Carsten Frank1, Friedhelm Schroeder. 1. GKSS Research Centre, Institute for Coastal Research, Max-Planck-Strasse, 21502 Geesthacht, Germany.
Abstract
This article summarises the advantages of the sequential injection analysis (SIA) for the online determination of nutrients in coastal waters. It concentrates on techniques to improve the reliability of the gained data by continuously monitoring one or more standards and on the advantages of online standard additions and offline determination of manually collected samples with the online SIA system. These measures are advantageous during method development and validation and can be used to verify the system performance on a regular base to reduce the amount of erroneous results. No changes in the flow system are necessary and the sample throughput is only slightly reduced. These techniques have been applied to a SIA system which is able to simultaneously determine ammonium and phosphate at a rate of more than 100 samples per hour each and detection limits (3sigma) of 0.06 muM and 0.05 muM. Results from a campaign in summer 2005 are shown.
This article summarises the advantages of the sequential injection analysis (SIA) for the online determination of nutrients in coastal waters. It concentrates on techniques to improve the reliability of the gained data by continuously monitoring one or more standards and on the advantages of online standard additions and offline determination of manually collected samples with the online SIA system. These measures are advantageous during method development and validation and can be used to verify the system performance on a regular base to reduce the amount of erroneous results. No changes in the flow system are necessary and the sample throughput is only slightly reduced. These techniques have been applied to a SIA system which is able to simultaneously determine ammonium and phosphate at a rate of more than 100 samples per hour each and detection limits (3sigma) of 0.06 muM and 0.05 muM. Results from a campaign in summer 2005 are shown.
Online methods are
analytical methods aimed for the direct and fast determination of
analytes. They integrate—or are connected to—sampling and
sample pretreatment system which can deliver fresh drawn samples
directly to the analytical system. Such systems are used to either
avoid sample storage and all problems connected to it
[1-8], or they are used to gain analytical
results as fast as possible while monitoring fast changing systems
(e.g., as regulation parameters in bioreactors). Online sampling
and analysis systems are usually more complex and expensive than
manual sampling, sample pretreatment, and determination. However,
in many cases online systems are more suitable than manual
approaches, especially if large amounts of samples have to be
taken and analysed or the contamination risk during sample storage
and transport is too high [9].Depending on the operational area, online systems have
to fulfill different requirements. Systems located in remote
sampling stations have to be reliable but not necessarily fast,
flexible or mobile. More important are comparability and stability
which ideally should be proved by, for example, the automatic
determination of standards and spiked samples. Online systems used
for shipboard campaigns have to be reliable, fast and mobile.
While the mobility of a system is a relative feature, the
sensitivity is given by the respective application and the cruise
speed of the ship defines the required analysis time. Furthermore,
the requirements for the reliability of a shipboard online system
is slightly different: these systems are in most cases used for
campaigns lasting only several days with a tight schedule.
Therefore, the online system must work from the start to the end
of the campaign independently of interfering parameters like
temperature, wind speed, and wave height. In general, the
collected data should be supported by regular calibrations and
standard additions. Additionally, it is advantageous to manually
collect and pretreat samples and then analyse them with the
respective online analyser to eliminate errors due to the online
sampling and sample pretreatment system.A recently developed online sequential injection analysis system
(SIA) for the combined determination of ammonium and phosphate
[10, 11] is used to demonstrate the advantages of the SIA if
used in an online arrangement. Especially the use of a
programmable syringe pump and a multiport switching valve as an
autosampler replacement in addition to their normal functions leads
to an improved quality control for the online data. Several
campaigns were performed with this device of which one transect
was selected to underline the applicability of the methods
described here.
