Re: Mean Deviation Four Decades Of Progressive Heavy Metal.pdf
Nelson Suggs
Appendix B Conceptual Site ModelsB.1 Summarize Known Site ConditionsB.2 Screen for Potential Environmental HazardsB.3 Default Conceptual Site ModelsB.4 Advanced Site Conceptual ModelsB.5 Maintaining and Updating the Conceptual Site Model
Appendix C Example Decision Unit Designation SchemesC.1 Commercial and Industrial SitesC.2 Single-Family HomesC.3 High-Density HousingC.4 SchoolsC.5 Large Single-Use AreasC.6 Very Small AreasC.7 Subsurface Decision UnitsC.8 StockpilesC.9 Building DemolitionC.10 Large Industrial ComplexesC.11 Investigation of Petroleum ReleasesC.12 Gas Station ClosureC.13 Sediment Decision Units
Appendix E Use and Misuse of Discrete Sample DataE.1 Background and Key AssumptionsE.2 Field Study of Discrete Sample Data ReliabilityE.3 Implications of for Reliance on Discrete Sample DataE.4 Contamination ZonesE.5 Use of Discrete Sample Data for Preliminary Screening
Appendix G Collection of Subsurface Soil SamplesG.1 Exploratory Pits, Trenches and BoringsG.2 Direct-Push TechnologiesG.3 Borehole Core Increment SubsamplesG.4 Pit or Trench Sample CollectionG.5 Hollow Stem AugersG.6 Rotary Drills
Appendix K Laboratory Processing of Multi Increment SamplesK.1 IntroductionK.2 Sample ProcessingK.3 Subsample CollectionK.4 Analytical Subsample MassK.5 Particle Size ReductionK.6 Semi-volatile and Unstable ChemicalsK.7 Testing of Samples for Contaminant Bioaccessibility
Appendix N Common Investigation Errors and ProblemsN.1 Inappropriately Sized DUsN.2 Data Gaps Between Surface DUs and Subsurface DU LayersN.3 Inadequate Number of Increments and Bulk Sample MassN.4 Improper Increment SpacingN.5 Improper Increment ShapeN.6 Misuse of Co-located Discrete Samples and Increment SplitsN.7 Inadequate Laboratory ProcessingN.8 Inadequate Subsample Mass for AnalysisN.9 Lack of Field Replicate Sample DataN.10 Reversion to Discrete Sampling
These methods apply to nonvolatile and volatile contaminants as well as surface and subsurface soils. Similar sampling methods have been used for decades by the mineral exploration and agriculture industries but are relatively new to the environmental industry, where the error in the representativeness of sample data is less evident.
Risk-based DUs should be selected based on site history and current potential exposure pathways. Exposure Area DUs include unpaved areas where children and adults frequently play or work, such as playgrounds, schoolyards, gardens, open areas of commercial and industrial sites and exposed soil at construction sites. These are a very common components of human health risk assessments. The exact size of an Exposure Area DU is site-specific but normally ranges from a few hundred to a few thousand square meters (few thousand to a few tens of thousands of square feet) in area and from one hundred to several hundred cubic meters of soil in volume with the upper 5 to 15 centimeters tested (two to six inches).
Areas of known or suspected heavily contaminated soil that are almost certain to pose a risk if exposed at the surface are designated for separate testing to optimize anticipated remediation. These are referred to as Source Area (or Spill Area) DUs. Source Area DUs are surrounded by anticipated clean Boundary DUs to isolate areas of heavy contamination to the extent practicable and cost-beneficial in terms of anticipated remediation needs. Successful remediation of contamination can be verified by designation and testing of Exposure Areas DUs in the same locations.
DUs are designated to characterize both surface soil and, as needed, subsurface soil. Subsurface soil is characterized in terms of stacked DU Layers. Suspect layers of subsurface soil, identified by site history, initial surface soil data or other observations, should be designated for separate testing to bound the vertical extent of the contamination. Designation of subsurface DUs is normally done at a scale that will assist in optimization of potential remediation. Testing and documentation of subsurface contamination might also be performed for long-term management purposes to avoid potential excavation of the material in the future and inadvertent reuse on the surface.
A default of 50 increments per sample is recommended. This will provide reliably representative sample data under most site scenarios based on past field experience and comparison of replicate sample data. Fewer increments might be acceptable for testing of liquid releases (anticipated lower heterogeneity). A larger number of increments is required for contaminants present in the soil as clumps or chips (anticipated higher heterogeneity).
