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 document describes a method to firstly identify the specific nature of oils spilled in the environment and secondly compare the chemical composition of spilled oil or oily samples with that of suspected sources. Specifically, the document describes the detailed analytical methods and data processing specifications for identifying the specific nature of 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 related products containing a significant proportion of hydrocarboncomponents with a boiling point above 150°C. Examples are: crude oils, higher boiling condensates, diesel oils, residual bunker or heavy fuel oils, lubricants, and mixtures of bilge and sludge samples, as well as distillate fuels and blends. 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 weatheringresistant diagnostic ratios, may have applicability in spills involving lower boiling oils.
Paraffin as petroleum product (for candles, etc.) is outside the scope of this method, because too many compounds have been removed during the production process. Still the method can be used to analyse the type of product involved.

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

Dieses Dokument beschreibt ein Verfahren, um zum einen die spezifische Beschaffenheit von in die Umwelt freigesetzten Ölen zu identifizieren und zum anderen die chemische Zusammensetzung von Proben aus freigesetztem Öl mit denen von mutmaßlichen Quellen zu vergleichen. Das Dokument beschreibt insbesondere die ausführlichen Festlegungen von Analyseverfahren und Datenverarbeitung zur Identifi-zierung der spezifischen Beschaffenheit von Ölverschmutzungen und zur Ermittlung ihrer Korrelation mit mutmaßlichen Quellen. Selbst wenn keine Proben oder Daten von mutmaßlichen Quellen zum Vergleich zur Verfügung stehen, kann die Feststellung der spezifischen Beschaffenheit (z. B. raffiniertes Mineralöl, Rohöl, Altöl usw.) des freigesetzten Öls dennoch dabei helfen, die mögliche(n) Quelle(n) des freigesetzten Öls einzugrenzen.
Diese Methodik ist auf mineralölbezogene Erzeugnisse beschränkt, die einen erheblichen Anteil an Kohlenwasserstoffkomponenten mit einem Siedepunkt über 150 °C enthalten. Beispiele sind: Rohöle, höhersiedende Kondensate, Dieselöle, Rückstände von Bunker- oder Schwerölen, Schmiermittel und Mischungen aus Bilgen(wasser)- und Schlammproben sowie Destillat-Kraft- und Brennstoffe und Mischungen. Obwohl die spezifischen Analyseverfahren möglicherweise nicht für niedrigersiedende Öle (z. B. Kerosine, Flugturbinenkraftstoffe oder Ottokraftstoff) geeignet sind, können die in dieser Methodik beschriebenen allgemeinen Konzepte, d. h. der statistische Vergleich alterungsbeständiger diagnostischer Verhältnisse, bei Verschmutzungen unter Einbeziehung dieser Art von Ölen anwendbar sein.
Paraffin als Mineralölerzeugnis (für Kerzen usw.) fällt nicht in den Anwendungsbereich dieses Verfahrens, weil während des Herstellungsprozesses zu viele Verbindungen entfernt wurden [37]. Dennoch kann das Verfahren zur Analyse der Art des betreffenden Produkts verwendet werden.
Dieses Verfahren ist nicht direkt für die Identifizierung von Ölverschmutzungen in Matrices wie Grundwasser, Vegetation, Wildtiere/Geweben, Böden oder Sedimenten vorgesehen, und obwohl seine Anwendung bei diesen Matrices nicht ausgeschlossen ist, erfordert das jedoch Vorsicht. Der Grund für die Vorsicht liegt darin, dass die extrahierbaren Verbindungen in diesen Matrices im Vergleich zur Probe von der Quelle sich verändern und/oder zusätzliche Verbindungen einbringen können, was, wenn es nicht erkannt wird, zu „falschen Nicht-Übereinstimmungen“ führen kann. Es ist daher ratsam, Hintergrund-probe(n) aus scheinbar nicht verunreinigter Matrix zu analysieren. Das Einbeziehen dieser „Nicht-Öl“-Matrices in dieses Verfahren zur Identifizierung von Ölverschmutzungen kann eine zusätzliche Probenvorbereitung (z. B. Reinigung) im Laboratorium vor der Analyse und die Berücksichtigung des Ausmaßes erfordern, in dem die Matrix die erzielte Korrelation beeinflussen kann. Die Bewertung der möglichen Auswirkungen in diesen Matrices fällt nicht in den Anwendungsbereich dieses Dokuments. Ob das Verfahren für diese Art von Matrices verwendet werden kann, kann von der Ölkonzentration im Vergleich zur „Matrixkonzentration“ der Proben abhängen. In Matrices, die eine verhältnismäßig hohe Konzentration an Öl enthalten, kann immer noch auf eine positive Übereinstimmung geschlossen werden. In Matrices, die eine verhältnismäßig geringe Konzentration an freigesetztem Öl enthalten, könnte aufgrund von Matrixeffekten eine falsche Nicht-Übereinstimmung oder eine nicht eindeutige Übereinstimmung erzielt werden.

