火焰原子吸收光谱法分析沉积物中重金属元素的形态

采用原子吸收光谱法研究了金沙江攀枝花段水系沉积物中重金属的形态及分布特征。研究发现,各重金属的形态以残渣态为主,离子交换态含量很少。同时说明原子吸收光谱法完全可以用来研究重金属形态特征,在环境研究中具有重要意义。     

Chemometrical investigation of the presence and distribution of organochlorine and polyaromatic compounds in sediments of the Ebro River Basin

A multivariate statistical data analysis, using principal component analysis, of historical data from 1996 to 2003 concerning the concentration of different polycyclic aromatic hydrocarbons and organochlorine compounds in sediment samples from different sampling sites of the Ebro River Basin was performed under the UE funded project AQUATERRA. Three major contamination sources were identified and their composition and distribution profiles were resolved. The first contamination profile was mostly loaded by polycyclic aromatic hydrocarbons, the second contamination profile was loaded by some organochlorine compounds and the third contamination profile was more specifically loaded by naphthalene. Samples from the different geographical regions of the Ebro River Basin were grouped according to the contamination described by these three major profiles.     

The recognition of similarities in trace elements content in medicinal plants using MLP and RBF neural networks

The objective of the paper was to verify if the content of some elements provides enough information for proper classification of the medicinal plant raw materials. Such information could be helpful in standardization process of herbal products. Four elements—zinc, copper, lead and cadmium were determined using inverse voltammetry in commercially available medicinal herbal raw materials. Initially, principal component analysis (PCA) was employed to investigate the relationships among the analyzed trace elements. In the next stage of the study, two different types of feed-forward artificial neural networks (FANNs)—multilayer perceptron (MLP) and radial basis function (RBF) were applied. The concentrations of the elements were used as input variables to neural networks models, which were to recognize the taxonomy of the plant and the anatomical part it originated from. Although full recognition of the samples with use of FANNs on the basis of some trace elements content was not achieved, it was possible to identify two elements—cadmium and lead as the most important in the classification analysis of medicinal plants.     

Spectrophotometric determination of metal ions in electroplating solutions in the presence of EDTA with the aid of multivariate calibration and artificial neural networks

Metal ions such as Co(II), Ni(II), Cu(II), Fe(III) and Cr(III), which are commonly present in electroplating baths at high concentrations, were analysed simultaneously by a spectrophotometric method modified by the inclusion of the ethylenediaminetetraacetate (EDTA) solution as a chromogenic reagent. The prediction of the metal ion concentrations was facilitated by the use of an orthogonal array design to build a calibration data set consisting of absorption spectra collected in the 370-760 nm range from solution mixtures containing the five metal ions earlier. With the aid of this data set, calibration models were built based on 10 different chemometrics methods such as classical least squares (CLS), principal component regression (PCR), partial least squares (PLS), artificial neural networks (ANN) and others. These were tested with the use of a validation data set constructed from synthetic solutions of the five metal ions. The analytical performance of these chemometrics methods were characterized by relative prediction errors and recoveries (%). On the basis of these results, the computational methods were ranked according to their performances using the multi-criteria decision making procedures preference ranking organization method for enrichment evaluation (PROMETHEE) and geometrical analysis for interactive aid (GAIA). PLS and PCR models applied to the spectral data matrix that used the first derivative pre-treatment were the preferred methods. They together with ANN-radial basis function (RBF) and PLS were applied for analysis of results from some typical industrial samples analysed by the EDTA-spectrophotometric method described. DPLS, DPCR and the ANN-RBF chemometrics methods performed particularly well especially when compared with some target values provided by industry.     

