Process for Assessing Data Usability 

DEP-EA 001/07 

Florida Department of Environmental Protection 

2600 Blair Stone Road 

Tallahassee, FL 32399-2400 

Bureau of Standards and Special Projects 

Environmental Assessment Section 

March 31, 2008 
Process for Assessing Data Usability 

DEP-EA 001/07 

Table of Contents 

1. Introduction ........................................................................................................................... 1

1.1. The Data Assessment Process ..................................................................................... 1

1.2. Evaluating Data Quality Indicator Failures .................................................................... 1

2. Data Quality Indicators (DQI) ................................................................................................ 2

3. Laboratory Control Sample or Spike (LCS)........................................................................... 2

3.1. General Requirements .................................................................................................. 2

3.2. Evaluation of LCS Recovery ......................................................................................... 3

4. Matrix Spikes (MS) ................................................................................................................ 3

4.1. General Requirements .................................................................................................. 3

4.2. Evaluation of MS Recovery ........................................................................................... 4

5. Surrogate Spikes................................................................................................................... 5

6. LCS Duplicates or Replicates (LCSD) and Matrix Spike Duplicates (MSD) ......................... 5

6.1. General Requirements .................................................................................................. 5

6.2. Evaluation of Duplicates ................................................................................................ 5

7. Sample Duplicates (SD) ........................................................................................................ 6

7.1. General Requirements .................................................................................................. 6

7.2. Evaluation of Sample Duplicates................................................................................... 6

8. Calibrations ........................................................................................................................... 7

8.1. Initial Calibration ............................................................................................................ 7

8.2. Calibration Verification (CV) .......................................................................................... 7

9. Method Blanks or Other Analytical Blanks - .......................................................................... 8

10. Field Quality Control Blanks (Trip Blanks, Field Blanks or Equipment Blanks .................. 9

11. Holding Times ................................................................................................................... 9

12. Quality Control Check Samples ...................................................................................... 10

12.1. BOD Analyses ............................................................................................................. 10

12.2. Chlorophyll Analyses ................................................................................................... 10

12.3. Matrix-Specific Evaluation for Known or Suspected Interferences.............................. 11

13. Sample Preservation Checks .......................................................................................... 12

14. Evaluation of the Reported MDL ..................................................................................... 12

15. Evaluation of the Reported PQL ..................................................................................... 12

16. Evaluation of Reversals (Parts vs. Whole Comparison ................................................... 12

17. General Principles of Data Quality Assessment.............................................................. 13

18. Procedure for Data Usability Determinations .................................................................. 15

19. Summary of the Data Usability Assessment Process ..................................................... 16

Page i of i Revision Date: March 31, 2008 
Process for Assessing Data Usability 

DEP-EA 001/07 

1. Introduction - The intent of this document is to outline the process to be used by the 

Department when evaluating Data Quality Indicators (DQI) and determining the usability 

of analytical data. 

1.1. The Data Assessment Process - Determining if data are usable for a particular 

purpose is a complex task, requiring a reasonable and balanced evaluation of many factors. 

The procedural components of the usability assessment must be performed by auditors with 

sufficient scientific expertise in environmental data verification and validation, and include, 

but are not limited to: Understanding the purpose for auditing the data (project or program 

data quality objectives provide the context for the audit); 

• Identifying the set of data to be audited, the types of analytes or parameters in the 

data set and the reported values (e.g., concentration) for the analytical results for all 

components; 

• Determining the relationship between each analytical result, the associated decision 

or action level (e.g., water quality standard or clean up target) and the laboratory’s 

quantitation limit; 

• Evaluating the documented calibration, quality control and other supporting data 

against designated Data Quality Indicators; 

• Establishing the pattern, frequency, and magnitude of any failures or other 

deficiencies associated with the results; 

• Determining the extent to which the audited data set fulfills the Data Quality 

Objectives of the project or Program; 

• Evaluating corroborative data (e.g., performance tests, data from other laboratories); 

• Providing usability recommendations to the Program data users. 

1.2. Evaluating Data Quality Indicator Failures - Exceeding the acceptance criteria for 

one or more Data Quality Indicators does not necessarily mean the data are unusable. The 

factors mentioned in 1.1 above must be systematically evaluated before a usability decision 

can be made 

1.2.1. The purpose for which the analytical data were collected can vary widely, and 

may include such diverse activities as: initial screening or scoping studies, permit 

compliance monitoring, assessing waters for Total Maximum Daily Load development or 

determining whether a permitted waste facility has met “clean closure” site 

contamination assessment requirements. 

1.2.2. A Data Quality Indicator failure that is acceptable for a screening study may not 

be acceptable for declaring a site free from contamination. 

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1.2.3. In practical terms, it is not possible in this document to discuss each potential 

scenario that might be associated with a data usability recommendation for a particular 

purpose. Therefore, the factors affecting this decision (outlined in 1.1 and 1.2, above) 

and the thought process applied to the data usability assessment are addressed by the 

general principles and examples listed below. 

2. Data Quality Indicators (DQI) - The following Data Quality Indicators (Sections 3.0 – 16) 

are targets used in the context of assessing data usability. Depending on a given 

situation, not all DQIs are applicable to the specific assessment project. 

Example: To be considered usable, a data submittal to DEP consisting only of 

high sample concentrations (with no values near the PQL) need not be 

associated with records demonstrating evaluation or verification of the PQL. 

2.1. The application of DQIs to sample results presumes the random occurrence of nonroutine criteria failures to be an expected fact associated with all analyses. The frequency 

of DQI failures are considered as part of the overall data usability assessment in order to 

determine those instances where routine or systematic failures indicate a significant data 

usability problem. 

