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过一硫酸盐体系中铜分布模式控制活性物种的产生和污染物降解路径

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Engineering 2024年第4期35卷 168-179页

作者： Ning Li Haoxi Dai Mengting He Jun Wang Zhanjun Cheng beibei yan Wenchao Peng Guanyi Chen School of Environmental Science and Engineering&Tianjin Engineering Research Center of Bio Gas/Oil Technology Tianjin UniversityTianjin 300072China Department of Chemical Engineering Tianjin UniversityTianjin 300350China School of Mechanical Engineering Tianjin University of CommerceTianjin 300134China School of Science Tibet UniversityLhasa 850012China

The distribution pattern of metals as active centers on a substrate can influence the peroxymonosulfate(PMS)activation and contaminants degradation.Herein,atomic layer deposition is applied to prepare Cu single atom(SA-Cu),cluster(C-Cu),and film(F-Cu)decorated MXene catalysts by regulating the number of deposition cycles.In comparison with SA-Cu-MXene(adsorption energy(E_(ads))=-4.236 eV)and F-Cu-MXene(E_(ads)=-3.548 eV),PMS is shown to adsorb preferably on the C-Cu-MXene surface for activation(E_(ads)=-5.435 eV),realizing higher utilization efficiency.More SO_(4)^(·-)are generated in C-Cu-MXene/PMS system with steady-state concentration and 1–3 orders of magnitude higher than those in the SA-Cu-MXene and F-Cu-MXene activated PMS systems.Particularly,the contribution of SO_(4)^(·-)oxidation to sulfamethoxazole(SMX)degradation followed the order,C-Cu-MXene(97.3%)>SA-Cu-MXene(90.4%)>FCu-MXene(71.9%),realizing the larger SMX degradation rate in the C-Cu-MXene/PMS system with the degradation rate constants(k)at 0.0485 min^(-1).Additionally,SMX degradation routes in C-Cu-MXene/PMS system are found with fewer toxic intermediates.Through this work,we highlighted the importance of guided design of heterogeneous catalysts in the PMS system.Appropriate metal distribution patterns need to be selected according to the actual water treatment demand.Metal sites could be then fully utilized to produce specific active species to improve the utilization efficiency of the oxidants.

关键词： Cu cluster Distribution pattern Peroxymonosulfate Active species Degradation routes

可生物降解塑料取代传统塑料--对碳排放的影响

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Engineering 2024年第1期32卷 152-162页

作者： Guanyi Chen Jianyuan Li Yunan Sun Zhi Wang Gary ALeeke Christian Moretti Zhanjun Cheng Yuan Wang Ning Li Lan Mu Jinyu Li Junyu Tao beibei yan Li'an Hou Interdisciplinary Innovation Lab for Environment and Energy School of Mechanical Engineering&School of Biotechnology and Food ScienceTianjin University of CommerceTianjin 300134China School of Environmental Science and Engineering Tianjin UniversityTianjin 300350China School of Ecology and Environment Tibet UniversityLhasa 850012China Tianjin Key Laboratory of Biomass Wastes UtilizationTianjin Engineering Research Center for Organic Wastes Safe Disposal and Energy UtilizationTianjin 300072China School of Chemical Engineering University of BirminghamBirmingham B152TTUK Department of Environmental Systems Science ETH ZürichZürich CH-8092Switzerland

In recent years,a great deal of attention has been focused on the environmental impact of plastics,includ-ing the carbon emissions related to plastics,which has promoted the application of biodegradable plas-tics.Countries worldwide have shown high interest in replacing traditional plastics with biodegradable plastics.However,no systematic comparison has been conducted on the carbon emissions of biodegrad-able versus traditional plastic products.This study evaluates the carbon emissions of traditional and biodegradable plastic products(BPPs)over four stages and briefly discusses environmental and economic perspectives.Four scenarios-namely,the traditional method,chemical recycling,industrial composting,and anaerobic digestion-are considered for the disposal of waste BPPs(WBPPs).The analysis takes China as a case study.The results show that the carbon emissions of 1000traditional plastic products(plastic bags,lunch boxes,cups,etc.)were52.09-150.36 carbon emissions equivalent of per kilogram(kg CO_(2)eq),with the stage of plastic production contributing 50.71%-50.77%.In comparison,1000 similar BPPs topped out at 21.06-56.86 kg CO_(2)eq,approximately 13.53%-62.19%lower than traditional plastic prod-ucts.The difference was mainly at the stages of plastic production and waste disposal,and the BPPs showed significant carbon reduction potential at the raw material acquisition stage.Waste disposal plays an important role in environmental impact,and composting and anaerobic digestion are considered to be preferable disposal methods for WBPPs.However,the high cost of biodegradable plastics is a challenge for their widespread use.This study has important reference significance for the sustainable development of the biodegradableplastics industry.

关键词： Carbon emissions Biodegradable plastics Different disposal scenarios Daily life consumption Environmental and economic discussion

State-of-the-art applications of machine learning in the life cycle of solid waste management

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Frontiers of Environmental Science & Engineering 2023年第4期17卷 53-69页

作者： Rui Liang Chao Chen Akash Kumar Junyu Tao yan Kang Dong Han Xianjia Jiang Pei Tang beibei yan Guanyi Chen School of Environmental Science and Engineering Tianjin UniversityTianjin 300350China School of Mechanical Engineering Tianjin University of CommerceTianjin 300134China Tianjin Key Laboratory of Biomass Wastes Utilization/Tianjin Engineering Research Center of Bio Gas/Oil Technology Tianjin 300072China School of Science Tibet UniversityLhasa 850012China

Due to the superiority of machine learning(ML)data processing,it is widely used in research of solid waste(SW).This study analyzed the research and developmental progress of the applications of ML in the life cycle of SW.Statistical analyses were undertaken on the literature published between 1985 and 2021 in the Science Citation Index Expanded and Social Sciences Citation Index to provide an overview of the progress.Based on the articles considered,a rapid upward trend from 1985 to 2021 was found and international cooperatives were found to have strengthened.The three topics of ML,namely,SW categories,ML algorithms,and specific applications,as applied to the life cycle of SW were discussed.ML has been applied during the entire SW process,thereby affecting its life cycle.ML was used to predict the generation and characteristics of SW,optimize its collection and transportation,and model the processing of its energy utilization.Finally,the current challenges of applying ML to SW and future perspectives were discussed.The goal is to achieve high economic and environmental benefits and carbon reduction during the life cycle of SW.ML plays an important role in the modernization and intellectualization of SW management.It is hoped that this work would be helpful to provide a constructive overview towards the state-of-the-art development of SW disposal.

关键词： Machine learning(ML) Solid waste(SW) Bibliometrics SW management Energy utilization Life cycle

The beneficial effects of Tartary buckwheat (Fagopyrum tataricum Gaertn.) on diet-induced obesity in mice are related to the modulation of gut microbiota composition

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Food Science and Human Wellness 2023年第4期12卷 1323-1330页

作者： Yiming Zhou Haoyu Lu Shen Zhao beibei yan Hong Wang Xiaoli Zhou Ying Xiao School of Perfume and Aroma Technology Shanghai Institute of TechnologyShanghai 201418China University Think Tank of Shanghai Municipality Institute of Beautiful China and Ecological CivilizationShanghai 201418China

The gut is home to a large number of intestinal microbiota that play an important role in the metabolism and immune system of the host.A growing body of evidence suggests that a high-fat diet is closely associated with many metabolic disorders,including fatty liver and type 2 diabetes.According to reports,Tartary buckwheat extract has a positive effect on intestinal microbiota in animals.The effects of Tartary buckwheat on biochemical indexes and intestinal microflora in mice were studied.Tartary buckwheat protein(FGP),Tartary buckwheat resistant starch(FGS)and Tartary buckwheat flour(FGF)alleviated organ damage in mice and lowered the atherosclerotic index(AI)in plasma.Otherwise,principal coordinate analysis(PCoA)showed that intestinal bacterial structure of FGF were separated apparently from other groups.The Firmicutes/Bacteroidetes(F/B)value of the high-fat(HF)-FGF group was significantly lower than that of the HF-FGP and HF-FGS groups.FGF significantly increases the abundance of beneficial bacteria such as Bifidobacterium,while decreasing the abundance of lipopolysaccharide(LPS)-producing bacteria.Observation of blood lipid metabolism parameters and analysis of the intestinal microbiota suggested that FGF can be more effective than FGP and FGS to reduce the effects of a high-fat diet in mice,restoring the blood parameters to values similar of those in mice fed a low-fat diet.FGF may be used to prevent or treat blood lipid metabolism disorders and intestinal microbiota disorders in mice fed a high-fat diet.

