PFAS-LEACH analytical model: a graphical tool for evaluating PFAS soil-to-groundwater leaching and site-specific soil screening levels
Min Ma1, Jacob Smith1, Mark L.Brusseau1,2, Bo Guo1,*
1Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ
2Department of Environmental Science, University of Arizona, Tucson, AZ
PFAS-contaminated soils represent persistent sources of groundwater pollution due to their unique retention mechanisms in the vadose zone, particularly adsorption at air–water interfaces. While detailed numerical transport models can explicitly simulate these processes, they require extensive site-characterization data and substantial computational resources, limiting their practicality for screening-level assessments across the large number of PFAS-impacted sites. There is therefore a critical need for computationally efficient analytical tools that adequately capture PFAS-specific transport processes. We present PFAS-LEACH Tier 3-4, an Excel-based analytical tool for simulating PFAS leaching through the vadose zone and deriving site-specific soil screening levels (SSLs). The tool employs analytical solutions that account for advection–dispersion transport, rate-limited solid-phase sorption, and air–water interfacial adsorption, coupled with a groundwater dilution model consistent with the U.S. EPA framework.
PFAS-LEACH Tier 3-4 supports both deterministic and probabilistic analyses, including parameter sensitivity analysis and Monte Carlo uncertainty quantification, with built-in QSPR-based parameter estimation routines to reduce input requirements when site-specific measurements are unavailable. The tool is demonstrated through case studies at two PFAS-impacted military sites: one evaluates model-predicted vadose-zone PFAS mass discharge against field-based estimates, and the other illustrates probabilistic SSL derivation under parameter uncertainty. Results demonstrate that PFAS-LEACH Tier 3-4 produces physically consistent and practical estimates of PFAS leaching behavior, groundwater impacts, and SSLs, supporting risk-based decision-making at contaminated sites.