河流底泥DOM、营养盐与重金属空间分异特征及响应关系

为探究河流底泥中的溶解性有机物(DOM)和营养盐对重金属迁移转化的影响,以沈阳市新穆河、南小河和老背河为研究对象,利用三维荧光光谱,结合平行因子(PARAFAC)、主成分分析(PCA)和结构方程模型(SEM)研究了底泥中的DOM、营养盐与重金属的空间分异特征及DOM与营养盐对重金属的响应关系.结果表明,3条河流底泥中的总氮(TN)和总磷(TP)呈重度污染状态.南小河底泥中的ω(Zn)、ω(As)、ω(Cu)、ω(Ni)和ω(Cd)分别是辽宁省土壤背景值的2.48、 1.02、 3.45、 3.00和39.05倍,老背河的ω(Zn)、ω(Cu)和ω(Cd)分别是背景值的2.56、 1.92和8.00倍,新穆河的ω(Zn)和ω(Cu)分别是背景值的1.40和1.10倍,总体上3条河流均存在重金属累积现象,累积严重程度为：南小河>老背河>新穆河,其中南小河和老背河Cd污染严重.应用PARAFAC共解析出5类DOM组分,分别为类色氨酸、酚类络合物、微生物代谢产物、类富里酸和类胡敏酸,其中类富里酸和类胡敏酸丰度较高;基于PCA分析,新穆河底泥污染的主控因子为TN、 TP、类富里酸和类...     

基于SEM的城市突发事件现场应急指挥能力影响因素分析

为提升城市突发事件现场应急指挥能力,通过分析城市现场应急指挥能力影响因素,构建城市现场应急指挥能力影响因素与突发事件应急指挥效果结构方程模型,并采用SPSS和AMOS软件对北京市现场应急指挥能力进行研究。结果表明:应急指挥统筹决策对应急指挥能力影响相对较大,应急指挥对象影响相对较小;应急指挥体系建设对应急指挥统筹决策影响相对最大,其次是应急信息平台系统。城市应综合考虑各因素间相关关系,有针对性地提高应急指挥能力。     

新疆盐尘颗粒的迁移及其对城市大气颗粒物的贡献

对2017年9月至2018年8月、12月采集的乌鲁木齐市PM_2.5、“沙雪”样品和克拉玛依土样的水溶性离子进行分析,并结合城市主要风向、扫描电镜联能谱（SEM/EDS）和后向轨迹模型（HYSPLIT）,对环境中盐尘粒子的来源及其对大气颗粒物形成的影响进行了研究.结果表明：PM_2.5中总水溶性离子平均浓度为（62.65±64.75）μg/m³,变化范围为0.69~328.60 μg/m³.其中SO₄²、Ca²⁺、Na⁺、Cl^-、K⁺和Mg²⁺ 6种盐尘粒子浓度分别为（22.73±26.45）,（2.11±3.11）,（1.85±1.43）,（0.40±0.40）,（0.28±0.20）,（0.21±0.15）μg/m³.四季风向结合HYSPLIT模型结果可知,PM_2.5中盐尘粒子主要来源于艾比湖及玛纳斯盐湖的气团;受风沙影响,乌鲁木齐市雪样中Cl^-、SO₄^2-、Ca²⁺、K⁺、Mg²⁺和Na⁺分别增加了30,19,20,5,7和5倍.     

Exploring the influence of lake water chemistry on chlorophyll a: A multivariate statistical model analysis

A multivariate statistical approach integrating the absolute principal components score (APCS) and multivariate linear regression (APCS-MLR), along with structural equation modeling (SEM), was used to model the influence of water chemistry variables on chlorophyll a (Chl a) in Lake Qilu, a severely polluted lake in southwestern China. Water quality was surveyed monthly from 2000 to 2005. APCS-MLR was used to identify key water chemistry variables, mine data for SEM, and predict Chl a. Seven principal components (PCs) were determined as eigenvalues >1, which explained 68.67% of the original variance. Four PCs were selected to predict Chl a using APCS-MLR. The results showed a good fit between the observed data and modeled values, with R² = 0.80. For SEM, Chl a and eight variables were used: NH₄-N (ammonia-nitrogen), total phosphorus (TP), Secchi disc depth (SD), cyanide (CN), arsenic (As), cadmium (Cd), fluoride (F), and temperature (T). A conceptual model was established to describe the relationships among the water chemistry variables and Chl a. Four latent variables were also introduced: physical factors, nutrients, toxic substances, and phytoplankton. In general, the SEM demonstrated good agreement between the sample covariance matrix of observed variables and the model-implied covariance matrix. Among the water chemistry factors, T and TP had the greatest positive influence on Chl a, whereas SD had the largest negative influence. These results will help researchers and decision-makers to better understand the influence of water chemistry on phytoplankton and to manage eutrophication adaptively in Lake Qilu.     

