PCB Exposure Modeling and Human Health Risk Assessment for Indoor Air and Dust in School Buildings
Project Overview
RoseyFields performed a technical exposure and risk-assessment project focused on polychlorinated biphenyl (PCB) exposure in school environments, with particular attention to how indoor air, settled dust, soil, and background exposures combine to affect total dose in students and staff. The project centered on EPA’s PCB Exposure Estimation Tool (PEET), a spreadsheet-based modeling framework developed to estimate total PCB exposure in school settings by integrating school-specific exposures with non-school background exposures. Rather than evaluating indoor air concentrations in isolation, the work examined how PCB contamination in multiple media contributes to aggregate dose across inhalation, incidental dust and soil ingestion, dermal absorption from dust, and background dietary exposure. This type of assessment is especially important in legacy school buildings, where PCB-containing caulks, sealants, paints, and other building materials can elevate indoor air and dust concentrations above normal background levels and create long-term exposure concerns for teachers, staff, and students.
The project was designed to answer a practical risk question that arises frequently in school PCB matters: at what indoor air concentration would total PCB exposure in a school population exceed health-protective benchmarks once all other exposure pathways are considered? To answer that question, RoseyFields evaluated the structure and assumptions embedded in PEET, including age-specific body weights, inhalation rates, dust and soil ingestion rates, dermal contact assumptions, time spent indoors and outdoors, school attendance frequency, and background dietary PCB exposure. The tool incorporates both school exposures and background non-school exposures, allowing risk assessors to estimate the fraction of total PCB dose attributable to time spent in school and to determine the maximum indoor school-air concentration that would keep total dose below EPA’s reference dose for Aroclor 1254.
This work illustrates RoseyFields’ approach to forensic exposure reconstruction and health risk assessment in complex indoor contamination cases. Rather than relying solely on screening levels or building-wide exceedance values, the analysis focused on how exposure actually occurs across different routes and how school-specific conditions change total dose. By reviewing the equations, assumptions, and age-stratified outputs in the PEET framework, RoseyFields evaluated how PCB exposure in schools can be quantified in a way that is transparent, reproducible, and directly tied to toxicological benchmarks used in regulatory and litigation settings.
Chemicals of Concern
The principal chemicals of concern were polychlorinated biphenyls (PCBs), a class of persistent chlorinated compounds historically used in electrical equipment, caulks, sealants, coatings, and other building materials. In older schools, PCBs are often associated with legacy construction materials that slowly release PCB congeners into indoor air and settled dust over time. Because these compounds are persistent, lipophilic, and capable of accumulating in indoor environments, school occupants may be exposed not only through inhalation of indoor air, but also through incidental ingestion of contaminated dust or soil and dermal contact with dust on exposed skin.
The PEET framework treats PCB exposure as a multi-pathway problem. For school environments, it includes dust ingestion, soil ingestion, inhalation of indoor and outdoor air, and dermal absorption from dust. For background non-school exposure, it also incorporates dietary ingestion, reflecting the fact that PCBs remain present in the general environment and food supply. These combined pathways are important because they demonstrate that school indoor air is only one component of total PCB dose. Even where the risk question is framed around indoor air contamination, a defensible assessment must account for the contribution of other routes and other environments to overall exposure.
Methods
RoseyFields reviewed EPA’s PCB Exposure Estimation Tool (PEET), Version 2.1, a spreadsheet-based model designed to estimate total PCB dose for different school-age populations. The tool separates exposure into two major components: background (non-school) exposure and school exposure. Background exposure includes dust ingestion, soil ingestion, inhalation of indoor and outdoor air, dermal absorption from dust, and dietary PCB intake from food. School exposure includes dust ingestion, soil ingestion, inhalation of indoor and outdoor air at school, and dermal absorption from school dust. The total PCB dose is then calculated by summing school and non-school contributions and comparing the result to EPA’s oral reference dose for PCB Aroclor 1254.
The PEET model is age-stratified and includes separate calculations for daycare toddlers, preschool children, elementary students, middle-school students, and older groups. Each age band has its own body weight, inhalation rate, dust ingestion rate, soil ingestion rate, exposed skin surface area, and time-activity assumptions. This structure matters because PCB dose per unit body weight can vary substantially by age, particularly when younger children have higher ingestion rates relative to body size and spend large fractions of time indoors where PCB-containing dust may accumulate. By using age-specific exposure factors rather than a single generic school occupant, the tool provides a more refined estimate of how PCB exposure may differ across the school population.
