The use of on-site mobile laboratories at Los Alamos National Laboratory (LANL) has increased within the last year to accommodate the diverse analytical requirements of demands for the Environmental Restoration Project (ERP). The purpose of the mobile laboratory is to provide sample results with the appropriate QC components within a near real time (i.e. < 8 hours) to aid in a real time decision process such as determining the extent of contamination and/or where to focus the sampling efforts. To meet the data quality objectives (DQOS) of ERP, a flexible QA/QC program needs to exist. By developing a QA/QC program containing the capability to measure extraction efficiency and instrument sensitivity and by participating in the DQO process, the appropriate QC can easily be tailored to provide quick and inexpensive analytical data while still meeting the project requirements. An QA/QC program, consisting of both static and dynamic elements, can be tailored to meet the ERP objectives

Canavan, H.E.

Kelly, L.A.

Roberts, J.B.

Swanson, A.L.

Kelly, Laura A.

Roberts, Jeffrey B.

Swanson, Aaron L.

Canavan, Heather E.

UNT Digital Library

,. . I -. -_ L C  LA-UR- 96-170 Title: Author@): Submitted to: Los Alamos N A T I O N A L  L A B O R A T O R Y  DYNAMIC QUALITY ASSURANCE/QUALITY CONTROL (QA/QC) PROGRAM TO MAXIMIZE THE USE OF ON-SITE MEASUREMENT RECEIVED L. A. Kelly, J. B. Roberks, A. L. Swanson, H. E. Canavan 4th Int'l conf./On-Site Analysis, Orlando, FL January 1996 I Los Alamos National Laboratory, an affirmative action/equal opportunity empl-, 3r, is operated by the University of California for the US. Department of Energy under contract W-7405-ENG-36. By acceptance of this article, the publisher recognizes that the US. Government retains a nonexclusive, royalty-free license to publish or reproduce the published form of this contribution, or to allow others to do so, for US. Government purposes. The Los Alamos National Laboratory requests that the publisher identify this article as work performed under the auspices of the US. Department of Energy. DISCLAIMER Portions of this document may be illegible in electronic image products. Images are produced from the best available original document. . Dynamic Quality Assurance/Quality Control (QNQC) Program to Maximize the Use of On-site Measurement Laura A. Kelly, Jeffrey B. Roberts, Aaron L. Swanson, and Heather E. Canavan Organic Analysis Group; Chemistry, Science, and Technology (CST-12) Los Alamos National laboratory Los Alamos, New Mexico 87545 ABSTRACT The use of on-site mobile laboratories at Los Alamos National Laboratory (LANL) has increased within the last year to accommodate the diverse analytical requirements of demands for the Environmental Restoration Project (ERP). The purpose of the mobile laboratory is to provide sample results with the appropriate QC components within a near real time (Le. 8 hours) to aid in a real time decision process such as determining the extent of contamination and/or where to focus the sampling efforts. To meet the data quality objectives (DQOs) of ERP, a flexible QNQC program needs to exist. By developing a QNQC program containing the capability to measure extraction efficiency and instrument sensitivity and by participating in the DQO process, the appropriate 1 QC can easily be tailored to provide quick and inexpensive analytical data while still meeting the project requirements. An QNQC program, consisting of both static and dynamic elements, can be tailored to meet the ERP objectives. The following elements represent the foundation of the mobile laboratory’s QNQC program: method development and validation prior to deployment, performance evaluation outside of field activities, data reportingheviewing , and documentation of all activities involved with the analytical process. The flexibility in the QNQC program exists in the ability to adjust the standard operating procedures (SOPS) in order to address the customer requirements both prior to and during deployment, the ability to tailor methods accordingly, the frequency and type of QC samples as well as the rationale and interpretation of the data, and the sample results (i.e. do the reporting limits represent the DQO requirements). Not only do the dynamic elements integrate with the DQO process to streamline and maximize the efficiency of the analyses, but also balance against the customer and regulatory requirements for the sampling site. BACKGROUND In an effort to enhance the efficiency and cost-effectiveness of the environmental characterization process, the Organic Chemistry Group (CST-12) 2 with the aid of the Environmental Resortation Project (ERP) has established a capability consisting of two Mobile Chemical Analytical Laboratories (Chem Vans). The purpose of the Chem Vans is to provide near real time analytical support of field activities by determining the presence or absence of suspected analyte(s) and quantifying those analytes, determining the extent of contamination, and directing sampling events. Presently, the Chem Vans provide services for the following analyses: volatile organic compounds (VOC), polychlorinated biphenyls (PCB), polynuclear aromatic hydrocarbons (PAH), total petroleum hydrocarbons (TPH), high explosives (HE), and total metals. The Chem Van is capable of performing fully compliant SW 846 method 8260, a modified target list for BTEX (benzene, toluene, ethylbenzene, and xylenes) analyses, or volatile TPH. Extractable TPH is