The impact of biomass burning occurred in the Indo-China Peninsula on PM2.5 and its spatiotemporal characteristics over Yunnan Province

Being one of the most serious biomass burning regions in the world, the air pollution caused by spring combustion in the Indo-China Peninsula (ICP) has already had an impact on Yunnan Province's beautiful environment and excellent air quality to some extent. In this study, considering the differences in geographical location and topography of Yunnan, we used the K-Means algorithm to divide it into five clustering zones according to the spatiotemporal variation characteristics of PM2.5. Then this study explored the spatial and temporal characteristics of pollution in Yunnan Province and biomass combustion in ICP based on the multi-source data such as MOD14A1, GDAS1, and ground-based PM2.5 data, and used HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) pollution tracer analysis and other data statistical methods. The results show that the spatiotemporal variation characteristics of PM2.5 in Yunnan Province show large differences within each clustering zone (CZ). Spatially, CZ 2 has better air quality throughout the year, and the areas with higher PM2.5 are mainly in CZ 1 and CZ 3. Temporally, the months with higher concentration values were mainly from February to April, and also this period owed high biomass burning activities in the ICP, which resulted in pollution values exceeding 60 μg/m3 within certain CZs. Finally, the results of the pollution tracer analysis showed that within CZs other than CZ 2, the contribution due to the burning in the ICP was variable, and that the countries with a high contribution of pollution to Yunnan Province were Myanmar, and the other sources of pollution are mainly caused by local and neighbouring anthropogenic activities. Therefore, based on overall improvement of air quality, Yunnan Province is necessary to prevent and control not only the pollutants from the ICP from February to April, but also the pollution caused by the emissions from rapid economic development.

Sources, variability, long-term trends, and radiative forcing of aerosols in the Arctic: implications for Arctic amplification

Atmospheric pollution in the Arctic has been an important driver for the ongoing climate change there. Increase in the Arctic aerosols causes the phenomena of Arctic haze and Arctic amplification. Our analysis of aerosol optical depth (AOD), black carbon (BC), and dust using ground-based, satellite, and reanalysis data in the Arctic for the period 2003-2019 shows that the lowest amount of all these is found in Greenland and Central Arctic. There is high AOD, BC, and dust in the northern Eurasia and parts of North America. All aerosols show their highest values in spring. Significant positive trends in AOD (> 0.003 year-1) and BC (0.0002-0.0003 year-1) are found in the northwestern America and northern Asia. Significant negative trends are observed for dust (- 0.0001 year-1) around Central Arctic. Seasonal analysis of AOD, BC, and dust reveals an increasing trend in summer and decreasing trend in spring in the Arctic. The major sources of aerosols are the nearby Europe, Russia, and North America regions, as assessed using the potential source contribution function (PSCF). Anthropogenic emissions from the transport, energy, and household sectors along with natural sources such as wildfires contribute to the positive trends of aerosols in the Arctic. These increasing aerosols in the Arctic influence Arctic amplification through radiative effects. Here, we find that the net aerosol radiative forcing is high in Central Arctic, Greenland, Siberia, and Canadian Arctic, about 2-4 W/m2, which can influence the regional temperature. Therefore, our study can assist policy decisions for the mitigation of Arctic haze and Arctic amplification in this environmental fragile region of the Earth.

Ambient Volatile Organic Compound Characterization, Source Apportionment, and Risk Assessment in Three Megacities of China in 2019

In order to illustrate pollution characterization, source apportionment, and risk assessment of VOCs in Beijing, Baoding, and Shanghai, field observations of CO, NO, NO2, O3, and volatile organic compounds (VOCs) were conducted in 2019. Concentrations of VOCs were the highest in Beijing (105.4 ± 52.1 ppb), followed by Baoding (97.1 ± 47.5 ppb) and Shanghai (91.1 ± 41.3 ppb). Concentrations of VOCs were the highest in winter (120.3 ± 61.5 ppb) among the three seasons tested, followed by summer (98.1 + 50.8 ppb) and autumn (75.5 + 33.4 ppb). Alkenes were the most reactive VOC species in all cities, accounting for 56.0%, 53.7%, and 39.4% of ozone formation potential in Beijing, Baoding, and Shanghai, respectively. Alkenes and aromatics were the reactive species, particularly ethene, propene, 1,3,5-trimethylbenzene, and m/p-xylene. Vehicular exhaust was the principal source in all three cities, accounting for 27.0%, 30.4%, and 23.3% of VOCs in Beijing, Baoding, and Shanghai, respectively. Industrial manufacturing was the second largest source in Baoding (23.6%) and Shanghai (21.3%), and solvent utilization was the second largest source in Beijing (25.1%). The empirical kinetic modeling approach showed that O3 formation was limited by both VOCs and nitric oxides at Fangshan (the suburban site) and by VOCs at Xuhui (the urban site). Acrolein was the only substance with an average hazard quotient greater than 1, indicating significant non-carcinogenic risk. In Beijing, 1,2-dibromoethane had an R-value of 1.1 × 10-4 and posed a definite carcinogenic risk.

Long-term PM2.5 pollution over China: Identification of PM2.5 pollution hotspots and source contributions

Fine particulate matter, with an aerodynamic diameter ≤ 2.5 μm (PM_2.5), is a severe problem in China. The lack of ground-based measurements and its sparse distribution obstruct long-term air pollution impact studies over China. Therefore, the present study used newly updated Global Estimates (V5. GL.02) of monthly PM_2.5 data from 2001 to 2020 based on Geographically Weighted Regression (GWR) by Washington University. The GWR PM_2.5 data were validated against ground-based measurements from 2014 to 2020, and the validation results demonstrated a good agreement between GWR and ground-based PM_2.5 with a higher correlation (r = 0.95), lower error (8.14), and lower bias (-3.10 %). The long-term (2001-2020) PM_2.5 data were used to identify pollution hotspots and sources across China using the potential source contribution function (PSCF). The results showed highly significant PM_2.5 pollution hotspots in central (Henan, Hubei), North China Plain (NCP), northwest (Taklimakan), and Sichuan Basin (Chongqing, Sichuan) in China, with the most severe pollution occurring in winter compared to other seasons. During the winter, PM_2.5 was in the range from 6.08 to 93.05 μg/m³ in 33 provinces, which is 1.22 to 18.61 times higher than the World Health Organization (WHO) Air Quality Guidelines (AQG-2021; annual mean: 5 μg/m³). In 26 provinces, the reported PM_2.5 was 1.07 to 2.66 times higher than the Chinese Ambient Air Quality Standard (AAQS; annual mean: 35 μg/m³). Furthermore, provincial-level trend analysis shows that in most Chinese provinces, PM_2.5 increased significantly (3-43 %) from 2001 to 2012, whereas it decreased by 12-94 % from 2013 to 2020 due to the implementation of air pollution control policies. Finally, the PSCF analysis demonstrates that China's air quality is mainly affected by local PM_2.5 sources rather than by pollutants imported from outside China.

PM2.5 carbonaceous components and mineral dust at a COALESCE network site - Bhopal, India: Assessing the impacts of COVID-19 lockdowns on site-specific optical properties

Thermal elemental carbon (EC), optical black carbon (BC), organic carbon (OC), mineral dust (MD), and 7-wavelength optical attenuation of 24-hour ambient PM_2.5 samples were characterized/estimated at a regionally representative site (Bhopal, central India) during a business-as-usual year (2019) and the COVID-19 lockdowns year (2020). This dataset was used to estimate the influence of emissions source reductions on the optical properties of light-absorbing aerosols. During the lockdown period, the concentration of EC, OC, BC_{880 nm}, and PM_2.5 increased by 70 % ± 25 %, 74 % ± 20 %, 91 % ± 6 %, and 34 % ± 24 %, respectively, while MD concentration decreased by 32 % ± 30 %, compared to the same time period in 2019. Also, during the lockdown period, the estimated absorption coefficient (b_abs) and mass absorption cross-section (MAC) of Brown Carbon (BrC) at 405 nm was higher (42 % ± 20 % and 16 % ± 7 %, respectively), while these quantities for MD, i.e., b_abs-MD and MAC_MD values were lower (19 % ± 9 % and 16 % ± 10 %), compared to the corresponding period during 2019. Also, b_abs-BC-808 (115 % ± 6 %) and MAC_BC-808 (69 % ± 45 %) values increased during lockdown periods compared with the corresponding period during 2019. It is hypothesized that although anthropogenic emissions (chiefly industrial and vehicular) reduced drastically during the lockdown period compared to the business-as-usual period, an increase in the values of optical properties (b_abs and MAC) and concentrations of BC and BrC, were likely due to the increased local and regional biomass burning emissions during this period. This hypothesis is supported by the CBPF (Conditional Bivariate Probability Function) and PSCF (Potential Source Contribution Function) analyses for BC and BrC.

