, where the chemical characteristics of PM2.5 remain unclear due to limited studies there. Herein, we focused on PM2.5 pollution in small and medium-sized cities in key urban agglomerations and conducted a comprehensive study on the PM2.5 chemical characteristics, sources, and health risks. In the autumn and winter of 2019-2020, PM2.5 samples were collected simultaneously in four small and medium-sized cities in four key regions: Dingzhou (Beijing-Tianjin-Hebei region), Weinan (Fenwei Plain region), Fukang (Northern Slope of the Tianshan Mountain region), and Bozhou (Yangtze River Delta region). The results showed that secondary inorganic ions (43.1 %-67.0 %) and organic matter (OM, 8.6 %-36.4 %) were the main components of PM2.5 in all the cities. Specifically, Fukang with the most severe PM2.5 pollution had the highest proportion of SO42- (31.2 %), while the dominant components in other cities were NO3- and OM. The Multilinear Engine 2 (ME2) analysis identified five sources of PM2.5 in these cities. Coal combustion contributed most to PM2.5 in Fukang, but secondary sources in other cities. Combined with chemical characteristics and ME2 analysis, it was preliminarily determined that the primary emission of coal combustion had an important contribution to high SO42- in Fukang. Potential source contribution function (PSCF) analysis results showed that regional transport played an important role in PM2.5 in Dingzhou, Weinan and Bozhou, while PM2.5 in Fukang was mainly affected by short-range transport from surrounding areas. Finally, the health risk assessment indicated Mn was the dominant contributor to the total non-carcinogenic risks and Cr had higher carcinogenic risks in all cities. The findings provide a scientific basis for formulating more effective abatement strategies for PM2.5 pollution.

Identification of potential source regions and long-range transport routes/channels of marine PM2.5 at remote sites in East Asia

Long-range transport (LRT) of air masses in East Asia and their impacts on marine PM2.5 were explored. Situated in the leeward region of East Asia, Taiwan Island marked by its elevated Central Mountain Range (CMR) separates air masses into two distinct air currents. This study aims to investigate the transport of PM2.5 from the north to the leeward region. Six transport routes (A-F) were identified and further classified them into three main channels (i.e. East, West, and South Channels) based on their transport routes and potential sources. Green Island (Site GR) and Hengchun Peninsula (Site HC) exhibited similarities in their transport routes, with Central China, North China, and Korean Peninsula being the major source regions of PM2.5, particularly during the Asian Northeastern Monsoons (ANMs). Dongsha Island (Site DS) was influenced by both Central China and coastal regions of East China, indicating Asian continental outflow (ACO) as the major source of PM2.5. The positive matrix factorization (PMF) analysis of PM2.5 resolved that soil dust, sea salts, biomass burning, ship emissions, and secondary aerosols were the major sources. Northerly Channels (i.e. East and West Channels) were primarily influenced by ship emissions and secondary aerosols, while South Channel was dominated by oceanic spray and soil dust. The results of W-PSCF and W-CWT analysis indicated that three remote sites experienced significant contributions from Central China in the highest PM2.5 concentration range (75-100%). In contrast, PM2.5 in the 0-25% and 25-50% ranges primarily originated from the open seas, with ship emissions being the prominent source. It suggested that northern regions with heavy industrialization and urbanization have impacts on high PM2.5 concentrations, while open seas are the main sources of low PM2.5 concentrations.

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.

Analysis of PM2.5 inorganic and organic constituents to resolve contributing sources in Seoul, South Korea and Beijing, China and their possible associations with cytokine IL-8

China and South Korea are the most polluted countries in East Asia due to significant urbanization and extensive industrial activities. As neighboring countries, collaborative management plans to maximize public health in both countries can be helpful in reducing transboundary air pollution. To support such planning, PM2.5 inorganic and organic species were determined in simultaneously collected PM2.5 integrated filters. The resulting data were used as inputs to positive matrix factorization, which identified nine sources at the ambient air monitoring sites in both sites. Secondary nitrate, secondary sulfate/oil combustion, soil, mobile, incinerator, biomass burning, and secondary organic carbon (SOC) were found to be sources at both sampling sites. Industry I and II were only identified in Seoul, whereas combustion and road dust sources were only identified in Beijing. A subset of samples was selected for exposure assessment. The expression levels of IL-8 were significantly higher in Beijing (167.7 pg/mL) than in Seoul (72.7 pg/mL). The associations between the PM2.5 chemical constituents and its contributing sources with PM2.5-induced inflammatory cytokine (interleukin-8, IL-8) levels in human bronchial epithelial cells were investigated. For Seoul, the soil followed by the secondary nitrate and the biomass burning showed increase with IL-8 production. However, for the Beijing, the secondary nitrate exhibited the highest association with IL-8 production and SOC and biomass burning showed modest increase with IL-8. As one of the highest contributing sources in both cities, secondary nitrate showed an association with IL-8 production. The soil source having the strongest association with IL-8 production was found only for Seoul, whereas SOC showed a modest association only for Beijing. This study can provide the scientific basis for identifying the sources to be prioritized for control to provide effective mitigation of particulate air pollution in each city and thereby improve public health.

