1. LABORATORY MANAGEMENT and QUALITY ASSURANCE

2. Introduction “The analytical laboratory provides qualitative and quantitative data for use in decision-making. To be valuable, the data must accurately describe the characteristics and concentrations of constituents in the samples submitted to the laboratory. In many cases, because they lead to faulty interpretations, approximate or incorrect results are worse than no result at all.” –HANDBOOK FOR ANALYTICAL QUALITY CONTROL IN WATER AND WASTEWATER LABORATORIES, EPA 1979

3. Quality Assurance - Defined “Quality Assurance (QA) is a set of operating principles that, if strictly followed during sample collection and analysis, will produce data of known and defensible quality.” “The Accuracy of the analytical result can be stated with a high level of confidence.” –STANDARD METHODS, 18 th EDITION, 1992

4. Outline Laboratory Management Introduction to Quality Assurance Concepts

5. Laboratory Management Who should be involved in laboratory management and quality assurance?

6. Laboratory Management Everyone involved with the lab: –Person sampling –Person running the test –Person washing the glassware –Person doing maintenance on the instruments –Person interpreting the results

7. Laboratory Management Quality Assurance Program –Staff Organization and Responsibilities –Sample Control and Documentation –SOP for Analytical Methods & Procedures –Analyst Training Requirements –Equipment Preventative Maintenance –Calibration Procedures –Corrective Actions –Internal Quality Control Activities –Performance Audits –Data Assessment for Bias and Precision –Data Validation and Reporting

8. Laboratory Management Keys to Quality Assurance Program: –Documentation –Communication –Training –Cross-Training –Updating

9. Sample Control and Documentation A record keeping system (paper trail, chain of custody) should track samples before, during, and after analysis. Everyone involved needs to understand and utilize the system.

10. Sample Control and Documentation Efficiently process information through lab system while minimizing actual time spent recording data Keep it simple! –Collect only the information you need

11. Suggested Information - Field Date Conditions Collected By Site Code Comments: Hayfield Site Influent 04-15-02 8am HS IN 1Jim S. Sunny, 75F pH adjusted to <2 with nitric acid Grab sample

12. Suggested Information - Lab Date of analysis Laboratory technicians performing the analysis Results (including units) Analytical comments: based on need to know –Dilutions –Interferences encountered

13. SOP for Analytical Procedures Describes method in enough detail that an experienced analyst could obtain acceptable results.

15. SOP for Cleanliness Labware cleaning procedures should be documented and all persons involved should be trained.

16. Routine Cleaning Procedure Rinse glassware with tap water. Clean glassware with a solution of water and laboratory detergent. Rinse the glassware with an acidic solution –1.0 N HCl –6N HNO 3 for regulatory reporting of heavy metals Rinse glassware at least 3X with DI water.

17. Routine Cleaning Procedure (cont.) Glassware should be stored in a manner that prevents contamination from dust particles. Prior to analysis, rinse the glassware with sample to prevent contamination or dilution.

18. SOP for Instrumentation Maintenance Preventative maintenance is the key to optimal instrument performance. –Follow any maintenance program and guidelines suggested by the instrument manufacturer. –Instrument manual Reduces instrument downtime Service Contracts with Manufacturers

19. Analyst Training Sample Logging and Preservation Method SOPs Measuring –Use of Volumetric glassware (pipettes, graduated glassware) Weighing / Use and care of Analytical Balance Washing and Care of Glassware Operation of Analytical Instrumentation Data Handling and Reporting Quality Control Activities Safety

20. QUALITY ASSURANCE CONCEPTS

21. Quality Assurance Quality Control Certification of Analyst Competence Recovery of Known Additions Analysis of Standards Analysis of Reagent Blanks Calibration with Standards Analysis of Duplicates Maintenance of Control Charts Quality Assessment Performance Evaluation Samples Performance Audits

22. Quality Assurance Quality Control Certification of Analyst Competence Recovery of Known Additions Analysis of Standards Analysis of Reagent Blanks Calibration with Standards Analysis of Duplicates Maintenance of Control Charts Quality Assessment Performance Evaluation Samples Performance Audits

23. Certification of Analyst Competence Demonstration of acceptable precision and accuracy for each analyst Minimum of four replicate analyses on a known standard –Look for acceptable accuracy and precision –Acceptable limits vary per analytical method ‘Demonstration of Capability’

24. What is Accuracy? Accuracy is the nearness of a test result to the true value.

25. What is Precision? Precision is how closely repeated measurements agree with each other. Although good precision suggests good accuracy, precise results can be inaccurate.

