4.7 Article

Remediation of lignin and its derivatives from pulp and paper industry wastewater by the combination of chemical precipitation and ozonation

期刊

JOURNAL OF HAZARDOUS MATERIALS
卷 169, 期 1-3, 页码 428-434

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.jhazmat.2009.03.152

关键词

Lignin remediation; Chemical precipitation; Ozonation; Biodegradability

资金

  1. Department of Graduate Study and Investigation of the National Polytechnic Institute of Mexico [20070444]
  2. National Counsel of Science and Technology of Mexico-CONACyT [49367]

向作者/读者索取更多资源

In the present work the degradation of the lignin and its derivatives in the residual water of a paper industry by simple ozonation was investigated. The remediation of lignin was realized using the combination of the pre-treatment with chemical precipitation, using concentrated sulfuric acid (97.1%) at the pH 1 and 3, and of the simple ozonation of the filtered residual water at the pH 1. 3, 8 and 12. Since the high residues content (the initial chemical oxygen demand (COD) is 70,000 mg/L) in the experiments the diluted samples (1:10) were used. The previous precipitation has showed a significant effect on the reduction of the COD (77%) and color (96.1%). The sludge precipitated contents sulfolignin, which in the reaction with sulfuric acid was formed. In ozonation of the filtered residual water during 25 min at the pH 1, 3. 8 and 12 the follows by-products were formed: fumaric, maleic, malonic and formic acids. The biodegradability of the treated water in ozonation increases up 0.067-0.29. The effect of the precipitation and the ozonation conditions on the decolorization kinetics was evaluated. (C) 2009 Elsevier B.V. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Automation & Control Systems

Super-twisting-based sliding mode control of drum boiler energy conversion systems

Yazan M. Alsmadi, Imtiaz Ur Rehman, Ali A. Uppal, Vadim Utkin, Isaac Chairez, Mohammed Ibbini

Summary: In this research, super-twisting sliding mode controllers are designed for a drum boiler system to maintain desired water level and pressure, along with a gain-scheduled Utkin observer to estimate unknown states. Rigorous mathematical analysis shows local stability of the closed-loop system, while simulation results demonstrate satisfactory performance even in the presence of uncertainties and disturbances. Quantitative analysis comparing STSMC and PI controllers shows similar control energy consumption but better tracking performance for STSMC.

INTERNATIONAL JOURNAL OF CONTROL (2022)

Article Automation & Control Systems

Output feedback averaged sub-gradient integral sliding mode control to regulate the tridimensional autonomous motion of autonomous submersible vehicles

Alejandra Hernandez-Sanchez, Alexander Poznyak, Olga Andrianova, Isaac Chairez

Summary: This study presents the development of an output feedback control for regulating the movement of autonomous submersible vehicles in the tridimensional space. The proposed controller utilizes the Averaged Sub-Gradient Integral Sliding Mode algorithm and the estimation of translational velocity states by a distributed super-twisting algorithm. The results confirm the effectiveness of the proposed control scheme in guiding the vehicles along the desired trajectory.

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING (2023)

Article Computer Science, Cybernetics

On the dynamic neural network toolbox design for identification, estimation and control

Isaac Chairez, Israel Alejandro Guarneros-Sandoval, Vlad Prud, Olga Andrianova, Sleptsov Ernest, Viktor Chertopolokhov, Grigory Bugriy, Arthur Mukhamedov

Summary: This study introduces a toolbox for dynamic neural network approximation, which can be used for identifying nonlinear systems, nonparametric approximation, state estimation, and automatic control. The toolbox consists of three components: user layer, network manager, and network instance, providing high-level control and monitoring for users.

KYBERNETES (2023)

Article Engineering, Marine

Robust proportional-integral control of submersible autonomous robotized vehicles by backstepping-averaged sub-gradient sliding mode control

Alejandra Hernandez-Sanchez, Alexander Poznyak, Isaac Chairez

Summary: This study introduces a novel robust controller strategy for submersible autonomous robotized vehicles, which improves control effectiveness through optimized trajectory tracking.

OCEAN ENGINEERING (2022)

Article Automation & Control Systems

Output feedback adaptive controller of a autonomous skid-steering mobile vehicle based on sequential super-twisting differentiators

Ruben Fuentes-Alvarez, Isaac Chairez, Kim Adams, Sergio Salazar, Ricardo Lopez-Gutierrez

Summary: The main purpose of this work is to develop an output state-dependent controller that solves the path-tracking deviation error for a skid-steering autonomous vehicle. The controller takes advantage of a nonlinear diffeomorphism that transforms the skid-steering autonomous vehicle into a multi-input multi-output chain of integrators. Through the step-by-step differentiator, the velocity and acceleration of the vehicle are estimated, which are then used in the controller implementation. The adaptive control design based on the estimated states enforces the convergence of the tracking trajectories for the vehicle to the origin.