2. EXPERIMENTAL
2.1. Instrumentation
The analytical system used here consists of three analytical
procedures: sampling, sample pretreatment, and determination. On
the research vessel, Ludwig Prandtl, an in-situ pump—which is
part of the ship—is used to pump the seawater from an inlet at
the bow of the ship to the analyser. The water depth of the inlet
is about 1.20 m below the surface. To minimise the residence
time of the sample in the ship's tubing system, high flow rates
are generated by discharging the main part of the seawater using a
bypass at the end of the pipe. A second pump is used to pump the
water through a cross flow filter (Minikros M22M-100-01 N,
0.2 μm, mixed cellulose ester). The filtrate passes a tee
near to the valve (Knauer A1492) of the SIA analyser. The valve
itself is a 17-port/1-channel type where the central port is
connected via a 120 cm (0.8 mm i.d.) holding loop to the
syringe pump. The valve was selected due to its high
reliability—proven during another project [12]—and its high speed (about 0.2 seconds from port to port). During the whole
project with more than five shipboard campaigns and uncounted days
in the lab, the seal had to be exchanged only once, and the valve
only failed twice due to neglected service (missing grease). Two
other valves from different companies were tested and one failed
due to unreliable electronics and the other's seal had to be
replaced after only five days shipboard campaign. The syringe pump
is a standard series CAVRO xl 3000 which is able to perform speed
ramps. These configurable speed ramps are especially important to
reduce pressure peaks if high pump speeds are chosen. The risk of
vacuum conditions in the reaction loop or cuvette during
deceleration—which can lead to unwanted air bubbles—can be
reduced by selecting appropriate speed ramps.Two different fluorescence detectors are used in this setup
(see Figure 1). A Hitachi F1000 fluorescence spectrometer
(ex. 365 nm, emm. 425 nm) is used for the determination of
ammonium. It is connected to an HP 34401A digital multimeter which
is used as an analog-to-digital converter. The Hitachi fluorescence
spectrometer is connected to the valve via three identical
reaction loops (60 cm; 0.8 mm i.d.) which are heated using
home-made pipe system connected to a Haake DC 50 heating bath.
Phosphate is determined via a fluorescence detector (ex.
470 nm, emm. 550 nm) provided by IPHT Jena (Germany). It
is connected via a reaction loop (60 cm; 0.8 mm i.d.) to
the valve and uses a digital multimeter with RS232 connection
(keithley model 2000) as an analog-to-digital converter. All
components (the syringe pump, the valve, the multimeters, and the
heating bath) are connected via RS232 to a personal computer which
controls the whole setup by scripts written in the python
programming language.
Figure 1
Scheme of the SIA used for the fast determination of
ammonium and phosphate. RA: reagent for the determination of
ammonium, RP1: reagent one for the phosphate determination, RP2:
reagent two for the phosphate determination, rl 1–3: reaction
loops for the determination of ammonium, rl 4: reaction
loop for the determination of phosphate.
The ammonium determination is based on the reaction of
o-phthaldialdehyde (OPA) with sodium sulfite and ammonium to a
fluorescent product. This reaction needs about 60 seconds at
85°C to achieve about 70% of the maximal fluorescence
signal. To achieve a sample throughput higher than 60 samples per
hour, at least three reaction loops have to be used in parallel.
In the example presented here, three parallel reaction loops were
used for the determination of ammonium.A combined phosphate and ammonium determination starts with an
ammonium readout step which is used to determine the fluorescence
of the reagent-sample segment. This segment was loaded into the
actual reaction loop exactly 60 seconds (three cycles) afore (see
Figure 2).
Figure 2
Succession of ammonium load, readout, and phosphate determination steps.
After this readout step, the load step starts with the aspiration
of 8.3 μl ammonium reagent (RA) followed by
25.0 μl sample and 16.7 μl RA into the holding
loop. The whole reagent-sample segment is then pumped through the
valve into the heated part of reaction loop 1. After an idle
time—which is calculated based on a statistical evaluation of
prior measurements—25 μl phosphate reagent 1 (RP1)
followed by 50 μl sample, 10 μl phosphate reagent
2 (RP2), and 25 μl RP1 are aspirated. This segment is
pumped through the valve, reaction loop 4, and the second detector
following a certain speed profile. This speed profile ensures
sufficient dispersion in the reaction loop, low pump speed in the
detector and high speed to flush the system.This procedure is repeated for all three ammonium reaction loops
and then starts again from the beginning until the programme is
stopped.
3. REAGENTS
All reagents were prepared with fresh-drawn degassed deionised
water. Sigma analytical grade chemicals were used, unless otherwise stated.
3.1. Ammonium
O-phthaldialdehyde (OPA) stock solution was prepared by dissolving
2 g of o-phthaldialdehyde (Sigma P-1378) in 25 ml ethanol.
This solution has to be shaken for several minutes to achieve
complete dissolution. 2 g of sodium sulfite were dissolved in
250 ml to prepare the sulfite stock solution.Ammonium reagent (RA). 7.5 g of disodium tetraborate
decahydrate were diluted to 250 ml. The solution was stirred
until complete dissolution and then transferred into a dark glass
bottle. 5 ml of OPA stock solution were added. After stirring
500 μl of sulfite stock solution and 0.1 ml of a 30%
Brij (Merck 1.01894) solution were added. After stirring, the
solution was left to stand for several hours [10, 13].Ammonium standard stock solution was 1 g (NH)/l from Merck.
