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A strong red fluorescent nanocomposite, consisting of graphite-like carbon nitride nanosheets (g-C3N4 NSs) and serum albumin-capped Au nanoclusters (AuNCs), was synthesized. Dopamine (DA) can quench the red fluorescence of the nanocomposite, based on the Forster resonance energy transfer (FRET) mechanism. In this quenching process, the energy is transferred from the fluorescent g-C3N4 NSs-AuNCs to the oxidized DA quinine molecules (DA is easily oxidated to form DA quinine in air). The red fluorescence emission at 420 nm decreases dramatically and the quenching ratio (F0 – F)/F0 is linearly related to the concentration of DA in the range of 0.05–8.0 μmol L−1 with a detection limit of 0.018 μmol L−1 (S/N = 3). Additionally, this sensor has a potential of application to assay the DA in the real samples, such as human serum and human urine.

The interactions of the sugars glucose and lactose with the transport protein bovine serum albumin (BSA) were investigated using fluorescence, FT-IR and circular dichroism (CD) techniques. The results indicated that glucose could be bonded and transported by BSA, mainly involving hydrogen bonds and van der Waals interactions (ΔH = -86.13 kJ mol(-1)). The obtained fluorescence data from the binding of sugar and BSA were processed by the multivariate curve resolution-alternating least squares (MCR-ALS) method, and the extracted concentration profiles showed that the equilibrium constant, rglucose:BSA, was about 7. However, the binding of lactose to BSA did not quench the fluorescence significantly, and this indicated that lactose could not be directly transported by BSA. The binding experiments were further performed using the fluorescence titration method in the presence of calcium and BSA. Calcium was added so that the calcium/BSA reactions could be studied in the presence or absence of glucose, lactose or hydrolysis products. The results showed that hydrolyzed lactose seemed to enhance calcium absorption in bovine animals. It would also appear that for children, lactose provides better nutrition; however, glucose is better for adults.

An electrochemical biosensor capable of indirect detection of DNA damage induced by any one of the three endocrine-disrupting compounds (EDCs) – bisphenol A (BPA), 4-nonylphenol (NP) and 4- t -octylphenol (OP), has been researched and developed. The methylene blue (MB) dye was used as the redox indicator. The glassy carbon electrode (GCE) was modified by the assembled dsDNA/graphene oxide-chitosan/gold nano-particles to produce a dsDNA/GO-CS/AuNPs/GCE sensor. It was characterized with the use of electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV) and scanning electron microscopy (SEM) techniques. The loading/release of the MB dye by the dsDNA/GO-CS/AuNPs film was investigated, and the results showed that the process was reversible. Based on this, the sensor was used to measure the difference between the loading capabilities of intact and damaged dsDNA in the films. The sensor was then successfully applied to detect DNA damage electrochemically. The differential pulse voltammetry (DPV) peak current ratio for MB, observed before and after DNA damage, increased linearly in the presence the BPA, NP or OP compounds; the treatment range was 10–60 min, and the respective damage rates were 0.0069, 0.0044 and 0.0031 min −1 , respectively. These results were confirmed by the binding constants: 2.09 × 10 6 M −1 (BPA-DNA), 1.28 × 10 6 M −1 (NP-DNA) and 9.33 × 10 5 M −1 (OP-DNA), all of which were obtained with the use of differential pulse stripping voltammetry (DPSV).

Molybdenum disulfide (MoS2) is an emerging material with some unique physical and electronic properties somewhat comparable to those of graphene. It was prepared with the use of a simple hydrothermal process, and has a layered structure similar to that of graphene. Also, it has a peroxidase-like catalytic activity and is able to catalyze the oxidation of the colorless peroxidase substrate, 3,3',5,5'-tetramethylbenzidine (TMB), in the presence of H2O2 to produce a blue product. This reaction used MoS2 as a useful peroxidase, which involved a colorimetric method for trace analysis of H2O2 in water, e.g. lake waters. This method is uncomplicated, inexpensive and highly sensitive for H2O2 in the 0.125-1.75 μM range (LOD: 0.08 μM). It is also quite stable in the presence of many common inorganic and organic potentially interfering compounds, e.g. metal ions as well as amino acids and sugars.

A novel, uncomplicated and rapid method of analysis for organophosphorus (OP) pesticides was researched and developed using the important, common OP, dipterex, as a typical example. The basis of the method involved the citrate-capped silver nanoparticles (citrate-capped AgNPs) and Acetylthiocholine (ATCh). The latter compound can be catalyzed by Acetylcholinesterase (AChE) to form thiocholine (TCh), which induces the aggregation of AgNPs. Correspondingly, the color of AgNPs in solution changes from bright yellow to pink, and the UV–vis characteristic absorption peak of AgNPs at about 400 nm decreases; simultaneously, a new absorption band appears at about 520 nm. Irreversible inhibition of AChE activity caused by dipterex, prevents the aggregation of AgNPs. Thus, a UV–vis spectrophotometric method was developed for the analysis of dipterex. The absorbance ratio A396 nm/A520 nm was found to be linearly related to the concentration of dipterex in the range of 0.25–37.5 ng mL−1 with a detection limit of 0.18 ng mL−1. This method was used successfully to analyse dipterex in spiked, different water samples.

Hydrogen peroxide is an important analyte in biochemical, industrial and environmental systems. Therefore, development of novel rapid and sensitive analytical methods is useful. In this work, a hemin-graphene nano-sheets (H-GNs)/gold nano-particles (AuNPs) electrochemical biosensor for the detection of hydrogen peroxide (H2O2) was researched and developed; it was constructed by consecutive, selective modification of the GCE electrode. Performance of the H-GNs/AuNPs/GCE was investigated by chronoamperometry, and AFM measurements suggested that the graphene flakes thickness was ∼1.3 nm and that of H-GNs was ∼1.8 nm, which ultimately indicated that each hemin layer was ∼0.25 nm. This biosensor exhibited significantly better electrocatalytic activity for the reduction of hydrogen peroxide in comparison with the simpler AuNPs/GCE and H-GNs/GCE; it also displayed a linear response for the reduction of H2O2 in the range of 0.3 μM to 1.8 mM with a detection limit of 0.11 μM (S N−1 = 3), high sensitivity of 2774.8 μA mM−1 cm−2, and a rapid response, which reached 95% of the steady state condition within 5 s. In addition, the biosensor was unaffected by many interfering substances, and was stable over time. Thus, it was demonstrated that this biosensor was potentially suitable for H2O2 analysis in many types of sample.

