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DATE: July 21, 2017 TO: Felicia Barnett, Director SCMTSC, EPA, WAM FROM: Anita Singh, Ph.D., SERAS Statistician THROUGH: Richard Leuser, SERAS Deputy Program Manager SUBJECT: DRAFT - REVIEW OF APPENDIX P OF THE REMEDIAL INVESTIGATION

ADDENDUM, WEST LAKE LANDFILL OPERABLE UNIT 1, BRIDGETON, MO., SERAS-106, WO-75.

This technical memorandum (TM) summarizes review comments on the geostatistical methods used and described in Appendix P of the Remedial Investigation Addenda (RIA), June 2017 prepared for the West Lake Operable Unit (OU) -1 Respondents Group (PRPs). The RIA has 16 appendices: A through P with Appendix P describing details of the geostatistical approaches that the PRPs plan to use to address the two objectives: 1) delineate the extent of radiologically impacted material (RIM) and; 2) estimate RIM volumes present in the two areas of concern (AOCs): Area-1, Area-2 of OU-1. The main radionuclides of concern (ROCs) are: radium, thorium and uranium. The cleanup levels to determine site soils requiring further remediation investigations (e.g., partial/complete RIM excavation and removal) for combined radium, combined thorium and uranium are: • Cleanup level for combined Radium: Ra-226+Ra-228 = 7.9 pico-Curies per gram (pCi/g) • Cleanup level for combined Thorium: Th-230+Th-232 = 7.9 pCi/g • Clean for total uranium = 54.5 pCi/g RIM and No RIM for Potential Remediation: In Appendix P, RIM is defined as landfill material with concentrations of either combined radium (i.e., radium-226 + radium-228) or of combined thorium (thorium-230 + thorium-232) exceeding 7.9 pCi/g; material with both combined thorium and combined radium concentrations less than 7.9 pCi/g is determined to represent non-RIM material. RIM contaminated with ROCs are present in the surface soils (<0.5 feet deep) and in subsurface soils (> 0.5’ extending up to 10’ and higher depth levels) of the two AOCs. To estimate RIM volumes potentially requiring excavation, geospatial evaluations have been performed in horizontal as well as vertical directions. In Appendix P (with several appendices of its own such as A, B, …), statistical evaluations have been performed using combined radium and combined thorium concentrations, alpha (used in vertical variograms) and gamma emissions scanning data. Table 1 from the Supplemental Feasibility Study (SFS) Report (2011) summarizes the maximum reported activity levels in

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AOCs for the ROCs listed above. Considerable amount of laboratory (lab) concentration data for ROCs and field gamma scanning data at various depth levels have been collected from these AOCs since 2011and is summarized in Table A-1 (from Area-1) and in Table A-2 (Area-2) of Appendix A (within Appendix P). From data presented in Table 1 (below), Tables A-1 and A-2, it is noted that many locations of the two AOCs exhibit ROC activities much higher than pre-established cleanup levels which may require further remediation (partial or complete excavation and removal). Table 1. From SFS (2011) Report

C Some general comments about the methods used in most sections of Appendix P are presented as follows. Specific comments about data processing, correlation evaluations, thresholds, variogram models and assumptions made are provided in subsequent sections of this TM. General Comments:

In this section, comments are provided mainly on methods used/proposed and assumptions made as described in the first four sections of Appendix P. Appendix P does not provide any statistical details (e.g., summary statistics, correlation coefficients, regression equations) which are often accompanied with geostatistical evaluations. Evaluations described in the appendix lack transparency, therefore, it is not feasible to determine the validity and accuracy of the results and conclusions described. The two main methods used in Appendix P are: 1) regression analysis (Figures 4a and 4b); and 2) variogram modeling (Figure 7). It is not clearly stated which data sets have been used in the generation of these figures. In this review, it is assumed that: 1) all available data from Area 1 and Area 2 at all depth levels combined (from Table A-1 and Table A-2) have been used to perform regression analysis shown in Figures 4a and 4b; 2) combined radium data (hard lab data) from all depth levels and combined thorium data (hard) from all depth levels and perhaps gamma count soft data from locations without any concentration data for thorium and radium have been used to generate empirical horizonal variograms for Areas 1 and 2;