Control priority based on source-specific DALYs of PM2.5-bound heavy metals by PMF-PSCF-IsoSource model in urban and suburban Beijing

To determine the priority control sources, an approach was proposed to evaluate the source-specific contribution to health risks from inhaling PM2.5-bound heavy metals (PBHMs). A total of 482 daily PM2.5 samples were collected from urban and suburban areas of Beijing, China, between 2018 and 2019. In addition to the PMF-PSCF model, a Pb isotopic IsoSource model was built for more reliable source apportionment. By using the comprehensive indicator of disability-adjusted life years (DALYs), carcinogenic and noncarcinogenic health risks could be compared on a unified scale. The study found that the annual average concentrations of the total PBHMs were significantly higher in suburban areas than in urban areas, with significantly higher concentrations during the heating season than during the nonheating season. Comprehensive dust accounted for the largest contribution to the concentration of PBHMs, while coal combustion contributed the most to the DALYs associated with PBHMs. These results suggest that prioritizing the control of coal combustion could effectively reduce the disease burden associated with PBHMs, leading to notable public health benefits.

Effect of industrialization on the differences in sources and composition of ambient PM2.5 in two Southern Ontario locations

PM2.5 was sampled over a seven-year period (2013-2019) at two locations ∼50 km apart in Southern Ontario (concurrently for five years: 2015-2019). One is a heavily industrialized site (Hamilton), while the other was a rural site (Simcoe). To assess the impact of industrialization on the composition and sources of PM affecting air quality in these two locations, positive matrix factorization coupled with dispersion normalization (DN-PMF) was used to identify six and eight factors at Simcoe and Hamilton, respectively. The Simcoe factors in order of diminishing PM mass contribution were: particulate sulphate (pSO4), secondary organic aerosol (SOA), crustal matter, particulate nitrate (pNO3), biomass burning, and vehicular emissions. At Hamilton, the effects of industrialization were observed by the ∼36% higher average ambient PM2.5 concentration for the study period as well as the presence of factors unique to metallurgy, i.e., coking and steelmaking, compared to Simcoe. The coking and steelmaking factors contributed ∼15% to the PM mass at Hamilton. Seasonal variants of appropriate nonparametric trend tests with the associated slopes (Sen's) were used to assess statistically significant changes in the factor contributions to PM2.5 over time. Specifically at Hamilton, a significant decline in PM contributions was noted for coking (-0.03 μg/m³/yr or -4.1%/yr) while steelmaking showed no statistically significant decline over the study period. Other factors at Hamilton that showed statistically significant declines over the study period were: pSO4 (-0.27 μg/m³/yr or -12.6%/yr), biomass burning (-0.05 μg/m³/yr or -9.02%/yr), crustal matter (-0.03 μg/m³/yr or -5.28%/yr). These factors mainly accounted for the significant decline in PM2.5 over the study period (-0.35 μg/m³/yr or -4.24%/yr). This work shows the importance of long-term monitoring in assessing the unique contributions and temporal changes of industrialization on air quality in Ontario and similarly affected locations.

