CEN/TR 15522-2:2012

SLOVENSKI STANDARD
01-januar-2013
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SIST-TP CEN/TR 15522-2:2008
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Oil spill identification - Waterborne petroleum and petroleum products - Part 2: Analytical
methodology and interpretation of results based on GC-FID and GC-MS low resolution
analyses
Identifizierung von Ölverschmutzungen - Rohöl und Mineralölerzeugnisse aus dem
Wasser - Teil 2: Analytische Methodik und Interpretation der Ergebnisse, basierend auf
GC-FID- und GC-MS-Analysen bei niedriger Auflösung
Ta slovenski standard je istoveten z: CEN/TR 15522-2:2012
ICS:
13.020.40 Onesnaževanje, nadzor nad Pollution, pollution control
onesnaževanjem in and conservation
ohranjanje
13.060.99 Drugi standardi v zvezi s Other standards related to
kakovostjo vode water quality
2003-01.Slovenski inštitut za standardizacijo. Razmnoževanje celote ali delov tega standarda ni dovoljeno.

TECHNICAL REPORT
CEN/TR 15522-2
RAPPORT TECHNIQUE
TECHNISCHER BERICHT
October 2012
ICS 75.080 Supersedes CEN/TR 15522-2:2006
English Version
Oil spill identification - Waterborne petroleum and petroleum
products - Part 2: Analytical methodology and interpretation of
results based on GC-FID and GC-MS low resolution analyses

This Technical Report was approved by CEN on 13 August 2012.

CEN members are the national standards bodies of Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia,
Finland, Former Yugoslav Republic of Macedonia, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania,
Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey and United
Kingdom.
EUROPEAN COMMITTEE FOR STANDARDIZATION
COMITÉ EUROPÉEN DE NORMALISATION

EUROPÄISCHES KOMITEE FÜR NORMUNG

Management Centre: Avenue Marnix 17, B-1000 Brussels
© 2012 CEN All rights of exploitation in any form and by any means reserved Ref. No. CEN/TR 15522-2:2012: E
worldwide for CEN national Members.

Contents Page
Foreword .6
Introduction .7
1 Scope .9
2 Normative references .9
3 Terms, definitions and abbreviated terms .9
3.1 General .9
3.2 Sample comparison . 10
3.3 Conclusions . 11
3.4 Abbreviated terms . 11
4 Strategy for the identification of oil spills sources . 12
4.1 Introduction . 12
4.2 Basis for reliable conclusions – Numerical comparisons . 12
4.3 Overview of the procedure . 13
4.3.1 Sampling and sample preparation . 13
4.3.2 GC-FID and GC-MS analysis . 14
4.3.3 Conclusions and reporting . 14
5 Sample preparation . 16
5.1 General . 16
5.2 Visual examination and description of samples . 16
5.3 Preparation . 16
5.3.1 General . 16
5.3.2 Water samples . 16
5.3.3 Oil samples from an Ethylene tetrafluoroethylene (ETFE) net . 17
5.3.4 Thick oil and emulsified oil samples . 17
5.3.5 Tar balls and emulsified lumps . 17
5.3.6 Samples from oiled birds, fish and other animals and vegetation . 17
5.4 Sample clean-up . 18
5.4.1 General . 18
5.4.2 Biogenic materials . 18
5.4.3 Black oil/HFO (removing of asphaltenes and/or soot particles) . 18
5.5 Recommended injection concentration . 18
6 Characterisation and evaluation of analytical data . 19
6.1 General . 19
6.2 Characterisation by GC-FID – Level 1 . 20
6.2.1 General . 20
6.2.2 Evaluation of the influence of weathering on sample comparison . 21
6.2.3 Acyclic isoprenoids ratios . 22
6.2.4 Level 1 Conclusions . 22
6.3 Characterisation by GC-MS – Level 2 . 22
6.3.1 General . 22
6.3.2 Visual inspection and overall characterisation - Level 2.1 . 23
6.3.3 Treatment of the GC-MS results – Level 2.2 . 23
6.4 Treatment of the results using the MS-PW-plot– Level 2.2 . 23
6.4.1 General . 23
6.4.2 PW-plot calculations . 24
6.4.3 Evaluation of the variability of the analysis and peak integration . 24
6.4.4 Evaluation of weathering . 26
6.4.5 Evaluation of mixing . 29
6.5 Treatment of the results using ratios – Level 2.2 . 31
6.5.1 General . 31
6.5.2 Diagnostic ratios calculation . 32
6.5.3 Normative diagnostic ratios . 32
6.5.4 Analytical error . 35
6.5.5 Match-criterion for ratios . 35
6.5.6 Criteria for selecting, elimination and evaluating diagnostic ratios . 36