Application of chemometric methods to the investigation of main microcontaminant sources of endocrine disruptors in coastal and harbour waters and sediments

Identification, resolution and distribution of main microcontaminant sources of endocrine disruptors in Spanish harbours, coastal waters and sediments are investigated using chemometric methods. We investigated eighteen different endocrine disruptor chemical compounds, including non-ionic surfactants, their degradation products and linear alkylbenzene sulfonates, found in a total number of 74 samples (35 water samples and 39 sediment samples) over a period of 16 months from March 1999 to July 2000, and in 32 different geographical sites along the Spanish Mediterranean Coast (e.g. Barcelona, Tarragona, Almeria Harbour, Malaga and the Bay of Cadiz). Main environmental contamination sources of these endocrine disruptor compounds were investigated and interpreted according to their chemical composition and according to their resolved geographical distribution profiles.An erratum to this article can be found at     

Development of a four-zone carousel process packed with metal ion-imprinted polymer for continuous separation of copper ions from manganese ions,cobalt ions,and the constituent metal ions of the buffer solution used as eluent

A three-zone carousel process, in which Cu(II)-imprinted polymer (Cu-MIP) and a buffer solution were employed as adsorbent and eluent respectively, has been developed previously for continuous separation of Cu²⁺ (product) from Mn²⁺ and Co²⁺ (impurities). Although this process was reported to be successful in the aforementioned separation task, the way of using a buffer solution as eluent made it inevitable that the product stream included the buffer-related metal ions (i.e., the constituent metal ions of the buffer solution) as well as copper ions. For a more perfect recovery of copper ions, it would be necessary to improve the previous carousel process such that it can remove the buffer-related metal ions from copper ions while maintaining the previous function of separating copper ions from the other 2 impure heavy-metal ions. This improvement was made in this study by proposing a four-zone carousel process based on the following strategy: (1) the addition of one more zone for performing the two-step re-equilibration tasks and (2) the use of water as the eluent of the washing step in the separation zone. The operating conditions of such a proposed process were determined on the basis of the data from a series of single-column experiments. Under the determined operating conditions, 3 runs of carousel experiments were carried out. The results of these experiments revealed that the feed-loading time was a key parameter affecting the performance of the proposed process. Consequently, the continuous separation of copper ions from both the impure heavy-metal ions and the buffer-related metal ions could be achieved with a purity of 91.9% and a yield of 92.8% by using the proposed carousel process based on a properly chosen feed-loading time.     

Application of probabilistic neural networks in qualitative analysis of near infrared spectra: determination of producing area and variety of loquats

Near infrared (NIR) spectra of a sample can be treated as a signature, allowing samples to be grouped on basis of their spectral similarities. Near infrared spectroscopy (NIRS) combined with probabilistic neural networks (PNN) have been used to discriminate producing area and variety of loquats. Two varieties of loquats (‘Dahongpao’ and ‘Jiajiaozhong’) picked from two producing areas of ‘Tangxi’ and ‘Cunan’ in Zhejiang province were analyzed in this study. Principal component analysis (PCA) was applied before PNN modeling and the results indicated that the dimension of the vast spectral data can be effectively reduced. For each model, half samples were used to train the network and the remaining half were used to test the network. The results of the PCA-PNN models for discriminating the variety of samples from the same producing area or for discriminating the producing area of the same variety samples were much better than those of the PCA-PNN models for discriminating variety or producing area of all loquat samples. The results of this study show that NIRS combined with PCA-PNN is a feasible way for qualitative analysis of discriminating fruit producing areas and varieties.     

Principle component analysis (PCA) and second-order global hard-modelling for the complete resolution of transition metal ions complex formation with 1,10-phenantroline

Second-order global hard-modelling was applied to resolve the complex formation between Co²⁺, Ni²⁺, and Cd²⁺ cations and 1,10-phenantroline. The highly correlated spectral and concentration profiles of the species in these systems and low concentration of some species in the individual collected data matrices prevent the well-resolution of the profiles. Therefore, a collection of six equilibrium data matrices including series of absorption spectra taken with pH changes at different reactant ratios were analyzed. Firstly, a precise principle component analysis (PCA) of different augmented arrangements of the individual data matrices was used to distinguish the number of species involved in the equilibria. Based on the results of PCA, the equilibria included in the data were specified and second-order global hard-modelling of the appropriate arrangement of six collected equilibrium data matrices resulted in well-resolved profiles and equilibrium constants. The protonation constant of the ligand (1,10-phenantroline) and spectral profiles of its protonated and unprotonated forms are the additional information obtained by global analysis. For comparison, multivariate curve resolution-alternating least squares (MCR-ALS) was applied to the same data. The results showed that second-order global hard-modelling is more convenient compared with MCR-ALS especially for systems with completely known model. It can completely resolve the system and the concentration profiles which are closer to correct ones. Moreover, parameters showing the goodness of fit are better with second-order global hard-modelling.     

