vii
Contents
4 Quality Assurance/Quality Control
93
4.1
Introduction
93
4.2
Attributes of Data Quality
95
4.2.1 Method Detection and Reporting Limits
95
4.2.1.1 Method Detection Limit
95
4.2.1.2 Reporting Limit
98
4.2.2 Precision and Accuracy
101
4.2.3 Completeness
102
4.2.4 Comparability
103
4.2.5 Representativeness
103
4.2.6 Recommended Laboratory Data Quality Objectives
104
4.3
QA/QC Sample Types
105
4.3.1 Filter Blanks, Analytical Blanks, and Field Blanks
109
4.3.2 Replicate Environmental Samples
109
4.3.3 Spiked Project Samples
110
4.3.4 External Quality Assurance Samples
111
4.4
Field QA
113
4.4.1 Sample Containers
113
4.4.2 Field Measurements
113
4.5
Reporting QA Data
115
4.6
Laboratory Audits and Certification
117
4.7
Data Entry
118
4.8
Summary
119
References
120
5 Data Analysis
121
5.1
Background and Objectives
121
5.2
Evaluation of Data Quality
122
5.2.1 Charge Balance
126
5.2.2 Calculated versus Measured Conductivity
132
5.2.3 Calculated versus Measured ANC
133
5.2.3.1 Carbonate Alkalinity versus Titrated ANC
133
5.2.3.2 Calculated versus Titrated ANC
134
5.2.4 Other Validation Procedures
136
5.2.5 Final Data Quality Determination
137
5.3
Apply Procedures to Prepare Raw Data for Graphical and Statistical
Analysis
137
5.3.1 Censored Data
137
5.3.2 Outliers and Missing Values
138
5.3.3 Multiple Observations
141
5.3.4 Treatment of Zeros and Negative Values
142
5.3.5 Treatment of Seasonality
142