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3) and five different kind of soft (e.g., gamma, alpha) data sets have been used to generate vertical averaged variograms as shown in Figure 7. Several untenable assumptions not supported by graphical displays (e.g., Figure 7) have been used. For an example, the assumption that the nugget is ‘zero’ for all variogram evaluations in the horizontal direction based upon the combined radium and combined thorium data is not supported by empirical variograms shown in Figure 7. It is stated that multiple indicator kriging (MIK) has been performed for four threshold levels. However, it is noted that only one threshold of 7.9 pCi/g has been considered; variograms, estimates of RIM extent and RIM volumes are evaluated using indicator kriging (IK) for threshold level, 7.9 pCi/g. For transparency and clarity, it is suggested to make Appendix P less confusing and concise by removing irrelevant sections and paragraphs describing the use of MIK on multiple thresholds as no results based upon MIK are presented in Appendix P. As suggested in Appendix P, the appendix will be updated with more details in the pending focused feasibility study (FSS) by using MIK on multiple threshold values. It should however be noted that if the PRPs do plan to use MIK (for FSS), the use of more than 4 thresholds should be considered as suggested in the literature (e.g., Carvalho and Deutsch, January 2017). The primary objective of Appendix P should be to demonstrate that IK with one threshold value yields reliable estimates of RIM extent and RIM volumes by addressing uncertainties in RIM estimates. This requires the computation of kriging variances. It is suggested to pay extra attention to the generation of variograms and estimating all associated parameters: nugget, sill and range. All intermediate results should be provided in the appendix supporting the assumptions and claims made. Section 8.0 states that results and conclusions described in the appendix suffer from unquantifiable uncertainties. Sill is an important parameter and a reasonably good estimate of sill (by fitting a good variogram model) is required to compute kriging standard deviations. Kriging standard deviations are used to assess uncertainties associated with kriged (interpolated) estimates (RIM extent and RIM volumes). From regression lines shown in Figures 4a and 4b, it is noted that the correlations between combined thorium and bore hole gamma counts and total radium and borehole gamma counts appear to be reasonably high. However, important statistics including regression tables, slopes, correlation coefficients and mean square error (MSE) are not included in the text (e.g., pages 3-4 and 3-5). Instead of making qualitative statements (pages 3-4 and 3-5) such as the “relationship is weaker between gamma and combined thorium”, it is requested to include relevant regression statistics in Section 3. Without showing relevant work (regression equations and prediction intervals), it is not feasible to evaluate the accuracy of the statements such as: “For combined radium: if the normalized gamma is less than 0.0028, then the CDF corresponding with the first concentration threshold (i.e., 7.9 pCi/g) is 0.925, and the CDF corresponding with the second concentration threshold (in this instance, 52.9 pCi/g) is 1.000….,” made on page 3-5. The use of MIK requires generation of many variograms (e.g., 4 for each threshold) each of which will have its own parameter values (nugget, sill and range). Due to lack of data, one may not be able to use MIK for higher threshold values. The parameters for the various variograms may or may not be comparable. All these issues result in the use of many assumptions (0 nugget,

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same sill, same variogram for all thresholds) which in turn will yield RIM extent and RIM volume estimates with unquantifiable uncertainties. Moreover, it is not easy to understand and interpret RIM and non-RIM determination based upon probabilities, discretized cumulative distribution function (CDF) or piecewise continuous CDF. Due to the reasons described here, it might not be easy for the decision makers and other interested parties to make defensible and cost-effective remediation decisions based upon the results and estimates derived using MIK. It is suggested to use ordinary kriging (OK) on the observed and predicted (obtained using regression lines shown in Figures 4a and 4b) concentration data. Depending upon data variability and distribution of concentration data, OK can be performed on concentration data in the original scale or in the log-scale. More details on this issue are described in the ordinary kriging section below. Graphical Displays: In practice for better understanding of data, geostatistical evaluations are supplemented with simple summary statistics and exploratory graphical displays. Appendix P does not provide any summary statistics and does not use any exploratory graphical methods which are useful in verifying assumptions. There is no substitute for graphical displays of data. Graphical displays provide added insight about potential patterns present in data sets. The use graphical displays including histograms, boxplots and quantile-quantile (Q-Q) plots helps in: verifying the assumptions made, identifying extreme outliers and multiple populations, and evaluating data distribution. The use of side-by-side boxplots comparing ROC concentrations (and gamma emissions) for several depth intervals (bins) such as: (0’-0.5’), (0.5’-5’), (5’-10’), and (>10’) can provide visual information about contamination levels at those depth intervals. This information can be useful in estimating RIM volumes and in making remediation decisions. It is suggested to partition data (both hard and soft) into certain number of depth intervals (bins); use graphical displays to compare data in those intervals and provide summary statistics for those depth categories. Appendix B of Appendix P contains many graphs generated using the five types of soft scanning data and hard concentration data for combined radium and combined thorium. However, these graphs do not provide any useful information which can be used to estimate RIM extent and RIM volumes in the two AOCs of OU-1. It is documented in Appendix B (e.g., Section 1.1) that the northing and the easing coordinates and elevation information for sampled results for combined thorium and combined radium are available. Soft gamma count data is available at many depth levels where concentration data was not collected. It is suggested to use equations shown in Figures 4a and 4b to predict combined thorium and combined radium concentrations as functions of corrected gamma count data. The resulting observed and predicted concentration data can be used to generate graphical displays including box plots and posting plots for thorium and radium. This exercise will help in addressing uncertainties associated with RIM volumes. For transparency and better understanding of the evaluation process used, it is recommended to include some examples illustrating how regression lines (Figures 4a and 4b) were used to come to the conclusions made in Section 3 (first two paragraphs on page 3-5). It is also desirable to justify why one can use ‘0’ as an estimate of nugget for all variogram models, especially when only one value (maximum of duplicate and maximum of replicate) has been used for each sampled location. The value of sill should not be ignored as it is used to determine kriging standard deviations. Empirical variograms described in the appendix (Figure 7) do not support

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the assumption that the sill parameter value is the same for all variograms. It is recommended to provide material (intermediate work) in support of the qualitative statements, claims and assumptions made. Specific comments on sections of Appendix P are provided as follows. Most review comments have a section title followed by paragraph(s) from Appendix P in quotes which are followed by our Review Comments. Multiple Thresholds: Review comments: The use of MIK has been proposed on the combined thorium, combined radium, and alpha and gamma scanning data to determine probabilities of areas with RIM exceeding multiple threshold levels. It is stated that four threshold values have been considered including 7.9 pCi/g and 52.9 pCi/g. The values for the other two thresholds could not be found in the appendix. Moreover, variograms for only one threshold value of 7.9 pCi/g have been presented in the appendix. Instead of making things complicated and stating that multiple thresholds have been used and the same variogram has been used for all thresholds, it is suggested to clean the appendix and state that indicator kriging (IK) has been used for the threshold value of 7.9 pCi/g. All intermediate work supporting the claims (e.g., nugget is ‘0’, sill parameter same for all variograms) should be included in the appendix. Once it can be demonstrated (supplemented with regression models, values of variogram parameters, distributional graphical displays) that the suggested IK approach (for one threshold) performs well in estimating RIM extent and RIM volumes with quantifiable uncertainties (in terms of kriging standard deviation), MIK approach may be used for multiple thresholds with all supporting details to be included in the pending focused feasibility study (FSS). Correlation Evaluations – Pages 2-4 to 2-6:

The quoted paragraphs are taken from Appendix P which are followed by review comments.

“A relationship between (combined) radium concentrations and gamma readings is anticipated based on the decay characteristics of radium. A much weaker relationship would be anticipated between (combined) thorium concentrations and gamma readings based solely on the decay characteristics of thorium. However, because thorium and radium are often co-associated and correlated as depicted in Figures 2 and 3, there is a stronger relationship between (combined) thorium concentrations and gamma readings than that which would be anticipated based solely on thorium decay characteristics.” Review Comments: Based upon Figures 2 and 3, Appendix P concludes that thorium and radium are correlated at higher concentration levels. To quantify the level of association between thorium and radium, it is suggested to include equations (slopes, correlations, regression table) of regression lines shown in Figures 2 and 3 for the part where stronger relationship is anticipated. These statistics will assist in quantifying uncertainties associated with qualitative statements made in Sections 2 and 3.

