I MPROVING D ATA R ELIABILITY AND M INIMIZING D ELAYS WITH I NCREMENTAL S OIL S AMPLING Roger Brewer, PhD Hawai’i Dept of Health AGC-CEC S EPTEMBER

Sampling Theory is Independent of the Media Surface Water Food People Pharmaceuticals Dirt 2

What we’ve been doing for 30+ years; Why it’s unreliable and inefficient and why we should care; Why a switch to “incremental” sampling is necessary and how it’s done. Outline If I had one hour to solve the problems of the world I would spend 59 minutes on explaining the problem and 1 minute on explaining the answer. Albert Einstein 3

What’s Wrong With My Discrete Soil Samples? Need for multiple remobilizations and “step-out” investigations Failed confirmation samples and over excavations Accidental Import or Export of Contaminated Soil 4

Example Excavation Plan Based on Discrete Data Initial Sample Results X:Not detected X :Detected but below 1ppm screening level X :Detected above 1ppm screening level 25 discrete soil samples collected; # Samples based in part on budget; Soil excavation plan prepared. Apparent Isolated Hot Spot Apparent Isolated Cold Spot 5

Confirmation Sample Results :Not detected :Detected but below 1ppm screening level :Detected above 1ppm screening level Failed Excavation Confirmation Samples?? Multiple failed confirmation samples; Additional excavation and resampling required; No clear end point; Significant added time and cost to project. 6

Every wonder... ? X ? ? ? “What if I moved my sample point over a few feet? “What if the lab tested a different aliquot of soil?” Metals: grams VOCs: 5 grams PCBs, Pesticides, Dioxins, TPH, PAHs: grams 7

So did we… Discrete Soil Sample Variability Field Study Study Site A (arsenic in wastewater) Study Site B (lead in incinerator ash) Study Site C (PCBs transformer oil) Small-Scale Variability of Discrete Soil Sample Data (HDOH 2015) 24-Point Discrete Sample Grid at Each Site

Discrete Sample Variability Inter-Sample Variability Discrete sample ( g) collected from each corner and center of grid point; MIS processed at lab and tested for target metal. Intra-Sample Variability One sample tested ten times prior to MIS processing and testing (metals 1g, PCBs 10g). Metals PCBs Separate sample collected for PCBs

Study Site C (PCBs) Inter-Sample Variability 4.9 mg/kg 7.7 mg/kg 6.0 mg/kg 91 mg/kg 14 mg/kg 3 feet Average Variability = 11X Maximum Variability = 490X Variability Between Co-Located Samples (Samples IS Processed at Lab) Grid Pt #24 10

2,700 mg/kg 3,100 mg/kg 3,200 mg/kg 5,700 mg/kg 810 mg/kg 910 mg/kg 1,000 mg/kg 1,400 mg/kg 2,600 mg/kg 2,700 mg/kg Variability Within a Single Sample (Ten Subsamples Tested) Study Site C (PCBs) Intra-Sample Variability Grid Pt #24 Average Variability = 17X Maximum Variability = 116X Average= 2,400 mg/kg 11

Study Site C (PCBs) Inter-Sample Variability 4.9 mg/kg 7.7 mg/kg 6.0 mg/kg 91 mg/kg 14 mg/kg 3 feet Average Variability = 11X Maximum Variability = 490X 2,400! mg/kg Random Hot Spots Grid Pt #24 12

What’s Going On? Suspect PCB-Infused Tar Balls (Nuggets) Suspect PCB-Rich Nugget in Soil Easily Broken Photomicrograph (*different nugget) Suspect PCB-Infused Nuggets: Distinctly darker outer surface; Scattered but visible throughout soil sample; Rounded shape <1mm to 2mm in size; Soft, crumbles when pressed; Thin, outer rim with coating of fine particles; Darker particle mixture inside; Nuggets likely cause of high variability in co-located discrete soil samples. 2mm 1mm 1cm 13

