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Trace elements concentrations in soil, desert-adapted and non-desert plants in central Iran: Spatial patterns and uncertainty analysis

Overview of attention for article published in Environmental Pollution, December 2018
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Title
Trace elements concentrations in soil, desert-adapted and non-desert plants in central Iran: Spatial patterns and uncertainty analysis
Published in
Environmental Pollution, December 2018
DOI 10.1016/j.envpol.2018.08.071
Pubmed ID
Authors

Mohamad Sakizadeh, Jose Antonio Rodríguez Martín, Chaosheng Zhang, Fatemeh Mehrabi Sharafabadi, Hadi Ghorbani

Abstract

The concentrations of Cd, Cr and Pb in soil samples and As, Cd, Cr and Pb in plant specimens were analyzed in an arid area in central Iran. Plants were categorized into desert-adapted (Haloxylon ammodendron, Atraphaxis spinosa and Artemisia persica) and non-desert species. It was found that the trace element (TE) accumulating potential of the desert species (Haloxylon ammodendron and Artemisia persica) with a mean value of 0.1 mg kg-1 for Cd was significantly higher than that of the majority of the non-desert species with an average of 0.05 mg kg-1. Artemisia also had a high As accumulating capability with a mean level of 0.8 mg kg-1 in comparison with an average of 0.2 mg kg-1 for most of the other plant species. The mean values of Cr and Pb in Haloxylon ammodendron and Artemisia persica were 5 and 3 mg kg-1, respectively. Among the desert-adapted plants, Atraphaxis proved to be a species with high Cr and Pb accumulating potential, as well. The geoaccumulation index and the overall pollution scores indicated that the highest environmental risk was related to Cd. Different statistical analyses were used to study the spatial patterns of soil Cd and their connections with pollution sources. The variogram was estimated using a classical approach (weighted least squares) and was compared with that of the posterior summaries that resulted from the Bayesian technique, which lay within the 95% Bayesian credible quantile intervals (BIC) of posterior parameter distributions. The prediction of cadmium values at un-sampled locations was implemented by multi-Gaussian kriging and sequential Gaussian simulation methods. The prediction maps showed that the region most contaminated by Cd was the north-eastern part of the study area, which was linked to mining activities, while agricultural influence contributed less in this respect.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 17%
Lecturer > Senior Lecturer 3 13%
Student > Master 3 13%
Other 2 9%
Student > Bachelor 2 9%
Other 2 9%
Unknown 7 30%
Readers by discipline Count As %
Environmental Science 5 22%
Chemical Engineering 2 9%
Chemistry 2 9%
Engineering 2 9%
Agricultural and Biological Sciences 1 4%
Other 2 9%
Unknown 9 39%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 September 2018.
All research outputs
#11,945,297
of 13,472,025 outputs
Outputs from Environmental Pollution
#3,603
of 5,157 outputs
Outputs of similar age
#228,506
of 265,068 outputs
Outputs of similar age from Environmental Pollution
#129
of 190 outputs
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So far Altmetric has tracked 5,157 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.9. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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