Modeling fate and transport of arsenic in a chlorinated distribution system

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Abstract

Experimental and modeling studies were conducted to understand the fate and transport properties of arsenic in drinking water distribution systems. Pilot scale experiments were performed in a distribution system simulator by injecting arsenic and measuring both adsorption onto iron pipe material and the oxidation of arsenite by hypochlorite in tap water to form arsenate. A mathematical model describing these processes was developed and simulated using EPANET-MSX, a hydraulic and multi-species water quality software for pipe networks. Model parameters were derived from the pilot-scale experiments. The model was applied to both the distribution system simulator and EPANET example network #3, a real-world model of a drinking water system serving approximately 78,000 customers. The model can be applied to systems-level studies of arsenic fate and transport in drinking water resulting from natural occurrences, accidental spills, or intentional introduction into water.

Introduction

Arsenic (As) is a naturally occurring toxic material that is highly soluble and often found in water sources (U. S. EPA, 2012). The U.S. Environmental Protection Agency reduced maximum contaminant level (MCL) for As from 50 ppb to 10 ppb (μg/L) in 2001 (U. S. EPA, 2015). This MCL reduction and the known toxicity of As have resulted in significant research into technologies to remove As from drinking water (Pierce and Moore, 1980, Pierce and Moore, 1982, Lakshmipathiraj et al., 2006, AWWARF, 2005, Banerjee et al., 2008, Fuller et al., 1993, Zhao et al., 2011, Goldberg and Johnston, 2001, Goldberg, 2002, Dixit and Hering, 2003, O'Reilly et al., 2001, Mamindy-Pajany et al., 2009, Masue et al., 2007, Lafferty and Loeppert, 2005, Wingrich and Wolf, 2002, Bhandari et al., 2012, Payne and Abdel-Fattah, 2005, Jain et al., 1999, Lenoble et al., 2002, Impellitteri and Scheckel, 2006, Waltham and Eick, 2002, Raven et al., 1998, Jeppu et al., 2010, Guan et al., 2008, Habuda-Stanić et al., 2008, Driehaus et al., 1998, Jeppu and Clement, 2012, Catalano et al., 2011, Grossl et al., 1997, van Elteren et al., 2001, Dodd et al., 2006, Manning et al., 1998, Fendorf et al., 1997, Sorlini and Gialdini, 2010, Vasudevan et al., 2006, Jeppu et al., 2012, Philips and Taylor, 1976, Huang et al., 2011a, Huang et al., 2011b, Bissen and Frimmel, 2003, Hug et al., 2001, Dinesh and Pittman, 2007). Due to the high affinity of iron-based materials for As, many of these studies have investigated how much As adsorbs onto different iron-based materials in order to understand their viability for As removal in drinking water treatment (Pierce and Moore, 1980, Pierce and Moore, 1982, Lakshmipathiraj et al., 2006, AWWARF, 2005, Banerjee et al., 2008, Fuller et al., 1993, Zhao et al., 2011, Goldberg and Johnston, 2001, Goldberg, 2002, Dixit and Hering, 2003, O'Reilly et al., 2001, Mamindy-Pajany et al., 2009, Masue et al., 2007, Lafferty and Loeppert, 2005, Wingrich and Wolf, 2002, Bhandari et al., 2012, Payne and Abdel-Fattah, 2005, Jain et al., 1999, Lenoble et al., 2002, Impellitteri and Scheckel, 2006, Waltham and Eick, 2002, Raven et al., 1998, Jeppu et al., 2010, Guan et al., 2008, Habuda-Stanić et al., 2008, Driehaus et al., 1998, Jeppu and Clement, 2012, Catalano et al., 2011, Grossl et al., 1997, Manning et al., 1998, Fendorf et al., 1997, Bissen and Frimmel, 2003, Dinesh and Pittman, 2007).

Iron-based pipe materials can be found in the majority of drinking water distribution systems. Cast iron, ductile iron, and steel have been used in water distribution systems for many years. While some of this infrastructure is slowly being replaced with other materials, such as cement-lined cast iron, many older pipes within a distribution network may still have exposed iron-based surfaces. Over time, these iron-based pipes corrode and can also acquire mineral deposits or biofilms (Mohebbi and Li, 2011, Lytle et al., 2004a, Lytle et al., 2010, Lytle et al., 2014, Gerke et al., 2008). The corroded surface of iron pipes has been found to contain a mixture of different species of iron, such as amorphous ferric hydroxide, goethite, ferrihydrite, siderite, lepidocrocite, and magnetite (Lytle et al., 2004a). If arsenic is present in the water, it can adsorb to these iron-based pipe materials. Segments of pipes taken out of service have been found to contain elevated As levels even though only low As levels were present in the water (Lytle et al., 2004a).

The goal of this study was to develop a predictive model of arsenic fate and transport in drinking water systems. To this end, experimental studies were conducted to measure arsenic adsorption to and desorption from pipe walls and arsenite oxidation in chlorinated water. Cast iron coupons that were allowed to corrode in tap water were used to mimic the inner surface of pipes in older distribution systems, or where defects may have formed in newer cement-lined iron pipes. A mathematical model was developed that incorporates adsorption, desorption, advection, and reaction with chlorine. Model parameters were estimated from data collected during pilot-scale experiments. The model was simulated using EPANET-MSX, a hydraulic and multi-species water quality modeling tool, and applied to models of both a pilot scale pipe loop and a real-world drinking water system. The model is simple enough to apply to full-scale distribution system models to investigate naturally occurring arsenic or accidental contamination with arsenic species.

