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ALYSTTHE ANALYTICAL JOURNAL OF THE CHEMICAL SOCIETYEDITORIAL ADVISORY BOARD"Chairman: J. M. Ottaway (Glasgow)R. Belcher (Birmingham)L. J. Bellamy, C.B.E. (Walthsm Abbey)L. S. Birks (U.S.A.)E. Bishop (Exeter)L. R. P. Butler (South Africa)E. A. M. F. Dahmen (The Netherlands)A. C. Docherty (Billingham)D. Dyrssen (Sweden)J. Hoste (Belgium)H. M. N. H. Irving (South Acrica)M. T. Kelley (U.S.A.)W. Kemula (Poland)*J. H. Knox (Edinburgh)G. W. C. Milner (Harwell)G. H. Morrison (U.S.A.)*H. J. Cluley (Wembley)*P. Gray ( f e e d s )H. W. Nurnberg (West Germany)"G. E. Penketh (Wilton)E. Pungor (Hungary)D. I. Rees (London)"R. Sawyer (London)P. H. Scholes (Middlesbrough)"W. H. C. Shaw (Greenford)S. Siggia (USA.)"D. Simpson (Thorpe-/e-Soken)A. A.Smales, O.B.E. (Thornaby)*A. Townshend (Birmingham)A. Walsh (Australia)T. S. West (Aberdeen)"J. Whitehead (Stockton-on- Tees)A. L. Wilson (Medmenham)P. Zuman (U.S.A.)"Members of the Board serving on The Analyst Publications CommitteeREG I0 NAL ADVl SO RY EDITORSDr. J . Aggett, Department of Chemistry, University of Auckland, Private Bag, Auckland, NEW ZEALAN D.Professor G. Ghersini, Laboratori CISE, Casella Postale 3986, 201 00 Milano, ITALY.Professor L. Gierst, Universit6 Libre de Bruxelles, Facult6 des Sciences, Avenue F.-D. Roosevelt 50,Professor R. Herrmann, Abteilung fur Med. Physik., 63 Giessen, Schlangenzahl 29, W. GERMANY.Professor W . A. E. McBryde, Faculty of Science, University of Waterloo, Waterloo, Ontario, CANADA.Dr. W .Wayne Meinke, KMS Fusion Inc., 3941 Research Park Drive, P.O. Box 1567, Ann Arbor,Dr. I. Rubeska, Geological Survey of Czechoslovakia, Kostelni 26, Praha 7, CZECHOSLOVAKIA.Professor J . RGziEka, Chemistry Department A, Technical University of Denmark, 2800 Lyngby,Professor K. Saito, Department of Chemistry, Tohoku University, Sendai, JAPAN.Dr. A. Strasheim, National Physical Research Laboratory, P.O. Box 335, Pretoria, SOUTH AFRICA.Bruxelles, BELGIUM.Mich. 481 06, U.S.A.DENMARK.Published by The Chemical SocietyEditorial: The Director of Publications, The Chemical Society, Burlington House,London, WIV OBN. Telephone 01 -734 9864. Telex No. 268001Advertisements: Advertisement Department, The Chemical Society, Burlington House, Piccadilly,London, h'l V OBN. Telephone 01 -734 9864Subscriptions (non-members): The Chemical Society, Distribution Centre, Blackhorse Road,Letchworth, Herts., SG6 1 HNVolume I04 No 1237 April 1979@ The Chemical Society 197

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DOI:10.1039/AN97904FX013

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年代:1979

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ANALAO 104 (1 237) 273-384 (I 979)ISSN 0003-2654April 197927329029931 3323328334348358367371375378382THE ANALYSTTHE ANALYTICAL JOURNAL OF THE CHEMICAL SOCIETYCONTENTSApproach for Achieving Comparable Analytical Results from a Number o fLaboratories-A. L. WilsonAccuracy o f Determination o f Chloride in River Waters: Analytical QualityControl in the Harmonised Monitoring Scheme-Analytical Quality Control(Harmonised Monitoring) CommitteeStatistical Appraisal o f Interference Effects in the Determination o f TraceElements by Atomic-absorption Spectrophotometry in Applied Geo-chemistry-Michael Thompson, Stephen J. Walton and Shirley J. WoodMinimum Sample Preparation f o r the Determination o f Ten Elements in PigFaeces and Feeds by Atomic-absorption Spectrophotometry and a Spectro-photometric Procedure for Total Phosphorus-Edward P.Hilliard and J.David SmithSulphochlorophenol N as a Spectrophotometric Reagent f o r Vanadium(V)-M. ZenkiOxidative Determination of Dextromoramide (Palfium) in Body Fluids-B.Caddy and R. ldowuReproducibility o f Pyrolysis - Mass Spectrometry Using Three DifferentPyrolysis Systems-D. A. Hickman and I. JaneInterference Films on the Sensor Membranes o f Solid-state Copper(l1) lon-selective Electrodes-G. J. Moody, N. S. Nassory, J. D. R. Thomas, D. Betteridge,P. Szepesvary and B. J. WrightDetermination o f Nitrite Ion in Unused Cutting Fluids and Cutting Oils Using aGas-sensing Electrode Method-Ferrers R. S. C!ark and Hart B. MacPhersonSHORT PAPERSDicarboxidi ne [y,y'- (4,4- Diami no-3,3'-bi phenylylened ioxy)d i butyric Acid] as aReagent f o r the Spectrophotometric Determination of Cyanide andChlorine-Kerstin GroningssonSemi-automatic Determination of Manganese in Natural Waters and PlantDigests by Flow Injection Analysis-M. F. Gin& E. A. G. Zagatto and H.Bergamin FilhoGravimetric Determination o f Copper(l1) and Cobalt(l1) by Selective Precipita-t i o n with Benzimidazole-K. N. UpadhyayaRoutine Determination o f Nitrogen by Kjeldahl Digestion Without Use o fCatalyst-Eric Florence and Douglas Frank MilnerBook ReviewsSummaries of Papers in this lssue-Pages iv. v, viii, i xPrinted by Heffers Printers Ltd Cambridge EnglandEntered as Second Class at Now York. USA, Post Offic

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DOI:10.1039/AN97904BX015

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年代:1979

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iv SUMMARIES OF PAPERS I N THIS ISSUE April, 1979Summaries of Papers in this IssueApproach for Achieving Comparable Analytical Resultsfrom a Number of LaboratoriesIn the field of water analysis, growing importance is being attached to theability to compare, with confidence, the results from different laboratories.However, the errors in the results can invalidate such comparisons. Oneapproach to ensuring results of adequate accuracy is described in this paper.Examples of its successful application to river-water analysis within the UKwill be presented in subsequent papers.Keywords Water analysis ; accuracy of results ; inter-laboratory comparability ;A. L. WILSONanalytical quality controlWater Research Centre, Henley Road, Medmenham, Marlow, Buckinghamshire,SL7 2HD.Analyst, 1979, 104, 273-289.Accuracy of Determination of Chloride in River Waters :Analytical Quality Control in the Harmonised Monitoring SchemeThe Department of the Environment, in collaboration with the RegionalWater Authorities, has initiated a Scheme for the Harmonised Monitoring ofthe Quality of Inland Fresh Waters in England and Wales.The ScottishDevelopment Department has introduced a similar scheme in Scotland incollaboration with the Scottish River Purification Boards. To achieve therequired comparability of results from all laboratories involved, each labora-tory takes part in an analytical quality control (AQC) scheme; this work isco-ordinated by the Water Research Centre. The general approach adoptedto AQC has been described, and this paper presents the tests made and resultsobtained in the determination of chloride in river waters.Broadly,each of the ten participating laboratories achieved total errors not greaterthan &20% of the chloride concentration for concentrations greater than5 mg 1-1 of chloride.Keywords : River-water analysis ; chloride determination ; accuvacy of results ;ANALYTICAL QUALITY CONTROL (HARMONISED MONITORING)COMMITTEEWater Research Centre, Henley Road, Medmenham, Marlow, Buckinghamshire,SL7 2HD.Analyst, 1979, 104, 290-298.inter-laboratory comparability ; analytical quality controlStatistical Appraisal of Interference Effects in the Determinationof Trace Elements by Atomic-absorption Spectrophotometry inApplied GeochemistryInterference effects in the determination of trace elements by atomic-absorption spectrophotometry in applied geochemistry have been studied bya statistical appraisal and described in terms of a simple two-parametermathematical model.The experimental design incorporated features thatwould allow possible deviations from the model to be detected, but no seriousdeviations were detected except in a deliberately chosen example. The studyled to the identification of some important interference effects that couldaffect interpretation of geochemical data and also provided a formula thatcould be applied to correct the crude results.Keywords : Applied geochemistry ; mineral exploration ; atomic-absorptionMICHAEL THOMPSON, STEPHEN J.WALTON and SHIRLEY J. WOODspectrophotometry ; interferences ; chemometricsApplied Geochemistry Research Group, Department of Geology, Imperial College,London, SW7 2BP.Analyst, 1979, 104, 299-312April, 1979 SUMMARIES OF PAPERS I N THIS ISSUEMinimum Sample Preparation for the Determination of Ten Elementsin Pig Faeces and Feeds by Atomic-absorption Spectrophotometryand a Spectrophotometric Procedure for Total PhosphorusStudies of mineral metabolism in pigs and problems of manure disposal orutilisation are complicated by interactions of trace metals and major cations.A procedure for the determination of copper, zinc, cadmium, lead, iron,sodium, potassium, magnesium, calcium, phosphorus and arsenic in pigfaeces and feeds is described. Phosphorus is determined spectrophoto-metrically and the other elements by atomic-absorption spectrophotometry.Sample preparation is minimised, and all elements except arsenic are deter-mined after a single sample digestion in nitric acid - perchloric acid mixture.A separate sample digestion is necessary for arsenic.The accuracy andprecision of the method were rigorously tested, and are suitable for budgetstudies of all eleven elements.Keywords ; Pig faeces and feed analysis ; trace metal determination ; majorelements determination ; atomic-absorption spectrop hotometry ; spectro-photometryEDWARD P. HILLIARDSchool of Agriculture and Forestry, University of Melbourne, Parkville, Victoria3052, Australia.and J. DAVID SMITHSchool of Chemistry, University of Melbourne, Parkville, Victoria 3052, Australia.Analyst, 1979, 104, 313-322.Sulphochlorophenol N as a Spectrophotometric Reagentfor Vanadium(V)A spectrophotometric method for the determination of trace amounts ofvanadium(V) with sulphochlorophenol N is described.With this reagent,vanadium forms a blue complex, which is stable in the pH range 3.7-6.0.The coloured complex obeys Beer’s law a t 627 nm in aqueous solution with amolar absorptivity of 3.12 x lo4 1 mol-l cm-l. Copper and cobalt ionsinterfere in this method.Keywords : Bisazochromotropic acid dye ; spectrophotometry ; sulphochloro-phenol N ; vanadium determinationM. ZENKIDepartment of Chemistry, Okayama College of Science, 1-1, Ridai-cho, Okayama-shi,700, Japan.Analyst, 1979, 104, 323-327.Oxidative Determination of Dextromoramide (Palfium)in Body FluidsThe oxidation of dextromoramide to benzophenone with alkaline potassiumpermanganate and measurement of its ultraviolet absorbance is advocatedfor the determination of this drug in urine and serum over the concentrationrange 5-40 pgml-l.Keywords ; Dextromoramide determination ; urine ; serum ; plasma ; ultravioletspectrophotometryB. CADDY and R. IDOWUForensic Science Unit, Department of Pharmaceutical Chemistry, School of Pharma-ceutical Sciences, University of Strathclyde, Glasgow, G1 1XW.Analyst, 1979, 104, 328-333

ISSN:0003-2654    

DOI:10.1039/AN97904FP021

出版商:RSC    

年代:1979

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April, 1979 THE ANALYST viiThe City University, Northampton Square, London, EClWorkers in clinical industrial and academic environments will find this conference of particularvalue as it has been designed to provide a cross-fertilization of the ideas and concepts ofautomation between the three sectors. Not only scientific and technical aspects will beconsidered, but also managerial, organisational and economic considerations which are animportant part of the application of automation. The broad areas of the conference will be:education, new instrumentation, costing and management, new applications, evaluation andstandardizationKEYNOTE SPEAKERSProfessor M Bonner Denton, The University of Arizona, USADr F L Mitchell, Clinical Research Centre, Harrow, Middlesex, UK.Dr R W Arndt, Mettler Instruments AG, Griefensee, Switzerland.Some of the papers included in the programmeTraining of clinical laboratory personnel in the use and maintenance of automatic systems,Dr L B Roberts, Gartnavel General Hospital, UKAn experiment in education for automatic analysis: the 1979 Chemical Society SummerSchool, Dr D Betteridge, University College of Swansea, UK.Case studies in laboratory automation, Professor M Bonner Denton, The University of Arizona,USA.Recent developments in flow injection analysis, Dr J Ruzicka, the Technical University ofDenmark, Lyngby, Denmark.DACOS - a new approach to kinetic analysis, M Snook, Clinical Research Centre, Harrow,Middlesex, UK.Recent developments in automatic chromatography, Dr P B Stockwell, The Laboratory of theGovernment Chemist, London, UK.Automated method for determination of sulphate in water, M Stockley, Yorkshire WaterAuthority, and R J Vincent, Thames Water, UK.The cost benefits of automated analytical systems, J G Jones, Wessex Water Authority, Bath,UK .Economic techniques for evaluating automation alternatives, T M Craig, E I Du Pont deNemours & Co, Wilmington, Delaware, USA.Evaluation of clinical laboratory equipment, Dr L B Roberts, Gartnavel General Hospital,Clasgow, UK.Bartholomew’s Hospital, London, UK.Industrial applications of automation with particular reference to the InfraAlyzer, Dr H Swann,University of Nottingham, School of Agriculture, Sutton Bonnington, Loughborough, UK.Extraction in continuous flow systems with examples from pharmaceutical analysis, Dr BKarlberg, Astra Pharmaceuticals AB, Sodertalje, Sweden.Improved accuracy in automated chemistry through the use of reference materials, Dr R FColeman, National Physical Laboratory, Teddington, UK.The symposium fee will be €120.00 + 8% VAT and this fee will includea) documentation and abstracts of all papersb) luncheon, tea, coffee etc.To register for this symposium and obtain further details fill in the coupon below.I/We wish to register for the symposium and enclose my cheque for S .. . . . . . . .Block capitals pleaseName.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . T i t l e . . . . . . . . . . . . . . . . .Company/Organisat ion. . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Address . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Signed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Date. . . . . . . . . . . . . . . . .Please complete this form and return it to:Beverly Humphrey, Scientific Symposia Ltd., UTP House, 33/35 Bowling Green Lane,London EClR ODA. Tel: 01-837 1212I Automation of radioimmunoassay and related analytical techniques, Professor J Landon, StD O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O e ~ O O O O O O O O O O O O O O O O O O O O ~Analysis 79AUTOMATION IN INDUSTRIAL AND CLINICAL CHEMISTRY16 - 18 July, 197...Vlll SUMMARIES OF PAPERS I N THIS ISSUEDifferent Pyrolysis SystemsA study has been made into some of the factors that affect the reproducibilityof pyrolysis - mass spectrometry.Three separate pyrolysis systems wereexamined and three sample types, a simple system of easily pyrolysablepolymers, an acrylic paint, and an alkyd paint, were employed in order tocover a range of ease of sample pyrolysis. These samples were also examinedby pyrolysis - gas chromatography.The reproducibility of the pyrolysis - mass spectrometry system was foundto vary according to sample type. The source of irreproducibility wasidentified as the pyrolysis process and not the mass spectrometric detection.Keywords : Reproducibility ; Pyrolysis - mass spectrometry ; pyrolysis - gasApril, 1979Reproducibility of Pyrolysis - Mass Spectrometry Using Threechromatography ; paint analysisD.A. HICKMAN and I. JANEMetropolitan Police Forensic Science Laboratory, 109 Lambeth Road, London,SE1 7LP.Analyst, 1979, 104, 334-347.Interference Films on the Sensor Membranes of Solid-stateCopper(I1) Ion-selective ElectrodesCopper (11) ion-selective electrodes based on copper (11) sulphide - silversulphide sensor membranes, which showed anomalous responses withcopper(I1) nitrate in the presence of chloride, have been examined by Augerspectrometry. I n some electrodes exposed to solutions of potassium chloridethe chloride is found to have penetrated the bulk of the membrane matrix,whilst in others only a surface contamination is observed.The anomalouselectrode response is exhibited when exposure to chloride is in the presenceof copper nitrate. The Auger signal alters during the duration of the spectrumas a consequence of electron bombardment. The effects of argon-ion andelectron bombardment are compared.Keywords : Ion-selective electrodes f o r cop$er(II) ; interference films o n ion-selective electrodes ; Auger spectrometryG. J. MOODY, N. S. NASSORY and J. D. R. THOMASChemistry Department, University of Wales Institute of Science and Technology,Cardiff, CFl 3NU.D. BETTERIDGE, P. SZEPESVARY and B. J. WRIGHTChemistry Department, University College of Swansea, Singleton Park, Swansea,SA2 8PP.Analyst, 1979, 104, 348-357.Determination of Nitrite Ion in Unused Cutting Fluids andCutting Oils Using a Gas-sensing Electrode MethodModifications of the Orion NO, gas-sensing electrode method that were madeto determine nitrite ion in unused cutting fluids and cutting oils are described.Detection limits for both types of lubricants of the order of 15pgg-1 ofNO,- ion were obtained.Previous analysis of six cutting fluids, collectedin the Ottawa region and analysed by spectrophotometry, confirmed thepresence of high levels of nitrite ion and showed fair agreement betweenresults. Analysis of six other cutting fluids and 20 cutting oils collected inthe same region showed the presence of nitrite ion in only three instances.The operation of the electrode, interferences, the use of standard-additionand -subtraction methods and the possibility of applying this method toused cutting lubricants are discussed.Keywords ; Nitrite-ion determination ; gas-sensing electrode ; nitrogen oxideelectrode ; cutting fluids ; cutting oilsFERRERS R.S. CLARK and HART B. MACPHERSONProduct Safety Laboratory, Department of Consumer and Corporate Affairs,Tunney’s Pasture, Ottawa, Ontario, Canada, K1 A OC9.Analyst, 1979, 104, 358-366April, I979 SUMMARIES OF PAPERS I N THIS ISSUEDicarboxidine [y,y'-(4,4'-Diamino -3,3'- bipheny1enedioxy)dibutyricAcid] as a Reagent for the Spectrophotometric Determination ofCyanide and Chlorine1xShort PaperKeywords : Dicarboxidine [ y , y'- (4,4'-diamino-3,3'-biphenylylenedioxy) dibutyricacid] chromogen ; cyanide detevmination ; chlorine determination ; spectro-photometryKERSTIN GRONINGSSONResearch Department, Analytical Chemistry, AB KABI, S-112 87 Stockholm,Sweden.Analyst, 1979, 104, 367-370.Semi- automatic Determination of Manganese in Natural Waters andPlant Digests by Flow Injection AnalysisShort PaperKeywords : Manganese detevmination ; water analysis ; plant material analysis ;JOW injection analysis ; spectrophotometryM.F. GIN& E. A. G. ZAGATTO and H. BERGAMIN FILHOCentro de Energia Nuclear na Agricultura, CEP 13400 Piracicaba, S%o Paulo, Brazil.Analyst, 1979, 104, 371-375.Gravimetric Determination of Copper(I1) and Cobalt( 11) by SelectivePrecipitation with BenzimidazoleShort PaperKeywords : Copper determination; cobalt determination; benzimidazole ;gravimetryK.N. UPADHYAYAChemistry Department, University of Dar es Salaam, P.O. Box 35061, Dar es Salaam,Tanzania.Analyst, 1979, 104, 375-377.Routine Determination of Nitrogen by Kjeldahl DigestionWithout Use of CatalystShort PaperKeywords : Nitrogen determination ; non-toxic Kjeldahl digestion ; hydrogenperoxide oxidationERIC FLORENCE and DOUGLAS FRANK MILNERNational Institute for Research in Dairying, Shinfield, Reading, RG2 9AT.Analyst, 1979, 104, 378-381X THE ANALYST Afwil, 1979ANALYTICAL SCIENCES MONOGRAPHS No. 3Pyrolysis-Gas Chromatographyby R. W. May, E. F. Pearson and D. ScothernThis monograph attempts to present the available knowledge in a formuseful to the practising analyst, helping in the choice of an appropriatemethod and in the avoidance of the more common pitfalls in this, perhapsdeceptively, simple technique.Chapter 1 serves as an introduction to gas chromatography and will beof interest to those unfamiliar with the technique.The several methodsof pyrolysis used in pyrolysis-gas chromatography are described inChapter2; their merits and demerits in particular applications are discussed.The major analytical uses of the technique are presented in Chapter 3;the general analytical 'fingerprinting' aspects described separately fromthe method as applied to specific sample types. Chapter 4 deals with theidentification of the pyrolysis products which are eluted from the chrom-atography column, useful extra information allowing the possibility ofnaming a pyrolysed sample without recourse to a known identical sample.The necessity for increased standardization of the technique of pyrolysis-gas chromatography is discussed in Chapter 5.Clothbound 117pp 8s'' x 6" 0 85186 767 7 f7.20 ($14.40)CS Members f5.50ANALYTICAL SCIENCES MONOGRAPHS No.4Electrothermal Atomization forAtomic Absorption Spectrometryby C. W. FullerAt the present time the two most successful alternatives to the flame appearto be the electrothermal atomizer and the inductively-coupled plasma. Inthis book an attempt has been made to provide the author's views onthe historical development, commercial design features, theory, practicalconsiderations, analytical parameters of the elements, and areas of appli-cation of the first of these two techniques, electrothermal atomization.The chapter headings are as follows: History; Theoretical Aspects of theAtomization Process; General Experimental Conditions; Analytical Con-ditions for the Determination of the Elements by Atomic AbsorptionSpectrometry;Applications (Oil and Oil Products; Metals; Rocks, Minerals,and Soils; Waters; Plants; Food and Drugs; Biological Fluids; BiologicalTissues; Air Particulates; Refractory Oxides and Related Materials; OtherAnalytical Applications; Theoretical).Clothbound 135pp 8%" x 5" 0 851 86 777 4 f 6.75 ($1 3.50)CS Members f5.50THE CHEMICAL SOCIETYDistribution Centre, Blackhorse Road, Letchworth,Herts. SG6 1 HN, Englan

