Cover
Title Page
Copyright
Series Foreword
Foreword by Dame Sue Black
Foreword by Commissioner Mark Harrison
Foreword to the 1^st Edition
Book Endorsements
Preface to the 2^nd Edition
List of Abbreviations
About the Companion Website
Introduction: Stable Isotope ‘Profiling’ or Chemical ‘DNA’: A New Dawn for Forensic Chemistry?
1. References
Part I: How it Works
1. Chapter I.1: What are Stable Isotopes?
2. Chapter I.2: Natural Abundance Variation of Stable Isotopes
3. Chapter I.3: Chemically Identical and Yet Not the Same
4. Chapter I.4: Isotope Effects, Mass Discrimination and Isotopic Fractionation
  1. I.4.1 Physical Chemistry Background
  2. I.4.2 Fractionation Factor α and Enrichment Factor ε
  3. I.4.3 Isotopic Fractionation in Rayleigh Processes
5. Chapter I.5: Stable Isotopic Distribution and Isotopic Fractionation of Light Elements in Nature?
  1. I.5.1 Hydrogen
  2. I.5.2 Oxygen
  3. I.5.3 Carbon
  4. I.5.4 Nitrogen
  5. I.5.5 Sulfur
  6. I.5.6 Isoscapes
6. Chapter I.6: Stable Isotope Forensics in Everyday Life
  1. I.6.1 “Food Forensics”
  2. I.6.2 Authenticity and Provenance of other Premium Products
  3. I.6.3 Counterfeit Pharmaceuticals
  4. I.6.4 Environmental Forensics
  5. I.6.5 Wildlife Forensics
  6. I.6.6 Anti-Doping Control
7. Chapter I.7: Summary of Part I
8. References Part I
Part II: Instrumentation, Analytical Techniques and Data Quality
1. Chapter II.1: Mass Spectrometry versus Isotope Ratio Mass Spectrometry
  1. II.1.1 Stability, Isotopic Linearity and Isotopic Calibration
2. Chapter II.2: Instrumentation for Stable Isotope Analysis
  1. II.2.1 Dual-Inlet IRMS Systems
  2. II.2.2 Continuous-Flow IRMS Systems
  3. II.2.3 Bulk Material Stable Isotope Analysis
  4. II.2.4 Compound-Specific Stable Isotope Analysis of Volatile Organic Compounds
  5. II.2.5 Compound-Specific ¹³C/¹⁵N Analysis of Polar, Non-Volatile Organic Compounds by LC-IRMS
  6. II.2.6 Compound-Specific Isotope Analysis and Forensic Compound Identification
3. Chapter II.3: Quality Control and Quality Assurance in Continuous-Flow Isotope Ratio Mass Spectrometry
  1. II.3.1 Compliance with IUPAC Guidelines is a Prerequisite not a Luxury
  2. II.3.2 The Identical Treatment Principle
  3. II.3.3 The Importance of Scale Normalization
4. Chapter II.4: Points of Note for Stable Isotope Analysis
  1. II.4.1 Preparing for Analysis
  2. II.4.2 Generic Considerations for BSIA
  3. II.4.3 Particular Considerations for BSIA
  4. II.4.4 Points of Note for CSIA
5. Chapter II.5: Statistical Analysis of Stable Isotope Data within a Forensic Context
  1. II.5.1 Chemometric Analysis
  2. II.5.2 Bayesian Analysis
6. Chapter II.6: Quality Control and Quality Assurance in Forensic Stable Isotope Analysis
  1. II.6.1 Accreditation to ISO 17025
  2. II.6.2 The Forensic Isotope Ratio Mass Spectrometry Network
7. Chapter II.7: Summary of Part II
8. Appendix II.A: How to Set Up a Laboratory for Continuous-Flow Isotope Ratio Mass Spectrometry
  1. II.A.1 Pre-Installation Requirements
  2. II.A.2 Laboratory Location
  3. II.A.3 Temperature Control
  4. II.A.4 Power Supply
  5. II.A.5 Gas Supply
  6. II.A.6 Forensic Laboratory Considerations
  7. II.A.7 Finishing Touches
9. Appendix II.B: Sources of International Reference Materials and Tertiary Standards
10. Appendix II.C: Selected Sample Preparation Protocols
  1. II.C.1 Derivatization of Amino Acids for Compound Specific Isotope Analysis by GC-IRMS
  2. II.C.2 Acid Digest of Carbonate from Bio-apatite for ¹³C and $c0II-math-113$ Analysis
  3. II.C.3 Preparing Silver Phosphate from Bio-apatite for ¹⁸O Analysis
  4. II.C.4 Two-Point Water Equilibration Protocol for Determination of Non-ex δ²H Values of Human Hair
11. Appendix II.D: Internet Sources of Guidance and Policy Documents
12. References Part II
Part III: Stable Isotope Forensics: Case Studies and Current Research
1. Chapter III.1: Forensic Context
  1. III.1.1 Legal Context
2. Chapter III.2: Distinguishing Drugs
  1. III.2.1 Natural and Semisynthetic Drugs
  2. III.2.2 Synthetic Drugs
  3. III.2.3 “Legal Highs” and “Designer Drugs”
  4. III.2.4 Excipients
  5. III.2.5 Conclusions
3. Chapter III.3: Elucidating Explosives
  1. III.3.1 Stable Isotope Analysis of Explosives and Precursors
  2. III.3.2 Potential Pitfalls
  3. III.3.3 Conclusions
4. Chapter III.4: Matching Matchsticks
  1. III.4.1 ¹³C-Bulk Isotope Analysis
  2. III.4.2 ¹⁸O-Bulk Isotope Analysis
  3. III.4.3 ²H-Bulk Isotope Analysis
  4. III.4.4 Matching Matches from Fire Scenes
  5. III.4.5 Conclusions
5. Chapter III.5: Provenancing People
  1. III.5.1 Stable Isotope Abundance Variation in Human Tissue
  2. III.5.2 Case Examples
  3. III.5.3 Conclusions and Caveats
6. Chapter III.6: Stable Isotope Forensics of Other Physical Evidence
  1. III.6.1 Microbial Isotope Forensics
  2. III.6.2 Toxins and Poisons
  3. III.6.3 Paper, Plastic (Bags) and Parcel Tape
  4. III.6.4 Conclusions
7. Chapter III.7: Evaluative Interpretation of Forensic Stable Isotope Data
  1. III.7.1 Not Scale Referenced δ-Values
  2. III.7.2 Unresolved Contradictory Data
  3. III.7.3 Foregone Conclusions
  4. III.7.4 Logical Fallacies
  5. III.7.5 Untested Assumptions
  6. III.7.6 Conclusion
8. Chapter III.8: Summary of Part III
9. Appendix III.A: An Abridged List of Forensic Stable Isotope Laboratories Worldwide
10. References Part III
Recommended Reading
1. Books
2. Reviews
Author's Biography
Acknowledgements
Index
End User License Agreement

