Determination of geochemical background/baseline values in a biogeochemical province (a case study of the Lori region, Armenia)

The geochemical background/baseline is a key parameter for assessing environmental contamination and identifying potential risks to ecosystems and human health. However, the determination of these values requires careful handling of geochemical data. In practice, the geochemical background of chemical elements can be determined by both empirical and geostatistical methods. In addition, depending on the sampling scale and the area's natural landscape-geochemical characteristics, especially in biogeochemical provinces, the use of a single approach can lead to bias. Therefore, combining both approaches and incorporating several methods of geochemical data processing and spatial clustering is needed to unveil the hidden patterns and delineate representative areas, where separate processes and factors (natural and anthropogenic) condition the contents and distribution of chemical elements. In addition, adding auxiliary information related to the geological setting, soil types and potential sources of contamination can ensure the refinement of the data processing and increase the reliability of the estimated background/baseline values. This study aims to determine the geochemical background/baseline of arsenic (As) in the Lori region (Armenia) by dividing the soil data set into homogeneous subsamples using an algorithm combining data transformation, hot spot analysis (Local Moran I), univariate outlier detection and concept of normal distribution. The results of the study showed that the application of the Local Moran I index allows to identify clusters of samples (of high-high (HH) values, low-low (LL) values and not-significant (NS) values) that have a clear spatial separation. The boxplots of the As contents in the identified subsamples showed that outliers and extreme values are presented. After the elimination of these values, normal distribution was confirmed (Shapiro-Wilk test). The median value of As was 13 mg/kg, 16 mg/kg and 24 mg/kg for LL, NS and HH values, respectively. Meanwhile, the 95 percentile of the LL and NS values were 16 mg/kg and 21.4 mg/kg, respectively. The cluster of HH values spatially covers an area known for its natural mineralization, mining sites and Cu smelter, implying some level of anthropogenic quantities of As which is superimposed on the natural contents. Therefore, the estimated value for this area can be considered as a geochemical baseline rather than a geochemical background. The results of this study showed that in the case of biogeochemical provinces where natural mineralization and anthropogenic activities are presented, several background/baseline values can be determined. The algorithm proposed in this study can be used for other elements and serve as a justified approach to separate homogeneous subsamples and delineate areas for the application of these reference values.