Safety in Lab 2nd Applied Chem-49-64 PDF

Sampling and Sample Preparation 1. Introduction A chemical analysis is most often performed on only a small fraction of the material of interest, for example a few milliliters of water from a polluted lake. The composition of this fraction must reflect as closely as possible the average compositio...

Sampling and Sample Preparation 1. Introduction A chemical analysis is most often performed on only a small fraction of the material of interest, for example a few milliliters of water from a polluted lake. The composition of this fraction must reflect as closely as possible the average composition of the bulk of the material if the results are to be meaningful. The process by which a representative fraction is acquired is termed sampling. Often, sampling is the most difficult step in the entire analytical process and the step that limits the accuracy of the procedure. This statement is especially true when the material to be analyzed is a large and heterogeneous liquid, such as a lake, or a heterogeneous solid, such as an ore, a soil, or a piece of animal tissue. In designing an analytical method, we consider potential sources of determinate error and indeterminate error, and take appropriate steps to minimize their effect, such as including reagent blanks and calibrating instruments. Why might a carefully designed analytical method give poor results? One possibility is that we may have failed to account for errors associated with the sample. If we collect the wrong sample, or if we lose analyte while preparing the sample for analysis, then we introduce a determinate source of error. If we fail to collect enough samples, or if we collect samples of the wrong size, then our precision may suffer. Figure 1 shows the common steps of any analytical process. Problem definition & Method selection Sample collection (Sampling) Sample preservation Sample preparation Analyte separation Analysis Data processing and reporting Figure 1. Common steps of any analytical process. 45 For example: Common steps in analysis of food safety 2. Terminology - Sample: This is a small part drawn from the population, which represents the bulk, for the purpose of analysis. - Sampling unit: The minimum sized package from the population, which represents the sample, is called a sampling unit. e.g.– If a consignment contains many boxes, then each box is a sampling unit. - Sampling can be defined as the process or technique of selecting a suitable sample for the purpose of determining parameters or characteristics of the whole population. - Sampling is the process to get a representative and homogeneous sample. Representative means that content of analytical sample reflects content of bulk sample. Homogeneous means that the analytical sample has the same content throughout. 46 - Types of analysis Qualitative: it finds out the nature of elements or compounds (identifies what is inside the sample) Quantitative: it estimates the concentration of the elements or compounds present in a sample (finds out how much?) - Analyte and Matrix An analysis provides chemical or physical information about a sample. The component of interest in the sample is called the Analyte, and the remainder of the sample is the Matrix. - Population vs Sample The population is the entire group that you want to draw conclusions about. The sample (portion of a population) is the specific group of individuals that you will collect data from. - A lot is the total amount of material that you're going to take your sample from. For example, the lot may be a carton of chocolate at the grocery store. - Bulk sample is a large sample that is first taken from the lot. For example, it could be several candy bars from the carton. - Gross sample is several small portions of the sample. This is reduced to provide a laboratory sample. An aliquot of this sample is taken for the analysis sample. - Detector: A device that responds to the presence of the analyte, usually generating an electrical output. - Signal: The detector output that is displayed or recorded. 47 - Sensitivity: The change in detector signal vs change in analyte concentration. - Selectivity: The discrimination of an analyte vs other components in the sample. - Sampling error: This arises out of random sampling and is the discrepancies between sample values and the population value. Sample Size and Analyte Level Techniques for handling very small samples are quite different from those for treating macro samples. 48 3. Importance of Sampling and Sample Preparation One of the most important parts of the analytical process is sampling, which is highly dependent on the properties of the analyte and the nature of the sample. Obtaining correct and informative results from the analytical procedure is the main purpose of this step. Inappropriate sample collection causes irreparable impairment that cannot be compensated even by quality assurance measures. For example, in the field of environmental samples, such as soil, air, and water, consideration of representative sampling right at the point of collection is of great importance because it needs to consider the intrinsic heterogeneity of most materials. These considerations are highly important especially in performing analysis of trace and ultra-trace components, which require sample-specific strategies to obtain a clear and unbiased overview. After sample collection, it needs to be decided whether the entire sample or a portion of the sample requires to be analyzed. It should be noted that sampling depends on the location, depth, and time of the year, which affects the concentration of the sample. Sample contamination during sample collection is one of the main sources of acquiring invalid data. The purity of the sample should be ensured before taking a measurement to obtain the optimum results when using any instrument, irrespective of the technology. For this reason, sample preparation often involves a cleanup step for “dirty” samples besides extraction procedure. Sample preparation also includes all treatments to decompose the structure of the matrix in order to perform the fractionation, isolation, and enrichment of the proposed analytes. Figure 2 shows various sample preparation steps that may be employed in sample preparation in which most analysts use one to four steps for sample preparation, although, in some cases, more than seven steps may be used. 49 Figure 2. Sample preparation procedures commonly used. 50 4. Sampling Plan A sampling plan should be developed to ensure that the estimated value obtained from the laboratory sample is a good representation of the true value of the population. A sampling plan is a detailed outline of which measurements will be taken at what times, on which material, in what manner, and by whom. It includes a predetermined procedure for the selection, withdrawal, preservation, transportation, and preparation of the portions to be removed from a population as samples. Sampling plan includes: i) Number, location, and size of the samples ii) Instructions for altering, processing, or reducing samples iii) How many samples must be run iv) Which method or instrumentation to use v) How to report results 5. Types of Samples Where to Sample the Target Population A sampling error occurs whenever a sample’s composition is not identical to its target population. If the target population is homogeneous (e.g., a tanker of well stirred liquid oil), then we can collect individual samples without giving consideration to where to sample. In practice, most populations are heterogeneous and so we must carefully select a number of individual samples from different locations within the population to obtain an indication of the properties of the total population. Unfortunately, in most situations the target population is heterogeneous. Due to settling, a medication available as an oral suspension may have a higher concentration of its active ingredients at the bottom of the container. The composition of a clinical sample, such as blood or urine, may depend on when it is collected. A patient’s blood glucose level, for instance, changes in response to eating and exercise. 