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING (2023)

Article Engineering, Mechanical

Adaptive proportional derivative decentralized output based controller for a biped robotic device

Isaac Chairez, Yazan Alsmadi, Pamela Vera-Tizatl, Karla Rincon-Martinez

Summary: This paper presents a novel adaptive control method for tracking bioinspired reference trajectories in the context of an exoskeleton robot. The proposed controller adjusts the gains of a state feedback structure using a controlled Lyapunov function and a robust exact differentiator. Simulations demonstrate the controller's efficiency in rejecting external disturbances and uncertainties, as well as achieving a significant power reduction compared to a non-adaptive controller. Experimental evaluation confirms the benefits of the proposed adaptive gain controller in successfully tracking biomechanically inspired reference trajectories, suggesting its potential for rehabilitation purposes.

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART K-JOURNAL OF MULTI-BODY DYNAMICS (2022)

Article Chemistry, Multidisciplinary

Mathematical Modeling and Robust Control of a Restricted State Suspended Biped Robot Implementing Linear Actuators for Articulation Mobilization

Karla Rincon-Martinez, Isaac Chairez, Wen-Yu Liu

Summary: The aim of this study is to develop an adaptive automatic control method for solving the trajectory tracking problem for a biped robotic device (BRD) with linear actuators. The proposed adaptive control form has state-dependent gains and the stability analysis leads to the design of state-dependent adaptive gains based on a controlled Lyapunov function. Numerical simulations validate the effectiveness of the proposed controller.

APPLIED SCIENCES-BASEL (2022)

Article Automation & Control Systems

Cueing end-effector acceleration of a two-link robotic arm by dynamic averaged sub-gradient integral sliding mode control

Alejandra Hernandez-Sanchez, Isaac Chairez, Alexander Poznyak, Olga Andrianova, Viktor Chertopolokhov

Summary: The primary objective of this research is to determine if the dynamic version of an averaged sub-gradient (ASG) integral sliding mode (ISM) controller can effectively handle the end-effector acceleration tracking problem for a two-link robotic arm avoiding singularity conditions. The proposed scheme solves a nonlinear extremum seeking problem that minimizes a non-strictly convex function and allows for the achievement of the necessary ISM regime in the presence of considerable errors in the mathematical model description. A special switch between modes allows the controller to track accelerations even in extreme positions effectively.

ASIAN JOURNAL OF CONTROL (2023)

Review Chemistry, Multidisciplinary

Review on BCI Virtual Rehabilitation and Remote Technology Based on EEG for Assistive Devices

Alicia Guadalupe Lazcano-Herrera, Rita Q. Fuentes-Aguilar, Isaac Chairez, Luz Maria Alonso-Valerdi, Miguel Gonzalez-Mendoza, Mariel Alfaro-Ponce

Summary: Virtual reality is widely used in various industries, including entertainment, communication, and healthcare. In the health industry, virtual reality combined with brain-computer interfaces (BCIs) can provide rehabilitation measures such as remote rehabilitation. This manuscript presents a literature review of studies implementing virtual reality and assistive technologies for remote rehabilitation based on BCIs, aiming to improve the performance of rehabilitation processes.

APPLIED SCIENCES-BASEL (2022)

Article Automation & Control Systems

Trajectory tracking control with state restricted gains for a magnetic pendulum using electromagnetic actuators

Rafael Perez-San Lazaro, Rita Fuentes-Aguilar, Isaac Chairez

Summary: This paper presents an adaptive controller with Barrier Lyapunov Functions (BLF) for a magnetic pendulum with state restrictions. The controller utilizes fixed electromagnets to induce motion on the pendulum and approximate functions to estimate the force between magnetic elements. The effects of state restrictions on the control action are considered based on a control BLF. Simulation and experimental results demonstrate the advantages of employing BLF controllers in mechanical systems with specific boundaries.

