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Simplex optimisation of conditions for the determination of antimony in environmental samples by using electrothermal atomic absorption spectrometry
Talanta ELSEVIER
Talanta 44 (1997) 1241 1251
Simplex optimisation of conditions for the determination of antimony in environmental samples by using electrothermal atomic absorption spectrometry Iris Koch a, Christopher F. Harrington a, Kenneth J. Reimer b, William R. Cullen
~'*
~' University o[ British Columbia, Department o/ Chemistry 2036 Main Mall, Vaneouver, British Columbia, V6T IZI, Canada b Environmental Sciences Group, The Royal Military College o/' Canada, Kingston, Ontario, K7K 5LO, Canada
Received 15 April 1996: received in revised form 12 September 1996: accepted 13 September 1996
Abstract
Analysis of the total antimony in plant material was unsuccessful using the electrothermal atomic absorption spectrometry (ETAAS) conditions recommended by the instrument manufacturer. For this reason, an optimisation procedure utilising the Plackett-Burman method, simplex optimisation and visualisation of the generated response surface via principal components analysis, was carried out. The Plackett-Burman method was used to eliminate four of the initial variables chosen. Four variables (atomisation temperature, atomisation time, ash temperature and modifier concentration) were subsequently optimised using the composite modified simplex method and the results were visualised as a contour diagram, after reduction to two principal components. The optimised conditions were used for the analysis of both an acid digested pine needle standard reference material (NIST 1575) and a pond weed sample, collected from a contaminated site at Yellowknife Bay, Yellowknife, NWT, Canada. The total concentration of antimony present in the pine needles was statistically indistinguishable from the non-certified value, as was the value for the pond weed sample, compared with a value determined by neutron activation analysis (NAA). The results for the analysis of the pond weed sample by ETAAS agreed with those obtained from a subsequent analysis by inductively coupled plasma-mass spectrometry. :0 1997 Elsevier Science B.V. Keywords: Antimony; Electrothermal atomic absorption spectroscopy; Environmental samples: Simplex optimisation
and Plackett-Burman design
1. Introduction
A n t i m o n y has been f o u n d in biological, geological and water samples [1 4], and its toxicity has led the United States Environmental Protection * Corresponding author. Tel.: +1 604 8222938; fax: +1 604 8222847.
Agency (US-EPA) to consider it and its comp o u n d s priority pollutants [5]. C o m m o n techniques for determining the total a m o u n t o f a n t i m o n y include: inductively coupled plasma mass spectrometry (ICP-MS) or atomic emission spectroscopy (ICP-AES) and hydride generation, followed by different atomisation methods such as electrothermal or flame heated quartz tube atomic
0039-9140/97/$17.00 © 1997 Elsevier Science BN. All rights reserved. PII S0039-91 40( 96)021 68-6
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1. Koch et a l . / Talanta 44 (1997) 1241-1251
absorption spectroscopy (HG-QT-AAS) [1-3]. The preconcentration of antimony hydride in a graphite furnace, followed by atomisation has recently been developed as another method of analysis [6,7]. All these methods give low detection limits, but ICP based methods are expensive for routine analysis. Hydride generation may not give 100% recovery when non-hydride forming species are present in the sample and is labour intensive. Electrothermal atomic absorption spectroscopy (ETAAS) is a widely used analytical tool for the determination of many trace metals, including antimony, in a wide variety of sample matrices [8-11]. The use of ETAAS for the determination of total antimony is cost effective and simple, but no formal optimisation of conditions has been reported for plant samples. The very first studies [12] on the graphite furnace technique showed that the sample matrix has a pronounced effect on the absorbance signal observed for a particular element. These effects often lead to systematic errors when determining metals in complex organic matrices and result from substances not being fully volatilised prior to atomisation of the metal. Optimisation of instrumental conditions is therefore a prerequisite for development of an environmental analytical protocol using electrothermal AAS. Until recently it was usual to optimise a system using a one-factor-at-a-time-approach, in which each variable but one is held at a low level and the response is evaluated at the lower and the upper level of the factor being tested. Each variable is treated in turn, until the response is maximised or minimised, depending on the system. This approach is far from adequate because there is no guarantee that an optimum response will be found, it requires a large number of experiments to be carried out and the presence of inter-relationships between the variables (e.g., modifier concentration and ash temperature) means that the optimum obtained will depend on the initial conditions chosen. Factorial experiments, in which all the factors are varied simultaneously according to a pre-set design, have also been used to optimise analytical systems. However, this approach is highly dependent on the levels of each
factor and thus, it works best when some prior knowledge of the system is available. It also requires a large amount of experimentation when more than three variables are investigated. Simplex optimisation is a highly efficient, multifactor, empirical feedback, optimisation procedure, that does not require the large number of experiments nor the initial variable information that is necessary with the two methods outlined above. This procedure 'homes in' on the optimum response region by driving the experiments in the direction of steepest ascent of the response surface. The optimum thus obtained is generally a local optimum, but some assurance that it is the overall optimum can be obtained by repeating the search from different starting conditions to see if the same conditions are reached. Simplex optimisation is now routinely used as a method of maximising a response [13,14] or reducing interferences [15,16] in the analysis of trace elements. In the present work the use of the instrument manufacturer's recommended operating conditions [17] for the determination of antimony by ETAAS were completely unsuccessful, yielding no absorbance maximum. These conditions were: dry at 75°C for 5 s, then at 90°C for 60 s, then at 120°C for 10 s, hold at 120°C for 2 s, ramp to 2000°C in 1 s (maximum ramp rate), atomise at 2000°C for 3 s, clean at 2000°C for 1 s. A two stage approach was used to optimise the experimental conditions used for the determination of antimony in plant material. The first part of the investigation involved the use of the Plackett-Burman method to screen a number of potential variables to select the most appropriate to optimise using the composite modified simplex method [18,19]. The principle advantages of this approach are that information concerning the significance of each variable is obtained (PlackettBurman method) and the optimum conditions are efficiently reached, with less experimentation than would be necessary if none of the variables had been eliminated. Additionally, visualising the response surface eliminates the need for univariate searches around the optimum, which are often carried out to check that the optimum is correct. These goals are not possible using a one-step-at-atime-approach, or a factorial experiment.
1. Koch et al./Talanta 44 (1997) 1241 1251
To check the accuracy of the developed methodology the concentration of antimony in a pine needle standard reference material (SRM), NIST 1575, was determined. The pond weed sample was acid digested and methanol extracted and these samples were statistically compared with results obtained by ICP-MS, as well as by neutron activation analysis (NAA).
2. Experimental
2.1. Reagents Concentrated nitric and hydrochloric acids (both double sub-boiling distilled, Seastar Chemicals, Sidney, BC), concentrated sulphuric acid (Analytical grade, BDH Chemicals, Toronto, ON), and glacial acetic acid (Reagent grade, Fisher Scientific, Nepean, ON). Hydrogen peroxide (30%) (Assurance grade, BDH Chemicals, Toronto, ON), D-tartaric acid (Reagent grade, Allied Chemical Canada, Canada), palladium nitrate (Pd(NO3)2"2H20, Reagent grade, Sigma, St. Louis, MO), citric acid (Certified, Fisher Scientific, Fairlawn, N J). Water was purified to a final resistivity of better than 1 M ohm (Barnstead Mega-Pure system, Barnstead/Thermolyne, Dubuque, IA). Methanol (HPLC grade, Fisher Scientific, Nepean, ON). A methanol/water (1/1 v/v) solvent mixture was used to extract the aqueous antimony species. Antimony metal (Certified, Fisher Scientific, Fair Lawn, NJ) and 1000 mg 1 ~ indium (Spectroscopy standard, High-Purity Standards, Charleston, SC). The freeze dried pine needle standard reference material 1575, was obtained from the National Institute of Standards and Technology (NIST, Washington, DC). The pond weed sample (Potomogetan pectinatus) was collected from a site contaminated with mine tailings (Yellowknife Bay, NWT, Canada) as described previously [20] and freeze dried. The pine needle SRM (NIST 1575) was chosen as a representative standard reference material because it contains an uncertified antimony concentration of 0.2 mg kg ~.
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2.2. Preparation of samples and standards The pine needles (1575), and pond weed were dried to constant weight and then acid digested. Acid digestions were carried out in duplicate by adding 3 ml of concentrated nitric acid, 3 ml of 30% hydrogen peroxide, and 1 ml of concentrated sulphuric acid to a 250 ml round bottom flask containing pine needles (0.5 g) or pond weed (0.25-0.40 g) and refluxed for 3 h as described elsewhere [21]. An additional pine needle digestion was carried out by heating 1 g of material with the above acid/hydrogen peroxide mixture, in a vial on a hot plate, at 90°C for 3 h. After the digestions were complete, the partially evaporated samples were diluted to 5 ml (pine needles) and l0 ml (pond weed) using deionised water. Extraction of the pondweed was carried out by sonicating 0.5 g dry material with 10 ml methanol/water (1/1 v/v) for two samples, and 10 ml 0.2 M acetic acid for one sample. The sample and solvent were sonicated for 20 min, the mixture was centrifuged at 3000 rpm for 10 min and the supernatant was decanted. This was repeated five times and the combined extracts were evaporated under reduced pressure to dryness and made up to 5 ml with water. A stock solution of 1000 mg 1 1 antimony solution was prepared by dissolving 0.1000 g antimony metal in aqua regia and diluting to 100 ml with 1% D-tartaric acid. The 50 and 25 lag 1solutions for use in the standard additions determinations were prepared fresh daily from the stock. The palladium modifier solution was prepared by dissolving 0.1083 g palladium(II) nitrate dihydrate in 0.5 ml of concentrated nitric acid and diluting to 100 ml with 2% citric acid solution to give a 1000 mg 1-~ Pd solution. This stock solution was then diluted further with 2°/,, citric acid solution to give the various concentrations needed for the experiments. Indium solution was used as an internal standard in the ICP-MS determinations and was prepared by diluting an appropriate volume of a 200 ~tg 1 ~ standard solution so that the final concentration was 10 gg 1-~ in each sample.
1244
L Koch et al./Talanta 44 (1997) 1241 1251
2.3. Instrumentation
An atomic absorption spectrometer (Varian Techtron Model 1275, Australia) fitted with an auto-sampler, graphite furnace and programmer (GTA-95) was used throughout this work. The antimony hollow cathode lamp (SpectrAA, Varian, Australia) was operated at 10 mA with a slit corresponding to a spectral bandwidth of 0.2 nm and the 217.9 nm line was monitored. Continuous background correction was by a deuterium lamp (Varian, Australia). Pyrolytically coated graphite tubes (Varian, Germany) were used. The ICP-MS measurements were carried out using a VG PlasmaQuad 2 turbo plus instrument (VG Elemental, Fisons Scientific Equipment, Winsford, Cheshire, UK), operated at 1350 W RF power. Cooling, auxiliary and nebulizer gases (Ar) were at flow rates of 13.82, 0.69 and 1.00 1 rain ~, respectively. Masses were monitored in the peak jumping mode by using m/z 115 (In) and 12l (Sb). A real sample (pond weed digest diluted four times with deionised water) was used for the optimisation procedure outlined below. This sample was chosen, rather than an antimony standard, so that matrix and species dependent effects could be minimised and the antimony signal maximised. The OPTIMA3 computer program [18,19] was used for the simplex calculations and the generation of experimental conditions. The principal components analysis was carried out by using Systat~ 5.03 for windows (SYSTAT). Both of these programs were run under Windows ~ 3.1, on a DELL 466/M personal computer. NAA was carried out as described elsewhere [20,22]. 2.4. Plackett-Burman experiments
The initial variables chosen to be screened using the Plackett and Burman method were: dry time (Dt), dry temperature (DT), ash time (At), ash temperature (AT), atomisation ramp (AtR), atomisation time (Art), atomisation temperature (AtT) and modifier concentration (MC). This allowed for the use of three dummy variables and so had 3 df (see Table 1). Initial experiments
carried out using longer ash and atomisation times (up to 15 and 7 s, respectively) resulted in a short graphite tube lifetime (60 firings), thus limits for these variables were chosen to minimise tube deterioration. The limits for all the variables were chosen so as to show a change in measured absorbance, which was the response measured, rather than to reflect conditions usually used for ETAAS. After the first design was carried out, three variables (atomisation ramp, atomisation time and modifier concentration) were kept constant, whilst the effect of the other five variables were investigated using a N = 8 design (two dummy variables, 2 df) (see Table 2). The matrix designs, adapted from the method of Jones et al. [23], accompany the designations of variables in Table 1 and Table 2. 2.5. Simplex optimisation
The composite modified simplex (CMS) optimisation method described previously [18,19] was employed during this work. Having screened out the variables that did not have a significant effect on the response, the remaining four factors (atomisation temperature, atomisation time, ash temperature and modifier concentration) were optimised to provide the maximum antimony absorbance signal from a pond weed digestate. The upper and lower limits used in the CMS procedure as well as the stepsize for each variable are given in Table 3. Five initial experiments were conducted and the conditions tbr each factor, as well as the resulting absorbance, were entered into the OPTIMA3 computer program. The next set of experimental conditions were generated and carried out, and the response was entered, The simplex progressed via a series of reflections, expansions, contractions or fit points, towards the optimum absorbance (see Table 4). The process was continued until the standard deviation of the five highest responses was less than the value of the stepsize of the absorbance (0.010), three times sequentially. To prove that the optimum values determined were not due to a local region of maximum response, the procedure was repeated with different starting
+
4-
9 10 11 12
44--
44+
+ -
+ -
4-
_
At
70 90 3 1300 3 2300 1400 700 No change No change No change
U p p e r level ( + )
q +
+ -
+ 4-
-
4-
AT
+
-
+ +
4-
+
4-
Att
-
-
-
4-
4-
4-
44-
44-
-
_
44-
+ 4-
AtR
4-
AtT
~' E x p e r i m e n t s w e r e c a r r i e d o u t w i t h a c o n s t a n t injected v o l u m e o f 10 lal. b , 4 - , a n d " - ' s y m b o l s c o r r e s p o n d to t h e u p p e r a n d l o w e r levels o f v a r i a b l e values, as d e f i n e d b y the p r e c e d i n g table.
+
-
+
8
+
-
-
5 6 7
4-
+
-
3 4
4-
4-
4-b
1
2
Matrix
DT
Dt
Expt
L o w e r level ( - )
30 60 1 1000 1 1800 260 100 No change No change No change
Variable
Designation Dt D r y t i m e (s) DT D r y t e m p e r a t u r e (°C) At A s h t i m e (s) AT A s h t e m p e r a t u r e (°C) Art A t o m i s a t i o n t i m e (s) AtT A t o m i s a t i o n t e m p e r a t u r e (°C) AtR A t o m i s a t i o n r a m p (°/s) MC M o d i f i e r c o n c e n t r a t i o n ( r a g 1 1 pd)a D Dummy D Dummy D Dummy
Code
Table 1 P l a c k e t t - B u r m a n d e s i g n (N = 12) f o r the d e t e r m i n a t i o n o f s i g n i f i c a n t v a r i a b l e s to o p t i m i s e b y u s i n g s i m p l e x o p t i m i s a t i o n
4-
444-
4-
4-
m
MC
4-
-
4-
4+ 4-
4-
-
_
D
-
4-
-t-
+ 44-
-
_
4-
D
+
+
-
4-
44-
_
_
4-
--
D
4~
I
k~
{:
1. Koch et al./Talanta 44 (1997) 1241-1251
1246
Table 2 Plackett-Burman design (N = 8) for the determination of additional significant variables to optimise by using simplex optimisation Code
Variable
Lower level ( - )
Upper level ( + )
Designation Dt Dry time (s) DT Dry temperature (°C) At Ash time (s) D Dummy AT Ash temperature (°C) AtT Atomisation temperature (°C) D Dummy
30 60 1 No change 800 1800 No change
70 90 3 No change 1400 2300 No change
Expt.