6.5.7 Optional: Evaluation of diagnostic ratios using conventional or multivariate statistics . 39
6.6 Conclusions . 40
Annex A (normative) GC-FID analysis . 43
A.1 General . 43
A.2 Analytical standards for GC-FID analyses . 43
A.2.1 N-alkanes . 43
A.2.2 Injection concentration of the standard GC-FID . 43
A.2.3 Storage of standard solutions. 44
A.3 Suggested instrumental conditions . 44
A.4 Measures to improve and verify the accuracy of the method – GC-FID . 44
A.4.1 Mass discrimination . 44
A.4.2 Column resolution . 45
A.4.3 Calibration range . 46
A.4.4 Mid-level concentration . 46
A.4.5 Variance . 47
A.5 Sample analysis with GC-FID . 47
Annex B (normative) GC-MS analysis . 48
B.1 General . 48
B.2 Analytical standards for GC-MS analyses . 48
B.2.1 General . 48
B.2.2 SINTEF oil mixture . 49
B.2.3 Analytical standards for PAH homologues . 49
B.2.4 Storage of standard solutions. 49
B.3 Suggested instrumental conditions . 49
B.3.1 GC conditions for the exchange of analytical results. . 49
B.3.2 MS conditions for full-scan analysis . 52
B.3.3 MS preparation for selected ion monitoring (SIM) analysis . 52
B.4 Measures to improve and verify the accuracy of the GC-MS method . 53
B.4.1 Relative retention time . 53
B.4.2 Mass discrimination . 53
B.4.3 Peak symmetry and column resolution . 53
B.4.4 Patterns . 54
B.4.5 Calibration range . 54
B.4.6 Mid-level concentration . 54
B.4.7 Variance . 54
B.5 Sample analysis with GC-MS . 54
Annex C (informative) List of PAHs and biomarkers analysed by GC-MS-SIM . 55
Annex D (informative) Alkyl homologue patterns of PAHs . 57
Annex E (informative) Diagnostic ratios . 65
E.1 Diagnostic ratios of PAHs . 65
E.2 Diagnostic ratios of biomarkers . 69
Annex F (informative) General composition of oils – chemical groups . 76
F.1 Introduction . 76
F.2 Hydrocarbons . 76
F.3 Paraffins . 76
F.4 Naphthenes . 77
F.5 Aromatics . 77
F.6 Heteroatomic organic compounds . 77
F.7 Resins . 77
F.8 Asphaltenes . 77
Annex G (informative) Weathering of oils spilled on water . 79
G.1 Introduction . 79
G.2 Evaporation . 80
G.3 Dissolution . 82
G.4 Re-distribution of chemical composition . 83
G.5 Biodegradation . 86
G.6 Photooxidation . 86
G.7 Contamination . 88
Annex H (informative) Characteristic Features of Different Oil Types in Oil Spill Identification . 89
H.1 Introduction . 89
H.2 Light fuel oil (gas oil, diesel, fuel No 2) . 89
H.2.1 General . 89
H.2.2 Analysis, GC screening . 90
H.2.3 MS analysis (alternative parameters) . 92
H.2.4 Addition of biodiesel . 94
H.3 Lubricating oil . 95
H.3.1 General . 95
H.3.2 Analysis . 95
H.4 Heavy fuel oil (HFO, Bunker C, Fuel No 6) . 99
H.4.1 General . 99
H.4.2 Analysis . 99
H.5 Waste oil (bilge oil, sludge, slops) . 107
H.5.1 General . 107
H.5.2 Analysis . 108
H.6 Crude oil . 113
H.6.1 General . 113
H.6.2 Analysis . 113
H.7 Conclusion . 118
Annex I (informative) Example of internal documentation – technical report of an oil spill case . 120
I.1 General . 120
I.2 Sample information . 120
I.2.1 General . 120
I.2.2 Contact information . 120
I.2.3 Request . 120
I.2.4 Photo(s) of the samples . 121
I.3 Sample preparation and analyses. 121
I.4 Quality assurance . 124
I.5 GC-FID results . 125
I.6 GC-MS results . 128
I.6.1 General . 128
I.6.2 Comparison of the surface water samples. . 129
I.6.3 Comparison of the spill samples with bilge Sample 6. . 130
I.7 Conclusions . 131
I.7.1 Surface water Sample 1 with bilge Sample 6. . 131
I.7.2 Surface water Sample 2 with bilge Sample 6. . 132
I.7.3 Final conclusion: . 132
Annex J (informative) Example of external documentation – identification report of an oil spill
identification case. 133
J.1 Introduction . 133
J.2 Sample information . 133
J.3 Analytical procedure . 133
J.3.1 Method . 133
J.3.2 Dilution/extraction . 133
J.3.3 Analyses . 133
J.4 Results . 133
J.5 Interpretation . 134
J.5.1 General . 134
J.5.2 Positive match . 134
J.5.3 Probable match . 134
J.5.4 Inconclusive . 134
J.5.5 Non-match . 134
J.6 Conclusions . 134
Bibliography . 135

Foreword
This document (CEN/TR 15522-2:2012) supersedes CEN/TR 15522-2:2006, which was prepared by
CEN/BT/TF 120 "Oil Spill Identification" (now disbanded).
