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 [PM2.5], 2.5-5 µm [PM2.5-5], 5-10 µm [PM5-10], and 10-100 µm [PM10-100]) were collected to analyze the mass concentration and distribution characteristics of nine water-soluble ions (WSIs; F-, Cl-, NO3-, SO42-, 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 PM2.5, 80.99% of which was attributable to SO42-, 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 PM2.5 was alkaline overall, and K+ and NH4+ caused the highest RC/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 PM2.5. 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.

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.

Observation on the aerosol and ozone precursors in suburban areas of Shenzhen and analysis of potential source based on MAX-DOAS.

Long-term stereoscopic observations of aerosol, NO2, and HCHO were carried out at the Yangmeikeng (YMK) site in Shenzhen. Aerosol optical depths and NO2 vertical column concentration (NO2 VCD) derived from MAX-DOAS were found to be consistent with other datasets. The total NO2 VCD values of the site remained low, varying from 2 × 1015 to 8 × 1015 mol/cm2, while the HCHO VCD was higher than NO2 VCD, varying from 7 × 1015 to 11 × 1015 mol/cm2. HCHO VCD was higher from September to early November than that was from mid-late November to December and during February 2021, in contrast, NO2 VCD did not change much during the same period. In January, NO2 VCD and HCHO VCD were both fluctuating drastically. High temperature and HCHO level in the YMK site is not only driving the ozone production up but also may be driving up the ozone concentration as well, and the O3 production regime in the YMK site tends to be NOx-limited. At various altitudes, backward trajectory clustering analysis and Potential Source Contribution Function (PSCF) were utilized to identify possible NO2 and HCHO source locations. The results suggested that the Huizhou-Shanwei border and the Daya Bay Sea area were the key potential source locations in the lower (200 m) and middle (500 m) atmosphere (WPSCF > 0.6). The WPSCF value was high at the 1000 m altitude which was closer to the YMK site than the near ground, indicating that the pollution transport capability in the upper atmosphere was limited.

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

Here we present seasonal chemical characteristics, formations, sources of PM2.5 in the year 2020 in Suzhou, Yangtze River Delta, China. Expectedly, organic matter (OM) found to be the most dominant component of PM2.5, with a year-average value of 10.3 ± 5.5 µg m-3, followed by NO3- (6.7 ± 6.5 µg m-3), SO42- (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 PM2.5 showed the highest average value in spring, followed by winter, fall, and summer. Meanwhile, the formation mechanisms of the major PM2.5 species (NO3-, SO42-, 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 PM2.5 contributed significantly to the PM2.5 mass (42%), followed by the dust-related PM2.5 (38%) and the less-aged PM2.5 (21%). Potential contribution source function (PSCF) results indicated that aged PM2.5 were less affected by transportation than dust-related PM2.5.

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 PM2.5 (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 PM2.5 were measured and studied along with cluster analysis and Potential Source Contribution Function (PSCF) modelling. PM2.5 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.

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 Izmir and Balikesir during the autumn.

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 (PM2.5) 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.

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.

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 (PM2.5, 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 PM2.5 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 PM2.5 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.

Environmental impact and health risk assessment of volatile organic compound emissions during different seasons in Beijing.

Volatile organic compounds (VOCs) are major contributors to air pollution. Based on the emission characteristics of 99 VOCs that daily measured at 10 am in winter from 15 December 2015 to 17 January 2016 and in summer from 21 July to 25 August 2016 in Beijing, the environmental impact and health risk of VOC were assessed. In the winter polluted days, the secondary organic aerosol formation potential (SOAP) of VOC (199.70 ± 15.05 µg/m3) was significantly higher than that on other days. And aromatics were the primary contributor (98.03%) to the SOAP during the observation period. Additionally, the result of the ozone formation potential (OFP) showed that ethylene contributed the most to OFP in winter (26.00% and 27.64% on the normal and polluted days). In summer, however, acetaldehyde was the primary contributor to OFP (22.00% and 21.61% on the normal and polluted days). Simultaneously, study showed that hazard ratios and lifetime cancer risk values of acrolein, chloroform, benzene, 1,2-dichloroethane, acetaldehyde and 1,3-butadiene exceeded the thresholds established by USEPA, thereby presenting a health risk to the residents. Besides, the ratio of toluene-to-benzene indicated that vehicle exhausts were the main source of VOC pollution in Beijing. The ratio of m-/p-xylene-to-ethylbenzene demonstrated that there were more prominent atmospheric photochemical reactions in summer than that in winter. Finally, according to the potential source contribution function (PSCF) results, compared with local pollution sources, the spread of pollution from long-distance VOCs had a greater impact on Beijing.