The interaction of graphene oxide (GO), a medicinal drug (10-hydroxy camptothecin (HCPT)), and bovine serum albumin (BSA) was investigated with the aim of developing a method for the analysis of serum albumin proteins. It was demonstrated that HCPT could be readily loaded onto GO via the π–π stacking interaction, and the delivery of HCPT to BSA was improved in the presence of GO; this, in turn, facilitated the binding interaction of HCPT and BSA. Chemometrics methods, multivariate curve resolution-alternating least squares (MCR-ALS) and parallel factor analysis (PARAFAC), were applied to resolve spectral data, and this assisted in the elucidation of the above interaction. GO was found to enhance the fluorescence response of HCPT to BSA, and thus, a low cost fluorescence bio-sensing platform was developed for fluorescence-enhanced detection of BSA based on GO. The satisfactory analytical performance of this biosensor for BSA was attributed to the structure and electronic properties of GO.

Solids are widely identified as a carrier of harmful pollutants in stormwater runoff exerting a significant risk to receiving waters. This paper outlines the findings of an in-depth investigation on heavy metal adsorption to solids surfaces. Pollutant build-up samples collected from 16 road sites in residential, industrial, and commercial land uses were separated into four particle size ranges and analyzed for a range of physicochemical parameters and nine heavy metals including Iron (Fe), Aluminum (Al), Lead (Pb), Zinc (Zn), Cadmium (Cd), Chromium (Cr), Manganese (Mn), Nickel (Ni), and Copper (Cu). High specific surface area (SSA) and total organic carbon (TOC) content in finer particle size ranges were noted, thus confirming strong correlations with heavy metals. On the basis of their physicochemical characteristics, two different types of solids originating from traffic and soil sources were identified. Solids generated by traffic were associated with high loads of heavy metals, such as Cd and ...

Many complex natural or synthetic products are analysed either by the GC-MS (gas chromatography-mass spectrometry) or HPLC-DAD (high performance liquid chromatography-diode-array detector) technique, each of which produces a one-dimensional fingerprint for a given sample. This may be used for classification of different batches of a product. GC-MS and HPLC-DAD analyses of complex, similar substances represented by the three common types of the TCM (traditional Chinese medicine), Rhizoma Curcumae were analysed in the form of one- and two-dimensional matrices firstly with the use of PCA (Principal component analysis), which showed a reasonable separation of the samples for each technique. However, the separation patterns were rather different for each analytical method, and PCA of the combined data matrix showed improved discrimination of the three types of object; close associations between the GC-MS and HPLC-DAD variables were observed. LDA (linear discriminant analysis), BP-ANN (back propagation-artificial neural networks) and LS-SVM (least squares-support vector machine) chemometrics methods were then applied to classify the training and prediction sets. For one-dimensional matrices, all training models indicated that several samples would be misclassified; the same was observed for each prediction set. However, by comparison, in the analysis of the combined matrix, all models gave 100% classification with the training set, and the LS-SVM calibration also produced a 100% result for prediction, with the BP-ANN calibration closely behind. This has important implications for comparing complex substances such as the TCMs because clearly the one-dimensional data matrices alone produce inferior results for training and prediction as compared to the combined data matrix models. Thus, product samples may be misclassified with the use of the one-dimensional data because of insufficient information.

A novel kinetic spectrophotometric method was developed for determination of pyrocatechol, resorcin, hydroquinone and phenol based on their inhibitory effect on the oxidation of Rhodamine B (RhB) in acid medium at pH=3.0. A linear relationship was observed between the inhibitory effect and the concentrations of the compounds. The absorbance associated with the kinetic reactions was monitored at the maximum wavelength of 557nm. The effects of different parameters such as pH, concentration of RhB and KBrO(3), and temperature of the reaction were investigated and optimum conditions were established. The linear ranges were 0.22-3.30, 0.108-0.828, 0.36-3.96 and 1.52-19.76μg mL(-1) for pyrocatechol, resorcin, hydroquinone and phenol, respectively, and their corresponding detection limits were 0.15, 0.044, 0.16 and 0.60μg mL(-1). The measured data were processed by several chemometrics methods, such as principal component regression (PCR), partial least squares (PLS) and artificial neural network (ANN), and a set of synthetic mixtures of these compounds was used to verify the established models. It was found that the prediction ability of PLS, PCR and RBF-ANN was similar, however, the RBF-ANN model did perform somewhat better than the other methods. The proposed method was also applied satisfactorily for the simultaneous determination of pyrocatechol, resorcin, hydroquinone and phenol in real water samples.

An investigation into the effects of changes in urban traffic characteristics due to rapid urbanisation and the predicted changes in rainfall characteristics due to climate change on the build-up and wash-off of heavy metals was carried out in Gold Coast, Australia. The study sites encompassed three different urban land uses. Nine heavy metals commonly associated with traffic emissions were selected. The results were interpreted using multivariate data analysis and decision making tools, such as principal component analysis (PCA), fuzzy clustering (FC), PROMETHEE, and GAIA. Initial analyses established high, low, and moderate traffic scenarios as well as low, low to moderate, moderate, high, and extreme rainfall scenarios for build-up and wash-off investigations. GAIA analyses established that moderate to high traffic scenarios could affect the build-up, while moderate to high rainfall scenarios could affect the wash-off of heavy metals under changed conditions. However, in wash-off, metal concentrations in 1-75 μm fraction were found to be independent of the changes to rainfall characteristics. In build-up, high traffic activities in commercial and industrial areas influenced the accumulation of heavy metal concentrations in particulate size range from 75 -300 μm, whereas metal concentrations in finer size range of1-75 μm were not affected. As practical implications, solids1 μm and organic matter from 1 -300 μm can be targeted for removal of Ni, Cu, Pb, Cd, Cr, and Zn from build-up, while organic matter from1 -300 μm can be targeted for removal of Cd, Cr, Pb, and Ni from wash-off. Cu and Zn need to be removed as free ions from most fractions in wash-off.

This article discusses the outcomes of a research project on nutrients build-up on urban road surfaces. Nutrient build-up was investigated on road sites belonging to residential, industrial and commercial land use. Collected build-up samples were separated into five particle size ranges and were tested for total nitrogen (TN), total phosphorus (TP) and sub species of nutrients, namely, NO2-, NO3-, TKN and PO4(3-). Multivariate analytical techniques were used to analyse the data and to develop detailed understanding on buildup. Data analysis revealed that the solids loads on urban road surfaces are highly influenced by factors such as land use, antecedent dry period and traffic volume. However, the nutrient build-up process was found to be independent of the type of land use. It was solely dependent on the particle size of solids build-up. Most of the nutrients were associated with the particle size range150 microm. Therefore, the removal of particles below 150 microm from road surfaces is of importance for the removal of nitrogen and phosphorus from road surface solids build-up. It is also important to consider the difference in the composition of nitrogen and phosphorus build-up in the context of designing effective stormwater quality mitigation strategies.

A method for the simultaneous enzymatic kinetic determination of the pesticides, oxamyl, aldicarb and aminocarb in fruit, vegetables and water samples, has been researched and developed. It was based on enzymatic reaction kinetics and spectrophotometric measurements, and results were interpreted with the aid of chemometrics. The analytical method relies on the inhibitory effect of the pesticides on acetylcholinesterase (AChE), and the use of 5,5′-dithiobis (2-nitrobenzoic) acid (DTNB) as a chromogenic reagent for the thiocholine iodide (TChI) released from the acetylthiocholine iodide (ATChI) substrate. The complex rate equation for the formation of the chromogenic product, P, was solved under certain experimental conditions, and this enabled the absorbance (A p, at λ max = 412 nm) from the mixtures of the three pesticide inhibitors to be directly related to their concentrations. The detection limits of the enzymatic kinetic spectrophotometric procedures for the determination of the oxamyl, aldicarb and a...

A procedure for the simultaneous kinetic spectrophotometric determination of aminocarb and carbaryl in vegetable and water samples was described. The method was based on the differential oxidation rate of aminocarb and carbaryl when they were reacted with the oxidant, potassium ferricyanide (K 3 Fe(CN) 6 ), in an appropriate alkaline medium. Both species were instantly oxidized, and resulted in a decrease of ferricyanide concentration. This anion has a maximum spectral absorbance at about 420 nm. Under the optimum experimental conditions, the linear ranges were 0.05–0.6 mg L −1 and 0.1–1.2 mg L −1 for aminocarb and carbaryl, respectively. The kinetic data collected were processed by chemometrics methods, such as classical least squares (CLS), partial least squares (PLS), principal components regression (PCR), back propagation-artificial neural network (BP-ANN), radial basis function-artificial neural network (RBF-ANN), and principal component-radial basis function-artificial neural network (PC-RBF-ANN). These methods were applied for the prediction of the two carbamate pesticides. The results showed that the PLS and PC-RBF-ANN calibration models gave the lowest prediction errors. The proposed method was successfully applied to the simultaneous determination of aminocarb and carbaryl in vegetable and water samples, and satisfactory results were obtained.

Multi-wavelength fingerprints of Cassia seed, a traditional Chinese medicine (TCM), were collected by high-performance liquid chromatography (HPLC) at two wavelengths with the use of diode array detection. The two data sets of chromatograms were combined by the data fusion-based method. This data set of fingerprints was compared separately with the two data sets collected at each of the two wavelengths. It was demonstrated with the use of principal component analysis (PCA), that multi-wavelength fingerprints provided a much improved representation of the differences in the samples. Thereafter, the multi-wavelength fingerprint data set was submitted for classification to a suite of chemometrics methods viz. fuzzy clustering (FC), SIMCA and the rank ordering MCDM PROMETHEE and GAIA. Each method highlighted different properties of the data matrix according to the fingerprints from different types of Cassia seeds. In general, the PROMETHEE and GAIA MCDM methods provided the most comprehensive information for matching and discrimination of the fingerprints, and appeared to be best suited for quality assurance purposes for these and similar types of sample.

Synchronous fluorescence spectroscopy (SFS) was applied for the investigation of interactions of the antibiotic, tetracycline (TC), with DNA in the presence of aluminium ions Al3+. The study was facilitated by the use of the Methylene Blue (MB) dye probe, and the interpretation of the spectral data with the aid of the chemometrics method, parallel factor analysis (PARAFAC). Three-way synchronous fluorescence analysis extracted the important optimum constant wavelength differences, deltalambda, and showed that for the TC-Al3+-DNA, TC-Al3+ and MB dye systems, the associated deltalambda values were different (deltalambda=80, 75 and 30 nm, respectively). Subsequent PARAFAC analysis demonstrated the extraction of the equilibrium concentration profiles for the TC-Al3+, TC-Al3+-DNA and MB probe systems. This information is unobtainable by conventional means of data interpretation. The results indicated that the MB dye interacted with the TC-Al3+-DNA surface complex, presumably via a reaction intermediate, TC-Al3+-DNA-MB, leading to the displacement of the TC-Al3+ by the incoming MB dye probe.

A sensitive and selective enzymatic kinetic method for the simultaneous determination of mixtures of carbaryl and phoxim pesticides was researched and developed. It was based on the inhibitory effect of the pesticides on acetylcholinesterase (AChE), and the use of 5,5′-dithiobis(2-nitrobenzoic) acid (DTNB) as a chromogenic reagent for the thiocholine iodide (TChI) released from the acetylthiocholine iodide (ATChI) substrate. The DTNB-thiocholine reaction was investigated by a spectrophotometric-kinetic approach. The complex rate equation for the formation of the chromogenic product, P, was solved under certain experimental conditions, which enabled the absorbance ( A P , at λ max = 412 nm) from the mixtures of the two pesticide inhibitors to be directly related to their concentrations provided the absorbance additivity was followed. The spectra were measured for mixtures of carbaryl and phoxim at different concentrations, and at t = 904 s, T = 35 °C, pH = 7.5, c ATChI = 0.14, and c AChE = 0.10 mg mL −1 . The detection limits of the enzymatic kinetic spectrophotometric procedures for the determination of the carbaryl and phoxim were 4.7 and 0.59 μg L −1 , respectively. Calibration models for chemometrics methods, such as principal component regression (PCR), partial least squares (PLS) and radial basis function-artificial neural network (RBF-ANN) were constructed and verified with synthetic samples of the mixtures of the two pesticides. The best performing model was based on the RBF-ANN method yielding at approximately 10 ppb analyte concentrations, %RPE T (carbaryl = 5.2; phoxim = 6.5), %Recovery (approx.105%) and %RPE T (6.5). Various spiked town-water samples produced recoveries in the range of 98.8–103% for each pesticide.

Summary Physico-chemical properties of surface water and groundwater samples from some developing countries have been subjected to multivariate analyses by the non-parametric multi-criteria decision-making methods, PROMETHEE and GAIA. Complete ranking information necessary to select one source of water in preference to all others was obtained, and this enabled relationships between the physico-chemical properties and water quality to be assessed. Thus, the ranking of the quality of the water bodies was found to be strongly dependent on the total dissolved solid, phosphate, sulfate, ammonia–nitrogen, calcium, iron, chloride, magnesium, zinc, nitrate and fluoride contents of the waters. However, potassium, manganese and zinc composition showed the least influence in differentiating the water bodies. To model and predict the water quality influencing parameters, partial least squares analyses were carried out on a matrix made up of the results of water quality assessment studies carried out in Nigeria, Papua New Guinea, Egypt, Thailand and India/Pakistan. The results showed that the total dissolved solid, calcium, sulfate, sodium and chloride contents can be used to predict a wide range of physico-chemical characteristics of water. The potential implications of these observations on the financial and opportunity costs associated with elaborate water quality monitoring are discussed.