Attention is drawn to the possibility that some of the elements of this document may be the subject of patent
rights. CEN [and/or CENELEC] shall not be held responsible for identifying any or all such patent rights.
This document supersedes CEN/TR 15522-2:2006.
CEN/TR 15522 is composed of the following parts:
 Part 1: Sampling;
 Part 2: Analytical methodology and interpretation of results based on GC-FID and GC-MS low resolution
analyses (the present document).
Introduction
This Technical Report describes and recommends a forensic methodology for characterising and identifying
the source of waterborne oils resulting from accidental spills or intentional discharges. The methodology may
be used in support of the legal process as evidence for prosecuting offenders ("potential responsible party" –
PRP). This methodology is a technical revision of CEN/TR 15522-2 Version 1 published in December 2006.
This methodology is composed of two parts that are described by the following CEN documents:
 Part 1 – Sampling: describes sampling techniques and the handling of oil samples prior to their arrival at
the forensic laboratory;
 Part 2 – Methodology: covers the general concepts and laboratory procedures of oil spill identification
methodology, analytical techniques, data processing, data treatment, and interpretation/evaluation and
reporting of results.
Oil spill source identification is a complex methodology due to the large variation in samples and oil spill
situations that can be encountered. Part 1 is a compilation of instructions and experiences from experts all
over the world which will guide the user in sampling, storing and delivering oil samples for laboratory analysis.
Part 2 will guide the reader through the analytical process. It prescribes how to prepare and analyse oil
samples using GC-FID and GC-low-resolution mass spectrometry (MS). Any chemical differences found
between samples are only relevant if a difference is larger than the variability of the method itself. Good
analytical performance and strict quality assurance are therefore essential. In the Annexes of Part 2, relevant
information concerning different types of oil and oil comparison techniques is presented.
The main purpose of the methodology described in this Technical Report (TR) is to defensibly identify the
source of oil spills in marine, estuarine and other aquatic environments by comparing the chemical
compositions of samples from spills with those of suspected sources. The underlying basis for this method is
the widely variable nature of oils with respect to their specific chemical compositions, which allows oils from
different sources to be readily distinguished using the appropriate analytical methods. The method relies upon
detailed chemical characterisation and statistical comparison between samples' (i.e., a spilled oil and a
suspected source) diagnostic features in order to determine whether they “match”. To minimise the danger of
“false positive matches”, good laboratory practices are necessarily maintained. Even so, a “positive match”
between a spilled oil and a suspected source may not be used alone to identify the "potential responsible
party" (PRP), but this result is often a critical piece of evidence in proving a case within the legal process.
However, in some oil spill identification cases, both the oil spill and also suspected source(s) may not
necessarily be unique or homogeneous in nature, e.g., due to the changing/variable nature of oil in the bilge
tanks or due to mixing of oils spilled from several sources in a case of a larger incident. The risk therefore
exists that the chemical composition of the available source samples may not match to that of the available
spill samples. In such cases, oil spill identification methodologies in general will have limitations and may not
necessarily lead to unequivocal conclusions. In other words, the success of this methodology in defensibly
identifying a spilled oil’s source depends upon the samples available for chemical study. To minimise the
danger for “false positive” or “false non-matches”, good sampling practice, and particularly the need to obtain
appropriate reference/suspect source samples, is crucial (as described in Part 1: Sampling).
When oil from suspected sources is not available, this methodology may still be used to characterise the
spilled oil in order to determine the spilled oil type and any specific characteristics. The characterisation of a
spilled oil sample can still be useful for several reasons:
 If the source of an oil pollution event is unknown, the investigating authorities should be advised on the
type of oil in order to aid in the identification of a possible source. For example, in the case of a “mystery”
spill, the mere differentiation between pure, unused refined petroleum products (e.g. diesel fuel versus
heavy fuel oil) or versus crude oil or waste oil (e.g., bilge residues, sludge, slops) can provide potentially
valuable information as the possible source(s) for the spill. In such instances, the type of oil spilled should
be identified rapidly because the chances of identifying and collecting candidate source oils generally
decrease with time.