2.2. Use of DQIs with Other Published Criteria - Except as discussed otherwise in this 

document, sample results are evaluated for usability based on the procedural requirements 

and performance criteria established by the reported analytical methods, applicable project 

data quality objectives, applicable regulations, applicable NELAC Quality Systems 

standards and applicable DEP SOPs for field and laboratory activities (DEP-SOP-001/01 

and DEP-SOP-002/01). 

2.3. Use of Records to Assess Data Usability - As applicable to the data usability 

assessment process, any record associated with a reported sample result or set of sample 

results may be audited, per 62-160.240 & .340, FAC. Both original (“raw”) and reduced or 

summarized versions of data records are inspected in order to determine acceptance of the 

procedures and performance criteria that are used to generate and evaluate the sample 

data and associated quality control activities. 

2.4. The presence or absence of critical, archival records that support the sample results 

is considered when determining whether sufficient documentation is available to assess the 

usability of the data. 

3. Laboratory Control Sample or Spike (LCS) –In order of preference, LCS data are 

evaluated rather than matrix spike data (MS), if both types of data are generated for the 

associated sample preparation batch. However, the MS data are also used to evaluate 

the recoveries of the analytes for the parent sample and may affect the usability of the 

parent sample result. 

3.1. General Requirements 

3.1.1. An LCS result is linked or associated with all applicable reported sample results 

for the same preparation batch or analytical sequence of 20 samples or less. 

3.1.2. The LCS contains all of the analytes of interest for the method or project, or the 

mix of analytes in the LCS is rotated at a routine frequency as suggested in the NELAC 

Quality Systems standard in Appendix D. 

3.1.3. If a preparation step (such as digestion or extraction) is required for the analysis 

method, the LCS is prepared identically with and at the same time as the associated 

samples in the preparation batch. 

3.1.4. The LCS is analyzed or reanalyzed within a verified calibration bracket (analytical 

sequence see Section 8.2.2 for the definition). 

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3.1.5. All reanalyses are documented with a valid explanation of the systematic error 

that prompted the reanalyses. 

3.1.6. The concentration of the LCS is analyzed to be within the calibration range for 

the instrument as established by the concentrations of the standards used for the initial 

calibration and continuing calibration verifications. 

3.1.7. Where applicable, the LCS is prepared at the method-specified concentration or 

at a concentration appropriate for the project data quality objective. 

3.2. Evaluation of LCS Recovery - Where applicable, the control limits for the LCS are 

established by the laboratory for a specified matrix at ± 3X the standard deviation of the 

mean recovery of the cumulative LCS analyses at a specified concentration. Alternatively, 

the recovery control limits are established by linear regression for a range of concentrations 

using cumulative recovery data. The mean recovery is calculated or regression analysis is 

applied after outliers are eliminated from the recovery data set using any appropriate 

statistical test for outliers and after outliers due to known systematic errors are also 

censored from the data set. The mean recovery is recalculated or linear regression is 

reanalyzed if trend monitoring of individual LCS recoveries indicates that a systematic bias 

has developed and corrective action is needed. 

3.2.1. Alternatively, control limits are established by the laboratory using other 

technically justifiable and scientifically sound procedures in accordance with project data 

quality objectives. 

3.2.2. Where applicable, criteria established by rule, reported method or project data 

quality objectives are used to evaluate the LCS recoveries. 

3.2.3. If no other criteria are applicable, the following control limits are used to evaluate 

the LCS recoveries: 

80% - 120% (water) for Nitrate, Nitrite, Nitrate + Nitrite, Ammonium, TKN, 

Total Phosphorus, Orthophosphate 

85% - 115% (water) for Metals 

Laboratory Control Limits for: 

All Organic analytes for the LCS in any matrix 

All other analytes amenable to spiking for the LCS in water 

All analytes amenable to spiking for the LCS in non-aqueous matrices 

3.2.4. When applicable, sample results reported with failed LCS recoveries are 

documented with a valid explanation of the systematic error that occurred. 

3.2.5. Analytes or methods technically not amenable to spiking for recovery 

determinations are not evaluated. 

4. Matrix Spikes (MS) - Method-specified criteria are used to evaluate the MS, where 

applicable. If no LCS data is available for the sample preparation batch or analytical 

sequence being evaluated, the MS data is used to evaluate method control for all of the 

associated samples in the batch or sequence. 

4.1. General Requirements 

4.1.1. The MS contains all of the analytes of interest for the method or project, or the 

mix of analytes in the MS is rotated at a routine frequency as suggested in the NELAC 

Quality Systems standard in Appendix D. 

4.1.2. If a preparation step (such as digestion or extraction) is required for the analysis 

method, the MS is prepared identically with and at the same time as the associated 

samples in the preparation batch. 

Page 3 of 16 Revision Date: March 31, 2008 
4.1.3. The MS is analyzed or reanalyzed within a verified calibration bracket (analytical 

sequence). 

4.1.4. All reanalyses are documented with a valid explanation of the systematic error 

that prompted the reanalyses. 

4.1.5. The concentration of the MS is analyzed to be within the calibration range for the 

instrument as established by the concentrations of the standards used for the initial 

calibration and continuing calibration verifications. 

4.1.6. Where applicable, the MS is spiked at the method-specified concentration or at a 

concentration appropriate for the project data quality objective. 

4.2. Evaluation of MS Recovery 

4.2.1. The MS spike concentration is compared with the un-spiked, parent-sample 

concentration. The suitability of the spike concentration is evaluated on a case-by-case 

basis according to method specifications or project data quality objectives. 

