Environmental Sampling for Trace Analysis Ray E. Clement Ontario Ministry of the Environment Laboratory Services Branch 125 Resources Rd. P.O.Box 213 Rexdale, Ontario, Canada M9W 5L1
Hundreds of millions of dollars are spent worldwide each year on envi ronmental issues-based directly on the results of chemical analyses. One would think that students in chemistry and engineering programs, who will be employed in the environmental field, should receive basic training in evaluating the reliability of such chemical analyses. However, it is unfortunately true that far too few of these graduates will have such training. Many new environmental programs being introduced in our colleges and universities emphasize the study of environmental issues r a t h e r t h a n t h e scientific tools needed to investigate these issues. Few undergraduate programs em phasize the type of laboratory instruction in analysis that is needed to understand how reliable chemical data are generated. Although most analytical textbooks and courses dis cuss the importance of accurate sampling, students are seldom offered practical examples of the consequences of poor sampling. They may think that an analytical result generated by a million-dollar state-of-theart instrument is a number “carved in stone.” And because such analyses are expensive, they believe there is no need for replication. Can students learn the basic principles of environmental sampling and analysis from a simple classroom experiment? To find out, a sampling experiment was conducted at Mohawk College (Canada) in a class of students who were not chemistry majors. Although the experiment was originally designed to illustrate sampling difficulties and analytical er1076 A
A Classroom Experiment You Can Sink Your Teeth Into! rors that can occur in trace environmental determinations, it became apparent that it could also be used to describe many analytical conceptsincluding the importance of sample treatment and the need for selective detection. Most important, it clearly demonstrates the reality of errors in analytical measurements. Because the experiment is simple, interactive,
and directly analogous to the analytical principles described above, it is highly effective and even enjoyable.
Design of the experiment Nest16 manufactures a candy product called Smarties (available in Canada), which are button - shaped chocolate candies that have multicolored h a r d outer coatings. Individual Smarties are relatively uniform in shape and weight, and in appearance differ only in the color of the outer coating. (Any brand of multicolored candy can be substituted.) In the sampling experiment, different colors were used to represent different at-
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oms and molecules. Green was used to signifjr PCB molecules, blue represented Pb, brown designated Fe, and red symbolized chlorinated dioxin molecules. In addition, purple and pink represented unknown molecules. A soil matrix was depicted by combining yellow and orange candies. The manufacture of a sample where the matrix predominated was difficult, because the Smarties, as marketed, are fairly evenly distributed among the various colors. To avoid having to purchase kilogram quantities of Smarties, a second type of candy similar in appearance to Smarties was purchased. This candy, called Reese’s Pieces (manufactured by Hershey), comes in orange, yellow, and brown. The brown Reese’s Pieces also represented Fe. After combining the Smarties and Reese’s Pieces, the number of candies of each color were counted. Because the individual molecules and components of the soil matrix are almost uniform in size and shape, we assumed for the purpose of this experiment that the molecular weights of all the individual candy pieces were the same. Therefore, by counting the number of candies of the same color, the concentration of the molecule or atom represented by that colored candy could be determined in units of parts per hundred (pph) (Table I). Two volunteers from the class were selected to run the experiment. Student A was instructed to sample the contents of the plastic container in which the candies were brought to class by grabbing a small handful. After t h e first grab sample was taken, student A was told to make a second small grab and to keep this sample separate from the first. Student B was given the same instructions, except he was told to take large handfuls. The class was then told to determine the concentrations of all of our target analytes in parts per hundred-based on the four grab 0003-2700/92/0364-1076A/$03.00/0 0 1992 American Chemical Society
REPORT samples. An overhead projector was used to record the results.
Effect of sample size and replication on precision and accuracy The actual experimental data from this classroom experiment are shown in Table 11. Quite a large difference can be seen in the replicate results from student A, who collected total sample sizes of seven candies for each replicate. Unfortunately, the analyte with the highest concentration, Fe, was not detected in either replicate sample. PCBs, Pb, and the two unknown substances were detected in the first sample, each at 14 pph; only one of the unknowns was found in the second sample, at 28 PPh. Clearly, the differences between the replicates are significant. The result of selecting a small sample size was to increase (make worse) the detection limit of the determination. The comparison of individual results to the actual values seems pretty poor. However, when the averages of the values of the two determinations are taken, it can be seen that the estimates are much closer to the actual values; generally the estimated concentrations are within a factor of about 2-not too bad for trace analysis. Only the results for Fe and the unidentified pink analyte are way off. In the case of dioxin, the method is not sensitive enough to detect such an ultratrace analyte. Real - life trace environmental analysis is conceptually not so different from this example; when methodology is used that can barely detect analytes, it is not uncommon for the analytes to be observed in some samples but not in others, even though all samples were thought to be the same. For example, in a six-laboratory round-robin study of chlorinated dibenzo -$-dioxins and chlorinated dibenzofurans introduced into blank water samples, a significant variation in laboratory results was noted (1). The reported concentrations of :ntroduced at a con-
greater sample size. In these larger handfuls each analyte in the was detected in both replicates except for “dioxin,’’ which was observed in only one sample. The concentrations of all analytes are more accurate and more precise for the largesample - size experiment with the single exception of PCBs, where the mean concentration as determined from the first sampling experiment (small sample size) was closer to the actual value. As in the first sampling experiment, the mean estimates from two determinations were closer to the correct values than the estimates from an individual sampling event (with the single exception of PCBs, where both replicates from student B produced low estimates). The closeness of the mean analyte values from student B to the actual concentrations is quite reassuring.
