INRA, US1106 Unité Infosol, Centre de recherches d'Orléans, CS 40001, Ardon, 45075 Orléans Cedex 2, France.
Sci Total Environ. 2011 Sep 1;409(19):3719-31. doi: 10.1016/j.scitotenv.2011.05.048. Epub 2011 Jul 3.
Persistent organic pollutants (POPs) impact upon human and animal health and the wider environment. It is important to determine where POPs are found and the spatial pattern of POP variation. The concentrations of 90 molecules which are members of four families of POPs and two families of herbicides were measured within a region of Northern France as part of the French National Soil Monitoring Network (RMQS: Réseau de Mesures de la Qualité des Sols). We also gather information on five covariates (elevation, soil organic carbon content, road density, land cover and population density) which might influence POP concentrations. The study region contains 105 RMQS observation sites arranged on a regular square grid with spacing of 16 km. The observations include hot-spots at sites of POP application, smaller concentrations where POPs have been dispersed and observations less than the limit of quantification (LOQ) where the soil has not been impacted by POPs. Fifty nine of the molecules were detected at less than 50 sites and hence the data were unsuitable for spatial analyses. We represent the variation of the remaining 31 molecules by various linear mixed models which can include fixed effects (i.e. linear relationships between the molecule concentrations and covariates) and spatially correlated random effects. The best model for each molecule is selected by the Akaike Information Criterion. For nine of the molecules, spatial correlation is evident and hence they can potentially be mapped. For four of these molecules, the spatial correlation cannot be wholly explained by fixed effects. It appears that these molecules have been transported away from their application sites and are now dispersed across the study region with the largest concentrations found in a heavily populated depression. More complicated statistical models and sampling designs are required to explain the distribution of the less dispersed molecules.
持久性有机污染物（POPs）对人类和动物健康以及更广泛的环境都有影响。确定 POPs 的存在地点以及 POP 变化的空间模式非常重要。在法国北部的一个地区，作为法国国家土壤监测网络（RMQS：土壤质量监测网络）的一部分，我们测量了四个 POP 家族和两个除草剂家族的 90 种分子的浓度。我们还收集了可能影响 POP 浓度的五个协变量（海拔、土壤有机碳含量、道路密度、土地覆盖和人口密度）的信息。研究区域包含 105 个 RMQS 观测点，这些观测点排列在一个规则的正方形网格上，间隔为 16 公里。这些观测包括 POP 应用点的热点、POP 分散的较小浓度点和低于定量限（LOQ）的观测点，这些土壤没有受到 POP 的影响。59 种分子在不到 50 个地点被检测到，因此数据不适合空间分析。我们用各种线性混合模型来表示其余 31 种分子的变化，这些模型可以包括固定效应（即分子浓度和协变量之间的线性关系）和空间相关的随机效应。通过赤池信息量准则（Akaike Information Criterion）选择每个分子的最佳模型。对于其中 9 种分子，存在空间相关性，因此它们可能可以进行映射。对于这 9 种分子中的 4 种，空间相关性不能完全用固定效应来解释。这些分子似乎已经从它们的应用地点被运输走，现在在研究区域内分散开来，最大浓度出现在人口稠密的洼地。需要更复杂的统计模型和采样设计来解释分布更分散的分子的分布。
