Characterization and source apportionment of PM2.5 based on error estimation from EPA PMF 5.0 model at a medium city in China

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.

Fine particle trace elements at a mountain site in southern China: Source identification, transport, and health risks

Trace elements in atmospheric particulate matter play a significant role in air quality, human health, and biogeochemical cycles. In this study, the trace elements (Ca, Al, K, Fe, Na, Mg, Zn, Pb, Mn, Ti, Cu, Cr, Sr, Ni) in PM2.5 samples collected at the summit of Mt. Lushan were analyzed to quantify their abundance, source, transport, and health risks. During the whole sampling period, the major trace elements was Ca, Al, and K. While the trace metals with the lowest concentrations were Sr, Ni, Rb, and Cd. The trace elements were influenced by air mass transport routes, exhibiting an increasing trend of crustal elements in the northwesterly airmass and anthropogenic elements (Zn, Mn, Cu, and Ni) in the easterly air masses. Construction dust, coal + biomass burning, vehicle emission, urban nitrate-rich + urban waste incineration emissions, and soil dust + industry emissions were common sources of PM2.5 on Mt. Lushan. Different air mass transport routes had various source contribution patterns. These results indicate that trace elements at Mt. Lushan are influenced by regional anthropogenic emissions and monsoon-dominated trace element transport. The total resulting cancer risk value that these elements posed were below the acceptable risk value of 1 × 10-6, while the non-carcinogenic risk value (1.72) was higher than the safety level, suggesting that non-carcinogenic effects due to these trace elements inhalation were likely to occur. Vehicle emission and coal + biomass burning were the common dominant sources of non-cancer risks posed by trace elements at Mt. Lushan.

Characteristics of aerosol aminiums over a coastal city in North China: Insights from the divergent impacts of marine and terrestrial influences

Aminium ions, as crucial alkaline components within fine atmospheric particles, have a notable influence on new particle formation and haze occurrence. Their concentrations within coastal atmosphere depict considerable variation due to the interplay of distinctive marine and terrestrial sources, further complicated by dynamic meteorological conditions. This study conducted a comprehensive examination of aminiums ions concentrations, with a particular focus on methylaminium (MMAH+), dimethylaminium (DMAH+), trimethylaminium (TMAH+), and triethylaminium (TEAH+) within PM2.5, over varying seasons (summer, autumn, and winter of 2019 and summer of 2021), at an urban site in the coastal megacity of Qingdao, Northern China. The investigations revealed that the total concentration of particulate aminium ions (∑Aminium) was 21.6 ± 23.6 ng/m3, exhibiting higher values in the autumn and winter compared to the two summer periods. Considering diurnal variations during autumn and winter, concentrations of particulate aminium ions (excluding TEAH+) exhibited a slight increase during the day compared to night, with a notable peak during the morning hours. However, it was not the case for TEAH+, which was argued to be readily oxidized by ambient oxidants in the afternoon. Additionally, the ∑Aminium within the summer demonstrated markedly elevated levels during the day compared to night, potentially attributed to daytime sea fog associated with sea-land breeze interactions. Positive matrix factorization results indicate terrestrial anthropogenic emissions, including vehicle emission mixed with road dust and primary pollution, as the primary sources of MMAH+ and DMAH+. Conversely, TMAH+ was predominantly emitted from agricultural and marine sources. With the dominance of sea breeze in summer, TMAH+ was identified as a primary marine emission correlated with sea salt, while MMAH+, DMAH+, and TEAH+ were postulated to undergo secondary formation. Furthermore, a notable inverse correlation was observed between TMAH+ and methanesulfonate in PM2.5, consistent with dynamic emissions of sulfur-content and nitrogen-content gases reported in the literature.

Light absorption enhancement of black carbon and its impact factors during winter in a megacity of the Sichuan Basin, China

Carbonaceous aerosols play a vital role in global climate patterns due to their potent light absorption capabilities. However, the light absorption enhancement effect (Eabs) of black carbon (BC) is still subject to great uncertainties due to factors such as the mixing state, coating material, and particle size distribution. In this study, fine particulate matter (PM2.5) samples were collected in Chengdu, a megacity in the Sichuan Basin, during the winter of 2020 and 2021. The chemical components of PM2.5 and the light absorption properties of BC were investigated. The results revealed that secondary inorganic aerosols and carbonaceous aerosols were the dominant components in PM2.5. Additionally, the aerosol filter filtration-dissolution (AFD) treatment could improve the accuracy of measuring elemental carbon (EC) through thermal/optical analysis. During winter in Chengdu, the absorption enhancement values of BC ranged between 1.56 and 2.27, depending on the absorption wavelength and the mixing state of BC and non-BC materials. The presence of internally mixed BC and non-BC materials significantly contributed to Eabs, accounting for an average of 68 % at 405 nm and 100 % at 635 nm. The thickness of the BC coating influenced Eabs, displaying an increasing-then-decreasing trend. This trend was primarily attributed to the hygroscopic growth and dehydration shrinkage of particulate matter. Nitrate, as the major component of BC coating, played a crucial role in the lensing effect and exhibited fast growth during variation in Eabs. By combining the results from PMF, we identified the secondary formation and vehicle emission as the primary contributors to Eabs. Consequently, this study can provide valuable insights into the optical parameters, which are essential for assessing the environmental quality, improving regional atmospheric conditions, and formulating effective air pollution control strategies.

High spatial resolution estimates of major PM2.5 components and their associated health risks in Hong Kong using a coupled land use regression and health risk assessment approach

Few studies have focused on the spatial distribution of the typical components and source tracers of PM2.5 and their associated health risks, despite the fact that the chemical components of PM2.5 pose potentially significant and independent risks to human health. The main objective of this study was to evaluate the spatial distribution of major PM2.5 components and their associated health risks in Hong Kong using a coupled land use regression and health risk assessment modeling approach. The established land use regression models of the major PM2.5 components and source tracers achieved a relatively high statistical performance, with training and leave-one-out cross-validation R2 values of 0.85-0.96 and 0.62-0.88, respectively. The high spatial resolution (500 m × 500 m) distribution patterns of the chemical components of PM2.5 showed the heterogeneity of population exposure to different components and the related potential health risks, as evidenced by the weak spatial correlations between the mass of PM2.5 and some components. Elemental carbon, nickel, arsenic, and chromium from PM2.5 made major contributions to the total health risk and should therefore be reduced further. Our results will enable researchers to determine independent associations between exposure to the various components of PM2.5 and health endpoints in epidemiological studies.

Urban surface classification using semi-supervised domain adaptive deep learning models and its application in urban environment studies

High-resolution urban surface information, e.g., the fraction of impervious/pervious surface, is pivotal in studies of local thermal/wind environments and air pollution. In this study, we introduced and validated a domain adaptive land cover classification model, to automatically classify Google Earth images into pixel-based land cover maps. By combining domain adaptation (DA) and semi-supervised learning (SSL) techniques, our model demonstrates its effectiveness even when trained with a limited dataset derived from Gaofen2 (GF2) satellite images. The model's overall accuracy on the translated GF2 dataset improved significantly from 19.5% to 75.2%, and on the Google Earth image dataset from 23.1% to 61.5%. The overall accuracy is 2.9% and 3.4% higher than when using only DA. Furthermore, with this model, we derived land cover maps and investigated the impact of land surface composition on the local meteorological parameters and air pollutant concentrations in the three most developed urban agglomerations in China, i.e., Beijing, Shanghai and the Great Bay Area (GBA). Our correlation analysis reveals that air temperature exhibits a strong positive correlation with neighboring artificial impervious surfaces, with Pearson correlation coefficients higher than 0.6 in all areas except during the spring in the GBA. However, the correlation between air pollutants and land surface composition is notably weaker and more variable. The primary contribution of this paper is to provide an efficient method for urban land cover extraction which will be of great value for assessing the urban surface composition, quantifying the impact of land use/land cover, and facilitating the development of informed policies.

Chemical Source Profiles and Toxicity Assessment of Urban Fugitive Dust PM2.5 in Guanzhong Plain, China

Urban fugitive dust is a significant contributor to atmospheric PM2.5 and a potential risk to humans. In 2019, both road dust and construction dust were collected from four cities, including Xi'an, Xianyang, Baoji, and Tongchuan, in Guanzhong Plain, China. Elements, water-soluble ions, and carbonaceous fractions were determined to establish the chemical source profile. High enrichment degrees of Se, Sc, Cl, and Zn in both road dust and construction dust indicated that the industrial system and energy consumption influenced Guanzhong Plain strongly. According to the coefficient of divergence, the two datasets within Xianyang and Tongchuan were similar. Combined with the chemical profile, road dust was affected by more stationary emission sources than construction dust in Xi'an, while biomass burning and vehicle exhaust contributed more to road dust than construction dust in Baoji. Moreover, the health risk of heavy metal was assessed, and corresponding influencing factors were identified. Road dust in all cities showed a non-negligible non-carcinogenic risk for children. Ingestion and inhalation were the main exposure pathways to which As and Co contributed the most, respectively. The land-use regression model revealed that the first-class road in a 100 m radius impacted all high-risk level metals, and the commercial building material and enterprises weakly influenced Co and Pb, respectively.

