On the description of lead pollution in plants caused by traffic under application of robust statistics

Einax, Jürgen W.; Machelett, B.; Danzer, Klaus

doi:10.1007/bf00324405

Cited by 4 publications

(3 citation statements)

References 6 publications

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“…By comparing the lead concentrations in plants from other areas it was obvious that they are decreasing with lower traffic density. Einax [11] arrived at similar conclusions applying statistical calculations. The concentration of iron is also surprisingly high.…”

Section: Results and Dicussionsupporting

confidence: 72%

“…It was reported by some authors that several elements in plant samples had been measured using atomic absorption spectrometry [3,8,9,11]. Inductively coupled plasma atomic emission spectroscopy (ICP-AES) is one of the reliable analytical techniques applicable to different environmental samples [12,13] and has already been used for the determination of some metals in plants [10].…”

Section: Introductionmentioning

confidence: 99%

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Determination of heavy metal concentrations in plants exposed to different degrees of pollution using ICP-AES

Kos

Budič

Hudnik

et al. 1996

Analytical and Bioanalytical Chemistry

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Plant samples (Plantago lanceolata - narrow leaf plantain and Cichorium endiviae - endive) were collected in the surroundings of heavy metal emission sources and in other less contaminated areas. After digestion in a closed microwave system using HNO(3), the concentrations of Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb, and Zn were determined using ICP-AES. Detection limits for all the elements of interest are given. Differences in heavy metal uptake rate between both plant species were observed. The uptake is more intensive for endive than for narrow leaf plantain. High concentrations of some heavy metals were determined in the unwashed plant samples as a result of exposure to aerosols. Tukey's statistical test was used to confirm the discrepancy of Cr concentration in plant samples from various areas. Washing the leaves with water was found to remove a large amount of water-soluble aerosols.

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Section: Results and Dicussionsupporting

confidence: 72%

Section: Introductionmentioning

confidence: 99%

Determination of heavy metal concentrations in plants exposed to different degrees of pollution using ICP-AES

Kos

Budič

Hudnik

et al. 1996

Analytical and Bioanalytical Chemistry

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“…(2) with y i (measured values) in mg/L In an additional step it is possible to eliminate outliers by performing the reweighted least squares regression (RLSR). After reweighting the traditional LSR is carried out [16,17]. 1).…”

Section: Experimental Designmentioning

confidence: 99%

Complexation capacity of aquatic systems in dependence on different ligands and heavy metals ? Electroanalytical investigations and statistical evaluation

Einax

Kunze

1996

Analytical and Bioanalytical Chemistry

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Heavy metals exist in natural waters in different species. Mobility and bioavailability of bound metals can be influenced by some complex factors in the aquatic environment. Therefore, it is useful to determine the complexation properties of various ligands influenced by different metals. The copper and zinc complexation capacity was determined for a natural ligand (fulvic acid) and anthropogenic pollutants (e.g. nitrilotriacetic acid and ethylenediaminetetraacetic acid). The interactions between several ligands and metal ions and their effects on the complexation capacity were analyzed in particular. Applying methods of experimental design, such as multifactorial plans, it is possible to determine influence and interaction of various parameters (e.g. concentration of zinc or copper) by a minimum number of experiments. Differential pulse polarography was used for the determination of the complexation capacity. Methods of parametric and robust multiple linear regressions were applied for the interpretation of the measured values.

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Study of traffic-emitted lead pollution of soil and plants using different fuzzy clustering algorithms

Sârbu

Einax

2007

Anal Bioanal Chem

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We discuss the clustering of 234 environmental samples resulting from an extensive monitoring program concerning soil lead content, plant lead content, traffic density, and distance from the road at different sampling locations in former East Germany. Considering the structure of data and the unsatisfactory results obtained applying classical clustering and principal component analysis, it appeared evident that fuzzy clustering could be one of the best solutions. In the following order we used different fuzzy clustering algorithms, namely, the fuzzy c-means (FCM) algorithm, the Gustafson-Kessel (GK) algorithm, which may detect clusters of ellipsoidal shapes in data by introducing an adaptive distance norm for each cluster, and the fuzzy c-varieties (FCV) algorithm, which was developed for recognition of r-dimensional linear varieties in high-dimensional data (lines, planes or hyperplanes). Fuzzy clustering with convex combination of point prototypes and different multidimensional linear prototypes is also discussed and applied for the first time in analytical chemistry (environmetrics). The results obtained in this study show the advantages of the FCV and GK algorithms over the FCM algorithm. The performance of each algorithm is illustrated by graphs and evaluated by the values of some conventional cluster validity indices. The values of the validity indices are in very good agreement with the quality of the clustering results.

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On the description of lead pollution in plants caused by traffic under application of robust statistics

Cited by 4 publications

References 6 publications

Determination of heavy metal concentrations in plants exposed to different degrees of pollution using ICP-AES

Determination of heavy metal concentrations in plants exposed to different degrees of pollution using ICP-AES

Complexation capacity of aquatic systems in dependence on different ligands and heavy metals ? Electroanalytical investigations and statistical evaluation

Study of traffic-emitted lead pollution of soil and plants using different fuzzy clustering algorithms

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