Evaluation of geochemical associations as a screening tool for identifying anthropogenic trace metal contamination

Anderson, Rob; Kravitz, Michael

doi:10.1007/s10661-009-1079-2

Cited by 14 publications

(7 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For Mn concentrations, which were found to be normally distributed (Table 2), log transformation of the data resulted in no samples being identified as potentially contaminated; the upper limit of the log transformed boxplot was equal to the maximum of the unscreened dataset. These results highlight that errors in statistical interpretation can occur if the common assumption of environmental data being log normally distributed (Aide, 2005;Anderson and Kravitz, 2010;Hamon et al, 2004;Olszowey et al, 1995) is applied. The upper concentration limits derived from the observed point of inflection on a CFP and UW of a boxplot (normal distribution) were comparable (within 31%) to the maximum of the manually screened dataset.…”

Section: Comparison Of Statistical Methods For Exclusion Of Contaminated Samples With the Manually Screened Datasetmentioning

confidence: 96%

Assessment of ambient background concentrations of elements in soil using combined survey and open-source data

Mikkonen

Clarke

Dasika³

et al. 2017

Science of The Total Environment

View full text Add to dashboard Cite

Understanding ambient background concentrations in soil, at a local scale, is an essential part of environmental risk assessment. Where high resolution geochemical soil surveys have not been undertaken, soil data from alternative sources, such as environmental site assessment reports, can be used to support an understanding of ambient background conditions. Concentrations of metals/metalloids (As, Mn, Ni, Pb and Zn) were extracted from open-source environmental site assessment reports, for soils derived from the Newer Volcanics basalt, of Melbourne, Victoria, Australia. A manual screening method was applied to remove samples that were indicated to be contaminated by point sources and hence not representative of ambient background conditions. The manual screening approach was validated by comparison to data from a targeted background soil survey. Statistical methods for exclusion of contaminated samples from background soil datasets were compared to the manual screening method. The statistical methods tested included the Median plus Two Median Absolute Deviations, the upper whisker of a normal and log transformed Tukey boxplot, the point of inflection on a cumulative frequency plot and the 95th percentile. We have demonstrated that where anomalous sample results cannot be screened using site information, the Median plus Two Median Absolute Deviations is a conservative method for derivation of ambient background upper concentration limits (i.e. expected maximums). The upper whisker of a boxplot and the point of inflection on a cumulative frequency plot, were also considered adequate methods for deriving ambient background upper concentration limits, where the percentage of contaminated samples is <25%. Median ambient background concentrations of metals/metalloids in the Newer Volcanic soils of Melbourne were comparable to ambient background concentrations in Europe and the United States, except for Ni, which was naturally enriched in the basalt-derived soils of Melbourne.

show abstract

Section: Comparison Of Statistical Methods For Exclusion Of Contaminated Samples With the Manually Screened Datasetmentioning

confidence: 96%

Assessment of ambient background concentrations of elements in soil using combined survey and open-source data

Mikkonen

Clarke

Dasika³

et al. 2017

Science of The Total Environment

View full text Add to dashboard Cite

show abstract

“…Indeed these concentrations are related more to the chemical composition of the parent material and to the degree of weathering than to the anthropogenic influence (Zhao et al, 2007). As these geochemical associations differ significantly across the different soil orders (Anderson and Kravitz, 2010), this method should be applied to larger datasets with a detailed classification in more than two soil groups, in order to build models that are more robust than in our case study. However, some TMs, especially the most mobile ones, are not well correlated to the major elements and this can lead to high uncertainties in the calculation of the theoretical concentrations.…”

Section: Comparison Of the Different Methods Of Estimating Soil Metalmentioning

confidence: 99%

“…As TMs are naturally present in the primary and secondary minerals (e.g., silicates and oxides) of the soils (Wilson et al, 2008), the background concentrations are supposed to derive from the weathering of these minerals. Therefore, significant relationships can be found with other elements constitutive of minerals, such as Fe, Al and Mn, which are used as predictors of the natural concentrations of TMs (Anderson and Kravitz, 2010).…”