Assessing effects of pH,metal ion and natural organic matter on identification and determination of reduced glutathione by cathodic stripping voltammetry

The effects of pH, metal ions (i.e. Cu²⁺, Cd²⁺, Pb²⁺ and Zn²⁺) and natural organic matter (i.e. Suwannee River natural organic matter standard [SRNOM]) on determination of thiol (i.e. reduced glutathione [GSH]) by cathodic stripping voltammetry were evaluated. pH was the most critical parameter to influence GSH voltammogram (i.e. peak shape, position and height). In presence of Cu and Cd, secondary peaks were found at [metal]/GSH > 1 due to formation of GSH complexes at pH = 8.0 (Cu and Cd) and 2.5 (Cu only). On the other hand, Pb showed negligible influence on GSH voltammogram at pH 8.0 and 2.5 within [Pb]/[GSH] = 0.01–2.0. Zn significantly reduced GSH peak height at pH 2.5 at [Zn]/[GSH] = 0.01–2.0. SRNOM peak significantly overlapped with GSH peak at pH 8.0 and [SRNOM] > 1 mg L^?1 but was clearly separated from the GSH peak at pH 2.5. However, at pH 2.5, the presence of metal ions and/or SRNOM significantly underestimated GSH concentration (recovery = 21–69%), likely due to metal complexation with GSH and/or SRNOM adsorption onto Hg electrode. The effects of metal ions were minimised by the addition of EDTA. The interference induced by SRNOM adsorption was reduced as the [SRNOM] was reduced to 1 mg L^?1 and the recovery was improved to 98%.     

Modeling of the relationship between electroosmotic flow and separation parameters in capillary zone electrophoresis using artificial neural networks and experimental design

The prediction of migration time of electroosmotic flow (EOF) marker was achieved by applying artificial neural networks (ANN) model based on principal component analysis (PCA) and standard normal distribution simulation to the input variables. The voltage of performance, the temperature in the capillary, the pH and the ionic strength of background electrolytes (BGE) were applied as the input variables to ANN. The range of the performance voltage studied was from 15 to 27 kV, and that of the temperature in the capillary was from 20 to 30 °C. For the pH values studied, the range was from 5.15 to 8.04. The range of the ionic strength investigated in this paper was from 0.040 to 0.097. The prediction abilities of ANN with different pre-processing procedure to the input variables were compared. Under the same performance conditions, the average prediction error of the migration time of the EOF marker was 5.46% with RSD = 1.76% according to 10 parallel runs of the optimized ANN structure by the proposed approach, and that of the 10 parallel predictions of the optimal ANN structure for the different performance conditions was 12.95% with RSD = 2.29% according to the proposed approach. The study showed that the proposed method could give better predicted results than other approaches discussed.     

用化学计量法—分光光度法测定活体叶片中叶绿素a,b的含量

本文研究了用逐步回归分析法、主成分回归法、偏最小二乘法与人工神经网络法测定活体叶片中叶绿素a、b的含量。活体叶片的光谱由PC微机采集,测定叶绿素a与b的相关系数分别达到0.927～0.958与0.873～0.908;相对标准偏差约5％～9％(叶绿素a 9.4μg/2ml,n=20)。本方法可用于农业研究。     

Number of species in complexation equilibria of o-, m- and p-CAPAZOXS with Cd, Co, Ni, Pb and Zn ions by PCA of UV-vis spectra