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“Figure 4 depicts scatter plots of (a) combined thorium concentration and (b) combined radium concentration versus recorded gamma energy emissions counts (cpm). Sample data used to prepare Figures 4a and 4b are listed in Appendix A: Table A-1 and Table A-2, plotted for visual inspection in Appendix B and described further in Section 3. The gamma energy emission counts used to prepare Figures 4a and 4b have been corrected for the presence of baseline responses: the process of removing baseline responses from both alpha and gamma recordings prior to their plotting and consideration for use in the indicator kriging is detailed in Section 3 and Appendix B. Figures 4a and 4b visually illustrate the relationships that exist in the two areas between the concentration of combined radium or the concentration of combined thorium and the gamma counts recorded at the same location. Also plotted on Figures 4a and 4b are prediction intervals computed based upon the “fit” of a simple linear regression of the logarithm of the sampled radionuclide concentration with the logarithm of the gamma emission readings. The widths of the prediction intervals indicate in relative sense the likely error associated with predicting the concentration of a specific radionuclide in a sample based upon a gamma emission measurement (which is assumed to be made without error).” “The following are noted from Figures 4a and 4b: • The axes used in Figures 4a and 4b are logarithmic, due to the high variance of the data. Therefore, in each plot, the depicted relationship is between the logarithm of the concentration of the radionuclide and the logarithm of the gamma emission recordings. • With some exceptions, the relationship between radionuclide concentration and gamma readings appears stronger at relatively high concentrations and counts, for both combined radium and combined thorium. • For comparable gamma emission measurements, concentrations of combined thorium are typically greater than the concentrations of combined radium. This is illustrated by the relative slopes of the regression lines. • The relationship between radionuclide concentration and gamma readings appears stronger for combined radium than for combined thorium. This is qualitatively illustrated by the relative scatter on the combined radium versus gamma plots as compared to the combined thorium versus gamma plots, and more quantitatively depicted by the relative width of the prediction intervals along the ordinate axis which span about 2 orders of magnitude in the case of the combined radium, and about 3 orders of magnitude in the case of combined thorium.” Review Comments: Several qualitative statements have been made in the above paragraphs. Figure 4a has the simple linear regression line of combined logged thorium pCi/g (y-variable) versus borehole corrected gamma logged data (x-variable), and Figure 4b has the corresponding regression of combined radium (y-variable) on borehole corrected gamma logged data (x-variable). Regression lines shown in Figures 4a and 4b are to be used to forecast/predict concentration (y) data (in log-scale) as a function of corrected gamma count (x) data (log-scale). Even though lines and prediction intervals shown in these two figures have been used in evaluations summarized in the appendix, important useful statistics including regression tables, slopes, correlation coefficients and mean square error (MSE) are not provided anywhere in the

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text (e.g., above quoted paragraphs from Section 2 and pages 3-4 and 3-5 of the appendix). It is desirable to review these statistics rather than making qualitative statements about correlations and width of the prediction intervals (measured by MSE). Figures 4a and 4b have regressions lines which are to be used to predict concentration data (y) as functions of soft corrected gamma (x) data. However, it appears that lines shown in Figures 4a and 4b have been used to forecast gamma count data (x) as functions of combined thorium and combined radium which are then used in the generation of horizontal variograms and computing RIM and no-RIM estimates. It is requested to elaborate on this transformation of hard data into soft gamma count data. Regression lines shown in Figures 4a and 4b have also been used to predict gamma count for threshold level 7.9 pCi/g. Further clarification is requested about the use of regression lines shown in Figures 4a and 4b.Without exhibiting all relevant work (equations and prediction intervals), it is not feasible to verify the accuracy of statement, “For combined radium: if the normalized gamma is less than 0.0028, then the CDF corresponding with the first concentration threshold (i.e., 7.9 pCi/g) is 0.925, and the CDF corresponding with the second concentration threshold (in this instance, 52.9 pCi/g) is 1.000….,” made on page 3-5. Similar comments apply to the statement made about combined thorium on page 3-5. Hard Data Processing - Section 3-2: “Reported values of radium-226, radium-228 thorium-230 and thorium-232 were provided by EMSI as documented in the Remedial Investigation (RI) Addendum (RIA) (EMSI, 2017). In accordance with sample data processing steps agreed to in correspondence with the EPA, the database constructed by EMSI in the spring of 2017 selected the maximum value for duplicate and co-located samples (i.e. replicates). Combined radium and combined thorium results were calculated by adding the reported values of the individual radium isotopes (Ra-226, Ra-228) and thorium isotopes (Th-230, Th-232), respectively. If a reported value was below the Minimum Detectable Activity (MDA), half of the reported value was used in the combined isotope calculation.” Review Comments: From the process described above, it is noted that one and only one value (maximum duplicate, maximum replicate) is retained at each sampled location. This scenario should enable one to estimate nugget effect in fitting a variogram model. Assuming a ‘0’ nugget value (not supported by sample variograms in Figure 7) for all horizontal variograms will add unquantifiable level of uncertainty in kriged estimates of RIM extent and RIM volumes. Coding of the Soft Data – Section 3.3.4: “In anticipation of the need for calculations across a range of thresholds in support of remedial design evaluations, the CDF was discretized into several thresholds: however, results for only the first threshold – i.e., 7.9 pCi/g – are presented in this report. Further analysis will be undertaken for the other thresholds in support of a pending Focused Feasibility Study (FFS).”