Section: Multiple Linear Regressionmentioning

confidence: 99%

Modelling trace metal background to evaluate anthropogenic contamination in arable soils of south-western France

et al. 2013

View full text Add to dashboard Cite

The trace metal (TM) content in arable soils has been monitored across a region of France characterised by a large proportion of calcareous soils. Within this particular geological context, the objectives were to first determine the natural levels of trace metals in the soils and secondly, to assess which sites were significantly contaminated. Because no universal contamination assessment method is currently available, four different methods were applied and compared in order to facilitate the best diagnosis of contamination. First, the TM geochemical background was determined by using basic descriptive statistics and linear regression models calculated with semi-conservative major elements as predictors. The natural concentrations of trace metals varied greatly due to the high soil heterogeneity encountered on the regional scale and were more-or-less accurately modelled according to the considered TM. Second, the basic descriptive statistics and the linear regression methods were then compared with the enrichment factor (EF) method and multivariate analysis (PCA), in order to evaluate whether the concentrations measured in soils were abnormally high or not. The advantages and disadvantages of each method were discussed and their results used to identify the most probable contamination cases, the influence of the soils characteristics, as well as the agricultural land cover. The basic descriptive method was good as a first and easy approach to describe the TM ambient concentrations, but may misinterpret the natural anomalies as contaminations. Based on geochemical associations, the linear regression method provided more realistic results even if the relationships between major and trace metals were not significant for the most mobile TM. The EF method was useful to identify high point source contaminations, but it was not suitable when considering a large dataset of low TM concentrations. Finally, the PCA method was a good preliminary tool for the description of the global TM concentrations in a studied area, but it could only give indication on the highest contaminated points. By comparing the results of the different methods in the studied region, we estimated that 24% of the arable soils were contaminated by at least one trace metal, mainly Cu in vineyards/orchards and Cd, Pb and/or Zn in grazing lands. In addition, the calcareous soils exhibited globally higher natural and anthropogenic TM concentrations than non-calcareous soils, probably because of the lower TM mobility at alkaline pH.

show abstract

“…Determination of background spectrum and concentration thresholds were determined in accordance with the experience of other investigators (Reimannet et al, 2005;Grünfeld, 2005,Anderson & Kravitz, 2010. For the determination of the local background the soil samples were collected in an urbanized area of the city, which remained without direct visual anthropogenic interference.…”

Section: Figurementioning

confidence: 99%

Geochemical mapping and environmental indexing of an urban area (Rio Grande, RS)

Mirlean¹,

Gripp²

2018

Geochim. Bras.

View full text Add to dashboard Cite

+55 53 32336786; RESUMORealizamos um mapeamento geoquímico da cobertura de solo dos setores industriais e residenciais da cidade de Rio Grande (RS). Várias zonas anômalas de mercúrio, cobre, zinco, chumbo, níquel, cromo e ferro foram identificadas, o que correspondeu à alocação histórico-espacial de diferentes indústrias da cidade. O mapeamento do território da cidade usando o complexo índice eco-geoquímico Zc demonstrou que a maior parte da área urbana está contaminada com metais até o nível que requer medidas de mitigação obrigatórias. A aplicação do método de subtração sequencial a partir do complexo índice de elementos pelo grau de sua participação na contaminação do território possibilitou estabelecer uma associação paragenética de metais Cu, Pb, Zn, que formam os centros de contaminação por metais na cidade. Com base nos dados recebidos, uma avaliação da poluição da área urbana foi realizada de acordo com a legislação brasileira. A avaliação da área amostrada segundo a legislação referida enquadra o solo estudado como pertencente à Classe 4, ou seja, a área necessita de gerenciamento imediato, que incluem eliminação dos riscos à saúde humana e ao meio ambiente e planejamento dos usos futuros do solo. Palavras-Chave: mapeamento geoquímico, cobertura de solo, metais, áreas urbanas ABSTRACTWe have carried out a geochemical mapping of soil cover of industrial and residential sectors of the city of Rio Grande (RS). Various anomalous zones of mercury, copper, zinc, lead, nickel, chromium and iron have been identified, which corresponded to the historic-spatial allocation of different industries in the city. The mapping of the city's territory using the complex eco-geochemical index Zc demonstrated that most of the urban area is contaminated with metals up to the level requiring mandatory mitigation measures. The application of the method of sequential subtraction from the complex index of elements by the degree of their participation in the contamination of the territory made it possible to establish a paragenetic association of metals Cu, Pb, Zn, which forms the centers of metal contamination in the city. Based on the data received, an assessment of the pollution of the urban area was carried out in accordance with Brazilian legislation. This evaluation testified that studied soil belongs to Class 4 according to legislative norms, which means that the city needs immediate environmental management in terms of eliminating risks to human health and the environmental planning of future land use.

show abstract

Evaluation of geochemical associations as a screening tool for identifying anthropogenic trace metal contamination

Cited by 14 publications

References 36 publications

Assessment of ambient background concentrations of elements in soil using combined survey and open-source data

Assessment of ambient background concentrations of elements in soil using combined survey and open-source data

Modelling trace metal background to evaluate anthropogenic contamination in arable soils of south-western France

Geochemical mapping and environmental indexing of an urban area (Rio Grande, RS)

Contact Info

Product

Resources

About