土壤砷植物暴露途径的土壤因子模拟

Predicting the plant exposure to soil arsenic under varying soil factors

确定土壤中重金属生物有效性是评价土壤重金属污染生态风险的关键,然而在生态风险评价实际应用中,测定土壤重金属生物有效性耗时且高成本,限制了生物有效性评价法的应用。通过对模式植物的文献搜集,总结了影响植物富集土壤砷的7个土壤因子,揭示了土壤砷植物暴露的影响机制。运用SPSS 18.0对文献数据集各个土壤因子进行了回归分析、相关性分析和共线性分析。单因子回归分析表明营养盐类对植物富集砷影响很小,可以忽略不计;相关性分析和共线性分析结果表明土壤因子之间存在多元共线性;主成分分析结果表明,植物富集砷浓度主要受土壤质地的物理综合指标以及土壤总砷含量和土壤酸碱度等化学综合指标影响。其中植物富集浓度受土壤中总砷浓度影响最大,受土壤质地中砂粒含量影响其次;土壤粉粒、粘粒、有机质含量和阳离子交换量对富集也有一定影响;而土壤酸碱度对植物富集浓度的影响相对较小。最终通过数学模型解释植物富集砷浓度随土壤性质变化的规律,建立了土壤性质与土壤砷植物暴露的相关关系,为土壤重金属生物有效性风险评价法提供理论依据。

Determining bioavailability is a key process in ecological risk assessment of soil heavy metal pollution. It is timeconsuming and costly to measure the soil heavy metal bioavailability, limiting its application in ecological risk assessment. In this research, data collected from the literature was analyzed by regression analysis, correlation analysis and linear analysis using SPSS. Seven soil factors affecting plant uptake of soil arsenic are summarized. Mechanisms of plant exposed to soil arsenic are revealed. Statistical analyses showed that the influence of nutrition salts to plant accumulation of arsenic could be neglected, the soil factors were multiple linear and the plant accumulation concentration was mainly influenced by the physical composite index of soil texture, and chemical composite index of soil pH value and total arsenic concentration. Silt content, clay content, organic matter content and cation exchange capacity affect the accumulation to some extent. Mathematical model was developed to connect the soil properties and plant exposed to soil arsenic. It reveals the variation of plant accumulate arsenic concentration with soil properties, and provides the theory basis for soil heavy metal bioavailability risk evaluation method.