SIST-TP CEN/TR 15310-1:2007

SLOVENSKI STANDARD
01-april-2007
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Characterization of waste - Sampling of waste materials - Part 1: Guidance on selection
and application of criteria for sampling under various conditions
Charakterisierung von Abfall - Probenahme - Teil 1: Richtlinien zur Auswahl und
Anwendung von Kriterien für die Probenahme unter verschiedenen Bedingungen
Caractérisation des déchets - Prélevement des déchets - Partie 1 : Guide relatif au choix
et a l'application des criteres d'échantillonnage dans diverses conditions
Ta slovenski standard je istoveten z: CEN/TR 15310-1:2006
ICS:
13.030.10 Trdni odpadki Solid wastes
13.030.20 7HNRþLRGSDGNL%ODWR Liquid wastes. Sludge
2003-01.Slovenski inštitut za standardizacijo. Razmnoževanje celote ali delov tega standarda ni dovoljeno.

TECHNICAL REPORT
CEN/TR 15310-1
RAPPORT TECHNIQUE
TECHNISCHER BERICHT
November 2006
ICS 13.030.10; 13.030.20
English Version
Characterization of waste - Sampling of waste materials - Part 1:
Guidance on selection and application of criteria for sampling
under various conditions
Caractérisation des déchets - Prélèvement des déchets - Charakterisierung von Abfall - Probenahme - Teil 1:
Partie 1 : Guide relatif au choix et à l'application des Richtlinien zur Auswahl und Anwendung von Kriterien für
critères d'échantillonnage dans diverses conditions die Probenahme unter verschiedenen Bedingungen
This Technical Report was approved by CEN on 21 February 2006. It has been drawn up by the Technical Committee CEN/TC 292.
CEN members are the national standards bodies of Austria, Belgium, Cyprus, Czech Republic, Denmark, Estonia, Finland, France,
Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Romania,
Slovakia, Slovenia, Spain, Sweden, Switzerland and United Kingdom.
EUROPEAN COMMITTEE FOR STANDARDIZATION
COMITÉ EUROPÉEN DE NORMALISATION
EUROPÄISCHES KOMITEE FÜR NORMUNG
Management Centre: rue de Stassart, 36  B-1050 Brussels
© 2006 CEN All rights of exploitation in any form and by any means reserved Ref. No. CEN/TR 15310-1:2006: E
worldwide for CEN national Members.

Contents
Foreword. 4
Introduction . 5
1 Scope . 7
2 Terms and definitions. 7
3 Specify the objective of the Testing Programme . 12
4 Develop the technical goals from the objective . 13
4.1 General. 13
4.2 Define the population to be sampled. 14
4.2.1 General. 14
4.2.2 Overall population . 14
4.2.3 Population . 14
4.2.4 Sub-population. 14
4.2.5 Examples . 15
4.3 Assess variability. 16
4.3.1 General. 16
4.3.2 Spatial variability . 16
4.3.3 Temporal variability. 17
4.3.4 Random variability. 17
4.4 Select the sampling approach. 17
4.4.1 General. 17
4.4.2 Probabilistic sampling. 18
4.4.3 Judgemental sampling. 18
4.5 Identify the scale. 18
4.6 Choose the required statistical parameter.19
4.7 Choose the desired reliability. 20
4.7.1 General. 20
4.7.2 Precision and Confidence. 20
4.7.3 Errors in the Testing Programme. 20
5 Determine the Practical Instructions . 21
5.1 General. 21
5.2 Sampling pattern. 22
5.2.1 General. 22
5.2.2 Simple random sampling . 23
5.2.3 Stratified random sampling . 23
5.2.4 Systematic sampling . 24
5.2.5 Judgemental sampling. 24
5.3 Determine the increment and sample size (mass / volume). 24
5.3.1 General. 24
5.3.2 Liquids . 25
5.3.3 Powders and sludges. 25
5.3.4 Particulate / granular materials . 25
5.4 The use of composite versus individual samples. 26
5.5 Determine the required number of increments and samples. 26
6 Define the Sampling Plan. 27
Annex A The scale . 28
A.1 Scale. 28
A.2 Fundamental variability. 32
Annex B Statistical methods for characterising a population . 33
B.1 Terms and Definitions . 33
B.2 Probability distributions .35
B.3 Statistical parameters .37
Annex C Calculating the required numbers of increments and samples.43
C.1 Notation .43
C.2 Estimating a mean concentration.43
C.3 Estimating a standard deviation .46
C.4 Estimating a percentile .47
C.5 Estimating a percentage compliance with a given limit.48
Annex D Minimum increment and sample size (mass / volume).49
D.1 Estimation of increment and sample size.49
D.2 Determination of the number of increments and/or samples .51
D.3 Calculation of the actual increment and/or sample size .51
Annex E Example sampling scenarios.53
E.1 Sampling scenarios.53
E.2 Example 1: Waste producer to carry out a basic characterisation on the concentration of