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Review Comments: For clarity and to demonstrate the effectiveness of the approach, it is suggested that all intermediate work (at least on a subset data set) performed for the cleanup threshold value of 7.9 pCi/g be included in the appendix. It is requested to include graphical display of discretized CDF and thresholds mentioned in the above paragraph. “The CDFs relating gamma measurements to likely concentrations of combined radium and combined thorium were defined via the following two step process, undertaken separately for combined radium and combined thorium:” “• First, the relationship between the (logarithm of) radionuclide concentration and the (logarithm of) gamma count was explored to identify the approximate gamma count corresponding to a concentration of the radionuclide at the threshold concentration of interest. This was gleaned primarily from the relationships depicted in Figures 4a and 4b.” Review Comments: It is requested to explicitly demonstrate the use of relationship shown in Figures 4a and 4b in determining gamma count corresponding to threshold concentrations, 7.9 pCi/g and 52.9 pCi/g for both combined thorium and combined radium. “• Second, the potential relative error associated with forecasting a concentration of combined radium or combined thorium based upon a measurement of gamma was derived from the prediction intervals presented in Figures 4a and 4b. As noted above, because the relationship is weaker between gamma and combined thorium (as illustrated by the relative width of the prediction intervals along the ordinate axis), there is greater uncertainty associated with forecasting combined thorium concentrations from gamma than there is when forecasting combined radium concentrations.” Review Comments: The above paragraph implicitly states that concentrations of combined radium and combined thorium were predicted/forecasted using lines shown in Figures 4a and 4b. It is of interest to know – how the predicted concentration values were used in geostatistical evaluation summarized in the appendix. It is requested to include all relevant statistics associated with lines shown in Figures 4a and 4b which can be used directly to assess the strength/weakness of the relationships between hard and soft data and assess uncertainties (via prediction intervals and associated MSEs) associated with forecasted values of combined thorium and combined radium. “The complete CDFs that relate combined radium and combined thorium concentrations to gamma readings for purposes of coding the gamma readings as soft data for input to IK3D to map RIM in Areas 1 and 2 comprise multiple thresholds, as noted above. Full details of the derivation of the complete CDF will be provided in a subsequent report in support of the FFS.” Review Comments: There are conflicting statements about the number of thresholds used in the appendix. For clarification, conflicting statements about the number of thresholds considered should be removed from the report. If multiple thresholds were used and MIK was used, all details how complete CDFs were derived should be included in Appendix P. If gamma readings have been coded using multiple thresholds, it is requested to illustrate the coding process by using a small example data set from Area 1 or Area 2.