3.2. Phosphate
Rhodamine stock solution was prepared by dissolving 0.20 g of rhodamine 6G in 100 ml water. Molybdate stock solution was made by dissolving 12.8 g of ammonium heptamolybdate
tetrahydrate (Merck, analytical grade) in 100 ml water. To prepare reagent 1 (RP1), 200 μl rhodamine 6G stock solution was added to 90 ml water. 500 μl 5% IGEPAL (Polyoxyethylene(∗)octylphenyl ether, branched) was added and the solution diluted to 100 ml. Reagent 2 (RP2) was prepared by adding 8.45 ml of 30% (v/v) hydrochloric acid to about 75 ml of water. Add 4 ml of molybdate stock solution and
dilute to 100 ml. The reagents RP1 and RP2 were derived from Wei et al. [10, 14].Phosphate standard stock solution was 1 g (PO)/l from Merck.
4. RESULTS AND DISCUSSION
While laboratory conditions are usually stable and clean, the
conditions at online sampling sites can be less favourable. On a
ship, for example, the conditions can be even more inadequate with
variations in temperature, vibrations, and high accelerations.
Especially spectrometers can be sensitive to
vibrations and temperature changes and may therefore have
variations in their sensitivity. Other problems may occur due to
variations in the ambient temperature which affect the stability
of the reagents.To avoid inconclusive results, a method was established to ensure
continuous recording of the performance of the SIA system. One or
more standards are prepared and connected to the valve. These
standards are determined automatically on a regular base following
a certain order. All measured peaks are instantly integrated and
continuously displayed in a graph as tentative results. Any
deviation from the expected behaviour (compared to former results
in the same or similar areas) can be nearly instantly recognised.
A second graph displays the raw data from the detector showing the
last peaks in detail. This graph is on the one hand checked on a
regular basis for irregularities and on the other hand in case
that the first graph shows unexpected results. Nearly all problems
usually occurring in a SIA system cause an inconsistency in the
baseline or peakshape. Most inconsistencies are typical for
certain problems and can therefore be used to find the source of a
problem more easily. The raw data is also saved on the hard
disk of the computer and can be reviewed any time later.While problems with the SIA system can be almost certainly ruled
out by reviewing the stability of the determination of the
standards and by consulting the raw data, problems with
the sampling or the sample pretreatment system
cannot be ruled out this way. The most sensible approach to
eliminate these problem sources is to manually collect and
pretreat a sample and then connect it to an additional valve port.
The determination of this sample is then intergated into the
normal SIA programme flow. Using this system, the manually
collected sample can be determined contemporary (some minutes
later) to the online sample with the same system without
interrupting the online determination. In addition to the
determination with the online system, a part of this sample can be
preserved and determined later with a standardised laboratory
method. This eliminates any problems concerning the comparability
of the online sample with the manually collected one.Two more techniques can be used to improve the quality of the
gained data. First, online standard addition and sample dilution
can be performed by dividing the sample volume into sections with
standard and sample. While this procedure is not applicable in all
cases (e.g., the volumes of the sections must be large enough to
ensure precise dosing and the reaction loop must be long enough to
ensure sufficient mixing between sample and standard) and can not
replace the manual method due to its imprecision, this procedure
is nevertheless useful to monitor the influence of changes of the
sample matrix (e.g., marine and river water in coastal areas) to
the performance of the method. The second technique to improve
data reliability is the application of two different methods in
one system. As has been shown by Frank et al. [10], two different analytical methods can be used in one SIA system
without interfering each other. This approach can be used to
compare two methods for the same analyte without the need for an
independent extra analytical system.
4.1. Example: verification of analytical results with
an unexpected variability during the online
determination of ammonium and phosphate
The techniques suggested above were used to improve the
reliability of data gained of the online measurements of a new
sequential injection analysis-based ammonium and phosphate
analyser. This analyser is used to determine nutrients during
campaigns on the North Sea and the Wadden Sea.The example described here is an excerpt of a dataset gained
during a three-week campaign on the North Sea in summer 2005. Part
of this campaign was a transect from Buesum to Helgoland at July
the 9th during which the results of the online determinations of
both nutrients showed an unexpected variability. The expected
nutrient distribution of such a transect includes an increase of
the nutrient concentration roughly correlated to the distance to
the shore and comparably small inhomogeneities on the high seas.However, Figures 3 and 4 indicate either a
very uneven nutrient distribution which does only remotely
resemble the expected nutrient distribution or a problem with the
sequential injection analysis system and the online sampling
system. To eliminate analytical errors, all data collected during that transect was reviewed using the method described above.
