Numerical study of soil heterogeneity effects on contaminant transport in unsaturated soil (model development and validation)

The movement of chemicals through soil to groundwater is a major cause of degradation of water resources. In many cases, serious human and stock health implications are associated with this form of pollution. The study of the effects of different factors involved in transport phenomena can provide valuable information to find the best remediation approaches. Numerical models are increasingly being used for predicting or analyzing solute transport processes in soils and groundwater. This article presents the development of a stochastic finite element model for the simulation of contaminant transport through soils with the main focus being on the incorporation of the effects of soil heterogeneity in the model. The governing equations of contaminant transport are presented. The mathematical framework and the numerical implementation of the model are described. The comparison of the results obtained from the developed stochastic model with those obtained from a deterministic method and some experimental results shows that the stochastic model is capable of predicting the transport of solutes in unsaturated soil with higher accuracy than deterministic one. The importance of the consideration of the effects of soil heterogeneity on contaminant fate is highlighted through a sensitivity analysis regarding the variance of saturated hydraulic conductivity as an index of soil heterogeneity. © 2011 John Wiley & Sons, Ltd.

Relating monolithic and granular leaching from contaminated soil treated with different cementitious binders.

This work employed a clayey, silty, sandy gravel contaminated with a mixture of metals (Cd, Cu, Pb, Ni and Zn) and diesel. The contaminated soil was treated with 5 and 10% dosages of different cementitious binders. The binders include Portland cement, cement-fly ash, cement-slag and lime-slag mixtures. Monolithic leaching from the treated soils was evaluated over a 64-day period alongside granular leachability of 49- and 84-day old samples. Surface wash-off was the predominant leaching mechanism for monolithic samples. In this condition, with data from different binders and curing ages combined, granular leachability as a function of monolithic leaching generally followed degrees 4 and 6 polynomial functions. The only exception was for Cu, which followed the multistage dose-response model. The relationship between both leaching tests varied with the type of metal, curing age/residence time of monolithic samples in the leachant, and binder formulation. The results provide useful design information on the relationship between leachability of metals from monolithic forms of S/S treated soils and the ultimate leachability in the eventual breakdown of the stabilized/solidified soil.

Heavy Metals in Soil and Crops of an Intensively Farmed Area: A Case Study in Yucheng City, Shandong Province, China

lThe study was supported by the Knowledge Innovation Foundation of the institute of Geographical Sciences and Natural Resource, Chinese Academy of Sciences (Grant No. 200906002) and Key Directional Project of Knowledge Innovation of Chinese Academy of Sciences (Grant No. KSCX2-YW-N-46-01). The authors would like to thank to Luke Driskell for his kind help and hard work on English language polishing of the article.

Spatial distribution of soil heavy metal pollution estimated by different interpolation methods: Accuracy and uncertainty analysis

Mapping the spatial distribution of contaminants in soils is the basis of pollution evaluation and risk control. Interpolation methods are extensively applied in the mapping processes to estimate the heavy metal concentrations at unsampled sites. The performances of interpolation methods (inverse distance weighting, local polynomial, ordinary kriging and radial basis functions) were assessed and compared using the root mean square error for cross validation. The results indicated that all interpolation methods provided a high prediction accuracy of the mean concentration of soil heavy metals. However, the classic method based on percentages of polluted samples, gave a pollution area 23.54-41.92% larger than that estimated by interpolation methods. The difference in contaminated area estimation among the four methods reached 6.14%. According to the interpolation results, the spatial uncertainty of polluted areas was mainly located in three types of region: (a) the local maxima concentration region surrounded by low concentration (clean) sites, (b) the local minima concentration region surrounded with highly polluted samples; and (c) the boundaries of the contaminated areas. (C) 2010 Elsevier Ltd. All rights reserved.

Independence of alpine meadow plants from soil organic matter for nitrogen supply: evidence from stable nitrogen isotopes

Stable nitrogen isotope signatures of major sources of mineral nitrogen ( mineralization of soil organic nitrogen, biological N-2 fixation by legumes, annual precipitation and plant litter decomposition) were measured to relatively define their individual contribution to grass assimilation at the Haibei Alpine Meadow Ecosystem, Qinghai, China. The results indicated that delta N-15 values (- 2.40 parts per thousand to 0.97 parts per thousand) of all grasses were much lower than those of soil organic matter (3.4 +/- 0.18 parts per thousand) and mineral nitrogen ( ammonium and nitrate together,7.8 +/- 0.57 parts per thousand). Based on the patterns of stable nitrogen isotopes, soil organic matter (3.4 +/- 0.18 parts per thousand), biological N-2 fixation (0 parts per thousand), and precipitation (- 6.34 +/- 0.24 parts per thousand) only contributed to a small fraction of nitrogen requirements of grasses, but plant litter decomposition (- 1.31 +/- 1.01 parts per thousand) accounted for 67%.