Estimating exposure to volatile organic compounds from municipal water-supply systems: use of a better computational model.
The Southington, Connecticut, water-supply system is characterized by a distribution network that contains more than 1 700 pipeline segments of varying diameters and construction materials, more than 186 mi (299 km) of pipe, 9 groundwater extraction wells capable of pumping more than 4 700 gal/min (0.2965 m3/s), and 3 municipal reservoirs. Volatile organic compounds, which contaminated the underlying groundwater reservoir during the 1970s, contaminated the water-supply system and exposed the town's residents to volatile organic chemicals. We applied a computational model to the water-supply system to characterize and quantify the distribution of volatile organic compounds in the pipelines, from which we estimated the demographic distribution of potential exposure to the town's residents. Based on results from modeling analyses, we concluded the following: (a) exposure to volatile organic compound contamination may vary significantly from one census block to another, even when these census blocks are adjacent to each other within a specified radius; (b) maximum spatial spread of contamination in a water-distribution system may not occur under peak demand conditions, and, therefore, maximum spatial distribution of the exposed population also may not correspond to peak demand conditions, and (c) use of the proposed computational model allows for a more refined and rigorous methodology with which to estimate census-block-level contamination for exposure assessment and epidemiologic investigations.
Aral
M M
MM
School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, USA.
Maslia
M L
ML
Ulirsch
G V
GV
Reyes
J J
JJ
D000465:Algorithms; D003237:Connecticut; D004781:Environmental Exposure / Q000009:adverse effects* / Q000032:analysis / Q000706:statistics & numerical data; D006801:Humans; D015233:Models, Statistical; D014835:Volatilization; D014874:Water Pollutants, Chemical / Q000009:adverse effects* / Q000032:analysis; D014881:Water Supply / Q000032:analysis / Q000706:statistics & numerical data
D014874:Water Pollutants, Chemical