ISA TRANSACTIONS (2023)

Article Computer Science, Artificial Intelligence

Rational Continuous Neural Network Identifier for Singular Perturbed Systems With Uncertain Dynamical Models

O. Andrianova, A. Poznyak, R. Q. Fuentes-Aguilar, Isaac Chairez

Summary: This study aims to design a robust nonparametric identifier for singular perturbed systems (SPSs) with uncertain mathematical models. The identifier uses a novel differential neural network (DNN) structure, which takes into account the multirate nature of SPS. A rational form of the DNN and a mixed learning law are proposed to solve the identification of the fast dynamics in SPS. The study also proposes a control Lyapunov function and a nonlinear parameter identification methodology for the design of the learning laws. A complementary matrix inequality-based optimization method is used to obtain the smallest attainable convergence invariant region. A numerical example of an enzymatic-substrate-inhibitor system is provided to demonstrate the application of the DNN identifier. The benefits of using the rational form for the identifier in terms of mean square error (MSE) are highlighted in the comparison with a classical identifier.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2023)

Article Mathematics

Min-Max Dynamic Programming Control for Systems with Uncertain Mathematical Models via Differential Neural Network Bellman's Function Approximation

Alexander Poznyak, Sebastian Noriega-Marquez, Alejandra Hernandez-Sanchez, Mariana Ballesteros-Escamilla, Isaac Chairez

Summary: This research proposes a min-max robust control based on a neural dynamic programming approach using continuous differential neural networks (DNNs). The controller solves the robust optimization of a cost function that depends on the trajectories of a system with uncertain mathematical models. The proposed control is evaluated using a numerical example and shows an optimizing solution based on the DNN approximation.

MATHEMATICS (2023)

Article Biochemistry & Molecular Biology

Machine Learning Algorithms Applied to Predict Autism Spectrum Disorder Based on Gut Microbiome Composition

Juan M. Olaguez-Gonzalez, Isaac Chairez, Luz Breton-Deval, Mariel Alfaro-Ponce

Summary: The application of machine learning in studying the gut microbiome composition for the early diagnosis of autism spectrum disorder (ASD) shows promising results. The use of support vector machines, artificial neural networks, and random forest algorithms yielded a classification accuracy of up to 90%. The analysis also identified less abundant microbial communities as potential important factors in ASD development.

BIOMEDICINES (2023)

Article Computer Science, Artificial Intelligence

Differential Neural Network Identifier for Dynamical Systems With Time-Varying State Constraints

Ilya Nachevsky, Olga Andrianova, Isaac Chairez, Alexander Poznyak

Summary: This study presents a state nonparametric identifier based on neural networks with continuous dynamics and using control barrier Lyapunov functions. The developed learning laws consider the preliminary information of the system states and the state restrictions, improving the identification results without violating the state limits.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2023)

Article Biotechnology & Applied Microbiology

Simultaneous Production of Biohydrogen (bioH2) and Poly-Hydroxy-Alkanoates (PHAs) by a Photoheterotrophic Consortium Bioaugmented with Syntrophomonas wolfei

Axayacatl Gonzalez, Edgar Salgado, Zaira Vanegas, Cristina Nino-Navarro, Omar Cortes, Isaac Chairez, Elvia I. Garcia-Pena

Summary: Mixed cultures are superior to individual strains in the anaerobic fermentation process, as microbial interactions contribute to electron transfer and metabolic efficiency. Synthetic microbial communities achieved higher hydrogen and PHA production rates, utilizing a mixture of organic acids in dark fermentation effluents to produce both metabolites simultaneously.

FERMENTATION-BASEL (2022)

Article Engineering, Environmental

Temperature-modulated sensing characteristics of ultrafine Au nanoparticle-loaded porous ZnO nanobelts for identification and determination of BTEX

Shun-Shun Chen, Xu-Xiu Chen, Tian-Yu Yang, Li Chen, Zheng Guo, Xing-Jiu Huang

Summary: A temperature-modulated sensing strategy was proposed to identify and determine BTEX compounds. Highly effective identification of BTEX was achieved using linear discrimination and convolutional neural network analyses. Additionally, quantitative analysis of concentration was accomplished by establishing the relationship between concentration and response.

JOURNAL OF HAZARDOUS MATERIALS (2024)

Article Engineering, Environmental

Particulate matter-induced metabolic recoding of epigenetics in macrophages drives pathogenesis of chronic obstructive pulmonary disease

Myungkyung Noh, Jeong Yeon Sim, Jisung Kim, Jee Hwan Ahn, Hye-Young Min, Jong-Uk Lee, Jong-Sook Park, Ji Yun Jeong, Jae Young Lee, Shin Yup Lee, Hyo-Jong Lee, Choon-Sik Park, Ho-Young Lee

Summary: This study reveals that chronic exposure to PM induces chronic inflammation and development of COPD by dysregulating NAD+ metabolism and subsequent SIRT1 deficiency in pulmonary macrophages. Activation of SIRT1 by resveratrol effectively mitigates PM-induced inflammation and COPD development. Targeting metabolic and epigenetic reprogramming in macrophages induced by PM is a promising strategy for COPD treatment.