6+
Cr in a waste liquid during discharge to the on-site lagoon .57
E.3 Example 2: Waste producer to undertake a regular compliance testing programme to check
conformance with data obtained from the basic characterisation.59
E.4 Example 3: Regulator to undertake an on-site verification of supernatant liquid in the
hazardous waste lagoon.61
E.5 Example 4: Waste producer to carry out a basic characterisation on the concentration of
Cr6+ in a waste liquid held in drum storage at the factory, for disposal purposes .63
E.6 Example 5: Waste producer to carry out a compliance testing of the Cr6+ concentration of
waste liquid held in drums prior to disposal, against a permitted mean limit of 100 mg/l .65
E.7 Example 6: Carrier or Disposal company to carry out an on-site verification of drums
containing Cr-contaminated liquid sludge prior to treatment .67
E.8 Example 7: Carrier or Disposal Company to carry out an on-site verification of the contents
of tankers containing Cr6+ contaminated liquid sludge prior to treatment .68
E.9 Example 8: Treatment plant operator applying basic characterisation to identify variability of
Cr6+ in a treated waste using a two-step leaching test at LS 2 and LS 8.70
E.10 Example 9: Treatment plant operator to perform compliance testing to determine whether
the treated hazardous waste complies with a limit determined on the basis of the basic
characterisation, using a combined one-step leaching test at LS10 .72
E.11 Example 10: On-site verification.74
E.12 Example 11: Compliance testing .74
E.13 Example 12: On-site verification.74
E.14 Example 13: On-site verification.75
E.15 Example 14: Basic characterisation .75
Bibliography.76

Foreword
This Technical Report (CEN/TR 15310-1:2006) has been prepared by Technical Committee CEN/TC 292
“Characterization of waste”, the secretariat of which is held by NEN.
This Technical Report has been prepared under a mandate given to CEN by the European Commission and the
European Free Trade Association.
This Technical Report is one of a series of five Technical Reports dealing with sampling techniques and
procedures, and provides essential information and instructions for the application of the EN-standard:
EN 14899 Characterisation of Waste - Sampling of waste materials - Framework for the preparation and
application of a Sampling Plan
The principal component of the EN Standard is the mandatory requirement to prepare a Sampling Plan. This EN
14899 standard can be used to:
− produce standardised sampling plans for use in regular or routine circumstances (i.e. the
elaboration of daughter/derived standards dedicated to well defined sampling scenarios);
− incorporate specific sampling requirements into national legislation;
− design and develop a Sampling Plan on a case by case basis.
The Technical Reports display a range of potential approaches and tools to enable the project manager to tailor
his sampling plan to a specific testing scenario (i.e. a ‘shop shelf’ approach to sampling plan development for
waste testing). This approach allows flexibility in the selection of the sampling approach, sampling point, method
of sampling and equipment used.
This Technical Report describes the statistical principles related to sampling, and provides methods based on
these principles enabling a testing programme to be defined that will produce results sufficiently reliable for the
decision-making process for which they are required.
Wastes arise in a wide variety of types (e.g. pastes, liquids, granular materials, mixes of different materials) and
sampling situations (e.g. during a waste production process, stockpiles, tanks, drums). There can also be a
variety of sampling objectives within each of the three broad categories (basic characterisation, compliance
testing and on-site verification). Consequently the Report cannot provide definitive instructions for each and every
case on the practical details of the testing programme, such as the required number of samples, the size of these
samples, and whether they should be spot or composite samples. Instead, its aim is to expose the factors that
influence the choice of these detailed components of the sampling exercise, and to provide statistical tools that
can then be applied to determine the most appropriate testing programme for any given sampling scenario.