Distribution, source identification and ecological effects of aerosol dissolved nutrients in the Bohai Bay

The atmospheric aerosols around the Bohai Bay are affected intensively by the surrounding industrial, shipping and other human activities. Although atmospheric dry deposition is an important way for nutrients to enter the Bohai Bay, few studies explore the distribution patterns, source and deposition fluxes of typical nutrients in aerosols and their impacts on the marine ecosystem. This paper explored the spatial-temporal distribution of typical aerosol nutrients in summer and autumn, and their source and ecological effects were illustrated further. The mean concentration of dissolved total phosphorus (DTP), dissolved total nitrogen (DTN), dissolved organic nitrogen (DON), dissolved inorganic nitrogen (DIN), ammonium (NH₄-N), nitrate (NO₃-N), nitrite (NO₂-N), silicate (SiO₃-Si), phosphate (PO₄-P), and dissolved organic phosphorus (DOP) were 31.22, 847.22, 288.19, 559.77, 288.19, 304.00, 253.65, 2.12, 15.74 and 15.48 nmol/m³, respectively, while their fluxes were corresponding to 0.61, 8.36, 2.52, 4.90, 1.41, 2.49, 0.02, 0.04, 0.19 and 0.26 mmol/(m² month). Typical aerosol nutrient concentrations in autumn were mostly higher than those in summer, with high values occurring mainly in the central region. The potential sources of pollution were mainly concentrated in Shandong and Mongolia, and the sources of pollution were mainly agriculture, dust and industry. The large N:P and N:Si ratios in the dry deposition likely exacerbated Si and P limitation in the water column. These results provided the data basis for evaluating the pollution status and revealed that the dry deposition of aerosol nutrients should not be neglected by the ecological environment in the Bohai Bay.

Comparison of the sources and oxidative potential of PM2.5 during winter time in large cities in China and South Korea

Regional air pollution is rising in Northeast Asia due to increasing energy consumption resulting from a growing population and intensifying industrialization. This study analyzes the sources of air pollution using fine particulate matter (PM_2.5) sampling from the atmosphere over Korea and China. We then use this analysis to further investigate the relationship between organic compounds (source tracers) and the oxidative potential of PM_2.5. The PM_2.5 concentration during winter measured at a measurement stations in Korea showed no significant variation year-to-year. The PM_2.5 concentrations measured during winter at a site near Beijing, China were 62.45 μg/m³ in 2018 and 33.07 μg/m³ in 2020. The sources, as determined from PMF, were analyzed at a site in Korea, the sources as secondary nitrate (34.10 %), secondary sulfate (20.20 %), coal combustion (4.01 %), vehicle emission (8.55 %), cooking and biomass burning (18.39 %), dust (8.45 %), and SOA (6.29 %) were identified. At a site in China, secondary nitrate (17.54 %), secondary sulfate (12.03 %), coal combustion (15.53 %), vehicle emission (12.43 %), cooking and biomass burning (9.25 %), dust (26.40 %), secondary organic aerosol (6.82 %) were identified. Our results show secondary organic carbon had a positive association with oxidative potential in Korea while primary organic carbon presented higher correlation with oxidative potential in China. Further, the ECMWF Reanalysis v5 (ERA5) wind field during the high PM_2.5 events demonstrated airflow from the west coast of China resulting in high polar organic compounds at the Korean monitoring site. The results further support that aged PM_2.5, which contains secondary products, leads to increased oxidative potential. The results presented explain the high concentrations of secondary products and the impact on the biological activities of PM_2.5, supporting additional actions to address the impacts of long-range transport of PM_2.5.

Spatiotemporal Evolution and Driving Forces of PM2.5 in Urban Agglomerations in China

With the rapid development of China's economy, the process of industrialization and urbanization is accelerating, and environmental pollution is becoming more and more serious. The urban agglomerations (UAs) are the fastest growing economy and are also areas with serious air pollution. Based on the monthly mean PM_2.5 concentration data of 20 UAs in China from 2015 to 2019, the spatiotemporal distribution characteristics of PM_2.5 were analyzed in UAs. The effects of natural and social factors on PM_2.5 concentrations in 20 UAs were quantified using the geographic detector. The results showed that (1) most UAs in China showed the most severe pollution in winter and the least in summer. Seasonal differences were most significant in the Central Henan and Central Shanxi UAs. However, the PM_2.5 was highest in March in the central Yunnan UA, and the Harbin-Changchun and mid-southern Liaoning UAs had the highest PM_2.5 in October. (2) The highest PM_2.5 concentrations were located in northern China, with an overall decreasing trend of pollution. Among them, the Beijing-Tianjin-Hebei, central Shanxi, central Henan, and Shandong Peninsula UAs had the highest concentrations of PM_2.5. Although most of the UAs had severe pollution in winter, the central Yunnan, Beibu Gulf, and the West Coast of the Strait UAs had lower PM_2.5 concentrations in winter. These areas are mountainous, have high temperatures, and are subject to land and sea breezes, which makes the pollutants more conducive to diffusion. (3) In most UAs, socioeconomic factors such as social electricity consumption, car ownership, and the use of foreign investment are the main factors affecting PM_2.5 concentration. However, PM_2.5 in Beijing-Tianjin-Hebei and the middle and lower reaches of the Yangtze River are chiefly influenced by natural factors such as temperature and precipitation.

Impacts of dust events on chemical characterization and associated source contributions of atmospheric particulate matter in northern China

Sand and dust have significant impacts on air quality, climate, and human health. To investigate the influences of dust storms on chemical characterization and source contributions of fine particulate matter (PM_2.5) in areas with different distances from dust source regions, PM_2.5 and associated chemical composition were measured in two industrial cities with one near sand sources (i.e., Wuhai) and the other far from sand sources (i.e., Jinan) in northern China in March 2021. Results showed that PM mass concentrations significantly increased and exceeded the Chinese National Ambient Air Quality standard during the dust events, with absolute concentrations and fractional contributions of PM_2.5-bound crustal and trace elements increased while secondary inorganic ions decreased at both sites. Crustal materials dominated the increased PM_2.5 mass from non-dust period to dust period in both cities. These were further evidenced by PM_2.5 source apportionment results from positive matrix factorization model. During the dust events, dust sources contributed up to 88% of PM_2.5 mass in Wuhai and ∼38% of PM_2.5 mass in Jinan, a city about thousands of kilometers away from the sand source. Besides, the measurement data indicated that dust from northwest China may also bring along with high abundance of organic matter and vanadium. Secondary and traffic sources were two of the most important source contributors to PM_2.5 in both cities during the non-dust periods. However, the near sand source city was more susceptible to the aggravating effects of dust and minerals, with much higher contributions by crustal materials (∼47%, from the aspect of chemical components) and dust-related sources (∼26%, from the aspect of sources) to PM_2.5 mass even during non-dust periods. This study highlighted the urgent need for more action and effective control of sand sources to reduce the impact on air quality in downstream regions.

Exposure to construction dust and health impacts - A review

Construction dust contributes a significant proportion of airborne particulate matter, affecting the health of its surrounding environment and population. Construction workers are normally exposed to dust at high levels and bear severe health risks. The existing articles concerning the exposure and health impacts of construction dust are limited, but this research field has received more and more attention. This work reviews literature in the field and tries to systematically assess the current research state. Here, we review (1) methods used to monitor or sample construction dust; (2) main characteristics of construction dust, including dust classification, exposed populations, and exposure concentrations; (3) potential health hazards and (4) health risk assessment of construction dust. From existing literature, the exposure concentrations of different types and sources of construction dust are usually the focus of attention, while its particle size distribution and chemical composition are rarely mentioned. The classification and characteristics of populations exposed to construction dust ought to be a key consideration but not clear enough so far. There still lacks in-depth study of health hazards and systematic assessment of risks associated with construction dust. In future, it is valuable to develop utility instruments to precisely monitor construction dust. Besides, control means to reduce the pollution of construction dust deserve more studies. Health hazards of construction dust should be verified by biological experiments. Moreover, emerging algorithm models should be utilized in the risk assessment. The findings will help gain a better understanding of construction dust exposure and associated health risks.

Water-soluble ions and source apportionment of PM2.5 depending on synoptic weather patterns in an urban environment in spring dust season

Emission sources and meteorological conditions are key factors affecting the intensity and duration of air pollution events. In the current study, using the daily concentrations of PM_2.5 (particulate matter with a diameter ≤ 2.5 μm) and the water-soluble ions thereof in Lanzhou from March 1, 2021, to May 31, 2021, we investigated the contributions of emission sources and locations of potential sources through positive matrix factorization and potential source contribution function analysis. In addition, synoptic weather patterns affecting pollution were typed using T-model principal component analysis. The results revealed that the average concentrations of PM_2.5 for the entire spring, dust storm days, and normal days were 54.3, 158.1 and 33.0 μg/m³, respectively. During dust storm days, sulfate produced from primary emissions was mainly present in the form of K₂SO₄, Na₂SO₄, MgSO₄, and CaSO₄, and nitrate was mainly produced through secondary conversion and took the form of NH₄NO₃. Dust, industrial entities, biomass combustion, metal smelting, secondary aerosol, and sea salt contributed to 32.0, 29.8, 13.4, 11.2, 10.8 and 2.7% of the spring PM_2.5, respectively, in Lanzhou. The main potential sources of PM_2.5 during the normal days were in the western parts of Lanzhou. Dust storms entered Lanzhou through the Hexi Corridor from several dust sources: southeastern Kazakhstan, Mongolia, the Kurbantungut Desert, and the Badain Jaran Desert. The northwest high-pressure; northern strong high-pressure and southwest low-pressure; northwest high-pressure and southwest high-pressure synoptic weather circulation types were prone to dust storms. Our results may provide a basis for local environmental governance.

