Fluoroquinolones (FQs) are a class of antibiotics that pose significant environmental and health risks due to their toxicity, persistence, and contribution to antibiotic resistance. Among various removal methods, adsorption using nanomaterials has emerged as an efficient, cost-effective, and reusable approach. This review evaluates the adsorption capabilities of nanoparticles and nanocomposites for FQ removal, focusing on key mechanisms and influential factors. FQs, particularly norfloxacin, are prevalent in aqueous environments, with nanomaterials demonstrating exceptional potential for their removal. The Langmuir isotherm and pseudo-second-order kinetic models best describe the adsorption process. Adsorption of fluoroquinolones (FQs) is influenced by factors such as pH, FQ concentration (20–40 mg/L), adsorbent dose (5–20 g/L), temperature (15–35 °C), contact time (30–180 min), and the presence of competing substances like inorganic salts. Optimal adsorption occurs at pH values between pKa1 and pKa2, where electrostatic interactions are maximized. Adsorption efficiency increases with adsorbent dose up to a threshold, beyond which capacity declines due to site underutilization. Temperature affects adsorption through physisorption and chemisorption, with varying results in different studies. Inorganic salts influence adsorption via electrostatic competition and the salting-out effect. The primary adsorption mechanisms include electrostatic interactions, π–π donor–acceptor interactions, and hydrophobic forces, with electrostatic interactions dominant (72.3% of studies). Nanomaterials exhibit excellent reusability, making them promising for wastewater treatment. Challenges remain, including multi-component adsorption studies, improved regeneration techniques, and understanding environmental impacts. Future research should focus on optimizing nanomaterials for real-world applications, exploring functional groups, and conducting pilot-scale studies.

This study aims to evaluate various waste-to-energy conversion scenarios in terms of their potential to reduce greenhouse gas (GHG) emissions and improve sustainability based on economic and environmental outcomes. To achieve this, a comprehensive waste management model was developed using the system dynamics approach in the Vensim software to predict waste generation and composition and compare pyrolysis, incineration, gasification, and sanitary landfill scenarios with the baseline scenario over 25 years (2025–2050). The analysis of different waste management scenarios highlights the superior performance of pyrolysis in terms of energy recovery, economic profit, GHG emissions reduction, environmental outcomes, and long-term sustainability. Results show that the pyrolysis scenario generates the highest electricity, with a cumulative net electricity output of 10,469 GWh. Although pyrolysis has GHG emissions due to energy consumption and direct process emissions, it results in the largest net reduction in GHG emissions, primarily due to avoided emissions from increased electricity generation, leading to a 346% reduction compared to the baseline scenario. Furthermore, the pyrolysis scenario demonstrates the highest economic profit at 354 million USD and the highest sustainability index (SI) at 499 million USD. The cumulative SI from 2025 to 2050 shows a 503% increase compared to the business-as-usual scenario, highlighting its superior sustainability performance. This study highlights the importance of strategic waste-to-energy planning in reducing GHG emissions and promoting sustainability. It also offers valuable insights for policymakers and researchers, supporting the development of sustainable waste management strategies and effective efforts for climate change mitigation.