Section snippets

Background

Despite having been extensively studied, there is little agreement within the literature regarding the selection of adsorption models and associated parameters for modeling arsenic adsorption. Differences in test materials, research goals, and experimental designs have led to a wide range of numerical parameters for each adsorption model. General trends in adsorption behavior are consistent between various studies, but the interpretation of the behavior varies. Further, the species of iron

Material and methods

This study included both experimental and modeling work and methods for each are discussed here.

Results and discussion

The predictive model (equations (1), (2), (3), (4))) utilized three values that were determined experimentally under similar conditions (pH 8, room temperature) were selected from the literature. Pierce and Moore reported a value for the equilibrium constant for arsenate, Keq, of 0.0539 mg As/L for iron oxide in water at pH 8 (reported as 0.719 μM/L) (Pierce and Moore, 1982). Tanaka et al. reported the arsenate diffusion coefficient as 7.27 × 10−6 cm2/s (Tanaka et al., 2013). Dodd et al.

Conclusion

Experiments were conducted within a DSS to quantify adsorption and desorption of As onto iron pipe coupons and oxidation of arsenite in a chlorinated system. Results from these experiments were used to develop a general model for EPANET-MSX that could be applied to larger water distribution systems of any size. The adsorption and desorption model described herein was able to predict the adsorption and subsequent desorption of arsenic onto iron-based pipe materials. Previously reported arsenite

Acknowledgments and disclaimer

The U.S. Environmental Protection Agency through its Office of Research and Development funded and collaborated in the research described here under an Interagency Agreement with the Department of Energy's ORISE fellowship program and Contract EP-C-09-041 with Shaw Environmental. It has been reviewed by the Agency and approved for publication but does not necessarily reflect the Agency's views. No official endorsement should be inferred. EPA does not endorse the purchase or sale of any

References (69)

  • L.K. Koopal et al.

    A simple model for adsorption kinetics at charged solid-liquid interfaces

    Colloids Surfaces

    (2001)
  • P. Lakshmipathiraj et al.

    Adsorption of arsenate on synthetic goethite from aqueous solutions

    J. Hazard. Mater. B

    (2006)
  • V. Lenoble et al.

    Arsenic adsorption onto pillared clays and iron oxides

    J. Colloid Interface Sci.

    (2002)
  • D.A. Lytle et al.

    The accumulation of radioactive contaminants in drinking water systems

    Water Res.

    (2014)
  • Y. Mamindy-Pajany et al.

    Arsenic adsorption onto hematite and goethite

    Comptes Rendus Chim.

    (2009)
  • L. Monteiro et al.

    Modeling of chlorine decay in drinking water supply systems using EPANET MSX

    Procedia Eng.

    (2014)
  • J. Muranho et al.

    Technical performance evaluation of water distribution networks based on EPANET

    Procedia Eng.

    (2014)
  • M.L. Pierce et al.

    Adsorption of arsenite and arsenate on amorphous iron hydroxide

    Water Res.

    (1982)
  • N. Ratnayake et al.

    Study of transport of contaminants in a pipe network using the model EPANET

    Water Sci. Technol.

    (1999)
  • M. Tanaka et al.

    The difference of diffusion coefficients in water for arsenic compounds at various pH and its dominant factors implied by molecular simulations

    Geochimica Comsochimica Acta

    (2013)
  • Z. Zhao et al.

    Adsorption and heterogeneous oxidation of As(III) on ferrihydrite

    Water Res.

    (2011)
  • AWWARF

    Adsorbent Treatment Technologies for Arsenic Removal

    (2005)
  • N. Bhandari et al.

    Photoinduced oxidation of arsenite to arsenate ni the presence of goethite

    Environ. Sci. Technol.

    (2012)
  • M. Bissen et al.

    Aresnic – a review. Part II: oxidation of arsenic and its removal in water treatment

    Acta hydrochimica hydrobiologica

    (2003)
  • J.G. Catalano et al.

    Effect of aqueous fe(II) on arsenate sorption on goethite and hematite

    Environ. Sci. Technol.

    (2011)
  • L.S. Clesceri et al.

    Standard Methods for the Examination of Water and Wastewater

    (1998)
  • R.C. Copeland et al.

    Desorption of arsenic from drinking water distribution system solids

    Environ. Monit. Assess.

    (2007)
  • S.A. Crosby et al.

    Surface areas and porosities of Fe(III)- and Fe(II)-derived oxyhydroxides

    Environ. Sci. Technol.

    (1983)
  • E.L. Cussler

    Diffusion: Mass Transfer in Fluid Systems

    (1984)
  • M. Dinesh et al.

    Arsenic removal from water/wastewater using adsorbents—a critical review

    J. Hazard. Mater.

    (2007)
  • S. Dixit et al.

    Comparison of arsenic(V) and arsenic(III) sorption onto iron oxide minerals: implications for arsenic mobility

    Environ. Sci. Technol.

    (2003)
  • M.C. Dodd et al.

    Kinetics and mechanistic aspects of As(III) oxidation by aqueous chlorine, chloramines, and ozone: relevance to drinking water treatment

    Environ. Sci. Technol.

    (2006)
  • W. Driehaus et al.

    Granular ferric hydroxide—a new adsorbent for the removal of arsenic from natural waters

    J. Water Supply Res. Technology–AQUA

    (1998)
  • S. Fendorf et al.

    Arsenate and chromate retention mechanisms on goethite. 1. surface structure

    Environ. Sci. Technol.

    (1997)
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