Literature DB >> 31401754

Source and background threshold values of potentially toxic elements in soils by multivariate statistics and GIS-based mapping: a high density sampling survey in the Parauapebas basin, Brazilian Amazon.

Prafulla Kumar Sahoo1,2, Roberto Dall'Agnol3,4, Gabriel Negreiros Salomão3,4, Jair da Silva Ferreira Junior3, Marcio Souza da Silva3,5, Gabriel Caixeta Martins3, Pedro Walfir Martin E Souza Filho3,4, Mike A Powell6, Clovis Wagner Maurity3,4, Rômulo Simões Angelica4, Marlene Furtado da Costa7, José Oswaldo Siqueira3.   

Abstract

A high-density regional-scale soil geochemical survey comprising 727 samples (one sample per each 5 × 5 km grid) was carried out in the Parauapebas sub-basin of the Brazilian Amazonia, under the Itacaiúnas Basin Geochemical Mapping and Background Project. Samples were taken from two depths at each site: surface soil, 0-20 cm and deep soil, 30-50 cm. The ground and sieved (< 75 µm) fraction was digested using aqua regia and analyzed for 51 elements by inductively coupled plasma mass spectrometry (ICPMS). All data were used here, but the principal focus was on the potential toxic elements (PTEs) and Fe and Mn to evaluate the spatial distribution patterns and to establish their geochemical background concentrations in soils. Geochemical maps as well as principal component analysis (PCA) show that the distribution patterns of the elements are very similar between surface and deep soils. The PCA, applied on clr-transformed data, identified four major associations: Fe-Ti-V-Sc-Cu-Cr-Ni (Gp-1); Zr-Hf-U-Nb-Th-Al-P-Mo-Ga (Gp-2); K-Na-Ca-Mg-Ba-Rb-Sr (Gp-3); and La-Ce-Co-Mn-Y-Zn-Cd (Gp-4). Moreover, the distribution patterns of elements varied significantly among the three major geological domains. The whole data indicate a strong imprint of local geological setting in the geochemical associations and point to a dominant geogenic origin for the analyzed elements. Copper and Fe in Gp-1 were enriched in the Carajás basin and are associated with metavolcanic rocks and banded-iron formations, respectively. However, the spatial distribution of Cu is also highly influenced by two hydrothermal mineralized copper belts. Ni-Cr in Gp-1 are highly correlated and spatially associated with mafic and ultramafic units. The Gp-2 is partially composed of high field strength elements (Zr, Hf, Nb, U, Th) that could be linked to occurrences of A-type Neoarchean granites. The Gp-3 elements are mobile elements which are commonly found in feldspars and other rock-forming minerals being liberated by chemical weathering. The background threshold values (BTV) were estimated separately for surface and deep soils using different methods. The '75th percentile', which commonly used for the estimation of the quality reference values (QRVs) following the Brazilian regulation, gave more restrictive or conservative (low) BTVs, while the 'MMAD' was more realistic to define high BTVs that can better represent the so-called mineralized/normal background. Compared with CONAMA Resolution (No. 420/2009), the conservative BTVs of most of the toxic elements were below the prevention limits (PV), except Cu, but when the high BTVs are considered, Cu, Co, Cr and Ni exceeded the PV limits. The degree of contamination (Cdeg), based on the conservative BTVs, indicates low contamination, except in the Carajás basin, which shows many anomalies and had high contamination mainly from Cu, Cr and Ni, but this is similar between surface and deep soils indicating that the observed high anomalies are strictly related to geogenic control. This is supported when the Cdeg is calculated using the high BTVs, which indicates low contamination. This suggests that the use of only conservative BTVs for the entire region might overestimate the significance of anthropogenic contamination; thus, we suggest the use of high BTVs for effective assessment of soil contamination in this region. The methodology and results of this study may help developing strategies for geochemical mapping in other Carajás soils or in other Amazonian soils with similar characteristics.

