Vapor intrusion is the migration of volatile organic compounds (VOCs) from a subsurface source into the indoor air of an overlying building. Vapor intrusion models, including the Johnson and Ettinger (J&E) model, can be used to predict the concentration of VOCs in the indoor air of a building based on a measured subsurface soil gas concentration or contaminant source concentrations, either in non-aqueous phase liquid (NAPL), groundwater, or soil. An analysis of two of the EPA-implemented J&E spreadsheet models, one that considers subsurface soil gas data and one that considers groundwater data, was conducted. The governing equations, assumptions, and limitations of these spreadsheet models were investigated. A value of information (Vol) worksheet was developed that can assist practitioners in deciding what additional data to collect as part of a remedial investigation. The Vol worksheet calculates how varying values of model input parameters affect the model-predicted indoor air carcinogenic risk. The worksheet then compares the user-defined target risk to the range of potential risk values for different combinations of varying parameters. The results of this analysis allow the user to determine which groups of parameters have the most impact on the model results. This information can assist the practitioner in deciding whether or not to collect additional data to reduce the uncertainty in the input parameters. The EPA J&E soil gas and groundwater spreadsheet models, as well as the Vol worksheet developed for each model, were applied to case study data for a trichloroethylene-impacted site in Rhode Island. The results of the J&E model and Vol worksheet analyses for this case study predicted incremental carcinogenic risk values for trichloroethylene (TCE) below the risk value calculated based on measured indoor air data. This comparison suggests the potential for other sources of TCE within the building. Groups of parameters were identified for each model that impacted the model-predicted carcinogenic risk. The development of a cost-benefit analysis, which would be used to quantify the value of obtaining additional data for these critical parameters, is recommended for future research.

This book introduces key concepts in modeling and risk assessments of vapor intrusion, a process by which the subsurface volatile contaminants migrate into the building of concern. Soil vapor intrusion is the major exposure pathway for building occupants to chemicals from the subsurface, and its risk assessments determine the criteria of volatile contaminants in soil/groundwater in brownfield redevelopment. The chapters feature the recent advances in vapor intrusion studies and practices, including analytical and numerical modeling of vapor intrusion, statistical findings of United States Environmental Protection Agency’s Vapor Intrusion Database and Petroleum Vapor Intrusion Databases, the challenges of preferential pathways, and the application of building pressure cycling methods, and field practices of vapor intrusion risk assessments at developed contaminated sites and in brownfield redevelopment. This volume also summarizes the advantages and limits of current applications in vapor intrusion risk assessment, laying the groundwork for future research of better understanding in risk characterization of soil vapor intrusion using models. Written by experts in this field, Vapor Intrusion Simulations and Risk Assessments will serve as an invaluable reference for researchers, regulators, and practitioners, who are interested in perceiving the basic knowledge and current advances in risk assessments of soil vapor intrusion.

Vapor intrusion models were developed to predict indoor air concentrations from subsurface sources and then calculate an associated risk using toxicological data and exposure scenarios for the building occupants. Prior to the issuance of final guidance documents in 2015, the United States Environmental Protection Agency (USEPA) guidance on vapor intrusion was in draft form since November 2002. This delay between the draft version and the final guidelines resulted in the utilization of varying methodologies for assessing vapor intrusion by the regulated community and as well as the regulators at both state and local levels. The purpose of this study was to evaluate the accuracy of screening-level vapor intrusion models, using soil vapor samples collected from three sites with known or suspected contamination, and to compare the predicted indoor air results with measured indoor air results. The models evaluated were the County of San Diego Department of Environmental Health Vapor Risk 2000 Model, the Department of Toxic Substances Control (DTSC) version of the Johnson and Ettinger Model (J&E Model), and the USEPA, Office of Solid Waste and Emergency Response (OSWER), Vapor Intrusion Screening Level Calculator (VISLC). The results of this study found that the Vapor Risk 2000 Model more accurately predicts indoor air concentrations, followed by the J&E Model and VISLC. While the Vapor Risk 2000 Model more closely predicts the indoor air concentration, it does have a tendency to underpredict. Due to the underpredictions, there is more potential for false negatives (i.e., screening out sites that do have a potential for vapor intrusion. Similar to previous studies, this study found the Vapor Risk 2000 and J&E Models both over and under predict the indoor air concentrations. This may not necessarily be a reflection on the model’s prediction ability, but rather the complexity of vapor intrusion and the confounders of indoor air. Combined with additional lines of evidence (e.g., indoor air sampling), these screening-level vapor intrusion models can assist decision makers in screening in or out sites that are susceptible to vapor intrusion.

Vapor intrusion (VI), can pose health risks to building occupants. Assessment and mitigation at VI impacted sites have been guided by a site conceptual model (SCM) in which vapors originate from subsurface sources, diffuse through soil matrix and enter into a building by gas flow across foundation cracks. Alternative VI pathways and groundwater table fluctuations are not often considered. Alternative VI pathways, involving vapor transport along sewer lines and other subsurface infrastructure, have recently been found to be significant contributors to VI impacts at some sites. This study evaluated approaches for identifying and characterizing the significance of alternative VI pathways and assessed the effectiveness of conventional mitigation at a site with an alternative VI pathway that can be manipulated to be on or off. The alternative pathway could not be identified using conventional pathway assessment procedures and can only be discovered under controlled pressure method (CPM) conditions. Measured emission rates were two orders of magnitude greater than screening model estimates and sub-foundation vertical soil gas profiles changed and were no longer consistent with the conventional VI conceptual model when the CPM test was conducted. The pipe flow VI pathway reduced the vacuum performance of the sub-slab depressurization (SSD) VI mitigation system, but the SSD system still provided sufficient protection to the house. The relationship between groundwater table fluctuations and subsurface vapor emissions and transport is examined using multi-year data from the field site, and is studied in the laboratory. In addition, a broader range of conditions is examined through use of modeling validated with the experimental data. The results indicate that fluctuating groundwater tables will lead to amplified volatile organic chemical (VOC) emissions from groundwater to soil surface relative to steady water table elevation, however, the magnitude of this amplification is less concerned when long-term water fluctuation present. No clear correlations were found between VOC emissions and water table changes at the study site where annual water table fluctuations of about 0.3 m existed. Significant VOC emission amplifications by water table fluctuation would be expected under shallow groundwater conditions according to model analysis results.