1. 1 of 52 The EPA 7-Step DQO Process Step 4 - Specify Boundaries (60 minutes) (15 minute Afternoon Break) Presenter: Sebastian Tindall DQO Training Course Day 2 Module 14

2. 2 of 52 Step Objective: To define the spatial and temporal boundaries that the data must represent to support the decision statement Step 4: Specify Boundaries Step 2: Identify Decisions Step 3: Identify Inputs Step 1: State the Problem Step 5: Define Decision Rules Step 6 : Specify Error Tolerances Step 7 : Optimize Sample Design

3. 3 of 52 Information INActions Information OUT From Previous Step To Next Step Define the spatial boundaries of the decision statement Step 4- Specify Boundaries Unit of Decision Making Define the temporal boundary of the problem Define the scale of decision making Identify any practical constraints on data collection Information Needed to Resolve Decision Statements Define the population of interest

4. 4 of 52 In Step 4, setting the boundaries of decision- making, provides by far the biggest single opportunity for managing uncertainty, using: A. Results from comprehensive Scoping B. Professional Judgement PJ is the single most important skill a project can bring to bear in the DQO Process Step 4

5. 5 of 52 Knowledge and judgement come into play in many ways in the design of probability-samples; in defining the kind and size of sampling units; in delineating homogeneous of heterogeneous areas; in classifying sites into strata in ways that will be contributory toward reduction of sampling error. Professional Judgement Deming, W.E., 1950, Some Theory of Sampling, Dover Publications, New York Judgment is indispensable in any survey

6. 6 of 52 Professional Judgement There is no limitation to the amount of judgment of knowledge that can be used. However, this kind of knowledge is not allowed to influence the final selection of the particular locations of samples that are to be in the sample. This final selection must be automatic, for it is only then that the bias of selection in eliminated, and the sampling tolerance will be measurable and controllable. Deming, W.E., 1950, Some Theory of Sampling, Dover Publications, New York

7. 7 of 52 How Many Samples do I Need? REMEMBER: HETEROGENEITY IS THE RULE!

8. 8 of 52 Background It is difficult to make a decision with data that have not been drawn from a well-defined population The term “population” refers to the total universe of objects to be studied, from which an estimate will be made. Example: The total number of objects (samples of soil or sludge or sediment or air, etc.), that are contained within the spatial unit to be studied.

9. 9 of 52 Background It is difficult to make a decision with data that have not been drawn from a well-defined population In order to be well-defined and representative, a population also needs a characteristic to represent it. Concentration of a chemical in media (soil, water, air, etc.) Activity of a radionuclide in media Permeability of a soil Etc.

10. 10 of 52 n Spatial Boundaries : –Define the physical area/volume to which the decision will apply and from where the samples should be taken n Temporal Boundaries − Describe the timeframe that the data will represent and when the samples should be taken n Practical Constraints Background

11. 11 of 52 Boundaries will be used to ensure that: n The data are representative of the population n The data collection design incorporates: –The areas or volumes that should be sampled –The time periods when data should be collected Background A boundary unit containing a large area/volume may actually contain two or more smaller boundary units (sub-populations) each of which have some relatively homogenous characteristic. Sampling within the larger unit will not likely yield data which is representative of these sub-populations, leading to decision errors.

12. 12 of 52 Boundaries will be used to ensure that: n The data are representative of the population n The data collection design incorporates: –The areas or volumes that should be sampled –The time periods when data should be collected Background

13. 13 of 52 10 x 10 Field Population = All 100 Population Units

14. 14 of 52 10 x 10 Field Population = All 100 Population Units Action Level = 50 ppm 100 80 65 70 6560 50 29 28 40 49 25 30 49 30 32 35 45 47 49 46 18 32 35 30 42 40 42 44 49 48 35 36 32 38 36 30 49 34 35 40 27 25 38 33 35 40 49 45 40 30 28 39 27 32 30 40 49 48 22 27 26 23 10 35 38 20 40 10 26 2 15 10 25 20 4 25 1 10 20 35 10 25 20 22 27 5 40 20 35 24 25 15 25 2826