The interactions of salicylic acid (SL) and two different site markers (warfarin for site I and ibuprofen for site II) with bovine serum albumin (BSA) in pH 7.4 Tris–HCl buffer have been investigated with the use of spectrofluorimetry. An equilibrium solution of BSA and SA was titrated separately with the two markers. This initial work showed that the binding of SL with BSA could be quite complex, and that there was probably a competitive interaction occurring between ibuprofen and SL. However, the spectral results were difficult to interpret clearly for the interaction of warfarin and SL in similar circumstances. To extract more information from the resolution of fluorescence excitation-emission spectra, the contour plots of the fluorescence spectra indicated that the optimal excitation wavelengths for BSA, SL, warfarin and ibuprofen were different, and were found to be at 278, 295, 306 and 218 nm, respectively. The spectral information was arranged into three-way excitation-emission fluorescence matrix (EEM) stack arrays, and was submitted for analysis by the parallel factor analysis (PARAFAC) algorithm. Firstly, it was demonstrated that the estimated excitation and emission spectral responses for SL, BSA and the site markers, warfarin and ibuprofen, agreed well with the measured spectra. Then, the interpretation of the plots of simultaneously extracted (by PARAFAC) equilibrium concentrations for the above four reactants, showed that: (i) the SL primarily appears to bind in site I but at a different location from the high-affinity binding site (HAS) for warfarin, and the interaction partially overlaps with the low-affinity binding site (LAS) for warfarin. (ii) The SL may have two LAS—one in site II where the HAS for ibuprofen is located, and the other in site I at the LAS for ibuprofen. Thus, application of the PARAFAC method for the study of competitive interaction of SL and BSA with the aid of two different site markers has extracted information unobtainable by traditional methods such as the Scatchard plot, and provided useful means of data visualization.

Voltammetric behaviour of four carbamate pesticides, propoxur, isoprocarb, carbaryl and carbofuran, was investigated, and a method was developed for the simultaneous determination of these compounds. This was based on their anodic voltammetric behaviour observed following their alkaline hydrolysis, which produced electroactive phenol derivatives. It was found that by applying the differential pulse voltammertric (DPV) method in the presence of perchloric acid, the four compounds have well defined voltammetric oxidation waves with peak potentials at 712, 888, 664, and 688 mV, respectively. For each compound, a linear calibration was obtained in the concentration range of 1.0–30 mg l −1 . Serious overlapping of individual voltammetric peaks was observed for the mixtures of these four compounds, and to facilitate the resolution of these complex voltammograms, different calibration models were investigated based on four different chemometrics methods, viz., classical least squares (CLS), principal component regression (PCR), partial least squares (PLS) and radial basis function-artificial neural networks (RBF-ANN). The prediction ability of these models were tested with the use of a data set constructed from synthetic solutions of the four pesticides. The analytical performance of the prediction models was characterized with the use of various figures of merit, and the best results were obtained with the PC-RBF-ANN method (%RPE T = 5.6 and %Recovery (average) = 100). This method was then applied for the determination of the four pesticides in different water samples.

A differential pulse stripping voltammetry method (DPSV) is proposed for the determination of parathion-methyl (PTM), fenitrothion (FT) and parathion (PT) at a hanging mercury drop electrode (HMDE). The voltammograms of these three compounds overlap strongly, and it is difficult to determine the compounds individually from their mixtures. Quantitative analysis for each of the pesticide compounds in a mixture has been investigated with the aid of chemometrics and the prediction performance of the different methods such as classical least squares (CLS), principal component regression (PCR), partial least squares (PLS), Kalman filter (KF) and radial basis function-artificial neural networks (RBF-ANN), was compared. A set of synthetic mixtures of the three compounds was analysed by using the proposed methods, and it was found that the lowest relative prediction error (RPE) and satisfactory % recovery were achieved with the RBF-ANN procedure. The proposed method was also applied to several vegetable samples spiked with known amounts of the pesticides with satisfactory results.

This paper presents a study undertaken to evaluate site suitability for sewage effluent renovation based on physico-chemical characteristics of the soil. The results obtained showed that as the soil becomes acidic, the phosphorus concentration in the soil reduces accordingly. The chloride ion concentration was found to be a reliable indicator for evaluating the soil capacity to remove nitrogen. A high cation exchange capacity (CEC) can enhance the renovation of sewage effluent. Soils with high quartz content had a low CEC with high organic matter content (OM) being able to compensate. Therefore, an understanding of the micro-nutrients in the soil, organic matter content and chloride ion concentration are important. To facilitate a multi-variate approach for site selection, multicriteria decision-making (MCDM) methods, PROMETHEE and GAIA, were applied for analysis of a sequence of three matrices consisting of 8, 16, and 48 soil site objects, respectively, and seven soil property parameters. Matrix models and the interpretation of results are discussed in detail. From these analyses, PROMETHEE II net outranking flows, ϕ , found that two sites were always among the top three ranks of the three matrix models, which suggested that they were the most suitable for sewage effluent renovation. The criteria CEC and OM, were particularly important for the selection of these better sites, but pH and Cl − attributes discriminated the weaker performing sites from the better ones; as well the PO 4 3− and the NH 3 –N criteria were in general opposition to CEC, OM, pH and Cl − but were much less effective as discriminators. Consideration of net outranking flows suggested an approach method for the selection of other possibly suitable sites for sewage effluent renovation.

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.

A novel electrochemical biosensor, DNA/hemin/nafion–graphene/GCE, was constructed for the analysis of the benzo(a)pyrene PAH, which can produce DNA damage induced by a benzo(a)pyrene (BaP) enzyme-catalytic product. This biosensor was assembled layer-by-layer, and was characterized with the use of cyclic voltammetry, electrochemical impedance spectroscopy (EIS) and atomic force microscopy. Ultimately, it was demonstrated that the hemin/nafion–graphene/GCE was a viable platform for the immobilization of DNA. This DNA biosensor was treated separately in benzo(a)pyrene, hydrogen peroxide (H2O2) and in their mixture, respectively, and differential pulse voltammetry (DPV) analysis showed that an oxidation peak was apparent after the electrode was immersed in H2O2. Such experiments indicated that in the presence of H2O2, hemin could mimic cytochrome P450 to metabolize benzo(a)pyrene, and a voltammogram of its metabolite was recorded. The DNA damage induced by this metabolite was also detected by electrochemical impedance and ultraviolet spectroscopy. Finally, a novel, indirect DPV analytical method for BaP in aqueous solution was developed based on the linear metabolite versus BaP concentration plot; this method provided a new, indirect, quantitative estimate of DNA damage.

