Estimating impacts of LCRR's fifth-liter sampling and find-and-fix requirements on large water systems
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作者:
Bradley, Tyler C.
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机构:
Philadelphia Water Dept, Framingham, PA 01701 USA
Drexel Univ, Coll Civil Architectural & Environm Engn, Philadelphia, PA 19104 USAPhiladelphia Water Dept, Framingham, PA 01701 USA
Bradley, Tyler C.
[1
,2
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Masters, Sheldon V.
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机构:
Univ Colorado, Boulder, CO USAPhiladelphia Water Dept, Framingham, PA 01701 USA
Masters, Sheldon V.
[3
]
Bartrand, Timothy A.
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机构:
Environm Sci Policy & Res Inst, Bala Cynwyd, PA USAPhiladelphia Water Dept, Framingham, PA 01701 USA
Bartrand, Timothy A.
[4
]
Sales, Christopher M.
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机构:
Drexel Univ, Coll Civil Architectural & Environm Engn, Philadelphia, PA 19104 USAPhiladelphia Water Dept, Framingham, PA 01701 USA
Sales, Christopher M.
[2
]
机构:
[1] Philadelphia Water Dept, Framingham, PA 01701 USA
[2] Drexel Univ, Coll Civil Architectural & Environm Engn, Philadelphia, PA 19104 USA
[3] Univ Colorado, Boulder, CO USA
[4] Environm Sci Policy & Res Inst, Bala Cynwyd, PA USA
The United States Environmental Protection Agency's (USEPA's) Lead and Copper Rule Revisions (LCRR) introduced many changes to the existing regulation. Two major changes are the change in sample methodology to fifth-liter (L5) sampling for homes with lead service lines and the find-and-fix (FaF) provision following any single home lead action level exceedance. This research proposes a method which estimates L5 lead levels from first-draw (L1) LCR data. Using L1 data along with paired L5-L1 difference data from other systems with similar L1 results, L5 data can be estimated accurately by bootstrapping. Using L1 data from two utilities (DC Water and Utility B) with known L5 data, this method was validated to accurately estimate L5 data. This method was then applied to a third utility (Philadelphia Water Department, PWD) with LCR data without paired L5 results to estimate what it can expect from this sample methodology. This same method was then applied to PWD to estimate the impact that FaF would have on the system by identifying how quickly new, permanent Water Quality Parameter (WQP) sites would have to be added. Under all simulations, PWD eventually would reach the maximum number of required WQP sites. This study demonstrates a data driven method for estimating fifth-liter water lead levels from first-liter water lead data.