Comparison of pollution status and source apportionment for PCBs and OCPs of indoor dust from an industrial city

In this study, the pollution status of polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs) was investigated in indoor and outdoor dust from three different functional areas of Hefei, China. The relationship between the concentrations of PCBs and OCPs and different influencing factors in dwellings was studied. The results showed that the concentrations of PCBs and OCPs were higher in samples from dwellings with higher smoking frequency, lower cleaning frequency, higher floors and smaller household size. The results of Spearman's correlation coefficient analysis indicated that PCBs and OCPs were not consistently associated with each other, while sources of low-chlorinated PCBs and high-chlorinated PCBs were different. Scanning electron microscopy (SEM) shows the shape of indoor dust was a mixture of blocky, flocculated, spherical structures, and irregular shapes. The results of principal component analysis (PCA) and positive matrix factorization model (PMF) showed that the PCBs and OCPs of indoor dust came from both indoor and outdoor sources between local and regional transport. Carbon (δ¹³C) and Nitrogen (δ¹⁵N) stable isotope results indicate or show that the indoor dust (δ¹³C: - 24.37‰, δ¹⁵N: 6.88‰) and outdoor dust (δ¹³C: - 12.65‰, δ¹⁵N: 2.558‰) is derived from fossil fuel, coal combustion, road dust, fly ash, C4 biomass and soil. Potential source contribution factor (PSCF) and concentration weighted-trajectory analysis suggest that sources of pollutants were local and regional transport from surrounding provinces and marine emissions. The average daily dose (adult: 8.20E-04, children: 2.37E-03) of pollutants and the carcinogenic risks (adult: 1.23E-02, children: 2.65E-02) were relatively greater for children than adults. This study demonstrates the utility of SEM to characterize indoor dust morphology while combining PMF, PSCF, and stable isotope methods in identifying indoor PCBs and OCPs sources and regions.

PM2.5-bound polycyclic aromatic hydrocarbons of a megacity in eastern China: Source apportionment and cancer risk assessment

Ninety-six fine particulate matter (PM_2.5) samples covering four seasons from October 2020 to August 2021 were collected at a 'super' site in Hangzhou, a megacity in eastern China. These samples were analyzed to determine the sources and potential cancer risks to humans of 16 United States Environmental Protection Agency priority polycyclic aromatic hydrocarbons (PAHs). The average concentrations of the PAHs in PM_2.5 in autumn, winter, spring, and summer were 8.35 ± 4.90, 27.9 ± 13.6, 8.3 ± 5.97, and 1.05 ± 0.50 ng/m³, respectively, and with an annual average of 11.9 ± 13.2 ng/m3. The source apportionment by positive matrix factorization analysis indicated that, based on the yearly average, the major sources of PAHs were traffic emissions (38.2 %), coal combustion (28.9 %), coke (21.7 %), and volatilization (11.1 %). Strong correlations between high concentrations of carbonaceous aerosols and high-molecular-weight PAHs in winter could be attributed to incomplete combustion. Long-range transport of air from the sea to the southeast resulted in low concentrations of carbonaceous aerosols and low-molecular-weight PAHs in summer. Trajectory clustering and the potential source contribution function both indicated that the Yangtze River Delta was the main source region of PAHs for PM_2.5 in Hangzhou in spring and summer. In autumn and winter, it was dominated by long-range transport from northern China. Lifetime lung cancer risk assessment revealed that the PAHs in PM_2.5 impose moderate human health risks in Hangzhou due to traffic emissions. The results of this study provide important information for policymakers to establish abatement strategies to reduce PAH emissions in Hangzhou, and perhaps other urban centers across China.

Characteristics and source apportionment of water-soluble inorganic ions in atmospheric particles in Lvliang, China

Seasonal atmospheric particulate matter samples with different particle sizes (< 2.5 μm [PM_2.5], 2.5-5 μm [PM_2.5-5], 5-10 μm [PM_5-10], and 10-100 μm [PM_10-100]) were collected to analyze the mass concentration and distribution characteristics of nine water-soluble ions (WSIs; F^-, Cl^-, NO₃^-, SO₄^2-, Na⁺, NH₄⁺, K⁺, Mg²⁺, and Ca²⁺) in Lvliang in China. The results of chemical composition analysis indicated that the average concentration of total WSIs was 29.08 µg·m^-3 and accounted for 40.45% of PM_2.5, 80.99% of which was attributable to SO₄^2-, NH₄⁺, and NO₃^-; the concentration demonstrated obvious distribution characteristics. NO₃^- and NH₄⁺ primarily exist as NH₄NO₃ and (NH₄)₂SO₄, respectively, in fine particles but as NaNO₃ and NH₄Cl, respectively, in coarse particles. The PM_2.5 was alkaline overall, and K⁺ and NH₄⁺ caused the highest R_C/A values in autumn. Stationary sources contribute more to WSIs in particulates than mobile sources. The secondary transformation degree of SO₂ was higher than that of NOx, especially in fine particles. The positive matrix factorization (PMF) and potential source contribution function (PSCF) models were combined to determine the sources of WSIs in PM_2.5. Through use of the PMF model, five source factors were categorized: secondary aerosols (43.0%), biomass combustion (21.7%), coal combustion (17.6%), dust (10.9%), and vehicular traffic (6.8%). The results of the PSCF model suggested that the transport of pollutants from Shanxi, northwestern Shaanxi, Gansu, Inner Mongolia and Henan, had the greatest effect on air quality in Lvliang.

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.

Spatial distribution, driving factors and health risks of fine particle-bound polycyclic aromatic hydrocarbons (PAHs) from indoors and outdoors in Hefei, China

Atmospheric particulate matter, especially in urban and industrial environments, can act as a source of different organic pollutants that can pose significant health impacts to residents. However, the pollution status and transport mechanisms of fine particle-bound polycyclic aromatic hydrocarbons (PAHs) in indoor and outdoor environments are uncertain. This study aimed to determine the spatial distribution and morphological characteristics of fine particle-bound PAHs and analyze the factors (source contributions and backward trajectories) that influence their concentrations. The results showed that mean concentrations of 16 PAHs were higher in indoor dust as compared to outdoor dust. In addition, the lowest concentrations of the 16 PAHs were found on the 11-20th floor, with smoking households > nonsmoking households (except Nap, Acy, and Ace). The 2-3 ring PAHs were more prominent in households with cooking activities. The particle size distribution showed that most of the particles were <62 μm in diameter, indicating that the indoor particles were smaller in size. Furthermore, the range of δ13C values in the outdoor dust (-30.17 ~ -28.63 ‰) samples was significantly lower than in indoor dust (-28.29 ~ -22.53 ‰). The results based on diagnostic ratios, positive matrix factorization (PMF) analysis and backward trajectory model analysis suggested that the sources of PAHs in indoor and outdoor dust were mixed, originated both locally and from neighboring provinces transported over long distances, especially concentrated in the Yangtze River Delta area. Finally, carcinogenic risk values for indoor dust were greater than those for outdoor dust. Therefore, it is recommended that local governments and industries with high PAH emissions should implement proper protocols to monitor and minimize the pollution levels of PAHs in the urban industrial environment in order to mitigate their health risks.

Variabilities of δ13C and carbonaceous components in ambient PM2.5 in Northeast India: Insights into sources and atmospheric processes

A year-long sampling campaign of ambient PM_2.5 (particulate matter with aerodynamic diameter ≤2.5 mm) at a regional station in the North-Eastern Region (NER) of India was performed to understand the sources and formation of carbonaceous aerosols. Mass concentration, carbon fractions (organic and elemental carbon), and stable carbon isotope ratio (δ¹³C) of PM_2.5 were measured and studied along with cluster analysis and Potential Source Contribution Function (PSCF) modelling. PM_2.5 mass concentration was observed to be highest during winter and post-monsoon seasons when the meteorological conditions were relatively stable compared to other seasons. Organic carbon (OC) concentration was more than two times higher in the post-monsoon and winter seasons than in the pre-monsoon and monsoon seasons. Air mass back trajectory cluster analysis showed the dominance of local and regional air masses during winter and post-monsoon periods. In contrast, long-range transported air masses influenced the background site in pre-monsoon and monsoon. Air mass data and PSCF analysis indicated that aerosols during winter and post-monsoon are dominated by freshly generated emissions from local sources along with the influence from regional transport of polluted aerosols. On the contrary, the long-range transported air masses containing aged aerosols were dominant during pre-monsoon. No significant variability was observed in the range of δ¹³C values (-28.2‰ to -26.4‰) during the sampled seasons. The δ¹³C of aerosols indicates major sources to be combustion of biomass/biofuels (C3 plant origin), biogenic aerosols, and secondary aerosols. The δ¹³C variability and cluster/PSCF modelling suggest that aged aerosols (along with enhanced photo-oxidation derived secondary aerosols) influenced the final δ¹³C during the pre-monsoon. On the other hand, lower δ¹³C in winter and post-monsoon is attributed to the freshly emitted aerosols from biomass/biofuels.

