Inherent variability in lead and copper collected during standardized sampling

Masters, Sheldon; Parks, Jeffrey; Atassi, Amrou; Edwards, Marc

doi:10.1007/s10661-016-5182-x

Cited by 27 publications

(37 citation statements)

References 58 publications

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“…11 However, the amount of Pb (as well as Cu and other elements) found in an individual tap varies over time due to several parameters such as variation in the constitution of plumbing materials, plumbing age, water quality, sampling procedure (e.g., water stagnation time, and flow rate during sampling), water use, and temperature. 12,13 Studies involving elemental analysis of school drinking water have been carried out in the United States, 2,14,15 Canada 16,17 and Saudi Arabia, 18 however, most of them focused on just Cu and Pb, or Pb alone. In one of these studies, concentrations of Al, Cd, Cu, Fe, Ni and Zn in school water coolers in Saudi Arabia were found to exceed the guideline values set by the European Economic Community.…”

Section: Introductionmentioning

confidence: 99%

Trace Element Analysis, Model-Based Clustering and Flushing to Prevent Drinking Water Contamination in Public Schools

Carter¹,

Jones²,

Donati³

2018

J. Braz. Chem. Soc.

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Drinking water samples taken from cafeteria sinks and water fountains in each of the 76 schools in the Winston-Salem/Forsyth County Schools (WSFCS) district (North Carolina, United States) were analyzed by inductively coupled plasma tandem mass spectrometry (ICP-MS/MS) to determine As, Cd, Cr, Cu, Pb, Sb, Se and Tl. All samples from currently active schools tested below the maximum contaminant level (MCL) set for each element. Model-based clustering was employed to identify schools more prone to drinking water contamination. This multivariate approach may be used in a prevention program that can be tailored to specific school districts, with each school tested at a frequency compatible with its contamination risk level. Water flow stagnation during the summer break results in higher elemental concentrations in school drinking water, but a simple 5-60 min flushing procedure significantly reduces the contamination levels.

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Section: Introductionmentioning

confidence: 99%

Trace Element Analysis, Model-Based Clustering and Flushing to Prevent Drinking Water Contamination in Public Schools

Carter¹,

Jones²,

Donati³

2018

J. Braz. Chem. Soc.

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“…Consistent with typical levels of copper in new pipes with time [ 48 ], average total copper levels were initially 0.66 ± 0.21 mg/L after 2 weeks of aging, but decreased to 0.35 ± 0.10 mg/L by week 9. Variability in copper release was fairly high, as is characteristic in new pipes [ 49 , 50 ], with CVs of 32.2% during week 2 and 30.4% during week 9. This could be due to differential aging rates in individual pipes or differential release of pipe scale during the sampling procedure.…”

Section: Resultsmentioning

confidence: 99%

Replicable simulation of distal hot water premise plumbing using convectively-mixed pipe reactors

et al. 2020

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A lack of replicable test systems that realistically simulate hot water premise plumbing conditions at the laboratory-scale is an obstacle to identifying key factors that support growth of opportunistic pathogens (OPs) and opportunities to stem disease transmission. Here we developed the convectively-mixed pipe reactor (CMPR) as a simple reproducible system, consisting of off-the-shelf plumbing materials, that self-mixes through natural convective currents and enables testing of multiple, replicated, and realistic premise plumbing conditions in parallel. A 10-week validation study was conducted, comparing three pipe materials (PVC, PVC-copper, and PVC-iron; n = 18 each) to stagnant control pipes without convective mixing (n = 3 each). Replicate CMPRs were found to yield consistent water chemistry as a function of pipe material, with differences becoming less discernable by week 9. Temperature, an overarching factor known to control OP growth, was consistently maintained across all 54 CMPRs, with a coefficient of variation <2%. Dissolved oxygen (DO) remained lower in PVC-iron (1.96 ± 0.29 mg/L) than in PVC (5.71 ± 0.22 mg/L) or PVC-copper (5.90 ± 0.38 mg/L) CMPRs as expected due to corrosion. Further, DO in PVC-iron CMPRs was 33% of that observed in corresponding stagnant pipes (6.03 ± 0.33 mg/L), demonstrating the important role of internal convective mixing in stimulating corrosion and microbiological respiration. 16S rRNA gene amplicon sequencing indicated that both bulk water (P adonis = 0.001, R 2 = 0.222, P betadis = 0.785) and biofilm (P adonis = 0.001, R 2 = 0.119, P betadis = 0.827) microbial communities differed between CMPR versus stagnant pipes, consistent with creation of a distinct ecological niche. Overall, CMPRs can provide a more realistic simulation of certain aspects of premise plumbing than reactors commonly applied in prior research, at a fraction of the cost, space, and water demand of large pilot-scale rigs.

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“…However, lead release is dependent not only on stagnation time. The variability in premise plumbing materials and construction can result in unpredictable spikes of lead due to the semirandom release of particulate lead (Masters, Parks, Atassi, & Edwards, 2016;Sandvig et al, 2008;Schock, 1989). Compared with paired 6-h stagnation, higher lead concentrations in some random daytime and 30-min stagnation samples may indicate a sporadic but significant contribution of particulate lead from the premise plumbing; brass fixtures or faucets and lead-tin solder are possible sources in this case (Deshommes, Laroche, Nour, Cartier, & Prévost, 2010;Elfland et al, 2010;Lytle & Schock, 1996;Parks, Pieper, Katner, Tang, & Edwards, 2018;Sundberg, Holm, Hertzman, Hutchinson, & Lindh-Ulmgren, 2003;Triantafyllidou et al, 2007;Zhang & Edwards, 2011;Figure 3).…”

Section: Lead Release May Be Sporadic and Unpredictablementioning

confidence: 99%

Potential regulatory implications of Health Canada's new lead guideline

et al. 2020

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Health Canada's guideline for lead in drinking water was updated in March 2019. Two new sampling protocols were introduced—random daytime and 30‐min stagnation sampling—and the maximum acceptable concentration (MAC) of lead in drinking water was decreased from 10 to 5 μg/L. This study examined the possible impacts that changes in the guideline might have on water utilities in Canada. A lead‐monitoring survey of seven drinking water distribution systems was conducted using the random daytime and 30‐min stagnation protocols. Random daytime sampling captured an estimated 45% more lead than 30‐min stagnation sampling. However, both protocols yielded samples above the new MAC: 7.5% and 5.4% of random daytime and 30‐min stagnation samples, respectively, exceeded it. These data indicate that some drinking water providers—especially those supplying systems with legacy lead plumbing—may have difficulty achieving 100% compliance with the new guideline.

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Inherent variability in lead and copper collected during standardized sampling

Cited by 27 publications

References 58 publications

Trace Element Analysis, Model-Based Clustering and Flushing to Prevent Drinking Water Contamination in Public Schools

Trace Element Analysis, Model-Based Clustering and Flushing to Prevent Drinking Water Contamination in Public Schools

Replicable simulation of distal hot water premise plumbing using convectively-mixed pipe reactors

Potential regulatory implications of Health Canada's new lead guideline

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