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“For purposes of this report, which presents the estimated extent of RIM at concentrations exceeding 7.9 pCi/g, the following criteria from the complete CDF were used to define the relationship between gamma readings and combined radium or combined thorium: • For combined radium: if the normalized gamma is less than 0.0028, then the CDF corresponding with the first concentration threshold (i.e., 7.9 pCi/g) is 0.925, and the CDF corresponding with the second concentration threshold (in this instance, 52.9 pCi/g) is 1.000, reflecting the fact that the predictive error associated with the relation between gamma and combined radium concentrations is of the order of 1 order of magnitude. • For combined thorium: if the normalized gamma is less than 0.0017, then the CDF corresponding with the first concentration threshold (i.e., 7.9 pCi/g) is 0.850, and the CDF corresponding with the second concentration threshold (in this instance, 52.9 pCi/g) is 0.975, reflecting the fact that the predictive error associated with the relation between gamma and combined thorium concentrations extends beyond 1 order of magnitude.” Review Comments: Without providing the regression line equations and prediction intervals used in the above two paragraphs, it is not feasible to determine the accuracy and validity of the results and conclusions described in the above paragraphs. It is requested to provide all calculations used to compute predictive errors mentioned in the above paragraphs. “The normalized response could be encoded for use as soft data in the indicator kriging in one of two ways – in either case, the encoding relies upon a presumed correlation between the normalized response and the presence and concentration of combined radium or combined thorium.” Review Comments: The above paragraph suggests that regression lines shown in Figures 4a and 4b have been used in the coding process of the normalized soft data. It appears that lines shown in Figures 4a and 4b have been used to forecast normalized response (gamma count) as functions of combined thorium and combined radium concentrations. This needs further clarification as lines shown in Figures 4a and 4b are used to forecast hard (radium and thorium) data as functions of gamma count data. “First, the soft data could be encoded using zeros and ones comprising a discrete CDF: in this case, a value of one would identify that the soft data indicate without any associated uncertainty that the material at that location and depth represent RIM within a specific threshold concentration interval.” “Alternatively, the soft data could be encoded using a piecewise-continuous CDF: in this case, the values of the CDF would increase as the threshold concentration increases, and the normalized response would “shift” the CDF to reflect the balance of evidence for the presence of RIM. For example: a relatively high normalized response at a specific location and depth would tend to indicate that there is RIM present at some concentration (the latter depending on the relation between the normalized response and the combined radium or combined thorium concentration), which in turn indicates that at that location and depth the probability of not

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exceeding the lower thresholds is relatively low. In this study, the second approach was used: where the normalized gamma response data indicated negligible RIM a default CDF was used, and this default CDF was updated to reflect increasingly high normalized responses that indicated a likely presence of RIM at the corresponding location and depth. In anticipation of the need for calculations across a range of thresholds in support of remedial design evaluations, the CDF was discretized into several thresholds: however, results for only the first threshold – i.e., 7.9 pCi/g – are presented in this report.” Review Comments: Qualitative statements made in the above paragraph cannot be verified. It is requested to provide an example (perhaps using a small data set from Area 1 or Area 2) showing the exact process used. The highlighted sentence in the above paragraphs suggests that lines shown in Figures 4a and 4b were used to forecast normalized response (gamma count) as functions of combined thorium and combined radium concentrations (how?). Instead of describing the relationship between normalized gamma and CDF in words and sentences, it is requested to use graphical display(s) to illustrate the behavior of piecewise-continuous CDF versus multiple thresholds described in the above quoted paragraph. Variograms and MIK – Section 4: “The main parameters used to describe a single-structure model variogram are the nugget (n), which describes the variance at very small separation distances; the sill (s), which describes the asymptotic limit of the variance of the model variogram or no correlation limit; and the range (r) which describes the separation distance at which the variogram value is asymptotically or practically equivalent to the sill.” “The value ascribed to the sill does not alter the value of the interpolated estimate that is obtained at intermediate locations when kriging; however, it does alter the value of the kriging variance. Because kriging variances were not employed for any purpose in this study of the likely extent of RIM, the actual values ascribed to the sills are not of great importance, and emphasis is instead placed upon estimating and modeling the form of the variogram and the range-lengths in the horizontal and vertical directions. If kriging variances are to be used in future calculations, greater emphasis should be placed on obtaining accurate estimates of the variogram sills.” Review Comments: As commented earlier, variogram models used in the appendix assume a ‘0’ value for the nugget parameter. However, empirical variograms shown in Figure 7 do not support the assumption that the nugget, n is 0 for all models (e.g., for horizontal variograms) used. It is of interest to evaluate the impact of using a ‘0’ nugget on RIM extent and volume estimates. Additionally, kriging variance/standard deviation is an important part of a kriging exercise. Kriging standard deviations are used to determine uncertainties associated with interpolated estimates/probabilities computed for unsampled locations based upon data from sampled locations. Without calculating sill and kriging variances, the appropriateness of using MIK cannot be assessed as uncertainties associated with estimated RIM extent and RIM volumes cannot be determined. It is suggested to use variogram models by selecting the most appropriate parameter values supported by empirical variograms.

