Materials Subcommittee response to LRC comments on ASTM 2330 

and ASTM E2926 methods

The following section aims to address and clarify some general misconceptions 

reported by the LRC members in both documents (E2330 and E2926). Some general 

observations are provided below, while more specific answers are provided later in 

the document next to their respective LRC questions/comments.

1. The OSAC Materials Subcommittee would like to clarify that several of the LRC 

comments are beyond the scope of an ASTM standard test method:

A. An ASTM standard is a document that has been developed and 

established within the consensus principles of the society and that meets the 

approval requirements of ASTM procedures and regulations. 

B. There are various types of ASTM standards depending on the 

technical content and intended use (test methods, guide, practice, etc).

C. These two ASTM methods discussed here are “standard test methods.” 

The primary scope of a standard test method is to “describe a definitive 

procedure that produces a test result”, such as identification and 

measurement of the elemental profiles of glass.

D. The intended audience of these ASTM documents is the forensic 

practitioners who conduct the glass analyses.

E. As per the ASTM internal guide, documents require language 

consistency: use the word shall when stating mandatory requirements, use 

the word should as advisory, use the word may to indicate optional 

directives, avoid use of must whenever possible. The whole process of 

changing shall/should/must requires new balloting. Both of the revised 

methods were developed keeping this in mind with thorough consideration 

of the practical implications on when/why to use one term over the other.

F. The ASTM international guide requires the use of SI units.

G. With respect to comments regarding the references for a particular 

statement or recommendation, the ASTM international guide has 

requirements for the references to be included in the standard. They read, 

“Include only references to publications supporting or providing needed 

supplementary information. Historical and acknowledgment references are 

not desirable.” Per this requirement, background data about the value of 

elemental analysis of glass is beyond the scope of the standard.

H. The statement about safety concerns is a required caveat by ASTM.
I. The statement “This guide cannot replace knowledge, skill, ability 

acquired...” is not required by ASTM but is highly recommended by the E30 

ASTM committee. 

The intent of this wording appears to have been misinterpreted by the 

members of the Legal Resource Committee. This is standard ASTM E30 

wording that was intentionally placed into all ASTM forensic standards. The 

purpose of the wording is to prevent people who do not have any training 

from picking up the standard and performing the work without the proper 

background (training and demonstration of competence and proficiency). 

Hence the wording that is used in this standard cannot replace training and 

experience. People who use this standard should also have the knowledge, 

training, and experience necessary to perform the work. (Statement provided 

by Fire Debris Subcommittee)

Issues of interpretation, documentation, and training raised by the LRC are beyond 

the scope of these documents. Although we recognize that some of these concerns 

are valid for the overall practice of trace evidence, they can’t be addressed in an 

ASTM test method and therefore should not apply to the decision/recommendation 

of whether or not the test method should be included in the OSAC registry. See Form 

and Style for ASTM Methods (http://www.astm.org/COMMIT/Blue_Book.pdf). 

2. The OSAC Materials Subcommittee would like to provide some background on 

how the test criteria (a.k.a match criteria) were included in the ASTM standard test 

methods:

A. These methods are documents developed through a structured 

and rigorous consensus process that establish criteria for the analysis 

or methodology used during a particular examination. In the particular 

case of these two methods, they are designed to specify how the 

elemental analysis of glass is conducted for forensic comparisons (by 

ICP-MS or μXRF, respectively).

B. These ASTM standards were drafted by a NIJ-funded scientific group 

(the Elemental Analysis Working Group, a group of 34 scientists with 

particular expertise in elemental analysis of glass materials (forensic glass 

practitioners, researchers, and statisticians). The method was then exposed 

to revision by ASTM subcommittee and later exposed to the main committee 

and balloting/review process. 

C. The test criteria reported on these methods were based on interlaboratory studies designed to minimize both type I and type II errors in the 

comparison of elemental data. Several test criteria were tested on these 

studies based on statistical methods previously reported in 

validation/population/survey studies. Some methods that the forensic 

community was using in their protocols were also included in the study - no
consensus on match criteria existed within the community at the time the 

inter-laboratory tests were started. 

