Department of Health Seal

TGM for the Implementation of the Hawai'i State Contingency Plan
Section 4.2
USE OF MULTI INCREMENT SAMPLES TO CHARACTERIZE DUs

4.2 USE OF MULTI INCREMENT SAMPLES TO CHARACTERIZE DU's

The HEER Office strongly encourages the use of Multi Increment sample collection strategies to enhance sample representativeness in the investigation of contaminated soil. As described in this Section, Multi Increment samples are prepared by the collection and combination of a large number of small "increments" of soil from multiple locations within the targeted Decision Unit (DU). Multi Increment samples improve the reliability of sample data by reducing the variability of the data compared to past discrete sampling strategies (Ramsey and Hewitt, 2005; Jenkins et al., 2005). Multi Increment sample data generally have much lower variability than discrete sample data and a higher reproducibility. Higher reliability supports greater confidence for decision making.

The theory supporting Multi Increment sampling is based on particulate sampling approaches developed by geologist Pierre Gy to improve the quality of data for mineral exploration and mining (Pitard, 1993, 2005, 2009; USEPA 1999c; Minnitt et al., 2007). The approach can be used for both non-volatile and volatile contaminants, and testing of both surface and subsurface soils. The approach can also be used for sediment. These topics, as well as the use of Multi Increment sampling for stockpile investigations are discussed separately below, following a general discussion of Multi Increment sample collection.

To properly infer a representative average contaminant concentration by collecting and analyzing only a small portion of soil within the DU, it is very important that the sample collection and analysis be both unbiased and precise. Unbiased sampling requires random increments to be collected using the appropriate sampling tool and sampling method. Collection of precise samples requires an adequate volume of soil as well as a sufficient number of random increments from across the DU. Precision and absence of bias are needed to meet the Data Quality Objectives (DQO) established for soil investigations during systematic planning. Representative samples are generally collected with a soil coring device or other equipment to collect core-like samples across the DU from a minimum of 30 to 75 systematic random or stratified random locations. The resulting data are used to estimate average contaminant concentrations for the targeted area and volume of DU soil as a whole.

A Multi Increment sampling approach is recommended for the investigation and characterization of contaminated soil. Alternative approaches should be clearly discussed in a Sampling and Analysis Plan (SAP) presented to the HEER Office for review and meet data quality standards of Multi Increment sampling methods. This includes the need to test and verify the field precision of data (e.g. for any discrete sampling).

For surface soils where the use of hand tools is feasible, Multi Increment soil sample collection is relatively simple to accomplish (typically for non-volatile contaminants). Multi Increment soil sampling is more time and cost intensive for subsurface soils because in many situations, soil-drilling equipment or soil excavation equipment must be used. Limitations of the sampling data should be clearly discussed in the site investigation report if the recommended minimum number of increments (e.g., 30 to 75) cannot be collected in a subsurface DU due to site or cost constraints (e.g., reduced certainty in mean concentrations of targeted COPCs). Under these circumstances, it is important that a judgment call be made prior to sampling as to whether collecting limited sampling data would meet the DQO of the investigation, or some other option should be pursued as an alternative. The collection of replicate samples from one or more DUs will assist in evaluating the precision of the data (see Subsection 4.2.7).

Multi Increment sampling of subsurface soils contaminated with volatile chemicals involves similar challenges and warrants careful review of DQO, as well as options available for sampling. In addition, Multi Increment sampling for volatiles requires close coordination with the laboratory to implement appropriate modifications to the traditional "methanol method" for volatiles sampling in soils (see Subsection 4.2.8).

Professional judgment is critical in reviewing relevant information and choosing DUs where COPCs will be representatively sampled. Decision units represent the desired scale of mean contaminant concentration for decision making. As discussed in Section 3, considerations in choosing DUs include:

  • Present and potential future exposure scenarios;
  • The type of environmental hazard presented by the COPCs;
  • Knowledge of any spill areas;
  • Site physical characteristics that could influence the distribution of COPCs (e.g. soil types);
  • Historical information on past site activities (e.g. Phase 1 ESA or equivalent reports);
  • Observations from a complete site walk around;
  • Documentation of any areas not accessible for sampling;
  • Evaluation of any existing (site or adjacent land) screening or sampling data;
  • Other relevant factors.

Based on a review of such information, judgment is used to define DUs that will best represent COPCs at the site. Once DUs are selected, representative sampling methods are employed to sample and infer average contaminant concentrations across each DU. A single Multi Increment sample is collected to represent a DU, with replicate samples collected in at least 10% of the DUs to evaluate the combined field and laboratory precision of the data. Assuming the data meet precision requirements established in the DQOs, the average contaminant concentrations are compared to applicable HDOH Environmental Action Levels (EALs) or approved, alternative screening levels to make decisions regarding the need for any subsequent response actions.

4.2.1 MULTI INCREMENT SAMPLING METHODOLOGY

Multi Increment samples are prepared by collecting a large number of small increments of soil from random locations within a specified DU (Figures 4-8a&b). The increments are combined into a single bulk sample referred to as a "Multi Increment sample."

Figure 4-8a. Example Decision Units (see also Section 3.4)
DU for spill area contaminated with lead. Flags represent increment locations for confirmation sample collected at bottom of excavation.

Figure 4-8b. Example Decision Units
DU for hypothetical, residential lot on former agricultural land. Rows and increment collection points start from a single random location, and are arranged in a manner that ensures a minimum of thirty increments are collected across entire DU.

Most DUs will be tabular in shape, with the length and width significantly greater than the vertical thickness, similar to a flat lying book. Cores used to collect increments should typically cover the entire thickness of the DU. Note that there may be one or more designated vertical DUs below ground surface, depending on the site DQOs, or to further delineate the results from initial surface interval DUs. It is important that increments collected within a targeted DU be of the same approximate mass, shape, and size (see Subsection 4.4). An exception to the latter is a scenario where the thickness of the targeted layer of soil varies within the DU (e.g. very thin soil over bedrock, or an obvious layer with specific soil characteristics that is targeted in the DQOs). In this case the increment should again cover the entire thickness of the DU, but increment lengths and masses will vary to target the specific (variable-depth) layer. This allows for individual increments to be more representative of the volume of soil represented by that DU. A variable total mass of sample may also apply to subsampling of cores extracted from subsurface DUs, where a regular subsampling spacing is used between core increments (e.g. every 2-4 inches), but different total subsample masses may be generated from different vertical layer depths being sampled.

It is important to identify and document significant specific areas of soil within a proposed DU or site that are not accessible for sampling (e.g. under building foundation pads [unless drilled], very dense un-cleared vegetation, areas down steep inclines, etc.). These areas represent "data gaps" when reporting sampling results. Any area that is not accessible for systematic random sampling in the targeted DU(s) is not represented by the mean contaminant concentration determined with MI sampling. Inaccessible areas should be clearly identified in the site investigation report and on site maps. 

4.2.2 MINIMUM NUMBER OF INCREMENTS

The number of increments to be selected for the Multi Increment samples in a site investigation should be evaluated during systematic planning as part of the DQO and documented in the SAP. A minimum of 30 to 75+ increments per sample is recommended. This is based on MI sampling theory, 10 years of MIS field work experience in Hawai‘i, as well as additional published information (refer to Subsection 4.1; ITRC, 2012).

A minimum of 30 increments is recommended for release scenarios where small-scale variability (i.e. variability at the scale of an individual increment) can be assumed to be relative low. This includes soil suspected to be contaminated by aerial fallout (e.g., downwind of an incinerator) or for liquid-based chemicals that were released in a uniform manner (e.g., sprayed, water-based pesticides). A minimum of 75 increments per sample is recommended for contaminants suspected to be present as small nuggets in soil. This includes chips of lead-based paint, lead shot, oil-based chemicals that could form clumps in soil after release (e.g., PCB-infused transformer oil), and munitions and explosives of concern (MEC). A minimum of 50 increments per sample is recommended for other release scenarios. This includes, for example, characterization of fill material that includes lead-contaminated incinerator ash and sites where the relative degree of contaminant heterogeneity is uncertain. These minimum increment numbers are provided for initial guidance only. The representativeness of Multi Increment samples and precision of the resulting data for a site should ultimately be evaluated through the collection of replicate samples, as discussed in Subsection 4.2.7.

The number of increments incorporated into the field Multi Increment samples, and the overall mass of the Multi Increment samples collected are not dependent on the size of the decision unit. If the decision unit is the size of a small backyard garden suspected to be impacted by sprayed pesticides, then a minimum of 30 increments of similar mass is collected. If the decision unit is a 10-acre former field likewise suspected to be impacted by sprayed pesticides, then a minimum of 30 increments of a similar mass is again collected.

It may be desirable to increase the number of increments whenever contaminant distribution is expected to be especially heterogeneous or demonstrated to be so by replicates samples. Collection of an increased number of increments in each DU would be expected to reduce field sampling error and minimize the variation from the mean among replicate samples used to evaluate representativeness of the data collected. This could be especially important if the contaminant concentrations are very near the EAL, where the degree of sampling error could be critical for a final site decision (see Subsection 4.2.7).

4.2.3 TARGET MULTI INCREMENT SAMPLE MASS

Individual soil increments typically weigh between 5 and 50 grams, with bulk Multi Increment samples typically weighing between 300 and 2,500 grams (mass sufficient to minimize Fundamental Error for sample collection) after sieving soil samples to the target particle size. A target bulk sample mass of 1,000 to 2,500 grams is recommended for samples to be tested for non-volatile chemicals. Note that sieving of soil samples to the < 2mm particle size, typically performed in the laboratory sample preparation process for testing of non-volatile chemicals, will reduce the amount of soil mass available for analysis. This needs to be taken into consideration during the collection of samples in the field.