ISSN:0003-2654    

DOI:10.1039/AN97904BP025

出版商:RSC    

年代:1979

数据来源: RSC

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APRIL 1979 The llnalyst Vol. 104 No. 1237 Approach for Achieving Comparable Analytical Results from a Number of Laboratories A. L. Wilson Water Research Centre Henley Road Medmenham Marlow Buckinghamshire SL7 2HD In the field of water analysis growing importance is being attached to the ability to compare with confidence the results from different laboratories. However the errors in the results can invalidate such comparisons. One approach to ensuring results of adequate accuracy is described in this paper. Examples of its successful application to river-water analysis within the UK will be presented in subsequent papers. Keywords Water analysis ; accuracy of results ; inter-laboratory comparability ; analytical quality control 1 Introduction Increasing importance is being attached to the measurement and control of the quality of many types of water.This in turn has led to a growing need to control the accuracy* of analytical results so that valid conclusions can be drawn when results are compared either with each other or with water-quality standards. Such control generally presents problems because of the many factors that can adversely affect analytical accuracy. In the author’s experience a critical and well co-ordinated approach to such problems is essential if there is to be any chance of reliable achievement of a specified accuracy in routine analysis. The purpose of this paper is therefore two-fold (i) to describe the approach that is being used within the UK to ensure adequately accurate results for the Harmonised Monitoring of River Water Quality3; and (ii) to introduce a series of papers on the application of the approach to and the results obtained for a series of determinandst within that scheme.Hence this paper is concerned with a topic (analytical quality control) about which much has already been written. However to the author’s knowledge there has been little or no integrated discussion of all aspects of the topic relevant to water analysis although other publications5-12 deal with one or more of the important aspects. It is hoped therefore, that the present account of a complete analytical quality control scheme will be of general interest. The scheme described below was evolved about 15 years ago for a survey of feed-water quality in power stations of the Central Electricity Generating Board.The successful applications to river and other waters suggest that the approach may be of general value. It is interesting therefore to note that the scheme is very similar in fundamental concepts and practical aspects to an excellent and authoritative approach recently recommended for clinical chemistry.l 2 Approach to Analytical Quality Control 2.1 General Concepts The approach consists for each determinand of sequential completion of a number of individual but closely linked stages as summarised in Fig. 1. These activities and their sequence have been chosen so that generally important sources of error are eliminated progressively or controlled at adequately small values. In this way a permanently sound * Accuracy is used here with the sense of “total error” (h.the sum of random and systematic errors); accuracy is said to improve as the total error decreases. The total error of a result is the difference between the result and the “true value,” it being assumed here that a true value exists for every sample.’#* t Determinand is used here with the sense* “that which is to be determined.” 27 274 WILSON APPROACH FOR ACHIEVING COMPARABLE Analyst VoZ. 104 basis for control is ensured with a minimum chance of wasted effort. It is important, therefore that no stage is started until the preceding stage has been completed satisfactorily. The reasons for and activities involved in the individual stages are described in the following sections. Activity I 1 Establish working group I Define determinands and required accuracy Purpose To plan and co-ordinate all subsequent activities.To ensure clear specification of analytical requirements. Choose analytical methods To select methods capable of the required accuracy. Ensure unambiguous r- description of methods + Estimate within-laboratory precision To ensure that the chosen methods are properly followed. To ensure that each laboratory achieves adequate precision. Ensure accuracy of standard solutions t Set up qua1 ity-control charts + To eliminate this source of bias in each laboratory. To maintain continuing check of precision in each laboratory. Check between-laboratory bias To ensure that each laboratory achieves adequately small bias tests to be repeated a t regular intervals to main-tain a continuing check on bias.Fig. 1. Sequence of activities for analytical quality control. The detailed considerations and work necessary in each stage are governed by the particular determinand and the required accuracy. The aim here therefore has been to stress the principles involved ; subsequent papers will give the information relevant to particular applications. Emphasis has also been placed on analytical aspects and no attempt has been made to explain and give full computational details of all the statistical tests involved. Each such test is however stated and details can be obtained either from the references quoted or from general statistical texts. I t is also worth stating that many of the points made below are not novel.Nevertheless their inclusion is considered necessary because they are sometimes overlooked and more importantly they should be seen in the context of an integrated approach to analytical quality control. In particular as the literature has dealt with the early stages of Fig. 1 to a smaller extent than the latter the former are treated here in greater detail especially as they fonn the basis of all subsequent experimental work. One aspect of the scheme in Fig. 1 should be stressed at the outset i.e. everything possibl April 1979 ANALYTICAL RESULTS FROM A NUMBER O F LABORATORIES 275 is done to eliminate sources of error before making tests of between-laboratory bias. There are two main reasons for this. Firstly it is often difficult in water analysis to obtain a direct experimental estimate of this bias for all of the many types of sample usually analysed by laboratories.Secondly if such a bias is found considerable difficulty is often experienced in eliminating it particularly when the laboratories are widely dispersed geographically. 2.2 Establishment of a Working Group To ensure an efficient and uniform approach in all laboratories throughout the stages of Fig. 1 thorough co-ordination of all the work is necessary. At least one laboratory (see below) with the effort and resources necessary to provide advice and to plan and co-ordinate the work is essential; this laboratory is referred to as the co-ordinating laboratory. The effectiveness of any control scheme rests ultimately on the competence of individual laboratories.Hence the maximum possible understanding of all aspects of the work should be sought in all laboratories. This point is of special importance because the statistical procedures required in estimating errors may sometimes be unfamiliar to analysts. Under-standing and efficiency tend to be improved when laboratories are parties to decisions rather than having particular approaches imposed on them. For these and other reasons it is of value to establish a Working Group to plan and agree both the general approach and also the detailed procedures for each determinand. Whenever possible this Group should be composed of a representative from each of the participating and co-ordinating laboratories; other interested organisations may of course also be represented.In addition to the particular purposes mentioned above such Working Groups also act as a useful means of exchange of analytical information. The number of laboratories and/or their geographical distribution may sometimes be so large that it is impracticable for one co-ordinating laboratory to deal with all laboratories. When this is so a hierarchical scheme is useful i.e. the laboratories are divided into a number of groups each of which can be adequately serviced by a co-ordinating laboratory. All the co-ordinating laboratories then form one level in the hierarchy and they follow the scheme in Fig. 1. On satisfactory completion of all stages of the work for a particular determinand each co-ordinating laboratory then initiates an identical approach within its own group of laboratories.2.3 Definition of Determinands and Required Accuracy Unambiguous definition of the determinands of interest89ll and numerical definition of the accuracy required of the analytical results are essential for three main purposes in any control scheme (i) to allow the choice of analytical methods appropriate to the intended uses of the results; (ii) to provide clear criteria for deciding whether or not the errors observed in particular laboratories warrant corrective action ; and (iii) to ensure that adequate numbers of tests are made to allow errors of the magnitudes of interest to be detected as statistically significant. The first task of the Working Group is to ensure that these definitions of the requirements are available because they will form the basis of almost all subsequent work.Much could be written on their formulation but it suffices here to mention that they often appear to be accorded little or no attention and to summarise certain generally important points in sect ions 2.3.1-2.3.6. 2.3.1 results rather than by those who provide them. of course joint discussions are generally essential.8 Responsibility f o r definition of required determinands and accuracy Point (i) above implies that the requirements should be defined by those who will use the In principle this is correct but in practice, 2.3.2 Dejnition of determinands Many of the substances of interest in water analysis can exist in a variety of chemical and physical forms to each of which a given analytical method often responds to different extents.I t follows that an unambiguous definition of determinands is essential so that appropriate analytical methods can be selected. Examples of this and related points are discussed elsewhere.sJ 276 WILSON APPROACH FOR ACHIEVING COMPARABLE Analyst VoZ. 104 Many determinands in water analysis are non-specific,13 i.e. they do not correspond to one or more particular chemical species (chloride iron etc.) but rather express certain properties of samples e.g. colour biochemical oxygen demand which are governed by undefined species. In general the true values for such determinands in any sample are defined by the analytical methods used for their measurement. Therefore the determinands can be defined unambiguously only by defining a particular method to be used (see also section 2.4).The same approach may also be necessary for certain determinands that cannot be measured analytically by available methods e.g. “dissolved” iron. In this instance as a complete separation of dissolved and undissolved forms is not generally possible the procedures used for this separation can have markedly different efficiencies. Hence the separation procedure (e.g. the filtration system) may need to be specified as a means of defining the determinand. 2.3.3 Sources of error Inaccurate results can be caused by errors occurring during sampling (e.g. contamination), between sampling and analysis (e.g. through instability of the determinand) and during analysis.* In water analysis the first two sources can be very important for many deter-minands if appropriate precautions are not taken.Clearly attention must be paid to such errors in addition to those occurring during analysis. However control of the errors before analysis commonly involves different factors than those relevant to analysis. Further, analysts are often not directly involved with sampling. For these reasons the author favours two separate but closely linked approaches to the control of sampling and analytical errors and this is used in the Harmonised Monitoring Scheme. A similar suggestion has been made in the context of quality control in clinical chemistry.l However procedures suitable for ensuring constancy of the determinand concentrations between sampling and analysis (e.g. the addition of a chemical preserving reagent) can affect the performance of analytical methods ; close co-ordination of these aspects is therefore essential.On the above basis the remainder of this paper is concerned primarily with the control of errors arising during analysis. A subsequent paper will consider the other sources of error. 2.3.4 Method of exj5ressing the required accuracy This can be done in a number of ways and each scheme should choose the most appropriate for its purposes. However the approach described below is thought to be of general value in environmental monitoring and in similar applications where the determinand concentrations may cover a relatively wide range. For each determinand the smallest concentration? of interest is decided and this is equated to the limit of detection L required of the analytical method.The limit of detection is defined statistically1*J5 with the assumption that the random errors of analytical results follow a normal distribution. The maximum tolerable total error of an analytical result for any sample is then defined numerically by a statement in the form “The maximum tolerable total error of a result is 9% of the concentration of the determinand or L mg 1-1, whichever is the greater.” This method of expression recognises that relative errors increase markedly as the concentration of a deterrninand approaches the limit of detection. Appropriate numerical values of 9 and L are chosen for each determinand and scheme. For the Harmonised Monitoring Scheme p is 20 for most but not all determinands; the value of L varies with the determinand.3y11 Of course simpler expressions are possible when only a narrow range of determinand concentrations occurs or is of interest.Finally there is the question of how to express the required accuracy. 2.3.5 Dejnition of tolerable random and systematic errors It is also important to define separately the random and systematic errors that can be tolerated because they have different effects on the validity of results and because they are estimated in different ways. For the Harmonised Monitoring Scheme the random error * Errors arising through clerical errors and/or through the use of different units in reporting results, though important are not considered here. t Certain determinands are not expressed in concentration units.For simplicity here the term con-centration is used throughout April 1979 ANALYTICAL RESULTS FROM A NUMBER OF LABORATORIES 277 of a result is taken as twice the standard deviation of individual results and the maximum tolerable total error is divided equally between random and systematic errors. This division of total error between random and systematic errors is arbitrary but experience suggests it is often useful. Other divisions may be used if desired but experimental problems in checking bias can arise as the ratio of the tolerable random and systematic errors is increased (see section 2.9.3). Thus numerical values for the maximum tolerable standard deviation and bias of analytical results can be deduced for any concentration of determinand. For example the maximum tolerable standard deviation is 0.259% of the concentration of the determinand or 0.25L whichever is the greater.It is of interest to note that recent German proposals9 on monitoring drinking water have recommended maximum tolerable standard deviations for a number of determinands. For each determinand only one fixed value is given but the recommendations are concerned mainly with narrow concentration ranges around values specified in water-quality standards. The use of the above target values for random (precision) and systematic (bias) error is described in the following sections. 2.3.6 Provisos to the approach in sections 2.3.1-2.3.5 In the above approach a few points should be noted. (i) There is a slight numerical inconsistency between the values of L and the maximum tolerable standard deviation at low concentrations.Thus if results are normally distributed with a standard deviation uR independent of concentration at low concentrations the limit of detection is given by 3.290 (probabilities of errors of the first and second kinds1*J5 are both 0.05). Hence at low concentrations the maximum tolerable standard deviation (specified as 0.25L) is 0.82aR i.e. it is smaller than the standard deviation achieved aR. This inconsistency could be eliminated for example by selecting slightly different probability levels to define the limit of detection. However such complication is considered unnecessary because of the uncertainties involved in estimating uR and the fact that the targets for errors should not usually be regarded as precisely fixed constants.If the target values are interpreted with common sense no difficulty is caused by the above inconsistency. (ii) The limit of detection may not be directly relevant to certain deterrninands e.g. pH value. When this is so the expressions for tolerable errors will usually need to specify only fixed percentage or absolute errors. (iii) As mentioned above the numerical values of p and L should be chosen appropriately for each scheme. However as those values are reduced the analytical effort and cost needed to achieve them will generally increase and at some point will become impracticably large (see also section 2.9.3). Care is required therefore in specifying errors that are both tolerable and achievable. The target values in the Harmonised Monitoring Scheme may seem rather large but experience of the approach in this paper suggests that they are both useful and realistic.I t is interesting that McFarren et aZ.,16 in considering the results from many inter-laboratory studies of different analytical methods concluded that for only a relatively small fraction of methods studied were total errors* of 25% or less achieved. (iu) In specifying a particular method in order to define a non-specific determinand care is also necessary to ensure that the method selected is capable of the required accuracy and limit of detection. 2.4 Choice of Analytical Methods This is the most important stage of all because an inappropriate choice will not only prevent achievement of the required accuracy but is also likely to cause much wasted time and effort.Accordingly the choice of methods is considered in some detail below. It sometimes appears to be thought that comparable results can simply be achieved by ensuring that all laboratories use the same method for a particular determinand. However, innumerable experimental studies have shown that this approach does not necessarily control the errors of all laboratories; see for example the compilation of inter-laboratory tests given by McFarren et aZ.16 In addition use of the same method by all laboratories penalises * The definition of “total error” used by McFarren et al. is similar to but not identical with that in this paper; see also reference 17 278 WILSON APPROACH FOR ACHIEVING COMPARABLE Analyst VoZ. 104 those able to take advantage of analytical advances e g .by using new methods or instru-ments. This approach is not therefore gene]-ally recommended except when required by the definition of a determinand (see section 2.3.2). In principle the approach recommended here is simple in that each laboratory merely has to select a method capable of the required accuracy. Of course other factors such a< the speed and simplicity of a method are frequently important and should be consider d carefully when choosing a method from those capable of the required accuracy. In applying this approach several aspects need careful consideration and those of general importance are summarised below. 2.4.1 Definition of determinands by specifying particular analytical method The methods to be used for certain deternninands may already have been defined (see preceding section).When this is so there is in principle no choice to be made and it is necessary only to ensure that all laboratories follow essentially the same procedure (see section 2.5). This approach has been used in the Harmonised Monitoring Scheme for suspended solids and biochemical oxygen demand. It is also possible to allow the use of alternative methods for a particular determinand if they are first shown to give results in satisfactory agreement with the specified method. This latter approach is basically sound, but can lead to problems because of the experimental difficulties involved in proving satis-factory agreement particularly when the samples of interest are of markedly differing com posit ions.2.4.2 For any determinand other than those in section 2.4.1 the method should be selected from among those known to be capable of the required performance and for which a thorough investigation of the effects of relevant experimental parameters has been made.5918J9 If only one such method exists it is technically desirable for all laboratories to use that method, but see section 2.4.4. When several suitable methods are available for a particular deter-minand each laboratory is free to choose the one that it prefers. In making that choice it is useful to select methods capable of rather smaller errors than the maximum tolerable errors defined above. This will tend to ensure a safety margin and to reduce the need for frequent corrective action to reduce intolerably large errors.Particular attention should be paid to sources of bias when selecting a niethod5,11J8120 because in many situations the choice of a suitable method is the main control on bias in the analytical results. Notwith-standing the specified tolerable bias it is recommended that whenever possible the aim should be to select methods with negligible sources of bias. Determinands that are defined chemical sjhecies 2.4.3 In comparing the published performances of analytical methods with the required limit of detection and maximum tolerable standard deviation and bias care is necessary because the definitions of these characteristics and the methods used to estimate and report them often differ from one publication to another.1.8-22 This potential problem is readily elimi-nated if authors make clear the definitions and procedures relevant to their quoted perform-ance characteristics and if they give unambiguous information on the magnitudes of errors.Within the UK one particular approach to the definition and tabulation of performance characteristics has been developed by the Central Electricity Research Laboratories.5Jg-22 This approach has been followed by the Water Research Centre and recently by a committee* concerned with the selection evaluation and publication of methods for the analysis of a wide range of waters effluents and other materials.23 An example of such a tabulation is given in reference 24. Essentially the same approach is followed in the Harmonised Moni-toring Scheme. In comparing published and required values of standard deviations and limits of detection, careful consideration of the sensitivity and discrimination of the analytical-measurement system is also essential.For example a published method may have used an instrument Comparing the required and Published performances of analytical methods * The Standing Committee of Analysts to Review Standard Methods for Quality Control of the Water Cycle established by the Department of the Environment and the National Water Council April 1979 ANALYTICAL RESULTS FROM A NUMBER OF LABORATORIES 279 of better discrimination (ability to make finer readings of the instrument scale) than that available in another laboratory. If instrumental errors govern precision the latter labora-tory will be unable to achieve the published precision.Thus in selecting methods each laboratory should ensure that the sensitivity and discrimination of its preferred method will allow the required precision to be achieved. 2.4.4 Availability of suitable analytical methods The approach in section 2.4.2 cannot always be followed in the Hannonised Monitoring Scheme for two reasons. Firstly thoroughly evaluated and characterised methods are not at present available for all determinands. In the absence of such methods there is much to be said for delaying attempts to achieve comparable results but the need for information on water quality commonly requires some attempt to control analytical errors. Fortunately, this problem is gradually being eliminated by the work of the many laboratories and organisa-tions concerned with the development of analytical methods.Secondly the staff and/or equipment of a laboratory may necessitate the use of a method whose capability of achieving the required accuracy is at least partially in doubt. Therefore the use of methods not known to be suitable requires consideration. If a laboratory has to select an analytical method that has not been thoroughly evaluated, critical assessment of its likely errors is d e ~ i r a b l e . ~ * ~ ~ s ~ ~ Certain sources of bias can some-times be readily eliminated e.g. in the blank and calibration pro~edures.~~~*~~0 Other likely sources of bias and the method's ability to achieve the desired precision should then be assessed. To aid uniformity among laboratories in such appraisals it is useful for the co-ordinating laboratory to make similar assessments of all such methods; this approach is followed for all determinands in the Harmonised Monitoring Scheme.Whenever possible, each laboratory concerned should then make any preliminary tests needed to estimate the unquantified errors.195 This seldom presents great difficulty if only the precision is in doubt. However if as is common little is known of interference effects,ll the task is much more difficult because of the large amount of work needed for a reasonably thorough investigation of such errors,20 particularly for samples whose composition is as variable as river waters, Other sources of bias20 may also not be simple to determine. Such uncertainties and the effort needed to resolve them are a powerful argument for the approach in section 2.4.2.In the present context however experience shows that routine laboratories cannot usually make all the required tests. Hence all that can be done in the short term is for a laboratory to make as many tests as possible and then to proceed to subsequent stages of Fig. 1; the latter stages may detect certain sources of bias e.g. in the tests described in section 2.9. In the longer term the aim should be either to complete any tests on errors or to replace the method with one whose performance is better established. 2.4.5 Importance of sample preservation 9rocedures As mentioned above stability of the concentration of a determinand between sampling and analysis must be ensured but the procedures used to that end can affect the performance of a subsequent analytical method.It is desirable therefore to select only methods that include as an integral part of the total procedure all aspects relevant to sample preservation; e.g. details of sample containers and preserving reagents. 2.5 Written Descriptions of Analytical Methods Virtually all publications concerned with analytical quality control stress the importance of detailed written descriptions of analytical methods. In addition to the clear need for such descriptions in each participating laboratory they are also essential in assessing likely sources of error (see section 2.4.4). There are many possible formats that such descriptions can take and an international standard is a~ailable.~5 It suffices here to suggest that the aim should be to specify the entire experimental procedure in such detail that if it were faithfully followed an inexperi-enced analyst would be able reliably to achieve adequate accuracy.Relevant points have been reviewed by many workers; see for example references 18 and 19. The type of format favoured by the author is illustrated in references 5 and 24 280 WILSON APPROACH FOR ACHIEVING COMPARABLE AnaZyst VoZ. 104 It is also essential to do everything possible to ensure that the method is followed exactly in all subsequent work at least until tests have demonstrated the validity of any contem-plated changes. In considering such changes great caution is generally desirable ; even apparently minor procedural details can sometimes have unsuspectedly large effects particu-larly in trace analysis.One of the aims of subsequent stages of Fig. 1 is to detect any deterioration in the accuracy of routine analytical results caused by unsuspected changes in procedure. 2.6 Ensuring Adequate Within-laboratory Precision Three main considerations lead to this and the three subsequent stages of Fig. 1. (i) Many factors other than the written description of a method can affect the precision of analytical results. Such factors include the purities of reagents the reliabilities of instru-ments the abilities of analysts and the degree of contamination problems. Therefore the fact that one or more laboratories have achieved adequate precision when using a given method does not guarantee this for another laboratory. Experimental estimates of precision should therefore be obtained by each laboratory.(ii) Direct tests of between-laboratory bias are usually not easy to arrange on a frequent basis. There is an advantage therefore in attempting to control as many sources of error as possible by tests that can be made independently by each laboratory. (iii) The number of replicate tests needed to detect bias of a given magnitude is governed by the standard deviation of results.16p26 It i!j useful therefore to ensure that all labora-tories achieve adequately small standard deviations before making tests of bias. On this basis estimation of within-laboratory precision by all laboratories is the first of the experimental stages in Fig. 1. 