RoseyFields examined the equations used in PEET to calculate dose from each pathway. For dust ingestion, the model estimates average daily dose by multiplying PCB concentration in dust by the dust ingestion rate, the fraction of relevant time spent in school or non-school indoor settings, a unit conversion factor, and a relative absorption factor, then dividing by body weight. A similar approach is used for soil ingestion, with the fraction of outdoor time spent at school or away from school incorporated into the equation. For inhalation, the model estimates dose by combining inhalation rate, indoor or outdoor PCB concentration, the fraction of time spent in each setting, and a relative absorption assumption. Dermal absorption is modeled through contact with dust adhering to exposed skin, again using age-specific adherence and surface-area assumptions.
This pathway-specific structure is important because it allows the user to identify which exposure routes dominate total dose under different scenarios. In the default PEET example calculations, background dietary exposure and non-school indoor air inhalation contribute a large share of total PCB dose, while school indoor-air inhalation becomes the dominant school-specific pathway when indoor school air concentrations are elevated. Dust ingestion and dermal absorption contribute smaller but still meaningful fractions, particularly for younger age groups. That framework is useful in litigation and regulatory work because it shows whether a school contamination problem is being driven primarily by inhalation, by contaminated dust, or by a combination of multiple routes.
RoseyFields also evaluated the default assumptions and background concentrations embedded in the tool. PEET uses representative background concentrations for dust, soil, indoor air, and outdoor air, along with age-specific dietary PCB doses derived from FDA Total Diet Study information. The version reviewed here uses example background concentrations of 0.27 µg/g in dust, 0.06 µg/g in soil, 6.7 ng/m³ in non-school indoor air, and 0.53 ng/m³ in outdoor air. These values are combined with age-specific inhalation rates, body weights, and school attendance assumptions to estimate total background and school-related dose.
The tool also assumes that doses from the different pathways are normalized to a basis comparable to oral exposure so they can be evaluated against EPA’s oral reference dose for Aroclor 1254. Relative absorption factors are therefore used to convert inhalation, dust ingestion, soil ingestion, and dermal contact into dose estimates that can be summed consistently. This type of route-to-route normalization is a critical feature of the model because the risk question is not whether one pathway exceeds a standalone threshold, but whether the combined daily absorbed dose exceeds a health-protective benchmark.
A key function of the PEET framework is its ability to isolate the portion of total PCB dose attributable specifically to the school environment. RoseyFields reviewed the tool’s Total Exposure tab, which summarizes both background and school doses by pathway and age group and reports the fraction of total dose attributable to school exposures. In the default example scenario, school exposure accounts for a smaller fraction of total PCB dose than background non-school exposure because the default school concentrations are set equal to background concentrations. Even so, the tool provides a direct mechanism for increasing school indoor-air or dust concentrations to reflect actual sampling data and then recalculating the resulting school contribution to total dose.
This feature is particularly useful in school PCB cases because it allows the analyst to move beyond a simple “screening level exceeded” conclusion and instead quantify how much the contaminated school environment increases a child’s or staff member’s daily PCB dose above normal background exposure. That distinction matters in both litigation and risk communication. A school with elevated indoor air may not merely represent a localized exceedance; it may materially increase total absorbed PCB dose relative to what a child or employee would otherwise experience at home and in the broader environment.
RoseyFields also reviewed one of the most practical outputs of the PEET model: the calculation of the maximum PCB concentration in school indoor air that would not cause total exposure to exceed the reference dose, assuming all other exposure pathways remain unchanged. The tool derives this value by subtracting total estimated dose from the reference dose, adding back the current school indoor-air inhalation contribution, and converting the remaining allowable dose into an equivalent indoor-air concentration based on inhalation rate, body weight, time spent in school, and relative absorption assumptions.
In the PEET default example, the resulting maximum indoor-air concentration varies by age group, with younger children generally having lower allowable school-air concentrations because their total dose per unit body weight is higher. This type of calculation is extremely valuable in forensic and regulatory settings because it translates a complex multi-pathway exposure model into a practical risk-management output: a school-air concentration that can be compared to measured indoor-air data, used to evaluate remediation goals, or incorporated into expert testimony regarding whether a school’s PCB levels are consistent with health-protective occupancy.
