室外射击场(OSR)的土壤污染是人类健康的主要威胁,特别是当,活动结束后,土地用于娱乐区或农业生产。使用多传感器方法评估了意大利南部OSR的土地退化状况。它基于:i)近端传感器,包括用于测量土壤电导率(ECa)和磁化率(MSa)的电磁感应(EMI),K的γ射线光谱法,eU和eTh分析和超声波透入法检测代表土壤强度的锥体指数(CI)数据,ii)土壤厚度(ST)的实地调查,和iii)通过便携式X射线荧光光谱法对潜在有毒元素(PTE)进行实验室分析,并通过气相色谱法对多环芳烃(PAHs)进行实验室分析。使用地统计学方法对测量的空间变异性进行了建模和映射。测量最密集的协变量(即,表土的ECa)在具有外部漂移的克里格中使用,以改善PTE的预测。PTE图得到了空间不确定性图的补充。将稳健的多变量主成分分析(rPCA)应用于近端传感器和实验室数据,并允许识别PAHs的关联。铅,CI与表土ECa沿第一组分(PC1),强调土地人为效应与EMI措施之间的相关性;而ST(估计地下石灰华硬层的深度)与沿第二部分(PC2)的底部土壤ECa和MSa之间的关联证明了土壤地层学对EMI措施的影响。这项研究表明,同时使用与实验室分析相关的不同近端传感器可以评估和建模OSR的土地退化状态的空间变异性,包括土壤压实,有机和无机污染。EMI数据与PTEs含量之间的相关性突出了该技术在土壤污染领域的潜力。
Soil contamination in outdoor shooting ranges (OSRs) is a major threat for human health, particularly when, after the end of activities, the land is used for recreational areas or agricultural production. The status of land degradation of an OSR in southern Italy was assessed using a multisensor approach. It was based on: i) proximal sensors, including electromagnetic induction (EMI) for measuring soil electrical conductivity (ECa) and magnetic susceptibility (MSa), γ-ray spectrometry for K, eU and eTh analyses and ultrasonic penetrometry detecting cone index (CI) data representative of soil\'s strength, ii) field surveys on soil thickness (ST), and iii) laboratory analyses of potentially-toxic-elements (PTEs) by portable X-ray fluorescence spectrometry and polycyclic aromatic hydrocarbons (PAHs) by gas-chromatography. Spatial variability of measurements was modelled and mapped using geostatistical methods. The most densely measured covariate (i.e., the ECa of the topsoil) was used within kriging with external drift to improve the PTEs predictions. The PTEs maps were complemented by maps of spatial uncertainty. A robust multivariate principal component analysis (rPCA) was applied to proximal sensor and laboratory data and allowed to identify associations of PAHs, lead, CI with the topsoil ECa along the first component (PC1), highlighting the correlation between land anthropogenic effects and EMI measures; while the association between the ST (estimating the depth of underground travertine hard-layers) and the bottom soil ECa and MSa along the second component (PC2) evidenced the influence of soil stratigraphy on the EMI measures. This study demonstrates that the simultaneous use of different proximal sensors associated with laboratory analysis can allow to assess and model the spatial variability of the land degradation status of an OSR, including soil compaction, organic and inorganic contamination. The correlation between EMI data with the PTEs content highlights the potential of this technique in the field of soil contamination.