Identification des pollutions pétrolières - Pétrole et produits pétroliers dans l'eau - Partie 2 : Méthode d'analyse et interprétation des résultats sur la base des analyses par CPG-DIF et CPG-SM à basse résolution

Prepoznavanje razlitij olj - Nafta in naftni proizvodi v vodi - 2. del: Analizne metode in podajanje rezultatov, izhajajočih iz GC-FID in GC-MS nizke ločljivosti

General Information

Status
Not Published
Current Stage
4060 - Closure of enquiry - Enquiry
Due Date
18-Mar-2021
Completion Date
18-Mar-2021

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SLOVENSKI STANDARD
oSIST prEN 15522-2:2020
01-december-2020

Prepoznavanje razlitij olj - Nafta in naftni proizvodi v vodi - 2. del: Analizne metode

in podajanje rezultatov, izhajajočih iz GC-FID in GC-MS nizke ločljivosti

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: prEN 15522-2
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
75.080 Naftni proizvodi na splošno Petroleum products in
general
oSIST prEN 15522-2:2020 en

2003-01.Slovenski inštitut za standardizacijo. Razmnoževanje celote ali delov tega standarda ni dovoljeno.

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oSIST prEN 15522-2:2020
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oSIST prEN 15522-2:2020
DRAFT
EUROPEAN STANDARD
prEN 15522-2
NORME EUROPÉENNE
EUROPÄISCHE NORM
December 2020
ICS 13.020.40; 75.080 Will supersede CEN/TR 15522-2:2012
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
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

This draft European Standard is submitted to CEN members for enquiry. It has been drawn up by the Technical Committee

CEN/TC 19.

If this draft becomes a European Standard, CEN members are bound to comply with the CEN/CENELEC Internal Regulations

which stipulate the conditions for giving this European Standard the status of a national standard without any alteration.

This draft European Standard was established by CEN in three official versions (English, French, German). A version in any other

language made by translation under the responsibility of a CEN member into its own language and notified to the CEN-CENELEC

Management Centre has the same status as the official versions.

CEN members are the national standards bodies of Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia,

Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Norway,

Poland, Portugal, Republic of North Macedonia, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey and

United Kingdom.

Recipients of this draft are invited to submit, with their comments, notification of any relevant patent rights of which they are

aware and to provide supporting documentation.

Warning : This document is not a European Standard. It is distributed for review and comments. It is subject to change without

notice and shall not be referred to as a European Standard.
EUROPEAN COMMITTEE FOR STANDARDIZATION
COMITÉ EUROPÉEN DE NORMALISATION
EUROPÄISCHES KOMITEE FÜR NORMUNG
CEN-CENELEC Management Centre: Rue de la Science 23, B-1040 Brussels

© 2020 CEN All rights of exploitation in any form and by any means reserved Ref. No. prEN 15522-2:2020 E

worldwide for CEN national Members.
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Contents Page

European foreword ............................................................................................................................................ 3

Introduction .......................................................................................................................................................... 4

1 Scope .......................................................................................................................................................... 6

2 Normative references .......................................................................................................................... 6

3 Terms and definitions ......................................................................................................................... 7

4 Strategy for the identification of oil spill sources ................................................................... 10

5 General lab instructions ................................................................................................................... 12

6 Sample preparation ........................................................................................................................... 14

7 Characterisation and evaluation of analytical data ................................................................ 20

8 Reporting ............................................................................................................................................... 41

9 Quality assurance ............................................................................................................................... 43

Annex A (normative) T GC-FID analysis .................................................................................................... 44

Annex B (normative) GC-MS analysis ......................................................................................................... 49

Annex C (informative) Precision statement ............................................................................................ 57

Annex D (normative) Evaluative reporting using match definitions or likelihood ratios ..... 65

Annex E (normative) List of compounds and compound groups analysed by GC-MS-SIM ..... 68

Annex F (informative) Chromatograms and ratios of compounds and compound groups

analysed by GC-MS-SIM ..................................................................................................................... 79

Annex G (informative) General composition of oils – chemical groups ........................................ 99

Annex H (informative) Weathering of oils spilled on water and land ........................................ 103

Annex I (informative) Characteristic Features of Different Oil Types in Oil Spill Identification

................................................................................................................................................................ 131

Annex J (informative) Example of external documentation – identification report of an oil

spill identification............................................................................................................................ 165

Annex K (informative) Example of internal documentation – technical report of an oil spill

case ........................................................................................................................................................ 168

Bibliography .................................................................................................................................................... 189

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European foreword

This document (prEN 15522-2:2020) has been prepared by Technical Committee CEN/TC 19 “Gaseous

and liquid fuels, lubricants and related products of petroleum, synthetic and biological origin”, the

secretariat of which is held by NEN.
This document is currently submitted to the CEN Enquiry.
This document will supersede CEN/TR 15522-2:2012.

