One Corps Serving the Army and the Nation. Improving the Quality of Environmental Samples

Transcription

1 Improving the Quality of Environmental Samples

2 Initial Concerns Re Validity of Discrete Sampling, thanks to Sebastian Tindall, Portland 2002 How valid are discrete samples if they are not representative, repeatable or legally defensible?

3 HETEROGENEITY OF EXPLOSIVES CONTAMINATION IN SOIL per Tom Jenkins, 1996

4 US EPA Preparation of Soil Sampling Protocols: Sampling Techniques and Strategies - July 1992 One of the key characteristics of the soil system is its Extreme Variability. - Cline (1944) Spatial variability of soil is not an academic question. --- our unwillingness or inability to identify it in no way decreases its magnitude or existence. - Wilding (1985)

5 Average is Correct Using standard EPA default assumptions for intake and exposure conditions and an excess cancer risk of one in million, the SSL for Pu 239 in soil is 2.9 pci/g. This SSL is based on ingestion of soil that is age adjusted over a period of 30 years. More importantly, this SSL is based on an average soil concentration over an entire residential lot of ½ acre (EPA 2002). Use of the SSL (or the previously referenced PRG) as a screening value for single point, maximum value samples is inappropriate. Correct use of these risk-based SSLs requires that soil samples be composited or averaged over an entire exposure area (1/2 acre in this evaluation). ATSDR, Public Health Assessment of the Lawrence Livermore National Laboratory (Main Site), Plutonium 239 in Sewage Sludge Used as a Soil or Soil Amendment in the Livermore Community. Agency for Toxic Substances and Disease Registry, Atlanta GA, Aug. 26,

6 But Who Wants the Average? You do! The overall goals of the sampling effort are to estimate an average soil lead concentration for risk assessment purposes Project managers should carefully choose the sampling points needed to estimate the average lead concentration in a cost-effective manner Superfund Lead-Contaminated Residential Sites Handbook, OSWER

7 More Averages Compositing is typically used for large sites under investigation to improve the precision of the estimated average contaminant concentrations. Contract Laboratory Program guidance for Field Samplers EPA 540-R , 2003 verification sampling will be conducted on each 1/4 acre by collecting a 40 increment composite. Krejci Dump Site ROD Ohio EPA and National Park Service,

8 Joliet Former Army Reserve Site- East Side

9 Joliet Former Army Reserve Site- Central View

10 Joliet Former Army Reserve Site

11 Joliet Former Army Reserve Site- Sample Area 1 Wooden Stakes at 30 Random Sub-Sample Locs

12 Joliet Former Army Reserve Site- Sample Area #3 Orange Flags at Individual Sub-Sample Locations

13 Joliet Former Army Reserve Site- Sample Area #4 Note Orange Flags at Individual Increment Locations

14 Joliet Former Army Reserve Site-Portions of Sample Area #8- Note Gravel Surface

15 Typical Sampling Area Adjacent to Production Bldg

16 Total Measurement Variance = Sum of Component Variances V Total = V Field Sampling (largest source) + V Field Sample Processing (medium source) + V Laboratory Sub-Sampling (medium source) + V Analytical (least source)

17 Sample Measure / Decision V Field Sampling can be huge Error Must be at right or appropriate location - mitigated by having main stakeholders in field at beginning of field sampling Insufficient mass to adequately characterize effects of compositional heterogeneity Not enough samples to account for distributional heterogeneity 1 sample location 7 sample locations 30 sample locations

18 Sample Measure / Decision Error V Field Sample Processing - how select what part of sample goes to the laboratory? V Laboratory Sub-Sampling - lab will take 1 or 2 grams from an 8 oz sample jar how do they get a representative 1 or 2 gm from the 8 oz jar?

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20 Laboratory SOP

21 V Analytical - much effort is typically spent here- even though it is the least important The biggest problem when doing duplicate, split or replicate samples is getting similar samples from the field - huge problem

22 Basic Sampling Theory Basic Sampling Theory to determine a good approximation of the average How much sample to collect How to collect the sample Basic phenomenon that causes all sampling error is heterogeneity

23 Basic Sampling Theory Two types of heterogeneity Compositional difference in composition of particles that make up the population (peas - basketballs - smashed cars) applies to the analyte of interest, say lead for instance

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25 Basic Sampling Theory Two types of heterogeneity Compositional difference in composition of particles that make up the population (peas - basketballs - smashed cars) applies to the analyte of interest, say lead for instance Distributional Non-random distribution of particles due to gravity, chemical attractions, human activity, air resistance, etc in time Particles may be different shape size contaminant concentration

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27 Basic Sampling Theory How is heterogeneity controlled??????? Compositional Heterogeneity leads to fundamental error which is controlled by taking enough sample mass

28 Basic Sampling Theory

29 Basic Sampling Theory How is heterogeneity controlled??????? Compositional Heterogeneity leads to fundamental error which is controlled by taking enough sample mass V (Field Sample Size) = (22.5 x d95 3 )/ (Sample Mass- gms) if use d95 = 2 mm equals #10 seive size Take enough sample mass to represent all particles, especially the larger ones, for the materials we work in a good minimum amount of sample mass is 30 gms Distributional Heterogeneity is controlled by taking an appropriate number of random increments, in most of our cases, 30 increments is sufficient

30 Current Environmental Sampling Procedures Take limited number of discrete samples to characterize an exposure area, samples are not representative of an exposure area because so few of them artificially increases variability, which reduces confidence, typically; ND, ND, 800, 1000, 25,000 generates outliers, which causes much stress (ignore them, resample, include????) results are no where near close to being normally distributed results are no where near close to being log-normally distributed samples are not reproducible splits and replicates do not agree sampling error is completely ignored underestimates the mean or average, typically by several orders of magnitude sampling results are not legally defensible

31 Proposed Sampling Procedure Proposed Sampling Procedure discussion only applies to surface soil sampling and sediment Over an exposure area, or some other area whose delineation makes sense, but generally never smaller than ¼ to ½ acre, Take multi-increments in a stratified random manor, number of multi-increments depends on heterogeneity Stratified random provides locations over entire area of interest Field prepare about 1000 gm of soil the is < 2 mm (#10 sieve) to send to the lab dry and sieve on a #10 sieve the entire multi-increment sample spread out on flat surface take about 30, 1-gm increments from the flat surface and put in sample jar, or two jars if doing a split send the jar(s) to the lab(s) Insist that the laboratory use adequate subsampling procedures, not just take 1 or 2 gms off the top of the jar

32 Proposed Sampling Procedure Will generate more Representative samples Less variable samples Legally defensible results Valid approximation of the average soil concentration, Cs, for risk assessment ONLY WAY WE SHOULD EVER PREPARE DUPLICATE OR SPLIT SAMPLES

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35 Conclusions 1 Multi-incremental (MI) sampling is a practical, cost-effective method of collecting representative, repeatable, and legally defensible environmental samples. 2 Improved field sample processing greatly improves the representativeness and homogeneity of that portion of the field sample that is shipped to the lab. 3 A wide range of acceptance of MI sampling has been experienced by five state regulatory bodies, with much acceptance by the OH EPA to complete refusal by IN. 4 Upon discussion of MI sampling at a RAB meeting, the public appears to easily understand the concept, and has reservations about conventional discrete sampling. 5 Issues need to be resolved regarding integration of MI sampling into large bodies of existing discrete data. These issues do not appear to be insurmountable.