That finding comes from a team led by Ju-Hyeok Kwon and Byong-Hun Jeon at Hanyang University, working with colleagues at institutions across South Korea and the United States, in a study published in the journal Environmental Geochemistry and Health. The researchers set out to compare two of the most influential health risk assessment frameworks applied to fluoride-contaminated land: the United States Environmental Protection Agency’s Risk Assessment Guidance for Superfund, known as RAGS, and South Korea’s own soil-contamination risk assessment guidelines, abbreviated KRAG. Their motivation was practical. South Korea applies a residential soil fluoride standard of 800 milligrams per kilogram, but in some regions fluoride levels are elevated naturally, by geology rather than industry, and it has been unclear how those soil concentrations translate into actual health risk when people are exposed not just through soil but through drinking water and food grown in contaminated ground.

The core problem the study addresses is what risk assessors call multimedia exposure. A regulatory standard written for soil implicitly assumes that soil is the main pathway by which a contaminant reaches the human body, through accidental ingestion of dust and dirt, inhalation of particles, and skin contact. Fluoride does not respect that boundary. It dissolves into groundwater that supplies wells, and it is taken up by crops, accumulating in rice, vegetables, and other staples. Previous studies in India’s Punjab and West Bengal regions, in Iran’s Isfahan province, and in China’s northwest have documented that crop and water intake can dominate total fluoride exposure in affected communities. A soil-only standard, in other words, may capture only a slice of the real dose, and the slice it captures depends heavily on the mathematical assumptions baked into the assessment framework.

To test how much those assumptions matter, the researchers constructed exposure scenarios spanning realistic contamination ranges: soil fluoride concentrations from 200 to 4,000 milligrams per kilogram, water concentrations from 0.5 to 2.5 milligrams per liter, and crop concentrations from 5 to 40 milligrams per kilogram. They then ran these scenarios through both frameworks, calculating a metric called the hazard index, or HI, which compares estimated fluoride intake against a reference dose considered safe. An HI above one signals potential non-cancer health effects, such as dental or skeletal fluorosis. The two frameworks differ in the parameters they assign to exposure, including how much soil children are assumed to swallow, how much water different age groups drink relative to their body weight, and how exposure frequency and duration are defined. Those parameter differences, the study shows, are enough to change the risk verdict entirely.

The results were striking. Under the U.S. EPA’s RAGS framework, children exhibited the highest hazard index for fluoride, reaching a value of 9.116 in the most demanding scenarios, well above the threshold of concern. This reflects a well-known feature of child exposure: children eat and drink more per unit of body weight than adults, and their habits, hand-to-mouth contact, playing in dirt, put them in closer contact with contaminated soil and dust. But when the same scenarios were evaluated under the Korean KRAG guidelines, the hazard index estimates came out lower, and in some scenarios the framework produced a counterintuitive result: children appeared to face lower calculated risk than adults. For a regulatory tool whose purpose is to protect the most vulnerable, that inversion is a red flag, and the authors treat it as evidence that KRAG’s parameterization may understate child-specific exposure through water and food.

To understand exactly where the two frameworks diverge, the team turned to an increasingly popular tool in environmental science: explainable machine learning. Rather than using algorithms as a black box to predict risk, they applied explainable artificial intelligence to dissect the calculations themselves, identifying which input parameters drove the discrepancies between RAGS and KRAG estimates. The analysis pinpointed the parameterization inconsistencies, the differing assumptions about intake rates, body weights, and exposure pathways, that produced the divergent outcomes. This kind of forensic use of explainable AI is part of a broader trend; other recent studies have used machine learning to predict high-fluoride groundwater across the Yellow River Basin and elsewhere. Here, the technique serves a regulatory purpose, showing guideline developers precisely which knobs in the risk equation matter most and where refinement would be most consequential.

As a bridge between the two systems, the researchers proposed a modified approach they call RAGS-K, which applies Korean exposure parameters within the RAGS calculation structure. Under the examined scenarios, RAGS-K yielded higher hazard index estimates than KRAG, suggesting that the Korean framework’s lower estimates stem less from its calculation architecture than from the specific parameter values it assigns. The hybrid also preserved the multimedia structure of RAGS, which explicitly accounts for water and crop intake alongside soil and dust. The implication is that a country can adopt a more complete, child-protective risk calculation without wholesale adoption of foreign guidance; the parameters can be localized while the structure captures all relevant exposure routes.

Perhaps the most consequential finding is about where the risk actually comes from. Across the scenarios, intake from water and crops dominated the calculated child risk and was the main driver of the gap between adult and child hazard estimates. Soil ingestion, the pathway that soil standards are built around, played a comparatively minor role. That means a child drinking fluoride-rich well water and eating vegetables from a contaminated garden may exceed safe intake thresholds even where soil fluoride sits comfortably below the 800 milligram per kilogram regulatory limit. Conversely, remediating soil alone may do little to reduce total exposure if the water and food pathways remain open. The authors argue this supports a shift toward media-integrated risk assessment and management, in which soil, water, and agricultural pathways are evaluated together rather than by separate regulatory silos.

The study arrives amid a growing global literature on fluoride risk. Reviews have catalogued the mechanisms of fluoride toxicity, from enamel mottling to skeletal fluorosis, and field studies in Ethiopia’s Rift Valley have linked groundwater fluoride to dental fluorosis in children, measured through urinary fluoride levels. Remediation research, from granular ferric hydroxide filters to zirconium oxide-impregnated chitosan beads and electrokinetic soil treatment, offers engineering tools for contaminated sites. What has been missing, the Korean team contends, is a rigorous comparison of the regulatory lenses through which those risks are judged. Their work provides exactly that, and its message travels well beyond Korea. Any nation drafting or revising soil standards for fluoride, or for contaminants with similar multimedia behavior, faces the same structural question: a standard calibrated to one exposure pathway, with one set of behavioral assumptions, may silently misjudge risk when the real exposure comes from the dinner table and the kitchen tap. For the children of fluoride-endemic regions, the difference between frameworks is not a matter of statistical nuance. It may be the difference between a risk that is flagged and one that is missed.

Subject of Research: Comparative health risk assessment of fluoride-contaminated soil, water, and food using U.S. EPA and Korean regulatory frameworks

Article Title: Comparative evaluation of regulatory health risk assessment frameworks for fluoride-contaminated environments

Article References: Kwon, J.-H., Choi, K.-W., Park, W.-M., Cho, D.-W., Kumar, R., Lee, S., Choi, J., Chang, S. W., Kim, K.-Y., Ahn, Y., & Jeon, B.-H. (2026). Comparative evaluation of regulatory health risk assessment frameworks for fluoride-contaminated environments. Environmental Geochemistry and Health, 48(14), Article 580. https://doi.org/10.1007/s10653-026-03475-3

Image Credits: AI Generated

DOI: 10.1007/s10653-026-03475-3

Keywords: fluoride, soil contamination, health risk assessment, RAGS, KRAG, hazard index, groundwater, multimedia exposure, explainable machine learning, children's health, South Korea, environmental regulation