Lithium battery supply chain and waste, and lithium and per- and polyfluoroalkyl substances in drinking water in the United States
- 1Department of Public Health Sciences, Thompson School of Social Work and Public Health, University of Hawaiʻi at Mānoa, Honolulu, HI, USA
Abstract
Rechargeable lithium-ion batteries (LiBs) are central to the clean energy transition, but their production, use, and disposal may introduce contaminants into drinking water systems. Using U.S. EPA Fifth Unregulated Contaminant Monitoring Rule (UCMR5) data, we evaluated whether ZIP codes with LiB waste activity or LiB facilities had higher lithium or per- and polyfluoroalkyl substance (PFAS) burdens in drinking water. LiB waste activity was identified from the 2023 EPA Biennial Hazardous Waste Report, and LiB facilities were identified from the NAATBatt Lithium-Ion Battery Supply Chain Database. Among 17,860 ZIP codes, 254 had LiB waste activity and 633 had at least one LiB facility. In adjusted conventional regression models, waste presence (β = −0.464, 95% CI: −0.919, −0.010) and facility presence (β = −0.491, 95% CI: −0.786, −0.196) were inversely associated with lithium concentrations, but these associations were attenuated and no longer statistically significant in spatial-error models. PFAS findings were mixed. Waste presence was not associated with summed PFAS concentration (β = −0.051, 95% CI: −0.175, 0.073), while shipped waste tonnage showed a borderline positive association (β = 0.259, 95% CI: 0.000, 0.518) that was attenuated after spatial adjustment. In spatial-error models, facility presence (β = 0.067, 95% CI: 0.015, 0.120) and facility count (β = 0.086, 95% CI: 0.026, 0.146) were positively associated with summed PFAS concentration. Overall, associations were sensitive to spatial dependence and varied across LiB indicators. These exploratory findings do not establish that LiB activities caused PFAS contamination but suggest that LiB facility locations warrant further investigation as indicators of industrial environments with elevated or more complex PFAS contamination.
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BibTeX
@article{li2026lithium,
title = {{Lithium battery supply chain and waste, and lithium and per- and polyfluoroalkyl substances in drinking water in the United States}},
author = {Shiwen Li and Eryn Uemori},
journal = {Ecotoxicology and environmental safety},
year = {2026},
month = oct,
doi = {10.1016/j.ecoenv.2026.120991},
url = {https://doi.org/10.1016/j.ecoenv.2026.120991},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Lithium battery supply chain and waste, and lithium and per- and polyfluoroalkyl substances in drinking water in the United States
AU - Shiwen Li
AU - Eryn Uemori
PY - 2026
DA - 2026/10/28
JO - Ecotoxicology and environmental safety
DO - 10.1016/j.ecoenv.2026.120991
UR - https://doi.org/10.1016/j.ecoenv.2026.120991
AB - Rechargeable lithium-ion batteries (LiBs) are central to the clean energy transition, but their production, use, and disposal may introduce contaminants into drinking water systems. Using U.S. EPA Fifth Unregulated Contaminant Monitoring Rule (UCMR5) data, we evaluated whether ZIP codes with LiB waste activity or LiB facilities had higher lithium or per- and polyfluoroalkyl substance (PFAS) burdens in drinking water. LiB waste activity was identified from the 2023 EPA Biennial Hazardous Waste Report, and LiB facilities were identified from the NAATBatt Lithium-Ion Battery Supply Chain Database. Among 17,860 ZIP codes, 254 had LiB waste activity and 633 had at least one LiB facility. In adjusted conventional regression models, waste presence (β = −0.464, 95% CI: −0.919, −0.010) and facility presence (β = −0.491, 95% CI: −0.786, −0.196) were inversely associated with lithium concentrations, but these associations were attenuated and no longer statistically significant in spatial-error models. PFAS findings were mixed. Waste presence was not associated with summed PFAS concentration (β = −0.051, 95% CI: −0.175, 0.073), while shipped waste tonnage showed a borderline positive association (β = 0.259, 95% CI: 0.000, 0.518) that was attenuated after spatial adjustment. In spatial-error models, facility presence (β = 0.067, 95% CI: 0.015, 0.120) and facility count (β = 0.086, 95% CI: 0.026, 0.146) were positively associated with summed PFAS concentration. Overall, associations were sensitive to spatial dependence and varied across LiB indicators. These exploratory findings do not establish that LiB activities caused PFAS contamination but suggest that LiB facility locations warrant further investigation as indicators of industrial environments with elevated or more complex PFAS contamination.
SN - 0147-6513
SN - 1090-2414
ER -