Comparing sources of carbonaceous aerosols during haze and nonhaze periods in two northern Chinese cities

Radiocarbon (14C), stable carbon isotope (13C), and levoglucosan in PM2.5 were measured in two northern Chinese cities during haze events and nonhaze periods in January 2019, to ascertain the sources and their differences in carbonaceous aerosols between the two periods. The contribution of primary vehicle emissions (17.8 ± 3.7%) to total carbon in Beijing during that haze event was higher than that of primary coal combustion (7.3 ± 4.2%), and it increased significantly (7.1%) compared to the nonhaze period. The contribution of primary vehicle emissions (4.1 ± 2.8%) was close to that of primary coal combustion (4.3 ± 3.3%) during the haze event in Xi'an, and the contribution of primary vehicle emissions decreased by 5.8% compared to the nonhaze period. Primary biomass burning contributed 21.1 ± 10.5% during the haze event in Beijing and 40.9 ± 6.6% in Xi'an (with an increase of 3.3% compared with the nonhaze period). The contribution of secondary fossil fuel sources to total secondary organic carbon increased by 29.2% during the haze event in Beijing and by 18.4% in Xi'an compared to the nonhaze period. These results indicate that specific management measures for air pollution need to be strengthened in different Chinese cities in the future, that is, controlling vehicle emissions in Beijing and restricting the use of coal and biomass fuels in winter in Xi'an.

Removal of Particulate Matter by a Non-Powered Brush Filter Using Electrostatic Forces

In urban areas, a major source of harmful particulate matter is generated by vehicles. In particular, bus stops, where people often stay for public transportation, generate high concentrations of particulate matter compared to the general atmosphere. In this study, a non-powered type brush filter that generates electrostatic force without using a separate power source was developed to manage the concentration of particulate matter exposed at bus stops, and the removal performance of particulate matter was evaluated. The dust collection performance of the non-motorized brush filter varied by material, with particle removal efficiencies of 82.1 ± 3.4, 76.1 ± 4.7, and 73.7 ± 4.5% for horse hair, nylon, and stainless steel, respectively. In conditions without the fan running to see the effect of airflow, the particle removal efficiency was relatively low at 58.2 ± 8.4, 53.6 ± 9.2, and 58.0 ± 7.3%. Then, to check the dust collection performance according to the density, the number of brushes was increased to densify the density, and the horse hair, nylon, and stainless steel brush filters showed a maximum dust collection performance of 89.6 ± 2.2, 88.3 ± 3.2, and 82.1 ± 3.8%, respectively. To determine the replacement cycle of the non-powered brush filter, the particulate removal performance was initially 88.0 ± 3.2% when five horse hair brushes were used. Over time, particulate matter tended to gradually decrease, but after a period of time, particulate matter tended to increase again. The purpose of this study is to evaluate the particulate matter removal performance using a brush filter that generates electrostatic force without a separate power source. This study's brush filter is expected to solve the maintenance problems caused by the purchase and frequent replacement of expensive HEPA filters that occur with existing abatement devices, and the ozone problems caused by abatement devices that use high voltages.

PM2.5-bound polyhalogenated carbazoles (PHCZs) in urban Beijing, China: Occurrence and the source implication

Polyhalogenated carbazoles (PHCZs) are recently raising much attention due to their toxicity and ubiquitous environmental distribution. However, little knowledge is known about their ambient occurrences and the potential source. In this study, we developed an analytical method based on GC-MS/MS to simultaneously determine 11 PHCZs in PM_2.5 from urban Beijing, China. The optimized method provided low method limit of quantifications (MLOQs, 1.45-7.39 fg/m³) and satisfied recoveries (73.4%-109.5%). This method was applied to analyze the PHCZs in the outdoor PM_2.5 (n = 46) and fly ash (n = 6) collected from 3 kinds of surrounding incinerator plants (steel plant, medical waste incinerator and domestic waste incinerator). The levels of ∑₁₁PHCZs in PM_2.5 ranged from 0.117 to 5.54 pg/m³ (median 1.18 pg/m³). 3-chloro-9H-carbazole (3-CCZ), 3-bromo-9H-carbazole (3-BCZ), and 3,6-dichloro-9H-carbazole (36-CCZ) were the dominant compounds, accounting for 93%. 3-CCZ and 3-BCZ were significantly higher in winter due to the high PM_2.5 concentration, while 36-CCZ was higher in spring, which may be related to the resuspending of surface soil. Furthermore, the levels of ∑₁₁PHCZs in fly ash ranged from 338 to 6101 pg/g. 3-CCZ, 3-BCZ and 36-CCZ accounted for 86.0%. The congener profiles of PHCZs between fly ash and PM_2.5 were highly similar, indicating that combustion process could be an important source of ambient PHCZs. To the best of our knowledge, this is the first research providing the occurrences of PHCZs in outdoor PM_2.5.

