Pub Date : 2023-03-23DOI: 10.1080/10643389.2023.2190314
Qinghua Ji, Xiaojie Yu, Li Chen, A. T. Mustapha, C. Okonkwo, Cunshan Zhou, Xianming Liu
Abstract Converting biomass to produce renewable chemicals is one of the significant ways to realize the development of green chemistry and sustainable chemical industry. As the main component of lignocellulosic biomass, lignin is the most abundant natural polyphenol. Its unique phenolic properties and high carbon content make it potentially exploited. Biomass lignin depolymerization can be divided into thermochemical, chemical catalysis, electrocatalysis, and biological depolymerization methods. In this review, the catalytic reaction systems involved in different methods of lignin depolymerization were extensively described from various aspects, and the degradation products and reaction mechanisms were discussed and analyzed. The effects of novel green-deep eutectic solvents on biomass lignin depolymerization were reviewed in particular. Each method of biomass lignin depolymerization has its own advantages and disadvantages. The different sources of biomass lignin should be selected objectively according to its compositional structure, so as to achieve efficient biomass lignin depolymerization. In addition, the challenges and future development prospects of biomass lignin depolymerization were also discussed.
{"title":"Comprehensive depolymerization of lignin from lignocellulosic biomass: A review","authors":"Qinghua Ji, Xiaojie Yu, Li Chen, A. T. Mustapha, C. Okonkwo, Cunshan Zhou, Xianming Liu","doi":"10.1080/10643389.2023.2190314","DOIUrl":"https://doi.org/10.1080/10643389.2023.2190314","url":null,"abstract":"Abstract Converting biomass to produce renewable chemicals is one of the significant ways to realize the development of green chemistry and sustainable chemical industry. As the main component of lignocellulosic biomass, lignin is the most abundant natural polyphenol. Its unique phenolic properties and high carbon content make it potentially exploited. Biomass lignin depolymerization can be divided into thermochemical, chemical catalysis, electrocatalysis, and biological depolymerization methods. In this review, the catalytic reaction systems involved in different methods of lignin depolymerization were extensively described from various aspects, and the degradation products and reaction mechanisms were discussed and analyzed. The effects of novel green-deep eutectic solvents on biomass lignin depolymerization were reviewed in particular. Each method of biomass lignin depolymerization has its own advantages and disadvantages. The different sources of biomass lignin should be selected objectively according to its compositional structure, so as to achieve efficient biomass lignin depolymerization. In addition, the challenges and future development prospects of biomass lignin depolymerization were also discussed.","PeriodicalId":10823,"journal":{"name":"Critical Reviews in Environmental Science and Technology","volume":"53 1","pages":"1866 - 1887"},"PeriodicalIF":12.6,"publicationDate":"2023-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48595865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-23DOI: 10.1080/10643389.2023.2190313
Lang Lei, Ruirui Pang, Zhibang Han, Dong Wu, Bing Xie, Yinglong Su
Abstract With the continuous release into environments, emerging contaminants (ECs) have attracted widespread attention for the potential risks, and numerous studies have been conducted on their identification, environmental behavior bioeffects, and removal. Owing to the superiority of dealing with high-dimensional and unstructured data, a new data-driven approach, machine learning (ML), has been gradually applied in the research of ECs. This review described the fundamental principle, algorithms, and workflow of ML, and summarized advances of ML applications for typical ECs (per- and polyfluoroalkyl substances, nanoparticles, antibiotic resistance genes, endocrine-disrupting chemicals, microplastics, antibiotics, and pharmaceutical and personal care products). ML methods showed practicability, reliability, and effectiveness in predicting or analyzing the occurrence, distribution, bioeffects, and removal of ECs, and various algorithms and derived models were developed and optimized to obtain better performance. Moreover, the size and homogeneity of the data set strongly influence the application of ML, and choosing the appropriate ML models with different characteristics is crucial for addressing specific problems related to the data sets. Future efforts should focus on improving the quality of data set and adopting more advanced algorithms, developing the potential of quantitative structure-activity relationship, and promoting the applicability domains and interpretability of models. In addition, the development of codeless ML tools will benefit the accessibility of ML models. Graphical abstract
{"title":"Current applications and future impact of machine learning in emerging contaminants: A review","authors":"Lang Lei, Ruirui Pang, Zhibang Han, Dong Wu, Bing Xie, Yinglong Su","doi":"10.1080/10643389.2023.2190313","DOIUrl":"https://doi.org/10.1080/10643389.2023.2190313","url":null,"abstract":"Abstract With the continuous release into environments, emerging contaminants (ECs) have attracted widespread attention for the potential risks, and numerous studies have been conducted on their identification, environmental behavior bioeffects, and removal. Owing to the superiority of dealing with high-dimensional and unstructured data, a new data-driven approach, machine learning (ML), has been gradually applied in the research of ECs. This review described the fundamental principle, algorithms, and workflow of ML, and summarized advances of ML applications for typical ECs (per- and polyfluoroalkyl substances, nanoparticles, antibiotic resistance genes, endocrine-disrupting chemicals, microplastics, antibiotics, and pharmaceutical and personal care products). ML methods showed practicability, reliability, and effectiveness in predicting or analyzing the occurrence, distribution, bioeffects, and removal of ECs, and various algorithms and derived models were developed and optimized to obtain better performance. Moreover, the size and homogeneity of the data set strongly influence the application of ML, and choosing the appropriate ML models with different characteristics is crucial for addressing specific problems related to the data sets. Future efforts should focus on improving the quality of data set and adopting more advanced algorithms, developing the potential of quantitative structure-activity relationship, and promoting the applicability domains and interpretability of models. In addition, the development of codeless ML tools will benefit the accessibility of ML models. Graphical abstract","PeriodicalId":10823,"journal":{"name":"Critical Reviews in Environmental Science and Technology","volume":"53 1","pages":"1817 - 1835"},"PeriodicalIF":12.6,"publicationDate":"2023-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43204347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-09DOI: 10.1080/10643389.2023.2183700
Li Chen, Fayuan Wang, Zhiqing Zhang, Herong Chao, Haoran He, Weifang Hu, Yifeng Zeng, Chengjiao Duan, Ji Liu, Linchuan Fang
Abstract Soil pollution from potentially toxic elements (PTEs) is a serious environmental issue worldwide that affects agricultural safety and human health. Arbuscular mycorrhizal fungi (AMF), as ecosystem engineers, can alleviate PTE toxicity in crop plants. However, the comprehensive effects of AMF on crop performance in PTE-contaminated soils have not yet been recognized globally. Here, a meta-analysis of 153 studies with 3213 individual observations was conducted to evaluate the effects of AMF on the growth and PTE accumulation of five staple crops (wheat, rice, maize, soybean, and sorghum) in contaminated soils. Our results demonstrated that AMF had strong positive effects on the shoot and root biomass. This is because AMF can effectively alleviate oxidative damage induced by PTEs by stimulating photosynthesis, promoting nutrition, and activating non-enzymatic and enzymatic defense systems in crop plants. AMF also decreased shoot PTE accumulation by 23.6% and increased root PTE accumulation by 0.8%, demonstrating that AMF effectively inhibited the PTE transfer and uptake by crop shoot. Meanwhile, AMF-mediated effects on shoot PTE accumulation were weaker in soils with pH > 7.5. Overall, this global survey has essential implications on the ability of AMF to enhance crop performance in PTE-contaminated soils and provides insights into the guidelines for safe agricultural production worldwide. Graphical abstract
{"title":"Influences of arbuscular mycorrhizal fungi on crop growth and potentially toxic element accumulation in contaminated soils: A meta-analysis","authors":"Li Chen, Fayuan Wang, Zhiqing Zhang, Herong Chao, Haoran He, Weifang Hu, Yifeng Zeng, Chengjiao Duan, Ji Liu, Linchuan Fang","doi":"10.1080/10643389.2023.2183700","DOIUrl":"https://doi.org/10.1080/10643389.2023.2183700","url":null,"abstract":"Abstract Soil pollution from potentially toxic elements (PTEs) is a serious environmental issue worldwide that affects agricultural safety and human health. Arbuscular mycorrhizal fungi (AMF), as ecosystem engineers, can alleviate PTE toxicity in crop plants. However, the comprehensive effects of AMF on crop performance in PTE-contaminated soils have not yet been recognized globally. Here, a meta-analysis of 153 studies with 3213 individual observations was conducted to evaluate the effects of AMF on the growth and PTE accumulation of five staple crops (wheat, rice, maize, soybean, and sorghum) in contaminated soils. Our results demonstrated that AMF had strong positive effects on the shoot and root biomass. This is because AMF can effectively alleviate oxidative damage induced by PTEs by stimulating photosynthesis, promoting nutrition, and activating non-enzymatic and enzymatic defense