Systematic Planning Process

1. Systematic Planning Process Topic 2

2. Topic 2 Objectives • DESCRIBE the process for defining the environmental problem statement • EXPLAIN the use of the systematic planning process (SPP) • DESCRIBE the importance of sampling design and the relationship to the heterogeneity of cleanup sites

3. Topic 2 Introduction • Systematic Planning Process (SPP) • Form Project Team • Define Environmental Problem • Identify Investigation Objectives • Implement • Quality assurance project plan used for implementation of the data collection activities Ensure data are of known and documented quality and appropriate for their intended use

4. SPP Steps • Identify Lead Organization • Project Organization and Responsibilities • Convene Scoping Sessions • Define Environmental Problem and Objectives • Define Project Schedule • Determine Type of Data Needed • Determine Quality of Data Needed • Determine Quantity of Data Needed • Determine Data Review Needed …

5. SPP Steps (Continued) • Define Sampling Design Rationale • Determine Sampling Requirements • Select Sampling SOPs with QC • Develop Analytical Requirements • Determine QA Assessments • Decide Data Usability Assessment Process • Prepare, Review and Submit QAPP for approval • Implement QAPP

6. QUIZ! • Why do systematic planning?

7. QUIZ! • Why do systematic planning? • Define what questions need to be answered • Revise questions as more information is gathered • Define roles and responsibilities of players • Define activities to answer the questions • Keep project focused and on target

8. Define Problem

9. Define Problem • Research site history and background • Identify secondary data sources and limitations • Identify decisions that need to be made • Identify questions that require an answer • Decide if formal DQO process is required • Identify data user’s needs • Develop if/then statements that link data results and possible actions

10. Questions to Answer • Who will use the data? • What will the data be used for? • What type of data are needed? • How “good” do the data need to be in order to support the decision? • How much data are needed?

11. Questions to Answer • Where, when and how should the data be collected/generated? • Who will collect and generate the data? • Who will determine the usability of the data? • How will the data be reported? • How will the data be archived?

12. Gather Information • Site Maps • Detailed map of current site with boundaries • Historical maps or plans • Map placing site in geographical context • Historical and current aerial photographs • Develop Conceptual Site Model (CSM) • CSM documented in QAPP

13. Conceptual Site Model (CSM) • Term used by many • UFP-QAPP Section 3.1.1 paragraph 2 • “Picture” of a site and its environment • Sources of contamination • Actual, potentially complete or incomplete exposure pathways • Current or reasonable proposed use of site and potential receptors • Assists team in planning, data interpretation and communication (from USACE EM 1110-1-1200 Conceptual Site Models for OE and HTRW Projects, 2/2003)

14. CSM - continued • Integration of all relevant information assembled for the purposes of investigating or remediating a site • Captures heterogeneity & physical reality • Distinguishes differentdecision-driven populations • A CSM is not merely a: • Computer model…or • Risk receptor model (fate and transport)…or • Geological evaluation … alone

15. Identify possible contaminants Create list of possible contaminants with rationale for inclusions Provide rationale for exclusions Specify release mechanisms Conceptual Site Model (CSM) Identify fate and transport mechanisms List potential receptors Problem Statement Estimate contaminant distributions Discuss decision drivers Write CSM Summary Narrative

16. Conceptual Site Model Inputs • Contaminant Releases: what, how, where, spatial distributions/patterns? • Contaminant movement: migration, transport mechanisms • Contaminant fate and degradation • Potential receptors: human, ecological • Potential exposure pathways • Exposure mitigation (cleanup, containment)

17. Building a Conceptual Site Model • Review transport of contaminant • How did it get there? • Where did it go? Did it bind to matrix components? • Could it have gone somewhere else? • Review fate • Will it change form or composition? • Harm to ecology or humans? • What is future land use? • Exposure pathways?

18. Building a CSM (Continued) • Review chemistry, biology, geology, statistics, or other science to evaluate need for data in making decision • Can it still be there? Will it be present? • Can we sample it? Can we analyze for it? • What is the risk to receptors?

19. Building a CSM (Continued) • Highlights Physical Features of Site • Man-made Structures / Historically Disturbed Areas / Accumulation Points • Actual Site Data or Professional Conjecture • Contaminants of Concern • Release Mechanisms • Incorporates known Societal Considerations • Future Land Use / Community Goals • Potential Exposure Pathways • Risk Management Scenarios

20. Data for Building CSM • Related information: • other nearby contaminated sites – regulatory agencies • state geological surveys • research by academic institutions • Professional judgment: • scientific knowledge • conjecture

21. How Might a CSM Appear?

22. Modeled CSM-High Density Direct-push MIP-PID sensing: high areal & vertical data density (existing wells shown) Slide adapted from Columbia Technologies, Inc., 2003 Jul 2000 BTEX plume

23. Problem Definition • Summarize the problem to be addressed • Summarize the environmental questions being asked/decisions to be made • Include observations from any site reconnaissance reports • Prepare a synopsis of existing data or information from prior site reports

24. Problem Definition • List possible classes of contaminants and the affected matrices • Record the rationale for inclusion of chemical and non-chemical analyses • Compile information concerning various environmental indicators • Write problem statements initially at a very general level (specifics to come later); get planning team concurrence

25. Problem Statement Format • General Format: • In order to[support decisions for site remediation/better understand the nature of the waste/establish a basis for materials management]data are required that define[the nature and extent of contamination/the constituents of concern/the source and characteristics of the materials].