Variations of PM2.5-bound elements and their associated effects during long-distance transport of dust storms: Insights from multi-sites observations

Dust storms are a significant concern because of their adverse effects on ambient air quality and human health. To investigate the evolution of dust storms during long-distance transport and its impacts on air quality and human health risks in cities along the transport pathway, we monitored the major fraction of dust (i.e., particle-bound elements) online in four cities in northern China during March 2021. Three dust events originating from the Gobi Desert of North China and Mongolia and the Taklimakan Desert of Northwest China were captured. We investigated the source regions of dust storms using daily multi-sensor absorbing aerosol index products, backward trajectories, and specific element ratios, identified and quantified sources of particle-bound elements using Positive Matrix Factorization model, and calculated the carcinogenic and non-carcinogenic risks of elements using a health risk assessment model. Our results indicated that under the influence of dust storms, mass concentrations of crustal elements increased up to dozens of times in cities near the dust source and up to ten times in cities farther from the source. In contrast, anthropogenic elements increased less or even decreased, depending on the relative contributions of the increase caused by accumulation of dust itself and entrainment along the transport path and the decrease caused by dilution of high wind speeds. Si/Fe ratio was found to be a valuable indicator for characterizing the attenuation of the amount of dust along its transport pathways, especially for the case originated from northern source regions. This study highlights the significant role of source regions, intensity and attenuation rates of dust storms, and wind speeds in determining the increased levels of element concentrations during dust storms and its associated impacts on downwind areas. Furthermore, non-carcinogenic risks of particle-bound elements increased at all sites during dust events, emphasizing the importance of personal exposure protection during dust storms.

Outdoor Health Risk of Atmospheric Particulate Matter at Night in Xi'an, Northwestern China

The deterioration of air quality via anthropogenic activities during the night period has been deemed a serious concern among the scientific community. Thereby, we explored the outdoor particulate matter (PM) concentration and the contributions from various sources during the day and night in winter and spring 2021 in a megacity, northwestern China. The results revealed that the changes in chemical compositions of PM and sources (motor vehicles, industrial emissions, coal combustion) at night lead to substantial PM toxicity, oxidative potential (OP), and OP/PM per unit mass, indicating high oxidative toxicity and exposure risk at nighttime. Furthermore, higher environmentally persistent free radical (EPFR) concentration and its significant correlation with OP were observed, suggesting that EPFRs cause reactive oxygen species (ROS) formation. Moreover, the noncarcinogenic and carcinogenic risks were systematically explained and spatialized to children and adults, highlighting intensified hotspots to epidemiological researchers. This better understanding of day-night-based PM formation pathways and their hazardous impact will assist to guide measures to diminish the toxicity of PM and reduce the disease led by air pollution.

Emissions from ships' activities in the anchorage zone: A potential source of sub-micron aerosols in port areas

Busan Port is among the world's top ten most air-polluted ports, but the role of the anchorage zone as a significant contributor to pollution has not been studied. To assess the emission characteristics of sub-micron aerosols, a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) was deployed in Busan, South Korea from September 10 to October 6, 2020. The concentration of all AMS-identified species and black carbon were highest when the winds came from the anchorage zone (11.9 µg·m^-3) and lowest with winds from the open ocean (6.64 µg·m^-3). The positive matrix factorization model identified one hydrocarbon-like organic aerosol (HOA) and two oxygenated organic aerosol (OOA) sources. HOAs were highest with winds from Busan Port, while oxidized OOAs were predominant with winds from the anchorage zone (less oxidized) and the open ocean (more oxidized). We calculated the emissions from the anchorage zone using ship activity data and compared them to the total emissions from Busan Port. Our results suggest that emissions from ship activities in the anchorage zone should be considered a significant source of pollution in the Busan Port area, especially given the substantial contributions of gaseous emissions (NOx: 8.78%; volatile organic compounds: 7.52%) and their oxidized moieties as secondary aerosols.

