Analysing spatial patterns of soil pollution profiles in floodplain exposed to historical environmental load using correlation of proportional similarity matrices with spatial matrices

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00027049%3A_____%2F17%3AN0000029" target="_blank" >RIV/00027049:_____/17:N0000029 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00027049:_____/17:N0000016

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Analysing spatial patterns of soil pollution profiles in floodplain exposed to historical environmental load using correlation of proportional similarity matrices with spatial matrices

Popis výsledku v původním jazyce

The Czech Republic belongs to the countries with long-term industrial history, especially along the Czech – Saxony border, where the industrial rapid growth was led by coal processing. High TEs contents may be attributed to a spatial interaction of various pollution sources (long-term airborne pollution due to combustion of fossil fuel and chemical industry, geochemical anomalies of metal-logenic zones). High environmental load caused by various sources interference may be reported in the adjacent watersheds of the Ohře River. A regional analysis of soil contamination in floodplain soils (100-year flood inundation areas) was conducted by trace elements (Be, Cd, Co, Cr, Cu, Hg, Pb, Ni, V, Zn) assessment with the objectives of revealing both the spatial patterns of pollution magnitude as well as pollutants’ composition. There were compared trace elements contents (2M nitric acid extract) with national background values and geoaccumulation indices were calculated for each sample. Proportional similarities (cosine-theta matrix) between all the samples were calculated after the relative contributions of each element to the overall index had been calculated and transformed (range transformation, constant-row sum normalization). We correlated the proportional similarities matrix (cosine-theta matrix) with various spatial matrices (simple matrix of Euclidean distance derived from spatial coordinates, river network spatial distance) by the Mantel correlation test. There was found statistically significant Mantel correlation between proportional similarity and both spatial matrices. A multivariate Mantel correlogram was then computed to analyse spatial correlation changes of proportional similarities among the samples in relation to distance binding (a normalized Mantel statistic between a similarity matrix among sites and a matrix where pairs of sites belonging to the same distance class receive value 0 and the other pairs, value 1). There was proved that the proportional similarity of pollution profiles of soil samples diminished with the sample distance increase (from the distance of 20 km the Mantel correlation became insignificant and continued to approximate zero). The used methodology seems to be a promising tool to supplement geostatistical analyses of pollution magnitude and may bring a new angle to environmental gradients in riverine landscape because the spatial relations of proportional similarity may reflect various aspects of soil pollution - geochemical variation, pollution sources incidence, soil/environmental conditions changes along the watercourse.

Název v anglickém jazyce

Analysing spatial patterns of soil pollution profiles in floodplain exposed to historical environmental load using correlation of proportional similarity matrices with spatial matrices

Popis výsledku anglicky

The Czech Republic belongs to the countries with long-term industrial history, especially along the Czech – Saxony border, where the industrial rapid growth was led by coal processing. High TEs contents may be attributed to a spatial interaction of various pollution sources (long-term airborne pollution due to combustion of fossil fuel and chemical industry, geochemical anomalies of metal-logenic zones). High environmental load caused by various sources interference may be reported in the adjacent watersheds of the Ohře River. A regional analysis of soil contamination in floodplain soils (100-year flood inundation areas) was conducted by trace elements (Be, Cd, Co, Cr, Cu, Hg, Pb, Ni, V, Zn) assessment with the objectives of revealing both the spatial patterns of pollution magnitude as well as pollutants’ composition. There were compared trace elements contents (2M nitric acid extract) with national background values and geoaccumulation indices were calculated for each sample. Proportional similarities (cosine-theta matrix) between all the samples were calculated after the relative contributions of each element to the overall index had been calculated and transformed (range transformation, constant-row sum normalization). We correlated the proportional similarities matrix (cosine-theta matrix) with various spatial matrices (simple matrix of Euclidean distance derived from spatial coordinates, river network spatial distance) by the Mantel correlation test. There was found statistically significant Mantel correlation between proportional similarity and both spatial matrices. A multivariate Mantel correlogram was then computed to analyse spatial correlation changes of proportional similarities among the samples in relation to distance binding (a normalized Mantel statistic between a similarity matrix among sites and a matrix where pairs of sites belonging to the same distance class receive value 0 and the other pairs, value 1). There was proved that the proportional similarity of pollution profiles of soil samples diminished with the sample distance increase (from the distance of 20 km the Mantel correlation became insignificant and continued to approximate zero). The used methodology seems to be a promising tool to supplement geostatistical analyses of pollution magnitude and may bring a new angle to environmental gradients in riverine landscape because the spatial relations of proportional similarity may reflect various aspects of soil pollution - geochemical variation, pollution sources incidence, soil/environmental conditions changes along the watercourse.

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

10511 - Environmental sciences (social aspects to be 5.7)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů