Chemical characteristics and source apportionment of PM2.5 in a petrochemical city: Implications for primary and secondary carbonaceous component.

To study the pollution features and underlying mechanism of PM2.5 in Luoyang, a typical developing urban site in the central plain of China, 303 PM2.5 samples were collected from April 16 to December 29, 2015 to analyze the elements, water soluble inorganic ions, organic carbon and elemental carbon. The annual mean concentration of PM2.5 was 142.3 µg/m3, and 75% of the daily PM2.5 concentrations exceeded the 75 µg/m3. The secondary inorganic ions, organic matter and mineral dust were the most abundant species, accounting for 39.6%, 19.2% and 9.3% of the total mass concentration, respectively. But the major chemical components showed clear seasonal dependence. SO42- was most abundant specie in spring and summer, which related to intensive photochemical reaction under high O3 concentration. In contrast, the secondary organic carbon and ammonium while primary organic carbon and ammonium significantly contributed to haze formation in autumn and winter, respectively. This indicated that the collaboration effect of secondary inorganic aerosols and carbonaceous matters result in heavy haze in autumn and winter. Six main sources were identified by positive matrix factorization model: industrial emission, combustion sources, traffic emission, mineral dust, oil combustion and secondary sulfate, with the annual contribution of 24%, 20%, 24%, 4%, 5% and 23%, respectively. The potential source contribution function analysis pointed that the contribution of the local and short-range regional transportation had significant impact. This result highlighted that local primary carbonaceous and precursor of secondary carbonaceous mitigation would be key to reduce PM2.5 and O3 during heavy haze episodes in winter and autumn.

Ambient black carbon variations and emission characteristics of typical Chinese vessels in the Yangtze River Delta, China.

Black carbon (BC) has a significant impact on air quality, climate change, and human health. Studies on BC from vessel exhaust have been focused on in recent years. To realize the contribution of BC from vessels to ambient air quality, 28 months of BC variation were observed from February 2019 to May 2022, including 3 fishing moratoriums and 2 normal periods. The results showed that the average daily concentration of BC in the fishing moratorium was significantly lower than that in the normal period. The difference proportion of the BC concentration between 370 and 880 nm was calculated over the whole period. As a result, the mean difference value in the fishing moratorium from February to May was 0.06 ± 0.07, and the normal period was -0.02 ± 0.05. The aethalometer model indicated that BC was greatly affected by fossil fuel combustion in the normal period. The effect of vessel emissions on regional BC concentrations was considerable. In addition, 16 PAHs and 21 elements in PM emitted from 24 vessels of different types were sampled and analyzed in Dianshan Lake and the Taipu River. EC accounted for the highest proportion (23.64%) in the sample of small trawlers compared to the emissions from cargo ships with large tonnages. The component profiles of vessel exhaust showed that Zn, As, phenanthrene (Phe), anthracene (Ant), fluoranthene (Fla), and pyrene (Pyr) were the dominant species, although some of these species were mainly recognized as characteristic factors of coal combustion. To improve the accuracy of identifying the vessel source, the diagnostic ratios of Ant/(Ant + Phe), BaA/(BaA + Chr), Phe/Ant, and BaA/Chr were provided, and they exhibited the obvious characteristics of fuel combustion.

[Seasonal Variations and Source Apportionment of Carbonaceous Components in Luoyang: Implication for Brown Carbon Contribution].

A total of 98 samples were collected to analyze the seasonal variation and source apportionment of carbonaceous components, especially brown carbon (BrC), of PM2.5in Luoyang during 2018-2019. The concentrations of organic carbon (OC) and elemental carbon (EC) ranged from (7.04±1.82) µg·m-3to(23.81±8.68) µg·m-3and (2.96±1.4) µg·m-3to (13.41±7.91) µg·m-3, respectively, showing the seasonal variation of being high in winter and low in summer; the carbonaceous fraction and secondary organic aerosol percentages were higher by 8.33%-141.03% and by 0.77%-63.14%, respectively, compared with that in 2015. The light absorption cross section (MAC) values showed different seasonal variations with the concentration of carbonaceous fraction, shown in descending order as autumn (7.67 m2·g-1)>winter (5.65 m2·g-1)>spring (5.13 m2·g-1)>summer (3.84 m2·g-1). The MAC values ranged from 3.84 to 7.67 m2·g-1 at 445 nm, which was lower than that in coal ash. Seasonal variation in light absorption and the contribution of BrC to total light absorption (babs,BrC,405 nm, babs,BrC,405 nm/babs,405 nm) in descending order was winter (31.57 Mm-1, 33%), autumn (11.40 Mm-1, 25%), spring (4.88 Mm-1, 23%), and summer (2.12 Mm-1, 21%). The proportion of carbonaceous components decreased as haze episodes evolved, whereas the contribution of light absorption of BrC increased, highlighting the important contribution of BrC to the total light absorption. The results of PMF and correlation coefficients of babs,BrC,405 nm and PM2.5 components indicated that motor vehicles and secondary nitrate contributed 27.7% and 24.0%, respectively. Our findings have significant scientific implications for the deep controlling of carbonaceous aerosol, especially for BrC, in Luoyang in the future.

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.