PSCF and CWT methods as a tool to identify potential sources of 7Be and 210Pb aerosols in Granada, Spain

This research is focused on studying the preferred source regions and the pathways of the air masses with high particulate concentrations impacting on the activity concentrations of ⁷Be and ²¹⁰Pb aerosols in Granada atmosphere. For this purpose, three different source-receptor methods have been used: Cluster Analysis, Potential Source Contribution Function (PSCF), and Concentration Weighted Trajectory (CWT). Air filter samples were weekly collected and analysed in Granada university (Spain 37.177N, 3.598 W, 687m a.s.l.) during 12 years (2006-2017) for the activity concentration of ⁷Be, and during 5 years (2010-2014) for the one of ²¹⁰Pb. The time series of the collected data indicate that the concentration of both radiotracers present a cyclical and seasonal pattern, in association with their origins and atmospheric conditions. Clustering analysis showed that the air masses arriving to Granada can be classified as: (1) tropical continental air masses coming from the Mediterranean Sea, (2) tropical and warm polar maritime air masses produced over the Atlantic Ocean, and (3) continental air masses originated over Europe and Northern Africa. The PSCF and CWT methods confirmed that the main source areas of ⁷Be are located in the Atlantic coast of southern Morocco, and Northern Africa. On the other hand, southern France and the Algerian desert were found to be the main region sources of ²¹⁰Pb. In addition, the Mediterranean Basin has been postulated as a strong source region for ⁷Be and ²¹⁰Pb. Furthermore, the PSCF and CWT models show that the regions with larger ⁷Be/²¹⁰Pb ratios are located in the Atlantic Ocean, due to frequent stratospheric intrusions specially during the winter months.

Characteristics, formation, and sources of PM2.5 in 2020 in Suzhou, Yangtze River Delta, China

Here we present seasonal chemical characteristics, formations, sources of PM_2.5 in the year 2020 in Suzhou, Yangtze River Delta, China. Expectedly, organic matter (OM) found to be the most dominant component of PM_2.5, with a year-average value of 10.3 ± 5.5 μg m^-3, followed by NO₃^- (6.7 ± 6.5 μg m^-3), SO₄^2- (3.3 ± 2.5 μg m^-3), NH₄⁺ (3.2 ± 2.8 μg m^-3), EC (1.1 ± 1.3 μg m^-3), Cl^- (0.57 ± 0.56 μg m^-3), Ca²⁺ (0.55 ± 0.91 μg m^-3), K⁺ (0.2 ± 1.0 μg m^-3), Na⁺ (0.18 ± 0.45 μg m^-3), and Mg²⁺ (0.09 ± 0.15 μg m^-3). Seasonal variations of PM_2.5 showed the highest average value in spring, followed by winter, fall, and summer. Meanwhile, the formation mechanisms of the major PM_2.5 species (NO₃^-, SO₄^2-, and OM) varied in seasons. Interestingly, NO₂ may have the highest conversion rate to NO₃^- in spring, which might be linked with the nighttime chemistry due to the high relative humidity. Moreover, OM in summer was mainly produced by the daytime oxidation of volatile organic compounds, while local primary organic aerosols might play a significant role in other seasons. Source apportionment showed that the more-aged PM_2.5 contributed significantly to the PM_2.5 mass (42%), followed by the dust-related PM_2.5 (38%) and the less-aged PM_2.5 (21%). Potential contribution source function (PSCF) results indicated that aged PM_2.5 were less affected by transportation than dust-related PM_2.5.

Seasonal variations and potential sources of biomass burning tracers in particulate matter in Nanjing aerosols during 2017-2018

Biomass burning (BB) is an important source of atmospheric particulate matter and can adversely affect air quality, visibility, human health, and climate change. To study the characteristics and potential source regions of BB tracers in PM_2.5, a liquid chromatography-mass spectrometry instrument (HPLC-MS/MS) is applied in this study to develop and validate a method to determine organic tracers of BB in 397 aerosol samples. The total mean concentrations of 17 tracers measured in 2017 and 2018 were 333.32 ng m^-3 and 243.45 ng m^-3, respectively. Among them, the concentration of levoglucosan was the highest among all the tracers, with 325.63 ng m^-3 in 2017 and 237.47 ng m^-3 in 2018. The BB tracers showed obvious seasonal variations characteristics, most of which were abundant in winter. However, the concentrations of 3,4-dimethoxyacetic acid and sinapinic acid were higher in summer and spring than that in the other seasons. There were obvious differences in the Potential Source Contribution Factor (PSCF) model results of the BB's potential source area annually and in different seasons. The results of the potential source analysis showed that Beijing-Tianjin-Hebei had a great impact on the Nanjing air quality in 2017. Finally, five source factors for BB were identified based on the Positive Matrix Factor (PMF) model, and these were cellulose, hardwood, softwood, grass, and secondary formed. During the 2 years, cellulose was the largest contributor to biomass burning. Owing to the different fire conditions each year, the contribution of the five factors to the BB tracers was also different. For example, the contribution of softwood to the BB tracers was greater in 2018 (8.4%) than in 2017 (5.2%), while the contributions of hardwood and cellulose did not change significantly.

Seven-year study of monsoonal rainwater chemistry over the mid-Brahmaputra plain, India: assessment of trends and source regions of soluble ions

This work is a 7-year study of monsoonal rainwater chemistry (n = 302), over mid-Brahmaputra plain during 2012 to 2018. The samples were analyzed for major chemical parameters viz. pH, electrical conductivity (EC), and ions (SO₄^2-, NO₃^-, Br^-, Cl^-, F^-, Mg²⁺, Ca²⁺, K⁺, NH₄⁺, Na⁺, and Li⁺) to assess the chemistry. The mean pH of rainwater varied among the years, which was maximum in 2018 (6.18 ± 0.72) and minimum in the year 2014 (5.39 ± 0.54), and the variations were significant at p < 0.0001. Ridgeline plots were drawn to visualize interannual variations, which revealed that Ca²⁺ was the dominant cation in the early years, whereas NH₄⁺ prevailed in the latter years. Mann-Kendall analysis and Sen's slope statistical tests were employed, and it was found that all the ions showed positive S values indicating increasing trends. Enrichment factors (EF) of K⁺, SO₄^2-, and NO₃^- were found to be high with respect to both soil and seawater suggesting the influence of emissions from fossil fuel and biomass burning in the chemistry of rainwater. Principal component analysis (PCA) was applied to identify the sources of rain constituents, and five factors were obtained explaining crustal dust, biomass burning, fossil fuel combustion, agricultural emissions, and coal burning as possible sources. Airmass back trajectory clusters and Potential Source Contribution Function (PSCF) were computed by application of HYbrid Single-Particle Lagrangian Integrated Trajectory model to appreciate the terrestrial influence on the chemistry. The results indicated inputs from both local and regional dust and anthropogenic constituents that influenced the monsoonal rainwater chemistry over Brahmaputra Valley.

Study on the Spatial and Temporal Distribution Characteristics and Influencing Factors of Particulate Matter Pollution in Coal Production Cities in China

In recent years, with the continuous advancement of China's urbanization process, regional atmospheric environmental problems have become increasingly prominent. We selected 12 cities as study areas to explore the spatial and temporal distribution characteristics of atmospheric particulate matter in the region, and analyzed the impact of socioeconomic and natural factors on local particulate matter levels. In terms of time variation, the particulate matter in the study area showed an annual change trend of first rising and then falling, a monthly change trend of "U" shape, and an hourly change trend of double-peak and double-valley distribution. Spatially, the concentration of particulate matter in the central and southern cities of the study area is higher, while the pollution in the western region is lighter. In terms of social economy, PM_2.5 showed an "inverted U-shaped" quadratic polynomial relationship with Second Industry and Population Density, while it showed a U-shaped relationship with Generating Capacity and Coal Output. The results of correlation analysis showed that PM_2.5 and PM₁₀ were significantly positively correlated with NO₂, SO₂, CO and air pressure, and significantly negatively correlated with O₃ and air temperature. Wind speed was significantly negatively correlated with PM_2.5, and significantly positively correlated with PM₁₀. In terms of pollution transmission, the southwest area of Taiyuan City is a high potential pollution source area of fine particles, and the long-distance transport of PM_2.5 in Xinjiang from the northwest also has a certain contribution to the pollution of fine particles. This study is helpful for us to understand the characteristics and influencing factors of particulate matter pollution in coal production cities.

