limnology and oceanography: methods · the analyzer is capable of sampling hourly and has a...

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Introduction

Ammonium is the most reduced form of inorganic nitrogenin seawater, and it is the initial inorganic nitrogen speciesreleased during the remineralization of nitrogen containingorganic matter (Von Brand et al. 1937). Ammonium can beassimilated and incorporated into organic molecules by pri-mary producers and bacteria, or it can be oxidized throughvarious inorganic pathways mediated by bacteria in aerobic(nitrification) or anaerobic (anaerobic ammonium oxidation)

environments (Furman et al. 1988; Herbert 1999; Dalsgaard etal. 2005; Francis et al. 2007). The residence time of dissolvedammonium in the surface ocean is typically hours or less (Sut-tle et al. 1990; Clark et al. 2008), yet from day to day, theammonium concentration often varies little, suggesting aclose balance between removal and production processes(Dodds 1993).

Given the importance of ammonium in the marine nitro-gen cycle, accurate measurements of ambient concentrationsare needed for many research applications. Standard methods,however, can be problematic and lead to uncertainties in themeasurements. Discrepancies are most pronounced whenmeasuring nanomolar concentrations, or nanomolar changesin concentration over time. Uncertainties result from a com-bination of factors including: sample storage effects, contami-nation, matrix mismatches during analysis between the cali-bration standards and the sample, and blank problems(Degobbis 1973; Aminot et al. 1997). In addition to analyticalproblems, many ecological systems of interest are undersam-pled relative to the time scales at which ammonium concen-trations change. This is typically due to the significant effortand resources required to manually collect samples from theaquatic environment. This, in turn, can cause aliasing of thesample data variability, which may lead to inaccurate conclu-sions about the fate of the analyte and ecosystem processes ingeneral (Johnson et al. 2007).

NH4-Digiscan: an in situ and laboratory ammonium analyzer forestuarine, coastal, and shelf watersJ. N. Plant1, K. S. Johnson1, J. A. Needoba2, and L. J. Coletti11Monterey Bay Aquarium Research Institute (MBARI), 7700 Sandholdt Road, Moss Landing, CA 950392Department of Science & Engineering, School of Medicine, Oregon Health & Science University, 20000 NW Walker Rd.Beaverton, OR 97006

AbstractThe NH4-Digiscan is an in situ analyzer designed for measuring ammonium in estuarine, coastal, and shelf

waters at depths of less than 3 m. This wet chemical analyzer uses micro-solenoid pumps to propel sample andreagents, a gas diffusion cell to isolate the analyte from the matrix, and a conductivity detector for analytedetection. Instrument measurements are stable for deployments of at least 30 d. In estuarine and coastal waters,the analyzer is capable of sampling hourly and has a detection limit of 0.2 μM. In shelf waters, the NH4-Digiscancan be configured to have a detection limit of 0.014 μM. The simple chemistry, in situ capability, and high res-olution sampling minimizes the use of toxic reagents, minimizes many of the problems plaguing ammoniumanalyses, and adequately captures the high temporal variability of coastal waters, which is often undersampled.The analyzer has been successfully deployed on coastal moorings, benthic flux chambers, and on a drifter 500km west of Monterey Bay, California. The system can also be easily configured for laboratory bench top analy-sis of discrete samples.

*Corresponding author: E-mail: [email protected]

AcknowledgmentsThis work was funded by the David and Lucile Packard Foundation

through a grant to the Monterey Bay Aquarium Research Institute andby the NSF Biocomplexity in the Environment program through grantECS-0308070. The analyzer development benefited from the help ofmany people. The diffusion cells and housings were designed by HansJannasch and fabricated by the machine shop at the Monterey BayAquarium Research Institute. The conductivity cells and detector circuit-ry were customized by the team at Amber Scientific, Eugene, Oregon.The field validation would not have been possible without ship timeaboard the R/V Western Flyer and help from the crew as well as the useof boats from Moss Landing Marine Labs Small Boat Operations.Verification of nanomolar measurements would not have been possiblewithout the help of Carole Sakamoto and the multiple test deploymentswould not have been possible without the help of Steve Fitzwater.

Limnol. Oceanogr.: Methods 7, 2009, 144–156© 2009, by the American Society of Limnology and Oceanography, Inc.

LIMNOLOGYand

OCEANOGRAPHY: METHODS

Plant et al. NH4-Digiscan ammonium analyzer

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To better understand the role of ammonium in the marinenitrogen cycle, an instrument capable of in situ measurementsis required. For a prolonged deployment a simple, robust, andstable methodology would be advantageous. While theindophenol-blue (IPB) colorimetric method is probably themost widely applied ammonium analysis, the technique canalso be difficult to use (Solorzano 1969; Koroleff 1983; Aminotet al. 1997). The technique suffers from poor sensitivity andreproducibility when measuring sub-micromolar ammoniumconcentrations (Harwood and Huyser 1970; Mantoura andWoodward 1983; Aminot et al. 1997; Pai et al. 2001). In addi-tion, some of the reagents used are quite toxic (Molins-Leguaet al. 2006), and therefore, would present problems for in situinstrument operations in sensitive environments.