Introduction
Wastes are materials, which the holder discards, or intends or is required to discard, and which may
be sent for final disposal, reuse or recovery. Such materials are generally heterogeneous and it will
be necessary therefore to specify in the testing programme the amount of material for which the
characteristics of interest need to be defined. The testing of wastes allows informed decisions to be
made on how they should be treated (or not), recovered or disposed of. In order to undertake valid
tests, some sampling of the waste is required.
The principal component of the standard EN 14899 is the mandatory requirement to prepare a
Sampling Plan, within the framework of an overall testing programme as illustrated in Figure 1 of
EN 14899:2005 and can be used to:
− produce standardised sampling plans for use in regular or routine circumstances (elaboration of
daughter/derived standards dedicated to well defined sampling scenarios);
− incorporate the specific sampling requirements of European and national legislation;
− design and develop a Sampling Plan for use on a case by case basis.
The development of a Sampling Plan within this framework involves the progression through three
steps or activities:
1) define the Sampling Plan;
2) take a field sample in accordance with the Sampling Plan;
3) transport the laboratory sample to the laboratory.
This Technical Report provides information to support Key Step 1 of the Sampling Plan process map
and describes the selection of sampling approach that can be used in the recovery of a sample for a
wide variety of waste types and arisings. Specifically this Technical Report provides information to
support 4.2.7 (Select sampling approach) of the Framework Standard. Due consideration and
selection of statistical criteria is of key importance in the production of a Sampling Plan as it provides
the sole means of ensuring that, wherever possible, the type and number of samples taken will
address a clearly identified objective and will provide results that achieve a tolerable level of
reliability.
Table 1 - Main statistical steps in defining a sampling plan for a testing programme

Step Subject
Specify the objective of the Testing Programme
1 Specify the objective of the Testing
Programme
Develop the Technical Goals from the objective
2 Define the population to be sampled
3 Assess variability
4 Select the sampling approach
5 Identify the scale
6 Choose the required statistical approach
7 Choose the desired reliability
Determine the practical instructions
8 Choose the sampling pattern
9 Determine the increment/ sample size
10 Determine the use of composite or individual
samples
11 Determine required number of samples
Define the Sampling Plan
12 Define the Sampling Plan
To illustrate the application of these principles, a series of 14 examples of sampling scenarios for a
single waste stream are provided in Annex E.
This Technical Report should be read in conjunction with the Framework Standard for the
preparation and application of a Sampling Plan as well as the other Technical Reports that contain
essential information to support the Framework Standard. The full series comprises:
− EN 14899 Characterization of waste - Sampling of waste materials - Framework for the
preparation and application of a Sampling Plan;
− CEN/TR 15310-1, Characterization of waste – Sampling of waste materials – Part 1: Guidance
on selection and application of criteria for sampling under various conditions;
− CEN/TR 15310-2, Characterization of waste – Sampling of waste materials – Part 2: Guidance
on sampling techniques;
− CEN/TR 15310-3, Characterization of waste – Sampling of waste materials – Part 3: Guidance
on procedures for sub-sampling in the field;
− CEN/TR 15310-4, Characterization of waste – Sampling of waste materials – Part 4: Guidance
on procedures for sample packaging, storage, preservation, transport and delivery;
− CEN/TR 15310-5, Characterization of waste – Sampling of waste materials – Part 5: Guidance
on the process of defining the Sampling Plan.
The Technical Reports contain procedural options (as detailed in Figure 2 of EN 14899:2005) that
can be selected to match the sampling requirements of any testing programme.

1 Scope
This Technical Report discusses the statistical principles of sampling, and provides a number of
statistical tools to assist in the design of testing programmes for application to sampling under
various conditions.
NOTE 1 Given the great variety of waste types, sampling situations and objectives, this Technical Report
cannot provide definitive instructions that cover all scenarios. Instead, it discusses the basic statistical approach
to be followed, and provides statistical tools that can be applied to determine the amount and type of sampling
(e.g. number of samples and sample size) in any given situation to achieve results of adequate reliability (i.e.
precision and confidence).
