A local natural background level concept to improve the natural background level: a case study on the drainage basin of the Venetian Lagoon in Northeastern Italy

Conceptual Model of Arsenic Mobility in the Shallow Alluvial Aquifers Near Venice (Italy) Elucidated Through Machine Learning and Geochemical Modeling

“…According to this model, in iron‐rich environments As tends to adsorb onto HFOs, which are precipitated during oxidizing conditions and to desorb from HFOs when these oxides dissolve during reducing conditions (Appelo & Postma, 2005). Previous works on the VAP had already postulated this mechanism (Carraro et al, 2013, 2015; Dalla Libera et al, 2017, 2018), which is commonly adopted when modeling As mobility in several other young aquifers of the world (e.g., Smedley & Kinniburgh, 2013), such as Bengal Basin (Kinniburgh & Smedley, 2001) and the Mekong Valley and Red River aquifers in Vietnam (Berg et al, 2001; Postma et al, 2007) or in Cambodia (Richards et al, 2019). Redox‐controlled As mobility has been also reported in other Italian sites (e.g., Aiuppa et al, 2003; Molinari et al, 2013; Rotiroti et al, 2014; Ungaro et al, 2008).…”

“…We demonstrated the proposed approach to elucidate the main geochemical processes controlling As mobility in the Venetian Alluvial Plain (VAP) near Venice, Italy. The VAP shows geogenic As contamination affecting the local shallow aquifers (Carraro et al, 2013, 2015), leading to complex spatiotemporal variability of concentrations that locally and temporally exceed 10 μg/L (Dalla Libera et al, 2017, 2018, 2016). To date, no documented work has investigated with sufficient detail physical and geochemical processes linked to As mobilization in the shallow aquifers of the VAP, making this a novel contribution for the understanding of As risk in the studied area.…”

Deriving Natural Background Levels of Arsenic at the Meso-Scale Using Site-Specific Datasets: An Unorthodox Method

“…The component separation approach involves the subdivision of the working dataset into normally and log-normally distributed populations, considering the latter as representative of the natural background [8,20,[35][36][37]. The new approaches mentioned above involve the combination of the preselection or component separation methods with geostatistical tools that take into account the actual distribution of the contaminant of concern and its correlation with other environmental parameters (e.g., indicator kriging [21,23,[38][39][40] or object-oriented statistics [24]). These approaches allow for a spatial enhancement of the high-quality information provided by national or regional monitoring networks by producing maps of NBLs or associated probability of exceedance, instead of assigning a single background value or a range of values for the whole groundwater body.…”

Hydrogeochemical Processes and Natural Background Levels of Chromium in an Ultramafic Environment. The Case Study of Vermio Mountain, Western Macedonia, Greece

“…The NBLs are a set of several varying hydrogeological (i.e., the residence time of groundwater in the saturated zone, recharge by precipitation, hydraulic connection with other aquifer systems) [3][4][5], and hydrogeochemical (i.e., water-rock interaction, pH/redox conditions, chemical, and biological processes in the unsaturated zone) [5][6][7] factors. The determination of NBLs requires in-depth knowledge of geological/hydrogeochemical processes [8] and the distinguishment of natural and anthropogenic factors that affect the groundwater systems [9]. The need to separate NBLs from the anthropogenic impacts (e.g., urbanization, industrialization, agricultural activity) is frequently satisfied through statistical and pre-selection (PS) methods [10].…”