D. The inter-laboratory tests not only provided an effective way of crossvalidating methods used for the elemental analysis of glass but also

demonstrated which match criteria were more appropriate for elemental 

analysis of glass. The studies showed that the selection of test criteria was 

dependent on the capabilities, limitations and precision of the method of 

analysis. After thorough evaluation of the data derived from “worst case 

scenarios” the group arrived at a consensus on the best test criteria for glass 

examinations (by ICPMS, LAICPMS or μXRF). Decisions were made on the 

basis of lowest type I and type II error rates. 

For example, ICP-MS and LA-ICPMS provide quantitative data with the

precision of the measurements typically lower than 3%RSD, while μXRF

produced semi-quantitative data with typical precision ranging from 2-

25%RSD, depending on the element and its concentration. 

Variability between the measurements is a combined effect of natural 

heterogeneity of the sample and the precision of the method. For methods 

with low variability of the measurements, (such as ICPMS) a narrow test 

criterion such as 2s or 3s produced high false exclusions. On the other hand, 

for a method with larger variability such as μXRF, a wide criterion of 4s 

would introduce an unacceptably high number of false inclusions. For a 

detailed description of the results the following scientific publications are 

provided:

a. T. Trejos, R. Koons, S. Becker, T. Berman, J. Buscaglia, M. Dueckin, T. EckertLumsdon, T. Ernst, C. Hanlon, A. Heydon, K. Mooney, R. Nelson, K Olsson, C. 

Palenik, E. Pollock, D. Rudell, S. Ryland, A. Tarifa, M. Valadez, P. Weis and J. 

Almirall. Cross-validation and evaluation of the performance of methods for 

the elemental analysis of forensic glass by μ-XRF, ICP-MS and LA-ICP-MS,

Journal of Anal. Bional. Chem, 2013, 405: 5393-5409

b. T. Trejos, R. Koons, P. Weis, S.Becker, T. Berman, C. Dalpe, M. Duecking, J. 

Buscaglia, T. Eckert-Lumsdon, T. Ernst, C. Hanlon, A. Heydon, K. Mooney, R. 

Nelson, K. Olsson, E. Schenk , C. Palenik, E. Chip Pollock, D.Rudell, S. Ryland, A. 

Tarifa, M.Valadez, A. van Es , V. Zdanowicz, and J.R. Almirall. Forensic 

analysis of glass by μ-XRF, ICP-MS, LA-ICP-MS and LA-ICP-OES: Evaluation of 

the performance of different criteria for comparing elemental composition, 

Journal of Analytical Atomic Spectrometry, 2013, 38, 1270-1282

c. Ernst, T.; Berman, T.; Buscaglia, J.; Eckert-Lumsdon, T.; Hanlon, C.; Olsson, K.; 

Palenik, C.; Ryland, S.; Trejos, T.; Valadez, M.; Almirall, J. R. Signal-to-noise 

ratios in forensic glass analysis by micro X-ray fluorescence spectrometry. XRay Spectrom. 2012, 43, 13-21.

d. Weis, P.; Dücking, M.; Watzke, P.; Menges, S.; Becker, S. Establishing a match 

criterion in forensic comparison analysis of float glass using laser ablation 

inductively coupled plasma mass spectrometry. J. Anal. At. Spectrom. 2011, 
26, 1273-1284.

e. Berends-Montero, S.; Wiarda, W.; de Joode, P.; van der Peijl, G. Forensic 

analysis of float glass using laser ablation inductively coupled plasma mass 

spectrometry (LA-ICP-MS): validation of a method. J. Anal. At. Spectrom. 

2006, 21, 1185-1193.

f. Hendrik Dorn, David E. Ruddell, Alex Heydon & Brenda D. Burton 

(2015)Discrimination of float glass by LA-ICP-MS: assessment of exclusion 

criteria using casework samples,Canadian Society of Forensic Science 

Journal, 48:2, 85-96.

E. The match/test criteria used for glass examinations cannot be directly 

applied to other materials because the selection of match criteria is not only 

dependent on the analytical method performance as described above but 

also on the natural heterogeneity of the sample. With this said, it is 

inappropriate to compare the case/scope/purpose of elemental analysis of 

bullet lead to glass. There are significant differences between the materials in 

terms of manufacturing, packaging, distribution, heterogeneity and chemical 

composition. 