Figure 3
Ammonium data gained with the SIA system during a trip
from Helgoland to Eidersperrwerk in summer 2005. The results of
only one of the three ammonium “channels” (reaction loops) are
shown. Blank (bottom line), 3.6 μM standard (line at about
0.8 counts) and sample are shown.
Figure 4
Phosphate date gained contemporaneously to the ammonium
data displayed above. The vertical lines indicate the points in
time when the sensitivity of the system was changed by changing
the sample volume [11]. Blank (top line), 0.52 μM and 1.56 μM standard are shown next to the sample.
The first step of this review is shown in Figures 3 and 4, in which the online sample as well as the standards
are plotted against the time. In both graphs, the blank as well as
the standard are stable during the whole period of more than five
hours. This leads to the assumption that the performance of the
SIA system was stable over the whole time period. Any change in
the performance of the SIA system would have also influenced the
determination results of the blank and/or the standard.During the second step of the review, the raw data of the
respective time period is analysed (extract in Figures 5
and 6) to exclude erroneous results due to, for
example, air bubbles in the sample. These air bubbles can occur
due to a high oxygen concentration in the water caused by high
algal primary production during sunny days. Neither the raw
phosphate nor the ammonium data did show any irregularities.
Figure 5
Raw data of all three ammonium channels gained during the same time as the data shown in Figure 3. The peaks marked with 1 are from the same “channel.” The channels are slightly different and are calibrated independently.
Figure 6
Raw data gained from the phosphate detector.
The third and last step of such a review would be the comparison
of manually collected and pretreated samples with the online
sample. However, due to the assumed inhomogeneity of the water
body and the proven inertness of the sampling and sample
pretreatment system (a circular pump and a cross-flow filter), the
manual samples were taken from the filtrate stream as indicated in
Figure 7. These seven minutes pooled samples were
integrated into the SIA system using a former unused valve port.
The results of these determinations are shown together with the
online data in the Figures 8 and 9. Together with the legitimate assumption that neither the pumping nor the
filtration did have a that significant effect on the sample, it
can be proposed that there may occur high variations in the
concentration of ammonium in the open sea.
Figure 7
Offline samples were taken from the filtrate stream.
Figure 8
Data gained with all three ammonium “channels” combined with the results of the offline samples. The offline samples
were determined with the same SIA system up to an hour after
online determination. The differences between the online
samples (dots) and the offline samples (diamonds) can be
explained with the high variability of the ammonium concentration
in the sample stream which is averaged by the higher sample volume
and the sampling time (about seven minutes) for the offline
samples.
Figure 9
Phosphate data in μM calculated from the values
indicated in Figure 4. Additionally, offline samples
(diamonds) are integrated into the diagram. The arrows point to
the theoretically corresponding online samples with the same
restrictions as explained in Figure 8.
It was found that the unexpected high variability of the
concentration of ammonium (and on a smaller scale also phosphate)
was most probably connected to the patchy bloom of the heterotroph
plankton Noctiluca which discharges high amounts of
ammonium and phosphate during cell lysis [15].
5. CONCLUSIONS
While all flow techniques are more or less suitable for online
analysis systems, the sequential injection analysis (SIA) is
especially qualified for online applications. Unlike all other
flow techniques, the SIA integrates the ability to perform quality
assuring measures in an automated manner without any supplementary
devices (e.g., valves or autosamplers). This leads to analytical
systems that are more portable than comparable systems which makes
these systems especially suitable for monitoring applications in
remote locations or on ships.
Authors: P C Gardolinski; G Hanraha; E P Achterberg; M Gledhill; A D Tappin; W A House; P J Worsfold Journal: Water Res Date: 2001-10 Impact factor: 11.236
Authors: Amanda J Lyddy-Meaney; Peter S Ellis; Paul J Worsfold; Edward C V Butler; Ian D McKelvie Journal: Talanta Date: 2002-12-06 Impact factor: 6.057