Dt
DT
At
D
AT
AtT
1
+a
+
+
_
+
_
_
2
+ +
+ + -
+ + +
+ + + -
+ + + -
+ + + +
+ + +
+
-
-
+
D
Matrix
3 4 5 6 7 8
+
.
" ' + ' and ' - '
+
.
.
.
-
.
.
.
symbols correspond to the upper and lower levels of variable values, as defined by the preceding table.
conditions; the same optimum conditions were found.
2.6. Visualisation of the response surface The experimental results were analysed by using principal components analysis, as described in detail and with examples by Molinero [24]. Briefly, principle components analysis was used to reduce the four variables from the simplex optimisation to two new variables (principle components 1 and 2). The scores of these principle components give coordinates for all the
experimental vertices. Thus, the vertices of the simplex previously represented by n variables, are now represented by two variables, and the responses are plotted against these variables, to generate the response surface. The relative significance of the effects of the original variables on the responses can be evaluated by considering the loading of each variable on each principle component, which indicates to what degree each principle component is influenced by each of the original variables. This approach provides visual information on the optimum and the response surface, which is not possible with the simplex
Table 3 Range and stepsize of the variables being optimised by the composite modified simplex method Variable
Lower limit
Upper limit
Stepsize"
Atomisation temperature (°C) Atomisation time (s) Ash temperature (°C) Modifier concentration (rag 1-~)b
1400 0 800 100
2700 4 1600 900
100 1 50 100
Same units as variables. Experiments carried out with a constant injected volume of 10 lal.
I. Koch et al. /Talanta 44 (1997) 1241 1251
1247
Table 4 Simplex experiments and responses Expt. No.
Atomisation temp. (°C)
Atomisation time (s)
Ash temp. (°C)
Modifier conc. (mg 1 ~)~
Point type b
Response c (absorbance)
l 2 3 4 5 6 7 8 9 l0 11 12 13 14 15 16 17 18 19 20 21 22 23 a 24 25 26 27 28 29
18110 1800 2200 2400 2400 2100 2700 2500 2300 2700 2600 24(10 2100 1800 1700 2400 2300 2200 2000 2300 2000 2300 22110 2000 2300 2300 2300 2200 2000
0 3 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
1400 800 1000 1400 1400 1100 1050 1600 800 1050 1600 1050 1450 1600 1600 1200 1600 1250 1600 1200 1300 1400 1350 1250 1350 1350 1450 1400 1550
500 500 900 200 200 500 200 100 600 100 100 400 500 600 700 300 300 500 500 400 700 300 400 600 300 400 300 400 500
1 1 1 I I R R R C R R C R E R C R C R C R C F R C F R C R
0,1(13 0,056 0,085 0.179 0.026 0.145 0.139 0.000 0.116 0.138 0.000 0.155 0.264 0.055 0.048 0.217 0.009 I).204 0.043 0.167 0.105 0.266 0.280 0.129 0.258 0.262 0.214 0.270 0.128
" Constant volume of 10 gl. b Initial (I), reflection (R), contraction (C), extension (E) and fit (F). c Response is mean of three determinations, a Optimum conditions.
search alone. The response surface can be studied to determine more information such as the presence or absence of ridge features or local maxima. It also helps to show other factor levels that could
provide better experimental conditions in terms of lower temperature operating conditions, or less modifier, thus resulting in a more cost effective procedure.
Table 5 t Values for 12 and 8 variable designs used in the Plackett-Burman experiments Variables
Dt
DT
At
AT
An
AtT
AtR
MC
12 8
- 1.58 - 0.54
2.55 - 0.79
-0.97 - 2.34
1.74 14.90"
-4.46* -
-0.83 18.20*
-2.46 -
3.49* -
* Indicates that the variable is significant at the 95% confidence level.
1248
I. Koch et al./Talanta 44 (1997) 1241-1251 2.0
i
i
i
I
i
3_
i
Atomisation temperature •
2
i
!
•
•. . . . . . . . . . .
15 1
Ash temperature
~o
o I-
ASh time LL
0 <
ummy 05['jDrytemperature
r!
-1
-2
O0 "1" r ~ 0
LL
,.,ylte,mJ
,
J
I
,
20
30
40
50
60
10
70
-3 -3
Variable effect
Fig. 1. Birnbaun plot for the second Plackett-Burman, showing the significance of the two variables atomisation temperature and ash temperature.
3. Results and discussion 3. I, P l a c k e t t - B u r m a n
experiments
The results for the first Plackett-Burm experiment were used to obtain a minimum t value of 3.18 for a 95% confidence interval. Only the atomisation time and modifier concentration give t values above this and so are the only significant variables at this confidence level (Table 5). Birnbaun plots can be used to confirm or help clarify results obtained from such experiments, as explained in more detail elsewhere [23]. Briefly, deviance of points from a straight line indicate large variable effects [14]. In this instance, the Birnbaun
-2
1
0
1
2
FACTOR(2)
Fig. 2. Contour diagram showing the response surface for the first optimisation.
plot (not shown) gives essentially a straight line and therefore does not help with the further interpretation of this experiment. The second Plackett-Burman experiment was carried out by holding three factors constant and hence utilised five of the original variables and two dummies (2 df). The atomisation time and modifier concentration shown to be important by the first experiment were held constant at 0 s and 500 mg 1 1, respectively, in the hopes that any other significant variables might be revealed. The ramp rate was observed in these and preliminary experiments to give maximum results at higher speeds, as noted by Pergantis et al. [l 1] in their optimisation for arsenic. Instrumental constraints
Table 6 The optimised furnace program, used for quantitation of antimony in plant samples (400 mg L - 1 or 4 pg Pd as modifier was used) Step No.
Temperature (°C)
Duration (s)
Gas flow (L m i n - t Ar)
Function
1 2 3 4 5 6 7
90 120 1350 1350 1350 2200 2200
30 10 1.9 2 1 0.5 3
3 3 3 3 0 0 3
Dry/ramp Dry/ramp Ash/ramp Ash/hold Ash/gas off Atom/ramp" Clean
" 2000°C s-~ ramp from 1350°C to 2200°C, integration during this step.