4.2.2. MS recovery data is evaluated if specified by applicable data quality objectives, 

but the recovery of the MS is only associated with the parent sample, unless no LCS is 

associated with the preparation batch or analytical sequence of 20 samples or less. In 

this case, the MS recovery is associated with all of the samples in the preparation batch 

or analytical sequence of 20 samples or less for evaluation of sample data usability. 

4.2.3. Where applicable, the control limits for the MS are established by the laboratory 

for a specified matrix at ± 3X the standard deviation of the mean recovery of the 

cumulative MS analyses for the associated matrix at a specified concentration. 

Alternatively, the recovery control limits are established by linear regression for a range 

of concentrations for the associated matrix using cumulative recovery data. The mean 

recovery is calculated or regression analysis is applied after outliers are eliminated from 

the recovery data set using any appropriate statistical test for outliers and after outliers 

due to known systematic errors are also censored from the data set. The mean 

recovery is recalculated or linear regression is reanalyzed if trend monitoring of 

individual MS recoveries indicates that a systematic bias has developed and corrective 

action is needed. 

4.2.4. Alternatively, control limits are established by the laboratory using other 

technically justifiable and scientifically sound procedures in accordance with project data 

quality objectives. 

4.2.5. If the MS is used to evaluate all associated batch samples, the applicable LCS 

criteria are used to evaluate the MS recovery. 

4.2.6. Where applicable, criteria established by rule, reported method or project data 

quality objectives are used to evaluate the MS recoveries. 

4.2.7. If no other criteria are applicable, the following control limits are used to evaluate 

the MS recoveries: 

80% - 120% (water) for Nitrate, Nitrite, Nitrate + Nitrite, Ammonium, TKN, 

Total Phosphorus, Orthophosphate 

70% - 130% (water) for Metals 

Laboratory Control Limits 

 All Organic analytes at any concentration 

 All other analytes amenable to spiking at any concentration 

 All analytes in non-aqueous matrices 

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4.2.8. When applicable, sample results reported with failed MS recoveries are 

documented with a valid explanation of the systematic error that occurred. 

4.2.9. Analytes or methods technically not amenable to spiking for recovery 

determinations are not evaluated. 

5. Surrogate Spikes - Surrogate spikes are evaluated according to method-specified 

requirements and the NELAC Quality Systems standards (Chapter 5 and Appendix D). 

5.1. The concentration of the surrogate spike is analyzed to be within the initial calibration 

range established for the instrument. 

5.2. When applicable, sample results reported with failed surrogate spike recoveries are 

documented with a valid explanation of the systematic error that occurred. 

5.3. Analytes or methods technically not amenable to spiking for recovery determinations 

are not evaluated. 

6. LCS Duplicates or Replicates (LCSD) and Matrix Spike Duplicates (MSD) - In order of 

preference, LCSD data are evaluated rather than MSD data, if both types of data are 

generated for the associated samples. However, the MSD data are also used to 

evaluate the precision of the analytes for the parent sample and may affect the usability 

of the parent sample result. 

6.1. General Requirements 

6.1.1. When applicable, replicate rather than duplicate LCS/MS data are evaluated for 

precision control. 

6.1.2. An LCSD/MSD result is linked or associated with all applicable reported sample 

results for the same preparation batch or analytical sequence of 20 samples or less. 

6.1.3. The LCSD/MSD contains all of the analytes of interest for the method or project, 

or the mix of analytes in the LCSD is rotated at a routine frequency as suggested in the 

NELAC Quality Systems standard in Appendix D. 

6.1.4. If a preparation step (such as digestion or extraction) is required for the analysis 

method, the LCSD/MSD is prepared identically with and at the same time as the 

associated samples in the preparation batch. 

6.1.5. The LCSD/MSD is analyzed or reanalyzed within a verified calibration bracket 

(analytical sequence). 

6.1.6. All reanalyses are documented with a valid explanation of the systematic error 

that prompted the reanalyses. 

6.1.7. The concentration of the LCSD/MSD is analyzed to be within the calibration 

range for the instrument as established by the concentrations of the standards used for 

the initial calibration and continuing calibration verifications. 

6.1.8. Where applicable to the evaluation, the MSD spike concentration is compared 

with the un-spiked, parent-sample concentration. The suitability of the spike 

concentration is evaluated on a case-by-case basis according to method specifications 

or project data quality objectives. 

6.2. Evaluation of Duplicates 

6.2.1. Where applicable, the control limits for the LCSD/MSD are established by the 

laboratory for a specified matrix at ≤3X the standard deviation of the mean precision 

(absolute or relative) of the cumulative LCSD analyses for the associated matrix at a 

specified concentration. Alternatively, the precision control limits are established by 

linear regression for a range of concentrations for the associated matrix using 

cumulative precision data. The mean precision is calculated or regression analysis is 

applied after outliers are eliminated from the precision data set using any appropriate 

Page 5 of 16 Revision Date: March 31, 2008 
6.2.2. Alternatively, control limits are established by the laboratory using other 

technically justifiable and scientifically sound procedures in accordance with project data 

quality objectives. 

6.2.3. Where applicable, criteria established by rule, reported method or project data 

quality objectives are used to evaluate the LCSD/MSD precision. 

6.2.4. If no other criteria are applicable, precision data for the LCSD/MSD are evaluated 

using the laboratory control limits, with a target precision of ≤20% RPD or RSD for water 

samples and ≤40% RPD or RSD for non-aqueous and solid-matrix samples. 

