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Wang X, Chen H, Qian Y, Li X, Li X, Xu X, Wu Y, Zhang W, Xue G. Sludge-derived hydrochar modulates complete nonradical electron transfer in peroxydisulfate activation via pyrrolic-N and carbon defect: Implication for degrading electron-rich ionizable anilines compounds. JOURNAL OF HAZARDOUS MATERIALS 2024; 479:135724. [PMID: 39236539 DOI: 10.1016/j.jhazmat.2024.135724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Revised: 07/28/2024] [Accepted: 08/31/2024] [Indexed: 09/07/2024]
Abstract
Nonradical electron transfer process (ETP) is a promising pathway for pollutant degradation in peroxydisulfate-based advanced oxidation processes (PDS-AOPs). However, there is a critical bottleneck to trigger ETP by sludge-derived hydrochar due to its negatively charged surface, inferior porosity and electrical conductivity. Herein, pyrrolic-N doped and carbon defected sludge-derived hydrochar (SDHC-N) was constructed for PDS activation to degrade anilines ionizable organic compounds (IOC) through complete nonradical ETP oxidation. Degradation of anilines IOC was not only affected by the electron-donating capacity but also proton concentration in solution because of the ionizable amino group (-NH2). Diverse effects including proton favor, insusceptible and inhibition were observed. Impressively, addition of HCO3 with strong proton binding capacity boosted aniline degradation nearly 10 times. Moreover, characterizations and theoretical calculations demonstrated that pyrrolic-N increased electron density and created positively charged surface, profoundly promoting generation of SDHC-N-S2O82-* complexes. More delocalized electrons around carbon defect could enhance electron mobility. This work guides a rational design of sludge-derived hydrochar to mediate nonradical ETP oxidation, and provides insights into the impacts of proton on anilines IOC degradation.
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Affiliation(s)
- Xiaonuan Wang
- College of Environmental Science and Engineering, Donghua University, Shanghai 201620, China
| | - Hong Chen
- College of Environmental Science and Engineering, Donghua University, Shanghai 201620, China
| | - Yajie Qian
- College of Environmental Science and Engineering, Donghua University, Shanghai 201620, China
| | - Xiang Li
- College of Environmental Science and Engineering, Donghua University, Shanghai 201620, China
| | - Xianying Li
- College of Environmental Science and Engineering, Donghua University, Shanghai 201620, China
| | - Xianbao Xu
- College of Environmental Science and Engineering, Donghua University, Shanghai 201620, China
| | - Ying Wu
- College of Environmental Science and Engineering, Donghua University, Shanghai 201620, China
| | - Wenjuan Zhang
- College of Chemistry and Chemical Engineering, Shanghai University of Engineering Science, 201620, China
| | - Gang Xue
- College of Environmental Science and Engineering, Donghua University, Shanghai 201620, China.
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2
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Hou N, Tong Y, Zhou M, Li X, Sun X, Li D. New Strategies for constructing and analyzing semiconductor photosynthetic biohybrid systems based on ensemble Machine learning Models: Visualizing complex mechanisms and yield prediction. BIORESOURCE TECHNOLOGY 2024; 412:131404. [PMID: 39222858 DOI: 10.1016/j.biortech.2024.131404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2024] [Revised: 08/28/2024] [Accepted: 08/30/2024] [Indexed: 09/04/2024]
Abstract
Photosynthetic biohybrid systems (PBSs) composed of semiconductor-microbial hybrids provide a novel approach for converting light into chemical energy. However, comprehending the intricate interactions between materials and microbes that lead to PBSs with high apparent quantum yields (AQY) is challenging. Machine learning holds promise in predicting these interactions. To address this issue, this study employs ensemble learning (ESL) based on Random Forest, Gradient Boosting Decision Tree, and eXtreme Gradient Boosting to predict AQY of PBSs utilizing a dataset comprising 15 influential factors. The ESL model demonstrates exceptional accuracy and interpretability (R2 value of 0.927), offering insights into the impact of these factors on AQY while facilitating the selection of efficient semiconductors. Furthermore, this research propose that efficient charge carrier separation and transfer at the bio-abiotic interface are crucial for achieving high AQY levels. This research provides guidance for selecting semiconductors suitable for productive PBSs while elucidating mechanisms underlying their enhanced efficiency.
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Affiliation(s)
- Ning Hou
- College of Resources and Environment, Northeast Agricultural University, Harbin 150030, Heilongjiang, PR China
| | - Yi Tong
- College of Resources and Environment, Northeast Agricultural University, Harbin 150030, Heilongjiang, PR China
| | - Mingwei Zhou
- College of Resources and Environment, Northeast Agricultural University, Harbin 150030, Heilongjiang, PR China
| | - Xianyue Li
- College of Resources and Environment, Northeast Agricultural University, Harbin 150030, Heilongjiang, PR China
| | - Xiping Sun
- Grainger College of Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61820, USA
| | - Dapeng Li
- College of Resources and Environment, Northeast Agricultural University, Harbin 150030, Heilongjiang, PR China.
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3
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Li H, Guo L, Chen L, Zhang F, Wang W, Lam TKY, Xia Y, Cai Z. Machine learning-assisted optimization of food-grade spirulina cultivation in seawater-based media: From laboratory to large-scale production. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 369:122279. [PMID: 39217904 DOI: 10.1016/j.jenvman.2024.122279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 07/11/2024] [Accepted: 08/15/2024] [Indexed: 09/04/2024]
Abstract
The shortage of food and freshwater sources threatens human health and environmental sustainability. Spirulina grown in seawater-based media as a healthy food is promising and environmentally friendly. This study used three machine learning techniques to identify important cultivation parameters and their hidden interrelationships and optimize the biomass yield of Spirulina grown in seawater-based media. Through optimization of hyperparameters and features, eXtreme Gradient Boosting, along with the recursive feature elimination (RFE) model demonstrated optimal performance and identified 28 important features. Among them, illumination intensity and initial pH value were critical determinants of biomass, which impacted other features. Specifically, high initial pH values (>9.0) mainly increased biomass but also increased nutrient sedimentation and ammonia (NH3) losses. Both batch and continuous additions could decrease nutrient losses by increasing their availability in the seawater-based media. When illumination intensity exceeded 200 μmol photons/m2/s, it amplified the growth of Spirulina by mitigating the light attenuation caused by a high initial inoculum level and counteracted the negative effect of low temperature (<25 °C). In large-scale cultivation, production efficiency would be reduced if illumination was not maintained at a high level. High salinity and sodium bicarbonate (NaHCO3) addition promoted carbohydrate accumulation, but suitable dilution could keep the required protein content in Spirulina with relatively low media and production costs. These findings reveal the interactive influence of cultivation parameters on biomass yield and help us determine the optimal cultivation conditions for large-scale cultivation of Spirulina-based seawater system based on a developed graphical user interface website.
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Affiliation(s)
- Huankai Li
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR China
| | - Lei Guo
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR China; Interdisciplinary Institute of Medical Engineering, Fuzhou University, Fuzhou, 350108, China
| | - Leijian Chen
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR China
| | - Feng Zhang
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR China
| | - Wei Wang
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR China
| | - Thomas Ka-Yam Lam
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR China
| | - Yongjun Xia
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Zongwei Cai
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR China.
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Wang K, Zhao T, Ren NQ, Ho SH. Asymmetric defective sites-mediated high-valent cobalt-oxo species in self-suspension aerogel platform for efficient peroxymonosulfate activation. WATER RESEARCH 2024; 265:122304. [PMID: 39197391 DOI: 10.1016/j.watres.2024.122304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2024] [Revised: 08/10/2024] [Accepted: 08/19/2024] [Indexed: 09/01/2024]
Abstract
The main pressing problems should be solved for heterogeneous catalysts in activation of peroxymonosulfate (PMS) are sluggish mass transfer kinetics and low intrinsic activity. Here, oxygen vacancies (Vo)-rich of Co3O4 nanosheets were anchored on the superficies of spirulina-based reduced graphene oxide-konjac glucomannan (KGM) aerogel (R-Co3O4-x/SRGA). The porous structure and superhydrophilicity conferred by KGM maximized the diffusion and transport of reactant. More interestingly, R-Co3O4-x/SRGA came true self-suspension rather than conventional self-floating without the aid of external force, maximizing space utilization and facilitating catalysts recovery. Anchored R-Co3O4-x nanosheets acted as "engines" to drive the reaction. Density functional theory (DFT) manifested Vo was capable of breaking the symmetry of the electronic structure of Co3O4. The formation of asymmetric active sites (Vo) was revealed to modulate the d-band center, enhanced affinity for PMS, and promoted evolution of high-valent cobalt-oxo (Co(IV)=O) species. R-Co3O4-x/SRGA achieved complete removal of sulfamethoxazole (SMX) within 12 min. Furthermore, R-Co3O4-x/SRGA demonstrated exceptional stability in the presence of various environmental interference factors and continuous flow device. This insightful work cleverly integrates the macroscopic design of structure, and the microscopic regulation of active sites is expected to open up new opportunities for the development of water treatment.