 In some court trials, the differentiation between pure refined products and waste oil may be very important
because it allows conclusions to be drawn regarding the cause of an oil discharge, e.g. technical failure,
accidental discharge, intentional discharge.
 In some countries, photos (e.g. taken from an airplane) from a plume behind a ship, combined with the
evidence that the plume contains mineral oil, is enough for a condemnation.
 Finally, characterisation of the spilled oil provides a baseline against which future impacts to the affected
area/environment might be compared.
This Technical Report is the result of advancements in the field of oil spill identification [e.g., 13, 21, 44, 46
and 50] that have been made since the Nordtest Method [35, 36] was first introduced in 1991. These have
included:
 advancements in analytical methodologies;
 improved understanding of the specific chemical compositions and diagnostic features of oils;
 improved understanding of how an oil’s composition may change in the environment (e.g., due to
weathering);
 improvements in the statistical and numerical analysis of chemical data.
These advancements have been made by researchers around the world and documented in a wide range of
peer-reviewed literature. In addition, numerous round robin tests have been conducted to evaluate and
improve upon the methodology. Since 2004, in the framework of Bonn-OSINET (Bonn-greement Oil Spill
Identification Network), annual round robin tests are organised jointly by RWS-WD (Rijkswaterstaat - Center
for Water Management in the Netherlands) and BSH (Bundesamt für Seeschiffahrt und Hydrographie in
Germany) in which laboratories from around the world participate. The round robin tests have covered oil spill
cases dealing with light fuel oil distillates (diesel oils), bilge water samples (a mixture of gas oils and lube oil),
crude oils and heavy fuel oils. Findings from these RR-tests have been discussed at annual meetings by the
participating scientists and have been taken into account for refining the suggested methodology described
herein. The final reports of the RR-tests can be downloaded for free from the Bonn-OSINET part of the Bonn-
agreement website [7].
1 Scope
This Technical Report (TR) describes a methodology to firstly identify the specific nature of oils spilled in
marine, estuarine and aquatic environments and secondly compare the chemical composition of spilled oil or
oily samples with that of suspected sources. Specifically, the TR describes the detailed analytical methods
and data processing specifications for identifying the specific nature of waterborne oil spills and establishing
their correlation to suspected sources. Even when samples or data from suspected sources are not available
for comparison, establishing the specific nature (e.g., refined petroleum, crude oil, waste oil, etc.) of the spilled
oil may still help constrain the possible source(s) of the spilled oil.
This methodology is restricted to petroleum and petroleum products containing a significant proportion of
hydrocarbon-components with a boiling point above 200°C. Examples are: crude oils, higher boiling
condensates, diesel oils, residual bunker or heavy fuel oils, lubricants, and mixtures of bilge and sludge
samples. While the specific analytical methods may not be appropriate for lower boiling oils (e.g. kerosenes,
jet fuels, or gasoline), the general concepts described in this methodology, i.e., statistical comparison of
weathering-resistant diagnostic ratios, may have applicability in spills involving lower boiling oils.
This method is not directly intended for oil spills impacting groundwater, vegetation, wildlife/tissues, soils, or
sediments, and although its application in these matrices is not precluded, it requires caution. The reason for
caution is that the extractable compounds in these matrices may alter and/or contribute additional compounds
compared to the source sample, which if left unrecognised, can lead to “false non-matches”. Including these
“non-oil” matrices in this oil spill identification method may require additional sample preparation (e.g. clean-
up) in the laboratory prior to analysis and consideration of the extent to which the matrix may affect the
correlation achieved. Evaluating the possible effects in these matrices is beyond the scope of this guideline.
Whether the method can be used for this kind of “non-oil” matrices may depend on the oil concentration
compared to the “matrix concentration” of the samples. In “non-oil” matrices containing a relative high
concentration of oil, a positive match can still be concluded. In “non-oil” matrices containing a relative low
concentration of spilled oil, a non-match or an inconclusive match could be achieved due to matrix effects.
2 Normative references
The following documents, in whole or in part, are normatively referenced in this document and are
indispensable for its application. For dated references, only the edition cited applies. For undated references,
the latest edition of the referenced document (including any amendments) applies.
CEN/TR 15522-1, Oil spill identification – Waterborne petroleum and petroleum products – Part 1: Sampling
3 Terms, definitions and abbreviated terms
For the purposes of this document, the following terms and definitions apply.
