Table I. Reproducibility and Correlation of Peak Area with Peak Height at Different Element Concentrations in Lake Superior Water Tot a1 Mean Mean element Coefficient peak concenpeak of height, tration, area, correlationb Element fig/La mmC fiv-s
cu
0
1 10
Pb
0
898 (91) 20093 (5.9) 185405 (2.5) 1213 (60) 18996 (12.4) 205339
2 (29) 93 (5.0) 858 (1.8)
3 (32) 0.8 134 (10.5) 1393 10 (8.8) (6.6) 2 0 419 Cd (62) (162) 69 0.06 10383 (7.1) (8.4) 902 125258 0.7 (4.6) (4.1) a 1OO-fiLinjections. Concentration 0 refers to
.,
0.992 0.999
... 0.971 0.996
... 0.981 0.998
instrument blank. Peak area vs peak height correlation from linear least squares fit comprised of 10 instrument atomization blanks and 10 replicate atomization signals at the specified concentration. Normalized to highest scale expansion. ( ) Indicates relative standard deviation for the mean of 10 replicates. (32 Hz) was checked by obtaining 10 representative peak areas and comparing them in a linear least squares fashion against corresponding peak heights. Experiments were performed at two different concentrations; one approximately 5-7 times above the working limit of instrumental detection and the other about 10 times higher (Table I). Relative standard deviations were in expected ranges (2). Coefficients of correlation in all cases were close to 1;correlations were lower and relative standard deviations were higher for the lower concentrations, particularly for lead. It is noted, however, that reproducibility may be slightly poorer than indicated, depending on operating conditions. The peak integration calculations are such that the area
depends on the system drawing the baseline from a point a t the beginning of atomization when a predetermined slope threshold is exceeded to the nearest point further in time when the slope threshold is again not exceeded. The practicalities of FAAS are such that slight “tailing noise” peaks can sometimes and unpredictably be present, especially when routinely working near detection limits. These might be best described as small superimposed peaks of negligible area immediately following the main atomization peak before the time it reaches baseline. They will often not affect peak height, but under these circumstancesthe complete area under the peak will not be obtained because of the manner in which the baseline is drawn. Therefore, a low result might be calculated. To circumvent this, appropriate precautions were always taken to assure that well-formed nontailing atomization signals were obtained, such as employing only graphite tubes in good condition. Use of this instrumental configuration for the analysis of these and other elements for more than a year’s time has demonstrated a high degree of performance and efficiency. Hardware additions and the design of post-run calculation program are generally applicableto other data systems capable of accurately integrating rapid atomization signals, having a suitable method for output of peak data, and possessing sufficient memory for BASIC. In addition, it is noteworthy to state that a newly available commercial automatic sampling system (Perkin-Elmer, Model AS-1) is essentially compatible with this system’s configuration. The programs written for this work are available from the author on request.
LITERATURE CITED G. E. Glass and J. E. Poldoski, Verh. Int. Ver. Limnol., 19, 405 (1975). R. E. Sturgeon, C. L. Chakrabarti, and P. C. Bertels, Anal. Chem., 47, 1250 (1975). R. E. Sturgeon, C. L. Chakrabarti, I. S. Maines, and P. C. Bertels, Anal. Chem., 47, 1240 (1975). J. E. Poldoski and G. E. &ass, “Proceedings of the Internabnal Conference on Heavy Metals in the Environment”, Toronto, October 1975, in press. H. V. Malmstadt, C. G. Enke, and E. C. Toren, “Electronics for Scientists”, W. A. Benjamin, Inc., New York, 1963, p 354. Hewlett-Packard Co., “Stat Pac”, Vol. I, pp 165-166, No. 09810-70800, Loveland, Colo. G. W. Snedecor, and W. G. Cochran, “Statistical Methods”, 6th ed.,Iowa State University Press, Ames, Iowa, 1967, Chapter 13.
RECEIVED for review December 22,1976. Accepted March 3, 1977. Mention of trade names of commercial products is only for identification purposes.
Solid State Programmable Switching Device for Semiautomated Multichannel Gas Analyses with Nondispersive Infrared Spectrometers H. L. Gearhart“ and R. L. Cook Department of Chemistry, Oklahoma State University, Stillwater, Oklahoma 74074
R. W. Whitney Department of Agricultural Engineering, Oklahoma State University, Stillwater, Oklahoma 74074
R. D. Hefner Tucson, Arizona 85724
Nondispersive infrared spectrometry has been widely applied in the field of gas analysis in recent years. Some typical uses include monitoring industrial and automotive emissions such as SO2, N20, various hydrocarbons, HF, NH3, organic acids, COz, CO, and H20, as well as anesthetic and associated gases in operating rooms. Nondispersive infrared
analyzers (NDIR) are particularly adaptable to continuous process monitoring as well as remote, mobile sampling due to the simplicity and ruggedness incorporated in their design (1-4).NDIR instruments available from Beckman Instruments (Models 864,865, and LB-2), Mines Safety Appliances (Models 303 and 202), Anarad, Inc. (Models AR-400, AR-500, ANALYTICAL CHEMISTRY, VOL. 49, NO. 6, MAY 1977
893
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Pneumatic as flow diagram, as modified, for the IR-Industries Model 755 Gas Sampling Conditioner (with permisslon of Infrared Industries, Santa Barbara, Calif. Flgure 1.
and AR-600),Infrared Industries (Models IR 702 and IR 703), Wilks Scientific Corp. (MIRAN 101 and MIRAN l),and others, are all either one- or two-channel analyzers. All require a sampling system, usually consisting of a simple pump and filter arrangement, to extract a representative sample from a process stream or other source. Single-point sampling systems are commercially available at relatively low cost. Some NDIR applications require remote multiple-point sampling. In these cases, custom built commercial units (e.g., Infrared Industries Model 755 Gas Sampling System) may be obtained, usually up to 10 channels maximum, for relatively high additional cost. The major limiting factors involved in multiplexing sample channels involve: 1) the time interval required for remote sampling with manual procedures and 2) the small number of sampling channels available on custom commercial equipment. Some applications, such as insect attraction studies or toxic emissions monitoring, requiring remote multipoint sampling, preclude physical human interference in the experimental arena. This paper outlines the design and operation of a solid state sample channel switching device capable of several preselected programmed operating modes. The device was used in lieu of a 10-position mechanical switch in a modified Infrared Industries Model 755 Gas Sample Conditioning System. The remote channel capacity was thereby increased in this unit from the existing 10 to 999999 (potential). The largest number of switching solenoids practical is