15. 15 of 52 Risk Pathway

16. 16 of 52 Scale of the Decision is Often Based on Risk Scenario n Decision unit is based on risk scenario n Decision makers create/approve risk scenario n Risk scenario defines the exposure to the receptor(s) – pathway from receptor to contaminant – duration of exposure – persons size and weight – amount absorbed or inhaled or drunk – etc

17. 17 of 52 EPA Risk Assessment Guidance for Superfund (RAGS), Volume 1, page 6-41; Human Health Evaluation Manual, Dec 1989; EPA/540/1-89/002 BWxAT D FxABSxEFxE CSxCFxSAxA daykgmgseAbsorbed Do  )/( Example Scenario: Residential Exposure: Dermal Contact with Chemicals in Soil

18. 18 of 52 EPA Risk Assessment Guidance for Superfund (RAGS), Volume 1, page 6-41; Human Health Evaluation Manual, Dec 1989; EPA/540/1-89/002 CS = Chemical Concentration in Soil (mg/kg) CF = Conversion Factor (10 -6 kg/mg) SA = Skin Surface Area Available for Contact (cm 2 /event) AF = Soil to Skin Adherence Factor (mg/cm 2 ) ABS = Absorption Factor (unitless) EF = Exposure Frequency (events/year) ED = Exposure Duration (years) BW = Body Weight (kg) AT = Averaging Time (period over which exposure is average -- days) Example Scenario Residential Exposure: Dermal Contact with Chemicals in Soil

19. 19 of 52 Action Limit = 50.0 ppm Average = 33.8 ppm

20. 20 of 52 60 ug/kg Average <1 ug/kg Action level = 10 ug/kg

21. 21 of 52 Practical Constraint: Any hindrance or obstacle that may interfere with the full implementation of the data collection design Background

22. 22 of 52 Information INActions Information OUT From Previous Step To Next Step Define the spatial boundaries of the decision statement Unit of Decision Making Define the temporal boundary of the problem Define the scale of decision making Identify any practical constraints on data collection Information Needed to Resolve Decision Statements Define the population of interest Examples: The universe of: Surface soil samples (3”x 3” x6”) within the area of interest Subsurface soil samples (3” x 3” x 6”) within the area of interest to a depth of 15 feet Surface water samples (1 liter) within perimeter boundaries of the pond Sediment samples (1 kg) from the top 6 inches of lake bottom Direct surface activity measurement areas (100 cm 2 ) on the building wall surfaces Step 4- Specify Boundaries

23. 23 of 52 Example Types of Populations n This pile of waste n Top two inches of soil n Blue drums n The part of the lagoon within three feet of the pipe discharge n Only the yellow granular material

24. 24 of 52 Information INActions Information OUT From Previous Step To Next Step Define the spatial boundaries of the decision statement Unit of Decision Making Define the temporal boundary of the problem Define the scale of decision making Identify any practical constraints on data collection Information Needed to Resolve Decision Statements Define the population of interest Define the geographic area/volume to which the decision statement applies. Note, the population described above resides within this area/volume. The geographic area is a region distinctively marked by some physical feature, such as: Area (surface soil to a depth of 6 inches in the Smith’s backyard) Volume (soil to a depth of 20 feet within the area of the waste pit) Length (the pipeline) Some identifiable boundary (the natural habitat range of a particular animal/plant species) Step 4- Specify Boundaries

25. 25 of 52 Information INActions Information OUT From Previous Step To Next Step Define the spatial boundaries of the decision statement Unit of Decision Making Define the temporal boundary of the problem Define the scale of decision making Identify any practical constraints on data collection Information Needed to Resolve Decision Statements Define the population of interest Divide the population into strata (statistical) that have relatively homogeneous characteristics Dividing the population into strata is desirable for the purpose of: Addressing sub-populations Reducing variability Reducing the complexity of the problem (breaking it into more manageable pieces) Step 4- Specify Boundaries

26. 26 of 52 What is the One Phenomenon that Causes ALL Sampling Error? HETEROGENEITY

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29. 29 of 52 1 1 1 1 122 2 2 2 2 2 2 11 1 51 52 51 52 51 52 51 52 The standard deviation of the 16 blue cells = 0.516. The standard deviation of the 16 pink cells = 0.516. The standard deviation of the 32 cells combined is 25.41! Action Level = 25 units

30. 30 of 52 How Many Samples do I Need? REMEMBER: HETEROGENEITY IS THE RULE!