List of Illustrations

Chapter I.2: Natural Abundance Variation of Stable Isotopes
1. Figure I.1 New Period Table of Elements showing isotope abundance ranges.
Chapter I.3: Chemically Identical and Yet Not the Same
1. Figure I.2 δ²H and δ¹³C values of beet sugar and cane sugar of different geographic origin.
Chapter I.5: Stable Isotopic Distribution and Isotopic Fractionation of Light Elements in Nature?
1. Figure I.3 Schematic representation of changing δ²H and δ¹⁸O-values of meteoric water as a result of repeated fractional precipitation.
2. Figure I.4 δ²H and δ¹⁸O values of whole wood and plant sugars (beet as well as cane sugar) in the framework of the global meteoric water line (GMWL).
3. Figure I.5 Correlation plot of δ¹⁸O values versus δ²H values of fruit water pressed from fresh raspberries grown in Spain and in Scotland. Error bars are ± 1 σ. Solid trend line is based on least squares regression while the hashed trend lines is based on orthogonal regression.
4. Figure I.6 Correlation plot of true, H-exchange corrected δ²H_VSMOW values and δ¹⁸O_VSMOW values of raw cotton from eight different countries. Error bars are ± 1 σ. Trend line is δ²H = 3.83 δ¹⁸O – 133.13.
5. Figure I.7 Bivariate graph plotting δ¹⁵N versus δ¹³C-values of scalp hair samples volunteered by residents in different countries reflecting their regionally different diet. Error bars are ± 1 σ of groups comprising 4 to 10 individuals per region.
6. Figure I.8 ¹³C isotopic composition of selected fruit, meat, fish and vegetables. Please note, human collagen and human hair δ¹³C-values included here are typical for people with a terrestrial C₃-plant dominated diet.
7. Figure I.9 ¹⁵N isotopic composition isotopic composition of selected fruit, meat, fish and vegetables. Please, note, δ¹⁵N values of fruit and vegetable are not fixed constants but vary depending on farming practice and type of fertilizer usage.
8. Figure I.10 Simplified schematic representation of typical δ¹⁵N-values for proteinogenous tissue of terrestrial mammals in relation to their trophic level in the food web.
9. Figure I.11 Global δ²H isoscape of ²H abundance in annual precipitation.
10. Figure I.12 Isoscapes of ²H (left) and ¹⁸O abundance (right) in freshwater lakes and reservoirs in Scotland. Red dots mark sampling locations. X and Y axes are degrees Longitude West and degrees Latitude North.
11. Figure I.13 δ²H isoscape of ²H abundance in annual precipitation of 2009 in New Zealand.
12. Figure I.14 Global δ¹³C isoscape of mean annual ¹³C abundance in plant carbon of terrestrial vegetation.
Chapter I.6: Stable Isotope Forensics in Everyday Life
1. Figure I.15 Natural variation in ¹³C isotopic composition of single seed vegetable oils and selected fatty acids isolated from these oils.
2. Figure I.16 Dendrogram of 11 pumpkin seed oils obtained from Hierarchical Cluster Analysis of a multivariate data set comprised of ²H, ¹³C and ¹⁸O abundance values and concentration values of 17 trace elements.
3. Figure I.17 Bivariate plot of δ²H and δ¹⁸O values of authentic Scottish whisky samples as well as whisky samples known or suspected to be counterfeit;
4. Figure I.18 An isotopic bivariate plot of δ¹³C and δ¹⁵N-values of the API Folic Acid from three different manufacturers at three different locations; mean ±1 σ of each cluster is shown in the middle of the cluster.
5. Figure I.19 An isotopic bivariate plot of δ¹³C and δ¹⁸O-values of the API Naproxen from six different manufacturers (Mfr A to F) in four different countries.
6. Figure I.20 Principal Component Plot from a principal component analysis of ²H, ¹³C, ¹⁵N and ¹⁸O abundance data of sildenafil citrate tablets from different manufacturers with first and second component explaining 48 % and 39 % respectively of all variability in the data. The large ellipse represents the 95 % confidence interval based on Hotelling's T².
7. Figure I.21 ²H and ¹⁸O abundance data of sildenafil citrate tablets from different manufacturers including genuine Pfizer Viagra® (dashed circle).
8. Figure I.22 Bivariate plot of corresponding δ²H and δ¹³C values of fatty alcohols showing differentiation according to source.
Chapter II.1: Mass Spectrometry versus Isotope Ratio Mass Spectrometry
1. Figure II.1 Schematic (top) and photograph (bottom) of a modern IRMS magnetic sector instrument with multi-collector analyser. IS, ion source; EM, electro-magnet, FCC: Faraday cup collectors.
2. Figure II.2 Graphical representation of isotopic linearity and shot noise envelope for a typical IRMS instrument. Dashed lines at ±0.06 ‰ represent linearity acceptance criterion for ¹³C. Δδ = δ_accepted − δ_measured.
Chapter II.2: Instrumentation for Stable Isotope Analysis
1. Figure II.3 Schematic (top) and photograph (bottom) of a typical continuous-flow elemental analyser–isotope ratio mass spectrometer system (EA-IRMS).
2. Figure II.4 Schematic (top) and photograph (bottom) of a continuous-flow high-temperature conversion/elemental analyser–isotope ratio mass spectrometer system (HTC/EA-IRMS).
3. Figure II.5 Schematic (top) and photograph (bottom) of a gas chromatography/combustion interface IRMS system (GC/C-IRMS).
