This study investigates the use of six plant-based coagulants - , , , , , and for the removal of turbidity from wastewater effluent. The coagulants were characterized using Scanning Electron Microscopy (SEM) to determine morphological structure, X-r...
Mg-modified biochar shows high adsorption performance under weakly acidic and neutral water conditions. However, its phosphate removal efficiency markedly decreases in naturally alkaline wastewater, such as that released in livestock farming (anaerob...
International journal of biological macromolecules
Nov 27, 2024
In this study, a new magnetic biocompatible hydrogel was synthesized as an adsorbent for Deltamethrin pesticide removal. The optimal conditions and adsorption process of Deltamethrin by chitosan/polyacrylic acid/FeO nanocomposite hydrogel was studied...
Wastewater sludges (WSs) are major reservoirs and emission sources of antibiotic resistance genes (ARGs) in cities. Identifying antimicrobial resistance (AMR) host bacteria in WSs is crucial for understanding AMR formation and mitigating biological a...
Due to environmental concerns and economic value, the adsorption process using agricultural wastes is one of the promising methods to remove lead (Pb) from contaminated water. The relationships between agricultural waste properties, adsorption condit...
Anais da Academia Brasileira de Ciencias
Nov 25, 2024
Fixed-bed columns are a well-established water purification technology. Several models have been constructed over the decades to scale up and predict the breakthrough curve of an adsorption column varying the flow rate, length, and initial concentrat...
The contamination of water by arsenic (As) poses a substantial environmental challenge with far-reaching influence on human health. Accurately predicting adsorption capacities of arsenite (As(III)) and arsenate (As(V)) on different materials is cruci...
Accurately predicting drinking water quality is critical for intelligent water supply management and for maintaining the stability and efficiency of water treatment processes. This study presents an optimized time series machine learning approach for...
Interpretable causal machine learning (ICML) was used to predict the performance of denitrification and clarify the relationships between influencing factors and denitrification. Multiple models were examined, and XG-Boost model provided the best pre...
Arsenic, a poisonous and carcinogenic heavy metal in drinking water, presents severe health risks to humans, including skin lesions, neurological damage, and circulatory disorders. Despite extensive research efforts have been carried out on removing ...
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