ES&T
LETTERS Trace analyses for wastewaters Dear Sir: The recent feature article by Glaser et al. {1 ) in the December 1981 issue presents an operational approach to defining detection limit as "the minimum concentration of a substance that can be identified, measured, and reported with 99% confidence that the analyte concentration is greater than zero and is determined from replicate analyses of a sample." A theory is presented to justify the approach used in defining the detection limit. This theory deviates from most others that have been proposed in that the variability of blank measurements is not the basis of establishing the detection limit (2-6). An error distribution is presented for the measured analyte concentration when the true value of the analyte is equal to MDL. While no mention is made of blanks, presumably the distribution corresponds to the final analytical results, which may or may not have included blank correction. Both cases are included in the application of theory to the organic priority pollutant methods (i.e., the single-step procedure gives the option of including blank measurements, which was done, for example, in the analysis of heptachlor epoxide by Method 608). If blank correction is included in the recommended procedure, then the theory should also include treatment of blanks. Assuming that the measured analyte concentration includes any blank correction that may be necessary, the measured analyte concentration or analytical result is equal to the difference between sample response and blank response. However, if blank responses are considered, there is the possibility of obtaining a blank-corrected result for a sample not containing the analyte which is greater than the MDL. This is due to the random nature of both blank and sample responses. This type of error is termed error of the first kind (i.e., the error of accepting an apparent effect arising by chance as a real effect) and is not accounted for in the theory presented, which only considers 430A
Environ. Sci. Technol., Vol. 16, No. 8, 1982
error of the second kind (i.e., the error of failing to recognize a real effect). Also, the statement that sample standard deviation at zero concentration is "a concept which necessitates the possibility of negative analytical responses at zero concentration of analyte" is not correct. As has already been mentioned, an analytical result is equal to the difference between sample response and blank response, and it is the difference that may be negative, not the analytical responses themselves. Indeed, the error distribution presented by Glaser et al. indicates that there is a 1% chance for analyte concentration to be negative when the true value is equal to the defined method detection limit (MDL). It is not clear how MDL would be used in practice. O'Haver has stated that "a concentration at the detection limit can only be detected, as the term 'detection limit' implies, and not measured quantitatively." (7) Yet Glaser et al. state that " . . . the MDL for a given analyte in a given matrix does not preclude quantitation below the MDL." Besides the theoretical deficiencies mentioned, the procedures presented for determining MDL are somewhat arbitrary. This is indicated by the failure of the single-step procedure to give reasonable detection limit values, and such statements as "the closeness of the initial estimate to the final calculated MDL is a critical concern in using this procedure," and "the MDL procedure can give meaningless values when the analyte or analyte plus interference is present at levels much larger than 10 times the MDL value in reagent water." The statement is also made that "experience has shown that when the relative standard deviation is at or near 10% the calculated MDL values can be below instrumental detection limits." It is difficult to understand how a detection limit based on a "complete analytical procedure" can be less than a detection limit of one component in the procedure. I share with Glaser et al. their concern over the limitations in the application of definitions of detection limit based on the variability of blank mea-
surements. These limitations have been summarized by Cheeseman and Wilson (#). The definitions assume that the standard deviations of both the blank and samples containing low concentrations of the analyte are the same. The definitions are also not necessarily valid when the analytical response is zero for finite concentrations of the analyte. Finally, if the sample and blank are biased with respect to each other (for example, by the presence of interfering substances in the sample and/or the blank), the definitions are not valid. Unfortunately, the approach suggested by Glaser et al. in response to these limitations suffers from a lack of both a complete theoretical justification and a logically consistent procedure for determining the MDL, and I believe that application of the suggested procedures is not to be recommended. Cliff J. Kirchmer, Ph.D. Quality Assurance Manager Envirodyne Engineers 12161 Lackland Rd. St. Louis, Mo. 63141
References (1) Glaser, J. A. et al. Environ. Sci. Technol. 1981, 75,1426-1435. (2) Kaiser, H. "Two Papers on the Limit of Detection of a Complete Analytical Procedure"; Adam Hilger: London, 1968. (3) Currie, L. A. Anal. Chem. 1968, 40, 586-593. (4) Roos, J. B. Analyst 1962,87, 832-833. (5) Wilson, A. L. Talanta 1973, 20, 725732. (6) Morrison, G. H.; Skogerboe, R. K. In "Trace Analysis: Physical Methods"; Morrison, G. H., Ed.; Interscience Publishers: New York, 1965; Chap. 1. (7) O'Haver, T. C. In "Analytical Considerations in Trace Analysis: Spectroscopic Methods for Elements;" Winefordner, J. D., Ed.; John Wiley & Sons: New York, 1976; Chap. 2. (8) Cheeseman, R. V.; Wilson, A. L. "Manual on Analytical Quality Control for the Water Industry," Technical Report 66; Water Research Centre: England, January 1978.