The target bulk sample mass should be reflected in the target mass of individual increments. For example, a target 1.5kg bulk sample can be prepared by the collection and combination of 50, 30g increments. A minimum 10g increment mass is required to obtain a minimum bulk sample mass of 300 grams for a 30 increment bulk sample. The final mass of the Multi Increment samples depends on the number of increments collected and the size (i.e. coring tool diameter) and depth of the increments. Although based primarily on sampling theory and the need to collect a representative sample, the sampling scheme should also be reviewed with the laboratory to ensure that the final mass will be adequate for the total number and type of analyses planned and QA/QC requirements.

Care should be taken to ensure that individual increments are of adequate mass to produce the target mass of the bulk Multi Increment sample. Removal of large sticks, stones and other particles from bulk Multi Increment samples can be carried out in the field. Processing of samples in the field, such as sieving for the designated analysis particle size, is generally not recommended due to the potential to introduce additional error into the data under variable field conditions. In most cases processing is best carried out in a controlled laboratory setting (see Subsection 4.2.6).

Any processing of bulk MI samples that does occur in the field, including representative subsampling to reduce the bulk sample size or sieving bulk samples to the designated analysis particle size should be conducted under an established operating procedure developed as part of the Sampling and Analysis Plan. This field processing procedure should accommodate contingencies for variable weather conditions, include appropriate equipment and work station set-up to carry out the processing and clean equipment as may be needed. Field processing of samples should be documented with photos, recorded in the sample log, and discussed in the site investigation report (see Section 5.5).

The collection of 1,000 g or more of soil may not be practical for samples to be tested for volatile chemicals, due to the large amount of methanol required (see Subsection 4.2.8). The use of one-liter amber jars to collect soil samples will normally limit the mass of soil that can be collected to approximately 300 grams, or 60, five-gram plugs of soil (assuming a 1:1 soil to methanol ratio). Testing and discovery of VOCs over EALs in vadose-zone soil should normally be accompanied by the concurrent or followup collection of groundwater (Section 6) and/or soil vapor samples (see Section 7). Volatile chemicals primarily pose potential leaching and/or vapor intrusion hazards. These concerns can be more directly addressed through testing of groundwater and soil vapors.

4.2.4 INCREMENT DISTRIBUTION

4.2.4.1 SYSTEMATIC RANDOM GRIDS

A systematic random ("systematic") increment collection scheme is recommended for the collection of a Multi Increment sample from a DU (Figure 4-9). Under this approach increments are collected in a grid fashion at a fixed spacing, beginning from a random starting point in the DU. Systematic sampling approaches have been demonstrated in field studies to generate more reproducible data than purely random approaches, where each increment location is independently selected, as well as stratified random or related sampling schemes (Figure 4-10; see ITRC 2012). The collection of closely spaced increments from more widely spaced rows as depicted in Figure 4-10 is likewise not considered to be reliable.

Figure 4-9. Example Increment Collection Locations Based on a Systematic Random Grid Scheme
Grid spacing determined based on DU area and number of desired increments. Initial increment location selected from random location, subsequent increments collected at uniform spacing within DU.

Figure 4-10. Examples of Simple Random (a) and Stratified Random (b) Increment Location Patterns and Collection of Closely Spaced Increments from More Widely Spaced Rows (c)
Each approach leads to uneven coverage of the DU and has been demonstrated in field tests to be less reliable and reproducible than systematic random sample collection (see Figure 4-9).

Systematic sampling requires that increment locations be evenly spaced between all axes of the grid to the extent feasible in the field. The spacing of increments within a DU is a function of the area of the DU and the number of increments to be collected. The increment spacing is calculated as the square root of the DU area divided by the targeted number of increments:

   Eq. 1.)

The calculated spacing reflects hypothetical division of the DU into a number of cells equal to the targeted number of increments (see Figure 4-9). The area of each cell is calculated as the total area of the DU divided by the number of increments. Taking the square root of this area yields the length of the each side of the cell, assuming a square shape.

Actual increment collection locations reflect a random offset of this grid, with increments collected from an identical (i.e., systematic) location within each cell. The spacing can be slightly adjusted (e.g., rounded to nearest whole foot) as needed in the field to aid in establishing the grid in the field for sample collection.

In the example depicted in Figure 4-9 the increment is collected from the lower left-hand corner of each cell. In the field the initial increment point can be placed anywhere within the targeted spacing distance of the DU corner; i.e., anywhere within the first cell. This point is subsequently used to establish a grid of increment collection points within the DU using the spacing estimated from the above equation.

For example, consider a 5,000 ft2 DU from which a Multi Increment sample composed of 50 increments is to be collected in a systematic random fashion. A target increment spacing of 10 feet is calculated. This reflects a hypothetical division of the DU into 50, 10 ft by 10 ft cells, each with an area of 100 ft2. An initial increment collection location is then randomly designated in a corner cell, for example 2 feet in from either direction. A grid with a spacing of 10 ft is then initiated at this point outward toward the boundaries of the DU until the next subsequent point would fall outside of the DU boundary. Table 4.1 provides approximate increment spacing in feet for a range of DU sizes and numbers of increments selected.

Table 4-1. Approximate Increment Spacing (in feet) for Decision Unit Area (see Equation 1)
Number of Increments Decision Unit Area (acres)
0.10 0.20 0.25 0.50 1.0 2.0 3.0 4.0 5.0
30 12 17 19 27 38 54 66 76 85
40 10 15 16 23 33 46 57 66 73
50 9 13 15 21 29 41 51 59 66
75 8 11 12 17 24 34 41 48 54
100 7 9 10 15 21 29 36 41 46

This approach will work for DUs of any shape and size in most cases, including squares, rectangles and DUs with irregular or unequal sides. In the latter case the number of increments collected within rows may differ in different parts of the DU (Figure 4-11). The increment spacing calculation remains the same, however. When possible, inclusion of at least one, square corner for a DU from which to initiate increment collection will greatly facilitate establishment of a grid within the rest of the DU and help expedite sample collection. Note that the collection of increments from partial cells along the outer edges of the DU will result in a somewhat larger, final number of increments than initially used to establish the grid spacing (e.g., upper boundary and right boundary in Figure 4-11).

Figure 4-11. Systematic Increment Locations for Odd Shaped DUs (compare to Figure 4-9)
The number of increments collected within grid rows can vary in different areas of the DU.

Figure 4-12. Example Collection of Increment Location Points for Triplicate Multi Increment Samples
Increments collected in a systematic random method. Circles, triangles and squares depict increment collection locations for three, respective Multi Increment samples (increments collected halfway between initial increment grid point locations).

Exceptions to the above approach include long, narrow DUs where the width is less than the increment spacing calculated above, for example a drainage ditch (see following subsection). In this case the length of the DU should simply be divided by the desired number of increments and this distance used to space increments.

A simple approach for the collection of field replicate samples and in this case triplicate Multi Increment samples is depicted in Figure 4-12. In this example the initial increment is collected from a random location within the lower quarter of the initial increment collection cell. The first Multi Increment sample, represented by the filled circles, is collected in the same manner as described above. The increment collection grid is then shifted half-way of the calculated increment spacing in the direction of the X axis and then the Y axis for the collection of two replicate samples, represented by the filled squares (increments locations for 2nd Multi Increment sample) and the filled triangles (increment locations for 3rd Multi Increment sample). The collection and evaluation of replicate data is discussed in more detail in Subsection 4.2.7.

The above increment spacing examples are for general guidance only. Other increment collection schemes are possible. An effort should be made, however, to ensure that increments are evenly spaced and distributed within a DU. Replicate samples should be collected to verify the reproducibility of the sampling approach. The final approach used to space and collect increments should be clearly described in the site investigation report.

4.2.5 SAMPLE COLLECTION

A detailed, logistical discussion of the collection of increments and Multi Increment samples in the field is provided in Section 5. An overview of the basic design of Multi Increment sample collection is provided below.

4.2.5.1 LOCATING INCREMENT COLLECTION POINTS

The corners of the DU(s) (or enough points to delineate the DU shape, if irregular) should be recorded via Global Positioning System (GPS) to document the DU location. Note that GPS location information can be several meters off. Use of tape measures or equivalent approaches in the field is recommended to document the exact dimensions of a DU. If there are buildings on the site near established DUs, physical (tape) measurements from these fixed locations can also be made to help generate maps and GPS DU locations using existing GPS map resources.

Approximate increment spacing should be estimated using Equation 1 given in Subsection 4.2.4.1. A tape measure (or careful pacing) can be used to identify increment locations within the DU. Documenting or flagging the location of every individual increments collected within a DU is not necessary, although spacing and number of increments collected per DU should be stated in the site investigation report. Flagging the locations of increment rows along the perimeter of a DU is usually adequate to guide collection of increments within the DU itself (Figure 4-13). A few rows of flags can also be placed within large or long DUs as needed to help guide increment collection.

Figure 4-13. Example Flag Placement (red circles) for Collection of Increments in the Field
Increment collection direction noted by arrows.

Figure 4-14. Collection of Increments in a Long, Narrow DU
Tape measure or measured rope placed in DU; arrows indicate direction of increment collection (note even placement of increments).

Use of a GPS in the absence of flags can expedite the location and collection of increments for very large DUs, where error in increment location within a few meters is acceptable and where pacing might not be accurate or practical due to vegetation, topography, or other access issue (e.g., tens or hundreds of acres).

Increments should be collected in an evenly spaced, zig-zag pattern in long narrow DUs, as depicted in Figure 4-14. A tape measure or rope with flags tied at the appropriate spacing can be placed in the DU to assist in increment collection, without the need to flag individual points.