4. Figure II.6 Schematic (top) and photograph (bottom) of a GC(MS)-IRMS hybrid system based on the author's original design, showing from left to right MS, GC with conversion reactor unit and autosampler, the interface unit to the IRMS, and the IRMS.
Chapter II.3: Quality Control and Quality Assurance in Continuous-Flow Isotope Ratio Mass Spectrometry
1. Figure II.7 Scale normalization equations and linear regression lines obtained from contemporaneously analysed reference materials VMSOW, SLAP2 (solid line) or IAEA-CH-7 and IA-R002 (dashed line) based on data presented in Table II.4.
2. Figure II.8 Scale normalization equations and linear regression lines obtained from contemporaneously analysed reference materials IAEA-CH-7 and IAEA-CH-6 (solid line) or IAEA-CH-7 and NBS 22 (dashed line) based on data presented in Table II.6.
Chapter II.4: Points of Note for Stable Isotope Analysis
1. Figure II.9 A Costech Zero-Blank autosampler as used in our laboratory for bulk stable isotope analysis by EA- or HTC/EA-IRMS. The 1/16′′ tubing above the isolation valve delivers helium to the autosampler tray while the 1/16′′ tubing below delivers helium to the conversion reactor.
2. Figure II.10 Effect of Argon (Ar) concurrently present with CO₂ in the ion source on measured δ¹³C values of same sized aliquots of CO₂ (accepted δ¹³C_VPDB = −32.56 ‰).
3. Figure II.11 Illustration of the potential interference on isotope ratio measurement of an H₂ peak caused by partial overlap with a following N₂ peak.
4. Figure II.12 Comparison of peak heights, peak shape and retention time of an H₂ peak in the absence (left) and the presence (right) of a partially overlapping N₂ peak.
5. Figure II.13 Top: Untreated ammonium nitrate from six different sources. Note the already “wet” appearance of the sample in the top right corner. Bottom: The same samples after an 8-day exposure to ambient atmosphere.
6. Figure II.14 Part of a cellulose sheet showing grey circles around some of the non-exchangeable hydrogen fixed by hydrogen bridge bonding while black circles are drawn around hydrogen atoms prone to exchange.
7. Figure II.15 Part of a protein chain illustrating how intra-molecular hydrogen bridging bonds between peptide bonds maintain (or fix) an α-helical structure. A grey ellipse is drawn around the hydrogen bridging bond to indicate the non-exchangeable nature of the hydrogen atoms locked up in this bond.
8. Figure II.16 Part of a β-keratin sheet showing how intra-molecular hydrogen bridging bonds between peptide bonds maintain (or fix) a β-sheet structure. Grey ellipses are drawn around some of the hydrogen bridging bonds to indicate the non-exchangeable nature of the hydrogen atoms locked up in these bonds.
9. Figure II.17 Consistent longitudinal values of hydrogen exchange corrected true δ²H values of human hair (circles and diamonds) determined as a result of contemporaneous two-stage equilibration and therefore IT principle based measurement of total hydrogen δ²H values (squares).
10. Figure II.18 Comparability of non-exchangeable true δ²H_hair values for four stock hair samples determined by two-point exchange equilibration methods as implemented by three laboratories located in Canada (O), USA (U) and the UK (S).
11. Figure II.19 Correction by comparative equilibration based on linear regression analysis of measured/true δ²H values for β-keratin standards Cow Hoof (CHK) and Bowhead Whale Baleen (BWB-II) (diamonds) with β-keratin standard Chicken Feather (CFK) (square) serving as quality control.
12. Figure II.20 Illustration of the time displacement between ¹³CO₂ (m/z 45) and ¹²CO₂ (m/z 44) peaks of a compound CO₂ peak due to the “inverse” chromatographic isotope effect. Note the S-shaped 45/44 ratio trace as a result of the ¹³CO₂ peak (m/z 45 signal) preceding the ¹²CO₂ peak (m/z 44 signal). The line marks indicate start, centre (apex), and end of the peak/s. Overall peak width of the compound CO₂ peak at baseline is 19 s.
Chapter II.5: Statistical Analysis of Stable Isotope Data within a Forensic Context
1. Figure II.21 Trivariate plots of measured δ¹³C, δ²H and δ¹⁵N values of 10 Ecstasy tablets from eight different seizures in two different European countries. A circle is drawn around the data points of tablets from the same seizure.
2. Figure II.22 HCA using δ²H, δ¹³C, δ¹⁵N and δ¹⁸O values as well as MDMA content from 10 Ecstasy tablets from eight different seizures in two different European countries (furthest neighbour, Euclidean distance). Cases 2, 3 and 4 are Ecstasy tablets from the same seizure.
3. Figure II.23 Plot of PCA score factors for the first two principal components of multivariate data from farmed and wild European sea bass.
4. Figure II.24 The means of δ²H, δ¹³C and δ¹⁸O observations for each of the 51 white paint samples plotted over the smoothed bivariate density (darker colour equates to higher density) for each variate pair. The items are represented as ellipses corresponding to 95 % of the empirical distribution for that item.
Appendix II.A: How to Set Up a Laboratory for Continuous-Flow Isotope Ratio Mass Spectrometry
