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.     

Application of Multivariate curve resolution-alternating least square methods on the resolution of overlapping CE peaks from different separation conditions

Discussed in this paper is the development of a new strategy to improve resolution of overlapping CE peaks by using second-order multivariate curve resolution with alternating least square (second-order MCR-ALS) methods. Several kinds of organic reagents are added, respectively, in buffers and sets of overlapping peaks with different separations are obtained. Augmented matrix is formed by the corresponding matrices of the overlapping peaks and is then analyzed by the second-order MCR-ALS method in order to use all data information to improve the precision of the resolution. Similarity between the resolved unit spectrum and the true one is used to assess the quality of the solutions provided by the above method. 3,4-Dihydropyrimidin-2-one derivatives (DHPOs) are used as model components and mixed artificially in order to obtain overlapping peaks. Three different impurity levels, 100, 20, and 10% relative to the main component, are used. With this strategy, the concentration profiles and spectra of impurities, which are no more than 10% of the main component, can be resolved from the overlapping peaks without pure standards participant in the analysis. The effects of the changes in the components spectra in the buffer with different organic reagents on the resolution are also evaluated, which are slight and can thus be ignored in the analysis. Individual data matrices (two-way data) are also analyzed by using MCR-ALS and heuristic evolving latent projections (HELP) methods and their results are compared with those when MCR-ALS is applied to augmented data matrix (three-way data) analysis.     

Trilinearity and component interaction constraints in the multivariate curve resolution investigation of NO and O<Subscript>3</Subscript> pollution in Barcelona

Multiway and multiset data analysis extensions of the multivariate curve resolution alternating least squares (MCR-ALS) method are proposed for the investigation of the temporal distribution of the pollution by nitric oxide (NO) and ozone (O₃) in one sampling station in the urban centre of Barcelona (Catalonia, Spain), during the years 2000–2006. Different specific studies were performed considering the annual and pluriannual contamination by these two contaminants, individually or in combination using different data matrix augmentation strategies and multiway and multiset data analysis models. Daily, hourly and annual profiles were estimated describing different patterns and summarising the main contamination processes. The daily and night trends found were mainly attributed to traffic and photochemical processes favoured by light radiation. Moreover, winter–summer seasonal trends were also clearly detected and their changes over different years assessed. The extension MCR-ALS method to multiset data analysis using different constraints like non-negativity, trilinearity and interaction among components is confirmed to be a powerful method to improve the interpretability of the different contamination patterns in atmospheric contamination studies.     

Analysis of environmental samples by application of multivariate curve resolution on fused high-performance liquid chromatography-diode array detection mass spectrometry data

Multivariate curve resolution-alternating least squares (MCR-ALS) is applied to solve coelution problems in liquid chromatograpy with diode array detection (DAD) and mass spectrometry (MS). Fusion of DAD and MS detector signals improved results versus those obtained using only one of the two detector signals. Application of wavelet transform to MS data before its fusion with DAD data, further help to facilitate the resolution and quantitation of the coeluted compounds under study, besides a decrease of time of analysis. Mixtures of biocide compounds in standard mixtures and in environmental samples (sediment and wastewater samples) were analyzed with estimated quantitation errors below 12%.     

Solving liquid chromatography mass spectrometry coelution problems in the analysis of environmental samples by multivariate curve resolution

Multivariate curve resolution-alternating least squares (MCR-ALS) is shown to be a powerful tool to resolve coelution problems in liquid chromatograpy-mass spectrometry (LC-MS) in scan mode. This investigation was performed using two types of LC columns, one traditional LC column of 25 cm length with a slow gradient and a shorter LC column of 7.5 cm with a rapid gradient which allowed much faster analysis and save of reagents and solvents. Mixtures of multiple biocide compounds were simultaneously analyzed in standard mixtures and in environmental samples (sediment and wastewater samples) with little sample pretreatment. Using the more traditional LC 25 cm column, all biocide compounds were properly resolved by MCR-ALS and quantitatively analyzed with estimated errors always below 20%. When fast chromatography (LC column of 7.5 cm) was used, MCR-ALS resolution of the more strongly coeluted compounds was also achieved but limitations were found in their simultaneous quantitative determination, specially for environmental samples.     

Application of multivariate curve resolution alternating least squares (MCR-ALS) to the quantitative analysis of pharmaceutical and agricultural samples

Application of multivariate curve resolution alternating least squares (MCR-ALS), for the resolution and quantification of different analytes in different type of pharmaceutical and agricultural samples is shown. In particular, MCR-ALS is applied first to the UV spectrophotometric quantitative analysis of mixtures of commercial steroid drugs, and second to the near-infrared (NIR) spectrophotometric quantitative analysis of humidity and protein contents in forage cereal samples. Quantitative results obtained by MCR-ALS are compared to those obtained using the well established partial least squares regression (PLSR) multivariate calibration method.     

