# Estimating Tetrachloroethene Sorption Coefficients Based on Soil Properties in Organic-Poor Soils
## 1 Introduction  
The fate of nonpolar hydrophobic organic compounds, such as chlorinated solvents and aromatic hydrocarbons, in subsurface environments is predominantly controlled by their sorptive behavior [1]. Accurately characterizing this behavior is essential for predicting the transport, transformation, and ultimate fate of these compounds within the subsurface, which is crucial for conducting rigorous risk assessments and developing effective remediation strategies [2]. The extent to which a compound associates with solid phases at equilibrium is quantified by the solid-water distribution coefficient (\(K_{\mathrm{d}}\)), which represents the ratio of the compound's equilibrium concentration in the solid phase to its concentration in the aqueous phase [3]. \(K_{\mathrm{d}}\) is a critical parameter that directly influences the modeling of volatile organic compounds' (VOCs) transport in soil and groundwater [4]. Given the inherent complexity of soil as a geosorbent, practical constraints often necessitate limiting the assessment of sorption characteristics to fundamental parameters that can provide reasonable estimates of contaminant behavior. Early studies have highlighted the critical role of the quantity and nature of organic matter in soil in influencing sorption [5; 6; 7], leading to the normalization of sorption coefficients to organic carbon (OC) content [8; 9]. However, the assumption that OC has uniform sorption properties has been challenged by observations such as the nonlinear shape of sorption isotherms [10; 11] or multiphasic desorption kinetics [12]. The \(K_{\mathrm{d}}\) values can be influenced by various factors, including claymineral content and type [13; 14; 15; 16], moisture levels [17; 18; 19], particle size distribution [20], porosity [21; 22], the specific surface area (SSA) of the soil [23], and the presence of salts in soil solutions [24]. For nonpolar hydrophobic organic compounds, the \(K_{\mathrm{d}}\) value is often estimated in practice [25] using the fraction of organic carbon content (\(f_{\mathrm{OC}}\)) and OC-normalized \(K_{\mathrm{d}}\) (\(K_{\mathrm{OC}}\), L kg\({}^{-1}\)) applying the equation \(K_{\mathrm{d}}=K_{\mathrm{OC}}\times f_{\mathrm{OC}}\)[3]. This approach allows for efficient predictions, particularly in cases where detailed site-specific data are unavailable [26]. It is especially useful for rapid assessments, as it bypasses the complex and resource-intensive processes involved in fully characterizing contaminated areas. However, empirically estimated \(K_{\mathrm{d}}\) values are often lower than the experimentally determined ones; and this approach is more accurate for soils with high OC content, where the correlation between OC content and sorption behavior is strong [27]. Conversely, for soils with low OC content, predictions based on \(K_{\mathrm{OC}}\) are less reliable [28]. This reduced reliability stems from the increased influence of other soil properties, such as clay content, whose mineral surfaces play a significant role in physical sorption, which is neglected in these models. As a result, these models are less applicable to low-organic-carbon soils. This inaccuracy can lead to underestimating total contaminant levels in the subsurface, potentially resulting in an underassessment of associated risks [29; 30]. Direct experimental measurements of \(K_{\mathrm{d}}\) values are therefore essential for these soils to manage subsurface contamination precisely [31; 32; 33; 34]. Nevertheless, determining \(K_{\mathrm{d}}\) experimentally presents significant challenges due to the volatility of contaminants, their susceptibility to degradation, and competitive interactions among solutes [35]. Therefore, developing a robust and accurate \(K_{\mathrm{d}}\) prediction methodology for soils with low OC content based on a wider range of soil characteristics would significantly enhance the precision of risk assessments and improve the effectiveness of remediation efforts [36; 37; 38].