26. Imprecise and inaccurate Precise but inaccurate Accurate but imprecise Precise and accurate

27. Quality Assurance Quality Control Certification of Analyst Competence Recovery of Known Additions Analysis of Standards Analysis of Reagent Blanks Calibration with Standards Analysis of Duplicates Maintenance of Control Charts Quality Assessment Performance Evaluation Samples Performance Audits

28. Standards What is a standard? –Solution containing a known amount of a specific substance –Example – 1.00mg/L iron standard

29. Standards How are standards used? –Instrument calibration –Instrument verification/accuracy check –Analyst training

30. Standards Analysis of Known Standard Solutions – Am I running the test correctly? –Verifies instrument, technique, and reagents

31. Standards Analysis of Known Standard Solutions – –How often? –Daily, every Sample ‘Batch’? National Institute of Standards and Technology –“NIST”

32. Standards Recovery of Known Additions – –Is my sample compatible with the test? –Identifies interferences and percent recovery Standard Addition ‘Spiked sample’

33. 33 = 1.00 mg/L 50 mg/L Iron Standard 1.20 mg/L1.39 mg/L1.58 mg/L Correct?? 1.20 mg/L1.40 mg/L1.60 mg/L

34. 34 X100 = 100 % 1.20 mg/L X100 = 99 % 1.39 mg/L 1.40 mg/L X100 = 98.7 % 1.58 mg/L 1.60 mg/L

36. Calibration with Standards Some instruments have built-in calibration curves, not necessary to calibrate Instrument without preprogrammed calibration curves –Prepare curve daily - OR –Whenever a new lot of reagents is prepared

37. Calibrations mg/L ABS

39. pH Calibration Curve mV pH 0 +180 -180 4 7 10

40. Standards “It’s what I always get” “It meets the permit limit” “I did”: –what the manual said –what tech support said –what you told me “It’s the same number the City of ____ gets” “I got what I expected” “I’ve run standards” “It’s a XXX brand instrument, the best!” “After 20 years you get a feel for it” “I’m a chemist” “It’s the same answer the lab got”

41. Quality Assurance Quality Control Certification of Analyst Competence Recovery of Known Additions Analysis of Standards Analysis of Reagent Blanks Calibration with Standards Analysis of Duplicates Maintenance of Control Charts Quality Assessment Performance Evaluation Samples Performance Audits

42. Reagent Blanks Some reagents contribute color to a sample –Quantifies amount of reagent contribution to color formation –Monitors of purity of reagents On each new lot of reagents 5% of samples (Standard Methods)

43. Reagent Blanks

45. Quality Assurance Quality Control Certification of Analyst Competence Recovery of Known Additions Analysis of Standards Analysis of Reagent Blanks Calibration with Standards Analysis of Duplicates Maintenance of Control Charts Quality Assessment Performance Evaluation Samples Performance Audits

46. Analysis of Duplicates Assesses precision 5% of sample need to be Duplicates –(Standard Methods)

47. Quality Assurance Quality Control Certification of Analyst Competence Recovery of Known Additions Analysis of Standards Analysis of Reagent Blanks Calibration with Standards Analysis of Duplicates Maintenance of Control Charts Quality Assessment Performance Evaluation Samples Performance Audits

48. What is a Control Chart? Quality control (QC) measuring device that visually represents the QC data Information in a control chart can aid in determining: –Probable source of measurement variability –Whether or not a process is in statistical control

49. How do Control Charts Work? If the chart displays other than random variation around the expected result, it suggests a problem with the measurement process. –Control limits are plotted on the chart, to assess whether this has happened. The measurement results are expected to remain within these limits.

50. Normal Distribution (Standard Deviation around the Mean) +2s+3s+1s-1s-2s-3sMEAN

51. Confidence Limits +2s+3s+1s-1s-2s-3s10.00 68%

52. Confidence Limits +2s+3s+1s-1s-2s-3s10.00 95%

53. Confidence Limits +2s+3s+1s-1s-2s-3s10.00 99%

54. Control Charts A control chart is essentially a normal distribution flipped on its side A control chart is a plot of: –Test units on the vertical scale –Sequence of time on the horizontal scale

55. Control Chart +3s +2s +1s Mean -1s -2s -3s

56. Control Chart +3s +2s +1s Mean -1s -2s -3s Upper Warning Limit Lower Warning Limit

57. Control Chart +3s +2s +1s Mean -1s -2s -3s Upper Control Limit Lower Control Limit

58. How do Control Charts Work? Warning Limits –Set at ±2s –Standard Methods suggests: If 2 of 3 points are outside warning limits, analyze another sample. If it is within warning limits, continue. If it is outside warning limits, stop and troubleshoot.

