Handbook of Water Analysis - Taylor & Francis

© 2011 Taylor & Francis Group, LLC

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T H I R D E D I T I O N

E D I T E D B Y

L e o M . L . N o l l e tL e e n S . P. D e G e l d e r

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Contents

Preface ...................................................................................................................................................... ixEditors ....................................................................................................................................................... xiContributors ............................................................................................................................................xiii

Section I Sampling and Data Treatment Methods

1. Sampling Methods in Surface Waters ............................................................................................ 3Munro Mortimer, Jochen F. Müller, and Matthias Liess

2. Methods of Treatment of Data ...................................................................................................... 47Riccardo Leardi

Section II Radioanalytical Analysis

3. Radioanalytical Methodology for Water Analysis ...................................................................... 79Jorge S. Alvarado

Section III Organoleptical Analysis

4. Organoleptical Methodology ........................................................................................................101Abdul Moheman, Md. Musawwer Khan, and K. S. Siddiqi

Section IV Analysis of Biological Parameters

5. Bacteriological Analysis of Water ................................................................................................115Paulinus Chigbu and Salina Parveen

6. Marine Toxins Analysis ................................................................................................................153Luis M. Botana, A. Alfonso, M. R. Vieytes, N. Vilariño, A. M. Botana, C. Louzao, and C. Vale

7. Algal Analysis ................................................................................................................................163Leonardo Rubi Rörig

Section V Halogens, N-Compounds, and Phosphates

8. Halogens .........................................................................................................................................189Géza Nagy and Livia Nagy

9. Analysis of Sulfur Compounds in Water ................................................................................... 233Leo M. L. Nollet

vi Contents


10. Determination of Ammonia in Water Samples ......................................................................... 249Juliana Antunes Galvão, Alexandre Matthiensen, Marília Oetterer, Y. Moliner-Martínez, R. A. Gonzalez-Fuenzalida, M. Muñoz-Ortuño, R. Herráez-Hernández, J. Verdú-Andrés, C. Molins-Legua, and P. Campíns Falcó

11. Nitrites and Nitrates ..................................................................................................................... 283Adnan Aydın

12. Phosphates in Aquatic Systems ................................................................................................... 327Alexandre Matthiensen, Juliana Antunes Galvão, and Marília Oetterer

Section VI Cyanides, Asbestos, Metals, and Si-Compounds

13. Cyanides ........................................................................................................................................ 365Leo M. L. Nollet

14. Asbestos in Water ......................................................................................................................... 379James S. Webber

15. Heavy Metals, Major Metals, Trace Elements .......................................................................... 385Jorge E. Marcovecchio, Sandra E. Botté, Claudia E. Domini, and Rubén H. Freije

16. Determination of Silicon and Silicates ........................................................................................435Salah M. Sultan

Section VII Organic Parameters

17. Main Parameters and Assays Involved with the Organic Pollution of Water ....................... 459Lorena Vidal, Claudia E. Domini, and Antonio Canals

18. Determination of Organic Nitrogen in the Aquatic Environment .......................................... 493Juliana Antunes Galvão, Alexandre Matthiensen, and Marília Oetterer

19. Determination of Urea in Aquatic Samples ................................................................................511Juliana Antunes Galvão, Alexandre Matthiensen, and Marília Oetterer

20. Organic Acids ................................................................................................................................521Mercedes Gallego Fernández, Evaristo Ballesteros Tribaldo, and Beatriz Jurado Sánchez

21. Determination of Volatile Organic Compounds in Water ....................................................... 549Iván P. Román Falcó and Marta Nogueroles Moya

Section VIII Phenolic and Humic Compounds

22. Determination of Phenolic Compounds in Water ......................................................................613Leo M. L. Nollet

23. Characterization of Humic Matter ............................................................................................. 647Leo M. L. Nollet

viiContents


Section IX Residues of Pesticides

24. Determination of Pesticides in Water ......................................................................................... 665Evaristo Ballesteros Tribaldo

25. Analysis of Herbicide and Fungicide Residues in Waters ........................................................ 697N. Sridhara Chary, Maria Jose Gómez Ramos, and Amadeo R. Fernández-Alba

Section X Residues of PCBs, PCDDs, PCDFS, and PAHs

26. Analysis of PCBs in Waters ......................................................................................................... 765L. Bartolomé, O. Zuloaga, and N. Etxebarria

27. PCDDs and PCDFs ...................................................................................................................... 789Luigi Turrio-Baldassarri, Paola Pettine, and Laura Achene

28. Polynuclear Aromatic Hydrocarbons ......................................................................................... 807Chimezie Anyakora

Section XI Surfactants and Petroleum Hydrocarbon Analysis

29. Surfactants .................................................................................................................................... 825Eva Pocurull and Rosa Maria Marcé

30. Petroleum Hydrocarbon Analysis .............................................................................................. 845Iván P. Román Falcó

Section XII EDCs and Residues of Plastics

31. Endocrine-Disrupting Chemicals, Pharmaceuticals, and Personal Care Products .............. 871Dimitra A. Lambropoulou and Eleni Evgenidou

32. Residues of Plastics .......................................................................................................................917Dimitra A. Lambropoulou and Eleni Evgenidou

ix© 2011 Taylor & Francis Group, LLC

Preface

The Handbook of Water Analysis, Third Edition, strives to provide the most comprehensive text available in terms of the physicochemical and biological properties and analysis techniques of all types of water.

Organized in sections, most chapters cover the physical, chemical, and other relevant properties of a particular subset of water components, followed by a description of sampling, cleanup, extraction, and derivatization procedures, and concluding with detection methods. Earlier techniques that are still frequently in use are compared to recently developed protocols, and an outlook is provided on future trends. Figures are incorporated to provide procedure �ow charts and schematics concerning sampling or analytical devices. Numerous tables categorizing methods according to type of component, origin of the water sample, parameters and procedures used, and application range, facilitate the search for further references.

Section I of the book lays out two crucial aspects besides the actual analysis procedures. Sound scien-ti�c investigation starts with a sampling strategy designed to capture the real-world situation as closely as possible, and ends with an adequate chemometrical and statistical treatment of the acquired data.

Section II summarizes health and environmental problems due to radionuclides in water and presents new techniques for their determination.

Section III regarding organoleptical analysis of water acknowledges that ultimately the consumers of drinking water have the �nal vote over its quality regarding odor, �avor, and color.

Water houses many organisms, of which the smallest may cause illness and produce toxic substances. Section IV discusses bacteriological and algal analysis, as well as the occurrence and detection of marine toxins.

Sections V through XII encompass harmful or toxic components originating from domestic, agricul-tural, or industrial sources that can be found in different waters. Inorganic substances include nitrogen, sulfur, phosphate, silica, and halogenated compounds, cyanides, (heavy) metals, and asbestos. Organic compounds comprise organic nitrogen and acids, volatile and phenolic compounds, and humic mat-ter. The main groups of anthropogenic polluting compounds are discussed: pesticides, PCBs, PCDDs, PCDFS, PAHs, petroleum hydrocarbons, and surfactants.

Speci�c chapters in these sections are also dedicated to the challenging category of micropollut-ants, such as endocrine disrupting compounds, pharmaceutical and personal care products and plastic residues.

This book aims to be a reference work for anybody learning about or carrying out water analysis, from undergraduate and graduate students to scienti�c researchers and technicians in academic, governmen-tal, industrial, or nonpro�t sectors.

All contributors are international experts in their �eld of water analysis, whom we would like to thank cordially for all their efforts.

This book is dedicated to three granddaughters, Fara, Fleur, and Kato, and two grandsons Naut and Roel and two daughters, Hanne and Mona, for whom we wish that they can always enjoy fresh, clean water in their lifetime.

It is far more impressive when others discover your good qualities without your help.

— Judith Martin

xi© 2011 Taylor & Francis Group, LLC

Editors

Leo M. L. Nollet received an MS (1973) and a PhD (1978) in biology from the Katholieke Universiteit Leuven, Belgium. Dr. Nollet is the editor and associate editor of numerous books. He edited for Marcel Dekker, New York—now CRC Press of Taylor & Francis Group—the �rst, second, and third editions of Food Analysis by HPLC and Handbook of Food Analysis. The last edition is a three-volume book. He also edited the Handbook of Water Analysis (�rst and second editions) and Chromatographic Analysis of the Environment, third edition (CRC Press).

With F. Toldrá he coedited two books published in 2006 and 2007: Advanced Technologies for Meat Processing (CRC Press) and Advances in Food Diagnostics (Blackwell Publishing—now Wiley). With M. Poschl he coedited Radionuclide Concentrations in Foods and the Environment also published in 2006 (CRC Press).

Dr. Nollet coedited several books with Y. H. Hui and other colleagues such as the Handbook of Food Product Manufacturing (Wiley, 2007), Handbook of Food Science, Technology and Engineering (CRC Press, 2005), Food Biochemistry and Food Processing, �rst and second editions (Blackwell Publishing—Wiley, 2006 and 2012), and Handbook of Fruits and Vegetable Flavors (Wiley, 2010). He edited the Handbook of Meat, Poultry and Seafood Quality, �rst and second editions (Blackwell Publishing—Wiley, 2007 and 2012).

From 2008 to 2011 he published �ve volumes with F. Toldrá in animal products–related books: Handbook of Muscle Foods Analysis, Handbook of Processed Meats and Poultry Analysis, Handbook of Seafood and Seafood Products Analysis, Handbook of Dairy Foods Analysis, and Handbook of Analysis of Edible Animal By-Products. Also in 2011 with F. Toldrá he coedited two volumes for CRC Press: Safety Analysis of Foods of Animal Origin and Sensory Analysis of Foods of Animal Origin. In 2012 Nollet and Toldrá published the Handbook of Analysis of Active Compounds in Functional Foods.

Coediting with Hamir Rathore, the book Handbook of Pesticides: Methods of Pesticides Residues Analysis was marketed in 2009 and Pesticides: Evaluation of Environmental Pollution in 2012.

Other completed book projects are Food Allergens: Analysis, Instrumentation, and Methods with A. van Hengel (CRC Press, 2011) and Analysis of Endocrine Compounds in Food (Wiley-Blackwell, 2011).

Leen S. P. De Gelder is a professor of microbiology, biochemical technology, and environmental bio-technology at the Faculty of Bioscience Engineering of Ghent University, Belgium. Her main research interests include applied microbiology, microbial ecology, biodegradation and biological waste water treatment. She received her MS in bioengineering (2002) from the University of Ghent, Ghent, Belgium and her PhD in biology (2006) from the University of Idaho, Moscow, USA, and is the author or coauthor of several peer-reviewed articles and conference abstracts.

xiii© 2011 Taylor & Francis Group, LLC

Laura AcheneIstituto Superiore di SanitàRome, Italy

A. AlfonsoDepartment of PharmacologyCampus de Lugo, USCLugo, Spain

Jorge S. AlvaradoEnvironmental Science DivisionArgonne National LaboratoryArgonne, Illinois

Chimezie AnyakoraDepartment of Pharmaceutical ChemistryUniversity of LagosLagos, Nigeria

Adnan AydınDepartment of ChemistryMarmara UniversityIstanbul, Turkey

L. Bartolomé General Research ServiceUniversity of the Basque Country (UPV/EHU)Bizkaia, Spain

A. M. BotanaDepartment of Analytical ChemistryCampus de Lugo, USCLugo, Spain

Luis M. BotanaDepartment of PharmacologyCampus de Lugo, USCLugo, Spain

Sandra E. BottéArea de Oceanogra�a QuimicaInstituto Argentino de Oceanogra�a

(IADO-CONICET/UNS)Casilla de CorreoBahia Blanca, Argentina

Antonio Canals Departamento de Química AnalíticaNutrición y Bromatología e Instituto

Universitario de MaterialesUniversidad de AlicanteAlicante, Spain

N. Sridhara CharyIMDEA-Water (Madrid Institute for Advanced

Studies-Water) Cienti�co de la Universidad de AlcalaAlcalá de HenaresMadrid, Spain

Paulinus ChigbuDepartment of Natural SciencesUniversity of Maryland Eastern ShorePrincess Anne, Maryland

Claudia E. Domini Departamento de QuímicaUniversidad Nacional del SurBahía Blanca, Argentina

N. EtxebarriaDepartment of Analytical ChemistryUniversity of the Basque Country

(UPV/EHU)Biscay (Basque Country), Spain

Eleni EvgenidouDepartment of ChemistryAristotle University of ThessalonikiThessaloniki, Greece

Iván P. Román FalcóDepartment of Analytical Chemistry and

Food SciencesUniversity of AlicanteAlicante, Spain

P. Campíns FalcóDepartamento de Química AnalíticaUniversitat de ValenciaValencia, Spain

Contributors

xiv Contributors


Mercedes Gallego FernándezDepartment of Analytical ChemistryUniversity of CórdobaCórdoba, Spain

Amadeo R. Fernández-Alba IMDEA-Water (Madrid Institute forAdvanced

Studies-Water)Cienti�co de la Universidad de AlcalaAlcalá de HenaresMadrid, SpainandPesticide Residue Research GroupUniversity of AlmeríaAlmería, Spain

Rubén H. Freije Area de Oceanogra�a QuimicaInstituto Argentino de Oceanogra�a


Juliana Antunes GalvãoDepartment of Agri-Food IndustryUniversity of São PauloSão Paulo, Brazil

R. A. Gonzalez-FuenzalidaDepartamento de Química AnalíticaUniversitat de ValenciaValencia, Spain

R. Herráez-HernándezDepartamento de Química AnalíticaUniversitat de ValenciaValencia, Spain

Musawwer KhanDepartment of ChemistryAligarh Muslim University Aligarh, India

Dimitra A. LambropoulouDepartment of ChemistryAristotle University of ThessalonikiThessaloniki, Greece

Riccardo LeardiDepartment of PharmacyUniversity of GenovaGenova, Italy

Matthias LiessDepartment of System-EcotoxicologyUFZ-Helmholtz-Zentrum für Umweltforschung

GmbHLeipzig, Deutschland

C. LouzaoDepartment of PharmacologyCampus de Lugo, USCLugo, Spain

Rosa Maria MarcéDepartment of Analytical Chemistry and

Organic ChemistryUniversitat Rovira i VirgiliTarragona, Spain

Jorge E. MarcovecchioArea de Oceanogra�a QuimicaInstituto Argentino de Oceanogra�a


Alexandre Matthiensen Department of Agri-Food IndustryUniversity of São PauloSão Paulo, BrazilandEmbrapa-Brazilian Agricultural Research

CorporationEmbrapa Swine and PoultrySanta Catarina, Brazil

Abdul MohemanDepartment of ChemistryAligarh Muslim UniversityAligarh, India

Y. Moliner-MartínezDepartamento de Química AnalíticaUniversitat de ValenciaValencia, Spain

C. Molins-LeguaDepartamento de Química AnalíticaUniversitat de ValenciaValencia, Spain

Munro MortimerNational Research Centre for Environmental

ToxicologyThe University of QueenslandBrisbane, Australia

xvContributors


Marta Nogueroles MoyaDepartment of Analytical Chemistry and Food

SciencesUniversity of AlicanteAlicante, Spain

Jochen F. MüllerNational Research Centre for Environmental

ToxicologyThe University of QueenslandBrisbane, Australia

M. Muñoz-OrtuñoDepartamento de Química AnalíticaUniversitat de ValenciaValencia, Spain

Géza NagyDepartment of General and Physical

ChemistryUniversity of PécsPécs, Hungary

Livia NagyDepartment of General and Physical

ChemistryUniversity of PécsPécs, Hungary

Leo M. L. Nollet (Retired)University College GhentGent, Belgium

Marília Oetterer Department of Agri-Food IndustryUniversity of São PauloSão Paulo, Brazil

Salina ParveenDepartment of Agriculture, Food and Resource

SciencesUniversity of Maryland Eastern ShorePrincess Anne, Maryland

Paola PettineIstituto Superiore di SanitàRome, Italy

Eva PocurullDepartment of Analytical Chemistry and

Organic ChemistryUniversitat Rovira i VirgiliTarragona, Spain

Maria Jose Gómez RamosIMDEA-Water (Madrid Institute forAdvanced

Studies-Water)Cienti�co de la Universidad de AlcalaAlcalá de HenaresMadrid, SpainandPesticide Residue Research GroupUniversity of AlmeríaAlmería, Spain

Leonardo Rubi RörigDepartment of BotanyFederal University of Santa CatarinaSanta Catarina, Brazil

Beatriz Jurado SánchezDepartment of Analytical ChemistryUniversity of CórdobaCórdoba, Spain

K. S. SiddiqiDepartment of ChemistryAligarh Muslim UniversityAligarh, India

Salah M. SultanSamf Pharmaceutical Co, WLLTubli, Bahrain

Evaristo Ballesteros TribaldoDepartment of Physical and Analytical

ChemistryUniversity of JaénJaén, Spain

Luigi Turrio-BaldassarriIstituto Superiore di SanitàRome, Italy

C. ValeDepartment of PharmacologyCampus de Lugo, USCLugo, Spain

J. Verdú-AndrésDepartamento de Química AnalíticaUniversitat de ValenciaValencia, Spain

xvi Contributors


Lorena Vidal Departamento de Química AnalíticaUniversidad de AlicanteAlicante, Spain

M. R. VieytesDepartment of PhysiologyCampus de Lugo, USCLugo, Spain

N. VilariñoDepartment of PharmacologyCampus de Lugo, USCLugo, Spain

James S. WebberWadworth CenterNew York State Department of HealthAlbany, New York

O. Zuloaga Department of Analytical ChemistryUniversity of the Basque Country

(UPV/EHU)Biscay (Basque Country), Spain


Section I

Sampling and Data Treatment Methods

3© 2011 Taylor & Francis Group, LLC

1Sampling Methods in Surface Waters

Munro Mortimer, Jochen F. Müller, and Matthias Liess

CONTENTS

1.1 Introduction ...................................................................................................................................... 41.2 General Aspects of Sampling and Sample Handling ...................................................................... 5

1.2.1 Initial Considerations .......................................................................................................... 51.2.2 Spatial Aspects .................................................................................................................... 61.2.3 Temporal Aspects ................................................................................................................ 61.2.4 Number of Samples ............................................................................................................. 71.2.5 Sample Volume .................................................................................................................... 71.2.6 Storage and Conservation .................................................................................................... 7

1.2.6.1 Contamination...................................................................................................... 71.2.6.2 Loss ...................................................................................................................... 81.2.6.3 Sorption ................................................................................................................ 81.2.6.4 Recommended Storage ........................................................................................ 91.2.6.5 Quality Control in Water Sampling ....................................................................16

1.3 Sampling Strategies for Different Ecosystems ...............................................................................161.3.1 Lakes and Reservoirs .........................................................................................................161.3.2 Streams and Rivers .............................................................................................................17

1.3.2.1 Location of Sampling within the Stream ............................................................171.3.2.2 Description of the Longitudinal Gradient ..........................................................181.3.2.3 Temporal Changes of Water Quality ..................................................................181.3.2.4 Using Sediments to Integrate over Time ........................................................... 19

1.3.3 Estuarine and Marine Environments ................................................................................ 191.3.4 Urban Areas ....................................................................................................................... 201.3.5 Wastewater Systems .......................................................................................................... 21

1.4 Sampling Equipment ...................................................................................................................... 221.4.1 General Comments ............................................................................................................ 221.4.2 Manual Sampling Systems ................................................................................................ 22

1.4.2.1 Simple Sampler for Shallow Water .................................................................... 221.4.2.2 Sampler for Large Quantities in Shallow Water ................................................ 221.4.2.3 Simple Sampler for Deepwater .......................................................................... 221.4.2.4 Deepwater Sampler (Not Adding Air to the Sample) ........................................ 231.4.2.5 Deepwater Sampler for Trace Elements (Allowing Air to Mix

with the Sample) ................................................................................................ 231.4.3 Systems for Sampling the Benthic Boundary Layer at Different Depths ......................... 26

1.4.3.1 Deepwater (>50 m) ............................................................................................. 261.4.3.2 Shallow Water (<50 m) ...................................................................................... 26

1.4.4 Automatic Sampling Systems ............................................................................................ 261.4.4.1 Sampling Average Concentrations ..................................................................... 261.4.4.2 Sampling Average Concentrations: Sampling Buoy .......................................... 261.4.4.3 Event-Controlled Sampling of Industrial Short-Term Contamination .............. 271.4.4.4 Rapid Underway Monitoring ............................................................................. 27

4 Handbook of Water Analysis


1.1 Introduction

A U.S. Environmental Protection Agency (USEPA) wastewater sampling handbook published three decades ago lists four basic factors that affect the quality of environmental data—sample collection, sample preservation, analyses, and recording, and warns that improper actions in any one of these “may result in poor data from which poor judgements are certain” [1]. That advice is as relevant today as it was then—the quality of output from an environmental sampling project is limited by whichever is the weakest component—whether that occurs during sampling or analysis.