Investigation of a haze-to-dust and dust swing process at a coastal city in northern China part I: Chemical composition and contributions of anthropogenic and natural sources

The long retention of dust air masses in polluted areas, especially in winter, may efficiently change the physicochemical properties of aerosols, causing additional health and ecological effects. A large-scale haze-to-dust weather event occurred in the North China Plain (NCP) region during the autumn-to-winter transition period in 2018, affecting the coastal city Qingdao several times between Nov. 27th and Dec. 1st. To study the evolution of the pollution process, we analyzed the chemical characteristics of PM_2.5 and PM_10-2.5 and source apportionments of PM_2.5 and PM_10, The dust stagnated around NCP and moved out and back to the site, noted as dust swing process, promoting SO₄^2- formation in PM_2.5 and NO₃^- formation in PM_10-2.5. Source apportionments were analyzed using the Positive Matrix Factorization (PMF) receptor model and weighted potential source contribution function (WPSCF). Before the dust invasion, Qingdao was influenced by severe haze; waste incineration and coal burning were the major contributors (~80 %) to PM_2.5, and the source region was in the southwest of Shandong Province. During the initial dust event, mineral dust and the mixed factor of dust and sea salt were the major contributors (46.0 % of PM_2.5 and 86.5 % of PM₁₀). During the polluted dust period, the contributions of regional transported biomass burning (22.3 %), vehicle emissions (20.8 %), and secondary aerosols (33.8 %) to PM_2.5 from the Beijing-Tianjin-Hebei region significantly increased. The secondary aerosols source was more regional than that of vehicle emissions and biomass burning and contributed considerably to PM₁₀ (30.8 %) during the dust swing process. Our findings demonstrate that environmental managers should consider the possible adverse effects of winter dust on regional and local pollution.

Significant Promotion of Light Absorption Ability and Formation of Triplet Organics and Reactive Oxygen Species in Atmospheric HULIS by Fe(III) Ions

Metal ions are key components in atmosphere that potentially affect the optical properties and photochemical reactivity of atmospheric humic-like substances (HULIS), while this mechanism is still unclear. In this study, we demonstrated that atmospheric HULIS coupled with Fe³⁺, Cu²⁺, Zn²⁺, and Al³⁺ exhibited distinct optical properties and reactive intermediates from that of HULIS utilizing three-dimensional fluorescence spectroscopy and electron paramagnetic resonance spectroscopy. The HULIS components showed light absorption that increased by 56% for the HULIS-Fe³⁺ system, fluorescence blue shift, and fluorescence quenching, showing a certain dose-effect relationship. These are mainly attributed to the fact that the highly oxidative HULIS chromophores have a stronger complexing ability with Fe³⁺ ions than the other metal ions. In addition, triplet organics (promoting ratio: 53%) and reactive oxygen species (promoting ratio: 82.6%) in the HULIS-Fe³⁺ system showed obvious generation promotion. Therefore, the main assumption of the photochemical mechanisms of atmospheric HULIS in the HULIS-Fe³⁺ system is that Fe³⁺ ions can form ³HULIS*-Fe³⁺ complexation with photoexcited ³HULIS* and then transition to the ground state through energy transfer, electron transfer, or nonradiative transition, accompanied by the formation of singlet oxygen and hydroxyl radicals. Our results provide references for evaluating the radiative forcing and aging effect of metal ions on atmospheric aerosols.

Evaluating the influence of constant source profile presumption on PMF analysis of PM2.5 by comparing long- and short-term hourly observation-based modeling

Hourly PM_2.5 speciation data have been widely used as an input of positive matrix factorization (PMF) model to apportion PM_2.5 components to specific source-related factors. However, the influence of constant source profile presumption during the observation period is less investigated. In the current work, hourly concentrations of PM_2.5 water-soluble inorganic ions, bulk organic and elemental carbon, and elements were obtained at an urban site in Nanjing, China from 2017 to 2020. PMF analysis based on observation data during specific pollution (firework combustion, sandstorm, and winter haze) and emission-reduction (COVID-19 pandemic) periods was compared with that using the whole 4-year data set (PMF_whole). Due to the lack of data variability, event-based PMF solutions did not separate secondary sulfate and nitrate. But they showed better performance in simulating average concentrations and temporal variations of input species, particularly for primary source markers, than the PMF_whole solution. After removing event data, PMF modeling was conducted for individual months (PMF_month) and the 4-year period (PMF_4-year), respectively. PMF_month solutions reflected varied source profiles and contributions and reproduced monthly variations of input species better than the PMF_4-year solution, but failed to capture seasonal patterns of secondary salts. Additionally, four winter pollution days were selected for hour-by-hour PMF simulations, and three sample sizes (500, 1000, and 2000) were tested using a moving window method. The results showed that using short-term observation data performed better in reflecting immediate changes in primary sources, which will benefit future air quality control when primary PM emissions begin to increase.

Air Pollutants in Metropolises of Eastern Coastal China

Recently released hourly particular matter (PM:PM_2.5 and PM₁₀) and gaseous pollutants (SO₂, NO₂, CO, and O₃) data observed in Qingdao, Hangzhou, and Xiamen from 2015 to 2019 were utilized to reveal the current situation of air pollution over eastern coastal China. The PM pollution situation over the three metropolises ameliorated during studied period with the concentrations decreasing about 20-30%. Gas pollutants, excepting SO₂, generally exhibit no evident reduction tendencies, and a more rigorous control standard on gaseous pollutants is neededEven for the year 2018 with low pollution levels among the study period, these levels (<10% of PM_2.5, <6% of PM₁₀, and <15% of O₃) surpass the Grade II of the Chinese Ambient Air Quality Standard (CAAQS) over these metropolises of eastern coast China. No matter in which year, both SO₂ and CO concentrations are always below the Grade-II standards. According to the comparative analysis of PM_2.5/PM₁₀ and PM_2.5/CO during episode days and non-episode days, the formation of secondary aerosols associated with stagnant weather systems play an important role in the pollutant accumulation as haze episodes occurred. The stronger seasonal variations and higher magnitude occur in Qingdao and Hangzhou, while weaker seasonal variations and lower magnitudes occur in Xiamen. In Qingdao and Hangzhou, PM, NO₂, SO₂, and CO show relatively high levels in the cold wintertime and low levels in summer, whereas O₃ shows a completely opposite pattern. Xiamen exhibits high levels of all air pollutants except O₃ in spring due to its subtropical marine monsoon climate with mild winters. According to the back trajectory hierarchical clustering and concentration weighted trajectory (CWT) analysis, the regional transmission from adjacent cities has a significant impact on the atmospheric pollutant concentrations under the control of the prejudiced winds. Thus, besides local emission reduction, strengthening regional environmental cooperation and implementing joint prevention are effective measures to mitigate air pollution in the eastern coastal areas of China.

Seasonal variation and source apportionment of inorganic and organic components in PM2.5: influence of organic markers application on PMF source apportionment

PM_2.5 samples collected over a 1-year period in a Chinese megacity were analyzed for organic carbon (OC), elemental carbon (EC), water-soluble ions, elements, and organic markers such as polycyclic aromatic hydrocarbons (PAHs), hopanes, steranes, and n-alkanes. To study the applicability of organic markers in source apportionment, the relationship between organic and inorganic components was analyzed, and four scenarios were implemented by incorporating different combinations of organic and inorganic tracers. The consistent temporal variations trend of 4-ring PAHs and SO₄^2- prove that coal burning directly emits a portion of sulfate. The concentrations of ∑5-7-ring PAHs, NO₃^-, and NO₂ show a trend of simultaneous increase and decrease, implying collective impacts from the vehicle source. The concentrations of OC and EC positively correlate with the 5-7-ring PAHs and Cu and Zn, which proves that part of Cu and Zn comes from vehicle emissions. Five factors were identified by incorporating only conventional components, including secondary source (SS, 30%), fugitive dust (FD, 14%), construction dust (CD, 4%), traffic source (TS, 19%), and coal combustion (CC, 14%). Six factors were identified by incorporating conventional components and PAHs, including SS (28%), FD (15%), CD (4%), CC (13%), gasoline vehicles (GV, 12%), and diesel vehicles (DV, 10%). Eight factors were identified by incorporating conventional components, PAHs, hopanes, and n-alkanes, including SS (26%), FD (17%), CD (3%), GV (14%), DV (8%), immature coal combustion (ICC, 5%), mature coal combustion (MCC, 10%), and biogenic source (BS, 1%).

Effect of restricted emissions during COVID-19 on atmospheric aerosol chemistry in a Greater Cairo suburb: Characterization and enhancement of secondary inorganic aerosol production

To prevent the rapid spreading of the COVID-19 pandemic, the Egyptian government had imposed partial lockdown restrictions which led emissions reduction. This served as ideal conditions for a natural experiment, for study the effect of partial lockdown on the atmospheric aerosol chemistry and the enhanced secondary inorganic aerosol production in a semi-desert climate area like Egypt. To achieve this objective, SO₂, NO₂, and PM_2.5 and their chemical compositions were measured during the pre-COVID, COVID partial lockdown, and post-COVID periods in 2020 in a suburb of Greater Cairo, Egypt. Our results show that the SO₂, NO₂, PM_2.5 and anthropogenic elements concentrations follow the pattern pre-COVID > post-COVID > COVID partial lockdown. SO₂ and NO₂ reductions were high compared with their secondary products during the COVID partial lockdown compared with pre-COVID. Although, PM_2.5, anthropogenic elements, NO₂, SO₂, SO₄ ^2-, NO₃ ^-, and NH₄ ⁺ decreased by 39%, 38-55%, 38%, 32.9%. 9%, 14%, and 4.3%, respectively, during the COVID partial lockdown compared with pre-COVID, with the secondary inorganic ions (SO₄ ^2-, NO₃ ^-, and NH₄ ⁺) being the dominant components in PM_2.5 during the COVID partial lockdown. Moreover, the enhancement of NO₃ ^- and SO₄ ^2- formation during the COVID partial lockdown was high compared with pre-COVID. SO₄ ^2- and NO₃ ^- formation enhancements were significantly positive correlated with PM_2.5 concentration. Chemical forms of SO₄ ^2- and NO₃ ^- were identified in PM_2.5 based on their NH₄ ⁺/SO₄ ^2- molar ratio and correlation between NH₄ ⁺ and both NO₃ ^- and SO₄ ^2-. The particles during the COVID partial lockdown were more acidic than those in pre-COVID.

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.

Estimation of the fraction of soil-borne particulates in indoor air by PMF and its impact on health risk assessment of soil contamination in Guangzhou, China

The fraction of soil-borne particulates in indoor air (fspi), a principal exposure factor in health risk assessment of soil, is used to calculate the inhaled dose of contaminants in air particulates (PM₁₀) from soil. To investigate the fspi, consecutive 24-h PM₁₀ samples (n = 180) of indoor ambient were collected from September 2019 to January 2020 in Guangzhou main urban areas, China. The concentrations of twenty-six metal elements, five anions, organic carbon (OC) and elemental carbon (EC) in samples were measured. The sources of indoor ambient PM₁₀ and the value of fspi were identified by the method of Positive Matrix Factor analysis (PMF). Results showed that the main sources contributing to indoor PM₁₀ content were combustion sources (50.53%) and vehicular sources (28.17%). The soil sources (the local fspi) were 19.96%. The soil contents of indoor PM₁₀ in Guangzhou main urban areas were in accordance with those in similar monsoon climate regions, such as Malaysia. The health risks of the inhalation route were dropped by about 62% for some common brownfield contaminants (Cr (VI), Ni, Be and Cd) with the investigated local fspi in Guangzhou main urban areas, compared with using the fspi (0.8) recommended by the C-RAG model in China. The results supplied a new effective methodology for estimation of the local fspi value in health risk assessment of soil contamination in urban areas.

Effects of energy structure differences on chemical compositions and respiratory health of PM2.5 during late autumn and winter in China

To understand the influence of the energy structure (including solid fuel and clean energy) on air pollution, two comprehensive measurement campaigns were conducted in Baoding and Shanghai in late autumn and winter during 2017-2018. The chemical compositions, driving factors, regional transport of pollutants, and potential respiratory disease (RD) health risks of PM_2.5 for Baoding and Shanghai were analyzed. The results showed that the concentration of PM_2.5 in Baoding (156.9 ± 139.8 μg m^-3) was 2.6 times of that in Shanghai (60.9 ± 45.9 μg m^-3). The most important contributor to PM_2.5 in Baoding was organic matter (OM), while inorganic aerosols accounted for major fractions of PM_2.5 in Shanghai. Positive matrix factorization (PMF) results indicated that coal combustion (CC; 39%) accounted for the most in Baoding, followed by secondary aerosols (21%), biomass burning (BB; 20%), industrial emissions (14%), dust (3%), and vehicle exhaust (2%). However, the average contribution in Shanghai followed the order: secondary aerosols (44%), vehicle exhaust (36%), dust (11%), marine aerosols (6%), and BB (3%). The evolution of source contributions at different pollution levels revealed that haze episodes in Baoding and Shanghai were triggered by CC and secondary formation, respectively; however, the air quality on clean days in Baoding and Shanghai was affected mostly by BB and vehicle emissions, respectively. Potential source contribution function (PSCF) results suggested that CC in Baoding was primarily from local emissions, while BB was primarily from local and regional transport. Vehicle exhaust and secondary aerosols in Shanghai were mainly from local emissions and regional transport. The number of RD deaths related to haze episodes in Baoding and Shanghai were 215 (95% CI: 109, 319) and 76 (95% CI: 11, 135), respectively. This research also emphasized the importance of further attention to the usage of coal in Baoding and vehicle emissions in Shanghai.

The environmental benefit of Beijing-Tianjin-Hebei coal banning area for North China

In order to achieve the targets specified in the Action Plan for Air Pollution Prevention and Control (APAPPC), a limited coal banning area (10,000 km2) was designated in the heavily polluted Beijing-Tianjin-Hebei region (BTH) for the first time in 2017. PM2.5 and elements were sampled by the network of BTH to evaluate the effectiveness of this policy. This study found that the fine days with PM2.5 < 75 μg m-3 accounted for 74.3% in the autumn and winter of 2017, which was significantly higher than that in 2016 (43%). The heavily polluted days (PM2.5 > 150 μg m-3) also decreased from 32.2% in 2016 to 4.9% in 2017. Arsenic (As) is an important tracer in coal consumption, which can be used to reflect the influence of the establishment of coal banning areas on north China. The cluster analysis of air mass forward trajectory identified that the number of polluted trajectories with PM2.5 and As in 2017 decreased by 47.6% and 49.7%, respectively. Under the implementation of the coal banning policy, the weighted concentration of PM2.5 and As decreased by 94.2 μg m-3 and 5.1 ng m-3 in the coal banning area, 60.9 μg m-3 and 3.4 ng m-3 in the no coal banning area in BTH, respectively. The influence of weighted concentration of PM2.5 and As in coal banning area on North China were 1.6-49.2 μg m-3 and 0.15-2.8 ng m-3, respectively, which was 38.8% and 29.7% lower than 2016. In coal banning area, BTH and other parts of North China, the reduction of the weight concentration of PM2.5 in 2017 accounted for 41.4%, 26.8% and 31.8% of the total reduction, respectively, so was the As in 39%, 26.3% and 34.6%, indicating that setting up a coal banning area scientifically in limited areas can produce remarkable regional benefit.

Characterization and sources of trace elements in PM1 during autumn and winter in Qingdao, Northern China

Atmospheric sub-micrometer particles (PM₁, particles with an aerodynamic diameter ≤ 1.0 μm) monitoring in Qingdao, a coastal city in Northern China, was conducted for two consecutive years from November 1, 2018 to January 31, 2019 (hereafter referred to as OP_2018-2019) and from October 28, 2019 to January 20, 2020 (hereafter referred to as OP_2019-2020). The results showed that compared with OP_2018-2019, the concentrations of V, Ni, As, Pb, and Cd in PM₁ in OP_2019-2020 decreased by 61.9%, 31.4%, 49.2%, 25.4%, and 27.1%, respectively. For the indicators of ship emission sources, a significant reduction in V (73.3%) and Ni (22.1%) concentrations were observed after the implementation of the updated Domestic Emission Control Area (DECA 2.0) policy for ships since January 1, 2019 proposed by the Ministry of Transportation. This result demonstrated that the implementation of the DECA 2.0 policy had a significant effect on reducing ship emissions. The Field Emission Scanning Electron Microscope analysis identified the impact of ship emission sources, while the inconsistent distribution of V and Ni revealed other potential sources of Ni. The V/Ni ratios during the pre-policy and post-policy periods decreased by 40.7%. Along with the further implementation of the domestic coastal ship pollution control zone policy, V/Ni ratio should be cautiously used as a parameter for ship emission sources. The positive matrix factorization method identified five source factors: coal combustion/biomass burning (47.8%), crustal sources (21.2%), vehicle exhaust/road dust (15.1%), industrial emissions (11.1%), and ship emissions (4.9%). The contribution rates of ship emission sources before and after the DECA 2.0 policy were analyzed and found to be 5.6% and 3.4%. The potential source contribution factor analysis of As showed that the potential emission source areas were significantly reduced in OP_2019-2020, which might be related to the coal fired cleanup operations conducted in Beijing-Tianjin-Hebei and surrounding areas.

Association between satellite-based estimates of long-term PM2.5 exposure and cardiovascular disease: evidence from the Indonesian Family Life Survey

Exposure to particulate matter with a diameter < 2.5 µm (PM_2.5) increases the risk of cardiovascular disease (CVD), which is the leading cause of both morbidity and mortality in Indonesia, accounting for one-third of all deaths. Indonesian authorities started to monitor PM_2.5 levels in urban areas in 2015. However, there is still no study examining the association between long-term PM_2.5 exposure and CVD in Indonesia. In this study, we combined PM_2.5 data and health survey data. Long-term (2000-2007) exposure to PM_2.5 was measured based on satellite-derived aerosol optical depth measurements (1 × 1 km²) that could be used to predict ground-level PM_2.5 concentrations. Population data on residents of Sumatra Island were obtained from the fourth wave of the Indonesian Family Life Survey (IFLS). A cross-sectional study was performed with 2324 participants who were aged ≥ 40 years old, and a report of doctor-diagnosed CVD determined CVD status. We used logistic regression to analyze the association between PM_2.5 and CVD prevalence, adjusting for multiple covariates. Of the sample, 52.1% were women, and 47.9% were men. The sample was divided into those aged 40-59 (adults) and those ≥ 60 (older adults). The CVD prevalence was 4.05% (n = 94), with a mean (standard deviation) PM_2.5 concentration of 14.4 (6.4) µg/m³. In adjusted models, a 10-µg/m³ increase in annual average PM_2.5 levels was associated with 29% higher odds of having CVD (odds ratio = 1.29; 95% confidence interval: 1.02, 1.47). In this population-based IFLS data, long-term exposure to PM_2.5 is associated with a higher prevalence of CVD in Sumatera, Indonesia.

Spatio-Temporal Characteristics of Air Quality Index (AQI) over Northwest China

In recent years, air pollution has become a serious threat, causing adverse health effects and millions of premature deaths in China. This study examines the spatial-temporal characteristics of ambient air quality in five provinces (Shaanxi (SN), Xinjiang (XJ), Gansu (GS), Ningxia (NX), and Qinghai (QH)) of northwest China (NWC) from January 2015 to December 2018. For this purpose, surface-level aerosol pollutants, including particulate matter (PMx, x = 2.5 and 10) and gaseous pollutants (sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3)) were obtained from China National Environmental Monitoring Center (CNEMC). The results showed that fine particulate matter (PM2.5), coarse particulate matter (PM10), SO2, NO2, and CO decreased by 28.2%, 32.7%, 41.9%, 6.2%, and 27.3%, respectively, while O3 increased by 3.96% in NWC during 2018 as compared with 2015. The particulate matter (PM2.5 and PM10) levels exceeded the Chinese Ambient Air Quality Standards (CAAQS) Grade II standards as well as the WHO recommended Air Quality Guidelines, while SO2 and NO2 complied with the CAAQS Grade II standards in NWC. In addition, the average air quality index (AQI), calculated from ground-based data, improved by 21.3%, the proportion of air quality Class I (0–50) improved by 114.1%, and the number of pollution days decreased by 61.8% in NWC. All the pollutants’ (except ozone) AQI and PM2.5/PM10 ratios showed the highest pollution levels in winter and lowest in summer. AQI was strongly positively correlated with PM2.5, PM10, SO2, NO2, and CO, while negatively correlated with O3. PM10 was the primary pollutant, followed by O3, PM2.5, NO2, CO, and SO2, with different spatial and temporal variations. The proportion of days with PM2.5, PM10, SO2, and CO as the primary pollutants decreased but increased for NO2 and O3. This study provides useful information and a valuable reference for future research on air quality in northwest China.