How to Make PCB Nuggets in Soil 1cm Thin Outer Rim Fresh Olive Oil Droplet Droplet Remnant After Sinking Into Flour Olive Oil-Infused Nuggets in Flour Olive Oil Droplets Formed on Dry Flour 14

No wonder... Discrete samples are too SMALL Mass Tested by Lab Metals: grams VOCs: 5 grams PCBs, Pesticides, Dioxins, TPH, PAHs: grams 15

What Soil Contamination Would Look Like if You Could Actually See It Jackson Pollock splatter painting Spilled milk following low areas Can’t be reliably characterized using discrete samples Discrete Samples (actual size) 16

Why Confirmation Samples (or Pass) Small-scale, random variability of contaminant concentrations over a few inches or feet; Concentration reported for any given discrete sample is largely random; Statistics can’t fix bad data. Concentrations highly variable around any given grid point Problem can’t be fixed by collected more discrete samples 17

How Did This Happen? “When there is little distance between points it is expected that there will be little variability between points.” USEPA 1989: Methods for Evaluating the Attainment of Cleanup Standards “The implicit assumption (that…) contamination is… likely to be (uniformly) present anywhere within the sampling area is reasonable.” USEPA 1985: Verification of PCB Spill Cleanup Origin of Problem: Early sampling guidance based on experience with industrial waste streams (very consistent); Use of discrete sampling methods for soil never tested in field; Lack of training in Sampling Theory; Field quality of environmental data is not market-driven. 18

Solution: Sampling Theory -Decision Units & Incremental Sampling- Sometimes the questions are complicated and the answers are easy. Dr Seuss 19

DU = Volume of soil you would send to lab as a single sample if possible; Used in the mining and agriculture industries for decades; Ensures high-quality, risk-based, reliable and reproducible data. DU Basics: Area/volume of soil about which a decision will be made; Designated based on suspect spill areas, risk-based exposure areas, boundaries of contamination, remedial action design, etc.; Objective is to determine mean concentration for DU volume of soil (basis of risk assessment and risk- based screening levels); Sample must capture and represent smaller-scale variability within DU. Exposure AreasSource Areas Decision Units (DUs) and Incremental Sampling (IS) Example Decision Units 20

Collection of Incremental Soil Samples X Increment collection locations Single sample prepared by collecting and combining small “increments” of soil (25-50g) within DU (target 1-2+kg bulk sample); Similar in concept to “composite” samples but important differences; Samples carefully processed and subsampled at laboratory to retain field representativeness; Replicate samples collected from different locations to evaluate precision; Objective is to identify “hot areas” not “hot spots”; Acute toxicity from tiny spots (e.g., 10 grams) not documented, impossible to verify absence (billions of DUs) and no acute soil screening levels; “Maximum” concentration always either 0 ppm or 1,000,000 ppm at some scale, not important. Targeted DU Area 21

Sampling Theory – Detailed Details… Causes of Erroneous Data: Fundamental Error; Grouping & Segregation Error; Increment Delimitation Error; Increment Extraction Error; Periodic Error; Preparation Error; Analytical Error; etc. 22

Sampling Theory Training Envirostat, Inc.: Chuck Ramsey ( Four-day, detailed introduction to sampling theory and Multi-Increment Sample ® (MIS) site investigations. ITRC: Incremental Sampling Methodology (ISM) Introduction to basics of sampling theory and incremental sampling (guidance + semi-annual webinars) Hawai’i DOH Technical Guidance Manual Implementation of DU-MIS investigations in the field (1 st edition 2009, updates in preparation) 23

Sampling Theory Explained With Salad Wrong Questions: What is the maximum concentration of tomato in this salad? What is the concentration of tomato at point “X”? 24 Primary concern exposure to toxic tomatoes

Step 1: Define Objectives and Designate Decision Units Right Question: What is the mean concentration of tomato in this salad? Primary concern long-term, repeated exposure to tomatoes; Salad to be eaten over a lifetime; Entire salad represents the “Exposure Area” Decision Unit. 25