In comparison with the previous edition, the following technical modifications have been made:

— adding compounds to be analysed in order to include light products in the diesel range;

— adding more information about biodegradation;
— adding a Reporting and a Quality assurance chapter;
— adding Annex C with precision data;
— adding Annex D with likelihood grade conclusions;
— introduction of characterization of FAME in Annex I;

— serious revision of Annexes H, I, J and K, adding new pictures and chromatograms.

This document has been prepared under a mandate given to CEN by the European Commission and the

European Free Trade Association, and supports essential requirements of EU Directive(s).

A list of all parts in a series can be found on the CEN website.
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Introduction

This document describes a forensic method for characterising and identifying the source of oils spills in

the environment as a resulting from accidents or intentional discharges. The method can be used in

support of the legal process as evidence for prosecuting offenders. This method is based on the

experience gained with its former publications over the years.

EN 15522 is composed of two parts that are described by the following CEN documents:

 EN 15522-1 – Sampling, describing good sampling practice, detailing sampling equipment, sampling

techniques and the handling of oil samples prior to their arrival at the forensic laboratory;

 EN 15522-2 – Analytical Method, which covers the general concepts and laboratory procedures of oil

spill identification, analytical techniques, data processing, data treatment, interpretation/evaluation

and reporting of results.

Oil spill source identification is a complex methodology due to the large variation in sample types 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 (GC-MS). Any

chemical difference found between samples is only relevant if this 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 are presented.

In the usual test method standard, instructions are given how to perform an “analytical” procedure. Oil

spill identification however comprises of an analytical part and an assessment part. The sample

preparation part is described in Chapter 5 and the analytical parts in Annex A for the GC-FID and in

Annexes B, E and F for the GC-MS. The other parts of the document describe tools and instructions how

to assess the analytical data and how to come to a final conclusion. Because each oil case is different in

situation, size, products and weathering, the evaluation part of the method is described as a toolbox. The

Annexes J and K evaluate an oil case and show how the tools may be applied. More examples of specific

oil cases are available as summary reports of the annual round robins organised by Bonn-OSINet [11]

and in literature.

The main purpose of the methodology described in this part of the document is to defensibly identify the

source of an oil spill in the environment 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 must be maintained. Even so, a “positive match” between a spilled

oil and a suspected source may not be used alone to identify the PRP (potential responsible party), 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 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 with 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

document in defensibly identifying a spilled oil’s source depends upon the samples available for chemical

study. To minimise the danger for “false positive” and especially “false non-matches”, good sampling

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practice is essential, and particularly the need to obtain appropriate suspect source samples, is crucial

(as described in Part 1: Sampling).

When oil from suspected sources is not available, this document can 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

suspected 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 document is the result of advancements in the field of oil spill identification [e.g. 22, 36, 66, 67 and

78] that have been made since the Nordtest Method [54] 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 changes 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 Proficiency Testing Programs (PTPs; RR-tests) have

been conducted to evaluate and improve upon the methodology. Since 2004, in the framework of Bonn-

OSINET (Bonn-Agreement Oil Spill Identification Network), annual interlaboratory studies have been

organised jointly by RWS-lab (Rijkswaterstaat - Laboratory in the Netherlands) and BSH (Bundesamt für

Seeschifffahrt und Hydrographie in Germany) in which laboratories from around the world participate.

The studies have covered oil spill cases dealing with light fuel oil distillates (diesel oils), bilge water

samples (a mixture of water, gas oils and lubricating oil), crude oils and heavy fuel oils. Findings from

these studies have been discussed at annual meetings by the participating analysts and have been taken

into account for refining the suggested methodology described herein. The final reports of the

interlaboratory studies can be downloaded for free from the Bonn-OSINET part of the Bonn-Agreement

website [11].
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1 Scope

This document describes a method to firstly identify the specific nature of oils spilled in the environment

and secondly compare the chemical composition of samples from spilled oil with those of suspected

sources. Specifically, the document describes the detailed analytical methods and data processing

specifications for identifying the specific nature of 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 can still

help to constrain the possible source(s) of the spilled oil.

