Characterization of Lead Leaching in Drinking Water Distribution Systems Relative to Water Age and Water Quality Parameters

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Title: Characterization of Lead Leaching in Drinking Water Distribution Systems Relative to Water Age and Water Quality Parameters
Author: Wang, Zheng Ming Michael
Advisors: Allen C. Chao, Committee Co-Chair
M. Shamimur Rahman, Committee Member
Ranji S. Ranjithan, Committee Member
Hugh A. Devine, Committee Co-Chair
Abstract: Lead (Pb) leaching has occurred in the water distribution systems (WDSs) of many cities and towns in the United States. This heavy metal can dissolve in drinking water from lead pipes, lead solders and lead-containing plumbing fixtures. Exposure to lead can be seriously hazardous to human health, especially to children. While the treated water from water treatment plants does not generally contain lead, physical and chemical conditions in WDSs may cause lead to leach into the drinking water. Although the seriousness of lead corrosion in drinking water has long been recognized and researchers have analyzed the chemical causes of lead leaching, the use of computer water quality models combined with water quality parameters to analyze spatial locations and areas where lead leaching may occur has not been detailed. This study characterizes water age and its influence on water quality; especially lead leaching, in WDSs. The goal is for water utility managers and operators to efficiently target areas prone to lead leaching in WDSs. The approach has three components, (1) calculating water ages utilizing a computer water quality model, (2) analyzing spatially distributed water age and lead occurrence levels, and (3) evaluating the influences of other routinely monitored water quality parameters on lead leaching in water distribution systems. A water quality model is a model that is upgraded from an existing hydraulic trunk-main model using geographic information systems (GIS) about the WDSs. The results used in this study were calculated from the water quality models that are allowed by the United States Environmental Protection Agency (US EPA) to be applied in evaluating water quality in water distribution systems. The qualifications are determined and outlined by the US EPA for the initial distribution system evaluation (IDSE) from the recently promulgated Stage 2 Disinfection and Disinfectant Byproduct Rule (EPA, 2006). We then calculated the water age using the GIS-assisted water quality model. Based on recent occurrences of lead leaching in several local utilities in North Carolina, we hypothesized that the lead leaching may correlate to the hydraulic residence time. We combined the calculated water age and water quality parameters sampled in water distribution systems utilizing spatial analysis tools in GIS. We geo-coded these data and spatially joined them based on street addresses. Matrices were generated for spatial database analyses to map the lead levels versus the building ages, and the water age, one of the results from the water quality model simulation. We tested the hypothesis using the data from three water utilities in North Carolina. Some of these data were gathered for compliance with the US EPA Lead and Copper Rule, and others for preventive measuring. We analyzed approximately 400 samples. To aid the test of the hypothesis, we evaluated the other water quality parameters and their influence to lead leaching. These consisted of pH, HPC, and nitrate measures, all of which are routinely monitored by water utilities. All of the analysis components use the spatial and water measurement data that are readily available to most utilities. The approach developed in this study can also be used to analyze other pollutants that may be regulated under the US EPA Safe Drinking Water Act in the future. Overlay of derived GIS maps, including water quality model simulation results, lead sampling data, and other routinely monitored water quality parameters will allow utility managers to target lead sample sites and allocate their scarce resources more efficiently to alleviate the problems.
Date: 2007-07-31
Degree: PhD
Discipline: Civil Engineering

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