Progress in analytical protocols, including the development of new and more sophisticated tech-niques described elsewhere in this handbook, results in the taking of samples increasingly becoming the quality- determining step in water quality assessment [2,3]. Conclusions based on laboratory results from the most careful analysis of water samples may be invalidated because the original collection of the samples was inadequate or invalid. Poor sampling design or mistakes in sampling technique or sample handling during the sampling process inevitably lead to erroneous results, which cannot be corrected afterward [4–8]. For example, a recent review [9] found that in sampling from sources inherently vari-able in terms of �ow rate and contaminant concentrations, less than 5% of studies explicitly considered internationally acknowledged guidelines or methods for the experimental design of monitoring. Thus, owing to relatively long sampling intervals, potentially inadequate sampling methods, or insuf�cient documentation, it was unclear whether observed variations were actually “real” variations or merely sampling artifacts. Further, despite the critical role of an appropriate sampling protocol in ensuring good quality data, the review noted that in almost all papers, the descriptions of analytical methods usually extended over several paragraphs and up to several pages, but sampling methodology was covered in one or two sentences, with justi�cation for choice of protocol generally more implicit than explicit.

The objective of this chapter is to describe and discuss methods for environmental sampling in surface waters (lakes, rivers, and the marine environment). This aspect of sampling is of major importance in view of the increasing concern about environmental contamination and its correct description and moni-toring. Conventional methods used for sampling solid material differ considerably and are not covered in this chapter. However, where appropriate, a short discussion of sampling of suspended particulates (mineral or organic sediments) is included. These water-associated solids are of great importance for the less water-soluble chemicals (like many insecticides) since such chemicals are dynamically distributed between the small suspended particles and the water phase.

One of the basic problems of environmental water analysis is that, generally, it must be carried out with selected portions (i.e., samples) of the water of interest, and the quality of this water must then be inferred from that of the samples. If the quality is essentially constant in time and space, this inference would present no problem. However, such constancy is rare if ever observed in the real world; in most circumstances, virtually all waters show both spatial and temporal variations in quality. It follows that the timing and choice of location for taking water samples must be chosen with great care. Also, since an increase in the number of sampling locations and sampling occasions increases the cost of the mea-surement program, it is important to attempt to de�ne the minimal number of sampling positions and occasions needed to provide the desired information.

1.4.4.5 Event-Controlled Sampling: Surface Water Runoff from Agricultural Land ................................................................................................................... 291.4.4.6 Other Considerations Regarding Automatic Sampling Equipment ................... 30

1.4.5 Extraction Techniques ....................................................................................................... 321.4.5.1 Liquid–Liquid Extraction of Large Volumes .................................................... 321.4.5.2 Solid-Phase Extraction Techniques ................................................................... 321.4.5.3 Passive Sampler Devices .................................................................................... 35

1.4.6 Concentration of Contaminants in Suspensions and Sediment ........................................ 391.4.6.1 Suspended-Particle Sampler for Small Streams ................................................ 39

Acknowledgment ..................................................................................................................................... 42References ................................................................................................................................................ 42



The whole process of analyzing a material consists of several steps: sampling, sample storage, sample preparation, measurement, evaluation of results, comparison with standards or threshold values, and assess-ment of results. This chapter is concerned with sampling strategy, storage of samples, and sampling equip-ment. Further steps will be described and discussed in the following chapters on speci�c chemical groups.

Section 1.2 focuses on some general aspects of sampling design and some characteristics of the sub-stances to be sampled and analyzed, since properties such as degradation or sorption that may occur after sample collection can substantially affect the results. Section 1.3 gives an overview of sampling strategies in different ecosystems. The temporal and spatial scaling of sampling depends to a great extent on the ecosystem under study and on the question being addressed by the study. Finally, Section 1.4 describes some types of sampling equipment and their speci�c properties. This part covers general methods as well as speci�c methods like deepwater sampling, event-controlled sampling, large-volume sampling, and time-integrated (passive sampling) methods.

1.2 General Aspects of Sampling and Sample Handling

1.2.1 Initial Considerations

It can be said that there are as many approaches to sampling as there are possible moves in a chess game. First, the situation to be assessed must be accurately de�ned. Then, an appropriate sampling design should be chosen on the basis of temporal and spatial processes of the part of the ecosystem under inves-tigation to ensure that the samples are truly representative of the system from which they are taken. This is a prerequisite to providing meaningful analytical results. Handling, preservation, and storage of the samples should be adapted to the properties of the chemicals of interest and the effort invested should be optimized to obtain the necessary information with such resources as are available. To achieve these objectives, the following considerations are useful (Figure 1.1).

Define time and frequencyof sampling

Define objectivesand accuracy required

Define locationsof sampling

Choose analytical methods,sampling volume

Choose sampling methods

Define sample stabilizationand transport

Define analytical procedures

Interpretation on the basis of–assessed accuracy

–sampling design (arrows)

FIGURE 1.1 Initial considerations for planning and carrying out sampling procedures.



1.2.2 Spatial Aspects

Sampling for quality control of material in the metal or food industry normally follows statistical approaches to ensure that relatively small subsamples will be representative of the material as a whole. Although simi-lar requirements exist for environmental sampling, the principal difference is that spatial variation is gener-ally very much greater in the case of environmental contamination. Currents in �owing water and marine ecosystems must be considered. Very often, strati�cation crucially affects the distribution of substances of interest, especially in lakes (see Section 1.3.1). The chosen locations for environmental sampling must be related to the expected sources of contamination, for example, different distances downstream of a sewage ef�uent discharge point. A detailed description and understanding of the exact sampling site (locational coordinates, longitudinal gradient, lateral gradient, depth, water level, and distance to possible sources of contamination) is a basic requirement of designing an adequate sampling program.

1.2.3 Temporal Aspects

The temporal pattern of sampling is of great importance if the environment to be sampled shows changes over time, for example, river systems within minutes or hours, or lakes within days or weeks. The sched-ule of the sampling program depends mainly on the expected temporal resolution of changes in the envi-ronment. In governmental programs for monitoring wastewater-treatment ef�uents, sampling around the clock may be required to determine whether control variables have been met or exceeded.

A single sample gives only a snapshot of the situation, and the power and reliability of the results are normally low and depend strongly on the background data and additional information available. However, the advantage is that often the equipment necessary for this type of sampling is very simple and inexpensive.

If many samples are taken over a period of time, it is often appropriate to match the sampling rate to the expected pattern of variation in the environment. For example, to detect peak concentrations during short-term changes of water quality, event-controlled samplers are useful. When it is necessary to quan-tify a contaminant load, discontinuous sampling systems may be needed. Various types of discontinuous sampling that are of special importance for quality control purposes and for automatic wastewater sam-pling in accordance with international standards (ISO 5667-10) are illustrated in Figure 1.2. If sampling is time proportional, then samples containing identical volumes are taken at constant time intervals. In discharge-proportional sampling, the time intervals are constant but the volume of each sample is

Q

t

Q

tTime proportional

Q

tDischarge proportional

Q

tQuantity proportional

FIGURE 1.2 Different types of discontinuous sampling.



proportional to the volume of discharge during the speci�c time interval. In quantity-proportional sam-pling (or �ow-weighted sampling), the volume of each sample is constant but the temporal resolution of sampling is proportional to the discharge. The last type is event-controlled sampling, which depends on a trigger signal (e.g., discharge threshold), which is discussed in Section 1.4.5.

In addition to single and discontinuous sampling, continuous sampling and determination of analyti-cal values is desirable in some cases. An example is the quality control for a very complex ef�uent with unpredictable temporal changes in composition that are not linked to possible trigger variables like discharge or temperature. For this purpose, automatic sampling and in some cases automatic analyzing units are useful. The expenditure of time and money is in general considerably higher for this type of sampling and cannot always be justi�ed.

Another important type of sample is a composite sample generated by mixing several single samples, or a composite of samples accumulated during an automatic sampling program. Composite samples can also be generated by mixing discontinuous samples collected according to any of the types discussed previously and depicted in Figure 1.2.

1.2.4 Number of Samples

The number of samples required depends on the problem to be addressed. If an average concentration is to be obtained from several samples, a general calculation of the necessary number of samples N can be done using the following equation:

N

Sxd

=

42

where S is the estimate of standard deviation of the arithmetic mean of all single samples, x is the estimate of arithmetic mean of all single samples, and d is the tolerable uncertainty of the result, for example, 20% (d = 0.2).

If peak concentrations are to be quanti�ed, the number of samples depends on the speci�c problem.

1.2.5 Sample Volume

The appropriate sample volume depends on the elements or substances required to be analyzed on their expected concentration in the sample and on the required quanti�cation limits. For trace metal analyses, sample volumes of about 100 mL are suf�cient in most cases. For the analysis of organic chemicals (e.g., pesticides), 1 L samples are commonly used. A 3 L sample volume has been suggested for both �rst-�ush and �ow-weighted composite samples in the monitoring of storm water runoff from industries and municipalities [10]. Fox [11] described an apparatus and procedure for the collection, �ltration, and subsequent extraction of 20 L water and suspended-solid samples using readily available, inexpensive, and sturdy equipment. With this equipment, he obtained quanti�cation limits for several organochlorine (OC) substances at nanogram per liter levels.

1.2.6 Storage and Conservation

Samples that are not analyzed immediately must be protected from addition of contaminants, loss of determinants by sorption or other means, and any other unintended changes that affect the concentra-tions of determinants of interest. For this purpose sample bottles should be chosen for long-term storage with no or as few changes to sample composition as possible.

1.2.6.1 Contamination

An unintended contamination of samples can occur during the sampling process, either from external sources or from contaminated sampling or storage equipment. Normally, polyethylene or Te�on® bottles are used in inorganic, and glass or quartz bottles in organic trace analysis. Organic compounds have



been known to leach from the bottle material into the sample, react with the trace elements under study, and cause systematic mistakes. Such problems become very important at detection limits below the microgram per gram level.

Some publications recommend that each sample container should be rinsed two or three times with sample before �nally being �lled. However, this may lead to errors when undissolved materials, and perhaps also readily adsorbed substances, are of interest. It is suggested not to rinse containers with the sample when trace organic compounds are of interest [4], and in particular when sampling for determi-nants that adsorb to container surfaces.

Empirical studies have shown that poly(tetra�uoroethylene) (PTFE) and poly(vinylidene di�ouride) (PVDF) can be of varying purity, often resulting in unexpected contamination problems in ultratrace analysis, whereas per�uoroalkoxy (PFA) �uorocarbon proved to be cleaner by origin, and consequently, acidic washing processes could be successfully applied. These different �uorinated polymers have been compared regarding their suitability for container or sampler material [10]. It has been found that PFA exhibits the lowest nanoroughness and hence seems best suited as container material.

1.2.6.2 Loss

Loss during storage can result from biological processes, hydrolysis, or evaporation. Available proce-dures to reduce or prevent these loss processes include:

• Acidification to pH between 1 and 2: prevention of metabolism by microorganisms and of hydrolysis and precipitation

• Cooling and freezing: reduction of bacterial activity

• Addition of complexing substances: reduction of evaporation

• UV irradiation (together with addition of H2O2): destruction of biological and organic com-pounds to prevent complexation reactions

Loss of target elements can also occur due to volatilization. When contact of the sample with air is to be avoided (because it contains dissolved gases or volatile substances), sample containers or sample bottles should be completely �lled. Evaporation is a problem during storage of mercury under reducing conditions; other elements evaporate as oxides (e.g., As, Sb), halogenides (e.g., Ti, Cr, Mo), or hydrides (e.g., As, Sb, Se), or they are able to diffuse through the walls of plastic bottles. Volatilization is a special problem in the case of organic compounds like hydrocarbons or halogenated hydrocarbons.

1.2.6.3 Sorption

Sorption to the walls of sample bottles can reduce the concentration in the water phase considerably. Depending on the target substances, plastic or quartz bottles show the lowest adsorption and can, there-fore, be used for the storage of samples in aqueous solution. In general, the wall material of storage bottles can change over time and the potential for adsorption of target substances can increase consider-ably. In the case of many metals, this problem can be reduced by acidifying the sample.

The af�nity to glass and PTFE of selected OC, pyrethroid, and triazine pesticides at concentrations ≤0.25 μg L−1 has been described [11]. For the OC pesticides, the adsorption behavior correlates well with octanol–water partition coef�cients. For triazines, sorption to glass or PTFE is negligible, whereas for the pesticides α-BHC, lindane, dieldrin, and endrin are weakly adsorbed relative to DDT, DDE, TDE, permethrin, cypermethrin, and fenvalerate. Adsorption constants Ka (= amount of adsorbed pesticide per unit area of surface) have been calculated (Table 1.1) by these authors to quantify the sorption af�nity of the compounds on glass and PTFE:

Ka

Amount of sorbed pesticideper unitareaof surface,ngcmConce

=−2

nntration in aqueous solution ngcm, −3



As an example, the adsorption of fenvalerate on a Duran glass surface is calculated using the above equation: A bottle with a surface area of 325 cm2 contains 500 mL of an aqueous solution of fenvalerate. After 48 h under these circumstances, approximately 84% of the fenvalerate is adsorbed to the glass sur-face and only about 16% remains in solution, with the concentration in water reduced accordingly (e.g., from an initial concentration of 10 ng mL−1 in a 500 mL bottle, 4.2 ng are adsorbed and 0.8 ng stays in solution, a concentration of only 1.6 ng mL−1). For lindane and permethrin, 0.32% and 96%, respectively, of the chemical are absorbed to the glass surface after 48 h.

The role of �ltration of water samples at the time of collection and in relation to storage and preser-vation of the sample is often an important consideration. Many substances of interest may be present in a water sample in particulate as well as soluble form. Filtration removes particulate matter so that a decision on whether to �lter at the point of collection will depend on the objectives of the study. Another consideration relevant to �ltration and the possible presence of particulate matter are the effects on such matter of adding a sample preservative such as acid. Generally, it is a sound practice to �lter before add-ing a preservative that may solubilize particulate matter or leach contaminants from it.

In the case of water samples that contain microscopic cellular matter such as algae, the potential effects of �ltration, added preservatives, and freezing as a means of preservation, each need to be con-sidered. Filtration will remove microscopic cellular matter, and along with it determinants that may be relevant to the study. On the other hand, some preservatives, and certainly freezing, can cause cells to rupture and release materials that may be of relevance. Guidance to appropriate courses of action is provided in the section that follows.

1.2.6.4 Recommended Storage

For quality control and for the use of analytical results in forensic chemistry, national and international standardizations are necessary. Several international standards (ISO) have been de�ned for water quality sampling. These cover, among other topics, guidance on the design of sampling programs [12], sampling techniques [13], and the preservation and handling of water samples [14]. An alternative source of advice is a compilation of the USEPA’s recommended sampling and analysis methods, which also covers sample preservation, sample preparation, quality control, and analytical instrumentation [15–17].

Even if the above-mentioned conservation methods are used, the storage period for water samples is limited. Table 1.2, derived from the current (2003 edition) international ISO standard [14], gives an overview of recommended sampling and storage bottles as well as conservation methods and maximum storage periods for different determinants in the sample.

TABLE 1.1

Mean Values of the Distribution Coef�cient Ka Calculated for Duran Glass and PTFE Containers (48 h at 25°C) with the Associated Deviations (in Brackets) Appropriate to the Range of Concentrations Determined in the Solution

Duran Glass Surface PTFE Surface

Pesticide Ka (cm)Concentration

Range (ng mL−1) Ka (cm)Concentration

Range (ng mL−1)

α-BHC 0.014 (0.007) 0.05 0.036 (0.011) 0.01–0.04

Lindane 0.005 0.04–0.12 0.048 0.04–0.07

Dieldrin 0.027 (0.009) 0.17–0.19 0.093 (0.009) 0.11–0.15

Endrin 0.019 (0.006) 0.19–0.21 0.059 (0.005) 0.12–0.18

DDD 0.226 (0.053) 0.09–0.11 0.887 (0.087) 0.01–0.07

DDE 1.35 (0.38) 0.03–0.05 5.94 (1.35) 0.005–0.02

DDT 0.87 (0.25) 0.04–0.07 2.028 (0.116) 0.008–0.04

Permethrin 1.44 (0.30) 0.01–0.07 3.32 (1.68) 0.001–0.01

Cypermethrin 43.3 (16.8) 0.002–0.007 11.61 (5.97) 0.002–0.007

Fenvalerate 8.15 (2.48) 0.002–0.03 11.8 (3.99) 0.002–0.01

Source: From House, W.A. and Ou, Z., Chemosphere, 24, 819, 1992. With permission.