Trends of source apportioned PM2.5 in Tianjin over 2013-2019: Impacts of Clean Air Actions

A long-term (2013-2019) PM_2.5 speciation dataset measured in Tianjin, the largest industrial city in northern China, was analyzed with dispersion normalized positive matrix factorization (DN-PMF). The trends of source apportioned PM_2.5 were used to assess the effectiveness of source-specific control policies and measures in support of the two China's Clean Air Actions implemented nationwide in 2013-2017 and 2018-2020, respectively. Eight sources were resolved from the DN-PMF analysis: coal combustion (CC), biomass burning (BB), vehicular emissions, dust, steelmaking and galvanizing emissions, a mixed sulfate-rich factor and secondary nitrate. After adjustment for meteorological fluctuations, a substantial improvement in PM_2.5 air quality was observed in Tianjin with decreases in PM_2.5 at an annual rate of 6.6%/y. PM_2.5 from CC decreased by 4.1%/y. The reductions in SO₂ concentration, PM_2.5 contributed by CC, and sulfate demonstrated the improved control of CC-related emissions and fuel quality. Policies aimed at eliminating winter-heating pollution have had substantial success as shown by reduced heating-related SO₂, CC, and sulfate from 2013 to 2019. The two industrial source types showed sharp drops after the 2013 mandated controls went into effect to phaseout outdated iron/steel production and enforce tighter emission standards for these industries. BB reduced significantly by 2016 and remained low due to the no open field burning policy. Vehicular emissions and road/soil dust declined over the Action's first phase followed by positive upward trends, showing that further emission controls are needed. Nitrate concentrations remained constant although NO_X emissions dropped significantly. The lack of a decrease in nitrate may result from increased ammonia emissions from enhanced vehicular NO_X controls. The port and shipping emissions were evident implying their impacts on coastal air quality. These results affirm the effectiveness of the Clean Air Actions in reducing primary anthropogenic emissions. However, further emission reductions are needed to meet global health-based air quality standards.

Predicting latent source-specific PM2.5 pollution from regional sources at unmonitored sites by Bayesian spatial multivariate receptor modeling

Fine particulate matter (PM_2.5) has been a pollutant of main interest globally for more than two decades, owing to its well-known adverse health effects. For developing effective management strategies for PM_2.5, it is vital to identify its major sources and quantify how much they contribute to ambient PM_2.5 concentrations. With the expanded monitoring efforts established during recent decades in Korea, speciated PM_2.5 data needed for source apportionment of PM_2.5 are now available for multiple sites (cities). However, many cities in Korea still do not have any speciated PM_2.5 monitoring station, although quantification of source contributions for those cities is in great need. While there have been many PM_2.5 source apportionment studies throughout the world for several decades based on monitoring data collected from receptor site(s), none of those receptor-oriented studies could predict unobserved source contributions at unmonitored sites. This study predicts source contributions of PM_2.5 at unmonitored locations using a recently developed novel spatial multivariate receptor modeling (BSMRM) approach, which incorporates spatial correlation in data into modeling and estimation for spatial prediction of latent source contributions. The validity of BSMRM results is also assessed based on the data from a test site (city), not used in model development and estimation.

Do heat waves worsen air quality? A 21-year observational study in Seoul, South Korea

Heat waves are generally known to deteriorate air quality. However, the impacts of heat waves on air quality can substantially vary depending on characteristics of heat waves. In this study, we examine air quality changes in Seoul during heat waves and their associations with large-scale atmospheric patterns. For this, air quality data from 25 stations and meteorological data from 23 weather stations and reanalysis datasets during July and August of 2001-2021 are used. Under heat waves, the mean daily PM₁₀, NO₂, and CO concentrations decrease by 7.9 %, 6.1 %, and 4.6 %, respectively, whereas the mean daily PM_2.5, O₃, and SO₂ concentrations increase by 4.1 %, 17.2 %, and 2.9 %, respectively. The atmospheric circulation under heat waves is less favorable for long-range transport of air pollutants to Seoul. The PM_2.5/PM₁₀ ratio increases under heat waves, indicating that the secondary formation of aerosols becomes more important under heat waves. 37 % of the heat wave days are accompanied by severe O₃ pollution exceeding the O₃ concentration standard in South Korea. There is a significant variability of air quality in Seoul within heat waves. The heat wave days with higher concentrations of PM_2.5, PM₁₀, O₃, NO₂, and CO than their non-heat wave means exhibit a prominent difference in large-scale atmospheric pattern from the heat wave days with lower concentrations. This difference is characterized by a zonal wave-like pattern of geopotential height, which is similar to the circumglobal teleconnection pattern known as one of the major patterns for heat waves in South Korea. This zonal wave-like pattern produces more stagnant conditions over Seoul.

