72 resultados para TRACE METALS


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Heavy metal pollution of sediments is a growing concern in most parts of the world, and numerous studies focussed on identifying contaminated sediments by using a range of digestion methods and pollution indices to estimate sediment contamination have been described in the literature. The current work provides a critical review of the more commonly used sediment digestion methods and identifies that weak acid digestion is more likely to provide guidance on elements that are likely to be bioavailable than other traditional methods of digestion. This work also reviews common pollution indices and identifies the Nemerow Pollution Index as the most appropriate method for establishing overall sediment quality. Consequently, a modified Pollution Index that can lead to a more reliable understanding of whole sediment quality is proposed. This modified pollution index is then tested against a number of existing studies and demonstrated to give a reliable and rapid estimate of sediment contamination and quality.

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A facile and sensitive surface-enhanced Raman scattering substrate was prepared by controlled potentiostatic deposition of a closely packed single layer of gold nanostructures (AuNS) over a flat gold (pAu) platform. The nanometer scale inter-particle distance between the particles resulted in high population of ‘hot spots’ which enormously enhanced the scattered Raman photons. A renewed methodology was followed to precisely quantify the SERS substrate enhancement factor (SSEF) and it was estimated to be (2.2 ± 0.17) × 105. The reproducibility of the SERS signal acquired by the developed substrate was tested by establishing the relative standard deviation (RSD) of 150 repeated measurements from various locations on the substrate surface. A low RSD of 4.37 confirmed the homogeneity of the developed substrate. The sensitivity of pAu/AuNS was proven by determining 100 fM 2,4,6-trinitrotoluene (TNT) comfortably. As a proof of concept on the potential of the new pAu/AuNS substrate in field analysis, TNT in soil and water matrices was selectively detected after forming a Meisenheimer complex with cysteamine.

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A miniaturized flow-through system consisting of a gold coated silicon substrate based on enhanced Raman spectroscopy has been used to study the detection of vapour from model explosive compounds. The measurements show that the detectability of the vapour molecules at room temperature depends sensitively on the interaction between the molecule and the substrate. The results highlight the capability of a flow system combined with Raman spectroscopy for detecting low vapour pressure compounds with a limit of detection of 0.2 ppb as demonstrated by the detection of bis(2-ethylhexyl)phthalate, a common polymer additive emitted from a commercial polyvinyl chloride (PVC) tubing at room temperature.

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A combined data matrix consisting of high performance liquid chromatography–diode array detector (HPLC–DAD) and inductively coupled plasma-mass spectrometry (ICP-MS) measurements of samples from the plant roots of the Cortex moutan (CM), produced much better classification and prediction results in comparison with those obtained from either of the individual data sets. The HPLC peaks (organic components) of the CM samples, and the ICP-MS measurements (trace metal elements) were investigated with the use of principal component analysis (PCA) and the linear discriminant analysis (LDA) methods of data analysis; essentially, qualitative results suggested that discrimination of the CM samples from three different provinces was possible with the combined matrix producing best results. Another three methods, K-nearest neighbor (KNN), back-propagation artificial neural network (BP-ANN) and least squares support vector machines (LS-SVM) were applied for the classification and prediction of the samples. Again, the combined data matrix analyzed by the KNN method produced best results (100% correct; prediction set data). Additionally, multiple linear regression (MLR) was utilized to explore any relationship between the organic constituents and the metal elements of the CM samples; the extracted linear regression equations showed that the essential metals as well as some metallic pollutants were related to the organic compounds on the basis of their concentrations

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A novel, highly selective resonance light scattering (RLS) method was researched and developed for the analysis of phenol in different types of industrial water. An important aspect of the method involved the use of graphene quantum dots (GQDs), which were initially obtained from the pyrolysis of citric acid dissolved in aqueous solutions. The GQDs in the presence of horseradish peroxidase (HRP) and H2O2 were found to react quantitatively with phenol such that the RLS spectral band (310 nm) was quantitatively enhanced as a consequence of the interaction between the GQDs and the quinone formed in the above reaction. It was demonstrated that the novel analytical method had better selectivity and sensitivity for the determination of phenol in water as compared to other analytical methods found in the literature. Thus, trace amounts of phenol were detected over the linear ranges of 6.00×10−8–2.16×10−6 M and 2.40×10−6–2.88×10−5 M with a detection limit of 2.20×10−8 M. In addition, three different spiked waste water samples and two untreated lake water samples were analysed for phenol. Satisfactory results were obtained with the use of the novel, sensitive and rapid RLS method.