Color removal efficiency of dyes using nanozerovalent iron treatment

In this study, zerovalent iron nanoparticles (Fe⁰) were synthesized by chemical reduction method using ferric chloride hexahydrate (FeCl₃?·?6H₂O) as a starting material. Sodium borohydride (NaBH₄) was used as a reducer. The synthesized nanozerovalent iron (NZVI) was separated using magnets. The X-ray diffraction pattern of iron (Fe) nanoparticles showed that the presence of intensive diffraction peak at 2θ value of 45.33° from the lattice plane of face-centered cubic Fe unequivocally indicates that the particles are made of pure Fe. The size of the synthesized NZVI was found to be 16.64?nm. The scanning electron micrograph revealed that the particles have a hexagonal and spherical shape in nature. EDX showed the surface atomic distribution and chemical composition of NZVI. The decolorization efficiency rose with increasing concentration of nanoparticles as well as with time. Maximal color removal efficiency was 90.72% when using 0.5?g/100?mL Fe nanoparticle for acridine orange. Data revealed that the function of NZVI on color removal efficiency was statistically significant. The correlation coefficient between NZVI concentration and time showed a strong negative correlation for dyes used in the experiment.     

基于EFQM的建筑企业安全投入绩效评估SEM

为解决目前我国建筑业安全生产事故频发,安全投入不足及其绩效产出低下的现状,通过探索性因子分析,从建筑企业安全投入22项组成内容中提炼出6项要素;借鉴欧洲质量卓越(EFQM)模型,建立建筑企业安全投入绩效评估结构方程模型(SEM),实证分析安全投入构成要素之间的复杂交互影响关系:领导分别对人员、资源设施、政策战略具有正向直接影响;人员与资源受到政策战略的正向直接影响,并对生产过程与事故损失产生正向直接与间接影响。因此,在加强领导投入以提升整体安全投入绩效的前提下,提高政策战略对于人员、资源与设施的约束性,将最终保障安全生产与减少事故损失。     

组织及环境因素对员工不安全行为影响的SEM研究

为分析组织及环境因素对员工不安全行为意向和不安全行为的影响,收集7个煤矿的735名一线作业人员有效调查问卷,采用因子分析方法(FAM)和结构方程模型(SEM),构建组织与环境因素对不安全行为意向及其行为的SEM。结果表明:不安全行为意向与安全装备、安全理念、危险源管理、工作压力、违章处罚、安全管理行为显著相关;不安全行为与危险源管理、工作压力、管理承诺、物态环境、违章惩罚显著相关;不安全行为与安全理念、安全装备、安全管理行为关系不显著;不安全行为意向与管理承诺、物态环境关系不显著。     

煤矿组织安全行为对个体不安全行为的作用机理研究

为了探究煤矿组织安全行为对个体不安全行为的作用机理,总结国内外相关研究成果,提出个体不安全行为包含心理、生理、技能3个影响因素,涵盖记忆、思维、情绪、意志、性格、气质、能力、态度、知识、专业操作技能10个方面。在此基础上,构建了组织安全行为对个体不安全行为的结构方程模型（SEM）,运用统计分析方法（AMOS17.0）进行了验证分析。结果显示态度、情绪、意志、能力、专业操作技能容易受组织安全行为的影响,而性格、气质等因素由于是个体相对稳定的心理特征,受组织安全行为影响相对较小。深入研究煤矿组织安全行为对个体不安全行为的作用机理,有利于煤矿从组织安全行为入手有针对性的制定行为干预方案并控制个体不安全行为。     

安全注意力对矿工不安全行为影响的代际差异研究

为探究安全注意力对新、老两代矿工的安全行为影响的差异,基于代际划分的视角和安全注意力的分类,结合多群组结构方程模型,构建不同类型安全注意力对矿工不安全行为影响的路径模型。结果表明:在新、老两代矿工群体中不同类型安全注意力对矿工不安全行为的影响存在差异;有意注意对新、老两代矿工不安全行为有显著性影响;无意注意对新生代矿工不安全行为无显著性影响,而对老一代矿工影响显著;有意后注意对群体安全行为有显著性影响,对个体安全行为的影响存在代际差异。     

Deliquescence of Deposited Atmospheric Particles on Leaf Surfaces

A large fraction of deposited aerosol particles on leafsurfaces represents hygroscopic material in a high humidity environment, likely to become deliquescent within the water vapour transpired by the leaf. Microscopic observations on leaf surfaces of beech, kohlrabi and elder leaves grown in a particle-free environment and/or treated with defined particle load are presented. Spreading of deliquescent particles, formation of salt crusts, and encoating of and by waxes was observed. Deliquescence of NaNO₃ particles (deliquescence point 74% RH at 25 °C) was observed on and near the stomata at 35% relative humidity (RH) of the surrounding air, illustrating the influence of the boundary layer. Aerosols are difficult to identify on leaf surfaces, as similar patterns may be produced by deliquescent particles and processes like salt creep. These problems are especially important on leaves from the natural environment if only scanning electron microscopy (SEM) is used. These patterns could appear similar to the fused waxes described in forest decline research. Strong gradients are formed between deliquescent particles and the apoplastic solution within the leaf, promoting cuticular and stomatal uptake.