2.6.1 In deciding an appropriate experimental design for such tests several desiderata are generally relevant.1s6s21 (i) Precision commonly depends on the concentration of the determinand.Therefore, except when interest is attached only to a narrow concentration range,9 estimates of standard deviation should be obtained for at least two concentrations.21 Further whenever the limit of detection is of interest the within-batch standard deviation of blank determinations should usually be e ~ t i m a t e d . ~ ~ s ~ 5 $ ~ ~ (ii) Precision commonly worsens as the time period over which the tests are made is increased. As it is the precision of routine analytical results that is of interest the tests should be spread over a number of occasions rather than being made on only one occasion. (iii) Precision may depend on the nature oi the sample analysed and in particular real samples (e.g.river waters) may give worse precision than standard solutions. However, standard solutions are of general value in analytical quality contr01~~~J1 and tests of precision €or both standards and real samples are therefore useful (see section 2.8). (iv) Precision is assessed from replicate results for a given sample; these results should be independent of each other.21 The determinand concentration in the sample must also be the same on each occasion it is analysed. (v) As the number of tests and samples is increased more information is obtained and the uncertainties of the estimated standard deviations tend to decrease. This has generally to be balanced against the amount of effort required and available for the tests.Many experimental designs for estimating precision have been described and any may be used provided valid estimates of the required information are obtained. The design normally followed in the Harmonised Monitoring Scheme aims to meet the above de~iderata,~,~l and is summarised in section 2.6.2; experience to date suggests the design to be of general value. Important factors to be considered in designing tests of precision 2.6.2 Typical experimental design In each of m batches of analyses (no more than one batch in any one day) n portions of each of the following are analysed in random order (i) blank determination; (ii) standard solution of concentration 0.1 C (C = upper concentration limit of the analytical method); (iii April 1979 ANALYTICAL RESULTS FROM A NUMBER OF LABORATORIES 281 standard solution of concentration 0.9 C,; (iv) a sample of river water; and (v) the same as (iv) but with an accurately known addition (equivalent to 0.5 C,) of the determinand.All analyses are made exactly as for normal samples by the same experienced analyst. The values of rn and n are usually 10 and 2 respectively but other values can be used.5921 Special consideration of the value for n may be needed if the analytical method specifies analysis of more than one portion of a sample and/or blank in order to produce an analytical result for a sample. The value n = 2 mentioned above applies to the usual situation where only one portion of a sample and a blank is specified in the method. Other details are given elsewhere.5~~1 Precautions are necessary when the determinand is unstable and these are summarised in the Appendix.2.6.3 At the end of the tests for each of the solutions (ii)-(v) the 20 analytical results are analysed ~tatistically~,~~ to obtain estimates of the within-batch (sw) between-batch (sb) and total (st) standard deviations where st2 = sw2 + sb2. The results for the blanks are used to provide an estimate of its within-batch standard deviation (in concentration units). For each of the solutions (ii)-(v) the value of st is compared (variance-ratio test) with the maximum tolerable standard deviation at the corresponding concentration of the deter-minand. The precision is then accepted as adequate if st is not significantly greater (0.05 probability level) than the target value (see Appendix).Similarly the limit of detection can be calculated from the value of sw for the blank and then compared with the target value (see Appendix). If all targets are achieved it can be concluded (but see the Appendix) that the precision is adequate. If one or more targets are not achieved sources of imprecision should be sought reduced and the tests then repeated. When this is necessary the values of sw and s b for a particular solution may help to indicate the likely source of e r r ~ r ~ ~ ~ and this is one of the main reasons for choosing n = 2 i.e. this allows separate estimations of sw s b and st. When n = 1 only st can be estimated. In addition to the above estimates of precision the recovery of the determinand added to solution (v) is also calculated.This recovery will generally differ from 100yo even in the absence of bias as a result of random errors and a criterion is therefore needed to decide whether or not the observed recovery is to be considered as adequate. In the Harmonised Monitoring Scheme this criterion is that the recovery should not differ significantly (t-test, 0.05 probability level) from the range 95-105%. Again if the results are unsatisfactory, the cause should be sought reduced and the tests then repeated. Finally the results from solutions (i)-(iii) allow the analytical sensitivity* to be com-pared with that expected for the method. Other aspects such as the linearity of the cali-bration graph should also be checked. If such parameters depart appreciably from those expected for the method it is as well to seek and if necessary eliminate the reasons for such differences as they may indicate mis-application of the method or other problems.When all the above aspects can be regarded as satisfactory the next stage in Fig. 1 (section 2.7) is started. Calculations and com9arison of required and achieved performances 2.6.4 Co-ordination of tests To ensure that all laboratories carry out the agreed tests arid calculations uniformly the co-ordinating laboratory should prepare (i) detailed descriptions of all aspects of the tests for each determinand and (ii) suitably designed forms on which laboratories can enter the results from the tests. These forms can also and in the Harmonised Monitoring Scheme do, include detailed instructions on how to make the various statistical calculations involved, Experience shows that if such details and forms are not supplied to all laboratories some participants may make inappropriate tests and calculations and this may invalidate their work.The co-ordinating laboratory is also likely to meet problems in attempting to check and collate all results if they have not been calculated and presented in a uniform format. One general point on these and subsequent tests in laboratories is worth noting here. * The term sensitivity is used here to denote the rate of change of the analytical response with deter-Thus when the response is directly proportional to concentration the sensitivity minand concentration. is the slope of the calibration graph 282 WILSON APPROACH FOR ACHIEVING COMPARABLE Analyst VoZ.104 2.7 Accuracy of Standard Solutions This stage is intended to ensure that the standard solutions (used for calibration purposes) of all laboratories are in satisfactory agreement and hence do not cause important between-laboratory bias. In principle this aim could be achieved by the co-ordinating laboratory providing the necessary standard solutions for all laboratories. In practice however this approach is not favoured because it is cumbersome liable to practical difficulties and very demanding of effort from the co-ordinating laboratory. A better approach and one which is used in the Harmonised Monitoring Scheme is as follows. All laboratories prepare their standards as prescribed in their analytical methods and the co-ordinating laboratory distributes a portion of its own concentrated standard solution for the determinand under study to each laboratory.Of course considerable care is essential to ensure that the distributed standard has a negligible error. In water analysis particular care is often required to ensure that the concentration of the determinand in the distributed solution is stable for an adequate time period and that the containers used for the standard do not cause contamination. Such problems are usually minimised by distributing relatively concentrated standard solutions ; this also aids transport arrangements because relatively small volumes of such solutions suffice for the subsequent tests. Each laboratory then compares the concentrations of its own standard with the distributed standard in the following way.Both standard solutions are diluted accurate1.y to the same concentration this concentra-tion being that for which the tests in section 2.6.2 have indicated the smallest within-batch relative standard deviation*; this concentration is usually at or near C,. Then (I portions of each diluted standard solution and one blank determination are analysed in one batch of analysis in a prescribed order? and the mean results for each standard compared using a t-test. The value of q is calculated by each laboratory to allow the experiment to have the desired statistical power of detecting a difference of d% between the two standards.26 In the Harmonised Monitoring Scheme d = 2 and the probabilities of errors of the first and second kinds are both set at 0.05.If any laboratory finds that its standard solution is in error by more than d% the cause is sought and reduced and the tests are repeated. When a laboratory’s standard is in satisfactory agreement with the distributed standard the next stage in Fig. 1 (section 2.8) is started. 2.8 Analytical Quality-Control Charts Even though a laboratory has satisfactorily completed the two preceding stages this by no means guarantees that its accuracy will remain permanently satisfactory. It is essential, therefore for each laboratory to maintain continuing checks that its errors remain adequately small. A widely recommended and used is to make special control tests in each batch of the normal analyses and to plot the results immediately they are obtained on statistical quality-control charts.If the results from the control tests indicate that the accuracy has worsened appreciably further analysis of samples is stopped until the source of the increased error has been found and eliminated. This use of quality-control charts is recommended here and is followed in the Harmonised Monitoring Scheme. Several important aspects in using such charts for analytical quality control are summarised in sections 2.8.1-2.8.6. It will be seen that various uncertainties arise and this emphasises the desirability of laboratories seeking to obtain accuracy rather better than that expressed by the maxi-mum tolerable errors. 2.8.1 Basis of q.uality-control charts For those who may be unfamiliar with the concepts underlying statistical quality-control charts most general statistical texts deal with the topic; see for example references 27 and 28.The use of these charts in analysis has also been described by many worker~.5~6,*,12,29 * The relative standard deviation signifies here th,e standard deviation for a particular concentration t A random order is usually suitable but systematic orders may be preferable if the analytical response expressed as a percentage of that concentration. can drift continually in one direction April 1979 ANALYTICAL RESULTS FROM A NUMBER OF LABORATORIES 283 2.8.2 Choice of type of control test For example if a standard solution is analysed in each batch of analyses this gives information on precision and certain sources of bias but clearly gives no direct information on the accuracy of sample analysis.Information on the precision for samples can be obtained by analysing two or more portions of a sample in each batch but this gives no information on bias. Recovery tests using samples may be useful in providing information on certain though not all sources of bias but are likely to present problems in assessing precision. Ideally all these and any other relevant control tests would be made routinely but a compromise with the effort required is usually necessary. Each situation should therefore be assessed individually to decide the most appropriate control test(s) for a given determinand. This has been dis-cussed in more detail elsewhere,30 and the results from the preceding tests of within-laboratory precision are of value in deciding which control tests to use.For most determinands the single best control test is usually considered to be the analysis of a standard solution particu-larly when the initial tests of precision have shown essentially the same precision for standard solutions and samples. Of course when this control is used it is essential to ensure that the concentration of the standard solution has negligible error on each occasion it is analysed. Another factor frequently relevant to the choice of the control test(s) is the extent to which precision depends on the concentration of the determinand. If for example the standard deviation of results increases markedly with concentration there is some problem in deciding the best single concentration to use for a control standard.Of course if only a narrow range of concentrations exists or is of interest the mid-point of that range will usually be a suitable value for a control standard. Otherwise it is preferable to use two control standards one near the lower limit of the concentration range of the method and the second near the upper limit. If the effort necessary for both standards is not available the use of the upper concentration is on balance favoured. It should be noted that problems also arise in the construction and interpretation of control charts for the two other types of control test mentioned in the preceding paragraph whenever precision depends on concentra-tion and the concentrations in samples cover a wide range.30 Various devices can be used to reduce such problems.For example one control chart for each of a number of relatively narrow concentration ranges can be used for each type of control test the results being plotted on the appropriate chart. In general no single control test can check all possible sources of error. 2 3.3 Frequency distribution followed by results To allow exact interpretation of the results of control tests the nature of the probability distribution followed by the results must be known; it is convenient and common to assume the normal distribution. To ensure that the results of control tests closely follow this distribution statistical texts usually recommend that for example the control test is replicated in each batch and the mean of the results is plotted as the control point for each batch.This approach is desirable but again the effort available may only allow single control tests in a batch. When this is so it is still of value to use control charts but it must be accepted that the control charts cannot be exactly interpreted without further information on the nature of the probability distribution of results. In practice this is not considered an important objection. 2.8.4 Types of quality-control chart In the Harmonised Monitoring Scheme the results from control tests are plotted on Shewhart-type control ~ h a r t s . ~ ~ - ~ ~ In recent years another type of chart the CUSUM quality-control chart has come into common use and is said to be advantageous in allowing more rapid detection of changes of a c ~ u r a c y . ~ ~ ~ ~ ~ This latter chart has been recommended for use in clinical chemistryl~~~ and has been included in one manual on analytical quality control in water analysk6 An investigation of the use of CUSUM charts in water analysis is to be made in the author’s laboratory.At present however it is considered that there is little to choose between the two types of chart for analytical quality control given the various uncertainties involved in the practical use of control charts 284 WILSON APPROACH FOR ACHIEVING COMPARABLE Analyst Vol. 104 2.8.5 Before a control chart can be constructed an estimate of the standard deviation of the results of control tests is required to allow insertion of the warning and action limits. Ideally this estimate would have a large number of degrees of but insistence on this would delay construction of the chart for a relatively long period while the necessary tests were being made.In the Harmonised Monitoring Scheme therefore a preliminary control chart is constructed as soon as a 1abora.tory’s standard solution has been shown to be adequately accurate. The estimates of standard deviation obtained from the tests of precision are used for this purpose. Such estimates have at least 9 and usually more, degrees of freedom (see the Appendix) but revised estimates should be obtained (and the warning and action limits on the chart adjusted accordingly) as the results from control tests accumulate.30 Particular care is needed in using the chart initially but it is of value for laboratories to have a sequential record of the control tests from the outset especially as an appreciable time period may elapse before the next stage (section 2.9) of Fig.1. Construction of Shewhart-type quality-control charts 2.8.6 Anonymity of control solutions There is value but commonly difficulty in arranging that the analysts concerned are unaware of which solutions are control^.^ In the Harmonised Monitoring Scheme individual laboratories decide whether or not to adopt this approach. The importance of this aspect is much reduced if all analytical staff are brought into a quality-control scheme properly, with full understanding of its purposes. 2.9 Checking Between-laboratory Bias As soon as all laboratories have satisfactorily completed the previous stages this final stage is begun. Portions of one or more standard solutions and/or samples are distributed to each laboratory which then makes sufficient replicate determinations on each solution to allow detection of a bias equal to the maximum tolerable value.The bias is assessed separately for each solution because both bias and precision may depend on the concentration of the determinand and on the nature and general composition of the solution. Other approaches to between-laboratory tests have been described which may allow some economy of effort or a greater amount of information for the same effort ; such approaches have been briefly reviewed.’ However these advantages are gained by making assumptions such as equal precision in all laboratories. For present purposes it is considered essential not to make such assumptions and the approach described below is followed.The co-ordinating laboratory prepares and distributes appropriate solutions to all labora-tories; only a broad indication of the concentrations of these solutions is given to the laboratories. Each laboratory then analyses w portions of each solution the normal control test@) (see section 2.8) being included in each batch of analysis. The results obtained are reported to the co-ordinating laboratory for assessment of the bias for each laboratory and solution. Any laboratories with an unacceptably large bias are informed so that they can seek and reduce the cause before undertaking further tests of bias. Further details relevant to this approach are given below. The approach adopted is very simple.2.9.1 Solutions to be used The main sources of bias needing to be checked are those arising from the analysis of samples rather than standard solutions. Emphasis should whenever possible therefore be given to the distribution of the former. Nevertheless it is useful to include at least one standard solution so that the true concentration of at least one distributed solution is known. The distributed solutions should also cover the range of determinand concentrations of interest and in general the more types of sam.ple that can be included the better In the Harmonised Monitoring Scheme the general aim is to distribute one standard solution near the middle of the concentration range of interest and two samples of river water of different types with concentrations near the lower and upper concentrations of interest.Whenever possible (see section 2.9.2) these solutions are distributed at the above concentrations so that their dilution before analysis is not necessary; such dilution may prevent detection of certain sources of bias April 1979 ANALYTICAL RESULTS FROM A NUMBER OF LABORATORIES 285 2.9.2 Stability of distributed solutions It is essential that the co-ordinating laboratory takes great care to ensure that each laboratory receives essentially identical portions of each of the distributed solutions. Of particular importance in water analysis are the cleanliness of solution containers and the stability of the deterrninand. Preliminary tests in the co-ordinating laboratory are often desirable to ensure this identity of the distributed solutions.In water analysis many determinands are so unstable that distribution of samples without special treatment is impossible. When this is so the use of preserving reagents can be of value but the co-ordinating laboratory should first ensure that a reagent it proposes to use is compatible with the analytical methods used by all laboratories. One approach commonly recommended to overcome such problems is to distribute a stable standard solution with a sample the former being used to spike a portion of the latter before analysis. The difference between the results for the spiked and unspiked portions is then used to assess the bias. This procedure can be of value but should be used with caution because it may not detect those sources of bias whose magnitudes are independent of the concentration of the determinand (see section 2.9.4).Therefore the best approach needs to be decided individually for each study; the procedures used in the Harmonised Monitoring Scheme for particular determinands will be described in subsequent papers. 2.9.3 Number of analyses required on each solution The number of replicate analyses w required on each solution depends on the ratio B/a, where B is the maximum tolerable bias and a is the standard deviation of results. DaviesZ6 describes the calculation of w for different values of B/a for various probability levels and when a is not known exactly. In the Harmonised Monitoring Scheme an approximate value for w to be used by all laboratories is obtained by setting B and at equal to their maximum tolerable values.The ratio B/at is therefore 2.0 and the corresponding value of w (0.05 probability of errors of the first and second kind) is approximately 3. However it is necessary to increase this value somewhat because only an estimate of at is available.26 At the same time there will be a tendency for at to be less than the maximum tolerable value. Hence for convenience the approximation w = 5 is used for each solution; experience shows this to be a reasonable approach. The precision achieved by certain laboratories may be substantially better than the maximum tolerable value so that a value for w smaller than 5 could be used. However the use of w = 5 throughout is preferred because it provides better estimates of precision from these tests (see section 2.9.5) and also ensures better ability to detect bias by those laboratories with better precision.I t is also worth noting that the values of the maximum tolerable bias and standard devi-ation have a marked effect on the number of tests needed to detect such bias. For example, suppose that B is 5% at is 5% and that a laboratory just achieves the required precision. The number of tests required on each solution would on the above basis be approximately 15 a number that for several reasons would often be impracticable. Whenever possible one portion of each of the distributed solutions is analysed on each of five days. This approach makes some allowance for the possibility that bias can vary from day to day and thus provides an estimate of the average bias; see also section 2.9.5.How-ever if the stability of a distributed solution or the convenience of the laboratories require, all replicate analyses may be made on one day without great effect on the value of the informa-tion. 2.9.4 In the Harmonised Monitoring Scheme for each solution and laboratory the mean and its 90% confidence limits 5 4 h are calculated from the five individual results. The upper limit for the true bias (95% confidence level) is then calculated by the co-ordinating labora-tory as 5 + h - T if 5 > T (where T is the true value for the distributed solution) or as 5 - h - T if 3 < T. These expressions apply when the value of T is such that the maxi-mum tolerable bias is a fixed concentration (see section 2.3). For greater values of T where the target is a fixed percentage of T the corresponding expressions for bias become lOO(3 + h - T)/T and lOO(5 - h - T)/Tyo.If the estimated bias is greater than the maximum tolerable value laboratories are informed as soon as possible so that in general, Calculation of bias for each laborator 286 WILSON APPROACH FOR ACHIEVING COMPARABLE Analyst VOl. 104 possible causes of the bias can be sought and eliminated. In practice this assessment of bias also includes some subjective consideration. For example a laboratory whose bias marginally exceeded the maximum tolerable value for one solution but was well within the target for other solutions is usually considered acceptable. On the other hand a laboratory only just within the target for all solutions may well have need to check possible sources of bias.In this approach T is equated to the known concentration of the distributed standard solution. For samples of river water the value of T is not generally known and an approxi-mate value must be used. In the Harmonised Monitoring Scheme this value has generally been equated to the mean of results from all laboratories. This approach is considi.red reasonable given the preceding stages of Fig. 1 and the number of laboratories (11) involved,* but it is of course not necessarily correct. Careful consideration of the results from each test and of possible sources of bias in the analytical methods used is generally essential before assigning a value to T.' This problem can sometimes be much reduced if a sample can be obtained with a negligible concentration of the determinand but typical in all other respects.An accurately known amount of the determinand can then be added by the co-ordinating laboratory before distribution of portions of the spiked solution. In this situation the value of T can be determined with reasonably small error and this approach has been useful in connection with the determination of lead in drinking water.34 Similarly T would be known if bias is assessed from the difference between the results for spiked and unspilced portions of a distributed solution (see section 2.9.2). 2.9.5 Estimates of precision The results from these tests also provide estimates of the standard deviation st of analytical results for each of the distributed solutions. These estimates are poor in that they have only four degrees of freedom but it is useful to compare these estimates with the target values as in the tests of within-laboratory precision.If there has been any deteriora-tion of precision not revealed by the control chart(s) the upper limit for bias may be largely governed by the imprecision (&h) of the mean iresult rather than by bias. 2.9.6 Need for further inter-laboratory tests of bitzs On satisfactory completion of this final stage of Fig. 1 it is provisionally taken that laboratories have achieved the required accuracy. However precision and bias at this stage have been estimated for few sample types and both parameters may also deteriorate subsequently. As explained above the use of control tests will help to ensure that precision and certain sources of bias remain satisfactory but it is also considered essential to repeat the tests of between-laboratory bias regularly.As always the more frequent such tests and the greater the number of samples included in them the better will be the control. The effort involved is however substantial and at present in the Harmonised Monitoring Scheme, the tests are repeated at approximately 6-monthly intervals for each of the determinands studied to date. Further only one sample is distributed in each repeat test but the aim is to use samples of types different to those distributed in previous tests. 3 Conclusions The discussion above has shown that close attention must be paid to many different aspects of analysis if the accuracy of routine analytical results is to meet a specified and reasonable value.I t is worth stressing that virtually all the many points and suggestions mentioned in this long paper have been included because they have caused problems in one or more groups of laboratories with which the a.uthor has been involved. To overcome such problems permanently a systematic approach is essential and the scheme described here (summarised in Fig. 1) represents one such approach that has been found successful in the analysis of river and other waters. It is considered that the principles of this approach are of general value and validity but of course many detailed modifications are possible. The fact that the scheme is invol.ved and unlikely to achieve rapid progress is * The accuracy of the value used for T will all other things being equal improve as the number of laboratories increases April 1979 ANALYTICAL RESULTS FROM A NUMBER OF LABORATORIES 287 a disadvantage.However it seems to the author that it is only by a scheme of this nature that any progress will be achieved on a permanent and sound basis. Clearly there is no substitute for detailed consideration of each particular application and this may well suggest simplifications of value. Nevertheless such simplifications should only be undertaken after very careful consideration; experience shows that lack of success and wasted effort can result if short cuts are taken on insufficient evidence. Clearly effort is required to implement analytical quality control and the amount depends on the required accuracy the analytical methods and the degree of control considered appropriate.As a broad indication suggestions have been made that 10-20%11 or 15-20~0s of an analyst’s time should be devoted to quality-control work. This proportion may seem rather large and may be difficult to achieve in initially establishing an analytical quality-control scheme in a laboratory. Nevertheless such effort is considered a reasonable goal though initiation of control schemes should not be prevented if only a smaller amount of effort is available initially. Finally it is worth making the obvious point that it is not generally possible to obtain direct estimates of precision and bias for every sample that laboratories analyse. Hence, though in the author’s opinion analytical quality control should be an integral part of the work of a laboratory it cannot prove the accuracy of every result.Rather it provides valuable confirmatory evidence of the adequacy of all the various means adopted by the analyst to ensure the required accuracy. In other words the continuing and critical assess-ment by the analyst of all that he does remains as always of prime importance. In general a little control is better than none. Many colleagues have contributed to many aspects of the approach described in this paper. The author is grateful to them all but particular thanks are due to Messrs. R. V. Cheeseman D. J. Dewey I. R. Morrison and W. J. Wyse and for much guidance and advice on statistical aspects to Messrs. W. J. Allum J. C. Ellis R. E. Fry and R.F. Lacey. Thanks are also due to the author’s many colleagues in the Department of the Environment Water Authorities and River Purification Boards who operate the Harmonised Monitoring Scheme. Finally the author is also grateful to the Director of the Water Research Centre for per-mission to publish this paper. Appendix A few points of detail concerning the tests of within-laboratory precision are mentioned below. (a) The degrees of freedom of the estimates sw and s b are m(n - 1) and (m - l) respec-tively. The concept of degrees of freedom is not strictly applicable to the combined estimate st but a reasonable approximation is to assign f degrees of freedom to st where f is the integer nearest to the value of using the notation in reference 21. ( b ) In comparing an experimental estimate of a standard deviation with a target value by the variance-ratio test the target standard deviation has an infinite number of degrees of freedom.(c) For a given solution the precision of a laboratory is considered acceptable if st is not significantly greater (0.05 probability level) than the target value. Such values of st can be obtained when the population standard deviation ut is greater than the target value, i.e. the probability of an error of the second kind is much greater than 0.05. If desired this probability can be decreased by increasing the number of replicate analyses used to estimate st26S27 but the number corresponding to a probability of 0.05 will normally be impracticable. An estimate st is obtained for each of several solutions and this provides an opportunity to judge whether or not there is a general tendency for all s t values to approach or exceed the targets.Three points reduce though they do not eliminate this problem. (i 288 WILSON APPROACH FOR ACHIEVING COMPARABLE Analyst VoZ. 104 (ii) Subsequent tests (see section 2.8) will provide more precise estimates of at. (iii) By aiming to use methods capable of rather better precision than required there will be a tendency to obtain at values less than the targets. ( d ) To ensure valid estimates of ab and at the concentration of the determinand in a given solution must be the same for all batches of analyses. When determinands are unstable, this condition can be satisfied for standard solutions by using freshly prepared solutions for each batch However for samples no direct estimates of ab and at are possible and the following approximate approach is followed.A freshly collected sample is used for each batch these m samples being selected so that the determinand concentration is approxi-mately the same in each. Alternatively the same sample can be used for all batches provided its concentration of determinand changes by no more than approximately 20%. On completion of the m batches sw s b and st are calculated for standard solutions and sw is calculated for samples. The assumption is then made that the between-batch random error is due only to uncorrected variations in the calibration graph from batch to batch. On this basis and when the analytical response is directly proportional to the concentration of the determinand (Tb is independent of the type of solution and is also directly proportional to concentration ie.ab = kC. An approximate value of k can therefore be obtained from values of s b for standard solutions. Thus an approximate value for s b for a sample can be obtained from its mean concentration and the estimated value of k . Finally st for a sample can then be calculated from .st = .\/(s + ~ 2 ) . (e) The limit of detection (0.05 probability of errors of the first and second kinds) is given by 4.65aw where ow is the within-batch standard deviation of blank determinations (in concentration units) ,14915 provided that : (i) an analytical result is obtained by making one measurement each of a blank and a sample the apparent concentration of the blank being subtracted (in fact or in effect) from that of the sample; (ii) the apparent concentrations of any solution of low concentration follow the normal distribution; and (iii) the within-batch standard deviation of the apparent concentrations for any solution of low concentration is independent of the concentration of the determinand and is the same for blanks and samples.If any one of these conditions is not satisfied other expressions for the limit of detection are req~ired.1~ 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. References Biittner J. Borth R. Boutwell J. H. and Broughton P. M. G. Clinica Chim. Acta 1976 63, Eisenhart C. J . Res. Natn. Bur. Stand. 1963 67C 161. Simpson E.A. J . Inst. Water Engrs Scient. 1978 32 45. Wilson A. L. Talanta 1965 12 701. Research and Development Department Central Electricity Generating Board “Methods of Sampling and Analysis Volume 1. Analytical Quality Control Laboratory “Handbook for Analytical Quality Control in Water and Wastewater Laboratories,” US Environmental Protection Agency Cincinnati 1972. Cheeseman R. V. Technical Memorandum TM 96 Water Research Centre Medmenham Bucks., 1974. Wilson A. L. “The Chemical Analysis of Water,” Analytical Sciences Monograph No. 2 Society for Analytical Chemistry London 1974. Gans I. and Sonneborn M. in Aurand K. Hasselborth U. Miiller G. Schumacher W. and Steuer W. Editors “Die Trinkwasser-Verordnung,” Erich Schmidt Verlag Berlin 1977 pp. 181-195.Green A. C. and Naegele R. Report EPA-600/4-77-031 US Environmental Protection Agency, Cincinnati 1977. Wilson A. L. J . Inst. Water Engrs Scient. 1978 32 57. Ekedahl G. Rondell B. and Wilson A. L. “Analytical Errors” in “Manual on Analysis for Water Allen H. E. and Mancy K. H. in Ciaccio L. Id. Editor “Water and Water Pollution Handbook, Roos J . B. Analyst 1962 87 832. Currie L. A. Analyt. Chem. 1968 40 586. McFarren E. F. Lishka R. J. and Parker J. H. Analyt. Chem. 1970 42 358. Eckschlager K. Analyt. Chem. 1972 44 878. F25. Steam and Water,” 1966. Pollution Control,’’ World Health Organization Geneva in the press. Volume 3,” Marcel Dekker New York 1972 pp. 971-1020 Apri1 1979 ANALYTICAL RESULTS FROM A NUMBER OF LABORATORIES 289 18. 19. 20. 21.22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 34. Biittner J. Borth R. Boutwell J. H. Broughton P. M. G. and Bowyer R. C. Clinica Chim. Wilson A. L. Talanta 1970 17 21. Wilson A. L. Talanta 1974 21 1109. Wilson A. L. Talanta 1970 17 31. Wilson A. L. Talanta 1973 20 725. “Standing Committee of Analysts to Review Standard Methods for Quality Control of the Water Cycle. Standing Technical Committee Reports Number 7 Department of the Environment/National Water Council London 1977. Department of the Environment/National Water Council “Lead in Potable Waters by Atomic Absorption Spectrophotometry 1976,” Methods for the Examination of Waters and Associated Materials HM Stationery Office London 1977. ISO/R78-1969(E) International Standardization Organization Geneva 1969. Davies 0. L. Editor “Design and Analysis of Industrial Experiments,” Second Edition Oliver and Boyd Edinburgh 1956. Davies 0. L. and Goldsmith P. L. Editors “Statistical Methods in Research and Production,” Fourth Revised Edition Oliver and Boyd Edinburgh 1972. Bennett C. A. and Franklin N. L. “Statistical Analysis in Chemistry and the Chemical Industry,” Chapman and Hall London 1954. Nalimov V. V. “The Application of Mathematical Statistics to Chemical Analysis,” Pergamon Press Oxford 1963. Wilson A. L. Technical Memorandum TM 56 Water Research Association Medmenham Bucks., 1970. Woodward R. H. and Goldsmith P. L. “Cumulative Sum Techniques,” Oliver and Boyd Edin-burgh 1964. Griffin D. F. Am. J. Med. Technol. 1968 34 644. Ranson L. and Wilson A. L. Technical Report TR 28 Water Research Centre Medmenham, Bucks. 1976. Ada 1976 69 F1. First Report May 1973- January 1977.” Received September 1 lth 1978 Accepted November 2nd 197

