Source apportionment and specific-source-site risk of quinolone antibiotics for effluent-receiving urban rivers and groundwater in a city, China

Integrating microbial community dynamics and emerging contaminants (ECs) for precisely quantifying the sources in groundwater affected by livestock farming

Livestock farming is a major emission source of emerging contaminants (ECs); improper management of ECs could lead to severe groundwater pollution. However, research on accurately controlling the impact of large-scale livestock pollution in groundwater and quantifying sources of ECs pollution from livestock farming to formulating effective control measures is scarce. For the first time, the groundwater near four livestock farms (broiler, dairy, aquaculture, and pig farms) was selected as the research object to characterize the ECs, analyze the impact of ECs on microbial communities, and identify the pollution sources of livestock groundwater by the fast expectation-maximization of microbial source tracking (FEAST). Significant differences in the levels of antibiotics and hormones from four livestock farms led to changes in the groundwater microbial communities. The ECs improved the uniqueness of source biomarkers, providing better help for FEAST distinguishing livestock pollution sources at various groundwater mixing ratios. This study improved the accuracy of FEAST in investigating the pollution sources in groundwater and provided experimental evidence for accurate source tracking of ECs in groundwater in large-scale areas heavily polluted by livestock farming.

A nationwide probabilistic risk assessment and a new insight into source-specific risk apportionment of antibiotics in eight typical river basins in China: Human health risk and ecological risk

China is the largest producer and consumer of antibiotics, a nationwide study on the contamination of antibiotics in China is urgently needed, and source apportionment towards risks associated with antibiotics is now attracting increasing attention. In this study, based on eight antibiotics at 666 sampling sites, spatial variations and probabilistic risks (human health and ecological risk) of antibiotics in eight river basins in China were analyzed. Source-specific health and ecological risk associated with antibiotics in a typical basin was apportioned quantitatively. Results showed that mean antibiotic concentration in Haihe River Basin (HaiRB) and Yellow River Basin (178.25 and 257.36 ng·L-1, respectively) was higher than other basins. In HaiRB, the contribution of livestock and poultry breeding (31.89 %) was the largest of all sources for health risk, whereas pharmaceutical wastewater (35.97 %) was the most dominant source for ecological risk. To determine the most important source for risks associated with antibiotics, the concept of risks-targeted key source was proposed, and a risks-targeted key source apportionment model was developed. Results showed that pharmaceutical wastewater should be prior controlled among all sources. The concept and apportionment model of risks-targeted key source proposed in this study are applicable and referential for related studies.

Simulation and prediction of sulfamethazine migration, transformation and risk diffusion during cross-media infiltration from surface water to groundwater driven by dynamic water level: Machine learning coupled HYDRUS-GMS model

Seasonal water level fluctuations in rivers significantly influenced the cross-media migration, transformation, and risk diffusion of antibiotics from the vadose zone into groundwater. This study developed a coupled model integrating machine learning (ML) with HYDRUS-3D and GMS to accurately predict sulfamethazine migration under dynamic water levels. The predictive accuracy (E≥0.98) of this ML-HYDRUS-GMS model was enhanced by accounting for seasonal water level fluctuations and biogeochemical variability. Significant seasonal differences presented with sulfamethazine diffusion in the vadose zone with the migration rate decreased from 0.06 m/d to 0.02 m/d with the transition from wet to dry seasons. After 6 years of infiltration, it reached groundwater, where lateral migration rates, influenced by seasonal flow variations, were 0.12 m/d in the wet season and decreased to 0.07 m/d in the dry season, with a diffusion range extending to 217 m over 100 years. This discrepant continuous filtration of sulfamethazine and the succession of metabolic pathways induced toxicity range to expand by 65.6 m and the risk to increase to warning level. Sulfamethazine underwent oxidative breakdown in aerobic vadose zone conditions, while anaerobic groundwater conditions led to hydrogenation and reduction, increasing its migration distance.