51  Other target populations show both spatial and temporal heterogeneity. The concentration of dissolved O2 in a lake is heterogeneous due both to the changing seasons and to point sources of pollution. 6. Sampling Methods (Techniques) There are two types of sampling methods namely, probability (random) sampling and non- probability sampling. In random selection, every member of the population has an equal chance of being selected for the sample. In other words, the sampling process is not based on the judgment of the researcher. Sample selected at random to minimize bias. On the other hand, in non-Probability sampling, sample units are selected on the basis of personal judgment. The guiding factors in non- probability sampling include the availability of the units, the personal experience. There are different types of random sampling: - Simple –any sample has an equal chance of selection 52 As seen in the picture above, in part A of the picture, the sampling of river water is done randomly but the samples are collected from various points distributed over the entire space. In part B, however, the sampling is done in a haphazard manner and the sample points are not evenly spread over the entire area of the river. Thus, in the case of B, we shall not get a sample, which correctly represents the river water(bulk). The variation in sampling is called sampling error. - Systematic –first sample is selected at random and then next samples are sampled at intervals –i.e., 5th, 10th, etc… or 5 min, 10 min, etc… - Stratified –the lot is subdivided, and sample selected - Cluster- Cluster sampling also involves dividing the population into subgroups, but each subgroup should have similar characteristics to the whole sample. Instead of sampling individuals from each subgroup, you randomly select entire subgroups. 53  Figure 3. Random sampling Figure 4. Judgmental sampling 54 55 7. What type of sample to collect? After determining where to collect samples, the next step in designing a sampling plan is to decide what type of sample to collect. There are three common methods for obtaining samples: grab sampling, composite sampling, in situ sampling. The most common type of sample is a grab sample, in which we collect a portion of the target population at a specific time and/or location, providing a “snapshot” of the target population. If our target population is homogeneous, a series of random grab samples allows us to establish its properties. For a heterogeneous target population, systematic grab sampling allows us to characterize how its properties change over time and/or space. A composite sample is a set of grab samples that we combine into a single sample before analysis. Because information is lost when we combine individual samples, we normally analyze grab sample separately. In some situations, however, there are advantages to working with a composite sample. One situation where composite sampling is appropriate is when our interest is in the target population’s average composition over time or space. For example, wastewater treatment plants must monitor and report the average daily composition of the treated water they release to the environment. The analyst can collect and analyze individual grab samples using a systematic sampling plan, reporting the average result, or she can combine the grab samples into a single composite sample. Analyzing a single composite sample instead of many individual grab samples, saves time and money. Composite sampling is also useful when a single sample cannot supply sufficient material for the analysis. For example, analytical methods for determining polychlorinated biphenyls (PCBs) in fish often require as much as 50 g of tissue, an amount that may be difficult to obtain from a single fish. By combining and homogenizing tissue samples from several fish, it is easy to obtain the necessary 50-g sample. A significant disadvantage of grab samples and composite samples is that we cannot use them to continuously monitor a time-dependent change in the target population. In situ sampling, in which we insert an analytical sensor into the target population, allows us to continuously monitor the target population without removing individual grab samples. For example, we can monitor 56 the pH of a solution moving through an industrial production line by immersing a pH electrode in the solution’s flow. Steps involved in sampling bulk material: Identify the population from which the sample is to be obtained. Collect a gross sample that is truly representative of the population being sampled. Reduce the gross sample to a laboratory sample that is suitable for analysis. 8. Error Sources Prior to Total Element Determination There are some typical errors that often occur in the course of planning and performing sample collection prior to trace analysis. Particular error sources in performing various tasks are summarized and discussed below: - Contamination of all used sampling tools and vessels, as well as adsorption of the analytes on the surface of the collection and storage tools, has to be strictly avoided or as far as possible minimized for the collection of liquid, sometimes also solid samples with very low or only slightly elevated natural levels. These analytically difficult matrices include e. g. blood, urine, human milk, wet precipitation, sea water, fresh water, soil solution and some basic food materials. Typical trace element levels in human body fluids, sea and fresh water 57 are given in Table 1.1 and Table 1.2 and have been taken from various, predominantly recent sources. From these data, it is obvious that the subsequently applied determination methods also have to be extremely sensitive and reliable. For the proper dissection of human and animal tissues with trace element levels in the order of a few µg/kg or even less, the use of tools made from quartz glass, purified by rinsing with ultrapure acids, has proven to be very useful. - Also, the time of sampling, e.g., for body fluids and fresh waters (rivers, lakes) has to be considered. For waters it is also often useful to optimize the frequency of sampling to reduce the running costs of surveillance programs. - In many environmental samples, e.g., plants and soils, (Table 1.3), waste and industrial materials, the concentration of trace metals is often relatively high, e.g., at the mg/kg level. Thus, in these cases contamination plays no or only a very minor role. Here, the decisive terms for reliable environmental sampling are, for example, the selected (plant or animal) species considered as bioindicators or biomonitors and the homogenization procedures for reducing the basic material to manageable amounts in order to obtain representative analytical subsamples. This is especially important for heterogeneous materials that occur under various conditions. Furthermore, for environmental as well as for industrial materials the place of sampling is very closely linked to a proper sampling strategy. - Finally, for all sampling tasks the careful selection of a statistically relevant number and mass of individual samples is very important and greatly depends on the distribution and concentration of the analyte in the collected material, i.e. its homogeneity or heterogeneity. 58 59 60