Handbook of Residue Analytical Methods for Agrochemicals

Handbook of Residue Analytical Methods for Agrochemicals VOLUME 1 and VOLUME 2 Editor-in-Chief Dr Philip W Lee DuPont Cr...

Author: Dr Philip W. Lee | Hiroyasu Aizawa | Aldos C. Barefoot | John J. Murphy

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Handbook of Residue Analytical Methods for Agrochemicals VOLUME 1 and VOLUME 2 Editor-in-Chief Dr Philip W Lee DuPont Crop Protection USA

C 2003 John Wiley & Sons Ltd, The Atrium, Copyright Southern Gate, Chichester, West Sussex PO19 8SQ, England

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(+44) 1243 779777

Email (for orders and customer service enquiries): [email protected] Visit our Home Page on www.wileyeurope.com or www.wiley.com All Rights Reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning or otherwise, except under the terms of the Copyright, Designs and Patents Act 1988 or under the terms of a licence issued by the Copyright Licensing Agency Ltd, 90 Tottenham Court Road, London W1T 4LP, UK, without the permission in writing of the Publisher. Requests to the Publisher should be addressed to the Permissions Department, John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ, England, or emailed to [email protected], or faxed to (+44) 1243 770620. This publication is designed to provide accurate and authoritative information in regard to the subject matter covered. It is sold on the understanding that the Publisher is not engaged in rendering professional services. If professional advice or other expert assistance is required, the services of a competent professional should be sought. Other Wiley Editorial Offices John Wiley & Sons Inc., 111 River Street, Hoboken, NJ 07030, USA Jossey-Bass, 989 Market Street, San Francisco, CA 94103-1741, USA Wiley-VCH Verlag GmbH, Boschstr. 12, D-69469 Weinheim, Germany John Wiley & Sons Australia Ltd, 33 Park Road, Milton, Queensland 4064, Australia John Wiley & Sons (Asia) Pte Ltd, 2 Clementi Loop #02-01, Jin Xing Distripark, Singapore 129809 John Wiley & Sons Canada Ltd, 22 Worcester Road, Etobicoke, Ontario, Canada M9W 1L1 Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic books. Where articles in the Handbook of Residue Analytical Methods for Agrochemicals have been written by government employees in the United States of America, please contact the publisher for information on the copyright status of such works, if required. Works written by US government employees and classified as US Government Works are in the public domain in the United States of America.

Preface The agrochemical industry is, globally, one of the most heavily regulated industries today. Extensive product chemistry, environmental fate, residue chemistry, ecotoxicology, and mammalian toxicology data are required to support the registration and reregistration of all crop protection products. This information is used not only to conduct human dietary and worker exposure risk assessments but also to determine the potential impact of the agrochemicals and their degradation products/metabolites on the environment and sensitive ecosystems. The quality of the residue data, including the reliability and sensitivities of the analytical methods and the validity of the collected biological/environmental samples, is critical to the acceptability and validity of the risk characterization/assessment. Differences in testing guidelines between the various regulatory authorities and the lack of standardization in test method specifications further complicate the interpretation and broad application of the exposure data. Significant progress has been achieved in residue analytical technology in the past 50 years. Today’s residue analytical methodology detects multiple analytes routinely at the nanogram per kilogram (ppt) level in a wide variety of sample matrices with a high level of selectively and accuracy. The role of the residue analytical chemist is no longer limited to the development and validation of analytical methods but also includes design and conduct of complex field crop residue and environmental monitoring studies. This is a real challenge, especially when studies are conducted under the strict Good Laboratory Practices guidelines. Recognizing the diverse and rapid growth of residue chemistry as an important scientific discipline, Dr Terry Roberts, Founding Editor of the Handbook of the Residue Analytical Methods of Agrochemicals, organized this publication effort in 1999. The editorial team includes Dr Hiro Aizawa (Hiro Research Consultancy), Dr Al Barefoot (DuPont Crop Protection) and Dr John Murphy (Bayer CropScience). The scope/objective of this handbook is to present to the reader a comprehensive overview of current global regulatory requirements and the application of various analytical technologies (chromatographic and non-chromatographic) to residue analysis. Best practices to conduct various crop residue and field monitoring studies and detailed method procedures for the determination of major classes of agrochemicals, as well as individual compounds, are key components of this handbook. This handbook consists of two volumes and approximately 80 individual chapters. The editorial team acknowledges the high quality of the contributions from the regulatory, academic, and industrial researchers around the world. It is their commitment in time and effort that make this a successful publication project. Each chapter was reviewed by at least one editor and often by other technical experts. The editorial team acknowledges the generous advice and reviews provided by our colleagues from DuPont Crop Protection (Dr Wynn John, Dr Chuck Powley) and Bayer CorpScience (Dr Lou Russo), the US EPA (Dr Alex Krynitsky) and the USDA ARS (Dr David Smith). We would also appreciate comments, feedback and upgrades from the readers, so that correction and improvement can be made for later editions or printings.

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Preface

The editorial team is also grateful for the valuable support from the Publisher (John Wiley & Sons Ltd.), in particular Ms Lynette James, and from the Project Manager (Gray Publishing), in particular Ms Lesley Gray, for their efficient coordination during the planning, review and production phase of this publication effort. Finally, this handbook is dedicated to all past and present residue analytical chemists. It is their vision and creativity that continues to push back the frontier of residue analytical technology. Philip W. Lee Newark, Delaware December, 2002

Editorial Board Editor-in-Chief Dr Philip W Lee DuPont Crop Protection Stine-Haskell Research Center Newark Delaware USA

Associate Editors Professor Hiroyasu Aizawa Hiro Research Consultancy Inc.(HRCI) Tokyo Japan

Dr Aldos C Barefoot DuPont Crop Protection Stine-Haskell Research Center Newark Delaware USA

Founding Editor Dr Terry Roberts Anglesey North Wales UK

Dr John J Murphy Dietary Exposure Bayer CropScience Stilwell Kansas USA

List of contributors Lutz Alder Federal Institute for Health Protection of Consumers and Veterinary Medicine (BgVV), Berlin, Germany Todd A. Anderson Texas Tech University, Lubbock, TX, USA Reiner Bacher

PTRL Europe GmbH, Ulm, Germany

Johannes Corley Rutgers, The State University of New Jersey, North Brunswick, NJ, USA Kay K. Curry Technology Sciences Group Inc., Washington, DC, USA William J. Englar Englar Food Laboratories, Inc., Moses Lake, WA, USA

Michael R. Barrett United States Environmental Protection Agency, Washington, DC, USA

Cheryl M. Englar-Coulter Englar Food Laboratories, Inc., Moses Lake, WA, USA

Elizabeth Behl United States Environmental Protection Agency, Washington, DC, USA

Neal Ewing CA, USA

Kimberly S. Billesbach Bayer CropScience, Stilwell, KS, USA

John Fuhrman

James F. Brady Syngenta Crop Protection, Inc., Greensboro, NC, USA David J. Brookman Technology Sciences Group Inc., Washington, DC, USA Thomas J. Burnett Eli Lilly and Company, Greenfield, IN, USA Maria Elena Y. Cabusas DuPont Crop Protection, Newark, DE, USA Leslie S. Carver Waterborne Environmental, Inc., Leesburg, VA, USA Andrey Chen

FMC, Princeton, NJ, USA

Joseph R. Chepega Waterborne Environmental, Inc., Leesburg, VA, USA Mihai Cicotti Switzerland

Battelle Memorial Institute, Geneva,

National Food Laboratory, Inc., Dublin,

Monsanto, St. Louis, MO, USA

Richard J. Fussell Central Science Laboratory, York, UK Willa Garner GARNDAL Associates, Inc., Mount Airy, MD, USA Shirley J. Gee USA

University of California, Davis, CA,

Thomas J. Gould Bayer CropScience, Stilwell, KS, USA Timothy J. Grace USA

Bayer CropScience, Stilwell, KS,

Charles A. Green Valent USA Corporation, Dublin, CA, USA Amy Hackett

Monsanto, St. Louis, MO, USA

Bruce D. Hammock CA, USA

University of California, Davis,

Thomas J. Class PTRL Europe GmbH, Ulm, Germany

Ralf Hänel Federal Biological Research Centre for Agriculture and Forestry (BBA), Braunschweig, Germany

George P. Cobb USA

Vincent Hebert WA, USA

Texas Tech University, Lubbock, TX,

Washington State University, Richland,

xliv

List of contributors

Andrew J. Hewitt Stewart Agricultural Research Services, Macon, MO, USA

James S. LeNoir DuPont Crop Protection, Newark, DE, USA

Richard Honeycutt H.E.R.A.C., Inc., Greensboro, NC, USA

Yi Lin USA

Mitsumasa Ikeda Kumiai Chemical Industry Co., Ltd, Shizuoka, Japan

Cynthia Lipton

Yuji Ikemoto

Nihon Nohyaku Co. Ltd, Osaka, Japan

Syngenta Crop Protection, Inc., Greensboro, NC,

Byotix, Inc., Richmond, CA, USA

Joseph H. Massey Mississippi State University, Starkville, MS, USA

Fujio Ishijima Hokko Chemical Industry Co. Ltd, Kanagawa, Japan

Greg C. Mattern USA

Scott H. Jackson BASF Corporation, Research Triangle Park, NC, USA

Joseph P. McClory DE, USA

Kathryn M. Jernberg DuPont Crop Protection, Newark, DE, USA

Carolyn Mentzer MD, USA

William W. John DuPont Crop Protection, Stine Haskell Research Center, Newark, DE, USA

D. Larry Merricks MD, USA

Setsuko Katsurada Sankyo Co. Ltd, Shiga, Japan

Sean M. Moore

Guenther Kempe Landesuntersuchungsanstalt, Chemnitz, Germany

Kouji Nakamura Saitama Prefecture Agriculture and Forestry Research Center, Kuki, Japan

Douglas E. Kiehl Eli Lilly and Company, Greenfield, IN, USA

Kazuo Ogura Agricultural Chemicals Inspection Station, Tokyo, Japan

Philip James Kijak US Food and Drug Administration, Laurel, MD, USA

Jeff Old

Alexander J. Krynitsky US Environmental Protection Agency, EPA Environmental Science Center, Fort Meade, MD, USA Chung K. Lam Bayer CropScience, Stilwell, KS, USA

DuPont Crop Protection, Newark,

Agrisearch Incorporated, Thurmont,

Agrisearch Incorporated, Frederick,

Bayer CropScience, Stilwell, KS, USA

Inveresk Research, Tranent, UK

Takeo Otsuka Hiroko Kobayashi Research Institute of Japan Plant Protection Association, Ibaraki, Japan

Bayer CropScience, Stilwell, KS,

Sankyo Co. Ltd, Shiga, Japan

John C. Peterson Englar Food Laboratories, Inc., Moses Lake, WA, USA Beth M. Polakoff USA

Exponent, Inc., Washington, DC,

Charles R. Powley DuPont Crop Protection, Newark, DE, USA

Steven J. Lehotay USDA Agricultural Research Service, Eastern Regional Research Center, Wyndmoor, PA, USA

Robin S. Readnour IN, USA

William M. Leimkuehler Bayer CropScience, Stilwell, KS, USA

Valerie B. Reeves US Food and Drug Administration, Rockville, MD, USA

Eli Lilly and Company, Greenfield,

List of contributors

xlv

Stewart L. Reynolds Central Science Laboratory, York, UK

Guy R. Stehly USGS, Biological Resources Division, La Crosse, WI, USA

Neil J. Robinson Syngenta, Bracknell, UK

Shigeji Sugimoto

Janine E. Rose

Manabu Toujigamori

PTRL West, Inc., Hercules, CA, USA

Nippon Soda Co. Ltd, Tokyo, Japan Sankyo Co. Ltd, Shiga, Japan

Louis Russo USA

Bayer CropScience, Kansas City, MO,

Yasuhiro Tsujino

Mariko Sabi


Michael P. Turberg Eli Lilly and Company, Greenfield, IN, USA

Shingo Sadakane


Manasi Saha BASF Corporation, Research Triangle Park, NC, USA Takashi Saito


Yoshihiro Saito Shizuoka, Japan

Kumiai Chemical Industry Co., Ltd,

Thomas Schreier Valent USA Corporation, Dublin, CA, USA James N. Seiber Western Regional Research Center, USDA Agricultural Research Service, Albany, CA, USA Robert J. Seymour Bayer CropScience, Research Triangle Park, NC, USA Guomin Shan Dow AgroSciences LLC, Indianapolis, IN, USA Weilin L. Shelver US Department of Agriculture, Agricultural Research Service, Fargo, ND, USA Johannes Siebers Federal Biological Research Centre for Agriculture and Forestry (BBA), Braunschweig, Germany David J. Smith US Department of Agriculture, Agricultural Research Service, Fargo, ND, USA Craig A. Smitley NC, USA

Takashi Ueda



Masako Ueji National Institute for Agro-Environmental Sciences, Tsukuba, Japan Noriharu Umetsu Otsuka Chemical Co. Ltd, Naruto, Japan David L. Valcore USA

Dow AgroSciences, Indianapolis, IN,

Chantel Van Bellinghan Monsanto, Brussels, Belgium Michael F. Wilson Central Science Laboratory, York, UK James E. Woodrow University of Nevada, Reno, NV, USA Akira Yagi Kumiai Chemical Industry Co., Ltd, Shizuoka, Japan Katsura Yagi Otsuka Chemical Co. Ltd, Naruto, Japan Hisayoshi Yamagishi Research Institute of Japan Plant Protection Association, Ibaraki, Japan Hiroki Yamamoto Japan

Shimane University, Matsue,

Robert A. Yokley Syngenta Crop Protection, Inc., Greensboro, NC, USA

Scynexis, Research Triangle Park,

Lisa D. Spurlock-Brouwer Eli Lilly and Company, Greenfield, IN, USA

Sabrina X. Zhao

Pfizer Inc., Groton, CT, USA

Eberhard Zietz Institut Fresenius, Taunusstein, Germany

Contents of Volume 1 Preface List of contributors Introduction James N. Seiber Introduction Relationship of pesticide residue analysis, regulation, and risk assessment Who does residue analysis and why Challenges References

xli xliii

1 1 4 5 7 8

Regulatory guidance and scientific consideration for residue analytical method development and validation Assessment of residue analytical methods for crops, food, feed, and environmental samples: the approach of the European Union Johannes Siebers and Ralf Hänel Introduction Legal background General Council Directive 91/414/EEC Legislation related to MRLs Legislation related to residues limits for soil, water, and air Provisions for residue analytical methods Evaluation of the submitted methods Institutional background Validation parameters Requirements for post-registration and monitoring (enforcement) methods General requirements Specific requirements Requirements for data generation methods General requirements Specific requirements Availability of analytical methods Perspectives Acknowledgement References

13 13 14 14 14 15 18 18 20 20 21 23 23 27 31 32 33 34 35 36 36

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Contents of Volume 1

Regulatory considerations for residue analysis and methods on crops and food: the approach of Japan Kazuo Ogura, Hisayoshi Yamagishi and Shigeji Sugimoto Background Plant metabolism studies Residue studies on crops Residue analytical method Preferred methodology for conducting supervised field trials Field data (field report) presentation Extrapolation among the formulation types Residue definition Market basket survey in Japan Conclusion Further reading

General approaches for residue analytical method development and validation Thomas J. Class and Reiner Bacher Introduction Approaches to analytical method development Properties of the analyte(s) Functional groups of the analyte(s) Properties of the sample material Availability and practicality of analytical instrumentation Consideration of time, throughput, ruggedness and quality Practical examples Extending the scope of the multi-residue method DFG S19 What can go wrong? Beyond the limits References

Best practices in establishing detection and quantification limits for pesticide residues in foods Johannes Corley Introduction Definitions Methods for defining LOD and LOQ IUPAC method Propagation of errors method Hubaux–Vos approach Two-step approach (proposed by the US EPA) RMSE method The t99 sLLMV method Confirmation Representative data Conclusions Acknowledgements References

38 38 40 41 41 41 46 47 47 48 49 49

50 50 51 51 52 53 54 54 55 55 57 58 58

59 59 61 63 63 66 67 67 68 70 71 72 73 74 74


The process of development and validation of animal drug residue methods for US Food and Drug Administration regulatory use Philip James Kijak and Valerie B. Reeves Introduction The method Determinative procedures Confirmatory procedures Development of methods for regulatory use Practicability of methods Analyte selection Specificity Ruggedness Stability System suitability Method criteria Standards Precision Accuracy Other considerations Confirmatory procedure criteria Standard operating procedures (SOPs) Determinative procedure Confirmatory procedure Other considerations The method trial Second analyst/laboratory check FDA review Inter-laboratory method trial Confirmatory procedure method trial Non-NADA method trial Evaluation of data and recommendation for use Conclusion References

Validation of analytical methods for post-registration control and monitoring purposes in the European Union Lutz Alder Introduction Evaluation of enforcement methods for food provided by manufacturers The need for enforcement methods from the applicant The problem with residue definition Elements and format of method description Assessment of validation results Matrices in validation experiments Test of multi-residue methods Independent laboratory validation Statement on extraction efficiency Perspectives

76 76 78 79 79 80 80 80 81 81 82 82 83 83 83 84 84 85 85 85 87 87 88 88 88 89 91 91 92 92 93

94 94 95 95 96 98 101 105 107 108 108 109

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Validation of European standard (CEN) methods Scope and format of CEN methods CEN requirements for widely accepted multi-matrix/multi-residue methods Requirements for (newer) methods with limited scope Assessment and documentation of validation results Validation of official methods of EU member states Overview of existing method collections and validation requirements Single-laboratory validation in the UK Validation procedures of the Nordic countries Validation of official methods in Germany The problem of appropriate documentation of validation data of multi-matrix/multi-residue methods Summary and conclusion References

110 110 112 112 113 115 115 115 119 124 127 128 130

Best practices in the generation and analysis of residues in crop, food and feed Conducting crop residue field trials in the USA William W. John Introduction Description of the different types of field crop residue studies EPA guidelines and requirements Planning phase Testing strategy Crop and crop grouping Site/location selection Good Agricultural Practice (GAP) and use patterns Test substance Residue decline trials Processing study requirement Contract research organizations Best practices in conducting field study Protocol development The test site Test material Application phase Sampling phase Sample storage and shipping Sample preparation Field QA components Data presentation and communication Summary References

135 135 137 137 140 140 141 143 144 145 145 146 147 148 148 149 153 155 157 159 162 163 165 167 167


Conducting crop residue field trials in Europe Jeff Old Introduction General issues and considerations in conducting residue studies in Europe Regulation guidelines European comparable climatic zones/weather influences Crop and grouping Study planning phase Study objectives Role and responsibility of study personnel Preparing the study plan Product use pattern Test site requirements, evaluation and selection Best practices to conduct field studies Evaluation and selection of field investigators and testing personnel Preparation of field testing study plan Test item (previously termed test substance) Trial layout Growing and maintenance of trial site crops Calibration/servicing of application equipment Test item application Sampling of crops Sample shipping and transportation Sample storage Record keeping Good Laboratory Practice Field QA audits and study involvement Archiving Conclusion Further reading

Conducting crop residue field trials in Mexico and Latin America Louis Russo Introduction Regulatory requirements Planning a field residue trial in Latin America Number and locations of trials Personnel requirements Protocol preparation Test materials Quality assurance Budget considerations Communications Pre-implementation activities Translation of critical documents Preparation of the field notebook formats Pre-meetings in testing regions Implementation of testing procedures GLP training and protocol discussion Safety training

169 169 169 169 170 170 173 173 173 176 177 177 178 178 179 179 180 181 181 182 184 188 189 191 193 194 195 196 197

198 198 199 201 201 202 203 203 204 204 206 206 206 207 207 210 210 211

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x


First application Sampling and shipping Food Quality Protection Act (FQPA) considerations Reporting and closure Abbreviations

Food processing of raw agricultural commodities for residue analysis William J. Englar, Neal Ewing, John C. Peterson and Cheryl M. Englar-Coulter Overview of processing of agricultural commodities Historical background Basis for selecting a process method Laboratory/pilot processing of agricultural commodities Processing requirements of individual agricultural commodities Pilot laboratory processing versus commercial processing Effect of processing on pesticide residues Good Laboratory Practice (GLP) regulations and their impact on the small-scale processing procedures Development and validation of SOPs Development of processing protocol Role of study personnel Protocol deviations Organization of a processing report Raw data notebook Summary report of processing procedures Summary References

Best practices in the implementation of a large-scale market basket residue survey study David J. Brookman, Kay K. Curry and Beth M. Polakoff Introduction General considerations Case study (Organophosphates Market Basket Survey) Development of study protocol Definition of study objectives Role and responsibilities of study personnel Selection of products and of properties to be evaluated Sample collection strategy Analyses and data reporting Implementation of sampling plan Shopper selection and training Sample collection, storage, shipment, receipt, and documentation Analytical phase Analytical method Obtaining control commodities Assignment of products to laboratories Standardization of results reporting Presentation and review of study findings

211 212 213 213 213

215 215 215 216 218 218 219 223 224 224 224 226 227 227 227 228 230 230

231 231 231 232 233 234 235 236 237 238 239 239 240 241 241 242 242 243 245


Quality assurance functions Interpretation of study findings

Procedures and best practices for conducting residue studies of animal health drugs in food animals David J. Smith, Guy R. Stehly and Michael P. Turberg Introduction Purpose of residue studies Studies sponsored by the animal health industry Other studies Protocol development Animal selection and animal receipt Animal considerations for GLP studies Other considerations in animal selection Preparation of test article Animal dosing Oral administration Parenteral administration Other methods of drug administration In-life sample collection Facility considerations Animal weights, feed and water intakes, and dose Nutritional and environmental considerations Sample collection Residue analysis Radiochemical analysis Analysis of the marker residue Quality control Report Conclusions References

Sampling and analyses of foodstuffs from animal origin Robin S. Readnour, Thomas J. Burnett, Douglas E. Kiehl and Lisa D. Spurlock-Brouwer Introduction Sample collection and storage Sampling and homogenization Stability Extraction and sample preparation Extraction Sample preparation Separation and detection Liquid chromatography Liquid chromatography/mass spectrometry Gas chromatography Immunoassay Data handling and presentation Method validation

246 247

248 248 249 249 257 259 261 262 264 265 267 268 271 272 274 274 275 276 276 281 281 283 291 292 292 293

300 300 302 302 303 304 304 307 310 311 314 315 317 318 319

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Regulatory guidelines Inter-laboratory/collaborative studies Conclusion References

319 321 321 321

Compound class Anilides Hiroko Kobayashi Introduction Residue analytical methods for plant materials Nature of the residue Analytical method Residue analytical methods for soil Nature of the residues Analytical method Analytical methodology for water Nature of the residues Analytical method References

Chloroacetanilide herbicides Amy Hackett, John Fuhrman and Chantel Van Bellinghan Introduction Analytical methodology for plant and animal products Nature of the residue Rationale for the presented methods Description of methodology Analytical methodology for water and soil Nature of the residue Rationale for the methods presented Description of methodology Analytical method for the determination of acetochlor and its metabolites in plants and animals Outline of method Apparatus Reagents Analytical standards Analytical procedure Instrumentation Calculation of residues Evaluation Analytical method for the determination of propachlor and its metabolites in plants and animals Outline of method Apparatus Reagents Analytical standards Analytical procedure Instrumentation

327 327 327 327 329 336 336 336 339 339 339 342

344 344 347 347 347 347 348 348 349 350 350 351 351 352 354 355 359 359 360 361 361 361 362 363 363 366


Calculation of residues Evaluation Multi-residue analytical method for the determination of acetochlor, alachlor, and metolachlor in aqueous samples Outline of method Apparatus Reagents Analytical standards Analytical procedure Calculation of residues Evaluation Multi-residue analytical method for the determination of acetochlor, alachlor, and metolachlor soil metabolites in aqueous samples Outline of method Apparatus Reagents Analytical standards Analytical procedures Calculation of residues Evaluation Future directions for environmental monitoring Acknowledgements References

Dinitroaniline herbicides Masako Ueji Introduction Analytical methodology for plant materials Nature of the residues Method principle Analytical methodology for soil Nature of the residues Method principle Analytical method for soil metabolites Analytical methodology for water Nature of the residues Analytical method References

Sulfonylurea herbicides Charles R. Powley Introduction Analytical methodology LC/MS/MS analysis Crops, food and feed Soil Water Conclusions and future directions Acknowledgements References

367 367 368 369 369 370 371 373 376 377 378 380 380 381 381 382 385 385 387 387 387

389 389 390 390 391 395 395 395 397 398 398 398 399

400 400 402 402 405 407 408 409 410 410

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Triazine herbicide methodology Robert A. Yokley Introduction/general description Analytical methodology for water samples Water sample preparation Analytical methodology for soil samples Liquid–solid extraction Sonication Microwave extraction Supercritical fluid extraction Subcritical fluid extraction On-line SFE Analytical methodology for crops, food, feed, and animal tissues Analytical methodology for biological fluids Analytical methodology for air samples Instrumentation Gas chromatography Liquid chromatography Supercritical fluid chromatography Electrochemical analysis Other techniques Future directions References

Diphenyl ethers Masako Ueji Introduction Analytical methodology for plant materials Nature of the residues Analytical method Analytical methodology for soil Nature of the residues Analytical method Analytical method for the metabolites of diphenyl ether herbicides in soil Analytical methodology for water Nature of the residues Analytical method References

412 412 416 416 429 430 431 432 432 434 435 435 437 438 439 439 441 442 443 443 443 445

451 451 453 453 453 458 458 459 460 461 461 462 464

Individual compounds Bispyribac-sodium Yoshihiro Saito, Mitsumasa Ikeda and Akira Yagi Introduction Outline of method Apparatus Reagents Sampling and sample preparation

469 469 469 470 470 471


Procedure Extraction Cleanup Gas-chromatographic determination Evaluation Method Recoveries, limit of detection and limit of determination Calculation of residues Important points

Carfentrazone-ethyl Audrey Chen Introduction Outline of method Apparatus Reagents Sampling and preparation Analytical procedures for nonoil crop matrices Sample extraction, filtration and concentration Partition Determination of carfentrazone-ethyl Determination of acid metabolites Analytical procedures for crop refined oils Analytical procedures for animal matrices Instrumentation Method validation and quality control Experimental design Preparation of standards Calculation Time required for analysis Accuracy and precision Important points Storage stability Acknowledgements

Flucarbazone-sodium Thomas J. Gould and Chung K. Lam Introduction Outline of method Apparatus Reagents and consumable supplies Sampling and preparation Procedure Extraction Cleanup/concentration Chromatographic determination Evaluation Method Recoveries, limit of detection and limit of quantitation Calculation of residues

471 471 472 473 473 473 473 474 474

475 475 476 477 479 479 480 480 480 480 481 482 483 483 484 484 484 485 486 486 486 488 488

489 489 490 490 491 491 491 491 492 493 494 494 495 496

xv

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Important points References

Flumetralin Robert A. Yokley Introduction Outline of methods Apparatus Reagents Sample preparation Soil Plant materials Instrumentation Evaluation Method Recoveries, limit of detection (LOD) and limit of quantitation (LOQ) Calculation of residues Reference

Flumioxazin Thomas Schreier

497 497

498 498 498 499 499 499 499 500 500 501 501 501 501 501

502

Introduction Outline of method Plant matrices Soil Water Apparatus Reagents Sampling and preparation Procedure Extraction Cleanup Determination Evaluation Method Recoveries, limit of detection and limit of quantitation Calculation of residues Important points

502 503 503 503 503 503 503 504 504 504 505 506 507 507 507 507 508

Isoxaflutole Robert J. Seymour, Craig A. Smitley and Sabrina X. Zhao

509

Introduction Outline of method Reagents and standards Equipment and supplies Sampling and preparation Extraction procedure Manual procedure

509 510 510 510 511 511 511


Automated procedure using a Zymark Benchmate Workstation with EasyFill module Determination by LC/MS/MS Evaluation Performance criteria Recoveries, limit of detection and limit of quantifiation Calculation

Orbencarb Mitsumasa Ikeda, Yoshihiro Saito and Akira Yagi Introduction Outline of method Equipment Reagents Sample preparation Procedure Extraction Cleanup Gas-chromatographic determination Evaluation Method Recoveries and limits of detection Calculation of residues Important points Liquid–liquid partition Cleanup Evaporation Detection Determination of Metabolite II in soil Reference Further reading

Prodiamine Robert A. Yokley Introduction Outline of method Apparatus Reagents Sample preparation Air Soil Water Instrumentation Evaluation Method Recoveries, limit of detection(LOD) and limit of quantitation (LOQ) Calculation of residues Important point

512 514 515 515 515 515

519 519 519 520 520 521 521 521 522 523 524 524 524 524 524 524 525 525 525 525 525 525

526 526 527 527 527 528 528 528 528 529 530 530 530 530 531

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Prohexadione-calcium Akira Yagi, Mitsumasa Ikeda and Yoshihiro Saito Introduction Outline of method Apparatus Reagents Sampling and sample preparation Procedure Extraction Ion-exchange column chromatography Methylation Reversed-phased silica gel column chromatography cleanup High-performance liquid chromatographic determination Evaluation Method Recoveries and limits of detection Calculation of residues Important points References

Pyraflufen-ethyl Yuji Ikemoto Introduction Outline of method Multi-residue analytical method Apparatus Reagents and supplies Procedure Total toxic residue analytical method Apparatus Reagents and supplies Procedure Evaluation Important points References

Pyriminobac-methyl Akira Yagi, Mitsumasa Ikeda and Yoshihiro Saito Introduction Outline of method Apparatus Reagents Sampling and sample preparation Procedure Extraction Liquid–liquid partition (rice grain, rice straw and soil) Cleanup Gas-chromatographic determination

532 532 532 533 533 534 534 534 535 536 536 536 537 537 537 537 538 538

540 540 541 542 542 543 543 547 547 547 547 549 550 550

551 551 551 552 552 552 553 553 553 553 554


Evaluation Method Recoveries and limit of detection Calculation of residues Important points Method for extraction of pyriminobac-methyl from soil Extraction of pyriminobac-methyl from rice grain and rice straw Cleanup GC column Sample storage stability References

Pyrithiobac-sodium Yoshihiro Saito, Mitsumasa Ikeda and Akira Yagi Introduction Outline of method Apparatus Reagents Sampling and sample preparation Procedure Extraction Cleanup Gas-chromatographic determination Evaluation Method Recoveries, limit of detection and limit of determination Calculation of residues Important points Reference

Sulfentrazone Andrey Chen Introduction Method description Method development history Outline of method Apparatus Reagents Sampling and preparation Analytical procedures for nonoil crop matrices Sample extraction, filtration and concentration Second reflux (conversion of SCA to DMS and release of conjugated HMS) and filtration C8 SPE cartridge C8 SPE cartridge/first slica gel SPE cartridge Derivatization (silylation of 3-hydroxymethyl sulfentrazone) Second (post-derivatization) silica gel SPE cartridge Analytical procedures for oily crop matrices

555 555 555 555 555 555 556 556 556 556 557

558 558 558 559 559 560 560 560 560 561 562 562 562 562 563 563

564 564 566 566 566 566 568 568 569 569 569 569 570 570 570 571

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xx


Analytical procedures for crop refined oils Instrumentation Method validation and quality control Experimental design Preparation of standards Calculation Time required for analysis Accuracy and precision Important points Storage stability Acknowledgments

Terbacil Janine E. Rose Introduction Outline of method Apparatus Reagents Sampling and preparation Procedure Extraction Derivatization Cleanup Determination Evaluation Method Recoveries, limit of detection and limit of determination Calculation of residues Important points Reference

Thenylchlor Hiroko Kobayashi Introduction Outline of method Apparatus Reagents Sampling and preparation Procedure Extraction Cleanup Determination (rice grain, soil and water) Evaluation Method Recoveries and limit of detection Calculation of residues Important points References

571 571 573 573 573 573 575 575 575 576 577

578 578 578 579 580 580 580 580 581 581 582 582 582 583 583 583 584

585 585 585 586 586 586 586 586 587 588 588 588 588 589 589 589


Trinexapac-ethyl Yi Lin Introduction Outline of methods Trinexapac-ethyl Trinexapac Apparatus Reagents Sampling and preparation Extraction and cleanup Trinexapac-ethyl Trinexapac Determination Evaluation Method Recoveries, limit of detection (LOD) and limit of quantitation (LOQ) Calculation of residues Acknowledgments References

Abbreviations and acronyms Index

590 590 591 591 592 592 592 593 593 593 594 595 597 597 597 598 599 599 I III

xxi

Contents of Volume 2 Preface List of contributors

xli xliii

Recent advances in analytical technology, immunoassay and other nonchromatographic methods Regulatory considerations for environmental analytical methods for environmental fate and water quality impact assessments of agrochemicals Michael R. Barrett and Elizabeth Behl Introduction Regulatory perspectives Scientific perspectives Risk assessment perspective Acceptance criteria of environmental analytical methods for pesticide regulation Method submission and evaluation criteria Validation and availability of methods and standards Specific method development issues Identification of unknowns/selection of analyte(s) Detection limits/reporting limits Extraction efficiency/mass balance Matrix effects Specific environmental sample analysis issues Identification of target population in monitoring programs Sample collection strategy: study design Effect of inert ingredients Field quality control issues Conclusions: regulatory context References

Immunoassay, biosensors and other nonchromatographic methods Guomin Shan, Cynthia Lipton, Shirley J. Gee and Bruce D. Hammock Introduction Immunoassay for pesticides Principles of immunoassays Immunoassay formats Data reduction Sample collection and preparation Development of pesticide immunoassays Applications PCR for products of agricultural biotechnology Basic principles of agricultural biotechnology

603 603 603 604 605 606 606 608 609 609 610 612 613 614 614 615 617 618 619 620

623 623 623 624 625 628 629 631 648 653 654


Basic principles of the PCR Basic principles of real-time PCR Applications of PCR to agricultural biotechnology Recent advances in nucleic acid amplification and detection Biosensors: immunosensors Biological transducers Conclusion Abbreviations Acknowledgements References

Immunologically based assays for pesticide/veterinary medicine residues in animal products Weilin L. Shelver and David J. Smith Introduction Immunoassays and animal production agriculture Considerations involved in immunoassay development Immunoassay format End user Assay interferences Detection levels (sensitivity) Target tissues Assay validation using incurred or fortified tissues General sample treatments for eggs, milk, and meat Eggs Milk Tissues Food-animal immunoassay applications Agrochemical residue immunoassay applications Detection of veterinary medicine residues Other therapeutic agents Other antibody-based technologies Conclusion Abbreviations Acknowledgements References

Validated immunoassay methods James F. Brady Introduction Enzyme immunoassays Choice of tube or plate format Calculation of residues Comparison with chromatography-based methods Requirements for validating a residue method Examples of validated immunoassay methods Conclusion References

659 665 668 669 669 670 671 671 673 673

680 680 680 681 681 683 683 688 691 691 692 692 693 693 694 695 698 707 708 709 709 709 710

714 714 714 716 718 718 721 723 725 725

xxiii

xxiv


Advances in methods for pesticide residues in food Michael F. Wilson, Stewart L. Reynolds and Richard J. Fussell Introduction Sample processing considerations Extraction procedures Cleanup procedures Instrumental techniques for detecting, identifying and quantifying pesticide residues in food GC LC Electrophoretic techniques Immunochemical and biosensor techniques Future developments and trends Silicon-based technologies Biosensors Imprinted polymers Analyses of chiral pesticides References

Overview of analytical technologies available to regulatory laboratories for the determination of pesticide residues Alexander J. Krynitsky and Steven J. Lehotay Introduction Sample preparation Extraction Cleanup Analytical separations and detection Gas chromatography/mass spectrometry (GC/MS) HPLC/MS Capillary electrophoresis (CE) Conclusions Acknowledgements References

727 727 728 729 734 737 737 742 743 746 747 747 748 748 748 749

753 753 754 754 759 762 762 765 781 784 784 785

Best practices in the generation and analyses of residues in environmental samples Best practices in the analysis of residues in environmental samples: groundwater and soil-water monitoring procedures Leslie S. Carver and Joseph R. Chepega Introduction Sources for the collection of groundwater samples Monitoring wells Water supply wells Other groundwater sources Groundwater sampling procedures Pesticides of interest

789 789 790 790 799 799 800 800


Sample collection techniques Sampling of other groundwater sources Suction lysimeter installation and sampling procedures Preparation and installation Lysimeter sampling Summary References

800 811 812 812 814 815 816

Preparation and instrumental analysis of agrochemical residues in water samples William M. Leimkuehler 818 Introduction Regulatory issues Historical perspectives Sample preparation Instrumentation Historical perspective Current technology: Mass spectrometry Selected reaction monitoring (SRM)/confirmation Matrix effects, calibration and quantitation Quantitation Detection limits Applications of LC/API-MS and LC/API-MS/MS in water sample analyses Conclusion References

Sampling and analysis of soil Joseph H. Massey, Scott H. Jackson, Manasi Saha and Eberhard Zietz Introduction Phase I: field study design and logistics Physicochemical properties Use-pattern considerations Analytical considerations Basic experimental designs for field soil dissipation studies Additional considerations Phase II: field study conduct Test site selection Test substance application Soil sampling techniques Phase III: sample processing and analysis Sample homogenization Sample extraction Sample cleanup Derivatization techniques Analytical detection and quantitation techniques Freezer storage stability Phase IV: reporting of results Goodness of fit testing Models for agrochemical dissipation in soil DT50 versus T1/2 values

818 819 820 821 826 826 828 831 832 833 833 834 836 838

840 840 841 841 845 850 853 858 858 858 861 863 872 873 874 876 877 878 879 880 880 881 883

xxv

xxvi


Determining water balance and leaching potential Weather data requirements for water balance and mobility assessments Summary and conclusions Abbreviations References

884 888 888 888 889

Sampling sediment and water in rice paddy fields and adjacent water bodies Hiroki Yamamoto and Kouji Nakamura

892

Introduction Rice production in paddy fields Regulatory requirements and guidelines Study design Study objectives Preparation of study protocol Study best practices Sediment sampling Water sampling Sample handling and shipment Quality control (QC) and quality assurance (QA) Data presentation and interpretation Conclusion References

Monitoring of agrochemical residues in air James E. Woodrow, Vincent Hebert and James S. LeNoir Introduction Sample collection techniques Chemical vapors Chemicals in aerosols Trapping efficiency Chemical vapors Aerosols Field sampling procedures for airborne pesticides Localized programs Regional field procedures QA/QC considerations Summary References

Biological sampling: determining routes of wildlife exposure to pesticides George P. Cobb and Todd A. Anderson Introduction Regulatory requirements and guidelines Historical perspectives Study designs and best practices Define study objectives Preparation of study protocol Test substances

892 892 893 894 894 895 899 899 901 902 904 905 906 907

908 908 909 909 912 916 917 922 924 924 927 929 931 932

936 936 938 938 939 940 940 941


Test systems Selection of test sites Preparation of test sites Application phase Sampling Sample handling and shipment QA and field data requirements Data reporting Data presentation and interpretation Case studies overview Case study with Diazinon 50W Fortress-5G case study Conclusions and recommendations Acknowledgments References

Best practices in conducting dislodgeable foliar residue studies Joseph P. McClory and D. Larry Merricks Introduction Regulatory requirements and experimental field design Protocol design Test system Justification of test system Materials and methods – test substance Study locations Plot layout Application Foliar sampling Soil sampling Sampling intervals Dislodging residue from leaf surface Field fortifications Analysis Quality assurance Results Recommendations References

Best practices to conduct spray drift studies Andrew J. Hewitt and David L. Valcore Introduction Study designs Study objectives Tracer materials Selection of sampling locations and site preparation Sampling devices Field data requirements Performance criteria

942 942 943 943 944 945 946 946 946 947 948 952 956 956 957

960 960 961 962 962 962 963 963 964 965 966 966 966 967 968 968 971 972 973 973

974 974 975 975 976 977 978 983 984

xxvii

xxviii


Covariate study designs Summary References

Field methods for performing farm worker exposure and re-entry studies Richard Honeycutt Introduction Current field methods for measuring mixer–loader and re-entry worker exposure to pesticide residues Study design and protocol preparation Site selection Setting up a field laboratory and auxiliary equipment Acquiring consent from study participants Execution of the field portion of the worker exposure/re-entry study Observations of the volunteers during the conduct of the field study Data collection and the use of field forms Storage and shipping of study samples Making sense of field data from worker exposure and re-entry studies Organizing field data Correcting field and analytical data Conclusions References

Electronic record keeping in a regulated environment Willa Garner and Carolyn Mentzer Introduction Management and integration of electronic records and documents Electronic reporting requirements Electronic data management of protocols and SOPs Management of field data and information Management of laboratory data and information Selection of a data system System qualification Access control Metrology Building blocks of a metrology program Quality assurance (QA) and data audit Critical areas to consider for auditing field studies Critical areas to consider for auditing analytical laboratory studies Validation of computerized systems System life cycle Validation of chromatography software Validation priority setting and risk assessment Organizational considerations Validation of in-house and vendor-supplied systems Electronic archiving Managing durability Managing usability

985 986 987

989 989 991 991 992 993 998 1000 1021 1022 1023 1023 1023 1024 1024 1025

1027 1027 1028 1029 1029 1034 1036 1037 1038 1038 1039 1040 1043 1048 1052 1055 1056 1058 1058 1059 1061 1061 1063 1064


Open and closed systems Electronic records and electronic signatures Storage media issues Audit trail Considerations for electronic submission Creation of PDF documents Benefits of PDF documents Supplemental files Central Data Exchange (CDX) An industry perspective Evaluator needs United States EDS process EPA Office of Enforcement (OE) perspective Regulatory enforcement of electronic data management Harmonization Canada European Union References

1064 1065 1065 1066 1066 1067 1068 1069 1072 1073 1075 1075 1077 1078 1080 1081 1082 1085

Compound class Alkylenebis(dithiocarbamates) Mihai Cicotti Introduction Method overview Sample preparation Analytical method for the determination of alkylenebis(dithiocarbamates) in plant commodities by hot acid decomposition and spectrophotometric determination Principle of the method Apparatus Reagents Solutions Standards and standard solutions Reflux procedure Photometric measurement Recovery experiments Limit of quantitation Methyl xanthate spectrophotometric method Analytical method for the determination of alkylenebis(dithiocarbamates) in plant commodities by headspace GC and flame photometric (FPD) detection Principle of the method Apparatus Reagents Solutions Standards and standard solutions Headspace procedure Gas-chromatographic conditions Recovery experiments Conclusions References

1089 1089 1090 1091 1092 1092 1092 1092 1093 1093 1093 1094 1094 1095 1095 1095 1095 1096 1096 1096 1097 1097 1097 1097 1098 1098

xxix

xxx


Multi-residue methods (S19) to measure azole fungicides in crop samples Guenther Kempe Introduction Introduction to the method General overview of the various modules Identification and confirmation Calculation Extraction Module E1: extraction and subsequent liquid/liquid partition for materials with a water content exceeding 70 g/100 g and a fat content below 2.5 g/100 g Module E2: extraction and subsequent liquid/liquid partition for materials with a water content below 70 g/100 g and a fat content below 2.5 g/100 g Module E3: extraction and subsequent liquid/liquid partition for materials with a water content exceeding 70 g/100 g, a fat content below 2.5 g/100 g and a high acid content (highly recommended for determining acid-sensitive analytes) Module E4: two-stage extraction and liquid/liquid partition for materials with a water content exceeding 70 g/100 g and a fat content below 2.5 g/100 g Module E5: two-stage extraction and liquid/liquid partition for materials with a water content below 70 g/100 g and a fat content below 2.5 g/100 g Module GPC: gel permeation chromatography Module C1: column chromatography on a small silica gel column Gas chromatography with ECD and NPD Procedure Summary References

Neonicotinoids Hiroko Kobayashi Introduction Analytical methodology for plant materials Nature of the residue Analytical method principle Analytical methodology for soil Nature of soil residues Analytical method Analytical methodology for water Nature of the residues Analytical method References

Oxime carbamates Maria Elena Y. Cabusas Introduction Analytical methodology Reversed-phase HPLC/fluorescence analysis Reversed-phase HPLC/MS and HPLC/MS/MS analysis Crops, food, feed, and animal tissue Soil Water

1099 1099 1099 1102 1103 1104 1104 1104 1107

1108 1110 1111 1113 1115 1117 1117 1127 1127

1128 1128 1128 1128 1130 1138 1138 1139 1141 1141 1142 1143

1144 1144 1147 1147 1148 1153 1158 1159


Conclusions and future directions Acknowledgements References

1161 1162 1162

Individual compounds Azoxystrobin Neil J. Robinson Introduction Outline of methodology Crop samples Soil Water Animal matrices Air Apparatus Reagents Sampling and preparation Procedure Extraction Sample cleanup procedures Determination Evaluation Method Recoveries, limit of detection and limit of quantification Calculation of residues Important points Reference

Famoxadone Kathryn M. Jernberg Introduction Outline of method Apparatus Plants Soil and water Reagents Plants Soil and water Sampling and preparation Procedure Extraction Cleanup Determination Evaluation Method Recoveries, limit of detection, and limit of quantification Calculation of residues Important points

1167 1167 1168 1168 1168 1168 1168 1169 1169 1169 1170 1170 1170 1170 1173 1174 1174 1174 1175 1176 1176

1177 1177 1178 1178 1178 1179 1180 1180 1180 1180 1180 1180 1181 1184 1187 1187 1188 1189 1190

xxxi

xxxii


Fluthiacet-methyl Mitsumasa Ikeda, Yoshihiro Saito and Akira Yagi Introduction Outline of method Equipment Reagents Sample preparation Procedure Extraction Cleanup Determination Evaluation Method Recoveries and limit of detection Calculation of residues Important points

Flutolanil Yuji Ikemoto Introduction Outline of method Multi-residue analytical method (for potatoes) Apparatus Reagents and supplies Procedure Evaluation Total toxic residue analytical method (for rice plant) Apparatus Reagents and supplies Procedure Evaluation Important points GC/FTD method Apparatus Reagents and supplies Procedure Evaluation GC/MS method Apparatus Reagents and supplies Procedure Evaluation References

Hymexazol Shingo Sadakane, Takeshi Saito, Mariko Sabi and Takeo Otsuka Introduction Outline of method

1191 1191 1192 1192 1192 1193 1193 1193 1194 1195 1196 1196 1196 1196 1197

1198 1198 1199 1200 1200 1200 1200 1202 1202 1202 1203 1203 1205 1206 1206 1206 1207 1207 1208 1208 1208 1209 1209 1210 1210

1211 1211 1211


Apparatus Reagents Sampling and preparation Procedure Extraction Liquid–liquid partition Determination by gas chromatography Evaluation Method Limit of detection Method recovery in plant Important points

Imibenconazole Fujio Ishijima Introduction Outline of method Apparatus Reagents Sampling and preparation Procedure Extraction Cleanup Gas-chromatographic determination Evaluation Method Recoveries, limit of detection and limit of determination Calculation of residues Important point

Mepanipyrim Mitsumasa Ikeda, Yoshihiro Saito and Akira Yagi Introduction Outline of method Equipment Reagents Sample preparation Procedure Extraction Cleanup Gas-chromatographic determination Evaluation Method Recoveries and limit of detection Calculation of residues Important points Analysis of plant metabolites Extraction rate from soil Further reading

1212 1212 1212 1212 1212 1213 1213 1213 1213 1214 1214 1214

1215 1215 1216 1216 1216 1217 1217 1217 1217 1218 1219 1219 1219 1219 1220

1221 1221 1222 1222 1222 1223 1223 1223 1224 1224 1225 1225 1225 1226 1226 1226 1227 1227

xxxiii

xxxiv


Mepronil Yoshihiro Saito, Mitsumasa Ikeda and Akira Yagi Introduction Outline of method Apparatus Reagents Sampling and sample preparation Procedure Extraction Cleanup Gas-chromatographic determination Evaluation Method Recoveries, limit of detection and limit of determination Calculation of residues Important points

Tebuconazole Greg C. Mattern, Chung V. Lam and Timothy J. Grace Introduction Outline of method Apparatus Reagents/supplies and reference standards Reagents/supplies Reference materials Sampling and preparation Procedures Extraction Cleanup Determination Evaluation Method Recoveries, limits of detection, and limits of quantification Calculation of residues Reference

Acetamiprid Shigeji Sugimoto Introduction Outline of method Plant Soil Apparatus Reagents Sampling and preparation Green tea Fruits and vegetables Procedure Extraction

1228 1228 1228 1229 1229 1230 1230 1230 1230 1231 1231 1231 1232 1232 1232

1233 1233 1234 1234 1235 1235 1235 1235 1236 1236 1236 1237 1238 1238 1239 1240 1241

1242 1242 1243 1243 1243 1243 1244 1244 1244 1244 1245 1245


Cleanup Determination Evaluation Method Recoveries, limit of detection and limit of determination Calculation of residues Important points Further reading

Alanycarb Katsura Yagi and Noriharu Umetsu Introduction Outline of method Apparatus Reagents Sampling and preparation Procedure Extraction Cleanup Saponification Determination Evaluation Method Recoveries, limit of detection and limit of determination Calculation of residues Important points

Azinphos-methyl Sean M. Moore Introduction Outline of method Apparatus Reagents Sampling and preparation Procedure Extraction of plant material Determination Evaluation Response factor Recoveries, limit of detection and limit of quantification Calculation of residues Important points

Benfuracarb Katsura Yagi and Noriharu Umetsu Introduction Outline of method Apparatus

1246 1247 1248 1248 1248 1249 1249 1249

1250 1250 1251 1251 1252 1252 1252 1252 1253 1254 1254 1255 1255 1255 1256 1257

1258 1258 1259 1259 1259 1259 1259 1259 1260 1261 1261 1261 1262 1262

1263 1263 1264 1264

xxxv

xxxvi


Reagents Sampling and preparation Procedure Extraction Cleanup Determination Evaluation Method Recoveries, limit of detection and limit of determination Calculation of residues Important points References

Buprofezin Yuji Ikemoto Introduction Outline of method Multi-residue analytical method (for plants) Apparatus Reagents and supplies Procedure Evaluation Important points GC/MS method (for plants) Apparatus Reagents and supplies Procedure Evaluation Multi-residue analytical method (for soil) Apparatus Reagents and supplies Procedure Evaluation GC/MS method (for water) Apparatus Reagents and supplies Procedure Evaluation References

Cyfluthrin Chung V. Lam and Sean M. Moore Introduction Outline of method Apparatus Reagents/supplies and reference standards Reagents/supplies Reference materials Sampling and preparation

1265 1265 1265 1265 1266 1267 1267 1267 1268 1268 1269 1269

1270 1270 1271 1272 1272 1272 1272 1273 1274 1274 1274 1275 1275 1276 1276 1276 1277 1277 1278 1279 1279 1279 1279 1280 1281

1282 1282 1283 1283 1284 1284 1284 1284


Procedures Extraction Cleanup Determination Evaluation Method Recoveries, limits of detections, and limits of quantitation Calculation of residues

Fenothiocarb Akira Yagi, Mitsumasa Ikeda and Yoshihiro Saito Introduction Outline of method Apparatus Reagents Sampling and sample preparation Procedure Extraction Cleanup Gas-chromatographic determination Evaluation Method Recoveries, limit of detection and limit of determination Calculation of residues Important points References

Fenoxycarb Robert A. Yokley Introduction Outline of methods Apparatus Air Water Soil Pasture grass hay, forage, cucurbits, citrus, pome fruit, tree nuts, fruiting vegetables, and cotton substrates Animal tissues, milk, blood, and eggs Reagents Sample preparation Air Water Soil Plant material Animal material Instrumentation Evaluation Method

1284 1284 1285 1285 1286 1286 1286 1287

1288 1288 1288 1289 1289 1289 1290 1290 1290 1291 1292 1292 1292 1292 1293 1293

1294 1294 1295 1295 1295 1295 1295 1296 1296 1296 1297 1297 1297 1298 1298 1301 1302 1305 1305

xxxvii

xxxviii


Recoveries, limit of detection (LOD) and limit of quantitation (LOQ) Calculation of residues Reference

Fenpyroximate Yuji Ikemoto Introduction Outline of method Multi-residue analytical method (for plants and soil) Apparatus Reagents and supplies Procedure Evaluation Multi-residue analytical method (for water) Apparatus Reagents and supplies Procedure Evaluation References

Hexythiazox Shigeji Sugimoto Introduction Outline of method Apparatus Reagents Sampling and preparation Green tea Fruits and vegetables Procedure Extraction Cleanup Determination Evaluation Method Recoveries, limit of detection and limit of determination Calculation of residues Important point Reference

Imidacloprid William M. Leimkuehler and Kimberly S. Billesbach Introduction Outline of method Reagents and standards Native standards Internal standards Native stock solutions

1306 1306 1307

1308 1308 1309 1309 1309 1310 1310 1312 1313 1313 1313 1313 1314 1314

1316 1316 1317 1317 1317 1317 1317 1317 1318 1318 1318 1318 1319 1319 1319 1319 1319 1319

1320 1320 1321 1321 1321 1321 1322


Mixed standard solution Internal standard stock solutions Mixed internal standard solution Apparatus Sampling and preparation Procedure Sample setup Determination Evaluation Method Recoveries, limit of detection (LOD) and limit of quantitation (LOQ) Calculations Important points Reference

Isoxathion Shingo Sadakane, Manabu Toujigamori, Takeshi Saito and Yasuhiro Tsujino Introduction Outline of method Apparatus Reagents Analytical procedure Extraction Partition of n-hexane and aqueous solution Partition of acetonitrile and hexane Florisil column chromatography Determination Evaluation Method Limit of detection Recovery rate in plants

Milbemectin Shingo Sadakane, Takashi Ueda, Takashi Saito, Setsuko Katsurada, Mariko Sabi and Yasuhiro Tsujino Introduction Outline of method Apparatus Reagents Sample preparation Procedure Extraction Cleanup Conversion of M.A3 and M.A4 to corresponding fluorescent anhydride derivatives Determination by HPLC Evaluation Method

1322 1322 1322 1322 1323 1323 1323 1323 1324 1324 1325 1325 1326 1326

1327 1327 1327 1328 1328 1328 1328 1328 1328 1329 1329 1329 1329 1330 1330

1331 1331 1332 1332 1333 1333 1333 1333 1334 1334 1334 1335 1335

xxxix

xl


Limit of detection Recovery from plants Recovery from soil Important points

Pyrimidifen Shingo Sadakane, Takashi Ueda, Takashi Saito, Setsuko Katsurada and Mariko Sabi Introduction Outline of method Apparatus Reagents Sampling and preparation Procedure Extraction Cleanup Determination Evaluation Method Limit of detection Recovery Calculation of residue Important point

Pyriproxyfen Charles A. Green Introduction Outline of method Fruits and vegetables Ginned cottonseed Nutmeats Soil Water Apparatus Reagents Sampling and preparation Procedure Extraction and cleanup Determination Evaluation Method Recoveries, limit of quantitation, and limit of detection Calculation of residues Important points

Abbreviations and acronyms Index

1335 1335 1335 1335

1336 1336 1336 1337 1337 1337 1337 1337 1337 1338 1338 1338 1338 1339 1339 1339

1340 1340 1341 1341 1341 1341 1341 1341 1342 1342 1343 1343 1343 1348 1349 1349 1349 1350 1350 I III

Introduction James N. Seiber Western Regional Research Center, USDA Agricultural Research Service, Albany, CA, USA

1 Introduction The first generation of pest control agents, consisting largely of botanicals and inorganic substances containing copper, lead, sulfur, or arsenic, received little regulatory interest, and thus there was little monitoring of the products applied or of the residues remaining from them. Visual monitoring could be done for some materials, such as Paris Green, which was blue–green from its copper content, or lead arsenate, which often left a white residue on apples and other produce because of the high application rates. Simple gravimetric, titrimetric, or colorimetric methods could be used to quantify residues of many agents, including copper-, arsenic-, sulfur-, and lead-containing products or their derivatives.1 Thoroughly washing treated fruit and fresh vegetables probably removed most residues since the materials in use were largely nonsystematic and water soluble or water wettable, lessening their hazard to the consumer. This situation changed significantly with the introduction of second-generation pest control agents, largely synthetic organics such as DDT, 2,4-D, and ethyl parathion, from the 1940s on. These chemicals had a number of qualities which invited heightened consumer concern, regulatory attention, and monitoring activity: 1. They were more widely used, some would argue overused, compared with firstgeneration products. 2. They were applied at such rates that their residues were not visible or detectable to the consumer. 3. Many were acutely toxic and/or chronically toxic to humans, domestic animals, and wildlife. Their ability to cause tumors, at least in laboratory animals, was of particular concern. 4. Their residues were mobile, systemically within plants and environmentally in air, water, soil, and food chains. 5. Many degraded/metabolized to products which had different toxicity and dissipation characteristics than the parents. Regulation was developed in the 1950s and 1960s to include legal limits (tolerances) for residues on foods and in feeds and, with time, in water and air.2 Enforcing these regulations required analytical methods of ever-increasing sophistication and Handbook of Residue Analytical Methods for Agrochemicals. C 2003 John Wiley & Sons Ltd.

2

Introduction

sensitivity as public concern grew with each new residue-related crisis or toxicology finding. Early efforts at regulating residues confounded the situation. Legislators introduced a ‘zero tolerance’ concept for pesticides that produced cancer in experimental animals, for agricultural crops or food animal products such as milk and butter. However, as analytical methods improved, what was ‘zero’ by prior methods and instrumentation became detectable. Zweig3 described three incidents in the 1950s and 1960s that showed the futility of zero tolerances. One was the analytical finding, using a new method, of aminotriazole residues on cranberries from Oregon and Massachusetts in 1959, the week before Thanksgiving. The fungicide was a carcinogen with a ‘zero tolerance’. The Food and Drug Administration (FDA) confiscated most of the cranberry harvest of 1959 and even some canned products from previous years. This gave a clear signal that ‘zero’ was a moving analytical target. Veteran residue chemists refer to the periods before and after 1959 as BC and AC – before and after cranberries! A second was the 1960 finding of chlorinated insecticides, using a paper chromatography method perfected by Mills4 and Mitchell,5 and by the Schecter et al.6 colorimetric method, in butter shipped from the mainland to Hawaii. This finding resulted in seizure of butter, milk, and other dairy products and posed a major dilemma for the government. Clearly, low residues of organochlorine insecticides in animal feed, which was practically unavoidable given the widespread use of these materials and their stability, could transfer to animals and dairy products in quantities detectable by residue analytical methods. The development of the electron capture detector for gas chromatography (GC) at about the same time7 foreshadowed even more challenges for ‘zero tolerance.’ The third was the publication, in 1962, of ‘Silent Spring’,8 which revealed to a previously unaware public the extent of contamination of food with pesticide residues which were undetected by prior methods, and raised the possibility of irreversible harm to wildlife. The outcry which followed resulted in increased funds for research on better analytical methods for monitoring, as well as more extensive toxicology, environmental fate, and ecological effects studies. ‘Silent Spring’ set in motion a series of actions including the US Department of Health, Education, and Welfare Report (‘Mrak Commission’),9 establishment of the Environmental Protection Agency,10 and the banning of dichlorodiphenyltrichloroethane (DDT) for agricultural uses in the USA in 1972, a century after it was discovered.11 With this backdrop, pesticide residue analysis grew and matured from, roughly, the 1950s to the present. Early advances and applications are published in such primary outlets as the Journal of the Association of Official Analytical Chemists (now Journal of AOAC International), Journal of Agricultural and Food Chemistry, Analytical Chemistry, and The Analyst. Secondary references or compendia include those by Gunther and Blinn,1 Gunther,12 Zweig,13 and Moye14 and the ‘Pesticide Analytical Manual’.15 The Association of Official Agricultural Chemists [later named the Association of Official Analytical Chemists (AOAC) and now AOAC International], the American Chemical Society’s Division of Pesticide Chemistry (now the Agrochemical Division), and the International Union of Pure and Applied Chemistry (IUPAC) pesticide congresses were (and still are) popular meeting grounds for residue chemists. A cadre of analytical agricultural chemists specializing in pesticide residue analysis emerged at a few North American, European and Japanese Universities, regulatory

Introduction

agencies, food companies, and agricultural chemical companies. These chemists proved equal to the challenges posed by changing regulations, new toxicological findings, societal concerns, and the occasional crises. Colorimetry, polarography, and both paper and thin-layer chromatography provided minimum analyte detectabilities of 10−5 –10−8 g (10 µg–10 ng).3 GC with element-selective detectors or electron capture detection (ECD) provided analyte detection limits of 10−9 – 10−12 g (1 ng–1 pg). Hyphenated techniques, such as gas chromatography/mass spectrometry (GC/MS), gas chromatography/tandem mass spectrometry (GC/MS/MS) and high-performance liquid chromatography/mass spectrometry (HPLC/MS) also gave analyte detectabilities of 10−9 –10−12 g, but with exceptional, often single analyte selectivity. Enzyme-linked immunosorbent assay (ELISA) and other antibodybased immunoassays operate in the same range, often at significantly reduced costs.16 When pushed to the limit by overriding human health concerns, residue chemists have achieved detection limits of 1 ppt (1 ng kg−1 ) or even into the low ppqr (1 pg kg−1 ) range. An example at the 1 ppt level is provided by methods for 2,3,7,8tetrachlorodibenzodioxin (TCDD) in milk17 and TCDD in adipose tissue.18 For relatively clean matrices such as water and air, preconcentration on solid-phase adsorbents followed by GC or gas chromatography/mass spectrometry (GC/MS) can provide detection limits of 1 ng m−3 and less for air (examples in Majewski and Capel19 ) and 1 ng L−1 and less for water (examples in Larson et al.20 ). A summary of units of weight and concentration used to express residue data is given in Table 1. The improvement in detection limits (and in accuracy and precision) can be ascribed to at least four advances in techniques and instrumentation: 1. advent of commercial ultraviolet (UV) visible spectrophotometers, beginning with the Beckman DU spectrophotometer, and associated derivatization techniques to form UV-absorbing or colored derivatives; 2. development of chromatography, with its unsurpassed ability to resolve individual chemical species; 3. development of class- and chemical-specific spray reagents (paper and thin-layer) and electronic detectors for GC and high-performance liquid chromatography (HPLC), using element-selective and electron capture (GC), UV visible (HPLC), and mass spectrometry (both GC and HPLC). Table 1 Units of weight and concentration commonly employed in pesticide residue chemistry Units of weight Unit

Gram equivalents

1 microgram (1 µg) 1 nanogram (1 ng) 1 picogram (1 pg) 1 femtogram (1 fg) 1 attagram (1 ag)

10−6 10−9 10−12 10−15 10−18

a

Units of concentration Unit

wt/wt equivalenta

1 part per million (ppm) 1 part per billion (ppb) 1 part per trillion (ppt) 1 part per quadrillion (ppqr)

1 mg kg−1 1 µg kg−1 1 ng kg−1 1 pg kg−1

For water, the density of which is 1 kg L−1 , the same units are used.

3

4

Introduction

These high-profile developments were accompanied by improvements in technology such as electronics, particularly the advent of transistors and integrated circuit boards, fiber optics, and computer interfaces.

2 Relationship of pesticide residue analysis, regulation, and risk assessment Pesticide residue chemistry has responded to the challenges posed by new regulations and, in fact, underpins the ability to make tolerances, action limits, permissible levels, and acceptable daily intakes work. The dramatic lowering of permissible limits for pesticides in food, water, and air in the 1970s prompted dramatic decreases in limits of detection of analytical methods. The establishment and enforcement of tolerances for new chemicals, such as glyphosate,14 which were difficult analytical challenges, required considerable innovations by residue chemists. Innovations occurred with single residue methods (SRMs) and multiresidue methods (MRMs). The latter allows the monitoring of a broad range of pesticides (and significant transformation products) in the same sample of foods, feeds, and environmental media. The FDA’s 1987 MRMs, for example, included 316 pesticides for which tolerance levels had been set, 74 pesticides with temporary and pending tolerances, 56 pesticides with no Environmental Protection Agency (EPA) tolerance levels (i.e., those previously canceled or those used only in foreign countries), and 297 metabolites, impurities, inert ingredients, and other pesticide-associated chemicals.21 These methods, or subsets of them, are used by the FDA for general commodity monitoring (ca 15 000 annual samples) and total diet study samples (234 food types sampled four times each year), again citing 1987 figures.22 The MRMs of the FDA and other federal and state agencies have been summarized by Seiber.23 Other analytical challenges have been posed by new discoveries of toxic metabolites and formulation impurities. Included are ethylenethiourea (ETU) from the ethylenebis(dithiocarbamate) (EBDC) fungicides, dialkylnitrosamines from the dialkylamines used to formulate salts of phenoxy herbicides (as well as other sources), unsymmetrical dimethylhydrazine (UDMH) from daminozide (Alar) growth regulator, and aldicarb sulfoxide from aldicarb.24 A challenge yet to be fully met by residue chemistry was posed by the most recent US pesticide-related law, the 1996 Food Quality Protection Act, which requires, among other things, that residue monitoring be conducted for foods significantly consumed by children and other subgroups, and that pesticide-related chemicals be screened and tested as endocrine-disrupting chemicals (EDCs).25 The focus on EDCs has resulted in a world-wide effort to develop biological and chemical testing procedures for humans, wildlife, food, and environmental media.26 In addition to meeting the challenges posed by regulations, pesticide residue chemistry also plays a proactive role by detecting pesticides and their metabolites in environments where they were previously undetected and could pose undue hazards to people and/or wildlife. Examples include DDT and a host of other organohalogenated substances, now appropriately termed persistent organic pollutants (POPs), in a variety of samples ranging from human adipose tissue to bald eagles to Arctic

Introduction

seals and polar bears.27 The residue findings undoubtedly hastened the banning of DDT and other organochlorine insecticides in the USA and most industrial nations in the 1970s. The advent of risk science and risk assessment has provided a framework for targeting the type of residue information that would be most useful to society.28 Rather than relying on blind monitoring, i.e., without a hypothesis or framework, risk assessment emphasizes measuring exposures relevant to at-risk populations as a prelude to assessing impact, or potential impact, on the health of humans or wildlife. Exposure assessment requires good analytical chemistry to determine (or estimate) the average daily dose and the aggregate and cumulative exposure at several life stages. Without at least some quantitative exposure information, the uncertainty of assessing risks is too great to provide relevant, meaningful information. Exposure and risk assessment are, not surprisingly, cornerstones of the Food Quality Protection Act of 1996 (FQPA), indicating an even greater role for exposure analysis in the future.

3 Who does residue analysis and why Ultimately, all food and environmental analyses are conducted to safeguard human health and the environment. Methods are selected and applied based upon specific needs within this broader framework, including adherence to regulations, tolerances, threshold levels, etc.29 For companies that develop and register pesticides, the relevant laws (FIFRA and the FQPA) require the development of analytical methods which provide analytical data on the formulations used and measure the residues incurred during the testing phase leading to registration. These methods must be suitable for enforcement of tolerances and other restrictions after registration is granted. However, development of analytical methods is a tedious process. The methods need to account for the parent chemical as well as toxicologically significant formulation impurities, environmental breakdown products, and metabolites. Several iterations of method development may occur, because all of the impurities, metabolites, or breakdown products may not be known until each step of development of the new chemical is completed. Plant, animal, and soil metabolism studies and some studies of product breakdown by photolysis, hydrolysis, or microbial conversion are done using radiolabeled material. These studies are important for identifying conversion products, but the radioanalytical methods used are not applicable to monitoring the products and their residues after registration and use. The net result is that methods – often several for the same product – must be developed or provided by the registrant for monitoring food and feed, as well as soil, water, air, and nontarget organisms such as fish and other wildlife. Methods which have been thoroughly validated will be published in such compendia as the FDA Pesticide Analytical Manual15 or the ‘Official Methods of Analysis of the Association of Official Analytical Chemists’.30 In addition to regulatory agencies, the US Department of Agriculture (USDA), through its Cooperative State Research Education and Extension Service (CSREES) and the Agricultural Research Service (ARS), funds or carries out the development of analytical methods and the collection of residue data in studies for registration

5

6

Introduction

of pesticides in ‘minor use’ situations through the IR-4 (Interregional Project No. 4) program. Minor crops are those crops, such as strawberries, apricots, broccoli, etc., whose acreage or usage of pesticides is too small to warrant the time and expense of the registrant alone to conduct tests needed to add the crop or use to the label. The use, however, may still be important to farmers who grow these crops. IR-4 residue research is carried out at one of the four IR-4 Leader Laboratories located at Cornell University, University of California, Davis, Michigan State University, and the University of Florida or at one of the satellite laboratories or field locations of the Leader laboratories. The ARS has a parallel network of laboratories and field sites to conduct IR-4 work. The analytical methods required by agencies that conduct or oversee monitoring for pesticide residues may be different from those submitted by the registrant or developed by IR-4 laboratories or other groups. Monitoring agencies usually conduct multiresidue analyses, as noted above for the FDA, and thus may modify the submitted method or, more likely, incorporate the newly registered product in an existing multiresidue method published in the ‘Pesticide Analytical Manual’,15 Vol. I (see also other discussions21,31 ). In addition to US organizations involved in monitoring pesticides in foods (Table 2), there are a number of international agencies and governmental organizations with expertise in pesticide residue analysis. These include the ISO (International Organization for Standardization), which includes 130 countries, AOACI (Association of Official Analytical Chemists International), IUPAC (International Union of Pure and Applied Chemistry), Codex Alimentarius, OECD (Organization for Economic Cooperation and Development), and FAO/WHO (Food and Agriculture Organization of the United Nations, World Health Organization). These organizations have initiatives to standardize methods and follow established protocols for producing acceptable data, and, in several cases, for carrying out monitoring activities.32 The collection of residue monitoring data, begun in the 1950s (and reported in the Pesticide Monitoring Journal as well as other outlets), has played a major role in understanding how residues are deposited and dissipated. Unfortunately, much of the older monitoring data is of limited utility, because the samples were not properly handled and preserved, the methods were not validated for precision and accuracy, and/or the results were not confirmed with an independent method; any of these deficiencies is enough to cast doubt on the quality of the data. Because analytical data are increasingly used for making regulatory or economic decisions that can affect the availability of chemicals, their safe handling, and the safety of the food supply, there has been much more emphasis, including regulatory requirements, that residue chemists pay close attention to the quality and meaning of the data they generate. Accreditation, quality assurance (QA)/quality control (QC) and Good Laboratory Practice (GLP) are integral components of a pesticide residue chemistry program, just as they are for toxicology laboratories.33 Unfortunately, these new requirements with associated certification, chain-of-custody, record keeping, archival preservation and other requirements may increase the time and cost of residue procedures significantly. However, this extra effort is compensated for by the gain in confidence in the quality of the data and their comparability from one laboratory to another.

Introduction Table 2 Agencies and other organizations in the USA that conduct analyses for pesticide residues in foods 23 Name Federal Environmental Protection Agency Food and Drug Administration Food Safety and Inspection Service Agricultural Marketing Service Fish and Wildlife Service State California Department of Food and Agriculture Florida Department of Agriculture Texas, New York, Oregon, Washington, Massachusetts and other states Universities Cornell University, University of California, Davis, University of Florida, Michigan State University, and various satellite university laboratories Industry National Food Processors Association

General Mills, Del Monte, Campbell, and other food companies Dow, DuPont, Syngenta, Bayer CropScience, Monsanto, and other chemical companies Private Laboratories Commercial analytical laboratories

Purview Reviews and checks out analytical methods for pesticides submitted by registrants Monitors residues in imported and domestic food, including processed food Monitors residues in meat and poultry Conducts market basket surveys Monitors pesticides in fish and wildlife Monitors pesticides and other contaminants in, primarily, fruits, and vegetables Monitors pesticides and other contaminants in raw and processed foods Monitor foodstuffs of specific interest to those states Conduct analyses for pesticides crops as part of the USDA IR-4 Minor Use registration program

Monitor pesticide residues, other additives/ contaminants in fresh and processed commodities Monitor pesticides and other chemical contaminants for their company’s products Conduct analytical support for their own products in food and environmental media

Conduct analyses for pesticides and other toxicants (metals, solvents, additives) in foods, soil, water, and wastes, under contract

4 Challenges Pesticide residue chemistry has developed largely by adapting techniques and instrumentation to the unique problems of ultra-low level analysis in complex matrices. New developments in molecular biology are providing new techniques, such as those of proteomics and genomics, which may lead to creating biologically based detection methods, further refinements of immunoassay and other antibody-based methods, and whole new classes of biosensors. Coupling the exciting advances in molecular biology with the already strong analytical chemistry underpinnings of pesticide residue analysis can benefit both areas. Applying the biosensor process to measuring residues where they count – in specific cells, and at specific receptors – may lead to a better understanding of the biological significance of residues. Related to this, crops that

7

8

Introduction

are genetically modified to incorporate pest control agents pose new challenges for residue chemists in detecting the genetically modified material through the distribution chain to the consumer’s diet and to nontarget species – further areas for applying tools of molecular biology in residue analysis.34 Residue chemists will need to continue to improve the speed of analysis. In situ measuring methods that can be applied in the field or processing plant or retail outlet would be particularly useful, so that decisions can be made rapidly which might avert toxicity to humans or wildlife, potential residue problems or unnecessary economic loss. In addition, further automation will be needed in what is still very much a hands-on art. Autoinjectors coupled to complete analytical data systems and readers for 96well plates are the beginning of what will continue to be a necessary trend of residue chemistry. The application of the techniques of combinatorial chemistry/biochemistry, which has produced screening methodology for handling many variables, might be appropriate to residue chemistry. The following pages of this book will show how far pesticide residue chemistry has come and provide a platform for the many advances still in the offing.

References 1. F.A. Gunther and R.C. Blinn, ‘Analysis of Insecticides and Acaricides,’ Interscience, New York (1955). 2. G.J. Marco, R.M. Hollingworth, and J.R. Plimmer (eds), ‘Regulation of Agrochemicals. A Driving Force in their Evolution,’ American Chemical Society, Washington, DC (1991). 3. G. Zweig, ‘The vanishing zero: the evolution of pesticide analysis,’ in “Essays in Toxicology,” ed. F.R. Blood, Academic Press, New York, Vol. 2 (1970). 4. P.A. Mills, J. Assoc. Off. Agric. Chem., 42, 734 (1959). 5. L.C. Mitchell, J. Assoc. Off. Agric. Chem., 41, 781 (1958). 6. M.S. Schechter, S.B. Soloway, R.A. Hayes, and H.L. Haller, Ind. Eng. Chem. Anal. Ed., 17, 704 (1945). 7. K.P. Dimick and H. Hartman, Residue Rev., 4, 150 (1963). 8. R. Carson, ‘Silent Spring,’ Houghton, Boston, MA (1962). 9. US Department of Health, Education, and Welfare, ‘Report of the Secretary’s Commission on Pesticides and their Relationship to Environmental Health. Parts I and II,’ US Government Printing Office, Washington, DC (1969). 10. ‘Code of Federal Regulations,’ Title 3, 1966–1970 Comp. (1970). 11. R.L. Metcalf, J. Agric. Food Chem., 21, 511 (1973). 12. F.A. Gunther, (ed.), ‘Residue Reviews (Residues of Pesticides and Other Foreign Chemicals in Foods and Feed),’ Academic Press, New York, and Springer, Berlin (1962) (subsequent volumes are up to Vol. 171, 2001, edited by G. Ware). 13. G. Zweig (ed.), ‘Analytical Methods for Pesticides, Plant Growth Regulators, and Food Additives,’ Academic Press, New York, Vol. 1 (1963) (subsequent volumes are up to Vol. 17, 1989, edited by J. Sherma). 14. H.A. Moye, ‘Analysis of Pesticide Residues,’ Wiley, New York (1981). 15. Food and Drug Administration, ‘Pesticide Analytical Manual,’ US Department of Health and Human Services, Washington, DC (1994). 16. H.A. Moye, ‘Enzyme-linked immunosorbent assay (ELISA),’ in ‘Pesticide Residues in Foods: Methods, Techniques, and Regulations,’ W.G. Fong, H.A. Moye, J.N. Seiber, and J.P. Toth (eds), Wiley, New York, Chapt. 6 (1999). 17. M.L. Langhorst and L.A. Shadoff, Anal. Chem., 52, 2037 (1980).

Introduction

18. D.G. Patterson, J.S. Holler, C.R. Lapeza, Jr, L.A. Alexander, D.F. Groce, R.C. O’Connor, S.J. Smith, J.A. Liddle, and L.L. Needham, Anal. Chem., 58, 705 (1986). 19. M.S. Majewski and P.D. Capel, ‘Pesticides in the Atmosphere: Distribution, Trends, and Governing Factors,’ Ann Arbor Press, Chelsea, MI, Chapt. 2 (1995). 20. S.J. Larson, P.D. Capel, and M.S. Majewski, ‘Pesticides in Surface Waters: Distribution, Trends, and Governing Factors,’ Ann Arbor Press, Chelsea, MI, Chapt. 2 (1997). 21. Office of Technology Assessment (OTA), ‘Pesticide Residues in Food: Technologies for Detection,’ US Congress, Office of Technology Assessment, Washington, DC (1988). 22. B.M. McMahon and J.A. Burke, J. Assoc. Off. Anal. Chem., 70, 1072 (1987). 23. J.N. Seiber, ‘Extraction, cleanup, and fractionation methods,’ in “Pesticide Residues in Foods,’ ed. W.G. Fong, H.A. Moye, J.N. Seiber, and J. P. Toth, Wiley, New York, Chapt. 2 (1999). 24. J.N. Seiber, ‘Analytical chemistry and pesticide regulation,’ in “Regulation of Agrochemicals. A Driving Force in their Evolution,’ ed. G.J. Marco, R.M. Hollingworth, and J.R. Plimmer, American Chemical Society, Washington, DC, Chapt. 10 (1991). 25. S.L. Johnson and J.E. Bailey, ‘Food Quality Protection Act of 1996,’ in “Pesticides: Managing Risks and Optimizing Benefits,” N.N. Ragsdale and J. N. Seiber (eds), ACS Symposium Series 734, American Chemical Society, Washington, DC, pp. 8–15 (1999). 26. L.H. Keith, T.L. Jones-Lepp, and L.L. Needham, ‘Analysis of Environmental Endocrine Disruptors,’ ACS Symposium Series 747, American Chemical Society, Washington, DC (2000). 27. C. Bernes, ‘Persistent Organic Pollutants. A Swedish View of an International Problem,’ Swedish Environmental Protection Agency, Stockholm (1998). 28. National Research Council, ‘Pesticides in the Diets of Infants and Children,’ National Academy Press, Washington, DC (1993). 29. J.N. Seiber, ‘Analysis of chemical toxicants and contaminants in foods, in “Food Toxicology,” ed. W. Helferich and C. K. Winter, CRC Press, Boca Raton, FL, Chapt. 9 (2001). 30. Association of Official Analytical Chemists, ‘Official Methods of Analysis of the Association of Official Analytical Chemists,’ 15th edition, AOAC, Arlington, VA (1990). 31. W.G. Fong, H.A. Moye, J.N. Seiber, and J.P. Toth, “Pesticide Residues in Foods: Methods, Techniques, and Regulations,” Wiley, New York (1999). 32. A. Ambrus, ‘Quality of residue data,’ in “Pesticide Chemistry and Bioscience: The Food– Environment Challenge,” ed. G.T. Brooks and T.R. Robers, Royal Society of Chemistry, Cambridge, pp. 339–350 (1999). 33. W.G. Fong, ‘Regulatory aspects: pesticide registration, risk assessment and tolerance, residue analysis, and monitoring,’ in “Pesticide Residues in Foods: Methods, Techniques, and Regulations,” ed. W.G. Fong, H.A. Moye, J.N. Seiber, and J.P. Toth, Wiley, New York, Chapt. 7 (1999). 34. National Research Council, ‘The Future Role of Pesticides in U.S. Agriculture,’ National Academy Press, Washington, DC (2000).

9

Abbreviations and acronyms A Ab ACCD ACCS Ag ALS ASE AV bDNA bp BSA Bt C CaMV CCD CD CFR CMC

CMV CT DAM DCC DMF DNA dNTP ECD EDC EDTA ELISA EPA EPSPS

Adenine Antibody 1-Aminocyclopropane-1Carboxylic acid deaminase Aminocyclopropane carboxylic acid synthase Antigen Acetolactate synthase Accelerated solvent extraction Application verification Branched DNA Base pairs Bovine serum albumin Bacillus thuringiensis Cytosine Cauliflower mosaic virus Charge-coupled device Compact disk Code of Federal Regulations 1-Cyclohexyl-3-(2Morpholinoethyl)carbodiimide metho- p-Toluenesulfonate (same as Morpho CDI) Cucumber mosaic virus Threshold cycle DNA adenine methylase Dicyclohexylcarbodiimide Dimethylformamide Deoxyribonucleic acid Deoxynucleoside triphosphate Electron capture detection 1-Ethyl-3-(3-Dimethylaminopropyl)carbodiimide HCl Ethylenediaminetetraacetic acid Enzyme-linked immunosorbent assay Environmental Protection Agency 5-Enolpyruvylshikimate-3Phosphate synthase

EU FATUS FDA FIIA FQPA FRET G GC GC/MS GE GLC GLP GM GMO GOX HPLC HRP HSA I50

IA IAC IgG KA K D , K OC KH

KLH λmax LACPA LC

European Union Foreign Agricultural Trade of the US Food and Drug Administration Flow injection immunoassay Food Quality Protection Act Forster resonance energy transfer Guanine Gas chromatography Gas chromatography/mass spectrometry Genetically engineered Gas–liquid chromatography Good Laboratory Practice Genetically modified Genetically modified organism Glyphosate oxidoreductase High-performance liquid chromatography Horseradish peroxidase Human serum albumin The concentration of analyte that inhibits the immunoassay by 50% Immunoassay Immunoaffinity chromatography Immunoglobulin G Equilibrium binding constant for the binding of analyte to antibody Soil sorption coefficients Equilibrium binding constant for the binding of hapten to antibody Keyhole limpet hemocyanin Wavelength of maximum absorption Latin American Crop Protection Association Liquid chromatography

II

Abbreviations and acronyms

LC/MS LLD LOD LOQ LPH LSC MALDI-MS MBS Morpho CDI

MRL MS MS/MS MSDS NAFTA NHS NPD NPTII OD OPPQ OPPTS PAT PBA PCB PCR PG pK a

Liquid chromatography/mass spectrometry Lower limit of detection Limit of detection Limit of quantitation Horseshoe crab hemocyanin Liquid scintillation counting Matrix-assisted laser desorption/ ionization mass spectrometry m-Maleimidobenzoyl-N Hydroxysuccinimide 1-Cyclohexyl-3-(2-Morpholinoethyl)carbodiimide metho- pToluenesulfonate (same as CDI) Maximum residue limit Mass spectrometry Tandem mass spectrometry Material safety data sheet North American Free Trade Act N -Hydroxysuccinimide Nitrogen–phosphorus detection Neomycin phosphotransferase II Optical density Office of Plant Protection and Quarantine Office of Prevention, Protection and Toxic Substances Phosphinothricin acetyltransferase Phenoxybenzoic acid Polychlorinated biphenyl Polymerase chain reaction Polygalacturonase Acid dissociation constant

PPQ PRSV PVP QA QC r R2

Plant protection and quarantine Papaya ringspot virus Polyvinylpyrrolidine Quality assurance Quality control Regression correlation coefficient Regression coefficient of determination RCA Rolling circle amplification Sw Water solubility SDS Sodium dodecyl sulfate SFE Supercritical fluid extraction SOP Standard operating procedure SPE Solid-phase extraction SPR Surface plasmon resonance T Thymine Ta Annealing temperature TCDD 2,3,7,8-Tetrachlorodibenzo- pDioxin Tm Melting temperature TDR Time domain reflectometry Ti Tumor-inducing TOF Time-of-flight TPS Template preparation solution USDA United States Department of Agriculture USDA GIPSA United States Department of Agriculture Grain Inspection Protection Service USEPA United States Environmental Protection Agency UV Ultraviolet UV/VIS Ultraviolet/visible WMV2 Watermelon mosaic virus2 ZYMV Zucchini yellow mosaic virus

Regulatory guidance and scientific consideration for residue analytical method development and validation

Assessment of residue analytical methods for crops, food, feed, and environmental samples: the approach of the European Union Johannes Siebers and Ralf Hänel Federal Biological Research Centre for Agriculture and Forestry (BBA), Braunschweig, Germany

1 Introduction Plant protection products are widely used throughout the world to reduce the loss in crop production caused by harmful organisms and weeds. However, their usage poses potential risks to humans, animals and the environment, especially if used without having been evaluated for safety and without having been authorized. In order to minimize the risks and to facilitate the trade of plant protection products and agricultural produces within the common market, the European Community (EC) has adopted Council Directive 91/414/EEC of 15 July 1991 concerning the placing of plant protection products on the market.1 As a result, the evaluation of the safety of active ingredients (a.i.) contained in plant protection products is now carried out on the basis of data requirements which are harmonized throughout the EC. For reasons of preventive health protection and protection of the environment, the use of plant protection products has to be limited to the minimum level compatible with effective crop protection. Maximum residue limits (MRLs) are established for crops and food. Member States are responsible for monitoring the compliance of foodstuffs with these MRL levels on a regular basis to ensure that no misuse of products has taken place. In view of the importance of the quality of water intended for human consumption, a general limit for crop protection products and toxicologically relevant metabolites/degradation products is also established for drinking water. For surface water, soil, and air, there are no harmonized limits; however, pesticide residue levels in these environmental compartments are regulated at the national level. Residue analytical methods are needed to enforce these legally based limits or guidance values and to perform monitoring projects. For existing a.i., validated analytical procedures for only a few selected compounds have been published in journals or Handbook of Residue Analytical Methods for Agrochemicals. C 2003 John Wiley & Sons Ltd.

14

Regulatory and scientific consideration for residue analytical methods

handbooks. But for many compounds in use and especially for new a.i., there are no sufficiently validated residue analytical methods available in open literature. Therefore, legal provisions are created to supply laboratories involved in post-registration control and monitoring with residue analytical methods for plant protection products. Analytical methods are required, as part of the registration data package, to be evaluated at national and/or at Community level. The purpose of this article is to clarify the assessment of residue analytical methods in the context of Directive 91/414/EEC. After discussing the legal and historical background, requirements for enforcement methods as well as data generation methods are reviewed. Finally, an outlook over further developments in the assessment and validation of analytical methods is provided.

2 Legal background 2.1 General Since the foundation of the European Communities was laid in 1952 with the European Coal and Steel Community (ECSC), the importance of the European Communities within their own borders and for the global economic system has increased. Starting with six European countries in 1952, the EC now comprises of 15 Member States, and enlargement negotiations are in progress. The European Communities have continued to develop, becoming the European Union (EU), an umbrella for the three extant European Communities, ECSC, European Atomic Energy Community (EURATOM), and European Community [EC, formerly European Economic Community (EEC)]. Institutions involved in the legislative process are the Council of the European Union, usually known as the Council of Ministers (of the Member States), the European Commission (the administration of the EC) and, with limited powers, the European Parliament. The Court of Justice ensures that the law is observed in all Community and Member State activities. Community law may take the following forms: regulations are applied directly in all Member States without the need for national measures to implement them.2 Directives bind Member States to achieve the objectives while leaving the national authorities the power to choose the form and the means for implementing the Directives. Decisions are binding in all their aspects for those to whom they are addressed.2 A decision may be addressed to any or all Member States, to undertakings or to individuals. Recommendations are not legally binding. Community legislation is published in the Official Journal of the European Communities in all official languages of the EC. Guidance documents do not intend to produce legally binding effects and by their nature do not prejudice any measure taken by a Member State within its implementation of Directives. Details of the legal background are described, for example, by Wirsing et al.2

2.2 Council Directive 91/414/EEC Until 1991, all Member States of the EC applied their own registration regime for plant protection products and operated independently with very little collaboration

Assessment of residue analytical methods for crops, food, feed, and environmental samples

between the countries in most cases. These individual regimes were considered to constitute a barrier to trade in plant protection products and agricultural produce within the internal market of the EC. In order to set up a harmonized framework for the regulation of plant protection products in the EC, Council Directive 91/414/EEC of 15 July 1991 concerning the placing of plant protection products on the market was adopted and implemented in all Member States. Six annexes were established within this Directive, providing the basis for the harmonization of registration procedures and regulatory decisions (Table 1). Through the adoption of Directive 91/414/EEC, a decision-making regime for determining the acceptability of a.i., which are denoted as active substances (a.s.) in the EU’s legislation, was established. Authorization of plant protection products was still to be undertaken at national level by the individual Member States. A national authorization may be granted providing that the a.i. has been included in the ‘positive Community list’ of a.i. (Annex I to the Directive), and the ‘uniform principles’ for evaluation are applied, as defined in Annex VI to the Directive. Annex I inclusion of an a.i. is the result of a harmonized evaluation and decisionmaking procedure, performed on the basis of harmonized data requirements, as detailed in Annexes II and III to the Directive. These annexes set out the requirements for the dossier to be submitted by applicants either for inclusion of an a.i. in Annex I or for authorization of a plant protection product. Active ingredients are listed in Annex I if their use and their residues, resulting from applications consistent with good plant protection practice [or Good Agricultural Practice (GAP)] do not have harmful effects on human and animal health, or on ground water or any unacceptable influence on the environment (Article 5 of the Directive). In order to take account of developments in science and technology, the inclusion of an a.i. in Annex I is limited to a period not exceeding 10 years to ensure that the inclusion is regularly reviewed to meet modern safety standards. Furthermore, Annex I listing is the prerequisite for the mutual recognition of authorizations between Member States, whereby one Member State is obliged to accept the evaluation and authorization prepared by another Member State in situations where the agricultural, plant health, and environmental (including climatic) conditions relevant to the use of the plant protection product are comparable in the regions concerned (Article 10 of the Directive).2

2.3 Legislation related to MRLs Pesticide residue levels in foodstuffs are generally regulated in order to:

r minimize the exposure of consumers to the harmful or unnecessary intake of pesticides

r allow control over the use of plant protection products r permit the free circulation of products treated with pesticides as long as they comply with the established MRL. The MRL for pesticide residues is the maximum concentration of a pesticide residue (expressed milligrams per kilogram) legally permitted in or on food commodities and

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16


Table 1 Annexes of Council Directive 91/414/EEC of 15 July 1991 concerning the placing of plant protection products on the market and its implementation (status: published up to February 2002) Annex Annex I

Annex II

Content Active substances autho(a.s.)a rized for incorporation in plant protection products

Requirements for the dossier to be submitted for the inclusion of an active substance in Annex I Part A: Chemical substances Part B: Microorganisms and viruses

Annex III

Annex IV Annex V Annex VI

a

Requirements of the dossier to be submitted for the authorization of a plant protection product Part A: Chemical preparations Part B: Preparations of microorganisms or viruses Risk phrases Safety phrases Uniform principles for the evaluation of plant protection products

Implementation b

New as

Existing asc

Acibenzolar-S-methyl Azimsulfuron Azoxystrobin Cyclanilide Fenhexamid Flupyrsulfuron-methyl Iron(III) phosphate Kresoxim-methyl Paecilomyces Prohexadion-calcium Pymetrozine Pyraflufen-ethyl Spiroxamine

Amitrol Bentazon λ-Cyhalothrin 2,4-D Diquat Fluroxypyr Esfenvalerat Glyphosate Imazail Isoproturon Metsulfuron-methyl Pyridat Thiabendazole Triasulfuron Thifensulfuron-methyl

Part A: Chemicals as

Directive

Efficacy Physical-chemical properties Analytical methods Toxicology and metabolism Residues Fate and behavior in the environment Ecotoxicology Part B: Microorganisms and viruses

93/71/EEC 94/37/EC 96/46/EC 94/79/EC 96/86/EC 95/36/EC 96/12/EC Directive 93/71/EEC 2001/36/EC

In preparation In preparation Directive 97/57/EC

Term for a.i. used in EU legislation. New a.s. are active substances not on the market of EC in protection products before 25 July 1993. c Noninclusion has been decided for the following as after evaluation: azinphos-ethyl, chlozolinate, chlorfenapyr, cyhalothrin, dinoterb, DNOC, fentin-acetate, fentin-hydroxide, fenvalerate, ferbam, lindane, monolinuron, parathion, permethrin, propham, pyrazophos, quintozen, tecnazen, zineb. b


animal feed. MRLs are based on GAP. These should reflect minimum quantities of pesticide necessary to achieve adequate pest control, applied in such a manner that the residues are as low as practicable. MRLs are also established at or about the limit of determination where there are no approved uses or where no residues occur when the pesticide is used according to GAP. MRLs are not toxicological limits but must be toxicologically acceptable. Exceeding the MRL is a violation of GAP. Legislation at Community level dates back to November 1976 when Council Directive 76/895/EEC3 established MRLs for 43 active substances in fruits and vegetables. These MRLs were based on the best data available at that time. These MRLs are gradually being reviewed and, where appropriate, replaced with MRLs based on more current information and higher standards. Current pesticide MRL legislation is derived from/based on four Council Directives:

r Council Directive 76/895/EEC3 establishing MRLs for fruits and vegetables r Council Directive 86/362/EEC 4 establishing MRLs for cereals and cereal products r Council Directive 86/363/EEC5 establishing MRLs for products of animal origin r Council Directive 90/642/EEC6 establishing MRLs for products of plant origin, including fruits and vegetables.

Legislation for pesticide residues, including the setting of MRLs in food commodities, is a shared responsibility between the Commission and the Member States. To date, Community MRLs have been established for about 130 pesticide a.i. For pesticides and commodities where no Community MRL exists, the situation is not harmonized and the Member States may set MRLs at national levels to protect the health of its citizens. Where nonharmonized national MRLs exist, there is always a possibility of trade disputes. Until 1997, MRLs were established on raw commodities only. Directive 97/41/EC changed three important aspects of the work:

r it provided a mechanism to set MRLs in processed products and composite foodstuffs, based on the MRLs fixed for raw agricultural products

r it established a conciliation procedure through which cases where national MRLs led to barriers of trade within the Community could be resolved

r it transferred the competence for setting MRLs from the Council of the Member States to the Commission in Brussels. Member States monitor the compliance of foodstuffs with these MRLs regularly. Inspections and monitoring should be carried out in accordance with the provisions of Council Directive 89/397/EEC7 on the official control of foodstuffs, and Council Directive 93/99/EC8 on additional measures concerning the official control of foodstuffs. The MRLs are derived from data from supervised residue trials that are generally carried out in the context of food production. Specific conditions of feed production are not considered. Therefore, many practical problems for the official control of feed must be solved in future, e.g., application of transfer factors and the calculation of MRLs for mixed feed. Besides national monitoring programs, the participation of each Member State in an EU-coordinated monitoring program is recommended. These monitoring programs

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18


have existed since 1996, and are intended to provide an accurate dietary pesticide exposure throughout the EU and Norway. They will have covered all major pesticide– commodity combinations by the end of 2003. The choice of commodities includes the major components of the Standard European Diet of the World Health Organization. In recent years, new legislation (Council Directive 99/39/EC) has placed severe restrictions on the use of pesticides in the production of food for infants and young children.

2.4 Legislation related to residues limits for soil, water, and air The natural and socio-economic differences within the EU require the most decisions on the monitoring and enforcement of residues in the environment as well as measures to redress failures at local, regional, and national levels. Therefore, no harmonized limits for pesticides in soil and in air exist. Because of the great importance of drinking water for human health, quality standards for pesticides in water were developed at Community level based on the precautionary principle.9 Toxicological considerations were not taken into account to derive the general limit for pesticides. Within the EU, many water-related Directives have been established over the past years. The most important one for the assessment of analytical methods for plant protection products is Directive 98/83/EC on the quality of water intended for human consumption.10 According to Annex I Part B to the Directive, a general limit of 0.1 µg L−1 applies uniformly to each individual pesticide. The sum of all individual pesticides detected may not exceed 0.5 µg L−1 . Only those pesticides which are likely to be present in a water supply need to be monitored. As a result, analytical methods used for water monitoring purposes must be able to determine pesticide residues at the 0.1 µg L−1 level. As a contrast to the concept of setting MRLs, the concept of a general limit excludes specific considerations on the properties of individual a.i., e.g., toxicity. From an analytical point of view, this concept leads in some cases to inconsistencies regarding naturally occurring insecticides listed by the Commission such as carbon dioxide, rape seed oil, nitrogen, or naturally occurring herbicides like such as iron (II) sulfate and iron (III) sulfate. Moreover, additional specific limits apply to copper compounds (copper: 3 mg L−1 ) and cyanide (50 µg L−1 ). For surface water, there are no legally binding limits except for parathion, HCH, and dieldrin in surface water intended for drinking water preparation (Directive 75/440/EEC). Possibly the establishment of the Water Frame Directive of 22 December 2000 will lead to harmonized quality standards for selected pesticides in surface water. Currently, provisions of Annex VI to Directive 91/414/EEC concerning the acceptable exposure of aquatic nontarget organisms are the basis for calculating guidance limits for assessing analytical methods for surface water.

2.5 Provisions for residue analytical methods The first step to define data requirements and criteria for decision making for residue analytical methods was attempted in Council Directive 94/43/EC, establishing


Annex VI to Directive 91/414/EEC concerning the placing of plant protection products on the market. The section concerning residue analytical methods was not fully finalized when the Directive was first adopted. There were no provisions for methods to determine residues from a.i. and relevant metabolites in soil, water, and air. The criteria for foodstuffs partly proved to be not helpful for the practice of assessment (e.g., with regard to reproducibility, ISO 5725 requires validation in at least eight independent laboratories). Although Directive 94/43/EC was later substituted by Council Directive 97/57/EC of 22 September 1997,11 the provisions for analytical methods remained unchanged. Commission Directive 96/46/EC of 16 July 1996, amending Annex II to the Directive 91/414/EEC, is the basis for the assessment of residue analytical methods for crops, food, feed, and environmental samples.12 Provisions of this Directive cover methods required for post-registration control and monitoring purposes but not data generation methods. Because it is necessary to provide applicants as precisely as possible with details on the required information, the guidance document SANCO/825/00 rev. 6 dated 20 June 2000 (formerly 8064/VI/97 rev. 4, dated 5 December 1998)13 was elaborated by the Commission Services in cooperation with the Member States. Moreover, this document provides guidance to Member States on the interpretation of the provisions of Directive 96/46/EC concerning minimum validation requirements for residue analytical methods. For analytical methods used for generating data required in the field of residue behavior, environmental fate, and other fields, the guidance document SANCO/3029/99 rev. 4 was developed.14 According to guidance document 7109/VI/94 rev. 6, the development and validation of an analytical method for monitoring purposes and post-registration control are not subject to Good Laboratory Practice (GLP) regulation. However, where the method is used to generate data for registration purposes, for example residue data, these studies must be conducted according to GLP.15

Table 2 Relevant legal provisions for residue analysis Document

Year of publication

Directive 85/591/EEC

1985

Directive 89/397/EEC Directive 94/43/EC (Annex VI of 91/414/EEC) Directive 96/46/EC

1989 1994

Guidance document 8064/VI/97

1997

Directive 97/57/EC Recommendation 1999/333/EC (Annex II) Guidance document SANCO/825/00

1997 1999

Guidance document SANCO/3029/99

2000

1996

2000

Scope Analytical methods for food control General principles of food control Uniform principles for national authorizations Data requirements and principles for evaluation Details concerning Directive 96/46/EC Substitutes Directive 94/43/EC Quality control measures for monitoring laboratories Substitutes 8064/VI/97 (LC/MS, LC/MS/MS possible) Details concerning data generation methods

19

20


In addition to data requirements and assessment criteria in the context of Annex I listing and the authorization of plant protection products, there are legislative demands for analytical methods addressed to food control and monitoring laboratories. Council Directive 89/397/EEC lays down general principles to be followed by the official food control. Additional measures are stipulated by Council Directive 93/99/EEC. Criteria which should be tested, as far as possible, are described in Annex I to Council Directive 85/591/EEC of 20 December 1985 concerning the introduction of Community methods and analysis for the monitoring of foodstuffs intended for human consumption.16 Quality control measures are highlighted in guideline 7826/VI/97, which is published as Annex II to the Commission Recommendation 1999/333/EC.17 Relevant legal provisions for residue analysis are summarized in Table 2.

3 Evaluation of the submitted methods 3.1 Institutional background The evaluation of a.i. including the evaluation of the analytical methods is jointly carried out by competent authorities of the Member States and the European Commission. For each a.i., a designated Rapporteur Member State performs the evaluation of the dossier, which is submitted by the applicant and in which all requirements of Annexes II and III to Directive 91/414/EEC must be addressed. The Rapporteur evaluates the data and prepares a draft assessment report (monograph) including a proposal for inclusion or noninclusion in Annex I. The monograph is distributed by the European Commission. Any comments from the Member States and the applicant as well as details of the monograph are discussed in peer review meetings. Issues relating to analytical methods are discussed together with physico-chemical properties in an expert group consisting of about 5–7 alternating scientists named by the Commission as private experts. Their task is to identify problems and to confirm open data requirements. Specific scientific issues may be transferred to the Scientific Committee on Plants. The conclusions of the evaluation of an a.i. are laid down in a Review Report, prepared by the Commission. After consideration by the Standing Committee on Plant Health (since January 2002, the Standing Committee on the Food Chain and Animal Health), a final decision on Annex I inclusion is taken by the European Commission and a Directive is adopted. A detailed description of the whole procedure is given by Wirsing et al.2 Inclusion in Annex I is the prerequisite for the mutual recognition of authorizations between Member States. At the time Directive 91/414/EEC was adopted in 1991, there were over 800 a.i. authorized for use in the Member States. The goal was to evaluate these at Community level within 12 years. However, the resources necessary to carry out this exercise were not fully recognized when the legislation was adopted. Moreover, time-consuming decision procedures delay the review process. Up to February 2002, 15 existing a.i. and 13 new a.i. were listed in Annex I, whereas 19 a.i. were rejected (see also Table 1). There is clearly a lack of mutual recognition between Member States. In addition to the evaluation at Community level, Member States have to evaluate the data submitted by applicants, because the authorization of plant protection products


is the responsibility of the individual Member State. It is not possible to apply for authorization at Community level. Therefore, every Member State has established a Competent Authority which may grant authorization (Table 3). For this reason, there are various procedures of data evaluation at Member State level under national legislation and with different institutional backgrounds. Details of the 15 different procedures applied in the Member States cannot be discussed in this article.

3.2 Validation parameters Validation may mean different things to different people, depending on the context and the application of analytical science. For food control and monitoring purposes, it is generally expected that validation includes the establishment of performance characteristics and evidence that the method fits the respective purpose.18 Analytical methods submitted by applicants are evaluated using harmonized criteria (see Section 2.5). The following presentation provides a brief overview of the validation parameters used in the registration of plant protection products and their a.i. These parameters are as follows:

r Trueness

r

r

r

There are various approaches to determine the trueness of methods.19 The most common is the performance of recovery experiments. According to the guidance document SANCO/825/00,13 the mean recovery should be in the range of 70–110%. In justified cases, recoveries outside this range can be acceptable. Repeatability Repeatability is defined as precision under conditions where independent test results are obtained with the same method on identical test material in the same laboratory by the same operator using the same equipment within short intervals of time. The replicate analytical portion for testing can be prepared from a common field sample containing incurred residues. This approach is used extremely rarely. Normally, repeatability is estimated by the relative standard deviation of recoveries, which should be lower than 20% per commodity and fortification levels according to SANCO/825/00. In justified cases, higher variability can be accepted. Reproducibility Reproducibility in the context of Directive 96/46/EC is defined as a validation of the repeatability of recovery, from representative matrices at representative levels, by at least one laboratory, which is independent of the laboratory which initially validated the study. This independent laboratory may be within the same company, but may not be involved in the development of the method. This concept of independent laboratory validation (ILV) substitutes the conduct of interlaboratory trials (e.g., according to ISO 5725) because the resources are not available taking into consideration the high number of a.i., matrix types and concentration levels which must be validated in the registration procedure. Specificity Specificity is defined in Directive 96/46/EC as the ability of a method to distinguish between the analyte being measured and other substances. According to SANCO/825/00, blank values must be reported using representative matrices. They

21

22

Regulatory and scientific consideration for residue analytical methods Table 3 Competent authorities for the authorization of plant protection products (status: August 2001) Authority

Address

Bundesamt und Forschungszentrum für Landwirtschaft Institut für Pflanzenschutzmittelprüfung Ministère des Classes Moyennes et de l’Agriculture Inspection Générale des Matières Premières et Produits Transformés

Spargelfeldstraße 191, 1226 Vienna, Austria WTC 3, 8e e´ tage, Boulevard Simon Bolivar 30, 1000 Brussels, Belgium Messeweg 11/12, 38104 Braunschweig, Germany

Biologische Bundesanstalt für Land- und Forstwirtschaft Abteilung für Pflanzenschutzmittel und Anwendungstechnik (BBA) Miljoestyrelsen

Ministerio de Agricultura Pesca y Alimentación Subdirección General de Medios de Producción Agricola Ministère de l’Agriculture Protection des Végétaux Plant Production Inspection Centre Pesticide Division Ministry of Agriculture Directorate of Plant Produce Protection Department of Pesticides Ministero della Sanità Dipartimento per l’Igiene degli Alimenti e della Sanità Pubblica Veterinaria Pesticide Control Service Abbotstown Laboratory Complex Administration des Services Techniques de l’Agriculture

College voor de Toelating van de Bestrijdingsmiddelen

Centro Nacional de Proteccao da Producao Agricola Kemikalie Inspektionen

Pesticides Safety Directorate Mallard House, King’s Pool

Strandgade 29, 1401 Copenhagen, Denmark Velazuez 147, 28002 Madrid, Spain 251 rue de Vaugirard, 75732 Paris Cedex 15, France Vilhonvuorenkatu 11 C, V Floor, 00500 Helsinki, Finland Hippokratus Str. 3–5, 10164 Athens, Greece Piazza Marconi 25, 00144 Rome, Italy Abbotstown, Castleknock, Dublin 15, Ireland 16 route d’Esch, BP 1904, 1019 Luxembourg, Luxembourg Stadsbrink 5, 6700 AA Wageningen, The Netherlands Quinta do Marques, 2780 Oeiras, Portugal PO Box 13 84, 17127 Solna, Sweden 3 Peasholme Green, York Y01 7PX, UK


r

r

should not be higher than 30% of the limit of determination. Moreover, confirmation techniques must be presented in order to avoid false positive results. Limits of determination The limit of determination [or limit of quantitation (LOQ)] is defined in Directive 96/46/EC as the lowest concentration tested at which an acceptable mean recovery (normally 70–110%) and acceptable relative standard deviation (normally 100 are used for identification/quantitation. The rationale for the selection of the ions monitored should also be provided. When a confirmatory method/technique is required to demonstrate specificity, the properties of the analyte should be considered when deciding on an appropriate method/technique. In SANCO/825/00 acceptable confirmatory techniques are specified as follows:

r HPLC/DAD, if the UV spectrum is characteristic; in this case a UV spectrum obtained under the conditions of determination must be submitted

r alternative chromatographic principle (e.g., substitution of HPLC by GC) from the original method

r alternative detection method r derivatization, if it was not the first-choice method r different stationary and/or mobile phase of different selectivities. In addition, variation of partitioning and/or cleanup steps can be useful for confirmation in special cases. The extent of validation of confirmatory techniques is currently under consideration. One approach is that the extent of validation may be smaller than for the enforcement method. In principle, validation in triplicate at the relevant concentration level (LOQ or MRL) is sufficient. In the case where an MRL is set for multiple crops, a single validation in all representative crop groups is sufficient. A confirmatory method for residues in air is not required if a corresponding method was submitted for the other sample matrices. This approach is realized in Germany.30

4.2 Specific requirements 4.2.1 Food of plant and animal origin The enforcement method must be suitable for the determination of all compounds included in the residue definition in order to enable Member States to determine compliance with MRLs. It is not feasible to validate a method for all commodities if a wide range of MRLs are set. Therefore, a concept of crop groups was developed in SANCO/825/00. The following crop groups with representative crops are presented:

r cereals and other dry crops (e.g., barley, wheat, rye) r commodities with high water content (e.g., lettuce, cucumber)

27

28


r commodities with high fat content (e.g., rape seed, linseed, olives) r fruits with high acid content (e.g., lemons, grapefruits). For each group, one representative sample matrix has to be used for method validation. If the intended use is restricted to one of the crop groups, the method must be validated only for this group. On the other hand, the method has to be validated for all groups if the use is intended for a variety of crops that belong to two or more different groups. In addition, specific crops which are difficult to analyze due to matrix interference require individual method validation (e.g., hops, brassica varieties, bulb vegetables, herbs, tea). There is some discussion within the Member States aimed at method validation for all crop groups in every case in order to support the enforcement of MRLs established for other crops. Additionally, detailed lists of the crop groups are under development. For example, it seems to be that almost all fruits can be classified as ‘fruits with high acid content’ (exception: e.g., bananas and certain varieties of apples). Depending on the variation of the analytical method necessary to obtain acceptable results, it may be possible to cover more than one group by validation using one crop. For example, if the validation is performed with lemons and the pH value has no influence on the recovery of the a.i., it may be acceptable to waive the validation using a representative commodity with a higher water content. Validation of the analytical methods for food of animal origin has to be performed with milk, egg, meat, and fat. The latter is required only if log PO/W is >3 and metabolism studies indicate significant residues in fat, because in this case it is likely that an MRL will be set. Other tissues such as kidney or liver must be validated only if an MRL is set or proposed for these tissues. The issue of the general necessity of analytical methods for food of animal origin is not addressed in Directive 96/46/EC or SANCO/825/00. At this moment, the Working Group ‘Pesticide Residues’ proposes an MRL on a case-by-case basis. However, a pragmatic approach is presented in SANCO/825/00. According to Directive 96/68/EC,31 an analytical method for the determination of residues in food of animal origin is not required when metabolism study in animals is not required. On the other hand, according to Point 6.4 of the Directive, where a feeding study is required, an analytical method for the determination of residues in products of animal origin must be submitted. In other cases, the requirement for an analytical method depends on the establishment of an MRL for food commodities of animal origin. Two additional requirements are specific to the analysis of residues in food. The first requirement depends on the LOQ to be achieved (see Table 5). Table 5 Relation between the maximum residue limit (MRL) and the limit of quantitation (LOQ) MRL (mg kg−1 )

LOQ (mg kg−1 )

>0.1 0.1 0.05 20 m

0.5m buffer

Sampling area

> 71 m

1.5 m

Buffer zone

Sprayed area

2 - 2.5 m

40.5 m

Treated plots

A

B

C

20 19 18 17 16 15 14 13

20 19 18 17 16 15 14 13

12 11 10 9 8 7 6 5 4 3

12 11 10 9 8 7 6 5 4 3

2 1

2 1 > 3.5 m

Figure 4

D

Randomized block design using four replications having 20 sub-plots each

856

Best practices in the generation and analyses of residues in environmental samples

The width of an individual treated replicate should not be wider than 3 m to enable test substance application using a single pass of a conventional plot sprayer. The application is made in the same direction as the layout of the plot. If multiple boom widths are used in treating a single plot, it is critical that areas of potential over-spray and under-spray are avoided during soil sampling. Study designs requiring multiple application passes within a single treated area are not recommended owing to potential issues arising from areas of over- or under-spray. Five soil cores are typically collected from a predetermined subplot within each replication at each sampling period. As mentioned previously, the number of soil cores collected increases with increasing residue variability. The order of subplot sampling is determined using a randomization procedure38 or by random-number subroutines common to many computer spreadsheet programs. The areas between the treated replicates serve as buffer zones and provide access lanes for study personnel and vehicles. Within each row, the subplots are separated by a buffer zone of 0.5 m. An important advantage of the completely randomized block design is that sample collection is distributed across the entire test plot, helping to capture effects of soil spatial variability on agrochemical dissipation. The design presented in Figure 4 is readily adapted to bare-soil and cropped studies. Additional planning and sample numbers are often required when agrochemicals are applied as banded rather than broadcast applications. The soil sampling techniques devised for banded fertilizer applications provide a good basis for the sampling of agrochemical residues.39,40 For example, the recommended approach for sampling fields receiving banded nitrogen fertilizer applications involves the collection of 15– 30 composite cores taken between the banded rows and inter-rows of the field.39 Sampling at multiple positions perpendicular to the application band provides a measure of agrochemical distribution throughout the surface soil. Similarly, determining representative soil sampling locations for agrochemicals applied by chemigation is not a trivial undertaking and requires increased sample numbers to account for increased residue variability.18

2.4.5 Plot markers A field soil dissipation study usually lasts between 1 and 2 years; long-term soil accumulation studies may last for up to 6 years. Hence, it is essential that test plots are clearly marked to ensure accurate sampling for the duration of the study. Durable, highly visible markers (stakes) made of plastic, metal, or wood should be located at the main corners of the treated and control plots. Additional markers indicating replication and subplot number or line number, as appropriate, must also be installed. Weather-proof signs must be installed that clearly indicate the Study Director and contact information, study number, test substance and application rate, and study initiation and termination dates. This information helps to prevent application and sampling errors. Plot markers and signs should be checked regularly to ensure that they are legible and in good physical condition. Permanent markers outside the study area should also be located and used in the event that one or more plot markers are inadvertently moved or lost. One option is to locate a minimum of two permanent reference points outside of the study area

Sampling and analysis of soil

857

Permanent marker

50 to 80 cm

Stake marking individual sub-plot

Post marking individual replicate

50 to 80 cm

Sub-soil marker

Figure 5

Techniques used to mark test plots in field soil dissipation trials

that can be used to re-survey the test area by triangulation (Figure 5). The distances to prominent points such as the ends of sampling plots should be recorded in the study records and indicated on corresponding plot maps. Another option is the use of sub-soil markers that are detected by induction (Figure 5). Because these markers are placed 60–80 cm directly below prominent points in the study area, it is unlikely that they will be moved during the study. The sub-soil markers are especially useful in long-term accumulation studies that involve seasonal plowing or cultivation and when permanent landmarks are not conveniently located near the study area.

858


2.5 Additional considerations 2.5.1 Study documentation Overall study success depends upon the careful documentation of key aspects of study conduct. As mentioned previously, a formal, written study plan (protocol) is required for GLP studies and is highly recommended for non-GLP studies. Other key information to document in the study records includes example calculations involving the application rate, anticipated zero-time concentration, and those associated with the analysis of soil. Additional documentation should include the source, purity, test site location(s), soil textural class, diagrams of test site layout, type and inner diameters of soil corers, sampling depths, pertinent weather parameters, amount and timing of all supplemental irrigation, and the names of all personnel involved with study conduct. The date and time of each application, sample collection, freezer storage, sample extraction, and analysis should all be carefully recorded. Any events that result in deviations from the written protocol must be carefully recorded in the study records and, in the case of GLP studies, the Study Director notified of these events within 24 h of their occurrence. Photographs taken during test substance application and sampling and of the equipment related to these activities are useful in reconstructing key aspects of study conduct. Thorough documentation is as vital for non-GLP research as it is for studies conducted for regulatory purposes. 2.5.2 Safety Equipment used to apply agrochemicals and to collect and process soil is inherently dangerous. The appropriate personal protective equipment must be worn and minimally includes protective eyewear and gloves. Additional protective equipment may include spray suits, respirators, steel-toed boots, and hearing protection, depending on the particular materials being investigated and equipment being used. Large physical force is required to insert a soil probe into the ground; this same force can crush or amputate human limbs. Hence, workers must be well trained in the operation of sampling equipment. Fieldwork also requires physical exertion so caution should be observed when working in high temperature and humidity conditions. Studies involving the application of radiolabeled materials require prior written permission from the appropriate regulatory authorities as well as special provisions for the proper removal and disposal of treated soils and sub-soils.

3 Phase II: field study conduct Each of the five main steps in field conduct (site selection, test plot layout, test substance application, sample collection, and sample storage/handling) is addressed below.

3.1 Test site selection Once the targeted study regions, soil textures, space requirements, and other key aspects of study design have been determined, the search for suitable test sites


859

begins. Test site selection is critical to the success of a field soil dissipation study as field-related factors have a major influence on the overall outcome of the study. Even for bare-soil studies, an ‘agriculturally viable’ soil that would be capable of growing a healthy crop is usually desired. Hence it is important to ascertain the soil’s recent cropping and management history before choosing a particular site. Table 2 lists basic criteria that can be used during field site selection for baresoil and cropped studies. Priority among the selection criteria depends upon the particular goals of the study but certain factors (e.g., slope >1%, excessive rocks, flood prone, potential plot disturbance by wildlife) usually serve to exclude certain sites automatically. If the region of interest is far away, it is best to seek the assistance of university investigators, extension agents, and consultants who are familiar with the regional agricultural practices and local soil and climatic conditions.

Table 2 Site-selection criteria for field soil dissipation studies Selection criterion

Prioritya

Basis for selection

Comments

Region

A or B

Site must match the climatic, soil, and agricultural conditions typical of the target crop

Soil properties

A

Soil texture (sand, silt, clay), organic matter/carbon content, and pH Stones, roots, and hardpans must be largely absent to allow representative sampling of soil profile Soil properties should appear uniform over test site

Site topography

Exclusion

Must have slope ≤1% Site must not be susceptible to flooding Shallow water table or tile drains must not interfere with sampling

Size of test site

B

Depends on study design. The minimum area required for a typical large-plot design is about 0.25 ha

Some crops are grown only in certain regions (e.g., rice) while others are common to many regions (e.g., maize). Thus, selection of a test region may be restrictive or relatively flexible Soil texture data should be available at time of site selection. Soil properties must match study purpose. This can be ‘realistic use’ conditions, ‘realistic worst-case’ or ‘worst-case’ in terms of agrochemical mobility and persistence Must ensure that the majority of samples can be taken from the deepest sampling horizon. Information about sub-soils can be obtained from soil maps, test coring and on-site interviews These are exclusion criteria that have to be carefully determined during on-site inspection Site must be level to prevent losses of agrochemical due to surface run-off and soil erosion Site must not be susceptible to runoff from other areas higher than test site Test site must allow for test design plus sufficient buffer zone around perimeter of field to protect against external disturbance For bare-soil studies, shady sites should be avoided (Continued overleaf )

860


Table 2 —Continued Selection criterion

Prioritya

Basis for selection

Comments

Cropping history and previous pesticide use

Exclusion

The cropping and pesticide history for the previous 3 years must be well documented The test substance must not have been applied to site within the past 3 years

Irrigation

Exclusion

Site must be equipped with sprinkler irrigation

Test site security

A

Access of unauthorized persons, livestock, etc., must be restricted

Plot maintenance

B

Expertise must be available to maintain the test site and, if cropped, to take care of the crop

Ownership

A

Access to test site must be guaranteed for the duration of study

Weather station/ weather data requirements

A

On-site weather station is preferred and may be mandatory for certain studies. Minimally, a station must be located within 10 km of test site

This information is crucial and evidence of careful record keeping reflects favorably upon the future reliability of a field cooperator Prior application of agrochemical forming identical/similar degradation products as test substance should be considered as potential analytical interferences Previous management practices (e.g., soil amendments, tillage, crop type) should have been uniformly applied across test site Irrigation is necessary to ensure 110% of historical rainfall for dryland settings or to follow regional irrigation practices in irrigated cropping settings Potential impact of any nearby construction, utility lines, rights-of-way, etc., must also be assessed For bare-soil studies, the soil surface must be carefully prepared prior to test substance application and kept weed-free without disturbing the test areas. If the test is cropped, the crop should be treated according to Good Agricultural Practice. In case of a soil accumulation study, the field may be cultivated and cropped each season for up to 6 years Owner must agree to grant access to the site for duration of study plus possible time extensions. As a result, sub-leasing of the test site is not preferred. This criterion is extremely important for long-term studies such as field soil accumulation studies In certain cases, a weather station located within 10 km of the test site may be sufficient. If water balances are to be determined, an on-site weather station is necessary to measure, at a minimum, precipitation, solar radiation, wind speed, relative humidity, and air temperature

a ‘Exclusion’ implies that criteria must be fulfilled without compromise since the study may be jeopardized if the criteria are not met; ‘Priority A’ implies some flexibility after careful consideration; ‘Priority B’ factors offer the greatest flexibility in terms of site selection.

3.1.1 Collection of control soil Once test sites have been identified, control soil should be collected and returned to the laboratory. This soil is used to (1) verify soil texture and related properties, (2) ensure adequate analytical recovery of target analytes, and (3) determine the presence of potential background interferences in the soil.


3.1.2 Soil surface preparation Preparation of the soil surface is critical to achieving acceptable results with minimal variability. Surface roughness due to the presence of crop debris or soil clods makes representative sampling nearly impossible. This same material also interferes with sample homogenization. As a result, the importance of proper soil surface preparation for bare-soil studies cannot be overstated. If vegetation exists on the selected site, it must be removed for bare-soil study designs. Vegetation can be removed by application of a nonselective herbicide such as glyphosate, paraquat, or glufosinate followed by mowing, raking, and harrowing once the vegetation has died. A combination of techniques is normally required to smooth the soil properly. For example, disking is usually followed by multiple passes of a rolling-cage cultivator. If necessary, individual subplots can be hand-raked. Sandy soils are the easiest to prepare and dry quickly after rainfall. Silt loam to clay loam soils form clods when worked too wet. Hence timing field preparation around rainfall and soil moisture content is always a factor in preparing test plots. Heavy clay soils containing >40% clay pose real challenges in terms of surface preparation owing to excessive clod formation and surface cracking and should be avoided. When clayey soils are investigated, increased numbers of soil samples should be collected to compensate for the additional variability typically associated with these soils. In addition to being smooth, it is preferable that the soil surface be firmly packed. This is because loose soil is not always retained in large-diameter sampling probes. Firming of the soil surface may be accomplished using a turf roller or equivalent. Alternatively, the soil surface may be prepared in advance of study initiation to allow rainfall or irrigation to settle and firm the soil. This latter approach also allows soil surface depressions to be observed and avoided when laying out the test plots.

3.2 Test substance application Accurate and even application of test substance is absolutely critical to study success. If the application is highly variable or deviates significantly from the target application rate, the study results may be technically unusable and/or unacceptable to regulatory authorities. Accurate agrochemical application begins with careful calibration of the spray equipment. Hence Study Directors should be familiar with sprayer calibration techniques,41,42 even if they will not be personally making the applications. Braverman et al.43 found that factors responsible for inaccurate pesticide applications made for crop residue trials (i.e., application rates applied at >10% or 5 cm with good results under a variety of field conditions. 3.3.2 Minimizing plot disturbance and cross-contamination Great care should be taken while moving in and around the plots so that the sampling areas are not disturbed. The importance of minimizing soil surface disturbance and drag down during sampling is critical as one tries to assess the potential mobility of an agrochemical. This is particularly an issue when one attempts to collect many samples from a relatively small area. In general, the risk of sub-surface contamination is greatly minimized by using zero contamination sampling techniques. To avoid cross-contamination of control samples, untreated controls are collected before the treated samples. Preferably, personnel who handle the upper cores should be different from those handling the lower depth cores. This further reduces potential cross-contamination of lower depth cores. Sampler handlers should change their gloves each time a new subplot is sampled. The use of disposable shoe covers also lessens the possibility of cross-contamination. Once the soil cores have been collected, all boreholes must be backfilled with untreated soil (with frequent tamping) to prevent bypass flow that could transport residues into the lower soil profile. After backfilling, flags or stakes should be placed at the boreholes. This serves as an additional check to ensure that sub-plots are not sampled more than one time during the study. (Note that these boreholes should

865

866


Top Soil Layer 0 - 5 cm

Disassembling of the corer and replacing the cartridge

Sub-soil Layer 5 - 20 cm

Stainless steel retainer sleeve 12-cm (ID)

5 - 20 cm 0 cm 10 cm 20 cm

Step 1

Step 2

Step 3

40 cm

Reassembling of the corer and drilling down to 40 cm

Reassembling of the corer and drilling further down

20 - 40 cm 5 - 20 cm 0 cm 10 cm 20 cm

40 cm

Step 4

Step 5

60 cm

Step 6 80 cm

Figure 7

Alternative zero-contamination sampling method for soil


be periodically checked for subsidence over time and backfilled with soil again, if necessary, to prevent water infiltration.) 3.3.3 Cleaning procedure for soil sampling equipment All sampling equipment coming in contact with treated soil (e.g., sample probes and sectioning equipment) must be thoroughly cleaned between compounds and collection periods. Cleaning is best accomplished by first brushing off any soil adhering to equipment. The next step is washing with pressurized water or soap and water, and finally rinsing with a solvent such as acetone or isopropyl alcohol, alone or in combination with clean water. The use of a solvent will facilitate faster drying of equipment. 3.3.4 Protection of sample integrity All application verification and soil samples must be individually labeled with unique sample identification (ID) and other identifying information such as study ID, test substance name, sample depth, replicate, subplot and date of collection, as appropriate. Proper study documentation requires that sample lists and labels be created prior to work commencing in the field. Water- and tear-resistant labels should be used since standard paper labels may become water-soaked and easily torn during sample handling. Sample lists should have the same information on them as the labels and are a convenient place to record plot randomization, initials of the individual who collected the sample, and date of collection. As such, the sample list is important in establishing chain of custody from the point of sample collection until its arrival at the laboratory. As soon as the sample has been properly labeled and recorded, it should be placed in a generator-powered chest freezer located directly in the field. A flat-bed trailer can be used to transport freezers to and from the field site. Insulated boxes filled with dryice can be used as a substitute for freezers. However, chest freezers typically work better than dry-ice since they allow more cold air circulation around the samples, facilitating more rapid freezing. After the samples have been placed in the freezer, it is critical that they remain frozen until analysis. Electronic temperature data-loggers can be used to monitor conditions during storage. Simpler techniques, such as inverting plastic tubes partially filled with ice or placing plastic bags containing ice cubes, can also be used in combination with a mercury thermometer (any movement of the ice in the inverted tube or melting of the ice cubes indicates that the soil samples may have been subjected to temperatures >0 ◦ C and, hence, sample integrity potentially compromised). Since electronic dataloggers are fairly inexpensive, however, continuous monitoring of freezer storage conditions is strongly recommended. 3.3.5 Zero-time recovery and importance of the soil micro-layer Proper sample collection and handling are the key to acceptable agrochemical recovery at zero time. The zero-time sample interval is defined as the first sample collected after application. Zero-time soil samples should be collected within 3 h after application. Zero-time soil core concentrations, such as those given in Table 3,

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Site location (state)

Nominal soil concentration (mg kg−1 )

(A) Zero-time soil recovery results CA – bare soil 0.25 FL – bare soil 0.25 a b

Calculated soil concentration based on average pass time (mg kg−1 )

Maximum observed concentration on (mg kg−1 )

Day maximum concentration observed (DALA)a

Recovery (%) based on application rate (0.28 kg a.i. ha−1 )

0.281 ± 0.003 0.282 ± 0.003

0.236 0.123

1 0

94 (104)b 49 (53)b

Days after last application. The number in parentheses denotes procedural correction using a 90% recovery for the CA site and a 93% recovery for the FL site. AV – fortified samples: mean concentration (µg)

Site/application no.

Expected fortification (nominal/assessed)

(B) Application verification (AV) monitor results CA – App. 1 420.0/423.8 CA – App. 2 CA – App. 3 CA – App. 4 FL – App. 1 420.0/423.8 FL – App. 2 FL – App. 3 FL – App. 3

AV – spray samples: total a.i. recovered (µg)

Observed fortification

Expected AV – spray

Observed AV – spray

Recovery (%)

419.3 403.4 387.0 413.1 365.4 349.1 385.0 372.3

535 535 535 535 535 535 535 535

529.3 483.2 480.3 507.4 476.2 482.4 501.2 482.2

99 90 90 95 89 90 94 90


Table 3 Summary of zero-time soil concentration and application verification (AV) monitor results for Pyraclostrobin applied at two field sites


are calculated by first subtracting any parent residue present in the core before last application (e.g., −T4) from the parent residue measured immediately after the last application (e.g., T4). For example, at the CA site, the soil concentration of BAS 500 F one day after last application (DALA) was 0.769 mg kg−1 . Prior to application, the soil concentration was 0.533 mg kg−1 . By subtraction, a concentration of 0.236 mg kg−1 was determined for BAS 500 F in the 0–8-cm section. This results in a zero-time soil recovery of 94% [(0.236 mg kg−1 )/(0.25 mg kg−1 ) × 100]. The parent residue concentration used to calculate recovery was the maximum concentration reached at any time during sampling after the last application. Zero-time core recoveries (corrected) ranged from 53 to 104% for the FL and CA sites (Table 3). These data show that even when considerable effort has been expended on proper test substance application (as evident by the excellent pass-time and AV recovery results) and sampling, zero-time recoveries are frequently lower and more variable than desired. Discrepancies between AV monitor and pass-time (or catch-back) results and actual zero-time soil concentrations are most likely due to residue losses occurring during sample handling. Similar discrepancies may also arise for very labile compounds owing to rapid abiotic and/or biotic losses in soil; the presence of degradates in zerotime samples would indicate that low zero-time recovery was due to degradation losses. Immediately after application, all residues, with the exception of those compounds that are soil incorporated, are located in the uppermost layer of the soil core. This thin layer of surface soil is called the soil micro-layer. Loss of soil micro-layer residues is believed to be the main reason for low and/or highly variable zero-time recoveries from soil cores. Initial loss of the soil micro-layer is also believed to be the reason why maximum residue concentrations commonly occur days to weeks after application rather than at time-zero.46 Until these surface residues are redistributed into the core by capillary action, precipitation, or irrigation, they remain subject to loss. Careful handling of the soil samples in the field and laboratory remains especially critical until surface residue redistribution has occurred. Empirical evidence supporting the role of soil micro-layer losses in zero-time issues is given by the often-seen rise in post zero-time residue recoveries. The improved recoveries likely result from the micro-layer residue redistribution that reduces losses of the highly concentrated surface residues. There has been some speculation that zerotime core recoveries may be due to volatilization losses not measured by standard laboratory studies. If this were the case, however, increases in residue concentrations would not occur over time since volatilized residues would be lost to the atmosphere.46 3.3.6 Sectioning of soil cores The upper soil core can be further sectioned into ≥2.5-cm lengths according to study needs and purposes. Sectioning of the upper core can be done in the laboratory but is most efficiently performed immediately after the core has been removed from the soil profile. In-field sectioning begins by using a metal or plastic ‘punch’ having a wide circular surface on one end to push the lower portion (i.e., the end furthest from soil surface) of the core out of the liner to the desired length. Next, a metal cutting tool (e.g., knife or spatula) is used to slice the soil core at the correct length. As the soil is being sliced, it is directed into a pre-labeled sample bag. This process is repeated, working from the lower to upper portion of the core, until all the appropriate sections

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have been sliced away. The sample bags should be rotated in and out of the on-site freezer until all the sectioning depths have been collected from each core within a subplot. This technique works well for all soil textures. Once the lower 15–120-cm cores are completely frozen, they can be further sectioned into 10–15-cm lengths using a hacksaw or band saw. As before, red and black caps are placed on the tops and bottoms of each newly created core section. Each new section also receives a unique sample ID number and new label containing all pertinent sample information. Care must be used when cutting frozen cores to prevent damage to original sample labels. An advantage of the sampling approach shown in Figure 7 is that the soil cores generally require no additional sectioning. 3.3.7 Field-fortification samples In order to determine the dissipation rate and assess the potential mobility of an agrochemical in soil, it is crucial that the residue level measured in a particular sample reflects the actual concentration present in the soil profile at the time of sampling. If this basic assumption cannot be assured, the validity of resulting data may be questioned. Regulatory concerns have arisen over past improper sample-handling practices that might have artificially accelerated agrochemical dissipation in the soil samples. This could occur, for example, whenever samples are exposed to elevated temperatures and/or direct sunlight for extended periods of time prior to freezer storage. As a result, regulatory authorities have requested that a set of fortified samples having a known amount of active ingredient be prepared in the field. These field fortification samples are intended to indicate how well the integrity of the actual field samples was preserved during sample collection, transportation, and storage. If the field-fortified residues are found to be stable, the sample handling conditions are deemed sufficient also to have protected the integrity of the actual field samples. In contrast, if the recovery from the field fortification samples is low, this implies that sample integrity was compromised at some point during study conduct. Although theoretically sound, field fortification samples often generate as many questions as they answer. This is because accurate and precise fortification of soil is difficult to accomplish under field conditions except when the field site is very near the supporting laboratory. For a distant field site, the fortification solution is typically prepared and assayed in the laboratory prior to overnight shipment. If agrochemical recovery from the resulting field fortification samples is low, this may be due to accelerated dissipation, problems associated with the fortification solution itself or improper technique used by field personnel. Shipping fortifying solutions to the field is further complicated by the fact that many active ingredients make only suspensions, not true solutions. Once frozen or left without agitation for extended periods, these formulations are difficult to re-suspend, as is required for proper soil fortification. As a result, acceptable recovery from field spikes helps to address the issue of sample integrity, but poor recovery only results in more questions as to its cause. A solution to this dilemma is to place soil samples immediately in a freezer located in the field, the temperature of which is continuously monitored, as described previously. Laboratory-prepared storage study samples can then be used to determine test substance stability under freezer storage conditions that match those used in the field and during transportation and final storage. If a valid laboratory storage stability


study indicates that residues are stable, any observed decline in soil residues can then be assumed to have occurred in situ. Details on the conduct of a freezer storage study are given in Section 4. 3.3.8 Test plot maintenance The guiding principles in test plot maintenance are to (1) minimize soil surface disturbance at all times, (2) ensure that control and treated plots are similarly maintained, (3) avoid applying other agrochemicals that may interfere with sample analysis or that are otherwise contrary to the purpose of the study, (4) follow the prescribed irrigation policy determined for the study site, and (5) keep bare-soil test plots free of vegetation, as follows. For bare-soil studies, vegetation is controlled on an ‘as-needed basis’ by application of nonselective herbicides (e.g., glyphosate, paraquat, glufosinate) or by careful hand weeding. Vegetation control may be required on a weekly basis during the growing season. The use of glyphosate or paraquat is a widely accepted means of controlling unwanted vegetation in and around test plots, and has the added advantage of controlling weeds without physically disturbing soil surfaces. Because physical disturbance of the soil surface is to be avoided, hoeing or other forms of mechanical removal should not be used in the actual test plots. Vegetation that is pulled by hand should remain on the test plots to avoid inadvertent removal of agrochemical residues. 3.3.9 Irrigation Because soil moisture plays such a critical role in determining agrochemical dissipation rate and mobility, it is important to devise carefully an irrigation plan that clearly specifies the timing and amount of irrigation that is to be added at each study site. One must be able to justify all irrigation applications based upon the relevant agricultural practices in the study region and actual use pattern of the agrochemical. For studies conducted in regions of irrigated agriculture, the plots must be irrigated according to the soil-water budget method. This is determined by calculating the evapotranspiration rate for the target crop (ETc ) and adjusting irrigation amounts to 110% of the ETc : ETc = ET0 × K c Irrigation to apply = ETc × 110%

(4) (5)

where ET0 is the actual daily evapotranspiration rate and K c is the specific crop coefficient based on the targeted crop and appropriate growth stage. Deficiencies should be reconciled about every 10 days, as required. In regions of rain-fed agriculture, the test plots must receive 110% of the monthly historical rainfall. Differences in this total should be reconciled every 10 days. If the plots do not receive 110% of historical monthly rainfall, the study may be severely compromised. Apply the supplemental water inputs via sprinkler irrigation. Do not flood or furrow irrigate since these practices may disturb soil surface residues. Be aware that even

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sprinkler irrigation can cause uneven application of water and, if leaks occur, severe erosion of the soil surface. Therefore, regularly inspect irrigation equipment and function. The control and treated plots must be irrigated in a similar manner. Record the volume and date of all irrigations, the source of irrigation water, and the type of irrigation system used. If water begins to pool or run off of the soil surface, stop irrigating immediately. Resume irrigation only after the risk of runoff is over. To avoid runoff, carefully match the application rate to the soil infiltration rate. Note that, in cold climates, irrigation equipment is winterized to prevent damage from freezing and is generally not available for use during the winter months.

4 Phase III: sample processing and analysis Once soil samples have been received and properly logged in by the laboratory, there is a multi-step process required to isolate agrochemical residues from the sample matrix so that sensitive, reproducible analysis can occur. Residue methods for agrochemicals in soil involve the basic steps shown in Figure 8.

Homogenization

Extraction

Cleanup

Derivatization

Cleanup

Analyte Quantitation*

*HPLC-UV, GC-ECD, GC-MS, LC-MS

Figure 8

Schematic of general analytical method for soil analysis


A general overview of each of these steps is given below. This is followed by a specific example involving an increasingly powerful quantitation technique, liquid chromatography/tandem mass spectrometry (LC/MS/MS).

4.1 Sample homogenization Soil homogenization is the critical first step in the analysis of soil samples. Improper homogenization can lead to variable results that seriously confound the interpretation of soil residue data. Samples are commonly homogenized using equipment called size-reducing mills. Size-reducing mills can be further categorized as being ‘grinder’, ‘rotary blade’, or ‘hammer’ type mills. Each of these has advantages and disadvantages but the ability to mix uniformly the anticipated volume of soil and the ease with which the mill can be cleaned are key considerations when choosing a particular mill. The design of the mill should also prevent the loss of fine soil particles generated during the blending process. Other key aspects of sample homogenization are addressed below. 4.1.1 Protecting sample integrity When processing samples, they should always be milled using dry-ice in amounts sufficient to ensure that the samples remain frozen during homogenization. As discussed previously, protecting sample integrity is of utmost concern throughout every aspect of study conduct. The use of adequate dry-ice also helps keep soil from sticking to the mill. Some mills have been designed to use liquid nitrogen rather than dry-ice for cooling, and also work well with soils. 4.1.2 Minimizing cross-contamination To minimize cross-contamination, soil cores are processed beginning with the lowest depth samples and progressing to the surface samples. It is very important that the mill be thoroughly cleaned between samples so as to minimize the risk of crosscontamination. The machinery should be thoroughly cleaned with water followed by a water–solvent solution such as acetone. Typically, the machine should be cleaned after running one replicate set of samples from the lowest depth to the surface. If the samples have coarse fragments in them, it may be necessary to sieve the samples prior to homogenization. As mentioned previously, soils with a large percentage of clods or rocks should be excluded during the site selection process since they also interfere with sample collection in the field. 4.1.3 Ensuring thorough sample homogenization Before processing actual study samples, and periodically during the course of a study, it is important to test the thoroughness of the homogenization procedure using soils having a range of textures. This is typically done by measuring the analytical variance between sub-samples, and is the only reliable method for determining the effectiveness of a blending technique. Depending on the soil type and sample size, it may be necessary to pass the sample through a mill twice to ensure proper homogenization. For example, experience has shown that when using a rotary-blade type mill, two passes are normally required for proper homogenization of turf or sod samples. When

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Best practices in the generation and analyses of residues in environmental samples Table 4 Tepraloxydim analytical results used to determine efficacy of soil homogenization procedure Residue found (mg kg−1 )

Description Sample weight = 10 g of soil Sample 1 Sample 2 Sample 3 Sample 3, duplicate analysis Sample 4 Sample 4, duplicate analysis

Control Fortified sample, 0.1 mg kg−1 Treated sample, replicate 1 Treated sample, replicate 1 Treated sample, replicate 2 Treated sample, replicate 2

Not detected 0.101 0.120 0.110 0.050 0.057

Sample weight = 5 g of soil Sample 5 Sample 6 Sample 7 Sample 7, duplicate analysis Sample 8 Sample 8, duplicate analysis


Not detected 0.099 0.110 0.180 0.054 0.068

Sample weight = 2 g of soil Sample 9 Sample 10 Sample 11 Sample 11, duplicate analysis Sample 12 Sample 12, duplicate analysis


Not detected 0.102 0.148 0.133 0.059 0.063

turf samples are being processed, it is also essential that the sod plug be totally frozen so that the plug will break up as it passes through the mill. An example of adequate sample homogenization is given in Table 4. The experiment was conducted with two replicate treated soil samples. Each replicate was analyzed in duplicate. Three different sample aliquots (2, 5 and 10 g) were used from each replicate. Analyses of controls and fortified samples were also conducted concurrently with treated samples to evaluate method performance (i.e., extraction recoveries). These results show that residue values are the same regardless of sample size. Thus, thorough homogenization of soil samples coupled with rugged analytical methodology provides for satisfactory residue analysis.

4.2 Sample extraction An efficient and reproducible extraction procedure is mandatory when analyzing agrochemicals in soil. An overview of common soil extraction techniques is given below. 4.2.1 Solvent selection Soil samples are generally extracted with one or more organic solvents mixed with up to 10% (v/v) water. A wide variety of solvents is used for extraction, the choice


of which depends upon the polarity of the compound to be extracted.47 For example, extraction with methanol and methanol–water usually works well for compounds with medium to high polarity. Acetonitrile is another common solvent used in soil extractions. Sometimes pH adjustment is also required for compounds that are acidic or basic in nature (e.g., ammonium carbonate is often added to improve the extractability of weak organic acids). Starch-encapsulated formulations may benefit from an enzymatic pretreatment prior to extraction from soil.48 Several extraction techniques are used in the analysis of soil. The following are brief descriptions of some of the most commonly used techniques. 4.2.2 Mechanical shaker A commonly used extraction technique involves shaking soil with a suitable solvent on a mechanical shaker at about 300 rpm. After extraction, the soil extracts are collected by centrifugation followed by decantation or filtration. This technique could be used for any amount of soil samples (from 10 to >100 g). Soil samples greater than 100 g require efficient agitation to achieve acceptable recoveries. 4.2.3 Soxhlet extraction This technique is used to extract effectively analytes that are polar in nature and strongly bound to soil. Typically, a solvent mixture containing a water-miscible solvent and an apolar solvent (e.g. methanol–dichloromethane) is used. A small aliquot of soil (10–30 g) is dried by mixing with sodium sulfate and refluxed for 8–16 h to extract the residues. 4.2.4 Sonication This technique is used mainly for nonpolar compounds. Typically a small aliquot of soil (10–30 g) is dried by mixing with sodium sulfate prior to extraction. Next, the sample is extracted with a solvent for 10–20 min using a sonicator probe. The choice of solvent depends on the polarity of the parent compound. The ultrasonic power supply converts a 50/60-Hz voltage to high-frequency 20-kHz electric energy that is ultimately converted into mechanical vibrations. The vibrations are intensified by a sonic horn (probe) and thereby disrupt the soil matrix. The residues are released from soil and dissolved in the solvent. 4.2.5 Supercritical fluid extraction (SFE) SFE is used mainly for nonpolar compounds [e.g. polychlorinated biphenyls (PCBs)]. Typically, small aliquots of soil (0.5–10 g) are used for extraction. The extraction solvent is a supercritical fluid, most commonly carbon dioxide, which has properties of both a liquid and gas. The supercritical fluid easily penetrates the small pores of soil and dissolves a variety of nonpolar compounds. Supercritical carbon dioxide extracts compounds from environmental samples at elevated temperature (100–200 ◦ C) and pressure (5000–10 000 psi). High-quality carbon dioxide is required to minimize

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analytical interferences. Compounds with different chemical natures can be selectively extracted by varying the extraction pressure and temperature. The addition of an organic modifier, such as methanol, may improve the recoveries of polar compounds. 4.2.6 Accelerated solvent extraction (ASE) This fully automated process developed by Dionex is used for a variety of compounds having a wide range of polarities.49 Typically, a small aliquot of soil (0.5–20 g) is extracted using a variety of solvents. As with other techniques, the solvent choice depends upon the polarity of the compound to be extracted. The unit extracts soil at elevated temperatures (>60 ◦ C) and pressures (>1000 psi). The increased temperature accelerates the extraction kinetics while the elevated pressure keeps the solvent(s) below the boiling point, thus allowing safe and rapid extraction. Both time and solvent consumption are dramatically reduced compared with mechanical shaking. There are now several published United States Environmental Protection Agency (USEPA) methods that use ASE (e.g., USEPA Method 600/4-81-055, ‘Interim Methods for the Sampling and Analysis of Priority Pollutants in Sediment and Fish Tissue’). 4.2.7 Microwave extraction This is a relatively new technique that is used for PCBs and other nonpolar, volatile and semi-volatile organic compounds. Typically, a small aliquot of soil sample (0.5–20 g) is used for the extraction. Soil samples are extracted with one or more organic solvents using microwave energy at elevated temperature (100–115 ◦ C) and pressure (50–175 psi). This method uses less solvent and takes significantly less time than Soxhlet extraction but is limited to thermally stable compounds.

4.3 Sample cleanup Trace analysis of soil samples often requires post-extraction cleanup to remove coextracted matrix interferences. There are several difficulties that may arise during chromatographic analysis due to interferences present in sample extracts. To avoid these and other issues, one or more of the following cleanup techniques are often used. 4.3.1 Liquid–liquid partition This technique provides a convenient method for separating an agrochemical compound from a highly aqueous extraction mixture. The partitioning solvent is usually a volatile, water-immiscible organic solvent that can be removed by evaporation after the desired component has been extracted. This technique is based on the principle that when a substance is soluble to some extent in two immiscible liquids, it can be transferred from one liquid to another by shaking. The degree of partitioning from one solvent to the other depends on the agrochemical’s distribution coefficient between the immiscible liquids. This technique is particularly useful for the cleanup of ionizable compounds, since the pH of the aqueous solution can be adjusted to maximize partitioning into the organic or water phases, as desired.


4.3.2 Solid-phase extraction (SPE) This technique is based on the same separation mechanisms as found in liquid chromatography (LC). In LC, the solubility and the functional group interaction of sample, sorbent, and solvent are optimized to effect separation. In SPE, these interactions are optimized to effect retention or elution. Polar stationary phases, such as silica gel, Florisil and alumina, retain compounds with polar functional group (e.g., phenols, humic acids, and amines). A nonpolar organic solvent (e.g. hexane, dichloromethane) is used to remove nonpolar inferences where the target analyte is a polar compound. Conversely, the same nonpolar solvent may be used to elute a nonpolar analyte, leaving polar inferences adsorbed on the column. The most common technique used for agrochemicals is reversed-phase SPE. Here, the bonded stationary phase is silica gel derivatized with a long-chain hydrocarbon (e.g. C4 –C18 ) or styrene–divinylbenzene copolymer. This technique operates in the ‘reverse’ of normal-phase chromatography since the mobile phase is polar in nature (e.g., water or aqueous buffers serve as one of the solvents), while the stationary phase has nonpolar properties. Ion-exchange solid-phase extractions are used for ionic compounds. The pH of the extracts is adjusted to ionize the target analytes so that they are preferentially retained by the stationary bonded phase. Selection of the bonded phase depends on the pK a or pK b of the target analytes. Sample cleanup using ion exchange is highly selective and can separate polar ionic compounds that are difficult to extract by the liquid–liquid partition technique. A variety of solid-phase cartridges are available from a number of different manufacturers (e.g. J.T. Baker, Varian). Most cartridges, however, use a similar extraction procedure that consists of these basic steps:

1. Conditioning the column. This step prepares the column to absorb the analytes and also pre-washes the column with the solvents that are used for the cleanup. 2. Sample application. The sample extract is dissolved in the weaker solvent and applied to the top of the column. The analytes of interest are extracted from the crude sample extract and are adsorbed on the column. 3. Wash. Solvents, weaker than the elution solvents, are used to remove interferences selectively. 4. Elution. The compound of interest is selectively eluted with a stronger solvent.

4.4 Derivatization techniques A derivatization technique is commonly applied to an agrochemical with certain reactive functional groups (e.g., carboxylic acid, amine, phenol) to make the compound amenable to either gas chromatography (GC) or LC analysis. An in-depth discussion of derivatization reactions used in the analysis of agrochemicals is beyond the scope of this article. For more information on this topic, the reader is referred to Knapp.50

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4.5 Analytical detection and quantitation techniques The most common final separation techniques used for agrochemicals are GC and LC. A variety of detection methods are used for GC such as electron capture detection (ECD), nitrogen–phosphorus detection (NPD), flame photometric detection (FPD) and mass spectrometry (MS). For LC, typical detection methods are ultraviolet (UV) detection, fluorescence detection or, increasingly, different types of MS. The excellent selectivity and sensitivity of LC/MS/MS instruments results in simplified analytical methodology (e.g., less cleanup, smaller sample weight and smaller aliquots of the extract). As a result, this state-of-the-art technique is becoming the detection method of choice in many residue analytical laboratories. An example of an LC/MS/MS method with an LOQ of 0.01 mg kg−1 is illustrated in Figure 9. This method was used to analyze tepraloxydim and its primary metabolite

O

N

O

CI

O

O

OH

OH O

O

Tepraloxydim

DP-6

Soil (25 g) - Extract with dichloromethane 3 X 50 mL - Centrifuge

Combined dichloromethane extract Marc (discard)

- Evaporate to dryness Dissolve in acetonitrile-water (80:20, v/v) - Dilute with:1 • Acetonitrile-water (1:1) + 0.1% formic acid or • Methanol-water (1:1) + 0.1% formic acid, 4 mM ammonium formate LC/MS/MS determination Analysis for tepraloxydim (m/z 342 to 250) and DP-6 (m/z 253 to 197) in positive ion mode

1

Modifications were used for different soil types.

Method diagram for the determination of tepraloxydim and its degradate, DP-6, in soil (LOQ 0.01 mg kg−1 )

Figure 9


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Table 5 Recoveries of tepraloxyim and degradates from soil dissipation studies conducted in the USA and Canada Recovery range (%)

Mean recovery (%)

Compound fortifieda

North Dakota

Mississippi

California

North Dakota

Mississippi

California

(A) US sites Tepraloxydim

78–119

74–106

86–113

DP-6

69–116

71–102

77–102

96 ± 10 (n = 46) 93 ± 11 (n = 46)

86 ± 7 (n = 44) 92 ± 7 (n = 44)

100 ± 9 (n = 26) 89 ± 7 (n = 26)

Recovery range (%)

Mean recovery (%)

Compound fortifieda

Manitoba

Saskatchewan

Alberta

Manitoba

Saskatchewan

Alberta

(B) Canadian sites Tepraloxydim

77–110

72–121

70–107

DP-6

71–116

74–119

72–118

92 ± 9 (n = 39) 90 ± 10 (n = 39)

90 ± 9 (n = 44) 94 ± 11 (n = 44)

88 ± 8 (n = 43) 94 ± 16 (n = 43)

a

Fortification range for all three sites was 0.01–0.1 mg kg−1 .

DP-6 over 3000 soil samples collected from several terrestrial field dissipation studies. The sample procedural recoveries using this method, conducted concurrently with the treated samples during soil residue analysis, are summarized in Table 5. This method was proven to be short, rugged, sensitive, and suitable for measuring residues in soil and sediment at levels down to 0.01 mg kg−1 . The reproducibility of the methods also indicated acceptable method performance and, as a result, thousands of samples were analyzed using this methodology.

4.6 Freezer storage stability Most agrochemicals remain stable in frozen soil for many months. However, it is important to verify this stability by conducting a freezer storage stability study. One type of study is conducted by fortifying known amounts of test substance and its major transformation products into control soil collected from a participating field site. Fortification normally occurs at two levels: replicate soil samples are fortified at the LOQ and at the highest expected residue concentration for each analyte of interest. The fortified soil samples are stored under the same conditions as the field samples and analyzed at different time periods that bracket the storage time of the actual field samples. The recoveries of the storage samples are compared with those obtained from day zero analyses to obtain the storage stability. In general, the method of analysis is the same as used for the soil residue analysis. A second approach to determining freezer storage stability involves the reanalysis of incurred residues found in actual samples that are stored over time. Using this approach, soil from an actual field sample containing residues is periodically analyzed

880


during the course of the analysis phase of the study. A key advantage of this method is that the stability of actual field-derived residues is being determined. The main drawback is that this approach does not work for degradates that do not form in the field at concentrations at or above their LOQ values.

5 Phase IV: reporting of results Once soil samples have been analyzed and it is certain that the corresponding results reflect the proper depths and time intervals, the selection of a method to calculate dissipation times may begin. Many equations and approaches have been used to help describe dissipation kinetics of organic compounds in soil. Selection of the equation or model is important, but it is equally important to be sure that the selected model is appropriate for the dataset that is being described. To determine if the selected model properly described the data, it is necessary to examine the statistical assumptions for valid regression analysis.

5.1 Goodness of fit testing There are two statistical assumptions made regarding the valid application of mathematical models used to describe data.51 The first assumption is that row and column effects are additive. The first assumption is met by the nature of the study design, since the regression is a series of X , Y pairs distributed through time. The second assumption is that residuals are independent, random variables, and that they are normally distributed about the mean. Based on the literature, the second assumption is typically ignored when researchers apply equations to describe data. Rather, the correlation coefficient (r ) is typically used to determine goodness of fit. However, this approach is not valid for determining whether the function or model properly described the data. In Figure 10, two solutions (models) are shown for the same data set. The first solution is based on a linear fit (Hamaker equation) that provided a high correlation coefficient of 0.93. The second solution (Gustafson–Holden model) is based on a nonlinear solution that provided a high correlation coefficient of 0.98. However, based on an examination of the residuals from both equations, it is evident that the linear model failed to describe properly the data based on the second assumption for valid regression analysis (Figure 11). In other words, the residuals were not randomly distributed; initially they are greater than zero but become increasingly negative as time progresses. In contrast, the residuals from the nonlinear model are equally negative and positive throughout time and it appears, therefore, that the nonlinear model fulfills the second assumption for valid analysis (Figure 12). The second assumption for valid analysis becomes especially important when kinetics are implied based on the fit of the model. However, a kinetic model truly cannot be proven by a fit to data from a field dissipation study.52–54 Therefore, the appropriateness of a model should be determined by its ability to empirically describe the data without implication of mechanism (order).


0.5 Gustafson--Holden (R=0.98) Hamaker (r=0.93)

ln of Concentration (mg kg−1)

0.0

-0.5

-1.0

-1.5

-2.0

-2.5 0

20

40

60

80

100

120

140

160

180

200

Days After Application

Comparison of linear (Hamaker) and nonlinear (Gustafson–Holden) solutions for a typical soil dissipation data set

Figure 10

0.6

Hamaker

0.4

Residuals

0.2

0.0 -0.2 -0.4 -0.6 0

20

40

60

80

100

120

140

160

180

200

Days After Application Figure 11

Residuals plot for the linear model

5.2 Models for agrochemical dissipation in soil Since many equations and analysis procedures have been described in the literature, we present here just a few of the most commonly used equations. The solutions to these equations are obtained using a nonlinear curve fitting routine found in many commercially available statistical programs.

881


0.3

Gustafson--Holden

0.2 0.1

Residuals

882

0.0 -0.1 -0.2 -0.3 -20

0

20

40

60

80

100 120 140

160 180 200

Days After Application Figure 12

Residuals plot for the nonlinear model

5.2.1 Hamaker equation The equation by Hamaker55 is one of the most commonly used methods for describing dissipation kinetics using a linear fit. The basic computational form of the equation is y = a exp(−bX )

(6)

This equation is satisfactory for data sets that are linear when ln of concentration is plotted vs time. 5.2.2 Hamaker equation (power rate form) As mentioned previously, most agrochemicals do not exhibit linear degradation patterns. As a result, Hamaker55 proposed another variation of the linear-fit equation that allows better description of nonlinear data sets: 1

y = a01−n + (n − 1)bX 1−n

(7)

where n = 1; n is the rate order and a and b are solved as unknowns 1 and 2. The disadvantage of this type of approach is that the user is simply choosing a power or ‘order’ that empirically describes the data better than the single exponential form of the equation. 5.2.3 Timme–Frehse–Laska equation In a similar approach to Hamaker, Timme et al.56 proposed six functions that are also empirically based. However, they took the additional step of suggesting that the choice of the equation should be based on the regression correlation coefficient (r ).


However, regression coefficients cannot be used to determine the adequacy of a model choice, as discussed previously. Order 1: y=

log X log b

2 (8)

Order 1.5: y=

2

a √ ( X − 1) b

(9)

Order 2:

a y = (X − 1) b

2 (10)

Similarly to the Hamaker parameters, a and b are solved as unknowns 1 and 2. 5.2.4 Gustafson–Holden equation The Gustafson–Holden equation57 is a unique approach that allows both linear and nonlinear datasets to be solved since it is based on a gamma distribution. The equation is first order and has three unknowns (a, b and c): y = a − b ln(1 + cX )

(11)

This equation requires more data points than the previous equations. 5.2.5 Wolt equation The Wolt equation52 is also a unique approach that is described as being a quasi-firstorder equation. This equation also has three unknowns that are solved (a, b, and c): y = a + b exp(−cX ) + e

(12)

The variable e has been described as an error term, but is not used in most applications of the equation.

5.3 DT50 versus T1/2 values It is important that a clear distinction be made between DT50 and T1/2 values. A DT50 implies that the value describes the time required for 50% of the starting concentration to dissipate or degrade. A T1/2 result implies that the number is derived from a rate constant, which may or may not describe where 50% of the starting concentration has dissipated or degraded. If a logarithm concentration data set is nonlinear with time,

883

884


a rate constant will not accurately describe the data. If the dataset is linear, the rate constant and the DT50 result should be about equal. A rate constant solution describes a data set with the assumption that an equal change in concentration occurs with an equal change in time. The Hamaker equation is an example of one of the most widely used rate constant equations.

5.4 Determining water balance and leaching potential One of the objectives for a field dissipation study is to determine how the leaching behavior of an agrochemical is correlated with water inputs occurring at the field site. In order to answer this question, researchers often overlay water additions on top of graphs displaying residue movement. However, this method often falls short of answering the basic question of whether sufficient water was applied to allow leaching to occur. For example, clay loam soils have on average a 6.4-cm water holding capacity per 30-cm depth. If the water content of the clay soil is approximately at permanent wilt point and a 4-cm irrigation event occurs, the 30-cm depth of soil will not reach field capacity. If the field capacity is never exceeded, no movement of soil solute from the 0- to 30-cm depth would be expected to occur. (These techniques do not address preferential or by-pass flow processes where agrochemicals are transported to subsoils via water following root channels, cracks, etc. Techniques to address preferential flow are not well established at this time.) If three days later an additional 3.2-cm rainfall event occurred, the 0- to 30-cm depth of soil would still not have been brought back to field capacity (assuming 0.7-cm evaporation on the previous two days). For these reasons, it is desirable to perform a series of simple calculations to determine if the field capacity for a given depth of soil is ever exceeded, rather than simply overlaying water inputs over plots of residue data. The following series of calculations addresses the primary issue of whether sufficient water was applied to the test system at appropriate intervals to create leaching opportunities:58 Surface-layer calculation: θ1it+1 =

t+1

[(P + SM + I ) − (Q − ETc )]

(13)

1i

Sub-surface-layer calculation: θ1it+1 =

t+1

(Inf − RFc )

(ETc if θ in an overlying layer = 0)

1i

where t = θ = P = SM =

time in days volumetric water content precipitation snow melt (when snow pack exists and ambient temperature is >0 ◦ C)

(14)


I = irrigation Q = runoff ETc = evapotranspiration corrected for the crop (ETc = ET0 × K c ) or E soil (E soil = ET0 × k) Inf = infiltration RFc = root extraction factor RF = RF × c, c = 1.0 Once performed, these calculation results can be graphed as shown in Figure 13. This type of information provides more insight into the soil water status at a site than simply graphing rainfall. This figure also helps determine if soil water movement occurred out of a given depth of soil. Moreover, it is useful to overlay Figure 13 with a graph of compound movement by depth to determine if the predicted water flux at a given depth corresponds to actual residue movement.

Volumetric Water Content

0.21 0.18 0.15 0.12 0.09 0.06

CA

0-30 cm

0.21 0.18 0.15 0.12 0.09

30-60 cm

0.21 60-90 cm

0.18 0.15 0.12 0.09 0.15

90-120 cm

0.12 0.09 0.06

cm

15.3

Accumulating Flux Past 120 cm

10.2 5.1 0.0 0

Figure 13

50

100

150 Days

200

250

300

Volumetric water contents for Haw series soil calculated using the Penman equation

885


0.21 0.18 0.15 0.12 0.09 0.06

CA

0-30 cm

0.21 Volumetric Water Content

0.18

30-60 cm

0.15 0.12 0.09 0.21 60-90 cm

0.18 0.15 0.12 0.09 0.15

90-120 cm

0.12 0.09 0.06 15.3 cm

886

Accumulating Flux Past 120 cm

10.2 5.1 0.0 0

50

100

150 Days

200

250

300

Comparison of actual volumetric water contents (measured by time domain reflectometry) and calculated soil-water flux values (Penman equation) at four soil depths

Figure 14

More sophisticated methods that actually measure volumetric water content can also be used, such as time domain reflectometry (TDR). In Figure 14, an example of TDR results is presented. Both the calculated and measured (i.e., TDR) volumetric water contents provide a similar picture of the profile water status by depth with time. Proper soil characterization data, such as those shown in Table 6, are necessary for these calculations and improve understanding of the test system. The determination of water-holding capacity (WHC) at 0.03 MPa field capacity (FC) and 1.5 MPa


887

Table 6 Soil characterization results used in water balance calculations and data interpretations Depth increment (cm) Soil characteristic

0–15

15–30

30–45

45–60

60–75

75–90

90–105

105–120

Sand (%) Silt (%) Clay (%) Organic matter (%) Bulk density (g cm−3 ) pH WHCa at 0.33 bar (%) WHC at 15 bar (%) CECb (mequiv. per 100 g soil) Textural classification

85 9 6 2.1 1.33 6.1 9.9 5.1

85 9 6 0.9 1.41 6.1 6.4 3.4

85 9 6 0.3 1.49 7.2 5.4 2.4

83 13 4 0.2 1.46 6.1 4.7 2.0

79 15 6 0.2 1.45 5.9 5.8 2.1

85 9 6 0.1 1.43 6.2 5.8 2.7

85 9 6 0.1 1.45 6.4 5.1 2.1

83 11 6 0.1 1.47 6.2 5.4 2.3

8.1 Loamy sand

5.8 Loamy sand

6.4 Loamy sand

3.5 Loamy sand

2.9 Loamy sand

4.0 Loamy sand

2.9 Loamy sand

3.1 Loamy sand

a b

WHC = water-holding capacity. CEC = cation-exchange capacity.

permanent wilt point (PWP) is important for any type of soil-water calculations or for field sensor measurements. In Table 7, a comparison of actual measurements, and also two well-known pedotransfer functions, can be found by depth. It is important to note that there is a large difference in water content between the disturbed soil core samples and the undisturbed samples. Additionally, the two pedo-transfer functions also exhibit a large difference in predicted water content. Therefore, when doing calculations or trying

Table 7 Measured and estimated volumetric water contents as a function of depth and matrix potential for a Haw series soil (Payette Country, Idaho) Volumetric water content Intact soil core: measured

a b

Pedo-transfer function I: estimateda

Pedo-transfer function II: estimatedb

Intact soil core: measured

Soil matrix potential, 0.03 MPa (field capacity)

Depth (cm) 0–15 15–30 30–45 45–60 60–75 75–90 90–105 105–120

Disturbed soil core: measured

28.60 27.85 35.88 43.68 37.55 39.83 38.23 38.10

33.50 34.90 41.10 43.80 41.10 42.40 40.70 37.10

36.93 31.30 27.82 20.98 21.12 20.58 24.04 27.40

Estimated using the method of Rawls et al.59 Estimated using the method of Bauer and Black.60

27.18 27.18 27.18 26.24 26.71 24.84 24.84 24.84

Disturbed soil core: measured

Pedo-transfer function I: estimated

Pedo-transfer function II: estimated

Soil matrix potential, 1.5 MPa (permanent wilting point) 18.73 19.07 25.17 32.27 30.23 28.30 26.03 26.30

23.40 26.10 26.60 28.50 25.80 23.50 23.50 20.60

19.14 17.72 14.89 7.59 7.62 8.14 13.12 16.70

12.05 12.05 12.04 11.48 11.75 10.68 10.71 10.73

888


to calibrate field sensors, the magnitude of the differences observed in Table 7 must be considered and a compromise should be struck between precision and accuracy.

5.5 Weather data requirements for water balance and mobility assessments If basic calculations such as those presented are to be conducted, it is important to collect enough weather parameters to calculate reference evapotranspiration (ET0 ). An on-site weather station should be considered a basic requirement: minimum sensor requirements to calculate a Penman equation would include solar radiation, wind speed, relative humidity or actual vapor pressure, and air temperature. An on-site rain gauge is essential but it is also a good idea to have a rain gauge on the weather station even if it is not directly on-site. The most accurate variations of the Penman equation calculate ET0 on an hourly basis. However, Penman routines using daily summaries are typically satisfactory for the purpose of calculating soil-water recharge.

6 Summary and conclusions The proper conduct of a field soil dissipation study represents a significant commitment of labor, money, and time. As such, there are many important study details that cannot be left to chance, or addressed as an afterthought, once the study is underway. Each of the four main phases of study conduct, (1) planning and design, (2) field conduct, (3) sample processing and analysis, and (4) data handling and reporting, is vitally linked to the next. Each phase is critical to study success. This article addresses key aspects of study design and conduct necessary for successful study completion. When properly planned and conducted, these studies provide valuable information regarding the environmental persistence and mobility of agrochemicals in field soils.

7 Abbreviations ASE AV ECD GC LC LOQ MS NPD SFE SPE TDR USEPA UV K D , K OC

Accelerated solvent extraction Application verification Electron capture detection Gas chromatography Liquid chromatography Limit of quantitation Mass spectrometry Nitrogen–phosphorus detection Supercritical fluid extraction Solid-phase extraction Time domain reflectometry United States Environmental Protection Agency Ultraviolet Soil sorption coefficients


pK a r R2 Sw

Acid dissociation constant Regression correlation coefficient Regression coefficient of determination Water solubility

References 1. S.K. Singles, R.F. Dietrich, and R.D. McFetridge, ‘Degradation of pyrithiobac sodium in soil in the laboratory and field,’ in “Pesticide Environmental Fate, Bridging the Gap Between Laboratory and Field Studies,” ed. W. Phelps, K. Winton, and W.R. Effland, ACS Symposium Series No. 813, American Chemical Society, Washington, DC, Chapter 15, pp. 207–221 (2002). 2. B. Stenberg, M. Johansson, M. Pell, K. Sjödahl-Svensson, J. Stenström, and L. Torstensson, Soil Biol. Biochem., 30, 393 (1998). 3. S.L. Trabue, T.M. Crowe, and J.H. Massey, ‘Changes in soil biomass and microbial community structure as affected by storage temperature and duration: effect on the degradation of metsulfuron methyl’ in ‘Pesticide Environmental Fate: Bridging the Gap Between Laboratory and Field Studies’, ed. W. Phelps, K. Winton, and W.R. Effland, ACS Symposium Series 813, American Chemical Society, Washington, DC (2002). 4. L.O. Osa-Afiana and M. Alexander, Soil Sci. Soc. Am. J., 46, 285 (1982). 5. J.E. Woodrow, J.S. Seiber, and L.W. Baker, Environ. Sci. Technol., 31, 523 (1997). 6. I.J. van Wesenbeeck, J.M. Zabik, J.D. Wolt, G.A. Bormett, and D.W. Roberts, J. Agric. Food Chem., 45, 3299 (1997). 7. J.M. Zabik, I.J. van Wesenbeeck, A.L. Peacock, L.M. Kennard, and D.W. Roberts, J. Agric. Food Chem., 49, 3284 (2001). 8. H.J. Strek, Pestic. Sci., 53, 52 (1998). 9. R.C. Knox, D.A. Sabatini, and L.W. Canter, ‘Subsurface Transport and Fate Processes,’ Lewis Publishers, Boca Raton, FL, Chapter 6, pp. 268–272 (1993). 10. P.H. Nicholls and A.A. Evans, Pestic. Sci., 33, 319 (1991). 11. S.Z. Cohen, S.M. Creeger, R.F. Carsel, and C.G. Enfield, ‘Potential for pesticide contamination of ground water from agricultural uses,’ in “Treatment and Disposal of Pesticide Wastes,” ed. R.F. Krueger and J.N. Seiber, ACS Symposium Series No. 259, American Chemical Society, Washington, DC, Chapter 18, pp. 318–319 (1984). 12. H.H. Cheng, ‘Pesticides in the Soil Environment: Processes, Impacts and Modeling,’ Soil Science Society of America, Madison, WI (1990). 13. M.A. Locke and C.T. Bryson, Weed Sci., 45, 307 (1997). 14. A.W. Taylor, H.P. Freeman, and W.M. Edwards, J. Agric. Food Chem., 19, 832 (1971). 15. J. Rouchaud, O. Neus, K. Cools, and R. Bulcke, J. Agric. Food Chem., 47, 3872 (1999). 16. X. Jianming, W.C. Koskinen and H.H. Cheng, Pedosphere, 10, 289 (2000). 17. D. Hillel, ‘Environmental Soil Physics,’ Academic Press, New York, Chapters 18 and 19, pp. 507– 587 (1998). 18. A.S. Felsot, R.G. Evans, and J.R. Ruppert, ‘Field studies of imidacloprid distribution following application to soil through a drip irrigation system’, in “Terrestrial Field Dissipation Studies: Design, Interpretation and Purpose,” ed. E.L. Arthur, V.E. Clay, and A. Barefoot, ACS Symposium Series No. 842, American Chemical Society, Washington, DC (2003). 19. W.R. Effland, N.C. Thurman, R. Gangaraju, I. Nicholson, and D. Kroetsch, ‘GIS decision support system to evaluate U.S. and Canada field study areas for agrochemicals,’ in “Pesticide Environmental Fate, Bridging the Gap Between Laboratory and Field Studies,” ed. W. Phelps, K. Winton, and W. R. Effland, ACS Symposium Series No. 813, American Chemical Society, Washington, DC, Chapter 2, pp. 2–21 (2002). 20. R.K. Trubey, R.A. Bethem, and B. Peterson, J. Agric. Food Chem., 46, 2360 (1998). 21. D.L. Suett, Pestic. Sci., 6, 385 (1975). 22. L.E. Bode and M.R. Gebhardt, Weed Sci., 17, 551 (1969).

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23. R.D. Wauchope, J.M. Chandler, and K.E. Savage, Weed Sci., 25, 193 (1977). 24. C.G. McWhorter and O.B. Wooten, Weeds, 9, 42 (1961). 25. C.L. Stiles, C.E. Sams, D.K. Robinson, D.L. Coffey, and T.C. Mueller, J. Agric. Food Chem., 48, 4681 (2000). 26. FIFRA Scientific Advisory Panel Meeting Report, ‘Review of Proposed Revised Guidelines for Conducting Terrestrial Field Dissipation Studies’, SAP Report No. 90-01, United States Environmental Protection Agency, Washington, DC, p. 32 (1998). 27. ‘Pesticide Rejection Rate Analysis – Environmental Fate,’ EPA 738-R-93-010, United States Environmental Protection Agency, Washington, DC (1993). 28. M. Alexander, ‘Biodegradation and Bioremediation,’ second edition, Academic Press, San Diego, Chapter 6, pp. 99–100 (1999). 29. J.H. Massey and J.S. LeNoir, ‘Sources and magnitudes of variability in terrestrial field dissipation of agrochemicals,’ in “Terrestrial Field Dissipation Studies: Design, Interpretation and Purpose,” ed. E.L. Arthur, V.E. Clay, and A. Barefoot, ACS Symposium Series No. 842, American Chemical Society, Washington, DC (2003). 30. A. Walker and P.A. Brown, Crop Protect., 2, 17 (1983). 31. P.S.C. Rao and R.J. Wagenet, Weed Sci., 33 (Suppl. 2), 18 (1985). 32. L.S. Wood, H.D. Scott, D.B. Marx, and T.L. Lavy, J. Environ. Qual., 16, 251 (1987). 33. J.M. Novak, T.B. Mooreman, and C.A. Cambardella, J. Environ. Qual., 26, 1271 (1997). 34. C. Vischetti, M. Businelli, M. Marini, E. Capri, M. Travisan, A.A.M. Del Re, L. Donnarumma, E. Conte, and G. Imbroglini, Pestic. Sci., 50,175 (1997). 35. K.A. Gomez and A.A. Gomez, ‘Statistical Procedures for Agricultural Research,’ second edition Wiley, New York, Chapter 2, pp. 7–83 (1984). 36. M.G. Cline, Soil Sci., 58, 275 (1944). 37. R.G. Petersen and L.D. Calvin, ‘Sampling,’ in “Methods of Soil Analysis, Part I. Physical and Mineralogical Methods,” Agronomy Monograph No. 9, second edition, American Society for Agronomy, Madison, WI, Chapter 2, pp. 33–51 (1986). 38. D.C. Montgomery, ‘Design and Analysis of Experiments,’ second edition, Wiley, New York, Chaper 3, p. 51 (1984). 39. S.A. Clay, D.E. Clay, W.C. Koskinen, and G.L. Malzer, J. Environ. Sci. Health, B27, 125 (1992). 40. D.E. Clay, C.G. Carlson, K. Brix-Davis, J. Oolman, and B. Berg, J. Prod. Agric., 10, 446 (1997). 41. W.P. Anderson, ‘Weed Science Principles’, second edition, West Publishing, St. Paul, MN, Chapter 8, pp. 341–364 (1983). 42. TeeJet, ‘Agricultural Spray Products, Catalog 47,’ Spraying Systems, Wheaton, IL, p. 136 (1998). 43. M.P. Braverman,, J.S. Corley, D.C. Thompson, M. Arsenovic, V.R. Starner, K.S. Samoil, F.P. Salzman, D.L. Kunkel, and J.J. Baron. Proc. Weed Sci. Soc. Am., 41, 17 (2001). 44. A. Nordby and R. Skuterud, Weed Res., 14, 385 (1975). 45. J.H. Massey and S.K. Singles, ‘Photostability of two fungicides on spray application monitors,’ in “Terrestrial Field Dissipation Studies: Design, Interpretation and Purpose,” ed. E.L. Arthur, V.E. Clay, and A. Barefoot, ACS Symposium Series No. 842, American Chemical Society, Washington, DC (2003). 46. D.G. Graham, V. Clay, S.H. Jackson, and R. Jones, ‘Field dissipation studies – The measurement of zero-time residues,’ in “Terrestrial Field Dissipation Studies: Design, Interpretation and Purpose,” ed. E.L. Arthur, V.E. Clay, and A. Barefoot, ACS Symposium Series No. 842, American Chemical Society, Washington, DC (2003). 47. T.H. Dao, T.L. Lavy, and J. Dragun, Residue Rev., 87, 92 (1983). 48. B.J. Weinhold and T.J. Gish, Weed Sci., 39, 423 (1991). 49. B. Richter, J. Ezzell, and D. Felix, ‘Single Laboratory Method Validation Report: Extraction of Organo-phosphorus Agrochemicals, Chlorinated Herbicides and Polychlorinated Biphenyls Using Accelerated Solvent Extraction (ASE) with Analytical Validation by GC/NPD and GC/ECD,’ Document 101124, Dionex Sunnyvale, CA (1994). 50. D.R. Knapp, ‘Handbook of Derivatization Reactions,’ Wiley, New York (1979).


51. G.W. Snedecor and W.G. Cochran, ‘Statistical Methods,’ Iowa State University Press, Ames, IA (1987). 52. J.D. Wolt, ‘Soil Solution Chemistry,’ Wiley, New York (1994). 53. J.D. Wolt, H.P. Nelson, Jr, C.B. Cleveland, and I.J. van Wesenbeeck, Rev. Environ. Contam. Toxicol., 169, 123 (2001). 54. D.L. Sparks, ‘Kinetics of Soil Chemical Processes,’ Academic Press, San Diego (1989). 55. J.W. Hamaker, ‘Decomposition: quantitative aspects,’ in “Organic Chemicals in the Soil Environment”, ed. C.A.I. Goring and J.W. Hamaker, Marcel Dekker, New York, pp. 253–340 (1972). 56. G.H. Timme, H. Freshe, and V. Laska, Pflanzenschutz-Nachr. Bayer, 39, 187 (1986). 57. D.I. Gustafson and L. Holden, Environ. Sci. Technol., 24, 1032 (1990). 58. R.G. Allen, L.S. Pereira, D. Raes, and M. Smith, ‘Crop Evapotranspiration – Guidelines for Computing Crop Water Requirements,’ FAO Irrigation and Drainage Paper 56, Food and Agriculture Organization of the United Nations, Rome (1998). Also available on the World Wide Web: http://www.fao.org/docrep/x0490e/x0490e00.htm. 59. W.J. Rawls, D.L. Brakensiek, and K.E. Saxton, Trans. ASAE, 81, 2510 (1982). 60. A. Bauer and A.L. Black. Soil Sci. Soc. Am. J., 56, 248 (1992).

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Sampling sediment and water in rice paddy fields and adjacent water bodies Hiroki Yamamoto Shimane University, Matsue, Japan

Kouji Nakamura Saitama Prefecture Agriculture and Forestry Research Center, Kuki, Japan

1 Introduction 1.1 Rice production in paddy fields Rice is one of the most important and basic staple foods for about half of the world’s population and provides over 20% of the global calorie intake. World rice production is projected to expand by 1.4% per year to 424 million tonnes by 2005, according to the Food and Agricultural Organization (FAO). In key rice-producing regions in Asia, rice production is performed mostly in paddy fields where crop production has been highly sustainable owing to: 1. avoidance of soil-borne disease so that the production can be repeated every year on the same field, in some cases for more than 1000 years 2. avoidance of soil erosion, enabling fertile surface soil to be conserved 3. substantial additional benefits in flood control and groundwater conservation. The above-mentioned features are consistent with the wider global efforts at sustainable agriculture. With the predicted increase in world population, the production of rice in paddy fields will increase further in importance in producing and maintaining the necessary food supply. Therefore, the importance of plant protection in rice paddies by the use of suitable agrochemicals must be taken into consideration. The potential impact of agrochemicals on the rice paddy environment and adjacent areas presents challenges to agriculture and the regulation of agrochemicals. The application of pesticides to paddy fields represents a unique set of issues compared with many other use patterns. Agrochemicals used in rice production are introduced directly or indirectly into paddy water, and there are more opportunities for

Handbook of Residue Analytical Methods for Agrochemicals. C 2003 John Wiley & Sons Ltd.

Sampling sediment and water in rice paddy fields and adjacent water bodies

paddy water to be released into aquatic bodies in the environment through agricultural drains. Under typical agricultural conditions after an agrochemical application, paddy water is held in the paddy for a period of 5–14 days before release. The length of the water-holding period depends on the type of chemical used and local cultural practices. If the residues of agrochemical are released with paddy water into adjacent water bodies, there would be a potential risk to both aquatic organisms and the quality of drinking water that need to be assessed. Understanding of this transport pathway is of critical importance ecotoxicologically for rice paddy agrochemicals. This involves consideration not only of relevant species living in the water phase but also those living species that spend a major portion of their lifecycle living in and on aquatic sediments. Direct transfer of chemicals from sediments to organisms is now considered to be a major route of exposure for many species. River water is the main source of drinking water in Japan, in contrast to Europe and the USA where groundwater is the main source. In Japan, river water contamination by agrochemicals is an important component in assessing consumer safety via the consumption of drinking water. Government agencies (Ministry of the Environment, Ministry of Agriculture, Forestry and Fisheries, and Ministry of Health, Labor and Welfare) and many chemical companies have carried out water quality monitoring of major rivers in Japan to determine the significance of agrochemicals in sources of drinking water. Water management of paddy fields is very important not only with respect to the cultivation practice of rice but also for the prevention of the contamination of water. Irrigation control after the application of agrochemicals could be the most important approach to avoiding environmental impact. Agrochemicals applied to rice paddy fields could be easily transported to adjacent water bodies compared with those in use on upland areas. Japanese researchers have clarified the relationship between the rate of flow out of paddies and the water solubility of agrochemicals.1,2 Pesticides that have high water solubility have the greatest potential to flow out into adjacent water bodies. In this article, sampling methods for sediments of both paddy field and adjacent water bodies, and also for water from paddy surface and drainage sources, streams, and other bodies, are described. Proper sample processing, residue analysis, and mathematical models of dissipation patterns are also overviewed.

1.2 Regulatory requirements and guidelines Japan has unique regulations regarding environmental fate in the registration of agrochemicals applied in paddy fields. In addition to ordinary environmental fate studies such as biodegradability in soil and hydrolysis and photolysis in water, additional lysimeter studies are required for the registration. Concentrations of agrochemicals in surface water, sediment, and leaching water after the application should be determined during a certain period with more than two model paddies using lysimeters (Figure 1) filled with different types of paddy soil generally distributed in Japan.

893

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100cm

15cm

50cm

Soil layer

20cm 20cm

Sand layer Gravel layer

Drain valve

Concrete

1m x 1m x 1m Figure 1

Structure of a lysimeter for a model paddy study

Drinking water quality should be taken into account from a human toxicological viewpoint because the main source of drinking water is river water. Japanese regulatory procedures allocate 10% of the acceptable daily intake (ADI) in principle to the intake from drinking water. Monitoring studies in the actual fields are not required because Japan has no provisional registration system. Most companies, however, have been voluntarily monitoring their chemicals in river water after distribution. Ecotoxicological data based on Organization for Economic Cooperation and Development (OECD) guidelines are also required, and the endpoints for aquatic organisms, such as fish, daphnia, algae and aquatic plants, are needed for utilization as part of the risk assessment process.

2 Study design 2.1 Study objectives Generally, pesticides applied in rice paddies disperse in sediment and water in the paddy field, and are released into adjacent water bodies through the agricultural drain. The objective of sediment and water sampling is to obtain reliable information about the behavior of pesticides and describe dissipation in the environment. Also, water quality monitoring has great importance for drinking water safety, especially in countries where river water is used as drinking water. The sample collected to obtain information may or may not be representative of the environment. The reliability of data acquired from samples depends on how the sample is selected and collected.


2.2 Preparation of study protocol 2.2.1 Test substances (1) Use pattern information. Information regarding use patterns listed below is essential for the analysis of data:

r active ingredient r formulation r method of application (e.g., paddy water surface, foliar, nursery box) r application rate [including active ingredient(s) contents] r date of application r target crop r history of agrochemical and fertilizer use (2) Physico-chemical properties. Chemical and biochemical degradation pathways and physical mechanisms of removal or disappearance by transport process govern the fate of agrochemicals in the environment. Therefore, the physico-chemical properties of the chemical listed below regarding persistence in sediment or water are important:

r soil adsorption coefficient (K oc ) r water solubility r octanol–water partition coefficient (K ow ) r chemical stability, e.g., photolysis, hydrolysis r aerobic and anaerobic biodegradability 2.2.2 Selection of test sites Field studies in at least two paddies where the sediment has different characteristics of pH, texture and organic carbon contents are required for registration purposes. Since especially clay content and organic carbon content affect the agrochemical behavior in sediments, it is desirable that both systems have widely different characteristics with respect to these two criteria. These paddies should have cultivation history records on type of crop, variety, and agrochemical applications for at least 5 years. When aimed at a single paddy field, the waterway connected with a paddy field serves as a target for a survey. Since a water intake and a drain are installed in each paddy, a major flow of water prevails from the intake to the drain. Hence, starting and ending points should be considered when water sampling is done. For the sampling of water, at least one point in the upstream of the inflow and more than one point in the downstream of the drain should be set. When aimed at a group of paddy fields (an area or a region), sampling points should be set at locations where all the irrigation canals come into the area and all the drainage canals go out from the area. For water sampling from drainage or streams, points near a drain port of a paddy field or an industrial factory, etc., should be avoided in order that water monitoring reflects the concentration of agrochemicals in the entire area rather than a point source.

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2.2.3 Sampling (1) Sampling design. To investigate the behavior of agrochemicals in a paddy field or a group of paddy fields, paddy water and surface sediments of the paddy field and water and sediments of waterways must be collected. In addition, a sediment column is collected and analyzed independently in depth segments to investigate the vertical movement of agrochemicals. All soils and sediments are naturally variable. Their properties change horizontally across the landscape and vertically down the sediment profile. Heterogeneity may occur even in paddy fields where the transplanting of rice seedlings is practiced, although the horizontal variability in the surface layer is usually less than in upland arable lands or paddy fields receiving direct sowing, since the paddling practice in the field reduces the variability to some extent. The times of sample collection for a single paddy survey are set with respect to the application time, such as just before an application, immediately after, and 1, 3, and 7 days post-application, and at longer intervals as appropriate. For an area survey of water and waterway sediments, samples are usually collected periodically over a cultivation season focusing on the application time. The dissipation pattern observed depends mainly on the chemical itself, physicochemical properties of sediment and formulation of the agrochemical because adsorption–desorption processes within the sediment are affected by these factors. The physico-chemical properties of the sediment, especially clay contents and organic carbon contents, affect the partitioning of the chemical to sediment. Degradation by both photolysis and hydrolysis may occur in the water phase. Microbial degradation may occur in both the water and sediment phases. At the initial stage of the dissipation when the concentration of a chemical is high immediately after an application, the distribution of the chemical affects the dissipation pattern. As a matter of course, the physico-chemical properties of the chemical such as adsorption coefficients (K oc ), water solubility, and octanol–water partition coefficients (K ow ) influence the dissipation pattern for the same reason. The formulation of the chemical may affect the dissipation pattern. For example, a dissipation rate of a granule that takes a certain time to dissolve is lower than that of a wettable powder, emulsifiable concentrate, or aqueous solution concentrate. (2) Critical information required at each sampling. The following information must be recorded for an environmental fate study in a paddy field:

r study identification r Study Director/field investigator r testing dates r test location (address-lot number, latitude–longitude) r description of the test plot —soil name —soil map unit name —irrigation and drainage system —landscape as useful accessory information —landform —climate (annual rainfall and temperature)


r basic sampling data

r

—paddy water depth —horizon or depth sampled —sampling date —name of sampler —sampling method (e.g., probe, auger, core) —sampling plan (e.g., random, purposeful) crop (e.g., rice plant, rush)

The position relationship between irrigation canals and drainage canals connected with the paddy(s) and an adjacent river should be described distinctly. 2.2.4 Sediment characterization The physico-chemical characteristics of the sediment sample significantly influence the fate of agrochemicals in a paddy field and a waterway system. Therefore, the factors that influence adsorption, retention, and degradation of agrochemicals are very important. As a minimum the characteristics of the sediment sample listed below should be described:

r pH r texture (clay, silt, and sand proportions) in the United States Department of Agriculture (USDA) classification

r total and organic carbon contents r total nitrogen contents The data listed below are valuable for a more detailed analysis:

r cation-exchange capacity (CEC) r phosphate absorption coefficient (PAC) r microbial biomass r clay mineralogy 2.2.5 Water quality determination It is desirable to determine the chemical properties of irrigation water, paddy water in the field, and adjacent streams and rivers. Since especially the pH of the paddy water fluctuates diurnally (high in daytime and low at night), this may affect the water solubility of certain chemicals, e.g., sulfonylureas, which have dissociation constants (pK a ) in an environmentally relevant range. 2.2.6 Minimum weather data Data on weather conditions, especially temperature and rainfall (temporal distribution and intensity) in the study area are essential for the evaluation of the dissipation data. It is very important to understand the water balance in the paddy field as accurately as possible when calculating the rate of outflow. Records of changes in water temperature and sediment temperature are also helpful for modeling the behavior of a chemical in the rice paddy field.

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2.2.7 Irrigation program Water management practices and the related information listed below should be described:

r date of plowing r date of paddling (paddy preparation) r date of sowing or transplanting r water management

—daily depth of paddy water after the chemical application —flooding period —water holding times —flow rate into and out of the paddy —date of drainage The irrigation method in the period of flooding, e.g., ‘days of holding water in paddy’, could be important information for data interpretation. Water management during the study should be conducted in accordance with the usual local best agricultural practice of rice cultivation except where specific investigation of a parameter requires an alternative. Usually, water is introduced to plowed paddy fields before paddling (Sirokaki in Japanese) for transplanting. Chemicals may be applied before or after transplanting and usually water is retained in the paddy field for 3–7 days after the application to ensure exposure of target organisms to the crop protection product. The loss of water through percolation and evapotranspiration is made up by adding water to the field from irrigation canals or wells. Thereafter, water is allowed to flow into and out of the rice field and the water level is kept at about a depth of 5 cm. After 30–50 days of flooded conditions, the rice field is drained. After about 2 weeks in a drained condition (midseason drainage, Nakabosi), water is reintroduced and maintained at a depth of 5–8 cm for several weeks. Intermittent irrigation and/or surface drainage follow after the deep flooding for the maturing stage (Figure 2).

Harvesting

Maturing

Oct

Fungicide Insecticide

Sep

Heading

Fertilizing

Aug

Fungicide Insecticide

July Active-Tillering

Herbicide

Transplanting

June

Paddling Fertilizing

Plowing

Works

Growing Stage

May

* Japanese in parentheses

Water Management

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Figure 2

Shallow Flooding (Asamizu)* Midseason Drainage (Nakaboshi )

Deep Flooding (Fukamizu)

Intermittent Irrigation (Kandan Kansui ) Surface Drainage (Rakusui )

Typical work system and water management for rice cultivation in paddy fields


3 Study best practices 3.1 Sediment sampling Although it is desirable to collect the sample from as many locations as possible in order to obtain a representative value, the exact number of sampling points can be determined in context with a field size or a waterway width. Sediment samples are collected from more than four locations in a field in order to acquire samples that represent the field. Since there is a water intake and a drain in each paddy, their position should be considered in the sampling design. As shown in Figure 3, sampling points on diagonal lines of the field are recommended avoiding the area within 10 m of a water intake or a drain. In the case of the determination of a chemical in the whole plow layer (usually 25–30-cm depth), approximately 200 g of sediment column up to a 10-cm depth including surface water are collected using a sample borer for each sampling point. If the sampler is a liner installation type, as many liners should be prepared as there are samples and to be used as sample containers. If one uses one sampler for all sampling, the sampler should be washed well and rinsed with distilled water before each sampling. The leading edge of the borer should be kept sharpened with a bevel on the lower outside edge to minimize compaction of the sediment column while the borer is being pressed into the sediment. It is recommended to use a borer of diameter greater than 5 cm to avoid column compaction. The sediment columns are mixed and homogenized and a subsample is taken for laboratory analysis. To investigate the vertical distribution of a chemical for

Recommended sampling points for single paddy study Area within 10 m from an intake or a drain where sampling should be avoided Figure 3

Recommended sampling points for paddy field area study (The number of samples depends on the width of waterway)

Recommended sampling points for a single paddy study and a paddy field area study

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a leaching study, a sediment column up to the desired depth can be collected using a longer borer, then divided into parts with required depth increments. Typically sediment columns are 30 cm in length and are divided into 3–6 segments to allow the investigation of chemical mobility through the sediment profile. Flooded water on the sediment can be removed by decantation or by pushing the soil column upwards with a stick that has the same inner diameter as the borer. In this manner, the compaction ratio should be recorded for a vertical distribution study. The method above, however, is not suitable when one needs a precise study of the vertical distribution of pesticides. Generally, the concentration of pesticides in paddy sediment is highest at the surface. Special care is required to avoid contamination with surface soil when the sediment is collected. The sediment core should be collected in two stages. First, a pipe with a diameter greater than that of the core sampler is inserted in the sediment and then water inside the pipe is removed gently with a syringe, pipet, etc. Next, a layer of surface soil (1–3 cm) is taken with a spatula or a trowel and then subsurface soil is collected with a core sampler to the desired depth; see also Figure 4. It is useful to check for the existence of gravel or stones in the sediment beforehand since these may obstruct the insertion of a sampling borer. Putting a pipe with a length of approximately 30 cm and diameter 20–30 cm into sediment makes it easy to collect surface sediment. It is best to collect sediment with a trowel or a spatula after water inside the pipe has been removed. For sampling sediments of adjacent water bodies, an appropriate sediment sampler such as an Ekman–Birge grab sampler for clay or loamy sediment, or a Smith– McIntyre grab sampler for sandy sediment is effective in deeper streams or rivers. These grab samplers are shown in Figure 5. Sediments in a shallow drainage can be sampled with the same method as in a paddy field. More than three locations around the sampling point decided in advance should be selected based on the width

Insert a pipe at the target position and gently pump out the water inside the pipe.

Take surface sediment with a spatula, then insert a sampling borer to take cores. Figure 4 Method of taking sediment samples in a paddy field minimizing contamination with surface sediment and water


(a)

(b)

(a) Ekman–Birge grab sampler for clay or loamy sediments and (b) Smith–McIntyre grab sampler for sandy sediments are effective in deeper streams or rivers

Figure 5

of the drainage, the velocity of water flow, etc. At each sampling time, three sediment samples are taken at each sampling point. Specific sample locations should be chosen to represent the entire sampling site and should include locations in the major part of the watercourse. Since sediments may be sinks for chemicals adsorbed on soil particles, it may be necessary to analyze sediment deposits separately to determine the significance of sediment-adsorbed chemicals as a source of the chemical in the river or stream.

3.2 Water sampling Surface water samples from a paddy field should also be collected from at least four locations. Sampling points could be chosen by the same method as sediment sampling (Figure 3). At each sampling point, approximately 200 mL of water are collected carefully from a depth of 1–3 cm into a well-washed glass bottle with a glass syringe so that bottom mud and suspended organic debris may not enter. Every bottle of water should be mixed and a subsample taken for laboratory analysis. The required volume for the analysis of water samples from a drainage flow, stream, or river is collected from a depth of up to 50 cm at the center of a flow using an appropriate sampling bottle. A sample size of 1000 mL should be sufficient for the usual type of determination. The sampling bottle and bottles for storage and shipment should be well washed with an appropriate organic solvent and distilled water so that the sample is not contaminated, and keeping those bottles in a clean container is recommended. It is recommended that samples taken are kept below 5 ◦ C and shipped to the laboratory as soon as possible. During sampling, care to avoid floating materials (e.g., litter, oils, etc.) in water is necessary. Also, careful attention should be given to the collection of the water without disturbing sediments in shallow water. If the water sample has high turbidity, it may be necessary to separate suspended solid (SS) from water before the analysis as described later. Chemicals that are hydrophobic and of low water solubility are easy to adsorb on SS.

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3.3 Sample handling and shipment 3.3.1 Prevention of cross-contamination A clean sampler should be used at different sampling points in order to prevent contamination as described earlier. A borer with a liner is recommended to minimize contamination. Using this type of sampling device, only the liner is exchanged. When a borer has to be re-used, it should be thoroughly washed and rinsed with distilled water. Other sampling instruments are dealt with in the same manner. Special care is required to prevent contamination with surface soil when the sediment is collected to study the vertical distribution of a pesticide. The method described earlier (Section 3.1.1) is strongly recommended. The sample water container should be made of appropriate materials to avoid adsorption of the chemical of interest on the vessel surfaces. In most cases, a glass bottle may be better than a plastic bottle. The bottle is washed with an organic solvent in advance and also washed with sample water just before sampling. The bottle should be filled to the limit with water and capped tightly with a Teflon seal to prevent contamination. The top 1-cm of water is not taken to prevent the mixing of floating materials such as oil.

3.3.2 Sample containers, labeling and shipment considerations Sample soil or sediment is put into polyethylene bags or glass containers and sample water into bottles as mentioned above. A label which indicates the sample name, date and time of sampling, sampling point, sampling depth, name of sampler, etc., is attached to the container. Care should be taken that the label does not become wet and the sample information does not disappear during transportation. The general conditions at the sampling point, weather conditions, etc., at the time of the collection should be recorded on the sampling data sheet separately. It is desirable to determine and record the pH, electrical conductivity, etc., of the water at the sampling location, if possible. An important consideration prior to sample collection is transportation and storage. Samples should be treated so as to retain the integrity of the sample from the moment of collection to the time of analysis. The physico-chemical characteristics of a sediment sample change during drying, with effects on the sorption–desorption behavior of chemicals. Standard analytical techniques for sampling and pretreatment and analytical requirements for sediment studies are less available than for water and soil studies. To obtain meaningful results from laboratory experiments, the sediment samples should be kept in the original aqueous matrix, and analyses should be carried out immediately to minimize changes to the sample matrix due to chemical and biological processes that could occur during storage. After removing gravel and large organic debris, the collected sediment is put into a polyethylene bag or suitable container and kept in an ice-cooled container during transportation. Collected water is transferred to a suitable bottle with a tightly sealed cap and also kept in an ice-cooled container. During transportation, cushions are packed between bottles to prevent breakage. It is best to analyze samples as soon as possible


after collection, otherwise they should be frozen at −20 ◦ C until analysis. Care should be taken to prevent breaking of frozen glass bottles filled with water samples. A special plastic bottle (e.g., Teflon) can be used to avoid this, but may be expensive. 3.3.3 Core sectioning techniques To investigate a vertical distribution of a chemical, a sediment column is divided into sections with appropriate thickness. The sediment column taken in a pipe should be refrigerated in an ice-cooled container, transported to the laboratory, and removed carefully on to a clean tray so that there is as little disturbance as possible to the soil core structure. In the case of a column in which there is little soil moisture and it tends to collapse, the soil should be pushed out to each required thickness and carved off. It is also possible to take a sediment column up to a 30-cm depth using a pipe that is connected to cylinders (5-cm height) with sealing tape. In this case, the sample in each 5-cm fraction can be obtained as it is, after removing the tape. 3.3.4 Importance of proper sediment/water preparation Soil or sediment samples for the determination of agrochemicals should not be dried prior to residue analysis, whereas most soil or sediment samples are air-dried prior to analysis for inorganic nutrients such as nitrate, ammonium, metals, etc. Stones, gravel, large organic debris, etc., should be removed as much as possible since these affect the homogeneity of the sample and give rise to analytical errors. After removing large stones, etc., the sample should be passed through a 5-mm (or 2-mm, if possible) sieve using a silicon spatula in order to facilitate the passage of soil through a sieve. Sieves should be cleaned for every sample otherwise contamination may occur during the sieving process. A water sample is usually analyzed as it is, but is filtered through a glass-fiber filter to remove SS or to analyze both water and SS separately when chemicals adsorbed on SS used to be determined for a special purpose of a study. All filtration apparatus should be washed with the sample water in order to avoid contamination. 3.3.5 Sediment moisture determination The water content of a sample is a basic datum for calculating the value per gram of dry matter. Water content is expressed as the ratio of the mass of water present in the sample to the mass of the sample after it has been oven dried at 105 ◦ C to a constant mass. Alternatively, the ratio of the mass of water present in the sample to the mass of the sample before oven drying is used. It is important to specify which is being used. Also, the loss on ignition is preferably determined for a waterway sediment sample because of its high content of immature organic matter. Loss on ignition is determined with a muffle furnace in which organic matter is ignited at 600 ◦ C for more than 2 h. 3.3.6 Extraction and cleanup techniques Extraction and cleanup techniques for soil and water samples are described in other articles, and only comments specific to sediments are included here.

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Organic solvents or mixtures of water and solvents such as acetone or water–acetone are commonly used to extract chemicals from sediment samples as for upland soil. An analysis of sediment, collected from waterways or extremely low Eh paddies, frequently requires the removal of sulfur-containing species, although there is little interference from sulfur if the sediments are in a not very reductive condition. Reduced copper and silver nitrate columns are usually used for the removal, but these procedures are not always successful. Recovery studies could be needed to confirm an interference with sulfur. Subsequently, the determination of chemicals in the extract can be performed according to general analytical procedures that are described in other articles in this Handbook. The concentration of agrochemicals in water samples is usually low compared with soil or crop samples except immediately after the application time. Water sample preparation may include liquid–liquid extraction, solid-phase extraction or direct analysis by reversed-phase high-performance liquid chromatography (HPLC) or liquid chromatography/mass spectrometry (LC/MS). Although there have been many advances in chromatographic analyses, some sample cleanup and concentration steps may be required to obtain the necessary specificity and quantitation limits demanded by regulatory agencies.

3.4 Quality control (QC) and quality assurance (QA) 3.4.1 Method recovery and reproducibility Method validation is needed to demonstrate the acceptability of the analytical method. A recovery test on a chemical being determined should be performed in order to verify the reliability of the series of analyses. Recovery studies are usually conducted by spiking untreated sediment with the target chemical at the detection limit, quantitation limit and in the range of 10–50 times the detection limit. The method is considered acceptable when the recoveries typically are greater than 70%. When the recovery is less than 70%, an improvement in the analytical methods is needed. Where this is not possible for technical reasons, then lower recovery levels may be acceptable provided that method validation has demonstrated that reproducible recoveries are obtained at a lower level of recovery. Analysis is usually done in duplicate or more, and the coefficient of variation (CV) should be less than 10% to ensure that recoveries will be consistently within the range 70–110%. 3.4.2 Techniques used to determine storage stability Analysis should be performed as soon as possible after sample collection. When this is not possible, freeze preservation is recommended. The sample can generally be refrigerated below 5 ◦ C, provided that the storage period is limited to a few days. Some agrochemicals may degrade during such a storage period. In order to verify the degradation of target chemicals during such storage, the stability of the chemical is examined by the addition of a known amount to the sample and storage under identical conditions. This kind of validation study is also performed to investigate the effects of transportation and shipping on stability of the target chemical in samples.


The degradation of agrochemicals during storage may result from a variety of factors such as acidic and alkaline hydrolysis, enzymatic action, etc. It is recommended that a preliminary stability study be performed for the chemical in the environmental sample. If the chemical is stable under acidic conditions, for example, samples can be stored after acidification with hydrochloric or phosphoric acid. 3.4.3 Bound residues in sediment Some agrochemicals bind strongly to the soil component as bound residues, which cannot be extracted without vigorous extraction procedures. In this case, an acidic (e.g., hydrochloric acid, sulfuric acid) or alkaline solution (e.g., sodium hydroxide, potassium hydroxide) can be used as an extraction solvent, and also heating may be effective in improving the extraction of the residues. Analytical procedures after the extraction are the same as above, but a filtration procedure may be troublesome in some of these situations. However, these procedures are rare exceptions or are needed for specific chemicals that are stable under such harsh extraction conditions.

3.5 Data presentation and interpretation The article on soil analysis has an extensive discussion of the kinetics on the dissipation rate. This article includes a recommendation on the data that should be reported. 3.5.1 Data presentation Test chemicals and their use pattern information, physico-chemical properties of sediment samples, water sample quality, study field information, and climatic conditions of the study area are essential as basic information. Data concerning dissipation patterns or distributions of the chemical should be reported as those in the surface water layer, in the sediment layer, and the sum of the two. The concentration should be expressed as micrograms per kilogram for a sediment (SS also if needed) on a dry weight basis, and micrograms per liter for water. 3.5.2 Mathematical models for data interpretation Computer-aided mathematical modeling is a useful tool to supplement monitoring studies and to evaluate the environmental fate of agrochemicals under various conditions. A simulation procedure with a mathematical model using parameters observed in the monitoring study could be helpful for the interpretation of the data obtained in the study. Only a few models applicable to paddy field conditions have been developed. RICEWQ by Williams,3 PADDY by Inao and Kitamura,4 and PCPF-1 by Watanabe and Takagi 5 are useful for paddy fields. EXAMS2 by the United States Environmental Protection Agency (USEPA),6 a surface water model, can also be used to simulate paddy fields with an appropriate model scenario and has been used for the prediction of sulfonylurea herbicide behavior in paddy fields.7 The prediction accuracy of PADDY and PCPF-1 is high, although these models require less parameter

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input than RICEWQ, because these models have been developed as models only for paddy field scenarios. RICEWQ was the first model developed for agrochemical runoff from paddy fields, incorporating aircraft application, dissipation by drift, adhesion on leaf surfaces, and dissipation from the leaf surface in addition to the processes affecting degradation and transport in sediment and paddy water. An important parameter, desorption from sediment to paddy water, is not considered, although this is not as important as other parameters in paddy fields such as sedimentation rate, behavior of SS, etc. PADDY focuses particularly on the granule formulation of agrochemicals in paddy fields. Considering the main processes on the basis of a compartment system, it assesses the behavior of agrochemicals. The mass-balance equations for agrochemicals in the compartments are derived from kinetic data. The main processes are dissolution of agrochemicals from the granules into paddy water, adsorption and desorption with sediment, run-off, leaching, volatilization, and degradations in sediment and water. The uptake process by plants is not considered. PCPF-1 differs greatly from RICEWQ and PADDY in that the sediment layer is divided into an oxidative layer and a reductive layer because the 0–1-cm depth of sediment is oxidative, where most agrochemicals are adsorbed, and below 1 cm it is reductive. Agrochemical degradation can be different in the oxidative and reductive layers of the sediment. The prediction accuracy of agrochemical concentrations is improved sharply by this consideration.

4 Conclusion The objective of sediment and water sampling is to obtain reliable information about the behavior of agrochemicals applied to paddy fields. Errors or variability of results can occur randomly or be due to bias. The two major sources of variability are ‘sediment body or water body variability’ and ‘measurement variability’. For the former, a statistical approach is required; the latter can be divided into sampling variability, handling, shipping and preparation variability, subsampling variability, laboratory analysis variability, and between-batch variability.8 All soil and sediments are naturally variable; their properties change horizontally across the landscape, although this is not as frequent in paddy fields as in upland fields. First, sufficient care should be taken with this point as it is important for sampling procedures. Typically, the error arising from field sampling is much larger than that associated with handling, preparation or analysis. Special consideration is needed for studies of paddy field and adjacent water bodies, where surface water and sediment are at the same place and collected separately. Furthermore, in such fields, surface sediments differ considerably from subsurface sediments in their performance, including adsorption of chemicals and redox potential. Hence surface sediments and subsurface sediments should be collected separately with minimum contamination when the sediment collection is done for the study of the behavior of agrochemicals such as vertical distribution, dissipation pattern, etc. Emphasis on the above points during the selection of sampling location, sampling and analysis should bring effective results.


References 1. S. Maru, Spec. Bull. Chiba Agric. Exp. Stn., No.18 (1991). 2. K. Nakamura, Bull. Saitama Agric. Exp. Stn., No. 46 (1993). 3. M.W. Williams, RICEWQ Users’ Manual and Program Documentation, Version 1.4, Waterborne Environment, Leesburg, VA (1998). 4. K. Inao and Y. Kitamura, Pestic. Sci., 55, 38 (1999). 5. H. Watanabe and K. Takagi, Environ. Sci. Technol., 21, 1379 (2000). 6. L.A. Burns and D.M. Cline, “Exposure Analysis Modeling System: Reference Manual for EXAMS2,” EPA/600/3-85/038, NTIS Publication No. PB85-228138, Environmental Protection Agency, Washington, DC (1985). 7. K.L. Armbrust, Y. Okamaoto, J. Grochulska, and A.C. Barefoot, J. Pestic. Sci., 24, 357 (1999). 8. J. Crépin and R.L. Johnson, ‘Soil sampling for environmental assessment,’ in “Soil Sampling and Methods of Analysis,” ed. M.R. Carter, Lewis Publishers, Boca Raton, FL, pp. 5–18 (1993).

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Monitoring of agrochemical residues in air James E. Woodrow,1 Vincent Hebert,2 and James S. LeNoir3 1

University of Nevada, Reno, NV, USA; Washington State University, Richland, WA, USA; and 3 DuPont Crop Protection, Newark, DE, USA 2

1 Introduction Pesticides are being applied in urban and agricultural settings at a rate of over 2 billion kilograms each year in the USA. Although these materials are applied to specific targets, such as soil, water, or plant foliage, pesticide residues can be unintentionally transported from the target site as a mixture of vapors and aerosols. Once airborne, pesticides may move downwind, where they can affect nontarget organisms such as vegetation, aquatic and terrestrial wildlife, and humans. However, the assessment of nontarget impacts of pesticides requires that pesticide transport from the source region be accurately quantified. Establishing pesticide concentrations in the ambient air, whether in the vapor or aerosol phase, requires proper selection of air samplers, sampling media, suitable field siting strategies, sampling frequencies and sampling durations. This article details various air sampling techniques and field siting strategies for monitoring pesticide residues in local or regional airsheds. Understanding the physical properties of the pesticide (i.e., primarily its vapor pressure) and climatic conditions are key to the selection of an appropriate field sampling and siting strategy. The distributional characteristics of airborne pesticide residues, whether vapor or aerosol, must also be considered when one is faced with the task of extracting these residues from ambient air for subsequent analysis. These characteristics determine the preferred air sampling method and procedures that must be used in the field. Furthermore, the preferred method is selected on its ability to sample, efficiently, enough material to be well above the quantitation limit of the analytical method. The fundamental goal in any air sampling design is to collect enough ambient air and to gather a sufficient number of field samples to address the underlying study objectives, whether local or regional in scope.

Handbook of Residue Analytical Methods for Agrochemicals. C 2003 John Wiley & Sons Ltd.

Monitoring of agrochemical residues in air Table 1 Airborne pesticide characteristics and air sampling methods Pesticide characteristicsa ◦

Vapor (P > 0.1 Pa) Vapor + aerosols (P ◦ ≈ 10−5 –0.1 Pa) Aerosols (P ◦ < 10−5 Pa) a

Appropriate sampling method Adsorbents, canisters, impingers Filters, adsorbents, annular denuder Filters, impactors, cyclone separators

P ◦ = compound saturation vapor pressure.5

2 Sample collection techniques Vapor pressure is singly the most important physical property in determining the air sampling method of choice. The airborne distribution between vapor and aerosol in the ambient air is greatly affected by the compound’s vapor pressure.1 In the discussion that follows, sampling techniques specific to aerosol and vapor forms of pesticides will be described. For example, common methods for trapping vapors utilize adsorbents, canisters, and liquid impingers, whereas trapping aerosols and their associated pesticides may involve the use of filters and inertial samplers, such as impactors (cascade, dichotomous) and cyclone separators. However, it is expected that these specific techniques will, in practice, be used in combination to characterize both aerosols and vapor during an exposure event. For example, aerosol and vapor techniques are often used in tandem, with aerosol removal from the airstream commonly occurring first, followed by vapor removal.2 A reverse arrangement is the annular denuder sampler that removes vapors first, by diffusion, followed by filtration, to recover aerosols, and a final adsorbent vapor trap.3 These sampling configurations are used in recognition of the fact that there is often a distribution between aerosol and vapor for many of the semi-volatile pesticides.4 However, no sampler arrangement can completely differentiate between aerosol and vapor, although many techniques are capable of approaching this ideal, depending on the physico-chemical properties of the analyte. A rule-of-thumb approach using compound vapor pressure can be used to estimate the physical form for airborne pesticides (Table 1).5 Pesticides with vapor pressures greater than about 0.1 Pa will exist primarily as vapor [e.g., fumigants, S-ethyl dipropylthiocarbamate (EPTC)]. Pesticides with vapor pressures in the range 0.00001–0.1 Pa will lead to both vapor and aerosol (e.g., chlorinated hydrocarbons, organophosphates), and pesticides with vapor pressures less than about 0.00001 Pa (e.g., phenoxy herbicide salts, paraquat) will be found primarily in aerosols.

2.1 Chemical vapors 2.1.1 Adsorbents The most common methods for trapping pesticide vapors from air use adsorbents. Common air sampling adsorbents include charcoal (derived from petroleum or coconut) and synthetic polymeric materials, such as cross-linked polystyrene and open-cell polyurethane foam. Charcoal has been used for the cumulative sampling of volatile

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soil fumigants, such as methyl bromide,6−8 methyl isothiocyanate (MITC),9−15 and the halogenated refrigerants.16,17 Charcoal contains various amounts of impurities, including metal oxides, which can successfully chemisorb airborne chemicals, many of which are gases at ambient conditions (e.g., methyl bromide and refrigerants). However, charcoal has limited applicability owing to its propensity for trapping moisture and creating strongly alkaline conditions, which will promote the hydrolysis of some susceptible chemicals (e.g., methyl bromide and MITC).8,14,18,19 Furthermore, trapped moisture also competes with chemicals for active sites, leading to reduced trapping efficiency for many analytes. Moreover, the use of charcoal as an adsorbent is limited to relatively simple chemicals, such as methyl bromide and MITC that can be desorbed intact. More complex chemicals are often irreversibly adsorbed and can undergo chemical conversions due to heterogeneous catalysis. Polymeric materials, on the other hand, do not have these problems because they do not contain the chemically active impurities that make charcoal a relatively strong adsorbent. The trapping ability of polymeric materials is strongly affected by the volatility of the chemical analyte, since the adsorption mechanism does not involve chemisorption, but depends entirely on the weaker van der Waals dispersive and electrostatic forces. Therefore, polymeric adsorbents are limited to use for the cumulative sampling of semi-volatile compounds. A less common variant of the adsorption approach is the use of a solid matrix (e.g., glass beads, polymeric beads) coated with a chemically reactive reagent that will form a derivative with the chemical analyte during sampling. An example is Occupational Safety and Health Administration (OSHA) method 52 for sampling formaldehyde using a polystyrene support coated with 2-(hydroxymethyl)piperidine to form a stable oxazolidine derivative.20 A similar NIOSH Method (Method 2016) uses silica gel coated with 2,4-dinitrophenylhydrazine as the derivatizing reagent to form the hydrazone.21 This approach, however, is used in only a few special cases where derivatizing reagents of rapid reactivity are available and for which air concentrations are relatively high (e.g., ∼20 µg m−3 detection limit for formaldehyde using coated supports).

2.1.2 Canister and bags A sampling technique that is more commonly used in air pollution studies, but is gaining in some use for pesticide vapor sampling, employs evacuated steel canisters22 (Figure 1a). A less costly alternative method uses gas sampling polymeric bags (Figure 1b). Although not suitable for cumulative sampling, canisters can be used for grab sampling through a rapid open–close action of the valve or time-averaged sampling by allowing a slow leak through the valve over a more prolonged period of time. In practice, the sampling valve remains open until the internal pressure of the canister equals the external pressure. For flexible, polymeric bags, two sampling options are available. Positive pressure sampling can be done, where a pump is used to ‘push’ a sample into the bag until it is fully inflated. The other option is to place the bag inside a vacuum chamber and pump down the chamber, allowing the bag to expand, thereby capturing a sample through a port penetrating the wall of the chamber (SKC, Eighty Four, PA, USA). In either case, the sampling rate could be rapid for grab sampling or relatively slow for time-averaged sampling.

Monitoring of agrochemical residues in air Inlet valve

Evacuated steel cylinder

(a) Inlet valve

(b) Figure 1

Tedlar bag

Schematic diagrams of (a) stainless steel air sampling canister and (b) Tedlar bag

A pump (metal bellows) can be used with canisters to meter the air sample through the valve into the evacuated canister and then to increase the internal pressure to a value greater than the external pressure before closing the valve. This feature allows sub-sampling of the canister contents without having to use a pressurization gas that would dilute the contents. Sampling bags, on the other hand, can be simply subjected to an external pressure to force the contents out into an analytical system, or a more sophisticated, computer-controlled autosampler can be used to withdraw fixed volumes of sample from the bags (SKC). Canisters are made of highly polished stainless steel and the interior surface is passivated, usually by electropolishing or by lining with fused silica, to render it essentially chemically inert. Electropolished canisters are commonly used to sample fixed gases (e.g., CO, CO2 ) and nonpolar compounds (e.g., benzene, toluene, xylene). Fused-silica lined canisters can also be used for sampling fixed gases, but they are highly recommended for sampling polar compounds and sulfur-containing compounds which may react with stainless steel. Because of passivation, canisters

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can be used for relatively long-term storage of air samples, depending on the class of compound.23 Gas sampling bags, however, are commonly made of Tedlar, a Teflon copolymer, which can be permeable to some chemicals, which results in changing sample composition over time. While sampling bags provide a cost-effective alternative to canisters, bags are unsuitable for long-term storage for most chemicals,24 so the contents of the bag should be analyzed soon after sampling. Unlike adsorption techniques, canisters/bags do not discriminate with regard to the chemical distribution of the air sample, since the chemical distribution of the canister/ bag sample is essentially the same as for the atmosphere from which the sample was taken. Adsorbent techniques, on the other hand, are designed to trap preferentially one chemical over another. Also, adsorbent techniques often require some post-sampling workup, such as solvent desorption and concentration, that is not required with canister/bag sampling. Furthermore, canister/bag sampling avoids problems related to the interaction of the chemical analyte with the trapping medium, as can occur when charcoal is used to trap chemically sensitive volatile analytes. However, since canister/bag sampling is not a cumulative method, fairly sensitive analytical methods with relatively low detection limits are required for quantitation. In practice, to aid in detection, the entire contents of a canister/bag are often cryofocused before injection into a gas chromatograph (GC) or gas chromatograph/mass spectrometer (GC/MS) system. Additional sensitivity can be gained by operating the GC/MS in the selected-ion mode.

2.1.3 Miscellaneous methods A less commonly employed sampling method makes use of liquid-filled impingers, which are often filled with ethylene or hexylene glycol as the trapping medium. However, the flow rate is limited to 8 µm out

Polystyrene beads 0.05 m3 min−1

0.45 m3 min−1

(a)

0.05 m3 min−1

Inlet nozzle Collection liquid

(b) Figure 4

(a) High-volume dichotomous (virtual) impactor and (b) liquid-filled impinger

3 Trapping efficiency In general, determination of trapping efficiency for an air sampling device involves a comparison of the amount of material trapped with the original amount in the airstream. In practice, for chemical vapors trapped on adsorbents, this often means passing an airstream over a deposit of a known mass of the chemical and then passing the airstream containing volatilized chemical through the trapping medium. For whole air samplers (canisters, bags), the composition of the captured sample is compared with that of the calibration standard from which the sample was taken. For aerosols, dust feeders and nebulizers are commonly used to produce specific sizes of dust or liquid aerosols, respectively, and at known mass output rates. Aerosol sampling devices are then evaluated in terms of their ability to trap a particular size aerosol. The

Monitoring of agrochemical residues in air

following is a more detailed discussion of the determination of trapping efficiency for vapor and aerosol samplers.

3.1 Chemical vapors 3.1.1 Adsorbents For semi-volatile compounds, a common practice is to place a deposit of a known amount of the chemical on a glass surface, flow air of known temperature and flow rate over the deposit, and direct the airstream containing the volatilized chemical through the adsorbent (Figure 5a and b). The adsorbent and original chemical deposits are then extracted with solvent and the chemical residues assayed. Trapping efficiency (%TE) is then calculated using the following expression: %TE = [(mass on adsorbent)/(original deposit − remaining deposit)] × 100

(1)

The adsorbent also needs to be spiked directly with the chemical to determine the recovery from the adsorbent, and this recovery value can be used to adjust the recovery from the adsorbent after air sampling. For compounds with extremely low volatilities, the chemical deposit can be heated to promote volatilization and to minimize the time required for the trapping experiments. The above approach is not entirely suitable for very volatile compounds or for compounds that are gases under ambient conditions. Deposits of very volatile compounds can volatilize quickly under typical air sampling regimes, exposing the adsorbent to unrealistically high vapor densities. Controlled metering of the volatile chemical into the airstream is required. This can be accomplished by the use of permeation tubes, consisting of sealed Teflon FEP tubes containing the volatile compound, for which permeation rates through the polymer have been established for given temperatures (Figure 5c). These tubes allow the establishment of very low concentrations of a volatile chemical in an airstream for the evaluation of an air sampling adsorbent. Already calibrated permeation tubes are available commercially for a number of chemicals or the user can prepare them. These ‘home-made’ permeation devices can be easily calibrated at carefully measured temperatures by weighing the device before and after an air sampling experiment. For compounds that are gases under ambient conditions, controlled metering can be accomplished by tapping into a reservoir (e.g., glass chamber, gas sampling bag) containing a mixture of air and the chemical at predetermined concentrations. The trapping efficiency of polymeric, microporous adsorbents [e.g., polystyrene, polyurethane foam (PUF), Tenax] for compound vapors will be affected by compound vapor density (i.e., equilibrium vapor pressure). The free energy change required in the transition from the vapor state to the condensed state (e.g., on an adsorbent) is known as the adsorption potential (calories per mole), and this potential is proportional to the ratio of saturation to equilibrium vapor pressure. This means that changes in vapor density (equilibrium vapor pressure) for very volatile compounds, or for compounds that are gases under ambient conditions, can have a dramatic effect on the trapping efficiency for polymeric microporous adsorbents.

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Adsorbent (e.g., charcoal, polystyrene, PUF) Primary

(a)

Glass tube containing pesticide deposit

Secondary

1000 L min−1 and are set according to anticipated analytical detectability requirements of the study and to minimize breakthrough. The EPA also provides useful interval sampling guidelines for various airborne pesticide groups when using two-stage glass-fiber filter/PUF assemblies.22 Although only a few samples may be taken on a daily or weekly basis from each sampling site, the total number of samples may be substantial since experimental timeframes may extend over many months. For example, in the comprehensive 2-year national pesticide monitoring program study by Kutz et al.,54 nearly 2500 samples were collected which individually assessed over 40 individual pesticides and reaction by-products per sample. A regional air monitoring sampling scheme is illustrated in Figure 7. This study was conducted in 1995 to determine the ambient concentrations of methyl bromide in the Salinas Valley of Central California.69 The Salinas Valley is a coastal valley approximately 18 miles wide and 47 miles in length, oriented in a NW–SE direction. It is bounded to the east by the Gabilan mountain range and the Sierra de Salinas Mountains to the West. The typical wind pattern is a northwest flow during the day and a southeast flow during the evening. Methyl bromide is predominantly used in strawberry fields in and around the area of Salinas, so in this case Salinas was considered the source of emission. Air samples were collected at 11 sites throughout the valley and surrounding hills. The sampling site located on the coast of Monterey was used as a background site; any concentration of methyl bromide at this site during on-shore breezes would indicate the ocean as a source.


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c Illustration of air sampling station locations (|䉴) in a regional study. Map created with TOPO! 2001 National Geographic Holdings

Figure 7

4.3 QA/QC considerations Data generated by environmental and biomedical studies are required to stand up to scrutiny in a court of law, owing to the growing possibility of litigation. Furthermore, performing an air sampling study using good science may not guarantee the overall quality or constructibility of the generated data. Therefore, investigators now formulate and implement procedures that guarantee the quality and reliability of the project data. Procedures for ensuring the quality of data related to air sampling include (1) calibration of air sampling equipment and analytical instrumentation to attain accuracy, (2) replication to establish precision limits, and (3) determination of the stability of the analytes during sampling, sample workup for analysis, and storage. The air sampler manufacturer, who will also supply certification, often performs calibration of certain kinds of air sampling equipment. Air pumps and blowers will always require calibration when used. This involves the use of flow meters certified for accuracy by the manufacturer. In the same way, analytical instrumentation will

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require periodic calibration during an assay. This is accomplished by the use of pure reference standards of the target analytes prepared at various concentrations of experimental interest to generate multipoint calibration curves that are often repeated. It is recommended that new calibration curves be routinely generated to account for the possibility of instrument ‘drift’ due to ‘aging’ of the analytical column and detector. In addition, ‘spot checks’ should be made every 2–5 samples (i.e., depending on instrument baseline stability) using suitable calibration standards. If reference standards are obtained from commercial sources, suppliers will often certify purity. Otherwise, purity will need to be established using standard analytical techniques (e.g., GC/MS) with documentation. If reference standards are not available and synthesis is required, preparation and purification of the needed reference analyte(s) must be carefully documented. Once the reference standards are at hand, they will need to be properly labeled and stored under conditions that will maintain stability (e.g., in a refrigerator/freezer away from light). Even so, an expiration date should be assigned, but one that is reasonable with regard to the physical and chemical properties of the analyte(s). Pure primary standards, from which secondary dilute standards will be prepared, should be maintained in a freezer and have an assigned expiration date. The secondary standards, which will be used to calibrate the analytical instrumentation and determine analyte stability and recovery, should have assigned expiration dates, but ones that are more current owing to frequent handling. As indicated earlier, background ambient air sampling should be performed at each of the individual sampling stations before a known application event, if possible. Flow controllers (rotameter, electronic flow controller, or critical orifice) should be calibrated in the field against a reference standard prior to a monitoring period. Replication in the field involves taking collocated samples during each sampling period. Assay results for collocated samples will give the precision for sampling under field conditions, and concentrations in air will be the averages of the assay results, with standard deviations reflecting both systematic and random errors. For proper statistics, at least three, and preferably more, collocated samples should be taken during a particular sampling period. 4.3.1 Laboratory, trip and field spikes All fortified (spiked) matrix samples are prepared in the laboratory at the same concentration. Laboratory spikes are immediately put into cold storage. Trip and field spikes are kept cold and sent to the field. The trip spikes will accompany sample shipments. The field spikes are stored and transported in the same manner as the trip spikes. When practical, air should be pulled through field spikes in the same manner as actual field samples being taken at the time of the study. Analyte stability is also of concern during sampling, sample workup, and storage. Stability in the field during sampling can be assessed by using reference standards to spike an air sampler far removed from a specific source or to spike an air sampler at levels well in excess of expected environmental levels. In this way, it is possible to determine if conversion of an analyte under field conditions is an artifact of sampling, a result of environmental conditions and physico-chemical properties, or a combination of all.70 The stability of solvent-extracted laboratory samples during the workup process can be evaluated by simply comparing expected percentage recoveries of


a laboratory-fortified extract against a reference standard of known concentration. Stability during freezer storage can be assessed by including laboratory-spiked matrix samples along with the actual collected field samples. Over the course of time as the field samples are assayed, several freezer spikes can be removed from time to time for assay also, leaving several spikes in the freezer to be assayed after all the field samples have been processed. In this way, it is possible to determine the time course of analyte decline during storage. Freezer blanks, consisting of clean trapping medium, can also be included to assess the stability of the medium during storage and the possibility of the buildup of freezer-related contaminants over time. An exception to the freezer approach involves the use of canisters, which are usually stored at room temperature. It is a general practice, for quality assurance (QA)/quality control (QC) considerations, to assay 10% of the canisters a second time. To assess long-term stability of analytes, sub-sampling of single canisters over a period of months may be required. For all of the QA/QC-related activities just described, thorough documentation is of crucial importance. Standard operating procedures (SOPs) should be prepared well ahead of sampling describing and documenting (1) the calibration and operation of specific sampling equipment, (2) the preparation, storage, shipment, and handling of samples, (3) the calibration and operation of analytical instrumentation, and (4) all aspects of data recording and processing, including computer hardware and software used. The SOPs should include specific stepwise, clearly written instructions and be developed by the laboratory personnel conducting the work. At a minimum, documentation should include field notebooks and logs, equipment/instrumentation operation manuals and maintenance logs, sample chain-of-custody forms, sample receiving and storage/archival forms and logs, sample handling logs, and final reports. All documentation must be dated and signed at the time the documentation is created.

5 Summary Airborne residues of pesticides will occur as vapor and in aerosol form. The distribution between vapor and aerosol will be greatly affected by compound vapor pressure. This property will also be one of the important factors in determining the air sampling method of choice. For those pesticides that are mostly or solely in vapor form, the sampling options available include adsorbents and canisters/bags. The performance of polymeric adsorbents that rely on surface electrostatic potential to trap pesticides will be greatly affected by compound vapor pressure (i.e., adsorption potential). Pesticides with vapor pressures somewhat greater than about 0.1–0.2 Pa will not be efficiently trapped by polymeric adsorbents. In this case, chemisorption on charcoal or inert solid supports coated with derivatizing reagents would be a more reasonable choice. An alternative choice for volatile pesticides would involve the use of canisters/bags. Unlike adsorbents, which are necessarily cumulative, canister/bags do not concentrate the analyte, but instead are ‘whole air’ samplers. However, canisters/ bags can be used for grab sampling and also for time-weighted sampling. For aerosols of nonvolatile pesticides (e.g., paraquat) and aerosols containing pesticides, sampling methods consisting of filtration and employing inertial samplers

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(impactors, cyclones) are available. If there is a chance that pesticides on aerosols can volatilize to some extent, then the aerosol sampler is followed by a vapor trap, usually consisting of a polymeric adsorbent. If the distribution between aerosol and vapor is important, then annular denuders can be used first to trap vapors by diffusion, and then to trap the aerosol by filtration, followed by a vapor trap to collect aerosol-associated residues. For developing suitable localized and regional evaluations, the proper selection of air samplers and sampling media, together with designing suitable siting strategies, sampling frequencies, and sampling durations, will be critical in establishing pesticide concentrations in the ambient air. Considering the distribution of the pesticide among vapor and aerosol phases at equilibrium becomes especially important for regional assessments when developing suitable sampling procedures, whether single-stage adsorbent or multi-stage aerosol–vapor air sampling devices. There still continues to be limited guidance made available to local, State and Federal agencies and other research institutions on field procedures for sampling pesticides from ambient air. This limited guidance is directly associated with the complexity in developing standardized sampling procedures for an array of pesticides with different methods of field application, types of formulation, and diverse physico-chemical properties. As a result, the lack of consistency in sampling methodologies, sampling site placement, collection times, and sampling durations will continue to make comparisons of residue results difficult to interpret. The on-going efforts by the EPA in preparing a compendium of analytical methods for sampling airborne pesticides are commendable.22 The efforts of the California ARB in providing procedural guidelines for localized near-field sampling are also to be commended and should be useful for the construction of verifiable procedures for future local and regional air assessments.42 Owing to increasing local and regional public concern and need for data comparability, greater efforts should continue to be directed at establishing more uniform sampling procedures for pesticides in air. Regardless of the field sampling procedure and air sampling method that one chooses, the overarching concern should always be quality of the data. Assurance of quality can be met by instituting sound and verifiable laboratory practices at the start of any air sampling program. This, for the most part, involves having SOPs in place at the start for all activities (e.g., equipment calibration, sampling, sample handling, assay, storage, stability, etc.) and developing a clear plan of action or protocol. Perhaps the most important practice is to ensure study construction through rigorous documentation that can be verified by an independent quality assurance unit. In combination with the SOPs, protocol, documentation, and verification of all activities will go far to provide defensible data and conclusions of the program and lead to a product that will be able to stand on its own.

References 1. M.S. Majewski and P.D. Capel, in ‘Pesticides in the Atmosphere: Distribution, Trends, and Governing Factors,’ ed. R.J. Gilliol, Vol. 1, ‘Pesticides in the Hydrologic System,’ Ann Arbor Press, Ann Arbor, MI (1995). 2. R.G. Lewis and S.M. Gordon, ‘Sampling for organic chemicals in air,’ in ‘Principles of Environmental Sampling,’ ed. L.H. Keith, American Chemical Society, Washington, DC, Chapt. 23 (1996).


3. A.J. Peters, D.A. Lane, L.A. Gundel, G.L. Northcott, and K.C. Jones, Environ. Sci. Technol., 34, 5001 (2000). 4. T.F. Bidleman, Environ. Sci. Technol., 22, 361 (1988). 5. J.N. Seiber and J.E. Woodrow, ‘Airborne residues and human exposure,’ in “Determination and Assessment of Pesticide Exposure,” ed. M. Siewierski, Studies in Environmental Science 24, Elsevier, New York, pp. 133–146 (1984). 6. J.N. Seiber, J.E. Woodrow, P.S. Honaganahalli, J.S. LeNoir, and K.C. Dowling, ‘Flux, dispersion characteristics, and sinks for airborne methyl bromide downwind of a treated agricultural field,’ in “Fumigants: Environmental Fate, Exposure, and Analysis,” ed. J.N. Seiber, J.A. Knuteson, J.E. Woodrow, N.L. Wolfe, M.V. Yates, and S.R. Yates, ACS Symposium Series No. 652, American Chemical Society, Washington, DC, pp. 154–177 (1997). 7. J.E. Woodrow, P.S. Honaganahalli, and J.N. Seiber, ‘Determination of methyl bromide in air resulting from pest control fumigations,’ in “Fumigants: Environmental Fate, Exposure, and Analysis,” ed. J.N. Seiber, J.A. Knuteson, J.E. Woodrow, N.L. Wolfe, M.V. Yates, and S.R. Yates, ACS Symposium Series No. 652, American Chemical Society, Washington, DC, pp. 189–201 (1997). 8. J.E. Woodrow, J.S. LeNoir, and J.N. Seiber, Chemosphere, 35, 2543 (1997). 9. A. Collina and P. Maini, Bull. Environ. Contam. Toxicol., 22, 400 (1979). 10. L.G. Tuinstra, W.A. Traag, and A.H. Roos, J. High Resolut. Chromatogr. Chromatogr. Communi., 11, 106 (1988). 11. F. van den Berg, Atmos. Environ., Part A, 27, 63 (1993). 12. CDPR, Air Monitoring for Methyl Isothiocyanate During a Sprinkler Application of MetamSodium, Report EH 94-02, California Department of Pesticide Regulation, Sacramento, CA (1994). 13. F. van den Berg, A.H. Roos, L.G.M.T. Tuinstra, and M. Leistra, Water Air Soil Pollut., 78, 247 (1994). 14. J.E. Woodrow, J.S. LeNoir, J.N. Seiber, T. Dinoff, and R.I. Krieger, Determination of MITC in Air Downwind of Fields Treated with Metam Sodium by Drip Irrigation, Final Report to the Metam Sodium Task Force, University of Nevada, Reno, NV and University of California, Riverside, CA (1998). 15. J.N. Seiber, J.E. Woodrow, R.I. Krieger, and T. Dinoff, Determination of Ambient MITC Residues in Indoor and Outdoor Air in Townships near Fields Treated with Metam Sodium, Final Report to the Metam Sodium Task Force, University of Nevada, Reno, NV and University of California, Riverside, CA (1999). 16. NIOSH, ‘Method 1006 (Freon 11),’ in “Manual of Analytical Methods (NMAM),” ed. M.E. Cassinelli and P.F. O’Conner, fourth edition, DHHS (NIOSH) Publication 94-113, Department of Health and Human Services, Washington, DC (1994). 17. OSHA, ‘Method 113 (Freon 141b, Freon 113),’ http://www.osha-sic.gov/dts/sltc/methods/ organic/org113/org113.html (1998). 18. J. Gan, M.A. Anderson, M.V. Yates, W.F. Spencer, and S.R. Yates, J. Agric. Food Chem., 43, 1361 (1995). 19. P.M. Jeffers and N.L. Wolfe, ‘Hydrolysis of methyl bromide, ethyl bromide, chloropicrin, 1,4dichloro-2-butene, and other halogenated hydrocarbons,’ in “Fumigants: Environmental Fate, Exposure, and Analysis,” ed. J.N. Seiber, J.A. Knuteson, J.E. Woodrow, N.L. Wolfe, M.V. Yates, and S.R. Yates, ACS Symposium Series No. 652, American Chemical Society, Washington, DC, pp. 32–41 (1997). 20. OSHA, ‘Method 52 (formaldehyde),’ in Analytical Methods Manual, US Department of Labor, Occupational Safety and Health Administration, OSHA Analytical Laboratory, Salt Lake City, UT (1985). 21. NIOSH, ‘Method 2016 (formaldehyde),’ in “Manual of Analytical Methods (NMAM),” ed. M.E. Cassinelli and P.F. O’Conner, fourth edition, DHHS (NIOSH) Publication 94-113, Department of Health and Human Services, Washington, DC (1994). 22. EPA, ‘Compendium of Methods for Toxic Organic Air Pollutants,’ Methods TO-1 through TO17, EPA/625/SR-96/010b, US Environmental Protection Agency, Washington, DC (1999). 23. D.A. Brymer, L.D. Ogle, C.J. Jones, and D.L. Lewis, Environ. Sci. Technol., 30, 188 (1996). 24. J.C. Posner and W.J. Woodfin, Appl. Ind. Hyg., 1, 163 (1986).

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25. J.P. Lodge, Jr. (ed.), ‘Methods of Air Sampling and Analysis,’ third edition, Lewis, Chelsea, MI (1989). 26. H.W. Biermann, ‘Time-resolved air monitoring using Fourier transform infrared spectroscopy,’ in “Fumigants: Environmental Fate, Exposure, and Analysis, ed. J.N. Seiber, J.A. Knuteson, J.E. Woodrow, N.L. Wolfe, M.V. Yates, and S.R. Yates, ACS Symposium Series No. 652, American Chemical Society, Washington, DC, pp. 202–211 (1997). 27. K. Willeke and P.A. Baron (eds), ‘Aerosol Measurement: Principles, Techniques, and Applications,’ Van Nostrand Reinhold, New York (1993). 28. EPA, ‘National ambient air quality standards for particulate matter (40 CFR 50, 53, 58),’ Fed. Regist., 62(138), 1–102, July 18 (1997). 29. B.C. Daube, Jr, R.C. Flagan, and M.R. Hoffmann, ‘Active cloudwater collector,’ US Pat. 4 697 462 (1987). 30. J.L. Collett, Jr, B.C. Daube, Jr, J.W. Munger, and M.R. Hoffmann, Atmos. Environ. Part A, 24, 1684 (1990). 31. D.E. Glotfelty, J.N. Seiber, and L.A. Liljedahl, ‘Pesticides and other organics in fog,’ in “Measurement of Toxic Air Pollutants, Proceedings of the 1986 EPA/APCA Symposium,” April 27–30, 1986, Air Pollution Control Association/EPA, Raleigh, NC, pp. 168–175 (1987). 32. M.M. Dubinin and E.D. Zaverina, Zhru. Fiz. Kim., 23, 1129 (1949). 33. L.A. Jonas and J.A. Rehrmann, Carbon, 10, 657 (1972). 34. L.A. Jonas and J.A. Rehrmann, Carbon, 11, 59 (1973). 35. P.J. Reucroft, W.H. Simpson, and L.A. Jonas, J. Phys. Chem., 75, 3526 (1971). 36. D.A. Kurtz (ed.), ‘Long Range Transport of Pesticides,’ Lewis, Chelsea, MI (1990). 37. EPA, ‘Compendium of Methods for Toxic Organic Air Pollutants,’ Method TO-17, EPA/625/R96/010b, US Environmental Protection Agency, Washington, DC (1999). 38. J.E. Woodrow, M.M. McChesney, and J.N. Seiber, Anal. Chem., 60, 509 (1988). 39. L.J. Ross, B. Johnson, K.D. Kim, and J. Hsu, J. Environ. Qual., 25, 885 (1996). 40. H.W. Biermann and T. Barry, ‘Evaluation of Charcoal Tube and SUMMA Canister Recoveries for Methyl Bromide Air Sampling,’ Report EH 9902, California Environmental Protection Agency, Department of Pesticide Regulation, Sacramento, CA (1999). 41. J. Gan, S.R. Yates, W.F. Spencer, and M.V. Yates, J. Chromatogr. A, 684, 121 (1994). 42. L.W. Baker, D.L. Fitzell, J.N. Seiber, T.R. Parker, T. Shibamoto, M.W. Poore, K.E. Longley, R.P. Tomlin, R. Propper, and D.W. Duncan, Environ. Sci. Technol., 30, 1365 (1996). 43. EPA, ‘Compendium of Methods for Toxic Organic Air Pollutants,’ Methods TO-4A and TO-10A, EPA/625/R-96/010b, US Environmental Protection Agency, Washington, DC (1999). 44. J.M. Zabik and J.N. Seiber, J. Environ. Qual., 22, 80 (1993). 45. L.S. Aston and J.N. Seiber, J. Environ. Qual., 26, 1483 (1997). 46. K.R. May, J. Aerosol Sci., 4, 235 (1973). 47. R.A. Gussman, Am. Ind. Hyg. Assoc. J., 45, No. 3, B8 (1984). 48. B.M. Wright, J. Sci. Instrum., 27, 12 (1950). 49. P.L. Magill, F.R. Holden, and C. Ackley (eds), ‘Air Pollution Handbook,’ McGraw-Hill, New York (1956). 50. R. Dennis (ed.) ‘Handbook on Aerosols,’ TID No. 26608, National Technical Information Service, Washington, DC (1976). 51. K. Willeke (ed.), ‘Generation of Aerosols and Facilities for Exposure Experiments,’ Ann Arbor Science, Ann Arbor, MI (1980). 52. W.C. Hinds, Aerosol Technology: Properties, Behavior, and Measurement of Airborne Particles. John Wiley & Sons, New York (1982). 53. R.K.A.M. Mallant and G.P.A. Kos, Aerosol. Sci. Technol., 13, 196 (1990). 54. F.W. Kutz, A.R. Yobs, and S.C. Yang, ‘National pesticide monitoring programs,’ in “Air Pollution from Pesticides and Agricultural Processes,” ed. R.E. Lee, Jr, CRC Press, Cleveland, OH, pp. 95–136 (1976). 55. D.A. Goolsby, E.M. Thuman, M.L. Pommes, and W.A. Battaglin, ‘Temporal and geographic distribution of herbicides in precipitation in the Midwest and Northeast United States, 1990– 1991,’ in ‘Proceedings of the Fourth National Pesticide Conference,’ Richmond, VA, November 1–3, 1993, pp. 20–22 (1994).


56. B.R. Hillery, M.F. Simcik, H. Basu, R.M. Hoff, W. Strachan, D. Burniston, C.H. Chan, K.A. Brice, C.W. Sweet, and R. Hites, Environ. Sci. Technol., 32, 2216 (1998). 57. J. Haugen, F. Wania, and Y. Lei, Environ. Sci. Technol., 33, 2340 (1999). 58. L. McConnell, J. Kuchlick, T. Bidleman, G. Ivanov, and S. Chernyak, Environ. Sci. Technol., 30, 2975 (1996). 59. M. Oehme, J.-E. Haugen, and M. Schlabach, Environ. Sci. Technol., 30, 2294 (1996). 60. H. Iwata, S. Tanabe, N. Sakia, and R. Tatsukawa, Environ. Sci. Technol., 27, 1080 (1993). 61. R. Taksukawa, Y. Yamaguchi, M. Kawano, N. Kannan, and S. Tababe, ‘Global monitoring of organochlorine insecticides—an eleven year case study (1975–1985) of HCHs and DDTs in the open ocean atmosphere and hydrosphere,’ in “Long Range Transport of Pesticides,” ed. D.A. Kurtz, Lewis, Chelsea, MI, pp. 127–141 (1990). 62. D.F. Rawn, T.H. Halldorson, B.D. Larson, and C.G. Muir, J. Environ. Qual., 28, 898 (1999). 63. J.N. Seiber, B.W. Wilson, and M.M. McChesney, Environ. Sci. Technol., 27, 2236 (1993). 64. EPA, Ambient Air Quality Surveillance Criteria, 40 CFR, Part 58.12 (1999). 65. California Air Resources Board, “Quality Assurance Plan for Pesticide Monitoring,” California Air Resources Board, Sacramento, CA (1999). 66. J.S. Lenoir, L.L. McConnell, G.M. Fellers, T.M. Cahill, and J.N. Seiber, Environ. Toxicol. Chem., 18, 2715 (1999). 67. L.L. McConnell, E. Nelson, C.P. Rice, J.E. Baker, W.E. Johnson, J.A. Harman, and K. Bialek Environ. Sci. Technol., 31, 1390 (1997). 68. R.A. Reisinger and E. Robinson, J. Appl. Meteorol., 15, 836 (1976). 69. P.S. Honaganahalli and J.N. Seiber, Atmos. Environ., 34, 3511 (2000). 70. J.E. Woodrow, D.G. Crosby, T. Mast, K.W. Moilanen, and J.N. Seiber, J. Agric. Food Chem., 26, 1312 (1978).

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Biological sampling: determining routes of wildlife exposure to pesticides George P. Cobb and Todd A. Anderson Texas Tech University, Lubbock, TX, USA

1 Introduction When risks to wildlife are evaluated, avian or small mammalian species are most often considered.1–3 A separate group of regulations specify studies to evaluate aquatic organisms.1,2,4 When evaluating wildlife, risks of adverse exposure must be quantified by determining residue concentrations of parent compounds and/or degradation products in surface soil, plant materials, food items (insects, earthworms, etc.) and/or water to document pesticide occurrence in the study area and for the study duration. There is also the possibility that reptiles or amphibians, rather than birds, may be selected as indicator species. In this case, pesticide concentrations should also be evaluated in sediments. These data provide the foundation to test hypotheses regarding exposure of nontarget species to pesticides. The first step in a wildlife exposure assessment is to document the occurrence and persistence of a pesticide in the study area throughout the study duration. Several articles in this book describe the experimental designs and best practices to conduct field crop and environmental dissipation (air, soil and water) studies. This article presents methods to quantify spatial and temporal distributions of pesticide presence in ecosystems following normal application and resultant exposure of nontarget wildlife. Exposure routes for nontarget animals include ingestion of pesticide-containing food, inhalation and dermal contact. Ingestion is considered the primary route of pesticide exposure for wildlife.3,5,6 This route is the easiest to quantify since representative food items such as plant material, insects and earthworms can be collected within the foraging areas of avian or mammalian study species. Also, food items may be collected nonlethally using standard esophageal restriction methods.7,8 To implement successfully an assessment of pesticide ingestion, it is critical to monitor food consumption (see below) by representative species (see below) from the different phyla and genera in the study area. Study species should also be selected to represent as many feeding guilds as practical. With this wide array of potential exposure routes, data describing ingestion rates and pesticide occurrence in/on food items provide critical information for proper evaluation of chemical exposure and potential effect. Handbook of Residue Analytical Methods for Agrochemicals. C 2003 John Wiley & Sons Ltd.

Biological sampling: determining routes of wildlife exposure to pesticides

Other exposure routes, dermal and inhalation, are less frequently evaluated since pesticide uptake by routes other than ingestion is poorly described for most species. Dermal exposure information is available from laboratory studies for many pesticides, but these data are generated using exposure scenarios that are unrealistic in the environment. Poor characterization is also due to the difficulty of presenting a dermal exposure without concomitant inhalation or ingestion. Inhalation is usually not evaluated in field trials designed to determine wildlife effects, since the data regarding inhalation are meager for wildlife species of concern,6 and total inhalation is considered small relative to ingestion pathways.3,5,6 Maternal transfer of crop protection products to offspring is generally considered to be negligible with most current use (nonpersistent) insecticides. As pesticides are targeted at specific biochemical pathways and optimized for specific biochemistries of pest species, more persistence may be tolerated for these highly specific pesticides. With newly developed persistent insecticides, significant maternal transfer has been observed during laboratory studies with deleterious effects on avian hatchability.9 This route of exposure should be considered when chemical half-lives in the environment or in the body exceed the time required to conceive and rear one litter/clutch of offspring. Plant materials contribute to dermal and ingestion routes of exposure for animals.10–15 Foliage is often the target of pesticide application. Hence pesticide residue quantitation must be considered in plant materials (root, foliage and seeds) that are likely to be ingested by wildlife species that are considered to be at risk. In these cases, analysis of plant material may constitute a major part of verifying the spatial distribution of applied pesticide. Foliar residues often occur as dislodgeable residues from spray applications. Systemic compounds/degradation products can reach both the root and foliage in biologically relevant concentrations.11,12 In either case, wildlife ingesting this foliage will be exposed to pesticide residues. Chemical analyses have provided good measures of avian and mammalian exposure to pesticides.16–27 These analyses are particularly powerful when used in comprehensive ecotoxicological evaluations,7,20,28,29 designed to assess pesticide risks to wildlife (see Section 1.1). In such studies, representative types of organisms from the study area should be selected to serve as indicators of exposure and/or effect. Species selection criteria include both sensitivity to the test compound and the likelihood that the species will be exposed to the compound. A wide variety of indicator species can be selected based on these criteria. For example, if insecticides are being studied, insectivorous vertebrates are most likely to be considered, and other organisms would be considered at risk only if their food preferences included materials likely to experience pesticide treatment/uptake. The extent to which these indicator species are exposed to a given pesticide is readily established by analyzing food items.8,15,16,19 These food item collections are possible in large-scale regional studies designed to evaluate risks at the population/metapopulation level.7 Food items can be targeted based on knowledge of feeding strategies of the indicator species; for example, ingestion risks for quail may be evaluated by selection of various seed types, while assessments for robins would require attention to soil-dwelling invertebrates also. When using this approach, care should be taken to obtain feeding strategies in the ecosystems being studied and not to accept generic strategies that may poorly represent specific agroecosystem being evaluated. Using the example from above, the types of seeds preferred by quail and the types of earthworms available to robins may

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be different in different agroecosystems. This problem can be overcome in studies of many avian species by sampling food items directly from indicator species.7,8,29 This approach requires frequent visits to the nest or filming the feeding behavior of study species to guide human collection of food items. Although the former process is a direct measure, both procedures allow reliable assessment of pesticide ingestion by indicator species.

1.1 Regulatory requirements and guidelines Within the USA, the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA) requires that pesticide hazards be determined before registration and as part of pesticide reregistration. Registration and reregistration are contingent upon demonstrated acceptable risk from exposure to the pesticide.1–3 Previous regulatory policies required full-scale field studies, wherein risks from a given pesticide were evaluated for multiple receptor species in all ecoregions that were known (or proposed) to receive large-scale pesticide treatment. However, current regulatory policy has significantly delayed these tests in the registration process. As part of current ecological risk assessment guidelines,1–3 terrestrial and aquatic systems are treated differently. In assessing risks to terrestrial organisms, avian species are the primary species to be considered. Laboratory studies are largely performed at Tier 1, and limited field data such as species distributions in pertinent ecoregions, pesticide occurrence in likely food items of sensitive species and areas receiving pesticide treatment are evaluated in Tier 2.1–3 Probabilistic evaluation of pesticide risks should be assessed in the field at Tier 3 of the assessment process. Under the new guidance, few pesticides have reached the stage that requires an assessment of their potential effects on reproduction and mortality in the field. As more products reach the market and risk assessment models suggest potential mortality in the field, assessment of wildlife exposure to pesticides and resultant effects are likely to become necessary. European Union regulations30 require ongoing monitoring of potential ecological impacts if risks of mortality are high for nontarget vertebrates. Such monitoring is triggered if the worst case residue occurrence in/on wildlife food items is predicted to be 10 times the LD50 for a sensitive species occupying the agroecosystem in which the pesticide will be applied.30 Scenarios that trigger such monitoring are infrequent, but do still occur. Some aspects of the studies presented below could be useful in those monitoring efforts.

1.2 Historical perspectives Potential effects of pesticide exposure to nontarget organisms can be estimated in a number of indirect ways. In efforts to reduce costs in the regulatory process, modeling has become the most common technique for estimating effects. However, potentially large errors are the trade-off for reduced cost. In the new US Environmental Protection Agency (EPA) paradigms, few agricultural chemicals have progressed to the point within the regulatory process where field validation of potential adverse effects is required. However, this verification is part of higher tier (also termed ‘levels of


refinement’ in some EPA documents) risk assessments. It is in this verification process that studies will be needed on large spatial scales. For this reason, data are presented from two case studies that were conducted when full-scale field studies were required of registrants in the USA. The design and implementation of these studies should benefit those attempting to verify modeling output of higher tier risk assessments and to provide examples illustrating the protocol design and best practices necessary to conduct field biological monitoring studies.

2 Study designs and best practices Once exposure of indicator species is established by food item analysis, uptake is most often quantified by analysis of organ tissues.23,24,29,31–34 For most current use pesticides, residues are not present in target tissues for extended periods, and concentrations do not increase following repeated low-dose exposures. Rather, the clearance rates for pesticides and their transformation products are relatively rapid.35 Residues are often determined in gastrointestinal (GI) tract or liver. Analysis of blood may also provide exposure information, but detection limits are poor for most study species since blood is normally collected nonlethally. Hence smaller blood samples are collected relative to other matrices, on a dry weight basis. The advantage of blood sampling is that the technique can be performed nonlethally, allowing the indicator species to survive for further observation.22 Excrement has also been used to estimate uptake, although material that passes through the GI tract without uptake can be present in excrement, thus incorrectly elevating the estimate of uptake by the study species. This is why studies emphasizing pesticide uptake by earthworms include a step where earthworm GI tracts are purged. One way to minimize the problem of collecting excreta that has not actually been incorporated into mammalian tissues is to evaluate urine, which by definition contains materials filtered from the blood by the kidney. Another viable approach is to quantify specific transformation products that are unlikely to be formed without exposure to the pesticide or one of its toxic metabolites.19 The analysis of total carcass can also be performed to determine residues, but this method minimizes the concentration of important analytes by diluting them throughout the entire mass of the organism. While whole-body analyses offer the possibility of obtaining uptake data when low detection limits are not achievable, target tissues and nonlethally collected samples are preferable from study design and natural resource preservation perspectives.7,29,36–39 To evaluate realistic exposure scenarios properly, study sites must be selected with great care to encompass a distribution of site characteristics (see Section 2.5) while maintaining enough similarities to allow appropriate statistical comparisons. It is often advantageous to have replicated fields of different characteristics, such as edge habitat, topography, drainage patterns or soil type. The latter characteristic should be evaluated closely to avoid runoff events into small water bodies. Such runoff is unusual, but can occur during incidences of unusually high rainfall. In grain crops, hedgerow presence and previous uses are additional critical characteristics. In orchard ecosystems, investigators should consider orchard maturity, proximity to other orchards and irrigation source. It should also be noted that in some ecoareas the majority of crops must be irrigated.

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2.1 Define study objectives Biological monitoring studies are designed to evaluate actual exposures and effects at the highest tiers of pesticide ecological risk assessments. With this in mind, hypotheses should be stated clearly before studies are designed to allow appropriate methodologies, sample replication and quality assurance (QA) oversight in the field and the laboratory. Two critical objectives that must be addressed are the extent of effect that a study will strive to detect and the desired confidence that the effect was in fact manifested. Two case studies described in this article were designed and implemented to measure organophosphate insecticide residue occurrence in agroecosystems under normal-use scenarios and resultant wildlife exposure. Study designs specifically evaluated avian species and emphasized nestling exposures as this life stage has been found to be most sensitive to anticholinergic agents.39 This design allows the sensitive evaluation of passerine exposures to insecticides and illustrates the objectives for other monitoring studies that may be needed for other terrestrial species. Studies may be designed for estimating exposures to a wide array of wildlife, including birds, mammals and amphibians. Many regulatory requirements involve birds, and less emphasis is currently placed on other species. As regulatory requirements evolve, ecological risk assessments will be required for more species. This may require alternative approaches for food item analysis to allow estimates of pesticide ingestion. One shortcoming in many field studies is a failure to address adequately exposure to toxic transformation products. In efforts to manage time and cost constraints, the concentrations of parent materials and transformation products are often added together to produce a total ‘toxic residue’ amount.3,40,41 However, it is more appropriate to evaluate individual transformation products as their toxicity may be significantly increased (e.g. active oxons) or decreased (e.g. dehalogenation or dealkylation products) relative to the parent compound.10,41–45

2.2 Preparation of study protocol 2.2.1 Role and responsibility of study personnel When designing and implementing field studies to evaluate pesticide dissipation and ecological effect, communication between ecologists, chemists, toxicologists and often agricultural engineers is critical to a successful study. This communication must begin when protocol development begins. Sponsor representatives should relay the scope of the study and the questions to be answered. In many cases the sponsor representative is fully engaged in protocol development. The Study Director has overall responsibility for protocol development. Perhaps the most important duty of the Study Director is to organize a team of capable individuals who are committed to conducting the best possible study. If this is accomplished, the team will work together well to develop and implement accurate timelines and high data quality objectives for each phase of the study. Protocol development must include at a minimum one representative from each facet of the study. For dissipation and exposure studies, this means that representatives from field teams, laboratory teams and QA must sit together to develop reasonable protocols. Representatives should include not only the managers of laboratories or field operations, but should also involve experienced personnel


who will actually generate data. It is critical that each team understands the needs and constraints of other teams. For instance, the field personnel need to understand that certain container types minimize interferences, and laboratory personnel need to understand that for each food item sample collected a ladder has to be taken to a nest box and climbed. These discussions during protocol development allow solid study designs with achievable goals. It should be noted that if shipping personnel are not part of the technical or QA groups, their representatives should also be consulted to make sure that the critical transition of samples is accomplished. After the sponsor representative has made comments on the draft protocol, all members of the protocol development team should be involved in the finalization of the document. It is at this point that some protocols can have items added that are difficult to achieve for reasons of time or logistics. 2.2.2 Training of study personnel When possible, all personnel should be employees of the same organization and personnel managers should be a team of experienced environmental scientists. Training of all study personnel must include sample handling, sample storage, data recording, data storage and safety. Training must be documented by managers of each facet of the investigation. Field personnel should be trained on site to allow site-specific logistics and potential hazards to be addressed. Of particular concern is timing of reentry following pesticide use.46 Laboratory personnel should be trained in the specific laboratory used for the study, and in the event that more than one laboratory location is used for a study, all personnel should be trained by a single person to maximize data quality from the two laboratories.

2.3 Test substances Chemical characteristics and environmental conditions will influence the design of field studies to assess distributions of occurrence and exposure.11,12,23,29,47–49 Important chemical characteristics of the test substance include water solubility, K oc , vapor pressure, degradation rate and potentially labile functional groups. These characteristics also need to be known for toxicologically important transformation products. One shortcoming in many field studies is a failure to address adequately exposure to toxic transformation products. Typical formulated products should be used since biological monitoring studies are required when actual adverse exposures are predicted by lower tier risk assessments. There is also conflicting information regarding the influence of formulated and pure active ingredients. Thus formulated products are required in field studies to represent actual use scenarios. The formulation and carrier of all applied test substances should be well defined before study initiation and should be monitored during actual application. In the two case studies, Diazinon 50W (active ingredient: diazinon, CAS No. 333-41-5) and Fortress-5G (active ingredient: chlorethoxyfos, CAS No. 54593-838) are discussed. Diazinon 50W was applied as an aqueous emulsion or in superior oil, and Fortress-5G was applied as a granular formulation. Results from case studies showed that formulation components could alter the precision of the application made in agroecosystems. This is a parameter infrequently evaluated in field studies.

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2.4 Test systems For the purposes of these field studies, a test system is defined as a specific tract of land managed in part through use of pesticides. Test systems are normally limited to one crop or land use type and may include row crops, grains, fruits or golf courses. The tract of land, of course, has associated biota that are present naturally or as part of the management practices. These biota are also part of the test system and are normally described as test species or species of interest. Selection of test systems is critical to evaluate wildlife exposure scenarios in a sufficient number of sites within appropriate geographic regions.

2.5 Selection of test sites The number of sites needed for a successful study often depends on specific site characteristics such as the following:

r weather patterns r field size r presence of adjacent fields r edge characteristics r general vegetative cover r topography r soil r wildlife occurrence. In areas with little differences in characteristics, there may be no need for evaluation in multiple field types. However, for areas where these parameters are widely variable, sites must be replicated for each type of site. The number of sites required will increase if multiple regions must be evaluated. It should be pointed out that evaluating different edge characteristics usually plays a crucial role in study design as food resources and cover are often dependent on edge habitat. Ecosystems to be evaluated must represent areas of realistic test substance use. Each test site within an evaluated ecosystem must be characterized to finalize the field study duration and the frequency of sampling that is needed to obtain meaningful exposure data. Test site characteristics (see above) not only dictate pesticide transport and transformation21,39,50–53 but also control the wildlife species that are available for study28,54–62 and may limit access of investigators to areas likely to be impacted by pesticide use. Soil type, slope, vegetative cover, wildlife occupancy and climatic factors are primary factors to consider when selecting study sites. If the pesticide in question is used significantly in different climatic regions, design considerations should include evaluations in regions of major use. Habitat diversity surrounding sites and the management practices to enhance this diversity are critical criteria as they increase wildlife diversity and maximize the potential exposure of wildlife to test compounds.54–62 Although this can only be quantified by wildlife surveys at each test site, edge habitat that provides good cover, nesting and burrowing locations is likely to provide a diverse wildlife population at the study sites. When possible, test sites should be located so that they are completely surrounded by areas treated with the pesticide being studied.28 The border around


a test site should encompass the home range of test species inhabiting the test site. Ideally, when small mammals are being evaluated, the treated area beyond the test site should be large enough that any recruitment of study species to the test site will be from a treated area. It is not possible to cover this recruitment area for most bird species and it is often impractical for small rodents, but should be considered. Owing to abundance, home range and recruitment dynamics, small passerines and small rodents are often selected as test species. It is common for site selection to require several months of intense evaluation. Selection criteria (see characteristics above) should be evaluated on-site, during the appropriate season, 1 year before research is to be performed. This timing also allows some time to develop partnerships with landowners, who must cooperate if research designs are to be successful. This is not a simple matter when conducting research with high-value crops such as fruits.29

2.6 Preparation of test sites Issues important to site preparation include defining borders of study areas and establishing transects for monitoring wildlife presence and activity. This can be done with simple utility flags to designate the areas to be sampled and to designate which areas have been covered recently by observers. Carcass searching along these transects is also important to discover potential mortalities that might be missed in standard nest surveys.63,64 Carcass searching includes a number of specific procedures that are likely to be site specific. Important procedures include consistent time of day, consistent search duration, new search area each day, consistent amount of area searched each day, adequate inspection of accessible edge areas and quantitation of search efficiency for each searcher. Transects or trapping grids are also the best accepted means of monitoring rodent activity on test sites.65–68 Specifications for nest box placement and predator guards should also be included. Specifics of nest box placement will depend on the behavior of avian species being monitored. Inter-box distances and orientation to test areas are two parameters that may vary widely with the organism being studied. Predators vary from area to area, and if nest boxes are near tree canopies, predation from above may in fact be the dominant route of predator intrusion rather than the standard access from the ground. Since large-scale field studies most often involve accessing private property, measures for contacting landowners regarding routine and nonroutine activities is essential. Developing and maintaining good relationships with landowners is essential for long-term utilization of sufficient acreages in different ecoregions.

2.7 Application phase 2.7.1 Preparation of application media Protocols to determine exposure scenarios should require that application be made using normal practices. Test substance application must be thoroughly documented by researchers. Documentation should include weights and volumes of materials added to

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spray tanks or hoppers. Granular products should be weighed before placement in application equipment. The time of preparation and application should also be recorded. 2.7.2 Calibration of application equipment Protocols must specify calibration of application equipment before and after application to determine the rate of product delivery when application equipment was traveling at a constant ground speed. Liquid or emulsion samples should be collected from spray nozzles and granule collection should occur as the test substance exits the application equipment. Once the correct ground speed has been determined for a given application system, that speed is maintained throughout the application process. Protocols should require documentation of actual application practices and times. Samples of applied pesticides should be collected to document application rates to study sites. The test substance must be applied with typical equipment used for the crop, and the application must be made in accordance with the labeled use. Another variable that impacts such studies is the fact that most landowners have their own application equipment, which increases the variance in actual application rates among fields and may cause differential intra-field heterogeneity in application rates.

2.8 Sampling Protocols must specify the number of study sites to be sampled for residues and the number of stations within a study site to be sampled. This is a difficult process to specify, but depends on traditional sampling theory.69 In general, the parameters that need to be evaluated for proper sampling design are the following:

r What materials are likely to contain pesticide residues following application? r What are the known degradation kinetics of the crop protection product being evaluated?

r What are the known errors in quantifying residues in different matrices? r What organisms are considered to be at risk, and at what life stages? r What extent of adverse effect is acceptable? r What confidence is desired in evaluating this effect threshold? Protocols should also specify biotic and abiotic sample types to be collected from each sampling station and the intervals for sampling. Biotic samples should come from potentially contaminated food items (seeds, soil-dwelling invertebrates, flying insects), study species (birds, mammals) or collected carcasses. Abiotic samples normally include soil, water and less frequently sediments. Strategies and techniques for compositing both biotic and abiotic samples should also be part of the protocol to minimize the costs of performing analyses. Collection tools, storage containers and storage conditions must be specified. Chemical occurrence and degradation must be evaluated in the matrix to which the pesticide is applied and in the matrices that are likely to receive unintentional pesticide deposition. Target areas are likely to be soil or foliage, and nontarget areas could be edge habitat or other areas that might receive significant pesticide drift. Requisite sampling should begin as near as practical to the time of application, and sampling


frequency should be based on laboratory-derived degradation rates. Significant replication within and among study fields is critical to obtain sufficient information to produce degradation rates with reasonable confidence intervals. Since ecological parameters vary widely within and among ecoregions, the number of study sites will vary depending on the geographic range of the crop and variable cropping practices. In general, a minimum of three treatment sites are required to represent each type of site (block) within the ecoregion. In the case studies described later, four sites were selected to represent chemical degradation in each ecoregion and 10 treatment sites were monitored to evaluate potential exposure to birds from application of diazinon to apples. Of the eight treatment sites chosen for the chlorethoxyfos study, four were sampled for residue occurrence in soils and four were abandoned when adverse weather prevented application during the target time frame. More sites may be required when the test chemical is used over a wide geographic area or is used in crops that require widely different management practices or that produce significantly different habitat types within the managed area. One fact that is often given too little attention is the actual variability inherent in pesticide application under normal use scenarios. Part of the reason for discounting this variability is that well controlled pesticide applications are often made with standard deviations that are ±40% of the mean. Using this variance, and the equation N = (zσ/ε)2

(1)

where N = number of samples needed to obtain a desired confidence in a given estimate, z = standard normal variant (1.96 for 95% confidence), σ = standard deviation of the observation and ε = acceptable difference between actual mean and estimated mean, 16 sampling sites are needed per field if the research hopes to achieve a 95% confidence that estimates of application rates fall within 20% of the actual mean. These sampling sites need to be evaluated with sufficient frequency to establish pesticide presence in the study area and possible exposure routes for nontarget species. It should also be noted that variance will be reduced if composite samples are taken from each sampling site, and generally individual samples of biotic media are analyzed to obtain the distribution of residues needed for contemporary risk assessments.

2.9 Sample handling and shipment Protocols normally specify that, once collected, all field samples will be immediately double-bagged, placed on dry-ice and then transported to field headquarters where they are logged in and placed in a designated freezer. Glass sampling containers may also be more appropriate to minimize interferences but normally increase shipping weights and thus costs. Freezer temperatures should be monitored daily, if not continuously. It is normally a good idea to store control and treatment samples in different coolers and in different freezers. Sample segregation should also continue for shipment to off-site facilities if required. For some chemicals, rapid dissipation may require special storage or analysis considerations. Attention to this detail can mean the difference between good quality data and uninterpretable data.

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Each utensil contacting the samples should be thoroughly washed with soap that is reasonably free of components that might interfere with chemical analyses. Utensils should then be washed with water and acetone between sample collection. A separate set of collection utensils should be assigned to each field to avoid inter-field crosscontamination. Proper data recording of sampling locations within a study site and sampling area are critical to maintaining data quality. Sample placement in coolers should occur immediately after sample collection to minimize pesticide volatilization or degradation in the sample container.

2.10 QA and field data requirements Audits of each phase of the study should include personnel training, preparation of collection forms, application calibration, each sample collection procedure, sample transport, each type of chemical analysis, data recording, data entry, data verification and data storage. Data collection in the field is often tedious if automated logging devices are not in place. To ensure data integrity, the paper and ink used for field studies should be waterproof. Each data collection form should contain appropriate locations for information detailing the time and location of sample collection, sample transport and sample analysis. Data collection forms should be stored in an orderly fashion in a secure location immediately upon return of field teams from the field at the end of each day. It is also important for data quality for studies to collect necessary field data seven days per week when required. In our experience, poor study quality is likely when field sample and data collection do not proceed on weekends.

2.11 Data reporting Each data point must be transferred from data sheets into spreadsheets or databases. Verification of each datum should be performed by an individual who did not enter the data being verified. Audits of each phase of the study should be performed (i.e. preparation of collection forms, application calibration, each type of sample collection, sample transport, each type of chemical analysis, data recording, data entry, data verification and data storage).

2.12 Data presentation and interpretation Data presentations should include the parent compound and all toxic transformation products. This is particularly important for oxidation of sulfide linkages to sulfoxides or sulfones. These products are often equally toxic to the parent with increased availability. Attention should also be given to oxidative desulfuration of phosphorothionate esters. Data should show pesticide occurrence and dissipation in important matrices during the study period (Figure 1). This has been extensively covered in other articles and will not be elaborated here. Exposure routes should be characterized well enough to quantify the dosages that are experienced by nontarget organisms. This is often


Diazinon Dissipation from Vegetation in PA Orchard 19 600 Drip Ring

Concentration (µg g–1)

500 Tree Row

400

Leaf

300 200 100 0 90

110

130

150

170

190

Diazinon Dissipation from Vegetation in PA Orchard 21 600 Drip Ring

Concentration (µg g–1)

500

Tree Row

400

Leaf

300 200 100 0 90

110

130

150

170

190

Mean diazinon dissipation from vegetation collected within two orchards in Pennsylvania following five applications spanning Julian days 93–187. Note that leaves were infrequently present until Julian day 120

Figure 1

difficult and may require knowledge of toxicokinetics for the test chemicals during laboratory studies. The data in each table and figure of reports submitted to sponsors should be verified by QA personnel. Team leaders, laboratory managers, field managers and the Study Director should meet routinely to discuss the meaning of the data as the study develops. This allows early discussions regarding data interpretation and allows several viewpoints to be explored, which ultimately strengthen the final report for the study.

3 Case studies overview Crop protection chemicals undergoing field testing to determine dissipation, wildlife exposure and toxicological effects will have undergone extensive laboratory tests to

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evaluate their potential to cause adverse effects in wildlife.1–3 Chemical characteristics, mode of action and area of pesticide application are critical factors in determining the probability of adverse ecological effects. If laboratory data indicate the potential for unacceptable risk, exposure assessment data are needed for nontarget organisms that inhabit ecosystems in which the pesticide is most likely to be used. In current risk assessment processes, distributions of chemical occurrence, persistence and effect are essential to develop probabilities of adverse effect.1–3,70,71 Distributions of chemical occurrence and the longevity of effects are poorly defined in agroecosystems. These parameters are necessary to reduce the uncertainty in risk assessment processes. Adverse effects predicted by these risk assessments should be validated in well designed field studies. Numerous field studies have been designed and conducted to evaluate pesticide impacts on wildlife. Some of these are published, and many others were submitted to support chemical registration or reregistration.20,28,29,72–74 The latter group of studies is more difficult to access due to EPA sensitivity to confidentiality. The remainder of this article will address some of the design and implementation considerations for reregistration studies involving Diazinon 50W and for registration studies involving Fortress-5G. Overview findings documenting observed distributions for insecticide application, dissipation and uptake will be emphasized.

3.1 Case study with Diazinon 50W Diazinon is a widely used agricultural and residential insecticide.75 Biological monitoring studies for diazinon in orchard ecosystems were located in south central Pennsylvania (PA), and in central Washington (WA). Habitat diversity, isolation from other orchards and orchardist cooperation were primary considerations for the study.29 Habitat diversity was of concern to maximize the number of potential species inhabiting study sites, and orchard isolation was essential to minimize exposure of study species to crop protection products from other cultivated areas. When evaluating ecological effects in fruit orchards, the need to control pest management practices also allows the possibility of severe crop damage. Finding orchardists who agree to control their management practices is time consuming and expensive. Of 20 study sites in each State, four treatment sites and one control site were randomly selected in each State and sampled for residues.29

3.1.1 Methods Diazinon 50W was applied by air blast sprayers in accordance with typical application practices for orchards. Application began in March and continued until earlyto mid-July. Dormant sprays typically contained diazinon in an oil mixture.29 Aqueous emulsions were applied as foliar sprays thereafter. Equipment was calibrated to provide an application rate of 3.4 kg active ingredient (a.i.) ha−1 .18,29 At least five applications were made at approximately 2-week intervals. During these applications, 233 samples were taken from spray tanks across the four treatment fields to estimate the application rate in PA, and 244 samples were collected in WA.


All field procedures have been described in detail18,29 and the following samples were obtained. In each of eight orchards, apple leaves (LV), under story vegetation beneath the tree canopy (DR) and under story vegetation within tree rows (TR), were collected in predetermined locations with shears. Earthworms were collected by digging to 25-cm depth in approximately a 1-m2 area. Environmental samples were collected from each station before the first diazinon application and additional sampling occurred at 0, 4 and 12 days post-application (D0, D4 and D12). Pesticide ingestion by avian nestlings was quantified using esophageal restriction.8,29 Diazinon was also determined in avian GI tracts of juvenile nestlings collected at 15 days posthatch or carcasses found during daily searches.29 Each vegetation, soil or tissue sample was uniquely numbered and stored individually in a plastic Ziploc bag.29 Samples were frozen until shipped to laboratory facilities. Samples were shipped in coolers with dry-ice and were returned to freezers immediately upon receipt at the analytical laboratories. Control samples were stored separately from treated samples. (1) Chemical analysis. Tissues were homogenized before extraction. Diazinon and diazoxon was recovered from samples with n-hexane–acetone solvent extraction. Each sample was fortified with chlorpyrifos, as a reference standard, to determine the recovery during each extraction. Three portions of solvent were used, and the combined extract for each sample was dried with sodium sulfate. Analyses employed gas chromatography/flame photometric detection. Limits of detection for vegetation and animal tissues were 0.2 and 0.007 µg g−1 , respectively. Recoveries from fortified samples were 82%.29 Diazoxon occurrence was infrequent and at trace concentrations. Therefore, the data presented and discussed below address only diazinon.

3.1.2 Critical observations (1) Distributions of residues are needed to estimate pesticide exposure. Spatial heterogeneity of diazinon residues demonstrated that exposure distributions are needed to estimate hazards to nontarget organisms (Table 1). The range of residue concentrations may be caused by variability in application rates, dissipation rates and by interception of the food item by the applied spray. Residue analyses of tank samples showed that the average application rates were within 10% of the nominal application rates. The average rate was 3.16 ± 0.20 kg a.i. ha−1 (mean ± SE) in PA and 3.06 ± 0.14 kg a.i. ha−1 in WA, although the measured application rates varied among orchards. The more important information available from the many analyses of spray tank samples was the distribution of insecticide applied across a given field on a given day. These distributions contained many values near the mean application rate, but a few spray tank samples were removed from the mean by a factor of six. In this and other distributions discussed, the general shape of application distributions can be described by skewed distributions such as logarithmic or beta. Considering all foliar and dormant sprays, 74% of applications in PA and 72% in WA were within the range 2–4 kg a.i. ha−1 . When evaluating foliar applications only, this range was achieved in 77 and 91% of cases from PA and WA, respectively. The difference in the application precision demonstrates that dormant spray (oil-based) applications were

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Best practices in the generation and analyses of residues in environmental samples Table 1 Diazinon concentrations in crop samples collected from European starlings (Sturnus vulgarus) following several applications to orchards in eastern Washington, USA Residuesa

Application

DPAb

N

nc

Geometric mean

1 2

27 0 1 2 3 4 5 6 7 8 9 10 12 0 1 3 5 10 8 12

1 1 2 1 4 3 6 9 7 5 3 11 4 17 3 5 1 1 2 2

1 0 1 0 2 1 3 0 3 0 0 3 3 9 1 0 1 1 0 0

0.173

Handbook of Residue Analytical Methods for Agrochemicals

Handbook of Residue Analytical Methods for Agrochemicals

Residue

Residue

Analytical Methods for Food Additives

Methods of analytical dynamics

Analytical Methods for Food Additives

Analytical methods for Markov semigroups

Analytical Methods for Food Additives

Analytical Methods for Markov Semigroups

Analytical methods for food additives

Analytical Methods for Problems of Molecular Transport

Analytical Methods for Problems of Molecular Transport

Handbook of analytical techniques

Handbook of Instrumental Techniques for Analytical Chemistry

Handbook Of Instrumental Techniques For Analytical Chemistry

Handbook of instrumental techniques for analytical chemistry

Worker Exposure to Agrochemicals: Methods for Monitoring and Assessment

Analytical and numerical methods for Volterra equations

Mathematical Methods for Physical and Analytical Chemistry

Analytical Methods in Oceanography

Analytical and numerical methods for Volterra equations

Analytical Methods for Food and Dairy Powders

Analytical Methods in Elasticity

Current Methods in Forensic Gunshot Residue Analysis

Food Contaminants and Residue Analysis, Volume 51 (Comprehensive Analytical Chemistry)

Dean's Analytical Chemistry Handbook

Dean's analytical chemistry handbook

Dean's Analytical Chemistry Handbook

Analytical instrumentation handbook

Dean's Analytical Chemistry Handbook

Handbook of Residue Analytical Methods for Agrochemicals