Investigation - Derived Waste Program

WSRC-TR-98-00190

by C. Beardsley Westinghouse Savannah River Company Savannah River Site Aiken, South Carolina 29808

R. Anderson

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Investigation-Derived Waste Program

Presented at the Pollution Prevention Conference

Seattle, Washington

June 3,1998

Presented by Clarence C. Beardsley, Project Manager Bechtel Savannah River Incorporated Environmental Restoration Division

Environmental Restoration ProgramdWaste Treatment

Authored by Rachel A. Anderson, Project Lead (rachel.anderson@srs.gov)

Westinghouse Savannah River Company Savannah River Technology Center

Environmental Science and Technology Statistical Consulting Section

Table of Contents

1. Introduction

2. Background

3. History

4. Description

5. Algorithm

6. Containerization Files

7. Special Reports

8. Key Benefits

9. Conclusion

Investigation-Derived Waste Program

1. Introduction

The Investigation-Derived Waste Program (IDWP) is a software application that was developed to identify the groundwater monitoring wells at the Savannah River Site (SRS) that require containerization and treatment for purge water generated during sampling. Created by the Statistical Consulting Section (SCS) of the Savannah River Technology Center, IDWP is a SAS@ application that retrieves the necessary data from the Site’s groundwater database for wells selected by the user. The program then applies an algorithm, derived by the Environmental Protection Department (EPD) from the Investigation-Derived Waste (IDW) Management Plan, to the analytical results to determine whether containerization is required for the specified wells. IDWP produces output files that designate the containerization status of each of the selected wells, provide statistics to support the treatment facilities’ permits, and assist with controlling and scheduling the handling of the managed purge water. The Aqueous IDW Administrator in the Environmental Restoration Division (ERD) uses IDWP in conjunction with knowledge of new wells to produce quarterly reports that specify which groundwater monitoring wells require containerization for purge water. Special reports supply other groundwater information of interest to ERD, such as analytical concentration plots and groundwater data gathering. IDWP is the product of inter-division collaboration, and project scope continually expands to accommodate changes to the IDW Management Plan and to satisfy additional needs as they are identified.

2. Background

Purge water is stagnant water purged from a well system in the process of sampling a monitoring well to ensure that samples collected will be representative of the aquifer. It is an aqueous formof IDW, investigation-derived waste generated during investigations performed under the regulatory authority of RCRA (the Resource Conservation & Recovery Act) and CERCLA (the Comprehensive Environmental Response, Compensation, & Liability Act). The management of purge water from monitoripg wells having certain analytes at specified concentrations is critical for the proper disposal of regulated waste. The Investigation-Derived Waste Management Plan defines the IDW management strategy, which is to m i n i the quantity of IDW generated while cost-effectively managing the IDW that must be generated. The primary driver for IDWP is waste minimization, since at least two volumes of water are purged from each well before samples are drawn. Of approximately 1700 monitoring wells currently sampled at SRS, about 400 of them require containerization for purge water. Around 56,000 gallons of purge water are containerized per year out of the 200,000 gallons generated with the current sampling schedule.

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3. History

This project was initiated in May 1996, when SCS was tasked with combining some 13 SAS* programs developed and used by a single individual in the Environmental Protection Department into an application ERD to use. Mainframe dependencies had to be changed to those for a DEC Alpha running OpenVMS; the programs had to be altered to pull and use data from a relational database on a remote machine instead of existing flat files; some data validation had to be added; and a user interface had to be developed. A test version of JDWP was released at the end of Ey1996. Following ERD’s review, revisions were made, and the test version underwent a software quality assurance study. Further enhancements were incorporated into IDWP version 1, released at the end of Ey1997. The need for Web access is under consideration for Version 2, scheduled for release in September of 1998.

4. Description

SCS developed the Investigation-Derived Waste Program in SAS* version 6.12 on a DEC Alpha machine. The application prompts the user to select a well set (all, area, series or individual wells) and then retrieves the appropriate data from the Site standard groundwater database on a remote computer using SQLNet*. The Geochemical Information Management System (GIMS) is an Oracle* database that resides on an RS6000 machine running UNIX. GIMS contains over 2.5 million analytic sampling records from SRS’s 2000+ groundwater monitoring wells, in addition to QA, field, well, and other data, in some 125 tables. IDWP applies EPD’s containerization algorithm that examines the concentration of certain analytes to determine whether purge water from any given well requires containerization and creates output files of the results.

IDWP presents a us&-friendly interface and produces results in a timely, consistent manner. IDW allows any user with appropriate privileges to generate the purge water containerization list from any networked computer with X-windowing capabilities, such as a workstation or a PC or Macintosh with an emulator like Hummingbird’s Exceed*. Moreover, multiple users can access IDWP simultaneously. The SAS@ programmer designated by the SCS manager as IDWP’s software configuration manager can edit the computer programs to encompass changes to the IDW procedure, and the security on these files is set such that no other person can edit them. So, IDW is not dependent on any particular person in order to function but has only one authorized source for changes. These and other such issues are covered in the Software Quality Assurance Plan for the application. Along with IDWP, SCS also supplies software maintenance and support, software upgrades as needed, installation of emulator and FTP packages, user documentation, software QA support, showcasing, and training.