TABLE 1.2

Recommended Storage Containers for Water Samples, with Preservation Options and Maximum Recommended Periods for Storage Prior to Analysis

AnalyteContainer

(Capacity mL) PreservationMaximum Time Recommended Notes

Acidity, alkalinity and hydrogen carbonates

P G 500or C air24 h On-site analysis preferable,

particularly for samples high in dissolved gases. Preservation to 14 days feasible

Acidic herbicides 1000 + PTFEcap liner and leave air space

G HCl C 2 weeks Do not prerinse with sample (analytes absorb to glass) and extract both container and sample. If chlorinated see Note 1

Adsorbable organic halides (AOX) and organic chlorine

P G 1000or airHNO3 C5 days

1000P F 1 month

AluminiumG orPA 100or BGA HNO3

1 month

Ammonia, free or ionized

P Gor 500 CH2SO421 days Filter on-site before

preservation

P 500 F 1 month Filter on-site before preservation

Anions (Br, F, Cl, NO2, NO3, SO4, and PO4)

P Gor 500 C 24 h Filter on-site before preservation

P 500 F 1 month Filter on-site before preservation

Antimony100GAPA or HCl HNO3or 1 month HCl should be used if

hydride technique used for analysis

Arsenic500GAPA or HCl HNO3or 1 month HCl should be used if

hydride technique used for analysis

Barium PA BGA 100or HNO31 month Do not use H2SO4

Beryllium100GAPA or HNO3

1 month

Biochemical oxygen demand (BOD)

P Gor 1000 air C24 h

P 1000 F 1 month Feasible to store 6 months if frozen and BOD <50 mg L−1

Boron P 100 air1 month Feasible to store 6 months

Bromate, bromide and bromine compounds

P Gor 100 C 1 month

Bromine residual P Gor 500 C24 h Analysis should be completed

on-site within 5 min of sample collection



TABLE 1.2 (continued)


AnalyteContainer


Cadmium PA BGA 100or HNO31 month Feasible to store 6 months

Calcium and hardness

P Gor 100 HNO31 month

Carbamate pesticides

GS 1000 C 14 days If chlorinated, see Note 1

P 1000 F 1 month If chlorinated, see Note 1

Carbon dioxide P Gor 500 C air24 h Preferable to measure on-site

Carbon, total organic (TOC)

P Gor 100 H2SO4 C 7 days Acidi�cation with H3PO4 is suitable. If volatile organics suspected, do not acidify, and analyse within 8 hP 100 F 1 month

Chemical oxygen demand

P Gor 100 H2SO41 month Feasible to store 6 months

P 100 F 1 month Feasible to store 6 months

Chloramine P Gor 500 5 min Analyse on-site within 5 min of collection

Chlorate P Gor 500 C 7 days

Chloride P Gor 100 1 month

Chlorinated solvents

250 + head space vial with PTFE cap

G HCl

C air

24 h For purge and trap, HCl interferes. If chlorinated, see Note 124 h

Chlorine dioxide/residual

P Gor 500 5 min Analyse on-site within 5 min of collection

Chlorite P Gor 500 C5 min Analyse on-site within 5 min

of collection

Chlorophyll P Gor 1000 C24 h

1000P filter, and extract with hot ethanol

F1 month

1000P F* filter1 month

Chromium100GAPA or HNO3

1 month Feasible to store 6 months

Chromium (VI)100GAPA or C 24 h

Cobalt PA BGA 100or HNO31 month Feasible to store 6 months

Colour P Gor 500 C5 days

continued





AnalyteContainer


Conductivity P BGor 100 C air24 h Analysis on-site preferable

Copper100GAPA or HNO3


Cyanide by diffusion at pH6

500P NaOHC 24 h

Cyanide easily liberated

500P NaOHC7 days Preservation only 24 h if

sulphide present

Cyanide, total500P NaOHC

7 days Feasible to store 6 months. Preservation only 24 h if sulphide present

Cyanochloride500P C 24 h

Fluorides200 not PTFEP 1 month

Hydrazine G 500 HCl24 h

Hydrocarbons and petroleum

GS 1000 HCl H2SO4or 1 month Bottle rinse solvent same as used for extraction. Do not prerinse bottle with sample (analytes absorb to glass)

Iodide G 500 C 1 month

Iodine G 500 C24 h

Iron (II) PA BGA 100or airHCl7 days

Iron, total PA BGA 100or HNO31 month

Kjeldahl nitrogen P BGor 250 H2SO41 month Feasible to store 6 months

250P F 1 month Feasible to store 6 months

LeadPA BGA 100or HNO3


Lithium250P 1 month

MagnesiumPA BGA 100or HNO3

1 month

ManganesePA BGA 100or HNO3

1 month

MercuryBGA 500 HNO3 K2Cr2O7

1 month K2Cr2O7 0.05% by �nal mass concentration

Monocyclic aromatic hydrocarbons

500 vials with PTFE-lined septum

G airH2SO4

7 days If chlorinated, see Note 1





AnalyteContainer


NickelPA BGA 100or HNO3


Nitrate P Gor 250 C 24 h

P Gor 250 HCl 7 days

P 250 F 1 month

Nitrite 200GorP C 24 h Analysis preferably on-site. Feasible to store 2 days

Nitrogen total 500GorP H2SO41 month

500P F 1 month

Odour 500G C 6 h Qualitative test can be conducted on site

Oil and grease GS 1000 HClorH2SO41 month

Organotin compounds

500G C 7 days Extraction on site preferable

Oxygen (dissolved)P Gor 300 C air

4 days On-site measurement preferable

Permanganate index

500GorP H2SO42 days Analyse as soon as possible,

acid 8 mol L−1

500GorP C2 days Analyse as soon as possible

500P F 1 month

Pesticides, (organochlorine, organophosphate, organo-nitrogen containing)

GS 1000 – 3000 + PTFE cap liner andleave air space

C 5 days (for extract)

Do not pre-rinse container with sample (analytes absorb to glass). Extraction within 24 hours of sampling is desirable. If chlorinated, see Note 1

1000 – 3000 only for glyphosate

P

pH 100GorP airC6 h On-site measurement

preferable

Phenol index1000G

See comments 21 days CuSO4 to inhibit biochemical oxidation, and acidify to pH < 4 with H3PO4

Phenols BGS 1000 + PTFE cap liner and leave air space

See comments 3 weeks Do not prerinse container with sample (analytes absorb to glass). Acidify to pH < 4 with H3PO4 or H2SO4. If chlorinated, see Note 1

continued





AnalyteContainer


Phosphorus and orthophosphates (dissolved)

BG orG 250or P C 1 month Filter on-site at the time of sampling, oxidising agents may be removed by addition of iron(II) sulfate or sodium arsenite prior to analysis

250P F 1 month

Phosphorus and orthophosphates (total)

BG orG 250or P H2SO41 month Filter on-site at the time of

sampling, oxidising agents may be removed by addition of iron(II) sulfate or sodium arsenite prior to analysis

250P F 1 month

Polychlorinated biphenyls (PCBs)

GS 1000 with PTFE cap liner and leave air space

C 7 days Do not prerinse container with sample (analytes absorb to glass). Extraction on-site is desirable. If chlorinated, see Note 1

Polycyclic aromatic hydrocarbons (PAHs)

GS 500 with PTFE cap liner

C 7 days Extraction on-site is desirable. If chlorinated, see Note 1

Potassium100P HNO3

1 month

Purgeables by purge and trap

100 with PTFE cap liner

G H2SO47 days If chlorinated, see Note 1

Feasible to store 14 days

Selenium100GAPA or HNO3

1 month

Silicates (dissolved)

200P C 1 month Filter on-site at the time of sampling

Silicates (total)100P C 1 month

Silver100GAPA or HNO3

1 month

Sodium 100GorP HNO31 month

Solids (suspended) 500GorP C 2 days

Sulfate200GorP C 1 month

Sul�de (easily liberated)

500P C air1 week Fix immediately on-site with

2 mL zinc acetate with 10% mass concentration. If chlorinated, add 80 mg ascorbic acid per 100 mL of sample

Sul�te 500GorP air2 days Fix on-site with 1 mL of 2.5%

by mass EDTA per 100 mL of sample

Surfactants and detergents (anionic)

500 + rinse with methanol

G C H2SO42 days Glassware should not be

detergent-washedSame sample can be used for nonionic





AnalyteContainer


Surfactants and detergents (cationic)

500 + rinse with methanol

G C 2 days Glassware should not be detergent-washed

Surfactants and detergents (nonionic)

500G

+ see comments

airC1 month Glassware should not be

detergent-washed. Add 37% by vol. formaldehyde to give 1% by vol. solution

TinPA BGA 100or HCl 1 month

Total solids (total residues, dry extract)

100GorP C 24 h

Trihalomethanes 100 vials with PTFE septum

G airC14 days If chlorinated, see Note 1

Turbidity 100GorP C24 h On-site measurement

preferable

UraniumPA BGA 200or HNO3

1 month

VanadiumPA BGA 100or HNO3

1 month

ZincPA BGA 100or HNO3

1 month

P Plastic C Cool to 1–5°C

PA Plastic, acid-washed F Freeze to –20°C

GGlass F* Freeze to –80°C

GA Glass, acid-washed Exclude light (e.g., amber glass or wrap in foil)

GS Glass, solvent-washedair

Exclude air (e.g., �ll bottle to cap)

BGBorate glass HNO3

Acidify with nitric acid to pH 1–2

BGABorate glass, acid-washed H2SO4

Acidify with sulphuric acid to pH 1–2

BGSBorate glass, solvent washed HCl Acidify with hydrochloric acid to pH 1–2

NaOH Add sodium hydroxide to pH >12

Note 1. If sample chlorinated, add Na2S2O3 ⋅ 5H2O at rate of 80 mg per liter of sample.

K2Cr2O7Add potassium dichromate 0.05% by mass �nal concentration

Source: Consistent with ISO. Water quality—Sampling—Part 3: Guidance on the preservation and handling of samples. ISO 5667/3 2003.



1.2.6.5 Quality Control in Water Sampling

Each of the sample collection, sample handling, sample storage, and sample preservation steps should be validated to ensure positive or negative interferences with the determinants of interest are eliminated or at least reduced and quanti�ed. This involves the use of blanks (to determine possible additions) and ref-erence samples containing known levels of the relevant analytes (to determine losses and/or changes). In general, such blanks should accompany each batch of sample containers to a �eld sampling site, and be subjected to the same handling regime (e.g., opening, closure, preservation) as actual sample containers.

1.3 Sampling Strategies for Different Ecosystems

The strategy to be used in environmental sampling differs considerably depending on the details of the investigated ecosystem and the problems at issue. Hence, strategies can be described in relation to either the goals of the study or the ecosystems involved. In the following section, the different sampling strate-gies appropriate to the main types of ecosystem (still water, �owing water, estuarine or marine environ-ment) and their temporal and spatial scaling are discussed. In Section 1.3.4, considerations for sampling storm water runoff are used as an example of a sampling design speci�c to urban areas.

1.3.1 Lakes and Reservoirs

Often, a number of physical, chemical, and biological processes have to be considered as they may mark-edly affect water quality and its spatial variations. Sources of heterogeneity within a body of water that need careful consideration in selecting sampling sites are as follows:

• Thermal strati�cation, which leads to variations of quality in depth

• Effects of in�uent streams

• Lake morphology

• Wind

Any of these factors acting alone or in combination may produce both lateral and vertical heterogene-ity of water quality.

Some important topics relevant to the choice of sites for sampling are noted (e.g., Refs. [4,18]). It must be kept in mind that shallow and/or relatively isolated embayments of lakes and reservoirs may show marked differences in quality from the main body of water.

In water bodies of suf�cient depth in temperate climates, thermal strati�cation is often the most important source of vertical heterogeneity from spring to autumn (Figure 1.3). Measurement of dissolved oxygen and temperature is a convenient means of following the development of such strati�cation, and has the advantage that both measurements can be made automatically and continuously in situ.

Thermal strati�cation may retard the mixing of streams entering lakes or reservoirs. This important source of materials derived from the surrounding land consequently has to be sampled with due consid-eration of its spatial variability.

The number of algae in the surface layer of a water body may have a marked effect on the concentra-tions of nutrients and other substances: It is often not possible to measure any dissolved nutrients during algal blooms because all nutrients are bound in the algae. Therefore, the trophic status and spatial het-erogeneity in the distribution of algae should be considered while choosing a sampling site.

The choice of the correct sampling point can depend on the depth of a lake [19]. These authors have compared different water sampling techniques in a series of lakes. In deep lakes, they observed no signi�cant differences between mean summer nutrient concentrations measured in a tube sample integrating over the photic zone, taken from the deepest point, and a surface dip sample taken by wad-ing into the water’s edge. However, in shallower lakes, the integrating tube sampler gave signi�cantly higher estimates of mean concentrations than the other method due to the increase in volume of the unmixed hypolimnion, which reduced the depth of the well-mixed epilimnion to less than the tube



length. For national survey purposes, they suggested samples taken from the edge of the lake as the most cost effective.

1.3.2 Streams and Rivers

1.3.2.1 Location of Sampling within the Stream

Sampling locations especially in larger streams and rivers should, whenever possible, be at cross sections where vertical and lateral mixing of any ef�uents or tributaries is complete. To avoid nonrepresentative samples caused by surface �lms and/or the entrainment of bottom deposits, it has often been recommended that samples should, whenever possible, be collected no closer than 30 cm to the surface or the bottom [6].

Simple surface-grab procedures have been compared with more involved, cross-sectionally inte-grated techniques in streams [20]. Paired samples for analysis of selected constituents were collected over various �ow conditions at four sites to evaluate differences between the two sampling methods. Concentrations of dissolved constituents were not consistently different. However, concentrations of sus-pended sediment and the total forms of some sediment-associated constituents, such as phosphorus, iron, and manganese, were signi�cantly lower in the surface-grab samples than in the cross-sectionally integrated samples. The largest median percent difference in concentration for a site was 60% (total recoverable manganese). Median percent differences in concentration for sediment-associated constitu-ents considering all sites grouped were in the range of 20–25%. The surface-grab samples underrepre-sented concentrations of suspended sediment and some sediment-associated constituents, thus limiting the applicability of such data for certain purposes.

When the quality of river water extracted for a particular end use is of interest (e.g., the production of drinking water), the sampling point should, in general, be at or near the point of extraction. It must be noted, however, that changes in quality may occur between the actual point of extraction and the inlet to

O2

O2

O2

O2

Ice

4°C

20°C

4°C

Winter

Autumn

Summer

EM

H

Spring

FIGURE 1.3 Seasonal variation of oxygen and temperature within the different layers of a meso/eutrophic lake in temper-ate latitudes. E, epilimnion; M, metalimnion; H, hypolimnion.



the treatment plant. If the amount or time of extraction is to be controlled on the basis of the water qual-ity, an additional sampling location upstream of the extraction point will usually be needed, the distance upstream being dependent on the travel-time of the river, the speed with which the relevant analysis can be made, and the upstream locations of sources of the determinants. This is of course dif�cult to achieve. The need of an early warning system for drinking water purposes was emphasized by the Sandoz acci-dent in 1986, since which online biomonitors have been in place in the Rhine River [21].

1.3.2.2 Description of the Longitudinal Gradient

When the aim is to assess the quality of a complete stream, river or river basin, the number of potentially relevant sampling locations is usually extremely large. It is, therefore, usually necessary to assign differ-ent priorities to the various locations to arrive at a feasible sampling program [6,18]. Such considerations are very closely connected to the issue of sampling frequency, and a number of approaches for the overall design of sampling programs for river systems have been described [4]. The value of, and need for, iden-ti�cation of locations where quality problems are or may be most acute, have been stressed several times. These questions can be addressed with �xed-location monitoring and intensive, short-term surveys at selected locations for the routine assessment of rivers.

Water quality is usually monitored on a regular basis at only a small number of locations in a catch-ment, generally concentrated at the catchment outlet. This integrates the effect of all the point and non-point source processes occurring throughout the catchment. However, effective catchment management requires data that identify major sources and processes. For example, as part of a wider study aimed at providing technical information for the development of integrated catchment management plans for a 5000 km2 catchment in southeastern Australia, a “snapshot” of water quality was undertaken during stable summer �ow conditions. These low �ow conditions exist for long periods, so water quality at these �ow levels is an important constraint on the health of instream biological communities. Over a 4-day period, a study of the low �ow water quality characteristics throughout the Latrobe River catch-ment was undertaken. Sixty-four sites were chosen to enable a longitudinal pro�le of water quality to be established. All tributary junctions and sites along major tributaries as well as all major industrial inputs were included. Samples were analyzed for a range of parameters, including total suspended solid concentration, pH, dissolved oxygen, electrical conductivity, turbidity, �ow rate, and water temperature. Filtered and un�ltered samples were taken from 27 sites along the mainstream and tributary con�uences for the analysis of total N, NH4, oxidized N, total P, and dissolved reactive P concentrations. The data were used to illustrate the utility of this sampling methodology for establishing speci�c sources and estimating nonpoint source loads of phosphorus, total suspended solids, and total dissolved solids. The methodology enabled several new insights into system behavior, including quanti�cation of unknown point discharges, identi�cation of key instream sources of suspended material, and the extent to which biological activity (phytoplankton growth) affects water quality. The costs and bene�ts of the sampling exercise are reviewed in Ref. [22].

1.3.2.3 Temporal Changes of Water Quality

The discharge of streams in comparison with larger rivers is highly dynamic, depending mainly on local rainfall conditions and/or groundwater level [23]. It follows that the chemical composition of the stream water is profoundly in�uenced by the allochthonous input of water, nutrients, sediments, and pesticides. Two-thirds of the contamination of headwater streams with sediments, nutrients, and pesticides is caused by those nonpoint sources [24]. Substances with a high water solubility are introduced through soil �ltra-tion. Less water-soluble substances enter by way of the surface water runoff during heavy rains [25]. The total loss of a particular pesticide depends on the time period between application and the rain event, the pattern of precipitation, various soil parameters, and the physical and chemical properties of the pesti-cide. Consequently, streams with an agricultural catchment area are susceptible to unpredictable, brief pesticide inputs following precipitation [26,27].

To determine the in�uence of sampling frequency on the reliability of water quality estimates in small streams, a cultivated (0.12 km2) and a forested basin (0.07 km2) were studied in spring and autumn



[28]. During the 2-month spring season and 3-month autumn season, 97–99% of the annual loads of total nitrogen, total phosphorus, and suspended solids was acquired from the cultivated basin and 89%–91% from the forested basin. During the same seasons, 99% and 87% of the total annual runoffs were recorded in the cultivated and forested basins. This means that in only 5 months of the year more than 95% of the nutrient and water runoff occurred in the cultivated catchment, and about 90% in the forested catchment. Thus, the values of nonpoint loads, normally presented as annual means, can give a very misleading impression of the effects of nonpoint loading on watercourses, particularly in the case of relatively small streams.

The same author [28] estimated the number of samples needed to calculate the load of various sub-stances by varying the sampling frequency at the two sites. In the cultivated basin, the means of concen-tration data would be within ±20% of the mean of the whole data set in spring, if nitrogen and phosphorus samples were taken at least �ve times and suspended-solid samples at least three times monthly. In the forested basin, the corresponding sampling frequencies were twice monthly for nitrogen samples and four times monthly for phosphorus and suspended solids. In autumn, the concentration means in runoff waters would be within ±20% of the mean obtained using the whole data set if three samples per month were taken for nitrogen and phosphorus and �ve samples for suspended solids. In the forested basin the same deviation of the mean would be obtained with 1 nitrogen sample, 5 phosphorus samples, and 16 suspended-solid samples.

When intending to measure the peak concentrations of slightly soluble substances in streams within a cultivated watershed, it is necessary to use runoff-triggered sampling methods. A headwater stream in an agricultural catchment in northern Germany was intensively monitored for insecticide occurrence (lindane, parathion-ethyl, fenvalerate). Brief insecticide inputs following precipitation with subsequent surface runoff result in high concentrations in water and suspended matter (e.g., fenvalerate: 6.2 μg L−1, 302 μg kg−1). These transient insecticide contaminations are typical of headwater streams with an agri-cultural catchment area, but have been rarely reported. Event-controlled sampling methods for the deter-mination of this runoff-related contamination with a time resolution of as little as 1 h make it possible to detect such events [29].

Within monitoring programs, loading errors are generally associated with an inadequate speci�cation of the temporal variance of discharge and of the parameters of interest. Often little consideration is given to the impact of additional transport characteristics on contaminant sampling error and design. Detailed examination of �ve transport characteristics at a single river cross section emphasizes the importance of understanding the complete transport/loading regime at a sampling station, de�ning the required end products of the monitoring program, and de�ning the accuracy required to meet speci�c program needs before implementing or evaluating a monitoring program. River transport characteristics are: (a) con-taminant transport modes, (b) short-term temporal and seasonal variability, (c) the relationship between dissolved and particulate contaminant concentrations and discharge, (d) load distribution with sediment particle size, and (e) spatial variability in a cross section [30].

It is also worth noting that the procedure known as catchment quality control, though intended for a different purpose, includes the identi�cation of most important ef�uents entering a river system from a viewpoint of water quality [31].

1.3.2.4 Using Sediments to Integrate over Time

The analysis of river sediments has been suggested as a convenient means of reconnaissance of river systems to decide the locations where water quality is of particular interest with respect to pollutants.

1.3.3 Estuarine and Marine Environments

The potential spatial heterogeneity (lateral and vertical—both are time-dependent) of these bodies of water makes it essential that sampling locations be chosen with reference to the relevant basic processes [18]. Sampling of ocean waters and the handling of such samples have been described in general [5].

A well-known practical problem is the unintended contamination of samples by material released from the research vessel or by the sampling apparatus. A sampling apparatus for the collection and



�ltration of up to 28 L of water at sea has been designed to minimize possible contamination from both the equipment and the ship’s surroundings [32]. It was used in the analysis of chlorinated biphe-nyls (CBs), persistent OC pesticides, and pentachlorophenol (PCP), in both the aqueous and particu-late phases. The system is suitable for collection of estuarine and coastal waters where the levels of dissolved CBs, OCs, and PCP are above the limit of determination of 15 pg L−1. The ef�ciency of the recovery of these compounds and variance of the extraction and analysis have been estimated by anal-ysis of �ltered seawater spiked at a range of concentrations from picogram per liter to nanogram per liter. Recoveries ranged from 66.5% to 97.3% with coef�cients of variation for the complete method from 7.2% to 29.9%.

The procedure of using small boats provided with sample bottles attached to a telescopic device is recommended as a means to minimize contamination from the research vessel during coastal water sampling. Of the wires used to suspend samplers, plastic-coated steel gave negligible, and Kevlar and stainless steel only slight, contamination for some metals [8].