systems in crop plants. AMF also decreased shoot PTE accumulation by 23.6% and increased root PTE accumulation by 0.8%, demonstrating that AMF effectively inhibited the PTE transfer and uptake by crop shoot. Meanwhile, AMF-mediated effects on shoot PTE accumulation were weaker in soils with pH > 7.5. Overall, this global survey has essential implications on the ability of AMF to enhance crop performance in PTE-contaminated soils and provides insights into the guidelines for safe agricultural production worldwide. Graphical abstract","PeriodicalId":10823,"journal":{"name":"Critical Reviews in Environmental Science and Technology","volume":"53 1","pages":"1795 - 1816"},"PeriodicalIF":12.6,"publicationDate":"2023-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48286578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-06DOI: 10.1080/10643389.2023.2183699
Henry C. Croll, Kaoru Ikuma, S. Ong, S. Sarkar
Abstract Wastewater treatment process control optimization is a complex task in a highly nonlinear environment. Reinforcement learning (RL) is a machine learning technique that stands out for its ability to perform better than human operators for certain high-dimensional, complex decision-making problems, making it an ideal candidate for wastewater treatment process control optimization. However, while RL control optimization strategies have shown potential to provide operational cost savings and effluent quality improvements, RL has proven slow to be adopted among environmental engineers. This review provides an overview of existing RL applications for wastewater treatment control optimization found in literature and evaluates five key challenges that must be addressed prior to widespread adoption: practical RL implementation, managing data, integrating existing process models, building trust in empirical control strategies, and bridging gaps in professional training. Finally, this review discusses potential paths forward to addressing each key challenge, including leveraging soft sensing to improve online data collection, working with process engineers to integrate RL programming with existing industry software, utilizing supervised training to build expert knowledge into the RL agent, and focusing research efforts on known scenarios such as the Benchmark Simulation Model No. 1 to build a robust database of RL agent control optimization results. GRAPHICAL ABSTRACT
摘要污水处理过程控制优化是一个高度非线性环境下的复杂任务。强化学习（RL）是一种机器学习技术，它能够在某些高维、复杂的决策问题上比人类操作员表现得更好，是废水处理过程控制优化的理想候选者。然而，尽管RL控制优化策略已显示出节省运营成本和改善出水质量的潜力，但事实证明，RL在环境工程师中的应用进展缓慢。这篇综述概述了文献中现有的RL在废水处理控制优化中的应用，并评估了在广泛采用之前必须解决的五个关键挑战：实际的RL实施、数据管理、集成现有的过程模型、在经验控制策略中建立信任，以及弥合专业培训中的差距。最后，这篇综述讨论了解决每一个关键挑战的潜在途径，包括利用软测量改进在线数据收集，与流程工程师合作将RL编程与现有行业软件集成，利用监督培训将专家知识构建到RL代理中，并将研究重点放在已知场景上，如Benchmark Simulation Model No.1，以建立RL agent控制优化结果的鲁棒数据库。图形摘要
{"title":"Reinforcement learning applied to wastewater treatment process control optimization: Approaches, challenges, and path forward","authors":"Henry C. Croll, Kaoru Ikuma, S. Ong, S. Sarkar","doi":"10.1080/10643389.2023.2183699","DOIUrl":"https://doi.org/10.1080/10643389.2023.2183699","url":null,"abstract":"Abstract Wastewater treatment process control optimization is a complex task in a highly nonlinear environment. Reinforcement learning (RL) is a machine learning technique that stands out for its ability to perform better than human operators for certain high-dimensional, complex decision-making problems, making it an ideal candidate for wastewater treatment process control optimization. However, while RL control optimization strategies have shown potential to provide operational cost savings and effluent quality improvements, RL has proven slow to be adopted among environmental engineers. This review provides an overview of existing RL applications for wastewater treatment control optimization found in literature and evaluates five key challenges that must be addressed prior to widespread adoption: practical RL implementation, managing data, integrating existing process models, building trust in empirical control strategies, and bridging gaps in professional training. Finally, this review discusses potential paths forward to addressing each key challenge, including leveraging soft sensing to improve online data collection, working with process engineers to integrate RL programming with existing industry software, utilizing supervised training to build expert knowledge into the RL agent, and focusing research efforts on known scenarios such as the Benchmark Simulation Model No. 1 to build a robust database of RL agent control optimization results. GRAPHICAL ABSTRACT","PeriodicalId":10823,"journal":{"name":"Critical Reviews in Environmental Science and Technology","volume":"53 1","pages":"1775 - 1794"},"PeriodicalIF":12.6,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43382476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1080/10643389.2023.2181620
Benjamin C. Davis, Connor L. Brown, Suraj Gupta, Jeannette Calarco, Krista Liguori, Erin Milligan, V. Harwood, A. Pruden, Ishi Keenum
Abstract Shotgun metagenomic sequencing of the collective genomic information carried across microbial communities is emerging as a powerful approach for monitoring antibiotic resistance in environmental matrices. Metagenomics is advantageous in that known and putative antibiotic resistance genes (ARGs) (i.e., the resistome) can be screened simultaneously without a priori selection of targets. Additionally, as new ARGs are discovered and catalogued, stored sequencing data can be reanalyzed to assess the prevalence of emerging genes or pathogens. However, best practices for metagenomic data generation and processing are needed to support comparability across space and time. To support reproducible downstream analysis, guidance is first needed with respect to sampling design, sample preservation and storage, DNA extraction, library preparation, sequencing depth, and experimental controls. Here we conducted a systematic review to assess current practices for the application of metagenomics for AR profiling of wastewater, recycled water, and surface water and to offer recommendations to support comparability in the collection, production, and analysis of resulting data. Based on integrated analysis of findings and data reported across 95 articles identified, a field to benchtop metagenomic workflow is discussed for optimizing the representativeness and comparability of generated data. Through the reanalysis of 1474 publicly-available metagenomes, appropriate sequencing depths per environment and uniform normalization strategies are provided. Further, there is opportunity to harness the quantitative capacity of metagenomics more overtly through inclusion of sequencing controls. The recommendations will amplify the overall value of the metagenomic data generated to support within and between study comparisons, now and in the future. Graphical Abstract
{"title":"Recommendations for the use of metagenomics for routine monitoring of antibiotic resistance in wastewater and impacted aquatic environments","authors":"Benjamin C. Davis, Connor L. Brown, Suraj Gupta, Jeannette Calarco, Krista Liguori, Erin Milligan, V. Harwood, A. Pruden, Ishi Keenum","doi":"10.1080/10643389.2023.2181620","DOIUrl":"https://doi.org/10.1080/10643389.2023.2181620","url":null,"abstract":"Abstract Shotgun metagenomic sequencing of the collective genomic information carried across microbial communities is emerging as a powerful approach for monitoring antibiotic resistance in environmental matrices. Metagenomics is advantageous in that known and putative antibiotic resistance genes (ARGs) (i.e., the resistome) can be screened simultaneously without a priori selection of targets. Additionally, as new ARGs are discovered and catalogued, stored sequencing data can be reanalyzed to assess the prevalence of emerging genes or pathogens. However, best practices for metagenomic data generation and processing are needed to support comparability across space and time. To support reproducible downstream analysis, guidance is first needed with respect to sampling design, sample preservation and storage, DNA extraction, library preparation, sequencing depth, and experimental controls. Here we conducted a systematic review to assess current practices for the application of metagenomics for AR profiling of wastewater, recycled water, and surface water and to offer recommendations to support comparability in the collection, production, and analysis of resulting data. Based on integrated analysis of findings and data reported across 95 articles identified, a field to benchtop metagenomic workflow is discussed for optimizing the representativeness and comparability of generated data. Through the reanalysis of 1474 publicly-available metagenomes, appropriate sequencing depths per environment and uniform normalization strategies are provided. Further, there is opportunity to harness the quantitative capacity of metagenomics more overtly through inclusion of sequencing controls. The recommendations will amplify the overall value of the metagenomic data generated to support within and between study comparisons, now and in the future. Graphical Abstract","PeriodicalId":10823,"journal":{"name":"Critical Reviews in Environmental Science and Technology","volume":"53 1","pages":"1731 - 1756"},"PeriodicalIF":12.6,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45048574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-24DOI: 10.1080/10643389.2023.2183072
P. Lei, Ri Yu, Yaqi Kong, S. Bertilsson, M. Tsui, Tao Jiang, Jiating Zhao, Yurong Liu, Rinklebe Joerg, Huan Zhong