Sample collection methods for volatile chemicals require that separate increments are combined in a bottle containing a pre-measured volume of methanol. Further details on sample collection methods for volatile chemicals are discussed in Appendix I.
Step 4: Sample Processing and AnalysisContact the laboratory during the planning phase to ensure that they are experienced in processing and testing of MI samples. Ensure also that the laboratory can achieve the desired reporting limits and data quality objectives. Select analyses that achieve the desired risk concerns and goals. Avoid testing for unneeded unknowns to keep costs under control.
Once collected, the sample is sent to a laboratory for processing and testing. The laboratory will not be able to test the entire 1 to 3 kg sample. Strict protocols must be followed in order to collect a representative subsample for testing. The bulk field sample is normally air dried for 24 to 48 hours and then passed through a sieve to remove large rocks and other debris and isolate the target particle size (e.g.,
Step 5: Data Review and Decision MakingWhen the laboratory data are received, a review of the overall reliability of the data is made based on field and laboratory replicate samples and other quality control measures. If the replicate data are very different and the problem is determined to be at the laboratory, then retesting of the samples might be required. If the problem is determined to be related to the method used to collect the samples in the field, then the sampling process will be reviewed and the collection of new samples might be required. Field error is often due to the presence of previously unidentified, highly heterogeneous source areas within the initially targeted DU. Error associated with sample collection and laboratory testing decreases as experience is gained.
Once the data are determined to be usable, the data for each DU can be directly compared to risk-based screening levels applicable to the investigation question(s) of interest and decisions can be made on the need for cleanup or other soil management actions. The need to collect additional samples should be minimal, assuming that DUs were appropriately designated at the beginning of the project and DU questions and decision statements were properly prepared ahead of time.
Scientists and field workers began to warn in the early 1990s that this was not the case. Data for co-located samples often varied widely and randomly, as did data for duplicate subsamples tested by the laboratory. This caused confusion in the field regarding the extent of contamination above levels of potential concern and in the assessment of risk. The need to repeatedly remobilize field teams for sample collection and the discovery of additional contamination after remediation was thought to be completed, caused some projects to be delayed for years and in some cases to be abandoned due to the lack of a clear endpoint.
The mineral exploration and agricultural industries recognized the same problems many years ago. Gold exploration companies often went bankrupt when the amount of gold initially estimated to be presented in stockpiles of crushed ore, based on traditional sampling methods accepted at the time, proved dramatically different from the mass of gold ultimately extracted from the ore after selling it to a processor. Farmers realized the unreliability of discrete sample data very quickly, as crop yields failed to meet expectations or large sums of money were unnecessarily spent on fertilizer or other field amendments.
The result was the development of the Theory of Sampling by Pierre Gy in the 1950s. The Theory of Sampling serves as the basis of the DU-MIS methods described in this fact sheet. Errors in sample data and decision making are less obvious in the environmental industry, but DU-MIS methods are continually improved to make the investigation, assessment and remediation of contaminated soil as efficient and reliable as possible.
The Conceptual Site Model (CSM) prepared during the first step of the systematic planning is a comprehensive representation of site environmental conditions with respect to recognized or potential environmental hazards. The CSM is continuously updated as the site investigation progresses, and the site conditions are better understood.
A basic understanding of contaminant migration pathways and exposure pathways is necessary to formulate a CSM and to guide site investigation and response actions, including preparation of remedial actions and/or long-term management plans. Preparation and submittal of a formal, detailed CSM, however, is generally only required at sites where significant contamination exists and cleanup activities are anticipated to take more than a year to complete.
The first step in the preparation of a CSM is to summarize current site conditions. At the most basic level, this includes a summary of the known or suspected extent and magnitude of soil and groundwater contamination. In addition, site conditions such as land use, groundwater use, potential onsite and offsite receptors, exposure or isolation of contaminated soil, etc., are identified, as are specific environmental hazards that might be posed by the identified contamination.
A basic understanding of potential environmental hazards in terms of the environmental fate and transport of contaminants of potential concern (COPCs) targeted for a site is important for development of a CSM and subsequent stages of an investigation. As discussed in Section 3.2.2 and in Appendix C, the designation of DUs is intricately tied to the type of environmental hazard(s) posed by the COPC.
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