1. Koch et al./Talanta 44 (1997) 1241 1251 Table 7 Concentration of antimony (mg kg t dry weight) in pine needles (NIST 1575) after analysis by ETAAS Sample Total digest 1~ Total digest 2 Total digest 3
ETAAS analysis _+ S.D. ~
Comparison to
0.220 +_0.012 0.208 + 0.019~ 0.231 + 0.044
nsdd at 98% nsd at 95% nsd at 95%
SRM b
Precision expressed as standard deviation (S.D.) based on five analytical replicates, except where indicated. h Antimony concentration (0.2 mg kg ~). " Hot plate digestion. a nsd: not significantly different at confidence level indicated. Four analytical replicates. limited the r a m p to 2000°C s - ~ a n d this value was used for all subsequent experiments. T h e results for the second e x p e r i m e n t p r o d u c e d a m i n i m u m t value at the 95% confidence interval o f 4.3 a n d the t values for the two variables, ash a n d a t o m i s a t i o n t e m p e r a t u r e were greater, indicating t h a t these variables have a significant effect on the a n t i m o n y response. T h e B i r n b a u n p l o t in Fig. 1 shows that the ash a n d a t o m i s a t i o n temperatures deviate f r o m a straight line because o f large variable effects, which confirms the significance o f these variables. F o u r variables: a t o m i s a t i o n time, a t o m i s a t i o n t e m p e r a t u r e , ash t e m p e r a t u r e a n d modifier concentration, were s u b s e q u e n t l y o p t i m i s e d b y using the c o m p o s i t e m o d i f i e d simplex p r o c e d u r e (CMS).
1249
3.2. S i m p l e x optimisation A total o f 29 e x p e r i m e n t s were carried o u t a n d the m a x i m u m response was r e a c h e d after 23 exp e r i m e n t s (see T a b l e 4). T h e o p t i m u m p a r a m e t e r s were f o u n d to be: a t o m i s a t i o n t e m p e r a t u r e , 2200°C; a t o m i s a t i o n time, 0 s; ash t e m p e r a t u r e , 1350°C; a n d modifier c o n c e n t r a t i o n , 400 m g 1 T h e simplex analysis was r e p e a t e d f r o m different initial c o n d i t i o n s a n d the m a x i m u m response was: a t o m i s a t i o n t e m p e r a t u r e , 2200°C; a t o m i s a t i o n time, 0 s; ash t e m p e r a t u r e , 1450°C; a n d modifier c o n c e n t r a t i o n , 400 m g 1 ~. These c o n d i t i o n s were reached after 22 e x p e r i m e n t s f r o m a total o f 27. The c o n d i t i o n s f r o m the first o p t i m i s a t i o n are considered to be better for routine use, because the lower ash t e m p e r a t u r e is less destructive to the g r a p h i t e cuvette. The response surfaces g e n e r a t e d from b o t h searches are n o t identical, b u t the characteristic ridge feature o f high a b s o r b a n c e is present in b o t h (see Fig. 2 for the response surface generated from the first simplex). T h e results for the principle c o m p o n e n t s analysis ( P C A ) indicate t h a t the first a n d second principle c o m p o n e n t s (PC) retain 43.8 a n d 31.5%, respectively o f the original variance o f the data. This is similar to values r e p o r t e d in previous w o r k [24]. T h e results also d e m o n s t r a t e that the a t o m i s a t i o n t e m p e r a t u r e a n d modifier c o n c e n t r a t i o n have the greatest influence on the first PC, whereas ash t e m p e r a t u r e has the greatest
Table 8 Comparison of the concentrations of antimony (mg kg I dry weight) in pond weed samples from Yellowknife, NWT, Canada Sample Extract
Id
Extract 2 Extract 3 Total digest I Total digest 2
Determined by ETAAS _+S.D. "
Determined by ICP-MS +_S.D. b
Comparison ~
0.28 + 0.04 0.26 + 0.02~ 0.28 + 0.02 39 + 5 40 _+5
0.222 + 0.003 0.221 + 0.002 0.179 + 0.003 32.6" 41.8 ~
nsd nsd nsd nsd nsd
Determination by optimised ETAAS and ICP-MS. Precision expressed as standard deviation (S.D.) based on five analytical replicates, except where indicated. b Two analytical replicates except where indicated. nsd, not significantly different at confidence level indicated. J Acetic acid/water extraction. Four analytical replicates. t"No replication.
at at at at at
95% 95% 98% 98% 95%
1250
1. Koch et al. /Talanta 44 (1997) 1241-1251
influence on the second PC. Generation of the response surface also eliminates the need to carry out univariate searches around the optimum to establish that it is correct. Therefore, after carrying out the simplex optimisation twice, from two different starting conditions and then analysing each response surface using principle components analysis, it was felt that further univariate investigates of the optimum were unnecessary.
3.3. Analysis" of samples by using the optimised temperature program The optimised procedure (Table 6) was used to determine the antimony concentration in pine needle SRM and pond weed, by using ETAAS and the method of standard additions. The results obtained for analysis of the pine needles are shown in Table 7, along with a comparison to the reference value. The concentrations for pine needles, with an average observed concentration of 0.220 mg kg ~, do not differ significantly from the non-certified concentration of 0.2 mg kg 1 The pond weed sample is from a contaminated site near a gold mine in the Northwest Territories, Canada. The concentration of antimony in this sample was determined by ICP-MS to verify the values obtained by ETAAS and the results are given in Table 8. The results for the two methods do not differ significantly, as shown by the statistical comparison. The concentration of antimony for each digestion does not differ significantly (95'70 level) from the value determined by neutron activation analysis of 41.2 mg kg k-~. The aqueous phase soluble antimony species were extracted from the pond weed sample with 1/1 methanol/water (V/V), so that further analysis by speciation techniques such as HPLC-ICP-MS or HG-GC-MS [24] can be carried out. However, prior to this it is important to establish the total antimony concentration, both hydride and nonhydride forming, present in the extract. Although the values obtained for the methanol/water extracts after analysis by ETAAS and ICP-MS do not differ statistically, consistently lower values for the ICP-MS results were observed. This is probably due to matrix or solvent effects, as the
ETAAS analyses were carried out by using the method of standard additions, whereas the ICPMS analyses were carried out using external calibration with aqueous standards. By the analysis of the SRM and the methanol/ water extract the optimised ETAAS procedure for the determination of antimony has been shown to overcome any interferences due to the sample matrix and any differences due to the different antimony species present. In addition, the method can be used for any total antimony determinations in samples of plant origin.
Acknowledgements The authors would like to thank Dr M. Dodd for provision of the pond weed samples and NAA results, Mr B. Mueller for help with ICP-MS analysis, Ms M. Winters for assistance with sample preparation and Dr A. Wade for comments on the manuscript. We would like to acknowledge Dr K.J. Reimer, Environmental Sciences Group, Kingston, Ontario and the Natural Sciences and Engineering Research Council of Canada for financial assistance.
References [1] M.O. Andreae, J.-F. Asmode, P. Foster and L. Van't Dack, Anal. Chem., 53 (1981) 1766. [2] X. Lu, J. Li, S. Chen and D. Guosheng, Acta Ocean. Sinica, 9 (1990) 255. [3] R. Kantin, Limnol. Oceanogr., 28 (1983) 165. [4] H. Onishi, and E.B. Sanddl, Geochim. Cosmochim. Acta, 8 (1955) 213. [5] L.H. Keith, and W.A. Telliard, Environ. Sci. Technol., 13 (1979) 416. [6] M. Walcerz, S. Garbos, E. Balska and A. Hulanicks, Fresenius J. Anal. Chem., 350 (1994) 662. [7] R.E. Sturgeon, S.N. Willie and S.S. Berman, Anal. Chem., 57 (1985) 2311. [8] R.E. Sturgeon, Can. J. Spectrosc., 32 (1987) 79. [9] J.G.S. Gupta and J.L. Bouvier, Talanta, 42 (1995) 269. [10] M.T. Perez-Corona, M.B. De La Calle-Guntinas, Y. Madrid and C. Carmara, J. Anal. At. Spectrom., 10 (1995) 321. [11] S.A. Pergantis, W.R. Cullen and A.P. Wade, Talanta, 41 (1994) 205.
