Environmental Chemometrics: Principles and Modern Applications

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Multivariate, heterogeneous data has been traditionally analyzed using the "one at a time" variable approach, often missing the main objective of discovering the relationships among multiple variables and samples. Enter chemometrics, with its powerful tools for design, analysis, and data interpretation of complex environmental systems. Delineating the rigors of modern environmental analysis and how to effectively solve limitations through multivariate approaches, Environmental Chemometrics: Principles and Modern Applications provides an introduction and practical guide to chemometric methods used in environmental chemical analysis.

The text begins with an overview of chemometrics in relation to quantitative environmental analysis and a review of descriptive statistical concepts. Building on this, the author covers environmental sampling considerations, experimental design and optimization techniques, multivariate analysis of environmental and chemical data sets, time series analysis, and quality assurance and method validation. Each chapter contains problem-oriented exercises and research applications from the author’s own work and from other experts in the field.

The author’s presentation of the basic principles of these methods together with real applications in the field of environmental chemistry makes the comprehension of complex environmental problems and chemically-related concepts more accessible. He covers all major areas of environmental analysis backed by studies from experts in the field. The book is a valuable tool for understanding the rapidly developing world of chemometric methods in environmental analysis.

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Product Details

  • ISBN-13: 9781420067965
  • Publisher: Taylor & Francis
  • Publication date: 11/17/2008
  • Series: Analytical Chemistry Series
  • Pages: 310
  • Product dimensions: 6.10 (w) x 9.20 (h) x 0.70 (d)

Table of Contents


Chemometrics—An Overview The Importance of Quantitative Environmental Analysis

Common Chemical and Biological Pollutants in Environmental Matrices

Overview of Chemometric Methods Used in Environmental Analysis

Chapter Summary

End of Chapter Problems


Review of Statistics and Analytical Figures of Merit

Error and Sampling Considerations

Descriptive Statistics

Distribution of Repeated Measurements

Data Quality Indicators

Confidence Intervals

Statistical Tests

Outlying Results 1

Analysis of Variance

Regression and Calibration Methods

Sensitivity and Limit of Detection

Bayesian Statistics Considered

Expanded Research Application I—Statistical Merits of Calculating Transfer Coeffi cients Among Environmental Media


Quality Assurance in Environmental Analysis

The Role of Chemometrics in Quality Assurance

Quality Assurance Considerations

Environmental Sampling Protocol—General Considerations

Quality Assurance: Sample Collection, Preparation and Storage

Field QA/QC Samples

Laboratory and Instrumental Methods: QA/QC Samples

Standard Addition and Internal Standard Methods

Certified Reference Materials

Statistical Quality Control Charts

Proficiency Testing

Data Archiving, Storage, and Auditing

Multivariate Quality Assurance/Control—Initial Considerations

Expanded Research Application II—Monte Carlo Simulation for Estimating Uncertainty Intervals for the Determination of Nitrate in Drinking Water

Chapter Summary

End of Chapter Problems


Experimental Design and Optimization Techniques

System Theory

Review of Linear Regression Models and Matrix Notation

Experimental Design Considerations

Single Factor Categorical Designs

Screening Designs

Three-Level Designs: Response Surface Methodology

Doehlert Matrix Design

Mixture Designs

Expanded Research Application III—Optimized Separation of Benzo[a]Pyrene-Quinone Isomers Using Liquid Chromatography-Mass Spectrometry (LC-MS) and Response Surface Methodology

Chapter Summary

End of Chapter Problems


Time Series Analysis

Introduction to Time Series Analysis

Smoothing and Digital Filtering

Times Series and Forecast Modeling—A Detailed Look

ARIMA models

Outliers in Time Series Analysis

Export Coeffi cient Modeling

Expanded Research Application IV—Export Coefficient Modeling and Time Series Analysis of Phosphorus in a Chalk Stream Watershed

Chapter Summary

End of Chapter Problems

References 02

Multivariate Data Analysis

Introduction to Multivariate Data Analysis

Data Preprocessing

Correlation Analysis

Pattern Recognition—Unsupervised

Pattern Recognition—Supervised

K-Nearest Neighbor Classification

Soft Independent Modeling of Class Analogy (SIMCA)

Multivariate Calibration Methods

Multivariate T 2 Control Charts

Cusum Control Charts

Soft Computing Techniques

Expanded Research Application—A Multivariate Study of the Relations Between PM10 Composition and Cell Toxicity

Chapter Summary

End of Chapter Problems


Appendix I: Common Excel® Shortcuts and Key Combinations

Appendix II: Symbols Used in Escuder-Gilabert et al. (2007)

Appendix III: Review of Basic Matrix Algebra Notation and Operations

Appendix IV: Environmental Chain of Custody


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