RileyÌýMulhern, PhD

  • ENVIRONMENTAL STUDIES
Riley Mulhern headshot

Dr. Mulhern is an Assistant Professor in the department of Environmental Studies where his research focuses on helping people make decisions to reduce environmental health risks. He is particularly interested in understanding how drinking water quality varies across social, demographic, and spatial lines, and the ways in which technology fits within systems of governance and service delivery to combat these disparities. Additional areas of research include private well water quality in the U.S., lead in schools and low-income housing, PFAS, environmental health impacts of mining, and the effectivenessÌýof point-of-use water treatment. Dr. Mulhern is committed to interdisciplinary approaches, using both data science and community engagement, to inform risk management decisions.Ìý

Education

  • PhD – Environmental Sciences and Engineering, University of North Carolina at Chapel Hill
  • MS – Environmental Engineering, Â鶹ÊÓƵ
  • BS – Physics, Wheaton College

Recent Publications

  • Jones, C. H., Mulhern, R. E., Wylie, V., Fawell, J., Oza, S., Holmer, M., & Bell, K. (2025). Quantitative relative chemical assessment to support risk frameworks for water recycling. ES&T Water. In press. https://doi.org/10.1021/acsestwater.4c01140
  • MacDonald Gibson, J., Desclos, A., Harrington, J., Mcelmurry, S. P., & Mulhern, R.(2024). Effect of community water service on lead in drinking water in an environmental justice community. Environmental Science & Technology.
  • Bauza, V., Furey, S., Alvarez-Sala, J., Bartram, J., Danert, K., Jennifer, D. F., Samuel, D., Fisher, M. B., Hansen, D., Hutchings, P., Lindsay, C., Mulhern, R., Norman, R., Ramseier, C., Strandberg, J., Studer, P., & Salzberg, A. (2023). Eliminating lead exposure from drinking water — A global call to action. PLOS Water, 2(4), e0000122.
  • Mulhern, R. E., Kondash, A., Norman, E., Johnson, J., Levine, K., McWilliams, A., Napier, M., Weber, F., Stella, L., Wood, E., Lee Pow Jackson, C., Colley, S., Cajka, J., MacDonald Gibson, J., & Hoponick Redmon, J. (2023). Improved decision making for water lead testing in U.S. child care facilities using machine-learned Bayesian networks. Environmental Science & Technology.