performed using a GC/FID or IR based method. PAH's are analyzed using GC/MS with a reduced scanning range to enhance sensitivity. Metals are analyzed by X-Ray Fluorescence. Mini-extractions, typically using 5 to I O  grams of sample to 5 - 10 mls of solvent, are used instead of a sonication or soxhlet extraction (both of which require more solvent and time). Analytical methods are designed to be flexible to account for unforeseen complications and/or changes in data requirements of ERP. performed approximately 3200 analyses. Last year the Chem Van 3 < <  A final critical component of the Chem Van's capability is a flexible QNQC program that has been developed to meet the objective of providing quality data for continually changing data requirements and to effectively support field decisions. This paper decribes the need, characteristics, and the process of developing the Chem Van's QNQC program. QNQC PROGRAM In order to meet the data requirements of the ERP and to optimize the utility of the Chem Vans, it was necessary to develop a QNQC program consisting of dynamic elements integrated with a classical QNQC foundation. The Foundation - Static Elements Typically, QNQC programs used by in-house laboratories have an extensive list of requirements which is rigid and designed to meet strigent data quality objectives. From this list of requirements, the following elements serve as the foundation for the Chem Van's QNQC program: method validation, performance evaluation studies, data reporting/reviewing formats, and documentation of all 4 activities involved with the analytical process. Method validation is the process of certifying the reporting limits, precision and bias an analytical method prior to its use. Method validation is accomplished by performing a Method Detection Limit (MDL) Study as given in SW 846. This procedure requires a triplicate analyses of a matrix spike containing the analyte(s) of interest at a concentration three to five times the estimated MDL. Further method validation can be achieved by participating in a performance evaluation study program. By analyzing EPA check samples provided under the Water Suplly (WS) and Water Pollution (WP) Performance Evaluation Studies every three months, the reporting limits, precision, and bias can periodically be measured and recorded. Blind QC samples obtained from the Analytical Services Group (CST-3) containing the analyte(s) of interest can be submitted with the collected samples as an additional QC parameter. All activities associated with the analytical process require documentation, from the acceptance of samples to the reporting of data. When samples are accepted by the Chem Van, the condition of the samples and the chain of custody are examined and approved. Any anomalies such as missing custody seals or samples are documented on the chain of custody. Extraction, standard, and instrument/analyticaI logbooks are used following good laboratory 5 . '  standard, and instrument/analytical log books are used following good laboratory practices (GLP). Often, the same sample will require more than one analysis. One common extraction logbook has been created to record sample weight and other comments for all analyses performed. An instrument/analyticaI logbook exists for each instrument and is used to track instrument maintenance, troubleshooting, and analytical activities. Other documentation practices such as a temperature logbook for recording the temperature of the sample and standard refrigerators and an analytical balance logbook for checking the accuracy of the balanced used are a vital part of the QNQC program. Another element essential in the generation of quality data is the reviewing and reporting of the data. Data is reported using Excel spreadsheets. Each analysis has a spreadsheet for recording sample weight, dilution factors, and any detection of analyte(s). Data entry typically occurs after the raw data has been obtained. Self and peer reviews are then applied. Each data package given to the client contains the sample raw data, Excel spreadsheet, calibration summary, and review checklist. A diskette containing the Excel spreadsheets is provided. Dynamic Elements 6 ' .  The flexibility of the Chem Van's QNQC program exists in the ability to adjust analytical and oversight parameters to meet a wide range of data requirements. The parameters include standard operating procedures (SOPs), analytical methods, type and frequency of QC samples, and reporting limits. While these parameters exist in any QNQC program, the success of the Chem Van methods lies in their ability to break through classical QNQC ideology to focus on what is necessary, practical, and scientifically proven in order to provide quality data. Since SW 846 and CLP methods are not practical for on-site analyses, the Chem Van uses methods which have been modified to deliver quality data in a shorter period of time and to analyze for compounds of interest which may not be covered in SW 846 The core of the Chem Van's flexible QNQC program exists in writing SOPs to reflect a wide range of analytical techniques. Including the fundamentals of extraction and instrumental processes allows for the ability to adjust a method in order to address alterations in data requirements both prior to and during employment can easily occur. By writing general and flexible SOPs, the ability to allow for revisions exist while still retaining the QA oversight aspect of a SOP The analytical