Spatial analysis of chromium in southwestern part of Iran: probabilistic health risk and multivariate global sensitivity analysis.

This study was concerned with chromium as a potential carcinogenic contaminant in 64 wells located in five aquifers, southwest of Iran. A probabilistic health risk assessment indicated a high risk to the local residents including adults and children in the study area. A sequential sensitivity analysis and a novel approach known as multivariate global sensitivity analysis using both principal component analysis and B-spline were applied to investigate the behavior of health risk model along time considering four independent input parameters in the risk equation. In this context, based on the results of sensitivity analysis, concentration of chromium in drinking water (Cw) and body weight (W) were the most influential parameters. Random forest (RF) was used as a variable selection method to choose the most influential parameters for the prediction of chromium. Five parameters, among 13 water quality variables, including phosphate, nitrate, fluoride, manganese and iron were selected by RF as the most important parameters for spatial prediction. Hybrid methods of RF and ordinary kriging (RFOK) and RF and inverse distance weighting (RFIDW) were then applied for spatial prediction of Cr using the secondary variables. The RFOK and RFIDW were more efficient than that of ordinary kriging (OK) with respect to a cross-validation algorithm. For instance, in terms of relative root mean squared error, the performance of OK was improved from 31.72 to 23.21 and 23.61 for RFOK and RFIDW, respectively.

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

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.