JOURNAL OF HAZARDOUS MATERIALS (2024)

Article Engineering, Environmental

Electrocatalytic degradation of nitrogenous heterocycles on confined particle electrodes derived from ZIF-67

Yu Liu, Linlin Qin, Yiming Qin, Tong Yang, Haoran Lu, Yulong Liu, Qiqi Zhang, Wenyan Liang

Summary: Co/NC/PAC electrode was prepared by compounding ZIF-67 with powder-activated carbon for the electrocatalytic treatment of nitrogen-containing heterocyclic compounds. The degradation efficiency of the four compounds reached 90.2-93.7% under optimal conditions, and the degradation order was pyridazine < pyrimidine < pyrazine < pyridine.

JOURNAL OF HAZARDOUS MATERIALS (2024)

Article Engineering, Environmental

Yttrium speciation variability in bauxite residues of various origins, ages and storage conditions

Julien Couturier, Pierre Tamba Oulare, Blanche Collin, Claire Lallemand, Isabelle Kieffer, Julien Longerey, Perrine Chaurand, Jerome Rose, Daniel Borschneck, Bernard Angeletti, Steven Criquet, Renaud Podor, Hamed Pourkhorsandi, Guilhem Arrachart, Clement Levard

Summary: This study analyzes the properties of bauxite residue samples and explores the influence of bauxite ore origin, storage conditions, and storage time. The results show that the speciation of yttrium is related to the origin of bauxite ore, while no significant variation was observed with storage conditions or aging of the residues.

JOURNAL OF HAZARDOUS MATERIALS (2024)

Article Engineering, Environmental

Trophic transfer and their impact of microplastics on estuarine food chain model

Sakthinarenderan Saikumar, Ravi Mani, Mirunalini Ganesan, Inbakandan Dhinakarasamy, Thavamani Palanisami, Dharani Gopal

Summary: Microplastic contamination in marine ecosystems poses a growing concern due to its trophic transfer and negative effects on marine organisms. This study investigates the transfer and impacts of polystyrene microplastics in an estuarine food chain. The results show that microplastics can be transferred through the food chain, although the transfer rates are low. The exposed organisms exhibit stress responses, suggesting the potential risk of microplastics reaching humans through the food chain.

JOURNAL OF HAZARDOUS MATERIALS (2024)

Review Engineering, Environmental

Antibiotic resistance genes and heavy metals in landfill: A review

Yan-Jiao Li, Ying Yuan, Wen-Bing Tan, Bei-Dou Xi, Hui Wang, Kun-Long Hui, Jia-Bao Chen, Yi-Fan Zhang, Lian-Feng Wang, Ren-Fei Li

Summary: This review investigated and analyzed the distribution, composition, and abundance of heavy metals and antibiotic resistance genes (ARGs) in landfill. The results showed that heavy metals have lasting effects on ARGs, and complexes of heavy metals and organic matter are common in landfill. This study provides a new basis to better understand the horizontal gene transfer (HGT) of ARGs in landfill.

JOURNAL OF HAZARDOUS MATERIALS (2024)

Article Engineering, Environmental

The effect of synthesis conditions on the in situ grown MIL-100(Fe)-chitosan beads: Interplay between structural properties and arsenic adsorption

Jessy Joseph, Ari Vaisanen, Ajay B. Patil, Manu Lahtinen

Summary: Efficient and environmentally friendly porous hybrid adsorbent beads have been developed for the removal of arsenic from drinking water. The structural tuning of the adsorbents has been shown to have a significant impact on their adsorption performance, with high crystallinity leading to increased adsorption capacity and selectivity towards As5+.

JOURNAL OF HAZARDOUS MATERIALS (2024)

Article Engineering, Environmental

Phthalate metabolites in breast milk from mothers in Southern China: Occurrence, temporal trends, daily intake, and risk assessment

Yangyang Liu, Minhua Xiao, Kaiqin Huang, Juntao Cui, Hongli Liu, Yingxin Yu, Shengtao Ma, Xihong Liu, Meiqing Lin

Summary: This study measured the levels of phthalate metabolites in breast milk collected from mothers in southern China. The results showed that phthalates are still prevalent in the region, and breastfeeding contributes to phthalate intake in infants. However, the levels detected do not pose significant health risks to infants based on dietary exposure. The increasing exposure to certain phthalates calls for further research into their sources and potential risks.