A critical comparison of the selected derivative principal component analysis (PCA) methods on the absorbance matrix data concerning the complexation equilibria between o-CAPAZOXS and Cd²⁺, Pb²⁺ and Zn²⁺ or m-CAPAZOXS and Cd²⁺, Co²⁺, Ni²⁺ and Zn²⁺ or p-CAPAZOXS and Cd²⁺ and Zn²⁺ at 25 °C is provided. As the number of complex species in a complex-forming equilibria mixture is an important step in spectral data treatment, the nine selected index functions for the prediction of the number of light-absorbing species that contribute to a set of spectra is critically tested by the PCA. An improved identification with the second SD(AE) or third derivative TD(AE) and derivative ratio function ROD(AE) for the average error criterion AE is preferred. After the number of various complexes formed the stability constants of species ML, ML₂ (and ML₃, respectively) type log β₁₁, log β₁₂ (and log β₁₃, respectively) for the system of o-CAPAZOXS (ligand L) with the metals (the standard deviation s(log β_pq) of the last valid digits is given in brackets) Cd²⁺ (6.39(5) and 11.51(9)), Pb²⁺ (4.24(2) and 9.01(2)) and Zn²⁺ (5.18(7) and 9.06(10)) and for the system of m-CAPAZOXS with Cd²⁺ (6.59(20) and 11.51(32)), Co²⁺ (7.19(6) and 12.19(8)), Ni²⁺ (7.64(7) and 13.39(12)) and Zn²⁺ (4.83(3) and 9.57(3)) and for the system of p-CAPAZOXS with Cd²⁺ (6.44(5), 10.99(10) and 14.57(25)) and Zn²⁺ (6.84(16), 13.05(29) and 18.74(43)) at 25 °C are estimated using SQUAD(84) nonlinear regression of the mole-ratio spectrophotometric data. The computational strategy is presented with goodness-of-fit tests and various regression diagnostics capable of proving the reliability of the chemical model proposed.     

Biomass valorization of walnut shell into biochar as a resource for electrochemical simultaneous detection of heavy metal ions in water and soil samples: Preparation,characterization, and applications

Lately, due to its accessibility and eco-friendliness, walnut shell biochar (WS-BC) is gaining attention as an electrode material component in the electrochemical detection of water pollutants. The overall performance of WS-BC is reliant on the nature of raw biomass and the production methods as well. In our concept, biochar, prepared from raw walnut shell (WS) by pyrolysis, was added to a carbon paste electrode (CPE), and poly-tyrosine (p-Tyr) was electrodeposited on the surface of the BC-doped electrode. The conditions of the elaboration of the electrode, such as pH, potential, and the number of deposition cycles, pH were optimized. The obtained p-Tyr-BC-CPE platform was tested for the determination of cadmium, lead, copper, and mercury ions in water and soil samples, using square wave voltammetry (SWV). The raw WS biomass and its BC were examined by thermal analysis (TG-DSC), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM/EDX) techniques. The synergistic effects of the coexistence of the WS-BC and the thin film of p-Tyr, for the detection of traces of heavy metal ions were investigated by electrochemical tests. The electrochemical characterization of the unmodified and modified electrodes was performed using the cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) methods, while the Cd²⁺, Pb²⁺, Cu^2+, and Hg²⁺ detection experiments were studied using the CV and SWV techniques. The optimized experimental conditions for the p-Tyr-BC-CPE platform were evaluated. The obtained electrochemical results showed that the p-Tyr-BC-CPE platform produced excellent sensitivity toward the heavy metal ions: LOD of 0.086, 0.175, 0.246, and 0.383 nM for Cd(II), Pb(II), Cu(II) and Hg(II), respectively. The modified electrode platform displayed high selectivity, stability, and good reproducibility.     