A second approach measures the fluorescence producedwhen ammonium is mixed with ortho-phthaldialdehyde(OPA) in the presence of sodium sulfite (Genfa and Dasgupta1989). The OPA method is very sensitive and has a largedynamic range of 1.5 nM to 250 μM, but the reaction is verytemperature sensitive and at room temperature requires 3 to 4h (Kerouel and Aminot 1997). This slow reaction rate at ambi-ent temperature can be a disadvantage for in situ work. Aheater could be employed to speed up the OPA reaction, butthis would also increase energy consumption and make theanalyzer more complex.

A third approach uses gas diffusion to separate ammoniumfrom the sample matrix prior to detection (Willason and John-son 1986; Schulze et al. 1988; Jones 1991; Hall and Aller 1992;Gray et al. 2006). Generally, a sample is mixed with base toraise the pH above 10.5 and convert ammonium ions toammonia gas. The gas then diffuses across a hydrophobic gaspermeable membrane into a receiving solution for detection.This technique is advantageous because the separation is veryselective, it makes preconcentration possible, and it eliminatesmatrix effects from the sample solution. Hall and Aller (1992)use 50 μM hydrochloric acid for the receiving solution anddetect changes in conductivity as ammonia diffused across themembrane. Ammonia gas reacts with the protons in the acidsolution forming ammonium ions at the expense of protons.Since an ammonium ion is less mobile than a proton, the netresult is a drop in the receiving solution conductivity. Thisconductivity change is proportional to the ammonium con-centration of the sample (Shaw and Staddon 1958). Thismethod is advantageous for in situ instrumentation due to itssimple and robust chemistry, low detection capabilities, andnontoxic reagents.

Here we report on an in situ ammonium analyzer, the NH4-Digiscan, which is based on the chemistry developed by Halland Aller (1992). The analyzer is capable of collecting over 800samples with sub micromolar sensitivity and a minimum sam-pling period of 7 min. The instrument uses micro-solenoiddiaphragm pumps to propel reagents and monitors changesin conductivity for signal detection. The simple chemistryand in situ analysis minimize analytical problems plaguing

ammonium analyses. The analyzer is capable of measuringammonium in estuarine, coastal and shelf environments andcan be configured for bench top laboratory measurements aswell.

Materials and proceduresThe NH4-Digiscan ammonium analyzer is based on a set of

individually controlled micro solenoid diaphragm pumps(Weeks and Johnson 1996). This pulsed flow technology issimilar to the multi-pumping flow systems described by Lapaet al. (2002) and Lima et al. (2004). It offers several advantagesover traditional flow injection analysis systems driven by peri-staltic pumps. These advantages include smaller size, lowerpower consumption, greater analytical flexibility, reduction inreagent usage, less contamination, improved mixing, betterflushing, and less dispersion (Weeks and Johnson 1996; VanAkker et al. 1999; Francis et al. 2002; Lapa et al. 2002; Lima etal. 2004). In situ chemical analyzers based on this concepthave been developed by Thouron et al. (2003) and Chapin etal. (2004) where a data logger/controller powers solenoidpumps, which drive reagents and sample through a flow pathyielding a chemical reaction. The reaction product is quanti-tatively measured with a detector, and the resulting data arethen processed and stored by the logger.

The NH4-digiscan is primarily designed for in situ use atdepths of less than 3 m, but it is also well suited for bench-topapplications. The main differences are that for in situ applica-tions, the electrical components reside in housings and reagentsare contained in bags, while the reagents for the bench top sys-tem are stored in Nalgene high density polyethylene (HDPE)bottles. For in situ ammonium analysis, a combined solution of50 mM sodium hydroxide and 200 mM trisodium citrate dihy-drate is mixed with sample, standard or blank. This mixture ispumped through 0.5 meter mixing coil and then through oneside of the gas diffusion cell, where the ammonia gas diffusesacross the membrane into a 20 μM HCl receiving solution onthe other side. Next the volume of ammonium-enriched HCl inthe diffusion cell is pumped through the conductivity cell fordetection (Fig. 1). The integrated ammonium system can besubdivided into four components for discussion purposes: fluiddelivery, fluid circuitry, detection, and control.

Fluid delivery—The pumping system for the in situ analyzeris contained within an oil-filled (polydimethylsiloxane – DowCorning 200), pressure-compensated housing composed ofpolycarbonate. The housing holds up to 7 micro-solenoiddiaphragm pumps manufactured by the Lee Co. Pressure com-pensation of the housing is achieved using two 20 cm3 rollinghat diaphragms. The 5 volt pumps, which deliver 50 μL perstoke, are modified by the Lee Co. to operate in oil (part #LPX0502_950A). The side vent hole is enlarged, and a secondhole is drilled through the top of the pump to allow better flowof oil behind the diaphragm during actuation. The Kaptontape around the pump piston is replaced with 0.038 mm cellu-lose triacetate shim stock to prevent the oil from dissolving the


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glue on the Kapton tape, which causes pump failure. The pur-pose of either material is to act as a lubricant between the mag-netic coil and the pump piston to prevent galling.

In addition to the 5 Volt pumps, which are used for the insitu analyzer, 12 Volt pumps made by both the Lee Co. (part #LPX0502600AA) and by Bio-Chem Valve Inc. (part # 120SP-S3)are used for the bench top analyzer. The 12 Volt Lee Co.pumps have a fixed stroke volume of 50 μL, while the strokevolume of the Bio-Chem Valve Inc. pumps can be variedbetween 20 μL and 60 μL per stroke. The Bio-Chem Valve Inc.pumps are used for sample (60 μL) and base (20 μL) delivery.The increased sample to base ratio increases the overall ammo-nium concentration entering the sample side of the diffusioncell which increases the analytical response.