3.1 General
3.1.1
chain of custody
line of recorded actions taken for samples collected from spill and suspected sources at court for safe
surveillance and storing; to ensure that the samples have not been tampered with or altered accidentally
3.1.2
mixing
mixing can include chemical changes brought about by (a) the mixing of multiple oils, (b) mixing with pre-
existing background compounds from biogenic or anthropogenic sources, or (c) heterogeneity within the
sample(s) (e.g., within a vessel, tank, or oil slick)
3.1.3
sample heterogeneity
non-representative or non-homogenous character of samples caused for example by variable degrees of
mixing within a vessel, tank or oil slick
3.1.4
contamination
changes in oil composition which take place during/after the spillage, by mixing with additional compounds,
including naturally-occurring chemicals or other products
3.1.5
waterborne oil
petroleum and petroleum products borne by water or available in the water column from marine, estuarial and
aquatic environments
Note 1 to entry: These environments include lakes and rivers but exclude groundwater.
3.1.6
weathering
changes in oil composition which take place after the spillage, including evaporation, dissolution,
emulsification, oxidation and biological decomposition
Note 1 to entry: See also Annex G.
3.1.7
bilge water
mixture including water and oil collected in the bilge of the machinery space in a ship as a result of leakage,
drainage, etc.
3.1.8
slop
mixture of water and oil residues from cargo tanks in oil tankers that may contain oil/water emulsions, wax,
sediments and other tank residues
3.1.9
sludge
deposits, generally from the purification of fuel and lubrication oils, consisting of mixtures including oil, wax,
sand and water
3.1.10
tank washings
tank washing water containing cargo tank residues including oil, wax, sediment and other foreign matter such
as tank cleaning chemicals
3.2 Sample comparison
3.2.1
PW-plot
graph based on GC-FID or GC-MS data of two samples normalised to a non-weathered compound or group of
compounds and sorted on boiling point or retention time
Note 1 to entry: The name “PW-plot” is originally a reference to Per Wrang, who introduced the plot in the Nordtest
method [36]. In this TR, the name PW-plot will be used as an abbreviation of a “Percentage Weathering” plot.
3.2.2
diagnostic ratios (DR)
ratios between the peak height or peak area of single compounds or compound groups selected by their
diversity in chemical composition in petroleum and petroleum products and on their known behaviour in
weathering processes
3.2.3
critical difference (CD)
14 % of the mean value of a ratio for two different samples
Note 1 to entry The fixed value of 14 % is based on the maximum allowable relative standard deviation of 5 % for the
ratios [23, 24, 25].
3.3 Conclusions
3.3.1
positive match
differences in the chromatographic patterns and diagnostic ratios of samples submitted for comparison are
lower than the variability of the method or can be explained unequivocally, for example by weathering
Note 1 to entry: The samples are considered to match to a high degree of scientific certainty.
3.3.2
probable match
differences in chromatographic patterns and diagnostic ratios do not permit an unequivocal positive match, but
they can be explained reasonably by external factors, for example weathering in combination with mixing or by
non-representative or heterogeneous properties of the available samples
Note 1 to entry: The samples are considered to match to a reasonable degree of scientific certainty.
Note 2 to entry: Unavailability of a representative source sample. For example, if a vessel that has discharged all of its
bilge water, a representative source sample may not be available. Therefore, when comparing an individual source
lubricating oil with the lubricating oil component of a bilge sample, certain differences have to be expected due to other
bilge sample components besides the source lubricating oil.
3.3.3
inconclusive
differences in the chromatographic patterns and diagnostic ratios of the samples submitted for comparison, do
not permit a probable or non-match conclusion; for example in case the concentration of the contaminant in a
sample is too low
3.3.4
non-match
differences in the chromatographic patterns and diagnostic ratios of the samples submitted for comparison are
pronounced and are larger than the variability of the method, and such differences cannot be explained by any
external factors such as weathering, contamination or heterogeneity
Note 1 to entry: The samples are concluded to not match to a high degree of scientific certainty.
3.4 Abbreviated terms
CD Critical difference
DR Diagnostic ratio
FID Flame ionisation detection
GC Gas chromatography
HFO Heavy Fuel Oil
IUPAC International Union of Pure and Applied Chemistry
LCO Light cycle oil
LFO Light fuel oil
MS Mass spectrometry
NR Normative ratio
PCA Principal component analysis
RSD Relative standard deviation
TR Technical report
4 Strategy for the identification of oil spills sources
4.1 Introduction
Identification of spilled oils in the context of this Technical Report (TR) implies the comparison of the total
chemical composition of the spilled oil
...