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

To clarify the chemical characteristics, source contributions, and health risks of pollution events associated with high PM2.5 in typical industrial areas of North China, manual sampling and analysis of PM2.5 were conducted in the spring, summer, autumn, and winter of 2019 in Pingyin County, Jinan City, Shandong Province. The results showed that the total concentration of 29 components in PM2.5 was 53.4 ± 43.9 µg·m-3, including OC/EC, water-soluble ions, inorganic elements, and metal elements. The largest contribution was from the NO3- ion, at 14.6 ± 14.2 µg·m-3, followed by organic carbon (OC), SO42-, and NH4+, with concentrations of 9.3 ± 5.5, 9.1 ± 6.4, and 8.1 ± 6.8 µg·m-3, respectively. The concentrations of OC, NO3-, and SO42- were highest in winter and lowest in summer, whereas the NH4+ concentration was highest in winter and lowest in spring. Typical heavy metals had higher concentrations in autumn and winter, and lower concentrations in spring and summer. The annual average sulfur oxidation rate (SOR) and nitrogen oxidation rate (NOR) were 0.30 ± 0.14 and 0.21 ± 0.12, respectively, with the highest SO2 emission and conversion rates in winter, resulting in the SO42- concentration being highest in winter. The average concentration of secondary organic carbon in 2019 was 2.8 ± 1.9 µg·m-3, and it comprised approximately 30% of total OC. The concentrations of 18 elements including Na, Mg, and Al were between 2.3 ± 1.6 and 888.1 ± 415.2 ng·m-3, with Ni having the lowest concentration and K the highest. The health risk assessment for typical heavy metals showed that Pb poses a potential carcinogenic risk for adults, whereas As may pose a carcinogenic risk for adults, children, and adolescents. The non-carcinogenic risk coefficients for all heavy metals were lower than 1.0, indicating that the non-carcinogenic risk was negligible. Positive matrix factorization analysis indicated that coal-burning emissions contributed the largest fraction of PM2.5, accounting for 35.9% of the total. The contribution of automotive emissions is similar to that of coal, at 32.1%. The third-largest contributor was industrial sources, which accounted for 17.2%. The contributions of dust and other emissions sources to PM2.5 were 8.4% and 6.4%, respectively. This study provides reference data for policymakers to improve the air quality in the NCP.

[Analysis of Stable Carbon Isotope Characteristics of PM2.5 in Summer and Winter Season in Xinxiang City].

We study the seasonal variations of δ13C ratios in aerosol fine particulate matter (PM2.5) using 91 PM2.5 samples collected from Xinxiang, China, during the summer and winter in 2017. Mass concentrations of total carbon (TC), water soluble ions, and stable carbon isotope ratios (δ13C) were determined. The mean concentrations of TC in the summer and winter were 11.78 µg·m-3 and 26.6 µg·m-3, respectively. The δ13C ratio in the summer ranged from -27.70‰ to -25.22‰. The daily δ13C ratio fluctuated in the first half of the summer months (mean -26.96‰), whereas the δ13C ratio in the second half of the summer was relatively stable (mean -25.69‰). The number of fires in the study area during the first half of the summer was quite different to the number during the second half of the summer, meanwhile, there was a positive correlation between the Knss+ concentration and the TC mass concentration (R2=0.62, P<0.01). This indicates that biomass burning most likely contributed to variations in δ13C. During the winter there was a significant negative correlation between winter RH and the TC/PM2.5 mass ratio (R2=0.68, P<0.01), which suggests that SOA growth was dominant in the early stage of haze development, whereas the pollution period was dominated by SIA components. The ratio of δ13C ranged from -26.72‰ to -23.49‰, and there was a difference between the variation of the δ13C ratio in haze episode (when it was mainly enriched in the development stage) to that in the stage dominated by depletion.

[Concentration Characteristics and Source Analysis of PM2.5 During Wintertime in Zhengzhou-Xinxiang].

To study the pollution characteristics, sources, and transportation process of PM2.5 and its chemical compositions in the Zhengzhou-Xinxiang region, PM2.5 samples were collected using a middle volume sampler, in Zhengzhou and Xinxiang urban areas for 30 consecutive days during the winter of 2016. The mass concentration of PM2.5 was measured gravimetrically. 17 trace metals were determined by inductively coupled plasma-mass spectrometry (ICP-MS), and 7 water-soluble ions were determined by ion chromatography. The enrichment factor (EF) method and principal component analysis were employed to determine the source apportionment. The results showed that the daily mean PM2.5 mass concentration during the winter sampling period of 2016 in Xinxiang and Zhengzhou was 223.87 µg·m-3 and 226.67 µg·m-3, respectively, which indicated that pollution levels were relatively high in both cities. The concentration of three macro elements (Al, Ca, and Fe) accounted for 50% of the total metal elements in both cities, while the heavy metals concentration was higher in Xinxiang than in Zhengzhou. The EFs of Cd, Ag, and Pb in Xinxiang were far higher than 1000, while only Cd was higher than 1000 in Zhengzhou. NO3-, SO42-, and NH4+ were the main ions in the two cities. They exceeded 94% of total water-soluble ions and existed in the forms of (NH4)2SO4 and NH4NO3. The principle component analysis showed that the main contributors to PM2.5 were a mixture of biomass combustion and secondary aerosol in Xinxiang, and a mixture of coal combustion and traffic emissions in Zhengzhou, accounting for 34.94% and 33.99% of total PM2.5 emissions, respectively.