Fluid circuitry—Reagent bags, plumbing, and the diffu-sion cell comprise the fluidic circuitry of the in situ NH4-Digiscan. Reagents are contained in Stedim Flexboy drugdelivery bags, and PTFE tubing is used for all plumbingincluding the mixing coil (1.6 mm outer diameter by 0.8mm inner diameter). Plumbing connections are made with1/4-28 PEEK fittings and flangeless ferrules from UpchurchScientific. All reagents are stored in high density polyethyl-ene bottles and made with freshly produced Milli-Q water(resistivity > 18.2 MΩ cm at 25°C, 0.22 μm filtered) andreagent grade chemicals.

Sodium hydroxide and sodium citrate solution. For in situapplications, 2 g NaOH were dissolved in 1000 g Milli-Q waterfollowed by 60 g C6H8O7Na3 2H2O. The final concentrationswere approximately 50 mM sodium hydroxide and 200 mMtrisodium citrate dihydrate solution. The bench top methodrequired a more concentrated base (150 mM) and citrate solu-tion (660 mM) due to the 60 + 20 sample to base mixing ratio.0.72 g of NaOH were added to 120 g of Milli-Q water followedby 23.3 g C6H8O7Na3 2H2O.

HCl solution. A 41 mM stock solution was prepared bydiluting 2.0 mL of 6M HCl with 290 g Milli-Q water. 1.0 mL ofthis stock solution was then added to 2000 g Milli-Q water toyield a 20 μM HCl solution.

Blank and standards. The blank consisted of 2 L of aged (>3 mo), low ammonium surface seawater collected offshore ofMonterey Bay, California. The seawater ammonium concen-tration was less than 0.01 μM. All working standards in thelaboratory were made by spiking ~50 g of low ammoniumseawater (density = 1.027 kg m–3) just prior to analysis. Theseawater aliquots were either spiked with a 1.0 mM NH4Clstandard (for 1 to 10 μM working standards) or a 20 μMNH4Cl standard (for 0.020 to 0.125 μM working standards).Weighing the seawater minimized contamination by trans-fers through volumetric containers. The 1.0 mM spikingstandard was prepared with Milli-Q water and was stable forat least 6 mo in a 1.0 L HDPE bottle, while the 20 μM spik-ing standard was prepared by spiking low ammonium sea-water with the 1.0 mM spiking standard just prior to use. The~14 μM in situ standard (7 mL 1.0 mM NH4Cl spiking stan-dard + 500 g low ammonium seawater) was filter sterilizeddirectly into a sterile 500 mL drug delivery bag using a 0.2μm PALL Acrodisc syringe filter (PN 4129). For laboratorytesting, standards were made by spiking ~50 g low ammo-nium seawater just prior to analysis.

Gas diffusion cell. The gas diffusion cell consisted of a 127× 51 × 0.071 mm strip of military grade Teflon pipe tape(McMaster Carr # 6802k77) sandwiched between two polysul-fone blocks. Each block (105 × 40 × 13 mm) contained a fluidtrack 324 mm long by 1.52 mm wide. The sample side was0.20 mm deep while the receiving solution side was 0.10 mmdeep yielding 100 μL and 50 μL volumes respectively (Fig. 2).The track was serpentine in shape to increase mixing and themating faces were machined flat to 0.025 mm.

Fig. 1. Schematic representation of the in situ NH4-Digiscan. Darkened circles represent solenoid pumps. Rounded rectangles to the left of the pumpsrepresent reagent bags. Solid lines represent fluid circuitry while dotted lines represent electrical connections between the housings.


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Detection and control—Conductivity was measured using aconductivity cell (# 829) and detector board (# 4083D) fromAmber Scientific, Eugene, Oregon. The cell was modified in thelab by installing a 4.0 mm spacer between the drive and sens-ing plates. This was half the original width and decreased thecell constant from 100 to 50 cm–1. Amber Scientific modifiedthe conductivity board so that the gain was doubled. These twochanges increased the response of the system by four times. Forin situ analysis the cell and board were powered by a 12 voltbattery pack (8 × 1.5V alkaline D cells), and all componentswere contained within a watertight PVC housing.

The analyzer is controlled by a Tattletale 5F data logger/con-troller running a TXBASIC program developed for this applica-tion. The program is designed to allow analytical flexibility andenables the user to tailor the sampling routine to the particularenvironment being studied. The software manages the pump-ing sequences, flow rates, sampling and calibration intervals,data collection, processing and storage, and testing routines. Ananalysis can be divided into three parts: the flushing sequence,the loading sequence, and the eluting sequence. Each sequencecan have a unique flow rate and pumping schedule. The flush-ing sequence delivers fresh sample, standard or blank into thesystem, flushes the sample path with blank and then loads thereceiving side of the diffusion cell with fresh acid. The loadingsequence mixes sample, standard or blank with base and pushesit through the diffusion cell. The eluting sequence then pushesacid through the conductivity cell for detection. A typical insitu analysis for coastal waters uses 1.65 mL of sample, 3.8 mLof reagents, and requires less than 7 min (Table 1). For in situanalysis, the controller and pumps are powered by a 11.7 volt,30 Ah lithium battery (3B3612 – 1SW, Battery Specialties, Inc.),which enables a five-week deployment at an hourly samplingfrequency. The battery and controller module are packaged in aseparate watertight PVC housing.