Schisandrae Fructus ethanol extract attenuates particulate matter 2.5-induced inflammatory and oxidative responses by blocking the activation of the ROS-dependent NF-κB signaling pathway

BACKGROUND/OBJECTIVES

Schisandrae Fructus, the fruit of Schisandra chinensis Baill., has traditionally been used as a medicinal herb for the treatment of various diseases, and has proven its various pharmacological effects, including anti-inflammatory and antioxidant activities. In this study, we investigated the inhibitory effect of Schisandrae Fructus ethanol extract (SF) on inflammatory and oxidative stress in particulate matter 2.5 (PM2.5)-treated RAW 264.7 macrophages.

MATERIALS/METHODS

To investigate the anti-inflammatory and antioxidant effects of SF in PM2.5-stimulated RAW 264.7 cells, the levels of pro-inflammatory mediator such as nitric oxide (NO) and prostaglandin E₂ (PGE₂), cytokines including interleukin (IL)-6 and IL-1β, and reactive oxygen species (ROS) were measured. To elucidate the mechanism underlying the effect of SF, the expression of genes involved in the generation of inflammatory factors was also investigated. We further evaluated the anti-inflammatory and antioxidant efficacy of SF against PM2.5 in the zebrafish model.

RESULTS

The results indicated that SF treatment significantly inhibited the PM2.5-induced release of NO and PGE₂, which was associated with decreased inducible NO synthase and cyclooxygenase-2 expression. SF also attenuated the PM2.5-induced expression of IL-6 and IL-1β, reducing their extracellular secretion. Moreover, SF suppressed the PM2.5-mediated translocation of nuclear factor-kappa B (NF-κB) from the cytosol into nuclei and the degradation of inhibitor IκB-α, indicating that SF exhibited anti-inflammatory effects by inhibiting the NF-κB signaling pathway. In addition, SF abolished PM2.5-induced generation of ROS, similar to the pretreatment of a ROS scavenger, but not by an inhibitor of NF-κB activity. Furthermore, SF showed strong protective effects against NO and ROS production in PM2.5-treated zebrafish larvae.

CONCLUSIONS

Our findings suggest that SF exerts anti-inflammatory and antioxidant effects against PM2.5 through ROS-dependent down-regulating the NF-κB signaling pathway, and that SF can be a potential functional substance to prevent PM2.5-mediated inflammatory and oxidative damage.

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.

Composition analysis of PM2.5 at multiple sites in Zhengzhou, China: implications for characterization and source apportionment at different pollution levels

Zhengzhou is one of the most heavily polluted cities in China. This study collected samples of PM_2.5 (atmospheric fine particulate matter with aerodynamic diameter ≤ 2.5 μm) at five sites in different functional areas of Zhengzhou in 2016 to investigate the chemical properties and sources of PM_2.5 at three pollution levels, i.e., PM_2.5 ≤ 75 μg/m³ (non-pollution, NP), 75 μg/m³ < PM_2.5 ≤ 150 μg/m³ (moderate pollution, MP), and PM_2.5 > 150 μg/m³ (heavy pollution, HP). Chemical analysis was conducted, and source categories and potential source region were identified for PM_2.5 at different pollution levels. The health risks of toxic elements were evaluated. Results showed that the average PM_2.5 concentration in Zhengzhou was 119 μg/m³, and the sum of the concentrations of SO₄^2-, NO₃^-, and NH₄⁺ increased with the aggravation of pollution level (23, 42, and 114 μg/m³ at NP, MP, and HP days, respectively). Positive Matrix Factorization analysis indicated that secondary aerosols, coal combustion, vehicle traffic, industrial processes, biomass burning, and dust were the main sources of PM_2.5 at three pollution levels, and accounted for 38.4%, 21.6%, 16.7%, 7.4%, 7.7%, and 8.1% on HP days, respectively. Trajectory clustering analysis showed that close-range transport was one of the dominant factors on HP days in Zhengzhou. The potential source areas were mainly located in Xinxiang, Kaifeng, Xuchang, and Pingdingshan. Significant risks existed in the non-carcinogenic risk of As (1.4-2.3) for children at three pollution levels and the non-carcinogenic risk of Pb (1.0-1.4) for children with NP and MP days.

Heating events drive the seasonal patterns of volatile organic compounds in a typical semi-arid city

The emission characteristics, source apportionment and chemical behavior of volatile organic compounds (VOCs) are important for strategy-making on ozone (O₃) and fine particulate matter (PM_2.5) control. Based on the continuous observation during four seasons, the seasonal characteristics, chemical reactivity and source apportionment of 116 VOCs species were studied in a typical semi-arid city with no relevant research. The results showed that the annual average concentrations of total volatile organic compounds (TVOCs) in Hohhot was 44.67 ± 46.59 ppbv with the predominant of alkanes and oxygenated volatile organic compounds (OVOCs). The sharp increment of TVOCs were explained by the elevating OVOCs and alkanes in autumn, while alkanes and alkenes in winter. The levels of alkenes presented negative and positive correlations with solar radiation and PM₁₀, respectively. The mixing ratios accounted for 30% (alkanes) and 23% (alkenes and aromatics) of the TVOCs, respectively; while their ozone formation potential (OFP) ~15% and nearly 50% (even 75% in winter), respectively, indicating that the OFP of different VOCs species depends not only on their concentrations but more importantly on their chemical activity in atmosphere. According to the seasonal source apportionment, both the high levels of short-chain alkanes, alkenes and aromatics and the increasing coal sales volume suggested that the combustion sources were the predominant in heating seasons, while solvent uses was extracted as the most predominant during non-heating seasons. In non-heating seasons, the biogenic emission sources, ranking as the second contributor, were significantly higher than heating seasons. Isoprene was the most active biogenic VOCs species, bagging test results showed that deciduous trees were the predominant contributors for isoprene (~99%), while coniferous trees and shrub for monoterpenes (>95%). It will be helpful for understanding the characteristics of VOCs in Chinese national key development areas and informing policy to control semi-arid regional VOCs air pollution.

Quantifying spatial heterogeneity of vulnerability to short-term PM2.5 exposure with data fusion framework

The current estimations of the burden of disease (BD) of PM_2.5 exposure is still potentially biased by two factors: ignorance of heterogeneous vulnerabilities at diverse urbanization levels and reliance on the risk estimates from existing literature, usually from different locations. Our objectives are (1) to build up a data fusion framework to estimate the burden of PM_2.5 exposure while evaluating local risks simultaneously and (2) to quantify their spatial heterogeneity, relationship to land-use characteristics, and derived uncertainties when calculating the disease burdens. The feature of this study is applying six local databases to extract PM_2.5 exposure risk and the BD information, including the risks of death, cardiovascular disease (CVD), and respiratory disease (RD), and their spatial heterogeneities through our data fusion framework. We applied the developed framework to Tainan City in Taiwan as a use case estimated the risks by using 2006-2016 emergency department visit data, air quality monitoring data, and land-use characteristics and further estimated the BD caused by daily PM_2.5 exposure in 2013. Our results found that the risks of CVD and RD in highly urbanized areas and death in rural areas could reach 1.20-1.57 times higher than average. Furthermore, we performed a sensitivity analysis to assess the uncertainty of BD estimations from utilizing different data sources, and the results showed that the uncertainty of the BD estimations could be contributed by different PM_2.5 exposure data (20-32%) and risk values (0-86%), especially for highly urbanized areas. In conclusion, our approach for estimating BD based on local databases has the potential to be generalized to the developing and overpopulated countries and to support local air quality and health management plans.

PM1 chemical composition and light absorption properties in urban and rural areas within Sichuan Basin, southwest China

Sichuan Basin is encircled by high mountains and plateaus with the heights ranging from 1 km to 3 km, and is one of the most polluted regions in China. However, the dominant chemical species and light absorption properties of aerosol particles is still not clear in rural areas. Chemical composition in PM₁ (airborne particulate matter with an aerodynamic diameter less than 1 μm) and light-absorbing properties were determined in Chengdu (urban) and Sanbacun (rural) in western Sichuan Basin (WSB), Southwest China. Carbonaceous aerosols and secondary inorganic ions (NH₄⁺, NO₃^- and SO₄^2-) dominate PM₁ pollution, contributing more than 85% to PM₁ mass at WSB. The mean concentrations of organic and elemental carbon (OC, EC), K⁺ and Cl^- are 19.69 μg m^-3, 8.00 μg m^-3, 1.32 μg m^-3, 1.16 μg m^-3 at the rural site, which are 26.2%, 65.3%, 34.7% and 48.7% higher than those at the urban site, respectively. BrC (brown carbon) light absorption coefficient at 405 nm is 63.90 ± 27.81 M m^-1 at the rural site, contributing more than half of total absorption, which is about five times higher than that at urban site (10.43 ± 4.74 M m^-1). Compared with secondary OC, rural BrC light absorption more depends on primary OC from biomass and coal burning. The rural MAE_BrC (BrC mass absorption efficiency) at 405 nm ranges from 0.6 to 5.1 m² g^-1 with mean value of 3.5 ± 0.8 m² g^-1, which is about three times higher than the urban site.