59. How do Control Charts Work? Control Limits –Set at ±3s –Standard Methods suggests: If any point is outside control limits, analyze another sample. If it is within control limits, continue. If it is outside control limits, stop and troubleshoot.

60. How do Control Charts Work? A standard is measured regularly, and the results are plotted on the control chart. Control chart is a graph of concentration versus time.

61. +3s +2s +1s Mean -1s -2s -3s UC L LC L LW L UW L Control Chart Iron Standard, FerroVer Procedure Time

62. Constructing a Control Chart A control chart can be constructed in a variety of ways: –Graph paper –Spreadsheet problem, such as Excel

63. Constructing a Control Chart Analyze 10-15 replicates of a standard. Determine the mean and standard deviation. –Calculate ±2s and ±3s Construct the control chart around the mean value –Use ±2s as the warning limits –Use ±3s as the control limits

64. Example – Iron Standard Replicates Samplemg/L Iron 11.003 21.010 30.995 41.007 50.993 61.018 71.000 80.986 91.014 101.005 110.990 121.000 130.982 141.000 150.997

65. Example – Iron Standard Replicates Calculate: –Mean –Standard Deviation (±1s) –±2s –±3s

66. Example – Iron Standard Replicates Calculate: –Mean1.000 –Standard Deviation (±1s)±0.010 (0.990-1.010) –±2s±0.020 (0.980-1.020) –±3s±0.030 (0.970-1.030)

67. +3s +2s +1s Mean -1s -2s -3s UC L LC L LW L UW L Control Chart Iron Standard, FerroVer Procedure Time 1.00 mg/L 1.02 mg/L 0.98 mg/L 1.03 mg/L 0.97 mg/L

68. Constructing a Control Chart First, set up a spreadsheet with columns for UWL, LWL, UCL, LCL, and sample results

69. Constructing a Control Chart Fill in values for UWL, LWL, UCL, LCL, and sample results

70. +3s +2s +1s Mean -1s -2s -3s UC L LC L LW L UW L Control Chart Iron Standard, FerroVer Procedure Time 1.00 mg/L 1.02 mg/L 0.98 mg/L 1.03 mg/L 0.97 mg/L

71. Constructing a Control Chart Fill in values for UWL, LWL, UCL, LCL, and sample results

72. Constructing a Control Chart Highlight data and create a graph

73. Constructing a Control Chart Format graph as necessary

74. Example Control Charts Control Analysis Results – Week 1 Samplemg/L Iron Mon1.003 Tues0.995 Wed1.006 Thurs0.988 Fri0.992 Sat0.992 Sun1.004

75. Example Control Charts Week 1 results display normal, random variation between the UWL and LWL.

76. Example Control Charts Control Analysis Results – Week 2 Samplemg/L Iron Mon1.008 Tues1.000 Wed0.996 Thurs0.993 Fri0.989 Sat0.988 Sun0.983

77. Example Control Charts Week 2 – Three or more points in one direction indicates a possible bias in analytical results. Investigate!

78. Example Control Charts Control Analysis Results – Week 3 Samplemg/L Iron Mon1.012 Tues1.000 Wed1.015 Thurs0.986 Fri0.994 Sat0.968 Sun0.997

79. Example Control Charts Week 3 – Data has a high degree of scatter to the LCL. Investigate!

80. Quality Assurance Quality Control Certification of Analyst Competence Recovery of Known Additions Analysis of Standards Analysis of Reagent Blanks Calibration with Standards Analysis of Duplicates Maintenance of Control Charts Quality Assessment Performance Evaluation Samples Performance Audits

81. Performance Evaluation Samples Standards provided by an outside agency –‘Blind’ Samples

82. Performance Audits Inspection to document sampling handling from receipt to final reporting of results –To detect any variations from SOPs –Checklists developed for each analysis type Sample entered in log book? Meter calibrated? Standard Analyzed? Etc., etc…..

83. LABORATORY MANAGEMENT and QUALITY ASSURANCE

84. References Standards Methods “Handbook for Analytical Quality Control in Water and Wastewater Laboratories” –EPA 1979 Hach Water Analysis Handbook “An Introduction to Standards and Quality Control for the Laboratory” –Barbara Martin, Hach Company