Occurrence, source apportionment, and ecological risk of legacy and emerging per- and poly-fluoroalkyl substances (PFASs) in the Dahei river basin of a typical arid region in China.

Per- and poly-fluoroalkyl substances (PFASs) are artificial chemicals with broad commercial and industrial applications. Many studies about PFASs have been conducted in densely industrial and populated regions. However, fewer studies have focused on the PFASs' status in a typical arid region. Here, we investigated 30 legacy and emerging PFASs in surface water from the mainstream and tributaries of the Dahei River. Our results revealed that total PFASs concentrations (∑30PFASs) in water ranged from 3.13 to 289.1 ng/L (mean: 25.40 ng/L). Perfluorooctanoic acid (PFOA) had the highest mean concentration of 2.44 ng/L with a 100% detection frequency (DF), followed by perfluorohexanoic acid (PFHxA) (mean concentration: 1.34 ng/L, DF: 59.26%). Also, perfluorohexane sulfonate (DF: 44.44%), perfluorobutane sulfonate (DF: 88.89%), and perfluorooctane sulfonate (PFOS) (DF: 92.59%) had mean concentrations of 12.94, 2.00, and 1.05 ng/L, respectively. Source apportionment through ratio analysis and principal component analysis-multiple linear regression analysis showed that treated or untreated sewage, aqueous film-forming foam, degradation of precursors, and fluoropolymer production were the primary sources. The PFOS alternatives were more prevalent than those of PFOA. Conductivity, total phosphorus, and chlorophyll a positively correlated with Σ30PFASs and total perfluoroalkane sulfonates concentrations. Furthermore, ecological risk assessment showed that more attention should be paid to perfluorooctadecanoic acid, perfluorohexadecanoic acid, perfluorooctane sulfonate, perfluorohexane sulfonate, and (6:2 and 6:2/8:2) polyfluoroalkyl phosphate mono- and di-esters. The mass load of PFASs to the Yellow River was 1.28 kg/year due to the low annual runoff in the Dahei River in the arid region. This study provides baseline data for PFASs in the Dahei River that can aid in the development of effective management strategies for controlling PFASs pollution in typical arid regions in China.

Differential analysis of FA-NNC, PCA-MLR, and PMF methods applied in source apportionment of PAHs in street dust.

Many source apportionment models have been applied to identify pollution sources, and differences often exist in the diagnostic results. The reasons causing these differences have not been fully elucidated. In this study, three receptor models, principal component analysis-multiple linear regression (PCA-MLR), positive matrix factorization (PMF), and factor analysis-nonnegative constraints (FA-NNC), were compared and applied for the analysis of 16 EPA priority polycyclic aromatic hydrocarbons (PAHs) adsorbed in street dust samples from Harbin City (China). The differences in the results were caused by different calculation approaches, including matrix decomposition, variable grouping extraction, and nonnegative constraints, especially between PCA-MLR and the other two models. PCA-MLR has no nonnegative constraints, making PCA-MLR less similar to the real world than the other two. Both PMF and FA-NNC have a nonnegative constraint process, which may be the main reason why their results were much more similar to each other than to those of PCA-MLR. PCA-MLR distinguishes variables into several groups that have the greatest variances from each other, whereas the other two methods find similarities among variables and extract them. In the case study of Harbin City, the contributions of mobile and industrial sources ranged from 47 to 69%, and the contributions of coal and other sources ranged from 30 to 52%. The recognized types of pollution sources were generally equivalent, but the proportional contributions were different. PCA-MLR performed best in calculating contributions, whereas PMF and FA-NNC were better in terms of source diagnosis.

Spatial Variability and Source Apportionment of Aliphatic Hydrocarbons in Sediments from the Typical Coal Mining Area.

Fifty-four surface sediments from the typical coal mining area were analyzed for pristane, phytane and C8-C40 n-alkanes using gas chromatography-mass spectrometry (GC-MS). The spatial distribution, homolog profiles and source apportionment of aliphatic hydrocarbons were investigated. Bimodal distribution pattern, centered at C16-C20 and C27-C33 n-alkanes, were observed in all sediment samples with an obvious dominance of low molecular weight homologues. Principal component analysis-multiple linear regression (PCA-MLR) was used to predict the contributions of different sources. The result implied that natural input was the main source, contribution of which accounted for 60.8%, and the contributions of different sources were estimated as follow: 21.8% for terrestrial higher plants, 24.1% for algae and photosynthetic bacteria, 14.9% for submerged/floating macrophytes, 23.5% for fossil fuel combustion and 15.7% for petroleum hydrocarbons. Moreover, relatively high median concentrations of fossil fuel combustion were observed in Shou County and Fengtai County, indicating the high contribution of fossil fuel combustion in these two areas.