关键词： Tartary buckwheat High-fat diet Biochemical parameters Gut microbiota Lipid metabolism

New insight into the synergy of nitrogen-related sites on biochar surface for sulfamethoxazole adsorption from water

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中国化学快报:英文版 2023年第9期34卷 254-257页

作者： Chuanbin Wang Lingchao Kong yanshan Wang Xiaoqiang Cui Ning Li beibei yan Guanyi Chen School of Environmental Science and Engineering/Tianjin Engineering Research Center of Bio Gas/Oil Technology Tianjin UniversityTianjin 300072China School of Environmental Science&Engineering Southern University of Science and TechnologyShenzhen 518055China Georgia Tech Shenzhen Institute Tianjin UniversityShenzhen 518071China School of Mechanical Engineering Tianjin University of CommerceTianjin 300134China School of Science Tibet UniversityLhasa 850012China

In-depth exploration of the relationship among different adsorption sites is conducive to design of efficient adsorbents for target pollutants removal from water.In this study,the experiments,multivariate non-linear regression and density functional theory calculations are applied to explore the possible synergistic effects of three nitrogen(N)-containing sites on cow dung biochar surface for sulfamethoxazole(SMX)adsorption.Notably,a strong synergistic effect between pyridinic N and pyrrolic N sites was found for sulfamethoxazole adsorption.The adsorption energies of SMX on four pyrrolic N-coupled pyridinic N structures were-1.02,-0.41,-0.49 and-0.72 e V,much higher than the sum of adsorption energies(-0.31 e V)on pyrrolic N and pyridinic N.Besides,the alteration of Mulliken charge revealed that the simultaneous presence of pyridinic N and pyrrolic N improved the electron transfer remarkably from-0.459 e and 0.094 e to-0.649 e and 0.186 e,benefiting for SMX adsorption.This work firstly explored the possible synergies of adsorption sites on biochar surface for organic contaminants removal from water,which shed new lights on the adsorption mechanism and provided valuable information to design efficient adsorbents in the field of water treatment.

关键词： Synergy Pyrrolic N Pyridinic N Biochar Adsorption

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我国出版公共服务社会化探索

出版科学 2024年第1期32卷 5-11页

作者：黄先蓉严贝贝武汉大学信息管理学院/武汉大学出版研究院武汉430072 武汉大学信息管理学院武汉430072

基于对出版公共服务的供需主体、价值关系、对接关系的分析,本文提出建立主体之间的协同关系,形成出版公共服务多元治理结构、完善出版公共服务合作供给模式,推动政府主导与市场化运作相结合、健全出版公共服务社会化保障机制,促进供需... 详细信息

基于对出版公共服务的供需主体、价值关系、对接关系的分析,本文提出建立主体之间的协同关系,形成出版公共服务多元治理结构、完善出版公共服务合作供给模式,推动政府主导与市场化运作相结合、健全出版公共服务社会化保障机制,促进供需关系的良好运转等具体路径,以实现我国出版公共服务社会化探索。

关键词：出版公共服务社会化供需关系出版公共服务社会化公民文化权益

Prediction of high-density polyethylene pyrolysis using kinetic parameters based on thermogravimetric and artificial neural networks

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Frontiers of Environmental Science & Engineering 2023年第1期17卷 63-74页

作者： Xiaoxiao Yin Junyu Tao Guanyi Chen Xilei Yao Pengpeng Luan Zhanjun Cheng Ning Li Zhongyue Zhou beibei yan School of Mechanical Engineering Tianjin University of CommerceTianjin 300134China School of Environmental Science and Engineering Tianjin UniversityTianjin 300350China Key Laboratory for Power Machinery and Engineering of Ministry of Education Shanghai Jiao Tong UniversityShanghai 200240China

Pyrolysis is considered an attractive option and a promising way to dispose waste plastics.The thermogravimetric experiments of high-density polyethylene(HDPE)were conducted from 105℃ to 900℃ at different heating rates(10℃/min,20℃/min,and 30℃/min)to investigate their thermal pyrolysis behavior.We investigated four methods including three model-free methods and one modelfitting method to estimate dynamic parameters.Additionally,an artificial neural network model was developed by providing the heating rates and temperatures to predict the weight loss(wt.%)of HDPE,and optimized via assessing mean squared error and determination coefficient on the test set.The optimal MSE(2.6297×10^(−2))and R^(2) value(R^(2)>0.999)were obtained.Activation energy and preexponential factor obtained from four different models achieves the acceptable value between experimental and predicted results.The relative error of the model increased from 2.4%to 6.8%when the sampling frequency changed from 50 s to 60 s,but showed no significant difference when the sampling frequency was below 50 s.This result provides a promising approach to simplify the further modelling work and to reduce the required data storage space.This study revealed the possibility of simulating the HDPE pyrolysis process via machine learning with no significant accuracy loss of the kinetic parameters.It is hoped that this work could potentially benefit to the development of pyrolysis process modelling of HDPE and the other plastics.