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5. Algorithm

The containerization algorithm was developed by ERD from the IDW Management Plan to process the data to determine whether containerization is required for each well. To represent the amount of contamination in a well, a scenario is defined for each analyte based on its concentration in relation to a health-based level (HBL) specified in Appendix A of the IDW Management Plan. A scenario value of two or greater for any analyte in the well indicates that the purge water from that well requires containerization and treatment.

Data for all analytes for each well in the user’s selected well set are pulled from GIMS, and some basic data qualification (e.g., unit conversion) is performed. If a well has been abandoned, it is deleted from the analysis. For each analyte at each well, the four most recent quarters of data are retained; if there are fewer than two quarters worth of results, the analyte is excluded from the analysis. Comparison to laboratory blanks is performed, and all results below detection are set to negative values. The highest result for each quarter is retained. Then the 2 - 4 quarters of results for each analyte in each well are placed in numerical order, regardless of time order. A scenario is defined for each analyte, based on the number of results above detection, the size of the second biggest result in relation to the HBL, and other factors.

,

Well-analytes with fewer than two above detection results have scenarios designated by capital letters, while analytes with at least two-above detection results have numeric scenarios. The second highest above detection result determines the magnitude of the numeric scenarios, and larger scenarios correspond to higher concentrations. The second highest result is used in this decision, because confirmation is required for containerization. (According to permit requirements, elevated values must be confirmed by reanalyis, and two results represent confirmation.) If the second highest above detection result exceeds the analyte’s health-based level (HBL) multiplied by the dilution and attenuation factor (DAF), then the analyte receives a scenario of two or higher and requires containerization. The DAF is ten for all analytes except for tritium and for RCRA Appendix IX analytes in wells that are monitoring facilities known to have received listed (i.e., RCRA hazardous) waste. As specified in the IDW Manageinent Plan, tritium does not undergo the comparison because it cannot be treated and exists at acceptable levels for all wells presently purged. However, the tritium levels are inspected periodically as the list of RCO wells is updated. Appendix IX analytes in wells monitoring facilities known to have received listed waste have a DAF of one. If any analyte in a particular well requires containerization, then purge water from that well must be containerized.

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7. Special Reports

As additional data needs are identified, special reports are incorporated into IDWP. Presently, the user can view the analyte HBL and classifications that influence the containerization decision. Full analyte names are matched with the test codes used to identify them at SRS. A table of well dates shows the installation and abandonment dates for all wells. The user can specify a date to define “new wells,” which produces a table of wells installed since that date. The special report data can be compiled into output files.

6. Containerization Files

The focus of this effort is the containerization lists, which are placed in tab-delimited text files. They can be transferred to the user’s PC or Macintosh by an FTP package like WS-FTP32 and then opened in MS Excel@ using the Text Import Wizard, which is automatically invoked for text files. A fie of statistics and purge volumes for wells that require containerization and a file of purge volumes for wells that do not require containerization are produced for each treatment facility. Three treatment facilities handle purge water from different areas on Site due to the distinct types of contamination. Explanations for wells dropped from containerization analysis are cataloged in another file. Two files inventory problem data, analytes with at least two above detection results but no HBL and old data for well-analytes triggering containerization. Other facility-specific files identify the actual results for well analytes with at least two above detection results and various statistics (mean, maximum, and second highest concentration and scenario) for each analyte in each well, The data for containerized wells are summarized by series and by area in separate files.

Sometimes the user has a need for specific GIMS data, and IDWP provides a mechanism for creating output files of such data. The user can gather data for one analyte in one well series, QA data for one analyte, and pH data for one well series. Also, the two most recent all well containerization lists can be compared in an output file.

To gauge trends and to look for outliers in the data, historical concentration plots are available. After standardizing the result units and performing some other basic data qualification, IDWP produces a time plot of the concentration of a selected analyte in a selected well. The result qualifier drawn in red serves as the plot symbol so that the user can identify below detection and other commented results. If the result is unqualified, a black pound (number) sign is used.

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8. KeyBenefits

IDWP has greatly decreased the cycle time and effort for generating containerization lists. The list no longer depends on any particular person and can be performed by ERD itself due to the user friendliness of the interface. The application of the algorithm is consistent, and the results are accurate. Multiple users can concurrently access IDWP. Also, user documentation exists, and assistance and training are readily available on Site. IDWP is flexible in that information routinely needed by ERD can be incorporated as special reports. Its single source ensures easy maintenance. Overall, IDWP is a cost-effective way to generate the information ERD requires for containerization and treatment and other project work.

9. Conclusion

In summary, IDWP serves as a quick and reliable tool for E m ’ s IDW Aqueous Administrator and other users. The main functions of IDWP are:

0 To determine which wells require containerization for purge water generated . duringsampling;

To assist in controlling and scheduling the handling, treatment, and discharge of purge water; To provide statistics to support the treatment facilities’ permits;

0 To provide statistics for ERD project work; 0 To gather analytic and other data from a remote database; 0 To plot analytic concentrations through time; 0 To provide tables of analyte and well information.

The success of IDWP comes from its collaborative development and the immediate availability of compfehensive software support for ERD from the SRS’s Statistical Consulting Section.

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