Results and Technical Findings
The project demonstrated that PCB exposure in schools must be evaluated as an aggregate, multi-pathway exposure problem rather than a single indoor-air measurement problem. The PEET framework makes clear that total PCB dose is driven by a combination of background and school-specific exposures, including dust ingestion, soil ingestion, inhalation, dermal contact, and diet. Even when the school environment is the focus of concern, the risk benchmark is applied to total dose, not merely to the school-air contribution in isolation. This is a critical point in school PCB matters because it means that health-protective indoor-air targets must account for the fact that children and staff are already exposed to PCBs through other routes outside of school.
The analysis also showed that indoor air inhalation is often a dominant school-specific pathway, but not the only pathway that matters. The PEET equations explicitly include dust ingestion and dermal absorption from dust, recognizing that PCB-containing building materials can contaminate not only indoor air but also settled dust on classroom and office surfaces. For younger children in particular, dust ingestion can be a nontrivial contributor to school-related dose because of age-specific hand-to-mouth behavior and lower body weight. The model therefore supports a more realistic view of school PCB exposure than a framework that evaluates air concentrations alone.
A third key finding is that allowable indoor-air concentrations are highly age dependent. Because the tool uses age-specific body weights, inhalation rates, dust ingestion rates, and time-activity patterns, the indoor-air concentration that can be tolerated without exceeding EPA’s reference dose is lower for younger children than for older students or adults. This is an important consideration in schools serving mixed age groups or in litigation involving child versus adult exposures. It means that the same measured indoor-air concentration may imply different levels of concern depending on who occupies the building and how long they spend there.
Finally, the project highlights the usefulness of PEET as a forensic risk-assessment tool rather than simply a regulatory spreadsheet. By adjusting school-specific concentrations and exposure assumptions, the model can be used to estimate dose for a particular school, age group, or occupancy pattern; identify which pathways drive risk; and evaluate whether measured indoor-air concentrations are compatible with health-protective exposure levels once background dose is taken into account. In other words, it provides a bridge between environmental sampling data and individualized risk conclusions.
Conclusions
This project illustrates RoseyFields’ ability to conduct technical PCB exposure modeling and human-health risk assessment for indoor environmental contamination in schools. By evaluating EPA’s PCB Exposure Estimation Tool and the assumptions underlying its dose calculations, RoseyFields examined how PCB contamination in indoor air, dust, and other media translates into aggregate exposure for school occupants across multiple pathways. The work demonstrates the importance of integrating background exposure, age-specific activity patterns, and route-specific absorption into a defensible estimate of total PCB dose rather than focusing on indoor air alone.
The project also reflects a broader strength in forensic exposure reconstruction. In school PCB matters, the central question is often not simply whether PCBs were detected, but whether the concentrations and occupancy patterns were sufficient to increase total dose above health-protective thresholds. Answering that question requires a model that accounts for multiple exposure routes, different age groups, and the contribution of both school and non-school environments. RoseyFields’ review of PEET shows how those factors can be combined into a practical and scientifically grounded framework for evaluating PCB risk in occupied school buildings.
More broadly, this work is representative of RoseyFields’ experience in occupational and indoor environmental exposure assessment, particularly where legacy contaminants in buildings require integration of environmental sampling, toxicology, exposure modeling, and risk interpretation. Whether the setting is a school, office, residential building, or industrial facility, RoseyFields can evaluate how contaminants move through indoor environments, how people are exposed, and whether those exposures are consistent with accepted health-protective benchmarks.
Dr. Paul Rosenfeld led the technical evaluation of PCB exposure modeling and risk-assessment methodology for this matter, applying environmental exposure science, toxicology, and regulatory risk-assessment principles to assess how PCB concentrations in indoor air, dust, soil, and background media contribute to total dose in school occupants. His work focused on integrating pathway-specific dose calculations, age-specific exposure assumptions, and health-protective benchmarks into a defensible framework for evaluating PCB risks in occupied school buildings. The project reflects Dr. Rosenfeld’s broader expertise in indoor environmental contamination, exposure modeling, and forensic human-health risk assessment for legacy contaminants in schools and other occupied structures.
References
U.S. Environmental Protection Agency. (2020, January 16). PCB Exposure Estimation Tool (PEET), Version 2.1.
U.S. Environmental Protection Agency. Integrated Risk Information System (IRIS). Aroclor 1254 reference dose information.
U.S. Food and Drug Administration. Total Diet Study PCB dietary exposure data (as incorporated into PEET Version 2.1).