Deployment procedure—Before a typical deployment, the diffu-sion cell and associated fittings were dismantled and cleaned inan ultrasonic bath first in Versa-clean liquid cleaner (Fisher Sci-entific # 04-343) diluted 1 + 30 with warm tap water followed byseveral Milli-Q water washings. The cell was then reassembledwith a new membrane and reconnected to the analyzer plumb-ing. The in situ standard was made as described above and thenall remaining reagents were transferred into bags using a 60 mL

plastic syringe body as a funnel, air bubbles were removed, andthen the bags were attached to their respective pump intake lines.

Before and after a deployment a set of calibration standardsare run as well as an aliquot of the in situ standard as a sam-ple to verify that the analyzer pumps were operating properlyand to confirm the value for the in situ standard. A 10 μmultra high molecular weight polyethylene solvent filter(Upchurch Scientific, A-427) is installed on the sample intakeline to prevent clogging by large particles.

AssessmentAnalytical response—The response of the NH4-digiscan to a

given sample ammonium concentration is dependent upon

Fig. 2. Diffusion cell displayed in assembled and disassembled states.

Table 1. Typical analyzer parameters for in situ coastal and (shelf) deployments*

Sequence Pump(s) Strokes Volume (mL) Flow rate (mL/min) Time (s)

Flush Sample 25 (25) 1.25 (1.25) 1.0 (1.0) 75 (75)

Blank 18 (20) 0.90 (1.0) 1.0 (1.0) 54 (60)

Acid 18 (20) 0.90 (1.0) 1.0 (1.0) 54 (60)

Load Sample & Base 8 (70) 0.80 (7.0) 0.8 (0.6) 60 (700)

Blank 12 (10) 0.60 (0.5) 0.4 (0.3) 90 (100)

Elute Acid 20 (20) 1.0 (1.0) 1.0 (1.0) 60 (60)

Totals 5.45 (11.75) 393 (1055)

*Pump stroke volumes are 50 μL.


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several factors including: 1) detector gain, 2) moles of ammo-nia passing through the diffusion cell, 3) transfer efficiency ofammonia gas across the membrane, 4) volume and concen-tration of the receiving acid solution in the diffusion cell, and5) the dispersion of the conductivity signal as it travels fromthe diffusion cell through the conductivity cell since responsewas measured as peak height.

To better understand the overall efficiency and potential ofthe NH4-Digiscan, the measured response was compared witha theoretical estimate based on known chemical equilibria andmass balance. The change in conductivity of the receivingsolution at a reference temperature of 25°C is equal to the sumof the change in concentration of all the ions present multi-plied by their respective molar ionic conductivities:

103Δk = λH ΔH+ + λNH4 ΔNH4+ + λCl ΔCl– + λOH ΔOH– (1)

where H+, NH4+, CL– and OH– represent the concentrations of the

ions in the receiving solution (M), Δ is change, k is conductivity(S cm–1), λ is the molar ionic conductivity (Scm2mol–1), and thesubscripts refer to the ionic species in solution. Eq. 1 can be sim-plified if only the linear response is considered:

Δk = NH4+ (λNH4 – λH) 10–3 = NH4

+ (–0.2762) (2)

Eq. 2 can then be rearranged in terms of the actual sampleammonium concentration, Cs :

Δk/Cs = –0.2762(Ps Vs/Va) ft fd (3)

where the analyzer response is modulated by the number ofsample pump strokes (Ps), the volume of a sample pumpstroke (Vs), the volume of the receiving side of the diffusioncell (Va), the transfer efficiency (ft), and the peak attenuationdue to dispersion (fd). To convert the raw data to μS cm–1, thecounts are multiplied by a constant of 2.5, which accounts forthe cell constant of the diffusion cell as well as the modifica-tion in detector gain. Raw data counts are output as countsdivided by 1000.

For a given set of deployment conditions and a constanttemperature, the ammonia flux across the membrane isdependent only upon the sample ammonia concentration andits residence time in the diffusion cell (Schulze et al. 1988).This allows the transfer efficiency (ft) to be modeled with thefollowing equation:

ft = R/Rmax = (1 – e–bτ) (4)

where R is the measured response and Rmax is the maximum ana-lyzer response (conductivity counts/μM), b (s–1) is the transfercoefficient, and τ is the residence time (s), which was calculatedas the sample side volume of the diffusion cell divided by theflow rate. The transfer efficiency was estimated by measuring Rfor different loading flow rates and fitting Eq. 4 to the data in aleast squares sense. This resulted in a transfer coefficient of0.061 s–1 (Fig. 3A). The transfer coefficient, b, is independent ofsample concentration (Tryzell and Karlberg 1995) and shouldonly be a function of the membrane properties (thickness and

porosity) and the diffusion coefficient of ammonia gas in themembrane. The peak dispersion factor, fd, was estimated to be40%. For a 7 July 2006 calibration, the loading flow rate was 1.0mL min–1. This corresponded to a residence time of 6 s, a trans-fer efficiency of 31.9%, and an expected response of –0.184counts/μM (Fig. 3B and Eq. 3). The measured response, how-ever, was only –0.071 counts/μM and the linear range was about2.6 times greater than expected (Fig. 3B).