Per- and polyfluoroalkyl substances in the atmospheric total suspended particles in Karachi, Pakistan: Profiles, potential sources, and daily intake estimates

Per- and polyfluoroalkyl substances (PFAS) have received continuous attention; however, there is limited understanding of their sources in the atmosphere and related human exposure risks. This study measured PFAS in the atmospheric total suspended particles collected from Karachi, Pakistan, during the winter. Among the quantified PFAS, perfluorobutanoic acid (PFBA) showed the highest average concentration (3.11 ± 2.64 pg/m³), accounting for 32% of the total PFAS. Wind speed was positively correlated with perfluorohexanoic acid (PFHxA) and N-ethyl perfluorooctanesulfonamide (N-EtFOSA), while relative humidity was negatively correlated with perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA). Weighted potential source contribution function (WPSCF) and concentration weighted trajectory (WCWT) analyses suggested that northwestern Pakistan and western Afghanistan areas were highly associated with the long-range atmospheric transport of PFAS. We also calculated the daily intake of PFAS via inhalation, which were in the range of 0.07-3.98 and 0.01-0.33 pg/kg bw/d for children and adults, respectively. The calculated hazard quotient (HQ) of PFOS and PFOA was significantly lower than 1, indicating less or unlikely to cause non-carcinogenic effect via inhalation exposure. Overall, this study contributes to the understanding of geographic origins and human inhalation risks of airborne PFAS on a regional scale.

Transport routes and potential source areas of PM10 in Kirklareli, Turkey

In this study, the seasonal variation, transport routes, and potential source areas of PM₁₀ in the central district of Kirklareli (Turkey) were investigated. It was determined that PM₁₀ concentrations had the highest seasonal average value in autumn and the lowest seasonal average value in spring. Cumulative distributions of PM₁₀ concentrations data set were examined. In order to determine the air mass source and transport routes, the backward trajectories of the air masses obtained by using the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model were run and cluster analysis, which is one of the multivariate statistical analyses, was performed. Cluster analysis results revealed that there are five main clusters affecting the receptor site in all four seasons. By defining the PM₁₀ concentrations data as an input to the potential source contribution function (PSCF) model, the probable locations of potential source areas were identified. It has been observed that there are obvious seasonal differences in the potential source areas of PM₁₀. High PSCF values were observed especially in Greece and the Mediterranean during the winter and especially in Albania and Greece during the spring. While high PSCF values were observed especially in the Anatolian side of Istanbul, Kocaeli, Sakarya, and the Black Sea coasts of these regions during the summer, they were observed especially in İzmir and Balikesir during the autumn.

Spatial Characteristics and Regional Transmission Analysis of PM2.5 Pollution in Northeast China, 2016-2020

Northeast China is an essential industrial development base in China and the regional air quality is severely affected by PM_2.5 pollution. In this paper, spatial autocorrelation, trajectory clustering, hotspot analysis, PSCF and CWT analysis are used to explore the spatial pollution characteristics of PM_2.5 and determine the atmospheric regional transmission pattern for 40 cities in Northeast China from 2016 to 2020. Analysis of PM_2.5 concentration characteristics in the northeast indicates that the annual average value and total exceedance days of PM_2.5 concentration in Northeast China showed a U-shaped change, with the lowest annual average PM_2.5 concentration (31 μg/m³) in 2018, decreasing by 12.1% year-on-year, and the hourly PM_2.5 concentration exploding during the epidemic lockdown period in 2020. A stable PM_2.5 pollution band emerges spatially from the southwest to Northeast China. Spatially, the PM_2.5 in Northeast China has a high degree of autocorrelation and a south-hot-north-cool characteristic, with all hotspots concentrated in the most polluted Liaoning province, which exhibits the H-H cluster pattern and hotspot per year. Analysis of the air mass trajectories, potential source contributions and concentration weight trajectories in Northeast China indicates that more than 74% of the air mass trajectories were transmitted to each other between the three heavily polluted cities, with the highest mean value of PM_2.5 pollution trajectories reaching 222.4 μg/m³, and the contribution of daily average PM_2.5 concentrations exceeding 60 μg/m³ within Northeast China. Pollution of PM_2.5 throughout the Northeast is mainly influenced by short-range intra-regional transport_, with long-range transport between regions also being an essential factor; organized integration is the only fundamental solution to air pollution.

Fine particle-bound PAHs derivatives at mountain background site (Mount Tai) of the North China: Concentration, source diagnosis and health risk assessment

Ten nitrated polycyclic aromatic hydrocarbons (nPAHs) and 4 oxygenated polycyclic aromatic hydrocarbons (oPAHs) in fine particulate matter (PM_2.5) samples from Mount Tai were analyzed during summer (June to August), 2015. During the observation campaign, the mean concentration of total nPAHs and oPAHs was 31.62 pg/m³ and 0.15 ng/m³, respectively. Two of the monitored compounds, namely 9-nitro-anthracene (9N-ANT) (6.86 pg/m³) and 9-fluorenone (9FO) (0.05 ng/m³) were the predominant compounds of nPAHs and oPAHs, respectively. The potential source and long-range transportation of nPAHs and oPAHs were investigated by the positive matrix factorization (PMF) method and the potential source contribution function (PSCF) methods. The results revealed that biomass/coal burning, gasoline vehicle emission, diesel vehicle emission and secondary formation were the dominant sources of nPAHs and oPAHs, which were mainly from Henan province and Beijing-Tianjin-Hebei region and Bohai sea. The incremental life cancer risk (ILCR) values were calculated to evaluate the exposure risk of nPAHs and oPAHs for three group people (infant, children and adult), and the values of ILCR were 7.02 × 10^-10, 3.49 × 10^-9 and 1.41 × 10^-8 for infant, children and adults, respectively. All these values were lower than the standard of EPA (Environmental Protection Agency) (<10^-6), indicating acceptable health risk of nPAHs and oPAHs.

Environmental implications of reduced electricity consumption in Wuhan during COVID-19 outbreak: A brief study

Due to the COVID-19 outbreak, Wuhan was locked down from 23 January 2020 to 8 April 2020, a total of 76 days. It is well known that the electricity consumption is a direct reflection of human activity. During the lockdown of Wuhan, most of human activities were forbidden. The reduction in human activity would inevitably lead to a reduction in electricity consumption. At the same time, anthropogenic emissions of air pollutants would also be reduced with the reduction of human activity. In this study, the correlation between electricity consumption and air pollutants during lockdown was discussed in detail. The result showed that the drop in pollutants concentrations in January should be attributed to the washout effect of rainfall rather than the lockdown. The decrease of electricity consumption in the secondary industry might play a significant role on the decrease of PM 2.5 and NO₂ concentrations in Wuhan in February 2020. The decrease in NO₂ concentration in March should be attributed to the reduction of pollutants emissions from the tertiary industry, which means that more attention should be paid to the control of NO₂ emission in the tertiary industry. Due to reduced emissions from local sources, the role of long-range transport sources might be more significant during the lockdown of Wuhan. By PSCF analysis, southeast of Wuhan could be the major potential emission sources of PM 2.5 , especially in the northern part of Jiangxi province. It was suggested that stricter regulation of pollutants emissions should be implemented in this area.

Severe haze events in the Indo-Gangetic Plain during post-monsoon: Synergetic effect of synoptic meteorology and crop residue burning emission

In recent years, the frequent occurrence of haze events in the Indo-Gangetic Plain (IGP) during crop residue burning period has caused a serious reduction in atmospheric visibility and deteriorated air quality. The present study is carried out to investigate the haze event observed in IGP in Nov 2017 using ground-based observations, satellite data and synoptic meteorology to understand the possible factors responsible for haze formation. PM_2.5 (particulate matter with aerodynamic diameter ≤ 2.5 μm) concentrations and Air Quality Index (AQI) at two sites (Agra and Delhi) situated in the central Indo-Gangetic Plain (CIGP) showed a sudden increase in PM_2.5 concentrations and deteriorated air quality during 7-14 Nov. To monitor the variation of particulate matter (PM) in IGP, PM_2.5 and PM₁₀ (particulate matter with aerodynamic diameter ≤ 10 μm) concentrations were monitored at 22 stations in 12 cities of IGP during 1-15 Nov which also showed an increase in PM concentrations during haze event (7-14 Nov). Crop residue burning activities in north-west Indo-Gangetic Plain (NW-IGP) were observed during haze event. Synoptic weather conditions of IGP identified using geopotential height and wind at 700 hPa showed high-pressure systems and low winds in IGP favoring stagnant conditions during haze event. A detailed analysis of the variation of pollutants and meteorology was carried out at Agra. Ozone (O₃), carbon monoxide (CO), sulphur dioxide (SO₂) and nitrogen oxides (NO_x) showed higher concentrations during haze event along with lower temperature, low wind speed and high relative humidity. Aerosol ionic composition showed a higher contribution (~84%) of Cl^-, NO₃^-, SO₄^2- and NH₄⁺ to total soluble ions suggesting secondary aerosol formation during haze event.

