[Spatial and Temporal Distribution of Antibiotic Resistance Genes in Different River Sediments in Typical Cities: A Case Study of Shijiazhuang].

Rivers are important reservoirs of antibiotic resistance genes (ARGs). However, most current studies have focused on the temporal and spatial distribution, and data on the differences in the species and abundance of ARGs between urban and rural rivers is still lacking for certain areas. In view of this, two rural rivers and three urban rivers were selected in Shijiazhuang City. In both December 2020 and April 2021, sediments were collected at 15 sampling sites. Metagenomic sequencing technology was used to compare the differences in temporal-spatial variation for ARGs in sediments. The results showed that:① 162 and 79 ARGs were detected in urban (4 776 ±4 452) and rural rivers (1 043 ±632), respectively. The abundance and species of ARGs in urban rivers were higher than those in rural rivers. ② The relative abundances of sulfonamide (SAs,27 %), aminoglycoside (AGs,26 %), and multidrug (MDs,15 %) ARGs had the highest abundance in urban rivers, whereas the relative abundance of MDs ARGs was highest in rural rivers (65 %). On the whole, the complexity of ARGs in urban rivers was higher than that in rural rivers. ③ There was a significant positive correlation between SAs, AGs, MDs, tetracycline, phenicol, macrolides-lincosamids-streptogramins (MLS), ß-lactams, and diaminopyrimidine ARGs in urban rivers (P < 0.01); however, there was a significant negative correlation between glycopeptide ARGs and all types of ARGs (P < 0.05 and P < 0.01). There was a significant positive correlation between MDs and SAs ARGs in rural rivers (P < 0.05), but there was a significant negative correlation between amino aminocoumarin, peptide, rifamycin, and fosfomycin ARGs (P < 0.05 and P < 0.01). ④ For the temporal variation in urban rivers, 162 ARGs (4 776 ±4 452) and 148 ARGs (5 673 ±5 626) were detected in December and April, respectively. For the temporal variation in rural rivers, 79 species (1 043 ±632) and 46 species (467 ±183) were detected in December and April, respectively. ⑤ RDA analysis results showed that the spatial-temporal distributions of ARGs in urban and rural rivers were different. Correlation analysis showed that the ARGs in urban rivers were significantly correlated with the number of industrial enterprises, whereas the ARGs in rural rivers were significantly correlated with the output value of animal husbandry. In general, this study identified the main influencing factors for ARGs in different rivers and provided data support for ARGs risk management in different rivers.

[Source Analysis and Health Risk Assessment of Heavy Metals in the Groundwater of Shijiazhuang, a Typical City in North China Plain].

Increasing attention has been paid to the heavy metal pollution in groundwater. The source analysis and risk assessment of heavy metals will provide data and method support for the targeted control of heavy metal pollution in groundwater. In this study, 20 sampling sites were selected in Shijiazhuang City. The APCS-MLR model and health risk model were applied to analyze and evaluate the pollution sources and health risks of 10 types of heavy metals in the groundwater of Shijiazhuang. The results showed that ① the mean concentration of heavy metals in groundwater followed the order of Fe>Zn>Mn>Cu>Al>Pb>Cr>As>Cd>Hg, and the mean ρ(Fe) and ρ(Pb) were 260.3 µg·L-1 and 10.01 µg·L-1, respectively. According to the results of the single factor and Nemerow index, Pb, Fe, and Cd primarily contributed to the heavy metal pollution in the groundwater. ② The concentration of heavy metals ranged from 47.30 to 2560 µg·L-1. In terms of spatial distribution, the highest concentration appeared at S3 (2560 µg·L-1), whereas the lowest concentration was at S9 (47.30 µg·L-1). ③ Source analysis results showed that industrial and agricultural activities, transportation emission, and geological background were the major heavy metal sources, among which the contribution of industrial and agricultural activities was the highest (47.83%). ④ The industrial-agricultural activities posed a potential threat to adults (HI>1); however, the non-cancer and the cancer risks of other sources for both adults and children were at an acceptable level (HI<1) and potential threat level, respectively; industrial-agricultural activities were the major source of non-cancer (adults:52.46%, children:52.45%) and cancer risks (adults:65.22%, children:65.69%), among which Cd and As showed high cancer risk. Therefore, to ensure the safety of the groundwater environment, strictly controlling the pollution sources and further strengthening the risk control of heavy metal pollution in groundwater are necessary.

[Source Apportionment and Source-specific Risk of Typical Antibiotics in Baiyangdian Lake].

The current situation of antibiotic pollution in lakes is critical. At present, most of the previous studies on antibiotics in lakes have focused on the spatiotemporal distribution and risk assessment, while less attention has been paid to the source apportionment. Ultra-high performance liquid chromatography-mass spectrometry was used to determine the concentration of tetracyclines (TCs), sulfonamides (SAs), and quinolones (QNs) in the samples. The source apportionment and source-specific risk of typical antibiotics in the study area were analyzed using the combination of a PMF model and risk quotients (RQ). The results showed that ① the total concentrations of target antibiotics (Σ antibiotics) ranged from ND to 2635 ng·L-1 for surface water and from ND to 259.8 ng·g-1 for sediments. ② The spatial distribution of QNs in surface water decreased from west to east, SAs decreased from middle to north and south, and TCs increased from middle to north and south. In the sediment, QNs decreased from middle to east and west, whereas SAs and TCs increased from east to west. ③ Aquaculture was the major antibiotic source, accounting for the highest proportion (33.2%), followed by sewage treatment plants (29.2%), livestock activities (18.9%), and domestic sewage (18.7%). ④ The ecological risk assessment results showed that enrofloxacin and flumequine were at a medium-high risk level. ⑤ For the spatial distribution of source-specific risk, the results showed that the aquaculture at S1 was at a high risk level, whereas the source-specific risks for other sites were at a medium-low risk level. In terms of source types, aquaculture was at a medium-high risk level, whereas the other sources were at a medium-low risk level. Therefore, considering the major sources and source-specific risk level of antibiotics, more precise and scientific antibiotic risk control should be adopted in Baiyangdian Lake.