4.2.5.2 INCREMENT AND BULK SAMPLE COLLECTION

Figure 4-15. Multi Increment Sample Collection
Collect an "increment" of soil at each point. In this example (very soft soils), a sampling tube is used to extract a cylindrical volume of soil to a depth of approximately 10 cm. Each increment typically weighs 20 to 50 grams. Subsequent increments for the target DU are placed in the same container.

Figure 4-16. Core-shaped Versus Wedge-shaped Increments
Core-shaped increments provide equal coverage across the entire targeted depth of soil. Hand trowels are more likely to produce wedge-shaped increments with most of the soil coming from the upper few inches of the targeted depth.

A detailed logistical discussion of the collection of increments and Multi Increment samples in the field is provided in Section 5. Individual increments collected are placed into a single sample container to produce the bulk, Multi Increment sample (Figure 4-15).

Using the wrong tools or collecting a sample that contains more soil particles from the top of the targeted DU than the bottom will lead to biased sample results and potentially non-representative data, due to a heterogeneous vertical distribution of contaminants in the soil. As shown in Figure 4-16, a core-shaped increment is ideal.

Core-shaped increments can be collected using a soil coring sampler, soil sampling tubes (both preferred), or drills with specialized bits. This ensures equal coverage at all depths of the targeted DU layer. Hand trowels tend to produce wedge-shaped increments, with a bias towards the upper section of the targeted soil and are generally not recommended. If used, an effort should be made to extract core-shaped increments.

Figure 4-17. Increments Combined to Generate 1-2 kg Bulk Multi Increment Sample
Note that the collection of co-located increments or "splits" of initially collected increments for later, individual testing is not recommended or valid in terms of sampling theory. The prevalence of random, small-scale variability of contaminant concentrations within small masses of soil negates the reliability of any given increment to be representative of the immediately surrounding soil (refer to Subsection 4.1.2). Simple "splits" of increments can vary by orders of magnitude, as can the concentration of contaminants between co-located increments or discrete soil samples.

Proper planning should be carried out to ensure that the final bulk Multi Increment samples will be reasonably close in size to the original targeted mass (e.g., 1-2 kg; Figure 4-17). Processing of a bulk Multi Increment sample in the field to reduce the mass of soil beyond removal of sticks and large rocks is not recommended, due to potential logistic issues and weather-related conditions that could introduce error into the sample data. This can be accomplished by establishing a target mass for individual increments up front and using proper tools to collect the increments.

Testing of smaller groupings of increments collected within a single DU (e.g., four groupings of ten increments each) is likewise invalid, since the resulting data cannot be assumed to be representative of the area from which the increments were collected. Doing so may be wasteful of both field time and analytical budgets. The collection of an adequate number of increments and sample mass from each area during the initial field work should not add significantly to the time or cost of the project and will significantly improve the usefulness and reliability of the resulting data.

If a greater resolution of contaminant distribution might be required for a targeted area then the initial designated DU should be subdivided into smaller DUs from the start, with a defensible Multi Increment sample collected from each area (refer to Section 3.4.1). The same holds true in cases where significant contamination is identified in a large DU where contamination was not initially anticipated. If a greater resolution is subsequently desired to optimize remedial actions, then the DU should be subdivided accordingly, and proper Multi Increment samples collected from each new DU.

4.2.6 LABORATORY PREPARATION OF SAMPLES

Talk to your laboratory ahead of time to ensure they are familiar with the Multi Increment sampling strategy and associated laboratory drying, sieving, and subsampling requirements, as well as minimum laboratory subsample mass requirements based on particle size, and other topics discussed below. Discrete soil samples, if collected, should also be processed in the manner described if the investigation DQOs requires that data representative of mean contaminant concentrations in DUs be obtained.

Data for samples that are not processed at the laboratory using procedures described in this subsection, or equivalent, cannot reliably be considered representative of the bulk MI samples provided from the field. Documentation of sample processing methods should be included in the laboratory report and summarized in the investigation report. Ensure that the laboratory has a Standard Operating Procedure for Multi Increment sample processing and analysis that conforms to HDOH recommendations prior to submittal of samples for testing.

Bulk MI samples collected in the field should be kept to a maximum mass of approximately 2 kilograms unless otherwise coordinated with the laboratory, due to handling and storage limitations. Laboratories might charge extra for processing and disposal of excess soil. Sample mass can be reduced in the field using incremental subsampling methods if a larger amount of soil is inadvertently collected (see Subsection 4.2.3). This is not recommended as a standard practice, however, due to the potential to introduce additional error and uncertainty into the data. Any field processing of bulk samples should be clearly described in the investigation report.

Laboratory processing of Multi Increment samples typically consists of the following steps:

  • Empty entire bulk sample onto tray made of or lined with material compatible with contaminant of interest and drying temperature;
  • Spread evenly into thin layer;
  • Allow to air dry until a constant weight is established by re-weighing or air dry until soil agglomerates are crushable and a separate subsample can be used for moisture analysis and dry weight correction;
  • Sieve entire bulk sample to <2mm to remove greater than "soil-sized" particles;
  • Subsample entire sieved portion using a sectorial splitter or Multi Increment sampling methods to collect appropriate mass for each targeted analysis (minimum ten grams for the <2 mm particle size; including testing for metals).

Soil particles <2mm sized are generally considered "soil" for the purposes of an environmental investigation and contaminant analysis, including comparison of data to risk-based action levels (HDOH 2016). Sieving to <2mm to remove gravel, sticks and other large debris also establishes the maximum particle size of the sample, which is necessary (in accordance with sampling theory) to determine the minimum subsample mass necessary for extraction and analysis in the laboratory.

Although sieving to the <2mm particle size is typical, there could be contaminant investigations or analyses where alternate particle sizes are of interest. For example, bioaccessible arsenic tests require that the <250µm fraction be tested (see Section 9). In these cases, the rationale for sieving to other specific particle sizes (and associated changes to lab processing/analysis) should be clearly discussed in the DQO/SAP.

In certain cases, grinding of the sample may be required to reduce Fundamental Error and/or include contaminants in larger particles in the data. Grinding is not recommended as a default step in sample processing, however, unless specified by EPA analysis method (e.g. Method 8330b for explosives residues). The HEER Office should be consulted when grinding is proposed as part of the site investigation Sampling and Analysis Plan.

Sample processing is discussed in more detail in the sections below. Contaminant analyses of all soil samples, regardless of how they were collected, should be reported on a dry weight basis. Data for samples that are air dried to constant weight and sieved prior to analysis can be considered dry weight without additional analysis for moisture content. The moisture content should be tested for samples that are not dried prior to the collection of subsamples for analysis (e.g., TPHd and semi-volatile chemicals). Any remaining soil is disposed of by the laboratory, normally after thirty days (consult laboratory for details). If archiving of samples is warranted or decisions on potential additional analyses of remaining MIS soils have not been made within 30 days, special arrangements should be made with the laboratory for longer-term storage.

4.2.6.1 SAMPLE PROCESSING

Bulk Multi Increment samples should be spread into a thin layer (~ 0.5 to 1.0 cm) on a large tray and placed in a ventilated area. Aluminum or plastic trays are commonly used for drying, but should be avoided if aluminum, phthalates or other plastic components are contaminants of potential concern. Paper liners should be avoided if organic carbon is to be tested for or if contaminants are present that could sorb to the paper (e.g., heavy oil).

Samples to be tested for non-volatile chemicals should be air dried under ambient conditions (e.g., 15 to 30°C). Soil moisture content should be reduced to achieve a constant air-dried weight for the samples, as determined by periodic re-weighing or air dry until soil agglomerates are crushable and a separate subsample can be used for moisture analysis and dry weight correction. Drying times can vary between a few hours for course soils with initially low moisture to several days for wet, fine-grained soils. Higher temperature (and faster) drying methods are acceptable provided that the laboratory has a Standard Operating Procedure and it has demonstrated this procedure will not result in significant chemical loss or transformation.

Wet, clayey samples should be periodically crushed with a pestle to avoid formation of hard bricks. Disaggregation should be done in a manner that avoids crushing of rock fragments and other naturally large particles. More intensive particle reduction methods (e.g., grinding) are described below.

Samples should be sieved to <2mm following drying and then subsampled as described below. Note that soil (or sediment) samples that consist entirely of <2mm material do not require drying and sieving to address fundamental error concerns, although some degree of drying and sieving may be desirable by the laboratory for testing purposes. Exceeding recommended holding times for non-volatile chemicals in order to permit drying, sieving, and more definitive subsampling and data is generally acceptable but should be minimized to the extent practicable (see Section 11; see also USEPA, 2003c).

4.2.6.2 SUBSAMPLE COLLECTION

Subsampling for collection of a mass of soil for extraction and analysis is accomplished with a sectorial splitter (Figure 4-18; also called a rotary riffle splitter, this subsampling method is generally considered best). Note that multiple splits using a sectorial splitter may be necessary to reduce the bulk sample mass down to the desired amount for extraction and analysis. As an alternative, a representative subsample can be collected by removing approximately 30 small increments in systematic random locations and of sufficient mass to generate the desired subsample for testing (Figure 4-19). The processed sample (e.g. dried and sieved) is spread into a thin (e.g., < 1 cm) layer for collection of subsample increments when using the MI subsampling method.

Figure 4-18. Use of a Sectorial Splitter to Collect Laboratory Subsamples from Bulk MI Field Samples
Sectorial splitter (rotary riffle splitter) used to collect lab analysis subsamples from a bulk Multi Increment sample that has been dried and sieved to the < 2 mm particle size. If a sectorial splitter is not available, then collect Multi Increment subsamples of appropriate mass by hand (see Figure 4-19).

Figure 4-19. Manual Collection of Subsamples in the Laboratory
The laboratory subsamples the bulk Multi Increment sample that has been air-dried and sieved to the < 2 mm particle size. Approximately 30 increments are collected. The mass of each increment is based on the total mass of sample needed for the relevant analyses (typically a minimum of 10 grams).

Subsampling is used to collect a representative mass of soil from a single Multi Increment sample (and any lab replicates), and to provide representative subsamples for multiple analyses. The mass of soil needed for the analytical test or tests is used to determine the parameters for splitting the sample with the sectorial splitter, or in determining the mass of each subsample increment if collected by hand. In either case, it is critical that the entire mass of dried and sieved sample be utilized for the subsampling process.

The Gy sampling theory, which is the foundation of the Multi Increment sampling approach, is also the basis of two primary references on laboratory subsampling and analysis of particulate samples: United States Environmental Protection Agency (USEPA, 2003b) and American Society for Testing and Materials (ASTM, 2003). These, as well as the laboratory processing information provided in the ITRC Incremental Sampling Methodology guidance (ITRC, 2012), are recommended as lab guidance by the HEER Office. Of all the laboratory steps necessary to process and analyze environmental samples, subsampling is widely believed to present the greatest potential for error. The lab subsampling guidance applies to all types of soil samples collected in the field, whether Multi Increment, discrete, or judgmental samples.

One issue discussed in both the USEPA and ASTM guidance documents is the choice of a minimum subsample mass for extraction/analysis of soil samples in order to reduce "Fundamental Error" of the lab analyses to approximately 15% or less, which is also recommended by the HEER Office as a primary lab data quality objective (see also ITRC, 2012). The minimum appropriate mass is based on the maximum particle size in the soil samples. For samples with a maximum particle size of <2mm, the minimum extraction/analysis mass is 10 grams.

Laboratories may need to modify USEPA methods appropriately to achieve the minimum 10 gram subsample mass for extraction and analysis (for example modify extractions for metals analysis), or conduct multiple small subsample extractions and combine them for analysis. This is primarily a concern for metals, where methods may call for only one gram to be tested. With the possible exception of mercury, extraction and testing of 10 g subsamples is feasible for most metals if specifically requested. Mercury sample extraction mass might be limited to 5 grams or several grams due to the laboratory method involved. If this is the case, then a minimum of five grams should be extracted, with multiple extracts combined and tested as a single extract solution as necessary. Milling of samples is another option, provided that the method used does not generate excess heat that could cause elemental mercury to volatize (see Subsection 4.2.6.3). If the laboratory is unable to test the recommended minimum sample mass for any analyses, then replicate subsamples (i.e. triplicates) should be tested for these samples in order to evaluate subsampling precision.

For analyses of fine particulates (e.g., < 250 μm), a one-gram subsample may in theory be adequate to reduce Fundamental Error below 15%. If a larger mass can be reliably run by the method (e.g., 2-10 grams), however, the HEER Office recommends doing so to help reduce opportunity for error. Note that this applies to bioaccessible arsenic tests (see Section 9 for bioaccessible arsenic information).

4.2.6.3 PARTICLE SIZE REDUCTION

Milling ("grinding") of samples beyond crushing of soil clumps by hand or using a simple mortar and pestle is not normally recommended as a default sample processing procedure, unless specified by an EPA analysis method (e.g. Method 8330b for explosives residues). However, milling could be necessary in some other specific cases, and these should be discussed with the HEER Office as part of the planning process for site investigations. Data for sieved but un-milled samples are typically more appropriate for evaluation of chronic health risks under current site conditions. The evaluation of direct-exposure risk to contaminants in soil is generally based on the concentration of the contaminants in the < 2 mm or smaller particle fraction of the soil (USEPA, 2011d). Milling of the < 2 mm fraction can also overestimate the risk posed by metals in rock fragments and mineral grains that would otherwise be tightly bound and not available for uptake.

Milling of soil samples could be appropriate in the following circumstances:

  • Presence of large (i.e., > 2 mm) fragments of contaminants in the sample that could contribute to the potential risk to human health and the environment;
  • Need to reduce particle size to address Fundamental Error and achieve greater reproducibility of analytical results, or
  • Need to test smaller subsample masses (e.g., ≤ 10g; refer to Subsection 4.2.6.2)

Examples of the first scenario include the suspected presence of large chips of lead-based paint in soil around the perimeter of a building. The chips could break down overtime into finer particles. In such cases testing of both un-milled and milled samples should be carried out to evaluate current and potential future risk. The same is true of lead shot in soil. Samples should be milled if particles that could pose potential leaching hazards are present in the sample and could be excluded from the data if un-milled samples are tested (e.g., large nuggets of munitions related compounds such as RDX). Note that batch leaching tests are normally run on subsamples from un-milled samples. As noted in Subsection 4.1, releases of PCB containing oils and similar liquids can form "nuggets" in the soil, causing error in both sample collection in the field and subsample collection in the laboratory.

Milling can be especially useful when data for replicate, Multi Increment samples are highly variable, in order to help discern if the problem is related to field versus laboratory error. Milling samples to achieve very uniform small particle sizes can help reduce Fundamental Error and improve the precision of laboratory subsampling when replicate data suggest a problem. Milling also allows for a smaller subsample and extraction/analysis mass for non-volatile contaminants.

Refer to the ITRC Incremental Sampling Methodology document for a detailed review of milling options (ITRC, 2012). Milling of a minimum 300g of soil is recommended (minimum mass necessary to address Fundamental Error; see Subsection 4.2.3). Milling of larger masses (e.g., 1kg) is preferable. Milling of a minimum 20g subsample is recommended in cases where milling of larger masses is not feasible. Collection of a representative subsample following the procedures described in Subsection 4.2.6.2 should be adhered to if the bulk sample is too large to be milled.

Puck and ring mills (“puck mills” Figure 4-20) and ball mills (Figure 4-21) are most commonly employed. Puck mills are able to reach a finer consistency, but can increase the temperature of samples and result in a loss of organic compounds. Puck mills can also normally only grind a small mass of soil at a time. Ball mills are able to mill larger masses of soil (e.g., up to 1+kg), provide more gentle, particle-size reduction and minimize heat generation in comparison to traditional puck mills. Ball mills cannot grid a sample to the same fineness as a puck mill but are normally adequate for environmental investigations.

Consider the chemical composition of the mill and target analytes of interest when selecting an appropriate mill. Pucks and rings in puck mills and cylinders in ball mills are typically composed of stainless steel, tungsten carbide and ceramic. Stainless steel pucks and rings or cylinders should, for example, not be used when chromium is an analyte of interest or when heat generation is a concern (e.g., elemental mercury). Ceramic equipment can contribute aluminum to the sample.

Note that non-elemental, mercury-based compounds used as fungicides at former sugarcane operations such as phenylmercuric acetate are not considered to be significantly volatile or susceptible to loss during processing, especially in aged releases to soil (USNLM 2016; see Subsection 4.2.6.4). Nonetheless, use of a ceramic mill is recommended in order to minimize heating of the sample.

USEPA SW-846 Method 8330b for processing and analyzing energetic compounds calls for grinding the samples to meet data quality objectives (USEPA, 2006d). This method also includes guidance on field Multi Increment sampling for energetic compounds. Note that suitable grinders are expensive, add cost to processing and analysis of samples, and may not be available at many labs.

Figure 4-20. Puck and ring mill, used to crush small masses of soil to very fine grain size

Figure 4-21. Ball mill with ceramic cylinders used for moderate crushing of large soil volumes

4.2.6.4 SEMI-VOLATILE AND UNSTABLE CHEMICALS

Samples to be tested for semi-volatile chemicals or non-volatile chemicals with a very short half-life (e.g., <30 days) should be immediately subsampled for testing after receipt by the laboratory and prior to air drying and sieving in order to minimize significant contaminant loss (e.g., >10% of original mass; see Appendix 4-A). Information on the collection of Multi Increment samples to be tested for volatiles is provided in Subsection 4.2.8.

For the purposes of this Section, a chemical is considered to be semi-volatile if its vapor pressure is between 0.1 and 1.0 mm Hg or if it is a liquid at 25ºC or if the Henry’s Law Constant exceeds 0.00001atm-m3/mol (USEPA 2015). Chemicals listed in the HDOH EAL guidance that fall into this category include TPHd, some PAHs, and elemental mercury. A chemical is considered to be unstable if its half-life is less than 30 days. This will most commonly be a potential concern for pesticides with a low persistence. These criteria might be overly conservative for aged chemicals in soil or other factors that could reduce volatility in comparison to fresh product. Discuss the acceptability to subsample without drying and sieving with the laboratory. Note and justify any deviation from the default recommendations in the laboratory report.

Appendix 4-A provides information on specific SVOCs (including TPHd, some PAHs, and mercury), pesticides and other chemicals that are highly biodegradable, chemically unstable, or otherwise have a low persistence (i.e., half-life less than 30 days). Refer to Section 9 and Appendix 9-B for a list of chemicals with low persistence that are known to be have been used in sugarcane and pineapple agriculture in Hawai‘i.

Multi Increment samples for SVOCs and unstable chemicals should be cooled immediately after collection. The samples should be subsampled and extracted for analysis within holding times recommended for those chemicals, as noted in Section 11 or otherwise agreed upon with the HEER Office.

At the laboratory, bulk Multi Increment samples to be tested for SVOCs and unstable chemicals should be spread out and subsampled prior to drying and sieving. Surface soil samples that have been exposed to air on site prior to sample collection are acceptable for air drying (if needed) even when determining higher vapor pressure SVOCs. This and other alternative approaches should be discussed with the HEER Office and described in the investigation Sampling and Analysis Plan. Check with the laboratory to determine feasibility of wet sieving the sample to remove > 2 mm particles prior to subsampling (see ITRC, 2012). An effort should otherwise be made to collect < 2 mm particles in lab subsamples (i.e. avoid collection of gravel or larger materials if possible). A separate subsample should also be collected from the wet material in the same manner as done for targeted analytes and used to test for soil moisture, so analytical results can be converted to a dry-weight basis.