Determination and Ecological Risk Assessment of Quinolone Antibiotics in Drinking and Environmental Waters Using Fully Automated Disk-Based SPE Coupled with UPLC-MS/MS

Quinolone antibiotics (QNs) contamination in the aquatic environment is a global public health issue considering their resistance and mobility. In this study, a simple, efficient, and sensitive method was developed for the accurate quantification of fifteen QNs in water using automated disk-based solid-phase extraction (SPE) coupled with ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). By utilizing a 3M SDB-XC disk to enrich QNs from a 1000 mL water sample, the detection limits were improved to 0.008-0.055 ng/L due to the satisfactory enrichment factors of 897-1136, but only requiring about 60 min per six samples. The linearity of the method ranged from 0.05 to 100 μg/L for the 15 QNs, with correlation coefficients of 0.9992-0.9999, and the recoveries were in the range of 81-114%, with relative standard deviations of 0.2-13.3% (n = 6). The developed method was applicable for the quantification of trace QNs at low ng/L levels in drinking and environmental waters. The results showed that no QNs were detected in tap water, while three and four QNs were detected in the river water of Zhoushan and the seawater of Daiquyang and Yueqing Bay, East China, respectively, with a total concentration of 1.600-8.511 ng/L and 1.651-16.421 ng/L, respectively. Among the detected QNs, ofloxacin (OFL) was the predominant compound in river water, while enrofloxacin (ENR) was predominant in seawater. The risk quotient (RQ) results revealed that QNs posed a low risk to crustaceans and fish, but a low-to-medium risk to algae, and OFL presented the main ecological risk factor in river water, while ENR and CIP in seawater. Overall, the proposed automated disk-based SPE-UPLC-MS/MS method is highly efficient and sensitive, making it suitable for routine analysis of QNs in drinking and environmental waters.

High performance enrichment and analysis of fluoroquinolones residues in environmental water using cobalt ion mediated paper-based molecularly imprinted polymer chips

BACKGROUND

Fluoroquinolones (FQs) are widely used for their excellent antimicrobial properties, yet their release into aquatic environments pose risks to ecosystems and public health. The accurate monitoring and analysis of FQs present challenges due to their low concentrations and the complex matrices found in actual environmental samples. To address the need for auto-pretreatment and on-line instrumental analysis, developing new microextraction materials and protocols is crucial. Such advancements will provide better analytical assurance for the effective extraction and determination of FQs at trace levels, which is of great significance to environmental protection and human health.

RESULTS

In this work, we presented a Co2+ mediated paper-based molecularly imprinted polymer chip (CMC@Co-MIP), combined with UPLC analysis, to develop an effective analytical method for identifying and quantifying trace amounts of ciprofloxacin (CIP) and enrofloxacin (ENR) in water samples. Notably, the addition of Co2+ in CMC@Co-MIP helped to capture the template molecule CIP through coordination before imprinting, which significantly improved the ordering of the imprinted cavities. CMC@Co-MIP exhibited a maximum adsorption capacity up to 500.20 mg g-1 with an imprinting factor of 4.12, surpassing previous reports by a significant margin. Furthermore, the enrichment mechanism was extensively analyzed by various characterization techniques. The developed method showed excellent repeatability and reproducibility (RSD < 13.0 %) with detection limits ranging from 0.15 to 0.21 μg L-1 and recoveries ranging from 64.9 % to 102.3 % in real spiked water samples.

SIGNIFICANCE

We developed a novel microextraction paper-based chip based on Co2+ mediation, which effectively improved the selectivity and convenience of extracting FQs. This breakthrough allowed the chip to have a high enrichment efficiency as well as provide a robust on-line instrumental program. It also confirms that the imprinting scheme based on metal ion coordination is a high-performance strategy.

Ecological risk assessment of commonly used antibiotics in aquatic ecosystems along the coast of China

The consistent input of antibiotics into aquatic environments may pose risks to various creatures and ecosystems. However, risk assessment of pharmaceuticals and personal care products (PPCPs) in aquatic environments is frequently limited by the lack of toxicity data. To investigate the risk of commonly used antibiotics to various aquatic creatures, we focused on the distribution patterns and temporal dynamics of antibiotics in the coastal estuary area of China and performed a comprehensive ecological risk assessment for four antibiotics: erythromycin (ERY), tetracycline (TCN), norfloxacin (NOR) and sulfamethoxazole (SMX). An interspecies correlation estimation (ICE)-species sensitivity distribution (SSD) combined model was applied to predict the toxicity data of untested aquatic species, and an accurate ecological risk assessment procedure was developed to evaluate the risk level of PPCPs. The results of risk quotient assessments and probabilistic risk assessments (PRAs) suggested that four objective antibiotics in the Chinese coastal estuary area were at a low risk level. These antibiotics posed a high risk in antibiotic-related global hot spots, with probabilistic risk values for ERY, NOR, SMX, and TCN of 81.33 %, 27.08 %, 21.13 %, and 15.44 %, respectively. We applied an extrapolation method to overcome the lack of toxicity data in ecological risk assessment, enhanced the ecological reality of water quality criteria derivation and reduced the uncertainty of risk assessment for antibiotics.