Chemical Education Today
Report
Streaming Waters: Challenges in Monitoring the Chemistry of Dynamic Environments by Joseph H. Aldstadt, III and Melissa A. Singer Pressman
What little survives from the writings of the philosopher Heraclitus (~535–475 B.C.E.) are collected as “Fragments” (1). One of the most compelling can be translated to …one cannot step twice into the same river. Whereas philosophically one might interpret this to mean that both the observer and the observed undergo constant change, in a scientific context, the meaning can be more literal. That is, nature is in a perpetual state of flux. Environmental waters are some of the more obvious examples of this—whether they be ocean, lake, river, or stream. To understand their chemical composition requires measurements at frequencies that are high enough to create a realistic picture of the true state of the system. As we describe in the following, this presents an opportunity to incorporate a novel type of instrument into the analytical chemistry curriculum. Students can learn to build simple monitors that illustrate the challenges (and frustrations) and benefits (and drawbacks) of remote environmental monitoring. The Problem of Under-Sampling Although the concentrations of components in environmental waters change continuously over time, they must be sampled at discrete intervals. These discrete measurements are then used to reconstruct the original, continuous signal. Defining the appropriate sampling frequency can be difficult. If one samples too frequently (over-samples), one can become burdened with unnecessary work and voluminous data. However, under-sampling can have even more dire consequences.
Figure 1. A simulated example of “under-sampling” in which weekly measurements (--●--) do not accurately reflect measurements made on a daily basis (–□–).
When discrete points that are taken too infrequently are then used to reconstruct by interpolation the continuous “true” signal, artifacts can be created. Creating artifacts as the result of the inaccurate interpolation is called “aliasing”. Figure 1 is an example of aliasing during a simulated monitoring period. The proper sampling frequency can be approached by applying the Nyquist–Shannon theorem, which is known as “the cardinal theorem of interpolation theory” (2). The Nyquist–Shannon theorem requires one to sample at a rate that is at least twice the frequency of the true signal to prevent aliasing. A more accurate understanding of a dynamic system will allow for a better understanding of the biogeochemical processes that occur therein. Given the dynamics of natural waters, however, and typical “grab” sampling methodologies, under-sampling is prone to occur in more rapidly changing environments. While concentrations of the chemical components that are found in the middle of a large lake or in a groundwater formation, for example, may vary little over relatively long periods of time, concentrations in tidal basins, rivers, and streams tend to fluctuate considerably. In Situ Monitoring Approaches To monitor dynamic environmental phenomena, ideally one would want to make the measurement directly at the point of sampling, or “in situ” because measurements can be made at high frequency. Not surprisingly, this has been an area of intensive research in analytical chemistry in recent years (3). Early approaches, in which instruments designed for a laboratory environment were made more rugged for field use, failed because the instruments were expensive, bulky, fragile, etc. More recent research has centered upon designing in situ instruments from the “bottom up”, and applying them to the determination of chemical species even at trace levels in complex matrices (4–7). Additionally, in situ measurements are immune from the possibility of sample contamination that occurs, at least to some degree, during transport to a laboratory and storage. The ability of these instruments to self-calibrate is a crucial characteristic in maintaining high data quality. While the quality of the data generated cannot match the precision and accuracy that is attainable with off-site fixed laboratory measurements, nor the power of sensitive multi-analyte determinations such as provided by GC–MS or ICP–MS, for many applications in situ monitoring instruments provide the desired quality of information. Thus in situ instruments that have a capability of self-calibration can be particularly useful by attaining higher data quality. In situ monitoring instrumentation can be divided into two general categories: “chemical sensors” and “chemical analyzers” (8). Chemical sensors, in which mass transfer by diffusion brings the analyte to the transducer surface, are mechanically simple
© Division of Chemical Education • www.JCE.DivCHED.org • Vol. 85 No. 2 February 2008 • Journal of Chemical Education
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Chemical Education Today
Report and practical in terms of their low power requirements, ruggedness, and small size and weight. Chemical sensors, however, often exhibit lower selectivity because their operation is based upon reversible chemical reactions. The interaction of the analyte with the sensor (transducer) surface must have a large binding (formation) constant Kf if trace levels (sub-µg/mL) are to be measured. Consider the reaction of analyte A with ligand B to form complex AB:
A + B → AB
rate = -(d/dt) [A] = -(d/dt) [B] = k1[A][B]
AB → A + B
rate = -(d/dt) [AB] = k2[AB]
(1)
(2)