Source apportionment of ambient PM2.5 in an industrialized city using dispersion-normalized, multi-time resolution factor analyses

Ambient fine particulate matter (PM_2.5) data were collected in the lower City of Hamilton, Ontario to apportion the sources of this pollutant over an 18-month period. Hamilton has complex topographical features that may result in worsened air pollution within the lower city, thus, dispersion-normalized, multi-time resolution factor analysis (DN-MT-FA) was used to identify and quantify contributions of factors in a manner that reduced the influence of local meteorology. These factors were secondary organic aerosols type 1 (SOA_1), particulate nitrate (pNO3), particulate sulphate (pSO4), primary traffic organic matter (PTOM), Steel/metal processing and vehicular road dust emissions (Steel & Mobile) and, secondary organic aerosols type 2 (SOA_2) with origins ranging from mainly regional to mainly local. Factors that were mainly local (PTOM, Steel & Mobile, SOA_2) contributed up to 17% of the average PM_2.5 mass while mixed local/regional factors (pNO3, pSO4) made up 43% on average, indicating the potential for further reduction of harmful PM concentrations locally. Of particular interest from a health protection perspective, was the composition of PM_2.5 on days when an exceedance of the 24-hr WHO air quality guideline for this pollutant was observed. In general, SOA_1 was found to drive summer exceedances while pNO3 dominated in the winter. During the summer period, SOA_1 was attributable to wildfires in the northern parts of Canada while local traffic sources in winter contributed to the high levels of pNO3. While local, industrial factors only had minor relative mass contributions during exceedances, they are high in highly oxidized organic species (SOA_2) and toxic metals (Steel & Mobile). Thus, they are likely to have more impacts on human health. The methods and results described in this work will be useful in understanding prevalent sources of particulate matter pollution in the ambient air in the presence of complex topography and meteorological effects.

Dynamic harmonization of source-oriented and receptor models for source apportionment

Millions of premature mortalities are caused by the air pollution of fine particulate matter with aerodynamic diameters less than 2.5 μm (PM_2.5) globally per year. To effectively control the dominant emission sources and abate air pollution, source apportionment of PM_2.5 is normally conducted to quantify the contributions of various sources, but the results of different methods might be inconsistent. In this study, we dynamically harmonized the results from the two dominant source apportionment methods, the source-oriented and receptor models, by updating the emission inventories of primary PM_2.5 from the major sectors based on the Bayesian Inference. An adjoint model was developed to efficiently construct the source-receptor sensitivity matrix, which was the critical information for the updates, and depicted the response of measurements to the changes in the emissions of various sources in different regions. The harmonized method was applied to a measurement campaign in Beijing from January to February 2021. The results suggested a significant reduction of primary PM_2.5 emissions in Beijing. Compared with the baseline emission inventory of 2017, the primary PM_2.5 emissions from the local residential combustion and industry in Beijing had significantly declined by about 90 % during the investigated period of the year, and the traffic emission decreased by about 50 %. The proposed methods successfully identified the temporally dynamic changes in the emissions induced by the Spring Festival. The methods could be a promising pathway for the harmonization of source-oriented and receptor source apportionment models.

Health Risk Assessment of Heavy Metals in Shallow Groundwater of Coal-Poultry Farming Districts

This study aimed to assess the heavy metal (Mn, Ni, Cu, Zn, Sr, Cd, Pb, and Cr) pollution characteristics, sources, and human health risks in shallow groundwater in the impact zones of urban and rural semi-intensive poultry farms in Suzhou City. Ordinary kriging interpolation showed that poultry farming contributed substantially to the pollution of shallow groundwater by Mn, Zn, and Cu. Positive matrix factorization was applied to identify the sources of heavy metals, and the health risks were assessed based on the hazard index and carcinogenic risks of the various sources. Heavy metal enrichment was closely related to anthropogenic activities. In addition, four sources were identified: poultry manure (29.33%), natural source (27.94%), industrial activities (22.29%), and poultry wastewater (20.48%). The main exposure route of carcinogenic and non-carcinogenic risks to adults and children was oral ingestion. The non-carcinogenic risk of oral ingestion in children was higher than that in adults; the carcinogenic risk was higher in adults than in children. Poultry manure (42.0%) was considered the largest contributor to non-carcinogenic risk, followed by poultry wastewater (21%), industrial activities (20%), and natural sources (17%). Industrial activity (44%) was the primary contributor to carcinogenic risk, followed by poultry wastewater (25%), poultry manure (19%), and natural sources (12%).