Multivariate curve resolution of overlapping voltammetric peaks: quantitative analysis of binary and quaternary metal mixtures

The application of multivariate curve resolution-alternating least squares (MCR-ALS) to the quantitative analysis of different metal ion mixtures using voltammetric data is described. The performance of MCR-ALS was evaluated in the resolution and quantitation of overlapped voltammetric peaks obtained in the analysis of binary and quaternary mixtures of Cd(II), In(III), Pb(II) and Tl(I) metal ions by anodic stripping voltammetry. Quality assessment of qualitative and quantitative determinations was evaluated considering the effects of different constraints and of initial estimations. MCR-ALS results were validated and compared with those obtained by applying other well-established multivariate calibration methods, such as partial least squares (PLS) and direct classical least squares (DCLS) methods.     

Use of chemometric and geostatistical methods to evaluate pesticide pollution in the irrigation and drainage channels of the Ebro river delta during the rice-growing season

Data sets obtained from quantitative analysis of seventeen pesticides in water samples from a network of irrigation and drainage channels in the Ebro river delta (Catalonia, NE Spain) have been analysed by chemometric and geostatistical methods. Samples were taken at fourteen locations during the main rice-growing season, from May to August 2005. Principal-component analysis enabled investigation of the spatial and temporal distribution of the main pollution patterns caused by application of pesticides in the region under study. A first pesticide-contamination pattern from the Ebro river was differentiated from a second more specific pattern from the water-drainage channels of the delta, collected from the rice fields. The seasonal peak in this more specific rice pesticide source was observed in July. Coupling the results from chemometric data analysis with use of geostatistical methods was shown to be a useful procedure for discovery of the most significant spatial and monthly variations of the main pesticide-contamination patterns, taking into account the particular geographical structure of the area under study.     

Mass spectrometry for the detection of differentially expressed proteins: a comparison of surface-enhanced laser desorption/ionization and capillary electrophoresis/mass spectrometry

The discovery of biomarkers is currently attracting much interest as it harbors great potential for the diagnosis and monitoring of human diseases. Here we have used two advanced mass spectroscopy based technologies, surface enhanced laser desorption ionization (SELDI-MS) and capillary electrophoresis/mass spectrometry (CE/MS), to obtain proteomic patterns of urine samples from patients suffering from membranous glomerulonephritis (MGN) and healthy volunteers. The results indicate that CE/MS analysis is able to display a rich and complex pattern of polypeptides with high resolution and high mass accuracy. In order to analyze these patterns, the MosaiqueVisu software was developed for peak identification, deconvolution and the display of refined maps in a three-dimensional format. The polypeptide profiles obtained with SELDI-MS from the same samples are much sparser and show lower resolution and mass accuracy. The SELDI-MS profiles are further heavily dependent on analyte concentration. SELDI-MS analysis identified three differentially expressed polypeptides, which are potential biomarkers that can distinguish healthy donors from patients with MGN. In contrast, approximately 200 potential biomarkers could be identified by CE/MS. Thus, while SELDI-MS is easy to use and requires very little sample, CE/MS generates much richer data sets that enable an in-depth analysis.     

A review on advanced oxidation processes: From classical to new perspectives coupled to two- and multi-way calibration strategies to monitor degradation of contaminants in environmental samples

This paper offers a critical review from classical to new perspectives of advanced oxidation processes (AOPs) coupled to two- and multi-way calibration strategies based on multivariate curve resolution – alternating least-squares (MCR-ALS) and parallel factory analysis (PARAFAC) with various analytical techniques to monitor the degradation of contaminants in environmental samples. It focuses on the generation of highly reactive hydroxyl (HO•) radicals (classical AOPs with emphasis on Fenton, photo-Fenton and ozonation processes) and emerging reactive sulphate (SO₄^•−) radicals (new perspectives of AOPs) for effective degradation of recalcitrant compounds. Other new perspectives of AOPs were also addressed, namely semiconductor photocatalysis (TiO₂/UV), combination of processes involving at least one AOP (hybrid or single-step processes and sequential or two-step processes), novel advanced electrochemical oxidation technologies (electro-Fenton and electro-photo-Fenton) and nanocatalytic heterogeneous Fenton technology with high specific surface area. Literature reports since 2008 for real applications in the environmental remediation based on AOPs (from classical to new perspectives) coupled to PARAFAC and MCR-ALS with first-, second- and third-order data were reviewed and the improvements obtained were briefly discussed. The two- and multi-way calibration strategies allow one the successful decomposition of first-, second- and third-order data collected from different analytical techniques. Therefore, the respective profiles obtained allowed qualitative (spectral profiles) and quantitative (concentration profiles) analysis of complex samples during the degradation of contaminants through the second-order advantage. Finally, trends of future research directions for AOPs coupled to various analytical techniques and advanced chemometric models were provided.     