Note that mercury in soils impacted by release of phenylmercuric acetate and similar mercury-based fungicides is not anticipated to be significantly mobile or volatile and normal MI sample processing methods are acceptable (USNLM 2016; see also Appendix 9-A and Appendix 9-B in Section 9). When released to soil, these compounds are expected to dissociate forming relatively stable cations and adsorb to organic matter and clay more strongly than the parent compounds. Volatilization from moist soil and water surfaces will not be significant. This is supported by high concentrations of mercury in surface soils at former sugarcane, seed dipping operations decades after the releases occurred (Section 9.1.4.3).

Follow standard sample drying and sieving methods described above if additional tests are required for non-volatile chemicals using a different lab analysis. If both SVOC and non-volatile PAHs are targeted as contaminants of potential concern then include testing for both in laboratory subsamples collected from the Multi Increment sample prior to drying and sieving. Note that testing of soil for semi-volatile PAHs potentially associated with diesel and other middle distillate fuels is no longer required (tested for groundwater only; refer to Section 9). Note also that naphthalene can be reported under most VOC analyses if the laboratory is notified ahead of time.

4.2.6.5 BIOACCESSIBLE ARSENIC

Multi Increment samples collected for arsenic analyses that contain >24 mg/kg total arsenic should subsequently be tested for bioaccessible arsenic (see Section 9.1.3.2; see also HDOH 2016). On some sites where numerous DUs exceed 24 mg/kg total arsenic, analyzing a subset of the samples for bioaccessible arsenic is acceptable (e.g., two or three samples with highest total arsenic). This should be discussed with a HEER Office project manager. The same Multi Increment samples collected for total arsenic (for example, the entire remaining < 2 mm fraction of these samples) should be further sieved to the < 250 µm particle size, representatively subsampled and analyzed for bioaccessible arsenic using the SBRC assay method (gastric phase only; this requires 1-2 grams; SBRC, 1999). Total arsenic in the < 250 µm fraction should also be reported by the laboratory to examine the magnitude of "enrichment" of total arsenic in the < 250 µm fraction compared to the < 2 mm particle size fraction.

4.2.6.6 OTHER LABORATORY ISSUES

High concentrations of iron and titanium in volcanic soils and calcium in carbonate-rich, coastal soils (or sediments) can interfere with the detection of other metals, resulting in an overestimation of metal concentrations:

  • High levels of iron and titanium can interfere with the detection of arsenic, beryllium and cadmium;
  • High levels of calcium can interfere with the detection of barium.

Notify laboratory if soil or sediment samples could have high concentrations of these metals and ask them to modify sample preparation procedures to remove the interference as needed to meet target soil action levels (for example, modified extraction or analysis method).

Reduced iron and calcium in the < 250 um particle fraction (fraction required for bioaccessible arsenic analysis) can remove the interference but be aware that natural background levels of total arsenic in this fraction can approach 50 mg/kg or higher in comparison to the < 2 mm particle size fraction (generally < 24 mg/kg, default HEER Office EAL background level).

4.2.7 REPLICATE SAMPLES

Proper sample collection (mass, shape, etc.) is the first element of the quality control process (Subsection 4.2.5). A DU is further considered to be adequately characterized when repeat testing of the same DU with independent samples yields similar estimates of the average concentration of a contaminant. These are referred to as "replicate" samples. The representativeness of Multi Increment data for a DU is evaluated by a comparison and statistical evaluation of replicate sample data from the subject DU or from a DU(s) reasonably considered to have a similar history and distribution of contaminants.

Re-testing of DUs due to failed replicate samples or identification of contamination after a site has been cleared can be very expensive. Careful evaluation of sample collection methods in the field and sample processing and analysis procedures at the laboratory prior to initiation of a project is important.

Replicate subsamples should be collected and tested by the laboratory in order to evaluate the precision of the subsampling method. This is carried out in a similar manner as done for field replicates.

4.2.7.1 FIELD REPLICATE SAMPLES

Replicate samples are collected in exactly the same manner as the initial Multi Increment sample. This includes the number, shape, depth and mass of individual increments as well as the sampling design (e.g., systematic random) and spacing between increments. The final bulk sample mass of replicate samples should also be similar.

Under ideal circumstances replicate samples would be collected in each DU in order to document the reproducibility of the MIS data on a DU-specific basis. The HEER Office recognizes that this is not feasible in terms of time and cost for many projects, however, or even necessary for decision making in cases where there is already a high confidence of the reproducibility of the data. The collection of representative Multi Increment samples using sufficiently large numbers of increments and well-thought-out DU sizes and placements, may decrease the overall number of replicate samples needed to evaluate the site investigation.

Replicate samples should be collected from at least a representative subset of DUs investigated at a given site. Each site will be unique in terms of number and similarities of DUs. The rational for the use of single set of replicate samples to represent multiple DUs should be clearly discussed in the SAP as well as the final investigation report. Replicate samples collected in one DU can be used to represent other DUs provided that the DUs are similar in terms of use history, soil type, size and mechanism of contaminant release, and anticipated degree of small-scale contaminant heterogeneity (see Section 3.5). Note that this is similar to one per "batch" of 10-20 samples for replicate analysis selection used by laboratories to evaluate subsampling and analysis precision.

Field replicates should be collected from a minimum of ten percent of DUs characterized as part of a site investigation. A minimum of one set of replicate samples should be collected, if less than ten DUs are to be characterized. At a minimum, collect replicate samples in the DU (or DUs) with the highest anticipated contamination, since the need for remedial actions will initially be determined based on data from this area of the site. Replicate samples are also recommended for the DU that represents the highest likelihood for exposure to contaminants (e.g., currently used playground), if different from the suspect, most contaminated DU. It is also important to have replicates representing all the different COPCs that may be investigated in DUs at a particular site.

Triplicate samples (i.e., original sample plus two replicates) should be collected to evaluate the precision of field sampling methods used. Each set of replicate increments must be collected from completely independent (systematic random) locations. Collection of increments around a single grid point is not appropriate for replicate samples, since this might not adequately test small-scale variability within the DU.

Figure 4-22. Example Pattern of Increment Collection for Triplicate Multi Increment Samples

Replicate sample increments are typically collected along the same approximate directional lines established through the DU for the initial Multi Increment sample, though at different systematic random locations (Figure 4-22). For example, the grid used to select increment collection points for the first sample can be shifted halfway between the original points in each of two directs. This helps to limit the need for additional increment demarcation and simplify sample collection in the field.

Replicate samples are sent to the laboratory as "blind" samples, meaning the sample(s) are labeled so that the laboratory does not know they represent replicate samples of the initial Multi Increment sample(s). The replicate samples are prepared and analyzed in the same manner as carried out for the initial sample.

The statistical evaluation of replicate samples is discussed in Subsection 4.2.7.3. Under ideal circumstances, the reported concentration of a target contaminant will be very similar between replicates. Experience with replicate data under different contaminant release scenarios will improve sampling methodologies and minimize the need for additional sample collection following an initial investigation.

4.2.7.2 LABORATORY REPLICATE SAMPLES

Laboratory replicate samples are collected in the same manner as that used to collect the initial laboratory subsample for analysis (see Subsection 4.2.6.2). Reprocessing or mechanical mixing of the sample is not required between replicate samples. Separate subsamples can be collected from the sectorial splitter, if used. If subsamples are collected by hand, then approximately 30 increments should again be collected in a systematic random fashion from different locations within the processed bulk sample.

Triplicate samples (i.e., original subsample plus two replicates) should be collected to evaluate the precision of the laboratory subsampling methods used. Laboratory replicates should be collected from a minimum of ten to twenty percent of Multi Increment samples submitted for analysis. A minimum of one set of replicate samples should be collected, if less than 10 Multi Increment samples are collected. At a minimum, conduct a laboratory subsampling replicates for the Multi Increment sample anticipated to have the highest contamination. Designating laboratory subsampling replicates to be conducted for one or more of the field replicate samples can prove useful when conducting the data evaluation (see Subsection below). As noted earlier, if samples are labeled in a way that the laboratory does not know which samples are field replicates, then designating one or more of the field replicate samples to be included as the laboratory subsampling replicate can also be done in a "blind" manner.

4.2.7.3 EVALUATION OF DATA REPRESENTATIVENESS

Statistical methods to evaluate the representativeness of Multi Increment sample data have been included in the HEER Office TGM since 2008. A refined approach for use in Hawai‘i based on experience at sites over the past seven years, as well as consideration of statistical methods discussed in the ITRC document Incremental Sampling Methodology (ITRC 2012), is provided below. The discussion applies to evaluation of both field and laboratory replicate data.

Acceptance criteria for the statistical evaluation of the MIS data are established as part of the DQO process for the site investigation. A two-step process is presented. The Relative Standard Deviation (RSD) of the contaminant concentration reported for each replicate sample is first calculated. This provides a measure of the precision of the Multi Increment sampling method used to estimate the mean contaminant concentration for the DU in terms of combined field and laboratory error. The lower the RSD the more precise the sampling approach used, and the more reproducible the data. As discussed below, an RSD of 35% is considered to indicate good reproducibility and reliable data for decision making. An RSD of >100% is considered to be very poor, and not typically appropriate for final decision making (see discussion below).