This methodology is restricted to petroleum related products containing a significant proportion of

hydrocarbon-components with a boiling point above 150 °C. Examples are: crude oils, higher boiling

condensates, diesel oils, residual bunker or heavy fuel oils, lubricants, and mixtures of bilge and sludge

samples, as well as distillate fuels and blends. 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, can have

applicability in spills involving this kind of oils.

Paraffin as petroleum product (for candles, etc.) is outside the scope of this method, because too many

compounds have been removed during the production process [37]. Still the method can be used to

analyse the type of product involved.

This method is not directly intended for identifying oil spills in matrixes like 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”. It is therefore advisable to analyse background sample(s) from seemingly

uncontaminated matrix. Including these “non-oil” matrices in this oil spill identification method can

require additional sample preparation (e.g. clean-up) in the laboratory prior to analysis and

consideration of the extent to which the matrix can affect the correlation achieved. Evaluating the

possible effects in these matrices is beyond the scope of this document. Whether the method can be used

for this kind of matrices may depend on the oil concentration compared to the “matrix concentration” of

the samples. In matrices containing relatively high concentration of oil, a positive match can still be

concluded. In matrices containing relatively low concentration of spilled oil, a false non-match or an

inconclusive match could be achieved due to matrix effects.
2 Normative references

The following documents are referred to in the text in such a way that some or all of their content

constitutes requirements of this document. For dated references, only the edition cited applies. For

undated references, the latest edition of the referenced document (including any amendments) applies.

EN 15522-1, Oil spill identification –petroleum and petroleum products – Part 1: Sampling

ISO 1998-1:1998, Petroleum industry — Terminology — Part 1: Raw materials and products

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3 Terms and definitions

For the purposes of this document, the terms and definitions given in ISO 1998-1:1998 apply.

ISO and IEC maintain terminological databases for use in standardization at the following addresses:

 IEC Electropedia: available at http://www.electropedia.org/
 ISO Online browsing platform: available at http://www.iso.org/obp
3.1 General
3.1.1
chain of custody

practice of ensuring security of the sample so that no one has an opportunity to tamper with or otherwise

alter the sample or the results

Note 1 to entry: It includes chronological documentation that records the sequence of sample handling including

sampling, sealing, storage, transfer, analysis and disposal to ensure that only documented sample handlers have

direct access to the samples.
3.1.2
mixing

mixing of sources containing or consisting of petroleum (products) before, during or after the spillage

Note 1 to entry: Can result in a heterogeneous spill composition (see 3.1.4).
3.1.3
contamination

changes in oil composition which take place during/after the spillage in either sample by addition of non-

petroleum compounds from biogenic (e.g. fat from feathers) or anthropogenic sources (e.g. compounds

from plastics)

Note 1 to entry: mixing and contamination are used to differentiate between the addition of petroleum products

(mixing) and non-petroleum products ( contamination)
3.1.4
sample heterogeneity

non-homogenous character of samples caused for example by variable degrees of stirring within a vessel,

tank, pipeline or oil slick originally containing oil(product)s with different compositions

3.1.5
duplicate

two times the injection of the same sample extract within a sequence or within an oil case

3.1.6
replicate

two aliquots of a sample or two samples taken from exact the same sample location and at the same time

Note 1 to entry: Two samples taken from different locations of a larger spill are no replicates, but different samples.

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3.1.7
waterborne oil

petroleum or petroleum product borne by water or available in the water column from marine, estuarial

and aquatic environments

Note 1 to entry: Aquatic environments include lakes and rivers, but exclude groundwater.

3.1.8
weathering

processes that cause changes in oil composition of source and spill samples which can take place after

the spillage, including natural processes like evaporation, dissolution, emulsification, photo oxidation,

biodegradation, wax redistribution and also processes caused by oil response techniques like chemical

dispersion and burning

Note 1 to entry: Sometimes the source is more weathered that the spill. For example when a slop tank contains a

mixture of oil and water and is leaking oil into much colder water, the oil in the slop tank can be biodegraded to a

higher degree than the spilled oil.
3.1.9
bilge

water which may be contaminated by oil resulting from things such as leakage or maintenance work in

machinery spaces. Any liquid entering the bilge system including bilge wells, bilge piping, tank top or

bilge holding tanks is considered oily bilge water
[48]
[SOURCE: MEPC. 187(59) ]
3.1.10
slop (tank)

mixture of water and oil residues from cargo tanks in oil tankers that may contain crude oil, heavy fuel

oil/water emulsions, wax, sediments and other tank residues
3.1.11
sludge

the residual waste oil products generated during the normal operation of a ship such as those from the

purification of fuel or lubricating oil from main or auxiliary machinery, separated waste oil from oil

filtering equipment, waste oil collected in drip trays, and waste hydraulic and lubricating oils

[48]
[SOURCE: MEPC. 187(59) ]
3.1.12
tank washings

tank washing water containing cargo tank residues including oil, wax, sediment and other foreign matter

such as tank cleaning chemicals
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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 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 [54]. In this document, the name PW-plot is used as an abbreviation of a “Percentage Weathering” plot.

