Journal article
A Novel, Metal-Based Approach to Identify Residences with Lead Service Lines
Environmental science & technology letters, Vol.12(8), pp.918-923
08/12/2025
DOI: 10.1021/acs.estlett.5c00552
Abstract
There is an urgent need for rapid, cost-effective approaches to identify residences with lead service lines (LSLs). We evaluated whether analyzing water for corrosion-related metals could accurately identify residences with LSLs without relying on potentially inaccurate property records. We applied principal component analysis logistic regression (PCA-LR) and classification tree models using 28 analytes per bottle (including Pb, Cu, Zn, Fe, Al, and others) measured in 216 water samples collected in Flint, Michigan, in August 2015. The PCA-LR model achieved 87% accuracy (AUROC = 0.93) with 81% sensitivity and 90% specificity, while the classification tree model achieved 80% accuracy (AUROC = 0.77) with 74% sensitivity and 84% specificity. The classification tree provided interpretable decision rules identifying key predictive metals, primarily relying on 1 min flush Pb concentrations with Zn and Al as secondary predictors. It also revealed distinct metal co-occurrence patterns between LSLs and premise plumbing, offering insights into Pb source identification. The tree’s interpretable structure makes it particularly valuable for practical implementation by utilities. Although additional work is needed to extend these models to other water systems, our results suggest that metal analysis provides an accurate, cost-effective, and minimally invasive tool that complements existing approaches for predicting the presence of an LSL.
Details
- Title: Subtitle
- A Novel, Metal-Based Approach to Identify Residences with Lead Service Lines
- Creators
- Danielle Land - Michigan State UniversityGrant D. Brown - University of Iowa, BiostatisticsDavid M. Cwiertny - University of IowaMarc A. Edwards - Virginia TechMona Hanna - Michigan State UniversityDrew E. Latta - University of IowaMichelle M. Scherer - Michigan Technological University
- Resource Type
- Journal article
- Publication Details
- Environmental science & technology letters, Vol.12(8), pp.918-923
- DOI
- 10.1021/acs.estlett.5c00552
- ISSN
- 2328-8930
- eISSN
- 2328-8930
- Publisher
- American Chemical Society
- Grant note
- U.S. Department of Housing and Urban Development: IAHHU0067-21 U.S. Department of Housing and Urban Development (Healthy Home Technical Studies)
The work that provided the basis for this publication was supported by funding under an award with the U.S. Department of Housing and Urban Development (Healthy Home Technical Studies Grant IAHHU0067-21). The substance and findings of the work are dedicated to the public. The author and publisher are solely responsible for the accuracy of the statements and interpretations contained in this publication. Such interpretations do not necessarily reflect the views of the Government. The authors would like to thank the Virginia Tech Flint Water Study Team for sharing their water data and Jared Webb and BlueConduit for sharing the Flint service line inventory. The authors would like to thank Jonathan Durst, Water Superintendent for the City of Iowa City, for his helpful comments and feedback during the development of this work. We would also like to acknowledge the four anonymous reviewers for their constructive comments that greatly improved this manuscript.
- Language
- English
- Electronic publication date
- 07/30/2025
- Date published
- 08/12/2025
- Academic Unit
- Center for Health Effects of Environmental Contamination; Civil and Environmental Engineering; Biostatistics; IIHR--Hydroscience and Engineering; Chemistry; Chemical and Biochemical Engineering
- Record Identifier
- 9984944724802771
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