Application of Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) to remote sensing hyperspectral imaging

The application of the MCR-ALS method is demonstrated on two simulated remote sensing spectroscopic images and on one experimental reference remote sensing spectroscopic image obtained by the Airborn Visible/Infrared Imaging Spectrometer (AVIRIS). By application of MCR-ALS, the spectra signatures of the pure constituents present in the image and their concentration distribution at a pixel level are estimated. Results obtained by MCR-ALS are compared to those obtained by other methods frequently used in the remote sensing spectroscopic imaging field like VCA and MVSA. In the case of the analysis of the experimental data set, the resolved pure spectra signatures were compared to reference spectra from USGS library for their identification. In all cases, results were also evaluated for the presence of rotational ambiguities using the MCR-BANDS method. The obtained results confirmed that the MCR-ALS method can be successfully used for remote sensing hyperspectral image resolution purposes. However, the amount of rotation ambiguity still present in the solutions obtained by this and other resolution methods (like VCA or MVSA) can still be large and it should be evaluated with care, trying to reduce its effects by selecting the more appropriate constraints. Only in this way it is possible to increase the reliability of the solutions provided by these methods and decrease the uncertainties associated to their use.     

Antarctic marine sediments as fingerprints of pollution migration

Forty elements in 21 coastal marine sediment samples collected duringthe second Antarctic scientific expedition from 18 different sites of Brekilenarea located at the coast of Antarctica were analysed by instrumental neutronactivation analysis (INAA) to detect eventual pollution. Radio-assay schemesfor three sets of elements after neutron irradiation and cooling were evolvedto avoid matrix effects. Data have been compared with those for sedimentsof various stations at Antarctica and two other regions in different continents.Lower concentration of certain elements in the Antarctic sediments reflectsless environmental exposition. Enrichment factors (EF) were calculated forall the elements using the earth crust as reference matrix, based on elementalvalues by MASON, TAYLOR and WEDEPOHL which show a normal pattern near to unityexcept for Ag and Br. The data obtained could also serve as a reference pointfrom which changes in the global environment can be studied. The quality assuranceof data was performed using standard reference materials (SRMs) of a similarmatrix (IAEA Marine Sediment SD-M/TM and Chinese Marine Sediment GBW 07313).     

Multivariate Observations of the Distribution of Polychlorinated Biphenyls in Environmental Compartments of Two Harbours

Abstract

The objectives of this study were to identify, classify and categorize polychlorinated biphenyl (PCB) residues in samples collected from the Hamilton and Wheatley Harbour environmental compartments. The study is built around the use of a principal components analysis method, namely the soft independent modelling of class analogy (SIMCA) technique. This multivariate method is widely used for evaluating differences and observing similarities among multiple objects. The results obtained from this work confirm that the gas chromatographic data sets obtained with the samples provide a good approximation of the pattern derived from a determination of the composition of commercial Aroclors in water, sediment and biota samples. The data analysis technique provides insight into the origin of PCB contamination in environmental samples and indicates pathways for the environmental degradation or bioaccumulation of PCBs. This investigation contributes some evidence that multivariate reduction techniques are suitable for the investigation of complex data sets in environmental studies.     

多元曲线分辨-交替最小二乘方法在联用数据分辨中的应用

通过对模拟数据和高效毛细管电泳实验数据的分析,讨论了多元曲线分辨-交替最小二乘方法(MCR-ALS)在毛细管电泳-二极管阵列检测(CE-DAD)联用数据分辨中的应用.讨论了几种因素对MCR-ALS单个数据矩阵分辨结果的影响,包括待分析物光谱间的相似程度、浓度曲线的重叠程度以及由渐进因子分析(EFA)所得到的浓度初始值等.MCR-ALS还可用于多个数据矩阵的同时分析,即二阶MCR-ALS.结果表明,与一阶MCR-ALS相比,二阶MCR-ALS方法能够更好地解决各种分辨问题,得到合理和满意的分辨结果.     

通过红外光谱结合化学计量学方法研究奥克托今的合成机理

通过红外(IR)光谱在线监测醋酐法合成奥克托今(HMX)的反应过程, 采用渐进因子分析(EFA)结合多元曲线分辨-交替最小二乘法(MCR-ALS)以及直观推导式演进特征投影法(HELP)等化学计量学方法对反应过程的光谱数据矩阵进行解析, 获得了各组分浓度变化曲线和对应的IR光谱; 并采用密度泛函理论(DFT)的B3LYP方法, 在6-31G^*基组水平上得到该化合物的全优化结构, 在振动分析的基础上求得体系的振动频率和IR光谱. 通过对比发现, MCR-ALS和HELP法可得出相互验证的一致结论; 将通过量子化学计算的中间体的IR光谱特征吸收峰与2种方法进行比较, 结果吻合, 从而推导出合理的反应机理. 实验结果表明, 化学计量学方法结合在线红外光谱是研究反应机理的有效手段, 对反应路线的选择具有指导意义.     

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.     

Novel combination of non-aqueous capillary electrophoresis and multivariate curve resolution-alternating least squares to determine phenolic acids in virgin olive oil

This paper presents the development of a non-aqueous capillary electrophoresis method coupled to UV detection combined with multivariate curve resolution-alternating least-squares (MCR-ALS) to carry out the resolution and quantitation of a mixture of six phenolic acids in virgin olive oil samples. p-Coumaric, caffeic, ferulic, 3,4-dihydroxyphenylacetic, vanillic and 4-hydroxyphenilacetic acids have been the analytes under study. All of them present different absorption spectra and overlapped time profiles with the olive oil matrix interferences and between them. The modeling strategy involves the building of a single MCR-ALS model composed of matrices augmented in the temporal mode, namely spectra remain invariant while time profiles may change from sample to sample. So MCR-ALS was used to cope with the coeluting interferences, on accounting the second order advantage inherent to this algorithm which, in addition, is able to handle data sets deviating from trilinearity, like the data herein analyzed. The method was firstly applied to resolve standard mixtures of the analytes randomly prepared in 1-propanol and, secondly, in real virgin olive oil samples, getting recovery values near to 100% in all cases. The importance and novelty of this methodology relies on the combination of non-aqueous capillary electrophoresis second-order data and MCR-ALS algorithm which allows performing the resolution of these compounds simplifying the previous sample pretreatment stages.     

Interaction of anionic dyes and cationic surfactants with ionic liquid character

The interactions of an imidazolium based ionic liquid (IL), namely 1-dodecyl-3-methylimidazolium chloride [C12 mim][Cl] with two sulfonated anionic dyes, azocarmine G and methyl orange, are studied spectrophotometrically in both acidic and basic media. ILs (with some surface active character) can interact with the above dyes and cause considerable shifts in their spectra. These interactions are then compared with some surfactant-dye interactions. Evolving factor analysis (EFA) and multivariate curve resolution-alternating least squares (MCR-ALS) are used for complete resolution of the measured spectrophotometric data. The concentration and spectral profiles of all species were calculated without any assumption of the chemical models. The spectral variation of dye solutions as a function of IL concentrations below and above the critical aggregation concentration (CAC) is analyzed using MCR-ALS as a soft-modeling technique. The ion pair formation constants between ILs and dyes were calculated using the obtained concentration profiles.     

Resolution of multicomponent overlapped peaks A comparison of several curve resolution methods

Several curve resolution methods were compared in their performance of identification and quantification of overlapping peaks. These resolution methods are heuristic evolving latent projections (HELP), sub-window factor analysis (SFA), and orthogonal projection resolution (OPR). In this paper, HELP, SFA and OPR with the rank map produced by evolving factor analysis (EFA) or fixed size moving window-evolving factor analysis (FSMW-EFA) were applied to the simulated and experimental data. The resolved results were compared qualitatively and quantitatively. In addition, the further comparison was carried out with the results obtained from multivariate curve resolution-alternate least square (MCR-ALS) by using the initial estimates provided by EFA.     

Multivariate curve resolution of pH gradient flow injection mixture analysis with correction of the Schlieren effect

Multivariate curve resolution using alternating least squares (MCR-ALS) was used to quantify ascorbic (AA) and acetylsalicylic (ASA) acids in four pharmaceutical samples using a flow injection analysis (FIA) system with pH gradient and a diode array (DAD) spectrometer as a detector. Four different pharmaceutical drugs were analyzed, giving a data array of dimensions 51 x 291 x 61, corresponding respectively to number of samples, FIA times and spectral wavelengths. MCR-ALS was applied to these large data sets using different constraints to have optimal resolution and optimal quantitative estimations of the two analytes (AA and ASA). Since both analytes give an acid-basic pair of species contributing to the UV recorded signal, at least four components sholuld be proposed to model AA and ASA in synthetic mixture samples. Moreover, one additional component was needed to resolve accurately the Schlieren effect and another additional component was also needed to model the presence of possible interferences (like caffeine) in the commercial drugs tablets, giving therefore a total number of 6 independent components needed. The best quantification relative errors were around 2% compared to the reference values obtained by HPLC and by the oxidation-reduction titrimetric method, for ASA and AA respectively. In this work, the application of MCR-ALS allowed for the first time the full resolution of the FIA diffusion profile due to the Schlieren effect as an independent signal contribution, suggesting that the proposed MCR-ALS method allows for its accurate correction in FIA-DAD systems.