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This article in JEQ

  1. Vol. 43 No. 2, p. 611-616
     
    Received: July 30, 2013
    Published: June 23, 2014


    * Corresponding author(s): Rajith.Mukundan@hunter.cuny.edu
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doi:10.2134/jeq2013.07.0305

Predicting Trihalomethanes in the New York City Water Supply

  1. Rajith Mukundan *a and
  2. Richard Van Dreasonb
  1. a Institute for Sustainable Cities, City University of New York, NY, 10065
    b Bureau of Water Supply, New York City Department of Environmental Protection, Kingston, NY, 12401

Abstract

Chlorine, a commonly used disinfectant in most water supply systems, can combine with organic carbon to form disinfectant byproducts, including carcinogenic trihalomethanes. We used water quality data from 24 monitoring sites within the New York City water supply distribution system, measured between January 2009 and April 2012, to develop an empirical model for predicting total trihalomethane (TTHM) levels. Terms in the model included the following water quality parameters: total organic carbon, pH, water age (reaction time), and water temperature. Reasonable estimates of TTHM levels were achieved with overall R2 of about 0.75, and predicted values on average were within 6 μg L−1 of measured values. A sensitivity analysis indicated that total organic carbon and water age are the most important factors for TTHM formation, followed by water temperature; pH was the least important factor within the boundary conditions of observed water quality. Although never out of compliance in 2011, the TTHM levels in the water supply increased after tropical storms Irene and Lee, with 45% of the samples exceeding the 80 μg L−1 maximum contaminant level in October and November. This increase was explained by changes in water quality parameters, particularly by the increase in total organic carbon concentration during this period. This study demonstrates the use of an empirical model to understand TTHM formative factors and their relative importance in a drinking water supply. This has implications for simulating management scenarios and real-time estimation of TTHMs in water supply systems under changing environmental conditions.

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