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“The use of MIK to evaluate data across multiple thresholds could employ variograms that are specific to each threshold, resulting in four potentially different variograms to represent one constituent (e.g., combined radium) across four thresholds. However, because the proportion of samples exceeding higher values declines quickly, it prevents the development of empirical variograms specific to high concentration thresholds.” “As a consequence, a single variogram model was used for all indictor thresholds, and emphasis was placed on estimating the directional range lengths for this single, horizontally-isotropic vertically-anisotropic spherical variogram model in two steps, as follows: first, the (isotropic) variogram range-length in the horizontal direction (and the sill) were estimated for Areas 1 and 2 separately from the complete set of combined thorium and combined radium sample data obtained from each Area, respectively.” Review Comments: It is not clear which multiple thresholds were used. From evaluations described in the appendix and shown in Figures 8 through 11 and in Tables 1 and 2, it is noted that only one threshold value (7.9 pCi/g) was used to generate variograms shown in Figure 7. If indeed multiple thresholds were used, it needs to be demonstrated that assumptions made about the use of the same variogram spherical model for all four empirical variograms (one for each threshold) and ‘0’ nugget are tenable. If the assumptions cannot be verified and supported by data, it is highly likely that RIM estimates (extent and volume) suffer from unquantifiable uncertainties posing difficulties in making defensible and cost-effective remediation decisions. No sill estimates were provided in the appendix for any of the four horizonal variogram models shown in Figure 7. The above paragraphs also state difficulties in estimating RIM extent and volumes based upon MIK for multiple thresholds. An alternative approach based upon OK has been suggested which is briefly described in the ordinary kriging section. Equivalent Sill Value in All Direction and Other Assumptions “Next, the range-length in the vertical direction was estimated from gamma response data which is more continuously available in the vertical direction. Although the range-lengths of the horizontal and vertical variogram models were defined on the basis of different data types – i.e., the range-length of the horizontal variogram was defined from the combined radium and combined thorium sample data, whereas the range-length of the vertical variogram was defined from gamma counts – it is assumed that the sill is equivalent in all directions and is equal to that which is obtained from the horizontal empirical variogram calculated from the combined radium and combined thorium sample data. Furthermore, the variogram range length was assumed equal for the combined radium and combined thorium within each area, derived on the basis of a visual “fit” to empirical indicator variograms constructed for indicator-transformed values of combined radium and combined thorium corresponding to the first concentration threshold alone.” Review Comments: Several assumptions (highlighted) have been made about variograms and associated parameters (sill, range-length) without theoretical justification. Sill values for any of the variogram models shown in Figure 7 are not provided. A quick review of variograms presented in Figure 7 leads to the conclusion that the assumption made in sentence, “it is assumed that the sill is equivalent in all directions and is equal to that which is obtained from the