1. Figure II.A.1 Pressure-triggered change-over unit for helium supply.
2. Figure II.A.2 Laboratory gas delivery manifold fed from external gas supply.
Chapter III.2: Distinguishing Drugs
1. Figure III.1 Morphine and diacetylmorphine a.k.a. heroin.
2. Figure III.2 Cocaine.
3. Figure III.3 Cocaine δ²H (a) and δ¹⁵N (b) isoscapes of Colombia based on 336 authentic samples prepared from coca leafs.
4. Figure III.4 Six amphetamine powders from the 18 seizures isotopically profiled in Figure III.5.
5. Figure III.5 Bivariate isotope profile plot of δ¹⁵N and corresponding δ¹³C values for 18 amphetamine samples seized from 6 different individuals.
6. Figure III.6 Schematic of synthetic routes “Emde”, “Nagai”, “Moscow” and “Hypo” for preparing methamphetamine from ephedrine or pseudoephedrine.
7. Figure III.7 Bivariate isotope profile plot of δ²H and corresponding δ¹³C values of six methamphetamine batches per synthetic route each, synthesized from aliquots of the same precursor. Arrows and isotopic fractionation factors refer to the centroid positions of all batches per synthetic route.
8. Figure III.8 Bivariate isotope profile plot of δ²H and corresponding δ¹³C values of six methamphetamine batches per synthetic route each, synthesized from aliquots of pseudo-ephedrine extracted from Sudafed™ tablets using methylated spirits (DIY store brand). Arrows and isotopic fractionation factors refer to the centroid positions of all batches per synthetic route.
9. Figure III.9 Schematic synthetic route for PMK from safrole.
10. Figure III.10 Schematic synthetic routes for MDMA from PMK.
11. Figure III.11 Bivariate isotope profile plot of δ¹⁵N and corresponding δ¹³C values of six MDMA batches each per synthetic route with three different synthetic routes being studied.
12. Figure III.12 Bivariate isotope profile plot of δ²H and corresponding δ¹³C values of six MDMA batches each per synthetic route with three different synthetic routes being studied.
13. Figure III.13 Dendrogram resulting from HCA of 18 batches of MDMA; three variables; Euclidean distance, single linkage. Cases 1–6, 7–12 and 13–18 refer to synthetic routes Al/Hg amalgam, NaBH₄ and Pt/H₂ respectively.
14. Figure III.14 Bivariate plot of δ²H and corresponding δ¹³C values of MDMA*HCl batches from controlled (recipe “a”), centre-point (recipe “b”) and factorial design synthetic routes.
15. Figure III.15 Bivariate plot of δ¹⁵N and corresponding δ¹³C values of MDMA*HCl batches from controlled (recipe “a”), centre-point (recipe “b”) and factorial design synthetic routes.
16. Figure III.16 PCA scores plot for the first two principal components (PC1, PC2) using both IRMS and GC–MS data (Van Deursen normalized to the sum of the targets; pre-treated with the fourth root method) for all synthesized MDMA*HCl samples permitting discrimination by laboratory product: () Al/Hg amalgam; () NaBH₄; () Pt/H₂ recipe “a”; () Pt/H₂ recipe “b”; () Pt/H₂ factorial design batches.
17. Figure III.17 Schematic synthetic route for 4′-methylmethcathinone (4-MMC) from 4′-methylpropiophenone.
18. Figure III.18 Bivariate isotope profile plot of δ²H and corresponding δ¹³C values of six batches of 4-MMC, synthesized from aliquots of the same precursor #S.
19. Figure III.19 Bivariate isotope profile plot of δ²H and corresponding δ¹³C values of six batches of 4-MMC, synthesized from aliquots of the same precursor #A.
20. Figure III.20 Schematic synthetic route for benzylpiperazine*HCl (BZP*HCl) from piperazine hexahydrate (PH) and piperazine dihydrochloride (PD) via intermediate piperazine*HCl.
21. Figure III.21 Bivariate isotope profile plot of average δ¹⁵N and corresponding mean δ¹³C values of six batches of BZP*HCl, synthesized from aliquots of chemically identical precursors PH and PD sourced from three different suppliers AA, MP and SA.
22. Figure III.22 Bivariate isotope profile plot of δ¹⁵N and corresponding δ¹³C values of 21 designer drug tablets containing both BZP and TMFPP, seized by police on two separate occasions.
23. Figure III.23 Bivariate isotope profile plot of δ²H and corresponding δ¹⁵N values of 21 benzocaine control samples as analysed by two stable isotope laboratories in Australia and the UK. Error bars represent overall measurement uncertainty at 95% confidence level.
24. Figure III.24 PCA scores plot for principal components t(1) and t(2) of a multivariate stable isotope dataset of the benzocaine samples of various seizures from two Operations F and P run by two different UK law enforcement agencies. The first principal component accounts for 83.1% of all the variability in the data. The large ellipse represents the 95% confidence interval based on Hotelling's T². The smaller ellipses are indicative of groupings obtained from HCA of the same dataset.
Chapter III.3: Elucidating Explosives
1. Figure III.25 Bivariate isotope profile plot of δ¹⁵N and corresponding δ¹⁸O values of ammonium nitrate prills (n = 41) from various sources with either country of origin or manufacturer shown where known. Error bars are ±1 σ. Ellipses represent groupings obtained from HCA.
