[Temporal and Spatial Distribution Characteristics and Driving Factors of Denitrification Bacterial Community Structure from Landscape Water in Hebei Province: Taking Shijiazhuang as Example].

Landscape water is an important part of urban water systems, and excessive nitrogen affects its ecological functions. This study aimed to investigate the temporal and spatial distribution characteristics and driving factors of the community structure of denitrifying bacteria from landscape water. The functional gene nirS was used as a functional marker to explore the community of denitrifying bacteria in the water and sediment of landscape water. Based on parameters of the water and sediment, the temporal and spatial distribution characteristics and driving factors of the community of denitrifying bacteria were studied. The results showed significant seasonal differences in water parameters and spatial differences in sediment nitrogen (P<0.001). No significant difference (P>0.05) was observed in α-diversity; the EC and SOEF-NH4+-N were important factors affecting the α-diversity of the water and sediment. Denitrifying bacteria mainly belonged to the phylum Proteobacteria and the genera Dechloromonas, Rhodocyclaceae, Pseudomonas, Rhodobacter, and Thauera. Principal coordinate analysis revealed that the community of denitrifying bacteria in the water and sediment exhibited significant spatial differences (P<0.001); keystone denitrifying bacteria in the water also exhibited significant spatial differences (P<0.001). RDA and RF analysis showed that the permanganate index and TP were the main environmental factors affecting the total and keystone denitrifying bacteria in the water; SOEF-NH4+-N, IEF-NH4+-N, and WAEF-NO3--N were the main environmental factors affecting the total and keystone denitrifying bacteria in the sediment. These findings could serve as a reference to understand the interaction mechanism between nitrogen and denitrification bacterial communities in landscape water.

[Spatial Distribution Characteristics of the Spectrum, Source Analysis, and Nitrogen Response of Dissolved Organic Matter in Summer Rainfall in the Hebei Province].

Dissolved organic matter(DOM) is an important component of the organic matter in the environment. This study explored the characteristics of DOM. The components and spectral characteristics of rainwater DOM were measured using Ultraviolet-visible absorption spectrum(UV-vis) and three-dimensional fluorescence spectrum in the Hebei province. The results showed significant differences for DOM molecular weight in the northern, central, and southern region; the DOM of the northern region exhibited the lowest molecular weight. Two humic-like(C1 and C4), one protein-like(C2) and one fulvic-like(C3) components were identified by parallel factor(PARAFAC) analysis. Component C2 had a significant positive correlation with components C3 and C4(P<0.001), which may have similar sources. The C2(protein-like substances) accounted for the major proportion of DOM with the average abundance 40.59%. The DOM components based on PARAFAC exhibited significantly difference between city and country regions without spatial difference, which was consistent with the result of fluorescence regional integration(FRI). The protein-like substances based on FRI were the main components, which accounted for 61.59%-89.01%. Redundancy analysis(RDA) showed that total nitrogen, nitrate, and ammonia were the main environmental factors determining the distribution of DOM. Spectral indices presented a significant difference between city and country regions. High fluorescence(FI) and biological(BIX) and low humification(HIX) values showed that summer rain exhibited the strong autochthonous and low humification characteristics, and country region have stronger autochthonous characteristics than city region. The regression analysis demonstrates that the prediction accuracy of rainwater quality parameters in city region is high. From all the results, rainwater DOM, showing strong autogenous characteristics, exhibited significant differences between city and country regions without spatial difference in Hebei. Meanwhile, it can also provide technical support for rainwater nitrogen concentration prediction based on DOM components.