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horizontal empirical variogram calculated from the combined radium and combined thorium sample data,” is not tenable. Without using defensible sill values, the uncertainties associated with estimates of RIM extent (e.g., Figures 8-11) and RIM volumes cannot be evaluated. It is a common practice to transform field data (gamma counts) into concentration data based upon a good significant regression equation. In the above paragraph, it is stated that combined thorium and combined radium values have been transformed into indicator values (‘0’ and ‘1’ values based upon predicted gamma counts). It is not clear how this transformation was performed as lines shown in Figures 4a and 4b are used to transform gamma counts data into concentration data. Range-Length Parameters “On the basis of the multi-boring vertical empirical variograms plotted together by data class in Appendix C, and the variogram model visually fit to the weighted average of these empirical variograms normalized by their average binned (semi-)variance shown in Figure 7, the final variogram models developed for Areas 1 and 2 were parameterized as follows (in each case, using a spherical model variogram structure): • Area 1: horizontal range-length = 140 feet; vertical range-length = 3.5 feet. • Area 2: horizontal range-length = 200 feet; vertical range-length = 3.5 feet.” Review Comments: Variograms shown in Figure 7 do not support the above range-length parameters. For Area 1, horizontal range length appears to be around 300’ – 350’ and for Area 2, the horizontal range length appears to be around 600’. The vertical range length based upon the averaged variogram model (based upon 5 types of soft data) appear to be between 4’-4.5’. Suggestions - Use Ordinary Kriging (OK): When using MIK for four or more thresholds (use of 7 to 15 thresholds is recommended in the literature), the number of variograms and associated parameters can become unmanageable to interpret and derive conclusions. For each threshold level, 6 empirical variograms will be generated: 3 for Area 1(horizonal for combined radium, horizontal for combined thorium and vertical) and 3 for Area 2 ((horizonal for combined radium and combined thorium and vertical). The use of MIK with 4 thresholds will require the generation of 6*4 = 24 empirical variograms and determining 24 variogram models with 24* 3 = 78 parameters. Summarizing information provided by so many variograms becomes tedious without making many assumptions. The use of untenable assumptions (e.g., same variogram model for all thresholds with equivalent sill) introduces uncertainties in estimates of interest (RIM extent and RIM volumes). Moreover, one needs to make decisions based upon probability maps (for coded corrected gamma count data) and relation between CDFs and threshold values which gets complicated and tedious as the number of thresholds increases. The issue of generating 4 variogram models for each of the 4 thresholds can be addressed by using OK on concentration data sets containing: observed concentration data for combined radium and combined thorium and predicted concentration data obtained using regression lines shown in Figures 4a and 4b on gamma count data where concentration data was not collected

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Note: Note that regression lines shown in Figures 4a and 4b are derived using all available hard concentration and corrected gamma count data (sharing the same location) collected from all depth levels, therefore those lines are applicable to predict concentration data as functions of corrected gamma count (separately for thorium and radium) data at locations for which lab thorium and radium data is not available. The observed and predicted data for combined thorium and combined radium can be used to perform OK directly on concentration data requiring the generation of at most 6 variograms (3 for each AOC). Remediation decisions are made separately for Area 1 and 2. Therefore, one needs to summarize information provided by 3 variogram models and associated parameters for each area separately. Once kriged surfaces (concentration maps) have been generated, prediction contour plots with 90% or 95% confidence coefficient around kriged surfaces can be generated to quantify uncertainties associated with estimated RIM extents (kriged surfaces). When dealing with spatially collected data, uncertainty is addressed by contour plots (90%, 95%) drawn around kriged surfaces. For example, using a 95% contour plot around a kriged surface, one can say that mean concentration of a ROC at an unsampled location will lie in the prediction interval with 95% confidence coefficient. OK yields exact values at sampled locations. For vertical variograms, instead of using the average of 5 (one for each kind of soft data) different variogram models described in Appendix C (each associated with uncertainties), it is suggested to use OK on observed and predicted (as functions of corrected gamma cpm data) thorium and radium concentration data obtained using regression models shown in Figures 4a and 4b. These models should be supplemented with graphical displays described in the general comment section.

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References Carvalho, D. and Deutsch, C. 2017. An Overview of Multiple Indicator Kriging. Geostatistics Lessons. Engineering Management Support, Inc. (EMSI), 2011, Supplemental Feasibility Study Radiological-Impacted Material Excavation Alternatives Analysis West Lake Landfill Operable Unit-1. December 16, 2011. Lipton, I., Gaze, R., Horton, J., and Khosrowshahi, S. Practical Application of Multiple Indicator Kriging and Conditional Simulation to Recoverable Resource Estimation for Halley’s Lateritic Nickel Deposit. Mining and Resource Technology. Symposium on Beyond Ordinary Kriging. Remedial Investigation Addenda (2017). West Lake Landfill Operable Unit-1. June 16. DRAFT Xavier E. and Ortiz, J.M. (2004). Shortcomings of multiple indicator kriging for assessing local distributions. Applied Earth Science, 113:4, 249-259.