The high spatial and temporal variability of estuaries poses a challenge for characterizing estuarine water quality. This problem was examined by conducting monthly high-resolution transects for several water quality variables (chlorophyll-a, suspended particulate matter, and salinity) in San Francisco Bay, California [33]. Using these data, six different ways of choosing station locations along a transect, to estimate mean conditions, were compared. In addition, 11 approaches to estimating the variance of the transect mean when stations are equally spaced were compared, and the relationship between variance of the estimated transect mean and number of stations was determined. These results were used to derive guidelines for sampling along the axis of an estuary. In addition, the changes in the concentration of various substances due to the tide seem to be extremely important. Seawater with a low concentration of substances becomes mixed with the highly loaded water in the estuaries and along the shores. Automatic samplers can be used to integrate the concentrations of materials over time (see Section 1.4).

An overview of the analysis of polar pesticides in water samples has been presented [34]. The sam-pling plans and strategies for different types of waters such as rivers, wells, and seawater are discussed. In situ preconcentration methods, involving online techniques or direct measurement, are suggested as alternatives to conventional techniques. Attention is devoted to the in�uence of organic matter and its interaction with polar pesticides. The use of various types of �ltration steps prior to the preconcentration of the analytes from water samples is also reviewed.

1.3.4 Urban Areas

In urban areas, sampling strategies for storm water runoff from industries and municipalities are of speci�c importance. The United States Federal Storm Water Regulations of 1990 specify protocols for such storm water runoff sampling. These regulations de�ne two separate samples that must be collected when a storm occurs. A �rst-�ush sample is to be collected during the �rst 30 min of the storm event. A �ow-weighted composite sample must be collected for the entire storm event or at least the �rst 3 h of the event [35].

The �rst-�ush sample and the �ow-weighted composite sample must be analyzed for the pollutants listed in Table 1.3. In general, the sample volume required for laboratory analysis depends on the particular pol-lutants being monitored and varies for each application. As a general rule, a 3 L sample volume for both �rst-�ush and �ow-weighted composite sample usually is suf�cient for the majority of applications [35].

Both manual and automatic methods can be used to collect samples for the required analysis [35]. For manual sampling, the samples can be taken at �xed time intervals in individual bottles. After collection, a speci�c volume must be poured out of each bottle to form a �ow-weighted composite. The exact vol-ume must be calculated using the �ow data taken when each bottle was �lled. The advantage of manual sample collection is that, regardless of runoff amount, a fairly constant volume of sample is collected. This is because the �ow-weighted composite is formed after the event and does not depend on calcula-tions for runoff volume.

Automatic storm water monitoring systems typically consist of a rain gauge, �owmeter, automatic sampler, and power source. The rain gauge measures on-site rainfall. The �owmeter measures the runoff



water level and converts this level to a �ow rate. In many systems, the �owmeter activates the sampler when user-speci�ed conditions of rainfall and water level have been reached. Once activated, the sampler collects water samples by pumping the runoff water into bottles inside the sampler.

Automatic storm water monitoring systems can form the �ow-weighted composite sample automati-cally during the storm event, if there is suf�cient storage capacity to accommodate variations in the runoff amount. Such automatic samplers are described in Refs. [16,17,35].

1.3.5 Wastewater Systems

By their nature and function, wastewater systems are a potential source of contaminants of interest in relation to potential impacts in downstream receiving waters, as shown in the growing interest in sources and fate of “contaminants of concern” (CECs) in surface waters such as endocrine-disrupting com-pounds (EDCs) as well as pharmaceuticals and personal care products (PPCPs) [36]. See Ref. [37] for a recent review. However, the design of a sampling protocol to capture adequately a truly representative sample of a wastewater discharge is often a far from simple task because of a number of factors inherent to the purpose, design, and function of wastewater systems. This can result in highly variable volumes of discharge over short time periods as well as short-term �uctuations in the concentrations of contami-nants of interest in the system input and discharge streams. Despite this complexity, a recent review of published papers relating to the assessment of chemicals in the input to sewage treatment systems [8] suggests that the sampling protocols in less than 5% of studies explicitly considered and took account of these short-term �uctuations.

TABLE 1.3

Storm Water Analysis Requirements According to the United States Federal Storm Water Regulations

Industrial Municipal

PollutantFirst-Flush

Grab SampleFlow-Weighted

Composite SampleFlow-Weighted

Composite Sample

Oil and grease X X

pH X X

Biological oxygen demand (BOD) X X X

Chemical oxygen demand (COD) X X X

Total suspended solids (TSS) X X X

Total phosphorus X X X

Nitrate and nitrite nitrogen X X X

Total Kjeldahl nitrogen X X X

Any pollutant in the facility’s ef�uent guideline X X

Any pollutant in the facility’s NPDESa permit X X

Any pollutant in the EPA form 2F tables believed to be present

X X

Total dissolved solids X

Fecal streptococcus X

Fecal coliforms X

Dissolved phosphorus X

Total ammonia plus organic nitrogen X

13 Metals, total cyanide, and total phenol X

28 Volatile compounds X

11 Acid compounds X

46 Base/neutral compounds X

25 Pesticides X

Source: From Friling, L., Pollut. Eng., 25, 36, 1993. With permission.Note: X, analysis required.a National pollutant discharge elimination system.



For an example approach to characterization of variability in wastewater and the optimization of sam-pling protocols to minimize errors caused by temporal variation, see Ref. [38]. This typically involves a preliminary sampling study in which a high frequency is necessary.

For the purpose of quantifying dilution of a sewage ef�uent discharge to receiving waters, recent work [39] demonstrated that due to the widespread use in human disease treatment of the rare earth element gadolinium as a contrast agent in magnetic resonance imaging (MRI), this anthropogenic Gd can be used as a conservative tracer for discharges from sewage treatment systems with catchments contain-ing MRI facilities, and potentially even small catchments where an anthropogenic Gd signature can be generated by MRI patients treated elsewhere [40].

1.4 Sampling Equipment

1.4.1 General Comments

This section discusses the advantages and disadvantages of sampling systems designed for the various sampling roles discussed above.

Any component of a sampling device that is not normally present in the water body may affect the concentrations of determinants of interest in the water through three main effects: (a) by disturbance of physical, chemical, and biological processes and equilibria, (b) by contaminating the water with some parts of the sampler (e.g., organic compounds may leach out of plastic materials), and (c) by direct reac-tions between determinants and the materials of which the device is constructed (e.g., dissolved oxygen can react with copper, decreasing the oxygen concentration in the water). Another source of error may occur from processes within sample devices, such as the deposition of undissolved, solid materials on to the walls of a device, or sorption of chemicals to such surfaces.

1.4.2 Manual Sampling Systems

1.4.2.1 Simple Sampler for Shallow Water

For many purposes, specially designed and installed sampling devices are not required. It often suf�ces simply to immerse a bottle in the water of interest, and this technique may be applicable also for some purposes in water-treatment plant.

1.4.2.2 Sampler for Large Quantities in Shallow Water

A system for the sampling and �ltering of large quantities of surface seawater that is suitable for trace metal analysis is described in Ref. [41]. The water is brought aboard the ship via an all-Te�on pump and PFA tubing from a buoy deployed away from the vessel. The sample is delivered directly into a polycarbonate pressure reservoir and is subsequently �ltered through a polycarbonate �lter and in-line holder.

Sampling systems based not on sample containers but on inlet tubes are commonly required in water-treatment and other plants, and are also employed in a number of applications for natural waters [6]. In some systems, the �ow of sample through the inlet tube is achieved by the natural pressure differential, whereas in others the sample must be pumped, sucked (by vacuum), or pressurized (by a gas) through the tube. When dissolved gases and volatile organic compounds and possibly other determinants whose chemical forms and concentrations may be affected by dissolved gases are of interest, it is generally desirable to ensure that the sample is slightly pressurized to prevent gases coming out of solution.

1.4.2.3 Simple Sampler for Deepwater

When it is necessary to sample from a particular depth in waters where the simple technique (see Section 1.2.2) cannot be used, special sample collection containers are available that can be lowered into the water on a cable to collect a sealed sample at the required depth.



One of the simplest kinds of equipment with which to obtain samples from various depths is an empty weighted bottle closed with a stopper. This stopper is connected to the bottleneck by a rope, which can be used for releasing the stopper and opening the bottle at the desired depth (scoop bottle according to Meyer, Figure 1.4). However, for some sampling tasks, such as measuring dissolved gases, allowing the water �owing into the bottle to mix with the air inside the bottle is unacceptable.

This simple-technology approach can be adapted easily to enable sample collection for a more com-plex sampling design. For example, as illustrated in Figure 1.5, if the sampling design requires samples to be taken simultaneously at several discrete depths in the water column, this can be achieved by mount-ing sample collection bottles on a pole, and using multiple ropes to release the stoppers.

1.4.2.4 Deepwater Sampler (Not Adding Air to the Sample)

A common tool for taking water samples from different depths is the standard water sampler according to Ruttner. The sampler, still open, is lowered by cable into the water. When it reaches the desired depth, a messenger is let down on the cable. Upon striking the standard water sampler, the messenger releases the closing mechanism and the lids of the sampling tube close. In some versions, a separate cable is used to close the sampling bottle. The advantage is that no mixing of air with the sample will occur. But this system has the disadvantage that the inner surface of the sampling tube is in contact with water at all the depths through which the sampler travels on its way to the desired depth, and thus may introduce contaminants to the sample from the shallower layers through which it has passed.

Figure 1.6 shows an apparatus from Hydrobios as an example of a sampler according to Ruttner. This version contains a thermometer ranging from −2°C to +30°C, indicating the temperature of the sample; the temperature can easily be read through the plastic tube of the sampler. The water sample can be drawn off through the discharge cock in the lower lid for the various analyses. A similar version with a metal-free interior of the sampling tube for the determination of trace metals is also available.

1.4.2.5 Deepwater Sampler for Trace Elements (Allowing Air to Mix with the Sample)

The Mercos Water Sampler from Hydrobios (Figure 1.7) is suitable for ultratrace metal analysis. It con-sists of a holder device and exchangeable 500 mL Te�on bottles as sampling vessels, which can be used down to 100 m water depth. All �ttings are made of titanium.

The sampler is attached to a plastic-coated steel hydrographic wire and lowered into the water in closed con�guration to prevent sample contamination by surface water. Upon reaching the desired water

Cork

Sample bottle

Weight

FIGURE 1.4 Scoop bottle according to Meyer, a very simple sampler for various depths.



depth, the sampler is opened by means of plastic-covered messengers. When the messenger hits the anvil, the silicone tubings spring up to allow water to �ow in and air to leave the bottle. In the case of serial operation, a second messenger for release of the next sampler is set free at the same time. A disad-vantage of the system is the contact between air and the water sample within the bottle.

For the determination of trace elements in seawater, the system sampling bottle = storage bottle = reac-tion vessel is used, so that the samples cannot be falsi�ed by pouring from one vessel to another. To sterilize the bottles for microbiological investigations, the Te�on bottles, along with coupling pieces and silicone tubings, can easily be taken from the holder.

A modi�cation of an inexpensive and easy-to-handle let-go system, a semiautomatic apparatus for primary production incubations at depths between 0 and 200 m, has been suggested [42]. The system is composed of a buoy, a nylon line, a �berglass ballast weight, and about 15 sampling chambers. The entire volume of this apparatus is less than 80 dm3 and weighs about 7–8 kg. The sampling chambers sink with the ballast in an open position. When the line is stretched between the buoy at the surface and the bal-last at the bottom, the chambers automatically enclose the water sample at the predetermined depth. The complete deployment of the apparatus takes less than 10 min. By an easy modi�cation of the length of the line and/or the position of the chambers along it, sampling depth can be varied for repeated deploy-ment over variable depth. The advantage of this system is that parallel samples from different depths can be obtained with relatively low costs and technical complexity.

FIGURE 1.5 A simple sampler approach for taking simultaneous samples at discrete depths in the water column. Individual sample bottles are attached with standard laboratory clamps to a pole premarked with a depth scale. Individual ropes attached to bottle stoppers enable the samples to be taken when the pole is in position. This sampler was used to sample water from storage tanks, but the approach is adaptable to a variety of �eld situations such as lakes and streams. (Photograph from T. Soutberg and C. Barnes.)



FIGURE 1.6 Standard water sampler according to Ruttner for various depths. (Photograph from Hydrobios Apparatebau GmbH.)

FIGURE 1.7 MERCOS water sampler with two bottles that are lowered while closed and are opened at the desired depth. (Photograph from Hydrobios Apparatebau GmbH.)



1.4.3 Systems for Sampling the Benthic Boundary Layer at Different Depths

1.4.3.1 Deepwater (>50 m)

Instrumented tripods with �owmeters, transmissiometers, optical backscatter sensors (OBS), in situ settling cylinders, and programmable camera systems have often been used in marine environments, for example, oceanographic studies of �ow conditions and suspended particle movements in the bottom nepheloid layer [43,44]. These instruments were deployed to study suspended-sediment dynamics in the benthic bound-ary layer and were able to collect small water samples (1–2 L) at given distances from the sea�oor. An instrumented tripod system (Bioprobe), which collects water samples and time-series data on physical and geological parameters within the benthic layer in the deep sea at a maximum depth of 4000 m, has been described [45]. For biogeochemical studies, four water samples of 15 L each can be collected between 5 and 60 cm above the sea�oor. Bioprobe contains three thermistor �owmeters, three temperature sensors, a transmissiometer, a compass with current direction indicator, and a bottom camera system.

1.4.3.2 Shallow Water (<50 m)

An instrument that collects water from the benthic boundary layer in more shallow waters with a maxi-mum depth of 50 m is described in Ref. [46]. Four water samples of 7 L each can be collected between 5 and 40 cm above the sediment. Handling is easy and the sampling operation is brief enough to allow repeated employment even on time-limited, routine investigations.

1.4.4 Automatic Sampling Systems

As already noted, it is usual that concentrations of determinants of interest in a water sampling project are variable over time. To describe this situation in the �eld, it might be necessary either to take an average of the contamination or to obtain information about the short-term peak concentration. To estimate the average contamination, often the simplest way is to take a continuous sample or to generate a composite sample by sampling with constant time intervals. In this case, the frequency of sampling should be at least as great as the frequency with which the concentration changes. If nonpredictable peak concentrations are to be sampled, it is necessary to use a trigger, some easy-to-measure variable that speci�es the optimum sampling time. A wide range of triggers are available (e.g., water level, conductivity, turbidity, temperature).

1.4.4.1 Sampling Average Concentrations

Automatic systems consist, in general, of a sampling device and a unit, which automatically controls the timing of the collection of a series of samples and houses the appropriate number of sampling containers [4,6,16,17]. The control unit usually provides the ability to vary several factors such as the number of samples in a given time period, the length of that period, and the time period over which each sample is collected. Some units also allow sample collection to be based on the �ow rate of the water of interest rather than time. One common example of the application of such a system is the collection of 12 or 24 samples in a period of 24 h. The individual samples can be analyzed separately or subsequently be used to prepare one composite sample for analysis. Such automatic sampler units, which allow composite samples to be taken, are available, for example, from ISCO Inc.

1.4.4.2 Sampling Average Concentrations: Sampling Buoy

An automatic sampler for water and suspensions (SWS), which can be used in marine systems, lakes, and rivers, is shown in Figure 1.8. Pumps and bottles are situated in the underwater part of the �oating device so that the sampler can be used in subzero weather (no freezing of water samples) and tropical regions (no overheating of electronic circuits). As the sampling time can be programmed, the data provided by this sampler re�ect the average level of contamination (e.g., metals and pesticides) better than do single or random samples.



1.4.4.3 Event-Controlled Sampling of Industrial Short-Term Contamination

Short-term loading of toxic substances into natural waterways is a common phenomenon, with substan-tial impacts on biota. The effects of shock (pulse) pollution loading from two major industries on a river and wetland system in southern Ontario, Canada have been described in Ref. [47]. The assessment of shock loading frequency indicated that sporadic discharges of polluted water occurred on average once every other day during the 38 days of monitoring in the period April 1986 to November 1987. To estimate the frequency and intensity of the shock loads, an automatic pump sampler triggered by a threshold con-ductivity was used. Samples were withdrawn from the river when the speci�c conductivity of the stream exceeded a threshold value of two times background.

1.4.4.4 Rapid Underway Monitoring

The advent of easy access to the satellite-based global positioning system (GPS) and availability of off-the-shelf portable probes and rapid analyzers for a number of water quality determinants have enabled the development of systems that can be carried on small survey vessels to map water quality conditions. Rapid data acquisition is now practical using probes and sondes for measuring temperature, conductivity, turbidity, pH, and dissolved oxygen; �uorometric technologies for chlorophyll biomass and phytoplank-ton composition; �ow injection and loop �ow analysis for some nutrient species; and acoustic Doppler-based devices for current pro�ling.

One such onboard rapid monitoring system was developed recently and �eld tested in Queensland, Australia [48]. A schematic representation of the system is shown in Figure 1.9. While the survey vessel is underway, subsurface water is pumped to the instrumentation using a diaphragm pump from an intake positioned approximately 1 m below the surface to avoid turbulence created by boat wash. Trials of the system have shown that it can be successfully used from vessels as small as 4 m, and depending on which instruments are deployed, data acquired at speeds of 25 knots or more.

0.5 m

1 1

2

5

3 4 4

6

8

7

Surface

Bottom

1. Inner tube of tire2. Water pump and timer3. Battery4. Bottle (8 L), one PE one glass

5. Connection tube, PTFF6. Inlet tube, PTFF7. Ropes8. Anchor

FIGURE 1.8 Design of a sampler for water and suspensions (SWS) in marine systems including subzero temperature and tropical regions and in large rivers or lakes. (Design: Liess, M., used in Duquesne, S. and Liess, M., 2003. Increased sensi-tivity of the macroinvertebrate Paramorea walkeri to heavy-metal contamination in the presence of solar UV radiation in Antarctic shoreline waters, Marine Ecology Progress Series, 255, 183–191.)



Trials of the system in the estuarine reaches of the Brisbane River, Queensland, successfully mapped small-scale differences in turbidity and salinity pro�les during a high rainfall period. The onboard rapid monitoring data were characterized by sharp spikes and dips in turbidity and salinity, respectively, associated with inputs from tributaries (Figure 1.10). Such perturbations were not present during a dry season sampling run when freshwater inputs from the tributaries were negligible. In addi-tion, the overlay on Figure 1.10 of turbidity data points acquired from routine �xed-site monitoring points illustrates the relative underestimation of turbidity by routine monitoring under such spatially variable conditions.

The potential of such a vessel-mounted rapid data acquisition system for assessing discharge mixing zone size and compliance was demonstrated during dry weather sampling runs past the discharge point of a wastewater-treatment plant near the mouth of the Brisbane River. The impacts of the discharge on the ambient environment were readily captured (Figure 1.11), showing spikes in chlorophyll-a and turbidity and a dip in salinity. The perturbations returned to ambient conditions within a few hundred meters of the discharge point.

Three-dimensional underway monitoring is also feasible with the addition to the system of a towed body probe (Bio�sh; ADM-Elektronik, Germany) that continually moves between surface and bottom waters under control from the towing vessel, collecting water quality data and relaying it to an onboard computer. Such an approach has been employed for water quality monitoring on the Great Barrier Reef, Australia [49].

Graphicalinterface

Water intake vent

Waterdischarge

vents

Serial to USBconverters (×2)

GPS receiver(g)

(f) Acoustic Doppler current profiler(current velocity and direction,

TSS estimates)

(e) Depth sounder

(d) Nutrient analyzer(dissolved forms of N and P)

(c) Chlorophyll-a fluorescence probe(major groups and photosynthetic capacity)

(b) Multiparameter water quality probe(pH, DO, temperature, salinity,

turbidity, chlorophyll-a fluorescence)

(a)Diaphragm pump

FIGURE 1.9 Schematic diagram of the rapid underway monitoring system illustrating key components and required integration: Diaphragm pump (a) used to deliver water to the onboard instrumentation (b–d), instruments mounted in the water column (e,f), and GPS unit and computer components (g). (Reproduced from Hodge, J. et al. Mar. Pol. Bull., 51, 113, 2005. With permission.)



The use of rapid underway monitoring systems offers the capacity to detect small-scale spatial vari-ability in water quality parameters that might otherwise be missed by discrete sampling site methodolo-gies. Potentially, a rapid underway system provides a detailed view of where problem areas originate and their spatial extent.