The use of elemental analysis for glass comparisons has a very strong 

foundation with dozens of scientific articles describing the heterogeneity and 

distribution of elements on glass panes, variability, origin, and reasoning on 

which elements are more discriminating/informing and how they were 

selected for chemical profiling/comparison of glass. A few of these 

publications are listed below:

a. Almirall, J. R.; Trejos, T. Advances in forensic analysis of glass fragments with 

a focus on refractive index and elemental analysis. Forensic Sci. Rev. 18 2006, 

2, 74-96.

b. Almirall, J. R.; Trejos, T. Forensic Applications of Mass Spectrometry. In 

Encyclopedia of Mass Spectrometry, 1st ed.; Beauchemin, D.; Matthews, D., 

Eds.; Elsevier, 2010; Vol. 5, pp 705-717.

c. Andrasko, J.; Maehly, A. C. The discrimination between samples of window 

glass by combining physical and chemical techniques. J. Forensic Sci. 1978, 

23, 250-262.

d. Becker, S.; Gunaratnam, L.; Hicks, T.; Stoecklein, W.; Warman, G. The 

differentiation of float glass using refractive index and elemental analysis: 

Comparisons of techniques. Probl. Forensic Sci. 2001, 47, 80-92.

e. Berends-Montero, S.; Wiarda, W.; de Joode, P.; van der Peijl, G. Forensic 

analysis of float glass using laser ablation inductively coupled plasma mass 

spectrometry (LA-ICP-MS): validation of a method. J. Anal. At. Spectrom. 

2006, 21, 1185-1193.

f. Buscaglia, J. Elemental analysis of small glass fragments in forensic science. 

Anal. Chim. Acta 1994, 288, 17-24.

g. Duckworth, D. C.; Baynes, C. K.; Morton, S. J.; Almirall, J. R. Analysis of 

variance in forensic glass analysis by ICP-MS: Variance within the method. J. 

Anal. At. Spectrom. 2000, 15, 821-828.
h. Duckworth, D. C.; Morton, S. J.; Baynes, C. K.; Koons, R. D.; Montero, S.; 

Almirall, J. R. Forensic glass analysis by ICP-MS: A multi-element assessment 

of discriminating power via analysis of variance and pairwise comparisons. J. 

Anal. At. Spectrom. 2002, 17, 662-668.

i. Hicks, T.; Monard Sermier, F.; Goldmann, T.; Brunelle, A.; Champod, C.; 

Margot, P. The classification and discrimination of glass fragments using non 

destructive energy dispersive X-ray μ fluorescence. Forensic Sci. Int. 2003, 

137, 107-118.

j. Koons, R. D.; Fiedler, C.; Rawalt, R. C. Classification and discrimination of 

sheet and container glasses by inductively coupled plasma-atomic emission 

spectometry and pattern recognition. J. Forensic Sci. 1988, 33, 49-67.

k. Koons, R. D.; Peters, C. A.; Rebbert, P. S. Comparison of refractive index, 

energy dispersive X-ray fluorescence and inductively coupled plasma atomic 

emission spectrometry for forensic characterization of sheet glass fragments. 

J. Anal. At. Spectrom. 1991, 6, 451-456.

l. Latkoczy, C.; Becker, S.; Dücking, M.; Günther, D.; Hoogewerff, J. A.; Almirall, J. 

