Per- and polyfluoroalkyl substances (PFAS) are a large family of chemicals widely used in industrial processes. 3M, one of the major historic PFAS manufacturers, had produced raw materials and PFAS contained products at its Cottage Grove plant in Washington County, Minnesota, for decades. In 2002, the Minnesota Pollution Control Agency (MPCA) and Minnesota Department of Health (MDH) started drinking water investigations near the 3M plant and related legacy waste disposal sites. The long-term investigation has accumulated a large amount of data. In this study, we curated the PFAS monitoring data with other potential factors and trained Bayesian network models to predict PFAS exposure risk in the Minneapolis East Metro area. The model accuracy was assessed using the area under the receiver-operating characteristic curve (AUC), where AUCs range from 0 to 1 and a value of 1 indicates a perfectly accurate model. Furthermore, we evaluated the temporal shift in risk factors according to the mutual information between PFAS exposure risks and explanatory variables. As a result, the trained Bayesian network models successfully predicted the PFOA and PFOS exposure risks in groundwater for five different time slots, with the AUC index ranging from 83.9% to 94.5% in the cross-validation. For PFOA, distances to major pollution sources (the 3M plant and historical dump sites) are the most critical risk factors in the early years. The impact of other pollution sources, such as fire stations, septic systems, and land application sites, became more evident after 2016. For PFOS, the major pollution sources maintained their impacts throughout all time. However, a shift was observed from the 3M plant in the early years to two historical dump sites after 2016. This different observation in PFOA and PFOS risk factors could be further explained by the change of their exposure risks’ spatial pattern over time.

Temporal shift in risk factors for PFOA and PFOS exposure in the Minneapolis East Metro area

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