Dispersion acts to reduce the response, but it will not affectthe linear range (compare Fig. 3B solid and dashed lines). Thedecreased response and extended range can only occur if fewermoles of ammonia gas than predicted are available for transfer

Fig. 3. (A) Measured response, modeled response, and transfer effi-ciency as a function of residence time at a temperature of 25°C. (B) 7 July2006 calibration data compared with theoretical results with varyingtransfer efficiencies and dispersion coefficients. Each curve is labeled withits calculated response slope. The receiving solution was 21.9 μM HCl, 10sample load pulses, a loading flow rate of 1.0 mL min–1 and correspon-ding transfer efficiency of 31.9%.


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across the membrane. One possibility is that there is incompletemixing between the sample and base solutions when theymerge and mix due to the 50 μL pulse increments of the sam-ple and base pumps. This would prevent a portion of theammonium from being converted to ammonia gas as it passesthrough the sample side of the diffusion cell. Despite the over-all efficiency of only 12.5% (Fig. 3B, dotted line), the analyzer isquite sensitive and has the potential for considerable improve-ment in the future if the mixing efficiency can be increased.

Sample ammonium blank—When measuring nanomolarconcentrations of ammonium, the sample blank can be a rel-atively large percentage of the analytical response. Thisresponse can arise from ammonium in either the seawaterused for calibration or in the sodium hydroxide/sodium cit-rate solution that is mixed with the sample. Aging unfilteredlow nutrient seawater for several months has worked well forcreating low ammonium seawater with an ammonium con-centration of at least less than 10 nM. The aged seawater con-centration was compared with freshly tapped Milli-Q water aswell as oligotrophic surface and 200 m waters to verify its lowammonium concentration. There were no measurable differ-ences in these waters.

The sodium citrate solution did however contribute signif-icantly to the blank. Despite the high pH of the sodiumhydroxide + sodium citrate solution, ammonium is collectedand retained in this solution. This same observation was notedby Jones (1991). This problem was solved by passing the basicsolution through one side of a separate diffusion cell and pass-ing 175 μM HCl on the other side before merging the solutionwith the sample stream during low level analyses. This scrub-bing procedure dropped the blank peak height from –0.017counts to –0.003 counts, which was equivalent to about 44nM ammonium (Fig. 4A).

Stability, sensitivity and precision—The analyzer was quite sta-ble and showed little drift over 30 d when deployed on the L01mooring of the Land/Ocean Biogeochemical Observatory infra-structure in Elkhorn Slough, California (www.mbari.org/lobo,Jannasch et al. 2008). For example, during a February 2006deployment, the pre- and post-deployment calibrationsshowed no change in slope and the in situ standard onlydecreased by 6.7% from 11.8 μM to 11.0 μM. Despite theeutrophic nature of Elkhorn Slough, biofouling was not a prob-lem and if the membrane efficiency was ever reduced overtime, the in situ calibrations would account for this drift.

As stated earlier, the operation of the ammonium analyzeris quite flexible by design. When the NH4-digiscan was set upto measure coastal waters (Table 1) and deployed on the L01mooring, the analyzer had a linear range up to 18 μM and adetection limit of 0.20 μM (Table 2). At 1 μM, the relative stan-dard error was 6%, but this decreased to less than 2.5% forsamples greater than 3 μM. When the in situ analyzer wasoptimized for shelf water measurements the detection limitwas 0.014 μM with a linear range up to 2.0 μM. The bench topanalyzer had a similar low level sensitivity with a detection

limit of 0.010 μM and a linear range up to 2.0 μM (Table 2 andFig. 4A). The detection limits were defined as three times thestandard deviation of the blank.

The lower detection limits are achieved by increasing theamount of sample pulses passing through the diffusion cell andslowing down the flow rate to increase the sensitivity (Table 2).The lowest detection limit is set by the fact that the Teflon pipetape is not perfectly selective for gases. The tape also allows aslight transfer of ions from the sample side to the acid side. Thetransfer coefficient for ammonia gas is much greater than thatfor the ions, but at low nM ammonia concentrations the ion

Fig. 4. (A) High sensitivity calibration curve using the bench top ana-lyzer. The calibration using pretreated base had 50 sample loading pulseswhile the calibration with untreated base had 40 sample loading pulses.(B) Blank peaks for different sample residence times in the diffusion cell. τis the sample residence time in seconds. Sample loading pulses = 50.


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concentrations in the sample stream can be several orders ofmagnitude greater than that of the ammonia gas. The net resultis that as the sample residence time is increased by slowingdown the loading flow rate, the average mass transfer of ammo-nia gas eventually becomes less than the mass transfer of ionsinto the receiving solution. The ion transport increases the con-ductivity of the receiving solution and opposes the drop in con-ductivity due to the ammonia transfer. This positive response atlow ammonium concentrations was also alluded to by Hall andAller (1992). Fig. 4B shows the increasing positive peaks as theloading flow rate is slowed down during the analysis of lowammonium seawater (<10 nM NH4

+). It was interesting to notethat the positive peaks eluted quicker than the negative ammo-nium peaks, possibly due to interactions of the ammonium ionswith solid surfaces in the dilute HCl side of the diffusion cell.