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 PM2.5 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.

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 (PNC2.5), the continuous measurement of PNC2.5, chemical components in PM2.5, gaseous pollutants and meteorological conditions were conducted at an urban site in Tianjin in June 2015. Results indicated that the average PNC2.5 was 2839±2430 dN/dlogDp 1/cm3 during the campaign. Compared to other meteorological parameters, the relative humidity (RH) had the strongest relationship with PNC2.5, with a Pearson's correlation coefficient of 0.53, and RH larger than 30% influenced strongly PNC2.5. The important influence of secondary reactions on PNC2.5 was inferred due to higher correlation coefficients between PNC2.5 and SO42-, NO3-, NH4+ (r=0.78-0.89; p<0.01) and between PNC2.5 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 PNC2.5 and NO3-, SO42-, NH4+, while those between PNC2.5 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 PNC2.5. 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 PNC2.5. The north of Jiangsu, the west of Shandong, and the east of Hebei were distinguished as major potential source-areas of PNC2.5 by PSCF model.

Six sources mainly contributing to the haze episodes and health risk assessment of PM2.5 at Beijing suburb in 2016.

Aiming to a better understanding sources contributions and regional sources of fine particles, a total of 273 filter samples (159 of PM2.5 and 114 of PM1.0) were collected per 8 h during the winter 2016 at a southwest suburb of Beijing. Chemical compositions, including water soluble ions, organic carbon (OC), and elemental carbon (EC), as well as secondary organic carbon (SOC), were systematically analyzed and estimated. The total ions concentrations (TIC), OC, and SOC of PM2.5 were with the following order: 16:00-24:00 > 08:00-16:00 > 00:00-08:00. Since primary OC and EC were mainly attributed to the residential combustion in the night time, their valley values were observed in the daytime (08:00-16:00). However, the highest ratio value of SOC/OC was observed in the daytime. It is because that SOC is easily formed under sunshine and relatively high temperature in the daytime. Positive matrix factorization (PMF), clustering, and potential source contribution function (PSCF) were employed for apportioning sources contributions and speculating potential sources spatial distributions. The average concentrations of each species and the source contributions to each species were calculated based on the data of species concentrations with an 8 h period simulated by PMF model. Six likely sources, including secondary inorganic aerosols, coal combustion, industrial and traffic emissions, road dust, soil and construction dust, and biomass burning, were contributed to PM2.5 accounting for 29%, 21%, 17%, 16%, 9%, 8%, respectively. The results of cluster analysis indicated that most of air masses were transported from West and Northwest directions to the sampling location during the observation campaign. Several seriously polluted areas that might affect the air quality of Beijing by long-range transport were identified. Most of air masses were transported from Western and Northwestern China. According to the results of PSCF analysis, Western Shandong, Southern Hebei, Northern Henan, Western Inner Mongolia, Northern Shaanxi, and the whole Shanxi provinces should be the key areas of air pollution control in China. The exposure-response function was used to estimate the health impact associated with PM2.5 pollution. The population affected by PM2.5 during haze episodes reached 0.31 million, the premature death cases associated with PM2.5 reached 2032. These results provided important implication for making environmental policies to improve air quality in China.

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 PM2.5 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 PM2.5 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 PM2.5. 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.

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.

PSCF method for source identification of particulate matter in an agricultural background region in Brazil.

The use of mathematical and statistical models to investigate potential sources of pollutants that have been transported by air masses to a study site is important for establishing control and monitoring measures for air pollutants such as PM10 and PM2.5. During the study period, from 2018 to 2021, the concentrations of PM10 and PM2.5 recorded in Ribeirão Preto (SP, Brazil) were higher during spring and winter, with a tendency to increase the amplitude and its maximum values relative to daily averages. The source-receptor model, Potential Source Contribution Function (PSCF), was used to identify probable sources of these pollutants, and the regions known as Triângulo Mineiro and Intermediate Geographic Region of Juiz de Fora (MG, Brazil) were the main regions associated with high PSCF probability values (> 0.5) as sources of PM. These regions indicate that the possible sources of PM emissions are associated with industrial complexes and agriculture, especially coffee production.

Dry deposition fluxes and inhalation risks of toxic elements in total suspended particles in the Bohai Rim region: Long-term trends and potential sources.