The voltammetric behavior of antipsychotic drugs, such as, chlorpromazine hydrochloride and promethazine hydrochloride has been investigated at a glassy carbon electrode in Britton–Robinson buffer of pH 9. It was found by applying the differential pulse stripping voltammetry (DPSV) that both chlorpromazine hydrochloride and promethazine hydrochloride had well formed oxidation voltammetric waves, with the peak potential for chlorpromazine hydrochloride at 620 mV, and for the two peaks of promethazine hydrochloride at 444 and 668 mV. The calibrations were linear for chlorpromazine hydrochloride and promethazine hydrochloride in the concentration ranges of 0.05–1.2 and 0.1–1 mg l−1, respectively. However, the voltammetric peaks of these two drugs, seriously overlap and it is difficult to determine them individually from a response of a drug mixture. In this work, a method for the simultaneous determination of these two drugs is proposed, and is based on their oxidation at the glassy carbon electrode. The interpretation of the complex voltammograms is achieved with the aid of chemometric methods, such as, classical least squares (CLS), principal component regression (PCR) and partial least squares (PLS). The proposed method was applied to determine these two drugs in a set of synthetic mixtures and blood samples, and in general, satisfactory results were obtained.

The voltammetric behaviour of five nitro-substituted aromatic compounds, such as nitrobenzene, 2-, 3-, 4-nitrophenol and 2,4-dinitrophenol, was investigated, and a method was developed for the simultaneous determination of these compounds, based on their reduction at a hanging mercury drop electrode (HMDE). It was found that by applying the differential pulse voltammetric (DPV) approach in a Britton–Robinson buffer of pH 5.4, nitrobenzene, 2-, 3- and 4-nitrophenol had well defined voltammetric reduction waves with peak potentials at −344, −284, −292 and −376 mV, respectively. However, 2,4-dinitrophenol had two peaks with potentials at −240 and −364 mV under the same conditions. For each compound linear calibration graphs were obtained in the general concentration range of 0.05–3.0 mg l−1. In mixtures of the five compounds, serious overlapping of voltammetric peaks was observed, and with conventional analytical methodology pre-separation steps would be required. In this study, chemometrics methods of data analysis, such as partial least squares (PLS), principal component regression (PCR) and classical least squares (CLS), were applied to resolve the overlapped voltammograms. Orthogonal experimental design was used for construction of the training sets containing the five aromatic compounds in the concentration range of 0.1–2.6 mg l−1. Five significant factors or principal components were modelled for prediction by the PLS and PCR methods, respectively. The percent of relative prediction error (RPE) was similar and acceptable for both methods being approximately ±10%. The percent of recoveries were within ±10% of the target value. The CLS method performed poorly (RPET=38%). The developed method was then applied to the analysis of these nitro-substituted aromatic compounds in field samples with similar satisfactory results.

A kinetic spectrophotometric method has been developed for simultaneous quantitative determination of acetaminophen and phenobarbital in pharmaceutical preparations, and relies on the different kinetic rates of the analytes in their oxidative coupling reaction with 3-methylbenzothiazolin-2-one hydrazone (MBTH) in the presence of hydrochloric acid and the Fe(III) oxidant. The absorbance was measured and recorded from 440 to 740 nm every 60 s from 15 to 435 s. An artificial neural network (ANN) coupled with principal component analysis (principal component artificial neural network, PC-ANN) has been described, and its principles and applications were illustrated by a simulated kinetic system. The performance of the PC-ANN was compared with a conventional ANN model. PC-ANN, as well as ANN and partial least squares (PLS), were applied to a validation set of overlapping spectra containing kinetic data of binary mixtures with different concentration ratios of acetaminophen and phenobarbital. The results show that PC-ANN is the most efficient of the three chemometrics methods applied for prediction of the two analytes.

The voltammetric behavior of synthetic food antioxidants, such as butylated hydroxyanisole (BHA), butylated hydroxytoluene (BHT), propyl gallate (PG) and tert-butylhydroquinone (TBHQ), at a glassy carbon electrode in solution of 0.1 mol l−1 perchloric acid containing 1% methanol has been investigated. The obtained linear sweep voltammograms (LSV) showed that all these four compounds have well-defined oxidation waves with peak potentials of 629, 818, 599 and 501 mV for BHA, BHT, PG and TBHQ, respectively. Linear calibration graphs were also obtained in the concentration ranges of 0.5–15.0, 0.5–8.0, 1.0–15.0 and 1.0–15.0 mg l−1 for BHA, BHT, PG and TBHQ, respectively. However, the voltammetric peaks of these antioxidants seriously overlap and it is difficult to determine them individually from a mixture without prior separation. In this work, a method for simultaneous determination of these antioxidants, based on their oxidation at the glassy carbon electrode, with the aid of chemometric approaches, such as classical least squares (CLS), principal component regression (PCR) and partial least squares (PLS), has been developed. The method was applied to determine the four antioxidants in a set of synthetic mixtures and several commercial food samples; in general, satisfactory results were obtained.

Human-scalp hair samples were discriminated by Fourier transform infrared (FT-IR) micro-spectroscopy and chemometrics. The hairs were flattened with a small metallic roller, and the spectra were collected in the reflectance mode. The effects of gender, race and hair oxidation were examined. The results indicate a clear separation between FT-IR spectra collected from the heads of two different subjects of the same gender, race, hair colour, hair length, and treatment. The same results have also indicated a discrimination between spectra of hairs collected from the LHS and RHS of a head of a given subject. In addition, FT-IR spectra collected from different subjects were discriminated on the basis of treatment and gender. The study has demonstrated that chemometrics provides information that is not readily available by conventional visual methods of spectral interpretation.

Various rice samples were collected in Vietnam from the Red River region, and some other parts of the country as well as from Yanco, NSW, Australia. The rice samples were analysed for 14 elements (P, K, Mg, Ca, Mn, Zn, Fe, Cu, Al, Na, Ni, As, Mo, and Cd) by ICP-AES, ICP-MS and FAAS. The analytical procedures were carefully controlled and validated using the rice flour certified material (NIES No 10). In general, the results showed that Vietnamese rice has elemental concentration ranges similar to those of the Australian and other overseas rice. However, analyses for some elements are characteristic of some Vietnamese and Australian rice samples. Thus, Vietnamese rice shows somewhat higher levels of P, K and Mg than rice samples from other countries; Mn could be a marker for the Australian rice grown in the Yanco region, and the analysed Australian samples were also very low in Cd (0.003 mg kg-1). An unusual distribution of Ni, present in higher concentrations in the white rice samples than in the brown ones, was observed for some Vietnamese rice samples.

