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Chemometric Analysis of Heavy Metal Content for Various Environmental Matrices in Terms of Their Use in Biomass Thermal Processing

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Chemometric Analysis of Heavy Metal Content for Various Environmental Matrices in Terms of Their Use in Biomass Thermal Processing Cent. Eur. J. Chem. • 10(5) • 2012 • 1696-1706 DOI: 10.2478/s11532-012-0096-0 Central European Journal of Chemistry Chemometric analysis of heavy metal content for various environmental matrices in terms of their use in biomass thermal processing Research Article Marcin Sajdak1*, Celina Pieszko2 1Institute for Chemical Processing of Coal, 41-803 Zabrze, Poland 2Department of Analytical Chemistry, Faculty of Chemistry, University of Silesia, 44-100 Gliwice, Poland Received 3 March 2012; Accepted 4 July 2012 Abstract: Chemometric analysis was performed to determine the heavy metal content, such as Zn, Cd, Ni, Mn, Cu, Pb, and Fe, in 36 samples of Scots Pine taken from 9 locations within the Upper Silesian Industrial Basin. The samples, after being pre-processed, were examined for the above elements through the use of atomic absorption spectroscopy (AAS). The highest concentration of heavy metals was discovered in samples from Jaworzno. Based on the concentration assessment, the relationship between element quantity, sampling location, and matrix type has been determined, and definite element group co-existence has been confirmed and described. Keywords: Environmental survey • Scots Pine • Branches • Heavy metals • Concentration assessment © Versita Sp. z o.o. 1. Introduction these techniques, it is possible to find the following relationships: metal-matrix A – B matrix or matrix - Biomass is defined as organic, non-fossil material of metal A – metal B. This survey determined the Zn, Cd, biological origin that can be used as fuel to produce Ni, Mn, Cu, Pb, and Fe contents in various Scots Pine heat or generate electricity. The main solid fuel used in components, including the needles, branches, cones, biomass is forest biomass (firewood) in the form of logs, and forest bed. The analysis was carried out using flame wood chips, briquettes, pellets and waste from forestry in atomic absorption spectroscopy (F-AAS). the form of undersized wood. It is therefore important to Several examples of chemometrics methods control metals, in particular heavy metals, which emerge application in environmental protection can be found in in the combustion process along with the dust, and offend literature [8,9]. Most chemometric methods are used to up in fly ash. analyse data on water pollution [10-12] or air pollution Chemometric assessment is very often used to [13,14]. Research related to the accumulation of metals optimise technological processes or chemical analyses in plant material is more difficult to carry out, because [1-3]. It may also be used for environmental surveys aimed it is more time-consuming (no on-line monitoring in the at discovering relationships between individual chemicals case of water and air), which results in less interest [4-7] in the scope of this study and to form a picture of in such studies [15,16]. This translates into the use contamination emissions in biomass processing. This of chemometrics methods, which according to the study aims to define methods for associating heavy metal description of some dependencies require a substantial occurrence in different parts of the Silesian Voivodeship. A set of data. survey with a few chemometric and statistical techniques The aim of this study was to find and describe the has been performed. These techniques include similarity relationship between the types of the sample matrix, the analysis, k-means, and correlative analysis. By using analysed metals and the place of sampling. It was found * E-mail: [email protected] 1696 M. Sajdak, C. Pieszko Figure 1. Plan of collecting materials for analysis from different sampling sites. that principal component analysis (PCA) and cluster collected this way was split into smaller parts and then analysis (CA), which were used during testing, are very homogenized in order to obtain analytical samples. The effective techniques to find relationships between the above mentioned method was used at every collection variables mentioned earlier. The article presents the site. results of the relationship between copper and nickel The material was air dried, powdered in a titanium content in the forest bed (R2 = 0.881), between zinc and blade grinder and again dried at 110°C. At this stage, the cadmium content in the city of Sosnowiec and the town samples were mineralised by “dry ashing” in a muffle of Dabrowa Górnicza studied in branches and the forest furnace at a temperature of 350°C. The ash obtained 2 bed (R = 0.992) as well as among samples of cones was moved to a beaker and dissolved in a 10% HNO3 (R2 = 0.988 ). solution. After the respective sample condensation increase, the mineralisation product was moved to a 10 mL graduated flask. The metals were diluted 10 times 2 . Experimental procedure in solutions and then marked. All of the plant materials were assessed for the The research material consisted of 36 samples of cones presence of Zn, Cd, Ni, Mn, Cu, Pb, and Fe with flame [C], needles [N], branches [B] and forest bed [F] of Scots atomic absorption spectroscopy. A Carl Zeiss Jena AAS Pine taken from nine different locations in the Silesian 3 spectrometer was used to survey the materials. The Voivodeship (Szczekociny, Żarnowiec, Sławniów, values for recovery of materials were compared between Podlesice, Solca, Sławków, Dąbrowa Górnicza, the reference and the model material. Conditions of AAS Jaworzno, and Sosnowiec). analysis are presented in Table 1. In each of the ten sampling sites, the material was LOD - limit of detection of the measuring instrument collected from eight stations chosen in accordance with used for each of the patterns, calculated using the the plan presented in Fig. 1. The plan was built on the following formula: plane of a square with sides of 400×400 m with a second ⋅Sb)(3.3 smaller square with dimensions of 212×212 m (150√2) =LOD (1) a typed and rotated in the first quadrant. The material 1697 Chemometric analysis of heavy metal content for various environmental matrices in terms of their use in biomass thermal processing Table 1. Conditions of AAS analysis. Element Pyrolysis Atomization Lamp Analytical Spectral Analytical LOD [μg temperature temperature current line [nm] gap [nm] range [μg kg-1] [ºC] [ºC] [mA] kg-1] Zn 400 1800 5.0 213.9 0.5 10-1500 5.0 Cd 300 1800 3.0 228.8 0.5 10-1800 4.0 Ni 900 2400 4.0 241.5 0.2 600-25000 9.0 Mn 700 2400 5.0 403.1 0.2 2700-27000 2.0 Cu 800 2300 3.0 222.6 1.0 700-180000 1.0 Pb 400 2000 5.0 217.0 1.0 200-20000 10.0 Fe 800 2300 7.0 372.0 0.2 900-80000 5.0 Where: the sampling location. Overall, 71.5% of the cones Sb- standard deviation of residuals of the calibration examined have the lowest metal content (regardless of curve, sampling location). The nickel content was higher in the a- gradient of the line. cones than any other component. The lead content in the cones was 98% convergent with that in branches not older than three years. As hypothesised, in 86% of all 3. Results and discussion cases, the highest contents of the elements examined were found in the forest bed. The results were used for The mineralised samples contained concentration further analysis of the relationships between qualitative ranges of 6500-51500 µg kg-1 for zinc, and quantitative concentrations of the assessed 100-5500 µg kg-1 for lead, 3500-97200 µg kg-1 for materials by use of chemometric techniques such as copper, 400-7500 µg kg-1 for nickel, 1000-71500 µg kg-1 CA, k-means and PCA. for manganese, 10-300 µg kg-1 for cadmium, and Fig. 2 shows a dendrogram of the concentrations 1000-75200 µg kg-1 for iron. Table 2 shows the total for the examined mineralised samples of various pine content of the examined elements in the pine samples components. This dendogram applies to the analysed from the different locations. Those samples were metals (variables) in relation to the sample types. pre-processed by the dry method, so the results obtained Four distinctly separate groups, divided into smaller for the dry mass consider the recovery in terms of the subgroups, have been obtained. The first group consists survey procedure. Each sample was analysed eight of two subgroups, the first of which has a high linear times, and the results are shown as the mean of those correlation among the cadmium contents in the samples eight parallel runs. After the preliminary processing (ranging from 30-1300 µg kg-1). Because of the high (mineralisation) of the samples by the dry method, the similarity between the samples, by knowing the cadmium individual analyte contents were not equal (Table 2). content in the cones (Cd C), the cadmium content in the The confidence interval was calculated using the needles (Cd N) can be estimated with 99.2% certainty. following formula: Similarly, the cadmium content in the forest bed (Cd F) and in the branches (Cd B) can be estimated with 96% (2) and 97% certainty, respectively. The second group consists of needle (N) and cone (C) where x - the arithmetic average of the measurements; samples in which nickel, lead and iron were assessed. σ - standard deviation, calculated using the following In this group, Pb C and Pb N had similar lead values, formula: and their convergent contents were between 1600 and 3500 µg kg-1 per sample. Moreover, the first subgroup (3) has a very high similarity between its components (83-86%) and shows that the lead content in the cones n - number of measurements; x - single measurement and needles is related to the iron content in the needles.
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