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An Analysis of Spatial Variability in Disinfection By-Product Concentrations for Exposure Assessment Applications

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Many epidemiological studies of disinfection by-products (DBPs) rely on aggregatewater system average trihalomethane (i.e., THM4: sum of chloroform, dibromochloromethane, bromodichloromethane and bromoform) and haloacetic acid (i.e., HAA5: sum of monochloroacetic acid, dichloroacetic acid, trichloroacetic acid, monobromoacetic acid and dibromoacetic acid) concentrations as surrogate measures for individual-level exposures. It is critical that these surrogates accurately reflect temporal and spatial variability in DBP concentrations to reduce exposure measurement error. System-average concentrations may inadequately capture spatial variability in DBP formation if large differences occur between sample sites within a distribution system. To determine the utility of system-averages in estimating individual DBP levels, we assessed spatial variability in routinely-collected THM4 and HAA5 monitoring data for 144 and 132 public water systems (PWSs), respectively, in Massachusetts from 1995-2004. Information on water source and principal type of disinfectant (i.e., ozone, chlorine dioxide, chlorine, or chloramination) was also collected for each PWS.

High spatial variability was defined using three methods. Methods 1 and 2 are based on the absolute differences between at least two sampling locations in the distribution system of ≥20 and ≥30 μg/L, respectively. If any PWS exceeds these differences for at least 1 sample date during the 10 year study period, then they are classified as having high spatial variability. Based on intra-system THM4 differences of ≥20 μg/L (Method 1), 108 PWSs (75%) had high spatial variability compared to 95 PWSs (66%) using Method 2. Over half of these PWSs had high spatial variability for at least 25% of their sampling dates, according to either method. The percentage of PWSs with high spatial variability for HAA5 was slightly lower with 79 PWSs (59%) and 60 PWSs (45%) according to Method 1 and 2, respectively. Similar to THM4, over half of the PWSs had high spatial variability for 25% or more of their sampling dates. We also examined spatial variability based on a ≥30 μg/L (Method 2) difference for THM4 based on 99 PWSs (69%) using chlorination and 14 PWSs (10%) using chloramination during the entire period. Among the chlorinated systems, 28% of the PWSs had high spatial variability compared to 21% of the chloraminated sample dates. Using a subset of the data (17 PWSs), we compared these spatial variation approaches (Methods 1 and 2) to another approach (Method 3) that classifies spatial variation using three exposure categories. We found comparable results for Methods 1 and 3, with 76% of PWSs experiencing high spatial variation by both methods. In conclusion, the spatial variability noted across several water systems could result inmisclassification bias if system averages are used to estimate individual-level trihalomethane and haloacetic acid exposures. Therefore, exposure assessment approaches should target drinking water distribution systems with minimal spatial variability for epidemiological application.
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Keywords: Disinfection by-products; drinking water; exposure assessment; exposure misclassification; spatial variability

Document Type: Research Article

Publication date: 2011-01-01

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