A review on the alternatives to antibiotics and the treatment of antibiotic pollution: Current development and future prospects

Yang, Weiqing; Li, Jing; Yao, Zhiliang; Li, Mi

doi:10.1016/j.scitotenv.2024.171757

Cited by 21 publications

(3 citation statements)

References 189 publications

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“…However, the excessive use of antibiotics causes bacterial drug resistance and antibiotic resistance [3]. In addition to the potential harm caused by antibiotic-resistant bacteria, the one-time or continuous intake of antibiotics beyond the maximum dosage for the human body also brings direct adverse effects and even toxicity to the human body [4]. Nowadays, antibiotic residues in the environment have become a global concern.…”

Section: Introductionmentioning

confidence: 99%

Peroxymonosulfate Activation by Bi-Fe Oxide Co-Doped Graphitic Carbon Nitride for Degradation of Sulfamethoxazole: Performance and Mechanism

Wang,

Liang,

et al. 2024

Applied Sciences

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Graphite carbon nitride (g-C3N4) has been employed as an emerging metal-free catalyst in heterogeneous catalysis. However, the catalyst has a poor activation property for peroxymonosulfate (PMS). In this study, Bi-Fe oxide co-doped g-C3N4 (Bi@Fe/CN) was synthesized for PMS activation to degrade sulfamethoxazole (SMX). In particular, Bi@Fe/CN-3 presented remarkable catalytic performance with 99.7% removal of SMX within 60 min in the PMS system. Additionally, Bi@Fe/CN-3 presented good stability and recyclability through the cycling experiments. Moreover, it was shown that free radicals (O2•−, •OH, and SO4•−) and non-free radicals (1O2) were the primary active species in the Bi@Fe/CN-3/PMS system. Bi, Fe, and surface lattice oxygen were confirmed to be the main contributors to the active species. This work elucidates the mechanism of activation of PMS by Bi@Fe/CN-3, which is beneficial to promote the application of bimetallic oxide-modified g-C3N4/PMS systems in wastewater treatment.

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Section: Introductionmentioning

confidence: 99%

Peroxymonosulfate Activation by Bi-Fe Oxide Co-Doped Graphitic Carbon Nitride for Degradation of Sulfamethoxazole: Performance and Mechanism

Wang,

Liang,

et al. 2024

Applied Sciences

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“…Negative impacts resulting from the presence of drugs in the environment include the development of drug resistance in humans and animals and leading to a loss of antibiotic effectiveness in disease treatment 3 – 5 . Furthermore, there are harms to beneficial microorganisms in aquatic and soil environments, adverse effects on animals and plants, a reduction in soil microbial diversity, and the destruction of agricultural productivity and soil structure 6 . Antibiotics can enter the environment through various avenues, with major contributors being the pharmaceutical industry, improper use in agriculture and livestock, incorrect disposal through municipal waste, and excretion from the human body 7 , 8 .…”

