Brent A. Pulsipher

Role of Sampling Designs in Obtaining Representative Data

Representative environmental data are necessary to make defensible environmental decisions. Representative data can be obtained using unbiased sampling designs developed in the context of the project to achieve sampling objectives with required confidence and minimal cost. This article stresses the importance of systematic planning and an adequate conceptual site model to develop an appropriate sampling design. Various sampling designs are discussed and examples are used to illustrate sampling designs for various sampling objectives.

Determining the optimum number of increments in composite sampling

Composite sampling can be more cost effective than simple random sampling. This paper considers how to determine the optimum number of increments to use in composite sampling. Composite sampling terminology and theory are outlined and a method is developed which accounts for different sources of variation in compositing and data analysis. This method is used to define and understand the process of determining the optimum number of increments that should be used in forming a composite. The blending variance is shown to have a smaller range of possible values than previously reported when estimating the number of increments in a composite sample. Accounting for differing levels of the blending variance significantly affects the estimated number of increments.

Development and Demonstration of a Method to Evaluate Bio-Sampling Strategies Using Building Simulation and Sample Planning Software.

In an effort to validate and demonstrate response and recovery sampling approaches and technologies, the U.S. Department of Homeland Security (DHS), along with several other agencies, have simulated a biothreat agent release within a facility at Idaho National Laboratory (INL) on two separate occasions in the fall of 2007 and the fall of 2008. Because these events constitute only two realizations of many possible scenarios, increased understanding of sampling strategies can be obtained by virtually examining a wide variety of release and dispersion scenarios using computer simulations. This research effort demonstrates the use of two software tools, CONTAM, developed by the National Institute of Standards and Technology (NIST), and Visual Sample Plan (VSP), developed by Pacific Northwest National Laboratory (PNNL). The CONTAM modeling software was used to virtually contaminate a model of the INL test building under various release and dissemination scenarios as well as a range of building design and operation parameters. The results of these CONTAM simulations were then used to investigate the relevance and performance of various sampling strategies using VSP. One of the fundamental outcomes of this project was the demonstration of how CONTAM and VSP can be used together to effectively develop sampling plans to support the various stages of response to an airborne chemical, biological, radiological, or nuclear event. Following such an event (or prior to an event), incident details and the conceptual site model could be used to create an ensemble of CONTAM simulations which model contaminant dispersion within a building. These predictions could then be used to identify priority area zones within the building and then sampling designs and strategies could be developed based on those zones.

Cross-combined composite sampling designs for identification of elevated regions

Analyzing soils for contaminants can be costly. Generally, discrete samples are gathered from within a study area, analyzed by a laboratory and the results are used in a site-specific statistical analysis. Because of the heterogeneities that exist in soil samples within study areas, a large amount of variability and skewness may be present in the sample population. This necessitates collecting a large number of samples to obtain reliable inference on the mean contaminant concentration and to understand the spatial patterns for future remediation. Composite, or Incremental, sampling is a commonly applied method for gathering multiple discrete samples and physically combining them, such that each combination of discrete samples requires a single laboratory analysis, which reduces cost and can improve the estimates of the mean concentration. While incremental sampling can reduce cost and improve mean estimates, current implementations do not readily facilitate the characterization of spatial patterns or the detection of elevated constituent regions within study areas. The methods we present in this work provide efficient estimation and inference for the mean contaminant concentration over the entire spatial area and enable the identification of high contaminant regions within the area of interest. We develop sample design methodologies that explicitly define the characteristics of these designs (such as sample grid layout) and quantify the number of incremental samples that must be obtained under a design criteria to control false positive and false negative (Type I and II) decision errors. We present the sample design theory and specifications as well as results on simulated and real data.

Enhanced Chemical Incident Response Plan (ECIRP) - Appendix F: Remediation Analysis with Decision Support Tools (DSTs) for Wide-Area Chemical Hazards

The Defense Threat Reduction Agency (DTRA) commissioned an assessment of the Consequence Management (CM) plans in place on military bases for response to a chemical attack. The effectiveness of the CM plans for recovering from chemical incidents was modeled using a multiple Decision Support Tools (DSTs). First, a scenario was developed based on an aerial dispersion of a chemical agent over a wide-area of land. The extent of contamination was modeled with the Hazard Prediction and Assessment Capability (HPAC) tool. Subsequently, the Analyzer for Wide Area Restoration Effectiveness (AWARE) tool was used to estimate the cost and time demands for remediation based on input of contamination maps, sampling and decontamination resources, strategies, rates and costs. The sampling strategies incorporated in the calculation were designed using the Visual Sample Plan (VSP) tool. Based on a gaps assessment and the DST remediation analysis, an Enhanced Chemical Incident Response Plan (ECIRP) was developed.

Visual Sample Plan (VSP) Statistical Software as Related to the CTBTO's On-Site Inspection Procedure

In the event of a potential nuclear weapons test the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) is commissioned to conduct an on-site investigation (OSI) of the suspected test site in an effort to find confirmatory evidence of the nuclear test. The OSI activities include collecting air, surface soil, and underground samples to search for indications of a nuclear weapons test - these indicators include radionuclides and radioactive isotopes Ar and Xe. This report investigates the capability of the Visual Sample Plan (VSP) software to contribute to the sampling activities of the CTBTO during an OSI. VSP is a statistical sampling design software, constructed under data quality objectives, which has been adapted for environmental remediation and contamination detection problems for the EPA, US Army, DoD and DHS among others. This report provides discussion of a number of VSP sample designs, which may be pertinent to the work undertaken during an OSI. Examples and descriptions of such designs include hot spot sampling, combined random and judgment sampling, multiple increment sampling, radiological transect surveying, and a brief description of other potentially applicable sampling methods. Further, this work highlights a potential need for the use of statistically based sample designs in OSI activities. The use of such designs may enable canvassing a sample area without full sampling, provide a measure of confidence that radionuclides are not present, and allow investigators to refocus resources in other areas of concern.

Identifying Minefields and Verifying Clearance: Adapting Statistical Methods for UXO Target Detection

It may not be feasible to completely survey large tracts of land suspected of containing minefields. It is desirable to develop a characterization protocol that will confidently identify minefields within these large land tracts if they exist. Naturally, surveying areas of greatest concern and most likely locations would be necessary but will not provide the needed confidence that an unknown minefield had not eluded detection. Once minefields are detected, methods are needed to bound the area that will require detailed mine detection surveys. The US Department of Defense Strategic Environmental Research and Development Program (SERDP) is sponsoring the development of statistical survey methods and tools for detecting potential UXO targets. These methods may be directly applicable to demining efforts. Statistical methods are employed to determine the optimal geophysical survey transect spacing to have confidence of detecting target areas of a critical size, shape, and anomaly density. Other methods under development determine the proportion of a land area that must be surveyed to confidently conclude that there are no UXO present. Adaptive sampling schemes are also being developed as an approach for bounding the target areas. These methods and tools will be presented and the status of relevant research in this area will be discussed.