A 95% Upper Confidence Level (UCL) of the mean contaminant concentration can be calculated for the DU if necessary. This can be used to assist in decision making regarding the potential risks posed by the contamination and the need for remedial actions. Under some circumstances, the RSD can also be used to evaluate MIS data for DUs with similar characteristics in the absence of separate replicate data for those DUs. These topics are discussed in more detail below.

Data Precision

Data precision is evaluated by comparing data for replicate samples collected from the same DU. Replicate Multi Increment samples are intended to provide estimates of the mean concentration of a contaminant in a DU that approximate a statistically normal distribution. This allows statistical evaluation of data with as few as three replicate samples. The precision of the data for a given DU can be evaluated in terms of the Standard Deviation (SD) or more specifically the Relative Standard Deviation (RSD) of replicates. The SD and RSD reflect the total sum of field and laboratory error in the data (i.e., field sampling error + lab processing/subsampling error + lab analysis error).

Standard deviation is a well-known measure of the variation from the mean among a group of samples (USEPA 2006g,b). The lower the standard deviation (i.e., the closer the replicate data are to the mean) the more precise the site data are as an estimate of average contaminant concentration in the DU under investigation. When the mean concentration of a contaminant reported for a set of MIS replicate samples is close to the HDOH EAL, a lower standard deviation for the replicates provides stronger evidence that the true DU mean is indeed below the action level. A low standard deviation for soil sample data is achieved by minimizing error in sample collection, processing and analysis to the extent feasible.

The RSD represents the ratio of the standard deviation of the replicate set over the mean of the replicate set, expressed as a percentage:

   Eq. 2)

An RSD less than 35% is considered to reflect good precision for estimates of the average (see ITRC 2012). Good precision implies that the sampling method used, including the number, spacing, and size/shape of increments collected was adequate to capture and reflect small-scale heterogeneity of contaminant distribution within the DU and that error in the laboratory processing and analysis methods was low.

For example, assume that concentrations of 9 mg/kg, 10 mg/kg and 11 mg/kg are reported for a target contaminant in triplicate Multi Increment samples collected from a DU. The mean concentration is 10 mg/kg. The SD is 1 and the RSD is 10%, indicating good precision of the data. Now consider concentrations of 5 mg/kg, 10 mg/kg and 15 mg/kg for a set of triplicate samples. The mean is again 10 mg/kg. The SD is now 5 mg/kg and the RSD is 50%, indicating lower precision and confidence in the replicate data.

The higher the RSD, the less confidence there is that the mean contaminant concentration estimated for any individual DU (i.e. the mean of a replicate set of samples for a DU) is representative of the true mean for the DU. A higher RSD (e.g., >35%) could be due to error in the field and/or laboratory. Field sampling error is the most likely source of data variability. Inadequate sample processing and subsampling is the main source of error at the laboratory, rather than analytical error. This can be evaluated by a review of sample collection, processing and subsampling procedures, as well as testing of replicate samples. The field replicate RSDs are used to estimate the total error for the sample data. The lab subsampling and analysis RSDs are use to estimate the lab subsampling and analysis error for the sample data. The lab subsampling and analysis error can then be subtracted from the total error to compare errors attributable to 1) field sampling, and 2) to lab subsampling and analysis. This analysis should be routinely carried out to evaluate sample data and help identify errors that may be corrected. In limited instances, grinding of samples in the laboratory might be required to reduce the grain size and allow the collection of more representative subsamples, since the ability to increase the mass of soil extracted and tested is limited (see Subsection 4.2.6).

If the RSD for field replicate samples (total error) is high, and RSD(s) for the lab subsampling and analysis replicates are reasonably low, then field error is the indicated source. A high RSD typically indicates the presence of small nuggets of the contaminant in soil or the presence of small, randomly scattered areas of high contamination within the DU. This problem is not insurmountable. One of the strong points of the Multi Increment sampling approach is that field precision and sample representativeness can be evaluated in an efficient manner. The field precision of replicate samples for a DU can be improved by increasing the number of increments and total sample mass to provide better coverage and sample support. The original DU can also be subdivided into smaller DUs for characterization.

The latter may or may not be beneficial, depending on the nature of contaminant distribution. The use of smaller DUs in the absence of increasing the number of increments collected will improve MIS data precision if the contaminant is concentrated within one area of the original DU. The use smaller DUs might not improve data precision, however, if the contaminant is evenly dispersed throughout the DU but highly heterogeneous at the scale of an individual increment. In this case, an increase in the number of increments collected and the mass of sample collected will be necessary to obtain representative and reproducible data.

As the RSD exceeds 35% and replicate contaminant concentrations approach a target action level, there is increasing uncertainty that the data are adequately representative of the true mean of the DU. This calls for an assessment of the sample collection approach employed as well as increasing reliance on other statistical measures to determine the need for further action. As discussed in the next section, this includes use of the 95% Upper Confidence Level (UCL) of the mean for comparison to action levels and for final decision making. This will necessarily be a site-specific decision and is part of the iterative, DQO process described in Section 3 of the TGM.

Adjustment of Data for Decision Making

Table 4-2 presents a recommended approach for evaluation of DU data based on a review of replicate sample data, either collected directly from the DU in question or based from replicate data from similar DUs. Although somewhat subjective, the approach helps to minimize the need to re-sample DUs when proper field and laboratory protocols are followed, while balancing the need to ensure that significant risks to human health and the environment are not inadvertently missed.

RSD <35%

Direct comparison of unadjusted DU data, or the arithmetic mean of replicate data to target action levels, is acceptable when the RSD of the representative replicate data set for the contaminant of concern is less than 35%. Adjustment of the data with respect to the RSD (or calculation of a 95% Upper Confidence Level) is not considered warranted given the overall acceptable sample precision. This assumes, of course, that the samples were collected, processed, and tested in an unbiased manner and are reasonably representative of the targeted DU. If soil remediation is carried out then unadjusted DU data can be used for confirmation samples.

RSD >35% but <50%

A thorough review of field and laboratory procedures should be included in the site investigation report to determine the adequacy of DU-MIS methods used for cases where the RSD for replicate samples exceeds 35%. This review can help identify the need for improvements in field or laboratory methods for future investigations. If recommended field and laboratory procedures were properly followed, and the RSD is greater than 35% but less than or equal to 50%, then unadjusted DU data can be used for initial screening of DUs and determination of the need for remedial actions.

The collection of additional Multi Increment samples is recommended for confirmation of remediation of DUs that exceeded action levels, even if Perimeter DU data collected during the initial investigation were below action levels. The confirmation sampling should include the use of a greater number of increments per DU and/or division of the area into smaller DUs for characterization.

RSD >50% but <100%

If the replicate RSD(s) fall between 50% and 100%, the adequacy of field sampling methods and laboratory processing and analysis methods used in the investigation is (again) important to review, and a discussion of potential sources of error should be included in the investigation report.

If analysis of the field sampling error vs the laboratory subsampling and analytical error reveals that a large majority of the error may be attributable to laboratory subsampling and analysis error rather than field sampling error, then the laboratory should be contacted regarding the need to subsample and reanalyze the selected (lab replicate) MI sample again (which should still be stored at the laboratory), as well as potentially subsample and re-analyze any associated DU samples analyzed in that same "batch" of samples.

A 95% UCL concentration should be calculated in cases where the RSD exceeds 50%, using the Chebyshev method. A 95% UCL should also be estimated for related DUs from which replicates were not collected, as described. Use the highest RSD calculated if replicate samples were collected from multiple DUs. Data for associated DUs should likewise be adjusted for comparison to action levels. Note that the RSD will differ between targeted chemicals.

The 95% UCL should be compared to 150% of the target action level (see Use of 95% UCL subsection below). This helps to ensure that potentially significant risk to human health and the environment is not inadvertently overlooked under a worst-case scenario when the true mean does in fact exceed the action level (e.g., non-cancer Hazard Quotient not significantly greater than 1 and within target 10-4 to 10-6 excess cancer risk range; see USEPA 2006g and HDOH 2016).

Provide additional, multiple lines of evidence for acceptance (or rejection) of the data for decision making purposes. This can, for example, include knowledge of the site history and the anticipated potential for contamination above levels of concern, the adequacy of the methods used to collect, process, and analyze samples, and the approximation of the data to action levels.

Additional confirmation sampling should be carried out following removal or in situ treatment of contaminated soil. This should include the use of smaller DUs and/or a larger number of increments in order to improve field precision of the data. Replicate samples should also be collected and evaluated in the same manner described above (e.g., minimum 10% of DUs).

RSD >100%

Contaminants present in soil primarily as small nuggets rather than disseminated throughout the soil matrix can result in replicate RSDs above 100% even when strict collection protocols are followed in the field. High RSDs are often generated for soils contaminated with chips of lead-based paint, lead pellets at shooting ranges or even PCBs (see HDOH 2015), Re-sampling of such sites might not be feasible due to cost or access limitations. This requires especially careful designation of DUs (e.g., multiple small DUs vs single large DU; see Section 3.4.3) as well as the collection of a greater sample mass from a large number of increment locations (see Subsection 4.2.2). Grinding of samples may also be required to manage laboratory subsampling error (see Subsection 4.2.6.3).

Data should be considered especially suspect when the RSD for replicate samples exceeds 100%. Field sample collection and laboratory processing methodologies should again be evaluated and potential sources of error in the data discussed. If analysis of the sampling data reveals that a large majority of the error is attributable to laboratory subsampling and analysis error rather than field sampling error, then the laboratory should be contacted regarding the need to subsample and reanalyze the selected (lab replicate) MI sample again, as well as potentially subsample and re-analyze any associated DU samples analyzed in that same "batch" of samples.