1.4.4.5 Event-Controlled Sampling: Surface Water Runoff from Agricultural Land

Streams in intensively cultivated areas are characterized by a high input of material from the surround-ings. The characteristics of this contamination have been detailed in Section 1.3.2.3; most important are the unpredictability and brevity of such inputs.

0 10 20 30 40 50 60 70 80Distance upstream (km)

3530

25201510

50

Salin

ity (p

pt)

1009080

605040302010

0

70

Turb

idity

(NTU

)

TurbiditySalinityRoutine sites

FIGURE 1.10 Turbidity and salinity data acquired by the rapid underway monitoring system from the Brisbane River during a sampling run in January 2004 (high-rainfall period). High small-scale variability was evident in relation to inputs from tributaries at 7, 40, and 60 km. In addition, the overlay of data points from routine site-based monitoring shows that such monitoring underestimates the underlying conditions revealed by the rapid underway monitoring system. (Reproduced from Hodge, J. et al. Mar. Pol. Bull., 51, 113, 2005. With permission.)

TurbiditySalinityChlorophyll-a

6

5

4

3

2

1

000.50

0

5

10

15

20

25

30

35

4020

15

10

5

0

Turb

idity

(NTU

)

Salin

ity (p

pt)

Distance upstream (km)

Chlo

roph

yll-a

(μg

L−1)

FIGURE 1.11 Data captured by the rapid underway monitoring system show the increase in turbidity, and decrease in salinity, as well as the more diffuse increase in chlorophyll-a associated with the discharge from a major wastewater- treatment plant near the mouth of the Brisbane River. One useful application of the system is this capacity to map mixing and impact zones from discharges. (Reproduced from Hodge, J. et al. Mar. Pol. Bull., 51, 113, 2005. With permission.)



Because typical runoff water has low conductivity, in such circumstances, the conductivity of a stream is lowered when it receives edge-of-�eld runoff. This conductivity decrease was used to trigger an auto-matic sampler, which provides an accurate measurement of the maximum pesticide contamination of sus-pended matter and water, by sampling only the brief peak contamination levels during runoff events [29]. The conductivity was measured every 4 min. During runoff events, a 500 mL water sample was taken every 8 min. For each event, a mixture of subsamples was analyzed for insecticide content. An example of the high variability of the measured concentrations of insecticides is shown in Figures 1.12 and 1.13.

A simple qualitative method for the detection of pesticide contamination in the rainfall-induced sur-face runoff from agricultural �elds into surface waters is described in Ref. [50]. At each runoff site in an agricultural catchment, a passively collecting glass bottle (2.5 L) was installed in the embankment. The glass bottle was placed in a plastic container with a lid, the upper surface of which was �ush with the soil surface. The neck of the bottle passed through a 4 cm diameter hole in the lid. The opening of the bottle (diameter 3 cm) was 2 cm above the soil surface. This value was chosen to prevent animals (e.g., carabid beetles) from falling into the bottles and to sample runoff water in excess of a particular amount. A metal roof prevented rainfall from entering the collecting bottle (Figure 1.14).

1.4.4.6 Other Considerations Regarding Automatic Sampling Equipment

1.4.4.6.1 Interference from Biological Films

Since automatic samplers generally include an inlet tube, the development of problematic biological �lms within the tube and control unit can arise. The in�uence of automatic sampling equipment on biological oxygen demand (BOD) test nitri�cation in nonnitri�ed �nal ef�uent has been evaluated [51]. Samples were tested for BOD, carbonaceous BOD, nitrogenous oxygen demand, and concentration of nitrifying bacteria.

Feb. Mar. Apr. May Jun. Jul. Sep. Oct. Nov.Aug.Time (month)

1

10

100

1000

1 2 5 63 4 7 8 9 10

510

20

30

40

Disc

harg

e (L

s−1 )

Rain

fall

(mm

day

−1)

FIGURE 1.12 Daily rainfall, discharge, and surface runoff events in an agricultural stream in 1994. The arrows indicate the time of surface runoff. Black arrows point to insecticide contamination. (Reproduced from Liess, M. et al. Water Res., 33(1), 239, 1999. With permission.)



Bio�lms inside the equipment were tested for nitri�cation potential. A sampler utilizing continuous circula-tion of �nal ef�uent was found to support attached growth of nitrifying bacteria and was associated with relatively high-ef�uent nitrogenous oxygen demand. The ef�uent nitrogenous oxygen demand and nitri�ca-tion potential of attached growth were signi�cantly less with a unit that aspirated ef�uent on an intermittent basis, purging the sample line with air before and after sampling. Peak nitri�er counts in samples from the continuous-�ow equipment exceeded those in samples from the intermittent-�ow equipment.

1.4.4.6.2 Deterioration of Samples

For some determinants, the possibility that the integrity of samples taken by automatic sampling equipment may be compromised by losses or other changes in concentration of determinants due to delayed preserva-tion (see Section 1.4.6) needs to be considered. More sophisticated samplers, which provide refrigeration of samples after collection and/or addition of appropriate preservatives, are commercially available.

Agricultural field

2.5 L Glass bottle

Roof

Height: 2 cm

Plastic container

Stream

FIGURE 1.14 Construction of a runoff-sampling apparatus, which is installed in erosion rills in the embankment. (Reproduced from Schulz, R. et al. Chemosphere, 36(15), 3071, 1998. With permission.)

0

1

2

3

4

5

6

7

Rainfall events

Mar

-01-

1994

Apr

-13-

1994

Apr

-25-

1994

May

-19-

1994

May

-25-

1994

Jun-

08-1

994

Aug

-13-

1994

Aug

-18-

1994

Aug

-24-

1994

May

-27-

1995

Mar

-17-

1994

Jun-

01-1

995

Apr

-19-

1995

Jul-0

2-19

95

Jul-1

7-19

95

Jul-2

7-19

95

Aug

-25-

1995

Aug

-29-

1995

Nov

-02-

1995

Parathion-ethylLindaneFenvalerate

Conc

entr

atio

n in

runo

ff w

ater

(μg

L−1)

FIGURE 1.13 Insecticide contamination during runoff events in an agricultural stream, 1994 and 1995. (Data from Liess, M. et al. Water Res., 33(1), 239, 1999.)



1.4.5 Extraction Techniques

All the sampling systems that are mentioned previously are based on the principle of extracting the con-taminants from the water samples after collection, or direct identi�cation/quanti�cation of determinants. Systems are also available for concentrating and/or extracting contaminants directly in the �eld. These systems take advantage of the tendency of determinants with low water solubility to bind to speci�c solid materials (solid-phase extraction [SPE]) or the fact that a determinant is more soluble in speci�c solvents (liquid–liquid extraction) than in the water phase.

One main advantage of in situ concentration is that huge amounts of water can be extracted in the �eld and need not be transported. In addition, because these systems can be deployed for long periods, they can pro-vide a relatively inexpensive method for integration of contaminants over time. Another advantage of in situ concentration is that for many organic chemicals, the typical sample volumes normally collected by “grab-sampling” methods are often inadequate for obtaining analytical results in the concentration range necessary for assessment of whether the chemicals pose a risk to the environment or human health, since threshold concentrations of concern may be near or less than levels of quantitation from a typical “grab-sample.”

1.4.5.1 Liquid–Liquid Extraction of Large Volumes

An accurate extraction and measurement procedure to determine CBs in surface waters is presented in Ref. [52]. The procedure involved a 10 L batch liquid–liquid extraction directly from the sample bottle to prevent loss due to adsorption to the wall. Exhaustive extraction for recovery measurements was proposed, resulting in an extraction time of 10–45 h. A detection limit lower than 10 pg kg−1 and a coef-�cient of variation of 3–9% were obtained.

Equipment and procedure for the collection, �ltration, and subsequent extraction of 20 L of water and suspended-solid samples to be analyzed for organic chemicals using readily available, inexpensive, and sturdy apparatus have been described [53]. Water collection, �ltration, and extraction of both phases can be accomplished in less than 1 h. Recoveries of selected representative OC contaminants spiked into “organic-free” water and Lake Ontario water at environmentally realistic levels are presented (Table 1.4). These data show good total recoveries from the lake water and suspended sediments for all except a few compounds for which poor recoveries from the solids may be a factor, since their recoveries from “organic-free” water were relatively ef�cient.

1.4.5.2 Solid-Phase Extraction Techniques

1.4.5.2.1 Overview

The growing availability of SPE media with an af�nity for a wide spectrum of compounds, reduced solvent requirements relative to liquid–liquid extraction techniques, high recovery rates and ease of use, has lead to an increasing application of high-volume water sampling in the �eld based on SPE tech-niques [54] and a number of commercial devices such as the In�ltrex and Kiel in situ pump are avail-able, although the basic elements for such a system (piping, �lter, sorbent column, pump, power supply, �owmeter, and control system) can be assembled readily by a good laboratory workshop. Such a system is illustrated in Figure 1.15.

An XAD-4 resin accumulative sampling method was tested as a means of on-site extraction of sur-face waters [55]. Recoveries for most OC, organophosphorus, organonitrogen, chlorophenol, and chlo-rophenoxy acid pesticides and related pollutants were acceptable (≥50%) when samples were spiked at the 10 and 0.1 μg kg−1 levels. Detection limits of 1−100 pg kg−1 were attainable for most compounds in river water, although lower levels required the use of an HPLC cleanup/fractionation step prior to those GC determinations using electron-capture detection. XAD-4 accumulative sampling was competitive with solvent extraction of grab samples in terms of recoveries, and offered advantages in volume of water sampled, detection limits, and sample handling. The wide range of solute applicability combined with the ease of constructing and operating the accumulative sampler recommends it over grab sam-pling for many types of monitoring applications. The use of a similar system, supported liquid mem-branes for sampling and sample preparation of pesticides in water, has been described [56]. A porous



PTFE membrane is impregnated with a water-immiscible organic solvent, producing the supported liquid membrane.

Owing to the risk of contamination during �eld extraction of water samples using SPE, it is highly desirable to avoid contact of water being sampled with the mechanical components of the pump prior to the water reaching the extractant. Generally, this necessitates plumbing the pump so that it sucks rather than drives water through the extracting media. In practice, this requires that the sampling device be situated as close as practical to the level of the water source because suction is limited to 1 atm of nega-tive pressure, and in practice, due to inherent resistances in the system (piping, �lters, and extracting media), 1–2 m altitude difference is the maximum.

Thorough �ltration of the inward water stream prior to extraction is a necessity since only the dissolved phase should be captured by the absorbant media. In addition, the �lter residue may be of interest in its own right in some studies (see Section 1.4.6). Many studies have used glass �ber �lters with a maximum cut off of 1 μm (Table 1.5). Filter breakthrough problems can be reduced by minimizing overall �ow rate through the system and maximizing contact time in the sorbent column. As shown in Table 1.5, most workers have limited �ow rate to less than 1 L min−1. The use of two extracting columns in parallel can reduce the overall sampling time while maintaining low �ow conditions [57]. Flow through centrifuges has also been used prior to �ltration to reduce the load on the �lter [58], but again this introduces a risk of contamination.

The most commonly used sorbent media for these systems is XAD polymer (Table 1.5), used as early as 1972 for assessing polychlorinated biphenyls (PCBs) contaminants in the North Atlantic by extracting 60 L water samples [72]. However, XADs require time-consuming and solvent-intensive cleaning and

TABLE 1.4

Recovery of Spiked Organochlorine Contaminants from “Organic-Free” and Lake Ontario Water and Suspended Solids

Percentage Recovery

“Organic-Free” FiltrateLake Ontario

FiltrateLake Ontario

Suspended Solids

Compound

Amount Spiked

(ng L −1)Spike

1Spike

2 MeanSpike

1Spike

2Spike

1Spike

2Mean Total

1,2,4-Trichlorobenzene 0.83 88 95 92 104 101 nd nd 103

1,2,3-Trichlorobenzene 0.42 110 121 116 117 119 nd nd 118

2,4,5-Trichlorotoluene 0.94 104 87 96 78 92 nd nd 85

2,3,6-Trichlorotoluene 0.93 93 97 95 85 77 nd nd 81

1,2,4,5-Tetrachlorobenzene 0.59 113 106 110 99 94 nd nd 97

1,2,3,4-Tetrachlorobenzene 0.24 120 107 114 91 122 nd nd 107

Pentachlorobenzene 0.12 100 98 99 68 87 nd nd 78

Pentachlorotoluene 0.18 112 107 110 105 95 nd nd 100

Hexachlorobenzene 0.14 99 89 94 88 62 <1 nd 75

2,2′,5-Trichlorobiphenyl 0.79 83 88 86 65 67 <1 3 68

2,2′,5,5′-Tetrachlorobiphenyl 0.52 109 112 111 93 81 13 16 102

2,2′,3,3′-Tetrachlorobiphenyl 0.34 128 134 131 93 80 20 16 105

2,2′,4,4′,5-Pentachlorobiphenyl 0.42 81 94 88 54 35 19 11 60

2,2′,4,4′,5,5′-Hexachlorobiphenyl 0.33 93 132 113 43 34 19 21 59

2,2′,3,3′,4,4′,5,5′-Octachlorobiphenyl 0.23 85 96 91 36 38 19 23 58

Octachlorostyrene 0.14 102 91 97 59 70 54 35 109

Mirex 0.33 87 101 94 28 35 23 25 56

Overall mean recovery 102 86

Source: From Fox, M.E., in Methods for Analysis of Organic Compounds in the Great Lakes, University of Wisconsin Sea Grant Institute, Madison, 1986, 27–34. With permission.

Note: nd, not detected.



Filterdisk

Pump

Inflow

Outflow

Sorbentcolumn

Flow meter

FIGURE 1.15 An example of a system for high-volume extraction in the �eld based on solid-phase extraction techniques.

TABLE 1.5

Published High-Volume Solid-Phase Extraction Con�gurations for Water Sampling in the Field

AdsorbantFilter

Cutoff (µm)Diameter

(cm)Flow Rate (mL min−1)

Column Dimensions

Volume Extracted (L)

Water Sampling Context and Reference

Insolute Env+ GF/F ns ns 200 mg 20 Arctic [59]

XAD-2 and Speedisks

GF/F ns 200 ns 50 High elevation lake [60]

XAD-2 0.1 14.2 300 75 g 100 Mountain lake [61]XAD-2 GF/F 29.3 <600 75 g ns Lake Superior [62]

XAD-2 0.7 29.3 1000 (�lter) 250 (column)

ns 65 Lake Michigan [63]

XAD-2 and PUF GF/F 14.2 100–1900 PUF: 5 × 30.5 cm 42–1000 Seawater [64]

0.5 XAD: 2.7 × 20 cmXAD-2 140 14 1600 2 × 75 g in parallel 1000 Ohio River [57]

XAD-2 and C18 GF/F ns 400 (XAD-2) XAD-2:50 g XAD: 50 Milli-Q and seawater [65]Empore 0.7 50 (C18) 90 mm dia disk C18:10XAD-2 None ns 50–200 37 cm length

2.5 cm dians Ocean outfalls, California

[66]XAD-2 Gelmasn AE

GF/F14.9 500 100 mL 221–435 Reef platform and

seawater basins [67]PUF GF/F 0.7 14.2 1000 45 mm length

30 mm dia30–40 Aluminum reduction plant

discharge [68]XAD-2 None ns <300 300 mm length

22 mm diameter150–400 Oceanic [69]

XAD-2 1.0 ns 1400 250 g and 2 × 75 g 400 San Francisco Estuary [70]

XAD-2 GF/F ns 5 bed volumes ns ns Deep Atlantic [71]

Source: From Stephens, S. and Mueller, J., in Passive Sampling Techniques in Environmental Monitoring, Elsevier, Amsterdam, 2006.

Note: ns, not stated.



extracting procedures and are prone to contamination during transport and handling [54]. Other sorbents such as SBD-1 or LiChrolut EN have been reported to be less susceptible to contamination [65,73]. Premature breakthrough (the formation of water channels) in the sorbent column is another potential problem in high-volume water SPE. More modern sorbent products such as particle-loaded Empore disks [74] and Bakerbond Speedisks are reportedly less prone to this problem [54].

Summaries of the properties of both classical and modern sorbents and their applications in high- and low-volume extractions of surface waters are found in Refs. [75,76]. Novel SPE products with application in surface water sampling will continue into the future, and detailed information concerning these as well as existing sorbents can be sourced from manufacturers.

1.4.5.2.2 Solid-Phase Extraction Using Floating Complexing Granules

A technique for solid-phase preconcentration of contaminants dissolved in surface waters has been presented in Ref. [77]. The method is based on application of extraction material that is not packed, as in conventional SPE systems, but instead is present in a freely �oating form, as in a �uidized-bed reactor. The feasibility of the �uidized-bed extraction approach has been demonstrated for the determination of heavy metals in surface waters using 8-hydroxyquinoline attached to solid supports as complexing agent. Recoveries, repeatability, and sensitivity appear satisfactory for this applica-tion, even when no �ltration of the sample is done. As �uidized-bed extraction is based on free-�oating, unpacked extraction material, the pressure drop over the column is minimal and �ltration is not required. Hence, the technique seems eminently suited for employment as an in situ, long-term, sampling method. As such, it will provide time-integrated contamination levels that are not biased by biological variability or �ltration artifacts, disadvantages of the commonly used methods for monitor-ing of contaminants in surface water.

1.4.5.3 Passive Sampler Devices

1.4.5.3.1 Overview

Systematic attempts have been made to develop passive sampling systems that accumulate chemicals, and from which reliable exposure concentrations can be calculated. The passive samplers used in such systems are usually designed either as “kinetic samplers” or as “equilibrium samplers.”

The concept of the equilibrium sampler is analogous to that of the octanol–water equilibrium partition coef�cient (Kow) used since the 1970s to predict the potential for persistent nonpolar contaminants to concentrate in aquatic organisms [71]. The use of equilibrium-type passive samplers in the aquatic envi-ronment depends on the development of a sampler–water partition coef�cient (Ksw) de�ned as the ratio of sampler to water concentration of the compound of interest at thermodynamic equilibrium. The other key parameter determining the utility of an equilibrium-type passive sampler is the time taken to reach an approximate equilibrium condition. A range of approaches applied in developing equilibrium-type passive samplers include polyethylene or silicon sheets of various volume to surface area ratio [78,79] and solid-phase microextraction techniques [80].

In the last two decades, there has been substantial progress in developing kinetics-based passive sam-plers for ultratrace pollutants in water. These allow prediction of time-averaged concentrations of chemi-cals for the period when samplers were exposed [81–87]. In principle, kinetic samplers rely on a large sampler capacity, or a large sampler–water partition coef�cient, for the contaminants to be sampled. This ensures that under sampling conditions, the concentration of the chemical within the sampler does not approach an equilibrium state during sampler exposure. The models used to calculate the chemical con-centration in the water-phase (Cp) sampled are based on the assumption that uptake is linearly related to the exposure concentration throughout exposure, that is, a �rst-order diffusion model. Resistance at either the hydrodynamic boundary layer or within the sampler membrane/sequestering phase acts to control con-taminant �ux into the sampler. The mean concentration in the water-phase Cp can then be predicted from

C

C VR tp

s s

s=



where Cs is the concentration of the analyte in the sampler, Vs is the sampler volume, Rs is the speci�c sampling rate, and t is the exposure period. Note that the volume of a sampler with a given con�guration is necessarily related to its sampling area for which Rs is determined in laboratory exposure experiments. Models such as the one above have been used to describe the behavior of passive samplers and to esti-mate the concentration of chemicals in water.

These time-integrating passive sampling techniques have become widely used in the last decade. In particular, the use of performance reference compounds introduced into the sampler to enable adjust-ment of �eld data from the samplers using kinetic data from the laboratory has increased user con�-dence in these sampling techniques. Table 1.6 provides a summary of the major types of such devices developed to date and their application. While some uncertainty factors associated with the use of these sampling techniques remain, such as their representativeness as mimics of biota uptake and measures of bioavailable fractions, as well as issues relating to biofouling and nonlinear uptake, the utility of these new sampling tools in part re�ects the limitations of the other techniques available. Accordingly, these sampling techniques provide an additional set of tools often useful for modern monitoring programs.

1.4.5.3.2 Kinetic Samplers for Nonpolar Organic Chemicals

The development of kinetic samplers for nonpolar chemicals in water commenced in the 1980s. Since then, probably the most widely used passive sampler design for nonpolar chemicals in water is the semi-permeable membrane device (SPMD). Standard commercially available SPMDs consist of a strip of nonporous polyethylene tubing �lled with a small volume (1 mL) of triolein [87]. Other samplers using the same approach, but different membranes and/or solvent–lipids combinations (e.g., hexane or tri-methylpentane), are also used [88]. It has been argued that the combination of small solvent or lipid volume with a large membrane simulates the high surface-area-to-volume ratios characteristic of gill structures. Trace levels of contaminants that cannot be detected in conventional water samples are often concentrated to detectable levels by SPMDs or similar devices placed in water for a controlled exposure period. One general problem with passive samplers is that they can become coated with a bio�lm that

TABLE 1.6

Examples of Passive Samplers for Trace Aquatic Pollutants

Chemicals of Interest for Sampling Purposes Sampler Types Comments

Nonpolar organic pollutants, for example, PAHs, PCBs, OCs, and other nonpolar pesticides

Semipermeable membrane device (SPMD)

(1) PE only samplers(2) Trimethylpentane �lled PE sampler

A relatively large surface area of nonpolar membrane is required because these chemicals often occur at ultratrace levels. SPMDs are commercially available and the most widely used type of passive samplers to date. Some advantages for SPMDs over other passive sampler types are the availability of the largest set of calibration data together with an extensive literature and the use of performance reference compounds for in situ calibration is routine. However, analysis of SPMDs is relatively complex compared to PE and trimethylpentane samplers. All samplers have biofouling issues

Polar chemicals Polar organic chemical-integrated sampler (POCIS); Portsmouth sampler using solid-phase sorbent-based samplers

Relatively new methods developed in parallel through the last decade. Limitations to the methods and availability of the devices at the present time should be solved in the near future. The optional use of different phases and membranes or even deployment without a membrane provides a high selectivity and �exibility in the analytes targeted. To date, few calibration data are available and the polar samplers are not yet widely used for routine monitoring but show great potential

Metals, radionuclides, and some nutrients

Diffusion gradient in thin �lms (DGT) and equilibrium techniques such as Peepers and DETs

Developed in the 1990s, these are now a widely used method for monitoring certain trace metals. To date, primarily used in research and not for routine monitoring, although increasing numbers of studies show the potential of this technique for sampling metals. Discussion continues concerning the fraction of metal collected with DGTs



reduces the uptake of organic chemicals [89]. Furthermore, the uptake also depends on temperature and the boundary layer between membrane and water. All these parameters are dif�cult to assess over a long exposure period (weeks). However, in situ calibration techniques have been developed that can be used to obtain information on kinetics to improve the predictive capabilities of passive sampling techniques [87]. A typical form of the SPMD passive sampling device is illustrated in Figure 1.16.

1.4.5.3.3 Kinetic Passive Samplers for Polar Organic Chemicals

In the last decade, the importance of polar organic pollutants has resulted in the development of kinetic samplers for polar organic pollutants. These types of samplers typically consist of a solid-phase absorp-tion media with a relatively high capacity for the chemical of interest, combined in most cases with a membrane that allows diffusion of polar chemicals. Examples of these types of devices include the Chemcatcher passive sampling device developed by Kingston et al. [84], which is a very robust passive sampling device that employs the C18 Empore disk as the absorbant media. Similarly, Alvarez et al. developed the polar organic chemical-integrated sampler [92]. Stephens and Mueller [54] have demon-strated that SDB Empore disks without membranes are effective samplers for herbicides. An illustration of the Chemcatcher device is illustrated in Figure 1.17. As the use of performance reference compounds for polar organic compounds is still de�cient [93,94] samplers need to be calibrated in situ to derive time-weighted average concentrations from kinetic sampling.

1.4.5.3.4 Devices Comprising Diffusive and Resin Gels

The diffusion gradient in thin �lms (DGT) device originally developed in the early 1990s at Lancaster University (UK) [86] employs a resin gel as the accumulating absorbant media, overlaid by a �lter (to exclude particulates) and a diffusive hydrogel to maintain a concentration gradient, with the whole loaded into a cylindrical plastic housing (Figure 1.18). A series of different gels have been developed to sample a range of metals (both labile and organic species), phosphorus, sul�des, and radioactive cesium, and are available in a range of thicknesses. Parallel deployment of two DGT units assembled with different diffu-sive gel thicknesses allows accurate measurement under low �ow conditions. For measurement of metal concentrations, the DGT has been shown to give results close to those of anodic stripping voltammetry [86,86], and with dissolved metals measured by �ltration or in situ dialysis when the natural waters con-tain low proportions of metals present as colloids or strong complexes [95,96].

An important advantage of using DGT to measure metals in saline or marine waters is that the gels do not accumulate the major ions that often cause interferences in the analysis of metals in grab samples of water. The devices sample satisfactorily over a range of pH, with the range limits varying between

A length of sealed lay-flat PE tubing (themembrane) containing a small volume oftriolene (the absorbant phase) is wovenaround a stainless steel frameThe device is then inserted into a perforatedstainless steel shroud for protection frommechanical damage during deployment

Photograph supplied by M. Shaw,EnTox, Brisbane, Australia

FIGURE 1.16 An example of a semipermeable sampling device (SPMD).



5

6

10

1

7

4

21 7

39

568 11

Exposure towater column

The sampler consists of three interlocking sections (2, 3, 9) manufactured from polytetrafluoroethylene(PTFE) that screw together during deployment to form water-tight seals (4, 10)

Integral to the device is a 50 mm rigid PTFE disk (7) designed to support both the chromatographicreceiving phase (5) and the diffusion-limiting membrane (6)

On the reverse is a lug (1) for attaching the device during deployment

The surface of the diffusion-limiting membrane is protected from mechanical damage duringdeployment by a mesh (8) of either stainless steel for organic analytes or nylon for inorganic analytes.This mesh is held in place during deployment by a removable PTFE ring (g)

A PTFE screw cap (11) replaces the ring (9) during transport to and from the deployment site

FIGURE 1.17 The Chemcatcher passive sampler. (Reproduced from Kingston, J.K. et al. J. Environ. Monit., 2, 487, 2000. With permission.)

(a)

(b)C

(c)

20 mm

Membrane filterDiffusive gelBinding gel

Diagram supplied by Jerry Forsberg,Lulea° University of Technology, Sweden

FIGURE 1.18 The diffusion gradient in thin �lms (DGT) passive sampler. (a) Oblique view of sampler, (b) sampler in cross-section, and (c) enlargement of the section marked in (b).



metals (e.g., down to pH 2 for Cu, but only 4.5 for Cd) and over the range pH 2 to 9 for phosphate [97]. For published reports from �eld trials of DGT devices, see Refs. [98,99].

A variant of the device, known as diffusive equilibrium in thin �lms (DET), can be deployed to per-form relatively rapid (within a day) response times and has the ability to measure at high spatial resolu-tion. The DET comprises a single relatively thick sheet of gel (typically 0.8 mm) supported in a holder. Solutes in the surrounding water diffuse into the gel until concentrations in gel and water are equal.

DGT and DET devices, for both of which the University of Lancaster (UK) holds a worldwide patent, are available commercially, either preassembled or in kit form (gel disks and strips for local assembly). For details of supply, see http://www. dgtresearch.com.

1.4.6 Concentration of Contaminants in Suspensions and Sediment

It is generally accepted that heavy metals both of geogenic (i.e., natural) origin, like the so-called ref-erence elements, and those introduced anthropogenically are preferentially found (by 85–95%) in the �ne-grain fraction (≤ 20 μm fraction) of aquatic sediments and suspended solids. Similar conditions are assumed for pesticides with low water solubilities [100]. For this reason, sampling of contaminants in the suspended particulates can sometimes be much more effective than sampling in the water phase. In a study in the North Saskatchewan River [101], pathways and distribution of anthropogenic contaminants in water and in suspended and bottom sediments were examined. Synoptic sampling during stable low �ow allows maximum inference of point sources and, therefore, of chemical complexity. After chemical extraction of contaminants into two fractions for aqueous samples and �ve fractions for sediment sam-ples, the authors were able to assess the toxicity of the fractions using two independent bioassays. The results called into question the ef�cacy of a standard menu of priority chemicals applied to water samples for ambient (i.e., not end-of-pipe) aquatic quality sensing (monitoring) purposes. They concluded that water may be an inappropriate medium upon which to base toxic chemical criteria for toxic chemical sensing purposes in aquatic systems. Furthermore, a study on 97 pesticides in 24 streams comparing sediment sampling, grab water sampling, and passive sampling showed that sediment samples were most suitable to characterize toxic exposure of benthic organisms [102]. Nevertheless, for polar compounds, a similar study demonstrated that water and passive samplers deliver more relevant information for toxic exposure of aquatic organisms to pesticides than suspended-particle concentrations [103].

1.4.6.1 Suspended-Particle Sampler for Small Streams

An economical alternative to event-controlled sampling for sampling potentially contaminated sus-pended particles in small streams is the employment of sedimentation vessels (suspended particle sam-pler [SPS]) through which the water �ows continuously [104]. The SPS (Figure 1.19) is positioned in the stream so that water �ows through it from (a) to (e). It includes a 10 L sedimentation vessel (c) made of

e db a

gf

c

a: Inflowing waterb: Inlet tubec: Collecting vessel (10 L)d: Outlet tubee: Outflowing waterf: Cover plateg: Stainless steel box

WaterSediment

FIGURE 1.19 Construction of the suspended particle sampler (SPS). (Reproduced from Liess, M., Schulz, R., and Neumann, M., Chemosphere, 32(10), 1963, 1996. With permission.)



glass. This vessel is seated in a stainless-steel box (g) inserted into the bottom sediment of the stream. The box, closed by a cover plate (f) made of stainless steel, is positioned with the cover plate in the same plane as the stream bed, to prevent mobilization of the stream sediment in the region of the inlet tube (b). In addition to the inlet tube, an outlet tube (d) is mounted in the cover plate. Both tubes are 34 mm in diameter. The inlet tube is closed at its upper end and has a slit measuring 25 × 5 mm in the wall facing upstream. As a result, a pressure �ow is directed into the collecting vessel. The outlet tube is cut at an angle of 45° at its upper end, forming an opening facing downstream (e), exerting suction on the collect-ing vessel. By rotating the outlet tube, the magnitude of the suction effect can be changed, so that the velocity of �ow into the inlet tube can be matched to the current of the stream. The height of the inlet opening can be adjusted to enable sampling at any desired level in the water. This device cannot be used to measure exact maximal concentration, but gives the mean sediment contamination during the period from one emptying of the vessel to the next.

The grain-size-speci�c retention of the SPS was determined in laboratory experiments for the differ-ent �ow velocities (Figure 1.20). As expected, the amount retained by the SPS decreased with increasing rate of �ow. In evaluating retention properties, particular weight was placed on the small grain sizes

Current: 0.05 m s−1

Current: 0.12 m s−1

100908070605040302010

0100

908070605040302010

0100

90

2010

0

Current: 0.41 m s−1807060504030Re

tent

ion

(%)

Rete

ntio

n (%

)Re

tent

ion

(%)

<0.002 0.002<0.006

0.006<0.02 <0.06 <0.02

0.02 0.06

Grain size (mm)

Org. C

FIGURE 1.20 Retention by the suspended particle sampler (SPS) for current velocities between 0.05 and 0.41 m s−1. (Reproduced from Liess, M., Schulz, R., and Neumann, M., Chemosphere, 32(10), 1963, 1996. With permission.)



because pollutants become attached preferentially to the grain-size fraction below 0.02 mm grain diam-eter [25]. At the highest �ow velocity, 0.41 m s−1, the retention rate was 15% for the grain-size fraction smaller than 0.02 mm. However, such rapid �ow is rare in �atland streams. With the lower �ow veloci-ties tested here, the retention rate for this fraction was between 27% and 50%. The proportion of organic carbon retained, another parameter that is important regarding pesticide content, was between about 40% and 60% for these currents.

An example of long-term measurements of the concentrations of parathion-ethyl in an agricultural stream is shown in Figure 1.21.

0

5

10

15

20

*

0

5

10

15

20

* 1

10

100

1000

0

5

10

15

20

* 1

10

100

10000

5

10

15

20

*

50

1

10

100

10001

10

100

1000

Conc

entr

atio

n (μ

g kg

−1 d

w)

Disc

harg

e (L

s−1)

1995

1994

1993

1992

Time (month)Feb. Mar. Apr. May Jun. Jul. Sep. Oct. Nov.Aug.Jan. Dec.

FIGURE 1.21 Discharge and concentration of parathion-ethyl in suspended particles sampled with the SPS in an agri-cultural stream. * = limit of analytical determination. (Reproduced from Liess, M. et al. Water Res., 33(1), 239, 1999. With permission.)



ACKNOWLEDGMENTThe authors acknowledge the contribution of Ralf Schulz in the �rst edition of this chapter as published in Handbook of Water Analysis edited by L.M.L. Nollet, Marcel Dekker, New York, 2000.

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HMSO, 1980, pp. 15–48. 19. J. Hilton, T. Carrick, E. Rigg, and J.P. Lishman. Sampling strategies for water quality monitoring in lakes:

The effect of sampling method. Environ. Pollut., 57:223–234, 1989. 20. G.R. Martin, J.L. Smoot, and K.D. White. A comparison of surface-grab and cross sectionally integrated

stream-water-quality sampling methods. Water Environ. Res., 64:866–876, 1992. 21. K.G. Malle. Cleaning-up the River Rhine. Sci. Am., 274:55–59, 1996. 22. R.B. Grayson, C.J. Gippel, B.L. Finlayson, and B.T. Hart. Catchment-wide impacts on water quality: The

use of “snap shot” sampling during stable �ow. J. Hydrol., 199:121–134, 1997. 23. L.W.G. Higler. Caddis larvae in a Dutch lowland stream. Proceedings of the Third International

Symposium on Trichoptera, Perugia, Italy, 1981, pp. 127–128. 24. C.M. Cooper. Biological effects of agriculturally derived surface-water pollutants on aquatic systems—A

review. J. Environ. Qual., 22:402–408, 1993. 25. H. Ghadiri and C.W. Rose. Sorbed chemical transport in overland �ow. 2. Enrichment ratio variation with

erosion processes. J. Environ. Qual., 20:634–642, 1991. 26. J. Kreuger. Monitoring of pesticides in subsurface and surface water within an agricultural catchment

in southern Sweden. British Crop Protection Council Monograph No 62: Pesticide Movement to Water, 81–86, 1995.



27. R.D. Wauchope. The pesticide content of surface water draining from agricultural �elds—A review. J. Environ. Qual., 7:459–472, 1978.

28. T. Kohonen. Influence of Sampling Frequency on the Estimates of Runoff Water Quality. Helsinki: Water Research Institute, 1982.

29. M. Liess, R. Schulz, H.-D. Liess, B. Rother, and R. Kreuzig. Determination of insecticide contamination in agricultural headwater streams. Water Res., 33(1):239–247, 1999.

30. I.G. Droppo and C. Jaskot. Impact of river transport characteristics on contaminant sampling error and design. Environ. Sci. Technol., 29:161–170, 1995.

31. M.L. Richardson and J.M. Bowron. Notes on Water Research No. 32. Medmenham, Bucks: Water Research Centre, 1983, 241pp.

32. A.G. Kelly, I. Cruz, and D.E. Wells. Polychlorobiphenyls and persistent organochlorine pesticides in sea water at the pg L−1 level. Sampling apparatus and analytical methodology. Anal. Chim. Acta, 276:3–13, 1993.

33. A.D. Jassby, B.E. Cole, and J.E. Cloern. The design of sampling transects for characterizing water quality in estuaries. Estuar. Coast. Shelf Sci., 45:285–302, 1997.

34. D. Barcelo and M.C. Hennion. Sampling of polar pesticides from water matrices. Anal. Chim. Acta, 338:3–18, 1997.

35. L. Friling. Monitoring storm water runoff. Pollut. Eng., 25:36–39, 1993. 36. C.G. Daughton and I.S. Ruhoy. Environmental footprint of pharmaceuticals: The signi�cance of factors

beyond direct excretion to sewers. Environ. Toxicol. Chem., 28(12):2495–2521, 2009. 37. Treating Contaminants of Emerging Concern. A Literature Review Database. US Environmental

Protection Agency Of�ce of Water (4303T). EPA-820-R-10-002, 2010. 38. C. Ort, M.G. Lawrence, J. Reungoat, and J.F. Mueller. Sampling for PPCPs in wastewater systems:

Comparison of different sampling modes and optimization strategies Environ. Sci. Technol., 44, 6289–6296, 2010.

39. M.G. Lawrence and D.G. Bariel. Tracing treated wastewater in an inland catchment using anthropogenic gadolinium. Chemosphere, 80:794–799, 2010.

40. M. Rabiet, F. Brissaud, J.L. Seidel, S. Pistre, and F. Elbaz-Poulichet. Positive gadolinium anomalies in wastewater treatment plant ef�uents and aquatic environment in the Herault watershed (South France). Chemosphere, 75, 1057–1064, 2009.

41. D.J. Harper. A new trace metal-free surface water sampling device. Mar. Chem., 21:183–188, 1987. 42. P. Conan, M. Pujo-Pay, M. Leveau, and P. Raimbault. Une autre utilisation du systeme let-go:

Echantillonnage rapide d’une colonne d’Eau Entre 0 et 200 M. Annales de L’Institut Oceanographique, 72:221–227, 1996.

43. G.C. Kineke and R.W. Sternberg. The effect of particle settling velocity on computed suspended sedi-ment concentration pro�les. Mar. Geol., 90:159–174, 1989.

44. I.N. McCave and T.J. Gross. The effect of particle settling velocity on computed suspended sediment concentration pro�les. Mar. Geol., 99:403–413, 1991.

45. L. Thomsen, G. Graf, V. Martens, and E. Steen. An instrument for sampling water from the benthic boundary layer. Cont. Shelf Res., 14:871–882, 1994.

46. U. Eversberg. A new device for sampling water from the benthic boundary layer. Helgolaender Meeresunter Suchungen, 44:329–334, 1990.

47. M. Dickman and F. Johnson. Deployment of a threshold activated pump sampler in an industrial shock load impact study. Hydrobiologia, 344:181–193, 1997.

48. J. Hodge, B. Longstaff, A. Steven, P. Thornton, P. Ellis, and I. McKelvie. Rapid underway pro�ling of water quality in Queensland estuaries. Mar. Pollut. Bull., 51:113–118, 2005.

49. J. Udy, M. Gall, B. Longstaff, K. Moore, C. Roelfsema, D.R. Spooner, and S. Albert. Water quality moni-toring: A combined approach to investigate gradients of change in the Great Barrier Reef, Australia. Mar. Pollut. Bull., 51:224–238, 2005.

50. R. Schulz, M. Hauschild, M. Ebeling, J. Nanko-Drees, J. Wogram, and M. Liess. A qualitative �eld method for monitoring pesticides in the edge-of-�eld runoff. Chemosphere, 36(15):3071–3082, 1998.

51. B. Koopman, C.M. Stevens, C.L. Logue, P. Karney, and G. Bitton. Automatic sampling equipment and BOD test nitri�cation. Water Res., 23:1555–1562, 1989.



52. H. Hermans, F. Smedes, J.W. Hofstratt, and W.P. Co�no. A method for estimation of chlorinated biphe-nyls in surface waters: In�uence of sampling method on analytical results. Environ. Sci. Technol., 26:2028–2035, 1992.

53. M.E. Fox. A practical sampling and extraction system for the quantitative analysis of sub-ng/L organo-chlorine contaminants in �ltered water and suspended solids. In: W.C. Sonzogni and D.J. Dube, eds. Methods for Analysis of Organic Compounds in the Great Lakes. Madison, WI: University of Wisconsin Sea Grant Institute, 1986, pp. 27–34.

54. S. Stephens and J. Mueller. Techniques for quantitatively evaluating aquatic passive sampling devices. In: R. Greenwood, G.A. Mills, and B. Vrana, eds. Passive Sampling Techniques in Environmental Monitoring. Comprehensive Analytical Chemistry Series, Damia Barcelo (series editor), Elsevier: Amsterdam, 2006.

55. J.E. Woodrow, M.S. Majewski, and J.N. Seiber. Accumulative sampling of trace pesticides and other organics in surface water using XAD-4 resin. J. Environ. Sci. Health B, 21:143–164, 1986.

56. M. Knutsson, G. Nilve, L. Mathiasson, and J.A. Jonsson. Supported liquid membranes for sampling and sample preparation of pesticides in water. J. Chromatogr. A, 754:197–205, 1996.

57. S.A. Dinkins. Quanti�cation of dioxin concentrations in the Ohio River using high volume water sam-pling. Available online at: http://tinyurl.com/9valj.

58. M. Winkler, G. Kopf, C. Hauptvogel, and T. Neu. Fate of arti�cial musk fragrances associated with suspended particulate matter (SPM) from the River Elbe (Germany) in comparison to other organic con-taminants. Chemosphere, 37(6):1139–1156, 1998.

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63. D.R. Achman, K.C. Hornbuckle, and S.J. Eisenreich. Volatilization of polychlorinated biphenyls from Green Bay, Lake Michigan. Environ. Sci. Technol., 27(1):75–87, 1993.

64. J.I. Gomez-Bellinchon, J.O. Grimalt, and J. Albaiges. Intercomparison study of liquid–liquid extraction and adsorption on polyurethane and Amberlite XAD-2 for the analysis of hydrocarbons, polychlorobi-phenyls, and fatty acids dissolved in seawater. Environ. Sci. Technol., 22:677–685, 1988.

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66. D.R. Green, J.K. Stull, and T.C. Heesen. Determination of chlorinated hydrocarbons in coastal waters using a moored in situ sampler and transplanted live mussels. Mar. Pollut. Bull., 17(7):324–329, 1986.

67. M.G. Ehrhard and K.A. Burns. Petroleum derived dissolved organic compounds concentrated from inshore waters in Bermuda. J. Exp. Mar. Biol. Ecol., 138(1):35–47, 1990.

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73. A. Rantalainen, M. Ikonomou, M.G. Ikonomou, and I.H. Rogers. Lipid-containing semipermeable mem-brane devices (SPMDs) as concentrators of toxic chemicals in the lower Fraser River, Vancouver, British Columbia. Chemosphere, 37(6):1119–1138, 1998.

74. T. McDonnell and J. Rosen�eld. Solid-phase sample preparation of natural waters with reversed-phase disks. J. Chromatogr. A, 629(1):41–53, 1993.

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78. J. Müller, M. Krishnamohan, M. Mortimer, and M.S. McLaughlin. Partitioning of polycyclic aromatic hydrocarbons in the polyethylene/water system. Fresen. J. Anal. Chem., 371:816–822, 2001.

79. R.B. Schäfer, L. Hearn, B.J. Kefford, D. Nugegoda, and J.F. Mueller, Using silicone passive samplers to detect polycyclic aromatic hydrocarbons from wild�res in streams and potential acute effects for inver-tebrate communities. Water Res., 44(15):4590–4600, 2010.

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89. R.B. Schäfer, A. Paschke, and M. Liess. Aquatic passive sampling of a short-term thiacloprid pulse with the Chemcatcher: Impact of biofouling and use of a diffusion-limiting membrane on the sampling rate. J. Chromatogr., 1203(1):1–6, 2008.

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94. M. Shaw, G. Eaglesham, J.F. Mueller. Uptake and release of polar compounds in SDB-RPS Empore (TM) disks; implications for their use as passive samplers. Chemosphere, 75(1):1–7, 2009.

95. H. Zang and W. Davidson. Performance characteristics of the technique of diffusion gradients in thin �lms (DGT) for the measurement of trace metals in aqueous solution. Anal. Chem., 67:3391–3400, 1995.

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1 Chapter 1 - Sampling Methods in SurfaceWaters

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19. J. Hilton, T. Carrick, E. Rigg, and J.P. Lishman.Sampling strategies for water quality monitoring in lakes:The effect of sampling method. Environ. Pollut.,57:223–234, 1989.

20. G.R. Martin, J.L. Smoot, and K.D. White. A comparisonof surface-grab and cross sectionally integratedstream-water-quality sampling methods. Water Environ. Res.,64:866–876, 1992.

21. K.G. Malle. Cleaning-up the River Rhine. Sci. Am.,274:55–59, 1996.

22. R.B. Grayson, C.J. Gippel, B.L. Finlayson, and B.T.Hart. Catchment-wide impacts on water quality: The use of“snap shot” sampling during stable �ow. J. Hydrol.,199:121–134, 1997.

23. L.W.G. Higler. Caddis larvae in a Dutch lowland stream.Proceedings of the Third International Symposium onTrichoptera, Perugia, Italy, 1981, pp. 127–128.

24. C.M. Cooper. Biological effects of agriculturallyderived surface-water pollutants on aquatic systems—Areview. J. Environ. Qual., 22:402–408, 1993.

25. H. Ghadiri and C.W. Rose. Sorbed chemical transport in

overland �ow. 2. Enrichment ratio variation with erosionprocesses. J. Environ. Qual., 20:634–642, 1991.

26. J. Kreuger. Monitoring of pesticides in subsurface andsurface water within an agricultural catchment in southernSweden. British Crop Protection Council Monograph No 62:Pesticide Movement to Water, 81–86, 1995.

27. R.D. Wauchope. The pesticide content of surface waterdraining from agricultural �elds—A review. J. Environ.Qual., 7:459–472, 1978.

28. T. Kohonen. Influence of Sampling Frequency on theEstimates of Runoff Water Quality. Helsinki: WaterResearch Institute, 1982.

29. M. Liess, R. Schulz, H.-D. Liess, B. Rother, and R.Kreuzig. Determination of insecticide contamination inagricultural headwater streams. Water Res., 33(1):239–247,1999.

30. I.G. Droppo and C. Jaskot. Impact of river transportcharacteristics on contaminant sampling error and design.Environ. Sci. Technol., 29:161–170, 1995.

31. M.L. Richardson and J.M. Bowron. Notes on WaterResearch No. 32. Medmenham, Bucks: Water Research Centre,1983, 241pp.

32. A.G. Kelly, I. Cruz, and D.E. Wells.Polychlorobiphenyls and persistent organochlorinepesticides in sea water at the pg L −1 level. Samplingapparatus and analytical methodology. Anal. Chim. Acta,276:3–13, 1993.

33. A.D. Jassby, B.E. Cole, and J.E. Cloern. The design ofsampling transects for characterizing water quality inestuaries. Estuar. Coast. Shelf Sci., 45:285–302, 1997.

34. D. Barcelo and M.C. Hennion. Sampling of polarpesticides from water matrices. Anal. Chim. Acta,338:3–18, 1997.

35. L. Friling. Monitoring storm water runoff. Pollut.Eng., 25:36–39, 1993.

36. C.G. Daughton and I.S. Ruhoy. Environmental footprintof pharmaceuticals: The signi�cance of factors beyonddirect excretion to sewers. Environ. Toxicol. Chem.,28(12):2495–2521, 2009.

37. Treating Contaminants of Emerging Concern. A LiteratureReview Database. US Environmental Protection Agency Of�ceof Water (4303T). EPA-820-R-10-002, 2010.

38. C. Ort, M.G. Lawrence, J. Reungoat, and J.F. Mueller.Sampling for PPCPs in wastewater systems: Comparison ofdifferent sampling modes and optimization strategiesEnviron. Sci. Technol., 44, 6289– 6296, 2010.

39. M.G. Lawrence and D.G. Bariel. Tracing treatedwastewater in an inland catchment using anthropogenicgadolinium. Chemosphere, 80:794–799, 2010.

40. M. Rabiet, F. Brissaud, J.L. Seidel, S. Pistre, and F.Elbaz-Poulichet. Positive gadolinium anomalies inwastewater treatment plant ef�uents and aquatic environmentin the Herault watershed (South France). Chemosphere, 75,1057–1064, 2009.

41. D.J. Harper. A new trace metal-free surface watersampling device. Mar. Chem., 21:183–188, 1987.

42. P. Conan, M. Pujo-Pay, M. Leveau, and P. Raimbault. Uneautre utilisation du systeme let-go: Echantillonnagerapide d’une colonne d’Eau Entre 0 et 200 M. Annales deL’Institut Oceanographique, 72:221–227, 1996.

43. G.C. Kineke and R.W. Sternberg. The effect of particlesettling velocity on computed suspended sedimentconcentration pro�les. Mar. Geol., 90:159–174, 1989.

44. I.N. McCave and T.J. Gross. The effect of particlesettling velocity on computed suspended sedimentconcentration pro�les. Mar. Geol., 99:403–413, 1991.

45. L. Thomsen, G. Graf, V. Martens, and E. Steen. Aninstrument for sampling water from the benthic boundarylayer. Cont. Shelf Res., 14:871–882, 1994.

46. U. Eversberg. A new device for sampling water from thebenthic boundary layer. Helgolaender MeeresunterSuchungen, 44:329–334, 1990.

47. M. Dickman and F. Johnson. Deployment of a thresholdactivated pump sampler in an industrial shock load impactstudy. Hydrobiologia, 344:181–193, 1997.

48. J. Hodge, B. Longstaff, A. Steven, P. Thornton, P.Ellis, and I. McKelvie. Rapid underway pro�ling of water

quality in Queensland estuaries. Mar. Pollut. Bull.,51:113–118, 2005.

49. J. Udy, M. Gall, B. Longstaff, K. Moore, C. Roelfsema,D.R. Spooner, and S. Albert. Water quality monitoring: Acombined approach to investigate gradients of change in theGreat Barrier Reef, Australia. Mar. Pollut. Bull.,51:224–238, 2005.

50. R. Schulz, M. Hauschild, M. Ebeling, J. Nanko-Drees, J.Wogram, and M. Liess. A qualitative �eld method formonitoring pesticides in the edge-of-�eld runoff.Chemosphere, 36(15):3071–3082, 1998.

51. B. Koopman, C.M. Stevens, C.L. Logue, P. Karney, and G.Bitton. Automatic sampling equipment and BOD testnitri�cation. Water Res., 23:1555–1562, 1989.

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FURTHER READING

Books

KR Beebe, RJ Pell, and MB Seasholtz. 1998. Chemometrics: APractical Guide. New York: Wiley & Sons.

RG Brereton. 2003. Chemometrics—Data Analysis for theLaboratory and Chemical Plant. Chichester: Wiley.

S Brown, R Tauler, and B Walczak (eds). 2009. ComprehensiveChemometrics, 1st edition. Chemical and Biochemical DataAnalysis. Amsterdam: Elsevier.

R Leardi (ed). 2003. Nature-Inspired Methods inChemometrics: Genetic Algorithms and Artificial NeuralNetworks, in Data Handling in Science and TechnologySeries, vol. 23. Amsterdam: Elsevier.

BFJ Manly. 1986. Multivariate Statistical Methods. APrimer. London: Chapman and Hall.

H Martens and T Naes. 1991. Multivariate Calibration. NewYork: Wiley & Sons.

DL Massart, BGM Vandeginste, SN Deming, Y Michotte, and LKaufman. 1990. Chemometrics: A Textbook, in Data Handlingin Science and Technology Series, vol. 2. Amsterdam:Elsevier.

DL Massart, BGM Vandeginste, LMC Buydens, S de Jong, PJLewi, and J Smeyers-Verbeke. 1997. Handbook ofChemometrics and Qualimetrics, Part A, in Data Handling inScience and Technology Series, vol. 20A. Amsterdam:Elsevier.

DL Massart, BGM Vandeginste, LMC Buydens, S de Jong, PJLewi, and J Smeyers-Verbeke. 1998. Handbook ofChemometrics and Qualimetrics, Part B, in Data Handling inScience and Technology Series, vol. 20B. Amsterdam:Elsevier.

M Meloun, J Militky, and M Forina. 1992. Chemometrics forAnalytical Chemistry. Vol 1: PC-Aided Statistical DataAnalysis. Chichester: Ellis Horwood.

M Meloun, J Militky, and M Forina. 1994. Chemometrics forAnalytical Chemistry. Vol 2: PC-Aided Regression andRelated Methods. Hemel Hempstead: Ellis Horwood.

MA Sharaf, DL Illman, and BR Kowalski. 1986. Chemometrics,in Chemical Analysis, A Series of Monographs on AnalyticalChemistry and Its Applications Series, vol. 82, PJ Elving,JD Winefordner (eds.,) New York: Wiley & Sons.

Websites

http://ull.chemistry.uakron.edu/chemometrics/

http://www.chemometry.com/

http://www.models.kvl.dk/

http://www.namics.nysaes.cornell.edu/

http://www.spectroscopynow.com

http://statmaster.sdu.dk/courses/ST02/index.html

http://www.statsoft.com/textbook/stathome.html Section IIRadioanalytical Analysis

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TABLE 5.16

Selective Media for the Enumeration of Staphylococcus Usingthe MPN Method

Medium Typical Reactions Incubation Conditions Reference

Presumptive Test

m-Staphylococcus broth Growth (turbid medium) 35°C ± 1°Cfor 24 h APHA 1998

Trypticase soy broth

(TSB) with 10% NaCl

and 1% sodium pyruvate Growth (turbid medium) 35°C for 48 ±2 h APHA 1998

Baird–Parker (BP)

medium Shiny, black convex colonies (1–5 mm in diameter)surrounded by clear zone 35°C for 48 ± 2 h APHA 1998

Confirmation Test

Lipovitellin salt mannitol

agar Colonies surrounded with yellow (after 48 h) oropaque (after 24 h) zones 35°C ± 1°C for 24–48 h APHA 1998

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(a) (b) Gar_98 Transparency Transparency Como_AbbadiaMag_99 Mag_97 Mag_98 Gar_99 Ise_99 Alkalinity Alkalinity TPTribon Volvoc Chl a 1

–1.0

– 1

. 0 1.0

1 . 0 – 1 . 0 1 . 0 –1.0 1.0 1.5 3.5 54 Chloro NostocChlamy Desmid Zygnem Peridi Ochrom Oscill Pennal CryptoCentra Chrooc Prymne Lug_99 Ise_98 Lug_98 Lug_00 Ise_00 Chla TP

FIGURE 7.8 Ordination of (a) some alpine lakes and (b)phytoplankton orders in a canonical correspondence analysis

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9 Chapter 9 - Analysis of SulfurCompounds in Water

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4. D. Tang, L.-S. Wen, and P.H. Santschi. Analysis ofbiogenic thiols in natural water samples byhigh-performance liquid chromatographic separation anduorescence detection with ammonium7-�uorobenzo2-oxa-1,3-diazole-4-sulfonate (SBD-F). Anal.Chim. Acta, 408, 299–307, 2000.

5. S. Bilgi and C. Demir. Identi�cation of photooxidationdegradation products of C.I. Reactive Orange 16 dye by gaschromatography–mass spectrometry. Dyes Pigments, 66, 69–76,2005.

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7. Y. Miura, Y. Matsushita, and P.R. Haddad. Stabilizationof sul�de and sul�te and ion-pair chromatography ofmixtures of sul�de, sul�te, sulfate and thiosulfate. J.Chromatogr. A, 1085, 47–53, 2005.

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9. A. Kloepfer, M. Jekel, and T. Reemtsma. Determination ofbenzothiazoles from complex aqueous samples by liquidchromatography–mass spectrometry following solid-phaseextraction. J. Chromatogr. A, 1058, 81–88, 2004.

10. T. Reemtsma. Analysis of sulphotalimide and some of itsderivatives by liquid chromatography–electrospray

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11. C. Crescenzi, A. Di Corcia, A. Marcomini, G. Pojana,and R. Samperi. Method development for trace determinationof poly(naphthalenesulfonate)-type pollutants in water byliquid chromatography–electrospray mass spectrometry. J.Chromatogr. A, 923, 97–105, 2001.

12. F. Hissner, J. Mattusch, and K. Heinig. Quantitativedetermination of sulfur-containing anions in complexmatrices with capillary electrophoresis and conductivitydetection. J. Chromatogr. A, 848, 503–513, 1999.

13. L. Ferrer, G. de Armas, M. Miró, J.M. Estela, and V.Cerdà. A multisyringe �ow injection method for theautomated determination of sul�de in waters usingminiaturised optical �ber spectrophotometer. Talanta, 64,1119–1126, 2004.

14. M.S.P. Silva, C.X. Galhardo, and J.C. Masini.Application of sequential injection-monosegmented �owanalysis (SI-MSFA) to spectrophotometric determination ofsulphide in simulated waters samples. Talanta, 60, 45–52,2003.

15. D.S. Mackie, C.M.G. van den Berg, and J.W. Readman.Determination of pyrithione in natural waters by cathodicstripping voltammetry. Anal. Chim. Acta, 511, 47–53, 2004.

16. L. Ferrer, G. de Armas, M. Miró, J.M. Estela, and V.Cerdá. Interfacing in-line gas-diffusion separation withoptrode sorptive preconcentration exploiting multisyringe�ow injection analysis. Talanta, 68, 343–350, 2005.

17. I.P.A. Morais, M.R.S. Souto, T.I.M.S. Lopes, andA.O.S.S. Rangel. Use of a single air segment to minimisedispersion and improve mixing in sequential injection:Turbidimetric determination of sulphate in waters. WaterRes., 37, 4243–4249, 2003.

18. G. de Armas, L. Ferrer, M. Miró, J.M. Estela, and V.Cerdá. In-line membrane separation method for sul�demonitoring in wastewaters exploiting multisyringe �owinjection analysis. Anal. Chim. Acta, 524, 89–96, 2004.

19. M.C. Alonso, L. Tirapu, A. Ginebreda, and D. Barceló.Monitoring and toxicity of sulfonated derivatives ofbenzene and naphthalene in municipal treatment plants.Environ. Pollut., 137, 232–262, 2005.

20. K.J. Huang, C.H. Han, C.Q. Han, J. Li, Z.W. Wu , andY.M. Liu. Determination of thiol compounds by solid-phaseextraction using multi-walled carbon nanotubes as adsorbentcoupled with high-performance liquidchromatography-�uorescence detection. Microchim. Acta, 174(3–4), 421–427, 2011.

21. K. Beiner, P. Popp, and R. Wennrich. Selectiveenrichment of sul�des, thiols and methylthiophosphatesfrom water on metal-loaded cation-exchange materials forgas chromatographic analysis. J. Chromatogr. A, 968,171–176, 2002.

22. G. Socher, R. Nussbaum, K. Rissler, and E. Lankmayr.Analysis of sulfonated compounds by ion-exchangehigh-performance liquid chromatography–mass spectrometry.J. Chromatogr. A, 912, 53–60, 2001.

23. E. Caro, R.M. Marcé, P.A.G. Cormack, D.C. Sherrington,and F. Borrull. A new molecularly imprinted solid-phaseextraction of naphthalene sulfonates from water. J.Chromatogr. A, 1047, 175–180, 2004.

24. M. Holcapek, P. Jandera, and P. Zderadicka. Highperformance liquid chromatography–mass spectometricanalysis of sulphonated dyes and intermediates. J.Chromatogr. A, 926, 175–186, 2001.

25. M. Stüber and T. Reemstma. Evaluation of threecalibration methods to compensate matriz effects inenvironmental analysis with LC-ESI-MS. Anal. Bioanal.Chem., 378, 910–916, 2004.

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27. M.C. Alonso, M. Castillo, and D. Barceló. Solid-phaseextraction procedure of polar benzene- andnaphthalenesulfonates in industrial ef�uents followed byunequivocal determination with ion-pairchromatography/electrospray–mass spectrometry. Anal. Chem.,71, 2586–2593, 1999.

28. T. Storm, T. Reemtsma, and M. Jekel. Use of volatileamines as ion-pairing agents for the high-performanceliquid chromatographic–tandem mass spectrometricdetermination of aromatic sulfonates in industrial

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30. I. Lavilla, F. Pena-Pereira, S. Gil, M. Costas, and C.Bendicho. Microvolume turbidimetry for rapid and sensitivedetermination of the acid labile sul�de fraction in watersafter headspace single-drop microextraction with in situgeneration of volatile hydrogen sul�de. Anal. Chim. Acta,647(1), 112–116, 2009.