3.2.2
diagnostic ration (DR)

ratio between the peak heights of single compounds or peak areas of compound groups of the same

sample selected by their diversity in chemical composition in petroleum and petroleum products, their

discriminative power and on their known behaviour in weathering processes
3.2.3
likelihood ratio (LR)
ratio of two probabilities

Note 1 to entry: The numerator is the probability of obtaining the evidence when the prosecutors scenario is true.

The dominator is the probability of obtaining the evidence when the defence scenario is true (see Annex D).

3.2.4
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 RSD of 5 % for the diagnostic ratios

(see 7.5.5).
3.2.5
significant difference

difference between a property or analytical result of two samples that cannot be explained as caused by

weathering, mixing or contamination

Note 1 to entry: Your skin turning brown or red after a while in the sun, doesn’t make you a different person and is

therefore not a significant difference.
3.3 Abbreviations
CD Critical Difference
DR Diagnostic Ratio
FAMEs Fatty Acid Methyl Esters
FID Flame Ionisation Detection
GC Gas Chromatography
HFO Heavy Fuel Oil
HVO Hydrotreated Vegetable Oil
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LCO Light Cycle Oil
LFO Light Fuel Oil
MS Mass Spectrometry
NR Normative Ratio
PTP Proficiency Testing Program
RR Round Robin Test;
RSD Relative Standard Deviation
ULSFO Ultra-Low Sulfur Fuel Oil
VGO Vacuum Gas Oil
4 Strategy for the identification of oil spill sources
4.1 Introduction

Identification of spilled oils in the context of this document implies the comparison of the total chemical

composition of the spilled oil with that of candidate source samples.
NOTE See Annex G for further explanation on composition of oils.

The likeness of a source and spill sample should be tested by analysing the samples with GC-FID and/or

GC-low resolution-MS and by comparing their detailed chemical compositions using a suite of generic

and diagnostic petroleum components. If no or only insignificant differences (i.e. differences being

smaller than the analytical variability limits defined) are observed, a “positive match” should be

concluded. On the other hand, if true differences (i.e. differences not related to changes in the chemical

composition introduced after the spill, e.g. from weathering, contamination or heterogeneity) that are

larger than the variance of the analysis are observed within these diagnostic compounds, it should be

concluded that the samples are a “non-match”. Some investigations can result in conclusions intermediate

to “positive match” and “non-match”, such as “probable match” or “inconclusive” (see D.2). All these

classifications are used in the descriptions and examples of this document.

IMPORTANT - It is practically and technically impossible to measure and compare every chemical in

spilled oil and its prospective source in order to conclude a positive match exists. Therefore, in practice,

two samples are considered a positive match if no statistically significant differences in diagnostic metrics

determined by GC-FID and GC-MS analysis are present that cannot be explained by weathering, mixing

or heterogeneity. This approach, i.e. looking for differences in diagnostic features instead of similarity

among every possible feature, is conceptually more logical and more practically and technically

achievable. As such, only distinct differences between samples can be proved. Therefore, when no

statistically significant differences between samples are observed, a “positive match to a high degree of

scientific certainty” should be concluded.
4.2 Basis for reliable conclusions – Numerical comparisons

The usual practice is to analyse samples qualitatively and then compare the chromatograms and ion

chromatograms visually, such as described in the original Nordtest Method (1991) [54] and the ASTM

methods [3, 4]. The outcome of such qualitative comparisons is subjective and depends on the experience

or bias of the analyst. Because of the high complexity of oils, and the many details that can be compared

in the often very complex chromatograms, qualitative comparisons should always form an integral part

of oil sample comparisons. However, in order to make conclusions more objective, reproducible, and

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oSIST prEN 15522-2:2020
prEN 15522-2:2020 (E)

therefore, more reliable, this document also requires the use and comparison of quantitative metrics; i.e.

specific peaks or groups of peaks have to be measured and peak ratios have to be calculated and

compared.
These integration values are used in two different ways:

a) Measurements of single compounds normalised to hopane – or, if hopane is not sufficiently

present, to phytane – or, if phytane is also not sufficiently present, to bicyc
...

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