Different Sources, Fractionation, and Migration of Legacy and Novel Per- and Polyfluoroalkyl Substances between Greenhouse and Open-Field Soils.

Perfluoroalkyl substances (PFASs) are widely present in agricultural soils, but their sources and fate in greenhouse soils remain unclear. In this study, the sources, fractionation, and migration of PFASs were compared in the greenhouse and open-field soils of the Fen-Wei Plain, China. The total concentrations of PFASs (Σ17PFAS) were comparable in the greenhouse and open-field soils but with different profiles. Detrended correspondence and correlation analyses indicated that dry deposition was an important source of PFASs in the open-field soils, whereas surface water had a notable contribution to the greenhouse soils due to more frequent irrigation. The PFASs in the soils were mainly present in water-soluble fraction (F1). The F1 proportions of short-chain and long-chain PFASs were negatively correlated with the anion exchange capacity (AEC) and organic carbon content (foc) in soil, respectively, with that of short-chain PFASs being higher than long-chain ones. The AEC was significantly higher while foc was lower in the greenhouse soil than the open-field soil, leading to lower proportions of F1 for short-chain PFASs while higher for long-chain ones in the greenhouse soil. Frequent irrigation and elevated temperatures promoted the migration of PFASs in greenhouse soil; thus, the Σ17PFAS and F1 exhibited an increasing trend with soil depth.

Significant contribution of secondary particulate matter to recurrent air pollution: Evidence from in situ observation in the most polluted city of Fen-Wei Plain of China.

Particulate matter (PM) pollution in high emission regions will affect air quality, human health and climate change on both local and regional scales, and thus attract worldwide attention. In this study, a comprehensive study on PM2.5 and its chemical composition were performed in Yuncheng (the most polluted city of Fen-Wei Plain of China) from November 28, 2020 to January 24, 2021. The average concentration of PM2.5 was 87.8 ± 52.0 µg/m3, which were apparently lower than those observed during the same periods of past five years, attributable to the clean air action plan implemented in this region. NO3- and organic carbon (OC) were the dominant particulate components, which on average contributed 22.6% and 16.5% to PM2.5, respectively. The fractions of NO3-, NH4+, OC and trace metals increased while those of crustal materials and elemental carbon decreased with the degradation of PM2.5 pollution. Six types of PM2.5 sources were identified by the PMF model, including secondary inorganic aerosol (35.3%), coal combustion (28.7%), vehicular emission (20.7%), electroplating industry (8.6%), smelt industry (3.9%) and dust (2.8%). Locations of each identified source were pinpointed based on conditional probability function, potential source contribution function and concentration weighted trajectory, which showed that the geographical distribution of the sources of PM2.5 roughly agreed with the areas of high emission. Overall, this study provides valuable information on atmospheric pollution and deems beneficial for policymakers to take informed action to sustainably improve air quality in highly polluted region.

[Orographic Influences on the Spatial Distribution of PM2.5 on the Fen-Wei Plain].

Topography not only has an effect on the spatial distribution of pollutants by restricting populations and industrial activities, but also affects the formation, transmission, accumulation, diffusion, and sedimentation of PM2.5. Topography is, therefore, an essential variable for understanding the spatial distribution of PM2.5, especially in basin areas. Based on gridded data and both natural and human indexes, this paper examines orographic effects on the distribution of PM2.5 on the Fen-Wei Plain based on the change point method, regression, the geographical detector method, and bivariate spatial autocorrelation. The results indicate that:① The relief amplitude of the plain is generally lower in its central part than at its edge, which is similar to the attitudinal distribution in this region; ② The distribution of PM2.5 is negatively related to relief amplitude, with high concentrations in central area and lower concentrations at the edge; ③ Based on the geographical detector analysis, PM2.5 patterns in this region are shaped by human factors including population, gross domestic product(GDP), and energy consumption, as well as natural factors including meteorological conditions and vegetation; and ④ Topography has a significant effect on both human and natural factors; an increase of relief amplitude is associated with a decrease in population, GDP, and energy consumption based on power function. Accordingly, temperature goes down linearly; precipitation, relative moisture, and wind speed increase linearly; and the vegetation index increases based on a logarithmic function.