Section: Introductionmentioning

confidence: 99%

Cefixime removal via WO3/Co-ZIF nanocomposite using machine learning methods

Sheikhmohammadi,

Alamgholiloo,

Golaki

et al. 2024

Sci Rep

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In this research, an upgraded and environmentally friendly process involving WO3/Co-ZIF nanocomposite was used for the removal of Cefixime from the aqueous solutions. Intelligent decision-making was employed using various models including Support Vector Regression (SVR), Genetic Algorithm (GA), Artificial Neural Network (ANN), Simulation Optimization Language for Visualized Excel Results (SOLVER), and Response Surface Methodology (RSM). SVR, ANN, and RSM models were used for modeling and predicting results, while GA and SOLVER models were employed to achieve the optimal conditions for Cefixime degradation. The primary goal of applying different models was to achieve the best conditions with high accuracy in Cefixime degradation. Based on R analysis, the quadratic factorial model in RSM was selected as the best model, and the regression coefficients obtained from it were used to evaluate the performance of artificial intelligence models. According to the quadratic factorial model, interactions between pH and time, pH and catalyst amount, as well as reaction time and catalyst amount were identified as the most significant factors in predicting results. In a comparison between the different models based on Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Coefficient of Determination (R2 Score) indices, the SVR model was selected as the best model for the prediction of the results, with a higher R2 Score (0.98), and lower MAE (1.54) and RMSE (3.91) compared to the ANN model. Both ANN and SVR models identified pH as the most important parameter in the prediction of the results. According to the Genetic Algorithm, interactions between the initial concentration of Cefixime with reaction time, as well as between the initial concentration of Cefixime and catalyst amount, had the greatest impact on selecting the optimal values. Using the Genetic Algorithm and SOLVER models, the optimum values for the initial concentration of Cefixime, pH, time, and catalyst amount were determined to be (6.14 mg L−1, 3.13, 117.65 min, and 0.19 g L−1) and (5 mg L−1, 3, 120 min, and 0.19 g L−1), respectively. Given the presented results, this research can contribute significantly to advancements in intelligent decision-making and optimization of the pollutant removal processes from the environment.

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“…Biodegradation appears to be a sustainable option, yet its practical application remains limited by efficiency and scalability issues [ 3 ]. Given the major environmental and health risks posed by antibiotic pollution, especially with the presence of antibiotic residues in aquatic environments, there is an urgent need to develop new, effective pollutant removal technologies [ 4 , 5 , 6 ]. In this context, photocatalytic technology has emerged as a cutting-edge research direction due to its ability to degrade pollutants using visible light.…”

Section: Introductionmentioning

confidence: 99%

Innovative Bi5O7I/MIL-101(Cr) Compounds: A Leap Forward in Photocatalytic Tetracycline Removal

Hong,

Chu,

et al. 2024

IJMS

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In environmental chemistry, photocatalysts for eliminating organic contaminants in water have gained significant interest. Our study introduces a unique heterostructure combining MIL-101(Cr) and bismuth oxyiodide (Bi5O7I). We evaluated this nanostructure’s efficiency in adsorbing and degrading tetracycline (TC) under visible light. The Bi5O7I@MIL-101(Cr) composite, with a surface area of 637 m2/g, prevents self-aggregation seen in its components, enhancing visible light absorption. Its photocatalytic efficiency surpassed Bi5O7I and MIL-101(Cr) by 33.4 and 9.2 times, respectively. Comprehensive analyses, including scanning electron microscopy (SEM) and transmission electron microscopy (TEM), confirmed the successful formation of the heterostructure with defined morphological characteristics. BET analysis demonstrated its high surface area, while X-ray diffraction (XRD) confirmed its crystallinity. Electron spin resonance (ESR) tests showed significant generation of reactive oxygen species (ROS) like h+ and·•O2− under light, crucial for TC degradation. The material maintained exceptional durability over five cycles. Density functional theory (DFT) simulations and empirical investigations revealed a type I heterojunction between Bi5O7I and MIL-101(Cr), facilitating efficient electron–hole pair separation. This study underscores the superior photocatalytic activity and stability of Bi5O7I@MIL-101(Cr), offering insights into designing innovative photocatalysts for water purification.

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A review on the alternatives to antibiotics and the treatment of antibiotic pollution: Current development and future prospects

Cited by 21 publications

References 189 publications

Peroxymonosulfate Activation by Bi-Fe Oxide Co-Doped Graphitic Carbon Nitride for Degradation of Sulfamethoxazole: Performance and Mechanism

Peroxymonosulfate Activation by Bi-Fe Oxide Co-Doped Graphitic Carbon Nitride for Degradation of Sulfamethoxazole: Performance and Mechanism

Cefixime removal via WO3/Co-ZIF nanocomposite using machine learning methods

Innovative Bi5O7I/MIL-101(Cr) Compounds: A Leap Forward in Photocatalytic Tetracycline Removal

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