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Affiliation(s)
- Ke Wang
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, 150090, PR China
| | - Tong Zhao
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, 150090, PR China
| | - Nan-Qi Ren
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, 150090, PR China
| | - Shih-Hsin Ho
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, 150090, PR China.
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Zhao J, Zhang S, Zhang X, Zhou W, Zhao Q, Wu F, Xing B. Machine learning and experimentally exploring the controversial role of nitrogen in CO 2 uptake by waste-derived nitrogen-containing porous carbons. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 938:173471. [PMID: 38788946 DOI: 10.1016/j.scitotenv.2024.173471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Revised: 04/27/2024] [Accepted: 05/21/2024] [Indexed: 05/26/2024]
Abstract
Waste-derived nitrogen-containing porous carbons were widely accepted as promising carbon capture materials. However, roles of nitrogen in CO2 uptake were highly controversial, posing a challenge in designing high CO2 uptake porous carbons. Herein, nitrogen-containing species was firstly introduced into machine learning (ML) models to uncover the complex relationship of nitrogen, micropore and CO2 uptake by combining ML models, DFT computations and experiments. The results revealed that micropore volume (Vmicro) was the most important property influencing CO2 uptake, but was not the only determinant factor. Nitrogen-containing species (pyrrolic/pyridonic-N (N5) and pyridinic-N (N6)) rather than total nitrogen content, also played an essential role. On the one hand, they can enhanced CO2 adsorption by Lewis acid-base and hydrogen bonding. On the other hand, they promoted development of micropores by participating in activation reactions. The model further indicated that excessive N5 (>1.5 wt%) or N6 (>1.7 wt%) led to restriction on developments of micropores, which was attributed to enlargement of pore size, collapses or blockage of micropores. The double edged-sword effect of N5 and N6 on changes of microporous structures was responsible for the long-standing controversy over nitrogen. The result was further verified by synthesizing eight porous carbons with different textural and chemical properties. This study provided not only a new perspective for resolving the controversy of nitrogen in CO2 uptake, but also a graphical user interface prediction software meaningful for designing porous carbons.
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Affiliation(s)
- Jingjing Zhao
- Key Laboratory of Pollution Ecology and Environmental Engineering, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Siyu Zhang
- Key Laboratory of Pollution Ecology and Environmental Engineering, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China
| | - Xuejiao Zhang
- Key Laboratory of Pollution Ecology and Environmental Engineering, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China
| | - Wenneng Zhou
- Guangdong Provincial Key Laboratory of Water Quality Improvement and Ecological Restoration for Watersheds, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou 510006, China.
| | - Qing Zhao
- Key Laboratory of Pollution Ecology and Environmental Engineering, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China; National-Regional Joint Engineering Research Center for Soil Pollution Control and Remediation in South China, Guangdong Key Laboratory of Integrated Agro-environmental Pollution Control and Management, Institute of Eco-environmental and Soil Sciences, Guangdong Academy of Sciences, Guangzhou 510650, China; Wuhu Haichuang Environmental Protection Technology Co., Ltd, Wuhu 241000, China.
| | - Fengchang Wu
- Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Baoshan Xing
- Stockbridge School of Agriculture, University of Massachusetts, Amherst, MA 01003, USA
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Zhou T, Shi C, Wang Y, Wang X, Lei Z, Liu X, Wu J, Luo F, Wang L. Progress of metal-loaded biochar-activated persulfate for degradation of emerging organic contaminants. WATER SCIENCE AND TECHNOLOGY : A JOURNAL OF THE INTERNATIONAL ASSOCIATION ON WATER POLLUTION RESEARCH 2024; 90:824-843. [PMID: 39141037 DOI: 10.2166/wst.2024.256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 07/15/2024] [Indexed: 08/15/2024]
Abstract
In recent years, studies on the degradation of emerging organic contaminants by sulfate radical (SO4-·) based advanced oxidation processes (SR-AOPs) have triggered increasing attention. Metal-loaded biochar (Me-BC) can effectively prevent the agglomeration and leaching of transition metals, and its good physicochemical properties and abundant active sites induce outstanding in activating persulfate (PS) for pollutant degradation, which is of great significance in the field of advanced oxidation. In this paper, we reviewed the preparation method and stability of Me-BC, the effect of metal loading on the physicochemical properties of biochar, the pathways of pollutant degradation by Me-BC-activated PS (including free radical pathways: SO4-·, hydroxyl radical (·OH), superoxide radicals (O2-·); non-free radical pathways: singlet oxygen (1O2), direct electron transfer), and discussed the activation of different active sites (including metal ions, persistent free radicals, oxygen-containing functional groups, defective structures, etc.) in the SR-AOPs system. Finally, the prospect was presented for the current research progress of Me-BC in SR-AOPs technology.
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Affiliation(s)
- Tianhong Zhou
- School of Environmental and Municipal Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
| | - Chao Shi
- School of Environmental and Municipal Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China; Eco-Environmental Science Center (Guangdong, Hong-Kong, Macau), Guangzhou 510555, China E-mail:
| | - Yangyang Wang
- Eco-Environmental Science Center (Guangdong, Hong-Kong, Macau), Guangzhou 510555, China; School of Materials and Environmental Engineering, Institute of Urban Ecology and Environment Technology, Shenzhen Polytechnic University, Shenzhen 518055, China
| | - Xiaoshu Wang
- School of Materials and Environmental Engineering, Institute of Urban Ecology and Environment Technology, Shenzhen Polytechnic University, Shenzhen 518055, China
| | - Zhenle Lei
- School of Environmental and Municipal Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
| | - Xunjie Liu
- School of Materials and Environmental Engineering, Institute of Urban Ecology and Environment Technology, Shenzhen Polytechnic University, Shenzhen 518055, China
| | - Jinyu Wu
- School of Materials and Environmental Engineering, Institute of Urban Ecology and Environment Technology, Shenzhen Polytechnic University, Shenzhen 518055, China
| | - Fengxiang Luo
- School of Materials and Environmental Engineering, Institute of Urban Ecology and Environment Technology, Shenzhen Polytechnic University, Shenzhen 518055, China
| | - Lei Wang
- Eco-Environmental Science Center (Guangdong, Hong-Kong, Macau), Guangzhou 510555, China; School of Materials and Environmental Engineering, Institute of Urban Ecology and Environment Technology, Shenzhen Polytechnic University, Shenzhen 518055, China
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7
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Jiang J, Xiang X, Zhou Q, Zhou L, Bi X, Khanal SK, Wang Z, Chen G, Guo G. Optimization of a Novel Engineered Ecosystem Integrating Carbon, Nitrogen, Phosphorus, and Sulfur Biotransformation for Saline Wastewater Treatment Using an Interpretable Machine Learning Approach. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:12989-12999. [PMID: 38982970 DOI: 10.1021/acs.est.4c03160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2024]
Abstract
The denitrifying sulfur (S) conversion-associated enhanced biological phosphorus removal (DS-EBPR) process for treating saline wastewater is characterized by its unique microbial ecology that integrates carbon (C), nitrogen (N), phosphorus (P), and S biotransformation. However, operational instability arises due to the numerous parameters and intricates bacterial interactions. This study introduces a two-stage interpretable machine learning approach to predict S conversion-driven P removal efficiency and optimize DS-EBPR process. Stage one utilized the XGBoost regression model, achieving an R2 value of 0.948 for predicting sulfate reduction (SR) intensity from anaerobic parameters with feature engineering. Stage two involved the CatBoost classification and regression model integrating anoxic parameters with the predicted SR values for predicting P removal, reaching an accuracy of 94% and an R2 value of 0.93, respectively. This study identified key environmental factors, including SR intensity (20-45 mg S/L), influent P concentration (<9.0 mg P/L), mixed liquor volatile suspended solids (MLVSS)/mixed liquor suspended solids (MLSS) ratio (0.55-0.72), influent C/S ratio (0.5-1.0), anoxic reaction time (5-6 h), and MLSS concentration (>6.50 g/L). A user-friendly graphic interface was developed to facilitate easier optimization and control. This approach streamlines the determination of optimal conditions for enhancing P removal in the DS-EBPR process.
