Abstract A significant reduction in the costs associated with contamination assessments can be achieved if traditional soil sampling for contaminated-site characterization is complemented by real-time sampling using proximal soil sensors. Real-time sampling using a portable X-ray fluorescence (pXRF) device is a cheap and fast sampling method to provide more data and reduce the time needed to map soil contamination. The main disadvantage of using pXRF is the degree of uncertainty of these in situ measurements due to the technology’s indirect nature, and its sensitivity to soil heterogeneity and soil moisture content. This study evaluates the potential of using both pXRF and traditional soil sampling measurements to accurately map soil contamination due to the presence of heavy metals. The approach proposed uses geostatistical sequential simulation with local probability distributions to characterize and integrate pXRF uncertainty at each sampling location. The resulting maps agree with the contamination map obtained using traditional laboratory data only, in terms of mapping accuracy and extent of contaminated areas. This study shows that with few collocated pXRF and laboratory analytical data it is possible to identify contaminated areas accurately, thus providing a cost-effective solution to work with pXRF data directly.

中文翻译：

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集成便携式 X 射线荧光 (pXRF) 测量不确定度以实现准确的土壤污染绘图

摘要 如果用于污染场地表征的传统土壤采样与使用近端土壤传感器的实时采样相辅相成，则可以显着降低与污染评估相关的成本。使用便携式 X 射线荧光 (pXRF) 设备进行实时采样是一种廉价且快速的采样方法，可提供更多数据并减少绘制土壤污染图所需的时间。使用 pXRF 的主要缺点是由于该技术的间接性质及其对土壤异质性和土壤水分含量的敏感性，这些原位测量的不确定性程度。本研究评估了使用 pXRF 和传统土壤采样测量来准确绘制因存在重金属而导致的土壤污染的潜力。所提出的方法使用具有局部概率分布的地质统计序列模拟来表征和整合每个采样位置的 pXRF 不确定性。由此产生的地图与仅使用传统实验室数据获得的污染地图在绘图准确性和污染区域范围方面一致。该研究表明，只需很少并置的 pXRF 和实验室分析数据，就可以准确识别受污染区域，从而为直接处理 pXRF 数据提供了一种经济高效的解决方案。