Accuracy—The accuracy of the instrument was tested by col-lecting duplicate samples and comparing the gas diffusion-con-ductometric approach to the traditional IPB method ofSolorzano (1969). For shelf waters, the IBP method was modi-fied in two ways to enhance the sensitivity. First a 2-m longpath liquid waveguide capillary cell was used to increase theoptical path length (Li et al. 2005). Second a completeabsorbance spectrum between 640 nM and 770 nM was ana-lyzed instead of a single wavelength measurement at 640 nM.This helped to account for baseline drift associated with air bub-bles in the capillary cell. The absorbance spectra were processedby fitting the known ammonium absorption spectrum to thesample spectra in a fashion analogous to that described byJohnson and Coletti (2002) for nitrate measurements by UVabsorption. A total of 160 coastal samples were collected duringtwo 24-h surveys in Elkhorn Slough, California. 98 offshoresamples were collected and promptly analyzed at sea from CTDcasts 200 to 400 km west of Monterey Bay, California. Model IIlinear regressions yielded slopes of 1.01 and 1.02 and correla-tion coefficients of 0.994 and 0.997 for coastal and offshoresamples (Fig. 5A and 5B). This demonstrates excellent agree-ment between the two techniques.

Chelators—The high pH required to convert ammoniumions to ammonia gas in seawater also causes the precipitationof magnesium and calcium hydroxides (Irving 1926). If thesecations are not chelated, the precipitates will reduce the effi-ciency of the gas diffusion membrane and clog the plumbingof the sample stream. Two complexing agents commonly usedin the seawater analysis of ammonium were tested for their

effectiveness. The disodium salt of ethylenediaminotetraaceticacid (EDTA) was used in a 1 + 1 stoichiometric ratio to themagnesium + calcium in the seawater sample but precipita-tion still occurred. This was likely due to incomplete mixing

Table 2. Comparison of sampling parameters and response for the in situ and bench top analyzers

Stroke Volume Load Flow rate Slope Range Detection limit Analyzer (μL) Pulses (mL/min) counts/μM (μM) (μM)

Sample Base

In situ (coastal) 50 50 8 0.8 –0.070 18 0.200

In situ (shelf) 50 50 70 0.6 –0.277 2.0 0.014

Bench Top (shelf) 60 20 50 0.8 –0.317 2.0 0.010

Fig. 5. Comparison of the IBP (colorimetric) method to the conducti-metric approach: (A) coastal waters and (B) shelf waters.


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of the sample and base, which was not 1 + 1 at either end ofthe sample + base plug. If excess sample mixed with base, thepH could still be high enough to cause precipitation, yet therewould not be enough EDTA to complex the magnesium andcalcium. A potential solution was to add excess EDTA. How-ever once EDTA was in excess of calcium + magnesium, a pos-itive blank peak was observed suggesting that uncomplexedEDTA interacted with the membrane to enhance ion transportinto the receiving solution. Sodium citrate was tested next instoichiometric excess of magnesium + calcium (200 mM). Nopositive peak or precipitation was observed so citrate was usedas the complexing agent. However, when using sodium citrateas a chelator, the pH of the sample + base mixture must bekept below 11, otherwise sodium citrate becomes ineffective atchelating magnesium and calcium and precipitation willoccur (Gibb et al. 1995; Pai et al. 2001).

Membrane type and performance—Since the membrane ulti-mately determines the sensitivity and response of the ana-lyzer, several different membrane materials were tested usingthe bench top system (Table 3). Membrane behavior is espe-cially important for submicromolar measurements where theanalytical response is a balance between ammonia diffusionand ion leakage across the membrane into the receiving solu-tion (see Sensitivity and precision section). High gas diffusionand low ion leakage will give the best response. The bench topsystem was configured to closely match typical in situ param-eters (loading flow rate = 0.8 mL min–1 and 10 sample andbases pulses, see Table 2). Each membrane was tested with a 3μM ammonium standard and a blank to calculate a responseas well as to see if the blank exhibited a positive peak (ionleakage). Several types of Teflon film were tested as well asKapton and silicone film. Expanded PTFE (ePTFE) had the bestresponse for a given thickness, but it also exhibited the largestpositive blank peak, which limited its potential use as a mem-brane material. Sintered PTFE and FEP film, though quite thin,exhibited no response within the sampling parameters. Thiswas true for Kapton and silicone film as well. Polypropylenehad a moderate response, but also had a positive blank peak.

Unsintered PTFE tape (plumber’s pipe tape) with a thicknessbetween 0.076 and 0.089 mm had the best overall response ofthe materials tested. The response can vary considerably evenwithin a batch or roll of pipe tape (Gray et al. 2006) so carefulinitial testing proved to be important. Once installed themembranes were quite robust and lasted at least a month at anhourly sampling schedule.

Temperature and salinity effects—During deployments inElkhorn Slough, California the temperature varied from 9 to20°C and salinity varied from 17 to 34.5 psu. Temperatureaffects the in situ ammonium analyzer in two ways. First, theconductivity measurement is strongly dependant upon tem-perature, varying by 1.5% to 2.0% per degree. The Amber Sci-entific cell is temperature compensated and corrects for thischange. In addition, the temperature response changes lin-early over the limited conductivity range of the receiving solu-tion. This affects the baseline and peak measurements equally.Therefore the peak height calculation corrects for any temper-ature-related change in conductivity not accounted for by theAmber Scientific electronics. The second problematic temper-ature effect occurs in the diffusion cell. The transfer of ammo-nia from the sample to the receiving solution is also tempera-ture dependant. This dependency is greatest when the transferefficiency is lowest due to shorter sample residence times(higher flow rates). Transfer efficiency (and analyticalresponse) is an exponential function of residence time, sosmall changes in transfer efficiency at low efficiencies willhave a much larger effect on the analytical response thansmall changes at higher efficiencies (Fig. 3A). For example, thepercent change and standard error in analytical response perdegree C for deployments with residence times of 3 s was 6.4± 0.11% while deployments with residence times of 7.5 s hada 2.6 ± 0.13% change (Fig. 6A).

