Models to predict perfluorooctanesulfonic acid (PFOS) concentrations in livestock based on soil concentrations are essential to guide decisions surrounding food testing and farm management. A key parameter in modeling soil-to-livestock exposure pathways is the plant transfer factor (TF) from soil into forages. Uptake of PFOS and other individual per- and polyfluoroalkyl substances (PFASs) were examined in perennial mixed grasses and legumes on PFAS-contaminated farm fields. In a field plot study, PFOS TFs were similar within each plot over three consecutive years but varied 10-fold among the four plots with mean TFs ranging from 0.026 to 0.27. In a multifarm field survey study, mean PFOS TFs ranged from 0.039 to 0.37. Increasing concentrations of two PFOS precursors in soil were significantly associated with increasing PFOS TFs. These data represent a substantial increase in empirical observations of PFAS TFs for grass-based forages for use in modeling soil-to-livestock exposure scenarios.

Historical application of wastewater treatment sludge (biosolids) has introduced per- and polyfluoroalkyl substances (PFAS) into agricultural systems and led to contamination of crops and livestock. Previous work validated a dynamic exposure and population toxicokinetic (DE_PopTK) modeling approach for estimating perfluorooctane sulfonic acid (PFOS) and perfluorohexane sulfonic acid (PFHxS) concentrations in cattle tissues at sites primarily dominated by water contamination. This work expands the efforts to validate the DE_PopTK model at a self-contained beef farm in Maine with PFAS exposures from feed grown on site where soil is contaminated from historical biosolids applications. The model is also extended to estimate perfluorodecanoic acid (PFDA) exposure and tissue levels. Farm-specific data were obtained to consider farm management practices, spatial variation of PFAS in soil, animal growth, and seasonal and annual variability in estimating daily exposures based on water, feed, and soil intake. A dynamic exposure pattern was observed as cattle accumulated PFAS while consuming feed grown on contaminated land and eliminated it while grazing on non-contaminated pastures. Model-estimated PFOS and PFDA levels in serum and muscle were in good agreement with biomonitoring data collected at the farm over a four-year period to reflect periods of accumulation and depuration, with the percentage error ranging from 16% to 73% when comparing modeled and measured data. Our findings demonstrated that understanding farm exposures and collecting site-specific data were integral to model performance. The model was applied to simulate management strategies and complement economic analyses to demonstrate that, with modifications to management practices, it is feasible for the farm to achieve lower PFOS and PFDA levels in beef and maintain economic viability despite elevated PFAS soil levels.

Background: Soil screening levels (SSLs) are an important guidance tool for identifying sites where exposure to soil contaminants may pose health risks to people residing or working nearby; however, to date, no soil screening levels or default exposure scenario have been established specifically for farmworkers who have frequent, direct soil contact through their typical occupational tasks and behaviors. Objective: We developed an exposure scenario for a vegetable farmworker’s soil exposure. We apply this exposure scenario to derive and compare noncarcinogenic-based soil screening levels for four PFAS commonly detected in soil from farm fields with a history of land application of biosolids in Maine. Methods: We used existing EPA models for incidental soil ingestion and dermal contact, parameterizing model inputs with distributions drawn from the literature to be more representative for farmworkers. We developed an empirical model of the inhalation pathway using literature-reported exposure and time-activity data. We used Monte Carlo simulation to evaluate these models with toxicity values in the EPA Regional Screening Levels database to derive SSLs for the individual and combined pathways and compared these results to soil PFAS levels from a statewide testing program of biosolids-amended farmland. Results: The 5 ^th percentile values from the distribution of combined pathway SSLs were 26, 7.9, 790, and 0.5 ng/g for PFOS, PFOA, PFNA, and PFDA, respectively. Sensitivity analyses identified the incidental soil ingestion rate as the most influential parameter in deriving a SSL for our farmworker scenario. We found overlap for PFOS, PFOA, and PFDA in the distributions of plausible SSLs for a vegetable farmworker scenario and measured soil levels from a statewide testing program. Significance: Our comparison of these farmworker SSLs to more routinely evaluated adult exposure scenarios (residential, outdoor worker, construction worker) indicated that these other scenarios may not be protective of farmworkers. Impact Statement: The farmworker exposure scenario and PFAS soil screening levels we developed are a novel and necessary public health tool for protecting farmworkers from exposure to contaminants in soils and informing risk management decisions for farms and fields amended with biosolids.