NOTE 2 The document provides considerable detail on current best practice, but is not exhaustive.
NOTE 3 To clarify the text, the document provides a number of worked examples.
2 Terms and definitions
For the purposes of this Technical Report, we have used or adapted the definitions of ISO 3534
Parts 1, 2 and 3 wherever possible. In a minority of cases, however, those definitions are couched in
technical statistical language, which is likely to be unhelpful to the intended readership. In these
instances we have either supplemented the formal definition with an additional note, or provided an
alternative simpler definition.
NOTE In order to keep the list of definitions as compact as possible, some terms that are used only
occasionally in the main text have been omitted. B.1 provides an additional list of definitions that are specifically
relevant to the various annexes.
2.1
analytical error
collective term for the imprecision and bias associated with the analytical method
2.2
characteristic
property, which helps to identify or differentiate between items of a given population
[ISO 3534-1]
NOTE The characteristic may be either quantitative (by variables) or qualitative (by attributes).
2.3
coefficient of variation
for a non-negative characteristic the ratio of the standard deviation to the average
[ISO 3534-1]
2.4
compliance (and non-compliance)
compliance is achieved when the sample values from a monitoring programme meet a pre-defined
set of criteria. Conversely, non-compliance occurs when the sample values fail to meet the pre-
defined criteria
NOTE Examples of compliance criteria are:
− The estimated mean should be ≤ 20 mg/kg;
− Fewer than 3 sample values out of 20 should exceed 50 µg/l.
2.5
composite sample
two or more increments / sub-samples mixed together in appropriate proportions, either discretely or
continuously (blended composite sample), from which the average value of a desired characteristic
may be obtained
[ISO 11074-2]
2.6
confidence interval
interval within which a particular population parameter may be stated to lie at a specified confidence
level. The bounds of the confidence interval are termed the upper and lower confidence limits
2.7
fundamental variability
inherent variability shown by a material at the smallest scale of measurement
2.8
heterogeneity
degree to which a property or a constituent is not uniformly distributed throughout a quantity of
material
NOTE 1 A material may be heterogeneous with respect to one analyte or property but not with respect to
another.
NOTE 2 The degree of heterogeneity is a key-determining factor in sampling error.
2.9
increment
individual portion of material collected by a single operation of a sampling device
NOTE 1 Increments may be reduced and tested individually or combined with other increments, with the
resulting composite reduced in size and tested as a single unit.
NOTE 2 Increments are created by the sampling operation and are usually taken from parts of a lot
separated in time or space.
2.10
judgemental sampling
samples collected using at best a partially-probabilistic procedure and at worst a non-probabilistic
approach. Usually these samples are taken from a sub-population which is substantially more
restrictive than the overall population.
2.11
mean (arithmetic mean)
sum of values divided by the number of values
[ISO 3534-1]
NOTE For example, the arithmetic mean of the five values 12, 4, 11, 9 and 6 is 8.4.
2.12
overall population
entire volume of material about which information is required.
NOTE 1 For example, the overall population might be the output of waste over the whole lifetime of the plant.
NOTE 2 See ‘population’.
2.13
percentile
P-percentile of a population is the value below which P% of the values in the population fall, and hence is
exceeded by (100-P)% of the population.
NOTE For example, 95 % of the values in a population are less than or equal to the 95-percentile, and 5 %
of the population values exceed it.
2.14
physical sampling error
error attributable to the activity of taking the sample

2.15
population
totality of items under consideration. [ISO 3534-1:1993, definition 2.3]
NOTE The population will generally be a convenient, well-defined subset of the overall population (e.g. a
year’s production of waste) that is believed to be typical of that wider population.
2.16
precision
closeness of agreement between independent test results obtained under stipulated conditions
[ISO 3534-1]
NOTE 1 Precision depends only on the distribution of random errors and does not relate to the true value or
the specified value.
NOTE 2 The measure of precision usually is expressed in terms of imprecision and computed as a standard
deviation of the test results. A lower precision is reflected by a larger standard deviation.
2.17
probabilistic sampling
sampling conducted according to the statistical principles of sampling
NOTE 1 The essential principle of probabilistic sampling is that every individual particle or item in the population has an equal
chance of being sampled.