Entities:  

Keywords:  Environmental contamination; Geochemical background; Multivariate analysis; Potentially toxic elements; Soil geochemical mapping; Southeastern Amazon

Mesh:

Substances:

Year:  2019        PMID: 31401754     DOI: 10.1007/s10653-019-00345-z

Source DB:  PubMed          Journal:  Environ Geochem Health        ISSN: 0269-4042            Impact factor:   4.609


  18 in total

1.  Multivariate statistical and GIS-based approach to identify heavy metal sources in soils.

Authors:  A Facchinelli; E Sacchi; L Mallen
Journal:  Environ Pollut       Date:  2001       Impact factor: 8.071

2.  Four decades of land-cover, land-use and hydroclimatology changes in the Itacaiúnas River watershed, southeastern Amazon.

Authors:  Pedro Walfir M Souza-Filho; Everaldo B de Souza; Renato O Silva Júnior; Wilson R Nascimento; Breno R Versiani de Mendonça; José Tasso F Guimarães; Roberto Dall'Agnol; José Oswaldo Siqueira
Journal:  J Environ Manage       Date:  2016-02-01       Impact factor: 6.789

3.  Background and threshold: critical comparison of methods of determination.

Authors:  Clemens Reimann; Peter Filzmoser; Robert G Garrett
Journal:  Sci Total Environ       Date:  2005-06-15       Impact factor: 7.963

4.  A visual basic spreadsheet macro for geochemical background analysis.

Authors:  Zoran Nakić; Kristijan Posavec; Andrea Bacani
Journal:  Ground Water       Date:  2007 Sep-Oct       Impact factor: 2.671

5.  Establishing geochemical background variation and threshold values for 59 elements in Australian surface soil.

Authors:  Clemens Reimann; Patrice de Caritat
Journal:  Sci Total Environ       Date:  2016-11-16       Impact factor: 7.963

6.  Reference values for heavy metals in soils of the Brazilian agricultural frontier in Southwestern Amazônia.

Authors:  Sabrina Novaes dos Santos; Luís Reynaldo Ferracciú Alleoni
Journal:  Environ Monit Assess       Date:  2012-11-10       Impact factor: 2.513

Review 7.  Correlation Coefficients: Appropriate Use and Interpretation.

Authors:  Patrick Schober; Christa Boer; Lothar A Schwarte
Journal:  Anesth Analg       Date:  2018-05       Impact factor: 5.108

8.  Methodology for the determination of normal background concentrations of contaminants in English soil.

Authors:  E Louise Ander; Christopher C Johnson; Mark R Cave; Barbara Palumbo-Roe; C Paul Nathanail; R Murray Lark
Journal:  Sci Total Environ       Date:  2013-04-10       Impact factor: 7.963

9.  Urban geochemistry: research strategies to assist risk assessment and remediation of brownfield sites in urban areas.

Authors:  I Thornton; M E Farago; C R Thums; R R Parrish; R A R McGill; N Breward; N J Fortey; P Simpson; S D Young; A M Tye; N M J Crout; R L Hough; J Watt
Journal:  Environ Geochem Health       Date:  2008-12       Impact factor: 4.609

10.  Soil heavy metal pollution and risk assessment in Shenyang industrial district, Northeast China.

Authors:  Xudong Jiao; Yanguo Teng; Yanhong Zhan; Jin Wu; Xueyu Lin
Journal:  PLoS One       Date:  2015-05-21       Impact factor: 3.240

View more
  2 in total

1.  The Optimization Strategy of the Existing Urban Green Space Soil Monitoring System in Shanghai, China.

Authors:  Weiwei Zhang; Jigang Han; Abiot Molla; Shudi Zuo; Yin Ren
Journal:  Int J Environ Res Public Health       Date:  2021-04-30       Impact factor: 3.390

2.  An integrated approach for spatial distribution of potentially toxic elements (Cu, Pb and Zn) in topsoil.

Authors:  Azadeh Vaziri; Ahad Nazarpour; Navid Ghanavati; Teimor Babainejad; Michael J Watts
Journal:  Sci Rep       Date:  2021-04-08       Impact factor: 4.379

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.