Step 2: Sampling Theory - Collect a BIG Sample ( in order to capture and represent random, small-scale variability) Soil: Typical Minimum 1-2+kg 26

How to Collect a Representative Sample Collect evenly spaced increments collection from targeted DU Area; Sample must capture representative # of “hot spots” and “cold spots”; Minimum 30 (low heterogeneity) to 75+ (high heterogeneity) points. Increments Incremental Sample 27

Laboratory Processing and Subsampling -Repeat Method Used in Field- Bulk soil IS sample dried and sieved; Subsampling process repeated to collect aliquot for testing (minimum 30 increments); Preserves field quality of original sample; Minimum 10g mass tested (normal metals = 1g). Aliquot Tested by Lab 28

Repeat Three Times and Compare to Test Precision (“Replicates”) Analysis 29

Increase Resolution of Data as Needed Anticipate failing screening levels; Use smaller DUs to isolate and test suspected “hot areas;” Optimizes “remediation” and quickly clears “clean” areas. *Suspected “hot” spill area and “clean” perimeters tested separately DU-1 DU-2 DU-3 Perimeter DUs Suspect Spill Area 30

Compare to Discrete Samples… Discrete Sample Too small, too few and don’t address the question asked. 31

More Food for Thought… What we thought in the 1980s:What we know in the 2010s: Contaminated Soil is like a Bowl of Cheerios Contaminant concentrations can vary significantly between discrete-size masses of soil; Collection and combination of a large number of “increments” is required to obtain a representative sample. Contaminated Soil is like a Bowl of Froot Loops Contaminant concentrations identical regardless of sample location and mass of soil tested sample; Testing of any given, small mass will be representative of area as a whole.

Objective: Determine if mean arsenic concentration exceeds soil action level within defined spill or exposure area DUs. Soil action levels based on chronic, long-term random exposure. DU-1DU-2 DU-3DU-4 Perimeter DUs (8 total) Primary DUs (4 total) DU-5DU-6 DU-7 DU-8 DU-9 DU-10 DU-11 DU Decision Unit & Increment Sampling Approach

Decision Unit (DU) & Multi-Increment Sample MIS Approach 34 MI samples collected from each DU; Minimum 30 to 75+ “increments” per DU; Triplicate MI samples collected from two DUS (10%) (e.g., suspect most contaminated, highest risk, etc.); Average minutes per sample; Total 16 samples sent for processing and testing XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX X: Increments collected from systematic, random grid Replicate Data Sample A: 140 mg/kg Sample B: 179 mg/kg Sample C: 135 mg/kg RSD = 16% (good!) 95% UCL: 192 mg/kg

Example DU-IS Results Confirmation Sample Results :Not detected :Detected but <screening level :Detected and >screening level Additional testing required in one area; Confirm depth of contamination prior to excavation (subsurface IS). Additional Step Out Testing Required 35

Details, Details (see HDOH TGM) Field Tools (vary with soil type & depth) Good Not good Increment Shape Core wedgesPlugs (+/- COH 4 ) Subsample cores 36

Ecological Decision Units (e.g., skeet range and wetland) Lagoon Upland Intertidal Nearshore Mix of Source Area and Eco- Based DUs For example only 37

Excavation Decision Units Floor and Sides Tested as Separate DUs x xxxxxxx x xxxxxxx x xxxxxxx x xxxxxxx DU-3 DU-1 DU-2 x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x Sidewall MI Confirmation Sample Collected from Borings Prior to Excavation 38

DU volumes based on planned reuse; Examples: Residential: cyds (5,000 ft 2 to ½ acre x 6” depth); Commercial: cyds (½ to acre x 6” depth). Stockpile Decision Units DU volumes based on planned reuse; 39

Subsurface IS Samples From Trenches & Pits Subsurface DU Layer (6”- 1 ft) Subsurface DU Layer (1 ft – 3 ft) Floor too mixed to sample Surface DU (0-6”) l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l Soil Increment (elongated for better coverage) 40

Subsurface IS Samples From Borings -Targeted DU Layers- -0.5m 0.0m -1m -2m -3m DU-1 DU-2 DU-3 DU-4 Ideal 30+ Increments per DU Layer Core Increments DU Layers designated based on spill/release characteristics; Each core through layer represents an increments; Subsampled and combined to prepare a bulk MIS sample for DU layer; Smaller number or cores or even single borehole (‘Borehole DU’) to determine presence or absence may be useful but use with caution. 41

Single Boring “DUs” Estimate lateral or vertical extent of contamination; Boring divided into targeted intervals (not discrete depths); Entire core interval sent to lab for processing; Presence or absence only; Risk of false negatives. 42

Incremental Soil Samples for VOCs Methanol pre-added to jar by lab based on planned mass of soil (mass methanol = mass soil); Soil increments (or increment subsamples) placed in methanol in field (or individually frozen); TerraCore-type sampler commonly used (cheap); Mass VOC Extracted in Methanol Mass of Soil Placed in Jar VOC Concentration = 43

s Guidance: Single Discrete Sample Represents a “Sampling Area” Use of Incremental Sampling for PCBs under TSCA “The implicit assumption (that…) contamination is… likely to be (uniformly) present anywhere within the sampling area is reasonable.” USEPA 1985: Verification of PCB Spill Cleanup

Intent of “Sampling Areas” similar to current concept of Decision Units Better understanding of DU size and location based on suspect spill areas and health risk; Incremental samples more representative of targeted DU areas; Intentional combination of anticipated PCB spill areas with anticipated clean areas as a single DU for testing may violate “anti-dilution” clause in TSCA (40 CFR761.1(b)(5)): “"No person may avoid any provision specifying a PCB concentration by diluting the PCBs, unless otherwise provided”; Requires careful designation of Spill Area DUs in coordination with overseeing regulatory agency. 45 Sampling Areas and Discrete Samples vs Decision Units and Incremental Samples

46 Limited Discrete Sample Compositing Allowed Under TSCA Multiple discrete samples (max 10) composited and tested as a single sample; Potential dilution of higher concentrations in individual sampling areas; Laboratory results divided by number of discrete samples (i.e., “Sampling Areas”) included in composite for comparison to cleanup level; Ensure that no single sampling area exceeds target cleanup level.

Compositing of Incremental Samples Across DUs NOT Allowed 47 X X X X XXXXXXXXXX XXXXXXXXX XXXXXXXXX XXXXXXXXX XXXXXXXXX Designate DU sizes adequate for decision making up front; Representative IS sample collected and independently tested for each DU; Include adequate number of increments (e.g., 30-75) with bulk mass 1-2kg; Each sample independently processed, subsampled and tested at lab.

Discrete Sampling Change Can Be Disrupting… Incremental Sampling The World is Round 48 Technical justification for need to switch from discrete to incremental sampling under TSCA largely agreed on. Currently preparing a formal agreement on a regulatory pathway forward using “risk-based” option under TSCA.

Discrete soil sample data are unreliable and inefficient for use in environmental investigations; Grids of discrete samples might be useful for large-scale site screening (Caution! Easy to be fooled by heterogenetity); Designate Decision Units based on the investigation objective; Collect incremental samples to ensure technically defensible and reproducible data for decision making; More initial preparation time (DUs) & slightly more field time but lower lab costs and more cost effective by project end; Reduces uncertainty and potential for unanticipated delays and future environmental liability; Training and discussions to overcome engrained regulatory hurdles required (e.g., TSCA); Experience in the field is the best teacher. Summary 49

Perhaps the sentiments contained in the following pages, are not yet sufficiently fashionable to procure them general Favor; a long habit of not thinking a Thing wrong gives it a superficial appearance of being right, and raises at first a formidable outcry in defense of Custom. But the Tumult soon subsides. Time makes more Converts than Reason. Thomas Paine, 1776 (Common Sense, on succession and independence of the new United States from Great Britain) Questions? 50