ISSN:0003-2654    

DOI:10.1039/AN9790400273

出版商:RSC    

年代:1979

数据来源: RSC

摘要:

290 Analyst, April, 1979, Vol. 104, p p . 290-298 Accuracy of Determination of Chloride in River Waters: Analytical Quality Control in the Harmonised Monitoring Scheme Analytical Quality Control (Harmonised Monitoring) Committee" Water Research Centre, Henley Road, Medmenham, Marlow, Buckinghamshire, SL7 2HD The Department of the Environment, in collaboration with the Regional Water Authorities, has initiated a Scheme for the Harmonised Monitoring of the Quality of Inland Fresh Waters in England and Wales. The Scottish Development Department has introduced a similar scheme in Scotland in collaboration with the Scottish River Purification Boards. To achieve the required comparability of results from all laboratories involved, each labora- tory takes part in an analytical quality control (AQC) scheme; this work is co-ordinated by the Water Research Centre.The general approach adopted to AQC has been described, and this paper presents the tests made and results obtained in the determination of chloride in river waters. Broadly, each of the ten participating laboratories achieved total errors not greater than *ZO% of the chloride concentration for concentrations greater than 5 mg 1-1 of chloride. Keywords : River-water analysis ; chloride determination ; accuvacy of results ; inter-laboratory comparability ; analytical quality control The scheme for the Harmonised Monitoring of the Quality of Inland Fresh Water has been described recently in detail.1 It is intended to provide objective data on river water quality so that accurate assessments can be made of long-term trends in the qualities of rivers and of the amount of material discharged by them to the sea.The Scheme complements moni- toring carried out for regional or local purposes and one of its essential aims is to achieve comparability of the results from all participating laboratories. To that end, special investi- gations have been made to establish suitable locations for sampling and to define the necessary sampling frequencies. Sampling procedures have been harmonised, and to ensure that subsequent analyses do not introduce unacceptably large errors, each participating laboratory carries out a specially designed programme of tests to ensure that their analytical results are of adequate accuracy for the Scheme. The Water Research Centre (WRC) is under contract to the Department of the Environment to advise on and co-ordinate this analytical quality- control (AQC) programme.The need for, and details of an approach to, a planned AQC system for this and similar schemes have been discussed in some detail elsewhere in this issue.2 In view of the growing interest in achieving comparable results from each of a number of laboratories, it was thought useful to describe the AQC work for the Harmonised Monitoring Scheme and to present the results obtained for different determinands. This paper considers the determination of chloride and subsequent papers will deal with other determinands of general importance in rivers. Chloride was chosen for the first study of the Committee because serious problems in achieving the required accuracy were not expected and it was considered, therefore, that this would facilitate the introduction of the AQC programme.The work presented in this paper was originally published as a WRC Technical R e p ~ r t . ~ Organisation of the Work A Committee was formed to plan the collaborative work, and has representatives? from the Department of the Environment, Scottish Development Department, each Regional * Communications concerning this paper should be addressed to D. J. Dewey, at the Water Research t The names of representatives a t the time the work reported here was carried out are given in the Centre. Appendix.ANALYTICAL QUALITY CONTROL (HARMONISED MONITORING) COMMITTEE 291 Water Authority (RWA), Scottish River Purification Boards and the WRC. This Com- mittee decided to adopt the approach to the AQC described elsewhere in this issue,2 each determinand being studied in two phases.Phase (i). One laboratory in each of the ten RWAs and one in Scotland participated, the WRC acting as the co-ordinating laboratory2 ; eleven laboratories were generally involved. Phase (ii). After satisfactory results have been obtained in Phase (i), those laboratories act as co-ordinators of tests within RWAs and Scotland. Certain RWAs are not involved in this phase because all analyses for Harmonised Monitoring are made by one laboratory. This paper deals only with Phase (i). Required Analytical Accuracy The following requirements were agreed by the Committee to represent the targets a t which to aim2; maximum tolerable bias, 10% of the chloride concentration or 0.5 mg 1-1 of chloride, whichever is the greater; and maximum tolerable total standard deviation, 5% of the chloride concentration or 0.25 mg 1-1 of chloride, whichever is the greater.Analytical Quality Control The approach followed was exactly as presented previously2; no attempt is made here, therefore, to explain the reasons underlying the various activities described below. The South West Water Authority was unable to participate in the tests reported here though it has now undertaken the work. The participating laboratories were : Anglian Water Authority, Welland and Nene River Division Laboratory, Oundle ; Northumbrian Water Authority, Headquarters Laboratory, Gosforth; North West Water Authority, Mersey and Weaver River Unit Laboratory, Warrington ; Severn-Trent Water Authority, Regional Laboratory, Finham ; Southern Water Authority, Resource Planning Laboratory, Winchester ; Thames Water Authority, Thames Conservancy Division Laboratory, Reading; Welsh Water Authority, Dee and Clwyd River Division Laboratory, Chester ; Wessex Water Authority, Bristol Avon Divisional Laboratory, Saltford; Yorkshire Water Authority, Headquarters Laboratory, Leeds ; and Forth River Purification Board, Headquarters Laboratory, Edin- burgh.The sequence of participating laboratories in the above list does not relate to the order of numbering of laboratories in the Tables. Choice of Analytical Methods Participating laboratories each chose a method they thought capable of achieving the required accuracy.The methods involved were (i) manual Mohr t i t r a t i ~ n , ~ (ii) manual mercury(I1) nitrate - diphenylcarbazone titration4 and (iii) semi-automatic continuous flow spectrophotometric methods based on the procedure in reference 5 [mercury(II) thiocyanate - iron(II1) salt]. One of the laboratories initially selected a commercially available instrument for the coulometric titration of chloride. Preliminary tests showed, however, that the discrimina- tion with which the instrument response could be read did not allow achievement of the required precision at low concentrations (below 10 mg 1-l). This procedure was, therefore, abandoned, and the laboratory adopted method (iii). Within-laboratory Precision and Recovery Tests Following any preliminary tests considered necessary by the laboratories, each then carried out the same programme of tests to assess the precision of, and certain sources of bias in, its results.Laboratories using method (iii) checked that their calibration graphs were linear. All laboratories, on each of 10 days, carried out in random order a batch of analyses consisting of two blank determinations and two portions of each of the following solutions, two standard solutions, a river water and the same river water after addition of a known amount of chloride. Each laboratory collected its own sample of river water from a local source and the same sample was used throughout the tests. The amount of chloride added to the spiked sample varied from laboratory to laboratory, but was in the range 0.2-0.5 Cu, where C, is the upper concentration limit of a laboratory’s method.Each laboratory292 ANALYTICAL QUALITY CONTROL (HARMONISED MONITORING COMMITTEE) : Analyst, Vol. 104 prepared its own standard solutions from its own stock standard solution just before each batch of analyses. The concentrations of the two standards used for the tests were usually 0.1 C, and 0.9 C,. On completion of the tests, each laboratory analysed its results statistically to obtain estimates of the within-batch (sw), between-batch (sb) and total (st) standard deviations,6 where st = d ( s i + sg). The values of st for the two standards, the river water and the spiked river water were compared with the appropriate target value using the F-test,2 and were accepted as satisfactory provided st was not significantly greater (9 = 0.05) than the target.2 The results from these tests are summarised in Table I.For the particular solutions used the chloride concentrations were such that the target for precision was a relative total standard deviation not greater than 5%. This value was exceeded in only three instances, Laboratories 1 and 7 river water and Laboratory 6 standard solution (20 mg 1-1 of chloride). However, in those instances the observed relative standard devi- ations were only marginally, and not significantly, greater than 5%. The results were, therefore, considered acceptable. It is further of interest to note that estimates of precision varied considerably between laboratories, even for the analysis of standard solutions of similar concentration.Of course some of these differences reflect random uncertainty in the estimates of precision. However, some differences between estimates are sufficiently large to indicate real differences in the precision of results obtained by individual laboratories. This reflects differences in the choice of method used and its application in individual laboratories. However, these differences were not important in the context of this exercise and, it is emphasised again, results were within the targets set other than the exceptions discussed above. Each laboratory also calculated the recovery, R, of chloride from the spiked river water, where R = 100 (cs - C,)/A, and c, and c, are the mean concentrations found for the spiked and unspiked river water, respectively, and A is the equivalent concentration of chloride added to the spiked sample, allowance being made for the slight dilution of the sample caused by the addition of a standard solution of chloride.It was agreed that recoveries would be considered acceptable if R was not significantly worse (t-test, p = 0.05) than the closer of the two values, 95 and 105%. These results are also summarised in Table I, which shows recoveries between 95 and 104% with an over-all mean of 99.6%. None of the individual recoveries were significantly worse than 95 or 105% and the results were, therefore, considered acceptable. The satisfactory completion of these tests in all laboratories indicated that within-laboratory precision was adequate and the next stage of the AQC work was started.Accuracy of Standard Solutions To ensure that differences in the chloride concentrations of laboratories’ standard solutions did not cause important between-laboratory bias, the following tests were made. The WRC prepared a standard solution of sodium chloride (1 000 mg 1-1 of chloride) and portions were sent to all laboratories. Each laboratory then accurately diluted portions of the WRC solution and its own standard solution to nominally the same concentration, which was usually at or near C, so as to achieve the smallest relative standard deviation. Sufficient replicate analyses of both the diluted standards were made in one batch of analyses so that if there were a difference of 2% in their true concentrations, a statistically significant difference (95% confidence level) between the two means would be found.The required number of analyses on each standard was calculated statistically using the estimates of within-batch standard deviation obtained in the preceding stage of the work.2 On completion of the tests, each laboratory compared the mean values obtained for each standard (t-test, p = 0.05) and the results are summarised in Table 11. None of the labora- tories’ standards differed from the WRC by as much as 2%, the maximum observed difference was 0.4% and the over-all mean difference was 0.1%. These results were consideredsatis- factory. Each laboratory then set up a preliminary statistical quality control chart2 based on the analysis of a standard solution in each subsequent batch of analyses. These charts are intended to aid the continuing, long-term assessnient of accuracy in each laboratory and are not further discussed here.TABLE I RESULTS FROM WITHIN-LABORATORY PRECISION TESTS Laboratory No.and analytical method* Sample Standard solution 1 . Standard solution 2 . River water . . . Spiked river water . Parameter Chloride concentration/mg 1-I Relative total standard deviation,? yo Total standard deviationtlmg 1-l Chloride concentration/mg 1-I Relative total standard deviation,? % Total standard deviationt/mg 1-l Chloride concentration/mg 1-I Relative total standard deviation,? yo Total standard deviationtlmg 1-l Chloride concentration/mg 1-l Relative total standard deviation,? yo Total standard deviationtlmg 1-' Mean recovery of chloride from spiked river water,$ % r 1, M 2, M 2.6 (0.0) 0.65 (0.0) 0.26 0.20 0.52 0.49 6.1 54 5.1 1.3 0.31 0.68 25 50 200 250 106 99 0.36 0.59 0.38 0.58 100.0 f 0.1 101.5 f 1.1 3, MN 20 1.5 0.29 180 0.23 0.42 47 1.2 0.55 139 0.50 0.70 99.2 f 0.5 4, MN 5, SA 8 20 1.5 3.6 0.12 0.71 0.18 0.89 0.14 1.6 0.57 2.2 0.09 0.94 0.11 1.9 0.07 2.4 80 180 16 42 65 124 99.8 f 0.1 94.7 f 1.9 6, SA 20 6.0 1.2 1.2 2.1 40 180 2.2 0.89 1.2 1.6 104.2 f 1.0 137 7, SA 8, SA 9, SA 30 5 5 3.7 3.8 3.4 1.1 0.19 0.17 270 45 45 1 .o 0.33 0.93 2.7 0.15 0.42 5.4 0.92 3.1 0.97 0.24 0.71 18 26 23 111 45 36 1.4 0.42 2.8 1.5 0.19 1 .o 98.6 f 1.0 96.4 f 1.2 102.6 f 3.1 * M = Mohr titration'; MN = mercury(I1) nitrate titratiod; SA = semi-automatic spectrophotometric method based on reference 5 (see Choice of Analytical Methods). t The total standard deviations have between 9 and 19 effective degrees of freedom.' $ 95% confidence limits of the mean recovery are also given.10, SA' 4.2 0.84 20 180 0.89 1.6 53 2.9 1.5 144 0.96 1.4 99.1 f 0.8294 ANALYTICAL QUALITY CONTROL (HARMONISED MONITORING COMMITTEE) : Analyst, VoZ. 104 TABLE I1 COMPARISON OF PARTICIPANTS' AND WRC STANDARD SOLUTIONS Mean difference between laboratory Laboratory and WRC standards,* % 1 -0.16 f 0.05 2 -0.05 f 0.29 3 0.33 f 0.96 4 0.35 f 0.17 5 0.14 & 0.99 6 0.09 f 0.83 7 0.30 f 0.57 8 0.07 f 1.00 9 0.07 f 0.58 10 0.00 f 0.55 Mean 0.11 * The 95% confidence limits of the mean difference are also given. Tests of Between-laboratory Bias To complete this initial phase of AQC, direct checks of any between-laboratory bias were made as follows.The WRC prepared and distributed portions of a standard solution (46.0 mg 1-1 of chloride) and samples of two different river waters to all laboratories, each participant being given only a broad indication of the concentration of these solutions. One of the river samples was a hard, lowland water, and the other was of the soft, moorland type. Each laboratory analysed each solution once on each of 5 days, and then calculated the mean of the five results and its 90% confidence limits (obtained from the five results only) for each solution. These results were then returned to the WRC for examination for any evidence of bias. For each solution, tests were made to decide if the mean result from any laboratory could be regarded as a statistical outlier.' No such outliers were indicated ( p = 0.05) for the two river waters.For the standard solution, the result from Laboratory 5 just achieved signifi- cance, but neglect of this result only changed the over-all mean from 46.0 to 45.7 mg 1-1 of chloride. In view of this small difference and because no reasons for regarding the result as suspect were known, it was thought better not to reject the result of Laboratory 5. The results in Table I11 show that the confidence intervals of the mean results of different laboratories for a given solution do not all overlap, i.e. , a certain amount of between-laboratory bias exists. To assess whether or not the bias of any laboratory exceeded the target value of loyo, the following procedure was used.2 Denoting the mean and its 90% confidence limits for a given solution and the ith laboratory by Xi hi, the upper limit (95% confidence) for the bias of the laboratory, U , was calculated as follows: if Zi > T , 100 (Zt + hi - T ) T U = or, if Zi < T, 100 (Xi - hi - T ) T U = where T is the true concentration of chloride in the standard solution or the over-all mean concentration of chloride in the river waters. For this purpose, the over-all means for the river waters were calculated from the means of individual laboratories, no weighting for the precisions of the means being used.The values for U are also given in Table 111, which shows that they were usually substantially less than the maximum tolerable bias of 10%. In only two instances did U exceed the target and then only marginally (Laboratories 6 and 8 for river water B).However, the mean results of these two laboratories were within 5% of the over-all mean for that sample and their values of U for the other two solutions were much smaller than 10%. It was decided, therefore, that the results from all laboratories could be regarded as satisfactory.RESULTS FRO1 TABLE I11 TESTS OF BETWEE ABORATORY BIAS Mean of all Sample Parameter 1, M 2, M 3, MN 4, MN 5, SA 6, SA 7, SA 8, SA 9, SA 10, SA tories Laboratory No. and analytical method* c r , labora- Standard chloride solution, 46.0 mg I-' Mean chloride contenttlmg 1-l 46.0 f 0.1 45.0 & 0.3 46.0 f 0.4 45.9 f 0.1 48.0 + 0.9 46.0 f 1.2 45.8 + 1.6 45.0 f 0.2 46.1 + 0.4 46.2 + 0.4 46.0 River water A .. Mean chloride contentt/mg 1-l 97.9 f 0.2 97.4 f 0.5 97.0 f 0.3 96.7 f 0.2 94.6 f 1.0 95.7 f 1.5 97.2 & 1.6 95.2 f 0.3 97.1 f 0.2 8 96.57 River water B . . Mean chloride contentt/mgl-l 8.52 f 0.17 8.28 & 0.13 8.80 0.23 8.39 & 0.11 8.90 f 0.40 8.24 f 0.60 8.60 -+ 0.52 9.02 f 0.43 8.48 f 0.38 8.60 f 0.52 8.587 Upper limit for bias,$ % f0.2 - 2.7 fO.9 -0.5 + 6.3 12.7 - 3.8 -2.6 +1.2 +1.4 - Upper limit for bias,$ yo + 1.6 +1.4 +0.8 + 0.4 - 3.0 - 2.4 + 2.4 -1.6 + 0.8 § - Upper limit for bias,$ % - 2.7 - 5.0 + 5.2 - 3.5 +8.4 -11.0 +6.2 +10.1 - 5.6 +6.3 - Mean upper limit for bias for the three above solutions, % - .0.4 - 2.1 + 2.3 - 1.2 + 3.9 - ,5.4 +1.6 + 2.0 - +3.9 - 1.2 * M = Mohr titration'; MN = mercury(I1) nitrate titration4; SA = semi-automatic spectrophotometric method based on reference 5 (see Choice of Analytical Methods).t The goo/, confidence limits are also given for each mean. $ See text for method of calculating the upper limit (95% confidence) for bias. 5 This laboratory originally conducted the work on another semi-automatic system and repeated all the tests on changing to the present system. Insufficient sample of river water A remained for tests fl The values obtained by the WRC for river waters A and B were 96.2 and 8.48 mg 1-l of chloride, respectively. with the new system. t9 W 01296 ANALYTICAL QUALITY CONTROL (HARMONISED MONITORING COMMITTEE) : Analyst, VoZ. 104 At this point the objectives of the initial AQC programme had been achieved, and a similar programme was started for the next determinand of interest, ammoniacal nitrogen.Routine AQC To attempt to ensure that the required accuracy of results for chloride is maintained, AQC is now an integral part of the routine analyses for the Harmonised Monitoring Scheme. As mentioned above, prime reliance for this purpose is placed on within-laboratory AQC using statistical quality control charts. However, to obtain direct checks of between- laboratory bias, portions of a river-water sample are distributed occasionally by the WRC to all laboratories. The first four such tests (over a period of approximately 2 years) are of value in indicating the efficiency of the AQC work, and are, therefore, summarised in Table IV. Each of these tests was carried out as described in the previous section except that, for the fourth test, the five replicate analyses were all made in one batch of analyses.Table IV shows that the upper limit (95% confidence level) for bias is usually less than 10% and that the mean of the individual upper limits is less than 10% for each laboratory. Overall, therefore, it appears that reasonably satisfactory accuracy has been maintained. However, the need for continuing care and emphasis on AQC is indicated by the fact that certain laboratories appear to be rather prone to bias close to or slightly exceeding the target. Therefore, of the 40 sample - laboratory combinations, eight provide upper limits for bias of greater than 10%; of these eight instances, Laboratory 10 gave three, and Laboratories 5 and 9 each gave two.Each laboratory calculated the standard deviation from the five results for each sample. Of the first three tests (for which the relative total standard deviation could be calculated), no laboratory obtained any values significantly greater (j5 = 0.05) than the target of 5% and only four of the values were greater than 5%. It appears, therefore, that precision was maintained reasonably well. TABLE IV RESULTS FROM ROUTINE TESTS OF BETWEEN-LABORATORY BIAS River water C River water D River water E River water F (September 1975) (April 1976) (March 1977) (December 1977) 7-p- Mean Mean Mean Mean chloride Upper limit chloride Upper limit chloride Upper limit chloride Upper limit Mean upper content/ for bias, content/ for bias, content for bias, content/ for bias, limit for Laboratory mg 1-1 % mg 1-1 % mg 1-l % mg 1-I % bias, yo 1 2 3 4 5 6 7 A 9 10 Meant 17.5 + 3.5 58.0 + 2.6 29.8 + 5.3 18.1 + 5.7 56.8 - 1.2 29.4 + 3.3 17.6 + 3.9 56.2 - 2.8 27.4 - 6.3 16.5 - 4.9 56.0 - 2.1 29.0 + 1.6 15.6 - 14.4 59.0 + 4.2 26.0 - 12.5 15.4 -15.5 54.4 - 8.5 28.8 + 5.8 11.4 + 4.1 56.6 - 3.3 28.8 + 3.4 16.8 - 6.4 57.0 + 0.2 29.6 + 3.6 18.7 +11.1 58.8 + 3.9 31.6 +12.2 65.0 +16.8 26.4 -16.9 - 57.0 - 28.7 18.6 17.2 - +11.0 37.4 +2.5 37.1 + 1.7 34.6 - 7.2 35.6 -3.5 34.0* -7.3 37.0* +0.9 40.0* + 9.1 36.0* -1.8 37.02 + 0.9 36.8 + 1.5 36.7 - + 3.5 +2.4 - 3.1 - 2.2 - 7.5 -4.3 + 3.3 - 1.2 + 7.0 + 3.1 - * The five results were reported as identical.t No laboratory’s results were rejected in calculating the over-all mean for samples C, E and F; the result of Laboratory 10 was rejected for sample D.Discussion The detailed results provide evidence on a number of points relevant to the design of AQC schemes for a group of laboratories, e.g., the dependence of standard deviation on the con- centration of the determinand and the relative importance of different sources of error. However, discussion of such aspects is best deferred until the results for other determinands and analytical techniques have been published. One point is worth a brief mention here, namely the suitability of the accuracy targets for chloride. The targets for systematic and random errors imply that the tolerable total error (95% confidence level) of individual analytical results is 20% of the chloride concentration or 1 mg 1-1 of chloride, whichever is the greater.The former target may well be thought rather lax, particularly as chloride is usually regarded as a determinand for which good accuracy is readily achieved. It is interesting, therefore, to consider the consequences ofApril, 1979 ACCURACY OF DETERMINATION OF CHLORIDE I N RIVER WATERS 297 reducing the maximum tolerable errors to half the values used in this work. If the experi- mental estimates of errors in this paper were compared with these reduced targets in the manner described above, the following targets would not be achieved : precision tests from Laboratories 1, 6 and 7 ; recovery tests from Laboratories 5 and 6; accuracy of standard solutions from Laboratories 3, 5 and 8; and between-laboratory bias from Laboratories 3, 5, 6, 7, 8, 9 and 10.In contrast, with the targets adopted in this work, only two instances occurred where the targets were exceeded, i.e., Laboratories 6 and 8 in the tests of between-laboratory bias. This analysis suggests that substantially greater effort would be required in most laboratories to achieve the smaller targets routinely. Hence, the idea that better accuracy than that aimed for in this work can readily be achieved would seem to be incorrect even for chloride, which is normally regarded as being determined with good accuracy and precision. The approach to AQC described in this paper aims progressively to identify and, if necessary, control particular sources of error so that a permanently sound basis is established for routine achievement of the required accuracy.2 The individual tests are, therefore, designed to provide many opportunities for unsuspectedly large errors to reveal themselves.Of all the tests described above, none gave positive evidence that a target was not achieved, although there were several instances where the results indicated that a target could have been exceeded, e.g., the bias of Laboratories 6 and 8 for river water B could have exceeded the target of 10% (see Table 111). Such uncertainties are bound to arise as a result of random errors, and in this situation, a partially subjective judgement on the basis of the complete set of tests is necessary. In this way, it is considered reasonable to conclude that all laboratories achieved the required accuracy in the preliminary AQC work.The results of subsequent tests (see Table IV) indicate that this accuracy has been maintained over a period of almost 3 years. So far as is known, this is the first time that such an achievement has been reported for the analysis of river waters. The success of the work is attributed to two main factors: (i) the suitability of the analytical methods adopted by the laboratories; and (ii) the sequential approach followed in the AQC programme. The latter involves a relatively large amount of work in each laboratory and a rather long period is necessary to complete all tests. These are disadvantages in the approach, but they are counterbalanced by its ability to ensure that the required accuracy is achieved. Most of the participating laboratories had no previous experience of this type of work, but all agreed that the approach should be retained for tests on other determinands and it is hoped to report the results in subsequent papers.Conclusions The targets chosen for accuracy and precision of results appear to be suitable for the Harmonised Monitoring Scheme and capable of achievement for the river waters tested. All participants achieved the required accuracy during the tests. To ensure that the position is maintained, continuing care is needed, and subsequent analytical quality control will, in addition to normal precautions, be based mainly on the use of quality-control charts and the analysis of samples distributed at regular intervals by the WRC. The work has confirmed that each of three types of method [i.e., (i), (ii) and (iii) in the section Choice of Analytical Methods] are capable of achieving the target accuracy.Valuable experience of this collaborative work has been gained. The participating laboratories have commented favourably on the approach adopted and on the co-ordination of the work by the WRC. This approach is now being applied to successive studies of other determinands, the results for which will be reported in subsequent papers. For those Authorities with more than one participating laboratory, the tests within each area (Phase ii) need to be completed before the over-all situation can be regarded as satis- factory. The results in this paper suggest that no undue problems are to be expected in this second stage of testing. The work has demonstrated a procedure for ensuring permanent comparability of results from many laboratories, Already some of the Authorities have taken advantage of this by extending the procedure to laboratories not directly concerned with the Harmonised Moni- toring Scheme.Such extensions are recommended.298 ANALYTICAL QUALITY CONTROL (HARMONISED MONITORING) COMMITTEE Appendix The following were members of the Analytical Quality Control (Harmonised Monitoring) Committee at the time of the initial work on chloride: Mr. A. L. Wilson, Chairman (Water Research Centre), Dr. E. A. Simpson, Secretary (Department of the Environment), Mr. M. J. Beard (Southern Water Authority), Mr. J. R. Borland (Welsh Water Authority), Mr. R. V. Cheeseman (Water Research Centre), Mr. N. Croft (Yorkshire Water Authority), Dr. B. T. Croll (Anglian Water Authority), Mr. D. V. Hopkin (Thames Water Authority), Mr. J. G. Jones (Wessex Water Authority), Mr. P. Kingslan (Department of the Environ- ment), Mr. J. C. Lambie (Scottish Development Department), Mr. B. Milford (South West Water Authority), Mr. P. Morries (North West Water Authority), Mr. B. D. Ravenscroft (Northumbrian Water Authority), Mr. D. Rodda (Water Data Unit), Mr. J. E. Saunders (Welsh Office), Dr. K. C. Wheatstone (Severn-Trent Water Authority), and Mr. T. William- son (Forth River Purification Board). 1 . 2. 3. 4. 5. 6 . 7 . References Simpson, E. A., J . Inst. Wat. Engrs Scient., 1978, 32, 45. Wilson, A. L., Analyst, 1979, 104, 273. Analytical Quality Control (Harmonised Monitoring) Committee, “Accuracy of Determination of Chloride in River Waters,” Technical Report TR 27, Water Research Centre, Medmenham, Bucks., 1976. Department of the Environment, “Analysis of Raw, Potable and Waste Waters,” HM Stationery Office, London, 1972, pp. 73-76. Zall, D. M., Fisher, D., and Garner, M. D., Analyt. Chew., 1956, 28, 1665. Wilson, A. L., Talanta, 1970, 17, 31. Davies, 0. L., and Goldsmith, P. L., Editors, “Statistical Methods in Research and Production,” Fourth Revised Edition, Oliver and Boyd, Edinburgh, 1972, pp. 49-50. Received September l l t h , 1978 Accepted November 2nd, 1978

ISSN:0003-2654    

DOI:10.1039/AN9790400290

出版商:RSC    

年代:1979

数据来源: RSC

摘要:

Anabst, April, 1979, Vol. 104, $9. 299-312 299 Statistical Appraisal of Interference Effects in the Determination of Trace Elements by Atomic-a bsorption Spectrop hotometry in Applied Geochemistry Michael Thompson, Stephen J. Walton and Shirley J. Wood Applied Geochemistry Research Group, Department of Geology, Imperial College, London, S W7 2BP Interference effects in the determination of trace elements by atomic- absorption spectrophotometry in applied geochemistry have been studied by a statistical appraisal and described in terms of a simple two-parameter mathematical model. The experimental design incorporated features that would allow possible deviations from the model to be detected, but no serious deviations were detected except in a deliberately chosen example. The study led to the identification of some important interference effects that could affect interpretation of geochemical data and also provided a formula that could be applied to correct the crude results.Keywords : Applied geochemistry ; mineral exploration ; atomic-absorption spectrophotometry ; interferences ; chemometrics Flame atomic-absorption spectrophotometry is by far the most frequently used analytical method in applied geochemistry, whether in the field of mineral exploration or of environ- mental studies. Although sample media and dissolution techniques vary, most commonly a rock, soil or sediment sample is treated with a mineral acid or mixture of acids to release into solution the trace elements of interest, notably copper, lead, zinc and nickel.1,2 Depending on the mineralogy of the sample and the acids used, considerable concentrations of the major metallic constituents of such samples are present in the solution presented for analysis.These elements (calcium, magnesium, iron, aluminium, sodium and potassium) are known to cause a variety of interferences, but apart from background correction by means of a continuum source, the effects are largely ignored in applied geochemical work.334 This is because, to be cost-effective, geochemical analyses have to be simple, rapid and cheap. Procedures such as solvent extraction, which separate the trace elements of interest from the major constituents, are usually inadmissible for this reason. Matrix matching is not usually practicable because wide variation in bulk composition within a batch of samples is common.In view of this widespread use of atomic-absorption spectrophotometry in applied geo- chemistry it is desirable to have a comprehensive and readily applicable account of the interference effects, so that circumstances where the interference is intolerable (i.e., likely to produce an incorrect interpretation of the data) can be identified. Govett and Whitehead5 have studied the effects of the major constituents on the deter- mination of trace amounts of copper, zinc, cobalt and nickel. At low concentrations of the major elements, it was found that the main effects were enhancements due to background absorption. At higher concentrations the enhancements were diminished or even reversed. The effects were found to depend on the concentrations both of the major elements and of the trace elements.However, no clear conclusion was drawn (except the need for caution), because of the difficulty of generalising the results obtained in the absence of any simple mathematical model. A further difficulty in interference studies is the possibility of complex interactions between the major constituents, producing effects on the apparent concentration of the trace analyte that are not predictable from results obtained with each major constituent separately. This difficulty has been pointed out by Woodis et aL6 and Thompson et al.' Usually the possi- bility of complex interactions is ignored because of the difficulty in elucidating them. A simple way to detect such interactions for two interfering elements would be to obtain a three-dimensional response surface at a fixed concentration of the trace analyte, representing300 THOMPSON et al.: STATISTICAL APPRAISAL OF INTERFERENCE Analyst, VoE. 104 the apparent level of the element as a function of the two interferents. This procedure would require at least a 10 x 10 matrix of points to obtain a reasonable representation of the surface, and the experiment would have to be repeated at several analyte concentra- tions. However, this approach would scarcely be possible for more than two interferents because of the large number of possible combinations and the difficulty of representing a surface in more than three dimensions. In this study, we used a simple mathematical model of interference, which greatly facilitated the interpretation of the results obtained and led to straightforward decisions as to whether interference was likely to be important.The model is the same as one that has been widely and successfully used in X-ray fluorescence analysis,* but has not, apparently, been fully developed in atomic-absorption work. An experimental design, based on the model, was devised to enable the results to be obtained with the minimum of effort, to allow the data to be tested for possible deviations from the mathematical model and, for the elements studied, to confirm the absence of complex interactions. Where an interference effect was found to be important, the coefficients derived from the data provided correction factors that could be used to improve considerably the accuracy of the raw result. While our conclusions would be expected to have broad generality in geochemical work, the magnitude of the effects are liable to vary with different instrumental arrangements and operating conditions.Consequently, the data presented in this work should be regarded as illustrating the method of investigation. Theoretical Model Interference of a major constituent on a trace analyte can be considered to consist of two components, one independent of the trace analyte concentration and the other dependent on it. In terms of the effect on a trace element calibration graph, these can be considered as a translational effect and a rotational effect as shown in Fig. 1. The translational effect True concentration True concentration Fig.1. Results of (a) the rotational effect and (b) the translational effect on a calibration line. The full lines indicate no interference and the broken lines a constant concentration of interferent. corresponds, in atomic-absorption spectrophotometry, to “background” interferences, such as molecular absorption and light scattering, and the rotational effects to physical, chemical and ionisation interferences. In general, the extent of the effect will be a function of the concentration (X) of the major constituent, so that the rotational effect can be formulated as The two components can operate in combination. where C, and C, are, respectively, the apparent concentration and the true concentration of the analyte. In this instance f(0) = 1, as C, = CT when X = 0, and we have A simple assumption is that C,/C, is a linear function of X.April, 1979 EFFECTS IN THE DETERMINATION OF TRACE ELEMENTS BY AAS where a is the constant coefficient for the rotational effect. In a similar way, the translational effect can be formulated as 301 Again, the assumption is made that the effect is a linear function of X.f(0) = 0 and we obtain the equation In this instance C, = C T + bX . . .. . . .. - * (4) where b is the coefficient for the translational effect. together we have When the two effects are operating C, = C, (1 + a x ) + bX . . .. .. - . (5) or where d, = CTa + b. For a given value of CT, determine the value of dc [= (dC,/dX),,] by plotting the apparent concentration at various levels of X. The slope will have a constant value if the initial assumptions are correct.In a similar manner values of d, at various levels of C, are obtained. As d, = C,a + b, a plot of d, against C, will give a line with a slope of a and intercept of b, as illustrated in Fig. 3. With the values of a and b determined, for known X the true concentration can be obtained from the apparent by Experimental quantification of a and b can be undertaken in the following manner. This is illustrated in Fig. 2. inverting equation (5) : CT = (C, - bX)/(1 + a x ) . . .. .. r C e Cl 2 L_J interferent concentration ( X I (7) Fig. 2. Effect of increasing inter- ferent concentration ( X ) on the appa- Fig. 3. Relationship between d , rent analyte concentration (CA) for a and CT, showing how to obtain values fixed level of analyte (CT).of a and b. If more than one interfering major constituent is present and complex interactions do not occur, the interference can be represented by the equation * (8) C, = CT (1 + CaiXi) + CbiX, . . .. .. where ai, bi and X i refer to values for the ith interfering element, and all the effects are independent and additive. In that instance the individual ai and bi can be obtained as302 THOMPSON et al. : STATISTICAL APPRAISAL OF INTERFERENCE Analyst, VoZ. 104 previously, by studying the effect on C, of varying each Xi separately, or by allowing all of the Xi to vary simultaneously, separating the effects by means of multiple regression techniques. There are no a priori reasons for believing that the simplifying assumptions (of independent, linear, additive effects) are correct.The experimental design must therefore contain features that enable these assumptions to be tested. If the system under study conforms fairly closely to the model, as demonstrated in the results presented here, the interference effects can be characterised simply and quantified quickly. If there are serious deviations, a much more extensive programme of work may be called for. Experimental Apparatus meter. linearisation where appropriate. handbook, the response being optimised for flame height and nebuliser adjustment. mental conditions are shown in Table I. hydrochloric acid solution. All measurements were made on a Perkin-Elmer 403 atomic-absorption spectrophoto- Readings were made without background correction in the concentration mode, with Gas flow-rates were those recommended in the instrument Instru- Single element standards were prepared in a 1 M TABLE I INSTRUMENTAL CONDITIONS Element Cadmium ..Cobalt . . Copper . . Lithium . . Manganese . . Nickel . . Lead .. Titanium . . Zinc. . .. Wavelength/nm .. 228.8 .. 240.7 .. 324.7 .. 335.4 .. 279.5 .. 232.0 .. 283.3 .. 365.3 .. 213.8 Lamp current/mA Slit width 10 4 20 3 15 4 15 4 20 3 20 3 10 4 25 3 20 4 Reagents The trace metal solutions were prepared from BDH atomic-absorption standards, except titanium, which was prepared from potassium titanium oxalate. The major element solutions were prepared from specially purified samples of the metal chlorides. De-ionised water and AnalaR hydrochloric acid were used throughout. Computing All computing was carried out on Imperial College Computer Centre’s CDC 6400/7314 facility. Multiple regression was performed by a slightly modified version of the routine STEPR from the IBM Scientific Subroutine Package.Regression with analysis of variance for lack of fit, and weighted linear regression were carried out, respectively, by means of the FORTRAN routines REPELF and WAYLIN written by one of the authors (MT). Experimental Design One hundred solutions were prepared in 1 M hydrochloric acid, each of which contained the trace analytes (vix., cadmium, cobalt, copper, lithium, manganese, nickel, lead and zinc) and the major constituents (vix., aluminium, calcium, iron, potassium, magnesium and sodium) at a pre-determined level. The concentration levels selected for the analytes spanned the useful calibration range for each element, while those of the major constituents covered the range likely to be encountered in solutions derived from rocks, soils and sedi- ments.The 100 solutions were divided into five sets of 20. Within each set all of the trace analytes were present at only one of the five concentration levels, the five sets thus covering the whole range of the trace con- centrations. For each solution within a set, the concentration of each major element was The concentrations are shown in Tables I1 and 111.A@?’&?, 1979 EFFECTS IN THE DETERMINATION OF TRACE ELEMENTS BY AAS 303 TABLE I1 CONCENTRATIONS OF ANALYTES (pg ml-l) USED IN INTERFERENCE STUDY r Analyte 1 Cadmium . . . . 0.00 Cobalt ... . 0.00 Copper .. . . 0.00 Lithium . . . . 0.00 Manganese . . . . 0.00 Nickel . . . . . . 0.00 Lead .. .. . . 0.00 Zinc . . .. . . 0.00 2 0.48 1.19 1.19 1.19 2.38 1.19 2.38 0.48 Level 3 0.88 2.19 2.19 2.19 4.38 2.19 4.38 0.88 4 1.43 3.57 3.57 3.57 7.14 3.57 7.14 1.43 - 5 - 1.90 4.76 4.76 4.76 9.52 4.76 9.52 1.90 individually selected at random from its ten possible levels in such a way that each level was selected exactly twice. An example of such a randomised scheme is shown in Table IV. The apparent concentration of trace analytes in each solution was then determined by atomic- absorption spectrophotometry, each solution being analysed twice in a random sequence. TABLE I11 CONCENTRATIONS OF INTERFERENTS (yo m/V) USED IN INTERFERENCE STUDY Level r 1 Interferent 1 2 3 4 5 6 7 8 9 10 Aluminium .. 0 0.0190 0.0380 0.0570 0.0760 0.0952 0.1143 0.1333 0.1524 0.1905 Calcium. . . . 0 0.0952 0.1905 0.2857 0.3810 0.4762 0.5714 0.6667 0.7619 0.9524 Iron . . . . 0 0.0190 0.0380 0.0570 0.0760 0.0952 0.1143 0.1333 0.1524 0.1905 Potassium . . 0 0.0190 0.0380 0.0570 0.0760 0.0952 0.1143 0.1333 0.1524 0.1905 Magnesium . . 0 0.0190 0.0380 0.0570 0.0760 0.0952 0.1143 0.1333 0.1524 0.1905 Sodium . . . . 0 0.0190 0.0380 0.0570 0.0760 0.0952 0.1143 0.1333 0.1524 0.1905 The types of sample preparation generally used in applied geochemical work do not lead to the presence of silicon in solution except sometimes as a trace constituent, and silicon was therefore not included among the interferents. Other non-metallic interferents (e.g., sulphur and phosphorus) are likely to be present only in minor concentrations compared with the metals, and were excluded from this study.The solutions used are thus reasonably representative of those derived from real samples. The randomisation scheme is necessary in order to avoid any systematic effects, which are thereby converted into random effects. In addition, complex interactions may be obscured if there is any correlation between the concentrations of the major elements. The duplication of major element concentrations is required in order to make a statistical test for lack of fit (caused in this instance by non-linearity). The duplication of the measure- ments is undertaken to obtain an estimate of instrumental variance, to provide a base-level against which other variances can be compared.The experimental design does not allow for the possibility of interference from trace element interactions. These are assumed to be unimportant at such concentrations. Results and Discussion The essential feature in the interpretation of the data is the analysis of variance at each level of a trace analyte. If there were no interference then each solution would produce an identical result (apart from instrumental and volumetric variations). In fact, all of the solutions give different results owing to the interferences and this is quantified by the total variance. The analysis of variance distributes this total variance between (i) that which can be accounted for by linear relationships with the major constituent concentrations, i.e., by linear regressions; (ii) that due to “lack of fit,” i.e., by a failure of the initial304 THOMPSON et al.: STATISTICAL APPRAISAL OF INTERFERENCE Analyst, VoZ. 104 TABLE IV EXAMPLE OF A RANDOMISED DUPLICATED SCHEME FOR THE Solution number 1 2 3 4 6 6 7 8 9 10 11 12 13 14 16 16 17 18 19 20 CONCENTRATIONS OF THE MAJOR ELEMENTS Concentration level* A \ Aluminium 1 8 3 2 6 6 8 4 1 9 7 9 7 2 5 4 10 3 10 6 Calcium 4 8 6 7 6 10 4 3 1 2 6 5 2 8 3 9 7 10 9 1 Iron 7 10 8 8 1 2 6 6 1 3 7 9 4 6 10 9 2 6 3 4 Potassium 6 2 3 1 7 2 1 6 4 8 3 4 10 7 8 6 6 10 9 9 Magnesium 8 3 6 7 2 4 9 10 3 2 6 6 1 7 8 9 6 1 4 10 Sodium' 1 4 9 3 7 6 3 6 8 1 9 8 7 6 5 2 2 4 10 10 * For actual concentrations corresponding to these levels, see Table 111. assumption that the interference effects are linear functions of the major element concentra- tions; (iii) that due to complex interactions, ie., by a failure of the second assumption; and (iv) that due to instrumental variations and volumetric errors. Each of these features is illustrated in the ensuing discussion.The diagrams are not usually necessary for the statistical analysis but serve here to illustrate several of its features, and are sometimes helpful in interpreting dubious examples. A comprehensive account of regression methods is given by Draper and Smith.9 Copper The first stage of the procedure is the multiple regression, which is carried out separately for each level of the trace analytes. Thus, for copper at level 1 (k, zero concentration) STEPR produced the results summarised in Table V.The regressions are given in decreasing order of significance as shown by the values of Student's t. Only the regressions on calcium and iron are significant at the 95% confidence limits. The intercept (0.002) is not signifi- cantly different from the true value of zero. The standard error of the estimate is equivalent to the standard deviation of the distances between the experimental points and the calculated TABLE V MULTIPLE REGRESSION OF COPPER ON MAJOR CONSTITUENTS Results at level 1 (zero analyte concentration). Regression Major constituent coefficient Calcium .. .. 0.1569 Iron . . .. .. 0.1088 Aluminium . . .. 0.0294 Potassium . . . . 0.027 2 Sodium . . .. .. 0.009 1 Magnesium . . .. 0.0109 Standard error of coefficient 0.0090 0.047 3 0.043 4 0.045 7 0.0484 0.043 7 t-value 17.36 2.30 0.68 0.60 0.23 0.21 Intercept = 0.0020.Standard error of estimate = 0.013. Explained variance = 96.5%.A$riZ, 1979 EFFECTS IN THE DETERMINATION OF TRACE ELEMENTS BY AAS 305 lines. In this instance it is not significantly greater than normal instrumental noise levels (0.01 pgml-l) as judged from the duplicated measurements. The implication is that all of the measurable interference can be attributed to calcium and iron by linear relationships with their concentrations. However, consideration of the standard error of the estimate is not a certain test of good regression, as will be shown below, and other statistics should be considered at the same time. In the context of this work, the percentage variance explained and an examination of residuals are useful supplementary tests.The multiple regression is repeated at each of the analyte concentration levels. The next stage of the procedure is illustrated by the results obtained for the interference effects of calcium on copper, but the same procedure is followed for each analyte - interferent combina- tion. The regression data extracted for the copper -calcium pair are given in Table VI. TABLE VI STATISTICS FOR THE REGRESSION OF APPARENT CONCENTRATION OF COPPER ON CALCIUM CONCENTRATION, AT VARIOUS CONCENTRATIONS O F COPPER Analyte Copper concentration/ Regression Standard error Standard error level pg ml-l coefficient of coefficient t-value of estimate* 1 0.00 0.156 9 0.0090 17.36 0.013 2 1.19 0.042 9 0.01 7 2 2.50 0.024 3 2.19 -0.013 8 0.018 1 -0.76 0.026 4 3.67 - 0.089 7 0.0309 -2.91 0.043 5 4.76 - 0.145 4 0.0462 -3.14 0.065 * This value is the residual after all the regressions are included, not only calcium.These data and statistics are illustrated in Fig. 4, which shows the apparent concentrations of copper as a function of calcium concentration. (It must be noted that the visible differ- ences between the duplicated results at each level of calcium is not variance caused by analytical error but by the different levels of all of the other major elements.) Both the data and Fig. 4 show the regression coefficient changing from positive to negative as the copper concentration increases. At approximately 2 pg ml-1 of copper the coefficient is zero, showing that at this concentration there is no apparent effect of calcium on copper, 0 0.2 0,4 0.6 0.8 1.0 Calcium concentration, % Fig.4. Effect of calcium concentration on the apparent concentration of copper a t various true concentrations (CT) of the analyte. Open points, single observations; and closed points, two coincident observations. This system shows a significant change in slope with CT.306 THOMPSON et aZ. : STATISTICAL APPRAISAL OF INTERFERENCE Analyst, VoZ. 104 even though there is an effect at both higher and lower copper concentrations. This high- lights the erroneous conclusions that can be drawn from interference studies carried out at a single trace element concentration. The standard error of the estimate is satisfactorily low at each copper concentration level, suggesting that there is no measurable non-linearity or complex interactions for copper.The values of the regression coefficients correspond to variable dc in equation (6) while the analyte concentrations correspond to C,. The values of a and b can now be obtained by regression of d, on C,. It is necessary to obtain also the standard errors of the intercept (b) and the slope (a) so that the values can be tested as to whether they are significantly greater than zero. However, normal regression can give misleading results for the standard errors, as the variance at higher trace levels, necessarily greater than at lower levels, has too much influence on the regression. In this technique, each observation is weighted by a factor inversely proportional to its variance. The variance in this instance is the square of the standard error of the coefficient.The necessity for this procedure is illustrated in Fig. 5. The error bars on each point represent the 95% confidence limits, i.e. , twice the standard error. It is clear that the regression lines produced by weighted regression and by simple regression are very close and not significantly different. However, the standard errors of the intercepts are very different. The 95% confidence limits for the simple regression include zero, implying that the intercept is not significant. The same confidence limits for the weighted regression, which are clearly more realistic, show the intercept to be highly significant. The values extracted for copper were a = -0.071 (t = 11.2) and b = 0.150 (t = 16.1).Hence, the measurable interference from calcium on copper under the conditions studied can be expressed by C, = (C, -0.15OX)/(l -0.071X) where C, and C, are expressed in micrograms per millilitre and X as a percentage. Weighted regression therefore has to be used. 0.3 - f--,95% confidence region for intercept - normal regression 1 I I I I 0 1 2 3 4 5 -0.3 I True copper concentration (CT)/pg ml-' Fig. 5. Regression of dc on CT for copper/calcium. The error Broken line, bars are the 95% confidence regions for the dc values. normal regression ; and solid line, weighted regression. The Other Analytes The results are summarised in Table VII, which shows all of the a and b values that were more signifi- cant than 95%. Most of the values were also more significant than 99% and those are shown in italic type.All but two of the a values were negative, representing suppression of the analytical signal by the major component. The exceptions were sodium and potassium on lithium. Most of the b values are positive, representing positive changes in background absorption, which in most instances accounts for the greater part of the interference. Broadly, the effects found were as expected from experience of atomic-absorption spectrometry, in confirmation of the adequacy of the model. An example of an analyte - interferent pair (cadmium - calcium) , which shows only background interference, is illustrated in Fig. 6. As before, non-adherence to the theoretical model 'was tested by examination of the standard errors of the estimate, and the percentage variance explained, at each level for each analyte.The procedure outlined for copper was repeated for the other seven analytes.April, 1979 EFFECTS IN THE DETERMINATION OF TRACE ELEMENTS BY AAS 307 TABLE VII SIGNIFICANT VALUES OF a AND b FOUND IN THE INTERFERENCE STUDY “important” effects. Figures in italic type are significant at 99% level, others a t 95% level. Asterisks indicate Major r constituent Cd co Aluminium . . a -0.114 -0.320* b 1.026* b 0.213* 0.852* Iron . . .. a b Potassium . . a b Magnesium . . a b Sodium . . .. a b 0.085 0.547 Calcium. . .. a - 0.051 Trace analyte c u Li Mn 0.044 0.150* 0.036 0.193 -0.168 -0.224* -0.162 -0.071 -0.262* -0.066 - 0.281 -0.016 0.065 -0.111 -0.118 0.019 -0.011 > Ni Pb Zn - 0.290* -0.111 0.068 -0.062 1.277* 1.601* 0.133 0.831 0.360 0.114 - 0.315 0.559 Of the analytes only lithium showed significantly large standard errors. Non-linear effects accounted for the deviation in the lithium results.These effects were tested for by performing a regression with analysis of variance for “pure error” and “lack of fit” at each analyte level. In this technique, the variance caused by the difference between the pairs of results for each level of the interferent (which is due to the effect of different concentrations of the other major elements) is compared with that related to the mean distance of the two points from the regression line. This procedure is illustrated in Fig. 7, which shows the results of the regression of the lithium results on calcium. The individual results are plotted together with the calculated linear regression lines.For the higher concentrations of lithium the diagram clearly shows a non-linear effect, which the linear regression underestimates in some ranges and overestimates elsewhere. All of the significant regressions were tested 2‘5r- CT = 1.90 CT = 1.43 CT = 0.00 0 0.2 0.4 0.6 0.8 1 .o Calcium concentration, % Fig. 6. Effect of calcium on the apparent concentration This system shows only of cadmium at various levels. “background” interference. Symbols as in Fig. 4.308 THOMPSON et al. : STATISTICAL APPRAISAL OF INTERFERENCE Analyst, VoZ. 104 e &\. h c, F ,CT = 3.57 c,= 1.19 A . _ . _ P ' . O t z l c, = 0.00 A A &~- A A ! ' 5 ' 0 0.2 0.4 0.6 0.8 1 .o Calcium concentration, % Fig.7. Effect of calcium concentration on the apparent concentration of lithium at various levels. This shows the significant lack of fit of the linear regressions (solid lines) at the higher levels. Symbols as in Fig. 4. individually in this way, but only lithium (at four levels) and cobalt (at one level) were found to have significant lack of fit, as judged by the value of the F (variance ratio) test. To obtain an adequate fit for such data a more elaborate mathematical relationship is required. Generally, polynomial fits do not give satisfactory results. However, it is clear from Fig. 7 that even a linear fit would provide a substantial improvement in accuracy. For cobalt, inspection of the residuals strongly suggested that the isolated significant lack of fit was caused by a random fluctuation rather than a non-linear effect at one level.The statistical test alone cannot distinguish between the two possibilities. The success of the two-parameter model in describing the interferences was tested by applying to the experimental data corrections based on the inverse of equation (€9, i.e., C, = (C, - CbiXi)/(l + ZaiXi) .. .. ' (9) TABLE TUII CORRECTION OF EXPERIMENTAL RESULTS BY USE OF TWO-PARAMETER MODEL The results of all significant corrections have been applied to the uncorrected (raw) data to give the corrected value (con.) for comparison with the true value. Means are given for each level (standard deviations in parentheses). Analyte concentration/pg ml-I A Trace 7 \ level Result Cadmium Cobalt Copper Lithium hlanganese Nickel Lead Zinc 1 Raw 0.12 (0.07) 0.63 (0.27) 0.09 (0.05) 0.02 (0.01) 0.11 (0.07) 0.83 (0.42) 1.02 (0.49) 0.12 (0.05) Corr.0.03 (0.01) 0.17 (0.09) 0.02 (0.01) 0.00 (0.00) 0.03 (0.04) 0.25 (0.09) 0.25 (0.09) 0.01 (0.01) True 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2 Raw 0.61 (0.06) 1.85 (0.26) 1.21 (0.03) 1.03 (0.09) 2.43 (0.05) 1.96 (0.39) 3.42 (0.44) 0.59 (0.04) Corr. 0.52 (0.01) 1.43 (0.10) 1.20 (0.02) 1.23 (0.02) 2.42 (0.05) 1.42 (0.08) 2.71 (0.09) 0.49 (0.01) True 0.48 1.19 1.19 1.19 2.38 1.19 2.38 0.48 3 Raw 0.98 (0.06) 2.79 (0.25) 2.09 (0.03) 1.82 (0.18) 4.22 (0.06) 2.87 (0.40) 5.28 (0.41) 0.95 (0.05) Corr. 0.89 (0.01) 2.40 (0.10) 2.13 (0.03) 2.17 (0.06) 4.25 (0.06) 2.35 (0.09) 4.63 (0.08) 0.85 (0.02) True 0.88 2.19 2.19 2.19 4.38 2.19 4.38 0.88 4 Raw 1.56 (0.06) 4.15 (0.23) 3 42 (0.05) 3.02 (0.29) t.99 (0.12) 4.30 (0.35) 8.18 (0.36) 1.66 (0.06) Corr.1.46 (0.02) 3.79 (0.17) 3.32 (0.04) 3.62 (0.06) r.11 (0.08) 3.81 (0.11) 7.61 (0.10) 1.45 (0.03) True 1.43 3.57 3.57 3.57 7.14 3.57 7.14 1.43 5 Raw 2.01 (0.07) 5.32 (0.23) 4.48 (0.09) 3.97 (0.39) 9.17 (0.21) 5.43 (0.38) 10.47 (0.37) 2.02 (0.06) Corr. 1.92 (0.03) 5.00 (0.16) 4.62 10.06) 4.76 (0.11) 9.35 (0.17) 4.98 (0.14) 9.97 (0.17) 1.93 (0.02) True 1.90 4.76 4.76 4.76 9.62 4.78 9.62 1.90Apt‘&?, 1979 EFFECTS I N THE DETERMINATION OF TRACE ELEMENTS BY AAS 309 for all significant values of a and b. The results obtained are summarised in Table VIII, which shows, for each level of each trace analyte, the mean and standard deviation of all the solutions of the uncorrected (raw) results, the corrected results and the true concentra- tion present.In virtually all instances the mean result was brought substantially closer to the true result and the range (as indicated by the standard deviation) was markedly reduced, showing a considerable degree of success with the two-parameter model. Some of the data are illustrated in Fig. 8 for two different types of interference. D Concentration presendpg mI-’ Fig. 8. Range of experimental results for (a) lithium and (b) lead, both uncorrected (narrow bars) and corrected with all significant parameters (thick bars). The Magnitude of the Interferences While the procedure described above enabled all of the statistically significant (k, measurable) effects to be quantified, it did not in itself provide information as to whether the magnitude of the effects was likely to be “important” ( i e ., likely to affect interpretation of geochemical data). This information can be obtained by the application of empirical criteria appropriate to the data usage. For geochemical work we have applied the following criteria: an effect is “important” if la1 > o.05/Mg, or Ibl > T,/Mgg, where Mgg is the 99th percentile concentration (in per cent.) of the major element in the population of samples to be analysed, and T , is the fifth percentile of the trace element concentration (in micrograms per millilitre). Thus, when the factor a is equal to the criterion, only for one sample in 100 will the interference effect exceed a relative change of &5y0 in the apparent analyte con- centration. When b is equal to the criterion, the interference will equal the analyte concentration only when the interferent exceeds its 99th percentile at the same time as the trace analyte falls below its 5th percentile, i.e., a probability of 0.0005 if the concentrations of the two elements are independent.The “importance” of the b value thus depends on the concentration range of the analyte. For example, the b value for cadmium - calcium of 0.213 is graded “important” : a sample of pure limestone (which contains 40% calcium) would produce an apparent cadmium level of 40 x 0.213 or about 8 p.p.m. compared with the normal level of <1 p.p.m. This is clearly important. The corresponding effect for zinc would amount to 40 x 0.133 or 5.3 p.p.m.However, the normal level of zinc is in the range 50-100 p.p.m. so the effect is not important. The “important” effects identified in this way are shown in Table VII with an asterisk. The percentiles were taken from a major geochemical survey involving 50000 ~amples.~ Only aluminium and calcium produce “important” effects in the context of geochemical analysis. Aluminium produces mainly rotational type effects (factor a) , on cobalt, lithium and nickel. Calcium produces translational effects (factor b) on cadmium, cobalt, copper, nickel and lead. While the background interference can be at least partly corrected by means of absorption measurements with a continuum source, there is no universally applicable method for removing rotational effects. For lesser major concentrations a smaller interference will be found.310 THOMPSON et d.: STATISTICAL APPRAISAL OF INTERFERENCE Analyst, VOZ. 104 An Example of Complex Interaction The interference effects studied could be effectively accounted for by a simple model of linear, independent, additive effects. Only in one instance (calcium on lithium) was a significant non-linear effect identified, and even here the linear approximation was an adequate model. In these circumstances the methodological approach suggested in this work is capable of elucidating the interference effects. However, it is often suspected and sometimes demonstrated that more complex types of interference are occurring. We have examined one such system, the interference of iron and aluminium on titanium, which is known to have non-linear effects and complex interactions.llSl2 The sole purpose of this additional study was to examine the performance of the statistical approach under conditions where the simple assumptions of the method are likely to fail, and to determine whether the failure manifests itself clearly by the statistical tests.Titanium would be only partially extracted by the acid attacks described here. The experimental design was as described above, with titanium at 5 levels (0, 10,20, 30 and 40 pg ml-l) and iron and aluminium within the ranges 0-10000 and 0-2000 pg ml-1, respectively, and with no other interferent present. Multiple regression (the first stage of the data analysis) produced the statistics summarised in Table IX. The percentages of the variances explained were small, the standard errors of the estimates were large compared with the pure analytical error, and the regression co- efficients and values of t were small.In addition, analysis of variance for lack of fit (titanium against aluminium) showed highly significant lack of fit. Thus, in all these ways the statistics show a non-conforming interference system. Only the low regression coefficients might suggest to the unwary that there was no significant interference. The reason for this is the extreme non-linearity of the effect of aluminium. This is illustrated in Fig. 9, which shows the failure of linear regression to represent this type of data. Thus, it is important to take note of all statistics and visually to examine the residual plots in doubtful instances.A two-way plot of these data showed that there were complex interactions in the system as well as non-linear features. The data produced in the simple experiment were not sufficient to characterise the response surface and a more comprehensive experiment was required. It was found that the effect of iron and aluminium can be represented approximately by the surface shown in Fig. 10, for any level of titanium. It is difficult adequately to express a complex surface like this in terms of polynomial trend analysis. TABLE IX STATISTICS FOR THE MULTIPLE REGRESSION STUDIES ON THE INTERFERENCE OF ALUMINIUM AND IRON ON TITANIUM Analyte Regression Standard error Variance 1 Iron 0.000 :;:i4 ) 0.74 18.5 Aluminium 0.005 2 Iron 0.001 Aluminium 0.002 Aluminium -0.002 -0.25 } 2*8 Aluminium -0.004 -0.42 } 3'8 Aluminium 0.000 -0.06 } 3*8 level Interferent coefficient t-value of estimate explained, % } 1.81 37.5 18.9 3 Iron 0.000 0.07 15.I 4 Iron 0.005 2.55 30.0 5 Iron -0.008 -3.82 Summary and Conclusions It has been shown that a simple two-parameter model of interference with independent, linear, additive effects is adequate to describe the measurable interference in the atomic- absorption determination of cadmium, cobalt, copper, lithium, manganese, nickel, lead and zinc in geochemical samples. The statistically significant parameters have been evaluatedApril, 1979 EFFECTS I N THE DETERMINATION OF TRACE ELEMENTS BY AAS 311 and those of important magnitude have been indicated by an empirical but uniformly applicable criterion.This enables the analyst to identify conditions where interferences might have a noticeable effect on data interpretation, and where appropriate, to make suitable corrections in the form of equation (9). Where large numbers of data are involved the corrections can be applied automatically by computer. This will become increasingly easy as microprocessor-controlled data logging systems become more common. Although an elaborate experimental design and data appraisal are required in order to characterise the interference model, the parameters a and b can be evaluated with only four solutions once it has been established that the system conforms to the model. Naturally the values of a and b will depend on the instrumental settings, the use of background correc- tion and other factors, and should be checked for each analytical batch.In addition, it is good practice to reduce interferences to as low a level as possible before attempting correc- tions, which should generally be regarded as a last resort. Where deviations from the model occur, the experimental design ensures that they are detected and suggests how more elaborate tests can be made to characterise them. In most of these instances informal designs in interference studies would give misleading results, especially with regard to complex interactions in multi-interferent systems, which usually remain undetected. These effects may still remain too complex to elucidate fully, but even so, it is important for the analyst to know when these occur. Where they occur it is necessary to resort to the use of appropriate standard solutions whose major constituents correspond in composition to those of the average sample. CT = 0.0 0 I h 9 : Q G II ”,” a n P 0 - li Fig. 9. Effect of aluminium on the apparent con- centration of titanium in the system Ti- A1 - Fe. This shows failure of the linear system to represent these data. Symbols as in Fig. 4.312 THOMPSON, WALTON AND WOOD 9 Iron concentration, 96 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. Fig. 10. Combined effect of aluminium and iron on the apparent concentration of titanium a t 30 pg ml-1. The contours indicate relative enhancement as a percentage. References Foster, J. R., Can. Min. Metall. Bull., 1973, 66, 85. Webb, J . S., and Thompson, M., Pure Appl. Chem., 1977, 49, 1507. Fletcher, K., Econ. Geol., 1970, 65, 588. Foster, J. R., in Boyle, R. W., and McGerrigle, J. I., Editors, “Proceedings of the Third International Geochemical Exploration Symposium, Toronto, 1970,” Special Volume 11, Canadian Institution of Mining and Metallurgy, Toronto, 1970, pp. 554-560. Govett, G. J. S., and Whitehead, R. E., J . Geochem. Explor., 1973, 2, 121. Woodis, T. C., Hunter, G. B., and Johnson, F. J., Analytica Chim. Acta, 1977, 90, 127. Thompson, M., Pahlavanpour, B., Walton, S. J., and Kirkbright, G. F., Analyst, 1978, 103, 705. Alley, B. J., and Myers, R. H., Analyt. Chem., 1965, 13, 1685. Draper, N. R., and Smith, H., “Applied Regression Analysis,” John Wiley, New York, 1966. Webb, J. S., Thornton, I., Thompson, M., Howarth, R. J., and Lowenstein, P., “The Wolfson Geochemical Atlas of England and Wales,” Oxford University Press, London, 1978. Cobb, W. D., Foster, W. W., and Harrison, T. S . , Analytica Chim. Acta, 1975, 78, 293. Walsh, J. N., Analyst, 1977, 102, 972. Received June 26th, 1978 Accepted November 15th, 1978

ISSN:0003-2654    

DOI:10.1039/AN9790400299

出版商:RSC    

年代:1979

数据来源: RSC

摘要:

Analyst, April, 1979, Vol. 104, $9. 313-322 313 Minimum Sample Preparation for the Determination of Ten Elements in Pig Faeces and Feeds by Atomic-absorption Spectrophotometry and a Spectrophotometric Procedure for Total Phosphorus Edward P. Hilliard" and J. David Smith School of Agriculture and Forestry, University of Melbourne, ParRviZle, Victoria 3052, Australia School of Chemistry, University of Melbourne, Parkville, Victoria 3052, Australia Studies of mineral metabolism in pigs and problems of manure disposal or utilisation are complicated by interactions of trace metals and major cations. A procedure for the determination of copper, zinc, cadmium, lead, iron, sodium, potassium, magnesium, calcium, phosphorus and arsenic in pig faeces and feeds is described. Phosphorus is determined spectrophoto- metrically and the other elements by atomic-absorption spectrophotometry.Sample preparation is minimised, and all elements except arsenic are deter- mined after a single sample digestion in nitric acid - perchloric acid mixture. A separate sample digestion is necessary for arsenic. The accuracy and precision of the method were rigorously tested, and are suitable for budget studies of all eleven elements. Keywords : Pig faeces and feed analysis ; trace metal determination ; major element determination ; atomic-absorption spectrophotowtetry ; spectro- photometry Intensification in animal production in recent years has generated problems in relation to the disposal or utilisation of the large amounts of manure produced per annum. Manures from pig, poultry or dairy/beef units have traditionally been spread on land to utilise their fertiliser values, With the trend towards larger intensive units, and a decrease in land area suitable for manure spreading from such units, attention is being given to alternative means of manure disposal.The environmental effects of disposing of large amounts of manure to small land areas is causing concern, particularly where the manures contain high concentrations of metals.lY2 Commercially formulated pig diets generally contain supple- mental mineral salts to improve growth and development and to compensate for deficiencies due to interactions between some elements. Minerals at high levels in the feed are not fully absorbed by the pig and can be concentrated by a factor of four in the faeces.2 Because of the unusually high levels of minerals in pig faeces and feeds, these materials provide an unusual matrix when the accurate determination of element concentrations is required.Investigations into the fate of minerals or trace elements in biological systems are compli- cated by the interactions of some elements with each other, and with other metabolites in the system.3~~ For this reason, it is rare to encounter experimental work on mineral meta- bolism that reports the functions and fate of single elements without examining the influence of potential interacting elements within the system under investigation. Hence, it is essential that laboratories use methods that permit determination of the maximum number of elements but with the minimum of sample preparation.Our investigations were principally aimed at the development of economical methods for the analysis of pig manures and feeds for a wide range of elements, giving results of high accuracy and precision. To minimise sample manipulation, calibration over a wide range was used and linear or quadratic equations were fitted to the calibration lines. Concentrations of elements in the * Present address : The Agricultural Institute, Dunsinea, Castleknock, Co. Dublin, Ireland.314 HILLIARD AND SMITH: MINIMUM SAMPLE PREPARATION FOR THE Analyst, vol. 104 sample solutions were computed using these equations. was used for the more sensitive and abundant elements. Some degree of burner rotation Experimental Apparatus Atomic-absorption spectrophotometer. A Varian Techtron, Model 1200, instrument with an air - acetylene burner and digital read-out was used for the determination of copper, zinc, cadmium, lead, iron, sodium, potassium, magnesium and calcium.A Varian Techtron, Model AA5, instrument with a BC-6 simultaneous background corrector and a Mace 1100 strip-chart recorder was used for the determination of arsenic. A Varian Techtron, Model 64, hydride-generation kit was used with a nitrogen - hydrogen flame using the burner supplied for air - propane. Spectrophotometer. A Unicam SP600 instrument with a I-cm light path flow-through cell attachment was used for the determination of phosphorus. Computation. A Sharp, Model 365P, programmable calculator was used to fit linear calibration lines to the equation y = a + bx and quadratic curvilinear calibration lines to the equation y = a + bx + ex2. Kjeldahl digestionjasks.Flasks of capacity 50 ml on an electric heat bank with individual heat controls were used. Glass culture tubes with PTFE seal screwcaps. Capacity 25 ml. Reagents All solutions were prepared using glass-distilled water in glassware that had previously been washed with 10% nitric acid and rinsed with distilled water. Concentrated acids from Ajax Chemicals Pty. Ltd. were selected batches of low trace-element content. Unless specified otherwise, all chemicals used were of analytical-reagent grade. Nitric acid, sp. gr. 1.42. Dilute nitric acid, 2 M. Perchloric acid, 70%, sp. gr. 1.54. Sulphuric acid, sj5. gr. 1.84. Hydrochloric acid, sp.gr. 1.18. Nitric acid - perchloric acid digestion mixture. Mix equal volumes of the concentrated acids. Sulphuric acid - perchloric acid - sodium molybdate digestion mixture. Dissolve 2 g of sodium molybdate (Na2Mo0,.2H20) in 40 ml of water, add 50 ml of concentrated sulphuric acid, allow the mixture to cool and add 10 ml of concentrated perchloric acid. Ammonia solution, sp. gr. 0.880. Bromophenol blue indicator solution, 0.1% mlV in methanol. Citrate bufer. Dissolve 210 g of citric acid and 29.5 g of trisodium citrate in water and dilute to lo00 ml with water. Ammonium tetramethylenedithiocarbamate solution, 0.5% mlV in water. Prepare fresh daily. 4-Methylpentan-2-one. Sodium tetralzydroborate(III) solution, 5% mlV in 0.1 yo sodium hydroxide solution. Use within 14 h of preparation.Lanthanum - caesium solution, 5% m/V lanthanum and 2% mlV caesium in water. Dissolve 2.5 g of caesium chloride in 100 ml of water and add 100 ml of 10% m/V lanthanum solution (BDH standard solution for spectroscopy) . Vanadate reagent for phosphate determination. Solution A : dissolve 25 g of ammonium molybdate in 400 ml of water. Solution B: dissolve 1.25 g of ammonium metavanadate in 300 ml of boiling water, cool and add 200 ml of concentrated perchloric acid. Add solution A to solution B and dilute to lo00 ml with water. Arsenic standard solutions. Dissolve 0.832 9 g of sodium arsenate (Na,HAs0,.7H20) in water and dilute to 1000 ml with water. Dilute 3 ml of this solution to 200 ml with water to give a 3 pg ml-l arsenic stock standard solution.Prepare arsenic standard solutions in the range 0.03-0.36 pg ml-l by diluting appropriate volumes of the stock standard solution with 5% sulphuric acid. Dilute 127 ml of the concentrated acid to lo00 ml with water. Purified by extraction with 2 M nitric acid.April, 1979 315 BDH cadmium standard solution for atomic-absorption spectrophotometry, containing 1000 pg ml-l of cadmium, diluted with 2 M nitric acid to give standard solutions in the range 0.05-1.50 pg ml-l of cadmium. These solutions should be saturated with 4-methylpentan-2-one prior to use. BDH lead standard solution for atomic-absorption spectro- photometry, containing 1000 pg ml-l of lead, diluted with 2 M nitric acid to give standard solutions in the range 0.5-15.0pgml-1 of lead.These solutions should be saturated with 4-methylpentan-2-one prior to use. The following stock solutions are prepared for inclusion in the multi-element stock standard solution : 1000 pg ml-l solutions of copper, zinc and iron ; available as BDH standard solutions for atomic-absorption spectrophotometry. 10000 pg ml-1 of calcium; 6.2425 g of calcium carbonate dissolved in 120 ml of water plus 15 ml of concentrated hydrochloric acid. 10000 pg ml-l of magnesium; 20.270 g of magnesium sulphate (MgS0,.7H20) dissolved in 150 ml of water. Add 2 ml of concentrated hydrochloric acid and dilute to 200 ml with water. D. 1000Opg~ml-l of sodium; 6.355g of sodium chloride dissolved in and diluted to 250 ml with water. E. 100000 pg ml-1 of potassium; 19.08 g of potassium chloride.Add 1 ml of con- centrated hydrochloric acid and dilute to 100 ml with water. F. 10000 pg ml-l of phosphorus; 10.6603 g of ammonium orthophosphate [(NH,),HPO,] dissolved in and diluted to 250 ml with water. Appropriate volumes of each stock solution are added to a 1000-ml calibrated flask and diluted to volume with water to give a multi-element stock standard solution containing each element at the following concentrations (pg ml-l) : DETERMINATION OF TEN ELEMENTS IN PIG FAECES AND FEEDS BY AAS Cadmium standard solutions. Lead standard solutions. Multi-element stock standard solution. A. B. C. Dilute to 250 ml with water. cu Zn Fe Na K Mg Cu P 20 60 100 2000 1000 1000 2000 2000 Procedure for Measuring Accuracy and Precision of Analytical Techniques through a 1-mm screen of a stainless-steel laboratory mill.were bulked to provide a large representative sample of pig faeces. precision of the techniques were assessed as follows. Samples of pig faeces were collected from 24 commercial piggeries, freeze-dried and ground Sub-samples from each sample The accuracy and The over-all precision of the techniques was determined by analysis of at least six replicate 2-g samples of dried, ground pig faeces. To determine the recovery of each element and assess losses due to volatilisation or precipitation during digestion, known amounts of each element were added to triplicate 2-g samples of the bulk faeces sample before and after digestion. These standard additions were made by adding 10 ml of the multi-element stock standard solution. The arsenic recovery was determined separately by adding 1 ml of the arsenic stock standard solution to triplicate 2-g samples.To establish if sample matrix effects such as ionisation or chemical interference affected the accurate determination of each element, the following procedure was adopted. Prior to digestion, 10- and 15-ml aliquots of the multi-element stock standard solution were added to 1.0-, 1.5- and 2.0-g masses of faeces in triplicate. Effects on arsenic determination were examined separately by adding 1 and 2 rnl of the arsenic standard solution to triplicate 1- and 2-g masses of faeces before digestion. The accuracy of the methods was assessed by analysing the US National Bureau of Standards Reference Material 1571, “orchard leaves.’’ Duplicate 2-g samples were digested and analysed by the method described below.1. 2. 3. 4. Digestion Procedure several ways. The preparation of biological material for multi-element analysis can be accomplished in Dry ashing, which requires heating the sample to temperatures above31 6 HILLIARD AND SMITH: MINIMUM SAMPLE PREPARATION FOR THE Analyst, VOl. 104 400 "C, was considered to be unsuitable because of the potential losses of lead, cadmium and arsenic due to volatilisation at the ashing temperatures5 Wet digestion, by heating with acids, was considered to be a more suitable means of destroying organic matter. The choice oi reagents for wet digestion was made after considering the solubility of salts formed during digestion. Sulphuric acid was not used when the likely losses of calcium and lead as insoluble sulphates would be significant.A mixture of nitric and perchloric acids (1 + 1) was selected as the digestion mixture for copper, zinc, cadmium, lead, iron, sodium, potassium, magnesium, calcium and phosphorus. An oxidising solution of sodium molybdate in sulphuric - perchloric acids was used for arsenic samples. For determination of copper, zinc, cadmium, lead, iron, sodium, potassium, magnesium, calcium and phosphorus Approximately 2 g of sample were weighed accurately into Kjeldahl flasks and digested initially with 15 ml of concentrated nitric acid (sp. gr. 1.42) and finally with 15 ml of the nitric - perchloric acid digestion mixture. Appropriate additions of the multi-element standard solution were made before or after digestion as required.The digest solutions were then transferred quantitatively into 100-ml calibrated flasks and diluted to the mark with water. For detmnination of arsenic Approximately 2 g of sample were weighed accurately into Kjeldahl flasks and digested initially with 10 ml of concentrated nitric acid (sp. gr. 1.42) and finally with 15 ml of the sulphuric acid - perchloric acid - molybdate digestion mixture. Standard additions of arsenic were made as required. The digest solutions were then transferred quantitatively into 50-ml calibrated flasks and diluted to the mark with water. Determination of Elements The instrument settings and flame conditions suitable for each element are shown in Table I. A 25-ml aliquot of digest solution was removed from each 100-ml calibrated flask TABLE I INSTRUMENT SETTINGS AND FLAMES USED FOR ATOMIC-ABSORPTION SPECTROPHOTOMETRY Element f A 7 Condition Cu Zn Cd Pb Fe Na K Mg Ca As Wavelength (nm) .. 324.7 213.9 228.8 217.0 372.0 330.2 404.4 285.2 422.7 193.7 Slit width (mm) . . . . 0.2 0.2 0.5 1.0 0.5 1.0 1.0 0.5 0.2 0.25 L Y J Flame . . .. .. Air - acetylene H2 - N, for the determination of copper, zinc, iron, sodium, potassium, magnesium, calcium and phosphorus. The digest solution remaining in the flask (approximately 75 ml) was retained for the determination of cadmium and lead. 'The multi-element stock standard solution was diluted with 4% perchloric acid to give standards within the ranges shown in Table 11. TABLE I1 ELEMENT CONCENTRATIONS I N THE MULTI-ELEMENT STANDARD SOLUTIONS Element cu Zn Cd Pb Fe Na K Ca P Mg Lowest standard/ Highest standard/ Stock standard/ pg ml-1 pg ml-l pg ml-l 0.4 16 20 1.2 48 60 0.004 0.16 0.2 0.04 1.6 2 2 80 100 40 1600 2 000 20 800 1000 20 800 1000 40 1600 2 000 40 1600 2 000April, 1979 DETERMINATION OF TEN ELEMENTS IN PIG FAECES AND FEEDS BY AAS Copper, zinc and iron Copper and iron are generally free from interference during atomic-absorption spectro- photometry, so the digests and standards were nebulised directly into the flame.The copper calibration graph was linear over the complete range and had a correlation coefficient (YJ of 0.999. Copper concentrations in the sample digests were computed from a linear regression equation. The iron calibration line was curved above 30 pg ml-l and concentra- tions of iron in sample solutions were computed from a quadratic equation fitting the calibration line. Because non-atomic absorption from sample solutions was considered possible at the zinc wavelength, the absorbance was also measured separately at 213.9nm using a hydrogen lamp.No significant absorbance was observed using the hydrogen lamp with the necessary 80" burner rotation. The zinc calibration line was linear up to 24 pg ml-l (yXy = 0.998) and was used up to 60 pg ml-l by fitting a quadratic equation to the curve. 31 7 Cadmium and lead Levels of cadmium and lead in faeces and feeds were found to be too low for direct deter- mination on the digest solution. A procedure for the concentration of these elements by solvent extraction was developed utilising ammonium tetramethylenedithiocarbamate and 4-methylpentan-2-one.Optimum conditions for the extraction of trace amounts of cadmium and lead from the digest solution were determined experimentally. The efficiency of the extraction procedure was determined as follows. Appropriate volumes of the multi-element stock standard solution were diluted to 100ml with 4% perchloric acid to give solutions containing 0.004-0.100 pg ml-l of cadmium and 0.04-1.0 pg ml-l of lead in a multi-element matrix similar to the sample digest. A blank of 100 ml of perchloric acid was also prepared. A 25-ml volume was removed by pipette from each flask, leaving 75 ml of solution, similar to the sample digest volume available for analysis. Bromophenol blue indicator was added to each flask and ammonia solution (sp.gr. 0.880) added dropwise until the end-point was reached. A 5-ml volume of 1 M citrate buffer (pH 4.0) was added, followed by 3 ml of 0.5% ammonium tetramethylenedithiocarbamate solution. The contents of each flask were mixed, 10 ml of 4-methylpentan-2-one added and the contents mixed again. The organic layer was allowed to separate, then transferred by Pasteur pipette into a 25-ml culture tube. The aqueous phase was extracted with a further 5 ml of 4-methylpentan-2-one, which was also added to the culture tube. As the cadmium and lead complexes are not stable for more than about 2 h,6 cadmium and lead were back-extracted from the 4-methylpentan-2-one into 5 ml of 2 M nitric acid. This procedure eliminated the necessity of preparing standards in 4-methylpentan-2-one.The upper organic layer was removed from the culture tube, leaving the cadmium and lead in 2 M nitric acid. Complete extraction of cadmium and lead from the standards would yield solutions containing 0.06-1.50 pg ml-l of cadmium and 0.6-15.0pgml-l of lead. Standard solutions of cadmium and lead covering similar concentration ranges were prepared in 2 M nitric acid saturated with 4-methylpentan-2-one to simulate the extracted standards. Absorbances of the extracted and non-extracted standards were measured using the conditions described in Table I. The instrument was adjusted to zero with distilled water and the absorbance of a 2 M nitric acid solution saturated with 4-methylpentan-2-one subtracted from all readings. The absorbance of extracted and non-extracted cadmium and lead standards showed that the recovery of cadmium and lead through the extraction procedure was essentially quantitative (Table 111).This extraction procedure was applied to test faeces samples digests. Magnesium and calcium To overcome potential problems due to ionisation or chemical interferences in the deter- mination of magnesium and calcium, various combinations of releasing agents and ionisation suppressants were examined under different flame conditions. The most suitable conditions were as follows. Sample and standard solutions were diluted 1 + 49 by adding 2 ml of a solution of 5% lanthanum - 2y0 caesium to 0.2 ml of sample or standard and diluting to 10 ml with water. These solutions were aspirated into the instrument using the settings shown in Table I and gave curved calibration lines over the standard ranges used.31 8 HILLIARD AND SMITH: MINIMUM SAMPLE PREPARATION FOR THE Artalyst, VoZ.104 TABLE I11 COMPARISON OF ABSORBANCES OF EXTRACTED AND NON-EXTRACTED CADMIUM AND LEAD STANDARD SOLUTIONS, SHOWING RECOVERY BY THE SOLVENT-EXTRACTION PROCEDURE Standard concentration/ pg ml-l 0.06 0.15 0.30 0.75 1.50 Cadmium standards A Absorb an c e - Non- Extracted extracted 0.010 0.009 0.024 0.023 0.049 0.047 0.120 0.117 0.221 0.229 Lead standards Absorbance - I A \ Standard Recovery, concentration/ Non- Recovery, 0.6 0.009 0.010 90 % 111 104 1.5 0.019 0.020 95 104 3.0 0.038 0.036 106 103 7.5 0.095 0.092 103 97 15.0 0.186 0.180 103 pg ml-l Extracted extracted % Sodium and potassium Sodium and potassium can form refractory compounds during digestion and may also ionise in an air - acetylene flame.To overcome these effects, 4 ml of sample or standard solutions were added to 1 ml of a solution containing 5% lanthanum - 2% caesium before aspirating into the instrument using the settings shown in Table I. The calibration lines were curved over the standard range used. Phosphorus The molybdophosphovanadate yellow colour method described by Jackson' was examined for its applicability to the determination of phosphorus levels in pig faeces digest solutions. A 1.0-ml volume of sample or standard solution was mixed with 10 ml of molybdovanadate reagent, then diluted with water to 50ml in a calibrated flask, and the colour was allowed to develop for at least 10min.Using a wavelength of 440nm and a l-cm light path, a linear calibration graph was obtained for standards in the range 2-15 pg ml-1 of phosphorus. Arsenic Arsenic can be determined in biological materials by the generation of arsine and measure- ment by atomic-absorption spectrophotometry,8 or colorimetrically using silver diethyldithio- arb am ate.^ The atomic-absorption method was chosen because it has the greater sensitivity needed for the materials being studied. Preliminary experiments using digestion with nitric - perchloric acids followed by arsine generation using the method described by Duncan and Parker* showed that variable losses of up to 50% occurred during digestion. Double peaks of arsenic absorbance were recorded, indicating that arsine was being formed at two different reaction rates.A similar occurrence was observed by Aggett and Aspell,lo who used the differences in reaction rates to separate arsenic(II1) from arsenic(V) in sample digests. Another digestion technique was sought that would not result in losses of arsenic and that would maintain arsenic in a single valency state for hydride generation. Simon et aZ.11 showed that loss of arsenic as the volatile arsenic(II1) chloride during acid digestion procedures can be prevented by maintaining strong oxidising conditions by inclusion of sodium molybdate (Na,MoO,) in the digestion mixture. Comparison of the recoveries of trivalent and pentavalent arsenic added to samples before and after digestion showed that under their digestion conditions arsenic was converted into and maintained in the non-volatile pentavalent form, and using a coulometric technique recoveries of approximately 94% were obtained. This procedure was adapted for prevention of losses during digestion and double-peak formation with arsine generation.Test faeces samples were digested for arsenic according to the procedure described earlier. Arsenic standard solutions in the range 0.03-0.36pgml-l in 5% sulphuric acid were pre- pared from the 3 pg ml-l arsenic stock standard solution. A 2-ml volume of sample or standard solution was placed in the reaction vessel with 2.5 ml of concentrated hydrochloric acid. Arsine was generated by the addition of 5 ml of 5% sodium tetrahydroborate(II1) in 0.1 yo sodium hydroxide solution and measured using the instrumental conditions shown in Table I.The calibration line of arsenic concentration veisZts peak height was curved overApril, 1979 DETERMINATION OF TEN ELEMENTS IN PIG FAECES AND FEEDS BY AAS 319 the standard range and was fitted by a quadratic equation. No significant losses of arsenic occurred during digestion of samples (Table V), and arsine was generated at one reaction rate, as indicated by the absence of double peaks during measurement. Results and Discussion The over-all precision of the procedure is summarised in Table IV and shows that coefficients of variation of better than 5% were obtained for all elements except lead and arsenic. The higher variability associated with the determination of these two elements is consistent with their presence at relatively low concentrations in the sample.TABLE IV RESULTS OF REPLICATE ANALYSIS OF 2-g SAMPLES OF BULK PIG FAECES USING THE RECOMMENDED PROCEDURE Element Parameter Cu Zn Cd Pb Fe Na K Mg Ca P As Number of replicates . . . . . . 6 6 12 12 6 6 6 6 6 6 6 Mean concentration (dry matterbasis) . . .. .. 290 511 0.86 8.96 1740 0.32% 0.83% 0.82% 3.88% 2.45% 2.0 Standard deviation . . . . . . 10.5 23.8 0.04 0.84 40 0.01% 0.03% 0.02% 0.09% 0.06% 0.27 Coefficient of variation, % . . .. 3.6 4.7 4.8 9.4 2.3 3.3 3.8 2.1 2.4 2.3 13.5 I.Lg g-1 vg g-1 wg g-1 I.Lg g-1 Yg g-' Ilg g-' Ilgg-1 vg g-l w g - l w g - ' vgg-' wg g-1 The mean recovery of standard additions of all elements made before and after digestion are summarised in Table V.Application of Student's t-test indicated no significant losses of any element during the digestion procedure. This is important as the literature frequently reports losses of cadmium, lead and arsenic in procedures for determining these elements in biological material. TABLE V STATISTICAL COMPARISON OF RECOVERIES OF ELEMENTS ADDED TO 2 g OF PIG FAECES BEFORE AND AFTER DIGESTION Number of Element replicates Amount added cu 3 200 Pg Zn 3 600 CLg Cd 4 2 CLg Pb 4 20 Fe 3 1000 pg Na 4 20 mg K 4 10 mg 3 10 mg 3 20 mg Mg Ca P 3 20 mg As 3 3 * N.S. indicates not significant. Mean recovery, % Pre-digestion Pos t-diges tion addition addition 105.8 f 1.5 97.5 f 9.8 98.6 f 3.6 95.1 f 6.8 91.9 f 4.4 87.2 f 4.0 93.0 f 17.8 97.9 f 6.5 93.2 &- 10.1 101.5 & 11.8 101.9 f 9.6 105.2 f 9.0 100.1 f 7.1 93.5 f 9.6 98.5 f 12.3 90.3 f 4.4 91.5 f 9.0 91.1 f 8.5 110.5 f 9.0 f A \ 101.7 f 12.4 100.7 & 2.6 101.9 f 4.4 Student's t-test (P <0.05) N.S.* N.S.N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. The mean recoveries of all elements added to increasing masses of sample are summarised in Table VI. The recoveries were quantitative for copper, zinc, lead, sodium, potassium, magnesium, calcium and arsenic. Lower recoveries, but better than 90%, were observed for cadmium, iron and phosphorus. These losses could not be accounted for by losses during digestion (Table V) or by chemical association or precipitation with other elements or com- pounds in the sample material (Tables V and VI). The losses were of constant magnitude and could perhaps be explained by the formation of insoluble salts of the digesting acids or by the absorption of small amounts of these elements on the surface of the digestion flask.Similar losses for iron were reported by the US National Bureau of Standards in the analysis of their reference materials. Coefficients of variation around the mean percentage recovery320 HILLIARD AND SMITH : MINIMUM SAMPLE PREPARATION FOR THE Analyst, V d . 104 of cadmium, lead and iron (Table VI) were sufficiently low to permit the valid application of factors to correct the results obtained with the technique described. Measured concentra- tions of cadmium, iron and phosphorus (in sample digests) were corrected for apparent losses by dividing by 0.90, 0.92 and 0.94, respectively. These factors represent the mean recovery of these elements as shown in Table VI.TABLE VI MEAN PERCENTAGE RECOVERIES OF TWO LEVELS OF STANDARD ADDITION T 1 INCREASING MASSES OF A REPRESENTATIVE PIG FAECES SAMPLE Element c u Zn Cd Pb Fe Na K Mg Ca P As Standard addition 200 CLQ 300 Pg 600 Pg 900 Clg 2.0 Pg 3.0 Pg 20 P!3 30 Pg 1000 pg 1500 pg 20 mg 30 mg 10 mg 15 mg 10 mg 15 mg 20 mg 30 mg 20 mg 30 mg 3.0 CLg 6.0 Pg Mean* recoveries (yo) from r A \ 1.0 g 1.5 g 2.0 g 100.3 102.6 97.2 98.6 104.1 102.5 99.8 98.4 104.8 106.7 105.7 107.9 83.7 94.7 89.8 93.7 89.2 90.8 99.3 101.9 96.6 108.7 101.0 95.1 93.2 94.2 83.7 90.5 89.8 93.1 99.1 102.3 99.9 95.7 96.6 99.6 95.8 105.0 97.3 97.3 102.5 98.4 91.7 97.2 102.6 102.9 103.4 100.4 94.6 98.8 107.7 100.9 97.5 92.9 96.5 90.8 94.9 100.4 95.4 91.3 99.0 91.1 95.2 94.9 Meant recovery using pooled data, % 101.1 f 5.3 C.V.: = 5.2% 102.1 -+ 6.0 C.V.= 5.9% 90.1 & 4.9 C.V. = 5.4% 99.5 f 10.3 C.V. = 10.3% 92.0 f 7.1 c.v.= 7.7% 99.6 f 3.2 C.V. = 3.2% 100.1 f 8.0 C.V. = 8.0% 100.5 f 6.5 C.V. = 6.5% 98.0 & 7.9 C.V. = 8.0% C.V. = 5.5% 93.9 f 5.2 97.0 & 12.1 C.V. = 12.5% * Mean of 3 determinations. 7 Mean of 18 determinations, except for As, which is mean of 12 determinations. C.V. = coefficient of variation. A two-way analysis of variance was performed to establish if the recovery was affected by two levels of standard addition to increasing masses of sample material, and the results are shown in Table VII. This method of analysis showed an apparently significant effect (P < 0.05) for zinc between recovery and level of standard addition.The mean recovery of 600 pg of zinc added to 1.0, 1.5 and 2.0 g of faeces was 101.0 & 6.2y0, whereas the recovery of 900 pg of zinc from similar masses of sample was 106.7 & 1.7%. Differences of this order could be attributed to pipetting errors and no real practical significance could be attached to these variations. The statistical analysis in Table VII indicated an interactions effect between sample mass, standard addition and recovery for both calcium and cadmium. The recovery data for calcium (Table VI) indicated that when 20 mg of calcium were added to increasing masses of faeces the percentage recovery increased with mass, but when 30mg of calcium were added the recovery decreased with increasing mass of faeces.These results imply that an optimum range existed for calcium recovery and that the maximum recovery of added calcium was obtained when the total concentration of calcium (from sample and standard addition) in the digest was between 700 and 1000 pg ml-l. It is possible thatApril, 1979 DETERMINATION OF TEN ELEMENTS IN PIG FAECES AND FEEDS BY AAS TABLE VII 321 TWO-WAY ANALYSIS OF VARIANCE TO DETERMINE THE EFFECTS ON RECOVERY OF TWO LEVELS OF STANDARD ADDITION TO THREE DIFFERENT MASSES OF BULK PIG FAECES Mean square (M.S.) and degrees of freedom (D.F.) for source of variation A f \ Increased sample Increased standard mass addition Interaction Error - -----I Element M.S. D.F. M.S. D.F. M.S. D.F. M.S. D.F. c u 27.97 2 13.35 1 18.27 2 19.47 12 Zn 28.87 2 145.64* 1 8.41 2 21.42 12 Cd 16.01 2 15.49 1 91.24* 2 17.40 12 Pb 104.39 2 24.50 1 55.77 1 56.89 12 Fe 25.61 2 2.64 1 84.93 2 41.97 12 Na 6.26 2 24.50 1 24.37 2 7.62 12 K 87.32 2 0.02 1 7.48 2 57.64 12 28.77 2 115.52 1 68.53 2 27.15 12 11.77 2 48.35 1 171.88* 2 37.88 12 Ca P 57.42 2 11.36 1 31.36 2 19.48 12 As 79.05 1 2.80 1 23.52 1 188.87 4 * Indicates significance a t P <0.05.Mg these results are a statistical or analytical anomaly, as the analysis of NBS orchard leaves 1571 (Table VIII) by our technique gave a calcium level of 2.1174, which is in good agree- ment with the quoted level of 2.09 & 0.03%. The digest solution of this material had a calcium concentration of approximately 420 pg ml-1, which is outside the apparent optimum range. The interaction effect on cadmium recoveries (Table VII) is barely significant and there were no obvious trends in recovery associated with increasing sample mass or standard addition. We concluded that any apparent significance of the interaction was fortuitous as at a 5% probability level it is possible to obtain one erroneous result in twenty.Our study involved a total of 33 analyses of variance and it was possible for us t o obtain at least one apparently significant result due to chance. TABLE VIII ANALYSIS OF NBS ORCHARD LEAVES 1571 USING THE PROPOSED PROCEDURE Element Certified concentration found* Concentration c u 12 i 1 pgg-1 12 ll.gg-l Zn 25 z t 3 pgg-l 27 C L g e Cd 0.11 & 0.02 pgg-1 0.09 pg 8-1 Pb 45 f 3 pgg-l 47 tLg g-l Na 82 f 6 pgg-l -t 2.11% Mg P 0.21 f 0.01% 0.20% As 14 i 2 pg g-' 16 pg 8-l Fe 300 & 20 pg g-l 287 pg g-l K 1.47 f 0.03% 1.48% 0.62 f 0.02% 0.61% Ca 2.09 f 0.03% * Dry matter basis.Concentrations quoted as found are means of duplicate analyses. t Na was not determined as its concentration in the reference material fell below the calibration range of our procedure. Results of analysis of NBS orchard leaves 1571 are shown in Table VIII. The level of sodium in the orchard leaves is outside the working range of the proposed procedure. Sodium levels similar to those found in orchard leaves can be determined by using the more sensitive sodium line at 589.0 nm. Comparison of the certified values for orchard leaves and those found by using our technique (Table VIII) confirmed the accuracy of our methods.All of the concentrations we found were within the standard deviations associated with the certified levels.322 HILLIARD AND SMITH Our procedure offers high accuracy and precision when used to measure the concentrations of these eleven elements in pig faeces. It is applicable to other biological materials, as shown by analysis of NBS orchard leaves 1571, and can be used to determine economically the concentrations of copper, zinc, cadmium, lead, iron, sodium, potassium, calcium, magnesium and phosphorus from a single digestion. Arsenic can be determined separately using the acid - molybdate digestion solution. Application of the Procedure These procedures were used to analyse samples of pig faeces and pig feeds collected from commercial piggeries in Victoria, Australia.Results of these analyses were used to deter- mine the mineral status of the pig rations and to evaluate the environmental consequences of various methods of disposal or utilisation of piggery effluents. Typical levels of the elements assayed for are presented in Table IX. TABLE IX ANALYSIS OF PIG DIETS AND PIG FAECES USING THE PROPOSED PROCEDURE (DRY MATTER BASIS) Cul Znl Cd/ Pbl Fel N,”, K, Mg, Ca, P, As1 Sample No* !-a g-’ I*g g-’ I*g g-’ I*g g’ I*g g-1 /o % % % % wgg-1 Diet ._ _ . 1 23 231 0.02 1.20 299 0.13 0.49 n.16 1.60 1.00 n.5 - _ _ 2 163 152 0.27 1.24 341 0.25 0.71 0.19 1.65 1.25 0.2 3 183 167 0.31 1.57 458 0.37 0.74 0.21 1.35 1.26 0.5 4 20 140 0.04 2.85 353 0.20 0.61 0.11 1.14 0.93 32.4 5 8 97 0.02 1.22 241 0.14 0.50 0.13 0.68 0.66 0.4 Faeces . . 1 64 766 0.04 12.65 5098 0.18 0.86 0.48 3.21 1.99 4.4 2 364 572 0.74 20.73 2098 0.24 1.05 0.68 4.18 2.04 1.1 3 569 802 1.20 3.88 6407 0.20 0.99 0.82 4.63 3.13 19.7 4 76 622 0.32 6.84 5306 0.28 0.80 0.51 3.40 3.26 102.6 5 55 616 0.26 0.29 1557 0.12 0.87 0.82 2.93 2.15 18.3 The authors thank Mr. G. Perry, Mr. R. Reid and Mr. E. Butler for their assistance during the development and calibration of these analytical techniques. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. References Pearce, G. R., “Managing Livestock Wastes. Proceedings of the 3rd International Symposium on Hilliard, E. P., and Pearce, G. R., Agric. Envir., 1978, 4, 65. Underwood, E. J., “Trace Elements in Human and Animal Nutrition,” Academic Press, New York, Bremner, I., Q. Rev. Biophys., 1974, 7, 75. Christian, G. D., and Feldman, F. J., “Atomic A4bsorption Spectroscopy : Applications in Agri- de Vries, M. P. C., Tiller, K. G., and Beckett, R. S., Commun. Soil Sci. Pl. Anal., 1975, 6, 299. Jackson, M. L., “Soil Chemical Analysis,” Constable, London, 1962, p. 153. Duncan, L., and Parker, C. R., “Varian Techtron Technical Topics,’’ Varian Techtron Pty. Ltd., Analyt‘ical Methods Committee, Analyst, 1975, 100, 54. Aggett, J., and Aspell, A. C., Analyst, 1976, 101, 341. Simon, R. K., Christian, G. D., and Purdy, W. C., Am. J . Clin. Path., 1968, 49, 207. Livestock Wastes,” American Society of Agricultural Engineers, Michigan, 1975, p. 218. 1977. culture, Biology and Medicine,’’ Wiley-Interscience, New York, 1970, p. 188. Springvale, Victoria, Australia. Received August 31st. 1977 Amended August 8th, 1978 Accepted October 2nd, 1978

ISSN:0003-2654    

DOI:10.1039/AN9790400313

出版商:RSC    

年代:1979

数据来源: RSC

摘要:

Analyst, April, 1979, Vol. 104, pp. 323-327 323 Sulphochlorophenol N as a Spectrophotometric Reagent for Vanadium(V) M. Zenki Department of Chemistry, Okayama College of Science, 1-1, Ridai-cho, Okayama-shi, 700, Japan A spectrophotometric method for the determination of trace amounts of vanadium (V) with sulphochlorophenol N is described. With this reagent, vanadium forms a blue complex, which is stable in the pH range 3.7-6.0. The coloured complex obeys Beer's law at 627 nm in aqueous solution with a molar absorptivity of 3.12 x lo4 1 mol-l cm-l. Copper and cobalt ions interfere in this method. Keywords Bisazochromotropac acid dye ; s+ectrophotometry ; sulphochloro- Phenol N ; vanadium determination Many bisazochromotropic acid derivatives, such as arsenazo 111, are well known as highly sensitive spectrophotometric reagents for various metal ions1 Alimarin and co-~orkers~,~ reported that some derivatives of 4,5-dihydroxynaphthalene-2,7-disulphonic acid (chromo- tropic acid) were useful reagents for the photometric determination of niobium and other metals (zirconium, hafnium, vanadium, molybdenum, scandium, aluminium, indium, gallium and palladium). Sulphochlorophenol S (3,6-bis [ (5-chloro-2-hydroxy-3-sulphophenyl) azo] - 4,5-dihydroxynaphthalene-2,7-disulphonic acid), which is a symmetrical derivative, has been used for the determination of niobium in steel^,^^^ tantalum metal,5 titanium oxide,6 uranium' and zirconium alloys.2 However, no derivatives that could be used for the deter- mination of vanadium, which is in the same Group as niobium in the Periodic Table, have been reported.Further investigation of bisazo derivatives of chromotropic acid has revealed that the introduction of a nitro group in the @am-position in one of the benzene rings, such as arsenazo-f~-N0,8,~ or carboxynitrazo,lO produces a high sensitivity and selectivity and a wide absorption peak shift. Preliminary studies have shown that an asymmetric bisazo derivative, sulphochlorophenol N (3- [ (5-chloro-2-hydroxy-3-sulphophenyl) azo]4,5-dihydroxy- 6- [ (4-nitrophenyl)azo]naphthalene-2,7-disulphonic acid) (I) reacts with vanadium rather than niobium to form a blue complex under suitable conditions. This paper reports a sensitive and selective spectrophotometric method for the determina- tion of vanadium using sulphochlorophenol N.Attempts to determine a small amount of vanadium in steels have been made. OH OH Experimental Apparatus Absorption spectra were recorded with a Hitachi, Model 124, automatic recording spectro- photometer and other spectrophotometric measurements were made with a Hitachi, Model 139, spectrophotometer, with 1-cm matched cells. A Hitachi-Horiba pH meter, Model F-~ss, was used for the pH measurements. Reagents in all dilutions. All reagents used were of analytical-reagent grade. De-ionised distilled water was used324 ZENKI: SULPHOCHLOROYHENOL N AS A Analyst, VoJ. 104 3- [ (5-Chloro-2-hydroxy-3-sul~hophenyl)azo] -4,5-dihydroxy-6- [ (4-nitrophenyl)azo]naphthalene- 2,7-disulp honic acid (sulphochloro~henol N ) . Diazotise 2-amino-4-chlorophenol-6-sulphonic acid (0-5 "C) and couple with an equimolar amount of chromotropic acid in dilute sodium hydroxide solution.Salt-out the monoazo dye with saturated sodium chloride solution, and then couple with an equimolar amount of 4-nitroaniline diazonium salt, in the presence of calcium hydroxide, to produce the bisazo dye. Allow the reaction mixture to stand at room temperature for 12 h and acidify it by adding concentrated hydrochloric acid. Filter off the precipitate and wash it with hydrochloric acid (1 + 4). Re-precipitate 2-3 times by dissolving in water by the addition of dilute sodium hydroxide solution, followed by hydrochloric acid, until one spot appears on a paper chromato- gram, developed with 2 M ammonia solution saturated with butan-2-01.11 The extraction method12 was employed to remove calcium and sodium from the purified compound com- pletely.Dissolve 0.2 g of sulphochlorophenol N in 1 1 of de-ionised distilled water. This solution is stable for several months. Vanadium( V ) standard solution. Dissolve 0.585 0 g of ammonium metavanadate (NH,VO,) in water in a 500-ml calibrated flask to make a 1 0 - 2 ~ stock solution. Dilute 100-fold with water to make a working solution. This solution contains 5.1 pg ml-l of vanadium. A 0.1 M acetic acid - 0.1 M sodium acetate solution system was used. The yield is approximately 40%. Bufer solution, pH 5.0. Citric acid solution, 0.1 M. Dissolve 21 g of citric acid in water and dilute to 11. Calibration Using a pipette, introduce aliquots of the standard vanadium(V) solution containing 0, 10.2, 20.4, 30.6 and 40.8 pg of vanadium into 25-ml calibrated flasks.Add 5 ml of buffer solution (pH 5.0), 1 ml of 0.1 M citric acid solution and 5 ml of 0.02% sulphochlorophenol N solution, then dilute to the mark with distilled water. Allow the mixture to stand for 10 min and measure the absorbance at 627 nm, with a reagent blank solution prepared at the same time as the sample solution as reference. Draw a calibration graph; this should be linear and pass through the origin. Absorption Spectra at apparent pH 5.0. Results and Discussion Fig. 1 shows the absorption spectra of sulphochlorophenol N and its vanadium(V) complex The absorption maximum of the complex occurs at 627 nm, and there 600 620 640 660 680 7 10 Wavelength/nm Fig. 1. Absorption spectra: A, vanadium - sulpho- chlorophenol N complex containing 20.4 pg of vanadium(V) measured against reagent blank; and B, reagent blank measured against water.April, 1979 SPECTROPHOTOMETRIC REAGENT FOR VANADIUM(V) 325 was no shift in the wavelength when either the pH was varied from 3.4 to 9.1 or the molar ratio of vanadium to sulphochlorophenol N was varied from 1 : 5 to 5: 1.Sulphochlorophenol N reacted similarly with vanadium(1V) to form a blue complex (absorption maximum 630 nm) under the same conditions. Further investigation was not carried out because the sensitivity was fairly low compared with the absorption of vanadium (V) complexes. Influence of pH from 1.8 to 12.9 (Fig. 2). pH 3.7 and 6.0. Therefore, the pH was adjusted to about 5.0.The influence of the pH on the absorbance at 627nm was examined over a pH range A maximum and constant absorbance was obtained between a, 0.61 O*** 0 2 4 6 I PH Fig. 2. Effect of pH on absorbance measured a t 627 nm. Reagent Concentration The effect of the amount of sulphochlorophenol N on the absorbance was examined by varying the molar ratio of sulphochlorophenol N to vanadium(V), the amount of the latter being kept constant (Fig. 3). The results showed that the absorbance of the complex was constant over a 1.5-fold molar excess of the reagent. The recommended volume of reagent, 5 ml, corresponds to a concentration of about 5.7 x 10-5 M in the final solution. This represents a 1.6-fold excess over the highest point on the calibration graph, i.e., 40 pg of vanadium in 25 ml of solution.Molar ratio of sulphochlorophenol N to vanadium(1V) Fig. 3. Effect of reagent concentra- tion on the formation of the vanadium- (V) complex. Effect of Time complex was examined. The time necessary for complete formation of the sulphochlorophenol N and vanadium Even when a 2-fold molar excess of sulphochlorophenol N was326 ZENKI: SULPHOCHLOROPHENOL N AS A Analyst, Vol. 104 added to vanadium, about 5min were sufficient for complete reaction at 20 "C and the absorbance of the complex did not change for at least 2 d. Therefore, the measurement of the absorbance was carried out a t least 10 min after addition of the reagent. Beer's Law The calibration graph was linear in the range 0-1.6 pg ml-l of vanadium(V), Le., up to at least 40pg of vanadium in 25ml of solution, and its slope corresponded to a molar absorptivity for the complex of 3.12 x lo4 1 mol-l cm-1 at 627 nm. Composition of the Complex Attempts to determine the composition of the complex in aqueous solution were made by the continuous-variation and molar-ratio methods (Fig.3). Both methods revealed that vanadium(V) forms a 1 : 1 complex with sulphochlorophenol N. This is in agreement with Alimarin and Savvin's observation2 that sulphochlorophenol S forms a 1 : 1 complex with niobium. Interferences The effect of several possible interferences on the determination of 20.4pg of vanadium is shown in Table I. No interference was noted with large amounts of acetate, bromide, chloride, citrate, fluoride, iodide, nitrate and sulphate. EDTA and tartrate interfered in the determination.The serious interferences arising from cobalt(I1) and copper(I1) may be caused by complexation with sulphochlorophenol N, which cannot be suppressed by the addition of the usual masking agents. TABLE I EFFECT OF DIVERSE IONS ON VANADIUM(V) DETERMINATION Tests were made by adding the interfering ion t o a solution containing 20.4 pg of vanadium(V). Ion added Al(II1) . . Bi(II1) . . Ca(I1) .. Cd(I1) .. Co(I1) .. Cr(V1) .. Cu(I1) .. Cr(II1) . . Fe(II1) . . Mn(I1) .. Mo(V1) . . Ni(I1). . Sb(II1) . . .. .. W V ) Pb(I1) . . Si(1V) .. Sn(I1) . . Ti(1V) .. Zn(I1) .. Te(1V) . . .. .. .. . . .. .. .. .. .. .. .. .. .. .. .. .. . . - . . . .. Amount of ion added/ pg 20 20 100 100 20 1000 20 20 20 100 1000 100 20 100 20 1000 20 20 20 100 Amount of vanadium recovered/ pg 20.2 19.9 20.4 20.4 30.1 19.6 12.6 33.2 21.0 19.4 21.2 21.3 20.6 20.0 20.4 21.0 20.4 20.4 20.2 20.1 Recovery, % 99.0 97.5 100 100 148 96.1 61.2 163 103 104 104 101 100 103 100 100 95.1 98.0 99.0 98.5 Application to the Determination of Vanadium in Steel Two samples of Japanese Standards of Iron and Steel (JSS) were analysed in order to check the validity of the method.When carrying out the determination of vanadium in steels, a large amount of iron(II1) also interferes and a suitable preliminary treatment is therefore required. If the vanadium(V) ion is reduced to vanadium(IV), the extraction method of Specker and Doll13 with 4-methylpentan-2-one should prove satisfactory. Ammonium iron(I1) sulphate is suitable for this purpose as a reducing agent.The preparation of the sample solution is as follows. Transfer a suitable mass (0.05-0.5 g) of the finely divided iron or steel sample into a 100-ml beaker and add 5 ml of water, 5 ml of concentrated hydrochloric acid and 1 ml of concentrated nitric acid. Heat gently untilApril, 1979 SPECTROPHOTOMETRIC REAGENT FOR VANADIUM(V) 327 all of the metal is in solution, then evaporate almost to dryness. Dissolve the residue in 5 ml of concentrated hydrochloric acid and then transfer the solution completely (rinse with 10 ml of water) into a 100-ml separating funnel. Add 10 ml of concentrated hydro- chloric acid, about 3 mg of ammonium iron(I1) sulphate and 30 ml of 4-methylpentan-2-one, shake the funnel vigorously for a few minutes and allow it to stand for 30min.Transfer the aqueous phase into an evaporating dish and evaporate to dryness. Add a small amount of concentrated nitric acid and heat again. Dissolve the residue in distilled water and adjust this solution to about pH 5 with 1 N sodium hydroxide solution. Then dilute to 100 ml with distilled water in a calibrated flask. Transfer 1-5 ml of the solution, with a pipette, into a 25-ml calibrated flask and determine the vanadium as described above. The results obtained are given in Table 11. It can be seen that the experimental results are in good agreement with the certified values. Recovery tests were also carried out by adding 10.2pg of the vanadium standard solution to the steel-sample solution. The mean recovery was 102% with a standard deviation of 0.5%.TABLE I1 DETERMINATION OF VANADIUM(V) IN JSS SAMPLES Average of at least four determinations. Mass of sample/ ------ -, Relative error, Vanadium content, yo Sample g Certified value Found Y O JSS 159-3 . . . . 0.1017 0.31 0.305 - 1.6 0.200 1 0.316 + 1.9 0.5003 0.320 +3.2 JSS 852-1 . . . . 0.0496 0.52 0.528 + 1.5 0.0498 0.534 +2.7 0.062 8 0.495 -4.8 and 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. The author is indebted to Professor Kyoji TGei, Okayama University, for valuable advice discussions and to Mr. K. Kaichida for technical assistance. References Flaschka, H. A., and Barnard, A. J . , Jr., Editors, “Chelates in Analytical Chemistry,” Volume 2, Alimarin, I. P., and Savvin, S. B., Talanta, 1966, 13, 689. Alimarin, I . P., Savvin, S. B., and Okhanova, L. A., Talanta, 1968, 15, 601. Wakamatsu, S., Bunseki Kagaku, 1969, 18, 376. Hashitani, H., and Adachi, T., Bunseki Kagaku, 1975, 24, 303. Ilsemann, K., and Bock, R., 2. Analyt. Chem., 1975, 274, 185. Budesinsky, B., and Savvin, S. B., 2. Analyt. Chem., 1965, 214, 189. PeriSiC-JanjiC, N. U., Muk, A. A,, and CaniC, V. D., Analyt. Chem., 1973, 45, 798. Muk, A. A., and Pravica, M. B., Analyt. Chem., 1974, 46, 1121. Savvin, S. B., Petrova, T. V., and Romanov, P. N., Talanta, 1972, 19, 1437. Budesinsky, B., and Krumlova, L., Analytica Chim. Acta, 1967, 39, 375. Zenki, M., Analytica Chim. Acta, 1977, 93, 323. Specker, H., and Doll, W., 2. Analyt. Chem., 1956, 152, 178. Marcel Dekker, New York, 1969, p. 1. Received July 14th, 1978 Accepted October llth, 1978

ISSN:0003-2654    

DOI:10.1039/AN9790400323

出版商:RSC    

年代:1979

数据来源: RSC

摘要:

328 Analyst, April, 1979, Vol. 104, $9. 328-333 Oxidative Determination of Dextromoramide (Palfium) in Body Fluids B. Caddy and R. ldowu Forensic Science Unit, Department of Pharmaceutical Chemistry, School of Pharmaceutical Sciences, University of StrathcZyde, GZasgow, G1 1XW The oxidation of dextromoramide to benzophenone with alkaline potassium permanganate and measurement of its ultraviolet absorbance is advocated for the determination of this drug in urine and serum over the concentration range 5-40 pg ml-l. Keywords : Dextrornoramide determination ; urine ; serum ; plasma ; ultraviolet spectrop hotometry Although the drug dextromoramide (I) has been used for some years as an analgesic, there is a paucity of information on methods for its assay when present in biological fluids.This gap has caused problems in drug treatment centres1 and in a forensic2 context where it has been necessary to identify and deterrnine the drug. Interpretation of any results obtained in these circumstances would also be impossible in view of the lack of information available on the urine and blood levels to be expected after normal therapeutic use. This paper describes an oxidative procedure that may be applied to the determination of this drug and/or metabolites containing the diphenylmethyl moiety, following their extraction from an alkaline solution. Reagents n WN - 0 CH;! - Q. It C H - C - C- I I Experimental r L N All reagents were of analytical-reagent grade unless otherwise stated. Instrumentation photometer, using a silica cell with a path length of 2 cm.All ultraviolet spectra were recorded on a Cecil CE505, double-beam ultraviolet spectro- Preparation of Calibration Graphs for Dextromoramide in Aqueous Solution A stock solution containing the equivalent of 5OOpgml-l of dextromoramide base was prepared by dissolving 69.1 mg of dextromoramide tartrate in 100 ml of water. A 20-ml volume of this solution was diluted to 100 ml in order to give a working solution containing 100 pg ml-l of drug base. Aliquots (0.05-0.5 ml) of this working solution were taken and an oxidising solution, prepared by mixing 10 ml of 4% m/V potassium permanganate with 15 ml of 9 M sodium hydroxide solution, was added, followed by 5ml of hexane. The mixture was refluxed for 40 min in a water-bath thermostatically controlled at 70-80 "C.After cooling in air for 15 min, the condenser was rinsed with water to wash any oxidation product into the flask and the mixture transferred into a glass-stoppered test-tube. An aliquot of the hexane layer was removed and its absorbance over the range 220-280nmCADDY AND IDOWU 329 recorded using hexane, which had been separately refluxed with the oxidising mixture, as reference. This procedure was repeated six times for statistical evaluation. The above oxidations with alkaline permanganate were repeated using various strengths of sodium hydroxide solution in the range 3-14 M, the last concentration being that described by Caddy et aL3 for the oxidation of methadone. Preparation of Calibration Graphs for Dextromoramide in Urine Standard solutions of the drug were prepared as detailed above, using drug-free urine in place of water.Aliquots (1-10 ml) of the urine solution (containing 5-50 pg of drug base) were pipetted into 100-ml glass-stoppered test-tubes and solid sodium carbonate and sodium hydrogen carbonate (1 + 1 m/m) added until a saturated solution was obtained. To the alkaline urine an amount of 2,2,4-trimethylpentane - pentan-1-01 (20 + 1 V/V) was added such that the ratio of the volume of urine sample to that of the extracting solvent was not less than 1 : 4. The tubes were shaken for 15min using a tilt shaker and set aside until the phases separated. The extract was evaporated to dryness under reduced pressure and the residue subjected to the oxidation procedure detailed above. The absorbance of the hexane layer was recorded over the range 220-280 nm using hexane from a similarly treated, drug-free urine sample as reference.This procedure was repeated three times for statistical evaluation. Preparation of Calibration Graphs for Dextromoramide in Serum A 2-ml volume of serum was taken in a glass-stoppered test-tube and 0.1-0.8 ml of an aqueous solution containing the equivalent of 100 pg ml-1 of dextromoramide base was added followed by 5 ml of 1 M sodium hydroxide solution and 10 ml of 2,2,4-trimethyl- pentane (reagent grade). Any emulsion formed was completely cleared by adding 5 ml of 2,2,4-trimethylpentane - pentan-l- 01 (20 + 1 V/V). The organic layer was separated and evaporated to dryness under reduced pressure and the residue oxidised with alkaline permanganate as detailed for dextro- moramide in aqueous solutions.Following oxidation, the absorbance of the hexane layer was recorded over the range 220-280 nm using a hexane extract from drug-free serum that had been similarly treated, as the reference solution. The procedure was repeated nine times for statistical evaluation. The mixture was shaken for 15 min using a tilt shaker. Oxidation of Dextromoramide with Other Oxidising Agents Solutions of dextromoramide base containing 20 pg of the drug were oxidised with aqueous acidic dichromate s~lution,~ non-aqueous acidic (glacial acetic acid - concentrated sulphuric acid) chromium(V1) oxide solution5 and acidic cerium(1V) sulphate solution,6 the last procedure being modified by replacing hydrochloric acid with sulphuric acid.Dextro- moramide (20 pg) was oxidised with barium peroxide in 66% rn/V sulphuric acid and 9 M sodium hydroxide solution as described by Wallace et a1.' Drug Regime and Biological Sampling stered to a patient. intervals over a period of 24 h and one sample at 48 h. the alkaline permanganate oxidation procedure detailed above. A single oral therapeutic dose of Palfium (dextromoramide tartrate, 5mg) was admini- Serum (10 ml) and urine (25 ml) samples were obtained at hourly These samples were analysed by Results and Discussion Oxidation of Dextromoramide with Alkaline Permanganate Caddy et aL3 reported that a concentration of 1 4 ~ sodium hydroxide solution is the optimum for the oxidation of dipipanone and methadone with alkaline permanganate.As dextromoramide (I) is structurally similar to both dipipanone (11) and methadone (111), it might be expected that the same conditions would be applicable to its oxidation to benzophenone with alkaline permanganate. This was found to be so, but reproducible quantitative results were not given by this procedure. However, a problem associated with330 - H - l H 3 CADDY AND IDOWU: OXIDATIVE DETERMINATION OF Analyst, vd. 104 Q CH2 -C - 0 C - CH2 - CH3 II H3C\N / H3C 8 - CH2 - CH3 II Ill the use of sodium hydroxide solution at this concentration is that the decomposition of alkaline permanganate to manganate occurs with great facility. This can be explained in terms of the reversible reaction MnO, + HO- + Mn0,2- + HO' proposed by Symons*s@ and by Jezowska-Trezebiatowska et aL1O as the initiating reaction in a multi-step mechanism proposed for the decomposition of alkaline permanganate to manganate and oxygen.An increase in concentration of sodium hydroxide will therefore facilitate the decomposition of permanganate. When using 14 M sodium hydroxide solution, it was observed that the oxidising mixture turned green (indicating the presence of the manganate species) before the oxidation of dextromoramide was completed. The use of 9~ sodium hydroxide solution and an increase in the ratio of permanganate to alkali solution from 1 + 3 (V/V) to 2 + 3 (VlV) was found to be optimum for the oxida- tion of dextromoramide (Fig. 1). This concentration of reagents also ensured that there was an excess of permanganate in the mixture at the end of the oxidation procedure.Further, it was observed that the hexane layer from mixtures that were green owing to the presence of manganate had an unusually high absorbance at 247 nm compared with hexane from mixtures that still had an excess of permanganate after the oxidation. 0.20 - o) 0.15- C m G SI a 0.10- a 0.05- I I 220 240 250 260 270 Wavelength/nrn Fig. 1. Typical spectra of the oxidation product in hexane obtained from 30 pg of dextromoramide originally present in: A, aqueous solution; B, urine; and C, serum; together with D, serum blank; and E, urine blank.April, 1979 DEXTROMORAMIDE (PALFIUM) IN BODY FLUIDS 331 The probable explanation for this observation is that the permanganate was reduced by the organic drug molecule to give the hypomanganate (Mn043-), which in the strongly alkaline medium disproportionated to manganate and manganese dioxide : A fine suspension of manganese dioxide in the hexane layer scattered the light during the ultraviolet measurements, thereby giving rise to the apparent high values of absorbance observed.In the presence of excess of permanganate, any hypomanganate formed was instantane- ously oxidised and the formation of manganese dioxide prevented. Preparation of Calibration Graphs for Dextromoramide in Aqueous Solution and in Urine The choice of extraction solvent is dictated by the need to avoid those solvents (e.g., chloroform) which, even in trace amounts, might interfere by reacting with the oxidant, thereby lowering the yield of benzophenone from the drug.The most effective solvent for this purpose was found to be heptane or 2,2,4-trimethylpentane containing a small amount of pentan-1-01, 2,2,4-trimethylpentane being preferred for urine as heptane gave high blank values. At the solvent evaporation stage it is also most important to remove the last traces of pentan-1-01. The use of a solid mixture of sodium carbonate and sodium hydrogen carbonate to adjust the pH of the urine was found to be advantageous in avoiding emulsification during the extraction procedure. Typical ultraviolet spectra of the oxidation product, which also show appropriate blanks, read against hexane are given in Fig. 1. Statistical evaluation of the graphs obtained from both aqueous (Table I) and urinary (Table 11) samples by comparison of their variances (F = 0.004) shows there is no signifi- cant difference between the two graphs and therefore the extraction of the drug from urine is complete. This finding is consistent with simple weighing experiments using 50-mg samples, which show an extracting efficiency of 97%.A value of 114y0 was obtained from the ratio of the slopes of the two regression lines but it is not possible to calculate the standard deviation of this value. Calibration graphs of absorbance of the hexane layer at 247 nm against concentration of the drug in micrograms per millilitre in water have good linearity and reproducibility over the range 5-50 pg ml-l and can be used in the determination of the drug in urine. Preparation of Calibration Graphs for Dextromoramide in Serum The choice of extraction solvent was determined by the same considerations as stated for TABLE I RELATIONSHIP BETWEEN THE CONCENTRATION OF AQUEOUS SOLUTIONS OF DEXTROMORAMIDE AND THE ABSORBANCE OF ITS ALKALINE PERMANGANATE OXIDATION PRODUCT I N HEXANE Amount of dextromoramide base/pg* 5 10 20 30 40 50 Absorbance of hexane Standard layer a t 247 nmt deviation 0.058 0.013 0.087 0.013 0.176 0.037 0.230 0.032 0.287 0.026 0.373 0.014 Correlation coefficient = 0.975 & 0.015 (95% confidence limits).Regression equation: y = 0.024 + O.O07x, where y = absorbance of hexane layer a t 247 nm and x ( p g ) = amount of dextromoramide base oxidised. Standard error of y = 0.004. * Actual amount of drug oxidised. t All values are the means of six determinations.332 CADDY AND IDOWU : OXIDATIVE DETERMINATION OF TABLE I1 Analyst, VoZ.104 RELATIONSHIP BETWEEN THE CONCENTRATION OF DEXTROMORAMIDE IN URINE AND THE ABSORBANCE OF ITS OXIDATION PRODUCT I N HEXANE Amount of dextromoramide base/pg* 5 10 20 30 40 50 Absorbance of hexane layer a t 247 nmt 0.033 0.094 0.173 0.264 0.315 0.414 Standard deviation 0.032 0.034 0.003 0.048 0.019 0.010 Correlation coefficient = 0.965 f 0.025 (95% confidence limits). Regression equation: y = 0.002 + 0 . 0 0 8 ~ ; x and y as stated in Table I. Standard error of y = 0.009. * Actual amount of drug oxidised. t All values are the means of three determinations. the preparation of the calibration graph for dextromoramide in urine. The 2,2,4-trimethyl- pentane - pentan-1-01 mixture used for the extraction of urine was unsuitable for use in the extraction of serum as it gave rise to high blank values in the final hexane solution and recourse was made to 2,2,4-trimethylpentane alone.The recovery of dextromoramide from serum using this solvent was found to be 36% as measured from the ratio of the slopes of the regression lines. This value is lower than would be expected from simple weighing experiments using 50-mg samples of drug extracted from plasma (68%) and may be either a reflection of the efficiency of oxidation for this type of sample or more simply because of the reduction in solvent polarity that results from the omission of the pentan-1-01. How- ever, the extract was clean and results were reproducible. The analytical results are given in Table 111. A typical ultraviolet spectrum of the oxidation product produced from the oxidation of an extract of serum, together with an appropriate blank, read against hexane, is shown in Fig.1. TABLE I11 RELATIONSHIP BETWEEN THE CONCENTRATION OF DEXTROMORAMIDE IN SERUM AND THE ABSORBANCE OF ITS OXIDATION PRODUCT I N HEXANE Concentration of dextromoramide base*/ Absorbance of hexane Standard d-' layer a t 247 nmt deviation 5 10 20 30 40 0.022 0.049 0.094 0.146 0.208 0.0062 0.0103 0.0192 0.041 0 0.025 Correlation coefficient = 0.94 -& 0.03 (95% confidence limits). Regression equation: y = 0.005 1 + 0.0026%; x and y as in Table I. Standard error of y = 0.0035. * Original concentration of drug in a 2-ml sample of serum. t All values are means of nine determinations. Serum and Plasma Levels Found in a Patient Administered a Single Therapeutic Dose of Palfium The methods described above have been applied successfully to the determination of dextromoramide and/or its metabolites containing the diphenylmethyl moiety present in the urine and serum of a patient administered a single oral therapeutic dose of the drug.The levels found are given in Table IV. The time of maximum serum concentration is 4 h and that for urine 5 h. Interestingly the concentration in the serum is still higher thanA@+?, 1979 DEXTROMORAMIDE (PALFIUM) IN BODY FLUIDS TABLE IV URINE AND SERUM LEVELS OF DEXTROMORAMIDE FOUND OVER A 48-h PERIOD FOLLOWING THE INGESTION OF A SINGLE THERAPEUTIC DOSE The results also include any metabolites containing the diphenylmethyl group.333 Time/h . . .. .. . . 1 2 3 4 5 6 7 8 24 48 Serum concentration/ig in 10 ml . . 21 23 28.5 29.5 29 24.5 22.8 21 18.5 18 Urine concentration/pg in 10 ml . . 13.5 14 14.5 14.9 20 8.5 4.1 5 6.5 8 that in the urine even after 48 h. paper. It is hoped to present more excretion data in a further Oxidation of Dextromoramide with Other Oxidising Agents The use of reagents other than alkaline permanganate for the oxidation of drugs containing either the diphenylmethyl grouping or an aromatic ring with a suitable side-chain have been reported by several workers.4-7 As many of these compounds, especially in a forensic context, may be present in body fluids together with dextromoramide, it is necessary to establish if this latter drug is oxidised to benzophenone under the conditions used for the oxidative assay of these other drugs.Other reagents, such as acidified dichromateJ4 chromium(V1) oxide5 and acidified cerium(1V) sulphate,6 used for the oxidation of diphen- hydramine4s5 and dexamphetamine,6 respectively, and barium peroxideJ7 used for the oxida- tive assay of methadone, failed to oxidise dextromoramide. Although this failure to oxidise dextromoramide (I) to benzophenone with acidic oxidising agents can be explained by the absence of the requisite structural features, it is difficult to account for the lack of formation of benzophenone when dextromoramide is oxidised with barium peroxide, especially in view of its structural similarity to methadone (111). As barium peroxide has rarely been employed as an oxidant in organic chemistry, the answer may lie in the mode of action of this reagent, which is at present unknown.Use can be made of the selectivity of barium peroxide as oxidant for methadone in an assay for this drug in admixture with dextromoramide. Using the conditions detailed above, a methadone - dextromoramide mixture was first oxidised with barium peroxide and then with alkaline permanganate. The difference between the absorbances of the benzo- phenone in the hexane solution was found to be a measure of the amount of dextromoramide present. Conclusion Oxidation of dextromoramide with alkaline permanganate and subsequent measurement of the absorbance of the benzophenone obtained provides a satisfactory method for the assay of the drug and/or its metabolites containing the diphenylmethyl moiety in biological fluids. Satisfactory calibration graphs were obtained for the drug over the concentration ranges reported. Other oxidation methods investigated were of no analytical value in the oxidative deter- mination of dextromoramide, as the different oxidising agents failed to convert dextro- moramide to benzophenone. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. References Berry, D. J., personal communication. Clatworthy, A. J., personal communication. Caddy, B., Fish, F., Tranter, J . , and Mullen, P. W., J. Forens. Sci. SOC., 1973, 13, 127. Caddy, B., Fish, F., and Tranter, J., Analyst, 1974, 99, 565. Vessman, J . , Hartwig, P., and Stromberg, S., Acta Pharm. Suec., 1970, 7, 373. Wallace, J . E., Biggs, J . D., and Ladd, S. L., Analyt. Chem., 1968, 40, 2207. Wallace, J . E., Hamilton, H. E., Payte, J. T., and Blum, K., J. Pharm. Scz., 1972, 61, 1397. Symons, M. C. R., J . Chem. SOC., 1953, 3956. Symons, M. C. R., J . Chem. SOC., 1954, 3676. Jezowska-Trezebiatowska, B., Nawojska, M., and Wronska, M., Bull. Acad. Pol. Sci., Cl. 111, 1953, Received ApriE 24th, 1978 Accepted October 19th, 1978 1, 311; Chem. Abstr., 1954, 48, 97952.

ISSN:0003-2654    

DOI:10.1039/AN9790400328

出版商:RSC    

年代:1979

数据来源: RSC