1. Koch et al. ,. Talanta 44 (1997) 1241
[12] B. Welz, Atomic Absorption Spectrometry, 2nd edn., VCH, Wenheim, 1985, p. 64 159. [13] M.J. Ford, L. Ebdon, R.C. Hutton and S.J. Hill, Anal. Chim. Acta, 23 (1994) 23. [14] D.J. Roberts and K.V. Kahokola, J. Anal. At. Spectrom., 4 (1989) 185. [15] T. Van der Velde-Koerts and J.L.M. de Boer, J. Anal. At. Spectrom., 9 (1994) 1093. [16] S.J. Hill, M.J. Ford and L. Ebdon, J. Anal. At. Spectrom., 7 (1992) 719. [17] T. Mackenzie, in E. Rothery (Ed.), Analytical Methods for Graphite Tube Atomizers, Varian, Australia, Publication No. 85-100447-00, 1982, pp. 43.
1251
1251
[18] D. Betteridge, A.P. Wade and A.B. Howard, Talanta, 32 (1985) 709. [19] D. Betteridge, A.P. Wade and A.B. Howard, Talanta, 32 (1985) 723. [20] D.A. Bright, W.T. Dushenko and K.J. Reimer, Aquat. Bot., 50 (1995) 141. [21] S. Bajo, B. Surer and B. Aeschliman, Anal. Chim. Acta, 149 (1983) 321. [22] D.A. Bright, B. Coedy, W.T. Dushenko and K.J. Reimer, Sci. Tot. Environ., 155 (1994) 237. [23] K. Jones, Int. Lab., November (1986) 32. [24] M.L. Molinero, Anal. China. Acta, 297 (1994) 417.
Talanta 44 (1997) 1241 1251
Simplex optimisation of conditions for the determination of antimony in environmental samples by using electrothermal atomic absorption spectrometry Iris Koch a, Christopher F. Harrington a, Kenneth J. Reimer b, William R. Cullen
~'*
~' University o[ British Columbia, Department o/ Chemistry 2036 Main Mall, Vaneouver, British Columbia, V6T IZI, Canada b Environmental Sciences Group, The Royal Military College o/' Canada, Kingston, Ontario, K7K 5LO, Canada
Received 15 April 1996: received in revised form 12 September 1996: accepted 13 September 1996
Abstract
Analysis of the total antimony in plant material was unsuccessful using the electrothermal atomic absorption spectrometry (ETAAS) conditions recommended by the instrument manufacturer. For this reason, an optimisation procedure utilising the Plackett-Burman method, simplex optimisation and visualisation of the generated response surface via principal components analysis, was carried out. The Plackett-Burman method was used to eliminate four of the initial variables chosen. Four variables (atomisation temperature, atomisation time, ash temperature and modifier concentration) were subsequently optimised using the composite modified simplex method and the results were visualised as a contour diagram, after reduction to two principal components. The optimised conditions were used for the analysis of both an acid digested pine needle standard reference material (NIST 1575) and a pond weed sample, collected from a contaminated site at Yellowknife Bay, Yellowknife, NWT, Canada. The total concentration of antimony present in the pine needles was statistically indistinguishable from the non-certified value, as was the value for the pond weed sample, compared with a value determined by neutron activation analysis (NAA). The results for the analysis of the pond weed sample by ETAAS agreed with those obtained from a subsequent analysis by inductively coupled plasma-mass spectrometry. :0 1997 Elsevier Science B.V. Keywords: Antimony; Electrothermal atomic absorption spectroscopy; Environmental samples: Simplex optimisation
and Plackett-Burman design
1. Introduction
A n t i m o n y has been f o u n d in biological, geological and water samples [1 4], and its toxicity has led the United States Environmental Protection * Corresponding author. Tel.: +1 604 8222938; fax: +1 604 8222847.
Agency (US-EPA) to consider it and its comp o u n d s priority pollutants [5]. C o m m o n techniques for determining the total a m o u n t o f a n t i m o n y include: inductively coupled plasma mass spectrometry (ICP-MS) or atomic emission spectroscopy (ICP-AES) and hydride generation, followed by different atomisation methods such as electrothermal or flame heated quartz tube atomic
0039-9140/97/$17.00 © 1997 Elsevier Science BN. All rights reserved. PII S0039-91 40( 96)021 68-6
1242
1. Koch et a l . / Talanta 44 (1997) 1241-1251
absorption spectroscopy (HG-QT-AAS) [1-3]. The preconcentration of antimony hydride in a graphite furnace, followed by atomisation has recently been developed as another method of analysis [6,7]. All these methods give low detection limits, but ICP based methods are expensive for routine analysis. Hydride generation may not give 100% recovery when non-hydride forming species are present in the sample and is labour intensive. Electrothermal atomic absorption spectroscopy (ETAAS) is a widely used analytical tool for the determination of many trace metals, including antimony, in a wide variety of sample matrices [8-11]. The use of ETAAS for the determination of total antimony is cost effective and simple, but no formal optimisation of conditions has been reported for plant samples. The very first studies [12] on the graphite furnace technique showed that the sample matrix has a pronounced effect on the absorbance signal observed for a particular element. These effects often lead to systematic errors when determining metals in complex organic matrices and result from substances not being fully volatilised prior to atomisation of the metal. Optimisation of instrumental conditions is therefore a prerequisite for development of an environmental analytical protocol using electrothermal AAS. Until recently it was usual to optimise a system using a one-factor-at-a-time-approach, in which each variable but one is held at a low level and the response is evaluated at the lower and the upper level of the factor being tested. Each variable is treated in turn, until the response is maximised or minimised, depending on the system. This approach is far from adequate because there is no guarantee that an optimum response will be found, it requires a large number of experiments to be carried out and the presence of inter-relationships between the variables (e.g., modifier concentration and ash temperature) means that the optimum obtained will depend on the initial conditions chosen. Factorial experiments, in which all the factors are varied simultaneously according to a pre-set design, have also been used to optimise analytical systems. However, this approach is highly dependent on the levels of each
factor and thus, it works best when some prior knowledge of the system is available. It also requires a large amount of experimentation when more than three variables are investigated. Simplex optimisation is a highly efficient, multifactor, empirical feedback, optimisation procedure, that does not require the large number of experiments nor the initial variable information that is necessary with the two methods outlined above. This procedure 'homes in' on the optimum response region by driving the experiments in the direction of steepest ascent of the response surface. The optimum thus obtained is generally a local optimum, but some assurance that it is the overall optimum can be obtained by repeating the search from different starting conditions to see if the same conditions are reached. Simplex optimisation is now routinely used as a method of maximising a response [13,14] or reducing interferences [15,16] in the analysis of trace elements. In the present work the use of the instrument manufacturer's recommended operating conditions [17] for the determination of antimony by ETAAS were completely unsuccessful, yielding no absorbance maximum. These conditions were: dry at 75°C for 5 s, then at 90°C for 60 s, then at 120°C for 10 s, hold at 120°C for 2 s, ramp to 2000°C in 1 s (maximum ramp rate), atomise at 2000°C for 3 s, clean at 2000°C for 1 s. A two stage approach was used to optimise the experimental conditions used for the determination of antimony in plant material. The first part of the investigation involved the use of the Plackett-Burman method to screen a number of potential variables to select the most appropriate to optimise using the composite modified simplex method [18,19]. The principle advantages of this approach are that information concerning the significance of each variable is obtained (PlackettBurman method) and the optimum conditions are efficiently reached, with less experimentation than would be necessary if none of the variables had been eliminated. Additionally, visualising the response surface eliminates the need for univariate searches around the optimum, which are often carried out to check that the optimum is correct. These goals are not possible using a one-step-at-atime-approach, or a factorial experiment.