26. Decision Statement General Format Determine whether [Principal Study Question #1]requires [Alternative Action A] or [Alternative Action B]. • Example: Determine whether the surface soil of the Smith property is radiologicallycontaminatedand requires further action or requires no action.

27. If…then… Statement • General Format If [Principal Study Question #1] is above or equal to the action level then proceed with[Alternative Action A] or If [Principal Study Question #1] is below the action level then proceed with[Alternative Action B] • Example: If the surface soil of the Smith property is below the level defined for radiologicalcontaminationthen no action is required.

28. “Outcome” vs “Decisions” • Desired project outcome (starting point) • Desired site restoration/reuse outcome • May have tiered options (Plan A, B,…) • Achieving an outcome requires making project decisions about contaminant nature & extent, exposure risk, cleanup potential and cost, etc. • How long this discussion takes depends on the complexity of perceived site conditions and participant interests

29. QUIZ! • Why define the problem?

30. QUIZ! • Why define the problem? • Ensure agreement by all parties on the data gathering that will resolve the problem to all parties satisfaction • Determine how much is known and how must must be determined • Understand the expectations of all parties as to the outcome and decisions for this phase of the project

31. Project Quality Objectives (PQOs) • Define the type, quantity, and quality of data needed to answer specific environmental questions and support proper environmental decisions • Developed using a systematic planning process • Qualitative and quantitative statements

32. PQOs Before Iteration • Obtain data to locate source(s) of contamination or show that a major source does not exist • Obtain data to understand the lateral and vertical extent of contamination in both the saturated overburden and the fractured bedrock aquifer within the limits of the site • Obtain data to characterize the fractured bedrock aquifer

33. PQOs After Iteration • Identify the highest concentration of VOCs in the overburden soil and groundwater • Determine the placement of additional permanent saturated overburden monitoring wells, if any, to further evaluate risk posed to human health • Gather soil analytical data, if warranted, to evaluate risk to human health

34. Summarize Data Needs • Focus on data needed to address the information gaps identified • List information gaps in tables • Gather specific data needs from scoping participants & data users’ perspectives (e.g., risk assessors, remedial action planners) • Summarize and collate the data needs • Update and record throughout planning

35. Data Needs Table

36. Project Tasks • Sampling tasks • Analysis tasks • Quality control tasks • Secondary data • Data management tasks • Documentation and records • Assessment/audit tasks • Data review tasks

37. Sampling Tasks Laboratory Subsample

38. Representative Sample • When sampling, what are you trying to represent with the data? • Representative of the decision to be made on: • site • area • drum • an individual sample container UFP-QAPP Manual 2.6.2.4

39. Sampling Design • Statistically based sampling design vs. professional judgment? • Sample locations & numbers • Grab or composite (multi-increment) samples • Sample matrices • Time frequency of sample collection • Sample collection procedures • Mixing and homogenization Complicated by contaminant variability

40. Within-Sample Populations Adapted from ITRC (2003 ); http://www.itrcweb.org/SMART-1.pdf

41. Measurement Performance Criteria • Determine metrics to be used to assess measurement performance, e.g.: • Precision: Relative percent difference • Bias: Percent recovery • Other Data Quality Indicators • Determine criteria appropriate to your project • Identify QC sample and/or activity to assess measurement performance

42. Sensitivity: Reference Limits • Summarize project action limits (AL) and the quantitation limit (QL) goals for each analyte in each matrix at each concentration level • Evaluate available methods and analytical performance against AL and QL goals

43. QUIZ! • Why PQO’s?

44. QUIZ! • Why PQO’s? • Specify the type and quantity of data for each decision • Ensure measurement performance criteria are applicable to the decision • Ensure measurement organization data meets the quality criteria for the decision • Ensure quality control samples are used as part of the decision making to reduce wasted dollars for unused data • Understand sampling and testing limitations in order to balance costs with decision needs

45. QA/QC Compendium • Part IIB of UFP-QAPP guidance • Decisions by IDQTF • Definitions of QA/QC activities • Minimum QA/QC activities • List of specific QA/QC activities • QA matrix • CERCLA data collection, analysis and use

46. Apply Compendium To… • All phases of CERCLA process • Preliminary assessment • Site investigation • Remedial investigation • Feasibility study • Removal • Post ROD Phase • Project management • Decision making

47. Decisions • Intermediate • screening data • Final • definitive data NOTE: CHANGE IN TERMS Screening does NOT mean field data

48. Project Team Decisions • Compendium based on CERCLA phases • Specify minimum QA/QC activities for CERCLA phase • QC samples selected based on MPC • Data review involves completeness check through data usability assessment

49. Site-Specific Guidelines • Types of decisions supported by data • Project quality objectives • Acceptance criteria for DQI • Sampling plan • includes location and QC samples • Types of contaminants

50. DQI MPC Analysis QC Criteria QC PQO DQI MPC Analysis QC Criteria QC Graphical Presentation Data Review Environmental Question