6.2.5. When applicable, sample results reported with failed LCSD/MSD precision are 

documented with a valid explanation of the systematic error that occurred. 

6.2.6. Analytes or methods technically not amenable to precision determinations are 

not evaluated. 

7. Sample Duplicates (SD) 

7.1. General Requirements 

7.1.1. Sample matrix duplicates are evaluated for the analytes present in the sample if 

no LCSD/MSD data is available or if required by the method or project data quality 

objectives. 

7.1.2. When applicable, replicate rather than duplicate sample data are evaluated for 

precision control. 

7.1.3. If a preparation step (such as digestion or extraction) is required for the analysis 

method, the SD is prepared identically with and at the same time as the associated 

samples in the preparation batch. 

7.1.4. If no LCSD/MSD is available for evaluation, an SD result is linked or associated 

with all applicable reported sample results for the same preparation batch or analytical 

sequence of 20 samples or less. 

7.1.5. The SD is analyzed or reanalyzed within a verified calibration bracket (analytical 

sequence). 

7.1.6. All reanalyses are documented with a valid explanation of the systematic error 

that prompted the reanalyses. 

7.1.7. The concentration of the SD is analyzed to be within the calibration range for the 

instrument as established by the concentrations of the standards used for the initial 

calibration and continuing calibration verifications. 

7.2. Evaluation of Sample Duplicates 

7.2.1. Where applicable, the control limits for the SD are established by the laboratory 

for a specified matrix at ≤3X the standard deviation of the mean precision (absolute or 

relative) of the cumulative SD analyses for the associated matrix at a specified 

concentration. Alternatively, the precision control limits are established by linear 

regression for a range of concentrations for the associated matrix using cumulative 

precision data. The mean precision is calculated or regression analysis is applied after 

outliers are eliminated from the precision data set using any appropriate statistical test 

for outliers and after outliers due to known systematic errors are also censored from the 

data set. The mean precision is recalculated or linear regression is reanalyzed if trend 

Page 6 of 16 Revision Date: March 31, 2008 
7.2.2. Alternatively, control limits are established by the laboratory using other 

technically justifiable and scientifically sound procedures in accordance with project data 

quality objectives. 

7.2.3. Where applicable, criteria established by rule, reported method or project data 

quality objectives are used to evaluate the SD precision. 

7.2.4. If no other criteria are applicable, precision data for the SD are evaluated using 

the laboratory control limits, with a target precision of ≤20% RPD or RSD for water 

samples and ≤40% RPD or RSD for non-aqueous and solid-matrix samples. 

7.2.5. When applicable, sample results reported with failed SD precision are 

documented with a valid explanation of the systematic error that occurred. 

7.2.6. Analytes or methods technically not amenable to precision determinations are 

not evaluated. 

8. Calibrations - Except as discussed elsewhere in this document, all calibrations are 

evaluated according to method-specified requirements and applicable NELAC Quality 

Systems standards. 

8.1. Initial Calibration 

8.1.1. The number of standard concentrations specified by the method or project data 

quality objectives is used to perform the initial calibration of the instrument or technique. 

8.1.2. Where applicable, the concentration values specified by the method or project 

data quality objectives are used to perform the initial calibration of the instrument or 

technique. 

8.1.3. If not specified by the method or project objectives and when applicable to the 

analytical technology, at least two standard concentrations and a blank are used for a 

linear calibration curve. 

8.1.4. The acceptance of the initial calibration is evaluated using the method-specified 

criteria or the criteria specified by the project data quality objectives. 

8.1.5. If not specified by the method or project data quality objectives and when 

applicable to the analytical technology: 

• The correlation coefficient for a regression is ≥0.995 when applied to the 

linear calibration curve. 

• Higher-order calibration curve regressions have a coefficient of determination 

of ≥0.99, using 6 calibration points for a second order curve and 7 calibration 

points for a third order curve. The calibration points used for the curve 

include a result for the calibration blank. 

8.1.6. Where applicable, the initial calibration range is extended by an accepted 

calibration verification. 

8.1.7. Unless allowed by the method or project data quality objectives, applicable 

sample results whose analyzed concentrations fall outside of the calibration range 

established by the standard concentrations used for the initial calibration (excluding the 

calibration blank) and calibration verifications are not usable without further evaluation or 

qualification. 

8.2. Calibration Verification (CV) 

8.2.1. At least one verification standard is from a second source as indicated in the 

applicable NELAC Quality Systems standard for initial calibrations. 

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8.2.2. An acceptable calibration verification is analyzed at the beginning and end of the 

analytical batch (verified calibration bracket) or as otherwise required by the applicable 

NELAC Quality Systems standard for continuing calibration verifications. 

8.2.3. The analytical batch is determined as defined by the applicable NELAC Quality 

Systems standard. 

8.2.4. As applicable or when specified by rule or project data quality objectives, the 

calibration verification standard is analyzed at the method-specified frequency. 

8.2.5. As applicable or when specified by rule or project data quality objectives, the 

calibration verification result is evaluated using the method-specified criteria. 

8.2.6. In the absence of acceptance criteria specified by rule, project data quality 

objectives or method, and where applicable, the control limits for the CV are established 

by the laboratory for a specified matrix at ± 3X the standard deviation of the mean 

recovery of the cumulative CV analyses at a specified concentration. For this purpose, 

recovery is defined as the percent of expected concentration analyzed for the CV 

standard. The mean recovery is calculated after outliers are eliminated from the 

recovery data set using any appropriate statistical test for outliers and after outliers due 

to known systematic errors are also censored from the data set. The mean recovery is 

recalculated if trend monitoring of individual CV recoveries indicates that a systematic 

bias has developed and corrective action is needed. 

8.2.7. Alternatively, control limits are established by the laboratory using other 

technically justifiable and scientifically sound procedures in accordance with project data 

quality objectives. 

8.2.8. If a continuing calibration verification did not meet the acceptance criterion, but is 

immediately reanalyzed with acceptable results, the samples analyzed before the failed 

verification result are valid, provided that the verification previous to the failed verification 

and following the reanalyzed verification are also acceptable and comprise a verified 

calibration bracket or analytical batch. 

8.2.9. Sample results that are not analyzed within a verified analytical batch or 

calibration bracket are reanalyzed or qualified as estimated values. 

8.2.10. Alternatively, for purposes of assessing the usability of the sample data where 

verifications have failed and where the reported sample values are relevant to the 

regulatory action level, compliance limit or other project data quality objective, the failed 

continuing calibration verifications are evaluated for potential high or low bias according 

to the applicable NELAC Quality Systems standards for calibration verifications. 

9. Method Blanks or Other Analytical Blanks - All method blanks and other types of 

analytical blanks use to control analytical contamination are evaluated for the presence 

of the analytes of interest for the project or method. 

9.1. A blank result is linked or associated with all applicable reported sample results for 

the same preparation batch or analytical sequence of 20 samples or less. 

9.2. If a preparation step (such as digestion or extraction) is required for the analysis 

method, at least one blank is prepared identically with and at the same time as the 

associated samples in the preparation batch. 

9.3. The blank is analyzed or reanalyzed within a verified calibration bracket (analytical 

sequence). 

9.4. All reanalyses are documented with a valid explanation of the systematic error that 

prompted the reanalyses. 

Page 8 of 16 Revision Date: March 31, 2008 
9.5. Unless specified otherwise by rule, an applicable analytical method or project data 

quality objectives, it is expected that the concentration of analytes detected in the blank 

(above the reported MDL) will be less than 10% of the concentration in the individual 

samples of the associated preparation batch or analytical sequence (for the affected 

analytes). 

9.6. Where samples are diluted for analysis, the evaluation of the blank results is 

considered with respect to the dilution factors associated with the samples. 

9.7. BOD method blanks are evaluated against the method criterion. 

9.8. No colonies are reported in bacteriological method blanks. 

10. Field Quality Control Blanks (Trip Blanks, Field Blanks or Equipment Blanks) - Field 

QC Blanks associated with the samples for a specific sampling event are evaluated for 

contamination as indicated by the presence of the analytes of interest for the project or 

method. 

10.1. If a preparation step (such as digestion or extraction) is required for the analysis 

method, the blank is prepared identically as the associated samples in the preparation 

batch. 

10.2. The blank is analyzed or reanalyzed within a verified calibration bracket (analytical 

sequence). 

10.3. Unless specified otherwise by rule, an applicable analytical method or project data 

quality objectives, it is expected that the concentration of analytes detected in the blank 

(above the reported MDL) will be less than 10% of the concentration in the associated field 

sample (for the affected analytes). 

10.4. Where samples are diluted for analysis, the evaluation of the blank results is 

considered with respect to the dilution factors associated with the samples. 

11. Holding Times - Holding times as specified in the tables in FS 1000 of the DEP SOPs are 

met. 

11.1. For those analytes where there is no separate holding time specified for the extract, 

digestate or other processed sample, the holding period ends when the sample processing 

begins. 

11.2. Holding times that are specified in “hours” are met if the sample processing (e.g., 

extraction, digestion, filtration, etc) or analysis, as applicable, begins within the last hour of 

the specified holding time, accounting for the time zone in which the sample was collected. 

Example: For a sample with a 24-hour holding time that was collected at 

14:15 on May 20, 2007, the sample is within holding time if the sample is 

processed before 15:15 on May 21, 2007. 

11.3. Holding times that are specified in “days” are met if the sample processing begins 

before 24:00 on the final day, accounting for the time zone in which the sample was 

collected. 

11.4. Clarifications 

11.4.1. For microbiology, the holding time is evaluated as the duration between the 

sample collection date and time and the date and time of the placement of the 

processed sample into or on the applicable growth medium. 

11.4.2. For BOD or CBOD, the holding time is evaluated as the duration between the 

sample collection date and time and the date and time of the initial DO measurement for 

the test. 

Page 9 of 16 Revision Date: March 31, 2008 
11.4.3. For toxicity testing, the holding time is evaluated as the duration between the 

sample collection date and time and the date and time of introduction of the last 

individual test organism into a test sample. 

12. Quality Control Check Samples – The following criteria are used to evaluate specific 

quality control check samples for the indicated test. 

12.1. BOD Analyses 

12.1.1. For each preparation batch of 20 samples or less, glucose-glutamic acid (GGA) 

samples are analyzed to obtain values within the method-specified acceptance control 

limits. 

12.1.2. Alternatively, per approved revisions to SM 5210 B, other compounds are used 

to control the method, when applicable to a specific wastewater effluent. 

12.1.3. In order of preference, replicate check sample data are evaluated rather than 

sample replicate data, if both types of data are generated for the associated samples. 

12.1.4. Precision data for the replicate check sample analyses are evaluated using the 

laboratory control limits, with a target precision of ≤20% RPD or RSD expected. 

12.1.5. Where applicable, the control limits for the replicate check sample analyses are 

established by the laboratory at ≤3X the standard deviation of the mean precision 

(absolute or relative) of the cumulative check sample analyses. The mean precision is 

calculated after outliers are eliminated from the precision data set using any appropriate 

statistical test for outliers and after outliers due to known systematic errors are also 

censored from the data set. The mean precision is recalculated if trend monitoring of 

individual check sample results indicates that a systematic error has occurred and 

corrective action is needed. 