NOTE 2 Probabilistic sampling results in boundary conditions for the type of sampling equipment used, the method of
sampling (where, when, how) and the minimum size of increments and (composite) samples.
2.18
probability
real number in the scale 0 to 1 attached to a random event
[ISO 3534-1]
NOTE An event with a probability close to zero is very unlikely to happen. For example, the probability of
obtaining ‘heads’ in each of 10 consecutive spins of a coin is about 0.001. Conversely, an event with probability
close to 1 is very likely to happen. For example, the event of obtaining at least one ‘six’ when rolling 25 dice is
about 0.99.
2.19
probability distribution (of a random variable)
function giving the probability that a random variable takes any given value or belongs to a given set
of values
[ISO 3534-1]
NOTE The probability distribution is a mathematical description of the relative frequencies with which
different values arise in the population. It is commonly represented graphically, and can be thought of as the
curve that the histogram of random sample values would tend towards as the number of samples becomes
indefinitely large.
2.20
random sample
sample of n sampling units taken from a population in such a way that each of the possible
combinations of n sampling units has a particular (known) probability of being taken
[ISO 3534-1]
2.21
random sampling
process of taking a random sample
[ISO 3534-1]
2.22
reliability
collective term for the degree of precision and confidence achieved by a given sampling scheme
2.23
representative
sample resulting from a sampling plan that can be expected to reflect adequately the properties of
interest in the parent population
[ISO 11074-2]
2.24
representative sample
sample in which the characteristic(s) of interest is (are) present with a reliability appropriate for the purposes of
the testing programme
2.25
sample
portion of material selected from a larger quantity of material. [ISO 11074-2:1998, definition 1.5]
NOTE 1 The manner of selection of the sample should be described in a sampling plan.
NOTE 2 The use of the term ‘sample’ should be supported with a preface as far as possible as it does not indicate to which
step of the total sampling procedure it is related when used alone e.g. field sample, laboratory sample.
2.26
sample size
number of items or the quantity of material constituting a sample.
NOTE In statistical sampling theory, the term ‘sample size’ is commonly used to denote the number of
samples. To lessen the risk of confusion, that usage has been avoided in this Technical Report; thus ‘sample
size’ refers unambiguously to the volume or mass of any one sample.
2.27
sampling error
that part of the estimation error, which is due to the fact that only a sample of size less than the
population size, is observed
[ISO 3534-1]
2.28
sampling pattern
collective term for the method of sampling to be adopted, such as random, systematic, stratified
random or judgemental
2.29
scale
stated size or volume that is considered appropriate for assessing the material
NOTE 1 It follows that variations occurring in the material on any finer scale than this are deemed not to be
of relevance.
NOTE 2 Annex A provides further explanation of the concept of scale.
2.30
simple random sample
sample of n sampling units taken from a population in such a way that all possible combinations of n
sampling units have the same probability of being taken
[ISO 3534-1]
2.31
spatial variability
general term for the variability between locations in the material to be sampled
2.32
spot sampling
sample of a specified number or size taken from a specified place in a material or at a specified
place and time in a stream of material and representative of its own immediate or local environment
[ISO 11074-2]
NOTE Form of sampling in which each sample is individually analysed (in contrast to composite sampling).
2.33
standard deviation
positive square root of the variance
[ISO 3534-1]
NOTE This is the most commonly used measure of variability of a data set or statistical population. For
example, the standard deviation of the values 3.7, 5.5, 2.8, 9.1 and 6.0 is 2.43.
2.34
stratum/strata
strata are mutually exclusive and exhaustive parts of a population. They are identified either, because they are
believed to be different from each other or for the purposes of sampling
2.35
stratified sampling
in a population which can be divided into mutually exclusive and exhaustive strata (i.e. sub-
populations), sampling carried out in such a way that specified proportions of the sample are drawn
from the different strata and each stratum is sampled with at least one sampling unit
[ISO 3534-1]
NOTE The objective of taking stratified samples is to obtain a more representative sample than that which
might otherwise be obtained by random sampling.
2.36
sub-population
defined part of the population that will be targeted for the purposes of sampling
2.37
systematic error (or Bias)
difference between the expectation of the test results and an accepted reference value
[ISO 3534-1]
NOTE Bias is a systematic tendency for the observations in a set of samples to be displaced above or
below the true or accepted value.