R.; Buscaglia, J.; Dobney, A.; Koons, R. D.; Montero, S.; van der Peijl, G. J.; 

Stoecklein, W. R.; Trejos, T.; Watling, J. R.; Zdanowicz, V. S. Development and 

evaluation of a standard method for the quantitative determination of 

eements in float glass samples by LA-ICP-MS. J. Forensic Sci. 2005, 50, 1327-

1341.

m. Montero, S. Trace elemental analysis of glass by inductively coupled plasmamass spectrometry (ICP-MS) and laser ablation-inductively coupled plasmamass spectrometry (LA-ICP-MS), Florida International University, Miami, 

Florida, 2002.

n. Naes, B. E.; Umpierrez, S.; Ryland, S.; Barnett, C.; Almirall, J. R. A comparison 

of laser ablation inductively coupled plasma mass spectrometry, micro X-ray 

fluorescence spectroscopy, and laser induced breakdown spectroscopy for 

the discrimination of automotive glass. Spectrochim. Acta, Part B 2008, 63, 

1145-1150.

o. Parouchais, T.; Warner, I. M.; Palmer, L. T.; Kobus, H. The analysis of small 

glass fragments using inductively coupled plasma mass spectrometry. J. 

Forensic Sci. 1996, 41, 351-360.

p. Roedel, T. C.; Bronk, H.; Haschke, M. Investigation of the influence of particle 

size on the quantitative analysis of glasses by energy-dispersive micro x-ray 

fluorescence spectrometry. X-Ray Spectrom. 2002, 31, 16-26.

q. Ryland, S. G. Discrimination of flat (sheet) glass specimens having similar 

refractive indices using micro X-ray fluorescence spectrometry. Journal of 

the American Society of Trace Evidence Examiners 2011, 2, 2-12.

r. Suzuki, Y.; Sugita, R.; Suzuki, S.; Marumo, Y. Forensic discrimination of bottle 

glass by refractive index measurement and analysis of trace elements with 

ICP-MS. Anal. Sci. 2000, 16, 1195-1198.

s. Trejos, T.; Almirall, J. R. Sampling strategies for the analysis of glass 

fragments by LA-ICP-MS Part I. Micro-homogeneity study of glass and its 

application to the interpretation of forensic evidence. Talanta 2005a, 67, 

388-395.

t. Trejos, T.; Almirall, J. R. Sampling strategies for the analysis of glass 

fragments by LA-ICP-MS Part II: Sample size and sample shape 

considerations. Talanta 2005b, 67, 396-401.
u. Trejos, T.; Montero, S.; Almirall, J. R. Analysis and comparison of glass 

fragments by laser ablation inductively coupled plasma mass spectrometry 

(LA-ICP-MS) and ICP-MS. Anal. Bioanal. Chem. 2003, 376, 1255-1264.

v. Trejos, T.; Koons, R.; Becker, S.; Berman, T.; Buscaglia, J.; Duecking, M.; 

Eckert-Lumsdon, T.; Ernst, T.; Hanlon, C.; Heydon, A.; Mooney, K.; Nelson, R.; 

Olsson, K.; Palenik, C.; Pollock, E. C.; Rudell, D.; Ryland, S.; Tarifa, A.; Valadez, 

M.; Weis, P.; Almirall, J. R. Cross-validation and evaluation of the 

performance of methods for the elemental analysis of forensic glass by μXRF, ICP-MS, and LA-ICP-MS. Anal. Bioanal. Chem. 2013a, 405, 5393-5409.

w. Trejos, T.; Koons, R.; Weis, P.; Becker, S.; Berman, T.; Dalpe, C.; Duecking, M.; 

Buscaglia, J.; Eckert-Lumsdon, T.; Ernst, T.; Hanlon, C.; Heydon, A.; Mooney, 

K.; Nelson, R.; Olsson, K.; Schenk, E.; Palenik, C.; Pollock, E. C.; Rudell, D.; 

Ryland, S.; Tarifa, A.; Valadez, M.; van Es, A.; Zdanowicz, V.; Almirall, J. R. 

Forensic analysis of glass by μ-XRF, SN-ICP-MS, LA-ICP-MS and LA-ICP-OES: 

evaluation of the performance of different criteria for comparing elemental 

composition. J. Anal. At. Spectrom. 2013b, 28, 1270-1282.

x. Weis, P.; Dücking, M.; Watzke, P.; Menges, S.; Becker, S. Establishing a match 

criterion in forensic comparison analysis of float glass using laser ablation 

inductively coupled plasma mass spectrometry. J. Anal. At. Spectrom. 2011, 

26, 1273-1284. 

y. P.M.L. Sandercock (2000) Sample Size Considerations for Control Glass in 

Casework, Canadian Society of Forensic Science Journal, 33:4, 173-185

z. Hendrik Dorn, David E. Ruddell, Alex Heydon & Brenda D. Burton 

(2015)Discrimination of float glass by LA-ICP-MS: assessment of exclusion 

criteria using casework samples, Canadian Society of Forensic Science 

Journal, 48:2, 85-96.

We would like to stress that the overall scientific foundation of glass 

examinations includes aspects of transfer, persistence, and methodology 

validity. The principles and utility of forensic glass examinations is supported 

by at least 130 publications over the last 3 decades. The list provided above 

represents only a snapshot of the scientific support on the particular topics 

of sampling, homogeneity, and discrimination/variations in glass populations. 

F. We are aware of Bayesian/likelihood approaches for the 

interpretation of glass evidence. We are not against these strategies. 

However, the test methods discussed here are limited to the comparison of 

“elemental data” to determine whether the elemental compositions of two 

glass samples (aka K/Q) are distinguishable or not. 

What the scientists conclude based on the evaluation of the data is outside

the scope of these test methods. After applying these test methods, the 

practitioner will need to follow an interpretation guide/standard to write a 

conclusion (whether they decide to use Bayesian or traditional approaches). 

The test criterion is a necessary step prior to any further data interpretation. 

These test methods aim to standardize the way in which practitioners should 

conduct data analysis to determine if the elemental composition is different 
or not. Nonetheless, conducting elemental analysis via either of these test 

methods is only one of many steps/examinations that the glass examiner 

must follow and later put together to evaluate the evidence and write a 

conclusion based on the overall glass examination (physical, optical and 

chemical). 

It is critical to keep in mind the scope of the test method when evaluating 

these documents. 

3. Implications of the use of different types of data in forensic science: The 

elemental composition of materials can be obtained by spectrochemical methods 

(i.e. μXRF, ICP) in three main forms:

a) qualitative

b) quantitative

c) semi-quantitative

All 3 forms of data comprise true/valid scientific information/data that can be used 

to determine the source of a material or make inferences about commonality, 

similarity or difference of chemical composition.

The decision of whether we use one form of data or another is dictated by the 

nature of the material, the limitations/capabilities of the technique, and the purpose 

of the analysis.

A. Qualitative data: this is, for example, a graphical representation of a 

spectrum that shows the identification of elements present/detected in a 

specimen, such as iron, calcium, etc. You can use qualitative data to 

determine which elements are present or absent in a sample and/or to 

compare if the same elements are present or absent in a comparison sample. 

You can overlay two spectra to compare their qualitative profile.

B. Quantitative data: quantitative data involves the identification of the 

element followed by the calculation of the absolute concentration (amount). 

In solid materials such as glass this is typically reported in ug/g. Calibrations

are made by using certified standards of known concentration. For instance, 

ICPMS is a method able to generate quantitative data with excellent precision 

and accuracy. You can not only determine that iron and calcium are present, 

you can also report the actual concentration and uncertainty for each 

element. This data can be used to detect significant differences in the 

composition of the elements in comparison samples.

C. Semi-quantitative data: in some instances, the conditions for 

reliable quantitative data are not met. For example, in the case of μXRF
quantitative data requires calibration with solid standards of glass at 

concentrations detectable by this method and the glass fragment must have 

minimum thickness/shape requirements to attenuate differences in the way 

that the X-rays are released from the glass into the detector. 

Because of the typical sample/shape of glass fragments, these limitations 

prevent quantitative measurements by μXRF. Instead, ratios of elements are 

used to compensate for those variations. The ratios of elements are 

selected/recommended based on similar anticipated behavior to optimize 

that normalization of the data. For example, these ratios of the peak areas of 

calcium to iron generate “numerical” data. That ratio data is not “quantitative” 

but due to its numerical nature it is considered “semi-quantitative” because 

you are comparing the relative amounts of these elements in the samples. 

Semi-quantitative data allows the calculation of uncertainties and is widely 

accepted in the scientific community. Semi-quantitative data is the 

foundation of other forensic materials, such as DNA analysis.