12.1.6. Alternatively, control limits are established by the laboratory using other 

technically justifiable and scientifically sound procedures in accordance with project data 

quality objectives. 

12.1.7. When applicable, sample results reported with failed check sample precision are 

documented with a valid explanation of the systematic error that occurred. 

12.2. Chlorophyll Analyses 

12.2.1. For each preparation batch of 20 samples or less, or at least once every three 

months, a chlorophyll extract solution in acetone is analyzed to evaluate recovery at the 

concentration for the extract. 

12.2.2. A vendor-assayed source of chlorophyll is used to prepare the check sample 

extract. 

12.2.3. The concentration of the check sample extract is such that when extrapolated to 

the volume of a nominal whole-water concentration, the extract appropriately represents 

the estimated reporting limit for the whole water sample. 

12.2.4. The check-sample results at the extract concentration are evaluated using 

control limits established by the laboratory. 

12.2.5. The control limits for the extract check-sample solution are established by the 

laboratory at ± 3X the standard deviation of the mean result of the cumulative checksample analyses expressed as a percentage of the expected value of the check-sample 

concentration. The mean result is calculated after outliers are eliminated from the 

check-sample data set using any appropriate statistical test for outliers and after outliers 

due to known systematic errors are also censored from the data set. The mean result is 

recalculated if trend monitoring of individual check-sample results indicates that a 

systematic bias has developed and corrective action is needed. 

Page 10 of 16 Revision Date: March 31, 2008 
12.2.6. Alternatively, control limits are established by the laboratory using other 

technically justifiable and scientifically sound procedures in accordance with project data 

quality objectives. 

12.3. Matrix-Specific Evaluation for Known or Suspected Interferences - An example 

of typical interferences of concern to DEP is the analyses for trace metal concentrations in 

seawater. 

12.3.1. When applicable to the project data quality objectives and when technically 

feasible, known or suspected interferences in the matrix specific to the project analytes 

and samples are evaluated using quality control (QC) samples of known matrix 

composition and analyte concentration. 

12.3.2. The QC sample result is linked or associated with all applicable reported field 

sample results for the same preparation batch or analytical sequence of 20 samples or 

less. 

12.3.3. The composition of the matrix for the QC sample is controlled for the analytes 

and interferences of interest and closely matches or approximates the matrix of the 

associated field samples. 

12.3.4. A naturally derived or artificially formulated matrix is used to prepare the QC 

sample. 

12.3.5. The QC sample is prepared by the analyzing laboratory using a second source 

standard for the analyte of interest. The second-source standard is selected as 

indicated in the NELAC Quality Systems standard for initial calibrations. 

12.3.6. Alternatively, the QC sample is obtained from an external source such as a 

commercial vendor of QC-check samples or Standard Reference Materials. 

12.3.7. Where applicable, the QC sample is prepared at the method-specified 

concentration or at a concentration selected according to project data quality objectives. 

12.3.8. Where applicable, the concentration of the QC sample is evaluated against any 

data quality objectives for minimum quantitation level applicable to the data use and 

does not exceed 2X the minimum quantitation level. 

12.3.9. If a preparation step (such as digestion or extraction) is required for the analysis 

method, the QC sample is prepared identically with and at the same time as the 

associated samples in the preparation batch. 

12.3.10. The QC sample is analyzed or reanalyzed within a verified calibration bracket 

(analytical sequence). 

12.3.11. All reanalyses are documented with a valid explanation of the systematic 

error that prompted the reanalyses. 

12.3.12. The concentration of the QC sample is analyzed to be within the calibration 

range for the instrument as established by the concentrations of the standards used for 

the initial calibration and continuing calibration verifications. 

12.3.13. As applicable, the recovery for the QC sample is evaluated using methodspecified criteria, vendor-specified criteria, or control limits established by the laboratory. 

12.3.14. Where applicable, the control limits for the QC sample are established by the 

laboratory for a specified matrix at ± 3X the standard deviation of the mean recovery of 

the cumulative QC sample analyses at a specified concentration. Alternatively, the 

recovery control limits are established by linear regression for a range of concentrations 

using cumulative recovery data. The mean recovery is calculated or regression analysis 

is applied after outliers are eliminated from the recovery data set using any appropriate 

statistical test for outliers and after outliers due to known systematic errors are also 

Page 11 of 16 Revision Date: March 31, 2008 
censored from the data set. The mean recovery is recalculated or linear regression is 

reanalyzed if trend monitoring of individual QC sample recoveries indicates that a 

systematic bias has developed and corrective action is needed. 

12.3.15. Alternatively, control limits are established by the laboratory using other 

technically justifiable and scientifically sound procedures in accordance with project data 

quality objectives. 

12.3.16. When applicable, sample results reported with failed QC sample recoveries 

are documented with a valid explanation of the systematic error that occurred. 

13. Sample Preservation Checks 

13.1. The field records demonstrate positive indication that the samples are properly 

preserved (including thermal preservation). 

13.2. The laboratory records demonstrate that proper thermal preservation was checked 

upon receipt at the laboratory, per the instructions in the NELAC Quality Systems standards. 

13.3. The laboratory records demonstrate that samples that have been collected on the 

same day and hand-delivered are received at the laboratory in ice if the temperature check 

fails the applicable rule or method requirement. 

13.4. The laboratory records demonstrate positive indication that the samples are checked 

for proper chemical preservation prior to or during sample preparation or analysis. 