Abstract Distinguishing the respective contributions of various microbes to methylmercury (MeHg) production is critical for predicting MeHg bioaccumulation and exposure risk. Metabolic inhibitors have been commonly used to block the activity of specific microbial groups and identify primary Hg methylating microbes. By reviewing literatures and our empirical data, we demonstrate how multiple factors, including (1) the addition of inappropriate amounts of inhibitors, (2) a tendency to overlook microbial syntrophy, and (3) the absence of comprehensive proxy systems of Hg methylation, would impact result interpretation of this approach. We thus suggest that the design of inhibition assays should consider the environmental properties, e.g., background levels of electron acceptors, concentrations of metabolic substrates, and abundances of Hg methylating microbes. We also recommend that inhibitors should be added at multiple concentrations and that observed changes in Hg methylation should be assessed with comprehensive indicators. Revealing the key factors responsible for the improper usage of this method and inadequate interpretation of the results would help optimize inhibition assays for robust predictions of MeHg production in nature. Graphical Abstract
{"title":"Properly interpret metabolic inhibition results to identify primary mercury methylating microbes","authors":"P. Lei, Ri Yu, Yaqi Kong, S. Bertilsson, M. Tsui, Tao Jiang, Jiating Zhao, Yurong Liu, Rinklebe Joerg, Huan Zhong","doi":"10.1080/10643389.2023.2183072","DOIUrl":"https://doi.org/10.1080/10643389.2023.2183072","url":null,"abstract":"Abstract Distinguishing the respective contributions of various microbes to methylmercury (MeHg) production is critical for predicting MeHg bioaccumulation and exposure risk. Metabolic inhibitors have been commonly used to block the activity of specific microbial groups and identify primary Hg methylating microbes. By reviewing literatures and our empirical data, we demonstrate how multiple factors, including (1) the addition of inappropriate amounts of inhibitors, (2) a tendency to overlook microbial syntrophy, and (3) the absence of comprehensive proxy systems of Hg methylation, would impact result interpretation of this approach. We thus suggest that the design of inhibition assays should consider the environmental properties, e.g., background levels of electron acceptors, concentrations of metabolic substrates, and abundances of Hg methylating microbes. We also recommend that inhibitors should be added at multiple concentrations and that observed changes in Hg methylation should be assessed with comprehensive indicators. Revealing the key factors responsible for the improper usage of this method and inadequate interpretation of the results would help optimize inhibition assays for robust predictions of MeHg production in nature. Graphical Abstract","PeriodicalId":10823,"journal":{"name":"Critical Reviews in Environmental Science and Technology","volume":"53 1","pages":"1757 - 1773"},"PeriodicalIF":12.6,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48095496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-23DOI: 10.1080/10643389.2023.2180285
Litao Wang, Xuran Du, Y. Li, Yuhong Bai, Teng Tang, Jing-guo Wu, Hong Liang, Dawen Gao
Abstract Removing recalcitrant organic contaminants from the soil via sustainable and environmentally friendly technologies are essential for environment and human health. Microbial enzyme is a promising biocatalyst, particularly in environmental bioremediation. To improve their stability and catalytic ability, enzymes are often immobilized on supporting materials. Nevertheless, the most appropriate immobilization technology and supporting materials must be selected in advance to achieve high eco-remediation efficiency. This review highlighted the recent advances and provided the future perspectives of immobilization techniques and supporting materials, with particular attention on ensuring basic features and possibilities of immobilized enzymes for eco-remediation of organic contaminated soil. The bioavailability, biodegradability and high cost of immobilized carriers have limited their industrial application and commercialization in remediation of organic contaminated soil, which was hereby thoroughly reviewed. Finally, future directions, including minimizing enzyme production costs, inexpensive and scalable immobilization carriers, and methods, were highlighted to offer new perspectives on the eco-remediation of organic contaminated soil. HIGHLIGHTS Immobilized approaches and carriers were classified and introduced. Immobilized enzymes have tremendous potential in soil eco-remediation. The main mechanism for soil remediation is the presence of a suitable microenvironment. Bioavailability, high cost and accessibility limited the large-scale applications. Future directions for soil eco-remediation with enzyme immobilization were proposed. GRAPHICAL ABSTRACT
{"title":"Enzyme immobilization as a sustainable approach toward ecological remediation of organic-contaminated soils: Advances, issues, and future perspectives","authors":"Litao Wang, Xuran Du, Y. Li, Yuhong Bai, Teng Tang, Jing-guo Wu, Hong Liang, Dawen Gao","doi":"10.1080/10643389.2023.2180285","DOIUrl":"https://doi.org/10.1080/10643389.2023.2180285","url":null,"abstract":"Abstract Removing recalcitrant organic contaminants from the soil via sustainable and environmentally friendly technologies are essential for environment and human health. Microbial enzyme is a promising biocatalyst, particularly in environmental bioremediation. To improve their stability and catalytic ability, enzymes are often immobilized on supporting materials. Nevertheless, the most appropriate immobilization technology and supporting materials must be selected in advance to achieve high eco-remediation efficiency. This review highlighted the recent advances and provided the future perspectives of immobilization techniques and supporting materials, with particular attention on ensuring basic features and possibilities of immobilized enzymes for eco-remediation of organic contaminated soil. The bioavailability, biodegradability and high cost of immobilized carriers have limited their industrial application and commercialization in remediation of organic contaminated soil, which was hereby thoroughly reviewed. Finally, future directions, including minimizing enzyme production costs, inexpensive and scalable immobilization carriers, and methods, were highlighted to offer new perspectives on the eco-remediation of organic contaminated soil. HIGHLIGHTS Immobilized approaches and carriers were classified and introduced. Immobilized enzymes have tremendous potential in soil eco-remediation. The main mechanism for soil remediation is the presence of a suitable microenvironment. Bioavailability, high cost and accessibility limited the large-scale applications. Future directions for soil eco-remediation with enzyme immobilization were proposed. GRAPHICAL ABSTRACT","PeriodicalId":10823,"journal":{"name":"Critical Reviews in Environmental Science and Technology","volume":"53 1","pages":"1684 - 1708"},"PeriodicalIF":12.6,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42208429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-07DOI: 10.1080/10643389.2023.2174771
Yang Yang, Y. Tao, Zixu Li, Yunhe Cui, Jinzhu Zhang, Ying Zhang
Abstract The massive application of agrochemicals and associated environmental residues greatly threaten human health. Cardiac dysfunction, as a major contributing factor to human mortality, is increasingly reported in health risk assessments to be associated with agrochemical exposure. In this mini-review, we summarize the cardiotoxicity of various agrochemicals including herbicides, insecticides, fungicides, and acaricides on zebrafish embryos/larvae and systematically discuss the role of cardiac development-related pathway disorders, imbalance in Ca2+ homeostasis, mitochondrial dysfunction, and general negative effects such as oxidative stress and apoptosis. Moreover, the crosstalk identified in combined analysis of predisposing factors of cardiac dysfunction not only explains the coexistence of multiple negative effects after agrochemical exposure, but also helps researchers identify key factors in predisposing cardiotoxicity as well as provides a theoretical basis for the diagnosis and treatment of certain congenital cardiac diseases. Graphic abstract
{"title":"Agrochemical-mediated cardiotoxicity in zebrafish embryos/larvae: What we do and where we go","authors":"Yang Yang, Y. Tao, Zixu Li, Yunhe Cui, Jinzhu Zhang, Ying Zhang","doi":"10.1080/10643389.2023.2174771","DOIUrl":"https://doi.org/10.1080/10643389.2023.2174771","url":null,"abstract":"Abstract The massive application of agrochemicals and associated environmental residues greatly threaten human health. Cardiac dysfunction, as a major contributing factor to human mortality, is increasingly reported in health risk assessments to be associated with agrochemical exposure. In this mini-review, we summarize the cardiotoxicity of various agrochemicals including herbicides, insecticides, fungicides, and acaricides on zebrafish embryos/larvae and systematically discuss the role of cardiac development-related pathway disorders, imbalance in Ca2+ homeostasis, mitochondrial dysfunction, and general negative effects such as oxidative stress and apoptosis. Moreover, the crosstalk identified in combined analysis of predisposing factors of cardiac dysfunction not only explains the coexistence of multiple negative effects after agrochemical exposure, but also helps researchers identify key factors in predisposing cardiotoxicity as well as provides a theoretical basis for the diagnosis and treatment of certain congenital cardiac diseases. Graphic abstract","PeriodicalId":10823,"journal":{"name":"Critical Reviews in Environmental Science and Technology","volume":"53 1","pages":"1662 - 1683"},"PeriodicalIF":12.6,"publicationDate":"2023-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41867505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-07DOI: 10.1080/10643389.2023.2174770
Yan Huili, Zhang Hezifan, Hao Shuangnan, Wang Luyao, Xu Wenxiu, Malkov Mi, Luo Yongming, He Zhenyan
Abstract With mankind entering the smart age, Cd contamination risk control in food crop revolution has been put on the agenda. Based on the theoretical basis, technical methods and developing trends, this review look back and forward the age of Cd contamination risk control driven by ‘genotype (G)+ envirotype (E)’ dual-engines. Focusing on G, an inter-specific Cd contamination risk assessment meta-analysis was carried, in which a higher Cd contamination risk in rice and wheat than maize was observed. So different strategies are recommended to be taken considering inter-specific difference. To control the risk in crops with high accumulating characteristic, smart creation of low-Cd crops can be applied by two methods: 1) Excavating and pyramiding natural variations in natural population and 2) designing and implementing artificial variations which do not exist in natural population. Focusing on E, the influence of environmental factors to food crop Cd accumulation was discussed and the strategy using Envirotype-to-phenotype (E2P) models to predict and implement safety threshold were offered. In the foreseeable future, with the support of environmental science, biology, big data, artificial intelligence and other interdisciplinary and multi-technology, Cd contamination risk control will move toward intelligent, efficient and directional, ultimately realizing the revolutionary transformation from ‘experience’ to ‘smart’. Graphical abstract
{"title":"Cadmium contamination in food crops: Risk assessment and control in smart age","authors":"Yan Huili, Zhang Hezifan, Hao Shuangnan, Wang Luyao, Xu Wenxiu, Malkov Mi, Luo Yongming, He Zhenyan","doi":"10.1080/10643389.2023.2174770","DOIUrl":"https://doi.org/10.1080/10643389.2023.2174770","url":null,"abstract":"Abstract With mankind entering the smart age, Cd contamination risk control in food crop revolution has been put on the agenda. Based on the theoretical basis, technical methods and developing trends, this review look back and forward the age of Cd contamination risk control driven by ‘genotype (G)+ envirotype (E)’ dual-engines. Focusing on G, an inter-specific Cd contamination risk assessment meta-analysis was carried, in which a higher Cd contamination risk in rice and wheat than maize was observed. So different strategies are recommended to be taken considering inter-specific difference. To control the risk in crops with high accumulating characteristic, smart creation of low-Cd crops can be applied by two methods: 1) Excavating and pyramiding natural variations in natural population and 2) designing and implementing artificial variations which do not exist in natural population. Focusing on E, the influence of environmental factors to food crop Cd accumulation was discussed and the strategy using Envirotype-to-phenotype (E2P) models to predict and implement safety threshold were offered. In the foreseeable future, with the support of environmental science, biology, big data, artificial intelligence and other interdisciplinary and multi-technology, Cd contamination risk control will move toward intelligent, efficient and directional, ultimately realizing the revolutionary transformation from ‘experience’ to ‘smart’. Graphical abstract","PeriodicalId":10823,"journal":{"name":"Critical Reviews in Environmental Science and Technology","volume":"53 1","pages":"1643 - 1661"},"PeriodicalIF":12.6,"publicationDate":"2023-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41779638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-06DOI: 10.1080/10643389.2023.2172928
Zixuan Wang, Fubin Liu, Zhenli He
Abstract Phosphorus (P) is abundant in wastewater sludge and can be a secondary P source that will contribute to a circular economy. Electrochemical systems are an emerging technology that can be used to release and recover P from wastewater sludge. This paper introduces and analyzes the state-of-the-art electrochemical methods for P release and recovery from wastewater sludge, both qualitatively and quantitatively. Electrochemical P release, which involves mobilizing P from the solid phase into the aqueous phase, is categorized into three major mechanisms, electro-biological release, anodic P release, and cathodic P release. Anodic P release has been most widely studied with a median P release rate of 92.4 mg d−1. Correlation analysis revealed that the type of feed sludge, sludge P contents, sludge loading rate, and current density have a significant impact on the P release performance. The released P is subsequently separated from the heavy metal laden sludge and then recovered via different electrochemical systems such as three-chamber cells, two-chamber cells, and their variations. Those systems can achieve P recovery efficiency of 50 ∼ 80% and a recovery rate of 2.0 × 102∼1.8 × 103 mg P d−1. Energy consumption of electrochemical P recovery is estimated at 50 ∼ 200 kWh kg−1 P but only 27.3% of literature reported such data. This work provides insights into the development and challenges of electrochemical P release & recovery from wastewater sludge and discusses the challenges that need to be addressed to advance the viability of electrochemical P recovery approach.
摘要磷(P)在污水污泥中含量丰富，可以作为二次磷源，有助于循环经济。电化学系统是一项新兴技术，可用于从废水污泥中释放和回收磷。本文从定性和定量两方面介绍和分析了目前最先进的电化学方法对废水污泥中磷的释放和回收。电化学P释放是指将P从固相转移到水相的过程，主要有电生物释放、阳极P释放和阴极P释放三种机制。阳极P释放研究最为广泛，中位P释放率为92.4 mg d - 1。相关分析表明，饲料污泥类型、污泥磷含量、污泥负荷率和电流密度对磷释放性能有显著影响。释放出的磷随后从重金属污泥中分离出来，然后通过不同的电化学系统(如三室电池、两室电池及其变体)进行回收。这些系统的P回收率为50 ~ 80%，回收率为2.0 × 102 ~ 1.8 × 103 mg P d−1。电化学P回收的能量消耗估计为50 ~ 200 kWh kg - 1 P，但只有27.3%的文献报道了这一数据。这项工作提供了对废水污泥电化学P释放和回收的发展和挑战的见解，并讨论了需要解决的挑战，以推进电化学P回收方法的可行性。
{"title":"Electrochemical phosphorus release and recovery from wastewater sludge: A review","authors":"Zixuan Wang, Fubin Liu, Zhenli He","doi":"10.1080/10643389.2023.2172928","DOIUrl":"https://doi.org/10.1080/10643389.2023.2172928","url":null,"abstract":"Abstract Phosphorus (P) is abundant in wastewater sludge and can be a secondary P source that will contribute to a circular economy. Electrochemical systems are an emerging technology that can be used to release and recover P from wastewater sludge. This paper introduces and analyzes the state-of-the-art electrochemical methods for P release and recovery from wastewater sludge, both qualitatively and quantitatively. Electrochemical P release, which involves mobilizing P from the solid phase into the aqueous phase, is categorized into three major mechanisms, electro-biological release, anodic P release, and cathodic P release. Anodic P release has been most widely studied with a median P release rate of 92.4 mg d−1. Correlation analysis revealed that the type of feed sludge, sludge P contents, sludge loading rate, and current density have a significant impact on the P release performance. The released P is subsequently separated from the heavy metal laden sludge and then recovered via different electrochemical systems such as three-chamber cells, two-chamber cells, and their variations. Those systems can achieve P recovery efficiency of 50 ∼ 80% and a recovery rate of 2.0 × 102∼1.8 × 103 mg P d−1. Energy consumption of electrochemical P recovery is estimated at 50 ∼ 200 kWh kg−1 P but only 27.3% of literature reported such data. This work provides insights into the development and challenges of electrochemical P release & recovery from wastewater sludge and discusses the challenges that need to be addressed to advance the viability of electrochemical P recovery approach.","PeriodicalId":10823,"journal":{"name":"Critical Reviews in Environmental Science and Technology","volume":"53 1","pages":"1359 - 1377"},"PeriodicalIF":12.6,"publicationDate":"2023-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46792499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：