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.

A seriously air pollution area affected by anthropogenic in the central China: temporal-spatial distribution and potential sources

This study used the officially released data by the Chinese air quality monitoring network to analyze the pollution characteristics of six air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃) for 29 cities in the Central Plains Economic Zone (CPEZ; China) in 2015. During 2015, serious particulate matter (PM) pollution often occurred, and the concentrations of PM_2.5 and PM₁₀ were 77 μg m^-3 and 128 μg m^-3, respectively. Air pollutants were at higher concentrations in the northern cities than those in the southern region of the CPEZ, and the correlation among the cities indicated that there was regional pollution in CPEZ. Generally, PM, SO₂, NO₂, and CO showed similar seasonal characteristics and the highest and lowest concentrations appeared in winter and summer, respectively. In addition, we used the HYSPLIT model and trajStat model to identify the potential source contribution function and concentration-weighted trajectory of Zhengzhou, the central city of CPEZ. More serious air pollution occurred when air masses were transported from the west of the CPEZ. Shaanxi Province, Hubei Province, Anhui Province and the northwest of the CPEZ were found to be the main exogenous sources of total PM with contributions of > 100 μg m^-3 PM_2.5 and > 180 μg m^-3 PM₁₀. Therefore, the concentrations of PM in 2015 at Zhengzhou were probably influenced by both long-distance transmission and local emissions.

Source-resolved attribution of ground-level ozone formation potential from VOC emissions in Metropolitan Vancouver, BC

The common regulatory approach for managing ground-level ozone (O₃) formation is based upon reducing the emission of total VOC in VOC limited regions, and the emission of NO_x in NO_x limited regions. However, the characteristic VOC species emitted from different sources are of different ozone formation potentials (OFP). Without an in-depth understanding of the relative OFP contributions from specific sources, the effectiveness of the existing approach for controlling ground-level O₃ at the regional scale is limited. This study collected and analyzed five years (2012-2016) of monitoring data for 56 most photochemically reactive VOC species at Port Moody, an industrial city in Metro Vancouver, Canada that has experienced elevated O₃ levels in its ambience. Source-specific contributions to OFP were quantified for major VOC emitters to deliberate the underlying causes of elevated O₃ recently observed in this populated region. Six sources were identified using the positive matrix factorization (PMF) model, consisting of fuel production and combustion, fuel evaporation, vehicle exhaust, industrial coatings/solvents, petrochemical source, and other industrial emission. Although the top three contributors to total VOCs are fuel production and combustion (34.5%), fuel evaporation (21.4%), and vehicle exhaust (20.6%), the top three contributors to OFP are fuel production and combustion (27.1%), vehicle exhaust (23.7%), and industrial coatings/solvents (17.2%). Additionally, potential source contribution function (PSCF) analysis was conducted to generate the geographical distribution of VOC and OFP sources in different seasons. The results revealed that, in the Metro Vancouver area, the OFP hotspots have been significantly different from the VOC emission hotspots. In general, regional sources, especially those located in the northeastern direction of Metro Vancouver, have greater influence on the VOCs levels. However, OFP has been predominantly affected by transportation and industrial sources at the local scale. Therefore, to formulate effective strategies for reducing ground-level O₃, the seasonal and spatial variations of major OFP sources should be assessed by the regulatory authorities.

Background concentrations of benzene, potential long range transport influences and corresponding cancer risk in four cities of central Europe, in relation to air mass origination

Benzene concentrations covering the three year period 2015-2017, were derived from four background monitoring stations located in Berlin (Germany), Budapest (Hungary), Mons (Belgium) and Torino (Italy), in order to calculate the corresponding Incremental Lifetime Cancer Risk (ILCR) of an average adult, associated with the inhalation of benzene. In addition, a cluster analysis of backward air mass trajectories was coupled with Potential Source Contribution Function (PSCF) model aiming to identify possible exogenous source regions of benzene affecting the four cities and also to allocate the ILCR in atmospheric circulation patterns. A potential health risk (ILCR>10^-6) from benzene exposure was estimated in all four cities. In Berlin and Mons, an enhanced fraction of the ILCR was associated with Southeast short range trajectories of slow moving air masses, which were also related to extreme long range transport episodes. Furthermore, increased benzene concentrations in Budapest were observed during the prevalence of short range Southwest airflows, whilst PSCF model isolated the transboundary emission sources in the industrialized North Italy. Long range trajectories of fast moving marine air masses from North Atlantic, not influenced by anthropogenic emissions, improved the benzene related air quality in Berlin and Mons due to dispersion. No long range transport effects were confirmed in Torino.

Dual-modelling-based source apportionment of NOx in five Chinese megacities: Providing the isotopic footprint from 2013 to 2014

In China, nitrate (NO₃^-) becomes the main contributor to fine particles (PM_2.5) because the emissions of its precursor, nitrogen oxides (NO_x), were not recognized and controlled well in recent years. In this work, sources, conversion, and geographical origin of NO_x were interpreted combining the isotopic information (δ¹⁵N and δ¹⁸O) of NO₃^- and dual modelling at five Chinese megacities (Beijing, Shanghai, Guangzhou, Wuhan and Chengdu) during 2013-2014. Results showed that the δ¹⁵N-NO₃^- values (n = 512) ranged from -12.3‰ to +22.9‰, and the average δ¹⁸O-NO₃^- value was +83.4‰ ± 17.2‰. The isotopic compositions both had a rising tendency as ambient temperature dropped, attributing largely to the source changes. Bayesian model indicated the percentage for the OH pathway of NO_x conversion had a clear seasonal variation with a higher value during summer (58.0% ± 9.82%) and a lower value during winter (11.1% ± 3.99%); it was also significantly correlated with latitude (p < 0.01). Coal combustion was the most important source of NO_x (31.1%-41.0%), which was geographically derived from North China and other south-central developed regions implied by Potential Source Contribution Function (PSCF). Apart from Chengdu, mobile sources was the second largest contributor to NO_x. This source was extensive but uniformly distributed all around the typical urban agglomerations of China. Biomass burning and microbial processes shared similar source areas, mostly originating from the North China Plain and Sichuan Basin. Based on the NO_x features, we infer that residential coal combustion was the primary source of heavy PM_2.5 pollution in Chinese megacities. Controlling the source categories of these regional priorities would help mitigate atmospheric pollution in these areas.

Black carbon in Xiamen, China: Temporal variations, transport pathways and impacts of synoptic circulation

Black carbon (BC) plays a vital role in atmospheric environment and climate change. Temporal variations and transport pathways of BC in Xiamen, China with the impacts of synoptic circulation were investigated in 2014 with Aethalometer. Annual mean BC concentration was 4270 ng m^-3. BC exhibited clear diurnal (seasonal) variations, with the maximum of 6182 (4755) ng m^-3 at 6:00 (in spring) and minimum of 2847 (3774) ng m^-3 at 13:00 (in summer). Conditional probability function analysis indicated that high BC concentrations were associated with northwesterly winds with low wind speed. Air masses originating from the East China Sea and passing along with East China Coast had the highest BC concentrations. Potential source contribution function and concentration weighted trajectory analysis suggested that major sources for BC included the surrounding region, southwestern Fujian and eastern Guangdong to the southwest, Hubei, Hunan and Jiangxi to the northwest, the East China Sea and the South China Sea. Of the nine synoptic circulation patterns, three cyclone-related patterns were associated with low BC concentrations and small biomass burning (BC_bb) contributions. Of the six anticyclone-related patterns, the three cold-high circulations around winter were associated with moderate BC concentrations and large BC_bb contributions. The two cold-high patterns in spring and autumn were associated with high BC concentrations and small BC_bb contributions, while the warm-high pattern was associated with moderate BC concentration and small BC_bb contribution. The findings provide insights into the transport mechanisms of BC with the impacts of synoptic pattern in China.