14. Evaluation of the Reported MDL 

14.1. If no analyte is detected in the evaluated sample, the assessment of sample data 

usability includes establishing that the laboratory determined, evaluated and verified the 

reported MDL for the analyte according to the requirements in the applicable NELAC Quality 

Systems standards, regulatory requirement or reported method. 

14.2. The MDL determination, evaluation and verification are considered when 

establishing the usability of the sample data where the reported MDL is relevant to the 

regulatory action level, compliance limit or other project data quality objective. 

14.3. For the purposes of data usability evaluation, the DEP-defined MDL is equivalent to 

the NELAC-defined LOD. 

15. Evaluation of the Reported PQL 

15.1. If the concentration of the evaluated sample is below the concentration value of the 

reported PQL or is below the concentration value of the lowest initial calibration standard or 

continuing calibration verification standard associated with the sample, the assessment of 

sample data usability includes establishing that the laboratory determined, evaluated and 

verified the reported PQL for the analyte according to the requirements in the applicable 

NELAC Quality Systems standards. 

15.2. The PQL determination, evaluation and verification are considered when establishing 

the usability of the sample data where the reported PQL is relevant to the regulatory action 

level, compliance limit or other project data quality objective. 

15.3. For the purposes of data usability evaluation, the DEP-defined PQL is equivalent to 

the NELAC-defined LOQ. 

16. Evaluation of Reversals (Parts vs. Whole Comparison) 

16.1. Where applicable, sample results are evaluated to determine if the sum of reported 

parts or fractions for the associated sample analyte results exceed 120% of the 

corresponding reported or calculated whole. 

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16.2. Evaluation of reversals with respect to sample data usability is assessed on a caseby-case basis with more extensive validation of the specifically affected analyses conducted 

as needed. 

Examples of reversals include the following: 

Parameter Part Parameter Whole 

Total ammonia TKN 

Orthophosphate Total phosphorus 

Nitrate Measured Total nitrite/nitrate 

Nitrite Measured Total nitrite/nitrate 

Sum of nitrite and nitrate Measured Total nitrite/nitrate 

Sum of nitrite, nitrate and TKN Measured Total nitrogen 

Sum of measured total nitrite/nitrate and 

TKN 

Measured Total nitrogen 

Filtered sample results (e.g., dissolved 

metals) 

Unfiltered sample results (e.g., total 

metals) 

Methyl mercury Total mercury 

DOC TOC 

17. General Principles of Data Quality Assessment - The following principles will be used 

when evaluating sample data for data usability determinations using specified Data 

Quality Indicators. The guidelines discussed in this section are only applicable if specific 

data quality assessment directives have not been provided in any other Department 

Rule or reporting format. The examples given below are illustrative and simplistic in 

nature. 

17.1. Supporting data that fail the target acceptance criteria for specific Data Quality 

Indicators will be evaluated against the affected sample result and the magnitude of the 

failure. 

Examples: 

A wastewater effluent, with a nitrate discharge permit level of 10 mg/L, was 

analyzed by a laboratory and found to have a nitrate concentration of 0.26 

mg/L. For the recovery of the Laboratory Control Sample (LCS), the 

laboratory has established acceptance criteria of 80 – 120%. For this 

particular batch of samples, recovery for the LCS was 78%, and the laboratory 

properly qualified the result with a “J”. Because the actual nitrate value was 

significantly lower than the permit limit, and the quality control failure was 

relatively minor, this result is judged to be usable. 

A Class I waterbody was sampled for benzene to determine if concentrations 

complied with the water quality standard of 1.18 ug/L. A benzene analysis 

was performed with initial calibration standards ranging from 1 ug/L to 200 

ug/L. All QC checks associated with this analysis were within the calibration 

range and within acceptance criteria. One of the project samples had a 

benzene concentration of 210 ug/L. The sample was qualified by the 

laboratory with a “J” and an explanation provided that the result exceeded the 

high level calibration standard. Because of the absolute magnitude of the 

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sample result (exceeding the water quality standard by nearly 209 ug/L), and 

the fact that it exceeded the high level standard by only 5%, the data is usable 

for the project. 

A wastewater effluent sample, which was collected to determine compliance 

with a 10 ug/L arsenic permit limit, was found to have 9.5 ug/L of arsenic. 

While the Laboratory Control Sample acceptance criteria previously 

established by the laboratory was 75 – 125%, the LCS recovery associated 

with this sample was only 65%. These data are unusable to demonstrate 

compliance, due to the close proximity of the sample to the action level, and 

the low LCS recovery (well outside of the targeted acceptance criteria). 

17.2. The magnitude of the sample result is considered when evaluating the 

consequences of the failed or absent Data Quality Indicators. 

Examples: 

An Everglades surface water sample, analyzed for compliance with a 10 ug/L 

total phosphorus criterion, was found to contain 21 ug/l of total phosphorus. 

The sample was properly preserved, but due to a laboratory mistake, the 

original sample had to be re-analyzed. The second analysis produced a total 

phosphorus result of 17 ug/L, but now the holding time was exceeded by 1 

week. The value was qualified by the laboratory with a “Q” for exceeding the 

holding time. Despite a reduction in the phosphorus concentration that could 

have been associated with exceeding the holding time, the analytical result 

still exceeded the action level, and the datum is usable. 

For a waste facility study, benzene was found in groundwater at a 

concentration of 5.7 ug/L. However, the reported method detection limit 

(MDL) for this particular benzene analysis was 1 ug/L, with a practical 

quantitation limit (PQL) of 4 ug/L. The Rule 62-777 FAC guidance document 

for routinely achievable PQLs indicates the target PQL for benzene is 1 ug/L. 

