Hydraulic jumps with low inflow Froude numbers: air–water surface patterns and transverse distributions of two-phase flow properties

Environmental Fluid Mechanics - Hydraulic jumps are commonly employed as energy dissipators to guarantee long-term operation of hydraulic structures. A comprehensive and in-depth understanding of...     

Water-dispersible nano-pollutions reshape microbial metabolism in type-specific manners: A metabolic and bacteriological investigation in Escherichia coli

• Water-dispersible nano-pollutions exhibit type-specific toxic effects on E. coli. • Global metabolite profiling was used to characterize metabolic disruption patterns. • Key dysregulated metabolites responsive to nano-pollution exposures were found. • Amino acid metabolism and purine metabolism are perturbed at nano-pollutions. Incomplete separation and recycling of nanoparticles are causing undesirable nanopollution and thus raising great concerns with regard to nanosafety. Since microorganisms are important regulator of physiological processes in many organisms, the interaction between nanopollution and microbial metabolomics and the resultant impact on the host’s health are important but unclear. To investigate how typical nanopollution perturbs microbial growth and metabolism, Escherichia coli (E. coli) in vitro was treated with six water-dispersible nanomaterials (nanoplastic, nanosilver, nano-TiO₂, nano-ZnO, semiconductor quantum dots (QDs), carbon dots (CDs)) at human-/environment-relevant concentration levels. The nanomaterials exhibited type-specific toxic effects on E. coli growth. Global metabolite profiling was used to characterize metabolic disruption patterns in the model microorganism exposed to different nanopollutants. The percentage of significant metabolites (p<0.05, VIP>1) accounted for 6%–38% of the total 293 identified metabolites in each of the nanomaterial-contaminated bacterial groups. Metabolic results also exhibited significant differences between different nanopollutants and dose levels, revealing type-specific and untypical concentration-dependent metabolic responses. Key metabolites responsive to nanopollution exposures were mainly involved in amino acid and purine metabolisms, where 5, 4, and 7 significant metabolic features were included in arginine and proline metabolism, phenylalanine metabolism, and purine metabolism, respectively. In conclusion, this study horizontally compared and demonstrated how typical nanopollution perturbs microbial growth and metabolomics in a type-specific manner, which broadens our understanding of the ecotoxicity of nanopollutants on microorganisms.     

Direct degradation of methylene blue by unactivated peroxymonosulfate: reaction parameters,kinetics, and mechanism

Environmental Science and Pollution Research - Advanced oxidation processes (AOPs) are efficient methods for water purification. However, there are few studies on using peroxymonosulfate (PMS) to...     

Human health risk assessment of heavy metals from PM2.5 in China’s 29 provincial capital cities

Environmental Science and Pollution Research - After years of governance, China’s PM2.5 pollution has improved significantly, but some problems remain. PM2.5 is the carrier of many heavy...     

Influence of different inoculation densities of black soldier fly larvae (Hermetia illucens) on heavy metal immobilization in swine manure

The disposal of organic waste by the biocomposting of black soldier fly larvae (BSFL) has drawn broad attention. However, the discrepancies in heavy metal immobilization between BSFL biocomposting with different inoculation densities and aerobic composting need to be further researched. In this study, BSFL with inoculation densities of 0.08%, 0.24% and 0.40% was added to swine manure to investigate its influence on heavy metal bioaccumulation and bioavailability. The physicochemical properties, BSFL growth performance and amino acid contents were measured. The results showed that the germination index, total prepupal yield and bioavailable fraction removal rate (%) of Cr and Pb at an inoculation density of 0.40% of BSFL were the highest among all of the BSFL biocomposting groups. Although the bioaccumulation factor and heavy metal (Cd, Cr, Cu and Zn) concentrations of the BSFL body from swine manure with inoculation densities of 0.24% and 0.40% of BSFL were similar, the BSFL inoculation density of 0.40% had the best absorption effect on these heavy metals in terms of total prepupal yield. Therefore, this study provides a basis for exploring the optimal inoculation density of BSFL biocomposting to reduce the harmful effects of heavy metals in swine manure.

     

Removal performance and mechanisms of Pb(II) and Sb(V) from water by iron-doped phosphogypsum: single and coexisting systems

Environmental Science and Pollution Research - The serious environmental risks caused by Pb(II) and Sb(V) co-contamination increase the need for their efficient and simultaneous removal. In this...     

The U.S.-China Supply Competition for Rare Earth Elements: a Dynamic Game View

Environmental Modeling & Assessment - Rare earth elements govern today’s high-tech world and are deemed to be essential for the attainment of sustainable development goals. Since the...     

模拟SPO情境中的飞行员脑力负荷测量与分析*

为探究单一飞行员驾驶模式（SPO）下飞行员的脑力负荷水平,设计并实施模拟单人驾驶情境中的非正常任务场景处置实验。首先,基于准5级模拟驾驶舱,设计飞行任务场景;其次,招募20名航线飞行员被试,开展模拟飞行实验,记录被试的生理数据心率变异性指标及眼动数据;最后,结合客观生理数据以及主观量表进行脑力负荷分析,记录单发失效故障处置时间并进行任务绩效分析。研究结果表明:与双人制机组相比,单人驾驶情境中飞行员的脑力负荷增幅并不显著,处于可接受范围;单人制驾驶舱的任务设计及智能辅助系统使用对于降低飞行员工作负荷,提升飞行绩效至关重要。研究结果可为单一飞行员驾驶模式实施提供理论支持,并为未来单人制驾驶舱及机载自动化系统设计提供指标参考。     

城市燃气管网泄漏事故分析知识图谱构建及应用研究*

为深入认识燃气管网泄漏事故的发生发展机理,提高事故分析预测的自动化、智能化、数字化水平,利用知识图谱对燃气管网泄漏事故进行研究。在事故案例分析的基础上,从人-物-环-管的角度对燃气泄漏过程以及火灾爆炸次生事故的相关实体进行归纳梳理,对实体间的逻辑关系和非逻辑关系进行辨识,并对实体的属性进行分类,进而构建出较为全面的燃气管网泄漏事故知识图谱。在此基础上,搭建BP神经网络模型,基于已知实体或属性状态,预测相关联其他实体或属性的状态。研究结果表明:燃气管网知识图谱能够有效展示燃气管网泄漏事故发展的动态过程及相关要素,结合BP神经网络能够有效预测事故的发展路径及相关状态,从而提高燃气管网泄漏事故的分析预测水平与效率。     

三元空间融合视阈下的安全态势感知模型研究*

为全面辨识系统风险并准确评估系统安全状况,从3元空间（信息-物理-社会）融合视角出发,界定安全态势感知概念并解读其内涵,提出安全态势感知概念模型和理论模型,并解析安全态势数据采集层、觉察层、理解层、投射层和预警层的具体内涵和功能。研究结果表明:3元空间融合视阈下的安全态势感知,能够通过物联网和互联网同步采集安全态势数据,在现有安全态势感知（安全态势信息输入、处理、输出）基础上,实现对人、机、物及其相互关系的整体感知,有效应对当前复杂多变的安全态势,为安全态势感知体系优化提供理论指导。