Wragg Joanna, Cave Mark, Nathanail Paul
British Geological Survey, Keyworth, Nottingham, UK.
J Environ Sci Health A Tox Hazard Subst Environ Eng. 2007 Jul 15;42(9):1303-15. doi: 10.1080/10934520701436062.
Twenty samples from soils developed over the Northampton Sand ironstone formation were collected from, in and around the town of Wellingborough, Northamptonshire, UK. The total arsenic (As) content ranged from ca. 20-100 mg kg(-1) and the bioaccessible As content, as measured by a physiologically based in vitro extraction test, ranged from 1 to 6 mg kg(-1). A chemometric algorithm for mixture resolution, when applied to total element and total organic carbon concentration of the soils, was able to identify chemically distinct soil constituents and their associated As content. Multiple linear regression (MLR) modelling, using the As content of the intrinsic soil constituents and their first order interactions as independent variables, was able to predict the bioaccessible As content of the soils (R2=0.85) with an uncertainty of 1.33 mg kg(-1). Although the MLR model showed that the interactions between the soil constituents were the key factors controlling the bioaccessible fraction in each soil most of the total As was found to be bound to an Fe oxide soil constituent. The model predictions shown are currently only valid for the geological and soil chemical setting investigated here, extrapolation to other geological settings would require additional investigations.
从英国北安普敦郡韦林伯勒镇及其周边地区发育于北安普敦砂岩铁矿石地层之上的土壤中采集了20个样本。总砷（As）含量范围约为20 - 100毫克/千克，通过基于生理学的体外提取试验测定的生物可利用砷含量范围为1至6毫克/千克。一种用于混合物解析的化学计量算法，应用于土壤的总元素和总有机碳浓度时，能够识别化学性质不同的土壤成分及其相关的砷含量。多元线性回归（MLR）建模，以固有土壤成分的砷含量及其一阶相互作用作为自变量，能够预测土壤的生物可利用砷含量（R2 = 0.85），不确定性为1.33毫克/千克。尽管MLR模型表明土壤成分之间的相互作用是控制每种土壤中生物可利用部分的关键因素，但发现大部分总砷与一种铁氧化物土壤成分结合。所示的模型预测目前仅适用于此处研究的地质和土壤化学环境，外推到其他地质环境需要进一步研究。
