Environmental Chemometrics: Principles and Modern Applications

by Hanrahan; Grady

• ISBN13: 9781420067965
• ISBN10: 1420067966
• Edition: 1st
• Format: Nonspecific Binding
• Copyright: 2008-11-21
• Publisher: CRC Press

Summary

To keep pace with the rapidly emerging area of chemometrics, this volume presents basic principles together with real applications in environmental chemistry. It provides an overview in relation to quantitative environmental analysis, and a review of descriptive statistical concepts. It covers environmental sampling considerations, experimental design, and optimization techniques, and multivariate analysis of environmental and chemical data sets. The book also covers quality assurance and method validation. Each chapter contains exercises and research applications from noted experts. The author has also written a lab manual (cat no. 6794X) to accompany the text.

Table of Contents

Preface	p. xiii
Acknowledgments	p. xv
Author	p. xvii
Introduction	p. 1
Chemometrics-An Overview	p. 1
The Importance of Quantitative Environmental Analysis	p. 2
Common Chemical and Biological Pollutants in Environmental Matrices	p. 2
Air	p. 3
Water	p. 7
Soils and Sediments	p. 16
Overview of Chemometric Methods Used in Environmental Analysis	p. 17
Chapter Summary	p. 18
End of Chapter Problems	p. 21
References	p. 21
Review of Statistics and Analytical Figures of Merit	p. 25
Error and Sampling Considerations	p. 25
Descriptive Statistics	p. 26
Distribution of Repeated Measurements	p. 28
Data Quality Indicators	p. 34
Primary DQIs	p. 35
Secondary DQIs	p. 36
Confidence Intervals	p. 37
Statistical Tests	p. 38
Outlying Results	p. 41
Analysis of Variance	p. 44
Regression and Calibration Methods	p. 47
Sensitivity and Limit of Detection	p. 49
Bayesian Statistics Considered	p. 52
Expanded Research Application I-Statistical Merits of Calculating Transfer Coefficients among Environmental Media	p. 54
Statement of Problem	p. 54
Research Objectives	p. 54
Experimental Methods and Calculations	p. 55
Results and Interpretation	p. 55
Summary and Significance	p. 58
Introduction to Excel	p. 58
Chapter Summary	p. 62
End of Chapter Problems	p. 63
References	p. 65
Quality Assurance in Environmental Analysis	p. 67
The Role of Chemometrics in Quality Assurance	p. 67
Quality Assurance Considerations	p. 67
Project Planning and Preparation	p. 67
Traceability	p. 68
Sample Handling and Chain of Custody	p. 69
Accreditation	p. 69
Good Laboratory Practice	p. 71
Environmental Sampling Protocol-General Considerations	p. 72
Quality Assurance: Sample Collection, Preparation, and Storage	p. 73
Sampling Design	p. 73
Sample Collection, Preservation, and Storage	p. 75
Field QA/QC Samples	p. 80
Laboratory and Instrumental Methods: QA/QC Samples	p. 81
Standard Addition and Internal Standard Methods	p. 83
Certified Reference Materials	p. 86
Statistical Quality Control Charts	p. 88
Proficiency Testing	p. 91
Data Archiving, Storage, and Auditing	p. 95
Multivariate Quality Assurance/Control-Initial Considerations	p. 96
Expanded Research Application II-Monte Carlo Simulation for Estimating Uncertainty Intervals for the Determination of Nitrate in Drinking Water	p. 96
Statement of Problem	p. 97
Research Objectives	p. 97
Experimental Methods and Calculations	p. 97
Results and Interpretation	p. 98
Summary and Significance	p. 99
Chapter Summary	p. 100
End of Chapter Problems	p. 101
References	p. 102
Experimental Design and Optimization Techniques	p. 105
System Theory	p. 105
Review of Linear Regression Models and Matrix Notation	p. 105
Experimental Design Considerations	p. 108