Raw naturally coloured and white cotton cellulose fibres were investigated by Fourier transform near-infrared (FT-NIR) spectroscopy and chemometric methods, namely principal component analysis (PCA). In general, the white cotton exhibited bands that could be associated with the structural features of the cotton cellulose polymer. But the FT-NIR spectrum of the green cotton, which is reported for the first time, exhibited a sharp band at 4250 cm–1. Further band analysis indicated that green cotton contains a higher C–H content and a lower C–C/C–O and O–H fractions than other natural cotton fibres, suggesting that it has undergone an oxidation process as indicated in the previous FT-Raman spectroscopic study (see Liu, Y., Kokot, S., and Sambi, J., Analyst, 1998, 123, 633). Although the PCA scores plot of FT-NIR spectra of seven types of cotton fibres showed no better separation than that of FT-Raman spectra, it is still possible to differentiate the various types of natural cotton fibres.

Phenols are well known noxious compounds, which are often found in various water sources. A novel analytical method has been researched and developed based on the properties of hemin-graphene hybrid nanosheets (H-GNs). These nanosheets were synthesized using a wet-chemical method, and they have peroxidase-like activity. Also, in the presence of H2O2, the nanosheets are efficient catalysts for the oxidation of the substrate, 4-aminoantipine (4-AP), and the phenols. The products of such an oxidation reaction are the colored quinone-imines (benzodiazepines). Importantly, these products enabled the differentiation of the three common phenols - pyrocatechol, resorcin and hydroquinone, with the use of a novel, spectroscopic method, which was developed for the simultaneous determination of the above three analytes. This spectroscopic method produced linear calibrations for the pyrocatechol (0.4-4.0 mg L(-1)), resorcin (0.2-2.0 mg L(-1)) and hydroquinone (0.8-8.0 mg L(-1)) analytes. In addition, kinetic and spectral data, obtained from the formation of the colored benzodiazepines, were used to establish multi-variate calibrations for the prediction of the three phenol analytes found in various kinds of water; partial least squares (PLS), principal component regression (PCR) and artificial neural network (ANN) models were used and the PLS model performed best.

A novel modified electrode was constructed by the electro-polymerization of 4,5-dihydroxy-3-[(2-hydroxy-5-sulfophenyl)azo]-2,7-naphthalenedisulfonic acid trisodium salt (acid chrome blue K (ACBK)) at a graphene oxide (GO)-nafion modified glassy carbon electrode (GCE). The characterization of an electrochemically synthesized poly-ACBK/GO-nafion film was investigated by electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), atomic force microscopy (AFM) and scanning electron microscopy (SEM) techniques, and the results were interpreted and compared at each stage of the electrode construction. Electrochemical oxidation of eight β-agonists – clenbuterol, salbutamol, terbutaline, ractopamine, dopamine, dobutamine, adrenaline, and isoprenaline, was investigated by CV at the different electrodes. At the poly-ACBK/GO-nafion/GCE, the linear sweep voltammetry peak currents of the eight β-agonists increased linearly with their concentrations in the range of 1.0–36.0 ng mL−1, respectively, and their corresponding limits of detection (LODs) were within the 0.58–1.46 ng mL−1 range. This electrode showed satisfactory reproducibility and stability, and was used successfully for the quantitative analysis of clenbuterol in pork samples.

A comparison of predicted values of the breaking force of cotton fabrics as measured by diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy and thermogravimetry (TG) was carried out with the aid of the partial least squares (PLS) method. Excellent agreement was found for the validation set of samples with a standard errors of prediction (SEP) value of about 3%. Three thermal degradation parameters of eight different cellulosic samples, predicted from thermogravimetric measurements again using PLS, gave good analytical results on a small validation sample set.

The polarographic waves of pyrazine and its methyl derivatives are seriously overlapping, so they cannot be determined individually by polarographic methods without a prior separation. In this paper, a chemometric approach, iterative target transformation factor analysis (ITTFA), is developed and applied to the determination of mixtures of pyrazines at trace level (2.0–9.0 × 10 −6 moll −1 ) by using differential pulse polarography (DPP) and a static mercury drop electrode (SMDE). Different from the general ITTFA method, only one-dimensional measurement data of n − 1 standards and an unknown were used in this work. It produced acceptable results with average recoveries in the 96–108% range and relative standard errors in the 3.4–9.5% range.

A set of natural cellulosic and regenerated fabrics was analysed by thermogravimetry (TG) and differential scanning calorimetry (DSC). The results were interpreted by chemometrics methods of data analysis, viz., principal component analysis (PCA) and SIMCA. PCA scores plots conveniently displayed the overall information from the TG and DSC data respectively, and the SIMCA classification analysis provided supporting quantitative information. The chemometrics analysis showed that both the TG and DSC data from the natural cellulosic fabrics clustered in a sequence: raw fabrics, linen, bleached fabrics and poplin. This sequence was related to the thermal degradation parameters of maximum weight loss rate and enthalpy of these fabrics.

Electrochemical behavior of three antioxidants: butylated hydroxyanisole (BHA), butylated hydroxytoluene (BHT) and butylated hydroquinone (TBHQ), was investigated at a glassy carbon electrode modified with gold nanoparticles (AuNPs/GCE). This electrode was characterized by scanning electron microscopy (SEM). The experimental results indicated that the modified electrode was strongly electroactive during the redox reactions of BHA, BHT and TBHQ, and this was confirmed by the observed increased redox peak currents and shifted potentials; in addition, the oxidation products of BHA and TBHQ were found to be the same. The experimental conditions were optimized and the oxidation peaks of BHA and BHT were clearly separated. Based on this, an electrochemical method was researched and developed for the simultaneous determination of BHA, BHT and TBHQ in mixtures with the use of first derivative voltammetry; the linear concentration ranges were 0.10-1.50 μg mL(-1), 0.20-2.20 μg mL(-1) and 0.20-2.80 μg mL(-1), and detection limits were 0.039, 0.080 and 0.079μgmL(-1), for BHA, BHT and TBHQ, respectively. The proposed method was successfully applied for the analysis of the three analytes in edible oil samples.

A new modified electrode was constructed by the electro-polymerization of 7-[(2,4-dihydroxy-5-carboxybenzene)azo]-8-hydroxyquinoline-5-sulfonic acid (DHCBAQS) at a graphene-nafion modified glassy carbon electrode (GCE). The construction process was performed stepwise and at each step the electrochemical characteristics were investigated particularly with respect to the oxidation of the three noxious analytes, 2-nitroaniline (2-NA), 3-nitroaniline (3-NA), 4-nitroaniline (4-NA); the electrode treated with the fluorescence reagent DHCBAQS performed best. At this electrode, the differential pulse voltammetry peak currents of the three isomers increased linearly with their concentrations in the range of 0.05-0.60 μg mL(-1), respectively, and their corresponding limits of detection (LODs) were all about 0.022 μg mL(-1). Furthermore, satisfactory results were obtained when this electrode was applied for the simultaneous quantitative analysis of the nitroaniline isomer mixtures by Principal component regression (PCR) and Partial least squares (PLS) as calibration methods (relative prediction error (PRE(T)) - 9.04% and 9.23%) and average recoveries (101.0% and 101.7%), respectively. The above novel poly-DHCBAQS/graphene-nafion/GCE was successfully employed for the simultaneous analysis of the three noxious nitroaniline isomers in water and sewage samples.

