Global Approaches to Environmental Management on Military Training Ranges. Tracey Temple

21]. The tool also enables the sampler to collect the increments from an upright position, greatly facilitating the process. Sampling bias is also reduced as the coring bit is pushed into the soil by the sampler’s foot, aiding in the penetration of the coring bit through surface vegetation, a situation that will cause a sampler using a spoon or trowel to seek an easier location to sample. The coring tool will help minimize ME during sampling, reducing the total sampling error.

      Figure 2.6. An example of a sampling tool for obtaining uniform soil increments.

      Sample handling is a very important aspect of sampling that is often overlooked, especially in the field. Most effort is focused on a chain of custody procedures, which are necessary but do not address sample integrity. Each sample collected in the field represents not only the DU from which it was obtained but a significant investment on the part of the entity tasked with sample collection. Sample labeling and documentation are thus a very important step in the field sampling process. Most MI samples should be collected in lab-grade clean polyethylene bags. The samples are labeled on the outside of the bag with an ink marker and recorded in a field notebook. Before sealing the bag with a plastic wire tie, we fill out a plastic tag with a sealable cover as a secondary label for each sample (figure 2.7). If the notation on the bag rubs off or becomes illegible, the tag can be used to identify the sample. If the tag is lost, the bag may retain enough information to identify the sample. The tag is also be used to ‘track’ the sample if it is rebagged for any reason. By transferring the tag to the new bag, all the original information is retained. During a field campaign at a closed military range, a contractor would not allow the employees to fill out and attach a tag to each sample. During shipping, the nomenclature rubbed off three sample bags, one of which was for a triplicate sample. The samples had to be reacquired at a cost of over USD 150 000 to the project.

      Figure 2.7. Field labeling of samples: bags with tags (left) and close-up of tag (right).

      Many soil samples will contain very low concentrations of munitions constituents. Cross contamination between samples from potentially high concentration DUs with samples known to be from areas of low potential contamination is very possible. A sample must be double-bagged in the field after documentation and stored separately during transportation and when in the lab. This precaution significantly improves the sample quality by reducing the variance between sample replicates.

      Using the correct sample preparation techniques is also critical in maintaining sample quality [26, 27]. Subsampling of the DU sample must be done carefully. A large source of error occurs during comminution, the process used to reduce the variance in particle sizes in the sample, which allows more uniform distribution of the analytes within the total mass of the sample. Diminution typically is conducted with a grinder. Puck grinders, used in the mining industry, have been found to achieve the best results based on lab, field and project studies. It is important to follow the correct grinding procedures, as the analyte can be lost during grinding, as was found when using a ball mill. Subsampling should be done in the lab following grinding, never in the field using sample splitting. The process must ensure that the subsamples represent the sample, much as the sample must represent the DU from which it was taken. If not, the subsample will be no better than a grab sample. In section 2.7 we will go into detail on field splitting, sample preparation in the processing lab, grinding to reduce sample particles to a more consistent size (comminution) and subsampling.

2.5 Sampling

      Sampling is the process of obtaining a portion of a total population that represents that population as a whole. That portion is called the sample. Samples must be representative of the area as a whole from which they are collected or they will be meaningless, representing only themselves. How is a representative sample collected? This section will guide the reader through the process required to ensure that the samples collected will fulfill the objectives that the sample is required to meet. Subsampling, the process of obtaining a portion of a collected sample that represents the sample as a whole and thus the total population, will be discussed in section 2.7.

2.5.1 Objectives

      Before going to the field to obtain samples, a sampling plan must be created. A key element of the sampling plan is the establishment of objectives that the samples are to meet. In the US, the Environmental Protection Agency has established a method based on what it calls the ‘data quality objectives (DQO) process’ [28]. The DQO process is iterative and will evolve as the project progresses. The SQC process, described in section 2.3.1, is a more direct approach that pares the development of objectives down to its essentials. Other countries have processes similar to these. The key elements for any sampling plan are that the sample must represent the mean concentration of the analytes in the DU, the samples must be reproducible (replicate samples from the field, not subsamples in the lab), and the data resulting from the analyses of the samples must be defensible. Without a robust sampling plan, the samples collected will not fulfill the objectives of the project.

      At this point, it is worth saying something about ‘hot spots’. The concept of hot spots has been around since samples were first collected. However, the definition of a hot spot has not [29, 30]. There are no mass, distribution, or availability criteria associated with a hot spot. Thus, hot spots are meaningless. If there is any analyte present in a DU, the highest concentration, the hottest hot spot, will be a million parts per million: a particle of pure substance (if it is present in that form). How many hot spots by this definition will occur within a DU? Many! Is there enough mass associated with these ‘hot spots’ to pose a risk to the receptor within the DU? The only way to determine this is to estimate a mean value of the analyte within the DU. Thus, the most important estimate that can be made within a DU is the mean concentration of the analyte. Hot spots are irrelevant.