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32. M. Colon, J.L. Todolí, M. Hidalgo, and M. Iglesias.Development of novel and sensitive methods for thedetermination of sul�de in aqueous samples by hydrogensul�de generation-inductively coupled plasmaatomic emissionspectroscopy. Anal. Chim. Acta, 609, 160–180, 2008.

33. D.-M. Tsai, A.S. Kumar, and J.-M. Zen. A highly stableand sensitive chemically modi�ed screen-printed electrodefor sul�de analysis. Anal. Chim. Acta, 556(1), 145–150,2006.

34. I. Kristiana, A. Heitz, C. Joll, and A. Satahasivan.Analysis of polysul�des in drinking water distributionsystems using headspace solid-phase microextraction and gaschromatography-mass spectrometry. J. Chromatogr. A, 1217,5995–6001, 2010.

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10 Chapter 10 - Determination of Ammoniain Water Samples

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13 Chapter 13 - Cyanides

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16 Chapter 16 - Determination of Siliconand Silicates

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3. ASTM Standard C33, Specification for ConcreteAggregates, ASTM International, West Conshohocken, PA,2003, DOI: 10.1520/C0033-03E01.

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28. Silica in waters, EPA Standard Method No.10-114-27-1-A; Reference No. 370.1.

29. Silicate in waters, EPA Standard Method No.10-114-27-1-B; Reference No. 370.1.

30. Silicate in brackish or seawater, EPA Standard MethodNo. 30-114-27-1-A; Reference No. 370.1.

31. Silicate in brackish or seawater, EPA Standard MethodNo. 31-114-27-1-A; Reference No. 370.1.

32. Silica (SiO 2 ) in brackish waters, EPA Standard MethodNo. 31-114-27-1-B; Reference No. 370.1.

33. Silicate in brackish water, EPA Standard Method No.31-114-27-1-D; Reference No. 370.1.

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20 Chapter 20 - Organic Acids

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21 Chapter 21 - Determination of VolatileOrganic Compounds in Water

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85. 2005. Standard Method 6200. Volatile organic compounds.21st.

86. 2005. Standard Method 6040-D Solid-phasemicroextraction. 21st.

87. 2005. Standard Method 6232. Trihalomethanes andchlorinated organic solvents. 21st.

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291. Zhao, R. s., Lao, W. j., Xu, X. b. 2004. Headspaceliquid-phase microextraction of trihalomethanes indrinking water and their gas chromatographic determination.Talanta 62(4): 751–756.

292. Bagheri, H., Salemi, A. 2006. Headspace solventmicroextraction as a simple and highly sensitive samplepretreatment technique for ultra trace determination ofgeosmin in aquatic media. J. Sep. Sci. 29(1): 57–65.

293. Ghasemi, E., Sillanpää, M., Naja�, N. M. 2011.Headspace hollow �ber protected liquid-phasemicroextraction combined with gas chromatography-massspectroscopy for speciation and determination of volatileorganic compounds of selenium in environmental andbiological samples. J. Chromatogr. A 1218(3): 380–386.

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298. Aguilera-Herrador, E., Lucena, R., Cárdenas, S.,Valcárcel, M. 2008. Ionic liquid-based single-dropmicroextraction/gas chromatographic/mass spectrometricdetermination of benzene, toluene, ethylbenzene and xyleneisomers in waters. J. Chromatogr. A 1201(1): 106–111.

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300. Hao-Yu, Shen, Ping, Lu, Ming-Min, Huai, Sheng-Dong,Pan, Yun, Zhang. 2011. Determination of trichlorobenzenesand 2,4,6-trichlorophenol in wastewater of machining bydispersive liquid-liquid microextraction—gaschromatography/mass spectrometry. Bioinformatics andBiomedical Engineering, (ICBBE) 2011 5th InternationalConference on, 1–4.

301. Ye, Q., Zheng, D., Liu, L., Hong, L. 2011. Rapidanalysis of aldehydes by simultaneous microextraction andderivatization followed by GC-MS. J. Sep. Sci. 34(13):

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302. Karimi, M., Sereshti, H., Samadi, S., Parastar, H.2010. Optimization of dispersive liquid-liquidmicroextraction and improvement of detection limit ofmethyl tert-butyl ether in water with the aid ofchemometrics. J. Chromatogr. A 1217(45): 7017–7023.

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304. Kozani, R. R., Assadi, Y., Shemirani, F., Hosseini, M.R. M., Jamali, M. R. 2007. Part-per-trillion determinationof chlorobenzenes in water using dispersive liquid-liquidmicroextraction combined gas chromatographyGÇôelectroncapture detection. Talanta 72(2): 387–393.

305. Rahnama Kozani, R., Assadi, Y., Shemirani, F., MilaniHosseini, M., Jamali, M. 2007. Determination oftrihalomethanes in drinking water by dispersiveliquid-liquid microextraction then gas chromatography withelectron-capture detection. Chromatographia 66(1): 81–86.Section VIII Phenolic and Humic Compounds

22 Chapter 22 - Determination of PhenolicCompounds in Water

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48. E.R. Brouwer and U.A.Th. Brinkman. Determination ofphenolic compounds in surface water using on-line liquidchromatographic precolumn-based column-switchingtechniques. J. Chromatogr. A 678:223–231, 1994.

49. A.C. Hogenboom, I. Jagt, J.J. Vreuls, and U.A.Th.Brinkman. On-line trace level determination of polarorganic microcontaminants in water using variouspre-column–analytical column liquid chromatographictechniques with ultraviolet absorbance and massspectrometric detection. Analyst 122:1371–1378, 1997.

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27 Chapter 27 - PCDDs and PCDFs

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28 Chapter 28 - Polynuclear AromaticHydrocarbons

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2. Anyakora, C.A. et al., Determination of polynucleararomatic hydrocarbons in marine samples of Siokolo FishingSettlement. J. Chromatogr. A, 1073, 323, 2005.

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6. Nieva-Cano, M.J., Rubio-Barroso, S. Santos-Delgado,M.J., Determination of PAH in food samples by HPLC withuorimetric detection following sonication extractionwithout clean-up. Analyst, 126, 1326, 2001.

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29. Nieva-Cano, M.J., Rubio-Barroso, S., Santos-Delgado,M.J., Determination of PAHs in food samples by HPLC withuorimetric detection following sonication extractionwithout clean-up. Analyst, 126, 1326, 2001.

30. Pensado, L. et al., Strategic sample composition in thescreening of polycyclic aromatic hydrocarbons in drinkingwater samples using liquid chromatography with �uorimetricdetection. J. Chromatogr. A, 1056, 121, 2004.

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34. Dalluge, J., Roose, P., Brinkman, U.A.Th., Evaluationof a high-resolution time-of-�ight mass spectrometer forthe gas chromatographic determination of selectedenvironmental contaminants. J. Chromatogr. A, 970, 213,2002.

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41. Miege, C., Bouzige, M., Nicol, S., Dugay, J., Pichon,V., Hennion, M.C., Selective immunoclean-up followed byliquid or gas chromatography for the monitoring of

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42. Bouzige, M., Pichon, V., Hennion, M.C., Class selectiveimmunosorbent for the trace level determination ofpolycyclic aromatic hydrocarbons in complex sample matricesused in off-line procedure or online coupled with liquidchromatography/�uorescence and diode array detections inseries. Environ. Sci. Technol. 33, 1916, 1999.

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57. Letzel, T., Pöschl, U., Wissiack, R., Rosenberg, E.,Grasserbauer, M., Niessner, R., Phenyl-modi�edreversed-phase liquid chromatography coupled to atmosphericpressure chemical ionization mass spectrometry: A universalmethod for the analysis of partially oxidized aromatichydrocarbons. Anal. Chem., 73(7), 1634, 2001.

58. Chen, S., Meyerhoff, M., Shape-selective retention ofpolycyclic aromatic hydrocarbons onmetalloprotoporphyrin–silica phases: Effect of metal ioncenter and porphyrin coverage. Anal. Chem., 70(13), 2523,1998.

59. Saito, Y., Nojiri, M., Shimizu, Y., Jinno, K., Liquidchromatographic retention behavior of polycyclic aromatichydrocarbons on newly-synthesized chitosan stationaryphases cross-linked with long aliphatic chains. J. Liq.Chromatogr. Relat. Technol., 25, 2767, 2002.

60. Li, J., Hu, Y., Carr, P.W., Fast separations atelevated temperatures on polybutadiene-coated zirconiareversed-phase material. Anal. Chem., 69(19), 3884, 1997.

61. Braun, J.M., Ines, W.L., Characterization of insitu-generated ionene micellar mimetic stationary phasefor liquid chromatography. Anal. Lett., 33, 2983, 2000.

62. Brown, J.N., Peake, B.M., Determination ofcolloidally-associated polycyclic aromatic hydrocarbons(PAHs) in fresh water using C18 solid phase extractiondisks. Anal. Chim. Acta, 486, 159, 2003.

63. Telli-Karakoc, F., Tolun, L., Henkelmann, B., Klimm,C., Okay, O., Schramm, K.W., Polycyclic aromatichydrocarbons (PAHs) and polychlorinatedbiphenyls (PCBs)distributions in the Bay of Marmara Sea: Izmit Bay.Environ. Pollut., 119, 383, 2002.

64. Kondo, T., Yang, Y., Lamm, L., Separation of polar andnon-polar analytes using dimethyl sulfoxidemodi�edsubcritical water. Anal. Chim. Acta, 460(2), 185, 2000.

65. Kuusimäki, L., Peltonen, Y., Kyyro, E., Mutanen, P.,Peltonen, K., Savela, K., Exposure of garbage truckdrivers and maintenance personnel at a waste handlingcentre to polycyclic aromatic hydrocarbons derived fromdiesel exhaust. J. Environ. Monit., 4, 722, 2002.

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67. Jones, A. Yang, Y., Separation of nonpolar analytesusing methanol-water mixtures at elevated temperatures.Anal. Chim. Acta, 485, 51, 2003.

68. Chen, B.H., Wang, C.Y., Chiu, C.P. Evaluation ofanalysis of polycyclic aromatic hydrocarbons in meatproducts by liquid chromatography. J. Agric. Food Chem.,44(8), 2244, 1996.

69. Chen, Y. et al., Emission factors for carbonaceousparticles and polycyclic aromatic hydrocarbons fromresidential coal combustion in China. Environ. Sci.Technol., 39(6), 1861, 2005.

70. Fernández-Pérez, V., Luque de Castro, M.D., Micelleformation for improvement of continuous subcritical waterextraction of polycyclic aromatic hydrocarbons in soilprior to high-performance liquid chromatography–�uorescencedetection. J. Chromatogr. A, 902(2), 357, 2000.

71. McGowin, A.E., Adom, K.K., Obubuafo, A.K., Screening ofcompost for PAHs and pesticides using static subcriticalwater extraction. Chemosphere, 45, 857, 2000.

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29 Chapter 29 - Surfactants

Abrar S. and Trathnigg B. 2010. Separation of nonionicsurfactants according to functionality by hydrophilicinteraction chromatography and comprehensivetwo-dimensional liquid chromatography. J. Chromatogr. A1217: 8222–8229.

Barco M., Planas C., Palacios O., Ventura F., River J., andCaixach J. 2003. Simultaneous quantitative analysis ofanionic, cationic, and nonionic surfactants in water byelectrospray ionization mass spectrometry with �owinjection analysis. Anal. Chem. 75: 5129–5136.

Bernabé-Zafón V., Torres-Lapasió J.R., Ortega-Gadea S.,Simó-Alfonso E.F., and Ramis-Ramos G. 2005. Capillaryelectrophoresis enhanced by automatic two-way backgroundcorrection using cubic smoothing splines and multivariatedata analysis applied to the characterisation of mixturesof surfactants. J. Chromatogr. A 1065: 301–313.

Cantero M., Rubio, S., and Pérez-Bendito D. 2005.Determination of nonionic polyethoxylated surfactants inwastewater and river water by mixed hemimicelle extractionand liquid chromatography–ion trap mass spectrometry. J.Chromatogr. A 1067: 161–170.

Céspedes R., Lacorte S., Ginebreda A., and Barceló D. 2008.Occurrence and fate of alkylphenols and alkylphenolethoxylates in sewage treatment plants and impact onreceiving waters along the Ter river. Environ. Pollut.153: 384–392.

Clara M., Scharf S., Scheffknecht C., and Gans O. 2007.Occurrence of selected surfactants in untreated andtreated water. Water Res. 41: 4339–4348.

Eganhouse R.P., Pontolillo J., Gaines R.B. et al. 2009.Isomer-speci�c determination of 4-nonylphenols usingcomprehensive two-dimensional gaschromatography/time-of-�ight mass spectrometry. Environ.Sci. Technol. 43: 9306–9313.

Frömel T. and Knepper T.P. 2008. Mass spectrometry as anindispensable tool for studies of biodegradation ofsurfactants. Trends Anal. Chem. 27: 1091–1106.

Gómez V., Ferreres L., Pocurull E., and Borrull F. 2011.Determination of nonionic and anionic surfactants inenvironmental water matrices. Talanta 84: 859–866.

González S., Petrovic M., and Barceló D. 2007a. Advancedliquid chromatography–mass spectrometry (LC– MS) methodsapplied to wastewater removal and the fate of surfactantsin the environment. Trends Anal. Chem. 26: 116–124.

González S., Petrovic M., and Barceló D. 2007b. Removal ofa broad range of surfactants from municipal wastewater.Comparison between membrane bioreactor and conventionalactivated sludge treatment. Chemosphere 67: 335–343.

Guan Z., Huang Y., and Wang W. 2008. Carboxyl modi�edmultiwalled carbon nanotubes as solid-phase extractionadsorbents combined with high-performance liquidchromatography for analysis of linear alkylbenzenesulfonates. Anal. Chim. Acta 627: 225–231.

Hu Y.-Y., He Y.-Z., Qian L.-L., and Wang L. 2005. Onlineion pair solid-phase extraction of electrokineticmulticommutation for determination of trace anionsurfactants in pond water. Anal. Chim. Acta 536: 251–257.

Hu J. and Yu J. 2010. An LC–MS–MS method for thedetermination of per�uorinated surfactants in environmentalmatrices. Chromatographia 72: 411–416.

Khaled E., Mohamed G.G., and Awad T. 2008. Disposalscreen-printed carbon paste electrodes for thepotentiometric titration of surfactants. Sens. Actuator135: 74–80.

Lara-Martín P.A., Gómez-Parra A., and González-Mazo E.2006. Development of a method for the simultaneous analysisof anionic and nonionic surfactants and their carboxylatedmetabolites in environmental samples by mixed-mode liquidchromatography–mass spectrometry. J. Chromatogr. A 1137:188–197.

Lara-Martín P.A., Gómez-Parra A., and González-Mazo E.2008. Reactivity and fate of synthetic surfactants inaquatic environments. Trends Anal. Chem. 27: 684–695.

Lara-Martín P.A., González-Mazo E., and Brownawell B.J.2011. Multiresidue method for the analysis of syntheticsurfactants and their degradation metabolites in aquaticsystems by liquid chromatography–timeof-�ight–massspectrometry. J. Chromatog. A 1218: 4799–4807.

Lavorante A.F., Morales-Rubio A., de la Guardia M., andReis B.F. 2007. A multicommmuted stop-�ow system employing

LEDs-based photometer for the sequential determination ofanionic and cationic surfactants in water. Anal. Chim.Acta 600: 58–65.

Levine L.H., Garland J.L., and Johnson J.V. 2005.Simultaneous quanti�cation of polydispersed anionic,amphoteric and nonionic surfactants in simulated wastewatersamples using C 18 high-performance liquidchromatography–quadrupole ion-trap mass spectrometry. J.Chromatogr. A 1062: 217–225.

Lian J., Liu J.X., and Wei Y.S. 2009. Fate of nonylphenolpolyethoxylates and their metabolites in four Beijingwastewater treatment plants. Sci. Total Environ. 407:4261–4268.

Lizondo-Sabater J., Martínez-Máñez R., Sancenón F., SeguíM.J., and Soto J. 2008. Ion-selective electrodes foranionic surfactants using a cyclam derivative as ionophore.Talanta 75: 317–325.

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Luque N., Rubio S., and Pérez-Bendito D. 2007. Use ofcoacervates for the on-site extraction/preservation ofpolycyclic aromatic hydrocarbons and benzalkoniumsurfactants. Anal. Chim. Acta 584: 181–188.

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30 Chapter 30 - Petroleum HydrocarbonAnalysis

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2. Bernabeu, A. M., Rey, D., Rubio, B., Vilas, F.,Domínguez, C., Bayona, J. M., and Albaigés, J. 2009.Assessment of cleanup needs of oiled sandy beaches: Lessonsfrom the Prestige oil spill. Environmental Science &Technology 43(7): 2470–2475.

3. Fernández-Varela, R., Andrade, J. M., Muniategui, S.,Prada, D., and Ramírez-Villalobos, F. 2009. The comparisonof two heavy fuel oils in composition and weatheringpattern, based on IR, GC-FID and GC-MS analyses:Application to the Prestige wreackage. Water Research43(4): 1015–1026.

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5. Wardlaw, G. D., Arey, J. S., Reddy, C. M., Nelson, R.K., Ventura, G. T., and Valentine, D. L. 2008.Disentangling oil weathering at a marine seep using GCxGC:Broad metabolic speci�city accompanies subsurfacepetroleum biodegradation. Environmental Science &Technology 42(19): 7166–7173.

6. Bauer, S. J., Ehgartner, B. L., and Neal, J. T. 1997.Geotechnical studies associated with decommisioning thestrategic petroleum reserve facility at Weeks Island,Louisiana: A case history. International Journal of RockMechanics and Mining Sciences 34(3–4): 25.

7. Autin, W. J. 2002. Landscape evolution of the FiveIslands of south Louisiana: Scienti�c policy and salt domeutilization and management. Geomorphology 47(2–4): 227–244.

8. Fredrich, J. T., Fossum, A. F., and Hickman, R. J. 2007.Mineralogy of deepwater Gulf of Mexico salt formations andimplications for constitutive behavior. Journal ofPetroleum Science and Engineering 57(3–4): 354–374.

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10. Todd, G. D., Chessin, R. L., and Colman, J. 1999.ATSDR: Toxicological pro�le for total petroleumhydrocarbons (TPH). Atlanta, U.S. Department of Health andHuman Services.

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12. Fingas, M. F. Ed. 2011. Introduction to oil chemicalanalysis. In Oil Spill Science and Technology: Prevention,Response, and Cleanup, Elsevier/Gulf Professional Pub.:Burlington, MA, pp. 87–109.

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15. AlSalka, Y., Karabet, F., and Hashem, S. 2011.Evaluation of electrochemical processes for the removal ofseveral target aromatic hydrocarbons from petroleumcontaminated water. Journal of Environmental Monitoring13(3): 605–613.

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22. Christensen, J. H., Tomasi, G., and Hansen, A. B. 2005.Chemical �ngerprinting of petroleum biomarkers using timewarping and PCA. Environmental Science & Technology 39(1):255–260.

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24. Dellavedove, P., Vitelli, M., Ferraro, V., Di Toro, M.,and Santoro, M. 2006. Application of enhanced large volumeinjection; an approach to the analysis of petroleumhydrocarbons in water. Chromatographia 63(1/2): 73–76.

25. Wang, Z. and Fingas, M. F. 2003. Development of oilhydrocarbon �ngerprinting and identi�cation techniques.Marine Pollution Bulletin 47: 423–452.

26. CEN/TR 15522-2. 2006. Oil spill identi�cation.Waterborne petroleum and petroleum products. Part 2:Analytical methodology and interpretation of results. CEN,Technical Report TC/BT TF 120 WI CSS27003.

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30. EPA Method 3510. C. Separatoty funnel liquid−liquidextraction. Revision 3.1996.

31. Massachusetts Department of Environmental ProtectionMethod for the determination of extractable petroleumhydrocarbons (EPH). 2004.

32. Saravanabhavan, G., Helferty, A., Hodson, P. V., andBrown, R. S. 2007. A multi-dimensional high performanceliquid chromatographic method for �ngerprinting polycyclicaromatic hydrocarbons and their alkyl-homologs in theheavy gas oil fraction of Alaskan North Slope crude.Journal of Chromatography A 1156(1–2): 124–133.

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