不同土壤中镍的离子活度研究  

The Study of Nickel Speciation in Different Soils

作　　者：李波[1,2] 马义兵[2] 史奕[3] LI Bo;MA Yibing;SHI Yi(Institute of Plant Nutrition and Environmental Resources. Liaoning Academy of Agricultural Sciences, Shenyang 110161, China;Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China;Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 11()016, China)

机构地区：[1]辽宁省农业科学院植物营养与环境资源研究所,辽宁沈阳110161 [2]中国农业科学院农业资源与农业区划研究所,北京100081 [3]中国科学院沈阳应用生态研究所,辽宁沈阳110016

出　　处：《环境科学与技术》2019年第4期202-206,共5页Environmental Science & Technology

基　　金：国家自然科学基金(41401361);国家科技支撑项目资助(2015BAD05B03)

摘　　要：自由离子浓度(或活度)是决定重金属的生物有效性和化学行为的关键因素,然而土壤系统中自由金属离子的活度测定与模型预测还存在很多不确定因素。该研究以重金属元素镍为研究对象,从它的固液分配系数、自由离子活度影响因素出发,通过经验的多元回归模型以及腐殖质平衡模型(WHAM VI)分析了影响其指标变化的关键因子。结果发现,土壤孔隙水的pH是影响镍在土壤固/液相分配的最关键因子,可以解释91%固液分配系数(K_d)的变化;同时,它也是影响自由镍离子活度占总镍百分比的最关键因子(r^2=0.74),土壤孔隙水中溶解性有机碳含量(DOC)可以提高回归模型的预测,但贡献率仅占10%。使用WHAM VI预测土壤孔隙水中自由镍离子活度的结果显示,采用惯用的65%活性富里酸(AFA)代替孔隙水中的活性DOM会导致预测值低于道南膜技术(DMT)测定值20%左右(碱性土壤除外),两者均方根误差(RMSE)达到15.7。分别降低碱性、中性、酸性土壤中的%AFA至50%、10%、5%,模型预测能力显著提高,预测值与实测值百分比的RMSE达到8.65。其研究结果说明土壤中的活性DOM比例较低(5%～50%),尤其对于中性与酸性土壤来说,活性DOM≤10%。该研究结果对于土壤系统的模型构建与重金属镍的环境风险评估具有重要意义。Free nickel(Ni) species in soils is a key issue to its bioavailability. However, predictive models for Ni speciation across a wide range of soils are still unavailable. In this study, Ni distribution and its speciation in three contaminated soil samples are investigated via Donnan membrane dialysis technique(DMT) and predictive models. The results showed p H is the most important factor affecting distribution of Ni in soil solid and liquid. Also, pH is also the most key parameter explaining the percentage of free Ni2+ to total dissolved Ni in soil pore water. According to model, most of free Ni^2+ fraction was underestimated when using default log KNiFA and 65% active fulvic acid(AFA) as inputs in WHAM VI, especially for neutral and acidic soils. The best prediction was found when using adjusted %AFA with 5% for acidic soil, 10% for neutral soil and 50% for alkaline soil with the smallest RMSE = 8.65 and biggest r^2= 0.74. Decreasing binding constant of FA to Ni would not help model to improve the prediction for free Ni^2+ fraction significantly. The study presents a comprehensive database of Ni speciation and an effective attempt of free Ni2+ prediction in classical Chinese soils.

关 键 词：镍离子活度 土壤孔隙水 固液分配 模型预测 

分 类 号：X142[环境科学与工程—环境科学]