Rapid assessment of smelter/mining soil contamination via portable X-ray fluorescence spectrometry and indicator kriging

Industrial pollution is a worldwide problem, especially near mining/smelter sites where toxic metals tend to accumulate in soils, sediments, and water. These elements pose a risk both for humans and other organisms' health. In Eastern Europe, assessment of toxic elements such as Pb, Cu, Zn, and others remain challenging because traditional methods are costly and time consuming due to sample collection, chemical digestion, and quantification in laboratories. To reduce these limitations, new assessment methods are needed for deployment in impacted areas. The study conducted herein is the first of its kind to combine portable X-ray fluorescence (PXRF) spectrometry with non-parametric indicator kriging for rapid soil pollution hotspot mapping in Eastern Europe. PXRF was used to assess As, Cu, Cr, Mn, Pb, Zn, and V at 131 georeferenced points (121 impacted; 10 control) in and around the city of Baia Mare, Romania. For spatial variability analysis, ordinary kriging interpolation was used to predict elemental levels in unsampled locations. Pb exceeded the action limit in 91.09% of the area, followed by As (81.20%), Cu (41.52%), Zn (26.69%), and Cr (5.58%). Indicator kriging was then used to estimate the probabilities of data exceeding certain threshold levels. As a result, the pollution hotspots were quickly identified. The highest estimated probabilities of surpassing the Romanian action limits were found around the smelting plant and dispersal stack. Results indicated a likelihood of exceeding action limits of 75% for Cu and between 50 and 75% for Zn. A major portion of the study area showed high probabilities for As and Pb surpassing the Romanian action limits by 75%. Summarily, the PXRF/indicator kriging approach proved effective at rapidly assessing the potential of metal-laden soils to exceed government mandated limits. Using this approach, other cities impacted by similar operations can quickly and cost effectively map areas of concern.