Previous Page  38 / 44 Next Page
Information
Show Menu
Previous Page 38 / 44 Next Page
Page Background

Ref. No. [UMCES] CBL 2017-050

ACT VS17-05

38

Table 9. The number of reference samples collected during the laboratory test and at each field site.

Site

No. of

Samples

No. of

Replicates

per

Sample

No. of

Analytes

1/

Measured

in Each

Replicate

No. of

Measurement

s

Maumee River

61

3

3

549

CBL – Field

120

3

3

1080

CBL – Lab

92

5

3

1380

Hawaii

73

3

3

657

Total

346

3,666

1/

NO

2

; NO23; PO

4

The data review verified that the sampling and analysis protocols specified in the Test

Protocols were followed, and that the ACT measurement and analytical systems performed in

accordance with approved methods, based on:

The raw data records were complete, understandable, well-labeled, and traceable;

All data identified in the Test Protocols were collected;

QC criteria were achieved; and

Data calculations were accurate.

Data validation uses the outputs from data verification and included inspection of the verified

field and laboratory data to determine the analytical quality of the data set. A representative set of

approximately 10% of the reference data was traced in detail from 1) raw data from field and

laboratory logs, 2) data transcription, 3) data reduction and calculations, to 4) final reported data.

Validation of the data sets established:

Required sampling methods were used;

Sampling procedures and field measurements met performance criteria; and

Required analytical methods were used.

The data validation also confirmed that the data were accumulated, transferred, summarized,

and reported correctly. There is sufficient documentation of all procedures used in the data collection

and analysis to validate that the data were collected in accordance with the evaluation’s quality

objectives.

A Data Quality Assessment (DQA) is the third and final process of the overall data

assessment. It is a scientific and statistical evaluation of validated data to determine if the data are

of the right type, quality, and quantity to support conclusions on the performance of the technologies.

The DQA determined that the test’s data quality objectives, described in Section 7.1 of the Test

Protocols and Section 3.4 and Appendix B of the ACT QAPP (ACT, 2016), were achieved. This

evidence supports conclusions that: