Anal. Chem. 1990, 62, 1452-1457
1452
Determination of Subnanogram per Cubic Meter Concentrations of Metals in the Air of a Trace Metal Clean Room by Impaction Graphite Furnace Atomic Absorption and Laser Excited Atomic Fluorescence Spectrometry Zhongwen Liang, Guor-Tzo Wei, Richard L. Irwin, Andrew P. Walton, and Robert G. Michel*
Department
of
Chemistry, University of Connecticut, 215 Glenbrook Road, Storrs, Connecticut 06269-3060
Joseph Sneddon
Department of Chemistry, University of Lowell, 1 University Avenue, Lowell, Massachusetts 01854
Alr, drawn by vacuum through a jet, was Impacted against the inside surface of an atomk absorption graphhe electrothermal atomizer (ETA). The amounts of the partkles thus Collected were determined at the ng m3 level by graphite furnace atomic absorption or at the pg m-3 level by laser exclted atomic fluorescence. The overall reproduclblllty of two sets of measurements, made 7 months apart, was 23%, wlth no significant dmerence between the two sets of data, based on Student’s “ 1 ” test at the 95% confidence level. Short-term reproduclblllty varled from 13% to 34% depending upon the air concentration of the metal. The method shows promise for monltoring long-term effectlveness of the filtering systems in trace metal clean rooms. I t was not possible to test for accuracy, due to the low concentrations involved, but accuracy was expected to be wltMn a factor of 2 or 3 of the actual value, based on theoretical aspects of impaction.
Recent work from this laboratory has involved the development of laser excited atomic fluorescence spectrometry (LEAFS) in an electrothermal atomizer (ETA, or graphite furnace) for ultrahigh sensitivity determinations of metals in samples. Detection limits in the femtogram range are routine by this technique (1-4). At these levels, a major concern is contamination from glassware, the handling of the solutions prior to introduction to the instrument, and the atmosphere in which the solutions are prepared. In the first two cases, careful attention to cleaning the glassware, and to laboratory procedures can control contamination. In order to adress airborne metal contamination, we have installed a trace metal clean room that is described briefly in this paper. All our analyses, at concentrations a t the picogram and femtogram levels, have been done in the clean room, but after several years of use we questioned whether the high-efficiency particulate filters, that were used to clean the air in the room continued to be effective in reducing airborne metal contamination. This paper relates how we attempted to measure the concentration of metals in the air in our various clean air stations. In addition, we compared these measurements with similar measurements in the normal laboratories that we use for trace metal analyses. Traditional methods of metal determination in the atmosphere involve collection of particulates on some form of filter system, by pulling a known volume of air for a preset time, digestion of the filter, and subsequent analysis, typically by atomic spectrometric techniques (5-1 0). The disadvantages *Author to whom correspondence should be sent. 0003-2700/90/0362-1452$02.50/0
are that the analyses are time-consuming and the detection limits are not particularly good. Typical detection limits are usually above 100 ng m-3 (for a sampling time of 1 h) which is not low enough to determine the concentration of metals in our clean room air. Matousek and Brodie (11, 12) demonstrated the determination of lead and cadmium in air particulates by furnace atomic absorption (ETA-AAS) following collection on 0.22-pm Millipore filter disks inserted into modified graphite sampling cups. Noller and Bloom further evaluated this method (13). Moura et al. compared this method with wet digestion of atmospheric aerosols and obtained good agreement (14). Chakrabarti and co-workers (15) described the direct determination of the metal content of air particulates by use of the graphite probe modification of the furnace atomic absorption spectrometric technique. Detection limits were at the nanogram or subnanogram per cubic meter level in air. Woodriff et al. (16-20) reported the direct determination of selenium, silver, mercury, lead, beryllium, and cadmium, by sampling the air through a porous graphite cup followed by electrothermal atomic absorption spectrometry. Torsi and his coworkers (21,22) described a method that combined “in situ“ electrostatic accumulation with electrothermal atomic absorption spectrometry. Both the latter techniques have high sensitivity, in the nanogram per cubic meter region (for a sampling time of 1 h). A series of papers by Sneddon (23-26) have shown the potential of connecting a single stage impactor to an electrothermal atomizer, for the atomic absorption spectrometric determination of metals in the atmosphere, at the nanogram per cubic meter levels, in a direct and nearly real-time manner. In the present work we used a sampling chamber based on Sneddon’s (23-26) single stage impactor and electrothermal atomizer tube, for the determination of copper, iron, lead, manganese, tin, and thallium in the atmospheres of both our clean room and our normal trace metal research laboratory. The low amounts of metal collected in the graphite tube were determined by either AAS or LEAFS measurements. The atomic fluorescence measurements allowed for several orders of magnitude of improved sensitivity to determine those metals that could not be determined by AAS. They represent the first time that LEAFS has been used to measure ultratrace concentrations of metals in air by the impaction approach and are probably among the most sensitive measurements of trace metals in air to date. The sensitivity offered by LEAFS allows for measurements at low enough concentrations to give some assurance that relatively contamination free conditions continue in the clean room. The air analyses were done on two separate occasions, 7 months apart, to illustrate the possible long-term monitoring potential of this approach as well as the C2 1990 American Chemical Society
ANALYTICAL CHEMISTRY, VOL. 62, NO. 14, JULY 15, 1990 a
Table I. Atomic Absorption Instrumental Conditions for Direct Collection and Determination of Metals in Air manganese
copper iron hollow cathode lamp current, mA electrodeless discharge lamp energy, W wavelength, nm spectral band-pass, nm Zeeman background correction dry temp for 60 s, O C char temp for 30 s, "C atomization temp for 5 ("C)
clean out temp for 5 s,
15
30
lead
1453
GRAPHITE TUBE TO PUMP
tin
12
9
8
324.7 248.3 0.7 0.2 Yes Yes
279.5 0.7 yes
283.3 286.3 0.7 0.7 Yes Yes
200 800 2100
200 900 2200
200 800 2100
200 200 400 900 1500 2300
2700
2700
2700
2700 2700
300
300
300
300
1 Omm TANTALUM J E T
TO PUMP b
A
RUBBER O - T N G
O C
internal gas flow (argon, mL/min) (I
300
No internal gas flow.
GRAPHITE TUBE HOLDER C
HOLDER
Table 11. Laser Excited Atomic Fluorescence Instrumental Parameters for Direct Determination of Metals in Air
A d An," nm dye laser power, @J/pulse monochromator slit widths, mm PMT voltage, V atomization temp, "C
lead
thallium
3831405 R-575' 5 0.5 1900 1600
2771353 R-560'
I
5
0.5 1900 1700
A,, exciting wavelength; An, fluorescence wavelength. * R-575, Rhodamine 575 (chloride). 'R-560, Rhodamine 560 (chloride).
short-term reproducibility. Here it is illustrated that the reproducibility of this impaction approach is sufficient to monitor long-term changes in the air metal concentrations in a trace-metal clean room. It was not possible to test for accuracy due to the low concentrations involved, but accuracy was expected to be within a factor of 2 or 3 of the actual value, based on theoretical aspects of impaction. EXPERIMENTAL SECTION Apparatus. The atomic absorption measurements were performed with a Perkin-Elmer Zeeman 5000 spectrometer (Perkin-Elmer Corp., Norwalk, CT). The Perkin-Elmer Data System 10 was used for data acquisition and manipulation. Peak area rather than peak height measurements were always done. The detailed experimental parameters are listed in Table I. The atomic fluorescence measurements were conducted with a system described previously ( 1 , 2 )with experimental parameters given in Table 11. Reagents. All stock solutions, 1000 pg mL-', were prepared by dissolving appropriate amounts of spectroscopically pure metals or compounds (Spec Industries, Inc., Metuchen, NJ) in deionized-distilled water or ultrapure mineral acids. Working solutions were prepared routinely from stock solutions. Impactor. The sampling chamber is shown in Figure 1. The basic principle of this type of system has been outlined previously (23) and involves an atmospheric air sample drawn by use of a vacuum pump through the jet, with the output stream directed against the electrothermal atomizer (impaction surface) opposite the injection port. The impaction surface deflects the flow rate to form an abrupt bend in the streamline. Particles with sufficient inertia are unable to follow the streamline, and impact onto the wall of the electrothermal atomizer. Procedures. Before use, each graphite furnace was given a normal cleanout by heating it in the atomic absorption or fluorescence instrument at 2700 "C for 10 s. If the furnace was new, it was fired several times before use. Typically five or six graphite tubes were in use at one time. Several impacted air
DIAMETER NOZZLE Flgure 1. Three views of the impaction chamber: (a) general view; (b) impaction device mounted into the graphite furnace; (c) close up
of the nozzle inside the graphite tube. Table 111. Sampling Times for Atomic Absorption and Atomic Fluorescence Determinations sampling location copper iron authors' 5-30 laboratory, min clean 60 room, min clean 6 hood or bench in clean room, h a
lead
3-12 10-80
40 6
60' 6*
manganese
tin
thalliuma
10-20
60-360
20
60
360
120
6
6
12
'
LEAFS. AAS and LEAFS.
samples were collected, and the graphite furnaces were stored in a plastic box until a time was chosen to do the analyses. The lifetime of these tubes were greater than 250 fiiings. The impactor was placed on the laboratory bench, either in the normal laboratory or inside the clean area of a class 100 clean bench or hood in the clean room. The whole of our clean room does not have filtered air. So a third type of measurement was made inside the clean room, but not in the clean bench area. This is a significant measurement because the clean air from the clean bench is eventually blown into the main part of the clean room and does result in a reduction in metal concentration in the air as shown in the measurements reported here. Measurements were made typically at a height of about 1.4 m above the floor. The vacuum pump was placed outside the clean room during the measurement, in order to avoid contamination from pump exhaust gases. Sampling flow rate for all measurements was 12 L mi&, and
1454
ANALYTICAL CHEMISTRY, VOL. 62, NO. 14, JULY 15, 1990 a +
I
18.5'
1 CLERN BENCH
4,
I 14.5'
DOOR
j
EXHAUST TO ROOF
I'lr;.+l.IR
INTRKE
CLERN
HOOD
~
DOOR
'F! INTAKE
FILTER
I
Figure 2. Trace metal clean room: (a) placement of the clean benches and hood; (b) sue view of the fume hood; (c)side view of the clean benches. Air sampling was done about 19 in. above each bench top.
sampling times are listed in Table 111. After collection, the impactor was dismantled and the electrothermal atomizer was removed carefully from the chamber, using Teflon-coated tweezers, and inerted into a Perkin-Elmer furnace system for ETA-AAS and ETA-LEAFS determination. The concentrations of the metals in the air were obtained by constructing a calibration curve with aqueous standards at the ng mL-' level. The results were converted to ng m-3 by using the following equation:
where C, is the concentration of metal in ng m-3, M , is the mass of metal in ng, V , is the volume of the atmosphere sampled in m3,Cd is the concentration of metal aqueous standard in ng mL-', Vatdis the volume of standard solution added in pL, F,is the flow rate in L min-', and S, is the sampling time in min.
RESULTS AND DISCUSSION In common with many analysts the prospect of constructing a full clean room facility was daunting, due to the complexity of the design and the cost of such a project. Hence, we decided to build a room that contained just two class 100 (Federal standard 209b, ref 27) clean bench areas, and a class 100 clean air exhaust hood (Figure 2). Each of the clean bench areas was composed of a ceiling mounted HEPA filter through which room air was driven with a fan (Model TCM 24s and Model VWM 24s class 100 clean air ceiling units supplied by Laminaire Co., Rahway, NJ). The cleaned air, blowing through the filter, was then directed over an area of a normal laboratory bench, bounded by a Plexiglas box. The inside of the box could be accessed through a hinged Plexiglas door for sample manipulation. The air exited from the box into the room through a gap of about 30 cm underneath the door. The clean hood (Model 931P-4', Contamination Control Inc., Lansdale, PA) was a purpose built unit, made almost entirely of wood,
and lined with 5/16 in. thick polypropylene. The manufacturers were instructed to use as little metal as possible for the construction, especially in the work area that contained the clean air. A side view of this hood is shown in Figure 2b. Two makeup air inlets, in the walls of the room near the ceiling, provided a positive air pressure in the room. This air was not filtered except with a coarse dust filter. It is planned that in the future the whole room could be equipped with class 100 clean air filters, and this makeup air would be used for those filters. Much of the metal equipment in the room, such as metal plumbing and electrical conduits, was replaced with the equivalent plastic parts. The walls were sealed with a white, two-part epoxy paint that is generally available in hardware stores. Additionally, all exposed metal surfaces were painted with the epoxy paint, including fluorescent light fittings, and the heating system. This room was built in 1984, and the filter units have been operating continuously since then. Particle Sizes Collected. The minimum particle size that can be collected by this impaction system can be calculated by using the following equation (28):
where Stk is the Stokes number, which both theoretically and experimentally has been shown to have values between 0.15 and 0.21 (28-32) a t a collection efficiency of 50% depending upon the physical design of the impactor (& is 0.40-0.70 a t 100% efficiency), pp is the density of the particle, V, is the average flow velocity a t the exit of the jet, C, is the Cunningham correction factor which is always greater than one, D, is the diameter of the particle, p is the viscosity of the medium, for air p = 1.8 X lo4 g/(cm.s), and W is the diameter of the nozzle (0.1 cm in this case). If we assume a Stknumber at 50% efficiency of 0.25, and the density of the airborne particulates is 1.48 g ~ m -for ~ ,a typical dust particle (30),then for a minimum value of C,, i.e. 1, the minimum particle diameter likely to be collected by the single-stage impactor is 0.3 pm (or 0.5 pm for an efficiency of 1.0). If a density of 5 or 6 g were to be assumed for some pure metal particles, rather than 1.48 g ~ m -then ~ , the minimum particle size would change by only a factor of 2, to 0.15 pm. As our clean room high-efficiency particulate filters (HEPA) were certified to remove particles of 0.3 pm and larger, it is clear that this impaction system is potentially capable of determining whether or not the HEPA filters are working properly. Although doubts are bound to exist about the smallest particles that can be collected, due to uncertainties in the value of the constants in the above equation, small particles are less likely to cause contamination problems, because the absolute amount of metal in a small particle is likely to be considerably less than in a large particle. At the higher end of the scale of particle sizes, it is assumed that particles of greater than 90-100 pm in diameter will tend to settle out by gravitation ( 5 ) ,especially in the undisturbed rooms that were monitored for this work. It has been suggested (23)that particles up to 90 pm in diameter can be collected with good efficiency by this impaction approach. Analyses. Three basic measurements of trace metals in the air were made. The first was in our normal instrument laboratory, the second was inside the clean room, but not in the clean hood or bench areas, the third was in the clean hood, or in one of the clean bench areas. The results are shown in Table IV. The data show that there are differences in the concentrations of the metals in air in all three situations. It was gratifying that the air in the clean room was cleaner than the normal laboratory air and that the concentrations of the metal in the clean bench area were so low that it was clear
ANALYTICAL CHEMISTRY, VOL. 62, NO. 14, JULY 15, 1990
1455
Table IV. Determination of Metals in Air by Atomic Absorption and Fluorescence‘
element CU
Fe Mn Pb Sn T1 mean RSDh
concentration of metals in air, ng/ms clean room clean hood or bench Nov 1988 June 1989 Nov 1988 June 1989
authors’ laboratory Nov 1988 June 1989
detection limitC
1.43 f 0.27 (4)#~# 0.31 f 0.10 (5)
0.41 f 0.05 (4);
b
b
0.02
16.9 f 0.47 (4)# . .
1.54 f 0.58 (3)
4.13 f 0.61 (4)X
0.049 f 0.029 (4)
0.046 f 0.016 (4);
0.01
0.70 f 0.12 (3)*
0.16 f 0.07 (4)
0.093 f 0.025 (3);
b
b
0.005
1.24 f 0.03 (4)*
0.19 f 0.02 (4)
0.18 f 0.04 (3);
b
b
0.01
0.21 f 0.04 (6) 0.0043 (4)d f 0.0009
0.27 f 0.12 (4).
0.32 f 0.05 (4)d 0.60 f 0.18 (4)dd 0.072 f 0.013 (4) 0.038 f 0.015 (3)’
0.0079 (4)d9* f 0.0018
0.00086 (3)d f 0.00013
0.00099 (3)4* f 0.00017
0.000029 (3)d f O.oooO14
O.oooO43 (4)dv* f 0.000025
13
18
26
22
34
34
1.89 f 0.13 (6) 6.65 f 0.75 (6) 0.71 f 0.08 (6) 1.25 f 0.09 (6)
total mean RSDf.
22% (Nov., 1988 data),
0.0072 f 0.0020 (4)d 0.0063 f 0.0020 (4)d** 0.0001d 0.072 f 0.001 (4) 0.040 f 0.004 (3)X 0.01 O.oooOlOd@
23% (June, 1989 data)
mean RSD of the pooled data: 23% a Data are expressed as the mean f the standard deviation, the number of replicate measurements (n)in each data set, is given in parentheses; Measurements were by ETA-AAS, except those indicated by d. *Below the detection limit. CSamplingtime was 6 h, detection limits based on a signal to noise ratio of 3. dDeterminedby LEAFS. “Sampling time of 12 h. ’A Student’s ‘t” test of the pooled data indicated that, overall, the data of Nov 1988 were no different from the data of June 1989. #Student’s ‘t” test of individual sets of data showed no significant difference for most cases of paired data (*), and a significant difference for five cases (#I. hMean relative standard deviation (by column).
that the HEPA filters (they were certified to be 99.97% effective for particles 0.3 pm or larger) were filtering the air sufficiently to remove substantial amounts of airborne particulates that contained metal. The concentrations of metals in the authors’ normal laboratory were in the range from ng m-3 of copper, iron, and lead to subnanogram amounts of manganese and tin (Table IV). Thallium was at an extremely low level. In the clean room the concentrations of metals were 3 to 10 times lower than in the normal laboratory. Extremely low concentrations were found in the hood and clean bench areas of the clean room, as expected. The concentration of thallium in the hood was as low as 29 fg m-3. Statistically this number is the same or lower than our detection limit for thallium, and hence it cannot be said that we detected thallium in the clean bench or hood. It is of interest that the values for tin in the clean bench or hood and in the clean room were almost the same. The likely reason for this is that the hood was probably made of plastic materials that contained some organotin compounds which were used as stabilizers, or chain terminators, during the manufacture of the plastic (33). For the determination of lead in the clean room, the LEAFS results were in reasonable agreement with those of AAS. For various practical reasons we could not do all the analyses by both techniques. Clearly, it was not possible to determine thallium by impaction AAS due to the very low levels that were only just measurable by LEAFS. It is notable that we have been preparing thallium solutions in the clean room for a number of years now, and hence the ambient level of thallium, recently measured, may well have been introduced by our solution preparation activities rather than resulting from a normal ambient level. However, in the clean bench/hood the level of thallium was still so low that we could not detect it by graphite furnace laser excited atomic fluorescence. A linear relationship between sampling time and atomic absorption signal was obtained for all the metals concerned. Linear regression gave an intercept, measured as absorption peak area, in the range from -0.0038 to 0.0033 Ass, which is well within the error of absorption measurements. The correlation coefficient was in the range from 0.9971 to 0.9995 for all metals. Long-Term Measurement Stability. After seven months, determinations of all the above metals were conducted again
(see Table IV). Student’s t test, at the 95% confidence level, was applied to each pair of data for each element. Only 5 out of the 17 pairs of data indicated that the June 1989 data might be any different from the Nov 1988 data. The biggest difference, by a factor of 3, was the iron data. One might expect this element to cause particular contamination problems due to its ubiquitous nature. It could be said that correlation would not necessarily be expected between data taken seven months apart, as potential variations caused by seasonal changes in contamination might affect the data, but these data indicate that the concentrations of metals in our laboratories’ air were fairly stable. Indeed, after dividing the data into two pools, one for Nov 1988 and one for June 1989, Student’s “t” test indicated that there was no overall significant difference between the two sets of data, including the iron data. The aim in this work was not to monitor short-term changes in contamination within the rooms. Accordingly, division of the data into the two pools separated by several months and doing Student’s t test achieved the aim of looking at long-term stability considerations. Short-TermPrecision. Table IV indicates the short-term reproducibility of the measurements in the undisturbed atmospheres of the various laboratories. The data in the authors’ normal laboratory had the best precision (13-18%) due to the higher concentrations that were measured. The clean room data had a precision of 22-26%, while the lowest concentrations measurements in the class 100 clean hood had a precision of 34%. Inspection of the detection limits given in Table IV confirms how close the clean hood data were to the detection limits and indicates that the poorer precision was to be expected. The overall mean relative standard deviation was 23 % . It was of concern to us that, in general, our measurements gave lower concentrations than we were used to seeing for typical metal concentrationsin air as reported in the literature. However, we found that if we sampled near the floor of the labs, while walking around the lab during the sampling time, then we could increase the numbers by 1 to 2 orders of magnitude. Hence, all our measurements represent sampling a relatively undisturbed laboratory environment. This also minimized short-term contamination problems and helped ensure the stability of the long-term measurements that were the primary aim of this work. The measurements were in
1456
ANALYTICAL CHEMISTRY, VOL. 62, NO. 14, JULY 15, 1990
T a b l e V. C o m p a r i s o n of t h e D e t e c t i o n L i m i t s of V a r i o u s T e c h n i q u e s for A i r Sampling
method wet digestion, ETA-AAS wet digestion, ETA-AAS direct, f i l t e r paper, ETAAS direct f i l t e r paper ETAAS porous graphite t u b e ETAAS porous graphite probe ETAAS electrostatic precipitation,
ETA-AAS ETA-AAS ETA-LEAFS
t h i s work,
sampling flow rate
20 m3/h 2.7 L/min
1.2 m 3 / ( c m di 40 mL/min 1.25 L/min 100 mL/min 10 Ljmin 12 L/min
Lead by
detection limit," ng/m3
240 120 3 8b 0.16 10' 0.01
ref
6 7 14 11 16
15 21, 22
0.Oi
0.0008
" S a m p l i n g time: 1 h *Characteristic mass. CBased o n a signal-to-noise r a t i o o f 2 ( a l l others are signal-to-noise r a t i o o f 3).
order of magnitude agreement with some of the data in the literature (8, 15). In a disturbed atmosphere it was not possible to obtain results that had the degree of short-term precision shown in Table IV. Copper levels could be as high as 23.4 ng m-3 in the authors' laboratory when the atmosphere was disturbed by people. Comparisons with Other Methods. The detection limits of some other air sampling and analysis methods for lead are summarized in Table V, from which it can be seen that impaction ETA-AAS and ETA-LEAFS are among the most sensitive techniques. Our data for impaction ETA-LEAFS are not extensive, but it is clear that the several orders of magnitude improvement in sensitivity over atomic absorption, that is expected of graphite furnace LEAFS, can be directly translated into the impaction method of measuring metal concentrations in air. Accuracy. Our data do not illustrate how efficiently we can collect the metal bearing particulates in the furnace. Hence, the accuracy of our measurements is unproven. Due partially to time and equipment constraints, we did not attempt to use any of the other established methods listed in Table V, which would have allowed for some comparisons of measured levels of metal concentrations in the air. Moreover, the sensitivity of these methods probably would not have been sufficient to make comparisons with our measurements. In one set of experiments, we tried the addition of matrix modifiers to the graphite furnace, after collection of air samples and just prior to atomization of the sample. We reasoned that if the signals were improved by a matrix modifier, then this would indicate that matrix interferences were occurring and that a matrix matching approach would be necessary to standarize the analyses. A matrix interference would have indicated that the response of the atomizer system to solid air particulates was different from its response to the aqueous standards. A sample that could have been used for matrix matching was the NIST urban particulate Standard Reference Material, 1648, added as a solution, slurry, or powder. However, it turned out that the modifiers that we tried, which were palladium or a mixture of magnesium nitrate and ammonium phosphate, did not alter the signal sizes from the collected samples, indicating that the measured signal represented complete recovery of the impacted metals without any chemical or physical interferences. In the absence of matrix interferences, it is only the efficiency of the sampling step that is of concern. For example, if certain sizes of particles are not collected by the impactor, then the measured metal concentrations will be too low. Such a source of inaccuracy does not affect the conclusion of this paper, that it is possible to use this technique to test clean room HEPA filters for their continuing ability to reduce metal concentrations. The long-term stability of the measurements, rather than accuracy.
is more important to test the filters. The factors that affect collection efficiency by impaction are mainly from wall loses, bounce off, and blow off, which have been extensively studied and reported in the literature (34-38). Lundgren (34)investigated losses for four kinds of cascade impactor. Total losses varied from 9.9% for the Andersen impactor, to 30.6% for the Lundgren impactor. For a single-step impactor, wall losses have been quantified (36) as generally between 10% and 50% due to bounce off and blow off. The worst result, for a single stage impactor, was a loss of 70% (35, 36) where the collection surface was uncoated glass; moreover the tested aerosols were resilient polystyrene latex spheres. Thus in this study, worst case collection efficiencies of 30% or better could be expected, if it is assumed that the surface of the pyrolytic graphite, used here, behaved similarly to the uncoated glass of refs 35 and 36. This shows that the accuracies of the data are likely to be within a factor of 3 of the numbers given in Table IV. Possible further work on the accuracy of the impaction approach includes the challenging task of developing a standard aerosol, based on approaches that might use the electrothermally generated aerosol of Sneddon (25) or the aerosols typically used for introducing samples into flames and plasmas. Such work is continuing at the University of Lowell. Despite these doubts about the accuracy of the method, it appears that the excellent long-term reproducibility of the measurements is sufficient to allow monitoring of the air in a trace metal clean room with appropriate conclusions about the efficacy of the clean room HEPA filters. It is unlikely that it is useful to know the air metal concentrations more accurately than a factor of 3, because of the short-term inhomogeneity problems associated with air sampling. For example, simply walking around in a room can change air concentrations by orders of magnitude, as noted earlier. Registry No. Cu, 7440-50-8;Fe, 7439-89-6;Pb, 7439-92-1; Mn, 7439-96-5;Sn, 7440-31-5;T1, 7440-28-0.
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RECEIVED for review February 1, 1990.
Accepted April 12, 1990. This work was supported by the National Institutes of Health under Grant No. GM 32002 and presented at the 16th annual FACSS meeting in Chicago, IL, Oct 1-6, 1989, as paper number 71. R.G.M. was supported by a Research Career Development Award from the National Institute of Environmental Health Sciences under Grant No. ES00130.
Determination of Physiological Levels of Glucose in an Aqueous Matrix with Digitally Filtered Fourier Transform Near-Infrared Spectra M a r k A. Arnold a n d Gary
W.Small*
Department of Chemistry, T h e University of Zowa, Iowa City, Iowa 52242
A procedure is described for the measurement of cilnicaiiy relevant concentratlons of glucose in aqueous solutions with near-infrared (NIR) absorbance spectroscopy. A glucose band centered at 4400 cm-' is used for this analysis. NIR spectra are collected over the frequency range 5000-4000 cm-l with a Fourier transform spectrometer. A narrowband-pass optical interference filter is placed in the optical path of the spectrometer to eliminate ilght outside this restricted range. This configuration provides a 2.9-fold reduction in spectral noise by utilizing the dynamic range of the detector solely for light transmitted through the filter. I n addition, a novel spectral processing scheme is described for extracting glucose concentration information from the resulting absorbance spectra. The key component of this scheme is a digital Fourier filter that removes both high-frequency nolse and low-frequency base-llne variations from the spectra. Numerlcal optimizatlon procedures are used to identify the best locatlon and wldth of a Gausslan-shaped frequency response function for this Fourier filter. A dynamic area calculation, coupled with a simple linear base-llne correction, provides an Integrated area from the processed spectra that is linearly related to glucose concentratlons over the range 1-20 mM. The linear callbration model accurately predicted glucose levels in a series of test solutions with an overall mean percent error of 2.5 % . Based on the uncertainty in the parameters defining the callbration model and the variability of the magnitudes of the integrated areas, an overall Uncertainty of 7.8 % was estimated for predicted glucose concentrations.
INTRODUCTION Considerable effort has been placed on the development of a reliable glucose sensor capable of serving as the active sensing element for an implantable artificial pancreas (1-4). To be considered for this application, the sensor must be able to measure glucose selectively and continuously under in vivo conditions for at least 1year. Although glucose sensors have been successfuly developed for short-term continuous monitoring (5-7), none of these devices is suitable for long-term
in vivo applications. The primary limitation has been a fundamental lack of compatibility between the sensor and the site of implantation (8). The issue of biocompatibility has been recognized for many years as the ultimate barrier to the successful development of an implantable glucose sensor (9, 10). An alternative approach is to monitor in vivo glucose levels by a noninvasive spectroscopic measurement. In concept, noninvasive blood glucose measurements can be made by transmitting a selected band of radiation through a vascular region of the body and calculating the clinically relevant glucose concentration from the resulting transmission spectrum. With such a noninvasive approach, biocompatibility issues are irrelevant because nothing is in direct contact with the sample. In addition, a noninvasive approach is reagentless and, therefore, is not limited by the stability or consumption of reagents. These attributes make a noninvasive blood glucose sensing scheme ideal for the continuous measurements required for the artificial pancreas. Such a sensing scheme would also be attractive for short-term continuous measurements such as during emergency treatment of extreme hyperglycemia. A noninvasive monitor would also be preferred for daily patient measurements at home where a simple and painless technique is desirable, especially for measurements on children. Because neither chemical reagents nor physical separations can be used in a noninvasive approach, the primary concern is selectivity. Overall, the spectroscopy alone must provide sufficient selectivity for the measurement. The challenge is to establish a procedure that accurately predicts the concentration of glucose at clinically relevant levels in the complex matrix of whole blood from the information in a transmission spectrum. Results from two recently reported investigations suggest that vibrational spectroscopy can be used for this measurement. Zeller and co-workers (11)have concluded that a single frequency in the midinfrared region is suitable for selective glucose measurements. Their preliminary results indicate that measurements at 1040 cm-' will provide selective information over proteins, carbohydrates associated with proteins, hemoglobin, urea, and lipids. Heise and co-workers (12),on the
0003-2700/90/0362-1457$02.50100 1990 American Chemical Society