Extension and application of multivariate curve resolution-alternating least squares to four-way quadrilinear data-obtained in the investigation of pollution patterns on Yamuna River,India—A case study

This study focuses on the development and extension of Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) to the analysis of four-way datasets. The proposed extension of the MCR-ALS method with non-negativity and the newly developed quadrilinear constraints can be exploited to summarize and manage huge multidimensional datasets and resolve their four way component profiles. In this study, its application is demonstrated by analyzing a four-way data set obtained in a long term environmental monitoring study (15 sampling sites × 9 variables × 12 months × 7 years) belonging to the Yamuna River, one of the most polluted rivers of India and the largest tributary of the Ganges river. MCR-ALS resolved pollution profiles described appropriately the major observed changes on pH, organic pollution, bacteriological pollution and temperature, along with their spatial and temporal distribution patterns for the studied stretch of Yamuna River. Results obtained by MCR-ALS have also been compared with those obtained by another multi-way method, PARAFAC. The methodology used in this study is completely general and it can be applied to other multi-way datasets.     

Genetic Algorithm Based Potential Selection in Simultaneous Voltammetric Determination of Isoniazid and Hydrazine by Using Partial Least Squares (PLS) and Artificial Neural Networks (ANNs)

The voltammetric behavior of isoniazid and hydrazine at an overoxidized polypyrrole modified glassy carbon electrode has been investigated. The obtained cyclic voltammograms showed that their oxidation peaks were overlapped and it is difficult to determine them individually from a mixture without separation. To overcome this limitation, a procedure was proposed for resolution of overlapped voltammetric signals from mixtures of isoniazid and hydrazine. In this procedure, genetic algorithm was used for the selection of potentials for partial least squares. A feed forward artificial neural network with back propagation error algorithm was used to process the nonlinear relationship between currents and concentrations of hydrazine and isoniazid. The proposed method was suitable for determination of isoniazid in pharmaceutical tablets and detection of hydrazine impurities in the same samples.     

Simultaneous determination of Co, Ni, Cu and Zn ions in foodstuffs and vegetables with a new Schiff base using artificial neural networks

New complexes of Co²⁺, Ni²⁺, Cu²⁺ and Zn²⁺ with a recently synthesized Schiff base derived from 3,6-bis((aminoethyl)thio)pyridazine were applied for their simultaneous determination with artificial neural networks. The analytical data show the ratio of metal to ligand in all metal complexes is 1:1. The absorption spectra were evaluated with respect to Schiff base concentration, pH and time of the color formation reactions. It was found that at pH 10.0 and 60 min after mixing, the complexation reactions are completed and the colored complexes exhibited absorption bands in the wavelength range 300-500 nm. Spectral data was reduced using principal component analysis and subjected to artificial neural networks. The data obtained from synthetic mixtures of four metal ions were processed by principal component-feed forward neural networks (PCFFNNs) and principal component-radial basis function networks (PCRBFNs). Performances of the proposed methods were tested with regard to root mean square errors of prediction (RMSEP%), using synthetic solutions. Under the working conditions, the proposed methods were successfully applied to simultaneous determination of Co²⁺, Ni²⁺, Cu²⁺ and Zn²⁺ in different vegetable, foodstuff and pharmaceutical product samples.     

Catalysis by Ir(III), Rh(III) and Pd(II) metal ions in the oxidation of organic compounds with H2O2

Catalytic activities of three transition metals, as iridium (III) chloride, rhodium (III) chloride and palladium (II) chloride, were compared in the oxidation of six aromatic aldehydes (benzaldehyde, p‐chloro benzaldehyde, p‐nitro benzaldehyde, m‐nitro benzaldehyde, p‐methoxy benzaldehyde and cinnamaldehyde), two hydrocarbons (viz. (anthracene and phenanthrene)) and one aromatic and one cyclic alcohol (cyclohexanol and benzyl alcohol) by 50% H₂O₂. The presence of traces (substrate: catalyst ratio equal to 1:62500 to 1:1961) of the chlorides of iridium(III), rhodium(III) and palladium(II) catalyze these oxidations, resulting in good to excellent yields. It was observed that in most of the cases palladium(II) chloride is the most efficient catalyst. Conditions for the highest and most economical yields were obtained. Deviation from the optimum conditions decreases the yields. Oxidation in aromatic aldehydes is selective at the aldehydeic group only and other groups remain unaffected. This new, simple and economical method, which is environmentally safe, also requires less time. Reactive species of catalysts, existing in the reaction mixture are also discussed. Copyright © 2007 John Wiley & Sons, Ltd.     