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This project was the first comprehensive assessment of heavy metals to be conducted in the sediments of Northern Moreton Bay since the 1970s and found that shipping and shipping related activities contributed significantly to the level of sediment contamination in the area. The study was also used to develop and test new methods of assessing heavy metal sediment quality.

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Road deposited dust is a complex mixture of pollutants derived from a wide range of sources. Accurate identification of these sources is seminal for effective source-oriented control measures. A range of techniques such as enrichment factor analysis (EF), principal component analysis (PCA) and hierarchical cluster analysis (HCA) are available for identifying sources of complex mixtures. However, they have multiple deficiencies when applied individually. This study presents an approach for the effective utilisation of EF, PCA and HCA for source identification, so that their specific deficiencies on an individual basis are eliminated. EF analysis confirmed the non-soil origin of metals such as Na, Cu, Cd, Zn, Sn, K, Ca, Sb, Ba, Ti, Ni and Mo providing guidance in the identification of anthropogenic sources. PCA and HCA identified four sources, with soil and asphalt wear in combination being the most prominent sources. Other sources were tyre wear, brake wear and sea salt.

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This study investigates the level of pollutants (polycyclic aromatic hydrocarbons (PAHs) and heavy metals) in three car parks at QUT, one at Kelvin Grove campus and two at the Gardens Point campus. In addition, comparisons between site designs were assessed to identify the possible sources of heavy metals and PAHs. The main contributing source for heavy metals was identified to be from vehicle debris and emissions, while the source of PAHs was identified to be from petrol and diesel engine vehicle emissions. The highest concentration of pollutants was typically found for the 63 micro meter dust samples, proposed to be due to increased surface areas and thus available adsorption sites.

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In the context of increasing threats to the sensitive marine ecosystem by toxic metals, this study investigated the metal build-up on impervious surfaces specific to commercial seaports. The knowledge generated in this study will contribute to managing toxic metal pollution of the marine ecosystem. The study found that inter-modal operations and main access roadway had the highest loads followed by container storage and vehicle marshalling sites, while the quay line and short term storage areas had the lowest. Additionally, it was found that Cr, Al, Pb, Cu and Zn were predominantly attached to solids, while significant amount of Cu, Pb and Zn were found as nutrient complexes. As such, treatment options based on solids retention can be effective for some metal species, while ineffective for other species. Furthermore, Cu and Zn are more likely to become bioavailable in seawater due to their strong association with nutrients. Mathematical models to replicate the metal build-up process were also developed using experimental design approach and partial least square regression. The models for Cr and Pb were found to be reliable, while those for Al, Zn and Cu were relatively less reliable, but could be employed for preliminary investigations.

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Toxic chemical pollutants such as heavy metals (HMs) are commonly present in urban stormwater. These pollutants can pose a significant risk to human health and hence a significant barrier for urban stormwater reuse. The primary aim of this study was to develop an approach for quantitatively assessing the risk to human health due to the presence of HMs in stormwater. This approach will lead to informed decision making in relation to risk management of urban stormwater reuse, enabling efficient implementation of appropriate treatment strategies. In this study, risks to human health from heavy metals were assessed as hazard index (HI) and quantified as a function of traffic and land use related parameters. Traffic and land use are the primary factors influencing heavy metal loads in the urban environment. The risks posed by heavy metals associated with total solids and fine solids (<150µm) were considered to represent the maximum and minimum risk levels, respectively. The study outcomes confirmed that Cr, Mn and Pb pose the highest risks, although these elements are generally present in low concentrations. The study also found that even though the presence of a single heavy metal does not pose a significant risk, the presence of multiple heavy metals could be detrimental to human health. These findings suggest that stormwater guidelines should consider the combined risk from multiple heavy metals rather than the threshold concentration of an individual species. Furthermore, it was found that risk to human health from heavy metals in stormwater is significantly influenced by traffic volume and the risk associated with stormwater from industrial areas is generally higher than that from commercial and residential areas.

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Assessment of heavy metal bioavailability in sediments is complex because of the number of partial extraction methods available for the assessment and the general lack of certified reference materials. This study evaluates five different extraction methodologies to ascertain the relative strengths and weaknesses of each method. The results are then compared to previously published work to ascertain the most effective partial extraction technique, which was established to be dilute (0.75 – 1 M) nitric acid solutions. These results imply that single reagent; weak acid extractions provide a better assessment of potentially bioavailable metals than the chelating agents used in sequential extraction methods.