Potential source regions of air pollutants at a regional background station in Northern China

Understanding the potential source regions of air pollutants and their relative contribution from surrounding areas are of great importance for air pollution control strategies in Northern China. Six years of measurement of air pollutants was conducted from 2005 to 2010 in Shangdianzi (SDZ) regional background station. During the study period, the annual average concentrations of sulfur dioxide (SO₂), carbon monoxide (CO), nitrogen dioxide and ozone (O_x), and fine particle matter less than or equal to 2.5 μm (PM_2.5) range from 15.7 to 20.0 μg/m³, 577.7 to 856.0 μg/m³, 90.4 to 101.8 μg/m₃, and 39.8 to 62.4 μg/m³, respectively. In this work, Potential Source Contribution Function (PSCF) and Trajectory Sector Analysis (TSA) methods are applied to identify locations of sources and their relatively contribution of air pollutants at SDZ. PSCF analysis shows that central Inner Mongolia, north Shanxi, west and south Hebei, and west Liaoning are all potential sources of SO₂. The North China Plain (NCP) region, especially south Hebei and north Shandong, are major potential source regions for CO, O_x, and PM_2.5. Therefore, reducing anthropogenic emissions from the coal industry, biomass burning, agricultural activities, and vehicles in these areas could be an effective way of controlling air pollution at SDZ. Based on the TSA results, the contributions of SO₂, CO, O_x, and PM_2.5 from long-distance transport are 5.5 μg/m³, 301.4 μg/m³, 14.8 μg/m³, and 25.8 μg/m³, accounting for approximately 22.6%, 32.3%, 13.1%, and 37.5% of the respective air pollutant concentrations at SDZ.

Seasonal variations of NPAHs and OPAHs in PM2.5 at heavily polluted urban and suburban sites in North China: Concentrations, molecular compositions, cancer risk assessments and sources

16 nitrated polycyclic aromatic hydrocarbons (NPAHs) and 5 oxygenated polycyclic aromatic hydrocarbons (OPAHs) in PM_2.5 at two locations in Northern China were analyzed by Gas Chromatography-Mass Spectrometry (GC-MS). Sampling was conducted at an urban site in Shandong University in Jinan (SDU) and a suburban site in Qixingtai in Jinan (QXT) in March, June, September and December in 2016. Overall, the concentrations of NPAHs and OPAHs were higher at SDU (1.88 and 9.49 ng/m³, respectively) than QXT (1.57 and 6.90 ng/m³, respectively), and the NPAHs and OPAHs concentrations were significantly higher during the winter than the other seasons at both sites. The incremental lifetime cancer risk (ILCR) values were lower than 10^-6 for all sites, seasons and age groups (ranging between 1.85E-08 and 2.56E-07), so there was no risk of carcinogenesis due to exposure to these pollutants. Total cancer risk at SDU was higher than QXT and NPAHs have the highest carcinogenic risk for adults aged from 30 to 70 years. The positive matrix factorization (PMF) results revealed that coal/biomass combustion, diesel vehicle emissions, gasoline vehicle emissions and secondary formation were the main sources of NPAHs and OPAHs at SDU and QXT. Coal/biomass combustion contributed more in spring, autumn and winter; diesel vehicle emission contributed the most in summer; secondary formation made greatest contributions in winter; the contributions of gasoline vehicle emission were similar in summer, autumn and winter. Diagnostic ratios clearly demonstrated that secondary formation is more active in winter than in other seasons, and the reactions of PAHs and OH radical were the dominant secondary formation pathway at both SDU and QXT. In addition, the potential source contribution function (PSCF) identified that the Beijing-Tianjin-Hebei region, Shandong province, Bohai Sea, Yellow Sea, Anhui province and Henan province were the main source regions of NPAHs and OPAHs in Jinan.

VOC characteristics, sources and contributions to SOA formation during haze events in Wuhan, Central China

Based on detailed data on 102 volatile organic compounds (VOCs) measured continuously from 2016.10.9 to 2016.11.17 in Wuhan, the VOC characteristics, secondary organic aerosol (SOA) characteristics, SOA formation potential (SOAP), potential source regions, sources and contributions during different haze episodes were analyzed. The total VOC (TVOC) concentrations on clear days (visibility >10 km), slight haze days (visibility of 5-10 km), and severe haze days (visibility <5 km) were 34.87 ± 14.89 ppbv, 45.06 ± 26.69 ppbv, and 49.55 ± 24.82 ppbv, respectively. The SOAP on haze days (447.04 ± 253.85 ppbv) was significantly higher than that on clear days (300.62 ± 138.48 ppbv), and aromatics were the dominant contributors to SOA formation under different visibility conditions, accounting for approximately 97% of the total SOAP. The ratio of ethylbenzene to m/p-xylene (E/X) indicated that atmospheric photochemical reactions were slightly stronger on haze days. The ratio of toluene to benzene (T/B) indicated that vehicle exhaust had significant effects on VOCs, but no significant changes occurred during different haze episodes. The ratio of benzene, toluene, ethylbenzene and xylenes (BTEX) to CO indicated that VOCs from solvent usage in painting/coating and industrial emissions increased with increasing haze pollution. Based on backward trajectories and the potential source contribution function (PSCF), short-distance transport was the main source influencing VOC pollution, especially transport from the southwest. Seven sources were identified by positive matrix factorization (PMF): industrial sources, vehicular exhaust, solvent usage in painting/coating, fuel evaporation, liquefied petroleum gas (LPG) usage, biogenic sources and biomass burning. Moreover, solvent usage in painting/coating, vehicle exhaust and LPG usage were the most important sources that significantly aggravated VOC pollution during haze events. The results can provide references for local governments developing control strategies of VOCs during haze pollution events.

Temporal variations and potential sources of organophosphate esters in PM2.5 in Xinxiang, North China

We monitored the concentrations of 10 organophosphate esters (OPEs) in 52 fine particulate matter (PM_2.5) samples in Xinxiang, Henan Province, North China, in 2015. During the sampling period, the OPE concentrations in most samples (n = 47) differed minimally and were relatively stable (mean: 2.02 ± 0.93 ng m^-3), although several samples (n = 5) had high total OPE (Ʃ₁₀OPE) concentrations (mean: 9.99 ± 5.69 ng m^-3), which may have been influenced by high PM_2.5 levels. Meanwhile, some samples had high PM_2.5 concentrations but low Ʃ₁₀OPE concentrations (i.e. low OPE/PM_2.5 ratios) or low PM_2.5 concentrations but high Ʃ₁₀OPE concentrations, which might have been influenced by air mass sources. Therefore, we assessed air mass sources using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and wind direction frequency data, and subsequently analysed PM_2.5 and OPE sources using a potential source contribution function (PSCF) model. The results revealed that air mass sources couldn't represent the source of specific pollutants, including PM_2.5 and OPEs. Generally, both PM_2.5 and OPEs were from Henan and Shandong Provinces; however, the major source areas differed, which may have resulted from diverse pollution characteristics in various source areas. The principal component analysis and PSCF results revealed that the 10 OPEs could be segmented into three groups, which were associated with different source areas. These results suggested that pollution characteristics of contaminants in source areas should be considered in source apportionment.

Insight into the critical factors determining the particle number concentrations during summer at a megacity in China

To identify the critical factors impacting the number concentration of particles with the aerodynamic diameters less than 2.5μm (PNC_2.5), the continuous measurement of PNC_2.5, chemical components in PM_2.5, gaseous pollutants and meteorological conditions were conducted at an urban site in Tianjin in June 2015. Results indicated that the average PNC_2.5 was 2839±2430 dN/dlogDp 1/cm³ during the campaign. Compared to other meteorological parameters, the relative humidity (RH) had the strongest relationship with PNC_2.5, with a Pearson's correlation coefficient of 0.53, and RH larger than 30% influenced strongly PNC_2.5. The important influence of secondary reactions on PNC_2.5 was inferred due to higher correlation coefficients between PNC_2.5 and SO₄^2-, NO₃^-, NH₄⁺ (r=0.78-0.89; p<0.01) and between PNC_2.5 and ratios that represent the conversion of nitrogen and sulfur oxides to particulate matter (r=0.42-0.49; p<0.01). Under specific RH conditions, there were even stronger correlations between PNC_2.5 and NO₃^-, SO₄^2-, NH₄⁺, while those between PNC_2.5 and EC, OC were relatively weak, especially when RH exceeded 50%. Principal component analysis (PCA) and Pearson's correlation analysis indicated that secondary sources, vehicle emission and coal combustion might be major contributors to PNC_2.5. Backward trajectory and potential source contribution function (PSCF) analysis suggested that the transport of air masses originated from these regions around Tianjin (Liaoning, Hebei, Shandong and Jiangsu) influenced critically PNC_2.5. The north of Jiangsu, the west of Shandong, and the east of Hebei were distinguished as major potential source-areas of PNC_2.5 by PSCF model.