Relationship between heavy metal distribution in sediment samples and their ecotoxicity by the use of the Hasse diagram technique

Many studies assessing the quality of sediments and their pollution impact use monitoring data consisting predominantly of chemical indicators. Recently, ecotoxicity estimates have been used as very important parameters of the ecological state of sediment samples. Thus, a more complete sediment risk assessment is achieved and more reliable information on the sediment pollution history is extracted. The data interpretation could be improved if multivariate statistical techniques were applied to data classification, modelling and interpretation. The starting classification of the data was performed using self-organizing maps (SOM) approach in order to reveal specific relationship patterns for objects and for variables. The original element of the present study is the use of the Hasse diagram technique (HDT) for partial ordering in order to explain some specific relations between the chemical indicators analysed (heavy metal content in different sediment compartments) and the ecotoxicity tests for acute and chronic toxicity. In principle, a reliable estimate of the pollution impact of a large environmental object (the Mar Menor lagoon in Spain) is achieved. The specific role of each one of the five heavy metals involved (Zn, Cu, Mn, Pb, and Cd) is interpreted in the context of the additional ecotoxicity tests.     

Simultaneous determination of iridoids, phenolic acids, flavonoids, and saponins in Flos Lonicerae and Flos Lonicerae Japonicae by HPLC-DAD-ELSD coupled with principal component analysis

A method, HPLC coupled with diode-array and evaporative light scattering detectors (HPLC-DAD-ELSD), was newly developed to evaluate the quality of Flos Lonicerae (FL) and Flos Lonicerae Japonicae (FLJ), through a simultaneous determination of multiple types of bioactive components. By employing DAD, the detection wavelengths were set at 240 nm for the determination of iridoids, 330 nm for phenolic acids, and 360 nm for flavonoids, respectively. While ELSD, connected in series after DAD, was applied to the determination of saponins. This assay was fully validated with respect to precision, repeatability, and accuracy. Moreover, principal component analysis (PCA) was used for the similarity evaluation of different samples, and it was proven straightforward and reliable to differentiate FL and FLJ samples from different origins. For PCA, two principal components have been extracted. Principal component 1 (PC1) influences the separation between different sample sets, capturing 54.598% variance, while principal component 2 (PC2) affects differentiation within sample sets, capturing 12.579% variance. In conclusion, simultaneous quantification of bioactive components by HPLC-DAD-ELSD coupled with PCA would be a well-acceptable strategy to differentiate the sources and to comprehensively control the quality of the medicinal plants FL and FLJ.     

Spectroscopic, thermal and antitumor investigations of sulfasalazine drug in situ complexation with alkaline earth metal ions

The complexes of sulfasalazine (H₃Suz) with some of alkaline metals Mg(II), Ca(II), Sr(II) and Ba(II) have been investigated. Sulfasalazine complexes were synthesized and characterized by spectroscopic tools; infrared spectra, electronic and mass spectra. The IR spectra of the prepared complexes were suggested that the H₃Suz behaves as a bi-dentate ligand through the carboxylic and phenolic groups. The molar conductance measurements gave an idea about the non-electrolytic behavior of the H₃Suz complexes. The thermal decomposition processes for metal(II) complexes of H₃Suz viz: [M(HSuz)(H₂O)₄] (where M = Mg(II), Ca(II), Sr(II) or Ba(II)) have been accomplished on the basis of TG/DTG and DTA studies, and the formula conforms to the stoichiometry of the complexes based on elemental analysis. The kinetic analyses of the thermal decomposition were studied using the Coats–Redfern and Horowitz–Metzger equations. The antitumor and antimicrobial activities of the H₃Suz and their alkaline metal(II) complexes were evaluated.