2.38
systematic sampling
sampling by some systematic method
[ISO 3534-1]
NOTE Examples are where samples are taken at regular intervals through time (e.g. weekly) or through
space (e.g. every tenth skip).
2.39
temporal variability
general term for the variability through time
2.40
uncertainty
an estimate attached to a test result, which characterises the range of values within which the true
value is asserted to lie
[ISO 3534-1]
NOTE In general, uncertainty of measurement comprises many components. Some of these may be
estimated on the basis of the statistical distribution of the results of a series of measurements and can be
characterised by standard deviations. Estimates of other components can only be based on experience or other
information.
2.41
within-population variability
dispersion of observations or test results obtained within a population
[ISO 3534-2]
NOTE The within-population variation may be estimated from data from a single population, or by pooling
the estimates for several populations, as appropriate.
3 Specify the objective of the Testing Programme
The objective of the Testing Programme consists of a general statement of overall purpose. The
objective should be made clear prior to selecting a sampling strategy, as it is an essential first step
towards defining the type and quality of the information that is to be obtained through sampling. A
clearly defined objective is required to identify the material population that will be characterized
through sampling.
NOTE 1 In most cases a Testing Programme can only have one objective. In other words, each single
objective will generally result in a separate Testing Programme.
NOTE 2 Examples of possible objectives of the Testing Programme are:
− to compare the quality of the test material with quality levels defined in national or international legislation;
− to characterise the test material following a change in ownership;
− to determine the reusability of the test material;
− to determine the leachability of the test material;
− to assess the human health and / or environmental risks posed by the test material.

NOTE 3 The Landfill Directive (1999/31/EC) requires technical instruments to fulfil its role in setting
European policy goals on waste disposal. The technical instruments on sampling are provided by CEN/TC 292
(WG1), which has developed the Framework Standard EN 14899 on waste sampling supported by a series of
Technical Reports (see the Introduction). Examples of testing requirements relating to the Landfill Directive are:
− basic (comprehensive) characterisation, consisting of a thorough determination of the behaviour and
properties of interest of the material.
− compliance testing, consisting of (periodic) testing to determine compliance with specific conditions or
reference conditions e.g. legislation or contract.
− on-site verification, consisting of ‘quick check’ methods to establish consistency with other tests or other
formulated documentation.
This Technical Report can be applied to meet the needs of the Landfill Directive but has not been written
exclusively for that purpose, as it deals with the sampling of wastes and associated materials in a wider context.

NOTE 4 Sampling will not be necessary in every case for meeting the objective. For example, the objective
of an on-site verification may be simply to establish the identity of the waste material received. (Is it a liquid? Is
its colour blue?)
In the majority of cases, the objective is too general and non-specific for it to lead directly to the
detailed instructions necessary for the Sampling Plan. It is therefore necessary to translate the
objective into technical goals. These provide a more detailed specification of the sampling activity,
and are sufficiently comprehensive to enable all aspects of the sampling plan to be determined - the
type, size, scale and number of samples to be taken, the way they are selected from the material
under investigation, and so on. The process of developing the technical goals from the objective is
discussed in detail in Clause 4.
4 Develop the technical goals from the objective
4.1 General
Once the objective of the Sampling Plan has been agreed (see Clause 3), the next step is to
develop the technical goals. This is a critical step, because once the technical goals have been
defined, we can determine specific sampling and data analysis requirements and identify the
statistical analytical tools that will provide a consistent means of assessing and interpreting testing
data. Such tools ultimately provide the means of verifying whether or not the technical goals have
been met.
In the process of deriving the technical goals from the objective, it is important to remain focussed
on the conclusions that the sampling is intended to deliver, and their implications for the technical
specification of the testing programme.
In some cases the translation from the objective to the technical goals is straightforward because
details such as the type of sample to be taken, or the statistical parameter to be determined from the
results, may already be laid down in national or international legislation. Otherwise, however, the
project manager needs to define the technical goals in close consultation with all involved parties, as
the technical goals will lead directly to the practical instructions that are given to the sampler prior to
sampling. Conflicts can often arise between (a) the desired reliability and scope of the sampling, and
(b) the available resources, in which case compromises will be necessary. This makes it all the more
essential that the involved parties do agree on the technical goals and their implications prior to
sampling.