Variation in PM2.5 sources in central North China Plain during 2017-2019: Response to mitigation strategies

Central North China Plain (NCP) is one of the most important source region of air pollutants over the Beijing-Tianjin-Hebei (BTH) region. The national government has issued abatement measures to improve the air quality in this area from 2017. To examine the effects of control measures, observational analysis on PM_2.5 characteristics was performed in a city of central NCP during 2017-2019 to investigate the variation in mass concentration, chemical composition, and emission source of PM_2.5. Annual PM_2.5 concentration significantly reduced by 16% from 2017 to 2019, implying substantial improvements in air quality. PM_2.5 enriched in autumn-winter seasons was dominated by SNA (sum of sulfate, nitrate and ammonium; ~38%), followed by organic carbon matters (OM; ~24%) and fine soil (FS; ~12%). This chemical composition was different from that in a megacity in NCP (Beijing) where OM accounted for a comparable fraction to SNA. Approximately half of SNA was attributed to nitrate, indicating that SNA changed from sulfate-driven to nitrate-driven, and the considerable effects of coal combustion cutoff, in which sulfate was concentrated. Decreased mass fraction of SNA and increased OM fraction in PM_2.5 were observed in 2018-2019 partly contributed to the decrease in PM_2.5. A progressive increase in the contribution of heterogeneous formed SNA whilst a decrease in OM was observed as the pollution elevated from clean to heavily polluted. Six sources (soil dust, biomass burning, secondary emission, road traffic, coal combustion and industry) were identified by the Positive Matrix Factorization (PMF) model in both years and dominated by secondary aerosols, respectively contributing 39% and 41% to PM_2.5. The decreasing concentrations (with reductions of 17%-61%) of the secondary source, coal combustion, soil dust and biomass burning largely accounted for the reduction in PM_2.5, as a consequence of the recent abatement measures. By contrast, contributions of vehicle-related emissions, similar to the increasing contribution of vehicles at sites in NCP after 2013, should receive increased attention.

Spatial-temporal characteristics, source-specific variation and uncertainty analysis of health risks associated with heavy metals in road dust in Beijing, China

Based on the concentrations of ten heavy metals (As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Zn, Fe) in 144 road dust samples collected from 36 sites across 4 seasons from 2016 to 2017 in Beijing, this study systematically analyzed the levels and main sources of health risks in terms of their temporal and spatial variations. A combination of receptor models (positive matrix factorization and multilinear engine-2), human health risk assessment models, and Monte Carlo simulations were used to apportion the seasonal variation of the health risks associated with these heavy metals. While non-carcinogenic risks were generally acceptable, Cr and Ni induced cautionary carcinogenic risks (CR) to children (confidence levels was approximately 80% and 95%, respectively).. Additionally, fuel combustion posed cautionary CR to children in all seasons, while the level of CR from other sources varied, depending on the seasons. Heavy metal concentrations were the most influential variables for uncertainties, followed by ingestion rate and skin adherence factor. The values and spatial patterns of health risks were influenced by the spatial pattern of risks from each source.

Health risks of inhaled selected toxic elements during the haze episodes in Shijiazhuang, China: Insight into critical risk sources

PM_2.5 in Shijiazhuang was collected from October 15, 2018 to January 31, 2019, and selected toxic elements were measured. Five typical haze episodes were chosen to analyze the health risks and critical risk sources. Toxic elements during the haze episodes accounted for 0.33% of PM_2.5 mass. Non-cancer risk of toxic elements for children was 1.8 times higher than that for adults during the haze episodes, while cancer risk for adults was 2.5 times higher than that for children; cancer and non-cancer risks were primarily attributable to As and Mn, respectively. Health risks of toxic elements increased during the growth and stable periods of haze episodes. Non-cancer and cancer risks of toxic elements during the haze stable periods were higher than other haze stages, and higher for children than for adults during the stable period. Mn was the largest contributor to non-cancer risk during different haze stages, while As was the largest contributor to cancer risk. Crustal dust, vehicle emissions, and industrial emissions were critical sources of cancer risk during the clean-air periods; while vehicle emissions, coal combustion, and crustal dust were key sources of cancer risk during the haze episodes. Cancer risks of crustal dust and vehicle emissions during the haze episodes were 2.0 and 1.7 times higher than those in the clean-air periods. Non-cancer risks from emission sources were not found during different periods. Cancer risks of biomass burning and coal combustion increased rapidly during the haze growth period, while that of coal combustion decreased sharply during the dissipation period. Vehicle emissions, crustal dust, and coal combustion were significant cancer risk sources during different haze stages, cancer risk of each source was the highest during the stable period. Southern Hebei, Northern and central Shaanxi were potential risk regions that affected the health of both adults and children in Shijiazhuang.

Impact of SARS-CoV-2 on Ambient Air Quality in Northwest China (NWC)

SARS-CoV-2 was discovered in Wuhan (Hubei) in late 2019 and covered the globe by March 2020. To prevent the spread of the SARS-CoV-2 outbreak, China imposed a countrywide lockdown that significantly improved the air quality. To investigate the collective effect of SARS-CoV-2 on air quality, we analyzed the ambient air quality in five provinces of northwest China (NWC): Shaanxi (SN), Xinjiang (XJ), Gansu (GS), Ningxia (NX) and Qinghai (QH), from January 2019 to December 2020. For this purpose, fine particulate matter (PM2.5), coarse particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) were obtained from the China National Environmental Monitoring Center (CNEMC). In 2020, PM2.5, PM10, SO2, NO2, CO, and O3 improved by 2.72%, 5.31%, 7.93%, 8.40%, 8.47%, and 2.15%, respectively, as compared with 2019. The PM2.5 failed to comply in SN and XJ; PM10 failed to comply in SN, XJ, and NX with CAAQS Grade II standards (35 µg/m3, 70 µg/m3, annual mean). In a seasonal variation, all the pollutants experienced significant spatial and temporal distribution, e.g., highest in winter and lowest in summer, except O3. Moreover, the average air quality index (AQI) improved by 4.70%, with the highest improvement in SN followed by QH, GS, XJ, and NX. AQI improved in all seasons; significant improvement occurred in winter (December to February) and spring (March to May) when lockdowns, industrial closure etc. were at their peak. The proportion of air quality Class I improved by 32.14%, and the number of days with PM2.5, SO2, and NO2 as primary pollutants decreased while they increased for PM10, CO, and O3 in 2020. This study indicates a significant association between air quality improvement and the prevalence of SARS-CoV-2 in 2020.

Source apportionment of absorption enhancement of black carbon in different environments of China

Black carbon (BC) is an important pollutant for both air quality and earth's radiation balance because of its strong absorption enhancement. The enhanced light absorption of BC caused by other pollutants is one of the most important sources of uncertainty in global radiative forcing. The light absorption of BC is highly dependent on the emission source and very few studies have been carried out for the source apportionment of BC absorption enhancement. Thus, with this objective, continuous measurements of particulate matter (PM_2.5) were performed at three different sites: a traffic site in Nanjing, an urban site in Jinan, and a rural site in Yucheng; the BC absorption enhancement and its source contributions were determined. The mass absorption cross-section (MAC) of BC aerosols was reduced after the removal of the coating material. The maximum MAC enhancement (E_MAC) was found to be 2.25 ± 0.5 at the rural site, followed by 2.07 ± 0.7 at the urban site and 1.7 ± 0.6 at the traffic site, suggesting an approximately double enhancement in BC absorption due to different coating materials. The source apportionment of absorption enhancement of BC analysis using the positive matrix factorization model suggests five major emission sources. Among them, secondary sources were the main source of E_MAC at all the three sites with a percentage contribution of 43.4% (rural site), 34.6% (traffic site), and 31% (urban site). However, other emission sources, such as biomass burning (21.1% at rural site) and vehicular emissions (33.8% at traffic site) also had a significant contribution to E_MAC, suggesting that there could be large variations in BC absorption enhancement due to differences in emission sources together with aerosol aging processes.

Source appointment of PM2.5 in Qingdao Port, East of China

Field measurements were conducted near Qingdao Port to characterize the particulate air pollutants, assess the spatial and seasonal characteristics of the pollutants, and identify the contribution from ship traffic emissions. By utilizing multiple statistical methods and data collected at two sites in Qingdao, we comprehensively explored the PM_2.5 seasonal characteristics and source apportionments of different PM_2.5 constituents, especially those originating from ship emissions, and identified potential source regions for samples collected in Qingdao. In this study, 118 concurrent daily PM_2.5 samples were collected from August 2018 to May 2019 at a port site (QH) and a coastal background site (BG). Vanadium (V) and Nickel (Ni) are the dominant metal elements from crude oil and crude oil combustion emissions. The significant correlations between V and Ni at both sampling sites, indicating that shipping emissions have a significant impact on the port and background area. Additionally, Ni and other metals showed significant correlations at the BG site, implying Ni also emission from the land-based oil at this site. The positive matrix factorization (PMF) model identified six main sources for the PM_2.5 samples in Qingdao, and they are coal combustion, industrial emissions/mineral dust, marine vessel emissions, secondary aerosols/biomass burning, sea salt/crustal emissions, and vehicle exhaust, respectively. Marine vessel emissions were the dominant contributor to PM_2.5 in Qingdao during the sampling periods (25.05%). The potential source contribution function (PSCF) analysis suggested that the Yellow Sea and Jiaodong Peninsula were the major sources regions for PM_2.5 in Qingdao. The Yellow Sea and Bohai Sea were the potential source regions for shipping emissions in Qingdao. Therefore, efforts to control shipping emissions should be strengthened not only at the Qingdao Port but also in surrounding ports.

