ABSTRACT

The reduction/oxidation (redox) condition of ground water affects the concentration, transport, and fate of many anthropogenic and natural contaminants. The redox state of a ground-water sample is defined by the dominant type of reduction/oxidation reaction, or redox process, occurring in the sample, as inferred from water-quality data. However, because of the difficulty in defining and applying a systematic redox framework to samples from diverse hydrogeologic settings, many regional water-quality investigations do not attempt to determine the predominant redox process in ground water. Recently, McMahon and Chapelle (2008) devised a redox framework that was applied to a large number of samples from 15 principal aquifer systems in the United States to examine the effect of redox processes on water quality. This framework was expanded by Chapelle and others (in press) to use measured sulfide data to differentiate between iron(III)- and sulfate-reducing conditions. These investigations showed that a systematic approach to characterize redox conditions in ground water could be applied to datasets from diverse hydrogeologic settings using water-quality data routinely collected in regional water-quality investigations.

This report describes the Microsoft^® Excel^® workbook, RedoxAssignment_McMahon&Chapelle.xls, that assigns the predominant redox process to samples using the framework created by McMahon and Chapelle (2008) and expanded by Chapelle and others (in press). Assignment of redox conditions is based on concentrations of dissolved oxygen (O₂), nitrate (NO₃^–), manganese (Mn²⁺), iron (Fe²⁺), sulfate (SO₄^2–), and sulfide (sum of dihydrogen sulfide [aqueous H₂S], hydrogen sulfide [HS^–], and sulfide [S^2–]). The logical arguments for assigning the predominant redox process to each sample are performed by a program written in Microsoft^® Visual Basic^® for Applications (VBA). The program is called from buttons on the main worksheet. The number of samples that can be analyzed is only limited by the number of rows in Excel^® (65,536 for Excel^® 2003 and XP^®; and 1,048,576 for Excel^® 2007), and is therefore appropriate for large datasets.