Geostatistical modeling of the spatial distribution of soil dioxin in the vicinity of an incinerator. 2. Verification and calibration study
Geostatistical modeling of the spatial distribution of soil dioxin in the vicinity of an incinerator. 2. Verification and calibration study
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DOI：
10.1021/es7024966
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发表时间：
2008-05-15
影响因子：
11.4
通讯作者：
Adriaens, Peter
中科院分区：
文献类型：
--
作者：
Goovaerts, Pierre;Trinh, Hoa T.;Adriaens, Peter
在对诸如焚化炉之类的点源污染与人类健康之间的因果关系进行任何调查时，一个关键组成部分是获得与健康数据相同规模或地理位置的接触测量和/或准确模型。地质统计学允许人们模拟污染物浓度在各种空间支撑上的空间分布，同时结合现场数据和确定性分散模型的预测。在一篇论文中，该方法被用于确定密歇根州米德兰焚化炉周围二恶英TEQ（毒性当量）超过给定水平的概率很高的人口普查街区。该地质统计模型与人口数据一起，为收集51个新土壤数据提供了指导，从而可以验证地质统计预测并校准模型。每个新的土壤测量值都与最近网格节点模拟的100个TEQ值进行比较。测量浓度与平均模拟值之间的相关性为中等（0.44），在工厂属性线附近，实际浓度明显被高估。然而，从模拟TEQ值计算的概率区间提供了一个精确的不确定性模型：落在这些区间内的观测值的比例超过了模型的预期。基于模拟的概率区间也比从数据的全局直方图中得到的区间窄，这表明地质统计学方法的精度更高。对于本验证研究中使用的小而采样良好的区域，对数正态普通克里格法提供了相当相似的估计结果；然而，不确定性模型并不总是准确的。然后，利用53个原始土壤样本和51个新土壤样本的组合集进行回归分析和地质统计模拟，得出了密歇根州米德兰地区TEQ空间分布的更新模型。
A key component in any investigation of cause-effect relationships between point source pollution, such as an incinerator, and human health is the availability of measurements and/or accurate models of exposure at the same scale or geography as the health data. Geostatistics allows one to simulate the spatial distribution of pollutant concentrations over various spatial supports while incorporating both field data and predictions of deterministic dispersion models. This methodology was used in a companion paper to identify the census blocks that have a high probability of exceeding a given level of dioxin TEQ (toxic equivalents) around an incinerator in Midland, MI. This geostatistical model, along with population data, provided guidance for the collection of 51 new soil data,which permits the verification of the geostatistical predictions, and calibration of the model. Each new soil measurement was compared to the set of 100 TEQ values simulated at the closest grid node. The correlation between the measured concentration and the averaged simulated value is moderate (0.44), and the actual concentrations are clearly overestimated in the vicinity of the plant property line. Nevertheless, probability intervals computed from simulated TEQ values provide an accurate model of uncertainty: the proportion of observations that fall within these intervals exceeds what is expected from the model. Simulation-based probability intervals are also narrower than the intervals derived from the global histogram of the data, which demonstrates the greater precision of the geostatistical approach. Log-normal ordinary kriging provided fairly similar estimation results for the small and well-sampled area used in this validation study; however, the model of uncertainty was not always accurate. The regression analysis and geostatistical simulation were then conducted using the combined set of 53 original and 51 new soil samples, leading to an updated model for the spatial distribution of TEQ in Midland, MI.