1. Koch et al./Talanta 44 (1997) 1241 1251
To check the accuracy of the developed methodology the concentration of antimony in a pine needle standard reference material (SRM), NIST 1575, was determined. The pond weed sample was acid digested and methanol extracted and these samples were statistically compared with results obtained by ICP-MS, as well as by neutron activation analysis (NAA).
2. Experimental
2.1. Reagents Concentrated nitric and hydrochloric acids (both double sub-boiling distilled, Seastar Chemicals, Sidney, BC), concentrated sulphuric acid (Analytical grade, BDH Chemicals, Toronto, ON), and glacial acetic acid (Reagent grade, Fisher Scientific, Nepean, ON). Hydrogen peroxide (30%) (Assurance grade, BDH Chemicals, Toronto, ON), D-tartaric acid (Reagent grade, Allied Chemical Canada, Canada), palladium nitrate (Pd(NO3)2"2H20, Reagent grade, Sigma, St. Louis, MO), citric acid (Certified, Fisher Scientific, Fairlawn, N J). Water was purified to a final resistivity of better than 1 M ohm (Barnstead Mega-Pure system, Barnstead/Thermolyne, Dubuque, IA). Methanol (HPLC grade, Fisher Scientific, Nepean, ON). A methanol/water (1/1 v/v) solvent mixture was used to extract the aqueous antimony species. Antimony metal (Certified, Fisher Scientific, Fair Lawn, NJ) and 1000 mg 1 ~ indium (Spectroscopy standard, High-Purity Standards, Charleston, SC). The freeze dried pine needle standard reference material 1575, was obtained from the National Institute of Standards and Technology (NIST, Washington, DC). The pond weed sample (Potomogetan pectinatus) was collected from a site contaminated with mine tailings (Yellowknife Bay, NWT, Canada) as described previously [20] and freeze dried. The pine needle SRM (NIST 1575) was chosen as a representative standard reference material because it contains an uncertified antimony concentration of 0.2 mg kg ~.
1243
2.2. Preparation of samples and standards The pine needles (1575), and pond weed were dried to constant weight and then acid digested. Acid digestions were carried out in duplicate by adding 3 ml of concentrated nitric acid, 3 ml of 30% hydrogen peroxide, and 1 ml of concentrated sulphuric acid to a 250 ml round bottom flask containing pine needles (0.5 g) or pond weed (0.25-0.40 g) and refluxed for 3 h as described elsewhere [21]. An additional pine needle digestion was carried out by heating 1 g of material with the above acid/hydrogen peroxide mixture, in a vial on a hot plate, at 90°C for 3 h. After the digestions were complete, the partially evaporated samples were diluted to 5 ml (pine needles) and l0 ml (pond weed) using deionised water. Extraction of the pondweed was carried out by sonicating 0.5 g dry material with 10 ml methanol/water (1/1 v/v) for two samples, and 10 ml 0.2 M acetic acid for one sample. The sample and solvent were sonicated for 20 min, the mixture was centrifuged at 3000 rpm for 10 min and the supernatant was decanted. This was repeated five times and the combined extracts were evaporated under reduced pressure to dryness and made up to 5 ml with water. A stock solution of 1000 mg 1 1 antimony solution was prepared by dissolving 0.1000 g antimony metal in aqua regia and diluting to 100 ml with 1% D-tartaric acid. The 50 and 25 lag 1solutions for use in the standard additions determinations were prepared fresh daily from the stock. The palladium modifier solution was prepared by dissolving 0.1083 g palladium(II) nitrate dihydrate in 0.5 ml of concentrated nitric acid and diluting to 100 ml with 2% citric acid solution to give a 1000 mg 1-~ Pd solution. This stock solution was then diluted further with 2°/,, citric acid solution to give the various concentrations needed for the experiments. Indium solution was used as an internal standard in the ICP-MS determinations and was prepared by diluting an appropriate volume of a 200 ~tg 1 ~ standard solution so that the final concentration was 10 gg 1-~ in each sample.
1244
L Koch et al./Talanta 44 (1997) 1241 1251
2.3. Instrumentation
An atomic absorption spectrometer (Varian Techtron Model 1275, Australia) fitted with an auto-sampler, graphite furnace and programmer (GTA-95) was used throughout this work. The antimony hollow cathode lamp (SpectrAA, Varian, Australia) was operated at 10 mA with a slit corresponding to a spectral bandwidth of 0.2 nm and the 217.9 nm line was monitored. Continuous background correction was by a deuterium lamp (Varian, Australia). Pyrolytically coated graphite tubes (Varian, Germany) were used. The ICP-MS measurements were carried out using a VG PlasmaQuad 2 turbo plus instrument (VG Elemental, Fisons Scientific Equipment, Winsford, Cheshire, UK), operated at 1350 W RF power. Cooling, auxiliary and nebulizer gases (Ar) were at flow rates of 13.82, 0.69 and 1.00 1 rain ~, respectively. Masses were monitored in the peak jumping mode by using m/z 115 (In) and 12l (Sb). A real sample (pond weed digest diluted four times with deionised water) was used for the optimisation procedure outlined below. This sample was chosen, rather than an antimony standard, so that matrix and species dependent effects could be minimised and the antimony signal maximised. The OPTIMA3 computer program [18,19] was used for the simplex calculations and the generation of experimental conditions. The principal components analysis was carried out by using Systat~ 5.03 for windows (SYSTAT). Both of these programs were run under Windows ~ 3.1, on a DELL 466/M personal computer. NAA was carried out as described elsewhere [20,22]. 2.4. Plackett-Burman experiments
The initial variables chosen to be screened using the Plackett and Burman method were: dry time (Dt), dry temperature (DT), ash time (At), ash temperature (AT), atomisation ramp (AtR), atomisation time (Art), atomisation temperature (AtT) and modifier concentration (MC). This allowed for the use of three dummy variables and so had 3 df (see Table 1). Initial experiments
carried out using longer ash and atomisation times (up to 15 and 7 s, respectively) resulted in a short graphite tube lifetime (60 firings), thus limits for these variables were chosen to minimise tube deterioration. The limits for all the variables were chosen so as to show a change in measured absorbance, which was the response measured, rather than to reflect conditions usually used for ETAAS. After the first design was carried out, three variables (atomisation ramp, atomisation time and modifier concentration) were kept constant, whilst the effect of the other five variables were investigated using a N = 8 design (two dummy variables, 2 df) (see Table 2). The matrix designs, adapted from the method of Jones et al. [23], accompany the designations of variables in Table 1 and Table 2. 2.5. Simplex optimisation
The composite modified simplex (CMS) optimisation method described previously [18,19] was employed during this work. Having screened out the variables that did not have a significant effect on the response, the remaining four factors (atomisation temperature, atomisation time, ash temperature and modifier concentration) were optimised to provide the maximum antimony absorbance signal from a pond weed digestate. The upper and lower limits used in the CMS procedure as well as the stepsize for each variable are given in Table 3. Five initial experiments were conducted and the conditions tbr each factor, as well as the resulting absorbance, were entered into the OPTIMA3 computer program. The next set of experimental conditions were generated and carried out, and the response was entered, The simplex progressed via a series of reflections, expansions, contractions or fit points, towards the optimum absorbance (see Table 4). The process was continued until the standard deviation of the five highest responses was less than the value of the stepsize of the absorbance (0.010), three times sequentially. To prove that the optimum values determined were not due to a local region of maximum response, the procedure was repeated with different starting
+
4-
9 10 11 12
44--
44+
+ -
+ -
4-
_
At
70 90 3 1300 3 2300 1400 700 No change No change No change
U p p e r level ( + )
q +
+ -
+ 4-
-
4-
AT
+
-
+ +
4-
+
4-
Att
-
-
-
4-
4-
4-
44-
44-
-
_
44-
+ 4-
AtR
4-
AtT
~' E x p e r i m e n t s w e r e c a r r i e d o u t w i t h a c o n s t a n t injected v o l u m e o f 10 lal. b , 4 - , a n d " - ' s y m b o l s c o r r e s p o n d to t h e u p p e r a n d l o w e r levels o f v a r i a b l e values, as d e f i n e d b y the p r e c e d i n g table.
+
-
+
8
+
-
-
5 6 7
4-
+
-
3 4
4-
4-
4-b
1
2
Matrix
DT
Dt
Expt
L o w e r level ( - )
30 60 1 1000 1 1800 260 100 No change No change No change
Variable
Designation Dt D r y t i m e (s) DT D r y t e m p e r a t u r e (°C) At A s h t i m e (s) AT A s h t e m p e r a t u r e (°C) Art A t o m i s a t i o n t i m e (s) AtT A t o m i s a t i o n t e m p e r a t u r e (°C) AtR A t o m i s a t i o n r a m p (°/s) MC M o d i f i e r c o n c e n t r a t i o n ( r a g 1 1 pd)a D Dummy D Dummy D Dummy
Code
Table 1 P l a c k e t t - B u r m a n d e s i g n (N = 12) f o r the d e t e r m i n a t i o n o f s i g n i f i c a n t v a r i a b l e s to o p t i m i s e b y u s i n g s i m p l e x o p t i m i s a t i o n
4-
444-
4-
4-
m
MC
4-
-
4-
4+ 4-
4-
-
_
D
-
4-
-t-
+ 44-
-
_
4-
D
+
+
-
4-
44-
_
_
4-
--
D
4~
I
k~
{:
1. Koch et al./Talanta 44 (1997) 1241-1251
1246
Table 2 Plackett-Burman design (N = 8) for the determination of additional significant variables to optimise by using simplex optimisation Code
Variable
Lower level ( - )
Upper level ( + )
Designation Dt Dry time (s) DT Dry temperature (°C) At Ash time (s) D Dummy AT Ash temperature (°C) AtT Atomisation temperature (°C) D Dummy
30 60 1 No change 800 1800 No change
70 90 3 No change 1400 2300 No change
Expt.
Dt
DT
At
D
AT
AtT
1
+a
+
+
_
+
_
_
2
+ +
+ + -
+ + +
+ + + -
+ + + -
+ + + +
+ + +
+
-
-
+
D
Matrix
3 4 5 6 7 8
+
.
" ' + ' and ' - '
+
.
.
.
-
.
.
.
symbols correspond to the upper and lower levels of variable values, as defined by the preceding table.
conditions; the same optimum conditions were found.
2.6. Visualisation of the response surface The experimental results were analysed by using principal components analysis, as described in detail and with examples by Molinero [24]. Briefly, principle components analysis was used to reduce the four variables from the simplex optimisation to two new variables (principle components 1 and 2). The scores of these principle components give coordinates for all the
experimental vertices. Thus, the vertices of the simplex previously represented by n variables, are now represented by two variables, and the responses are plotted against these variables, to generate the response surface. The relative significance of the effects of the original variables on the responses can be evaluated by considering the loading of each variable on each principle component, which indicates to what degree each principle component is influenced by each of the original variables. This approach provides visual information on the optimum and the response surface, which is not possible with the simplex
Table 3 Range and stepsize of the variables being optimised by the composite modified simplex method Variable
Lower limit
Upper limit
Stepsize"
Atomisation temperature (°C) Atomisation time (s) Ash temperature (°C) Modifier concentration (rag 1-~)b
1400 0 800 100
2700 4 1600 900
100 1 50 100
Same units as variables. Experiments carried out with a constant injected volume of 10 lal.
I. Koch et al. /Talanta 44 (1997) 1241 1251
1247
Table 4 Simplex experiments and responses Expt. No.
Atomisation temp. (°C)
Atomisation time (s)
Ash temp. (°C)
Modifier conc. (mg 1 ~)~
Point type b
Response c (absorbance)
l 2 3 4 5 6 7 8 9 l0 11 12 13 14 15 16 17 18 19 20 21 22 23 a 24 25 26 27 28 29
18110 1800 2200 2400 2400 2100 2700 2500 2300 2700 2600 24(10 2100 1800 1700 2400 2300 2200 2000 2300 2000 2300 22110 2000 2300 2300 2300 2200 2000
0 3 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
1400 800 1000 1400 1400 1100 1050 1600 800 1050 1600 1050 1450 1600 1600 1200 1600 1250 1600 1200 1300 1400 1350 1250 1350 1350 1450 1400 1550
500 500 900 200 200 500 200 100 600 100 100 400 500 600 700 300 300 500 500 400 700 300 400 600 300 400 300 400 500
1 1 1 I I R R R C R R C R E R C R C R C R C F R C F R C R
0,1(13 0,056 0,085 0.179 0.026 0.145 0.139 0.000 0.116 0.138 0.000 0.155 0.264 0.055 0.048 0.217 0.009 I).204 0.043 0.167 0.105 0.266 0.280 0.129 0.258 0.262 0.214 0.270 0.128
" Constant volume of 10 gl. b Initial (I), reflection (R), contraction (C), extension (E) and fit (F). c Response is mean of three determinations, a Optimum conditions.
search alone. The response surface can be studied to determine more information such as the presence or absence of ridge features or local maxima. It also helps to show other factor levels that could
provide better experimental conditions in terms of lower temperature operating conditions, or less modifier, thus resulting in a more cost effective procedure.
Table 5 t Values for 12 and 8 variable designs used in the Plackett-Burman experiments Variables
Dt
DT
At
AT
An
AtT
AtR
MC
12 8
- 1.58 - 0.54
2.55 - 0.79
-0.97 - 2.34
1.74 14.90"
-4.46* -
-0.83 18.20*
-2.46 -
3.49* -
* Indicates that the variable is significant at the 95% confidence level.
1248
I. Koch et al./Talanta 44 (1997) 1241-1251 2.0
i
i
i
I
i
3_
i
Atomisation temperature •
2
i
!
•
•. . . . . . . . . . .
15 1
Ash temperature
~o
o I-
ASh time LL
0 <
ummy 05['jDrytemperature
r!
-1
-2
O0 "1" r ~ 0
LL
,.,ylte,mJ
,
J
I
,
20
30
40
50
60
10
70
-3 -3
Variable effect
Fig. 1. Birnbaun plot for the second Plackett-Burman, showing the significance of the two variables atomisation temperature and ash temperature.
3. Results and discussion 3. I, P l a c k e t t - B u r m a n
experiments
The results for the first Plackett-Burm experiment were used to obtain a minimum t value of 3.18 for a 95% confidence interval. Only the atomisation time and modifier concentration give t values above this and so are the only significant variables at this confidence level (Table 5). Birnbaun plots can be used to confirm or help clarify results obtained from such experiments, as explained in more detail elsewhere [23]. Briefly, deviance of points from a straight line indicate large variable effects [14]. In this instance, the Birnbaun
-2
1
0
1
2
FACTOR(2)
Fig. 2. Contour diagram showing the response surface for the first optimisation.
plot (not shown) gives essentially a straight line and therefore does not help with the further interpretation of this experiment. The second Plackett-Burman experiment was carried out by holding three factors constant and hence utilised five of the original variables and two dummies (2 df). The atomisation time and modifier concentration shown to be important by the first experiment were held constant at 0 s and 500 mg 1 1, respectively, in the hopes that any other significant variables might be revealed. The ramp rate was observed in these and preliminary experiments to give maximum results at higher speeds, as noted by Pergantis et al. [l 1] in their optimisation for arsenic. Instrumental constraints
Table 6 The optimised furnace program, used for quantitation of antimony in plant samples (400 mg L - 1 or 4 pg Pd as modifier was used) Step No.