2. Figure III.26 Ammonium nitrate prills from various sources. Image provided courtesy of Dr Sarah Benson (Forensic Operations Laboratory, Australian Federal Police, Canberra).
3. Figure III.27 Detailed bivariate isotope profile plot of δ¹⁵N and corresponding δ¹³C values for the explosive RDX from two different sources demonstrating homogeneity of the samples and repeatability of stable isotope analysis (N = 18). Figure is based on data generated by or for my then PhD student Claire Lock.
4. Figure III.28 Three-dimensional plot of corresponding δ²H, δ¹⁵N and δ¹³C values for the RDX precursor hexamine. The encircled two data points are samples HEX#G and HEX#N from two different bottles of the same batch from the same supplier. Figure is based on data generated by or for my then PhD student Claire Lock.
5. Figure III.29 Dendrogram of a HCA (single linkage, Euclidean distance) of the trivariate stable isotope data set of 15 hexamine samples examined. Figure is based on data generated by or for my then PhD student Claire Lock.
6. Figure III.30 Schematic synthetic route for RDX and HMX from hexamine.
7. Figure III.31 Bivariate plot of δ¹⁵N and corresponding δ¹³C values of six batches of RDX, synthesized from hexamine from five different sources using the Woolwich process.
8. Figure III.32 Chemical structures of HMTD and TATP.
9. Figure III.33 Bivariate isotope profile plot of δ²H and corresponding δ¹³C values of TATP made from acetone from different sources.
10. Figure III.34 Schematic of the first five reaction steps of TATP synthesis involving the enol form of acetone as starting point of the reaction thus explaining the introduction of an alien hydrogen (shown in boldface) into the molecule.
11. Figure III.35 Correlation plot of δ¹⁸O of hydrogen peroxide solutions and corresponding δ¹⁸O values of TATP.
12. Figure III.36 Correlation plot of δ¹⁸O of hydrogen peroxide solutions and corresponding δ¹⁸O values of HMTD.
13. Figure III.37 Changing δ²H values of a 60% hydrogen peroxide solution with increasing dilution. Figure is based on data generated by or for my then PhD student Claire Lock.
14. Figure III.38 Changing δ¹⁸O values of a 60% hydrogen peroxide solution with increasing dilution. Figure is based on data generated by or for my then PhD student Claire Lock.
15. Figure III.39 Mixing curve showing δ¹⁸O values calculated for samples of flour/hydrogen peroxide mixtures composed of decreasing amount of flour and increasing amount of H₂O₂ (0 % mark = 100% flour and no H₂O₂; 100% mark = no flour and 100% H₂O₂ at a concentration of 70% w/w). This mixing curve is based on δ¹⁸O_VSMOW values of +25 ‰ and +12 ‰ for flour and H₂O₂ respectively.
16. Figure III.40 Mixing curve showing δ¹⁸O_VSMOW values calculated for samples of flour/hydrogen peroxide mixtures composed of a constant amount of flour and increasing amounts of H₂O₂ (0% no H₂O₂; 100% mark: flour : H₂O₂ = 50 : 50; 200% mark: flour : H₂O₂ = 33.3 : 66.7). This mixing curve is based on δ¹⁸O_VSMOW values of +25 and +12 ‰ for flour and hydrogen peroxide respectively.
Chapter III.4: Matching Matchsticks
1. Figure III.41 Schematic of a series of reactions that may result in a change of ¹⁸O abundance in oxygen bound as carbonyl (C=O) group. Note that in a living organism the steps involving H⁺ transfer for example would require NADH+H⁺/NADH.
2. Figure III.42 Bivariate isotope profile plot of δ²H and corresponding δ¹³C values from matchsticks recovered at the crime scene, matchsticks seized from the suspect's house and matchsticks collected to serve as controls.
3. Figure III.43 Examination by microscopy of the thin sections of matches secured at the crime scene and seized from the suspects house confirms conclusion drawn from stable isotope analysis presented in Figure III.35.
Chapter III.5: Provenancing People
1. Figure III.44 You are what and where you eat and drink – the presence of stable isotopes of light elements in the human body.
2. Figure III.45 Different human tissues provide different chronological stable isotopic records and thus different levels of information about a person's life history or life trajectory prior to death.
3. Figure III.46 Correlation between δ²H values of human scalp hair and δ²H values of source water for populations whose diet is sourced regionally (non-globalised; dashed line), country-wide (solid lines) or almost globalised (here: North America-wide; dot-dashed line).
4. Figure III.47 Bivariate plot of corresponding δ¹⁵N and δ¹³C values in human scalp hair from people with different geographical, ethnic and cultural backgrounds.
5. Figure III.48 Comparison of matching scalp hair and nail δ¹³C values from 93 volunteers living in 31 countries illustrating the trend for nail δ¹³C values to be slightly more negative than their corresponding hair δ¹³C values (dashed line). The solid line represents the line of δ¹³C (hair) = δ¹³C (nail).
6. Figure III.49 Global distribution of ¹³C in human scalp hair.
7. Figure III.50 Comparison of matching scalp hair and nail δ¹⁵N values from 93 volunteers living in 31 countries illustrating the trend for nail δ¹⁵N values to be more positive than their corresponding hair δ¹⁵N values (dashed line). The solid line represents the line of δ¹⁵N (hair) = δ¹⁵N (nail).
8. Figure III.51 Equilibrium reactions of CO₂/[CO₃²⁻] with and in water that may result in a change of ¹⁸O abundance in oxygen bound in carbon dioxide.
9. Figure III.52 (a) δ¹⁸O isoscape of ¹⁸O abundance in tap water the contiguous USA. (b) δ¹⁸O isoscape of ¹⁸O abundance in carbonate of tooth enamel throughout the USA.
10. Figure III.53 Correlation graphs according to Daux et al. (2008), Longinelli (1984) and Luz and Kolodny (1985) for δ¹⁸O_phosphate v. δ¹⁸O_water and the resulting range of calculated δ¹⁸O_water for the same δ¹⁸O_phosphate.
11. Figure III.54 Correlation graph for δ¹⁸O_phosphate values of tooth enamel, calculated from measured δ¹⁸O_carbonate values, versus corresponding δ¹⁸O_water values taken from the OIPC for the volunteers' known locations.
12. Figure III.55 Approximate δ¹³C values for ¹³C isotopic composition of various body pools and tissue. Please, note, all human tissue δ¹³C-values shown here are based on a terrestrial C₃-plant dominated diet of an omnivore.
13. Figure III.56 ¹³C isotopic composition of various food, animal and human tissue. Please note that human collagen and human hair δ¹³C values shown here are typical for people with a terrestrial C₃ plant-dominated diet.
14. Figure III.57 Simplified schematic representation of corresponding δ¹³C/δ¹⁵N values typically observed for human scalp hair in relation to a person's diet and trophic level or health status.
15. Figure III.58 Bivariate graph plotting δ¹⁵N against corresponding δ¹³C values from scalp hair of a vegan and scalp hair of an omnivore whose staple diet is comprised to a large extent of fish and meat.
16. Figure III.59 Diagram of the area of skull submitted for stable isotope analysis (shaded in black).
17. Figure III.60 Sample of scalp hair as submitted for sequential stable isotope analysis.
18. Figure III.61 Time-resolved changes in ¹⁵N composition of the victim's scalp hair. Long dashed lines indicate periods of stable nutritional status while dot-dashed line indicate periods of nutritional stress that were interpreted to result from (enforced) crash diets to facilitate clandestine transfer across borders.
19. Figure III.62 Time-resolved changes in ²H composition of the victim's scalp hair.
20. Figure III.63 Tentative geographic life history for the last 17 months prior to death as gleaned from ²H analysis of scalp hair segments from the skull found in 2001 at Minerals Road, Conception Bay South, Newfoundland.
21. Figure III.64 Poster based on information derived from, amongst other sources, stable isotope analysis for an appeal to the public for information regarding the murder victim found at Minerals Road, Conceptions Bay South, Newfoundland.
22. Figure III.65 Geographic life trajectory of the murder victim found in the Dublin Royal Canal (ROI, Republic of Ireland) based on ¹⁸O analysis of bone phosphate extracted from a piece of femur.
23. Figure III.66 Chronology of changing diet δ¹³C and tissue δ¹⁵N values falling into three distinct periods I, II and III during the last 12 months in the life of a 5-year-old child.
24. Figure III.67 Schematic chronology of a murder victim's geographic movement showing six periods of residency in four different regions during the last two years of her life. Modelled source water δ¹⁸O values are based on measured hair δ¹⁸O values.
25. Figure III.68 Chronological dietary life history obtained from five different tissue of the murder victim found in Eastern Germany with samples from left to right moving from the most distant to the most recent time period; δ-values of collagen are tissue shift adjusted to bring them line with hair δ-values.
26. Figure III.69 Global map with highlighted areas of model δ¹⁸O predictions for precipitation δ¹⁸O values ranging from −10.1 ‰ to −7.6 ‰ illustrating the constraining power of stable isotope profiling in aid of human provenancing.
27. Figure III.70 Zoomed-in version of the global map shown in Figure III.69 focusing on Central Europe and the United Kingdom.
Chapter III.6: Stable Isotope Forensics of Other Physical Evidence
1. Figure III.71 Correlation plot of total δ²H values and corresponding δ¹⁸O values for seven batches of natural spun cotton yarn made from cotton grown in Argentina (AR), Egypt (EG), Turkey (TR) and Uzbekistan (Uzb). Light circles are centroids of individual analyses (dark circles).
2. Figure III.72 Intra-ream variability in ¹³C and ¹⁸O composition of five different brands of office paper; six samples per ream were collected and each sample was analysed in replicates of eight.
3. Figure III.73 Inter-ream variability in ¹³C and ¹⁸O composition of four different brands of office paper; seven reams per brand were sampled and samples from each ream were analysed in replicates of seven at least.
4. Figure III.74 Bivariate plot of δ²H and corresponding δ¹³C values of intact (untreated) brown parcel tape samples.
5. Figure III.75 Bivariate plot of δ²H and corresponding δ¹³C values of treated brown parcel tape samples, i.e. backing material only.

List of Tables

Chapter I.1: What are Stable Isotopes?
1. Table I.1 Key figures for stable isotopes of light elements
Chapter I.2: Natural Abundance Variation of Stable Isotopes
1. Table I.2 Scale reference points and their defining scale anchors for stable isotopes of light elements
2. Table I.3 A representative but not exhaustive list of international reference materials for stable isotope ratio mass spectrometry together with their stable isotope abundance values as published by the Commission on Isotopic Abundances and Atomic Weights (CIAAW; http://www.ciaaw.org/reference-materials.htm)
Chapter I.3: Chemically Identical and Yet Not the Same
1. Table I.4 Select examples of ¹³C and ²H abundance values of sugar from different plant sources and of different geographic origin
2. Table I.5 Influence of isotopic composition on physical properties of H₂O and its isotopologues
Chapter I.6: Stable Isotope Forensics in Everyday Life
1. Table I.6 Impact of using reference materials (RM) other than VSMOW (RM1) and SLAP (RM2) on δ¹⁸O values calculated using equation I.16
Chapter II.1: Mass Spectrometry versus Isotope Ratio Mass Spectrometry
1. Table II.1 Comparison of MS and IRMS systems when applied to stable isotope analysis at near natural abundance level
Chapter II.2: Instrumentation for Stable Isotope Analysis
1. Table II.2 Key dates in instrument research and development influencing design and evolution of commercially available CF-IRMS systems
Chapter II.3: Quality Control and Quality Assurance in Continuous-Flow Isotope Ratio Mass Spectrometry
1. Table II.3 Example of the day-to-day variability of measured δ values for international reference materials USGS40, USGS41, IAEA-601, IAEA-602, VSMOW and SLAP2, and resulting differences for stretch factor s and off-set b in corresponding scale normalization equations
2. Table II.4 Sample scale normalization to VSMOW/SLAP; δ²H values rounded to 2 decimal places
3. Table II.5 Two end-member δ²H scale normalization to VSMOW showing the effect of appropriate [a] and inappropriate [b] choice of scale anchors (shown in bold face)
4. Table II.6 Organic ¹³C reference materials^a
5. Table II.7 Two-end-member VPDB δ¹³C scale normalization examples showing the effect of appropriate (a) and inappropriate (b) choice of scale anchors (shown in bold face). All δ¹³C values are given as ‰ values
Chapter II.4: Points of Note for Stable Isotope Analysis
1. Table II.8 List of new reference materials for BSIA and CSIA^a (Schimmelmann et al., 2016)
2. Table II.9 Generic batch sequence composition in BSIA favouring high sample throughput under stable experimental conditions using ²H isotope analysis as example
3. Table II.10 Influence of reactor set-up on accuracy of δ²H measurement of caffeine and human hair standards of different ²H composition^a
4. Table II.11 Relative amino acid abundance as % value of the total number of amino acids per protein unit in human hair (α-keratin), claws or feathers (β-keratin), type I collagen (e.g. bone collagen), casein (bovine milk protein) and honey protein
5. Table II.12 Total number of H atoms and number of exchangeable H atoms in α-keratin's 16 most abundant amino acids
6. Table II.13 Calculated and measured molar exchange fraction f_E for H of proteins and cellulose
7. Table II.14 Scale normalized δ²H_VSMOW and δ¹⁸O_VSMOW values for matching paired sets of hair samples from different individuals and geographic regions^a
8. Table II.15 Measured values for the molar H exchange fraction f_E and “true” δ²H_vsmow values of human hair standards USGS42 and USGS43 at different equilibration temperatures
9. Table II.16 Influence of reactor set-up on δ²H values of N- and Cl-rich compounds obtained by CSIA and BSIA using different reactor set-ups^a
Chapter II.5: Statistical Analysis of Stable Isotope Data within a Forensic Context
1. Table II.17 List of 51 white architectural paints from different sources^a
2. Table II.18 Percentage distributions for the likelihood ratios from each comparison^a
Chapter II.6: Quality Control and Quality Assurance in Forensic Stable Isotope Analysis
1. Table II.19 Comparison of longitudinal CO₂ cylinder gas calibration based on averaged Δδ off-sets versus scale normalization. All δ¹³C values are given as ‰ values.
Appendix II.A: How to Set Up a Laboratory for Continuous-Flow Isotope Ratio Mass Spectrometry
1. Table II.A.1 List of useful tools and equipment in an IRMS laboratory
2. Table II.A.2 List of drying agents in order of their hygroscopic nature and thus efficiency as desiccant
Chapter III.2: Distinguishing Drugs
1. Table III.1 Drug schedules and drug classes in the US and the UK respectively
2. Table III.2 Observed ranges for δ²H, δ¹³C, δ¹⁵N and δ¹⁸O values of natural and semisynthetic drugs
3. Table III.3 Stable isotope abundance ranges observed in 529 authentic samples of cocaine from 19 known different South American coca-growing regions
4. Table III.4 Reported δ²H, δ¹³C and δ¹⁵N values of ephedrine *HCl and pseudoephedrine from various sources
5. Table III.5 δ²H values (given as ‰ values) for amphetamines synthesized by the “nitrostyrene” route under controlled conditions and samples seized from a clandestine laboratory
6. Table III.6 Summary δ²H, δ¹³C and δ¹⁵N values of MDMA hydrochloride samples synthesized from aliquots of the same precursor PMK but by three different synthetic routes of reductive amination
Chapter III.3: Elucidating Explosives
1. Table III.7 Summary of fractionation factors α and enrichment factors ϵ for individual hexamine/RDX precursor/product pairs
Chapter III.5: Provenancing People
1. Table III.8 Formation, mineralisation and eruption of selected permanent teeth
2. Table III.9 Approximate tissue specific stable isotope abundance values^a in relation to dietary stable isotopic composition^a for a healthy omnivorous human subsisting on a terrestrial, C₃ plant dominated diet
3. Table III.10 Results of stable isotope analysis of the tissue samples studied in the case of the unidentified body found at Minerals Road, Conception Bay South, Newfoundland. Table is based on data generated by Maria Hillier, Dr Vaughan Grimes, and the author as part of this case investigation. Stable isotope abundance values are given as 10³ × δ^hE

Stable Isotope Forensics

Methods and Forensic Applications of Stable Isotope Analysis

Second Edition

Wolfram Meier-Augenstein

Robert Gordon University

Aberdeen, UK

This edition first published 2018

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Library of Congress Cataloging-in-Publication Data

Names: Meier-Augenstein, Wolfram.

Title: Stable isotope forensics : methods and forensic applications of stable isotope analysis / Professor Dr. Wolfram Meier-Augenstein, Robert Gordon University, Aberdeen, UK.

Description: Second edition. | Hoboken, NJ : Wiley, 2018. | Series: Developments in forensic science | Includes bibliographical references and index. | Description based on print version record and CIP data provided by publisher; resource not viewed.