Association of systemic inflammation and coagulation biomarkers with source-specific PM2.5 mass concentrations among young and elderly subjects in central Tehran

In this study, we investigated the association between short-term exposure to different sources of fine particulate matter (PM_2.5) and biomarkers of coagulation and inflammation in two different panels of elderly and healthy young individuals in central Tehran. Five biomarkers, including white blood cells (WBC), high sensitive C-reactive protein (hsCRP), tumor necrosis factor-soluble receptor-II (sTNF-RII), interleukin-6 (IL-6), and von Willebrand factor (vWF) were analyzed in the blood samples drawn every 8 weeks from the subjects between May 2012 and May 2013. The studied populations consisted of 44 elderly individuals at a retirement home as well as 40 young adults residing at a school dormitory. Positive Matrix Factorization (PMF)-resolved source-specific PM_2.5 mass concentrations and biomarker levels were used as the input to the linear mixed-effects regression model to evaluate the impact of exposure to previously identified PM sources at retirement home and school dormitory in two time lag configurations: lag 1-3 (1-3 days before the blood sampling), and lag 4-6 (4-6 days before the blood sampling). Our analysis of the elderly revealed positive associations of all biomarkers (except hsCRP) with particles of secondary origin in both time lags, further corroborating the toxicity of secondary aerosols formed by photochemical processing in central Tehran. Moreover, industrial emissions, and road dust particles were positively associated with WBC, sTNF-RII, and IL-6 among seniors, while vehicular emissions exhibited positive associations with all biomarkers in either first- or second-time lag. In contrast, most of the PM_2.5 sources showed insignificant associations with biomarkers of inflammation in the panel of healthy young subjects. Therefore, findings from this study indicated that various PM_2.5 sources increase the levels of inflammation and coagulation biomarkers, although the strength and significance of these associations vary depending on the type of PM sources, demographic characteristics, and differ across the different time lags. Implications: Tehran, the capital of Iran with a population of more than 9 million people, has been facing serious air pollution challenges as a result of extensive vehicular, and industrial activities in the previous years. Among various air pollutants in Tehran, fine particulate matters (PM_2.5, particles with aerodynamic diameters < 2.5 µm) are known as one of the most important critical pollutants, causing several adverse health impacts including lung cancer, respiratory, cardiovascular, and cardiopulmonary diseases. Therefore, a number of studies in the area have tried to investigate the adverse health impacts of exposure to PM_2.5. However, no studies have ever been conducted in Tehran to examine the association between specific PM_2.5 sources and biomarkers of coagulation and systemic inflammation as indicators of cardiovascular disorders. Indeed, this is the first study in the area investigating the association of source-specific PM_2.5 with biomarkers of inflammation including white blood cells (WBC), high sensitive C-reactive protein (hsCRP), tumor necrosis factor-soluble receptor-II (sTNF-RII), interleukin-6 (IL-6), and von Willebrand factor (vWF). Our results have important implications for policy makers in identifying the most toxic sources of PM_2.5, and in turn designing schemes for mitigating adverse health impacts of air pollution in Tehran.

Light absorption enhancement of particulate matters and their source apportionment over the Asian continental outflow site and South Yellow Sea

Light absorption enhancement of black carbon due to the aerosol mixing states is an important parameterization for climate modeling, while emission source contributions to the enhancement factor are unclear. An intensive campaign was conducted simultaneously at a China coastal site (Qingdao city) and maritime sites (South Yellow Sea, SYS) in August and Nov to Dec 2018. The absorption enhancement (E_MAC) of the black carbon was calculated using a two-step solvent dissolution protocol and found 1.96 ± 0.68, 1.64 ± 0.38, and 2.40 ± 0.76 for Qingdao summer (QS), Qingdao autumn (QA), and SYS, respectively. Positive matrix factorization (PMF) model identified six sources of PM_2.5 and E_MAC, which were secondary aerosol (with contribution 27.9% and 29.2%), coal combustion (24.9% and 20.2%), industrial emissions (15.2% and 25.4%), sea salt (6.9% and 9.6%), vehicle emissions (12.1% and 10.9%), and soil dust (13.0% and 4.7%), respectively. These sources increased the absorption of black carbon by a factor of 1.25 ± 0.11 (secondary aerosol), 1.21 ± 0.20 (industrial emissions), 1.17 ± 0.08 (coal combustion), 1.09 ± 0.07 (vehicle emissions), 1.08 ± 0.17 (sea salt), and 1.04 ± 0.10 (soil dust). Based on the correlation between PM and E_MAC source contributions, we estimated that secondary aerosols, industrial emissions, and coal combustion contributed to 74.8% of absorption enhancement at a regional scale in China. The source apportionment for E_MAC offers a new diagnosis for each source regarding aerosol forcing simulation which inputs from the individual emission sector.

Humidity and PM2.5 composition determine atmospheric light extinction in the arid region of northwest China

Atmospheric visibility can directly reflect the air quality. In this study, we measured water-soluble ions (WSIs), organic and element carbon (OC and EC) in PM_2.5 from September 2017 to August 2018 in Urumqi, NW China. The results show that SO₄^2-, NO₃^- and NH₄⁺ were the major WSIs, together accounting for 7.32%-84.12% of PM_2.5 mass. Total carbon (TC=OC+EC) accounted for 12.12% of PM_2.5 mass on average. And OC/EC > 2 indicated the formation of secondary organic carbon (SOC). The levels of SO₄^2-, NO₃^- and NH₄⁺ in low visibility days were much higher than those in high visibility days. Relative humidity (RH) played a key role in affecting visibility. The extinction coefficient (b_ext) that estimated via Koschmieder formula with visibility was the highest in winter (1441.05 ± 739.95 Mm^-1), and the lowest in summer (128.58 ± 58.00 Mm^-1). The b_ext that estimated via IMPROVE formula with PM_2.5 chemical component was mainly contributed by (NH₄)₂SO₄ and NH₄NO₃. The b_ext values calculated by both approaches presented a good correlation with each other (R² = 0.87). Multiple linear regression (MLR) method was further employed to reconstruct the empirical regression model of visibility as a function of PM_2.5 chemical components, NO₂ and RH. The results of source apportionment by Positive Matrix Factorization (PMF) model showed that residential coal combustion and vehicle emissions were the major sources of b_ext.

Spatial distribution of fine and coarse particulate matter during a southwest monsoon in Peninsular Malaysia

This study aimed to determine the spatial distribution of PM_2.5 and PM₁₀ collected in four regions (North, Central, South and East Coast) of Peninsular Malaysia during the southwest monsoon. Concurrent measurements of PM_2.5 and PM₁₀ were performed using a high volume sampler (HVS) for 24 h (August to September 2018) collecting a total of 104 samples. All samples were then analysed for water soluble inorganic ions (WSII) using ion chromatography, trace metals using inductively coupled plasma-mass spectroscopy (ICP-MS) and polycyclic aromatic hydrocarbon (PAHs) using gas chromatography-mass spectroscopy (GC-MS). The results showed that the highest average PM_2.5 concentration during the sampling campaign was in the North region (33.2 ± 5.3 μg m^-3) while for PM₁₀ the highest was in the Central region (38.6 ± 7.70 μg m^-3). WSII recorded contributions of 22% for PM_2.5 and 20% for PM₁₀ mass, with SO₄^2- the most abundant species with average concentrations of 1.83 ± 0.42 μg m^-3 (PM_2.5) and 2.19 ± 0.27 μg m^-3 (PM₁₀). Using a Positive Matrix Factorization (PMF) model, soil fertilizer (23%) was identified as the major source of PM_2.5 while industrial activity (25%) was identified as the major source of PM₁₀. Overall, the studied metals had hazard quotients (HQ) value of <1 indicating a very low risk of non-carcinogenic elements while the highest excess lifetime cancer risk (ELCR) was recorded for Cr VI in the South region with values of 8.4E-06 (PM_2.5) and 6.6E-05 (PM₁₀). The incremental lifetime cancer risk (ILCR) calculated from the PAH concentrations was within the acceptable range for all regions.

Chemical characteristics and sources of ambient PM2.5 in a harbor area: Quantification of health risks to workers from source-specific selected toxic elements

Samples of ambient PM_2.5 were collected in the Qingdao harbor area between 21 March and May 25, 2016, and analyzed to investigate the compositions and sources of PM_2.5 and to assess source-specific selected toxic element health risks to workers via a combination of positive matrix factorization (PMF) and health risk (HR) assessment models. The mean concentration of PM_2.5 in harbor area was 48 μg m^-3 with organic matter (OM) dominating its mass. Zn and V concentrations were significantly higher than the other selected toxic elements. The hazard index (HI) and cancer risk (R_i) of all selected toxic elements were lower than the United States Environmental Protection Agency (USEPA) limits. There were no non-cancer and cancer risks for workers in harbor area. The contributions from industrial emissions (IE), ship emissions (SE), vehicle emissions (VE), and crustal dust and coal combustion (CDCC) to selected toxic elements were 39.0%, 12.8%, 24.0%, and 23.0%, respectively. The HI values of selected toxic elements from IE, CDCC, SE, and VE were 1.85 × 10^-1, 7.08 × 10^-2, 6.36 × 10^-2, and 3.37 × 10^-2, respectively; these are lower than the USEPA limits. The total cancer risk (R_t) value from selected toxic elements in CDCC was 2.04 × 10^-7, followed by IE (6.40 × 10^-8), SE (2.26 × 10^-8), and VE (2.18 × 10^-8). CDCC and IE were the likely sources of cancer risk in harbor area. The Bo Sea and coast were identified as the likely source areas for health risks from IE via potential source contribution function (PSCF) analysis based on the results of PMF-HR modelling. Although the source-specific health risks were below the recommended limit values, this work illustrates how toxic species in PM_2.5 health risks can be associated with sources such that control measures could be undertaken if the risks warranted it.