Some technical goals can be sufficiently well defined that they can be directly implemented into the
Sampling Plan (for example, the material to be sampled and the constituents to be tested), whilst
other technical goals (for example the scale and confidence level) may require further ‘translation’
into practical instructions to the sampler.
Define the population to be sampled See 4.2 and CEN/TR 15310-5
Assess variability See 4.3
Select the sampling approach See 4.4
Select constituents to be studied See CEN/TR 15310-5
Identify the scale See 4.5, Annex A and CEN/TR 15310-5
Choose the required statistical parameter See 4.6
Choose the desired reliability See 4.7
4.2 Define the population to be sampled
4.2.1 General
The term ‘population’ is a statistical term for defining the total volume of material about which
information is required through sampling. Specification of the population should be one of the first
steps in defining the Sampling Plan.
It is important to check in the process of defining the Sampling Plan that all involved parties are
talking about ‘the same amount of material’.
4.2.2 Overall population
4.2.3 Population
Commonly it is impractical to sample from the overall population. Difficulties arise particularly where
the overall population relates to the whole lifetime’s operation of a plant. Any associated sampling
programme would then need to cover broadly that same period, and it would clearly be unhelpful if
the operator had to wait until nearly all the waste had been produced before being able to make an
assessment of its characteristics.
It is customary, therefore, to define the ‘population’ as a convenient sub-set of the overall population
that is believed to be typical of that wider overall population. For example, one month’s ash
production might be thought typical of overall incinerator performance; the contents of a lagoon on a
particular date might be thought typical of the contents on any other day in the year. It is important to
appreciate that an appropriate choice of population relies on the experience and judgement of the
interested parties: it is not a statistical task.
It is also important to define the population explicitly over space and/or time; if this is not done, it is
impossible to say whether a particular sampling exercise will result in representative samples.
NOTE For some sampling objectives, spatial variation may not be relevant (e.g. when sampling liquid from
a pipeline at intervals through time), whilst for other objectives, temporal variation may not be relevant (e.g.
when sampling from a number of heaps in a disposal site).
In defining the population for sampling it is important to consider the issue of ‘scale’ (see 4.5).
4.2.4 Sub-population
Cases arise where it is difficult or even impossible to sample certain parts of the population due to
access restrictions. In such circumstances it is useful to define a subset of the population - termed
the ‘sub-population’ - which restricts sampling to a more convenient region. The sub-population is
therefore the specific part of the population that will be targeted for sampling, and which is thought to
be sufficient to characterise the population. Sampling may therefore be carried out on either the
population or sub-population depending on the volume of, and access to, the waste under
consideration.
The definition of a number of sub-populations may be useful where a large population is under
investigation. These might be based on known changes in the production process or expected
concentration levels. Alternatively the sub-population may be based on a characteristic of the
material, such as any ‘deviating parts’ (e.g. white particles in a black material).
NOTE 1 A variety of terms could be used to define a sub-population according to the context, including ‘lot’,
‘sub-population’, ‘drum’ or ‘stockpile’. Whatever terms are used, their interpretation might easily be confusing
and will be highly dependent on the definition of the testing programme. For stockpile sampling, for example,
the population will often be the same as the lot or sub-population to be sampled, while a sub-population would
be a part of that lot. In other cases, however, a number of individual stockpiles may be related to each other -
for example, through being the daily arisings from a treatment plant. The stockpiles might then be viewed
collectively as the population, while an individual stockpile is the sub-population. Alternatively, it might be
appropriate to define the collective of stockpiles as the overall population and each individual stockpile as a
population.
NOTE 2 Given this risk of multiple interpretations, the EN and CEN/TRs in this series only use the terms
‘overall population’, ‘population’ and ‘sub-population’.
4.2.5 Examples
Some examples illustrating how it is possible to define overall population, population and sub-
population for various categories of material are as follows:

Example 1: Liquids
Overall population: The total amount of liquid that passes through the slurry lagoon during a year
Population: The total liquid held in a slurry lagoon on a
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