Groundwater remediation of LNAPLs (Light Non-Aqueous Phase Liquids) has advanced with improved models for multi-phase flow and contaminant transport, essential for mapping out contaminant plumes and formulating remediation plans. While LNAPL models simulate how LNAPL interacts with water, air, and soil, their use is limited by specific site conditions, data access, and expertise level. Geological variations, like confining layers and barriers, must be considered as they affect LNAPL flow.
Accurate subsurface evaluation is pivotal, with LNAPL transmissivity measurement proving superior to traditional monitoring for assessing contamination and predicting remediation systems' efficacy. New refined computational techniques in modeling offer a precise representation of complex interactions between LNAPL, water, and air and pinpoint the boundaries between these fluids and improve parameter estimation through data integration. Moreover, joining geostatistical methods with physical models has made simulations of LNAPL spread more realistic, and the integration with Geographic Information Systems (GIS) enhances the analysis and depiction of contamination over time.
While sophisticated models offer detailed predictions, their utility in practice is contingent on validating assumptions through field data, simplifying model complexities for interpretability, and ensuring stakeholders' comprehension of model outputs. Environmental professionals must navigate the trade-off between model sophistication and operational feasibility, ensuring that the application of such models ultimately serves the goal of effective and sustainable LNAPL remediation.
This abstract advocates the need for regulatory acceptance of LNAPL transmissivity as a closure criterion, and for elaborating on best practices that can bridge the gap between theoretical modeling and field application. By doing so, it furthers our collective capacity for informed decision-making in LNAPL-impacted site management.