Carbonaceous Aerosols in PM1, PM2.5, and PM10 Size Fractions over the Lanzhou City, Northwest China

Carbonaceous particles have been confirmed as major components of ambient aerosols in urban environments and are related to climate impacts and environmental and health effects. In this study, we collected different-size particulate matter (PM) samples (PM1, PM2.5, and PM10) at an urban site in Lanzhou, northwest China, during three discontinuous one-month periods (January, April, and July) of 2019. We measured the concentrations and potential transport pathways of carbonaceous aerosols in PM1, PM2.5, and PM10 size fractions. The average concentrations of OC (organic carbon) and EC (elemental carbon) in PM1, PM2.5, and PM10 were 6.98 ± 3.71 and 2.11 ± 1.34 μg/m3, 8.6 ± 5.09 and 2.55 ± 1.44 μg/m3, and 11.6 ± 5.72 and 4.01 ± 1.72 μg/m3. The OC and EC concentrations in PM1, PM2.5, and PM10 had similar seasonal trends, with higher values in winter due to the favorable meteorology for accumulating pollutants and urban-increased emissions from heating. Precipitation played a key role in scavenge pollutants, resulting in lower OC and EC concentrations in summer. The OC/EC ratios and principal component analysis (PCA) showed that the dominant pollution sources of carbon components in the PMs in Lanzhou were biomass burning, coal combustion, and diesel and gasoline vehicle emissions; and the backward trajectory and concentration weight trajectory (CWT) analysis further suggested that the primary pollution source of EC in Lanzhou was local fossil fuel combustion.

Bibliometric and Social Network Analysis of Civil Engineering Sustainability Research from 2015 to 2019

With the development of civil engineering sustainability, the scope of corresponding research covers a broader range. It is difficult for researchers to master the holistic situation of the study, leading to duplication and lag of their research. Therefore, this paper aims to present a state-of-the-art of the research of civil engineering sustainability by adopting two new methods (bibliometric and social network analysis) to review the literature of this field. It is concluded that the existing research takes engineering as the main subject to improve its sustainability through technologies. Current research mainly focuses on technological innovations and evaluations of environmental impacts in the fields of construction technology, energy consumption, material preparation, and design. The countries with the largest number of published articles are the United States and China. The Hong Kong Polytechnic University is the institution that has published more articles than others. Journal of Cleaner Production and Sustainability are the journals that have published the most articles. For the researchers, a professor of the University of Adelaide is the researcher who has published the most articles, and experts from South China University of Technology, Chongqing University, and University of Brighton are the main hubs among different researchers.

Chemical Characteristics of Major Inorganic Ions in PM2.5 Based on Year-Long Observations in Guiyang, Southwest China—Implications for Formation Pathways and the Influences of Regional Transport

Sulfate, nitrate and ammonium (SNA) are the dominant components of water-soluble ions (WSIs) in PM2.5, which are of great significance for understanding the sources and transformation mechanisms of PM2.5. In this study, daily PM2.5 samples were collected from September 2017 to August 2018 within the Guiyang urban area and the concentrations of the major WSIs in the PM2.5 samples were characterized. The results showed that the average concentration of SNA (SO42−, NO3−, NH4+) was 15.01 ± 9.35 μg m−3, accounting for 81.05% (48.71–93.76%) of the total WSIs and 45.33% (14.25–82.43%) of the PM2.5 and their possible chemical composition in PM2.5 was (NH4)2SO4 and NH4NO3. The highest SOR (sulfur oxidation ratio) was found in summer, which was mainly due to the higher temperature and O3 concentrations, while the lowest NOR (nitrogen oxidation ratio) found in summer may ascribe to the volatilization of nitrates being accelerated at higher temperature. Furthermore, the nitrate formation was more obvious in NH4+-rich environments so reducing NH3 emissions could effectively control the formation of nitrate. The results of the trajectory cluster analysis suggested that air pollutants can be easily enriched over short air mass trajectories from local emission sources, affecting the chemical composition of PM2.5.

Pollution characteristics of bioaerosols in PM2.5 during the winter heating season in a coastal city of northern China

Frequent heavy air pollution occurred during the winter heating season of northern China. In this study, PM_2.5 (particles with an aerodynamic diameter less than 2.5 μm) was collected from a coastal city of China during the winter heating season from January 1 to March 31, 2018, and the soluble ions, organic carbon (OC), elemental carbon (EC), bacterial, endotoxin, and fungal concentration in PM_2.5 were analyzed. During the winter heating season, PM_2.5 and bioaerosols increased on polluted days, and the secondary inorganic ions, including NO₃^-, NH₄⁺, and SO₄^2-, increased significantly. Meteorological factors, such as wind direction and wind speed, had major impacts on the distributions of PM_2.5 and bioaerosols. Pollutant concentration was high when there was a westerly wind with the speed of 3-6 m/s from inland area. Using the air mass backward trajectories and principal component analysis, we elucidate the potential origins of bioaerosol in PM_2.5. The backward trajectory suggested that air mass for polluted samples (PM_2.5 > 75 μg/m³) commonly originated from continent (9.62%), whereas air masses for clean samples (PM_2.5 < 35 μg/m³) were mainly from marine (56.73%). The interregional transport of pollutants from continental area contributed most to PM_2.5. Principal component analysis of the water-soluble ions and bioaerosol indicated that air pollution of the coastal city was greatly affected by coal combustion, biomass burning, and regional transmission of high-intensity pollutants from continent. Among that, interregional transport, biomass burning, and dust from soil and plants were main sources of bioaerosol. Our findings provide important insights into the origins and characteristics of bioaerosol in PM_2.5 during the winter heating season of the coastal city in northern China.

Chemical characteristics and source apportionment of PM2.5 using PMF modelling coupled with 1-hr resolution online air pollutant dataset for Linfen, China

The chemical species in PM_2.5 and air pollutant concentration data with 1-hr resolution were monitored synchronously between 15 November 2018 and 20 January 2019 in Linfen, China, which were analysed for multiple temporal patterns, and PM_2.5 source apportionment using positive matrix factorisation (PMF) modelling coupled with online chemical species data was conducted to obtain the apportionment results of distinct temporal patterns. The mean concentration of PM_2.5 was 124 μg/m³ during the heating period, and NO₃^- and organic carbon (OC) were the dominant species. The concentrations and percentages of NO₃^-, SO₄^2-, and OC increased notably during the growth periods of haze events, thereby indicating secondary particle formation. Six factors were identified by the PMF model during the heating period, including vehicular emissions (VE: 26.5%), secondary nitrate (SN: 16.5%), coal combustion and industrial emissions (CC&IE: 25.7%), secondary sulfate and secondary organic carbon (SS&SOC: 24.4%), biomass burning (BB: 1.0%), and crustal dust (CD: 5.9%). The primary sources of PM_2.5 on clean days were CD (33.3%), VE (23.1%), and SS&SOC (20.6%), while they were CC&IE (32.9%) and SS&SOC (28.3%) during the haze events. The contributions of secondary sources and CC&IE increased rapidly during the growth periods of haze events, while that of CD increased during the dissipation period. Diurnal variations in the contribution of secondary sources were mainly related to the accumulation and transformation of corresponding gaseous precursors. In comparison, contributions of CC&IE and VE varied as a function of the domestic heating load and peak levels occurred during the morning and evening rush hours. High contributions of major sources (CC&IE and SS&SOC) during haze events originated mainly from the north and south, while high contribution of a major source (CD) on clean days was from the northwest.

Investigating the impacts of coal-fired power plants on ambient PM2.5 by a combination of a chemical transport model and receptor model

Aimed at evaluating the impacts of coal-fired power plants on urban air quality and human health, a one-month intensive observation campaign was conducted in a typical polluted city located in the 2 + 26 city cluster (Beijing, Tianjin and 26 other cities) of the North China Plain in December 2017. The observation results illustrated that the coal-fired power plant in this city increased the monthly average fine particulate matter (PM_2.5) concentration by ~5% at the city scale. The impacts differed under various diffusion conditions. A three-dimensional nested air quality condition model (the Nested Air Quality Perdition Model System or NAQPMS) with source apportionment was employed to analyze the impacts. The results indicated that power plants had the largest effect on regional air quality during the severe-pollution period, while any influence could be ignored during periods with excellent dissipation under robust winds. PM_2.5 contributed by the power plant mainly occurred below 150 m, diffused 100 km away, and reached a level of approximately 5 μg m^-3 during the light-pollution period. During the accumulation period, the plume reached a height of 500 m, diffused to the downwind area approximately 100 km away within half a day, and contributed at most 40 μg m^-3 to PM_2.5. The affected area expanded to 250 km during the severe-pollution period, and the contribution to PM_2.5 was at least 10 μg m^-3 at different distances. The affected height reached approximately 500 m, with PM_2.5 exceeding 10 μg m^-3, mainly constrained below 150 m. Overall, regional integrated control strategies should be implemented for the power plants in the 2 + 26 city cluster during pollution episodes to further improve air quality.

Occurrence and sources of chromophoric organic carbon in fine particulate matter over Xi'an, China

Understanding the characteristics and sources of atmospheric chromophores is essential to assess their impact on climate change and the quality of atmospheric environment. In this work, the fine particulate matter (PM_2.5) samples of Xi'an, China in 2017 were analyzed by excitation-emission matrices and parallel factor analysis (EEM-PARAFAC) method to obtain the species, content, sources and seasonal variation characteristics of atmospheric chromophores. The results showed that humic-like (HULIS) chromophores and polycyclic aromatic hydrocarbons-like (PAHs-like) chromophores were the most abundant chromophores in the samples, accounting for 42% and 33%, respectively. With the aggravation of air pollution, the relative content of low-polarity chromophores increased markedly, while the relative content of polar chromophores decreased. The concentrations of atmospheric chromophores exhibited obvious seasonal variation characteristics: high in winter and low in summer. Similarly, the relative contributions of atmospheric chromophores from each source varied with the season. In addition, special weather and human activities had a significant influence on the source of atmospheric chromophores. Dust source was an important source of atmospheric chromophores, which was susceptible to long-range incoming air masses from northwestern regions in spring. However, the chromophores from the dust source were easily removed by wet precipitation, which was the same as the chromophores from the combustion source. The chromophores from the combustion source were susceptible to human activities. The contribution of combustion source to atmospheric chromophores was reduced due to the implementation of air pollution control policies during the Chinese Spring Festival. In summer, the formation of photochemical secondary chromophores was more significant than in other seasons, and the photochemical secondary chromophores increased due to the formation of liquid phase reactions under high relative humidity conditions.