127 resultados para Environmental analysis


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The bioavailability of soil arsenic (As) is determined by its speciation in soil solution, i.e., arsenite [As(III)] or arsenate [As(V)]. Soil bioavailability studies require suitable methods to cope with small volumes of soil solution that can be speciated directly after sampling, and thereby minimise any As speciation change during sample collection. In this study, we tested a self-made microcartridge to separate both As species and compared it to a commercially available cartridge. In addition, the diffusive gradient in thin films technique (DGT), in combination with the microcartridges, was applied to synthetic solutions and to a soil spiked with As. This combination was used to improve the assessment of available inorganic As species with ferrihydrite(FH)-DGT, in order to validate the technique for environmental analysis, mainly in soils. The self-made microcartridge was effective in separating As(III) from As(V) in solution with detection by inductively coupled plasma optical emission spectrometry (ICP-OES) in volumes of only 3 ml. The DGT study also showed that the FH-based binding gels are effective for As(III) and As(V) assessment, in solutions with As and P concentrations and ionic strength commonly found in soils. The FH-DGT was tested on flooded and unflooded As spiked soils and recoveries of As(III) and As(V) were 85–104% of the total dissolved As. This study shows that the DGT with FH-based binding gel is robust for assessing inorganic species of As in soils.

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This paper outlines a forensic method for analysing the energy, environmental and comfort performance of a building. The method has been applied to a recently developed event space in an Irish public building, which was evaluated using on-site field studies, data analysis, building simulation and occupant surveying. The method allows for consideration of both the technological and anthropological aspects of the building in use and for the identification of unsustainable operational practice and emerging problems. The forensic analysis identified energy savings of up to 50%, enabling a more sustainable, lower-energy operational future for the building. The building forensic analysis method presented in this paper is now planned for use in other public and commercial buildings.

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A compositional multivariate approach is used to analyse regional scale soil geochemical data obtained as part of the Tellus Project generated by the Geological Survey Northern Ireland (GSNI). The multi-element total concentration data presented comprise XRF analyses of 6862 rural soil samples collected at 20cm depths on a non-aligned grid at one site per 2 km2. Censored data were imputed using published detection limits. Using these imputed values for 46 elements (including LOI), each soil sample site was assigned to the regional geology map provided by GSNI initially using the dominant lithology for the map polygon. Northern Ireland includes a diversity of geology representing a stratigraphic record from the Mesoproterozoic, up to and including the Palaeogene. However, the advance of ice sheets and their meltwaters over the last 100,000 years has left at least 80% of the bedrock covered by superficial deposits, including glacial till and post-glacial alluvium and peat. The question is to what extent the soil geochemistry reflects the underlying geology or superficial deposits. To address this, the geochemical data were transformed using centered log ratios (clr) to observe the requirements of compositional data analysis and avoid closure issues. Following this, compositional multivariate techniques including compositional Principal Component Analysis (PCA) and minimum/maximum autocorrelation factor (MAF) analysis method were used to determine the influence of underlying geology on the soil geochemistry signature. PCA showed that 72% of the variation was determined by the first four principal components (PC’s) implying “significant” structure in the data. Analysis of variance showed that only 10 PC’s were necessary to classify the soil geochemical data. To consider an improvement over PCA that uses the spatial relationships of the data, a classification based on MAF analysis was undertaken using the first 6 dominant factors. Understanding the relationship between soil geochemistry and superficial deposits is important for environmental monitoring of fragile ecosystems such as peat. To explore whether peat cover could be predicted from the classification, the lithology designation was adapted to include the presence of peat, based on GSNI superficial deposit polygons and linear discriminant analysis (LDA) undertaken. Prediction accuracy for LDA classification improved from 60.98% based on PCA using 10 principal components to 64.73% using MAF based on the 6 most dominant factors. The misclassification of peat may reflect degradation of peat covered areas since the creation of superficial deposit classification. Further work will examine the influence of underlying lithologies on elemental concentrations in peat composition and the effect of this in classification analysis.

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Increasing emphasis is being placed on the evaluation of health-related quality of life. However, there is no consensus on the definition of this concept and as a result there are a plethora of existing measurement instruments. Head-to-head comparisons of the psychometric properties of existing instruments are necessary to facilitate evidence-based decisions about which instrument should be chosen for routine use. Therefore, an individualised instrument (the modified Patient Generated Index), a generic instrument (the Short Form 36) and a disease-specific instrument (the Quality of Life after Myocardial Infarction questionnaire) were administered to patients with ischaemic heart disease (n=117) and the evidence for the validity, reliability and sensitivity of each instrument was examined and compared. The modified Patient Generated Index compared favourably with the other instruments but none of the instruments examined provided sound evidence for sensitivity to change. Therefore, any recommendation for the use of the individualised approach in the routine collection of health-related quality of life data in clinical practice must be conditional upon the submission of further evidence to support the sensitivity of such instruments.