复合螯合剂/活性碳分离富集和ICP—AES同时测定水样中痕量元素

本文提出将复合螯合剂（NaDDTC／8—Oxin）饱和吸附于活性碳上作为吸附材料．分离富集和ICP—AES同时测定水中痕量金属元素的方法。用ICP—AES研究了该吸附材料对某些痕量元素的吸附和解吸性能；考察了共存元素的影响。方法应用于湖水中Fe、Cu、Mn、Y和Sc的测定，检出限为ng／ml级，RSD为1．9％～4．4％，加入回收率81％～101％间，试样分析结果满意。     

ICP-AES法测定大气降水中微量金属元素

利用电感耦合等离子体原子发射光谱法(ICP-AES)对降水中的Al、Ba、Cr、Fe、Ni、Ti和Zn 7种微量金属元素进行了同时测定。通过信噪比选取了这7种元素的最佳分析谱线和最优仪器测试条件。在此条件下,7种元素的线性相关系数r均大于0.999,6次测试样品的相对标准偏差均小于5%,Al、Ba、Cr、Fe、Ni、Ti和Zn的检出限分别为0.79、0.34、0.33、0.25、0.54、0.08和0.85μg/L。空白加标回收率为93.24%~100.88%,该方法操作简单、准确、快速,适用于大气降水中多种微量金属元素的同时测定。     

电感耦合等离子体发射光谱法测定地下水中锰的不确定度评定

本文对电感耦合等离子体发射光谱法测定地下水中锰含量的不确定度进行了评定,标准曲线采用双误差拟合法,建立了不确定度评定模型,对测定地下水样品中锰含量的不确定度作了评估。     

废TFT-LCD面板中主要元素溶出特性

以废TFT-LCD面板破碎料为研究对象,在使用XRF（X射线荧光光谱分析仪）分析其主要元素组成以及采用ICP-AES测试不同酸体系下主要元素浓度的基础上,研究了不同酸体系下主要元素的溶出特性. 结果表明:废TFT-LCD面板由Si、Al、Sr和In等10余种元素组成,其主要组成元素在不同酸体系下的溶出特性存在明显差异,这与其赋存形态有密切关系. In在各种酸体系下溶出浓度变化较小,为283～306 mgL. Fe的溶出特性与In相似,是主要伴随离子. Al和Sr易在浓盐酸体系下溶出. As在含有浓硝酸的体系下溶出率较高,最高溶出率为100%,而在无浓硝酸体系下的溶出率最低值仅为293%. Zn、Ti、Cu、Sn和Cr在各酸体系下的溶出浓度均较低(均低于1 mgL),不宜回收.      

Trace metals distribution and their dependence on some physico-chemical parameters in creek sediment

The concentrations of the trace metals Mn, Zn, Cr, V, Co, Ni, Ba, Pb, Cu, Cd, As and Hg, their spatial distribution, and their correlation as a function of physico-chemical parameters were investigated for grab sediment samples collected from different locations across the Thane Creek, Mumbai, India. Hydride generation atomic absorption spectrometry, inductively coupled plasma atomic emission spectrometry, and differential pulse anodic stripping voltammetry were adopted for chemical analyses. Various geochemical indices were evaluated. The studied metal/metalloids were compared with sediment quality guideline values. Besides, the role of different physico-chemical parameters of the sediments such as pH, CaCO₃, cation exchange capacity, total carbon, and of the relative composition in respect to very coarse, coarse and medium sand, fine sand and very fine sand, silt and clay fraction were also critically investigated. Positive one-to-one correlations between fine sand and very fine sand, silt and clay, and total carbon with sediment metal concentrations have been noticed. Multiple regression analysis reveals strong positive correlations between sediment metal concentrations and total carbon content only.     

Using multivariate regression modeling for sampling and predicting chemical characteristics of mixed waste in old landfills

Municipal solid waste landfills pose a threat on environment and human health, especially old landfills which lack facilities for collection and treatment of landfill gas and leachate. Consequently, missing information about emission flows prevent site-specific environmental risk assessments. To overcome this gap, the combination of waste sampling and analysis with statistical modeling is one option for estimating present and future emission potentials. Optimizing the tradeoff between investigation costs and reliable results requires knowledge about both: the number of samples to be taken and variables to be analyzed.This article aims to identify the optimized number of waste samples and variables in order to predict a larger set of variables. Therefore, we introduce a multivariate linear regression model and tested the applicability by usage of two case studies. Landfill A was used to set up and calibrate the model based on 50 waste samples and twelve variables. The calibrated model was applied to Landfill B including 36 waste samples and twelve variables with four predictor variables.The case study results are twofold: first, the reliable and accurate prediction of the twelve variables can be achieved with the knowledge of four predictor variables (Loi, EC, pH and Cl). For the second Landfill B, only ten full measurements would be needed for a reliable prediction of most response variables. The four predictor variables would exhibit comparably low analytical costs in comparison to the full set of measurements. This cost reduction could be used to increase the number of samples yielding an improved understanding of the spatial waste heterogeneity in landfills.Concluding, the future application of the developed model potentially improves the reliability of predicted emission potentials. The model could become a standard screening tool for old landfills if its applicability and reliability would be tested in additional case studies.     

耐候钢中微量元素的测定

本文分别用化学法和电感耦合等离子体发射光谱法(ICP-AES)测定了Corten-B和Sten3两种耐候钢中Cr、Cu、Mn、Sb、Si、V、P、Ti等8种微量元素的含量,并与传统的化学法进行了对比.试验证明ICP-AES光谱法不但技术简便、快速、易于推广应用,而且ICP-AES光谱法和微波消解技术联用在微量元素测量上有更准确、安全等方面的优点.另外,ICP-AES仅通过对少量样屑的一次溶样即可得到全部元素的分析结果,节省了钢样,这对于难以取样的情况尤为有利.     

大气颗粒物中重金属元素在不同粒径上的形态分布

采用DFJ 1型五段分级采样器 ,对衡阳市区冬、夏两季空气中不同粒径颗粒物中重金属元素的组成和化学形态进行了分析。应用ICP AES法测定了各形态中元素的含量 ,计算了元素在各种形态中的分配比例。结果表明 ,衡阳市大气环境中多数重金属元素的含量冬季明显高于夏季。对人体危害较大的金属元素主要富集在小于 2 0 μm的细颗粒上 ,Mn、Zn、Cu和Co主要分布在氧化态、水可溶态、碳酸盐态和有机态中 ,Pb和V主要分布在不溶态中     

电感耦合等离子光谱法测定油中硫的方法探讨

研究了以航空煤油作稀释剂,选择合适的稀释比例,在电感耦合等离子光谱仪(ICP-AES)上采取直接进样测定不同类型油样中硫的方法。由本实验得出方法的检出限为0.06%(600mg/kg),相对标准偏差为1.0%～5.0%,实际样品的测定结果与用国标方法的测定结果相符。     

电感耦合等离子体发射光谱法(ICP-AES)测定水中钴

利用电感耦合等离子体发射光谱法测定水中钴,并优化了测定条件.结果表明,本方法检出限低,准确度高,精密度好.