methods used by the mobile laboratory rely on basic scientific principal and good laboratory practices (GLP), similar to SW 846 methods, but 7 . '  may not include as stringent a QA oversight. The differences between the modified methods and SW 846 methods are the variations in extraction, calibration, and/or instrumentation parameters. However, the modified methods still contain the necessary QNQC criteria to measure extraction efficiency, to ensure instrument sensitivity, and to provide reliable quantitative results. Flexibility in the extraction process is achieved by adjusting the sample size, final volume, and/or timing of dilutions resulting in a better ability to changing analytical requirements. Utilization of different solvents can result in better analyte solubility and/or less water or instrument interference. For example, acetone rather than acetonitrile is used to extract HE samples due to enhance solubility. This results in better extraction efficiencies reducing the necessary extraction time. In addition to making extraction modifications, taking advantage of the latest technologies in instrumentation (such as better absorptant traps, columns, and/or mass spectrometers) can help accomodate heavy sampling activities, facilitate faster results reporting, or improved instrument sensitivity. Instrument parameters such as choice of detector, temperature program, injection volume, and mass ranges can be optimized to reduce the analysis time and adjust the sensitivity appropriately. These adjustments may alleviate the need to concentrate during extraction or perform excessive dilutions. Once a method has been developed to accommodate the data needs, certain QC samples are required in order to measure the method's extraction efficiency, 8 ' .  . I  instrument sensitivity, and accuracy. The Chem Van's QNQC program uses surrogate(s), initial and continuing calibration, method blank, and (if requested) a laboratory control sample (LCS). This type of QNQC program requires a limited number of QC samples as compared to CLP and SW 846 methods, where QC can account for up to 25% of the samples analyzed. By streamlining the number of QC samples required, valuable analysis time can be devoted to the customer's samples. The justification for using QC samples should be based on scientific reason and realistic expectations. For example, if the daily calibration and the surrogate recoveries met the acceptance criteria, it is questionable whether it is necessary to analyze a matrix spike, matrix spike duplicate and/or laboratory control sample. Typically, a matrix spike and matrix spike duplicate will only provide bias and precision data for a limited number of analytes in one type of matrix. The rationale for the amount of QC needed should solely be dependent upon the customer's needs and the regulatory requirements rather than perceived requirements based on past experiences. DQO Process When tailoring a QNQC program to meet the data requirements of the ERP, an important issue is the amount of QNQC needed. The Data Quality Objective (DQO) process is a series of planning steps that are designed to clarify study 9 objectives, define appropriate types of data to collect, and to specify the tolerable levels of potential decision errors. In summary, the DOQ process is designed to answer the following four basic questions: I) what information is needed, 2) why the information is needed, 3) how the information will be used, and 4) what is the acceptable tolerance for error. The DQO process helps define the level of QC required. The DQO process consists of the following elements: 1. State the problem 2. Identify the decision 3. 4. Define the study boundaries 5. 6. 7. Identify inputs to the decision Define the quality based on customer needs for the project Specify limits on decision error Optimize design for obtaining data Applying the DQO process in a stepwise fashion is a means by which the customer can determine the acceptable amount of QNQC based on the end use of the data. Once the level of W Q C  has been determined, the flexibility of the QNQC program allows appropriate rnodications to the analytical methods to meet the DQO's. 10 SUMMARY The success of the Chem Van within the last year resided in the ability to recognize the need for a flexible and practical QNQC program to accomodate changing data requirements for ERP. While the QNQC program contained the elements covered in a standard QNQC program, the dynamic feature of this program lie in the ability to choose selected elements which could easily be modified on a real-time basis. As a result, a unique strategy has been developed: the ability to tailor the appropriate method and QC to provide quick and inexpensive analytical data while still meeting the data requirements of the ERP. ACKNOWLEDGEMENTS The authors would like to acknowledge the support of: Margaret A. Gautier, Joan Fisk, and the Environmental Restoration Program. DISCLAIMER This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsi- bility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Refer- ence herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recom- mendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. 11 : C 

Dynamic quality assurance/quality control (QA/QC) program to maximize the use of on-site measurement

Dynamic quality assurance/quality control (QA/QC) program to maximize the use of on-site measurement

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