Chemical composition and sources of PM1 and PM2.5 in Beijing in autumn

Beijing, the capital of China, suffers from severe atmospheric aerosol pollution; nevertheless, a comprehensive study of the constituents and sources of PM₁ is still lacking, and the differences between PM₁ and PM_2.5 are still unclear. In this study, an intensive observation was conducted to reveal the pollution characteristics of PM₁ and PM_2.5 in Beijing in autumn. Positive matrix factorization (PMF), backward trajectories and a potential source contribution function (PSCF) model were used to identify the source categories and source areas of PM₁ and PM_2.5. The results showed that the average concentrations of PM₁ and PM_2.5 reached 78.20μg/m³ and 95.47μg/m³ during the study period, respectively. PM₁ contributed greatly to PM_2.5. The PM₁/PM_2.5 value increased from 73.6% to 90.1% with PM₁ concentration growing from <50μg/m³ to >150μg/m³. Higher secondary inorganic aerosol (SIA) proportions (31.3%-70.8%) were found in PM₁. The higher fraction of SIA, OC, EC and typical elements in PM₁ illustrated that anthropogenic components accumulated more in smaller size particles. Three typical weather patterns causing the heavy pollution in autumn were found as follows: (1) Siberian high and uniform high pressure field, (2) cold front and low-voltage system, and (3) uniform low pressure field. A PMF analysis indicated that secondary aerosols and coal combustion, vehicle, industry, biomass burning, and dust were the important sources of PM, accounting for 53.8%, 8.0%, 13.0%, 13.2% and 12.0% of PM₁, respectively, and for 47.5%, 9.9%, 12.4%, 8.4% and 21.8% of PM_2.5, respectively. The HYSPLIT and chemical components analysis indicated the potential contribution from biomass burning and fertilization ammonia emissions to PM₁ in autumn. The source areas were similar for PM₁ and PM_1-2.5 under general polluted conditions, but during the heavily polluted periods, the source areas were distributed in farther regions from Beijing for PM₁ than for PM_1-2.5.

Sources and geographic origin of particulate matter in urban areas of the Danube macro-region: The cases of Zagreb (Croatia), Budapest (Hungary) and Sofia (Bulgaria)

The contribution of main PM pollution sources and their geographic origin in three urban sites of the Danube macro-region (Zagreb, Budapest and Sofia) were determined by combining receptor and Lagrangian models. The source contribution estimates were obtained with the Positive Matrix Factorization (PMF) receptor model and the results were further examined using local wind data and backward trajectories obtained with FLEXPART. Potential Source Contribution Function (PSCF) analysis was applied to identify the geographical source areas for the PM sources subject to long-range transport. Gas-to-particle transformation processes and primary emissions from biomass burning are the most important contributors to PM in the studied sites followed by re-suspension of soil (crustal material) and traffic. These four sources can be considered typical of the Danube macro-region because they were identified in all the studied locations. Long-range transport was observed of: a) sulphate-enriched aged aerosols, deriving from SO₂ emissions in combustion processes in the Balkans and Eastern Europe and b) dust from the Saharan and Karakum deserts. The study highlights that PM pollution in the studied urban areas of the Danube macro-region is the result of both local sources and long-range transport from both EU and no-EU areas.

Seasonal variation and potential source regions of PM2.5-bound PAHs in the megacity Beijing, China: Impact of regional transport

Based on the 12-hour PM_2.5 samples collected in an urban site of Beijing, sixteen PM_2.5-bound Polycyclic Aromatic Hydrocarbons (PAHs) were measured to investigate the characteristics and potential source regions of particulate PAHs in Beijing. The study period included the summer period in July-August 2014, the APEC source control period during the Asia-Pacific Economic Cooperation (APEC) meeting in the first half of November 2014, and the heating period in the second half of November 2014. Compared to PM_2.5, sum of 16 PM_2.5-bound PAHs exhibited more significant seasonal variation with the winter concentration largely exceeding the summer concentration. Temperature appeared to be the most crucial meteorological factor during the summer and heating periods, while PM_2.5-bound PAHs showed stronger correlation with relative humidity and wind speed during the APEC source control period. Residential heating significantly increased the concentrations of higher-ring-number (≥4) PAHs measured in PM_2.5 fraction. Potential source contribution function (PSCF) and concentration weighted trajectory (CWT) analysis as well as the (3 + 4) ring/(5 + 6) ring PAH ratio analysis revealed the seasonal difference in the potential source area of PM_2.5-bound PAHs in Beijing. Southern Hebei was the most likely potential source area in the cold season. Using black carbon (BC) and carbon monoxide (CO) as the PAH tracers, regional residential, transportation and industry emissions all contributed to the PAH pollution in Beijing.

Identification of long-range transport pathways and potential sources of PM2.5 and PM10 in Beijing from 2014 to 2015

Trajectory clustering, potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) methods were applied to investigate the transport pathways and identify potential sources of PM_2.5 and PM₁₀ in different seasons from June 2014 to May 2015 in Beijing. The cluster analyses showed that Beijing was affected by trajectories from the south and southeast in summer and autumn. In winter and spring, Beijing was not only affected by the trajectories from the south and southeast, but was also affected by trajectories from the north and northwest. In addition, the analyses of the pressure profile of backward trajectories showed that backward trajectories, which have important influence on Beijing, were mainly distributed above 970hPa in summer and autumn and below 950hPa in spring and winter. This indicates that PM_2.5 and PM₁₀ were strongly affected by the near surface air masses in summer and autumn and by high altitude air masses in winter and spring. Results of PSCF and CWT analyses showed that the largest potential source areas were identified in spring, followed by winter and autumn, then summer. In addition, potential source regions of PM₁₀ were similar to those of PM_2.5. There were a clear seasonal and spatial variation of the potential source areas of Beijing and the airflow in the horizontal and vertical directions. Therefore, more effective regional emission reduction measures in Beijing's surrounding provinces should be implemented to reduce emissions of regional sources in different seasons.

Chemical characteristics and source apportionment of PM2.5 using PCA/APCS, UNMIX, and PMF at an urban site of Delhi, India

The present study investigated the comprehensive chemical composition [organic carbon (OC), elemental carbon (EC), water-soluble inorganic ionic components (WSICs), and major & trace elements] of particulate matter (PM_2.5) and scrutinized their emission sources for urban region of Delhi. The 135 PM_2.5 samples were collected from January 2013 to December 2014 and analyzed for chemical constituents for source apportionment study. The average concentration of PM_2.5 was recorded as 121.9 ± 93.2 μg m^-3 (range 25.1-429.8 μg m^-3), whereas the total concentration of trace elements (Na, Ca, Mg, Al, S, Cl, K, Cr, Si, Ti, As, Br, Pb, Fe, Zn, and Mn) was accounted for ∼17% of PM_2.5. Strong seasonal variation was observed in PM_2.5 mass concentration and its chemical composition with maxima during winter and minima during monsoon seasons. The chemical composition of the PM_2.5 was reconstructed using IMPROVE equation, which was observed to be in good agreement with the gravimetric mass. Source apportionment of PM_2.5 was carried out using the following three different receptor models: principal component analysis with absolute principal component scores (PCA/APCS), which identified five major sources; UNMIX which identified four major sources; and positive matrix factorization (PMF), which explored seven major sources. The applied models were able to identify the major sources contributing to the PM_2.5 and re-confirmed that secondary aerosols (SAs), soil/road dust (SD), vehicular emissions (VEs), biomass burning (BB), fossil fuel combustion (FFC), and industrial emission (IE) were dominant contributors to PM_2.5 in Delhi. The influences of local and regional sources were also explored using 5-day backward air mass trajectory analysis, cluster analysis, and potential source contribution function (PSCF). Cluster and PSCF results indicated that local as well as long-transported PM_2.5 from the north-west India and Pakistan were mostly pertinent.

Long-range and regional transported size-resolved atmospheric aerosols during summertime in urban Shanghai

In this study, the concentrations of water soluble ions (WSI), organic carbon (OC), and elemental carbon (EC) of size-resolved (0.056-18μm) atmospheric aerosols were measured in July and August 2015 in Shanghai, China. Backward trajectory model and potential source contribution function (PSCF) model were used to identify the potential source distributions of size-resolved particles and PM_1.8-associated atmospheric inorganic and carbonaceous aerosols. The results showed that the average mass concentrations of PM_0.1, PM₁, and PM_1.8 were 21.21, 82.90, and 100.1μgm^-3 in July and 7.00, 29.21, and 35.10μgm^-3 in August, respectively, indicating that the particulate matter pollution was more serious in July than in August in this study due to the strong dependence of the aerosol species on the air mass origins. The trajectory cluster analysis revealed that the air masses originated from heavily industrialized areas including the Pearl River Delta (PRD) region, the Yangtze River Delta (YRD) region and the Beijing-Tianjin region were characterised with high OC and SO₄^2- loadings. The results of PSCF showed that the pollution in July was mainly influenced by long-range transport while it was mainly associated to local and intra-regional transport in August. Besides the contributions of anthropogenic sources from YRD and PRD region, ship emissions from the East China Sea also made a great contribution to the high loadings of PM_1.8 and PM_1.8-associated NO₃^-, NH₄⁺, and EC in July. SO₄^2- in Shanghai was dominantly ascribed to anthropogenic sources and the high PSCF values for PM_1.8-associated SO₄^2- observed in August was mainly due to the ship emissions of Shanghai port, such as Wusong port and Yangshan deep-water port. These results indicated that the particulate pollutants from long-range transported air masses and shipping made a significant contribution to Shanghai's air pollution.