In this case, despite the elevated detection limit (indicating use of a less 

sensitive method), the sample result was above the reported PQL, and this 

result is usable. 

A surface water sample was analyzed by membrane filtration for fecal 

coliform, to determine if the 800 Colonies/100 mL water quality standard was 

exceeded. The analytical result was calculated to be 1,200 Colonies/100 mL. 

Method blanks were run simultaneously with the surface water samples by 

filtering 100 mL of sterilized dilution water, which resulted in the presence of 2 

– 5 target colonies in the blank samples. The laboratory did not use “V” 

(analyte detected in blank) to qualify the result. This result is usable despite 

the failure of the lab to properly qualify the samples, the high magnitude of the 

result exceedance, compared with the minor contamination in the blanks. 

Biochemical Oxygen Demand analysis conducted on a surface water sample 

yielded a result of 5.5 mg/L. Dissolved oxygen depletion in the associated 

method blank was 0.3 mg/L, exceeding method criteria by 0.1 mg/L. The 

results were properly qualified with “V”. The data is usable based on the 

magnitude of the exceedance compared with the quality control failure. 

17.3. The evaluation of laboratory performance or the determination of usability for a data 

set will be based on a preponderance of Data Quality Indicator failures pointing to specific, 

systematic problems with the laboratory operation or the data set. 

Examples: 

Page 14 of 16 Revision Date: March 31, 2008 
The analytical data generated by a County surface water monitoring program 

were being audited to determine if the data could support Impaired Waters 

Rule listing decisions for the Total Maximum Daily Load (TMDL) program. 

Fifteen chlorophyll a samples, which had been analyzed over a five year 

period, were evaluated. Twice in this five year period, due to laboratory 

oversights, the 48 hour hold time for filtration was not met. Records 

demonstrated that the 48 hour hold time was the laboratory’s target and that a 

quality system for meeting this objective was evident. Upon reviewing 

additional chlorophyll a quality control records, it was determined these 

holding time exceedances were isolated instances and that the 5 year period 

of data is usable. 

Upon auditing a laboratory’s quality control information associated with data 

submitted to the TMDL program, it was discovered that the majority of 

samples were analyzed beyond the accepted holding time, and that none of 

these results were qualified with “Q”. When the laboratory manager was 

asked about the discrepancy, they indicated that the qualifiers were purposely 

suppressed so that the TMDL program would use all the data. Because these 

admissions indicated that the entire quality system was compromised, the 

data were deemed not usable. 

17.4. Project management goals are taken into consideration when making data usability 

assessments. Specific Data Quality Objectives are established for certain analytical 

activities within a project, and these objectives will be evaluated when making a usability 

statement. 

Examples: 

A cleanup goal established for a waste remediation site stated that all 

analytical work must be sensitive enough to meet the Cleanup Target Levels 

(CTL) in Rule 62 – 777 FAC. During the project, a previously unknown area of 

contamination was discovered, and the Project Manager ordered some grab 

samples to delineate the aerial extent and magnitude of the newly found 

contamination. The lab used a method with a higher PQL (that did not meet 

the original cleanup objectives) but use of this method allowed a rapid turnaround time, enabling an effective adaptive management approach to better 

address the newly discovered contamination. These data are usable based 

on this set of objectives (delineating the new area of concern). 

Four monitoring wells were sampled for trichloroethane (TCE) at a 

groundwater remediation site previously known to have TCE concentrations 

ranging from 20-30 ug/L. During this particular sampling, TCE measured at 

the four wells was found to be below 1 ug/L, and there were no laboratory 

quality control failures of any kind. However, sampling records indicated that 

large volumes of groundwater were purged with a centrifugal pump in a short 

time period, and that dissolved oxygen levels in the wells exceed 7 mg/L. 

Because the evidence indicates that improper sampling occurred, resulting in 

excessive aeration and de-gassing of volatile compounds, these data were 

determined to be unusable. 

18. Procedure for Data Usability Determinations 

18.1. Data auditors will review and evaluate the following information: 

• The purpose for auditing the data; 

• The reported values of the analytical results; 

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• The relationship between each analytical result and an associated decision or action 

level; 

• The documented calibration, quality control and other supporting data compared with 

designated Data Quality Indicators in 62-160, F.A.C. or other specified Data Quality 

Objectives; 

• The pattern, frequency, and magnitude of any failures or other deficiencies 

associated with the results; 

• The extent to which the audited data set fulfills the Data Quality Objectives of the 

project or Program. 

18.2. Based on the evaluation, the auditors will determine how the data can be used by the 

relevant Department programs. 

19. Summary of the Data Usability Assessment Process 

Based on the above inputs, the auditor will extrapolate audit findings to determine the overall 

performance of a laboratory for a period of record, and determine the usability of the data in 

question for a Department purpose. Usability assessments will evaluate the Data Quality 

Indicator results for the subject data set relative to DEP program or project objectives, and the 

follow the principles characterized in this guidance document to draw an “overall conclusion” 

concerning the usability of the data set. This conclusion will address individual samples or will 

express a “general assessment” based on examination of a representative sample set over a 

pre-determined time period, depending on the project objectives and the sample set being 

evaluated. This assessment will include, where applicable, the evaluation of data trends relative 

to laboratory corrective actions or laboratory events (e.g., laboratory instituted NELAC 

standards in November of 2004). The resulting usability determination would be characterized 

over certain segments of the audited period. Recommendations concerning usability of the data 

will be communicated with appropriate Department staff.