Experimental Uncertainty and Replication	p. 108
Sample Size and Power	p. 109
Blocking and Randomization	p. 109
Orthogonality	p. 109
Confounding	p. 109
Center Points	p. 110
Single Factor Categorical Designs	p. 110
Randomized Block Designs	p. 110
Latin Square Design	p. 110
Greco-Latin Square Design	p. 111
Screening Designs	p. 112
Full Factorial Designs (Two Levels per Factor)	p. 112
Fractional Factorial Designs (Two Levels per Factor)	p. 116
Plackett-Burman and Taguchi Designs	p. 117
Three-Level Designs: Response Surface Methodology	p. 122
Central Composite Designs	p. 123
Box-Behnken Design	p. 125
Doehlert Matrix Design	p. 129
Mixture Designs	p. 132
Simplex Centroid Designs	p. 136
Simplex Lattice Designs	p. 137
Split-Plot Mixture Designs	p. 140
Simplex Optimization	p. 141
Expanded Research Application III-Optimized Separation of Benzo[a]Pyrene-Quinone Isomers Using Liquid Chromatography-Mass Spectrometry and Response Surface Methodology	p. 145
Statement of Problem	p. 145
Research Objectives	p. 147
Experimental Methods and Calculations	p. 147
Results and Interpretation	p. 149
Summary and Significance	p. 154
Chapter Summary	p. 154
End of Chapter Problems	p. 155
References	p. 155
Time Series Analysis	p. 159
Introduction to Time Series Analysis	p. 159
Smoothing and Digital Filtering	p. 162
Moving Average Smoothing	p. 162
Exponential Smoothing	p. 164
Times Series and Forecast Modeling-A Detailed Look	p. 165
Model Choice and Diagnostics	p. 166
Harmonic Analysis Techniques	p. 173
ARIMA Models	p. 180
Nonseasonal ARIMA Models	p. 180
Seasonal ARIMA Models	p. 183
Outliers in Time Series Analysis	p. 187
Export Coefficient Modeling	p. 189
Expanded Research Application IV-Export Coefficient Modeling and Time Series Analysis of Phosphorus in a Chalk Stream Watershed	p. 191
Statement of Problem	p. 191
Research Objectives	p. 191
Experimental Methods and Calculations	p. 192
Results and Interpretation	p. 193
Summary and Significance	p. 200
Chapter Summary	p. 201
End of Chapter Problems	p. 201
References	p. 202
Multivariate Data Analysis	p. 207
Introduction to Multivariate Data Analysis	p. 207
Data Preprocessing	p. 207
Correlation Analysis	p. 210
Correlation Matrix	p. 210
Inverse Correlations, Partial Correlations, and Covariance Matrix	p. 211
Pairwise Correlations	p. 212
Fit Functions	p. 214
Scatterplot Matrix	p. 216
Color Maps and 3D Ellipsoid Plots	p. 216
Nonparametric Correlations	p. 218
Pattern Recognition-Unsupervised	p. 222
Cluster Analysis	p. 222
Factor Analytic Techniques	p. 225
Pattern Recognition-Supervised	p. 231
Discriminant Analysis	p. 233
K-Nearest Neighbor Classification	p. 235
Soft Independent Modeling of Class Analogy	p. 237
Multivariate Calibration Methods	p. 237
Multivariate Linear Regression	p. 237
Partial Least Squares	p. 239
Principal Component Regression	p. 241
Multivariate T[superscript 2] Control Charts	p. 243
CUSUM Control Charts	p. 246
Soft Computing Techniques	p. 248
Artificial Neural Networks	p. 248
Fuzzy Logic	p. 253
Expanded Research Application-A Multivariate Study of the Relations between PM[subscript 10] Composition and Cell Toxicity	p. 256
Statement of Problem	p. 256
Research Objectives	p. 257
Experimental Methods and Calculations	p. 257
Results and Interpretation	p. 257
Summary and Significance	p. 262
Chapter Summary	p. 262
End of Chapter Problems	p. 263
References	p. 263
Common Excel Shortcuts and Key Combinations	p. 269
Symbols Used in Escuder-Gilabert et al. (2007)	p. 271
Review of Basic Matrix Algebra Notation and Operations	p. 273
Environmental Chain of Custody	p. 277
Index	p. 279
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