If one or more of the replicate samples exceeds the target action level then remediation of the DU should be considered, even if the mean concentration is well below the target action level. In the absence of other information, remediation of associated DUs where replicate samples were not collected should also be considered, regardless of the concentration of the contaminant reported. Re-sampling of the DU using a greater number of increments and/or smaller DUs is otherwise recommended.

If all replicate samples are below the action level then the approach described above for cases where the RSD falls between 50% and 100% can be followed, provided that confirmation samples are collected for DUs where remediation is ultimately carried out. Data for associated DUs should likewise be adjusted for comparison to action levels.

Additional, multiple lines of evidence for acceptance (or rejection) of the data for decision making purposes should be provided. This approach recognizes cases where two of three replicate samples might be significantly lower than the action level, but the variance between the data yields a high RSD. Consider for example a case where a DU tested for lead yields replicate data of 20 mg/kg, 30 mg/kg and 205 mg/kg with a target action level of 200 mg/kg. The mean of the replicate samples is 85 mg/kg, but the RSD is a very high 122%, indicating poor data precision. It is unlikely that the HEER office would recommend re-sampling or remediation of this DU, however. Compare this to a scenario where the variance between triplicate samples is very low but are just under the target action level, for example 175 mg/kg, 190 mg/kg and 205 mg/kg lead, with a mean of 190 mg/kg lead. The RSD of 8% implies very good data precision. The second DU is clearly more contaminated than the previous example, however, and would be considered a higher priority for remediation if it were to be required.

Table 4-2. Recommended Adjustment of Multi Increment Data for Decision Making Based on Relative Standard Deviation (RSD) of Replicate Samples.
RSD Data Decision Unit Data Adjustment
Good Precision (RSD <35%)
  • DU-MIS samples should be collected, processed, and tested in an unbiased manner;
  • Compare unadjusted MI data directly to target action level for decision making (use arithmetic mean for replicate sample sets);
  • Data can be used for confirmation purposes without the need for additional sampling, if action levels are met.
Moderate Precision (RSD >35% but <50%)
  • Review and discuss field sampling methods and laboratory processing and analysis methods and discuss potential sources of error (e.g., improper increment collection methods, inadequate number or mass of increments, unrepresentative laboratory subsampling methods, etc.);
  • Compare unadjusted MI data directly to target action level for decision making (use the arithmetic mean for the replicate sample sets);
  • Additional confirmation sampling recommended following remediation of DUs that exceed action levels, including use of smaller DUs and/or a larger number of increments and collection of additional replicate samples.
Poor Precision (RSD >50% but <100%)
  • Review and discuss field sampling methods and laboratory processing and discuss potential sources of error in report;
  • If the large majority of total error is attributable to laboratory subsampling and analysis error, request laboratory to subsample and analyze the batch of DU samples again using correct techniques, and include additional subsampling replicates;
  • Compare the 95% UCL (Chebyshev method) for replicate data to 150% of the target action level for decision making ;
  • Estimate a 95% UCL for DUs where replicates were not collected based on the 95% UCL and mean calculated for the replicate data; Compare results to 150% of the target action level;
  • Provide additional, multiple lines of evidence for acceptance (or rejection) of the data for decision making purposes including knowledge of the site history and the anticipated potential for contamination above levels of concern, the adequacy of the methods used to collect, process and analyze samples, and the approximation of the data to action levels;
  • Additional confirmation sampling recommended following remediation of DUs that exceed action level , including use of smaller DUs and/or a larger number of increments and collection of additional replicate samples.
Very Poor Precision (RSD >100%)
  • Data should be considered suspect;
  • If the large majority of total error is attributable to laboratory subsampling and analysis error, request laboratory to subsample and analyze the batch of DU samples again using correct techniques, and include additional subsampling replicates;
  • Review and discuss field sampling methods and laboratory processing and analysis methods and discuss potential sources of error in report;
  • Consider re-sampling of DU(s) most suspect for contamination using a larger number of increments and/or smaller DUs;
  • If one or more of the replicate samples exceeds the target action level then remediation of the DU should be considered, even if the mean concentration is well below the target action level. Remediation of associated DUs where replicate samples were not collected should also be considered;
  • If all replicate samples are below the Action Level, then compare the 95% UCL (Chebyshev method) for replicate data to the unadjusted target action level for decision making ;
  • If all replicate samples are below the Action Level, estimate a 95% UCL for DUs where replicates were not collected based on the 95% UCL and mean calculated for the replicate data and compare results to unadjusted target action levels;
  • Provide additional, multiple lines of evidence for acceptance (or rejection) of the data for decision making purposes including knowledge of the site history and the anticipated potential for contamination above levels of concern, the adequacy of the methods used to collect, process and analyze samples and the approximation of the data to action levels;
  • Additional confirmation sampling recommended following remediation of DUs that exceed action levels , including use of smaller DUs and/or a larger number of increments and collection of additional replicate samples.

Use of 95% UCL

Multiple approaches are available for calculation of UCL values, based in part on the variance between individual replicate sample data. An increase in variance between replicate samples will cause a similar increase in confidence intervals and a less precise estimate of the mean. Two equations can be used to bracket the range of UCL values that might be calculated from a set of multi increment replicate samples, the Student’s-t UCL and the Chebyshev UCL (ITRC, 2012).

Calculation of a 95% Upper Confidence Limit (UCL) of the mean contaminant concentration for a DU is not required if the RSD for replicate data is equal to or less than 35% (see Table 4-2). If use of a 95% UCL is required for risk assessment or other purposes outside of the HEER Office (and RSD is equal to or less than 35%), then use of the Student’s-t method is recommended (see ITRC 2012). This method assumes a normal distribution of replicate data with a UCL calculated as follows:

Eq. 3)

where
mean = arithmetic mean of replicate samples;
SD = standard deviation of replicate samples;
r = number of replicate samples; and
α = acceptable level of potential decision error (e.g., 0.05 or 5% for a 95% UCL);
t = (1-α)th quantile of the Student’s-t distribution with (r-1) degrees of freedom.

The Chebyshev method is considered to be most appropriate for estimation of a 95% UCL when the variance between replicate samples is high (e.g., >35%; after ITRC 2012). This method assumes a non-normal or skewed, nonparametric distribution of data and is calculated as follows:

Eq. 4)

where the symbol α is again the acceptable level of potential decision error.

The need for replicate data and calculation of a 95% UCL should be evaluated as part of the systematic planning process described in Section 3. A 95% UCL should ideally be calculated based on replicate sample data specific to the DU in question. If replicate data are not available for a DU, then the a 95% UCL value should be estimated based on replicate data collected for a similar DU at the site. This is done by multiplying the contaminant concentration reported for that DU by the ratio of the 95% UCL and the mean for the replicate data set:

Eq. 5)

where "Conc." is the concentration of the targeted contaminant reported for the subject DU and "X" is mean concentration of the replicate data set used to calculate the initial 95% UCL.

As discussed in Subsection 4.2.4, this approach should only be applied for DUs that can reasonably be assumed to have a similar history and distribution of contamination (see also Section 3.4, DU designation). Note that approaches for calculation of a 95% UCL may differ for different chemicals, depending on the calculated RSD for each targeted chemical. Additional, DU-specific replicate samples may be warranted for more direct assessment of mean contaminant concentrations in DUs that could pose a potentially high risk. Examples include a playground area where contaminant concentrations approach an action level and replicate samples from related DUs suggest poor precision of the data.

As discussed in the previous section, direct comparison of a UCL value to a published action level is not required, since the probability that this value is representative of the true mean concentration for the DU is by intent assumed to be very low (i.e., 0.05 or 5%). The 95% UCL should instead be compared to a concentration of the chemical in the soil that could pose an especially heightened risk of adverse health effects in the unlikely event that this concentration represented the true mean for the DU (refer to USEPA 2006g). As a default, an alternative screening level equal to 150% of the original screening level is considered appropriate. This reflects only a marginal increase in overall health risk for screening levels based on a target cancer risk of 10-6 and a non-cancer hazard of 1. Alternative approaches should be discussed with the HEER office on a case-by-case basis.

In some cases, the DQO/SAP may specify use of an alternate approach to measure and evaluate variation from the mean in replicate sample data. These alternatives should be clearly identified and discussed with a HEER Office project manager for use in the site investigation. Calculated 95% UCL values can also be used in a forward risk assessment to quantify excess cancer risk and non-cancer hazard.

4.2.8 OTHER CONSIDERATIONS

4.2.8.1 MULTI INCREMENT SOIL SAMPLE COLLECTION FOR VOLATILE ANALYSES

A detailed discussion of the field collection of Multi Increment samples to be tested for volatile contaminants is provided in Section 5. For the purposes of soil sample collection, a chemical is considered to be volatile if the molecular weight is less than 200 and the vapor pressure is greater than 1 mm Hg (25ºC) or the Henry’s Law Constant is greater than 0.00001 atm-m3/mol (see Appendix 4-A). Samples to be analyzed for VOCs (including TPH-g) are collected separately from samples to be analyzed for SVOCs and non-volatile chemicals (including TPH-d and TPH-o). The collection of soil gas samples is also recommended at sites where significant VOC contamination is known or suspected (refer to Section 7).

Decision Unit and Multi Increment sampling approaches should be used to characterize soil for volatile organic compounds (VOCs). This includes testing of samples from cores, excavation bottoms and walls, stockpiles and underneath paved areas. Volatiles are not typically sampled in surface soils, especially for any aged/historic releases. The use of discrete soil samples to characterize soil for VOCs is not considered to be reliable due to potentially high small-scale variability, the minimal mass of soil tested at the laboratory (e.g., five grams), and the resulting unreliability of the data.

Distinct spill areas are oftentimes associated with the release of volatile organic chemicals. Primary environmental hazards posed by VOC-contaminated soil include vapor intrusion, leaching and gross contamination hazards. This normally requires that spill areas be designated and characterized as separate DUs.

Multi Increment sample collection points are established for a DU in the same manner as discussed above. A minimum of 30 increments should be collected. Samples will most commonly be collected from subsurface DU layers and associated increment borings (refer to Section 3.4.4 and Section 5.6). Other DU examples include an area of obvious staining and the walls and floor of an excavation. In some cases each side wall and floor of an excavation area may be separate Decision Units, or the floor of an excavation could be divided into more than one Decision Unit to evaluate a more specific area where contamination may have migrated. In other cases, certain side walls or all the side walls maybe combined into a single Decision Unit. The rationale for selecting DUs within an excavation should be clearly addressed in the DQO/SAP for the site investigation.

As described in Section 5, testing of soil for VOCs should follow approaches described in USEPA Method 5035 Closed System Purge-and-Trap and Extraction for Volatile Organics in Soil and Waste Samples (see MADEP, 2002, TNRCC, 2002, CalEPA, 2004b), modified to incorporate DU-Multi Increment sampling approaches. This test method includes procedures for the collection, preservation, handling, and preparation of soil samples to minimize the loss of the VOCs prior to analysis.

Soil gas data are also highly recommended for characterization of sites contaminated with volatile chemicals, and may be more appropriate for some site investigations than soil sampling. Soil gas data are much more reliable than soil data for evaluating potential vapor intrusion hazards associated with volatile contaminants in soil (and groundwater). Soil gas data are also very useful for identifying and locating areas of heavy contamination. Refer to the HDOH guidance document Evaluation of Environmental Hazards at Sites with Contaminated Soil and Groundwater (HDOH 2016) and Section 7 of this TGM for additional information.

4.2.8.2 COLLECTION OF SUBSURFACE MULTI INCREMENT SAMPLES

Decision Unit designation for subsurface soil is discussed in Section 3.4.4. A detailed discussion of the collection of Multi Increment samples from subsurface soil is provided in Section 5.

The following circumstances are examples of when delineation of the vertical distribution of contaminants in soil might be warranted:

  • Potentially leachable contaminants are found in surface soils above HDOH EALs;
  • Groundwater data suggest that a release has occurred and contamination has migrated through the vadose zone;
  • The property is to be redeveloped and significant disturbance of subsurface soil is anticipated with some soil potentially being reused at the surface;
  • The property is to be sold or a property lease terminated, and a potential buyer or landowner requires documentation that subsurface soil has not been contaminated by past activities.
  • Excavation and offsite disposal or reuse of soil is planned and there is reason to suspect that deeper soils could be contaminated.

The collection of samples from subsurface soils is more challenging than for exposed surface soils.

Data for each Multi Increment sample are used to generate a three-dimensional map of contaminant concentrations in soil. The core from a targeted DU layer in a single boring represents the "increment" for the DU layer, identical to increments collected from a surface soil decision unit. Use of a direct-push rig allows collection of continuous cores and collection of the full interval of targeted DU layers.

Most DU layers are tabular shaped, with the vertical thickness being significantly less that the lateral width and length. In such cases, increments should cover the full thickness of the DU layer, as done for surface soil. Increments of adequate mass to produce a 500 g - 2 kg bulk sample should be collected from systematic random core locations across the DU.

Ideally, the entire core section of the DU layer would be used to prepare a bulk Multi Increment sample for tabular, subsurface DUs. This may not be practical due to soil volume constraints at the laboratory, however, and as described in Section 5 subsampling of core increments in the field will be required to generate a manageable bulk sample mass for processing and testing. Core increments will ideally be subsampled by slicing a thin wedge from the full length of the targeted DU layer. This provides 100% vertical coverage of the increment and minimizes bias. Increment wedges from same-depth layers are then combined to generate the bulk Multi Increment sample.

This may not be feasible in sandy or gravelly soils. As an alternative, increments can be subsampled by the removal of regularly spaced plugs of equal mass from the core. As a default, the removal of 5-10 g plugs at two to four inch intervals is recommended (similar to the method used for VOCs), or as otherwise necessary to generate a 1-2 kg bulk sample following combination of all subsampled increments for a DU layer. Note that 30+ subsamples, as recommended for DUs in general, are not required from each core increment for DU layers.

In some cases collection of the recommended minimum number of increments from subsurface DU layers may not feasible due to access or cost constraints. Reducing the number of increments collected for the Multi Increment may be necessary. If this is the case, it is important to recognize that the quality and reliability of the resulting data will be compromised. This should be taken into account when used to estimate the extent of contamination and the mean concentration of contaminants in the targeted DU layer. Replicate field samples will be critical to help evaluate precision of the data collected in these circumstances (see Subsection 4.2.7).

A smaller number of increments might be useful to identify the general presence or absence of a contaminant in a DU and even the general magnitude of contamination. As discussed in Section 3.4.4, the use of single boreholes to initially explore a site for the presence or absence of subsurface contamination is common practice. In such cases, however, the core borehole should be subdivided into targeted layers for testing (e.g., based on apparent or suspect contamination). Subsamples of the targeted layers could be collected in the field (as described above) or the entire core interval could be submitted to the laboratory for MIS processing and subsampling (the latter option is typically more feasible for non-volatile contaminants). Narrower DU intervals are used to provide a higher vertical resolution of contaminant distribution as needed. This provides a significantly more reliable screen of contamination than traditional discrete soil samples collected from a single point within a core.

The collection of replicate samples from subsurface DUs to help evaluate the field precision of the data is equally important as it is for surface soils. Two types of replicate samples should ideally be collected (Figure 4-22 and Figure 4-23; see also Figure 3-12 in Section 3): 1) Replicates to evaluate precision with respect to distributional heterogeneity within the DU Layers, and 2) Replicates to evaluate the precision of core increment subsampling.

Figure 4-23. DU Layer Replicates Collected from Separate Sets of Cores to Test Precision of Data with Respect to Distributional Heterogeneity
Each color represents one set of cores used to prepare a Multi Increment sample for each layer, with increments of the same color combined to prepare a bulk sample for that layer (all cores not shown, ideally 30 cores per replicate sample; see also Figure 4-9 and Figure 3-12 in Section 3).

Figure 4-24. Collection of Increment Subsample Replicates (Triplicates) from Subsurface Core Increments
Used to test precision of subsampling from subsurface cores (plugs being placed in methanol for VOC analysis in example photo)

Replicates to test field precision in terms of contaminant distributional heterogeneity within a DU are collected and evaluated in an identical manner to replicates collected from exposed surface DUs (see Figure 4-10). Triplicate samples recommended for at least 10% of DU layers. If this is not practicable due to access or cost reasons then this should again be noted and discussed in the review of data quality and limitations. Replicate samples must be collected from entirely separate borings and cores. The collection of separate subsamples from single cores evaluates subsampling precision, not field precision in terms of distributional heterogeneity.

Sets of increment subsample replicates should be collected from core increments for a DU. For example, three separate wedges or three sets of plugs of soil might be removed from a of a core increment layer, (see Figure 4-24; e.g., most suspect contaminated layer). A minimum 10 to 50 grams of soil should be removed from each increment, similar to the mass recommended for increments collected from surface samples. A default, two to four-inch (5-10 cm) spacing for removal of 5-10 g plugs is recommended, with the adequacy of this approach verified by comparison of replicate data. This process is repeated for each core increment from each boring until triplicate samples are prepared for the targeted DU layer(s). Each replicate sample is then independently processed and tested.

Increment subsample replicates are typically unique to the collection of subsurface samples, where limitation of individual increments to 30-50 g is not typically feasible and the mass of individual increments must be reduced to prepare a manageable bulk sample (see also HDOH, 2011i). The collection of subsampling replicates is recommended anytime that subsampling of core increments is required. Triplicate samples are recommended for at least 10% of DU layers.

Replicate data for DU layers and increment subsamples should be evaluated in the same manner as described in Subsection 4.2.7, with potential limitations on use of the data discussed. Variance in the resulting data for each set of replicates reflects the sum of both lab and field error. Lab replicates for one or more of the samples can be used to evaluate the proportion of error attributed to each source. Field error is likely to dominate error, given the much larger masses of soil involved. If it is possible for the entire cores to be retained in case additional subsampling to improve data reproducibility is necessary (e.g. for non-volatile contaminants), that should be considered. For example, if increment subsampling replicate data indicates a poor degree of precision (e.g., RSD >50%), then select cores could be re-sampled to improve data quality and decision making.

Alternative characterization approaches should also be considered to support subsurface Multi Increment soil samples, for example the collection of soil gas samples for volatile contaminants or testing of groundwater for contaminants that pose potential leaching hazards. Sampling constraints and potential impacts on data quality and decision making should be discussed in the resulting site investigation report and Environmental Hazard Evaluation (see Section 13).

4.2.8.3 COLLECTION OF MULTI INCREMENT SAMPLES FOR STOCKPILES

Multi Increment sampling is recommended for characterization of soil stockpiles. Designation of DU volumes for stockpiles based on planned reuse of the soil is discussed in Section 3.5.7. Segregating and flattening stockpiles for Multi Increment sample collection is discussed in Section 5. Stockpile sampling strategies and methods are addressed in greater detail in the Guidance for the Evaluation of Imported and Exported Fill Material, Including Contaminant Characterization of Stockpiles (See Appendix 3-A; HDOH, 2011e).

It is important that all portions of the stockpile are equally accessible for the collection of increments during sampling. Replicate samples should be collected from a minimum of 10% of the DUs in order to evaluate data precision (see Subsection 4.2.7). The HEER Office should be consulted on options for alternate sampling plans in cases where access and/or safety issues hamper the collection of proper samples from stockpiles.