The equilibrium constant (Kf ) for formation of AB is the ratio of the rate constants for the formation and dissociation of AB:
Kf = k1 / k2
The recovery time is defined as the time required for dissociation of AB such that the baseline response characteristic of the absence of analyte A is once again restored. Rapid response of the sensor requires a large k1. For a large Kf, the value of k2 must be small—the smaller the better. This requires that the rate of dissociation be small and the recovery time large (9). Large recovery times detract from performance of the sensor. To address this predicament, “renewable reagent” chemical sensors have been developed, wherein the reagent (ligand B) is pumped directly to the surface of the sensor (10). Chemical analyzers represent the second trend in the design of in situ monitors. These types of instruments rely upon active transport of the analyte into and away from the monitor, thereby providing a faster response as well as a shorter recovery time. While the requisite valves and pumps increase the cost as well as the complexity, they also provide a means to introduce in-line standards and wash solutions into the manifold design. This is a critical difference when compared to typical chemical sensor designs because sensor-based monitors are calibrated before and after deployment, with the assumption of linear behavior during the interpolated monitoring period. Furthermore, active transport of multiple reagents can open the door to more complex formation reaction chemistries that can be used to increase the sensitivity and selectivity of the instrument. Finally, in addition to injecting standards into the flow path, solutions of dilute acids can be periodically introduced to maintain a clean detector (e.g. electrode surface or optical flow cell), an essential function for maintaining the operation of remotely deployed monitors. The chemical analyzer-type of in situ monitor has been applied to both freshwater and marine environments (4–11). From a pedagogical standpoint, these instrument designs are also attractive. Flow channels are machined or forged into a plastic substrate; solenoid valves are then added for introducing reagents, standards, washes, etc. Propulsion of sample and reagents at µL/hr rates is accomplished by either use of osmotic
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Figure 2. In situ chemical analyzer for nitrate developed at Moss Landing Marine Laboratory (4). STD = standard; BLK = blank; SULF = p=amino-benzenesulfonamide; NED = N-(1-naphthyl)ethylenediamine dihydrochloride. Note that osmotic reagent pumps are used to deliver solutions (lower left) while four other osmotic pumps are used in concert (right) to draw sample through the manifold. As shown in the lower right, the osmotic pressure gradient is created across a semi-permeable membrane that separates a saturated solution of NaCl from a solution of low salinity. Reproduced with permission from Anal. Chem. 1994, 66, 3352. Copyright 1994 American Chemical Society.
pumps or miniature peristaltic pumps—the former attractive because of their simplicity, the latter advantageous for pressure differentials that are more demanding. One of the earliest successful designs is shown in Figure 2, as described by researchers at Moss Landing Marine Laboratory (4), for monitoring nitrate levels in sea water in Monterey Bay, CA. A well-established method was used to measure aqueous nitrate colorimetrically: nitrate was reduced to nitrite using an in-line copperized cadmium surface, nitrite was derivatized in an acidic solution of pamino-benzenesulfonamide to form a diazonium ion, this then reacted with N-(1-naphthyl)ethylenediamine dihydrochloride to form an azo dye of high molar absorptivity. Quantitation of the azo dye was done by molecular absorbance spectroscopy using a Z-type flow cell comprised of a light-emitting diode (LED) source and photodiode detector. In Situ Monitoring: Hexavalent Chromium While much in situ monitoring work has focused on quantitation of nutrients (e.g., nitrate, phosphate) at mM to μM levels, the measurement of metals at μM to nM levels has also been reported (7, 12, 13). Chromium in environmental waters is challenging to measure, given the low levels (sub-mg/L) at which it is monitored for regulatory compliance. Additionally, because chromium toxicity is a function of its speciation (i.e., the hexavalent form is a known carcinogen whereas the trivalent form is considered an essential nutrient), the ability to quantify Cr(VI) at low levels with high frequency for applications in rapidly changing systems (e.g., rivers or harbors) is of interest. For this work, building primarily upon the work of Jannasch and
Journal of Chemical Education • Vol. 85 No. 2 February 2008 • www.JCE.DivCHED.org • © Division of Chemical Education
Chemical Education Today
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Figure 3. Schematic diagram of the Cr(VI) monitor (7). A = sample inlet; B = reagent osmotic pump; C, D = cleaning and QC standard osmotic pumps, resp.; E, F = solenoid valves; G = mini-peristaltic pump; H = forged channel; I = optical cell; J = waste container; K, L = Plexiglas plates; M = vinyl sealing layer; N = 1/4-28 holes for securing plates. Datalogger, signal conditioning board, and battery pack are not shown. Reproduced by permission of The Royal Society of Chemistry.
colleagues, our goal was to develop a robust monitor to use in Milwaukee Harbor, where industrial sources result in the presence of Cr(III) and Cr(VI) in surface waters at levels ranging