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Affiliation(s)
- Jinqi Jiang
- Hubei Key Laboratory of Multi-media Pollution Cooperative Control in Yangtze Basin, School of Environmental Science & Engineering, Huazhong University of Science and Technology (HUST), 1037 Luoyu Road, Wuhan, Hubei 430074, China
- School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Xiang Xiang
- School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Qinhao Zhou
- School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Lichang Zhou
- Hubei Key Laboratory of Multi-media Pollution Cooperative Control in Yangtze Basin, School of Environmental Science & Engineering, Huazhong University of Science and Technology (HUST), 1037 Luoyu Road, Wuhan, Hubei 430074, China
| | - Xinqi Bi
- Hubei Key Laboratory of Multi-media Pollution Cooperative Control in Yangtze Basin, School of Environmental Science & Engineering, Huazhong University of Science and Technology (HUST), 1037 Luoyu Road, Wuhan, Hubei 430074, China
| | - Samir Kumar Khanal
- Department of Molecular Biosciences and Bioengineering, University of Hawai'i at Ma̅noa, 1955 East-West Road, Honolulu, Hawaii 96822, United States
| | - Zongping Wang
- Hubei Key Laboratory of Multi-media Pollution Cooperative Control in Yangtze Basin, School of Environmental Science & Engineering, Huazhong University of Science and Technology (HUST), 1037 Luoyu Road, Wuhan, Hubei 430074, China
| | - Guanghao Chen
- Civil & Environmental Engineering and Hong Kong Branch of the Chinese National Engineering Research Center for Control & Treatment of Heavy Metal Pollution, The Hong Kong University of Science and Technology, Hong Kong 999077, PR China
| | - Gang Guo
- Hubei Key Laboratory of Multi-media Pollution Cooperative Control in Yangtze Basin, School of Environmental Science & Engineering, Huazhong University of Science and Technology (HUST), 1037 Luoyu Road, Wuhan, Hubei 430074, China
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Wang K, Wang R, Zhang S, Wang M, He Z, Chen H, Ho SH. Hollow Nanoreactors Unlock New Possibilities for Persulfate-Based Advanced Oxidation Processes. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024:e2401796. [PMID: 38966879 DOI: 10.1002/smll.202401796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 05/20/2024] [Indexed: 07/06/2024]
Abstract
As a novel type of catalytic material, hollow nanoreactors are expected to bring new development opportunities in the field of persulfate-based advanced oxidation processes due to their peculiar void-confinement, spatial compartmentation, and size-sieving effects. For such materials, however, further clarification on basic concepts and construction strategies, as well as a discussion of the inherent correlation between structure and catalytic activity are still required. In this context, this review aims to provide a state-of-the-art overview of hollow nanoreactors for activating persulfate. Initially, hollow nanoreactors are classified according to the constituent components of the shell structure and their dimensionality. Subsequently, the different construction strategies of hollow nanoreactors are described in detail, while common synthesis methods for these construction strategies are outlined. Furthermore, the most representative advantages of hollow nanoreactors are summarized, and their intrinsic connections to the nanoreactor structure are elucidated. Finally, the challenges and future prospects of hollow nanoreactors are presented.
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Affiliation(s)
- Ke Wang
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, 150040, P. R. China
| | - Rupeng Wang
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, 150040, P. R. China
| | - Shiyu Zhang
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, 150040, P. R. China
| | - Meng Wang
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, 150040, P. R. China
| | - Zixiang He
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, 150040, P. R. China
| | - Honglin Chen
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, 150040, P. R. China
| | - Shih-Hsin Ho
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, 150040, P. R. China
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Kumar V, Sharma N, Panneerselvam B, Dasarahally Huligowda LK, Umesh M, Gupta M, Muzammil K, Zahrani Y, Malmutheibi M. Lignocellulosic biomass for biochar production: A green initiative on biowaste conversion for pharmaceutical and other emerging pollutant removal. CHEMOSPHERE 2024; 360:142312. [PMID: 38761824 DOI: 10.1016/j.chemosphere.2024.142312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 03/25/2024] [Accepted: 05/09/2024] [Indexed: 05/20/2024]
Abstract
Lignocellulosic waste generation and their improper disposal has accelerated the problems associated with increased greenhouse gas emissions and associated environmental pollution. Constructive ways to manage and mitigate the pollution associated with lignocellulosic waste has propelled the research on biochar production using lignocellulose-based substrates. The sustainability of various biochar production technologies in employing lignocellulosic biomass as feedstock for biochar production not only aids in the lignocellulosic biomass valorization but also helps in carbon neutralization and carbon utilization. Functionalization of biochar through various physicochemical methods helps in improving their functional properties majorly by reducing the size of the biochar particles to nanoscale and modifying their surface properties. The usage of engineered biochar as nano adsorbents for environmental applications like dye absorption, removal of organic pollutants and endocrine disrupting compounds from wastewater has been the thrust areas of research in the past few decades. This review presents a comprehensive outlook on the up-to-date research findings related to the production and engineering of biochar from lignocellulosic biomass and their applications in environmental remediation especially with respect to wastewater treatment. Further a detailed discussion on various biochar activation methods and the future scope of biochar research is presented in this review work.
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Affiliation(s)
- Vinay Kumar
- Biomaterials and Tissue Engineering (BITE) Laboratory, Department of Community Medicine, Saveetha Medical College and Hospital, Saveetha Institute of Medical and Technical Sciences (SIMATS), Chennai, Thandalam, 602105, India.
| | - Neha Sharma
- Department of Biochemistry, Saveetha Medical College and Hospital, Saveetha Institute of Medical and Technical Sciences (SIMATS), Chennai, Thandalam, 602105, India
| | - Balamurugan Panneerselvam
- Center of Excellence in Interdisciplinary Research for Sustainable Development, Chulalongkorn University, Bangkok, 10330, Thailand; Department of Community Medicine, Saveetha Medical College, SIMATS, Chennai, 602105, India
| | | | - Mridul Umesh
- Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, 560029, Karnataka, India
| | - Manish Gupta
- Chitkara Centre for Research and Development, Chitkara University, Himachal Pradesh, 174103, India
| | - Khursheed Muzammil
- Department of Public Health, College of Applied Medical Sciences, Khamis Mushait Campus, King Khalid University, Abha, 62561, Saudi Arabia
| | - Yousef Zahrani
- Department of Public Health, College of Applied Medical Sciences, Khamis Mushait Campus, King Khalid University, Abha, 62561, Saudi Arabia
| | - Musa Malmutheibi
- Department of Public Health, College of Applied Medical Sciences, Khamis Mushait Campus, King Khalid University, Abha, 62561, Saudi Arabia
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10
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Wu T, Zhang N, Liu C, Ding C, Zhang P, Hu S, Huang Y, Ge Z, Cui P, Wang Y. Factors driving antimony accumulation in soil-pakchoi and wheat agroecosystems: Insights and predictive models. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 351:124016. [PMID: 38648966 DOI: 10.1016/j.envpol.2024.124016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 11/28/2023] [Accepted: 04/18/2024] [Indexed: 04/25/2024]
Abstract
The accumulation of antimony (Sb) in plants and its potential effects on human health are of increasing concern. Nevertheless, only a few countries or regions have established soil Sb thresholds for agricultural purposes, and soil properties have not been taken into account. This study investigated the accumulation of Sb in the edible parts of pakchoi and wheat grain by adding exogenous Sb to 21 soils with varying properties. The results revealed a positive correlation between bioavailable Sb (Sbava, extracted by 0.1 M K2HPO4) in soil and Sb in the edible parts of pakchoi (R2 = 0.77, p < 0.05) and wheat grain (R2 = 0.54, p < 0.05). Both machine learning and traditional multiple regression analysis indicated Sbava was the most critical feature and the main soil properties that contributed to Sb uptake by pakchoi and wheat were CaCO3 and clay, respectively. The advisory food limits for Sb in pakchoi and wheat were estimated based on health risk assessment, and used to derive soil thresholds for safe pakchoi and wheat production based on Sbtot and Sbava, respectively. These findings hold potential for predicting Sb uptake by crops with different soil properties and informing safe production management strategies.
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Affiliation(s)
- Tongliang Wu
- Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China
| | - Naichi Zhang
- Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Cun Liu
- Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China
| | - Changfeng Ding
- Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China
| | - Peng Zhang
- Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China; Department of Agronomy, Hetao University, Bayannur, 015000, China
| | - Sainan Hu
- Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China
| | - Yihang Huang
- College of Environmental Science and Engineering, Central South University of Forestry and Technology, Changsha, 410004, China
| | - Zixuan Ge
- College of Environmental Science and Engineering, Yangzhou University, Yangzhou, 225009, China
| | - Peixin Cui
- Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China
| | - Yujun Wang
- Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
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11
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Jiang S, Xu W, Xia Q, Yi M, Zhou Y, Shang J, Cheng X. Application of machine learning in the study of cobalt-based oxide catalysts for antibiotic degradation: An innovative reverse synthesis strategy. JOURNAL OF HAZARDOUS MATERIALS 2024; 471:134309. [PMID: 38653133 DOI: 10.1016/j.jhazmat.2024.134309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 04/07/2024] [Accepted: 04/13/2024] [Indexed: 04/25/2024]
Abstract
This study addresses antibiotic pollution in global water bodies by integrating machine learning and optimization algorithms to develop a novel reverse synthesis strategy for inorganic catalysts. We meticulously analyzed data from 96 studies, ensuring quality through preprocessing steps. Employing the AdaBoost model, we achieved 90.57% accuracy in classification and an R²value of 0.93 in regression, showcasing strong predictive power. A key innovation is the Sparrow Search Algorithm (SSA), which optimizes catalyst selection and experimental setup tailored to specific antibiotics. Empirical experiments validated SSA's efficacy, with degradation rates of 94% for Levofloxacin and 97% for Norfloxacin, aligning closely with predictions within a 2% margin of error. This research advances theoretical understanding and offers practical applications in material science and environmental engineering, significantly enhancing catalyst design efficiency and accuracy through the fusion of advanced machine learning techniques and optimization algorithms.
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Affiliation(s)
- Siyuan Jiang
- Key Laboratory for Environmental Pollution Prediction and Control, Gansu Province, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, PR China
| | - Wen Xu
- Key Laboratory for Environmental Pollution Prediction and Control, Gansu Province, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, PR China
| | - Qi Xia
- Key Laboratory for Environmental Pollution Prediction and Control, Gansu Province, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, PR China
| | - Ming Yi
- Key Laboratory for Environmental Pollution Prediction and Control, Gansu Province, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, PR China
| | - Yuerong Zhou
- Key Laboratory for Environmental Pollution Prediction and Control, Gansu Province, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, PR China
| | - Jiangwei Shang
- Key Laboratory for Environmental Pollution Prediction and Control, Gansu Province, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, PR China
| | - Xiuwen Cheng
- Key Laboratory for Environmental Pollution Prediction and Control, Gansu Province, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, PR China.
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12
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Oral B, Coşgun A, Günay ME, Yıldırım R. Machine learning-based exploration of biochar for environmental management and remediation. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 360:121162. [PMID: 38749129 DOI: 10.1016/j.jenvman.2024.121162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 04/30/2024] [Accepted: 05/10/2024] [Indexed: 06/05/2024]
Abstract
Biochar has a wide range of applications, including environmental management, such as preventing soil and water pollution, removing heavy metals from water sources, and reducing air pollution. However, there are several challenges associated with the usage of biochar for these purposes, resulting in an abundance of experimental data in the literature. Accordingly, the purpose of this study is to examine the use of machine learning in biochar processes with an eye toward the potential of biochar in environmental remediation. First, recent developments in biochar utilization for the environment are summarized. Then, a bibliometric analysis is carried out to illustrate the major trends (demonstrating that the top three keywords are heavy metal, wastewater, and adsorption) and construct a comprehensive perspective for future studies. This is followed by a detailed review of machine learning applications, which reveals that adsorption efficiency and capacity are the primary utilization targets in biochar utilization. Finally, a comprehensive perspective is provided for the future. It is then concluded that machine learning can help to detect hidden patterns and make accurate predictions for determining the combination of variables that results in the desired properties which can be later used for decision-making, resource allocation, and environmental management.
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Affiliation(s)
- Burcu Oral
- Department of Chemical Engineering, Boğaziçi University, 34342, Bebek, Istanbul, Turkey
| | - Ahmet Coşgun
- Department of Chemical Engineering, Boğaziçi University, 34342, Bebek, Istanbul, Turkey
| | - M Erdem Günay
- Department of Energy Systems Engineering, Istanbul Bilgi University, 34060, Eyupsultan, Istanbul, Turkey.
| | - Ramazan Yıldırım
- Department of Chemical Engineering, Boğaziçi University, 34342, Bebek, Istanbul, Turkey.
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13
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Cao X, Huang J, Du K, Tian Y, Hu Z, Luo Z, Wang J, Guo Y. Machine-Learning-Assisted Descriptors Identification for Indoor Formaldehyde Oxidation Catalysts. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:8372-8379. [PMID: 38691628 DOI: 10.1021/acs.est.4c01691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2024]
Abstract
The development of highly efficient catalysts for formaldehyde (HCHO) oxidation is of significant interest for the improvement of indoor air quality. Up to 400 works relating to the catalytic oxidation of HCHO have been published to date; however, their analysis for collective inference through conventional literature search is still a challenging task. A machine learning (ML) framework was presented to predict catalyst performance from experimental descriptors based on an HCHO oxidation catalysts database. MnOx, CeO2, Co3O4, TiO2, FeOx, ZrO2, Al2O3, SiO2, and carbon-based catalysts with different promoters were compiled from the literature. Notably, 20 descriptors including reaction catalyst composition, reaction conditions, and catalyst physical properties were collected for data mining (2263 data points). Furthermore, the eXtreme Gradient Boosting algorithm was employed, which successfully predicted the conversion efficiency of HCHO with an R-square value of 0.81. Shapley additive analysis suggested Pt/MnO2 and Ag/Ce-Co3O4 exhibited excellent catalytic performance of HCHO oxidation based on the analysis of the entire database. Validated by experimental tests and theoretical simulations, the key descriptor identified by ML, i.e., the first promoter, was further described as metal-support interactions. This study highlights ML as a useful tool for database establishment and the catalyst rational design strategy based on the importance of analysis between experimental descriptors and the performance of complex catalytic systems.
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Affiliation(s)
- Xinyuan Cao
- College of Chemistry, Central China Normal University, Wuhan, Hubei 430079, P. R. China
| | - Jisi Huang
- College of Chemistry, Central China Normal University, Wuhan, Hubei 430079, P. R. China
| | - Kexin Du
- College of Chemistry, Central China Normal University, Wuhan, Hubei 430079, P. R. China
| | - Yawen Tian
- College of Chemistry, Central China Normal University, Wuhan, Hubei 430079, P. R. China
| | - Zhixin Hu
- College of Chemistry, Central China Normal University, Wuhan, Hubei 430079, P. R. China
| | - Zhu Luo
- College of Chemistry, Central China Normal University, Wuhan, Hubei 430079, P. R. China
| | - Jinlong Wang
- College of Chemistry, Central China Normal University, Wuhan, Hubei 430079, P. R. China
- Wuhan Institute of Photochemistry and Technology, Wuhan, Hubei 430083, P. R. China
- Engineering Research Center of Photoenergy Utilization for Pollution Control and Carbon Reduction, Ministry of Education, Wuhan 430079, P. R. China
| | - Yanbing Guo
- College of Chemistry, Central China Normal University, Wuhan, Hubei 430079, P. R. China
- Wuhan Institute of Photochemistry and Technology, Wuhan, Hubei 430083, P. R. China
- Engineering Research Center of Photoenergy Utilization for Pollution Control and Carbon Reduction, Ministry of Education, Wuhan 430079, P. R. China
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14
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Shi S, Bao J, Guo Z, Han Y, Xu Y, Egbeagu UU, Zhao L, Jiang N, Sun L, Liu X, Liu W, Chang N, Zhang J, Sun Y, Xu X, Fu S. Improving prediction of N 2O emissions during composting using model-agnostic meta-learning. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 922:171357. [PMID: 38431167 DOI: 10.1016/j.scitotenv.2024.171357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 02/24/2024] [Accepted: 02/27/2024] [Indexed: 03/05/2024]
Abstract
Nitrous oxide (N2O) represents a significant environmental challenge as a harmful, long-lived greenhouse gas that contributes to the depletion of stratospheric ozone and exacerbates global anthropogenic greenhouse warming. Composting is considered a promising and economically feasible strategy for the treatment of organic waste. However, recent research indicates that composting is a source of N2O, contributing to atmospheric pollution and greenhouse effect. Consequently, there is a need for the development of effective, cost-efficient methodologies to quantify N2O emissions accurately. In this study, we employed the model-agnostic meta-learning (MAML) method to improve the performance of N2O emissions prediction during manure composting. The highest R2 and lowest root mean squared error (RMSE) values achieved were 0.939 and 18.42 mg d-1, respectively. Five machine learning methods including the backpropagation neural network, extreme learning machine, integrated machine learning method based on ELM and random forest, gradient boosting decision tree, and extreme gradient boosting were adopted for comparison to further demonstrate the effectiveness of the MAML prediction model. Feature analysis showed that moisture content of structure material and ammonium concentration during composting process were the two most significant features affecting N2O emissions. This study serves as proof of the application of MAML during N2O emissions prediction, further giving new insights into the effects of manure material properties and composting process data on N2O emissions. This approach helps determining the strategies for mitigating N2O emissions.
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Affiliation(s)
- Shuai Shi
- College of Resources and Environment, Northeast Agricultural University, Harbin 150030, China
| | - Jiaxin Bao
- College of Resources and Environment, Northeast Agricultural University, Harbin 150030, China
| | - Zhiheng Guo
- College of Resources and Environment, Northeast Agricultural University, Harbin 150030, China
| | - Yue Han
- College of Resources and Environment, Northeast Agricultural University, Harbin 150030, China
| | - Yonghui Xu
- College of Resources and Environment, Northeast Agricultural University, Harbin 150030, China
| | - Ugochi Uzoamaka Egbeagu
- College of Resources and Environment, Northeast Agricultural University, Harbin 150030, China
| | - Liyan Zhao
- College of Resources and Environment, Northeast Agricultural University, Harbin 150030, China
| | - Nana Jiang
- College of Resources and Environment, Northeast Agricultural University, Harbin 150030, China
| | - Lei Sun
- College of Resources and Environment, Northeast Agricultural University, Harbin 150030, China
| | - Xinda Liu
- College of Resources and Environment, Northeast Agricultural University, Harbin 150030, China
| | - Wanying Liu
- College of Resources and Environment, Northeast Agricultural University, Harbin 150030, China
| | - Nuo Chang
- College of Resources and Environment, Northeast Agricultural University, Harbin 150030, China
| | - Jining Zhang
- College of Resources and Environment, Northeast Agricultural University, Harbin 150030, China
| | - Yu Sun
- College of Resources and Environment, Northeast Agricultural University, Harbin 150030, China
| | - Xiuhong Xu
- College of Resources and Environment, Northeast Agricultural University, Harbin 150030, China.
| | - Song Fu
- School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150030, China.
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15
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Yuan X, Suvarna M, Lim JY, Pérez-Ramírez J, Wang X, Ok YS. Active Learning-Based Guided Synthesis of Engineered Biochar for CO 2 Capture. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:6628-6636. [PMID: 38497595 PMCID: PMC11025117 DOI: 10.1021/acs.est.3c10922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/25/2023] [Revised: 02/21/2024] [Accepted: 02/22/2024] [Indexed: 03/19/2024]
Abstract
Biomass waste-derived engineered biochar for CO2 capture presents a viable route for climate change mitigation and sustainable waste management. However, optimally synthesizing them for enhanced performance is time- and labor-intensive. To address these issues, we devise an active learning strategy to guide and expedite their synthesis with improved CO2 adsorption capacities. Our framework learns from experimental data and recommends optimal synthesis parameters, aiming to maximize the narrow micropore volume of engineered biochar, which exhibits a linear correlation with its CO2 adsorption capacity. We experimentally validate the active learning predictions, and these data are iteratively leveraged for subsequent model training and revalidation, thereby establishing a closed loop. Over three active learning cycles, we synthesized 16 property-specific engineered biochar samples such that the CO2 uptake nearly doubled by the final round. We demonstrate a data-driven workflow to accelerate the development of high-performance engineered biochar with enhanced CO2 uptake and broader applications as a functional material.
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Affiliation(s)
- Xiangzhou Yuan
- Ministry
of Education of Key Laboratory of Energy Thermal Conversion and Control,
School of Energy and Environment, Southeast University, Nanjing 210096, China
- Korea
Biochar Research Center, APRU Sustainable Waste Management Program
& Division of Environmental Science and Ecological Engineering, Korea University, Seoul 02841, Republic of Korea
| | - Manu Suvarna
- Institute
for Chemical and Bioengineering, Department of Chemistry and Applied
Biosciences, ETH Zurich, Vladimir-Prelog-Weg 1, 8093 Zurich, Switzerland
| | - Juin Yau Lim
- Korea
Biochar Research Center, APRU Sustainable Waste Management Program
& Division of Environmental Science and Ecological Engineering, Korea University, Seoul 02841, Republic of Korea
| | - Javier Pérez-Ramírez
- Institute
for Chemical and Bioengineering, Department of Chemistry and Applied
Biosciences, ETH Zurich, Vladimir-Prelog-Weg 1, 8093 Zurich, Switzerland
| | - Xiaonan Wang
- Department
of Chemical Engineering, Tsinghua University, Beijing 100084, China
| | - Yong Sik Ok
- Korea
Biochar Research Center, APRU Sustainable Waste Management Program
& Division of Environmental Science and Ecological Engineering, Korea University, Seoul 02841, Republic of Korea
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16
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Peng B, Liao P, Jiang Y. A Meta-Analysis to Revisit the Property-Aggregation Relationships of Carbon Nanomaterials: Experimental Observations versus Predictions of the DLVO Theory. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2024; 40:7127-7138. [PMID: 38512061 DOI: 10.1021/acs.langmuir.4c00274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/22/2024]
Abstract
Contradicting relationships between physicochemical properties of nanomaterials (e.g., size and ζ-potential) and their aggregation behavior have been constantly reported in previous literature, and such contradictions deviate from the predictions of the classic Derjaguin-Landau-Verwey-Overbeek (DLVO) theory. To resolve such controversies, in this work, we employed a meta-analytic approach to synthesize the data from 46 individual studies reporting the critical coagulation concentration (CCC) of two carbon nanomaterials, namely, graphene oxide (GO) and carbon nanotube (CNT). The correlations between CCC and material physicochemical properties (i.e., size, ζ-potential, and surface functionalities) were examined and compared to the theoretical predictions. Results showed that the CCC of electrostatically stabilized carbon nanomaterials increased with decreasing nanomaterial size when their hydrodynamic sizes were smaller than ca. 200 nm. This is qualitatively consistent with the prediction of the DLVO theory but with a smaller threshold size than the predicted 2 μm. Above the threshold size, the material ζ-potential can be correlated to CCC for nanomaterials with moderate/low surface charge, in agreement with the DLVO theory. The correlation was not observed for highly charged nanomaterials because of their underestimated surface potential by the ζ-potential. Furthermore, a correlation between the C/O ratio and CCC was observed, where a lower C/O ratio resulted in a higher CCC. Overall, our findings rationalized the inconsistency between experimental observation and theoretical prediction and provided essential insights into the aggregation behavior of nanomaterials in water, which could facilitate their rational design.
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Affiliation(s)
- Bo Peng
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China
| | - Peng Liao
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, 99 Lingcheng West Road, Guiyang 550081, China
| | - Yi Jiang
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China
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17
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He J, Boersma M, Song Z, Krebsbach S, Fan D, Duin EC, Wang D. Biochar and surfactant synergistically enhanced PFAS destruction in UV/sulfite system at neutral pH. CHEMOSPHERE 2024; 353:141562. [PMID: 38417493 DOI: 10.1016/j.chemosphere.2024.141562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 02/22/2024] [Accepted: 02/24/2024] [Indexed: 03/01/2024]
Abstract
The UV/sulfite-based advanced reduction process (ARP) emerges as an effective strategy to combat per- and polyfluoroalkyl substances (PFAS) pollution in water. Yet, the UV/sulfite-ARP typically operates at highly alkaline conditions (e.g., pH > 9 or even higher) since the generated reductive radicals for PFAS degradation can be quickly sequestered by protons (H+). To overcome the associated challenges, we prototyped a biochar-surfactant-system (BSS) to synergistically enhance PFAS sorption and degradation by UV/sulfite-ARP. The degradation and defluorination efficiencies of perfluorooctanoic acid (PFOA) depended on solution pH, and concentrations of surfactant (cetyltrimethylammonium bromide; CTAB), sulfite, and biochar. At high pH (8-10), adding biochar and BSS showed no or even small inhibitory effect on PFOA degradation, since the degradation efficiencies were already high enough that cannot be differentiated. However, at acidic and neutral pH (6-7), an evident enhancement of PFOA degradation and defluorination efficiencies occurred. This is due to the synergies between biochar and CTAB that create favorable microenvironments for enhanced PFOA sorption and deeper destruction by prolonging the longevity of reductive radicals (e.g., SO3•-), which is less affected by ambient pH conditions. The performance of UV/sulfite/BSS was further optimized and used for the degradation of four PFAS. At the optimal experimental condition, the UV/sulfite/BSS system can completely degrade PFOA with >30% defluorination efficiency for up to five continuous cycles (n = 5). Overall, our BSS provides a cost-effective and sustainable technique to effectively degrade PFAS in water under environmentally relevant pH conditions. The BSS-enabled ARP technique can be easily tied into PFAS treatment train technology (e.g., advanced oxidation process) for more efficient and deeper defluorination of various PFAS in water.
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Affiliation(s)
- Jianzhou He
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn university, Auburn, 36849, United States
| | - Melissa Boersma
- Department of Chemistry and Biochemistry, Auburn university, Auburn, 36849, United States
| | - Ziteng Song
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn university, Auburn, 36849, United States
| | - Samuel Krebsbach
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn university, Auburn, 36849, United States
| | - Dimin Fan
- Geosyntec Consultants, Inc, 10211 Wincopin Circle, 4th Floor, Columbia, 21044, United States
| | - Evert C Duin
- Department of Chemistry and Biochemistry, Auburn university, Auburn, 36849, United States
| | - Dengjun Wang
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn university, Auburn, 36849, United States.
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18
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Jiang BN, Zhang YY, Zhang ZY, Yang YL, Song HL. Tree-structured parzen estimator optimized-automated machine learning assisted by meta-analysis for predicting biochar-driven N 2O mitigation effect in constructed wetlands. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 354:120335. [PMID: 38368804 DOI: 10.1016/j.jenvman.2024.120335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 01/29/2024] [Accepted: 02/08/2024] [Indexed: 02/20/2024]
Abstract
Biochar is a carbon-neutral tool for combating climate change. Artificial intelligence applications to estimate the biochar mitigation effect on greenhouse gases (GHGs) can assist scientists in making more informed solutions. However, there is also evidence indicating that biochar promotes, rather than reduces, N2O emissions. Thus, the effect of biochar on N2O remains uncertain in constructed wetlands (CWs), and there is not a characterization metric for this effect, which increases the difficulty and inaccuracy of biochar-driven alleviation effect projections. Here, we provide new insight by utilizing machine learning-based, tree-structured Parzen Estimator (TPE) optimization assisted by a meta-analysis to estimate the potency of biochar-driven N2O mitigation. We first synthesized datasets that contained 80 studies on global biochar-amended CWs. The mitigation effect size was then calculated and further introduced as a new metric. TPE optimization was then applied to automatically tune the hyperparameters of the built extreme gradient boosting (XGBoost) and random forest (RF), and the optimum TPE-XGBoost obtained adequately achieved a satisfactory prediction accuracy for N2O flux (R2 = 91.90%, RPD = 3.57) and the effect size (R2 = 92.61%, RPD = 3.59). Results indicated that a high influent chemical oxygen demand/total nitrogen (COD/TN) ratio and the COD removal efficiency interpreted by the Shapley value significantly enhanced the effect size contribution. COD/TN ratio made the most and the second greatest positive contributions among 22 input variables to N2O flux and to the effect size that were up to 18% and 14%, respectively. By combining with a structural equation model analysis, NH4+-N removal rate had significant negative direct effects on the N2O flux. This study implied that the application of granulated biochar derived from C-rich feedstocks would maximize the net climate benefit of N2O mitigation driven by biochar for future biochar-based CWs.
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Affiliation(s)
- Bi-Ni Jiang
- School of Environment, Nanjing Normal University, Jiangsu Province Engineering Research Center of Environmental Risk Prevention and Emergency Response Technology, Jiangsu Engineering Lab of Water and Soil Eco-remediation, Wenyuan Road 1, Nanjing 210023, China; Institute of Agricultural Resources and Environment, Jiangsu Academy of Agricultural Sciences, Ministry of Agriculture and Rural Affairs, Liuhe Observation and Experimental Station of National Agro-Environment, Nanjing, 210014, China
| | - Ying-Ying Zhang
- Institute of Agricultural Resources and Environment, Jiangsu Academy of Agricultural Sciences, Ministry of Agriculture and Rural Affairs, Liuhe Observation and Experimental Station of National Agro-Environment, Nanjing, 210014, China
| | - Zhi-Yong Zhang
- Institute of Agricultural Resources and Environment, Jiangsu Academy of Agricultural Sciences, Ministry of Agriculture and Rural Affairs, Liuhe Observation and Experimental Station of National Agro-Environment, Nanjing, 210014, China.
| | - Yu-Li Yang
- School of Environment, Nanjing Normal University, Jiangsu Province Engineering Research Center of Environmental Risk Prevention and Emergency Response Technology, Jiangsu Engineering Lab of Water and Soil Eco-remediation, Wenyuan Road 1, Nanjing 210023, China
| | - Hai-Liang Song
- School of Environment, Nanjing Normal University, Jiangsu Province Engineering Research Center of Environmental Risk Prevention and Emergency Response Technology, Jiangsu Engineering Lab of Water and Soil Eco-remediation, Wenyuan Road 1, Nanjing 210023, China.
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19
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Tan L, Nie Y, Chang H, Zhu L, Guo K, Ran X, Zhong N, Zhong D, Xu Y, Ho SH. Adsorption performance of Ni(II) by KOH-modified biochar derived from different microalgae species. BIORESOURCE TECHNOLOGY 2024; 394:130287. [PMID: 38181998 DOI: 10.1016/j.biortech.2023.130287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 12/28/2023] [Accepted: 12/30/2023] [Indexed: 01/07/2024]
Abstract
Microalgae biochar is potential adsorbents to remove heavy metals from wastewater due to abundant functional groups, high porosity and wide sources, but performance is not fully developed since it depends on microalgae species attributing to distinct morphology and biomass compositions. Here, two microalgae species Chlorella Pyrenoidosa and Scenedesmus Obliquus were used for biochar preparation via KOH-modification, biochar properties and their influences on Ni(II) adsorption were investigated. Ni(II) adsorption performances responding to biochar properties and operating conditions were upgraded via progressive optimization and response surface methodology. Together, adsorption isotherms and kinetics were analyzed to obtain significant factors for Ni(II) removal. As results, 100 % of Ni(II) removal was achieved under 100 mg/L initial Ni(II) concentration as pH was higher than the biochar zero-charge point of 6.87 with low biochar dosage (0.5 g/L), which provides an efficient approach for heavy metal removal from wastewater with microalgae biochar.
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Affiliation(s)
- Ling Tan
- College of Chemistry and Chemical Engineering, Chongqing University of Technology, Chongqing 400054, China; School of Resources & Environmental Science, Hubei Key Laboratory of Biomass-Resources Chemistry and Environmental Biotechnology, Wuhan University, Wuhan 430079, China
| | - Yudong Nie
- College of Chemistry and Chemical Engineering, Chongqing University of Technology, Chongqing 400054, China
| | - Haixing Chang
- School of Resources & Environmental Science, Hubei Key Laboratory of Biomass-Resources Chemistry and Environmental Biotechnology, Wuhan University, Wuhan 430079, China.
| | - Liandong Zhu
- School of Resources & Environmental Science, Hubei Key Laboratory of Biomass-Resources Chemistry and Environmental Biotechnology, Wuhan University, Wuhan 430079, China
| | - Kehong Guo
- College of Chemistry and Chemical Engineering, Chongqing University of Technology, Chongqing 400054, China
| | - Xiongwei Ran
- College of Chemistry and Chemical Engineering, Chongqing University of Technology, Chongqing 400054, China
| | - Nianbing Zhong
- Intelligent Fiber Sensing Technology of Chongqing Municipal Engineering Research Center of Institutions of Higher Education, Chongqing Key Laboratory of Fiber Optic Sensor and Photodetector, Chongqing University of Technology, Chongqing 400054, China
| | - Dengjie Zhong
- College of Chemistry and Chemical Engineering, Chongqing University of Technology, Chongqing 400054, China
| | - Yunlan Xu
- College of Chemistry and Chemical Engineering, Chongqing University of Technology, Chongqing 400054, China
| | - Shih-Hsin Ho
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, Heilongjiang Province 150090, China
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20
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Wang W, Chang JS, Lee DJ. Machine learning applications for biochar studies: A mini-review. BIORESOURCE TECHNOLOGY 2024; 394:130291. [PMID: 38184089 DOI: 10.1016/j.biortech.2023.130291] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 12/20/2023] [Accepted: 12/31/2023] [Indexed: 01/08/2024]
Abstract
Biochar is a promising carbon sink whose application can assist in reducing carbon emissions. Development of this technology currently relies on experimental trials, which are time-consuming and labor-intensive. Machine learning (ML) technology presents a potential solution for streamlining this process. This review summarizes the current research on ML's applications in biochar production, characterization, and applications. It briefly explains commonly used machine learning algorithms and discusses prospects and challenges. A hybrid model that combines ML with mechanism-based analysis could be a future trend, addressing the ML's black-box nature. While biochar studies have adopted ML technology, current works mostly use lab-scale data for model training. Further work is needed to develop ML models based on pilot or industrial-scale data to realize the use of ML techniques for the field application of biochar.
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Affiliation(s)
- Wei Wang
- Department of Chemical Engineering, National Taiwan University, Taipei 106, Taiwan
| | - Jo-Shu Chang
- Research Center for Smart Sustainable Circular Economy, Tunghai University, Taichung 407, Taiwan; Department of Chemical Engineering, National Cheng Kung University, Tainan, Taiwan; Department of Chemical and Materials Engineering, Tunghai University, Taichung 407, Taiwan
| | - Duu-Jong Lee
- Department of Chemical Engineering, National Taiwan University, Taipei 106, Taiwan; Department of Mechanical Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong.
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21
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Zhao W, Hu T, Ma H, Li D, Zhao Q, Jiang J, Wei L. A review of microbial responses to biochar addition in anaerobic digestion system: Community, cellular and genetic level findings. BIORESOURCE TECHNOLOGY 2024; 391:129929. [PMID: 37923231 DOI: 10.1016/j.biortech.2023.129929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 10/11/2023] [Accepted: 10/26/2023] [Indexed: 11/07/2023]
Abstract
The biochar is a well-developed porous material with various excellent properties, that has been proven with excellent ability in anaerobic digestion (AD) efficiency promotion. Current research is usually focused on the macro effects of biochar on AD, while the systematic review about the mechanisms of biochar on microbial behavior are still lacking. This review summarizes the effects and potential mechanisms of biochar on microorganisms in AD systems, and found that biochar addition can provide habitats for microbial colonization, alleviate toxins stress, supply essential nutrients, and accelerate interspecies electron transferring. Moreover, it also improves microbial community diversity, facilitates EPS secretion, enhances functional enzyme activity, promotes functional genes expression, and inhibits the antibiotic resistance genes transformation. Future research directions including biochar targeted design, in-depth microbial mechanisms revelation, and modified model development were suggested, which could promote the widely practical application of of biochar-amended AD technology.
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Affiliation(s)
- Weixin Zhao
- State Key Laboratory of Urban Water Resources and Environment (SKLUWRE), School of Environment, Harbin Institute of Technology, Harbin 150090, China
| | - Tianyi Hu
- State Key Laboratory of Urban Water Resources and Environment (SKLUWRE), School of Environment, Harbin Institute of Technology, Harbin 150090, China
| | - Hao Ma
- State Key Laboratory of Urban Water Resources and Environment (SKLUWRE), School of Environment, Harbin Institute of Technology, Harbin 150090, China
| | - Dan Li
- State Key Laboratory of Urban Water Resources and Environment (SKLUWRE), School of Environment, Harbin Institute of Technology, Harbin 150090, China
| | - Qingliang Zhao
- State Key Laboratory of Urban Water Resources and Environment (SKLUWRE), School of Environment, Harbin Institute of Technology, Harbin 150090, China
| | - Junqiu Jiang
- State Key Laboratory of Urban Water Resources and Environment (SKLUWRE), School of Environment, Harbin Institute of Technology, Harbin 150090, China
| | - Liangliang Wei
- State Key Laboratory of Urban Water Resources and Environment (SKLUWRE), School of Environment, Harbin Institute of Technology, Harbin 150090, China.
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22
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Zhang L, Zhang Q, Wang Y, Cui X, Liu Y, Ruan R, Wu X, Cao L, Zhao L, Zheng H. Preparation and application of metal-modified biochar in the purification of micro-polystyrene polluted aqueous environment. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 347:119158. [PMID: 37804638 DOI: 10.1016/j.jenvman.2023.119158] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 09/15/2023] [Accepted: 09/25/2023] [Indexed: 10/09/2023]
Abstract
Microplastics (MPs) have already spread across the globe and have been found in drinking water and human tissues. This may pose severe threats to human health and water environment. Therefore, this study accurately evaluated the removal effect of metal-modified biochar on polystyrene microplastics (PS-MPs) (1.0 μm) in the water environment using a high-throughput fluorescence quantification method. The results indicated that Fe-modified biochar (FeBC) and Fe/Zn-modified biochar (Fe/ZnBC) had good removal efficiencies for PS-MPs under the dosage of 3 g/L, which were 96.24% and 84.77%, respectively. Although pore effects were observed (such as "stuck", "trapped"), the electrostatic interaction was considered the main mechanism for the adsorption of PS-MPs on metal-modified biochar, whereas the formation of metal-O-PS-MPs may also contribute to the adsorption process. The removal efficiency of PS-MPs by FeBC was significantly reduced under alkaline conditions (pH = 9 and 11) or in the presence of weak acid ions (PO43-, CO32-, HCO3-). A removal efficiency of 72.39% and 78.33% of PS-MPs was achieved from tap water (TW) and lake water (LW) using FeBC when the initial concentration was 20 mg/L. However, FeBC had no removal effect on PS-MPs in biogas slurry (BS) and brewing wastewater (BW) due to the direct competitive adsorption of high concentrations of chemical oxygen demand (COD). The findings of this study highlighted that metal-modified biochar had a potential application in purifying tap water or lake water which contaminated by MPs.
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Affiliation(s)
- Longfei Zhang
- State Key Laboratory of Food Science and Resources, Engineering Research Center for Biomass Conversion, Ministry of Education, Nanchang University, Nanchang, Jiangxi 330047, PR China
| | - Qi Zhang
- State Key Laboratory of Food Science and Resources, Engineering Research Center for Biomass Conversion, Ministry of Education, Nanchang University, Nanchang, Jiangxi 330047, PR China.
| | - Yunpu Wang
- State Key Laboratory of Food Science and Resources, Engineering Research Center for Biomass Conversion, Ministry of Education, Nanchang University, Nanchang, Jiangxi 330047, PR China
| | - Xian Cui
- State Key Laboratory of Food Science and Resources, Engineering Research Center for Biomass Conversion, Ministry of Education, Nanchang University, Nanchang, Jiangxi 330047, PR China
| | - Yuhuan Liu
- State Key Laboratory of Food Science and Resources, Engineering Research Center for Biomass Conversion, Ministry of Education, Nanchang University, Nanchang, Jiangxi 330047, PR China.
| | - Roger Ruan
- Center for Biorefining and Dept. of Bioproducts and Biosystems Engineering, University of Minnesota, Paul 55108, USA
| | - Xiaodan Wu
- State Key Laboratory of Food Science and Resources, Engineering Research Center for Biomass Conversion, Ministry of Education, Nanchang University, Nanchang, Jiangxi 330047, PR China
| | - Leipeng Cao
- State Key Laboratory of Food Science and Resources, Engineering Research Center for Biomass Conversion, Ministry of Education, Nanchang University, Nanchang, Jiangxi 330047, PR China
| | - Lantian Zhao
- Jiangxi Qiangsheng Technology Co., Ltd., Nanchang, Jiangxi 330052, PR China
| | - Hongli Zheng
- State Key Laboratory of Food Science and Resources, Engineering Research Center for Biomass Conversion, Ministry of Education, Nanchang University, Nanchang, Jiangxi 330047, PR China
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23
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Chen Y, Zhao M, Li Y, Liu Y, Chen L, Jiang H, Li H, Chen Y, Yan H, Hou S, Jiang L. Regulation of tourmaline-mediated Fenton-like system by biochar: Free radical pathway to non-free radical pathway. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 344:118497. [PMID: 37413726 DOI: 10.1016/j.jenvman.2023.118497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Revised: 06/13/2023] [Accepted: 06/22/2023] [Indexed: 07/08/2023]
Abstract
The heterogeneous Fenton-like systems induced by Fe-containing minerals have been largely applied for the degradation of organic pollutants. However, few studies have been conducted on biochar (BC) as an additive to Fenton-like systems mediated by iron-containing minerals. In this study, the addition of BC prepared at different temperatures was found to significantly enhance the degradation of contaminants in the tourmaline-mediated Fenton-like system (TM/H2O2) using Rhodamine B (RhB) as the target contaminant. Furthermore, the hydrochloric acid-modified BC prepared at 700 °C (BC700(HCl)) could achieve complete degradation of high concentrations of RhB in the BC700(HCl)/TM/H2O2 system. Free radical quenching experiments showed that TM/H2O2 system removed contaminants mainly mediated by the free radical pathway. After adding BC, the removal of contaminants is mainly mediated by the non-free radical pathway in BC700(HCl)/TM/H2O2 system which was confirmed by the Electron paramagnetic resonance (EPR) experiments and electrochemical impedance spectroscopy (EIS). In addition, BC700(HCl) had broad feasibility in the degradation of other organic pollutants (Methylene Blue (MB) 100%, Methyl Orange (MO) 100%, and tetracycline (TC) 91.47%) in the tourmaline-mediated Fenton-like system. Possible pathways for the degradation of RhB by the BC700(HCl)/TM/H2O2 system were also proposed.
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Affiliation(s)
- Yaoning Chen
- College of Environmental Science and Engineering, Hunan University and Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha, 410082, PR China.
| | - Mengyang Zhao
- College of Environmental Science and Engineering, Hunan University and Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha, 410082, PR China
| | - Yuanping Li
- School of Municipal and Geomatics Engineering, Hunan City University, Yiyang, 413000, China.
| | - Yihuan Liu
- College of Environmental Science and Engineering, Hunan University and Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha, 410082, PR China
| | - Li Chen
- College of Environmental Science and Engineering, Hunan University and Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha, 410082, PR China
| | - Hongjuan Jiang
- College of Environmental Science and Engineering, Hunan University and Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha, 410082, PR China
| | - Hui Li
- State Key Laboratory of Utilization of Woody Oil Resource and Institute of Biological and Environmental Engineering, Hunan Academy of Forestry, Changsha, 410004, China
| | - Yanrong Chen
- School of Resource & Environment, Hunan University of Technology and Business, Changsha, 410205, China
| | - Haoqin Yan
- College of Environmental Science and Engineering, Hunan University and Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha, 410082, PR China
| | - Suzhen Hou
- College of Environmental Science and Engineering, Hunan University and Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha, 410082, PR China
| | - Longbo Jiang
- College of Environmental Science and Engineering, Hunan University and Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha, 410082, PR China
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24
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Yuan X, Cao Y, Li J, Patel AK, Dong CD, Jin X, Gu C, Yip ACK, Tsang DCW, Ok YS. Recent advancements and challenges in emerging applications of biochar-based catalysts. Biotechnol Adv 2023; 67:108181. [PMID: 37268152 DOI: 10.1016/j.biotechadv.2023.108181] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Revised: 05/21/2023] [Accepted: 05/24/2023] [Indexed: 06/04/2023]
Abstract
The sustainable utilization of biochar produced from biomass waste could substantially promote the development of carbon neutrality and a circular economy. Due to their cost-effectiveness, multiple functionalities, tailorable porous structure, and thermal stability, biochar-based catalysts play a vital role in sustainable biorefineries and environmental protection, contributing to a positive, planet-level impact. This review provides an overview of emerging synthesis routes for multifunctional biochar-based catalysts. It discusses recent advances in biorefinery and pollutant degradation in air, soil, and water, providing deeper and more comprehensive information of the catalysts, such as physicochemical properties and surface chemistry. The catalytic performance and deactivation mechanisms under different catalytic systems were critically reviewed, providing new insights into developing efficient and practical biochar-based catalysts for large-scale use in various applications. Machine learning (ML)-based predictions and inverse design have addressed the innovation of biochar-based catalysts with high-performance applications, as ML efficiently predicts the properties and performance of biochar, interprets the underlying mechanisms and complicated relationships, and guides biochar synthesis. Finally, environmental benefit and economic feasibility assessments are proposed for science-based guidelines for industries and policymakers. With concerted effort, upgrading biomass waste into high-performance catalysts for biorefinery and environmental protection could reduce environmental pollution, increase energy safety, and achieve sustainable biomass management, all of which are beneficial for attaining several of the United Nations Sustainable Development Goals (UN SDGs) and Environmental, Social and Governance (ESG).
