PAPER making! g! FROM THE PUBLISHERS OF PAPER TECHNOLOGY INTERNATIONAL ® Volume 11, Number 1, 2025
Sathyanathan, Environmental Monitoring and Assessment , Vol.197, article number 176, (2025). Papermaking wastewater consists of a sizable amount of industrial wastewater; hence, real-time access to precise and trustworthy effluent indices is crucial. Because wastewater treatment processes are complicated, nonlinear, and time-varying, it is essential to adequately monitor critical quality indices, especially chemical oxygen demand (COD). Traditional models for predicting COD often struggle with sensitivity to parameter tuning and lack interpretability, underscoring the need for improvement in industrial wastewater treatment. In this manuscript, an optimized papermaking wastewater treatment method is proposed that predicts effluent quality using node-level capsule graph neural networks (PWWT-PEQ-NLCGNN). To improve the accuracy of predicting important effluent COD quality indices, the NLCGNN weight parameters are optimized using the hermit crab optimization (HCO) algorithm. The performance of the proposed PWWT-PEQ-NLCGNN technique demonstrated improvements over existing techniques. Specifically, the proposed strategy achieved 30.53%, 23.34%, and 32.64% higher accuracy; 20.53%, 25.34%, and 29.64% higher precision; and 20.53%, 25.34%, and 29.64% higher sensitivity compared to the water quality prediction model using Gaussian process regression based on deep learning for carbon neutrality in papermaking wastewater treatment system (WQP-GPR-DL- CLPWWTS), the prediction of effluent quality in papermaking wastewater treatment processes using dynamic kernel-based extreme learning machine (POEQ-PWWTP- DKBELM), and the quality-related monitoring of papermaking wastewater treatment processes using dynamic multi-block partial least squares (QRM-PWWTP-DMPLS). These results highlight the potential of the PWWT-PEQ-NLCGNN method for enabling timely and accurate monitoring of wastewater treatment processes. “ A critical review on biofuels generation from pulp-paper mill sludge with emphasis on pretreatment methods: renewable energy for environmental sustainability ”, Vineet Kumar, Pradeep Verma, Flávio Augusto de Freitas, Praveen Kumar Srivastava, Amit Vashishth & Juliana Heloisa Pinê Américo Ǧ Pinheiro, BMC Environmental Science , Vol.2, article number 2, (2025). The pulp and paper mills generates substantial amounts of sludge, posing significant environmental challenge. Addressing this issue, this review explores the dual objective of renewable energy generation and mitigating the environmental impact of pulp-paper mill sludge (PPMS), filling a critical gap in the existing literature. PPMS is recognized as a promising source of fermentable sugars, mainly glucose, and holds potential as a feedstock for biorefinery applications to produce various renewable biofuels, such as biomethane, biohydrogen, bioethanol, biobutanol, and biodiesel, using biorefining concepts. These efforts align with the the United Nations Sustainable Development Goals (UN SDGs) by resource recovery and reducing environmental impact. The present article provides insights on renewable energy generation from PPMS. Despite its promise for bioenergy production, numerous bottlenecks have been identified, including high ash content and the presence of toxic inhibitors, such as phenolics, lignin, chlorolignin, and ligno-carbohydrate complexes which impact the hydrolysis of cellulosic fibers and limit the amount of energy recovery. Various pretreatment methods, such as mechanical, thermal, thermochemical, chemo-mechanical, enzymatic, and microbial are emphasized for their ability to enhance sludge solubility by modifying its structure, thereby releasing fermentable sugars. Pretreatment can decrease crystallinity of cellulose, increase accessible surface area, reduce lignin content, and improve bioenergy recovery in the form of oil and gases from PPMS. Finally, the article suggested future research directions in feedstock pretreatment, catalyst development, and optimization of the overall production system. These areas could address existing gaps in the literature and make the process more feasible and practical for real-world applications. In conclusion, bioenergy recovery from PPMS not only helps reduce the demand for fossil fuels in the near future but also
Technical Abstracts
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