Long-term changes in dry deposition fluxes (DDF) and health risks for toxic elements (TE) in total suspended particles (TSP) in the Bohai Rim region are important for assessing control effects of pollution sources. Thus, we investigated the trends in DDF and concentrations for TSP and TE and health risks of TE in eight cities in the region from 2011-2020. TSP concentration and DDF showed general downward trends. Compared to the before Clear Air Action Plan (BCAAP, 2011-2012) period, concentration and DDF of TE over the Clear Air Action Plan (CAAP, 2013-2017) period substantially decreased, with the highest decrease rates in Zn, Cd, and Cr. During the study period, non-carcinogenic (HI) and total carcinogenic (TCR) risks for children and adults were 0.09 and 0.04, and 1.54 × 10-5 and 2.65 × 10-5, respectively, with Cr6+ and As being dominant contributors. Compared to the BCAAP period, HI and TCR over the CAAP period decreased by 36.8 % and 32.4 %, respectively. However, their risks increased over the Blue Sky Protection Campaign (BSPC, 2018-2020) period. Potential source contribution function suggested substantial changes in potential risk areas over different control periods, with the BSPC primarily being on land and the Yellow Sea.

A comprehensive exploration of characteristics and source attribution of carbonaceous aerosols in PM2.5 in an East China megacity.

A total of 84 PM2.5 (fine particulate matter) aerosol samples were collected between October 2020 and August 2021 within an urban site in Hangzhou, an East China megacity. Chemical species, such as organic carbon (OC), elemental carbon (EC), as well as char, soot, and n-alkanes, were analyzed to determine their pollution characteristics and source contributions. The mean yearly concentrations of OC, EC, char, soot, and total n-alkanes (∑n-alkane) were 8.76 ± 3.61 µg/m3, 1.44 ± 0.76 µg/m3, 1.21 ± 0.69 µg/m3, 0.3 ± 0.1 µg/m3, and 24.2 ± 10.6 ng/m3. The OC, EC, and ∑n-alkanes were found in the highest levels during winter and lowest during summer. There were strong correlations between OC and EC in both winter and spring, suggesting similar potential sources for these carbonaceous components in both seasons. There were poor correlations among the target pollutants due to summertime secondary organic carbon formation. Potential source contribution functions analysis showed that local pollution levels in winter and autumn were likely influenced by long-range transportation from the Plain of North China. Source index and positive matrix factorization models provided insights into the complex sources of n-alkanes in Hangzhou. Their major contributors were identified as terrestrial plant releases (32.7%), traffic emissions (28.8%), coal combustion (27.3%), and microbial activity (11.2%). Thus, controlling vehicular emissions and coal burning could be key measures to alleviate n-alkane concentrations in the atmosphere of Hangzhou, as well as other Chinese urban centers.

Spatio-temporal variation of particulate matter with health impact assessment and long-range transport - case study: Ankara, Türkiye.

A clean atmosphere should be provided as a right for human beings to live. The reality is that a significant proportion of the population is exposed to air pollution. This study presents an in-depth investigation into the spatio-temporal dynamics of PM2.5 concentrations in Ankara, Türkiye, spanning over three years. With particular emphasis on the impact of COVID-19 lockdown measures and local air quality management strategies, data from eight air pollution monitoring stations were analyzed. The findings indicate a significant reduction in PM2.5 levels during lockdown periods, with an average decrease of 18 % observed across the city. Implementing the Ankara Provincial Clean Air Action Plan further contributed to a 9.1 % decrease in PM2.5 concentrations in 2021, followed by an additional 6.6 % decrease in 2022 compared to 2020. The spatial distribution of PM2.5 concentrations reveals the influence of industrial and urban areas on pollution levels. Potential Source Contribution Function (PSCF) and Concentration-Weighted Trajectory (CWT) methods were employed to investigate the spatial and temporal variation of long-range transport source regions contributing to the PM2.5 levels in Ankara. PSCF and CWT analyses revealed a decreasing trend in anthropogenic contribution to PM2.5 from 2020 to 2022. The AirQ+ model was employed to predict the long-term mortality rates attributable to PM2.5 across different monitoring stations. Based on the estimations, all stations' average estimated attributable proportion is 9.8 % (3.3 %-27.8 %). The results depict varying trends in estimated mortality rates, emphasizing the importance of targeted interventions to mitigate the public health risks arising from exposure to polluted air. Overall, the results of this study show significant measures for the development of effective clean air quality strategies can effectively change the direction of the adverse impact of air pollution on public health.

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

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