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http://dx.doi.org/10.1021/acsestwater.4c00641 | DOI Listing |
Adv Mater
January 2025
College of Chemistry and Materials Science, Anhui Normal University, Wuhu, 241002, P. R. China.
The conversion of nitrate-rich wastewater and biomass-derived blocks into high-value products using renewably generated electricity is a promising approach to modulate the artificial carbon and nitrogen cycle. Here, a new synthetic strategy of WO sub-nanoclusters is reported and supported on carbon materials as novel efficient electrocatalysts for nitrate reduction and its coupling with α-keto acids. In acidic solutions, the NH-NHOH selectivity can also optimized by adjusting the potential, with the total FE exceeding 80% over a wide potential range.
View Article and Find Full Text PDFEnviron Res
January 2025
State Key Laboratory of Marine Pollution and Department of Chemistry, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong 999077, China; School of Energy and Environment, City University of Hong Kong, Tat Chee Avenue, Hong Kong Kowloon, 999077, China. Electronic address:
Bisphenol A (BPA) is a commonly used endocrine-disrupting chemical found in high levels in wastewater worldwide. Aerobic denitrification is a promising alternative to conventional nitrogen removal processes. However, the effects of BPA on this novel nitrogen removal process have rarely been reported.
View Article and Find Full Text PDFEnviron Res
January 2025
Department of Chemistry, University college in Al-Jamoum, Umm Al-Qura University, 21955, Makkah, Saudi Arabia.
Accurate quantification of neonicotinoid insecticides is pivotal to ensure environmental safety by examining and mitigating their potential harmful effects on pollinators and aquatic ecosystems. In this scenario, detection of neonicotinoid insecticide, thiamethoxam (TMX), is significant for safeguarding ecological balance and human health. Hence, we developed a highly sensitive electrochemical sensor for detection of TMX in environmental samples, utilizing a novel nanocomposite with superior electrocatalytic properties and integrating an optimized neural network for accurate data analysis.
View Article and Find Full Text PDFEnviron Res
January 2025
Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, Nanjing Forestry University, Nanjing 210037, China; Shandong Huatai Paper Co. Ltd., Dongying 257335, China. Electronic address:
Wastewater treatment systems are essential for sustainable water resource management but face challenges such as equipment and sensor malfunctions, fluctuating influent conditions, and operational disturbances that compromise process stability and detection accuracy. To address these challenges, this paper systematically reviews data-driven fault detection and diagnosis (FDD) methods applied in wastewater treatment systems from 2014 to 2024, focusing on their applications, advancements, and limitations. Main contributions include an overview of key treatment processes, a detailed evaluation of fault types (process and sensor faults), advancements in multivariate statistical methods, machine learning (ML), and hybrid FDD techniques, as well as their effectiveness in anomaly detection, managing complex data distributions, and enabling real-time monitoring.
View Article and Find Full Text PDFBioresour Technol
January 2025
School of Environmental Engineering, Henan University of Technology, Zhengzhou 450001, China; Zhengzhou Key Laboratory of Water Safety and Water Ecology Technology, Zhengzhou 450001, China; Henan International Joint Laboratory of Environmental Pollution Remediation and Grain Quality Security, Zhengzhou 450001, China.
This study integrates partial denitrification/Anammox (PD/A) with hydroxyapatite (HAP) crystallization in a single reactor, achieving simultaneous nitrogen and phosphorus removal along with phosphorus recovery. By adjusting pH, sludge concentration, low COD/TN ratio, and applying moderate dissolved oxygen stress, the system operated stably and promoted the synergistic growth of HAP and biomass. Results showed a nitrogen removal efficiency (NRE) of 94.
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