Background Soil Guidance

Background Soil Guidance

Division of Waste Management Background Soil Guidance August 14, 2018 Rationale for Updating the Guidance The FDEP soil background guidance was written in 2012. Since this time: ProUCL has updated/added statistical methods used in the program. Lessons learned from use of the guidance at different sites has highlighted the need for updates to the recommended procedures. 08/08/18 Background Guidance Updates 2 Lessons Learned 1. Non-parametric tests can mask contamination due to the ranking procedure. Hot spots are more easily identified than low levels of contamination. 2. Large numbers of non-detected data can also mask low levels of contamination, especially with multiple detection limits. 08/08/18 Background Guidance Updates 3 Updates Analyses were added from the USEPA Guidance for Comparing Background and Chemical Concentrations in Soil for CERCLA Sites (2002). Added to help project managers get

a better understanding of the dataset. All additional analyses can be performed in ProUCL: https://www.epa.gov/land-research /proucl-software 08/08/18 Background Guidance Updates 4 1. Summary Statistics Kaplan Meier method provides better estimates for mean and standard deviation than detection limit for datasets with non-detects. Summary Statistics for Censored Data Set (with Non-Detects (NDs)) using Kaplan Meier Method Variable NumObs Cu (alluvial fan) 65 Cu (alluvial fan) 49 # Missing 3 1 NumDs 48 35 NumNDs 17 14 % NDs 26.15% 28.57% Min ND 1 1 Max ND 20

15 Median 2 3 Var 16.04 27.18 KM Mean 3.608 4.362 KM Var 13.08 21.64 KM SD 3.616 4.651 MK CV 1.002 1.066 Summary Statistics for Raw Data Sets using Detected Data Only Variable NumObs Cu (alluvial fan) 48 Cu (alluvial fan) 35 # Missing Minimum Maximum 3 1 20 1 1 23 Mean 4.146 5.229

SD 4.005 5.214 MAD/0.675 Skewness 1.483 2.256 2.965 1.878 CV 0.966 0.997 Percentiles using all Detects (Ds) and NDs Variable NumObs Cu (alluvial fan) 65 Cu (alluvial fan) 49 08/08/18 # Missing 3 1 10%ile 1 1 20%ile 2 2 25%ile(Q1) 50%ile(Q2) 75%ile(Q3) 80%ile 2 3 5 7 2 4 8 9.4

Background Guidance Updates 90%ile 10 12.4 95%ile 15.2 15 99%ile 20 20.12 5 2. Quantile-Quantile Plots Helps to visualize whether background and site concentrations are from the same population. Unless sites are identical, the trendlines will be slightly different. Deviations of data points from the trendline should be similar. 08/08/18 Background Guidance Updates 6 Quantile-Quantile Plots When two populations are not equivalent, it helps in visualizing where the site concentrations deviate from background. Q-Q plots are useful, but should not be used as a sole line of evidence for equivalence or nonequivalence of two populations. 08/08/18 Background Guidance Updates 7 3. General outlier tests Tests whether a sample is likely to be an outlier. Used to identify elevated concentrations in the

dataset. Presents statistical evidence the data point is not from the same population as the rest of the data. 08/08/18 Background Guidance Updates 8 3. Specific outlier tests Outlier Tests for Selected Variables replacing Nondetects with 1/2 the Detection Limit Rosners test is used for greater than or equal to 25 data points, Dixons test is used for less than 25 data points. Outliers in background dataset suggests the sample was collected in an area that was not truly background. Outliers in the site dataset suggests areas of low level contamination. 08/08/18 Options User Selected Date/Time of Computation ProUCL 5.14/24/2018 8:28:34 AM From File WorkSheet.xls Full Precision OFF Rosner's Outlier Test for 5 Outliers in Site 0-05 Number Total N Number NDs Detects 56 0

56 # Mean SD 1 2 3 4 5 0.902 0.844 0.802 0.766 0.735 0.814 0.703 0.637 0.585 0.544 Background Guidance Updates Mean with NDs=DL/2 SD with NDs=DL/2 Number of data Number of suspected outliers 0.902 0.821

56 5 Potential outlier 4.1 3.1 2.7 2.4 2.2 NDs replaced with half value. Obs. Critical value Critical value Number Test value (5%) (1%) 27 3.93 3.172 3.528 4 3.21 3.162 3.518 39 2.981 3.158 3.514 3 2.791 3.148 3.508 46 2.693 3.138 3.498 For 5% significance level, there are 2 Potential Outliers 4.1, 3.1

For 1% Significance Level, there is 1 Potential Outlier 4.1 9 4. UTL Approach A 95% upper tolerance limit (UTL) on background 95% of background concentrations will fall below this value with 95% confidence. Site data are compared to the 95% UTL. If more than 5% of the data exceed the 95% UTL, it suggests a greater number of elevated concentrations on the site than background. In other words, the site may not be equivalent to background. Background Statistics assuming Lognormal Distribution 95% UTL with 95% Coverage 808.1 08/08/18 95% UPL (t) 440.6 95% USL 1162 90% Percentile (z) 265.4 Background Guidance Updates 95% Percentile (z) 393.5 99% Percentile (z) 823.5 10 5. Statistical tests Outlier Tests for Selected Variables replacing Nondetects with 1/2 the Detection Limit Wilcoxon Rank Sum (WRS) test is no longer on ProUCL. It was replaced with the

similar Wilcoxon-MannWhitney (WMW) test, which can be used instead. Gehan or Tarone-Ware test are used for datasets with greater than 40% nondetects or with multiple detection limits. Options User Selected Date/Time of ProUCL 5.14/24/2018 8:49:57 AM Computation From File WorkSheet.xls Full Precision OFF Full Precision OFF Confidence Coefficient 95% Selected Null Hypothesis Sample 1 Mean/Median >= Sample 2 Mean/Median (Form 2) Alternative Hypothesis Sample 1 Mean/Median < Sample 2 Mean/Median Raw Statistics Number of Number of Number of Minimum Maximum Percent Sample Valid Data Non-Detects Detect Data Non-Detect Non-Detect Non-detects 1 2 47 12 7 2 40 10 0.1 0.715 0.1 0.735 Maximum Mean of Median of SD of Sample Minimum Detect Detect Detects Detects Detects 14.89% 16.67% KM KM SD Mean 1 0.1 4.1 0.773 0.5 0.882 0.672 0.838 2 0.745 2.175 1.211 1.065 0.505 1.128 0.475 Sample 1 vs Sample 2 Gehan Test H0: Mean of Sample 1 >= Mean of background

Gehan z Test Value Critical z (0.05) P-Value -2.553 -1.645 0.00534 08/08/18 Sample 2 Data: BG 05-2 Sample 1 Data: Site 1-2 Background Guidance Updates Conclusion with Alpha = 0.05 Reject H0, Conclude Sample 1 < Sample 2 P-Value < alpha (0.05) 11 Conclusion The primary statistical approach is the ranking test (WMW, Gehan, Tarone-Ware). Additional methods should be used as lines of evidence to support the determination of whether site concentrations are representative of background. 08/08/18 Background Guidance Updates 12

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