| Nickel contamination has always been a wordwide concern because of Ni’s hazardous effects on organisms.Accurate evaluation of the bioavailability of heavy metals in soil is the basis for its ecological risk assessment,no method has been advocated universally because heavy metals uptake is influenced by soil properties.The mechanism-based multi-surface model have been successfully used to describe the solid-solution partition of metals in soils,however,the application of multi-surface model to the soil-plant system has not been performed.In this thesis,the adsorption behaviors of Ni2+ and Co2+on goethite surface were studied by batch adsorption experiments,and the CD-MUSIC model parameters of Ni2+and Co2+ on goethite were obtained by fitting the adsorption experimental data.Subsequently,19 soils representing the major soil types in China were selected to examine the performance of the multi-surface model in predicting the 0.01 mol·L-1 CaCl2-extracted Ni.Finally,the phytoaccumulation of Ni in wheat grown in 19 soils was assessed using MSMs with "generic"parameters.The model’s performance was compared with those of other chemical extraction techniques and a multiple regression model.The main conclusions are as follows:(1)The adsorption of Ni2+ and Co2+ on the surface of goethite were inner-sphere surface complexation,the adsorption of Ni2+ and Co2+ were strongly influenced by the pH of the and increased with the increasing pH,and the ionic strength showed little effect to Ni2+ and Co2+adsorption.The CD-MUSIC model was used to successfully fit the adsorption datas under different conditions(R2=0.995 and 0.990).The surface adsorption reactions were:2≡FeOH0.5+Ni2+=(≡FeOH)2-·Ni2+(log K=9.46)and 2≡FeOH-0.5+Co2+=(≡FeOH)2-·Co2+(log K=9.26).The parameters were used to predict the adsorption data of Ni2+and Co2+ in goethite obtained from the published papere,and their applicability and accuracy have been demonstrated.(2)The multi-surface model predicted the 0.01 mol·L-1 CaCl2-extracted Ni concentration favorably,and the performance of the two-site model was superior to that of one-site model.The model predictions further illustrated the contribution of each soil components to the Ni2+binding:in acidic soils,SOM was the main pool for Ni2+,whereas in alkaline soils,the contribution of ferric oxides increased.(3)The use of multi-surface adsorption model has achieved satisfactory results in predicting Ni bioavailability(R2=0.848 and 0.830 for root and shoot,respectivly).The correlation coefficients(R2)obtained using various methods have the following order:soil pore water>MSMs>DGT>soil total Ni>0.43 mol·L-1 HNO3>0.01 mol·L-1 CaCl2(for roots);soil pore water>DGT>MSMs>0.01 mol·L-1 CaCl2>soil total Ni>0.43 mol·L-1 HNO3(for shoots).Ni extracted using the DGT and the Ni concentration in soil pore water have advantages in predicting Ni bioavailability in soil;the extraction efficiency of 0.01 mol·L-1 CaCl2 for alkaline soils is much lower than that for acidic soils,its application to alkaline soils has been limited;extraction using 0.43 mol·L-1 HNO3 may overestimate the bioavailability of metals in soils..(4)Compared with the empirical regression model,both MSM and empirical regression model can predict the Ni bioavailability well,but MSM has advantages in extrapolation,and the empirical regression model is mainly applicable to soil types and environmental conditions that the regression equations were dirived.The results show that the multi-surface model can be used to predict the bioavailability of Ni in soil,and as a supplement to traditional chemical research methods,it provides a practical tool for studying the Ni migration behavior and risk assessment in soil. |
PDF Full Text Request