An electrochemical method involving a gold nanoparticle modified glassy carbon electrode (AuNPs/GCE) was researched and developed for the simultaneous analysis of three β(2)-agonists, ractopamine (RAC), salbutamol (SAL) and clenbuterol (CLB). The three analytes were electrocatalytically oxidized at the AuNP/GCE, which enhanced the oxidation peak current and influenced the shift of the oxidation potentials to lower values in comparison with the analysis involving only the GCE. The differential pulse stripping voltammetry (DPSV) voltammograms from the drug mixture produced complex, overlapping profiles, and chemometrics methods were applied for calibration modeling. The peak currents associated with RAC, SAL and CLB measurements were linear as a function of their concentrations (ranges within 0.005-0.150 μg mL(-1)); the detection limits for RAC, SAL and CLB were 2.4, 5.8 and 2.6 ng mL(-1), respectively. It was shown that satisfactory quantitative results were obtained with the use of the MVC1 package of chemometrics methods e.g. the PLS1 calibration model produced a relative prediction error (RPE(T)) of 7.0% and an average recovery of 97.6%. The above AuNP/GCE was successfully employed for the simultaneous analysis of RAC, SAL and CLB in pork meat, liver and pig feed samples.

A sensitive kinetic spectrophotometric method was developed for the determination of four flavor enhancers—maltol, ethyl maltol, vanillin, and ethyl vanillin—in food samples. The method was based on the reduction of iron(III) by the four analytes in a sulfuric acid medium (0.012 mol/L), and the subsequent interaction of iron(II) with hexacyanoferrate(III) to form the strongly colored Prussian blue complex, which exhibited an absorption maximum at 800 nm. The optimized method had linear calibrations over the concentration ranges of 0.2–2.8 mg/L for maltol, ethyl maltol, and vanillin, as well as 0.2–1.8 mg/L for ethyl vanillin; the corresponding detection limits were 0.07, 0.07, 0.06, and 0.06 mg/L, respectively. Calibration models were constructed from the original and frst-derivative spectral data with the use of partial least-squares (PLS) and principal component regression chemometrics methods. Ultimately, the proposed analytical procedure was successively applied for the determination of the four compounds in commercial food samples with the use of a PLS calibration based on the frst-derivative spectral data. The results were comparable with those from a reference HPLC method.

Road dust contain potentially toxic pollutants originating from a range of anthropogenic sources common to urban land uses and soil inputs from surrounding areas. The research study analysed the mineralogy and morphology of dust samples from road surfaces from different land uses and background soil samples to characterise the relative source contributions to road dust. The road dust consist primarily of soil derived minerals (60%) with quartz averaging 40-50% and remainder being clay forming minerals of albite, microcline, chlorite and muscovite originating from surrounding soils. About 2% was organic matter primarily originating from plant matter. Potentially toxic pollutants represented about 30% of the build-up. These pollutants consist of brake and tire wear, combustion emissions and fly ash from asphalt. Heavy metals such as Zn, Cu, Pb, Ni, Cr and Cd primarily originate from vehicular traffic while Fe, Al and Mn primarily originate from surrounding soils. The research study confirmed the significant contribution of vehicular traffic to dust deposited on urban road surfaces.

The application of four chemometrics procedures viz., principal components analysis, SIMCA, multicriteria decision-making routines PROMETHEE and GAIA, and fuzzy clustering, was investigated for the selection of a suitable microwave digestion method for sediment and rock samples. The NBS 2704 SRM and a secondary rock standard were acid digested by 15 different methods and the digests analysed for six metals, Cu, Pb, Ni, Cr, Co and Zn. The four chemometrics approaches produced consistent results and provided similar information about the data structure (outliers, groupings, trends). Only the PROMETHEE procedure gave the ranking information necessary for the selection of a suitable digestion method. This method was based on the HF-HNO3 acid composition of the digest mixture.

Principal component analysis (PCA) and the multicriteria decision making methods, PROMETHEE and GAIA, were used to select a suitable microwave digestion method for metal analysis of soil samples. When the residuals matrix derived from the Cu, Pb, Co, Mn and Zn analyses of 18 different digests of the NBS 2704 SRM, was subjected to PCA and PROMETHEE ranking, two prefered methods were isolated. This PROMETHEE ranking together with the microwave oven settings and digest acid composition were then used as variables. The corresponding data matrix was subjected to PROMETHEE analysis coupled with the visualisation technique, GAIA. This illustrated the relationship between the different practical variables and method perfromance leading to the selection of the most suitable digestion method.

This paper presents the outcomes of a research project, which focused on developing a set of surrogate parameters to evaluate urban stormwater quality using simulated rainfall. Use of surrogate parameters has the potential to enhance the rapid generation of urban stormwater quality data based on on-site measurements and thereby reduce resource intensive laboratory analysis. The samples collected from rainfall simulations were tested for a range of physico-chemical parameters which are key indicators of nutrients, solids and organic matter. The analysis revealed that [total dissolved solids (TDS) and dissolved organic carbon (DOC)]; [total solids (TS) and total organic carbon (TOC)]; [turbidity (TTU)]; [electrical conductivity (EC)]; [TTU and EC] as appropriate surrogate parameters for dissolved total nitrogen (DTN), total phosphorus (TP), total suspended solids (TSS), TDS and TS respectively. Relationships obtained for DTN-TDS, DTN-DOC, and TP-TS demonstrated good portability potential. The portability of the relationship developed for TP and TOC was found to be unsatisfactory. The relationship developed for TDS-EC and TS-EC also demonstrated poor portability.

The binding interaction of Alpinetin (APT) with bovine serum albumin (BSA) was studied by fluorescence, UV–visible and synchronous fluorescence spectroscopy (SFS) under simulated physiological conditions. The measured complex spectra were resolved by multivariate curve resolution-alternating least squares (MCR-ALS), yielding a host of data and information, which otherwise would have been impossible to obtain. The extracted profiles corresponded to the spectra of the single species in the APT/BSA mixture. In addition, the presence of the APT–BSA complex was demonstrated, and it was shown that the associated quenching of the fluorescence from the BSA protein resulted from the formation of APT–BSA complex via a static mechanism. The binding constant ( K a(ave) = 2.34 × 10 6 L mol −1 ) and the number of sites ( n = 1) were obtained by fluorescence methods as were the thermodynamic parameters (Δ H 0 , Δ S 0 and Δ G 0 ). This work suggested that the principal binding between APT to BSA was facilitated by hydrophobic interactions. The thermodynamic parameters for APT were compared to those from the structurally similar Chrysin and Wogonin molecules. It appeared that the entropy parameters were relatively more affected by the small structural changes. SFS from the interaction of BSA and APT showed that the ligand affected the conformation of BSA. The competitive interaction of APT and site makers with BSA indicated site I as the binding area of APT in BSA.

This review explores the question whether chemometrics methods enhance the performance of electroanalytical methods. Electroanalysis has long benefited from the well-established techniques such as potentiometric titrations, polarography and voltammetry, and the more novel ones such as electronic tongues and noses, which have enlarged the scope of applications. The electroanalytical methods have been improved with the application of chemometrics for simultaneous quantitative prediction of analytes or qualitative resolution of complex overlapping responses. Typical methods include partial least squares (PLS), artificial neural networks (ANNs), and multiple curve resolution methods (MCR-ALS, N-PLS and PARAFAC). This review aims to provide the practising analyst with a broad guide to electroanalytical applications supported by chemometrics. In this context, after a general consideration of the use of a number of electroanalytical techniques with the aid of chemometrics methods, several overviews follow with each one focusing on an important field of application such as food, pharmaceuticals, pesticides and the environment. The growth of chemometrics in conjunction with electronic tongue and nose sensors is highlighted, and this is followed by an overview of the use of chemometrics for the resolution of complicated profiles for qualitative identification of analytes, especially with the use of the MCR-ALS methodology. Finally, the performance of electroanalytical methods is compared with that of some spectrophotometric procedures on the basis of figures-of-merit. This showed that electroanalytical methods can perform as well as the spectrophotometric ones. PLS-1 appears to be the method of practical choice if the %relative prediction error of approximately +/-10% is acceptable.

A differential kinetic spectrophotometric method was researched and developed for the simultaneous determination of iron and aluminium in food samples. It was based on the direct reaction kinetics and spectrophotometry of these two metal ions with Chrome Azurol S (CAS) in ethylenediamine–hydrochloric acid buffer (pH 6.3). The results were interpreted with the use of chemometrics. The kinetic runs and the visible spectra of the complex formation reaction were studied between 540 and 750 nm every 30 s over a total period of 285 s. A set of synthetic metal mixture samples was used to build calibrations models. These were based on the spectral and kinetic two-way data matrices, which were processed separately by the radial basis function-artificial neural network (global RBF-ANN) method. The prediction performance of these models was poorer than that from the combined kinetic-spectral three-way array, which was similarly processed by the same method (% relative prediction error (RPET) = 5.6). These results demonstrate that improved predictions can be obtained from the data array, which has more information, and that appropriate chemometrics methods can enhance analytical performance of simple techniques such as spectrophotometry. Other chemometrics models were then applied: N-way partial least squares (NPLS), parallel factor analysis (PARAFAC), back propagation-artificial neural network (BP-ANN), single radial basis function-artificial neural network (RBF-ANN), and principal component neural network (PC-RBF-ANN). There was no substantial difference between the methods with the overall %RPET range being 5.0–5.8. These two values corresponded to the NPLS and BP-ANN models, respectively. The proposed method was applied for the determination of iron and aluminium in some commercial food samples with satisfactory results.

The interaction of quercetin-Cu(II) complex with calf thymus DNA was investigated with the use of Neutral Red (NR) dye as a spectral probe by the application of UV-vis spectrophotometry, cyclic voltammetry and synchronous fluorescence spectroscopy. The results showed that both quercetin-Cu(II) complex and the NR molecule can intercalate into the double helix of the DNA. The 2:1 quercetin:Cu(II) complex (estimated binding constant = 2.85 x 10(9)) is stabilized by intercalation in the DNA (binding constant, K[quercetin-Cu(II)-DNA] = (1.82 +/- 0.20) x 10(5) M-1), and displaces the NR dye from the NR-DNA complex in a competitive reaction. Cyclic voltammetry studies confirm the intercalation reaction and show that the ratio (K-R/K-O) of binding constants for the reduced and oxidized forms of the metal complex is 2.05. Furthermore, the alternative least squares (ALS) method was applied to resolve a complex two-way array of the absorption spectra data. This yielded the equilibrium concentration profiles of each component in the reaction (NR, NR-DNA and quercetin-Cu(II)) as well as the corresponding pure spectra. The extracted profiles showed that at equilibrium the [NR-DNA] and [NR] trends decreased and increased symmetrically, respectively, with approximately linear behaviour being observed below 10 x 10(-6) mol L-1 of the added quercetin-Cu2+ complex. Thereafter, these trends converged asymptotically. The free [quercetin-Cu(II)] trend-line at equilibrium was linear over the whole range of the complex added. It was possible to estimate the approximate value of the equilibrium constant of the exchange process (approximately 5 x 10(-1)) involving the intercalation of the quercetin-Cu(II) complex. It was also found that about 35% of the bound complex was unaccounted by the intercalation reaction, presumably being stabilized at an alternative site. (c) 2006 Elsevier B.V. All rights reserved.

This paper reports the first application of the multicriteria decision making methods, PROMETHEE and GAIA, to indoor and outdoor air quality data. Fourteen residential houses in a suburb of Brisbane, Australia were investigated for 21 air quality-influencing criteria, which included the characteristics of the houses as well as the concentrations of volatile organic compounds, fungi, bacteria, submicrometer, and supermicrometer particles in their indoor and outdoor air samples. Ranking information necessary to select one house in preference to all others and to assess the parameters influencing the differentiation of the houses was found with the aid of PROMETHEE and GAIA. There was no correlation between the rank order of each house and the health complaints of its occupants. Patterns in GAIA plots show that indoor air quality in these houses is strongly dependent on the characteristics of the houses (construction material, distance of the house from a major road, and the presence of an in-built garage). Marked similarities were observed in the patterns obtained when GAIA and factor analysis were applied to the data. This underscores the potential of PROMETHEE and GAIA to provide information that can assist source apportionment and elucidation of effective remedial measures for indoor air pollution.

The versatility of FTIR spectrometry was explored by considering a variety of samples drawn from industrial applications, materials science and biomedical research. These samples included polymeric insulators, bauxite ore, clay, human hair and human skin. A range of sampling techniques suitable for these samples is discussed, in particular FTIR microscopy, FTIR emission spectroscopy, attenuated total reflectance and photoacoustic FTIR spectrometry. The power of modern data processing techniques, particularly multivariate analysis, to extract useful information from spectral data is also illustrated.