Abstract
The growing water demand requires advanced treatment technologies to efficiently remove recalcitrant organic compounds from wastewater for its reuse. This study evaluated and compared the performance of various advanced oxidation processes (AOPs) for total organic carbon (TOC) removal, focusing on UV-based systems. Among the tested methods, UV/PS and UV/TiO2/Persulfate (PS) achieved the highest TOC removal efficiencies of 89.1% and 92.6%, respectively, under optimized conditions. The UV/TiO2/PS process, which combines persulfate activation with TiO2 photocatalysis, demonstrated superior performance under conditions 1 g/L persulfate, 1 g/L TiO2, and 39 W UV output, making it a promising option for wastewater reuse. Non-UV-based AOPs, including US/H2O2 and US/PS, also exhibited high TOC removal efficiencies (87.8% and 81.9%, respectively) due to ultrasonic cavitation. However, their high energy intensity requirements challenges for process scalability. O3/H2O2 achieved moderate efficiency (70.5%), while Fenton-based processes (Fenton and Ultrasound (US)/Fenton) showed lower efficiencies (59.5% and 71.6%) due to their sensitivity to pH conditions. Overall, UV-based systems outperformed others in efficiency and adaptability, with UV/TiO2/PS identified as the most effective for treating recalcitrant pollutants. In the UV/PS and UV/TiO2/PS systems, sulfate ion generation confirmed effective persulfate activation, resulting in sulfate radical formation. Compared to Fenton-based processes, which generate substantial sludge, these systems represent an environmentally favorable alternative.
Key Words
advanced oxidation processes; sustainable waster reuse; total organic carbon removal; persulfate activation; UV-based system; wastewater treatment
Address
Junyoung Park, Sangmin Lee and Gahyeon Jin: Department of Environmental Engineering, Kongju National University, Cheonan 31080, Republic of Korea
Address
Ya-Jun Chen, Yao Pan and Hai-Yin YU: College of Chemistry and Materials Science, Anhui Normal University, 189 Jiuhua Nanlu, Wuhu, Anhui 241002, China
Yi-Kun Wang: College of Chemistry and Materials Science, Anhui Normal University, 189 Jiuhua Nanlu, Wuhu, Anhui 241002, China/ Zhejiang University of Science and Technology, 318 Liuhe road, Hangzhou, Zhejiang, 310023, China
Jin Zhou: Department of Material and Chemical Engineering, Chizhou University, Chizhou 247000, China
Peng-Sheng Miao: Anhui HuaShang Cable Technology Co., Ltd, Bawan industrial Zone, Gaogou Town, Wuwei City, Wuhu City, Anhui Province, 238339, P.R. China
Abstract
A model for water quality index is proposed. This index is based on the input quality variables such as concentration of turbidity, chlorophyll-a, ATP, absorbance at 260 nm and TOC. The index can be used for estimation of water quality before SWRO since the existing water quality metrics such as SDI and its derivatives do not provide reliable estimation for potential fouling. The impact of input variables was approximated by the second order function. The level of impact of input variables (such as concentration of chlorophyll-a; ATP; absorbance; TOC and turbidity) is characterized by weight factors. The target function – Z(X_j) was assumed to be proportional to the probability of membrane fouling that, in turn, proportional to SDI. The target function implies cumulative-composite structure. It includes imbedded sub-models f(X_j) for different fouling factors, X_1-X_5. The proposed model can be applied in different characteristic locations such as seawater intake, the points before and after pretreatment. The developed model can represent mathematical background for the software for monitoring and management of feed water quality in desalination. Individual weight factors and target function in real time can be used as a component in the early warning system.
Key Words
desalination; modelling; reverse osmosis; water quality
Address
Anton Dukhov, Fahed Ebisi, Michael Themel and Sergey Agashichev: R&D Centre, Dubai Electricity and Water Authority, Dubai, P.O. Box 564, UAE
Abstract
This study develops a quantitative structure-property relationship (QSPR) model using a hybrid neural network and particle swarm optimization (PSO) to predict the gas separation performance of 120 polymers of intrinsic microporosity (PIMs). Over 5000 descriptors, including topological, constitutional, functional groups, and geometrical properties, were computed using alvaDesc software. Genetic algorithm optimization combined with partial least squares regression was used to select relevant descriptors for predicting PIM permeability to N2, CH4, and CO2. A hybrid neural network model with particle swarm optimization-based backpropagation (PSO-BP) algorithms was used for permeability prediction, and the results were compared to experimental published data. The PSO-BP model showed promising results, with root mean squared error (RMSE) values of 0.0048, 0.000743, and 0.0045 for CO2, N2, and CH4, permeabilities respectively. Key descriptors for predicting PIM permeability are associated with multiple physicochemical properties, including GATS, 3D Morse, TDB, SpMax, MATS, CATS3D, RDF, and ATS descriptors. CO2 permeability prediction requires more 3D descriptors than N2 and CH4.
Key Words
descriptors; gases; particle swarm optimization-based backpropagation; polymers of intrinsic microporosity; quantitative structure-property relationship
Address
Maroua Henni, Hanaa Hasnaoui and Mohamed Krea: Material and Environmental Laboratory, GPE department, Faculty of Technology, University of Medea 26000, Algeria
Denis Roizard: Laboratoire Reactions et Genie des Procedes – CNRS 7274, Université de Lorraine, ENSIC, 1, rue Grandville – BP 20451, 54001 Nancy Cedex, France
Abstract
The ANAMMOX process offers energy-efficient nitrogen removal but remains vulnerable to biomass loss due to the slow growth of ANAMMOX bacteria. This study evaluated the potential for performance recovery after biomass washout by supplementing with supernatant from a stable ANAMMOX reactor. A 5L reactor experienced intentional Mixed Liquor Suspended Solid(MLVSS) loss and was operated under reduced nitrogen loading. Recovery was initiated by adding 4 L of filtered supernatant. Reactor performance improved rapidly, with MLVSS increasing from 340 mg/L to 590 mg/L and Nitrogen Removal Rate(NRR) from 0.076 to 0.1832 kg-N/m3/day within 8 days. Sponge-type carrier media also showed biomass accumulation. The results suggest that the supernatant contained components that stimulated ANAMMOX activity, enabling fast recovery. Supernatant supplementation may offer a practical strategy for restoring ANAMMOX performance after biomass loss.
Key Words
ANAMMOX; biomass loss; carrier media; MLVSS; restoration
Address
Sungryul Kim and Kyungik Gil: Department of Civil Engineering, Seoul National University of Science and Technology, Nowon-gu, Seoul 01811, South Korea
Woo Hyoung Lee: Department of Civil, Environmental and Construction Engineering, University of Central Florida, Florida 32816, United States of America