Analysis of Heavy Metal Sources in the Soil of Riverbanks Across an Urbanization Gradient.

Regional soil quality issues arising from rapid urbanization have received extensive attention. The riverbank that runs through a city is representative of urbanization gradient transformation. Thirty soil samples in the Yangtze River Delta urban agglomeration were collected and analyzed for the concentrations of seven analytes. Correlation, principle component analysis, cluster analysis and GeoDetector models suggested that the four groups (Cr-Ni-Cu, Cu-Zn-As-Sb, Cd and Pb) shared the same sources in the core urban region; five groups (Cr-Ni-Cu-Zn, As, Cd, Sb and Pb) in the suburbs and three groups (Cr-Ni, Cu-Zn-Cd-Sb-Pb and As) in the exurbs. GeoDetector methods not only validated the results of the three other methods, but also provided more possible impact factors. Besides the direct influences, the interaction effects among factors were quantified. Interactive combination with strong nonlinear increment changed from between-two-weak factors in the central region to between-strong-and-weak factors in the suburbs. In the exurbs, the stronger interaction effects were observed between strong and weak factors. Therefore, the GeoDetector model, which provided more detailed information of artificial sources could be used as a tool for identifying the potential factors of toxic elements and offering scientific basis for the development of subsequent pollution reduction strategies.

Space-time quantitative source apportionment of soil heavy metal concentration increments.

Assessing the space-time trends and detecting the sources of heavy metal accumulation in soils have important consequences in the prevention and treatment of soil heavy metal pollution. In this study, we collected soil samples in the eastern part of the Qingshan district, Wuhan city, Hubei Province, China, during the period 2010-2014. The Cd, Cu, Pb and Zn concentrations in soils exhibited a significant accumulation during 2010-2014. The spatiotemporal Kriging technique, based on a quantitative characterization of soil heavy metal concentration variations in terms of non-separable variogram models, was employed to estimate the spatiotemporal soil heavy metal distribution in the study region. Our findings showed that the Cd, Cu, and Zn concentrations have an obvious incremental tendency from the southwestern to the central part of the study region. However, the Pb concentrations exhibited an obvious tendency from the northern part to the central part of the region. Then, spatial overlay analysis was used to obtain absolute and relative concentration increments of adjacent 1- or 5-year periods during 2010-2014. The spatial distribution of soil heavy metal concentration increments showed that the larger increments occurred in the center of the study region. Lastly, the principal component analysis combined with the multiple linear regression method were employed to quantify the source apportionment of the soil heavy metal concentration increments in the region. Our results led to the conclusion that the sources of soil heavy metal concentration increments should be ascribed to industry, agriculture and traffic. In particular, 82.5% of soil heavy metal concentration increment during 2010-2014 was ascribed to industrial/agricultural activities sources. Using STK and SOA to obtain the spatial distribution of heavy metal concentration increments in soils. Using PCA-MLR to quantify the source apportionment of soil heavy metal concentration increments.

Occurrence and carcinogenic potential of airborne polycyclic aromatic hydrocarbons in some large-scale enclosed/semi-enclosed vehicle parking areas.

Polycyclic aromatic hydrocarbons (PAHs) originating from vehicle exhaust have aroused much attention due to their potential healthy effect. In this study, air samples were collected from three representative parking lots in a metropolitan area, analyzed for PAHs and evaluated for inhalation risk. Atmospheric PAH levels of these parking areas ranged between 1,178-4,793 ng m(-3), one order of magnitude higher than general urban areas. Their benzo[a]pyrene equivalent (BaPeq) values varied in 11.0-98.0 ng m(-3), far exceeding the air quality standard of WHO (1.0 ng m(-3)). Monte Carlo simulation (100,000 trials) results suggest that the potential lifetime inhalation cancer risks of PAHs were 0.27 × 10(-5) to 7.11 × 10(-5) for park employees, which are in the acceptable range acknowledged by US EPA (1.0 × 10(-6) to 1.0 × 10(-4)). Several source diagnostic methods proved that vehicle exhaust was the dominant PAH contributor of these parks with the contribution percentages being >53%; oil combustion and/or coal combustion were other important sources. Logarithms of gas-particle distribution coefficients (Kps) of PAHs in all studied parks were linearly correlated with those of both their sub-cooled vapor pressures (pLs) and octanol-air partition coefficients (KOAs). The correlation coefficients indicated that both adsorption onto black carbon and absorption into organic matter were involved in the partition process, but the latter was dominant.