The response of the analyzer to changes in salinity wastested in the lab using the bench top system at two differentsample residence times (flow rates). Five point calibrationcurves (0 to 8 μM) were compared from standards madewith freshly produced Milli-Q water, low ammonium

Table 3. Comparison of the analytical response of gas diffusion membrane materials

Material Supplier Thickness (mm) Response (counts/μM) Positive blank peak

ePTFE (1.0 μm pore size Gore-Tex) W. L. Gore and Associates, Inc. 0.051 0.164 X

ePTFE (233TS) Dewal Industries 0.076 0.137 X

PTFE tape (6802K77) McMaster Carr 0.076 0.114

PTFE tape (6802K77) 0.076 0.095

Full density PTFE Tape Plastomer Technologies 0.089 0.111

0.102 0.031

Polypropylene (2400) Celgard Inc. 0.025 0.049 X

FEP film (sintered) McMaster Carr 0.013 0.001

PTFE film (sintered) McMaster Carr 0.013 0.000

Kapton film (30 HN) DuPont 0.013 0.000

Silicon film (SSPM823) Specialty Silicone Products 0.076 0.000


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seawater, and mixes of the two. Results showed that therewas a –0.31 ± 0.037% change in response per unit of salin-ity increase (Fig. 6B). The higher response at lower salinityis possibly due to the higher pH of the reaction mixture,which favors a greater proportion of ammonia gas. Thissalinity effect amounts to only a 3.1% change in responsefor a 10 psu change in salinity, which is within the precisionof the instrument.

To minimize temperature effects, the sample residence timein the diffusion cell was increased to 7.5 s and in situ calibra-tions were performed every 7 h to correct for any changes inanalyzer response. In regions of high temperature or salinityvariability, the calibration frequency must be adjusted to coin-cide with changing conditions and the salinity of the standardand blank should match the sample as closely as possible.

Field validation—Several field tests were performed to assessthe potential of the NH4-Digiscan. The analyzer was deployedmultiple times on Land/Ocean Biogeochemical Observatory(LOBO) moorings (Jannasch et al. 2008) located withinElkhorn Slough, California. Elkhorn Slough is a seasonaleutrophic estuary at the head of Monterey Bay, California(Caffrey et al. 2002). Fig. 7A shows results from a month longdeployment on the LOBO LO1 mooring located closest to themouth of Elkhorn Slough. The analyzer sampled 831 timesfrom an intake approximately 1 m below the surface at a fre-quency of once an hour. The results indicate that significantvariability in ammonium concentrations was present, withlarge gradients between low and high tides evident through-out the sample period. The gradient is likely caused by themixing of ammonium rich waters from the upper slough andwaters low in ammonium from Monterey Bay. On the incom-ing tide, low ammonium Monterey Bay water travels past themooring and is sampled by the analyzer. During the outgoingtide an ammonium gradient is observed as various propor-tions of ammonium rich water from the upper slough andMonterey Bay water pass the mooring. In addition, ammo-nium spikes are apparent at the beginning of the flood tidesthat are associated with localized inputs from the agriculturalregion upstream of Moss Landing Harbor. These high resolu-tion measurements are sufficient to capture the tidal variabil-ity and demonstrate the utility of the NH4-Digiscan for coastalmonitoring applications.

In a second experiment, the analyzer sampled 2 times anhour from a 27 cm diameter polycarbonate benthic fluxchamber that was 21 cm tall. The chamber was equipped withan electric stirrer consisting of two crossed 1.3 cm diameterPVC rods which rotated at 5 rpm. The flux chamber wasdeployed on a shallow mud flat in upper Elkhorn Slough at adepth of 1.0 m or less and penetrated 4 cm into the sediment.The flux chamber was also equipped with an Aanderaa oxygenoptode which sampled every 15 min. The data appear to showa diurnal oscillation in the net benthic ammonium and oxy-gen fluxes (Fig. 7B). During the early afternoon, when primaryproduction should be highly active, ammonium was con-

sumed at 2.0 mmol m–2 d–1 while oxygen was produced at 46mmol m–2 d–1. Between late afternoon and early morning,both fluxes reversed their daytime direction, suggesting thataerobic respiration was dominant. During this period, ammo-nium was produced at 1.0 mmol m–2 d–1 while oxygen wasconsumed at 92 mmol m–2 d–1. Of further interest is the factthat oxygen was still produced for about 5 h after the magni-tude of the ammonium flux reversed.

In a third test, the bench top system was configured for lowlevel analysis (Table 2, bench top) and taken out to sea duringa research cruise on board the R/V Western Flyer in July 2007.

Fig. 6. (A) Percent change in in situ calibration response due to temper-ature for deployments with sample residence times (τ) of 3.0 and 7.5 s.(B) Percent change in analyzer response due to salinity for sample resi-dence times (τ) of 3.0 and 7.5 s.


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Fig. 7. (A) Hourly ammonium record from LOBO L01 mooring in Elkhorn Slough, California. (B) Ammonium and oxygen data from a benthic flux cham-ber deployed in Elkhorn Slough. (C) Ammonium profile from the water column 290 km west of Monterey Bay, California. (D) In situ surface water ammo-nium measurements collected on a drifter deployed 500 km west of Monterey Bay.