Author's response The major premise in our practical approach to estimating the method detection limit (MDL) is that the MDL must reflect method perfor-
mance when the analyte is present. As such, the variability of the data will be the sum of all sources of variability that can occur at any step of the complete analytical procedure. We do not know of a universally applicable procedure that will measure the Type I error distribution; therefore, we do not assign a concentration level that represents a specific percentile of the Type I error distribution. All too often we think of the Type I error distribution completely described in the signalto-noise (S/N) ratio at a recording instrument and dismiss any contributions to the Type I errors that can and do arise in other steps of the method. This inability to measure the Type I error distribution is one of the reasons why our approach to determining the MDL is based on adding analyte to the matrix. Since our approach begins at higher concentrations and usually iterates to lower concentrations, the calculated MDL values are usually biased high. An analytical response (AR) is not simply the difference between the sample response (Rs) and the background response (RB)· The analytical response is calculated by applying the calibration function (g(R)) to both the sample response and background response; AR = g(R s ) - g(REs)· Calibration functions cast in terms of linear regressions can give negative numbers when the analyte concentration is at or is approaching zero. Also when Ko is used as the sample standard deviation at zero concentration to set confidence intervals above and below a regression line, negative results are possible at zero concentration of analyte. The analyst usually censors or dismisses these negative results, but they are possible and are due to certain mathematical manipulations. Also, as Kirchmer points out, if g(Rs) is less than g(RB), a negative result is obtained. By determining the MDL using finite quantities of analyte that do not approach zero concentration, these situations are avoided. Quantitative values can be assigned to concentrations below the MDL concentration. A single analysis giving a concentration level below the MDL will have a much lower than 99% confidence that the concentration is greater than zero. The average of a large number of replicates can be less than the MDL, but then enough information will be available to assign the degree of confidence that this level is greater than zero. In one of the earliest applications of the MDL procedure, Method 502.1 (/ ), the analyst reported the calculated MDL and an estimated concentration
level that corresponded to a peak height of three times the S/N ratio. The first set of the seven replicates contained 16 analytes, each of which gave a relative standard deviation (RSD) of less than 12%. For nine of these analytes the MDL value was estimated to correspond to a peak height between 3 to 9 times the S/N ratio, six analytes gave MDL values estimated to correspond to a peak height between 1.8 to 3 times the S/N ratio, and one analyte gave an MDL value estimated to correspond to a peak height of 1.2 times the S/N ratio. These results led us to establish the criterion for the reasonableness of the calculated MDL. If the dose level falls within 0.64 to 2.20 times the calculated MDL, another iteration will not significantly improve the calculated MDL. Alternately stated, if the RSD is between 20.5% and 70.1%, no further iterations are necessary. Hence our caution that if the RSD is at or near 10%, the calculated MDL can be below instrumental detection limits. In retrospect, the analyst is certain that the variability of these data was attenuated when the peak heights (3-8 mm) were measured and reported only to the nearest 0.5 mm. In any case, the MDL procedure signals when MDL values should be improved by performing an iteration of procedure. We place a heavy emphasis on the MDL values obtained using reagent water. These are the MDL values to be used in comparing method performance for a particular method in different laboratories. MDL values for a particular matrix can be derived using our procedure, but will generally give values that are inflated compared to reagent water values. These inflated values are caused by the presence of any interfering species and the variability due to sampling errors. The variability due to sampling errors and interfering species is at a minimum when MDL values are generated using reagent water. Denis L. Foerst, Research Chemist U.S. Environmental Protection Agency Environmental Monitoring and Support Laboratory Cincinnati, Ohio 45268 Reference (1) "The Determination of Halogenated Chemicals in Water by the Purge and Trap Method,"EPA #600/4-81-059,April 1981, Organic Analyses Section, EMSL, Cincinnati, Ohio 45268.
More on microorganisms Dear Sir: We were most pleased with the publication of the article entitled "Microbial removal of hazard-
ous organic compounds" by Hester Kobayashi and Bruce E. Rittmann (ES&T, Vol. 16, No. 3, 1982). This is an excellent literature review; unfortunately, it suffers from at least one glaring deficiency. It completely ignores extensive full-scale applications of selected mutant microorganisms that have been going on for several years now in the U.S. and about which there has been extensive publication. The sections entitled "Selective use of microorganisms" and "State-of-theart" create a misleading picture of the current situation in that they exclude extensive published data on the use of specialized microorganisms in fullscale biological treatment systems. I have attached an extensive reference list of the publications I have described. I have also attached a reprint of an article that describes just such applications, which are described as "nonexistent" in this country. Clearly, recent advances in genetic research offer opportunities to expand on the extensive work already undertaken in the application of specialized microbial strains in pollution control systems. The literature review undertaken by the authors is carefully done and of obvious value. However, the authors must have been living in their own world, and not that of the operating wastewater engineer, when they put this review together. Further, it does a disservice to your readers to exclude data that are of significant value in the context of the subject at hand. Thomas G. Zitrides, President Polybac Corp. Allentown, Pa. 18103 References (1) Beltrame, P.; Beltrame, P. L.; Carniti, P.; Pitea, D. Water Pollut. Control Fed. J. 1980, 52(1), 126. (2) Bradford, H. T.; McDowell, C. S.; Zitrides, T. G. "Mutant Bacteria Improve Wastewater Treatment System Performance," presented at Florida Section American Waterworks Association & Florida Pollution Control Association, Miami Beach, Fla., Nov. 5-8, 1978. (3) Dobbs, D.; Walton, G. C. "Biodégradation of Hazardous Materials in Spill Situations," presented at the 1980 National Conference on Control of Hazardous Material Spills, Louisville, Ky., May 13-15, 1980. (4) Goma, G.; Ani, D. Α.; Pareilleux, A. "Hy drocarbon Uptake by Microorganisms"; La boratoire de Genie Biochimique: INSA, Av. de Rangueil, 31077 Toulouse. (5) Himebaugh, R. R., "The Use of Selec tively-Adapted, Mutant Bacteria: Case Histories," presented at National Trainers Institute Process Control Instructors Work shop, Sponsored by U.S. EPA, Battelle In stitute, Columbus, Ohio, March 4, 1982. (6) Holladay, D. W.; Hancher, C. W.; Chilcote, D. D.; Scott, C. D. "Biodégradation of Phenolic Waste Liquors in Stirred-Tank, Co{continued on p. 432A) Environ. Sci. Technol., Vol. 16, No. 8, 1982
431A