关键词： HDPE Pyrolysis Kinetics Thermogravimetric ANOVA Artificial neural network

Thermogravimetric analysis of bamboo-tar under different heating rates based on distributed activation energy model

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International Journal of Agricultural and Biological Engineering 2018年第6期11卷 180-186页

作者： Huan Zhang beibei yan Tingzhou Lei Tao Liu Jianjun Hu Yameng Li Guanyi Chen School of Environmental Science&Engineering Tianjin UniversityTianjin 300350China Collaborative Innovation Center of Biomass Energy Henan Agricultural UniversityZhengzhou 450002China Energy Institute Henan Academy of SciencesZhengzhou 450002China College of Resources and Environment Henan University of Economics and LawZhengzhou 450002China

Carbon fiber is a kind of new polymer material with excellent mechanical properties and being applied widely.The process of carbon fiber prepared by bamboo tar,including extraction,condensation,spinning,oxidation and carbonation,is influenced by the pyrolysis kinetics significantly.In this paper,the thermogravimetric analysis(TGA)of bamboo tar produced in the process of pyrolysis and gasification of the bamboo which is known as Phylostachys sulphurea,was analyzed by the distributed activation energy model(DAEM)to understand the kinetic properties and parameters of bamboo tar.The thermogravimetric analysis of bamboo tar which is used as the raw material of carbon fiber was conducted under 5 different heating rates(i.e.5,10,15,30 and 50℃/min,etc.)in nitrogen atmosphere.The results show that the activation energy of bamboo tar and the exponential factor increased significantly with the increase of the heating rate,and the low heating rate is advantageous to the extraction of bamboo tar solvent and the thermal polycondensation,which can provide scientific reference for the optimization of carbon fiber technology.The thermal weight results show that the temperature range of bamboo tar being decomposed rapidly is 213℃-410℃.The ranges of the activation energy were calculated by DAEM,which have small difference in comparisons with five heating rates when the conversion rate is at 0.1-0.6 and the average value of the activation energy is 119 kJ/mol.The stability range of the activation energy is enlarged when the conversion rate is greater than 0.6 and heating rate increases.

关键词： bamboo tar carbon fiber thermogravimetric analysis(TGA) distributed activation energy model(DAEM)

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基于改进YOLOv5s的茶叶嫩芽检测

中国农机化学报 2024年第4期45卷 168-174页

作者：严蓓蓓纪元浩曲凤凤许金普青岛农业大学动漫与传媒学院青岛市266109 青岛农业大学园艺学院青岛市266109

为提高对茶叶嫩芽识别的准确率,提升自动采摘机器人的工作效率,减少人工采摘成本,提出一种对茶叶嫩芽目标检测的模型。通过拍摄包含白豪早茶叶嫩芽图片,进行筛选后得到179张图像,使用Mosic数据扩增后获得716张图像,建立数据集,按照训练... 详细信息

为提高对茶叶嫩芽识别的准确率,提升自动采摘机器人的工作效率,减少人工采摘成本,提出一种对茶叶嫩芽目标检测的模型。通过拍摄包含白豪早茶叶嫩芽图片,进行筛选后得到179张图像,使用Mosic数据扩增后获得716张图像,建立数据集,按照训练集、测试集和验证集7∶2∶1的比例划分数据集。针对复杂背景下茶叶嫩芽存在重叠以及遮挡所导致的识别精准度低的问题,对YOLOv5s模型进行改动,在骨干网络上增添注意力机制模块SE和CBAM进行比较;Neck网络由原来的PAFPN改为可以进行双向加权融合的BiFPN,Head结构增加浅层下采样的P2模块,提出一种茶叶嫩芽检测的模型。试验表明YOLOv5s添加SE模块结合BiFPN时模型具有更高的检测精度,并对试验结果进行十折交叉验证,相较于基线精确率提高10.46%,达到88.30%,平均精度均值mAP提高6.47%,达到85.83%。最后使用相同的数据集和预处理方法对比YOLOv5m、Faster R-CNN和YOLOv4-tiny,证明该试验方法综合强于其他经典深度学习方法,能更有效地提升茶叶嫩芽检测精准度,可以为茶叶自动采摘机器人提供理论依据。

关键词：茶叶嫩芽检测 YOLOv5s 注意力机制双向特征金字塔