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Discrete samples analyzed from a 200-m water cast 290 kmwest of Monterey Bay show a distinct subsurface maximum of0.200 μM at 50 m with rapid decreases above and below thispeak to below detection limits (Fig. 7C). The same sampleswere also analyzed with the long path length IBP method dis-cussed in the Accuracy section. The comparison is quite goodthough several of the near zero ammonium values below thesubsurface maximum diverge slightly due to baseline prob-lems associated with the IBP method which yield negativeestimates of concentrations.

For a final experiment, the in situ analyzer was optimized forlow level analysis (Table 2, in situ – shelf waters), attached 1meter below a drifting buoy and deployed in waters 500 km westof Monterey Bay. The analyzer was calibrated on board the shipprior to deployment and set to sample every 30 minutes. An insitu blank was analyzed every 8 samples, but no in situ standardwas used due to the instability of low nM standards. The drifterwas deployed to assess if there were any diel increases in ammo-nium at night due to relative increases in grazing or respirationover photosynthesis. During the 4d deployment the drifter trav-eled 140 km toward the south east. Throughout this period, nodiel changes in ammonium concentration were observed (Fig.7D) as the measured concentration was always at or below thedetection limit of the analyzer (14 nM). The negative values,at first, seem contrary during this deployment because con-centration cannot be negative. But concentration is inferredthrough measurement and calibration with another propertyof the analyte (conductivity), and there is error associatedwith this measurement. Measurements at the detection limitof the analyzer should be randomly distributed about zeroincluding negative values (Thompson 1998). The mean of thedeployment was –0.0005 μM which was not significantly dif-ferent than zero (P = 0.122).

Discussion

In coastal waters, nutrient inputs from land can lead toincreased productivity and potentially eutrophication. Under-standing the impact of nutrient loading is a prerequisite tomanaging and mitigating the problem. However, even manualcollection of samples at daily intervals almost invariablyresults in undersampling and a biased understanding of envi-ronmental processes. For example, Fig. 8 shows a four-weekrecord of ammonium measured hourly with the NH4-Digiscanat the LOBO L01 mooring. A clear tidal signal is present as dis-cussed above. In addition, the data record captures a precipi-tation event toward the end of the deployment that is evidentin the oscillating and decreasing salinity data and oscillatingand increasing ammonium concentrations. Runoff from landdilutes the seawater and delivers increased ammonium to theslough. However, if this data set is subsampled at daily inter-vals, a very different perspective emerges. All tidal variabilityis lost and a 06:30 DST sample time yields a very different pic-ture from a 12:30 DST sample time. It is essential to beginmeasuring key environmental variables, such as ammonium,at higher frequencies. This will require in situ analysis.

Here we show that it is feasible to measure ammonia witha relatively simple chemistry and hardware system in situ. Thein situ ammonium analyzer has proven to be an effective androbust instrument for the measurement of ammonium incoastal waters. The month-long deployments displayed in Fig.7A and Fig. 8 captured variability that would not have beenpossible (or at least practical) with manual collection efforts.These data show that high resolution sampling is needed ifaccurate flux calculations are to be made in dynamic coastalenvironments.

High resolution sampling also shows that lack of variabilitycan lead to important new understandings in more olig-

Fig. 8. Hourly ammonium measurements from the LOBO L01 mooring in Elkhorn Slough captured with the NH4-Digiscan and then resampled on dailyfrequencies to emphasize the potential problems of undersampling.


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otrophic environments. For example, in the offshore waters, 4d of in situ measurements did not reveal any detectableammonium concentration spikes (Fig. 7D) that might resultfrom episodic grazing, microbial degradation events, or dielchanges between rates of ammonium production and con-sumption as has been observed in more productive environ-ments (Cochlan at al. 1991; Priddle et al. 1997). Production ofammonium that is recycled from cells via grazing and rem-ineralization is generally believed to fuel greater than 80% ofthe primary production in offshore waters. The absence of adiel cycle with an amplitude greater than the detection limitplaces strong constraints on the role of ammonium as a nitro-gen source for the production of organic matter, and it sug-gests that there may be limited diel cycling of the net ammo-nium fluxes.

Application of the ammonium analyzer in a benthic fluxchamber also yields new insights. There appears to be diel cyclingin the direction and magnitude of the net oxygen and ammo-nium fluxes. Additionally, the ammonium flux does not alwaysappear to be directly coupled to the oxygen flux. In this system,fluxes are much larger than might be expected from moleculardiffusion and bio-irrigation must play a large role in transportingdissolved chemicals across the sediment-water interface.

Together, these applications illustrate the significant advan-tages that result from deployment of in situ analyzers and thenew types of knowledge that may be obtained when under-sampling in time is avoided. The method also exhibited flexi-bility for laboratory measurements of discrete samples in thelab and at sea. The adaptability of the hardware and softwareallow the measurement of eutrophic coastal waters as well aslower nutrient shelf waters. The generic analyzer design,largely due to the use of independently controlled micro-sole-noid pumps (Weeks and Johnson 1996), also makes it poten-tially adaptable to a wide variety of chemical analyses bychanging reagents, software configuration, and detector type.

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Submitted 14 July 2008Revised 16 December 2008

Accepted 19 December 2008

limnology and oceanography: methods · the analyzer is capable of sampling hourly and has a...

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