31. 31 of 52 Information INActions Information OUT From Previous Step To Next Step Define the spatial boundaries of the decision statement Unit of Decision Making Define the temporal boundary of the problem Define the scale of decision making Identify any practical constraints on data collection Information Needed to Resolve Decision Statements Define the population of interest Determine the timeframe to which the decision applies. Is it always possible to collect data over the full time period to which the decision will apply? No One performs a risk assessment that covers the time a normal resident or worker would be exposed in their lifetime. This is a ‘sampling’ of the timeframe to which the decision applies. e.g., 8 years; 30 years; 70 years; Step 4- Specify Boundaries

32. 32 of 52 Information INActions Information OUT From Previous Step To Next Step Define the spatial boundaries of the decision statement Unit of Decision Making Define the temporal boundary of the problem Define the scale of decision making Identify any practical constraints on data collection Information Needed to Resolve Decision Statements Define the population of interest Example: “The airborne PM-10 concentration over a period of a 24 hours.” Step 4- Specify Boundaries

33. 33 of 52 Information INActions Information OUT From Previous Step To Next Step Define the spatial boundaries of the decision statement Unit of Decision Making Define the temporal boundary of the problem Define the scale of decision making Identify any practical constraints on data collection Information Needed to Resolve Decision Statements Define the population of interest Determine When to Collect Data Determine when conditions will be most favorable for collecting data Select the most appropriate time period to collect data that reflect those conditions Step 4- Specify Boundaries

34. 34 of 52 Information INActions Information OUT From Previous Step To Next Step Define the spatial boundaries of the decision statement Unit of Decision Making Define the temporal boundary of the problem Define the scale of decision making Identify any practical constraints on data collection Information Needed to Resolve Decision Statements Define the population of interest Why: Conditions (factors) may vary over the course of data collection. May affect: - Success of collecting the data - Interpretation of the data Step 4- Specify Boundaries

35. 35 of 52 Information INActions Information OUT From Previous Step To Next Step Define the spatial boundaries of the decision statement Unit of Decision Making Define the temporal boundary of the problem Define the scale of decision making Identify any practical constraints on data collection Information Needed to Resolve Decision Statements Define the population of interest Factors may include: - Weather- Temperature - Humidity- Amount of sunlight - Wind/direction- Rainfall - Etc. Step 4- Specify Boundaries

36. 36 of 52 Information INActions Information OUT From Previous Step To Next Step Define the spatial boundaries of the decision statement Unit of Decision Making Define the temporal boundary of the problem Define the scale of decision making Identify any practical constraints on data collection Information Needed to Resolve Decision Statements Define the population of interest Example: A study to measure ambient airborne particulate matter may give misleading information if the sampling is conducted in the wetter winter months rather than the drier summer months. Step 4- Specify Boundaries

37. 37 of 52 Information INActions Information OUT From Previous Step To Next Step Define the spatial boundaries of the decision statement Unit of Decision Making Define the temporal boundary of the problem Define the scale of decision making Identify any practical constraints on data collection Information Needed to Resolve Decision Statements Define the population of interest Define the basis for selecting the decision unit. Risk Permits/regulatory conditions Technological considerations Financial scale Other Step 4- Specify Boundaries

38. 38 of 52 Information INActions Information OUT From Previous Step To Next Step Define the spatial boundaries of the decision statement Unit of Decision Making Define the temporal boundary of the problem Define the scale of decision making Identify any practical constraints on data collection Information Needed to Resolve Decision Statements Define the population of interest Define the smallest, most appropriate subsets of the population (sub- populations) for which decisions will be made based on the spatial or temporal boundaries. Step 4- Specify Boundaries