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Affiliation(s)
- Xiangzhou Yuan
- Ministry of Education of Key Laboratory of Energy Thermal Conversion and Control, School of Energy and Environment, Southeast University, Nanjing 210096, China; Korea Biochar Research Center, APRU Sustainable Waste Management Program & Division of Environmental Science and Ecological Engineering, Korea University, Seoul 02841, Republic of Korea
| | - Yang Cao
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China
| | - Jie Li
- CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Anil Kumar Patel
- Institute of Aquatic Science and Technology, College of Hydrosphere, National Kaohsiung University of Science and Technology, Kaohsiung 81157, Taiwan
| | - Cheng-Di Dong
- Department of Marine Environmental Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 81157, Taiwan
| | - Xin Jin
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China
| | - Cheng Gu
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China
| | - Alex C K Yip
- Department of Chemical and Process Engineering, University of Canterbury, Christchurch, New Zealand
| | - Daniel C W Tsang
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China; Research Centre for Resources Engineering towards Carbon Neutrality, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China.
| | - Yong Sik Ok
- Korea Biochar Research Center, APRU Sustainable Waste Management Program & Division of Environmental Science and Ecological Engineering, Korea University, Seoul 02841, Republic of Korea.
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25
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Hung CM, Chen CW, Huang CP, Dong CD. Effects of pyrolysis conditions and heteroatom modification on the polycyclic aromatic hydrocarbons profile of biochar prepared from sorghum distillery residues. BIORESOURCE TECHNOLOGY 2023:129295. [PMID: 37311529 DOI: 10.1016/j.biortech.2023.129295] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 06/04/2023] [Accepted: 06/06/2023] [Indexed: 06/15/2023]
Abstract
The formation of 2- to 6-ring polycyclic aromatic hydrocarbons (PAHs) in sorghum distillery residue-derived biochar (SDRBC) was evaluated under different thermochemical pyrolysis conditions of carbonization atmosphere (N2 or CO2), temperature (300-900 °C) and doping with nonmetallic elements, i.e., N, B, O, P, N + B, and N + S. The results indicated that without surface modification, PAHs formation was 944 ± 74 ng g-1, the highest level, and 181 ± 16 ng g-1, the lowest level, at 300 °C in N2 and CO2 atmosphere, respectively. Boron doping of SDRBC significantly reduced the PAHs content (by 97%) under N2 at 300 °C. Results demonstrated that boron modified SDRBC exhibited the highest degree of PAH reduction. Combined pyrolysis temperature and atmosphere in addition to heteroatom doping is a robust and viable strategy for efficient suppression of PAHs formation and high-value utilization of pyrolysis products of low carbon footprint.
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Affiliation(s)
- Chang-Mao Hung
- Department of Marine Environmental Engineering, National Kaohsiung University of Science and Technology, Kaohsiung City, Taiwan; Institute of Aquatic Science and Technology, College of Hydrosphere Science, National Kaohsiung University of Science and Technology, Kaohsiung City, Taiwan
| | - Chiu-Wen Chen
- Department of Marine Environmental Engineering, National Kaohsiung University of Science and Technology, Kaohsiung City, Taiwan
| | - Chin-Pao Huang
- Department of Civil and Environmental Engineering, University of Delaware, Newark, USA
| | - Cheng-Di Dong
- Department of Marine Environmental Engineering, National Kaohsiung University of Science and Technology, Kaohsiung City, Taiwan; Institute of Aquatic Science and Technology, College of Hydrosphere Science, National Kaohsiung University of Science and Technology, Kaohsiung City, Taiwan.
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26
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Lin Y, Hao Z, Liu J, Han J, Wang A, Ouyang Q, Fu F. Molecular probing of dissolved organic matter and its transformation in a woolen textile wastewater treatment station. JOURNAL OF HAZARDOUS MATERIALS 2023; 457:131807. [PMID: 37307730 DOI: 10.1016/j.jhazmat.2023.131807] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 05/26/2023] [Accepted: 06/07/2023] [Indexed: 06/14/2023]
Abstract
Woolen textile industry produces enormous wastewater (WTIW) with high pollution loads, and needs to be treated by wastewater treatment stations (WWTS) before centralized treatment. However, WTIW effluent still contains many biorefractory and toxic substances; thus, comprehensive understandings of dissolved organic matter (DOM) of WTIW and its transformation are essential. In this study, total quantity indices, size exclusion chromatography, spectral methods, and Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) were used for comprehensively characterizing DOM and its transformation during full-scale treatments, including influent, regulation pool (RP), flotation pool (FP), up-flow anaerobic sludge bed (UA), anaerobic/oxic (AO) and effluent. DOM in influent featured a large molecular weight (5-17 kDa), toxicity (0.201 HgCl2 mg/L), and a protein content of 338 mg C/L. FP largely removed 5-17 kDa DOM with the formation of 0.45-5 kDa DOM. UA and AO removed 698 and 2042 chemicals, respectively, which were primarily saturated components (H/C > 1.5); however, both UA and AO contributed to the formation of 741 and 1378 stable chemicals, respectively. Good correlations were found among water quality indices and spectral/molecular indices. Our study reveals the molecular composition and transformation of WTIW DOM during treatments and encourages the optimization of the employed processes in WWTS.
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Affiliation(s)
- Yaohui Lin
- Key Laboratory for Analytical Science of Food Safety and Biology of MOE, Fujian Provincial Key Lab of Analysis and Detection for Food Safety, College of Chemistry, Fuzhou University, Fuzhou, Fujian 350116, China; State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, P.O. Box 2871, Beijing 100085, China
| | - Zhineng Hao
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, P.O. Box 2871, Beijing 100085, China.
| | - Jingfu Liu
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, P.O. Box 2871, Beijing 100085, China; School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Jinglong Han
- State Key Laboratory of Urban Water Resource and Environment Harbin Institute of Technology, Shenzhen, China
| | - Aijie Wang
- State Key Laboratory of Urban Water Resource and Environment Harbin Institute of Technology, Shenzhen, China
| | | | - Fengfu Fu
- Key Laboratory for Analytical Science of Food Safety and Biology of MOE, Fujian Provincial Key Lab of Analysis and Detection for Food Safety, College of Chemistry, Fuzhou University, Fuzhou, Fujian 350116, China.
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27
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Pei X, Li T, He Y, Wong PK, Zeng G, Tang Y, Jia X, Peng X. Adsorbed copper on urea modified activated biochar catalyzed H 2O 2 for oxidative degradation of sulfadiazine:Degradation mechanism and toxicity assessment. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 342:118196. [PMID: 37209646 DOI: 10.1016/j.jenvman.2023.118196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 05/07/2023] [Accepted: 05/15/2023] [Indexed: 05/22/2023]
Abstract
The combined pollution of heavy metals and organic compounds usually occurs simultaneously and induces high toxicity. The technology of simultaneous removal of combined pollution is lacking and the removal mechanism is not clear. Sulfadiazine (SD), a widely used antibiotic, was used as a model contaminant. Urea modified sludge-based biochar (USBC) was prepared and used to catalyze H2O2 to remove the combined pollution of Cu2+ and sulfadiazine (SD) without causing secondary pollution. After 2 h, the removal rates of SD and Cu2+ were 100 and 64.8%, respectively. Cu2+ adsorbed on the surface of USBC accelerated the activation of H2O2 by the USBC catalyzed by CO bond to produce hydroxyl radical (•OH) and single oxygen (1O2) to degrade SD. Twenty-three intermediate products were detected, most of which were completely decomposed into CO2 and H2O. The toxicity was significantly reduced in the combined polluted system. This study highlights the potential of the low-cost technology based on sludge reuse and its inherent significance in reducing the toxic risk of combined pollution in the environment.
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Affiliation(s)
- Xiangyang Pei
- School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China; Yellow River Engineering Consulting Co., Ltd, China
| | - Tianyu Li
- School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China
| | - Yuzhe He
- School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China
| | - Po Keung Wong
- School of Life Sciences, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR, China; Institute of Environmental Health and Pollution Control, College of Environmental Science and Engineering, Guangdong University of Technology, Guangzhou 510006, China
| | - Guoqu Zeng
- State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, China
| | - Yetao Tang
- School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China; Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology, Sun Yat-sen University, Guangzhou, China
| | - Xiaoshan Jia
- School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China; Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology, Sun Yat-sen University, Guangzhou, China
| | - Xingxing Peng
- School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China; Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology, Sun Yat-sen University, Guangzhou, China.
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