Sample preparation and analyte detection A number of important concepts relating to sample preparation and analyte detection can be illustrated by this simulated soil- sampling experiment. Before sampling, the class was asked if any special sample preparation were needed. Almost everyone suggested t h a t the sampling container should be well mixed before samples were withdrawn. It was also important (for this specific experiment) that the sampler take a “blind” sample; otherwise, the sample se lected could be b’ sampler’s favorite is not recommende
concentrations by using a 1078 A
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contaminant plume that is emitted from a plant. Some s a m p l e “cleanup” w a s needed before analytes could be accurately detected. In this experiment, cleanup consisted of sorting the candies into groups according to color, after which they could be assayed by counting. For the large sample, an accurate quantitative determination could not be made without this sorting step, although without cleanup it is still possible to do a qualitative determination of the analytes present by recording the different colors observed. The physical separation of the candies into different colors is analogous to various chromatographic separation methods that are the basis of most real cleanup schemes. Note that the cleanup is more difficult to perform with the large sample. In real life, it is not difficult to overload cleanup methods by choosing sample sizes greater than those for which the cleanup is designed. I n such cases, choosing a large sample size will increase rather than reduce the detection limits ac experiment the dete not good for the sm taken initially, but
tection took more time to complete. The detector in this experiment was the human eye. By observing the various colors in the sample, the different analytes were identified (qualitative analysis). By counting the number of candies in each color group, quantitative estimates of
Table II. “Contaminant” dat; ~~
ND
.4
4.2
28
their concentrations were deter mined. A serendipitous illustration of some of the difficulties in analyte detection could be made because the test sample was made up of a mixture of Smarties and Reese’s Pieces. Although they appeared to be similar, Reese’s Pieces are a bit smaller than Smarties. This size difference is not critical for the “soil matrix” itself, but it is important for the detection of the brown-colored candies used to represent Fe. Therefore the method of detection (color) by itself cannot distinguish between the two brown analytes. A determination of physical properties (size) is also needed to avoid i overestimation of Fe in the
tected are inaccurate because the students conducted sampling without replacement. In other words, the candies taken from the container by the first sampler were not replaced; consequently, the actual concentrations of the candies in subsequent samplings were affected by this omission. This is true, but by selecting a large original population size, this factor is not significant (at least for the purposes of this experiment). In real environmental sampling, the amount of analyte removed from the area sampled (e.g., field, lake, or ambient air) is trivial wheh compared with the total amount of analyte present. In fact, in real environmental sampling one samples such a small amount of the whole area to be tested that a single sample quite likely is not representative of the area under investigation. Therefore
ten important to know form of an analyte is present in the environment and, as illustrated in this experiment, this can be very difficult. In this case, a second method of detection (taste) can be used to distinguish between the Smarties and Reese’s Pieces. (Note that taste is destructive detection; observation of color is nondestructive detection.)
Other observations and limitations At this time some readers may be noting that the concentrations de-
The sampling experiment with candies represents an idealized situation in which the entire population
is present in a plastic container, and therefore the concentrations of the various analytes could be determined exactly. In the environment, it is not possible to know the exact concentration of any analyte in the population. The best we can do is to estimate analyte concentrations by using a rigorous and careful sampling program, with judicious use of replication to determine the precision of our estimates. The population used in this experiment is also static; the exact numbers of the various color dies could change only i removed by accident or environment represents situation in which anal trations depend on wea tions, time of day, type and natural processes occ
mine concenmust find the detector response to analytes by evaluating standards prepared with known concentrations of these analytes. For this soil-sampling experi-
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ment, the concentrations of the two unknown analytes could not be determined until their identities were established. An interesting problem was presented to the students after the initial sampling experiment was com pleted. They were asked to sample the population to find a single poisoned candy that had been thrown in. In the absence of a specific detector that could selectively detect the poison (nobody volunteered to perform a taste test!), the students favored disposal of the entire population. This specific situation seldom occurs in an environmental analysis, but it is now obvious that the objectives of a sampling experiment should be clearly stated before any work is performed. The methods selected for any application depend on the specific results desired.
Conclusions In the 30 minutes it took to conduct this experiment, students received a better understanding of the principles of environmental sampling and analysis than if they had read a textbook on the subject. Hands-on exper-
iments capture t h e interest and attention of the students and encourage them to use their imaginations. Nobody is suggesting that the students are now experts in environmental sampling and analysis, but after this experiment they are better prepared t o consider the details of such methods used for environmental investigations. The most impor tant lesson is t h a t sampling and analysis methods are used to estimate the concentrations of analytes, and the answers obtained are subject to error. Proper methods are required to give the most accurate and precise results. After the experiment and discussion, the remaining candies were passed around the class for individual sampling and detection by taste. The students unanimously agreed that the soil - sampling experiment was literally one they could sink their teeth into.
Reference (1)Tashiro, C.; Clement, R. E.; Davies, S.; Oliver, B.; Munshaw, T.; Fenwick, J.; Chittim, B.; Foster, M. G. Chemosphere 1990,20(10-12), 1313-17.
Suggested reading Principles of Environmental Sampling; Keith, L. H., Ed.; ACS Professional Reference Books; American Chemical Society: Washington, DC, 1988. Keith, L. H. Environmental Sampling and Analysis: A Practical Guide; Lewis Publishers: Chelsea, MI, 1992.
Ray E. Clement received a Ph.D. in analytical chemistry (1981)from the University of Waterloo under the supervision of F. W. Karasek. He then joined the Ontario Ministry of the Environment where he is a senior scientist in the R&D department. He has authored more than 100 publications, most of which concern trace determination of chlorinated dioxins and jkrans in environmental samples.
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