39. 39 of 52 Information INActions Information OUT From Previous Step To Next Step Define the spatial boundaries of the decision statement Unit of Decision Making Define the temporal boundary of the problem Define the scale of decision making Identify any practical constraints on data collection Information Needed to Resolve Decision Statements Define the population of interest Exposure Unit: An area/volume which has a size that corresponds to the area/volume where the receptors derive the majority of their exposure. (EXAMPLE: A play area or an average residential lot size.) Remediation Unit: An area/volume which has been determined to be the most cost-effective area/volume for remediation. (EXAMPLE: The volume of a dump truck or a railroad car, the surface area of each building wall.) Step 4- Specify Boundaries

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41. 41 of 52 How Many Samples do I Need? REMEMBER: HETEROGENEITY IS THE RULE!

42. 42 of 52 Information INActions Information OUT From Previous Step To Next Step Define the spatial boundaries of the decision statement Unit of Decision Making Define the temporal boundary of the problem Define the scale of decision making Identify any practical constraints on data collection Information Needed to Resolve Decision Statements Define the population of interest Identify any constraints or obstacles that could potentially interfere with the full implementation of the data collection design, such as: Seasonal or meteorological conditions when sampling is not possible Inability to gain site access or informed consent Unavailability of personnel, time, or equipment Step 4- Specify Boundaries

43. 43 of 52 Information INActions Information OUT From Previous Step To Next Step Define the spatial boundaries of the decision statement Unit of Decision Making Define the temporal boundary of the problem Define the scale of decision making Identify any practical constraints on data collection Information Needed to Resolve Decision Statements Define the population of interest Example: Population: Total number of soil samples within the spatial boundary that could potentially be collected and measured for lead content Spatial Boundary: Top 6 inches of soil within the backyard of the Smith’s property Temporal Boundary: 8 years (average length of residence) Unit of Decision: Top 6 inches of soil within the backyard of the Smith’s property over the next 8 years Step 4- Specify Boundaries

44. Areas to be Investigated CS Plan View Former Pad Location Runoff Zone 050100150 ft 01530 46 m Buffer Zone 44 of 52

45. Spatial and Temporal Boundaries CS 45 of 52

46. Scale of Decision Making CS 46 of 52

47. 47 of 52 Additional Population Considerations n Sample support - “physical size, shape and orientation of the material that is extracted from the sampling unit that is actually available to be measured or observed, and therefore, to represent the sampling unit.” n Assure enough sample for analyses n Specify how the sample support will be processed and sub-sampled for analysis. EPA Guidance on Choosing a Sampling Design for Environmental Data Collection, EPA QA/G-5S, December 2002, EPA/240/R-02/005

48. 48 of 52 Sub-Sampling n The DQO must define what represents the population in terms of laboratory sample size: n Typical laboratory sample sizes that are digested or extracted: metals - 1g, volatiles - 5g, semi-volatiles - 30 g n The 1g or 30g sample analyzed by the lab is supposed to represent a larger area/mass (e.g., acre). Does it?

49. 49 of 52 Summary n Population is the TOTAL universe (N) n We cannot measure the entire population (perform a census) n Population must be sampled to provide an estimate n Identification of strata decreases variance, and may allow a smaller sample size (n) n Stratification presents huge opportunities to manage uncertainty

50. 50 of 52 Step 4, setting the boundaries of decision- making, provides by far the biggest single opportunity for managing uncertainty, using: A. Results from comprehensive Scoping B. Professional Judgement PJ is the single most important skill a project can bring to bear in the DQO Process Summary

51. 51 of 52 Information INActions Information OUT From Previous Step To Next Step Define the spatial boundaries of the decision statement Unit of Decision Making Define the temporal boundary of the problem Define the scale of decision making Identify any practical constraints on data collection Information Needed to Resolve Decision Statements Define the population of interest Step 4- Specify Boundaries

52. 52 of 52 End of Module 14 Thank You Questions? We will now take a 15-minute Afternoon Break. Please be back in 15 minutes