Identifiers: LCCN 2017010492 (print) | LCCN 2017011764 (ebook) | ISBN 9781119080220 (pdf) | ISBN 9781119080237 (epub) | ISBN 9781119080206 (cloth)

Subjects: LCSH: Chemistry, Forensic. | Stable isotopes.

Classification: LCC RA1057 (ebook) | LCC RA1057 .M45 2018 (print) | DDC 614/.12–dc23

LC record available at https://lccn.loc.gov/2017010492

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Series Foreword

The world of forensic science is changing at a very fast pace in terms of the provision of forensic science services, the development of technologies and knowledge and the interpretation of analytical and other data as it is applied within forensic practice. Practicing forensic scientists are constantly striving to deliver the very best for the judicial process and as such need a reliable and robust knowledge base within their diverse disciplines. It is hoped that this book series will provide a resource by which such knowledge can be underpinned for both students and practitioners of forensic science alike.

It is the objective of this book series to provide a valuable resource for forensic science practitioners, educators and others in that regard. The books developed and published within this series come from some of the leading researchers and practitioners in their fields and will provide essential and relevant information to the reader.

Professor Niamh NicDaéid
Series Editor

Foreword by Dame Sue Black

I am so delighted to be asked to write the foreword for a text where I understand so little of the background science. A reasonable question might be, then why ask a forensic anthropologist to do this when she barely passed Higher Chemistry and has absolutely no experience in the field of stable isotope analysis? One of the most important aspects of working within a forensic team is to know the limits of one's own ability and to recognize and utilize the strengths of others. It has been my pleasure to work with Wolfram for many years and when forensic casework comes to me, it is without second thought that I pass it on to him knowing that the investigative authorities will not be hoodwinked by a pseudoscientist.

A single-author text in these days is rare and the value of this book lies in the dedication and experience of the author, which is evident in the clarity of prose, the honest illustration of evidence and the realistic practical application of the subject – it makes this a text of genuine scientific value. That a second edition has been requested is a clear indication that the field is still progressing and that new research is still being reported. In the current world of forensic science flux, it is vital that robust scientific research endeavours continue and that it be reported not only in published peer-reviewed papers but collocated in scholarly tomes for easy reference.

In my early discussions with Wolfram I admit to having been a bit of a sceptic, but over time I have been educated and fully persuaded of the value of stable isotope analysis to the world of provenancing and human identification. There have been several instances where conclusions drawn regarding ethnic origin based on forensic anthropological examination of skeletal remains were corroborated independently by results from stable isotope analysis of bone and teeth. One need only read the case histories included in the text to appreciate the practical value of this approach to forensic investigations and, in particular, when attempting to establish the identity of the deceased, which is a pivotal component of any successful investigation.

For me, one of the most important and reassuring aspects of this text is its brutal openness, honesty and transparency. Without apology it identifies equally where are the strengths and limitations of the science and its interpretation for forensic purposes. Whilst this book will challenge those who are not chemically literate, it will quickly become established as the “go-to” text for all practitioners and end users who require to have a firm grasp of the complexities of the subject if its relevance is to be fully understood as a part of intelligence-based investigation.

Prof. Dame Sue Black, PhD, DBE, OBE, FRSE
Leverhulme Research Centre for Forensic Science
University of Dundee, UK

Foreword by Commissioner Mark Harrison

As an early adopter in applying stable isotope forensic techniques to aid my own criminal investigations, I have followed closely its further development and I am honoured to write the foreword for this second edition of Stable Isotope Forensics by Dr Meier-Augenstein.

Since Dr Meier-Augenstein's first edition of this textbook, crime, through globalization has become more transnational requiring law enforcement to operate in a criminal environment where uncertainty and complexity are increasing and their time to respond is decreasing. Forensic science's response to these challenges has seen the expansion of its contribution beyond prosecution and more to aid investigators in the disruption of crime.

This changing emphasis by law enforcement to one of disrupting organized crime and terrorism is enabling stable isotope forensics (SIF) to increase its value to investigators whereby its contribution to casework is both evidential and in the provision of forensic intelligence.

Criminal syndicates are increasingly interconnected and often commodity based and it is here that SIF profiling is adding value in diverse areas such as narcotics, human trafficking and environmental crime, where provenance is an investigative priority enabling the mapping of criminal networks and the source and transit countries they use. Further SIF innovation has been seen in recent times through countries testing the waste water in their cities and towns to gain greater understanding of the geographic and demographic profiles of drug use, bringing together law enforcement and health agencies in harm reduction programs.

Since the first edition of this book, terrorist groups have become less formalized and radicalization affects all societies through the interconnected world of the Internet. The online-inspired foreign fighter phenomenon has enabled opportunities for SIF profiles to provide significant forensic intelligence value to law enforcement in provenancing the origin of these terrorists and their movements throughout the world.

The scope of SIF contribution is expanding and is only currently limited due to the provision of reference databases. The next decade will see increasing convergences with other techniques such as DNA phenotyping to provide a more holistic picture of criminal identity. Big data challenges will also be addressed to enable timely processing of samples for both evidentiary and forensic intelligence purposes to rapidly answer the who, what, where and how that are, and will continue to be the key drivers of all criminal investigations.

Commissioner Mark Harrison, MBE
Head of Criminal Intelligence, Australian Federal Police

Foreword to the 1^st Edition

I am delighted to be able to write the foreword for this, the first textbook on stable isotope forensics.

The coverage is wide, ranging from fundamentals to policy issues, and therefore this text will be of benefit to practitioners, researchers and investigators, indeed to anyone who has an interest in this new forensic discipline.

The year 2001 saw the formation of the Forensic Isotope Ratio Mass Spectrometry (FIRMS) Network. Since then much has been achieved in terms of advancing the forensic application of stable isotope analysis, this textbook being the latest significant step.