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

Heze city, a medium-size city in Shandong province, Eastern China. Ambient PM_2.5 samples were collected in urban area of Heze from August 2015 to April 2016, and chemical species and sources of PM_2.5 were investigated in this paper. The results indicated that the average concentration of PM_2.5 was 100.9 μg/m³ during the sampling period, and the water-soluble ions, carbonaceous species included elemental carbon (EC) and organic carbon (OC), as well as elements contributed 32.7-51.7%, 16.3% and 12.5%, respectively, to PM_2.5. Pearson's correlation analysis showed that the existing form of NH₄⁺ was more complex and diverse in spring/summer, and ammonium nitrate, ammonium sulfate and ammonium hydrogen sulfate might be major form of NH₄⁺ in autumn/winter. Correlation analysis between PM_2.5 and SO₄^2-/NO₃^-, PM_2.5 and OC/EC during different seasons suggested that mobile sources might make an important impact on the increase of PM_2.5 concentrations in spring/summer, and stationary sources might play a critical role on the increase of PM_2.5 concentrations in autumn/winter. Seven factors were selected in Positive Matrix Factorization (PMF) models analysis based on the Error Estimation (EE) diagnostics during different seasons. Secondary source had the highest contribution to PM_2.5 in Heze for the whole year, and followed by coal combustion, vehicle exhaust, soil dust, construction dust, biomass burning and metal manufacturing, and their annual contributions to PM_2.5 were 26.5%, 17.2%, 16.5%, 11.5%, 7.7%, 7.0% and 3.8%, respectively. The air masses that were originated from Mongolia reflected the features of large-scale and long-distance air transport; while the air masses that began in Jiangsu, Shandong and Henan showed the features of small-scale and short-distance. Shandong, Henan and Jiangsu were identified as the major potential sources-areas of PM_2.5 by using potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) models.

Evaluation of background soil and air polychlorinated biphenyl (PCB) concentrations on a hill at the outskirts of a metropolitan city

Air and soil sampling was conducted inside a forested area for 22 months. The sampling location is situated to the north of a metropolitan city. Average atmospheric gas and particle concentrations were found to be 180 and 28 pg m(-3) respectively, while that of soil phase was detected to be 3.2 ng g(-1) on dry matter, The congener pairs of PCB#4-10 had the highest contribution to each medium. TEQ concentration was 0.10 pg m(-3), 0.07 pg m(-3), 21.92 pg g(-1), for gas, particle and soil phases, respectively. PCB#126 and PCB#169 contributed to over 99% of the entire TEQ concentrations for each medium. Local sources were investigated by conditional probability function (CPF) and soil/air fugacity. Landfilling area and medical waste incinerator, located to the 8 km northeast, contributed to ambient concentrations, especially in terms of dioxin-like congeners. The industrial settlement (called Dilovasi being to the east southeast of 60 km distant) contributed from southeast direction. Further sources were identified by potential source contribution function (PSCF). Sources at close proximity had high contribution. Air mass transportation from Aliaga industrial region (being to the southwest of 300 km distant) moderately contributed to ambient concentrations. Low molecular weight congeners were released from soil body. 5-CBs and 6-CBs were close to equilibrium state between soil/air interfaces. PCB#171 was close to equilibrium and PCB#180 was likely to evaporate from soil, which constitute 7-CBs. PCB#199, representing 8-CBs deposited to soil. 9-CB (PCB#207) was in equilibrium between soil and air phases.

Short-term dynamics of indoor and outdoor endotoxin exposure: Case of Santiago, Chile, 2012

Indoor and outdoor endotoxin in PM2.5 was measured for the very first time in Santiago, Chile, in spring 2012. Average endotoxin concentrations were 0.099 and 0.094 [EU/m(3)] for indoor (N=44) and outdoor (N=41) samples, respectively; the indoor-outdoor correlation (log-transformed concentrations) was low: R=-0.06, 95% CI: (-0.35 to 0.24), likely owing to outdoor spatial variability. A linear regression model explained 68% of variability in outdoor endotoxins, using as predictors elemental carbon (a proxy of traffic emissions), chlorine (a tracer of marine air masses reaching the city) and relative humidity (a modulator of surface emissions of dust, vegetation and garbage debris). In this study, for the first time a potential source contribution function (PSCF) was applied to outdoor endotoxin measurements. Wind trajectory analysis identified upwind agricultural sources as contributors to the short-term, outdoor endotoxin variability. Our results confirm an association between combustion particles from traffic and outdoor endotoxin concentrations. For indoor endotoxins, a predictive model was developed but it only explained 44% of endotoxin variability; the significant predictors were tracers of indoor PM2.5 dust (Si, Ca), number of external windows and number of hours with internal doors open. Results suggest that short-term indoor endotoxin variability may be driven by household dust/garbage production and handling. This would explain the modest predictive performance of published models that use answers to household surveys as predictors. One feasible alternative is to increase the sampling period so that household features would arise as significant predictors of long-term airborne endotoxin levels.

Sources apportionment of PM2.5 in a background site in the North China Plain

To better understand the sources and potential source regions of PM2.5, a field study was conducted from January 2011 to November 2011 at a background site, the Yellow River Delta National Nature Reserve (YRDNNR) in the North China Plain. Positive matrix factorisation (PMF) analysis and a potential source contribution function (PSCF) model were used to assess the data, which showed that YRDNNR experienced serious air pollution. Concentrations of PM2.5 at YRDNNR were 71.2, 92.7, 97.1 and 62.5 μg m(-3) in spring, summer, autumn and winter, respectively, with 66.0% of the daily samples exhibiting higher concentrations of PM2.5 than the national air quality standard. PM2.5 mass closure showed remarkable seasonal variations. Sulphate, nitrate and ammonium were the dominant fractions of PM2.5 in summer (58.0%), whereas PM2.5 was characterized by a high load of organic aerosols (40.2%) in winter. PMF analysis indicated that secondary sulphate and nitrate (54.3%), biomass burning (15.8%), industry (10.7%), crustal matter (8.3%), vehicles (5.2%) and copper smelting (4.9%) were important sources of PM2.5 at YRDNNR on an annual average. The source of secondary sulphate and nitrate was probably industrial coal combustion. PSCF analysis indicated a significant regional impact on PM2.5 at YRDNNR all year round. Local emission may be non-negligible at YRDNNR in summer. The results of the present study provide a scientific basis for the development of PM2.5 control strategies on a regional scale.

Ambient polychlorinated biphenyl levels and their evaluation in a metropolitan city

In this study, summer and autumn ambient PCB concentrations were investigated in metropolitan city of Istanbul. 84 congeners were targeted from di-CBs to nona-CBs on both particle and gaseous phases. Gaseous ambient concentrations were determined to be 372 ± 134 pg·m(-3), while on the particle phase this value was 49 ± 17 pg·m(-3), corresponding to an average of 420 pg·m(-3). About one-tenth of all PCBs lay in ambient aerosols, while 90% of all comprise 2-, 3-, 4-, and 5-CBs. Measured ambient concentrations of each congener group were tested against meteorological data. The di-CB concentrations were independent of ambient temperature while northerly winds lead to an increase in their concentrations, which was an indicator of considerable contribution to di-CB concentrations from the medical waste incineration plant in Istanbul. In contrast, other congeners' concentrations were found to be correlated with southerly winds. Being an inland sea and having been contaminated, for years, by industrial discharges along the coastline, volatilization from Marmara Sea was considered as the most probable source of other congeners. PSCF analysis was run with 12-hour trajectories to locate possible local sources and check these results. Gas/particle partitioning was applied using three different models. mr and br values for log PL(0) model were determined as -0.23 ± 0.09 and -3.25 ± 0.38, respectively. For absorption based log Koa model, m and b values were calculated as 0.23 ± 0.08 and -4.73 ± 0.83, respectively.