Temperature (°C)
Duration (s)
Gas flow (L m i n - t Ar)
Function
1 2 3 4 5 6 7
90 120 1350 1350 1350 2200 2200
30 10 1.9 2 1 0.5 3
3 3 3 3 0 0 3
Dry/ramp Dry/ramp Ash/ramp Ash/hold Ash/gas off Atom/ramp" Clean
" 2000°C s-~ ramp from 1350°C to 2200°C, integration during this step.
1. Koch et al./Talanta 44 (1997) 1241 1251 Table 7 Concentration of antimony (mg kg t dry weight) in pine needles (NIST 1575) after analysis by ETAAS Sample Total digest 1~ Total digest 2 Total digest 3
ETAAS analysis _+ S.D. ~
Comparison to
0.220 +_0.012 0.208 + 0.019~ 0.231 + 0.044
nsdd at 98% nsd at 95% nsd at 95%
SRM b
Precision expressed as standard deviation (S.D.) based on five analytical replicates, except where indicated. h Antimony concentration (0.2 mg kg ~). " Hot plate digestion. a nsd: not significantly different at confidence level indicated. Four analytical replicates. limited the r a m p to 2000°C s - ~ a n d this value was used for all subsequent experiments. T h e results for the second e x p e r i m e n t p r o d u c e d a m i n i m u m t value at the 95% confidence interval o f 4.3 a n d the t values for the two variables, ash a n d a t o m i s a t i o n t e m p e r a t u r e were greater, indicating t h a t these variables have a significant effect on the a n t i m o n y response. T h e B i r n b a u n p l o t in Fig. 1 shows that the ash a n d a t o m i s a t i o n temperatures deviate f r o m a straight line because o f large variable effects, which confirms the significance o f these variables. F o u r variables: a t o m i s a t i o n time, a t o m i s a t i o n t e m p e r a t u r e , ash t e m p e r a t u r e a n d modifier concentration, were s u b s e q u e n t l y o p t i m i s e d b y using the c o m p o s i t e m o d i f i e d simplex p r o c e d u r e (CMS).
1249
3.2. S i m p l e x optimisation A total o f 29 e x p e r i m e n t s were carried o u t a n d the m a x i m u m response was r e a c h e d after 23 exp e r i m e n t s (see T a b l e 4). T h e o p t i m u m p a r a m e t e r s were f o u n d to be: a t o m i s a t i o n t e m p e r a t u r e , 2200°C; a t o m i s a t i o n time, 0 s; ash t e m p e r a t u r e , 1350°C; a n d modifier c o n c e n t r a t i o n , 400 m g 1 T h e simplex analysis was r e p e a t e d f r o m different initial c o n d i t i o n s a n d the m a x i m u m response was: a t o m i s a t i o n t e m p e r a t u r e , 2200°C; a t o m i s a t i o n time, 0 s; ash t e m p e r a t u r e , 1450°C; a n d modifier c o n c e n t r a t i o n , 400 m g 1 ~. These c o n d i t i o n s were reached after 22 e x p e r i m e n t s f r o m a total o f 27. The c o n d i t i o n s f r o m the first o p t i m i s a t i o n are considered to be better for routine use, because the lower ash t e m p e r a t u r e is less destructive to the g r a p h i t e cuvette. The response surfaces g e n e r a t e d from b o t h searches are n o t identical, b u t the characteristic ridge feature o f high a b s o r b a n c e is present in b o t h (see Fig. 2 for the response surface generated from the first simplex). T h e results for the principle c o m p o n e n t s analysis ( P C A ) indicate t h a t the first a n d second principle c o m p o n e n t s (PC) retain 43.8 a n d 31.5%, respectively o f the original variance o f the data. This is similar to values r e p o r t e d in previous w o r k [24]. T h e results also d e m o n s t r a t e that the a t o m i s a t i o n t e m p e r a t u r e a n d modifier c o n c e n t r a t i o n have the greatest influence on the first PC, whereas ash t e m p e r a t u r e has the greatest
Table 8 Comparison of the concentrations of antimony (mg kg I dry weight) in pond weed samples from Yellowknife, NWT, Canada Sample Extract
Id
Extract 2 Extract 3 Total digest I Total digest 2
Determined by ETAAS _+S.D. "
Determined by ICP-MS +_S.D. b
Comparison ~
0.28 + 0.04 0.26 + 0.02~ 0.28 + 0.02 39 + 5 40 _+5
0.222 + 0.003 0.221 + 0.002 0.179 + 0.003 32.6" 41.8 ~
nsd nsd nsd nsd nsd
Determination by optimised ETAAS and ICP-MS. Precision expressed as standard deviation (S.D.) based on five analytical replicates, except where indicated. b Two analytical replicates except where indicated. nsd, not significantly different at confidence level indicated. J Acetic acid/water extraction. Four analytical replicates. t"No replication.
at at at at at
95% 95% 98% 98% 95%
1250
1. Koch et al. /Talanta 44 (1997) 1241-1251
influence on the second PC. Generation of the response surface also eliminates the need to carry out univariate searches around the optimum to establish that it is correct. Therefore, after carrying out the simplex optimisation twice, from two different starting conditions and then analysing each response surface using principle components analysis, it was felt that further univariate investigates of the optimum were unnecessary.
3.3. Analysis" of samples by using the optimised temperature program The optimised procedure (Table 6) was used to determine the antimony concentration in pine needle SRM and pond weed, by using ETAAS and the method of standard additions. The results obtained for analysis of the pine needles are shown in Table 7, along with a comparison to the reference value. The concentrations for pine needles, with an average observed concentration of 0.220 mg kg ~, do not differ significantly from the non-certified concentration of 0.2 mg kg 1 The pond weed sample is from a contaminated site near a gold mine in the Northwest Territories, Canada. The concentration of antimony in this sample was determined by ICP-MS to verify the values obtained by ETAAS and the results are given in Table 8. The results for the two methods do not differ significantly, as shown by the statistical comparison. The concentration of antimony for each digestion does not differ significantly (95'70 level) from the value determined by neutron activation analysis of 41.2 mg kg k-~. The aqueous phase soluble antimony species were extracted from the pond weed sample with 1/1 methanol/water (V/V), so that further analysis by speciation techniques such as HPLC-ICP-MS or HG-GC-MS [24] can be carried out. However, prior to this it is important to establish the total antimony concentration, both hydride and nonhydride forming, present in the extract. Although the values obtained for the methanol/water extracts after analysis by ETAAS and ICP-MS do not differ statistically, consistently lower values for the ICP-MS results were observed. This is probably due to matrix or solvent effects, as the
ETAAS analyses were carried out by using the method of standard additions, whereas the ICPMS analyses were carried out using external calibration with aqueous standards. By the analysis of the SRM and the methanol/ water extract the optimised ETAAS procedure for the determination of antimony has been shown to overcome any interferences due to the sample matrix and any differences due to the different antimony species present. In addition, the method can be used for any total antimony determinations in samples of plant origin.
Acknowledgements The authors would like to thank Dr M. Dodd for provision of the pond weed samples and NAA results, Mr B. Mueller for help with ICP-MS analysis, Ms M. Winters for assistance with sample preparation and Dr A. Wade for comments on the manuscript. We would like to acknowledge Dr K.J. Reimer, Environmental Sciences Group, Kingston, Ontario and the Natural Sciences and Engineering Research Council of Canada for financial assistance.
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