JOURNAL OF HAZARDOUS MATERIALS (2024)

Article Engineering, Environmental

Depth significantly affects plastisphere microbial evenness, assembly and co-occurrence pattern but not richness and composition

Zhiqiang Wu, Jianxing Sun, Liting Xu, Hongbo Zhou, Haina Cheng, Zhu Chen, Yuguang Wang, Jichao Yang

Summary: Ocean depth affects microbial diversity, composition, and co-occurrence patterns of microplastic microbial communities. Deterministic processes dominate the assembly of mesopelagic plastisphere microbial communities, while stochastic processes shape the assembly of bathypelagic microbial communities. The relationships between microorganisms in the mesopelagic layer are more complex and stable, with Proteobacteria and Actinobacteriota playing important roles.

JOURNAL OF HAZARDOUS MATERIALS (2024)

Article Engineering, Environmental

Abatement of antibiotics and resistance genes during catalytic ozonation enhanced sludge dewatering process: Synchronized in volume and hazardousness reduction

Tingting Xiao, Renjie Chen, Chen Cai, Shijie Yuan, Xiaohu Dai, Bin Dong, Zuxin Xu

Summary: Based on the efficiency of catalytic ozonation techniques in enhancing sludge dewaterability, this study investigated its effectiveness in simultaneous reduction of antibiotics and antibiotic resistance genes. The results showed that catalytic ozonation conditioning changed the distribution of antibiotics and achieved high degradation rates. It also significantly reduced the abundance of ARGs, inhibited horizontal gene transfer, and decreased the signal transduction of typical ARGs host bacteria.

JOURNAL OF HAZARDOUS MATERIALS (2024)

Article Engineering, Environmental

Unlocking the potential of ferrate(VI) in water treatment: Toward one-step multifunctional solutions

Yang Deng, Xiaohong Guan

Summary: This article discusses two different development approaches for ferrate(VI) technology in water treatment, arguing that process integration is a promising method that can drive technological innovation and revolution in water treatment, achieving higher treatment efficiency, reduced costs and energy consumption, and a smaller physical footprint.

JOURNAL OF HAZARDOUS MATERIALS (2024)

Article Engineering, Environmental

Floating Catalytic Foam with prominent heat-induced convection for the effective photocatalytic removal of antibiotics

Zhe Zhang, Lu Zhang, Zhihao Huang, Yuxin Xu, Qingqing Zhao, Hongju Wang, Meiqing Shi, Xiangnan Li, Kai Jiang, Dapeng Wu

Summary: In this study, a floating catalytic foam was designed and prepared to enhance the mass transfer in immobilized photocatalysts for wastewater treatment. The floating catalytic foam could float on the water surface and establish a temperature gradient, effectively promoting the diffusion and adsorption of target molecules during the photocatalytic process.

JOURNAL OF HAZARDOUS MATERIALS (2024)

Article Engineering, Environmental

Mechanism and synergistic effect of sulfadiazine (SDZ) and cadmium toxicity in spinach (Spinacia oleracea L.) and its alleviation through zinc fortification

Muhammad Nafees, Adiba Khan Sehrish, Sarah Owdah Alomrani, Linlin Qiu, Aasim Saeed, Shoaib Ahmad, Shafaqat Ali, Hongyan Guo

Summary: The accumulation of cadmium and antibiotics in edible plants and fertile soil is a worldwide problem. This study investigated the potential of zinc oxide nanoparticles to alleviate the toxicity of both cadmium and antibiotics and promote spinach growth.

JOURNAL OF HAZARDOUS MATERIALS (2024)

Article Engineering, Environmental

Aminoalkyl organosilicon with dual chemical sites for SO2 absorption and analysis of site-specific absorption entropy and enthalpy

Lurui Wan, Kai Wang, Yuan Chen, Zhiyong Xu, Wenbo Zhao

Summary: In this study, a low viscosity and high thermal stability SO2 absorbent with dual interacting sites was successfully synthesized. The absorbent showed the highest absorption enthalpy change and entropy change values among reported SO2 absorbents, and exhibited lower viscosity and comparable thermal stability to ILs.

JOURNAL OF HAZARDOUS MATERIALS (2024)

Article Engineering, Environmental

Improvement of Fe(III)/percarbonate system by molybdenum powder and tripolyphosphate: Co-catalytic performance, low oxidant consumption, pH-dependent mechanism

Zhengwei Zhou, Guojie Ye, Yang Zong, Zhenyu Zhao, Deli Wu

Summary: This study utilized Mo powder and STPP to enhance the performance of the sodium percarbonate system in pollutant degradation. The presence of Mo and STPP resulted in a higher degradation rate of the model pollutant SMX, with low oxidant consumption. The system generated multiple active species through a series of chain reactions at different pH values, exhibiting excellent performance towards electron-rich pollutants. Furthermore, Mo demonstrated excellent stability and reusability.

JOURNAL OF HAZARDOUS MATERIALS (2024)